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Articoli di riviste sul tema "Signature inversion"

Autore: Grafiati
Pubblicato: 21 dicembre 2024
Ultima modifica: 5 luglio 2025

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1

Van Den Broeke, Matthew S. "Bioscatter Characteristics Related to Inversion Variability in Atlantic Basin Tropical Cyclones." Earth Interactions 26, no. 1 (2022): 28–38. http://dx.doi.org/10.1175/ei-d-21-0010.1.

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Abstract Tropical cyclones (TCs) routinely transport organisms at their centers of circulation. The TC center of circulation is also often marked by an inversion, and the height of the inversion base may change as the TC intensifies or weakens. In this study, a dataset of 49 dropsonde-measured inversions in 20 separate Atlantic Ocean TCs is compared with spatiotemporally collocated polarimetric radar measurements of bioscatter. Bioscatter signature maximum altitude is found to be a function of temperature lapse rate across the inversion base (r = 0.473), and higher inversion bases were generally associated with denser bioscatter signatures, especially when strong hurricanes (minimum pressure < 950 hPa) were considered (r = 0.601). Characteristics of the bioscatter signature had some skill in predicting TC inversion characteristics (adjusted r2 of 16%–40%), although predictability was increased when TC intensity was also included as a predictor (adjusted r2 of 40%–59%). These results indicate promise for using the bioscatter signature to monitor the TC inversion and represent an example of a situation in which the behavior of organisms in the airspace may be indicative of ongoing atmospheric processes. Significance Statement Tropical cyclone centers of circulation are often associated with an inversion, the base of which changes altitude with system strengthening and weakening. They may also contain a radar-observable bioscatter signature. In this study, we wanted to determine how the bioscatter signature relates to inversion characteristics for the benefit of meteorologists and biologists. Bioscatter signature characteristics were related to strength of the temperature and dewpoint lapse rates across the inversion base, and deeper/denser bioscatter signatures were typically associated with higher inversion bases. The findings suggest that trends in tropical cyclone inversion characteristics could be remotely monitored via the bioscatter signature. They also support prior speculation that some birds may seek the relatively laminar flow above an inversion base.
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2

Zhang, Jian Hong, Hua Chen, and Yi Xian Yang. "Efficient Blind Signature Scheme Based on Modified Generalized Bilinear Inversion." Key Engineering Materials 439-440 (June 2010): 1265–70. http://dx.doi.org/10.4028/www.scientific.net/kem.439-440.1265.

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As a special anonymous signature, the blindness of blind signatures makes it play an important role in electronic commerce. In this paper we first propose a novel blind signature scheme from bilinear pairings. Furthermore, we also give a formal proof of security for the proposed schemes in the random oracle model. And we show that the scheme satisfies the two properties of blind signature: blindness and unforgeability. As for efficiency of the scheme, the size of our blind signature is 320 bits, and no pairings operator are required in the blind signing phas and two pairing operators are needed I the verification phase.
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3

Vallée, Marc A., William A. Morris, Stéphane Perrouty, et al. "Geophysical inversion contributions to mineral exploration: lessons from the Footprints project." Canadian Journal of Earth Sciences 56, no. 5 (2019): 525–43. http://dx.doi.org/10.1139/cjes-2019-0009.

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Magnetic and gravity inversions are used to create 2D or 3D models of the magnetic susceptibility and density, respectively, using potential field data. Unconstrained inversions generate an output based on mathematical constraints imposed by the inversion algorithm. Constrained inversions integrate lithological, structural, and petrophysical information in the inversion process to produce more geologically meaningful results. This study analyses the validity of this assertion in the context of the NSERC-CMIC Mineral Exploration Footprints project. Unconstrained and constrained geophysical inversions were computed for three mining sites: a gold site (Canadian Malartic, Québec), a copper site (Highland Valley, British Columbia), and a uranium site (Millennium – McArthur River, Saskatchewan). After initially computing unconstrained inversions, constrained inversions were developed using physical property measurements, which directly link geophysics to geology, and lithological boundaries extracted from an interpreted geological model. While each derived geological model is consistent with the geophysical data, each site exhibited some magnetic complexity that confounded the inversion. The gold site includes regions with a strong magnetic signature that masks the more weakly magnetic zone, thereby hiding the magnetic signature associated with the ore body. Initial unconstrained inversions for the copper site yielded solutions with invalid depth extent. A consistency between the constrained model and the geological model is reached with iterative changes to the depth extent of the model. At the uranium site, the observed magnetic signal is weak, but the inversion provided some insights that could be interpreted in terms of an already known complexly folded geological model.
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Zhang, Jian Hong, Min Xu, and Xiu Na Su. "An Efficient and Provably Secure Proxy Signature Scheme." Advanced Materials Research 211-212 (February 2011): 876–80. http://dx.doi.org/10.4028/www.scientific.net/amr.211-212.876.

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As a concept of delegating signing rights for digital signatures, proxy signature is a well studied subject in cryptography. Proxy signature is an important delegation technique. It plays an important role in auto-office system. In this paper, we give a secure and efficient proxy signature scheme. The security of the scheme is base on the fixed inversion problem of bilinear map. It has the following advantages: simple construction, short size and low computation.
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5

Landrø, M., and R. Sollie. "Source signature determination by inversion." GEOPHYSICS 57, no. 12 (1992): 1633–40. http://dx.doi.org/10.1190/1.1443230.

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A new method for estimating the pressure wavefield generated by a marine air‐gun array is presented. It is assumed that data is acquired at a ministreamer located below the source array. Effective source signatures for each air gun are estimated by an inversion algorithm. The forward modeling scheme used in the inversion algorithm is based upon a physical modeling of the air bubble generated by each air gun. This means that typical inversion parameters are: gun depths, empirical damping coefficients, and reflection coefficient of the sea surface. Variations in streamer depth are also taken into account by the inversion scheme. The algorithm has been successfully tested on examples with unknown streamer positions, gun parameters, reflection coefficient of sea surface, and ministreamer data contaminated with white noise.
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6

Onishi, N., and N. Tajima. "An Interpretation of Signature Inversion." Progress of Theoretical Physics 80, no. 1 (1988): 130–37. http://dx.doi.org/10.1143/ptp.80.130.

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7

Zhou, S.-G., Y.-Z. Liu, Y.-J. Ma, and C.-X. Yang. "Low-spin signature inversion in." Journal of Physics G: Nuclear and Particle Physics 22, no. 3 (1996): 415–20. http://dx.doi.org/10.1088/0954-3899/22/3/014.

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8

Xu, F. R., W. Satuła, and R. Wyss. "Quadrupole pairing interaction and signature inversion." Nuclear Physics A 669, no. 1-2 (2000): 119–34. http://dx.doi.org/10.1016/s0375-9474(99)00817-9.

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9

Lyons, Terry J., and Weijun Xu. "Hyperbolic development and inversion of signature." Journal of Functional Analysis 272, no. 7 (2017): 2933–55. http://dx.doi.org/10.1016/j.jfa.2016.12.024.

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10

Aghamiry, H. S., F. W. Mamfoumbi-Ozoumet, A. Gholami, and S. Operto. "Efficient extended-search space full-waveform inversion with unknown source signatures." Geophysical Journal International 227, no. 1 (2021): 257–74. http://dx.doi.org/10.1093/gji/ggab202.

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SUMMARY Full waveform inversion (FWI) requires an accurate estimation of source signatures. Due to the coupling between the source signatures and the subsurface model, small errors in the former can translate into large errors in the latter. When direct methods are used to solve the forward problem, classical frequency-domain FWI efficiently processes multiple sources for source signature and wavefield estimations once a single lower–upper (LU) decomposition of the wave-equation operator has been performed. However, this efficient FWI formulation is based on the exact solution of the wave equation and hence is highly sensitive to the inaccuracy of the velocity model due to the cycle skipping pathology. Recent extended-space FWI variants tackle this sensitivity issue through a relaxation of the wave equation combined with data assimilation, allowing the wavefields to closely match the data from the first inversion iteration. Then, the subsurface parameters are updated by minimizing the wave-equation violations. When the wavefields and the source signatures are jointly estimated with this approach, the extended wave equation operator becomes source dependent, hence making direct methods and, to a lesser extent, block iterative methods ineffective. In this paper, we propose a simple method to bypass this issue and estimate source signatures efficiently during extended FWI. The proposed method replaces each source with a blended source during each data-assimilated wavefield reconstruction to make the extended wave equation operator source independent. Besides computational efficiency, the additional degrees of freedom introduced by spatially distributing the sources allows for a better signature estimation at the physical location when the velocity model is rough. We implement the source signature estimation with a variable projection method in the recently proposed iteratively refined wavefield reconstruction inversion (IR-WRI) method. Numerical tests on the Marmousi II and 2004 BP salt synthetic models confirm the efficiency and the robustness against velocity model errors of the new method compared to the case where source signatures are known.
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11

Lamani, Umakant, Pragya Das, and S. G. Wahid. "Study of signature inversion in 123,125I using Particle Rotor Model calculations." International Journal of Modern Physics E 30, no. 07 (2021): 2150062. http://dx.doi.org/10.1142/s0218301321500622.

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The phenomenon of signature inversion in positive parity yrast states of 123,125I nuclei has been studied using the Particle Rotor Model (PRM) calculations. The experimentally observed signature inversion is well reproduced from the PRM calculations. The change in the value of a triaxial parameter [Formula: see text] was observed after the inversion. The PRM calculations were also used to describe the reduced transition probabilities. The derived change in the value of “[Formula: see text]” (in Lund convention) after inversion is interpreted as the change in nuclear shape from near triaxial to tending towards noncollective oblate.
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12

Frazer, L. Neil, and Xinhua Sun. "New objective functions for waveform inversion." GEOPHYSICS 63, no. 1 (1998): 213–22. http://dx.doi.org/10.1190/1.1444315.

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Inversion is an organized search for parameter values that maximize or minimize an objective function, referred to here as a processor. This note derives three new seismic processors that require neither prior deconvolution nor knowledge of the source‐receiver wavelet. The most powerful of these is the fourwise processor, as it is applicable to data sets from multiple shots and receivers even when each shot has a different unknown signature and each receiver has a different unknown impulse response. Somewhat less powerful than the fourwise processor is the pairwise processor, which is applicable to a data set consisting of two or more traces with the same unknown wavelet but possibly different gains. When only one seismogram exists the partition processor can be used. The partition processor is also applicable when there is only one shot (receiver) and each receiver (shot) has a different signature. In fourwise and pairwise inversions the unknown wavelets may be arbitrarily long in time and need not be minimum phase. In partition inversion the wavelet is assumed to be shorter in time than the data trace itself but is not otherwise restricted. None of the methods requires assumptions about the Green’s function.
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13

Zhang, Y. H., F. R. Xu, J. J. He, et al. "Signature inversion phenomena in odd-odd 182Au." European Physical Journal A 14, no. 3 (2002): 271–74. http://dx.doi.org/10.1140/epja/i2002-10041-9.

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14

Mathur, Tripti, and Shankar N. Mukherjee. "Signature inversion and change in triaxiality inTm159andEr159." Physical Review C 49, no. 1 (1994): 142–48. http://dx.doi.org/10.1103/physrevc.49.142.

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15

Landulfo, E., D. F. Winchell, J. X. Saladin, et al. "High-spin states and signature inversion inBr78." Physical Review C 54, no. 2 (1996): 626–37. http://dx.doi.org/10.1103/physrevc.54.626.

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16

Ikeda, Akitsu, and Takafumi Shimano. "Shape fluctuation as responsible for signature inversion." Physical Review Letters 63, no. 2 (1989): 139–42. http://dx.doi.org/10.1103/physrevlett.63.139.

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17

Riedinger, L. "Signature inversion in odd-odd deformed nuclei." Progress in Particle and Nuclear Physics 38 (1997): 251–61. http://dx.doi.org/10.1016/s0146-6410(97)00035-5.

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18

Akitsu, Ikeda, and Åberg Sven. "Signature-inversion in particle-triaxial rotor system." Nuclear Physics A 480, no. 1 (1988): 85–103. http://dx.doi.org/10.1016/0375-9474(88)90386-7.

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19

Mannisenaho, Vilma, Aki Tsuruta, Leif Backman та ін. "Global Atmospheric δ13CH4 and CH4 Trends for 2000–2020 from the Atmospheric Transport Model TM5 Using CH4 from Carbon Tracker Europe–CH4 Inversions". Atmosphere 14, № 7 (2023): 1121. http://dx.doi.org/10.3390/atmos14071121.

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This study investigates atmospheric δ13CH4 trends, as produced by a global atmospheric transport model using CH4 inversions from CarbonTracker-Europe CH4 for 2000–2020, and compares them to observations. The CH4 inversions include the grouping of the emissions both by δ13CH4 isotopic signatures and process type to investigate the effect, and to estimate the CH4 magnitudes and model CH4 and δ13CH4 trends. In addition to inversion results, simulations of the global atmospheric transport model were performed with modified emissions. The estimated global CH4 trends for oil and gas were found to increase more than coal compared to the priors from 2000–2006 to 2007–2020. Estimated trends for coal emissions at 30∘ N–60∘ N are less than 50% of those from priors. Estimated global CH4 rice emissions trends are opposite to priors, with the largest contribution from the EQ to 60∘ N. The results of this study indicate that optimizing wetland emissions separately produces better agreement with the observed δ13CH4 trend than optimizing all biogenic emissions simultaneously. This study recommends optimizing separately biogenic emissions with similar isotopic signature to wetland emissions. In addition, this study suggests that fossil-based emissions were overestimated by 9% after 2012 and biogenic emissions are underestimated by 8% in the inversion using EDGAR v6.0 as priors.
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20

QI, B., S. Q. ZHANG, S. Y. WANG, and J. MENG. "SIGNATURE SPLITTING IN 173W WITH TRIAXIAL PARTICLE ROTOR MODEL." International Journal of Modern Physics E 18, no. 01 (2009): 109–22. http://dx.doi.org/10.1142/s0218301309012094.

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A particle rotor model with a quasi-neutron coupled with a triaxially deformed rotor is applied to study signature splitting for bands with intruder orbital ν7/2+[633] and nonintruder orbital ν5/2-[512] in 173 W . Excellent agreement with the observed energy spectra has been achieved for both bands. Signature splitting for band ν7/2+[633], and band ν5/2-[512] before the onset of signature inversion, is satisfactorily reproduced by introducing the γ degree of freedom. The phase and amplitude of signature splitting in band ν5/2-[512] are attributed to strong competition between 2f7/2 and 1h9/2 components. However, the self-consistent explanation of signature inversion in band ν5/2-[512] is beyond the present one quasi-neutron coupled with a triaxially deformed rotor.
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21

Xu, Kun, Stewart A. Greenhalgh, and MiaoYue Wang. "Comparison of source-independent methods of elastic waveform inversion." GEOPHYSICS 71, no. 6 (2006): R91—R100. http://dx.doi.org/10.1190/1.2356256.

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In this paper, we investigate several source-independent methods of nonlinear full-waveform inversion of multicomponent elastic-wave data. This includes iterative estimation of source signature (IES), standard trace normalization (STN), and average trace normalization (ATN) inversion methods. All are based on the finite-element method in the frequency domain. One synthetic elastic crosshole model is used to compare the recovered images with all these methods as well as the known source signature (KSS) inversion method. The numerical experiments show that the IES method is superior to both STN and ATN methods in two-component, elastic-wave inversion in the frequency domain when the source signature is unknown. The STN and ATN methods have limitations associated with near-zero amplitudes (or polarity reversals) in traces from one of the components, which destroy the energy balance in the normalized traces and cause a loss of frequency information. But the ATN method is somewhat superior to the STN method in suppressing random noise and improving stability, as the developed formulas and the numerical experiments show. We suggest the IES method as a practical procedure for multicomponent seismic inversion.
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22

Behura, Jyoti, and Roel Snieder. "Virtual Real Source: Source signature estimation using seismic interferometry." GEOPHYSICS 78, no. 5 (2013): Q57—Q68. http://dx.doi.org/10.1190/geo2013-0069.1.

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Knowledge of the seismic source signature is crucial in numerousproblems in exploration seismology, especially in full-waveform inversion. However, existing methods of source signature estimation like statistical methods and well-log-based methods suffer from several drawbacks arising from assumptions such as whiteness of the reflectivity series and the minimum-phase character of the wavelet. Also, estimation of the source signature using wave-theoretical methods requires the recording of the wavefield and its normal derivative or additional recordings above the receiver surface which are not always available. We introduce a method, called the Virtual Real Source, of extracting the source signature based on the theory of seismic interferometry, also known as the virtual source method. This method is independent of the assumptions and drawbacks of the above-mentioned methods. The only requirement for the method of Virtual Real Source is to have a virtual source location coincide with the physical shot position whose source signature is desired. The virtual source location does not necessarily have to be a zero-offset receiver because one can use interpolation for it. The source signature is extracted by deconvolving the real recording at a receiver from the virtual source recording. Through modeling examples, we show that Virtual Real Source produces accurate source signatures even for complicated subsurface structures and source signatures, and is robust in the presence of noise. Source signature of every shot in a survey can be extracted reliably as long as the source signatures have similar amplitude spectra. The phase spectrum of the source signature is always extracted accurately even if it varies randomly from one shot to another. The Virtual Real Source applied on a 2D streamer data set from the North Viking Graben in the North Sea extracts all the airgun signatures with the main pulse and the bubble oscillation.
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23

Landrø, Martin, Jan Langhammer, Roger Sollie, Losse Amundsen, and Eivind Berg. "Source signature determination from ministreamer data." GEOPHYSICS 59, no. 8 (1994): 1261–69. http://dx.doi.org/10.1190/1.1443683.

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Two methods for estimating the pressure wavefield generated by a marine airp‐gun array are tested. Data have been acquired at a ministreamer located below the source array. Effective source signatures for each air gun are estimated. In the first method a nonlinear inversion algorithm is used, where the forward modeling scheme is based upon a physical modeling of the air bubble generated by each air gun. In the second method a linear inversion method is used, with the assumption that the physics in the problem can be described by the acoustic wave equation with explosive point sources as the driving term. From the estimated effective source signatures, far‐field signatures have been calculated for both methods and compared with measured far‐field signatures. The error energy between the measured and estimated far‐field signatures was approximately 8 percent for both methods.
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24

Kundu, Tribikram. "Inversion of acoustic material signature of layered solids." Journal of the Acoustical Society of America 91, no. 2 (1992): 591–600. http://dx.doi.org/10.1121/1.402521.

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25

Chattopadhyay, S., H. C. Jain, J. A. Sheikh, Y. K. Agarwal, and M. L. Jhingan. "Rotational structure and signature inversion in odd-oddY84." Physical Review C 47, no. 1 (1993): R1—R4. http://dx.doi.org/10.1103/physrevc.47.r1.

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26

Moon, C. B., T. Komatsubara, Y. Sasaki, et al. "Signature inversion in the yrare band of 119Xe." European Physical Journal A 14, no. 1 (2002): 13–16. http://dx.doi.org/10.1140/epja/iepja1438.

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García-Bermúdez, G., M. A. Cardona, A. Filevich, R. V. Ribas, H. Somacal, and L. Szybisz. "Transition strengths and signature inversion in odd-odd74Br." Physical Review C 59, no. 4 (1999): 1999–2003. http://dx.doi.org/10.1103/physrevc.59.1999.

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Landrø, Martin. "Source signature determination by inversion of ministreamer data." Leading Edge 19, no. 1 (2000): 46–49. http://dx.doi.org/10.1190/1.1438452.

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Shen, Shuifa, Jiahui Gu, Shuanghui Shi, Jingyi Liu, Jianzhong Zhou, and Wenqing Shen. "Signature inversion caused by shape change in 84Rb." Physics Letters B 554, no. 3-4 (2003): 115–20. http://dx.doi.org/10.1016/s0370-2693(03)00002-9.

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Hara, K., and Y. Sun. "On the mechanism of backbending and signature inversion." Zeitschrift f�r Physik A Hadrons and Nuclei 339, no. 1 (1991): 15–21. http://dx.doi.org/10.1007/bf01282929.

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31

Zhu, Sheng-jiang, M. Sakhaee, J. H. Hamilton, et al. "Octupole Deformation and Signature Inversion in 145 Ba." Chinese Physics Letters 16, no. 10 (1999): 715–17. http://dx.doi.org/10.1088/0256-307x/16/10/005.

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Zhang, Y. H., T. Hayakawa, M. Oshima, et al. "Observation of signature inversion in odd-odd 178Ir." European Physical Journal A 8, no. 4 (2000): 439–42. http://dx.doi.org/10.1007/s100500070066.

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Matsuzaki, Masayuki. "Signature inversion in quasiparticle energy and B(M1)." Nuclear Physics A 504, no. 3 (1989): 456–66. http://dx.doi.org/10.1016/0375-9474(89)90552-6.

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Chen, Xuguang, Vishwa Parekh, Luke peng, et al. "RADT-14. COMPARISON OF MACHINE LEARNING ALGORITHMS IN DISTINGUISHING RADIATION NECROSIS FROM PROGRESSION OF BRAIN METASTASES TREATED WITH STEREOTACTIC RADIOSURGERY (SRS)." Neuro-Oncology 22, Supplement_2 (2020): ii184. http://dx.doi.org/10.1093/neuonc/noaa215.767.

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Abstract PURPOSE To test the effectiveness of machine learning algorithms in distinguishing radiation necrosis (RN) from tumor progression (TP) using MRI radiomic features. METHODS Brain metastases were treated with SRS to a median dose of 18Gy. Lesions that showed evidence of progression on follow-up MRI were sampled surgically, and diagnoses confirmed by histopathology. Cases from 2 institutions were combined and randomly assigned for training (70%) and testing (30%). T1 post-contrast (T1c) and T2 fluid attenuated inversion recovery (T2 FLAIR) MRI were used for radiomic feature extraction (50 features each). Three subsets of radiomic features were obtained and tested: Signature #1 included 10 previously published features that correlated with diagnosis on T test; signature #2 and #3 included 5 and 12 features obtained through recursive elimination using random forest (RF) and support vector machine (SVM), respectively. Supervised machine learning models were trained using RF, SVM (radial kernel) and regularized discriminant analysis (RDA) algorithms based on all three radiomics signatures. Receiver operator characteristics (ROC) were compared between signatures and algorithms. RESULTS A total of 135 individual lesions (37 RN and 98 TP) were included. Signature #3 demonstrated the highest area under the curve in the training set (average AUC=0.98, vs 0.95 and 0.92 for signature #1 and #2), as well as the testing set (average AUC=0.83, vs 0.74 and 0.79 for signature #1 and #2). RF and SVM demonstrated similar performance in both training (average AUC 0.99-1) and testing datasets (average AUC 0.79-0.80) among all three signatures. Both RF and SVM were superior to RDA in performance (average training AUC 0.83, testing AUC 0.77). The greatest sensitivity (83%) and specificity (100%) in the testing set were achieved using signature #3 and SVM. CONCLUSION RF and SVM are effective in distinguishing RN from TP in a multi-institution dataset using radiomic signatures.
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Svarva Helgebostad, Kristian, Martin Landrø, Vetle Vinje, and Carl-Inge Nilsen. "Estimating source signatures from source-over-spread marine seismic data." GEOPHYSICS 83, no. 6 (2018): P39—P48. http://dx.doi.org/10.1190/geo2017-0789.1.

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Recent developments in marine seismic acquisition include deploying a source vessel above a towed-streamer spread. We have developed an inversion algorithm to estimate source signatures for such acquisition configurations, by minimizing the difference between the recorded and a modeled direct wave. The forward modeling is based upon a physical modeling of the air bubble created by each air gun in the source array, and a damped Gauss-Newton approach is used for the optimization. Typical inversion parameters are empirical damping factors for the bubble oscillations and firing time delays for each air gun. Variations in streamer depth are taken into account, and a constant sea-surface reflection coefficient is also estimated as a by-product of the inversion. For data acquired in shallow waters, we have developed an extension of the forward modeling to include reflections from the water bottom to stabilize the inversion. The algorithm is tested on synthetic- and field-data examples, and the estimated source signature for the field-data example is used in a designature processing flow.
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KUMAR, VINOD, SURESH KUMAR, SUSHIL KUMAR, et al. "A SEMI-CLASSICAL APPROACH TO SIGNATURE SPLITTING AND SIGNATURE INVERSION IN ODD–ODD NUCLEI." International Journal of Modern Physics E 20, no. 06 (2011): 1455–63. http://dx.doi.org/10.1142/s0218301311018447.

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The signature inversion observed in rotational bands belonging to high-j configurations of odd–odd deformed nuclei has been analyzed within the framework of an axially symmetric rotor plus two-particle model. The Coriolis and n–p interaction are considered the main cause of energy staggering. However, γ-triaxial deformation and the numbers of valence protons, Np, and neutrons, Nn also contribute to the energy staggering between odd- and even-spin states.
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Borah, Ujjal K., and Prasanta K. Patro. "The interrelationship between electrical resistivity and VP/VS ratio: A novel approach to constrain the subsurface resistivity structure in data gap areas in a seismogenic zone." GEOPHYSICS 87, no. 1 (2021): B57—B67. http://dx.doi.org/10.1190/geo2021-0200.1.

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Large man-made water reservoirs promote fluid diffusion and cause critically stressed fault zones underneath to trigger earthquakes. Electrical resistivity is a crucial property to investigate such fluid-filled fault zones. Therefore, we carry out magnetotelluric (MT) investigation to explore an intraplate earthquake zone, which is related to artificial reservoir-triggered seismicity. However, due to surface access restrictions, our data set has a gap in coverage in the middle part of the study area. This data gap region coincides with the earthquake hypocenter distribution in that intraplate earthquake zone. Therefore, it is vital to fill the data gap to obtain the electrical signature of the active seismic zone. To compensate for the data gap, we have developed a relation that connects resistivity with the ratio of seismic P- to S-wave velocity ([Formula: see text]). Using this relation, we estimate a priori resistivity distribution in the data gap region from known [Formula: see text] values during the inversion to compensate for the data gap. A comparison study of the root-mean-square misfits of inversion outputs (with and without data gap filled) proves the effectiveness of the established relation. The inversion output obtained using the established relation brings out fault signatures in the data gap region. To examine the reliability and accuracy of these fault signatures, we occupy a portion of the data gap with new MT sites. We compare the inversion output from this new setup with the inversion output obtained from the established relation and observe that the electrical signatures in both outputs are spatially correlated. Furthermore, a synthetic test on a similar earth model establishes the credibility and robustness of the derived relation.
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38

Brier, Éric, Houda Ferradi, Marc Joye, and David Naccache. "New number-theoretic cryptographic primitives." Journal of Mathematical Cryptology 14, no. 1 (2020): 224–35. http://dx.doi.org/10.1515/jmc-2019-0035.

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AbstractThis paper introduces new prq-based one-way functions and companion signature schemes. The new signature schemes are interesting because they do not belong to the two common design blueprints, which are the inversion of a trapdoor permutation and the Fiat–Shamir transform. In the basic signature scheme, the signer generates multiple RSA-like moduli ni = pi2qi and keeps their factors secret. The signature is a bounded-size prime whose Jacobi symbols with respect to the ni’s match the message digest. The generalized signature schemes replace the Jacobi symbol with higher-power residue symbols. Given of their very unique design, the proposed signature schemes seem to be overlooked “missing species” in the corpus of known signature algorithms.
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39

Li, G. S., X. H. Zhou, Y. H. Zhang, et al. "Signature inversion in the 7/2−[503] band of185Pt." Journal of Physics G: Nuclear and Particle Physics 38, no. 9 (2011): 095105. http://dx.doi.org/10.1088/0954-3899/38/9/095105.

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40

Hu, Shi-Peng, Hai-Liang Ma, Xue-Peng Cao, et al. "Multiple triaxial bands and abnormal signature inversion in As3374." Physics Letters B 732 (May 2014): 59–64. http://dx.doi.org/10.1016/j.physletb.2014.03.014.

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41

Cardona, M. A., M. E. Debray, D. Hojman, et al. "Yrast bands and signature inversion in doubly odd162, 164Lu." Zeitschrift für Physik A Hadrons and Nuclei 354, no. 1 (1996): 5–6. http://dx.doi.org/10.1007/s002180050003.

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42

Han, Guang-bing, Shu-xian Wen, Xiao-guang Wu, et al. "High Spin States and Signature Inversion in 84 Rb." Chinese Physics Letters 16, no. 7 (1999): 487–89. http://dx.doi.org/10.1088/0256-307x/16/7/007.

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43

Li, Hao, Guo-Fa Li, Xiang-Hui Guo, Xi-Ping Sun, and Jian-Fu Wang. "Nonstationary inversion-based directional deconvolution of airgun array signature." Applied Geophysics 16, no. 1 (2019): 116–24. http://dx.doi.org/10.1007/s11770-019-0752-7.

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44

Alshehhi, Rasha, Chris S. Hanson, Laurent Gizon, and Shravan Hanasoge. "Supervised neural networks for helioseismic ring-diagram inversions." Astronomy & Astrophysics 622 (February 2019): A124. http://dx.doi.org/10.1051/0004-6361/201834237.

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Context. The inversion of ring fit parameters to obtain subsurface flow maps in ring-diagram analysis for eight years of SDO observations is computationally expensive, requiring ∼3200 CPU hours. Aims. In this paper we apply machine-learning techniques to the inversion step of the ring diagram pipeline in order to speed up the calculations. Specifically, we train a predictor for subsurface flows using the mode fit parameters and the previous inversion results to replace future inversion requirements. Methods. We utilize artificial neural networks (ANNs) as a supervised learning method for predicting the flows in 15° ring tiles. We discuss each step of the proposed method to determine the optimal approach. In order to demonstrate that the machine-learning results still contain the subtle signatures key to local helioseismic studies, we use the machine-learning results to study the recently discovered solar equatorial Rossby waves. Results. The ANN is computationally efficient, able to make future flow predictions of an entire Carrington rotation in a matter of seconds, which is much faster than the current ∼31 CPU hours. Initial training of the networks requires ∼3 CPU hours. The trained ANN can achieve a rms error equal to approximately half that reported for the velocity inversions, demonstrating the accuracy of the machine learning (and perhaps the overestimation of the original errors from the ring-diagram pipeline). We find the signature of equatorial Rossby waves in the machine-learning flows covering six years of data, demonstrating that small-amplitude signals are maintained. The recovery of Rossby waves in the machine-learning flow maps can be achieved with only one Carrington rotation (27.275 days) of training data. Conclusions. We show that machine learning can be applied to and perform more efficiently than the current ring-diagram inversion. The computation burden of the machine learning includes 3 CPU hours for initial training, then around 10−4 CPU hours for future predictions.
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45

Montahaei, Mansoure, and Saeid Ghanbarifar. "A comparison of regularized, sharp boundary and tear zone inversions along an MT profile in Sabalan geothermal field, Iran." E3S Web of Conferences 211 (2020): 02004. http://dx.doi.org/10.1051/e3sconf/202021102004.

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This paper investigates magnetotelluric (MT) data recorded along a profile in the Sabalan geothermal region, NW of Iran. To find the range of relevant models consistent with the data, this study employed the so-called regularized, tear zone, and sharp boundary inversions. This study could effectively derive three alternative classes of models. Although the models show stable common resistive and conductive features there are some inconsistent details. Unaltered surface rocks and porous Basalt exhibit a high resistive overburden underlain by relatively more conductive Paleozoic sediments. A common signature of hydrothermal systems appears, and resistivities increase beneath a highly conductive clay cap in deeper parts. An intriguing feature resolved in the smoothest inversion model is a second deep conductor of 30 Ωm resistivities at a depth of 3 km, extending close to the surface. It can be related to the hot, solidified volcanic intrusions, resemblingthe heat source in a geothermal system. This study applied the two other inversion approaches for further hypothesis tests. Although the tear zone inversion re-establish the deep conductor (with 38 Ωm resistivities at 3 km depth), it is absent in the sharp boundary inversion result. This study concludes that the second deep conductor has a limited structure resolution.
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46

He, Baowei, Shengdao Liu, and Jingwen Zong. "Comparative study on the applicability of regularization method in ship’s magnetic signature modeling based on monopole array." AIP Advances 12, no. 10 (2022): 105221. http://dx.doi.org/10.1063/5.0119856.

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In this paper, we first study the applicability and stability of the Tikhonov regularization method (TRM) and the truncated singular value decomposition method in ship’s magnetic signature inversion modeling. To further improve the noise immunity and robustness of the model, we apply an iterative regularization algorithm based on the conjugate gradient least squares (CGLS) method. Numerical simulation shows that the proposed algorithm is more applicable and can obtain better results of ship’s magnetic field extrapolation under different noise backgrounds. In the ship model experiment, the errors of the TRM and CGLS method for magnetic signature extrapolation are, respectively, 4.77% and 3.67%, showing that the proposed algorithm can improve the inversion effect of the ship model magnetic field.
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47

Morrison, Anthony E., Steven T. Siems, Michael J. Manton, and Alex Nazarov. "A Modeling Case Study of Mixed-Phase Clouds over the Southern Ocean and Tasmania." Monthly Weather Review 138, no. 3 (2010): 839–62. http://dx.doi.org/10.1175/2009mwr3011.1.

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Abstract The cloud structure associated with two frontal passages over the Southern Ocean and Tasmania is investigated. The first event, during August 2006, is characterized by large quantities of supercooled liquid water and little ice. The second case, during October 2007, is more mixed phase. The Weather Research and Forecasting model (WRFV2.2.1) is evaluated using remote sensed and in situ observations within the post frontal air mass. The Thompson microphysics module is used to describe in-cloud processes, where ice is initiated using the Cooper parameterization at temperatures lower than −8°C or at ice supersaturations greater than 8%. The evaluated cases are then used to numerically investigate the prevalence of supercooled and mixed-phase clouds over Tasmania and the ocean to the west. The simulations produce marine stratocumulus-like clouds with maximum heights of between 3 and 5 km. These are capped by weak temperature and strong moisture inversions. When the inversion is at temperatures warmer than −10°C, WRF produces widespread supercooled cloud fields with little glaciation. This is consistent with the limited in situ observations. When the inversion is at higher altitudes, allowing cooler cloud tops, glaciated (and to a lesser extent mixed phase) clouds are more common. The simulations are further explored to evaluate any orographic signature within the cloud structure over Tasmania. No consistent signature is found between the two cases.
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48

Wu, Xiaoping, Jürgen Kusche, and Felix W. Landerer. "A new unified approach to determine geocentre motion using space geodetic and GRACE gravity data." Geophysical Journal International 209, no. 3 (2017): 1398–402. http://dx.doi.org/10.1093/gji/ggx086.

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Abstract Geocentre motion between the centre-of-mass of the Earth system and the centre-of-figure of the solid Earth surface is a critical signature of degree-1 components of global surface mass transport process that includes sea level rise, ice mass imbalance and continental-scale hydrological change. To complement GRACE data for complete-spectrum mass transport monitoring, geocentre motion needs to be measured accurately. However, current methods of geodetic translational approach and global inversions of various combinations of geodetic deformation, simulated ocean bottom pressure and GRACE data contain substantial biases and systematic errors. Here, we demonstrate a new and more reliable unified approach to geocentre motion determination using a recently formed satellite laser ranging based geocentric displacement time-series of an expanded geodetic network of all four space geodetic techniques and GRACE gravity data. The unified approach exploits both translational and deformational signatures of the displacement data, while the addition of GRACE's near global coverage significantly reduces biases found in the translational approach and spectral aliasing errors in the inversion.
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49

Matsuzaki, Masayuki. "Signature inversion driven by wobbling motion in negative-gamma nuclei." Physical Review C 46, no. 4 (1992): 1548–51. http://dx.doi.org/10.1103/physrevc.46.1548.

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50

Timár, J., J. Simpson, E. S. Paul, et al. "High-spin structure of121Xe: Triaxiality, band termination and signature inversion." Physica Scripta T56 (January 1, 1995): 325–27. http://dx.doi.org/10.1088/0031-8949/1995/t56/060.

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