Applications of a fast, continuous wavelet transform
Dress, W.B.
1997-02-01
A fast, continuous, wavelet transform, based on Shannon`s sampling theorem in frequency space, has been developed for use with continuous mother wavelets and sampled data sets. The method differs from the usual discrete-wavelet approach and the continuous-wavelet transform in that, here, the wavelet is sampled in the frequency domain. Since Shannon`s sampling theorem lets us view the Fourier transform of the data set as a continuous function in frequency space, the continuous nature of the functions is kept up to the point of sampling the scale-translation lattice, so the scale-translation grid used to represent the wavelet transform is independent of the time- domain sampling of the signal under analysis. Computational cost and nonorthogonality aside, the inherent flexibility and shift invariance of the frequency-space wavelets has advantages. The method has been applied to forensic audio reconstruction speaker recognition/identification, and the detection of micromotions of heavy vehicles associated with ballistocardiac impulses originating from occupants` heart beats. Audio reconstruction is aided by selection of desired regions in the 2-D representation of the magnitude of the transformed signal. The inverse transform is applied to ridges and selected regions to reconstruct areas of interest, unencumbered by noise interference lying outside these regions. To separate micromotions imparted to a mass-spring system (e.g., a vehicle) by an occupants beating heart from gross mechanical motions due to wind and traffic vibrations, a continuous frequency-space wavelet, modeled on the frequency content of a canonical ballistocardiogram, was used to analyze time series taken from geophone measurements of vehicle micromotions. By using a family of mother wavelets, such as a set of Gaussian derivatives of various orders, features such as the glottal closing rate and word and phrase segmentation may be extracted from voice data.
The Wavelet Element Method. Part 2; Realization and Additional Features in 2D and 3D
NASA Technical Reports Server (NTRS)
Canuto, Claudio; Tabacco, Anita; Urban, Karsten
1998-01-01
The Wavelet Element Method (WEM) provides a construction of multiresolution systems and biorthogonal wavelets on fairly general domains. These are split into subdomains that are mapped to a single reference hypercube. Tensor products of scaling functions and wavelets defined on the unit interval are used on the reference domain. By introducing appropriate matching conditions across the interelement boundaries, a globally continuous biorthogonal wavelet basis on the general domain is obtained. This construction does not uniquely define the basis functions but rather leaves some freedom for fulfilling additional features. In this paper we detail the general construction principle of the WEM to the 1D, 2D and 3D cases. We address additional features such as symmetry, vanishing moments and minimal support of the wavelet functions in each particular dimension. The construction is illustrated by using biorthogonal spline wavelets on the interval.
Applications of a fast continuous wavelet transform
NASA Astrophysics Data System (ADS)
Dress, William B.
1997-04-01
A fast, continuous, wavelet transform, justified by appealing to Shannon's sampling theorem in frequency space, has been developed for use with continuous mother wavelets and sampled data sets. The method differs from the usual discrete-wavelet approach and from the standard treatment of the continuous-wavelet transform in that, here, the wavelet is sampled in the frequency domain. Since Shannon's sampling theorem lets us view the Fourier transform of the data set as representing the continuous function in frequency space, the continuous nature of the functions is kept up to the point of sampling the scale-translation lattice, so the scale-translation grid used to represent the wavelet transform is independent of the time-domain sampling of the signal under analysis. Although more computationally costly and not represented by an orthogonal basis, the inherent flexibility and shift invariance of the frequency-space wavelets are advantageous for certain applications. The method has been applied to forensic audio reconstruction, speaker recognition/identification, and the detection of micromotions of heavy vehicles associated with ballistocardiac impulses originating from occupants' heart beats. Audio reconstruction is aided by selection of desired regions in the 2D representation of the magnitude of the transformed signals. The inverse transform is applied to ridges and selected regions to reconstruct areas of interest, unencumbered by noise interference lying outside these regions. To separate micromotions imparted to a mass- spring system by an occupant's beating heart from gross mechanical motions due to wind and traffic vibrations, a continuous frequency-space wavelet, modeled on the frequency content of a canonical ballistocardiogram, was used to analyze time series taken from geophone measurements of vehicle micromotions. By using a family of mother wavelets, such as a set of Gaussian derivatives of various orders, different features may be extracted from voice
A parallel splitting wavelet method for 2D conservation laws
NASA Astrophysics Data System (ADS)
Schmidt, Alex A.; Kozakevicius, Alice J.; Jakobsson, Stefan
2016-06-01
The current work presents a parallel formulation using the MPI protocol for an adaptive high order finite difference scheme to solve 2D conservation laws. Adaptivity is achieved at each time iteration by the application of an interpolating wavelet transform in each space dimension. High order approximations for the numerical fluxes are computed by ENO and WENO schemes. Since time evolution is made by a TVD Runge-Kutta space splitting scheme, the problem is naturally suitable for parallelization. Numerical simulations and speedup results are presented for Euler equations in gas dynamics problems.
The Continuous wavelet in airborne gravimetry
NASA Astrophysics Data System (ADS)
Liang, X.; Liu, L.
2013-12-01
Airborne gravimetry is an efficient method to recover medium and high frequency band of earth gravity over any region, especially inaccessible areas, which can measure gravity data with high accuracy,high resolution and broad range in a rapidly and economical way, and It will play an important role for geoid and geophysical exploration. Filtering methods for reducing high-frequency errors is critical to the success of airborne gravimetry due to Aircraft acceleration determination based on GPS.Tradiontal filters used in airborne gravimetry are FIR,IIR filer and so on. This study recommends an improved continuous wavelet to process airborne gravity data. Here we focus on how to construct the continuous wavelet filters and show their working principle. Particularly the technical parameters (window width parameter and scale parameter) of the filters are tested. Then the raw airborne gravity data from the first Chinese airborne gravimetry campaign are filtered using FIR-low pass filter and continuous wavelet filters to remove the noise. The comparison to reference data is performed to determinate external accuracy, which shows that continuous wavelet filters applied to airborne gravity in this thesis have good performances. The advantages of the continuous wavelet filters over digital filters are also introduced. The effectiveness of the continuous wavelet filters for airborne gravimetry is demonstrated through real data computation.
NASA Astrophysics Data System (ADS)
Antoine, Jean-Pierre; Vandergheynst, Pierre; Bouyoucef, Karim; Murenzi, Romain
1995-06-01
Both in 1D (signal analysis) and 2D (image processing), the wavelet transform (WT) has become by now a standard tool. Although the discrete version, based on multiresolution analysis, is probably better known, the continous WT (CWT) plays a crucial role for the detection and analysis of particular features in a signal, and we will focus here on the latter. In 2D however, one faces a practical problem. Indeed, the full parameter space of the wavelet transform of an image is 4D. It yields a representation of the image in position parameters (range and perception angle), as well as scale and anisotropy angle. The real challenge is to compute and visualize the full continuous wavelet transform in all four variables--obviously a demanding task. Thus, in order to obtain a manageable tool, some of the variables must be frozen. In other words, one must limit oneself to sections of the parameter space, usually 2D or 3D. For 2D sections, two variables are fixed and the transform is viewed as a function of the two remaing ones, and similarly for 3D sections. Among the six possible 2D sections, two play a privileged role. They yield respectively the position representation, which is the standard one, and the scale-angle representation, which has been proposed and studied systematically by two of us in a number of works. In this paper we will review these results and investigate the four remaining 2D representations. We will also make some comments on possible applications of 3D sections. The most spectacular property of the CWT is its ability at detecting discontinuities in a signal. In an image, this means in particular the sharp boundary between two regions of different luminosity, that is, a contour or an edge. Even more prominent in the transform are the corners of a given contour, for instance the contour of a letter. In a second part, we will exploit this property of the CWT and describe how one may design an algorithm for automatic character recognition (here we
Continuous wavelet transform in quantum field theory
NASA Astrophysics Data System (ADS)
Altaisky, M. V.; Kaputkina, N. E.
2013-07-01
We describe the application of the continuous wavelet transform to calculation of the Green functions in quantum field theory: scalar ϕ4 theory, quantum electrodynamics, and quantum chromodynamics. The method of continuous wavelet transform in quantum field theory, presented by Altaisky [Phys. Rev. D 81, 125003 (2010)] for the scalar ϕ4 theory, consists in substitution of the local fields ϕ(x) by those dependent on both the position x and the resolution a. The substitution of the action S[ϕ(x)] by the action S[ϕa(x)] makes the local theory into a nonlocal one and implies the causality conditions related to the scale a, the region causality [J. D. Christensen and L. Crane, J. Math. Phys. (N.Y.) 46, 122502 (2005)]. These conditions make the Green functions G(x1,a1,…,xn,an)=⟨ϕa1(x1)…ϕan(xn)⟩ finite for any given set of regions by means of an effective cutoff scale A=min(a1,…,an).
Wavelet characterization of 2D turbulence and intermittency in magnetized electron plasmas
NASA Astrophysics Data System (ADS)
Romé, M.; Chen, S.; Maero, G.
2016-06-01
A study of the free relaxation of turbulence in a two-dimensional (2D) flow is presented, with a focus on the role of the initial vorticity conditions. Exploiting a well-known analogy with 2D inviscid incompressible fluids, the system investigated here is a magnetized pure electron plasma. The dynamics of this system are simulated by means of a 2D particle-in-cell code, starting from different spiral density (vorticity) distributions. A wavelet multiresolution analysis is adopted, which allows the coherent and incoherent parts of the flow to be separated. Comparison of the turbulent evolution in the different cases is based on the investigation of the time evolution of statistical properties, including the probability distribution functions and structure functions of the vorticity increments. It is also based on an analysis of the enstrophy evolution and its spectrum for the two components. In particular, while the statistical features assess the degree of flow intermittency, spectral analysis allows us not only to estimate the time required to reach a state of fully developed turbulence, but also estimate its dependence on the thickness of the initial spiral density distribution, accurately tracking the dynamics of both the coherent structures and the turbulent background. The results are compared with those relevant to annular initial vorticity distributions (Chen et al 2015 J. Plasma Phys. 81 495810511).
Laboratory Experiments On Continually Forced 2d Turbulence
NASA Astrophysics Data System (ADS)
Wells, M. G.; Clercx, H. J. H.; Van Heijst, G. J. F.
There has been much recent interest in the advection of tracers by 2D turbulence in geophysical flows. While there is a large body of literature on decaying 2D turbulence or forced 2D turbulence in unbounded domains, there have been very few studies of forced turbulence in bounded domains. In this study we present new experimental results from a continuously forced quasi 2D turbulent field. The experiments are performed in a square Perspex tank filled with water. The flow is made quasi 2D by a steady background rotation. The rotation rate of the tank has a small (<8 %) sinusoidal perturbation which leads to the periodic formation of eddies in the corners of the tank. When the oscillation period of the perturbation is greater than an eddy roll-up time-scale, dipole structures are observed to form. The dipoles can migrate away from the walls, and the interior of the tank is continually filled with vortexs. From experimental visualizations the length scale of the vortexs appears to be largely controlled by the initial formation mechanism and large scale structures are not observed to form at large times. Thus the experiments provide a simple way of cre- ating a continuously forced 2D turbulent field. The resulting structures are in contrast with most previous laboratory experiments on 2D turbulence which have investigated decaying turbulence and have observed the formations of large scale structure. In these experiments, decaying turbulence had been produced by a variety of methods such as the decaying turbulence in the wake of a comb of rods (Massen et al 1999), organiza- tion of vortices in thin conducting liquids (Cardoso et al 1994) or in rotating systems where there are sudden changes in angular rotation rate (Konijnenberg et al 1998). Results of dye visualizations, particle tracking experiments and a direct numerical simulation will be presented and discussed in terms of their oceanographic application. Bibliography Cardoso,O. Marteau, D. &Tabeling, P
A new stationary gridline artifact suppression method based on the 2D discrete wavelet transform
Tang, Hui; Tong, Dan; Dong Bao, Xu; Dillenseger, Jean-Louis
2015-04-15
Purpose: In digital x-ray radiography, an antiscatter grid is inserted between the patient and the image receptor to reduce scattered radiation. If the antiscatter grid is used in a stationary way, gridline artifacts will appear in the final image. In most of the gridline removal image processing methods, the useful information with spatial frequencies close to that of the gridline is usually lost or degraded. In this study, a new stationary gridline suppression method is designed to preserve more of the useful information. Methods: The method is as follows. The input image is first recursively decomposed into several smaller subimages using a multiscale 2D discrete wavelet transform. The decomposition process stops when the gridline signal is found to be greater than a threshold in one or several of these subimages using a gridline detection module. An automatic Gaussian band-stop filter is then applied to the detected subimages to remove the gridline signal. Finally, the restored image is achieved using the corresponding 2D inverse discrete wavelet transform. Results: The processed images show that the proposed method can remove the gridline signal efficiently while maintaining the image details. The spectra of a 1D Fourier transform of the processed images demonstrate that, compared with some existing gridline removal methods, the proposed method has better information preservation after the removal of the gridline artifacts. Additionally, the performance speed is relatively high. Conclusions: The experimental results demonstrate the efficiency of the proposed method. Compared with some existing gridline removal methods, the proposed method can preserve more information within an acceptable execution time.
Spike detection using the continuous wavelet transform.
Nenadic, Zoran; Burdick, Joel W
2005-01-01
This paper combines wavelet transforms with basic detection theory to develop a new unsupervised method for robustly detecting and localizing spikes in noisy neural recordings. The method does not require the construction of templates, or the supervised setting of thresholds. We present extensive Monte Carlo simulations, based on actual extracellular recordings, to show that this technique surpasses other commonly used methods in a wide variety of recording conditions. We further demonstrate that falsely detected spikes corresponding to our method resemble actual spikes more than the false positives of other techniques such as amplitude thresholding. Moreover, the simplicity of the method allows for nearly real-time execution. PMID:15651566
Time-frequency analysis with the continuous wavelet transform
NASA Astrophysics Data System (ADS)
Lang, W. Christopher; Forinash, Kyle
1998-09-01
The continuous wavelet transform can be used to produce spectrograms which show the frequency content of sounds (or other signals) as a function of time in a manner analogous to sheet music. While this technique is commonly used in the engineering community for signal analysis, the physics community has, in our opinion, remained relatively unaware of this development. Indeed, some find the very notion of frequency as a function of time troublesome. Here spectrograms will be displayed for familiar sounds whose pitches change with time, demonstrating the usefulness of the continuous wavelet transform.
NASA Astrophysics Data System (ADS)
Sato, Haruo; Fehler, Michael C.
2016-10-01
The envelope broadening and the peak delay of the S-wavelet of a small earthquake with increasing travel distance are results of scattering by random velocity inhomogeneities in the earth medium. As a simple mathematical model, Sato proposed a new stochastic synthesis of the scalar wavelet envelope in 3-D von Kármán type random media when the centre wavenumber of the wavelet is in the power-law spectral range of the random velocity fluctuation. The essential idea is to split the random medium spectrum into two components using the centre wavenumber as a reference: the long-scale (low-wavenumber spectral) component produces the peak delay and the envelope broadening by multiple scattering around the forward direction; the short-scale (high-wavenumber spectral) component attenuates wave amplitude by wide angle scattering. The former is calculated by the Markov approximation based on the parabolic approximation and the latter is calculated by the Born approximation. Here, we extend the theory for the envelope synthesis of a wavelet in 2-D random media, which makes it easy to compare with finite difference (FD) simulation results. The synthetic wavelet envelope is analytically written by using the random medium parameters in the angular frequency domain. For the case that the power spectral density function of the random velocity fluctuation has a steep roll-off at large wavenumbers, the envelope broadening is small and frequency independent, and scattering attenuation is weak. For the case of a small roll-off, however, the envelope broadening is large and increases with frequency, and the scattering attenuation is strong and increases with frequency. As a preliminary study, we compare synthetic wavelet envelopes with the average of FD simulation wavelet envelopes in 50 synthesized random media, which are characterized by the RMS fractional velocity fluctuation ε = 0.05, correlation scale a = 5 km and the background wave velocity V0 = 4 km s-1. We use the radiation
NASA Astrophysics Data System (ADS)
Sato, Haruo; Fehler, Michael C.
2016-07-01
The envelope broadening and the peak delay of the S-wavelet of a small earthquake with increasing travel distance are results of scattering by random velocity inhomogeneities in the earth medium. As a simple mathematical model, Sato (2016) proposed a new stochastic synthesis of the scalar wavelet envelope in 3-D von Kármán type random media when the center wavenumber of the wavelet is in the power-law spectral range of the random velocity fluctuation. The essential idea is to split the random medium spectrum into two components using the center wavenumber as a reference: the long-scale (low-wavenumber spectral) component produces the peak delay and the envelope broadening by multiple scattering around the forward direction; the short-scale (high-wavenumber spectral) component attenuates wave amplitude by wide angle scattering. The former is calculated by the Markov approximation based on the parabolic approximation and the latter is calculated by the Born approximation. Here, we extend the theory for the envelope synthesis of a wavelet in 2-D random media, which makes it easy to compare with finite difference (FD) simulation results. The synthetic wavelet envelope is analytically written by using the random medium parameters in the angular frequency domain. For the case that the power spectral density function of the random velocity fluctuation has a steep roll-off at large wavenumbers, the envelope broadening is small and frequency independent, and scattering attenuation is weak. For the case of a small roll-off, however, the envelope broadening is large and increases with frequency, and the scattering attenuation is strong and increases with frequency. As a preliminary study, we compare synthetic wavelet envelopes with the average of FD simulation wavelet envelopes in 50 synthesized random media, which are characterized by the RMS fractional velocity fluctuation ε=0.05, correlation scale a =5 km and the background wave velocity V0=4 km/s. We use the radiation
NASA Astrophysics Data System (ADS)
Plesniak, Daniel H.; Bulusu, Kartik V.; Plesniak, Michael W.
2012-11-01
Interpretation of complex flow patterns observed in this study of a model curved artery required characterization of multiple, low-circulation secondary flow structures that were observed during the late systolic deceleration and diastolic phases under physiological inflow conditions. Phase-locked, planar vorticity PIV data were acquired at various cross-sectional locations of the 180-degree bent tube model. High circulation, deformed Dean- and Lyne-type vortices were observed during early stages of deceleration, while several smaller scale, highly deformed, low-circulation vortical patterns appeared in the core and near-wall regions during late systolic deceleration and diastolic phases. Due to the multiplicity of vortical scales and shapes, anisotropic 2D Ricker wavelets were used for coherent structure detection in a continuous wavelet transform algorithm (PIVlet 1.2). Our bio-inspired study is geared towards understanding whether optimizing the shape of the wavelet kernel will enable better resolution of several low-circulation, multi-scale secondary flow morphologies and whether new insights into the dynamics of arterial secondary flow structures can accordingly be gained. Supported by the National Science Foundation, Grant No. CBET-0828903 and GW Center for Biomimetics and Bioinspired Engineering (COBRE).
NASA Astrophysics Data System (ADS)
Wang, Chun-Hsiung; Hsu, Kuan-Yu; Lee, Chih-Kung
2016-03-01
A real-time three-dimensional surface profile metrology system was implemented by integrating Fourier Transform (FT) based algorithms to convert interference intensity fringes to wrapped frequency phase maps and then to unwrapped phase maps. The revival of this field can find its roots in recognizing the development of high-resolution high-speed CCD/CMOS over the years. Two-dimensional Continuous Wavelet Transform (2D-CWT), which possesses the ability to construct daughter wavelets of good time and frequency localization according to different fringes conditions from a characteristic mother wavelet, was implemented with an attempt to reduce redundant fitting process of ordinary Short Time Fourier Transform (STFT), also known as Windowed Fourier Transform (WFT), and therefore to accelerate the FT-related algorithms needed. Implemented with the efficient wavelet construction process by using 2D-CWT, Electronic Speckle Pattern Interferometer (ESPI) was adopted to take advantage of this new process. Different from using several phase shifting steps before to solve the direction ambiguity, which takes time to capture multiple intensity maps during measurement, the phase maps needed were retrieved from a single frame interference fringes. It is to be noted that this one-image interference fringe was captured by having a pre-introduced spatial carrier frequency embedded within the experimental setup so as to remove the directional ambiguity. 2D-CWT dealing with different signal-to-noise ratios was also designed by selecting wavelet parameters properly, which is expected to achieve higher accuracy and faster processing speed. For phase unwrapping, Poisson's equation with Neumann boundary condition was solved by using FFT. The benefit of using 2D-CWTs with different wavelets as compared to WFT was demonstrated experimentally.
Continuous wavelet transform for non-stationary vibration detection with phase-OTDR.
Qin, Zengguang; Chen, Liang; Bao, Xiaoyi
2012-08-27
We propose the continuous wavelet transform for non-stationary vibration measurement by distributed vibration sensor based on phase optical time-domain reflectometry (OTDR). The continuous wavelet transform approach can give simultaneously the frequency and time information of the vibration event. Frequency evolution is obtained by the wavelet ridge detection method from the scalogram of the continuous wavelet transform. In addition, a novel signal processing algorithm based on the global wavelet spectrum is used to determine the location of vibration. Distributed vibration measurements of 500 Hz and 500 Hz to 1 kHz sweep events over 20 cm fiber length are demonstrated using a single mode fiber.
Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification.
Soares, João V B; Leandro, Jorge J G; Cesar Júnior, Roberto M; Jelinek, Herbert F; Cree, Michael J
2006-09-01
We present a method for automated segmentation of the vasculature in retinal images. The method produces segmentations by classifying each image pixel as vessel or nonvessel, based on the pixel's feature vector. Feature vectors are composed of the pixel's intensity and two-dimensional Gabor wavelet transform responses taken at multiple scales. The Gabor wavelet is capable of tuning to specific frequencies, thus allowing noise filtering and vessel enhancement in a single step. We use a Bayesian classifier with class-conditional probability density functions (likelihoods) described as Gaussian mixtures, yielding a fast classification, while being able to model complex decision surfaces. The probability distributions are estimated based on a training set of labeled pixels obtained from manual segmentations. The method's performance is evaluated on publicly available DRIVE (Staal et al., 2004) and STARE (Hoover et al., 2000) databases of manually labeled images. On the DRIVE database, it achieves an area under the receiver operating characteristic curve of 0.9614, being slightly superior than that presented by state-of-the-art approaches. We are making our implementation available as open source MATLAB scripts for researchers interested in implementation details, evaluation, or development of methods.
Cell classification by moments and continuous wavelet transform methods
Chen, Qian; Fan, Yuan; Udpa, Lalita; Ayres, Virginia M
2007-01-01
Image processing techniques are bringing new insights to biomedical research. The automatic recognition and classification of biomedical objects can enhance work efficiency while identifying new inter-relationships among biological features. In this work, a simple rule-based decision tree classifier is developed to classify typical features of mixed cell types investigated by atomic force microscopy (AFM). A combination of continuous wavelet transform (CWT) and moment-based features are extracted from the AFM data to represent that shape information of different cellular objects at multiple resolution levels. The features are shown to be invariant under operations of translation, rotation, and scaling. The features are then used in a simple rule-based classifier to discriminate between anucleate versus nucleate cell types or to distinguish cells from a fibrous environment such as a tissue scaffold or stint. Since each feature has clear physical meaning, the decision rule of this tree classifier is simple, which makes it very suitable for online processing. Experimental results on AFM data confirm that the performance of this classifier is robust and reliable. PMID:17722546
NASA Astrophysics Data System (ADS)
Nenna, V.; Pidlisecky, A.
2012-12-01
scales: 1:4 km, 4:9 km, 9:15 km, and 15:30 km. The average normalized power within a scale bin for each sounding and time-channel are combined into four 2D maps. The maps show similar results over several time-channels, which allows us to average results in three time bins: early- (channels 6-12), mid- (channels 13-16), and late-time (channels 17-20). The B-field and dB/dt power maps contain highly linear and angular features that manifest differently in the two data sets and do not correlate with subsurface structure. Comparison of power maps from the two data types suggests that cultural noise is most prevalent at short spatial scales, which is consistent with the finite spatial continuity of infrastructure, and at late-time, when geologic signals are weakest and the signal to noise ratio is smallest. We conclude from these results that a CWT approach can be used to identify areas in which cultural noise impacts collected data. Future work is required to assess the magnitude of this impact and to filter the signals from cultural noise from the data.
Continuous wavelet transform analysis of acceleration signals measured from a wave buoy.
Chuang, Laurence Zsu-Hsin; Wu, Li-Chung; Wang, Jong-Hao
2013-01-01
Accelerometers, which can be installed inside a floating platform on the sea, are among the most commonly used sensors for operational ocean wave measurements. To examine the non-stationary features of ocean waves, this study was conducted to derive a wavelet spectrum of ocean waves and to synthesize sea surface elevations from vertical acceleration signals of a wave buoy through the continuous wavelet transform theory. The short-time wave features can be revealed by simultaneously examining the wavelet spectrum and the synthetic sea surface elevations. The in situ wave signals were applied to verify the practicality of the wavelet-based algorithm. We confirm that the spectral leakage and the noise at very-low-frequency bins influenced the accuracies of the estimated wavelet spectrum and the synthetic sea surface elevations. The appropriate thresholds of these two factors were explored. To study the short-time wave features from the wave records, the acceleration signals recorded from an accelerometer inside a discus wave buoy are analysed. The results from the wavelet spectrum show the evidence of short-time nonlinear wave events. Our study also reveals that more surface profiles with higher vertical asymmetry can be found from short-time nonlinear wave with stronger harmonic spectral peak. Finally, we conclude that the algorithms of continuous wavelet transform are practical for revealing the short-time wave features of the buoy acceleration signals. PMID:23966188
2016-01-01
A novel method of extracting heart rate and oxygen saturation from a video-based biosignal is described. The method comprises a novel modular continuous wavelet transform approach which includes: performing the transform, undertaking running wavelet archetyping to enhance the pulse information, extraction of the pulse ridge time–frequency information [and thus a heart rate (HRvid) signal], creation of a wavelet ratio surface, projection of the pulse ridge onto the ratio surface to determine the ratio of ratios from which a saturation trending signal is derived, and calibrating this signal to provide an absolute saturation signal (SvidO2). The method is illustrated through its application to a video photoplethysmogram acquired during a porcine model of acute desaturation. The modular continuous wavelet transform-based approach is advocated by the author as a powerful methodology to deal with noisy, non-stationary biosignals in general. PMID:27382479
Addison, Paul S
2016-06-01
A novel method of extracting heart rate and oxygen saturation from a video-based biosignal is described. The method comprises a novel modular continuous wavelet transform approach which includes: performing the transform, undertaking running wavelet archetyping to enhance the pulse information, extraction of the pulse ridge time-frequency information [and thus a heart rate (HRvid) signal], creation of a wavelet ratio surface, projection of the pulse ridge onto the ratio surface to determine the ratio of ratios from which a saturation trending signal is derived, and calibrating this signal to provide an absolute saturation signal (SvidO2). The method is illustrated through its application to a video photoplethysmogram acquired during a porcine model of acute desaturation. The modular continuous wavelet transform-based approach is advocated by the author as a powerful methodology to deal with noisy, non-stationary biosignals in general. PMID:27382479
NASA Astrophysics Data System (ADS)
Gdeisat, Munther; Burton, David; Lilley, Francis; Lalor, Michael; Moore, Chris
2010-04-01
This paper proposes the use of the two-dimensional continuous Paul wavelet transform to extract the phase of spatial carrier fringe patterns. The proposed algorithm has been tested using computer-generated and real fringe patterns, and these tests have demonstrated the suitability of the proposed technique for the phase demodulation of fringe patterns. Additionally, this algorithm is compared to three two-dimensional continuous wavelet algorithms that have figured prominently in the literature, specifically the Morlet, advanced Morlet and fan mother wavelets. This comparison has revealed that the proposed algorithm outperforms the other three mother wavelets in terms of its suitability for extracting the phase of fringe patterns that exhibit large phase variations.
Gao, Zhan; Deng, Yan; Duan, Yiting; Zhang, Zhifeng; Wei, Cheng; Chen, Shiqian; Cui, Jianying; Feng, Qibo
2012-01-01
A heterodyne temporal speckle pattern interferometer that measures the in-plane displacement dynamically has been built. The object is displaced in its plane continuously and the frequency-modulated output signals with a carrier frequency are recorded by a CCD camera. The displacement information is extracted with wavelet transform technique. Preliminary experiments have been performed with such interferometer. The respective measurement results recovered from wavelet transform and Fourier transform are compared.
Analysis of Mold Friction in a Continuous Casting Using Wavelet Entropy
NASA Astrophysics Data System (ADS)
Yong, Ma; Fangyin, Wang; Cheng, Peng; Wei, Gui; Bohan, Fang
2016-06-01
By studying mold friction (MDF), we observed that monitoring and controlling of the friction between the strand and the mold is very important for continuous casting to improve lubrication and prevent breakout. However, existing analysis technologies of MDF do not support the continuous casting very well. In addition, we found that the wavelet entropy has multiscale and statistical properties. Informed by these observations, in this article, we use wavelet entropy to judge the lubrication state between the strand and the mold. First, we demonstrate the implementation and superiority of wavelet entropy and how it helps in efficient evaluation of the lubrication state in mold. A study of wavelet entropy of MDF, which is obtained from the abnormal continuous casting production, such as level fluctuation, submerged entry nozzle broken, and breakout, has been performed to achieve relevant conclusions. The results indicate that the information of MDF in time and frequency domains could be obtained simultaneously by the application of wavelet entropy and that the wavelet entropy has a good sensibility for the study of disorder of MDF, which could further reveal the nature of MDF.
Delay-dependent stability and stabilisation of continuous 2D delayed systems with saturating control
NASA Astrophysics Data System (ADS)
Hmamed, Abdelaziz; Kririm, Said; Benzaouia, Abdellah; Tadeo, Fernando
2016-09-01
This paper deals with the stabilisation problem of continuous two-dimensional (2D) delayed systems, in the presence of saturations on the control signals. For this, a new delay decomposition approach is proposed to deal with the stability and stabilisation issues. The idea is that the range of variation of each delay is divided into segments, and a specific Lyapunov- Krasovskii functional is used that contains different weight matrices in each segment. Then, based on this approach, new delay-dependent stability and stabilisation criteria for continuous 2D delayed systems are derived. These criteria are less conservative and include some existing results as special cases. Some numerical examples are provided to show that a significant improvement is achieved using the proposed approach.
Exploration of EEG features of Alzheimer's disease using continuous wavelet transform.
Ghorbanian, Parham; Devilbiss, David M; Hess, Terry; Bernstein, Allan; Simon, Adam J; Ashrafiuon, Hashem
2015-09-01
We have developed a novel approach to elucidate several discriminating EEG features of Alzheimer's disease. The approach is based on the use of a variety of continuous wavelet transforms, pairwise statistical tests with multiple comparison correction, and several decision tree algorithms, in order to choose the most prominent EEG features from a single sensor. A pilot study was conducted to record EEG signals from Alzheimer's disease (AD) patients and healthy age-matched control (CTL) subjects using a single dry electrode device during several eyes-closed (EC) and eyes-open (EO) resting conditions. We computed the power spectrum distribution properties and wavelet and sample entropy of the wavelet coefficients time series at scale ranges approximately corresponding to the major brain frequency bands. A predictive index was developed using the results from statistical tests and decision tree algorithms to identify the most reliable significant features of the AD patients when compared to healthy controls. The three most dominant features were identified as larger absolute mean power and larger standard deviation of the wavelet scales corresponding to 4-8 Hz (θ) during EO and lower wavelet entropy of the wavelet scales corresponding to 8-12 Hz (α) during EC, respectively. The fourth reliable set of distinguishing features of AD patients was lower relative power of the wavelet scales corresponding to 12-30 Hz (β) followed by lower skewness of the wavelet scales corresponding to 2-4 Hz (upper δ), both during EO. In general, the results indicate slowing and lower complexity of EEG signal in AD patients using a very easy-to-use and convenient single dry electrode device.
Exploration of EEG features of Alzheimer's disease using continuous wavelet transform.
Ghorbanian, Parham; Devilbiss, David M; Hess, Terry; Bernstein, Allan; Simon, Adam J; Ashrafiuon, Hashem
2015-09-01
We have developed a novel approach to elucidate several discriminating EEG features of Alzheimer's disease. The approach is based on the use of a variety of continuous wavelet transforms, pairwise statistical tests with multiple comparison correction, and several decision tree algorithms, in order to choose the most prominent EEG features from a single sensor. A pilot study was conducted to record EEG signals from Alzheimer's disease (AD) patients and healthy age-matched control (CTL) subjects using a single dry electrode device during several eyes-closed (EC) and eyes-open (EO) resting conditions. We computed the power spectrum distribution properties and wavelet and sample entropy of the wavelet coefficients time series at scale ranges approximately corresponding to the major brain frequency bands. A predictive index was developed using the results from statistical tests and decision tree algorithms to identify the most reliable significant features of the AD patients when compared to healthy controls. The three most dominant features were identified as larger absolute mean power and larger standard deviation of the wavelet scales corresponding to 4-8 Hz (θ) during EO and lower wavelet entropy of the wavelet scales corresponding to 8-12 Hz (α) during EC, respectively. The fourth reliable set of distinguishing features of AD patients was lower relative power of the wavelet scales corresponding to 12-30 Hz (β) followed by lower skewness of the wavelet scales corresponding to 2-4 Hz (upper δ), both during EO. In general, the results indicate slowing and lower complexity of EEG signal in AD patients using a very easy-to-use and convenient single dry electrode device. PMID:25863694
A new methodology to map double-cropping croplands based on continuous wavelet transform
NASA Astrophysics Data System (ADS)
Qiu, Bingwen; Zhong, Ming; Tang, Zhenghong; Wang, Chongyang
2014-02-01
Cropping intensity is one of the major factors in crop production and agricultural intensification. A new double-cropping croplands mapping methodology using Moderate Resolution Imaging Spectroradiometer (MODIS) time series datasets through continuous wavelet transform was proposed in this study. This methodology involved four steps. First, daily continuous MODIS Enhanced Vegetation Index (EVI) time series datasets were developed for the study year. Next, the EVI time series datasets were transformed into a two dimensional (time-frequency) wavelet scalogram based on continuous wavelet transform. Third, a feature extraction process was conducted on the wavelet scalogram, where the characteristic spectra were calculated from the wavelet scalogram and the feature peak within two skeleton lines was obtained. Finally, a threshold was determined for feature peak values to discriminate double-cropping croplands within each pixel. The application of the proposed procedure to China's Henan Province in 2010 produced an objective and accurate spatial distribution map, which correlated well with in situ observation data (over 90% agreement). The proposed new methodology efficiently handled complex variability that might be caused by regional variation in climate, management practices, growth peaks by winter weed or winter wheat, and data noise. Therefore, the methodology shows promise for future studies at regional and global scales.
NASA Astrophysics Data System (ADS)
Galiana-Merino, J. J.; Rosa-Herranz, J. L.; Rosa-Cintas, S.; Martinez-Espla, J. J.
2013-01-01
A MATLAB-based computer code has been developed for the simultaneous wavelet analysis and filtering of multichannel seismic data. The considered time-frequency transforms include the continuous wavelet transform, the discrete wavelet transform and the discrete wavelet packet transform. The developed approaches provide a fast and precise time-frequency examination of the seismograms at different frequency bands. Moreover, filtering methods for noise, transients or even baseline removal, are implemented. The primary motivation is to support seismologists with a user-friendly and fast program for the wavelet analysis, providing practical and understandable results. Program summaryProgram title: SeismicWaveTool Catalogue identifier: AENG_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AENG_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC license, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 611072 No. of bytes in distributed program, including test data, etc.: 14688355 Distribution format: tar.gz Programming language: MATLAB (MathWorks Inc.) version 7.8.0.347 (R2009a) or higher. Wavelet Toolbox is required. Computer: Developed on a MacBook Pro. Tested on Mac and PC. No computer-specific optimization was performed. Operating system: Any supporting MATLAB (MathWorks Inc.) v7.8.0.347 (R2009a) or higher. Tested on Mac OS X 10.6.8, Windows XP and Vista. Classification: 13. Nature of problem: Numerous research works have developed a great number of free or commercial wavelet based software, which provide specific solutions for the analysis of seismic data. On the other hand, standard toolboxes, packages or libraries, such as the MathWorks' Wavelet Toolbox for MATLAB, offer command line functions and interfaces for the wavelet analysis of one-component signals. Thus, software usually is focused on very specific problems
Analysis of photonic Doppler velocimetry data based on the continuous wavelet transform
Liu Shouxian; Wang Detian; Li Tao; Chen Guanghua; Li Zeren; Peng Qixian
2011-02-15
The short time Fourier transform (STFT) cannot resolve rapid velocity changes in most photonic Doppler velocimetry (PDV) data. A practical analysis method based on the continuous wavelet transform (CWT) was presented to overcome this difficulty. The adaptability of the wavelet family predicates that the continuous wavelet transform uses an adaptive time window to estimate the instantaneous frequency of signals. The local frequencies of signal are accurately determined by finding the ridge in the spectrogram of the CWT and then are converted to target velocity according to the Doppler effects. A performance comparison between the CWT and STFT is demonstrated by a plate-impact experiment data. The results illustrate that the new method is automatic and adequate for analysis of PDV data.
NASA Astrophysics Data System (ADS)
Fayadh, Rashid A.; Malek, F.; Fadhil, Hilal A.; Dawood, Sameer A.; Abdullah, Farah Salwani
2015-05-01
In this paper, three levels of analysis and synthesis filter banks were used to create coefficients for a continuous wavelet transform (CWT) and discrete wavelet transform (DWT). The main property of these wavelet transform schemes is their ability to construct the transmitted signal across a log-normal fading channel over additive white Gaussian noise (AWGN). Wireless rake-receiver structure was chosen as a major application to reduce the inter-symbol interference (ISI) and to minimize the noise. In this work, a new scheme of rake receiver is proposed to receive indoor, multi-path components (MPCs) for ultra-wideband (UWB) wireless communication systems. Rake receivers consist of a continuous wavelet rake (CW-rake) and a discrete wavelet rake (DW-rake), and they use huge bandwidth (7.5 GHz), as reported by the Federal Communications Commission (FCC). The indoor channel models chose for analysis in this research were the non line-of-sight (LOS) channel model (CM4 from 4 to 10 meters) to show the behavior of bit error rate (BER) with respect to signal-to noise ratio (SNR). Two types of rake receiver were used in the simulation, i.e., partial-rake and selective-rake receivers with the maximal ratio combining (MRC) technique to capture the energy of the signal from the output of the rake's fingers.
Application Of Continuous Wavelet Transform On Aeromagnetic Data To Identify Volcanic Rocks
NASA Astrophysics Data System (ADS)
Yang, Y.; Li, Y.; Liu, T.
2008-12-01
This paper focuses on the application of continuous wavelet transform on aeromagnetic data, to locate and characterize volcanic rocks. The studied structure is sited in the north centre of the Huanghua depression in the Bohaiwan basin of east China. As channels of magmatism activities, the faults have caused multi-stage magma outpouring and intrusion, forming igneous rocks of different series of strata. As a traditional frequency decomposition method, the discrete wavelet transform is unable to localize frequency variations over time. To handle this problem, the short time Fourier transform method is widely used for the decomposition of non-stationary signals. One problem with this approach is that the fixed width `window function' results in limited resolution. Therefore, the continuous wavelet transform decomposition was used as an alternative approach to overcome this resolution problem. In the continuous wavelet transform, the signal is multiplied with a function similar to a `window function' but the width of the window is not fixed. The time window width is allowed to vary depending upon the frequency that is being considered. As for the magnetic anomalies of igneous rocks, they have different frequencies due to their depths; by analyzing the complex wavelet-based time-frequency characteristics of certain frequencies, we can identify the residual anomalies caused by volcanic rocks in different depths. The theoretical results show that local high frequency spectrum anomalies are the reflection of magnetic sources, and different scales (or different center frequencies) reflect different source depths, with larger scales for deeper sources. Therefore, by analyzing the complex wavelet-based frequency spectrum under different centre frequencies, we can analyze the distribution of magnetic field sources. Then the continuous wavelet transform was applied on the RTP aeromagnetic data of our study area. The data processing results present a detailed description of the
NASA Astrophysics Data System (ADS)
Elbarghathi, F.; Wang, T.; Zhen, D.; Gu, F.; Ball, A.
2012-05-01
Vibration signals from a gearbox are usually very noisy which makes it difficult to find reliable symptoms of a fault in a multistage gearbox. This paper explores the use of time synchronous average (TSA) to suppress the noise and Continue Wavelet Transformation (CWT) to enhance the non-stationary nature of fault signal for more accurate fault diagnosis. The results obtained in diagnosis an incipient gear breakage show that fault diagnosis results can be improved by using an appropriate wavelet. Moreover, a new scheme based on the level of wavelet coefficient amplitudes of baseline data alone, without faulty data samples, is suggested to select an optimal wavelet.
NASA Astrophysics Data System (ADS)
Liu, Yao; Wang, Xiufeng; Lin, Jing; Zhao, Wei
2016-11-01
Motor current is an emerging and popular signal which can be used to detect machining chatter with its multiple advantages. To achieve accurate and reliable chatter detection using motor current, it is important to make clear the quantitative relationship between motor current and chatter vibration, which has not yet been studied clearly. In this study, complex continuous wavelet coherence, including cross wavelet transform and wavelet coherence, is applied to the correlation analysis of motor current and chatter vibration in grinding. Experimental results show that complex continuous wavelet coherence performs very well in demonstrating and quantifying the intense correlation between these two signals in frequency, amplitude and phase. When chatter occurs, clear correlations in frequency and amplitude in the chatter frequency band appear and the phase difference of current signal to vibration signal turns from random to stable. The phase lead of the most correlated chatter frequency is the largest. With the further development of chatter, the correlation grows up in intensity and expands to higher order chatter frequency band. The analyzing results confirm that there is a consistent correlation between motor current and vibration signals in the grinding chatter process. However, to achieve accurate and reliable chatter detection using motor current, the frequency response bandwidth of current loop of the feed drive system must be wide enough to response chatter effectively.
Ok, Jong G; Panday, Ashwin; Lee, Taehwa; Jay Guo, L
2014-12-21
We present a versatile and simple methodology for continuous and scalable 2D micro/nano-structure fabrication via sequential 1D patterning strokes enabled by dynamic nano-inscribing (DNI) and vibrational indentation patterning (VIP) as well as a 'single-stroke' 2D patterning using a DNI tool in VIP. PMID:25363145
Khaloo, Shokooh S; Ensafi, Ali A; Khayamian, T
2007-01-15
A new method is proposed for the determination of bismuth and copper in the presence of each other based on adsorptive stripping voltammetry of complexes of Bi(III)-chromazorul-S and Cu(II)-chromazorul-S at a hanging mercury drop electrode (HMDE). Copper is an interfering element for the determination of Bi(III) because, the voltammograms of Bi(III) and Cu(II) overlapped with each other. Continuous wavelet transform (CWT) was applied to separate the voltammograms. In this regards, wavelet filter, resolution of the peaks and the fitness were optimized to obtain minimum detection limit for the elements. Through continuous wavelet transform Symlet4 (Sym4) wavelet filter at dilation 6, quantitative and qualitative analysis the mixture solutions of bismuth and copper was performed. It was also realized that copper imposes a matrix effect on the determination of Bi(III) and the standard addition method was able to cope with this effect. Bismuth does not have matrix effect on copper determination, therefore, the calibration curve using wavelet coefficients of CWT was used for determination of Cu(II) in the presence of Bi(III). The detection limits were 0.10 and 0.05ngml(-1) for bismuth and copper, respectively. The linear dynamic range of 0.1-30.0 and 0.1-32.0ngml(-1) were obtained for determination of bismuth in the presence of 24.0ngml(-1) of copper and copper in the presence of 24.0ngml(-1) of bismuth, respectively. The method was used for determination of these two cations in water and human hair samples. The results indicate the ability of method for the determination of these two elements in real samples. PMID:19071307
Mouse EEG spike detection based on the adapted continuous wavelet transform
NASA Astrophysics Data System (ADS)
Tieng, Quang M.; Kharatishvili, Irina; Chen, Min; Reutens, David C.
2016-04-01
Objective. Electroencephalography (EEG) is an important tool in the diagnosis of epilepsy. Interictal spikes on EEG are used to monitor the development of epilepsy and the effects of drug therapy. EEG recordings are generally long and the data voluminous. Thus developing a sensitive and reliable automated algorithm for analyzing EEG data is necessary. Approach. A new algorithm for detecting and classifying interictal spikes in mouse EEG recordings is proposed, based on the adapted continuous wavelet transform (CWT). The construction of the adapted mother wavelet is founded on a template obtained from a sample comprising the first few minutes of an EEG data set. Main Result. The algorithm was tested with EEG data from a mouse model of epilepsy and experimental results showed that the algorithm could distinguish EEG spikes from other transient waveforms with a high degree of sensitivity and specificity. Significance. Differing from existing approaches, the proposed approach combines wavelet denoising, to isolate transient signals, with adapted CWT-based template matching, to detect true interictal spikes. Using the adapted wavelet constructed from a predefined template, the adapted CWT is calculated on small EEG segments to fit dynamical changes in the EEG recording.
2D CFD Analysis of an Airfoil with Active Continuous Trailing Edge Flap
NASA Astrophysics Data System (ADS)
Jaksich, Dylan; Shen, Jinwei
2014-11-01
Efficient and quieter helicopter rotors can be achieved through on-blade control devices, such as active Continuous Trailing-Edge Flaps driven by embedded piezoelectric material. This project aims to develop a CFD simulation tool to predict the aerodynamic characteristics of an airfoil with CTEF using open source code: OpenFOAM. Airfoil meshes used by OpenFOAM are obtained with MATLAB scripts. Once created it is possible to rotate the airfoil to various angles of attack. When the airfoil is properly set up various OpenFOAM properties, such as kinematic viscosity and flow velocity, are altered to achieve the desired testing conditions. Upon completion of a simulation, the program gives the lift, drag, and moment coefficients as well as the pressure and velocity around the airfoil. The simulation is then repeated across multiple angles of attack to give full lift and drag curves. The results are then compared to previous test data and other CFD predictions. This research will lead to further work involving quasi-steady 2D simulations incorporating NASTRAN to model aeroelastic deformation and eventually to 3D aeroelastic simulations. NSF ECE Grant #1358991 supported the first author as an REU student.
NASA Astrophysics Data System (ADS)
Timoshevskiy, M. V.; Zapryagaev, I. I.; Pervunin, K. S.; Markovich, D. M.
2016-10-01
In the paper, the possibility of active control of a cavitating flow over a 2D hydrofoil that replicates a scaled-down model of high-pressure hydroturbine guide vane (GV) was tested. The flow manipulation was implemented by a continuous tangential liquid injection at different flow rates through a spanwise slot in the foil surface. In experiments, the hydrofoil was placed in the test channel at the attack angle of 9°. Different cavitation conditions were reached by varying the cavitation number and injection velocity. In order to study time dynamics and spatial patterns of partial cavities, high-speed imaging was employed. A PIV method was used to measure the mean and fluctuating velocity fields over the hydrofoil. Hydroacoustic measurements were carried out by means of a pressure transducer to identify spectral characteristics of the cavitating flow. It was found that the present control technique is able to modify the partial cavity pattern (or even totally suppress cavitation) in case of stable sheet cavitation and change the amplitude of pressure pulsations at unsteady regimes. The injection technique makes it also possible to significantly influence the spatial distributions of the mean velocity and its turbulent fluctuations over the GV section for non-cavitating flow and sheet cavitation.
Determination of human EEG alpha entrainment ERD/ERS using the continuous complex wavelet transform
NASA Astrophysics Data System (ADS)
Chorlian, David B.; Porjesz, Bernice; Begleiter, Henri
2003-04-01
Alpha entrainment caused by exposure to a background stimulus continuously flickering at a rate of 8 1/3 Hz was affected by the appearance of a foreground target stimulus to which the subjects were requested to press a button. With the use of bipolar derivations (to reduce volume conduction effects), scalp recorded EEG potentials were subjected to a continuous wavelet transform using complex Morlet wavelets at a range of scales. Complex Morlet wavelets were used to calculate efficiently instantaneous amplitudes and phases on a per-trial basis, rather than using the Hilbert transform on band-pass filtered data. Multiple scales were employed to contrast the pattern of alpha activity with those in other bands, and to determine whether the harmonics observed in the spectral analysis of the data were simply a result of the non-sinusoidal response to the entraining signal or a distinct neural phenomenon. We were thus able to calculate desynchronization/resynchronization for both the entrained and non-entrained alpha activity. The occurance of the target stimulus caused a sharp increase in amplitude in both the entrained and non-entrained alpha activity, followed by a sharp decrease, and then a return to baseline, over a period of 2.5 seconds. However, the entrained alpha activity showed a much more rapid recovery than non-entrained activity.
NASA Astrophysics Data System (ADS)
Gu, Junhua; Xu, Haiguang; Wang, Jingying; An, Tao; Chen, Wen
2013-08-01
We propose a continuous wavelet transform based non-parametric foreground subtraction method for the detection of redshifted 21 cm signal from the epoch of reionization. This method works based on the assumption that the foreground spectra are smooth in frequency domain, while the 21 cm signal spectrum is full of saw-tooth-like structures, thus their characteristic scales are significantly different. We can distinguish them in the wavelet coefficient space easily and perform the foreground subtraction. Compared with the traditional spectral fitting based method, our method is more tolerant to complex foregrounds. Furthermore, we also find that when the instrument has uncorrected response error, our method can also work significantly better than the spectral fitting based method. Our method can obtain similar results with the Wp smoothing method, which is also a non-parametric method, but our method consumes much less computing time.
Heterogeneities Analysis Using the Generalized Fractal Dimension and Continuous Wavelet Transform
NASA Astrophysics Data System (ADS)
Ouadfeul, S.; Aliouane, L.; Boudella, A.
2012-04-01
The main goal of this work is analyze heterogeneities from well-logs data using the wavelet transform modulus maxima lines (WTMM). Firstly, the continuous wavelet transform (CWT) with sliding window is calculated. The next step consists to calculate the maxima of the modulus of the CWT and estimate the spectrum of exponents. The three generalized fractal dimensions D0, D1 and D2 are then estimated. Application of the proposed idea at the synthetic and real well-logs data of a borehole located in the Algerian Sahara shows that the fractal dimensions are very sensitive to lithological variations. The generalized fractal dimensions are a very robust tool than can be used for petroleum reservoir characterization. Keywrods: reservoir, Heterogeneities, WTMM, fractal dimension.
NASA Astrophysics Data System (ADS)
Dai, Yu; Xue, Yuan; Zhang, Jianxun
2016-01-01
Impulsive noise caused by some random events has the main character of short rise-time and wide frequency spectrum range, so it has the potential to degrade the performance and reliability of the harmonic estimation. This paper focuses on the harmonic estimation procedure based on continuous wavelet transform (CWT) when the analyzed signal is corrupted by the impulsive noise. The digital CWT of both the time-varying sinusoidal signal and the impulsive noise are analyzed, and there are two cross ridges in the time-frequency plane of CWT, which are generated by the signal and the noise separately. In consideration of the amplitude of the noise and the number of the spike event, two inequalities are derived to provide limitations on the wavelet parameters. Based on the amplitude distribution of the noise, the optimal wavelet parameters determined by solving these inequalities are used to suppress the contamination of the noise, as well as increase the amplitude of the ridge corresponding to the signal, so the parameters of each harmonic component can be estimated accurately. The proposed procedure is applied to a numerical simulation and a bone vibration signal test giving satisfactory results of stationary and time-varying harmonic parameter estimation.
Automatic detection of position and depth of potential UXO using continuous wavelet transforms
NASA Astrophysics Data System (ADS)
Billings, Stephen D.; Herrmann, Felix J.
2003-09-01
Inversion algorithms for UXO discrimination using magnetometery have recently been used to achieve very low False Alarm Rates, with 100% recovery of detected ordnance. When there are many UXO and/or when the UXO are at significantly different depths, manual estimation of the initial position and scale for each item, is a laborious and time-consuming process. In this paper, we utilize the multi-resolution properties of wavelets to automatically estimate both the position and scale of dipole peaks. The Automated Wavelet Detection (AWD) algorithm that we develop consists of four-stages: (i) maxima and minima in the data are followed across multiple scales as we zoom with a continuous wavelet transform; (ii) the decay of the amplitude of each peak with scale is used to estimate the depth to source; (iii) adjacent maxima and minima of comparable depth are joined together to form dipole anomalies; and (iv) the relative positions and amplitudes of the extrema, along with their depths, are used to estimate a dipole model. We demonstrate the application of the AWD algorithm to three datasets with different characteristics. In each case, the method rapidly located the majority of dipole anomalies and produced accurate estimates of dipole parameters.
NASA Astrophysics Data System (ADS)
Chiariotti, P.; Revel, G. M.; Martarelli, M.
2016-06-01
Continuous Scanning Laser Doppler Vibrometry (CSLDV) is a well-known technique within the structural dynamic community. However, the whole potentials of CSLDV for diagnostic purposes have not been fully exploited yet. This paper presents a time domain approach for identifying damages in structures. The method, which is based on a wavelet processing of vibration data collected by CSLDV, does not need any a-priori knowledge of the vibration behavior of the undamaged sample. Applications on real test cases are presented and discussed in the paper, demonstrating the promising performance of the approach as a non-destructive testing technique.
NASA Astrophysics Data System (ADS)
Qian, Jinfang; Zhang, Changjiang
2014-11-01
An efficient algorithm based on continuous wavelet transform combining with pre-knowledge, which can be used to detect the defect of glass bottle mouth, is proposed. Firstly, under the condition of ball integral light source, a perfect glass bottle mouth image is obtained by Japanese Computar camera through the interface of IEEE-1394b. A single threshold method based on gray level histogram is used to obtain the binary image of the glass bottle mouth. In order to efficiently suppress noise, moving average filter is employed to smooth the histogram of original glass bottle mouth image. And then continuous wavelet transform is done to accurately determine the segmentation threshold. Mathematical morphology operations are used to get normal binary bottle mouth mask. A glass bottle to be detected is moving to the detection zone by conveyor belt. Both bottle mouth image and binary image are obtained by above method. The binary image is multiplied with normal bottle mask and a region of interest is got. Four parameters (number of connected regions, coordinate of centroid position, diameter of inner cycle, and area of annular region) can be computed based on the region of interest. Glass bottle mouth detection rules are designed by above four parameters so as to accurately detect and identify the defect conditions of glass bottle. Finally, the glass bottles of Coca-Cola Company are used to verify the proposed algorithm. The experimental results show that the proposed algorithm can accurately detect the defect conditions of the glass bottles and have 98% detecting accuracy.
Determination of solar cycle length variations using the continuous wavelet transform
NASA Astrophysics Data System (ADS)
Fligge, M.; Solanki, S. K.; Beer, J.
1999-06-01
The length of the sunspot cycle determined by Friis-Christensen & Lassen (1991) correlates well with indicators of terrestrial climate, but has been criticized as being subjective. In the present paper we present a more objective and general cycle-length determination. Objectivity is achieved by using the continuous wavelet transform based on Morlet wavelets and carrying out a careful error analysis. Greater generality comes from the application of this technique to different records of solar activity, e.g. sunspot number, sunspot area, plage area or (10) Be records. The use of different indicators allows us to track cycle length variations back to the 15th century. All activity indicators give cycle length records which agree with each other within the error bars, whereby the signal due to the solar cycle is weaker within (10) Be than in the other indicators. In addition, all records exhibit cycle length variations which are, within the error bars, in accordance with the record originally proposed by Friis-Christensen & Lassen (1991). In the 16th century, however, the (10) Be record suggests a much longer cycle than the auroral record used by Friis-Christensen & Lassen. Also, the presence of a distinct 11-year cycle in the (10) Be record during the Maunder Minimum is confirmed. By combining the results from all the indicators a composite of the solar cycle length is constructed, which we expect to be more reliable than the length derived from individual records.
Instrument-independent analysis of music by means of the continuous wavelet transform
NASA Astrophysics Data System (ADS)
Olmo, Gabriella; Dovis, Fabio; Benotto, Paolo; Calosso, Claudio; Passaro, Pierluigi
1999-10-01
This paper deals with the problem of automatic recognition of music. Segments of digitized music are processed by means of a Continuous Wavelet Transform, properly chosen so as to match the spectral characteristics of the signal. In order to achieve a good time-scale representation of the signal components a novel wavelet has been designed suited to the musical signal features. particular care has been devoted towards an efficient implementation, which operates in the frequency domain, and includes proper segmentation and aliasing reduction techniques to make the analysis of long signals feasible. The method achieves very good performance in terms of both time and frequency selectivity, and can yield the estimate and the localization in time of both the fundamental frequency and the main harmonics of each tone. The analysis is used as a preprocessing step for a recognition algorithm, which we show to be almost independent on the instrument reproducing the sounds. Simulations are provided to demonstrate the effectiveness of the proposed method.
A continuous wavelet transform and classification method for delirium motoric subtyping.
Godfrey, Alan; Conway, Richard; Leonard, Maeve; Meagher, David; Olaighin, Gearóid M
2009-06-01
The usefulness of motor subtypes of delirium is unclear due to inconsistency in subtyping methods and a lack of validation with objective measures of activity. The activity of 40 patients was measured over 24 h with a discrete accelerometer-based activity monitor. The continuous wavelet transform (CWT) with various mother wavelets were applied to accelerometry data from three randomly selected patients with DSM-IV delirium that were readily divided into hyperactive, hypoactive, and mixed motor subtypes. A classification tree used the periods of overall movement as measured by the discrete accelerometer-based monitor as determining factors for which to classify these delirious patients. This data used to create the classification tree were based upon the minimum, maximum, standard deviation, and number of coefficient values, generated over a range of scales by the CWT. The classification tree was subsequently used to define the remaining motoric subtypes. The use of a classification system shows how delirium subtypes can be categorized in relation to overall motoric behavior. The classification system was also implemented to successfully define other patient motoric subtypes. Motor subtypes of delirium defined by observed ward behavior differ in electronically measured activity levels. PMID:19497833
Use of continuous optimization methods to find carbon links in 2D INADEQUATE spectra
NASA Astrophysics Data System (ADS)
Anand, Christopher Kumar; Bain, Alex D.; Watson, Sean C.
2011-05-01
The 2-D INADEQUATE experiment is a useful experiment for determining carbon structures of organic molecules, which is known for having low signal-to-noise ratios. A non-linear optimization method for solving low-signal spectra resulting from this experiment is introduced to compensate. The method relies on the peak locations defined by the INADEQUATE experiment to create boxes around these areas and measure the signal in each. By measuring pairs of these boxes and applying penalty functions that represent a priori information, we are able to quickly and reliably solve spectra with an acquisition time approximately a quarter of that required by traditional methods. Examples are shown using the spectrum of sucrose.
Cheng, Tao; Rivard, Benoit; Sánchez-Azofeifa, Arturo G; Féret, Jean-Baptiste; Jacquemoud, Stephane; Ustin, Susan L
2012-08-15
Leaf water content is an important variable for understanding plant physiological properties. This study evaluates a spectral analysis approach, continuous wavelet analysis (CWA), for the spectroscopic estimation of leaf gravimetric water content (GWC, %) and determines robust spectral indicators of GWC across a wide range of plant species from different ecosystems. CWA is both applied to the Leaf Optical Properties Experiment (LOPEX) data set and a synthetic data set consisting of leaf reflectance spectra simulated using the leaf optical properties spectra (PROSPECT) model. The results for the two data sets, including wavelet feature selection and GWC prediction derived using those features, are compared to the results obtained from a previous study for leaf samples collected in the Republic of Panamá (PANAMA), to assess the predictive capabilities and robustness of CWA across species. Furthermore, predictive models of GWC using wavelet features derived from PROSPECT simulations are examined to assess their applicability to measured data. The two measured data sets (LOPEX and PANAMA) reveal five common wavelet feature regions that correlate well with leaf GWC. All three data sets display common wavelet features in three wavelength regions that span 1732-1736 nm at scale 4, 1874-1878 nm at scale 6, and 1338-1341 nm at scale 7 and produce accurate estimates of leaf GWC. This confirms the applicability of the wavelet-based methodology for estimating leaf GWC for leaves representative of various ecosystems. The PROSPECT-derived predictive models perform well on the LOPEX data set but are less successful on the PANAMA data set. The selection of high-scale and low-scale features emphasizes significant changes in both overall amplitude over broad spectral regions and local spectral shape over narrower regions in response to changes in leaf GWC. The wavelet-based spectral analysis tool adds a new dimension to the modeling of plant physiological properties with
Ullah, Saleem; Skidmore, Andrew K; Naeem, Mohammad; Schlerf, Martin
2012-10-15
Leaf water content determines plant health, vitality, photosynthetic efficiency and is an important indicator of drought assessment. The retrieval of leaf water content from the visible to shortwave infrared spectra is well known. Here for the first time, we estimated leaf water content from the mid to thermal infrared (2.5-14.0 μm) spectra, based on continuous wavelet analysis. The dataset comprised 394 spectra from nine plant species, with different water contents achieved through progressive drying. To identify the spectral feature most sensitive to the variations in leaf water content, first the Directional Hemispherical Reflectance (DHR) spectra were transformed into a wavelet power scalogram, and then linear relations were established between the wavelet power scalogram and leaf water content. The six individual wavelet features identified in the mid infrared yielded high correlations with leaf water content (R(2)=0.86 maximum, 0.83 minimum), as well as low RMSE (minimum 8.56%, maximum 9.27%). The combination of four wavelet features produced the most accurate model (R(2)=0.88, RMSE=8.00%). The models were consistent in terms of accuracy estimation for both calibration and validation datasets, indicating that leaf water content can be accurately retrieved from the mid to thermal infrared domain of the electromagnetic radiation.
NASA Astrophysics Data System (ADS)
Sarma, Bornali; Chauhan, Sourabh S.; Wharton, A. M.; Iyengar, A. N. Sekar; Iyengar
2013-10-01
Characterization of self-similarity properties of turbulence in magnetized plasma is being carried out in DC glow discharge plasma. The time series floating potential fluctuation experimental data are acquired from the plasma by Langmuir probe. Continuous wavelet transform (CWT) analysis considering db4 mother wavelet has been applied to the experimental data and self-similarity properties are detected by evaluating the Hurst exponent from the wavelet variance plotting. From the CWT spectrum, effort is made to extract a highly correlated frequency by locating the brightest spot. Accordingly, those signals are treated for finding out correlation dimension and the Liapunov exponent so that the exact frequency responsible for the chaotic behavior could be found out.
Continuous catchment-scale monitoring of geomorphic processes with a 2-D seismological array
NASA Astrophysics Data System (ADS)
Burtin, A.; Hovius, N.; Milodowski, D.; Chen, Y.-G.; Wu, Y.-M.; Lin, C.-W.; Chen, H.
2012-04-01
The monitoring of geomorphic processes during extreme climatic events is of a primary interest to estimate their impact on the landscape dynamics. However, available techniques to survey the surface activity do not provide a relevant time and/or space resolution. Furthermore, these methods hardly investigate the dynamics of the events since their detection are made a posteriori. To increase our knowledge of the landscape evolution and the influence of extreme climatic events on a catchment dynamics, we need to develop new tools and procedures. In many past works, it has been shown that seismic signals are relevant to detect and locate surface processes (landslides, debris flows). During the 2010 typhoon season, we deployed a network of 12 seismometers dedicated to monitor the surface processes of the Chenyoulan catchment in Taiwan. We test the ability of a two dimensional array and small inter-stations distances (~ 11 km) to map in continuous and at a catchment-scale the geomorphic activity. The spectral analysis of continuous records shows a high-frequency (> 1 Hz) seismic energy that is coherent with the occurrence of hillslope and river processes. Using a basic detection algorithm and a location approach running on the analysis of seismic amplitudes, we manage to locate the catchment activity. We mainly observe short-time events (> 300 occurrences) associated with debris falls and bank collapses during daily convective storms, where 69% of occurrences are coherent with the time distribution of precipitations. We also identify a couple of debris flows during a large tropical storm. In contrast, the FORMOSAT imagery does not detect any activity, which somehow reflects the lack of extreme climatic conditions during the experiment. However, high resolution pictures confirm the existence of links between most of geomorphic events and existing structures (landslide scars, gullies...). We thus conclude to an activity that is dominated by reactivation processes. It
Estimating 3D movements from 2D observations using a continuous model of helical swimming.
Gurarie, Eliezer; Grünbaum, Daniel; Nishizaki, Michael T
2011-06-01
Helical swimming is among the most common movement behaviors in a wide range of microorganisms, and these movements have direct impacts on distributions, aggregations, encounter rates with prey, and many other fundamental ecological processes. Microscopy and video technology enable the automated acquisition of large amounts of tracking data; however, these data are typically two-dimensional. The difficulty of quantifying the third movement component complicates understanding of the biomechanical causes and ecological consequences of helical swimming. We present a versatile continuous stochastic model-the correlated velocity helical movement (CVHM) model-that characterizes helical swimming with intrinsic randomness and autocorrelation. The model separates an organism's instantaneous velocity into a slowly varying advective component and a perpendicularly oriented rotation, with velocities, magnitude of stochasticity, and autocorrelation scales defined for both components. All but one of the parameters of the 3D model can be estimated directly from a two-dimensional projection of helical movement with no numerical fitting, making it computationally very efficient. As a case study, we estimate swimming parameters from videotaped trajectories of a toxic unicellular alga, Heterosigma akashiwo (Raphidophyceae). The algae were reared from five strains originally collected from locations in the Atlantic and Pacific Oceans, where they have caused Harmful Algal Blooms (HABs). We use the CVHM model to quantify cell-level and strain-level differences in all movement parameters, demonstrating the utility of the model for identifying strains that are difficult to distinguish by other means. PMID:20725795
2005-07-01
Aniso2d is a two-dimensional seismic forward modeling code. The earth is parameterized by an X-Z plane in which the seismic properties Can have monoclinic with x-z plane symmetry. The program uses a user define time-domain wavelet to produce synthetic seismograms anrwhere within the two-dimensional media.
NASA Astrophysics Data System (ADS)
Li, Yuanyuan; Braitenberg, Carla; Yang, Yushan
2013-03-01
A slightly bended gravity high along the Chad lineament in Central North Africa is analyzed and interpreted by the continuous wavelet transform (CWT) method. We use scale normalization on the continuous wavelet transform, allowing analysis of the gravity field in order to determine the sources at different depths. By focusing on homogenous standard sources, such as sphere or cube, horizontal cylinder or prism, sheet and infinite step, we derive the relationships between the source depth and pseudo-wavenumber. Then the source depth can be recovered from tracing the maximal values of the modulus of the complex wavelet coefficients in the CWT-based scalograms that are function of the pseudo-wavenumber. The studied area includes a central gravity high up to 75 km wide, and a secondary high that occurs at the southern part of the anomaly. The interpretation of the depth slices and vertical sections of the modulus maxima of the complex wavelet coefficients allows recognition of a relatively dense terrane located at middle crustal levels (10-25 km depth). A reasonable geological model derived from the 2.5D gravity forward modelling indicates the presence of high density bodies, probably linked to a buried suture, which were thrusted up into the mid-crust during the Neo-Proterozoic terrane collisions between the Saharan metacraton and the Arabian-Nubian shield. We conclude that the Chad line delineates a first order geological boundary, missing on the geologic maps.
NASA Astrophysics Data System (ADS)
Cheng, Tao; Rivard, Benoit; Sánchez-Azofeifa, Arturo G.; Féret, Jean-Baptiste; Jacquemoud, Stéphane; Ustin, Susan L.
2014-01-01
Leaf mass per area (LMA), the ratio of leaf dry mass to leaf area, is a trait of central importance to the understanding of plant light capture and carbon gain. It can be estimated from leaf reflectance spectroscopy in the infrared region, by making use of information about the absorption features of dry matter. This study reports on the application of continuous wavelet analysis (CWA) to the estimation of LMA across a wide range of plant species. We compiled a large database of leaf reflectance spectra acquired within the framework of three independent measurement campaigns (ANGERS, LOPEX and PANAMA) and generated a simulated database using the PROSPECT leaf optical properties model. CWA was applied to the measured and simulated databases to extract wavelet features that correlate with LMA. These features were assessed in terms of predictive capability and robustness while transferring predictive models from the simulated database to the measured database. The assessment was also conducted with two existing spectral indices, namely the Normalized Dry Matter Index (NDMI) and the Normalized Difference index for LMA (NDLMA). Five common wavelet features were determined from the two databases, which showed significant correlations with LMA (R2: 0.51-0.82, p < 0.0001). The best robustness (R2 = 0.74, RMSE = 18.97 g/m2 and Bias = 0.12 g/m2) was obtained using a combination of two low-scale features (1639 nm, scale 4) and (2133 nm, scale 5), the first being predominantly important. The transferability of the wavelet-based predictive model to the whole measured database was either better than or comparable to those based on spectral indices. Additionally, only the wavelet-based model showed consistent predictive capabilities among the three measured data sets. In comparison, the models based on spectral indices were sensitive to site-specific data sets. Integrating the NDLMA spectral index and the two robust wavelet features improved the LMA prediction. One of the bands
Hamaneh, Mehdi Bagheri; Chitravas, Numthip; Kaiboriboon, Kitti; Lhatoo, Samden D; Loparo, Kenneth A
2014-06-01
The electrical potential produced by the cardiac activity sometimes contaminates electroencephalogram (EEG) recordings, resulting in spiky activities that are referred to as electrocardiographic (EKG) artifact. For a variety of reasons it is often desirable to automatically detect and remove these artifacts. Especially, for accurate source localization of epileptic spikes in an EEG recording from a patient with epilepsy, it is of great importance to remove any concurrent artifact. Due to similarities in morphology between the EKG artifacts and epileptic spikes, any automated artifact removal algorithm must have an extremely low false-positive rate in addition to a high detection rate. In this paper, an automated algorithm for removal of EKG artifact is proposed that satisfies such criteria. The proposed method, which uses combines independent component analysis and continuous wavelet transformation, uses both temporal and spatial characteristics of EKG related potentials to identify and remove the artifacts. The method outperforms algorithms that use general statistical features such as entropy and kurtosis for artifact rejection.
Adamczyk, Marek; Genzel, Lisa; Dresler, Martin; Steiger, Axel; Friess, Elisabeth
2015-01-01
Mounting evidence for the role of sleep spindles in neuroplasticity has led to an increased interest in these non-rapid eye movement (NREM) sleep oscillations. It has been hypothesized that fast and slow spindles might play a different role in memory processing. Here, we present a new sleep spindle detection algorithm utilizing a continuous wavelet transform (CWT) and individual adjustment of slow and fast spindle frequency ranges. Eighteen nap recordings of ten subjects were used for algorithm validation. Our method was compared with both a human scorer and a commercially available SIESTA spindle detector. For the validation set, mean agreement between our detector and human scorer measured during sleep stage 2 using kappa coefficient was 0.45, whereas mean agreement between our detector and SIESTA algorithm was 0.62. Our algorithm was also applied to sleep-related memory consolidation data previously analyzed with a SIESTA detector and confirmed previous findings of significant correlation between spindle density and declarative memory consolidation. We then applied our method to a study in monozygotic (MZ) and dizygotic (DZ) twins, examining the genetic component of slow and fast sleep spindle parameters. Our analysis revealed strong genetic influence on variance of all slow spindle parameters, weaker genetic effect on fast spindles, and no effects on fast spindle density and number during stage 2 sleep. PMID:26635577
Phase characteristic analysis of continuous depth air-gun source wavelet
NASA Astrophysics Data System (ADS)
Xing, Lei; Liu, Huaishan; Zheng, Xilai; Liu, Xueqin; Zhang, Jin; Wang, Linfei; Zou, Zhihui; Xu, Yiming
2016-10-01
Air guns are important sources for marine seismic exploration. Far-field wavelet of air gun arrays, as a necessary parameter for pre-stack processing and source models, plays an important role during marine seismic data processing and interpretation. When an air gun fires, it generates a series of air bubbles. Similar to onshore seismic exploration, the water forms a plastic fluid near the bubble; the farther the air gun is located from the measurement, the more steady and more accurately represented the wavelet will be. In practice, hydrophones should be placed more than 100 m from the air gun; however, traditional seismic cables cannot meet this requirement. On the other hand, vertical cables provide a viable solution to this problem. This study uses a vertical cable to receive wavelets from 38 air guns and data are collected offshore Southeast Qiong, where the water depth is over 1000 m. In this study, the wavelets measured using this technique coincide very well with the simulated wavelets and can therefore represent the real shape of the wavelets. This experiment fills a technology gap in China.
Paul, Sabyasachi; Rao, D D; Sarkar, P K
2012-11-01
Measurement of environmental dose in the vicinity of a nuclear power plant site (Tarapur, India) is carried out continuously for the years 2007-2010 and attempts have been made to quantify the additional contributions from nuclear power plants over natural background by segregating the background fluctuations from the events due to plume passage using a non-decimated wavelet approach. A conservative estimate obtained using wavelet based analysis has shown a maximum annual dose of 38 μSv in a year at 1.6 km and 4.8 μSv at 10 km from the installation. The detected events within a year are in good agreement with the month wise wind-rose profile indicating reliability of the algorithm for proper detection of an event from the continuous dose rate measurements. The results were validated with the dispersion model dose predictions using the source term from routine monitoring data and meteorological parameters.
NASA Astrophysics Data System (ADS)
Fefferman, C. L.; Lee-Thorp, J. P.; Weinstein, M. I.
2016-03-01
Edge states are time-harmonic solutions to energy-conserving wave equations, which are propagating parallel to a line-defect or ‘edge’ and are localized transverse to it. This paper summarizes and extends the authors’ work on the bifurcation of topologically protected edge states in continuous two-dimensional (2D) honeycomb structures. We consider a family of Schrödinger Hamiltonians consisting of a bulk honeycomb potential and a perturbing edge potential. The edge potential interpolates between two different periodic structures via a domain wall. We begin by reviewing our recent bifurcation theory of edge states for continuous 2D honeycomb structures (http://arxiv.org/abs/1506.06111). The topologically protected edge state bifurcation is seeded by the zero-energy eigenstate of a one-dimensional Dirac operator. We contrast these protected bifurcations with (more common) non-protected bifurcations from spectral band edges, which are induced by bound states of an effective Schrödinger operator. Numerical simulations for honeycomb structures of varying contrasts and ‘rational edges’ (zigzag, armchair and others), support the following scenario: (a) for low contrast, under a sign condition on a distinguished Fourier coefficient of the bulk honeycomb potential, there exist topologically protected edge states localized transverse to zigzag edges. Otherwise, and for general edges, we expect long lived edge quasi-modes which slowly leak energy into the bulk. (b) For an arbitrary rational edge, there is a threshold in the medium-contrast (depending on the choice of edge) above which there exist topologically protected edge states. In the special case of the armchair edge, there are two families of protected edge states; for each parallel quasimomentum (the quantum number associated with translation invariance) there are edge states which propagate in opposite directions along the armchair edge.
NASA Astrophysics Data System (ADS)
Gallego, A.; Moreno-García, P.; Casanova, Cesar F.
2013-06-01
Structural studies to find defects (in particular delaminations) in composite plates have been very prevalent in the Structural Health Monitoring field. The present work develops a new method to detect delaminations in CFRP (Carbon Fiber Reinforced Polymer) plates. In this paper the method is validated with numerical simulations, which come to support its adequacy for use with real acquisition data. This is done firstly through the implementation of a delaminated plate finite element. Using the classical lamination plate theory, delamination is considered in the kinematic equations through jump functions and additional degrees of freedom. The element allows the introduction of nd delaminations through its thickness. Classical QMITC (Quadrilateral Mixed Interpolation Tensorial Components) and DKQ (Discrete Kirchhoff Quadrilateral) elements are used for the membrane and bending FEM (Finite Element Method) formulation. Second, using the vibration modes obtained with the FEM, a damage location technique based on the variational Ritz method and Wavelet Analysis is proposed. The approach has the advantage of requiring only damaged modes and not the healthy ones. Both FEM simulations and Ritz/Wavelet damage detection schemes are applied in an orthotropic CFRP plate with the stacking sequence [0/90]3S. In addition, the influence of delamination thickness position, boundary conditions and added noise (in order to simulate experimental measures) was studied.
Adaptive Multilinear Tensor Product Wavelets.
Weiss, Kenneth; Lindstrom, Peter
2016-01-01
Many foundational visualization techniques including isosurfacing, direct volume rendering and texture mapping rely on piecewise multilinear interpolation over the cells of a mesh. However, there has not been much focus within the visualization community on techniques that efficiently generate and encode globally continuous functions defined by the union of multilinear cells. Wavelets provide a rich context for analyzing and processing complicated datasets. In this paper, we exploit adaptive regular refinement as a means of representing and evaluating functions described by a subset of their nonzero wavelet coefficients. We analyze the dependencies involved in the wavelet transform and describe how to generate and represent the coarsest adaptive mesh with nodal function values such that the inverse wavelet transform is exactly reproduced via simple interpolation (subdivision) over the mesh elements. This allows for an adaptive, sparse representation of the function with on-demand evaluation at any point in the domain. We focus on the popular wavelets formed by tensor products of linear B-splines, resulting in an adaptive, nonconforming but crack-free quadtree (2D) or octree (3D) mesh that allows reproducing globally continuous functions via multilinear interpolation over its cells.
Dinç, Erdal; Ragno, Gaetano; Ioele, Giuseppina; Baleanu, Dumitru
2006-01-01
Fractional wavelet transform (FWT) was applied to the original absorption spectra of lacidipine (LAC) and its photodegradation product (LACD), and the resulting FWT spectra were processed by continuous wavelet transform (CWT) and multilinear regression calibration (MLRC) for the simultaneous quantitative analysis of both products in their binary mixtures. These methods do not require any chemical separation step and chemical complex reaction to obtain a detectable signal for the degradation product. By using the Mexican hat function, 2 calibration functions for LAC and LACD were obtained by measuring the CWT transformed signals at 416.1 nm for LAC and 414.6 nm for LACD, after FWT processing of the original absorption spectra. The calibration graphs were linear in the concentration range of 5.08-40.64 microg/mL for LAC and 0.51-8.16 microg/mL for LACD. The limit of detection and the limit of quantitation were found to be 0.289 and 0.956 microg/mL for LAC and 0.036 and 0.118 microg/mL for LACD, respectively. For comparison, the MLRC algorithm was applied to the linear regression functions for the individual drug and its photoproduct. In this approach, a set of linear regression functions was obtained from the relationship between concentrations and FWT signals in the wavelength range 411.0-412.4 nm. Both methods were applied to the quantitative evaluation of LAC and LACD in laboratory and pharmaceutical samples, and produced very satisfactory results.
Hu, Ying; Mo, Wenqin; Dong, Kaifeng; Jin, Fang; Song, Junlei
2016-06-10
The maximum spectrum of the continuous wavelet transform (MSCWT) is proposed to demodulate the central wavelengths for the overlapped spectrum in a serial fiber Bragg grating (FBG) sensing system. We describe the operation principle of the MSCWT method. Moreover, the influence of the interval gap between two FBG wavelengths, 3 dB bandwidths, and optical powers of the reflected spectra are discussed. The simulation and experimental results indicate that the MSCWT can resolve an overlapped spectrum and decode the central wavelength with high accuracy. More importantly, the proposed peak detection method can enhance the sensing capacity of a wavelength division multiplexing FBG sensor network. PMID:27409024
Elzanfaly, Eman S; Hassan, Said A; Salem, Maissa Y; El-Zeany, Badr A
2015-12-01
A comparative study was established between two signal processing techniques showing the theoretical algorithm for each method and making a comparison between them to indicate the advantages and limitations. The methods under study are Numerical Differentiation (ND) and Continuous Wavelet Transform (CWT). These methods were studied as spectrophotometric resolution tools for simultaneous analysis of binary and ternary mixtures. To present the comparison, the two methods were applied for the resolution of Bisoprolol (BIS) and Hydrochlorothiazide (HCT) in their binary mixture and for the analysis of Amlodipine (AML), Aliskiren (ALI) and Hydrochlorothiazide (HCT) as an example for ternary mixtures. By comparing the results in laboratory prepared mixtures, it was proven that CWT technique is more efficient and advantageous in analysis of mixtures with severe overlapped spectra than ND. The CWT was applied for quantitative determination of the drugs in their pharmaceutical formulations and validated according to the ICH guidelines where accuracy, precision, repeatability and robustness were found to be within the acceptable limit.
Komorowski, Dariusz; Pietraszek, Stanislaw
2016-01-01
This paper presents the analysis of multi-channel electrogastrographic (EGG) signals using the continuous wavelet transform based on the fast Fourier transform (CWTFT). The EGG analysis was based on the determination of the several signal parameters such as dominant frequency (DF), dominant power (DP) and index of normogastria (NI). The use of continuous wavelet transform (CWT) allows for better visible localization of the frequency components in the analyzed signals, than commonly used short-time Fourier transform (STFT). Such an analysis is possible by means of a variable width window, which corresponds to the scale time of observation (analysis). Wavelet analysis allows using long time windows when we need more precise low-frequency information, and shorter when we need high frequency information. Since the classic CWT transform requires considerable computing power and time, especially while applying it to the analysis of long signals, the authors used the CWT analysis based on the fast Fourier transform (FFT). The CWT was obtained using properties of the circular convolution to improve the speed of calculation. This method allows to obtain results for relatively long records of EGG in a fairly short time, much faster than using the classical methods based on running spectrum analysis (RSA). In this study authors indicate the possibility of a parametric analysis of EGG signals using continuous wavelet transform which is the completely new solution. The results obtained with the described method are shown in the example of an analysis of four-channel EGG recordings, performed for a non-caloric meal.
NASA Astrophysics Data System (ADS)
Gdeisat, Munther A.; Abid, Abdulbasit; Burton, David R.; Lalor, Michael J.; Lilley, Francis; Moore, Chris; Qudeisat, Mohammed
2009-12-01
This paper presents a thorough discussion on the application of the one-dimensional continuous wavelet transform (1D-CWT) in order to retrieve phase information in temporally and spatially tilted fringe patterns and highlights recent progress and challenges. The paper also suggests some possible future developments for this method. The advantages and drawbacks of the one-dimensional continuous wavelet transform technique are discussed here and in this context are compared to the widely used methods of Fourier fringe analysis, phase stepping and the windowed Fourier transform. A description is given of the manner in which the CWT phase gradient and phase estimation methods may be used to extract the phase of fringe patterns, and these two methods are compared and contrasted. Five different ridge extraction algorithms are explained and the performance of three of these is evaluated. To alleviate the distortions that may occur at the image borders and at regions close to holes in fringe patterns, two methods are described and evaluated for extending the image edges and for filling in holes within fringe patterns. A novel mother wavelet is presented which has been designed to improve the ability of the continuous wavelet transform to analyse fringe patterns that contain sudden phase variations. The sampling and structural conditions that are required to obtain 'correct' phase are also discussed.
NASA Astrophysics Data System (ADS)
Qiu, Bingwen; Feng, Min; Tang, Zhenghong
2016-05-01
This study proposed a simple Smoother without any local adjustments based on Continuous Wavelet Transform (SCWT). And then it evaluated its performance together with other commonly applied techniques in phenological estimation. These noise reduction methods included Savitzky-Golay filter (SG), Double Logistic function (DL), Asymmetric Gaussian function (AG), Whittaker Smoother (WS) and Harmonic Analysis of Time-Series (HANTS). They were evaluated based on fidelity and smoothness, and their efficiencies in deriving phenological parameters through the inflexion point-based method with the 8-day composite Moderate Resolution Imaging Spectroradiometer (MODIS) 2-band Enhanced Vegetation Index (EVI2) in 2013 in China. The following conclusions were drawn: (1) The SG method exhibited strong fidelity, but weak smoothness and spatial continuity. (2) The HANTS method had very robust smoothness but weak fidelity. (3) The AG and DL methods performed weakly for vegetation with more than one growth cycle (i.e., multiple crops). (4) The WS and SCWT smoothers outperformed others with combined considerations of fidelity and smoothness, and consistent phenological patterns (correlation coefficients greater than 0.8 except evergreen broadleaf forests (0.68)). (5) Compared with WS methods, the SCWT smoother was capable in preservation of real local minima and maxima with fewer inflexions. (6) Large discrepancy was examined from the estimated phenological dates with SG and HANTS methods, particularly in evergreen forests and multiple cropping regions (the absolute mean deviation rates were 6.2-17.5 days and correlation coefficients less than 0.34 for estimated start dates).
Wavelet Analyses and Applications
ERIC Educational Resources Information Center
Bordeianu, Cristian C.; Landau, Rubin H.; Paez, Manuel J.
2009-01-01
It is shown how a modern extension of Fourier analysis known as wavelet analysis is applied to signals containing multiscale information. First, a continuous wavelet transform is used to analyse the spectrum of a nonstationary signal (one whose form changes in time). The spectral analysis of such a signal gives the strength of the signal in each…
NASA Astrophysics Data System (ADS)
Esposito, Angelo; Russo, Luigi; Kändler, Christoph; Pianese, Cesare; Ludwig, Bastian; Steiner, Nadia Yousfi
2016-06-01
The on-line diagnostics of Solid Oxide Fuel Cells (SOFCs) is a critical tool to achieve optimal performance and extend the lifetime. The Continuous Wavelet Transform (CWT) methodology was applied to the SOFC voltage signal to detect signatures that reveal the presence of a fault in the cell/stack. The selected fault was anode re-oxidation caused by high Fuel Utilization (FU) (higher then nominal). To experimentally emulate the high FU faults, a standard test procedure was developed, which was used to characterize a μ-CHP system at high FU operation. To complete the analysis, data collected on Single Cells were exploited too. The CWT was applied to the voltage signal for each FU level to verify the qualitative difference (signature) between the signals at different FU's within the same tests as well as the correspondence between the same conditions over different tests. A statistical study was performed to quantify the observed differences and to determine the correspondence between CWT coefficients and operating conditions. The approach proves to be suitable to diagnose high FU in SOFC, showing a successful detection rate above 76%. The results show the good potential of using the CWT methodology as diagnostic tools for SOFCs from cell to stack level.
NASA Astrophysics Data System (ADS)
Sánchez-Úbeda, Juan Pedro; Calvache, María Luisa; Duque, Carlos; López-Chicano, Manuel
2016-11-01
A new methodology has been developed to obtain tidal-filtered time series of groundwater levels in coastal aquifers. Two methods used for oceanography processing and forecasting of sea level data were adapted for this purpose and compared: HA (Harmonic Analysis) and CWT (Continuous Wavelet Transform). The filtering process is generally comprised of two main steps: the detection and fitting of the major tide constituents through the decomposition of the original signal and the subsequent extraction of the complete tidal oscillations. The abilities of the optional HA and CWT methods to decompose and extract the tidal oscillations were assessed by applying them to the data from two piezometers at different depths close to the shoreline of a Mediterranean coastal aquifer (Motril-Salobreña, SE Spain). These methods were applied to three time series of different lengths (one month, one year, and 3.7 years of hourly data) to determine the range of detected frequencies. The different lengths of time series were also used to determine the fit accuracies of the tidal constituents for both the sea level and groundwater heads measurements. The detected tidal constituents were better resolved with increasing depth in the aquifer. The application of these methods yielded a detailed resolution of the tidal components, which enabled the extraction of the major tidal constituents of the sea level measurements from the groundwater heads (e.g., semi-diurnal, diurnal, fortnightly, monthly, semi-annual and annual). In the two wells studied, the CWT method was shown to be a more effective method than HA for extracting the tidal constituents of highest and lowest frequencies from groundwater head measurements.
Tsanas, Athanasios; Clifford, Gari D
2015-01-01
Sleep spindles are critical in characterizing sleep and have been associated with cognitive function and pathophysiological assessment. Typically, their detection relies on the subjective and time-consuming visual examination of electroencephalogram (EEG) signal(s) by experts, and has led to large inter-rater variability as a result of poor definition of sleep spindle characteristics. Hitherto, many algorithmic spindle detectors inherently make signal stationarity assumptions (e.g., Fourier transform-based approaches) which are inappropriate for EEG signals, and frequently rely on additional information which may not be readily available in many practical settings (e.g., more than one EEG channels, or prior hypnogram assessment). This study proposes a novel signal processing methodology relying solely on a single EEG channel, and provides objective, accurate means toward probabilistically assessing the presence of sleep spindles in EEG signals. We use the intuitively appealing continuous wavelet transform (CWT) with a Morlet basis function, identifying regions of interest where the power of the CWT coefficients corresponding to the frequencies of spindles (11-16 Hz) is large. The potential for assessing the signal segment as a spindle is refined using local weighted smoothing techniques. We evaluate our findings on two databases: the MASS database comprising 19 healthy controls and the DREAMS sleep spindle database comprising eight participants diagnosed with various sleep pathologies. We demonstrate that we can replicate the experts' sleep spindles assessment accurately in both databases (MASS database: sensitivity: 84%, specificity: 90%, false discovery rate 83%, DREAMS database: sensitivity: 76%, specificity: 92%, false discovery rate: 67%), outperforming six competing automatic sleep spindle detection algorithms in terms of correctly replicating the experts' assessment of detected spindles. PMID:25926784
Tsanas, Athanasios; Clifford, Gari D.
2015-01-01
Sleep spindles are critical in characterizing sleep and have been associated with cognitive function and pathophysiological assessment. Typically, their detection relies on the subjective and time-consuming visual examination of electroencephalogram (EEG) signal(s) by experts, and has led to large inter-rater variability as a result of poor definition of sleep spindle characteristics. Hitherto, many algorithmic spindle detectors inherently make signal stationarity assumptions (e.g., Fourier transform-based approaches) which are inappropriate for EEG signals, and frequently rely on additional information which may not be readily available in many practical settings (e.g., more than one EEG channels, or prior hypnogram assessment). This study proposes a novel signal processing methodology relying solely on a single EEG channel, and provides objective, accurate means toward probabilistically assessing the presence of sleep spindles in EEG signals. We use the intuitively appealing continuous wavelet transform (CWT) with a Morlet basis function, identifying regions of interest where the power of the CWT coefficients corresponding to the frequencies of spindles (11–16 Hz) is large. The potential for assessing the signal segment as a spindle is refined using local weighted smoothing techniques. We evaluate our findings on two databases: the MASS database comprising 19 healthy controls and the DREAMS sleep spindle database comprising eight participants diagnosed with various sleep pathologies. We demonstrate that we can replicate the experts' sleep spindles assessment accurately in both databases (MASS database: sensitivity: 84%, specificity: 90%, false discovery rate 83%, DREAMS database: sensitivity: 76%, specificity: 92%, false discovery rate: 67%), outperforming six competing automatic sleep spindle detection algorithms in terms of correctly replicating the experts' assessment of detected spindles. PMID:25926784
NASA Astrophysics Data System (ADS)
Balafas, Konstantinos; Kiremidjian, Anne S.
2014-03-01
This paper proposes a series of novel Damage Sensitive Features for earthquake damage estimation. The features take into account input (ground motion) and output acceleration (structure response) measurements. The Continuous Wavelet Transform is applied to both acceleration signals in order to obtain both time domain and frequency domain resolution. An algorithm that has been proposed for Maximum Entropy Deconvolution is applied to the Continuous Wavelet Transforms in order to obtain a matrix that relates the output wavelet coefficients to the input ones. The Damage Sensitive Features are then derived through statistical processing of the resulting matrix. This algorithm has been applied on data acquired from shake table tests where the structures were subjected to progressive damage. The proposed features are compared to response quantities that are indicative of damage (such as the hysteretic energy dissipated) and show high correlation with the extent of damage. The data utilized has not been pre-processed, illustrating the robustness of the algorithm against sensor noise. The proposed algorithm has several advantages: Minimal input and knowledge of the structure is required. More information on the structure's state is extracted through use of both the input and output signals than when only output signal is considered. Only two acceleration measurements are required to obtain a damage forecast utilizing primarily the strong motion recordings, resulting in easier sensor deployment. The use of strong motion recordings allows for information delivery immediately after an earthquake without additional data collection.
NASA Astrophysics Data System (ADS)
Sohrabi, Mahmoud Reza; Darabi, Golnaz
2016-01-01
Flavonoids are γ-benzopyrone derivatives, which are highly regarded in these researchers for their antioxidant property. In this study, two new signals processing methods been coupled with UV spectroscopy for spectral resolution and simultaneous quantitative determination of Myricetin, Kaempferol and Quercetin as flavonoids in Laurel, St. John's Wort and Green Tea without the need for any previous separation procedure. The developed methods are continuous wavelet transform (CWT) and least squares support vector machine (LS-SVM) methods integrated with UV spectroscopy individually. Different wavelet families were tested by CWT method and finally the Daubechies wavelet family (Db4) for Myricetin and the Gaussian wavelet families for Kaempferol (Gaus3) and Quercetin (Gaus7) were selected and applied for simultaneous analysis under the optimal conditions. The LS-SVM was applied to build the flavonoids prediction model based on absorption spectra. The root mean square errors for prediction (RMSEP) of Myricetin, Kaempferol and Quercetin were 0.0552, 0.0275 and 0.0374, respectively. The developed methods were validated by the analysis of the various synthetic mixtures associated with a well- known flavonoid contents. Mean recovery values of Myricetin, Kaempferol and Quercetin, in CWT method were 100.123, 100.253, 100.439 and in LS-SVM method were 99.94, 99.81 and 99.682, respectively. The results achieved by analyzing the real samples from the CWT and LS-SVM methods were compared to the HPLC reference method and the results were very close to the reference method. Meanwhile, the obtained results of the one-way ANOVA (analysis of variance) test revealed that there was no significant difference between the suggested methods.
Hidalgo, D; Sacco, A; Hernández, S; Tommasi, T
2015-11-01
A mixed microbial population naturally presents in seawater was used as active anodic biofilm of two Microbial Fuel Cells (MFCs), employing either a 2D commercial carbon felt or 3D carbon-coated Berl saddles as anode electrodes, with the aim to compare their electrochemical behavior under continuous operation. After an initial increase of the maximum power density, the felt-based cell reduced its performance at 5 months (from 7 to 4 μW cm(-2)), while the saddle-based MFC exceeds 9 μW cm(-2) (after 2 months) and maintained such performance for all the tests. Electrochemical impedance spectroscopy was used to identify the MFCs controlling losses and indicates that the mass-transport limitations at the biofilm-electrolyte interface have the main contribution (>95%) to their internal resistance. The activation resistance was one order of magnitude lower with the Berl saddles than with carbon felt, suggesting an enhanced charge-transfer in the high surface-area 3D electrode, due to an increase in bacteria population growth.
Hidalgo, D; Sacco, A; Hernández, S; Tommasi, T
2015-11-01
A mixed microbial population naturally presents in seawater was used as active anodic biofilm of two Microbial Fuel Cells (MFCs), employing either a 2D commercial carbon felt or 3D carbon-coated Berl saddles as anode electrodes, with the aim to compare their electrochemical behavior under continuous operation. After an initial increase of the maximum power density, the felt-based cell reduced its performance at 5 months (from 7 to 4 μW cm(-2)), while the saddle-based MFC exceeds 9 μW cm(-2) (after 2 months) and maintained such performance for all the tests. Electrochemical impedance spectroscopy was used to identify the MFCs controlling losses and indicates that the mass-transport limitations at the biofilm-electrolyte interface have the main contribution (>95%) to their internal resistance. The activation resistance was one order of magnitude lower with the Berl saddles than with carbon felt, suggesting an enhanced charge-transfer in the high surface-area 3D electrode, due to an increase in bacteria population growth. PMID:26166463
NASA Astrophysics Data System (ADS)
Ahmad, Mirza Naseer; Rowell, Philip; Sriburee, Suchada
2014-06-01
Fluvial sands host excellent oil and gas reservoirs in various fields throughout the world. However, the lateral heterogeneity of reservoir properties within these reservoirs can be significant and determining the distribution of good reservoirs is a challenge. This study attempts to predict sand distribution within fluvial depositional systems by applying the Continuous Wavelet Transformation technique of spectral decomposition along with full spectrum seismic attributes, to a 3D seismic data set in the Pattani Basin, Gulf of Thailand. Full spectrum seismic attributes such as root mean square and coherency help to effectively map fluvial systems down to certain depth below which imaging is difficult in the intervals of interest in this study. However, continuous wavelet transform used in conjunction with other attributes by applying visualization techniques of transparency and RGB can be used at greater depths to extract from 3D seismic data useful information of fluvial depositional elements. This workflow may help to identify different reservoir compartments within the fluvial systems of the Gulf of Thailand.
Abbasi Tarighat, Maryam
2016-02-01
Simultaneous spectrophotometric determination of a mixture of overlapped complexes of Fe(3+), Mn(2+), Cu(2+), and Zn(2+) ions with 2-(3-hydroxy-1-phenyl-but-2-enylideneamino) pyridine-3-ol(HPEP) by orthogonal projection approach-feed forward neural network (OPA-FFNN) and continuous wavelet transform-feed forward neural network (CWT-FFNN) is discussed. Ionic complexes HPEP were formulated with varying reagent concentration, pH and time of color formation for completion of complexation reactions. It was found that, at 5.0 × 10(-4) mol L(-1) of HPEP, pH 9.5 and 10 min after mixing the complexation reactions were completed. The spectral data were analyzed using partial response plots, and identified non-linearity modeled using FFNN. Reducing the number of OPA-FFNN and CWT-FFNN inputs were simplified using dissimilarity pure spectra of OPA and selected wavelet coefficients. Once the pure dissimilarity plots ad optimal wavelet coefficients are selected, different ANN models were employed for the calculation of the final calibration models. The performance of these two approaches were tested with regard to root mean square errors of prediction (RMSE %) values, using synthetic solutions. Under the working conditions, the proposed methods were successfully applied to the simultaneous determination of metal ions in different vegetable and foodstuff samples. The results show that, OPA-FFNN and CWT-FFNN were effective in simultaneously determining Fe(3+), Mn(2+), Cu(2+), and Zn(2+) concentration. Also, concentrations of metal ions in the samples were determined by flame atomic absorption spectrometry (FAAS). The amounts of metal ions obtained by the proposed methods were in good agreement with those obtained by FAAS. PMID:26304383
Barbosa, Eduardo; García-Manso, Juan M; Martín-González, Juan M; Sarmiento, Samuel; Calderón, Francisco J; Da Silva-Grigoletto, Marzo E
2010-01-01
This study sought to determine the effects of hyperbaric pressure on heart rate modulation, by analyzing potential changes in heart rate variability (HRV). Ten divers were exposed to pressures of 1, 2, 3, and 4 atmospheres absolute (ATA). The test was performed in a hyperbaric chamber. Heart rate (HR) was recorded in supine subjects for 10 minutes per atmosphere. HRV was analyzed in the frequency mode (fast-Fourier transform and continuous wavelet transform). Results confirmed bradycardia as pressure increased. The drop in HR attained statistical significance after 2, 3, and 4 ATA. Signal energy (normalized TP values) rose progressively, becoming significant at 2 ATA. High frequency and low frequency displayed similar behavior in both cases. Although frequency band peaks did not yield clear results, continuous wave transform analysis showed that the frequency spectrum tended to shift into the high-frequency range as pressure increased. In summary, increased pressure prompted increased bradycardia, and HRV shifted into high-frequency range.
Tryptic digests of human serum albumin (HSA) and human lung epithelial cell lysates were used as test samples in a novel proteomics study. Peptides were separated and analyzed using 2D-nano-LC/MSMS with strong cation exchange (SCX) and reverse phase (RP) chromatography and contin...
NASA Astrophysics Data System (ADS)
Karacan, C. Özgen; Olea, Ricardo A.
2014-06-01
Prediction of potential methane emission pathways from various sources into active mine workings or sealed gobs from longwall overburden is important for controlling methane and for improving mining safety. The aim of this paper is to infer strata separation intervals and thus gas emission pathways from standard well log data. The proposed technique was applied to well logs acquired through the Mary Lee/Blue Creek coal seam of the Upper Pottsville Formation in the Black Warrior Basin, Alabama, using well logs from a series of boreholes aligned along a nearly linear profile. For this purpose, continuous wavelet transform (CWT) of digitized gamma well logs was performed by using Mexican hat and Morlet, as the mother wavelets, to identify potential discontinuities in the signal. Pointwise Hölder exponents (PHE) of gamma logs were also computed using the generalized quadratic variations (GQV) method to identify the location and strength of singularities of well log signals as a complementary analysis. PHEs and wavelet coefficients were analyzed to find the locations of singularities along the logs. Using the well logs in this study, locations of predicted singularities were used as indicators in single normal equation simulation (SNESIM) to generate equi-probable realizations of potential strata separation intervals. Horizontal and vertical variograms of realizations were then analyzed and compared with those of indicator data and training image (TI) data using the Kruskal-Wallis test. A sum of squared differences was employed to select the most probable realization representing the locations of potential strata separations and methane flow paths. Results indicated that singularities located in well log signals reliably correlated with strata transitions or discontinuities within the strata. Geostatistical simulation of these discontinuities provided information about the location and extents of the continuous channels that may form during mining. If there is a gas
NASA Astrophysics Data System (ADS)
Conde, Vladimir; Bredemeyer, Stefan; Saballos, J. Armando; Galle, Bo; Hansteen, Thor H.
2016-07-01
San Cristóbal volcano is the highest and one of the most active volcanoes in Nicaragua. Its persistently high activity during the past decade is characterized by strong degassing and almost annual VEI 1-2 explosions, which present a threat to the local communities. Following an eruption on 8 September 2012, the intervals between eruptions decreased significantly, which we interpret as the start of a new eruptive phase. We present here the results of semi-continuous SO2 flux measurements covering a period of 18 months, obtained by two scanning UV-DOAS instruments installed as a part of the network for observation of volcanic and atmospheric change project, and the results of real-time seismic amplitude measurements (RSAM) data. Our data comprise a series of small to moderately explosive events in December 2012, June 2013 and February 2014, which were accompanied by increased gas emissions and seismicity. In order to approach an early warning strategy, we present a statistical method for the joint analysis of gas flux and seismic data, by using continuous wavelet transform and cross-wavelet transform (XWT) methods. This analysis shows that the XWT coefficients of SO2 flux and RSAM are in good agreement with the occurrence of eruptive events and thus may be used to indicate magma ascent into the volcano edifice. Such multi-parameter surveillance efforts can be useful for the interpretation and surveillance of possible eruptive events and could thus be used by local institutions for the prediction of upcoming volcanic unrest.
A Mellin transform approach to wavelet analysis
NASA Astrophysics Data System (ADS)
Alotta, Gioacchino; Di Paola, Mario; Failla, Giuseppe
2015-11-01
The paper proposes a fractional calculus approach to continuous wavelet analysis. Upon introducing a Mellin transform expression of the mother wavelet, it is shown that the wavelet transform of an arbitrary function f(t) can be given a fractional representation involving a suitable number of Riesz integrals of f(t), and corresponding fractional moments of the mother wavelet. This result serves as a basis for an original approach to wavelet analysis of linear systems under arbitrary excitations. In particular, using the proposed fractional representation for the wavelet transform of the excitation, it is found that the wavelet transform of the response can readily be computed by a Mellin transform expression, with fractional moments obtained from a set of algebraic equations whose coefficient matrix applies for any scale a of the wavelet transform. Robustness and computationally efficiency of the proposed approach are shown in the paper.
Adaptive wavelets and relativistic magnetohydrodynamics
NASA Astrophysics Data System (ADS)
Hirschmann, Eric; Neilsen, David; Anderson, Matthe; Debuhr, Jackson; Zhang, Bo
2016-03-01
We present a method for integrating the relativistic magnetohydrodynamics equations using iterated interpolating wavelets. Such provide an adaptive implementation for simulations in multidimensions. A measure of the local approximation error for the solution is provided by the wavelet coefficients. They place collocation points in locations naturally adapted to the flow while providing expected conservation. We present demanding 1D and 2D tests includingthe Kelvin-Helmholtz instability and the Rayleigh-Taylor instability. Finally, we consider an outgoing blast wave that models a GRB outflow.
NASA Astrophysics Data System (ADS)
Hegazy, Maha A.; Lotfy, Hayam M.; Mowaka, Shereen; Mohamed, Ekram Hany
2016-07-01
Wavelets have been adapted for a vast number of signal-processing applications due to the amount of information that can be extracted from a signal. In this work, a comparative study on the efficiency of continuous wavelet transform (CWT) as a signal processing tool in univariate regression and a pre-processing tool in multivariate analysis using partial least square (CWT-PLS) was conducted. These were applied to complex spectral signals of ternary and quaternary mixtures. CWT-PLS method succeeded in the simultaneous determination of a quaternary mixture of drotaverine (DRO), caffeine (CAF), paracetamol (PAR) and p-aminophenol (PAP, the major impurity of paracetamol). While, the univariate CWT failed to simultaneously determine the quaternary mixture components and was able to determine only PAR and PAP, the ternary mixtures of DRO, CAF, and PAR and CAF, PAR, and PAP. During the calculations of CWT, different wavelet families were tested. The univariate CWT method was validated according to the ICH guidelines. While for the development of the CWT-PLS model a calibration set was prepared by means of an orthogonal experimental design and their absorption spectra were recorded and processed by CWT. The CWT-PLS model was constructed by regression between the wavelet coefficients and concentration matrices and validation was performed by both cross validation and external validation sets. Both methods were successfully applied for determination of the studied drugs in pharmaceutical formulations.
Wavelet transforms as solutions of partial differential equations
Zweig, G.
1997-10-01
This is the final report of a three-year, Laboratory Directed Research and Development (LDRD) project at Los Alamos National Laboratory (LANL). Wavelet transforms are useful in representing transients whose time and frequency structure reflect the dynamics of an underlying physical system. Speech sound, pressure in turbulent fluid flow, or engine sound in automobiles are excellent candidates for wavelet analysis. This project focused on (1) methods for choosing the parent wavelet for a continuous wavelet transform in pattern recognition applications and (2) the more efficient computation of continuous wavelet transforms by understanding the relationship between discrete wavelet transforms and discretized continuous wavelet transforms. The most interesting result of this research is the finding that the generalized wave equation, on which the continuous wavelet transform is based, can be used to understand phenomena that relate to the process of hearing.
Optical wavelet transform for fingerprint identification
NASA Astrophysics Data System (ADS)
MacDonald, Robert P.; Rogers, Steven K.; Burns, Thomas J.; Fielding, Kenneth H.; Warhola, Gregory T.; Ruck, Dennis W.
1994-03-01
The Federal Bureau of Investigation (FBI) has recently sanctioned a wavelet fingerprint image compression algorithm developed for reducing storage requirements of digitized fingerprints. This research implements an optical wavelet transform of a fingerprint image, as the first step in an optical fingerprint identification process. Wavelet filters are created from computer- generated holograms of biorthogonal wavelets, the same wavelets implemented in the FBI algorithm. Using a detour phase holographic technique, a complex binary filter mask is created with both symmetry and linear phase. The wavelet transform is implemented with continuous shift using an optical correlation between binarized fingerprints written on a Magneto-Optic Spatial Light Modulator and the biorthogonal wavelet filters. A telescopic lens combination scales the transformed fingerprint onto the filters, providing a means of adjusting the biorthogonal wavelet filter dilation continuously. The wavelet transformed fingerprint is then applied to an optical fingerprint identification process. Comparison between normal fingerprints and wavelet transformed fingerprints shows improvement in the optical identification process, in terms of rotational invariance.
NASA Astrophysics Data System (ADS)
Nardi, Fernando; Petroselli, Andrea; Grimaldi, Salvatore
2013-04-01
Ongoing efforts of remote sensing technologies to provide more accurate digital elevation models (DEMs) at the global scale are supporting the use of terrain analysis and hydrologic and hydraulic modelling algorithms for flood mapping in ungauged basins. In this work we implement a fully continuous hydrologic-hydraulic model feeded by a rainfall synthetic time series for providing river hydrographs that are routed along the channel using a bidimensional hydraulic model for the detailed physically-based characterization of the inundation process. In this way the whole physical process is represented, from the net rainfall to the flow time series, avoiding any conceptual sub-method (design hyetograph and hydrograph) commonly needed to apply standard flood modelling and mapping procedures. Nevertheless, the floodplain information is no longer deterministic as the result of the evaluation of the impact on the river valley of a single design hydrologic scenario (event-based approach,EBA), but the final result is composed of a combination of data derived by the application of a fully-continuous approach (FCA). Indeed FCA provides a flow depth time series for each single cell of the inundated domain. The final flood map should be, thus, the result of a proper analysis of this dataset in statistical, qualitative and quantitative terms. Otherwise this would lead to an undefined flooding scenario that could be useless for flood risk management and decision making in urban plans.
Wavelet variance analysis for random fields on a regular lattice.
Mondal, Debashis; Percival, Donald B
2012-02-01
There has been considerable recent interest in using wavelets to analyze time series and images that can be regarded as realizations of certain 1-D and 2-D stochastic processes on a regular lattice. Wavelets give rise to the concept of the wavelet variance (or wavelet power spectrum), which decomposes the variance of a stochastic process on a scale-by-scale basis. The wavelet variance has been applied to a variety of time series, and a statistical theory for estimators of this variance has been developed. While there have been applications of the wavelet variance in the 2-D context (in particular, in works by Unser in 1995 on wavelet-based texture analysis for images and by Lark and Webster in 2004 on analysis of soil properties), a formal statistical theory for such analysis has been lacking. In this paper, we develop the statistical theory by generalizing and extending some of the approaches developed for time series, thus leading to a large-sample theory for estimators of 2-D wavelet variances. We apply our theory to simulated data from Gaussian random fields with exponential covariances and from fractional Brownian surfaces. We demonstrate that the wavelet variance is potentially useful for texture discrimination. We also use our methodology to analyze images of four types of clouds observed over the southeast Pacific Ocean.
Compression of echocardiographic scan line data using wavelet packet transform
NASA Technical Reports Server (NTRS)
Hang, X.; Greenberg, N. L.; Qin, J.; Thomas, J. D.
2001-01-01
An efficient compression strategy is indispensable for digital echocardiography. Previous work has suggested improved results utilizing wavelet transforms in the compression of 2D echocardiographic images. Set partitioning in hierarchical trees (SPIHT) was modified to compress echocardiographic scanline data based on the wavelet packet transform. A compression ratio of at least 94:1 resulted in preserved image quality.
Wavelet analysis of hemispheroid flow separation toward understanding human vocal fold pathologies
NASA Astrophysics Data System (ADS)
Plesniak, Daniel H.; Carr, Ian A.; Bulusu, Kartik V.; Plesniak, Michael W.
2014-11-01
Physiological flows observed in human vocal fold pathologies, such as polyps and nodules, can be modeled by flow over a wall-mounted protuberance. The experimental investigation of flow separation over a surface-mounted hemispheroid was performed using particle image velocimetry (PIV) and measurements of surface pressure in a low-speed wind tunnel. This study builds on the hypothesis that the signatures of vortical structures associated with flow separation are imprinted on the surface pressure distributions. Wavelet decomposition methods in one- and two-dimensions were utilized to elucidate the flow behavior. First, a complex Gaussian wavelet was used for the reconstruction of surface pressure time series from static pressure measurements acquired from ports upstream, downstream, and on the surface of the hemispheroid. This was followed by the application of a novel continuous wavelet transform algorithm (PIVlet 1.2) using a 2D-Ricker wavelet for coherent structure detection on instantaneous PIV-data. The goal of this study is to correlate phase shifts in surface pressure with Strouhal numbers associated with the vortex shedding. Ultimately, the wavelet-based analytical framework will be aimed at addressing pulsatile flows. This material is based in part upon work supported by the National Science Foundation under Grant Number CBET-1236351, and GW Center for Biomimetics and Bioinspired Engineering (COBRE).
Analysis of autostereoscopic three-dimensional images using multiview wavelets.
Saveljev, Vladimir; Palchikova, Irina
2016-08-10
We propose that multiview wavelets can be used in processing multiview images. The reference functions for the synthesis/analysis of multiview images are described. The synthesized binary images were observed experimentally as three-dimensional visual images. The symmetric multiview B-spline wavelets are proposed. The locations recognized in the continuous wavelet transform correspond to the layout of the test objects. The proposed wavelets can be applied to the multiview, integral, and plenoptic images. PMID:27534470
Perception-based reversible watermarking for 2D vector maps
NASA Astrophysics Data System (ADS)
Men, Chaoguang; Cao, Liujuan; Li, Xiang
2010-07-01
This paper presents an effective and reversible watermarking approach for digital copyright protection of 2D-vector maps. To ensure that the embedded watermark is insensitive for human perception, we only select the noise non-sensitive regions for watermark embedding by estimating vertex density within each polyline. To ensure the exact recovery of original 2D-vector map after watermark extraction, we introduce a new reversible watermarking scheme based on reversible high-frequency wavelet coefficients modification. Within the former-selected non-sensitive regions, our watermarking operates on the lower-order vertex coordinate decimals with integer wavelet transform. Such operation further reduces the visual distortion caused by watermark embedding. We have validated the effectiveness of our scheme on our real-world city river/building 2D-vector maps. We give extensive experimental comparisons with state-of-the-art methods, including embedding capability, invisibility, and robustness over watermark attacking.
NASA Astrophysics Data System (ADS)
Jang, Hyun-Sook; Yu, Changqian; Hayes, Robert; Granick, Steve
2015-03-01
Polymer vesicles (``polymersomes'') are an intriguing class of soft materials, commonly used to encapsulate small molecules or particles. Here we reveal they can also effectively incorporate nanoparticles inside their polymer membrane, leading to novel ``2D nanocomposites.'' The embedded nanoparticles alter the capacity of the polymersomes to bend and to stretch upon external stimuli.
Generalized Morse wavelets for the phase evaluation of projected fringe pattern
NASA Astrophysics Data System (ADS)
Kocahan Yılmaz, Özlem; Coşkun, Emre; Özder, Serhat
2014-10-01
Generalized Morse wavelets are proposed to evaluate the phase information from projected fringe pattern with the spatial carrier frequency in the x direction. The height profile of the object is determined through the phase change distribution by using the phase of the continuous wavelet transform. The choice of an appropriate mother wavelet is an important step for the calculation of phase. As a mother wavelet, zero order generalized Morse wavelet is chosen because of the flexible spatial and frequency localization property, and it is exactly analytic. Experimental results for the Morlet and Paul wavelets are compared with the results of generalized Morse wavelets analysis.
[Wavelet entropy analysis of spontaneous EEG signals in Alzheimer's disease].
Zhang, Meiyun; Zhang, Benshu; Chen, Ying
2014-08-01
Wavelet entropy is a quantitative index to describe the complexity of signals. Continuous wavelet transform method was employed to analyze the spontaneous electroencephalogram (EEG) signals of mild, moderate and severe Alzheimer's disease (AD) patients and normal elderly control people in this study. Wavelet power spectrums of EEG signals were calculated based on wavelet coefficients. Wavelet entropies of mild, moderate and severe AD patients were compared with those of normal controls. The correlation analysis between wavelet entropy and MMSE score was carried out. There existed significant difference on wavelet entropy among mild, moderate, severe AD patients and normal controls (P<0.01). Group comparisons showed that wavelet entropy for mild, moderate, severe AD patients was significantly lower than that for normal controls, which was related to the narrow distribution of their wavelet power spectrums. The statistical difference was significant (P<0.05). Further studies showed that the wavelet entropy of EEG and the MMSE score were significantly correlated (r= 0. 601-0. 799, P<0.01). Wavelet entropy is a quantitative indicator describing the complexity of EEG signals. Wavelet entropy is likely to be an electrophysiological index for AD diagnosis and severity assessment.
2011-12-31
Mesh2d is a Fortran90 program designed to generate two-dimensional structured grids of the form [x(i),y(i,j)] where [x,y] are grid coordinates identified by indices (i,j). The x(i) coordinates alone can be used to specify a one-dimensional grid. Because the x-coordinates vary only with the i index, a two-dimensional grid is composed in part of straight vertical lines. However, the nominally horizontal y(i,j0) coordinates along index i are permitted to undulate or otherwise vary. Mesh2d also assignsmore » an integer material type to each grid cell, mtyp(i,j), in a user-specified manner. The complete grid is specified through three separate input files defining the x(i), y(i,j), and mtyp(i,j) variations.« less
Optical pattern recognition with the real-time phase-only filters and wavelet matched filters
NASA Astrophysics Data System (ADS)
Sheng, Yunlong; Roberge, Danny; Neto, Luiz G.; Shen, Lixin; Paul-Hus, Gilles
1994-08-01
The spatial light modulator (SLM) is a key element of an optical processor. The limitations of the currently available SLM's are their limited phase and amplitude modulation capacity, limited space bandwidth product (SBWP) and limited speed. We use the commercial liquid crystal television (LCTV) as a SLM and build a real-time on-axis phase-only opticai correlator. This approach permits efficient use of the SBWP of the SLM (200 x 200 and 440 x 480 for new type of LCTV) and provides high light efficiency"2. Various continuous phase-only holograms, matched filters, circular harmonic filters and composite filters have been implemented with this coupled mode modulation SLM. The wavelet transform (WT) is a new mathematic tool for multiresolution local analysis of non-stationary and fast transient signals. It is efficient for local processing on edges, textures and deterministic objects in 2-D images3. We propose the wavelet matched filter (WMF) that performs the WT for edge enhancement and the matched filtering for correlation in a single step for automatic pattern recognition. Optics has advantage for shift invariant WT with the wavelet in the preselected frequency band and orientation4. The composite wavelet matched filter (CWMF) is a non-linear combination of the WMF's that produces desired outputs for a given set of objects. Both the WMF and CWMF are optically implemented with the couplemode modulation LCTV.
Real-time image analysis using wavelets: the "a trous" algorithm on MIMD architectures
NASA Astrophysics Data System (ADS)
Feil, Manfred; Uhl, Andreas
1999-03-01
The 'a trous' algorithm represents a discrete approach to the classical continuous wavelet transform. Similar to the fast wavelet transform the input signal is analyzed by using the coefficients of a properly chosen low-pass filter, but in contradistinction to the latter there follows no concluding decimation step. Examples of practical applications can be found in the field of cosmology for studying the formation of large scale structures of the Universe. In this paper we develop parallel algorithms on different MIMD architectures for the 2D 'a trous' decomposition. We implement the algorithm on several distributed memory architectures using the PVM paradigm and on a SGI POWERChallenge using a parallel version of the C programming language. Finally we investigate experimental results obtained on both of them.
NASA Astrophysics Data System (ADS)
Huda, Feblil; Kajiwara, Itsuro; Hosoya, Naoki
2014-08-01
In this paper, a vibration testing and health monitoring system based on an impulse response excited by laser is proposed to detect damage in membrane structures. A high power Nd: YAG pulse laser is used to supply an ideal impulse to a membrane structure by generating shock waves via laser-induced breakdown in air. A health monitoring apparatus is developed with this vibration testing system and a damage detecting algorithm which only requires the vibration mode shape of the damaged membrane. Artificial damage is induced in membrane structure by cutting and tearing the membrane. The vibration mode shapes of the membrane structure extracted from vibration testing by using the laser-induced breakdown and laser Doppler vibrometer are then analyzed by 2-D continuous wavelet transformation. The location of damage is determined by the dominant peak of the wavelet coefficient which can be seen clearly by applying a boundary treatment and the concept of an iso-surface to the 2-D wavelet coefficient. The applicability of the present approach is verified by finite element analysis and experimental results, demonstrating the ability of the method to detect and identify the positions of damage induced on the membrane structure.
Wavelet analysis and scaling properties of time series
NASA Astrophysics Data System (ADS)
Manimaran, P.; Panigrahi, Prasanta K.; Parikh, Jitendra C.
2005-10-01
We propose a wavelet based method for the characterization of the scaling behavior of nonstationary time series. It makes use of the built-in ability of the wavelets for capturing the trends in a data set, in variable window sizes. Discrete wavelets from the Daubechies family are used to illustrate the efficacy of this procedure. After studying binomial multifractal time series with the present and earlier approaches of detrending for comparison, we analyze the time series of averaged spin density in the 2D Ising model at the critical temperature, along with several experimental data sets possessing multifractal behavior.
2D Seismic Reflection Data across Central Illinois
Smith, Valerie; Leetaru, Hannes
2014-09-30
In a continuing collaboration with the Midwest Geologic Sequestration Consortium (MGSC) on the Evaluation of the Carbon Sequestration Potential of the Cambro-Ordovician Strata of the Illinois and Michigan Basins project, Schlumberger Carbon Services and WesternGeco acquired two-dimensional (2D) seismic data in the Illinois Basin. This work included the design, acquisition and processing of approximately 125 miles of (2D) seismic reflection surveys running west to east in the central Illinois Basin. Schlumberger Carbon Services and WesternGeco oversaw the management of the field operations (including a pre-shoot planning, mobilization, acquisition and de-mobilization of the field personnel and equipment), procurement of the necessary permits to conduct the survey, post-shoot closure, processing of the raw data, and provided expert consultation as needed in the interpretation of the delivered product. Three 2D seismic lines were acquired across central Illinois during November and December 2010 and January 2011. Traversing the Illinois Basin, this 2D seismic survey was designed to image the stratigraphy of the Cambro-Ordovician sections and also to discern the basement topography. Prior to this survey, there were no regionally extensive 2D seismic data spanning this section of the Illinois Basin. Between the NW side of Morgan County and northwestern border of Douglas County, these seismic lines ran through very rural portions of the state. Starting in Morgan County, Line 101 was the longest at 93 miles in length and ended NE of Decatur, Illinois. Line 501 ran W-E from the Illinois Basin – Decatur Project (IBDP) site to northwestern Douglas County and was 25 miles in length. Line 601 was the shortest and ran N-S past the IBDP site and connected lines 101 and 501. All three lines are correlated to well logs at the IBDP site. Originally processed in 2011, the 2D seismic profiles exhibited a degradation of signal quality below ~400 millisecond (ms) which made
Wavelet transform: fundamentals, applications, and implementation using acousto-optic correlators
NASA Astrophysics Data System (ADS)
DeCusatis, Casimer M.; Koay, J.; Litynski, Daniel M.; Das, Pankaj K.
1995-10-01
In recent years there has been a great deal of interest in the use of wavelets to supplement or replace conventional Fourier transform signal processing. This paper provides a review of wavelet transforms for signal processing applications, and discusses several emerging applications which benefit from the advantages of wavelets. The wavelet transform can be implemented as an acousto-optic correlator; perfect reconstruction of digital signals may also be achieved using acousto-optic finite impulse response filter banks. Acousto-optic image correlators are discussed as a potential implementation of the wavelet transform, since a 1D wavelet filter bank may be encoded as a 2D image. We discuss applications of the wavelet transform including nondestructive testing of materials, biomedical applications in the analysis of EEG signals, and interference excision in spread spectrum communication systems. Computer simulations and experimental results for these applications are also provided.
Wavelet based free-form deformations for nonrigid registration
NASA Astrophysics Data System (ADS)
Sun, Wei; Niessen, Wiro J.; Klein, Stefan
2014-03-01
In nonrigid registration, deformations may take place on the coarse and fine scales. For the conventional B-splines based free-form deformation (FFD) registration, these coarse- and fine-scale deformations are all represented by basis functions of a single scale. Meanwhile, wavelets have been proposed as a signal representation suitable for multi-scale problems. Wavelet analysis leads to a unique decomposition of a signal into its coarse- and fine-scale components. Potentially, this could therefore be useful for image registration. In this work, we investigate whether a wavelet-based FFD model has advantages for nonrigid image registration. We use a B-splines based wavelet, as defined by Cai and Wang.1 This wavelet is expressed as a linear combination of B-spline basis functions. Derived from the original B-spline function, this wavelet is smooth, differentiable, and compactly supported. The basis functions of this wavelet are orthogonal across scales in Sobolev space. This wavelet was previously used for registration in computer vision, in 2D optical flow problems,2 but it was not compared with the conventional B-spline FFD in medical image registration problems. An advantage of choosing this B-splines based wavelet model is that the space of allowable deformation is exactly equivalent to that of the traditional B-spline. The wavelet transformation is essentially a (linear) reparameterization of the B-spline transformation model. Experiments on 10 CT lung and 18 T1-weighted MRI brain datasets show that wavelet based registration leads to smoother deformation fields than traditional B-splines based registration, while achieving better accuracy.
NASA Astrophysics Data System (ADS)
Wang, Jin; Ma, Jianyong; Zhou, Changhe
2014-11-01
A 3×3 high divergent 2D-grating with period of 3.842μm at wavelength of 850nm under normal incidence is designed and fabricated in this paper. This high divergent 2D-grating is designed by the vector theory. The Rigorous Coupled Wave Analysis (RCWA) in association with the simulated annealing (SA) is adopted to calculate and optimize this 2D-grating.The properties of this grating are also investigated by the RCWA. The diffraction angles are more than 10 degrees in the whole wavelength band, which are bigger than the traditional 2D-grating. In addition, the small period of grating increases the difficulties of fabrication. So we fabricate the 2D-gratings by direct laser writing (DLW) instead of traditional manufacturing method. Then the method of ICP etching is used to obtain the high divergent 2D-grating.
The X-Ray Transform Projection of 3D Mother Wavelet Function
Yang, Xiangyu; Guo, Jiqiang; Lu, Li; Zeng, Li
2013-01-01
As we all know, any practical computed tomography (CT) projection data more or less contains noises. Hence, it will be inconvenient for the postprocessing of a reconstructed 3D image even when the noise in the projection data is white. The reason is that the noise in the reconstructed image may be nonwhite. X-ray transform can be applied to the three dimensional (3D) CT, depicting the relationship between material density and ray projection. In this paper, nontensor product relationship between the two dimensional (2D) mother wavelet and 3D mother wavelet is obtained by taking X-ray transform projection of 3D mother wavelet. We proved that the projection of the 3D mother wavelet is a 2D mother wavelet if the 3D mother wavelet satisfies certain conditions. So, the 3D wavelet transform of a 3D image can be implemented by the 2D wavelet transform of its X-ray transform projection and it will contribute to the reduction complexity and computation time during image processing. What is more, it can also avoid noise transfer and amplification during the processing of CT image reconstruction. PMID:24376470
3D Wavelet-Based Filter and Method
Moss, William C.; Haase, Sebastian; Sedat, John W.
2008-08-12
A 3D wavelet-based filter for visualizing and locating structural features of a user-specified linear size in 2D or 3D image data. The only input parameter is a characteristic linear size of the feature of interest, and the filter output contains only those regions that are correlated with the characteristic size, thus denoising the image.
NASA Astrophysics Data System (ADS)
Abbasi Tarighat, Maryam; Nabavi, Masoume; Mohammadizadeh, Mohammad Reza
2015-06-01
A new multi-component analysis method based on zero-crossing point-continuous wavelet transformation (CWT) was developed for simultaneous spectrophotometric determination of Cu2+ and Pb2+ ions based on the complex formation with 2-benzyl espiro[isoindoline-1,5oxasolidine]-2,3,4 trione (BSIIOT). The absorption spectra were evaluated with respect to synthetic ligand concentration, time of complexation and pH. Therefore according the absorbance values, 0.015 mmol L-1 BSIIOT, 10 min after mixing and pH 8.0 were used as optimum values. The complex formation between BSIIOT ligand and the cations Cu2+ and Pb2+ by application of rank annihilation factor analysis (RAFA) were investigated. Daubechies-4 (db4), discrete Meyer (dmey), Morlet (morl) and Symlet-8 (sym8) continuous wavelet transforms for signal treatments were found to be suitable among the wavelet families. The applicability of new synthetic ligand and selected mother wavelets were used for the simultaneous determination of strongly overlapped spectra of species without using any pre-chemical treatment. Therefore, CWT signals together with zero crossing technique were directly applied to the overlapping absorption spectra of Cu2+ and Pb2+. The calibration graphs for estimation of Pb2+ and Cu 2+were obtained by measuring the CWT amplitudes at zero crossing points for Cu2+ and Pb2+ at the wavelet domain, respectively. The proposed method was validated by simultaneous determination of Cu2+ and Pb2+ ions in red beans, walnut, rice, tea and soil samples. The obtained results of samples with proposed method have been compared with those predicted by partial least squares (PLS) and flame atomic absorption spectrophotometry (FAAS).
Abbasi Tarighat, Maryam; Nabavi, Masoume; Mohammadizadeh, Mohammad Reza
2015-06-15
A new multi-component analysis method based on zero-crossing point-continuous wavelet transformation (CWT) was developed for simultaneous spectrophotometric determination of Cu(2+) and Pb(2+) ions based on the complex formation with 2-benzyl espiro[isoindoline-1,5 oxasolidine]-2,3,4 trione (BSIIOT). The absorption spectra were evaluated with respect to synthetic ligand concentration, time of complexation and pH. Therefore according the absorbance values, 0.015 mmol L(-1) BSIIOT, 10 min after mixing and pH 8.0 were used as optimum values. The complex formation between BSIIOT ligand and the cations Cu(2+) and Pb(2+) by application of rank annihilation factor analysis (RAFA) were investigated. Daubechies-4 (db4), discrete Meyer (dmey), Morlet (morl) and Symlet-8 (sym8) continuous wavelet transforms for signal treatments were found to be suitable among the wavelet families. The applicability of new synthetic ligand and selected mother wavelets were used for the simultaneous determination of strongly overlapped spectra of species without using any pre-chemical treatment. Therefore, CWT signals together with zero crossing technique were directly applied to the overlapping absorption spectra of Cu(2+) and Pb(2+). The calibration graphs for estimation of Pb(2+) and Cu (2+)were obtained by measuring the CWT amplitudes at zero crossing points for Cu(2+) and Pb(2+) at the wavelet domain, respectively. The proposed method was validated by simultaneous determination of Cu(2+) and Pb(2+) ions in red beans, walnut, rice, tea and soil samples. The obtained results of samples with proposed method have been compared with those predicted by partial least squares (PLS) and flame atomic absorption spectrophotometry (FAAS).
Abbasi Tarighat, Maryam; Nabavi, Masoume; Mohammadizadeh, Mohammad Reza
2015-06-15
A new multi-component analysis method based on zero-crossing point-continuous wavelet transformation (CWT) was developed for simultaneous spectrophotometric determination of Cu(2+) and Pb(2+) ions based on the complex formation with 2-benzyl espiro[isoindoline-1,5 oxasolidine]-2,3,4 trione (BSIIOT). The absorption spectra were evaluated with respect to synthetic ligand concentration, time of complexation and pH. Therefore according the absorbance values, 0.015 mmol L(-1) BSIIOT, 10 min after mixing and pH 8.0 were used as optimum values. The complex formation between BSIIOT ligand and the cations Cu(2+) and Pb(2+) by application of rank annihilation factor analysis (RAFA) were investigated. Daubechies-4 (db4), discrete Meyer (dmey), Morlet (morl) and Symlet-8 (sym8) continuous wavelet transforms for signal treatments were found to be suitable among the wavelet families. The applicability of new synthetic ligand and selected mother wavelets were used for the simultaneous determination of strongly overlapped spectra of species without using any pre-chemical treatment. Therefore, CWT signals together with zero crossing technique were directly applied to the overlapping absorption spectra of Cu(2+) and Pb(2+). The calibration graphs for estimation of Pb(2+) and Cu (2+)were obtained by measuring the CWT amplitudes at zero crossing points for Cu(2+) and Pb(2+) at the wavelet domain, respectively. The proposed method was validated by simultaneous determination of Cu(2+) and Pb(2+) ions in red beans, walnut, rice, tea and soil samples. The obtained results of samples with proposed method have been compared with those predicted by partial least squares (PLS) and flame atomic absorption spectrophotometry (FAAS). PMID:25766479
Multiresolution With Super-Compact Wavelets
NASA Technical Reports Server (NTRS)
Lee, Dohyung
2000-01-01
approximation. The advantages of the multiresolution algorithm are that no special treatment is required at the boundaries of the interval, and that the application to functions which are only piecewise continuous (internal boundaries) can be efficiently implemented. In this presentation, Beam's supercompact wavelets are generalized to higher dimensions using multidimensional scaling and wavelet functions rather than alternating the directions as in the 1D version. As a demonstration of actual 3D data compression, supercompact wavelet transforms are applied to a 3D data set for wing tip vortex flow solutions (2.5 million grid points). It is shown that high data compression ratio can be achieved (around 50:1 ratio) in both vector and scalar data set.
Periodized Daubechies wavelets
Restrepo, J.M.; Leaf, G.K.; Schlossnagle, G.
1996-03-01
The properties of periodized Daubechies wavelets on [0,1] are detailed and counterparts which form a basis for L{sup 2}(R). Numerical examples illustrate the analytical estimates for convergence and demonstrated by comparison with Fourier spectral methods the superiority of wavelet projection methods for approximations. The analytical solution to inner products of periodized wavelets and their derivatives, which are known as connection coefficients, is presented, and their use ius illustrated in the approximation of two commonly used differential operators. The periodization of the connection coefficients in Galerkin schemes is presented in detail.
Baiz, Carlos R.; Schach, Denise; Tokmakoff, Andrei
2014-01-01
We describe a microscope for measuring two-dimensional infrared (2D IR) spectra of heterogeneous samples with μm-scale spatial resolution, sub-picosecond time resolution, and the molecular structure information of 2D IR, enabling the measurement of vibrational dynamics through correlations in frequency, time, and space. The setup is based on a fully collinear “one beam” geometry in which all pulses propagate along the same optics. Polarization, chopping, and phase cycling are used to isolate the 2D IR signals of interest. In addition, we demonstrate the use of vibrational lifetime as a contrast agent for imaging microscopic variations in molecular environments. PMID:25089490
Gaedigk, Andrea; Bradford, L Dianne; Alander, Sarah W; Leeder, J Steven
2006-04-01
Unexplained cases of CYP2D6 genotype/phenotype discordance continue to be discovered. In previous studies, several African Americans with a poor metabolizer phenotype carried the reduced function CYP2D6*10 allele in combination with a nonfunctional allele. We pursued the possibility that these alleles harbor either a known sequence variation (i.e., CYP2D6*36 carrying a gene conversion in exon 9 along the CYP2D6*10-defining 100C>T single-nucleotide polymorphism) or novel sequences variation(s). Discordant cases were evaluated by long-range polymerase chain reaction (PCR) to test for gene rearrangement events, and a 6.6-kilobase pair PCR product encompassing the CYP2D6 gene was cloned and entirely sequenced. Thereafter, allele frequencies were determined in different study populations comprising whites, African Americans, and Asians. Analyses covering the CYP2D7 to 2D6 gene region established that CYP2D6*36 did not only exist as a gene duplication (CYP2D6*36x2) or in tandem with *10 (CYP2D6*36+*10), as previously reported, but also by itself. This "single" CYP2D6*36 allele was found in nine African Americans and one Asian, but was absent in the whites tested. Ultimately, the presence of CYP2D6*36 resolved genotype/phenotype discordance in three cases. We also discovered an exon 9 conversion-positive CYP2D6*4 gene in a duplication arrangement (CYP2D6*4Nx2) and a CYP2D6*4 allele lacking 100C>T (CYP2D6*4M) in two white subjects. The discovery of an allele that carries only one CYP2D6*36 gene copy provides unequivocal evidence that both CYP2D6*36 and *36x2 are associated with a poor metabolizer phenotype. Given a combined frequency of between 0.5 and 3% in African Americans and Asians, genotyping for CYP2D6*36 should improve the accuracy of genotype-based phenotype prediction in these populations.
2004-08-01
AnisWave2D is a 2D finite-difference code for a simulating seismic wave propagation in fully anisotropic materials. The code is implemented to run in parallel over multiple processors and is fully portable. A mesh refinement algorithm has been utilized to allow the grid-spacing to be tailored to the velocity model, avoiding the over-sampling of high-velocity materials that usually occurs in fixed-grid schemes.
NASA Technical Reports Server (NTRS)
Kempel, Leo C.
1992-01-01
Wavelets are an exciting new topic in applied mathematics and signal processing. This paper will provide a brief review of wavelets which are also known as families of functions with an emphasis on interpretation rather than rigor. We will derive an indirect use of wavelets for the solution of integral equations based techniques adapted from image processing. Examples for resistive strips will be given illustrating the effect of these techniques as well as their promise in reducing dramatically the requirement in order to solve an integral equation for large bodies. We also will present a direct implementation of wavelets to solve an integral equation. Both methods suggest future research topics and may hold promise for a variety of uses in computational electromagnetics.
Combining Wavelet Transform and Hidden Markov Models for ECG Segmentation
NASA Astrophysics Data System (ADS)
Andreão, Rodrigo Varejão; Boudy, Jérôme
2006-12-01
This work aims at providing new insights on the electrocardiogram (ECG) segmentation problem using wavelets. The wavelet transform has been originally combined with a hidden Markov models (HMMs) framework in order to carry out beat segmentation and classification. A group of five continuous wavelet functions commonly used in ECG analysis has been implemented and compared using the same framework. All experiments were realized on the QT database, which is composed of a representative number of ambulatory recordings of several individuals and is supplied with manual labels made by a physician. Our main contribution relies on the consistent set of experiments performed. Moreover, the results obtained in terms of beat segmentation and premature ventricular beat (PVC) detection are comparable to others works reported in the literature, independently of the type of the wavelet. Finally, through an original concept of combining two wavelet functions in the segmentation stage, we achieve our best performances.
NASA Astrophysics Data System (ADS)
Wang, Yu-Ping
2005-08-01
Genetic image analysis is an interdisciplinary area, which combines microscope image processing techniques with the use of biochemical probes for the detection of genetic aberrations responsible for cancers and genetic diseases. Recent years have witnessed parallel and significant progress in both image processing and genetics. On one hand, revolutionary multiscale wavelet techniques have been developed in signal processing and applied mathematics in the last decade, providing sophisticated tools for genetic image analysis. On the other hand, reaping the fruit of genome sequencing, high resolution genetic probes have been developed to facilitate accurate detection of subtle and cryptic genetic aberrations. In the meantime, however, they bring about computational challenges for image analysis. In this paper, we review the fruitful interaction between wavelets and genetic imaging. We show how wavelets offer a perfect tool to address a variety of chromosome image analysis problems. In fact, the same word "subband" has been used in the nomenclature of cytogenetics to describe the multiresolution banding structure of the chromosome, even before its appearance in the wavelet literature. The application of wavelets to chromosome analysis holds great promise in addressing several computational challenges in genetics. A variety of real world examples such as the chromosome image enhancement, compression, registration and classification will be demonstrated. These examples are drawn from fluorescence in situ hybridization (FISH) and microarray (gene chip) imaging experiments, which indicate the impact of wavelets on the diagnosis, treatments and prognosis of cancers and genetic diseases.
Dependence and risk assessment for oil prices and exchange rate portfolios: A wavelet based approach
NASA Astrophysics Data System (ADS)
Aloui, Chaker; Jammazi, Rania
2015-10-01
In this article, we propose a wavelet-based approach to accommodate the stylized facts and complex structure of financial data, caused by frequent and abrupt changes of markets and noises. Specifically, we show how the combination of both continuous and discrete wavelet transforms with traditional financial models helps improve portfolio's market risk assessment. In the empirical stage, three wavelet-based models (wavelet-EGARCH with dynamic conditional correlations, wavelet-copula, and wavelet-extreme value) are considered and applied to crude oil price and US dollar exchange rate data. Our findings show that the wavelet-based approach provides an effective and powerful tool for detecting extreme moments and improving the accuracy of VaR and Expected Shortfall estimates of oil-exchange rate portfolios after noise is removed from the original data.
Climate wavelet spectrum estimation under chronology uncertainties
NASA Astrophysics Data System (ADS)
Lenoir, G.; Crucifix, M.
2012-04-01
Several approaches to estimate the chronology of palaeoclimate records exist in the literature: simple interpolation between the tie points, orbital tuning, alignment on other data... These techniques generate a single estimate of the chronology. More recently, statistical generators of chronologies have appeared (e.g. OXCAL, BCHRON) allowing the construction of thousands of chronologies given the tie points and their uncertainties. These techniques are based on advanced statistical methods. They allow one to take into account the uncertainty of the timing of each climatic event recorded into the core. On the other hand, when interpreting the data, scientists often rely on time series analysis, and especially on spectral analysis. Given that paleo-data are composed of a large spectrum of frequencies, are non-stationary and are highly noisy, the continuous wavelet transform turns out to be a suitable tool to analyse them. The wavelet periodogram, in particular, is helpful to interpret visually the time-frequency behaviour of the data. Here, we combine statistical methods to generate chronologies with the power of continuous wavelet transform. Some interesting applications then come up: comparison of time-frequency patterns between two proxies (extracted from different cores), between a proxy and a statistical dynamical model, and statistical estimation of phase-lag between two filtered signals. All these applications consider explicitly the uncertainty in the chronology. The poster presents mathematical developments on the wavelet spectrum estimation under chronology uncertainties as well as some applications to Quaternary data based on marine and ice cores.
DYNA2D96. Explicit 2-D Hydrodynamic FEM Program
Whirley, R.G.
1992-04-01
DYNA2D is a vectorized, explicit, two-dimensional, axisymmetric and plane strain finite element program for analyzing the large deformation dynamic and hydrodynamic response of inelastic solids. DYNA2D contains 13 material models and 9 equations of state (EOS) to cover a wide range of material behavior. The material models implemented in all machine versions are: elastic, orthotropic elastic, kinematic/isotropic elastic plasticity, thermoelastoplastic, soil and crushable foam, linear viscoelastic, rubber, high explosive burn, isotropic elastic-plastic, temperature-dependent elastic-plastic. The isotropic and temperature-dependent elastic-plastic models determine only the deviatoric stresses. Pressure is determined by one of 9 equations of state including linear polynomial, JWL high explosive, Sack Tuesday high explosive, Gruneisen, ratio of polynomials, linear polynomial with energy deposition, ignition and growth of reaction in HE, tabulated compaction, and tabulated.
Higher-order wavelet reconstruction/differentiation filters and Gibbs phenomena
NASA Astrophysics Data System (ADS)
Lombardini, Richard; Acevedo, Ramiro; Kuczala, Alexander; Keys, Kerry P.; Goodrich, Carl P.; Johnson, Bruce R.
2016-01-01
An orthogonal wavelet basis is characterized by its approximation order, which relates to the ability of the basis to represent general smooth functions on a given scale. It is known, though perhaps not widely known, that there are ways of exceeding the approximation order, i.e., achieving higher-order error in the discretized wavelet transform and its inverse. The focus here is on the development of a practical formulation to accomplish this first for 1D smooth functions, then for 1D functions with discontinuities and then for multidimensional (here 2D) functions with discontinuities. It is shown how to transcend both the wavelet approximation order and the 2D Gibbs phenomenon in representing electromagnetic fields at discontinuous dielectric interfaces that do not simply follow the wavelet-basis grid.
2001-01-31
This software reduces the data from two-dimensional kSA MOS program, k-Space Associates, Ann Arbor, MI. Initial MOS data is recorded without headers in 38 columns, with one row of data per acquisition per lase beam tracked. The final MOSS 2d data file is reduced, graphed, and saved in a tab-delimited column format with headers that can be plotted in any graphing software.
Dual tree fractional quaternion wavelet transform for disparity estimation.
Kumar, Sanoj; Kumar, Sanjeev; Sukavanam, Nagarajan; Raman, Balasubramanian
2014-03-01
This paper proposes a novel phase based approach for computing disparity as the optical flow from the given pair of consecutive images. A new dual tree fractional quaternion wavelet transform (FrQWT) is proposed by defining the 2D Fourier spectrum upto a single quadrant. In the proposed FrQWT, each quaternion wavelet consists of a real part (a real DWT wavelet) and three imaginary parts that are organized according to the quaternion algebra. First two FrQWT phases encode the shifts of image features in the absolute horizontal and vertical coordinate system, while the third phase has the texture information. The FrQWT allowed a multi-scale framework for calculating and adjusting local disparities and executing phase unwrapping from coarse to fine scales with linear computational efficiency. PMID:24388356
Davis, A. B.; Petrov, N. P.; Clothiaux, E. E.; Marshak, A.
2002-01-01
Spatial and/or temporal variabilities of clouds is of paramount importance for at least two in tensely researched sub-problems in global and regional climate modeling: (1) cloud-radiation interaction where correlations can trigger 3D radiative transfer effects; and (2) dynamical cloud modeling where the goal is to realistically reproduce the said correlations. We propose wavelets as a simple yet powerful way of quantifying cloud variability. More precisely, we use 'semi-discrete' wavelet transforms which, at least in the present statistical applications, have advantages over both its continuous and discrete counterparts found in the bulk of the wavelet literature. With the particular choice of normalization we adopt, the scale-dependence of the variance of the wavelet coefficients (i.e,, the wavelet energy spectrum) is always a better discriminator of transition from 'stationary' to 'nonstationary' behavior than conventional methods based on auto-correlation analysis, second-order structure function (a.k.a. the semi-variogram), or Fourier analysis. Indeed, the classic statistics go at best from monotonically scale- or wavenumber-dependent to flat at such a transition; by contrast, the wavelet spectrum changes the sign of its derivative with respect to scale. We apply 1D and 2D semi-discrete wavelet transforms to remote sensing data on cloud structure from two sources: (1) an upward-looking milli-meter cloud radar (MMCR) at DOE's climate observation site in Oklahoma deployed as part of the Atmospheric Radiation Measurement (ARM) Progrm; and (2) DOE's Multispectral Thermal Imager (MTI), a high-resolution space-borne instrument in sunsynchronous orbit that is described in sufficient detail for our present purposes by Weber et al. (1999). For each type of data, we have at least one theoretical prediction - with empirical validation already in existence - for a power-law relation for wavelet statistics with respect to scale. This is what is expected in physical (i
Spectral Laplace-Beltrami wavelets with applications in medical images.
Tan, Mingzhen; Qiu, Anqi
2015-05-01
The spectral graph wavelet transform (SGWT) has recently been developed to compute wavelet transforms of functions defined on non-Euclidean spaces such as graphs. By capitalizing on the established framework of the SGWT, we adopt a fast and efficient computation of a discretized Laplace-Beltrami (LB) operator that allows its extension from arbitrary graphs to differentiable and closed 2-D manifolds (smooth surfaces embedded in the 3-D Euclidean space). This particular class of manifolds are widely used in bioimaging to characterize the morphology of cells, tissues, and organs. They are often discretized into triangular meshes, providing additional geometric information apart from simple nodes and weighted connections in graphs. In comparison with the SGWT, the wavelet bases constructed with the LB operator are spatially localized with a more uniform "spread" with respect to underlying curvature of the surface. In our experiments, we first use synthetic data to show that traditional applications of wavelets in smoothing and edge detectio can be done using the wavelet bases constructed with the LB operator. Second, we show that multi-resolutional capabilities of the proposed framework are applicable in the classification of Alzheimer's patients with normal subjects using hippocampal shapes. Wavelet transforms of the hippocampal shape deformations at finer resolutions registered higher sensitivity (96%) and specificity (90%) than the classification results obtained from the direct usage of hippocampal shape deformations. In addition, the Laplace-Beltrami method requires consistently a smaller number of principal components (to retain a fixed variance) at higher resolution as compared to the binary and weighted graph Laplacians, demonstrating the potential of the wavelet bases in adapting to the geometry of the underlying manifold.
Rodriguez-Hernandez, Miguel A; Gomez-Sacristan, Angel; Sempere-Payá, Víctor M
2016-04-29
Ultrasound diagnosis is a widely used medical tool. Among the various ultrasound techniques, ultrasonic imaging is particularly relevant. This paper presents an improvement to a two-dimensional (2D) ultrasonic system using measurements taken from perpendicular planes, where digital signal processing techniques are used to combine one-dimensional (1D) A-scans were acquired by individual transducers in arrays located in perpendicular planes. An algorithm used to combine measurements is improved based on the wavelet transform, which includes a denoising step during the 2D representation generation process. The inclusion of this new denoising stage generates higher quality 2D representations with a reduced level of speckling. The paper includes different 2D representations obtained from noisy A-scans and compares the improvements obtained by including the denoising stage.
Rodriguez-Hernandez, Miguel A; Gomez-Sacristan, Angel; Sempere-Payá, Víctor M
2016-04-29
Ultrasound diagnosis is a widely used medical tool. Among the various ultrasound techniques, ultrasonic imaging is particularly relevant. This paper presents an improvement to a two-dimensional (2D) ultrasonic system using measurements taken from perpendicular planes, where digital signal processing techniques are used to combine one-dimensional (1D) A-scans were acquired by individual transducers in arrays located in perpendicular planes. An algorithm used to combine measurements is improved based on the wavelet transform, which includes a denoising step during the 2D representation generation process. The inclusion of this new denoising stage generates higher quality 2D representations with a reduced level of speckling. The paper includes different 2D representations obtained from noisy A-scans and compares the improvements obtained by including the denoising stage. PMID:27163318
Georgi, Howard; Kats, Yevgeny
2008-09-26
We discuss what can be learned about unparticle physics by studying simple quantum field theories in one space and one time dimension. We argue that the exactly soluble 2D theory of a massless fermion coupled to a massive vector boson, the Sommerfield model, is an interesting analog of a Banks-Zaks model, approaching a free theory at high energies and a scale-invariant theory with nontrivial anomalous dimensions at low energies. We construct a toy standard model coupling to the fermions in the Sommerfield model and study how the transition from unparticle behavior at low energies to free particle behavior at high energies manifests itself in interactions with the toy standard model particles.
Basis Selection for Wavelet Regression
NASA Technical Reports Server (NTRS)
Wheeler, Kevin R.; Lau, Sonie (Technical Monitor)
1998-01-01
A wavelet basis selection procedure is presented for wavelet regression. Both the basis and the threshold are selected using cross-validation. The method includes the capability of incorporating prior knowledge on the smoothness (or shape of the basis functions) into the basis selection procedure. The results of the method are demonstrated on sampled functions widely used in the wavelet regression literature. The results of the method are contrasted with other published methods.
NASA Astrophysics Data System (ADS)
Zahra, Noor e.; Sevindir, Huliya A.; Aslan, Zafar; Siddiqi, A. H.
2012-07-01
The aim of this study is to provide emerging applications of wavelet methods to medical signals and images, such as electrocardiogram, electroencephalogram, functional magnetic resonance imaging, computer tomography, X-ray and mammography. Interpretation of these signals and images are quite important. Nowadays wavelet methods have a significant impact on the science of medical imaging and the diagnosis of disease and screening protocols. Based on our initial investigations, future directions include neurosurgical planning and improved assessment of risk for individual patients, improved assessment and strategies for the treatment of chronic pain, improved seizure localization, and improved understanding of the physiology of neurological disorders. We look ahead to these and other emerging applications as the benefits of this technology become incorporated into current and future patient care. In this chapter by applying Fourier transform and wavelet transform, analysis and denoising of one of the important biomedical signals like EEG is carried out. The presence of rhythm, template matching, and correlation is discussed by various method. Energy of EEG signal is used to detect seizure in an epileptic patient. We have also performed denoising of EEG signals by SWT.
Perceptually Lossless Wavelet Compression
NASA Technical Reports Server (NTRS)
Watson, Andrew B.; Yang, Gloria Y.; Solomon, Joshua A.; Villasenor, John
1996-01-01
The Discrete Wavelet Transform (DWT) decomposes an image into bands that vary in spatial frequency and orientation. It is widely used for image compression. Measures of the visibility of DWT quantization errors are required to achieve optimal compression. Uniform quantization of a single band of coefficients results in an artifact that is the sum of a lattice of random amplitude basis functions of the corresponding DWT synthesis filter, which we call DWT uniform quantization noise. We measured visual detection thresholds for samples of DWT uniform quantization noise in Y, Cb, and Cr color channels. The spatial frequency of a wavelet is r 2(exp -1), where r is display visual resolution in pixels/degree, and L is the wavelet level. Amplitude thresholds increase rapidly with spatial frequency. Thresholds also increase from Y to Cr to Cb, and with orientation from low-pass to horizontal/vertical to diagonal. We propose a mathematical model for DWT noise detection thresholds that is a function of level, orientation, and display visual resolution. This allows calculation of a 'perceptually lossless' quantization matrix for which all errors are in theory below the visual threshold. The model may also be used as the basis for adaptive quantization schemes.
Zahra, Noor e; Sevindir, Huliya A.; Aslan, Zafar; Siddiqi, A. H.
2012-07-17
The aim of this study is to provide emerging applications of wavelet methods to medical signals and images, such as electrocardiogram, electroencephalogram, functional magnetic resonance imaging, computer tomography, X-ray and mammography. Interpretation of these signals and images are quite important. Nowadays wavelet methods have a significant impact on the science of medical imaging and the diagnosis of disease and screening protocols. Based on our initial investigations, future directions include neurosurgical planning and improved assessment of risk for individual patients, improved assessment and strategies for the treatment of chronic pain, improved seizure localization, and improved understanding of the physiology of neurological disorders. We look ahead to these and other emerging applications as the benefits of this technology become incorporated into current and future patient care. In this chapter by applying Fourier transform and wavelet transform, analysis and denoising of one of the important biomedical signals like EEG is carried out. The presence of rhythm, template matching, and correlation is discussed by various method. Energy of EEG signal is used to detect seizure in an epileptic patient. We have also performed denoising of EEG signals by SWT.
Position control using 2D-to-2D feature correspondences in vision guided cell micromanipulation.
Zhang, Yanliang; Han, Mingli; Shee, Cheng Yap; Ang, Wei Tech
2007-01-01
Conventional camera calibration that utilizes the extrinsic and intrinsic parameters of the camera and the objects has certain limitations for micro-level cell operations due to the presence of hardware deviations and external disturbances during the experimental process, thereby invalidating the extrinsic parameters. This invalidation is often neglected in macro-world visual servoing and affects the visual image processing quality, causing deviation from the desired position in micro-level cell operations. To increase the success rate of vision guided biological micromanipulations, a novel algorithm monitoring the changing image pattern of the manipulators including the injection micropipette and cell holder is designed and implemented based on 2 dimensional (2D)-to 2D feature correspondences and can adjust the manipulator and perform position control simultaneously. When any deviation is found, the manipulator is retracted to the initial focusing plane before continuing the operation.
Big data extraction with adaptive wavelet analysis (Presentation Video)
NASA Astrophysics Data System (ADS)
Qu, Hongya; Chen, Genda; Ni, Yiqing
2015-04-01
Nondestructive evaluation and sensing technology have been increasingly applied to characterize material properties and detect local damage in structures. More often than not, they generate images or data strings that are difficult to see any physical features without novel data extraction techniques. In the literature, popular data analysis techniques include Short-time Fourier Transform, Wavelet Transform, and Hilbert Transform for time efficiency and adaptive recognition. In this study, a new data analysis technique is proposed and developed by introducing an adaptive central frequency of the continuous Morlet wavelet transform so that both high frequency and time resolution can be maintained in a time-frequency window of interest. The new analysis technique is referred to as Adaptive Wavelet Analysis (AWA). This paper will be organized in several sections. In the first section, finite time-frequency resolution limitations in the traditional wavelet transform are introduced. Such limitations would greatly distort the transformed signals with a significant frequency variation with time. In the second section, Short Time Wavelet Transform (STWT), similar to Short Time Fourier Transform (STFT), is defined and developed to overcome such shortcoming of the traditional wavelet transform. In the third section, by utilizing the STWT and a time-variant central frequency of the Morlet wavelet, AWA can adapt the time-frequency resolution requirement to the signal variation over time. Finally, the advantage of the proposed AWA is demonstrated in Section 4 with a ground penetrating radar (GPR) image from a bridge deck, an analytical chirp signal with a large range sinusoidal frequency change over time, the train-induced acceleration responses of the Tsing-Ma Suspension Bridge in Hong Kong, China. The performance of the proposed AWA will be compared with the STFT and traditional wavelet transform.
NASA Technical Reports Server (NTRS)
Jameson, Leland
1996-01-01
Wavelets can provide a basis set in which the basis functions are constructed by dilating and translating a fixed function known as the mother wavelet. The mother wavelet can be seen as a high pass filter in the frequency domain. The process of dilating and expanding this high-pass filter can be seen as altering the frequency range that is 'passed' or detected. The process of translation moves this high-pass filter throughout the domain, thereby providing a mechanism to detect the frequencies or scales of information at every location. This is exactly the type of information that is needed for effective grid generation. This paper provides motivation to use wavelets for grid generation in addition to providing the final product: source code for wavelet-based grid generation.
A generalized wavelet extrema representation
Lu, Jian; Lades, M.
1995-10-01
The wavelet extrema representation originated by Stephane Mallat is a unique framework for low-level and intermediate-level (feature) processing. In this paper, we present a new form of wavelet extrema representation generalizing Mallat`s original work. The generalized wavelet extrema representation is a feature-based multiscale representation. For a particular choice of wavelet, our scheme can be interpreted as representing a signal or image by its edges, and peaks and valleys at multiple scales. Such a representation is shown to be stable -- the original signal or image can be reconstructed with very good quality. It is further shown that a signal or image can be modeled as piecewise monotonic, with all turning points between monotonic segments given by the wavelet extrema. A new projection operator is introduced to enforce piecewise inonotonicity of a signal in its reconstruction. This leads to an enhancement to previously developed algorithms in preventing artifacts in reconstructed signal.
NASA Astrophysics Data System (ADS)
Xu, Luopeng; Dan, Youquan; Wang, Qingyuan
2015-10-01
The continuous wavelet transform (CWT) introduces an expandable spatial and frequency window which can overcome the inferiority of localization characteristic in Fourier transform and windowed Fourier transform. The CWT method is widely applied in the non-stationary signal analysis field including optical 3D shape reconstruction with remarkable performance. In optical 3D surface measurement, the performance of CWT for optical fringe pattern phase reconstruction usually depends on the choice of wavelet function. A large kind of wavelet functions of CWT, such as Mexican Hat wavelet, Morlet wavelet, DOG wavelet, Gabor wavelet and so on, can be generated from Gauss wavelet function. However, so far, application of the Gauss wavelet transform (GWT) method (i.e. CWT with Gauss wavelet function) in optical profilometry is few reported. In this paper, the method using GWT for optical fringe pattern phase reconstruction is presented first and the comparisons between real and complex GWT methods are discussed in detail. The examples of numerical simulations are also given and analyzed. The results show that both the real GWT method along with a Hilbert transform and the complex GWT method can realize three-dimensional surface reconstruction; and the performance of reconstruction generally depends on the frequency domain appearance of Gauss wavelet functions. For the case of optical fringe pattern of large phase variation with position, the performance of real GWT is better than that of complex one due to complex Gauss series wavelets existing frequency sidelobes. Finally, the experiments are carried out and the experimental results agree well with our theoretical analysis.
Wavelet analysis of radon time series
NASA Astrophysics Data System (ADS)
Barbosa, Susana; Pereira, Alcides; Neves, Luis
2013-04-01
Radon is a radioactive noble gas with a half-life of 3.8 days ubiquitous in both natural and indoor environments. Being produced in uranium-bearing materials by decay from radium, radon can be easily and accurately measured by nuclear methods, making it an ideal proxy for time-varying geophysical processes. Radon time series exhibit a complex temporal structure and large variability on multiple scales. Wavelets are therefore particularly suitable for the analysis on a scale-by-scale basis of time series of radon concentrations. In this study continuous and discrete wavelet analysis is applied to describe the variability structure of hourly radon time series acquired both indoors and on a granite site in central Portugal. A multi-resolution decomposition is performed for extraction of sub-series associated to specific scales. The high-frequency components are modeled in terms of stationary autoregressive / moving average (ARMA) processes. The amplitude and phase of the periodic components are estimated and tidal features of the signals are assessed. Residual radon concentrations (after removal of periodic components) are further examined and the wavelet spectrum is used for estimation of the corresponding Hurst exponent. The results for the several radon time series considered in the present study are very heterogeneous in terms of both high-frequency and long-term temporal structure indicating that radon concentrations are very site-specific and heavily influenced by local factors.
High-order wavelet reconstruction/differentiation filters and Gibbs phenomena
NASA Astrophysics Data System (ADS)
Lombardini, Richard; Acevedo, Ramiro; Kuczala, Alexander; Keys, Kerry; Goodrich, Carl; Johnson, Bruce
2016-03-01
We have developed an efficient method to accurately represent 1D or 2D, smooth or discontinuous, solutions to partial differential equations (PDE's), such as Schrodinger or Maxwell's equations, in an orthogonal Daubechies wavelet basis. This is a crucial step in the future development of a wavelet method that solves these PDE's. There are two main developments from this research. First, a reconstruction transform for smooth functions, discovered in previous works [Keinert and Kwon (1997) and Neelov and Goedecker (2006)], is generalized in order to develop a systematic way of tuning its error. This transform converts the wavelet basis representation back to the actual point values of the function. Since this reconstruction can far exceed the wavelet approximation order, it is shown that shorter wavelets can be used while maintaining a high-order accuracy resulting in an increase of computational efficiency. Second, a new ``truncated'' reconstruction transform is developed, using pieces of wavelets, or ``tail functions'', which can be applied to discontinuous functions. Not only does it avoid the wavelet Gibbs phenomenon, but also maintains a tunable accuracy similar to the smooth function case.
An Introduction to Wavelet Theory and Analysis
Miner, N.E.
1998-10-01
This report reviews the history, theory and mathematics of wavelet analysis. Examination of the Fourier Transform and Short-time Fourier Transform methods provides tiormation about the evolution of the wavelet analysis technique. This overview is intended to provide readers with a basic understanding of wavelet analysis, define common wavelet terminology and describe wavelet amdysis algorithms. The most common algorithms for performing efficient, discrete wavelet transforms for signal analysis and inverse discrete wavelet transforms for signal reconstruction are presented. This report is intended to be approachable by non- mathematicians, although a basic understanding of engineering mathematics is necessary.
Multiscale peak detection in wavelet space.
Zhang, Zhi-Min; Tong, Xia; Peng, Ying; Ma, Pan; Zhang, Ming-Jin; Lu, Hong-Mei; Chen, Xiao-Qing; Liang, Yi-Zeng
2015-12-01
Accurate peak detection is essential for analyzing high-throughput datasets generated by analytical instruments. Derivatives with noise reduction and matched filtration are frequently used, but they are sensitive to baseline variations, random noise and deviations in the peak shape. A continuous wavelet transform (CWT)-based method is more practical and popular in this situation, which can increase the accuracy and reliability by identifying peaks across scales in wavelet space and implicitly removing noise as well as the baseline. However, its computational load is relatively high and the estimated features of peaks may not be accurate in the case of peaks that are overlapping, dense or weak. In this study, we present multi-scale peak detection (MSPD) by taking full advantage of additional information in wavelet space including ridges, valleys, and zero-crossings. It can achieve a high accuracy by thresholding each detected peak with the maximum of its ridge. It has been comprehensively evaluated with MALDI-TOF spectra in proteomics, the CAMDA 2006 SELDI dataset as well as the Romanian database of Raman spectra, which is particularly suitable for detecting peaks in high-throughput analytical signals. Receiver operating characteristic (ROC) curves show that MSPD can detect more true peaks while keeping the false discovery rate lower than MassSpecWavelet and MALDIquant methods. Superior results in Raman spectra suggest that MSPD seems to be a more universal method for peak detection. MSPD has been designed and implemented efficiently in Python and Cython. It is available as an open source package at .
Medical image compression by using three-dimensional wavelet transformation.
Wang, J; Huang, K
1996-01-01
This paper proposes a three-dimensional (3-D) medical image compression method for computed tomography (CT) and magnetic resonance (MR) that uses a separable nonuniform 3-D wavelet transform. The separable wavelet transform employs one filter bank within two-dimensional (2-D) slices and then a second filter bank on the slice direction. CT and MR image sets normally have different resolutions within a slice and between slices. The pixel distances within a slice are normally less than 1 mm and the distance between slices can vary from 1 mm to 10 mm. To find the best filter bank in the slice direction, the authors use the various filter banks in the slice direction and compare the compression results. The results from the 12 selected MR and CT image sets at various slice thickness show that the Haar transform in the slice direction gives the optimum performance for most image sets, except for a CT image set which has 1 mm slice distance. Compared with 2-D wavelet compression, compression ratios of the 3-D method are about 70% higher for CT and 35% higher for MR image sets at a peak signal to noise ratio (PSNR) of 50 dB, In general, the smaller the slice distance, the better the 3-D compression performance. PMID:18215935
Peak finding using biorthogonal wavelets
Tan, C.Y.
2000-02-01
The authors show in this paper how they can find the peaks in the input data if the underlying signal is a sum of Lorentzians. In order to project the data into a space of Lorentzian like functions, they show explicitly the construction of scaling functions which look like Lorentzians. From this construction, they can calculate the biorthogonal filter coefficients for both the analysis and synthesis functions. They then compare their biorthogonal wavelets to the FBI (Federal Bureau of Investigations) wavelets when used for peak finding in noisy data. They will show that in this instance, their filters perform much better than the FBI wavelets.
Resnikoff, H.L. )
1993-01-01
The theory of compactly supported wavelets is now 4 yr old. In that short period, it has stimulated significant research in pure mathematics; has been the source of new numerical methods for the solution of nonlinear partial differential equations, including Navier-Stokes; and has been applied to digital signal-processing problems, ranging from signal detection and classification to signal compression for speech, audio, images, seismic signals, and sonar. Wavelet channel coding has even been proposed for code division multiple access digital telephony. In each of these applications, prototype wavelet solutions have proved to be competitive with established methods, and in many cases they are already superior.
Perspectives for spintronics in 2D materials
NASA Astrophysics Data System (ADS)
Han, Wei
2016-03-01
The past decade has been especially creative for spintronics since the (re)discovery of various two dimensional (2D) materials. Due to the unusual physical characteristics, 2D materials have provided new platforms to probe the spin interaction with other degrees of freedom for electrons, as well as to be used for novel spintronics applications. This review briefly presents the most important recent and ongoing research for spintronics in 2D materials.
Adaptive wavelet-based recognition of oscillatory patterns on electroencephalograms
NASA Astrophysics Data System (ADS)
Nazimov, Alexey I.; Pavlov, Alexey N.; Hramov, Alexander E.; Grubov, Vadim V.; Koronovskii, Alexey A.; Sitnikova, Evgenija Y.
2013-02-01
The problem of automatic recognition of specific oscillatory patterns on electroencephalograms (EEG) is addressed using the continuous wavelet-transform (CWT). A possibility of improving the quality of recognition by optimizing the choice of CWT parameters is discussed. An adaptive approach is proposed to identify sleep spindles (SS) and spike wave discharges (SWD) that assumes automatic selection of CWT-parameters reflecting the most informative features of the analyzed time-frequency structures. Advantages of the proposed technique over the standard wavelet-based approaches are considered.
Electroencephalography data analysis by using discrete wavelet packet transform
NASA Astrophysics Data System (ADS)
Karim, Samsul Ariffin Abdul; Ismail, Mohd Tahir; Hasan, Mohammad Khatim; Sulaiman, Jumat; Muthuvalu, Mohana Sundaram; Janier Josefina, B.
2015-05-01
Electroencephalography (EEG) is the electrical activity generated by the movement of neurons in the brain. It is categorized into delta waves, theta, alpha, beta and gamma. These waves exist in a different frequency band. This paper is a continuation of our previous research. EEG data will be decomposed using Discrete Wavelet Packet Transform (DWPT). Daubechies wavelets 10 (D10) will be used as the basic functions for research purposes. From the main results, it is clear that the DWPT able to characterize the EEG signal corresponding to each wave at a specific frequency. Furthermore, the numerical results obtained better than the results using DWT. Statistical analysis support our main findings.
Quantitative 2D liquid-state NMR.
Giraudeau, Patrick
2014-06-01
Two-dimensional (2D) liquid-state NMR has a very high potential to simultaneously determine the absolute concentration of small molecules in complex mixtures, thanks to its capacity to separate overlapping resonances. However, it suffers from two main drawbacks that probably explain its relatively late development. First, the 2D NMR signal is strongly molecule-dependent and site-dependent; second, the long duration of 2D NMR experiments prevents its general use for high-throughput quantitative applications and affects its quantitative performance. Fortunately, the last 10 years has witnessed an increasing number of contributions where quantitative approaches based on 2D NMR were developed and applied to solve real analytical issues. This review aims at presenting these recent efforts to reach a high trueness and precision in quantitative measurements by 2D NMR. After highlighting the interest of 2D NMR for quantitative analysis, the different strategies to determine the absolute concentrations from 2D NMR spectra are described and illustrated by recent applications. The last part of the manuscript concerns the recent development of fast quantitative 2D NMR approaches, aiming at reducing the experiment duration while preserving - or even increasing - the analytical performance. We hope that this comprehensive review will help readers to apprehend the current landscape of quantitative 2D NMR, as well as the perspectives that may arise from it.
Birdsong Denoising Using Wavelets
Priyadarshani, Nirosha; Marsland, Stephen; Castro, Isabel; Punchihewa, Amal
2016-01-01
Automatic recording of birdsong is becoming the preferred way to monitor and quantify bird populations worldwide. Programmable recorders allow recordings to be obtained at all times of day and year for extended periods of time. Consequently, there is a critical need for robust automated birdsong recognition. One prominent obstacle to achieving this is low signal to noise ratio in unattended recordings. Field recordings are often very noisy: birdsong is only one component in a recording, which also includes noise from the environment (such as wind and rain), other animals (including insects), and human-related activities, as well as noise from the recorder itself. We describe a method of denoising using a combination of the wavelet packet decomposition and band-pass or low-pass filtering, and present experiments that demonstrate an order of magnitude improvement in noise reduction over natural noisy bird recordings. PMID:26812391
Wavelet entropy of stochastic processes
NASA Astrophysics Data System (ADS)
Zunino, L.; Pérez, D. G.; Garavaglia, M.; Rosso, O. A.
2007-06-01
We compare two different definitions for the wavelet entropy associated to stochastic processes. The first one, the normalized total wavelet entropy (NTWS) family [S. Blanco, A. Figliola, R.Q. Quiroga, O.A. Rosso, E. Serrano, Time-frequency analysis of electroencephalogram series, III. Wavelet packets and information cost function, Phys. Rev. E 57 (1998) 932-940; O.A. Rosso, S. Blanco, J. Yordanova, V. Kolev, A. Figliola, M. Schürmann, E. Başar, Wavelet entropy: a new tool for analysis of short duration brain electrical signals, J. Neurosci. Method 105 (2001) 65-75] and a second introduced by Tavares and Lucena [Physica A 357(1) (2005) 71-78]. In order to understand their advantages and disadvantages, exact results obtained for fractional Gaussian noise ( -1<α< 1) and fractional Brownian motion ( 1<α< 3) are assessed. We find out that the NTWS family performs better as a characterization method for these stochastic processes.
Wavelet theory and its applications
Faber, V.; Bradley, JJ.; Brislawn, C.; Dougherty, R.; Hawrylycz, M.
1996-07-01
This is the final report of a three-year, Laboratory-Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). We investigated the theory of wavelet transforms and their relation to Laboratory applications. The investigators have had considerable success in the past applying wavelet techniques to the numerical solution of optimal control problems for distributed- parameter systems, nonlinear signal estimation, and compression of digital imagery and multidimensional data. Wavelet theory involves ideas from the fields of harmonic analysis, numerical linear algebra, digital signal processing, approximation theory, and numerical analysis, and the new computational tools arising from wavelet theory are proving to be ideal for many Laboratory applications. 10 refs.
Wavelet multiscale processing of remote sensing data
NASA Astrophysics Data System (ADS)
Bagmanov, Valeriy H.; Kharitonov, Svyatoslav V.; Meshkov, Ivan K.; Sultanov, Albert H.
2008-12-01
There is comparative analysis of methods for estimation and definition of Hoerst index (index of self-similarity) and comparative analysis of wavelet types using for image decomposition are offered. Five types of compared wavelets are used for analysis: Haar wavelets, Daubechies wavelets, Discrete Meyer wavelets, symplets and coiflets. Best quality of restored image Meyer and Haar wavelets demonstrate, because of they are characterised by minimal errors of recomposition. But compression index for these types smaller, than for Daubechies wavelets, symplets and coiflets. Contrariwise the latter obtain less precision of decompression. As it is necessary to take into consideration the complexity of realization some wavelet transformation on digital signal processors (DSP), simplest method is Haar wavelet transformation.
Semi-orthogonal wavelets for elliptic variational problems
Hardin, D.P.; Roach, D.W.
1998-04-01
In this paper the authors give a construction of wavelets which are (a) semi-orthogonal with respect to an arbitrary elliptic bilinear form a({center_dot},{center_dot}) on the Sobolev space H{sub 0}{sup 1}((0, L)) and (b) continuous and piecewise linear on an arbitrary partition of [0, L]. They illustrate this construction using a model problem. They also construct alpha-orthogonal Battle-Lemarie type wavelets which fully diagonalize the Galerkin discretized matrix for the model problem with domain IR. Finally they describe a hybrid basis consisting of a combination of elements from the semi-orthogonal wavelet basis and the hierarchical Schauder basis. Numerical experiments indicate that this basis leads to robust scalable Galerkin discretizations of the model problem which remain well-conditioned independent of {epsilon}, L, and the refinement level K.
Wavelet-based polarimetry analysis
NASA Astrophysics Data System (ADS)
Ezekiel, Soundararajan; Harrity, Kyle; Farag, Waleed; Alford, Mark; Ferris, David; Blasch, Erik
2014-06-01
Wavelet transformation has become a cutting edge and promising approach in the field of image and signal processing. A wavelet is a waveform of effectively limited duration that has an average value of zero. Wavelet analysis is done by breaking up the signal into shifted and scaled versions of the original signal. The key advantage of a wavelet is that it is capable of revealing smaller changes, trends, and breakdown points that are not revealed by other techniques such as Fourier analysis. The phenomenon of polarization has been studied for quite some time and is a very useful tool for target detection and tracking. Long Wave Infrared (LWIR) polarization is beneficial for detecting camouflaged objects and is a useful approach when identifying and distinguishing manmade objects from natural clutter. In addition, the Stokes Polarization Parameters, which are calculated from 0°, 45°, 90°, 135° right circular, and left circular intensity measurements, provide spatial orientations of target features and suppress natural features. In this paper, we propose a wavelet-based polarimetry analysis (WPA) method to analyze Long Wave Infrared Polarimetry Imagery to discriminate targets such as dismounts and vehicles from background clutter. These parameters can be used for image thresholding and segmentation. Experimental results show the wavelet-based polarimetry analysis is efficient and can be used in a wide range of applications such as change detection, shape extraction, target recognition, and feature-aided tracking.
Low-Oscillation Complex Wavelets
NASA Astrophysics Data System (ADS)
ADDISON, P. S.; WATSON, J. N.; FENG, T.
2002-07-01
In this paper we explore the use of two low-oscillation complex wavelets—Mexican hat and Morlet—as powerful feature detection tools for data analysis. These wavelets, which have been largely ignored to date in the scientific literature, allow for a decomposition which is more “temporal than spectral” in wavelet space. This is shown to be useful for the detection of small amplitude, short duration signal features which are masked by much larger fluctuations. Wavelet transform-based methods employing these wavelets (based on both wavelet ridges and modulus maxima) are developed and applied to sonic echo NDT signals used for the analysis of structural elements. A new mobility scalogram and associated reflectogram is defined for analysis of impulse response characteristics of structural elements and a novel signal compression technique is described in which the pertinent signal information is contained within a few modulus maxima coefficients. As an example of its usefulness, the signal compression method is employed as a pre-processor for a neural network classifier. The authors believe that low oscillation complex wavelets have wide applicability to other practical signal analysis problems. Their possible application to two such problems is discussed briefly—the interrogation of arrhythmic ECG signals and the detection and characterization of coherent structures in turbulent flow fields.
Tests for Wavelets as a Basis Set
NASA Astrophysics Data System (ADS)
Baker, Thomas; Evenbly, Glen; White, Steven
A wavelet transformation is a special type of filter usually reserved for image processing and other applications. We develop metrics to evaluate wavelets for general problems on test one-dimensional systems. The goal is to eventually use a wavelet basis in electronic structure calculations. We compare a variety of orthogonal wavelets such as coiflets, symlets, and daubechies wavelets. We also evaluate a new type of orthogonal wavelet with dilation factor three which is both symmetric and compact in real space. This work was supported by the U.S. Department of Energy, Office of Science, Basic Energy Sciences under Award #DE-SC008696.
Staring 2-D hadamard transform spectral imager
Gentry, Stephen M.; Wehlburg, Christine M.; Wehlburg, Joseph C.; Smith, Mark W.; Smith, Jody L.
2006-02-07
A staring imaging system inputs a 2D spatial image containing multi-frequency spectral information. This image is encoded in one dimension of the image with a cyclic Hadamarid S-matrix. The resulting image is detecting with a spatial 2D detector; and a computer applies a Hadamard transform to recover the encoded image.
2D materials for nanophotonic devices
NASA Astrophysics Data System (ADS)
Xu, Renjing; Yang, Jiong; Zhang, Shuang; Pei, Jiajie; Lu, Yuerui
2015-12-01
Two-dimensional (2D) materials have become very important building blocks for electronic, photonic, and phononic devices. The 2D material family has four key members, including the metallic graphene, transition metal dichalcogenide (TMD) layered semiconductors, semiconducting black phosphorous, and the insulating h-BN. Owing to the strong quantum confinements and defect-free surfaces, these atomically thin layers have offered us perfect platforms to investigate the interactions among photons, electrons and phonons. The unique interactions in these 2D materials are very important for both scientific research and application engineering. In this talk, I would like to briefly summarize and highlight the key findings, opportunities and challenges in this field. Next, I will introduce/highlight our recent achievements. We demonstrated atomically thin micro-lens and gratings using 2D MoS2, which is the thinnest optical component around the world. These devices are based on our discovery that the elastic light-matter interactions in highindex 2D materials is very strong. Also, I would like to introduce a new two-dimensional material phosphorene. Phosphorene has strongly anisotropic optical response, which creates 1D excitons in a 2D system. The strong confinement in phosphorene also enables the ultra-high trion (charged exciton) binding energies, which have been successfully measured in our experiments. Finally, I will briefly talk about the potential applications of 2D materials in energy harvesting.
Internal Photoemission Spectroscopy of 2-D Materials
NASA Astrophysics Data System (ADS)
Nguyen, Nhan; Li, Mingda; Vishwanath, Suresh; Yan, Rusen; Xiao, Shudong; Xing, Huili; Cheng, Guangjun; Hight Walker, Angela; Zhang, Qin
Recent research has shown the great benefits of using 2-D materials in the tunnel field-effect transistor (TFET), which is considered a promising candidate for the beyond-CMOS technology. The on-state current of TFET can be enhanced by engineering the band alignment of different 2D-2D or 2D-3D heterostructures. Here we present the internal photoemission spectroscopy (IPE) approach to determine the band alignments of various 2-D materials, in particular SnSe2 and WSe2, which have been proposed for new TFET designs. The metal-oxide-2-D semiconductor test structures are fabricated and characterized by IPE, where the band offsets from the 2-D semiconductor to the oxide conduction band minimum are determined by the threshold of the cube root of IPE yields as a function of photon energy. In particular, we find that SnSe2 has a larger electron affinity than most semiconductors and can be combined with other semiconductors to form near broken-gap heterojunctions with low barrier heights which can produce a higher on-state current. The details of data analysis of IPE and the results from Raman spectroscopy and spectroscopic ellipsometry measurements will also be presented and discussed.
Group-normalized wavelet packet signal processing
NASA Astrophysics Data System (ADS)
Shi, Zhuoer; Bao, Zheng
1997-04-01
Since the traditional wavelet and wavelet packet coefficients do not exactly represent the strength of signal components at the very time(space)-frequency tilling, group- normalized wavelet packet transform (GNWPT), is presented for nonlinear signal filtering and extraction from the clutter or noise, together with the space(time)-frequency masking technique. The extended F-entropy improves the performance of GNWPT. For perception-based image, soft-logic masking is emphasized to remove the aliasing with edge preserved. Lawton's method for complex valued wavelets construction is extended to generate the complex valued compactly supported wavelet packets for radar signal extraction. This kind of wavelet packets are symmetry and unitary orthogonal. Well-defined wavelet packets are chosen by the analysis remarks on their time-frequency characteristics. For real valued signal processing, such as images and ECG signal, the compactly supported spline or bi- orthogonal wavelet packets are preferred for perfect de- noising and filtering qualities.
2D materials: to graphene and beyond.
Mas-Ballesté, Rubén; Gómez-Navarro, Cristina; Gómez-Herrero, Julio; Zamora, Félix
2011-01-01
This review is an attempt to illustrate the different alternatives in the field of 2D materials. Graphene seems to be just the tip of the iceberg and we show how the discovery of alternative 2D materials is starting to show the rest of this iceberg. The review comprises the current state-of-the-art of the vast literature in concepts and methods already known for isolation and characterization of graphene, and rationalizes the quite disperse literature in other 2D materials such as metal oxides, hydroxides and chalcogenides, and metal-organic frameworks.
Wavelet analysis of Snow course data within the Sierra Nevada Mountains
NASA Astrophysics Data System (ADS)
Rios, T.; Dracup, J. A.
2003-12-01
In recent years, an analytical method known as wavelet analysis has received increasing applications in geophysical fields (Foufoula-Georgiou and Kumar 1994). Wavelet analysis can be used to identify the time and frequency regime in data while still maintaining the time coordinate. By applying the wavelet analysis method to the Mount Shasta snow course for the time period from 1937-1997 using the continuous 1-D wavelet toolbox in MATLAB, we found that several frequency regimes are present within the signal. The inter-annual noise dominates the frequency regime below the seven-year scale, but there is a relatively consistent 9-13 year oscillation that is present within the snow data. This frequency regime is also observed to shift to lower scales as the time series progresses, possibly indicating a shift in the climate variability due to climate change. In addition, analyses of the depth and the water content data exhibit nearly identical wavelet images. We are currently in the process of identifying other climate variables that may exhibit similar periodicity with the continuous 1-D wavelet analysis, such as the PDO and ENSO. Preliminary results show that by analyzing the hydrologic variables of the Sierra Nevada snowpack depth and/or water content using the wavelet method, we may be able to provide useful insights into the synergy and expression of climate change and variability within the California Sierra Nevadas.
Wavelet-based Evapotranspiration Forecasts
NASA Astrophysics Data System (ADS)
Bachour, R.; Maslova, I.; Ticlavilca, A. M.; McKee, M.; Walker, W.
2012-12-01
Providing a reliable short-term forecast of evapotranspiration (ET) could be a valuable element for improving the efficiency of irrigation water delivery systems. In the last decade, wavelet transform has become a useful technique for analyzing the frequency domain of hydrological time series. This study shows how wavelet transform can be used to access statistical properties of evapotranspiration. The objective of the research reported here is to use wavelet-based techniques to forecast ET up to 16 days ahead, which corresponds to the LANDSAT 7 overpass cycle. The properties of the ET time series, both physical and statistical, are examined in the time and frequency domains. We use the information about the energy decomposition in the wavelet domain to extract meaningful components that are used as inputs for ET forecasting models. Seasonal autoregressive integrated moving average (SARIMA) and multivariate relevance vector machine (MVRVM) models are coupled with the wavelet-based multiresolution analysis (MRA) results and used to generate short-term ET forecasts. Accuracy of the models is estimated and model robustness is evaluated using the bootstrap approach.
2-d Finite Element Code Postprocessor
1996-07-15
ORION is an interactive program that serves as a postprocessor for the analysis programs NIKE2D, DYNA2D, TOPAZ2D, and CHEMICAL TOPAZ2D. ORION reads binary plot files generated by the two-dimensional finite element codes currently used by the Methods Development Group at LLNL. Contour and color fringe plots of a large number of quantities may be displayed on meshes consisting of triangular and quadrilateral elements. ORION can compute strain measures, interface pressures along slide lines, reaction forcesmore » along constrained boundaries, and momentum. ORION has been applied to study the response of two-dimensional solids and structures undergoing finite deformations under a wide variety of large deformation transient dynamic and static problems and heat transfer analyses.« less
Ginsparg, P.
1991-01-01
These are introductory lectures for a general audience that give an overview of the subject of matrix models and their application to random surfaces, 2d gravity, and string theory. They are intentionally 1.5 years out of date.
Ginsparg, P.
1991-12-31
These are introductory lectures for a general audience that give an overview of the subject of matrix models and their application to random surfaces, 2d gravity, and string theory. They are intentionally 1.5 years out of date.
Brittle damage models in DYNA2D
Faux, D.R.
1997-09-01
DYNA2D is an explicit Lagrangian finite element code used to model dynamic events where stress wave interactions influence the overall response of the system. DYNA2D is often used to model penetration problems involving ductile-to-ductile impacts; however, with the advent of the use of ceramics in the armor-anti-armor community and the need to model damage to laser optics components, good brittle damage models are now needed in DYNA2D. This report will detail the implementation of four brittle damage models in DYNA2D, three scalar damage models and one tensor damage model. These new brittle damage models are then used to predict experimental results from three distinctly different glass damage problems.
Chemical Approaches to 2D Materials.
Samorì, Paolo; Palermo, Vincenzo; Feng, Xinliang
2016-08-01
Chemistry plays an ever-increasing role in the production, functionalization, processing and applications of graphene and other 2D materials. This special issue highlights a selection of enlightening chemical approaches to 2D materials, which nicely reflect the breadth of the field and convey the excitement of the individuals involved in it, who are trying to translate graphene and related materials from the laboratory into a real, high-impact technology. PMID:27478083
Chemical Approaches to 2D Materials.
Samorì, Paolo; Palermo, Vincenzo; Feng, Xinliang
2016-08-01
Chemistry plays an ever-increasing role in the production, functionalization, processing and applications of graphene and other 2D materials. This special issue highlights a selection of enlightening chemical approaches to 2D materials, which nicely reflect the breadth of the field and convey the excitement of the individuals involved in it, who are trying to translate graphene and related materials from the laboratory into a real, high-impact technology.
Yang, Li-Ming; Dornfeld, Matthew; Frauenheim, Thomas; Ganz, Eric
2015-10-21
We predict a highly stable and robust atomically thin gold monolayer with a hexagonal close packed lattice stabilized by metallic bonding with contributions from strong relativistic effects and aurophilic interactions. We have shown that the framework of the Au monolayer can survive 10 ps MD annealing simulations up to 1400 K. The framework is also able to survive large motions out of the plane. Due to the smaller number of bonds per atom in the 2D layer compared to the 3D bulk we observe significantly enhanced energy per bond (0.94 vs. 0.52 eV per bond). This is similar to the increase in bond strength going from 3D diamond to 2D graphene. It is a non-magnetic metal, and was found to be the global minima in the 2D space. Phonon dispersion calculations demonstrate high kinetic stability with no negative modes. This 2D gold monolayer corresponds to the top monolayer of the bulk Au(111) face-centered cubic lattice. The close-packed lattice maximizes the aurophilic interactions. We find that the electrons are completely delocalized in the plane and behave as 2D nearly free electron gas. We hope that the present work can inspire the experimental fabrication of novel free standing 2D metal systems.
2d index and surface operators
NASA Astrophysics Data System (ADS)
Gadde, Abhijit; Gukov, Sergei
2014-03-01
In this paper we compute the superconformal index of 2d (2, 2) supersymmetric gauge theories. The 2d superconformal index, a.k.a. flavored elliptic genus, is computed by a unitary matrix integral much like the matrix integral that computes the 4d superconformal index. We compute the 2d index explicitly for a number of examples. In the case of abelian gauge theories we see that the index is invariant under flop transition and under CY-LG correspondence. The index also provides a powerful check of the Seiberg-type duality for non-abelian gauge theories discovered by Hori and Tong. In the later half of the paper, we study half-BPS surface operators in = 2 super-conformal gauge theories. They are engineered by coupling the 2d (2, 2) supersymmetric gauge theory living on the support of the surface operator to the 4d = 2 theory, so that different realizations of the same surface operator with a given Levi type are related by a 2d analogue of the Seiberg duality. The index of this coupled system is computed by using the tools developed in the first half of the paper. The superconformal index in the presence of surface defect is expected to be invariant under generalized S-duality. We demonstrate that it is indeed the case. In doing so the Seiberg-type duality of the 2d theory plays an important role.
The Kubo-Greenwood expression and 2d MIT transport
NASA Astrophysics Data System (ADS)
Castner, Theodore
2010-03-01
The 2d MIT in GaAs heterostructures (p- and n-type)features a mobility that drops continuously as the reduced density x= n/nc-1 is decreased. The Kubo-Greenwood result [1] predicts μ = (eɛh/hnc)α^2(x) where α is a normalized DOS. α(x)is obtained from the data [p-type, Gao et al. [2]; n-type Lilly et al. [3
Wavelet Representation of Contour Sets
Bertram, M; Laney, D E; Duchaineau, M A; Hansen, C D; Hamann, B; Joy, K I
2001-07-19
We present a new wavelet compression and multiresolution modeling approach for sets of contours (level sets). In contrast to previous wavelet schemes, our algorithm creates a parametrization of a scalar field induced by its contoum and compactly stores this parametrization rather than function values sampled on a regular grid. Our representation is based on hierarchical polygon meshes with subdivision connectivity whose vertices are transformed into wavelet coefficients. From this sparse set of coefficients, every set of contours can be efficiently reconstructed at multiple levels of resolution. When applying lossy compression, introducing high quantization errors, our method preserves contour topology, in contrast to compression methods applied to the corresponding field function. We provide numerical results for scalar fields defined on planar domains. Our approach generalizes to volumetric domains, time-varying contours, and level sets of vector fields.
Wavelets for sign language translation
NASA Astrophysics Data System (ADS)
Wilson, Beth J.; Anspach, Gretel
1993-10-01
Wavelet techniques are applied to help extract the relevant parameters of sign language from video images of a person communicating in American Sign Language or Signed English. The compression and edge detection features of two-dimensional wavelet analysis are exploited to enhance the algorithms under development to classify the hand motion, hand location with respect to the body, and handshape. These three parameters have different processing requirements and complexity issues. The results are described for applying various quadrature mirror filter designs to a filterbank implementation of the desired wavelet transform. The overall project is to develop a system that will translate sign language to English to facilitate communication between deaf and hearing people.
Recent advances in wavelet technology
NASA Technical Reports Server (NTRS)
Wells, R. O., Jr.
1994-01-01
Wavelet research has been developing rapidly over the past five years, and in particular in the academic world there has been significant activity at numerous universities. In the industrial world, there has been developments at Aware, Inc., Lockheed, Martin-Marietta, TRW, Kodak, Exxon, and many others. The government agencies supporting wavelet research and development include ARPA, ONR, AFOSR, NASA, and many other agencies. The recent literature in the past five years includes a recent book which is an index of citations in the past decade on this subject, and it contains over 1,000 references and abstracts.
NKG2D ligands mediate immunosurveillance of senescent cells.
Sagiv, Adi; Burton, Dominick G A; Moshayev, Zhana; Vadai, Ezra; Wensveen, Felix; Ben-Dor, Shifra; Golani, Ofra; Polic, Bojan; Krizhanovsky, Valery
2016-02-01
Cellular senescence is a stress response mechanism that limits tumorigenesis and tissue damage. Induction of cellular senescence commonly coincides with an immunogenic phenotype that promotes self-elimination by components of the immune system, thereby facilitating tumor suppression and limiting excess fibrosis during wound repair. The mechanisms by which senescent cells regulate their immune surveillance are not completely understood. Here we show that ligands of an activating Natural Killer (NK) cell receptor (NKG2D), MICA and ULBP2 are consistently up-regulated following induction of replicative senescence, oncogene-induced senescence and DNA damage - induced senescence. MICA and ULBP2 proteins are necessary for efficient NK-mediated cytotoxicity towards senescent fibroblasts. The mechanisms regulating the initial expression of NKG2D ligands in senescent cells are dependent on a DNA damage response, whilst continuous expression of these ligands is regulated by the ERK signaling pathway. In liver fibrosis, the accumulation of senescent activated stellate cells is increased in mice lacking NKG2D receptor leading to increased fibrosis. Overall, our results provide new insights into the mechanisms regulating the expression of immune ligands in senescent cells and reveal the importance of NKG2D receptor-ligand interaction in protecting against liver fibrosis. PMID:26878797
The EM Method in a Probabilistic Wavelet-Based MRI Denoising
2015-01-01
Human body heat emission and others external causes can interfere in magnetic resonance image acquisition and produce noise. In this kind of images, the noise, when no signal is present, is Rayleigh distributed and its wavelet coefficients can be approximately modeled by a Gaussian distribution. Noiseless magnetic resonance images can be modeled by a Laplacian distribution in the wavelet domain. This paper proposes a new magnetic resonance image denoising method to solve this fact. This method performs shrinkage of wavelet coefficients based on the conditioned probability of being noise or detail. The parameters involved in this filtering approach are calculated by means of the expectation maximization (EM) method, which avoids the need to use an estimator of noise variance. The efficiency of the proposed filter is studied and compared with other important filtering techniques, such as Nowak's, Donoho-Johnstone's, Awate-Whitaker's, and nonlocal means filters, in different 2D and 3D images. PMID:26089959
Wavelet steerability and the higher-order Riesz transform.
Unser, Michael; Van De Ville, Dimitri
2010-03-01
Our main goal in this paper is to set the foundations of a general continuous-domain framework for designing steerable, reversible signal transformations (a.k.a. frames) in multiple dimensions ( d >or= 2). To that end, we introduce a self-reversible, Nth-order extension of the Riesz transform. We prove that this generalized transform has the following remarkable properties: shift-invariance, scale-invariance, inner-product preservation, and steerability. The pleasing consequence is that the transform maps any primary wavelet frame (or basis) of [Formula: see text] into another "steerable" wavelet frame, while preserving the frame bounds. The concept provides a functional counterpart to Simoncelli's steerable pyramid whose construction was primarily based on filterbank design. The proposed mechanism allows for the specification of wavelets with any order of steerability in any number of dimensions; it also yields a perfect reconstruction filterbank algorithm. We illustrate the method with the design of a novel family of multidimensional Riesz-Laplace wavelets that essentially behave like the N th-order partial derivatives of an isotropic Gaussian kernel. PMID:20031498
Orthotropic Piezoelectricity in 2D Nanocellulose
NASA Astrophysics Data System (ADS)
García, Y.; Ruiz-Blanco, Yasser B.; Marrero-Ponce, Yovani; Sotomayor-Torres, C. M.
2016-10-01
The control of electromechanical responses within bonding regions is essential to face frontier challenges in nanotechnologies, such as molecular electronics and biotechnology. Here, we present Iβ-nanocellulose as a potentially new orthotropic 2D piezoelectric crystal. The predicted in-layer piezoelectricity is originated on a sui-generis hydrogen bonds pattern. Upon this fact and by using a combination of ab-initio and ad-hoc models, we introduce a description of electrical profiles along chemical bonds. Such developments lead to obtain a rationale for modelling the extended piezoelectric effect originated within bond scales. The order of magnitude estimated for the 2D Iβ-nanocellulose piezoelectric response, ~pm V‑1, ranks this material at the level of currently used piezoelectric energy generators and new artificial 2D designs. Such finding would be crucial for developing alternative materials to drive emerging nanotechnologies.
Orthotropic Piezoelectricity in 2D Nanocellulose
García, Y.; Ruiz-Blanco, Yasser B.; Marrero-Ponce, Yovani; Sotomayor-Torres, C. M.
2016-01-01
The control of electromechanical responses within bonding regions is essential to face frontier challenges in nanotechnologies, such as molecular electronics and biotechnology. Here, we present Iβ-nanocellulose as a potentially new orthotropic 2D piezoelectric crystal. The predicted in-layer piezoelectricity is originated on a sui-generis hydrogen bonds pattern. Upon this fact and by using a combination of ab-initio and ad-hoc models, we introduce a description of electrical profiles along chemical bonds. Such developments lead to obtain a rationale for modelling the extended piezoelectric effect originated within bond scales. The order of magnitude estimated for the 2D Iβ-nanocellulose piezoelectric response, ~pm V−1, ranks this material at the level of currently used piezoelectric energy generators and new artificial 2D designs. Such finding would be crucial for developing alternative materials to drive emerging nanotechnologies. PMID:27708364
2D microwave imaging reflectometer electronics
Spear, A. G.; Domier, C. W. Hu, X.; Muscatello, C. M.; Ren, X.; Luhmann, N. C.; Tobias, B. J.
2014-11-15
A 2D microwave imaging reflectometer system has been developed to visualize electron density fluctuations on the DIII-D tokamak. Simultaneously illuminated at four probe frequencies, large aperture optics image reflections from four density-dependent cutoff surfaces in the plasma over an extended region of the DIII-D plasma. Localized density fluctuations in the vicinity of the plasma cutoff surfaces modulate the plasma reflections, yielding a 2D image of electron density fluctuations. Details are presented of the receiver down conversion electronics that generate the in-phase (I) and quadrature (Q) reflectometer signals from which 2D density fluctuation data are obtained. Also presented are details on the control system and backplane used to manage the electronics as well as an introduction to the computer based control program.
Optical modulators with 2D layered materials
NASA Astrophysics Data System (ADS)
Sun, Zhipei; Martinez, Amos; Wang, Feng
2016-04-01
Light modulation is an essential operation in photonics and optoelectronics. With existing and emerging technologies increasingly demanding compact, efficient, fast and broadband optical modulators, high-performance light modulation solutions are becoming indispensable. The recent realization that 2D layered materials could modulate light with superior performance has prompted intense research and significant advances, paving the way for realistic applications. In this Review, we cover the state of the art of optical modulators based on 2D materials, including graphene, transition metal dichalcogenides and black phosphorus. We discuss recent advances employing hybrid structures, such as 2D heterostructures, plasmonic structures, and silicon and fibre integrated structures. We also take a look at the future perspectives and discuss the potential of yet relatively unexplored mechanisms, such as magneto-optic and acousto-optic modulation.
Visibility of wavelet quantization noise
NASA Technical Reports Server (NTRS)
Watson, A. B.; Yang, G. Y.; Solomon, J. A.; Villasenor, J.
1997-01-01
The discrete wavelet transform (DWT) decomposes an image into bands that vary in spatial frequency and orientation. It is widely used for image compression. Measures of the visibility of DWT quantization errors are required to achieve optimal compression. Uniform quantization of a single band of coefficients results in an artifact that we call DWT uniform quantization noise; it is the sum of a lattice of random amplitude basis functions of the corresponding DWT synthesis filter. We measured visual detection thresholds for samples of DWT uniform quantization noise in Y, Cb, and Cr color channels. The spatial frequency of a wavelet is r 2-lambda, where r is display visual resolution in pixels/degree, and lambda is the wavelet level. Thresholds increase rapidly with wavelet spatial frequency. Thresholds also increase from Y to Cr to Cb, and with orientation from lowpass to horizontal/vertical to diagonal. We construct a mathematical model for DWT noise detection thresholds that is a function of level, orientation, and display visual resolution. This allows calculation of a "perceptually lossless" quantization matrix for which all errors are in theory below the visual threshold. The model may also be used as the basis for adaptive quantization schemes.
Wavelet library for constrained devices
NASA Astrophysics Data System (ADS)
Ehlers, Johan Hendrik; Jassim, Sabah A.
2007-04-01
The wavelet transform is a powerful tool for image and video processing, useful in a range of applications. This paper is concerned with the efficiency of a certain fast-wavelet-transform (FWT) implementation and several wavelet filters, more suitable for constrained devices. Such constraints are typically found on mobile (cell) phones or personal digital assistants (PDA). These constraints can be a combination of; limited memory, slow floating point operations (compared to integer operations, most often as a result of no hardware support) and limited local storage. Yet these devices are burdened with demanding tasks such as processing a live video or audio signal through on-board capturing sensors. In this paper we present a new wavelet software library, HeatWave, that can be used efficiently for image/video processing/analysis tasks on mobile phones and PDA's. We will demonstrate that HeatWave is suitable for realtime applications with fine control and range to suit transform demands. We shall present experimental results to substantiate these claims. Finally this library is intended to be of real use and applied, hence we considered several well known and common embedded operating system platform differences; such as a lack of common routines or functions, stack limitations, etc. This makes HeatWave suitable for a range of applications and research projects.
Interframe vector wavelet coding technique
NASA Astrophysics Data System (ADS)
Wus, John P.; Li, Weiping
1997-01-01
Wavelet coding is often used to divide an image into multi- resolution wavelet coefficients which are quantized and coded. By 'vectorizing' scalar wavelet coding and combining this with vector quantization (VQ), vector wavelet coding (VWC) can be implemented. Using a finite number of states, finite-state vector quantization (FSVQ) takes advantage of the similarity between frames by incorporating memory into the video coding system. Lattice VQ eliminates the potential mismatch that could occur using pre-trained VQ codebooks. It also eliminates the need for codebook storage in the VQ process, thereby creating a more robust coding system. Therefore, by using the VWC coding method in conjunction with the FSVQ system and lattice VQ, the formulation of a high quality very low bit rate coding systems is proposed. A coding system using a simple FSVQ system where the current state is determined by the previous channel symbol only is developed. To achieve a higher degree of compression, a tree-like FSVQ system is implemented. The groupings are done in this tree-like structure from the lower subbands to the higher subbands in order to exploit the nature of subband analysis in terms of the parent-child relationship. Class A and Class B video sequences from the MPEG-IV testing evaluations are used in the evaluation of this coding method.
Wavelet Approximation in Data Assimilation
NASA Technical Reports Server (NTRS)
Tangborn, Andrew; Atlas, Robert (Technical Monitor)
2002-01-01
Estimation of the state of the atmosphere with the Kalman filter remains a distant goal because of high computational cost of evolving the error covariance for both linear and nonlinear systems. Wavelet approximation is presented here as a possible solution that efficiently compresses both global and local covariance information. We demonstrate the compression characteristics on the the error correlation field from a global two-dimensional chemical constituent assimilation, and implement an adaptive wavelet approximation scheme on the assimilation of the one-dimensional Burger's equation. In the former problem, we show that 99%, of the error correlation can be represented by just 3% of the wavelet coefficients, with good representation of localized features. In the Burger's equation assimilation, the discrete linearized equations (tangent linear model) and analysis covariance are projected onto a wavelet basis and truncated to just 6%, of the coefficients. A nearly optimal forecast is achieved and we show that errors due to truncation of the dynamics are no greater than the errors due to covariance truncation.
Inkjet printing of 2D layered materials.
Li, Jiantong; Lemme, Max C; Östling, Mikael
2014-11-10
Inkjet printing of 2D layered materials, such as graphene and MoS2, has attracted great interests for emerging electronics. However, incompatible rheology, low concentration, severe aggregation and toxicity of solvents constitute critical challenges which hamper the manufacturing efficiency and product quality. Here, we introduce a simple and general technology concept (distillation-assisted solvent exchange) to efficiently overcome these challenges. By implementing the concept, we have demonstrated excellent jetting performance, ideal printing patterns and a variety of promising applications for inkjet printing of 2D layered materials. PMID:25169938
Inkjet printing of 2D layered materials.
Li, Jiantong; Lemme, Max C; Östling, Mikael
2014-11-10
Inkjet printing of 2D layered materials, such as graphene and MoS2, has attracted great interests for emerging electronics. However, incompatible rheology, low concentration, severe aggregation and toxicity of solvents constitute critical challenges which hamper the manufacturing efficiency and product quality. Here, we introduce a simple and general technology concept (distillation-assisted solvent exchange) to efficiently overcome these challenges. By implementing the concept, we have demonstrated excellent jetting performance, ideal printing patterns and a variety of promising applications for inkjet printing of 2D layered materials.
KPLS-RWBFNN model for MFL 2D defect profile reconstruction
NASA Astrophysics Data System (ADS)
Xu, Chao; Wang, Changlong; Ji, Fengzhu
2013-03-01
Kernel partial least squares (KPLS) is normally very efficient for tackling nonlinear systems by mapping an original input space into a high-dimensional feature space and creating a linear PLS model in the feature space. Unlike other nonlinear PLS techniques, KPLS does not entail any nonlinear optimisation procedures. However, due to the linear inner model of PLS, KPLS is still inappropriate for describing the significant nonlinear characteristic data structure while dealing with complex physical systems in practical situations. Under this circumstance, radial wavelet basic function neural network (RWBFNN) can replace the linear inner model of PLS in the nonlinear kernel-based algorithm. Thus, KPLS-RWBFNN model is proposed in this paper and applied to multi-resolution approximation reconstruction of 2D defect profiles in magnetic flux leakage testing. The reconstructions of 2D defect profiles by this method are implemented, and the comparisons among reconstructions by KPLS, RWBFNN and the proposed approach are also undertaken. Meanwhile, the reconstructions of 2D defects by RWBFNN and the proposed approach at different SNR are also executed. The results indicate that KPLS-RWBFNN model could simplify the structure of the network while holding well-behaved generalisation and multi-resolution approximation and predict the 2D defect profiles accurately and rapidly with good robustness.
Defect Dynamics in Active 2D Nematic Liquid Crystals
NASA Astrophysics Data System (ADS)
Decamp, Stephen; Redner, Gabriel; Hagan, Michael; Dogic, Zvonimir
2014-03-01
Active materials are assemblies of animate, energy-consuming objects that exhibit continuous dynamics. As such, they have properties that are dramatically different from those found in conventional materials made of inanimate objects. We present a 2D active nematic liquid crystal composed of bundled microtubules and kinesin motor proteins that exists in a dynamic steady-state far from equilibrium. The active nematic exhibits spontaneous binding and unbinding of charge +1/2 and -1/2 disclination defects as well as streaming of +1/2 defects. By tuning ATP concentration, we precisely control the amount of activity, a key parameter of the system. We characterize the dynamics of streaming defects on a large, flat, 2D interface using quantitative polarization light microscopy. We report fundamental characteristics of the active nematics such as defect velocities, defect creation and annihilation rates, and emergent length scales in the system.
Parallel stitching of 2D materials
Ling, Xi; Wu, Lijun; Lin, Yuxuan; Ma, Qiong; Wang, Ziqiang; Song, Yi; Yu, Lili; Huang, Shengxi; Fang, Wenjing; Zhang, Xu; et al
2016-01-27
Diverse parallel stitched 2D heterostructures, including metal–semiconductor, semiconductor–semiconductor, and insulator–semiconductor, are synthesized directly through selective “sowing” of aromatic molecules as the seeds in the chemical vapor deposition (CVD) method. Lastly, the methodology enables the large-scale fabrication of lateral heterostructures, which offers tremendous potential for its application in integrated circuits.
Parallel Stitching of 2D Materials.
Ling, Xi; Lin, Yuxuan; Ma, Qiong; Wang, Ziqiang; Song, Yi; Yu, Lili; Huang, Shengxi; Fang, Wenjing; Zhang, Xu; Hsu, Allen L; Bie, Yaqing; Lee, Yi-Hsien; Zhu, Yimei; Wu, Lijun; Li, Ju; Jarillo-Herrero, Pablo; Dresselhaus, Mildred; Palacios, Tomás; Kong, Jing
2016-03-23
Diverse parallel stitched 2D heterostructures, including metal-semiconductor, semiconductor-semiconductor, and insulator-semiconductor, are synthesized directly through selective "sowing" of aromatic molecules as the seeds in the chemical vapor deposition (CVD) method. The methodology enables the large-scale fabrication of lateral heterostructures, which offers tremendous potential for its application in integrated circuits.
Modelling Elastic Media With Arbitrary Shapes Using the Wavelet Transform
NASA Astrophysics Data System (ADS)
Rosa, J. W.; Cardoso, F. A.; Rosa, J. W.; Aki, K.
2004-12-01
We extend the new method proposed by Rosa et al. (2001) for the study of elastic bodies with complete arbitrary shapes. The method was originally developed for modelling 2-D elastic media with the application of the wavelet transform, and was extended to cases where discontinuities simulated geologic faults between two different elastic media. In addition to extending the method for the study of bodies with complete arbitrary shapes, we also test new transforms with the objective of making the related matrices more compact, which are also applied to the most general case of the method. The basic method consists of the discretization of the polynomial expansion for the boundary conditions of the 2-D problem involving the stress and strain relations for the media. This parameterization leads to a system of linear equations that should be solved for the determination of the expansion coefficients, which are the model parameters, and their determination leads to the solution of the problem. Despite the fact that the media we studied originally were 2-D bodies, the result of the application of this new method can be viewed as an approximate solution to some specific 3-D problems. Among the motivations for developing this method are possible geological applications (that is, the study of tectonic plates and geologic faults) and simulations of the elastic behaviour of materials in several other fields of science. The wavelet transform is applied with two main objectives, namely to decrease the error related to the truncation of the polynomial expansion and to make the system of linear equations more compact for computation. Having validated this method for the original 2-D elastic media, we plan that this extension to elastic bodies with complete arbitrary shapes will enable it to be even more attractive for modelling real media. Reference Rosa, J. W. C., F. A. C. M. Cardoso, K. Aki, H. S. Malvar, F. A. V. Artola, and J. W. C. Rosa, Modelling elastic media with the
Non-stationary dynamics in the bouncing ball: A wavelet perspective
Behera, Abhinna K. Panigrahi, Prasanta K.; Sekar Iyengar, A. N.
2014-12-01
The non-stationary dynamics of a bouncing ball, comprising both periodic as well as chaotic behavior, is studied through wavelet transform. The multi-scale characterization of the time series displays clear signatures of self-similarity, complex scaling behavior, and periodicity. Self-similar behavior is quantified by the generalized Hurst exponent, obtained through both wavelet based multi-fractal detrended fluctuation analysis and Fourier methods. The scale dependent variable window size of the wavelets aptly captures both the transients and non-stationary periodic behavior, including the phase synchronization of different modes. The optimal time-frequency localization of the continuous Morlet wavelet is found to delineate the scales corresponding to neutral turbulence, viscous dissipation regions, and different time varying periodic modulations.
A new approach for crop identification with wavelet variance and JM distance.
Qiu, Bingwen; Fan, Zhanling; Zhong, Ming; Tang, Zhenghong; Chen, Chongcheng
2014-11-01
This paper develops a new crop mapping method through combined utilization of both time and frequency information based on wavelet variance and Jeffries-Matusita (JM) distance (CIWJ for short). A two-dimensional wavelet spectrum was obtained from datasets of daily continuous vegetation indices through a continuous wavelet transform using the Mexican hat and the Morlet mother wavelets. The time-average wavelet variance (TAWV) and the scale-average wavelet variance (SAWV) were then calculated based on the wavelet spectrum of the Mexican hat and the Morlet wavelet, respectively. The class separability based on the JM distance was evaluated to discriminate the proper period or scale range applied. Finally, a procedure for criteria quantification was developed using the TAWV and SAWV as the major metrics, and the similarity between unclassified pixels and established land use/cover types was calculated. The proposed CIWJ method was applied to the middle Hexi Corridor in northwest China using 250-m 8-day composite moderate-resolution imaging spectroradiometer (MODIS) enhanced vegetation index (EVI) time series datasets in 2012. The CIWJ method was shown to be efficient in crop field mapping, with an overall accuracy of 83.6 % and kappa coefficient of 0.7009, assessed with 30 m Chinese Environmental Disaster Reduction Satellite (HJ-1)-derived data. Compared with methods utilizing information on either frequency or time, the CIWJ method demonstrates tremendous potential for efficient crop mapping and for further applications. This method could be applied to either coarse or high spatial resolution images for agricultural crop identification, as well as other more general or specific land use classifications.
Application of 2D Non-Graphene Materials and 2D Oxide Nanostructures for Biosensing Technology
Shavanova, Kateryna; Bakakina, Yulia; Burkova, Inna; Shtepliuk, Ivan; Viter, Roman; Ubelis, Arnolds; Beni, Valerio; Starodub, Nickolaj; Yakimova, Rositsa; Khranovskyy, Volodymyr
2016-01-01
The discovery of graphene and its unique properties has inspired researchers to try to invent other two-dimensional (2D) materials. After considerable research effort, a distinct “beyond graphene” domain has been established, comprising the library of non-graphene 2D materials. It is significant that some 2D non-graphene materials possess solid advantages over their predecessor, such as having a direct band gap, and therefore are highly promising for a number of applications. These applications are not limited to nano- and opto-electronics, but have a strong potential in biosensing technologies, as one example. However, since most of the 2D non-graphene materials have been newly discovered, most of the research efforts are concentrated on material synthesis and the investigation of the properties of the material. Applications of 2D non-graphene materials are still at the embryonic stage, and the integration of 2D non-graphene materials into devices is scarcely reported. However, in recent years, numerous reports have blossomed about 2D material-based biosensors, evidencing the growing potential of 2D non-graphene materials for biosensing applications. This review highlights the recent progress in research on the potential of using 2D non-graphene materials and similar oxide nanostructures for different types of biosensors (optical and electrochemical). A wide range of biological targets, such as glucose, dopamine, cortisol, DNA, IgG, bisphenol, ascorbic acid, cytochrome and estradiol, has been reported to be successfully detected by biosensors with transducers made of 2D non-graphene materials. PMID:26861346
Application of 2D Non-Graphene Materials and 2D Oxide Nanostructures for Biosensing Technology.
Shavanova, Kateryna; Bakakina, Yulia; Burkova, Inna; Shtepliuk, Ivan; Viter, Roman; Ubelis, Arnolds; Beni, Valerio; Starodub, Nickolaj; Yakimova, Rositsa; Khranovskyy, Volodymyr
2016-01-01
The discovery of graphene and its unique properties has inspired researchers to try to invent other two-dimensional (2D) materials. After considerable research effort, a distinct "beyond graphene" domain has been established, comprising the library of non-graphene 2D materials. It is significant that some 2D non-graphene materials possess solid advantages over their predecessor, such as having a direct band gap, and therefore are highly promising for a number of applications. These applications are not limited to nano- and opto-electronics, but have a strong potential in biosensing technologies, as one example. However, since most of the 2D non-graphene materials have been newly discovered, most of the research efforts are concentrated on material synthesis and the investigation of the properties of the material. Applications of 2D non-graphene materials are still at the embryonic stage, and the integration of 2D non-graphene materials into devices is scarcely reported. However, in recent years, numerous reports have blossomed about 2D material-based biosensors, evidencing the growing potential of 2D non-graphene materials for biosensing applications. This review highlights the recent progress in research on the potential of using 2D non-graphene materials and similar oxide nanostructures for different types of biosensors (optical and electrochemical). A wide range of biological targets, such as glucose, dopamine, cortisol, DNA, IgG, bisphenol, ascorbic acid, cytochrome and estradiol, has been reported to be successfully detected by biosensors with transducers made of 2D non-graphene materials.
NASA Astrophysics Data System (ADS)
Ng, J.; Kingsbury, N. G.
2004-02-01
This book provides an overview of the theory and practice of continuous and discrete wavelet transforms. Divided into seven chapters, the first three chapters of the book are introductory, describing the various forms of the wavelet transform and their computation, while the remaining chapters are devoted to applications in fluids, engineering, medicine and miscellaneous areas. Each chapter is well introduced, with suitable examples to demonstrate key concepts. Illustrations are included where appropriate, thus adding a visual dimension to the text. A noteworthy feature is the inclusion, at the end of each chapter, of a list of further resources from the academic literature which the interested reader can consult. The first chapter is purely an introduction to the text. The treatment of wavelet transforms begins in the second chapter, with the definition of what a wavelet is. The chapter continues by defining the continuous wavelet transform and its inverse and a description of how it may be used to interrogate signals. The continuous wavelet transform is then compared to the short-time Fourier transform. Energy and power spectra with respect to scale are also discussed and linked to their frequency counterparts. Towards the end of the chapter, the two-dimensional continuous wavelet transform is introduced. Examples of how the continuous wavelet transform is computed using the Mexican hat and Morlet wavelets are provided throughout. The third chapter introduces the discrete wavelet transform, with its distinction from the discretized continuous wavelet transform having been made clear at the end of the second chapter. In the first half of the chapter, the logarithmic discretization of the wavelet function is described, leading to a discussion of dyadic grid scaling, frames, orthogonal and orthonormal bases, scaling functions and multiresolution representation. The fast wavelet transform is introduced and its computation is illustrated with an example using the Haar
Iterated oversampled filter banks and wavelet frames
NASA Astrophysics Data System (ADS)
Selesnick, Ivan W.; Sendur, Levent
2000-12-01
This paper takes up the design of wavelet tight frames that are analogous to Daubechies orthonormal wavelets - that is, the design of minimal length wavelet filters satisfying certain polynomial properties, but now in the oversampled case. The oversampled dyadic DWT considered in this paper is based on a single scaling function and tow distinct wavelets. Having more wavelets than necessary gives a closer spacing between adjacent wavelets within the same scale. As a result, the transform is nearly shift-invariant, and can be used to improve denoising. Because the associated time- frequency lattice preserves the dyadic structure of the critically sampled DWT it can be used with tree-based denoising algorithms that exploit parent-child correlation.
Fusion of digital breast tomosynthesis images via wavelet synthesis for improved lesion conspicuity
NASA Astrophysics Data System (ADS)
Hariharan, Harishwaran; Pomponiu, Victor; Zheng, Bin; Whiting, Bruce; Gur, David
2014-03-01
Full-field digital mammography (FFDM) is the most common screening procedure for detecting early breast cancer. However, due to complications such as overlapping breast tissue in projection images, the efficacy of FFDM reading is reduced. Recent studies have shown that digital breast tomosynthesis (DBT), in combination with FFDM, increases detection sensitivity considerably while decreasing false-positive, recall rates. There is a huge interest in creating diagnostically accurate 2-D interpretations from the DBT slices. Most of the 2-D syntheses rely on visualizing the maximum intensities (brightness) from each slice through different methods. We propose a wavelet based fusion method, where we focus on preserving holistic information from larger structures such as masses while adding high frequency information that is relevant and helpful for diagnosis. This method enables the spatial generation of a 2D image from a series of DBT images, each of which contains both smooth and coarse structures distributed in the wavelet domain. We believe that the wavelet-synthesized images, generated from their DBT image datasets, provide radiologists with improved lesion and micro-calcification conspicuity as compared with FFDM images. The potential impact of this fusion method is (1) Conception of a device-independent, data-driven modality that increases the conspicuity of lesions, thereby facilitating early detection and potentially reducing recall rates; (2) Reduction of the accompanying radiation dose to the patient.
Improving 3D Wavelet-Based Compression of Hyperspectral Images
NASA Technical Reports Server (NTRS)
Klimesh, Matthew; Kiely, Aaron; Xie, Hua; Aranki, Nazeeh
2009-01-01
Two methods of increasing the effectiveness of three-dimensional (3D) wavelet-based compression of hyperspectral images have been developed. (As used here, images signifies both images and digital data representing images.) The methods are oriented toward reducing or eliminating detrimental effects of a phenomenon, referred to as spectral ringing, that is described below. In 3D wavelet-based compression, an image is represented by a multiresolution wavelet decomposition consisting of several subbands obtained by applying wavelet transforms in the two spatial dimensions corresponding to the two spatial coordinate axes of the image plane, and by applying wavelet transforms in the spectral dimension. Spectral ringing is named after the more familiar spatial ringing (spurious spatial oscillations) that can be seen parallel to and near edges in ordinary images reconstructed from compressed data. These ringing phenomena are attributable to effects of quantization. In hyperspectral data, the individual spectral bands play the role of edges, causing spurious oscillations to occur in the spectral dimension. In the absence of such corrective measures as the present two methods, spectral ringing can manifest itself as systematic biases in some reconstructed spectral bands and can reduce the effectiveness of compression of spatially-low-pass subbands. One of the two methods is denoted mean subtraction. The basic idea of this method is to subtract mean values from spatial planes of spatially low-pass subbands prior to encoding, because (a) such spatial planes often have mean values that are far from zero and (b) zero-mean data are better suited for compression by methods that are effective for subbands of two-dimensional (2D) images. In this method, after the 3D wavelet decomposition is performed, mean values are computed for and subtracted from each spatial plane of each spatially-low-pass subband. The resulting data are converted to sign-magnitude form and compressed in a
Wavelet analysis in two-dimensional tomography
NASA Astrophysics Data System (ADS)
Burkovets, Dimitry N.
2002-02-01
The diagnostic possibilities of wavelet-analysis of coherent images of connective tissue in its pathological changes diagnostics. The effectiveness of polarization selection in obtaining wavelet-coefficients' images is also shown. The wavelet structures, characterizing the process of skin psoriasis, bone-tissue osteoporosis have been analyzed. The histological sections of physiological normal and pathologically changed samples of connective tissue of human skin and spongy bone tissue have been analyzed.
Wavelet analysis of epileptic spikes
NASA Astrophysics Data System (ADS)
Latka, Miroslaw; Was, Ziemowit; Kozik, Andrzej; West, Bruce J.
2003-05-01
Interictal spikes and sharp waves in human EEG are characteristic signatures of epilepsy. These potentials originate as a result of synchronous pathological discharge of many neurons. The reliable detection of such potentials has been the long standing problem in EEG analysis, especially after long-term monitoring became common in investigation of epileptic patients. The traditional definition of a spike is based on its amplitude, duration, sharpness, and emergence from its background. However, spike detection systems built solely around this definition are not reliable due to the presence of numerous transients and artifacts. We use wavelet transform to analyze the properties of EEG manifestations of epilepsy. We demonstrate that the behavior of wavelet transform of epileptic spikes across scales can constitute the foundation of a relatively simple yet effective detection algorithm.
Stochastic Inversion of 2D Magnetotelluric Data
Chen, Jinsong
2010-07-01
The algorithm is developed to invert 2D magnetotelluric (MT) data based on sharp boundary parametrization using a Bayesian framework. Within the algorithm, we consider the locations and the resistivity of regions formed by the interfaces are as unknowns. We use a parallel, adaptive finite-element algorithm to forward simulate frequency-domain MT responses of 2D conductivity structure. Those unknown parameters are spatially correlated and are described by a geostatistical model. The joint posterior probability distribution function is explored by Markov Chain Monte Carlo (MCMC) sampling methods. The developed stochastic model is effective for estimating the interface locations and resistivity. Most importantly, it provides details uncertainty information on each unknown parameter. Hardware requirements: PC, Supercomputer, Multi-platform, Workstation; Software requirements C and Fortan; Operation Systems/version is Linux/Unix or Windows
Explicit 2-D Hydrodynamic FEM Program
1996-08-07
DYNA2D* is a vectorized, explicit, two-dimensional, axisymmetric and plane strain finite element program for analyzing the large deformation dynamic and hydrodynamic response of inelastic solids. DYNA2D* contains 13 material models and 9 equations of state (EOS) to cover a wide range of material behavior. The material models implemented in all machine versions are: elastic, orthotropic elastic, kinematic/isotropic elastic plasticity, thermoelastoplastic, soil and crushable foam, linear viscoelastic, rubber, high explosive burn, isotropic elastic-plastic, temperature-dependent elastic-plastic. Themore » isotropic and temperature-dependent elastic-plastic models determine only the deviatoric stresses. Pressure is determined by one of 9 equations of state including linear polynomial, JWL high explosive, Sack Tuesday high explosive, Gruneisen, ratio of polynomials, linear polynomial with energy deposition, ignition and growth of reaction in HE, tabulated compaction, and tabulated.« less
Stochastic Inversion of 2D Magnetotelluric Data
2010-07-01
The algorithm is developed to invert 2D magnetotelluric (MT) data based on sharp boundary parametrization using a Bayesian framework. Within the algorithm, we consider the locations and the resistivity of regions formed by the interfaces are as unknowns. We use a parallel, adaptive finite-element algorithm to forward simulate frequency-domain MT responses of 2D conductivity structure. Those unknown parameters are spatially correlated and are described by a geostatistical model. The joint posterior probability distribution function ismore » explored by Markov Chain Monte Carlo (MCMC) sampling methods. The developed stochastic model is effective for estimating the interface locations and resistivity. Most importantly, it provides details uncertainty information on each unknown parameter. Hardware requirements: PC, Supercomputer, Multi-platform, Workstation; Software requirements C and Fortan; Operation Systems/version is Linux/Unix or Windows« less
Static & Dynamic Response of 2D Solids
1996-07-15
NIKE2D is an implicit finite-element code for analyzing the finite deformation, static and dynamic response of two-dimensional, axisymmetric, plane strain, and plane stress solids. The code is fully vectorized and available on several computing platforms. A number of material models are incorporated to simulate a wide range of material behavior including elasto-placicity, anisotropy, creep, thermal effects, and rate dependence. Slideline algorithms model gaps and sliding along material interfaces, including interface friction, penetration and single surfacemore » contact. Interactive-graphics and rezoning is included for analyses with large mesh distortions. In addition to quasi-Newton and arc-length procedures, adaptive algorithms can be defined to solve the implicit equations using the solution language ISLAND. Each of these capabilities and more make NIKE2D a robust analysis tool.« less
Static & Dynamic Response of 2D Solids
Lin, Jerry
1996-07-15
NIKE2D is an implicit finite-element code for analyzing the finite deformation, static and dynamic response of two-dimensional, axisymmetric, plane strain, and plane stress solids. The code is fully vectorized and available on several computing platforms. A number of material models are incorporated to simulate a wide range of material behavior including elasto-placicity, anisotropy, creep, thermal effects, and rate dependence. Slideline algorithms model gaps and sliding along material interfaces, including interface friction, penetration and single surface contact. Interactive-graphics and rezoning is included for analyses with large mesh distortions. In addition to quasi-Newton and arc-length procedures, adaptive algorithms can be defined to solve the implicit equations using the solution language ISLAND. Each of these capabilities and more make NIKE2D a robust analysis tool.
Explicit 2-D Hydrodynamic FEM Program
Lin, Jerry
1996-08-07
DYNA2D* is a vectorized, explicit, two-dimensional, axisymmetric and plane strain finite element program for analyzing the large deformation dynamic and hydrodynamic response of inelastic solids. DYNA2D* contains 13 material models and 9 equations of state (EOS) to cover a wide range of material behavior. The material models implemented in all machine versions are: elastic, orthotropic elastic, kinematic/isotropic elastic plasticity, thermoelastoplastic, soil and crushable foam, linear viscoelastic, rubber, high explosive burn, isotropic elastic-plastic, temperature-dependent elastic-plastic. The isotropic and temperature-dependent elastic-plastic models determine only the deviatoric stresses. Pressure is determined by one of 9 equations of state including linear polynomial, JWL high explosive, Sack Tuesday high explosive, Gruneisen, ratio of polynomials, linear polynomial with energy deposition, ignition and growth of reaction in HE, tabulated compaction, and tabulated.
2D photonic-crystal optomechanical nanoresonator.
Makles, K; Antoni, T; Kuhn, A G; Deléglise, S; Briant, T; Cohadon, P-F; Braive, R; Beaudoin, G; Pinard, L; Michel, C; Dolique, V; Flaminio, R; Cagnoli, G; Robert-Philip, I; Heidmann, A
2015-01-15
We present the optical optimization of an optomechanical device based on a suspended InP membrane patterned with a 2D near-wavelength grating (NWG) based on a 2D photonic-crystal geometry. We first identify by numerical simulation a set of geometrical parameters providing a reflectivity higher than 99.8% over a 50-nm span. We then study the limitations induced by the finite value of the optical waist and lateral size of the NWG pattern using different numerical approaches. The NWG grating, pierced in a suspended InP 265-nm thick membrane, is used to form a compact microcavity involving the suspended nanomembrane as an end mirror. The resulting cavity has a waist size smaller than 10 μm and a finesse in the 200 range. It is used to probe the Brownian motion of the mechanical modes of the nanomembrane. PMID:25679837
Compact 2-D graphical representation of DNA
NASA Astrophysics Data System (ADS)
Randić, Milan; Vračko, Marjan; Zupan, Jure; Novič, Marjana
2003-05-01
We present a novel 2-D graphical representation for DNA sequences which has an important advantage over the existing graphical representations of DNA in being very compact. It is based on: (1) use of binary labels for the four nucleic acid bases, and (2) use of the 'worm' curve as template on which binary codes are placed. The approach is illustrated on DNA sequences of the first exon of human β-globin and gorilla β-globin.
2D materials: Graphene and others
NASA Astrophysics Data System (ADS)
Bansal, Suneev Anil; Singh, Amrinder Pal; Kumar, Suresh
2016-05-01
Present report reviews the recent advancements in new atomically thick 2D materials. Materials covered in this review are Graphene, Silicene, Germanene, Boron Nitride (BN) and Transition metal chalcogenides (TMC). These materials show extraordinary mechanical, electronic and optical properties which make them suitable candidates for future applications. Apart from unique properties, tune-ability of highly desirable properties of these materials is also an important area to be emphasized on.
Layer Engineering of 2D Semiconductor Junctions.
He, Yongmin; Sobhani, Ali; Lei, Sidong; Zhang, Zhuhua; Gong, Yongji; Jin, Zehua; Zhou, Wu; Yang, Yingchao; Zhang, Yuan; Wang, Xifan; Yakobson, Boris; Vajtai, Robert; Halas, Naomi J; Li, Bo; Xie, Erqing; Ajayan, Pulickel
2016-07-01
A new concept for junction fabrication by connecting multiple regions with varying layer thicknesses, based on the thickness dependence, is demonstrated. This type of junction is only possible in super-thin-layered 2D materials, and exhibits similar characteristics as p-n junctions. Rectification and photovoltaic effects are observed in chemically homogeneous MoSe2 junctions between domains of different thicknesses. PMID:27136275
Realistic and efficient 2D crack simulation
NASA Astrophysics Data System (ADS)
Yadegar, Jacob; Liu, Xiaoqing; Singh, Abhishek
2010-04-01
Although numerical algorithms for 2D crack simulation have been studied in Modeling and Simulation (M&S) and computer graphics for decades, realism and computational efficiency are still major challenges. In this paper, we introduce a high-fidelity, scalable, adaptive and efficient/runtime 2D crack/fracture simulation system by applying the mathematically elegant Peano-Cesaro triangular meshing/remeshing technique to model the generation of shards/fragments. The recursive fractal sweep associated with the Peano-Cesaro triangulation provides efficient local multi-resolution refinement to any level-of-detail. The generated binary decomposition tree also provides efficient neighbor retrieval mechanism used for mesh element splitting and merging with minimal memory requirements essential for realistic 2D fragment formation. Upon load impact/contact/penetration, a number of factors including impact angle, impact energy, and material properties are all taken into account to produce the criteria of crack initialization, propagation, and termination leading to realistic fractal-like rubble/fragments formation. The aforementioned parameters are used as variables of probabilistic models of cracks/shards formation, making the proposed solution highly adaptive by allowing machine learning mechanisms learn the optimal values for the variables/parameters based on prior benchmark data generated by off-line physics based simulation solutions that produce accurate fractures/shards though at highly non-real time paste. Crack/fracture simulation has been conducted on various load impacts with different initial locations at various impulse scales. The simulation results demonstrate that the proposed system has the capability to realistically and efficiently simulate 2D crack phenomena (such as window shattering and shards generation) with diverse potentials in military and civil M&S applications such as training and mission planning.
2D Spinodal Decomposition in Forced Turbulence
NASA Astrophysics Data System (ADS)
Fan, Xiang; Diamond, Patrick; Chacon, Luis; Li, Hui
2015-11-01
Spinodal decomposition is a second order phase transition for binary fluid mixture, from one thermodynamic phase to form two coexisting phases. The governing equation for this coarsening process below critical temperature, Cahn-Hilliard Equation, is very similar to 2D MHD Equation, especially the conserved quantities have a close correspondence between each other, so theories for MHD turbulence are used to study spinodal decomposition in forced turbulence. Domain size is increased with time along with the inverse cascade, and the length scale can be arrested by a forced turbulence with direct cascade. The two competing mechanisms lead to a stabilized domain size length scale, which can be characterized by Hinze Scale. The 2D spinodal decomposition in forced turbulence is studied by both theory and simulation with ``pixie2d.'' This work focuses on the relation between Hinze scale and spectra and cascades. Similarities and differences between spinodal decomposition and MHD are investigated. Also some transport properties are studied following MHD theories. This work is supported by the Department of Energy under Award Number DE-FG02-04ER54738.
MAGNUM-2D computer code: user's guide
England, R.L.; Kline, N.W.; Ekblad, K.J.; Baca, R.G.
1985-01-01
Information relevant to the general use of the MAGNUM-2D computer code is presented. This computer code was developed for the purpose of modeling (i.e., simulating) the thermal and hydraulic conditions in the vicinity of a waste package emplaced in a deep geologic repository. The MAGNUM-2D computer computes (1) the temperature field surrounding the waste package as a function of the heat generation rate of the nuclear waste and thermal properties of the basalt and (2) the hydraulic head distribution and associated groundwater flow fields as a function of the temperature gradients and hydraulic properties of the basalt. MAGNUM-2D is a two-dimensional numerical model for transient or steady-state analysis of coupled heat transfer and groundwater flow in a fractured porous medium. The governing equations consist of a set of coupled, quasi-linear partial differential equations that are solved using a Galerkin finite-element technique. A Newton-Raphson algorithm is embedded in the Galerkin functional to formulate the problem in terms of the incremental changes in the dependent variables. Both triangular and quadrilateral finite elements are used to represent the continuum portions of the spatial domain. Line elements may be used to represent discrete conduits. 18 refs., 4 figs., 1 tab.
Engineering light outcoupling in 2D materials.
Lien, Der-Hsien; Kang, Jeong Seuk; Amani, Matin; Chen, Kevin; Tosun, Mahmut; Wang, Hsin-Ping; Roy, Tania; Eggleston, Michael S; Wu, Ming C; Dubey, Madan; Lee, Si-Chen; He, Jr-Hau; Javey, Ali
2015-02-11
When light is incident on 2D transition metal dichalcogenides (TMDCs), it engages in multiple reflections within underlying substrates, producing interferences that lead to enhancement or attenuation of the incoming and outgoing strength of light. Here, we report a simple method to engineer the light outcoupling in semiconducting TMDCs by modulating their dielectric surroundings. We show that by modulating the thicknesses of underlying substrates and capping layers, the interference caused by substrate can significantly enhance the light absorption and emission of WSe2, resulting in a ∼11 times increase in Raman signal and a ∼30 times increase in the photoluminescence (PL) intensity of WSe2. On the basis of the interference model, we also propose a strategy to control the photonic and optoelectronic properties of thin-layer WSe2. This work demonstrates the utilization of outcoupling engineering in 2D materials and offers a new route toward the realization of novel optoelectronic devices, such as 2D LEDs and solar cells.
Haar Wavelet Analysis of Climatic Time Series
NASA Astrophysics Data System (ADS)
Zhang, Zhihua; Moore, John; Grinsted, Aslak
2014-05-01
In order to extract the intrinsic information of climatic time series from background red noise, we will first give an analytic formula on the distribution of Haar wavelet power spectra of red noise in a rigorous statistical framework. The relation between scale aand Fourier period T for the Morlet wavelet is a= 0.97T . However, for Haar wavelet, the corresponding formula is a= 0.37T . Since for any time series of time step δt and total length Nδt, the range of scales is from the smallest resolvable scale 2δt to the largest scale Nδt in wavelet-based time series analysis, by using the Haar wavelet analysis, one can extract more low frequency intrinsic information. Finally, we use our method to analyze Arctic Oscillation which is a key aspect of climate variability in the Northern Hemisphere, and discover a great change in fundamental properties of the AO,-commonly called a regime shift or tripping point. Our partial results have been published as follows: [1] Z. Zhang, J.C. Moore and A. Grinsted, Haar wavelet analysis of climatic time series, Int. J. Wavelets, Multiresol. & Inf. Process., in press, 2013 [2] Z. Zhang, J.C. Moore, Comment on "Significance tests for the wavelet power and the wavelet power spectrum", Ann. Geophys., 30:12, 2012
Entangled Husimi Distribution and Complex Wavelet Transformation
NASA Astrophysics Data System (ADS)
Hu, Li-Yun; Fan, Hong-Yi
2010-05-01
Similar in spirit to the preceding work (Int. J. Theor. Phys. 48:1539, 2009) where the relationship between wavelet transformation and Husimi distribution function is revealed, we study this kind of relationship to the entangled case. We find that the optical complex wavelet transformation can be used to study the entangled Husimi distribution function in phase space theory of quantum optics. We prove that, up to a Gaussian function, the entangled Husimi distribution function of a two-mode quantum state | ψ> is just the modulus square of the complex wavelet transform of e^{-\\vert η \\vert 2/2} with ψ( η) being the mother wavelet.
Wavelet Sparse Approximate Inverse Preconditioners
NASA Technical Reports Server (NTRS)
Chan, Tony F.; Tang, W.-P.; Wan, W. L.
1996-01-01
There is an increasing interest in using sparse approximate inverses as preconditioners for Krylov subspace iterative methods. Recent studies of Grote and Huckle and Chow and Saad also show that sparse approximate inverse preconditioner can be effective for a variety of matrices, e.g. Harwell-Boeing collections. Nonetheless a drawback is that it requires rapid decay of the inverse entries so that sparse approximate inverse is possible. However, for the class of matrices that, come from elliptic PDE problems, this assumption may not necessarily hold. Our main idea is to look for a basis, other than the standard one, such that a sparse representation of the inverse is feasible. A crucial observation is that the kind of matrices we are interested in typically have a piecewise smooth inverse. We exploit this fact, by applying wavelet techniques to construct a better sparse approximate inverse in the wavelet basis. We shall justify theoretically and numerically that our approach is effective for matrices with smooth inverse. We emphasize that in this paper we have only presented the idea of wavelet approximate inverses and demonstrated its potential but have not yet developed a highly refined and efficient algorithm.
Visibility of Wavelet Quantization Noise
NASA Technical Reports Server (NTRS)
Watson, Andrew B.; Yang, Gloria Y.; Solomon, Joshua A.; Villasenor, John; Null, Cynthia H. (Technical Monitor)
1995-01-01
The Discrete Wavelet Transform (DWT) decomposes an image into bands that vary in spatial frequency and orientation. It is widely used for image compression. Measures of the visibility of DWT quantization errors are required to achieve optimal compression. Uniform quantization of a single band of coefficients results in an artifact that is the sum of a lattice of random amplitude basis functions of the corresponding DWT synthesis filter, which we call DWT uniform quantization noise. We measured visual detection thresholds for samples of DWT uniform quantization noise in Y, Cb, and Cr color channels. The spatial frequency of a wavelet is r 2(exp)-L , where r is display visual resolution in pixels/degree, and L is the wavelet level. Amplitude thresholds increase rapidly with spatial frequency. Thresholds also increase from Y to Cr to Cb, and with orientation from low-pass to horizontal/vertical to diagonal. We describe a mathematical model to predict DWT noise detection thresholds as a function of level, orientation, and display visual resolution. This allows calculation of a "perceptually lossless" quantization matrix for which all errors are in theory below the visual threshold. The model may also be used as the basis for adaptive quantization schemes.
Independent component analysis (ICA) using wavelet subband orthogonality
NASA Astrophysics Data System (ADS)
Szu, Harold H.; Hsu, Charles C.; Yamakawa, Takeshi
1998-03-01
There are two kinds of RRP: (1) invertible ones, such as global Fourier transform (FT), local wavelet transform (WT), and adaptive wavelet transform (AWT); and (2) non-invertible ones, e.g. ICA including the global principle component analysis (PCA). The invertible FT and WT can be related to the non-invertible ICA when the continuous transforms are approximate din discrete matrix-vector operations. The landmark accomplishment of ICA is to obtain, by unsupervised learning algorithm, the edge-map as image feature ayields, shown by Helsinki researchers using fourth order statistics of nyields -- Kurosis K(uyields), and derived from information- theoretical first principle is augmented by the orthogonality property of the DWT subband used necessarily for usual image compression. If we take the advantage of the subband decorrelation, we have potentially an efficient utilization of a pari of communication channels if we could send several more mixed subband images through the pair of channels.
Filtering of the Radon transform to enhance linear signal features via wavelet pyramid decomposition
NASA Astrophysics Data System (ADS)
Meckley, John R.
1995-09-01
The information content in many signal processing applications can be reduced to a set of linear features in a 2D signal transform. Examples include the narrowband lines in a spectrogram, ship wakes in a synthetic aperture radar image, and blood vessels in a medical computer-aided tomography scan. The line integrals that generate the values of the projections of the Radon transform can be characterized as a bank of matched filters for linear features. This localization of energy in the Radon transform for linear features can be exploited to enhance these features and to reduce noise by filtering the Radon transform with a filter explicitly designed to pass only linear features, and then reconstructing a new 2D signal by inverting the new filtered Radon transform (i.e., via filtered backprojection). Previously used methods for filtering the Radon transform include Fourier based filtering (a 2D elliptical Gaussian linear filter) and a nonlinear filter ((Radon xfrm)**y with y >= 2.0). Both of these techniques suffer from the mismatch of the filter response to the true functional form of the Radon transform of a line. The Radon transform of a line is not a point but is a function of the Radon variables (rho, theta) and the total line energy. This mismatch leads to artifacts in the reconstructed image and a reduction in achievable processing gain. The Radon transform for a line is computed as a function of angle and offset (rho, theta) and the line length. The 2D wavelet coefficients are then compared for the Haar wavelets and the Daubechies wavelets. These filter responses are used as frequency filters for the Radon transform. The filtering is performed on the wavelet pyramid decomposition of the Radon transform by detecting the most likely positions of lines in the transform and then by convolving the local area with the appropriate response and zeroing the pyramid coefficients outside of the response area. The response area is defined to contain 95% of the total
Widom, Julia R.; Johnson, Neil P.; von Hippel, Peter H.; Marcus, Andrew H.
2013-01-01
We have observed the conformation-dependent electronic coupling between the monomeric subunits of a dinucleotide of 2-aminopurine (2-AP), a fluorescent analog of the nucleic acid base adenine. This was accomplished by extending two-dimensional fluorescence spectroscopy (2D FS) – a fluorescence-detected variation of 2D electronic spectroscopy – to excite molecular transitions in the ultraviolet (UV) regime. A collinear sequence of four ultrafast laser pulses centered at 323 nm was used to resonantly excite the coupled transitions of 2-AP dinucleotide. The phases of the optical pulses were continuously swept at kilohertz frequencies, and the ensuing nonlinear fluorescence was phase-synchronously detected at 370 nm. Upon optimization of a point-dipole coupling model to our data, we found that in aqueous buffer the 2-AP dinucleotide adopts an average conformation in which the purine bases are non-helically stacked (center-to-center distance R12 = 3.5 Å ± 0.5 Å, twist angle θ12 = 5° ± 5°), which differs from the conformation of such adjacent bases in duplex DNA. These experiments establish UV-2D FS as a method for examining the local conformations of an adjacent pair of fluorescent nucleotides substituted into specific DNA or RNA constructs, which will serve as a powerful probe to interpret, in structural terms, biologically significant local conformational changes within the nucleic acid framework of protein-nucleic acid complexes. PMID:24223491
NASA Astrophysics Data System (ADS)
Kushwaha, Alok Kumar Singh; Srivastava, Rajeev
2015-09-01
Moving object segmentation using change detection in wavelet domain under continuous variations of lighting condition is a challenging problem in video surveillance systems. There are several methods proposed in the literature for change detection in wavelet domain for moving object segmentation having static backgrounds, but it has not been addressed effectively for dynamic background changes. The methods proposed in the literature suffer from various problems, such as ghostlike appearance, object shadows, and noise. To deal with these issues, a framework for dynamic background modeling and shadow suppression under rapidly changing illumination conditions for moving object segmentation in complex wavelet domain is proposed. The proposed method consists of eight steps applied on given video frames, which include wavelet decomposition of frame using complex wavelet transform; use of change detection on detail coefficients (LH, HL, and HH), use of improved Gaussian mixture-based dynamic background modeling on approximate coefficient (LL subband); cast shadow suppression; use of soft thresholding for noise removal; strong edge detection; inverse wavelet transformation for reconstruction; and finally using closing morphology operator. A comparative analysis of the proposed method is presented both qualitatively and quantitatively with other standard methods available in the literature for six datasets in terms of various performance measures. Experimental results demonstrate the efficacy of the proposed method.
Estimation of the instantaneous rotation speed using complex shifted Morlet wavelets
NASA Astrophysics Data System (ADS)
Gryllias, Konstantinos C.; Antoniadis, Ioannis A.
2013-07-01
The ability of the complex continuous wavelet transform (CCWT) to provide also an estimation of the instantaneous frequency of a signal, parallel to the estimation of the instantaneous amplitude of the signal, is proposed as an approach for the estimation of the instantaneous rotation speed of machinery. Complex shifted Morlet wavelets (CSMW) present a number of advantages. The concept of shifting the Morlet wavelet in the frequency domain allows the simultaneous optimal selection of both the wavelet center frequency and the wavelet bandwidth. In this paper it is shown that the recovery of the signal frequency can be performed accurately, without the requirement that the wavelet center frequency coincides to the signal frequency. Contrarily, the accurate recovery of the signal amplitude requires additionally this last condition. The algorithm is tested on two synthetic signals and four non-stationary experimental vibration signals, in an experimental fault test rig and in a motorcycle engine. The proposed instantaneous frequency estimation approach presents very good results and in comparison to the Hilbert Transform achieves a significantly lower RMSE.
GBL-2D Version 1.0: a 2D geometry boolean library.
McBride, Cory L. (Elemental Technologies, American Fort, UT); Schmidt, Rodney Cannon; Yarberry, Victor R.; Meyers, Ray J.
2006-11-01
This report describes version 1.0 of GBL-2D, a geometric Boolean library for 2D objects. The library is written in C++ and consists of a set of classes and routines. The classes primarily represent geometric data and relationships. Classes are provided for 2D points, lines, arcs, edge uses, loops, surfaces and mask sets. The routines contain algorithms for geometric Boolean operations and utility functions. Routines are provided that incorporate the Boolean operations: Union(OR), XOR, Intersection and Difference. A variety of additional analytical geometry routines and routines for importing and exporting the data in various file formats are also provided. The GBL-2D library was originally developed as a geometric modeling engine for use with a separate software tool, called SummitView [1], that manipulates the 2D mask sets created by designers of Micro-Electro-Mechanical Systems (MEMS). However, many other practical applications for this type of software can be envisioned because the need to perform 2D Boolean operations can arise in many contexts.
A new wavelet-based thin plate element using B-spline wavelet on the interval
NASA Astrophysics Data System (ADS)
Jiawei, Xiang; Xuefeng, Chen; Zhengjia, He; Yinghong, Zhang
2008-01-01
By interacting and synchronizing wavelet theory in mathematics and variational principle in finite element method, a class of wavelet-based plate element is constructed. In the construction of wavelet-based plate element, the element displacement field represented by the coefficients of wavelet expansions in wavelet space is transformed into the physical degree of freedoms in finite element space via the corresponding two-dimensional C1 type transformation matrix. Then, based on the associated generalized function of potential energy of thin plate bending and vibration problems, the scaling functions of B-spline wavelet on the interval (BSWI) at different scale are employed directly to form the multi-scale finite element approximation basis so as to construct BSWI plate element via variational principle. BSWI plate element combines the accuracy of B-spline functions approximation and various wavelet-based elements for structural analysis. Some static and dynamic numerical examples are studied to demonstrate the performances of the present element.
Periodically sheared 2D Yukawa systems
Kovács, Anikó Zsuzsa; Hartmann, Peter; Donkó, Zoltán
2015-10-15
We present non-equilibrium molecular dynamics simulation studies on the dynamic (complex) shear viscosity of a 2D Yukawa system. We have identified a non-monotonic frequency dependence of the viscosity at high frequencies and shear rates, an energy absorption maximum (local resonance) at the Einstein frequency of the system at medium shear rates, an enhanced collective wave activity, when the excitation is near the plateau frequency of the longitudinal wave dispersion, and the emergence of significant configurational anisotropy at small frequencies and high shear rates.
ENERGY LANDSCAPE OF 2D FLUID FORMS
Y. JIANG; ET AL
2000-04-01
The equilibrium states of 2D non-coarsening fluid foams, which consist of bubbles with fixed areas, correspond to local minima of the total perimeter. (1) The authors find an approximate value of the global minimum, and determine directly from an image how far a foam is from its ground state. (2) For (small) area disorder, small bubbles tend to sort inwards and large bubbles outwards. (3) Topological charges of the same sign repel while charges of opposite sign attract. (4) They discuss boundary conditions and the uniqueness of the pattern for fixed topology.
Efficient VLSI architecture for multi-dimensional discrete wavelet transform
NASA Astrophysics Data System (ADS)
Xiong, Cheng-Yi; Tian, Jin-Wen; Liu, Jian
2005-10-01
Efficient VLSI architectures for multi-dimensional (m-D) discrete wavelet transform (DWT), e.g. m=2, 3, are presented, in which the lifting scheme of DWT is used to reduce efficiently hardware complexity. The parallelism of 2m subbands transforms in lifting-based m-D DWT is explored, which increases efficiently the throughput rate of separable m-D DWT. The proposed architecture is composed of m2m-1 1-D DWT modules working in parallel and pipelined, which is designed to process 2m input samples per clock cycle, and generate 2m subbands coefficients synchronously. The total time of computing one level of decomposition for a 2-D image (3-D image sequence) of size N2 (MN2) is approximately N2/4 (MN2/8) intra- clock cycles (ccs). An efficient line-based architecture framework for both 2D+t and t+2D 3-D DWT is first proposed. Compared with the similar works reported in previous literature, the proposed architecture has good performance in terms of production of computation time and hardware cost. The proposed architecture is simple, regular, scalable and well suited for VLSI implementation.
Group theoretical methods and wavelet theory: coorbit theory and applications
NASA Astrophysics Data System (ADS)
Feichtinger, Hans G.
2013-05-01
theory of coorbit spaces,12, 13 established by the author jointly with K. Gröchenig. Starting from an integrable and irreducible representation of some locally compact group (such as the "ax+b"-group or the Heisenberg group) one can derive families of Banach spaces having natural atomic characterizations, or alternatively a continuous transform associated to it. So at the end function spaces of locally compact groups come into play, and their generic properties help to explain why and how it is possible to obtain (nonorthogonal) decompositions. While unification of these two groups was one important aspect of the approach given in the late 80th, it was also clear that this approach allows to formulate and exploit the analogy to Banach spaces of analytic functions invariant under the Moebius group have been at the heart in this context. Recent years have seen further new instances and generalizations. Among them shearlets or the Blaschke product should be mentioned here, and the increased interest in the connections between wavelet theory and complex analysis. The talk will try to summarize a few of the general principles which can be derived from the general theory, but also highlight the difference between the different groups and signal expansions arising from corresponding group representations. There is still a lot more to be done, also from the point of view of applications and the numerical realization of such non-orthogonal expansions.
WFR-2D: an analytical model for PWAS-generated 2D ultrasonic guided wave propagation
NASA Astrophysics Data System (ADS)
Shen, Yanfeng; Giurgiutiu, Victor
2014-03-01
This paper presents WaveFormRevealer 2-D (WFR-2D), an analytical predictive tool for the simulation of 2-D ultrasonic guided wave propagation and interaction with damage. The design of structural health monitoring (SHM) systems and self-aware smart structures requires the exploration of a wide range of parameters to achieve best detection and quantification of certain types of damage. Such need for parameter exploration on sensor dimension, location, guided wave characteristics (mode type, frequency, wavelength, etc.) can be best satisfied with analytical models which are fast and efficient. The analytical model was constructed based on the exact 2-D Lamb wave solution using Bessel and Hankel functions. Damage effects were inserted in the model by considering the damage as a secondary wave source with complex-valued directivity scattering coefficients containing both amplitude and phase information from wave-damage interaction. The analytical procedure was coded with MATLAB, and a predictive simulation tool called WaveFormRevealer 2-D was developed. The wave-damage interaction coefficients (WDICs) were extracted from harmonic analysis of local finite element model (FEM) with artificial non-reflective boundaries (NRB). The WFR-2D analytical simulation results were compared and verified with full scale multiphysics finite element models and experiments with scanning laser vibrometer. First, Lamb wave propagation in a pristine aluminum plate was simulated with WFR-2D, compared with finite element results, and verified by experiments. Then, an inhomogeneity was machined into the plate to represent damage. Analytical modeling was carried out, and verified by finite element simulation and experiments. This paper finishes with conclusions and suggestions for future work.
Microwave Assisted 2D Materials Exfoliation
NASA Astrophysics Data System (ADS)
Wang, Yanbin
Two-dimensional materials have emerged as extremely important materials with applications ranging from energy and environmental science to electronics and biology. Here we report our discovery of a universal, ultrafast, green, solvo-thermal technology for producing excellent-quality, few-layered nanosheets in liquid phase from well-known 2D materials such as such hexagonal boron nitride (h-BN), graphite, and MoS2. We start by mixing the uniform bulk-layered material with a common organic solvent that matches its surface energy to reduce the van der Waals attractive interactions between the layers; next, the solutions are heated in a commercial microwave oven to overcome the energy barrier between bulk and few-layers states. We discovered the minutes-long rapid exfoliation process is highly temperature dependent, which requires precise thermal management to obtain high-quality inks. We hypothesize a possible mechanism of this proposed solvo-thermal process; our theory confirms the basis of this novel technique for exfoliation of high-quality, layered 2D materials by using an as yet unknown role of the solvent.
Multienzyme Inkjet Printed 2D Arrays.
Gdor, Efrat; Shemesh, Shay; Magdassi, Shlomo; Mandler, Daniel
2015-08-19
The use of printing to produce 2D arrays is well established, and should be relatively facile to adapt for the purpose of printing biomaterials; however, very few studies have been published using enzyme solutions as inks. Among the printing technologies, inkjet printing is highly suitable for printing biomaterials and specifically enzymes, as it offers many advantages. Formulation of the inkjet inks is relatively simple and can be adjusted to a variety of biomaterials, while providing nonharmful environment to the enzymes. Here we demonstrate the applicability of inkjet printing for patterning multiple enzymes in a predefined array in a very straightforward, noncontact method. Specifically, various arrays of the enzymes glucose oxidase (GOx), invertase (INV) and horseradish peroxidase (HP) were printed on aminated glass surfaces, followed by immobilization using glutardialdehyde after printing. Scanning electrochemical microscopy (SECM) was used for imaging the printed patterns and to ascertain the enzyme activity. The successful formation of 2D arrays consisting of enzymes was explored as a means of developing the first surface confined enzyme based logic gates. Principally, XOR and AND gates, each consisting of two enzymes as the Boolean operators, were assembled, and their operation was studied by SECM. PMID:26214072
Bingi, Jayachandra; Murukeshan, Vadakke Matham
2015-01-01
Laser speckle pattern is a granular structure formed due to random coherent wavelet interference and generally considered as noise in optical systems including photolithography. Contrary to this, in this paper, we use the speckle pattern to generate predictable and controlled Gaussian random structures and quasi-random structures photo-lithographically. The random structures made using this proposed speckle lithography technique are quantified based on speckle statistics, radial distribution function (RDF) and fast Fourier transform (FFT). The control over the speckle size, density and speckle clustering facilitates the successful fabrication of black silicon with different surface structures. The controllability and tunability of randomness makes this technique a robust method for fabricating predictable 2D Gaussian random structures and black silicon structures. These structures can enhance the light trapping significantly in solar cells and hence enable improved energy harvesting. Further, this technique can enable efficient fabrication of disordered photonic structures and random media based devices.
Bingi, Jayachandra; Murukeshan, Vadakke Matham
2015-01-01
Laser speckle pattern is a granular structure formed due to random coherent wavelet interference and generally considered as noise in optical systems including photolithography. Contrary to this, in this paper, we use the speckle pattern to generate predictable and controlled Gaussian random structures and quasi-random structures photo-lithographically. The random structures made using this proposed speckle lithography technique are quantified based on speckle statistics, radial distribution function (RDF) and fast Fourier transform (FFT). The control over the speckle size, density and speckle clustering facilitates the successful fabrication of black silicon with different surface structures. The controllability and tunability of randomness makes this technique a robust method for fabricating predictable 2D Gaussian random structures and black silicon structures. These structures can enhance the light trapping significantly in solar cells and hence enable improved energy harvesting. Further, this technique can enable efficient fabrication of disordered photonic structures and random media based devices. PMID:26679513
Fast fractal image compression with triangulation wavelets
NASA Astrophysics Data System (ADS)
Hebert, D. J.; Soundararajan, Ezekiel
1998-10-01
We address the problem of improving the performance of wavelet based fractal image compression by applying efficient triangulation methods. We construct iterative function systems (IFS) in the tradition of Barnsley and Jacquin, using non-uniform triangular range and domain blocks instead of uniform rectangular ones. We search for matching domain blocks in the manner of Zhang and Chen, performing a fast wavelet transform on the blocks and eliminating low resolution mismatches to gain speed. We obtain further improvements by the efficiencies of binary triangulations (including the elimination of affine and symmetry calculations and reduced parameter storage), and by pruning the binary tree before construction of the IFS. Our wavelets are triangular Haar wavelets and `second generation' interpolation wavelets as suggested by Sweldens' recent work.
Complex wavelet based speckle reduction using multiple ultrasound images
NASA Astrophysics Data System (ADS)
Uddin, Muhammad Shahin; Tahtali, Murat; Pickering, Mark R.
2014-04-01
Ultrasound imaging is a dominant tool for diagnosis and evaluation in medical imaging systems. However, as its major limitation is that the images it produces suffer from low quality due to the presence of speckle noise, to provide better clinical diagnoses, reducing this noise is essential. The key purpose of a speckle reduction algorithm is to obtain a speckle-free high-quality image whilst preserving important anatomical features, such as sharp edges. As this can be better achieved using multiple ultrasound images rather than a single image, we introduce a complex wavelet-based algorithm for the speckle reduction and sharp edge preservation of two-dimensional (2D) ultrasound images using multiple ultrasound images. The proposed algorithm does not rely on straightforward averaging of multiple images but, rather, in each scale, overlapped wavelet detail coefficients are weighted using dynamic threshold values and then reconstructed by averaging. Validation of the proposed algorithm is carried out using simulated and real images with synthetic speckle noise and phantom data consisting of multiple ultrasound images, with the experimental results demonstrating that speckle noise is significantly reduced whilst sharp edges without discernible distortions are preserved. The proposed approach performs better both qualitatively and quantitatively than previous existing approaches.
A wavelet-based method for multispectral face recognition
NASA Astrophysics Data System (ADS)
Zheng, Yufeng; Zhang, Chaoyang; Zhou, Zhaoxian
2012-06-01
A wavelet-based method is proposed for multispectral face recognition in this paper. Gabor wavelet transform is a common tool for orientation analysis of a 2D image; whereas Hamming distance is an efficient distance measurement for face identification. Specifically, at each frequency band, an index number representing the strongest orientational response is selected, and then encoded in binary format to favor the Hamming distance calculation. Multiband orientation bit codes are then organized into a face pattern byte (FPB) by using order statistics. With the FPB, Hamming distances are calculated and compared to achieve face identification. The FPB algorithm was initially created using thermal images, while the EBGM method was originated with visible images. When two or more spectral images from the same subject are available, the identification accuracy and reliability can be enhanced using score fusion. We compare the identification performance of applying five recognition algorithms to the three-band (visible, near infrared, thermal) face images, and explore the fusion performance of combing the multiple scores from three recognition algorithms and from three-band face images, respectively. The experimental results show that the FPB is the best recognition algorithm, the HMM yields the best fusion result, and the thermal dataset results in the best fusion performance compared to other two datasets.
Wavelet transforms for electroencephalographic spike and seizure detection
NASA Astrophysics Data System (ADS)
Schiff, Steven J.; Milton, John G.
1993-11-01
The application of wavelet transforms (WT) to experimental data from the nervous system has been hindered by the lack of a straightforward method to handle noise. A noise reduction technique, developed recently for use in wavelet cluster analysis in cosmology and astronomy, is here adapted for electroencephalographic (EEG) time-series data. Noise is filtered using control surrogate data sets generated from randomized aspects of the original time-series. In this study, WT were applied to EEG data from human patients undergoing brain mapping with implanted subdural electrodes for the localization of epileptic seizure foci. EEG data in 1D were analyzed from individual electrodes, and 2D data from electrode grids. These techniques are a powerful means to identify epileptic spikes in such data, and offer a method to identity the onset and spatial extent of epileptic seizure foci. The method is readily applied to the detection of structure in stationary and non-stationary time-series from a variety of physical systems.
2-D or not 2-D, that is the question: A Northern California test
Mayeda, K; Malagnini, L; Phillips, W S; Walter, W R; Dreger, D
2005-06-06
Reliable estimates of the seismic source spectrum are necessary for accurate magnitude, yield, and energy estimation. In particular, how seismic radiated energy scales with increasing earthquake size has been the focus of recent debate within the community and has direct implications on earthquake source physics studies as well as hazard mitigation. The 1-D coda methodology of Mayeda et al. has provided the lowest variance estimate of the source spectrum when compared against traditional approaches that use direct S-waves, thus making it ideal for networks that have sparse station distribution. The 1-D coda methodology has been mostly confined to regions of approximately uniform complexity. For larger, more geophysically complicated regions, 2-D path corrections may be required. The complicated tectonics of the northern California region coupled with high quality broadband seismic data provides for an ideal ''apples-to-apples'' test of 1-D and 2-D path assumptions on direct waves and their coda. Using the same station and event distribution, we compared 1-D and 2-D path corrections and observed the following results: (1) 1-D coda results reduced the amplitude variance relative to direct S-waves by roughly a factor of 8 (800%); (2) Applying a 2-D correction to the coda resulted in up to 40% variance reduction from the 1-D coda results; (3) 2-D direct S-wave results, though better than 1-D direct waves, were significantly worse than the 1-D coda. We found that coda-based moment-rate source spectra derived from the 2-D approach were essentially identical to those from the 1-D approach for frequencies less than {approx}0.7-Hz, however for the high frequencies (0.7{le} f {le} 8.0-Hz), the 2-D approach resulted in inter-station scatter that was generally 10-30% smaller. For complex regions where data are plentiful, a 2-D approach can significantly improve upon the simple 1-D assumption. In regions where only 1-D coda correction is available it is still preferable over 2
NASA Astrophysics Data System (ADS)
Vanzo, Davide; Siviglia, Annunziato; Zolezzi, Guido
2014-05-01
In last decades, pushed by an increasing interest in environmental problems and supported by an exponential growth of computational capability, novel numerical methods and models have been developed. Despite the progress in parallel computing, computational time is still one of the main bottlenecks when dealing with long term environmental simulations. To overcome such time constraint in morphodynamic models, artificial acceleration of bed evolution has been implemented with different strategies (e.g. Roelvink 2006). The key idea is to accelerate the morphological evolution increasing the discrete bottom variations of a given "morphological factor" during numerical integration thus considerably speeding up computational time. On the other hand, an artificial alteration of the governing equations is put forward, for which related numerical and physical consequences are not completely known. The present work investigates the role of the morphological factor in numerical simulations of a well-defined, 2D reach-scale process in river morphodynamics, which can be taken as a benchmark for the established knowledge made available from theoretical and physical scale models developed in the past decades. The chosen process is the evolution of free migrating bars in a straight channel. The numerical morphodynamic model used in this work is GIAMT2D (Siviglia et al. 2013), which solves the governing system of shallow water and Exner equations following a fully coupled approach with a finite volume method on unstructured triangular grids. By processing numerical outcomes also through Continuous Wavelet Transform, the differences in free migrating bars properties (temporal evolution and equilibrium values of wavelength, amplitude, celerity) are investigated in simple test cases with different values of the morphological factor. Numerical results are compared with available analytical theories for free bars. The outcomes highlight the consequences of using the morphological
Adaptive directional wavelet transform based on directional prefiltering.
Tanaka, Yuichi; Hasegawa, Madoka; Kato, Shigeo; Ikehara, Masaaki; Nguyen, Truong Q
2010-04-01
This paper proposes an efficient approach for adaptive directional wavelet transform (WT) based on directional prefiltering. Although the adaptive directional WT is able to transform an image along diagonal orientations as well as traditional horizontal and vertical directions, it sacrifices computation speed for good image coding performance. We present two efficient methods to find the best transform directions by prefiltering using 2-D filter bank or 1-D directional WT along two fixed directions. The proposed direction calculation methods achieve comparable image coding performance comparing to the conventional one with less complexity. Furthermore, transform direction data of the proposed method can be used for content-based image retrieval to increase retrieval ratio. PMID:20028625
Automatic 2D to 3D conversion implemented for real-time applications
NASA Astrophysics Data System (ADS)
Ponomaryov, Volodymyr; Ramos-Diaz, Eduardo; Gonzalez Huitron, Victor
2014-05-01
Different hardware implementations of designed automatic 2D to 3D video color conversion employing 2D video sequence are presented. The analyzed framework includes together processing of neighboring frames using the following blocks: CIELa*b* color space conversion, wavelet transform, edge detection using HF wavelet sub-bands (HF, LH and HH), color segmentation via k-means on a*b* color plane, up-sampling, disparity map (DM) estimation, adaptive postfiltering, and finally, the anaglyph 3D scene generation. During edge detection, the Donoho threshold is computed, then each sub-band is binarized according to a threshold chosen and finally the thresholding image is formed. DM estimation is performed in the following matter: in left stereo image (or frame), a window with varying sizes is used according to the information obtained from binarized sub-band image, distinguishing different texture areas into LL sub-band image. The stereo matching is performed between two (left and right) LL sub-band images using processing with different window sizes. Upsampling procedure is employed in order to obtain the enhanced DM. Adaptive post-processing procedure is based on median filter and k-means segmentation in a*b* color plane. The SSIM and QBP criteria are applied in order to compare the performance of the proposed framework against other disparity map computation techniques. The designed technique has been implemented on DSP TMS320DM648, Matlab's Simulink module over a PC with Windows 7 and using graphic card (NVIDIA Quadro K2000) demonstrating that the proposed approach can be applied in real-time processing mode.
Wavelet assessment of cerebrospinal compensatory reserve and cerebrovascular pressure reactivity
NASA Astrophysics Data System (ADS)
Latka, M.; Turalska, M.; Kolodziej, W.; Latka, D.; West, B.
2006-03-01
We employ complex continuous wavelet transforms to develop a consistent mathematical framework capable of quantifying both cerebrospinal compensatory reserve and cerebrovascular pressure--reactivity. The wavelet gain, defined as the frequency dependent ratio of time averaged wavelet coefficients of intracranial (ICP) and arterial blood pressure (ABP) fluctuations, characterizes the dampening of spontaneous arterial blood oscillations. This gain is introduced as a novel measure of cerebrospinal compensatory reserve. For a group of 10 patients who died as a result of head trauma (Glasgow Outcome Scale GOS =1) the average gain is 0.45 calculated at 0.05 Hz significantly exceeds that of 16 patients with favorable outcome (GOS=2): with gain of 0.24 with p=4x10-5. We also study the dynamics of instantaneous phase difference between the fluctuations of the ABP and ICP time series. The time-averaged synchronization index, which depends upon frequency, yields the information about the stability of the phase difference and is used as a cerebrovascular pressure--reactivity index. The average phase difference for GOS=1 is close to zero in sharp contrast to the mean value of 30^o for patients with GOS=2. We hypothesize that in patients who died the impairment of cerebral autoregulation is followed by the break down of residual pressure reactivity.
A wavelet based approach to Solar-Terrestrial Coupling
NASA Astrophysics Data System (ADS)
Katsavrias, Ch.; Hillaris, A.; Preka-Papadema, P.
2016-05-01
Transient and recurrent solar activity drive geomagnetic disturbances; these are quantified (amongst others) by DST , AE indices time-series. Transient disturbances are related to the Interplanetary Coronal Mass Ejections (ICMEs) while recurrent disturbances are related to corotating interaction regions (CIR). We study the relationship of the geomagnetic disturbances to the solar wind drivers within solar cycle 23 where the drivers are represented by ICMEs and CIRs occurrence rate and compared to the DST and AE as follows: terms with common periodicity in both the geomagnetic disturbances and the solar drivers are, firstly, detected using continuous wavelet transform (CWT). Then, common power and phase coherence of these periodic terms are calculated from the cross-wavelet spectra (XWT) and wavelet-coherence (WTC) respectively. In time-scales of ≈27 days our results indicate an anti-correlation of the effects of ICMEs and CIRs on the geomagnetic disturbances. The former modulates the DST and AE time series during the cycle maximum the latter during periods of reduced solar activity. The phase relationship of these modulation is highly non-linear. Only the annual frequency component of the ICMEs is phase-locked with DST and AE. In time-scales of ≈1.3-1.7 years the CIR seem to be the dominant driver for both geomagnetic indices throughout the whole solar cycle 23.
A continuous point measure for quantifying skull deformation in medical diagnostics
Strachan, Ben; O'Connor, Bridget; Khandoker, Ahsan
2014-01-01
Deformational plagiocephaly (DP) manifests in a deformed skull primarily caused by retaining a constant sleeping position in infants. Manual measures of skull asymmetry based on MRI or CT scans combined with the cranial vault asymmetry index (CVAI) provides information on the extent of asymmetry. CVAI uses four points on the skull as markers for the asymmetry index but tends to underestimate the deformity because of the lack of sampling points. Computer-based continuous-point methods may be a more objective measure with better sensitivity for the skull contour. The outline of the skull circumference of infants with confirmed cranial deformity was obtained from the literature and analysed applying the mean bending energy (MBE) obtained from the Hermitian wavelet. MBE was shown to correlate with CVAI in the current sample and has the potential to add both quantitative and visual information in 2D or 3D space for the clinician to diagnose DP. Wavelet-based continuous-point estimation of skull asymmetry is a useful method as it is more sensitive to mild deformation anywhere along the skull outline and in assessing slow but progressive improvement as a result of treatment. The broader significance is that this method can be applied to other structural pathology analysis in clinical practice. PMID:26609378
Quantum damped oscillator II: Bateman's Hamiltonian vs. 2D parabolic potential barrier
Chruscinski, Dariusz . E-mail: darch@phys.uni.torun.pl
2006-04-15
We show that quantum Bateman's system which arises in the quantization of a damped harmonic oscillator is equivalent to a quantum problem with 2D parabolic potential barrier known also as 2D inverted isotropic oscillator. It turns out that this system displays the family of complex eigenvalues corresponding to the poles of analytical continuation of the resolvent operator to the complex energy plane. It is shown that this representation is more suitable than the hyperbolic one used recently by Blasone and Jizba.
Canard configured aircraft with 2-D nozzle
NASA Technical Reports Server (NTRS)
Child, R. D.; Henderson, W. P.
1978-01-01
A closely-coupled canard fighter with vectorable two-dimensional nozzle was designed for enhanced transonic maneuvering. The HiMAT maneuver goal of a sustained 8g turn at a free-stream Mach number of 0.9 and 30,000 feet was the primary design consideration. The aerodynamic design process was initiated with a linear theory optimization minimizing the zero percent suction drag including jet effects and refined with three-dimensional nonlinear potential flow techniques. Allowances were made for mutual interference and viscous effects. The design process to arrive at the resultant configuration is described, and the design of a powered 2-D nozzle model to be tested in the LRC 16-foot Propulsion Wind Tunnel is shown.
2D Electrostatic Actuation of Microshutter Arrays
NASA Technical Reports Server (NTRS)
Burns, Devin E.; Oh, Lance H.; Li, Mary J.; Kelly, Daniel P.; Kutyrev, Alexander S.; Moseley, Samuel H.
2015-01-01
Electrostatically actuated microshutter arrays consisting of rotational microshutters (shutters that rotate about a torsion bar) were designed and fabricated through the use of models and experiments. Design iterations focused on minimizing the torsional stiffness of the microshutters, while maintaining their structural integrity. Mechanical and electromechanical test systems were constructed to measure the static and dynamic behavior of the microshutters. The torsional stiffness was reduced by a factor of four over initial designs without sacrificing durability. Analysis of the resonant behavior of the microshutters demonstrates that the first resonant mode is a torsional mode occurring around 3000 Hz. At low vacuum pressures, this resonant mode can be used to significantly reduce the drive voltage necessary for actuation requiring as little as 25V. 2D electrostatic latching and addressing was demonstrated using both a resonant and pulsed addressing scheme.
2D Electrostatic Actuation of Microshutter Arrays
NASA Technical Reports Server (NTRS)
Burns, Devin E.; Oh, Lance H.; Li, Mary J.; Jones, Justin S.; Kelly, Daniel P.; Zheng, Yun; Kutyrev, Alexander S.; Moseley, Samuel H.
2015-01-01
An electrostatically actuated microshutter array consisting of rotational microshutters (shutters that rotate about a torsion bar) were designed and fabricated through the use of models and experiments. Design iterations focused on minimizing the torsional stiffness of the microshutters, while maintaining their structural integrity. Mechanical and electromechanical test systems were constructed to measure the static and dynamic behavior of the microshutters. The torsional stiffness was reduced by a factor of four over initial designs without sacrificing durability. Analysis of the resonant behavior of the microshutter arrays demonstrates that the first resonant mode is a torsional mode occurring around 3000 Hz. At low vacuum pressures, this resonant mode can be used to significantly reduce the drive voltage necessary for actuation requiring as little as 25V. 2D electrostatic latching and addressing was demonstrated using both a resonant and pulsed addressing scheme.
2D quantum gravity from quantum entanglement.
Gliozzi, F
2011-01-21
In quantum systems with many degrees of freedom the replica method is a useful tool to study the entanglement of arbitrary spatial regions. We apply it in a way that allows them to backreact. As a consequence, they become dynamical subsystems whose position, form, and extension are determined by their interaction with the whole system. We analyze, in particular, quantum spin chains described at criticality by a conformal field theory. Its coupling to the Gibbs' ensemble of all possible subsystems is relevant and drives the system into a new fixed point which is argued to be that of the 2D quantum gravity coupled to this system. Numerical experiments on the critical Ising model show that the new critical exponents agree with those predicted by the formula of Knizhnik, Polyakov, and Zamolodchikov.
Graphene suspensions for 2D printing
NASA Astrophysics Data System (ADS)
Soots, R. A.; Yakimchuk, E. A.; Nebogatikova, N. A.; Kotin, I. A.; Antonova, I. V.
2016-04-01
It is shown that, by processing a graphite suspension in ethanol or water by ultrasound and centrifuging, it is possible to obtain particles with thicknesses within 1-6 nm and, in the most interesting cases, 1-1.5 nm. Analogous treatment of a graphite suspension in organic solvent yields eventually thicker particles (up to 6-10 nm thick) even upon long-term treatment. Using the proposed ink based on graphene and aqueous ethanol with ethylcellulose and terpineol additives for 2D printing, thin (~5 nm thick) films with sheet resistance upon annealing ~30 MΩ/□ were obtained. With the ink based on aqueous graphene suspension, the sheet resistance was ~5-12 kΩ/□ for 6- to 15-nm-thick layers with a carrier mobility of ~30-50 cm2/(V s).
Wavelet analysis of circadian and ultradian behavioral rhythms
2013-01-01
We review time-frequency methods that can be useful in quantifying circadian and ultradian patterns in behavioral records. These records typically exhibit details that may not be captured through commonly used measures such as activity onset and so may require alternative approaches. For instance, activity may involve multiple bouts that vary in duration and magnitude within a day, or may exhibit day-to-day changes in period and in ultradian activity patterns. The discrete Fourier transform and other types of periodograms can estimate the period of a circadian rhythm, but we show that they can fail to correctly assess ultradian periods. In addition, such methods cannot detect changes in the period over time. Time-frequency methods that can localize frequency estimates in time are more appropriate for analysis of ultradian periods and of fluctuations in the period. The continuous wavelet transform offers a method for determining instantaneous frequency with good resolution in both time and frequency, capable of detecting changes in circadian period over the course of several days and in ultradian period within a given day. The discrete wavelet transform decomposes a time series into components associated with distinct frequency bands, thereby facilitating the removal of noise and trend or the isolation of a particular frequency band of interest. To demonstrate the wavelet-based analysis, we apply the transforms to a numerically-generated example and also to a variety of hamster behavioral records. When used appropriately, wavelet transforms can reveal patterns that are not easily extracted using other methods of analysis in common use, but they must be applied and interpreted with care. PMID:23816159
Metrology for graphene and 2D materials
NASA Astrophysics Data System (ADS)
Pollard, Andrew J.
2016-09-01
The application of graphene, a one atom-thick honeycomb lattice of carbon atoms with superlative properties, such as electrical conductivity, thermal conductivity and strength, has already shown that it can be used to benefit metrology itself as a new quantum standard for resistance. However, there are many application areas where graphene and other 2D materials, such as molybdenum disulphide (MoS2) and hexagonal boron nitride (h-BN), may be disruptive, areas such as flexible electronics, nanocomposites, sensing and energy storage. Applying metrology to the area of graphene is now critical to enable the new, emerging global graphene commercial world and bridge the gap between academia and industry. Measurement capabilities and expertise in a wide range of scientific areas are required to address this challenge. The combined and complementary approach of varied characterisation methods for structural, chemical, electrical and other properties, will allow the real-world issues of commercialising graphene and other 2D materials to be addressed. Here, examples of metrology challenges that have been overcome through a multi-technique or new approach are discussed. Firstly, the structural characterisation of defects in both graphene and MoS2 via Raman spectroscopy is described, and how nanoscale mapping of vacancy defects in graphene is also possible using tip-enhanced Raman spectroscopy (TERS). Furthermore, the chemical characterisation and removal of polymer residue on chemical vapour deposition (CVD) grown graphene via secondary ion mass spectrometry (SIMS) is detailed, as well as the chemical characterisation of iron films used to grow large domain single-layer h-BN through CVD growth, revealing how contamination of the substrate itself plays a role in the resulting h-BN layer. In addition, the role of international standardisation in this area is described, outlining the current work ongoing in both the International Organization of Standardization (ISO) and the
Saadi, Slami; Touiza, Maamar; Kharfi, Fayçal; Guessoum, Abderrezak
2013-12-01
In this work, we present a mixed software/hardware implementation of 2-D signals encoder/decoder using dyadic discrete wavelet transform (DWT) based on quadrature mirror filters (QMF); using fast wavelet Mallat's algorithm. This work is designed and compiled on the embedded development kit EDK6.3i, and the synthesis software, ISE6.3i, which is available with Xilinx Virtex-IIV2MB1000 FPGA. Huffman coding scheme is used to encode the wavelet coefficients so that they can be transmitted progressively through an Ethernet TCP/IP based connection. The possible reconfiguration can be exploited to attain higher performance. The design will be integrated with the neutron radiography system that is used with the Es-Salem research reactor. PMID:24041807
Saadi, Slami; Touiza, Maamar; Kharfi, Fayçal; Guessoum, Abderrezak
2013-12-01
In this work, we present a mixed software/hardware implementation of 2-D signals encoder/decoder using dyadic discrete wavelet transform (DWT) based on quadrature mirror filters (QMF); using fast wavelet Mallat's algorithm. This work is designed and compiled on the embedded development kit EDK6.3i, and the synthesis software, ISE6.3i, which is available with Xilinx Virtex-IIV2MB1000 FPGA. Huffman coding scheme is used to encode the wavelet coefficients so that they can be transmitted progressively through an Ethernet TCP/IP based connection. The possible reconfiguration can be exploited to attain higher performance. The design will be integrated with the neutron radiography system that is used with the Es-Salem research reactor.
Tracking of Ice Edges and Ice Floes by Wavelet Analysis of SAR Images
NASA Technical Reports Server (NTRS)
Liu, Antony K.; Martin, Seelye; Kwok, Ronald
1997-01-01
This paper demonstrates the use of wavelet transforms in the tracking of sequential ice features in the ERS-1 synthetic aperture radar (SAR) imagery, especially in situations where feature correlation techniques fail to yield reasonable results. Examples include the evolution of the St. Lawrence polynya and summer sea ice change in the Beaufort Sea. For the polynya, the evolution of the region of young ice growth surrounding a polynya can be easily tracked by wavelet analysis due to the large backscatter difference between the young and old ice. Also within the polynya, a 2D fast Fourier transform (FFT) is used to identify the extent of the Langmuir circulation region, which is coincident with the wave-agitated frazil ice growth region, where the sea ice experiences its fastest growth. Therefore, the combination of wavelet and FFT analysis of SAR images provides for the large-scale monitoring of different polynya features. For summer ice, previous work shows that this is the most difficult period for ice trackers due to the lack of features on the sea ice cover. The multiscale wavelet analysis shows that this method delineates the detailed floe shapes during this period, so that between consecutive images, the floe translation and rotation can be estimated.
NASA Astrophysics Data System (ADS)
Saadi, S.; Touiza, M.; Guessoum, A.
In this study, we present an implementation on FPGA of 2D signals Encoder/Decoder using dyadic Discrete Wavelet Transform based on quadrature mirror filters, by applying fast wavelet Mallat`s algorithm. The wavelet coefficients will be encoded by Huffman code in order to be transmitted progressively through an Ethernet TCP/IP based connection. The proposed study is implemented and synthesized in VHDL for Xilinx Virtex-IIV2MB1000 FPGA device using ISE 8.1 and simulated on Modelsim PE 6.0d. The synthesis results are presented in detail. The proposed design can substantially accelerate the DWT and the possible reconfiguration can be exploited to reach a higher performance in the future. The system is designed to be integrated as an extension to the nuclear imaging system implemented around our nuclear research reactor. Assuming a Pentium4 processor with clock frequency of 3.3 GHz for the Matlab software implementation, a speed up of over 5 times for a picture size of 256 x 256 was achieved.
Tan, Liying; Ma, Jing; Wang, Guangming
2005-12-01
The image formation and the point-spread function of an optical system are analyzed by use of the wavelet basis function. The image described by a wavelet is no longer an indivisible whole image. It is, rather, a complex image consisting of many wavelet subimages, which come from the changes of different parameters (scale) a and c, and parameters b and d show the positions of wavelet subimages under different scales. A Gaussian frequency-modulated complex-valued wavelet function is introduced to express the point-spread function of an optical system and used to describe the image formation. The analysis, in allusion to the situation of illumination with a monochromatic plain light wave, shows that using the theory of wavelet optics to describe the image formation of an optical system is feasible.
NASA Astrophysics Data System (ADS)
Tan, Liying; Ma, Jing; Wang, Guangming
2005-12-01
The image formation and the point-spread function of an optical system are analyzed by use of the wavelet basis function. The image described by a wavelet is no longer an indivisible whole image. It is, rather, a complex image consisting of many wavelet subimages, which come from the changes of different parameters (scale) a and c, and parameters b and d show the positions of wavelet subimages under different scales. A Gaussian frequency-modulated complex-valued wavelet function is introduced to express the point-spread function of an optical system and used to describe the image formation. The analysis, in allusion to the situation of illumination with a monochromatic plain light wave, shows that using the theory of wavelet optics to describe the image formation of an optical system is feasible.
A new inversion method for (T2, D) 2D NMR logging and fluid typing
NASA Astrophysics Data System (ADS)
Tan, Maojin; Zou, Youlong; Zhou, Cancan
2013-02-01
One-dimensional nuclear magnetic resonance (1D NMR) logging technology has some significant limitations in fluid typing. However, not only can two-dimensional nuclear magnetic resonance (2D NMR) provide some accurate porosity parameters, but it can also identify fluids more accurately than 1D NMR. In this paper, based on the relaxation mechanism of (T2, D) 2D NMR in a gradient magnetic field, a hybrid inversion method that combines least-squares-based QR decomposition (LSQR) and truncated singular value decomposition (TSVD) is examined in the 2D NMR inversion of various fluid models. The forward modeling and inversion tests are performed in detail with different acquisition parameters, such as magnetic field gradients (G) and echo spacing (TE) groups. The simulated results are discussed and described in detail, the influence of the above-mentioned observation parameters on the inversion accuracy is investigated and analyzed, and the observation parameters in multi-TE activation are optimized. Furthermore, the hybrid inversion can be applied to quantitatively determine the fluid saturation. To study the effects of noise level on the hybrid method and inversion results, the numerical simulation experiments are performed using different signal-to-noise-ratios (SNRs), and the effect of different SNRs on fluid typing using three fluid models are discussed and analyzed in detail.
Syndrome identification based on 2D analysis software.
Boehringer, Stefan; Vollmar, Tobias; Tasse, Christiane; Wurtz, Rolf P; Gillessen-Kaesbach, Gabriele; Horsthemke, Bernhard; Wieczorek, Dagmar
2006-10-01
Clinical evaluation of children with developmental delay continues to present a challenge to the clinicians. In many cases, the face provides important information to diagnose a condition. However, database support with respect to facial traits is limited at present. Computer-based analyses of 2D and 3D representations of faces have been developed, but it is unclear how well a larger number of conditions can be handled by such systems. We have therefore analysed 2D pictures of patients each being affected with one of 10 syndromes (fragile X syndrome; Cornelia de Lange syndrome; Williams-Beuren syndrome; Prader-Willi syndrome; Mucopolysaccharidosis type III; Cri-du-chat syndrome; Smith-Lemli-Opitz syndrome; Sotos syndrome; Microdeletion 22q11.2; Noonan syndrome). We can show that a classification accuracy of >75% can be achieved for a computer-based diagnosis among the 10 syndromes, which is about the same accuracy achieved for five syndromes in a previous study. Pairwise discrimination of syndromes ranges from 80 to 99%. Furthermore, we can demonstrate that the criteria used by the computer decisions match clinical observations in many cases. These findings indicate that computer-based picture analysis might be a helpful addition to existing database systems, which are meant to assist in syndrome diagnosis, especially as data acquisition is straightforward and involves off-the-shelf digital camera equipment. PMID:16773127
2D NMR-spectroscopic screening reveals polyketides in ladybugs
Deyrup, Stephen T.; Eckman, Laura E.; McCarthy, Patrick H.; Smedley, Scott R.; Meinwald, Jerrold; Schroeder, Frank C.
2011-01-01
Small molecules of biological origin continue to yield the most promising leads for drug design, but systematic approaches for exploring nature’s cache of structural diversity are lacking. Here, we demonstrate the use of 2D NMR spectroscopy to screen a library of biorationally selected insect metabolite samples for partial structures indicating the presence of new chemical entities. This NMR-spectroscopic survey enabled detection of novel compounds in complex metabolite mixtures without prior fractionation or isolation. Our screen led to discovery and subsequent isolation of two families of tricyclic pyrones in Delphastus catalinae, a tiny ladybird beetle that is employed commercially as a biological pest control agent. The D. catalinae pyrones are based on 23-carbon polyketide chains forming 1,11-dioxo-2,6,10-trioxaanthracene and 4,8-dioxo-1,9,13-trioxaanthracene derivatives, representing ring systems not previously found in nature. This study highlights the utility of 2D NMR-spectroscopic screening for exploring nature’s structure space and suggests that insect metabolomes remain vastly underexplored. PMID:21646540
2D NMR-spectroscopic screening reveals polyketides in ladybugs.
Deyrup, Stephen T; Eckman, Laura E; McCarthy, Patrick H; Smedley, Scott R; Meinwald, Jerrold; Schroeder, Frank C
2011-06-14
Small molecules of biological origin continue to yield the most promising leads for drug design, but systematic approaches for exploring nature's cache of structural diversity are lacking. Here, we demonstrate the use of 2D NMR spectroscopy to screen a library of biorationally selected insect metabolite samples for partial structures indicating the presence of new chemical entities. This NMR-spectroscopic survey enabled detection of novel compounds in complex metabolite mixtures without prior fractionation or isolation. Our screen led to discovery and subsequent isolation of two families of tricyclic pyrones in Delphastus catalinae, a tiny ladybird beetle that is employed commercially as a biological pest control agent. The D. catalinae pyrones are based on 23-carbon polyketide chains forming 1,11-dioxo-2,6,10-trioxaanthracene and 4,8-dioxo-1,9,13-trioxaanthracene derivatives, representing ring systems not previously found in nature. This study highlights the utility of 2D NMR-spectroscopic screening for exploring nature's structure space and suggests that insect metabolomes remain vastly underexplored. PMID:21646540
Wavelet-based multispectral face recognition
NASA Astrophysics Data System (ADS)
Liu, Dian-Ting; Zhou, Xiao-Dan; Wang, Cheng-Wen
2008-09-01
This paper proposes a novel wavelet-based face recognition method using thermal infrared (IR) and visible-light face images. The method applies the combination of Gabor and the Fisherfaces method to the reconstructed IR and visible images derived from wavelet frequency subbands. Our objective is to search for the subbands that are insensitive to the variation in expression and in illumination. The classification performance is improved by combining the multispectal information coming from the subbands that attain individually low equal error rate. Experimental results on Notre Dame face database show that the proposed wavelet-based algorithm outperforms previous multispectral images fusion method as well as monospectral method.
Wavelet Applications for Flight Flutter Testing
NASA Technical Reports Server (NTRS)
Lind, Rick; Brenner, Marty; Freudinger, Lawrence C.
1999-01-01
Wavelets present a method for signal processing that may be useful for analyzing responses of dynamical systems. This paper describes several wavelet-based tools that have been developed to improve the efficiency of flight flutter testing. One of the tools uses correlation filtering to identify properties of several modes throughout a flight test for envelope expansion. Another tool uses features in time-frequency representations of responses to characterize nonlinearities in the system dynamics. A third tool uses modulus and phase information from a wavelet transform to estimate modal parameters that can be used to update a linear model and reduce conservatism in robust stability margins.
NASA Astrophysics Data System (ADS)
Cheng, Chingyun; Kangara, Jayampathi; Arakelyan, Ilya; Thomas, John
2016-05-01
We tune the dimensionality of a strongly interacting degenerate 6 Li Fermi gas from 2D to quasi-2D, by adjusting the radial confinement of pancake-shaped clouds to control the radial chemical potential. In the 2D regime with weak radial confinement, the measured pair binding energies are in agreement with 2D-BCS mean field theory, which predicts dimer pairing energies in the many-body regime. In the qausi-2D regime obtained with increased radial confinement, the measured pairing energy deviates significantly from 2D-BCS theory. In contrast to the pairing energy, the measured radii of the cloud profiles are not fit by 2D-BCS theory in either the 2D or quasi-2D regimes, but are fit in both regimes by a beyond mean field polaron-model of the free energy. Supported by DOE, ARO, NSF, and AFOSR.
Competing coexisting phases in 2D water
Zanotti, Jean-Marc; Judeinstein, Patrick; Dalla-Bernardina, Simona; Creff, Gaëlle; Brubach, Jean-Blaise; Roy, Pascale; Bonetti, Marco; Ollivier, Jacques; Sakellariou, Dimitrios; Bellissent-Funel, Marie-Claire
2016-01-01
The properties of bulk water come from a delicate balance of interactions on length scales encompassing several orders of magnitudes: i) the Hydrogen Bond (HBond) at the molecular scale and ii) the extension of this HBond network up to the macroscopic level. Here, we address the physics of water when the three dimensional extension of the HBond network is frustrated, so that the water molecules are forced to organize in only two dimensions. We account for the large scale fluctuating HBond network by an analytical mean-field percolation model. This approach provides a coherent interpretation of the different events experimentally (calorimetry, neutron, NMR, near and far infra-red spectroscopies) detected in interfacial water at 160, 220 and 250 K. Starting from an amorphous state of water at low temperature, these transitions are respectively interpreted as the onset of creation of transient low density patches of 4-HBonded molecules at 160 K, the percolation of these domains at 220 K and finally the total invasion of the surface by them at 250 K. The source of this surprising behaviour in 2D is the frustration of the natural bulk tetrahedral local geometry and the underlying very significant increase in entropy of the interfacial water molecules. PMID:27185018
Phase Engineering of 2D Tin Sulfides.
Mutlu, Zafer; Wu, Ryan J; Wickramaratne, Darshana; Shahrezaei, Sina; Liu, Chueh; Temiz, Selcuk; Patalano, Andrew; Ozkan, Mihrimah; Lake, Roger K; Mkhoyan, K A; Ozkan, Cengiz S
2016-06-01
Tin sulfides can exist in a variety of phases and polytypes due to the different oxidation states of Sn. A subset of these phases and polytypes take the form of layered 2D structures that give rise to a wide host of electronic and optical properties. Hence, achieving control over the phase, polytype, and thickness of tin sulfides is necessary to utilize this wide range of properties exhibited by the compound. This study reports on phase-selective growth of both hexagonal tin (IV) sulfide SnS2 and orthorhombic tin (II) sulfide SnS crystals with diameters of over tens of microns on SiO2 substrates through atmospheric pressure vapor-phase method in a conventional horizontal quartz tube furnace with SnO2 and S powders as the source materials. Detailed characterization of each phase of tin sulfide crystals is performed using various microscopy and spectroscopy methods, and the results are corroborated by ab initio density functional theory calculations. PMID:27099950
Phase Engineering of 2D Tin Sulfides.
Mutlu, Zafer; Wu, Ryan J; Wickramaratne, Darshana; Shahrezaei, Sina; Liu, Chueh; Temiz, Selcuk; Patalano, Andrew; Ozkan, Mihrimah; Lake, Roger K; Mkhoyan, K A; Ozkan, Cengiz S
2016-06-01
Tin sulfides can exist in a variety of phases and polytypes due to the different oxidation states of Sn. A subset of these phases and polytypes take the form of layered 2D structures that give rise to a wide host of electronic and optical properties. Hence, achieving control over the phase, polytype, and thickness of tin sulfides is necessary to utilize this wide range of properties exhibited by the compound. This study reports on phase-selective growth of both hexagonal tin (IV) sulfide SnS2 and orthorhombic tin (II) sulfide SnS crystals with diameters of over tens of microns on SiO2 substrates through atmospheric pressure vapor-phase method in a conventional horizontal quartz tube furnace with SnO2 and S powders as the source materials. Detailed characterization of each phase of tin sulfide crystals is performed using various microscopy and spectroscopy methods, and the results are corroborated by ab initio density functional theory calculations.
Competing coexisting phases in 2D water
NASA Astrophysics Data System (ADS)
Zanotti, Jean-Marc; Judeinstein, Patrick; Dalla-Bernardina, Simona; Creff, Gaëlle; Brubach, Jean-Blaise; Roy, Pascale; Bonetti, Marco; Ollivier, Jacques; Sakellariou, Dimitrios; Bellissent-Funel, Marie-Claire
2016-05-01
The properties of bulk water come from a delicate balance of interactions on length scales encompassing several orders of magnitudes: i) the Hydrogen Bond (HBond) at the molecular scale and ii) the extension of this HBond network up to the macroscopic level. Here, we address the physics of water when the three dimensional extension of the HBond network is frustrated, so that the water molecules are forced to organize in only two dimensions. We account for the large scale fluctuating HBond network by an analytical mean-field percolation model. This approach provides a coherent interpretation of the different events experimentally (calorimetry, neutron, NMR, near and far infra-red spectroscopies) detected in interfacial water at 160, 220 and 250 K. Starting from an amorphous state of water at low temperature, these transitions are respectively interpreted as the onset of creation of transient low density patches of 4-HBonded molecules at 160 K, the percolation of these domains at 220 K and finally the total invasion of the surface by them at 250 K. The source of this surprising behaviour in 2D is the frustration of the natural bulk tetrahedral local geometry and the underlying very significant increase in entropy of the interfacial water molecules.
Fast and robust recognition and localization of 2D objects
NASA Astrophysics Data System (ADS)
Otterbach, Rainer; Gerdes, Rolf; Kammueller, R.
1994-11-01
The paper presents a vision system which provides a robust model-based identification and localization of 2-D objects in industrial scenes. A symbolic image description based on the polygonal approximation of the object silhouettes is extracted in video real time by the use of dedicated hardware. Candidate objects are selected from the model database using a time and memory efficient hashing algorithm. Any candidate object is submitted to the next computation stage which generates pose hypotheses by assigning model to image contours. Corresponding continuous measures of similarity are derived from the turning functions of the curves. Finally, the previous generated hypotheses are verified using a voting scheme in transformation space. Experimental results reveal the fault tolerance of the vision system with regard to noisy and split image contours as well as partial occlusion of objects. THe short cycle time and the easy adaptability of the vision system make it well suited for a wide variety of applications in industrial automation.
Depth migration with Gaussian wave packets based on Poincaré wavelets
NASA Astrophysics Data System (ADS)
Gorodnitskiy, Evgeny; Perel, Maria; Geng, Yu; Wu, Ru-Shan
2016-04-01
An approach to depth migration, based on an integral representation of seismic data, that is, wavefields recorded on the boundary, is presented in terms of Poincaré wavelets. Each wavelet is taken as a boundary datum for a high-frequency asymptotic solution of the wave equation. This solution, which we call the quasiphoton or the Gaussian wave packet, decreases in a Gaussian manner away from a point running along a ray that is launched from the surface. The deformation of the propagating packet is taken into account in the migration algorithm. A numerical example of zero-offset migration with synthetic seismograms calculated for the 2-D SEG/EAGE salt model is presented. The result, which uses only 3.9 per cent of the total number of coefficients, is a satisfactory image, with a threshold of 0.75 per cent.
Serial identification of EEG patterns using adaptive wavelet-based analysis
NASA Astrophysics Data System (ADS)
Nazimov, A. I.; Pavlov, A. N.; Nazimova, A. A.; Grubov, V. V.; Koronovskii, A. A.; Sitnikova, E.; Hramov, A. E.
2013-10-01
A problem of recognition specific oscillatory patterns in the electroencephalograms with the continuous wavelet-transform is discussed. Aiming to improve abilities of the wavelet-based tools we propose a serial adaptive method for sequential identification of EEG patterns such as sleep spindles and spike-wave discharges. This method provides an optimal selection of parameters based on objective functions and enables to extract the most informative features of the recognized structures. Different ways of increasing the quality of patterns recognition within the proposed serial adaptive technique are considered.
Fractal Markets Hypothesis and the Global Financial Crisis: Wavelet Power Evidence
NASA Astrophysics Data System (ADS)
Kristoufek, Ladislav
2013-10-01
We analyze whether the prediction of the fractal markets hypothesis about a dominance of specific investment horizons during turbulent times holds. To do so, we utilize the continuous wavelet transform analysis and obtained wavelet power spectra which give the crucial information about the variance distribution across scales and its evolution in time. We show that the most turbulent times of the Global Financial Crisis can be very well characterized by the dominance of short investment horizons which is in hand with the assertions of the fractal markets hypothesis.
Fractal markets hypothesis and the global financial crisis: wavelet power evidence.
Kristoufek, Ladislav
2013-01-01
We analyze whether the prediction of the fractal markets hypothesis about a dominance of specific investment horizons during turbulent times holds. To do so, we utilize the continuous wavelet transform analysis and obtained wavelet power spectra which give the crucial information about the variance distribution across scales and its evolution in time. We show that the most turbulent times of the Global Financial Crisis can be very well characterized by the dominance of short investment horizons which is in hand with the assertions of the fractal markets hypothesis. PMID:24091386
Fractal Markets Hypothesis and the Global Financial Crisis: Wavelet Power Evidence
Kristoufek, Ladislav
2013-01-01
We analyze whether the prediction of the fractal markets hypothesis about a dominance of specific investment horizons during turbulent times holds. To do so, we utilize the continuous wavelet transform analysis and obtained wavelet power spectra which give the crucial information about the variance distribution across scales and its evolution in time. We show that the most turbulent times of the Global Financial Crisis can be very well characterized by the dominance of short investment horizons which is in hand with the assertions of the fractal markets hypothesis. PMID:24091386
Lachaux, Jean-Philippe; Lutz, Antoine; Rudrauf, David; Cosmelli, Diego; Le Van Quyen, Michel; Martinerie, Jacques; Varela, Francisco
2002-06-01
This paper introduces the use of wavelet analysis to follow the temporal variations in the coupling between oscillatory neural signals. Coherence, based on Fourier analysis, has been commonly used as a first approximation to track such coupling under the assumption that neural signals are stationary. Yet, stationary neural processing may be the exception rather than the rule. In this context, the recent application to physical systems of a wavelet-based coherence, which does not depend on the stationarity of the signals, is highly relevant. This paper fully develops the method of wavelet coherence and its statistical properties so that it can be practically applied to continuous neural signals. In realistic simulations, we show that, in contrast to Fourier coherence, wavelet coherence can detect short, significant episodes of coherence between non-stationary neural signals. This method can be directly applied for an 'online' quantification of the instantaneous coherence between two signals.
2-D Animation's Not Just for Mickey Mouse.
ERIC Educational Resources Information Center
Weinman, Lynda
1995-01-01
Discusses characteristics of two-dimensional (2-D) animation; highlights include character animation, painting issues, and motion graphics. Sidebars present Silicon Graphics animations tools and 2-D animation programs for the desktop computer. (DGM)
Velocity and Object Detection Using Quaternion Wavelets
Traversoni, Leonardo; Xu Yi
2007-09-06
DStarting from stereoscopic films we detect corresponding objects in both and stablish an epipolar geometry as well as corresponding moving objects are detected and its movement described all using quaternion wavelets and quaternion phase space decomposition.
Wavelet analysis for characterizing human electroencephalogram signals
NASA Astrophysics Data System (ADS)
Li, Bai-Lian; Wu, Hsin-i.
1995-04-01
Wavelet analysis is a recently developed mathematical theory and computational method for decomposing a nonstationary signal into components that have good localization properties both in time and frequency domains and hierarchical structures. Wavelet transform provides local information and multiresolution decomposition on a signal that cannot be obtained using traditional methods such as Fourier transforms and distribution-based statistical methods. Hence the change in complex biological signals can be detected. We use wavelet analysis as an innovative method for identifying and characterizing multiscale electroencephalogram signals in this paper. We develop a wavelet-based stationary phase transition method to extract instantaneous frequencies of the signal that vary in time. The results under different clinical situations show that the brian triggers small bursts of either low or high frequency immediately prior to changing on the global scale to that behavior. This information could be used as a diagnostic for detecting the onset of an epileptic seizure.
Wavelet-based acoustic recognition of aircraft
Dress, W.B.; Kercel, S.W.
1994-09-01
We describe a wavelet-based technique for identifying aircraft from acoustic emissions during take-off and landing. Tests show that the sensor can be a single, inexpensive hearing-aid microphone placed close to the ground the paper describes data collection, analysis by various technique, methods of event classification, and extraction of certain physical parameters from wavelet subspace projections. The primary goal of this paper is to show that wavelet analysis can be used as a divide-and-conquer first step in signal processing, providing both simplification and noise filtering. The idea is to project the original signal onto the orthogonal wavelet subspaces, both details and approximations. Subsequent analysis, such as system identification, nonlinear systems analysis, and feature extraction, is then carried out on the various signal subspaces.
50 CFR Table 2d to Part 660... - At-Sea Whiting Fishery Annual Set-Asides, 2014 and Beyond
Code of Federal Regulations, 2014 CFR
2014-10-01
... 50 Wildlife and Fisheries 13 2014-10-01 2014-10-01 false At-Sea Whiting Fishery Annual Set-Asides, 2014 and Beyond 2d Table 2d to Part 660, Subpart C Wildlife and Fisheries FISHERY CONSERVATION AND MANAGEMENT, NATIONAL OCEANIC AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE (CONTINUED) FISHERIES OFF WEST COAST STATES Pt. 660, Subpt....
50 CFR Table 2d to Part 660... - At-Sea Whiting Fishery Annual Set-Asides, 2014 and Beyond
Code of Federal Regulations, 2013 CFR
2013-10-01
... 50 Wildlife and Fisheries 13 2013-10-01 2013-10-01 false At-Sea Whiting Fishery Annual Set-Asides, 2014 and Beyond 2d Table 2d to Part 660, Subpart C Wildlife and Fisheries FISHERY CONSERVATION AND MANAGEMENT, NATIONAL OCEANIC AND ATMOSPHERIC ADMINISTRATION, DEPARTMENT OF COMMERCE (CONTINUED) FISHERIES OFF WEST COAST STATES Pt. 660, Subpt....
Generates 2D Input for DYNA NIKE & TOPAZ
Hallquist, J. O.; Sanford, Larry
1996-07-15
MAZE is an interactive program that serves as an input and two-dimensional mesh generator for DYNA2D, NIKE2D, TOPAZ2D, and CHEMICAL TOPAZ2D. MAZE also generates a basic template for ISLAND input. MAZE has been applied to the generation of input data to study the response of two-dimensional solids and structures undergoing finite deformations under a wide variety of large deformation transient dynamic and static problems and heat transfer analyses.
MAZE96. Generates 2D Input for DYNA NIKE & TOPAZ
Sanford, L.; Hallquist, J.O.
1992-02-24
MAZE is an interactive program that serves as an input and two-dimensional mesh generator for DYNA2D, NIKE2D, TOPAZ2D, and CHEMICAL TOPAZ2D. MAZE also generates a basic template for ISLAND input. MAZE has been applied to the generation of input data to study the response of two-dimensional solids and structures undergoing finite deformations under a wide variety of large deformation transient dynamic and static problems and heat transfer analyses.
NASA Astrophysics Data System (ADS)
Andre, Julia; Kiremidjian, Anne; Liao, Yizheng; Georgakis, Christos; Rajagopal, Ram
2016-04-01
Ice accretion on cables of bridge structures poses serious risk to the structure as well as to vehicular traffic when the ice falls onto the road. Detection of ice formation, quantification of the amount of ice accumulated, and prediction of icefalls will increase the safety and serviceability of the structure. In this paper, an ice accretion detection algorithm is presented based on the Continuous Wavelet Transform (CWT). In the proposed algorithm, the acceleration signals obtained from bridge cables are transformed using wavelet method. The damage sensitive features (DSFs) are defined as a function of the wavelet energy at specific wavelet scales. It is found that as ice accretes on the cables, the mass of cable increases, thus changing the wavelet energies. Hence, the DSFs can be used to track the change of cables mass. To validate the proposed algorithm, we use the data collected from a laboratory experiment conducted at the Technical University of Denmark (DTU). In this experiment, a cable was placed in a wind tunnel as ice volume grew progressively. Several accelerometers were installed at various locations along the testing cable to collect vibration signals.
2d PDE Linear Symmetric Matrix Solver
1983-10-01
ICCG2 (Incomplete Cholesky factorized Conjugate Gradient algorithm for 2d symmetric problems) was developed to solve a linear symmetric matrix system arising from a 9-point discretization of two-dimensional elliptic and parabolic partial differential equations found in plasma physics applications, such as resistive MHD, spatial diffusive transport, and phase space transport (Fokker-Planck equation) problems. These problems share the common feature of being stiff and requiring implicit solution techniques. When these parabolic or elliptic PDE''s are discretized withmore » finite-difference or finite-element methods,the resulting matrix system is frequently of block-tridiagonal form. To use ICCG2, the discretization of the two-dimensional partial differential equation and its boundary conditions must result in a block-tridiagonal supermatrix composed of elementary tridiagonal matrices. The incomplete Cholesky conjugate gradient algorithm is used to solve the linear symmetric matrix equation. Loops are arranged to vectorize on the Cray1 with the CFT compiler, wherever possible. Recursive loops, which cannot be vectorized, are written for optimum scalar speed. For matrices lacking symmetry, ILUCG2 should be used. Similar methods in three dimensions are available in ICCG3 and ILUCG3. A general source containing extensions and macros, which must be processed by a pre-compiler to obtain the standard FORTRAN source, is provided along with the standard FORTRAN source because it is believed to be more readable. The pre-compiler is not included, but pre-compilation may be performed by a text editor as described in the UCRL-88746 Preprint.« less
2d PDE Linear Asymmetric Matrix Solver
1983-10-01
ILUCG2 (Incomplete LU factorized Conjugate Gradient algorithm for 2d problems) was developed to solve a linear asymmetric matrix system arising from a 9-point discretization of two-dimensional elliptic and parabolic partial differential equations found in plasma physics applications, such as plasma diffusion, equilibria, and phase space transport (Fokker-Planck equation) problems. These equations share the common feature of being stiff and requiring implicit solution techniques. When these parabolic or elliptic PDE''s are discretized with finite-difference or finite-elementmore » methods, the resulting matrix system is frequently of block-tridiagonal form. To use ILUCG2, the discretization of the two-dimensional partial differential equation and its boundary conditions must result in a block-tridiagonal supermatrix composed of elementary tridiagonal matrices. A generalization of the incomplete Cholesky conjugate gradient algorithm is used to solve the matrix equation. Loops are arranged to vectorize on the Cray1 with the CFT compiler, wherever possible. Recursive loops, which cannot be vectorized, are written for optimum scalar speed. For problems having a symmetric matrix ICCG2 should be used since it runs up to four times faster and uses approximately 30% less storage. Similar methods in three dimensions are available in ICCG3 and ILUCG3. A general source, containing extensions and macros, which must be processed by a pre-compiler to obtain the standard FORTRAN source, is provided along with the standard FORTRAN source because it is believed to be more readable. The pre-compiler is not included, but pre-compilation may be performed by a text editor as described in the UCRL-88746 Preprint.« less
Smart-phone based electrocardiogram wavelet decomposition and neural network classification
NASA Astrophysics Data System (ADS)
Jannah, N.; Hadjiloucas, S.; Hwang, F.; Galvão, R. K. H.
2013-06-01
This paper discusses ECG classification after parametrizing the ECG waveforms in the wavelet domain. The aim of the work is to develop an accurate classification algorithm that can be used to diagnose cardiac beat abnormalities detected using a mobile platform such as smart-phones. Continuous time recurrent neural network classifiers are considered for this task. Records from the European ST-T Database are decomposed in the wavelet domain using discrete wavelet transform (DWT) filter banks and the resulting DWT coefficients are filtered and used as inputs for training the neural network classifier. Advantages of the proposed methodology are the reduced memory requirement for the signals which is of relevance to mobile applications as well as an improvement in the ability of the neural network in its generalization ability due to the more parsimonious representation of the signal to its inputs.
CW-THz image contrast enhancement using wavelet transform and Retinex
NASA Astrophysics Data System (ADS)
Chen, Lin; Zhang, Min; Hu, Qi-fan; Huang, Ying-Xue; Liang, Hua-Wei
2015-10-01
To enhance continuous wave terahertz (CW-THz) scanning images contrast and denoising, a method based on wavelet transform and Retinex theory was proposed. In this paper, the factors affecting the quality of CW-THz images were analysed. Second, an approach of combination of the discrete wavelet transform (DWT) and a designed nonlinear function in wavelet domain for the purpose of contrast enhancing was applied. Then, we combine the Retinex algorithm for further contrast enhancement. To evaluate the effectiveness of the proposed method in qualitative and quantitative, it was compared with the adaptive histogram equalization method, the homomorphic filtering method and the SSR(Single-Scale-Retinex) method. Experimental results demonstrated that the presented algorithm can effectively enhance the contrast of CW-THZ image and obtain better visual effect.
Wavelet neural networks for stock trading
NASA Astrophysics Data System (ADS)
Zheng, Tianxing; Fataliyev, Kamaladdin; Wang, Lipo
2013-05-01
This paper explores the application of a wavelet neural network (WNN), whose hidden layer is comprised of neurons with adjustable wavelets as activation functions, to stock prediction. We discuss some basic rationales behind technical analysis, and based on which, inputs of the prediction system are carefully selected. This system is tested on Istanbul Stock Exchange National 100 Index and compared with traditional neural networks. The results show that the WNN can achieve very good prediction accuracy.
A Planar Quantum Transistor Based on 2D-2D Tunneling in Double Quantum Well Heterostructures
Baca, W.E.; Blount, M.A.; Hafich, M.J.; Lyo, S.K.; Moon, J.S.; Reno, J.L.; Simmons, J.A.; Wendt, J.R.
1998-12-14
We report on our work on the double electron layer tunneling transistor (DELTT), based on the gate-control of two-dimensional -- two-dimensional (2D-2D) tunneling in a double quantum well heterostructure. While previous quantum transistors have typically required tiny laterally-defined features, by contrast the DELTT is entirely planar and can be reliably fabricated in large numbers. We use a novel epoxy-bond-and-stop-etch (EBASE) flip-chip process, whereby submicron gating on opposite sides of semiconductor epitaxial layers as thin as 0.24 microns can be achieved. Because both electron layers in the DELTT are 2D, the resonant tunneling features are unusually sharp, and can be easily modulated with one or more surface gates. We demonstrate DELTTs with peak-to-valley ratios in the source-drain I-V curve of order 20:1 below 1 K. Both the height and position of the resonant current peak can be controlled by gate voltage over a wide range. DELTTs with larger subband energy offsets ({approximately} 21 meV) exhibit characteristics that are nearly as good at 77 K, in good agreement with our theoretical calculations. Using these devices, we also demonstrate bistable memories operating at 77 K. Finally, we briefly discuss the prospects for room temperature operation, increases in gain, and high-speed.
'Brukin2D': a 2D visualization and comparison tool for LC-MS data
Tsagkrasoulis, Dimosthenis; Zerefos, Panagiotis; Loudos, George; Vlahou, Antonia; Baumann, Marc; Kossida, Sophia
2009-01-01
Background Liquid Chromatography-Mass Spectrometry (LC-MS) is a commonly used technique to resolve complex protein mixtures. Visualization of large data sets produced from LC-MS, namely the chromatogram and the mass spectra that correspond to its compounds is the focus of this work. Results The in-house developed 'Brukin2D' software, built in Matlab 7.4, which is presented here, uses the compound data that are exported from the Bruker 'DataAnalysis' program, and depicts the mean mass spectra of all the chromatogram compounds from one LC-MS run, in one 2D contour/density plot. Two contour plots from different chromatograph runs can then be viewed in the same window and automatically compared, in order to find their similarities and differences. The results of the comparison can be examined through detailed mass quantification tables, while chromatogram compound statistics are also calculated during the procedure. Conclusion 'Brukin2D' provides a user-friendly platform for quick, easy and integrated view of complex LC-MS data. The software is available at . PMID:19534737
Inhibition of human cytochrome P450 2D6 (CYP2D6) by methadone.
Wu, D; Otton, S V; Sproule, B A; Busto, U; Inaba, T; Kalow, W; Sellers, E M
1993-01-01
1. In microsomes prepared from three human livers, methadone competitively inhibited the O-demethylation of dextromethorphan, a marker substrate for CYP2D6. The apparent Ki value of methadone ranged from 2.5 to 5 microM. 2. Two hundred and fifty-two (252) white Caucasians, including 210 unrelated healthy volunteers and 42 opiate abusers undergoing treatment with methadone were phenotyped using dextromethorphan as the marker drug. Although the frequency of poor metabolizers was similar in both groups, the extensive metabolizers among the opiate abusers tended to have higher O-demethylation metabolic ratios and to excrete less of the dose as dextromethorphan metabolites than control extensive metabolizer subjects. These data suggest inhibition of CYP2D6 by methadone in vivo as well. 3. Because methadone is widely used in the treatment of opiate abuse, inhibition of CYP2D6 activity in these patients might contribute to exaggerated response or unexpected toxicity from drugs that are substrates of this enzyme. PMID:8448065
Correlated Electron Phenomena in 2D Materials
NASA Astrophysics Data System (ADS)
Lambert, Joseph G.
In this thesis, I present experimental results on coherent electron phenomena in layered two-dimensional materials: single layer graphene and van der Waals coupled 2D TiSe2. Graphene is a two-dimensional single-atom thick sheet of carbon atoms first derived from bulk graphite by the mechanical exfoliation technique in 2004. Low-energy charge carriers in graphene behave like massless Dirac fermions, and their density can be easily tuned between electron-rich and hole-rich quasiparticles with electrostatic gating techniques. The sharp interfaces between regions of different carrier densities form barriers with selective transmission, making them behave as partially reflecting mirrors. When two of these interfaces are set at a separation distance within the phase coherence length of the carriers, they form an electronic version of a Fabry-Perot cavity. I present measurements and analysis of multiple Fabry-Perot modes in graphene with parallel electrodes spaced a few hundred nanometers apart. Transition metal dichalcogenide (TMD) TiSe2 is part of the family of materials that coined the term "materials beyond graphene". It contains van der Waals coupled trilayer stacks of Se-Ti-Se. Many TMD materials exhibit a host of interesting correlated electronic phases. In particular, TiSe2 exhibits chiral charge density waves (CDW) below TCDW ˜ 200 K. Upon doping with copper, the CDW state gets suppressed with Cu concentration, and CuxTiSe2 becomes superconducting with critical temperature of T c = 4.15 K. There is still much debate over the mechanisms governing the coexistence of the two correlated electronic phases---CDW and superconductivity. I will present some of the first conductance spectroscopy measurements of proximity coupled superconductor-CDW systems. Measurements reveal a proximity-induced critical current at the Nb-TiSe2 interfaces, suggesting pair correlations in the pure TiSe2. The results indicate that superconducting order is present concurrently with CDW in
Frequency Domain Modelling by a Direct-Iterative Solver: A Space and Wavelet Approach
NASA Astrophysics Data System (ADS)
Hustedt, B.; Operto, S.; Virieux, J.
2002-12-01
Seismic forward modelling of wave propagation phenomena in complex rheologic media using a frequency domain finite-difference (FDFD) technique is of special interest for multisource experiments and waveform inversion schemes, because the complete wavefield solution can be computed in a fast and efficient way. FDFD modelling requires the inversion of an extremely large matrix-equation A x x = b, by either a direct or an iterative solver. The direct solver computes an effective inverse of A, called LU factorization. The main handicap is additional computer memory required for storing matrix fill-in coefficients, that are created during the factorization process. Iterative solvers are not limited by memory constraints (additional coefficients), but the convergence depends on a good initial solution difficult to guess before hand. For both solvers, available computer resources has limited wide-spread FDFD modelling applications to mainly two-dimensional (2D) and rarely three-dimensional (3D) problems. In order to overcome these limits, we propose the combination of a direct solver and an iterative solver, called Direct-Iterative Solver (DIS). The direct solver is used to compute an exact wavefield solution on a coarse discretized grid. We use a multifrontal decomposition technique. The coarse-grid size is determined preliminary by limits of the available computer resources, rather than by the wave simulation problem. We project the exact coarse-grid solution on a fine-grid, and use it as an initial solution for an iterative solver, which convergences to an acceptable approximation of the desired fine-grid solution. Two different DIS schemes have been implemented and tested for numerical accuracy and computational performance. The first approach, called the Direct-Iterative-Space Solver (DISS), projects the coarse-grid solution on the fine-grid by a bilinear interpolation. Though the interpolated solution nicely approximates the desired fine-grid solution, still for
CYP2D7 Sequence Variation Interferes with TaqMan CYP2D6*15 and *35 Genotyping
Riffel, Amanda K.; Dehghani, Mehdi; Hartshorne, Toinette; Floyd, Kristen C.; Leeder, J. Steven; Rosenblatt, Kevin P.; Gaedigk, Andrea
2016-01-01
TaqMan™ genotyping assays are widely used to genotype CYP2D6, which encodes a major drug metabolizing enzyme. Assay design for CYP2D6 can be challenging owing to the presence of two pseudogenes, CYP2D7 and CYP2D8, structural and copy number variation and numerous single nucleotide polymorphisms (SNPs) some of which reflect the wild-type sequence of the CYP2D7 pseudogene. The aim of this study was to identify the mechanism causing false-positive CYP2D6*15 calls and remediate those by redesigning and validating alternative TaqMan genotype assays. Among 13,866 DNA samples genotyped by the CompanionDx® lab on the OpenArray platform, 70 samples were identified as heterozygotes for 137Tins, the key SNP of CYP2D6*15. However, only 15 samples were confirmed when tested with the Luminex xTAG CYP2D6 Kit and sequencing of CYP2D6-specific long range (XL)-PCR products. Genotype and gene resequencing of CYP2D6 and CYP2D7-specific XL-PCR products revealed a CC>GT dinucleotide SNP in exon 1 of CYP2D7 that reverts the sequence to CYP2D6 and allows a TaqMan assay PCR primer to bind. Because CYP2D7 also carries a Tins, a false-positive mutation signal is generated. This CYP2D7 SNP was also responsible for generating false-positive signals for rs769258 (CYP2D6*35) which is also located in exon 1. Although alternative CYP2D6*15 and *35 assays resolved the issue, we discovered a novel CYP2D6*15 subvariant in one sample that carries additional SNPs preventing detection with the alternate assay. The frequency of CYP2D6*15 was 0.1% in this ethnically diverse U.S. population sample. In addition, we also discovered linkage between the CYP2D7 CC>GT dinucleotide SNP and the 77G>A (rs28371696) SNP of CYP2D6*43. The frequency of this tentatively functional allele was 0.2%. Taken together, these findings emphasize that regardless of how careful genotyping assays are designed and evaluated before being commercially marketed, rare or unknown SNPs underneath primer and/or probe regions can impact
CYP2D7 Sequence Variation Interferes with TaqMan CYP2D6 (*) 15 and (*) 35 Genotyping.
Riffel, Amanda K; Dehghani, Mehdi; Hartshorne, Toinette; Floyd, Kristen C; Leeder, J Steven; Rosenblatt, Kevin P; Gaedigk, Andrea
2015-01-01
TaqMan™ genotyping assays are widely used to genotype CYP2D6, which encodes a major drug metabolizing enzyme. Assay design for CYP2D6 can be challenging owing to the presence of two pseudogenes, CYP2D7 and CYP2D8, structural and copy number variation and numerous single nucleotide polymorphisms (SNPs) some of which reflect the wild-type sequence of the CYP2D7 pseudogene. The aim of this study was to identify the mechanism causing false-positive CYP2D6 (*) 15 calls and remediate those by redesigning and validating alternative TaqMan genotype assays. Among 13,866 DNA samples genotyped by the CompanionDx® lab on the OpenArray platform, 70 samples were identified as heterozygotes for 137Tins, the key SNP of CYP2D6 (*) 15. However, only 15 samples were confirmed when tested with the Luminex xTAG CYP2D6 Kit and sequencing of CYP2D6-specific long range (XL)-PCR products. Genotype and gene resequencing of CYP2D6 and CYP2D7-specific XL-PCR products revealed a CC>GT dinucleotide SNP in exon 1 of CYP2D7 that reverts the sequence to CYP2D6 and allows a TaqMan assay PCR primer to bind. Because CYP2D7 also carries a Tins, a false-positive mutation signal is generated. This CYP2D7 SNP was also responsible for generating false-positive signals for rs769258 (CYP2D6 (*) 35) which is also located in exon 1. Although alternative CYP2D6 (*) 15 and (*) 35 assays resolved the issue, we discovered a novel CYP2D6 (*) 15 subvariant in one sample that carries additional SNPs preventing detection with the alternate assay. The frequency of CYP2D6 (*) 15 was 0.1% in this ethnically diverse U.S. population sample. In addition, we also discovered linkage between the CYP2D7 CC>GT dinucleotide SNP and the 77G>A (rs28371696) SNP of CYP2D6 (*) 43. The frequency of this tentatively functional allele was 0.2%. Taken together, these findings emphasize that regardless of how careful genotyping assays are designed and evaluated before being commercially marketed, rare or unknown SNPs underneath primer
Multiparameter radar analysis using wavelets
NASA Astrophysics Data System (ADS)
Tawfik, Ben Bella Sayed
Multiparameter radars have been used in the interpretation of many meteorological phenomena. Rainfall estimates can be obtained from multiparameter radar measurements. Studying and analyzing spatial variability of different rainfall algorithms, namely R(ZH), the algorithm based on reflectivity, R(ZH, ZDR), the algorithm based on reflectivity and differential reflectivity, R(KDP), the algorithm based on specific differential phase, and R(KDP, Z DR), the algorithm based on specific differential phase and differential reflectivity, are important for radar applications. The data used in this research were collected using CSU-CHILL, CP-2, and S-POL radars. In this research multiple objectives are addressed using wavelet analysis namely, (1)space time variability of various rainfall algorithms, (2)separation of convective and stratiform storms based on reflectivity measurements, (3)and detection of features such as bright bands. The bright band is a multiscale edge detection problem. In this research, the technique of multiscale edge detection is applied on the radar data collected using CP-2 radar on August 23, 1991 to detect the melting layer. In the analysis of space/time variability of rainfall algorithms, wavelet variance introduces an idea about the statistics of the radar field. In addition, multiresolution analysis of different rainfall estimates based on four algorithms, namely R(ZH), R( ZH, ZDR), R(K DP), and R(KDP, Z DR), are analyzed. The flood data of July 29, 1997 collected by CSU-CHILL radar were used for this analysis. Another set of S-POL radar data collected on May 2, 1997 at Wichita, Kansas were used as well. At each level of approximation, the detail and the approximation components are analyzed. Based on this analysis, the rainfall algorithms can be judged. From this analysis, an important result was obtained. The Z-R algorithms that are widely used do not show the full spatial variability of rainfall. In addition another intuitively obvious result
NASA Astrophysics Data System (ADS)
Vaudor, Lise; Piegay, Herve; Wawrzyniak, Vincent; Spitoni, Marie
2016-04-01
The form and functioning of a geomorphic system result from processes operating at various spatial and temporal scales. Longitudinal channel characteristics thus exhibit complex patterns which vary according to the scale of study, might be periodic or segmented, and are generally blurred by noise. Describing the intricate, multiscale structure of such signals, and identifying at which scales the patterns are dominant and over which sub-reach, could help determine at which scales they should be investigated, and provide insights into the main controlling factors. Wavelet transforms aim at describing data at multiple scales (either in time or space), and are now exploited in geophysics for the analysis of nonstationary series of data. They provide a consistent, non-arbitrary, and multiscale description of a signal's variations and help explore potential causalities. Nevertheless, their use in fluvial geomorphology, notably to study longitudinal patterns, is hindered by a lack of user-friendly tools to help understand, implement, and interpret them. We have developed a free application, The Wavelet ToolKat, designed to facilitate the use of wavelet transforms on temporal or spatial series. We illustrate its usefulness describing longitudinal channel curvature and slope of three freely meandering rivers in the Amazon basin (the Purus, Juruá and Madre de Dios rivers), using topographic data generated from NASA's Shuttle Radar Topography Mission (SRTM) in 2000. Three types of wavelet transforms are used, with different purposes. Continuous Wavelet Transforms are used to identify in a non-arbitrary way the dominant scales and locations at which channel curvature and slope vary. Cross-wavelet transforms, and wavelet coherence and phase are used to identify scales and locations exhibiting significant channel curvature and slope co-variations. Maximal Overlap Discrete Wavelet Transforms decompose data into their variations at a series of scales and are used to provide
Hoang, Vu Dang; Loan, Nguyen Thi; Tho, Vu Thi; Nguyen, Hue Minh Thi
2014-01-01
Signal processing methods based on the use of derivative, Fourier and wavelet transforms were proposed for the spectrophotometric simultaneous determination of cefoperazone and sulbactam in powders for injection. These transforms were successfully applied to UV spectra and ratio spectra to find suitable working wavelengths. Wavelet signal processing was proved to have distinct advantages (i.e. higher peak intensity obtained, additional smooth function and scaling factor process eliminated) over derivative and Fourier transforms. Especially, a better resolution of spectral overlapping bands was obtained by the use of double signal transform in the sequences such as (i) spectra pre-processed by Fractional Wavelet Transform and subsequently subjected to Continuous Wavelet Transform or Discrete Wavelet Transform, and (ii) derivative - wavelet transforms combined. Calibration graphs for cefoperazone and sulbactam were recorded for the range 10-35 mg/L. Good accuracy and precision were reported for all proposed methods by analyzing synthetic mixtures of cefoperazone and sulbactam. Furthermore, these methods were statistically comparable to RP-HPLC.
NASA Astrophysics Data System (ADS)
Wang, Zhengzi; Ren, Zhong; Liu, Guodong
2015-10-01
Noninvasive measurement of blood glucose concentration has become a hotspot research in the world due to its characteristic of convenient, rapid and non-destructive etc. The blood glucose concentration monitoring based on photoacoustic technique has attracted many attentions because the detected signal is ultrasonic signals rather than the photo signals. But during the acquisition of the photoacoustic signals of glucose, the photoacoustic signals are not avoid to be polluted by some factors, such as the pulsed laser, electronic noises and circumstance noises etc. These disturbances will impact the measurement accuracy of the glucose concentration, So, the denoising of the glucose photoacoustic signals is a key work. In this paper, a wavelet shift-invariant threshold denoising method is improved, and a novel wavelet threshold function is proposed. For the novel wavelet threshold function, two threshold values and two different factors are set, and the novel function is high order derivative and continuous, which can be looked as the compromise between the wavelet soft threshold denoising and hard threshold denoising. Simulation experimental results illustrate that, compared with other wavelet threshold denoising, this improved wavelet shift-invariant threshold denoising has higher signal-to-noise ratio(SNR) and smaller root mean-square error (RMSE) value. And this improved denoising also has better denoising effect than others. Therefore, this improved denoising has a certain of potential value in the denoising of glucose photoacoustic signals.
Tankanag, Arina V; Chemeris, Nikolay K
2009-10-01
The paper describes an original method for analysis of the peripheral blood flow oscillations measured with the laser Doppler flowmetry (LDF) technique. The method is based on the continuous wavelet transform and adaptive wavelet theory and applies an adaptive wavelet filtering to the LDF data. The method developed allows one to examine the dynamics of amplitude oscillations in a wide frequency range (from 0.007 to 2 Hz) and to process both stationary and non-stationary short (6 min) signals. The capabilities of the method have been demonstrated by analyzing LDF signals registered in the state of rest and upon humeral occlusion. The paper shows the main advantage of the method proposed, which is the significant reduction of 'border effects', as compared to the traditional wavelet analysis. It was found that the low-frequency amplitudes obtained by adaptive wavelets are significantly higher than those obtained by non-adaptive ones. The method suggested would be useful for the analysis of low-frequency components of the short-living transitional processes under the conditions of functional tests. The method of adaptive wavelet filtering can be used to process stationary and non-stationary biomedical signals (cardiograms, encephalograms, myograms, etc), as well as signals studied in the other fields of science and engineering.
3D weak lensing with spin wavelets on the ball
NASA Astrophysics Data System (ADS)
Leistedt, Boris; McEwen, Jason D.; Kitching, Thomas D.; Peiris, Hiranya V.
2015-12-01
We construct the spin flaglet transform, a wavelet transform to analyze spin signals in three dimensions. Spin flaglets can probe signal content localized simultaneously in space and frequency and, moreover, are separable so that their angular and radial properties can be controlled independently. They are particularly suited to analyzing cosmological observations such as the weak gravitational lensing of galaxies. Such observations have a unique 3D geometrical setting since they are natively made on the sky, have spin angular symmetries, and are extended in the radial direction by additional distance or redshift information. Flaglets are constructed in the harmonic space defined by the Fourier-Laguerre transform, previously defined for scalar functions and extended here to signals with spin symmetries. Thanks to various sampling theorems, both the Fourier-Laguerre and flaglet transforms are theoretically exact when applied to bandlimited signals. In other words, in numerical computations the only loss of information is due to the finite representation of floating point numbers. We develop a 3D framework relating the weak lensing power spectrum to covariances of flaglet coefficients. We suggest that the resulting novel flaglet weak lensing estimator offers a powerful alternative to common 2D and 3D approaches to accurately capture cosmological information. While standard weak lensing analyses focus on either real- or harmonic-space representations (i.e., correlation functions or Fourier-Bessel power spectra, respectively), a wavelet approach inherits the advantages of both techniques, where both complicated sky coverage and uncertainties associated with the physical modeling of small scales can be handled effectively. Our codes to compute the Fourier-Laguerre and flaglet transforms are made publicly available.
Mechanical characterization of 2D, 2D stitched, and 3D braided/RTM materials
NASA Technical Reports Server (NTRS)
Deaton, Jerry W.; Kullerd, Susan M.; Portanova, Marc A.
1993-01-01
Braided composite materials have potential for application in aircraft structures. Fuselage frames, floor beams, wing spars, and stiffeners are examples where braided composites could find application if cost effective processing and damage tolerance requirements are met. Another important consideration for braided composites relates to their mechanical properties and how they compare to the properties of composites produced by other textile composite processes being proposed for these applications. Unfortunately, mechanical property data for braided composites do not appear extensively in the literature. Data are presented in this paper on the mechanical characterization of 2D triaxial braid, 2D triaxial braid plus stitching, and 3D (through-the-thickness) braid composite materials. The braided preforms all had the same graphite tow size and the same nominal braid architectures, (+/- 30 deg/0 deg), and were resin transfer molded (RTM) using the same mold for each of two different resin systems. Static data are presented for notched and unnotched tension, notched and unnotched compression, and compression after impact strengths at room temperature. In addition, some static results, after environmental conditioning, are included. Baseline tension and compression fatigue results are also presented, but only for the 3D braided composite material with one of the resin systems.
Image wavelet decomposition and applications
NASA Technical Reports Server (NTRS)
Treil, N.; Mallat, S.; Bajcsy, R.
1989-01-01
The general problem of computer vision has been investigated for more that 20 years and is still one of the most challenging fields in artificial intelligence. Indeed, taking a look at the human visual system can give us an idea of the complexity of any solution to the problem of visual recognition. This general task can be decomposed into a whole hierarchy of problems ranging from pixel processing to high level segmentation and complex objects recognition. Contrasting an image at different representations provides useful information such as edges. An example of low level signal and image processing using the theory of wavelets is introduced which provides the basis for multiresolution representation. Like the human brain, we use a multiorientation process which detects features independently in different orientation sectors. So, images of the same orientation but of different resolutions are contrasted to gather information about an image. An interesting image representation using energy zero crossings is developed. This representation is shown to be experimentally complete and leads to some higher level applications such as edge and corner finding, which in turn provides two basic steps to image segmentation. The possibilities of feedback between different levels of processing are also discussed.
Wavelet Analysis for Investigation of Precise Gnss Solutions' Credibility
NASA Astrophysics Data System (ADS)
Bogusz, Janusz; Klos, Anna
2010-01-01
This publication presents the results of searching short-term oscillations of the ASG network sites using wavelet transform. Polish Active Geodetic Network (ASG-EUPOS) is the multifunctional precise satellite positioning system established by the Head Office of Geodesy and Cartography in 2008. The adjusted network consisted of over 130 stations from Poland and neighbouring countries. The period covered observations gathered from June 2008 to July 2010. The method of processing elaborated in the CAG (Centre of Applied Geomatics, Warsaw Military University of Technology), which is one of the 17 EPN LAC (EUREF Permanent Network Local Analysis Centre) acting now in Europe, established at the end of 2009, is similar with the official one used in EPN. It is based on the Bernese 5.0 software, but the difference to the EPN's solutions lies in the resolution of resulting coordinates. In the presented research the 1-hour sampling rate with 3-hour windowing (66% of correlation) is applied. This allows us to make the interpretations concerning short period information in GNSS (Global Navigation Satellite System) coordinates series. Analyses using FFT and least squares (tidal) gave very coherent results and confirmed several millimetres diurnal and sub-diurnal oscillations. Wavelet analysis is aimed at the investigation of credibility of the precise GNSS solutions in terms of changes of the amplitude of oscillations in time. As a result of this study the changes in the amplitude of oscillations at diurnal and sub-diurnal frequency bands were obtained. These could be caused by the artificial modulations of the near-by frequencies, but also some geophysical signals could be clearly distinguished. Additionally the comparison of Continuous Wavelet Transforms of near stations (three pairs from ASG-EUPOS network) was performed. This comparison showed different behaviour of oscillations of residual coordinates, mainly due to the different thermal response or artefacts related to the
Wavelet based detection of manatee vocalizations
NASA Astrophysics Data System (ADS)
Gur, Berke M.; Niezrecki, Christopher
2005-04-01
The West Indian manatee (Trichechus manatus latirostris) has become endangered partly because of watercraft collisions in Florida's coastal waterways. Several boater warning systems, based upon manatee vocalizations, have been proposed to reduce the number of collisions. Three detection methods based on the Fourier transform (threshold, harmonic content and autocorrelation methods) were previously suggested and tested. In the last decade, the wavelet transform has emerged as an alternative to the Fourier transform and has been successfully applied in various fields of science and engineering including the acoustic detection of dolphin vocalizations. As of yet, no prior research has been conducted in analyzing manatee vocalizations using the wavelet transform. Within this study, the wavelet transform is used as an alternative to the Fourier transform in detecting manatee vocalizations. The wavelet coefficients are analyzed and tested against a specified criterion to determine the existence of a manatee call. The performance of the method presented is tested on the same data previously used in the prior studies, and the results are compared. Preliminary results indicate that using the wavelet transform as a signal processing technique to detect manatee vocalizations shows great promise.
Review of wavelet transforms for pattern recognitions
NASA Astrophysics Data System (ADS)
Szu, Harold H.
1996-03-01
After relating the adaptive wavelet transform to the human visual and hearing systems, we exploit the synergism between such a smart sensor processing with brain-style neural network computing. The freedom of choosing an appropriate kernel of a linear transform, which is given to us by the recent mathematical foundation of the wavelet transform, is exploited fully and is generally called the adaptive wavelet transform (WT). However, there are several levels of adaptivity: (1) optimum coefficients: adjustable transform coefficients chosen with respect to a fixed mother kernel for better invariant signal representation, (2) super-mother: grouping different scales of daughter wavelets of same or different mother wavelets at different shift location into a new family called a superposition mother kernel for better speech signal classification, (3) variational calculus to determine ab initio a constraint optimization mother for a specific task. The tradeoff between the mathematical rigor of the complete orthonormality and the speed of order (N) with the adaptive flexibility is finally up to the user's needs. Then, to illustrate (1), a new invariant optoelectronic architecture of a wedge- shape filter in the WT domain is given for scale-invariant signal classification by neural networks.
Lifting wavelet method of target detection
NASA Astrophysics Data System (ADS)
Han, Jun; Zhang, Chi; Jiang, Xu; Wang, Fang; Zhang, Jin
2009-11-01
Image target recognition plays a very important role in the areas of scientific exploration, aeronautics and space-to-ground observation, photography and topographic mapping. Complex environment of the image noise, fuzzy, all kinds of interference has always been to affect the stability of recognition algorithm. In this paper, the existence of target detection in real-time, accuracy problems, as well as anti-interference ability, using lifting wavelet image target detection methods. First of all, the use of histogram equalization, the goal difference method to obtain the region, on the basis of adaptive threshold and mathematical morphology operations to deal with the elimination of the background error. Secondly, the use of multi-channel wavelet filter wavelet transform of the original image de-noising and enhancement, to overcome the general algorithm of the noise caused by the sensitive issue of reducing the rate of miscarriage of justice will be the multi-resolution characteristics of wavelet and promotion of the framework can be designed directly in the benefits of space-time region used in target detection, feature extraction of targets. The experimental results show that the design of lifting wavelet has solved the movement of the target due to the complexity of the context of the difficulties caused by testing, which can effectively suppress noise, and improve the efficiency and speed of detection.
Learning from graphically integrated 2D and 3D representations improves retention of neuroanatomy
NASA Astrophysics Data System (ADS)
Naaz, Farah
Visualizations in the form of computer-based learning environments are highly encouraged in science education, especially for teaching spatial material. Some spatial material, such as sectional neuroanatomy, is very challenging to learn. It involves learning the two dimensional (2D) representations that are sampled from the three dimensional (3D) object. In this study, a computer-based learning environment was used to explore the hypothesis that learning sectional neuroanatomy from a graphically integrated 2D and 3D representation will lead to better learning outcomes than learning from a sequential presentation. The integrated representation explicitly demonstrates the 2D-3D transformation and should lead to effective learning. This study was conducted using a computer graphical model of the human brain. There were two learning groups:
Computational Screening of 2D Materials for Photocatalysis.
Singh, Arunima K; Mathew, Kiran; Zhuang, Houlong L; Hennig, Richard G
2015-03-19
Two-dimensional (2D) materials exhibit a range of extraordinary electronic, optical, and mechanical properties different from their bulk counterparts with potential applications for 2D materials emerging in energy storage and conversion technologies. In this Perspective, we summarize the recent developments in the field of solar water splitting using 2D materials and review a computational screening approach to rapidly and efficiently discover more 2D materials that possess properties suitable for solar water splitting. Computational tools based on density-functional theory can predict the intrinsic properties of potential photocatalyst such as their electronic properties, optical absorbance, and solubility in aqueous solutions. Computational tools enable the exploration of possible routes to enhance the photocatalytic activity of 2D materials by use of mechanical strain, bias potential, doping, and pH. We discuss future research directions and needed method developments for the computational design and optimization of 2D materials for photocatalysis.
NASA Astrophysics Data System (ADS)
Luo, Hongjun; Kolb, Dietmar; Flad, Heinz-Jurgen; Hackbusch, Wolfgang; Koprucki, Thomas
2002-08-01
We have studied various aspects concerning the use of hyperbolic wavelets and adaptive approximation schemes for wavelet expansions of correlated wave functions. In order to analyze the consequences of reduced regularity of the wave function at the electron-electron cusp, we first considered a realistic exactly solvable many-particle model in one dimension. Convergence rates of wavelet expansions, with respect to L2 and H1 norms and the energy, were established for this model. We compare the performance of hyperbolic wavelets and their extensions through adaptive refinement in the cusp region, to a fully adaptive treatment based on the energy contribution of individual wavelets. Although hyperbolic wavelets show an inferior convergence behavior, they can be easily refined in the cusp region yielding an optimal convergence rate for the energy. Preliminary results for the helium atom are presented, which demonstrate the transferability of our observations to more realistic systems. We propose a contraction scheme for wavelets in the cusp region, which reduces the number of degrees of freedom and yields a favorable cost to benefit ratio for the evaluation of matrix elements.
Synthetic Covalent and Non-Covalent 2D Materials.
Boott, Charlotte E; Nazemi, Ali; Manners, Ian
2015-11-16
The creation of synthetic 2D materials represents an attractive challenge that is ultimately driven by their prospective uses in, for example, electronics, biomedicine, catalysis, sensing, and as membranes for separation and filtration. This Review illustrates some recent advances in this diverse field with a focus on covalent and non-covalent 2D polymers and frameworks, and self-assembled 2D materials derived from nanoparticles, homopolymers, and block copolymers.
Laboratory studies on N(2D) reactions of relevance to the chemistry of planetary atmospheres
NASA Astrophysics Data System (ADS)
Balucani, N.; Casavecchia, P.
Molecular nitrogen is a very stable molecule, practically inert from a chemical point of view. For a nitrogen chemistry to occur in the planetary atmospheres which contain N2 , it is necessary to transform it into an active form, such as atoms or ions. As far as the production of atomic nitrogen in the upper atmospheres of planets (like Mars) or moons (like Titan) is concerned, several processes - as N2 dissociation induced by electron impact, EUV photolysis (λ <80 nm) and dissociative photoionization, or galactic cosmic ray absorption and N+ dissociative recombination all 2 lead to atomic nitrogen, notably in the ground, 4 S3/2 , and first electronically excited, 2 D3/2,5/2 , states with comparable yields. The radiative lifetimes of the metastable states 2 D3/2 and 2 D5/2 are quite long (12.3 and 48 hours, respectively), because the transition from a doublet to a quartet state is strongly forbidden. In addition, the physical quenching of N(2 D) is often a slow process and in some important cases the main fate of N(2 D) is chemical reaction with other constituents of the planetary atmospheres. The production of N atoms in the 2 D state is an important fact, because N(4 S) atoms exhibit very low reactivity with closed-shell molecules and the probability of collision with an open-shell radical is small. Unfortunately laboratory experiments on the gas-phase reactions of N(2 D) have been lacking until recently, because of serious experimental difficulties in studying these reactive systems. Accurate kinetic data on the reactions of N(2 D) with the some molecules of relevance to the chemistry of planetary atmospheres have finally become available in the late 90's, but a better knowledge of the reactive behavior requires a dynamical investigation of N(2 D) reactions. The capability of generating intense continuous beams of N(2 D) achieved in our laboratory some years ago has opened up the possibility of studying the reactive scattering of this species under single
A Geometric Boolean Library for 2D Objects
2006-01-05
The 2D Boolean Library is a collection of C++ classes -- which primarily represent 2D geometric data and relationships, and routines -- which contain algorithms for 2D geometric Boolean operations and utility functions. Classes are provided for 2D points, lines, arcs, edgeuses, loops, surfaces and mask sets. Routines are provided that incorporate the Boolean operations Union(OR), XOR, Intersection and Difference. Various analytical geometry routines and routines for importing and exporting the data in various filemore » formats, are also provided in the library.« less
VizieR Online Data Catalog: The 2dF Galaxy Redshift Survey (2dFGRS) (2dFGRS Team, 1998-2003)
NASA Astrophysics Data System (ADS)
Colless, M.; Dalton, G.; Maddox, S.; Sutherland, W.; Norberg, P.; Cole, S.; Bland-Hawthorn, J.; Bridges, T.; Cannon, R.; Collins, C.; Couch, W.; Cross, N.; Deeley, K.; de Propris, R.; Driver, S. P.; Efstathiou, G.; Ellis, R. S.; Frenk, C. S.; Glazebrook, K.; Jackson, C.; Lahav, O.; Lewis, I.; Lumsden, S.; Madgwick, D.; Peacock, J. A.; Peterson, B. A.; Price, I.; Seaborne, M.; Taylor, K.
2007-11-01
The 2dF Galaxy Redshift Survey (2dFGRS) is a major spectroscopic survey taking full advantage of the unique capabilities of the 2dF facility built by the Anglo-Australian Observatory. The 2dFGRS is integrated with the 2dF QSO survey (2QZ, Cat. VII/241). The 2dFGRS obtained spectra for 245591 objects, mainly galaxies, brighter than a nominal extinction-corrected magnitude limit of bJ=19.45. Reliable (quality>=3) redshifts were obtained for 221414 galaxies. The galaxies cover an area of approximately 1500 square degrees selected from the extended APM Galaxy Survey in three regions: a North Galactic Pole (NGP) strip, a South Galactic Pole (SGP) strip, and random fields scattered around the SGP strip. Redshifts are measured from spectra covering 3600-8000 Angstroms at a two-pixel resolution of 9.0 Angstrom and a median S/N of 13 per pixel. All redshift identifications are visually checked and assigned a quality parameter Q in the range 1-5; Q>=3 redshifts are 98.4% reliable and have an rms uncertainty of 85 km/s. The overall redshift completeness for Q>=3 redshifts is 91.8% but this varies with magnitude from 99% for the brightest galaxies to 90% for objects at the survey limit. The 2dFGRS data base is available on the World Wide Web at http://www.mso.anu.edu.au/2dFGRS/. (6 data files).
Determination of curvature and twist by digital shearography and wavelet transforms.
Tay, Cho Jui; Fu, Yu
2005-11-01
A new technique based on digital shearography for determining the transient curvature and twist of a continuously deforming object from a series of speckle patterns is presented. The intensity variation of each pixel is analyzed along the time axis by using a complex Morlet wavelet transform. The absolute sign of the phase variation is determined by introduction of a temporal carrier when the speckle patterns are captured by a high-speed camera. A high-quality spatial distribution of the deflection derivative is extracted at any instant without the need for temporal or spatial phase unwrapping. The continuous Haar wavelet transform is subsequently processed as a differentiation operator to reconstruct the instantaneous curvature and twist of a continuously deforming object. PMID:16279454
Wavelet Analysis of Space Solar Telescope Images
NASA Astrophysics Data System (ADS)
Zhu, Xi-An; Jin, Sheng-Zhen; Wang, Jing-Yu; Ning, Shu-Nian
2003-12-01
The scientific satellite SST (Space Solar Telescope) is an important research project strongly supported by the Chinese Academy of Sciences. Every day, SST acquires 50 GB of data (after processing) but only 10GB can be transmitted to the ground because of limited time of satellite passage and limited channel volume. Therefore, the data must be compressed before transmission. Wavelets analysis is a new technique developed over the last 10 years, with great potential of application. We start with a brief introduction to the essential principles of wavelet analysis, and then describe the main idea of embedded zerotree wavelet coding, used for compressing the SST images. The results show that this coding is adequate for the job.
Wavelet analysis for wind fields estimation.
Leite, Gladeston C; Ushizima, Daniela M; Medeiros, Fátima N S; de Lima, Gilson G
2010-01-01
Wind field analysis from synthetic aperture radar images allows the estimation of wind direction and speed based on image descriptors. In this paper, we propose a framework to automate wind direction retrieval based on wavelet decomposition associated with spectral processing. We extend existing undecimated wavelet transform approaches, by including à trous with B(3) spline scaling function, in addition to other wavelet bases as Gabor and Mexican-hat. The purpose is to extract more reliable directional information, when wind speed values range from 5 to 10 ms(-1). Using C-band empirical models, associated with the estimated directional information, we calculate local wind speed values and compare our results with QuikSCAT scatterometer data. The proposed approach has potential application in the evaluation of oil spills and wind farms.
Component identification of nonstationary signals using wavelets
Otaduy, P.J.; Georgevich, V. )
1993-01-01
Fourier analysis is based on the decomposition of a signal into a linear combination of integral dilations of the base function e[sup ix],i.e., of sinusoidal waves. The larger the dilation the higher the frequency of the sinusoidal component. Each frequency component is of constant magnitude along the signal length. Localized features are averaged over the signal's length; thus, time localization is absent. Wavelet analysis is based on the decomposition of a signal into a linear combination of binary dilations and dyadic translations of a base function with compact support, i.e., a basic wavelet. A basic wavelet function can be, with basic restrictions, any function suitable to be a window in both the time.
Wavelet Analysis for Wind Fields Estimation
Leite, Gladeston C.; Ushizima, Daniela M.; Medeiros, Fátima N. S.; de Lima, Gilson G.
2010-01-01
Wind field analysis from synthetic aperture radar images allows the estimation of wind direction and speed based on image descriptors. In this paper, we propose a framework to automate wind direction retrieval based on wavelet decomposition associated with spectral processing. We extend existing undecimated wavelet transform approaches, by including à trous with B3 spline scaling function, in addition to other wavelet bases as Gabor and Mexican-hat. The purpose is to extract more reliable directional information, when wind speed values range from 5 to 10 ms−1. Using C-band empirical models, associated with the estimated directional information, we calculate local wind speed values and compare our results with QuikSCAT scatterometer data. The proposed approach has potential application in the evaluation of oil spills and wind farms. PMID:22219699
Wavelet analysis for wind fields estimation.
Leite, Gladeston C; Ushizima, Daniela M; Medeiros, Fátima N S; de Lima, Gilson G
2010-01-01
Wind field analysis from synthetic aperture radar images allows the estimation of wind direction and speed based on image descriptors. In this paper, we propose a framework to automate wind direction retrieval based on wavelet decomposition associated with spectral processing. We extend existing undecimated wavelet transform approaches, by including à trous with B(3) spline scaling function, in addition to other wavelet bases as Gabor and Mexican-hat. The purpose is to extract more reliable directional information, when wind speed values range from 5 to 10 ms(-1). Using C-band empirical models, associated with the estimated directional information, we calculate local wind speed values and compare our results with QuikSCAT scatterometer data. The proposed approach has potential application in the evaluation of oil spills and wind farms. PMID:22219699
Klassifikation von Standardebenen in der 2D-Echokardiographie mittels 2D-3D-Bildregistrierung
NASA Astrophysics Data System (ADS)
Bergmeir, Christoph; Subramanian, Navneeth
Zum Zweck der Entwicklung eines Systems, das einen unerfahrenen Anwender von Ultraschall (US) zur Aufnahme relevanter anatomischer Strukturen leitet, untersuchen wir die Machbarkeit von 2D-US zu 3D-CT Registrierung. Wir verwenden US-Aufnahmen von Standardebenen des Herzens, welche zu einem 3D-CT-Modell registriert werden. Unser Algorithmus unterzieht sowohl die US-Bilder als auch den CT-Datensatz Vorverarbeitungsschritten, welche die Daten durch Segmentierung auf wesentliche Informationen in Form von Labein für Muskel und Blut reduzieren. Anschließend werden diese Label zur Registrierung mittels der Match-Cardinality-Metrik genutzt. Durch mehrmaliges Registrieren mit verschiedenen Initialisierungen ermitteln wir die im US-Bild sichtbare Standardebene. Wir evaluierten die Methode auf sieben US-Bildern von Standardebenen. Fünf davon wurden korrekt zugeordnet.
Epitaxial 2D SnSe2/ 2D WSe2 van der Waals Heterostructures.
Aretouli, Kleopatra Emmanouil; Tsoutsou, Dimitra; Tsipas, Polychronis; Marquez-Velasco, Jose; Aminalragia Giamini, Sigiava; Kelaidis, Nicolaos; Psycharis, Vassilis; Dimoulas, Athanasios
2016-09-01
van der Waals heterostructures of 2D semiconductor materials can be used to realize a number of (opto)electronic devices including tunneling field effect devices (TFETs). It is shown in this work that high quality SnSe2/WSe2 vdW heterostructure can be grown by molecular beam epitaxy on AlN(0001)/Si(111) substrates using a Bi2Se3 buffer layer. A valence band offset of 0.8 eV matches the energy gap of SnSe2 in such a way that the VB edge of WSe2 and the CB edge of SnSe2 are lined up, making this materials combination suitable for (nearly) broken gap TFETs. PMID:27537619
CVMAC 2D Program: A method of converting 3D to 2D
Lown, J.
1990-06-20
This paper presents the user with a method of converting a three- dimensional wire frame model into a technical illustration, detail, or assembly drawing. By using the 2D Program, entities can be mapped from three-dimensional model space into two-dimensional model space, as if they are being traced. Selected entities to be mapped can include circles, arcs, lines, and points. This program prompts the user to digitize the view to be mapped, specify the layers in which the new two-dimensional entities will reside, and select the entities, either by digitizing or windowing. The new two-dimensional entities are displayed in a small view which the program creates in the lower left corner of the drawing. 9 figs.
NASA Astrophysics Data System (ADS)
Harikumar, Rajaguru; Vijayakumar, Thangavel
2014-12-01
The objective of this paper is to compare the performance of singular value decomposition (SVD), expectation maximization (EM), and modified expectation maximization (MEM) as the postclassifiers for classifications of the epilepsy risk levels obtained from extracted features through wavelet transforms and morphological filters from electroencephalogram (EEG) signals. The code converter acts as a level one classifier. The seven features such as energy, variance, positive and negative peaks, spike and sharp waves, events, average duration, and covariance are extracted from EEG signals. Out of which four parameters like positive and negative peaksand spike and sharp waves, events and average duration are extracted using Haar, dB2, dB4, and Sym 8 wavelet transforms with hard and soft thresholding methods. The above said four features are also extracted through morphological filters. Then, the performance of the code converter and classifiers are compared based on the parameters such as performance index (PI) and quality value (QV).The performance index and quality value of code converters are at low value of 33.26% and 12.74, respectively. The highest PI of 98.03% and QV of 23.82 are attained at dB2 wavelet with hard thresholding method for SVD classifier. All the postclassifiers are settled at PI value of more than 90% at QV of 20.
2D Four-Channel Perfect Reconstruction Filter Bank Realized with the 2D Lattice Filter Structure
NASA Astrophysics Data System (ADS)
Sezen, S.; Ertüzün, A.
2006-12-01
A novel orthogonal 2D lattice structure is incorporated into the design of a nonseparable 2D four-channel perfect reconstruction filter bank. The proposed filter bank is obtained by using the polyphase decomposition technique which requires the design of an orthogonal 2D lattice filter. Due to constraint of perfect reconstruction, each stage of this lattice filter bank is simply parameterized by two coefficients. The perfect reconstruction property is satisfied regardless of the actual values of these parameters and of the number of the lattice stages. It is also shown that a separable 2D four-channel perfect reconstruction lattice filter bank can be constructed from the 1D lattice filter and that this is a special case of the proposed 2D lattice filter bank under certain conditions. The perfect reconstruction property of the proposed 2D lattice filter approach is verified by computer simulations.
Characterization and simulation of gunfire with wavelets
Smallwood, D.O.
1998-09-01
Gunfire is used as an example to show how the wavelet transform can be used to characterize and simulate nonstationary random events when an ensemble of events is available. The response of a structure to nearby firing of a high-firing rate gun has been characterized in several ways as a nonstationary random process. The methods all used some form of the discrete fourier transform. The current paper will explore a simpler method to describe the nonstationary random process in terms of a wavelet transform. As was done previously, the gunfire record is broken up into a sequence of transient waveforms each representing the response to the firing of a single round. The wavelet transform is performed on each of these records. The mean and standard deviation of the resulting wavelet coefficients describe the composite characteristics of the entire waveform. It is shown that the distribution of the wavelet coefficients is approximately Gaussian with a nonzero mean and that the standard deviation of the coefficients at different times and levels are approximately independent. The gunfire is simulated by generating realizations of records of a single-round firing by computing the inverse wavelet transform from Gaussian random coefficients with the same mean and standard deviation as those estimated from the previously discussed gunfire record. The individual realizations are then assembled into a realization of a time history of many rounds firing. A second-order correction of the probability density function (pdf) is accomplished with a zero memory nonlinear (ZMNL) function. The method is straightforward, easy to implement, and produces a simulated record very much like the original measured gunfire record.
Functional characterization of CYP2D6 enhancer polymorphisms
Wang, Danxin; Papp, Audrey C.; Sun, Xiaochun
2015-01-01
CYP2D6 metabolizes nearly 25% of clinically used drugs. Genetic polymorphisms cause large inter-individual variability in CYP2D6 enzyme activity and are currently used as biomarker to predict CYP2D6 metabolizer phenotype. Previously, we had identified a region 115 kb downstream of CYP2D6 as enhancer for CYP2D6, containing two completely linked single nucleotide polymorphisms (SNPs), rs133333 and rs5758550, associated with enhanced transcription. However, the enhancer effect on CYP2D6 expression, and the causative variant, remained to be ascertained. To characterize the CYP2D6 enhancer element, we applied chromatin conformation capture combined with the next-generation sequencing (4C assays) and chromatin immunoprecipitation with P300 antibody, in HepG2 and human primary culture hepatocytes. The results confirmed the role of the previously identified enhancer region in CYP2D6 expression, expanding the number of candidate variants to three highly linked SNPs (rs133333, rs5758550 and rs4822082). Among these, only rs5758550 demonstrated regulating enhancer activity in a reporter gene assay. Use of clustered regularly interspaced short palindromic repeats mediated genome editing in HepG2 cells targeting suspected enhancer regions decreased CYP2D6 mRNA expression by 70%, only upon deletion of the rs5758550 region. These results demonstrate robust effects of both the enhancer element and SNP rs5758550 on CYP2D6 expression, supporting consideration of rs5758550 for CYP2D6 genotyping panels to yield more accurate phenotype prediction. PMID:25381333
Analysis of wavelet technology for NASA applications
NASA Technical Reports Server (NTRS)
Wells, R. O., Jr.
1994-01-01
The purpose of this grant was to introduce a broad group of NASA researchers and administrators to wavelet technology and to determine its future role in research and development at NASA JSC. The activities of several briefings held between NASA JSC scientists and Rice University researchers are discussed. An attached paper, 'Recent Advances in Wavelet Technology', summarizes some aspects of these briefings. Two proposals submitted to NASA reflect the primary areas of common interest. They are image analysis and numerical solutions of partial differential equations arising in computational fluid dynamics and structural mechanics.
Numerical Algorithms Based on Biorthogonal Wavelets
NASA Technical Reports Server (NTRS)
Ponenti, Pj.; Liandrat, J.
1996-01-01
Wavelet bases are used to generate spaces of approximation for the resolution of bidimensional elliptic and parabolic problems. Under some specific hypotheses relating the properties of the wavelets to the order of the involved operators, it is shown that an approximate solution can be built. This approximation is then stable and converges towards the exact solution. It is designed such that fast algorithms involving biorthogonal multi resolution analyses can be used to resolve the corresponding numerical problems. Detailed algorithms are provided as well as the results of numerical tests on partial differential equations defined on the bidimensional torus.
Wavelet analysis applied to the IRAS cirrus
NASA Technical Reports Server (NTRS)
Langer, William D.; Wilson, Robert W.; Anderson, Charles H.
1994-01-01
The structure of infrared cirrus clouds is analyzed with Laplacian pyramid transforms, a form of non-orthogonal wavelets. Pyramid and wavelet transforms provide a means to decompose images into their spatial frequency components such that all spatial scales are treated in an equivalent manner. The multiscale transform analysis is applied to IRAS 100 micrometer maps of cirrus emission in the north Galactic pole region to extract features on different scales. In the maps we identify filaments, fragments and clumps by separating all connected regions. These structures are analyzed with respect to their Hausdorff dimension for evidence of the scaling relationships in the cirrus clouds.
NASA Astrophysics Data System (ADS)
Chae, Dongho; Constantin, Peter; Wu, Jiahong
2014-09-01
We give an example of a well posed, finite energy, 2D incompressible active scalar equation with the same scaling as the surface quasi-geostrophic equation and prove that it can produce finite time singularities. In spite of its simplicity, this seems to be the first such example. Further, we construct explicit solutions of the 2D Boussinesq equations whose gradients grow exponentially in time for all time. In addition, we introduce a variant of the 2D Boussinesq equations which is perhaps a more faithful companion of the 3D axisymmetric Euler equations than the usual 2D Boussinesq equations.
Efficient Combustion Simulation via the Adaptive Wavelet Collocation Method
NASA Astrophysics Data System (ADS)
Lung, Kevin; Brown-Dymkoski, Eric; Guerrero, Victor; Doran, Eric; Museth, Ken; Balme, Jo; Urberger, Bob; Kessler, Andre; Jones, Stephen; Moses, Billy; Crognale, Anthony
Rocket engine development continues to be driven by the intuition and experience of designers, progressing through extensive trial-and-error test campaigns. Extreme temperatures and pressures frustrate direct observation, while high-fidelity simulation can be impractically expensive owing to the inherent muti-scale, multi-physics nature of the problem. To address this cost, an adaptive multi-resolution PDE solver has been designed which targets the high performance, many-core architecture of GPUs. The adaptive wavelet collocation method is used to maintain a sparse-data representation of the high resolution simulation, greatly reducing the memory footprint while tightly controlling physical fidelity. The tensorial, stencil topology of wavelet-based grids lends itself to highly vectorized algorithms which are necessary to exploit the performance of GPUs. This approach permits efficient implementation of direct finite-rate kinetics, and improved resolution of steep thermodynamic gradients and the smaller mixing scales that drive combustion dynamics. Resolving these scales is crucial for accurate chemical kinetics, which are typically degraded or lost in statistical modeling approaches.
Wavelet features for failure detection and identification in vibration systems
NASA Astrophysics Data System (ADS)
Deckert, James C.; Rhenals, Alonso E.; Tenney, Robert R.; Willsky, Alan S.
1992-12-01
The result of this effort is an extremely flexible and powerful methodology for failure detection and identification (FDI) in vibrating systems. The essential elements of this methodology are: (1) an off-line set of techniques to identify high-energy, statistically significant features in the continuous wavelet transform (CWT); (2) a CWT-based preprocessor to extract the most useful features from the sensor signal; and (3) simple artificial neural networks (incorporating a mechanism to defer any decision if the current feature sample is determined to be ambiguous) for the subsequent classification task. For the helicopter intermediate gearbox test-stand data and centrifugal and fire pump shipboard (mild operating condition) data used, the algorithms designed using this method achieved perfect detection performance (1.000 probability of detection, and 0.000 false alarm probability), with a probability less than 0.04 that a decision would be deferred-based on only 500 milliseconds of data from each sample case. While this effort shows the exceptional promise of our wavelet-based method for FDI in vibrating systems, more demanding applications, which also have other sources of high-energy vibration, raise additional technical issues that could provide the focus for a Phase 2 effort.
A Wavelet Analysis Approach for Categorizing Air Traffic Behavior
NASA Technical Reports Server (NTRS)
Drew, Michael; Sheth, Kapil
2015-01-01
In this paper two frequency domain techniques are applied to air traffic analysis. The Continuous Wavelet Transform (CWT), like the Fourier Transform, is shown to identify changes in historical traffic patterns caused by Traffic Management Initiatives (TMIs) and weather with the added benefit of detecting when in time those changes take place. Next, with the expectation that it could detect anomalies in the network and indicate the extent to which they affect traffic flows, the Spectral Graph Wavelet Transform (SGWT) is applied to a center based graph model of air traffic. When applied to simulations based on historical flight plans, it identified the traffic flows between centers that have the greatest impact on either neighboring flows, or flows between centers many centers away. Like the CWT, however, it can be difficult to interpret SGWT results and relate them to simulations where major TMIs are implemented, and more research may be warranted in this area. These frequency analysis techniques can detect off-nominal air traffic behavior, but due to the nature of air traffic time series data, so far they prove difficult to apply in a way that provides significant insight or specific identification of traffic patterns.
Wavelet-based detection of transients in biological signals
NASA Astrophysics Data System (ADS)
Mzaik, Tahsin; Jagadeesh, Jogikal M.
1994-10-01
This paper presents two multiresolution algorithms for detection and separation of mixed signals using the wavelet transform. The first algorithm allows one to design a mother wavelet and its associated wavelet grid that guarantees the separation of signal components if information about the expected minimum signal time and frequency separation of the individual components is known. The second algorithm expands this idea to design two mother wavelets which are then combined to achieve the required separation otherwise impossible with a single wavelet. Potential applications include many biological signals such as ECG, EKG, and retinal signals.
EEG analysis using wavelet-based information tools.
Rosso, O A; Martin, M T; Figliola, A; Keller, K; Plastino, A
2006-06-15
Wavelet-based informational tools for quantitative electroencephalogram (EEG) record analysis are reviewed. Relative wavelet energies, wavelet entropies and wavelet statistical complexities are used in the characterization of scalp EEG records corresponding to secondary generalized tonic-clonic epileptic seizures. In particular, we show that the epileptic recruitment rhythm observed during seizure development is well described in terms of the relative wavelet energies. In addition, during the concomitant time-period the entropy diminishes while complexity grows. This is construed as evidence supporting the conjecture that an epileptic focus, for this kind of seizures, triggers a self-organized brain state characterized by both order and maximal complexity.
Parallel object-oriented, denoising system using wavelet multiresolution analysis
Kamath, Chandrika; Baldwin, Chuck H.; Fodor, Imola K.; Tang, Nu A.
2005-04-12
The present invention provides a data de-noising system utilizing processors and wavelet denoising techniques. Data is read and displayed in different formats. The data is partitioned into regions and the regions are distributed onto the processors. Communication requirements are determined among the processors according to the wavelet denoising technique and the partitioning of the data. The data is transforming onto different multiresolution levels with the wavelet transform according to the wavelet denoising technique, the communication requirements, and the transformed data containing wavelet coefficients. The denoised data is then transformed into its original reading and displaying data format.
Adaptation algorithms for 2-D feedforward neural networks.
Kaczorek, T
1995-01-01
The generalized weight adaptation algorithms presented by J.G. Kuschewski et al. (1993) and by S.H. Zak and H.J. Sira-Ramirez (1990) are extended for 2-D madaline and 2-D two-layer feedforward neural nets (FNNs).
Integrating Mobile Multimedia into Textbooks: 2D Barcodes
ERIC Educational Resources Information Center
Uluyol, Celebi; Agca, R. Kagan
2012-01-01
The major goal of this study was to empirically compare text-plus-mobile phone learning using an integrated 2D barcode tag in a printed text with three other conditions described in multimedia learning theory. The method examined in the study involved modifications of the instructional material such that: a 2D barcode was used near the text, the…
Efficient Visible Quasi-2D Perovskite Light-Emitting Diodes.
Byun, Jinwoo; Cho, Himchan; Wolf, Christoph; Jang, Mi; Sadhanala, Aditya; Friend, Richard H; Yang, Hoichang; Lee, Tae-Woo
2016-09-01
Efficient quasi-2D-structure perovskite light-emitting diodes (4.90 cd A(-1) ) are demonstrated by mixing a 3D-structured perovskite material (methyl ammonium lead bromide) and a 2D-structured perovskite material (phenylethyl ammonium lead bromide), which can be ascribed to better film uniformity, enhanced exciton confinement, and reduced trap density. PMID:27334788
CYP2D6: novel genomic structures and alleles
Kramer, Whitney E.; Walker, Denise L.; O’Kane, Dennis J.; Mrazek, David A.; Fisher, Pamela K.; Dukek, Brian A.; Bruflat, Jamie K.; Black, John L.
2010-01-01
Objective CYP2D6 is a polymorphic gene. It has been observed to be deleted, to be duplicated and to undergo recombination events involving the CYP2D7 pseudogene and surrounding sequences. The objective of this study was to discover the genomic structure of CYP2D6 recombinants that interfere with clinical genotyping platforms that are available today. Methods Clinical samples containing rare homozygous CYP2D6 alleles, ambiguous readouts, and those with duplication signals and two different alleles were analyzed by long-range PCR amplification of individual genes, PCR fragment analysis, allele-specific primer extension assay, and DNA sequencing to characterize alleles and genomic structure. Results Novel alleles, genomic structures, and the DNA sequence of these structures are described. Interestingly, in 49 of 50 DNA samples that had CYP2D6 gene duplications or multiplications where two alleles were detected, the chromosome containing the duplication or multiplication had identical tandem alleles. Conclusion Several new CYP2D6 alleles and genomic structures are described which will be useful for CYP2D6 genotyping. The findings suggest that the recombination events responsible for CYP2D6 duplications and multiplications are because of mechanisms other than interchromosomal crossover during meiosis. PMID:19741566
Efficient Visible Quasi-2D Perovskite Light-Emitting Diodes.
Byun, Jinwoo; Cho, Himchan; Wolf, Christoph; Jang, Mi; Sadhanala, Aditya; Friend, Richard H; Yang, Hoichang; Lee, Tae-Woo
2016-09-01
Efficient quasi-2D-structure perovskite light-emitting diodes (4.90 cd A(-1) ) are demonstrated by mixing a 3D-structured perovskite material (methyl ammonium lead bromide) and a 2D-structured perovskite material (phenylethyl ammonium lead bromide), which can be ascribed to better film uniformity, enhanced exciton confinement, and reduced trap density.
Laser probe for measuring 2-D wave slope spectra of ocean capillary waves.
Palm, C S; Anderson, R C; Reece, A M
1977-04-01
A laser-optical instrument for use in determining the 2-D wave slope spectrum of ocean capillary waves is described. The instrument measures up to a 35 degrees tip angle of the surface normal by measuring the position of a refracted laser beam directed vertically upward through a water surface. A telescope, a continuous 2-D Schottky barrier photodiode, and a pair of analog dividers render the signals independent of water height and insensitive to laser beam intensity fluctuations. Calibration is performed entirely in the laboratory before field use. Sample records and wave slope spectra are shown for 1-D wave tank tests and for 2-D ocean tests. These are presented along with comparison spectra for calm and choppy water conditions. A mechanical wave follower was used to adjust the instrument position in the presence of large ocean swell and tides. PMID:20168638
Salau, J; Haas, J H; Thaller, G; Leisen, M; Junge, W
2016-09-01
Camera-based systems in dairy cattle were intensively studied over the last years. Different from this study, single camera systems with a limited range of applications were presented, mostly using 2D cameras. This study presents current steps in the development of a camera system comprising multiple 3D cameras (six Microsoft Kinect cameras) for monitoring purposes in dairy cows. An early prototype was constructed, and alpha versions of software for recording, synchronizing, sorting and segmenting images and transforming the 3D data in a joint coordinate system have already been implemented. This study introduced the application of two-dimensional wavelet transforms as method for object recognition and surface analyses. The method was explained in detail, and four differently shaped wavelets were tested with respect to their reconstruction error concerning Kinect recorded depth maps from different camera positions. The images' high frequency parts reconstructed from wavelet decompositions using the haar and the biorthogonal 1.5 wavelet were statistically analyzed with regard to the effects of image fore- or background and of cows' or persons' surface. Furthermore, binary classifiers based on the local high frequencies have been implemented to decide whether a pixel belongs to the image foreground and if it was located on a cow or a person. Classifiers distinguishing between image regions showed high (⩾0.8) values of Area Under reciever operation characteristic Curve (AUC). The classifications due to species showed maximal AUC values of 0.69. PMID:26837672
2D materials and van der Waals heterostructures.
Novoselov, K S; Mishchenko, A; Carvalho, A; Castro Neto, A H
2016-07-29
The physics of two-dimensional (2D) materials and heterostructures based on such crystals has been developing extremely fast. With these new materials, truly 2D physics has begun to appear (for instance, the absence of long-range order, 2D excitons, commensurate-incommensurate transition, etc.). Novel heterostructure devices--such as tunneling transistors, resonant tunneling diodes, and light-emitting diodes--are also starting to emerge. Composed from individual 2D crystals, such devices use the properties of those materials to create functionalities that are not accessible in other heterostructures. Here we review the properties of novel 2D crystals and examine how their properties are used in new heterostructure devices.
Van der Waals stacked 2D layered materials for optoelectronics
NASA Astrophysics Data System (ADS)
Zhang, Wenjing; Wang, Qixing; Chen, Yu; Wang, Zhuo; Wee, Andrew T. S.
2016-06-01
The band gaps of many atomically thin 2D layered materials such as graphene, black phosphorus, monolayer semiconducting transition metal dichalcogenides and hBN range from 0 to 6 eV. These isolated atomic planes can be reassembled into hybrid heterostructures made layer by layer in a precisely chosen sequence. Thus, the electronic properties of 2D materials can be engineered by van der Waals stacking, and the interlayer coupling can be tuned, which opens up avenues for creating new material systems with rich functionalities and novel physical properties. Early studies suggest that van der Waals stacked 2D materials work exceptionally well, dramatically enriching the optoelectronics applications of 2D materials. Here we review recent progress in van der Waals stacked 2D materials, and discuss their potential applications in optoelectronics.
Estrogen-Induced Cholestasis Leads to Repressed CYP2D6 Expression in CYP2D6-Humanized Mice
Pan, Xian
2015-01-01
Cholestasis activates bile acid receptor farnesoid X receptor (FXR) and subsequently enhances hepatic expression of small heterodimer partner (SHP). We previously demonstrated that SHP represses the transactivation of cytochrome P450 2D6 (CYP2D6) promoter by hepatocyte nuclear factor (HNF) 4α. In this study, we investigated the effects of estrogen-induced cholestasis on CYP2D6 expression. Estrogen-induced cholestasis occurs in subjects receiving estrogen for contraception or hormone replacement, or in susceptible women during pregnancy. In CYP2D6-humanized transgenic (Tg-CYP2D6) mice, cholestasis triggered by administration of 17α-ethinylestradiol (EE2) at a high dose led to 2- to 3-fold decreases in CYP2D6 expression. This was accompanied by increased hepatic SHP expression and subsequent decreases in the recruitment of HNF4α to CYP2D6 promoter. Interestingly, estrogen-induced cholestasis also led to increased recruitment of estrogen receptor (ER) α, but not that of FXR, to Shp promoter, suggesting a predominant role of ERα in transcriptional regulation of SHP in estrogen-induced cholestasis. EE2 at a low dose (that does not cause cholestasis) also increased SHP (by ∼50%) and decreased CYP2D6 expression (by 1.5-fold) in Tg-CYP2D6 mice, the magnitude of differences being much smaller than that shown in EE2-induced cholestasis. Taken together, our data indicate that EE2-induced cholestasis increases SHP and represses CYP2D6 expression in Tg-CYP2D6 mice in part through ERα transactivation of Shp promoter. PMID:25943116
Efficient architectures for two-dimensional discrete wavelet transform using lifting scheme.
Xiong, Chengyi; Tian, Jinwen; Liu, Jian
2007-03-01
Novel architectures for 1-D and 2-D discrete wavelet transform (DWT) by using lifting schemes are presented in this paper. An embedded decimation technique is exploited to optimize the architecture for 1-D DWT, which is designed to receive an input and generate an output with the low- and high-frequency components of original data being available alternately. Based on this 1-D DWT architecture, an efficient line-based architecture for 2-D DWT is further proposed by employing parallel and pipeline techniques, which is mainly composed of two horizontal filter modules and one vertical filter module, working in parallel and pipeline fashion with 100% hardware utilization. This 2-D architecture is called fast architecture (FA) that can perform J levels of decomposition for N * N image in approximately 2N2(1 - 4(-J))/3 internal clock cycles. Moreover, another efficient generic line-based 2-D architecture is proposed by exploiting the parallelism among four subband transforms in lifting-based 2-D DWT, which can perform J levels of decomposition for N * N image in approximately N2(1 - 4(-J))/3 internal clock cycles; hence, it is called high-speed architecture. The throughput rate of the latter is increased by two times when comparing with the former 2-D architecture, but only less additional hardware cost is added. Compared with the works reported in previous literature, the proposed architectures for 2-D DWT are efficient alternatives in tradeoff among hardware cost, throughput rate, output latency and control complexity, etc. PMID:17357722
Boussuges, A; Carturan, D; Ambrosi, P; Habib, G; Sainty, J M; Luccioni, R
1998-01-01
The aim of this study was to determine the utility of pulsed Doppler and 2D echocardiography for the detection and the quantification of circulating bubbles after decompression. Twenty-three sport divers performed 60 SCUBA dives (mean 32 msw). An evaluation of circulating bubbles was performed using 2D images one hour after diving. Circulating bubbles were also detected with pulsed Doppler. The sample volume was placed in the outflow area of the right ventricle 1-2 cm below the pulmonary valve. 2D echocardiography showed circulating bubbles in right cavities of the heart in 32 cases. Short axis parasternal view and right cavities long axis view were the best incidences. Pulsed Doppler confirmed the results in these 32 cases and detected circulating bubbles in seven other cases. Isometric contraction of muscle limb must be performed to increase the sensitivity of detection. The count of the bubbles may be evaluated when using a combination of Spencer's and Powell's grading. We conclude that 2D echocardiography is less accurate than pulsed Doppler in the detection of circulating bubbles after decompression. Further studies are needed to compare pulsed Doppler guided by 2D echocardiography to continuous Doppler for the detection of circulating bubbles.
NASA Astrophysics Data System (ADS)
Deliège, Adrien; Kleyntssens, Thomas; Nicolay, Samuel
2016-04-01
This work examines the scaling properties of Mars topography through a wavelet-based formalism. We conduct exhaustive one-dimensional (both longitudinal and latitudinal) and two-dimensional studies based on Mars Orbiter Laser Altimeter (MOLA) data using the multifractal formalism called Wavelet Leaders Method (WLM). This approach shows that a scale break occurs at approximately 15 km, giving two scaling regimes in both 1D and 2D cases. At small scales, these topographic profiles mostly display a monofractal behavior while a switch to multifractality is observed in several areas at larger scales. The scaling exponents extracted from this framework tend to be greater at small scales. In the 1D context, these observations are in agreement with previous works and thus suggest that the WLM is well-suited for examining scaling properties of topographic fields. Moreover, the 2D analysis is the first such complete study to our knowledge. It gives both a local and global insight on the scaling regimes of the surface of Mars and allows to exhibit the link between the scaling exponents and several famous features of the Martian topography. These results may be used as a solid basis for further investigations of the scaling laws of the Red planet and show that the WLM could be used to perform systematic analyses of the surface roughness of other celestial bodies.
NASA Astrophysics Data System (ADS)
Abuturab, Muhammad Rafiq
2015-11-01
A novel gyrator wavelet transform based non-linear multiple single channel information fusion and authentication is introduced. In this technique, each user channel is normalized, phase encoded, and modulated by random phase function, and then multiplexed into a single channel user ciphertext. Now, the secret channel of corresponding user is phase encoded, modulated by random phase function, and gyrator transformed, and then multiplexed into a single channel secret ciphertext. The user ciphertext and secret ciphertext are multiplied to get a single channel multiplex image and then inverse gyrator transformed. The resultant spectrum is phase- and amplitude-truncated to obtain the encrypted image and the asymmetric key, respectively. The encrypted image is a single-level 2-D discrete wavelet transformed. The information is decomposed into LL, HL, LH, and HH sub-bands. This process is repeated to obtain three sets of four sub-bands of three different images. Next, the individual sub-band of each encrypted image is fused to get four fused sub-bands. Finally, the four fused sub-bands are inverse single-level 2-D discrete wavelet transformed to obtain final encrypted image. This is the main advantage for the proposed system: using multiple individual decryption keys (authentication key, asymmetric key, secret keys, and sub-band keys) for each user not only expands the key spaces but also supplies non-linear keys to control the system security. Moreover, the orders of gyrator transform provide extra degrees of freedom. The theoretical analysis and numerical simulation results support the proposed method.
Abuturab, Muhammad Rafiq
2015-10-01
A novel method of group multiple-image encoding and watermarking using coupled logistic maps and gyrator wavelet transform is presented. The proposed method employs three different groups of multiple images. The color images of each group are individually segregated into R, G, and B channels. Each channel is first permutated by using a sequence of chaotic pairs generated with a system of two symmetrically coupled identical logistic maps and then gyrator transformed. The gyrator spectrum of each channel is multiplied together and then modulated by a random phase function to obtain a corresponding multiplex channel. The encoded multiplex image is restituted through a concatenation of R, G, and B multiplex channels. The phase and amplitude functions of the first, second, and third groups of encoded multiplex images are generated. The host image is a single-level 2D discrete wavelet transformed to decompose into LL, HL, LH, and HH subbands. HL, LH, and HH subbands are then replaced with phase functions of the first, second, and third groups, respectively. Finally, the resultant image is an inverse single-level 2D discrete wavelet transformed to construct a watermarked image. The three groups of multiple images are protected not only by the encryption algorithm but also visually by the host image. Thus, a high level of security can be achieved. Each group includes group decryption keys, and each image of the group comprises individual decryption keys beside parameters of coupled logistic maps and gyrator transform. As a result, the key space is very large. The decryption system can be realized by using an optoelectronic device. The numerical simulation results confirm the validity and security of the proposed scheme.
Abuturab, Muhammad Rafiq
2015-10-01
A novel method of group multiple-image encoding and watermarking using coupled logistic maps and gyrator wavelet transform is presented. The proposed method employs three different groups of multiple images. The color images of each group are individually segregated into R, G, and B channels. Each channel is first permutated by using a sequence of chaotic pairs generated with a system of two symmetrically coupled identical logistic maps and then gyrator transformed. The gyrator spectrum of each channel is multiplied together and then modulated by a random phase function to obtain a corresponding multiplex channel. The encoded multiplex image is restituted through a concatenation of R, G, and B multiplex channels. The phase and amplitude functions of the first, second, and third groups of encoded multiplex images are generated. The host image is a single-level 2D discrete wavelet transformed to decompose into LL, HL, LH, and HH subbands. HL, LH, and HH subbands are then replaced with phase functions of the first, second, and third groups, respectively. Finally, the resultant image is an inverse single-level 2D discrete wavelet transformed to construct a watermarked image. The three groups of multiple images are protected not only by the encryption algorithm but also visually by the host image. Thus, a high level of security can be achieved. Each group includes group decryption keys, and each image of the group comprises individual decryption keys beside parameters of coupled logistic maps and gyrator transform. As a result, the key space is very large. The decryption system can be realized by using an optoelectronic device. The numerical simulation results confirm the validity and security of the proposed scheme. PMID:26479935
TRUFAS, a wavelet-based algorithm for the rapid detection of planetary transits
NASA Astrophysics Data System (ADS)
Régulo, C.; Almenara, J. M.; Alonso, R.; Deeg, H.; Roca Cortés, T.
2007-06-01
Aims: We describe a fast, robust and automatic detection algorithm, TRUFAS, and apply it to data that are being expected from the CoRoT mission. Methods: The procedure proposed for the detection of planetary transits in light curves works in two steps: 1) a continuous wavelet transformation of the detrended light curve with posterior selection of the optimum scale for transit detection, and 2) a period search in that selected wavelet transformation. The detrending of the light curves are based on Fourier filtering or a discrete wavelet transformation. TRUFAS requires the presence of at least 3 transit events in the data. Results: The proposed algorithm is shown to identify reliably and quickly the transits that had been included in a standard set of 999 light curves that simulate CoRoT data. Variations in the pre-processing of the light curves and in the selection of the scale of the wavelet transform have only little effect on TRUFAS' results. Conclusions: TRUFAS is a robust and quick transit detection algorithm, especially well suited for the analysis of very large volumes of data from space or ground-based experiments, with long enough durations for the target-planets to produce multiple transit events.
Drag Reduction Study by Wavelet Analysis of Differential Pressure Signals in Turbulent Flow
Ling Zhen; Yassin, A. Hassan; Dominguez-Ontiveros, Elvis
2004-07-01
Drag reduction was studied when micro-bubbles with low void fractions were injected in the boundary layer of a turbulent channel flow. The particle tracking velocimetry (PIV) flow measurement technique was used to measure two-dimensional full velocity fields. Since pressure field distribution is associated with turbulence behavior and dissipation, it is important to study the changes of the pressure field. However, the differential pressure signals are difficult to analyze due to irregularity. The characteristics of these signals have been studied by traditional statistical methods. In this study, the multi-resolution technique of wavelet transform based on localized wavelet functions is utilized to nonlinear pressure signals. By using continuous wavelet transform method, the pressure signals in the turbulent flow can be decomposed into its approximations and details at different resolutions. The magnitudes of the coefficients represent the energy distribution at different scales and this also can facilitate the visual observation of the energy transition process. The wavelet decomposition coefficients at different scales plot would provide a tool to further our understanding of drag reduction mechanism via micro-bubbles injection. (authors)
Understanding wavelet analysis and filters for engineering applications
NASA Astrophysics Data System (ADS)
Parameswariah, Chethan Bangalore
Wavelets are signal-processing tools that have been of interest due to their characteristics and properties. Clear understanding of wavelets and their properties are a key to successful applications. Many theoretical and application-oriented papers have been written. Yet the choice of a right wavelet for a given application is an ongoing quest that has not been satisfactorily answered. This research has successfully identified certain issues, and an effort has been made to provide an understanding of wavelets by studying the wavelet filters in terms of their pole-zero and magnitude-phase characteristics. The magnitude characteristics of these filters have flat responses in both the pass band and stop band. The phase characteristics are almost linear. It is interesting to observe that some wavelets have the exact same magnitude characteristics but their phase responses vary in the linear slopes. An application of wavelets for fast detection of the fault current in a transformer and distinguishing from the inrush current clearly shows the advantages of the lower slope and fewer coefficients---Daubechies wavelet D4 over D20. This research has been published in the IEEE transactions on Power systems and is also proposed as an innovative method for protective relaying techniques. For detecting the frequency composition of the signal being analyzed, an understanding of the energy distribution in the output wavelet decompositions is presented for different wavelet families. The wavelets with fewer coefficients in their filters have more energy leakage into adjacent bands. The frequency bandwidth characteristics display flatness in the middle of the pass band confirming that the frequency of interest should be in the middle of the frequency band when performing a wavelet transform. Symlets exhibit good flatness with minimum ripple but the transition regions do not have sharper cut off. The number of wavelet levels and their frequency ranges are dependent on the two
Xie, Donghao; Ji, Ding-Kun; Zhang, Yue; Cao, Jun; Zheng, Hu; Liu, Lin; Zang, Yi; Li, Jia; Chen, Guo-Rong; James, Tony D; He, Xiao-Peng
2016-08-01
Here we demonstrate that 2D MoS2 can enhance the receptor-targeting and imaging ability of a fluorophore-labelled ligand. The 2D MoS2 has an enhanced working concentration range when compared with graphene oxide, resulting in the improved imaging of both cell and tissue samples.
NASA Astrophysics Data System (ADS)
Emoto, Kentaro; Sato, Haruo; Nishimura, Takeshi
2013-08-01
multiplying the angular spectrum by conversion or reflection coefficients and calculate the TFMCF for the converted or reflected wavelets at layer boundaries, we can calculate any phase generated due to velocity discontinuities. For the reflected wavelets, we solve the master equation of the TFMCF downward. To confirm the validity of the method, we directly synthesize mean square envelopes in 2-D two-layered random elastic media and compare them with the averaged envelopes calculated by finite difference (FD) simulations of the wave propagation in random elastic media. We find that the Markov envelopes well agree with the FD envelopes not only for a transmitted wavelet but also for a P to S converted wavelet and a reflected wavelet at a layer boundary.
Information retrieval system utilizing wavelet transform
Brewster, Mary E.; Miller, Nancy E.
2000-01-01
A method for automatically partitioning an unstructured electronically formatted natural language document into its sub-topic structure. Specifically, the document is converted to an electronic signal and a wavelet transform is then performed on the signal. The resultant signal may then be used to graphically display and interact with the sub-topic structure of the document.
Nonlinear adaptive wavelet analysis of electrocardiogram signals
NASA Astrophysics Data System (ADS)
Yang, H.; Bukkapatnam, S. T.; Komanduri, R.
2007-08-01
Wavelet representation can provide an effective time-frequency analysis for nonstationary signals, such as the electrocardiogram (EKG) signals, which contain both steady and transient parts. In recent years, wavelet representation has been emerging as a powerful time-frequency tool for the analysis and measurement of EKG signals. The EKG signals contain recurring, near-periodic patterns of P , QRS , T , and U waveforms, each of which can have multiple manifestations. Identification and extraction of a compact set of features from these patterns is critical for effective detection and diagnosis of various disorders. This paper presents an approach to extract a fiducial pattern of EKG based on the consideration of the underlying nonlinear dynamics. The pattern, in a nutshell, is a combination of eigenfunctions of the ensembles created from a Poincare section of EKG dynamics. The adaptation of wavelet functions to the fiducial pattern thus extracted yields two orders of magnitude (some 95%) more compact representation (measured in terms of Shannon signal entropy). Such a compact representation can facilitate in the extraction of features that are less sensitive to extraneous noise and other variations. The adaptive wavelet can also lead to more efficient algorithms for beat detection and QRS cancellation as well as for the extraction of multiple classical EKG signal events, such as widths of QRS complexes and QT intervals.
Parallel adaptive wavelet collocation method for PDEs
Nejadmalayeri, Alireza; Vezolainen, Alexei; Brown-Dymkoski, Eric; Vasilyev, Oleg V.
2015-10-01
A parallel adaptive wavelet collocation method for solving a large class of Partial Differential Equations is presented. The parallelization is achieved by developing an asynchronous parallel wavelet transform, which allows one to perform parallel wavelet transform and derivative calculations with only one data synchronization at the highest level of resolution. The data are stored using tree-like structure with tree roots starting at a priori defined level of resolution. Both static and dynamic domain partitioning approaches are developed. For the dynamic domain partitioning, trees are considered to be the minimum quanta of data to be migrated between the processes. This allows fully automated and efficient handling of non-simply connected partitioning of a computational domain. Dynamic load balancing is achieved via domain repartitioning during the grid adaptation step and reassigning trees to the appropriate processes to ensure approximately the same number of grid points on each process. The parallel efficiency of the approach is discussed based on parallel adaptive wavelet-based Coherent Vortex Simulations of homogeneous turbulence with linear forcing at effective non-adaptive resolutions up to 2048{sup 3} using as many as 2048 CPU cores.
Characterization and Simulation of Gunfire with Wavelets
Smallwood, David O.
1999-01-01
Gunfire is used as an example to show how the wavelet transform can be used to characterize and simulate nonstationary random events when an ensemble of events is available. The structural response to nearby firing of a high-firing rate gun has been characterized in several ways as a nonstationary random process. The current paper will explore a method to describe the nonstationary random process using a wavelet transform. The gunfire record is broken up into a sequence of transient waveforms each representing the response to the firing of a single round. A wavelet transform is performed on each of thesemore » records. The gunfire is simulated by generating realizations of records of a single-round firing by computing an inverse wavelet transform from Gaussian random coefficients with the same mean and standard deviation as those estimated from the previously analyzed gunfire record. The individual records are assembled into a realization of many rounds firing. A second-order correction of the probability density function is accomplished with a zero memory nonlinear function. The method is straightforward, easy to implement, and produces a simulated record much like the measured gunfire record.« less
Cosmic Ray elimination using the Wavelet Transform
NASA Astrophysics Data System (ADS)
Orozco-Aguilera, M. T.; Cruz, J.; Altamirano, L.; Serrano, A.
2009-11-01
In this work, we present a method for the automatic cosmic ray elimination in a single CCD exposure using the Wavelet Transform. The proposed method can eliminate cosmic rays of any shape or size. With this method we can eliminate over 95% of cosmic rays in a spectral image.
Efficient 2D MRI relaxometry using compressed sensing
NASA Astrophysics Data System (ADS)
Bai, Ruiliang; Cloninger, Alexander; Czaja, Wojciech; Basser, Peter J.
2015-06-01
Potential applications of 2D relaxation spectrum NMR and MRI to characterize complex water dynamics (e.g., compartmental exchange) in biology and other disciplines have increased in recent years. However, the large amount of data and long MR acquisition times required for conventional 2D MR relaxometry limits its applicability for in vivo preclinical and clinical MRI. We present a new MR pipeline for 2D relaxometry that incorporates compressed sensing (CS) as a means to vastly reduce the amount of 2D relaxation data needed for material and tissue characterization without compromising data quality. Unlike the conventional CS reconstruction in the Fourier space (k-space), the proposed CS algorithm is directly applied onto the Laplace space (the joint 2D relaxation data) without compressing k-space to reduce the amount of data required for 2D relaxation spectra. This framework is validated using synthetic data, with NMR data acquired in a well-characterized urea/water phantom, and on fixed porcine spinal cord tissue. The quality of the CS-reconstructed spectra was comparable to that of the conventional 2D relaxation spectra, as assessed using global correlation, local contrast between peaks, peak amplitude and relaxation parameters, etc. This result brings this important type of contrast closer to being realized in preclinical, clinical, and other applications.
Practical Algorithm For Computing The 2-D Arithmetic Fourier Transform
NASA Astrophysics Data System (ADS)
Reed, Irving S.; Choi, Y. Y.; Yu, Xiaoli
1989-05-01
Recently, Tufts and Sadasiv [10] exposed a method for computing the coefficients of a Fourier series of a periodic function using the Mobius inversion of series. They called this method of analysis the Arithmetic Fourier Transform(AFT). The advantage of the AFT over the FN 1' is that this method of Fourier analysis needs only addition operations except for multiplications by scale factors at one stage of the computation. The disadvantage of the AFT as they expressed it originally is that it could be used effectively only to compute finite Fourier coefficients of a real even function. To remedy this the AFT developed in [10] is extended in [11] to compute the Fourier coefficients of both the even and odd components of a periodic function. In this paper, the improved AFT [11] is extended to a two-dimensional(2-D) Arithmetic Fourier Transform for calculating the Fourier Transform of two-dimensional discrete signals. This new algorithm is based on both the number-theoretic method of Mobius inversion of double series and the complex conjugate property of Fourier coefficients. The advantage of this algorithm over the conventional 2-D FFT is that the corner-turning problem needed in a conventional 2-D Discrete Fourier Transform(DFT) can be avoided. Therefore, this new 2-D algorithm is readily suitable for VLSI implementation as a parallel architecture. Comparing the operations of 2-D AFT of a MxM 2-D data array with the conventional 2-D FFT, the number of multiplications is significantly reduced from (2log2M)M2 to (9/4)M2. Hence, this new algorithm is faster than the FFT algorithm. Finally, two simulation results of this new 2-D AFT algorithm for 2-D artificial and real images are given in this paper.
Investigation of aquifer-estuary interaction using wavelet analysis of fiber-optic temperature data
Henderson, R.D.; Day-Lewis, F. D.; Harvey, C.F.
2009-01-01
Fiber-optic distributed temperature sensing (FODTS) provides sub-minute temporal and meter-scale spatial resolution over kilometer-long cables. Compared to conventional thermistor or thermocouple-based technologies, which measure temperature at discrete (and commonly sparse) locations, FODTS offers nearly continuous spatial coverage, thus providing hydrologie information at spatiotemporal scales previously impossible. Large and information-rich FODTS datasets, however, pose challenges for data exploration and analysis. To date, FODTS analyses have focused on time-series variance as the means to discriminate between hydrologic phenomena. Here, we demonstrate the continuous wavelet transform (CWT) and cross-wavelet transform (XWT) to analyze FODTS in the context of related hydrologic time series. We apply the CWT and XWT to data from Waquoit Bay, Massachusetts to identify the location and timing of tidal pumping of submarine groundwater Copyright 2009 by the American Geophysical Union.
Fingerprint data acquisition, desmearing, wavelet feature extraction, and identification
NASA Astrophysics Data System (ADS)
Szu, Harold H.; Hsu, Charles C.; Garcia, Joseph P.; Telfer, Brian A.
1995-04-01
In this paper, we present (1) a design concept of a fingerprint scanning system that can reject severely blurred inputs for retakes and then de-smear those less blurred prints. The de-smear algorithm is new and is based on the digital filter theory of the lossless QMF (quadrature mirror filter) subband coding. Then, we present (2) a new fingerprint minutia feature extraction methodology which uses a 2D STAR mother wavelet that can efficiently locate the fork feature anywhere on the fingerprints in parallel and is independent of its scale, shift, and rotation. Such a combined system can achieve high data compression to send through a binary facsimile machine that when combined with a tabletop computer can achieve the automatic finger identification systems (AFIS) using today's technology in the office environment. An interim recommendation for the National Crime Information Center is given about how to reduce the crime rate by an upgrade of today's police office technology in the light of the military expertise in ATR.
2D electron cyclotron emission imaging at ASDEX Upgrade (invited)
Classen, I. G. J.; Boom, J. E.; Vries, P. C. de; Suttrop, W.; Schmid, E.; Garcia-Munoz, M.; Schneider, P. A.; Tobias, B.; Domier, C. W.; Luhmann, N. C. Jr.; Donne, A. J. H.; Jaspers, R. J. E.; Park, H. K.; Munsat, T.
2010-10-15
The newly installed electron cyclotron emission imaging diagnostic on ASDEX Upgrade provides measurements of the 2D electron temperature dynamics with high spatial and temporal resolution. An overview of the technical and experimental properties of the system is presented. These properties are illustrated by the measurements of the edge localized mode and the reversed shear Alfven eigenmode, showing both the advantage of having a two-dimensional (2D) measurement, as well as some of the limitations of electron cyclotron emission measurements. Furthermore, the application of singular value decomposition as a powerful tool for analyzing and filtering 2D data is presented.
Comparison of 2D and 3D gamma analyses
Pulliam, Kiley B.; Huang, Jessie Y.; Howell, Rebecca M.; Followill, David; Kry, Stephen F.; Bosca, Ryan; O’Daniel, Jennifer
2014-02-15
Purpose: As clinics begin to use 3D metrics for intensity-modulated radiation therapy (IMRT) quality assurance, it must be noted that these metrics will often produce results different from those produced by their 2D counterparts. 3D and 2D gamma analyses would be expected to produce different values, in part because of the different search space available. In the present investigation, the authors compared the results of 2D and 3D gamma analysis (where both datasets were generated in the same manner) for clinical treatment plans. Methods: Fifty IMRT plans were selected from the authors’ clinical database, and recalculated using Monte Carlo. Treatment planning system-calculated (“evaluated dose distributions”) and Monte Carlo-recalculated (“reference dose distributions”) dose distributions were compared using 2D and 3D gamma analysis. This analysis was performed using a variety of dose-difference (5%, 3%, 2%, and 1%) and distance-to-agreement (5, 3, 2, and 1 mm) acceptance criteria, low-dose thresholds (5%, 10%, and 15% of the prescription dose), and data grid sizes (1.0, 1.5, and 3.0 mm). Each comparison was evaluated to determine the average 2D and 3D gamma, lower 95th percentile gamma value, and percentage of pixels passing gamma. Results: The average gamma, lower 95th percentile gamma value, and percentage of passing pixels for each acceptance criterion demonstrated better agreement for 3D than for 2D analysis for every plan comparison. The average difference in the percentage of passing pixels between the 2D and 3D analyses with no low-dose threshold ranged from 0.9% to 2.1%. Similarly, using a low-dose threshold resulted in a difference between the mean 2D and 3D results, ranging from 0.8% to 1.5%. The authors observed no appreciable differences in gamma with changes in the data density (constant difference: 0.8% for 2D vs 3D). Conclusions: The authors found that 3D gamma analysis resulted in up to 2.9% more pixels passing than 2D analysis. It must
Recent advances in 2D materials for photocatalysis.
Luo, Bin; Liu, Gang; Wang, Lianzhou
2016-04-01
Two-dimensional (2D) materials have attracted increasing attention for photocatalytic applications because of their unique thickness dependent physical and chemical properties. This review gives a brief overview of the recent developments concerning the chemical synthesis and structural design of 2D materials at the nanoscale and their applications in photocatalytic areas. In particular, recent progress on the emerging strategies for tailoring 2D material-based photocatalysts to improve their photo-activity including elemental doping, heterostructure design and functional architecture assembly is discussed.
A real-time earthquake detector with prefiltering by wavelets
NASA Astrophysics Data System (ADS)
Botella, F.; Rosa-Herranz, J.; Giner, J. J.; Molina, S.; Galiana-Merino, J. J.
2003-08-01
With the recent development and the growth of personal computers technology, we decided to implement a new earthquake detector. This detector, WDetect, can register in continuous mode all signals received from all our stations of the Local Seismic Network in the province of Alicante in the South-East of Spain. Simultaneously, our program can detect and store seismic events using the classical algorithm based on short- and long-term averages (STA and LTA, respectively). As a new improvement in the detection process, we have added signal prefiltering using the discrete wavelet transform, which increases the detection rate and reduces the false alarm rate, in contrast to other detectors like XDetect or XRTP. All this has been achieved without losing any meaningful event. These improvements were verified by an analysis performed during March 2001 on data from the Local Seismic Network in the province of Alicante, where WDetect has been running since the end of year 2000.
NASA Astrophysics Data System (ADS)
Paliwal, Deepak; Choudhur, Achintya; Govandhan, T.
2014-06-01
Fault diagnosis of rolling element bearings requires efficient signal processing techniques. For this purpose, the performances of envelope detection with fast Fourier transform (FFT) and continuous wavelet transform (CWT) of vibration signals produced from a bearing with defects on inner race and rolling element, have been examined at low signal to noise ratio. Both simulated and experimental signals from identical bearings have been considered for the purpose of analysis. The bearings have been modeled as spring-mass-dashpot systems and the simulated signals have been obtained considering transfer functions for the bearing systems subjected to impulsive loads due to the defects. Frequency B spline wavelets have been applied for CWT and a discussion on wavelet selection has been presented for better effectiveness. Results show that use of CWT with the proposed wavelets overcomes the short coming of FFT while processing a noisy vibration signals for defect detection of bearings.
Alloyed 2D Metal-Semiconductor Atomic Layer Junctions.
Kim, Ah Ra; Kim, Yonghun; Nam, Jaewook; Chung, Hee-Suk; Kim, Dong Jae; Kwon, Jung-Dae; Park, Sang Won; Park, Jucheol; Choi, Sun Young; Lee, Byoung Hun; Park, Ji Hyeon; Lee, Kyu Hwan; Kim, Dong-Ho; Choi, Sung Mook; Ajayan, Pulickel M; Hahm, Myung Gwan; Cho, Byungjin
2016-03-01
Heterostructures of compositionally and electronically variant two-dimensional (2D) atomic layers are viable building blocks for ultrathin optoelectronic devices. We show that the composition of interfacial transition region between semiconducting WSe2 atomic layer channels and metallic NbSe2 contact layers can be engineered through interfacial doping with Nb atoms. WxNb1-xSe2 interfacial regions considerably lower the potential barrier height of the junction, significantly improving the performance of the corresponding WSe2-based field-effect transistor devices. The creation of such alloyed 2D junctions between dissimilar atomic layer domains could be the most important factor in controlling the electronic properties of 2D junctions and the design and fabrication of 2D atomic layer devices.
Emerging and potential opportunities for 2D flexible nanoelectronics
NASA Astrophysics Data System (ADS)
Zhu, Weinan; Park, Saungeun; Akinwande, Deji
2016-05-01
The last 10 years have seen the emergence of two-dimensional (2D) nanomaterials such as graphene, transition metal dichalcogenides (TMDs), and black phosphorus (BP) among the growing portfolio of layered van der Waals thin films. Graphene, the prototypical 2D material has advanced rapidly in device, circuit and system studies that has resulted in commercial large-area applications. In this work, we provide a perspective of the emerging and potential translational applications of 2D materials including semiconductors, semimetals, and insulators that comprise the basic material set for diverse nanosystems. Applications include RF transceivers, smart systems, the so-called internet of things, and neurotechnology. We will review the DC and RF electronic performance of graphene and BP thin film transistors. 2D materials at sub-um channel length have so far enabled cut-off frequencies from baseband to 100GHz suitable for low-power RF and sub-THz concepts.
2D hexagonal quaternion Fourier transform in color image processing
NASA Astrophysics Data System (ADS)
Grigoryan, Artyom M.; Agaian, Sos S.
2016-05-01
In this paper, we present a novel concept of the quaternion discrete Fourier transform on the two-dimensional hexagonal lattice, which we call the two-dimensional hexagonal quaternion discrete Fourier transform (2-D HQDFT). The concept of the right-side 2D HQDFT is described and the left-side 2-D HQDFT is similarly considered. To calculate the transform, the image on the hexagonal lattice is described in the tensor representation when the image is presented by a set of 1-D signals, or splitting-signals which can be separately processed in the frequency domain. The 2-D HQDFT can be calculated by a set of 1-D quaternion discrete Fourier transforms (QDFT) of the splitting-signals.
Technical Review of the UNET2D Hydraulic Model
Perkins, William A.; Richmond, Marshall C.
2009-05-18
The Kansas City District of the US Army Corps of Engineers is engaged in a broad range of river management projects that require knowledge of spatially-varied hydraulic conditions such as velocities and water surface elevations. This information is needed to design new structures, improve existing operations, and assess aquatic habitat. Two-dimensional (2D) depth-averaged numerical hydraulic models are a common tool that can be used to provide velocity and depth information. Kansas City District is currently using a specific 2D model, UNET2D, that has been developed to meet the needs of their river engineering applications. This report documents a tech- nical review of UNET2D.
Double resonance rotational spectroscopy of CH2D+
NASA Astrophysics Data System (ADS)
Töpfer, Matthias; Jusko, Pavol; Schlemmer, Stephan; Asvany, Oskar
2016-09-01
Context. Deuterated forms of CH are thought to be responsible for deuterium enrichment in lukewarm astronomical environments. There is no unambiguous detection of CH2D+ in space to date. Aims: Four submillimetre rotational lines of CH2D+ are documented in the literature. Our aim is to present a complete dataset of highly resolved rotational lines, including millimetre (mm) lines needed for a potential detection. Methods: We used a low-temperature ion trap and applied a novel IR-mm-wave double resonance method to measure the rotational lines of CH2D+. Results: We measured 21 low-lying (J ≤ 4) rotational transitions of CH2D+ between 23 GHz and 1.1 THz with accuracies close to 2 ppb.
Alloyed 2D Metal-Semiconductor Atomic Layer Junctions.
Kim, Ah Ra; Kim, Yonghun; Nam, Jaewook; Chung, Hee-Suk; Kim, Dong Jae; Kwon, Jung-Dae; Park, Sang Won; Park, Jucheol; Choi, Sun Young; Lee, Byoung Hun; Park, Ji Hyeon; Lee, Kyu Hwan; Kim, Dong-Ho; Choi, Sung Mook; Ajayan, Pulickel M; Hahm, Myung Gwan; Cho, Byungjin
2016-03-01
Heterostructures of compositionally and electronically variant two-dimensional (2D) atomic layers are viable building blocks for ultrathin optoelectronic devices. We show that the composition of interfacial transition region between semiconducting WSe2 atomic layer channels and metallic NbSe2 contact layers can be engineered through interfacial doping with Nb atoms. WxNb1-xSe2 interfacial regions considerably lower the potential barrier height of the junction, significantly improving the performance of the corresponding WSe2-based field-effect transistor devices. The creation of such alloyed 2D junctions between dissimilar atomic layer domains could be the most important factor in controlling the electronic properties of 2D junctions and the design and fabrication of 2D atomic layer devices. PMID:26839956
ORION96. 2-d Finite Element Code Postprocessor
Sanford, L.A.; Hallquist, J.O.
1992-02-02
ORION is an interactive program that serves as a postprocessor for the analysis programs NIKE2D, DYNA2D, TOPAZ2D, and CHEMICAL TOPAZ2D. ORION reads binary plot files generated by the two-dimensional finite element codes currently used by the Methods Development Group at LLNL. Contour and color fringe plots of a large number of quantities may be displayed on meshes consisting of triangular and quadrilateral elements. ORION can compute strain measures, interface pressures along slide lines, reaction forces along constrained boundaries, and momentum. ORION has been applied to study the response of two-dimensional solids and structures undergoing finite deformations under a wide variety of large deformation transient dynamic and static problems and heat transfer analyses.
White, M.A.; Schmidt, J.C.; Topping, D.J.
2005-01-01
Wavelet analysis is a powerful tool with which to analyse the hydrologic effects of dam construction and operation on river systems. Using continuous records of instantaneous discharge from the Lees Ferry gauging station and records of daily mean discharge from upstream tributaries, we conducted wavelet analyses of the hydrologic structure of the Colorado River in Grand Canyon. The wavelet power spectrum (WPS) of daily mean discharge provided a highly compressed and integrative picture of the post-dam elimination of pronounced annual and sub-annual flow features. The WPS of the continuous record showed the influence of diurnal and weekly power generation cycles, shifts in discharge management, and the 1996 experimental flood in the post-dam period. Normalization of the WPS by local wavelet spectra revealed the fine structure of modulation in discharge scale and amplitude and provides an extremely efficient tool with which to assess the relationships among hydrologic cycles and ecological and geomorphic systems. We extended our analysis to sections of the Snake River and showed how wavelet analysis can be used as a data mining technique. The wavelet approach is an especially promising tool with which to assess dam operation in less well-studied regions and to evaluate management attempts to reconstruct desired flow characteristics. Copyright ?? 2005 John Wiley & Sons, Ltd.
Phylogenetic tree construction based on 2D graphical representation
NASA Astrophysics Data System (ADS)
Liao, Bo; Shan, Xinzhou; Zhu, Wen; Li, Renfa
2006-04-01
A new approach based on the two-dimensional (2D) graphical representation of the whole genome sequence [Bo Liao, Chem. Phys. Lett., 401(2005) 196.] is proposed to analyze the phylogenetic relationships of genomes. The evolutionary distances are obtained through measuring the differences among the 2D curves. The fuzzy theory is used to construct phylogenetic tree. The phylogenetic relationships of H5N1 avian influenza virus illustrate the utility of our approach.
Generating a 2D Representation of a Complex Data Structure
NASA Technical Reports Server (NTRS)
James, Mark
2006-01-01
A computer program, designed to assist in the development and debugging of other software, generates a two-dimensional (2D) representation of a possibly complex n-dimensional (where n is an integer >2) data structure or abstract rank-n object in that other software. The nature of the 2D representation is such that it can be displayed on a non-graphical output device and distributed by non-graphical means.
Anisotropic 2D Materials for Tunable Hyperbolic Plasmonics.
Nemilentsau, Andrei; Low, Tony; Hanson, George
2016-02-12
Motivated by the recent emergence of a new class of anisotropic 2D materials, we examine their electromagnetic modes and demonstrate that a broad class of the materials can host highly directional hyperbolic plasmons. Their propagation direction can be manipulated on the spot by gate doping, enabling hyperbolic beam reflection, refraction, and bending. The realization of these natural 2D hyperbolic media opens up a new avenue in dynamic control of hyperbolic plasmons not possible in the 3D version.
A simultaneous 2D/3D autostereo workstation
NASA Astrophysics Data System (ADS)
Chau, Dennis; McGinnis, Bradley; Talandis, Jonas; Leigh, Jason; Peterka, Tom; Knoll, Aaron; Sumer, Aslihan; Papka, Michael; Jellinek, Julius
2012-03-01
We present a novel immersive workstation environment that scientists can use for 3D data exploration and as their everyday 2D computer monitor. Our implementation is based on an autostereoscopic dynamic parallax barrier 2D/3D display, interactive input devices, and a software infrastructure that allows client/server software modules to couple the workstation to scientists' visualization applications. This paper describes the hardware construction and calibration, software components, and a demonstration of our system in nanoscale materials science exploration.
QUENCH2D. Two-Dimensional IHCP Code
Osman, A.; Beck, J.V.
1995-01-01
QUENCH2D* is developed for the solution of general, non-linear, two-dimensional inverse heat transfer problems. This program provides estimates for the surface heat flux distribution and/or heat transfer coefficient as a function of time and space by using transient temperature measurements at appropriate interior points inside the quenched body. Two-dimensional planar and axisymmetric geometries such as turnbine disks and blades, clutch packs, and many other problems can be analyzed using QUENCH2D*.
Wavelet-based automatic determination of the P- and S-wave arrivals
NASA Astrophysics Data System (ADS)
Bogiatzis, P.; Ishii, M.
2013-12-01
The detection of P- and S-wave arrivals is important for a variety of seismological applications including earthquake detection and characterization, and seismic tomography problems such as imaging of hydrocarbon reservoirs. For many years, dedicated human-analysts manually selected the arrival times of P and S waves. However, with the rapid expansion of seismic instrumentation, automatic techniques that can process a large number of seismic traces are becoming essential in tomographic applications, and for earthquake early-warning systems. In this work, we present a pair of algorithms for efficient picking of P and S onset times. The algorithms are based on the continuous wavelet transform of the seismic waveform that allows examination of a signal in both time and frequency domains. Unlike Fourier transform, the basis functions are localized in time and frequency, therefore, wavelet decomposition is suitable for analysis of non-stationary signals. For detecting the P-wave arrival, the wavelet coefficients are calculated using the vertical component of the seismogram, and the onset time of the wave is identified. In the case of the S-wave arrival, we take advantage of the polarization of the shear waves, and cross-examine the wavelet coefficients from the two horizontal components. In addition to the onset times, the automatic picking program provides estimates of uncertainty, which are important for subsequent applications. The algorithms are tested with synthetic data that are generated to include sudden changes in amplitude, frequency, and phase. The performance of the wavelet approach is further evaluated using real data by comparing the automatic picks with manual picks. Our results suggest that the proposed algorithms provide robust measurements that are comparable to manual picks for both P- and S-wave arrivals.
An Undecimated Wavelet-based Method for Cochlear Implant Speech Processing
Hajiaghababa, Fatemeh; Kermani, Saeed; Marateb, Hamid R.
2014-01-01
A cochlear implant is an implanted electronic device used to provide a sensation of hearing to a person who is hard of hearing. The cochlear implant is often referred to as a bionic ear. This paper presents an undecimated wavelet-based speech coding strategy for cochlear implants, which gives a novel speech processing strategy. The undecimated wavelet packet transform (UWPT) is computed like the wavelet packet transform except that it does not down-sample the output at each level. The speech data used for the current study consists of 30 consonants, sampled at 16 kbps. The performance of our proposed UWPT method was compared to that of infinite impulse response (IIR) filter in terms of mean opinion score (MOS), short-time objective intelligibility (STOI) measure and segmental signal-to-noise ratio (SNR). Undecimated wavelet had better segmental SNR in about 96% of the input speech data. The MOS of the proposed method was twice in comparison with that of the IIR filter-bank. The statistical analysis revealed that the UWT-based N-of-M strategy significantly improved the MOS, STOI and segmental SNR (P < 0.001) compared with what obtained with the IIR filter-bank based strategies. The advantage of UWPT is that it is shift-invariant which gives a dense approximation to continuous wavelet transform. Thus, the information loss is minimal and that is why the UWPT performance was better than that of traditional filter-bank strategies in speech recognition tests. Results showed that the UWPT could be a promising method for speech coding in cochlear implants, although its computational complexity is higher than that of traditional filter-banks. PMID:25426428
An Undecimated Wavelet-based Method for Cochlear Implant Speech Processing.
Hajiaghababa, Fatemeh; Kermani, Saeed; Marateb, Hamid R
2014-10-01
A cochlear implant is an implanted electronic device used to provide a sensation of hearing to a person who is hard of hearing. The cochlear implant is often referred to as a bionic ear. This paper presents an undecimated wavelet-based speech coding strategy for cochlear implants, which gives a novel speech processing strategy. The undecimated wavelet packet transform (UWPT) is computed like the wavelet packet transform except that it does not down-sample the output at each level. The speech data used for the current study consists of 30 consonants, sampled at 16 kbps. The performance of our proposed UWPT method was compared to that of infinite impulse response (IIR) filter in terms of mean opinion score (MOS), short-time objective intelligibility (STOI) measure and segmental signal-to-noise ratio (SNR). Undecimated wavelet had better segmental SNR in about 96% of the input speech data. The MOS of the proposed method was twice in comparison with that of the IIR filter-bank. The statistical analysis revealed that the UWT-based N-of-M strategy significantly improved the MOS, STOI and segmental SNR (P < 0.001) compared with what obtained with the IIR filter-bank based strategies. The advantage of UWPT is that it is shift-invariant which gives a dense approximation to continuous wavelet transform. Thus, the information loss is minimal and that is why the UWPT performance was better than that of traditional filter-bank strategies in speech recognition tests. Results showed that the UWPT could be a promising method for speech coding in cochlear implants, although its computational complexity is higher than that of traditional filter-banks. PMID:25426428
NASA Astrophysics Data System (ADS)
Ren, Zhong; Liu, Guodong; Zeng, Lvming; Huang, Zhen; Huang, Shuanggen
2008-12-01
In this paper, an improved wavelet threshold denoising with combined translation invariance(TI)method is adopted to remove noises existed in the bio-chemical spectrum. Meanwhile, a novel wavelet threshold function and an optimal threshold determination algorithm are proposed. The new function is continuous and high-order derivable, it can overcome the vibration phenomena generated by the classical threshold function and decrease the error of reconstructed spectrum. So, it is superior to the frequency-domain filtering methods, the soft- and hard-threshold function proposed by D.L. Donoho and the semisoft-threshold function proposed by Gao, etc. The experimental results show that the improved TI wavelet threshold(TI-WT) denoising method can availably eliminate the Pseudo-Gibbs phenomena generated by the traditional wavelet thresholding method. At the same time, the improved wavelet threshold function and the TI-WT method present lower root mean-square-error (RMSE) and higher signal-to-noise ratio(SNR) than the frequency-domain filtering, classical soft and hard-threshold denoising The SNR increasing from 17.3200 to 32.5609, the RMSE decreasing from 4.0244 to 0.6257. Otherwise, The improved denoising method not only makes the spectrum smooth, but also effectively preserves the edge characteristics of the original spectrum.
Simulating MEMS Chevron Actuator for Strain Engineering 2D Materials
NASA Astrophysics Data System (ADS)
Vutukuru, Mounika; Christopher, Jason; Bishop, David; Swan, Anna
2D materials pose an exciting paradigm shift in the world of electronics. These crystalline materials have demonstrated high electric and thermal conductivities and tensile strength, showing great potential as the new building blocks of basic electronic circuits. However, strain engineering 2D materials for novel devices remains a difficult experimental feat. We propose the integration of 2D materials with MEMS devices to investigate the strain dependence on material properties such as electrical and thermal conductivity, refractive index, mechanical elasticity, and band gap. MEMS Chevron actuators, provides the most accessible framework to study strain in 2D materials due to their high output force displacements for low input power. Here, we simulate Chevron actuators on COMSOL to optimize actuator design parameters and accurately capture the behavior of the devices while under the external force of a 2D material. Through stationary state analysis, we analyze the response of the device through IV characteristics, displacement and temperature curves. We conclude that the simulation precisely models the real-world device through experimental confirmation, proving that the integration of 2D materials with MEMS is a viable option for constructing novel strain engineered devices. The authors acknowledge support from NSF DMR1411008.
Feature selection using Haar wavelet power spectrum
Subramani, Prabakaran; Sahu, Rajendra; Verma, Shekhar
2006-01-01
Background Feature selection is an approach to overcome the 'curse of dimensionality' in complex researches like disease classification using microarrays. Statistical methods are utilized more in this domain. Most of them do not fit for a wide range of datasets. The transform oriented signal processing domains are not probed much when other fields like image and video processing utilize them well. Wavelets, one of such techniques, have the potential to be utilized in feature selection method. The aim of this paper is to assess the capability of Haar wavelet power spectrum in the problem of clustering and gene selection based on expression data in the context of disease classification and to propose a method based on Haar wavelet power spectrum. Results Haar wavelet power spectra of genes were analysed and it was observed to be different in different diagnostic categories. This difference in trend and magnitude of the spectrum may be utilized in gene selection. Most of the genes selected by earlier complex methods were selected by the very simple present method. Each earlier works proved only few genes are quite enough to approach the classification problem [1]. Hence the present method may be tried in conjunction with other classification methods. The technique was applied without removing the noise in data to validate the robustness of the method against the noise or outliers in the data. No special softwares or complex implementation is needed. The qualities of the genes selected by the present method were analysed through their gene expression data. Most of them were observed to be related to solve the classification issue since they were dominant in the diagnostic category of the dataset for which they were selected as features. Conclusion In the present paper, the problem of feature selection of microarray gene expression data was considered. We analyzed the wavelet power spectrum of genes and proposed a clustering and feature selection method useful for
National Prociency Testing Result of CYP2D6*10 Genotyping for Adjuvant Tamoxifen Therapy in China.
Lin, Guigao; Zhang, Kuo; Yi, Lang; Han, Yanxi; Xie, Jiehong; Li, Jinming
2016-01-01
Tamoxifen has been successfully used for treating breast cancer and preventing cancer recurrence. Cytochrome P450 2D6 (CYP2D6) plays a key role in the process of metabolizing tamoxifen to its active moiety, endoxifen. Patients with variants of the CYP2D6 gene may not receive the full benefit of tamoxifen treatment. The CYP2D6*10 variant (the most common variant in Asians) was analyzed to optimize the prescription of tamoxifen in China. To ensure referring clinicians have accurate information for genotype-guided tamoxifen treatment, the Chinese National Center for Clinical Laboratories (NCCL) organized a national proficiency testing (PT) to evaluate the performance of laboratories providing CYP2D6*10 genotyping. Ten genomic DNA samples with CYP2D6 wild-type or CYP2D6*10 variants were validated by PCR-sequencing and sent to 28 participant laboratories. The genotyping results and pharmacogenomic test reports were submitted and evaluated by NCCL experts. Additional information regarding the number of samples tested, the accreditation/certification status, and detecting technology was also requested. Thirty-one data sets were received, with a corresponding analytical sensitivity of 98.2% (548/558 challenges; 95% confidence interval: 96.7-99.1%) and an analytic specificity of 96.5% (675/682; 95% confidence interval: 97.9-99.5%). Overall, 25/28 participants correctly identified CYP2D6*10 status in 10 samples; however, two laboratories made serious genotyping errors. Most of the essential information was included in the 20 submitted CYP2D6*10 test reports. The majority of Chinese laboratories are reliable for detecting the CYP2D6*10 variant; however, several issues revealed in this study underline the importance of PT schemes in continued external assessment and provision of guidelines. PMID:27603206
National Prociency Testing Result of CYP2D6*10 Genotyping for Adjuvant Tamoxifen Therapy in China.
Lin, Guigao; Zhang, Kuo; Yi, Lang; Han, Yanxi; Xie, Jiehong; Li, Jinming
2016-01-01
Tamoxifen has been successfully used for treating breast cancer and preventing cancer recurrence. Cytochrome P450 2D6 (CYP2D6) plays a key role in the process of metabolizing tamoxifen to its active moiety, endoxifen. Patients with variants of the CYP2D6 gene may not receive the full benefit of tamoxifen treatment. The CYP2D6*10 variant (the most common variant in Asians) was analyzed to optimize the prescription of tamoxifen in China. To ensure referring clinicians have accurate information for genotype-guided tamoxifen treatment, the Chinese National Center for Clinical Laboratories (NCCL) organized a national proficiency testing (PT) to evaluate the performance of laboratories providing CYP2D6*10 genotyping. Ten genomic DNA samples with CYP2D6 wild-type or CYP2D6*10 variants were validated by PCR-sequencing and sent to 28 participant laboratories. The genotyping results and pharmacogenomic test reports were submitted and evaluated by NCCL experts. Additional information regarding the number of samples tested, the accreditation/certification status, and detecting technology was also requested. Thirty-one data sets were received, with a corresponding analytical sensitivity of 98.2% (548/558 challenges; 95% confidence interval: 96.7-99.1%) and an analytic specificity of 96.5% (675/682; 95% confidence interval: 97.9-99.5%). Overall, 25/28 participants correctly identified CYP2D6*10 status in 10 samples; however, two laboratories made serious genotyping errors. Most of the essential information was included in the 20 submitted CYP2D6*10 test reports. The majority of Chinese laboratories are reliable for detecting the CYP2D6*10 variant; however, several issues revealed in this study underline the importance of PT schemes in continued external assessment and provision of guidelines.
National Prociency Testing Result of CYP2D6*10 Genotyping for Adjuvant Tamoxifen Therapy in China
Lin, Guigao; Zhang, Kuo; Yi, Lang; Han, Yanxi; Xie, Jiehong; Li, Jinming
2016-01-01
Tamoxifen has been successfully used for treating breast cancer and preventing cancer recurrence. Cytochrome P450 2D6 (CYP2D6) plays a key role in the process of metabolizing tamoxifen to its active moiety, endoxifen. Patients with variants of the CYP2D6 gene may not receive the full benefit of tamoxifen treatment. The CYP2D6*10 variant (the most common variant in Asians) was analyzed to optimize the prescription of tamoxifen in China. To ensure referring clinicians have accurate information for genotype-guided tamoxifen treatment, the Chinese National Center for Clinical Laboratories (NCCL) organized a national proficiency testing (PT) to evaluate the performance of laboratories providing CYP2D6*10 genotyping. Ten genomic DNA samples with CYP2D6 wild-type or CYP2D6*10 variants were validated by PCR-sequencing and sent to 28 participant laboratories. The genotyping results and pharmacogenomic test reports were submitted and evaluated by NCCL experts. Additional information regarding the number of samples tested, the accreditation/certification status, and detecting technology was also requested. Thirty-one data sets were received, with a corresponding analytical sensitivity of 98.2% (548/558 challenges; 95% confidence interval: 96.7–99.1%) and an analytic specificity of 96.5% (675/682; 95% confidence interval: 97.9–99.5%). Overall, 25/28 participants correctly identified CYP2D6*10 status in 10 samples; however, two laboratories made serious genotyping errors. Most of the essential information was included in the 20 submitted CYP2D6*10 test reports. The majority of Chinese laboratories are reliable for detecting the CYP2D6*10 variant; however, several issues revealed in this study underline the importance of PT schemes in continued external assessment and provision of guidelines. PMID:27603206
Use of the 'Precessions' process for prepolishing and correcting 2D & 2(1/2)D form.
Walker, David D; Freeman, Richard; Morton, Roger; McCavana, Gerry; Beaucamp, Anthony
2006-11-27
The Precessions process polishes complex surfaces from the ground state preserving the ground-in form, and subsequently rectifies measured form errors. Our first paper introduced the technology and focused on the novel tooling. In this paper we describe the unique CNC machine tools and how they operate in polishing and correcting form. Experimental results demonstrate both the '2D' and '2(1/2)D' form-correction modes, as applied to aspheres with rotationally-symmetric target-form.
Is 2-D turbulence relevant in the atmosphere?
NASA Astrophysics Data System (ADS)
Lovejoy, Shaun; Schertzer, Daniel
2010-05-01
Starting with (Taylor, 1935), the paradigm of isotropic (and scaling!) turbulence was developed initially for laboratory applications, but following (Kolmogorov, 1941), three dimensional isotropic turbulence was progressively applied to the atmosphere. Since the atmosphere is strongly stratified, a single wide scale range model which is both isotropic and scaling is not possible so that theorists had to immediately choose between the two symmetries: isotropy or scale invariance. Following the development of models of two dimensional isotropic turbulence ((Fjortoft, 1953), but especially (Kraichnan, 1967) and (Charney, 1971)), the mainstream choice was to first make the convenient assumption of isotropy and to drop wide range scale invariance. Starting at the end of the 1970's this "isotropy primary" (IP) paradigm has lead to a series of increasingly complex isotropic 2D/isotropic 3D models of atmospheric dynamics which continue to dominate the theoretical landscape. Justifications for IP approaches have focused almost exclusively on the horizontal statistics of the horizontal wind in both numerical models and analyses and from aircraft campaigns, especially the highly cited GASP (Nastrom and Gage, 1983), (Gage and Nastrom, 1986; Nastrom and Gage, 1985) and MOZAIC (Cho and Lindborg, 2001) experiments. Since understanding the anisotropy clearly requires comparisons between horizontal and vertical statistics/structures this focus has been unfortunate. Over the same thirty year period that 2D/3D isotropic models were being elaborated, evidence slowly accumulated in favour of the opposite theoretical choice: to drop the isotropy assumption but to retain wide range scaling. The models in the alternative paradigm are scaling but strongly anisotropic with vertical sections of structures becoming increasingly stratified at larger and larger scales albeit in a power law manner; we collectively refer to these as "SP" for "scaling primary" approaches. Early authors explicitly
Wavelet analysis and applications to some dynamical systems
NASA Astrophysics Data System (ADS)
Bendjoya, Ph.; Slezak, E.
1993-05-01
The main properties of the wavelet transform as a new time-frequency method which is particularly well suited for detecting and localizing discontinuities and scaling behavior in signals are reviewed. Particular attention is given to first applications of the wavelet transform to dynamical systems including solution of partial differential equations, fractal and turbulence characterization, and asteroid family determination from cluster analysis. Advantages of the wavelet transform over classical analysis methods are summarized.
Embedded wavelet packet transform technique for texture compression
NASA Astrophysics Data System (ADS)
Li, Jin; Cheng, Po-Yuen; Kuo, C.-C. Jay
1995-09-01
A highly efficient texture compression scheme is proposed in this research. With this scheme, energy compaction of texture images is first achieved by the wavelet packet transform, and an embedding approach is then adopted for the coding of the wavelet packet transform coefficients. By comparing the proposed algorithm with the JPEG standard, FBI wavelet/scalar quantization standard and the EZW scheme with extensive experimental results, we observe a significant improvement in the rate-distortion performance and visual quality.
Variability of Solar Irradiances Using Wavelet Analysis
NASA Technical Reports Server (NTRS)
Pesnell, William D.
2007-01-01
We have used wavelets to analyze the sunspot number, F10.7 (the solar irradiance at a wavelength of approx.10.7 cm), and Ap (a geomagnetic activity index). Three different wavelets are compared, showing how each selects either temporal or scale resolution. Our goal is an envelope of solar activity that better bounds the large amplitude fluctuations form solar minimum to maximum. We show how the 11-year cycle does not disappear at solar minimum, that minimum is only the other part of the solar cycle. Power in the fluctuations of solar-activity-related indices may peak during solar maximum but the solar cycle itself is always present. The Ap index has a peak after solar maximum that appears to be better correlated with the current solar cycle than with the following cycle.
Wavelets for full reconfigurable ECG acquisition system
NASA Astrophysics Data System (ADS)
Morales, D. P.; García, A.; Castillo, E.; Meyer-Baese, U.; Palma, A. J.
2011-06-01
This paper presents the use of wavelet cores for a full reconfigurable electrocardiogram signal (ECG) acquisition system. The system is compound by two reconfigurable devices, a FPGA and a FPAA. The FPAA is in charge of the ECG signal acquisition, since this device is a versatile and reconfigurable analog front-end for biosignals. The FPGA is in charge of FPAA configuration, digital signal processing and information extraction such as heart beat rate and others. Wavelet analysis has become a powerful tool for ECG signal processing since it perfectly fits ECG signal shape. The use of these cores has been integrated in the LabVIEW FPGA module development tool that makes possible to employ VHDL cores within the usual LabVIEW graphical programming environment, thus freeing the designer from tedious and time consuming design of communication interfaces. This enables rapid test and graphical representation of results.
Wavelet packet entropy for heart murmurs classification.
Safara, Fatemeh; Doraisamy, Shyamala; Azman, Azreen; Jantan, Azrul; Ranga, Sri
2012-01-01
Heart murmurs are the first signs of cardiac valve disorders. Several studies have been conducted in recent years to automatically differentiate normal heart sounds, from heart sounds with murmurs using various types of audio features. Entropy was successfully used as a feature to distinguish different heart sounds. In this paper, new entropy was introduced to analyze heart sounds and the feasibility of using this entropy in classification of five types of heart sounds and murmurs was shown. The entropy was previously introduced to analyze mammograms. Four common murmurs were considered including aortic regurgitation, mitral regurgitation, aortic stenosis, and mitral stenosis. Wavelet packet transform was employed for heart sound analysis, and the entropy was calculated for deriving feature vectors. Five types of classification were performed to evaluate the discriminatory power of the generated features. The best results were achieved by BayesNet with 96.94% accuracy. The promising results substantiate the effectiveness of the proposed wavelet packet entropy for heart sounds classification.
Wavelets and their applications past and future
NASA Astrophysics Data System (ADS)
Coifman, Ronald R.
2009-04-01
As this is a conference on mathematical tools for defense, I would like to dedicate this talk to the memory of Louis Auslander, who through his insights and visionary leadership, brought powerful new mathematics into DARPA, he has provided the main impetus to the development and insertion of wavelet based processing in defense. My goal here is to describe the evolution of a stream of ideas in Harmonic Analysis, ideas which in the past have been mostly applied for the analysis and extraction of information from physical data, and which now are increasingly applied to organize and extract information and knowledge from any set of digital documents, from text to music to questionnaires. This form of signal processing on digital data, is part of the future of wavelet analysis.
Wavelet Denoising of Mobile Radiation Data
Campbell, D; Lanier, R
2007-10-29
The investigation of wavelet analysis techniques as a means of filtering the gross-count signal obtained from radiation detectors has shown promise. These signals are contaminated with high frequency statistical noise and significantly varying background radiation levels. Wavelet transforms allow a signal to be split into its constituent frequency components without losing relative timing information. Initial simulations and an injection study have been performed. Additionally, acquisition and analysis software has been written which allowed the technique to be evaluated in real-time under more realistic operating conditions. The technique performed well when compared to more traditional triggering techniques with its performance primarily limited by false alarms due to prominent features in the signal. An initial investigation into the potential rejection and classification of these false alarms has also shown promise.
Wavelet analysis of the impedance cardiogram waveforms
NASA Astrophysics Data System (ADS)
Podtaev, S.; Stepanov, R.; Dumler, A.; Chugainov, S.; Tziberkin, K.
2012-12-01
Impedance cardiography has been used for diagnosing atrial and ventricular dysfunctions, valve disorders, aortic stenosis, and vascular diseases. Almost all the applications of impedance cardiography require determination of some of the characteristic points of the ICG waveform. The ICG waveform has a set of characteristic points known as A, B, E ((dZ/dt)max) X, Y, O and Z. These points are related to distinct physiological events in the cardiac cycle. Objective of this work is an approbation of a new method of processing and interpretation of the impedance cardiogram waveforms using wavelet analysis. A method of computer thoracic tetrapolar polyrheocardiography is used for hemodynamic registrations. Use of original wavelet differentiation algorithm allows combining filtration and calculation of the derivatives of rheocardiogram. The proposed approach can be used in clinical practice for early diagnostics of cardiovascular system remodelling in the course of different pathologies.
Orthogonal wavelet moments and their multifractal invariants
NASA Astrophysics Data System (ADS)
Uchaev, Dm. V.; Uchaev, D. V.; Malinnikov, V. A.
2015-02-01
This paper introduces a new family of moments, namely orthogonal wavelet moments (OWMs), which are orthogonal realization of wavelet moments (WMs). In contrast to WMs with nonorthogonal kernel function, these moments can be used for multiresolution image representation and image reconstruction. The paper also introduces multifractal invariants (MIs) of OWMs which can be used instead of OWMs. Some reconstruction tests performed with noise-free and noisy images demonstrate that MIs of OWMs can also be used for image smoothing, sharpening and denoising. It is established that the reconstruction quality for MIs of OWMs can be better than corresponding orthogonal moments (OMs) and reduces to the reconstruction quality for the OMs if we use the zero scale level.
Propagating unstable wavelets in cardiac tissue
NASA Astrophysics Data System (ADS)
Boyle, Patrick M.; Madhavan, Adarsh; Reid, Matthew P.; Vigmond, Edward J.
2012-01-01
Solitonlike propagating modes have been proposed for excitable tissue, but have never been measured in cardiac tissue. In this study, we simulate an experimental protocol to elicit these propagating unstable wavelets (PUWs) in a detailed three-dimensional ventricular wedge preparation. PUWs appear as fixed-shape wavelets that propagate only in the direction of cardiac fibers, with conduction velocity approximately 40% slower than normal action potential excitation. We investigate their properties, demonstrating that PUWs are not true solitons. The range of stimuli for which PUWs were elicited was very narrow (several orders of magnitude lower than the stimulus strength itself), but increased with reduced sodium conductance and reduced coupling in nonlongitudinal directions. We show that the phenomenon does not depend on the particular membrane representation used or the shape of the stimulating electrode.
A millimeter wave image fusion algorithm design and optimization based on CDF97 wavelet transform
NASA Astrophysics Data System (ADS)
Yu, Jian-cheng; Chen, Bo-yang; Xia, A.-lin; Liu, Xin-guang
2011-08-01
Millimeter wave imaging technology provides a new detection method for security, fast and safe. But the wave of the images is its own shortcomings, such as noise and low sensitivity. Systems used for security, since only the corresponding specific objects to retain the information, and other information missing, so the actual image is difficult to locate in the millimeter wave . Image fusion approach can be used to effectively solve this problem. People usually use visible and millimeter-wave image fusion. The use of visible image contains the visual information. The fused image can be more convenient site for the detection of concealed weapons and to provide accurate positioning. The integration of information from different detectors, and there are different between the two levels of signal to noise ratio and pixel resolution, so traditional pixel-level fusion methods often cannot satisfy the fusion. Many experts and scholars apply wavelet transform approach to deal with some remote sensing image fusion, and the performance has been greatly improved. Due to these wavelet transform algorithm with complexity and large amount of computation, many algorithms are still in research stage. In order to improve the fusion performance and gain the real-time image fusion, an Integer Wavelet Transform CDF97 based with regional energy enhancement fusion algorithm is proposed in this paper. First, this paper studies of choice of wavelet operator. The paper invites several characteristics to evaluate the performance of wavelet operator used in image fusion. Results show that CDF97 wavelet fusion performance is better than traditional wavelet wavelets such as db wavelet, the vanishing moment longer the better. CDF97 wavelet has good energy concentration characteristic. The low frequency region of the transformed image contains almost the whole image energy. The target in millimeter wave image often has the low-pass characteristics and with a higher energy compare to the ambient
Development of wavelet analysis tools for turbulence
NASA Technical Reports Server (NTRS)
Bertelrud, A.; Erlebacher, G.; Dussouillez, PH.; Liandrat, M. P.; Liandrat, J.; Bailly, F. Moret; Tchamitchian, PH.
1992-01-01
Presented here is the general framework and the initial results of a joint effort to derive novel research tools and easy to use software to analyze and model turbulence and transition. Given here is a brief review of the issues, a summary of some basic properties of wavelets, and preliminary results. Technical aspects of the implementation, the physical conclusions reached at this time, and current developments are discussed.
Wavelet features in motion data classification
NASA Astrophysics Data System (ADS)
Szczesna, Agnieszka; Świtoński, Adam; Słupik, Janusz; Josiński, Henryk; Wojciechowski, Konrad
2016-06-01
The paper deals with the problem of motion data classification based on result of multiresolution analysis implemented in form of quaternion lifting scheme. Scheme processes directly on time series of rotations coded in form of unit quaternion signal. In the work new features derived from wavelet energy and entropy are proposed. To validate the approach gait database containing data of 30 different humans is used. The obtained results are satisfactory. The classification has over than 91% accuracy.
2 D patterns of soil gas diffusivity , soil respiration, and methane oxidation in a soil profile
NASA Astrophysics Data System (ADS)
Maier, Martin; Schack-Kirchner, Helmer; Lang, Friederike
2015-04-01
The apparent gas diffusion coefficient in soil (DS) is an important parameter describing soil aeration, which makes it a key parameter for root growth and gas production and consumption. Horizontal homogeneity in soil profiles is assumed in most studies for soil properties - including DS. This assumption, however, is not valid, even in apparently homogeneous soils, as we know from studies using destructive sampling methods. Using destructive methods may allow catching a glimpse, but a large uncertainty remains, since locations between the sampling positions cannot be analyzed, and measurements cannot be repeated. We developed a new method to determine in situ the apparent soil gas diffusion coefficient in order to examine 2 D pattern of DS and methane oxidation in a soil profile. Different tracer gases (SF6, CF4, C2H6) were injected continuously into the subsoil and measured at several locations in the soil profile. These data allow for modelling inversely the 2 D patterns of DS using Finite Element Modeling. The 2D DS patterns were then combined with naturally occurring CH4 and CO2 concentrations sampled at the same locations to derive the 2D pattern of soil respiration and methane oxidation in the soil profile. We show that methane oxidation and soil respiration zones shift within the soil profile while the gas fluxes at the surface remain rather stable during a the 3 week campaign.
2D-3D hybrid stabilized finite element method for tsunami runup simulations
NASA Astrophysics Data System (ADS)
Takase, S.; Moriguchi, S.; Terada, K.; Kato, J.; Kyoya, T.; Kashiyama, K.; Kotani, T.
2016-09-01
This paper presents a two-dimensional (2D)-three-dimensional (3D) hybrid stabilized finite element method that enables us to predict a propagation process of tsunami generated in a hypocentral region, which ranges from offshore propagation to runup to urban areas, with high accuracy and relatively low computational costs. To be more specific, the 2D shallow water equation is employed to simulate the propagation of offshore waves, while the 3D Navier-Stokes equation is employed for the runup in urban areas. The stabilized finite element method is utilized for numerical simulations for both of the 2D and 3D domains that are independently discretized with unstructured meshes. The multi-point constraint and transmission methods are applied to satisfy the continuity of flow velocities and pressures at the interface between the resulting 2D and 3D meshes, since neither their spatial dimensions nor node arrangements are consistent. Numerical examples are presented to demonstrate the performance of the proposed hybrid method to simulate tsunami behavior, including offshore propagation and runup to urban areas, with substantially lower computation costs in comparison with full 3D computations.
Correlation Filtering of Modal Dynamics using the Laplace Wavelet
NASA Technical Reports Server (NTRS)
Freudinger, Lawrence C.; Lind, Rick; Brenner, Martin J.
1997-01-01
Wavelet analysis allows processing of transient response data commonly encountered in vibration health monitoring tasks such as aircraft flutter testing. The Laplace wavelet is formulated as an impulse response of a single mode system to be similar to data features commonly encountered in these health monitoring tasks. A correlation filtering approach is introduced using the Laplace wavelet to decompose a signal into impulse responses of single mode subsystems. Applications using responses from flutter testing of aeroelastic systems demonstrate modal parameters and stability estimates can be estimated by correlation filtering free decay data with a set of Laplace wavelets.
REVIEWS OF TOPICAL PROBLEMS: Wavelets and their uses
NASA Astrophysics Data System (ADS)
Dremin, Igor M.; Ivanov, Oleg V.; Nechitailo, Vladimir A.
2001-05-01
This review paper is intended to give a useful guide for those who want to apply the discrete wavelet transform in practice. The notion of wavelets and their use in practical computing and various applications are briefly described, but rigorous proofs of mathematical statements are omitted, and the reader is just referred to the corresponding literature. The multiresolution analysis and fast wavelet transform have become a standard procedure for dealing with discrete wavelets. The proper choice of a wavelet and use of nonstandard matrix multiplication are often crucial for the achievement of a goal. Analysis of various functions with the help of wavelets allows one to reveal fractal structures, singularities etc. The wavelet transform of operator expressions helps solve some equations. In practical applications one often deals with the discretized functions, and the problem of stability of the wavelet transform and corresponding numerical algorithms becomes important. After discussing all these topics we turn to practical applications of the wavelet machinery. They are so numerous that we have to limit ourselves to a few examples only. The authors would be grateful for any comments which would move us closer to the goal proclaimed in the first phrase of the abstract.
Coresident sensor fusion and compression using the wavelet transform
Yocky, D.A.
1996-03-11
Imagery from coresident sensor platforms, such as unmanned aerial vehicles, can be combined using, multiresolution decomposition of the sensor images by means of the two-dimensional wavelet transform. The wavelet approach uses the combination of spatial/spectral information at multiple scales to create a fused image. This can be done in both an ad hoc or model-based approach. We compare results from commercial ``fusion`` software and the ad hoc, wavelet approach. Results show the wavelet approach outperforms the commercial algorithms and also supports efficient compression of the fused image.
Wavelet-based moment invariants for pattern recognition
NASA Astrophysics Data System (ADS)
Chen, Guangyi; Xie, Wenfang
2011-07-01
Moment invariants have received a lot of attention as features for identification and inspection of two-dimensional shapes. In this paper, two sets of novel moments are proposed by using the auto-correlation of wavelet functions and the dual-tree complex wavelet functions. It is well known that the wavelet transform lacks the property of shift invariance. A little shift in the input signal will cause very different output wavelet coefficients. The autocorrelation of wavelet functions and the dual-tree complex wavelet functions, on the other hand, are shift-invariant, which is very important in pattern recognition. Rotation invariance is the major concern in this paper, while translation invariance and scale invariance can be achieved by standard normalization techniques. The Gaussian white noise is added to the noise-free images and the noise levels vary with different signal-to-noise ratios. Experimental results conducted in this paper show that the proposed wavelet-based moments outperform Zernike's moments and the Fourier-wavelet descriptor for pattern recognition under different rotation angles and different noise levels. It can be seen that the proposed wavelet-based moments can do an excellent job even when the noise levels are very high.
Improved total variation algorithms for wavelet-based denoising
NASA Astrophysics Data System (ADS)
Easley, Glenn R.; Colonna, Flavia
2007-04-01
Many improvements of wavelet-based restoration techniques suggest the use of the total variation (TV) algorithm. The concept of combining wavelet and total variation methods seems effective but the reasons for the success of this combination have been so far poorly understood. We propose a variation of the total variation method designed to avoid artifacts such as oil painting effects and is more suited than the standard TV techniques to be implemented with wavelet-based estimates. We then illustrate the effectiveness of this new TV-based method using some of the latest wavelet transforms such as contourlets and shearlets.
A Wavelet Packets Approach to Electrocardiograph Baseline Drift Cancellation
Mozaffary, Behzad
2006-01-01
Baseline wander elimination is considered a classical problem. In electrocardiography (ECG) signals, baseline drift can influence the accurate diagnosis of heart disease such as ischemia and arrhythmia. We present a wavelet-transform- (WT-) based search algorithm using the energy of the signal in different scales to isolate baseline wander from the ECG signal. The algorithm computes wavelet packet coefficients and then in each scale the energy of the signal is calculated. Comparison is made and the branch of the wavelet binary tree corresponding to higher energy wavelet spaces is chosen. This algorithm is tested using the data record from MIT/BIH database and excellent results are obtained. PMID:23165064
Wavelet and Multiresolution Analysis for Finite Element Networking Paradigms
NASA Technical Reports Server (NTRS)
Kurdila, Andrew J.; Sharpley, Robert C.
1999-01-01
This paper presents a final report on Wavelet and Multiresolution Analysis for Finite Element Networking Paradigms. The focus of this research is to derive and implement: 1) Wavelet based methodologies for the compression, transmission, decoding, and visualization of three dimensional finite element geometry and simulation data in a network environment; 2) methodologies for interactive algorithm monitoring and tracking in computational mechanics; and 3) Methodologies for interactive algorithm steering for the acceleration of large scale finite element simulations. Also included in this report are appendices describing the derivation of wavelet based Particle Image Velocity algorithms and reduced order input-output models for nonlinear systems by utilizing wavelet approximations.
Scope and applications of translation invariant wavelets to image registration
NASA Technical Reports Server (NTRS)
Chettri, Samir; LeMoigne, Jacqueline; Campbell, William
1997-01-01
The first part of this article introduces the notion of translation invariance in wavelets and discusses several wavelets that have this property. The second part discusses the possible applications of such wavelets to image registration. In the case of registration of affinely transformed images, we would conclude that the notion of translation invariance is not really necessary. What is needed is affine invariance and one way to do this is via the method of moment invariants. Wavelets or, in general, pyramid processing can then be combined with the method of moment invariants to reduce the computational load.
Wavelet-based verification of the quantitative precipitation forecast
NASA Astrophysics Data System (ADS)
Yano, Jun-Ichi; Jakubiak, Bogumil
2016-06-01
This paper explores the use of wavelets for spatial verification of quantitative precipitation forecasts (QPF), and especially the capacity of wavelets to provide both localization and scale information. Two 24-h forecast experiments using the two versions of the Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) on 22 August 2010 over Poland are used to illustrate the method. Strong spatial localizations and associated intermittency of the precipitation field make verification of QPF difficult using standard statistical methods. The wavelet becomes an attractive alternative, because it is specifically designed to extract spatially localized features. The wavelet modes are characterized by the two indices for the scale and the localization. Thus, these indices can simply be employed for characterizing the performance of QPF in scale and localization without any further elaboration or tunable parameters. Furthermore, spatially-localized features can be extracted in wavelet space in a relatively straightforward manner with only a weak dependence on a threshold. Such a feature may be considered an advantage of the wavelet-based method over more conventional "object" oriented verification methods, as the latter tend to represent strong threshold sensitivities. The present paper also points out limits of the so-called "scale separation" methods based on wavelets. Our study demonstrates how these wavelet-based QPF verifications can be performed straightforwardly. Possibilities for further developments of the wavelet-based methods, especially towards a goal of identifying a weak physical process contributing to forecast error, are also pointed out.
Bayesian Wavelet Shrinkage of the Haar-Fisz Transformed Wavelet Periodogram
2015-01-01
It is increasingly being realised that many real world time series are not stationary and exhibit evolving second-order autocovariance or spectral structure. This article introduces a Bayesian approach for modelling the evolving wavelet spectrum of a locally stationary wavelet time series. Our new method works by combining the advantages of a Haar-Fisz transformed spectrum with a simple, but powerful, Bayesian wavelet shrinkage method. Our new method produces excellent and stable spectral estimates and this is demonstrated via simulated data and on differenced infant electrocardiogram data. A major additional benefit of the Bayesian paradigm is that we obtain rigorous and useful credible intervals of the evolving spectral structure. We show how the Bayesian credible intervals provide extra insight into the infant electrocardiogram data. PMID:26381141
Denoising solar radiation data using coiflet wavelets
Karim, Samsul Ariffin Abdul Janier, Josefina B. Muthuvalu, Mohana Sundaram; Hasan, Mohammad Khatim; Sulaiman, Jumat; Ismail, Mohd Tahir
2014-10-24
Signal denoising and smoothing plays an important role in processing the given signal either from experiment or data collection through observations. Data collection usually was mixed between true data and some error or noise. This noise might be coming from the apparatus to measure or collect the data or human error in handling the data. Normally before the data is use for further processing purposes, the unwanted noise need to be filtered out. One of the efficient methods that can be used to filter the data is wavelet transform. Due to the fact that the received solar radiation data fluctuates according to time, there exist few unwanted oscillation namely noise and it must be filtered out before the data is used for developing mathematical model. In order to apply denoising using wavelet transform (WT), the thresholding values need to be calculated. In this paper the new thresholding approach is proposed. The coiflet2 wavelet with variation diminishing 4 is utilized for our purpose. From numerical results it can be seen clearly that, the new thresholding approach give better results as compare with existing approach namely global thresholding value.
Wavelet Technique Applications in Planetary Nebulae Images
NASA Astrophysics Data System (ADS)
Leal Ferreira, M. L.; Rabaça, C. R.; Cuisinier, F.; Epitácio Pereira, D. N.
2009-05-01
Through the application of the wavelet technique to a planetary nebulae image, we are able to identify different scale sizes structures present in its wavelet coefficient decompositions. In a multiscale vision model, an object is defined as a hierarchical set of these structures. We can then use this model to independently reconstruct the different objects that compose the nebulae. The result is the separation and identification of superposed objects, some of them with very low surface brightness, what makes them, in general, very difficult to be seen in the original images due to the presence of noise. This allows us to make a more detailed analysis of brightness distribution in these sources. In this project, we use this method to perform a detailed morphological study of some planetary nebulae and to investigate whether one of them indeed shows internal temperature fluctuations. We have also conducted a series of tests concerning the reliability of the method and the confidence level of the objects detected. The wavelet code used in this project is called OV_WAV and was developed by the UFRJ's Astronomy Departament team.
Multispectral multisensor image fusion using wavelet transforms
Lemeshewsky, George P.
1999-01-01
Fusion techniques can be applied to multispectral and higher spatial resolution panchromatic images to create a composite image that is easier to interpret than the individual images. Wavelet transform-based multisensor, multiresolution fusion (a type of band sharpening) was applied to Landsat thematic mapper (TM) multispectral and coregistered higher resolution SPOT panchromatic images. The objective was to obtain increased spatial resolution, false color composite products to support the interpretation of land cover types wherein the spectral characteristics of the imagery are preserved to provide the spectral clues needed for interpretation. Since the fusion process should not introduce artifacts, a shift invariant implementation of the discrete wavelet transform (SIDWT) was used. These results were compared with those using the shift variant, discrete wavelet transform (DWT). Overall, the process includes a hue, saturation, and value color space transform to minimize color changes, and a reported point-wise maximum selection rule to combine transform coefficients. The performance of fusion based on the SIDWT and DWT was evaluated with a simulated TM 30-m spatial resolution test image and a higher resolution reference. Simulated imagery was made by blurring higher resolution color-infrared photography with the TM sensors' point spread function. The SIDWT based technique produced imagery with fewer artifacts and lower error between fused images and the full resolution reference. Image examples with TM and SPOT 10-m panchromatic illustrate the reduction in artifacts due to the SIDWT based fusion.
Spectral Data Reduction via Wavelet Decomposition
NASA Technical Reports Server (NTRS)
Kaewpijit, S.; LeMoigne, J.; El-Ghazawi, T.; Rood, Richard (Technical Monitor)
2002-01-01
The greatest advantage gained from hyperspectral imagery is that narrow spectral features can be used to give more information about materials than was previously possible with broad-band multispectral imagery. For many applications, the new larger data volumes from such hyperspectral sensors, however, present a challenge for traditional processing techniques. For example, the actual identification of each ground surface pixel by its corresponding reflecting spectral signature is still one of the most difficult challenges in the exploitation of this advanced technology, because of the immense volume of data collected. Therefore, conventional classification methods require a preprocessing step of dimension reduction to conquer the so-called "curse of dimensionality." Spectral data reduction using wavelet decomposition could be useful, as it does not only reduce the data volume, but also preserves the distinctions between spectral signatures. This characteristic is related to the intrinsic property of wavelet transforms that preserves high- and low-frequency features during the signal decomposition, therefore preserving peaks and valleys found in typical spectra. When comparing to the most widespread dimension reduction technique, the Principal Component Analysis (PCA), and looking at the same level of compression rate, we show that Wavelet Reduction yields better classification accuracy, for hyperspectral data processed with a conventional supervised classification such as a maximum likelihood method.
Adaptive wavelet Wiener filtering of ECG signals.
Smital, Lukáš; Vítek, Martin; Kozumplík, Jiří; Provazník, Ivo
2013-02-01
In this study, we focused on the reduction of broadband myopotentials (EMG) in ECG signals using the wavelet Wiener filtering with noise-free signal estimation. We used the dyadic stationary wavelet transform (SWT) in the Wiener filter as well as in estimating the noise-free signal. Our goal was to find a suitable filter bank and to choose other parameters of the Wiener filter with respect to the signal-to-noise ratio (SNR) obtained. Testing was performed on artificially noised signals from the standard CSE database sampled at 500 Hz. When creating an artificial interference, we started from the generated white Gaussian noise, whose power spectrum was modified according to a model of the power spectrum of an EMG signal. To improve the filtering performance, we used adaptive setting parameters of filtering according to the level of interference in the input signal. We were able to increase the average SNR of the whole test database by about 10.6 dB. The proposed algorithm provides better results than the classic wavelet Wiener filter.
Adaptive wavelet Wiener filtering of ECG signals.
Smital, Lukáš; Vítek, Martin; Kozumplík, Jiří; Provazník, Ivo
2013-02-01
In this study, we focused on the reduction of broadband myopotentials (EMG) in ECG signals using the wavelet Wiener filtering with noise-free signal estimation. We used the dyadic stationary wavelet transform (SWT) in the Wiener filter as well as in estimating the noise-free signal. Our goal was to find a suitable filter bank and to choose other parameters of the Wiener filter with respect to the signal-to-noise ratio (SNR) obtained. Testing was performed on artificially noised signals from the standard CSE database sampled at 500 Hz. When creating an artificial interference, we started from the generated white Gaussian noise, whose power spectrum was modified according to a model of the power spectrum of an EMG signal. To improve the filtering performance, we used adaptive setting parameters of filtering according to the level of interference in the input signal. We were able to increase the average SNR of the whole test database by about 10.6 dB. The proposed algorithm provides better results than the classic wavelet Wiener filter. PMID:23192472
2D nanostructures for water purification: graphene and beyond.
Dervin, Saoirse; Dionysiou, Dionysios D; Pillai, Suresh C
2016-08-18
Owing to their atomically thin structure, large surface area and mechanical strength, 2D nanoporous materials are considered to be suitable alternatives for existing desalination and water purification membrane materials. Recent progress in the development of nanoporous graphene based materials has generated enormous potential for water purification technologies. Progress in the development of nanoporous graphene and graphene oxide (GO) membranes, the mechanism of graphene molecular sieve action, structural design, hydrophilic nature, mechanical strength and antifouling properties and the principal challenges associated with nanopore generation are discussed in detail. Subsequently, the recent applications and performance of newly developed 2D materials such as 2D boron nitride (BN) nanosheets, graphyne, molybdenum disulfide (MoS2), tungsten chalcogenides (WS2) and titanium carbide (Ti3C2Tx) are highlighted. In addition, the challenges affecting 2D nanostructures for water purification are highlighted and their applications in the water purification industry are discussed. Though only a few 2D materials have been explored so far for water treatment applications, this emerging field of research is set to attract a great deal of attention in the near future.
Ultrafast 2D-IR spectroelectrochemistry of flavin mononucleotide
NASA Astrophysics Data System (ADS)
El Khoury, Youssef; Van Wilderen, Luuk J. G. W.; Bredenbeck, Jens
2015-06-01
We demonstrate the coupling of ultrafast two-dimensional infrared (2D-IR) spectroscopy to electrochemistry in solution and apply it to flavin mononucleotide, an important cofactor of redox proteins. For this purpose, we designed a spectroelectrochemical cell optimized for 2D-IR measurements in reflection and measured the time-dependent 2D-IR spectra of the oxidized and reduced forms of flavin mononucleotide. The data show anharmonic coupling and vibrational energy transfer between different vibrational modes in the two redox species. Such information is inaccessible with redox-controlled steady-state FTIR spectroscopy. The wide range of applications offered by 2D-IR spectroscopy, such as sub-picosecond structure determination, IR band assignment via energy transfer, disentangling reaction mixtures through band connectivity in the 2D spectra, and the measurement of solvation dynamics and chemical exchange can now be explored under controlled redox potential. The development of this technique furthermore opens new horizons for studying the dynamics of redox proteins.
Ultrafast 2D-IR spectroelectrochemistry of flavin mononucleotide.
El Khoury, Youssef; Van Wilderen, Luuk J G W; Bredenbeck, Jens
2015-06-01
We demonstrate the coupling of ultrafast two-dimensional infrared (2D-IR) spectroscopy to electrochemistry in solution and apply it to flavin mononucleotide, an important cofactor of redox proteins. For this purpose, we designed a spectroelectrochemical cell optimized for 2D-IR measurements in reflection and measured the time-dependent 2D-IR spectra of the oxidized and reduced forms of flavin mononucleotide. The data show anharmonic coupling and vibrational energy transfer between different vibrational modes in the two redox species. Such information is inaccessible with redox-controlled steady-state FTIR spectroscopy. The wide range of applications offered by 2D-IR spectroscopy, such as sub-picosecond structure determination, IR band assignment via energy transfer, disentangling reaction mixtures through band connectivity in the 2D spectra, and the measurement of solvation dynamics and chemical exchange can now be explored under controlled redox potential. The development of this technique furthermore opens new horizons for studying the dynamics of redox proteins.
Mean flow and anisotropic cascades in decaying 2D turbulence
NASA Astrophysics Data System (ADS)
Liu, Chien-Chia; Cerbus, Rory; Gioia, Gustavo; Chakraborty, Pinaki
2015-11-01
Many large-scale atmospheric and oceanic flows are decaying 2D turbulent flows embedded in a non-uniform mean flow. Despite its importance for large-scale weather systems, the affect of non-uniform mean flows on decaying 2D turbulence remains unknown. In the absence of mean flow it is well known that decaying 2D turbulent flows exhibit the enstrophy cascade. More generally, for any 2D turbulent flow, all computational, experimental and field data amassed to date indicate that the spectrum of longitudinal and transverse velocity fluctuations correspond to the same cascade, signifying isotropy of cascades. Here we report experiments on decaying 2D turbulence in soap films with a non-uniform mean flow. We find that the flow transitions from the usual isotropic enstrophy cascade to a series of unusual and, to our knowledge, never before observed or predicted, anisotropic cascades where the longitudinal and transverse spectra are mutually independent. We discuss implications of our results for decaying geophysical turbulence.
Sparse radar imaging using 2D compressed sensing
NASA Astrophysics Data System (ADS)
Hou, Qingkai; Liu, Yang; Chen, Zengping; Su, Shaoying
2014-10-01
Radar imaging is an ill-posed linear inverse problem and compressed sensing (CS) has been proved to have tremendous potential in this field. This paper surveys the theory of radar imaging and a conclusion is drawn that the processing of ISAR imaging can be denoted mathematically as a problem of 2D sparse decomposition. Based on CS, we propose a novel measuring strategy for ISAR imaging radar and utilize random sub-sampling in both range and azimuth dimensions, which will reduce the amount of sampling data tremendously. In order to handle 2D reconstructing problem, the ordinary solution is converting the 2D problem into 1D by Kronecker product, which will increase the size of dictionary and computational cost sharply. In this paper, we introduce the 2D-SL0 algorithm into the reconstruction of imaging. It is proved that 2D-SL0 can achieve equivalent result as other 1D reconstructing methods, but the computational complexity and memory usage is reduced significantly. Moreover, we will state the results of simulating experiments and prove the effectiveness and feasibility of our method.
Ultrafast 2D NMR: an emerging tool in analytical spectroscopy.
Giraudeau, Patrick; Frydman, Lucio
2014-01-01
Two-dimensional nuclear magnetic resonance (2D NMR) spectroscopy is widely used in chemical and biochemical analyses. Multidimensional NMR is also witnessing increased use in quantitative and metabolic screening applications. Conventional 2D NMR experiments, however, are affected by inherently long acquisition durations, arising from their need to sample the frequencies involved along their indirect domains in an incremented, scan-by-scan nature. A decade ago, a so-called ultrafast (UF) approach was proposed, capable of delivering arbitrary 2D NMR spectra involving any kind of homo- or heteronuclear correlation, in a single scan. During the intervening years, the performance of this subsecond 2D NMR methodology has been greatly improved, and UF 2D NMR is rapidly becoming a powerful analytical tool experiencing an expanded scope of applications. This review summarizes the principles and main developments that have contributed to the success of this approach and focuses on applications that have been recently demonstrated in various areas of analytical chemistry--from the real-time monitoring of chemical and biochemical processes, to extensions in hyphenated techniques and in quantitative applications. PMID:25014342
2D nanostructures for water purification: graphene and beyond.
Dervin, Saoirse; Dionysiou, Dionysios D; Pillai, Suresh C
2016-08-18
Owing to their atomically thin structure, large surface area and mechanical strength, 2D nanoporous materials are considered to be suitable alternatives for existing desalination and water purification membrane materials. Recent progress in the development of nanoporous graphene based materials has generated enormous potential for water purification technologies. Progress in the development of nanoporous graphene and graphene oxide (GO) membranes, the mechanism of graphene molecular sieve action, structural design, hydrophilic nature, mechanical strength and antifouling properties and the principal challenges associated with nanopore generation are discussed in detail. Subsequently, the recent applications and performance of newly developed 2D materials such as 2D boron nitride (BN) nanosheets, graphyne, molybdenum disulfide (MoS2), tungsten chalcogenides (WS2) and titanium carbide (Ti3C2Tx) are highlighted. In addition, the challenges affecting 2D nanostructures for water purification are highlighted and their applications in the water purification industry are discussed. Though only a few 2D materials have been explored so far for water treatment applications, this emerging field of research is set to attract a great deal of attention in the near future. PMID:27506268
Blind watermark algorithm on 3D motion model based on wavelet transform
NASA Astrophysics Data System (ADS)
Qi, Hu; Zhai, Lang
2013-12-01
With the continuous development of 3D vision technology, digital watermark technology, as the best choice for copyright protection, has fused with it gradually. This paper proposed a blind watermark plan of 3D motion model based on wavelet transform, and made it loaded into the Vega real-time visual simulation system. Firstly, put 3D model into affine transform, and take the distance from the center of gravity to the vertex of 3D object in order to generate a one-dimensional discrete signal; then make this signal into wavelet transform to change its frequency coefficients and embed watermark, finally generate 3D motion model with watermarking. In fixed affine space, achieve the robustness in translation, revolving and proportion transforms. The results show that this approach has better performances not only in robustness, but also in watermark- invisibility.
[Wavelet analysis on SO2 pollution index changes of Shanghai in recent 10 years].
Wu, Xiao-ling; Zhang, Bin; Ai, Nan-shan; Liu, Li-jun
2009-08-15
Based on the continuous Mexican Hat wavelet transformation of time series of daily SO2 pollution index during last 10 years in Shanghai, the multiscale variations, primary period, catastrophe point and influencing factors are analyzed. The result shows that periodical fluctuation of SO2 pollution index varies at diverse time-scales, and the primary period of the daily variations is about 100 days; pollution pattern takes on serious in winter and light in summer in most scales due to meteorological conditions, and the catastrophe point of serious-light transformation of SO2 pollution index in a year is vernal and autumnal equinox; energy demand and socioeconomic development result in more seriousness in recent years and half result with twice the effort of endeavors of pollution elimination. Wavelet analysis is an effective method to time series of SO2 pollution index, also to multiscale variations of other pollutants. PMID:19799273
Graphene based 2D-materials for supercapacitors
NASA Astrophysics Data System (ADS)
Palaniselvam, Thangavelu; Baek, Jong-Beom
2015-09-01
Ever-increasing energy demands and the depletion of fossil fuels are compelling humanity toward the development of suitable electrochemical energy conversion and storage devices to attain a more sustainable society with adequate renewable energy and zero environmental pollution. In this regard, supercapacitors are being contemplated as potential energy storage devices to afford cleaner, environmentally friendly energy. Recently, a great deal of attention has been paid to two-dimensional (2D) nanomaterials, including 2D graphene and its inorganic analogues (transition metal double layer hydroxides, chalcogenides, etc), as potential electrodes for the development of supercapacitors with high electrochemical performance. This review provides an overview of the recent progress in using these graphene-based 2D materials as potential electrodes for supercapacitors. In addition, future research trends including notable challenges and opportunities are also discussed.
Secretory pathways generating immunosuppressive NKG2D ligands
Baragaño Raneros, Aroa; Suarez-Álvarez, Beatriz; López-Larrea, Carlos
2014-01-01
Natural Killer Group 2 member D (NKG2D) activating receptor, present on the surface of various immune cells, plays an important role in activating the anticancer immune response by their interaction with stress-inducible NKG2D ligands (NKG2DL) on transformed cells. However, cancer cells have developed numerous mechanisms to evade the immune system via the downregulation of NKG2DL from the cell surface, including the release of NKG2DL from the cell surface in a soluble form. Here, we review the mechanisms involved in the production of soluble NKG2DL (sNKG2DL) and the potential therapeutic strategies aiming to block the release of these immunosuppressive ligands. Therapeutically enabling the NKG2D-NKG2DL interaction would promote immunorecognition of malignant cells, thus abrogating disease progression. PMID:25050215
2D bifurcations and Newtonian properties of memristive Chua's circuits
NASA Astrophysics Data System (ADS)
Marszalek, W.; Podhaisky, H.
2016-01-01
Two interesting properties of Chua's circuits are presented. First, two-parameter bifurcation diagrams of Chua's oscillatory circuits with memristors are presented. To obtain various 2D bifurcation images a substantial numerical effort, possibly with parallel computations, is needed. The numerical algorithm is described first and its numerical code for 2D bifurcation image creation is available for free downloading. Several color 2D images and the corresponding 1D greyscale bifurcation diagrams are included. Secondly, Chua's circuits are linked to Newton's law φ ''= F(t,φ,φ')/m with φ=\\text{flux} , constant m > 0, and the force term F(t,φ,φ') containing memory terms. Finally, the jounce scalar equations for Chua's circuits are also discussed.
Focusing surface wave imaging with flexible 2D array
NASA Astrophysics Data System (ADS)
Zhou, Shiyuan; Fu, Junqiang; Li, Zhe; Xu, Chunguang; Xiao, Dingguo; Wang, Shaohan
2016-04-01
Curved surface is widely exist in key parts of energy and power equipment, such as, turbine blade cylinder block and so on. Cycling loading and harsh working condition of enable fatigue cracks appear on the surface. The crack should be found in time to avoid catastrophic damage to the equipment. A flexible 2D array transducer was developed. 2D Phased Array focusing method (2DPA), Mode-Spatial Double Phased focusing method (MSDPF) and the imaging method using the flexible 2D array probe are studied. Experiments using these focusing and imaging method are carried out. Surface crack image is obtained with both 2DPA and MSDPF focusing method. It have been proved that MSDPF can be more adaptable for curved surface and more calculate efficient than 2DPA.
Radiative heat transfer in 2D Dirac materials.
Rodriguez-López, Pablo; Tse, Wang-Kong; Dalvit, Diego A R
2015-06-01
We compute the radiative heat transfer between two sheets of 2D Dirac materials, including topological Chern insulators and graphene, within the framework of the local approximation for the optical response of these materials. In this approximation, which neglects spatial dispersion, we derive both numerically and analytically the short-distance asymptotic of the near-field heat transfer in these systems, and show that it scales as the inverse of the distance between the two sheets. Finally, we discuss the limitations to the validity of this scaling law imposed by spatial dispersion in 2D Dirac materials. PMID:25965703
Quantum process tomography by 2D fluorescence spectroscopy
Pachón, Leonardo A.; Marcus, Andrew H.; Aspuru-Guzik, Alán
2015-06-07
Reconstruction of the dynamics (quantum process tomography) of the single-exciton manifold in energy transfer systems is proposed here on the basis of two-dimensional fluorescence spectroscopy (2D-FS) with phase-modulation. The quantum-process-tomography protocol introduced here benefits from, e.g., the sensitivity enhancement ascribed to 2D-FS. Although the isotropically averaged spectroscopic signals depend on the quantum yield parameter Γ of the doubly excited-exciton manifold, it is shown that the reconstruction of the dynamics is insensitive to this parameter. Applications to foundational and applied problems, as well as further extensions, are discussed.
On 2D bisection method for double eigenvalue problems
Ji, X.
1996-06-01
The two-dimensional bisection method presented in (SIAM J. Matrix Anal. Appl. 13(4), 1085 (1992)) is efficient for solving a class of double eigenvalue problems. This paper further extends the 2D bisection method of full matrix cases and analyses its stability. As in a single parameter case, the 2D bisection method is very stable for the tridiagonal matrix triples satisfying the symmetric-definite condition. Since the double eigenvalue problems arise from two-parameter boundary value problems, an estimate of the discretization error in eigenpairs is also given. Some numerical examples are included. 42 refs., 1 tab.
Design of the LRP airfoil series using 2D CFD
NASA Astrophysics Data System (ADS)
Zahle, Frederik; Bak, Christian; Sørensen, Niels N.; Vronsky, Tomas; Gaudern, Nicholas
2014-06-01
This paper describes the design and wind tunnel testing of a high-Reynolds number, high lift airfoil series designed for wind turbines. The airfoils were designed using direct gradient- based numerical multi-point optimization based on a Bezier parameterization of the shape, coupled to the 2D Navier-Stokes flow solver EllipSys2D. The resulting airfoils, the LRP2-30 and LRP2-36, achieve both higher operational lift coefficients and higher lift to drag ratios compared to the equivalent FFA-W3 airfoils.
2012-01-05
Code is for a layered electric medium with 2d structure. Includes air-earth interface at node z=2.. The electric ex and ez fields are calculated on edges of elemental grid and magnetic field hy is calculated on the face of the elemental grid. The code allows for a layered earth with 2d structures. Solutions of coupled first order Maxwell's equations are solved in the two dimensional environment using a finite- difference scheme on a staggered spationamore » and temporal grid.« less
Noninvasive deep Raman detection with 2D correlation analysis
NASA Astrophysics Data System (ADS)
Kim, Hyung Min; Park, Hyo Sun; Cho, Youngho; Jin, Seung Min; Lee, Kang Taek; Jung, Young Mee; Suh, Yung Doug
2014-07-01
The detection of poisonous chemicals enclosed in daily necessaries is prerequisite essential for homeland security with the increasing threat of terrorism. For the detection of toxic chemicals, we combined a sensitive deep Raman spectroscopic method with 2D correlation analysis. We obtained the Raman spectra from concealed chemicals employing spatially offset Raman spectroscopy in which incident line-shaped light experiences multiple scatterings before being delivered to inner component and yielding deep Raman signal. Furthermore, we restored the pure Raman spectrum of each component using 2D correlation spectroscopic analysis with chemical inspection. Using this method, we could elucidate subsurface component under thick powder and packed contents in a bottle.
NASA Astrophysics Data System (ADS)
Hosomichi, Kazuo; Lee, Sungjay
2015-01-01
We study the system of M2-branes suspended between parallel M5-branes using ABJM model with a natural half-BPS boundary condition. For small separation between M5-branes, the worldvolume theory is shown to reduce to a 2D super Yang-Mills theory with some similarity to q-deformed Yang-Mills theory. The gauge coupling is related to the position of the branes in an interesting manner. The theory is considerably different from the 2D theory proposed for multiple "M-strings". We make a detailed comparison of elliptic genus of the two descriptions and find only a partial agreement.
Finite temperature corrections in 2d integrable models
NASA Astrophysics Data System (ADS)
Caselle, M.; Hasenbusch, M.
2002-09-01
We study the finite size corrections for the magnetization and the internal energy of the 2d Ising model in a magnetic field by using transfer matrix techniques. We compare these corrections with the functional form recently proposed by Delfino and LeClair-Mussardo for the finite temperature behaviour of one-point functions in integrable 2d quantum field theories. We find a perfect agreement between theoretical expectations and numerical results. Assuming the proposed functional form as an input in our analysis we obtain a relevant improvement in the precision of the continuum limit estimates of both quantities.
2dF grows up: Echidna for the AAT
NASA Astrophysics Data System (ADS)
McGrath, Andrew; Barden, Sam; Miziarski, Stan; Rambold, William; Smith, Greg
2008-07-01
We present the concept design of a new fibre positioner and spectrograph system for the Anglo-Australian Telescope, as a proposed enhancement to the Anglo-Australian Observatory's well-known 2dF facility. A four-fold multiplex enhancement is accomplished by replacing the 400-fibre 2dF fibre positioning robot with a 1600-fibre Echidna unit, feeding three clones of the AAOmega optical spectrograph. Such a facility has the capability of a redshift 1 survey of a large fraction of the southern sky, collecting five to ten thousand spectra per night for a million-galaxy survey.
Radiative heat transfer in 2D Dirac materials
Rodriguez-López, Pablo; Tse, Wang -Kong; Dalvit, Diego A. R.
2015-05-12
We compute the radiative heat transfer between two sheets of 2D Dirac materials, including topological Chern insulators and graphene, within the framework of the local approximation for the optical response of these materials. In this approximation, which neglects spatial dispersion, we derive both numerically and analytically the short-distance asymptotic of the near-field heat transfer in these systems, and show that it scales as the inverse of the distance between the two sheets. In conclusion, we discuss the limitations to the validity of this scaling law imposed by spatial dispersion in 2D Dirac materials.
Nomenclature for human CYP2D6 alleles.
Daly, A K; Brockmöller, J; Broly, F; Eichelbaum, M; Evans, W E; Gonzalez, F J; Huang, J D; Idle, J R; Ingelman-Sundberg, M; Ishizaki, T; Jacqz-Aigrain, E; Meyer, U A; Nebert, D W; Steen, V M; Wolf, C R; Zanger, U M
1996-06-01
To standardize CYP2D6 allele nomenclature, and to conform with international human gene nomenclature guidelines, an alternative to the current arbitrary system is described. Based on recommendations for human genome nomenclature, we propose that alleles be designated by CYP2D6 followed by an asterisk and a combination of roman letters and arabic numerals distinct for each allele with the number specifying the key mutation and, where appropriate, a letter specifying additional mutations. Criteria for classification as a separate allele and protein nomenclature are also presented. PMID:8807658
Spreading dynamics of 2D dipolar Langmuir monolayer phases.
Heinig, P; Wurlitzer, S; Fischer, Th M
2004-07-01
We study the spreading of a liquid 2D dipolar droplet in a Langmuir monolayer. Interfacial tensions (line tensions) and microscopic contact angles depend on the scale on which they are probed and obey a scaling law. Assuming rapid equilibration of the microscopic contact angle and ideal slippage of the 2D solid/liquid and solid/gas boundary, the driving force of spreading is merely expressed by the shape-dependent long-range interaction integrals. We obtain good agreement between experiment and numerical simulations using this theory. PMID:15278693
Evaluation of 2D ceramic matrix composites in aeroconvective environments
NASA Technical Reports Server (NTRS)
Riccitiello, Salvatore R.; Love, Wendell L.; Balter-Peterson, Aliza
1992-01-01
An evaluation is conducted of a novel ceramic-matrix composite (CMC) material system for use in the aeroconvective-heating environments encountered by the nose caps and wing leading edges of such aerospace vehicles as the Space Shuttle, during orbit-insertion and reentry from LEO. These CMCs are composed of an SiC matrix that is reinforced with Nicalon, Nextel, or carbon refractory fibers in a 2D architecture. The test program conducted for the 2D CMCs gave attention to their subsurface oxidation.
Quantum process tomography by 2D fluorescence spectroscopy
NASA Astrophysics Data System (ADS)
Pachón, Leonardo A.; Marcus, Andrew H.; Aspuru-Guzik, Alán
2015-06-01
Reconstruction of the dynamics (quantum process tomography) of the single-exciton manifold in energy transfer systems is proposed here on the basis of two-dimensional fluorescence spectroscopy (2D-FS) with phase-modulation. The quantum-process-tomography protocol introduced here benefits from, e.g., the sensitivity enhancement ascribed to 2D-FS. Although the isotropically averaged spectroscopic signals depend on the quantum yield parameter Γ of the doubly excited-exciton manifold, it is shown that the reconstruction of the dynamics is insensitive to this parameter. Applications to foundational and applied problems, as well as further extensions, are discussed.
Rowley-Neale, Samuel J; Fearn, Jamie M; Brownson, Dale A C; Smith, Graham C; Ji, Xiaobo; Banks, Craig E
2016-08-21
Two-dimensional molybdenum disulphide nanosheets (2D-MoS2) have proven to be an effective electrocatalyst, with particular attention being focused on their use towards increasing the efficiency of the reactions associated with hydrogen fuel cells. Whilst the majority of research has focused on the Hydrogen Evolution Reaction (HER), herein we explore the use of 2D-MoS2 as a potential electrocatalyst for the much less researched Oxygen Reduction Reaction (ORR). We stray from literature conventions and perform experiments in 0.1 M H2SO4 acidic electrolyte for the first time, evaluating the electrochemical performance of the ORR with 2D-MoS2 electrically wired/immobilised upon several carbon based electrodes (namely; Boron Doped Diamond (BDD), Edge Plane Pyrolytic Graphite (EPPG), Glassy Carbon (GC) and Screen-Printed Electrodes (SPE)) whilst exploring a range of 2D-MoS2 coverages/masses. Consequently, the findings of this study are highly applicable to real world fuel cell applications. We show that significant improvements in ORR activity can be achieved through the careful selection of the underlying/supporting carbon materials that electrically wire the 2D-MoS2 and utilisation of an optimal mass of 2D-MoS2. The ORR onset is observed to be reduced to ca. +0.10 V for EPPG, GC and SPEs at 2D-MoS2 (1524 ng cm(-2) modification), which is far closer to Pt at +0.46 V compared to bare/unmodified EPPG, GC and SPE counterparts. This report is the first to demonstrate such beneficial electrochemical responses in acidic conditions using a 2D-MoS2 based electrocatalyst material on a carbon-based substrate (SPEs in this case). Investigation of the beneficial reaction mechanism reveals the ORR to occur via a 4 electron process in specific conditions; elsewhere a 2 electron process is observed. This work offers valuable insights for those wishing to design, fabricate and/or electrochemically test 2D-nanosheet materials towards the ORR. PMID:27448174
Tønning, Erik; Polders, Daniel; Callaghan, Paul T; Engelsen, Søren B
2007-09-01
This paper demonstrates how the multi-linear PARAFAC model can with advantage be used to decompose 2D diffusion-relaxation correlation NMR spectra prior to 2D-Laplace inversion to the T(2)-D domain. The decomposition is advantageous for better interpretation of the complex correlation maps as well as for the quantification of extracted T(2)-D components. To demonstrate the new method seventeen mixtures of wheat flour, starch, gluten, oil and water were prepared and measured with a 300 MHz nuclear magnetic resonance (NMR) spectrometer using a pulsed gradient stimulated echo (PGSTE) pulse sequence followed by a Carr-Purcell-Meiboom-Gill (CPMG) pulse echo train. By varying the gradient strength, 2D diffusion-relaxation data were recorded for each sample. From these double exponentially decaying relaxation data the PARAFAC algorithm extracted two unique diffusion-relaxation components, explaining 99.8% of the variation in the data set. These two components were subsequently transformed to the T(2)-D domain using 2D-inverse Laplace transformation and quantitatively assigned to the oil and water components of the samples. The oil component was one distinct distribution with peak intensity at D=3 x 10(-12) m(2) s(-1) and T(2)=180 ms. The water component consisted of two broad populations of water molecules with diffusion coefficients and relaxation times centered around correlation pairs: D=10(-9) m(2) s(-1), T(2)=10 ms and D=3 x 10(-13) m(2) s(-1), T(2)=13 ms. Small spurious peaks observed in the inverse Laplace transformation of original complex data were effectively filtered by the PARAFAC decomposition and thus considered artefacts from the complex Laplace transformation. The oil-to-water ratio determined by PARAFAC followed by 2D-Laplace inversion was perfectly correlated with known oil-to-water ratio of the samples. The new method of using PARAFAC prior to the 2D-Laplace inversion proved to have superior potential in analysis of diffusion-relaxation spectra, as it
Rowley-Neale, Samuel J; Fearn, Jamie M; Brownson, Dale A C; Smith, Graham C; Ji, Xiaobo; Banks, Craig E
2016-08-21
Two-dimensional molybdenum disulphide nanosheets (2D-MoS2) have proven to be an effective electrocatalyst, with particular attention being focused on their use towards increasing the efficiency of the reactions associated with hydrogen fuel cells. Whilst the majority of research has focused on the Hydrogen Evolution Reaction (HER), herein we explore the use of 2D-MoS2 as a potential electrocatalyst for the much less researched Oxygen Reduction Reaction (ORR). We stray from literature conventions and perform experiments in 0.1 M H2SO4 acidic electrolyte for the first time, evaluating the electrochemical performance of the ORR with 2D-MoS2 electrically wired/immobilised upon several carbon based electrodes (namely; Boron Doped Diamond (BDD), Edge Plane Pyrolytic Graphite (EPPG), Glassy Carbon (GC) and Screen-Printed Electrodes (SPE)) whilst exploring a range of 2D-MoS2 coverages/masses. Consequently, the findings of this study are highly applicable to real world fuel cell applications. We show that significant improvements in ORR activity can be achieved through the careful selection of the underlying/supporting carbon materials that electrically wire the 2D-MoS2 and utilisation of an optimal mass of 2D-MoS2. The ORR onset is observed to be reduced to ca. +0.10 V for EPPG, GC and SPEs at 2D-MoS2 (1524 ng cm(-2) modification), which is far closer to Pt at +0.46 V compared to bare/unmodified EPPG, GC and SPE counterparts. This report is the first to demonstrate such beneficial electrochemical responses in acidic conditions using a 2D-MoS2 based electrocatalyst material on a carbon-based substrate (SPEs in this case). Investigation of the beneficial reaction mechanism reveals the ORR to occur via a 4 electron process in specific conditions; elsewhere a 2 electron process is observed. This work offers valuable insights for those wishing to design, fabricate and/or electrochemically test 2D-nanosheet materials towards the ORR.
NASA Astrophysics Data System (ADS)
Tønning, Erik; Polders, Daniel; Callaghan, Paul T.; Engelsen, Søren B.
2007-09-01
This paper demonstrates how the multi-linear PARAFAC model can with advantage be used to decompose 2D diffusion-relaxation correlation NMR spectra prior to 2D-Laplace inversion to the T2- D domain. The decomposition is advantageous for better interpretation of the complex correlation maps as well as for the quantification of extracted T2- D components. To demonstrate the new method seventeen mixtures of wheat flour, starch, gluten, oil and water were prepared and measured with a 300 MHz nuclear magnetic resonance (NMR) spectrometer using a pulsed gradient stimulated echo (PGSTE) pulse sequence followed by a Carr-Purcell-Meiboom-Gill (CPMG) pulse echo train. By varying the gradient strength, 2D diffusion-relaxation data were recorded for each sample. From these double exponentially decaying relaxation data the PARAFAC algorithm extracted two unique diffusion-relaxation components, explaining 99.8% of the variation in the data set. These two components were subsequently transformed to the T2- D domain using 2D-inverse Laplace transformation and quantitatively assigned to the oil and water components of the samples. The oil component was one distinct distribution with peak intensity at D = 3 × 10 -12 m 2 s -1 and T2 = 180 ms. The water component consisted of two broad populations of water molecules with diffusion coefficients and relaxation times centered around correlation pairs: D = 10 -9 m 2 s -1, T2 = 10 ms and D = 3 × 10 -13 m 2 s -1, T2 = 13 ms. Small spurious peaks observed in the inverse Laplace transformation of original complex data were effectively filtered by the PARAFAC decomposition and thus considered artefacts from the complex Laplace transformation. The oil-to-water ratio determined by PARAFAC followed by 2D-Laplace inversion was perfectly correlated with known oil-to-water ratio of the samples. The new method of using PARAFAC prior to the 2D-Laplace inversion proved to have superior potential in analysis of diffusion-relaxation spectra, as it
Labat, D; Ababou, R; Mangin, A
2001-01-01
Karstic systems are highly heterogeneous geological formations characterized by a multiscale temporal and spatial hydrologic behavior with more or less localized temporal and spatial structures. Classical correlation and spectral analyses cannot take into account these properties. Therefore, it is proposed to introduce a new kind of transformation: the wavelet transform. Here we focus particularly on the use of wavelets to study temporal behavior of local precipitation and watershed runoffs from a part of the karstic system. In the first part of the paper, a brief mathematical overview of the continuous Morlet wavelet transform and of the multiresolution analysis is presented. An analogy with spectral analyses allows the introduction of concepts such as wavelet spectrum and cross-spectrum. In the second part, classical methods (spectral and correlation analyses) and wavelet transforms are applied and compared for daily rainfall rates and runoffs measured on a French karstic watershed (Pyrénées) over a period of 30 years. Different characteristic time scales of the rainfall and runoff processes are determined. These time scales are typically on the order of a few days for floods, but they also include significant half-year and one-year components and multi-annual components. The multiresolution cross-analysis also provides a new interpretation of the impulse response of the system. To conclude, wavelet transforms provide a valuable amount of information, which may be now taken into account in both temporal and spatially distributed karst modeling of precipitation and runoff. PMID:11447860
Wavelet based image visibility enhancement of IR images
NASA Astrophysics Data System (ADS)
Jiang, Qin; Owechko, Yuri; Blanton, Brendan
2016-05-01
Enhancing the visibility of infrared images obtained in a degraded visibility environment is very important for many applications such as surveillance, visual navigation in bad weather, and helicopter landing in brownout conditions. In this paper, we present an IR image visibility enhancement system based on adaptively modifying the wavelet coefficients of the images. In our proposed system, input images are first filtered by a histogram-based dynamic range filter in order to remove sensor noise and convert the input images into 8-bit dynamic range for efficient processing and display. By utilizing a wavelet transformation, we modify the image intensity distribution and enhance image edges simultaneously. In the wavelet domain, low frequency wavelet coefficients contain original image intensity distribution while high frequency wavelet coefficients contain edge information for the original images. To modify the image intensity distribution, an adaptive histogram equalization technique is applied to the low frequency wavelet coefficients while to enhance image edges, an adaptive edge enhancement technique is applied to the high frequency wavelet coefficients. An inverse wavelet transformation is applied to the modified wavelet coefficients to obtain intensity images with enhanced visibility. Finally, a Gaussian filter is used to remove blocking artifacts introduced by the adaptive techniques. Since wavelet transformation uses down-sampling to obtain low frequency wavelet coefficients, histogram equalization of low-frequency coefficients is computationally more efficient than histogram equalization of the original images. We tested the proposed system with degraded IR images obtained from a helicopter landing in brownout conditions. Our experimental results show that the proposed system is effective for enhancing the visibility of degraded IR images.
NASA Astrophysics Data System (ADS)
Saadatinejad, M. R.; Hassani, H.
2013-04-01
The Persian Gulf and its surrounding area are some of the biggest basins and have a very important role in producing huge amounts of hydrocarbon, and this potential was evaluated in order to explore the target for geoscientists and petroleum engineers. Wavelet transform is a useful and applicable technique to reveal frequency contents of various signals in different branches of science and especially in petroleum studies. We applied two major capacities of continuous mode of wavelet transform in seismic investigations. These investigations were operated to detect reservoir geological structures and some anomalies related to hydrocarbon to develop and explore new petroleum reservoirs in at least 4 oilfields in the southwest of Iran. It had been observed that continuous wavelet transform results show some discontinuities in the location of faults and are able to display them more clearly than other seismic methods. Moreover, continuous wavelet transform, utilizing Morlet wavelet, displays low-frequency shadows on 4 different iso-frequency vertical sections to identify reservoirs containing gas. By comparing these different figures, the presence of low-frequency shadows under the reservoir could be seen and we can relate these variations from anomalies at different frequencies as an indicator of the presence of hydrocarbons in the target reservoir.
Advances in fast 2D camera data handling and analysis on NSTX
Davis, W. M.; Patel, R. I.; Boeglin, W. U.; Roquemore, A. L.; Maqueda, R. J.; Zweben, S. J.
2010-07-01
The use of fast 2D cameras on NSTX continues to grow. There are 6 cameras with the capability of taking up to 1–2 gigabytes (GBs) of data apiece during each plasma shot on the National Spherical Torus Experiment (NSTX). Efficient storage and retrieval of this data remains a challenge. Performance comparisons are presented for reading data stored in MDSplus, using both compressed data and segmented records, and direct access I/O with different read sizes. Encouragingly, fast 2D camera data provides considerable insight into plasma complexities, such as small-scale turbulence and particle transport. The last part of this paper is an example of more recent uses: dual cameras looking at the same region of the plasma from different angles, which can provide trajectories of incandescent particles in 3D. A laboratory simulation of the 3D trajectories is presented, as well as corresponding data from NSTX plasma where glowing dust particles can be followed.
Automatic 2D-to-3D image conversion using 3D examples from the internet
NASA Astrophysics Data System (ADS)
Konrad, J.; Brown, G.; Wang, M.; Ishwar, P.; Wu, C.; Mukherjee, D.
2012-03-01
repository. While far from perfect, the presented results demonstrate that on-line repositories of 3D content can be used for effective 2D-to-3D image conversion. With the continuously increasing amount of 3D data on-line and with the rapidly growing computing power in the cloud, the proposed framework seems a promising alternative to operator-assisted 2D-to-3D conversion.
Two-dimensional integer wavelet transform with reduced influence of rounding operations
NASA Astrophysics Data System (ADS)
Strutz, Tilo; Rennert, Ines
2012-12-01
If a system for lossless compression of images applies a decorrelation step, this step must map integer input values to integer output values. This can be achieved, for example, using the integer wavelet transform (IWT). The non-linearity, introduced by the obligatory rounding steps, is the main drawback of the IWT, since it deteriorates the desired filter characteristic. This paper discusses different methods for reducing the influence of rounding in 5/3 and 9/7 filter banks. A novel combination of two-dimensional implementations of the JPEG2000 9/7 filter bank with new filter coefficients is proposed and the effects of the methods on lossless image compression are investigated. In addition, these filter banks are compared to the 9/7 Deslauriers-Dubuc filter bank (97DD). The analysed two-dimensional implementations generally perform better than their one-dimensional counterparts in terms of compression ratio for natural images. On average, the 2D 97DD filter bank performs best. In addition, it has been found that the compression results cannot be improved by simply reducing the number of lifting steps via 2D implementations of the JPEG2000 9/7 filter bank. Only the 2D implementation with a minimum number of lifting steps, in combination with modified lifting coefficients, leads to fewer bits per pixel than the separable implementation on average for a selected set of images.
Discrepant Results in a 2-D Marble Collision
ERIC Educational Resources Information Center
Kalajian, Peter
2013-01-01
Video analysis of 2-D collisions is an excellent way to investigate conservation of linear momentum. The often-desired experimental design goal is to minimize the momentum loss in order to demonstrate the conservation law. An air table with colliding pucks is an ideal medium for this experiment, but such equipment is beyond the budget of many…
THz devices based on 2D electron systems
NASA Astrophysics Data System (ADS)
Xing, Huili Grace; Yan, Rusen; Song, Bo; Encomendero, Jimy; Jena, Debdeep
2015-05-01
In two-dimensional electron systems with mobility on the order of 1,000 - 10,000 cm2/Vs, the electron scattering time is about 1 ps. For the THz window of 0.3 - 3 THz, the THz photon energy is in the neighborhood of 1 meV, substantially smaller than the optical phonon energy of solids where these 2D electron systems resides. These properties make the 2D electron systems interesting as a platform to realize THz devices. In this paper, I will review 3 approaches investigated in the past few years in my group toward THz devices. The first approach is the conventional high electron mobility transistor based on GaN toward THz amplifiers. The second approach is to employ the tunable intraband absorption in 2D electron systems to realize THz modulators, where I will use graphene as a model material system. The third approach is to exploit plasma wave in these 2D electron systems that can be coupled with a negative differential conductance element for THz amplifiers/sources/detectors.
ELLIPT2D: A Flexible Finite Element Code Written Python
Pletzer, A.; Mollis, J.C.
2001-03-22
The use of the Python scripting language for scientific applications and in particular to solve partial differential equations is explored. It is shown that Python's rich data structure and object-oriented features can be exploited to write programs that are not only significantly more concise than their counter parts written in Fortran, C or C++, but are also numerically efficient. To illustrate this, a two-dimensional finite element code (ELLIPT2D) has been written. ELLIPT2D provides a flexible and easy-to-use framework for solving a large class of second-order elliptic problems. The program allows for structured or unstructured meshes. All functions defining the elliptic operator are user supplied and so are the boundary conditions, which can be of Dirichlet, Neumann or Robbins type. ELLIPT2D makes extensive use of dictionaries (hash tables) as a way to represent sparse matrices.Other key features of the Python language that have been widely used include: operator over loading, error handling, array slicing, and the Tkinter module for building graphical use interfaces. As an example of the utility of ELLIPT2D, a nonlinear solution of the Grad-Shafranov equation is computed using a Newton iterative scheme. A second application focuses on a solution of the toroidal Laplace equation coupled to a magnetohydrodynamic stability code, a problem arising in the context of magnetic fusion research.
Proteomic Profiling of Macrophages by 2D Electrophoresis
Bouvet, Marion; Turkieh, Annie; Acosta-Martin, Adelina E.; Chwastyniak, Maggy; Beseme, Olivia; Amouyel, Philippe; Pinet, Florence
2014-01-01
The goal of the two-dimensional (2D) electrophoresis protocol described here is to show how to analyse the phenotype of human cultured macrophages. The key role of macrophages has been shown in various pathological disorders such as inflammatory, immunological, and infectious diseases. In this protocol, we use primary cultures of human monocyte-derived macrophages that can be differentiated into the M1 (pro-inflammatory) or the M2 (anti-inflammatory) phenotype. This in vitro model is reliable for studying the biological activities of M1 and M2 macrophages and also for a proteomic approach. Proteomic techniques are useful for comparing the phenotype and behaviour of M1 and M2 macrophages during host pathogenicity. 2D gel electrophoresis is a powerful proteomic technique for mapping large numbers of proteins or polypeptides simultaneously. We describe the protocol of 2D electrophoresis using fluorescent dyes, named 2D Differential Gel Electrophoresis (DIGE). The M1 and M2 macrophages proteins are labelled with cyanine dyes before separation by isoelectric focusing, according to their isoelectric point in the first dimension, and their molecular mass, in the second dimension. Separated protein or polypeptidic spots are then used to detect differences in protein or polypeptide expression levels. The proteomic approaches described here allows the investigation of the macrophage protein changes associated with various disorders like host pathogenicity or microbial toxins. PMID:25408153
2D signature for detection and identification of drugs
NASA Astrophysics Data System (ADS)
Trofimov, Vyacheslav A.; Varentsova, Svetlana A.; Shen, Jingling; Zhang, Cunlin; Zhou, Qingli; Shi, Yulei
2011-06-01
The method of spectral dynamics analysis (SDA-method) is used for obtaining the2D THz signature of drugs. This signature is used for the detection and identification of drugs with similar Fourier spectra by transmitted THz signal. We discuss the efficiency of SDA method for the identification problem of pure methamphetamine (MA), methylenedioxyamphetamine (MDA), 3, 4-methylenedioxymethamphetamine (MDMA) and Ketamine.
2-D Imaging of Electron Temperature in Tokamak Plasmas
T. Munsat; E. Mazzucato; H. Park; C.W. Domier; M. Johnson; N.C. Luhmann Jr.; J. Wang; Z. Xia; I.G.J. Classen; A.J.H. Donne; M.J. van de Pol
2004-07-08
By taking advantage of recent developments in millimeter wave imaging technology, an Electron Cyclotron Emission Imaging (ECEI) instrument, capable of simultaneously measuring 128 channels of localized electron temperature over a 2-D map in the poloidal plane, has been developed for the TEXTOR tokamak. Data from the new instrument, detailing the MHD activity associated with a sawtooth crash, is presented.
On the sensitivity of the 2D electromagnetic invisibility cloak
NASA Astrophysics Data System (ADS)
Kaproulias, S.; Sigalas, M. M.
2012-10-01
A computational study of the sensitivity of the two dimensional (2D) electromagnetic invisibility cloaks is performed with the finite element method. A circular metallic object is covered with the cloak and the effects of absorption, gain and disorder are examined. Also the effect of covering the cloak with a thin dielectric layer is studied.
Rheological Properties of Quasi-2D Fluids in Microgravity
NASA Technical Reports Server (NTRS)
Stannarius, Ralf; Trittel, Torsten; Eremin, Alexey; Harth, Kirsten; Clark, Noel; Maclennan, Joseph; Glaser, Matthew; Park, Cheol; Hall, Nancy; Tin, Padetha
2015-01-01
In recent years, research on complex fluids and fluids in restricted geometries has attracted much attention in the scientific community. This can be attributed not only to the development of novel materials based on complex fluids but also to a variety of important physical phenomena which have barely been explored. One example is the behavior of membranes and thin fluid films, which can be described by two-dimensional (2D) rheology behavior that is quite different from 3D fluids. In this study, we have investigated the rheological properties of freely suspended films of a thermotropic liquid crystal in microgravity experiments. This model system mimics isotropic and anisotropic quasi 2D fluids [46]. We use inkjet printing technology to dispense small droplets (inclusions) onto the film surface. The motion of these inclusions provides information on the rheological properties of the films and allows the study of a variety of flow instabilities. Flat films have been investigated on a sub-orbital rocket flight and curved films (bubbles) have been studied in the ISS project OASIS. Microgravity is essential when the films are curved in order to avoid sedimentation. The experiments yield the mobility of the droplets in the films as well as the mutual mobility of pairs of particles. Experimental results will be presented for 2D-isotropic (smectic-A) and 2D-nematic (smectic-C) phases.
Second to fourth digit ratio (2D:4D) and concentrations of circulating sex hormones in adulthood
2011-01-01
Background The second to fourth digit ratio (2D:4D) is used as a marker of prenatal sex hormone exposure. The objective of this study was to examine whether circulating concentrations of sex hormones and SHBG measured in adulthood was associated with 2D:4D. Methods This analysis was based on a random sample from the Melbourne Collaborative Cohort Study. The sample consisted of of 1036 men and 620 post-menopausal women aged between 39 and 70 at the time of blood draw. Concentrations of circulating sex hormones were measured from plasma collected at baseline (1990-1994), while digit length was measured from hand photocopies taken during a recent follow-up (2003-2009). The outcome measures were circulating concentrations of testosterone, oestradiol, dehydroepiandrosterone sulphate, androstenedione, Sex Hormone Binding Globulin, androstenediol glucoronide for men only and oestrone sulphate for women only. Free testosterone and oestradiol were estimated using standard formulae derived empirically. Predicted geometric mean hormone concentrations (for tertiles of 2D:4D) and conditional correlation coefficients (for continuous 2D:4D) were obtained using mixed effects linear regression models. Results No strong associations were observed between 2D:4D measures and circulating concentrations of hormones for men or women. For males, right 2D:4D was weakly inversely associated with circulating testosterone (predicted geometric mean testosterone was 15.9 and 15.0 nmol/L for the lowest and highest tertiles of male right 2D:4D respectively (P-trend = 0.04). There was a similar weak association between male right 2D:4D and the ratio of testosterone to oestradiol. These associations were not evident in analyses of continuous 2D:4D. Conclusions There were no strong associations between any adult circulating concentration of sex hormone or SHGB and 2D:4D. These results contribute to the growing body of evidence indicating that 2D:4D is unrelated to adult sex hormone concentrations
On the Use of Adaptive Wavelet-based Methods for Ocean Modeling and Data Assimilation Problems
NASA Astrophysics Data System (ADS)
Vasilyev, Oleg V.; Yousuff Hussaini, M.; Souopgui, Innocent
2014-05-01
Latest advancements in parallel wavelet-based numerical methodologies for the solution of partial differential equations, combined with the unique properties of wavelet analysis to unambiguously identify and isolate localized dynamically dominant flow structures, make it feasible to start developing integrated approaches for ocean modeling and data assimilation problems that take advantage of temporally and spatially varying meshes. In this talk the Parallel Adaptive Wavelet Collocation Method with spatially and temporarily varying thresholding is presented and the feasibility/potential advantages of its use for ocean modeling are discussed. The second half of the talk focuses on the recently developed Simultaneous Space-time Adaptive approach that addresses one of the main challenges of variational data assimilation, namely the requirement to have a forward solution available when solving the adjoint problem. The issue is addressed by concurrently solving forward and adjoint problems in the entire space-time domain on a near optimal adaptive computational mesh that automatically adapts to spatio-temporal structures of the solution. The compressed space-time form of the solution eliminates the need to save or recompute forward solution for every time slice, as it is typically done in traditional time marching variational data assimilation approaches. The simultaneous spacio-temporal discretization of both the forward and the adjoint problems makes it possible to solve both of them concurrently on the same space-time adaptive computational mesh reducing the amount of saved data to the strict minimum for a given a priori controlled accuracy of the solution. The simultaneous space-time adaptive approach of variational data assimilation is demonstrated for the advection diffusion problem in 1D-t and 2D-t dimensions.
NASA Astrophysics Data System (ADS)
Rowley-Neale, Samuel J.; Fearn, Jamie M.; Brownson, Dale A. C.; Smith, Graham C.; Ji, Xiaobo; Banks, Craig E.
2016-08-01
Two-dimensional molybdenum disulphide nanosheets (2D-MoS2) have proven to be an effective electrocatalyst, with particular attention being focused on their use towards increasing the efficiency of the reactions associated with hydrogen fuel cells. Whilst the majority of research has focused on the Hydrogen Evolution Reaction (HER), herein we explore the use of 2D-MoS2 as a potential electrocatalyst for the much less researched Oxygen Reduction Reaction (ORR). We stray from literature conventions and perform experiments in 0.1 M H2SO4 acidic electrolyte for the first time, evaluating the electrochemical performance of the ORR with 2D-MoS2 electrically wired/immobilised upon several carbon based electrodes (namely; Boron Doped Diamond (BDD), Edge Plane Pyrolytic Graphite (EPPG), Glassy Carbon (GC) and Screen-Printed Electrodes (SPE)) whilst exploring a range of 2D-MoS2 coverages/masses. Consequently, the findings of this study are highly applicable to real world fuel cell applications. We show that significant improvements in ORR activity can be achieved through the careful selection of the underlying/supporting carbon materials that electrically wire the 2D-MoS2 and utilisation of an optimal mass of 2D-MoS2. The ORR onset is observed to be reduced to ca. +0.10 V for EPPG, GC and SPEs at 2D-MoS2 (1524 ng cm-2 modification), which is far closer to Pt at +0.46 V compared to bare/unmodified EPPG, GC and SPE counterparts. This report is the first to demonstrate such beneficial electrochemical responses in acidic conditions using a 2D-MoS2 based electrocatalyst material on a carbon-based substrate (SPEs in this case). Investigation of the beneficial reaction mechanism reveals the ORR to occur via a 4 electron process in specific conditions; elsewhere a 2 electron process is observed. This work offers valuable insights for those wishing to design, fabricate and/or electrochemically test 2D-nanosheet materials towards the ORR.Two-dimensional molybdenum disulphide nanosheets
The NH2D hyperfine structure revealed by astrophysical observations
NASA Astrophysics Data System (ADS)
Daniel, F.; Coudert, L. H.; Punanova, A.; Harju, J.; Faure, A.; Roueff, E.; Sipilä, O.; Caselli, P.; Güsten, R.; Pon, A.; Pineda, J. E.
2016-02-01
Context. The 111-101 lines of ortho- and para-NH2D (o/p-NH2D) at 86 and 110 GHz, respectively, are commonly observed to provide constraints on the deuterium fractionation in the interstellar medium. In cold regions, the hyperfine structure that is due to the nitrogen (14N) nucleus is resolved. To date, this splitting is the only one that is taken into account in the NH2D column density estimates. Aims: We investigate how including the hyperfine splitting caused by the deuterium (D) nucleus affects the analysis of the rotational lines of NH2D. Methods: We present 30 m IRAM observations of the above mentioned lines and APEX o/p-NH2D observations of the 101-000 lines at 333 GHz. The hyperfine patterns of the observed lines were calculated taking into account the splitting induced by the D nucleus. The analysis then relies on line lists that either neglect or include the splitting induced by the D nucleus. Results: The hyperfine spectra are first analyzed with a line list that only includes the hyperfine splitting that is due to the 14N nucleus. We find inconsistencies between the line widths of the 101-000 and 111-101 lines, the latter being larger by a factor of ~1.6 ± 0.3. Such a large difference is unexpected because the two sets of lines probably originate from the same region. We next employed a newly computed line list for the o/p-NH2D transitions where the hyperfine structure induced by both nitrogen and deuterium nuclei was included. With this new line list, the analysis of the previous spectra leads to compatible line widths. Conclusions: Neglecting the hyperfine structure caused by D leads to overestimating the line widths of the o/p-NH2D lines at 3 mm. The error for a cold molecular core is about 50%. This error propagates directly to the column density estimate. We therefore recommend to take the hyperfine splittings caused by both the 14N and D nuclei into account in any analysis that relies on these lines. Based on observations carried out with the IRAM
Schrödinger like equation for wavelets
NASA Astrophysics Data System (ADS)
Zúñiga-Segundo, A.; Moya-Cessa, H. M.; Soto-Eguibar, F.
2016-01-01
An explicit phase space representation of the wave function is build based on a wavelet transformation. The wavelet transformation allows us to understand the relationship between s - ordered Wigner function, (or Wigner function when s = 0), and the Torres-Vega-Frederick's wave functions. This relationship is necessary to find a general solution of the Schrödinger equation in phase-space.
Wavelet based feature extraction and visualization in hyperspectral tissue characterization
Denstedt, Martin; Bjorgan, Asgeir; Milanič, Matija; Randeberg, Lise Lyngsnes
2014-01-01
Hyperspectral images of tissue contain extensive and complex information relevant for clinical applications. In this work, wavelet decomposition is explored for feature extraction from such data. Wavelet methods are simple and computationally effective, and can be implemented in real-time. The aim of this study was to correlate results from wavelet decomposition in the spectral domain with physical parameters (tissue oxygenation, blood and melanin content). Wavelet decomposition was tested on Monte Carlo simulations, measurements of a tissue phantom and hyperspectral data from a human volunteer during an occlusion experiment. Reflectance spectra were decomposed, and the coefficients were correlated to tissue parameters. This approach was used to identify wavelet components that can be utilized to map levels of blood, melanin and oxygen saturation. The results show a significant correlation (p <0.02) between the chosen tissue parameters and the selected wavelet components. The tissue parameters could be mapped using a subset of the calculated components due to redundancy in spectral information. Vessel structures are well visualized. Wavelet analysis appears as a promising tool for extraction of spectral features in skin. Future studies will aim at developing quantitative mapping of optical properties based on wavelet decomposition. PMID:25574437
Half-metallicity in 2D organometallic honeycomb frameworks
NASA Astrophysics Data System (ADS)
Sun, Hao; Li, Bin; Zhao, Jin
2016-10-01
Half-metallic materials with a high Curie temperature (T C) have many potential applications in spintronics. Magnetic metal free two-dimensional (2D) half-metallic materials with a honeycomb structure contain graphene-like Dirac bands with π orbitals and show excellent aspects in transport properties. In this article, by investigating a series of 2D organometallic frameworks with a honeycomb structure using first principles calculations, we study the origin of forming half-metallicity in this kind of 2D organometallic framework. Our analysis shows that charge transfer and covalent bonding are two crucial factors in the formation of half-metallicity in organometallic frameworks. (i) Sufficient charge transfer from metal atoms to the molecules is essential to form the magnetic centers. (ii) These magnetic centers need to be connected through covalent bonding, which guarantee the strong ferromagnetic (FM) coupling. As examples, the organometallic frameworks composed by (1,3,5)-benzenetricarbonitrile (TCB) molecules with noble metals (Au, Ag, Cu) show half-metallic properties with T C as high as 325 K. In these organometallic frameworks, the strong electronegative cyano-groups (CN groups) drive the charge transfer from metal atoms to the TCB molecules, forming the local magnetic centers. These magnetic centers experience strong FM coupling through the d-p covalent bonding. We propose that most of the 2D organometallic frameworks composed by molecule—CN—noble metal honeycomb structures contain similar half metallicity. This is verified by replacing TCB molecules with other organic molecules. Although the TCB-noble metal organometallic framework has not yet been synthesized, we believe the development of synthesizing techniques and facility will enable the realization of them. Our study provides new insight into the 2D half-metallic material design for the potential applications in nanotechnology.
Half-metallicity in 2D organometallic honeycomb frameworks.
Sun, Hao; Li, Bin; Zhao, Jin
2016-10-26
Half-metallic materials with a high Curie temperature (T C) have many potential applications in spintronics. Magnetic metal free two-dimensional (2D) half-metallic materials with a honeycomb structure contain graphene-like Dirac bands with π orbitals and show excellent aspects in transport properties. In this article, by investigating a series of 2D organometallic frameworks with a honeycomb structure using first principles calculations, we study the origin of forming half-metallicity in this kind of 2D organometallic framework. Our analysis shows that charge transfer and covalent bonding are two crucial factors in the formation of half-metallicity in organometallic frameworks. (i) Sufficient charge transfer from metal atoms to the molecules is essential to form the magnetic centers. (ii) These magnetic centers need to be connected through covalent bonding, which guarantee the strong ferromagnetic (FM) coupling. As examples, the organometallic frameworks composed by (1,3,5)-benzenetricarbonitrile (TCB) molecules with noble metals (Au, Ag, Cu) show half-metallic properties with T C as high as 325 K. In these organometallic frameworks, the strong electronegative cyano-groups (CN groups) drive the charge transfer from metal atoms to the TCB molecules, forming the local magnetic centers. These magnetic centers experience strong FM coupling through the d-p covalent bonding. We propose that most of the 2D organometallic frameworks composed by molecule-CN-noble metal honeycomb structures contain similar half metallicity. This is verified by replacing TCB molecules with other organic molecules. Although the TCB-noble metal organometallic framework has not yet been synthesized, we believe the development of synthesizing techniques and facility will enable the realization of them. Our study provides new insight into the 2D half-metallic material design for the potential applications in nanotechnology.
Half-metallicity in 2D organometallic honeycomb frameworks.
Sun, Hao; Li, Bin; Zhao, Jin
2016-10-26
Half-metallic materials with a high Curie temperature (T C) have many potential applications in spintronics. Magnetic metal free two-dimensional (2D) half-metallic materials with a honeycomb structure contain graphene-like Dirac bands with π orbitals and show excellent aspects in transport properties. In this article, by investigating a series of 2D organometallic frameworks with a honeycomb structure using first principles calculations, we study the origin of forming half-metallicity in this kind of 2D organometallic framework. Our analysis shows that charge transfer and covalent bonding are two crucial factors in the formation of half-metallicity in organometallic frameworks. (i) Sufficient charge transfer from metal atoms to the molecules is essential to form the magnetic centers. (ii) These magnetic centers need to be connected through covalent bonding, which guarantee the strong ferromagnetic (FM) coupling. As examples, the organometallic frameworks composed by (1,3,5)-benzenetricarbonitrile (TCB) molecules with noble metals (Au, Ag, Cu) show half-metallic properties with T C as high as 325 K. In these organometallic frameworks, the strong electronegative cyano-groups (CN groups) drive the charge transfer from metal atoms to the TCB molecules, forming the local magnetic centers. These magnetic centers experience strong FM coupling through the d-p covalent bonding. We propose that most of the 2D organometallic frameworks composed by molecule-CN-noble metal honeycomb structures contain similar half metallicity. This is verified by replacing TCB molecules with other organic molecules. Although the TCB-noble metal organometallic framework has not yet been synthesized, we believe the development of synthesizing techniques and facility will enable the realization of them. Our study provides new insight into the 2D half-metallic material design for the potential applications in nanotechnology. PMID:27541575
Wavelet Analysis of Satellite Images for Coastal Watch
NASA Technical Reports Server (NTRS)
Liu, Antony K.; Peng, Chich Y.; Chang, Steve Y.-S.
1997-01-01
The two-dimensional wavelet transform is a very efficient bandpass filter, which can be used to separate various scales of processes and show their relative phase/location. In this paper, algorithms and techniques for automated detection and tracking of mesoscale features from satellite imagery employing wavelet analysis are developed. The wavelet transform has been applied to satellite images, such as those from synthetic aperture radar (SAR), advanced very-high-resolution radiometer (AVHRR), and coastal zone color scanner (CZCS) for feature extraction. The evolution of mesoscale features such as oil slicks, fronts, eddies, and ship wakes can be tracked by the wavelet analysis using satellite data from repeating paths. Several examples of the wavelet analysis applied to various satellite Images demonstrate the feasibility of this technique for coastal monitoring.
Application of harmonic wavelet to filtering of rockbolt detecting signal
NASA Astrophysics Data System (ADS)
Zhao, Yucheng; Liu, Hongyan; Wang, Jiyan; Miao, Xiexing
2008-11-01
Harmonic wavelet had explicit functional expression, flexible time-frequency division, simple transforming algorithm and a finer frequency refinement function than the others wavelet. In this paper based on frequency distributing characteristic of nondestructive testing signal from rockbolt supporting system, the discrete harmonic wavelet transforming theory was used to get rid of the lower and higher frequency signal from the initial signal. Meanwhile, the reconstruction algorithm of harmonic wavelet was brought forward to gain the signal without the unnecessary bandwidth signals. Finally, a numerical signal and real signal which can demonstrate superiority of harmonic wavelet in filtering are presented, and the transforming result shows that it would make the system run more precise and stably in the detecting to the quality of rockbolt supporting system.
A multiresolution wavelet representation in two or more dimensions
NASA Technical Reports Server (NTRS)
Bromley, B. C.
1992-01-01
In the multiresolution approximation, a signal is examined on a hierarchy of resolution scales by projection onto sets of smoothing functions. Wavelets are used to carry the detail information connecting adjacent sets in the resolution hierarchy. An algorithm has been implemented to perform a multiresolution decomposition in n greater than or equal to 2 dimensions based on wavelets generated from products of 1-D wavelets and smoothing functions. The functions are chosen so that an n-D wavelet may be associated with a single resolution scale and orientation. The algorithm enables complete reconstruction of a high resolution signal from decomposition coefficients. The signal may be oversampled to accommodate non-orthogonal wavelet systems, or to provide approximate translational invariance in the decomposition arrays.
A New Adaptive Mother Wavelet for Electromagnetic Transient Analysis
NASA Astrophysics Data System (ADS)
Guillén, Daniel; Idárraga-Ospina, Gina; Cortes, Camilo
2016-01-01
Wavelet Transform (WT) is a powerful technique of signal processing, its applications in power systems have been increasing to evaluate power system conditions, such as faults, switching transients, power quality issues, among others. Electromagnetic transients in power systems are due to changes in the network configuration, producing non-periodic signals, which have to be identified to avoid power outages in normal operation or transient conditions. In this paper a methodology to develop a new adaptive mother wavelet for electromagnetic transient analysis is proposed. Classification is carried out with an innovative technique based on adaptive wavelets, where filter bank coefficients will be adapted until a discriminant criterion is optimized. Then, its corresponding filter coefficients will be used to get the new mother wavelet, named wavelet ET, which allowed to identify and to distinguish the high frequency information produced by different electromagnetic transients.
A Multiscale Wavelet Solver with O( n) Complexity
NASA Astrophysics Data System (ADS)
Williams, John R.; Amaratunga, Kevin
1995-11-01
In this paper, we use the biorthogonal wavelets recently constructed by Dahlke and Weinreich to implement a highly efficient procedure for solving a certain class of one-dimensional problems, (∂21/∂x21)u = f,I ɛ Z, I > 0. For these problems, the discrete biorthogonal wavelet transform allows us to set up a system of wavelet-Galerkin equations in which the scales are uncoupled, so that a true multiscale solution procedure may be formulated. We prove that the resulting stiffness matrix is in fact an almost perfectly diagonal matrix (the original aim of the construction was to achieve a block diagonal structure) and we show that this leads to an algorithm whose cost is O(n). We also present numerical results which demonstrate that the multiscale biorthogonal wavelet algorithm is superior to the more conventional single scale orthogonal wavelet approach both in terms of speed and in terms of convergence.
An image fusion method based on biorthogonal wavelet
NASA Astrophysics Data System (ADS)
Li, Jianlin; Yu, Jiancheng; Sun, Shengli
2008-03-01
Image fusion could process and utilize the source images, with complementing different image information, to achieve the more objective and essential understanding of the identical object. Recently, image fusion has been extensively applied in many fields such as medical imaging, micro photographic imaging, remote sensing, and computer vision as well as robot. There are various methods have been proposed in the past years, such as pyramid decomposition and wavelet transform algorithm. As for wavelet transform algorithm, due to the virtue of its multi-resolution, wavelet transform has been applied in image processing successfully. Another advantage of wavelet transform is that it can be much more easily realized in hardware, because its data format is very simple, so it could save a lot of resources, besides, to some extent, it can solve the real-time problem of huge-data image fusion. However, as the orthogonal filter of wavelet transform doesn't have the characteristics of linear phase, the phase distortion will lead to the distortion of the image edge. To make up for this shortcoming, the biorthogonal wavelet is introduced here. So, a novel image fusion scheme based on biorthogonal wavelet decomposition is presented in this paper. As for the low-frequency and high-frequency wavelet decomposition coefficients, the local-area-energy-weighted-coefficient fusion rule is adopted and different thresholds of low-frequency and high-frequency are set. Based on biorthogonal wavelet transform and traditional pyramid decomposition algorithm, an MMW image and a visible image are fused in the experiment. Compared with the traditional pyramid decomposition, the fusion scheme based biorthogonal wavelet is more capable to retain and pick up image information, and make up the distortion of image edge. So, it has a wide application potential.