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Journal articles on the topic 'Time-varying source'

Author: Grafiati

Published: 20 February 2023

Last updated: 21 February 2023

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1

Coviello, Christian M., P. A. Yoon, and Leon H. Sibul. "Source separation and tracking for time-varying systems." IEEE Transactions on Aerospace and Electronic Systems 44, no. 3 (July 2008): 1198–214. http://dx.doi.org/10.1109/taes.2008.4655374.

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2

Soares, Cristiano, Martin Siderius, and Sérgio M. Jesus. "Source localization in a time-varying ocean waveguide." Journal of the Acoustical Society of America 112, no. 5 (November 2002): 1879–89. http://dx.doi.org/10.1121/1.1508786.

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3

Kian, Yavar, Éric Soccorsi, Qi Xue, and Masahiro Yamamoto. "Identification of time-varying source term in time-fractional diffusion equations." Communications in Mathematical Sciences 20, no. 1 (2022): 53–84. http://dx.doi.org/10.4310/cms.2022.v20.n1.a2.

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4

Eremin, Anton, Ekaterina Stefanyuk, and Liubov Abisheva. "Research on Heat Conductivity with a Time-Varying Heat Source." Applied Mechanics and Materials 698 (December 2014): 637–42. http://dx.doi.org/10.4028/www.scientific.net/amm.698.637.

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Using additional boundary conditions in the integral method of the heat balance, an approximate analytical solution to the heat conduction problem for an endless plate with time-varying heat sources has been found. It is shown that with any heat source capacity an unlimited plate temperature increase takes place in the course of time.

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5

Zuk, Nathaniel, and Bertrand Delgutte. "Neural coding of time-varying interaural time differences and time-varying amplitude in the inferior colliculus." Journal of Neurophysiology 118, no. 1 (July 1, 2017): 544–63. http://dx.doi.org/10.1152/jn.00797.2016.

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Binaural cues occurring in natural environments are frequently time varying, either from the motion of a sound source or through interactions between the cues produced by multiple sources. Yet, a broad understanding of how the auditory system processes dynamic binaural cues is still lacking. In the current study, we directly compared neural responses in the inferior colliculus (IC) of unanesthetized rabbits to broadband noise with time-varying interaural time differences (ITD) with responses to noise with sinusoidal amplitude modulation (SAM) over a wide range of modulation frequencies. On the basis of prior research, we hypothesized that the IC, one of the first stages to exhibit tuning of firing rate to modulation frequency, might use a common mechanism to encode time-varying information in general. Instead, we found weaker temporal coding for dynamic ITD compared with amplitude modulation and stronger effects of adaptation for amplitude modulation. The differences in temporal coding of dynamic ITD compared with SAM at the single-neuron level could be a neural correlate of “binaural sluggishness,” the inability to perceive fluctuations in time-varying binaural cues at high modulation frequencies, for which a physiological explanation has so far remained elusive. At ITD-variation frequencies of 64 Hz and above, where a temporal code was less effective, noise with a dynamic ITD could still be distinguished from noise with a constant ITD through differences in average firing rate in many neurons, suggesting a frequency-dependent tradeoff between rate and temporal coding of time-varying binaural information. NEW & NOTEWORTHY Humans use time-varying binaural cues to parse auditory scenes comprising multiple sound sources and reverberation. However, the neural mechanisms for doing so are poorly understood. Our results demonstrate a potential neural correlate for the reduced detectability of fluctuations in time-varying binaural information at high speeds, as occurs in reverberation. The results also suggest that the neural mechanisms for processing time-varying binaural and monaural cues are largely distinct.

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Zugmeyer, O., and J. P. Le Cadre. "A Multiscale Time-Varying Approach to Moving Source Tracking." IFAC Proceedings Volumes 25, no. 14 (July 1992): 481–86. http://dx.doi.org/10.1016/s1474-6670(17)50779-x.

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7

Bolster, Diogo, and CP Caulfield. "Transients in natural ventilation — A time-periodically-varying source." Building Services Engineering Research and Technology 29, no. 2 (May 2008): 119–35. http://dx.doi.org/10.1177/0143624407087849.

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8

Jiang, Jiaojiao, Sheng Wen, Shui Yu, Yang Xiang, and Wanlei Zhou. "Rumor Source Identification in Social Networks with Time-Varying Topology." IEEE Transactions on Dependable and Secure Computing 15, no. 1 (January 1, 2018): 166–79. http://dx.doi.org/10.1109/tdsc.2016.2522436.

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9

Sutton, Eric, and Helen Na. "Time-varying reconstruction of the ionosphere. 2. Data source analysis." International Journal of Imaging Systems and Technology 9, no. 6 (1998): 491–99. http://dx.doi.org/10.1002/(sici)1098-1098(1998)9:6<491::aid-ima11>3.0.co;2-0.

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10

Zhang, Jie, Hongli Gao, Qiyue Liu, and Christopher Grebe. "A new real-time signal processing approach for frequency-varying machinery." Journal of Vibration and Control 24, no. 11 (January 5, 2017): 2359–68. http://dx.doi.org/10.1177/1077546316687923.

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Development of condition monitoring approaches has played a key role in the stability and safety of frequency-varying machinery operations. Conventional time–frequency analysis methods suffer problems such as analysis results being too complex to realize highly intelligent and automated condition monitoring systems. Blind source separation is an attractive tool due to its excellent performance in separating defect source signals from their mixtures without detailed knowledge of sources and mixing processes; however, it can only be applied under some strict conditions. In this paper, a nonuniform sampling model is built and a new processing algorithm of frequency-varying signal is proposed. The relationship between the power spectral density (PSD) of the vibration signal of frequency-varying machinery and frequencies at different rotational speeds is derived. The proposed method can adaptively eliminate the influence of the varying rotational speed in the revised PSD. Some classical signal analysis methods are implemented to compare with the proposed approach by simulations. An experiment has been conducted by using a JD-1 wheel/rail simulation facility to illustrate the effectiveness of the proposed method.

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11

Pantazis, Dimitrios, and Amir Adler. "MEG Source Localization via Deep Learning." Sensors 21, no. 13 (June 22, 2021): 4278. http://dx.doi.org/10.3390/s21134278.

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We present a deep learning solution to the problem of localization of magnetoencephalography (MEG) brain signals. The proposed deep model architectures are tuned to single and multiple time point MEG data, and can estimate varying numbers of dipole sources. Results from simulated MEG data on the cortical surface of a real human subject demonstrated improvements against the popular RAP-MUSIC localization algorithm in specific scenarios with varying SNR levels, inter-source correlation values, and number of sources. Importantly, the deep learning models had robust performance to forward model errors resulting from head translation and rotation and a significant reduction in computation time, to a fraction of 1 ms, paving the way to real-time MEG source localization.

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12

Maloney, Philip. "Variability of Water Megamasers in AGN." Publications of the Astronomical Society of Australia 19, no. 1 (2002): 88–90. http://dx.doi.org/10.1071/as01106.

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AbstractPowerful water masers have been detected in 23 active galactic nuclei (AGN) to date. Most of the sources that have been monitored show evidence for variability, which may be either intrinsic (response of the masers to a time-varying pump or background source) or extrinsic (the effects of scintillation in the interstellar medium of the Galaxy). I briefly review the examples in which these mechanisms may be operating (interstellar scintillation in the Circinus galaxy, a time-varying background source in Mrk 348, and a time-varying AGN luminosity in NGC 1068).

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13

REN, Bin. "Multivariate Signal Time-varying Blind Source Separation for Locomotive Gear Transmission." Journal of Mechanical Engineering 52, no. 20 (2016): 8. http://dx.doi.org/10.3901/jme.2016.20.008.

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14

Estella Aguerri, Inaki, and Deniz Gunduz. "Joint Source-Channel Coding With Time-Varying Channel and Side-Information." IEEE Transactions on Information Theory 62, no. 2 (February 2016): 736–53. http://dx.doi.org/10.1109/tit.2015.2506575.

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15

Koivunen, V., M. Enescu, and E. Oja. "Adaptive Algorithm for Blind Separation from Noisy Time-Varying Mixtures." Neural Computation 13, no. 10 (October 1, 2001): 2339–57. http://dx.doi.org/10.1162/089976601750541822.

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This article addresses the problem of blind source separation from time-varying noisy mixtures using a state variable model and recursive estimation. An estimate of each source signal is produced real time at the arrival of new observed mixture vector. The goal is to perform the separation and attenuate noise simultaneously, as well as to adapt to changes that occur in the mixing system. The observed data are projected along the eigenvectors in signal subspace. The subspace is tracked real time. Source signals are modeled using low-order AR (autoregressive) models, and noise is attenuated by trading off between the model and the information provided by measurements. The type of zero-memory nonlinearity needed in separation is determined on-line. Predictor-corrector filter structures are proposed, and their performance is investigated in simulation using biomedical and communications signals at different noise levels and a time-varying mixing system. In quantitative comparison to other widely used methods, significant improvement in output signal-to-noise ratio is achieved.

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16

Feng, Xiao Li, and Bao Yun Qiu. "Optimal Operation for Source Parallel Pumping Stations." Applied Mechanics and Materials 325-326 (June 2013): 1445–49. http://dx.doi.org/10.4028/www.scientific.net/amm.325-326.1445.

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Pumping station transfers water from Yangtze River, and the head of is varied frequently within a wide range due to the tidal water. Taking Jiangdu parallel pumping stations in China as a case, under the premise of pumping certain volume of water per day, considering head varying and time-varying electrical price, mathematical models were established aiming at the minimum operation cost and solved with Simulated Annealing Particle Swarm Optimization. The number of running pump units and pump unit operation duties were determined in different time periods. The results indicate that operation cost of optimal operation schemes considering time-varying electrical price and adjusting blade angles is saved 13.72% than that of not considering.

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17

Amgain, Dipak Babu, and Tanka Nath Dhamala. "Quickest Flow Algorithms with Time-Varying Attributes." Journal of Institute of Science and Technology 26, no. 1 (June 17, 2021): 63–73. http://dx.doi.org/10.3126/jist.v26i1.37826.

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In many real-world situations, there are numerous network optimization problems where the network attributes depend on time. In this paper, we consider single-source single-sink discrete-time dynamic network flow problems. We review some algorithms for the quickest flow problems in two environments (to the network attributes): time-invariant and time-variant. This paper mainly focuses on the existing algorithms for a later one. In literature, most of the authors have made their objectives to determine the earliest arrival time paths along which a given amount of flow can be sent in the minimum time. Evacuation is the most recent research area of network optimization, where quickest flow models allow the estimation of the minimum time required to bring a given number of evacuees to safety.

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18

He, Pengju, Mi Qi, Wenhui Li, Mengyang Tang, and Ziwei Zhao. "A General Nonstationary and Time-Varying Mixed Signal Blind Source Separation Method Based on Online Gaussian Process." International Journal of Pattern Recognition and Artificial Intelligence 34, no. 11 (February 19, 2020): 2058015. http://dx.doi.org/10.1142/s021800142058015x.

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Most nonstationary and time-varying mixed source separation algorithms are based on the model of instantaneous mixtures. However, the observation signal is a convolutional mixed source in reverberation environment, such as mobile voice received by indoor microphone arrays. In this paper, a time-varying convolution blind source separation (BSS) algorithm for nonstationary signals is proposed, which can separate both time-varying instantaneous mixtures and time-varying convolution mixtures. We employ the variational Bayesian (VB) inference method with Gaussian process (GP) prior for separating the nonstationary source frame by frame from the time-varying convolution signal, in which the prior information of the mixing matrix and the source signal are obtained by the Gaussian autoregressive method, and the posterior distributions of parameters (source signal and mixing matrix) are obtained by the VB learning. In the learning process, the learned parameters and hyperparameters are propagated to the next frame for VB inference as the prior which is combined with the likelihood function to get the posterior distribution. The experimental results show that the proposed algorithm is effective for separating time-varying mixed speech signals.

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19

Belchior, Fernando Nunes, Paulo Fernando Ribeiro, and Frederico Marques Carvalho. "Comparative Analysis of Instruments Measuring Time Varying Harmonics." International Journal of Emerging Electric Power Systems 17, no. 4 (August 1, 2016): 463–69. http://dx.doi.org/10.1515/ijeeps-2015-0175.

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Abstract This paper aims to evaluate the performance of commercial class A and class S power quality (PQ) instruments when measuring time-varying harmonics. By using a high precision programmable voltage and current source, two meters from different manufacturers are analyzed and compared. Three-phase voltage signals are applied to PQ instruments, considering 3 situations of time-varying harmonic distortions, whose harmonic distortion values are in accordance with typical values found in power systems. This work is relevant considering that international standardization documents do not pay much attention to this aspect of harmonic distortion.

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20

Qiu, Panghe, Zhiyuan Ye, Zhichen Bai, Xin Liu, and Su Bo. "Computational Ghost Imaging with Multiplexed Time-Varying Signals." International Journal of Optics 2020 (July 18, 2020): 1–8. http://dx.doi.org/10.1155/2020/4109612.

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This study proposes two methods of optical watermarking based on multiplexed time-varying signals for computational ghost imaging using the Hadamard matrices. The proposed methods can realize image fusion and dual optical encryption. The time-varying signal is encoded into a specific Hadamard coefficient in advance and hidden in the light source of the transmitting end as a multiplicative factor or loaded at the receiving end as an additive factor. Theory and experiments confirm the feasibility of this scheme. Moreover, the scheme is highly scalable and has potential applications in multispectral single-pixel imaging.

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21

Wang, Cheng, Yanxia Hu, Wei Zhan, Jianying Wang, Baokun Yang, Yiwen Zhang, and Yewang Chen. "Multiple random fault sources adaptive blind separation in situation of time-varying source signals and system." Vibroengineering PROCEDIA 14 (October 21, 2017): 82–86. http://dx.doi.org/10.21595/vp.2017.19174.

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22

Cecconello, Elsa, Endrias G. Asgedom, Okwudili C. Orji, Morten W. Pedersen, and Walter Söllner. "Modeling scattering effects from time-varying sea surface based on acoustic reciprocity." GEOPHYSICS 83, no. 2 (March 1, 2018): T49—T68. http://dx.doi.org/10.1190/geo2017-0410.1.

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In marine seismic processing, the sea surface is often considered a flat mirror; hence, the effects of different weather conditions during the acquisition are largely ignored. However, studies have shown that rough sea-surface ghosts can severely damage the 4D signal, if not handled properly in data processing. To account for realistic sea-surface effects in processing, the impact of time-varying rough sea surfaces needs to be studied. We derive a method for modeling source and receiver ghosts from the time-varying rough sea surface and their interaction with subsurface reflections. This method is based on acoustic reciprocity and leads to integral equations of nonstationary wavefields. These modeling equations can also serve as a basis for investigating source and receiver deghosting methods for time-varying rough sea surfaces. Our developed modeling algorithm is validated against a frequency-domain approach for a “frozen” rough sea surface. For a moving simple sea surface, the Doppler shift produced by our method is in very good agreement with the analytical solution. Using a Pierson-Moskowitz spectrum, we derive a time-varying rough sea surface and model the receiver ghost, the source ghost, and the source-receiver ghost for the subsurface primary reflections of a heterogeneous geologic model. The results highlight that the source and receiver ghost interactions with a time-varying sea surface differently affect the subsurface reflections, and these effects can significantly impact the seismic repeatability of 4D studies.

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23

Cecconello, Elsa, Endrias G. Asgedom, and Walter Söllner. "Removal of all time-varying sea-surface effects by source deghosting and demultiple." GEOPHYSICS 84, no. 6 (November 1, 2019): T347—T362. http://dx.doi.org/10.1190/geo2018-0879.1.

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Seismic source deghosting and sea-surface-related demultiple have been long-standing problems in marine seismic data processing. Although the receiver ghost problem may be considered as solved by using collocated measurement of pressure and normal velocity wavefields, the source deghosting and demultiple algorithms are still limited by assumptions related to the sea-surface condition. We have investigated the impact of a time-varying rough sea surface on source deghosting and demultiple. Starting from Rayleigh’s reciprocity theorem for time-varying sea surfaces, we uncover a fundamental limitation for source deghosting of time-dependent wavefields, such as marine seismic data that contain a receiver ghost or sea-surface-related multiples. We use simple synthetic examples to study the impact of source deghosting on sea-surface-related multiples. To resolve this limitation, we derive a method for simultaneous source deghosting and sea-surface-related demultiple for time-variant wavefields. Finally, we use the complex geologic model Sigsbee 2B first to illustrate that the source deghosting operation brings significant errors when applied to a data set containing sea-surface multiples. Second, we find that this problem can be resolved by simultaneously performing source deghosting and demultiple operations even in the presence of time-varying sea surfaces.

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24

HAYASHI, Naoki, and Shigemasa TAKAI. "Distributed Source Identification by Two-Hop Consensus Dynamics with Uniform Time-Varying Communication Time-Delays." SICE Journal of Control, Measurement, and System Integration 10, no. 2 (2017): 70–76. http://dx.doi.org/10.9746/jcmsi.10.70.

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25

Mock, Adam. "Effective Single-Frequency Source Spectra in Broadband Time-Domain Electromagnetic Simulation of Time-Varying Materials." IEEE Transactions on Microwave Theory and Techniques 69, no. 7 (July 2021): 3192–207. http://dx.doi.org/10.1109/tmtt.2021.3072741.

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26

Sabeti, Malihe, and Reza Boostani. "Separation of P300 event-related potential using time varying time-lag blind source separation algorithm." Computer Methods and Programs in Biomedicine 145 (July 2017): 95–102. http://dx.doi.org/10.1016/j.cmpb.2017.04.014.

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27

Tsalaile, T., R. Sameni, S. Sanei, C. Jutten, and J. Chambers. "Sequential Blind Source Extraction For Quasi-Periodic Signals With Time-Varying Period." IEEE Transactions on Biomedical Engineering 56, no. 3 (March 2009): 646–55. http://dx.doi.org/10.1109/tbme.2008.2002141.

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28

Zobaa, A. F. "Voltage Harmonic Reduction for Randomly Time-Varying Source Characteristics and Voltage Harmonics." IEEE Transactions on Power Delivery 21, no. 2 (April 2006): 816–22. http://dx.doi.org/10.1109/tpwrd.2005.864043.

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29

Estella Aguerri, Inaki, and Deniz Gunduz. "Distortion Exponent in MIMO Fading Channels With Time-Varying Source Side Information." IEEE Transactions on Information Theory 62, no. 6 (June 2016): 3597–617. http://dx.doi.org/10.1109/tit.2016.2549037.

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30

Hu, L., Z. G. Zhang, and Y. Hu. "A time-varying source connectivity approach to reveal human somatosensory information processing." NeuroImage 62, no. 1 (August 2012): 217–28. http://dx.doi.org/10.1016/j.neuroimage.2012.03.094.

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31

Fallon, Maurice F., and Simon J. Godsill. "Acoustic Source Localization and Tracking of a Time-Varying Number of Speakers." IEEE Transactions on Audio, Speech, and Language Processing 20, no. 4 (May 2012): 1409–15. http://dx.doi.org/10.1109/tasl.2011.2178402.

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32

Digman, Matthew C., and Neil J. Cornish. "LISA Gravitational Wave Sources in a Time-varying Galactic Stochastic Background." Astrophysical Journal 940, no. 1 (November 1, 2022): 10. http://dx.doi.org/10.3847/1538-4357/ac9139.

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Abstract A unique challenge for data analysis with the Laser Interferometer Space Antenna (LISA) is that the noise backgrounds from instrumental noise and astrophysical sources will change significantly over both the year and the entire mission. Variations in the noise levels will be on timescales comparable to, or shorter than, the time most signals spend in the detector’s sensitive band. The variation in the amplitude of the galactic stochastic GW background from galactic binaries as the antenna pattern rotates relative to the galactic center is a particularly significant component of the noise variation. LISA’s sensitivity to different source classes will therefore vary as a function of sky location and time. The variation will impact both overall signal-to-noise and the efficiency of alerts to EM observers to search for multimessenger counterparts.

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33

Duteil, Nastassia Pouradier. "Mean-field limit of collective dynamics with time-varying weights." Networks and Heterogeneous Media 17, no. 2 (2022): 129. http://dx.doi.org/10.3934/nhm.2022001.

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<p style='text-indent:20px;'>In this paper, we derive the mean-field limit of a collective dynamics model with time-varying weights, for weight dynamics that preserve the total mass of the system as well as indistinguishability of the agents. The limit equation is a transport equation with source, where the (non-local) transport term corresponds to the position dynamics, and the (non-local) source term comes from the weight redistribution among the agents. We show existence and uniqueness of the solution for both microscopic and macroscopic models and introduce a new empirical measure taking into account the weights. We obtain the convergence of the microscopic model to the macroscopic one by showing continuity of the macroscopic solution with respect to the initial data, in the Wasserstein and Bounded Lipschitz topologies.</p>

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34

Charlot, P. "Models for Source Structure Corrections." International Astronomical Union Colloquium 180 (March 2000): 29–39. http://dx.doi.org/10.1017/s0252921100000075.

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AbstractAt the milliarcsecond scale, most of the extragalactic radio sources exhibit spatially-extended intrinsic structures which are variable in both time and frequency. Such radio structures set limits on the accuracy of source positions determined with the Very Long Baseline Interferometry (VLBI) technique unless their effects in the astrometric data can be accounted for. We review the modeling scheme for calculating source structure corrections and discuss the magnitude and impact of these effects for the sources that are part of the International Celestial Reference Frame (ICRF). Results obtained by applying source structure corrections to actual VLBI observations on the time-varying source 4C39.25 (0923 + 392) are also presented.

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35

de la Sen, M., S. Alonso-Quesada, A. J. Garrido, and A. Ibeas. "About the Maximum Transfer of Power in Time-Varying Linear Circuits." Advanced Materials Research 629 (December 2012): 894–99. http://dx.doi.org/10.4028/www.scientific.net/amr.629.894.

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This paper discusses the mathematical conditions of achievement of maximum power transfer from source to load in electric circuits where their basic elements (resistance, inductance and capacitance) are eventually linear and time-varying but not necessarily everywhere time-differentiable. This last concern is seen to be relevant for the inductive part of the circuit whose time- derivative, where it exists, plays the role of a resistor while it has an impulsive characterization at time instants where such a time-derivative does not exist. The power transfer degradation through time is also characterized related to the initial values of the circuitry provided that the source remains unaltered through time.

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JONES, PRESTON. "ELECTROMAGNETIC RADIATION FROM TEMPORAL VARIATIONS IN SPACE–TIME AND PROGENITORS OF GAMMA RAY BURST AND MILLISECOND PULSARS." International Journal of Modern Physics D 16, no. 11 (November 2007): 1871–77. http://dx.doi.org/10.1142/s0218271807011164.

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A time varying space–time metric is shown to be a source of electromagnetic radiation even in the absence of charge sources. The post-Newtonian approximation is used as a realistic model of the connection between the space–time metric and a time-varying gravitational potential. Rapid temporal variations in the metric from the coalescence of relativistic stars are shown to be likely progenitors of gamma ray burst and millisecond pulsars.

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37

Du, Yue, Liu, Liang, Wang, Gao, and Li. "Transient Temperature Field Model of Wear Land on the Flank of End Mills: A Focus on Time-Varying Heat Intensity and Time-Varying Heat Distribution Ratio." Applied Sciences 9, no. 8 (April 24, 2019): 1698. http://dx.doi.org/10.3390/app9081698.

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Modelling methods for the transient temperature field of wear land on the flank of end mills have been proposed to address the challenges of inaccurate prediction in the temperature field of end mills during the high-speed peripheral milling of Ti6Al4V that is a titanium alloy. A transient temperature rise model of wear land on the flank of end mills was constructed under the influence of heat sources in the primary shearing zone (PSZ), rake-chip zone (RCZ), flank-workpiece zone (FWZ), and dissipating heat source. Then the transient temperature field model of wear land on the flank of end mills was constructed. Finally, the transient temperature field model of wear land on the flank of end mills was constructed. Comparison of simulation result and experimental data verified the accuracy of the model. In sum, the proposed model may provide a temperature model support for future studies of flank wear rate in end mill modeling.

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38

Funaki, Keiichi, Yoshikazu Miyanaga, and Koji Tochinai. "A time‐varying ARMAX speech analysis method based on the glottal source model." Journal of the Acoustical Society of America 100, no. 4 (October 1996): 2602. http://dx.doi.org/10.1121/1.417617.

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39

Levine, Harold. "On the transient sound radiation from a planar source with time‐varying extent." Journal of the Acoustical Society of America 84, no. 5 (November 1988): 1924–28. http://dx.doi.org/10.1121/1.397158.

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40

Little, W. C., and G. L. Freeman. "Description of LV pressure-volume relations by time-varying elastance and source resistance." American Journal of Physiology-Heart and Circulatory Physiology 253, no. 1 (July 1, 1987): H83—H90. http://dx.doi.org/10.1152/ajpheart.1987.253.1.h83.

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If the left ventricle (LV) behaves as a time-varying elastance [E(t)] that is independent of load, then definition of E(t) during normal ejecting beats should permit accurate prediction of LV pressure (LVP) during a maximally afterloaded (isovolumic) beat. We tested this hypothesis in six dogs preinstrumented to measure LVP and aortic flow (Q) and to determine LV volume (V) from three dimensions. LVP and V were varied by caval occlusions. These data were used to determine E(t) and minimal volume required to generate pressure (Vo) at 10-ms intervals during systole using a simple E(t) model, P(t) = E(t) [V(t)-Vo], where P(t) is LVP at any time after the onset of contraction, and V(t) is the LV volume at t. LVP was measured during isovolumic beats generated by sudden balloon occlusion of the ascending aorta. The simple E(t) model accurately predicted isovolumic LVP during the first 70 ms of systole (r = 0.99) and also the end-systolic LVP but underestimated LVP during midsystole by 48 +/- 5 (SD) mmHg (P less than 0.05). When a pressure-dependent source resistance (K = 0.0015 s/ml) was added to the model to reduce LVP in proportion to Q, such that P(t) = E(t) [V(t)-Vo] X [1 - KQ]), LVP during the isovolumic beat was accurately predicted throughout systole (r = 0.99). However, the time to develop peak isovolumic pressure was 22 +/- 7 ms less than predicted. Similar results were obtained during inotropic stimulation with dobutamine in five animals.

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Nakatani, Tomohiro, Biing-Hwang Juang, Takuya Yoshioka, Keisuke Kinoshita, Marc Delcroix, and Masato Miyoshi. "Speech Dereverberation Based on Maximum-Likelihood Estimation With Time-Varying Gaussian Source Model." IEEE Transactions on Audio, Speech, and Language Processing 16, no. 8 (November 2008): 1512–27. http://dx.doi.org/10.1109/tasl.2008.2004306.

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Liu, Xiaoran, Fei Li, Hao Cai, Kai Zhang, Jinxiang Liu, Jiheng Xu, and Xianting Li. "Dynamical source term estimation in a multi-compartment building under time-varying airflow." Building and Environment 160 (August 2019): 106162. http://dx.doi.org/10.1016/j.buildenv.2019.106162.

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Mehta, Kurang, Jon L. Sheiman, Roel Snieder, and Rodney Calvert. "Strengthening the virtual-source method for time-lapse monitoring." GEOPHYSICS 73, no. 3 (May 2008): S73—S80. http://dx.doi.org/10.1190/1.2894468.

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Time-lapse monitoring is a powerful tool for tracking subsurface changes resulting from fluid migration. Conventional time-lapse monitoring can be done by observing differences between two seismic surveys over the surveillance period. Along with the changes in the subsurface, differences in the two seismic surveys are also caused by variations in the near-surface overburden and acquisition discrepancies. The virtual-source method monitors below the time-varying near-surface by redatuming the data down to the subsurface receiver locations. It crosscorrelates the signal that results from surface shooting recorded by subsurface receivers placed below the near-surface. For the Mars field data, redatuming the recorded response down to the permanently placed ocean-bottom cable (OBC) receivers using the virtual-source method allows one to reconstruct a survey as if virtualsources were buried at the OBC receiver locations and the medium above them were a homogeneous half-space. Separating the recorded wavefields into upgoing and downgoing (up-down) waves before crosscorrelation makes the resultant virtual-source data independent of the time-varying near-surface (seawater). For time-lapse monitoring, varying source signature for the two surveys and for each shot is also undesirable. Deconvolving the prestack crosscorrelated data (correlation gather) by the power spectrum of the source-time function results in virtual-source data independent of the source signature. Incorporating up-down wavefield separation and deconvolution of the correlation gather by the source power spectrum into the virtual-source method suppresses the causes of nonrepeatability in the seawater along with acquisition and source signature discrepancies. This processing combination strengthens the virtual-source method for time-lapse monitoring.

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Cuansing, Eduardo C. "Attenuation and amplification of the transient current in nanojunctions with time-varying gate potentials." International Journal of Modern Physics B 31, no. 14 (March 27, 2017): 1750105. http://dx.doi.org/10.1142/s0217979217501053.

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We study charge transport in a source-channel-drain system with a time-varying applied gate potential acting on the channel. We calculate both the current flowing from the source into channel and out of the channel into the drain. The current is expressed in terms of nonequilibrium Green’s functions. These nonequilibrium Green’s functions can be determined from the steady-state Green’s functions and the equilibrium Green’s functions of the free leads. We find that the application of the gate potential can induce current to flow even when there is no source-drain bias potential. However, the direction of the current from the source and the current to the drain are opposite, thereby resulting in no net current flowing within the channel. When a source-drain bias potential is present, the net current flowing to the source and drain can either be attenuated or amplified depending on the sign of the applied gate potential. We also find that the response of the system to a dynamically changing gate potential is not instantaneous, i.e., a relaxation time has to pass before the current settles into a steady value. In particular, when the gate potential is in the form of a step function, the current first overshoots to a maximum value, oscillates and then settles down to a steady-state value.

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Kou, Linlin, Baiqing Chu, Yan Chen, and Yong Qin. "An Automatic Partition Time-Varying Markov Model for Reliability Evaluation." Applied Sciences 12, no. 12 (June 10, 2022): 5933. http://dx.doi.org/10.3390/app12125933.

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As the service time of mechanical devices is getting longer and longer, the safe and reliability evaluation during operation is highlighted. Moreover, real-time reliability evaluation with consideration of multi-state performance degradation becomes increasingly important nowadays, since the consequences of sudden failures are more unacceptable than ever before. The Markov process is a commonly used model in multi-state reliability evaluation. However, little research of the Markov model can deal with multi-source monitoring data and time-varying properties of device performance degradation, as well as the scientific state number determination. In this article, a real-time reliability evaluation model based on automatic partition and the time-varying Markov chain is proposed to solve the problems of the scientific state number selection and time-varying properties description with the state transition matrix of the Markov process, together with taking advantage of multi-source information. The effectiveness of the proposed algorithm is demonstrated on the bearing with life-long vibration and temperature data. It shows that the proposed automatic partition time-varying Markov model can decide the state number automatically according to the trend of life-long data, and evaluate real-time reliability based on equipment operating hours and operating status. The result of predicted remaining useful life obtained by the proposed model is more accurate, and it also shows great superiority in conformity with reality.

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Li, Zhenjun, Zechen Lu, Chunyu Zhao, Fangchen Liu, and Ye Chen. "Heat Source Forecast of Ball Screw Drive System Under Actual Working Conditions Based on On-Line Measurement of Temperature Sensors." Sensors 19, no. 21 (October 29, 2019): 4694. http://dx.doi.org/10.3390/s19214694.

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In view of the time-varying complexity of the heat source for the ball screw feed system, this paper proposes an adaptive inverse problem-solving method to estimate the time-varying heat source and temperature field of the feed system under working conditions. The feed system includes multiple heat sources, and the rapid change of the moving heat source increases the difficulty of its identification. This paper attempts to develop a numerical calculation method for identifying the heat source by combining the experiment with the optimization algorithm. Firstly, based on the theory of heat transfer, a new dynamic thermal network model was proposed. The temperature data signal and the position signal of the moving nut captured by the sensors are used as input to optimize the solution of the time-varying heat source. Then, based on the data obtained from the experiment, finite element software parametric programming was used to optimize the estimate of the heat source, and the results of the two heat source prediction methods are compared and verified. The other measured temperature points obtained by the experiment were used to compare and verify the inverse method of this numerical calculation, which illustrates the reliability and advantages of the dynamic thermal network combined with the genetic algorithm for the inverse method. The method based on the on-line monitoring of temperature sensors proposed in this paper has a strong application value for heat source and temperature field estimation of complex mechanical structures.

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Lu, Jiantao, Wei Cheng, and Yanyang Zi. "Online blind source separation method with adaptive step size in both time-invariant and time-varying cases." Measurement Science and Technology 31, no. 4 (January 15, 2020): 045102. http://dx.doi.org/10.1088/1361-6501/ab5c75.

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S Patel, Pravesh, Hemal Shah, and Yogeshwar Kosta. "CHBR: Contact History Based Routing in Time Varying Approach." INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 13, no. 2 (April 16, 2014): 4237–47. http://dx.doi.org/10.24297/ijct.v13i2.2911.

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In Delay tolerant network having intermittent connectivity so there is no guarantee of finding a complete communication path that connecting the source and destination. There no any end to end connectivity for delay-tolerant network selection of routing protocol is important to deliver the message in an efficient way and increases chance to deliver a message to the destination. Some existing routing protocols improve the delivery ratio but it also increases the overhead. Our paper proposed Contact History Based Routing (CHBR) that use Neighborhood Index and Time varying properties such as temporal distance, Temporal Diameter and centrality for benchmarking the existing routing protocol. First, temporal metrics are evaluated for synthetic and real trace data. Then CHBR protocol is compared with the Epidemic and PROPHET for delivery ratio, overhead and the number of messages dropped. This has been carried using Opportunistic Network Environment simulator under real and synthetic datasets.

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Deviyantini, Deviyantini, Iman Sugema, and Tony Irawan. "STRUCTURAL BREAKS DAN KETIDAKSTABILAN PERMINTAAN UANG DI INDONESIA." JURNAL EKONOMI DAN KEBIJAKAN PEMBANGUNAN 6, no. 2 (July 31, 2018): 47–60. http://dx.doi.org/10.29244/jekp.6.2.2017.47-60.

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This research aims to identify the sources of instability of the money demand function (M1 and M2) due to structural changes that occur as a result of economic shocks. These shocks are technically shown by the presence of structural breaks in the data and can lead the parameters non-constancy. The instability of the money demand function was analyzed using the Gregory and Hansen test. The source of instability of the money demand was identified using time varying parameter model. This research used quarterly time series data from 1993Q1 to 2013Q4. The results show that the money demand function (M1 dan M2) is not cointegrated (unstable) and the source of the instability is exchange rate variable. Keywords: Stability money demand, Structural breaks, Time varying parameter model

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Deviyantini, Deviyantini, Iman Sugema, and Tony Irawan. "STRUCTURAL BREAKS DAN KETIDAKSTABILAN PERMINTAAN UANG DI INDONESIA." JURNAL EKONOMI DAN KEBIJAKAN PEMBANGUNAN 6, no. 2 (July 31, 2018): 47–60. http://dx.doi.org/10.29244/jekp.6.2.47-60.

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This research aims to identify the sources of instability of the money demand function (M1 and M2) due to structural changes that occur as a result of economic shocks. These shocks are technically shown by the presence of structural breaks in the data and can lead the parameters non-constancy. The instability of the money demand function was analyzed using the Gregory and Hansen test. The source of instability of the money demand was identified using time varying parameter model. This research used quarterly time series data from 1993Q1 to 2013Q4. The results show that the money demand function (M1 dan M2) is not cointegrated (unstable) and the source of the instability is exchange rate variable. Keywords: Stability money demand, Structural breaks, Time varying parameter model

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