Precoder and decoder prediction in time-varying MIMO channel
DEFF Research Database (Denmark)
Nguyen, Tuan Hung; Leus, Geert; Khaled, Nadia
2005-01-01
In mobile communications, time varying channels make the available channel information out of date. Timely updating the channel state is an obvious solution to improve the system performance in a time varying channel. However, a better knowledge of the channel comes at the cost of a decrease...... in the system throughput. Thus, predicting the future channel conditions can improve not only the performance but also the throughput of many types of wireless systems. This is especially true for a wireless system where multiple antennas are applied at both link ends. In this report we propose and evaluate...
Estimation of time-varying channels - A block approach
Leus, G.; Tang, Z.; Banelli, P.
2011-01-01
Channel state information (CSI) is indispensable for coherent detection in a wireless communication system. The pilot-aided method is one of the most intensively studied approaches for channel estimation. This method is especially attractive for time-varying channels because of their short coherence
Network Coded Cooperation Over Time-Varying Channels
DEFF Research Database (Denmark)
Khamfroush, Hana; Lucani Rötter, Daniel Enrique; Barros, joao
2014-01-01
In this paper, we investigate the optimal design of cooperative network-coded strategies for a three-node wireless network with time-varying, half-duplex erasure channels. To this end, we formulate the problem of minimizing the total cost of transmitting M packets from source to two receivers...... that are suitable for practical systems. We use two wireless channel models to analyse the performance of the proposed heuristics in practical wireless networks, namely, (a) an infrastructure-to-vehicle (I2V) communication in a highway scenario considering Rayleigh fading, and (b) real packet loss measurements...... for WiFi using Aalborg University’s Raspberry Pi testbed. We compare our results with random linear network coding (RLNC) broadcasting schemes showing that our heuristics can provide up to 2x gains in completion time and up to 4x gains in terms of reliably serviced data packets....
Multi-carrier Communications over Time-varying Acoustic Channels
Aval, Yashar M.
Acoustic communication is an enabling technology for many autonomous undersea systems, such as those used for ocean monitoring, offshore oil and gas industry, aquaculture, or port security. There are three main challenges in achieving reliable high-rate underwater communication: the bandwidth of acoustic channels is extremely limited, the propagation delays are long, and the Doppler distortions are more pronounced than those found in wireless radio channels. In this dissertation we focus on assessing the fundamental limitations of acoustic communication, and designing efficient signal processing methods that cam overcome these limitations. We address the fundamental question of acoustic channel capacity (achievable rate) for single-input-multi-output (SIMO) acoustic channels using a per-path Rician fading model, and focusing on two scenarios: narrowband channels where the channel statistics can be approximated as frequency- independent, and wideband channels where the nominal path loss is frequency-dependent. In each scenario, we compare several candidate power allocation techniques, and show that assigning uniform power across all frequencies for the first scenario, and assigning uniform power across a selected frequency-band for the second scenario, are the best practical choices in most cases, because the long propagation delay renders the feedback information outdated for power allocation based on the estimated channel response. We quantify our results using the channel information extracted form the 2010 Mobile Acoustic Communications Experiment (MACE'10). Next, we focus on achieving reliable high-rate communication over underwater acoustic channels. Specifically, we investigate orthogonal frequency division multiplexing (OFDM) as the state-of-the-art technique for dealing with frequency-selective multipath channels, and propose a class of methods that compensate for the time-variation of the underwater acoustic channel. These methods are based on multiple
Wireless Communication over Time-Varying Channels With Limited Feedback
Simon, C.
2011-01-01
The number of deployed wireless communication systems has grown rapidly in the last years. Their popularity is mainly due to the effortlessness with which the systems can be deployed. Further, the new generation of wireless systems, e.g., 802.11n, starts to close the performance gap to their wired
Prediction of the eigenvectors for spatial multiplexing MIMO systems in time-varying channels
DEFF Research Database (Denmark)
Nguyen, Hung Tuan; Leus, Geert; Khaled, Nadia
2005-01-01
: In mobile communications, time varying channels make the available channel information out of date. Timely updating the channel state is an obvious solution to improve the system performance in a time varying channel. However, a better knowledge of the channel comes at the cost of a decrease...... in the system throughput. Thus, predicting the future channel conditions can improve not only the performance but also the throughput of many types of wireless systems. This is especially true for a wireless system where multiple antennas are applied at both link ends. In this paper we propose and evaluate...
Shi, Lei; Yao, Bo; Zhao, Lei; Liu, Xiaotong; Yang, Min; Liu, Yanming
2018-01-01
The plasma sheath-surrounded hypersonic vehicle is a dynamic and time-varying medium and it is almost impossible to calculate time-varying physical parameters directly. The in-fight detection of the time-varying degree is important to understand the dynamic nature of the physical parameters and their effect on re-entry communication. In this paper, a constant envelope zero autocorrelation (CAZAC) sequence based on time-varying frequency detection and channel sounding method is proposed to detect the plasma sheath electronic density time-varying property and wireless channel characteristic. The proposed method utilizes the CAZAC sequence, which has excellent autocorrelation and spread gain characteristics, to realize dynamic time-varying detection/channel sounding under low signal-to-noise ratio in the plasma sheath environment. Theoretical simulation under a typical time-varying radio channel shows that the proposed method is capable of detecting time-variation frequency up to 200 kHz and can trace the channel amplitude and phase in the time domain well under -10 dB. Experimental results conducted in the RF modulation discharge plasma device verified the time variation detection ability in practical dynamic plasma sheath. Meanwhile, nonlinear phenomenon of dynamic plasma sheath on communication signal is observed thorough channel sounding result.
Identifying time-varying channels with aid of pilots for MIMO-OFDM
Tang, Z.; Leus, G.J.T.
2011-01-01
In this paper, we consider pilot-aided channel estimation for orthogonal frequency division multiplexing (OFDM) systems with a multiple-input multiple-output setup. The channel is time varying due to Doppler effects and can be approximated by an oversampled complex exponential basis expansion model.
DEFF Research Database (Denmark)
Pittalà, Fabio; Msallem, Majdi; Hauske, Fabian N.
2012-01-01
We propose a non-weighted feed-forward equalization method with filter update by averaging channel estimations based on short CAZAC sequences. Three averaging methods are presented and tested by simulations in a time-varying 2×2 MIMO optical system....
Low-Complexity Block Turbo Equalization for OFDM Systems in Time-Varying Channels
Fang, K.; Rugini, L.; Leus, G.
2008-01-01
We propose low-complexity block turbo equalizers for orthogonal frequency-division multiplexing (OFDM) systems in time-varying channels. The presented work is based on a soft minimum mean-squared error (MMSE) block linear equalizer (BLE) that exploits the banded structure of the frequency-domain
Identifying time-varying channels with aid of pilots for MIMO-OFDM
Tang, Zijian; Leus, Geert
2011-12-01
In this paper, we consider pilot-aided channel estimation for orthogonal frequency division multiplexing (OFDM) systems with a multiple-input multiple-output setup. The channel is time varying due to Doppler effects and can be approximated by an oversampled complex exponential basis expansion model. We use a best linear unbiased estimator (BLUE) to estimate the channel with the aid of frequency-multiplexed pilots. The applicability of the BLUE, which is referred to as the channel identifiability in this paper, relies upon a proper pilot structure. Depending on whether the channel is estimated within a single OFDM symbol or multiple OFDM symbols, we propose simple pilot structures that guarantee channel identifiability. Further, it is shown that by employing more receive antennas, the BLUE can combat more effectively the Doppler-induced interference and therefore improve the channel estimation performance.
Identifying time-varying channels with aid of pilots for MIMO-OFDM
Directory of Open Access Journals (Sweden)
Leus Geert
2011-01-01
Full Text Available Abstract In this paper, we consider pilot-aided channel estimation for orthogonal frequency division multiplexing (OFDM systems with a multiple-input multiple-output setup. The channel is time varying due to Doppler effects and can be approximated by an oversampled complex exponential basis expansion model. We use a best linear unbiased estimator (BLUE to estimate the channel with the aid of frequency-multiplexed pilots. The applicability of the BLUE, which is referred to as the channel identifiability in this paper, relies upon a proper pilot structure. Depending on whether the channel is estimated within a single OFDM symbol or multiple OFDM symbols, we propose simple pilot structures that guarantee channel identifiability. Further, it is shown that by employing more receive antennas, the BLUE can combat more effectively the Doppler-induced interference and therefore improve the channel estimation performance.
Spectrum Sensing Based on Censored Observations in Time-Varying Channels using AR-1 Model
Directory of Open Access Journals (Sweden)
Dhaval K Patel
2015-01-01
Full Text Available Non-parametric sensing algorithms are preferred in cognitive radio. In this paper, spectrum sensing method based on censored observations is proposed. We evaluate the performance of Censored Anderson-Darling (CAD sensing method in time-varying and flat-fading channel using Monte Carlo simulations. We have shown the performance of the CAD sensing in terms of receiver operating characteristic (ROC. The considered channel is modeled by Gaussian variables and characterized by a first ordered autoregressive process ($AR1$. It is shown that the proposed method outperforms prevailing techniques such as the Energy detection (ED sensing and Order-statistic (OS based sensing in time-varying channel at lower signal to noise ratio.
Bit and Power Allocation Strategies for OFDM Systems over Time-Varying Channels
Gao, Xiang; Naraghi-Pour, Mort
Many bit and power allocation algorithms have been recently developed for OFDM systems assuming perfect knowledge of the channel state information (CSI). In practice, however, these algorithms experience significant performance loss due to the inaccuracies in CSI. For time-varying channels the imperfect channel state information due to outdated channel estimates is a major source of these inaccuracies. To mitigate this effect, we propose to predict the channel state information and devise the bit and power allocation algorithm using the predicted CSI. We study several channel prediction algorithms for OFDM systems and present robust bit and power allocation schemes based on the predicted CSI. Simulation results show that for Doppler frequencies up to 100Hz, the proposed bit and power allocation algorithms (using the predicted CSI) can achieve performance close to that of the algorithms that assume perfect knowledge of CSI.
OFDM receiver for fast time-varying channels using block-sparse Bayesian learning
DEFF Research Database (Denmark)
Barbu, Oana-Elena; Manchón, Carles Navarro; Rom, Christian
2016-01-01
We propose an iterative algorithm for OFDM receivers operating over fast time-varying channels. The design relies on the assumptions that the channel response can be characterized by a few non-negligible separable multipath components, and the temporal variation of each component gain can be well...... characterized with a basis expansion model using a small number of terms. As a result, the channel estimation problem is posed as that of estimating a vector of complex coefficients that exhibits a block-sparse structure, which we solve with tools from block-sparse Bayesian learning. Using variational Bayesian...... inference, we embed the channel estimator in a receiver structure that performs iterative channel and noise precision estimation, intercarrier interference cancellation, detection and decoding. Simulation results illustrate the superior performance of the proposed receiver over state-of-art receivers....
Directory of Open Access Journals (Sweden)
Gill R. Tsouri
2009-01-01
Full Text Available A method of overloading subcarriers by multiple transmitters to secure OFDM in wireless time-varying channels is proposed and analyzed. The method is based on reverse piloting, superposition modulation, and joint decoding. It makes use of channel randomness, reciprocity, and fast decorrelation in space to secure OFDM with low overheads on encryption, decryption, and key distribution. These properties make it a good alternative to traditional software-based information security algorithms in systems where the costs associated with such algorithms are an implementation obstacle. A necessary and sufficient condition for achieving information theoretic security in accordance with channel and system parameters is derived. Security by complexity is assessed for cases where the condition for information theoretic security is not satisfied. In addition, practical means for implementing the method are derived including generating robust joint constellations, decoding data with low complexity, and mitigating the effects of imperfections due to mobility, power control errors, and synchronization errors.
Directory of Open Access Journals (Sweden)
Zhang Han
2009-01-01
Full Text Available We address the problem of superimposed trainings- (STs- based linearly time-varying (LTV channel estimation and symbol detection for orthogonal frequency-division multiplexing access (OFDMA systems at the uplink receiver. The LTV channel coefficients are modeled by truncated discrete Fourier bases (DFBs. By judiciously designing the superimposed pilot symbols, we estimate the LTV channel transfer functions over the whole frequency band by using a weighted average procedure, thereby providing validity for adaptive resource allocation. We also present a performance analysis of the channel estimation approach to derive a closed-form expression for the channel estimation variances. In addition, an iterative symbol detector is presented to mitigate the superimposed training effects on information sequence recovery. By the iterative mitigation procedure, the demodulator achieves a considerable gain in signal-interference ratio and exhibits a nearly indistinguishable symbol error rate (SER performance from that of frequency-division multiplexed trainings. Compared to existing frequency-division multiplexed training schemes, the proposed algorithm does not entail any additional bandwidth while with the advantage for system adaptive resource allocation.
STATISTICAL PROCESSES, MAXIMUM LIKELIHOOD ESTIMATION, *INTERSYMBOL INTERFERENCE, TIME VARYING SYSTEMS, VITERBI DECODING, COMPUTERIZED SIMULATION, DATA TRANSMISSION SYSTEMS , *DIGITAL COMMUNICATION SYSTEMS
Directory of Open Access Journals (Sweden)
Islam S.M. Khalil
2016-06-01
Full Text Available Targeted therapy using magnetic microparticles and nanoparticles has the potential to mitigate the negative side-effects associated with conventional medical treatment. Major technological challenges still need to be addressed in order to translate these particles into in vivo applications. For example, magnetic particles need to be navigated controllably in vessels against flowing streams of body fluid. This paper describes the motion control of paramagnetic microparticles in the flowing streams of fluidic channels with time-varying flow rates (maximum flow is 35 ml.hr−1. This control is designed using a magnetic-based proportional-derivative (PD control system to compensate for the time-varying flow inside the channels (with width and depth of 2 mm and 1.5 mm, respectively. First, we achieve point-to-point motion control against and along flow rates of 4 ml.hr−1, 6 ml.hr−1, 17 ml.hr−1, and 35 ml.hr−1. The average speeds of single microparticle (with average diameter of 100 μm against flow rates of 6 ml.hr−1 and 30 ml.hr−1 are calculated to be 45 μm.s−1 and 15 μm.s−1, respectively. Second, we implement PD control with disturbance estimation and compensation. This control decreases the steady-state error by 50%, 70%, 73%, and 78% at flow rates of 4 ml.hr−1, 6 ml.hr−1, 17 ml.hr−1, and 35 ml.hr−1, respectively. Finally, we consider the problem of finding the optimal path (minimal kinetic energy between two points using calculus of variation, against the mentioned flow rates. Not only do we find that an optimal path between two collinear points with the direction of maximum flow (middle of the fluidic channel decreases the rise time of the microparticles, but we also decrease the input current that is supplied to the electromagnetic coils by minimizing the kinetic energy of the microparticles, compared to a PD control with disturbance compensation.
Robust Stability of Scaled-Four-Channel Teleoperation with Internet Time-Varying Delays
Directory of Open Access Journals (Sweden)
Emma Delgado
2016-04-01
Full Text Available We describe the application of a generic stability framework for a teleoperation system under time-varying delay conditions, as addressed in a previous work, to a scaled-four-channel (γ-4C control scheme. Described is how varying delays are dealt with by means of dynamic encapsulation, giving rise to mu-test conditions for robust stability and offering an appealing frequency technique to deal with the stability robustness of the architecture. We discuss ideal transparency problems and we adapt classical solutions so that controllers are proper, without single or double differentiators, and thus avoid the negative effects of noise. The control scheme was fine-tuned and tested for complete stability to zero of the whole state, while seeking a practical solution to the trade-off between stability and transparency in the Internet-based teleoperation. These ideas were tested on an Internet-based application with two Omni devices at remote laboratory locations via simulations and real remote experiments that achieved robust stability, while performing well in terms of position synchronization and force transparency.
Beamforming transmission in IEEE 802.11ac under time-varying channels.
Yu, Heejung; Kim, Taejoon
2014-01-01
The IEEE 802.11ac wireless local area network (WLAN) standard has adopted beamforming (BF) schemes to improve spectral efficiency and throughput with multiple antennas. To design the transmit beam, a channel sounding process to feedback channel state information (CSI) is required. Due to sounding overhead, throughput increases with the amount of transmit data under static channels. Under practical channel conditions with mobility, however, the mismatch between the transmit beam and the channel at transmission time causes performance loss when transmission duration after channel sounding is too long. When the fading rate, payload size, and operating signal-to-noise ratio are given, the optimal transmission duration (i.e., packet length) can be determined to maximize throughput. The relationship between packet length and throughput is also investigated for single-user and multiuser BF modes.
An Immunity-Based RBF Network and Its Application in Equalization of Nonlinear Time-Varying Channels
Zang, Xiaogang; Gong, Xinbao; Jin, Ronghong; Ling, Xiaofeng; Tang, Bin
This paper proposes a novel RBF training algorithm based on immune operations for dynamic problem solving. The algorithm takes inspiration from the dynamic nature of natural immune system and locally-tuned structure of RBF neural network. Through immune operations of vaccination and immune response, the RBF network can dynamically adapt to environments according to changes in the training set. Simulation results demonstrate that RBF equalizer based on the proposed algorithm obtains good performance in nonlinear time-varying channels.
Directory of Open Access Journals (Sweden)
Bezan Scott
2006-01-01
Full Text Available To reliably transmit video over error-prone channels, the data should be both source and channel coded. When multiple channels are available for transmission, the problem extends to that of partitioning the data across these channels. The condition of transmission channels, however, varies with time. Therefore, the error protection added to the data at one instant of time may not be optimal at the next. In this paper, we propose a method for adaptively adding error correction code in a rate-distortion (RD optimized manner using rate-compatible punctured convolutional codes to an MJPEG2000 constant rate-coded frame of video. We perform an analysis on the rate-distortion tradeoff of each of the coding units (tiles and packets in each frame and adapt the error correction code assigned to the unit taking into account the bandwidth and error characteristics of the channels. This method is applied to both single and multiple time-varying channel environments. We compare our method with a basic protection method in which data is either not transmitted, transmitted with no protection, or transmitted with a fixed amount of protection. Simulation results show promising performance for our proposed method.
Longo, S.; Ungarish, M.; Di Federico, V.; Chiapponi, L.; Addona, F.
2016-04-01
We investigate high-Reynolds number gravity currents (GC) in a horizontal channel of circular cross-section. We focus on GC sustained by constant or time varying inflow (volume of injected fluid ∝ tα, with α = 1 and α > 1). The novelty of our work is in the type of the gravity currents: produced by influx/outflux boundary conditions, and propagation in circular (or semi-circular) channel. The objective is to elucidate the main propagation features and correlate them to the governing dimensionless parameters; to this end, we use experimental observations guided by shallow-water (SW) theoretical models. The system is of Boussinesq type with the denser fluid (salt water) injected into the ambient fluid (tap water) at one end section of a circular tube of 19 cm diameter and 605 cm long. The ambient fluid fills the channel of radius r* up to a given height H* = βr* (0 channel. The two different configurations (with return and no-return flow) allow to analyze the impact of the motion of the ambient fluid on the front speed of the intruding current. For Q larger than some threshold value, the current is expected theoretically to undergo a choking process which limits the speed/thickness of propagation. Two series of experiments were conducted with constant and time varying inflow. The choking effect was observed, qualitatively, in both series. The theory correctly predicts the qualitative behavior, but systematically overestimates the front speed of the current (consistent with previously-published data concerning rectangular and non-rectangular cross-sections), with larger discrepancies for the no-return flow case. These discrepancies are mainly due to: (i) the variations of the free-surface of the ambient fluid with respect to its nominal value (the theoretical model assumes a fixed free-slip top of the ambient fluid), and (ii) mixing/entrainment effects, as shown by specific measurements of the open interface level and velocity profiles.
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Huu Phu Bui
2010-01-01
Full Text Available Multiple-input multiple-output (MIMO systems employ advanced signal processing techniques. However, the performance is affected by propagation environments and antenna characteristics. The main contributions of the paper are to investigate Doppler spectrum based on measured data in a typical meeting room and to evaluate the performance of MIMO systems based on an eigenbeam-space division multiplexing (E-SDM technique in an indoor time-varying fading environment, which has various distributions of scatterers, line-of-sight wave existence, and mutual coupling effect among antennas. We confirm that due to the mutual coupling among antennas, patterns of antenna elements are changed and different from an omnidirectional one of a single antenna. Results based on the measured channel data in our measurement campaigns show that received power, channel autocorrelation, and Doppler spectrum are dependent not only on the direction of terminal motion but also on the antenna configuration. Even in the obstructed-line-of-sight environment, observed Doppler spectrum is quite different from the theoretical U-shaped Jakes one. In addition, it has been also shown that a channel change during the time interval between the transmit weight matrix determination and the actual data transmission can degrade the performance of MIMO E-SDM systems.
Miller, Andrew; Villegas, Arturo; Diez, F Javier
2015-03-01
The solution to the startup transient EOF in an arbitrary rectangular microchannel is derived analytically and validated experimentally. This full 2D transient solution describes the evolution of the flow through five distinct periods until reaching a final steady state. The derived analytical velocity solution is validated experimentally for different channel sizes and aspect ratios under time-varying pressure gradients. The experiments used a time resolved micro particle image velocimetry technique to calculate the startup transient velocity profiles. The measurements captured the effect of time-varying pressure gradient fields derived in the analytical solutions. This is tested by using small reservoirs at both ends of the channel which allowed a time-varying pressure gradient to develop with a time scale on the order of the transient EOF. Results showed that under these common conditions, the effect of the pressure build up in the reservoirs on the temporal development of the transient startup EOF in the channels cannot be neglected. The measurements also captured the analytical predictions for channel walls made of different materials (i.e., zeta potentials). This was tested in channels that had three PDMS and one quartz wall, resulting in a flow with an asymmetric velocity profile due to variations in the zeta potential between the walls. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
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Simoens Frederik
2006-01-01
Full Text Available This paper concerns channel tracking in a multiantenna context for correlated flat-fading channels obeying a Gauss-Markov model. It is known that data-aided tracking of fast-fading channels requires a lot of pilot symbols in order to achieve sufficient accuracy, and hence decreases the spectral efficiency. To overcome this problem, we design a code-aided estimation scheme which exploits information from both the pilot symbols and the unknown coded data symbols. The algorithm is derived based on a factor graph representation of the system and application of the sum-product algorithm. The sum-product algorithm reveals how soft information from the decoder should be exploited for the purpose of estimation and how the information bits can be detected. Simulation results illustrate the effectiveness of our approach.
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Carly A Buckner
Full Text Available Electromagnetic field (EMF exposures affect many biological systems. The reproducibility of these effects is related to the intensity, duration, frequency, and pattern of the EMF. We have shown that exposure to a specific time-varying EMF can inhibit the growth of malignant cells. Thomas-EMF is a low-intensity, frequency-modulated (25-6 Hz EMF pattern. Daily, 1 h, exposures to Thomas-EMF inhibited the growth of malignant cell lines including B16-BL6, MDA-MB-231, MCF-7, and HeLa cells but did not affect the growth of non-malignant cells. Thomas-EMF also inhibited B16-BL6 cell proliferation in vivo. B16-BL6 cells implanted in syngeneic C57b mice and exposed daily to Thomas-EMF produced smaller tumours than in sham-treated controls. In vitro studies showed that exposure of malignant cells to Thomas-EMF for > 15 min promoted Ca(2+ influx which could be blocked by inhibitors of voltage-gated T-type Ca(2+ channels. Blocking Ca(2+ uptake also blocked Thomas-EMF-dependent inhibition of cell proliferation. Exposure to Thomas-EMF delayed cell cycle progression and altered cyclin expression consistent with the decrease in cell proliferation. Non-malignant cells did not show any EMF-dependent changes in Ca(2+ influx or cell growth. These data confirm that exposure to a specific EMF pattern can affect cellular processes and that exposure to Thomas-EMF may provide a potential anti-cancer therapy.
Buckner, Carly A; Buckner, Alison L; Koren, Stan A; Persinger, Michael A; Lafrenie, Robert M
2015-01-01
Electromagnetic field (EMF) exposures affect many biological systems. The reproducibility of these effects is related to the intensity, duration, frequency, and pattern of the EMF. We have shown that exposure to a specific time-varying EMF can inhibit the growth of malignant cells. Thomas-EMF is a low-intensity, frequency-modulated (25-6 Hz) EMF pattern. Daily, 1 h, exposures to Thomas-EMF inhibited the growth of malignant cell lines including B16-BL6, MDA-MB-231, MCF-7, and HeLa cells but did not affect the growth of non-malignant cells. Thomas-EMF also inhibited B16-BL6 cell proliferation in vivo. B16-BL6 cells implanted in syngeneic C57b mice and exposed daily to Thomas-EMF produced smaller tumours than in sham-treated controls. In vitro studies showed that exposure of malignant cells to Thomas-EMF for > 15 min promoted Ca(2+) influx which could be blocked by inhibitors of voltage-gated T-type Ca(2+) channels. Blocking Ca(2+) uptake also blocked Thomas-EMF-dependent inhibition of cell proliferation. Exposure to Thomas-EMF delayed cell cycle progression and altered cyclin expression consistent with the decrease in cell proliferation. Non-malignant cells did not show any EMF-dependent changes in Ca(2+) influx or cell growth. These data confirm that exposure to a specific EMF pattern can affect cellular processes and that exposure to Thomas-EMF may provide a potential anti-cancer therapy.
Carly A Buckner; Buckner, Alison L.; Koren, Stan A.; Michael A. Persinger; Lafrenie, Robert M.
2015-01-01
Electromagnetic field (EMF) exposures affect many biological systems. The reproducibility of these effects is related to the intensity, duration, frequency, and pattern of the EMF. We have shown that exposure to a specific time-varying EMF can inhibit the growth of malignant cells. Thomas-EMF is a low-intensity, frequency-modulated (25-6 Hz) EMF pattern. Daily, 1 h, exposures to Thomas-EMF inhibited the growth of malignant cell lines including B16-BL6, MDA-MB-231, MCF-7, and HeLa cells but di...
DEFF Research Database (Denmark)
Christoffersen, Peter; Feunoua, Bruno; Jeon, Yoontae
We estimate a continuous-time model with stochastic volatility and dynamic crash probability for the S&P 500 index and find that market illiquidity dominates other factors in explaining the stock market crash risk. While the crash probability is time-varying, its dynamic depends only weakly...
Components in time-varying graphs
Nicosia, Vincenzo; Tang, John; Musolesi, Mirco; Russo, Giovanni; Mascolo, Cecilia; Latora, Vito
2012-06-01
Real complex systems are inherently time-varying. Thanks to new communication systems and novel technologies, today it is possible to produce and analyze social and biological networks with detailed information on the time of occurrence and duration of each link. However, standard graph metrics introduced so far in complex network theory are mainly suited for static graphs, i.e., graphs in which the links do not change over time, or graphs built from time-varying systems by aggregating all the links as if they were concurrent in time. In this paper, we extend the notion of connectedness, and the definitions of node and graph components, to the case of time-varying graphs, which are represented as time-ordered sequences of graphs defined over a fixed set of nodes. We show that the problem of finding strongly connected components in a time-varying graph can be mapped into the problem of discovering the maximal-cliques in an opportunely constructed static graph, which we name the affine graph. It is, therefore, an NP-complete problem. As a practical example, we have performed a temporal component analysis of time-varying graphs constructed from three data sets of human interactions. The results show that taking time into account in the definition of graph components allows to capture important features of real systems. In particular, we observe a large variability in the size of node temporal in- and out-components. This is due to intrinsic fluctuations in the activity patterns of individuals, which cannot be detected by static graph analysis.
A time-varying magnetic flux concentrator
Kibret, B.; Premaratne, M.; Lewis, P. M.; Thomson, R.; Fitzgerald, P. B.
2016-08-01
It is known that diverse technological applications require the use of focused magnetic fields. This has driven the quest for controlling the magnetic field. Recently, the principles in transformation optics and metamaterials have allowed the realization of practical static magnetic flux concentrators. Extending such progress, here, we propose a time-varying magnetic flux concentrator cylindrical shell that uses electric conductors and ferromagnetic materials to guide magnetic flux to its center. Its performance is discussed based on finite-element simulation results. Our proposed design has potential applications in magnetic sensors, medical devices, wireless power transfer, and near-field wireless communications.
Time-Varying Periodicity in Intraday Volatility
DEFF Research Database (Denmark)
Andersen, Torben Gustav; Thyrsgaard, Martin; Todorov, Viktor
with a constant time-of-day periodic component. We first construct time-of-day volatility estimates and studentize the high-frequency returns with these periodic components. If the intraday volatility periodicity is invariant over time, then the distribution of the studentized returns should be identical across......We develop a nonparametric test for deciding whether return volatility exhibits time-varying intraday periodicity using a long time-series of high-frequency data. Our null hypothesis, commonly adopted in work on volatility modeling, is that volatility follows a stationary process combined...... the trading day. Consequently, the test is based on comparing the empirical characteristic function of the studentized returns across the trading day. The limit distribution of the test depends on the error in recovering volatility from discrete return data and the empirical process error associated...
Network Coded Cooperation Over Time-Varying Channels
DEFF Research Database (Denmark)
Khamfroush, Hana; Roetter, Daniel Enrique Lucani; Barros, João
2014-01-01
for WiFi using Aalborg University’s Raspberry Pi testbed. We compare our results with random linear network coding (RLNC) broadcasting schemes showing that our heuristics can provide up to 2x gains in completion time and up to 4x gains in terms of reliably serviced data packets....
Adaptive time-varying detrended fluctuation analysis.
Berthouze, Luc; Farmer, Simon F
2012-07-30
Detrended fluctuation analysis (DFA) is a technique commonly used to assess and quantify the presence of long-range temporal correlations (LRTCs) in neurophysiological time series. Convergence of the method is asymptotic only and therefore its application assumes a constant scaling exponent. However, most neurophysiological data are likely to involve either spontaneous or experimentally induced scaling exponent changes. We present a novel extension of the DFA method that permits the characterisation of time-varying scaling exponents. The effectiveness of the methodology in recovering known changes in scaling exponents is demonstrated through its application to synthetic data. The dependence of the method on its free parameters is systematically explored. Finally, application of the methodology to neurophysiological data demonstrates that it provides experimenters with a way to identify previously un-recognised changes in the scaling exponent in the data. We suggest that this methodology will make it possible to go beyond a simple demonstration of the presence of scaling to an appreciation of how it may vary in response to either intrinsic changes or experimental perturbations. Copyright © 2012 Elsevier B.V. All rights reserved.
Time-Varying Space-Only Codes for Coded MIMO
Duyck, Dieter; Takawira, Fambirai; Boutros, Joseph J; Moeneclaey, Marc
2012-01-01
Multiple antenna (MIMO) devices are widely used to increase reliability and information bit rate. Optimal error rate performance (full diversity and large coding gain), for unknown channel state information at the transmitter and for maximal rate, can be achieved by approximately universal space-time codes, but comes at a price of large detection complexity, infeasible for most practical systems. We propose a new coded modulation paradigm: error-correction outer code with space-only but time-varying precoder (as inner code). We refer to the latter as Ergodic Mutual Information (EMI) code. The EMI code achieves the maximal multiplexing gain and full diversity is proved in terms of the outage probability. Contrary to most of the literature, our work is not based on the elegant but difficult classical algebraic MIMO theory. Instead, the relation between MIMO and parallel channels is exploited. The theoretical proof of full diversity is corroborated by means of numerical simulations for many MIMO scenarios, in te...
Market Channels of Technology Startups that Internationalize Rapidly from Inception
Directory of Open Access Journals (Sweden)
Simar Yoos
2012-10-01
Full Text Available The study of technology startups that internationalize rapidly from inception has increased in recent years. However, little is known about their channels to market. This article addresses a gap in the "born global" literature by examining the channels used by six startups that internationalized rapidly from inception as well as the programs they used to support their channel partners and customers. The six startups examined combined the use of the Internet with: i a relationship with a multi-national, ii distributors, iii re-sellers, or iv a direct sales force. They also delivered programs to support partners and customers that focused on communications, alliance and network development, education, marketing and promotion, and financial incentives. This article informs entrepreneurs who need to design go-to-market channels to exploit global opportunities about decisions made by other entrepreneurs who launched born-global companies. Normative rules and practitioner-oriented approaches are needed to help entrepreneurs explain and apply the results presented in this article.
The stability of multichannel sound systems with time-varying mixing matrices.
Schlecht, Sebastian J; Habets, Emanuël A P
2016-07-01
Various time-varying algorithms have been applied in multichannel sound systems to improve the system's stability and, among these, frequency shifting has been demonstrated to reach the maximum stability improvement achievable by time-variation in general. However, the modulation artifacts have been found to diminish the gain improvement unusable for a higher number of channels and high-quality applications such as music reproduction. This paper proposes alternatively time-varying mixing matrices, which is an efficient algorithm corresponding to symmetric up and down frequency shifting. It is shown with a statistical approach that time-varying mixing matrices can as well achieve maximum stability improvement for a higher number of channels. A listening test demonstrates the improved quality of time-varying mixing matrices over frequency shifting.
Research on Channel Estimation and OFDM Signals Detection in Rapidly Time-Variant Channels
Directory of Open Access Journals (Sweden)
M. Huang
2014-09-01
Full Text Available It is well known that iterative channel estimation and OFDM signals detection can significantly improve the performance of communication system. However, its performance is poor due to the modelling error of basis expansion model (BEM being large enough and can not being ignored in rapidly time-variant channels. In this paper, channel estimation and OFDM signals detection are integrated into a real non-linear least squares (NLS problem. Then the modified Broyden-Fletcher-Goldfarb-Shanno (MBFGS algorithm is adopted to search the optimal solution. In addition, Cramer-Rao Bound (CRB for our proposed approach is derived. Simulation results are presented to illustrate the superiority of the proposed approach.
Methods for time-varying exposure related problems in pharmacoepidemiology
DEFF Research Database (Denmark)
Pazzagli, Laura; Linder, Marie; Zhang, Mingliang
2017-01-01
PURPOSE: Lack of control for time-varying exposures can lead to substantial bias in estimates of treatment effects. The aim of this study is to provide an overview and guidance on some of the available methodologies used to address problems related to time-varying exposure and confounding...... pharmacoepidemiological problems, construction of treatment episodes, time-varying confounders, cumulative exposure and latency, and treatment switching. RESULTS: A correct treatment episodes construction is fundamental to avoid bias in treatment effect estimates. Several methods exist to address time-varying covariates...
Time-varying interaction leads to amplitude death in coupled ...
Indian Academy of Sciences (India)
A new form of time-varying interaction in coupled oscillators is introduced. In this interaction, each individual oscillator has always time-independent self-feedback while its interaction with other oscillators are modulated with time-varying function. This interaction gives rise to a phenomenon called amplitude death even in ...
Time-frequency representation based on time-varying ...
Indian Academy of Sciences (India)
Abstract. A parametric time-frequency representation is presented based on time- varying autoregressive model (TVAR), followed by applications to non-stationary vibration signal processing. The identification of time-varying model coefficients and the determination of model order, are addressed by means of neural ...
Time varying voltage combustion control and diagnostics sensor
Chorpening, Benjamin T [Morgantown, WV; Thornton, Jimmy D [Morgantown, WV; Huckaby, E David [Morgantown, WV; Fincham, William [Fairmont, WV
2011-04-19
A time-varying voltage is applied to an electrode, or a pair of electrodes, of a sensor installed in a fuel nozzle disposed adjacent the combustion zone of a continuous combustion system, such as of the gas turbine engine type. The time-varying voltage induces a time-varying current in the flame which is measured and used to determine flame capacitance using AC electrical circuit analysis. Flame capacitance is used to accurately determine the position of the flame from the sensor and the fuel/air ratio. The fuel and/or air flow rate (s) is/are then adjusted to provide reduced flame instability problems such as flashback, combustion dynamics and lean blowout, as well as reduced emissions. The time-varying voltage may be an alternating voltage and the time-varying current may be an alternating current.
Study of selected phenotype switching strategies in time varying environment
Energy Technology Data Exchange (ETDEWEB)
Horvath, Denis, E-mail: horvath.denis@gmail.com [Centre of Interdisciplinary Biosciences, Institute of Physics, Faculty of Science, P.J. Šafárik University in Košice, Jesenná 5, 040 01 Košice (Slovakia); Brutovsky, Branislav, E-mail: branislav.brutovsky@upjs.sk [Department of Biophysics, Institute of Physics, P.J. Šafárik University in Košice, Jesenná 5, 040 01 Košice (Slovakia)
2016-03-22
Population heterogeneity plays an important role across many research, as well as the real-world, problems. The population heterogeneity relates to the ability of a population to cope with an environment change (or uncertainty) preventing its extinction. However, this ability is not always desirable as can be exemplified by an intratumor heterogeneity which positively correlates with the development of resistance to therapy. Causation of population heterogeneity is therefore in biology and medicine an intensively studied topic. In this paper the evolution of a specific strategy of population diversification, the phenotype switching, is studied at a conceptual level. The presented simulation model studies evolution of a large population of asexual organisms in a time-varying environment represented by a stochastic Markov process. Each organism disposes with a stochastic or nonlinear deterministic switching strategy realized by discrete-time models with evolvable parameters. We demonstrate that under rapidly varying exogenous conditions organisms operate in the vicinity of the bet-hedging strategy, while the deterministic patterns become relevant as the environmental variations are less frequent. Statistical characterization of the steady state regimes of the populations is done using the Hellinger and Kullback–Leibler functional distances and the Hamming distance. - Highlights: • Relation between phenotype switching and environment is studied. • The Markov chain Monte Carlo based model is developed. • Stochastic and deterministic strategies of phenotype switching are utilized. • Statistical measures of the dynamic heterogeneity reveal universal properties. • The results extend to higher lattice dimensions.
Study of selected phenotype switching strategies in time varying environment
Horvath, Denis; Brutovsky, Branislav
2016-03-01
Population heterogeneity plays an important role across many research, as well as the real-world, problems. The population heterogeneity relates to the ability of a population to cope with an environment change (or uncertainty) preventing its extinction. However, this ability is not always desirable as can be exemplified by an intratumor heterogeneity which positively correlates with the development of resistance to therapy. Causation of population heterogeneity is therefore in biology and medicine an intensively studied topic. In this paper the evolution of a specific strategy of population diversification, the phenotype switching, is studied at a conceptual level. The presented simulation model studies evolution of a large population of asexual organisms in a time-varying environment represented by a stochastic Markov process. Each organism disposes with a stochastic or nonlinear deterministic switching strategy realized by discrete-time models with evolvable parameters. We demonstrate that under rapidly varying exogenous conditions organisms operate in the vicinity of the bet-hedging strategy, while the deterministic patterns become relevant as the environmental variations are less frequent. Statistical characterization of the steady state regimes of the populations is done using the Hellinger and Kullback-Leibler functional distances and the Hamming distance.
Time-varying multiplex network: Intralayer and interlayer synchronization
Rakshit, Sarbendu; Majhi, Soumen; Bera, Bidesh K.; Sinha, Sudeshna; Ghosh, Dibakar
2017-12-01
A large class of engineered and natural systems, ranging from transportation networks to neuronal networks, are best represented by multiplex network architectures, namely a network composed of two or more different layers where the mutual interaction in each layer may differ from other layers. Here we consider a multiplex network where the intralayer coupling interactions are switched stochastically with a characteristic frequency. We explore the intralayer and interlayer synchronization of such a time-varying multiplex network. We find that the analytically derived necessary condition for intralayer and interlayer synchronization, obtained by the master stability function approach, is in excellent agreement with our numerical results. Interestingly, we clearly find that the higher frequency of switching links in the layers enhances both intralayer and interlayer synchrony, yielding larger windows of synchronization. Further, we quantify the resilience of synchronous states against random perturbations, using a global stability measure based on the concept of basin stability, and this reveals that intralayer coupling strength is most crucial for determining both intralayer and interlayer synchrony. Lastly, we investigate the robustness of interlayer synchronization against a progressive demultiplexing of the multiplex structure, and we find that for rapid switching of intralayer links, the interlayer synchronization persists even when a large number of interlayer nodes are disconnected.
Tiled Parallel Coordinates for the Visualization of Time-Varying Multichannel EEG Data
Caat, M. ten; Maurits, N.M.; Roerdink, J.B.T.M.
2005-01-01
The field of visualization assists data interpretation in many areas, but some types of data are not manageable by existing visualization techniques. This holds in particular for time-varying multichannel EEG data. No existing technique can simultaneously visualize information from all channels in
Audio Effects Based on Biorthogonal Time-Varying Frequency Warping
Directory of Open Access Journals (Sweden)
Sergio Cavaliere
2001-03-01
Full Text Available We illustrate the mathematical background and musical use of a class of audio effects based on frequency warping. These effects alter the frequency content of a signal via spectral mapping. They can be implemented in dispersive tapped delay lines based on a chain of all-pass filters. In a homogeneous line with first-order all-pass sections, the signal formed by the output samples at a given time is related to the input via the Laguerre transform. However, most musical signals require a time-varying frequency modification in order to be properly processed. Vibrato in musical instruments or voice intonation in the case of vocal sounds may be modeled as small and slow pitch variations. Simulation of these effects requires techniques for time-varying pitch and/or brightness modification that are very useful for sound processing. The basis for time-varying frequency warping is a time-varying version of the Laguerre transformation. The corresponding implementation structure is obtained as a dispersive tapped delay line, where each of the frequency dependent delay element has its own phase response. Thus, time-varying warping results in a space-varying, inhomogeneous, propagation structure. We show that time-varying frequency warping is associated to an expansion over biorthogonal sets generalizing the discrete Laguerre basis. Slow time-varying characteristics lead to slowly varying parameter sequences. The corresponding sound transformation does not suffer from discontinuities typical of delay lines based on unit delays.
Estimation of Time Varying Autoregressive Symmetric Alpha Stable
National Aeronautics and Space Administration — In this work, we present a novel method for modeling time-varying autoregressive impulsive signals driven by symmetric alpha stable distributions. The proposed...
Modeling non-Gaussian time-varying vector autoregressive process
National Aeronautics and Space Administration — We present a novel and general methodology for modeling time-varying vector autoregressive processes which are widely used in many areas such as modeling of chemical...
A Semiparametric Recurrent Events Model with Time-varying Coefficients
Yu, Zhangsheng; Liu, Lei; Bravata, Dawn M.; Williams, Linda S.; Tepper, Robert S.
2013-01-01
SUMMARY We consider a recurrent events model with time-varying coefficients motivated by two clinical applications. A random effects (Gaussian frailty) model is used to describe the intensity of recurrent events. The model can accommodate both time-varying and time-constant coefficients. The penalized spline method is used to estimate the time-varying coefficients. Laplace approximation is used to evaluate the penalized likelihood without a closed form. The smoothing parameters are estimated in a similar way to variance components. We conduct simulations to evaluate the performance of the estimates for both time-varying and time-independent coefficients. We apply this method to analyze two data sets: a stroke study and a child wheeze study. PMID:22903343
Analysis of time-varying psoriasis lesion image patterns
DEFF Research Database (Denmark)
Maletti, Gabriela Mariel; Ersbøll, Bjarne Kjær; Nielsen, Allan Aasbjerg
2004-01-01
The multivariate alteration detection transform is applied to pairs of within and between time varying registered psoriasis image patterns. Color band contribution to the variates explaining maximal change is analyzed....
Design of 2D Time-Varying Vector Fields
Chen, Guoning
2012-10-01
Design of time-varying vector fields, i.e., vector fields that can change over time, has a wide variety of important applications in computer graphics. Existing vector field design techniques do not address time-varying vector fields. In this paper, we present a framework for the design of time-varying vector fields, both for planar domains as well as manifold surfaces. Our system supports the creation and modification of various time-varying vector fields with desired spatial and temporal characteristics through several design metaphors, including streamlines, pathlines, singularity paths, and bifurcations. These design metaphors are integrated into an element-based design to generate the time-varying vector fields via a sequence of basis field summations or spatial constrained optimizations at the sampled times. The key-frame design and field deformation are also introduced to support other user design scenarios. Accordingly, a spatial-temporal constrained optimization and the time-varying transformation are employed to generate the desired fields for these two design scenarios, respectively. We apply the time-varying vector fields generated using our design system to a number of important computer graphics applications that require controllable dynamic effects, such as evolving surface appearance, dynamic scene design, steerable crowd movement, and painterly animation. Many of these are difficult or impossible to achieve via prior simulation-based methods. In these applications, the time-varying vector fields have been applied as either orientation fields or advection fields to control the instantaneous appearance or evolving trajectories of the dynamic effects. © 1995-2012 IEEE.
Directory of Open Access Journals (Sweden)
Chen Bor-Sen
2010-01-01
Full Text Available A recursive maximum-likelihood (RML algorithm for channel estimation under rapidly fading channel and colored noise in a multicarrier code-division multiple-access (MC-CDMA system is proposed in this paper. A moving-average model with exogenous input (MAX is given to describe the transmission channel and colored noise. Based on the pseudoregression method, the proposed RML algorithm can simultaneously estimate the parameters of channel and colored noise. Following the estimation results, these parameters can be used to enhance the minimum mean-square error (MMSE equalizer. Considering high-speed mobile stations, a one-step linear trend predictor is added to improve symbol detection. Simulation results indicate that the proposed RML estimator can track the channel more precisely than the conventional estimator. Meanwhile, the performance of the proposed enhanced MMSE equalizer is robust to the rapidly Rayleigh fading channel under colored noise in the MC-CDMA systems.
Yang, Chang-Yi; Chen, Bor-Sen
2010-12-01
A recursive maximum-likelihood (RML) algorithm for channel estimation under rapidly fading channel and colored noise in a multicarrier code-division multiple-access (MC-CDMA) system is proposed in this paper. A moving-average model with exogenous input (MAX) is given to describe the transmission channel and colored noise. Based on the pseudoregression method, the proposed RML algorithm can simultaneously estimate the parameters of channel and colored noise. Following the estimation results, these parameters can be used to enhance the minimum mean-square error (MMSE) equalizer. Considering high-speed mobile stations, a one-step linear trend predictor is added to improve symbol detection. Simulation results indicate that the proposed RML estimator can track the channel more precisely than the conventional estimator. Meanwhile, the performance of the proposed enhanced MMSE equalizer is robust to the rapidly Rayleigh fading channel under colored noise in the MC-CDMA systems.
Simple reaction time to the onset of time-varying sounds.
Schlittenlacher, Josef; Ellermeier, Wolfgang
2015-10-01
Although auditory simple reaction time (RT) is usually defined as the time elapsing between the onset of a stimulus and a recorded reaction, a sound cannot be specified by a single point in time. Therefore, the present work investigates how the period of time immediately after onset affects RT. By varying the stimulus duration between 10 and 500 msec, this critical duration was determined to fall between 32 and 40 milliseconds for a 1-kHz pure tone at 70 dB SPL. In a second experiment, the role of the buildup was further investigated by varying the rise time and its shape. The increment in RT for extending the rise time by a factor of ten was about 7 to 8 msec. There was no statistically significant difference in RT between a Gaussian and linear rise shape. A third experiment varied the modulation frequency and point of onset of amplitude-modulated tones, producing onsets at different initial levels with differently rapid increase or decrease immediately afterwards. The results of all three experiments results were explained very well by a straightforward extension of the parallel grains model (Miller and Ulrich Cogn. Psychol. 46, 101-151, 2003), a probabilistic race model employing many parallel channels. The extension of the model to time-varying sounds made the activation of such a grain depend on intensity as a function of time rather than a constant level. A second approach by mechanisms known from loudness produced less accurate predictions.
Directory of Open Access Journals (Sweden)
Forouzan Amir R
2007-01-01
Full Text Available Line selection (LS, tone selection (TS, and joint tone-line selection (JTLS partial crosstalk cancellers have been proposed to reduce the online computational complexity of far-end crosstalk (FEXT cancellers in digital subscriber lines (DSL. However, when the crosstalk profile changes rapidly over time, there is an additional requirement that the partial crosstalk cancellers, particularly the LS and JTLS schemes, should also provide a low preprocessing complexity. This is in contrast to the case for perfect crosstalk cancellers. In this paper, we propose two novel channel matrix inversion methods, the approximate inverse (AI and reduced inverse (RI schemes, which reduce the recurrent complexity of the LS and JTLS schemes. Moreover, we propose two new classes of JTLS algorithms, the subsort and Lagrange JTLS algorithms, with significantly lower computational complexity than the recently proposed optimal greedy JTLS scheme. The computational complexity analysis of our algorithms shows that they provide much lower recurrent complexities than the greedy JTLS algorithm, allowing them to work efficiently in very fast time-varying crosstalk environments. Moreover, the analytical and simulation results demonstrate that our techniques are close to the optimal solution from the crosstalk cancellation point of view. The results also reveal that partial crosstalk cancellation is more beneficial in upstream DSL, particularly for short loops.
Energy Technology Data Exchange (ETDEWEB)
Mascarenhas, Ajith Arthur [Univ. of North Carolina, Chapel Hill, NC (United States)
2006-01-01
I present time-varying Reeb graphs as a topological framework to support the analysis of continuous time-varying data. Such data is captured in many studies, including computational fluid dynamics, oceanography, medical imaging, and climate modeling, by measuring physical processes over time, or by modeling and simulating them on a computer. Analysis tools are applied to these data sets by scientists and engineers who seek to understand the underlying physical processes. A popular tool for analyzing scientific datasets is level sets, which are the points in space with a fixed data value s. Displaying level sets allows the user to study their geometry, their topological features such as connected components, handles, and voids, and to study the evolution of these features for varying s. For static data, the Reeb graph encodes the evolution of topological features and compactly represents topological information of all level sets. The Reeb graph essentially contracts each level set component to a point. It can be computed efficiently, and it has several uses: as a succinct summary of the data, as an interface to select meaningful level sets, as a data structure to accelerate level set extraction, and as a guide to remove noise. I extend these uses of Reeb graphs to time-varying data. I characterize the changes to Reeb graphs over time, and develop an algorithm that can maintain a Reeb graph data structure by tracking these changes over time. I store this sequence of Reeb graphs compactly, and call it a time-varying Reeb graph. I augment the time-varying Reeb graph with information that records the topology of level sets of all level values at all times, that maintains the correspondence of level set components over time, and that accelerates the extraction of level sets for a chosen level value and time. Scientific data sampled in space-time must be extended everywhere in this domain using an interpolant. A poor choice of interpolant can create degeneracies that are
Time Varying Market Integration and Expected Rteurns in Emerging Markets
de Jong, F.C.J.M.; de Roon, F.A.
2001-01-01
We use a simple model in which the expected returns in emerging markets depend on their systematic risk as measured by their beta relative to the world portfolio as well as on the level of integration in that market.The level of integration is a time-varying variable that depends on the market value
Overcoming Spurious Regression Using time-Varying Fourier ...
African Journals Online (AJOL)
Non-stationary time series data have been traditionally analyzed in the frequency domain by assuming constant amplitudes regardless of the timelag. A new approach called time-varying amplitude method (TVAM) is presented here. Oscillations are analyzed for changes in the magnitude of Fourier Coefficients which are ...
Multivariate Option Pricing with Time Varying Volatility and Correlations
DEFF Research Database (Denmark)
Rombouts, Jeroen V.K.; Stentoft, Lars Peter
In recent years multivariate models for asset returns have received much attention, in particular this is the case for models with time varying volatility. In this paper we consider models of this class and examine their potential when it comes to option pricing. Specifically, we derive the risk ...
Time-frequency representation based on time-varying ...
Indian Academy of Sciences (India)
A parametric time-frequency representation is presented based on timevarying autoregressive model (TVAR), followed by applications to non-stationary vibration signal processing. The identiﬁcation of time-varying model coefﬁcients and the determination of model order, are addressed by means of neural networks and ...
Time-varying correlation and common structures in volatility
Liu, Yang
2016-01-01
This thesis studies time series properties of the covariance structure of multivariate asset returns. First, the time-varying feature of correlation is investigated at the intraday level with a new correlation model incorporating the intraday correlation dynamics. Second, the thesis develops a
Time-varying Combinations of Predictive Densities using Nonlinear Filtering
M. Billio (Monica); R. Casarin (Roberto); F. Ravazzolo (Francesco); H.K. van Dijk (Herman)
2012-01-01
textabstractWe propose a Bayesian combination approach for multivariate predictive densities which relies upon a distributional state space representation of the combination weights. Several specifications of multivariate time-varying weights are introduced with a particular focus on weight dynamics
Expected optimal feedback with Time-Varying Parameters
Tucci, M.P.; Kendrick, D.A.; Amman, H.M.|info:eu-repo/dai/nl/070970777
2011-01-01
In this paper we derive the closed loop form of the Expected Optimal Feedback rule, sometimes called passive learning stochastic control, with time varying parameters. As such this paper extends the work of Kendrick (1981,2002, Chapter 6) where parameters are assumed to vary randomly around a known
Electricity Futures Prices : Time Varying Sensitivity to Fundamentals
S-E. Fleten (Stein-Erik); R. Huisman (Ronald); M. Kilic (Mehtap); H.P.G. Pennings (Enrico); S. Westgaard (Sjur)
2014-01-01
textabstractThis paper provides insight in the time-varying relation between electricity futures prices and fundamentals in the form of prices of contracts for fossil fuels. As supply curves are not constant and different producers have different marginal costs of production, we argue that the
Mining Graphs for Understanding Time-Varying Volumetric Data.
Gu, Yi; Wang, Chaoli; Peterka, Tom; Jacob, Robert; Kim, Seung Hyun
2016-01-01
A notable recent trend in time-varying volumetric data analysis and visualization is to extract data relationships and represent them in a low-dimensional abstract graph view for visual understanding and making connections to the underlying data. Nevertheless, the ever-growing size and complexity of data demands novel techniques that go beyond standard brushing and linking to allow significant reduction of cognition overhead and interaction cost. In this paper, we present a mining approach that automatically extracts meaningful features from a graph-based representation for exploring time-varying volumetric data. This is achieved through the utilization of a series of graph analysis techniques including graph simplification, community detection, and visual recommendation. We investigate the most important transition relationships for time-varying data and evaluate our solution with several time-varying data sets of different sizes and characteristics. For gaining insights from the data, we show that our solution is more efficient and effective than simply asking users to extract relationships via standard interaction techniques, especially when the data set is large and the relationships are complex. We also collect expert feedback to confirm the usefulness of our approach.
Time varying market efficiency of the GCC stock markets
Charfeddine, Lanouar; Khediri, Karim Ben
2016-02-01
This paper investigates the time-varying levels of weak-form market efficiency for the GCC stock markets over the period spanning from May 2005 to September 2013. We use two empirical approaches: (1) the generalized autoregressive conditional heteroscedasticity in mean (GARCH-M) model with state space time varying parameter (Kalman filter), and (2) a rolling technique sample test of the fractional long memory parameter d. As long memory estimation methods, we use the detrended fluctuation analysis (DFA) technique, the modified R/S statistic, the exact local whittle (ELW) and the feasible Exact Local Whittle (FELW) methods. Moreover, we use the Bai and Perron (1998, 2003) multiple structural breaks technique to test and date the time varying behavior of stock market efficiency. Empirical results show that GCC markets have different degrees of time-varying efficiency, and also have experiencing periods of efficiency improvement. Results also show evidence of structural breaks in all GCC markets. Moreover, we observe that the recent financial shocks such as Arab spring and subprime crises have a significant impact on the time path evolution of market efficiency.
Eshtehardiha, S.; Poudeh, M. Bayati
2008-10-01
Reliable evaluation of distribution systems is of high importance in the maintenance and expansion of these systems. A time-sequential simulation technique is presented in this paper in which the effects of weather conditions and maintenance methods in the assessment of reliable cost of integrated distribution systems are provided. Time-Varying Weight Factors (TVWF) are defined to investigate the effect of weather conditions and present maintenance methods on Failure rates (FR). In fact, the average Failure Rate (FR) is combined with TVWF to provide time-varying repair times (TVRT) for each component. Similarly, the average Repair Time (RT) is also combined with TVWF to produce Time-Varying-Repair Time (TVRT). An experimental distribution system showed that TVFR has more effects on the interruption costs of the sensitive costumers. It has also significant effects on the indices of all costumers. So, it is necessary to consider TVRT in evaluating the reliability of the network cost.
H∞ Control of Four-Wheel-Independent-Drive Electric Vehicles with Random Time-Varying Delays
Directory of Open Access Journals (Sweden)
Gang Qin
2015-01-01
Full Text Available The random time-varying delays would reduce control performance and even deteriorate the EV system. To deal with random time-varying delays and achieve a real-time steady-state response, considering randomness of delay and a rapid response, an H∞-based delay-tolerant linear quadratic regulator (LQR control method based on Taylor series expansion is proposed in this paper. The results of cosimulations with Simulink and CarSim demonstrate the effectiveness of the proposed controller through the control performance of yaw rate, sideslip angle, and the running track. Moreover, the results of comparison with the other controller illustrate the strength of explicitly.
Vesicle biomechanics in a time-varying magnetic field.
Ye, Hui; Curcuru, Austen
2015-01-01
Cells exhibit distortion when exposed to a strong electric field, suggesting that the field imposes control over cellular biomechanics. Closed pure lipid bilayer membranes (vesicles) have been widely used for the experimental and theoretical studies of cellular biomechanics under this electrodeformation. An alternative method used to generate an electric field is by electromagnetic induction with a time-varying magnetic field. References reporting the magnetic control of cellular mechanics have recently emerged. However, theoretical analysis of the cellular mechanics under a time-varying magnetic field is inadequate. We developed an analytical theory to investigate the biomechanics of a modeled vesicle under a time-varying magnetic field. Following previous publications and to simplify the calculation, this model treated the inner and suspending media as lossy dielectrics, the membrane thickness set at zero, and the electric resistance of the membrane assumed to be negligible. This work provided the first analytical solutions for the surface charges, electric field, radial pressure, overall translational forces, and rotational torques introduced on a vesicle by the time-varying magnetic field. Frequency responses of these measures were analyzed, particularly the frequency used clinically by transcranial magnetic stimulation (TMS). The induced surface charges interacted with the electric field to produce a biomechanical impact upon the vesicle. The distribution of the induced surface charges depended on the orientation of the coil and field frequency. The densities of these charges were trivial at low frequency ranges, but significant at high frequency ranges. The direction of the radial force on the vesicle was dependent on the conductivity ratio between the vesicle and the medium. At relatively low frequencies (biomechanics under a time-varying magnetic field. Biological effects of clinical TMS are not likely to occur via alteration of the biomechanics of brain
Zuk, Nathaniel; Delgutte, Bertrand
2017-07-01
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
Oxidation of multiple methionine residues impairs rapid sodium channel inactivation
Kassmann, Mario; Hansel, Alfred; Leipold, Enrico; Birkenbeil, Jan; Lu, Song-Qing; Hoshi, Toshinori; Heinemann, Stefan H.
2010-01-01
Reactive oxygen species (ROS) readily oxidize the sulfur-containing amino acids cysteine and methionine (Met). The impact of Met oxidation on the fast inactivation of the skeletal muscle sodium channel NaV1.4 expressed in human embryonic kidney cells was studied by applying the Met-preferring oxidant chloramine-T (ChT) or by irradiating the ROS-producing dye Lucifer Yellow in the patch pipettes. Both interventions dramatically slowed down inactivation of the sodium channels. Replacement of Met in the Ile-Phe-Met inactivation motif with Leu (M1305L) strongly attenuated the oxidizing effect on inactivation but did not eliminate it completely. Mutagenesis of conserved Met residues in the intracellular linkers connecting the membrane-spanning segments of the channel (M1469L and M1470L) also markedly diminished the oxidation sensitivity of the channel, while that of other conserved Met residues (442, 1139, 1154, 1316) were without any noticeable effect. The results of mutagenesis of results, assays of other NaV channel isoforms (NaV1.2, NaV1.5, NaV1.7) and the kinetics of the oxidation-induced removal of inactivation collectively indicate that multiple Met target residues need to be oxidized to completely impair inactivation. This arrangement using multiple Met residues confers a finely graded oxidative modulation of NaV channels and allows organisms to adapt to a variety of oxidative stress conditions, such as ischemic reperfusion. PMID:18369661
Design of crusher liner based on time - varying uncertainty theory
Tang, J. C.; Shi, B. Q.; Yu, H. J.; Wang, R. J.; Zhang, W. Y.
2017-09-01
This article puts forward the time-dependent design method considering the load fluctuation factors for the liner based on the time-varying uncertainty theory. In this method, the time-varying uncertainty design model of liner is constructed by introducing the parameters that affect the wear rate, the volatility and the drift rate. Based on the design example, the timevarying design outline of the moving cone liner is obtained. Based on the theory of minimum wear, the gap curve of wear resistant cavity is designed, and the optimized cavity is obtained by the combination of the thickness of the cone and the cavity gap. Taking the PYGB1821 multi cylinder hydraulic cone crusher as an example, it is proved that the service life of the new liner is improved by more than 14.3%.
Modelling Time-Varying Volatility in Financial Returns
DEFF Research Database (Denmark)
Amado, Cristina; Laakkonen, Helinä
2014-01-01
The “unusually uncertain” phase in the global financial markets has inspired many researchers to study the effects of ambiguity (or “Knightian uncertainty”) on the decisions made by investors and their implications for the capital markets. We contribute to this literature by using a modified...... being captured by a stable GARCH(1,1) process and the second driven by the level of uncertainty in the financial market....... version of the time-varying GARCH model of Amado and Teräsvirta (2013) to analyze whether the increasing uncertainty has caused excess volatility in the US and European government bond markets. In our model, volatility is multiplicatively decomposed into two time-varying conditional components: the first...
The value premium and time-varying volatility
Li, X.; Brooks, C.; Miffre, J.
2009-01-01
Numerous studies have documented the failure of the static and conditional capital asset pricing models to explain the difference in returns between value and growth stocks. This paper examines the post-1963 value premium by employing a model that captures the time-varying total risk of the value-minus-growth portfolios. Our results show that the time-series of value premia is strongly and positively correlated with its volatility. This conclusion is robust to the criterion used to sort stock...
The Value Premium and Time-Varying Unsystematic Risk
Chris Brooks; Xiafei Li; Joelle Miffre
2007-01-01
Recent research has discussed the possible role of unsystematic risk in explaining equity returns. Simultaneously, but somehow independently, numerous other studies have documented the failure of the static and conditional capital asset pricing models to explain the differences in returns between value and growth stocks. This paper examines the post-1963 value premium by employing a model that captures the time-varying total risk of the value-minus-growth portfolios. In accordance with existi...
Electricity futures prices: time varying sensitivity to fundamentals
Fleten, Stein-Erik; Huisman, Ronald; Kilic, Mehtap; Pennings, Enrico; Westgaard, Sjur
2014-01-01
This paper provides insight into the time-varying relation between electricity futures prices and fundamentals in the form of contract prices for fossil fuels. As supply curves are not constant and different producers have different marginal costs of production, we argue that the relation between the prices of electricity futures and those of underlying fundamentals such as natural gas, coal and emission rights varies over time. We test this view by applying a model that linearly relates elec...
Modeling information diffusion in time-varying community networks
Cui, Xuelian; Zhao, Narisa
2017-12-01
Social networks are rarely static, and they typically have time-varying network topologies. A great number of studies have modeled temporal networks and explored social contagion processes within these models; however, few of these studies have considered community structure variations. In this paper, we present a study of how the time-varying property of a modular structure influences the information dissemination. First, we propose a continuous-time Markov model of information diffusion where two parameters, mobility rate and community attractiveness, are introduced to address the time-varying nature of the community structure. The basic reproduction number is derived, and the accuracy of this model is evaluated by comparing the simulation and theoretical results. Furthermore, numerical results illustrate that generally both the mobility rate and community attractiveness significantly promote the information diffusion process, especially in the initial outbreak stage. Moreover, the strength of this promotion effect is much stronger when the modularity is higher. Counterintuitively, it is found that when all communities have the same attractiveness, social mobility no longer accelerates the diffusion process. In addition, we show that the local spreading in the advantage group has been greatly enhanced due to the agglomeration effect caused by the social mobility and community attractiveness difference, which thus increases the global spreading.
Online dynamic mode decomposition for time-varying systems
Zhang, Hao; Rowley, Clarence; Deem, Eric; Cattafesta, Louis
2017-11-01
Dynamic mode decomposition (DMD) is a popular technique for modal decomposition, flow analysis, and reduced-order modeling. In situations where a system is time varying, one would like to update the system's description online as time evolves. This work provides an efficient method for computing the DMD matrix in real time, updating the approximation of a system's dynamics as new data becomes available. The algorithm does not require storage of past data, and computes the exact DMD matrix using rank-1 updates. A weighting factor that places less weight on older data can be incorporated in a straightforward manner, making the method particularly well suited to time-varying systems. The efficiency of the method is compared against several existing DMD algorithms: for problems in which the state dimension is less than about 200, the proposed algorithm is the most efficient for real-time computation, and it can be orders of magnitude more efficient than the standard DMD algorithm. The method is demonstrated on several examples, including a time-varying linear system and a more complex example using data from a wind tunnel experiment. Supported by AFOSR Grant FA9550-14-1-0289, and by DARPA award HR0011-16-C-0116.
Artificial Bee Colony Algorithm with Time-Varying Strategy
Directory of Open Access Journals (Sweden)
Quande Qin
2015-01-01
Full Text Available Artificial bee colony (ABC is one of the newest additions to the class of swarm intelligence. ABC algorithm has been shown to be competitive with some other population-based algorithms. However, there is still an insufficiency that ABC is good at exploration but poor at exploitation. To make a proper balance between these two conflictive factors, this paper proposed a novel ABC variant with a time-varying strategy where the ratio between the number of employed bees and the number of onlooker bees varies with time. The linear and nonlinear time-varying strategies can be incorporated into the basic ABC algorithm, yielding ABC-LTVS and ABC-NTVS algorithms, respectively. The effects of the added parameters in the two new ABC algorithms are also studied through solving some representative benchmark functions. The proposed ABC algorithm is a simple and easy modification to the structure of the basic ABC algorithm. Moreover, the proposed approach is general and can be incorporated in other ABC variants. A set of 21 benchmark functions in 30 and 50 dimensions are utilized in the experimental studies. The experimental results show the effectiveness of the proposed time-varying strategy.
Sensor trustworthiness in uncertain time varying stochastic environments
Verma, Ajay; Fernandes, Ronald; Vadakkeveedu, Kalyan
2011-06-01
Persistent surveillance applications require unattended sensors deployed in remote regions to track and monitor some physical stimulant of interest that can be modeled as output of time varying stochastic process. However, the accuracy or the trustworthiness of the information received through a remote and unattended sensor and sensor network cannot be readily assumed, since sensors may get disabled, corrupted, or even compromised, resulting in unreliable information. The aim of this paper is to develop information theory based metric to determine sensor trustworthiness from the sensor data in an uncertain and time varying stochastic environment. In this paper we show an information theory based determination of sensor data trustworthiness using an adaptive stochastic reference sensor model that tracks the sensor performance for the time varying physical feature, and provides a baseline model that is used to compare and analyze the observed sensor output. We present an approach in which relative entropy is used for reference model adaptation and determination of divergence of the sensor signal from the estimated reference baseline. We show that that KL-divergence is a useful metric that can be successfully used in determination of sensor failures or sensor malice of various types.
Social contagions on time-varying community networks
Liu, Mian-Xin; Wang, Wei; Liu, Ying; Tang, Ming; Cai, Shi-Min; Zhang, Hai-Feng
2017-05-01
Time-varying community structures exist widely in real-world networks. However, previous studies on the dynamics of spreading seldom took this characteristic into account, especially those on social contagions. To study the effects of time-varying community structures on social contagions, we propose a non-Markovian social contagion model on time-varying community networks based on the activity-driven network model. A mean-field theory is developed to analyze the proposed model. Through theoretical analyses and numerical simulations, two hierarchical features of the behavior adoption processes are found. That is, when community strength is relatively large, the behavior can easily spread in one of the communities, while in the other community the spreading only occurs at higher behavioral information transmission rates. Meanwhile, in spatial-temporal evolution processes, hierarchical orders are observed for the behavior adoption. Moreover, under different information transmission rates, three distinctive patterns are demonstrated in the change of the whole network's final adoption proportion along with the growing community strength. Within a suitable range of transmission rate, an optimal community strength can be found that can maximize the final adoption proportion. Finally, compared with the average activity potential, the promoting or inhibiting of social contagions is much more influenced by the number of edges generated by active nodes.
On enhanced time-varying distributed H systems
Directory of Open Access Journals (Sweden)
Sergey Verlan
2002-11-01
Full Text Available An enhanced time-varying distributed H system (ETVDH system is a slightly different definition of the time-varying distributed H system (TVDH system [9] and it was proposed by M. Margenstern and Yu. Rogozhin in [4] under the name of "extended time-varying distributed H system''. The main difference is that the components of the ETVDH system are H systems and therefore splicing rules may be applied more than once as it is done in TVDH systems. This leads to difficulties in investigating the behavior of such systems because they have a higher level of parallelism. It is proved that ETVDH systems of degree 2 (i.e. with 2 components generate all recursively enumerable languages in a sequential way [7] and that ETVDH systems of degree 4 generate all recursively enumerable languages in a "parallel'' way, modelling a formal type-0 grammar [11]. In this paper we improve the last result and we present an ETVDH system of degree 3 which generates all recursively enumerable languages modelling type-0 formal grammars. The problem of the existence of ETVDH systems of degree 2 which generate all recursively enumerable languages in a "parallel'' way is left open.
Time-varying value of electric energy efficiency
Energy Technology Data Exchange (ETDEWEB)
Mims, Natalie A.; Eckman, Tom; Goldman, Charles
2017-06-30
Electric energy efficiency resources save energy and may reduce peak demand. Historically, quantification of energy efficiency benefits has largely focused on the economic value of energy savings during the first year and lifetime of the installed measures. Due in part to the lack of publicly available research on end-use load shapes (i.e., the hourly or seasonal timing of electricity savings) and energy savings shapes, consideration of the impact of energy efficiency on peak demand reduction (i.e., capacity savings) has been more limited. End-use load research and the hourly valuation of efficiency savings are used for a variety of electricity planning functions, including load forecasting, demand-side management and evaluation, capacity and demand response planning, long-term resource planning, renewable energy integration, assessing potential grid modernization investments, establishing rates and pricing, and customer service. This study reviews existing literature on the time-varying value of energy efficiency savings, provides examples in four geographically diverse locations of how consideration of the time-varying value of efficiency savings impacts the calculation of power system benefits, and identifies future research needs to enhance the consideration of the time-varying value of energy efficiency in cost-effectiveness screening analysis. Findings from this study include: -The time-varying value of individual energy efficiency measures varies across the locations studied because of the physical and operational characteristics of the individual utility system (e.g., summer or winter peaking, load factor, reserve margin) as well as the time periods during which savings from measures occur. -Across the four locations studied, some of the largest capacity benefits from energy efficiency are derived from the deferral of transmission and distribution system infrastructure upgrades. However, the deferred cost of such upgrades also exhibited the greatest range
Timed arrays wideband and time varying antenna arrays
Haupt, Randy L
2015-01-01
Introduces timed arrays and design approaches to meet the new high performance standards The author concentrates on any aspect of an antenna array that must be viewed from a time perspective. The first chapters briefly introduce antenna arrays and explain the difference between phased and timed arrays. Since timed arrays are designed for realistic time-varying signals and scenarios, the book also reviews wideband signals, baseband and passband RF signals, polarization and signal bandwidth. Other topics covered include time domain, mutual coupling, wideband elements, and dispersion. The auth
Multireceiver Acoustic Communications in Time-Varying Environments
2014-06-01
AND CONTRIBUTION ..........................53 B. RECOMMENDATIONS FOR FURTHER WORK...................................53 APPENDIX A. MATLAB CODES...different frequencies, it depends on various factors like wind, wave actions, shipping, rainfall, marine animals, and seismic activities. For the...environments. 55 APPENDIX A. MATLAB CODES A. IMPULSE RESPONSE OF RAYLEIGH MULTIPATH FADING CHANNEL The impulse response of the channel
Taniguchi, Kristine; Biggs, Trent; Langendoen, Eddy; Castillo, Carlos; Gudiño, Napoleon; Yuan, Yongping; Liden, Douglas
2016-04-01
Urban-induced erosion in Tijuana, Mexico, has led to excessive sediment deposition in the Tijuana Estuary in the United States. Urban areas in developing countries, in contrast to developed countries, are characterized by much lower proportions of vegetation and impervious surfaces due to limited access to urban services such as road paving and landscaping, and larger proportions of exposed soils. In developing countries, traditional watershed scale variables such as impervious surfaces may not be good predictors of channel enlargement. In this research, we surveyed the stream channel network of an erodible tributary of the Tijuana River Watershed, Los Laureles Canyon, at 125 locations, including repeat surveys from 2008. Structure from Motion (SfM) and 3D photo-reconstruction techniques were used to create digital terrain models of stream reaches upstream and downstream of channel hardpoints. Channels are unstable downstream of hardpoints, with incision up to 2 meters and widening up to 12 meters. Coordinated channelization is essential to avoid piece-meal approaches that lead to channel degradation. Watershed impervious area is not a good predictor of channel erosion due to the overriding importance of hardpoints and likely to the high sediment supply from the unpaved roads which prevents channel erosion throughout the stream network.
Time-varying risk aversion. An application to energy hedging
Energy Technology Data Exchange (ETDEWEB)
Cotter, John [Centre for Financial Markets, School of Business, University College Dublin, Blackrock, Co. Dublin (Ireland); Hanly, Jim [School of Accounting and Finance, Dublin Institute of Technology, Dublin 2 (Ireland)
2010-03-15
Risk aversion is a key element of utility maximizing hedge strategies; however, it has typically been assigned an arbitrary value in the literature. This paper instead applies a GARCH-in-Mean (GARCH-M) model to estimate a time-varying measure of risk aversion that is based on the observed risk preferences of energy hedging market participants. The resulting estimates are applied to derive explicit risk aversion based optimal hedge strategies for both short and long hedgers. Out-of-sample results are also presented based on a unique approach that allows us to forecast risk aversion, thereby estimating hedge strategies that address the potential future needs of energy hedgers. We find that the risk aversion based hedges differ significantly from simpler OLS hedges. When implemented in-sample, risk aversion hedges for short hedgers outperform the OLS hedge ratio in a utility based comparison. (author)
Poverty Index With Time Varying Consumption and Income Distributions
Chattopadhyay, Amit K; Mallick, Sushanta K
2016-01-01
In a recent work (Chattopadhyay, A. K. et al, Europhys. Lett. {\\bf 91}, 58003, 2010) based on food consumption statistics, we showed how a stochastic agent based model could represent the time variation of the income distribution statistics in a developing economy, thereby defining an alternative \\enquote{poverty index} (PI) that largely agreed with poverty gap index data. This PI used two variables, the probability density function of the income statistics and a consumption deprivation (CD) function, representing the shortfall in the minimum consumption needed for survival. Since the time dependence of the CD function was introduced there through data extrapolation only and not through an endogenous time dependent series, this model left unexplained how the minimum consumption needed for survival varies with time. The present article overcomes these limitations and arrives at a new unified theoretical structure through time varying consumption and income distributions where trade is only allowed when the inc...
Controlling the Quantum State with a time varying potential.
Carrasco, Sebastián; Rogan, José; Valdivia, Juan Alejandro
2017-10-16
The problem of controlling the quantum state of a system is investigated using a time varying potential. As a concrete example we study the problem of a particle in a box with a periodically oscillating infinite square-well potential, from which we obtain results that can be applied to systems with periodically oscillating boundary conditions. We derive an analytic expression for the frequencies of resonance between states, and against standard intuition, we show how to use this behavior to control the quantum state of the system at will. In particular, we offer as an example the transition from the ground state to the first excited state of the square well potential. At first sight, it may be counter intuitive that we can control the state of such a quantum Hamiltonian, as the Schrödinger equation conserves the norm of the wave function. In this manuscript, we show how that can be achieved.
Epidemic spreading in time-varying community networks
Energy Technology Data Exchange (ETDEWEB)
Ren, Guangming, E-mail: wangxy@dlut.edu.cn, E-mail: ren-guang-ming@163.com [School of Electronic and Information, Guangdong Polytechnic Normal University, Guangzhou 510665 (China); Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024 (China); Wang, Xingyuan, E-mail: wangxy@dlut.edu.cn, E-mail: ren-guang-ming@163.com [Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024 (China)
2014-06-15
The spreading processes of many infectious diseases have comparable time scale as the network evolution. Here, we present a simple networks model with time-varying community structure, and investigate susceptible-infected-susceptible epidemic spreading processes in this model. By both theoretic analysis and numerical simulations, we show that the efficiency of epidemic spreading in this model depends intensively on the mobility rate q of the individuals among communities. We also find that there exists a mobility rate threshold q{sub c}. The epidemic will survive when q > q{sub c} and die when q < q{sub c}. These results can help understanding the impacts of human travel on the epidemic spreading in complex networks with community structure.
Bilateral Teleoperation in Cartesian Space with Time-Varying Delay
Directory of Open Access Journals (Sweden)
Zhang Chen
2012-10-01
Full Text Available The bilateral control of a teleoperator in Cartesian space with time-varying delay is studied in this paper. Compared with the traditional joint-space teleoperation mode, bilateral control in Cartesian space has advantages when dealing with the kinematically dissimilar (KDS teleoperation systems. A Cartesian space-based PD-like bilateral controller with dissipation factors is designed. Considering the fact that attitude errors derived by rotation matrix cannot be directly used for PD control, a quaternion-based approach is adopted to calculate the attitude errors in Cartesian space. In order to overcome the instability brought about by communication delay, local damping components are employed at both ends of the teleoperator system. The variation of time delay may generate extra energy and influence the stability of the system, thus dissipation factors are introduced into the controller. The stability of the proposed bilateral controller is proved and the simulations show the effectiveness of the approach.
Time-varying Capital Requirements and Disclosure Rules
DEFF Research Database (Denmark)
Kragh, Jonas; Rangvid, Jesper
Unique and confidential Danish data allow us to identify how changes in disclosure requirements and bank-specific time-varying capital requirements affect banks' lending and capital accumu-lation decisions. We find that banks increase their capital ratios after capital requirements are increased......, implying that resilience in the banking system is also increased. The increase in capital ratios is partly due to a modest reduction in lending. Using a policy changes, we show that banks react stronger to changes in capital requirements when these are public. Our results further suggest that the impact...... of capital requirements differ for small and large banks. Large banks raise their capital ratios more, reduce lending less, and accumulate more new capital compared to small banks....
Circular motion analysis of time-varying bioimpedance.
Sanchez, B; Louarroudi, E; Rutkove, S B; Pintelon, R
2015-11-01
This paper presents a step forward towards the analysis of a linear periodically time-varying (PTV) bioimpedance ZPTV(jw, t), which is an important subclass of a linear time-varying (LTV) bioimpedance. Similarly to the Fourier coefficients of a periodic signal, a PTV impedance can be decomposed into frequency dependent impedance phasors, [Formula: see text], that are rotating with an angular speed of wr = 2πr/TZ. The vector length of these impedance phasors corresponds to the amplitude of the rth-order harmonic impedance |Zr( jw)| and the initial phase is given by Φr(w, t0) = [Symbol: see text]Zr( jw) + 2πrt0/TZ, with t0∈[0, T] being a time instant within the measurement time T. The impedance period TZ stands for the cycle length of the bio-system under investigation; for example, the elapsed time between two consecutive R-waves in the electrocardiogram or the breathing periodicity in case of the heart or lungs, respectively. First, it is demonstrated that the harmonic impedance phasor [Formula: see text], at a particular measured frequency k, can be represented by a rotating phasor, leading to the so-called circular motion analysis technique. Next, the two dimensional (2D) representation of the harmonic impedance phasors is then extended to a three-dimensional (3D) coordinate system by taking into account the frequency dependence. Finally, we introduce a new visualizing tool to summarize the frequency response behavior of ZPTV( jw, t) into a single 3D plot using the local Frenet-Serret frame. This novel 3D impedance representation is then compared with the 3D Nyquist representation of a PTV impedance. The concepts are illustrated through real measurements conducted on a PTV RC-circuit.
Directory of Open Access Journals (Sweden)
Scinob Kuroki
Full Text Available An Asian spice, Szechuan pepper (sanshool, is well known for the tingling sensation it induces on the mouth and on the lips. Electrophysiological studies have revealed that its active ingredient can induce firing of mechanoreceptor fibres that typically respond to mechanical vibration. Moreover, a human behavioral study has reported that the perceived frequency of sanshool-induced tingling matches with the preferred frequency range of the tactile rapidly adapting (RA channel, suggesting the contribution of sanshool-induced RA channel firing to its unique perceptual experience. However, since the RA channel may not be the only channel activated by sanshool, there could be a possibility that the sanshool tingling percept may be caused in whole or in part by other sensory channels. Here, by using a perceptual interference paradigm, we show that the sanshool-induced RA input indeed contributes to the human tactile processing. The absolute detection thresholds for vibrotactile input were measured with and without sanshool application on the fingertip. Sanshool significantly impaired detection of vibrations at 30 Hz (RA channel dominant frequency, but did not impair detection of higher frequency vibrations at 240 Hz (Pacinian-corpuscle (PC channel dominant frequency or lower frequency vibrations at 1 Hz (slowly adapting 1 (SA1 channel dominant frequency. These results show that the sanshool induces a peripheral RA channel activation that is relevant for tactile perception. This anomalous activation of RA channels may contribute to the unique tingling experience of sanshool.
Time-varying trends of global vegetation activity
Pan, N.; Feng, X.; Fu, B.
2016-12-01
Vegetation plays an important role in regulating the energy change, water cycle and biochemical cycle in terrestrial ecosystems. Monitoring the dynamics of vegetation activity and understanding their driving factors have been an important issue in global change research. Normalized Difference Vegetation Index (NDVI), an indicator of vegetation activity, has been widely used in investigating vegetation changes at regional and global scales. Most studies utilized linear regression or piecewise linear regression approaches to obtain an averaged changing rate over a certain time span, with an implicit assumption that the trend didn't change over time during that period. However, no evidence shows that this assumption is right for the non-linear and non-stationary NDVI time series. In this study, we adopted the multidimensional ensemble empirical mode decomposition (MEEMD) method to extract the time-varying trends of NDVI from original signals without any a priori assumption of their functional form. Our results show that vegetation trends are spatially and temporally non-uniform during 1982-2013. Most vegetated area exhibited greening trends in the 1980s. Nevertheless, the area with greening trends decreased over time since the early 1990s, and the greening trends have stalled or even reversed in many places. Regions with browning trends were mainly located in southern low latitudes in the 1980s, whose area decreased before the middle 1990s and then increased at an accelerated rate. The greening-to-browning reversals were widespread across all continents except Oceania (43% of the vegetated areas), most of which happened after the middle 1990s. In contrast, the browning-to-greening reversals occurred in smaller area and earlier time. The area with monotonic greening and browning trends accounted for 33% and 5% of the vegetated area, respectively. By performing partial correlation analyses between NDVI and climatic elements (temperature, precipitation and cloud cover
Innovation diffusion on time-varying activity driven networks
Rizzo, Alessandro; Porfiri, Maurizio
2016-01-01
Since its introduction in the 1960s, the theory of innovation diffusion has contributed to the advancement of several research fields, such as marketing management and consumer behavior. The 1969 seminal paper by Bass [F.M. Bass, Manag. Sci. 15, 215 (1969)] introduced a model of product growth for consumer durables, which has been extensively used to predict innovation diffusion across a range of applications. Here, we propose a novel approach to study innovation diffusion, where interactions among individuals are mediated by the dynamics of a time-varying network. Our approach is based on the Bass' model, and overcomes key limitations of previous studies, which assumed timescale separation between the individual dynamics and the evolution of the connectivity patterns. Thus, we do not hypothesize homogeneous mixing among individuals or the existence of a fixed interaction network. We formulate our approach in the framework of activity driven networks to enable the analysis of the concurrent evolution of the interaction and individual dynamics. Numerical simulations offer a systematic analysis of the model behavior and highlight the role of individual activity on market penetration when targeted advertisement campaigns are designed, or a competition between two different products takes place.
Opinion formation with time-varying bounded confidence.
Zhang, YunHong; Liu, QiPeng; Zhang, SiYing
2017-01-01
When individuals in social groups communicate with one another and are under the influence of neighbors' opinions, they typically revise their own opinions to adapt to such peer opinions. The individual threshold of bounded confidence will thus be affected by both a change in individual confidence and by neighbor influence. Individuals thus update their own opinions with new bounded confidence, while their updated opinions also influence their neighbors' opinions. Based on this reasoned factual assumption, we propose an opinion dynamics model with time-varying bounded confidence. A directed network is formed by the rule of the individual bounded confidence threshold. The threshold of individual bounded confidence involves both confidence variation and the in/out degree of the individual node. When the confidence variation is greater, an individual's confidence in persisting in his own opinion in interactions is weaker, and the individual is more likely to adopt neighbors' opinions. In networks, the in/out degree is determined by individual neighbors. Our main research involves the process of opinion evolution and the basic laws of opinion cluster formation. Group opinions converge exponentially to consensus with stable neighbors. An individual opinion evolution is determined by the average neighbor opinion effect strength. We also explore the conditions involved in forming a stable neighbor relationship and the influence of the confidence variation in the convergence of the threshold of bounded confidence. The results show that the influence on opinion evolution is greater with increased confidence variation.
Complexity Variability Assessment of Nonlinear Time-Varying Cardiovascular Control
Valenza, Gaetano; Citi, Luca; Garcia, Ronald G.; Taylor, Jessica Noggle; Toschi, Nicola; Barbieri, Riccardo
2017-02-01
The application of complex systems theory to physiology and medicine has provided meaningful information about the nonlinear aspects underlying the dynamics of a wide range of biological processes and their disease-related aberrations. However, no studies have investigated whether meaningful information can be extracted by quantifying second-order moments of time-varying cardiovascular complexity. To this extent, we introduce a novel mathematical framework termed complexity variability, in which the variance of instantaneous Lyapunov spectra estimated over time serves as a reference quantifier. We apply the proposed methodology to four exemplary studies involving disorders which stem from cardiology, neurology and psychiatry: Congestive Heart Failure (CHF), Major Depression Disorder (MDD), Parkinson’s Disease (PD), and Post-Traumatic Stress Disorder (PTSD) patients with insomnia under a yoga training regime. We show that complexity assessments derived from simple time-averaging are not able to discern pathology-related changes in autonomic control, and we demonstrate that between-group differences in measures of complexity variability are consistent across pathologies. Pathological states such as CHF, MDD, and PD are associated with an increased complexity variability when compared to healthy controls, whereas wellbeing derived from yoga in PTSD is associated with lower time-variance of complexity.
Stability of stationary and time-varying nongyrotropic particle distributions
Directory of Open Access Journals (Sweden)
A. L. Brinca
Full Text Available The ubiquity of nongyrotropic particle populations in space plasmas warrants the study of their characteristics, in particular their stability. The unperturbed nongyrotropic distribution functions in homogeneous media without sources and sinks (closed phase space must be rotating and time-varying (TNG, whereas consideration of open phase spaces allows for the occurrence of homogeneous and stationary distributions (SNG. The free energy brought about by the introduction of gyrophase organization in a particle population can destabilize otherwise thoroughly stable magnetoplasmas (or, a fortiori, enhance pre-existing gyrotropic instabilities and feed intense wave growth both in TNG and SNG environments: The nongyrotropic (electron or ion species can originate unstable coupling among the gyrotropic characteristic waves. The stability properties of these two types of homogeneous nongyrotropy shall be contrasted for parallel (with respect to the ambient magnetic field and perpendicular propagation, and their potential role as wave activity sources shall be illustrated resorting to solutions of the appropriate dispersion equations and numerical simulations.
Key words. Space plasma physics (waves and instabilities · Magnetospheric physics (plasma waves and instabilities · Interplanetary physics (plasma waves and turbulence
On the Anonymity Risk of Time-Varying User Profiles
Directory of Open Access Journals (Sweden)
Silvia Puglisi
2017-04-01
Full Text Available Websites and applications use personalisation services to profile their users, collect their patterns and activities and eventually use this data to provide tailored suggestions. User preferences and social interactions are therefore aggregated and analysed. Every time a user publishes a new post or creates a link with another entity, either another user, or some online resource, new information is added to the user profile. Exposing private data does not only reveal information about single users’ preferences, increasing their privacy risk, but can expose more about their network that single actors intended. This mechanism is self-evident in social networks where users receive suggestions based on their friends’ activities. We propose an information-theoretic approach to measure the differential update of the anonymity risk of time-varying user profiles. This expresses how privacy is affected when new content is posted and how much third-party services get to know about the users when a new activity is shared. We use actual Facebook data to show how our model can be applied to a real-world scenario.
Microstructural Model of Ignition for Time Varying Loading Conditions
Browning, Richard V.; Scammon, Richard J.
2002-07-01
A micro-mechanical based model of ignition was developed about five years ago based on a simple inter-granular friction model of mechanical dissipation coupled with a fit to extensive direct numerical simulations of the resulting thermally induced decomposition. The chemical model used was the McGuire-Tarver ODTX based model for HMX decomposition. The resulting power law type model has been reasonably successful in predicting threshold conditions for Steven type experiments. The final power law form was obtained by assuming a constant time history for both the pressure and shear strain rate, resulting in time independent loading conditions for the chemical model. Here we propose to extend the model to handle time varying loading conditions. This is done using a linear operator that models reactive heat transfer simulations done for a wide variety of loading conditions. The linear operator is represented by a convolution integral with Prony series kernel form for efficient numerical implementation. To complete the model the same inter-granular friction model used previously is employed. Comparisons are made with results of numerical simulations and experiments. The technique used here is based on the notion of linearizing the reactive heat transfer problem. Although the chemical model involves four reactions and is highly nonlinear, we effectively linearize the problem around ignition conditions with a linear operator fit. We use a simple power law approximation that gives useful accuracy over at least 4 orders of magnitude in time and fluence. A non-dimensional scaling method is used to determine the final form. We believe the techniques used here could also be used with more detailed chemical models and with other types of mechanical dissipation models.
Hydrodynamic simulations of accretion flows with time-varying viscosity
Roy, Abhishek; Chakrabarti, Sandip K.
2017-12-01
X-ray outbursts of stellar-mass black hole candidates are believed to be due to a sudden rise in viscosity, which transports angular momentum efficiently and increases the accretion rates, causing higher X-ray flux. After the viscosity is reduced, the outburst subsides and the object returns back to the pre-outburst quiescence stage. In the absence of a satisfactory understanding of the physical mechanism leading to such a sharp time dependence of viscous processes, we perform numerical simulations where we include the rise and fall of a viscosity parameter at an outer injection grid, assumed to be located at the accumulation radius where matter from the companion is piled up before being released by enhanced viscosity. We use a power-law radial dependence of the viscosity parameter (α ˜ rɛ), but the exponent (ɛ) is allowed to vary with time to mimic a fast rise and decay of the viscosity parameter. Since X-ray spectra of a black hole candidate can be explained by a Keplerian disc component in the presence of a post-shock region of an advective flow, our goal here is also to understand whether the flow configurations required to explain the spectral states of an outbursting source could be obtained by a time-varying viscosity. We present the results of our simulations to prove that low-angular-momentum (sub-Keplerian) advective flows do form a Keplerian disc in the pre-shock region when the viscosity is enhanced, which disappears on a much longer time-scale after the viscosity is withdrawn. From the variation of the Keplerian disc inside an advective halo, we believe that our result, for the first time, is able to simulate the two-component advective flow dynamics during an entire X-ray outburst and explain the observed hysteresis effects in the hardness-intensity diagram.
Estimating time-varying RSA to examine psychophysiological linkage of marital dyads.
Gates, Kathleen M; Gatzke-Kopp, Lisa M; Sandsten, Maria; Blandon, Alysia Y
2015-08-01
One of the primary tenets of polyvagal theory dictates that parasympathetic influence on heart rate, often estimated by respiratory sinus arrhythmia (RSA), shifts rapidly in response to changing environmental demands. The current standard analytic approach of aggregating RSA estimates across time to arrive at one value fails to capture this dynamic property within individuals. By utilizing recent methodological developments that enable precise RSA estimates at smaller time intervals, we demonstrate the utility of computing time-varying RSA for assessing psychophysiological linkage (or synchrony) in husband-wife dyads using time-locked data collected in a naturalistic setting. © 2015 Society for Psychophysiological Research.
Effects of storm waves on rapid deposition of sediment in the Yangtze Estuary channel
Directory of Open Access Journals (Sweden)
Xu Fumin
2008-03-01
Full Text Available Recent research on short-term topographic change in the Yangtze Estuary channel under storm surge conditions is briefly summarized. The mild-slope, Boussinesq and action balance equations are compared and analyzed. The action balance equation, SWAN, was used as a wave numerical model to forecast strong storm waves in the Yangtze Estuary. The spherical coordinate system and source terms used in the equation are described in this paper. The significant wave height and the wave orbital motion velocity near the bottom of the channel during 20 m/s winds in the EES direction were simulated, and the model was calibrated with observation data of winds and waves generated by Tropical Cyclone 9912. The distribution of critical velocity for incipient motion along the bottom was computed according to the threshold velocity formula for bottom sediment. The mechanism of rapid deposition is analyzed based on the difference between the root-mean-square value of the near-bottom wave orbital motion velocity and the bottom critical tractive velocity. The results show that a large amount of bottom sediments from Hengsha Shoal and Jiuduan Shoal are lifted into the water body when 20 m/s wind is blowing in the EES direction. Some of the sediments may enter the channel with the cross-channel current, causing serious rapid deposition. Finally, the tendency of the storm to induce rapid deposition in the Yangtze Estuary channel zone is analyzed.
Sukas, S.; Erson, Ayse Elif; Sert, Cuneyt; Kulah, Haluk
2008-01-01
A new dual channel micro-electrophoresis system for rapid mutation detection based on heteroduplex analysis was designed and implemented. Mutation detection was successfully achieved in a total separation length of 250 μm in less than 3 min for a 590 bp DNA sample harboring a 3 bp mutation causing
Modeling the time--varying subjective quality of HTTP video streams with rate adaptations.
Chen, Chao; Choi, Lark Kwon; de Veciana, Gustavo; Caramanis, Constantine; Heath, Robert W; Bovik, Alan C
2014-05-01
Newly developed hypertext transfer protocol (HTTP)-based video streaming technologies enable flexible rate-adaptation under varying channel conditions. Accurately predicting the users' quality of experience (QoE) for rate-adaptive HTTP video streams is thus critical to achieve efficiency. An important aspect of understanding and modeling QoE is predicting the up-to-the-moment subjective quality of a video as it is played, which is difficult due to hysteresis effects and nonlinearities in human behavioral responses. This paper presents a Hammerstein-Wiener model for predicting the time-varying subjective quality (TVSQ) of rate-adaptive videos. To collect data for model parameterization and validation, a database of longer duration videos with time-varying distortions was built and the TVSQs of the videos were measured in a large-scale subjective study. The proposed method is able to reliably predict the TVSQ of rate adaptive videos. Since the Hammerstein-Wiener model has a very simple structure, the proposed method is suitable for online TVSQ prediction in HTTP-based streaming.
2017-10-25
competitively low computational burden. It is hoped that the compactness of this mathematical representation will facilitate more rapid development... Literature Survey ................................................................................................... 2 2. MATHEMATICAL BACKGROUND...approach to modeling clutter which has not received much attention in the literature is to use tools from linear time-varying system theory. A linear
Gendron, Paul J
2017-04-01
A hierarchical Gaussian mixture model has been proposed to characterize sparse space-time varying shallow water acoustic response functions [Gendron, J. Acoust. Soc. Am. 139, 1923-1937 (2016)]. Considered here is an extension of this model to a uniform linear vertical array in order to provide an empirical validation of the mixture model for receivers of small aperture. An acoustic environment between source and moving receiver is predicated on a small proportion of relatively coherent paths obeying an ensemble frequency-angle-Doppler distribution. Provided are quantile-quantile plots of the discrete mixture model versus the empirical channel coefficients that lend credence to its use as a sparse model for acoustic response functions.
Ghumare, Eshwar; Schrooten, Maarten; Vandenberghe, Rik; Dupont, Patrick
2015-08-01
Kalman filter approaches are widely applied to derive time varying effective connectivity from electroencephalographic (EEG) data. For multi-trial data, a classical Kalman filter (CKF) designed for the estimation of single trial data, can be implemented by trial-averaging the data or by averaging single trial estimates. A general linear Kalman filter (GLKF) provides an extension for multi-trial data. In this work, we studied the performance of the different Kalman filtering approaches for different values of signal-to-noise ratio (SNR), number of trials and number of EEG channels. We used a simulated model from which we calculated scalp recordings. From these recordings, we estimated cortical sources. Multivariate autoregressive model parameters and partial directed coherence was calculated for these estimated sources and compared with the ground-truth. The results showed an overall superior performance of GLKF except for low levels of SNR and number of trials.
Nonlinear systems time-varying parameter estimation: Application to induction motors
Energy Technology Data Exchange (ETDEWEB)
Kenne, Godpromesse [Laboratoire d' Automatique et d' Informatique Appliquee (LAIA), Departement de Genie Electrique, IUT FOTSO Victor, Universite de Dschang, B.P. 134 Bandjoun (Cameroon); Ahmed-Ali, Tarek [Ecole Nationale Superieure des Ingenieurs des Etudes et Techniques d' Armement (ENSIETA), 2 Rue Francois Verny, 29806 Brest Cedex 9 (France); Lamnabhi-Lagarrigue, F. [Laboratoire des Signaux et Systemes (L2S), C.N.R.S-SUPELEC, Universite Paris XI, 3 Rue Joliot Curie, 91192 Gif-sur-Yvette (France); Arzande, Amir [Departement Energie, Ecole Superieure d' Electricite-SUPELEC, 3 Rue Joliot Curie, 91192 Gif-sur-Yvette (France)
2008-11-15
In this paper, an algorithm for time-varying parameter estimation for a large class of nonlinear systems is presented. The proof of the convergence of the estimates to their true values is achieved using Lyapunov theories and does not require that the classical persistent excitation condition be satisfied by the input signal. Since the induction motor (IM) is widely used in several industrial sectors, the algorithm developed is potentially useful for adjusting the controller parameters of variable speed drives. The method proposed is simple and easily implementable in real-time. The application of this approach to on-line estimation of the rotor resistance of IM shows a rapidly converging estimate in spite of measurement noise, discretization effects, parameter uncertainties (e.g. inaccuracies on motor inductance values) and modeling inaccuracies. The robustness analysis for this IM application also revealed that the proposed scheme is insensitive to the stator resistance variations within a wide range. The merits of the proposed algorithm in the case of on-line time-varying rotor resistance estimation are demonstrated via experimental results in various operating conditions of the induction motor. The experimental results obtained demonstrate that the application of the proposed algorithm to update on-line the parameters of an adaptive controller (e.g. IM and synchronous machines adaptive control) can improve the efficiency of the industrial process. The other interesting features of the proposed method include fault detection/estimation and adaptive control of IM and synchronous machines. (author)
Khalil, I.S.M.; Abass, Hazem; Shoukry, Mostafa; Klingner, Anke; El-Nashar, Rasha M.; Serry, Mohamed; Misra, Sarthak
2016-01-01
Targeted therapy using magnetic microparticles and nanoparticles has the potential to mitigate the negative side-effects associated with conventional medical treatment. Major technological challenges still need to be addressed in order to translate these particles into in vivo applications. For
Li, Huaqing; Huang, Chicheng; Chen, Guo; Liao, Xiaofeng; Huang, Tingwen
2017-03-31
This paper considers solving a class of optimization problems which are modeled as the sum of all agents' convex cost functions and each agent is only accessible to its individual function. Communication between agents in multiagent networks is assumed to be limited: each agent can only interact information with its neighbors by using time-varying communication channels with limited capacities. A technique which overcomes the limitation is to implement a quantization process to the interacted information. The quantized information is first encoded as a binary sequence at the side of each agent before sending. After the binary sequence is received by the neighboring agent, corresponding decoding scheme is utilized to resume the original information with a certain degree of error which is caused by the quantization process. With the availability of each agent's encoding states (associated with its out-channels) and decoding states (associated with its in-channels), we devise a set of distributed optimization algorithms that generate two iterative sequences, one of which converges to the optimal solution and the other of which reaches to the optimal value. We prove that if the parameters satisfy some mild conditions, the quantization errors are bounded and the consensus optimization can be achieved. How to minimize the number of quantization level of each connected communication channel in fixed networks is also explored thoroughly. It is found that, by properly choosing system parameters, one bit information exchange suffices to ensure consensus optimization. Finally, we present two numerical simulation experiments to illustrate the efficacy of the algorithms as well as to validate the theoretical findings.
A Comparison of Evolutionary Algorithms for Tracking Time-Varying Recursive Systems
Directory of Open Access Journals (Sweden)
White Michael S
2003-01-01
Full Text Available A comparison is made of the behaviour of some evolutionary algorithms in time-varying adaptive recursive filter systems. Simulations show that an algorithm including random immigrants outperforms a more conventional algorithm using the breeder genetic algorithm as the mutation operator when the time variation is discontinuous, but neither algorithm performs well when the time variation is rapid but smooth. To meet this deficit, a new hybrid algorithm which uses a hill climber as an additional genetic operator, applied for several steps at each generation, is introduced. A comparison is made of the effect of applying the hill climbing operator a few times to all members of the population or a larger number of times solely to the best individual; it is found that applying to the whole population yields the better results, substantially improved compared with those obtained using earlier methods.
Stochastic Power Control for Time-Varying Long-Term Fading Wireless Networks
Directory of Open Access Journals (Sweden)
Charalambous Charalambos D
2006-01-01
Full Text Available A new time-varying (TV long-term fading (LTF channel model which captures both the space and time variations of wireless systems is developed. The proposed TV LTF model is based on a stochastic differential equation driven by Brownian motion. This model is more realistic than the static models usually encountered in the literature. It allows viewing the wireless channel as a dynamical system, thus enabling well-developed tools of adaptive and nonadaptive estimation and identification techniques to be applied to this class of problems. In contrast with the traditional models, the statistics of the proposed model are shown to be TV, but converge in steady state to their static counterparts. Moreover, optimal power control algorithms (PCAs based on the new model are proposed. A centralized PCA is shown to reduce to a simple linear programming problem if predictable power control strategies (PPCS are used. In addition, an iterative distributed stochastic PCA is used to solve for the optimization problem using stochastic approximations. The latter solely requires each mobile to know its received signal-to-interference ratio. Generalizations of the power control problem based on convex optimization techniques are provided if PPCS are not assumed. Numerical results show that there are potentially large gains to be achieved by using TV stochastic models, and the distributed stochastic PCA provides better power stability and consumption than the distributed deterministic PCA.
Fish, Jennifer A; Peters, Micah D J; Ramsey, Imogen; Sharplin, Greg; Corsini, Nadia; Eckert, Marion
2017-05-15
Exposure to smoke emitted from wildfire and planned burns (i.e., smoke events) has been associated with numerous negative health outcomes, including respiratory symptoms and conditions. This rapid review investigates recent evidence (post-2009) regarding the effectiveness of public health messaging during smoke events. The objectives were to determine the effectiveness of various communication channels used and public health messages disseminated during smoke events, for general and at-risk populations. A search of 12 databases and grey literature yielded 1775 unique articles, of which 10 were included in this review. Principal results were: 1) Smoke-related public health messages are communicated via a variety of channels, but limited evidence is available regarding their effectiveness for the general public or at-risk groups. 2) Messages that use simple language are more commonly recalled, understood, and complied with. Compliance differs according to socio-demographic characteristics. 3) At-risk groups may be advised to stay indoors before the general population, in order to protect the most vulnerable people in a community. The research included in this review was observational and predominantly descriptive, and is therefore unable to sufficiently answer questions regarding effectiveness. Experimental research, as well as evaluations, are required to examine the effectiveness of modern communication channels, channels to reach at-risk groups, and the 'stay indoors' message. Copyright © 2017 Elsevier Ltd. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Han, Kun Yeun; Park, Jae Hong; Lee, Eul Rae [Kyungpook National University, Taegu (Korea, Republic of)
1997-02-28
Petrov-Galerkin finite element model for analyzing dynamic wave equation is applied to gradually and rapidly varied unsteady flow. The model is verified by applying to hydraulic jump, nonlinear disturbance propagation in frictionless horizontal channel and dam-break analysis. It shows stable and accurate results compared with analytical solutions for various cases. The model is applied to a surge propagation in a frictionless horizontal channel. Three-dimensional water surface profiles show that the computed result converges to the analytical one with sharp discontinuity. The model is also applied to the Taehwa River to analyze unsteady flood wave propagation. The computed results have good agreements with those of DWOPER model in terms of discharge and stage hydrographs. (author). 19 refs., 22 figs.
A Microfluidic Channel Method for Rapid Drug-Susceptibility Testing of Pseudomonas aeruginosa
Matsumoto, Yoshimi; Grushnikov, Andrey; Kikuchi, Kazuma; Noji, Hiroyuki; Yamaguchi, Akihito; Yagi, Yasushi
2016-01-01
The recent global increase in the prevalence of antibiotic-resistant bacteria and lack of development of new therapeutic agents emphasize the importance of selecting appropriate antimicrobials for the treatment of infections. However, to date, the development of completely accelerated drug susceptibility testing methods has not been achieved despite the availability of a rapid identification method. We proposed an innovative rapid method for drug susceptibility testing for Pseudomonas aeruginosa that provides results within 3 h. The drug susceptibility testing microfluidic (DSTM) device was prepared using soft lithography. It consisted of five sets of four microfluidic channels sharing one inlet slot, and the four channels are gathered in a small area, permitting simultaneous microscopic observation. Antimicrobials were pre-introduced into each channel and dried before use. Bacterial suspensions in cation-adjusted Mueller–Hinton broth were introduced from the inlet slot and incubated for 3 h. Susceptibilities were microscopically evaluated on the basis of differences in cell numbers and shapes between drug-treated and control cells, using dedicated software. The results of 101 clinically isolated strains of P. aeruginosa obtained using the DSTM method strongly correlated with results obtained using the ordinary microbroth dilution method. Ciprofloxacin, meropenem, ceftazidime, and piperacillin caused elongation in susceptible cells, while meropenem also induced spheroplast and bulge formation. Morphological observation could alternatively be used to determine the susceptibility of P. aeruginosa to these drugs, although amikacin had little effect on cell shape. The rapid determination of bacterial drug susceptibility using the DSTM method could also be applicable to other pathogenic species, and it could easily be introduced into clinical laboratories without the need for expensive instrumentation. PMID:26872134
A Microfluidic Channel Method for Rapid Drug-Susceptibility Testing of Pseudomonas aeruginosa.
Directory of Open Access Journals (Sweden)
Yoshimi Matsumoto
Full Text Available The recent global increase in the prevalence of antibiotic-resistant bacteria and lack of development of new therapeutic agents emphasize the importance of selecting appropriate antimicrobials for the treatment of infections. However, to date, the development of completely accelerated drug susceptibility testing methods has not been achieved despite the availability of a rapid identification method. We proposed an innovative rapid method for drug susceptibility testing for Pseudomonas aeruginosa that provides results within 3 h. The drug susceptibility testing microfluidic (DSTM device was prepared using soft lithography. It consisted of five sets of four microfluidic channels sharing one inlet slot, and the four channels are gathered in a small area, permitting simultaneous microscopic observation. Antimicrobials were pre-introduced into each channel and dried before use. Bacterial suspensions in cation-adjusted Mueller-Hinton broth were introduced from the inlet slot and incubated for 3 h. Susceptibilities were microscopically evaluated on the basis of differences in cell numbers and shapes between drug-treated and control cells, using dedicated software. The results of 101 clinically isolated strains of P. aeruginosa obtained using the DSTM method strongly correlated with results obtained using the ordinary microbroth dilution method. Ciprofloxacin, meropenem, ceftazidime, and piperacillin caused elongation in susceptible cells, while meropenem also induced spheroplast and bulge formation. Morphological observation could alternatively be used to determine the susceptibility of P. aeruginosa to these drugs, although amikacin had little effect on cell shape. The rapid determination of bacterial drug susceptibility using the DSTM method could also be applicable to other pathogenic species, and it could easily be introduced into clinical laboratories without the need for expensive instrumentation.
Todd E. Clark; Francesco Ravazzolo
2012-01-01
This paper compares alternative models of time-varying macroeconomic volatility on the basis of the accuracy of point and density forecasts of macroeconomic variables. In this analysis, we consider both Bayesian autoregressive and Bayesian vector autoregressive models that incorporate some form of time-varying volatility, precisely stochastic volatility (both with constant and time-varying autoregressive coeffi cients), stochastic volatility following a stationary AR process, stochastic volat...
Directory of Open Access Journals (Sweden)
Johann A. Briffa
2014-06-01
Full Text Available In this study, the authors consider time-varying block (TVB codes, which generalise a number of previous synchronisation error-correcting codes. They also consider various practical issues related to maximum a posteriori (MAP decoding of these codes. Specifically, they give an expression for the expected distribution of drift between transmitter and receiver because of synchronisation errors. They determine an appropriate choice for state space limits based on the drift probability distribution. In turn, they obtain an expression for the decoder complexity under given channel conditions in terms of the state space limits used. For a given state space, they also give a number of optimisations that reduce the algorithm complexity with no further loss of decoder performance. They also show how the MAP decoder can be used in the absence of known frame boundaries, and demonstrate that an appropriate choice of decoder parameters allows the decoder to approach the performance when frame boundaries are known, at the expense of some increase in complexity. Finally, they express some existing constructions as TVB codes, comparing performance with published results and showing that improved performance is possible by taking advantage of the flexibility of TVB codes.
Rapid activation of inwardly rectifying potassium channels by immobile G-protein-coupled receptors.
Lober, Robert M; Pereira, Miguel A; Lambert, Nevin A
2006-11-29
G-protein-coupled receptors (GPCRs) mediate slow synaptic transmission and many other effects of small molecule and peptide neurotransmitters. In the standard model of GPCR signaling, receptors and G-proteins diffuse laterally within the plane of the plasma membrane and encounter each other by random collision. This model predicts that signaling will be most efficient if both GPCRs and G-proteins are free to diffuse, thus maximizing collision frequency. However, neuronal GPCRs are often recruited to and enriched at specific synaptic locations, suggesting receptor mobility is restricted in these cells. Here, we test the hypothesis that restricting GPCR mobility impairs signaling in neurons by limiting the frequency of collisions between receptors and G-proteins. Mu-opioid receptors (MORs) were immobilized on the surface of cerebellar granule neurons by avidin-mediated cross-linking, and inwardly rectifying potassium (GIRK) channels were used as rapid indicators of G-protein activation. Mobile and immobile MORs activated GIRK channels with the same onset kinetics and agonist sensitivity in these neurons. In a heterologous expression system, GFP (green fluorescent protein)-tagged G alpha(oA) subunits remained mobile after cross-linking, but their mobility was reduced in the presence of immobile MORs, suggesting that these receptors and subunits were transiently precoupled. In addition, channel activation could be reconstituted with immobile GPCRs, G-protein heterotrimers, and GIRK channels. These results show that collision frequency is not rate-limiting for G-protein activation in CNS neurons, and are consistent with the idea that signaling components are compartmentalized or preassembled.
NARX-based BPSO modelling for time-varying steam temperature of ...
African Journals Online (AJOL)
This paper focuses on a nonlinear modelling for a time-varying process of steam temperature by employing a polynomial Nonlinear Auto-Regressive with Exogenous Input (NARX) structure based on Binary Particle Swarm Optimization (BPSO) algorithm. The system identification time-varying steam temperature data was ...
Identification of Time-Varying Pilot Control Behavior in Multi-Axis Control Tasks
Zaal, Peter M. T.; Sweet, Barbara T.
2012-01-01
Recent developments in fly-by-wire control architectures for rotorcraft have introduced new interest in the identification of time-varying pilot control behavior in multi-axis control tasks. In this paper a maximum likelihood estimation method is used to estimate the parameters of a pilot model with time-dependent sigmoid functions to characterize time-varying human control behavior. An experiment was performed by 9 general aviation pilots who had to perform a simultaneous roll and pitch control task with time-varying aircraft dynamics. In 8 different conditions, the axis containing the time-varying dynamics and the growth factor of the dynamics were varied, allowing for an analysis of the performance of the estimation method when estimating time-dependent parameter functions. In addition, a detailed analysis of pilots adaptation to the time-varying aircraft dynamics in both the roll and pitch axes could be performed. Pilot control behavior in both axes was significantly affected by the time-varying aircraft dynamics in roll and pitch, and by the growth factor. The main effect was found in the axis that contained the time-varying dynamics. However, pilot control behavior also changed over time in the axis not containing the time-varying aircraft dynamics. This indicates that some cross coupling exists in the perception and control processes between the roll and pitch axes.
Kapoor, Vikrant; Provost, Allison C; Agarwal, Prateek; Murthy, Venkatesh N
2016-02-01
The serotonergic raphe nuclei are involved in regulating brain states over timescales of minutes and hours. We examined more rapid effects of raphe activation on two classes of principal neurons in the mouse olfactory bulb, mitral and tufted cells, which send olfactory information to distinct targets. Brief stimulation of the raphe nuclei led to excitation of tufted cells at rest and potentiation of their odor responses. While mitral cells at rest were also excited by raphe activation, their odor responses were bidirectionally modulated, leading to improved pattern separation of odors. In vitro whole-cell recordings revealed that specific optogenetic activation of raphe axons affected bulbar neurons through dual release of serotonin and glutamate. Therefore, the raphe nuclei, in addition to their role in neuromodulation of brain states, are also involved in fast, sub-second top-down modulation similar to cortical feedback. This modulation can selectively and differentially sensitize or decorrelate distinct output channels.
Rapid internalization of the oncogenic K+ channel K(V10.1.
Directory of Open Access Journals (Sweden)
Tobias Kohl
Full Text Available K(V10.1 is a mammalian brain voltage-gated potassium channel whose ectopic expression outside of the brain has been proven relevant for tumor biology. Promotion of cancer cell proliferation by K(V10.1 depends largely on ion flow, but some oncogenic properties remain in the absence of ion permeation. Additionally, K(V10.1 surface populations are small compared to large intracellular pools. Control of protein turnover within cells is key to both cellular plasticity and homeostasis, and therefore we set out to analyze how endocytic trafficking participates in controlling K(V10.1 intracellular distribution and life cycle. To follow plasma membrane K(V10.1 selectively, we generated a modified channel of displaying an extracellular affinity tag for surface labeling by α-bungarotoxin. This modification only minimally affected K(V10.1 electrophysiological properties. Using a combination of microscopy and biochemistry techniques, we show that K(V10.1 is constitutively internalized involving at least two distinct pathways of endocytosis and mainly sorted to lysosomes. This occurs at a relatively fast rate. Simultaneously, recycling seems to contribute to maintain basal K(V10.1 surface levels. Brief K(V10.1 surface half-life and rapid lysosomal targeting is a relevant factor to be taken into account for potential drug delivery and targeting strategies directed against K(V10.1 on tumor cells.
Rapid Internalization of the Oncogenic K+ Channel KV10.1
Kohl, Tobias; Lörinczi, Eva; Pardo, Luis A.; Stühmer, Walter
2011-01-01
KV10.1 is a mammalian brain voltage-gated potassium channel whose ectopic expression outside of the brain has been proven relevant for tumor biology. Promotion of cancer cell proliferation by KV10.1 depends largely on ion flow, but some oncogenic properties remain in the absence of ion permeation. Additionally, KV10.1 surface populations are small compared to large intracellular pools. Control of protein turnover within cells is key to both cellular plasticity and homeostasis, and therefore we set out to analyze how endocytic trafficking participates in controlling KV10.1 intracellular distribution and life cycle. To follow plasma membrane KV10.1 selectively, we generated a modified channel of displaying an extracellular affinity tag for surface labeling by α-bungarotoxin. This modification only minimally affected KV10.1 electrophysiological properties. Using a combination of microscopy and biochemistry techniques, we show that KV10.1 is constitutively internalized involving at least two distinct pathways of endocytosis and mainly sorted to lysosomes. This occurs at a relatively fast rate. Simultaneously, recycling seems to contribute to maintain basal KV10.1 surface levels. Brief KV10.1 surface half-life and rapid lysosomal targeting is a relevant factor to be taken into account for potential drug delivery and targeting strategies directed against KV10.1 on tumor cells. PMID:22022602
Directory of Open Access Journals (Sweden)
Mingzhu Song
2016-01-01
Full Text Available We address the problem of globally asymptotic stability for a class of stochastic nonlinear systems with time-varying delays. By the backstepping method and Lyapunov theory, we design a linear output feedback controller recursively based on the observable linearization for a class of stochastic nonlinear systems with time-varying delays to guarantee that the closed-loop system is globally asymptotically stable in probability. In particular, we extend the deterministic nonlinear system to stochastic nonlinear systems with time-varying delays. Finally, an example and its simulations are given to illustrate the theoretical results.
Estimation of time-varying selectivity in stock assessments using state-space models
DEFF Research Database (Denmark)
Nielsen, Anders; Berg, Casper Willestofte
2014-01-01
-varying selectivity pattern. The fishing mortality rates are considered (possibly correlated) stochastic processes, and the corresponding process variances are estimated within the model. The model is applied to North Sea cod and it is verified from simulations that time-varying selectivity can be estimated......Time-varying selectivity is one of the main challenges in single species age-based assessment models. In classical deterministic VPA-type models the fishing mortality rates are unfiltered representations of the observed catches. As a consequence the selectivity becomes time......-varying, but this representation is too fluctuating, because it includes the observation noise. In parametric statistical catch at age models a common assumption is that the selectivity is constant in all years, although time-varying selectivity can be introduced by splitting the data period in blocks with different selectivities...
Modeling and simulation of a time-varying inertia aircraft in aerial refueling
National Research Council Canada - National Science Library
Wang Haitao Dong Xinmin Xue Jianping Liu Jiaolong Wang Jian
2016-01-01
Studied in this paper is dynamic modeling and simulation application of the receiver aircraft with the time-varying mass and inertia property in an integrated simulation environment which includes two...
Design of reduced-order state estimators for linear time-varying multivariable systems
Nguyen, Charles C.
1987-01-01
The design of reduced-order state estimators for linear time-varying multivariable systems is considered. Employing the concepts of matrix operators and the method of canonical transformations, this paper shows that there exists a reduced-order state estimator for linear time-varying systems that are 'lexicography-fixedly observable'. In addition, the eigenvalues of the estimator can be arbitrarily assigned. A simple algorithm is proposed for the design of the state estimator.
Arbitrary eigenvalue assignments for linear time-varying multivariable control systems
Nguyen, Charles C.
1987-01-01
The problem of eigenvalue assignments for a class of linear time-varying multivariable systems is considered. Using matrix operators and canonical transformations, it is shown that a time-varying system that is 'lexicography-fixedly controllable' can be made via state feedback to be equivalent to a time-invariant system whose eigenvalues are arbitrarily assignable. A simple algorithm for the design of the state feedback is provided.
International Stock Market Efficiency: A Non-Bayesian Time-Varying Model Approach
Mikio Ito; Akihiko Noda; Tatsuma Wada
2012-01-01
This paper develops a non-Bayesian methodology to analyze the time-varying structure of international linkages and market efficiency in G7 countries. We consider a non-Bayesian time-varying vector autoregressive (TV-VAR) model, and apply it to estimate the joint degree of market efficiency in the sense of Fama (1970, 1991). Our empirical results provide a new perspective that the international linkages and market efficiency change over time and that their behaviors correspond well to historic...
Analysis of multilevel grouped survival data with time-varying regression coefficients.
Wong, May C M; Lam, K F; Lo, Edward C M
2011-02-10
Correlated or multilevel grouped survival data are common in medical and dental research. Two common approaches to analyze such data are the marginal and the random-effects approaches. Models and methods in the literature generally assume that the treatment effect is constant over time. A researcher may be interested in studying whether the treatment effects in a clinical trial vary over time, say fade out gradually. This is of particular clinical value when studying the long-term effect of a treatment. This paper proposed to extend the random effects grouped proportional hazards models by incorporating the possibly time-varying covariate effects into the model in terms of a state-space formulation. The proposed model is very flexible and the estimation can be performed using the MCMC approach with non-informative priors in the Bayesian framework. The method is applied to a data set from a prospective clinical trial investigating the effectiveness of silver diamine fluoride (SDF) and sodium fluoride (NaF) varnish in arresting active dentin caries in the Chinese preschool children. It is shown that the treatment groups with caries removal prior to the topical fluoride applications are most effective in shortening the arrest times in the first 6-month interval, but their effects fade out rapidly since then. The effects of treatment groups without caries removal prior to topical fluoride application drop at a very slow rate and can be considered as more or less constant over time. The applications of SDF solution is found to be more effective than the applications of NaF vanish. Copyright © 2010 John Wiley & Sons, Ltd.
On the time-varying trend in global-mean surface temperature
Energy Technology Data Exchange (ETDEWEB)
Wu, Zhaohua [Florida State University, Department of Meteorology and Center for Ocean-Atmospheric Prediction Studies, Tallahassee, FL (United States); Huang, Norden E. [National Central University, Research Center for Adaptive Data Analysis Center, Chungli (China); Wallace, John M.; Smoliak, Brian V. [University of Washington, Department of Atmospheric Sciences, Seattle, WA (United States); Chen, Xianyao [State Oceanic Administration, The First Institute of Oceanography, Qingdao (China)
2011-08-15
The Earth has warmed at an unprecedented pace in the decades of the 1980s and 1990s (IPCC in Climate change 2007: the scientific basis, Cambridge University Press, Cambridge, 2007). In Wu et al. (Proc Natl Acad Sci USA 104:14889-14894, 2007) we showed that the rapidity of the warming in the late twentieth century was a result of concurrence of a secular warming trend and the warming phase of a multidecadal ({proportional_to}65-year period) oscillatory variation and we estimated the contribution of the former to be about 0.08 C per decade since {proportional_to}1980. Here we demonstrate the robustness of those results and discuss their physical links, considering in particular the shape of the secular trend and the spatial patterns associated with the secular trend and the multidecadal variability. The shape of the secular trend and rather globally-uniform spatial pattern associated with it are both suggestive of a response to the buildup of well-mixed greenhouse gases. In contrast, the multidecadal variability tends to be concentrated over the extratropical Northern Hemisphere and particularly over the North Atlantic, suggestive of a possible link to low frequency variations in the strength of the thermohaline circulation. Depending upon the assumed importance of the contributions of ocean dynamics and the time-varying aerosol emissions to the observed trends in global-mean surface temperature, we estimate that up to one third of the late twentieth century warming could have been a consequence of natural variability. (orig.)
Vector-field statistics for the analysis of time varying clinical gait data.
Donnelly, C J; Alexander, C; Pataky, T C; Stannage, K; Reid, S; Robinson, M A
2017-01-01
In clinical settings, the time varying analysis of gait data relies heavily on the experience of the individual(s) assessing these biological signals. Though three dimensional kinematics are recognised as time varying waveforms (1D), exploratory statistical analysis of these data are commonly carried out with multiple discrete or 0D dependent variables. In the absence of an a priori 0D hypothesis, clinicians are at risk of making type I and II errors in their analyis of time varying gait signatures in the event statistics are used in concert with prefered subjective clinical assesment methods. The aim of this communication was to determine if vector field waveform statistics were capable of providing quantitative corroboration to practically significant differences in time varying gait signatures as determined by two clinically trained gait experts. The case study was a left hemiplegic Cerebral Palsy (GMFCS I) gait patient following a botulinum toxin (BoNT-A) injection to their left gastrocnemius muscle. When comparing subjective clinical gait assessments between two testers, they were in agreement with each other for 61% of the joint degrees of freedom and phases of motion analysed. For tester 1 and tester 2, they were in agreement with the vector-field analysis for 78% and 53% of the kinematic variables analysed. When the subjective analyses of tester 1 and tester 2 were pooled together and then compared to the vector-field analysis, they were in agreement for 83% of the time varying kinematic variables analysed. These outcomes demonstrate that in principle, vector-field statistics corroborates with what a team of clinical gait experts would classify as practically meaningful pre- versus post time varying kinematic differences. The potential for vector-field statistics to be used as a useful clinical tool for the objective analysis of time varying clinical gait data is established. Future research is recommended to assess the usefulness of vector-field analyses
Rapid effects of 17beta-estradiol on TRPV5 epithelial Ca2+ channels in rat renal cells.
LENUS (Irish Health Repository)
Irnaten, Mustapha
2009-08-01
The renal distal tubules and collecting ducts play a key role in the control of electrolyte and fluid homeostasis. The discovery of highly calcium selective channels, Transient Receptor Potential Vanilloid 5 (TRPV5) of the TRP superfamily, has clarified the nature of the calcium entry channels. It has been proposed that this channel mediates the critical Ca(2+) entry step in transcellular Ca(2+) re-absorption in the kidney. The regulation of transmembrane Ca(2+) flux through TRPV5 is of particular importance for whole body calcium homeostasis.In this study, we provide evidence that the TRPV5 channel is present in rat cortical collecting duct (RCCD(2)) cells at mRNA and protein levels. We demonstrate that 17beta-estradiol (E(2)) is involved in the regulation of Ca(2+) influx in these cells via the epithelial Ca(2+) channels TRPV5. By combining whole-cell patch-clamp and Ca(2+)-imaging techniques, we have characterized the electrophysiological properties of the TRPV5 channel and showed that treatment with 20-50nM E(2) rapidly (<5min) induced a transient increase in inward whole-cell currents and intracellular Ca(2+) via TRPV5 channels. This rise was significantly prevented when cells were pre-treated with ruthenium red and completely abolished in cells treated with siRNA specifically targeting TRPV5.These data demonstrate for the first time, a novel rapid modulation of endogenously expressed TRPV5 channels by E(2) in kidney cells. Furthermore, the results suggest calcitropic effects of E(2). The results are discussed in relation to present concepts of non-genomic actions of E(2) in Ca(2+) homeostasis.
Modeling of Electricity Demand for Azerbaijan: Time-Varying Coefficient Cointegration Approach
Directory of Open Access Journals (Sweden)
Jeyhun I. Mikayilov
2017-11-01
Full Text Available Recent literature has shown that electricity demand elasticities may not be constant over time and this has investigated using time-varying estimation methods. As accurate modeling of electricity demand is very important in Azerbaijan, which is a transitional country facing significant change in its economic outlook, we analyze whether the response of electricity demand to income and price is varying over time in this economy. We employed the Time-Varying Coefficient cointegration approach, a cutting-edge time-varying estimation method. We find evidence that income elasticity demonstrates sizeable variation for the period of investigation ranging from 0.48% to 0.56%. The study has some useful policy implications related to the income and price aspects of the electricity consumption in Azerbaijan.
Adaptive Control for Nonlinear Systems with Time-Varying Control Gain
Directory of Open Access Journals (Sweden)
Alejandro Rincon
2012-01-01
Full Text Available We propose a scheme for nonlinear plants with time-varying control gain and time-varying plant coefficients, on the basis of a plant model consisting of a Brunovsky-type model with polynomials as approximators. We develop an adaptive robust control scheme for this plant, under the following assumptions: (i the plant terms involve time-varying but bounded coefficients, being its upper bound unknown; (ii the control gain is unknown, not necessarily bounded, and only its signum is known. To achieve robustness, we use a combination of robustifying control inputs and dead zone-type update laws. We apply this methodology to the speed control of a permanent magnet synchronous motor (PMSM, and we achieve proper tracking results.
Linear Impulsive Periodic System with Time-Varying Generating Operators on Banach Space
Directory of Open Access Journals (Sweden)
Wei W
2007-01-01
Full Text Available A class of the linear impulsive periodic system with time-varying generating operators on Banach space is considered. By constructing the impulsive evolution operator, the existence of -periodic -mild solution for homogeneous linear impulsive periodic system with time-varying generating operators is reduced to the existence of fixed point for a suitable operator. Further the alternative results on -periodic -mild solution for nonhomogeneous linear impulsive periodic system with time-varying generating operators are established and the relationship between the boundness of solution and the existence of -periodic -mild solution is shown. The impulsive periodic motion controllers that are robust to parameter drift are designed for a given periodic motion. An example given for demonstration.
Performance Optimizing Adaptive Control with Time-Varying Reference Model Modification
Nguyen, Nhan T.; Hashemi, Kelley E.
2017-01-01
This paper presents a new adaptive control approach that involves a performance optimization objective. The control synthesis involves the design of a performance optimizing adaptive controller from a subset of control inputs. The resulting effect of the performance optimizing adaptive controller is to modify the initial reference model into a time-varying reference model which satisfies the performance optimization requirement obtained from an optimal control problem. The time-varying reference model modification is accomplished by the real-time solutions of the time-varying Riccati and Sylvester equations coupled with the least-squares parameter estimation of the sensitivities of the performance metric. The effectiveness of the proposed method is demonstrated by an application of maneuver load alleviation control for a flexible aircraft.
Containment problem with time-varying formation and collision avoidance for multiagent systems
Directory of Open Access Journals (Sweden)
Jesús Santiaguillo-Salinas
2017-05-01
Full Text Available This article studies a time-varying version of the so-called containment problem with collision avoidance for multiagent systems. The proposed control strategy is decentralized, since agents have no global knowledge of the goal to achieve, knowing only the position and velocity of a subset of agents. This control strategy allows a subset of mobile agents (called leaders to track a prescribed trajectory while they achieve a time-varying formation. Simultaneously, another subset of mobile agents (called followers converge exponentially to the region bounded by the leaders. For the collision avoidance, we added a repulsive vector field of the unstable focus type to the time-varying containment control law. Formation graphs are used to represent interactions between agents. The results are presented for the front points of differential-drive mobile robots. The theoretical results are verified by numerical simulation. Additionally, an experimental case study is presented.
Visulization of Time-Varying Multiresolution Date Using Error-Based Temporal-Spatial Resuse
Energy Technology Data Exchange (ETDEWEB)
Nuber, C; LaMar, E; Hamann, B; Joy, K
2002-04-22
In this paper, we report results on exploration of two-dimensional (2D) time varying datasets. We extend the notion of multiresolution spatial data approximation of static datasets to spatio-temporal approximation of time-varying datasets. Time-varying datasets typically do not change ''uniformly,'' i.e., some spatial sub-domains can experience only little or no change for extended periods of time. In these sub-domains, we show that approximation error bounds can be met when using sub-domains from other time-steps effectively. We generate a more general approximation scheme where sub-domains may approximate congruent sub-domains from any other time steps. While this incurs an O(T2) overhead, where T is the total number of time-steps, we show significant reduction in data transmission. We also discuss ideas for improvements to reduce overhead.
Pourbabaee, Bahareh; Meskin, Nader; Khorasani, Khashayar
2016-08-01
In this paper, a novel robust sensor fault detection and isolation (FDI) strategy using the multiple model-based (MM) approach is proposed that remains robust with respect to both time-varying parameter uncertainties and process and measurement noise in all the channels. The scheme is composed of robust Kalman filters (RKF) that are constructed for multiple piecewise linear (PWL) models that are constructed at various operating points of an uncertain nonlinear system. The parameter uncertainty is modeled by using a time-varying norm bounded admissible structure that affects all the PWL state space matrices. The robust Kalman filter gain matrices are designed by solving two algebraic Riccati equations (AREs) that are expressed as two linear matrix inequality (LMI) feasibility conditions. The proposed multiple RKF-based FDI scheme is simulated for a single spool gas turbine engine to diagnose various sensor faults despite the presence of parameter uncertainties, process and measurement noise. Our comparative studies confirm the superiority of our proposed FDI method when compared to the methods that are available in the literature.
Sanchez, B; Louarroudi, E; Jorge, E; Cinca, J; Bragos, R; Pintelon, R
2013-03-01
The bioimpedance measurement/identification of time-varying biological systems Z(ω, t) by means of electrical impedance spectroscopy (EIS) is still a challenge today. This paper presents a novel measurement and identification approach, the so-called parametric-in-time approach, valid for time-varying (bio-)impedance systems with a (quasi) periodic character. The technique is based on multisine EIS. Contrary to the widely used nonparametric-in-time strategy, the (bio-)impedance Z(ω, t) is assumed to be time-variant during the measurement interval. Therefore, time-varying spectral analysis tools are required. This new parametric-in-time measuring/identification technique has experimentally been validated through three independent sets of in situ measurements of in vivo myocardial impedance. We show that the time-varying myocardial impedance Z(ω, t) is dominantly periodically time varying (PTV), denoted as ZPTV(ω, t). From the temporal analysis of ZPTV(ω, t), we demonstrate that it is possible to decompose ZPTV(ω, t) into a(n) (in)finite sum of fundamental (bio-)impedance spectra, the so-called harmonic impedance spectra (HIS) Zk(ω)s with [Formula: see text]. This is similar to the well-known Fourier series of a periodic signal, but now understood at the level of a periodic system's frequency response. The HIS Zk(ω)s for [Formula: see text] actually summarize in the bi-frequency (ω, k) domain all the temporal in-cycle information about the periodic changes of Z(ω, t). For the particular case k = 0 (i.e. on the ω-axis), Z0(ω) reflects the mean in-cycle behavior of the time-varying bioimpedance. Finally, the HIS Zk(ω)s are directly identified from noisy current and voltage myocardium measurements at the multisine measurement frequencies (i.e. nonparametric-in-frequency).
Bank insolvency risk and time-varying Z-score measures
Lepetit, Laetitia; Strobel, Frank
2013-01-01
International audience; We compare the di¤erent existing approaches to the construction of time-varying Z-score measures, plus an additional alternative one, using a panel of banks for the G20 group of countries covering the period 1992–2009. We examine which ways of estimating the moments used in these di¤erent ap-proaches best …t the data, using a simple root mean squared error criterion. Our results are supportive of our alternative time-varying Z-score measure: it uses mean and standard d...
Time-varying long term memory in the European Union stock markets
Sensoy, Ahmet; Tabak, Benjamin M.
2015-10-01
This paper proposes a new efficiency index to model time-varying inefficiency in stock markets. We focus on European stock markets and show that they have different degrees of time-varying efficiency. We observe that the 2008 global financial crisis has an adverse effect on almost all EU stock markets. However, the Eurozone sovereign debt crisis has a significant adverse effect only on the markets in France, Spain and Greece. For the late members, joining EU does not have a uniform effect on stock market efficiency. Our results have important implications for policy makers, investors, risk managers and academics.
Long Memory of Financial Time Series and Hidden Markov Models with Time-Varying Parameters
DEFF Research Database (Denmark)
Nystrup, Peter; Madsen, Henrik; Lindström, Erik
2016-01-01
Hidden Markov models are often used to model daily returns and to infer the hidden state of financial markets. Previous studies have found that the estimated models change over time, but the implications of the time-varying behavior have not been thoroughly examined. This paper presents an adaptive...... to reproduce with a hidden Markov model. Capturing the time-varying behavior of the parameters also leads to improved one-step density forecasts. Finally, it is shown that the forecasting performance of the estimated models can be further improved using local smoothing to forecast the parameter variations....
Identification of time-varying nonlinear systems using differential evolution algorithm
DEFF Research Database (Denmark)
Perisic, Nevena; Green, Peter L; Worden, Keith
2013-01-01
, thus identification of time-varying systems with nonlinearities can be a very challenging task. In order to avoid conventional least squares and gradient identification methods which require uni-modal and double differentiable objective functions, this work proposes a modified differential evolution...... (DE) algorithm for the identification of time-varying systems. DE is an evolutionary optimisation method developed to perform direct search in a continuous space without requiring any derivative estimation. DE is modified so that the objective function changes with time to account for the continuing...
A Distributed Algorithm for Economic Dispatch Over Time-Varying Directed Networks With Delays
Energy Technology Data Exchange (ETDEWEB)
Yang, Tao; Lu, Jie; Wu, Di; Wu, Junfeng; Shi, Guodong; Meng, Ziyang; Johansson, Karl Henrik
2017-06-01
In power system operation, economic dispatch problem (EDP) is designed to minimize the total generation cost while meeting the demand and satisfying generator capacity limits. This paper proposes an algorithm based on the gradient-push method to solve the EDP in a distributed manner over communication networks potentially with time-varying topologies and communication delays. It has been shown that the proposed method is guaranteed to solve the EDP if the time-varying directed communication network is uniformly jointly strongly connected. Moreover, the proposed algorithm is also able to handle arbitrarily large but bounded time delays on communication links. Numerical simulations are used to illustrate and validate the proposed algorithm.
Directory of Open Access Journals (Sweden)
J. Thipcha
2013-01-01
Full Text Available The global exponential stability for bidirectional associative memory neural networks with time-varying delays is studied. In our study, the lower and upper bounds of the activation functions are allowed to be either positive, negative, or zero. By constructing new and improved Lyapunov-Krasovskii functional and introducing free-weighting matrices, a new and improved delay-dependent exponential stability for BAM neural networks with time-varying delays is derived in the form of linear matrix inequality (LMI. Numerical examples are given to demonstrate that the derived condition is less conservative than some existing results given in the literature.
Sabeti, Malihe; Boostani, Reza
2017-07-01
Synchronous averaging over time locked single-trial of event-related potential (ERP) is known as the simplest scheme to extract P300 component. This method assumes the P300 features are invariant through the time while they are affected by factors like brain fatigue and habitation. In this study, a new scheme is proposed termed as time-varying time-lag blind source separation (TT-BSS) which is upon the second order statistics of signal to separate P300 waveform from the background electroencephalogram (EEG) while it captures the time variation of P300 component. The time-lag parameter for all channels is determined by maximizing the correlation (similarity) between two successive trials. As the time-lag parameter is varying by time (trial to trial), an average is taken over the time-lag covariance matrices of all two consecutive trials. TT-BSS finally estimates a transform (separating matrix) by joint diagnolization of the covariance matrix of trials and the averaged covariance matrix of the time varying time-lag. To assess the proposed scheme, synthetic and real EEGs containing P300 are used. The EEG signals were collected from twenty schizophrenic and twenty age-matched normal subjects via 20 channels through the resting state and in presence of the oddball audio stimulus. Empirical achievements over the simulated and real EEGs imply on the superiority of TT-BSS in dynamic estimation of P300 characteristics compared to state-of-the-art counterparts such as constant time-lag BSS, constrained BSS and synchronous averaging. Copyright © 2017 Elsevier B.V. All rights reserved.
Modeling the Time-Varying Nature of Student Exceptionality Classification on Achievement Growth
Nese, Joseph F. T.; Stevens, Joseph J.; Schulte, Ann C.; Tindal, Gerald; Elliott, Stephen N.
2017-01-01
Our purpose was to examine different approaches to modeling the time-varying nature of exceptionality classification. Using longitudinal data from one state's mathematics achievement test for 28,829 students in Grades 3 to 8, we describe the reclassification rate within special education and between general and special education, and compare four…
The time-varying shortest path problem with fuzzy transit costs and speedup
Directory of Open Access Journals (Sweden)
Rezapour Hassan
2016-08-01
Full Text Available In this paper, we focus on the time-varying shortest path problem, where the transit costs are fuzzy numbers. Moreover, we consider this problem in which the transit time can be shortened at a fuzzy speedup cost. Speedup may also be a better decision to find the shortest path from a source vertex to a specified vertex.
Trip, Sebastian; Buerger, Mathias; De Persis, Claudio
This paper studies the problem of frequency regulation in power grids under unknown and possible time-varying load changes, while minimizing the generation costs. We formulate this problem as an output agreement problem for distribution networks and address it using incremental passivity and
Frequency variations of gravity waves interacting with a time-varying tide
Directory of Open Access Journals (Sweden)
C. M. Huang
2013-10-01
Full Text Available Using a nonlinear, 2-D time-dependent numerical model, we simulate the propagation of gravity waves (GWs in a time-varying tide. Our simulations show that when a GW packet propagates in a time-varying tidal-wind environment, not only its intrinsic frequency but also its ground-based frequency would change significantly. The tidal horizontal-wind acceleration dominates the GW frequency variation. Positive (negative accelerations induce frequency increases (decreases with time. More interestingly, tidal-wind acceleration near the critical layers always causes the GW frequency to increase, which may partially explain the observations that high-frequency GW components are more dominant in the middle and upper atmosphere than in the lower atmosphere. The combination of the increased ground-based frequency of propagating GWs in a time-varying tidal-wind field and the transient nature of the critical layer induced by a time-varying tidal zonal wind creates favorable conditions for GWs to penetrate their originally expected critical layers. Consequently, GWs have an impact on the background atmosphere at much higher altitudes than expected, which indicates that the dynamical effects of tidal–GW interactions are more complicated than usually taken into account by GW parameterizations in global models.
Perfect fluid Bianchi Type-I cosmological models with time varying G ...
Indian Academy of Sciences (India)
Bianchi Type-I cosmological models containing perfect fluid with time varying and have been presented. The solutions obtained represent an expansion scalar bearing a constant ratio to the anisotropy in the direction of space-like unit vector . Of the two models obtained, one has negative vacuum energy density, ...
A note on "Multicriteria adaptive paths in stochastic, time-varying networks"
DEFF Research Database (Denmark)
Pretolani, Daniele; Nielsen, Lars Relund; Andersen, Kim Allan
In a recent paper, Opasanon and Miller-Hooks study multicriteria adaptive paths in stochastic time-varying networks. They propose a label correcting algorithm for finding the full set of efficient strategies. In this note we show that their algorithm is not correct, since it is based on a property...
Wang, Limin; Shao, Cheng
2010-04-01
The issue of exponential stabilisation for a class of special time-varying delay switched systems resulting from actuator faults is considered in this article. The time-varying delay is assumed to belong to an interval and can be a slow or fast time-varying function. A hybrid state feedback strategy is redesigned to guarantee the system stable since the original controller is unavailable for some actuators failures. A class of switching laws incorporating the average dwell time method is proposed so that the special switched system with interval time-varying delay is exponentially stable. New delay-range-dependent stabilisation conditions using state feedback controllers are formulated in terms of linear matrix inequalities (LMIs) by choosing appropriate Lyapunov-Krasovskii functional without neglecting some useful knowledge on system states. Parameterised characterisations of the controllers are given in terms of the feasibility solutions to the LMIs. Two numeral examples are given to demonstrate the applicability and the effectiveness of the proposed method.
DEFF Research Database (Denmark)
Chon, Ki H; Zhong, Yuru; Moore, Leon C
2008-01-01
The extent to which renal blood flow dynamics vary in time and whether such variation contributes substantively to dynamic complexity have emerged as important questions. Data from Sprague-Dawley rats (SDR) and spontaneously hypertensive rats (SHR) were analyzed by time-varying transfer functions...
Dual Extended Kalman Filter for the Identification of Time-Varying Human Manual Control Behavior
Popovici, Alexandru; Zaal, Peter M. T.; Pool, Daan M.
2017-01-01
A Dual Extended Kalman Filter was implemented for the identification of time-varying human manual control behavior. Two filters that run concurrently were used, a state filter that estimates the equalization dynamics, and a parameter filter that estimates the neuromuscular parameters and time delay. Time-varying parameters were modeled as a random walk. The filter successfully estimated time-varying human control behavior in both simulated and experimental data. Simple guidelines are proposed for the tuning of the process and measurement covariance matrices and the initial parameter estimates. The tuning was performed on simulation data, and when applied on experimental data, only an increase in measurement process noise power was required in order for the filter to converge and estimate all parameters. A sensitivity analysis to initial parameter estimates showed that the filter is more sensitive to poor initial choices of neuromuscular parameters than equalization parameters, and bad choices for initial parameters can result in divergence, slow convergence, or parameter estimates that do not have a real physical interpretation. The promising results when applied to experimental data, together with its simple tuning and low dimension of the state-space, make the use of the Dual Extended Kalman Filter a viable option for identifying time-varying human control parameters in manual tracking tasks, which could be used in real-time human state monitoring and adaptive human-vehicle haptic interfaces.
Time-Varying Networks of Inter-Ictal Discharging Reveal Epileptogenic Zone
Directory of Open Access Journals (Sweden)
Luyan Zhang
2017-08-01
Full Text Available The neuronal synchronous discharging may cause an epileptic seizure. Currently, most of the studies conducted to investigate the mechanism of epilepsy are based on EEGs or functional magnetic resonance imaging (fMRI recorded during the ictal discharging or the resting-state, and few studies have probed into the dynamic patterns during the inter-ictal discharging that are much easier to record in clinical applications. Here, we propose a time-varying network analysis based on adaptive directed transfer function to uncover the dynamic brain network patterns during the inter-ictal discharging. In addition, an algorithm based on the time-varying outflow of information derived from the network analysis is developed to detect the epileptogenic zone. The analysis performed revealed the time-varying network patterns during different stages of inter-ictal discharging; the epileptogenic zone was activated prior to the discharge onset then worked as the source to propagate the activity to other brain regions. Consistence between the epileptogenic zones detected by our proposed approach and the actual epileptogenic zones proved that time-varying network analysis could not only reveal the underlying neural mechanism of epilepsy, but also function as a useful tool in detecting the epileptogenic zone based on the EEGs in the inter-ictal discharging.
Prediction of oil expression by uniaxial compression using time-varying oilseed properties
DEFF Research Database (Denmark)
Bargale, P. C.; Wulfsohn, Dvoralai; Irudayaraj, J.
2000-01-01
A mathematical simulation of uniaxial compression of oilseeds for oil extraction was developed based upon combining Terzaghi's theory of consolidation for saturated soils with Darcy's law for unsaturated flow, while incorporating the time-varying nature of the coefficients of permeability...
A comparison of time-varying covariates in two smoking cessation interventions for cardiac patients
Prenger, Hendrikje Cornelia; Pieterse, Marcel E.; Braakman-Jansen, Louise Marie Antoinette; Bolman, Catherine; Ruitenbeek-Wiggers, L.; de Vries, H.
2013-01-01
The aim of the study was to explore the time-varying contribution of social cognitive determinants of smoking cessation following an intervention on cessation. Secondary analyses were performed on data from two comparable randomized controlled trials on brief smoking cessation interventions for
Time-Varying Dynamic Properties of Offshore Wind Turbines Evaluated by Modal Testing
DEFF Research Database (Denmark)
Damgaard, Mads; Andersen, J. K. F.; Ibsen, Lars Bo
2014-01-01
resonance of the wind turbine structure. In this paper, free vibration tests and a numerical Winkler type approach are used to evaluate the dynamic properties of a total of 30 offshore wind turbines located in the North Sea. Analyses indicate time-varying eigenfrequencies and damping ratios of the lowest...
The necessity for a time local dimension in systems with time-varying attractors
DEFF Research Database (Denmark)
Særmark, Knud H; Ashkenazy, Y; Levitan, J
1997-01-01
We show that a simple non-linear system for ordinary differential equations may possess a time-varying attractor dimension. This indicates that it is infeasible to characterize EEG and MEG time series with a single time global dimension. We suggest another measure for the description of non...
The control of self-propelled microjets inside a microchannel with time-varying flow rates
Khalil, I.S.M.; Magdanz, Veronika; Sanchez, Samuel; Schmidt, Oliver S.; Misra, Sarthak
We demonstrate the closed-loop motion control of self-propelled microjets inside a fluidic microchannel. The motion control of the microjets is achieved in hydrogen peroxide solution with time-varying flow rates, under the influence of the controlled magnetic fields and the self-propulsion force.
DEFF Research Database (Denmark)
Andersen, P.; Skjærbæk, P. S.; Kirkegaard, Poul Henning
with the smoothed quanties which have been obtained from SARCOF. The results show the usefulness of the technique for identification of a time varying civil engineering structure. It is found that all the techniques give reliable estiates of the frequencies of the two lowest modes and the first mode shape. Only...
Dynamic coupling design for nonlinear output agreement and time-varying flow control
Buerger, Mathias; De Persis, Claudio
This paper studies the problem of output agreement in networks of nonlinear dynamical systems under time-varying disturbances, using dynamic diffusive couplings. Necessary conditions are derived for general networks of nonlinear systems, and these conditions are explicitly interpreted as conditions
The generalized harmonic potential theorem in the presence of a time-varying magnetic field.
Lai, Meng-Yun; Pan, Xiao-Yin
2016-10-17
We investigate the evolution of the many-body wave function of a quantum system with time-varying effective mass, confined by a harmonic potential with time-varying frequency in the presence of a uniform time-varying magnetic field, and perturbed by a time-dependent uniform electric field. It is found that the wave function is comprised of a phase factor times the solution to the unperturbed time-dependent Schrödinger equation with the latter being translated by a time-dependent value that satisfies the classical driven equation of motion. In other words, we generalize the harmonic potential theorem to the case when the effective mass, harmonic potential, and the external uniform magnetic field with arbitrary orientation are all time-varying. The results reduce to various special cases obtained in the literature, particulary to that of the harmonic potential theorem wave function when the effective mass and frequency are both static and the external magnetic field is absent.
Frequency variations of gravity waves interacting with a time-varying tide
Energy Technology Data Exchange (ETDEWEB)
Huang, C.M.; Zhang, S.D.; Yi, F.; Huang, K.M.; Gan, Q.; Gong, Y. [Wuhan Univ., Hubei (China). School of Electronic Information; Ministry of Education, Wuhan, Hubei (China). Key Lab. of Geospace Environment and Geodesy; State Observatory for Atmospheric Remote Sensing, Wuhan, Hubei (China); Zhang, Y.H. [Nanjing Univ. of Information Science and Technology (China). College of Hydrometeorolgy
2013-11-01
Using a nonlinear, 2-D time-dependent numerical model, we simulate the propagation of gravity waves (GWs) in a time-varying tide. Our simulations show that when aGW packet propagates in a time-varying tidal-wind environment, not only its intrinsic frequency but also its ground-based frequency would change significantly. The tidal horizontal-wind acceleration dominates the GW frequency variation. Positive (negative) accelerations induce frequency increases (decreases) with time. More interestingly, tidal-wind acceleration near the critical layers always causes the GW frequency to increase, which may partially explain the observations that high-frequency GW components are more dominant in the middle and upper atmosphere than in the lower atmosphere. The combination of the increased ground-based frequency of propagating GWs in a time-varying tidal-wind field and the transient nature of the critical layer induced by a time-varying tidal zonal wind creates favorable conditions for GWs to penetrate their originally expected critical layers. Consequently, GWs have an impact on the background atmosphere at much higher altitudes than expected, which indicates that the dynamical effects of tidal-GW interactions are more complicated than usually taken into account by GW parameterizations in global models.
Model reference adaptive control for linear time varying and nonlinear systems
Abida, L.; Kaufman, H.
1982-01-01
Model reference adaptive control is applied to linear time varying systems and to nonlinear systems amenable to virtual linearization. Asymptotic stability is guaranteed even if the perfect model following conditions do not hold, provided that some sufficient conditions are satisfied. Simulations show the scheme to be capable of effectively controlling certain nonlinear systems.
Reduction of time-varying nanotesla magnetic fields from electric power lines by twisting
Been, A.J.; Folkertsma, Gerrit Adriaan; Folkertsma, G.A.; Verputten, H.H.J.; Bolhuis, Thijs; Abelmann, Leon
2009-01-01
Time-varying magnetic fields generated by electrical power lines in the laboratory can disturb electron microscope imaging. Modern microscopes require these fields to be below 10 nT [2]. We calculated and measured magnetic fields from straight and twisted current-carrying wires, and show that
Mean square stability of uncertain stochastic BAM neural networks with interval time-varying delays.
Wu, Haixia; Liao, Xiaofeng; Feng, Wei; Guo, Songtao
2012-10-01
The robust asymptotic stability analysis for uncertain BAM neural networks with both interval time-varying delays and stochastic disturbances is considered. By using the stochastic analysis approach, employing some free-weighting matrices and introducing an appropriate type of Lyapunov functional which takes into account the ranges for delays, some new stability criteria are established to guarantee the delayed BAM neural networks to be robustly asymptotically stable in the mean square. Unlike the most existing mean square stability conditions for BAM neural networks, the supplementary requirements that the time derivatives of time-varying delays must be smaller than 1 are released and the lower bounds of time varying delays are not restricted to be 0. Furthermore, in the proposed scheme, the stability conditions are delay-range-dependent and rate-dependent/independent. As a result, the new criteria are applicable to both fast and slow time-varying delays. Three numerical examples are given to illustrate the effectiveness of the proposed criteria.
Analysis of nonlinear systems with time varying inputs and its application to gain scheduling
Directory of Open Access Journals (Sweden)
J.-T. Lim
1996-01-01
Full Text Available An analytical framework for analysis of a class of nonlinear systems with time varying inputs is presented. It is shown that the trajectories of the transformed nonlinear systems are uniformly bounded with an ultimate bound under certain conditions shown in this paper. The result obtained is useful for applications, in particular, analysis and design of gain scheduling.
Time-varying coefficient estimation in SURE models. Application to portfolio management
DEFF Research Database (Denmark)
Casas, Isabel; Ferreira, Eva; Orbe, Susan
This paper provides a detailed analysis of the asymptotic properties of a kernel estimator for a Seemingly Unrelated Regression Equations model with time-varying coefficients (tv-SURE) under very general conditions. Theoretical results together with a simulation study differentiates the cases for...
Time-varying Concurrent Risk of Extreme Droughts and Heatwaves in California
Sarhadi, A.; Diffenbaugh, N. S.; Ausin, M. C.
2016-12-01
Anthropogenic global warming has changed the nature and the risk of extreme climate phenomena such as droughts and heatwaves. The concurrent of these nature-changing climatic extremes may result in intensifying undesirable consequences in terms of human health and destructive effects in water resources. The present study assesses the risk of concurrent extreme droughts and heatwaves under dynamic nonstationary conditions arising from climate change in California. For doing so, a generalized fully Bayesian time-varying multivariate risk framework is proposed evolving through time under dynamic human-induced environment. In this methodology, an extreme, Bayesian, dynamic copula (Gumbel) is developed to model the time-varying dependence structure between the two different climate extremes. The time-varying extreme marginals are previously modeled using a Generalized Extreme Value (GEV) distribution. Bayesian Markov Chain Monte Carlo (MCMC) inference is integrated to estimate parameters of the nonstationary marginals and copula using a Gibbs sampling method. Modelled marginals and copula are then used to develop a fully Bayesian, time-varying joint return period concept for the estimation of concurrent risk. Here we argue that climate change has increased the chance of concurrent droughts and heatwaves over decades in California. It is also demonstrated that a time-varying multivariate perspective should be incorporated to assess realistic concurrent risk of the extremes for water resources planning and management in a changing climate in this area. The proposed generalized methodology can be applied for other stochastic nature-changing compound climate extremes that are under the influence of climate change.
San Roman Alerigi, Damian
2014-11-01
Over the past several decades our understanding and meticulous characterization of the transient and spatial properties of materials evolved rapidly. The results present an exciting field for discovery, and craft materials to control and reshape light that we are just beginning to fathom. State-of-the-art nano-deposition processes, for example, can be utilized to build stratified waveguides made of thin dielectric layers, which put together result in a material with effective abnormal dispersion. Moreover, materials once deemed well known are revealing astonishing properties, v.gr. chalcogenide glasses undergo an atomic reconfiguration when illuminated with electrons or photons, this ensues in a temporal modification of its permittivity and permeability which could be used to build new Photonic Integrated Circuits.. This work revolves around the characterization and model of heterogeneous and time-varying materials and their applications, revisits Maxwell\\'s equations in the context of nonlinear space- and time-varying media, and based on it introduces a numerical scheme that can be used to model waves in this kind of media. Finally some interesting applications for light confinement and beam transformations are shown.
Manivannan, R; Samidurai, R; Cao, Jinde; Alsaedi, Ahmed; Alsaadi, Fuad E
2017-03-01
This paper investigates the problems of exponential stability and dissipativity of generalized neural networks (GNNs) with time-varying delay signals. By constructing a novel Lyapunov-Krasovskii functionals (LKFs) with triple integral terms that contain more advantages of the state vectors of the neural networks, and the upper bound on the time-varying delay signals are formulated. We employ a new integral inequality technique (IIT), free-matrix-based (FMB) integral inequality approach, and Wirtinger double integral inequality (WDII) technique together with the reciprocally convex combination (RCC) approach to bound the time derivative of the LKFs. An improved exponential stability and strictly (Q,S,R)-γ-dissipative conditions of the addressed systems are represented by the linear matrix inequalities (LMIs). Finally, four interesting numerical examples are developed to verify the usefulness of the proposed method with a practical application to a biological network. Copyright © 2016 Elsevier Ltd. All rights reserved.
Cortical Dipole Imaging for Multiple Signal Sources Considering Time-Varying Non-Uniform Noise
Hori, Junichi; Watanabe, Yoshiki
Cortical dipole imaging is one of the spatial enhancement techniques from the scalp electroencephalogram. We investigated the dipole imaging for multiple signal sources under time-varying non-uniform noise conditions. The effects of incorporating statistical information of noise into the spatiotemporal inverse filter were examined by computer simulations and experimental studies in three sphere volume conductor model. The parametric projection filter that incorporated with noise covariance was applied to the inverse problem of EEG measurements. The noise covariance matrix was estimated by applying independent component analysis to the scalp potentials. The spatial filter was expanded to apply to the time-varying non-uniform noise conditions such as eye blink artifact. Moreover, multiple dipole distributions were introduced to extract and to visualize individual signal sources. The proposed imaging technique was applied to human experimental data of visual evoked potentials. We obtained reasonable results that coincide to physiological knowledge.
Directory of Open Access Journals (Sweden)
Cheng Liu
2010-01-01
Full Text Available Time-varying coherence is a powerful tool for revealing functional dynamics between different regions in the brain. In this paper, we address ways of estimating evolutionary spectrum and coherence using the general Cohen's class distributions. We show that the intimate connection between the Cohen's class-based spectra and the evolutionary spectra defined on the locally stationary time series can be linked by the kernel functions of the Cohen's class distributions. The time-varying spectra and coherence are further generalized with the Stockwell transform, a multiscale time-frequency representation. The Stockwell measures can be studied in the framework of the Cohen's class distributions with a generalized frequency-dependent kernel function. A magnetoencephalography study using the Stockwell coherence reveals an interesting temporal interaction between contralateral and ipsilateral motor cortices under the multisource interference task.
Model-free adaptive fractional order control of stable linear time-varying systems.
Yakoub, Z; Amairi, M; Chetoui, M; Saidi, B; Aoun, M
2017-03-01
This paper presents a new model-free adaptive fractional order control approach for linear time-varying systems. An online algorithm is proposed to determine some frequency characteristics using a selective filtering and to design a fractional PID controller based on the numerical optimization of the frequency-domain criterion. When the system parameters are time-varying, the controller is updated to keep the same desired performances. The main advantage of the proposed approach is that the controller design depends only on the measured input and output signals of the process. The effectiveness of the proposed method is assessed through a numerical example. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Control of parabolic PDEs with time-varying spatial domain: Czochralski crystal growth process
Ng, James; Aksikas, Ilyasse; Dubljevic, Stevan
2013-09-01
This paper considers the optimal control problem for a class of convection-diffusion-reaction systems modelled by partial differential equations (PDEs) defined on time-varying spatial domains. The class of PDEs is characterised by the presence of a time-dependent convective-transport term which is associated with the time evolution of the spatial domain boundary. The functional analytic description of the PDE yields the representation of the initial and boundary value problem as a nonautonomous parabolic evolution equation on an appropriately defined infinite-dimensional function space. The properties of the time-varying evolution operator to guarantee existence and well posedness of the initial and boundary value problem are demonstrated which serves as the basis for the optimal control problem synthesis. An industrial application of the crystal temperature regulation problem for the Czochralski crystal growth process is considered and numerical simulation results are provided.
A river water quality model for time varying BOD discharge concentration
Directory of Open Access Journals (Sweden)
Oppenheimer Seth F.
1999-01-01
Full Text Available We consider a model for biochemical oxygen demand (BOD in a semi-infinite river where the BOD is prescribed by a time varying function at the left endpoint. That is, we study the problem with a time varying boundary loading. We obtain the well-posedness for the model when the boundary loading is smooth in time. We also obtain various qualitative results such as ordering, positivity, and boundedness. Of greatest interest, we show that a periodic loading function admits a unique asymptotically attracting periodic solution. For non-smooth loading functions, we obtain weak solutions. Finally, for certain special cases, we show how to obtain explicit solutions in the form of infinite series.
Robust Fusion Filtering for Multisensor Time-Varying Uncertain Systems: The Finite Horizon Case
Directory of Open Access Journals (Sweden)
Xiaoliang Feng
2016-01-01
Full Text Available The robust H∞ fusion filtering problem is considered for linear time-varying uncertain systems observed by multiple sensors. A performance index function for this problem is defined as an indefinite quadratic inequality which is solved by the projection method in Krein space. On this basis, a robust centralized finite horizon H∞ fusion filtering algorithm is proposed. However, this centralized fusion method is with poor real time property, as the number of sensors increases. To resolve this difficulty, within the sequential fusion framework, the performance index function is described as a set of quadratic inequalities including an indefinite quadratic inequality. And a sequential robust finite horizon H∞ fusion filtering algorithm is given by solving this quadratic inequality group. Finally, two simulation examples for time-varying/time-invariant multisensor systems are exploited to demonstrate the effectiveness of the proposed methods in the respect of the real time property and filtering accuracy.
From calls to communities: a model for time varying social networks
Laurent, Guillaume; Karsai, Márton
2015-01-01
Social interactions vary in time and appear to be driven by intrinsic mechanisms, which in turn shape the emerging structure of the social network. Large-scale empirical observations of social interaction structure have become possible only recently, and modelling their dynamics is an actual challenge. Here we propose a temporal network model which builds on the framework of activity-driven time-varying networks with memory. The model also integrates key mechanisms that drive the formation of social ties - social reinforcement, focal closure and cyclic closure, which have been shown to give rise to community structure and the global connectedness of the network. We compare the proposed model with a real-world time-varying network of mobile phone communication and show that they share several characteristics from heterogeneous degrees and weights to rich community structure. Further, the strong and weak ties that emerge from the model follow similar weight-topology correlations as real-world social networks, i...
1986-01-01
The voltage-dependent action of several scorpion alpha-toxins on Na channels was studied in toad myelinated nerve under voltage clamp. These toxins slow the declining phase of macroscopic Na current, apparently by inhibiting an irreversible channel inactivation step and thus permitting channels to reopen from a closed state in depolarized membranes. In this article, we describe the rapid reversal of alpha- toxin action by membrane depolarizations more positive than +20 mV, an effect not achieved by extensive washing. Depolarizations that were increasingly positive and of longer duration caused the toxin to dissociate faster and more completely, but only up to a limiting extent. Repetitive pulses had a cumulative effect equal to that of a single pulse lasting as long as their combined duration. When the membrane of a nonperfused fiber was repolarized, the effects of the toxin returned completely, but if the fiber was perfused during the conditioning procedure, recovery was incomplete and occurred more slowly, as it did at lower applied toxin concentrations. Other alpha- type toxins, from the scorpion Centruroides sculpturatus (IVa) and the sea anemone Anemonia sulcata (ATXII), exhibited similar voltage- dependent binding, though each had its own voltage range and dissociation rate. We suggest that the dissociation of the toxin molecule from the Na channel is coupled to the inactivation process. An equivalent valence for inactivation gating, of less than 1 e per channel, is calculated from the voltage-dependent change in toxin affinity. PMID:2428923
Almirall, Daniel; Griffin, Beth Ann; McCaffrey, Daniel F.; Ramchand, Rajeev; Yuen, Robert A.; Murphy, Susan A.
2014-01-01
This article considers the problem of examining time-varying causal effect moderation using observational, longitudinal data in which treatment, candidate moderators, and possible confounders are time varying. The structural nested mean model (SNMM) is used to specify the moderated time-varying causal effects of interest in a conditional mean model for a continuous response given time-varying treatments and moderators. We present an easy-to-use estimator of the SNMM that combines an existing regression-with-residuals (RR) approach with an inverse-probability-of-treatment weighting (IPTW) strategy. The RR approach has been shown to identify the moderated time-varying causal effects if the time-varying moderators are also the sole time-varying confounders. The proposed IPTW+RR approach provides estimators of the moderated time-varying causal effects in the SNMM in the presence of an additional, auxiliary set of known and measured time-varying confounders. We use a small simulation experiment to compare IPTW+RR versus the traditional regression approach and to compare small and large sample properties of asymptotic versus bootstrap estimators of the standard errors for the IPTW+RR approach. This article clarifies the distinction between time-varying moderators and time-varying confounders. We illustrate the methodology in a case study to assess if time-varying substance use moderates treatment effects on future substance use. PMID:23873437
Hawrilenko, Matt; Eubanks Fleming, C J; Goldstein, Alana S; Cordova, James V
2016-07-01
Studies regarding the effectiveness of homework assignments in cognitive-behavioral treatments have demonstrated mixed results. This study investigated predictors of compliance with homework recommendations and the time-varying relationship of recommendation completion with treatment response in a brief couples' intervention (N = 108). More satisfied couples and couples with more motivation to change completed more recommendations, whereas couples with children completed fewer. The association between recommendation completion and treatment response varied with the passage of time, with the strongest effect observed 6 months after the intervention, but no discernible differences at 1 year postintervention. Couples that completed more recommendations experienced more rapid treatment gains, but even those couples doing substantially fewer recommendations ultimately realized equivalent treatment effects, although they progressed more slowly. Implications are discussed. © 2015 American Association for Marriage and Family Therapy.
Hawrilenko, Matt; Fleming, CJ Eubanks; Goldstein, Alana; Cordova, James V.
2015-01-01
Studies regarding the effectiveness of homework assignments in cognitive-behavioral treatments have demonstrated mixed results. This study investigated predictors of compliance with homework recommendations and the time-varying relationship of recommendation completion with treatment response in a brief couples intervention (N=108). More satisfied couples and couples with more motivation to change completed more recommendations, whereas couples with children completed fewer. The association between recommendation completion and treatment response varied with the passage of time, with the strongest effect observed six-months after the intervention, but no discernible differences at one year post-intervention. Couples that completed more recommendations experienced more rapid treatment gains, but even those couples doing substantially fewer recommendations ultimately realized equivalent treatment effects, although they progressed more slowly. Implications are discussed. PMID:26456167
Lan Liu; Ryan K. L. Ko; Guangming Ren; Xiaoping Xu
2017-01-01
As the adoption of Software Defined Networks (SDNs) grows, the security of SDN still has several unaddressed limitations. A key network security research area is in the study of malware propagation across the SDN-enabled networks. To analyze the spreading processes of network malware (e.g., viruses) in SDN, we propose a dynamic model with a time-varying community network, inspired by research models on the spread of epidemics in complex networks across communities. We assume subnets of the ne...
Estimation and Properties of a Time-Varying GQARCH(1,1-M Model
Directory of Open Access Journals (Sweden)
Sofia Anyfantaki
2011-01-01
analysis of these models computationally infeasible. This paper outlines the issues and suggests to employ a Markov chain Monte Carlo algorithm which allows the calculation of a classical estimator via the simulated EM algorithm or a simulated Bayesian solution in only ( computational operations, where is the sample size. Furthermore, the theoretical dynamic properties of a time-varying GQARCH(1,1-M are derived. We discuss them and apply the suggested Bayesian estimation to three major stock markets.
Real-Time Adaptation to Time-Varying Constraints for Medical Video Communications.
Antoniou, Zinonas C; Panayides, Andreas S; Pantziaris, Marios; Constantinides, Anthony G; Pattichis, Constantinos S; Pattichis, Marios S
2017-07-12
The wider adoption of mobile Health (mHealth) video communication systems in standard clinical practice requires real-time control to provide for adequate levels of clinical video quality to support reliable diagnosis. The latter can only be achieved with real-time adaptation to time-varying wireless networks' state to guarantee clinically acceptable performance throughout the streaming session, while conforming to device capabilities for supporting real-time encoding.
Improved Stability Analysis for Neural Networks with Time-Varying Delay
Directory of Open Access Journals (Sweden)
Yongming Li
2012-01-01
Full Text Available This paper concerned the problem of delay-dependent asymptotic stability for neural networks with time-varying delay. A new class of Lyapunov functional dividing the interval delay is constructed to derive some new delay-dependent stability criteria. The obtained criteria are less conservative because free-weighting matrices method, a convex optimization approach, and a mixed dividing delay interval approach are considered. Finally, numerical examples are given to illustrate the effectiveness of the proposed method.
Comparison of Guidance Modes for the AUV "Slocum Glider" in Time-Varying Ocean Flows
Eichhorn, Mike; Woithe, Hans Christian; Kremer, Ulrich
2017-01-01
This paper presents possibilities for the reliable guidance of an AUV "Slocum Glider" in time-varying ocean flows. The presented guidance modes consider the restricted information during a real mission about the actual position and ocean current conditions as well as the available control modes of a glider. A faster-than-real-time, full software stack simulator for the Slocum glider will be described in order to test the developed guidance modes under real mission conditions.
Bayesian Forecasting of WWW Traffic on the Time Varying Poisson Model
Koizumi, Daiki; Matsushima, Toshiyasu; Hirasawa, Shigeichi
2009-01-01
Traffic forecasting from past observed traffic data with small calculation complexity is one of important problems for planning of servers and networks. Focusing on World Wide Web (WWW) traffic as fundamental investigation, this paper would deal with Bayesian forecasting of network traffic on the time varying Poisson model from a viewpoint from statistical decision theory. Under this model, we would show that the estimated forecasting value is obtained by simple arithmetic calculation and exp...
Constructions of Strict Lyapunov Functions for Discrete Time and Hybrid Time-Varying Systems
Malisoff, Michael; Mazenc, Frédéric
2006-01-01
We provide explicit closed form expressions for strict Lyapunov functions for time-varying discrete time systems. Our Lyapunov functions are expressed in terms of known nonstrict Lyapunov functions for the dynamics and finite sums of persistency of excitation parameters. This provides a discrete time analog of our previous continuous time Lyapunov function constructions. We also construct explicit strict Lyapunov functions for systems satisfying nonstrict discrete time analogs of the conditio...
New convolutional code constructions and a class of asymptotically good time-varying codes
DEFF Research Database (Denmark)
Justesen, Jørn
1973-01-01
We show that the generator polynomials of certain cyclic codes define noncatastrophic fixed convolutional codes whose free distances are lowerbounded by the minimum distances of the cyclic codes. This result is used to construct convolutioual codes with free distance equal to the constraint length...... and to derive convolutional codes with good free distances from the BCH codes. Finally, a class of time-varying codes is constructed for which the free distance increases linearly with the constraint length....
Time-varying effects of a text-based smoking cessation intervention for urban adolescents.
Mason, Michael; Mennis, Jeremy; Way, Thomas; Lanza, Stephanie; Russell, Michael; Zaharakis, Nikola
2015-12-01
Craving to smoke is understood as an important mechanism for continued smoking behavior. Identifying how smoking interventions operate on craving with particular populations is critical for advancing intervention science. This study's objective was to investigate the time-varying effect of a text-delivered smoking cessation intervention. Toward this end, we used ecological momentary assessment (EMA) data collected from a five-day, automated text-messaging smoking cessation randomized clinical trial with 200 urban adolescents. We employed a time-varying effect model (TVEM) to estimate the effects of stress (time-varying covariate) and baseline nicotine dependence level (time-invariant covariate) on craving over six months by treatment condition. The TVEM approach models behavioral change and associations of coefficients expressed dynamically and graphically represented as smooth functions of time. Controlling for gender, age, and current smoking, differences in trajectories of craving between intervention and control conditions were apparent over the course of the study. During months 2 to 3, the association between stress and craving was significantly stronger among the control group, suggesting treatment dampens this association during this time period. The intervention also reduced the salience of baseline dependence among treatment adolescents, with craving being reduced steadily over time, while the control group increased craving over time. These results provide insight into the time-varying nature of treatment effects for adolescents receiving a text-based smoking cessation intervention. The ability to specify when in the course of an intervention the effect is strongest is important in developing targeted and adaptive interventions that can adjust strategically with time. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Improving Delay-Range-Dependent Stability Condition for Systems with Interval Time-Varying Delay
Directory of Open Access Journals (Sweden)
Wei Qian
2013-01-01
Full Text Available This paper discusses the delay-range-dependent stability for systems with interval time-varying delay. Through defining the new Lyapunov-Krasovskii functional and estimating the derivative of the LKF by introducing new vectors, using free matrices and reciprocally convex approach, the new delay-range-dependent stability conditions are obtained. Two well-known examples are given to illustrate the less conservatism of the proposed theoretical results.
Omidvarnia, Amir; Azemi, Ghasem; Boashash, Boualem; Otoole, John M.; Colditz, Paul B.; Vanhatalo, Sampsa
2014-01-01
This study aimed to develop a time-frequency method for measuring directional interactions over time and frequency from scalp-recorded electroencephalographic (EEG) signals in a way that is less affected by volume conduction and amplitude scaling. We modified the time-varying generalized partial directed coherence (tv-gPDC) method, by orthogonalization of the strictly causal multivariate autoregressive model coefficients, to minimize the effect of mutual sources. The novel measure, generalize...
Modal Vibration Control in Periodic Time-Varying Structures with Focus on Rotor Blade Systems
DEFF Research Database (Denmark)
Christensen, Rene Hardam; Santos, Ilmar
2004-01-01
to be overcome. Among others it is necessary, that the control scheme is capable to cope with non-linear time-varying dynamical system behaviour. However, rotating at constant speed the mathematical model becomes periodic time-variant. In this framework the present paper gives a contribution to design procedures...... to demonstrate the applicability and effectiveness of the technique. The results obtained shows that the control design technique is capable to cope with the time periodicity of this class of systems....
Modal Vibration Control in Periodic Time-Varying Structures with Focus on Rotor-Blade Systems
DEFF Research Database (Denmark)
Christensen, Rene Hardam; Santos, Ilmar
2003-01-01
to be overcome. Among others it is necessary, that the control scheme is capable to cope with non-linear time-varying dynamical system behaviour. However, rotating at constant speed the mathematical model becomes periodic time-variant. In this framework the present paper gives a contribution to design procedures...... to demonstrate the applicability and effectiveness of the technique. The results obtained shows that the control design technique is capable to cope with the time periodicity of this class of systems....
Leader-Following Consensus in Networks of Agents with Nonuniform Time-Varying Delays
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Zhao-Jun Tang
2012-01-01
Full Text Available This paper is concerned with a leader-following consensus problem for networks of agents with fixed and switching topologies as well as nonuniform time-varying communication delays. By employing Lyapunov-Razumikhin function, a necessary and sufficient condition is derived in the case of fixed topology, and a sufficient condition is obtained in the case when the interconnection topology is switched and satisfies certain condition. Simulation results are provided to illustrate the theoretical results.
Multimodal Pilot Behavior in Multi-Axis Tracking Tasks with Time-Varying Motion Cueing Gains
Zaal, P. M. T; Pool, D. M.
2014-01-01
In a large number of motion-base simulators, adaptive motion filters are utilized to maximize the use of the available motion envelope of the motion system. However, not much is known about how the time-varying characteristics of such adaptive filters affect pilots when performing manual aircraft control. This paper presents the results of a study investigating the effects of time-varying motion filter gains on pilot control behavior and performance. An experiment was performed in a motion-base simulator where participants performed a simultaneous roll and pitch tracking task, while the roll and/or pitch motion filter gains changed over time. Results indicate that performance increases over time with increasing motion gains. This increase is a result of a time-varying adaptation of pilots' equalization dynamics, characterized by increased visual and motion response gains and decreased visual lead time constants. Opposite trends are found for decreasing motion filter gains. Even though the trends in both controlled axes are found to be largely the same, effects are less significant in roll. In addition, results indicate minor cross-coupling effects between pitch and roll, where a cueing variation in one axis affects the behavior adopted in the other axis.
Opinion formation in time-varying social networks: The case of Naming Game
Maity, Suman Kalyan; Mukherjee, Animesh
2012-01-01
We study the dynamics of the Naming Game as an opinion formation model on time-varying social networks. This agent-based model captures the essential features of the agreement dynamics by means of a memory-based negotiation process. Our study focuses on the impact of time-varying properties of the social network of the agents on the Naming Game dynamics. We investigate the outcomes of the dynamics on two different types of time-varying data - (i) the networks vary across days and (ii) the networks vary within very short intervals of time (20 seconds). In the first case, we find that networks with strong community structure hinder the system from reaching global agreement; the evolution of the Naming Game in these networks maintains clusters of coexisting opinions indefinitely leading to metastability. In the second case, we investigate the evolution of the Naming Game in perfect synchronization with the time evolution of the underlying social network shedding new light on the traditional emergent properties o...
Yoon, Heonjun; Kim, Miso; Park, Choon-Su; Youn, Byeng D.
2018-01-01
Piezoelectric vibration energy harvesting (PVEH) has received much attention as a potential solution that could ultimately realize self-powered wireless sensor networks. Since most ambient vibrations in nature are inherently random and nonstationary, the output performances of PVEH devices also randomly change with time. However, little attention has been paid to investigating the randomly time-varying electroelastic behaviors of PVEH systems both analytically and experimentally. The objective of this study is thus to make a step forward towards a deep understanding of the time-varying performances of PVEH devices under nonstationary random vibrations. Two typical cases of nonstationary random vibration signals are considered: (1) randomly-varying amplitude (amplitude modulation; AM) and (2) randomly-varying amplitude with randomly-varying instantaneous frequency (amplitude and frequency modulation; AM-FM). In both cases, this study pursues well-balanced correlations of analytical predictions and experimental observations to deduce the relationships between the time-varying output performances of the PVEH device and two primary input parameters, such as a central frequency and an external electrical resistance. We introduce three correlation metrics to quantitatively compare analytical prediction and experimental observation, including the normalized root mean square error, the correlation coefficient, and the weighted integrated factor. Analytical predictions are in an excellent agreement with experimental observations both mechanically and electrically. This study provides insightful guidelines for designing PVEH devices to reliably generate electric power under nonstationary random vibrations.
Tracking control of time-varying knee exoskeleton disturbed by interaction torque.
Li, Zhan; Ma, Wenhao; Yin, Ziguang; Guo, Hongliang
2017-11-01
Knee exoskeletons have been increasingly applied as assistive devices to help lower-extremity impaired people to make their knee joints move through providing external movement compensation. Tracking control of knee exoskeletons guided by human intentions often encounters time-varying (time-dependent) issues and the disturbance interaction torque, which may dramatically put an influence up on their dynamic behaviors. Inertial and viscous parameters of knee exoskeletons can be estimated to be time-varying due to unexpected mechanical vibrations and contact interactions. Moreover, the interaction torque produced from knee joint of wearers has an evident disturbance effect on regular motions of knee exoskeleton. All of these points can increase difficultly of accurate control of knee exoskeletons to follow desired joint angle trajectories. This paper proposes a novel control strategy for controlling knee exoskeleton with time-varying inertial and viscous coefficients disturbed by interaction torque. Such designed controller is able to make the tracking error of joint angle of knee exoskeletons exponentially converge to zero. Meanwhile, the proposed approach is robust to guarantee the tracking error bounded when the interaction torque exists. Illustrative simulation and experiment results are presented to show efficiency of the proposed controller. Additionally, comparisons with gradient dynamic (GD) approach and other methods are also presented to demonstrate efficiency and superiority of the proposed control strategy for tracking joint angle of knee exoskeleton. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Smart panel with time-varying shunted piezoelectric patch absorbers for broadband vibration control
Casagrande, D.; Gardonio, P.; Zilletti, M.
2017-07-01
This paper presents a simulation study concerning the low and mid frequencies control of flexural vibration in a lightly damped thin plate equipped with five time-varying shunted piezoelectric patch absorbers. The panel is excited by a rain-on-the-roof broad frequency band stationary disturbance. The absorbers are composed by piezoelectric patches connected to time-varying RL shunt circuits. Discrete or continuous variations over time of the shunts are implemented in such a way as to either switch, between given values, or sweep, within certain ranges, the natural frequency and damping factor of the electro-mechanical absorbers to control either the resonant response of targeted flexural modes of the plate with natural frequency comprised between 30 Hz and 1 kHz or to control the resonant responses of all flexural modes with natural frequencies comprised between 30 Hz and 1 kHz. The proposed system is firstly presented; then, the vibration control effects produced by a single patch and by the array of five patches implementing the switching and sweeping shunts are investigated. Both time-varying operation modes produce significant vibration control effects, with reductions of the resonance peaks of the target resonances or target frequency band up to 12 dB. The piezoelectric patch absorbers with sweeping shunts offer an interesting practical solution since they are operated blindly, thus they do not require a system identification during installation and effectively work without on line tuning also on systems whose response may vary substantially in time.
A behavioral asset pricing model with a time-varying second moment
Energy Technology Data Exchange (ETDEWEB)
Chiarella, Carl [School of Finance and Economics, University of Technology, Sydney, P.O. Box 123, Broadway, NSW 2007 (Australia)]. E-mail: carl.chiarella@uts.edu.au; He Xuezhong [School of Finance and Economics, University of Technology, Sydney, P.O. Box 123, Broadway, NSW 2007 (Australia); Wang, Duo [LMAM, Department of Financial Mathematics, School of Mathematical Sciences, Peking University, Beijing 100871 (China)
2006-08-15
We develop a simple behavioral asset pricing model with fundamentalists and chartists in order to study price behavior in financial markets when chartists estimate both conditional mean and variance by using a weighted averaging process. Through a stability, bifurcation, and normal form analysis, the market impact of the weighting process and time-varying second moment are examined. It is found that the fundamental price becomes stable (unstable) when the activities from both types of traders are balanced (unbalanced). When the fundamental price becomes unstable, the weighting process leads to different price dynamics, depending on whether the chartists act as either trend followers or contrarians. It is also found that a time-varying second moment of the chartists does not change the stability of the fundamental price, but it does influence the stability of the bifurcations. The bifurcation becomes stable (unstable) when the chartists are more (less) concerned about the market risk characterized by the time-varying second moment. Different routes to complicated price dynamics are also observed. The analysis provides an analytical foundation for the statistical analysis of the corresponding stochastic version of this type of behavioral model.
Time-invariant measurement of time-varying bioimpedance using vector impedance analysis.
Sanchez, B; Louarroudi, E; Pintelon, R
2015-03-01
When stepped-sine impedance spectroscopy measurements are carried out on (periodically) time-varying bio-systems, the inherent time-variant (time-periodic) parts are traditionally ignored or mitigated by filtering. The latter, however, lacks theoretical foundation and, in this paper, it is shown that it only works under certain specific conditions. Besides, we propose an alternative method, based on multisine signals, that exploits the non-stationary nature in time-varying bio-systems with a dominant periodic character, such as cardiovascular and respiratory systems, or measurements interfered with by their physiological activities. The novel method extracts the best—in a mean square sense—linear time-invariant (BLTI) impedance approximation ZBLTI(jω) of a periodically time-varying (PTV) impedance ZPTV(jω, t) as well as its time-periodic part. Relying on the geometrical interpretation of the BLTI concept, a new impedance analysis tool, called vector impedance analysis (VIA), is also presented. The theoretical and practical aspects are validated through measurements performed on a PTV dummy circuit and on an in vivo myocardial tissue.
Rapid effects of 17beta-estradiol on epithelial TRPV6 Ca2+ channel in human T84 colonic cells.
LENUS (Irish Health Repository)
Irnaten, Mustapha
2008-11-01
The control of calcium homeostasis is essential for cell survival and is of crucial importance for several physiological functions. The discovery of the epithelial calcium channel Transient Receptor Potential Vaniloid (TRPV6) in intestine has uncovered important Ca(2+) absorptive pathways involved in the regulation of whole body Ca(2+) homeostasis. The role of steroid hormone 17beta-estradiol (E(2)), in [Ca(2+)](i) regulation involving TRPV6 has been only limited at the protein expression levels in over-expressing heterologous systems. In the present study, using a combination of calcium-imaging, whole-cell patch-clamp techniques and siRNA technology to specifically knockdown TRPV6 protein expression, we were able to (i) show that TRPV6 is natively, rather than exogenously, expressed at mRNA and protein levels in human T84 colonic cells, (ii) characterize functional TRPV6 channels and (iii) demonstrate, for the first time, the rapid effects of E(2) in [Ca(2+)](i) regulation involving directly TRPV6 channels in T84 cells. Treatment with E(2) rapidly (<5 min) enhanced [Ca(2+)](i) and this increase was partially but significantly prevented when cells were pre-treated with ruthenium red and completely abolished in cells treated with siRNA specifically targeting TRPV6 protein expression. These results indicate that when cells are stimulated by E(2), Ca(2+) enters the cell through TRPV6 channels. TRPV6 channels in T84 cells contribute to the Ca(2+) entry\\/signalling pathway that is sensitive to 17beta-estradiol.
A Kalman-filter based approach to identification of time-varying gene regulatory networks.
Directory of Open Access Journals (Sweden)
Jie Xiong
Full Text Available MOTIVATION: Conventional identification methods for gene regulatory networks (GRNs have overwhelmingly adopted static topology models, which remains unchanged over time to represent the underlying molecular interactions of a biological system. However, GRNs are dynamic in response to physiological and environmental changes. Although there is a rich literature in modeling static or temporally invariant networks, how to systematically recover these temporally changing networks remains a major and significant pressing challenge. The purpose of this study is to suggest a two-step strategy that recovers time-varying GRNs. RESULTS: It is suggested in this paper to utilize a switching auto-regressive model to describe the dynamics of time-varying GRNs, and a two-step strategy is proposed to recover the structure of time-varying GRNs. In the first step, the change points are detected by a Kalman-filter based method. The observed time series are divided into several segments using these detection results; and each time series segment belonging to two successive demarcating change points is associated with an individual static regulatory network. In the second step, conditional network structure identification methods are used to reconstruct the topology for each time interval. This two-step strategy efficiently decouples the change point detection problem and the topology inference problem. Simulation results show that the proposed strategy can detect the change points precisely and recover each individual topology structure effectively. Moreover, computation results with the developmental data of Drosophila Melanogaster show that the proposed change point detection procedure is also able to work effectively in real world applications and the change point estimation accuracy exceeds other existing approaches, which means the suggested strategy may also be helpful in solving actual GRN reconstruction problem.
Modelling time-varying volatility in the Indian stock returns: Some empirical evidence
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Trilochan Tripathy
2015-12-01
Full Text Available This paper models time-varying volatility in one of the Indian main stock markets, namely, the National Stock Exchange (NSE located in Mumbai, investigating whether it has been affected by the recent global financial crisis. A Chow test indicates the presence of a structural break. Both symmetric and asymmetric GARCH models suggest that the volatility of NSE returns is persistent and asymmetric and has increased as a result of the crisis. The model under the Generalized Error Distribution appears to be the most suitable one. However, its out-of-sample forecasting performance is relatively poor.
New Results of a Class of Two-Neuron Networks with Time-Varying Delays
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He Yigang
2008-01-01
Full Text Available With the help of the continuation theorem of the coincidence degree, a priori estimates, and differential inequalities, we make a further investigation of a class of planar systems, which is generalization of some existing neural networks under a time-varying environment. Without assuming the smoothness, monotonicity, and boundedness of the activation functions, a set of sufficient conditions is given for checking the existence of periodic solution and global exponential stability for such neural networks. The obtained results extend and improve some earlier publications.
Rajchakit, G; Saravanakumar, R; Ahn, Choon Ki; Karimi, Hamid Reza
2017-02-01
This article examines the exponential stability analysis problem of generalized neural networks (GNNs) including interval time-varying delayed states. A new improved exponential stability criterion is presented by establishing a proper Lyapunov-Krasovskii functional (LKF) and employing new analysis theory. The improved reciprocally convex combination (RCC) and weighted integral inequality (WII) techniques are utilized to obtain new sufficient conditions to ascertain the exponential stability result of such delayed GNNs. The superiority of the obtained results is clearly demonstrated by numerical examples. Copyright © 2016 Elsevier Ltd. All rights reserved.
Computing and visualizing time-varying merge trees for high-dimensional data
Energy Technology Data Exchange (ETDEWEB)
Oesterling, Patrick [Univ. of Leipzig (Germany); Heine, Christian [Univ. of Kaiserslautern (Germany); Weber, Gunther H. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Morozov, Dmitry [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Scheuermann, Gerik [Univ. of Leipzig (Germany)
2017-06-03
We introduce a new method that identifies and tracks features in arbitrary dimensions using the merge tree -- a structure for identifying topological features based on thresholding in scalar fields. This method analyzes the evolution of features of the function by tracking changes in the merge tree and relates features by matching subtrees between consecutive time steps. Using the time-varying merge tree, we present a structural visualization of the changing function that illustrates both features and their temporal evolution. We demonstrate the utility of our approach by applying it to temporal cluster analysis of high-dimensional point clouds.
Directory of Open Access Journals (Sweden)
Yueyang Li
2014-01-01
Full Text Available This paper investigates the H∞ fixed-lag fault estimator design for linear discrete time-varying (LDTV systems with intermittent measurements, which is described by a Bernoulli distributed random variable. Through constructing a novel partially equivalent dynamic system, the fault estimator design is converted into a deterministic quadratic minimization problem. By applying the innovation reorganization technique and the projection formula in Krein space, a necessary and sufficient condition is obtained for the existence of the estimator. The parameter matrices of the estimator are derived by recursively solving two standard Riccati equations. An illustrative example is provided to show the effectiveness and applicability of the proposed algorithm.
Distributed Event-Triggered Control of Multiagent Systems with Time-Varying Topology
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Jingwei Ma
2014-01-01
Full Text Available This paper studies the consensus of first-order discrete-time multiagent systems, where the interaction topology is time-varying. The event-triggered control is used to update the control input of each agent, and the event-triggering condition is designed based on the combination of the relative states of each agent to its neighbors. By applying the common Lyapunov function method, a sufficient condition for consensus, which is expressed as a group of linear matrix inequalities, is obtained and the feasibility of these linear matrix inequalities is further analyzed. Simulation examples are provided to explain the effectiveness of the theoretical results.
Control of Magnetic Bearings for Rotor Unbalance With Plug-In Time-Varying Resonators.
Kang, Christopher; Tsao, Tsu-Chin
2016-01-01
Rotor unbalance, common phenomenon of rotational systems, manifests itself as a periodic disturbance synchronized with the rotor's angular velocity. In active magnetic bearing (AMB) systems, feedback control is required to stabilize the open-loop unstable electromagnetic levitation. Further, feedback action can be added to suppress the repeatable runout but maintain closed-loop stability. In this paper, a plug-in time-varying resonator is designed by inverting cascaded notch filters. This formulation allows flexibility in designing the internal model for appropriate disturbance rejection. The plug-in structure ensures that stability can be maintained for varying rotor speeds. Experimental results of an AMB-rotor system are presented.
Modelling time-varying effects in Cox model under order restrictions
Salanti, Georgia; Ulm, Kurt
2003-01-01
The violation of the proportional hazards assumption in Cox model occurs quite often in studies concerning solid tumours or leukaemia. Then the time varying coefficients model is its most popular extension used. The function f(t) that measures the time variation of a covariate, can be assessed through several smoothing techniques, such as cubic splines. However, for practical propose, it is more convenient to assess f(t) by a step function. The main drawback of this approach is the lack of s...
A Test of the Adaptive Market Hypothesis using a Time-Varying AR Model in Japan
Akihiko Noda
2012-01-01
This study examines the adaptive market hypothesis (AMH) in Japanese stock markets (TOPIX and TSE2). In particular, we measure the degree of market efficiency by using a time-varying model approach. The empirical results show that (1) the degree of market efficiency changes over time in the two markets, (2) the level of market efficiency of the TSE2 is lower than that of the TOPIX in most periods, and (3) the market efficiency of the TOPIX has evolved, but that of the TSE2 has not. We conclud...
Time-Varying Formation Controllers for Unmanned Aerial Vehicles Using Deep Reinforcement Learning
Conde, Ronny; Llata, José Ramón; Torre-Ferrero, Carlos
2017-01-01
We consider the problem of designing scalable and portable controllers for unmanned aerial vehicles (UAVs) to reach time-varying formations as quickly as possible. This brief confirms that deep reinforcement learning can be used in a multi-agent fashion to drive UAVs to reach any formation while taking into account optimality and portability. We use a deep neural network to estimate how good a state is, so the agent can choose actions accordingly. The system is tested with different non-high-...
Analysis on Passivity for Uncertain Neural Networks with Time-Varying Delays
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O. M. Kwon
2014-01-01
Full Text Available The problem of passivity analysis for neural networks with time-varying delays and parameter uncertainties is considered. By the consideration of newly constructed Lyapunov-Krasovskii functionals, improved sufficient conditions to guarantee the passivity of the concerned networks are proposed with the framework of linear matrix inequalities (LMIs, which can be solved easily by various efficient convex optimization algorithms. The enhancement of the feasible region of the proposed criteria is shown via two numerical examples by the comparison of maximum allowable delay bounds.
Theory of electromagnetic cyclotron wave growth in a time-varying magnetoplasma
Gail, William B.
1990-01-01
The effect of a time-dependent perturbation in the magnetoplasma on the wave and particle populations is investigated using the Kennel-Petchek (1966) approach. Perturbations in the cold plasma density, energetic particle distribution, and resonance condition are calculated on the basis of the ideal MHD assumption given an arbitrary compressional magnetic field perturbation. An equation is derived describing the time-dependent growth rate for parallel propagating electromagnetic cyclotron waves in a time-varying magnetoplasma with perturbations superimposed on an equilibrium configuration.
H∞ Consensus for Multiagent Systems with Heterogeneous Time-Varying Delays
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Beibei Wang
2013-01-01
Full Text Available We apply the linear matrix inequality method to consensus and H∞ consensus problems of the single integrator multiagent system with heterogeneous delays in directed networks. To overcome the difficulty caused by heterogeneous time-varying delays, we rewrite the multiagent system into a partially reduced-order system and an integral system. As a result, a particular Lyapunov function is constructed to derive sufficient conditions for consensus of multiagent systems with fixed (switched topologies. We also apply this method to the H∞ consensus of multiagent systems with disturbances and heterogeneous delays. Numerical examples are given to illustrate the theoretical results.
Integrated planning problem in supply chains with time-varying delivery
Wang, Hai-ying; Liu, Da-cheng; Ding, Hua; Guo, Fu
2011-10-01
We consider a serial supply chain consisting of a raw material supplier, a manufacturer, a distribution centre and a retailer in the presence of time-varying delivery between manufacturer facility and the retailer warehouse. Delivery time functions are developed based on practical data analysis and the cost models for both linear and non-linear delivery time functions are derived. Analytic solution for system with linear delivery times is derived and a search algorithm for system with non-linear delivery times is established. Finally, sensitivity analysis is made to help decision makers achieve a lower total cost in practice.
Online Estimation of Time-Varying Volatility Using a Continuous-Discrete LMS Algorithm
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Jacques Oksman
2008-09-01
Full Text Available The following paper addresses a problem of inference in financial engineering, namely, online time-varying volatility estimation. The proposed method is based on an adaptive predictor for the stock price, built from an implicit integration formula. An estimate for the current volatility value which minimizes the mean square prediction error is calculated recursively using an LMS algorithm. The method is then validated on several synthetic examples as well as on real data. Throughout the illustration, the proposed method is compared with both UKF and offline volatility estimation.
Carrier frequency offset estimation for OFDM systems with time-varying DC Offset
Liu, Tao; Li, Hanzhang
2012-12-01
Orthogonal frequency division multiplexing (OFDM) systems with direct-conversion architecture suffer from both carrier frequency offset (CFO) and dc offset (DCO). In this paper, we study CFO estimation problem for OFDM systems with time-varying DCO (TV-DCO) caused by gain mode switch of low noise amplifier (LNA). Based on linear approximation of TV-DCO, a blind algorithm is proposed for CFO estimation by means of DCO compensation and power leakage minimization. Performance of the proposed algorithm is demonstrated by simulations.
DEFF Research Database (Denmark)
Callot, Laurent; Kristensen, Johannes Tang
This paper studies vector autoregressive models with parsimoniously time-varying parameters. The parameters are assumed to follow parsimonious random walks, where parsimony stems from the assumption that increments to the parameters have a non-zero probability of being exactly equal to zero......, or parameters varying randomly.We characterize the finite sample properties of the Lasso by deriving upper bounds on the estimation and prediction errors that are valid with high probability, and provide asymptotic conditions under which these bounds tend to zero with probability tending to one.We also provide...
Scalar Aharonov–Bohm Phase in Ramsey Atom Interferometry under Time-Varying Potential
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Atsuo Morinaga
2016-08-01
Full Text Available In a Ramsey atom interferometer excited by two electromagnetic fields, if atoms are under a time-varying scalar potential during the interrogation time, the phase of the Ramsey fringes shifts owing to the scalar Aharonov–Bohm effect. The phase shift was precisely examined using a Ramsey atom interferometer with a two-photon Raman transition under the second-order Zeeman potential, and a formula for the phase shift was derived. Using the derived formula, the frequency shift due to the scalar Aharonov–Bohm effect in the frequency standards utilizing the Ramsey atom interferometer was discussed.
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Kanit Mukdasai
2012-01-01
Full Text Available This paper investigates the problem of robust exponential stability for linear parameter-dependent (LPD systems with discrete and distributed time-varying delays and nonlinear perturbations. Parameter dependent Lyapunov-Krasovskii functional, Leibniz-Newton formula, and linear matrix inequality are proposed to analyze the stability. On the basis of the estimation and by utilizing free-weighting matrices, new delay-dependent exponential stability criteria are established in terms of linear matrix inequalities (LMIs. Numerical examples are given to demonstrate the effectiveness and less conservativeness of the proposed methods.
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Wu Kun-Shan
2002-01-01
Full Text Available In this paper, an EOQ inventory model is depleted not only by time varying demand but also by Weibull distribution deterioration, in which the inventory is permitted to start with shortages and end without shortages. A theory is developed to obtain the optimal solution of the problem; it is then illustrated with the aid of several numerical examples. Moreover, we also assume that the holding cost is a continuous, non-negative and non-decreasing function of time in order to extend the EOQ model. Finally, sensitivity of the optimal solution to changes in the values of different system parameters is also studied.
Reliable dissipative control of high-speed train with probabilistic time-varying delays
Kaviarasan, B.; Sakthivel, R.; Shi, Y.
2016-12-01
This paper investigates the reliable dissipative control problem for high-speed trains (HSTs) under probabilistic time-varying sampling with a known upper bound on the sampling intervals. In particular, random variables obeying the Bernoulli distribution are considered to account for the probabilistic time-varying delays. Based on Lyapunov-Krasovskii functional approach which considers full use of the available information about actual sampling pattern, a new set of sufficient condition is established to guarantee that the HST can well track the desired speed and the relative spring displacement between the two neighbouring carriages is asymptotically stable and the corresponding error system is strictly ?-dissipative. The existence condition of the dissipativity-based reliable sampled-data controller is obtained in terms of a set of linear matrix inequalities which are delay-distribution-dependent, i.e. the solvability of the condition depends on not only the variation range of the delay but also the probability distribution of it. Moreover, different control processes for the HST system can be obtained from the proposed design procedure and hence it can reduce the time and cost. Finally, the effectiveness and benefits of the proposed control law is demonstrated through a numerical example by taking the experimental values of Japan Shinkansen HST.
Time-varying land subsidence detected by radar altimetry: California, Taiwan and north China
Hwang, Cheinway; Yang, Yuande; Kao, Ricky; Han, Jiancheng; Shum, C. K.; Galloway, Devin L.; Sneed, Michelle; Hung, Wei-Chia; Cheng, Yung-Sheng; Li, Fei
2016-06-01
Contemporary applications of radar altimetry include sea-level rise, ocean circulation, marine gravity, and icesheet elevation change. Unlike InSAR and GNSS, which are widely used to map surface deformation, altimetry is neither reliant on highly temporally-correlated ground features nor as limited by the available spatial coverage, and can provide long-term temporal subsidence monitoring capability. Here we use multi-mission radar altimetry with an approximately 23 year data-span to quantify land subsidence in cropland areas. Subsidence rates from TOPEX/POSEIDON, JASON-1, ENVISAT, and JASON-2 during 1992-2015 show time-varying trends with respect to displacement over time in California’s San Joaquin Valley and central Taiwan, possibly related to changes in land use, climatic conditions (drought) and regulatory measures affecting groundwater use. Near Hanford, California, subsidence rates reach 18 cm yr-1 with a cumulative subsidence of 206 cm, which potentially could adversely affect operations of the planned California High-Speed Rail. The maximum subsidence rate in central Taiwan is 8 cm yr-1. Radar altimetry also reveals time-varying subsidence in the North China Plain consistent with the declines of groundwater storage and existing water infrastructure detected by the Gravity Recovery And Climate Experiment (GRACE) satellites, with rates reaching 20 cm yr-1 and cumulative subsidence as much as 155 cm.
Finite-Time Reentry Attitude Control Using Time-Varying Sliding Mode and Disturbance Observer
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Xuzhong Wu
2015-01-01
Full Text Available This paper presents the finite-time attitude control problem for reentry vehicle with redundant actuators in consideration of planet uncertainties and external disturbances. Firstly, feedback linearization technique is used to cancel the nonlinearities of equations of motion to construct a basic mode for attitude controller. Secondly, two kinds of time-varying sliding mode control methods with disturbance observer are integrated with the basic mode in order to enhance the control performance and system robustness. One method is designed based on boundary layer technique and the other is a novel second-order sliding model control method. The finite-time stability analyses of both resultant closed-loop systems are carried out. Furthermore, after attitude controller produces the torque commands, an optimization control allocation approach is introduced to allocate them into aerodynamic surface deflections and on-off reaction control system thrusts. Finally, the numerical simulation results demonstrate that both of the time-varying sliding mode control methods are robust to uncertainties and disturbances without chattering phenomenon. Moreover, the proposed second-order sliding mode control method possesses better control accuracy.
Dynamic IQC-Based Control of Uncertain LFT Systems With Time-Varying State Delay.
Yuan, Chengzhi; Wu, Fen
2016-12-01
This paper presents a new exact-memory delay control scheme for a class of uncertain systems with time-varying state delay under the integral quadratic constraint (IQC) framework. The uncertain system is described as a linear fractional transformation model including a state-delayed linear time-invariant (LTI) system and time-varying structured uncertainties. The proposed exact-memory delay controller consists of a linear state-feedback control law and an additional term that captures the delay behavior of the plant. We first explore the delay stability and the L2 -gain performance using dynamic IQCs incorporated with quadratic Lyapunov functions. Then, the design of exact-memory controllers that guarantee desired L2 -gain performance is examined. The resulting delay control synthesis conditions are formulated in terms of linear matrix inequalities, which are convex on all design variables including the scaling matrices associated with the IQC multipliers. The IQC-based exact-memory control scheme provides a novel approach for delay control designs via convex optimization, and advances existing control methods in two important ways: 1) better controlled performance and 2) simplified design procedure with less computational cost. The effectiveness and advantages of the proposed approach have been demonstrated through numerical studies.
Inferring the mesoscale structure of layered, edge-valued, and time-varying networks
Peixoto, Tiago P.
2015-10-01
Many network systems are composed of interdependent but distinct types of interactions, which cannot be fully understood in isolation. These different types of interactions are often represented as layers, attributes on the edges, or as a time dependence of the network structure. Although they are crucial for a more comprehensive scientific understanding, these representations offer substantial challenges. Namely, it is an open problem how to precisely characterize the large or mesoscale structure of network systems in relation to these additional aspects. Furthermore, the direct incorporation of these features invariably increases the effective dimension of the network description, and hence aggravates the problem of overfitting, i.e., the use of overly complex characterizations that mistake purely random fluctuations for actual structure. In this work, we propose a robust and principled method to tackle these problems, by constructing generative models of modular network structure, incorporating layered, attributed and time-varying properties, as well as a nonparametric Bayesian methodology to infer the parameters from data and select the most appropriate model according to statistical evidence. We show that the method is capable of revealing hidden structure in layered, edge-valued, and time-varying networks, and that the most appropriate level of granularity with respect to the additional dimensions can be reliably identified. We illustrate our approach on a variety of empirical systems, including a social network of physicians, the voting correlations of deputies in the Brazilian national congress, the global airport network, and a proximity network of high-school students.
Performance of growth mixture models in the presence of time-varying covariates.
Diallo, Thierno M O; Morin, Alexandre J S; Lu, HuiZhong
2017-10-01
Growth mixture modeling is often used to identify unobserved heterogeneity in populations. Despite the usefulness of growth mixture modeling in practice, little is known about the performance of this data analysis technique in the presence of time-varying covariates. In the present simulation study, we examined the impacts of five design factors: the proportion of the total variance of the outcome explained by the time-varying covariates, the number of time points, the error structure, the sample size, and the mixing ratio. More precisely, we examined the impact of these factors on the accuracy of parameter and standard error estimates, as well as on the class enumeration accuracy. Our results showed that the consistent Akaike information criterion (CAIC), the sample-size-adjusted CAIC (SCAIC), the Bayesian information criterion (BIC), and the integrated completed likelihood criterion (ICL-BIC) proved to be highly reliable indicators of the true number of latent classes in the data, across design conditions, and that the sample-size-adjusted BIC (SBIC) also proved quite accurate, especially in larger samples. In contrast, the Akaike information criterion (AIC), the entropy, the normalized entropy criterion (NEC), and the classification likelihood criterion (CLC) proved to be unreliable indicators of the true number of latent classes in the data. Our results also showed that substantial biases in the parameter and standard error estimates tended to be associated with growth mixture models that included only four time points.
Dynamics of Foreign Exchange Networks: A Time-Varying Copula Approach
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Gang-Jin Wang
2014-01-01
Full Text Available Based on a time-varying copula approach and the minimum spanning tree (MST method, we propose a time-varying correlation network-based approach to investigate dynamics of foreign exchange (FX networks. In piratical terms, we choose the daily FX rates of 42 major currencies in the international FX market during the period of 2005–2012 as the empirical data. The empirical results show that (i the distributions of cross-correlation coefficients (distances in the international FX market (network are fat-tailed and negatively skewed; (ii financial crises during the analyzed period have a great effect on the FX network’s topology structure and lead to the US dollar becoming more centered in the MST; (iii the topological measures of the FX network show a large fluctuation and display long-range correlations; (iv the FX network has a long-term memory effect and presents a scale-free behavior in the most of time; and (v a great majority of links between currencies in the international FX market survive from one time to the next, and multistep survive rates of FX networks drop sharply as the time increases.
A Bloch-based procedure for dispersion analysis of lattices with periodic time-varying properties
Vila, Javier; Pal, Raj Kumar; Ruzzene, Massimo; Trainiti, Giuseppe
2017-10-01
We present a procedure for the systematic estimation of the dispersion properties of linear discrete systems with periodic time-varying coefficients. The approach relies on the analysis of a single unit cell, making use of Bloch theorem along with the application of a harmonic balance methodology over an imposed solution ansatz. The solution of the resulting eigenvalue problem is followed by a procedure that selects the eigen-solutions corresponding to the ansatz, which is a plane wave defined by a frequency-wavenumber pair. Examples on spring-mass superlattices demonstrate the effectiveness of the method at predicting the dispersion behavior of linear elastic media. The matrix formulation of the problem suggests the broad applicability of the proposed technique. Furthermore, it is shown how dispersion can inform about the dynamic behavior of time-modulated finite lattices. The technique can be extended to multiple areas of physics, such as acoustic, elastic and electromagnetic systems, where periodic time-varying material properties may be used to obtain non-reciprocal wave propagation.
Time-varying land subsidence detected by radar altimetry: California, Taiwan and north China
Hwang, Cheinway; Yang, Yuande; Kao, Ricky; Han, Jiancheng; Shum, C.K.; Galloway, Devin L.; Sneed, Michelle; Hung, Wei-Chia; Cheng, Yung-Sheng; Li, Fei
2016-01-01
Contemporary applications of radar altimetry include sea-level rise, ocean circulation, marine gravity, and ice sheet elevation change. Unlike InSAR and GNSS, which are widely used to map surface deformation, altimetry is neither reliant on highly temporally-correlated ground features nor as limited by the available spatial coverage, and can provide long-term temporal subsidence monitoring capability. Here we use multi-mission radar altimetry with an approximately 23 year data-span to quantify land subsidence in cropland areas. Subsidence rates from TOPEX/POSEIDON, JASON-1, ENVISAT, and JASON-2 during 1992–2015 show time-varying trends with respect to displacement over time in California’s San Joaquin Valley and central Taiwan, possibly related to changes in land use, climatic conditions (drought) and regulatory measures affecting groundwater use. Near Hanford, California, subsidence rates reach 18 cm/yr with a cumulative subsidence of 206 cm, which potentially could adversely affect operations of the planned California High-Speed Rail. The maximum subsidence rate in central Taiwan is 8 cm/yr. Radar altimetry also reveals time-varying subsidence in the North China Plain consistent with the declines of groundwater storage and existing water infrastructure detected by the Gravity Recovery And Climate Experiment (GRACE) satellites, with rates reaching 20 cm/yr and cumulative subsidence as much as 155 cm.
Asymptotic theory of time varying networks with burstiness and heterogeneous activation patterns
Burioni, Raffaella; Ubaldi, Enrico; Vezzani, Alessandro
2017-05-01
The recent availability of large-scale, time-resolved and high quality digital datasets has allowed for a deeper understanding of the structure and properties of many real-world networks. The empirical evidence of a temporal dimension prompted the switch of paradigm from a static representation of networks to a time varying one. In this work we briefly review the framework of time-varying-networks in real world social systems, especially focusing on the activity-driven paradigm. We develop a framework that allows for the encoding of three generative mechanisms that seem to play a central role in the social networks’ evolution: the individual’s propensity to engage in social interactions, its strategy in allocate these interactions among its alters and the burstiness of interactions amongst social actors. The functional forms and probability distributions encoding these mechanisms are typically data driven. A natural question arises if different classes of strategies and burstiness distributions, with different local scale behavior and analogous asymptotics can lead to the same long time and large scale structure of the evolving networks. We consider the problem in its full generality, by investigating and solving the system dynamics in the asymptotic limit, for general classes of ties allocation mechanisms and waiting time probability distributions. We show that the asymptotic network evolution is driven by a few characteristics of these functional forms, that can be extracted from direct measurements on large datasets.
Identification of time-varying structural dynamic systems - An artificial intelligence approach
Glass, B. J.; Hanagud, S.
1992-01-01
An application of the artificial intelligence-derived methodologies of heuristic search and object-oriented programming to the problem of identifying the form of the model and the associated parameters of a time-varying structural dynamic system is presented in this paper. Possible model variations due to changes in boundary conditions or configurations of a structure are organized into a taxonomy of models, and a variant of best-first search is used to identify the model whose simulated response best matches that of the current physical structure. Simulated model responses are verified experimentally. An output-error approach is used in a discontinuous model space, and an equation-error approach is used in the parameter space. The advantages of the AI methods used, compared with conventional programming techniques for implementing knowledge structuring and inheritance, are discussed. Convergence conditions and example problems have been discussed. In the example problem, both the time-varying model and its new parameters have been identified when changes occur.
Time-varying land subsidence detected by radar altimetry: California, Taiwan and north China.
Hwang, Cheinway; Yang, Yuande; Kao, Ricky; Han, Jiancheng; Shum, C K; Galloway, Devin L; Sneed, Michelle; Hung, Wei-Chia; Cheng, Yung-Sheng; Li, Fei
2016-06-21
Contemporary applications of radar altimetry include sea-level rise, ocean circulation, marine gravity, and icesheet elevation change. Unlike InSAR and GNSS, which are widely used to map surface deformation, altimetry is neither reliant on highly temporally-correlated ground features nor as limited by the available spatial coverage, and can provide long-term temporal subsidence monitoring capability. Here we use multi-mission radar altimetry with an approximately 23 year data-span to quantify land subsidence in cropland areas. Subsidence rates from TOPEX/POSEIDON, JASON-1, ENVISAT, and JASON-2 during 1992-2015 show time-varying trends with respect to displacement over time in California's San Joaquin Valley and central Taiwan, possibly related to changes in land use, climatic conditions (drought) and regulatory measures affecting groundwater use. Near Hanford, California, subsidence rates reach 18 cm yr(-1) with a cumulative subsidence of 206 cm, which potentially could adversely affect operations of the planned California High-Speed Rail. The maximum subsidence rate in central Taiwan is 8 cm yr(-1). Radar altimetry also reveals time-varying subsidence in the North China Plain consistent with the declines of groundwater storage and existing water infrastructure detected by the Gravity Recovery And Climate Experiment (GRACE) satellites, with rates reaching 20 cm yr(-1) and cumulative subsidence as much as 155 cm.
A GPU-Accelerated Approach for Feature Tracking in Time-Varying Imagery Datasets.
Peng, Chao; Sahani, Sandip; Rushing, John
2017-10-01
We propose a novel parallel connected component labeling (CCL) algorithm along with efficient out-of-core data management to detect and track feature regions of large time-varying imagery datasets. Our approach contributes to the big data field with parallel algorithms tailored for GPU architectures. We remove the data dependency between frames and achieve pixel-level parallelism. Due to the large size, the entire dataset cannot fit into cached memory. Frames have to be streamed through the memory hierarchy (disk to CPU main memory and then to GPU memory), partitioned, and processed as batches, where each batch is small enough to fit into the GPU. To reconnect the feature regions that are separated due to data partitioning, we present a novel batch merging algorithm to extract the region connection information across multiple batches in a parallel fashion. The information is organized in a memory-efficient structure and supports fast indexing on the GPU. Our experiment uses a commodity workstation equipped with a single GPU. The results show that our approach can efficiently process a weather dataset composed of terabytes of time-varying radar images. The advantages of our approach are demonstrated by comparing to the performance of an efficient CPU cluster implementation which is being used by the weather scientists.
Time-Varying Effects of Prognostic Factors Associated With Disease-Free Survival in Breast Cancer
Natarajan, Loki; Pu, Minya; Parker, Barbara A.; Thomson, Cynthia A.; Caan, Bette J.; Flatt, Shirley W.; Madlensky, Lisa; Hajek, Richard A.; Al-Delaimy, Wael K.; Saquib, Nazmus; Gold, Ellen B.
2009-01-01
Early detection and effective treatments have dramatically improved breast cancer survivorship, yet the risk of relapse persists even 15 years after the initial diagnosis. It is important to identify prognostic factors for late breast cancer events. The authors investigated time-varying effects of tumor characteristics on breast-cancer-free survival using data on 3,088 breast cancer survivors from 4 US states who participated in a randomized dietary intervention trial in 1995–2006, with maximum follow-up through 15 years (median, 9 years). A piecewise constant penalized spline approach incorporating time-varying coefficients was adopted, allowing for deviations from the proportional hazards assumption. This method is more flexible than standard approaches, provides direct estimates of hazard ratios across time intervals, and is computationally tractable. Having a stage II or III tumor was associated with a 3-fold higher hazard of breast cancer than having a stage I tumor during the first 2.5 years after diagnosis; this hazard ratio decreased to 2.1 after 7.7 years, but higher tumor stage remained a significant risk factor. Similar diminishing effects were found for poorly differentiated tumors. Interestingly, having a positive estrogen receptor status was protective up to 4 years after diagnosis but detrimental after 7.7 years (hazard ratio = 1.5). These results emphasize the importance of careful statistical modeling allowing for possibly time-dependent effects in long-term survivorship studies. PMID:19403844
Fixed-b Inference in the Presence of Time-Varying Volatility
DEFF Research Database (Denmark)
Demetrescu, Matei; Hanck, Christoph; Kruse, Robinson
, JTSA) and (iii) consider to select test statistics and asymptotics according to the outcome of a heteroscedasticity test, since small-b asymptotics deliver standard limiting distributions irrespective of the socalled variance profile of the series. We quantify the degree of size distortions from using......The fixed-b asymptotic framework provides refinements in the use of heteroskedasticity and autocorrelation consistent variance estimators. The resulting limiting distributions of t-statistics are, however, not pivotal when the unconditional variance changes over time. Such time-varying volatility...... the standard fixed-b approach assuming homoskedasticity and compare the effectiveness of the corrections via simulations. It turns out that the wild bootstrap approach is highly recommendable in terms of size and power. An application to testing for equal predictive ability using the Survey of Professional...
Efficiency or speculation? A time-varying analysis of European sovereign debt
Ferreira, Paulo
2018-01-01
The outbreak of the Greek debt crisis caused turmoil in European markets and drew attention to the problem of public debt and its consequences. The increase in the return rates of sovereign debts was one of these consequences. However, like any other asset, sovereign debt returns are expected to have a memoryless behaviour. Analysing a total of 15 European countries (Eurozone and non-Eurozone), and applying a time-varying analysis of the Hurst exponent, we found evidence of long-range memory in sovereign bonds. When analysing the spreads between each bond and the German one, it is possible to conclude that Eurozone countries' spreads show more evidence of long-range dependence. Considering the Eurozone countries most affected by the Eurozone crisis, that long-range dependence is more evident, but started before the crisis, which could be interpreted as possible speculation by investors.
A Time-Varied Probabilistic ON/OFF Switching Algorithm for Cellular Networks
Rached, Nadhir B.
2018-01-11
In this letter, we develop a time-varied probabilistic on/off switching planning method for cellular networks to reduce their energy consumption. It consists in a risk-aware optimization approach that takes into consideration the randomness of the user profile associated with each base station (BS). The proposed approach jointly determines (i) the instants of time at which the current active BS configuration must be updated due to an increase or decrease of the network traffic load, and (ii) the set of minimum BSs to be activated to serve the networks’ subscribers. Probabilistic metrics modeling the traffic profile variation are developed to trigger this dynamic on/off switching operation. Selected simulation results are then performed to validate the proposed algorithm for different system parameters.
Gu, Huaying; Liu, Zhixue; Weng, Yingliang
2017-04-01
The present study applies the multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) with spatial effects approach for the analysis of the time-varying conditional correlations and contagion effects among global real estate markets. A distinguishing feature of the proposed model is that it can simultaneously capture the spatial interactions and the dynamic conditional correlations compared with the traditional MGARCH models. Results reveal that the estimated dynamic conditional correlations have exhibited significant increases during the global financial crisis from 2007 to 2009, thereby suggesting contagion effects among global real estate markets. The analysis further indicates that the returns of the regional real estate markets that are in close geographic and economic proximities exhibit strong co-movement. In addition, evidence of significantly positive leverage effects in global real estate markets is also determined. The findings have significant implications on global portfolio diversification opportunities and risk management practices.
Time-Varying Transition Probability Matrix Estimation and Its Application to Brand Share Analysis
Chiba, Tomoaki; Akaho, Shotaro; Murata, Noboru
2017-01-01
In a product market or stock market, different products or stocks compete for the same consumers or purchasers. We propose a method to estimate the time-varying transition matrix of the product share using a multivariate time series of the product share. The method is based on the assumption that each of the observed time series of shares is a stationary distribution of the underlying Markov processes characterized by transition probability matrices. We estimate transition probability matrices for every observation under natural assumptions. We demonstrate, on a real-world dataset of the share of automobiles, that the proposed method can find intrinsic transition of shares. The resulting transition matrices reveal interesting phenomena, for example, the change in flows between TOYOTA group and GM group for the fiscal year where TOYOTA group’s sales beat GM’s sales, which is a reasonable scenario. PMID:28076383
Combined time-varying forecast based on the proper scoring approach for wind power generation
DEFF Research Database (Denmark)
Chen, Xingying; Jiang, Yu; Yu, Kun
2017-01-01
Compared with traditional point forecasts, combined forecast have been proposed as an effective method to provide more accurate forecasts than individual model. However, the literature and research focus on wind-power combined forecasts are relatively limited. Here, based on forecasting error dis...... demonstrate that the proposed method improves the accuracy of overall forecasts, even compared with a numerical weather prediction.......Compared with traditional point forecasts, combined forecast have been proposed as an effective method to provide more accurate forecasts than individual model. However, the literature and research focus on wind-power combined forecasts are relatively limited. Here, based on forecasting error...... distribution, a proper scoring approach is applied to combine plausible models to form an overall time-varying model for the next day forecasts, rather than weights-based combination. To validate the effectiveness of the proposed method, real data of 3 years were used for testing. Simulation results...
Directory of Open Access Journals (Sweden)
Li XinBin
2010-01-01
Full Text Available Global phase synchronization for a class of dynamical complex networks composed of multiinput multioutput pendulum-like systems with time-varying coupling delays is investigated. The problem of the global phase synchronization for the complex networks is equivalent to the problem of the asymptotical stability for the corresponding error dynamical networks. For reducing the conservation, no linearization technique is involved, but by Kronecker product, the problem of the asymptotical stability of the high dimensional error dynamical networks is reduced to the same problem of a class of low dimensional error systems. The delay-dependent criteria guaranteeing global asymptotical stability for the error dynamical complex networks in terms of Liner Matrix Inequalities (LMIs are derived based on free-weighting matrices technique and Lyapunov function. According to the convex characterization, a simple criterion is proposed. A numerical example is provided to demonstrate the effectiveness of the proposed results.
RBF Neural Network of Sliding Mode Control for Time-Varying 2-DOF Parallel Manipulator System
Directory of Open Access Journals (Sweden)
Haizhong Chen
2013-01-01
Full Text Available This paper presents a radial basis function (RBF neural network control scheme for manipulators with actuator nonlinearities. The control scheme consists of a time-varying sliding mode control (TVSMC and an RBF neural network compensator. Since the actuator nonlinearities are usually included in the manipulator driving motor, a compensator using RBF network is proposed to estimate the actuator nonlinearities and their upper boundaries. Subsequently, an RBF neural network controller that requires neither the evaluation of off-line dynamical model nor the time-consuming training process is given. In addition, Barbalat Lemma is introduced to help prove the stability of the closed control system. Considering the SMC controller and the RBF network compensator as the whole control scheme, the closed-loop system is proved to be uniformly ultimately bounded. The whole scheme provides a general procedure to control the manipulators with actuator nonlinearities. Simulation results verify the effectiveness of the designed scheme and the theoretical discussion.
Multistability and instability analysis of recurrent neural networks with time-varying delays.
Zhang, Fanghai; Zeng, Zhigang
2018-01-01
This paper provides new theoretical results on the multistability and instability analysis of recurrent neural networks with time-varying delays. It is shown that such n-neuronal recurrent neural networks have exactly [Formula: see text] equilibria, [Formula: see text] of which are locally exponentially stable and the others are unstable, where k 0 is a nonnegative integer such that k 0 ≤n. By using the combination method of two different divisions, recurrent neural networks can possess more dynamic properties. This method improves and extends the existing results in the literature. Finally, one numerical example is provided to show the superiority and effectiveness of the presented results. Copyright © 2017 Elsevier Ltd. All rights reserved.
Stability analysis of switched stochastic neural networks with time-varying delays.
Wu, Xiaotai; Tang, Yang; Zhang, Wenbing
2014-03-01
This paper is concerned with the global exponential stability of switched stochastic neural networks with time-varying delays. Firstly, the stability of switched stochastic delayed neural networks with stable subsystems is investigated by utilizing the mathematical induction method, the piecewise Lyapunov function and the average dwell time approach. Secondly, by utilizing the extended comparison principle from impulsive systems, the stability of stochastic switched delayed neural networks with both stable and unstable subsystems is analyzed and several easy to verify conditions are derived to ensure the exponential mean square stability of switched delayed neural networks with stochastic disturbances. The effectiveness of the proposed results is illustrated by two simulation examples. Copyright © 2013 Elsevier Ltd. All rights reserved.
H∞state estimation of stochastic memristor-based neural networks with time-varying delays.
Bao, Haibo; Cao, Jinde; Kurths, Jürgen; Alsaedi, Ahmed; Ahmad, Bashir
2018-03-01
This paper addresses the problem of H ∞ state estimation for a class of stochastic memristor-based neural networks with time-varying delays. Under the framework of Filippov solution, the stochastic memristor-based neural networks are transformed into systems with interval parameters. The present paper is the first to investigate the H ∞ state estimation problem for continuous-time Itô-type stochastic memristor-based neural networks. By means of Lyapunov functionals and some stochastic technique, sufficient conditions are derived to ensure that the estimation error system is asymptotically stable in the mean square with a prescribed H ∞ performance. An explicit expression of the state estimator gain is given in terms of linear matrix inequalities (LMIs). Compared with other results, our results reduce control gain and control cost effectively. Finally, numerical simulations are provided to demonstrate the efficiency of the theoretical results. Copyright © 2018 Elsevier Ltd. All rights reserved.
Pinning synchronization of memristor-based neural networks with time-varying delays.
Yang, Zhanyu; Luo, Biao; Liu, Derong; Li, Yueheng
2017-09-01
In this paper, the synchronization of memristor-based neural networks with time-varying delays via pinning control is investigated. A novel pinning method is introduced to synchronize two memristor-based neural networks which denote drive system and response system, respectively. The dynamics are studied by theories of differential inclusions and nonsmooth analysis. In addition, some sufficient conditions are derived to guarantee asymptotic synchronization and exponential synchronization of memristor-based neural networks via the presented pinning control. Furthermore, some improvements about the proposed control method are also discussed in this paper. Finally, the effectiveness of the obtained results is demonstrated by numerical simulations. Copyright © 2017 Elsevier Ltd. All rights reserved.
Passivity analysis of memristor-based impulsive inertial neural networks with time-varying delays.
Wan, Peng; Jian, Jigui
2018-02-15
This paper focuses on delay-dependent passivity analysis for a class of memristive impulsive inertial neural networks with time-varying delays. By choosing proper variable transformation, the memristive inertial neural networks can be rewritten as first-order differential equations. The memristive model presented here is regarded as a switching system rather than employing the theory of differential inclusion and set-value map. Based on matrix inequality and Lyapunov-Krasovskii functional method, several delay-dependent passivity conditions are obtained to ascertain the passivity of the addressed networks. In addition, the results obtained here contain those on the passivity for the addressed networks without impulse effects as special cases and can also be generalized to other neural networks with more complex pulse interference. Finally, one numerical example is presented to show the validity of the obtained results. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
Time-varying Entry Heating Profile Replication with a Rotating Arc Jet Test Article
Grinstead, Jay Henderson; Venkatapathy, Ethiraj; Noyes, Eric A.; Mach, Jeffrey J.; Empey, Daniel M.; White, Todd R.
2014-01-01
A new approach for arc jet testing of thermal protection materials at conditions approximating the time-varying conditions of atmospheric entry was developed and demonstrated. The approach relies upon the spatial variation of heat flux and pressure over a cylindrical test model. By slowly rotating a cylindrical arc jet test model during exposure to an arc jet stream, each point on the test model will experience constantly changing applied heat flux. The predicted temporal profile of heat flux at a point on a vehicle can be replicated by rotating the cylinder at a prescribed speed and direction. An electromechanical test model mechanism was designed, built, and operated during an arc jet test to demonstrate the technique.
A time-varying copula mixture for hedging the clean spark spread with wind power futures
DEFF Research Database (Denmark)
Christensen, Troels Sønderby; Pircalabu, Anca; Høg, Esben
2017-01-01
The recently introduced German wind power futures have brought the opportunity to address the problem of volume risk in wind power generation directly. In this paper we study the hedging benefits of these instruments in the context of gas-fired power plants by employing a strategy that allows...... trading in the spot clean spark spread and wind power futures. To facilitate hedging decisions, we propose a time-varying copula mixture for the joint behavior of the spot clean spark spread and the daily wind index. The model describes the data surprisingly well, both in terms of the marginals...... and the dependence structure, while being straightforward and easy to implement. Based on Monte Carlo simulations from the proposed model, the results indicate that significant benefits can be achieved by using wind power futures to hedge the spot clean spark spread. Moreover, a comparison study shows...
Mitigation of time-varying distortions in Nyquist-WDM systems using machine learning
Granada Torres, Jhon J.; Varughese, Siddharth; Thomas, Varghese A.; Chiuchiarelli, Andrea; Ralph, Stephen E.; Cárdenas Soto, Ana M.; Guerrero González, Neil
2017-11-01
We propose a machine learning-based nonsymmetrical demodulation technique relying on clustering to mitigate time-varying distortions derived from several impairments such as IQ imbalance, bias drift, phase noise and interchannel interference. Experimental results show that those impairments cause centroid movements in the received constellations seen in time-windows of 10k symbols in controlled scenarios. In our demodulation technique, the k-means algorithm iteratively identifies the cluster centroids in the constellation of the received symbols in short time windows by means of the optimization of decision thresholds for a minimum BER. We experimentally verified the effectiveness of this computationally efficient technique in multicarrier 16QAM Nyquist-WDM systems over 270 km links. Our nonsymmetrical demodulation technique outperforms the conventional QAM demodulation technique, reducing the OSNR requirement up to ∼0.8 dB at a BER of 1 × 10-2 for signals affected by interchannel interference.
Huang, Congzhi; Sira-Ramírez, Hebertt
2015-12-01
A flatness-based active disturbance rejection control approach is proposed to deal with the linear systems with unknown time-varying coefficients and external disturbances. By selecting appropriate nominal values for the parameters of the system, all the deviation between the nominal and actual dynamics of the controlled process, as well as all the external disturbances can be viewed as a total disturbance. Based on the accurately estimated total disturbance with the aid of the proposed extended state observer, a linear proportional derivative feedback control law taking into account the derivatives of the desired output is designed to eliminate the effect of the total disturbance on the system performance. Finally, the load frequency control problem of a single-area power system with non-reheated unit is employed as an illustrative example to demonstrate the effectiveness of the proposed approach.
Specification and testing of Multiplicative Time-Varying GARCH models with applications
DEFF Research Database (Denmark)
Amado, Cristina; Teräsvirta, Timo
2017-01-01
In this article, we develop a specification technique for building multiplicative time-varying GARCH models of Amado and Teräsvirta (2008, 2013). The variance is decomposed into an unconditional and a conditional component such that the unconditional variance component is allowed to evolve smoothly...... over time. This nonstationary component is defined as a linear combination of logistic transition functions with time as the transition variable. The appropriate number of transition functions is determined by a sequence of specification tests. For that purpose, a coherent modelling strategy based...... on statistical inference is presented. It is heavily dependent on Lagrange multiplier type misspecification tests. The tests are easily implemented as they are entirely based on auxiliary regressions. Finite-sample properties of the strategy and tests are examined by simulation. The modelling strategy...
Almost Periodic Solution for Memristive Neural Networks with Time-Varying Delays
Directory of Open Access Journals (Sweden)
Huaiqin Wu
2013-01-01
Full Text Available This paper is concerned with the dynamical stability analysis for almost periodic solution of memristive neural networks with time-varying delays. Under the framework of Filippov solutions, by applying the inequality analysis techniques, the existence and asymptotically almost periodic behavior of solutions are discussed. Based on the differential inclusions theory and Lyapunov functional approach, the stability issues of almost periodic solution are investigated, and a sufficient condition for the existence, uniqueness, and global exponential stability of the almost periodic solution is established. Moreover, as a special case, the condition which ensures the global exponential stability of a unique periodic solution is also presented for the considered memristive neural networks. Two examples are given to illustrate the validity of the theoretical results.
Directory of Open Access Journals (Sweden)
Ghassan Atmeh
2016-02-01
Full Text Available This paper deals with the control of lighter-than-air vehicles, more specifically the design of an integrated guidance, navigation and control (GNC scheme that is capable of navigating an airship through a series of constant-altitude, planar waypoints. Two guidance schemes are introduced, a track-specific guidance law and a proportional navigation guidance law, that provide the required signals to the corresponding controllers based on the airship position relative to a target waypoint. A novel implementation of the extended Kalman filter, namely the scheduled extended Kalman filter, estimates the required states and wind speed to enhance the performance of the track-specific guidance law in the presence of time-varying wind. The performance of the GNC system is tested using a high fidelity nonlinear dynamic simulation for a variety of flying conditions. Representative results illustrate the performance of the integrated system for chosen flight conditions.
Robust H∞ control of uncertain systems with two additive time-varying delays
Syed, Ali M.; Saravanakumar, R.
2015-09-01
This paper is concerned with the problem of delay-dependent robust H∞ control for a class of uncertain systems with two additive time-varying delays. A new suitable Lyapunov-Krasovskii functional (LKF) with triple integral terms is constructed and a tighter upper bound of the derivative of the LKF is derived. By applying a convex optimization technique, new delay-dependent robust H∞ stability criteria are derived in terms of linear matrix inequalities (LMI). Based on the stability criteria, a state feedback controller is designed such that the closed-loop system is asymptotically stable. Finally, numerical examples are given to illustrate the effectiveness of the proposed method. Comparison results show that our results are less conservative than the existing methods. Project supported by the Fund from the Department of Science and Technology of India (Grant No. SR/FTP/MS-039/2011).
Off-Line Robust Constrained MPC for Linear Time-Varying Systems with Persistent Disturbances
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P. Bumroongsri
2014-01-01
Full Text Available An off-line robust constrained model predictive control (MPC algorithm for linear time-varying (LTV systems is developed. A novel feature is the fact that both model uncertainty and bounded additive disturbance are explicitly taken into account in the off-line formulation of MPC. In order to reduce the on-line computational burdens, a sequence of explicit control laws corresponding to a sequence of positively invariant sets is computed off-line. At each sampling time, the smallest positively invariant set containing the measured state is determined and the corresponding control law is implemented in the process. The proposed MPC algorithm can guarantee robust stability while ensuring the satisfaction of input and output constraints. The effectiveness of the proposed MPC algorithm is illustrated by two examples.
Directory of Open Access Journals (Sweden)
Cao Jinde
2011-01-01
Full Text Available Abstract In this paper, an integral sliding mode control approach is presented to investigate synchronization of nonidentical chaotic neural networks with discrete and distributed time-varying delays as well as leakage delay. By considering a proper sliding surface and constructing Lyapunov-Krasovskii functional, as well as employing a combination of the free-weighting matrix method, Newton-Leibniz formulation and inequality technique, a sliding mode controller is designed to achieve the asymptotical synchronization of the addressed nonidentical neural networks. Moreover, a sliding mode control law is also synthesized to guarantee the reachability of the specified sliding surface. The provided conditions are expressed in terms of linear matrix inequalities, and are dependent on the discrete and distributed time delays as well as leakage delay. A simulation example is given to verify the theoretical results.
Decentralized H∞ Control of Interconnected Systems with Time-varying Delays
Directory of Open Access Journals (Sweden)
Amal Zouhri
2017-01-01
Full Text Available This paper focuses on the problem of delay dependent stability/stabilization of interconnected systems with time-varying delays. The approach is based on a new Lyapunov-Krasovskii functional. A decentralized delay-dependent stability analysis is performed to characterize linear matrix inequalities (LMIs based on the conditions under which every local subsystem of the linear interconnected delay system is asymptotically stable. Then we design a decentralized state-feedback stabilization scheme such that the family of closedloop feedback subsystems enjoys the delay-dependent asymptotic stability for each subsystem. The decentralized feedback gains are determined by convex optimization over LMIs. All the developed results are tested on a representative example and compared with some recent previous ones.
Directory of Open Access Journals (Sweden)
Wu Wen
2015-01-01
Full Text Available This study is concerned with the problem of new delay-dependent exponential stability criteria for neural networks (NNs with mixed time-varying delays via introducing a novel integral inequality approach. Specifically, first, by taking fully the relationship between the terms in the Leibniz-Newton formula into account, several improved delay-dependent exponential stability criteria are obtained in terms of linear matrix inequalities (LMIs. Second, together with some effective mathematical techniques and a convex optimization approach, less conservative conditions are derived by constructing an appropriate Lyapunov-Krasovskii functional (LKF. Third, the proposed methods include the least numbers of decision variables while keeping the validity of the obtained results. Finally, three numerical examples with simulations are presented to illustrate the validity and advantages of the theoretical results.
Randomized gradient-free method for multiagent optimization over time-varying networks.
Yuan, Deming; Ho, Daniel W C
2015-06-01
In this brief, we consider the multiagent optimization over a network where multiple agents try to minimize a sum of nonsmooth but Lipschitz continuous functions, subject to a convex state constraint set. The underlying network topology is modeled as time varying. We propose a randomized derivative-free method, where in each update, the random gradient-free oracles are utilized instead of the subgradients (SGs). In contrast to the existing work, we do not require that agents are able to compute the SGs of their objective functions. We establish the convergence of the method to an approximate solution of the multiagent optimization problem within the error level depending on the smoothing parameter and the Lipschitz constant of each agent's objective function. Finally, a numerical example is provided to demonstrate the effectiveness of the method.
End-of-the-year economic growth and time-varying expected returns
DEFF Research Database (Denmark)
Møller, Stig V.; Rangvid, Jesper
2015-01-01
We show that macroeconomic growth at the end of the year (fourth quarter or December) strongly influences expected returns on risky financial assets, whereas economic growth during the rest of the year does not. We find this pattern for many different asset classes, across different time periods...... quarters of the year. Our findings suggest that expected returns, risk aversion, and economic growth are particularly related at the end of the year, when we also expect consumers׳ portfolio adjustments to be concentrated......., and for US and international data. We also show that movements in the surplus consumption ratio of Campbell and Cochrane (1999) , a theoretically well-founded measure of time-varying risk aversion linked to macroeconomic growth, influence expected returns stronger during the fourth quarter than the other...
Estimating time-varying conditional correlations between stock and foreign exchange markets
Tastan, Hüseyin
2006-02-01
This study explores the dynamic interaction between stock market returns and changes in nominal exchange rates. Many financial variables are known to exhibit fat tails and autoregressive variance structure. It is well-known that unconditional covariance and correlation coefficients also vary significantly over time and multivariate generalized autoregressive model (MGARCH) is able to capture the time-varying variance-covariance matrix for stock market returns and changes in exchange rates. The model is applied to daily Euro-Dollar exchange rates and two stock market indexes from the US economy: Dow-Jones Industrial Average Index and S&P500 Index. The news impact surfaces are also drawn based on the model estimates to see the effects of idiosyncratic shocks in respective markets.
Fault Detection for Non-Gaussian Stochastic Systems with Time-Varying Delay
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Tao Li
2013-01-01
Full Text Available Fault detection (FD for non-Gaussian stochastic systems with time-varying delay is studied. The available information for the addressed problem is the input and the measured output probability density functions (PDFs of the system. In this framework, firstly, by constructing an augmented Lyapunov functional, which involves some slack variables and a tuning parameter, a delay-dependent condition for the existence of FD observer is derived in terms of linear matrix inequality (LMI and the fault can be detected through a threshold. Secondly, in order to improve the detection sensitivity performance, the optimal algorithm is applied to minimize the threshold value. Finally, paper-making process example is given to demonstrate the applicability of the proposed approach.
An Explicit MOT-TD-VIE Solver for Time Varying Media
Sayed, Sadeed Bin
2016-03-15
An explicit marching on-in-time (MOT) scheme for solving the time domain electric field integral equation enforced on volumes with time varying dielectric permittivity is proposed. Unknowns of the integral equation and the constitutive relation, i.e., flux density and field intensity, are discretized using full and half Schaubert-Wilton-Glisson functions in space. Temporal interpolation is carried out using band limited approximate prolate spherical wave functions. The discretized coupled system of integral equation and constitutive relation is integrated in time using a PE(CE)m type linear multistep scheme. Unlike the existing MOT methods, the resulting explicit MOT scheme allows for straightforward incorporation of the time variation in the dielectric permittivity.
The co-movement of monetary policy and its time-varying nature: A DCCA approach
Rohit, Abhishek; Mitra, Subrata Kumar
2018-02-01
Employing a novel methodology of DCCA cross-correlation coefficient (ρDCCA), this study attempts to provide fresh evidences for the co-movement of monetary policies of the advanced (AEs) as well as the emerging economies (EMEs) vis-à-vis the United States. A higher degree of monetary co-movement as measured by ρDCCA values, is identified for the AEs as compared to the EMEs. Lower co-movement of monetary policy is especially noticeable in the short run for EMEs. We further investigate the time-varying nature of such co-movements for the AEs by splitting the period (1980-2014) into four sub periods and also by performing a rolling window estimation for the entire period to reveal smoother dynamics. Significant evidence of higher monetary coordination is revealed for sub-periods with stronger trade and financial linkages.
Alleviating Border Effects in Wavelet Transforms for Nonlinear Time-varying Signal Analysis
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SU, H.
2011-08-01
Full Text Available Border effects are very common in many finite signals analysis and processing approaches using convolution operation. Alleviating the border effects that can occur in the processing of finite-length signals using wavelet transform is considered in this paper. Traditional methods for alleviating the border effects are suitable to compression or coding applications. We propose an algorithm based on Fourier series which is proved to be appropriate to the application of time-frequency analysis of nonlinear signals. Fourier series extension method preserves the time-varying characteristics of the signals. A modified signal duration expression for measuring the extent of border effects region is presented. The proposed algorithm is confirmed to be efficient to alleviate the border effects in comparison to the current methods through the numerical examples.
A First-order Prediction-Correction Algorithm for Time-varying (Constrained) Optimization: Preprint
Energy Technology Data Exchange (ETDEWEB)
Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Simonetto, Andrea [Universite catholique de Louvain
2017-07-25
This paper focuses on the design of online algorithms based on prediction-correction steps to track the optimal solution of a time-varying constrained problem. Existing prediction-correction methods have been shown to work well for unconstrained convex problems and for settings where obtaining the inverse of the Hessian of the cost function can be computationally affordable. The prediction-correction algorithm proposed in this paper addresses the limitations of existing methods by tackling constrained problems and by designing a first-order prediction step that relies on the Hessian of the cost function (and do not require the computation of its inverse). Analytical results are established to quantify the tracking error. Numerical simulations corroborate the analytical results and showcase performance and benefits of the algorithms.
Statistical-Mechanical Analysis of LMS Algorithm for Time-Varying Unknown System
Ishibushi, Norihiro; Kajikawa, Yoshinobu; Miyoshi, Seiji
2017-02-01
We analyze the behaviors of the least-mean-square algorithm for a time-varying unknown system using a statistical-mechanical method. Cross-correlations between the elements of a primary path and those of an adaptive filter and autocorrelations of the elements of the adaptive filter are treated as macroscopic variables. We obtain simultaneous differential equations that describe the dynamical behaviors of the macroscopic variables under conditions in which the tapped delay line is sufficiently long. We analytically show the existence of an optimal step size. This result is supporting evidence of Widrow et al.'s pioneering work that clarified the trade-off between the noise misadjustment and the lag misadjustment. Furthermore, we obtain the exact solution of the optimal step size in the case of a white reference signal. The derived theory includes the behaviors for a time-constant unknown system as a special case.
Time-Varying Transition Probability Matrix Estimation and Its Application to Brand Share Analysis.
Chiba, Tomoaki; Hino, Hideitsu; Akaho, Shotaro; Murata, Noboru
2017-01-01
In a product market or stock market, different products or stocks compete for the same consumers or purchasers. We propose a method to estimate the time-varying transition matrix of the product share using a multivariate time series of the product share. The method is based on the assumption that each of the observed time series of shares is a stationary distribution of the underlying Markov processes characterized by transition probability matrices. We estimate transition probability matrices for every observation under natural assumptions. We demonstrate, on a real-world dataset of the share of automobiles, that the proposed method can find intrinsic transition of shares. The resulting transition matrices reveal interesting phenomena, for example, the change in flows between TOYOTA group and GM group for the fiscal year where TOYOTA group's sales beat GM's sales, which is a reasonable scenario.
Schlecht, Sebastian J; Habets, Emanuël A P
2015-09-01
This paper introduces a time-variant reverberation algorithm as an extension of the feedback delay network (FDN). By modulating the feedback matrix nearly continuously over time, a complex pattern of concurrent amplitude modulations of the feedback paths evolves. Due to its complexity, the modulation produces less likely perceivable artifacts and the time-variation helps to increase the liveliness of the reverberation tail. A listening test, which has been conducted, confirms that the perceived quality of the reverberation tail can be enhanced by the feedback matrix modulation. In contrast to the prior art time-varying allpass FDNs, it is shown that unitary feedback matrix modulation is guaranteed to be stable. Analytical constraints on the pole locations of the FDN help to describe the modulation effect in depth. Further, techniques and conditions for continuous feedback matrix modulation are presented.
Borsky, P. N.
1980-01-01
The design of a community noise survey to determine the effects of time varying noise exposures in residential communities is presented. Complex physical and human variables involved in the health and welfare effects of environmental noise and the number-level tradeoffs and time of day penalties are among the factors considered. Emphasis is placed on community reactions where noise exposures are equal in day or evening but differ in the night time, and the effects of ambient noise on more intense aircraft noise exposures. Thirteen different times of day and types of operation situations with exposed populations up to 8-10 miles from the airport are identified. A detailed personal interview questionnaire as well as specific instructions to interviewers are included.
Lebedev, Dmitry V; Steil, Jochen J; Ritter, Helge J
2005-04-01
We introduce a new type of neural network--the dynamic wave expansion neural network (DWENN)--for path generation in a dynamic environment for both mobile robots and robotic manipulators. Our model is parameter-free, computationally efficient, and its complexity does not explicitly depend on the dimensionality of the configuration space. We give a review of existing neural networks for trajectory generation in a time-varying domain, which are compared to the presented model. We demonstrate several representative simulative comparisons as well as the results of long-run comparisons in a number of randomly-generated scenes, which reveal that the proposed model yields dominantly shorter paths, especially in highly-dynamic environments.
Robust formation tracking control of mobile robots via one-to-one time-varying communication
Dasdemir, Janset; Loría, Antonio
2014-09-01
We solve the formation tracking control problem for mobile robots via linear control, under the assumption that each agent communicates only with one 'leader' robot and with one follower, hence forming a spanning-tree topology. We assume that the communication may be interrupted on intervals of time. As in the classical tracking control problem for non-holonomic systems, the swarm is driven by a fictitious robot which moves about freely and which is a leader to one robot only. Our control approach is decentralised and the control laws are linear with time-varying gains; in particular, this accounts for the case when position measurements may be lost over intervals of time. For both velocity-controlled and force-controlled systems, we establish uniform global exponential stability, hence consensus formation tracking, for the error system under a condition of persistency of excitation on the reference angular velocity of the virtual leader and on the control gains.
Magnetic design of a 3 T time-varying elliptical wiggler
Chang, C H; Hwang, C S; Huang Ming Hsiung; Fan, T C; Chen, H H; Lin, F Y
2000-01-01
This work describes the design of an elliptical wiggler capable of producing highly circular polarized light in the energy range of 1-10 keV. The time-varying elliptical wiggler consists of vertical and horizontal periodic magnet structures with a period length of 25 cm. The vertical magnetic field is generated by a hybrid permanent magnet structure with peak field strength of 3 T at a minimum gap of 12 mm. An iron core electromagnetic circuit that is shifted longitudinally by one-quarter period length relative to the vertical structure produces the AC horizontal magnetic field; it has peak field strength of 600 G. The right and left elliptically polarized light can be switched at a rate of 1 Hz. The magnetic field maximization and the spectral performance optimization are also presented.
Complete Periodic Synchronization of Memristor-Based Neural Networks with Time-Varying Delays
Directory of Open Access Journals (Sweden)
Huaiqin Wu
2013-01-01
Full Text Available This paper investigates the complete periodic synchronization of memristor-based neural networks with time-varying delays. Firstly, under the framework of Filippov solutions, by using M-matrix theory and the Mawhin-like coincidence theorem in set-valued analysis, the existence of the periodic solution for the network system is proved. Secondly, complete periodic synchronization is considered for memristor-based neural networks. According to the state-dependent switching feature of the memristor, the error system is divided into four cases. Adaptive controller is designed such that the considered model can realize global asymptotical synchronization. Finally, an illustrative example is given to demonstrate the validity of the theoretical results.
Directory of Open Access Journals (Sweden)
Baolin Qiu
2017-01-01
Full Text Available This paper concerns the problem of fixed/finite-time synchronization of hybrid coupled dynamical networks. The considered dynamical networks with multilinks contain only one transmittal time-varying delay for each subnetwork, which makes us get hold of more interesting and practical points. Two kinds of delay-dependent feedback controllers with multilinks as well as appropriate Lyapunov functions are defined to achieve the goal of fixed-time synchronization and finite-time synchronization for the networks. Some novel and effective criteria of hybrid coupled networks are derived based on fixed-time and finite-time stability analysis. Finally, two numerical simulation examples are given to show the effectiveness of the results proposed in our paper.
Lin, Wen-Juan; He, Yong; Zhang, Chuan-Ke; Wu, Min
2018-01-01
This paper is concerned with the stability analysis of neural networks with a time-varying delay. To assess system stability accurately, the conservatism reduction of stability criteria has attracted many efforts, among which estimating integral terms as exact as possible is a key issue. At first, this paper develops a new relaxed integral inequality to reduce the estimation gap of popular Wirtinger-based inequality (WBI). Then, for showing the advantages of the proposed inequality over several existing inequalities that also improve the WBI, four stability criteria are derived through different inequalities and the same Lyapunov-Krasovskii functional (LKF), and the conservatism comparison of them is analyzed theoretically. Moreover, an improved criterion is established by combining the proposed inequality and an augmented LKF with delay-product-type terms. Finally, several numerical examples are used to demonstrate the advantages of the proposed method.
Time-varying wing-twist improves aerodynamic efficiency of forward flight in butterflies.
Zheng, Lingxiao; Hedrick, Tyson L; Mittal, Rajat
2013-01-01
Insect wings can undergo significant chordwise (camber) as well as spanwise (twist) deformation during flapping flight but the effect of these deformations is not well understood. The shape and size of butterfly wings leads to particularly large wing deformations, making them an ideal test case for investigation of these effects. Here we use computational models derived from experiments on free-flying butterflies to understand the effect of time-varying twist and camber on the aerodynamic performance of these insects. High-speed videogrammetry is used to capture the wing kinematics, including deformation, of a Painted Lady butterfly (Vanessa cardui) in untethered, forward flight. These experimental results are then analyzed computationally using a high-fidelity, three-dimensional, unsteady Navier-Stokes flow solver. For comparison to this case, a set of non-deforming, flat-plate wing (FPW) models of wing motion are synthesized and subjected to the same analysis along with a wing model that matches the time-varying wing-twist observed for the butterfly, but has no deformation in camber. The simulations show that the observed butterfly wing (OBW) outperforms all the flat-plate wings in terms of usable force production as well as the ratio of lift to power by at least 29% and 46%, respectively. This increase in efficiency of lift production is at least three-fold greater than reported for other insects. Interestingly, we also find that the twist-only-wing (TOW) model recovers much of the performance of the OBW, demonstrating that wing-twist, and not camber is key to forward flight in these insects. The implications of this on the design of flapping wing micro-aerial vehicles are discussed.
Time-varying wing-twist improves aerodynamic efficiency of forward flight in butterflies.
Directory of Open Access Journals (Sweden)
Lingxiao Zheng
Full Text Available Insect wings can undergo significant chordwise (camber as well as spanwise (twist deformation during flapping flight but the effect of these deformations is not well understood. The shape and size of butterfly wings leads to particularly large wing deformations, making them an ideal test case for investigation of these effects. Here we use computational models derived from experiments on free-flying butterflies to understand the effect of time-varying twist and camber on the aerodynamic performance of these insects. High-speed videogrammetry is used to capture the wing kinematics, including deformation, of a Painted Lady butterfly (Vanessa cardui in untethered, forward flight. These experimental results are then analyzed computationally using a high-fidelity, three-dimensional, unsteady Navier-Stokes flow solver. For comparison to this case, a set of non-deforming, flat-plate wing (FPW models of wing motion are synthesized and subjected to the same analysis along with a wing model that matches the time-varying wing-twist observed for the butterfly, but has no deformation in camber. The simulations show that the observed butterfly wing (OBW outperforms all the flat-plate wings in terms of usable force production as well as the ratio of lift to power by at least 29% and 46%, respectively. This increase in efficiency of lift production is at least three-fold greater than reported for other insects. Interestingly, we also find that the twist-only-wing (TOW model recovers much of the performance of the OBW, demonstrating that wing-twist, and not camber is key to forward flight in these insects. The implications of this on the design of flapping wing micro-aerial vehicles are discussed.
Time-Varying Distortions of Binaural Information by Bilateral Hearing Aids
Rodriguez, Francisco A.; Portnuff, Cory D. F.; Goupell, Matthew J.; Tollin, Daniel J.
2016-01-01
In patients with bilateral hearing loss, the use of two hearing aids (HAs) offers the potential to restore the benefits of binaural hearing, including sound source localization and segregation. However, existing evidence suggests that bilateral HA users’ access to binaural information, namely interaural time and level differences (ITDs and ILDs), can be compromised by device processing. Our objective was to characterize the nature and magnitude of binaural distortions caused by modern digital behind-the-ear HAs using a variety of stimuli and HA program settings. Of particular interest was a common frequency-lowering algorithm known as nonlinear frequency compression, which has not previously been assessed for its effects on binaural information. A binaural beamforming algorithm was also assessed. Wide dynamic range compression was enabled in all programs. HAs were placed on a binaural manikin, and stimuli were presented from an arc of loudspeakers inside an anechoic chamber. Stimuli were broadband noise bursts, 10-Hz sinusoidally amplitude-modulated noise bursts, or consonant–vowel–consonant speech tokens. Binaural information was analyzed in terms of ITDs, ILDs, and interaural coherence, both for whole stimuli and in a time-varying sense (i.e., within a running temporal window) across four different frequency bands (1, 2, 4, and 6 kHz). Key findings were: (a) Nonlinear frequency compression caused distortions of high-frequency envelope ITDs and significantly reduced interaural coherence. (b) For modulated stimuli, all programs caused time-varying distortion of ILDs. (c) HAs altered the relationship between ITDs and ILDs, introducing large ITD–ILD conflicts in some cases. Potential perceptual consequences of measured distortions are discussed. PMID:27698258
Charbonneau, Jeremy
As the perceived quality of a product is becoming more important in the manufacturing industry, more emphasis is being placed on accurately predicting the sound quality of everyday objects. This study was undertaken to improve upon current prediction techniques with regard to the psychoacoustic descriptor of loudness and an improved binaural summation technique. The feasibility of this project was first investigated through a loudness matching experiment involving thirty-one subjects and pure tones of constant sound pressure level. A dependence of binaural summation on frequency was observed which had previously not been a subject of investigation in the reviewed literature. A follow-up investigation was carried out with forty-eight volunteers and pure tones of constant sensation level. Contrary to existing theories in literature the resulting loudness matches revealed an amplitude versus frequency relationship which confirmed the perceived increase in loudness when a signal was presented to both ears simultaneously as opposed to one ear alone. The resulting trend strongly indicated that the higher the frequency of the presented signal, the greater the increase in observed binaural summation. The results from each investigation were summarized into a single binaural summation algorithm and inserted into an improved time-varying loudness model. Using experimental techniques, it was demonstrated that the updated binaural summation algorithm was a considerable improvement over the state of the art approach for predicting the perceived binaural loudness. The improved function retained the ease of use from the original model while additionally providing accurate estimates of diotic listening conditions from monaural WAV files. It was clearly demonstrated using a validation jury test that the revised time-varying loudness model was a significant improvement over the previously standardized approach.
A hepatitis C virus infection model with time-varying drug effectiveness: solution and analysis.
Directory of Open Access Journals (Sweden)
Jessica M Conway
2014-08-01
Full Text Available Simple models of therapy for viral diseases such as hepatitis C virus (HCV or human immunodeficiency virus assume that, once therapy is started, the drug has a constant effectiveness. More realistic models have assumed either that the drug effectiveness depends on the drug concentration or that the effectiveness varies over time. Here a previously introduced varying-effectiveness (VE model is studied mathematically in the context of HCV infection. We show that while the model is linear, it has no closed-form solution due to the time-varying nature of the effectiveness. We then show that the model can be transformed into a Bessel equation and derive an analytic solution in terms of modified Bessel functions, which are defined as infinite series, with time-varying arguments. Fitting the solution to data from HCV infected patients under therapy has yielded values for the parameters in the model. We show that for biologically realistic parameters, the predicted viral decay on therapy is generally biphasic and resembles that predicted by constant-effectiveness (CE models. We introduce a general method for determining the time at which the transition between decay phases occurs based on calculating the point of maximum curvature of the viral decay curve. For the parameter regimes of interest, we also find approximate solutions for the VE model and establish the asymptotic behavior of the system. We show that the rate of second phase decay is determined by the death rate of infected cells multiplied by the maximum effectiveness of therapy, whereas the rate of first phase decline depends on multiple parameters including the rate of increase of drug effectiveness with time.
Local inertial oscillations in the surface ocean generated by time-varying winds
Chen, Shengli; Polton, Jeff A.; Hu, Jianyu; Xing, Jiuxing
2015-12-01
A new relationship is presented to give a review study on the evolution of inertial oscillations in the surface ocean locally generated by time-varying wind stress. The inertial oscillation is expressed as the superposition of a previous oscillation and a newly generated oscillation, which depends upon the time-varying wind stress. This relationship is employed to investigate some idealized wind change events. For a wind series varying temporally with different rates, the induced inertial oscillation is dominated by the wind with the greatest variation. The resonant wind, which rotates anti-cyclonically at the local inertial frequency with time, produces maximal amplitude of inertial oscillations, which grows monotonically. For the wind rotating at non-inertial frequencies, the responses vary periodically, with wind injecting inertial energy when it is in phase with the currents, but removing inertial energy when it is out of phase. The wind rotating anti-cyclonically with time is much more favorable to generate inertial oscillations than the cyclonic rotating wind. The wind with a frequency closer to the inertial frequency generates stronger inertial oscillations. For a diurnal wind, the induced inertial oscillation is dependent on latitude and is most significant at 30 °. This relationship is also applied to examine idealized moving cyclones. The inertial oscillation is much stronger on the right-hand side of the cyclone path than on the left-hand side (in the northern hemisphere). This is due to the wind being anti-cyclonic with time on the right-hand side, but cyclonic on the other side. The inertial oscillation varies with the cyclone translation speed. The optimal translation speed generating the greatest inertial oscillations is 2 m/s at the latitude of 10 ° and gradually increases to 6 m/s at the latitude of 30 °.
Using Graphs for Fast Error Term Approximation of Time-varying Datasets
Energy Technology Data Exchange (ETDEWEB)
Nuber, C; LaMar, E C; Pascucci, V; Hamann, B; Joy, K I
2003-02-27
We present a method for the efficient computation and storage of approximations of error tables used for error estimation of a region between different time steps in time-varying datasets. The error between two time steps is defined as the distance between the data of these time steps. Error tables are used to look up the error between different time steps of a time-varying dataset, especially when run time error computation is expensive. However, even the generation of error tables itself can be expensive. For n time steps, the exact error look-up table (which stores the error values for all pairs of time steps in a matrix) has a memory complexity and pre-processing time complexity of O(n2), and O(1) for error retrieval. Our approximate error look-up table approach uses trees, where the leaf nodes represent original time steps, and interior nodes contain an average (or best-representative) of the children nodes. The error computed on an edge of a tree describes the distance between the two nodes on that edge. Evaluating the error between two different time steps requires traversing a path between the two leaf nodes, and accumulating the errors on the traversed edges. For n time steps, this scheme has a memory complexity and pre-processing time complexity of O(nlog(n)), a significant improvement over the exact scheme; the error retrieval complexity is O(log(n)). As we do not need to calculate all possible n2 error terms, our approach is a fast way to generate the approximation.
Murugesan, Sugeerth; Bouchard, Kristofer; Chang, Edward; Dougherty, Max; Hamann, Bernd; Weber, Gunther H
2017-06-06
There exists a need for effective and easy-to-use software tools supporting the analysis of complex Electrocorticography (ECoG) data. Understanding how epileptic seizures develop or identifying diagnostic indicators for neurological diseases require the in-depth analysis of neural activity data from ECoG. Such data is multi-scale and is of high spatio-temporal resolution. Comprehensive analysis of this data should be supported by interactive visual analysis methods that allow a scientist to understand functional patterns at varying levels of granularity and comprehend its time-varying behavior. We introduce a novel multi-scale visual analysis system, ECoG ClusterFlow, for the detailed exploration of ECoG data. Our system detects and visualizes dynamic high-level structures, such as communities, derived from the time-varying connectivity network. The system supports two major views: 1) an overview summarizing the evolution of clusters over time and 2) an electrode view using hierarchical glyph-based design to visualize the propagation of clusters in their spatial, anatomical context. We present case studies that were performed in collaboration with neuroscientists and neurosurgeons using simulated and recorded epileptic seizure data to demonstrate our system's effectiveness. ECoG ClusterFlow supports the comparison of spatio-temporal patterns for specific time intervals and allows a user to utilize various clustering algorithms. Neuroscientists can identify the site of seizure genesis and its spatial progression during various the stages of a seizure. Our system serves as a fast and powerful means for the generation of preliminary hypotheses that can be used as a basis for subsequent application of rigorous statistical methods, with the ultimate goal being the clinical treatment of epileptogenic zones.
Time-Varying Wing-Twist Improves Aerodynamic Efficiency of Forward Flight in Butterflies
Zheng, Lingxiao; Hedrick, Tyson L.; Mittal, Rajat
2013-01-01
Insect wings can undergo significant chordwise (camber) as well as spanwise (twist) deformation during flapping flight but the effect of these deformations is not well understood. The shape and size of butterfly wings leads to particularly large wing deformations, making them an ideal test case for investigation of these effects. Here we use computational models derived from experiments on free-flying butterflies to understand the effect of time-varying twist and camber on the aerodynamic performance of these insects. High-speed videogrammetry is used to capture the wing kinematics, including deformation, of a Painted Lady butterfly (Vanessa cardui) in untethered, forward flight. These experimental results are then analyzed computationally using a high-fidelity, three-dimensional, unsteady Navier-Stokes flow solver. For comparison to this case, a set of non-deforming, flat-plate wing (FPW) models of wing motion are synthesized and subjected to the same analysis along with a wing model that matches the time-varying wing-twist observed for the butterfly, but has no deformation in camber. The simulations show that the observed butterfly wing (OBW) outperforms all the flat-plate wings in terms of usable force production as well as the ratio of lift to power by at least 29% and 46%, respectively. This increase in efficiency of lift production is at least three-fold greater than reported for other insects. Interestingly, we also find that the twist-only-wing (TOW) model recovers much of the performance of the OBW, demonstrating that wing-twist, and not camber is key to forward flight in these insects. The implications of this on the design of flapping wing micro-aerial vehicles are discussed. PMID:23341923
Time-Varying Distortions of Binaural Information by Bilateral Hearing Aids
Directory of Open Access Journals (Sweden)
Andrew D. Brown
2016-09-01
Full Text Available In patients with bilateral hearing loss, the use of two hearing aids (HAs offers the potential to restore the benefits of binaural hearing, including sound source localization and segregation. However, existing evidence suggests that bilateral HA users’ access to binaural information, namely interaural time and level differences (ITDs and ILDs, can be compromised by device processing. Our objective was to characterize the nature and magnitude of binaural distortions caused by modern digital behind-the-ear HAs using a variety of stimuli and HA program settings. Of particular interest was a common frequency-lowering algorithm known as nonlinear frequency compression, which has not previously been assessed for its effects on binaural information. A binaural beamforming algorithm was also assessed. Wide dynamic range compression was enabled in all programs. HAs were placed on a binaural manikin, and stimuli were presented from an arc of loudspeakers inside an anechoic chamber. Stimuli were broadband noise bursts, 10-Hz sinusoidally amplitude-modulated noise bursts, or consonant–vowel–consonant speech tokens. Binaural information was analyzed in terms of ITDs, ILDs, and interaural coherence, both for whole stimuli and in a time-varying sense (i.e., within a running temporal window across four different frequency bands (1, 2, 4, and 6 kHz. Key findings were: (a Nonlinear frequency compression caused distortions of high-frequency envelope ITDs and significantly reduced interaural coherence. (b For modulated stimuli, all programs caused time-varying distortion of ILDs. (c HAs altered the relationship between ITDs and ILDs, introducing large ITD–ILD conflicts in some cases. Potential perceptual consequences of measured distortions are discussed.
Dynamic linear models to explore time-varying suspended sediment-discharge rating curves
Ahn, Kuk-Hyun; Yellen, Brian; Steinschneider, Scott
2017-06-01
This study presents a new method to examine long-term dynamics in sediment yield using time-varying sediment-discharge rating curves. Dynamic linear models (DLMs) are introduced as a time series filter that can assess how the relationship between streamflow and sediment concentration or load changes over time in response to a wide variety of natural and anthropogenic watershed disturbances or long-term changes. The filter operates by updating parameter values using a recursive Bayesian design that responds to 1 day-ahead forecast errors while also accounting for observational noise. The estimated time series of rating curve parameters can then be used to diagnose multiscale (daily-decadal) variability in sediment yield after accounting for fluctuations in streamflow. The technique is applied in a case study examining changes in turbidity load, a proxy for sediment load, in the Esopus Creek watershed, part of the New York City drinking water supply system. The results show that turbidity load exhibits a complex array of variability across time scales. The DLM highlights flood event-driven positive hysteresis, where turbidity load remained elevated for months after large flood events, as a major component of dynamic behavior in the rating curve relationship. The DLM also produces more accurate 1 day-ahead loading forecasts compared to other static and time-varying rating curve methods. The results suggest that DLMs provide a useful tool for diagnosing changes in sediment-discharge relationships over time and may help identify variability in sediment concentrations and loads that can be used to inform dynamic water quality management.
Rapid Internalization of the Oncogenic K + Channel KV10.1
Tobias Kohl; Eva Lörinczi; Pardo, Luis A.; Walter Stühmer
2011-01-01
K(V)10.1 is a mammalian brain voltage-gated potassium channel whose ectopic expression outside of the brain has been proven relevant for tumor biology. Promotion of cancer cell proliferation by K(V)10.1 depends largely on ion flow, but some oncogenic properties remain in the absence of ion permeation. Additionally, K(V)10.1 surface populations are small compared to large intracellular pools. Control of protein turnover within cells is key to both cellular plasticity and homeostasis, and there...
Manners, R.; Schmidt, J. C.
2009-12-01
The resiliency and sensitivity of western rivers to future climate change may be partly anticipated by the response of these rivers to past perturbations in stream flow and sediment supply. Predictions of earlier spring runoff and reduced peak flows of snowmelt-dominated streams mimic hydrologic changes caused by the closure and operation of large dams built within the past century. In the Colorado River Basin, channels have narrowed between 5 and 26% following large dam construction, but the correlation between flow reduction and channel narrowing is confounded by changes in bank strength caused by the rapid spread of the non-native riparian shrub, tamarisk (Tamarix spp.). Thus, predictions of future changes in channel form and analysis of past changes related to dams must distinguish between channel narrowing caused by direct changes in flow, and caused by the indirect effects wherein changes in flow regime allow expansion of non-native riparian vegetation that in turn leads to accelerated channel narrowing. Our research evaluates the geomorphic controls on tamarisk colonization, the role of tamarisk in accelerating the narrowing process, and the dynamic feedbacks between channel changes on western rivers and the invasion of non-native riparian species. The transformation of formerly active bars and channel margins into stable inset floodplain surfaces is the dominant process by which these channels have narrowed, as determined by detailed alluvial stratigraphy and dendrogeomorphology. We recreated the 3-dimensional bar surface present at the time of tamarisk establishment by excavating an extensive network of trenches. In doing this, we evaluated the hydraulic environment within which tamarisk established. We also characterized the hydrodynamic roughness of aging tamarisk stands from ground-based LiDAR scans to evaluate the role of tamarisk in the promotion of floodplain formation. Our study sites are representative of the predominant geomorphic organization of
Comtois, Philippe; Sakabe, Masao; Vigmond, Edward J; Munoz, Mauricio; Texier, Anne; Shiroshita-Takeshita, Akiko; Nattel, Stanley
2008-10-01
Atrial fibrillation (AF) is the most common sustained clinical arrhythmia and is a problem of growing proportions. Recent studies have increased interest in fast-unbinding Na(+) channel blockers like vernakalant (RSD1235) and ranolazine for AF therapy, but the mechanism of efficacy is poorly understood. To study how fast-unbinding I(Na) blockers affect AF, we developed realistic mathematical models of state-dependent Na(+) channel block, using a lidocaine model as a prototype, and studied the effects on simulated cholinergic AF in two- and three-dimensional atrial substrates. We then compared the results with in vivo effects of lidocaine on vagotonic AF in dogs. Lidocaine action was modeled with the Hondeghem-Katzung modulated-receptor theory and maximum affinity for activated Na(+) channels. Lidocaine produced frequency-dependent Na(+) channel blocking and conduction slowing effects and terminated AF in both two- and three-dimensional models with concentration-dependent efficacy (maximum approximately 89% at 60 microM). AF termination was not related to increases in wavelength, which tended to decrease with the drug, but rather to decreased source Na(+) current in the face of large ACh-sensitive K(+) current-related sinks, leading to the destabilization of primary generator rotors and a great reduction in wavebreak, which caused primary rotor annihilations in the absence of secondary rotors to resume generator activity. Lidocaine also reduced the variability and maximum values of the dominant frequency distribution during AF. Qualitatively similar results were obtained in vivo for lidocaine effects on vagal AF in dogs, with an efficacy of 86% at 2 mg/kg iv, as well as with simulations using the guarded-receptor model of lidocaine action. These results provide new insights into the mechanisms by which rapidly unbinding class I antiarrhythmic agents, a class including several novel compounds of considerable promise, terminate AF.
Tunable Size- and Charge-based Particle Chromatography Using Time-varying Voltage Gradients
Fernandez Poza, Sergio; Mulder, Patty; Verpoorte, Elisabeth
2016-01-01
Here we present for the first time the implementation of Flow-Induced Electrokinetic Trapping (FIET) for the quantitative separation of polymer microparticles in microfluidic channels. FIET is a particle-trapping mechanism that depends on the generation of recirculating flows in non-uniform
Interactive exploration of large-scale time-varying data using dynamic tracking graphs
Widanagamaachchi, W.
2012-10-01
Exploring and analyzing the temporal evolution of features in large-scale time-varying datasets is a common problem in many areas of science and engineering. One natural representation of such data is tracking graphs, i.e., constrained graph layouts that use one spatial dimension to indicate time and show the "tracks" of each feature as it evolves, merges or disappears. However, for practical data sets creating the corresponding optimal graph layouts that minimize the number of intersections can take hours to compute with existing techniques. Furthermore, the resulting graphs are often unmanageably large and complex even with an ideal layout. Finally, due to the cost of the layout, changing the feature definition, e.g. by changing an iso-value, or analyzing properly adjusted sub-graphs is infeasible. To address these challenges, this paper presents a new framework that couples hierarchical feature definitions with progressive graph layout algorithms to provide an interactive exploration of dynamically constructed tracking graphs. Our system enables users to change feature definitions on-the-fly and filter features using arbitrary attributes while providing an interactive view of the resulting tracking graphs. Furthermore, the graph display is integrated into a linked view system that provides a traditional 3D view of the current set of features and allows a cross-linked selection to enable a fully flexible spatio-temporal exploration of data. We demonstrate the utility of our approach with several large-scale scientific simulations from combustion science. © 2012 IEEE.
Time-varying Risk Factors and Sexual Aggression Perpetration among Male College Students
Thompson, Martie P.; Kingree, J.B. (Kip); Zinzow, Heidi; Swartout, Kevin
2015-01-01
Purpose Preventing sexual aggression can be informed by determining if time-varying risk factors differentiate men who follow different sexual aggression risk trajectories. Methods Data are from a longitudinal study with 795 college males surveyed at the end of each of their four years of college in 2008–2011. Repeated measures general linear models tested if changes in risk factors corresponded with sexual aggression trajectory membership. Results Changes in the risk factors corresponded with SA trajectories. Men who came to college with a history of SA but decreased their perpetration likelihood during college showed concurrent decreases in sexual compulsivity, impulsivity, hostile attitudes toward women, rape supportive beliefs, perceptions of peer approval of forced sex, and perceptions of peer pressure to have sex with many different women, and smaller increases in pornography use over their college years. Conversely, men who increased levels of SA over time demonstrated larger increases in risk factors in comparison to other trajectory groups. Conclusions The odds that males engaged in sexual aggression corresponded with changes in key risk factors. Risk factors were not static and interventions designed to alter them may lead to changes in sexual aggression risk. PMID:26592333
Estimation of Bid Curves in Power Exchanges using Time-varying Simultaneous-Equations Models
Ofuji, Kenta; Yamaguchi, Nobuyuki
Simultaneous-equations model (SEM) is generally used in economics to estimate interdependent endogenous variables such as price and quantity in a competitive, equilibrium market. In this paper, we have attempted to apply SEM to JEPX (Japan Electric Power eXchange) spot market, a single-price auction market, using the publicly available data of selling and buying bid volumes, system price and traded quantity. The aim of this analysis is to understand the magnitude of influences to the auctioned prices and quantity from the selling and buying bids, than to forecast prices and quantity for risk management purposes. In comparison with the Ordinary Least Squares (OLS) estimation where the estimation results represent average values that are independent of time, we employ a time-varying simultaneous-equations model (TV-SEM) to capture structural changes inherent in those influences, using State Space models with Kalman filter stepwise estimation. The results showed that the buying bid volumes has that highest magnitude of influences among the factors considered, exhibiting time-dependent changes, ranging as broad as about 240% of its average. The slope of the supply curve also varies across time, implying the elastic property of the supply commodity, while the demand curve remains comparatively inelastic and stable over time.
Modeling broadband ocean acoustic transmissions with time-varying sea surfaces.
Siderius, Martin; Porter, Michael B
2008-07-01
Solutions to ocean acoustic scattering problems are often formulated in the frequency domain, which implies that the surface is "frozen" in time. This may be reasonable for short duration signals but breaks down if the surface changes appreciably over the transmission time. Frequency domain solutions are also impractical for source-receiver ranges and frequency bands typical for applications such as acoustic communications (e.g. hundreds to thousands of meters, 1-50 kHz band). In addition, a driving factor in the performance of certain acoustic systems is the Doppler spread, which is often introduced from sea-surface movement. The time-varying nature of the sea surface adds complexity and often leads to a statistical description for the variations in received signals. A purely statistical description likely limits the insight that modeling generally provides. In this paper, time-domain modeling approaches to the sea-surface scattering problem are described. As a benchmark for comparison, the Helmholtz integral equation is used for solutions to static, time-harmonic rough surface problems. The integral equation approach is not practical for time-evolving rough surfaces and two alternatives are formulated. The first approach is relatively simple using ray theory. This is followed with a ray-based formulation of the Helmholtz integral equation with a time-domain Kirchhoff approximation.
Directory of Open Access Journals (Sweden)
M. de la Sen
2008-01-01
Full Text Available This paper investigates the asymptotic stability of switched linear time-varying systems with constant point delays under not very stringent conditions on the matrix functions of parameters. Such conditions are their boundedness, the existence of bounded time derivatives almost everywhere, and small amplitudes of the appearing Dirac impulses where such derivatives do not exist. It is also assumed that the system matrix for zero delay is stable with some prescribed stability abscissa for all time in order to obtain sufficiency-type conditions of asymptotic stability dependent on the delay sizes. Alternatively, it is assumed that the auxiliary system matrix defined for all the delayed system matrices being zero is stable with prescribed stability abscissa for all time to obtain results for global asymptotic stability independent of the delays. A particular subset of the switching instants is the so-called set of reset instants where switching leads to the parameterization to reset to a value within a prescribed set.
Visualizing Robustness of Critical Points for 2D Time-Varying Vector Fields
Wang, B.
2013-06-01
Analyzing critical points and their temporal evolutions plays a crucial role in understanding the behavior of vector fields. A key challenge is to quantify the stability of critical points: more stable points may represent more important phenomena or vice versa. The topological notion of robustness is a tool which allows us to quantify rigorously the stability of each critical point. Intuitively, the robustness of a critical point is the minimum amount of perturbation necessary to cancel it within a local neighborhood, measured under an appropriate metric. In this paper, we introduce a new analysis and visualization framework which enables interactive exploration of robustness of critical points for both stationary and time-varying 2D vector fields. This framework allows the end-users, for the first time, to investigate how the stability of a critical point evolves over time. We show that this depends heavily on the global properties of the vector field and that structural changes can correspond to interesting behavior. We demonstrate the practicality of our theories and techniques on several datasets involving combustion and oceanic eddy simulations and obtain some key insights regarding their stable and unstable features. © 2013 The Author(s) Computer Graphics Forum © 2013 The Eurographics Association and Blackwell Publishing Ltd.
The Fast Simulation of Scattering Characteristics from a Simplified Time Varying Sea Surface
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Yiwen Wei
2015-01-01
Full Text Available This paper aims at applying a simplified sea surface model into the physical optics (PO method to accelerate the scattering calculation from 1D time varying sea surface. To reduce the number of the segments and make further improvement on the efficiency of PO method, a simplified sea surface is proposed. In this simplified sea surface, the geometry of long waves is locally approximated by tilted facets that are much longer than the electromagnetic wavelength. The capillary waves are considered to be sinusoidal line superimposing on the long waves. The wavenumber of the sinusoidal waves is supposed to satisfy the resonant condition of Bragg waves which is dominant in all the scattered short wave components. Since the capillary wave is periodical within one facet, an analytical integration of the PO term can be performed. The backscattering coefficient obtained from a simplified sea surface model agrees well with that obtained from a realistic sea surface. The Doppler shifts and width also agree well with the realistic model since the capillary waves are taken into consideration. The good agreements indicate that the simplified model is reasonable and valid in predicting both the scattering coefficients and the Doppler spectra.
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Lan Liu
2017-01-01
Full Text Available As the adoption of Software Defined Networks (SDNs grows, the security of SDN still has several unaddressed limitations. A key network security research area is in the study of malware propagation across the SDN-enabled networks. To analyze the spreading processes of network malware (e.g., viruses in SDN, we propose a dynamic model with a time-varying community network, inspired by research models on the spread of epidemics in complex networks across communities. We assume subnets of the network as communities and links that are dense in subnets but sparse between subnets. Using numerical simulation and theoretical analysis, we find that the efficiency of network malware propagation in this model depends on the mobility rate q of the nodes between subnets. We also find that there exists a mobility rate threshold qc. The network malware will spread in the SDN when the mobility rate q>qc. The malware will survive when q>qc and perish when q
Cao, Jiguo
2012-01-01
Ordinary differential equations (ODEs) are widely used in biomedical research and other scientific areas to model complex dynamic systems. It is an important statistical problem to estimate parameters in ODEs from noisy observations. In this article we propose a method for estimating the time-varying coefficients in an ODE. Our method is a variation of the nonlinear least squares where penalized splines are used to model the functional parameters and the ODE solutions are approximated also using splines. We resort to the implicit function theorem to deal with the nonlinear least squares objective function that is only defined implicitly. The proposed penalized nonlinear least squares method is applied to estimate a HIV dynamic model from a real dataset. Monte Carlo simulations show that the new method can provide much more accurate estimates of functional parameters than the existing two-step local polynomial method which relies on estimation of the derivatives of the state function. Supplemental materials for the article are available online.
Burstiness and tie activation strategies in time-varying social networks
Ubaldi, Enrico; Vezzani, Alessandro; Karsai, Márton; Perra, Nicola; Burioni, Raffaella
2017-04-01
The recent developments in the field of social networks shifted the focus from static to dynamical representations, calling for new methods for their analysis and modelling. Observations in real social systems identified two main mechanisms that play a primary role in networks’ evolution and influence ongoing spreading processes: the strategies individuals adopt when selecting between new or old social ties, and the bursty nature of the social activity setting the pace of these choices. We introduce a time-varying network model accounting both for ties selection and burstiness and we analytically study its phase diagram. The interplay of the two effects is non trivial and, interestingly, the effects of burstiness might be suppressed in regimes where individuals exhibit a strong preference towards previously activated ties. The results are tested against numerical simulations and compared with two empirical datasets with very good agreement. Consequently, the framework provides a principled method to classify the temporal features of real networks, and thus yields new insights to elucidate the effects of social dynamics on spreading processes.
Propagation of a laser beam in a time-varying waveguide. [plasma heating for controlled fusion
Chapman, J. M.; Kevorkian, J.
1978-01-01
The propagation of an axisymmetric laser beam in a plasma column having a radially parabolic electron density distribution is reported. For the case of an axially uniform waveguide it is found that the basic characteristics of alternating focusing and defocusing beams are maintained. However, the intensity distribution is changed at the foci and outer-beam regions. The features of paraxial beam propagation are discussed with reference to axially varying waveguides. Laser plasma coupling is considered noting the case where laser heating produces a density distribution radially parabolic near the axis and the energy absorbed over the focal length of the plasma is small. It is found that: (1) beam-propagation stability is governed by the relative magnitude of the density fluctuations existing in the axial variation of the waveguides due to laser heating, and (2) for beam propagation in a time-varying waveguide, the global instability of the propagation is a function of the initial fluctuation growth rate as compared to the initial time rate of change in the radial curvature of the waveguide.
Lu, S. F.; Zhang, W.; Song, X. J.
2017-09-01
Using Reddy's high-order shear theory for laminated plates and Hamilton's principle, a nonlinear partial differential equation for the dynamics of a deploying cantilevered piezoelectric laminated composite plate, under the combined action of aerodynamic load and piezoelectric excitation, is introduced. Two-degree of freedom (DOF) nonlinear dynamic models for the time-varying coefficients describing the transverse vibration of the deploying laminate under the combined actions of a first-order aerodynamic force and piezoelectric excitation were obtained by selecting a suitable time-dependent modal function satisfying the displacement boundary conditions and applying second-order discretization using the Galerkin method. Using a numerical method, the time history curves of the deploying laminate were obtained, and its nonlinear dynamic characteristics, including extension speed and different piezoelectric excitations, were studied. The results suggest that the piezoelectric excitation has a clear effect on the change of the nonlinear dynamic characteristics of such piezoelectric laminated composite plates. The nonlinear vibration of the deploying cantilevered laminate can be effectively suppressed by choosing a suitable voltage and polarity.
From dynamical systems with time-varying delay to circle maps and Koopman operators
Müller, David; Otto, Andreas; Radons, Günter
2017-06-01
In this paper, we investigate the influence of the retarded access by a time-varying delay on the dynamics of delay systems. We show that there are two universality classes of delays, which lead to fundamental differences in dynamical quantities such as the Lyapunov spectrum. Therefore, we introduce an operator theoretic framework, where the solution operator of the delay system is decomposed into the Koopman operator describing the delay access and an operator similar to the solution operator known from systems with constant delay. The Koopman operator corresponds to an iterated map, called access map, which is defined by the iteration of the delayed argument of the delay equation. The dynamics of this one-dimensional iterated map determines the universality classes of the infinite-dimensional state dynamics governed by the delay differential equation. In this way, we connect the theory of time-delay systems with the theory of circle maps and the framework of the Koopman operator. In this paper, we extend our previous work [A. Otto, D. Müller, and G. Radons, Phys. Rev. Lett. 118, 044104 (2017), 10.1103/PhysRevLett.118.044104] by elaborating the mathematical details and presenting further results also on the Lyapunov vectors.
Optimum Control for Nonlinear Dynamic Radial Deformation of Turbine Casing with Time-Varying LSSVM
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Cheng-Wei Fei
2015-01-01
Full Text Available With the development of the high performance and high reliability of aeroengine, the blade-tip radial running clearance (BTRRC of high pressure turbine seriously influences the reliability and performance of aeroengine, wherein the radial deformation control of turbine casing has to be concerned in BTRRC design. To improve BTRRC design, the optimum control-based probabilistic optimization of turbine casing radial deformation was implemented using time-varying least square support vector machine (T-LSSVM by considering nonlinear material properties and dynamic thermal load. First the T-LSSVM method was proposed and its mathematical model was established. And then the nonlinear dynamic optimal control model of casing radial deformation was constructed with T-LSSVM. Thirdly, through the numerical experiments, the T-LSSVM method is demonstrated to be a promising approach in reducing additional design samples and improving computational efficiency with acceptable computational precision. Through the optimum control-based probabilistic optimization for nonlinear dynamic radial turbine casing deformation, the optimum radial deformation is 7.865 × 10−4 m with acceptable reliability degree 0.995 6, which is reduced by 7.86 × 10−5 m relative to that before optimization. These results validate the effectiveness and feasibility of the proposed T-LSSVM method, which provides a useful insight into casing radial deformation, BTRRC control, and the development of gas turbine with high performance and high reliability.
Fogerty, Daniel
2015-09-01
The present study investigated how non-linguistic, indexical information about talker identity interacts with contributions to sentence intelligibility by the time-varying amplitude (temporal envelope) and fundamental frequency (F 0 ). Young normal-hearing adults listened to sentences that preserved the original consonants but replaced the vowels with a single vowel production. This replacement vowel selectively preserved amplitude or F 0 cues of the original vowel, but replaced cues to phonetic identity. Original vowel duration was always preserved. Three experiments investigated indexical contributions by replacing vowels with productions from the same or different talker, or by acoustically morphing the original vowel. These stimulus conditions investigated how vowel suprasegmental and indexical properties interact and contribute to intelligibility independently from phonetic information. Results demonstrated that indexical properties influence the relative contribution of suprasegmental properties to sentence intelligibility. F 0 variations are particularly important in the presence of conflicting indexical information. Temporal envelope modulations significantly improve sentence intelligibility, but are enhanced when either indexical or F 0 cues are available. These findings suggest that F 0 and other indexical cues may facilitate perceptually grouping suprasegmental properties of vowels with the remainder of the sentence. Temporal envelope modulations of vowels may contribute to intelligibility once they are successfully integrated with the preserved signal.
Soni, V.; Hadjadj, A.; Roussel, O.
2017-12-01
In this paper, a fully adaptive multiresolution (MR) finite difference scheme with a time-varying tolerance is developed to study compressible fluid flows containing shock waves in interaction with solid obstacles. To ensure adequate resolution near rigid bodies, the MR algorithm is combined with an immersed boundary method based on a direct-forcing approach in which the solid object is represented by a continuous solid-volume fraction. The resulting algorithm forms an efficient tool capable of solving linear and nonlinear waves on arbitrary geometries. Through a one-dimensional scalar wave equation, the accuracy of the MR computation is, as expected, seen to decrease in time when using a constant MR tolerance considering the accumulation of error. To overcome this problem, a variable tolerance formulation is proposed, which is assessed through a new quality criterion, to ensure a time-convergence solution for a suitable quality resolution. The newly developed algorithm coupled with high-resolution spatial and temporal approximations is successfully applied to shock-bluff body and shock-diffraction problems solving Euler and Navier-Stokes equations. Results show excellent agreement with the available numerical and experimental data, thereby demonstrating the efficiency and the performance of the proposed method.
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Corentin Herbert
2013-07-01
Full Text Available It has been suggested that the maximum entropy production (MEP principle, or MEP hypothesis, could be an interesting tool to compute climatic variables like temperature. In this climatological context, a major limitation of MEP is that it is generally assumed to be applicable only for stationary systems. It is therefore often anticipated that critical climatic features like the seasonal cycle or climatic change cannot be represented within this framework. We discuss here several possibilities in order to introduce time- varying climatic problems using the MEP formalism. We will show that it is possible to formulate a MEP model which accounts for time evolution in a consistent way. This formulation leads to physically relevant results as long as the internal time scales associated with thermal inertia are small compared to the speed of external changes. We will focus on transient changes as well as on the seasonal cycle in a conceptual climate box-model in order to discuss the physical relevance of such an extension of the MEP framework.
Do Tick Attachment Times Vary between Different Tick-Pathogen Systems?
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Stephanie L. Richards
2017-05-01
Full Text Available Improvements to risk assessments are needed to enhance our understanding of tick-borne disease epidemiology. We review tick vectors and duration of tick attachment required for pathogen transmission for the following pathogens/toxins and diseases: (1 Anaplasma phagocytophilum (anaplasmosis; (2 Babesia microti (babesiosis; (3 Borrelia burgdorferi (Lyme disease; (4 Southern tick-associated rash illness; (5 Borrelia hermsii (tick-borne relapsing fever; (6 Borrelia parkeri (tick-borne relapsing fever; (7 Borrelia turicatae (tick-borne relapsing fever; (8 Borrelia mayonii; (9 Borrelia miyamotoi; (10 Coxiella burnetii (Query fever; (11 Ehrlichia chaffeensis (ehrlichiosis; (12 Ehrlichia ewingii (ehrlichiosis; (13 Ehrlichia muris; (14 Francisella tularensis (tularemia; (15 Rickettsia 364D; (16 Rickettsia montanensis; (17 Rickettsia parkeri (American boutonneuse fever, American tick bite fever; (18 Rickettsia ricketsii (Rocky Mountain spotted fever; (19 Colorado tick fever virus (Colorado tick fever; (20 Heartland virus; (21 Powassan virus (Powassan disease; (22 tick paralysis neurotoxin; and (23 Galactose-α-1,3-galactose (Mammalian Meat Allergy-alpha-gal syndrome. Published studies for 12 of the 23 pathogens/diseases showed tick attachment times. Reported tick attachment times varied (<1 h to seven days between pathogen/toxin type and tick vector. Not all studies were designed to detect the duration of attachment required for transmission. Knowledge of this important aspect of vector competence is lacking and impairs risk assessment for some tick-borne pathogens.
Event-Triggered Discrete-Time Distributed Consensus Optimization over Time-Varying Graphs
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Qingguo Lü
2017-01-01
Full Text Available This paper focuses on a class of event-triggered discrete-time distributed consensus optimization algorithms, with a set of agents whose communication topology is depicted by a sequence of time-varying networks. The communication process is steered by independent trigger conditions observed by agents and is decentralized and just rests with each agent’s own state. At each time, each agent only has access to its privately local Lipschitz convex objective function. At the next time step, every agent updates its state by applying its own objective function and the information sent from its neighboring agents. Under the assumption that the network topology is uniformly strongly connected and weight-balanced, the novel event-triggered distributed subgradient algorithm is capable of steering the whole network of agents asymptotically converging to an optimal solution of the convex optimization problem. Finally, a simulation example is given to validate effectiveness of the introduced algorithm and demonstrate feasibility of the theoretical analysis.
Time-Varying Risk Factors and Sexual Aggression Perpetration Among Male College Students.
Thompson, Martie P; Kingree, Jeffrey Brooks; Zinzow, Heidi; Swartout, Kevin
2015-12-01
Preventing sexual aggression (SA) can be informed by determining if time-varying risk factors differentiate men who follow different sexual aggression risk trajectories. Data are from a longitudinal study with 795 college males surveyed at the end of each of their 4 years of college in 2008-2011. Repeated measures general linear models tested if changes in risk factors corresponded with sexual aggression trajectory membership. Changes in the risk factors corresponded with SA trajectories. Men who came to college with a history of SA but decreased their perpetration likelihood during college showed concurrent decreases in sexual compulsivity, impulsivity, hostile attitudes toward women, rape supportive beliefs, perceptions of peer approval of forced sex, and perceptions of peer pressure to have sex with many different women, and smaller increases in pornography use over their college years. Conversely, men who increased levels of SA over time demonstrated larger increases in risk factors in comparison to other trajectory groups. The odds that males engaged in sexual aggression corresponded with changes in key risk factors. Risk factors were not static and interventions designed to alter them may lead to changes in sexual aggression risk. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.
AST: Activity-Security-Trust driven modeling of time varying networks.
Wang, Jian; Xu, Jiake; Liu, Yanheng; Deng, Weiwen
2016-02-18
Network modeling is a flexible mathematical structure that enables to identify statistical regularities and structural principles hidden in complex systems. The majority of recent driving forces in modeling complex networks are originated from activity, in which an activity potential of a time invariant function is introduced to identify agents' interactions and to construct an activity-driven model. However, the new-emerging network evolutions are already deeply coupled with not only the explicit factors (e.g. activity) but also the implicit considerations (e.g. security and trust), so more intrinsic driving forces behind should be integrated into the modeling of time varying networks. The agents undoubtedly seek to build a time-dependent trade-off among activity, security, and trust in generating a new connection to another. Thus, we reasonably propose the Activity-Security-Trust (AST) driven model through synthetically considering the explicit and implicit driving forces (e.g. activity, security, and trust) underlying the decision process. AST-driven model facilitates to more accurately capture highly dynamical network behaviors and figure out the complex evolution process, allowing a profound understanding of the effects of security and trust in driving network evolution, and improving the biases induced by only involving activity representations in analyzing the dynamical processes.
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Kong-Fatt Wong
2007-11-01
Full Text Available How do neurons in a decision circuit integrate time-varying signals, in favor of or against alternative choice options? To address this question, we used a recurrent neural circuit model to simulate an experiment in which monkeys performed a direction-discrimination task on a visual motion stimulus. In a recent study, it was found that brief pulses of motion perturbed neural activity in the lateral intraparietal area (LIP, and exerted corresponding effects on the monkey's choices and response times. Our model reproduces the behavioral observations and replicates LIP activity which, depending on whether the direction of the pulse is the same or opposite to that of a preferred motion stimulus, increases or decreases persistently over a few hundred milliseconds. Furthermore, our model accounts for the observation that the pulse exerts a weaker influence on LIP neuronal responses when the pulse is late relative to motion stimulus onset. We show that this violation of time-shift invariance (TSI is consistent with a recurrent circuit mechanism of time integration. We further examine time integration using two consecutive pulses of the same or opposite motion directions. The induced changes in the performance are not additive, and the second of the paired pulses is less effective than its standalone impact, a prediction that is experimentally testable. Taken together, these findings lend further support for an attractor network model of time integration in perceptual decision making.
Replicability of time-varying connectivity patterns in large resting state fMRI samples.
Abrol, Anees; Damaraju, Eswar; Miller, Robyn L; Stephen, Julia M; Claus, Eric D; Mayer, Andrew R; Calhoun, Vince D
2017-12-01
The past few years have seen an emergence of approaches that leverage temporal changes in whole-brain patterns of functional connectivity (the chronnectome). In this chronnectome study, we investigate the replicability of the human brain's inter-regional coupling dynamics during rest by evaluating two different dynamic functional network connectivity (dFNC) analysis frameworks using 7 500 functional magnetic resonance imaging (fMRI) datasets. To quantify the extent to which the emergent functional connectivity (FC) patterns are reproducible, we characterize the temporal dynamics by deriving several summary measures across multiple large, independent age-matched samples. Reproducibility was demonstrated through the existence of basic connectivity patterns (FC states) amidst an ensemble of inter-regional connections. Furthermore, application of the methods to conservatively configured (statistically stationary, linear and Gaussian) surrogate datasets revealed that some of the studied state summary measures were indeed statistically significant and also suggested that this class of null model did not explain the fMRI data fully. This extensive testing of reproducibility of similarity statistics also suggests that the estimated FC states are robust against variation in data quality, analysis, grouping, and decomposition methods. We conclude that future investigations probing the functional and neurophysiological relevance of time-varying connectivity assume critical importance. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Within-Day Time-Varying Associations Between Behavioral Cognitions and Physical Activity in Adults.
Maher, Jaclyn P; Dzubur, Eldin; Huh, Jimi; Intille, Stephen; Dunton, Genevieve F
2016-08-01
This study used time-varying effect modeling to examine time-of-day differences in how behavioral cognitions predict subsequent physical activity (PA). Adults (N = 116) participated in three 4-day "bursts" of ecological momentary assessment (EMA). Participants were prompted with eight EMA questionnaires per day assessing behavioral cognitions (i.e., intentions, self-efficacy, outcome expectations) and wore an accelerometer during waking hours. Subsequent PA was operationalized as accelerometer-derived minutes of moderate- or vigorousintensity PA in the 2 hr following the EMA prompt. On weekdays, intentions positively predicted subsequent PA in the morning (9:25 a.m.-11:45 a.m.) and in the evening (8:15 p.m.-10:00 p.m.). Self-efficacy positively predicted subsequent PA on weekday evenings (7:35 p.m.-10:00 p.m.). Outcome expectations were unrelated to subsequent PA on weekdays. On weekend days, behavior cognitions and subsequent PA were unrelated regardless of time of day. This study identifies windows of opportunity and vulnerability for motivation-based PA interventions aiming to deliver intervention content within the context of adults' daily lives.
Nguyen, Hoai-Nam
2014-01-01
A comprehensive development of interpolating control, this monograph demonstrates the reduced computational complexity of a ground-breaking technique compared with the established model predictive control. The text deals with the regulation problem for linear, time-invariant, discrete-time uncertain dynamical systems having polyhedral state and control constraints, with and without disturbances, and under state or output feedback. For output feedback a non-minimal state-space representation is used with old inputs and outputs as state variables. Constrained Control of Uncertain, Time-Varying, Discrete-time Systems details interpolating control in both its implicit and explicit forms. In the former at most two linear-programming or one quadratic-programming problem are solved on-line at each sampling instant to yield the value of the control variable. In the latter the control law is shown to be piecewise affine in the state, and so the state space is partitioned into polyhedral cells so that at each sampling ...
Energy Technology Data Exchange (ETDEWEB)
Alexander S. Rattner; Donna Post Guillen; Alark Joshi
2012-12-01
Photo- and physically-realistic techniques are often insufficient for visualization of simulation results, especially for 3D and time-varying datasets. Substantial research efforts have been dedicated to the development of non-photorealistic and illustration-inspired visualization techniques for compact and intuitive presentation of such complex datasets. While these efforts have yielded valuable visualization results, a great deal of work has been reproduced in studies as individual research groups often develop purpose-built platforms. Additionally, interoperability between illustrative visualization software is limited due to specialized processing and rendering architectures employed in different studies. In this investigation, a generalized framework for illustrative visualization is proposed, and implemented in marmotViz, a ParaView plugin, enabling its use on variety of computing platforms with various data file formats and mesh geometries. Detailed descriptions of the region-of-interest identification and feature-tracking algorithms incorporated into this tool are provided. Additionally, implementations of multiple illustrative effect algorithms are presented to demonstrate the use and flexibility of this framework. By providing a framework and useful underlying functionality, the marmotViz tool can act as a springboard for future research in the field of illustrative visualization.
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Surafel Luleseged Tilahun
2017-01-01
Full Text Available Traffic congestion is one of the main issues in the study of transportation planning and management. It creates different problems including environmental pollution and health problem and incurs a cost which is increasing through years. One-third of this congestion is created by cars searching for parking places. Drivers may be aware that parking places are fully occupied but will drive around hoping that a parking place may become vacant. Opportunistic services, involving learning, predicting, and exploiting Internet of Things scenarios, are able to adapt to dynamic unforeseen situations and have the potential to ease parking search issues. Hence, in this paper, a cooperative dynamic prediction mechanism between multiple agents for parking space availability in the neighborhood, integrating foreseen and unforeseen events and adapting for long-term changes, is proposed. An agent in each parking place will use a dynamic and time varying Markov chain to predict the parking availability and these agents will communicate to produce the parking availability prediction in the whole neighborhood. Furthermore, a learning approach is proposed where the system can adapt to different changes in the parking demand including long-term changes. Simulation results, using synthesized data based on an actual parking lot data from a shopping mall in Geneva, show that the proposed model is promising based on the learning accuracy with service adaptation and performance in different cases.
A method for the assessment of time-varying brain shift during navigated epilepsy surgery.
De Momi, E; Ferrigno, G; Bosoni, G; Bassanini, P; Blasi, P; Casaceli, G; Fuschillo, D; Castana, L; Cossu, M; Lo Russo, G; Cardinale, F
2016-03-01
Image guidance is widely used in neurosurgery. Tracking systems (neuronavigators) allow registering the preoperative image space to the surgical space. The localization accuracy is influenced by technical and clinical factors, such as brain shift. This paper aims at providing quantitative measure of the time-varying brain shift during open epilepsy surgery, and at measuring the pattern of brain deformation with respect to three potentially meaningful parameters: craniotomy area, craniotomy orientation and gravity vector direction in the images reference frame. We integrated an image-guided surgery system with 3D Slicer, an open-source package freely available in the Internet. We identified the preoperative position of several cortical features in the image space of 12 patients, inspecting both the multiplanar and the 3D reconstructions. We subsequently repeatedly tracked their position in the surgical space. Therefore, we measured the cortical shift, following its time-related changes and estimating its correlation with gravity and craniotomy normal directions. The mean of the median brain shift amount is 9.64 mm ([Formula: see text] mm). The brain shift amount resulted not correlated with respect to the gravity direction, the craniotomy normal, the angle between the gravity and the craniotomy normal and the craniotomy area. Our method, which relies on cortex surface 3D measurements, gave results, which are consistent with literature. Our measurements are useful for the neurosurgeon, since they provide a continuous monitoring of the intra-operative sinking or bulking of the brain, giving an estimate of the preoperative images validity versus time.
Thermally driven classical Heisenberg model in 1D with a local time varying field
Bagchi, Debarshee
2013-12-01
We study thermal transport in the one-dimensional classical Heisenberg model driven by boundary heat baths and in the presence of a local time varying magnetic field. We find that, in the steady state, the energy current shows thermal resonance as the frequency of the time-periodic forcing is varied. Even in the absence of a thermal bias a steady nonzero energy current can be induced in the system, whereas for the thermally driven system a current reversal can be achieved in the bulk by suitably tuning the system parameters. When the amplitude of the forcing field is increased the system exhibits multiple resonance peaks. Thermal resonance survives in the thermodynamic limit and their magnitude increases as the temperature of the system is decreased. We find that the resonance frequency is an intrinsic frequency of the model and is related to its spin wave dispersion spectrum. Finally we show that, similar to other generic force-driven systems, there is no thermal pumping despite the current reversal in the bulk of the system.
Sun, Juan; Yan, Huang; Wugeti, Najina; Guo, Yujun; Zhang, Ling; Ma, Mei; Guo, Xingui; Jiao, Changan; Xu, Wenli; Li, Tianqi
2015-01-01
Atrial fibrillation (AF) arises from abnormalities in atrial structure and electrical activity. Microelectrode arrays (MEA) is a real-time, nondestructive measurement of the resting and action potential signal, from myocardial cells, to the peripheral circuit of electrophysiological activity. This study examined the field action potential duration (fAPD) of the right atrial appendage (RAA) by MEA in rapid atrial pacing (RAP) in the right atrium of rabbits. In addition, this study also investigated the effect of potassium ion channel blockers on fAPD. 40 New Zealand white rabbits of either sex were randomly divided into 3 groups: 1) the control, 2) potassium ion channel blocker (TEA, 4-Ap and BaCl2), and 3) amiodarone groups. The hearts were quickly removed and right atrial appendage sectioned (slice thickness 500 μm). Each slice was perfused with Tyrode's solution and continuously stimulated for 30 minutes. Sections from the control group were superfused with Tyrode's solution for 10 minutes, while the blocker groups and amiodarone were both treated with their respective compounds for 10 minutes each. The fAPD of RAA and action field action potential morphology were measured using MEA. In non-pace (control) groups, fAPD was 188.33 ± 18.29 ms after Tyrode's solution superfusion, and 173.91 ± 6.83 ms after RAP. In pace/potassium ion channel groups, TEA and BaCl2 superfusion prolonged atrial field action potential (fAPD) (control vs blocker: 176.67 ± 8.66 ms vs 196.11 ± 10.76 ms, 182.22 ± 12.87 ms vs 191.11 ± 13.09 ms with TEA and BaCl2 superfusion, respectively, P action potential in animal heart slices. After superfusing potassium ion channel blockers, fAPD was prolonged. These results suggest that Ito, IKur and IK1 remodel and mediate RAP-induced atrial electrical remodeling. Amiodarone alter potassium ion channel activity (Ito, IKur, IK1 and IKs), shortening fAPD.
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Lim Theodore
2007-01-01
Full Text Available Free-space optical interconnects (FSOIs are widely seen as a potential solution to current and future bandwidth bottlenecks for parallel processors. In this paper, an FSOI system called optical highway (OH is proposed. The OH uses polarizing beam splitter-liquid crystal plate (PBS/LC assemblies to perform reconfigurable beam combination functions. The properties of the OH make it suitable for embedding complex network topologies such as completed connected mesh or hypercube. This paper proposes the use of rapid prototyping technology for implementing an optomechanical system suitable for studying the reconfigurable characteristics of a free-space optical channel. Additionally, it reports how the limited contrast ratio of the optical components can affect the attenuation of the optical signal and the crosstalk caused by misdirected signals. Different techniques are also proposed in order to increase the optical modulation amplitude (OMA of the system.
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Rafael Gil-Otero
2007-02-01
Full Text Available Free-space optical interconnects (FSOIs are widely seen as a potential solution to current and future bandwidth bottlenecks for parallel processors. In this paper, an FSOI system called optical highway (OH is proposed. The OH uses polarizing beam splitter-liquid crystal plate (PBS/LC assemblies to perform reconfigurable beam combination functions. The properties of the OH make it suitable for embedding complex network topologies such as completed connected mesh or hypercube. This paper proposes the use of rapid prototyping technology for implementing an optomechanical system suitable for studying the reconfigurable characteristics of a free-space optical channel. Additionally, it reports how the limited contrast ratio of the optical components can affect the attenuation of the optical signal and the crosstalk caused by misdirected signals. Different techniques are also proposed in order to increase the optical modulation amplitude (OMA of the system.
Liu, Jing; Seo, Jung Hwan; Li, Yubo; Chen, Di; Kurabayashi, Katsuo; Fan, Xudong
2013-03-07
We developed a novel smart multi-channel two-dimensional (2-D) micro-gas chromatography (μGC) architecture that shows promise to significantly improve 2-D μGC performance. In the smart μGC design, a non-destructive on-column gas detector and a flow routing system are installed between the first dimensional separation column and multiple second dimensional separation columns. The effluent from the first dimensional column is monitored in real-time and decision is then made to route the effluent to one of the second dimensional columns for further separation. As compared to the conventional 2-D μGC, the greatest benefit of the smart multi-channel 2-D μGC architecture is the enhanced separation capability of the second dimensional column and hence the overall 2-D GC performance. All the second dimensional columns are independent of each other, and their coating, length, flow rate and temperature can be customized for best separation results. In particular, there is no more constraint on the upper limit of the second dimensional column length and separation time in our architecture. Such flexibility is critical when long second dimensional separation is needed for optimal gas analysis. In addition, the smart μGC is advantageous in terms of elimination of the power intensive thermal modulator, higher peak amplitude enhancement, simplified 2-D chromatogram re-construction and potential scalability to higher dimensional separation. In this paper, we first constructed a complete smart 1 × 2 channel 2-D μGC system, along with an algorithm for automated control/operation of the system. We then characterized and optimized this μGC system, and finally employed it in two important applications that highlight its uniqueness and advantages, i.e., analysis of 31 workplace hazardous volatile organic compounds, and rapid detection and identification of target gas analytes from interference background.
A Loudness Model for Time-Varying Sounds Incorporating Binaural Inhibition
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Brian C. J. Moore
2016-12-01
Full Text Available This article describes a model of loudness for time-varying sounds that incorporates the concept of binaural inhibition, namely, that the signal applied to one ear can reduce the internal response to a signal at the other ear. For each ear, the model includes the following: a filter to allow for the effects of transfer of sound through the outer and middle ear; a short-term spectral analysis with greater frequency resolution at low than at high frequencies; calculation of an excitation pattern, representing the magnitudes of the outputs of the auditory filters as a function of center frequency; application of a compressive nonlinearity to the output of each auditory filter; and smoothing over time of the resulting instantaneous specific loudness pattern using an averaging process resembling an automatic gain control. The resulting short-term specific loudness patterns are used to calculate broadly tuned binaural inhibition functions, the amount of inhibition depending on the relative short-term specific loudness at the two ears. The inhibited specific loudness patterns are summed across frequency to give an estimate of the short-term loudness for each ear. The overall short-term loudness is calculated as the sum of the short-term loudness values for the two ears. The long-term loudness for each ear is calculated by smoothing the short-term loudness for that ear, again by a process resembling automatic gain control, and the overall loudness impression is obtained by summing the long-term loudness across ears. The predictions of the model are more accurate than those of an earlier model that did not incorporate binaural inhibition.
A Loudness Model for Time-Varying Sounds Incorporating Binaural Inhibition.
Moore, Brian C J; Glasberg, Brian R; Varathanathan, Ajanth; Schlittenlacher, Josef
2016-01-01
This article describes a model of loudness for time-varying sounds that incorporates the concept of binaural inhibition, namely, that the signal applied to one ear can reduce the internal response to a signal at the other ear. For each ear, the model includes the following: a filter to allow for the effects of transfer of sound through the outer and middle ear; a short-term spectral analysis with greater frequency resolution at low than at high frequencies; calculation of an excitation pattern, representing the magnitudes of the outputs of the auditory filters as a function of center frequency; application of a compressive nonlinearity to the output of each auditory filter; and smoothing over time of the resulting instantaneous specific loudness pattern using an averaging process resembling an automatic gain control. The resulting short-term specific loudness patterns are used to calculate broadly tuned binaural inhibition functions, the amount of inhibition depending on the relative short-term specific loudness at the two ears. The inhibited specific loudness patterns are summed across frequency to give an estimate of the short-term loudness for each ear. The overall short-term loudness is calculated as the sum of the short-term loudness values for the two ears. The long-term loudness for each ear is calculated by smoothing the short-term loudness for that ear, again by a process resembling automatic gain control, and the overall loudness impression is obtained by summing the long-term loudness across ears. The predictions of the model are more accurate than those of an earlier model that did not incorporate binaural inhibition.
Changes of the time-varying percentiles of daily extreme temperature in China
Li, Bin; Chen, Fang; Xu, Feng; Wang, Xinrui
2017-11-01
Identifying the air temperature frequency distributions and evaluating the trends in time-varying percentiles are very important for climate change studies. In order to get a better understanding of the recent temporal and spatial pattern of the temperature changes in China, we have calculated the trends in temporal-varying percentiles of the daily extreme air temperature firstly. Then we divide all the stations to get the spatial patterns for the percentile trends using the average linkage cluster analysis method. To make a comparison, the shifts of trends percentile frequency distribution from 1961-1985 to 1986-2010 are also examined. Important results in three aspects have been achieved: (1) In terms of the trends in temporal-varying percentiles of the daily extreme air temperature, the most intense warming for daily maximum air temperature (Tmax) was detected in the upper percentiles with a significant increasing tendency magnitude (>2.5 °C/50year), and the greatest warming for daily minimum air temperature (Tmin) occurred with very strong trends exceeding 4 °C/50year. (2) The relative coherent spatial patterns for the percentile trends were found, and stations for the whole country had been divided into three clusters. The three primary clusters were distributed regularly to some extent from north to south, indicating the possible large influence of the latitude. (3) The most significant shifts of trends percentile frequency distribution from 1961-1985 to 1986-2010 was found in Tmax. More than half part of the frequency distribution show negative trends less than -0.5 °C/50year in 1961-1985, while showing trends less than 2.5 °C/50year in 1986-2010.
The time-varying association between perceived stress and hunger within and between days.
Huh, Jimi; Shiyko, Mariya; Keller, Stefan; Dunton, Genevieve; Schembre, Susan M
2015-06-01
Examine the association between perceived stress and hunger continuously over a week in free-living individuals. Forty five young adults (70% women, 30% overweight/obese) ages 18 to 24 years (Mean = 20.7, SD = 1.5), with BMI between 17.4 and 36.3 kg/m(2) (Mean = 23.6, SD = 4.0) provided between 513 and 577 concurrent ratings of perceived stress and hunger for 7 days via hourly, text messaging assessments and real-time eating records. Time-varying effect modeling was used to explore whether the within-day fluctuations in stress are related to perceived hunger assessed on a momentary basis. A generally positive stress-hunger relationship was confirmed, but we found that the strength of the relationship was not linear. Rather, the magnitude of the association between perceived stress and hunger changed throughout the day such that only during specific time intervals were stress and hunger significantly related. Specifically, the strength of the positive association peaked during late afternoon hours on weekdays (β = 0.31, p hunger associations that peak in the afternoon or evening hours. While we are unable to infer causality from these analyses, our findings provide empirical evidence for a potentially high-risk time of day for stress-induced eating. Replication of these findings in larger, more diverse samples will aid with the design and implementation of real-time intervention studies aimed at reducing stress-eating. Copyright © 2015 Elsevier Ltd. All rights reserved.
High-Resolution Gravity and Time-Varying Gravity Field Recovery using GRACE and CHAMP
Shum, C. K.
2002-01-01
This progress report summarizes the research work conducted under NASA's Solid Earth and Natural Hazards Program 1998 (SENH98) entitled High Resolution Gravity and Time Varying Gravity Field Recovery Using GRACE (Gravity Recovery and Climate Experiment) and CHAMP (Challenging Mini-satellite Package for Geophysical Research and Applications), which included a no-cost extension time period. The investigation has conducted pilot studies to use the simulated GRACE and CHAMP data and other in situ and space geodetic observable, satellite altimeter data, and ocean mass variation data to study the dynamic processes of the Earth which affect climate change. Results from this investigation include: (1) a new method to use the energy approach for expressing gravity mission data as in situ measurements with the possibility to enhance the spatial resolution of the gravity signal; (2) the method was tested using CHAMP and validated with the development of a mean gravity field model using CHAMP data, (3) elaborate simulation to quantify errors of tides and atmosphere and to recover hydrological and oceanic signals using GRACE, results show that there are significant aliasing effect and errors being amplified in the GRACE resonant geopotential and it is not trivial to remove these errors, and (4) quantification of oceanic and ice sheet mass changes in a geophysical constraint study to assess their contributions to global sea level change, while the results improved significant over the use of previous studies using only the SLR (Satellite Laser Ranging)-determined zonal gravity change data, the constraint could be further improved with additional information on mantle rheology, PGR (Post-Glacial Rebound) and ice loading history. A list of relevant presentations and publications is attached, along with a summary of the SENH investigation generated in 2000.
Higham, Timothy E; Russell, Anthony P
2012-02-01
Autotomy (voluntary loss of an appendage) is common among diverse groups of vertebrates and invertebrates, and much attention has been given to ecological and developmental aspects of tail autotomy in lizards. Although most studies have focused on the ramifications for the lizard (behavior, biomechanics, energetics, etc.), the tail itself can exhibit interesting behaviors once segregated from the body. For example, recent work highlighted the ability of leopard gecko tails to jump and flip, in addition to being able to swing back and forth. Little is known, however, about the control mechanisms underlying these movements. Using electromyography, we examined the time-varying in vivo motor patterns at four sites (two proximal and two distal) in the tail of the leopard gecko, Eublepharis macularius, following autotomy. Using these data we tested the hypothesis that the disparity in movements results simply from overlapping pattern generators within the tail. We found that burst duration, but not cycle duration, of the rhythmic swings reached a plateau at approximately 150 s following autotomy. This is likely because of physiological changes related to muscle fatigue and ischemia. For flips and jumps, burst and cycle duration exhibited no regular pattern. The coefficient of variation in motor patterns was significantly greater for jumps and flips than for rhythmic swings. This supports the conclusion that the different tail behaviors do not stem from overlapping pattern generators, but that they rely upon independent neural circuits. The signal controlling jumps and flips may be modified by sensory information from the environment. Finally, we found that jumps and flips are initiated using relatively synchronous activity between the two sides of the tail. In contrast, alternating activation of the right and left sides of the tail result in rhythmic swings. The mechanism underlying this change in tail behavior is comparable to locomotor gait changes in vertebrates.
Bayesian switching factor analysis for estimating time-varying functional connectivity in fMRI.
Taghia, Jalil; Ryali, Srikanth; Chen, Tianwen; Supekar, Kaustubh; Cai, Weidong; Menon, Vinod
2017-07-15
There is growing interest in understanding the dynamical properties of functional interactions between distributed brain regions. However, robust estimation of temporal dynamics from functional magnetic resonance imaging (fMRI) data remains challenging due to limitations in extant multivariate methods for modeling time-varying functional interactions between multiple brain areas. Here, we develop a Bayesian generative model for fMRI time-series within the framework of hidden Markov models (HMMs). The model is a dynamic variant of the static factor analysis model (Ghahramani and Beal, 2000). We refer to this model as Bayesian switching factor analysis (BSFA) as it integrates factor analysis into a generative HMM in a unified Bayesian framework. In BSFA, brain dynamic functional networks are represented by latent states which are learnt from the data. Crucially, BSFA is a generative model which estimates the temporal evolution of brain states and transition probabilities between states as a function of time. An attractive feature of BSFA is the automatic determination of the number of latent states via Bayesian model selection arising from penalization of excessively complex models. Key features of BSFA are validated using extensive simulations on carefully designed synthetic data. We further validate BSFA using fingerprint analysis of multisession resting-state fMRI data from the Human Connectome Project (HCP). Our results show that modeling temporal dependencies in the generative model of BSFA results in improved fingerprinting of individual participants. Finally, we apply BSFA to elucidate the dynamic functional organization of the salience, central-executive, and default mode networks-three core neurocognitive systems with central role in cognitive and affective information processing (Menon, 2011). Across two HCP sessions, we demonstrate a high level of dynamic interactions between these networks and determine that the salience network has the highest temporal
Effect of Time Varying Gravity on DORIS processing for ITRF2013
Zelensky, N. P.; Lemoine, F. G.; Chinn, D. S.; Beall, J. W.; Melachroinos, S. A.; Beckley, B. D.; Pavlis, D.; Wimert, J.
2013-12-01
Computations are under way to develop a new time series of DORIS SINEX solutions to contribute to the development of the new realization of the terrestrial reference frame (c.f. ITRF2013). One of the improvements that are envisaged is the application of improved models of time-variable gravity in the background orbit modeling. At GSFC we have developed a time series of spherical harmonics to degree and order 5 (using the GOC02S model as a base), based on the processing of SLR and DORIS data to 14 satellites from 1993 to 2013. This is compared with the standard approach used in ITRF2008, based on the static model EIGEN-GL04S1 which included secular variations in only a few select coefficients. Previous work on altimeter satellite POD (c.f. TOPEX/Poseidon, Jason-1, Jason-2) has shown that the standard model is not adequate and orbit improvements are observed with application of more detailed models of time-variable gravity. In this study, we quantify the impact of TVG modeling on DORIS satellite POD, and ascertain the impact on DORIS station positions estimated weekly from 1993 to 2013. The numerous recent improvements to SLR and DORIS processing at GSFC include a more complete compliance to IERS2010 standards, improvements to SLR/DORIS measurement modeling, and improved non-conservative force modeling to DORIS satellites. These improvements will affect gravity coefficient estimates, POD, and the station solutions. Tests evaluate the impact of time varying gravity on tracking data residuals, station consistency, and the geocenter and scale reference frame parameters.
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Huiguo Chen
2017-01-01
Full Text Available Based on the Kanai-Tajimi power spectrum filtering method proposed by Du Xiuli et al., a genetic algorithm and a quadratic optimization identification technique are employed to improve the bimodal time-varying modified Kanai-Tajimi power spectral model and the parameter identification method proposed by Vlachos et al. Additionally, a method for modeling time-varying power spectrum parameters for ground motion is proposed. The 8244 Orion and Chi-Chi earthquake accelerograms are selected as examples for time-varying power spectral model parameter identification and ground motion simulations to verify the feasibility and effectiveness of the improved bimodal time-varying modified Kanai-Tajimi power spectral model. The results of this study provide important references for designing ground motion inputs for seismic analyses of major engineering structures.
Zhang, Chuan; Wang, Xingyuan; Luo, Chao; Li, Junqiu; Wang, Chunpeng
2018-03-01
In this paper, we focus on the robust outer synchronization problem between two nonlinear complex networks with parametric disturbances and mixed time-varying delays. Firstly, a general complex network model is proposed. Besides the nonlinear couplings, the network model in this paper can possess parametric disturbances, internal time-varying delay, discrete time-varying delay and distributed time-varying delay. Then, according to the robust control strategy, linear matrix inequality and Lyapunov stability theory, several outer synchronization protocols are strictly derived. Simple linear matrix controllers are designed to driver the response network synchronize to the drive network. Additionally, our results can be applied on the complex networks without parametric disturbances. Finally, by utilizing the delayed Lorenz chaotic system as the dynamics of all nodes, simulation examples are given to demonstrate the effectiveness of our theoretical results.
Boldanov, R.; Degiannakis, S.; Filis, George
2015-01-01
This paper investigates the time-varying conditional correlation between oil price and stock market volatility for six major oil-importing and oil-exporting countries. The period of the study runs from January 2000 until December 2014 and a Diag-BEKK model is employed. Our findings report the following regularities. (i) The correlation between the oil and stock market volatilities changes over time fluctuating at both positive and negative values. (ii). Heterogeneous patterns in the time-vary...
Time-varying loss forecast for an earthquake scenario in Basel, Switzerland
Herrmann, Marcus; Zechar, Jeremy D.; Wiemer, Stefan
2014-05-01
When an unexpected earthquake occurs, people suddenly want advice on how to cope with the situation. The 2009 L'Aquila quake highlighted the significance of public communication and pushed the usage of scientific methods to drive alternative risk mitigation strategies. For instance, van Stiphout et al. (2010) suggested a new approach for objective evacuation decisions on short-term: probabilistic risk forecasting combined with cost-benefit analysis. In the present work, we apply this approach to an earthquake sequence that simulated a repeat of the 1356 Basel earthquake, one of the most damaging events in Central Europe. A recent development to benefit society in case of an earthquake are probabilistic forecasts of the aftershock occurrence. But seismic risk delivers a more direct expression of the socio-economic impact. To forecast the seismic risk on short-term, we translate aftershock probabilities to time-varying seismic hazard and combine this with time-invariant loss estimation. Compared with van Stiphout et al. (2010), we use an advanced aftershock forecasting model and detailed settlement data to allow us spatial forecasts and settlement-specific decision-making. We quantify the risk forecast probabilistically in terms of human loss. For instance one minute after the M6.6 mainshock, the probability for an individual to die within the next 24 hours is 41 000 times higher than the long-term average; but the absolute value remains at minor 0.04 %. The final cost-benefit analysis adds value beyond a pure statistical approach: it provides objective statements that may justify evacuations. To deliver supportive information in a simple form, we propose a warning approach in terms of alarm levels. Our results do not justify evacuations prior to the M6.6 mainshock, but in certain districts afterwards. The ability to forecast the short-term seismic risk at any time-and with sufficient data anywhere-is the first step of personal decision-making and raising risk
Tzeremes, Panayiotis
2017-12-14
This study is the first attempt to investigate the relationship between CO2 emissions, energy consumption, and economic growth at a state level, for the 50 US states, through a time-varying causality approach using annual data over the periods 1960-2010. The time-varying causality test facilitates the better understanding of the causal relationship between the covariates owing to the fact that it might identify causalities when the time-constant hypothesis is rejected. Our findings indicate the existence of a time-varying causality at the state level. Specifically, the results probe eight bidirectional time-varying causalities between energy consumption and CO2 emission, six cases of two-way time-varying causalities between economic growth and energy consumption, and five bidirectional time-varying causalities between economic growth and CO2 emission. Moreover, we examine the traditional environmental Kuznets curve hypothesis for the states. Notably, our results do not endorse the validity of the EKC, albeit the majority of states support an inverted N-shaped relationship. Lastly, we can identify multiple policy implications based on the empirical results.
Robust Estimation for Discrete Markov System with Time-Varying Delay and Missing Measurements
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Jia You
2013-01-01
Full Text Available This paper addresses the ℋ∞ filtering problem for time-delayed Markov jump systems (MJSs with intermittent measurements. Within network environment, missing measurements are taken into account, since the communication channel is supposed to be imperfect. A Bernoulli process is utilized to describe the phenomenon of the missing measurements. The original system is transformed into an input-output form consisting of two interconnected subsystems. Based on scaled small gain (SSG theorem and proposed Lyapunov-Krasovskii functional (LKF, the scaled small gains of the subsystems are analyzed, respectively. New conditions for the existence of the ℋ∞ filters are established, and the corresponding ℋ∞ filter design scheme is proposed. Finally, a simulation example is provided to demonstrate the effectiveness of the proposed approach.
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Ruth H. Keogh
2016-01-01
Full Text Available Abstract Background Traditional analyses of standard case-control studies using logistic regression do not allow estimation of time-varying associations between exposures and the outcome. We present two approaches which allow this. The motivation is a study of vaccine efficacy as a function of time since vaccination. Methods Our first approach is to estimate time-varying exposure-outcome associations by fitting a series of logistic regressions within successive time periods, reusing controls across periods. Our second approach treats the case-control sample as a case-cohort study, with the controls forming the subcohort. In the case-cohort analysis, controls contribute information at all times they are at risk. Extensions allow left truncation, frequency matching and, using the case-cohort analysis, time-varying exposures. Simulations are used to investigate the methods. Results The simulation results show that both methods give correct estimates of time-varying effects of exposures using standard case-control data. Using the logistic approach there are efficiency gains by reusing controls over time and care should be taken over the definition of controls within time periods. However, using the case-cohort analysis there is no ambiguity over the definition of controls. The performance of the two analyses is very similar when controls are used most efficiently under the logistic approach. Conclusions Using our methods, case-control studies can be used to estimate time-varying exposure-outcome associations where they may not previously have been considered. The case-cohort analysis has several advantages, including that it allows estimation of time-varying associations as a continuous function of time, while the logistic regression approach is restricted to assuming a step function form for the time-varying association.
Swartz, J. M.; Mohrig, D. C.; Gulick, S. P. S.; Stockli, D. F.; Daniller-Varghese, M. S.; Fernandez, R.
2016-12-01
The continental slope of the western Gulf of Mexico is host to a major depositional system, the Rio Grande Fan. Unlike many submarine fans, the surface of the Rio Grande Fan lacks large submarine channels and associated levees. Prior analysis of continental shelf stratigraphy has identified the presence of past extensive shelf-edge delta systems, when the Rio Grande River system flowed across the modern shelf and delivered high volumes of sediment to the shelf/slope break. A major gap in understanding this system is how large volumes of sediment, particularly sands, are transported from the shelf edge systems down the slope and onto the basin-floor fan without constructional channel-levee systems. Over 500km of new high-resolution 2D multichannel seismic (MCS) and CHIRP echosounder data were collected over the shelf edge and upper slope of the Rio Grande fan. These new data provide unprecedented imaging of the shelf-edge delta systems and associated slope deposits. Our preliminary observations indicate that while the modern seafloor morphology of the fan is dominated by mass-transport deposits, slumps and minor inactive channels, buried below thick mud deposits are very large aggradational channels-levee systems. These systems have channel belts almost 1km wide, with confining levees that approach 10km in width. The main body of the fan is built from these channel complexes, which appear to have then rapidly buried in mud. We document the evolution, from initial channelization to burial, of these massive slope systems. Regional correlation suggests that this most recent episode of channel-levee growth and shutoff occurred very rapidly, and could indicate drastically higher sediment flux through the paleo-Rio Grande River than that of the modern. Our results highlight an example of a slope-channel system that is subject to significant variations in sediment supply. Such systems can apparently build large late Pleistocene submarine fan deposits that can be difficult
Rapid assessment survey for exotic benthic species in the São Sebastião Channel, Brazil
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Antonio C Marques
2013-04-01
Full Text Available The study of biological invasions can be roughly divided into three parts: detection, monitoring, mitigation. Here, our objectives were to describe the marine fauna of the area of the port of São Sebastião (on the northern coast of the state of São Paulo, in the São Sebastião Channel, SSC to detect introduced species. Descriptions of the faunal community of the SSC with respect to native and allochthonous (invasive or potentially so diversity are lacking for all invertebrate groups. Sampling was carried out by specialists within each taxonomic group, in December 2009, following the protocol of the Rapid Assessment Survey (RAS in three areas with artificial structures as substrates. A total of 142 species were identified (61 native, 15 introduced, 62 cryptogenic, 4 not classified, of which 17 were Polychaeta (12, 1, 1, 3, 24 Ascidiacea (3, 6, 15, 0, 36 Bryozoa (17, 0, 18, 1, 27 Cmdana (2, 1, 24, 0, 20 Crustacea (11, 4, 5, 0, 2 Entoprocta (native, 16 Mollusca (13, 3, 0, 0. Twelve species are new occurrences for the SSC. Among the introduced taxa, two are new for coastal Brazil. Estimates of introduced taxa are conservative as the results of molecular studies suggest that some species previously considered cryptogenic are indeed introduced. We emphasize that the large number of cryptogenic species illustrates the need for a long-term monitoring program, especially in areas most susceptible to bioinvasion. We conclude that rapid assessment studies, even in relatively well-known regions, can be very useful for the detection of introduced species and we recommend that they be carried out on a larger scale in all ports with heavy ship traffic.
Rowan, Matthew J M; Christie, Jason M
2017-02-21
In many neurons, subthreshold depolarization in the soma can transiently increase action-potential (AP)-evoked neurotransmission via analog-to-digital facilitation. The mechanisms underlying this form of short-term synaptic plasticity are unclear, in part, due to the relative inaccessibility of the axon to direct physiological interrogation. Using voltage imaging and patch-clamp recording from presynaptic boutons of cerebellar stellate interneurons, we observed that depolarizing somatic potentials readily spread into the axon, resulting in AP broadening, increased spike-evoked Ca(2+) entry, and enhanced neurotransmission strength. Kv3 channels, which drive AP repolarization, rapidly inactivated upon incorporation of Kv3.4 subunits. This leads to fast susceptibility to depolarization-induced spike broadening and analog facilitation independent of Ca(2+)-dependent protein kinase C signaling. The spread of depolarization into the axon was attenuated by hyperpolarization-activated currents (Ih currents) in the maturing cerebellum, precluding analog facilitation. These results suggest that analog-to-digital facilitation is tempered by development or experience in stellate cells. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.
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Matthew J.M. Rowan
2017-02-01
Full Text Available In many neurons, subthreshold depolarization in the soma can transiently increase action-potential (AP-evoked neurotransmission via analog-to-digital facilitation. The mechanisms underlying this form of short-term synaptic plasticity are unclear, in part, due to the relative inaccessibility of the axon to direct physiological interrogation. Using voltage imaging and patch-clamp recording from presynaptic boutons of cerebellar stellate interneurons, we observed that depolarizing somatic potentials readily spread into the axon, resulting in AP broadening, increased spike-evoked Ca2+ entry, and enhanced neurotransmission strength. Kv3 channels, which drive AP repolarization, rapidly inactivated upon incorporation of Kv3.4 subunits. This leads to fast susceptibility to depolarization-induced spike broadening and analog facilitation independent of Ca2+-dependent protein kinase C signaling. The spread of depolarization into the axon was attenuated by hyperpolarization-activated currents (Ih currents in the maturing cerebellum, precluding analog facilitation. These results suggest that analog-to-digital facilitation is tempered by development or experience in stellate cells.
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Fengxia Xu
2014-01-01
Full Text Available U-model can approximate a large class of smooth nonlinear time-varying delay system to any accuracy by using time-varying delay parameters polynomial. This paper proposes a new approach, namely, U-model approach, to solving the problems of analysis and synthesis for nonlinear systems. Based on the idea of discrete-time U-model with time-varying delay, the identification algorithm of adaptive neural network is given for the nonlinear model. Then, the controller is designed by using the Newton-Raphson formula and the stability analysis is given for the closed-loop nonlinear systems. Finally, illustrative examples are given to show the validity and applicability of the obtained results.
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Lingyun Li
2013-01-01
Full Text Available We provide a new gossip algorithm to investigate the problem of opinion consensus with the time-varying influence factors and weakly connected graph among multiple agents. What is more, we discuss not only the effect of the time-varying factors and the randomized topological structure but also the spread of misinformation and communication constrains described by probabilistic quantized communication in the social network. Under the underlying weakly connected graph, we first denote that all opinion states converge to a stochastic consensus almost surely; that is, our algorithm indeed achieves the consensus with probability one. Furthermore, our results show that the mean of all the opinion states converges to the average of the initial states when time-varying influence factors satisfy some conditions. Finally, we give a result about the square mean error between the dynamic opinion states and the benchmark without quantized communication.
The Investigation of EM Scattering from the Time-Varying Overturning Wave Crest Model by the IEM
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Xiao Meng
2016-01-01
Full Text Available Investigation of the electromagnetic (EM scattering of time-varying overturning wave crests is a worthwhile endeavor. Overturning wave crest is one of the reasons of sea spike generation, which increases the probability of false radar alarms and reduces the performance of multitarget detection in the environment. A three-dimensional (3D time-varying overturning wave crest model is presented in this paper; this 3D model is an improvement of the traditional two-dimensional (2D time-varying overturning wave crest model. The integral equation method (IEM was employed to investigate backward scattering radar cross sections (RCS at various incident angles of the 3D overturning wave crest model. The super phenomenon, where the intensity of horizontal polarization scattering is greater than that of vertical polarization scattering, is an important feature of sea spikes. Simulation results demonstrate that super phenomena may occur in some time samples as variations in the overturning wave crest.
Lagona, Francesco; Jdanov, Dmitri; Shkolnikova, Maria
2014-10-15
Longitudinal data are often segmented by unobserved time-varying factors, which introduce latent heterogeneity at the observation level, in addition to heterogeneity across subjects. We account for this latent structure by a linear mixed hidden Markov model. It integrates subject-specific random effects and Markovian sequences of time-varying effects in the linear predictor. We propose an expectationŰ-maximization algorithm for maximum likelihood estimation, based on data augmentation. It reduces to the iterative maximization of the expected value of a complete likelihood function, derived from an augmented dataset with case weights, alternated with weights updating. In a case study of the Survey on Stress Aging and Health in Russia, the model is exploited to estimate the influence of the observed covariates under unobserved time-varying factors, which affect the cardiovascular activity of each subject during the observation period. Copyright © 2014 John Wiley & Sons, Ltd.
Cao, Ying; Rajan, Suja S; Wei, Peng
2016-12-01
A Mendelian randomization (MR) analysis is performed to analyze the causal effect of an exposure variable on a disease outcome in observational studies, by using genetic variants that affect the disease outcome only through the exposure variable. This method has recently gained popularity among epidemiologists given the success of genetic association studies. Many exposure variables of interest in epidemiological studies are time varying, for example, body mass index (BMI). Although longitudinal data have been collected in many cohort studies, current MR studies only use one measurement of a time-varying exposure variable, which cannot adequately capture the long-term time-varying information. We propose using the functional principal component analysis method to recover the underlying individual trajectory of the time-varying exposure from the sparsely and irregularly observed longitudinal data, and then conduct MR analysis using the recovered curves. We further propose two MR analysis methods. The first assumes a cumulative effect of the time-varying exposure variable on the disease risk, while the second assumes a time-varying genetic effect and employs functional regression models. We focus on statistical testing for a causal effect. Our simulation studies mimicking the real data show that the proposed functional data analysis based methods incorporating longitudinal data have substantial power gains compared to standard MR analysis using only one measurement. We used the Framingham Heart Study data to demonstrate the promising performance of the new methods as well as inconsistent results produced by the standard MR analysis that relies on a single measurement of the exposure at some arbitrary time point. © 2016 WILEY PERIODICALS, INC.
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Xinjiang Cai
Full Text Available The mammalian CatSper ion channel family consists of four sperm-specific voltage-gated Ca2+ channels that are crucial for sperm hyperactivation and male fertility. All four CatSper subunits are believed to assemble into a heteromultimeric channel complex, together with an auxiliary subunit, CatSperbeta. Here, we report a comprehensive comparative genomics study and evolutionary analysis of CatSpers and CatSperbeta, with important correlation to physiological significance of molecular evolution of the CatSper channel complex. The development of the CatSper channel complex with four CatSpers and CatSperbeta originated as early as primitive metazoans such as the Cnidarian Nematostella vectensis. Comparative genomics revealed extensive lineage-specific gene loss of all four CatSpers and CatSperbeta through metazoan evolution, especially in vertebrates. The CatSper channel complex underwent rapid evolution and functional divergence, while distinct evolutionary constraints appear to have acted on different domains and specific sites of the four CatSper genes. These results reveal unique evolutionary characteristics of sperm-specific Ca2+ channels and their adaptation to sperm biology through metazoan evolution.
Musa, Sarah; Supadi, Siti Suzlin; Omar, Mohd
2014-07-01
Rework is one of the solutions to some of the main issues in reverse logistic and green supply chain as it reduces production cost and environmental problem. Many researchers focus on developing rework model, but to the knowledge of the author, none of them has developed a model for time-varying demand rate. In this paper, we extend previous works and develop multiple batch production system for time-varying demand rate with rework. In this model, the rework is done within the same production cycle.
Schroeder, David; Keefe, Daniel F
2016-01-01
We present Visualization-by-Sketching, a direct-manipulation user interface for designing new data visualizations. The goals are twofold: First, make the process of creating real, animated, data-driven visualizations of complex information more accessible to artists, graphic designers, and other visual experts with traditional, non-technical training. Second, support and enhance the role of human creativity in visualization design, enabling visual experimentation and workflows similar to what is possible with traditional artistic media. The approach is to conceive of visualization design as a combination of processes that are already closely linked with visual creativity: sketching, digital painting, image editing, and reacting to exemplars. Rather than studying and tweaking low-level algorithms and their parameters, designers create new visualizations by painting directly on top of a digital data canvas, sketching data glyphs, and arranging and blending together multiple layers of animated 2D graphics. This requires new algorithms and techniques to interpret painterly user input relative to data "under" the canvas, balance artistic freedom with the need to produce accurate data visualizations, and interactively explore large (e.g., terabyte-sized) multivariate datasets. Results demonstrate a variety of multivariate data visualization techniques can be rapidly recreated using the interface. More importantly, results and feedback from artists support the potential for interfaces in this style to attract new, creative users to the challenging task of designing more effective data visualizations and to help these users stay "in the creative zone" as they work.
The time varying structure of a river plume: Observations with an autonomous glider.
Chant, R. J.; Glenn, S. M.; Gong, D.
2004-12-01
During the 2004 LaTTE (Lagrangian Transport and Transformation Experiment) pilot study we deployed a Slocum Autonomous glider on a 10-day mission to run repeated transects across the Hudson River Plume in the vicinity of Sandy Hook. The glider completed 13 cross-plume surveys during the mission with horizontal resolution of approximately 100 meters. Wind forcing was highly variable and fluctuated between upwelling and downwelling conditions at 1-2 day intervals. Tidal forcing decreased markedly from spring to neap tide conditions and river discharge averaged approximately 500 m3/s during the survey. The plume responded rapidly to the variable wind forcing. During upwelling conditions the plume thinned and extended over 30 km from shore, while during downwelling winds the plume thickened and was compressed at the shore. However, during both upwellling and downwelling conditions the plume remained detached from the bottom. The cross-sectional area of the plume also tended to vary with the wind forcing. However, a significant increase in the plume's area during the last half of the mission does not appear to be related to either wind forcing or river discharge. Instead, we suggest that the plumes structure could be impacted by spring neap variability which is known to control stratification and freshwater fluxes out of the Hudson River Estuary. This presentation will relate the structure of the plume to wind forcing, river flow and the spring/neap cycle.
Giugliano, Michele; La Camera, Giancarlo; Fusi, Stefano; Senn, Walter
2008-11-01
The response of a population of neurons to time-varying synaptic inputs can show a rich phenomenology, hardly predictable from the dynamical properties of the membrane's inherent time constants. For example, a network of neurons in a state of spontaneous activity can respond significantly more rapidly than each single neuron taken individually. Under the assumption that the statistics of the synaptic input is the same for a population of similarly behaving neurons (mean field approximation), it is possible to greatly simplify the study of neural circuits, both in the case in which the statistics of the input are stationary (reviewed in La Camera et al. in Biol Cybern, 2008) and in the case in which they are time varying and unevenly distributed over the dendritic tree. Here, we review theoretical and experimental results on the single-neuron properties that are relevant for the dynamical collective behavior of a population of neurons. We focus on the response of integrate-and-fire neurons and real cortical neurons to long-lasting, noisy, in vivo-like stationary inputs and show how the theory can predict the observed rhythmic activity of cultures of neurons. We then show how cortical neurons adapt on multiple time scales in response to input with stationary statistics in vitro. Next, we review how it is possible to study the general response properties of a neural circuit to time-varying inputs by estimating the response of single neurons to noisy sinusoidal currents. Finally, we address the dendrite-soma interactions in cortical neurons leading to gain modulation and spike bursts, and show how these effects can be captured by a two-compartment integrate-and-fire neuron. Most of the experimental results reviewed in this article have been successfully reproduced by simple integrate-and-fire model neurons.
Disrupted bandcount doubling in an AC-DC boost PFC circuit modeled by a time varying map
DEFF Research Database (Denmark)
Avrutin, Viktor; Zhusubaliyev, Zhanybai T.; Aroudi, Abdelali El
2016-01-01
averaged models. In this paper, we derive a time varying discretetime map modeling the behavior of a power factor correction AC-DC boost converter. This map is derived in closed-form and is able to faithfully reproduce the system behavior under realistic conditions. In the chaotic regime the map exhibits...
Xiong, Wenjun; Patel, Ragini; Cao, Jinde; Zheng, Wei Xing
In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.
Directory of Open Access Journals (Sweden)
Hui Zhou
2017-02-01
Full Text Available The “magnetic window” is considered a promising means to eliminate reentry communication blackout. However, the turbulence of plasma sheath results in phase jitter and amplitude turbulence of electromagnetic (EM wave and may influence the eliminating effect. Therefore, the effect of fluctuating property of reentry plasma sheath on EM wave propagation when a magnetic field is used for eliminating blackout is investigated. For this purpose, a time-varying electron density model, which includes both temporal variation and spatial turbulence, is proposed. Hybrid matrix method is also employed to investigate the interaction between time-varying magnetized plasma and EM wave. The EM wave transmission coefficients in time-varying magnetized and unmagnetized plasmas are likewise compared. Simulation results show that amplitude variation and phase jitter also exist on transmitted EM wave, and the turbulent deviation increases as the degree of plasma fluctuates. Meanwhile, the fluctuation of transmitted EM wave attenuates at low-frequency passband and increases at high-frequency passband with the increasing magnetic field. That is, comparing with unmagnetized time-varying plasma, the fluctuation effect can be mitigated by using a magnetic field when the EM wave frequency is at low-frequency passband. However, the mitigating effect can be influenced by the nonuniformity of magnetic field.
Perperoglou, Aris
2016-12-10
Flexible survival models are in need when modelling data from long term follow-up studies. In many cases, the assumption of proportionality imposed by a Cox model will not be valid. Instead, a model that can identify time varying effects of fixed covariates can be used. Although there are several approaches that deal with this problem, it is not always straightforward how to choose which covariates should be modelled having time varying effects and which not. At the same time, it is up to the researcher to define appropriate time functions that describe the dynamic pattern of the effects. In this work, we suggest a model that can deal with both fixed and time varying effects and uses simple hypotheses tests to distinguish which covariates do have dynamic effects. The model is an extension of the parsimonious reduced rank model of rank 1. As such, the number of parameters is kept low, and thus, a flexible set of time functions, such as b-splines, can be used. The basic theory is illustrated along with an efficient fitting algorithm. The proposed method is applied to a dataset of breast cancer patients and compared with a multivariate fractional polynomials approach for modelling time-varying effects. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Balandin, DV; Kogan, MM
2004-01-01
An algorithm for checking feasibility of the robust H-infinity-control problem for systems with time-varying norm bounded uncertainty is suggested. This algorithm is an iterative procedure on each step of which an optimization problem for a linear function under convex constraints determined by LMIs
Directory of Open Access Journals (Sweden)
Hong Zhang
2014-01-01
Full Text Available This paper is concerned with a nonautonomous fishing model with a time-varying delay. Under proper conditions, we employ a novel argument to establish a criterion on the global exponential stability of positive almost periodic solutions of the model with almost periodic coefficients and delays. Moreover, an example and its numerical simulation are given to illustrate the main results.
van Ophem, S.; Berkhoff, Arthur P.; Sas, P; Jonckheere, S.; Moens, D.
2012-01-01
Tracking behavior and the rate of convergence are critical properties in active noise control applications with time-varying disturbance spectra. As compared to the standard filtered-reference Least Mean Square (LMS) algorithm, improved convergence can be obtained with schemes based on
Weinstein, Sally M.; Mermelstein, Robin J.; Hedeker, Donald; Hankin, Benjamin L.; Flay, Brian R.
2006-01-01
The time-varying influences of peer and family support on adolescent daily mood were explored among youth transitioning from middle school to high school (8th to 9th grade, N = 268) as compared to youth transitioning from 10th to 11th grade (N = 240). Real-time measures of daily positive and negative affect (ecological momentary assessments) were…
Suweken, G.; van Horssen, W.T.
2002-01-01
In this paper the weakly nonlinear, transversal vibrations of a conveyor belt will be considered. The belt is assumed to move with a low and time-varying speed. Using Kirchhoff's approach a single equation of motion will be derived from a coupled system of partial differential equations describing
Douglass, Sara; Umaña-Taylor, Adriana J.
2016-01-01
Previous research has established that family ethnic socialization messages promote ethnic-racial identity (ERI) development, yet it is unknown whether these effects remain constant throughout adolescence. The current study examined the time-varying effects of family ethnic socialization on ERI exploration and resolution among Latino adolescents…
Estimation and Direct Equalization of Doubly Selective Channels
Barhumi, I.; Leus, G.; Moonen, M.
2006-01-01
We propose channel estimation and direct equalization techniques for transmission over doubly selective channels. The doubly selective channel is approximated using the basis expansion model (BEM). Linear and decision feedback equalizers implemented by time-varying finite impulse response (FIR)
Lee, Jiwon; Paek, Jungwook; Kim, Jaeyoun
2012-08-07
We present a new fabrication scheme for 3D-networked, cylindrical microfluidic (MF) channels based on shaping, bonding, and assembly of sucrose fibers. It is a simple, cleanroom-free, and environment-friendly method, ideal for rapid prototyping of lab-on-a-chip devices. Despite its simplicity, it can realize complex 3D MF channel architectures such as cylindrical tapers, internal loops, end-to-side junctions, tapered junctions, and stenosis. The last two will be of special use for realizing vaso-mimetic MF structures. It also enables molding with polymers incompatible with high-temperature processing.
Workman, E R; Haddick, P C G; Bush, K; Dilly, G A; Niere, F; Zemelman, B V; Raab-Graham, K F
2015-01-01
A single injection of N-methyl-D-aspartate receptor (NMDAR) antagonists produces a rapid antidepressant response. Lasting changes in the synapse structure and composition underlie the effectiveness of these drugs. We recently discovered that rapid antidepressants cause a shift in the γ-aminobutyric acid receptor (GABABR) signaling pathway, such that GABABR activation shifts from opening inwardly rectifiying potassium channels (Kir/GIRK) to increasing resting dendritic calcium signal and mammalian Target of Rapamycin activity. However, little is known about the molecular and biochemical mechanisms that initiate this shift. Herein, we show that GABABR signaling to Kir3 (GIRK) channels decreases with NMDAR blockade. Blocking NMDAR signaling stabilizes the adaptor protein 14-3-3η, which decouples GABABR signaling from Kir3 and is required for the rapid antidepressant efficacy. Consistent with these results, we find that key proteins involved in GABABR signaling bidirectionally change in a depression model and with rapid antidepressants. In socially defeated rodents, a model for depression, GABABR and 14-3-3η levels decrease in the hippocampus. The NMDAR antagonists AP5 and Ro-25-6981, acting as rapid antidepressants, increase GABABR and 14-3-3η expression and decrease Kir3.2. Taken together, these data suggest that the shift in GABABR function requires a loss of GABABR-Kir3 channel activity mediated by 14-3-3η. Our findings support a central role for 14-3-3η in the efficacy of rapid antidepressants and define a critical molecular mechanism for activity-dependent alterations in GABABR signaling. PMID:25560757
Workman, E R; Haddick, P C G; Bush, K; Dilly, G A; Niere, F; Zemelman, B V; Raab-Graham, K F
2015-03-01
A single injection of N-methyl-D-aspartate receptor (NMDAR) antagonists produces a rapid antidepressant response. Lasting changes in the synapse structure and composition underlie the effectiveness of these drugs. We recently discovered that rapid antidepressants cause a shift in the γ-aminobutyric acid receptor (GABABR) signaling pathway, such that GABABR activation shifts from opening inwardly rectifiying potassium channels (Kir/GIRK) to increasing resting dendritic calcium signal and mammalian Target of Rapamycin activity. However, little is known about the molecular and biochemical mechanisms that initiate this shift. Herein, we show that GABABR signaling to Kir3 (GIRK) channels decreases with NMDAR blockade. Blocking NMDAR signaling stabilizes the adaptor protein 14-3-3η, which decouples GABABR signaling from Kir3 and is required for the rapid antidepressant efficacy. Consistent with these results, we find that key proteins involved in GABABR signaling bidirectionally change in a depression model and with rapid antidepressants. In socially defeated rodents, a model for depression, GABABR and 14-3-3η levels decrease in the hippocampus. The NMDAR antagonists AP5 and Ro-25-6981, acting as rapid antidepressants, increase GABABR and 14-3-3η expression and decrease Kir3.2. Taken together, these data suggest that the shift in GABABR function requires a loss of GABABR-Kir3 channel activity mediated by 14-3-3η. Our findings support a central role for 14-3-3η in the efficacy of rapid antidepressants and define a critical molecular mechanism for activity-dependent alterations in GABABR signaling.
Strumbos, J G; Polley, D B; Kaczmarek, L K
2010-05-19
Recent studies have demonstrated that total cellular levels of voltage-gated potassium channel subunits can change on a time scale of minutes in acute slices and cultured neurons, raising the possibility that rapid changes in the abundance of channel proteins contribute to experience-dependent plasticity in vivo. In order to investigate this possibility, we took advantage of the medial nucleus of the trapezoid body (MNTB) sound localization circuit, which contains neurons that precisely phase-lock their action potentials to rapid temporal fluctuations in the acoustic waveform. Previous work has demonstrated that the ability of these neurons to follow high-frequency stimuli depends critically upon whether they express adequate amounts of the potassium channel subunit Kv3.1. To test the hypothesis that net amounts of Kv3.1 protein would be rapidly upregulated when animals are exposed to sounds that require high frequency firing for accurate encoding, we briefly exposed adult rats to acoustic environments that varied according to carrier frequency and amplitude modulation (AM) rate. Using an antibody directed at the cytoplasmic C-terminus of Kv3.1b (the adult splice isoform of Kv3.1), we found that total cellular levels of Kv3.1b protein-as well as the tonotopic distribution of Kv3.1b-labeled cells-was significantly altered following 30 min of exposure to rapidly modulated (400 Hz) sounds relative to slowly modulated (0-40 Hz, 60 Hz) sounds. These results provide direct evidence that net amounts of Kv3.1b protein can change on a time scale of minutes in response to stimulus-driven synaptic activity, permitting auditory neurons to actively adapt their complement of ion channels to changes in the acoustic environment. Copyright 2010 IBRO. Published by Elsevier Ltd. All rights reserved.
McNaughton Reyes, H Luz; Foshee, Vangie A; Bauer, Daniel J; Ennett, Susan T
2014-04-01
Although numerous studies have established a link between substance use and adult partner violence, little research has examined the relationship during adolescence and most extant research has not examined multiple substance use types. The current study used hierarchical growth modeling to simultaneously examine proximal (between-person) and time-varying (within-person) relations between cigarette, alcohol, marijuana and hard drug use and physical dating aggression across grades 8 through 12 while controlling for demographic covariates and shared risk factors. Proximal effects of marijuana use on dating aggression were found for girls and proximal effects of hard drug use on dating aggression were found for boys. Time-varying effects were found for alcohol for both boys and girls and for hard drug use for boys only. Overall, findings suggest that alcohol, marijuana and hard drug use predict whether and when adolescents engage in dating aggression and should be targeted by prevention interventions. Published by Elsevier Ltd.
Edalati, L.; Khaki Sedigh, A.; Aliyari Shooredeli, M.; Moarefianpour, A.
2018-02-01
This paper deals with the design of adaptive fuzzy dynamic surface control for uncertain strict-feedback nonlinear systems with asymmetric time-varying output constraints in the presence of input saturation. To approximate the unknown nonlinear functions and overcome the problem of explosion of complexity, a Fuzzy logic system is combined with the dynamic surface control in the backstepping design technique. To ensure the output constraints satisfaction, an asymmetric time-varying Barrier Lyapunov Function (BLF) is used. Moreover, by applying the minimal learning parameter technique, the number of the online parameters update for each subsystem is reduced to 2. Hence, the semi-globally uniformly ultimately boundedness (SGUUB) of all the closed-loop signals with appropriate tracking error convergence is guaranteed. The effectiveness of the proposed control is demonstrated by two simulation examples.
Energy Technology Data Exchange (ETDEWEB)
Teskey, G.C.; Prato, F.S.; Ossenkopp, K.P.; Kavaliers, M.
1988-01-01
The effects of exposure to clinical magnetic resonance imaging (MRI) on analgesia induced by the mu opiate agonist, fentanyl, was examined in mice. During the dark period, adult male mice were exposed for 23.2 min to the time-varying (0.6 T/sec) magnetic field (TVMF) component of the MRI procedure. Following this exposure, the analgesic potency of fentanyl citrate (0.1 mg/kg) was determined at 5, 10, 15, and 30 min post-injection, using a thermal test stimulus (hot-plate 50 degrees C). Exposure to the magnetic-field gradients attenuated the fentanyl-induced analgesia in a manner comparable to that previously observed with morphine. These results indicate that the time-varying magnetic fields associated with MRI have significant inhibitory effects on the analgesic effects of specific mu-opiate-directed ligands.
Directory of Open Access Journals (Sweden)
Jenq-Der Chen
2014-12-01
Full Text Available This paper deals with the switching signal design to robust exponential stability for uncertain discrete-time switched systems with interval time-varying delay. The lower and upper bounds of the time-varying delay are assumed to be known. By construction of a new Lyapunov-Krasovskii functional and employing linear matrix inequality, some novel sufficient conditions are proposed to guarantee the global exponential stability for such system with parametric perturbations by using a switching signal. In addition, some nonnegative inequalities are used to provide additional degrees of freedom and reduce the conservativeness of systems. Finally, some numerical examples are given to illustrate performance of the proposed design methods.
Directory of Open Access Journals (Sweden)
T. Botmart
2013-01-01
Full Text Available The problem of guaranteed cost control for exponential synchronization of cellular neural networks with interval nondifferentiable and distributed time-varying delays via hybrid feedback control is considered. The interval time-varying delay function is not necessary to be differentiable. Based on the construction of improved Lyapunov-Krasovskii functionals is combined with Leibniz-Newton's formula and the technique of dealing with some integral terms. New delay-dependent sufficient conditions for the exponential synchronization of the error systems with memoryless hybrid feedback control are first established in terms of LMIs without introducing any free-weighting matrices. The optimal guaranteed cost control with linear error hybrid feedback is turned into the solvable problem of a set of LMIs. A numerical example is also given to illustrate the effectiveness of the proposed method.
De Crescenzo, Giovanni; Cook, Debra; McIntosh, Allen; Panagos, Euthimios
2014-01-01
International audience; We study the problem of privately performing database queries (i.e., keyword searches and conjunctions over them), where a server provides its own database for client query-based access. We propose a cryptographic model for the study of such protocols,by expanding previous well-studied models of keyword search and private information retrieval to incorporate a more practical data model: a time-varying, multi-attribute and multiple-occurrence database table.Our first re...
Gianfrancesco, Milena A; Yazdany, Jinoos; Schmajuk, Gabriela
2017-12-05
In a recent publication, Quintana-Dunque et al. studied patients with early onset rheumatoid arthritis (RA) and showed that baseline smoking status was inversely associated with disease activity and disability at 36 months. The authors conclude that smoking may not be as deleterious as previously considered in RA disease course. However, the authors fail to highlight several limitations of study design and analysis, including time-varying confounding, which may have a direct impact on results and corresponding conclusions.
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Changjin Xu
2014-01-01
Full Text Available This paper deals with a kind of nonlinear Duffing equation with a deviating argument and time-varying delay. By using differential inequality techniques, some very verifiable criteria on the existence and exponential stability of antiperiodic solutions for the equation are obtained. Our results are new and complementary to previously known results. An example is given to illustrate the feasibility and effectiveness of our main results.
Reyes, H. Luz McNaughton; Vangie A Foshee; Bauer, Daniel J.; Ennett, Susan T.
2014-01-01
Although numerous studies have established a link between substance use and adult partner violence, little research has examined the relationship during adolescence and most extant research has not examined multiple substance use types. The current study used hierarchical growth modeling to simultaneously examine proximal (between-person) and time-varying (within-person) relations between cigarette, alcohol, marijuana and hard drug use and physical dating aggression across grades 8 through 12...
Silvennoinen, Annestiina; Terasvirta, Timo
2017-01-01
A new multivariate volatility model that belongs to the family of conditional correlation GARCH models is introduced. The GARCH equations of this model contain a multiplicative deterministic component to describe long-run movements in volatility and, in addition, the correlations are deterministically time-varying. Parameters of the model are estimated jointly using maximum likelihood. Consistency and asymptotic normality of maximum likelihood estimators is proved. Numerical aspects of the es...
Delay-Dependent Exponential Stability for Discrete-Time BAM Neural Networks with Time-Varying Delays
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Yonggang Chen
2008-01-01
Full Text Available This paper considers the delay-dependent exponential stability for discrete-time BAM neural networks with time-varying delays. By constructing the new Lyapunov functional, the improved delay-dependent exponential stability criterion is derived in terms of linear matrix inequality (LMI. Moreover, in order to reduce the conservativeness, some slack matrices are introduced in this paper. Two numerical examples are presented to show the effectiveness and less conservativeness of the proposed method.
Goldhaber-Fiebert, Jeremy D; Brandeau, Margaret L
2015-02-01
Risk factors increase the incidence and severity of chronic disease. To examine future trends and develop policies addressing chronic diseases, it is important to capture the relationship between exposure and disease development, which is challenging given limited data. To develop parsimonious risk factor models embeddable in chronic disease models, which are useful when longitudinal data are unavailable. The model structures encode relevant features of risk factors (e.g., time-varying, modifiable) and can be embedded in chronic disease models. Calibration captures time-varying exposures for the risk factor models using available cross-sectional data. We illustrate feasibility with the policy-relevant example of smoking in India. The model is calibrated to the prevalence of male smoking in 12 Indian regions estimated from the 2009-2010 Indian Global Adult Tobacco Survey. Nelder-Mead searches (250,000 starting locations) identify distributions of starting, quitting, and restarting rates that minimize the difference between modeled and observed age-specific prevalence. We compare modeled life expectancies to estimates in the absence of time-varying risk exposures and consider gains from hypothetical smoking cessation programs delivered for 1 to 30 years. Calibration achieves concordance between modeled and observed outcomes. Probabilities of starting to smoke rise and fall with age, while quitting and restarting probabilities fall with age. Accounting for time-varying smoking exposures is important, as not doing so produces smaller estimates of life expectancy losses. Estimated impacts of smoking cessation programs delivered for different periods depend on the fact that people who have been induced to abstain from smoking longer are less likely to restart. The approach described is feasible for important risk factors for numerous chronic diseases. Incorporating exposure-change rates can improve modeled estimates of chronic disease outcomes and of the long
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Xing Yin
2011-01-01
uncertain periodic switched recurrent neural networks with time-varying delays. When uncertain discrete-time recurrent neural network is a periodic system, it is expressed as switched neural network for the finite switching state. Based on the switched quadratic Lyapunov functional approach (SQLF and free-weighting matrix approach (FWM, some linear matrix inequality criteria are found to guarantee the delay-dependent asymptotical stability of these systems. Two examples illustrate the exactness of the proposed criteria.
Lu, Fengbin; Qiao, Han; Wang, Shouyang; Lai, Kin Keung; Li, Yuze
2017-01-01
This paper proposes a new time-varying coefficient vector autoregressions (VAR) model, in which the coefficient is a linear function of dynamic lagged correlation. The proposed model allows for flexibility in choices of dynamic correlation models (e.g. dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (GARCH) models, Markov-switching GARCH models and multivariate stochastic volatility models), which indicates that it can describe many types of time-varying causal effects. Time-varying causal relations between West Texas Intermediate (WTI) crude oil and the US Standard and Poor's 500 (S&P 500) stock markets are examined by the proposed model. The empirical results show that their causal relations evolve with time and display complex characters. Both positive and negative causal effects of the WTI on the S&P 500 in the subperiods have been found and confirmed by the traditional VAR models. Similar results have been obtained in the causal effects of S&P 500 on WTI. In addition, the proposed model outperforms the traditional VAR model. Copyright Â© 2016 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Ke Li
2016-01-01
Full Text Available A numerical electromagnetic method based on the physical optics with physical optics method (PO-PO is employed to calculate backscattered returns from a missile-like target above sea surface. Surfaces are time-varying Monte Carlo simulations initialized as realizations of a Pierson–Moskowitz spectrum. The monostatic normalized radar cross section of composite model by the hybrid PO-PO method is calculated and compared with those by the conventional method of moments, as well as the runtime and memory requirements. The results are found to be in good agreement. The runtime shows that the hybrid PO-PO method enables large-scale time-varying Monte Carlo simulations. The numerical simulations of the Doppler spectrum from the fast-moving target above time-varying lossy dielectric sea surface are obtained, and the Doppler spectra of backscattered signals from this model are discussed for different incident angles, speed of flying target, wind speeds, incident frequencies, and target altitudes in detail. Finally, the coupling effects on Doppler spectra are analyzed. All the results are obtained at the incidence of horizontal polarization wave in this study.
Xiao, Lin; Liao, Bolin; Li, Shuai; Chen, Ke
2018-02-01
In order to solve general time-varying linear matrix equations (LMEs) more efficiently, this paper proposes two nonlinear recurrent neural networks based on two nonlinear activation functions. According to Lyapunov theory, such two nonlinear recurrent neural networks are proved to be convergent within finite-time. Besides, by solving differential equation, the upper bounds of the finite convergence time are determined analytically. Compared with existing recurrent neural networks, the proposed two nonlinear recurrent neural networks have a better convergence property (i.e., the upper bound is lower), and thus the accurate solutions of general time-varying LMEs can be obtained with less time. At last, various different situations have been considered by setting different coefficient matrices of general time-varying LMEs and a great variety of computer simulations (including the application to robot manipulators) have been conducted to validate the better finite-time convergence of the proposed two nonlinear recurrent neural networks. Copyright © 2017 Elsevier Ltd. All rights reserved.
Zhang, Shangbin; He, Qingbo; Ouyang, Kesai; Xiong, Wei
2018-02-01
The wayside Acoustic Defective Bearing Detector (ADBD) system plays an important role in ensuring the safety of railway transportation. However, Doppler distortion and multi-bearing source aliasing in the acquired acoustic bearing signals significantly decrease the accuracy of bearing diagnosis. Traditional multisource separation schemes using time-frequency filters constructed by a single microphone signal always show poor performance on weak signal separation. Inspired by an assumption that the spatial location of different sources is different, this paper proposes a novel time-varying spatial filtering rearrangement (TSFR) scheme based on a microphone array to overcome current difficulties. In the scheme, a zero-angle spatial filter and peak searching are proposed to obtain the time-centers of corresponding sources. Based on these time-centers, several time-varying spatial filters are designed to extract different source signals. Then interpolation and rearrangement are used to correct the Doppler distortion and reconstruct the corresponding separated signals. Finally, the train bearing fault diagnosis is implemented by analyzing the envelope spectrum of the corrected signals. Because the time-varying spatial filter construction is only dependent on the source location and has little relationship with the signal energy, the proposed TSFR scheme has significant advantages in weak signal separation and diagnosis in comparison with traditional ones. With the verifications by both simulation and experiment cases, the proposed array-based TSFR scheme shows a good performance on multiple fault source separation and is expected to be used in the ADBD system.
Zhang, Zhijun; Li, Zhijun; Zhang, Yunong; Luo, Yamei; Li, Yuanqing
2015-12-01
We propose a dual-arm cyclic-motion-generation (DACMG) scheme by a neural-dynamic method, which can remedy the joint-angle-drift phenomenon of a humanoid robot. In particular, according to a neural-dynamic design method, first, a cyclic-motion performance index is exploited and applied. This cyclic-motion performance index is then integrated into a quadratic programming (QP)-type scheme with time-varying constraints, called the time-varying-constrained DACMG (TVC-DACMG) scheme. The scheme includes the kinematic motion equations of two arms and the time-varying joint limits. The scheme can not only generate the cyclic motion of two arms for a humanoid robot but also control the arms to move to the desired position. In addition, the scheme considers the physical limit avoidance. To solve the QP problem, a recurrent neural network is presented and used to obtain the optimal solutions. Computer simulations and physical experiments demonstrate the effectiveness and the accuracy of such a TVC-DACMG scheme and the neural network solver.
Study of the Influences of Transient Crack Propagation in a Pinion on Time-Varying Mesh Stiffness
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Youmin Hu
2016-01-01
Full Text Available Cracks in a cracked gear may further propagate by a tiny length in a very short time for several reasons, such as material fatigue and load fluctuations. In this paper, this dynamic process is defined as transient propagation of cracks. This research aims to calculate the time-varying mesh stiffness of gears when transient propagation of cracks arises, which has not been extensively studied in existing literatures. The transient propagation of cracks is modelled. An improved potential energy method is proposed by incorporating the propagation model into the potential energy method. The improved method can also be utilised to calculate the mesh stiffness of gears when transient propagation of cracks arises. Different transient propagation models are considered to simulate the propagation of cracks in a short amount of time. Different deterioration levels of cracks before transient propagation and different lengths and models of transient propagation are also examined. The variation rules of mesh stiffness caused by the transient propagation of cracks are summarised. The influence of the deterioration level of cracks on mesh stiffness variation when transient propagation arises is obtained. Simulation results show that the proposed method accurately calculates time-varying mesh stiffness when transient propagation of cracks arises. Furthermore, the method improves the monitoring of further propagation of cracks in gears from the perspective of time-varying mesh stiffness.
Zhao, Yong; Wang, Haoran; Zhang, Pingping; Sun, Chongyun; Wang, Xiaochen; Wang, Xinrui; Yang, Ruifu; Wang, Chengbin; Zhou, Lei
2016-02-17
The rapid high-throughput detection of foodborne pathogens is essential in controlling food safety. In this study, a 10-channel up-converting phosphor technology-based lateral flow (TC-UPT-LF) assay was established for the rapid and simultaneous detection of 10 epidemic foodborne pathogens. Ten different single-target UPT-LF strips were developed and integrated into one TC-UPT-LF disc with optimization. Without enrichment the TC-UPT-LF assay had a detection sensitivity of 10(4) CFU mL(-1) or 10(5) CFU mL(-1) for each pathogen, and after sample enrichment it was 10 CFU/0.6 mg. The assay also showed good linearity, allowing quantitative detection, with a linear fitting coefficient of determination (R(2)) of 0.916-0.998. The 10 detection channels did not cross-react, so multiple targets could be specifically detected. When 279 real food samples were tested, the assay was highly consistent (100%) with culture-based methods. The results for 110 food samples artificially contaminated with single or multiple targets showed a high detection rate (≥ 80%) for most target bacteria. Overall, the TC-UPT-LF assay allows the rapid, quantitative, and simultaneous detection of 10 kinds of foodborne pathogens within 20 min, and is especially suitable for the rapid detection and surveillance of foodborne pathogens in food and water.
Guo, Jun; Wang, Tingzhong; Yang, Tonghua; Xu, Jianmin; Li, Wentao; Fridman, Michael D.; Fisher, John T.; Zhang, Shetuan
2011-01-01
Cardiac repolarization is controlled by the rapidly (IKr) and slowly (IKs) activating delayed rectifier potassium channels. The human ether-a-go-go-related gene (hERG) encodes IKr, whereas KCNQ1 and KCNE1 together encode IKs. Decreases in IKr or IKs cause long QT syndrome (LQTS), a cardiac disorder with a high risk of sudden death. A reduction in extracellular K+ concentration ([K+]o) induces LQTS and selectively causes endocytic degradation of mature hERG channels from the plasma membrane. In the present study, we investigated whether IKs compensates for the reduced IKr under low K+ conditions. Our data show that when hERG and KCNQ1 were expressed separately in human embryonic kidney (HEK) cells, exposure to 0 mm K+ for 6 h completely eliminated the mature hERG channel expression but had no effect on KCNQ1. When hERG and KCNQ1 were co-expressed, KCNQ1 significantly delayed 0 mm K+-induced hERG reduction. Also, hERG degradation led to a significant reduction in KCNQ1 in 0 mm K+ conditions. An interaction between hERG and KCNQ1 was identified in hERG+KCNQ1-expressing HEK cells. Furthermore, KCNQ1 preferentially co-immunoprecipitated with mature hERG channels that are localized in the plasma membrane. Biophysical and pharmacological analyses indicate that although hERG and KCNQ1 closely interact with each other, they form distinct hERG and KCNQ1 channels. These data extend our understanding of delayed rectifier potassium channel trafficking and regulation, as well as the pathology of LQTS. PMID:21844197
Directory of Open Access Journals (Sweden)
Yingwei Li
2013-01-01
Full Text Available The global exponential stability issues are considered for almost periodic solution of the neural networks with mixed time-varying delays and discontinuous neuron activations. Some sufficient conditions for the existence, uniqueness, and global exponential stability of almost periodic solution are achieved in terms of certain linear matrix inequalities (LMIs, by applying differential inclusions theory, matrix inequality analysis technique, and generalized Lyapunov functional approach. In addition, the existence and asymptotically almost periodic behavior of the solution of the neural networks are also investigated under the framework of the solution in the sense of Filippov. Two simulation examples are given to illustrate the validity of the theoretical results.
Wei, Ruoyu; Cao, Jinde; Alsaedi, Ahmed
2018-02-01
This paper investigates the finite-time synchronization and fixed-time synchronization problems of inertial memristive neural networks with time-varying delays. By utilizing the Filippov discontinuous theory and Lyapunov stability theory, several sufficient conditions are derived to ensure finite-time synchronization of inertial memristive neural networks. Then, for the purpose of making the setting time independent of initial condition, we consider the fixed-time synchronization. A novel criterion guaranteeing the fixed-time synchronization of inertial memristive neural networks is derived. Finally, three examples are provided to demonstrate the effectiveness of our main results.
Cheng, Jun; Park, Ju H; Karimi, Hamid Reza; Shen, Hao
2017-08-02
This paper investigates the problem of sampled-data (SD) exponentially synchronization for a class of Markovian neural networks with time-varying delayed signals. Based on the tunable parameter and convex combination computational method, a new approach named flexible terminal approach is proposed to reduce the conservatism of delay-dependent synchronization criteria. The SD subject to stochastic sampling period is introduced to exhibit the general phenomena of reality. Novel exponential synchronization criterion are derived by utilizing uniform Lyapunov-Krasovskii functional and suitable integral inequality. Finally, numerical examples are provided to show the usefulness and advantages of the proposed design procedure.
Directory of Open Access Journals (Sweden)
Chen Qin
2013-01-01
Full Text Available This paper considers the problems of the robust stability and robust H∞ controller design for time-varying delay switched systems using delta operator approach. Based on the average dwell time approach and delta operator theory, a sufficient condition of the robust exponential stability is presented by choosing an appropriate Lyapunov-Krasovskii functional candidate. Then, a state feedback controller is designed such that the resulting closed-loop system is exponentially stable with a guaranteed H∞ performance. The obtained results are formulated in the form of linear matrix inequalities (LMIs. Finally, a numerical example is provided to explicitly illustrate the feasibility and effectiveness of the proposed method.
Directory of Open Access Journals (Sweden)
Yi-You Hou
2014-01-01
Full Text Available This paper considers the problem of the robust stability for the nonlinear system with time-varying delay and parameters uncertainties. Based on the H∞ theorem, Lyapunov-Krasovskii theory, and linear matrix inequality (LMI optimization technique, the H∞ quasi-sliding mode controller and switching function are developed such that the nonlinear system is asymptotically stable in the quasi-sliding mode and satisfies the disturbance attenuation (H∞-norm performance. The effectiveness and accuracy of the proposed methods are shown in numerical simulations.
Bell, Adrian R.; Brooks, Chris; Taylor, Nick
2016-01-01
This paper examines the time-varying nature of price discovery in eighteenth century cross-listed stocks. Specifically, we investigate how quickly news is reflected in prices for two of the great moneyed com- panies, the Bank of England and the East India Company, over the period 1723 to 1794. These British companies were cross-listed on the London and Amsterdam stock exchange and news between the capitals flowed mainly via the use of boats that transported mail. We examine in detail the hist...
Jia, Heping; Jin, Wende; Ding, Yi; Song, Yonghua; Yu, Dezhao
2017-01-01
With the expanding proportion of renewable energy generation and development of smart grid technologies, flexible demand resources (FDRs) have been utilized as an approach to accommodating renewable energies. However, multiple uncertainties of FDRs may influence reliable and secure operation of smart grid. Multi-state reliability models for a single FDR and aggregating FDRs have been proposed in this paper with regard to responsive abilities for FDRs and random failures for both FDR devices and information system. The proposed reliability evaluation technique is based on Lz transform method which can formulate time-varying reliability indices. A modified IEEE-RTS has been utilized as an illustration of the proposed technique.
Directory of Open Access Journals (Sweden)
Xuan Zhou
2014-01-01
Full Text Available This paper studies the cluster synchronization of a kind of complex networks by means of impulsive pinning control scheme. These networks are subject to stochastic noise perturbations and Markovian switching, as well as internal and outer time-varying delays. Using the Lyapunov-Krasovskii functional, Itö’s formula, and some linear matrix inequalities (LMI, several novel sufficient conditions are obtained to guarantee the desired cluster synchronization. At the end of this writing, a numerical simulation is given to demonstrate the effectiveness of those theoretical results.
Canfield, Brian K; King, Jason K; Robinson, William N; Hofmeister, William H; Davis, Lloyd M
2014-08-20
Cost-effective pharmaceutical drug discovery depends on increasing assay throughput while reducing reagent needs. To this end, we are developing an ultrasensitive, fluorescence-based platform that incorporates a nano/micro-fluidic chip with an array of closely spaced channels for parallelized optical readout of single-molecule assays. Here we describe the use of direct femtosecond laser machining to fabricate several hundred closely spaced channels on the surfaces of fused silica substrates. The channels are sealed by bonding to a microscope cover slip spin-coated with a thin film of poly(dimethylsiloxane). Single-molecule detection experiments are conducted using a custom-built, wide-field microscope. The array of channels is epi-illuminated by a line-generating red diode laser, resulting in a line focus just a few microns thick across a 500 micron field of view. A dilute aqueous solution of fluorescently labeled biomolecules is loaded into the device and fluorescence is detected with an electron-multiplying CCD camera, allowing acquisition rates up to 7 kHz for each microchannel. Matched digital filtering based on experimental parameters is used to perform an initial, rapid assessment of detected fluorescence. More detailed analysis is obtained through fluorescence correlation spectroscopy. Simulated fluorescence data is shown to agree well with experimental values.
Rothenberger, Scott D; Krafty, Robert T; Taylor, Briana J; Cribbet, Matthew R; Thayer, Julian F; Buysse, Daniel J; Kravitz, Howard M; Buysse, Evan D; Hall, Martica H
2015-04-01
No studies have evaluated the dynamic, time-varying relationship between delta electroencephalographic (EEG) sleep and high frequency heart rate variability (HF-HRV) in women. Delta EEG and HF-HRV were measured during sleep in 197 midlife women (M(age) = 52.1, SD = 2.2). Delta EEG-HF-HRV correlations in nonrapid eye movement (NREM) sleep were modeled as whole-night averages and as continuous functions of time. The whole-night delta EEG-HF-HRV correlation was positive. The strongest correlations were observed during the first NREM sleep period preceding and following peak delta power. Time-varying correlations between delta EEG-HF-HRV were stronger in participants with sleep-disordered breathing and self-reported insomnia compared to healthy controls. The dynamic interplay between sleep and autonomic activity can be modeled across the night to examine within- and between-participant differences including individuals with and without sleep disorders. Copyright © 2014 Society for Psychophysiological Research.
Nie, Xiaobing; Zheng, Wei Xing
2015-05-01
This paper is concerned with the problem of coexistence and dynamical behaviors of multiple equilibrium points for neural networks with discontinuous non-monotonic piecewise linear activation functions and time-varying delays. The fixed point theorem and other analytical tools are used to develop certain sufficient conditions that ensure that the n-dimensional discontinuous neural networks with time-varying delays can have at least 5(n) equilibrium points, 3(n) of which are locally stable and the others are unstable. The importance of the derived results is that it reveals that the discontinuous neural networks can have greater storage capacity than the continuous ones. Moreover, different from the existing results on multistability of neural networks with discontinuous activation functions, the 3(n) locally stable equilibrium points obtained in this paper are located in not only saturated regions, but also unsaturated regions, due to the non-monotonic structure of discontinuous activation functions. A numerical simulation study is conducted to illustrate and support the derived theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.
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Li Qi
2016-06-01
Full Text Available Dynamic time-varying operational conditions pose great challenge to the estimation of system remaining useful life (RUL for the deteriorating systems. This paper presents a method based on probabilistic and stochastic approaches to estimate system RUL for periodically monitored degradation processes with dynamic time-varying operational conditions and condition-specific failure zones. The method assumes that the degradation rate is influenced by specific operational condition and moreover, the transition between different operational conditions plays the most important role in affecting the degradation process. These operational conditions are assumed to evolve as a discrete-time Markov chain (DTMC. The failure thresholds are also determined by specific operational conditions and described as different failure zones. The 2008 PHM Conference Challenge Data is utilized to illustrate our method, which contains mass sensory signals related to the degradation process of a commercial turbofan engine. The RUL estimation method using the sensor measurements of a single sensor was first developed, and then multiple vital sensors were selected through a particular optimization procedure in order to increase the prediction accuracy. The effectiveness and advantages of the proposed method are presented in a comparison with existing methods for the same dataset.
Directory of Open Access Journals (Sweden)
Li Yang
2017-01-01
Full Text Available Paste-like tailings slurry (PTLS is always simplified as a Bingham plastic fluid, leading to excessive computational errors in the calculation of the hydraulic gradient. In the case of paste-like tailings in long-distance pipeline transportation, to explore a high-precision and reliable hydraulic gradient formula, the rheological behavior of paste-like tailings slurry was analyzed, a time-varying hydraulic gradient model was constructed, and a series of laboratory shear tests were conducted. The results indicate that the PTLS shows noticeable shear-thinning characteristics in constant shear tests; the calculated hydraulic gradient declined by about 56%, from 4.44 MPa·km−1 to 1.95 MPa·km−1 within 253 s, and remained constant for the next four hours during the pipeline transportation. Comparing with the balance hydraulic gradient obtained in a semi-industrial loop test, the computational errors of those calculated by using the time-varying hydraulic gradient model, Jinchuan formula, and Shanxi formula are 15%, 78%, and 130%, respectively. Therefore, our model is a feasible and high-precision solution for the calculation of the hydraulic gradient of paste-like tailings in long-distance pipeline transportation.
Markham, Michael R; Kaczmarek, Leonard K; Zakon, Harold H
2013-04-01
We investigated the ionic mechanisms that allow dynamic regulation of action potential (AP) amplitude as a means of regulating energetic costs of AP signaling. Weakly electric fish generate an electric organ discharge (EOD) by summing the APs of their electric organ cells (electrocytes). Some electric fish increase AP amplitude during active periods or social interactions and decrease AP amplitude when inactive, regulated by melanocortin peptide hormones. This modulates signal amplitude and conserves energy. The gymnotiform Eigenmannia virescens generates EODs at frequencies that can exceed 500 Hz, which is energetically challenging. We examined how E. virescens meets that challenge. E. virescens electrocytes exhibit a voltage-gated Na(+) current (I(Na)) with extremely rapid recovery from inactivation (τ(recov) = 0.3 ms) allowing complete recovery of Na(+) current between APs even in fish with the highest EOD frequencies. Electrocytes also possess an inwardly rectifying K(+) current and a Na(+)-activated K(+) current (I(KNa)), the latter not yet identified in any gymnotiform species. In vitro application of melanocortins increases electrocyte AP amplitude and the magnitudes of all three currents, but increased I(KNa) is a function of enhanced Na(+) influx. Numerical simulations suggest that changing I(Na) magnitude produces corresponding changes in AP amplitude and that K(Na) channels increase AP energy efficiency (10-30% less Na(+) influx/AP) over model cells with only voltage-gated K(+) channels. These findings suggest the possibility that E. virescens reduces the energetic demands of high-frequency APs through rapidly recovering Na(+) channels and the novel use of KNa channels to maximize AP amplitude at a given Na(+) conductance.
Yu, Hanjie; Li, Mengmeng; Shen, Xinbei; Lv, Dan; Sun, Xin; Wang, Jinting; Gu, Xinmei; Hu, Jingning; Wang, Chuang
2018-02-01
Previous studies have shown that a low dose of scopolamine produces rapid-acting antidepressant-like actions in rodents. Understanding the mechanisms underlying this effect and the dose-dependent variations of drug responses remains an important task. L-type voltage-dependent calcium channels were found to mediate rapid-acting antidepressant effects of certain medications (e.g., ketamine). Therefore, it is of great interest to determine the involvement of L-type voltage-dependent calcium channels in the action of scopolamine. Herein, we investigated the mechanisms underlying behavioral responses to various doses of scopolamine in mice to clarify the involvement of L-type voltage-dependent calcium channels in its modes of action. Open field test, novel object recognition test, and forced swimming test were performed on mice administered varied doses of scopolamine (0.025, 0.05, 0.1, 1, and 3 mg/kg, i.p.) alone or combined with L-type voltage-dependent calcium channel blocker verapamil (5 mg/kg, i.p.). Then, the changes in brain-derived neurotrophic factor and neuropeptide VGF (nonacronymic) levels in the hippocampus and prefrontal cortex of these mice were analyzed. Low doses of scopolamine (0.025 and 0.05 mg/kg) produced significant antidepressant-like effects in the forced swimming test, while higher doses (1 and 3 mg/kg) resulted in significant memory deficits and depressive-like behaviors. Moreover, the behavioral changes in responses to various doses may be related to the upregulation (0.025 and 0.05 mg/kg) and downregulation (1 and 3 mg/kg) of brain-derived neurotrophic factor and VGF in the hippocampus and prefrontal cortex in mice. We further found that the rapid-acting antidepressant-like effects and the upregulation on brain-derived neurotrophic factor and VGF produced by a low dose of scopolamine (0.025 mg/kg) were completely blocked by verapamil. These results indicate that L-type voltage-dependent calcium channels are likely involved in the behavioral
Garcia-Belmonte, Germà
2017-06-01
Spatial visualization is a well-established topic of education research that has allowed improving science and engineering students' skills on spatial relations. Connections have been established between visualization as a comprehension tool and instruction in several scientific fields. Learning about dynamic processes mainly relies upon static spatial representations or images. Visualization of time is inherently problematic because time can be conceptualized in terms of two opposite conceptual metaphors based on spatial relations as inferred from conventional linguistic patterns. The situation is particularly demanding when time-varying signals are recorded using displaying electronic instruments, and the image should be properly interpreted. This work deals with the interplay between linguistic metaphors, visual thinking and scientific instrument mediation in the process of interpreting time-varying signals displayed by electronic instruments. The analysis draws on a simplified version of a communication system as example of practical signal recording and image visualization in a physics and engineering laboratory experience. Instrumentation delivers meaningful signal representations because it is designed to incorporate a specific and culturally favored time view. It is suggested that difficulties in interpreting time-varying signals are linked with the existing dual perception of conflicting time metaphors. The activation of specific space-time conceptual mapping might allow for a proper signal interpretation. Instruments play then a central role as visualization mediators by yielding an image that matches specific perception abilities and practical purposes. Here I have identified two ways of understanding time as used in different trajectories through which students are located. Interestingly specific displaying instruments belonging to different cultural traditions incorporate contrasting time views. One of them sees time in terms of a dynamic metaphor
Luo, T. H.; Liang, S.; Miao, C. B.
2017-12-01
A method of terminal vibration analysis based on Time-varying Glowworm Swarm Optimization algorithm is proposed in order to solve the problem that terminal vibration of the large flexible robot cantilever under heavy load precision.The robot cantilever of the ballastless track is used as the research target and the natural parameters of the flexible cantilever such as the natural frequency, the load impact and the axial deformation is considered. Taking into account the change of the minimum distance between the glowworm individuals, the terminal vibration response and adaptability could meet. According to the Boltzmann selection mechanism, the dynamic parameters in the motion simulation process are determined, while the influence of the natural frequency and the load impact as well as the axial deformation on the terminal vibration is studied. The method is effective and stable, which is of great theoretical basis for the study of vibration control of flexible cantilever terminal.
Directory of Open Access Journals (Sweden)
Hamid Reza Karimi
2009-01-01
Full Text Available The problem of stability analysis for a class of neutral systems with mixed time-varying neutral, discrete and distributed delays and nonlinear parameter perturbations is addressed. By introducing a novel Lyapunov-Krasovskii functional and combining the descriptor model transformation, the Leibniz-Newton formula, some free-weighting matrices, and a suitable change of variables, new sufficient conditions are established for the stability of the considered system, which are neutral-delay-dependent, discrete-delay-range-dependent, and distributed-delay-dependent. The conditions are presented in terms of linear matrix inequalities (LMIs and can be efficiently solved using convex programming techniques. Two numerical examples are given to illustrate the efficiency of the proposed method.
Zhang, Wei; Huang, Tingwen; He, Xing; Li, Chuandong
2017-11-01
In this study, we investigate the global exponential stability of inertial memristor-based neural networks with impulses and time-varying delays. We construct inertial memristor-based neural networks based on the characteristics of the inertial neural networks and memristor. Impulses with and without delays are considered when modeling the inertial neural networks simultaneously, which are of great practical significance in the current study. Some sufficient conditions are derived under the framework of the Lyapunov stability method, as well as an extended Halanay differential inequality and a new delay impulsive differential inequality, which depend on impulses with and without delays, in order to guarantee the global exponential stability of the inertial memristor-based neural networks. Finally, two numerical examples are provided to illustrate the efficiency of the proposed methods. Copyright © 2017 Elsevier Ltd. All rights reserved.
Li, Hongfei; Jiang, Haijun; Hu, Cheng
2016-03-01
In this paper, we investigate a class of memristor-based BAM neural networks with time-varying delays. Under the framework of Filippov solutions, boundedness and ultimate boundedness of solutions of memristor-based BAM neural networks are guaranteed by Chain rule and inequalities technique. Moreover, a new method involving Yoshizawa-like theorem is favorably employed to acquire the existence of periodic solution. By applying the theory of set-valued maps and functional differential inclusions, an available Lyapunov functional and some new testable algebraic criteria are derived for ensuring the uniqueness and global exponential stability of periodic solution of memristor-based BAM neural networks. The obtained results expand and complement some previous work on memristor-based BAM neural networks. Finally, a numerical example is provided to show the applicability and effectiveness of our theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.
Feria, Ying; Cheung, Kar-Ming
1995-01-01
In a time-varying signal-to-noise-ratio (SNR) environment, symbol rate is changed to maximize data return. However, the symbol-rate changes may cause the receiver symbol loop to lose lock, thus losing real-time data. We propose an alternate way of varying the data rate in a seamless fashion by puncturing the convolutionally encoded symbol stream and transmitting the punctured encoded symbols with a constant symbol rate. We systematically searched for good puncturing patterns for the Galileo (14,1/4) convolutional code and changed the data rates by using the punctured codes to match the Galileo SNR profile of November 9, 1997. We concluded that this scheme reduces the symbol-rate changes from 9 to 2 and provides a larger data return and a higher symbol SNR during most of the day.
Seamless Data-Rate Change Using Punctured Convolutional Codes for Time-Varying Signal-to-Noise Ratio
Feria, Ying
1995-01-01
In a time-varying signal-to-noise (SNR) environment, symbol rate is often changed to maximize ata return. However, the symbol-rate change has some undesirable effects such as changing the ransmission bandwidth and perhaps causing the receiver symbol loop to lose lock temporarily, thus osing some data. In this article, we are proposing an alternate way of varying the data rate without hanging the symbol rate and therefore the transmission bandwidth. The data rate change is achieved n a seamless fashion by puncturing the convolutionally encoded symbol stream to adapt to the hanging SNR environment. We have also derived an exact expression to enumerate the number of nique puncturing patterns. To demonstrate this seamless rate-change capability, we searched for good uncturing patterns for the Galileo (14, 1/4) convolutional code and changed the data rates by using the unctured codes to match the Galileo SNR profile of November 9, 1997.
Wang, Leimin; Shen, Yi; Zhang, Guodong
2016-10-01
This paper is concerned with the synchronization problem for a class of switched neural networks (SNNs) with time-varying delays. First, a new crucial lemma which includes and extends the classical exponential stability theorem is constructed. Then by using the lemma, new algebraic criteria of ψ -type synchronization (synchronization with general decay rate) for SNNs are established via the designed nonlinear feedback control. The ψ -type synchronization which is in a general framework is obtained by introducing a ψ -type function. It contains exponential synchronization, polynomial synchronization, and other synchronization as its special cases. The results of this paper are general, and they also complement and extend some previous results. Finally, numerical simulations are carried out to demonstrate the effectiveness of the obtained results.
Varga, Peter; Grafarend, Erik; Engels, Johannes
2017-03-01
There are different equations to describe relations between different classes of Love-Shida numbers. In this study with the use of the time-varying gravitational potential an integral relation was obtained which connects tidal Love-Shida numbers (h, l, k), load numbers (h', l', k'), potential free Love-Shida numbers generated by normal (h″, l″, k″) and horizontal (h‴, l‴, k‴) stresses. The equations obtained in frame of present study is the only one which - holds for every type of Love-Shida numbers, - describes a relationship not between different, but the same type of Love-Shida numbers, - does not follow from the sixth-order differential equation system of motion usually applied to calculate the Love-Shida numbers.
DEFF Research Database (Denmark)
Silvennoinen, Annestiina; Terasvirta, Timo
A new multivariate volatility model that belongs to the family of conditional correlation GARCH models is introduced. The GARCH equations of this model contain a multiplicative deterministic component to describe long-run movements in volatility and, in addition, the correlations are deterministi......A new multivariate volatility model that belongs to the family of conditional correlation GARCH models is introduced. The GARCH equations of this model contain a multiplicative deterministic component to describe long-run movements in volatility and, in addition, the correlations...... are deterministically time-varying. Parameters of the model are estimated jointly using maximum likelihood. Consistency and asymptotic normality of maximum likelihood estimators is proved. Numerical aspects of the estimation algorithm are discussed. A bivariate empirical example is provided....
Directory of Open Access Journals (Sweden)
Shuo Li
2013-01-01
Full Text Available This paper investigates the problems of stability and l1-gain controller design for positive switched systems with time-varying delays via delta operator approach. The purpose is to design a switching signal and a state feedback controller such that the resulting closed-loop system is exponentially stable with l1-gain performance. Based on the average dwell time approach, a sufficient condition for the existence of an l1-gain controller for the considered system is established by constructing an appropriate copositive type Lyapunov-Krasovskii functional in delta domain. Moreover, the obtained conditions can unify some previously suggested relevant methods in the literature of both continuous- and discrete-time systems into the delta operator framework. Finally, a numerical example is presented to explicitly demonstrate the effectiveness and feasibility of the proposed method.
Directory of Open Access Journals (Sweden)
Jinxing Lin
2010-01-01
Full Text Available This paper is concerned with the problems of exponential admissibility and dynamic output feedback (DOF control for a class of continuous-time switched singular systems with interval time-varying delay. A full-order, dynamic, synchronously switched DOF controller is considered. First, by using the average dwell time approach, a delay-range-dependent exponential admissibility criterion for the unforced switched singular time-delay system is established in terms of linear matrix inequalities (LMIs. Then, based on this criterion, a sufficient condition on the existence of a desired DOF controller, which guarantees that the closed-loop system is regular, impulse free and exponentially stable, is proposed by employing the LMI technique. Finally, some illustrative examples are given to show the effectiveness of the proposed approach.
Gupta, Deepak K; Fonck, Raymond R
2008-01-01
A new time-delay estimation (TDE) technique based on dynamic programming is developed, to measures the time-varying time-delay between two signals. Dynamic programming based TDE technique provides a frequency response 5 to 10 times higher than previously known TDE techniques, namely those based on time-lag cross-correlation or wavelet analysis. Effects of frequency spectrum, signal-to-noise ratio and amplitude of time-delay on response (represented as transfer function) of TDE technique is studied using simulated data signals. Transfer function for the technique decreases with increase in noise in signal; however it is independent of signal spectrum shape. Dynamic programming based TDE technique is applied to the Beam-Emission-Spectroscopy (BES) diagnostic data to measure poloidal velocity fluctuations, which led to the observation of theoretically predicted zonal flows in high-temperature tokamak plasmas.
On the correct use of stepped-sine excitations for the measurement of time-varying bioimpedance.
Louarroudi, E; Sanchez, B
2017-02-01
When a linear time-varying (LTV) bioimpedance is measured using stepped-sine excitations, a compromise must be made: the temporal distortions affecting the data depend on the experimental time, which in turn sets the data accuracy and limits the temporal bandwidth of the system that needs to be measured. Here, the experimental time required to measure linear time-invariant bioimpedance with a specified accuracy is analyzed for different stepped-sine excitation setups. We provide simple equations that allow the reader to know whether LTV bioimpedance can be measured through repeated time- invariant stepped-sine experiments. Bioimpedance technology is on the rise thanks to a plethora of healthcare monitoring applications. The results presented can help to avoid distortions in the data while measuring accurately non-stationary physiological phenomena. The impact of the work presented is broad, including the potential of enhancing bioimpedance studies and healthcare devices using bioimpedance technology.
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Jun Li
2014-01-01
Full Text Available This paper is concerned with the stability problem for a class of uncertain impulsive stochastic genetic regulatory networks (UISGRNs with time-varying delays both in the leakage term and in the regulator function. By constructing a suitable Lyapunov-Krasovskii functional which uses the information on the lower bound of the delay sufficiently, a delay-dependent stability criterion is derived for the proposed UISGRNs model by using the free-weighting matrices method and convex combination technique. The conditions obtained here are expressed in terms of LMIs whose feasibility can be checked easily by MATLAB LMI control toolbox. In addition, three numerical examples are given to justify the obtained stability results.
Cai, Zuowei; Huang, Lihong
2014-05-01
In this paper, we formulate and investigate a class of memristor-based BAM neural networks with time-varying delays. Under the framework of Filippov solutions, the viability and dissipativity of solutions for functional differential inclusions and memristive BAM neural networks can be guaranteed by the matrix measure approach and generalized Halanay inequalities. Then, a new method involving the application of set-valued version of Krasnoselskii' fixed point theorem in a cone is successfully employed to derive the existence of the positive periodic solution. The dynamic analysis in this paper utilizes the theory of set-valued maps and functional differential equations with discontinuous right-hand sides of Filippov type. The obtained results extend and improve some previous works on conventional BAM neural networks. Finally, numerical examples are given to demonstrate the theoretical results via computer simulations.
2018-01-01
This paper mainly studies the globally fixed-time synchronization of a class of coupled neutral-type neural networks with mixed time-varying delays via discontinuous feedback controllers. Compared with the traditional neutral-type neural network model, the model in this paper is more general. A class of general discontinuous feedback controllers are designed. With the help of the definition of fixed-time synchronization, the upper right-hand derivative and a defined simple Lyapunov function, some easily verifiable and extensible synchronization criteria are derived to guarantee the fixed-time synchronization between the drive and response systems. Finally, two numerical simulations are given to verify the correctness of the results. PMID:29370248
Jeon, Hee Jung; Kim, Clara Tammy; An, Jung Nam; Lee, Hajeong; Kim, Hyosang; Park, Su-Kil; Joo, Kwon Wook; Lim, Chun Soo; Jung, In Mok; Ahn, Curie; Kim, Yon Su; Kim, Young Hoon; Lee, Jung Pyo
2015-12-01
In the general population, proteinuria is associated with progression to kidney failure, cardiovascular disease, and mortality. Here, we analyzed the effects of proteinuria on outcomes in kidney transplant recipients. We performed a retrospective, multi-centre cohort study involving 2047 recipients to evaluate the effects of post-transplant proteinuria on adverse cardiovascular events, graft failure, and mortality. Patients were classified into two groups according to their levels of proteinuria: patients without proteinuria (150 mg/day, n = 1113) and proteinuric patients (≥ 150 mg/day, n = 934). Multivariate Cox hazard model was conducted with using the maximal proteinuria as time-varying covariate. During a median 55.3-month (range, 0.6-167.1) follow-up, there were 50 cases of major adverse cardiac events (cardiac death, nonfatal myocardial infarction, or coronary revascularization), 115 cases of graft failure, and 52 patient deaths. In multivariate Cox regression with time-varying covariate, proteinuric recipients were significantly associated with major adverse cardiac events (hazard ratio [HR] 8.689, 95% confidence interval [CI] 2.929-25.774, P proteinuria. Recipients with proteinuria showed significantly higher incidences of acute rejection (23.1% vs. 9.4%, P proteinuria (HR 6.815, 95% CI 2.164-21.467, P = 0.001). Post-transplant proteinuria correlates with adverse cardiovascular events, graft failure, and mortality. Therefore, proteinuria should be evaluated and managed to improve the outcomes of renal recipients. © 2015 Asian Pacific Society of Nephrology.
Lyons, Jennifer G.; Cauley, Jane A.; Hochberg, Marc; Applebaum, Katie M.
2015-01-01
Background. Previous studies have shown inconsistent associations between caregiving and mortality. This may be due to analyzing caregiver status at baseline only, and that better health is probably related to taking on caregiving responsibilities and continuing in that role. The latter is termed The Healthy Caregiver Hypothesis, similar to the Healthy Worker Effect in occupational epidemiology. We applied common approaches from occupational epidemiology to evaluate the association between caregiving and mortality, including treating caregiving as time-varying and lagging exposure up to 5 years. Methods. Caregiving status among 1,068 women (baseline mean age = 81.0 years; 35% caregivers) participating in the Caregiver-Study of Osteoporotic Fractures study was assessed at five interviews conducted between 1999 and 2009. Mortality was determined through January 2012. Cox proportional hazards models were used to estimate adjusted hazard ratios and 95% confidence intervals adjusted for sociodemographics, perceived stress, and functional limitations. Results. A total of 483 participants died during follow-up (38.8% and 48.7% of baseline caregivers and noncaregivers, respectively). Using baseline caregiving status, the association with mortality was 0.77, 0.62–0.95. Models of time-varying caregiving status showed a more pronounced reduction in mortality in current caregivers (hazard ratios = 0.54, 0.38–0.75), which diminished with longer lag periods (3-year lag hazard ratio = 0.68, 0.52–0.88, 5-year lag hazard ratios = 0.76, 0.60–0.95). Conclusions. Overall, caregivers had lower mortality rates than noncaregivers in all analyses. These associations were sensitive to the lagged period, indicating that the timing of leaving caregiving does influence this relationship and should be considered in future investigations. PMID:25878033
Sotero, Roberto C; Shmuel, Amir
2012-06-01
Several studies posit energy as a constraint on the coding and processing of information in the brain due to the high cost of resting and evoked cortical activity. This suggestion has been addressed theoretically with models of a single neuron and two coupled neurons. Neural mass models (NMMs) address mean-field based modeling of the activity and interactions between populations of neurons rather than a few neurons. NMMs have been widely employed for studying the generation of EEG rhythms, and more recently as frameworks for integrated models of neurophysiology and functional MRI (fMRI) responses. To date, the consequences of energy constraints on the activity and interactions of ensembles of neurons have not been addressed. Here we aim to study the impact of constraining energy consumption during the resting-state on NMM parameters. To this end, we first linearized the model, then used stochastic control theory by introducing a quadratic cost function, which transforms the NMM into a stochastic linear quadratic regulator (LQR). Solving the LQR problem introduces a regime in which the NMM parameters, specifically the effective connectivities between neuronal populations, must vary with time. This is in contrast to current NMMs, which assume a constant parameter set for a given condition or task. We further simulated energy-constrained stochastic control of a specific NMM, the Wilson and Cowan model of two coupled neuronal populations, one of which is excitatory and the other inhibitory. These simulations demonstrate that with varying weights of the energy-cost function, the NMM parameters show different time-varying behavior. We conclude that constraining NMMs according to energy consumption may create more realistic models. We further propose to employ linear NMMs with time-varying parameters as an alternative to traditional nonlinear NMMs with constant parameters.
Ali, M Sanni; Groenwold, Rolf H H|info:eu-repo/dai/nl/30481203X; Belitser, Svetlana V; Souverein, Patrick C; Martín, Elisa; Gatto, Nicolle M; Huerta, Consuelo; Gardarsdottir, Helga|info:eu-repo/dai/nl/321858131; Roes, Kit C B|info:eu-repo/dai/nl/115147020; Hoes, Arno W|info:eu-repo/dai/nl/101111762; de Boer, Antonius; Klungel, Olaf H|info:eu-repo/dai/nl/181447649
2016-01-01
BACKGROUND: Observational studies including time-varying treatments are prone to confounding. We compared time-varying Cox regression analysis, propensity score (PS) methods, and marginal structural models (MSMs) in a study of antidepressant [selective serotonin reuptake inhibitors (SSRIs)] use and
Directory of Open Access Journals (Sweden)
Farnoosh Talaei
2017-12-01
Full Text Available This paper presents a reduced rank channel estimator for multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM high speed railway (HSR systems. Conventional interpolation based channel estimators require high pilot load for robust estimation of the rapidly time varying frequency-selective MIMO-OFDM HSR channel. To relax the high pilot overhead requirement, we take advantage of the channel’s restriction to low dimensional subspaces due to the time, frequency and spatial correlation and propose a low complexity linear minimum mean square error (LMMSE channel estimator. The channel estimator utilizes a four-dimensional (4D basis expansion channel model obtained from band-limited generalized discrete prolate spheroidal (GDPS sequences. Simulation results validate that the mean square estimation error of the proposed estimator is smaller than that of the conventional interpolation based least square (LS estimator and the performance is robust to different delay, Doppler and angular spreads.
Szalai, Emily B.; Fleischer, Guy W.; Bence, James R.
2003-01-01
A concurrent increase in lakewide abundance and decrease in size-at-age of bloater (Coregonus hoyi) in Lake Michigan have suggested density-dependent growth regulation. We investigated these temporal patterns by fitting a dynamic von Bertalanffy model and lengthweight relationship with time-varying parameters to mean length- and weight-at-ages (ages 17) from annual surveys (1965-1999). We modeled yearling length, asymptotic size (L‰), and the parameters of a power relationship between mean weight and mean length (α and β) as changing slowly over time using a random walk model. The Brody growth coefficient (k) was modeled as a linear function of L‰ with year-specific random deviations. Our results support a positive relationship between L‰ and k, indicating that under conditions supporting larger asymptotic lengths, individuals approach the asymptote more rapidly. We explored the relationship between year-specific growth parameters and indices of lakewide bloater abundance and found evidence of density-dependent growth. However, in the most recent years, L‰ and yearling length have remained low in Lake Michigan despite low bloater abundances, suggesting the occurrence of a fundamental shift in the food web.
DEFF Research Database (Denmark)
Bjerrum-Niese, Christian; Jensen, Leif Bjørnø
1996-01-01
Underwater acoustic modems using coherent modulation, such as phase-shift keying, have proven to efficiently exploit the bandlimited underwater acoustical communication channel. However, the performance of an acoustic modem, given as maximum range and data and error rate, is limited in the complex...
Directory of Open Access Journals (Sweden)
Alrijadjis .
2014-12-01
Full Text Available The proportional integral derivative (PID controllers have been widely used in most process control systems for a long time. However, it is a very important problem how to choose PID parameters, because these parameters give a great influence on the control performance. Especially, it is difficult to tune these parameters for nonlinear systems. In this paper, a new modified particle swarm optimization (PSO is presented to search for optimal PID parameters for such system. The proposed algorithm is to modify constriction coefficient which is nonlinearly decreased time-varying for improving the final accuracy and the convergence speed of PSO. To validate the control performance of the proposed method, a typical nonlinear system control, a continuous stirred tank reactor (CSTR process, is illustrated. The results testify that a new modified PSO algorithm can perform well in the nonlinear PID control system design in term of lesser overshoot, rise-time, settling-time, IAE and ISE. Keywords: PID controller, Particle Swarm Optimization (PSO,constriction factor, nonlinear system.
Wright, Aidan G.C.; Hallquist, Michael N.; Swartz, Holly A.; Frank, Ellen; Cyranowski, Jill M.
2014-01-01
Objective We demonstrate the utility of the time-varying effect model (TVEM) for the analysis of psychotherapy data, with the aim of elucidating complex patterns of change over time and dynamic associations between constructs of interest. Specifically, we examine the association between depression and co-occurring anxiety in a sample of adults treated with interpersonal psychotherapy for depression (IPT) or a variant designed to address both depression and co-occurring anxiety (IPT-PS, IPT for depression with panic and anxiety symptoms). Method Seventy-eight (82% female) adult outpatients with major depression and co-occurring anxiety were assessed at each of 16 outpatient treatment sessions using the Hamilton rating scales for depression and anxiety. Results On average, depressive symptoms declined in a quadratic form over the course of treatment. While the association between anxiety and depression was modest early in treatment, it strengthened over the middle and latter treatment phases. Finally, exploratory analyses suggest that while IPT and IPT-PS were similarly effective in reducing depressive symptoms, IPT-PS may be more effective at uncoupling the association between core anxiety and depressive symptoms. Conclusions Findings point to the utility of the TVEM for psychotherapy research, and the importance of assessing anxiety in the course of treating depression, especially following the initial phase of treatment (i.e., after session 5). PMID:24041230
Feria, Y.; Cheung, K.-M.
1995-01-01
In a time-varying signal-to-noise ration (SNR) environment, symbol rate is often changed to maximize data return. However, the symbol-rate change has some undesirable effects, such as changing the transmission bandwidth and perhaps causing the receiver symbol loop to lose lock temporarily, thus losing some data. In this article, we are proposing an alternate way of varying the data rate without changing the symbol rate and, therefore, the transmission bandwidth. The data rate change is achieved in a seamless fashion by puncturing the convolutionally encoded symbol stream to adapt to the changing SNR environment. We have also derived an exact expression to enumerate the number of distinct puncturing patterns. To demonstrate this seamless rate change capability, we searched for good puncturing patterns for the Galileo (14,1/4) convolutional code and changed the data rates by using the punctured codes to match the Galileo SNR profile of November 9, 1997. We show that this scheme reduces the symbol-rate changes from nine to two and provides a comparable data return in a day and a higher symbol SNR during most of the day.
Ahmad, Sahar; Khan, Muhammad Faisal
2015-12-01
In this paper, we present a new non-rigid image registration method that imposes a topology preservation constraint on the deformation. We propose to incorporate the time varying elasticity model into the deformable image matching procedure and constrain the Jacobian determinant of the transformation over the entire image domain. The motion of elastic bodies is governed by a hyperbolic partial differential equation, generally termed as elastodynamics wave equation, which we propose to use as a deformation model. We carried out clinical image registration experiments on 3D magnetic resonance brain scans from IBSR database. The results of the proposed registration approach in terms of Kappa index and relative overlap computed over the subcortical structures were compared against the existing topology preserving non-rigid image registration methods and non topology preserving variant of our proposed registration scheme. The Jacobian determinant maps obtained with our proposed registration method were qualitatively and quantitatively analyzed. The results demonstrated that the proposed scheme provides good registration accuracy with smooth transformations, thereby guaranteeing the preservation of topology. Copyright © 2015 Elsevier Ltd. All rights reserved.
Wu, R. Q.; Zhang, W.; Yao, M. H.
2018-02-01
In this paper, we analyze the complicated nonlinear dynamics of rotor-active magnetic bearings (rotor-AMB) with 16-pole legs and the time varying stiffness. The magnetic force with 16-pole legs is obtained by applying the electromagnetic theory. The governing equation of motion for rotor-active magnetic bearings is derived by using the Newton's second law. The resulting dimensionless equation of motion for the rotor-AMB system is expressed as a two-degree-of-freedom nonlinear system including the parametric excitation, quadratic and cubic nonlinearities. The averaged equation of the rotor-AMB system is obtained by using the method of multiple scales when the primary parametric resonance and 1/2 subharmonic resonance are taken into account. From the frequency-response curves, it is found that there exist the phenomena of the soft-spring type nonlinearity and the hardening-spring type nonlinearity in the rotor-AMB system. The effects of different parameters on the nonlinear dynamic behaviors of the rotor-AMB system are investigated. The numerical results indicate that the periodic, quasi-periodic and chaotic motions occur alternately in the rotor-AMB system.
Korayem, M H; Nekoo, S R
2015-01-01
This article investigates finite-time optimal and suboptimal controls for time-varying systems with state and control nonlinearities. The state-dependent Riccati equation (SDRE) controller was the main framework. A finite-time constraint imposed on the equation changes it to a differential equation, known as the state-dependent differential Riccati equation (SDDRE) and this equation was applied to the problem reported in this study that provides general formulation and stability analysis. The following four solution methods were developed for solving the SDDRE; backward integration, state transition matrix (STM) and the Lyapunov based method. In the Lyapunov approach, both positive and negative definite solutions to related SDRE were used to provide suboptimal gain for the SDDRE. Finite-time suboptimal control is applied for robotic manipulator, as finite-time constraint strongly decreases state error and operation time. General state-dependent coefficient (SDC) parameterizations for rigid and flexible joint arms (prismatic or revolute joints) are introduced. By including nonlinear control inputs in the formulation, the actuator׳s limits can be inserted directly to the state-space equation of a manipulator. A finite-time SDRE was implemented on a 6R manipulator both in theory and experimentally. And a reduced 3R arm was modeled and tested as a flexible joint robot (FJR). Evaluations of load carrying capacity and operation time were investigated to assess the capability of this approach, both of which showed significant improvement. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
DeGarmo, David S.
2010-01-01
This study tested identity theory models of father involvement for 230 divorced fathers of young children aged 4 to 11 followed over 18 months. Research questions were (1) Do measures of identity salience and centrality of the fathering role predict fathering involvement over time? (2) Does father involvement predict fathering identity over time? (3) Does father custody moderate these relationships? Involvement was assessed as contact frequency, number of father-child activities, and positive involvement observed during father-child interaction. Comparisons showed that the quantity of involvement differed by custody but there were few differences in the quality of involvement. Fathers did not exhibit significant mean decreases in involvement and custodial groups did not differ in the growth rates for involvement nor identity measures. However, there were significant individual differences in growth rates, meaning there was variance in fathers increasing and decreasing in measures over time. Time 1 father identities, measured as salience and centrality, predicted days per month, overnights per month, and father child activities over time. Time-varying predictors suggested that identities were more predictive of growth in involvement than vice versa although father involvement predicted salience and primarily centrality. Implications for practice and future research are discussed. PMID:20617120
Kuwata, Yoshiaki; Blackmore, Lars; Wolf, Michael; Fathpour, Nanaz; Newman, Claire; Elfes, Alberto
2009-01-01
Hot air (Montgolfiere) balloons represent a promising vehicle system for possible future exploration of planets and moons with thick atmospheres such as Venus and Titan. To go to a desired location, this vehicle can primarily use the horizontal wind that varies with altitude, with a small help of its own actuation. A main challenge is how to plan such trajectory in a highly nonlinear and time-varying wind field. This paper poses this trajectory planning as a graph search on the space-time grid and addresses its computational aspects. When capturing various time scales involved in the wind field over the duration of long exploration mission, the size of the graph becomes excessively large. We show that the adjacency matrix of the graph is block-triangular, and by exploiting this structure, we decompose the large planning problem into several smaller subproblems, whose memory requirement stays almost constant as the problem size grows. The approach is demonstrated on a global reachability analysis of a possible Titan mission scenario.
Energy Technology Data Exchange (ETDEWEB)
Zhang, Wenbing [Department of Mathematics, Yangzhou University, Yangzhou 225002 (China); Wang, Zidong [Department of Computer Science, Brunel University London, Uxbridge, Middlesex, UB8 3PH (United Kingdom); Liu, Yurong, E-mail: yrliu@yzu.edu.cn [Department of Mathematics, Yangzhou University, Yangzhou 225002 (China); Communication Systems and Networks (CSN) Research Group, Faculty of Engineering, King Abdulaziz University, Jeddah 21589 (Saudi Arabia); Ding, Derui [Shanghai Key Lab of Modern Optical System, Department of Control Science and Engineering, University of Shanghai for Science and Technology, Shanghai 200093 (China); Alsaadi, Fuad E. [Communication Systems and Networks (CSN) Research Group, Faculty of Engineering, King Abdulaziz University, Jeddah 21589 (Saudi Arabia)
2017-01-05
The paper is concerned with the state estimation problem for a class of time-delayed complex networks with event-triggering communication protocol. A novel event generator function, which is dependent not only on the measurement output but also on a predefined positive constant, is proposed with hope to reduce the communication burden. A new concept of exponentially ultimate boundedness is provided to quantify the estimation performance. By means of the comparison principle, some sufficient conditions are obtained to guarantee that the estimation error is exponentially ultimately bounded, and then the estimator gains are obtained in terms of the solution of certain matrix inequalities. Furthermore, a rigorous proof is proposed to show that the designed triggering condition is free of the Zeno behavior. Finally, a numerical example is given to illustrate the effectiveness of the proposed event-based estimator. - Highlights: • An event-triggered estimator is designed for complex networks with time-varying delays. • A novel event generator function is proposed to reduce the communication burden. • The comparison principle is utilized to derive the sufficient conditions. • The designed triggering condition is shown to be free of the Zeno behavior.
Degarmo, David S
2010-01-01
This study tested identity theory models of father involvement for 230 divorced fathers of young children aged 4 to 11 followed over 18 months. Research questions were (1) Do measures of identity salience and centrality of the fathering role predict fathering involvement over time? (2) Does father involvement predict fathering identity over time? (3) Does father custody moderate these relationships? Involvement was assessed as contact frequency, number of father-child activities, and positive involvement observed during father-child interaction. Comparisons showed that the quantity of involvement differed by custody but there were few differences in the quality of involvement. Fathers did not exhibit significant mean decreases in involvement and custodial groups did not differ in the growth rates for involvement nor identity measures. However, there were significant individual differences in growth rates, meaning there was variance in fathers increasing and decreasing in measures over time. Time 1 father identities, measured as salience and centrality, predicted days per month, overnights per month, and father child activities over time. Time-varying predictors suggested that identities were more predictive of growth in involvement than vice versa although father involvement predicted salience and primarily centrality. Implications for practice and future research are discussed.
Directory of Open Access Journals (Sweden)
Zheng Yang
2013-01-01
Full Text Available Torsional spring-loaded antibacklash gear which can improve the transmission precision is widely used in many precision transmission fields. It is very important to investigate the dynamic characteristics of antibacklash gear. In the paper, applied force analysis is completed in detail. Then, defining the starting point of double-gear meshing as initial position, according to the meshing characteristic of antibacklash gear, single- or double-tooth meshing states of two gear pairs and the transformation relationship at any moment are determined. Based on this, a nonlinear model of antibacklash gear with time-varying friction and meshing stiffness is proposed. The influences of friction and variations of torsional spring stiffness, damping ratio and preload on dynamic transmission error (DTE are analyzed by numerical calculation and simulation, and the results show that antibacklash gear can increase the composite meshing stiffness; when the torsional spring stiffness is large enough, the oscillating components of the DTE (ODTE and the RMS of the DTE (RDTE trend to be a constant value; the variations of ODTE and RDTE are not significant, unless preload exceeds a certain value.
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Corey B Hart
2013-05-01
Full Text Available We present and apply a method that uses point process statistics to discriminate the forms of synergies in motor pattern data, prior to explicit synergy extraction. The method uses electromyogram (EMG pulse peak timing or onset timing. Peak timing is preferable in complex patterns where pulse onsets may be overlapping. An interval statistic derived from the point processes of EMG peak timings distinguishes time-varying synergies from synchronous synergies. Model data shows that the statistic is robust for most conditions. Its application to both frog hindlimb EMG and rat locomotion hindlimb EMG show data from these preparations is clearly most consistent with synchronous synergy models (p<0.001. Additional direct tests of pulse and interval relations in frog data further bolster the support for synchronous synergy mechanisms in these data. Our method and analyses support separated control of rhythm and pattern of motor primitives, with the low level execution primitives comprising pulsed synchronous synergies in both frog and rat, and both episodic and rhythmic behaviors.
Robust Moving Horizon H∞ Control of Discrete Time-Delayed Systems with Interval Time-Varying Delays
Directory of Open Access Journals (Sweden)
F. Yıldız Tascikaraoglu
2014-01-01
Full Text Available In this study, design of a delay-dependent type moving horizon state-feedback control (MHHC is considered for a class of linear discrete-time system subject to time-varying state delays, norm-bounded uncertainties, and disturbances with bounded energies. The closed-loop robust stability and robust performance problems are considered to overcome the instability and poor disturbance rejection performance due to the existence of parametric uncertainties and time-delay appeared in the system dynamics. Utilizing a discrete-time Lyapunov-Krasovskii functional, some delay-dependent linear matrix inequality (LMI based conditions are provided. It is shown that if one can find a feasible solution set for these LMI conditions iteratively at each step of run-time, then we can construct a control law which guarantees the closed-loop asymptotic stability, maximum disturbance rejection performance, and closed-loop dissipativity in view of the actuator limitations. Two numerical examples with simulations on a nominal and uncertain discrete-time, time-delayed systems, are presented at the end, in order to demonstrate the efficiency of the proposed method.
Wang, Jing; Qi, Zhaohui; Wang, Gang
2017-10-01
The dynamic analysis of cable-pulley systems is investigated in this paper, where the time-varying length characteristic of the cable as well as the coupling motion between the cable and the pulleys are considered. The dynamic model for cable-pulley systems are presented based on the principle of virtual power. Firstly, the cubic spline interpolation is adopted for modeling the flexible cable elements and the virtual 1powers of tensile strain, inertia and gravity forces on the cable are formulated. Then, the coupled motions between the cable and the movable or fixed pulley are described by the input and output contact points, based on the no-slip assumption and the spatial description. The virtual powers of inertia, gravity and applied forces on the contact segment of the cable, the movable and fixed pulleys are formulated. In particular, the internal node degrees of freedom of spline cable elements are reduced, which results in that only the independent description parameters of the nodes connected to the pulleys are included in the final governing dynamic equations. At last, two cable-pulley lifting mechanisms are considered as demonstrative application examples where the vibration of the lifting process is investigated. The comparison with ADAMS models is given to prove the validity of the proposed method.
Liu, Minling; Li, Lixian; Yu, Wei; Chen, Jie; Xiong, Weibin; Chen, Shuang; Yu, Li
2017-03-21
It has been well recognized that the effects of many prognostic factors could change during long-term follow-up. Although marriage has been proven to be a significant prognostic factor for the survival of colon cancer, whether the effect of marriage is constant with time remain unknown. This study analyzed the impact of marital status on the mortality of colon cancer patients with an extended Cox model that allowed for time-varying effects. We identified 71,955 patients who underwent colectomy between 2004 and 2009 to treat colon adenocarcinoma from the Surveilance, Epidemiology and End Results Database. The multivariate extended Cox model was used to evaluate the effect of marital status on all-cause mortality, while the Fine-Gray competing risks model was used for colon cancer-specific mortality, with death from other causes as the competing risk. The unmarried patients carried a 1.37-fold increased risk of all-cause mortality compared with the married patients (95%CI: 1.33-1.40; peffects on survival. Marriage is a dependent prognosis factor for survival of surgically treated colon adenocarcinoma patients. Psychological interventions are suggested to improve receipt of treatment among unmarried patients, as their poor survival may be due to the inefficient treatment.
Adaptive RAC codes employing statistical channel evaluation ...
African Journals Online (AJOL)
In time varying channels the noise and interference vary randomly. Forward error correction codes (FEC) on such channels are designed to cater for the worst possible state and require a large amount of redundancy at all time. This means that when the channel is relatively noiseless, excessive error control power and ...
Wilusz, D. C.; Harman, C. J.; Ball, W. P.
2014-12-01
Modeling the dynamics of chemical transport from the landscape to streams is necessary for water quality management. Previous work has shown that estimates of the distribution of water age in streams, the transit time distribution (TTD), can improve prediction of the concentration of conservative tracers (i.e., ones that "follow the water") based on upstream watershed inputs. A major challenge however has been accounting for climate and transport variability when estimating TDDs at the catchment scale. In this regard, Harman (2014, in review) proposed the Omega modeling framework capable of using watershed hydraulic fluxes to approximate the time-varying TTD. The approach was previously applied to the Plynlimon research watershed in Wales to simulate stream concentration dynamics of a conservative tracer (chloride) including 1/f attenuation of the power spectra density. In this study we explore the extent to which TTDs estimated by the Omega model vary with the concentration of non-conservative tracers (i.e., ones whose concentrations are also affected by transformations and interactions with other phases). First we test the hypothesis that the TTD calibrated in Plynlimon can explain a large part of the variation in non-conservative stream water constituents associated with storm flow (acidity, Al, DOC, Fe) and base flow (Ca, Si). While controlling for discharge, we show a correlation between the percentage of water of different ages and constituent concentration. Second, we test the hypothesis that TTDs help explain variation in stream nitrate concentration, which is of particular interest for pollution control but can be highly non-conservative. We compare simulation runs from Plynlimon and the agricultural Choptank watershed in Maryland, USA. Following a top-down approach, we estimate nitrate concentration as if it were a conservative tracer and examine the structure of residuals at different temporal resolutions. Finally, we consider model modifications to
Halekas, J. S.; Poppe, A. R.; Farrell, W. M.; McFadden, J. P.
2016-01-01
By analyzing the trajectories of ionized constituents of the lunar exosphere in time-varying electromagnetic fields, we can place constraints on the composition, structure, and dynamics of the lunar exosphere. Heavy ions travel slower than light ions in the same fields, so by observing the lag between field rotations and the response of ions from the lunar exosphere, we can place constraints on the composition of the ions. Acceleration, Reconnection, Turbulence, and Electrodynamics of Moon's Interaction with the Sun (ARTEMIS) provides an ideal platform to utilize such an analysis, since its two-probe vantage allows precise timing of the propagation of field discontinuities in the solar wind, and its sensitive plasma instruments can detect the ion response. We demonstrate the utility of this technique by using fully time-dependent charged particle tracing to analyze several minutes of ion observations taken by the two ARTEMIS probes 3000-5000 km above the dusk terminator on 25 January 2014. The observations from this time period allow us to reach several interesting conclusions. The ion production at altitudes of a few hundred kilometers above the sunlit surface of the Moon has an unexpectedly significant contribution from species with masses of 40 amu or greater. The inferred distribution of the neutral source population has a large scale height, suggesting that micrometeorite impact vaporization and/or sputtering play an important role in the production of neutrals from the surface. Our observations also suggest an asymmetry in ion production, consistent with either a compositional variation in neutral vapor production or a local reduction in solar wind sputtering in magnetic regions of the surface.
Zhao, Dezun; Li, Jianyong; Cheng, Weidong; Wen, Weigang
2016-09-01
Multi-fault detection of the rolling element bearing under time-varying rotational speed presents a challenging issue due to its complexity, disproportion and interaction. Computed order analysis (COA) is one of the most effective approaches to remove the influences of speed fluctuation, and detect all the features of multi-fault. However, many interference components in the envelope order spectrum may lead to false diagnosis results, in addition, the deficiencies of computational accuracy and efficiency also cannot be neglected. To address these issues, a novel method for compound faults detection of rolling element bearing based on the generalized demodulation (GD) algorithm is proposed in this paper. The main idea of the proposed method is to exploit the unique property of the generalized demodulation algorithm in transforming an interested instantaneous frequency trajectory of compound faults bearing signal into a line paralleling to the time axis, and then the FFT algorithm can be directly applied to the transformed signal. This novel method does not need angular resampling algorithm which is the key step of the computed order analysis, and is hence free from the deficiencies of computational error and efficiency. On the other hand, it only acts on the instantaneous fault characteristic frequency trends in envelope signal of multi-fault bearing which include rich fault information, and is hence free from irrelevant items interferences. Both simulated and experimental faulty bearing signal analysis validate that the proposed method is effective and reliable on the compound faults detection of rolling element bearing under variable rotational speed conditions. The comprehensive comparison with the computed order analysis further shows that the proposed method produces higher accurate results in less computation time.
Libera, Arianna; de Barros, Felipe P. J.; Riva, Monica; Guadagnini, Alberto
2017-10-01
Our study is keyed to the analysis of the interplay between engineering factors (i.e., transient pumping rates versus less realistic but commonly analyzed uniform extraction rates) and the heterogeneous structure of the aquifer (as expressed by the probability distribution characterizing transmissivity) on contaminant transport. We explore the joint influence of diverse (a) groundwater pumping schedules (constant and variable in time) and (b) representations of the stochastic heterogeneous transmissivity (T) field on temporal histories of solute concentrations observed at an extraction well. The stochastic nature of T is rendered by modeling its natural logarithm, Y = ln T, through a typical Gaussian representation and the recently introduced Generalized sub-Gaussian (GSG) model. The latter has the unique property to embed scale-dependent non-Gaussian features of the main statistics of Y and its (spatial) increments, which have been documented in a variety of studies. We rely on numerical Monte Carlo simulations and compute the temporal evolution at the well of low order moments of the solute concentration (C), as well as statistics of the peak concentration (Cp), identified as the environmental performance metric of interest in this study. We show that the pumping schedule strongly affects the pattern of the temporal evolution of the first two statistical moments of C, regardless the nature (Gaussian or non-Gaussian) of the underlying Y field, whereas the latter quantitatively influences their magnitude. Our results show that uncertainty associated with C and Cp estimates is larger when operating under a transient extraction scheme than under the action of a uniform withdrawal schedule. The probability density function (PDF) of Cp displays a long positive tail in the presence of time-varying pumping schedule. All these aspects are magnified in the presence of non-Gaussian Y fields. Additionally, the PDF of Cp displays a bimodal shape for all types of pumping
Zhang, Zhen; Yan, Peng; Jiang, Huan; Ye, Peiqing
2014-09-01
In this paper, we consider the discrete time-varying internal model-based control design for high precision tracking of complicated reference trajectories generated by time-varying systems. Based on a novel parallel time-varying internal model structure, asymptotic tracking conditions for the design of internal model units are developed, and a low order robust time-varying stabilizer is further synthesized. In a discrete time setting, the high precision tracking control architecture is deployed on a Voice Coil Motor (VCM) actuated servo gantry system, where numerical simulations and real time experimental results are provided, achieving the tracking errors around 3.5‰ for frequency-varying signals. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Zeyad Al-Zhour
2016-06-01
Full Text Available In this paper, we generalize the time-varying descriptor systems to the case of fractional order in matrix forms. Moreover, we present the general exact solutions of the linear singular and non-singular matrix fractional time-varying descriptor systems with constant coefficient matrices in Caputo sense by using a new attractive method. Finally, two illustrated examples are also given to show our new approach.
Sen, Subhamoy; Crinière, Antoine; Mevel, Laurent; Cerou, Frederic; Dumoulin, Jean
2017-04-01
Keywords: Parameter estimation; Kalman filter; Particle filter; Particle-Kalman filter; Correlated noise Although Kalman filter (KF) was originally proposed for system control i.e. steering a system as desired by monitoring the system states, its application for parameter estimation problems is widespread because of the excellent similarity between these two apparently different problem types in state space description. In standard Kalman filter, system dynamics is described through the dynamics of certain internal variable, termed as states, evolving over time as defined by an assumed process model, while a measurement model maps these states to measurements. In some parameter estimation problems, the system is replaced by a state space formulation of the dynamic model with parameters appended in the unobserved states and collectively observed through the response measurements. Filtering based parameter estimation problems are thus inherently nonlinear due to the required nonlinear mapping of parameters to the corresponding observations. Being a linear estimator, Kalman Filter (KF) cannot be employed for such nonlinear system estimation and alternative filtering algorithms (eg. Particle filter) are therefore generally used. However, being model based, these filters optimally estimate the parameters of a quasi-static model of the real dynamic system. Consequently, any time variation in the system dynamics may completely diverge the estimation yielding a false or infeasible solution. By decoupling the estimation of system states and parameters, and applying concurrent filtering strategy that attempts conditional estimation of states based on parameters and vice versa, time varying systems can be estimated. This article attempts to combine KF with Particle filter (PF) and apply them for estimation of states and system parameters respectively on a system with correlated noise in process and measurement. The idea is to nest a bank of linear KFs for state estimation
Li, Qingjie; Sarna, Sushil K
2011-01-01
Chronic stress elevates plasma norepinephrine, which enhances expression of the α(1C)-subunit of Ca(v)1.2b channels in colonic smooth muscle cells within 1 h. Transcriptional upregulation usually does not explain such rapid protein synthesis. We investigated whether chronic stress-induced release of norepinephrine utilizes posttranscriptional mechanisms to enhance the α(1C)-subunit. We performed experiments on colonic circular smooth muscle strips and in conscious rats, using a 9-day chronic intermittent stress protocol. Incubation of rat colonic muscularis externa with norepinephrine enhanced α(1C)-protein expression within 45 min, without a concomitant increase in α(1C) mRNA, indicating posttranscriptional regulation of α(1C)-protein by norepinephrine. We found that norepinephrine activates the PI3K/Akt/GSK-3β pathway to concurrently enhance α(1C)-protein translation and block its polyubiquitination and proteasomal degradation. Incubation of colonic muscularis externa with norepinephrine or LiCl, which inhibits GSK-3β, enhanced p-GSK-3β and α(1C)-protein time dependently. Using enrichment of phosphoproteins and ubiquitinated proteins, we found that both norepinephrine and LiCl decrease α(1C) phosphorylation and polyubiquitination. Concurrently, they suppress eIF2α (Ser51) phosphorylation and 4E-BP1 expression, which stimulates gene-specific translation. The antagonism of two upstream kinases, PI3K and Akt, inhibits the induction of α(1C)-protein by norepinephrine. Cyanopindolol (β(3)-AR-antagonist) almost completely suppresses and propranolol (β(1/2)-AR antagonist) partially suppresses norepinephrine-induced α(1C)-protein expression, whereas phentolamine and prazosin (α-AR and α(1)-AR antagonist, respectively) have no significant effect. Experiments in conscious animals showed that chronic stress activates the PI3K/Akt/GSK-3β signaling. We conclude that norepinephrine released by chronic stress rapidly enhances the protein expression of α(1C
Jamal, Wasifa; Maharatna, Koushik
2016-01-01
In this paper, we have developed a new measure of understanding the temporal evolution of phase synchronization for EEG signals using cross-electrode information. From this measure it is found that there exists a small number of well-defined phase-synchronized states, each of which is stable for few milliseconds during the execution of a face perception task. We termed these quasi-stable states as synchrostates. We used k-means clustering algorithms to estimate the optimal number of synchrostates from 100 trials of EEG signals over 128 channels. Our results show that these synchrostates exist consistently in all the different trials. It is also found that from the onset of the stimulus, switching between these synchrostates results in well-behaved temporal sequence with repeatability which may be indicative of the dynamics of the cognitive process underlying that task. Therefore these synchrostates and their temporal switching sequences may be used as a new measure of the stability of phase synchrony and info...
Jin, Long; Zhang, Yunong; Li, Shuai
2016-12-01
Matrix inversion often arises in the fields of science and engineering. Many models for matrix inversion usually assume that the solving process is free of noises or that the denoising has been conducted before the computation. However, time is precious for the real-time-varying matrix inversion in practice, and any preprocessing for noise reduction may consume extra time, possibly violating the requirement of real-time computation. Therefore, a new model for time-varying matrix inversion that is able to handle simultaneously the noises is urgently needed. In this paper, an integration-enhanced Zhang neural network (IEZNN) model is first proposed and investigated for real-time-varying matrix inversion. Then, the conventional ZNN model and the gradient neural network model are presented and employed for comparison. In addition, theoretical analyses show that the proposed IEZNN model has the global exponential convergence property. Moreover, in the presence of various kinds of noises, the proposed IEZNN model is proven to have an improved performance. That is, the proposed IEZNN model converges to the theoretical solution of the time-varying matrix inversion problem no matter how large the matrix-form constant noise is, and the residual errors of the proposed IEZNN model can be arbitrarily small for time-varying noises and random noises. Finally, three illustrative simulation examples, including an application to the inverse kinematic motion planning of a robot manipulator, are provided and analyzed to substantiate the efficacy and superiority of the proposed IEZNN model for real-time-varying matrix inversion.
Mukherjee, Kunal; Wacaser, Brent A.; Bedell, Stephen W.; Sadana, Devendra K.
2017-06-01
Electron channeling contrast imaging (ECCI) is emerging as a technique for rapid and high-resolution characterization of individual crystalline defects in a scanning electron microscope. However, the application of ECCI to semiconductor materials has been limited to bare samples in plan-view geometry. In this paper, two modalities of this technique are demonstrated with relevance to semiconductor manufacturing and failure analysis: (1) The use of ECCI to reveal misfit dislocation defects along a cleaved cross-section of a SiGe compositionally graded buffer grown on Si and (2) plan-view imaging of misfit dislocations in metamorphic SiGe/Si layers covered by amorphous oxide layers, where the partial loss of contrast due to the oxide layers is quantified and the effect of the beam accelerating voltage is studied. These results demonstrate the power of ECCI in inspecting crystallographic defects non-destructively over large areas, which is highly desirable for substrate quality control in manufacturing of products based on crystalline materials.
Chen, Wei; Guo, Li-xin; Li, Jiang-ting
2017-04-01
This study analyzes the scattering characteristics of obliquely incident electromagnetic (EM) waves in a time-varying plasma sheath. The finite-difference time-domain algorithm is applied. According to the empirical formula of the collision frequency in a plasma sheath, the plasma frequency, temperature, and pressure are assumed to vary with time in the form of exponential rise. Some scattering problems of EM waves are discussed by calculating the radar cross section (RCS) of the time-varying plasma. The laws of the RCS varying with time are summarized at the L and S wave bands.
Directory of Open Access Journals (Sweden)
Jin Wang
2017-03-01
Full Text Available This article proposes a multiple-step fault estimation algorithm for hypersonic flight vehicles that uses an interval type-II Takagi–Sugeno fuzzy model. An interval type-II Takagi–Sugeno fuzzy model is developed to approximate the nonlinear dynamic system and handle the parameter uncertainties of hypersonic firstly. Then, a multiple-step time-varying additive fault estimation algorithm is designed to estimate time-varying additive elevator fault of hypersonic flight vehicles. Finally, the simulation is conducted in both aspects of modeling and fault estimation; the validity and availability of such method are verified by a series of the comparison of numerical simulation results.
de Jong, Roy G; Burden, Andrea M; de Kort, Sander; van Herk-Sukel, Myrthe P; Vissers, Pauline A; Janssen, Paddy K; Haak, Harm R; Masclee, Ad A; de Vries, Frank; Janssen-Heijnen, Maryska L
2017-01-01
Previous studies on metformin use and gastrointestinal (GI) cancer risk have yielded inconclusive results on metformin's chemoprotective effects. We aimed to evaluate GI cancer risk in users of metformin in The Netherlands using a time-varying approach in a large population-based database. A cohort
Hiemstra, J.M.; Otten, R.; Engels, R.C.M.E.
2012-01-01
This study examined the timing of smoking onset during mid- or late adolescence and the time-varying effects of refusal self-efficacy, parental and sibling smoking behavior, smoking behavior of friends and best friend, and parental smoking-specific communication. We used data from five annual waves
DeVico Fallani, F.; Latora, V.; Astolfi, L.; Cincotti, F.; Mattia, D.; Marciani, M. G.; Salinari, S.; Colosimo, A.; Babiloni, F.
2008-06-01
In this work, a novel approach based on the estimate of time-varying graph indices is proposed in order to capture the basic schemes of communication within the functional brain networks during a simple motor act. To achieve this, we used a cascade of computational tools able to estimate first the electrical activity of the cortical surface by using high-resolution EEG techniques. From the cortical signals of different regions of interests we estimated the time-varying functional connectivity patterns by means of the adaptive partial directed coherence. The time-varying connectivity estimation returns a series of networks evolving during the examined task which can be summarized and interpreted with the aid of mathematical indices based on graph theory. The combination of all these methods is demonstrated on a set of high-resolution EEG data recorded from a group of healthy subjects performing a simple foot movement. It can be anticipated that the combination of the time-varying connectivity with the theoretical graph analysis is able to reveal precious information about the interconnections of the cerebral network as the significant persistence of mutual links and three-node motifs.
Nocentini, Annalaura; Calamai, Giulia; Menesini, Ersilia
2012-01-01
The codevelopment of delinquent behaviors and depressive symptoms from Grade 9 to 11 was investigated on an Italian sample of 518 adolescents (399 male) after the transition to high school, evaluating the time-invariant effects of past school failure and social failure and the time-varying effects of school achievement and social problems.…
Roubos, D.; Bhulai, S.
2010-01-01
In this article we develop techniques for applying Approximate Dynamic Programming (ADP) to the control of time-varying queuing systems. First, we show that the classical state space representation in queuing systems leads to approximations that can be significantly improved by increasing the
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De Vico Fallani, F; Colosimo, A [Interdepartmental Research Centre for Models and Information Analysis in Biomedical Systems, University ' La Sapienza' , Corso V. Emanuele, 244, 00186, Rome (Italy); Latora, V [Department of Physics and Astronomy, University of Catania, Via S.Sofia, 64, Catania (Italy); Astolfi, L; Cincotti, F; Mattia, D; Marciani, M G; Babiloni, F [IRCCS ' Fondazione Santa Lucia' , Via Ardeatina, 306, Rome (Italy); Salinari, S [Department of ' Informatica e Sistemistica' , University ' Sapienza' , Via Ariosto, 25, Rome (Italy)], E-mail: fabrizio.devicofallani@uniroma1.it, E-mail: latora@ct.infn.it
2008-06-06
In this work, a novel approach based on the estimate of time-varying graph indices is proposed in order to capture the basic schemes of communication within the functional brain networks during a simple motor act. To achieve this, we used a cascade of computational tools able to estimate first the electrical activity of the cortical surface by using high-resolution EEG techniques. From the cortical signals of different regions of interests we estimated the time-varying functional connectivity patterns by means of the adaptive partial directed coherence. The time-varying connectivity estimation returns a series of networks evolving during the examined task which can be summarized and interpreted with the aid of mathematical indices based on graph theory. The combination of all these methods is demonstrated on a set of high-resolution EEG data recorded from a group of healthy subjects performing a simple foot movement. It can be anticipated that the combination of the time-varying connectivity with the theoretical graph analysis is able to reveal precious information about the interconnections of the cerebral network as the significant persistence of mutual links and three-node motifs.
Zhou, Si-Da; Ma, Yuan-Chen; Liu, Li; Kang, Jie; Ma, Zhi-Sai; Yu, Lei
2018-01-01
Identification of time-varying modal parameters contributes to the structural health monitoring, fault detection, vibration control, etc. of the operational time-varying structural systems. However, it is a challenging task because there is not more information for the identification of the time-varying systems than that of the time-invariant systems. This paper presents a vector time-dependent autoregressive model and least squares support vector machine based modal parameter estimator for linear time-varying structural systems in case of output-only measurements. To reduce the computational cost, a Wendland's compactly supported radial basis function is used to achieve the sparsity of the Gram matrix. A Gamma-test-based non-parametric approach of selecting the regularization factor is adapted for the proposed estimator to replace the time-consuming n-fold cross validation. A series of numerical examples have illustrated the advantages of the proposed modal parameter estimator on the suppression of the overestimate and the short data. A laboratory experiment has further validated the proposed estimator.
Directory of Open Access Journals (Sweden)
Fang Zhao
2016-02-01
Full Text Available Voltage-gated sodium channels (VGSCs are responsible for the generation of the action potential. Among nine classified VGSC subtypes (Nav1.1–Nav1.9, Nav1.7 is primarily expressed in the sensory neurons, contributing to the nociception transmission. Therefore Nav1.7 becomes a promising target for analgesic drug development. In this study, we compared the influence of an array of VGSC agonists including veratridine, BmK NT1, brevetoxin-2, deltamethrin and antillatoxin (ATX on membrane depolarization which was detected by Fluorescence Imaging Plate Reader (FLIPR membrane potential (FMP blue dye. In HEK-293 cells heterologously expressing hNav1.7 α-subunit, ATX produced a robust membrane depolarization with an EC50 value of 7.8 ± 2.9 nM whereas veratridine, BmK NT1, and deltamethrin produced marginal response. Brevetoxin-2 was without effect on membrane potential change. The ATX response was completely inhibited by tetrodotoxin suggesting that the ATX response was solely derived from hNav1.7 activation, which was consistent with the results where ATX produced a negligible response in null HEK-293 cells. Six VGSC antagonists including lidocaine, lamotrigine, phenytoin, carbamazepine, riluzole, and 2-amino-6-trifluoromethylthiobenzothiazole all concentration-dependently inhibited ATX response with IC50 values comparable to that reported from patch-clamp experiments. Considered together, we demonstrate that ATX is a unique efficacious hNav1.7 activator which offers a useful probe to develop a rapid throughput screening assay to identify hNav1.7 antagonists.
Zhao, Fang; Li, Xichun; Jin, Liang; Zhang, Fan; Inoue, Masayuki; Yu, Boyang; Cao, Zhengyu
2016-02-16
Voltage-gated sodium channels (VGSCs) are responsible for the generation of the action potential. Among nine classified VGSC subtypes (Nav1.1-Nav1.9), Nav1.7 is primarily expressed in the sensory neurons, contributing to the nociception transmission. Therefore Nav1.7 becomes a promising target for analgesic drug development. In this study, we compared the influence of an array of VGSC agonists including veratridine, BmK NT1, brevetoxin-2, deltamethrin and antillatoxin (ATX) on membrane depolarization which was detected by Fluorescence Imaging Plate Reader (FLIPR) membrane potential (FMP) blue dye. In HEK-293 cells heterologously expressing hNav1.7 α-subunit, ATX produced a robust membrane depolarization with an EC50 value of 7.8 ± 2.9 nM whereas veratridine, BmK NT1, and deltamethrin produced marginal response. Brevetoxin-2 was without effect on membrane potential change. The ATX response was completely inhibited by tetrodotoxin suggesting that the ATX response was solely derived from hNav1.7 activation, which was consistent with the results where ATX produced a negligible response in null HEK-293 cells. Six VGSC antagonists including lidocaine, lamotrigine, phenytoin, carbamazepine, riluzole, and 2-amino-6-trifluoromethylthiobenzothiazole all concentration-dependently inhibited ATX response with IC50 values comparable to that reported from patch-clamp experiments. Considered together, we demonstrate that ATX is a unique efficacious hNav1.7 activator which offers a useful probe to develop a rapid throughput screening assay to identify hNav1.7 antagonists.
Yang, Hanyu; Cranford, James A; Li, Runze; Buu, Anne
2015-02-20
This study proposes a generalized time-varying effect model that can be used to characterize a discrete longitudinal covariate process and its time-varying effect on a later outcome that may be discrete. The proposed method can be applied to examine two important research questions for daily process data: measurement reactivity and predictive validity. We demonstrate these applications using health risk behavior data collected from alcoholic couples through an interactive voice response system. The statistical analysis results show that the effect of measurement reactivity may only be evident in the first week of interactive voice response assessment. Moreover, the level of urge to drink before measurement reactivity takes effect may be more predictive of a later depression outcome. Our simulation study shows that the performance of the proposed method improves with larger sample sizes, more time points, and smaller proportions of zeros in the binary longitudinal covariate. Copyright © 2014 John Wiley & Sons, Ltd.
Dermody, Sarah S; Thomas, Katherine M; Hopwood, Christopher J; Durbin, C Emily; Wright, Aidan G C
2017-06-01
This paper demonstrates a recently-popularized quantitative method, the time-varying effect model (TVEM), in describing dynamic, momentary interpersonal processes implicated by Interpersonal Theory. We investigated moment-to-moment complementarity in affiliation and control behaviors (i.e., correspondence in affiliation and reciprocity in control between married dyad members) in a five-minute interaction (N=135), and how complementarity changed over time. Overall, results supported complementarity in affiliation and control. Moreover, effects were time-varying: Complementarity in affiliation increased over time and complementary in control changed over time in a cyclical manner. Dyadic adjustment moderated the strength in complementarity in control during specific timeframes. We discuss implications of these results and future directions. The findings support the utility of TVEM for studying dynamic and time-dependent interpersonal processes.
Hua, Yongzhao; Dong, Xiwang; Li, Qingdong; Ren, Zhang
2017-11-01
This paper investigates the fault-tolerant time-varying formation control problems for high-order linear multi-agent systems in the presence of actuator failures. Firstly, a fully distributed formation control protocol is presented to compensate for the influences of both bias fault and loss of effectiveness fault. Using the adaptive online updating strategies, no global knowledge about the communication topology is required and the bounds of actuator failures can be unknown. Then an algorithm is proposed to determine the control parameters of the fault-tolerant formation protocol, where the time-varying formation feasible conditions and an approach to expand the feasible formation set are given. Furthermore, the stability of the proposed algorithm is proven based on the Lyapunov-like theory. Finally, two simulation examples are given to demonstrate the effectiveness of the theoretical results. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
Veka, Steinar; Lien, Gudbrand; Westgaard, Sjur; Higgs, Helen
2012-01-01
In this paper we investigate the extent to which the price of Nordic electricity derivatives correlates with European Energy Exchange (EEX) and Intercontinental Exchange (ICE) electricity contracts. We also include their price correlation with ICE gas, Brent crude oil, coal and carbon emission contracts. Using multivariate generalized autoregressive conditional heteroskedasticity models, we find significant time-varying relationships between all of the energy commodities included in the analy...
Ali, M Sanni; Groenwold, Rolf H H; Belitser, Svetlana V; Souverein, Patrick C; Martín, Elisa; Gatto, Nicolle M; Huerta, Consuelo; Gardarsdottir, Helga; Roes, Kit C B; Hoes, Arno W; de Boer, Antonius; Klungel, Olaf H
2016-03-01
Observational studies including time-varying treatments are prone to confounding. We compared time-varying Cox regression analysis, propensity score (PS) methods, and marginal structural models (MSMs) in a study of antidepressant [selective serotonin reuptake inhibitors (SSRIs)] use and the risk of hip fracture. A cohort of patients with a first prescription for antidepressants (SSRI or tricyclic antidepressants) was extracted from the Dutch Mondriaan and Spanish Base de datos para la Investigación Farmacoepidemiológica en Atención Primaria (BIFAP) general practice databases for the period 2001-2009. The net (total) effect of SSRI versus no SSRI on the risk of hip fracture was estimated using time-varying Cox regression, stratification and covariate adjustment using the PS, and MSM. In MSM, censoring was accounted for by inverse probability of censoring weights. The crude hazard ratio (HR) of SSRI use versus no SSRI use on hip fracture was 1.75 (95%CI: 1.12, 2.72) in Mondriaan and 2.09 (1.89, 2.32) in BIFAP. After confounding adjustment using time-varying Cox regression, stratification, and covariate adjustment using the PS, HRs increased in Mondriaan [2.59 (1.63, 4.12), 2.64 (1.63, 4.25), and 2.82 (1.63, 4.25), respectively] and decreased in BIFAP [1.56 (1.40, 1.73), 1.54 (1.39, 1.71), and 1.61 (1.45, 1.78), respectively]. MSMs with stabilized weights yielded HR 2.15 (1.30, 3.55) in Mondriaan and 1.63 (1.28, 2.07) in BIFAP when accounting for censoring and 2.13 (1.32, 3.45) in Mondriaan and 1.66 (1.30, 2.12) in BIFAP without accounting for censoring. In this empirical study, differences between the different methods to control for time-dependent confounding were small. The observed differences in treatment effect estimates between the databases are likely attributable to different confounding information in the datasets, illustrating that adequate information on (time-varying) confounding is crucial to prevent bias. Copyright © 2016 John Wiley & Sons, Ltd.
LENUS (Irish Health Repository)
Muchekehu, Ruth W
2009-02-01
Steroid hormones target K+ channels as a means of regulating electrolyte and fluid transport. In this study, ion transporter targets of Estradiol (E2) were investigated in the human eccrine sweat gland cell line NCL-SG3.
Lee, Jungryun; Kim, Daesoo; Shin, Hee-Sup
2004-01-01
T-type calcium channels have been implicated as a pacemaker for brain rhythms during sleep but their contribution to behavioral states of sleep has been relatively uncertain. Here, we found that mice lacking α1G T-type Ca2+ channels showed a loss of the thalamic delta (1–4 Hz) waves and a reduction of sleep spindles (7–14 Hz), whereas slow (16 sec compared with the wild-type, whereas no difference was seen in BAs of
Akça, Haydar; Al-Zahrani, Eadah; Covachev, Valéry; Covacheva, Zlatinka
2017-07-01
From the mathematical point of view, a cellular neural network (CNN) can be characterized by an array of identical nonlinear dynamical systems called cells (neurons) that are locally interconnected. Using the semi-discretization method, in the present talk we construct a discrete-time counterpart of a neutral-type CNN with time-varying delays and impulses. Sufficient conditions for the existence of periodic solutions of the discrete-time system thus obtained are found by using the continuation theorem of coincidence degree theory.
Vachálek, Ján
2011-12-01
The paper compares the abilities of forgetting methods to track time varying parameters of two different simulated models with different types of excitation. The observed parameters in the simulations are the integral sum of the Euclidean norm, deviation of the parameter estimates from their true values and a selected band prediction error count. As supplementary information, we observe the eigenvalues of the covariance matrix. In the paper we used a modified method of Regularized Exponential Forgetting with Alternative Covariance Matrix (REFACM) along with Directional Forgetting (DF) and three standard regularized methods.
Zorilă, Tudor-Cătălin; Stylianou, Yannis; Flanagan, Sheila; Moore, Brian Cecil
2017-01-01
A model for the loudness of time-varying sounds [Glasberg and Moore (2012). J. Audio. Eng. Soc. 50, 331-342] was assessed for its ability to predict the loudness of sentences that were processed to either decrease or increase their dynamic fluctuations. In a paired-comparison task, subjects compared the loudness of unprocessed and processed sentences that had been equalized in (1) root-mean square (RMS) level; (2) the peak long-term loudness predicted by the model; (3) the mean long-term loud...
Directory of Open Access Journals (Sweden)
Chifu E. N.
2009-07-01
Full Text Available Here, we present a profound and complete analytical solution to Einstein’s gravitational field equations exterior to astrophysically real or hypothetical time varying distribu- tions of mass or pressure within regions of spherical geometry. The single arbitrary function f in our proposed exterior metric tensor and constructed field equations makes our method unique, mathematically less combersome and astrophysically satisfactory. The obtained solution of Einstein’s gravitational field equations tends out to be a gen- eralization of Newton’s gravitational scalar potential exterior to the spherical mass or pressure distribution under consideration
Directory of Open Access Journals (Sweden)
Minghui Yu
2017-01-01
Full Text Available The global exponential antisynchronization in mean square of memristive neural networks with stochastic perturbation and mixed time-varying delays is studied in this paper. Then, two kinds of novel delay-dependent and delay-independent adaptive controllers are designed. With the ability of adapting to environment changes, the proposed controllers can modify their behaviors to achieve the best performance. In particular, on the basis of the differential inclusions theory, inequality theory, and stochastic analysis techniques, several sufficient conditions are obtained to guarantee the exponential antisynchronization between the drive system and response system. Furthermore, two numerical simulation examples are provided to the validity of the derived criteria.
Callier, F. M.; Desoer, C. A.
1974-01-01
The loop transformation technique (Sandberg, 1965; Zames, 1966, Willems, 1971), and the fixed point theorem (Schwartz, 1970) are used to derive the L(superscript-p) stability for a class of multivariable nonlinear time-varying feedback systems which are open-loop unstable. The application of the fixed point theorem in L(superscript-p) shows that the nonlinear feedback system has one and only one solution for any pair of inputs in L(superscript-p), that the solutions are continuously dependent on the inputs, and that the closed loop system is L(superscript-p)-stable for any p ranging from 1 to infinity.
Directory of Open Access Journals (Sweden)
Chifu E. N.
2009-07-01
Full Text Available Here, we present a profound and complete analytical solution to Einstein's gravitational field equations exterior to astrophysically real or hypothetical time varying distributions of mass or pressure within regions of spherical geometry. The single arbitrary function $f$ in our proposed exterior metric tensor and constructed field equations makes our method unique, mathematically less combersome and astrophysically satisfactory. The obtained solution of Einstein's gravitational field equations tends out to be a generalization of Newton's gravitational scalar potential exterior to the spherical mass or pressure distribution under consideration.
Directory of Open Access Journals (Sweden)
Sirada Pinjai
2013-01-01
Full Text Available This paper is concerned with the problem of robust exponential stability for linear parameter-dependent (LPD neutral systems with mixed time-varying delays and nonlinear perturbations. Based on a new parameter-dependent Lyapunov-Krasovskii functional, Leibniz-Newton formula, decomposition technique of coefficient matrix, free-weighting matrices, Cauchy’s inequality, modified version of Jensen’s inequality, model transformation, and linear matrix inequality technique, new delay-dependent robust exponential stability criteria are established in terms of linear matrix inequalities (LMIs. Numerical examples are given to show the effectiveness and less conservativeness of the proposed methods.
Lee, Jungryun; Kim, Daesoo; Shin, Hee-Sup
2004-12-28
T-type calcium channels have been implicated as a pacemaker for brain rhythms during sleep but their contribution to behavioral states of sleep has been relatively uncertain. Here, we found that mice lacking alpha1(G) T-type Ca(2+) channels showed a loss of the thalamic delta (1-4 Hz) waves and a reduction of sleep spindles (7-14 Hz), whereas slow (sleep. Analysis of sleep disturbances, as defined by the occurrence of brief awakening (BA) episodes during NREM sleep, revealed that mutant mice exhibited a higher incidence of BAs of >16 sec compared with the wild-type, whereas no difference was seen in BAs of sleep spindles from cortically generated slow waves. These results also suggest that the alpha1(G)-subunit of T-type calcium channels plays a critical role in the genesis of thalamocortical oscillations and contributes to the modulation of sleep states and the transition between NREM sleep and wake states.
Rogers, Duane A; Ray, Steven J; Hieftje, Gary M
2010-04-01
A new time-of-flight mass spectrometer has been developed that uses an electrospray source and an inductively coupled plasma to extract molecular, atomic, and isotopic information simultaneously from a single sample. This paper will focus on characterization of the ESI channel. Sensitivities are reported for hexadecyltrimethylammonium, tetrahexylammonium, tetraoctylammonium, myoglobin, insulin, cyanocobalamin, leucine enkephalin, and alcohol dehydrogenase. Skimmer-nozzle collisionally induced dissociation is explored for adduct removal and analyte fragmentation on the ESI channel for tetraoctylammonium ion and leucine enkephalin. Long-term and short-term spray stability is also examined.
Abduljalil, Khaled; Jamei, Masoud; Rostami-Hodjegan, Amin; Johnson, Trevor N
2014-05-01
Although both POPPK and physiologically based pharmacokinetic (PBPK) models can account for age and other covariates within a paediatric population, they generally do not account for real-time growth and maturation of the individuals through the time course of drug exposure; this may be significant in prolonged neonatal studies. The major objective of this study was to introduce age progression into a paediatric PBPK model, to allow for continuous updating of anatomical, physiological and biological processes in each individual subject over time. The Simcyp paediatric PBPK model simulator system parameters were reanalysed to assess the impact of re-defining the individual over the study period. A schedule for re-defining parameters within the Simcyp paediatric simulator, for each subject, over a prolonged study period, was devised to allow seamless prediction of pharmacokinetics (PK). The model was applied to predict concentration-time data from multiday studies on sildenafil and phenytoin performed in neonates. Among PBPK system parameters, CYP3A4 abundance was one of the fastest changing covariates and a 1-h re-sampling schedule was needed for babies below age 3.5 days in order to seamlessly predict PK (age increased, reaching biweekly by 6 months of age. The PK of both sildenafil and phenytoin were predicted better at the end of a prolonged study period using the time varying vs fixed PBPK models. Paediatric PBPK models which account for time-varying system parameters during prolonged studies may provide more mechanistic PK predictions in neonates and infants.