Distribution Of Apparent Velocities Research Articles

Shear-wave velocity profiling of Jizan city, southwestern Saudi Arabia, using controlled-source spectral analysis of surface-wave measurements

Shear-wave velocity profiles are the main site-specific data for site classification, which are commonly used for the purposes of seismic microzonation and hazard assessment. The controlled-source spectral analysis of surface wave (CSSASW) dispersion measurements have been successfully performed to characterize seismic sites up to 30-m depths. This study utilizes the CSSASW application in Jizan City to obtain shear-wave velocity profiling at 14 sites distributed throughout the city using an electromagnetic vibrator. The recorded Rayleigh wave phase velocity dispersion curves are transformed to calculate the apparent velocity distribution in depth. Shear-wave velocities, calculated using theoretical relationships, can then be utilized to obtain design parameters for the soil strata. Shear-wave velocity varies from 216.97 to 829.59 m/s through Jizan City indicating the remarkable change of the near-surface sediments. The hard soil profiles of soft rock that were revealed by Vs values in this terrain (sites No. 7, 8, and 13) can be attributed to the existence of a dense layer of salt rock. Construction in such areas is prohibited due to the high susceptibility of large settlements in foundations as a consequence of salt dissolution. In the Sabkha terrains, all soil profiles were related to Vs, defined as stiff soils that were then modified to a softer class owing to their high liquefaction potential. These results should be considered before establishing important and strategic projects in the city.

A Hybrid Deep Model Using Deep Learning and Dense Optical Flow Approaches for Human Activity Recognition

Human activity recognition is a challenging problem with many applications including visual surveillance, human-computer interactions, autonomous driving and entertainment. In this study, we propose a hybrid deep model to understand and interpret videos focusing on human activity recognition. The proposed architecture is constructed combining dense optical flow approach and auxiliary movement information in video datasets using deep learning methodologies. To the best of our knowledge, this is the first study based on a novel combination of 3D-convolutional neural networks (3D-CNNs) fed by optical flow and long short-term memory networks (LSTM) fed by auxiliary information over video frames for the purpose of human activity recognition. The contributions of this paper are sixfold. First, a 3D-CNN, also called multiple frames is employed to determine the motion vectors. With the same purpose, the 3D-CNN is secondly used for dense optical flow, which is the distribution of apparent velocities of movement in captured imagery data in video frames. Third, the LSTM is employed as auxiliary information in video to recognize hand-tracking and objects. Fourth, the support vector machine algorithm is utilized for the task of classification of videos. Fifth, a wide range of comparative experiments are conducted on two newly generated chess datasets, namely the magnetic wall chess board video dataset (MCDS), and standard chess board video dataset (CDS) to demonstrate the contributions of the proposed study. Finally, the experimental results reveal that the proposed hybrid deep model exhibits remarkable performance compared to the state-of-the-art studies.

A Simple Analysis of Type I Superluminous Supernova Peak Spectra: Composition, Expansion Velocities, and Dynamics

Abstract We present a simple and well defined prescription to compare absorption lines in supernova (SN) spectra with lists of transitions drawn from the National Institute of Standards and Technology database. The method is designed to be applicable to simple spectra where the photosphere can be mostly described by absorptions from single transitions with a single photospheric velocity. These conditions are plausible for SN spectra obtained shortly after explosion. Here we show that the method also works well for spectra of hydrogen-poor (Type I) superluminous supernovae (SLSNe-I) around peak. Analysis of high signal to noise spectra leads to clear identification of numerous spectroscopic features arising from ions of carbon and oxygen, which account for the majority of absorption features detected in the optical range, suggesting the outer envelope of SLSN-I progenitors is dominated by these elements. We find that the prominent absorption features seen in the blue are dominated by numerous lines of O ii, as previously suggested, and that the apparent absorption feature widths are dominated by line density and not by Doppler broadening. In fact, we find that while the expansion velocities of SLSNe-I around peak are similar to those of normal SNe, the apparent velocity distribution (manifested as the width of single transition features) is much lower (∼1500 km s−1) indicating emission from a very narrow photosphere in velocity space that is nevertheless expanding rapidly. We inspect the controversial case of ASASSN-15lh, and find that the early spectrum of this object is not consistent with those of SLSNe-I. We also show that SLSNe that initially lack hydrogen features but develop these at late phases, such as iPTF15esb and iPTF16bad, also differ in their early spectra from standard SLSNe-I.

Visual Speech Recognition Using Optical Flow and Hidden Markov Model

The present work proposes audio-visual speech recognition with the use of Gammatone frequency cepstral coefficient (GFCC) and optical flow (OF) features with Hindi speech database. The OF refers to the distribution of apparent velocities of brightness pattern movements in an image. In this technique, OF is determined without extracting the location and contours of pair of lips of individual speaker. The visual features as horizontal component and vertical components of flow velocities have been calculated. Furthermore, the visual features are combined with audio features using early integration method followed by classification using hidden Markov model. The isolated Hindi digits were evaluated for their recognition performance using GFCC features not only in clean environment but also tested under noisy environment and compared with existing Mel frequency cepstral coefficient (MFCC) features. The GFCC shows almost comparable result with MFCC in clean environment; however, its performance goes down in noisy environment. Futhermore, the visual features obtained by the OF analysis when combine with GFCC audio features give significant improvement of ~ 12%, ~ 12%, and ~ 14% at different SNRs (5 dB, 10 dB, and 20 dB, respectively) in recognition performance under noisy environment.

UV laser desorption of nitric oxide from semiconducting C60/Cu(111)

The desorption of NO from a well-characterized, epitaxially grown semiconducting C60 surface is reported. Two different channels are identified in the laser desorption. Both channels yield a comparably high desorption cross section of σ1=7.0×10-17 cm2 and σ2=5.5×10-17 cm2 for the first and second channel, respectively. The laser desorbed NO molecules are detected with rovibrational state selectivity by (1+1) REMPI in the \(A^2\Sigma^+ \to{X}^2 \Pi\,\gamma\)-bands. In the first channel the desorbing molecules are highly excited with an average kinetic energy of 〈Ekin〉=174 meV. The rotational population distribution can be fitted by a rotational temperature of Trot=800 K. A rotational–translational coupling is observed, with velocities ranging from 1000 m/s for low to 1300 m/s for high rotational states. The vibrationally excited population is estimated to be less than 1% of the ground state. The second channel yields less excited molecules and an almost Boltzmann distributed rotational population with a temperature of Trot=280 K. The apparent velocity distribution derived from the pump-probe delay yields molecules much too slow to be explained by even a thermal desorption. This desorption is probably caused by a long-lived electronic excitation in the substrate for which a lifetime of τ≈160 μs is estimated.

Audio–visual person authentication using lip-motion from orientation maps

This paper describes a new identity authentication technique by a synergetic use of lip-motion and speech. The lip-motion is defined as the distribution of apparent velocities in the movement of brightness patterns in an image and is estimated by computing the velocity components of the structure tensor by 1D processing, in 2D manifolds. Since the velocities are computed without extracting the speaker’s lip-contours, more robust visual features can be obtained in comparison to motion features extracted from lip-contours. The motion estimations are performed in a rectangular lip-region, which affords increased computational efficiency. A person authentication implementation based on lip-movements and speech is presented along with experiments exhibiting a recognition rate of 98%. Besides its value in authentication, the technique can be used naturally to evaluate the “liveness” of someone speaking as it can be used in text-prompted dialogue. The XM2VTS database was used for performance quantification as it is currently the largest publicly available database (≈300 persons) containing both lip-motion and speech. Comparisons with other techniques are presented.

Multi-Modal Speech Recognition Using Optical-Flow Analysis for Lip Images

This paper proposes a multi-modal speech recognition method using optical-flow analysis for lip images. Optical flow is defined as the distribution of apparent velocities in the movement of brightness patterns in an image. Since the optical flow is computed without extracting the speaker's lip contours and location, robust visual features can be obtained for lip movements. Our method calculates two kinds of visual feature sets in each frame. The first feature set consists of variances of vertical and horizontal components of optical-flow vectors. These are useful for estimating silence/pause periods in noisy conditions since they represent movement of the speaker's mouth. The second feature set consists of maximum and minimum values of integral of the optical flow. These are expected to be more effective than the first set since this feature set has not only silence/pause information but also open/close status of the speaker's mouth. Each of the feature sets is combined with an acoustic feature set in the framework of HMM-based recognition. Triphone HMMs are trained using the combined parameter sets extracted from clean speech data. Noise-corrupted speech recognition experiments have been carried out using audio-visual data from 11 male speakers uttering connected digits. The following improvements of digit accuracy over the audio-only recognition scheme have been achieved when the visual information was used only for silence HMM: 4% at SNR = 5 dB and 13% at SNR = 10 dB using the integral information of optical flow as the visual feature set.

Further analysis of open-respirometry systems: an a-compartmental mechanistic approach.

A system is said to be "instantaneous" when for a given constant input an equilibrium output is obtained after a while. In the meantime, the output is changing from its initial value towards the equilibrium one. This is the transient period of the system and transients are important features of open-respirometry systems. During transients, one cannot compute the input amplitude directly from the output. The existing models (e.g., first or second order dynamics) cannot account for many of the features observed in real open-respirometry systems, such as time lag. Also, these models do not explain what should be expected when a system is speeded up or slowed down. The purpose of the present study was to develop a mechanistic approach to the dynamics of open-respirometry systems, employing basic thermodynamic concepts. It is demonstrated that all the main relevant features of the output dynamics are due to and can be adequately explained by a distribution of apparent velocities within the set of molecules travelling along the system. The importance of the rate at which the molecules leave the sensor is explored for the first time. The study approaches the difference in calibrating a system with a continuous input and with a "unit impulse": the former truly reveals the dynamics of the system while the latter represents the first derivative (in time) of the former and, thus, cannot adequately be employed in the apparent time-constant determination. Also, we demonstrate why the apparent order of the output changes with volume or flow.

Relativistic Beaming and the Nuclei of Double-lobed Radio Quasars

We have defined a complete sample of double-lobed 3CR quasars with minimal orientation bias. Properties of these objects on the >kpc scale are consistent with the simple beaming model for their nuclei. VLBI maps of six nuclei reveal “core-jet” structures. Both nuclei mapped at multiple epochs are modestly superluminal (3C245, 3.1c; 3C263, 1.3c; H0=100 km/s/Mpc, q0=0.5). The distribution of apparent velocities in this sample will provide a stringent test of beaming.

Seismic model of central and eastern Lesser Himalaya of Nepal

ABSTRACT
 The apparent velocity distribution of the local seismic of lesser Himalaya of central and Eastern Nepal allows to derive a three layered local seismic velocity model with first layer velocity of 5.6 Km/Sec, second layer of 6.5 Km/sec. and Moho discontinuity with 8.1 Km/sec. The first arrivals of different local phases of seismic waves are consistent with 20-23 Km thickness of the first layer and with crustal thickness of 55Km. The seismic events are confined to the first layer.
 Local velocity model derived after the seismic event of 6 Oct 1981, origin time 19 hr 18 mn 17 sec, by modelling the first arrivals and PMP (Moho reflection) arrivals within the interval of distance 138-218 Km confirms the velocity model derived from apparent velocity distribution.
 However, apparent velocity distribution of local seismic events occurring south of the line joining approximately Pokhara to Udayapur in plan does not seem to fit the theoretical distribution corresponding to the above three layered model with events within first layer. The apparent velocity of these events may be explained either (a) by the confinement of the focus of the events to the second layer or, (b) by the variation of the seismic velocity model with Moho depth at 35- 40 Km. i.e. with a normal Indian peninsular crust thickness.

Photoballistics of volcanic jet activity at Stromboli, Italy

Two night eruptions of the volcano Stromboli were studied through 70-mm photography. Single-camera techniques were used. Particle sphericity, constant velocity in the frame, and radial symmetry were assumed. Properties of the particulate phase found through analysis include: particle size, velocity, total number of particles ejected, angular dispersion and distribution in the jet, time variation of particle size and apparent velocity distribution, averaged volume flux, and kinetic energy carried by the condensed phase. The frequency distributions of particle size and apparent velocities are found to be approximately log normal. The properties of the gas phase were inferred from the fact that it was the transporting medium for the condensed phase. Gas velocity and time variation, volume flux of gas, dynamic pressure, mass erupted, and density were estimated. A CO2-H2O mixture is possible for the observed eruptions. The flow was subsonic. Velocity variations may be explained by an organ pipe resonance. Particle collimation may be produced by a Magnus effect.

A correlation method of apparent velocity measurement

Crustal refraction measurements present many uncertainties, some of which may be resolved by studying the apparent velocities of the entire train of arrivals. Discrete crustal layers have an over-all apparent velocity distribution which is distinctly different from that produced by a major crustal velocity gradient, while travel times show very little difference between the two. Visual measurement of apparent velocities in the secondary portion of a seismogram is uncertain and subject to error due to the lack of sharp onsets of events and to the generally higher background level. A computer method in which velocity filtering and statistical correlation are used has been developed. It eliminates this difficulty and makes it possible to investigate a wide range of apparent velocities. The first results of this method prove it to be a good constraint on a standard interpretation. Also, many features of the travel-time plot are revealed which have yet to be explained. The method promises to be a useful additional tool for the interpretation of crustal refraction measurements.