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Sample records for distributed time-varying delays

  1. Delay-dependent exponential passivity of uncertain cellular neural networks with discrete and distributed time-varying delays.

    PubMed

    Du, Yuanhua; Zhong, Shouming; Xu, Jia; Zhou, Nan

    2015-05-01

    This paper is concerned with the delay-dependent exponential passivity analysis issue for uncertain cellular neural networks with discrete and distributed time-varying delays. By decomposing the delay interval into multiple equidistant subintervals and multiple nonuniform subintervals, a suitable augmented Lyapunov-Krasovskii functionals are constructed on these intervals. A set of novel sufficient conditions are obtained to guarantee the exponential passivity analysis issue for the considered system. Finally, two numerical examples are provided to demonstrate the effectiveness of the proposed results. PMID:25702046

  2. Almost periodic solutions for a memristor-based neural networks with leakage, time-varying and distributed delays.

    PubMed

    Jiang, Ping; Zeng, Zhigang; Chen, Jiejie

    2015-08-01

    In this paper, we study the existence and global exponential stability of almost periodic solution for memristor-based neural networks with leakage, time-varying and distributed delays. Using a new Lyapunov function method, we prove that this delayed neural network has a unique almost periodic solution, which is globally exponentially stable. Moreover, the obtained conclusion on the almost periodic solution is applied to prove the existence and stability of periodic solution (or equilibrium point) for this delayed neural network with periodic coefficients (or constant coefficients). PMID:25978771

  3. Augmented Lyapunov approach to H∞ state estimation of static neural networks with discrete and distributed time-varying delays

    NASA Astrophysics Data System (ADS)

    Syed, Ali M.; Saravanakumar, R.

    2015-05-01

    This paper deals with H∞ state estimation problem of neural networks with discrete and distributed time-varying delays. A novel delay-dependent concept of H∞ state estimation is proposed to estimate the H∞ performance and global asymptotic stability of the concerned neural networks. By constructing the Lyapunov-Krasovskii functional and using the linear matrix inequality technique, sufficient conditions for delay-dependent H∞ performances are obtained, which can be easily solved by some standard numerical algorithms. Finally, numerical examples are given to illustrate the usefulness and effectiveness of the proposed theoretical results. Project supported by the Fund from National Board of Higher Mathematics (NBHM), New Delhi (Grant No. 2/48/10/2011-R&D-II/865).

  4. Global exponential stability of impulsive complex-valued neural networks with both asynchronous time-varying and continuously distributed delays.

    PubMed

    Song, Qiankun; Yan, Huan; Zhao, Zhenjiang; Liu, Yurong

    2016-09-01

    This paper investigates the stability problem for a class of impulsive complex-valued neural networks with both asynchronous time-varying and continuously distributed delays. By employing the idea of vector Lyapunov function, M-matrix theory and inequality technique, several sufficient conditions are obtained to ensure the global exponential stability of equilibrium point. When the impulsive effects are not considered, several sufficient conditions are also given to guarantee the existence, uniqueness and global exponential stability of equilibrium point. Two examples are given to illustrate the effectiveness and lower level of conservatism of the proposed criteria in comparison with some existing results. PMID:27239891

  5. Exponential Synchronization of Coupled Stochastic Memristor-Based Neural Networks With Time-Varying Probabilistic Delay Coupling and Impulsive Delay.

    PubMed

    Bao, Haibo; Park, Ju H; Cao, Jinde

    2016-01-01

    This paper deals with the exponential synchronization of coupled stochastic memristor-based neural networks with probabilistic time-varying delay coupling and time-varying impulsive delay. There is one probabilistic transmittal delay in the delayed coupling that is translated by a Bernoulli stochastic variable satisfying a conditional probability distribution. The disturbance is described by a Wiener process. Based on Lyapunov functions, Halanay inequality, and linear matrix inequalities, sufficient conditions that depend on the probability distribution of the delay coupling and the impulsive delay were obtained. Numerical simulations are used to show the effectiveness of the theoretical results. PMID:26485723

  6. New delay dependent stability criteria for recurrent neural networks with interval time-varying delay.

    PubMed

    Yang, Qiongfen; Ren, Quanhong; Xie, Xuemei

    2014-07-01

    This paper is concerned with the delay dependent stability criteria for a class of static recurrent neural networks with interval time-varying delay. By choosing an appropriate Lyapunov-Krasovskii functional and employing a delay partitioning method, the less conservative condition is obtained. Furthermore, the LMIs-based condition depend on the lower and upper bounds of time delay. Finally, a numerical example is also designated to verify the reduced conservatism of developed criteria. PMID:24908560

  7. Synchronization of Memristor-Based Coupling Recurrent Neural Networks With Time-Varying Delays and Impulses.

    PubMed

    Zhang, Wei; Li, Chuandong; Huang, Tingwen; He, Xing

    2015-12-01

    Synchronization of an array of linearly coupled memristor-based recurrent neural networks with impulses and time-varying delays is investigated in this brief. Based on the Lyapunov function method, an extended Halanay differential inequality and a new delay impulsive differential inequality, some sufficient conditions are derived, which depend on impulsive and coupling delays to guarantee the exponential synchronization of the memristor-based recurrent neural networks. Impulses with and without delay and time-varying delay are considered for modeling the coupled neural networks simultaneously, which renders more practical significance of our current research. Finally, numerical simulations are given to verify the effectiveness of the theoretical results. PMID:26054076

  8. Stochastic stability of switched genetic regulatory networks with time-varying delays.

    PubMed

    Zhang, Wenbing; Tang, Yang; Wu, Xiaotai; Fang, Jian-An

    2014-09-01

    This paper investigates the exponential stability problem of switched stochastic genetic regulatory networks (GRNs) with time-varying delays. Two types of switched systems are studied respectively: one is the stochastic switched delayed GRNs with only stable subsystems and the other is the stochastic switched delayed GRNs with both stable and unstable subsystems. By using switching analysis techniques and the modified Halanay differential inequality, new criteria are developed for the exponential stability of switched stochastic GRNs with time-varying delays. Finally, an example is given to illustrate the main results. PMID:25265564

  9. A delay-dependent approach to robust control for neutral uncertain neural networks with mixed interval time-varying delays

    NASA Astrophysics Data System (ADS)

    Lu, Chien-Yu

    2011-04-01

    This paper considers the problem of delay-dependent global robust stabilization for discrete, distributed and neutral interval time-varying delayed neural networks described by nonlinear delay differential equations of the neutral type. The parameter uncertainties are norm bounded. The activation functions are assumed to be bounded and globally Lipschitz continuous. Using a Lyapunov functional approach and linear matrix inequality (LMI) techniques, the stability criteria for the uncertain neutral neural networks with interval time-varying delays are established in the form of LMIs, which can be readily verified using the standard numerical software. An important feature of the result reported is that all the stability conditions are dependent on the upper and lower bounds of the delays. Another feature of the results lies in that it involves fewer free weighting matrix strategy, and upper bounds of the inner product between two vectors are not introduced to reduce the conservatism of the criteria. Two illustrative examples are provided to demonstrate the effectiveness and the reduced conservatism of the proposed method.

  10. Exponential Stability for Neutral Stochastic Markov Systems With Time-Varying Delay and Its Applications.

    PubMed

    Chen, Huabin; Shi, Peng; Lim, Cheng-Chew; Hu, Peng

    2016-06-01

    In this paper, the exponential stability in p th( p > 1 )-moment for neutral stochastic Markov systems with time-varying delay is studied. The derived stability conditions comprise two forms: 1) the delay-independent stability criteria which are obtained by establishing an integral inequality and 2) the delay-dependent stability criteria which are captured by using the theory of the functional differential equations. As its applications, the obtained stability results are used to investigate the exponential stability in p th( p > 1 )-moment for the neutral stochastic neural networks with time-varying delay and Markov switching, and the globally exponential adaptive synchronization for the neutral stochastic complex dynamical systems with time-varying delay and Markov switching, respectively. On the delay-independent criteria, sufficient conditions are given in terms of M -matrix and thus are easy to check. The delay-dependent criteria are presented in the forms of the algebraic inequalities, and the least upper bound of the time-varying delay is also provided. The primary advantages of these obtained results over some recent and similar works are that the differentiability or continuity of the delay function is not required, and that the difficulty stemming from the presence of the neutral item and the Markov switching is overcome. Three numerical examples are provided to examine the effectiveness and potential of the theoretic results obtained. PMID:27187938

  11. H ∞ synchronization of the coronary artery system with input time-varying delay

    NASA Astrophysics Data System (ADS)

    Xiao-Meng, Li; Zhan-Shan, Zhao; Jing, Zhang; Lian-Kun, Sun

    2016-06-01

    This paper investigates the H ∞ synchronization of the coronary artery system with input delay and disturbance. We focus on reducing the conservatism of existing synchronization strategies. Base on the triple integral forms of the Lyapunov–Krasovskii functional (LKF), we utilize single and double integral forms of Wirtinger-based inequality to guarantee that the synchronization feedback controller has good performance against time-varying delay and external disturbance. The effectiveness of our strategy can be exhibited by simulations under the different time-varying delays and different disturbances. Project supported by the National Natural Science Foundation of China (Grant Nos. 61503280, 61403278, and 61272006).

  12. Robust state estimation for uncertain neural networks with time-varying delay.

    PubMed

    Huang, He; Feng, Gang; Cao, Jinde

    2008-08-01

    The robust state estimation problem for a class of uncertain neural networks with time-varying delay is studied in this paper. The parameter uncertainties are assumed to be norm bounded. Based on a new bounding technique, a sufficient condition is presented to guarantee the existence of the desired state estimator for the uncertain delayed neural networks. The criterion is dependent on the size of the time-varying delay and on the size of the time derivative of the time-varying delay. It is shown that the design of the robust state estimator for such neural networks can be achieved by solving a linear matrix inequality (LMI), which can be easily facilitated by using some standard numerical packages. Finally, two simulation examples are given to demonstrate the effectiveness of the developed approach. PMID:18701365

  13. Containment consensus with measurement noises and time-varying communication delays

    NASA Astrophysics Data System (ADS)

    Zhou, Feng; Wang, Zheng-Jie; Fan, Ning-Jun

    2015-02-01

    In this paper, we consider the containment consensus control problem for multi-agent systems with measurement noises and time-varying communication delays under directed networks. By using stochastic analysis tools and algebraic graph theory, we prove that the followers can converge to the convex hull spanned by the leaders in the sense of mean square if the allowed upper bound of the time-varying delays satisfies a certain sufficient condition. Moreover, the time-varying delays are asymmetric for each follower agent, and the time-delay-dependent consensus condition is derived. Finally, numerical simulations are provided to illustrate the effectiveness of the obtained theoretical results. Project supported by the National Natural Science Foundation of China (Grant No. 11102019), the Aeronautical Science Foundation of China (Grant No. 2013ZC72006), and the Research Foundation of Beijing Institute of Technology, China.

  14. Passivity and Passification of Memristor-Based Recurrent Neural Networks With Additive Time-Varying Delays.

    PubMed

    Rakkiyappan, Rajan; Chandrasekar, Arunachalam; Cao, Jinde

    2015-09-01

    This paper presents a new design scheme for the passivity and passification of a class of memristor-based recurrent neural networks (MRNNs) with additive time-varying delays. The predictable assumptions on the boundedness and Lipschitz continuity of activation functions are formulated. The systems considered here are based on a different time-delay model suggested recently, which includes additive time-varying delay components in the state. The connection between the time-varying delay and its upper bound is considered when estimating the upper bound of the derivative of Lyapunov functional. It is recognized that the passivity condition can be expressed in a linear matrix inequality (LMI) format and by using characteristic function method. For state feedback passification, it is verified that it is apathetic to use immediate or delayed state feedback. By constructing a Lyapunov-Krasovskii functional and employing Jensen's inequality and reciprocal convex combination technique together with a tighter estimation of the upper bound of the cross-product terms derived from the derivatives of the Lyapunov functional, less conventional delay-dependent passivity criteria are established in terms of LMIs. Moreover, second-order reciprocally convex approach is employed for deriving the upper bound for terms with inverses of squared convex parameters. The model based on the memristor with additive time-varying delays widens the application scope for the design of neural networks. Finally, pertinent examples are given to show the advantages of the derived passivity criteria and the significant improvement of the theoretical approaches. PMID:25415991

  15. An observer for a velocity-sensorless VTOL aircraft with time-varying measurement delay

    NASA Astrophysics Data System (ADS)

    He, Qing; Liu, Jinkun

    2016-02-01

    This paper presents a kind of state observer for a velocity-sensorless vertical take-off and landing (VTOL) aircraft with bounded time-varying delay in its measurement outputs. The proposed observer predicts current state variables based on the delayed outputs, and the estimated state variables can be considered as the actual state variables for feedback control scheme design. Since the delay is time-varying, compared to the constant delay case, different analysis theory must be employed. Under the assumption that the delays are identical for different outputs and bounded input, the asymptotic convergence property of the estimation error based on Lyapunov-Razumikhin theorem is proved. A relative large time delay for the VTOL aircraft in the outputs has been tested in the numerical simulation, and the simulation results show the effectiveness of the proposed observer.

  16. New Stabilization for Dynamical System with Two Additive Time-Varying Delays

    PubMed Central

    Yang, Fan; Chen, Xiaozhou

    2014-01-01

    This paper provides a new delay-dependent stabilization criterion for systems with two additive time-varying delays. The novel functional is constructed, a tighter upper bound of the derivative of the Lyapunov functional is obtained. These results have advantages over some existing ones because the combination of the delay decomposition technique and the reciprocally convex approach. Two examples are provided to demonstrate the less conservatism and effectiveness of the results in this paper. PMID:24701159

  17. Generalized Projective Synchronization between Two Complex Networks with Time-Varying Coupling Delay

    NASA Astrophysics Data System (ADS)

    Sun, Mei; Zeng, Chang-Yan; Tian, Li-Xin

    2009-01-01

    Generalized projective synchronization (GPS) between two complex networks with time-varying coupling delay is investigated. Based on the Lyapunov stability theory, a nonlinear controller and adaptive updated laws are designed. Feasibility of the proposed scheme is proven in theory. Moreover, two numerical examples are presented, using the energy resource system and Lü's system [Physica A 382 (2007) 672] as the nodes of the networks. GPS between two energy resource complex networks with time-varying coupling delay is achieved. This study can widen the application range of the generalized synchronization methods and will be instructive for the demand-supply of energy resource in some regions of China.

  18. Improved delay-dependent stability criteria for neutral-type systems with time-varying delays: a delayed decomposition approach

    NASA Astrophysics Data System (ADS)

    Liu, Pin-Lin

    2014-08-01

    This paper discusses the neutral system with time-varying delay. Firstly, by developing a delayed decomposition approach and introducing integral inequality approach, the information of the delayed plant states can be taken into full consideration, and new delay-dependent sufficient stability criteria are obtained in terms of linear matrix inequalities (LMIs). Then, based on the Lyapunov method, delay-dependent stability criteria are devised by taking the relationship between the terms in the Leibniz-Newton formula into account. The criteria are derived in terms of LMIs, which can be easily solved by using various convex optimization algorithms. Three illustrative numerical examples are given to show the less conservatism of our obtained results and the effectiveness of the proposed method.

  19. Stability analysis of switched stochastic neural networks with time-varying delays.

    PubMed

    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. PMID:24365535

  20. Nonlinear adaptive control for teleoperation systems with symmetrical and unsymmetrical time-varying delay

    NASA Astrophysics Data System (ADS)

    Islam, S.; Liu, P. X.; El Saddik, A.

    2015-12-01

    The stability and trajectory tracking control problem of passive teleoperation systems with the presence of the symmetrical and unsymmetrical time-varying communication delay is addressed in this paper. The proposed teleoperator is designed by coupling local and remote sites by delaying position signals of the master and slave manipulator. The design also comprises local proportional and derivative signals with nonlinear adaptive terms to cope with parametric uncertainty associated with the master and slave dynamics. The Lyapunov-Krasovskii function is employed to establish stability conditions for the closed-loop teleoperators under both symmetrical and unsymmetrical time-varying communication delay. These delay-dependent conditions allow the designer to estimate the control gains a priori in order to achieve asymptotic property of the position, velocity and synchronisation errors of the master and slave systems. Finally, simulation results along with comparative studies are presented to illustrate the effectiveness of the proposed method.

  1. Image encryption using chaotic coupled map lattices with time-varying delays

    NASA Astrophysics Data System (ADS)

    Tang, Yang; Wang, Zidong; Fang, Jian-an

    2010-09-01

    In this paper, a novel image encryption scheme using coupled map lattices (CML) with time delay is proposed. By employing discretized tent map to shuffle the positions of image pixels and then using delayed coupled map lattices (DCML) to confuse the relationship between the plain-image and the cipher-image, image encryption algorithms with permutation-diffusion structure are introduced in detail. In the process of generating keystream, the time-varying delay is also embedded in our proposed scheme to enhance the security. Theoretical analysis and computer experiments confirm that the new algorithm possesses high security for practical image encryption.

  2. Global exponential stability for switched memristive neural networks with time-varying delays.

    PubMed

    Xin, Youming; Li, Yuxia; Cheng, Zunshui; Huang, Xia

    2016-08-01

    This paper considers the problem of exponential stability for switched memristive neural networks (MNNs) with time-varying delays. Different from most of the existing papers, we model a memristor as a continuous system, and view switched MNNs as switched neural networks with uncertain time-varying parameters. Based on average dwell time technique, mode-dependent average dwell time technique and multiple Lyapunov-Krasovskii functional approach, two conditions are derived to design the switching signal and guarantee the exponential stability of the considered neural networks, which are delay-dependent and formulated by linear matrix inequalities (LMIs). Finally, the effectiveness of the theoretical results is demonstrated by two numerical examples. PMID:27164266

  3. Robust stabilisation of time-varying delay systems with probabilistic uncertainties

    NASA Astrophysics Data System (ADS)

    Jiang, Ning; Xiong, Junlin; Lam, James

    2016-09-01

    For robust stabilisation of time-varying delay systems, only sufficient conditions are available to date. A natural question is as follows: if the existing sufficient conditions are not satisfied, and hence no controllers can be found, what can one do to improve the stability performance of time-varying delay systems? This question is addressed in this paper when there is a probabilistic structure on the parameter uncertainty set. A randomised algorithm is proposed to design a state-feedback controller, which stabilises the system over the uncertainty domain in a probabilistic sense. The capability of the designed controller is quantified by the probability of stability of the resulting closed-loop system. The accuracy of the solution obtained from the randomised algorithm is also analysed. Finally, numerical examples are used to illustrate the effectiveness and advantages of the developed controller design approach.

  4. Global robust dissipativity of interval recurrent neural networks with time-varying delay and discontinuous activations.

    PubMed

    Duan, Lian; Huang, Lihong; Guo, Zhenyuan

    2016-07-01

    In this paper, the problems of robust dissipativity and robust exponential dissipativity are discussed for a class of recurrent neural networks with time-varying delay and discontinuous activations. We extend an invariance principle for the study of the dissipativity problem of delay systems to the discontinuous case. Based on the developed theory, some novel criteria for checking the global robust dissipativity and global robust exponential dissipativity of the addressed neural network model are established by constructing appropriate Lyapunov functionals and employing the theory of Filippov systems and matrix inequality techniques. The effectiveness of the theoretical results is shown by two examples with numerical simulations. PMID:27475061

  5. Global robust dissipativity of interval recurrent neural networks with time-varying delay and discontinuous activations

    NASA Astrophysics Data System (ADS)

    Duan, Lian; Huang, Lihong; Guo, Zhenyuan

    2016-07-01

    In this paper, the problems of robust dissipativity and robust exponential dissipativity are discussed for a class of recurrent neural networks with time-varying delay and discontinuous activations. We extend an invariance principle for the study of the dissipativity problem of delay systems to the discontinuous case. Based on the developed theory, some novel criteria for checking the global robust dissipativity and global robust exponential dissipativity of the addressed neural network model are established by constructing appropriate Lyapunov functionals and employing the theory of Filippov systems and matrix inequality techniques. The effectiveness of the theoretical results is shown by two examples with numerical simulations.

  6. Global asymptotic stability analysis for neutral stochastic neural networks with time-varying delays

    NASA Astrophysics Data System (ADS)

    Su, Weiwei; Chen, Yiming

    2009-04-01

    In this paper, the global asymptotic stability is investigated for a class of neutral stochastic neural networks with time-varying delays and norm-bounded uncertainties. Based on Lyapunov stability theory and stochastic analysis approaches, delay-dependent criteria are derived to ensure the global, robust, asymptotic stability of the addressed system in the mean square for all admissible parameter uncertainties. The criteria can be checked easily by the LMI Control Toolbox in Matlab. A numerical example is given to illustrate the feasibility and effectiveness of the results.

  7. Adaptive control for a class of MIMO nonlinear time delay systems against time varying actuator failures.

    PubMed

    Hashemi, Mahnaz; Ghaisari, Jafar; Askari, Javad

    2015-07-01

    This paper investigates an adaptive controller for a class of Multi Input Multi Output (MIMO) nonlinear systems with unknown parameters, bounded time delays and in the presence of unknown time varying actuator failures. The type of considered actuator failure is one in which some inputs may be stuck at some time varying values where the values, times and patterns of the failures are unknown. The proposed approach is constructed based on a backstepping design method. The boundedness of all the closed-loop signals is guaranteed and the tracking errors are proved to converge to a small neighborhood of the origin. The proposed approach is employed for a double inverted pendulums benchmark and a chemical reactor system. The simulation results show the effectiveness of the proposed method. PMID:25792517

  8. Improved stability conditions for uncertain neutral-type systems with time-varying delays

    NASA Astrophysics Data System (ADS)

    Ren, Yu; Feng, Zhiguang; Sun, Guanghui

    2016-06-01

    This paper investigates the robust stability problem for a class of uncertain neutral-type delayed systems. The systems under consideration contain parameter uncertainties and time-varying delays. We aim at designing less conservative robust stability criteria for such systems. A new second-order reciprocally convex inequality is first proposed in order to deal with double integral terms. Then, by constructing a new Lyapunov- Krasovskii functional and employing the improved Wirtinger-based integral inequality and the reciprocally convex combination approaches, novel stability criteria are obtained. Moreover, the stability conditions for standard time-delay system are obtained as by-product results. Comparisons in three numerical examples illustrate the effectiveness of our results.

  9. Minimum-energy control for time-varying systems with multiple state and input delays

    NASA Astrophysics Data System (ADS)

    Liu, Hai-Lin; Tang, Gong-You; Yang, Xue

    2016-09-01

    This paper considers the minimum-energy control problem for a class of time-varying systems with multiple state and input delays. First, a state transform matrix is presented. By using the transform matrix, a system with multiple state and input delays is converted to a formal equivalent one without delay. Then, the optimal problem of the novel system is solved by using the maximum principle. Analytical expressions of the optimal control law and optimal performance are given by two formulas with respect to the state transform matrix. At last, an algorithm is given to solve the analytical expression of the state transform matrix. Simulation results show that the design algorithm is efficient and easy to implement.

  10. Attitude tracking control for spacecraft formation with time-varying delays and switching topology

    NASA Astrophysics Data System (ADS)

    Yang, Hongjiu; You, Xiu; Hua, Changchun

    2016-09-01

    This paper investigates attitude dynamic tracking control for spacecraft formation in the presence of unmeasurable velocity information with time-varying delays and switching topology. Based on an extended state observer, a nonlinear attitude tracking control approach is developed for spacecraft attitude model formulated by Euler-Lagrangian equations. The attitude tracking controller allows for external disturbances and absence of angular velocity information. Both auto-stable region techniques and a Lyapunov function approach are developed to prove ultimately bounded tracking. Simulation results demonstrate effectiveness of the nonlinear control techniques proposed in this paper.

  11. Adaptive Synchronization of Memristor-Based Neural Networks with Time-Varying Delays.

    PubMed

    Wang, Leimin; Shen, Yi; Yin, Quan; Zhang, Guodong

    2015-09-01

    In this paper, adaptive synchronization of memristor-based neural networks (MNNs) with time-varying delays is investigated. The dynamical analysis here employs results from the theory of differential equations with discontinuous right-hand sides as introduced by Filippov. Sufficient conditions for the global synchronization of MNNs are established with a general adaptive controller. The update gain of the controller can be adjusted to control the synchronization speed. The obtained results complement and improve the previously known results. Finally, numerical simulations are carried out to demonstrate the effectiveness of the obtained results. PMID:25389244

  12. Passivity of switched recurrent neural networks with time-varying delays.

    PubMed

    Lian, Jie; Wang, Jun

    2015-02-01

    This paper is concerned with the passivity analysis for switched neural networks subject to stochastic disturbances and time-varying delays. First, using the multiple Lyapunov functions method, a state-dependent switching law is designed to present a stochastic passivity condition. Second, a hysteresis switching law involving both the current state and the previous value of the switching signal are presented to avoid chattering resulted from the state-dependent switching. Third, based on the average dwell-time approach, a class of switching signals is determined to guarantee the switched neural network stochastically passive. Finally, three numerical examples are provided to illustrate the characteristics of three proposed switching laws. PMID:25576577

  13. Finite-time boundedness and stabilization of uncertain switched neural networks with time-varying delay.

    PubMed

    Wu, Yuanyuan; Cao, Jinde; Alofi, Abdulaziz; Al-Mazrooei, Abdullah; Elaiw, Ahmed

    2015-09-01

    This paper deals with the finite-time boundedness and stabilization problem for a class of switched neural networks with time-varying delay and parametric uncertainties. Based on Lyapunov-like function method and average dwell time technique, some sufficient conditions are derived to guarantee the finite-time boundedness of considered uncertain switched neural networks. Furthermore, the state feedback controller is designed to solve the finite-time stabilization problem. Moreover, the proposed sufficient conditions can be simplified into the form of linear matrix equalities for conveniently using Matlab LMI toolbox. Finally, two numerical examples are given to show the effectiveness of the main results. PMID:26103615

  14. Adaptive Q-S (lag, anticipated, and complete) time-varying synchronization and parameters identification of uncertain delayed neural networks

    NASA Astrophysics Data System (ADS)

    Yu, Wenwu; Cao, Jinde

    2006-06-01

    In this paper, a new type of generalized Q-S (lag, anticipated, and complete) time-varying synchronization is defined. Adaptive Q-S (lag, anticipated, and complete) time-varying synchronization and parameters identification of uncertain delayed neural networks have been considered, where the delays are multiple time-varying delays. A novel control method is given by using the Lyapunov functional method. With this new and effective method, parameters identification and Q-S (lag, anticipated, and complete) time-varying synchronization can be achieved simultaneously. Simulation results are given to justify the theoretical analysis in this paper.

  15. H∞ control problem for Hopfield neural networks with interval time-varying delay

    NASA Astrophysics Data System (ADS)

    Emharuethai, Chanikan

    2016-02-01

    In this paper, we consider H∞ control problem for a class Hopfield neural networks with interval time-varying delay. The time delay is a continuous function belonging to a given interval, but not necessariry differentiable. The stabilizing controllers to be designed must satisfy some exponential stability constraints on the closed-loop poles. Based on the construction of improved Lyapunov-Krasovskii functionals combined with Newton-Leibniz formula. H∞ controller is designed via memoryless state feedback control and new sufficient conditions for the existence of the H∞ state-feedback for the system are given in terms of linear matrix inequalities (LMIs). Numerical examples are given to illustrate the effectiveness of the obtained result.

  16. Containment Control for First-Order Multi-Agent Systems with Time-Varying Delays and Uncertain Topologies

    NASA Astrophysics Data System (ADS)

    Wang, Fu-Yong; Yang, Hong-Yong; Zhang, Shu-Ning; Han, Fu-Jun

    2016-08-01

    Containment control of first-order multi-agent systems with uncertain topologies and communication time-delays is studied. Suppose system topologies are dynamically changed, a containment control algorithm with time-varying delays is presented. The stability of the control algorithm is studied under the assumption that communication topologies are jointly-connected, and constraint condition of distributed containment control for delayed multi-agent systems is derived with the aid of Lyapunov-Krasovskii function. Simulation results are provided to prove the correctness and effectiveness of the conclusion. Supported by the National Natural Science Foundation of China under Grant Nos. 61273152, 61304052, 51407088, the Science Foundation of Education Office of Shandong Province of China under Grant Nos. ZR2011FM07, BS2015DX018

  17. Delay-dependent exponential stability for uncertain neutral stochastic neural networks with interval time-varying delay

    NASA Astrophysics Data System (ADS)

    Chen, Huabin; Zhao, Yang

    2015-10-01

    This paper is mainly concerned with the problem for the robustly exponential stability in mean square moment of uncertain neutral stochastic neural networks with interval time-varying delay. With an appropriate augmented Lyapunov-Krasovskii functional (LKF) formulated, the convex combination method is utilised to estimate the derivative of the LKF. Some new delay-dependent exponential stability criteria for such systems are obtained in terms of linear matrix inequalities, which involve fewer matrix variables and have less conservatism. Finally, two illustrative numerical examples are given to show the effectiveness of our obtained results.

  18. L2-Stable Bilateral Control System with Time-Varying Communication Delay

    NASA Astrophysics Data System (ADS)

    Yashiro, Daisuke; Natori, Kenji; Ohnishi, Kouhei

    Passivity theory is a very useful tool for the stability analysis of bilateral teleoperation with communication delay. Many researchers use passivity-based stabilization method such as those based on scattering theory or wave variables. However, passivity-based stabilization is too conservative for the design of a high-performance teleoperation system. The term “high-performance” implies that people who operate this system can experience a highly accurate reaction force from environments. In this study, we analyze the L2-stability of some bilateral control systems with time-varying communication delay by using the small-gain theorem. The small-gain theorem is known to be a stability condition for multi-input multi-output feedback systems. Additionally, a novel control structure for the bilateral control system with communication delay is proposed. The bilateral control system with the proposed structure satisfies the L2-stability condition of the small-gain theorem. The experimental results show the utility of the proposed control structure.

  19. Finite-time synchronization for memristor-based neural networks with time-varying delays.

    PubMed

    Abdurahman, Abdujelil; Jiang, Haijun; Teng, Zhidong

    2015-09-01

    Memristive network exhibits state-dependent switching behaviors due to the physical properties of memristor, which is an ideal tool to mimic the functionalities of the human brain. In this paper, finite-time synchronization is considered for a class of memristor-based neural networks with time-varying delays. Based on the theory of differential equations with discontinuous right-hand side, several new sufficient conditions ensuring the finite-time synchronization of memristor-based chaotic neural networks are obtained by using analysis technique, finite time stability theorem and adding a suitable feedback controller. Besides, the upper bounds of the settling time of synchronization are estimated. Finally, a numerical example is given to show the effectiveness and feasibility of the obtained results. PMID:26024807

  20. New passivity criteria for memristive uncertain neural networks with leakage and time-varying delays.

    PubMed

    Xiao, Jianying; Zhong, Shouming; Li, Yongtao

    2015-11-01

    In this paper, the problem of passivity analysis is studied for memristor-based uncertain neural networks with leakage and time-varying delays. By combining differential inclusions with set-valued maps, the system of memristive neural networks is changed into the conventional one. By adding a triple quadratic integral and relaxing the requirement for the positive definiteness of some matrices, a proper Lyapunov-Krasovskii functional is constructed. Based on the establishment of the novel Lyapunov-Krasovskii functional, the new passivity criteria are derived by mainly applying Wirtinger-based double integral inequality, S-procedure and so on. Moreover, the conservatism of passivity conditions can be reduced. Finally, four numerical examples are given to show the effectiveness and less conservatism of the proposed criteria. PMID:26434415

  1. Robust Reliable Control for Neutral-Type Nonlinear Systems with Time-Varying Delays

    NASA Astrophysics Data System (ADS)

    Mathiyalagan, K.; Sakthivel, R.; Park, Ju. H.

    2014-10-01

    The problem of robust reliable stabilization against actuator failures for a class of uncertain nonlinear neutral systems with time-varying delays is considered. Based on a new Lyapunov-Krasovskii functional, by employing linear matrix inequality technique and free weighting matrix approach, we derived a set of sufficient conditions for the existence of a reliable controller. The derived controller is applied for the robust stabilization of the nonlinear neutral system in the presence of known actuator failure matrix and uncertainties. Further, the results are extended to study the stabilization of neutral systems with unknown actuator failure matrix. The failure of actuators are considered by variables, which are varying in a given interval. The developed theoretical results are established in the form of linear matrix inequalities, which can be easily solved via standard numerical software. Finally, two numerical examples are presented to demonstrate the validity and less conservatism of the obtained results.

  2. Robust Stability of Scaled-Four-Channel Teleoperation with Internet Time-Varying Delays.

    PubMed

    Delgado, Emma; Barreiro, Antonio; Falcón, Pablo; Díaz-Cacho, Miguel

    2016-01-01

    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. PMID:27128914

  3. Robust Stability of Scaled-Four-Channel Teleoperation with Internet Time-Varying Delays

    PubMed Central

    Delgado, Emma; Barreiro, Antonio; Falcón, Pablo; Díaz-Cacho, Miguel

    2016-01-01

    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. PMID:27128914

  4. Delay-dependent passivity criteria for uncertain switched neural networks of neutral type with interval time-varying delay

    NASA Astrophysics Data System (ADS)

    Nagamani, G.; Balasubramaniam, P.

    2012-04-01

    This paper is concerned with the robust passivity analysis of uncertain switched neural networks of neutral type with interval time-varying delay. We first discuss the passivity conditions for the addressed model with norm bounded uncertainties and then extend this result to the case of interval uncertainties. For the neural networks under study, a generalized activation function is considered, where the traditional assumptions on the boundedness, monotonicity and differentiability of the activation functions are removed. Constructing a new Lyapunov-Krasovskii functional with triple integral terms and using a minimal number of free-weighting matrices, some passivity criteria are proposed in terms of linear matrix inequalities, which are dependent on the size of the time delay. Finally, some numerical examples are given to illustrate the effectiveness and merits of the developed techniques.

  5. Bilateral Teleoperation under Time-Varying Communication Time Delay Considering Contact with Environment

    NASA Astrophysics Data System (ADS)

    Iiyama, Noriko; Natori, Kenji; Ohnishi, Kouhei

    With recent popularization of the Internet, bilateral control systems which are robust to fluctuant and unpredictable time delay are desirable. In such a situation, communication disturbance observer (CDOB) has been proposed as a control method for fluctuant and unpredictable time delay in bilateral teleoperation. It compensates time delay using disturbance observer by considering the effect of communication delay on the system as acceleration dimensional disturbance. Since this method cannot separate network disturbance from contact force exerted on a slave, force response of the slave transmitted to the master side is not precise. This paper presents a method for separating network disturbance from the contact force exerted on the slave. By producing the compensation value using separated network disturbance, the force response value of the slave is transmitted to the master side more precisely. The validity of the proposed method is verified by experimental results.

  6. Finite-time stability for discrete-time system with time-varying delay and nonlinear perturbations.

    PubMed

    Kang, Wei; Zhong, Shouming; Shi, Kaibo; Cheng, Jun

    2016-01-01

    In this paper, the problem of finite-time stability for discrete-time system with time-varying delay and nonlinear perturbations is investigated. By constructing a novel Lyapunov-Krasovskii functional and employing a new summation inequality named discrete Wirtinger-based inequality, reciprocally convex approach and zero equality, the improved finite-time stability criteria are derived to guarantee that the state of the system with time-varying delay does not exceed a given threshold when fixed time interval. Furthermore, the obtained conditions are formulated in forms of linear matrix inequalities which can be solved by using some standard numerical packages. Finally, three numerical examples are given to show the effectiveness and less conservatism of the proposed method. PMID:26619938

  7. DDI-based finite-time stability analysis for nonlinear switched systems with time-varying delays

    NASA Astrophysics Data System (ADS)

    Xue, Wenping; Li, Kangji; Liu, Guohai

    2016-09-01

    This paper investigates the finite-time stability (FTS) analysis problem for switched systems with both nonlinear perturbation and time-varying delays. For the system to be finite-time stable, a sufficient condition is proposed based on some delay differential inequalities (DDIs), rather than the Lyapunov-like functions which are commonly used in the FTS analysis of switched systems. Compared with the Lyapunov-like function method, the FTS conditions based on the DDI method are easier for checking and do not require FTS of each subsystem. Two examples are given to illustrate the effectiveness of the developed theory.

  8. Robust synchronization analysis in nonlinear stochastic cellular networks with time-varying delays, intracellular perturbations and intercellular noise.

    PubMed

    Chen, Po-Wei; Chen, Bor-Sen

    2011-08-01

    Naturally, a cellular network consisted of a large amount of interacting cells is complex. These cells have to be synchronized in order to emerge their phenomena for some biological purposes. However, the inherently stochastic intra and intercellular interactions are noisy and delayed from biochemical processes. In this study, a robust synchronization scheme is proposed for a nonlinear stochastic time-delay coupled cellular network (TdCCN) in spite of the time-varying process delay and intracellular parameter perturbations. Furthermore, a nonlinear stochastic noise filtering ability is also investigated for this synchronized TdCCN against stochastic intercellular and environmental disturbances. Since it is very difficult to solve a robust synchronization problem with the Hamilton-Jacobi inequality (HJI) matrix, a linear matrix inequality (LMI) is employed to solve this problem via the help of a global linearization method. Through this robust synchronization analysis, we can gain a more systemic insight into not only the robust synchronizability but also the noise filtering ability of TdCCN under time-varying process delays, intracellular perturbations and intercellular disturbances. The measures of robustness and noise filtering ability of a synchronized TdCCN have potential application to the designs of neuron transmitters, on-time mass production of biochemical molecules, and synthetic biology. Finally, a benchmark of robust synchronization design in Escherichia coli repressilators is given to confirm the effectiveness of the proposed methods. PMID:21624379

  9. Delay-dependent stability and stabilization criteria for T-S fuzzy singular systems with interval time-varying delay by improved delay partitioning approach.

    PubMed

    Sun, Chao; Wang, Fuli; He, Xiqin

    2016-01-01

    This paper deals with the stability analysis and fuzzy stabilizing controller design for a class of Takagi-Sugeno fuzzy singular systems with interval time-varying delay and linear fractional uncertainties. By decomposing the delay interval into two unequal subintervals and seeking a appropriate ρ, a new Lyapunov-Krasovskii functional is constructed to develop the improved delay-dependent stability criteria, which ensures the considered system to be regular, impulse-free and stable. Furthermore, the desired fuzzy controller gains are also presented by solving a set of strict linear matrix inequalities. Compared with some existing results, the obtained ones give the result with less conservatism. Finally, some examples are given to show the improvement and the effectiveness of the proposed method. PMID:27066363

  10. Distribution Driven Extraction and Tracking of Features for Time-varying Data Analysis.

    PubMed

    Dutta, Soumya; Shen, Han-Wei

    2016-01-01

    Effective analysis of features in time-varying data is essential in numerous scientific applications. Feature extraction and tracking are two important tasks scientists rely upon to get insights about the dynamic nature of the large scale time-varying data. However, often the complexity of the scientific phenomena only allows scientists to vaguely define their feature of interest. Furthermore, such features can have varying motion patterns and dynamic evolution over time. As a result, automatic extraction and tracking of features becomes a non-trivial task. In this work, we investigate these issues and propose a distribution driven approach which allows us to construct novel algorithms for reliable feature extraction and tracking with high confidence in the absence of accurate feature definition. We exploit two key properties of an object, motion and similarity to the target feature, and fuse the information gained from them to generate a robust feature-aware classification field at every time step. Tracking of features is done using such classified fields which enhances the accuracy and robustness of the proposed algorithm. The efficacy of our method is demonstrated by successfully applying it on several scientific data sets containing a wide range of dynamic time-varying features. PMID:26529731

  11. State estimation for neural neutral-type networks with mixed time-varying delays and Markovian jumping parameters

    NASA Astrophysics Data System (ADS)

    Lakshmanan, S.; Ju, H. Park; Y. Jung, H.; Balasubramaniam, P.

    2012-10-01

    This paper is concerned with a delay-dependent state estimator for neutral-type neural networks with mixed time-varying delays and Markovian jumping parameters. The addressed neural networks have a finite number of modes, and the modes may jump from one to another according to a Markov process. By construction of a suitable Lyapunov—Krasovskii functional, a delay-dependent condition is developed to estimate the neuron states through available output measurements such that the estimation error system is globally asymptotically stable in a mean square. The criterion is formulated in terms of a set of linear matrix inequalities (LMIs), which can be checked efficiently by use of some standard numerical packages.

  12. Delay Analysis of Max-Weight Queue Algorithm for Time-Varying Wireless Ad hoc Networks—Control Theoretical Approach

    NASA Astrophysics Data System (ADS)

    Chen, Junting; Lau, Vincent K. N.

    2013-01-01

    Max weighted queue (MWQ) control policy is a widely used cross-layer control policy that achieves queue stability and a reasonable delay performance. In most of the existing literature, it is assumed that optimal MWQ policy can be obtained instantaneously at every time slot. However, this assumption may be unrealistic in time varying wireless systems, especially when there is no closed-form MWQ solution and iterative algorithms have to be applied to obtain the optimal solution. This paper investigates the convergence behavior and the queue delay performance of the conventional MWQ iterations in which the channel state information (CSI) and queue state information (QSI) are changing in a similar timescale as the algorithm iterations. Our results are established by studying the stochastic stability of an equivalent virtual stochastic dynamic system (VSDS), and an extended Foster-Lyapunov criteria is applied for the stability analysis. We derive a closed form delay bound of the wireless network in terms of the CSI fading rate and the sensitivity of MWQ policy over CSI and QSI. Based on the equivalent VSDS, we propose a novel MWQ iterative algorithm with compensation to improve the tracking performance. We demonstrate that under some mild conditions, the proposed modified MWQ algorithm converges to the optimal MWQ control despite the time-varying CSI and QSI.

  13. Global exponential stability of complex-valued neural networks with both time-varying delays and impulsive effects.

    PubMed

    Song, Qiankun; Yan, Huan; Zhao, Zhenjiang; Liu, Yurong

    2016-07-01

    In this paper, the global exponential stability of complex-valued neural networks with both time-varying delays and impulsive effects is discussed. By employing Lyapunov functional method and using matrix inequality technique, several sufficient conditions in complex-valued linear matrix inequality form are obtained to ensure the existence, uniqueness and global exponential stability of equilibrium point for the considered neural networks. Moreover, the exponential convergence rate index is estimated, which depends on the system parameters. The proposed stability results are less conservative than some recently known ones in the literatures, which is demonstrated via two examples with simulations. PMID:27136664

  14. Exponential Stabilization of Memristor-based Chaotic Neural Networks with Time-Varying Delays via Intermittent Control.

    PubMed

    Zhang, Guodong; Shen, Yi

    2015-07-01

    This paper is concerned with the global exponential stabilization of memristor-based chaotic neural networks with both time-varying delays and general activation functions. Here, we adopt nonsmooth analysis and control theory to handle memristor-based chaotic neural networks with discontinuous right-hand side. In particular, several new sufficient conditions ensuring exponential stabilization of memristor-based chaotic neural networks are obtained via periodically intermittent control. In addition, the proposed results here are easy to verify and they also extend the earlier publications. Finally, numerical simulations illustrate the effectiveness of the obtained results. PMID:25148672

  15. New results on anti-synchronization of switched neural networks with time-varying delays and lag signals.

    PubMed

    Cao, Yuting; Wen, Shiping; Chen, Michael Z Q; Huang, Tingwen; Zeng, Zhigang

    2016-09-01

    This paper investigates the problem of global exponential anti-synchronization of a class of switched neural networks with time-varying delays and lag signals. Considering the packed circuits, the controller is dependent on the output of the system as the inner states are very hard to measure. Therefore, it is necessary to investigate the controller based on the output of the neuron cell. Through theoretical analysis, it is obvious that the obtained ones improve and generalize the results derived in the previous literature. To illustrate the effectiveness, a simulation example with applications in image encryptions is also presented in the paper. PMID:27295505

  16. Time Varying Apparent Volume of Distribution and Drug Half-Lives Following Intravenous Bolus Injections

    PubMed Central

    Wesolowski, Carl A.; Wesolowski, Michal J.; Babyn, Paul S.

    2016-01-01

    We present a model that generalizes the apparent volume of distribution and half-life as functions of time following intravenous bolus injection. This generalized model defines a time varying apparent volume of drug distribution. The half-lives of drug remaining in the body vary in time and become longer as time elapses, eventually converging to the terminal half-life. Two example fit models were substituted into the general model: biexponential models from the least relative concentration error, and gamma variate models using adaptive regularization for least relative error of clearance. Using adult population parameters from 41 studies of the renal glomerular filtration marker 169Yb-DTPA, simulations of extracellular fluid volumes of 5, 10, 15 and 20 litres and plasma clearances of 40 and 100 ml/min were obtained. Of these models, the adaptively obtained gamma variate models had longer times to 95% of terminal volume and longer half-lives. PMID:27403663

  17. Further improved stability criteria for uncertain T-S fuzzy systems with time-varying delay by (m,N)-delay-partitioning approach.

    PubMed

    Yang, Jun; Luo, Wen-Pin; Wang, Yong-Hu; Cheng, Jun

    2015-11-01

    This paper mainly focuses on the robust stability criteria for uncertain T-S fuzzy systems with time-varying delay by (m,N)-delay-partitioning approach. A modified augmented LKF is established by partitioning the delay in all integral terms. Via taking into account of (i) the relationship between each subinterval and time-varying delay and (ii) the independent upper bounds of the delay derivative in the various delay intervals, some new results on tighter bounding inequalities such as Peng-Park׳s integral inequality and Free-Matrix-based integral inequality are introduced to effectively reduce the enlargement in bounding the derivative of LKF as much as possible, therefore, significant less conservative results can be expected in terms of es and LMIs, which can be solved efficiently with the Matlab LMI toolbox. Furthermore, it is worth mentioning that, when the delay-partitioning number m is fixed, the conservatism is gradually reduced with the increase of another delay-partitioning number N, but without increasing any computing burden. Finally, two numerical examples are included to show that the proposed method is less conservative than existing ones. PMID:26365365

  18. Input-output method to fault detection for discrete-time fuzzy networked systems with time-varying delay and multiple packet losses

    NASA Astrophysics Data System (ADS)

    Wang, Shenquan; Feng, Jian; Jiang, Yulian

    2016-05-01

    The fault detection (FD) problem for discrete-time fuzzy networked systems with time-varying delay and multiple packet losses is investigated in this paper. The communication links between the plant and the FD filter (FDF) are assumed to be imperfect, and the missing probability is governed by an individual random variable satisfying a certain probabilistic distribution over the interval [0 1]. The discrete-time delayed fuzzy networked system is first transformed into the form of interconnect ion of two subsystems by applying an input-output method and a two-term approximation approach, which are employed to approximate the time-varying delay. Our attention is focused on the design of fuzzy FDF (FFDF) such that, for all data missing conditions, the overall FD dynamics are input-output stable in mean square and preserves a guaranteed performance. Sufficient conditions are first established via H∞ performance analysis for the existence of the desired FFDF; meanwhile, the corresponding solvability conditions for the desired FFDF gains are characterised in terms of the feasibility of a convex optimisation problem. Moreover, we show that the obtained criteria based on the input-output approach can also be established by applying the direct Lyapunov method to the original time-delay systems. Finally, simulation examples are provided to demonstrate the effectiveness of the proposed approaches.

  19. Existence and global exponential stability of periodic solution of memristor-based BAM neural networks with time-varying delays.

    PubMed

    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. PMID:26752438

  20. Function projective synchronization of memristor-based Cohen-Grossberg neural networks with time-varying delays.

    PubMed

    Abdurahman, Abdujelil; Jiang, Haijun; Rahman, Kaysar

    2015-12-01

    This paper deals with the problem of function projective synchronization for a class of memristor-based Cohen-Grossberg neural networks with time-varying delays. Based on the theory of differential equations with discontinuous right-hand side, some novel criteria are obtained to realize the function projective synchronization of addressed networks by combining open loop control and linear feedback control. As some special cases, several control strategies are given to ensure the realization of complete synchronization, anti-synchronization and the stabilization of the considered memristor-based Cohen-Grossberg neural network. Finally, a numerical example and its simulations are provided to demonstrate the effectiveness of the obtained results. PMID:26557930

  1. Non-fragile H∞ dynamic output feedback control for uncertain Takagi-Sugeno fuzzy systems with time-varying delay

    NASA Astrophysics Data System (ADS)

    Huang, Sheng-Juan; Yang, Guang-Hong

    2016-09-01

    This paper mainly focuses on the problem of non-fragile H∞ dynamic output feedback control for a class of uncertain Takagi-Sugeno fuzzy systems with time-varying state delay. Based on a new type of Lyapunov-Krasovskii functional without ignoring any subtle integral terms in the derivatives, a less conservative dynamic output feedback controller with additive gain variations is designed, which guarantees that the closed-loop fuzzy system is asymptotically stable and satisfies a prescribed H∞-performance level. Furthermore, the obtained parameter-dependent conditions are given in terms of solution to a set of linear matrix inequalities, which improve some existing relevant results. Finally, numerical examples are given to illustrate the effectiveness and merits of the proposed method.

  2. Consensus with guaranteed convergence rate of high-order integrator agents in the presence of time-varying delays

    NASA Astrophysics Data System (ADS)

    Savino, H. J.; Souza, F. O.; Pimenta, L. C. A.

    2016-07-01

    This paper aims to study the consensus problem in directed networks of agents with high-order integrator dynamics and fixed topology. It is considered the existence of non-uniform time-varying delays in the agents control laws for each interaction between agents and their neighbours. Based on Lyapunov-Krasovskii stability theory and algebraic graph theory, sufficient conditions, in terms of linear matrix inequalities, are given to verify if consensus is achieved with guaranteed exponential convergence rate. The efficiency of the proposed method is verified by numerical simulations. The simulations reveal that the conditions established in this work outperformed the similar existing ones in all numerical tests accomplished in this paper.

  3. Nonlinear Reduced-Order Analysis with Time-Varying Spatial Loading Distributions

    NASA Technical Reports Server (NTRS)

    Prezekop, Adam

    2008-01-01

    Oscillating shocks acting in combination with high-intensity acoustic loadings present a challenge to the design of resilient hypersonic flight vehicle structures. This paper addresses some features of this loading condition and certain aspects of a nonlinear reduced-order analysis with emphasis on system identification leading to formation of a robust modal basis. The nonlinear dynamic response of a composite structure subject to the simultaneous action of locally strong oscillating pressure gradients and high-intensity acoustic loadings is considered. The reduced-order analysis used in this work has been previously demonstrated to be both computationally efficient and accurate for time-invariant spatial loading distributions, provided that an appropriate modal basis is used. The challenge of the present study is to identify a suitable basis for loadings with time-varying spatial distributions. Using a proper orthogonal decomposition and modal expansion, it is shown that such a basis can be developed. The basis is made more robust by incrementally expanding it to account for changes in the location, frequency and span of the oscillating pressure gradient.

  4. Stability criteria for T-S fuzzy systems with interval time-varying delays and nonlinear perturbations based on geometric progression delay partitioning method.

    PubMed

    Chen, Hao; Zhong, Shouming; Li, Min; Liu, Xingwen; Adu-Gyamfi, Fehrs

    2016-07-01

    In this paper, a novel delay partitioning method is proposed by introducing the theory of geometric progression for the stability analysis of T-S fuzzy systems with interval time-varying delays and nonlinear perturbations. Based on the common ratio α, the delay interval is unequally separated into multiple subintervals. A newly modified Lyapunov-Krasovskii functional (LKF) is established which includes triple-integral terms and augmented factors with respect to the length of every related proportional subintervals. In addition, a recently developed free-matrix-based integral inequality is employed to avoid the overabundance of the enlargement when dealing with the derivative of the LKF. This innovative development can dramatically enhance the efficiency of obtaining the maximum upper bound of the time delay. Finally, much less conservative stability criteria are presented. Numerical examples are conducted to demonstrate the significant improvements of this proposed approach. PMID:27138648

  5. Stochastic sampled data robust stabilisation of T-S fuzzy neutral systems with randomly occurring uncertainties and time-varying delays

    NASA Astrophysics Data System (ADS)

    Rakkiyappan, R.; Chandrasekar, A.; Lakshmanan, S.

    2016-07-01

    This paper is concerned with the stochastic sampled data robust stabilisation of T-S fuzzy neutral systems with randomly occurring uncertainties and time-varying delays. The sampling period is assumed to be m in number, whose occurrence probabilities are given constants and satisfy Bernoulli distribution. By introducing an improved Lyapunov-Krasovskii functional with new triple integral terms and by combining both the convex combination technique and reciprocal convex technique, delay-dependent robust stability criteria are obtained in terms of linear matrix inequalities. These linear matrix inequalities can be easily solved by using standard convex optimisation algorithms. The designed stochastic sampled data fuzzy controller gain can be obtained. Finally, three numerical examples are given to illustrate the effectiveness of the proposed methods.

  6. Further improved stability criteria for uncertain T-S fuzzy systems with interval time-varying delay by delay-partitioning approach.

    PubMed

    Yang, Jun; Luo, Wenpin; Cheng, Jun; Wang, Yonghu

    2015-09-01

    This paper focuses on further improved stability criteria for uncertain T-S fuzzy systems with interval time-varying delay by a delay-partitioning approach. A modified augmented Lyapunov-Krasovskii functional (LKF) is established by partitioning the delay in all integral terms. Then some tighter bounding inequalities, i.e., Peng-Park׳s integral inequality (reciprocally convex approach) and the Free-Matrix-Based integral inequality (which yields less conservative stability criteria than the use of Wirtinger-based inequality does) are introduced to reduce the enlargement in bounding the derivative of LKF as much as possible, therefore, less conservative results can be expected in terms of es and LMIs. Finally, a numerical example is included to show that the proposed methods are less conservative than existing ones. PMID:26073644

  7. Input-Output Approach to Control for Fuzzy Markov Jump Systems With Time-Varying Delays and Uncertain Packet Dropout Rate.

    PubMed

    Zhang, Lixian; Ning, Zepeng; Shi, Peng

    2015-11-01

    This paper is concerned with H∞ control problem for a class of discrete-time Takagi-Sugeno fuzzy Markov jump systems with time-varying delays under unreliable communication links. It is assumed that the data transmission between the plant and the controller are subject to randomly occurred packet dropouts satisfying Bernoulli distribution and the dropout rate is uncertain. Based on a fuzzy-basis-dependent and mode-dependent Lyapunov function, the existence conditions of the desired H∞ state-feedback controllers are derived by employing the scaled small gain theorem such that the closed-loop system is stochastically stable and achieves a guaranteed H∞ performance. The gains of the controllers are constructed by solving a set of linear matrix inequalities. Finally, a practical example of robot arm is provided to illustrate the performance of the proposed approach. PMID:26470060

  8. Analysis of global O(t(-α)) stability and global asymptotical periodicity for a class of fractional-order complex-valued neural networks with time varying delays.

    PubMed

    Rakkiyappan, R; Sivaranjani, R; Velmurugan, G; Cao, Jinde

    2016-05-01

    In this paper, the problem of the global O(t(-α)) stability and global asymptotic periodicity for a class of fractional-order complex-valued neural networks (FCVNNs) with time varying delays is investigated. By constructing suitable Lyapunov functionals and a Leibniz rule for fractional differentiation, some new sufficient conditions are established to ensure that the addressed FCVNNs are globally O(t(-α)) stable. Moreover, some sufficient conditions for the global asymptotic periodicity of the addressed FCVNNs with time varying delays are derived, showing that all solutions converge to the same periodic function. Finally, numerical examples are given to demonstrate the effectiveness and usefulness of our theoretical results. PMID:26922720

  9. M-matrix based robust stability and stabilization for uncertain discrete-time switched TS fuzzy systems with time-varying delays.

    PubMed

    Jaballi, Ahmed; Sakly, Anis; Hajjaji, Ahmed El

    2016-07-01

    This paper provides novel sufficient conditions on robust asymptotic stability and stabilization for a class of uncertain discrete-time switched fuzzy with time-varying delays. The attention is focused on developing new algebraic criteria to break with classical criteria in terms of Linear Matrix Inequalities (LMIs). Firstly, based on the M-matrix proprieties and through l1,∞ induced norms notion, new delay-dependent sufficient conditions are derived to ensure the asymptotic stability and stabilization for a class of uncertain discrete-time switched fuzzy systems with time-varying delay. Secondly, these results are extended for a class of uncertain discrete-time switched fuzzy systems with time delays, modeled by difference equations. Finally, two numerical examples and practical example (a robot arm) are provided to demonstrate the advantage and the effectiveness of our results. PMID:26996925

  10. The time-varying electron energy distribution function in the plume of a Hall thruster

    NASA Astrophysics Data System (ADS)

    Dannenmayer, K.; Mazouffre, S.; Kudrna, P.; Tichý, M.

    2014-12-01

    Time-resolved Langmuir probe measurements have been performed in the plume of the 1.5 kW class PPS®1350-ML Hall thruster. The time-dependent electron energy distribution function (EEDF) has been inferred from the probe current-voltage characteristic curves obtained after active stabilization of the discharge. The distribution function changes in the course of time at the breathing oscillation frequency (13.8 kHz). The EEDF is Maxwellian with a depleted tail above the xenon ionization energy whatever the location and the time. The electron density and temperature computed from the EEDF also oscillate at the breathing mode frequency. Experimental outcomes indicate the existence of a low-frequency plasma wave that propagates axially. The wave front speed (2700 m s-1) was found to be compatible with the ion acoustic speed (2300 m s-1).

  11. Modeling hyporheic exchange and in-stream transport with time-varying transit time distributions

    NASA Astrophysics Data System (ADS)

    Ball, A.; Harman, C. J.; Ward, A. S.

    2014-12-01

    Transit time distributions (TTD) are used to understand in-stream transport and exchange with the hyporheic zone by quantifying the probability of water (and of dissolved material) taking time T to traverse the stream reach control volume. However, many studies using this method assume a TTD that is time-invariant, despite the time-variability of the streamflow. Others assume that storage is 'randomly sampled' or 'well-mixed' with a fixed volume or fixed exchange rate. Here we present a formulation for a time-variable TTD that relaxes both the time-invariant and 'randomly sampled' assumptions and only requires a few parameters. The framework is applied to transient storage, representing some combination of in-stream and hyporheic storage, along a stream reach. This approach does not assume that hyporheic and dead-zone storage is fixed or temporally-invariant, and allows for these stores to be sampled in more physically representative ways determined by the system itself. Instead of using probability distributions of age, probability distributions of storage (ranked by age) called Ω functions are used to describe how the off-stream storage is sampled in the outflow. Here the Ω function approach is used to describe hyporheic exchange during diurnal fluctuations in streamflow in a gaining reach of the H.J. Andrews Experimental Forest. The breakthrough curves of salt slugs injected four hours apart over a 28-hour period show a systematic variation in transit time distribution. This new approach allows us to relate these salt slug TTDs to a corresponding time-variation in the Ω function, which can then be related to changes in in-stream storage and hyporheic zone mobilization under varying flow conditions. Thus, we can gain insights into how channel storage and hyporheic exchange are changing through time without having to specify difficult to measure or unmeasurable quantities of our system, such as total storage.

  12. Stability and synchronization of discrete-time neural networks with switching parameters and time-varying delays.

    PubMed

    Wu, Ligang; Feng, Zhiguang; Lam, James

    2013-12-01

    This paper is concerned with the problems of exponential stability analysis and synchronization of discrete-time switched delayed neural networks. Using the average dwell time approach together with the piecewise Lyapunov function technique, sufficient conditions are proposed to guarantee the exponential stability for the switched neural networks with time-delays. Benefitting from the delay partitioning method and the free-weighting matrix technique, the conservatism of the obtained results is reduced. In addition, the decay estimates are explicitly given and the synchronization problem is solved. The results reported in this paper not only depend upon the delay, but also depend upon the partitioning, which aims at reducing the conservatism. Numerical examples are presented to demonstrate the usefulness of the derived theoretical results. PMID:24805215

  13. Central suboptimal H ∞ filter design for linear time-varying systems with state and measurement delays

    NASA Astrophysics Data System (ADS)

    Basin, Michael; Shi, Peng; Calderon-Alvarez, Dario

    2010-04-01

    This article presents the central finite-dimensional H ∞ filters for linear systems with state and measurement delay that are suboptimal for a given threshold γ with respect to a modified Bolza-Meyer quadratic criterion including the attenuation control term with the opposite sign. In contrast to the results previously obtained for linear time delay systems, this article reduces the original H ∞ filtering problem to H 2 (optimal mean-square) filtering problem using the technique proposed in Doyle, Glover, Khargonekar, and Francis (1989 'State-space Solutions to Standard H 2 and H ∞ Control Problems', IEEE Transactions on Automatic Control, 34, 831-847). Application of the reduction technique becomes possible, since the optimal closed-form filtering equations solving the H 2 (mean-square) filtering problem have been obtained for linear systems with state and measurement delays. This article first presents the central suboptimal H ∞ filter for linear systems with state and measurement delays, based on the optimal H 2 filter from Basin, Alcorta-Garcia, and Rodriguez-Gonzalez (2005, 'Optimal Filtering for Linear Systems with State and Observation Delays', International Journal of Robust and Nonlinear Control, 15, 859-871), which consists, in the general case, of an infinite set of differential equations. Then, the finite-dimensional central suboptimal H ∞ filter is designed in case of linear systems with commensurable state and measurement delays, which contains a finite number of equations for any fixed filtering horizon; however, this number still grows unboundedly as time goes to infinity. To overcome that difficulty, the alternative central suboptimal H ∞ filter is designed for linear systems with state and measurement delays, which is based on the alternative optimal H 2 filter from Basin, Perez, and Martinez-Zuniga (2006, 'Alternative Optimal Filter for Linear State Delay Systmes', International Journal of Adaptive Control and Signal Processing, 20

  14. Robust reliable guaranteed cost piecewise fuzzy control for discrete-time nonlinear systems with time-varying delay and actuator failures

    NASA Astrophysics Data System (ADS)

    Kchaou, Mourad; Souissi, Mansour; Toumi, Ahmed

    2011-07-01

    In this paper, we investigate the delay-dependent robust reliable guaranteed cost (RRGC) fuzzy control problem for discrete-time nonlinear systems with time-varying delays. The delays may simultaneously appear in the state and in the control input. Also, both parametric uncertainties and control component failure may exist. Through Takagi-Sugeno fuzzy modelling of nonlinear delayed-systems and based on an appropriate piecewise Lyapunov-Krasovskii functional, a piecewise fuzzy controller is designed. Sufficient conditions for the existence of a RRGC controller are derived in terms of linear matrix inequalities (LMIs). Furthermore, a suboptimal RRGC fuzzy controller is given by means of a convex optimization procedure with LMI constraints which can not only guarantee the stability of the closed-loop fuzzy system, but also provides an optimized upper bound of the given cost performance despite possible actuator faults. Two numerical examples are presented in this paper to illustrate the feasibility of the theoretical developments.

  15. Neural-adaptive control of single-master-multiple-slaves teleoperation for coordinated multiple mobile manipulators with time-varying communication delays and input uncertainties.

    PubMed

    Li, Zhijun; Su, Chun-Yi

    2013-09-01

    In this paper, adaptive neural network control is investigated for single-master-multiple-slaves teleoperation in consideration of time delays and input dead-zone uncertainties for multiple mobile manipulators carrying a common object in a cooperative manner. Firstly, concise dynamics of teleoperation systems consisting of a single master robot, multiple coordinated slave robots, and the object are developed in the task space. To handle asymmetric time-varying delays in communication channels and unknown asymmetric input dead zones, the nonlinear dynamics of the teleoperation system are transformed into two subsystems through feedback linearization: local master or slave dynamics including the unknown input dead zones and delayed dynamics for the purpose of synchronization. Then, a model reference neural network control strategy based on linear matrix inequalities (LMI) and adaptive techniques is proposed. The developed control approach ensures that the defined tracking errors converge to zero whereas the coordination internal force errors remain bounded and can be made arbitrarily small. Throughout this paper, stability analysis is performed via explicit Lyapunov techniques under specific LMI conditions. The proposed adaptive neural network control scheme is robust against motion disturbances, parametric uncertainties, time-varying delays, and input dead zones, which is validated by simulation studies. PMID:24808577

  16. Time-varying BRDFs.

    PubMed

    Sun, Bo; Sunkavalli, Kalyan; Ramamoorthi, Ravi; Belhumeur, Peter N; Nayar, Shree K

    2007-01-01

    The properties of virtually all real-world materials change with time, causing their bidirectional reflectance distribution functions (BRDFs) to be time varying. However, none of the existing BRDF models and databases take time variation into consideration; they represent the appearance of a material at a single time instance. In this paper, we address the acquisition, analysis, modeling, and rendering of a wide range of time-varying BRDFs (TVBRDFs). We have developed an acquisition system that is capable of sampling a material's BRDF at multiple time instances, with each time sample acquired within 36 sec. We have used this acquisition system to measure the BRDFs of a wide range of time-varying phenomena, which include the drying of various types of paints (watercolor, spray, and oil), the drying of wet rough surfaces (cement, plaster, and fabrics), the accumulation of dusts (household and joint compound) on surfaces, and the melting of materials (chocolate). Analytic BRDF functions are fit to these measurements and the model parameters' variations with time are analyzed. Each category exhibits interesting and sometimes nonintuitive parameter trends. These parameter trends are then used to develop analytic TVBRDF models. The analytic TVBRDF models enable us to apply effects such as paint drying and dust accumulation to arbitrary surfaces and novel materials. PMID:17356224

  17. Energy-to-peak state estimation for Markov jump RNNs with time-varying delays via nonsynchronous filter with nonstationary mode transitions.

    PubMed

    Zhang, Lixian; Zhu, Yanzheng; Zheng, Wei Xing

    2015-10-01

    In this paper, the problem of energy-to-peak state estimation for a class of discrete-time Markov jump recurrent neural networks (RNNs) with randomly occurring nonlinearities (RONs) and time-varying delays is investigated. A practical phenomenon of nonsynchronous jumps between RNNs modes and desired mode-dependent filters is considered, and a nonstationary mode transition among the filters is used to model the nonsynchronous jumps to different degrees that are also mode dependent. The RONs are used to model a class of sector-like nonlinearities that occur in a probabilistic way according to a Bernoulli sequence. The time-varying delays are supposed to be mode dependent and unknown, but with known lower and upper bounds a priori. Sufficient conditions on the existence of the nonsynchronous filters are obtained such that the filtering error system is stochastically stable and achieves a prescribed energy-to-peak performance index. Further to the recent study on the class of nonsynchronous estimation problem, a monotonicity is observed in obtaining filtering performance index, while changing the degree of nonsynchronous jumps. A numerical example is presented to verify the theoretical findings. PMID:25576580

  18. Stochastic sampled-data control for synchronization of complex dynamical networks with control packet loss and additive time-varying delays.

    PubMed

    Rakkiyappan, R; Sakthivel, N; Cao, Jinde

    2015-06-01

    This study examines the exponential synchronization of complex dynamical networks with control packet loss and additive time-varying delays. Additionally, sampled-data controller with time-varying sampling period is considered and is assumed to switch between m different values in a random way with given probability. Then, a novel Lyapunov-Krasovskii functional (LKF) with triple integral terms is constructed and by using Jensen's inequality and reciprocally convex approach, sufficient conditions under which the dynamical network is exponentially mean-square stable are derived. When applying Jensen's inequality to partition double integral terms in the derivation of linear matrix inequality (LMI) conditions, a new kind of linear combination of positive functions weighted by the inverses of squared convex parameters appears. In order to handle such a combination, an effective method is introduced by extending the lower bound lemma. To design the sampled-data controller, the synchronization error system is represented as a switched system. Based on the derived LMI conditions and average dwell-time method, sufficient conditions for the synchronization of switched error system are derived in terms of LMIs. Finally, numerical example is employed to show the effectiveness of the proposed methods. PMID:25797504

  19. Global O(t(-α)) stability and global asymptotical periodicity for a non-autonomous fractional-order neural networks with time-varying delays.

    PubMed

    Chen, Boshan; Chen, Jiejie

    2016-01-01

    The present paper studies global O(t(-α)) stability and global asymptotical periodicity for a non-autonomous fractional-order neural networks with time-varying delays (FDNN). Firstly, some sufficient conditions are established to ensure that a non-autonomous FDNN is global O(t(-α)) stable based on a new Lyapunov function method and Leibniz rule for fractional differentiation. Next it is shown that the periodic or autonomous FDNN cannot generate exactly nonconstant periodic solution under any circumstances. Finally, we show that all solutions converge to a same periodic function for a periodic FDNN by using a fractional-order differential inequality technique. Our issues, methods and results are all new. PMID:26547243

  20. Observer-based robust finite time H∞ sliding mode control for Markovian switching systems with mode-dependent time-varying delay and incomplete transition rate.

    PubMed

    Gao, Lijun; Jiang, Xiaoxiao; Wang, Dandan

    2016-03-01

    This paper investigates the problem of robust finite time H∞ sliding mode control for a class of Markovian switching systems. The system is subjected to the mode-dependent time-varying delay, partly unknown transition rate and unmeasurable state. The main difficulty is that, a sliding mode surface cannot be designed based on the unknown transition rate and unmeasurable state directly. To overcome this obstacle, the set of modes is firstly divided into two subsets standing for known transition rate subset and unknown one, based on which a state observer is established. A component robust finite-time sliding mode controller is also designed to cope with the effect of partially unknown transition rate. It is illustrated that the reachability, finite-time stability, finite-time boundedness, finite-time H∞ state feedback stabilization of sliding mode dynamics can be ensured despite the unknown transition rate. Finally, the simulation results verify the effectiveness of robust finite time control problem. PMID:26777336

  1. Multistability analysis of a general class of recurrent neural networks with non-monotonic activation functions and time-varying delays.

    PubMed

    Liu, Peng; Zeng, Zhigang; Wang, Jun

    2016-07-01

    This paper addresses the multistability for a general class of recurrent neural networks with time-varying delays. Without assuming the linearity or monotonicity of the activation functions, several new sufficient conditions are obtained to ensure the existence of (2K+1)(n) equilibrium points and the exponential stability of (K+1)(n) equilibrium points among them for n-neuron neural networks, where K is a positive integer and determined by the type of activation functions and the parameters of neural network jointly. The obtained results generalize and improve the earlier publications. Furthermore, the attraction basins of these exponentially stable equilibrium points are estimated. It is revealed that the attraction basins of these exponentially stable equilibrium points can be larger than their originally partitioned subsets. Finally, three illustrative numerical examples show the effectiveness of theoretical results. PMID:27136665

  2. The Modeling of Time-Varying Stream Water Age Distributions: Preliminary Investigations with Non-Conservative Solutes

    NASA Astrophysics Data System (ADS)

    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

  3. Delay-dependent reliable H ∞ filtering for sector-bounded nonlinear continuous-time systems with time-varying state delays and sensor failures

    NASA Astrophysics Data System (ADS)

    Guo, Xiang-Gui; Yang, Guang-Hong

    2012-01-01

    In this article, the reliable H ∞ filtering problem against sensor failures is investigated for a class of continuous-time systems with simultaneous sector-bounded nonlinearities and varying time delays. The focus of this article is on designing a reliable filter such that the filtering error system is asymptotically stable and meets the prescribed H ∞ norm constraint in the normal case as well as in the sensor failure case simultaneously. Linear matrix inequality conditions, which depend not only on the upper and lower bounds of delay but also on the upper bound of delay derivative, are obtained for the existence of admissible filters and, based on these, the filter design is cast into a convex optimisation problem. What is worth mentioning is that the information about the upper bound of the delay derivative is taken into consideration even if this upper bound is not smaller than 1. A numerical example is presented to illustrate the effectiveness and advantage of the developed filter design method.

  4. Distributed finite-time consensus tracking for nonlinear multi-agent systems with a time-varying reference state

    NASA Astrophysics Data System (ADS)

    Wen, Guoguang; Yu, Yongguang; Peng, Zhaoxia; Rahmani, Ahmed

    2016-06-01

    This paper investigates the consensus tracking problem for nonlinear multi-agent systems with a time-varying reference state. The consensus reference is taken as a virtual leader, whose output is only its position information that is available to only a subset of a group of followers. The dynamics of each follower consists of two terms: nonlinear inherent dynamics and a simple communication protocol relying only on the position of its neighbours. In this paper, the consensus tracking problem is respectively considered under fixed and switching communication topologies. Some corresponding sufficient conditions are obtained to guarantee the states of followers can converge to the state of the virtual leader in finite time. Rigorous proofs are given by using graph theory, matrix theory, and Lyapunov theory. Simulations are presented to illustrate the theoretical analysis.

  5. Ultrasonic generator and detector using an optical mask having a grating for launching a plurality of spatially distributed, time varying strain pulses in a sample

    DOEpatents

    Maris, Humphrey J.

    2002-01-01

    A method and a system are disclosed for determining at least one characteristic of a sample that contains a substrate and at least one film disposed on or over a surface of the substrate. The method includes a first step of placing a mask over a free surface of the at least one film, where the mask has a top surface and a bottom surface that is placed adjacent to the free surface of the film. The bottom surface of the mask has formed therein or thereon a plurality of features for forming at least one grating. A next step directs optical pump pulses through the mask to the free surface of the film, where individual ones of the pump pulses are followed by at least one optical probe pulse. The pump pulses are spatially distributed by the grating for launching a plurality of spatially distributed, time varying strain pulses within the film, which cause a detectable change in optical constants of the film. A next step detects a reflected or a transmitted portion of the probe pulses, which are also spatially distributed by the grating. A next step measures a change in at least one characteristic of at least one of reflected or transmitted probe pulses due to the change in optical constants, and a further step determines the at least one characteristic of the sample from the measured change in the at least one characteristic of the probe pulses. An optical mask is also disclosed herein, and forms a part of these teachings.

  6. Ultrasonic generator and detector using an optical mask having a grating for launching a plurality of spatially distributed, time varying strain pulses in a sample

    DOEpatents

    Maris, Humphrey J.

    2003-01-01

    A method and a system are disclosed for determining at least one characteristic of a sample that contains a substrate and at least one film disposed on or over a surface of the substrate. The method includes a first step of placing a mask over a free surface of the at least one film, where the mask has a top surface and a bottom surface that is placed adjacent to the free surface of the film. The bottom surface of the mask has formed therein or thereon a plurality of features for forming at least one grating. A next step directs optical pump pulses through the mask to the free surface of the film, where individual ones of the pump pulses are followed by at least one optical probe pulse. The pump pulses are spatially distributed by the grating for launching a plurality of spatially distributed, time varying strain pulses within the film, which cause a detectable change in optical constants of the film. A next step detects a reflected or a transmitted portion of the probe pulses, which are also spatially distributed by the grating. A next step measures a change in at least one characteristic of at least one of reflected or transmitted probe pulses due to the change in optical constants, and a further step determines the at least one characteristic of the sample from the measured change in the at least one characteristic of the probe pulses. An optical mask is also disclosed herein, and forms a part of these teachings.

  7. Analysis of the time-varying energy of brain responses to an oddball paradigm using short-term smoothed Wigner-Ville distribution.

    PubMed

    Tağluk, M E; Cakmak, E D; Karakaş, S

    2005-04-30

    Cognitive brain responses to external stimuli, as measured by event related potentials (ERPs), have been analyzed from a variety of perspectives to investigate brain dynamics. Here, the brain responses of healthy subjects to auditory oddball paradigms, standard and deviant stimuli, recorded on an Fz electrode site were studied using a short-term version of the smoothed Wigner-Ville distribution (STSW) method. A smoothing kernel was designed to preserve the auto energy of the signal with maximum time and frequency resolutions. Analysis was conducted mainly on the time-frequency distributions (TFDs) of sweeps recorded during successive trials including the TFD of averaged single sweeps as the evoked time-frequency (ETF) brain response and the average of TFDs of single sweeps as the time-frequency (TF) brain response. Also the power entropy and the phase angles of the signal at frequency f and time t locked to the stimulus onset were studied across single trials as the TF power-locked and the TF phase-locked brain responses, respectively. TFDs represented in this way demonstrated the ERP spectro-temporal characteristics from multiple perspectives. The time-varying energy of the individual components manifested interesting TF structures in the form of amplitude modulated (AM) and frequency modulated (FM) energy bursts. The TF power-locked and phase-locked brain responses provoked ERP energies in a manner modulated by cognitive functions, an observation requiring further investigation. These results may lead to a better understanding of integrative brain dynamics. PMID:15814152

  8. Event-based distributed set-membership filtering for a class of time-varying non-linear systems over sensor networks with saturation effects

    NASA Astrophysics Data System (ADS)

    Wei, Guoliang; Liu, Shuai; Wang, Licheng; Wang, Yongxiong

    2016-07-01

    In this paper, based on the event-triggered mechanism, the problem of distributed set-membership filtering is concerned for a class of time-varying non-linear systems over sensor networks subject to saturation effects. Different from the traditional periodic sample-data approach, the filter is updated only when the predefined event is satisfied, which the event is defined according to the measurement output. For each node, the proposed novel event-triggered mechanism can reduce the unnecessary information transmission between sensors and filters. The purpose of the addressed problem is to design a series of distributed set-membership filters, for all the admissible unknown but bounded noises, non-linearities and sensor saturation, such that the set of all possible states can be determined. The desired filter parameters are obtained by solving a recursive linear matrix inequality that can be computed recursively using the available MATLAB toolbox. Finally, a simulation example is exploited to show the effectiveness of the proposed design approach in this paper.

  9. Time varied gain functions for pulsed sonars

    NASA Astrophysics Data System (ADS)

    MacLennan, D. N.

    1986-11-01

    The time varied gain (TVG) of a sonar is intended to remove the range dependence of echo strength. The conventional "40 log R" and "20 log R" TVG functions, which apply to single and distributed targets respectively, provide exact compensation only at infinite range. At short range, the conventional functions are inexact due to bandwidth related delays and the change in receiver gain over a pulse length. The theory of echo formation is used to derive exact gain functions which make the echo energy integral independent of the target range. In the case of randomly distributed targets, the linear form of the exact function is shown to be ( t)= ct exp (α ct/2)√{(1- T 1/t ) 2-( T 2/t ) 2}, for sound speed c and absorption coefficient α. T1 and T2 are constants for a given sonar and target. The ct exp ( αct/2) term is equivalent to "20 log R+2 αR". The single target function is similarly the conventional function multiplied by a polynomial expression in 1/ t. Analytic functions are derived for systems with simple transfer functions. As the pulse length bandwidth product increases, the exact function tends to that of the wideband ideal system for which T1= T/2 and T2 = T/√(12), T being the transmitter pulse length. Exact TVG functions are derived numerically for two echo sounders used in fishery research and are compared with the measured gain variation. The TVG function realized in sonars may depart considerably from the exact form. Delaying the start of the TVG ramp may reduce the error. The delay required for exact compensation depends upon the target range and is at least half the pulse length.

  10. Exponential stability and robust H∞ control of a class of discrete-time switched non-linear systems with time-varying delays via T-S fuzzy model

    NASA Astrophysics Data System (ADS)

    Mao, Yanbing; Zhang, Hongbin

    2014-05-01

    This paper deals with stability and robust H∞ control of discrete-time switched non-linear systems with time-varying delays. The T-S fuzzy models are utilised to represent each sub-non-linear system. Thus, with two level functions, namely, crisp switching functions and local fuzzy weighting functions, we introduce a discrete-time switched fuzzy systems, which inherently contain the features of the switched hybrid systems and T-S fuzzy systems. Piecewise fuzzy weighting-dependent Lyapunov-Krasovskii functionals (PFLKFs) and average dwell-time approach are utilised in this paper for the exponentially stability analysis and controller design, and with free fuzzy weighting matrix scheme, switching control laws are obtained such that H∞ performance is satisfied. The conditions of stability and the control laws are given in the form of linear matrix inequalities (LMIs) that are numerically feasible. The state decay estimate is explicitly given. A numerical example and the control of delayed single link robot arm with uncertain part are given to demonstrate the efficiency of the proposed method.

  11. Characterization of the startup transient electrokinetic flow in rectangular channels of arbitrary dimensions, zeta potential distribution, and time-varying pressure gradient.

    PubMed

    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. PMID:25502599

  12. Fractional diffusions with time-varying coefficients

    NASA Astrophysics Data System (ADS)

    Garra, Roberto; Orsingher, Enzo; Polito, Federico

    2015-09-01

    This paper is concerned with the fractionalized diffusion equations governing the law of the fractional Brownian motion BH(t). We obtain solutions of these equations which are probability laws extending that of BH(t). Our analysis is based on McBride fractional operators generalizing the hyper-Bessel operators L and converting their fractional power Lα into Erdélyi-Kober fractional integrals. We study also probabilistic properties of the random variables whose distributions satisfy space-time fractional equations involving Caputo and Riesz fractional derivatives. Some results emerging from the analysis of fractional equations with time-varying coefficients have the form of distributions of time-changed random variables.

  13. Fractal analysis of time varying data

    DOEpatents

    Vo-Dinh, Tuan; Sadana, Ajit

    2002-01-01

    Characteristics of time varying data, such as an electrical signal, are analyzed by converting the data from a temporal domain into a spatial domain pattern. Fractal analysis is performed on the spatial domain pattern, thereby producing a fractal dimension D.sub.F. The fractal dimension indicates the regularity of the time varying data.

  14. TIME-VARYING DYNAMICAL STAR FORMATION RATE

    SciTech Connect

    Lee, Eve J.; Chang, Philip; Murray, Norman

    2015-02-10

    We present numerical evidence of dynamic star formation in which the accreted stellar mass grows superlinearly with time, roughly as t {sup 2}. We perform simulations of star formation in self-gravitating hydrodynamic and magnetohydrodynamic turbulence that is continuously driven. By turning the self-gravity of the gas in the simulations on or off, we demonstrate that self-gravity is the dominant physical effect setting the mass accretion rate at early times before feedback effects take over, contrary to theories of turbulence-regulated star formation. We find that gravitational collapse steepens the density profile around stars, generating the power-law tail on what is otherwise a lognormal density probability distribution function. Furthermore, we find turbulent velocity profiles to flatten inside collapsing regions, altering the size-line width relation. This local flattening reflects enhancements of turbulent velocity on small scales, as verified by changes to the velocity power spectra. Our results indicate that gas self-gravity dynamically alters both density and velocity structures in clouds, giving rise to a time-varying star formation rate. We find that a substantial fraction of the gas that forms stars arrives via low-density flows, as opposed to accreting through high-density filaments.

  15. Effect modification by time-varying covariates.

    PubMed

    Robins, James M; Hernán, Miguel A; Rotnitzky, Andrea

    2007-11-01

    Marginal structural models (MSMs) allow estimation of effect modification by baseline covariates, but they are less useful for estimating effect modification by evolving time-varying covariates. Rather, structural nested models (SNMs) were specifically designed to estimate effect modification by time-varying covariates. In their paper, Petersen et al. (Am J Epidemiol 2007;166:985-993) describe history-adjusted MSMs as a generalized form of MSM and argue that history-adjusted MSMs allow a researcher to easily estimate effect modification by time-varying covariates. However, history-adjusted MSMs can result in logically incompatible parameter estimates and hence in contradictory substantive conclusions. Here the authors propose a more restrictive definition of history-adjusted MSMs than the one provided by Petersen et al. and compare the advantages and disadvantages of using history-adjusted MSMs, as opposed to SNMs, to examine effect modification by time-dependent covariates. PMID:17875581

  16. Oscillations in SIRS model with distributed delays

    NASA Astrophysics Data System (ADS)

    Gonçalves, S.; Abramson, G.; Gomes, M. F. C.

    2011-06-01

    The ubiquity of oscillations in epidemics presents a long standing challenge for the formulation of epidemic models. Whether they are external and seasonally driven, or arise from the intrinsic dynamics is an open problem. It is known that fixed time delays destabilize the steady state solution of the standard SIRS model, giving rise to stable oscillations for certain parameters values. In this contribution, starting from the classical SIRS model, we make a general treatment of the recovery and loss of immunity terms. We present oscillation diagrams (amplitude and period) in terms of the parameters of the model, showing how oscillations can be destabilized by the shape of the distributions of the two characteristic (infectious and immune) times. The formulation is made in terms of delay equations which are both numerically integrated and linearized. Results from simulations are included showing where they support the linear analysis and explaining why not where they do not. Considerations and comparison with real diseases are presented along.

  17. Components in time-varying graphs.

    PubMed

    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. PMID:22757508

  18. Components in time-varying graphs

    NASA Astrophysics Data System (ADS)

    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.

  19. Learning Time-Varying Coverage Functions

    PubMed Central

    Du, Nan; Liang, Yingyu; Balcan, Maria-Florina; Song, Le

    2015-01-01

    Coverage functions are an important class of discrete functions that capture the law of diminishing returns arising naturally from applications in social network analysis, machine learning, and algorithmic game theory. In this paper, we propose a new problem of learning time-varying coverage functions, and develop a novel parametrization of these functions using random features. Based on the connection between time-varying coverage functions and counting processes, we also propose an efficient parameter learning algorithm based on likelihood maximization, and provide a sample complexity analysis. We applied our algorithm to the influence function estimation problem in information diffusion in social networks, and show that with few assumptions about the diffusion processes, our algorithm is able to estimate influence significantly more accurately than existing approaches on both synthetic and real world data. PMID:25960624

  20. Modeling distributed axonal delays in mean-field brain dynamics

    NASA Astrophysics Data System (ADS)

    Roberts, J. A.; Robinson, P. A.

    2008-11-01

    The range of conduction delays between connected neuronal populations is often modeled as a single discrete delay, assumed to be an effective value averaging over all fiber velocities. This paper shows the effects of distributed delays on signal propagation. A distribution acts as a linear filter, imposing an upper frequency cutoff that is inversely proportional to the delay width. Distributed thalamocortical and corticothalamic delays are incorporated into a physiologically based mean-field model of the cortex and thalamus to illustrate their effects on the electroencephalogram (EEG). The power spectrum is acutely sensitive to the width of the thalamocortical delay distribution, and more so than the corticothalamic distribution, because all input signals must travel along the thalamocortical pathway. This imposes a cutoff frequency above which the spectrum is overly damped. The positions of spectral peaks in the resting EEG depend primarily on the distribution mean, with only weak dependences on distribution width. Increasing distribution width increases the stability of fixed point solutions. A single discrete delay successfully approximates a distribution for frequencies below a cutoff that is inversely proportional to the delay width, provided that other model parameters are moderately adjusted. A pair of discrete delays together having the same mean, variance, and skewness as the distribution approximates the distribution over the same frequency range without needing parameter adjustment. Delay distributions with large fractional widths are well approximated by low-order differential equations.

  1. A time-varying magnetic flux concentrator

    NASA Astrophysics Data System (ADS)

    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.

  2. Randomly Distributed Delayed Communication and Coherent Swarm Patterns

    PubMed Central

    Lindley, Brandon; Mier-y-Teran-Romero, Luis; Schwartz, Ira B.

    2013-01-01

    Previously we showed how delay communication between globally coupled self-propelled agents causes new spatio-temporal patterns to arise when the delay coupling is fixed among all agents [1]. In this paper, we show how discrete, randomly distributed delays affect the dynamical patterns. In particular, we investigate how the standard deviation of the time delay distribution affects the stability of the different patterns as well as the switching probability between coherent states. PMID:24309679

  3. Randomly Distributed Delayed Communication and Coherent Swarm Patterns.

    PubMed

    Lindley, Brandon; Mier-Y-Teran-Romero, Luis; Schwartz, Ira B

    2012-01-01

    Previously we showed how delay communication between globally coupled self-propelled agents causes new spatio-temporal patterns to arise when the delay coupling is fixed among all agents [1]. In this paper, we show how discrete, randomly distributed delays affect the dynamical patterns. In particular, we investigate how the standard deviation of the time delay distribution affects the stability of the different patterns as well as the switching probability between coherent states. PMID:24309679

  4. Controlling Contagion Processes in Time Varying Networks

    NASA Astrophysics Data System (ADS)

    Liu, Suyu; Perra, Nicola; Karsai, Marton; Vespignani, Alessandro

    2013-03-01

    The vast majority of strategies aimed at controlling contagion and spreading processes on networks consider the connectivity pattern of the system as quenched. In this paper, we consider the class of activity driven networks to analytically evaluate how different control strategies perform in time-varying networks. We consider the limit in which the evolution of the structure of the network and the spreading process are simultaneous yet independent. We analyze three control strategies based on node's activity patterns to decide the removal/immunization of nodes. We find that targeted strategies aimed at the removal of active nodes outperform by orders of magnitude the widely used random strategies. In time-varying networks however any finite time observation of the network dynamics provides only incomplete information on the nodes' activity and does not allow the precise ranking of the most active nodes as needed to implement targeted strategies. Here we develop a control strategy that focuses on targeting the egocentric time-aggregated network of a small control group of nodes.The presented strategy allows the control of spreading processes by removing a fraction of nodes much smaller than the random strategy while at the same time limiting the observation time on the system.

  5. Motion Editing for Time-Varying Mesh

    NASA Astrophysics Data System (ADS)

    Xu, Jianfeng; Yamasaki, Toshihiko; Aizawa, Kiyoharu

    2008-12-01

    Recently, time-varying mesh (TVM), which is composed of a sequence of mesh models, has received considerable interest due to its new and attractive functions such as free viewpoint and interactivity. TVM captures the dynamic scene of the real world from multiple synchronized cameras. However, it is expensive and time consuming to generate a TVM sequence. In this paper, an editing system is presented to reuse the original data, which reorganizes the motions to obtain a new sequence based on the user requirements. Hierarchical motion structure is observed and parsed in TVM sequences. Then, the representative motions are chosen into a motion database, where a motion graph is constructed to connect those motions with smooth transitions. After the user selects some desired motions from the motion database, the best paths are searched by a modified Dijkstra algorithm to achieve a new sequence. Our experimental results demonstrate that the edited sequences are natural and smooth.

  6. Time varying, multivariate volume data reduction

    SciTech Connect

    Ahrens, James P; Fout, Nathaniel; Ma, Kwan - Liu

    2010-01-01

    Large-scale supercomputing is revolutionizing the way science is conducted. A growing challenge, however, is understanding the massive quantities of data produced by large-scale simulations. The data, typically time-varying, multivariate, and volumetric, can occupy from hundreds of gigabytes to several terabytes of storage space. Transferring and processing volume data of such sizes is prohibitively expensive and resource intensive. Although it may not be possible to entirely alleviate these problems, data compression should be considered as part of a viable solution, especially when the primary means of data analysis is volume rendering. In this paper we present our study of multivariate compression, which exploits correlations among related variables, for volume rendering. Two configurations for multidimensional compression based on vector quantization are examined. We emphasize quality reconstruction and interactive rendering, which leads us to a solution using graphics hardware to perform on-the-fly decompression during rendering. In this paper we present a solution which addresses the need for data reduction in large supercomputing environments where data resulting from simulations occupies tremendous amounts of storage. Our solution employs a lossy encoding scheme to acrueve data reduction with several options in terms of rate-distortion behavior. We focus on encoding of multiple variables together, with optional compression in space and time. The compressed volumes can be rendered directly with commodity graphics cards at interactive frame rates and rendering quality similar to that of static volume renderers. Compression results using a multivariate time-varying data set indicate that encoding multiple variables results in acceptable performance in the case of spatial and temporal encoding as compared to independent compression of variables. The relative performance of spatial vs. temporal compression is data dependent, although temporal compression has the

  7. Efficient Encoding and Rendering of Time-Varying Volume Data

    NASA Technical Reports Server (NTRS)

    Ma, Kwan-Liu; Smith, Diann; Shih, Ming-Yun; Shen, Han-Wei

    1998-01-01

    Visualization of time-varying volumetric data sets, which may be obtained from numerical simulations or sensing instruments, provides scientists insights into the detailed dynamics of the phenomenon under study. This paper describes a coherent solution based on quantization, coupled with octree and difference encoding for visualizing time-varying volumetric data. Quantization is used to attain voxel-level compression and may have a significant influence on the performance of the subsequent encoding and visualization steps. Octree encoding is used for spatial domain compression, and difference encoding for temporal domain compression. In essence, neighboring voxels may be fused into macro voxels if they have similar values, and subtrees at consecutive time steps may be merged if they are identical. The software rendering process is tailored according to the tree structures and the volume visualization process. With the tree representation, selective rendering may be performed very efficiently. Additionally, the I/O costs are reduced. With these combined savings, a higher level of user interactivity is achieved. We have studied a variety of time-varying volume datasets, performed encoding based on data statistics, and optimized the rendering calculations wherever possible. Preliminary tests on workstations have shown in many cases tremendous reduction by as high as 90% in both storage space and inter-frame delay.

  8. Audibility of time-varying signals in time-varying backgrounds: Model and data

    NASA Astrophysics Data System (ADS)

    Moore, Brian C. J.; Glasberg, Brian R.

    2001-05-01

    We have described a model for calculating the partial loudness of a steady signal in the presence of a steady background sound [Moore et al., J. Audio Eng. Soc. 45, 224-240 (1997)]. We have also described a model for calculating the loudness of time-varying signals [B. R. Glasberg and B. C. J. Moore, J. Audio Eng. Soc. 50, 331-342 (2002)]. These two models have been combined to allow calculation of the partial loudness of a time-varying signal in the presence of a time-varying background. To evaluate the model, psychometric functions for the detection of a variety of time-varying signals (e.g., telephone ring tones) have been measured in a variety of background sounds sampled from everyday listening situations, using a two-alternative forced-choice task. The different signals and backgrounds were interleaved, to create stimulus uncertainty, as would occur in everyday life. The data are used to relate the detectability index, d', to the calculated partial loudness. In this way, the model can be used to predict the detectability of any signal, based on its calculated partial loudness. [Work supported by MRC (UK) and by Nokia.

  9. Reaching a consensus: a discrete nonlinear time-varying case

    NASA Astrophysics Data System (ADS)

    Saburov, M.; Saburov, K.

    2016-07-01

    In this paper, we have considered a nonlinear protocol for a structured time-varying and synchronous multi-agent system. By means of cubic triple stochastic matrices, we present an opinion sharing dynamics of the multi-agent system as a trajectory of a non-homogeneous system of cubic triple stochastic matrices. We show that the multi-agent system eventually reaches to a consensus if either of the following two conditions is satisfied: (1) every member of the group people has a positive subjective distribution on the given task after some revision steps or (2) all entries of some cubic triple stochastic matrix are positive.

  10. Compensation of distributed delays in integrated communication and control systems

    NASA Technical Reports Server (NTRS)

    Ray, Asok; Luck, Rogelio

    1991-01-01

    The concept, analysis, implementation, and verification of a method for compensating delays that are distributed between the sensors, controller, and actuators within a control loop are discussed. With the objective of mitigating the detrimental effects of these network induced delays, a predictor-controller algorithm was formulated and analyzed. Robustness of the delay compensation algorithm was investigated relative to parametric uncertainties in plant modeling. The delay compensator was experimentally verified on an IEEE 802.4 network testbed for velocity control of a DC servomotor.

  11. Stochastic parameter estimation in nonlinear time-delayed vibratory systems with distributed delay

    NASA Astrophysics Data System (ADS)

    Torkamani, Shahab; Butcher, Eric A.

    2013-07-01

    The stochastic estimation of parameters and states in linear and nonlinear time-delayed vibratory systems with distributed delay is explored. The approach consists of first employing a continuous time approximation to approximate the delayed integro-differential system with a large set of ordinary differential equations having stochastic excitations. Then the problem of state and parameter estimation in the resulting stochastic ordinary differential system is represented as an optimal filtering problem using a state augmentation technique. By adapting the extended Kalman-Bucy filter to the augmented filtering problem, the unknown parameters of the time-delayed system are estimated from noise-corrupted, possibly incomplete measurements of the states. Similarly, the upper bound of the distributed delay can also be estimated by the proposed technique. As an illustrative example to a practical problem in vibrations, the parameter, delay upper bound, and state estimation from noise-corrupted measurements in a distributed force model widely used for modeling machine tool vibrations in the turning operation is investigated.

  12. Parallel Rendering of Large Time-Varying Volume Data

    NASA Technical Reports Server (NTRS)

    Garbutt, Alexander E.

    2005-01-01

    Interactive visualization of large time-varying 3D volume datasets has been and still is a great challenge to the modem computational world. It stretches the limits of the memory capacity, the disk space, the network bandwidth and the CPU speed of a conventional computer. In this SURF project, we propose to develop a parallel volume rendering program on SGI's Prism, a cluster computer equipped with state-of-the-art graphic hardware. The proposed program combines both parallel computing and hardware rendering in order to achieve an interactive rendering rate. We use 3D texture mapping and a hardware shader to implement 3D volume rendering on each workstation. We use SGI's VisServer to enable remote rendering using Prism's graphic hardware. And last, we will integrate this new program with ParVox, a parallel distributed visualization system developed at JPL. At the end of the project, we Will demonstrate remote interactive visualization using this new hardware volume renderer on JPL's Prism System using a time-varying dataset from selected JPL applications.

  13. Holographic cinematography of time-varying reflecting and time-varying phase objects using a Nd:YAG laser

    NASA Technical Reports Server (NTRS)

    Decker, A. J.

    1982-01-01

    The use of a Nd:YAG laser to record holographic motion pictures of time-varying reflecting objects and time-varying phase objects is discussed. Sample frames from both types of holographic motion pictures are presented. The holographic system discussed is intended for three-dimensional flow visualization of the time-varying flows that occur in jet-engine components.

  14. Flexible Demand Management under Time-Varying Prices

    NASA Astrophysics Data System (ADS)

    Liang, Yong

    In this dissertation, the problem of flexible demand management under time-varying prices is studied. This generic problem has many applications, which usually have multiple periods in which decisions on satisfying demand need to be made, and prices in these periods are time-varying. Examples of such applications include multi-period procurement problem, operating room scheduling, and user-end demand scheduling in the Smart Grid, where the last application is used as the main motivating story throughout the dissertation. The current grid is experiencing an upgrade with lots of new designs. What is of particular interest is the idea of passing time-varying prices that reflect electricity market conditions to end users as incentives for load shifting. One key component, consequently, is the demand management system at the user-end. The objective of the system is to find the optimal trade-off between cost saving and discomfort increment resulted from load shifting. In this dissertation, we approach this problem from the following aspects: (1) construct a generic model, solve for Pareto optimal solutions, and analyze the robust solution that optimizes the worst-case payoffs, (2) extend to a distribution-free model for multiple types of demand (appliances), for which an approximate dynamic programming (ADP) approach is developed, and (3) design other efficient algorithms for practical purposes of the flexible demand management system. We first construct a novel multi-objective flexible demand management model, in which there are a finite number of periods with time-varying prices, and demand arrives in each period. In each period, the decision maker chooses to either satisfy or defer outstanding demand to minimize costs and discomfort over a certain number of periods. We consider both the deterministic model, models with stochastic demand or prices, and when only partial information about the stochastic demand or prices is known. We first analyze the stochastic

  15. Propagation of phase modulation signals in time-varying plasma

    NASA Astrophysics Data System (ADS)

    Yang, Min; Li, Xiaoping; Wang, Di; Liu, Yanming; He, Pan

    2016-05-01

    The effects of time-varying plasma to the propagation of phase modulation signals are investigated in this paper. Through theoretical analysis, the mechanism of the interaction between the time-varying plasma and the phase modulation signal is given. A time-varying plasma generator which could produce arbitrary time-varying plasma is built by adjusting the discharge power. A comparison of results from experiment and simulation prove that the time-varying plasma could cause the special rotation of QPSK (Quadrature Phase Shift Keying) constellation, and the mechanism of constellation point's rotation is analyzed. Additionally, the experimental results of the QPSK signals' EVM (Error Vector Magnitude) after time-varying and time-invariant plasma with different ωp/ω are given. This research could be used to improve the TT&C (Tracking Telemeter and Command) system of re-entry vehicles.

  16. Visualizing Time-Varying Distribution Data in EOS Application

    NASA Technical Reports Server (NTRS)

    Shen, Han-Wei

    2004-01-01

    In this research, we have developed several novel visualization methods for spatial probability density function data. Our focus has been on 2D spatial datasets, where each pixel is a random variable, and has multiple samples which are the results of experiments on that random variable. We developed novel clustering algorithms as a means to reduce the information contained in these datasets; and investigated different ways of interpreting and clustering the data.

  17. Noise Induced Pattern Switching in Randomly Distributed Delayed Swarms.

    PubMed

    Lindley, Brandon; Mier-Y-Teran-Romero, Luis; Schwartz, Ira B

    2013-01-01

    We study the effects of noise on the dynamics of a system of coupled self-propelling particles in the case where the coupling is time-delayed, and the delays are discrete and randomly generated. Previous work has demonstrated that the stability of a class of emerging patterns depends upon all moments of the time delay distribution, and predicts their bifurcation parameter ranges. Near the bifurcations of these patterns, noise may induce a transition from one type of pattern to another. We study the onset of these noise-induced swarm re-organizations by numerically simulating the system over a range of noise intensities and for various distributions of the delays. Interestingly, there is a critical noise threshold above which the system is forced to transition from a less organized state to a more organized one. We explore this phenomenon by quantifying this critical noise threshold, and note that transition time between states varies as a function of both the noise intensity and delay distribution. PMID:25382931

  18. Noise Induced Pattern Switching in Randomly Distributed Delayed Swarms

    PubMed Central

    Lindley, Brandon; Mier-y-Teran-Romero, Luis; Schwartz, Ira B.

    2013-01-01

    We study the effects of noise on the dynamics of a system of coupled self-propelling particles in the case where the coupling is time-delayed, and the delays are discrete and randomly generated. Previous work has demonstrated that the stability of a class of emerging patterns depends upon all moments of the time delay distribution, and predicts their bifurcation parameter ranges. Near the bifurcations of these patterns, noise may induce a transition from one type of pattern to another. We study the onset of these noise-induced swarm re-organizations by numerically simulating the system over a range of noise intensities and for various distributions of the delays. Interestingly, there is a critical noise threshold above which the system is forced to transition from a less organized state to a more organized one. We explore this phenomenon by quantifying this critical noise threshold, and note that transition time between states varies as a function of both the noise intensity and delay distribution. PMID:25382931

  19. Impacts of Time Delays on Distributed Algorithms for Economic Dispatch

    SciTech Connect

    Yang, Tao; Wu, Di; Sun, Yannan; Lian, Jianming

    2015-07-26

    Economic dispatch problem (EDP) is an important problem in power systems. It can be formulated as an optimization problem with the objective to minimize the total generation cost subject to the power balance constraint and generator capacity limits. Recently, several consensus-based algorithms have been proposed to solve EDP in a distributed manner. However, impacts of communication time delays on these distributed algorithms are not fully understood, especially for the case where the communication network is directed, i.e., the information exchange is unidirectional. This paper investigates communication time delay effects on a distributed algorithm for directed communication networks. The algorithm has been tested by applying time delays to different types of information exchange. Several case studies are carried out to evaluate the effectiveness and performance of the algorithm in the presence of time delays in communication networks. It is found that time delay effects have negative effects on the convergence rate, and can even result in an incorrect converge value or fail the algorithm to converge.

  20. Dynamics of strongly coupled spatially distributed logistic equations with delay

    NASA Astrophysics Data System (ADS)

    Kashchenko, I. S.; Kashchenko, S. A.

    2015-04-01

    The dynamics of a system of two logistic delay equations with spatially distributed coupling is studied. The coupling coefficient is assumed to be sufficiently large. Special nonlinear systems of parabolic equations are constructed such that the behavior of their solutions is determined in the first approximation by the dynamical properties of the original system.

  1. Common community structure in time-varying networks

    NASA Astrophysics Data System (ADS)

    Zhang, Shihua; Zhao, Junfei; Zhang, Xiang-Sun

    2012-05-01

    In this report we introduce the concept of common community structure in time-varying networks. We propose a novel optimization algorithm to rapidly detect common community structure in such networks. Both theoretical and numerical results show that the proposed method not only can resolve detailed common communities, but also can effectively identify the dynamical phenomena in time-varying networks.

  2. Time varying voltage combustion control and diagnostics sensor

    DOEpatents

    Chorpening, Benjamin T.; Thornton, Jimmy D.; Huckaby, E. David; Fincham, William

    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.

  3. Invited Commentary: Taking Advantage of Time-Varying Neighborhood Environments

    PubMed Central

    Lovasi, Gina S.; Goldsmith, Jeff

    2014-01-01

    Neighborhood built environment characteristics may encourage physical activity, but previous literature on the topic has been critiqued for its reliance on cross-sectional data. In this issue of the Journal, Knuiman et al. (Am J Epidemiol. 2014;180(5):453–461) present longitudinal analyses of built environment characteristics as predictors of neighborhood transportation walking. We take this opportunity to comment on self-selection, exposure measurement, outcome form, analyses, and future directions. The Residential Environments (RESIDE) Study follows individuals as they relocate into new housing. The outcome, which is neighborhood transportation walking, has several important limitations with regards to public health relevance, dichotomization, and potential bias. Three estimation strategies were pursued: marginal modeling, random-effects modeling, and fixed-effects modeling. Knuiman et al. defend fixed-effects modeling as the one that most effectively controls for unmeasured time-invariant confounders, and it will do so as long as confounders have a constant effect over time. Fixed-effects modeling requires no distributional assumptions regarding the heterogeneity of subject-specific effects. Associations of time-varying neighborhood characteristics with walking are interpreted at the subject level for both fixed- and random-effects models. Cross-sectional data have set the stage for the next generation of neighborhood research, which should leverage longitudinal changes in both place and health behaviors. Careful interpretation is warranted as longitudinal data become available for analysis. PMID:25117659

  4. Estimation of Time-Varying Pilot Model Parameters

    NASA Technical Reports Server (NTRS)

    Zaal, Peter M. T.; Sweet, Barbara T.

    2011-01-01

    Human control behavior is rarely completely stationary over time due to fatigue or loss of attention. In addition, there are many control tasks for which human operators need to adapt their control strategy to vehicle dynamics that vary in time. In previous studies on the identification of time-varying pilot control behavior wavelets were used to estimate the time-varying frequency response functions. However, the estimation of time-varying pilot model parameters was not considered. Estimating these parameters can be a valuable tool for the quantification of different aspects of human time-varying manual control. This paper presents two methods for the estimation of time-varying pilot model parameters, a two-step method using wavelets and a windowed maximum likelihood estimation method. The methods are evaluated using simulations of a closed-loop control task with time-varying pilot equalization and vehicle dynamics. Simulations are performed with and without remnant. Both methods give accurate results when no pilot remnant is present. The wavelet transform is very sensitive to measurement noise, resulting in inaccurate parameter estimates when considerable pilot remnant is present. Maximum likelihood estimation is less sensitive to pilot remnant, but cannot detect fast changes in pilot control behavior.

  5. Probability distributed time delays: integrating spatial effects into temporal models

    PubMed Central

    2010-01-01

    Background In order to provide insights into the complex biochemical processes inside a cell, modelling approaches must find a balance between achieving an adequate representation of the physical phenomena and keeping the associated computational cost within reasonable limits. This issue is particularly stressed when spatial inhomogeneities have a significant effect on system's behaviour. In such cases, a spatially-resolved stochastic method can better portray the biological reality, but the corresponding computer simulations can in turn be prohibitively expensive. Results We present a method that incorporates spatial information by means of tailored, probability distributed time-delays. These distributions can be directly obtained by single in silico or a suitable set of in vitro experiments and are subsequently fed into a delay stochastic simulation algorithm (DSSA), achieving a good compromise between computational costs and a much more accurate representation of spatial processes such as molecular diffusion and translocation between cell compartments. Additionally, we present a novel alternative approach based on delay differential equations (DDE) that can be used in scenarios of high molecular concentrations and low noise propagation. Conclusions Our proposed methodologies accurately capture and incorporate certain spatial processes into temporal stochastic and deterministic simulations, increasing their accuracy at low computational costs. This is of particular importance given that time spans of cellular processes are generally larger (possibly by several orders of magnitude) than those achievable by current spatially-resolved stochastic simulators. Hence, our methodology allows users to explore cellular scenarios under the effects of diffusion and stochasticity in time spans that were, until now, simply unfeasible. Our methodologies are supported by theoretical considerations on the different modelling regimes, i.e. spatial vs. delay-temporal, as indicated

  6. Reduction of chemical reaction networks through delay distributions

    NASA Astrophysics Data System (ADS)

    Barrio, Manuel; Leier, André; Marquez-Lago, Tatiana T.

    2013-03-01

    Accurate modelling and simulation of dynamic cellular events require two main ingredients: an adequate description of key chemical reactions and simulation of such chemical events in reasonable time spans. Quite logically, posing the right model is a crucial step for any endeavour in Computational Biology. However, more often than not, it is the associated computational costs which actually limit our capabilities of representing complex cellular behaviour. In this paper, we propose a methodology aimed at representing chains of chemical reactions by much simpler, reduced models. The abridgement is achieved by generation of model-specific delay distribution functions, consecutively fed to a delay stochastic simulation algorithm. We show how such delay distributions can be analytically described whenever the system is solely composed of consecutive first-order reactions, with or without additional "backward" bypass reactions, yielding an exact reduction. For models including other types of monomolecular reactions (constitutive synthesis, degradation, or "forward" bypass reactions), we discuss why one must adopt a numerical approach for its accurate stochastic representation, and propose two alternatives for this. In these cases, the accuracy depends on the respective numerical sample size. Our model reduction methodology yields significantly lower computational costs while retaining accuracy. Quite naturally, computational costs increase alongside network size and separation of time scales. Thus, we expect our model reduction methodologies to significantly decrease computational costs in these instances. We anticipate the use of delays in model reduction will greatly alleviate some of the current restrictions in simulating large sets of chemical reactions, largely applicable in pharmaceutical and biological research.

  7. Time varying networks and the weakness of strong ties

    NASA Astrophysics Data System (ADS)

    Karsai, Márton; Perra, Nicola; Vespignani, Alessandro

    2014-02-01

    In most social and information systems the activity of agents generates rapidly evolving time-varying networks. The temporal variation in networks' connectivity patterns and the ongoing dynamic processes are usually coupled in ways that still challenge our mathematical or computational modelling. Here we analyse a mobile call dataset and find a simple statistical law that characterize the temporal evolution of users' egocentric networks. We encode this observation in a reinforcement process defining a time-varying network model that exhibits the emergence of strong and weak ties. We study the effect of time-varying and heterogeneous interactions on the classic rumour spreading model in both synthetic, and real-world networks. We observe that strong ties severely inhibit information diffusion by confining the spreading process among agents with recurrent communication patterns. This provides the counterintuitive evidence that strong ties may have a negative role in the spreading of information across networks.

  8. Time varying networks and the weakness of strong ties.

    PubMed

    Karsai, Márton; Perra, Nicola; Vespignani, Alessandro

    2014-01-01

    In most social and information systems the activity of agents generates rapidly evolving time-varying networks. The temporal variation in networks' connectivity patterns and the ongoing dynamic processes are usually coupled in ways that still challenge our mathematical or computational modelling. Here we analyse a mobile call dataset and find a simple statistical law that characterize the temporal evolution of users' egocentric networks. We encode this observation in a reinforcement process defining a time-varying network model that exhibits the emergence of strong and weak ties. We study the effect of time-varying and heterogeneous interactions on the classic rumour spreading model in both synthetic, and real-world networks. We observe that strong ties severely inhibit information diffusion by confining the spreading process among agents with recurrent communication patterns. This provides the counterintuitive evidence that strong ties may have a negative role in the spreading of information across networks. PMID:24510159

  9. Statistical analysis of the electrical breakdown time delay distributions in krypton

    NASA Astrophysics Data System (ADS)

    Maluckov, Čedomir A.; Karamarković, Jugoslav P.; Radović, Miodrag K.; Pejović, Momčilo M.

    2006-08-01

    The statistical analysis of the experimentally observed electrical breakdown time delay distributions in the krypton-filled diode tube at 2.6mbar is presented. The experimental distributions are obtained on the basis of 1000 successive and independent measurements. The theoretical electrical breakdown time delay distribution is evaluated as the convolution of the statistical time delay with exponential, and discharge formative time with Gaussian distribution. The distribution parameters are estimated by the stochastic modelling of the time delay distributions, and by comparing them with the experimental distributions for different relaxation times, voltages, and intensities of UV radiation. The transition of distribution shapes, from Gaussian-type to the exponential-like, is investigated by calculating the corresponding skewness and excess kurtosis parameters. It is shown that the mathematical model based on the convolution of two random variable distributions describes experimentally obtained time delay distributions and the separation of the total breakdown time delay to the statistical and formative time delay.

  10. Statistical analysis of the electrical breakdown time delay distributions in krypton

    SciTech Connect

    Maluckov, Cedomir A.; Karamarkovic, Jugoslav P.; Radovic, Miodrag K.; Pejovic, Momcilo M.

    2006-08-15

    The statistical analysis of the experimentally observed electrical breakdown time delay distributions in the krypton-filled diode tube at 2.6 mbar is presented. The experimental distributions are obtained on the basis of 1000 successive and independent measurements. The theoretical electrical breakdown time delay distribution is evaluated as the convolution of the statistical time delay with exponential, and discharge formative time with Gaussian distribution. The distribution parameters are estimated by the stochastic modelling of the time delay distributions, and by comparing them with the experimental distributions for different relaxation times, voltages, and intensities of UV radiation. The transition of distribution shapes, from Gaussian-type to the exponential-like, is investigated by calculating the corresponding skewness and excess kurtosis parameters. It is shown that the mathematical model based on the convolution of two random variable distributions describes experimentally obtained time delay distributions and the separation of the total breakdown time delay to the statistical and formative time delay.

  11. Time-varying Reeb Graphs: A Topological Framework Supporting the Analysis of Continuous Time-varying Data

    SciTech Connect

    Mascarenhas, A

    2006-11-28

    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

  12. A dynamic p53-mdm2 model with distributed delay

    NASA Astrophysics Data System (ADS)

    Horhat, Raluca; Horhat, Raul Florin

    2014-12-01

    Specific activator and repressor transcription factors which bind to specific regulator DNA sequences, play an important role in gene activity control. Interactions between genes coding such transcripion factors should explain the different stable or sometimes oscillatory gene activities characteristic for different tissues. In this paper, the dynamic P53-Mdm2 interaction model with distributed delays is investigated. Both weak and Dirac kernels are taken into consideration. For Dirac case, the Hopf bifurcation is investigated. Some numerical examples are finally given for justifying the theoretical results.

  13. Decoupling in linear time-varying multivariable systems

    NASA Technical Reports Server (NTRS)

    Sankaran, V.

    1973-01-01

    The necessary and sufficient conditions for the decoupling of an m-input, m-output, linear time varying dynamical system by state variable feedback is described. The class of feedback matrices which decouple the system are illustrated. Systems which do not satisfy these results are described and systems with disturbances are considered. Some examples are illustrated to clarify the results.

  14. Time varying market efficiency of the GCC stock markets

    NASA Astrophysics Data System (ADS)

    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.

  15. Time-Varying Affective Response for Humanoid Robots

    NASA Astrophysics Data System (ADS)

    Moshkina, Lilia; Arkin, Ronald C.; Lee, Jamee K.; Jung, Hyunryong

    This paper describes the design of a complex time-varying affective architecture. It is an expansion of the TAME architecture (traits, attitudes, moods, and emotions) as applied to humanoid robotics. It particular it is intended to promote effective human-robot interaction by conveying the robot’s affective state to the user in an easy-to-interpret manner.

  16. Neuronal Mechanisms and Transformations Encoding Time-Varying Signals.

    PubMed

    Petkov, Christopher I; Bendor, Daniel

    2016-08-17

    Sensation in natural environments requires the analysis of time-varying signals. While previous work has uncovered how a signal's temporal rate is represented by neurons in sensory cortex, in this issue of Neuron, new evidence from Gao et al. (2016) provides insights on the underlying mechanisms. PMID:27537481

  17. On the form of the forgetting function: the effects of arithmetic and logarithmic distributions of delays.

    PubMed Central

    Sargisson, Rebecca J; White, K Geoffrey

    2003-01-01

    Forgetting functions with 18 delay intervals were generated for delayed matching-to-sample performance in pigeons. Delay interval variation was achieved by arranging five different sets of five delays across daily sessions. In different conditions, the delays were distributed in arithmetic or logarithmic series. There was no convincing evidence for different effects on discriminability of the distributions of different delays. The mean data were better fitted by some mathematical functions than by others, but the best-fitting functions depended on the distribution of delays. In further conditions with a fixed set of five delays, discriminability was higher with a logarithmic distribution of delays than with an arithmetic distribution. This result is consistent with the treatment of the forgetting function in terms of generalization decrement. PMID:14964709

  18. Almost periodic solutions for Lotka-Volterra systems with delays

    NASA Astrophysics Data System (ADS)

    Liang, Yanlai; Li, Lijie; Chen, Lansun

    2009-09-01

    This paper studies a general class of delayed almost periodic Lotka-Volterra system with time-varying delays and distributed delays. By using the definition of almost periodic function, the sufficient conditions for the existence and uniqueness of globally exponentially stable almost periodic solution are obtained. The conditions can be easily reduced to special cases of cooperative systems and competitive systems.

  19. The impact of command signal power distribution, processing delays, and speed scaling on neurally-controlled devices

    NASA Astrophysics Data System (ADS)

    Marathe, A. R.; Taylor, D. M.

    2015-08-01

    Objective. Decoding algorithms for brain-machine interfacing (BMI) are typically only optimized to reduce the magnitude of decoding errors. Our goal was to systematically quantify how four characteristics of BMI command signals impact closed-loop performance: (1) error magnitude, (2) distribution of different frequency components in the decoding errors, (3) processing delays, and (4) command gain. Approach. To systematically evaluate these different command features and their interactions, we used a closed-loop BMI simulator where human subjects used their own wrist movements to command the motion of a cursor to targets on a computer screen. Random noise with three different power distributions and four different relative magnitudes was added to the ongoing cursor motion in real time to simulate imperfect decoding. These error characteristics were tested with four different visual feedback delays and two velocity gains. Main results. Participants had significantly more trouble correcting for errors with a larger proportion of low-frequency, slow-time-varying components than they did with jittery, higher-frequency errors, even when the error magnitudes were equivalent. When errors were present, a movement delay often increased the time needed to complete the movement by an order of magnitude more than the delay itself. Scaling down the overall speed of the velocity command can actually speed up target acquisition time when low-frequency errors and delays are present. Significance. This study is the first to systematically evaluate how the combination of these four key command signal features (including the relatively-unexplored error power distribution) and their interactions impact closed-loop performance independent of any specific decoding method. The equations we derive relating closed-loop movement performance to these command characteristics can provide guidance on how best to balance these different factors when designing BMI systems. The equations reported

  20. Efficient Estimation of Time-Varying Intrinsic and Reflex Stiffness

    PubMed Central

    Ludvig, Daniel; Perreault, Eric J.; Kearney, Robert E.

    2013-01-01

    Dynamic joint stiffness defines the dynamic relationship between the position of the joint and the torque acting about it; hence it is important in the control of movement and posture. Joint stiffness consists of two components: intrinsic stiffness and reflex stiffness. Measuring intrinsic and reflex torques directly is not possible, thus estimating intrinsic and reflex stiffness is challenging. A further complication is that both intrinsic and reflex stiffness vary with joint position and torque. Thus, the measurement of dynamic joint stiffness during movement requires a time-varying algorithm. Recently we described an algorithm to estimate time-varying intrinsic and reflex stiffness and demonstrated its application. This paper describes modifications to that algorithm that significantly improves the accuracy of the estimates it generates while increasing its computational efficiency by a factor of seven. PMID:22255247

  1. Stabilising compensators for linear time-varying differential systems

    NASA Astrophysics Data System (ADS)

    Oberst, Ulrich

    2016-04-01

    In this paper, we describe a constructive test to decide whether a given linear time-varying (LTV) differential system admits a stabilising compensator for the control tasks of tracking, disturbance rejection or model matching and construct and parametrise all of them if at least one exists. In analogy to the linear time-invariant (LTI) case, the ring of stable rational functions, noncommutative in the LTV situation, and the Kučera-Youla parametrisation play prominent parts in the theory. We transfer Blumthaler's thesis from the LTI to the LTV case and sharpen, complete and simplify the corresponding results in the book 'Linear Time-Varying Systems' by Bourlès and Marinescu.

  2. Scaling properties in time-varying networks with memory

    NASA Astrophysics Data System (ADS)

    Kim, Hyewon; Ha, Meesoon; Jeong, Hawoong

    2015-12-01

    The formation of network structure is mainly influenced by an individual node's activity and its memory, where activity can usually be interpreted as the individual inherent property and memory can be represented by the interaction strength between nodes. In our study, we define the activity through the appearance pattern in the time-aggregated network representation, and quantify the memory through the contact pattern of empirical temporal networks. To address the role of activity and memory in epidemics on time-varying networks, we propose temporal-pattern coarsening of activity-driven growing networks with memory. In particular, we focus on the relation between time-scale coarsening and spreading dynamics in the context of dynamic scaling and finite-size scaling. Finally, we discuss the universality issue of spreading dynamics on time-varying networks for various memory-causality tests.

  3. Energy harvesting under excitations of time-varying frequency

    NASA Astrophysics Data System (ADS)

    Seuaciuc-Osório, Thiago; Daqaq, Mohammed F.

    2010-06-01

    The design and optimization of energy harvesters capable of scavenging energy efficiently from realistic environments require a deep understanding of their transduction under non-stationary and random excitations. Otherwise, their small energy outputs can be further decreased lowering their efficiency and rendering many critical and possibly life saving technologies inefficient. As a first step towards this critical understanding, this effort investigates the response of energy harvesters to harmonic excitations of time-varying frequency. Such excitations can be used to represent the behavior of realistic vibratory environments whose frequency varies or drifts with time. Specifically, we consider a piezoelectric stack-type harvester subjected to a harmonic excitation of constant amplitude and a sinusoidally varying frequency. We analyze the response of the harvester in the fixed-frequency scenario then use the Jacobi-Anger's expansion to analyze the response in the time-varying case. We obtain analytical expressions for the harvester's response, output voltage, and power. In-depth analysis of the attained results reveals that the solution to the more complex time-varying frequency can be understood through a process which "samples" the fixed-frequency response curve at a discrete and fixed frequency interval then multiplies the response by proper weights. Extensive discussions addressing the effect of the excitation parameters on the output power is presented leading to some initial suggestions pertinent to the harvester's design and optimization in the sinusoidally varying frequency case.

  4. Downdating a time-varying square root information filter

    NASA Technical Reports Server (NTRS)

    Muellerschoen, Ronald J.

    1990-01-01

    A new method to efficiently downdate an estimate and covariance generated by a discrete time Square Root Information Filter (SRIF) is presented. The method combines the QR factor downdating algorithm of Gill and the decentralized SRIF algorithm of Bierman. Efficient removal of either measurements or a priori information is possible without loss of numerical integrity. Moreover, the method includes features for detecting potential numerical degradation. Performance on a 300 parameter system with 5800 data points shows that the method can be used in real time and hence is a promising tool for interactive data analysis. Additionally, updating a time-varying SRIF filter with either additional measurements or a priori information proceeds analogously.

  5. Recursive time-varying filter banks for subband image coding

    NASA Technical Reports Server (NTRS)

    Smith, Mark J. T.; Chung, Wilson C.

    1992-01-01

    Filter banks and wavelet decompositions that employ recursive filters have been considered previously and are recognized for their efficiency in partitioning the frequency spectrum. This paper presents an analysis of a new infinite impulse response (IIR) filter bank in which these computationally efficient filters may be changed adaptively in response to the input. The filter bank is presented and discussed in the context of finite-support signals with the intended application in subband image coding. In the absence of quantization errors, exact reconstruction can be achieved and by the proper choice of an adaptation scheme, it is shown that IIR time-varying filter banks can yield improvement over conventional ones.

  6. Image Cross-Correlation Analysis of Time Varying Flows.

    PubMed

    Marquezin, Cassia A; Ceffa, Nicolò G; Cotelli, Franco; Collini, Maddalena; Sironi, Laura; Chirico, Giuseppe

    2016-07-19

    In vivo studies of blood circulation pathologies have great medical relevance and need methods for the characterization of time varying flows at high spatial and time resolution in small animal models. We test here the efficacy of the combination of image correlation techniques and single plane illumination microscopy (SPIM) in characterizing time varying flows in vitro and in vivo. As indicated by numerical simulations and by in vitro experiments on straight capillaries, the complex analytical form of the cross-correlation function for SPIM detection can be simplified, in conditions of interest for hemodynamics, to a superposition of Gaussian components, easily amenable to the analysis of variable flows. The possibility to select a wide field of view with a good spatial resolution along the collection optical axis and to compute the cross-correlation between regions of interest at varying distances on a single time stack of images allows one to single out periodic flow components from spurious peaks on the cross-correlation functions and to infer the duration of each flow component. We apply this cross-correlation analysis to the blood flow in Zebrafish embryos at 4 days after fertilization, measuring the average speed and the duration of the systolic and diastolic phases. PMID:27348197

  7. Stochastic analysis of epidemics on adaptive time varying networks

    NASA Astrophysics Data System (ADS)

    Kotnis, Bhushan; Kuri, Joy

    2013-06-01

    Many studies investigating the effect of human social connectivity structures (networks) and human behavioral adaptations on the spread of infectious diseases have assumed either a static connectivity structure or a network which adapts itself in response to the epidemic (adaptive networks). However, human social connections are inherently dynamic or time varying. Furthermore, the spread of many infectious diseases occur on a time scale comparable to the time scale of the evolving network structure. Here we aim to quantify the effect of human behavioral adaptations on the spread of asymptomatic infectious diseases on time varying networks. We perform a full stochastic analysis using a continuous time Markov chain approach for calculating the outbreak probability, mean epidemic duration, epidemic reemergence probability, etc. Additionally, we use mean-field theory for calculating epidemic thresholds. Theoretical predictions are verified using extensive simulations. Our studies have uncovered the existence of an “adaptive threshold,” i.e., when the ratio of susceptibility (or infectivity) rate to recovery rate is below the threshold value, adaptive behavior can prevent the epidemic. However, if it is above the threshold, no amount of behavioral adaptations can prevent the epidemic. Our analyses suggest that the interaction patterns of the infected population play a major role in sustaining the epidemic. Our results have implications on epidemic containment policies, as awareness campaigns and human behavioral responses can be effective only if the interaction levels of the infected populace are kept in check.

  8. Optimal transport in time-varying small-world networks

    NASA Astrophysics Data System (ADS)

    Chen, Qu; Qian, Jiang-Hai; Zhu, Liang; Han, Ding-Ding

    2016-03-01

    The time-order of interactions, which is regulated by some intrinsic activity, surely plays a crucial role regarding the transport efficiency of transportation systems. Here we study the optimal transport structure by measure of the length of time-respecting paths. Our network is built from a two-dimensional regular lattice, and long-range connections are allocated with probability Pi j˜rij -α , where ri j is the Manhattan distance. By assigning each shortcut an activity rate subjected to its geometric distance τi j˜rij -C , long-range links become active intermittently, leading to the time-varying dynamics. We show that for 0 time-varying transportation networks. Empirical studies on British Airways and Austrian Airlines provide consistent evidence with our conclusion.

  9. Evaluating multivariate visualizations on time-varying data

    NASA Astrophysics Data System (ADS)

    Livingston, Mark A.; Decker, Jonathan W.; Ai, Zhuming

    2013-01-01

    Multivariate visualization techniques have been applied to a wide variety of visual analysis tasks and a broad range of data types and sources. Their utility has been evaluated in a modest range of simple analysis tasks. In this work, we extend our previous task to a case of time-varying data. We implemented ve visualizations of our synthetic test data: three previously evaluated techniques (Data-driven Spots, Oriented Slivers, and Attribute Blocks), one hybrid of the rst two that we call Oriented Data-driven Spots, and an implementation of Attribute Blocks that merges the temporal slices. We conducted a user study of these ve techniques. Our previous nding (with static data) was that users performed best when the density of the target (as encoded in the visualization) was either highest or had the highest ratio to non-target features. The time-varying presentations gave us a wider range of density and density gains from which to draw conclusions; we now see evidence for the density gain as the perceptual measure, rather than the absolute density.

  10. Integrated Sachs-Wolfe effect in time varying vacuum model

    SciTech Connect

    Wang, Y. T.; Gui, Y. X.; Xu, L. X.; Lu, J. B.

    2010-04-15

    The integrated Sachs-Wolfe (ISW) effect is an important implication for dark energy. In this paper, we have calculated the power spectrum of the ISW effect in the time varying vacuum cosmological model, where the model parameter {beta}=4.407 is obtained by the observational constraint of the growth rate. It is found that the source of the ISW effect is not only affected by the different evolutions of the Hubble function H(a) and the dimensionless matter density {Omega}{sub m}(a), but also by the different growth function D{sub +}(a), all of which are changed due to the presence of a matter production term in the time varying vacuum model. However, the difference of the ISW effect in the {Lambda}(t)CDM model and the {Lambda}CDM model is lessened to a certain extent because of the integration from the time of last scattering to the present. It is implied that the observations of the galaxies with high redshift are required to distinguish the two models.

  11. Controlling Contagion Processes in Time-Varying Networks

    NASA Astrophysics Data System (ADS)

    Perra, Nicola; Liu, Suyu; Karsai, Marton; Vespignani, Alessandro

    2014-03-01

    The vast majority of strategies aimed at controlling contagion processes on networks considers the connectivity pattern of the system as either quenched or annealed. However, in the real world many networks are highly dynamical and evolve in time concurrently to the contagion process. Here, we derive an analytical framework for the study of control strategies specifically devised for time-varying networks. We consider the removal/immunization of individual nodes according the their activity in the network and develop a block variable mean-field approach that allows the derivation of the equations describing the evolution of the contagion process concurrently to the network dynamic. We derive the critical immunization threshold and assess the effectiveness of the control strategies. Finally, we validate the theoretical picture by simulating numerically the information spreading process and control strategies in both synthetic networks and a large-scale, real-world mobile telephone call dataset.

  12. Epidemic spreading in time-varying community networks

    SciTech Connect

    Ren, Guangming E-mail: ren-guang-ming@163.com; Wang, Xingyuan E-mail: ren-guang-ming@163.com

    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.

  13. A Symmetric Time-Varying Cluster Rate of Descent Model

    NASA Technical Reports Server (NTRS)

    Ray, Eric S.

    2015-01-01

    A model of the time-varying rate of descent of the Orion vehicle was developed based on the observed correlation between canopy projected area and drag coefficient. This initial version of the model assumes cluster symmetry and only varies the vertical component of velocity. The cluster fly-out angle is modeled as a series of sine waves based on flight test data. The projected area of each canopy is synchronized with the primary fly-out angle mode. The sudden loss of projected area during canopy collisions is modeled at minimum fly-out angles, leading to brief increases in rate of descent. The cluster geometry is converted to drag coefficient using empirically derived constants. A more complete model is under development, which computes the aerodynamic response of each canopy to its local incidence angle.

  14. Chimera states in time-varying complex networks

    NASA Astrophysics Data System (ADS)

    Buscarino, Arturo; Frasca, Mattia; Gambuzza, Lucia Valentina; Hövel, Philipp

    2015-02-01

    Chimera states have been recently found in a variety of different coupling schemes and geometries. In most cases, the underlying coupling structure is considered to be static, while many realistic systems display significant temporal changes in the pattern of connectivity. In this work we investigate a time-varying network made of two coupled populations of Kuramoto oscillators, where the links between the two groups are considered to vary over time. As a main result we find that the network may support stable, breathing, and alternating chimera states. We also find that, when the rate of connectivity changes is fast, compared to the oscillator dynamics, the network may be described by a low-dimensional system of equations. Unlike in the static heterogeneous case, the onset of alternating chimera states is due to the presence of fluctuations, which may be induced either by the finite size of the network or by large switching times.

  15. Circular motion analysis of time-varying bioimpedance.

    PubMed

    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. PMID:26489699

  16. The delay time distribution of massive double compact star mergers

    NASA Astrophysics Data System (ADS)

    Mennekens, N.; Vanbeveren, D.

    2016-05-01

    To investigate the temporal evolution of binary populations, in general, and double compact-star binaries and mergers, in particular, within a galactic evolution context, a very straightforward method is obviously to implement a detailed binary evolutionary model in a galactic chemical evolution code. To our knowledge, the Brussels galactic chemical evolution code is the only one that fully and consistently accounts for the important effects of interacting binaries on the predictions of chemical evolution. With a galactic code that does not explicitly include binaries, the temporal evolution of the population of double compact star binaries and mergers can be estimated with reasonable accuracy if the delay time distribution (DTD) for these mergers is available. The DTD for supernovae type Ia has been studied extensively in the past decade. In the present paper we present the DTD for merging double neutron-star binaries and mixed systems consisting of a neutron star and a black hole. The latter mergers are very promising sites for producing r-process elements, and the DTDs can be used to study the galactic evolution of these elements with a code that does not explicitly account for binaries.

  17. Time-varying effect models for ordinal responses with applications in substance abuse research

    PubMed Central

    Dziak, John J.; Li, Runze; Zimmerman, Marc A.; Buu, Anne

    2014-01-01

    Ordinal responses are very common in longitudinal data collected from substance abuse research or other behavioral research. This study develops a new statistical model with free SAS macro’s that can be applied to characterize time-varying effects on ordinal responses. Our simulation study shows that the ordinal-scale time-varying effects model has very low estimation bias and sometimes offers considerably better performance when fitting data with ordinal responses than a model that treats the response as continuous. Contrary to a common assumption that an ordinal scale with several levels can be treated as continuous, our results indicate that it is not so much the number of levels on the ordinal scale but rather the skewness of the distribution that makes a difference on relative performance of linear versus ordinal models. We use longitudinal data from a well-known study on youth at high risk for substance abuse as a motivating example to demonstrate that the proposed model can characterize the time-varying effect of negative peer influences on alcohol use in a way that is more consistent with the developmental theory and existing literature, in comparison to the linear time-varying effect model. PMID:25209555

  18. Time-varying coherence function for atrial fibrillation detection.

    PubMed

    Lee, Jinseok; Nam, Yunyoung; McManus, David D; Chon, Ki H

    2013-10-01

    We introduce a novel method for the automatic detection of atrial fibrillation (AF) using time-varying coherence functions (TVCF). The TVCF is estimated by the multiplication of two time-varying transfer functions (TVTFs). The two TVTFs are obtained using two adjacent data segments with one data segment as the input signal and the other data segment as the output to produce the first TVTF; the second TVTF is produced by reversing the input and output signals. We found that the resultant TVCF between two adjacent normal sinus rhythm (NSR) segments shows high coherence values (near 1) throughout the entire frequency range. However, if either or both segments partially or fully contain AF, the resultant TVCF is significantly lower than 1. When TVCF was combined with Shannon entropy (SE), we obtained even more accurate AF detection rate of 97.9% for the MIT-BIH atrial fibrillation (AF) database (n = 23) with 128 beat segments. The detection algorithm was tested on four databases using 128 beat segments: the MIT-BIH AF database, the MIT-BIH NSR database ( n = 18), the MIT-BIH Arrhythmia database ( n = 48), and a clinical 24-h Holter AF database ( n = 25). Using the receiver operating characteristic curves from the combination of TVCF and SE, we obtained a sensitivity of 98.2% and specificity of 97.7% for the MIT-BIH AF database. For the MIT-BIH NSR database, we found a specificity of 99.7%. For the MIT-BIH Arrhythmia database, the sensitivity and specificity were 91.1% and 89.7%, respectively. For the clinical database (24-h Holter data), the sensitivity and specificity were 92.3% and 93.6%, respectively. We also found that a short segment (12 beats) also provided accurate AF detection for all databases: sensitivity of 94.7% and specificity of 90.4% for the MIT-BIH AF, specificity of 94.4% for the MIT-BIH-NSR, the sensitivity of 92.4% and specificity of 84.1% for the MIT-BIH arrhythmia, and sensitivity of 93.9% and specificity of 84.4% for the clinical database. The

  19. Delay-dependent exponential state estimators for stochastic neural networks of neutral type with both discrete and distributed delays

    NASA Astrophysics Data System (ADS)

    Wang, Tong; Ding, Yongsheng; Zhang, Lei; Hao, Kuangrong

    2015-03-01

    This paper considered the state estimation for stochastic neural networks of neutral type with discrete and distributed delays. By using available output measurements, the state estimator can approximate the neuron states, and the asymptotic property of the state error is mean square exponential stable and also almost surely exponential stable in the presence of discrete and distributed delays. Under the Lipschitz assumptions for the activation functions and the measurement nonlinearity, a delay-dependent linear matrix inequality (LMI) criterion is proposed to guarantee the existence of the desired estimators by constructing an appropriate Lyapunov-Krasovskii function. It is shown that the existence conditions and the explicit expression of the state estimator can be parameterised in terms of the solution to a LMI. Finally, two numerical examples are presented to demonstrate the validity of the theoretical results and show that the theorem can provide less conservative conditions.

  20. Spatiotemporal Distributions of Migratory Birds: Patchy Models with Delay

    NASA Astrophysics Data System (ADS)

    Gourley, Stephen A.; Liu, Rongsong; Wu, Jianhong

    2010-01-01

    We derive and analyze a mathematical model for the spatiotemporal distribution of a migratory bird species. The birds have specific sites for breeding and winter feeding, and usually several stopover sites along the migration route, and therefore a patch model is the natural choice. However, we also model the journeys of the birds along the flyways, and this is achieved using a continuous space model of reaction-advection type. In this way proper account is taken of flight times and in-flight mortalities which may vary from sector to sector, and this information is featured in the ordinary differential equations for the populations on the patches through the values of the time delays and the model coefficients. The seasonality of the phenomenon is accommodated by having periodic migration and birth rates. The central result of the paper is a very general theorem on the threshold dynamics, obtained using recent results on discrete monotone dynamical systems, for birth functions which are subhomogeneous. For such functions, depending on the spectral radius of a certain operator, either there is a globally attracting periodic solution, or the bird population becomes extinct. Evaluation of the spectral radius is difficult, so we also present, for the particular case of just one stopover site on the migration route, a verifiable sufficient condition for extinction or survival in the form of an attractive periodic solution. This threshold is illustrated numerically using data from the U.S. Geological Survey on the bar-headed goose and its migration to India from its main breeding sites around Lake Qinghai and Mongolia.

  1. Acoustic thermometric reconstruction of a time-varying temperature profile

    NASA Astrophysics Data System (ADS)

    Anosov, A. A.; Kazanskii, A. S.; Mansfel'd, A. D.; Sharakshane, A. S.

    2016-03-01

    The time-varying temperature profiles were reconstructed in an experiment using a thermal acoustic radiation receiving array containing 14 sensors. The temperature was recovered by performing similar experiments using plasticine, as well as in vivo with a human hand. Plasticine preliminarily heated up to 36.5°C and a human hand were placed into water for 50 s at a temperature of 20°C. The core temperature of the plasticine was independently measured using thermocouples. The spatial resolution of the reconstruction in the lateral direction was determined by the distance between neighboring sensors and was equal to10 mm; the averaging time was 10 s. The error in reconstructing the core temperature determined in the experiment with plasticine was 0.5 K. The core temperature of the hand changed with time (in 50 s it decreased from 35 to 34°C) and space (the mean square deviation was 1.5 K). The experiment with the hand revealed that multichannel detection of thermal acoustic radiation using a compact 45 × 36 mm array to reconstruct the temperature profile could be performed during medical procedures.

  2. Ultrasound Background Cancellation Based on Time-Varying Synthesis

    NASA Astrophysics Data System (ADS)

    Mijares-Chan, Jose Juan; Thomas, Gabriel

    Fault detection based on ultrasonic imaging is a common technique used in non destructive testing. Correct interpretation of the scans requires training so that responses from unwanted echoes such as the background are discriminated from echoes corresponding to faults. Thus, enhancement in the form of displaying the desired echoes without the background response can offer an advantage for detection or further quantification of the fault. A fast way to achieve this goal and detect the background signatures and isolate them from the fault ones is to use time-frequency analysis. When time-varying filtering is used, the tendency is to recover the echoes coming from the faults. These echoes are reconstructed with no phase distortion because the system is linear and the scans c in which the background was cancelled in different specimens where faults were located very close to the surface buried within the initial pulse response and close to each other deeper in the specimen. This technique uses a single reference scan fast enough so that to finish the processing earlier than the time required to acquire a new scan.

  3. Innovation diffusion on time-varying activity driven networks

    NASA Astrophysics Data System (ADS)

    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.

  4. Study of selected phenotype switching strategies in time varying environment

    NASA Astrophysics Data System (ADS)

    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.

  5. Modeling of Time Varying Slag Flow in Coal Gasifiers

    SciTech Connect

    Pilli, Siva Prasad; Johnson, Kenneth I.; Williford, Ralph E.; Sundaram, S. K.; Korolev, Vladimir N.; Crum, Jarrod V.

    2008-08-30

    There is considerable interest within government agencies and the energy industries across the globe to further advance the clean and economical conversion of coal into liquid fuels to reduce our dependency on imported oil. To date, advances in these areas have been largely based on experimental work. Although there are some detailed systems level performance models, little work has been done on numerical modeling of the component level processes. If accurate models are developed, then significant R&D time might be saved, new insights into the process might be gained, and some good predictions of process or performance can be made. One such area is the characterization of slag deposition and flow on the gasifier walls. Understanding slag rheology and slag-refractory interactions is critical to design and operation of gasifiers with extended refractory lifetimes and also to better control of operating parameters so that the overall gasifier performance with extended service life can be optimized. In the present work, the literature on slag flow modeling was reviewed and a model similar to Seggiani’s was developed to simulate the time varying slag accumulation and flow on the walls of a Prenflo coal gasifier. This model was further extended and modified to simulate a refractory wall gasifier including heat transfer through the refractory wall with flowing slag in contact with the refractory. The model was used to simulate temperature dependent slag flow using rheology data from our experimental slag testing program. These modeling results as well as experimental validation are presented.

  6. Robust algorithm for estimation of time-varying transfer functions.

    PubMed

    Zou, Rui; Chon, Ki H

    2004-02-01

    We introduce a new method to estimate reliable time-varying (TV) transfer functions (TFs) and TV impulse response functions. The method is based on TV autoregressive moving average models in which the TV parameters are accurately obtained using the optimal parameter search method which we have previously developed. The new method is more accurate than the recursive least-squares (RLS), and remains robust even in the case of significant noise contamination. Furthermore, the new method is able to track dynamics that change abruptly, which is certainly a deficiency of the RLS. Application of the new method to renal blood pressure and flow revealed that hypertensive rats undergo more complex and TV autoregulation in maintaining stable blood flow than do normotensive rats. This observation has not been previously revealed using time-invariant TF analyses. The newly developed approach may promote the broader use of TV system identification in studies of physiological systems and makes linear and nonlinear TV modeling possible in certain cases previously thought intractable. PMID:14765694

  7. Contagion dynamics in time-varying metapopulation networks

    NASA Astrophysics Data System (ADS)

    Baronchelli, Andrea; Liu, Suyu; Perra, Nicola

    2013-03-01

    The metapopulation framework is adopted in a wide array of disciplines to describe systems of well separated yet connected subpopulations. The subgroups/patches are often represented as nodes in a network whose links represent the migration routes among them. The connections are usually considered as static, an approximation that is appropriate for the description of many systems, such as cities connected by human mobility, but it is obviously inadequate in those real systems where links evolve in time on a faster timescale. In the case of farmed animals, for example, the connections between each farm/node vary in time according to the different stages of production. Here we address this case by investigating simple contagion processes on temporal metapopulation networks. We focus on the SIR process, and we determine the mobility threshold for the onset of an epidemic spreading in the framework of activity-driven network models. Remarkably, we find profound differences from the case of static networks, determined by the crucial role played by the dynamical parameters defining the average number of instantaneously migrating individuals. Our results confirm the importance of addressing the time-varying properties of complex networks pointed out by the recent literature.

  8. Statistical signatures of geomagnetic storms with reference to delay distribution

    NASA Astrophysics Data System (ADS)

    Aslam, A. M.; Gwal, Ashok Kumar

    2016-07-01

    This paper presents a statistical study on the nature and association of time delay (between IMF Bz and Dst) with various solar wind parameters and Inter planetary Magnetic field components. The study integrally covers all (634 storms) the geomagnetic storms observed during 1996 to 2011. We have calculated the time delay (∆T) between the peak values of IMF Bz and minimum Dst for each event and statistically investigated its relation with various solar wind parameters and IMF. For this analysis we have taken Solar wind parameters; Velocity, Density, Plasma beta and Temperature as well as IMF Bz, into consideration. We have categorized the storms into three categories based on the Dst Index as weak (-30nT ≤ Dst ≤ -50nT), moderate (-50nT ≤ Dst ≤ -100nT) and intense (Dst ≤ -100nT) storms. The relation of delay with solar wind parameters and IMF components were studied separately for different classes of storms and for different delays viz. 0,1,2,3,4 (hours). From our analysis we are able to draw some interesting inferences. The fact, that the characteristic feature describing the geoeffectiveness of the IMF is its z-component; Bz, and the electric field component -V× Bz, stands true for all delay classes of the storms. The time delay (∆T) between peak values of IMF Bz and minimum Dst can vary in a wide range and mostly varies from 0-10 hours. However, it was found that a major percentage (~80 %) of the storms have a 0 - 4 hour delay. Meanwhile Temperature, density and plasma beta seems to have no significant association with the storm intensity.

  9. Robust H∞ Control for Time-Varying Delay Systems with Frequency-Dependent Performance Weights

    NASA Astrophysics Data System (ADS)

    Nagahara, Masanori; Arai, Shingo; Uchimura, Yutaka

    This paper proposes a control design that enables us to shape the frequency-dependent performance using a modified Lyapunov-Krasovskii-based stabilizing condition. A stabilizing controller can be obtained by solving the condition formulated in Linear Matrix Inequality (LMI). The designed controller is evaluated using numerical simulations, and it is employed to realize the velocity control of a DC motor. Experimental results verified that the proposed controller achieved better performance with less conservativeness and that it is applicable to real plants.

  10. Time-varying priority queuing models for human dynamics.

    PubMed

    Jo, Hang-Hyun; Pan, Raj Kumar; Kaski, Kimmo

    2012-06-01

    Queuing models provide insight into the temporal inhomogeneity of human dynamics, characterized by the broad distribution of waiting times of individuals performing tasks. We theoretically study the queuing model of an agent trying to execute a task of interest, the priority of which may vary with time due to the agent's "state of mind." However, its execution is disrupted by other tasks of random priorities. By considering the priority of the task of interest either decreasing or increasing algebraically in time, we analytically obtain and numerically confirm the bimodal and unimodal waiting time distributions with power-law decaying tails, respectively. These results are also compared to the updating time distribution of papers in arXiv.org and the processing time distribution of papers in Physical Review journals. Our analysis helps to understand human task execution in a more realistic scenario. PMID:23005156

  11. Time-varying priority queuing models for human dynamics

    NASA Astrophysics Data System (ADS)

    Jo, Hang-Hyun; Pan, Raj Kumar; Kaski, Kimmo

    2012-06-01

    Queuing models provide insight into the temporal inhomogeneity of human dynamics, characterized by the broad distribution of waiting times of individuals performing tasks. We theoretically study the queuing model of an agent trying to execute a task of interest, the priority of which may vary with time due to the agent's “state of mind.” However, its execution is disrupted by other tasks of random priorities. By considering the priority of the task of interest either decreasing or increasing algebraically in time, we analytically obtain and numerically confirm the bimodal and unimodal waiting time distributions with power-law decaying tails, respectively. These results are also compared to the updating time distribution of papers in arXiv.org and the processing time distribution of papers in Physical Review journals. Our analysis helps to understand human task execution in a more realistic scenario.

  12. ICASE/LaRC Symposium on Visualizing Time-Varying Data

    NASA Technical Reports Server (NTRS)

    Banks, D. C. (Editor); Crockett, T. W. (Editor); Stacy, K. (Editor)

    1996-01-01

    Time-varying datasets present difficult problems for both analysis and visualization. For example, the data may be terabytes in size, distributed across mass storage systems at several sites, with time scales ranging from femtoseconds to eons. In response to these challenges, ICASE and NASA Langley Research Center, in cooperation with ACM SIGGRAPH, organized the first symposium on visualizing time-varying data. The purpose was to bring the producers of time-varying data together with visualization specialists to assess open issues in the field, present new solutions, and encourage collaborative problem-solving. These proceedings contain the peer-reviewed papers which were presented at the symposium. They cover a broad range of topics, from methods for modeling and compressing data to systems for visualizing CFD simulations and World Wide Web traffic. Because the subject matter is inherently dynamic, a paper proceedings cannot adequately convey all aspects of the work. The accompanying video proceedings provide additional context for several of the papers.

  13. Multi-carrier Communications over Time-varying Acoustic Channels

    NASA Astrophysics Data System (ADS)

    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

  14. Energy decay for viscoelastic plates with distributed delay and source term

    NASA Astrophysics Data System (ADS)

    Mustafa, Muhammad I.; Kafini, Mohammad

    2016-06-01

    In this paper we consider a viscoelastic plate equation with distributed delay and source term. Under suitable conditions on the delay and source term, we establish an explicit and general decay rate result without imposing restrictive assumptions on the behavior of the relaxation function at infinity. Our result allows a wider class of relaxation functions and improves earlier results in the literature.

  15. Theory of electromagnetic cyclotron wave growth in a time-varying magnetoplasma

    NASA Technical Reports Server (NTRS)

    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.

  16. Integrated planning problem in supply chains with time-varying delivery

    NASA Astrophysics Data System (ADS)

    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.

  17. Recurrence of particles in static and time varying oval billiards

    NASA Astrophysics Data System (ADS)

    Leonel, Edson D.; Dettmann, Carl P.

    2012-04-01

    Dynamical properties are studied for escaping particles, injected through a hole in an oval billiard. The dynamics is considered for both static and periodically moving boundaries. For the static boundary, two different decays for the recurrence time distribution were observed after exponential decay for short times: A changeover to: (i) power law or; (ii) stretched exponential. Both slower decays are due to sticky orbits trapped near KAM islands, with the stretched exponential apparently associated with a single group of large islands. For time dependent case, survival probability leads to the conclusion that sticky orbits are less evident compared with the static case.

  18. Time-varying multivariate visualization for understanding terrestrial biogeochemistry

    NASA Astrophysics Data System (ADS)

    Sisneros, R.; Glatter, M.; Langley, B.; Huang, J.; Hoffman, F.; Erickson, D. J., Iii

    2008-07-01

    Petascale computing has brought forth a transformational way of doing science. To the global effort on studying climate change, this shift has enabled not only tools more functional and more powerful than before but also a scientific exploration more comprehensive than before. In this work, we report our efforts to employ recent ultrascale visualization technologies (SciDAC Ultravis) to study model comparison in terrestrial biogeochemistry datasets produced by computation (SciDAC C-LAMP). While many of the current efforts are specific to climate modeling research, our method of location-specific summarizing visualization of extreme and normal relative distribution patterns is generally applicable to other fields of computational sciences.

  19. Fission Fragment Distributions and Delayed Neutron Yields from Photon-Induced-Fission

    SciTech Connect

    David, J.-C.; Dore, D.; Giacri-Mauborgne, M.-L.; Ridikas, D.; Lauwe, A. van

    2005-05-24

    Fission fragment distributions and delayed neutron yields for 235U and 238U are provided by a complete modelization of the photofission process below 25 MeV. The absorption cross-section parameterization and the fission fragment distributions are given and compared to experimental data. The delayed neutron yields and the half-lives in terms of six groups are presented and compared to data obtained with a bremsstrahlung spectrum of 15 MeV.

  20. The Type Ia Supernova Rate and Delay-Time Distribution

    NASA Astrophysics Data System (ADS)

    Graur, Or

    2013-11-01

    The nature of the progenitor stellar systems of thermonuclear, or Type Ia, supernovae (SNe Ia) remains unknown. Unlike core-collapse (CC) SNe, which have been successfully linked, at least partially, to various types of massive stars, the progenitors of SNe Ia are to date undetected in pre-explosion images and the nature of these progenitors can only be probed using indirect methods. In this thesis, I present three SN surveys aimed at measuring the rates at which SNe Ia explode at different times throughout the Universe's history and in different types of galaxies. I use these rates to re-construct the SN Ia delay-time distribution (DTD), a function that connects between the star-formation history (SFH) of a specific stellar environment and its SN Ia rate, and I use it to constrain different progenitor models. In Chapter 1, I provide a brief introduction of the field. This is followed, in Chapter 2, by a description of the Subaru Deep Field (SDF) SN Survey. Over a period of three years between 2005-2008, the SDF was observed on four independent epochs with Suprime-Cam on the Subaru 8.2-m telescope, with two nights of exposure per epoch, in the R, i', and z' bands. In this survey, I discover 150 SNe out to redshift z ~ 2, including 27 SNe Ia in the range 1.0 < z < 1.5 and 10 in the range 1.5 < z < 2.0. The SN Ia rate measurements from this sample are consistent with those derived from the Hubble Space Telescope (HST) GOODS sample, but the overall uncertainty of the 1.5 < z < 2.0 measurement is a factor of 2 smaller, of 35-50%. Based on this sample, we find that the SN Ia rate evolution levels off at 1.0 < z < 2.0, but shows no sign of declining. Combining our SN Ia rate measurements and those from the literature, and comparing to a wide range of possible SFHs, the best-fitting DTD is a power law of the form Psi(t) ~ t^beta, with index beta = -1.1 ± 0.1 (statistical) ± 0.17 (systematic). By combining the contribution from CC SNe, based on the wide range of SFHs

  1. Hubble expansion and structure formation in time varying vacuum models

    SciTech Connect

    Basilakos, Spyros; Plionis, Manolis; Sola, Joan

    2009-10-15

    {lambda}{proportional_to}H model) in which clusters form at significantly earlier times (z{>=}4) with respect to all other models (z{approx}2). Finally, we derived the theoretically predicted dark matter halo mass function and the corresponding distribution of cluster-size halos for all the models studied. Their expected redshift distribution indicates that it will be difficult to distinguish the closely resembling models (constant vacuum, quantum field, and power law vacuum), using realistic future x-ray surveys of cluster abundances. However, cluster surveys based on the Sunayev-Zeldovich detection method give some hope to distinguish the closely resembling models at high redshifts.

  2. Extension of the spectral element method for stability analysis of time-periodic delay-differential equations with multiple and distributed delays

    NASA Astrophysics Data System (ADS)

    Lehotzky, David; Insperger, Tamas; Stepan, Gabor

    2016-06-01

    The spectral element method was introduced by Khasawneh and Mann (2013) for the stability analysis of time-periodic delay-differential equations (DDEs) with multiple delays. In this paper, this method is generalized for time-periodic DDEs with multiple delays and distributed delay. For this general case, an explicit formula is given for the construction of the matrix approximation of the monodromy operator. The derived formula enables the algorithmic application of the method to DDEs with general combinations of delays for arbitrary point sets and test functions. Stability analysis is demonstrated for specific case studies, and the computation code is provided for a complex example.

  3. Delayed Adulthood, Delayed Desistance? Trends in the Age Distribution of Problem Behaviors

    PubMed Central

    Hayford, Sarah R.; Furstenberg, Frank F.

    2009-01-01

    As the transition to adulthood becomes more protracted and less orderly, fewer young people occupy adult roles and experience the social control associated with these roles. One might therefore expect behaviors associated with the teenage years to spill over into older age groups, reflecting postponed entrance into full social adulthood. We test this hypothesis by examining trends over time in the age distribution of crime, substance use, and violent death. We find little evidence that behaviors typical of adolescence are moving upward to older ages. Although the achievement of adult roles is being pushed to older ages, this stretching of the transition to adulthood is not reflected in the observed patterns of substance use, violent death, and arrests. PMID:19633730

  4. Bifurcation analysis on the globally coupled Kuramoto oscillators with distributed time delays

    NASA Astrophysics Data System (ADS)

    Niu, Ben; Guo, Yuxiao

    2014-01-01

    Distributed delay interactions among a group of Kuramoto phase oscillators are studied from the viewpoint of bifurcation analysis. After restricting the system on the Ott-Antonsen manifold, a simplified model consisting of delay differential equations is obtained. Hopf bifurcation diagrams are drawn on some two-parameter planes around the incoherent state when delay follows Dirac, uniform, Gamma and normal distributions, respectively, and it is illustrated that stronger coupling is needed to achieve synchrony when increasing the variance of either natural frequency or time delay. With the aid of center manifold reduction and the normal form method, the direction of Hopf bifurcation and stability of bifurcating periodic solutions are investigated, and the existence of the hysteresis loop is explained theoretically.

  5. Least expected time paths in stochastic, time-varying transportation networks

    SciTech Connect

    Miller-Hooks, E.D.; Mahmassani, H.S.

    1999-06-01

    The authors consider stochastic, time-varying transportation networks, where the arc weights (arc travel times) are random variables with probability distribution functions that vary with time. Efficient procedures are widely available for determining least time paths in deterministic networks. In stochastic but time-invariant networks, least expected time paths can be determined by setting each random arc weight to its expected value and solving an equivalent deterministic problem. This paper addresses the problem of determining least expected time paths in stochastic, time-varying networks. Two procedures are presented. The first procedure determines the a priori least expected time paths from all origins to a single destination for each departure time in the peak period. The second procedure determines lower bounds on the expected times of these a priori least expected time paths. This procedure determines an exact solution for the problem where the driver is permitted to react to revealed travel times on traveled links en route, i.e. in a time-adaptive route choice framework. Modifications to each of these procedures for determining least expected cost (where cost is not necessarily travel time) paths and lower bounds on the expected costs of these paths are given. Extensive numerical tests are conducted to illustrate the algorithms` computational performance as well as the properties of the solution.

  6. A Parallel Pipelined Renderer for the Time-Varying Volume Data

    NASA Technical Reports Server (NTRS)

    Chiueh, Tzi-Cker; Ma, Kwan-Liu

    1997-01-01

    This paper presents a strategy for efficiently rendering time-varying volume data sets on a distributed-memory parallel computer. Time-varying volume data take large storage space and visualizing them requires reading large files continuously or periodically throughout the course of the visualization process. Instead of using all the processors to collectively render one volume at a time, a pipelined rendering process is formed by partitioning processors into groups to render multiple volumes concurrently. In this way, the overall rendering time may be greatly reduced because the pipelined rendering tasks are overlapped with the I/O required to load each volume into a group of processors; moreover, parallelization overhead may be reduced as a result of partitioning the processors. We modify an existing parallel volume renderer to exploit various levels of rendering parallelism and to study how the partitioning of processors may lead to optimal rendering performance. Two factors which are important to the overall execution time are re-source utilization efficiency and pipeline startup latency. The optimal partitioning configuration is the one that balances these two factors. Tests on Intel Paragon computers show that in general optimal partitionings do exist for a given rendering task and result in 40-50% saving in overall rendering time.

  7. Stability and Hopf bifurcation for a regulated logistic growth model with discrete and distributed delays

    NASA Astrophysics Data System (ADS)

    Fang, Shengle; Jiang, Minghui

    2009-12-01

    In this paper, we investigate the stability and Hopf bifurcation of a new regulated logistic growth with discrete and distributed delays. By choosing the discrete delay τ as a bifurcation parameter, we prove that the system is locally asymptotically stable in a range of the delay and Hopf bifurcation occurs as τ crosses a critical value. Furthermore, explicit algorithm for determining the direction of the Hopf bifurcation and the stability of the bifurcating periodic solutions is derived by normal form theorem and center manifold argument. Finally, an illustrative example is also given to support the theoretical results.

  8. Stability Analysis of SIR Model with Distributed Delay on Complex Networks.

    PubMed

    Huang, Chuangxia; Cao, Jie; Wen, Fenghua; Yang, Xiaoguang

    2016-01-01

    In this paper, by taking full consideration of distributed delay, demographics and contact heterogeneity of the individuals, we present a detailed analytical study of the Susceptible-Infected-Removed (SIR) epidemic model on complex population networks. The basic reproduction number [Formula: see text] of the model is dominated by the topology of the underlying network, the properties of individuals which include birth rate, death rate, removed rate and infected rate, and continuously distributed time delay. By constructing suitable Lyapunov functional and employing Kirchhoff's matrix tree theorem, we investigate the globally asymptotical stability of the disease-free and endemic equilibrium points. Specifically, the system shows threshold behaviors: if [Formula: see text], then the disease-free equilibrium is globally asymptotically stable, otherwise the endemic equilibrium is globally asymptotically stable. Furthermore, the obtained results show that SIR models with different types of delays have different converge time in the process of contagion: if [Formula: see text], then the system with distributed time delay stabilizes fastest; while [Formula: see text], the system with distributed time delay converges most slowly. The validness and effectiveness of these results are demonstrated through numerical simulations. PMID:27490363

  9. Stability Analysis of SIR Model with Distributed Delay on Complex Networks

    PubMed Central

    Huang, Chuangxia; Cao, Jie; Wen, Fenghua; Yang, Xiaoguang

    2016-01-01

    In this paper, by taking full consideration of distributed delay, demographics and contact heterogeneity of the individuals, we present a detailed analytical study of the Susceptible-Infected-Removed (SIR) epidemic model on complex population networks. The basic reproduction number R0 of the model is dominated by the topology of the underlying network, the properties of individuals which include birth rate, death rate, removed rate and infected rate, and continuously distributed time delay. By constructing suitable Lyapunov functional and employing Kirchhoff’s matrix tree theorem, we investigate the globally asymptotical stability of the disease-free and endemic equilibrium points. Specifically, the system shows threshold behaviors: if R0≤1, then the disease-free equilibrium is globally asymptotically stable, otherwise the endemic equilibrium is globally asymptotically stable. Furthermore, the obtained results show that SIR models with different types of delays have different converge time in the process of contagion: if R0>1, then the system with distributed time delay stabilizes fastest; while R0≤1, the system with distributed time delay converges most slowly. The validness and effectiveness of these results are demonstrated through numerical simulations. PMID:27490363

  10. Recursive state estimation for discrete time-varying stochastic nonlinear systems with randomly occurring deception attacks

    NASA Astrophysics Data System (ADS)

    Ding, Derui; Shen, Yuxuan; Song, Yan; Wang, Yongxiong

    2016-07-01

    This paper is concerned with the state estimation problem for a class of discrete time-varying stochastic nonlinear systems with randomly occurring deception attacks. The stochastic nonlinearity described by statistical means which covers several classes of well-studied nonlinearities as special cases is taken into discussion. The randomly occurring deception attacks are modelled by a set of random variables obeying Bernoulli distributions with given probabilities. The purpose of the addressed state estimation problem is to design an estimator with hope to minimize the upper bound for estimation error covariance at each sampling instant. Such an upper bound is minimized by properly designing the estimator gain. The proposed estimation scheme in the form of two Riccati-like difference equations is of a recursive form. Finally, a simulation example is exploited to demonstrate the effectiveness of the proposed scheme.

  11. Passivity analysis for memristor-based recurrent neural networks with discrete and distributed delays.

    PubMed

    Guodong Zhang; Yi Shen; Quan Yin; Junwei Sun

    2015-01-01

    In this paper, based on the knowledge of memristor and recurrent neural networks (RNNs), the model of the memristor-based RNNs with discrete and distributed delays is established. By constructing proper Lyapunov functionals and using inequality technique, several sufficient conditions are given to ensure the passivity of the memristor-based RNNs with discrete and distributed delays in the sense of Filippov solutions. The passivity conditions here are presented in terms of linear matrix inequalities, which can be easily solved by using Matlab Tools. In addition, the results of this paper complement and extend the earlier publications. Finally, numerical simulations are employed to illustrate the effectiveness of the obtained results. PMID:25462633

  12. Dynamic Divisive Normalization Predicts Time-Varying Value Coding in Decision-Related Circuits

    PubMed Central

    LoFaro, Thomas; Webb, Ryan; Glimcher, Paul W.

    2014-01-01

    Normalization is a widespread neural computation, mediating divisive gain control in sensory processing and implementing a context-dependent value code in decision-related frontal and parietal cortices. Although decision-making is a dynamic process with complex temporal characteristics, most models of normalization are time-independent and little is known about the dynamic interaction of normalization and choice. Here, we show that a simple differential equation model of normalization explains the characteristic phasic-sustained pattern of cortical decision activity and predicts specific normalization dynamics: value coding during initial transients, time-varying value modulation, and delayed onset of contextual information. Empirically, we observe these predicted dynamics in saccade-related neurons in monkey lateral intraparietal cortex. Furthermore, such models naturally incorporate a time-weighted average of past activity, implementing an intrinsic reference-dependence in value coding. These results suggest that a single network mechanism can explain both transient and sustained decision activity, emphasizing the importance of a dynamic view of normalization in neural coding. PMID:25429145

  13. Dynamic divisive normalization predicts time-varying value coding in decision-related circuits.

    PubMed

    Louie, Kenway; LoFaro, Thomas; Webb, Ryan; Glimcher, Paul W

    2014-11-26

    Normalization is a widespread neural computation, mediating divisive gain control in sensory processing and implementing a context-dependent value code in decision-related frontal and parietal cortices. Although decision-making is a dynamic process with complex temporal characteristics, most models of normalization are time-independent and little is known about the dynamic interaction of normalization and choice. Here, we show that a simple differential equation model of normalization explains the characteristic phasic-sustained pattern of cortical decision activity and predicts specific normalization dynamics: value coding during initial transients, time-varying value modulation, and delayed onset of contextual information. Empirically, we observe these predicted dynamics in saccade-related neurons in monkey lateral intraparietal cortex. Furthermore, such models naturally incorporate a time-weighted average of past activity, implementing an intrinsic reference-dependence in value coding. These results suggest that a single network mechanism can explain both transient and sustained decision activity, emphasizing the importance of a dynamic view of normalization in neural coding. PMID:25429145

  14. Global Stability of an HIV-1 Infection Model with General Incidence Rate and Distributed Delays

    PubMed Central

    2014-01-01

    In this work an HIV-1 infection model with nonlinear incidence rate and distributed intracellular delays and with humoral immunity is investigated. The disease transmission function is assumed to be governed by general incidence rate f(T, V)V. The intracellular delays describe the time between viral entry into a target cell and the production of new virus particles and the time between infection of a cell and the emission of viral particle. Lyapunov functionals are constructed and LaSalle invariant principle for delay differential equation is used to establish the global asymptotic stability of the infection-free equilibrium, infected equilibrium without B cells response, and infected equilibrium with B cells response. The results obtained show that the global dynamics of the system depend on both the properties of the general incidence function and the value of certain threshold parameters R0 and R1 which depends on the delays. PMID:27355007

  15. Preserved calibration of persistence based on delay-timing distribution during sleep deprivation.

    PubMed

    Massar, Stijn A A; Chee, Michael W L

    2015-12-01

    We frequently encounter decisions where we have to determine whether to wait for a certain reward delayed for an uncertain duration or to move on. The appropriate decision depends upon the underlying temporal distribution of the delay. With some distributions it is best to be completely persistent, whereas in others it is more appropriate to abandon waiting after a certain period of time. The current study examined whether the ability to form temporal expectations and adjust persistence accordingly is compromised by sleep deprivation. Participants performed a willingness-to-wait task either in a well-rested state or after a night of total sleep deprivation. Participants had to decide either to wait for a larger reward or to abandon waiting in favour of a smaller immediate reward. Delays were drawn from either a uniform distribution, where being persistent yields maximal returns, or from a heavy-tailed distribution, where occasional long delays render full persistence suboptimal. In spite of increased sleepiness and decreased vigilance, sleep-deprived participants were able to adjust waiting time appropriate to the experienced timing distribution. Additionally, sleep deprivation did not affect the foreperiod effect, indicating intact perception of conditional probability of temporal events and ability to adjust preparation accordingly. PMID:26179859

  16. The rates and time-delay distribution of multiply imaged supernovae behind lensing clusters

    SciTech Connect

    Li, Xue; Hjorth, Jens; Richard, Johan E-mail: jens@dark-cosmology.dk

    2012-11-01

    Time delays of gravitationally lensed sources can be used to constrain the mass model of a deflector and determine cosmological parameters. We here present an analysis of the time-delay distribution of multiply imaged sources behind 17 strong lensing galaxy clusters with well-calibrated mass models. We find that for time delays less than 1000 days, at z = 3.0, their logarithmic probability distribution functions are well represented by P(log Δt) = 5.3 × 10{sup −4}Δt{sup β-tilde}/M{sub 250}{sup 2β-tilde}, with β-tilde = 0.77, where M{sub 250} is the projected cluster mass inside 250 kpc (in 10{sup 14}M{sub ☉}), and β-tilde is the power-law slope of the distribution. The resultant probability distribution function enables us to estimate the time-delay distribution in a lensing cluster of known mass. For a cluster with M{sub 250} = 2 × 10{sup 14}M{sub ☉}, the fraction of time delays less than 1000 days is approximately 3%. Taking Abell 1689 as an example, its dark halo and brightest galaxies, with central velocity dispersions σ≥500kms{sup −1}, mainly produce large time delays, while galaxy-scale mass clumps are responsible for generating smaller time delays. We estimate the probability of observing multiple images of a supernova in the known images of Abell 1689. A two-component model of estimating the supernova rate is applied in this work. For a magnitude threshold of m{sub AB} = 26.5, the yearly rate of Type Ia (core-collapse) supernovae with time delays less than 1000 days is 0.004±0.002 (0.029±0.001). If the magnitude threshold is lowered to m{sub AB} ∼ 27.0, the rate of core-collapse supernovae suitable for time delay observation is 0.044±0.015 per year.

  17. Distributed Consensus of Stochastic Delayed Multi-agent Systems Under Asynchronous Switching.

    PubMed

    Wu, Xiaotai; Tang, Yang; Cao, Jinde; Zhang, Wenbing

    2016-08-01

    In this paper, the distributed exponential consensus of stochastic delayed multi-agent systems with nonlinear dynamics is investigated under asynchronous switching. The asynchronous switching considered here is to account for the time of identifying the active modes of multi-agent systems. After receipt of confirmation of mode's switching, the matched controller can be applied, which means that the switching time of the matched controller in each node usually lags behind that of system switching. In order to handle the coexistence of switched signals and stochastic disturbances, a comparison principle of stochastic switched delayed systems is first proved. By means of this extended comparison principle, several easy to verified conditions for the existence of an asynchronously switched distributed controller are derived such that stochastic delayed multi-agent systems with asynchronous switching and nonlinear dynamics can achieve global exponential consensus. Two examples are given to illustrate the effectiveness of the proposed method. PMID:26292354

  18. Signal power distribution in time delay in Tokyo City experimental sites

    NASA Astrophysics Data System (ADS)

    Hayakawa, M.; Katz, D.; Blaunstein, N.

    2008-06-01

    This paper presents experiments carried out in the city of Tokyo in two types of built-up environments. One environment is characterized by a straight-crossing street plan with buildings randomly lining the streets and the terminal antennas located at the line of sight (LOS) and quasi-LOS conditions along the streets. The second built-up area is characterized by straight-crossing streets with non-LOS (NLOS) conditions caused by the railway station and administrative buildings surrounding the terminal antennas. The time delay signal strength distributions obtained experimentally are presented for both multipath urban channels These test experiments are used to study whether any propagation modeling can predict the time delay distribution of signal power. Our theoretical framework is based on the corresponding crossing-street waveguide model taking into account the Poisson statistics for buildings randomly lining each street. The proposed analytical formulas are analyzed for different parameters of the built-up terrain, such as the street width, the average height of buildings, the terminal antenna heights with respect to the rooftops of buildings lining a street, and the gaps (slits) between the buildings. Then a comparison between the proposed theoretical model and experimental data is presented, which indicates a satisfactory agreement between the theoretical and experimental prediction of signal power distribution in the time delay domain. So, our modeling can be used as a promising predictor for the time delay distribution in the microcellular propagation environment.

  19. A multiscale MDCT image-based breathing lung model with time-varying regional ventilation.

    PubMed

    Yin, Youbing; Choi, Jiwoong; Hoffman, Eric A; Tawhai, Merryn H; Lin, Ching-Long

    2013-07-01

    A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung. For the first time, the algorithm is applied to three multi-detector row computed tomography (MDCT) volumetric lung images of the same individual. A key technique in linking global and local variables over multiple images is an in-house mass-preserving image registration method. Throughout breathing cycles, cubic interpolation is employed to ensure C 1 continuity in constructing time-varying regional ventilation at the whole lung level, flow rate fractions exiting the terminal airways, and airway deformation. The imaged exit airway flow rate fractions are derived from regional ventilation with the aid of a three-dimensional (3D) and one-dimensional (1D) coupled airway tree that connects the airways to the alveolar tissue. An in-house parallel large-eddy simulation (LES) technique is adopted to capture turbulent-transitional-laminar flows in both normal and deep breathing conditions. The results obtained by the proposed algorithm when using three lung volume images are compared with those using only one or two volume images. The three-volume-based lung model produces physiologically-consistent time-varying pressure and ventilation distribution. The one-volume-based lung model under-predicts pressure drop and yields un-physiological lobar ventilation. The two-volume-based model can account for airway deformation and non-uniform regional ventilation to some extent, but does not capture the non-linear features of the lung. PMID:23794749

  20. A multiscale MDCT image-based breathing lung model with time-varying regional ventilation

    SciTech Connect

    Yin, Youbing; Choi, Jiwoong; Hoffman, Eric A.; Tawhai, Merryn H.; Lin, Ching-Long

    2013-07-01

    A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung. For the first time, the algorithm is applied to three multi-detector row computed tomography (MDCT) volumetric lung images of the same individual. A key technique in linking global and local variables over multiple images is an in-house mass-preserving image registration method. Throughout breathing cycles, cubic interpolation is employed to ensure C{sub 1} continuity in constructing time-varying regional ventilation at the whole lung level, flow rate fractions exiting the terminal airways, and airway deformation. The imaged exit airway flow rate fractions are derived from regional ventilation with the aid of a three-dimensional (3D) and one-dimensional (1D) coupled airway tree that connects the airways to the alveolar tissue. An in-house parallel large-eddy simulation (LES) technique is adopted to capture turbulent-transitional-laminar flows in both normal and deep breathing conditions. The results obtained by the proposed algorithm when using three lung volume images are compared with those using only one or two volume images. The three-volume-based lung model produces physiologically-consistent time-varying pressure and ventilation distribution. The one-volume-based lung model under-predicts pressure drop and yields un-physiological lobar ventilation. The two-volume-based model can account for airway deformation and non-uniform regional ventilation to some extent, but does not capture the non-linear features of the lung.

  1. A multiscale MDCT image-based breathing lung model with time-varying regional ventilation

    PubMed Central

    Yin, Youbing; Choi, Jiwoong; Hoffman, Eric A.; Tawhai, Merryn H.; Lin, Ching-Long

    2012-01-01

    A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung. For the first time, the algorithm is applied to three multi-detector row computed tomography (MDCT) volumetric lung images of the same individual. A key technique in linking global and local variables over multiple images is an in-house mass-preserving image registration method. Throughout breathing cycles, cubic interpolation is employed to ensure C1 continuity in constructing time-varying regional ventilation at the whole lung level, flow rate fractions exiting the terminal airways, and airway deformation. The imaged exit airway flow rate fractions are derived from regional ventilation with the aid of a three-dimensional (3D) and one-dimensional (1D) coupled airway tree that connects the airways to the alveolar tissue. An in-house parallel large-eddy simulation (LES) technique is adopted to capture turbulent-transitional-laminar flows in both normal and deep breathing conditions. The results obtained by the proposed algorithm when using three lung volume images are compared with those using only one or two volume images. The three-volume-based lung model produces physiologically-consistent time-varying pressure and ventilation distribution. The one-volume-based lung model under-predicts pressure drop and yields un-physiological lobar ventilation. The two-volume-based model can account for airway deformation and non-uniform regional ventilation to some extent, but does not capture the non-linear features of the lung. PMID:23794749

  2. Propagation of a laser beam in a time-varying waveguide. [plasma heating for controlled fusion

    NASA Technical Reports Server (NTRS)

    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.

  3. Identification of Time-Varying Pilot Control Behavior in Multi-Axis Control Tasks

    NASA Technical Reports Server (NTRS)

    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.

  4. Convergence dynamics of hybrid bidirectional associative memory neural networks with distributed delays

    NASA Astrophysics Data System (ADS)

    Liao, Xiaofeng; Wong, Kwok-Wo; Yang, Shizhong

    2003-09-01

    In this Letter, the characteristics of the convergence dynamics of hybrid bidirectional associative memory neural networks with distributed transmission delays are studied. Without assuming the symmetry of synaptic connection weights and the monotonicity and differentiability of activation functions, the Lyapunov functionals are constructed and the generalized Halanay-type inequalities are employed to derive the delay-independent sufficient conditions under which the networks converge exponentially to the equilibria associated with temporally uniform external inputs. Some examples are given to illustrate the correctness of our results.

  5. Permanence extinction and global asymptotic stability in a stage structured system with distributed delays

    NASA Astrophysics Data System (ADS)

    Liu, Shengqiang; Kouche, Mahiéddine; Tatar, Nasser-Eddine

    2005-01-01

    In this paper we consider a nonautonomous stage-structured competitive system of n-species population growth with distributed delays which takes into account the delayed feedback in both interspecific and intraspecific interactions. We obtain, by using the method of repeated replace, sufficient conditions for permanence and extinction of the species. The global attractivity of the unique positive equilibrium is proved in the autonomous case. Our results extend previous ones obtained by Liu et al. in [Nonlinear Anal. 51 (2002) 1347-1361; J. Math. Anal Appl. 274 (2002) 667-684].

  6. Mathematical model describing the thyroids-pituitary axis with distributed time delays in hormone transportation

    NASA Astrophysics Data System (ADS)

    Neamţu, Mihaela; Stoian, Dana; Navolan, Dan Bogdan

    2014-12-01

    In the present paper we provide a mathematical model that describe the hypothalamus-pituitary-thyroid axis in autoimmune (Hashimoto's) thyroiditis. Since there is a spatial separation between thyroid and pituitary gland in the body, time is needed for transportation of thyrotropin and thyroxine between the glands. Thus, the distributed time delays are considered as both weak and Dirac kernels. The delayed model is analyzed regarding the stability and bifurcation behavior. The last part contains some numerical simulations to illustrate the effectiveness of our results and conclusions.

  7. Mixture distributions for the statistical time delay in synthetic air at low pressure

    NASA Astrophysics Data System (ADS)

    Jovanović, Aleksandar P.; Popović, Biljana Č.; Marković, Vidosav Lj.; Stamenković, Suzana N.; Stankov, Marjan N.

    2014-08-01

    The mixture distributions for statistical time delay of electrical breakdown are proposed along with the generalized relation for the effective electron yield. The validity of the proposed model is tested by applying this distribution to experimental data measured in synthetic air at low pressure. Two samples without and with oxide surface are compared in order to determine physical processes leading to appearance of mixture distributions in the case of oxidized cathode. The obtained distributions are tested by Kolmogorov-Smirnov statistical hypothesis test in order to justify the use of mixture distributions. The physical interpretation of mixture distribution measured in the synthetic air is proposed, accompanied by the calculated values of the effective electron yield of initiating electrons in the gas gap.

  8. Decelerated invasion and waning-moon patterns in public goods games with delayed distribution

    NASA Astrophysics Data System (ADS)

    Szolnoki, Attila; Perc, Matjaž

    2013-05-01

    We study the evolution of cooperation in the spatial public goods game, focusing on the effects that are brought about by the delayed distribution of goods that accumulate in groups due to the continuous investments of cooperators. We find that intermediate delays enhance network reciprocity because of a decelerated invasion of defectors, who are unable to reap the same high short-term benefits as they do in the absence of delayed distribution. Long delays, however, introduce a risk because the large accumulated wealth might fall into the wrong hands. Indeed, as soon as the curvature of a cooperative cluster turns negative, the engulfed defectors can collect the heritage of many generations of cooperators and by doing so start a waning-moon pattern that nullifies the benefits of decelerated invasion. Accidental meeting points of growing cooperative clusters may also act as triggers for the waning-moon effect, thus linking the success of cooperators with their propensity to fail in a rather bizarre way. Our results highlight that “investing in the future” is a good idea only if that future is sufficiently near and not likely to be burdened by inflation.

  9. Decelerated invasion and waning-moon patterns in public goods games with delayed distribution.

    PubMed

    Szolnoki, Attila; Perc, Matjaž

    2013-05-01

    We study the evolution of cooperation in the spatial public goods game, focusing on the effects that are brought about by the delayed distribution of goods that accumulate in groups due to the continuous investments of cooperators. We find that intermediate delays enhance network reciprocity because of a decelerated invasion of defectors, who are unable to reap the same high short-term benefits as they do in the absence of delayed distribution. Long delays, however, introduce a risk because the large accumulated wealth might fall into the wrong hands. Indeed, as soon as the curvature of a cooperative cluster turns negative, the engulfed defectors can collect the heritage of many generations of cooperators and by doing so start a waning-moon pattern that nullifies the benefits of decelerated invasion. Accidental meeting points of growing cooperative clusters may also act as triggers for the waning-moon effect, thus linking the success of cooperators with their propensity to fail in a rather bizarre way. Our results highlight that "investing in the future" is a good idea only if that future is sufficiently near and not likely to be burdened by inflation. PMID:23767662

  10. Exact reconstruction analysis/synthesis filter banks with time-varying filters

    NASA Technical Reports Server (NTRS)

    Arrowood, J. L., Jr.; Smith, M. J. T.

    1993-01-01

    This paper examines some of the analysis/synthesis issues associated with FIR time-varying filter banks where the filter bank coefficients are allowed to change in response to the input signal. Several issues are identified as being important in order to realize performance gains from time-varying filter banks in image coding applications. These issues relate to the behavior of the filters as transition from one set of filter banks to another occurs. Lattice structure formulations for the time varying filter bank problem are introduced and discussed in terms of their properties and transition characteristics.

  11. Preventing Delayed Voltage Recovery with Voltage-Regulating Distributed Energy Resources

    SciTech Connect

    Adhikari, Sarina; Li, Fangxing; Li, Huijuan; Xu, Yan; Kueck, John D; Rizy, D Tom

    2009-01-01

    With the large use of residential air conditioner (A/C) motors during the summer peaks, the potential of motor stalling events have increased in the recent years. The stalled motor loads have been found to be the most important cause of delayed voltage recovery following severe system disturbances, such as a subtransmission fault. The proper modeling of the stalled motors is a very important factor in identifying the effect of these motors in voltage recovery after the fault. This paper presents a methodology for modeling the stalled low inertia induction motors based on a sample utility system and a small primary distribution circuit. The prevention of the stalling of motors plays an important role in maintaining the voltage profile of the system after system disturbances. Distributed Energy Resource (DER) is used to prevent the motor stalling events so that the delayed voltage recovery of the system may be avoided.

  12. Recurrent event data analysis with intermittently observed time-varying covariates.

    PubMed

    Li, Shanshan; Sun, Yifei; Huang, Chiung-Yu; Follmann, Dean A; Krause, Richard

    2016-08-15

    Although recurrent event data analysis is a rapidly evolving area of research, rigorous studies on estimation of the effects of intermittently observed time-varying covariates on the risk of recurrent events have been lacking. Existing methods for analyzing recurrent event data usually require that the covariate processes are observed throughout the entire follow-up period. However, covariates are often observed periodically rather than continuously. We propose a novel semiparametric estimator for the regression parameters in the popular proportional rate model. The proposed estimator is based on an estimated score function where we kernel smooth the mean covariate process. We show that the proposed semiparametric estimator is asymptotically unbiased, normally distributed, and derives the asymptotic variance. Simulation studies are conducted to compare the performance of the proposed estimator and the simple methods carrying forward the last covariates. The different methods are applied to an observational study designed to assess the effect of group A streptococcus on pharyngitis among school children in India. Copyright © 2016 John Wiley & Sons, Ltd. PMID:26887664

  13. Measurement of time varying temperature fields using visible imaging CCD cameras

    SciTech Connect

    Keanini, R.G.; Allgood, C.L.

    1996-12-31

    A method for measuring time-varying surface temperature distributions using high frame rate visible imaging CCD cameras is described. The technique is based on an ad hoc model relating measured radiance to local surface temperature. This approach is based on the fairly non-restrictive assumptions that atmospheric scattering and absorption, and secondary emission and reflection are negligible. In order to assess performance, both concurrent and non-concurrent calibration and measurement, performed under dynamic thermal conditions, are examined. It is found that measurement accuracy is comparable to the theoretical accuracy predicted for infrared-based systems. In addition, performance tests indicate that in the experimental system, real-time calibration can be achieved while real-time whole-field temperature measurements require relatively coarse spatial resolution. The principal advantages of the proposed method are its simplicity and low cost. In addition, since independent temperature measurements are used for calibration, emissivity remains unspecified, so that a potentially significant source of error is eliminated.

  14. "Tools For Analysis and Visualization of Large Time- Varying CFD Data Sets"

    NASA Technical Reports Server (NTRS)

    Wilhelms, Jane; vanGelder, Allen

    1999-01-01

    During the four years of this grant (including the one year extension), we have explored many aspects of the visualization of large CFD (Computational Fluid Dynamics) datasets. These have included new direct volume rendering approaches, hierarchical methods, volume decimation, error metrics, parallelization, hardware texture mapping, and methods for analyzing and comparing images. First, we implemented an extremely general direct volume rendering approach that can be used to render rectilinear, curvilinear, or tetrahedral grids, including overlapping multiple zone grids, and time-varying grids. Next, we developed techniques for associating the sample data with a k-d tree, a simple hierarchial data model to approximate samples in the regions covered by each node of the tree, and an error metric for the accuracy of the model. We also explored a new method for determining the accuracy of approximate models based on the light field method described at ACM SIGGRAPH (Association for Computing Machinery Special Interest Group on Computer Graphics) '96. In our initial implementation, we automatically image the volume from 32 approximately evenly distributed positions on the surface of an enclosing tessellated sphere. We then calculate differences between these images under different conditions of volume approximation or decimation.

  15. Portfolio Value-at-Risk with Time-Varying Copula: Evidence from Latin America

    NASA Astrophysics Data System (ADS)

    Ozun, Alper; Cifter, Atilla

    Model risk in the estimation of value-at-risk is a challenging threat for the success of any financial investments. The degree of the model risk increases when the estimation process is constructed with a portfolio in the emerging markets. The proper model should both provide flexible joint distributions by splitting the marginality from the dependencies among the financial assets within the portfolio and also capture the non-linear behaviours and extremes in the returns arising from the special features of the emerging markets. In this study, we use time-varying copula to estimate the value-at-risk of the portfolio comprised of the Bovespa and the IPC Mexico in equal and constant weights. The performance comparison of the copula model to the EWMA portfolio model made by the Christoffersen back-test shows that the copula model captures the extremes most successfully. The copula model, by estimating the portfolio value-at-risk with the least violation number in the back-tests, provides the investors to allocate the minimum regulatory capital requirement in accordance with the Basel II Accord.

  16. In the interests of time: improving HIV allocative efficiency modelling via optimal time-varying allocations

    PubMed Central

    Shattock, Andrew J; Kerr, Cliff C; Stuart, Robyn M; Masaki, Emiko; Fraser, Nicole; Benedikt, Clemens; Gorgens, Marelize; Wilson, David P; Gray, Richard T

    2016-01-01

    Introduction International investment in the response to HIV and AIDS has plateaued and its future level is uncertain. With many countries committed to ending the epidemic, it is essential to allocate available resources efficiently over different response periods to maximize impact. The objective of this study is to propose a technique to determine the optimal allocation of funds over time across a set of HIV programmes to achieve desirable health outcomes. Methods We developed a technique to determine the optimal time-varying allocation of funds (1) when the future annual HIV budget is pre-defined and (2) when the total budget over a period is pre-defined, but the year-on-year budget is to be optimally determined. We use this methodology with Optima, an HIV transmission model that uses non-linear relationships between programme spending and associated programmatic outcomes to quantify the expected epidemiological impact of spending. We apply these methods to data collected from Zambia to determine the optimal distribution of resources to fund the right programmes, for the right people, at the right time. Results and discussion Considering realistic implementation and ethical constraints, we estimate that the optimal time-varying redistribution of the 2014 Zambian HIV budget between 2015 and 2025 will lead to a 7.6% (7.3% to 7.8%) decrease in cumulative new HIV infections compared with a baseline scenario where programme allocations remain at 2014 levels. This compares to a 5.1% (4.6% to 5.6%) reduction in new infections using an optimal allocation with constant programme spending that recommends unrealistic programmatic changes. Contrasting priorities for programme funding arise when assessing outcomes for a five-year funding period over 5-, 10- and 20-year time horizons. Conclusions Countries increasingly face the need to do more with the resources available. The methodology presented here can aid decision-makers in planning as to when to expand or contract

  17. JOINT STRUCTURE SELECTION AND ESTIMATION IN THE TIME-VARYING COEFFICIENT COX MODEL

    PubMed Central

    Xiao, Wei; Lu, Wenbin; Zhang, Hao Helen

    2016-01-01

    Time-varying coefficient Cox model has been widely studied and popularly used in survival data analysis due to its flexibility for modeling covariate effects. It is of great practical interest to accurately identify the structure of covariate effects in a time-varying coefficient Cox model, i.e. covariates with null effect, constant effect and truly time-varying effect, and estimate the corresponding regression coefficients. Combining the ideas of local polynomial smoothing and group nonnegative garrote, we develop a new penalization approach to achieve such goals. Our method is able to identify the underlying true model structure with probability tending to one and simultaneously estimate the time-varying coefficients consistently. The asymptotic normalities of the resulting estimators are also established. We demonstrate the performance of our method using simulations and an application to the primary biliary cirrhosis data. PMID:27540275

  18. A shortest path algorithm for satellite time-varying topological network

    NASA Astrophysics Data System (ADS)

    Zhang, Tao; Liu, Zhongkan; Zhuang, Jun

    2005-11-01

    Mobile satellite network is a special time-varying network. It is different from the classical fixed network and other time-dependent networks which have been studied. Therefore some classical network theories, such as the shortest path algorithm, can not be applied to it availably. However, no study about its shortest path problem has been done. In this paper, based on the proposed model of satellite time-varying topological network, the classical shortest path algorithm of fixed network, such as the Dijkstra algorithm, is proved to be restrictive when it is applied in satellite network. Here, a novel shortest path algorithm for satellite time-varying topological network is given and optimized. Correlative simulation indicates that this algorithm can be effectively applied to the satellite time-varying topological network.

  19. Synthesis procedure for linear time-varying feedback systems with large parameter ignorance

    NASA Technical Reports Server (NTRS)

    Mcdonald, T. E., Jr.

    1972-01-01

    The development of synthesis procedures for linear time-varying feedback systems is considered. It is assumed that the plant can be described by linear differential equations with time-varying coefficients; however, ignorance is associated with the plant in that only the range of the time-variations are known instead of exact functional relationships. As a result of this plant ignorance the use of time-varying compensation is ineffective so that only time-invariant compensation is employed. In addition, there is a noise source at the plant output which feeds noise through the feedback elements to the plant input. Because of this noise source the gain of the feedback elements must be as small as possible. No attempt is made to develop a stability criterion for time-varying systems in this work.

  20. Users manual for linear Time-Varying Helicopter Simulation (Program TVHIS)

    NASA Technical Reports Server (NTRS)

    Burns, M. R.

    1979-01-01

    A linear time-varying helicopter simulation program (TVHIS) is described. The program is designed as a realistic yet efficient helicopter simulation. It is based on a linear time-varying helicopter model which includes rotor, actuator, and sensor models, as well as a simulation of flight computer logic. The TVHIS can generate a mean trajectory simulation along a nominal trajectory, or propagate covariance of helicopter states, including rigid-body, turbulence, control command, controller states, and rigid-body state estimates.

  1. Arbitrary eigenvalue assignments for linear time-varying multivariable control systems

    NASA Technical Reports Server (NTRS)

    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.

  2. Applied Time Domain Stability Margin Assessment for Nonlinear Time-Varying Systems

    NASA Technical Reports Server (NTRS)

    Kiefer, J. M.; Johnson, M. D.; Wall, J. H.; Dominguez, A.

    2016-01-01

    The baseline stability margins for NASA's Space Launch System (SLS) launch vehicle were generated via the classical approach of linearizing the system equations of motion and determining the gain and phase margins from the resulting frequency domain model. To improve the fidelity of the classical methods, the linear frequency domain approach can be extended by replacing static, memoryless nonlinearities with describing functions. This technique, however, does not address the time varying nature of the dynamics of a launch vehicle in flight. An alternative technique for the evaluation of the stability of the nonlinear launch vehicle dynamics along its trajectory is to incrementally adjust the gain and/or time delay in the time domain simulation until the system exhibits unstable behavior. This technique has the added benefit of providing a direct comparison between the time domain and frequency domain tools in support of simulation validation. This technique was implemented by using the Stability Aerospace Vehicle Analysis Tool (SAVANT) computer simulation to evaluate the stability of the SLS system with the Adaptive Augmenting Control (AAC) active and inactive along its ascent trajectory. The gains for which the vehicle maintains apparent time-domain stability defines the gain margins, and the time delay similarly defines the phase margin. This method of extracting the control stability margins from the time-domain simulation is relatively straightforward and the resultant margins can be compared to the linearized system results. The sections herein describe the techniques employed to extract the time-domain margins, compare the results between these nonlinear and the linear methods, and provide explanations for observed discrepancies. The SLS ascent trajectory was simulated with SAVANT and the classical linear stability margins were evaluated at one second intervals. The linear analysis was performed with the AAC algorithm disabled to attain baseline stability

  3. Empirical mode decomposition as a time-varying multirate signal processing system

    NASA Astrophysics Data System (ADS)

    Yang, Yanli

    2016-08-01

    Empirical mode decomposition (EMD) can adaptively split composite signals into narrow subbands termed intrinsic mode functions (IMFs). Although an analytical expression of IMFs extracted by EMD from signals is introduced in Yang et al. (2013) [1], it is only used for the case of extrema spaced uniformly. In this paper, the EMD algorithm is analyzed from digital signal processing perspective for the case of extrema spaced nonuniformly. Firstly, the extrema extraction is represented by a time-varying extrema decimator. The nonuniform extrema extraction is analyzed through modeling the time-varying extrema decimation at a fixed time point as a time-invariant decimation. Secondly, by using the impulse/summation approach, spline interpolation for knots spaced nonuniformly is shown as two basic operations, time-varying interpolation and filtering by a time-varying spline filter. Thirdly, envelopes of signals are written as the output of the time-varying spline filter. An expression of envelopes of signals in both time and frequency domain is presented. The EMD algorithm is then described as a time-varying multirate signal processing system. Finally, an equation to model IMFs is derived by using a matrix formulation in time domain for the general case of extrema spaced nonuniformly.

  4. A Multi-Moded RF Delay Line Distribution System (MDLDS) for the Next Linear Collider

    SciTech Connect

    Nantista, Christopher D.

    2002-01-17

    The Delay Line Distribution System (DLDS) is an alternative to conventional pulse compression, which enhances the peak power of rf sources while matching the long pulse of those sources to the shorter filling time of accelerator structures. We present an implementation of this scheme that combines pairs of parallel delay lines of the system into single lines. The power of several sources is combined into a single waveguide delay line using a multi-mode launcher. The output mode of the launcher is determined by the phase coding of the input signals. The combined power is extracted from the delay line using mode-selective extractors, each of which extracts a single mode. Hence, the phase coding of the sources controls the output port of the combined power. The power is then fed to the local accelerator structures. We present a detailed design of such a system, including several implementation methods for the launchers, extractors, and ancillary high power rf components. The system is designed so that it can handle the 600 MW peak power required by the NLC design while maintaining high efficiency.

  5. Modeling and Calibration for Exposure to Time-Varying, Modifiable Risk Factors: The Example of Smoking Behavior in India

    PubMed Central

    Goldhaber-Fiebert, Jeremy D.; Brandeau, Margaret L.

    2014-01-01

    Background Risk factors increase chronic disease incidence and severity. To examine future trends and develop policies addressing chronic diseases, it is important to capture the relationship between exposure and disease development -- challenging given limited data. Objective To develop parsimonious risk factor models embeddable in chronic disease models, useful when longitudinal data are unavailable. Design 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. Methods The model is calibrated to prevalence of male smoking in 12 Indian regions estimated from the 2009–10 Indian Global Adult Tobacco Survey. Nelder-Mead searches (250,000 starting locations) identify distributions of starting, quitting, and re-starting 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 1–30 years. Results Calibration achieves concordance between modeled and observed outcomes. Probabilities of starting to smoke rise and fall with age, while quitting and re-starting 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 re-start. Conclusion The approach described is feasible for numerous chronic disease risk factors. Incorporating exposure-change rates can improve modeled estimates of chronic disease outcomes and long

  6. Stability of equations with a distributed delay, monotone production and nonlinear mortality

    NASA Astrophysics Data System (ADS)

    Berezansky, Leonid; Braverman, Elena

    2013-10-01

    We consider population dynamics models dN/dt = f(N(tτ)) - d(N(t)) with an increasing fecundity function f and any mortality function d which can be quadratic, as in the logistic equation, or have a different form provided that the equation has at most one positive equilibrium. Here the delay in the production term can be distributed and unbounded. It is demonstrated that the positive equilibrium is globally attractive if it exists, otherwise all positive solutions tend to zero. Moreover, we demonstrate that solutions of the equation are intrinsically non-oscillatory: once the initial function is less/greater than the equilibrium K > 0, so is the solution for any positive time value. The assumptions on f, d and the delay are rather nonrestrictive, and several examples demonstrate that none of them can be omitted.

  7. Model Predictive Optimal Control of a Time-Delay Distributed-Parameter Systems

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan

    2006-01-01

    This paper presents an optimal control method for a class of distributed-parameter systems governed by first order, quasilinear hyperbolic partial differential equations that arise in many physical systems. Such systems are characterized by time delays since information is transported from one state to another by wave propagation. A general closed-loop hyperbolic transport model is controlled by a boundary control embedded in a periodic boundary condition. The boundary control is subject to a nonlinear differential equation constraint that models actuator dynamics of the system. The hyperbolic equation is thus coupled with the ordinary differential equation via the boundary condition. Optimality of this coupled system is investigated using variational principles to seek an adjoint formulation of the optimal control problem. The results are then applied to implement a model predictive control design for a wind tunnel to eliminate a transport delay effect that causes a poor Mach number regulation.

  8. Consensus-based distributed estimation in multi-agent systems with time delay

    NASA Astrophysics Data System (ADS)

    Abdelmawgoud, Ahmed

    During the last years, research in the field of cooperative control of swarm of robots, especially Unmanned Aerial Vehicles (UAV); have been improved due to the increase of UAV applications. The ability to track targets using UAVs has a wide range of applications not only civilian but also military as well. For civilian applications, UAVs can perform tasks including, but not limited to: map an unknown area, weather forecasting, land survey, and search and rescue missions. On the other hand, for military personnel, UAV can track and locate a variety of objects, including the movement of enemy vehicles. Consensus problems arise in a number of applications including coordination of UAVs, information processing in wireless sensor networks, and distributed multi-agent optimization. We consider a widely studied consensus algorithms for processing sensed data by different sensors in wireless sensor networks of dynamic agents. Every agent involved in the network forms a weighted average of its own estimated value of some state with the values received from its neighboring agents. We introduced a novelty of consensus-based distributed estimation algorithms. We propose a new algorithm to reach a consensus given time delay constraints. The proposed algorithm performance was observed in a scenario where a swarm of UAVs measuring the location of a ground maneuvering target. We assume that each UAV computes its state prediction and shares it with its neighbors only. However, the shared information applied to different agents with variant time delays. The entire group of UAVs must reach a consensus on target state. Different scenarios were also simulated to examine the effectiveness and performance in terms of overall estimation error, disagreement between delayed and non-delayed agents, and time to reach a consensus for each parameter contributing on the proposed algorithm.

  9. Investigation of the delay time distribution of high power microwave surface flashover

    NASA Astrophysics Data System (ADS)

    Foster, J.; Krompholz, H.; Neuber, A.

    2011-01-01

    Characterizing and modeling the statistics associated with the initiation of gas breakdown has proven to be difficult due to a variety of rather unexplored phenomena involved. Experimental conditions for high power microwave window breakdown for pressures on the order of 100 to several 100 torr are complex: there are little to no naturally occurring free electrons in the breakdown region. The initial electron generation rate, from an external source, for example, is time dependent and so is the charge carrier amplification in the increasing radio frequency (RF) field amplitude with a rise time of 50 ns, which can be on the same order as the breakdown delay time. The probability of reaching a critical electron density within a given time period is composed of the statistical waiting time for the appearance of initiating electrons in the high-field region and the build-up of an avalanche with an inherent statistical distribution of the electron number. High power microwave breakdown and its delay time is of critical importance, since it limits the transmission through necessary windows, especially for high power, high altitude, low pressure applications. The delay time distribution of pulsed high power microwave surface flashover has been examined for nitrogen and argon as test gases for pressures ranging from 60 to 400 torr, with and without external UV illumination. A model has been developed for predicting the discharge delay time for these conditions. The results provide indications that field induced electron generation, other than standard field emission, plays a dominant role, which might be valid for other gas discharge types as well.

  10. Isosurface Extraction in Time-Varying Fields Using a Temporal Hierarchical Index Tree

    NASA Technical Reports Server (NTRS)

    Shen, Han-Wei; Gerald-Yamasaki, Michael (Technical Monitor)

    1998-01-01

    Many high-performance isosurface extraction algorithms have been proposed in the past several years as a result of intensive research efforts. When applying these algorithms to large-scale time-varying fields, the storage overhead incurred from storing the search index often becomes overwhelming. this paper proposes an algorithm for locating isosurface cells in time-varying fields. We devise a new data structure, called Temporal Hierarchical Index Tree, which utilizes the temporal coherence that exists in a time-varying field and adoptively coalesces the cells' extreme values over time; the resulting extreme values are then used to create the isosurface cell search index. For a typical time-varying scalar data set, not only does this temporal hierarchical index tree require much less storage space, but also the amount of I/O required to access the indices from the disk at different time steps is substantially reduced. We illustrate the utility and speed of our algorithm with data from several large-scale time-varying CID simulations. Our algorithm can achieve more than 80% of disk-space savings when compared with the existing techniques, while the isosurface extraction time is nearly optimal.

  11. Adaptive dynamic surface control for MIMO nonlinear time-varying systems with prescribed tracking performance

    NASA Astrophysics Data System (ADS)

    Wang, Chenliang; Lin, Yan

    2015-04-01

    In this paper, an adaptive dynamic surface control scheme is proposed for a class of multi-input multi-output (MIMO) nonlinear time-varying systems. By fusing a bound estimation approach, a smooth function and a time-varying matrix factorisation, the obstacle caused by unknown time-varying parameters is circumvented. The proposed scheme is free of the problem of explosion of complexity and needs only one updated parameter at each design step. Moreover, all tracking errors can converge to predefined arbitrarily small residual sets with a prescribed convergence rate and maximum overshoot. Such features result in a simple adaptive controller which can be easily implemented in applications with less computational burden and satisfactory tracking performance. Simulation results are presented to illustrate the effectiveness of the proposed scheme.

  12. Dynamic analysis of hoisting viscous damping string with time-varying length

    NASA Astrophysics Data System (ADS)

    Zhang, P.; Bao, J. H.; Zhu, C. M.

    2013-07-01

    The nonlinear dynamic analysis of a hoisting viscous damping string with time-varying length is investigated. The hoisting string is modeled as a taut translating string with a rigid body attached at its low end. A systematic procedure for deriving the system model of hoisting viscoelastic string with time-varying is presented. The governing equations are developed employing the extended Hamilton's principle considering coupling of axial movement and flexural deformation of string. The Galerkin's method and the 4th Runge-Kutta method are employed to numerically analyze the resulting equations. The motions of elevator hoisting system are presented to illustrate the proposed mathematical models. The results of simulation show that the material viscous damping helps stabilize the transverse vibration. The modeling methods can represent the transverse vibration of hoisting viscous damping string with time-varying length.

  13. Experimental Demonstration of Frequency Autolocking an Optical Cavity Using a Time-Varying Kalman Filter

    NASA Astrophysics Data System (ADS)

    Schütte, Dirk; Hassen, S. Z. Sayed; Karvinen, Kai S.; Boyson, Toby K.; Kallapur, Abhijit G.; Song, Hongbin; Petersen, Ian R.; Huntington, Elanor H.; Heurs, Michèle

    2016-01-01

    We propose and demonstrate a new autolocking scheme using a three-mirror ring cavity consisting of a linear quadratic regulator and a time-varying Kalman filter. Our technique does not require a frequency scan to acquire resonance. We utilize the singular perturbation method to simplify our system dynamics and to permit the application of linear control techniques. The error signal combined with the transmitted power is used to estimate the cavity detuning. This estimate is used by a linear time-varying Kalman filter which enables the implementation of an optimal controller. The experimental results validate the controller design, and we demonstrate improved robustness to disturbances and a faster locking time than a traditional proportional-integral controller. More important, the time-varying Kalman filtering approach automatically reacquires lock for large detunings, where the error signal leaves its linear capture range, a feat which linear time-invariant controllers cannot achieve.

  14. Parasitic modulation of electromagnetic signals caused by time-varying plasma

    SciTech Connect

    Yang, Min Li, Xiaoping; Xie, Kai; Liu, Yanming

    2015-02-15

    An experiment on the propagation of electromagnetic (EM) signals in continuous time-varying plasma is described. The time-varying characteristics of plasma are considered to cause a parasitic modulation in both amplitude and phase, and the strength of this modulation, which carries the information of the electron density profile, is closely related to the plasma frequency and the incident wave frequency. Through theoretical analysis, we give an explanation and mechanism of the interaction between the continuous time-varying plasma and EM waves, which is verified by a comparative analysis with experiments performed under the same conditions. The effects of this modulation on the EM signals in the plasma sheath cannot be ignored.

  15. Simulating a charged spherical pendulum in time-varying electric and magnetic fields

    NASA Astrophysics Data System (ADS)

    Wellons, Mark; King, Frank; McAlpine, Todd

    2008-03-01

    We simulate and analyze the dynamics of a charged spherical pendulum in time-varying electric and magnetic fields. The time-varying electric field is directed perpendicular to the gravitational field and serves as a driving force for the pendulum. The time-varying magnetic field is directed parallel to the gravitational field and serves to deflect the motion of the pendulum. We analyze the dynamics of the system to determine the conditions for which chaotic behavior is observed. We also include viscosity to look for strange attractors. The equations of motion are integrated using Objective C and the graphical user interface, including the three dimensional graphical representation of the system, is developed using Cocoa.

  16. Time-varying long term memory in the European Union stock markets

    NASA Astrophysics Data System (ADS)

    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.

  17. Exponential stability preservation in discrete-time analogues of artificial neural networks with distributed delays

    NASA Astrophysics Data System (ADS)

    Mohamad, Sannay

    2008-05-01

    This paper demonstrates that there is a discrete-time analogue which does not require any restriction on the size of the time-step in order to preserve the exponential stability of an artificial neural network with distributed delays. The analysis exploits an appropriate Lyapunov sequence and a discrete-time system of Halanay inequalities, and also either a Young inequality or a geometric-arithmetic mean inequality, to derive several sufficient conditions on the network parameters for the exponential stability of the analogue. The sufficiency conditions are independent of the time-step, and they correspond to those that establish the exponential stability of the continuous-time network.

  18. Distributed Interplanetary Delay/Disruption Tolerant Network (DTN) Monitor and Control System

    NASA Technical Reports Server (NTRS)

    Wang, Shin-Ywan

    2012-01-01

    The main purpose of Distributed interplanetary Delay Tolerant Network Monitor and Control System as a DTN system network management implementation in JPL is defined to provide methods and tools that can monitor the DTN operation status, detect and resolve DTN operation failures in some automated style while either space network or some heterogeneous network is infused with DTN capability. In this paper, "DTN Monitor and Control system in Deep Space Network (DSN)" exemplifies a case how DTN Monitor and Control system can be adapted into a space network as it is DTN enabled.

  19. Electrically-Tunable Group Delays Using Quantum Wells in a Distributed Bragg Reflector

    NASA Technical Reports Server (NTRS)

    Nelson, Thomas R., Jr.; Loehr, John P.; Fork, Richard L.; Cole, Spencer; Jones, Darryl K.; Keys, Andrew

    1999-01-01

    There is a growing interest in the fabrication of semiconductor optical group delay lines for the development of phased arrays of Vertical-Cavity Surface-Emitting Lasers (VCSELs). We present a novel structure incorporating In(x)GA(1-x)As quantum wells in the GaAs quarter-wave layers of a GaAs/AlAs distributed Bragg reflector (DBR). Application of an electric field across the quantum wells leads to red shifting and peak broadening of the el-hhl exciton peak via the quantum-confined Stark effect. Resultant changes in the index of refraction thereby provide a means for altering the group delay of an incident laser pulse. We discuss the tradeoffs between the maximum amount of change in group delay versus absorption losses for such a device. We also compare a simple theoretical model to experimental results, and discuss both angle and position tuning of the BDR band edge resonance relative to the exciton absorption peak. The advantages of such monolithically grown devices for phased-array VCSEL applications will be detailed.

  20. On delay adjustment for dynamic load balancing in distributed virtual environments.

    PubMed

    Deng, Yunhua; Lau, Rynson W H

    2012-04-01

    Distributed virtual environments (DVEs) are becoming very popular in recent years, due to the rapid growing of applications, such as massive multiplayer online games (MMOGs). As the number of concurrent users increases, scalability becomes one of the major challenges in designing an interactive DVE system. One solution to address this scalability problem is to adopt a multi-server architecture. While some methods focus on the quality of partitioning the load among the servers, others focus on the efficiency of the partitioning process itself. However, all these methods neglect the effect of network delay among the servers on the accuracy of the load balancing solutions. As we show in this paper, the change in the load of the servers due to network delay would affect the performance of the load balancing algorithm. In this work, we conduct a formal analysis of this problem and discuss two efficient delay adjustment schemes to address the problem. Our experimental results show that our proposed schemes can significantly improve the performance of the load balancing algorithm with neglectable computation overhead. PMID:22402679

  1. Investigation on the coloured noise in GPS-derived position with time-varying seasonal signals

    NASA Astrophysics Data System (ADS)

    Gruszczynska, Marta; Klos, Anna; Bos, Machiel Simon; Bogusz, Janusz

    2016-04-01

    The seasonal signals in the GPS-derived time series arise from real geophysical signals related to tidal (residual) or non-tidal (loadings from atmosphere, ocean and continental hydrosphere, thermo elastic strain, etc.) effects and numerical artefacts including aliasing from mismodelling in short periods or repeatability of the GPS satellite constellation with respect to the Sun (draconitics). Singular Spectrum Analysis (SSA) is a method for investigation of nonlinear dynamics, suitable to either stationary or non-stationary data series without prior knowledge about their character. The aim of SSA is to mathematically decompose the original time series into a sum of slowly varying trend, seasonal oscillations and noise. In this presentation we will explore the ability of SSA to subtract the time-varying seasonal signals in GPS-derived North-East-Up topocentric components and show properties of coloured noise from residua. For this purpose we used data from globally distributed IGS (International GNSS Service) permanent stations processed by the JPL (Jet Propulsion Laboratory) in a PPP (Precise Point Positioning) mode. After introducing a threshold of 13 years, 264 stations left with a maximum length reaching 23 years. The data was initially pre-processed for outliers, offsets and gaps. The SSA was applied to pre-processed series to estimate the time-varying seasonal signals. We adopted a 3-years window as the optimal dimension of its size determined with the Akaike's Information Criteria (AIC) values. A Fisher-Snedecor test corrected for the presence of temporal correlation was used to determine the statistical significance of reconstructed components. This procedure showed that first four components describing annual and semi-annual signals, are significant at a 99.7% confidence level, which corresponds to 3-sigma criterion. We compared the non-parametric SSA approach with a commonly chosen parametric Least-Squares Estimation that assumes constant amplitudes and

  2. Delay-dependent stability of neural networks of neutral type with time delay in the leakage term

    NASA Astrophysics Data System (ADS)

    Li, Xiaodi; Cao, Jinde

    2010-07-01

    This paper studies the global asymptotic stability of neural networks of neutral type with mixed delays. The mixed delays include constant delay in the leakage term (i.e. 'leakage delay'), time-varying delays and continuously distributed delays. Based on the topological degree theory, Lyapunov method and linear matrix inequality (LMI) approach, some sufficient conditions are derived ensuring the existence, uniqueness and global asymptotic stability of the equilibrium point, which are dependent on both the discrete and distributed time delays. These conditions are expressed in terms of LMI and can be easily checked by the MATLAB LMI toolbox. Even if there is no leakage delay, the obtained results are less restrictive than some recent works. It can be applied to neural networks of neutral type with activation functions without assuming their boundedness, monotonicity or differentiability. Moreover, the differentiability of the time-varying delay in the non-neutral term is removed. Finally, two numerical examples are given to show the effectiveness of the proposed method.

  3. The Role of Thermal Properties in Periodic Time-Varying Phenomena

    ERIC Educational Resources Information Center

    Marin, E.

    2007-01-01

    The role played by physical parameters governing the transport of heat in periodical time-varying phenomena within solids is discussed. Starting with a brief look at the conduction heat transport mechanism, the equations governing heat conduction under static, stationary and non-stationary conditions, and the physical parameters involved, are…

  4. Laser imaging of chemistry-flowfield interactions: Enhanced soot formation in time-varying diffusion flames

    SciTech Connect

    Harrington, J.E.; Shaddix, C.R.; Smyth, K.C.

    1994-12-31

    Models of detailed flame chemistry and soot formation are based upon experimental results obtained in steady, laminar flames. For successful application of these descriptions to turbulent combustion, it is instructive to test predictions against measurements in time-varying flowfields. This paper reports the use of optical methods to examine soot production and oxidation processes in a co-flowing, axisymmetric CH{sub 4}/air diffusion flame in which the fuel flow rate is acoustically forced to create a time-varying flowfield. For a particular forcing condition in which tip clipping occurs (0.75 V loudspeaker excitation), elastic scattering of vertically polarized light from the soot particles increases by nearly an order of magnitude with respect to that observed for a steady flame with the same mean fuel flow rate. The visible flame luminosity and laser-induced fluorescence attributed to polycyclic aromatic hydrocarbons (PAH) are also enhanced. Peak soot volume fractions, as measured by time-resolved laser extinction/tomography at 632.8 and 454.5 nm and calibrated laser-induced incandescence (LII), show a factor of 4--5 enhancement in this flickering flame. The LII method is found to track the soot volume fraction closely and to give better signal-to-noise than the extinction measurements in both the steady and time-varying flowfields. A Mie analysis suggests that most of the enhanced soot production results from the formation of larger particles in the time-varying flowfield.

  5. Distribution of the Latest Content in Dynamic Content Updates over Delay Tolerant Networks

    NASA Astrophysics Data System (ADS)

    Li, Yong; Jin, Depeng; Su, Li; Zeng, Lieguang

    The applications of dynamic content updates for a group of users, for example weather reports and news broadcast, have been shown to benefit significantly from Delay Tolerant Networks (DTNs) communication mechanisms. In this paper, we study the performance of dynamic content updates over DTNs by focusing on the latest content distribution, which is an important factor of the system energy consumption and content update efficiency. By characterizing the content generating process and content sharing process, we obtain an explicit expression for the latest content distribution, and prove it theoretically. Moreover, through simulations based on two synthetical mobility models and a real-world scenario, we demonstrate the accuracy and correctness of the theoretically obtained result.

  6. Finite-time consensus of time-varying nonlinear multi-agent systems

    NASA Astrophysics Data System (ADS)

    Liu, Qingrong; Liang, Zhishan

    2016-08-01

    This paper investigates the problem of leader-follower finite-time consensus for a class of time-varying nonlinear multi-agent systems. The dynamics of each agent is assumed to be represented by a strict feedback nonlinear system, where nonlinearities satisfy Lipschitz growth conditions with time-varying gains. The main design procedure is outlined as follows. First, it is shown that the leader-follower consensus problem is equivalent to a conventional control problem of multi-variable high-dimension systems. Second, by introducing a state transformation, the control problem is converted into the construction problem of two dynamic equations. Third, based on the Lyapunov stability theorem, the global finite-time stability of the closed-loop control system is proved, and the finite-time consensus of the concerned multi-agent systems is thus guaranteed. An example is given to verify the effectiveness of the proposed consensus protocol algorithm.

  7. When susceptible-infectious-susceptible contagion meets time-varying networks with identical infectivity

    NASA Astrophysics Data System (ADS)

    Zhang, Yi-Qing; Li, Xiang

    2014-10-01

    Transmission of infectious diseases among populations can be modelled as contagion processes on contact networks. These contact networks are highly evolved in time and are represented by time-varying networks. The agents in contagion processes may have finite infectivity independently of their connectivity. Here we present an analytical framework of the susceptible-infectious-susceptible contagion process on time-varying networks, namely activity-driven networks with identical infectivity. We derive the critical epidemic thresholds and immunization thresholds as a function of infectivity, and prove that targeted immunizations are more efficient than random immunizations independently of the infectivity. We validate our conclusions in a large-scale human indoor interaction data set. Finally, we assess the effects of finite size.

  8. An Integral Method for Determining Induced Voltage in Time-Varying Wire Inductors

    SciTech Connect

    Fasenfest, B; White, D; Rockway, J

    2005-05-27

    This report documents the creation of software tools to model time-varying wire inductors. The class of inductors studied consists of arbitrary wire shapes in nonmagnetic material. When the wire structures are deformed, the inductance changes, and a voltage is induced. This voltage is of interest, for instance when the inductor is used to measure or sense a shockwave. An integral technique, which only requires integrating over the wire segments, is used to find the inductance at each time step, with backwards-difference approximations being used on successive time steps to determine the voltage. This method allows for arbitrary time-varying wire structures. It was tested for several canonical problems and used to model a double helix solenoid compressed by a shockwave.

  9. Quantitative Characterization of Super-Resolution Infrared Imaging Based on Time-Varying Focal Plane Coding

    NASA Astrophysics Data System (ADS)

    Wang, X.; Yuan, Y.; Zhang, J.; Chen, Y.; Cheng, Y.

    2014-10-01

    High resolution infrared image has been the goal of an infrared imaging system. In this paper, a super-resolution infrared imaging method using time-varying coded mask is proposed based on focal plane coding and compressed sensing theory. The basic idea of this method is to set a coded mask on the focal plane of the optical system, and the same scene could be sampled many times repeatedly by using time-varying control coding strategy, the super-resolution image is further reconstructed by sparse optimization algorithm. The results of simulation are quantitatively evaluated by introducing the Peak Signal-to-Noise Ratio (PSNR) and Modulation Transfer Function (MTF), which illustrate that the effect of compressed measurement coefficient r and coded mask resolution m on the reconstructed image quality. Research results show that the proposed method will promote infrared imaging quality effectively, which will be helpful for the practical design of new type of high resolution ! infrared imaging systems.

  10. Time-varying transformations for Hill-Clohessy-Wiltshire solutions in elliptic orbits

    NASA Astrophysics Data System (ADS)

    Sherrill, Ryan E.; Sinclair, Andrew J.; Sinha, S. C.; Lovell, T. Alan

    2014-05-01

    The relative motion of chief and deputy satellites in close proximity with orbits of arbitrary eccentricity can be approximated by linearized time-periodic equations of motion. The linear time-invariant Hill-Clohessy-Wiltshire equations are typically derived from these equations by assuming the chief satellite is in a circular orbit. Two Lyapunov-Floquet transformations and an integral-preserving transformation are here presented which relate the linearized time-varying equations of relative motion to the Hill-Clohessy-Wiltshire equations in a one-to-one manner through time-varying coordinate transformations. These transformations allow the Hill-Clohessy-Wiltshire equations to describe the linearized relative motion for elliptic chief satellites.

  11. Applications, dosimetry and biological interactions of static and time-varying magnetic fields

    NASA Astrophysics Data System (ADS)

    Tenforde, T. S.

    1988-08-01

    The primary topics of this presentation include: (1) the applications of magnetic fields in research, industry, and medical technologies; (2) mechanisms of interaction of static and time-varying magnetic fields with living systems; (3) human health effects of exposure to static and time-varying magnetic fields in occupational, medical, and residential settings; and (4) recent advances in the dosimetry of extremely-low-frequency electromagnetic fields. The discussion of these topics is centered about two issues of considerable contemporary interest: (1) potential health effects of the fields used in magnetic resonance imaging and in vivo spectroscopy, and (2) the controversial issue of whether exposure to extremely-low-frequency (ELF) electromagnetic fields in the home and workplace leads to an elevated risk of cancer.

  12. Structural Nested Mean Models to Estimate the Effects of Time-Varying Treatments on Clustered Outcomes.

    PubMed

    He, Jiwei; Stephens-Shields, Alisa; Joffe, Marshall

    2015-11-01

    In assessing the efficacy of a time-varying treatment structural nested models (SNMs) are useful in dealing with confounding by variables affected by earlier treatments. These models often consider treatment allocation and repeated measures at the individual level. We extend SNMMs to clustered observations with time-varying confounding and treatments. We demonstrate how to formulate models with both cluster- and unit-level treatments and show how to derive semiparametric estimators of parameters in such models. For unit-level treatments, we consider interference, namely the effect of treatment on outcomes in other units of the same cluster. The properties of estimators are evaluated through simulations and compared with the conventional GEE regression method for clustered outcomes. To illustrate our method, we use data from the treatment arm of a glaucoma clinical trial to compare the effectiveness of two commonly used ocular hypertension medications. PMID:26115504

  13. Exponential networked synchronization of master-slave chaotic systems with time-varying communication topologies

    NASA Astrophysics Data System (ADS)

    Yang, Dong-Sheng; Liu, Zhen-Wei; Zhao, Yan; Liu, Zhao-Bing

    2012-04-01

    The networked synchronization problem of a class of master-slave chaotic systems with time-varying communication topologies is investigated in this paper. Based on algebraic graph theory and matrix theory, a simple linear state feedback controller is designed to synchronize the master chaotic system and the slave chaotic systems with a time-varying communication topology connection. The exponential stability of the closed-loop networked synchronization error system is guaranteed by applying Lyapunov stability theory. The derived novel criteria are in the form of linear matrix inequalities (LMIs), which are easy to examine and tremendously reduce the computation burden from the feedback matrices. This paper provides an alternative networked secure communication scheme which can be extended conveniently. An illustrative example is given to demonstrate the effectiveness of the proposed networked synchronization method.

  14. H∞ fault-tolerant control for time-varied actuator fault of nonlinear system

    NASA Astrophysics Data System (ADS)

    Liu, Chunsheng; Jiang, Bin

    2014-12-01

    This paper studies H∞ fault-tolerant control for a class of uncertain nonlinear systems subject to time-varied actuator faults. A radial basis function neural network is utilised to approximate the unknown nonlinear functions; an updating rule is designed to estimate on-line time-varied fault of actuator; and the controller with the states feedback and faults estimation is applied to compensate for the effects of fault and minimise H∞ performance criteria in order to get a desired H∞ disturbance rejection constraint. Sufficient conditions are derived, which guarantees that the closed-loop system is robustly stable and satisfies the H∞ performance in both normal and fault cases. In order to reduce computing cost, a simplified algorithm of matrix Riccati inequality is given. A spacecraft model is presented to demonstrate the effectiveness of the proposed methods.

  15. Time-varying creeping flow in an elastic shell enveloping a slender rigid center-body

    NASA Astrophysics Data System (ADS)

    Elbaz, Shai; Gat, Amir

    2014-11-01

    Flows in contact with elastic structures apply stress at the fluid-solid interface and thus create deformation fields in the solid. We study the time-varying interaction between elastic structures, subject to external forces, and an internal viscous liquid. We neglect inertia in the liquid and solid and focus on axi-symmetric annular flow enclosed by a thin-walled slender elastic shell and internally bounded by a variable cross-section rigid center-body. We employ elastic shell theory and the lubrication approximation to show that the problem is governed by the forced porous medium equation with regard to fluid pressure. We present several solutions of the flow-field and solid-deformation for various time-varying inlet pressure and external forces. The presented interaction between viscosity and elasticity may be applied to fields such as soft-robotics and micro-swimmers. Israel Science Foundation 818/13.

  16. Computer simulation of scalar vortex beams LG0L in time-varying random inhomogeneous media

    NASA Astrophysics Data System (ADS)

    Sennikov, Victor A.; Konyaev, Petr A.; Lukin, Vladimir P.

    2015-11-01

    Computer modeling of vortex beams LG0L propagation in random inhomogeneous media using the dynamic time varying algorithm of media evolution is presented. The temporal power spectrum of vortex beam LG0L has been investigated by numerical simulation of propagation through atmospheric turbulence. The split-step Fourier method was used for solving scalar wave equation for a randomly inhomogeneous medium with a power-law Kolmogorov spectrum.

  17. Piezoceramic devices and artificial intelligence time varying concepts in smart structures

    NASA Technical Reports Server (NTRS)

    Hanagud, S.; Calise, A. J.; Glass, B. J.

    1990-01-01

    The problem of development of smart structures and their vibration control by the use of piezoceramic sensors and actuators have been discussed. In particular, these structures are assumed to have time varying model form and parameters. The model form may change significantly and suddenly. Combined identification of the model from parameters of these structures and model adaptive control of these structures are discussed in this paper.

  18. Correcting for Measurement Error in Time-Varying Covariates in Marginal Structural Models.

    PubMed

    Kyle, Ryan P; Moodie, Erica E M; Klein, Marina B; Abrahamowicz, Michał

    2016-08-01

    Unbiased estimation of causal parameters from marginal structural models (MSMs) requires a fundamental assumption of no unmeasured confounding. Unfortunately, the time-varying covariates used to obtain inverse probability weights are often error-prone. Although substantial measurement error in important confounders is known to undermine control of confounders in conventional unweighted regression models, this issue has received comparatively limited attention in the MSM literature. Here we propose a novel application of the simulation-extrapolation (SIMEX) procedure to address measurement error in time-varying covariates, and we compare 2 approaches. The direct approach to SIMEX-based correction targets outcome model parameters, while the indirect approach corrects the weights estimated using the exposure model. We assess the performance of the proposed methods in simulations under different clinically plausible assumptions. The simulations demonstrate that measurement errors in time-dependent covariates may induce substantial bias in MSM estimators of causal effects of time-varying exposures, and that both proposed SIMEX approaches yield practically unbiased estimates in scenarios featuring low-to-moderate degrees of error. We illustrate the proposed approach in a simple analysis of the relationship between sustained virological response and liver fibrosis progression among persons infected with hepatitis C virus, while accounting for measurement error in γ-glutamyltransferase, using data collected in the Canadian Co-infection Cohort Study from 2003 to 2014. PMID:27416840

  19. State space modeling of time-varying contemporaneous and lagged relations in connectivity maps.

    PubMed

    Molenaar, Peter C M; Beltz, Adriene M; Gates, Kathleen M; Wilson, Stephen J

    2016-01-15

    Most connectivity mapping techniques for neuroimaging data assume stationarity (i.e., network parameters are constant across time), but this assumption does not always hold true. The authors provide a description of a new approach for simultaneously detecting time-varying (or dynamic) contemporaneous and lagged relations in brain connectivity maps. Specifically, they use a novel raw data likelihood estimation technique (involving a second-order extended Kalman filter/smoother embedded in a nonlinear optimizer) to determine the variances of the random walks associated with state space model parameters and their autoregressive components. The authors illustrate their approach with simulated and blood oxygen level-dependent functional magnetic resonance imaging data from 30 daily cigarette smokers performing a verbal working memory task, focusing on seven regions of interest (ROIs). Twelve participants had dynamic directed functional connectivity maps: Eleven had one or more time-varying contemporaneous ROI state loadings, and one had a time-varying autoregressive parameter. Compared to smokers without dynamic maps, smokers with dynamic maps performed the task with greater accuracy. Thus, accurate detection of dynamic brain processes is meaningfully related to behavior in a clinical sample. PMID:26546863

  20. Opinion formation in time-varying social networks: The case of the naming game

    NASA Astrophysics Data System (ADS)

    Maity, Suman Kalyan; Manoj, T. Venkat; Mukherjee, Animesh

    2012-09-01

    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. In particular, we perform a computational exploration of this model using simulations on top of real networks. We investigate the outcomes of the dynamics on two different types of time-varying data: (1) the networks vary on a day-to-day basis and (2) the networks vary within very short intervals of time (20 sec). 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 of the game that differ largely from what has been reported in the existing literature.

  1. Time-varying nonstationary multivariate risk analysis using a dynamic Bayesian copula

    NASA Astrophysics Data System (ADS)

    Sarhadi, Ali; Burn, Donald H.; Concepción Ausín, María.; Wiper, Michael P.

    2016-03-01

    A time-varying risk analysis is proposed for an adaptive design framework in nonstationary conditions arising from climate change. A Bayesian, dynamic conditional copula is developed for modeling the time-varying dependence structure between mixed continuous and discrete multiattributes of multidimensional hydrometeorological phenomena. Joint Bayesian inference is carried out to fit the marginals and copula in an illustrative example using an adaptive, Gibbs Markov Chain Monte Carlo (MCMC) sampler. Posterior mean estimates and credible intervals are provided for the model parameters and the Deviance Information Criterion (DIC) is used to select the model that best captures different forms of nonstationarity over time. This study also introduces a fully Bayesian, time-varying joint return period for multivariate time-dependent risk analysis in nonstationary environments. The results demonstrate that the nature and the risk of extreme-climate multidimensional processes are changed over time under the impact of climate change, and accordingly the long-term decision making strategies should be updated based on the anomalies of the nonstationary environment.

  2. Time-Varying Vocal Folds Vibration Detection Using a 24 GHz Portable Auditory Radar.

    PubMed

    Hong, Hong; Zhao, Heng; Peng, Zhengyu; Li, Hui; Gu, Chen; Li, Changzhi; Zhu, Xiaohua

    2016-01-01

    Time-varying vocal folds vibration information is of crucial importance in speech processing, and the traditional devices to acquire speech signals are easily smeared by the high background noise and voice interference. In this paper, we present a non-acoustic way to capture the human vocal folds vibration using a 24-GHz portable auditory radar. Since the vocal folds vibration only reaches several millimeters, the high operating frequency and the 4 × 4 array antennas are applied to achieve the high sensitivity. The Variational Mode Decomposition (VMD) based algorithm is proposed to decompose the radar-detected auditory signal into a sequence of intrinsic modes firstly, and then, extract the time-varying vocal folds vibration frequency from the corresponding mode. Feasibility demonstration, evaluation, and comparison are conducted with tonal and non-tonal languages, and the low relative errors show a high consistency between the radar-detected auditory time-varying vocal folds vibration and acoustic fundamental frequency, except that the auditory radar significantly improves the frequency-resolving power. PMID:27483261

  3. Model selection and change detection for a time-varying mean in process monitoring

    NASA Astrophysics Data System (ADS)

    Burr, Tom; Hamada, Michael S.; Ticknor, Larry; Weaver, Brian

    2014-07-01

    Process monitoring (PM) for nuclear safeguards sometimes requires estimation of thresholds corresponding to small false alarm rates. Threshold estimation is an old topic; however, because possible new roles for PM are being evaluated in nuclear safeguards, it is timely to consider modern model selection options in the context of alarm threshold estimation. One of the possible new PM roles involves PM residuals, where a residual is defined as residual=data-prediction. This paper briefly reviews alarm threshold estimation, introduces model selection options, and considers several assumptions regarding the data-generating mechanism for PM residuals. Four PM examples from nuclear safeguards are included. One example involves frequent by-batch material balance closures where a dissolution vessel has time-varying efficiency, leading to time-varying material holdup. Another example involves periodic partial cleanout of in-process inventory, leading to challenging structure in the time series of PM residuals. Our main focus is model selection to select a defensible model for normal behavior with a time-varying mean in a PM residual stream. We use approximate Bayesian computation to perform the model selection and parameter estimation for normal behavior. We then describe a simple lag-one-differencing option similar to that used to monitor non-stationary times series to monitor for off-normal behavior.

  4. Time-varying modal parameters identification of a spacecraft with rotating flexible appendage by recursive algorithm

    NASA Astrophysics Data System (ADS)

    Ni, Zhiyu; Mu, Ruinan; Xun, Guangbin; Wu, Zhigang

    2016-01-01

    The rotation of spacecraft flexible appendage may cause changes in modal parameters. For this time-varying system, the computation cost of the frequently-used singular value decomposition (SVD) identification method is high. Some control problems, such as the self-adaptive control, need the latest modal parameters to update the controller parameters in time. In this paper, the projection approximation subspace tracking (PAST) recursive algorithm is applied as an alternative method to identify the time-varying modal parameters. This method avoids the SVD by signal subspace projection and improves the computational efficiency. To verify the ability of this recursive algorithm in spacecraft modal parameters identification, a spacecraft model with rapid rotational appendage, Soil Moisture Active/Passive (SMAP) satellite, is established, and the time-varying modal parameters of the satellite are identified recursively by designing the input and output signals. The results illustrate that this recursive algorithm can obtain the modal parameters in the high signal noise ratio (SNR) and it has better computational efficiency than the SVD method. Moreover, to improve the identification precision of this recursive algorithm in the low SNR, the wavelet de-noising technology is used to decrease the effect of noises.

  5. Multimodal Pilot Behavior in Multi-Axis Tracking Tasks with Time-Varying Motion Cueing Gains

    NASA Technical Reports Server (NTRS)

    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.

  6. Stochastic Modeling and Power Control of Time-Varying Wireless Communication Networks

    SciTech Connect

    Olama, Mohammed M; Djouadi, Seddik M; Charalambous, Prof. Charalambos

    2014-01-01

    Wireless networks are characterized by nodes mobility, which makes the propagation environment time-varying and subject to fading. As a consequence, the statistical characteristics of the received signal vary continuously, giving rise to a Doppler power spectral density (DPSD) that varies from one observation instant to the next. This paper is concerned with dynamical modeling of time-varying wireless fading channels, their estimation and parameter identification, and optimal power control from received signal measurement data. The wireless channel is characterized using a stochastic state-space form and derived by approximating the time-varying DPSD of the channel. The expected maximization and Kalman filter are employed to recursively identify and estimate the channel parameters and states, respectively, from online received signal strength measured data. Moreover, we investigate a centralized optimal power control algorithm based on predictable strategies and employing the estimated channel parameters and states. The proposed models together with the estimation and power control algorithms are tested using experimental measurement data and the results are presented.

  7. Estimating time-varying effects for overdispersed recurrent events data with treatment switching

    PubMed Central

    CHEN, QINGXIA; ZENG, DONGLIN; IBRAHIM, JOSEPH G.; AKACHA, MOUNA; SCHMIDLI, HEINZ

    2014-01-01

    Summary In the analysis of multivariate event times, frailty models assuming time-independent regression coefficients are often considered, mainly due to their mathematical convenience. In practice, regression coefficients are often time dependent and the temporal effects are of clinical interest. Motivated by a phase III clinical trial in multiple sclerosis, we develop a semiparametric frailty modelling approach to estimate time-varying effects for overdispersed recurrent events data with treatment switching. The proposed model incorporates the treatment switching time in the time-varying coefficients. Theoretical properties of the proposed model are established and an efficient expectation-maximization algorithm is derived to obtain the maximum likelihood estimates. Simulation studies evaluate the numerical performance of the proposed model under various temporal treatment effect curves. The ideas in this paper can also be used for time-varying coefficient frailty models without treatment switching as well as for alternative models when the proportional hazard assumption is violated. A multiple sclerosis dataset is analysed to illustrate our methodology. PMID:24465031

  8. Time-varying effect modeling with longitudinal data truncated by death: conditional models, interpretations, and inference.

    PubMed

    Estes, Jason P; Nguyen, Danh V; Dalrymple, Lorien S; Mu, Yi; Şentürk, Damla

    2016-05-20

    Recent studies found that infection-related hospitalization was associated with increased risk of cardiovascular (CV) events, such as myocardial infarction and stroke in the dialysis population. In this work, we develop time-varying effects modeling tools in order to examine the CV outcome risk trajectories during the time periods before and after an initial infection-related hospitalization. For this, we propose partly conditional and fully conditional partially linear generalized varying coefficient models (PL-GVCMs) for modeling time-varying effects in longitudinal data with substantial follow-up truncation by death. Unconditional models that implicitly target an immortal population is not a relevant target of inference in applications involving a population with high mortality, like the dialysis population. A partly conditional model characterizes the outcome trajectory for the dynamic cohort of survivors, where each point in the longitudinal trajectory represents a snapshot of the population relationships among subjects who are alive at that time point. In contrast, a fully conditional approach models the time-varying effects of the population stratified by the actual time of death, where the mean response characterizes individual trends in each cohort stratum. We compare and contrast partly and fully conditional PL-GVCMs in our aforementioned application using hospitalization data from the United States Renal Data System. For inference, we develop generalized likelihood ratio tests. Simulation studies examine the efficacy of estimation and inference procedures. Copyright © 2015 John Wiley & Sons, Ltd. PMID:26646582

  9. Analysis on the exclusiveness of turbulence suppression between static and time-varying shear flow

    NASA Astrophysics Data System (ADS)

    Zhang, Y. Z.; Xie, T.; Mahajan, S. M.

    2012-02-01

    The analytical theory of turbulence suppression by shear flow [Y. Z. Zhang and S. M. Mahajan, Phys. Fluids B 4, 1385 (1992)] is extended to analyze the combined actions of flows that have time-varying as well as static components. It is found that each component, appearing alone, may yield the same suppression level. However, when both components co-exist, either tends to diminish the suppression caused by the other in certain parameter ranges—a conclusion that agrees with recently published simulation results by Maeyama et al. [Phys. Plasmas 17, 062305 (2010)]. In particular, the mutual exclusiveness is maximized as the strengths of the two components become comparable. The adopted averaging method of the asymptotic theory reveals that it is the coupling between the time-varying shear flow and the induced time-varying relative orbit motion that causes the asymmetry of the two components in turbulence suppression. The numerical results based on a Floquet analysis are also presented for comparison. The implications of the theory to L-H transition on tokamaks are discussed, especially, regarding experimental observations of the disappearance of the geodesic acoustic mode in H phases.

  10. Time-invariant measurement of time-varying bioimpedance using vector impedance analysis.

    PubMed

    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. PMID:25700023

  11. A comparison of DC and time-varying measurement of electrical conductivity in randomly generated two-phase networks.

    NASA Astrophysics Data System (ADS)

    Mandolesi, Eric; Moorkamp, Max; Jones, Alan G.

    2015-04-01

    Most electromagnetic (EM) geophysical methods focus on the electrical properties of rocks and sediments to determine reliable images of the subsurface, images routinely used in a broad range of applications. Often laboratory measurements of the same EM properties return equivocal results that are difficult to reconcile with observations obtained by EM imaging techniques. These inconsistencies lead to major interpretation problems. Different numerical approaches have been investigated in order to understand the consequences of the presence or absence of interconnected networks of fractures and pores on EM field measurements. These networks have a crucial effect on the EM field measurements, given that they can be permeated by conductive fluids that enhance the conductivity measurements of the whole environment. Most of the above-mentioned studies restrict their examination to direct current (DC) sources only. Bearing in mind that the time-varying nature of the natural electromagnetic sources play a major role in field measurements, we numerically model the effects of such EM sources on the conductivity measured on the surface of a randomly generated three-dimensional body buried in a uniform conductivity host by simulating a magnetotelluric (MT) station measurements on the top of the target random host itself. As a second experiment we simulated a DC measurement of the target bulk conductivity. The spatial distribution and shape of the conductor network allows in fact the propagation of time-varying EM fields by induction, leading the two different methods to measure a different numerical value for the bulk of the same physical property. We have compared the results from the simulated measurements obtained considering time-varying and DC sources with electrical conductivity predicted by both Hashin-Shtrikman (HS) bounds and Archie's Law, and we have compared these results with statistical properties of the model themselves. Our results suggest that for time-varying

  12. pp ii Global exponential stability and periodic solutions of Cohen-Grossberg neural networks with continuously distributed delays

    NASA Astrophysics Data System (ADS)

    Sun, Jianhua; Wan, Li

    2005-08-01

    Convergence dynamics of Cohen-Grossberg neural networks (CGNNs) with continuously distributed delays are discussed. Without assuming the differentiability and monotonicity of activation functions, the differentiability of amplification functions and the symmetry of synaptic interconnection weights, by skilfully constructing suitable Lyapunov functionals and employing inequality technique, three sets of easily verifiable delay independent criteria to guarantee the global exponential stability of a unique equilibrium point are given, and moreover, by constructing Poincaré mapping, other three sets of easily verifiable delay independent criteria to assure the existence and globally exponential stability of periodic solutions are obtained. Six examples are given to illustrate the theoretical results.

  13. Analysis of an SIR Epidemic Model with Pulse Vaccination and Distributed Time Delay

    PubMed Central

    Gao, Shujing; Teng, Zhidong; Nieto, Juan J.; Torres, Angela

    2007-01-01

    Pulse vaccination, the repeated application of vaccine over a defined age range, is gaining prominence as an effective strategy for the elimination of infectious diseases. An SIR epidemic model with pulse vaccination and distributed time delay is proposed in this paper. Using the discrete dynamical system determined by the stroboscopic map, we obtain the exact infection-free periodic solution of the impulsive epidemic system and prove that the infection-free periodic solution is globally attractive if the vaccination rate is larger enough. Moreover, we show that the disease is uniformly persistent if the vaccination rate is less than some critical value. The permanence of the model is investigated analytically. Our results indicate that a large pulse vaccination rate is sufficient for the eradication of the disease. PMID:18322563

  14. Failure Modes in Capacitors When Tested Under a Time-Varying Stress

    NASA Technical Reports Server (NTRS)

    Liu, David (Donhang)

    2011-01-01

    Power-on failure has been the prevalent failure mechanism for solid tantalum capacitors in decoupling applications. A surge step stress test (SSST) has been previously applied to identify the critical stress level of a capacitor batch to give some predictability to the power-on failure mechanism [1]. But SSST can also be viewed as an electrically destructive test under a time-varying stress (voltage). It consists of rapidly charging the capacitor with incremental voltage increases, through a low resistance in series, until the capacitor under test is electrically shorted. When the reliability of capacitors is evaluated, a highly accelerated life test (HALT) is usually adopted since it is a time-efficient method of determining the failure mechanism; however, a destructive test under a time-varying stress such as SSST is even more time efficient. It usually takes days or weeks to complete a HALT test, but it only takes minutes for a time-varying stress test to produce failures. The advantage of incorporating a specific time-varying stress profile into a statistical model is significant in providing an alternative life test method for quickly revealing the failure mechanism in capacitors. In this paper, a time-varying stress that mimics a typical SSST has been incorporated into the Weibull model to characterize the failure mechanism in different types of capacitors. The SSST circuit and transient conditions for correctly surge testing capacitors are discussed. Finally, the SSST was applied for testing Ta capacitors, polymer aluminum capacitors (PA capacitors), and multi-layer ceramic (MLC) capacitors with both precious metal electrodes (PME) and base metal electrodes (BME). The test results are found to be directly associated with the dielectric layer breakdown in Ta and PA capacitors and are independent of the capacitor values, the way the capacitors were built, and the capacitors manufacturers. The test results also show that MLC capacitors exhibit surge breakdown

  15. Using Time-Varying Sensitivity Analysis to Understand the Effects of Model Formulation on Model Behavior

    NASA Astrophysics Data System (ADS)

    Herman, J. D.; Reed, P. M.; Wagener, T.

    2012-12-01

    Lumped rainfall-runoff models are widely used for flow prediction, but a long-recognized need exists for diagnostic tools to determine whether the process-level behavior of a model aligns with the expectations inherent in its formulation. To this end, we develop a comprehensive exploration of dominant processes in the Hymod, HBV, and Sacramento Soil Moisture Accounting (SAC-SMA) model structures. Model controls are isolated using time-varying Sobol sensitivity analysis for twelve MOPEX watersheds in the eastern United States over a ten-year period. Sensitivity indices are visualized along gradients of observed precipitation and flow characteristics to identify key behavioral differences between the three models and to connect these back to the models' underlying assumptions. Results indicate that dominant processes strongly depend on time-varying hydroclimatic conditions. Parameters associated with surface processes generally dominate under dry conditions, while parameters associated with routing processes dominate under high flow conditions. The results highlight significant inter-model differences in dominant processes, even in models sharing the same process formulation (e.g., the soil moisture formulation in the Hymod and HBV models). The dominant processes identified are often counterintuitive; even these simple models represent complex, nonlinear systems, and the links between formulation and behavior are very difficult to discern a priori as complexity increases. Scrutinizing the links between model formulation and behavior becomes an important diagnostic approach, particularly in applications such as predictions under change where it is critical to identify how a model's dominant processes shift under hydrologic extremes. Sensitive parameters in the (a) Hymod, (b) SAC-SMA, and (c) HBV watershed models as conditions change from dry to wet. This is a qualitative summary of the time-varying sensitivity indices from twelve watersheds across a range of

  16. Perturbation analysis of queueing systems with a time-varying arrival rate

    NASA Technical Reports Server (NTRS)

    Cassandras, Christos G.; Pan, Jie

    1991-01-01

    The authors consider an M/G/1 queuing with a time-varying arrival rate. The objective is to obtain infinitesimal perturbation analysis (IPA) gradient estimates for various performance measures of interest with respect to certain system parameters. In particular, the authors consider the mean system time over n arrivals and an arrival rate alternating between two values. By choosing a convenient sample path representation of this system, they derive an unbiased IPA gradient estimator which, however, is not consistent, and investigate the nature of this problem.

  17. Indirect M-MRAC for Systems with Time Varying Parameters and Bounded Disturbances

    NASA Technical Reports Server (NTRS)

    Stepanyan, Vahram; Krishnakumar, Kalmanje

    2012-01-01

    The paper presents a prediction-identification model based adaptive control method for uncertain systems with time varying parameters in the presence of bounded external disturbances. The method guarantees desired tracking performance for the system s state and input signals. This is achieved by feeding back the state prediction error to the identification model. It is shown that the desired closed-loop properties are obtained with fast adaptation when the error feedback gain is selected proportional to the square root of the adaptation rate. The theoretical findings are confirmed via a simulation example.

  18. Time-varying Reeb Graphs for Continuous Space-Time Data

    SciTech Connect

    Edelsbrunner, H; Harer, J; Mascarenhas, A; Pascucci, V; Snoeyink, J

    2008-04-22

    The Reeb graph is a useful tool in visualizing real-valued data obtained from computational simulations of physical processes. We characterize the evolution of the Reeb graph of a time-varying continuous function defined in three-dimensional space. We show how to maintain the Reeb graph over time and compress the entire sequence of Reeb graphs into a single, partially persistent data structure, and augment this data structure with Betti numbers to describe the topology of level sets and with path seeds to assist in the fast extraction of level sets for visualization.

  19. A Method of Slowing and Cooling Molecules and Neutral Atoms Using Time Varying Electric Field Gradients

    NASA Astrophysics Data System (ADS)

    Gould, Harvey; Maddi, Jason; Dinneen, Timothy

    2000-06-01

    Time-invariant electric field gradients have long been used to deflect beams of molecules and neutral atoms. However, time-varying electric field gradients can also be used to accelerate, slow [1,2], cool [2], or bunch these same beams. The possible applications include slowing and cooling thermal beams of molecules and atoms, launching cold atoms from a trap into a fountain, beam transport, and measuring atomic dipole polarizabilities. [1] H.L. Bethlem, G. Berden, and G Meijer, Phys. Rev. Lett. 83, 1588 (1999). [2] J. A. Maddi, T.P. Dinneen, and H. Gould, Phys. Rev. A60, 3882 (1999).

  20. Dealing with periodical loads and harmonics in operational modal analysis using time-varying transmissibility functions

    NASA Astrophysics Data System (ADS)

    Weijtjens, Wout; Lataire, John; Devriendt, Christof; Guillaume, Patrick

    2014-12-01

    Periodical loads, such as waves and rotating machinery, form a problem for operational modal analysis (OMA). In OMA only the vibrations of a structure of interest are measured and little to nothing is known about the loads causing these vibrations. Therefore, it is often assumed that all dynamics in the measured data are linked to the system of interest. Periodical loads defy this assumption as their periodical behavior is often visible within the measured vibrations. As a consequence most OMA techniques falsely associate the dynamics of the periodical load with the system of interest. Without additional information about the load, one is not able to correctly differentiate between structural dynamics and the dynamics of the load. In several applications, e.g. turbines and helicopters, it was observed that because of periodical loads one was unable to correctly identify one or multiple modes. Transmissibility based OMA (TOMA) is a completely different approach to OMA. By using transmissibility functions to estimate the structural dynamics of the system of interest, all influence of the load-spectrum can be eliminated. TOMA therefore allows to identify the modal parameters without being influenced by the presence of periodical loads, such as harmonics. One of the difficulties of TOMA is that the analyst is required to find two independent datasets, each associated with a different loading condition of the system of interest. This poses a dilemma for TOMA; how can an analyst identify two different loading conditions when little is known about the loads on the system? This paper tackles that problem by assuming that the loading conditions vary continuously over time, e.g. the changing wind directions. From this assumption TOMA is developed into a time-varying framework. This development allows TOMA to not only cope with the continuously changing loading conditions. The time-varying framework also enables the identification of the modal parameters from a single dataset

  1. Performance of DPSK with convolutional encoding on time-varying fading channels

    NASA Technical Reports Server (NTRS)

    Mui, S. Y.; Modestino, J. W.

    1977-01-01

    The bit error probability performance of a differentially-coherent phase-shift keyed (DPSK) modem with convolutional encoding and Viterbi decoding on time-varying fading channels is examined. Both the Rician and the lognormal channels are considered. Bit error probability upper bounds on fully-interleaved (zero-memory) fading channels are derived and substantiated by computer simulation. It is shown that the resulting coded system performance is a relatively insensitive function of the choice of channel model provided that the channel parameters are related according to the correspondence developed as part of this paper. Finally, a comparison of DPSK with a number of other modulation strategies is provided.

  2. A novel time varying signal processing method for Coriolis mass flowmeter.

    PubMed

    Shen, Ting-Ao; Tu, Ya-Qing; Zhang, Hai-Tao

    2014-06-01

    The precision of frequency tracking method and phase difference calculation method affects the measurement precision of Coriolis Mass Flowmeter directly. To improve the accuracy of the mass flowrate, a novel signal processing method for Coriolis Mass Flowmeter is proposed for this time varying signal, which is comprised of a modified adaptive lattice notch filter and a revised sliding recursive discrete-time Fourier transform algorithm. The method cannot only track the change of frequency continuously, but also ensure the calculation accuracy when measuring phase difference. The computational load of the proposed method is small with higher accuracy. Simulation and experiment results show that the proposed method is effective. PMID:24985861

  3. Cascaded coherent tracking systems with time-varying channels. [for spacecraft

    NASA Technical Reports Server (NTRS)

    Weber, W. J., III; Yuen, J. H.

    1976-01-01

    A performance analysis is presented of a two-way coherent tracking system (of the type used for spacecraft tracking and navigation) in which the transmitted signals have pass through linear time-varying channels. The performance of the system is characterized by the steady state probability density function of the reduced phase error process in the second tracking loop, the system considered consisting of two first-order phase locked loops in cascade. While the log normal channel, which arises in communication through planetary atmospheres, was used as the channel model, the results can be extended to other channels, such as the Rice and Rayleigh channels.

  4. Time-Varying Expression of the Formation Flying along Circular Trajectories

    NASA Technical Reports Server (NTRS)

    Kawaguchi, Jun'ichiro

    2007-01-01

    Usually, the formation flying associated with circular orbits is discussed through the well-known Hill s or C-W equations of motion. This paper dares to present and discuss the coordinates that may contain time-varying coefficients. The discussion presents how the controller s performance is affected by the selection of coordinates, and also looks at the special coordinate suitable for designating a target bin to which each spacecraft in the formation has only to be guided. It is revealed that the latter strategy may incorporate the J2 disturbance automatically.

  5. On stability of cooperative and hereditary systems with a distributed delay

    NASA Astrophysics Data System (ADS)

    Berezansky, Leonid; Braverman, Elena

    2015-06-01

    We consider a system \\frac{dx}{dt}=r_1(t) G_1(x) [ \\inth_1(t)t f_1(y(s))~ds R1 (t,s) - x(t) ] , \\frac{dy}{dt}=r_2(t) G_2(y) [ \\inth_2(t)t f_2(x(s))~ds R2 (t,s) - y(t)] with increasing functions f1 and f2, which has at most one positive equilibrium. Here the values of the functions ri, Gi, fi are positive for positive arguments, the delays in the cooperative term can be distributed and unbounded, both systems with concentrated delays and integro-differential systems are a particular case of the considered system. Analyzing the relation of the functions f1 and f2, we obtain several possible scenarios of the global behaviour. They include the cases when all nontrivial positive solutions tend to the same attractor which can be the positive equilibrium, the origin or infinity. Another possibility is the dependency of asymptotics on the initial conditions: either solutions with large enough initial values tend to the equilibrium, while others tend to zero, or solutions with small enough initial values tend to the equilibrium, while others infinitely grow. In some sense solutions of the equation are intrinsically non-oscillatory: if both initial functions are less/greater than the equilibrium value, so is the solution for any positive time value. The paper continues the study of equations with monotone production functions initiated in Berezansky and Braverman (2013 Nonlinearity 26 2833-49).

  6. Adaptive sliding control of non-autonomous active suspension systems with time-varying loadings

    NASA Astrophysics Data System (ADS)

    Chen, Po-Chang; Huang, An-Chyau

    2005-04-01

    An adaptive sliding controller is proposed in this paper for controlling a non-autonomous quarter-car suspension system with time-varying loadings. The bound of the car-body loading is assumed to be available. Then, the reference coordinate is placed at the static position under the nominal loading so that the system dynamic equation is derived. Due to spring nonlinearities, the system property becomes asymmetric after coordinate transformation. Besides, in practical cases, system parameters are not easy to be obtained precisely for controller design. Therefore, in this paper, system uncertainties are lumped into two unknown time-varying functions. Since the variation bound of one of the unknown functions is not available, conventional adaptive schemes and robust designs are not applicable. To deal with this problem, the function approximation technique is employed to represent the unknown function as a finite combination of basis functions. The Lyapunov direct method can thus be used to find adaptive laws for updating coefficients in the approximating series and to prove stability of the closed-loop system. Since the position and velocity measurements of the unsprung mass are lumped into the unknown function, there is no need to install sensors on the axle and wheel assembly in the actual implementation. Simulation results are presented to show the performance of the proposed strategy.

  7. Adaptive algorithm for blind separation from noisy time-varying mixtures.

    PubMed

    Koivunen, V; Enescu, M; Oja, E

    2001-10-01

    This article addresses the problem of blind source separation from time-varying noisy mixtures using a state variable model and recursive estimation. An estimate of each source signal is produced real time at the arrival of new observed mixture vector. The goal is to perform the separation and attenuate noise simultaneously, as well as to adapt to changes that occur in the mixing system. The observed data are projected along the eigenvectors in signal subspace. The subspace is tracked real time. Source signals are modeled using low-order AR (autoregressive) models, and noise is attenuated by trading off between the model and the information provided by measurements. The type of zero-memory nonlinearity needed in separation is determined on-line. Predictor-corrector filter structures are proposed, and their performance is investigated in simulation using biomedical and communications signals at different noise levels and a time-varying mixing system. In quantitative comparison to other widely used methods, significant improvement in output signal-to-noise ratio is achieved. PMID:11571001

  8. Shape Morphing of an Elastic Cylinder via Time-Varying Internal Viscous Flows

    NASA Astrophysics Data System (ADS)

    Elbaz, Shai; Gat, Amir

    2013-11-01

    Viscous flows in contact with an elastic body apply both pressure and shear stress on the solid-liquid interface and thus create internal stress- and deformation-fields within the solid structure. We study the interaction between elastic slender axi-symmetric structures and internal time-varying viscous flows as a tool to create controlled shape-morphing of such elastic cylindrical structures. We neglect inertia in the liquid and solid and focus on two cases. Case 1 is viscous flow through a hollow elastic cylinder and case 2 is axial flow in the shallow gap created by two concentric cylinders, where the internal cylinder is rigid and the external elastic. For case 1, we obtain a linear diffusion equation and for case 2 we obtain a non-linear diffusion equation governing the deformation. Solutions for both cases allowing control of the time varying deformation field by way of controlling the liquid pressure at the inlet and outlet are presented. This research is of interest to applications such as micro-swimmers and soft-robotics. This research was supported by the ISRAEL SCIENCE FOUNDATION (Grant No. 818/13).

  9. Time-instant sampling based encoding of time-varying acoustic spectrum

    NASA Astrophysics Data System (ADS)

    Sharma, Neeraj Kumar

    2015-12-01

    The inner ear has been shown to characterize an acoustic stimuli by transducing fluid motion in the inner ear to mechanical bending of stereocilia on the inner hair cells (IHCs). The excitation motion/energy transferred to an IHC is dependent on the frequency spectrum of the acoustic stimuli, and the spatial location of the IHC along the length of the basilar membrane (BM). Subsequently, the afferent auditory nerve fiber (ANF) bundle samples the encoded waveform in the IHCs by synapsing with them. In this work we focus on sampling of information by afferent ANFs from the IHCs, and show computationally that sampling at specific time instants is sufficient for decoding of time-varying acoustic spectrum embedded in the acoustic stimuli. The approach is based on sampling the signal at its zero-crossings and higher-order derivative zero-crossings. We show results of the approach on time-varying acoustic spectrum estimation from cricket call signal recording. The framework gives a time-domain and non-spatial processing perspective to auditory signal processing. The approach works on the full band signal, and is devoid of modeling any bandpass filtering mimicking the BM action. Instead, we motivate the approach from the perspective of event-triggered sampling by afferent ANFs on the stimuli encoded in the IHCs. Though the approach gives acoustic spectrum estimation but it is shallow on its complete understanding for plausible bio-mechanical replication with current mammalian auditory mechanics insights.

  10. Optical measurement of sound using time-varying laser speckle patterns

    NASA Astrophysics Data System (ADS)

    Leung, Terence S.; Jiang, Shihong; Hebden, Jeremy

    2011-02-01

    In this work, we introduce an optical technique to measure sound. The technique involves pointing a coherent pulsed laser beam on the surface of the measurement site and capturing the time-varying speckle patterns using a CCD camera. Sound manifests itself as vibrations on the surface which induce a periodic translation of the speckle pattern over time. Using a parallel speckle detection scheme, the dynamics of the time-varying speckle patterns can be captured and processed to produce spectral information of the sound. One potential clinical application is to measure pathological sounds from the brain as a screening test. We performed experiments to demonstrate the principle of the detection scheme using head phantoms. The results show that the detection scheme can measure the spectra of single frequency sounds between 100 and 2000 Hz. The detection scheme worked equally well in both a flat geometry and an anatomical head geometry. However, the current detection scheme is too slow for use in living biological tissues which has a decorrelation time of a few milliseconds. Further improvements have been suggested.

  11. Trends, time-varying and nonlinear time series models for NGRIP and VOSTOK paleoclimate data

    NASA Astrophysics Data System (ADS)

    Matyasovszky, István

    2010-08-01

    In order to gain further insights into stochastic behaviour of paleoclimate data, including timescales at and below Milankovitch forcing, three specific questions are discussed using δ 18O NGRIP and Vostok Deuterium content data. A comparison of ordinary and time-varying coefficients autoregressive (AR) models shows that both data sets are distinguishable from data generated by suitable low-order AR processes in contrast to earlier conclusions. A harmonic regression analysis clearly distinguishing between discrete and continuous spectra detects cycles corresponding to variations of eccentricity, obliquity and precession. Contribution of eccentricity to the total variance in the last 422,766-year Vostok data is close to, while the variance reduction delivered jointly by obliquity and precession is substantially smaller than a previous recent finding. A harmonic regression analysis with time-varying frequencies and amplitudes is also performed. This approach delivers a gain over the constant frequency model at any reasonable significance level. It is demonstrated that variations of frequencies are at least partly due to real variations and not merely to timescale uncertainties. In order to consider nonlinearity in paleoclimate data, threshold autoregressive (TAR) models are applied to time series examined. A bivariate TAR model describing simultaneous NGRIP and Vostok data exhibits three fix points and one limit cycle related to a part of Dansgaard-Oeschger events. The model selected suggests that Greenland has a primary role in the Greenland-Antarctica climate variation relationship.

  12. PIV measurements of flow in a centrifugal blood pump: time-varying flow.

    PubMed

    Day, Steven W; McDaniel, James C

    2005-04-01

    Measurements of the time-varying flow in a centrifugal blood pump operating as a left ventricular assist device (LVAD) are presented. This includes changes in both the pump flow rate as a function of the left ventricle contraction and the interaction of the rotating impeller and fixed exit volute. When operating with a pulsing ventricle, the flow rate through the LVAD varies from 0-11 L/min during each cycle of the heartbeat. Phase-averaged measurements of mean velocity and some turbulence statistics within several regions of the pump, including the inlet, blade passage, exit volute, and diffuser, are reported at 20 phases of the cardiac cycle. The transient flow fields are compared to the constant flow rate condition that was reported previously in order to investigate the transient effects within the pump. It is shown that the quasi-steady assumption is a fair treatment of the time varying flow field in all regions of this representative pump, which greatly simplifies the comprehension and modeling of this flow field. The measurements are further interpreted to identify the effects that the transient nature of the flow field will have on blood damage. Although regions of recirculation and stagnant flow exist at some phases of the cardiac cycle, there is no location where flow is stagnant during the entire heartbeat. PMID:15971703

  13. Time-varying land subsidence detected by radar altimetry: California, Taiwan and north China

    PubMed Central

    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 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. PMID:27324935

  14. From calls to communities: a model for time-varying social networks

    NASA Astrophysics Data System (ADS)

    Laurent, Guillaume; Saramäki, Jari; Karsai, Márton

    2015-11-01

    Social interactions vary in time and appear to be driven by intrinsic mechanisms that shape the emergent structure of social networks. 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 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 small-world connectedness in social networks. 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, including the role of weak ties.

  15. Time-varying land subsidence detected by radar altimetry: California, Taiwan and north China.

    PubMed

    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 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. PMID:27324935

  16. Time-varying effects of prognostic factors associated with disease-free survival in breast cancer.

    PubMed

    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; Pierce, John P

    2009-06-15

    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

  17. Time-Varying Effects of Prognostic Factors Associated With Disease-Free Survival in Breast Cancer

    PubMed Central

    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

  18. Time-varying singular value decomposition for periodic transient identification in bearing fault diagnosis

    NASA Astrophysics Data System (ADS)

    Zhang, Shangbin; Lu, Siliang; He, Qingbo; Kong, Fanrang

    2016-09-01

    For rotating machines, the defective faults of bearings generally are represented as periodic transient impulses in acquired signals. The extraction of transient features from signals has been a key issue for fault diagnosis. However, the background noise reduces identification performance of periodic faults in practice. This paper proposes a time-varying singular value decomposition (TSVD) method to enhance the identification of periodic faults. The proposed method is inspired by the sliding window method. By applying singular value decomposition (SVD) to the signal under a sliding window, we can obtain a time-varying singular value matrix (TSVM). Each column in the TSVM is occupied by the singular values of the corresponding sliding window, and each row represents the intrinsic structure of the raw signal, namely time-singular-value-sequence (TSVS). Theoretical and experimental analyses show that the frequency of TSVS is exactly twice that of the corresponding intrinsic structure. Moreover, the signal-to-noise ratio (SNR) of TSVS is improved significantly in comparison with the raw signal. The proposed method takes advantages of the TSVS in noise suppression and feature extraction to enhance fault frequency for diagnosis. The effectiveness of the TSVD is verified by means of simulation studies and applications to diagnosis of bearing faults. Results indicate that the proposed method is superior to traditional methods for bearing fault diagnosis.

  19. Time-varying stiffness of human elbow joint during cyclic voluntary movement.

    PubMed

    Bennett, D J; Hollerbach, J M; Xu, Y; Hunter, I W

    1992-01-01

    The objective of this study was to determine the extent to which subjects modulate their elbow joint mechanical properties during ongoing arm movement. Small pseudo-random force disturbances were applied to the wrist with an airjet actuator while subjects executed large (1 rad) elbow joint movements. Using a lumped parameter model of the muscle, tendon and proprioceptive feedback dynamics, a time-varying system identification technique was developed to analyze the phasic changes in the elbow joint's mechanical response. The mechanical properties were found to be time-varying, and well approximated by a quasi-linear second-order model. The stiffness of the arm was found to drop during movement. The arm was always underdamped, with the damping ratio changing during movement. Inertia estimates were constant and consistent with previous measurements. Overall, the moving arm was found to be very compliant, with a peak stiffness value less than the lowest value measured during posture, and a natural frequency of less than 3 Hz. Changing the speed of movement, or the load from gravity, changed the stiffness measured, but not in strict proportion to the change in net muscle torque. PMID:1577114

  20. Atrial Fibrillation detection using time-varying coherence function and Shannon Entropy.

    PubMed

    Lee, J; McManus, D; Chon, K

    2011-01-01

    We introduce a novel method for automatic detection of Atrial Fibrillation (AF) using time-varying coherence functions (TVCF) and Shannon Entropy (SE). The TVCF is estimated by the multiplication of two time-varying transfer functions (TVTFs). Two TVTFs are obtained using two adjacent data segments with one data segment as the input signal and the other data segment as the output to produce the first TVTF; the second TVTF is produced by reversing the input and output signals. The detection algorithm was tested on RR interval time series derived from two databases: the MIT-BIH Atrial Fibrillation (AF) and the MIT-BIH normal sinus rhythm (NSR). The MIT-BIH database contains a variety of short and long AF beats from 25 subjects and the MIT-BIH NSR database consists of only normal sinus rhythms from 18 subjects. Using the receiver operating characteristic curves from the combination of TVCF and SE, we obtained the accuracy of 97.49%, sensitivity of 97.41% and specificity of 97.54% for the MIT-BIH AF database. Furthermore, the specificity of the MIT-BIH NSR database was 100%. PMID:22255383

  1. Inferring the mesoscale structure of layered, edge-valued, and time-varying networks.

    PubMed

    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. PMID:26565289

  2. Time-varying land subsidence detected by radar altimetry: California, Taiwan and north China

    NASA Astrophysics Data System (ADS)

    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.

  3. Time-varying land subsidence detected by radar altimetry: California, Taiwan and north China

    USGS Publications Warehouse

    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.

  4. LRS Bianchi Type-II Inflationary Universe with Massless Scalar Field and Time Varying Λ

    NASA Astrophysics Data System (ADS)

    Raj, Bali; Swati

    2012-08-01

    The locally rotationally symmetric (LRS) Bianchi type-II inflationary cosmological model is investigated for massless scalar field with flat potential and time varying Λ. To obtain the deterministic solution, it is assumed that scale factor is a(t)~eHt as we considered previously for Bianchi type-I spacetime and Λ~a-2 as considered by Chen and Wu, where H is the Hubble constant and effective potential V(phi)=const; phi Higg's field. It is shown that such a time varying Λ leads to no conflict with existing observations. However, it does change the predictions of standard cosmology in the matter-dominated phase and alleviates some problems in reconciling observations with the inflationary scenario. The model represents anisotropic spacetime in general. However, the model isotropizes for large values of t and β = 3H2, where β is constant. The physical and geometrical aspects of the model in the context of an inflationary scenario is also discussed.

  5. Tracking of time-varying genomic regulatory networks with a LASSO-Kalman smoother

    PubMed Central

    2014-01-01

    It is widely accepted that cellular requirements and environmental conditions dictate the architecture of genetic regulatory networks. Nonetheless, the status quo in regulatory network modeling and analysis assumes an invariant network topology over time. In this paper, we refocus on a dynamic perspective of genetic networks, one that can uncover substantial topological changes in network structure during biological processes such as developmental growth. We propose a novel outlook on the inference of time-varying genetic networks, from a limited number of noisy observations, by formulating the network estimation as a target tracking problem. We overcome the limited number of observations (small n large p problem) by performing tracking in a compressed domain. Assuming linear dynamics, we derive the LASSO-Kalman smoother, which recursively computes the minimum mean-square sparse estimate of the network connectivity at each time point. The LASSO operator, motivated by the sparsity of the genetic regulatory networks, allows simultaneous signal recovery and compression, thereby reducing the amount of required observations. The smoothing improves the estimation by incorporating all observations. We track the time-varying networks during the life cycle of the Drosophila melanogaster. The recovered networks show that few genes are permanent, whereas most are transient, acting only during specific developmental phases of the organism. PMID:24517200

  6. Fast Time-Varying Volume Rendering Using Time-Space Partition (TSP) Tree

    NASA Technical Reports Server (NTRS)

    Shen, Han-Wei; Chiang, Ling-Jen; Ma, Kwan-Liu

    1999-01-01

    We present a new, algorithm for rapid rendering of time-varying volumes. A new hierarchical data structure that is capable of capturing both the temporal and the spatial coherence is proposed. Conventional hierarchical data structures such as octrees are effective in characterizing the homogeneity of the field values existing in the spatial domain. However, when treating time merely as another dimension for a time-varying field, difficulties frequently arise due to the discrepancy between the field's spatial and temporal resolutions. In addition, treating spatial and temporal dimensions equally often prevents the possibility of detecting the coherence that is unique in the temporal domain. Using the proposed data structure, our algorithm can meet the following goals. First, both spatial and temporal coherence are identified and exploited for accelerating the rendering process. Second, our algorithm allows the user to supply the desired error tolerances at run time for the purpose of image-quality/rendering-speed trade-off. Third, the amount of data that are required to be loaded into main memory is reduced, and thus the I/O overhead is minimized. This low I/O overhead makes our algorithm suitable for out-of-core applications.

  7. Inferring the mesoscale structure of layered, edge-valued, and time-varying networks

    NASA Astrophysics Data System (ADS)

    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.

  8. Physiological and Molecular Genetic Effects of Time-Varying Electromagnetic Fields on Human Neuronal Cells

    NASA Technical Reports Server (NTRS)

    Goodwin, Thomas J.

    2003-01-01

    The present investigation details the development of model systems for growing two- and three-dimensional human neural progenitor cells within a culture medium facilitated by a time-varying electromagnetic field (TVEMF). The cells and culture medium are contained within a two- or three-dimensional culture vessel, and the electromagnetic field is emitted from an electrode or coil. These studies further provide methods to promote neural tissue regeneration by means of culturing the neural cells in either configuration. Grown in two dimensions, neuronal cells extended longitudinally, forming tissue strands extending axially along and within electrodes comprising electrically conductive channels or guides through which a time-varying electrical current was conducted. In the three-dimensional aspect, exposure to TVEMF resulted in the development of three-dimensional aggregates, which emulated organized neural tissues. In both experimental configurations, the proliferation rate of the TVEMF cells was 2.5 to 4.0 times the rate of the non-waveform cells. Each of the experimental embodiments resulted in similar molecular genetic changes regarding the growth potential of the tissues as measured by gene chip analyses, which measured more than 10,000 human genes simultaneously.

  9. Identification of time-varying structural dynamic systems - An artificial intelligence approach

    NASA Technical Reports Server (NTRS)

    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.

  10. Time-Varying Dynamical System Networks in the Light of Hybrid Symmetry

    NASA Astrophysics Data System (ADS)

    Hage-Packhäuser, S.; Dellnitz, M.

    2012-04-01

    Numerous dynamical systems describing real world phenomena exhibit a characteristic fine structure which stems from the interaction of many dynamic instances. Furthermore, since reality crucially depends on time, such dynamical system networks - more concisely termed coupled cell systems - are generally subject to temporal changes. Particularly in applications involving nature and technology, this temporal evolution of the system itself often occurs as a consequence of instantaneously time-varying network structures. In turn, this network switching may give rise to very regularly shaped dynamics. In this work, time-varying networks of dynamical systems are discussed in terms of hybrid dynamical systems with a special consideration of symmetries which are naturally due to the network structures involved. By means of the recent notion of hybrid symmetries, a hybrid symmetry framework is presented and symmetry-induced switching strategies are investigated. In the face of applications, this type of self-organized switching can be interpreted as cyclically moving network perturbations and it is shown to be relevant in connection with stabilization issues of switched systems.

  11. Tracking of time-varying genomic regulatory networks with a LASSO-Kalman smoother.

    PubMed

    Khan, Jehandad; Bouaynaya, Nidhal; Fathallah-Shaykh, Hassan M

    2014-01-01

    : It is widely accepted that cellular requirements and environmental conditions dictate the architecture of genetic regulatory networks. Nonetheless, the status quo in regulatory network modeling and analysis assumes an invariant network topology over time. In this paper, we refocus on a dynamic perspective of genetic networks, one that can uncover substantial topological changes in network structure during biological processes such as developmental growth. We propose a novel outlook on the inference of time-varying genetic networks, from a limited number of noisy observations, by formulating the network estimation as a target tracking problem. We overcome the limited number of observations (small n large p problem) by performing tracking in a compressed domain. Assuming linear dynamics, we derive the LASSO-Kalman smoother, which recursively computes the minimum mean-square sparse estimate of the network connectivity at each time point. The LASSO operator, motivated by the sparsity of the genetic regulatory networks, allows simultaneous signal recovery and compression, thereby reducing the amount of required observations. The smoothing improves the estimation by incorporating all observations. We track the time-varying networks during the life cycle of the Drosophila melanogaster. The recovered networks show that few genes are permanent, whereas most are transient, acting only during specific developmental phases of the organism. PMID:24517200

  12. Time-Varying Speckle Phenomena in Astronomical Imaging and in Laser Scattering.

    NASA Astrophysics Data System (ADS)

    O'Donnell, Kevin Arthur

    The properties of time-varying speckle phenomena in stellar imaging through turbulence and in laser scattering from moving diffusers are examined in both theory and experiment. It is found that the space-time correlation properties of stellar speckle images are important in stellar speckle interferometry, a method of obtaining diffraction limited information through the atmosphere. A theoretical study of exposure time effects in speckle interferometry reveals that the optimum exposure time is dependent on the space -time properties of the stellar image. A method of space -time speckle interferometry that may overcome exposure time effects of standard methods is also proposed. An experimental investigation of the space-time intensity correlation functions of the speckle image at two observing sites reveals rather different correlation structure. At Mees Observatory in Bristol Springs, New York, the image correlations indicate that translation of pupil turbulence was significant, while measurements at Mauna Kea Observatory in Hawaii suggest that boiling of turbulence rather than translation was the predominant effect. An analogous effect in laser scattering from moving diffusers is studied in some detail. In the experiment considered a translating diffuser is placed in the pupil of a lens and the time-varying speckle in the focal plane is studied. In this case the moving diffuser in front of the lens is analogous to wind-driven turbulence translating across the telescope objective. The theoretical space -time intensity correlation functions are calculated in the gaussian scattered amplitude limit and are found to be rather similar to those measured at Mees Observatory. Experimental measurements of the time-varying laser speckle are presented and excellent agreement with the theory is obtained. The detection of small amounts of aberrations and measurements of the lens modulation transfer function are possible applications of this phenomenon. A theoretical study of the

  13. Critical capacity, travel time delays and travel time distribution of rapid mass transit systems

    NASA Astrophysics Data System (ADS)

    Legara, Erika Fille; Monterola, Christopher; Lee, Kee Khoon; Hung, Gih Guang

    2014-07-01

    We set up a mechanistic agent-based model of a rapid mass transit system. Using empirical data from Singapore’s unidentifiable smart fare card, we validate our model by reconstructing actual travel demand and duration of travel statistics. We subsequently use this model to investigate two phenomena that are known to significantly affect the dynamics within the RTS: (1) overloading in trains and (2) overcrowding in the RTS platform. We demonstrate that by varying the loading capacity of trains, a tipping point emerges at which an exponential increase in the duration of travel time delays is observed. We also probe the impact on the rail system dynamics of three types of passenger growth distribution across stations: (i) Dirac delta, (ii) uniform and (iii) geometric, which is reminiscent of the effect of land use on transport. Under the assumption of a fixed loading capacity, we demonstrate the dependence of a given origin-destination (OD) pair on the flow volume of commuters in station platforms.

  14. Quantifying the line-of-sight mass distributions for time-delay lenses with stellar masses

    NASA Astrophysics Data System (ADS)

    Rusu, Cristian; Fassnacht, Chris; Treu, Tommaso; Suyu, Sherry; Auger, Matt; Koopmans, Leon; Marshall, Phil; Wong, Kenneth; Collett, Thomas; Agnello, Adriano; Blandford, Roger; Courbin, Frederic; Hilbert, Stefan; Meylan, Georges; Sluse, Dominique

    2014-12-01

    Measuring cosmological parameters with a realistic account of systematic uncertainties is currently one of the principal challenges of physical cosmology. Building on our recent successes with two gravitationally lensed systems, we have started a program to achieve accurate cosmographic measurements from five gravitationally lensed quasars. We aim at measuring H_0 with an accuracy better than 4%, comparable to but independent from measurements by current BAO, SN or Cepheid programs. The largest current contributor to the error budget in our sample is uncertainty about the line-of-sight mass distribution and environment of the lens systems. In this proposal, we request wide-field u-band imaging of the only lens in our sample without already available Spitzer/IRCA observations, B1608+656. The proposed observations are critical for reducing these uncertainties by providing accurate redshifts and in particular stellar masses for galaxies in the light cones of the target lens system. This will establish lensing as a powerful and independent tool for determining cosmography, in preparation for the hundreds of time-delay lenses that will be discovered by future surveys.

  15. Quantification of sound instability in embouchure tremor based on the time-varying fundamental frequency.

    PubMed

    Lee, André; Voget, Jakob; Furuya, Shinichi; Morise, Masanori; Altenmüller, Eckart

    2016-05-01

    Task-specific tremor in musicians is an involuntary oscillating muscular activity mostly of the hand or the embouchure, which predominantly occurs while playing the instrument. In contrast to arm or hand tremors, which have been examined and objectified based on movement kinematics and muscular activity, embouchure tremor has not yet been investigated. To quantify and describe embouchure tremor we analysed sound production and investigated the fluctuation of the time-varying fundamental frequency of sustained notes. A comparison between patients with embouchure tremor and healthy controls showed a significantly higher fluctuation of the fundamental frequency for the patients in the high pitch with a tremor frequency range between 3 and 8 Hz. The present findings firstly provide further information about a scarcely described movement disorder and secondly further evaluate a new quantification method for embouchure tremor, which has recently been established for embouchure dystonia. PMID:27023201

  16. Transport of time-varying plasma currents by whistler wave packets

    NASA Technical Reports Server (NTRS)

    Stenzel, R. L.; Urrutia, J. M.; Rousculp, C.

    1992-01-01

    The relationship between pulsed currents and electromagnetic waves is examined in a regime characterized by electron MHD. Pulsed currents are generated by (1) collection/emission of charged particles by/from biased electrodes and (2) induction of currents by time-varying and moving magnetic fields. Pulsed currents are observed to propagate at the speed of whistler wave packets. Their field structure forms ropelike configurations which are electromagnetically force-free. Moving sources induce 'eddy' currents which excite waves and form Cerenkov-like whistler 'wings'. The radiation patterns of moving magnetic antennas and electrodynamic tethers are investigated. Nonlinear effects of large-amplitude, antenna-launched whistler pulses are observed. These involve a new modulational instability in which a channel of high conductivity which permits the wave/currents to penetrate deeply into a collisional plasma is formed.

  17. An experimentally validated parametrically excited vibration energy harvester with time-varying stiffness

    NASA Astrophysics Data System (ADS)

    Zaghari, Bahareh; Rustighi, Emiliano; Ghandchi Tehrani, Maryam

    2015-03-01

    Vibration energy harvesting is the transformation of vibration energy to electrical energy. The motivation of this work is to use vibration energy harvesting to power wireless sensors that could be used in inaccessible or hostile environments to transmit information for condition health monitoring. Although considerable work has been done in the area of energy harvesting, there is still a demand for making a robust and small vibration energy harvesters from random excitations in a real environment that can produce a reliable amount of energy. Parametrically excited harvesters can have time-varying stiffness. Parametric amplification is used to tune vibration energy harvesters to maximize energy gains at system superharmonics, often at twice the first natural frequency. In this paper the parametrically excited harvester with cubic and cubic parametric nonlinearity is introduced as a novel work. The advantages of having cubic and cubic nonlinearity are explained theoretically and experimentally.

  18. On-Line Modal State Monitoring of Slowly Time-Varying Structures

    NASA Technical Reports Server (NTRS)

    Johnson, Erik A.; Bergman, Lawrence A.; Voulgaris, Petros G.

    1997-01-01

    Monitoring the dynamic response of structures is often performed for a variety of reasons. These reasons include condition-based maintenance, health monitoring, performance improvements, and control. In many cases the data analysis that is performed is part of a repetitive decision-making process, and in these cases the development of effective on-line monitoring schemes help to speed the decision-making process and reduce the risk of erroneous decisions. This report investigates the use of spatial modal filters for tracking the dynamics of slowly time-varying linear structures. The report includes an overview of modal filter theory followed by an overview of several structural system identification methods. Included in this discussion and comparison are H-infinity, eigensystem realization, and several time-domain least squares approaches. Finally, a two-stage adaptive on-line monitoring scheme is developed and evaluated.

  19. Induction of Oxidation in Living Cells by Time-Varying Electromagnetic Fields

    NASA Technical Reports Server (NTRS)

    Stolc, Viktor

    2015-01-01

    We are studying how biological systems can harness quantum effects of time varying electromagnetic (EM) waves as the time-setting basis for universal biochemical organization via the redox cycle. The effects of extremely weak EM field on the biochemical redox cycle can be monitored through real-time detection of oxidation-induced light emissions of reporter molecules in living cells. It has been shown that EM fields can also induce changes in fluid transport rates through capillaries (approximately 300 microns inner diameter) by generating annular proton gradients. This effect may be relevant to understanding cardiovascular dis-function in spaceflight, beyond the ionosphere. Importantly, we show that these EM effects can be attenuated using an active EM field cancellation device. Central for NASA's Human Research Program is the fact that the absence of ambient EM field in spaceflight can also have a detrimental influence, namely via increased oxidative damage, on DNA replication, which controls heredity.

  20. Electromagnetic wave propagation in spatially homogeneous yet smoothly time-varying dielectric media

    NASA Astrophysics Data System (ADS)

    Hayrapetyan, Armen G.; Götte, Jörg B.; Grigoryan, Karen K.; Fritzsche, Stephan; Petrosyan, Rubik G.

    2016-07-01

    We explore the propagation and transformation of electromagnetic waves through spatially homogeneous yet smoothly time-dependent media within the framework of classical electrodynamics. By modelling the smooth transition, occurring during a finite period τ, as a phenomenologically realistic and sigmoidal change of the dielectric permittivity, an analytically exact solution to Maxwell's equations is derived for the electric displacement in terms of hypergeometric functions. Using this solution, we show the possibility of amplification and attenuation of waves and associate this with the decrease and increase of the time-dependent permittivity. We demonstrate, moreover, that such an energy exchange between waves and non-stationary media leads to the transformation (or conversion) of frequencies. Our results may pave the way towards controllable light-matter interaction in time-varying structures.

  1. Measurement of speech levels in the presence of time varying background noise

    NASA Technical Reports Server (NTRS)

    Pearsons, K. S.; Horonjeff, R.

    1982-01-01

    Short-term speech level measurements which could be used to note changes in vocal effort in a time varying noise environment were studied. Knowing the changes in speech level would in turn allow prediction of intelligibility in the presence of aircraft flyover noise. Tests indicated that it is possible to use two second samples of speech to estimate long term root mean square speech levels. Other tests were also performed in which people read out loud during aircraft flyover noise. Results of these tests indicate that people do indeed raise their voice during flyovers at a rate of about 3-1/2 dB for each 10 dB increase in background level. This finding is in agreement with other tests of speech levels in the presence of steady state background noise.

  2. Holographic Dark Energy Model with Time Varying G as Well as c 2 Parameter

    NASA Astrophysics Data System (ADS)

    Borah, Bharat; Ansari, M.

    2014-04-01

    In this paper, we study a holographic dark energy model with time varying gravitational constant G as well as holographic parameter c 2 in flat FRW space-time geometry. We obtain the evolution of equation of state parameter and the exact differential equation, which determine the evolution of the dark energy density based on varying G and c 2 parameter. Also, we determine the deceleration parameter to explain the expansion of the universe. Further, we study the validity of the generalized second law of thermodynamics in this scenario. Finally, we find out a cosmological implication of our work by evaluating the holographic dark energy equation of state for low red-shifts containing both varying G and c 2 parameter corrections.

  3. Water Quality Management With Time Varying River Flow and Discharger Control

    NASA Astrophysics Data System (ADS)

    Herbay, Jean-Pierre; Smeers, Yves; Tyteca, Daniel

    1983-12-01

    An extension of the classical river quality management problem is presented that allows for time varying operation of the treatment plants. The hydrology of the river is represented by a set of steady state flow regimes; a river water quality model is used for each of these regimes to give a constraint set to be imposed on the discharges in order to achieve the stream standards during that regime. The objective function distinguishes between investment costs, fixed operating costs, and variable operating costs. A treatment system is sought that minimizes the sum of these costs, taking account of the possibility of operating the treatment system at various different levels during the year. The model is quantified and tested on an example.

  4. Query-Driven Visualization of Time-Varying Adaptive Mesh Refinement Data

    SciTech Connect

    Gosink, Luke J.; Anderson, John C.; Bethel, E. Wes; Joy, Kenneth I.

    2008-08-01

    The visualization and analysis of AMR-based simulations is integral to the process of obtaining new insight in scientific research. We present a new method for performing query-driven visualization and analysis on AMR data, with specific emphasis on time-varying AMR data. Our work introduces a new method that directly addresses the dynamic spatial and temporal properties of AMR grids which challenge many existing visualization techniques. Further, we present the first implementation of query-driven visualization on the GPU that uses a GPU-based indexing structure to both answer queries and efficiently utilize GPU memory. We apply our method to two different science domains to demonstrate its broad applicability.

  5. Time-varying functional connectivity for understanding the neural basis of behavioral microsleeps.

    PubMed

    Toppi, J; Astolfi, L; Poudel, G R; Babiloni, F; Macchiusi, L; Mattia, D; Salinari, S; Jones, R D

    2012-01-01

    Episodes of complete failure to respond during attentive tasks--lapses of responsiveness ('lapses')--accompanied by behavioral signs of sleep such as slow-eye-closure are known as behavioral microsleeps (BMs). The occurrence of BMs can have serious/fatal consequences, particularly in the transport sectors, and therefore further investigations on neurophysiological correlates of BMs are highly desirable. In this paper we propose a combination of High Resolution EEG techniques and an advanced method for time-varying functional connectivity estimation for reconstructing the temporal evolution of causal relations between cortical regions of BMs occurring during a visuomotor tracking task. The preliminary results highlight connectivity patterns involving parietal and fronto-parietal areas both preceding and following the onset of a BM. PMID:23366979

  6. Starting vortex behavior in flow through a time-varying rectangular slit

    NASA Astrophysics Data System (ADS)

    Barry, Michael; Krane, Michael; Wei, Timothy

    2006-11-01

    The behavior of the starting vortex issuing from a time-varying rectangular slit with an imposed pressure gradient, representing the flow through the human glottis, is presented. The range of reduced frequency of vibration was 0.01-0.04 and the Reynolds number 8000. DPIV measurements of the velocity field on the plane of symmetry show that the starting vortex formation takes a longer fraction of the vibration period as the reduced frequency increases. The formation time and strength of the starting vortex are estimated from the velocity field measurements. In addition, the volume flow measurements allow the stroke ratio L/D to be estimated. The correlation L/D and pinch-off is also discussed.

  7. Time-varying oscillations in the solar soft X-ray flux as observed from Skylab

    NASA Technical Reports Server (NTRS)

    Teuber, D. L.; Wilson, R. M.; Henze, W., Jr.

    1978-01-01

    Observations obtained by the Skylab/Apollo telescope S-056 X-ray experiment were used to study the time-varying oscillations in the solar soft X-ray flux during a flare. The observations consisted of count rates measured every 2.5 s by sealed, gas-filled counters operating over the 2.5-7.25-A and 6.1-20.0-A wavelength ranges. The power spectra for two other intervals were computed to determine whether the observed oscillations were flare-associated or instrumental in origin. The data indicate that the oscillations in the flare-associated X-ray flux are caused by waves which are generated during the flare and which periodically increase the electron density. No oscillations were observed during quiet periods.

  8. Robust formation tracking control of mobile robots via one-to-one time-varying communication

    NASA Astrophysics Data System (ADS)

    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.

  9. Time-varying Entry Heating Profile Replication with a Rotating Arc Jet Test Article

    NASA Technical Reports Server (NTRS)

    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.

  10. Sliding mode control for multi-agent systems under a time-varying topology

    NASA Astrophysics Data System (ADS)

    Dong, Lijing; Chai, Senchun; Zhang, Baihai; Kiong Nguang, Sing

    2016-07-01

    This paper addresses the tracking problem of a class of multi-agent systems under uncertain communication environments which has been modelled by a finite number of constant Laplacian matrices together with their corresponding scheduling functions. Sliding mode control method is applied to solve this nonlinear tracking problem under a time-varying topology. The controller of each tracking agent has been designed by using only its own and neighbours' information. Sufficient conditions for the existence of a sliding mode control tracking strategy have been provided by the solvability of linear matrix inequalities. At the end of this work, numerical simulations are employed to demonstrate the effectiveness of the proposed sliding mode control tracking strategy.

  11. Detection of time-varying harmonic amplitude alterations due to spectral interpolations between musical instrument tones.

    PubMed

    Horner, Andrew B; Beauchamp, James W; So, Richard H Y

    2009-01-01

    Gradated spectral interpolations between musical instrument tone pairs were used to investigate discrimination as a function of time-averaged spectral difference. All possible nonidentical pairs taken from a collection of eight musical instrument sounds consisting of bassoon, clarinet, flute, horn, oboe, saxophone, trumpet, and violin were tested. For each pair, several tones were generated with different balances between the primary and secondary instruments, where the balance was fixed across the duration of each tone. Among primary instruments it was found that changes to horn and bassoon [corrected] were most easily discriminable, while changes to saxophone and trumpet timbres were least discriminable. Among secondary instruments, the clarinet had the strongest effect on discrimination, whereas the bassoon had the least effect. For primary instruments, strong negative correlations were found between discrimination and their spectral incoherences, suggesting that the presence of dynamic spectral variations tends to increase the difficulty of detecting time-varying alterations such as spectral interpolation. PMID:19173434

  12. Comparison of different Kalman filter approaches in deriving time varying connectivity from EEG data.

    PubMed

    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. PMID:26736727

  13. Research plan for establishing the effects of time varying noise exposures on community annoyance and acceptability

    NASA Technical Reports Server (NTRS)

    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.

  14. Lagrangian Descriptors of Thermalized Transition States on Time-Varying Energy Surfaces

    NASA Astrophysics Data System (ADS)

    Craven, Galen T.; Hernandez, Rigoberto

    2015-10-01

    Thermalized chemical reactions driven under dynamical load are characteristic of activated dynamics for arbitrary nonautonomous systems. Recent generalizations of transition state theory to obtain formally exact rates have required the construction of a time-dependent transition state trajectory. Here, we show that Lagrangian descriptors can be used to obtain this structure directly. By developing a phase space separatrix that is void of recrossings, these constructs allow for the principal criterion in the implementation of modern rate theories to be satisfied. Thus, the reactive flux over a time-varying barrier can be determined without ambiguity in chemical reactions. The generality of the formalism suggests that this approach is applicable to any activated system subjected to arbitrary driving and thermal fluctuations.

  15. Lagrangian Descriptors of Thermalized Transition States on Time-Varying Energy Surfaces.

    PubMed

    Craven, Galen T; Hernandez, Rigoberto

    2015-10-01

    Thermalized chemical reactions driven under dynamical load are characteristic of activated dynamics for arbitrary nonautonomous systems. Recent generalizations of transition state theory to obtain formally exact rates have required the construction of a time-dependent transition state trajectory. Here, we show that Lagrangian descriptors can be used to obtain this structure directly. By developing a phase space separatrix that is void of recrossings, these constructs allow for the principal criterion in the implementation of modern rate theories to be satisfied. Thus, the reactive flux over a time-varying barrier can be determined without ambiguity in chemical reactions. The generality of the formalism suggests that this approach is applicable to any activated system subjected to arbitrary driving and thermal fluctuations. PMID:26551825

  16. Psychophysical Models for Signal Detection with Time Varying Uncertainty. Ph.D. Thesis

    NASA Technical Reports Server (NTRS)

    Gai, E.

    1975-01-01

    Psychophysical models for the behavior of the human operator in detection tasks which include change in detectability, correlation between observations and deferred decisions are developed. Classical Signal Detection Theory (SDT) is discussed and its emphasis on the sensory processes is contrasted to decision strategies. The analysis of decision strategies utilizes detection tasks with time varying signal strength. The classical theory is modified to include such tasks and several optimal decision strategies are explored. Two methods of classifying strategies are suggested. The first method is similar to the analysis of ROC curves, while the second is based on the relation between the criterion level (CL) and the detectability. Experiments to verify the analysis of tasks with changes of signal strength are designed. The results show that subjects are aware of changes in detectability and tend to use strategies that involve changes in the CL's.

  17. Non-Markovian master equation for a damped oscillator with time-varying parameters

    SciTech Connect

    Chang, K. W.; Law, C. K.

    2010-05-15

    We derive an exact non-Markovian master equation that generalizes the previous work [Hu, Paz and Zhang, Phys. Rev. D 45, 2843 (1992)] to damped harmonic oscillators with time-varying parameters. This is achieved by exploiting the linearity of the system and operator solution in Heisenberg picture. Our equation governs the non-Markovian quantum dynamics when the system is modulated by external devices. As an application, we apply our equation to parity kick decoupling problems. The time-dependent dissipative coefficients in the master equation are shown to be modified drastically when the system is driven by {pi} pulses. For coherence protection to be effective, our numerical results indicate that kicking period should be shorter than memory time of the bath. The effects of using soft pulses in an ohmic bath are also discussed.

  18. Ponderomotive force of a uniform electromagnetic wave in a time varying dielectric medium

    SciTech Connect

    Mori, W.B. ); Katsouleas, T. )

    1992-12-14

    A ponderomotive force associated with a [ital uniform] electromagnetic wave propagating in a medium with time varying dielectric properties [e.g., [epsilon]=[epsilon]([ital x][minus][ital v][sub 0][ital t])] is identified. In particular, when a laser ionizes a gas through which it propagates, a force is exerted on the medium at the ionization front that is proportional to ([del][epsilon])[ital E][sup 2] rather than the usual ([epsilon][minus]1)[del][ital E][sup 2]. This force excites a wake in the plasma medium behind the ionization front. The ponderomotive force and wake amplitude are derived and tested with 1D particle-in-cell simulations.

  19. Estimating time-varying conditional correlations between stock and foreign exchange markets

    NASA Astrophysics Data System (ADS)

    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.

  20. Tracking rhythmicity in nonstationary quasi-periodic biomedical signals using adaptive time-varying covariance.

    PubMed

    Li, Dan; Jung, Ranu

    2002-07-01

    A time-varying covariance method for detecting and quantifying the evolution of rhythmicity (frequency) in persistently varying quasi-periodic nonstationary signals is presented. The basic method, evaluated using chirp signals, utilizes a shifting window of fixed length. A substantial reduction in estimation bias and variability are obtained by utilizing an adaptive window whose length is dependent on past frequency estimates. The adaptive window yields estimates that are comparable in accuracy to those obtained using high-resolution time-frequency representation but with lower computation requirements and the potential for on-line application. Finally, an example of the application of the method for analyzing a neural recording is also illustrated. PMID:11931864

  1. Spectral factorization in periodically time-varying systems and application to navigation problems.

    NASA Technical Reports Server (NTRS)

    Nishimura, T.

    1972-01-01

    Spectral factorization has been used previously to derive the steady-state solution of Kalman filtering equations without iteration for constant coefficient systems. The present work extends the spectral factorization algorithm to time-varying systems having periodic coefficient matrices for cases of both discrete and continuous systems. Time-consuming, expensive iterations of sequential covariance equations are not required to reach the final solution since this is an algebraic algorithm employing existing eigenvalue, eigenvector subroutines. The computer program incorporating the algorithm is suitable for sensitivity studies in formulating navigation and guidance strategies of low-thrust interplanetary missions. The determination of an optimum tracking pattern from an earth station is examined as an example.

  2. Accelerating Time-Varying Hardware Volume Rendering Using TSP Trees and Color-Based Error Metrics

    NASA Technical Reports Server (NTRS)

    Ellsworth, David; Chiang, Ling-Jen; Shen, Han-Wei; Kwak, Dochan (Technical Monitor)

    2000-01-01

    This paper describes a new hardware volume rendering algorithm for time-varying data. The algorithm uses the Time-Space Partitioning (TSP) tree data structure to identify regions within the data that have spatial or temporal coherence. By using this coherence, the rendering algorithm can improve performance when the volume data is larger than the texture memory capacity by decreasing the amount of textures required. This coherence can also allow improved speed by appropriately rendering flat-shaded polygons instead of textured polygons, and by not rendering transparent regions. To reduce the polygonization overhead caused by the use of the hierarchical data structure, we introduce an optimization method using polygon templates. The paper also introduces new color-based error metrics, which more accurately identify coherent regions compared to the earlier scalar-based metrics. By showing experimental results from runs using different data sets and error metrics, we demonstrate that the new methods give substantial improvements in volume rendering performance.

  3. Randomized gradient-free method for multiagent optimization over time-varying networks.

    PubMed

    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. PMID:25099738

  4. Phase Response Synchronization in Neuronal Population with Time-Varying Coupling Strength

    PubMed Central

    Jiao, Xianfa; Zhao, Wanyu; Cao, Jinde

    2015-01-01

    We present the dynamic model of global coupled neuronal population subject to external stimulus by the use of phase sensitivity function. We investigate the effect of time-varying coupling strength on the synchronized phase response of neural population subjected to external harmonic stimulus. For a time-periodic coupling strength, we found that the stimulus with increasing intensity or frequency can reinforce the phase response synchronization in neuronal population of the weakly coupled neural oscillators, and the neuronal population with stronger coupling strength has good adaptability to stimulus. When we consider the dynamics of coupling strength, we found that a strong stimulus can quickly cause the synchronization in the neuronal population, the degree of synchronization grows with the increasing stimulus intensity, and the period of synchronized oscillation induced by external stimulation is related to stimulus frequency. PMID:26640514

  5. The dynamic wave expansion neural network model for robot motion planning in time-varying environments.

    PubMed

    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. PMID:15896575

  6. Estimating the Attack Ratio of Dengue Epidemics under Time-varying Force of Infection using Aggregated Notification Data

    PubMed Central

    Coelho, Flavio Codeço; Carvalho, Luiz Max de

    2015-01-01

    Quantifying the attack ratio of disease is key to epidemiological inference and public health planning. For multi-serotype pathogens, however, different levels of serotype-specific immunity make it difficult to assess the population at risk. In this paper we propose a Bayesian method for estimation of the attack ratio of an epidemic and the initial fraction of susceptibles using aggregated incidence data. We derive the probability distribution of the effective reproductive number, Rt, and use MCMC to obtain posterior distributions of the parameters of a single-strain SIR transmission model with time-varying force of infection. Our method is showcased in a data set consisting of 18 years of dengue incidence in the city of Rio de Janeiro, Brazil. We demonstrate that it is possible to learn about the initial fraction of susceptibles and the attack ratio even in the absence of serotype specific data. On the other hand, the information provided by this approach is limited, stressing the need for detailed serological surveys to characterise the distribution of serotype-specific immunity in the population. PMID:26675824

  7. Estimating the Attack Ratio of Dengue Epidemics under Time-varying Force of Infection using Aggregated Notification Data.

    PubMed

    Coelho, Flavio Codeço; de Carvalho, Luiz Max

    2015-01-01

    Quantifying the attack ratio of disease is key to epidemiological inference and public health planning. For multi-serotype pathogens, however, different levels of serotype-specific immunity make it difficult to assess the population at risk. In this paper we propose a Bayesian method for estimation of the attack ratio of an epidemic and the initial fraction of susceptibles using aggregated incidence data. We derive the probability distribution of the effective reproductive number, Rt, and use MCMC to obtain posterior distributions of the parameters of a single-strain SIR transmission model with time-varying force of infection. Our method is showcased in a data set consisting of 18 years of dengue incidence in the city of Rio de Janeiro, Brazil. We demonstrate that it is possible to learn about the initial fraction of susceptibles and the attack ratio even in the absence of serotype specific data. On the other hand, the information provided by this approach is limited, stressing the need for detailed serological surveys to characterise the distribution of serotype-specific immunity in the population. PMID:26675824

  8. Estimating the Attack Ratio of Dengue Epidemics under Time-varying Force of Infection using Aggregated Notification Data

    NASA Astrophysics Data System (ADS)

    Coelho, Flavio Codeço; Carvalho, Luiz Max De

    2015-12-01

    Quantifying the attack ratio of disease is key to epidemiological inference and public health planning. For multi-serotype pathogens, however, different levels of serotype-specific immunity make it difficult to assess the population at risk. In this paper we propose a Bayesian method for estimation of the attack ratio of an epidemic and the initial fraction of susceptibles using aggregated incidence data. We derive the probability distribution of the effective reproductive number, Rt, and use MCMC to obtain posterior distributions of the parameters of a single-strain SIR transmission model with time-varying force of infection. Our method is showcased in a data set consisting of 18 years of dengue incidence in the city of Rio de Janeiro, Brazil. We demonstrate that it is possible to learn about the initial fraction of susceptibles and the attack ratio even in the absence of serotype specific data. On the other hand, the information provided by this approach is limited, stressing the need for detailed serological surveys to characterise the distribution of serotype-specific immunity in the population.

  9. Time-varying wing-twist improves aerodynamic efficiency of forward flight in butterflies.

    PubMed

    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

  10. A Random Time-Varying Particle Swarm Optimization for the Real Time Location Systems

    NASA Astrophysics Data System (ADS)

    Zhu, Hui; Tanabe, Yuji; Baba, Takaaki

    The particle swarm optimizer (PSO) is a stochastic, population-based optimization technique that can be applied to a wide range of applications. This paper presents a random time variable PSO algorithm, called the PSO-RTVIWAC, introducing random time-varying inertia weight and acceleration coefficients to significantly improve the performance of the original algorithms. The PSO-RTVIWAC method originates from the random inertia weight (PSO-RANDIW) and time-varying acceleration coefficients (PSO-TVAC) methods. Through the efficient control of search and convergence to the global optimum solution, the PSO-RTVIWAC method is capable of tracking and optimizing the position evaluate in the highly nonlinear real-time location systems (RTLS). Experimental results are compared with three previous PSO approaches from the literatures, showing that the new optimizer significantly outperforms previous approaches. Simply employing a few particles and iterations, a reasonable good positioning accuracy is obtained with the PSO-RTVIWAC method. This property makes the PSO-RTVIWAC method become more attractive since the computation efficiency is improved considerably, i.e. the computation can be completed in an extremely short time, which is crucial for the RTLS. By implementing a hardware design of PSO-RTVIWAC, the computations can simultaneously be performed using hardware to reduce the processing time. Due to a small number of particles and iterations, the hardware resource is saved and the area cost is reduced in the FPGA implementation. An improvement of positioning accuracy is observed with PSO-RTVIWAC method, compared with Taylor Series Expansion (TSE) and Genetic Algorithm (GA). Our experiments on the PSO-RTVIWAC to track and optimize the position evaluate have demonstrated that it is especially effective in dealing with optimization functions in the nonlinear dynamic environments.

  11. High-dimensional propensity score algorithm in comparative effectiveness research with time-varying interventions.

    PubMed

    Neugebauer, Romain; Schmittdiel, Julie A; Zhu, Zheng; Rassen, Jeremy A; Seeger, John D; Schneeweiss, Sebastian

    2015-02-28

    The high-dimensional propensity score (hdPS) algorithm was proposed for automation of confounding adjustment in problems involving large healthcare databases. It has been evaluated in comparative effectiveness research (CER) with point treatments to handle baseline confounding through matching or covariance adjustment on the hdPS. In observational studies with time-varying interventions, such hdPS approaches are often inadequate to handle time-dependent confounding and selection bias. Inverse probability weighting (IPW) estimation to fit marginal structural models can adequately handle these biases under the fundamental assumption of no unmeasured confounders. Upholding of this assumption relies on the selection of an adequate set of covariates for bias adjustment. We describe the application and performance of the hdPS algorithm to improve covariate selection in CER with time-varying interventions based on IPW estimation and explore stabilization of the resulting estimates using Super Learning. The evaluation is based on both the analysis of electronic health records data in a real-world CER study of adults with type 2 diabetes and a simulation study. This report (i) establishes the feasibility of IPW estimation with the hdPS algorithm based on large electronic health records databases, (ii) demonstrates little impact on inferences when supplementing the set of expert-selected covariates using the hdPS algorithm in a setting with extensive background knowledge, (iii) supports the application of the hdPS algorithm in discovery settings with little background knowledge or limited data availability, and (iv) motivates the application of Super Learning to stabilize effect estimates based on the hdPS algorithm. PMID:25488047

  12. A Hepatitis C Virus Infection Model with Time-Varying Drug Effectiveness: Solution and Analysis

    PubMed Central

    Conway, Jessica M.; Perelson, Alan S.

    2014-01-01

    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. PMID:25101902

  13. Time-varying sensitivity analysis clarifies the effects of watershed model formulation on model behavior

    NASA Astrophysics Data System (ADS)

    Herman, J. D.; Reed, P. M.; Wagener, T.

    2013-03-01

    Lumped rainfall-runoff models are widely used for flow prediction, but a long-recognized need exists for diagnostic tools to determine whether the process-level behavior of a model aligns with the expectations inherent in its formulation. To this end, we develop a comprehensive exploration of dominant parameters in the Hymod, HBV, and Sacramento Soil Moisture Accounting (SAC-SMA) model structures. Model controls are isolated using time-varying Sobol' sensitivity analysis for twelve MOPEX watersheds in the eastern United States over a 10 year period. Sensitivity indices are visualized along gradients of observed precipitation and streamflow to identify key behavioral differences between the three models and to connect these back to the models' underlying assumptions. Results indicate that the models' dominant parameters strongly depend on time-varying hydroclimatic conditions. Parameters associated with surface processes such as evapotranspiration and runoff generally dominate under dry conditions, when high evaporative fluxes are required for accurate simulation. Parameters associated with routing processes typically dominate under high-flow conditions, when performance depends on the timing of flow events. The results highlight significant inter-model differences in performance controls, even in cases where the models share similar process formulations. The dominant parameters identified can be counterintuitive; even these simple models represent complex, nonlinear systems, and the links between formulation and behavior are difficult to discern a priori as complexity increases. Scrutinizing the links between model formulation and behavior becomes an important diagnostic approach, particularly in applications such as predictions under change where dominant model controls will shift under hydrologic extremes.

  14. Using Graphs for Fast Error Term Approximation of Time-varying Datasets

    SciTech Connect

    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.

  15. Analysis of local ionospheric time varying characteristics with singular value decomposition

    NASA Astrophysics Data System (ADS)

    Jakobsen, Jakob; Knudsen, Per; Jensen, Anna B. O.

    2010-07-01

    In this paper, a time series from 1999 to 2007 of absolute total electron content (TEC) values has been computed and analyzed using singular value decomposition (SVD). The data set has been computed using a Kalman Filter and is based on dual frequency GPS data from three reference stations in Denmark located in the midlatitude region. The station separation between the three stations is 132-208 km (the time series of the TEC can be freely downloaded at http://www.heisesgade.dk ). For each year, a SVD has been performed on the TEC time series in order to identify the three time varying (daily, yearly, and 11 yearly) characteristics of the ionosphere. The applied SVD analysis provides a new method for separating the daily from the yearly components. The first singular value is very dominant (approximately six times larger than the second singular value), and this singular value corresponds clearly to the variation of the daily cycle over the year. The second singular value corresponds to variations of the width of the daily peak over the year, and the third singular value shows a clear yearly variation of the daily signal with peaks around the equinoxes. The singular values for each year show a very strong correlation with the sunspot number for all the singular values. The correlation coefficients for the first 5 sets of singular values are all above 0.96. Based on the SVD analysis yearly models of the TEC in the ionosphere can be recomposed and illustrate the three time varying characteristics of the ionosphere very clearly. By prediction of the yearly mean sunspot number, future yearly models can also be predicted. These can serve as a priori information for a real time space weather service providing information of the current status of the ionosphere. They will improve the Kalman filter processing making it more robust, but can also be used as

  16. Tools for Analysis and Visualization of Large Time-Varying CFD Data Sets

    NASA Technical Reports Server (NTRS)

    Wilhelms, Jane; VanGelder, Allen

    1997-01-01

    In the second year, we continued to built upon and improve our scanline-based direct volume renderer that we developed in the first year of this grant. This extremely general rendering approach can handle regular or irregular grids, including overlapping multiple grids, and polygon mesh surfaces. It runs in parallel on multi-processors. It can also be used in conjunction with a k-d tree hierarchy, where approximate models and error terms are stored in the nodes of the tree, and approximate fast renderings can be created. We have extended our software to handle time-varying data where the data changes but the grid does not. We are now working on extending it to handle more general time-varying data. We have also developed a new extension of our direct volume renderer that uses automatic decimation of the 3D grid, as opposed to an explicit hierarchy. We explored this alternative approach as being more appropriate for very large data sets, where the extra expense of a tree may be unacceptable. We also describe a new approach to direct volume rendering using hardware 3D textures and incorporates lighting effects. Volume rendering using hardware 3D textures is extremely fast, and machines capable of using this technique are becoming more moderately priced. While this technique, at present, is limited to use with regular grids, we are pursuing possible algorithms extending the approach to more general grid types. We have also begun to explore a new method for determining the accuracy of approximate models based on the light field method described at ACM SIGGRAPH '96. In our initial implementation, we automatically image the volume from 32 equi-distant positions on the surface of an enclosing tessellated sphere. We then calculate differences between these images under different conditions of volume approximation or decimation. We are studying whether this will give a quantitative measure of the effects of approximation. We have created new tools for exploring the

  17. Investigation of the Acoustics of Plucked String Tones Based on the Analysis of Their Time-Varying Spectra.

    NASA Astrophysics Data System (ADS)

    Chen, Kwok-Ping John

    This research investigates two aspects of the time-varying vibration patterns of plucked string tones of classical guitar, Chinese pipa and Chinese ch'in. First, the assumption that horizontal and vertical frequencies and decay rates may be different is used as a basis for classifying the partial amplitude envelopes into four types. It is found that the partial envelopes of the tones produced by the three instruments, using the finger tip excitation method, on a single undamped string, can be described in terms of these four types. The results show that ch'in tones contain Type III, and IV, guitar tones contain Type I, II and III, and pipa tones contain all four types with a higher percentage of Type III and IV. Second, the theories of "missing modes" (Young, 1800), (Benade, 1976) and delayed generation of these modes (Fletcher, 1984), (Hall, 1987) are re-examined experimentally. The edge of a conventional guitar pick is used to excite a single undamped string on a classical guitar at nodal position N which is L/N from the bridge. As a result, it is a consistent feature that any mode whose index n is a multiple of N is attenuated during the attack phase but subsequently rises with a more gradual attack to reach a significant peak amplitude, except for the first multiple of locations L/3 to L/7. This amplitude envelope pattern, Type V, which is only applicable when the pick-edge excitation method is used, is distinct from the other four types mentioned above.

  18. Using Kalman Filtering to Predict Time-Varying Parameters in a Model Predicting Baroreflex Regulation During Head-Up Tilt.

    PubMed

    Matzuka, Brett; Mehlsen, Jesper; Tran, Hien; Olufsen, Mette Sofie

    2015-08-01

    The cardiovascular control system is continuously engaged to maintain homeostasis, but it is known to fail in a large cohort of patients suffering from orthostatic intolerance. Numerous clinical studies have been put forward to understand how the system fails, yet noninvasive clinical data are sparse, typical studies only include measurements of heart rate and blood pressure, as a result it is difficult to determine what mechanisms that are impaired. It is known, that blood pressure regulation is mediated by changes in heart rate, vascular resistance, cardiac contractility, and a number of other factors. Given that numerous factors contribute to changing these quantities, it is difficult to devise a physiological model describing how they change in time. One way is to build a model that allows these controlled quantities to change and to compare dynamics between subject groups. To do so, it requires more knowledge of how these quantities change for healthy subjects. This study compares two methods predicting time-varying changes in cardiac contractility and vascular resistance during head-up tilt. Similar to the study by Williams et al. [51], the first method uses piecewise linear splines, while the second uses the ensemble transform Kalman filter (ETKF) [1], [11], [12], [33]. In addition, we show that the delayed rejection adaptive Metropolis (DRAM) algorithm can be used for predicting parameter uncertainties within the spline methodology, which is compared with the variability obtained with the ETKF. While the spline method is easier to set up, this study shows that the ETKF has a significantly shorter computational time. Moreover, while uncertainty of predictions can be augmented to spline predictions using DRAM, these are readily available with the ETKF. PMID:25769142

  19. Lp-stability (1 less than or equal to p less than or equal to infinity) of multivariable nonlinear time-varying feedback systems that are open-loop unstable. [noting unstable convolution subsystem forward control and time varying nonlinear feedback

    NASA Technical Reports Server (NTRS)

    Callier, F. M.; Desoer, C. A.

    1973-01-01

    A class of multivariable, nonlinear time-varying feedback systems with an unstable convolution subsystem as feedforward and a time-varying nonlinear gain as feedback was considered. The impulse response of the convolution subsystem is the sum of a finite number of increasing exponentials multiplied by nonnegative powers of the time t, a term that is absolutely integrable and an infinite series of delayed impulses. The main result is a theorem. It essentially states that if the unstable convolution subsystem can be stabilized by a constant feedback gain F and if incremental gain of the difference between the nonlinear gain function and F is sufficiently small, then the nonlinear system is L(p)-stable for any p between one and infinity. Furthermore, the solutions of the nonlinear system depend continuously on the inputs in any L(p)-norm. The fixed point theorem is crucial in deriving the above theorem.

  20. Circuital characterisation of space-charge motion with a time-varying applied bias.

    PubMed

    Kim, Chul; Moon, Eun-Yi; Hwang, Jungho; Hong, Hiki

    2015-01-01

    Understanding the behaviour of space-charge between two electrodes is important for a number of applications. The Shockley-Ramo theorem and equivalent circuit models are useful for this; however, fundamental questions of the microscopic nature of the space-charge remain, including the meaning of capacitance and its evolution into a bulk property. Here we show that the microscopic details of the space-charge in terms of resistance and capacitance evolve in a parallel topology to give the macroscopic behaviour via a charge-based circuit or electric-field-based circuit. We describe two approaches to this problem, both of which are based on energy conservation: the energy-to-current transformation rule, and an energy-equivalence-based definition of capacitance. We identify a significant capacitive current due to the rate of change of the capacitance. Further analysis shows that Shockley-Ramo theorem does not apply with a time-varying applied bias, and an additional electric-field-based current is identified to describe the resulting motion of the space-charge. Our results and approach provide a facile platform for a comprehensive understanding of the behaviour of space-charge between electrodes. PMID:26133999

  1. Circuital characterisation of space-charge motion with a time-varying applied bias

    NASA Astrophysics Data System (ADS)

    Kim, Chul; Moon, Eun-Yi; Hwang, Jungho; Hong, Hiki

    2015-07-01

    Understanding the behaviour of space-charge between two electrodes is important for a number of applications. The Shockley-Ramo theorem and equivalent circuit models are useful for this; however, fundamental questions of the microscopic nature of the space-charge remain, including the meaning of capacitance and its evolution into a bulk property. Here we show that the microscopic details of the space-charge in terms of resistance and capacitance evolve in a parallel topology to give the macroscopic behaviour via a charge-based circuit or electric-field-based circuit. We describe two approaches to this problem, both of which are based on energy conservation: the energy-to-current transformation rule, and an energy-equivalence-based definition of capacitance. We identify a significant capacitive current due to the rate of change of the capacitance. Further analysis shows that Shockley-Ramo theorem does not apply with a time-varying applied bias, and an additional electric-field-based current is identified to describe the resulting motion of the space-charge. Our results and approach provide a facile platform for a comprehensive understanding of the behaviour of space-charge between electrodes.

  2. Reusable Launch Vehicle Attitude Control Using a Time-Varying Sliding Mode Control Technique

    NASA Technical Reports Server (NTRS)

    Shtessel, Yuri B.; Zhu, J. Jim; Daniels, Dan; Jackson, Scott (Technical Monitor)

    2002-01-01

    In this paper we present a time-varying sliding mode control (TVSMC) technique for reusable launch vehicle (RLV) attitude control in ascent and entry flight phases. In ascent flight the guidance commands Euler roll, pitch and yaw angles, and in entry flight it commands the aerodynamic angles of bank, attack and sideslip. The controller employs a body rate inner loop and the attitude outer loop, which are separated in time-scale by the singular perturbation principle. The novelty of the TVSMC is that both the sliding surface and the boundary layer dynamics can be varied in real time using the PD-eigenvalue assignment technique. This salient feature is used to cope with control command saturation and integrator windup in the presence of severe disturbance or control effector failure, which enhances the robustness and fault tolerance of the controller. The TV-SMC ascent and descent designs are currently being tested with high fidelity, 6-DOF dispersion simulations. The test results will be presented in the final version of this paper.

  3. Visual Predictive Check in Models with Time-Varying Input Function.

    PubMed

    Largajolli, Anna; Bertoldo, Alessandra; Campioni, Marco; Cobelli, Claudio

    2015-11-01

    The nonlinear mixed effects models are commonly used modeling techniques in the pharmaceutical research as they enable the characterization of the individual profiles together with the population to which the individuals belong. To ensure a correct use of them is fundamental to provide powerful diagnostic tools that are able to evaluate the predictive performance of the models. The visual predictive check (VPC) is a commonly used tool that helps the user to check by visual inspection if the model is able to reproduce the variability and the main trend of the observed data. However, the simulation from the model is not always trivial, for example, when using models with time-varying input function (IF). In this class of models, there is a potential mismatch between each set of simulated parameters and the associated individual IF which can cause an incorrect profile simulation. We introduce a refinement of the VPC by taking in consideration a correlation term (the Mahalanobis or normalized Euclidean distance) that helps the association of the correct IF with the individual set of simulated parameters. We investigate and compare its performance with the standard VPC in models of the glucose and insulin system applied on real and simulated data and in a simulated pharmacokinetic/pharmacodynamic (PK/PD) example. The newly proposed VPC performance appears to be better with respect to the standard VPC especially for the models with big variability in the IF where the probability of simulating incorrect profiles is higher. PMID:26265094

  4. Regularization of the big bang singularity with a time varying equation of state w > 1

    NASA Astrophysics Data System (ADS)

    Xue, BingKan; Belbruno, Edward

    2014-08-01

    We study the classical dynamics of the universe undergoing a transition from contraction to expansion through a big bang singularity. The dynamics is described by a system of differential equations for a set of physical quantities, such as the scale factor a, the Hubble parameter H, the equation of state parameter w, and the density parameter Ω. The solutions of the dynamical system have a singularity at the big bang. We study if the solutions can be regularized at the singularity in the sense of whether they have unique branch extensions through the singularity. In particular, we consider the model in which the contracting universe is dominated by a scalar field with a time varying equation of state w, which approaches a constant value wc near the singularity. We prove that, for {{w}_{c}}>1, the solutions are regularizable only for a discrete set of wc values that satisfy a coprime number condition. Our result implies that the evolution of a bouncing universe through the big bang singularity does not have a continuous classical limit unless the equation of state is extremely fine-tuned.

  5. Time Varying Compensator Design for Reconfigurable Structures Using Non-Collocated Feedback

    NASA Technical Reports Server (NTRS)

    Scott, Michael A.

    1996-01-01

    Analysis and synthesis tools are developed to improved the dynamic performance of reconfigurable nonminimum phase, nonstrictly positive real-time variant systems. A novel Spline Varying Optimal (SVO) controller is developed for the kinematic nonlinear system. There are several advantages to using the SVO controller, in which the spline function approximates the system model, observer, and controller gain. They are: The spline function approximation is simply connected, thus the SVO controller is more continuous than traditional gain scheduled controllers when implemented on a time varying plant; ft is easier for real-time implementations in storage and computational effort; where system identification is required, the spline function requires fewer experiments, namely four experiments; and initial startup estimator transients are eliminated. The SVO compensator was evaluated on a high fidelity simulation of the Shuttle Remote Manipulator System. The SVO controller demonstrated significant improvement over the present arm performance: (1) Damping level was improved by a factor of 3; and (2) Peak joint torque was reduced by a factor of 2 following Shuttle thruster firings.

  6. Mapping transverse capillary flow speed using time-varying OCT speckle signals (Conference Presentation)

    NASA Astrophysics Data System (ADS)

    Choi, Woo June; Wang, Ruikang K.

    2016-03-01

    We present an optical coherence tomography (OCT) based method for mapping transverse red blood cell (RBC) flow speed at capillary. This OCT velocimetry utilizes a quantitative laser speckle temporal contrast analysis that estimates reliable speckle decorrelation time from the observed speckle contrast, which is related to microcirculatory flow velocity. For capillary speed measurement, we employ a home-built 1.3 µm MHz swept-source OCT (SS-OCT) system that can acquire OCT B-frames at a rate of 1.7 kHz. From the multiple B-frames obtained at the same location, intensity profiles with time-varying OCT speckle contrast are extracted at single capillaries using a capillary binary mask and then the transverse flow speed is calculated by adapting the profiles to the speckle contrast analytic model. Finally, a 3D speed map can be achieved for OCT volume imaging. To validate this method, we perform a systematic study using both phantom and in vivo rodent models. Result shows that our method is effective to measure transverse capillary flow speed.

  7. Framework and algorithms for illustrative visualizations of time-varying flows on unstructured meshes

    DOE PAGESBeta

    Rattner, Alexander S.; Guillen, Donna Post; Joshi, Alark; Garimella, Srinivas

    2016-03-17

    Photo- and physically realistic techniques are often insufficient for visualization of fluid flow simulations, especially for 3D and time-varying studies. Substantial research effort has been dedicated to the development of non-photorealistic and illustration-inspired visualization techniques for compact and intuitive presentation of such complex datasets. However, a great deal of work has been reproduced in this field, as many research groups have developed specialized visualization software. Additionally, interoperability between illustrative visualization software is limited due to diverse processing and rendering architectures employed in different studies. In this investigation, a framework for illustrative visualization is proposed, and implemented in MarmotViz, a ParaViewmore » plug-in, enabling its use on a variety of computing platforms with various data file formats and mesh geometries. Region-of-interest identification and feature-tracking algorithms incorporated into this tool are described. Implementations of multiple illustrative effect algorithms are also presented to demonstrate the use and flexibility of this framework. Here, by providing an integrated framework for illustrative visualization of CFD data, MarmotViz can serve as a valuable asset for the interpretation of simulations of ever-growing scale.« less

  8. AST: Activity-Security-Trust driven modeling of time varying networks

    PubMed Central

    Wang, Jian; Xu, Jiake; Liu, Yanheng; Deng, Weiwen

    2016-01-01

    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. PMID:26888717

  9. AST: Activity-Security-Trust driven modeling of time varying networks

    NASA Astrophysics Data System (ADS)

    Wang, Jian; Xu, Jiake; Liu, Yanheng; Deng, Weiwen

    2016-02-01

    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.

  10. Long-Term Prediction of the Arctic Ionospheric TEC Based on Time-Varying Periodograms

    PubMed Central

    Liu, Jingbin; Chen, Ruizhi; Wang, Zemin; An, Jiachun; Hyyppä, Juha

    2014-01-01

    Knowledge of the polar ionospheric total electron content (TEC) and its future variations is of scientific and engineering relevance. In this study, a new method is developed to predict Arctic mean TEC on the scale of a solar cycle using previous data covering 14 years. The Arctic TEC is derived from global positioning system measurements using the spherical cap harmonic analysis mapping method. The study indicates that the variability of the Arctic TEC results in highly time-varying periodograms, which are utilized for prediction in the proposed method. The TEC time series is divided into two components of periodic oscillations and the average TEC. The newly developed method of TEC prediction is based on an extrapolation method that requires no input of physical observations of the time interval of prediction, and it is performed in both temporally backward and forward directions by summing the extrapolation of the two components. The backward prediction indicates that the Arctic TEC variability includes a 9 years period for the study duration, in addition to the well-established periods. The long-term prediction has an uncertainty of 4.8–5.6 TECU for different period sets. PMID:25369066

  11. Control of the tokamak safety factor profile with time-varying constraints using MPC

    NASA Astrophysics Data System (ADS)

    Maljaars, E.; Felici, F.; de Baar, M. R.; van Dongen, J.; Hogeweij, G. M. D.; Geelen, P. J. M.; Steinbuch, M.

    2015-02-01

    A controller is designed for the tokamak safety factor profile that takes real-time-varying operational and physics limits into account. This so-called model predictive controller (MPC) employs a prediction model in order to compute optimal control inputs that satisfy the given limits. The use of linearized models around a reference trajectory results in a quadratic programming problem that can easily be solved online. The performance of the controller is analysed in a set of ITER L-mode scenarios simulated with the non-linear plasma transport code RAPTOR. It is shown that the controller can reduce the tracking error due to an overestimation or underestimation of the modelled transport, while making a trade-off between residual error and amount of controller action. It is also shown that the controller can account for a sudden decrease in the available actuator power, while providing warnings ahead of time about expected violations of operational and physics limits. This controller can be extended and implemented in existing tokamaks in the near future.

  12. A Search For Time-Varying Diffuse Interstellar Bands in Moderate Resolution Supernova Spectra

    NASA Astrophysics Data System (ADS)

    Milisavljevic, Dan; Margutti, Raffaella; Crabtree, Kyle; Foster, Jonathan; Fesen, Robert; Parrent, Jerod; Drout, Maria; Kamble, Atish; Cenko, Brad; Silverman, Jeffrey; Filippenko, Alex; Mazzali, Paolo; Maeda, Keiichi; Marion, Howie; Soderberg, Alicia

    2014-08-01

    One of the longest standing problems in optical and infrared astronomy is the unknown nature of the diffuse interstellar bands (DIBs). The DIBs represent some 500 narrow absorption lines with central wavelengths that do not correspond with the spectral lines of any known ion or molecule and yet -- embarrassingly -- may be associated with a large reservoir of organic material in our Galaxy. Our group recently discovered unusually strong DIB absorption features in optical spectra of the broad-lined Type Ic supernova SN 2012ap that exhibited changes in equivalent width over short (30 days) timescales. These never-before-seen changes implied that the supernova was interacting with a nearby source of the DIBs and that the source was potentially associated with mass loss of the progenitor star. Moreover, additional examples of weak time-varying DIB features observed in archival low resolution spectra suggest that a wide variety of supernovae may also exhibit these changes but at levels that are more difficult to detect. We propose a ToO Gemini N+S GMOS program that will obtain moderate resolution spectra with high signal to noise ratios of nearby Type Ibc supernovae to robustly measure the ubiquity of this DIB time-variability phenomenon. These observations will reveal unique information about the mass-loss environment of Type Ibc progenitor systems and provide new constraints on the properties of DIB carriers.

  13. Steady and transient flow analysis of a magnetically levitated pediatric VAD: time varying boundary conditions.

    PubMed

    Throckmorton, Amy L; Tahir, Sharjeel A; Lopes, Sydnee P; Rangus, Owen M; Sciolino, Michael G

    2013-10-01

    A magnetically levitated impeller within a pediatric ventricular assist device operates under highly transient flow conditions. In this study, computational analyses were performed to investigate the hydraulic performance and fluid forces on the impeller under the steady and dynamic flow conditions, including: 1) time-varying boundary conditions (TVBC) considering a pulsed pump flow rate and pulsed left ventricular pressure; 2) transient rotational sliding interfaces (TRSI) to capture virtual blade rotation. Under steady flow conditions, the pressure generation for 0.5-6 l/min over 6000-10000 rpm was 20-140 mmHg; experimental validation agreed to within 6-27%. Under transient flow conditions, the outflow pressure of the pump increased with higher inlet pressure during the TVBC simulation. During TVBC, the pressure rise across the pump decreased as a function of higher flow rates and increased as a function of lower flow rates. The radial fluid forces varied directly with the flow rate by demonstrating larger forces at higher flow rates. For TRSI simulations, pressure fluctuations due the blade passage frequency were found to have 12 peaks per revolution, having magnitude ranges of 
0.7 and 1.0 mmHg for 8 000 and 10 000 rpm, respectively. At 8 000 rpm, the fluid forces ranged from 1.15-1.17 N (axial) and 0.02-0.11 N (radial). Transient simulations model implant scenarios more realistically and provide critical information about the fluid conditions in the pump. PMID:24254838

  14. Circuital characterisation of space-charge motion with a time-varying applied bias

    PubMed Central

    Kim, Chul; Moon, Eun-Yi; Hwang, Jungho; Hong, Hiki

    2015-01-01

    Understanding the behaviour of space-charge between two electrodes is important for a number of applications. The Shockley-Ramo theorem and equivalent circuit models are useful for this; however, fundamental questions of the microscopic nature of the space-charge remain, including the meaning of capacitance and its evolution into a bulk property. Here we show that the microscopic details of the space-charge in terms of resistance and capacitance evolve in a parallel topology to give the macroscopic behaviour via a charge-based circuit or electric-field-based circuit. We describe two approaches to this problem, both of which are based on energy conservation: the energy-to-current transformation rule, and an energy-equivalence-based definition of capacitance. We identify a significant capacitive current due to the rate of change of the capacitance. Further analysis shows that Shockley-Ramo theorem does not apply with a time-varying applied bias, and an additional electric-field-based current is identified to describe the resulting motion of the space-charge. Our results and approach provide a facile platform for a comprehensive understanding of the behaviour of space-charge between electrodes. PMID:26133999

  15. Mass Redistribution in the Core and Time-varying Gravity at the Earth's Surface

    NASA Technical Reports Server (NTRS)

    Kuang, Wei-Jia; Chao, Benjamin F.; Fang, Ming

    2003-01-01

    The Earth's liquid outer core is in convection, as suggested by the existence of the geomagnetic field in much of the Earth's history. One consequence of the convection is the redistribution of mass resulting from relative motion among fluid parcels with slightly different densities. This time dependent mass redistribution inside the core produces a small perturbation on the gravity field of the Earth. With our numerical dynamo solutions, we find that the mass redistribution (and the resultant gravity field) symmetric about the equator is much stronger than that anti-symmetric about the equator. In particular, J(sub 2) component is the strongest. In addition, the gravity field variation increases with the Rayleigh number that measures the driving force for the geodynamo in the core. With reasonable scaling from the current dynamo solutions, we could expect that at the surface of the Earth, the J(sub 2) variation from the core is on the order of l0(exp -16)/year relative to the mean (i.e. spherically symmetric) gravity field of the Earth. The possible shielding effect due to core-mantle boundary pressure variation loading is likely much smaller and is therefore negligible. Our results suggest that time-varying gravity field perturbation due to core mass redistribution may be measured with modem space geodetic observations, which will result a new means of detecting dynamical processes in the Earth's deep interior.

  16. Video Extrapolation Method Based on Time-Varying Energy Optimization and CIP.

    PubMed

    Sakaino, Hidetomo

    2016-09-01

    Video extrapolation/prediction methods are often used to synthesize new videos from images. For fluid-like images and dynamic textures as well as moving rigid objects, most state-of-the-art video extrapolation methods use non-physics-based models that learn orthogonal bases from a number of images but at high computation cost. Unfortunately, data truncation can cause image degradation, i.e., blur, artifact, and insufficient motion changes. To extrapolate videos that more strictly follow physical rules, this paper proposes a physics-based method that needs only a few images and is truncation-free. We utilize physics-based equations with image intensity and velocity: optical flow, Navier-Stokes, continuity, and advection equations. These allow us to use partial difference equations to deal with the local image feature changes. Image degradation during extrapolation is minimized by updating model parameters, where a novel time-varying energy balancer model that uses energy based image features, i.e., texture, velocity, and edge. Moreover, the advection equation is discretized by high-order constrained interpolation profile for lower quantization error than can be achieved by the previous finite difference method in long-term videos. Experiments show that the proposed energy based video extrapolation method outperforms the state-of-the-art video extrapolation methods in terms of image quality and computation cost. PMID:27305677

  17. Numerical Studies on Time-Varying Stiffness of Disk-Drum Type Rotor with Bolt Loosening

    NASA Astrophysics Data System (ADS)

    Qin, Zhaoye; Chu, Fulei

    2015-07-01

    Disk-drum type rotors are widely used in industry for their high stiffness and low weight properties. In disk-drum type rotors, the adjacent disks and drums are commonly connected by bolted joints. Those rotating joint interfaces are subjected to numerous combinations of loads during normal operation, where loosening of the connecting bolts might occur. The bolt loosening will change the local stiffness of the rotor, which in turn affect the rotor dynamics and even result in structural failures. In this paper, the local stiffness of a disk- drum rotor with bolt loosening is investigated numerically. A three-dimensional (3D) finite element (FE) model for the bolted disk-drum joint is established in ANSYS, where the bolt loosening is simulated by reducing the preloads of certain bolts, and removing those bolts as the limiting case. Simulations are performed on the FE model to evaluate the joint behaviour under static loads. Periodic variations of the joint deflections with respect to the rotation angle of the shaft are obtained, which implies the appearance of the time-varying local stiffness in the rotor system. The studies in this paper help accurate prediction of the rotor dynamics and early detection of bolt loosening.

  18. Towards damage detection using blind source separation integrated with time-varying auto-regressive modeling

    NASA Astrophysics Data System (ADS)

    Musafere, F.; Sadhu, A.; Liu, K.

    2016-01-01

    In the last few decades, structural health monitoring (SHM) has been an indispensable subject in the field of vibration engineering. With the aid of modern sensing technology, SHM has garnered significant attention towards diagnosis and risk management of large-scale civil structures and mechanical systems. In SHM, system identification is one of major building blocks through which unknown system parameters are extracted from vibration data of the structures. Such system information is then utilized to detect the damage instant, and its severity to rehabilitate and prolong the existing health of the structures. In recent years, blind source separation (BSS) algorithm has become one of the newly emerging advanced signal processing techniques for output-only system identification of civil structures. In this paper, a novel damage detection technique is proposed by integrating BSS with the time-varying auto-regressive modeling to identify the instant and severity of damage. The proposed method is validated using a suite of numerical studies and experimental models followed by a full-scale structure.

  19. Optimal routing of hazardous substances in time-varying, stochastic transportation networks

    SciTech Connect

    Woods, A.L.; Miller-Hooks, E.; Mahmassani, H.S.

    1998-07-01

    This report is concerned with the selection of routes in a network along which to transport hazardous substances, taking into consideration several key factors pertaining to the cost of transport and the risk of population exposure in the event of an accident. Furthermore, the fact that travel time and the risk measures are not constant over time is explicitly recognized in the routing decisions. Existing approaches typically assume static conditions, possibly resulting in inefficient route selection and unnecessary risk exposure. The report described the application of recent advances in network analysis methodologies to the problem of routing hazardous substances. Several specific problem formulations are presented, reflecting different degrees of risk aversion on the part of the decision-maker, as well as different possible operational scenarios. All procedures explicitly consider travel times and travel costs (including risk measures) to be stochastic time-varying quantities. The procedures include both exact algorithms, which may require extensive computational effort in some situations, as well as more efficient heuristics that may not guarantee a Pareto-optimal solution. All procedures are systematically illustrated for an example application using the Texas highway network, for both normal and incident condition scenarios. The application illustrates the trade-offs between the information obtained in the solution and computational efficiency, and highlights the benefits of incorporating these procedures in a decision-support system for hazardous substance shipment routing decisions.

  20. Analytical impact time and angle guidance via time-varying sliding mode technique.

    PubMed

    Zhao, Yao; Sheng, Yongzhi; Liu, Xiangdong

    2016-05-01

    To concretely provide a feasible solution for homing missiles with the precise impact time and angle, this paper develops a novel guidance law, based on the nonlinear engagement dynamics. The guidance law is firstly designed with the prior assumption of a stationary target, followed by the practical extension to a moving target scenario. The time-varying sliding mode (TVSM) technique is applied to fulfill the terminal constraints, in which a specific TVSM surface is constructed with two unknown coefficients. One is tuned to meet the impact time requirement and the other one is targeted with a global sliding mode, so that the impact angle constraint as well as the zero miss distance can be satisfied. Because the proposed law possesses three guidance gain as design parameters, the intercept trajectory can be shaped according to the operational conditions and missile׳s capability. To improve the tolerance of initial heading errors and broaden the application, a new frame of reference is also introduced. Furthermore, the analytical solutions of the flight trajectory, heading angle and acceleration command can be totally expressed for the prediction and offline parameter selection by solving a first-order linear differential equation. Numerical simulation results for various scenarios validate the effectiveness of the proposed guidance law and demonstrate the accuracy of the analytic solutions. PMID:26952314

  1. Generalized Framework and Algorithms for Illustrative Visualization of Time-Varying Data on Unstructured Meshes

    SciTech Connect

    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.

  2. AST: Activity-Security-Trust driven modeling of time varying networks.

    PubMed

    Wang, Jian; Xu, Jiake; Liu, Yanheng; Deng, Weiwen

    2016-01-01

    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. PMID:26888717

  3. SLR Station Recovery, Center of Frame Motion, and Time Varying Gravity

    NASA Technical Reports Server (NTRS)

    Zelensky, Nikita P.; Lemoine, Frank G.; Chinn, Douglas S.; Melachroinos, Stavros; Wiser Beall, Jennifer; Larson, Jordan D.

    2012-01-01

    Weekly station position estimates, beginning with 1993, are derived from the ITRF2008-based SLR processing of up to four satellites: Lageos 1, Lageos2, Starlette, and Stella. Helmert parameters obtained from c omparison of weekly SLR station positions and the a-priori SLRF2008 station complement are evaluated for geocenter motion and scale. Two me thods for modeling time varying gravity are employed in the SLR satel lite POD processing, with GGM03S serving as the static gravity field. Both methods forward model atmosphere gravity derived from 6-hour ECM WF pressure data. The standard approach applies an annual 20x20 field estimated from 4 years of GRACE data, and the IERS2003 recommended linear rates for C20, C30, C40, C21, and S21. The alternate approach us es a new set of low-order/degree 4x4 coefficients estimated weekly fr om SLR & DORIS processing to 10 satellites from 1993-2012. This exper imental tvg4x4 model has been shown to improve the TOPEX, Jason-1, and Jason-2 altimeter satellite orbits,. In this paper we apply the more detailed time-variable gravity modeling to the SLR satellite POD pro cessing and subsequent reference frame analyses. For this study we will evaluate the orbit differences (periodic and secular) for the satel lites concerned, characterize the impact on the station coordinate solutions, and the impact on reference frame parameters (geocenter and s cale).

  4. Indexical properties influence time-varying amplitude and fundamental frequency contributions of vowels to sentence intelligibility

    PubMed Central

    Fogerty, Daniel

    2015-01-01

    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 (F0). 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 F0 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. F0 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 F0 cues are available. These findings suggest that F0 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. PMID:26543276

  5. Coded throughput performance simulations for the time-varying satellite channel. M.S. Thesis

    NASA Technical Reports Server (NTRS)

    Han, LI

    1995-01-01

    The design of a reliable satellite communication link involving the data transfer from a small, low-orbit satellite to a ground station, but through a geostationary satellite, was examined. In such a scenario, the received signal power to noise density ratio increases as the transmitting low-orbit satellite comes into view, and then decreases as it then departs, resulting in a short-duration, time-varying communication link. The optimal values of the small satellite antenna beamwidth, signaling rate, modulation scheme and the theoretical link throughput (in bits per day) have been determined. The goal of this thesis is to choose a practical coding scheme which maximizes the daily link throughput while satisfying a prescribed probability of error requirement. We examine the throughput of both fixed rate and variable rate concatenated forward error correction (FEC) coding schemes for the additive white Gaussian noise (AWGN) channel, and then examine the effect of radio frequency interference (RFI) on the best coding scheme among them. Interleaving is used to mitigate degradation due to RFI. It was found that the variable rate concatenated coding scheme could achieve 74 percent of the theoretical throughput, equivalent to 1.11 Gbits/day based on the cutoff rate R(sub 0). For comparison, 87 percent is achievable for AWGN-only case.

  6. Simulations of Recovery of Time-Varying Gravity from DECIGO Pathfinder

    NASA Technical Reports Server (NTRS)

    Hasegawa, Takashi; Kyoto, U.; Rowlands, Dave; Luthcke, Scott; Sabaka, Terri; Camp, Jordan B.

    2011-01-01

    We simulated time-varying Earth's gravity field recovered from DPF to evaluate an impact of DPF and future satellite gradiometry mission on earth science. From hydrological water movement data and orbit information, gravity gradients to be measured at altitude about 500km were generated. Errors caused by atmospheric and oceanic variations and instrumental noise were added. Monthly gravity fields were estimated solving normal equations between spherical harmonic coefficients and simulated gravity gradient data. Simulation results show that DPF likely provides monthly hydrological water storage change with spatial scale between 400 and 1000km. Sensitivities to large scale estimates depends on long-term stability of gravity gradient measurement, and errors in short scale estimates are caused by instrumental noise and imperfections in atmospheric and ocean model. With acceleration noise level is lower than 5 x 10(exp -14) [m/s2/sqrtHz] at frequency higher than 3mHz, water storage changes at limited small basins will be provided by DPF. To monitor continental scale hydrological water movement, noise level must be lower than 5 x 10(exp -14) [m/s2/sqrtHz] at frequency higher than 1mHz.

  7. Effects of time-varying E×B flow on slab ion-temperature-gradient turbulence

    NASA Astrophysics Data System (ADS)

    Maeyama, S.; Ishizawa, A.; Watanabe, T.-H.; Škorić, M. M.; Nakajima, N.; Tsuji-Iio, S.; Tsutsui, H.

    2010-06-01

    Effects of time-varying sheared E×B flow on turbulence driven by slab ion temperature gradient instabilities are investigated by means of Landau fluid simulation. Here, the E×B flow, which consists of stationary and time-periodic oscillatory parts, is externally imposed to the turbulence. The dependence on the amplitude and frequency of E×B flow is examined in the case that the amplitude of oscillatory part is the same or less than that of stationary part. The ion heat transport caused by turbulence oscillates with the same period as the E×B flow and the time-averaged transport coefficient is larger than the coefficient which is evaluated without the oscillatory part. The time-averaged coefficient is maximized when the amplitude of oscillatory part is equal to that of stationary part. As the frequency of E×B flow increases, the time-averaged coefficient decreases and is close to the coefficient which is evaluated without the oscillatory part. This mechanism is explained by introducing a kind of the logistic equation which describes the time evolution of transport coefficient as a response of turbulence to the amplitude of E×B flow.

  8. A Bayesian proportional hazards regression model with non-ignorably missing time-varying covariates

    PubMed Central

    Bradshaw, Patrick T.; Ibrahim, Joseph G.; Gammon, Marilie D.

    2010-01-01

    Missing covariate data is common in observational studies of time to an event, especially when covariates are repeatedly measured over time. Failure to account for the missing data can lead to bias or loss of efficiency, especially when the data are non-ignorably missing. Previous work has focused on the case of fixed covariates rather than those that are repeatedly measured over the follow-up period, so here we present a selection model that allows for proportional hazards regression with time-varying covariates when some covariates may be non-ignorably missing. We develop a fully Bayesian model and obtain posterior estimates of the parameters via the Gibbs sampler in WinBUGS. We illustrate our model with an analysis of post-diagnosis weight change and survival after breast cancer diagnosis in the Long Island Breast Cancer Study Project (LIBCSP) follow-up study. Our results indicate that post-diagnosis weight gain is associated with lower all-cause and breast cancer specific survival among women diagnosed with new primary breast cancer. Our sensitivity analysis showed only slight differences between models with different assumptions on the missing data mechanism yet the complete case analysis yielded markedly different results. PMID:20960582

  9. Left ventricular function: time-varying elastance and left ventricular aortic coupling.

    PubMed

    Walley, Keith R

    2016-01-01

    Many aspects of left ventricular function are explained by considering ventricular pressure-volume characteristics. Contractility is best measured by the slope, Emax, of the end-systolic pressure-volume relationship. Ventricular systole is usefully characterized by a time-varying elastance (ΔP/ΔV). An extended area, the pressure-volume area, subtended by the ventricular pressure-volume loop (useful mechanical work) and the ESPVR (energy expended without mechanical work), is linearly related to myocardial oxygen consumption per beat. For energetically efficient systolic ejection ventricular elastance should be, and is, matched to aortic elastance. Without matching, the fraction of energy expended without mechanical work increases and energy is lost during ejection across the aortic valve. Ventricular function curves, derived from ventricular pressure-volume characteristics, interact with venous return curves to regulate cardiac output. Thus, consideration of ventricular pressure-volume relationships highlight features that allow the heart to efficiently respond to any demand for cardiac output and oxygen delivery. PMID:27613430

  10. A Class of Prediction-Correction Methods for Time-Varying Convex Optimization

    NASA Astrophysics Data System (ADS)

    Simonetto, Andrea; Mokhtari, Aryan; Koppel, Alec; Leus, Geert; Ribeiro, Alejandro

    2016-09-01

    This paper considers unconstrained convex optimization problems with time-varying objective functions. We propose algorithms with a discrete time-sampling scheme to find and track the solution trajectory based on prediction and correction steps, while sampling the problem data at a constant rate of $1/h$, where $h$ is the length of the sampling interval. The prediction step is derived by analyzing the iso-residual dynamics of the optimality conditions. The correction step adjusts for the distance between the current prediction and the optimizer at each time step, and consists either of one or multiple gradient steps or Newton steps, which respectively correspond to the gradient trajectory tracking (GTT) or Newton trajectory tracking (NTT) algorithms. Under suitable conditions, we establish that the asymptotic error incurred by both proposed methods behaves as $O(h^2)$, and in some cases as $O(h^4)$, which outperforms the state-of-the-art error bound of $O(h)$ for correction-only methods in the gradient-correction step. Moreover, when the characteristics of the objective function variation are not available, we propose approximate gradient and Newton tracking algorithms (AGT and ANT, respectively) that still attain these asymptotical error bounds. Numerical simulations demonstrate the practical utility of the proposed methods and that they improve upon existing techniques by several orders of magnitude.

  11. Time-varying span efficiency through the wingbeat of desert locusts

    PubMed Central

    Henningsson, Per; Bomphrey, Richard J.

    2012-01-01

    The flight performance of animals depends greatly on the efficacy with which they generate aerodynamic forces. Accordingly, maximum range, load-lifting capacity and peak accelerations during manoeuvres are all constrained by the efficiency of momentum transfer to the wake. Here, we use high-speed particle image velocimetry (1 kHz) to record flow velocities in the near wake of desert locusts (Schistocerca gregaria, Forskål). We use the measured flow fields to calculate time-varying span efficiency throughout the wing stroke cycle. The locusts are found to operate at a maximum span efficiency of 79 per cent, typically at a plateau of about 60 per cent for the majority of the downstroke, but at lower values during the upstroke. Moreover, the calculated span efficiencies are highest when the largest lift forces are being generated (90% of the total lift is generated during the plateau of span efficiency) suggesting that the combination of wing kinematics and morphology in locust flight perform most efficiently when doing the most work. PMID:22112649

  12. Central suboptimal H ∞ controller design for linear time-varying systems with unknown parameters

    NASA Astrophysics Data System (ADS)

    Basin, Michael V.; Soto, Pedro; Calderon-Alvarez, Dario

    2011-05-01

    This article presents the central finite-dimensional H ∞ controller for linear time-varying systems with unknown parameters, that is suboptimal for a given threshold γ with respect to a modified Bolza-Meyer quadratic criterion including the attenuation control term with the opposite sign. In contrast to the previously obtained results, this article reduces the original H ∞ controller problem to the corresponding H 2 controller problem, using the technique proposed in Doyle et al. [Doyle, J.C., Glover, K., Khargonekar, P.P., and Francis, B.A. (1989), 'State-space Solutions to Standard H 2 and H Infinity Control Problems', IEEE Transactions Automatic Control, 34, 831-847]. This article yields the central suboptimal H ∞ controller for linear systems with unknown parameters in a closed finite-dimensional form, based on the corresponding H 2 controller obtained in Basin and Calderon-Alvarez [Basin, M.V., and Calderon-Alvarez, D. (2008), 'Optimal LQG Controller for Linear Systems with Unknown Parameters', Journal of The Franklin Institute, 345, 293-302]. Numerical simulations are conducted to verify performance of the designed central suboptimal controller for uncertain linear systems with unknown parameters against the conventional central suboptimal H ∞ controller for linear systems with exactly known parameter values.

  13. Statistical inference of the time-varying structure of gene-regulation networks

    PubMed Central

    2010-01-01

    Background Biological networks are highly dynamic in response to environmental and physiological cues. This variability is in contrast to conventional analyses of biological networks, which have overwhelmingly employed static graph models which stay constant over time to describe biological systems and their underlying molecular interactions. Methods To overcome these limitations, we propose here a new statistical modelling framework, the ARTIVA formalism (Auto Regressive TIme VArying models), and an associated inferential procedure that allows us to learn temporally varying gene-regulation networks from biological time-course expression data. ARTIVA simultaneously infers the topology of a regulatory network and how it changes over time. It allows us to recover the chronology of regulatory associations for individual genes involved in a specific biological process (development, stress response, etc.). Results We demonstrate that the ARTIVA approach generates detailed insights into the function and dynamics of complex biological systems and exploits efficiently time-course data in systems biology. In particular, two biological scenarios are analyzed: the developmental stages of Drosophila melanogaster and the response of Saccharomyces cerevisiae to benomyl poisoning. Conclusions ARTIVA does recover essential temporal dependencies in biological systems from transcriptional data, and provide a natural starting point to learn and investigate their dynamics in greater detail. PMID:20860793

  14. Estimation of Bid Curves in Power Exchanges using Time-varying Simultaneous-Equations Models

    NASA Astrophysics Data System (ADS)

    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.

  15. The stability analysis of a general viral infection model with distributed delays and multi-staged infected progression

    NASA Astrophysics Data System (ADS)

    Wang, Jinliang; Liu, Shengqiang

    2015-01-01

    We investigate an in-host model with general incidence and removal rate, as well as distributed delays in virus infections and in productions. By employing Lyapunov functionals and LaSalle's invariance principle, we define and prove the basic reproductive number R0 as a threshold quantity for stability of equilibria. It is shown that if R0 > 1 , then the infected equilibrium is globally asymptotically stable, while if R0 ⩽ 1 , then the infection free equilibrium is globally asymptotically stable under some reasonable assumptions. Moreover, n + 1 distributed delays describe (i) the time between viral entry and the transcription of viral RNA, (ii) the n - 1 -stage time needed for activated infected cells between viral RNA transcription and viral release, and (iii) the time necessary for the newly produced viruses to be infectious (maturation), respectively. The model can describe the viral infection dynamics of many viruses such as HIV-1, HCV and HBV.

  16. Time-Varying Upper-Plate Deformation during the Megathrust Subduction Earthquake Cycle

    NASA Astrophysics Data System (ADS)

    Furlong, Kevin P.; Govers, Rob; Herman, Matthew

    2015-04-01

    Over the past several decades of the WEGENER era, our abilities to observe and image the deformational behavior of the upper plate in megathrust subduction zones has dramatically improved. Several intriguing inferences can be made from these observations including apparent lateral variations in locking along subduction zones, which differs from interseismic to coseismic periods; the significant magnitude of post-earthquake deformation (e.g. following the 20U14 Mw Iquique, Chile earthquake, observed on-land GPS post-EQ displacements are comparable to the co-seismic displacements); and incompatibilities between rates of slip deficit accumulation and resulting earthquake co-seismic slip (e.g. pre-Tohoku, inferred rates of slip deficit accumulation on the megathrust significantly exceed slip amounts for the ~ 1000 year recurrence.) Modeling capabilities have grown from fitting simple elastic accumulation/rebound curves to sparse data to having spatially dense continuous time series that allow us to infer details of plate boundary coupling, rheology-driven transient deformation, and partitioning among inter-earthquake and co-seismic displacements. In this research we utilize a 2D numerical modeling to explore the time-varying deformational behavior of subduction zones during the earthquake cycle with an emphasis on upper-plate and plate interface behavior. We have used a simplified model configuration to isolate fundamental processes associated with the earthquake cycle, rather than attempting to fit details of specific megathrust zones. Using a simple subduction geometry, but realistic rheologic layering we are evaluating the time-varying displacement and stress response through a multi-earthquake cycle history. We use a simple model configuration - an elastic subducting slab, an elastic upper plate (shallower than 40 km), and a visco-elastic upper plate (deeper than 40 km). This configuration leads to an upper plate that acts as a deforming elastic beam at inter

  17. Targeted learning in real-world comparative effectiveness research with time-varying interventions.

    PubMed

    Neugebauer, Romain; Schmittdiel, Julie A; van der Laan, Mark J

    2014-06-30

    In comparative effectiveness research (CER), often the aim is to contrast survival outcomes between exposure groups defined by time-varying interventions. With observational data, standard regression analyses (e.g., Cox modeling) cannot account for time-dependent confounders on causal pathways between exposures and outcome nor for time-dependent selection bias that may arise from informative right censoring. Inverse probability weighting (IPW) estimation to fit marginal structural models (MSMs) has commonly been applied to properly adjust for these expected sources of bias in real-world observational studies. We describe the application and performance of an alternate estimation approach in such a study. The approach is based on the recently proposed targeted learning methodology and consists in targeted minimum loss-based estimation (TMLE) with super learning (SL) within a nonparametric MSM. The evaluation is based on the analysis of electronic health record data with both IPW estimation and TMLE to contrast cumulative risks under four more or less aggressive strategies for treatment intensification in adults with type 2 diabetes already on 2+ oral agents or basal insulin. Results from randomized experiments provide a surrogate gold standard to validate confounding and selection bias adjustment. Bootstrapping is used to validate analytic estimation of standard errors. This application does the following: (1) establishes the feasibility of TMLE in real-world CER based on large healthcare databases; (2) provides evidence of proper confounding and selection bias adjustment with TMLE and SL; and (3) motivates their application for improving estimation efficiency. Claims are reinforced with a simulation study that also illustrates the double-robustness property of TMLE. PMID:24535915

  18. High-Resolution Gravity and Time-Varying Gravity Field Recovery using GRACE and CHAMP

    NASA Technical Reports Server (NTRS)

    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.

  19. Representation of Time-Varying Stimuli by a Network Exhibiting Oscillations on a Faster Time Scale

    PubMed Central

    Shamir, Maoz; Ghitza, Oded; Epstein, Steven; Kopell, Nancy

    2009-01-01

    Sensory processing is associated with gamma frequency oscillations (30–80 Hz) in sensory cortices. This raises the question whether gamma oscillations can be directly involved in the representation of time-varying stimuli, including stimuli whose time scale is longer than a gamma cycle. We are interested in the ability of the system to reliably distinguish different stimuli while being robust to stimulus variations such as uniform time-warp. We address this issue with a dynamical model of spiking neurons and study the response to an asymmetric sawtooth input current over a range of shape parameters. These parameters describe how fast the input current rises and falls in time. Our network consists of inhibitory and excitatory populations that are sufficient for generating oscillations in the gamma range. The oscillations period is about one-third of the stimulus duration. Embedded in this network is a subpopulation of excitatory cells that respond to the sawtooth stimulus and a subpopulation of cells that respond to an onset cue. The intrinsic gamma oscillations generate a temporally sparse code for the external stimuli. In this code, an excitatory cell may fire a single spike during a gamma cycle, depending on its tuning properties and on the temporal structure of the specific input; the identity of the stimulus is coded by the list of excitatory cells that fire during each cycle. We quantify the properties of this representation in a series of simulations and show that the sparseness of the code makes it robust to uniform warping of the time scale. We find that resetting of the oscillation phase at stimulus onset is important for a reliable representation of the stimulus and that there is a tradeoff between the resolution of the neural representation of the stimulus and robustness to time-warp. PMID:19412531

  20. Autonomic responses to cold face stimulation in sickle cell disease: a time-varying model analysis

    PubMed Central

    Chalacheva, Patjanaporn; Kato, Roberta M; Sangkatumvong, Suvimol; Detterich, Jon; Bush, Adam; Wood, John C; Meiselman, Herbert; Coates, Thomas D; Khoo, Michael C K

    2015-01-01

    Sickle cell disease (SCD) is characterized by sudden onset of painful vaso-occlusive crises (VOC), which occur on top of the underlying chronic blood disorder. The mechanisms that trigger VOC remain elusive, but recent work suggests that autonomic dysfunction may be an important predisposing factor. Heart-rate variability has been employed in previous studies, but the derived indices have provided only limited univariate information about autonomic cardiovascular control in SCD. To circumvent this limitation, a time-varying modeling approach was applied to investigate the functional mechanisms relating blood pressure (BP) and respiration to heart rate and peripheral vascular resistance in healthy controls, untreated SCD subjects and SCD subjects undergoing chronic transfusion therapy. Measurements of respiration, heart rate, continuous noninvasive BP and peripheral vascular resistance were made before, during and after the application of cold face stimulation (CFS), which perturbs both the parasympathetic and sympathetic nervous systems. Cardiac baroreflex sensitivity estimated from the model was found to be impaired in nontransfused SCD subjects, but partially restored in SCD subjects undergoing transfusion therapy. Respiratory-cardiac coupling gain was decreased in SCD and remained unchanged by chronic transfusion. These results are consistent with autonomic dysfunction in the form of impaired parasympathetic control and sympathetic overactivity. As well, CFS led to a significant reduction in vascular resistance baroreflex sensitivity in the nontransfused SCD subjects but not in the other groups. This blunting of the baroreflex control of peripheral vascular resistance during elevated sympathetic drive could be a potential factor contributing to the triggering of VOC in SCD. PMID:26177958

  1. Early diagnostic of concurrent gear degradation processes progressing under time-varying loads

    NASA Astrophysics Data System (ADS)

    Guilbault, Raynald; Lalonde, Sébastien

    2016-08-01

    This study develops a gear diagnostic procedure for the detection of multi- and concurrent degradation processes evolving under time-varying loads. Instead of a conventional comparison between a descriptor and an alarm level, this procedure bases its detection strategy on a descriptor evolution tracking; a lasting descriptor increase denotes the presence of ongoing degradation mechanisms. The procedure works from time domain residual signals prepared in the frequency domain, and accepts any gear conditions as reference signature. To extract the load fluctuation repercussions, the procedure integrates a scaling factor. The investigation first examines a simplification assuming a linear connection between the load and the dynamic response amplitudes. However, while generally valuable, the precision losses associated with large load variations may mask the contribution of tiny flaws. To better reflect the real non-linear relation, the paper reformulates the scaling factor; a power law with an exponent value of 0.85 produces noticeable improvements of the load effect extraction. To reduce the consequences of remaining oscillations, the procedure also includes a filtering phase. During the validation program, a synthetic wear progression assuming a commensurate relation between the wear depth and friction assured controlled evolutions of the surface degradation influence, whereas the fillet crack growth remained entirely determined by the operation conditions. Globally, the tested conditions attest that the final strategy provides accurate monitoring of coexisting isolated damages and general surface deterioration, and that its tracking-detection capacities are unaffected by severe time variations of external loads. The procedure promptly detects the presence of evolving abnormal phenomena. The tests show that the descriptor curve shapes virtually describe the constant wear progression superimposed on the crack length evolution. At the tooth fracture, the mean values of

  2. Identifiability of Additive, Time-Varying Actuator and Sensor Faults by State Augmentation

    NASA Technical Reports Server (NTRS)

    Upchurch, Jason M.; Gonzalez, Oscar R.; Joshi, Suresh M.

    2014-01-01

    Recent work has provided a set of necessary and sucient conditions for identifiability of additive step faults (e.g., lock-in-place actuator faults, constant bias in the sensors) using state augmentation. This paper extends these results to an important class of faults which may affect linear, time-invariant systems. In particular, the faults under consideration are those which vary with time and affect the system dynamics additively. Such faults may manifest themselves in aircraft as, for example, control surface oscillations, control surface runaway, and sensor drift. The set of necessary and sucient conditions presented in this paper are general, and apply when a class of time-varying faults affects arbitrary combinations of actuators and sensors. The results in the main theorems are illustrated by two case studies, which provide some insight into how the conditions may be used to check the theoretical identifiability of fault configurations of interest for a given system. It is shown that while state augmentation can be used to identify certain fault configurations, other fault configurations are theoretically impossible to identify using state augmentation, giving practitioners valuable insight into such situations. That is, the limitations of state augmentation for a given system and configuration of faults are made explicit. Another limitation of model-based methods is that there can be large numbers of fault configurations, thus making identification of all possible configurations impractical. However, the theoretical identifiability of known, credible fault configurations can be tested using the theorems presented in this paper, which can then assist the efforts of fault identification practitioners.

  3. Stability analysis and backward whirl investigation of cracked rotors with time-varying stiffness

    NASA Astrophysics Data System (ADS)

    AL-Shudeifat, Mohammad A.

    2015-07-01

    The dynamic stability of dynamical systems with time-periodic stiffness is addressed here. Cracked rotor systems with time-periodic stiffness are well-known examples of such systems. Time-varying area moments of inertia at the cracked element cross-section of a cracked rotor have been used to formulate the time-periodic finite element stiffness matrix. The semi-infinite coefficient matrix obtained by applying the harmonic balance (HB) solution to the finite element (FE) equations of motion is employed here to study the dynamic stability of the system. Consequently, the sign of the determinant of a scaled version of a sub-matrix of this semi-infinite coefficient matrix at a finite number of harmonics in the HB solution is found to be sufficient for identifying the major unstable zones of the system in the parameter plane. Specifically, it is found that the negative determinant always corresponds to unstable zones in all of the systems considered. This approach is applied to a parametrically excited Mathieu's equation, a two degree-of-freedom linear time-periodic dynamical system, a cracked Jeffcott rotor and a finite element model of the cracked rotor system. Compared to the corresponding results obtained by Floquet's theory, the sign of the determinant of the scaled sub-matrix is found to be an efficient tool for identifying the major unstable zones of the linear time-periodic parametrically excited systems, especially large-scale FE systems. Moreover, it is found that the unstable zones for a FE cracked rotor with an open transverse crack model only appear at the backward whirl. The theoretical and experimental results have been found to agree well for verifying that the open crack model excites the backward whirl amplitudes at the critical backward whirling rotational speeds.

  4. Transient evolution of eigenmodes in dynamic cavities and time-varying media

    NASA Astrophysics Data System (ADS)

    Gradoni, Gabriele; Arnaut, Luk R.

    2015-12-01

    In this paper, we investigate the perturbation of natural eigenmodes of dynamic cavities with boundaries moving at quasi-static speeds relative to the wave velocity. For an arbitrarily shaped source-free cavity, the amplitude of the irrotational mode is modeled as a damped harmonic oscillator with time-varying eigenfrequency, i.e., a parametric oscillator. It is found that the effect of the pure Doppler shift of the resonance frequencies of the eigenmodes is small at nonrelativistic speeds. However, it is known that any spectrum of eigenenergies that is perturbed by a space- and/or time-fluctuating medium can develop frequency shifts of arbitrary magnitude. By using a linear dynamic (time-dependent) shift for the cavity broad resonances, we find that Doppler-like large shifts result in a mere frequency modulation of the total (resultant) field amplitude, while nonuniform red or blue shift can create a hybrid amplitude and frequency modulation. Interestingly, the combined action of red and blue shifts of uniform magnitude can also create a hybrid modulation. If the angle between modal wave vector and stirrer speed is accounted for in the static (time-independent) shift, the resulting red and blue shifts lead to irregular hybrid modulations. This can occur even for regular perturbations in regular cavities. In addition, owing to the stochastic nature of mode-stirred cavities, the effect of random Doppler-like shifts is also investigated, leading to a Fokker-Planck equation whose diffusion coefficient shows quadratic dependence on the mode amplitude. Thus, the analysis of random perturbations offers an effective framework for observed instantaneous Doppler effects in closed electromagnetic environments. The mathematical framework obtained in terms of stochastic differential equations is useful to predict the nonstationary response of dynamic cavities with complicated or unknown boundary geometry.

  5. Decomposition Algorithm for Global Reachability on a Time-Varying Graph

    NASA Technical Reports Server (NTRS)

    Kuwata, Yoshiaki

    2010-01-01

    A decomposition algorithm has been developed for global reachability analysis on a space-time grid. By exploiting the upper block-triangular structure, the planning problem is decomposed into smaller subproblems, which is much more scalable than the original approach. Recent studies have proposed the use of a hot-air (Montgolfier) balloon for possible exploration of Titan and Venus because these bodies have thick haze or cloud layers that limit the science return from an orbiter, and the atmospheres would provide enough buoyancy for balloons. One of the important questions that needs to be addressed is what surface locations the balloon can reach from an initial location, and how long it would take. This is referred to as the global reachability problem, where the paths from starting locations to all possible target locations must be computed. The balloon could be driven with its own actuation, but its actuation capability is fairly limited. It would be more efficient to take advantage of the wind field and ride the wind that is much stronger than what the actuator could produce. It is possible to pose the path planning problem as a graph search problem on a directed graph by discretizing the spacetime world and the vehicle actuation. The decomposition algorithm provides reachability analysis of a time-varying graph. Because the balloon only moves in the positive direction in time, the adjacency matrix of the graph can be represented with an upper block-triangular matrix, and this upper block-triangular structure can be exploited to decompose a large graph search problem. The new approach consumes a much smaller amount of memory, which also helps speed up the overall computation when the computing resource has a limited physical memory compared to the problem size.

  6. Time-varying, serotype-specific force of infection of dengue virus.

    PubMed

    Reiner, Robert C; Stoddard, Steven T; Forshey, Brett M; King, Aaron A; Ellis, Alicia M; Lloyd, Alun L; Long, Kanya C; Rocha, Claudio; Vilcarromero, Stalin; Astete, Helvio; Bazan, Isabel; Lenhart, Audrey; Vazquez-Prokopec, Gonzalo M; Paz-Soldan, Valerie A; McCall, Philip J; Kitron, Uriel; Elder, John P; Halsey, Eric S; Morrison, Amy C; Kochel, Tadeusz J; Scott, Thomas W

    2014-07-01

    Infectious disease models play a key role in public health planning. These models rely on accurate estimates of key transmission parameters such as the force of infection (FoI), which is the per-capita risk of a susceptible person being infected. The FoI captures the fundamental dynamics of transmission and is crucial for gauging control efforts, such as identifying vaccination targets. Dengue virus (DENV) is a mosquito-borne, multiserotype pathogen that currently infects ∼390 million people a year. Existing estimates of the DENV FoI are inaccurate because they rely on the unrealistic assumption that risk is constant over time. Dengue models are thus unreliable for designing vaccine deployment strategies. Here, we present to our knowledge the first time-varying (daily), serotype-specific estimates of DENV FoIs using a spline-based fitting procedure designed to examine a 12-y, longitudinal DENV serological dataset from Iquitos, Peru (11,703 individuals, 38,416 samples, and 22,301 serotype-specific DENV infections from 1999 to 2010). The yearly DENV FoI varied markedly across time and serotypes (0-0.33), as did daily basic reproductive numbers (0.49-4.72). During specific time periods, the FoI fluctuations correlated across serotypes, indicating that different DENV serotypes shared common transmission drivers. The marked variation in transmission intensity that we detected indicates that intervention targets based on one-time estimates of the FoI could underestimate the level of effort needed to prevent disease. Our description of dengue virus transmission dynamics is unprecedented in detail, providing a basis for understanding the persistence of this rapidly emerging pathogen and improving disease prevention programs. PMID:24847073

  7. Effect of Time Varying Gravity on DORIS processing for ITRF2013

    NASA Astrophysics Data System (ADS)

    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.

  8. Estimated SLR station position and network frame sensitivity to time-varying gravity

    NASA Astrophysics Data System (ADS)

    Zelensky, Nikita P.; Lemoine, Frank G.; Chinn, Douglas S.; Melachroinos, Stavros; Beckley, Brian D.; Beall, Jennifer Wiser; Bordyugov, Oleg

    2014-06-01

    This paper evaluates the sensitivity of ITRF2008-based satellite laser ranging (SLR) station positions estimated weekly using LAGEOS-1/2 data from 1993 to 2012 to non-tidal time-varying gravity (TVG). Two primary methods for modeling TVG from degree-2 are employed. The operational approach applies an annual GRACE-derived field, and IERS recommended linear rates for five coefficients. The experimental approach uses low-order/degree coefficients estimated weekly from SLR and DORIS processing of up to 11 satellites (tvg4x4). This study shows that the LAGEOS-1/2 orbits and the weekly station solutions are sensitive to more detailed modeling of TVG than prescribed in the current IERS standards. Over 1993-2012 tvg4x4 improves SLR residuals by 18 % and shows 10 % RMS improvement in station stability. Tests suggest that the improved stability of the tvg4x4 POD solution frame may help clarify geophysical signals present in the estimated station position time series. The signals include linear and seasonal station motion, and motion of the TRF origin, particularly in Z. The effect on both POD and the station solutions becomes increasingly evident starting in 2006. Over 2008-2012, the tvg4x4 series improves SLR residuals by 29 %. Use of the GRGS RL02 series shows similar improvement in POD. Using tvg4x4, secular changes in the TRF origin Z component double over the last decade and although not conclusive, it is consistent with increased geocenter rate expected due to continental ice melt. The test results indicate that accurate modeling of TVG is necessary for improvement of station position estimation using SLR data.

  9. Early-Emerging Nicotine Dependence Has Lasting and Time-Varying Effects on Adolescent Smoking Behavior.

    PubMed

    Selya, Arielle S; Dierker, Lisa; Rose, Jennifer S; Hedeker, Donald; Mermelstein, Robin J

    2016-08-01

    Novice and light adolescent smokers can develop symptoms of nicotine dependence, which predicts smoking behavior several years into the future. However, little is known about how the association between these early - emerging symptoms and later smoker behaviors may change across time from early adolescence into young adulthood. Data were drawn from a 7-year longitudinal study of experimental (<100 cigarettes/lifetime; N = 594) and light (100+ cigarettes/lifetime, but ≤5 cigarettes/day; N = 152) adolescent smokers. Time-varying effect models were used to examine the relationship between baseline nicotine dependence (assessed at age 15 ± 2 years) and future smoking frequency through age 24, after controlling for concurrent smoking heaviness. Baseline smoking status, race, and sex were examined as potential moderators of this relationship. Nicotine dependence symptoms assessed at approximately age 15 significantly predicted smoking frequency through age 24, over and above concurrent smoking heaviness, though it showed declining trends at older ages. Predictive validity was weaker among experimenters at young ages (<16), but stronger at older ages (20-23), relative to light smokers. Additionally, nicotine dependence was a stronger predictor of smoking frequency for white smokers around baseline (ages 14.5-16), relative to nonwhite smokers. Nicotine dependence assessed in mid-adolescence predicts smoking frequency well into early adulthood, over and above concurrent smoking heaviness, especially among novice smokers and nonwhite smokers. Early-emerging nicotine dependence is a promising marker for screening and interventions aimed at preventing smoking progression. PMID:27312479

  10. Time-varying bispectral analysis of visually evoked multi-channel EEG

    NASA Astrophysics Data System (ADS)

    Chandran, Vinod

    2012-12-01

    Theoretical foundations of higher order spectral analysis are revisited to examine the use of time-varying bicoherence on non-stationary signals using a classical short-time Fourier approach. A methodology is developed to apply this to evoked EEG responses where a stimulus-locked time reference is available. Short-time windowed ensembles of the response at the same offset from the reference are considered as ergodic cyclostationary processes within a non-stationary random process. Bicoherence can be estimated reliably with known levels at which it is significantly different from zero and can be tracked as a function of offset from the stimulus. When this methodology is applied to multi-channel EEG, it is possible to obtain information about phase synchronization at different regions of the brain as the neural response develops. The methodology is applied to analyze evoked EEG response to flash visual stimulii to the left and right eye separately. The EEG electrode array is segmented based on bicoherence evolution with time using the mean absolute difference as a measure of dissimilarity. Segment maps confirm the importance of the occipital region in visual processing and demonstrate a link between the frontal and occipital regions during the response. Maps are constructed using bicoherence at bifrequencies that include the alpha band frequency of 8Hz as well as 4 and 20Hz. Differences are observed between responses from the left eye and the right eye, and also between subjects. The methodology shows potential as a neurological functional imaging technique that can be further developed for diagnosis and monitoring using scalp EEG which is less invasive and less expensive than magnetic resonance imaging.

  11. Adaptive calibration of a three-microphone system for acoustic waveguide characterization under time-varying conditions.

    PubMed

    van Walstijn, Maarten; de Sanctis, Giovanni

    2014-02-01

    The pressure and velocity field in a one-dimensional acoustic waveguide can be sensed in a non-intrusive manner using spatially distributed microphones. Experimental characterization with sensor arrangements of this type has many applications in measurement and control. This paper presents a method for measuring the acoustic variables in a duct under fluctuating propagation conditions with specific focus on in-system calibration and tracking of the system parameters of a three-microphone measurement configuration. The tractability of the non-linear optimization problem that results from taking a parametric approach is investigated alongside the influence of extraneous measurement noise on the parameter estimates. The validity and accuracy of the method are experimentally assessed in terms of the ability of the calibrated system to separate the propagating waves under controlled conditions. The tracking performance is tested through measurements with a time-varying mean flow, including an experiment conducted under propagation conditions similar to those in a wind instrument during playing. PMID:25234899

  12. Time-varying causal network of the Korean financial system based on firm-specific risk premiums

    NASA Astrophysics Data System (ADS)

    Song, Jae Wook; Ko, Bonggyun; Cho, Poongjin; Chang, Woojin

    2016-09-01

    The aim of this paper is to investigate the Korean financial system based on time-varying causal network. We discover many stylized facts by utilizing the firm-specific risk premiums for measuring the causality direction from a firm to firm. At first, we discover that the interconnectedness of causal network is affected by the outbreak of financial events; the co-movement of firm-specific risk premium is strengthened after each positive event, and vice versa. Secondly, we find that the major sector of the Korean financial system is the Depositories, and the financial reform in June-2011 achieves its purpose by weakening the power of risk-spillovers of Broker-Dealers. Thirdly, we identify that the causal network is a small-world network with scale-free topology where the power-law exponents of out-Degree and negative event are more significant than those of in-Degree and positive event. Lastly, we discuss that the current aspects of causal network are closely related to the long-term future scenario of the KOSPI Composite index where the direction and stability are significantly affected by the power of risk-spillovers and the power-law exponents of degree distributions, respectively.

  13. Accounting for Unobserved Time-Varying Quality in Recreation Demand: An Application to a Sonoran Desert Wilderness

    EPA Science Inventory

    Environmental variables can be important factors in recreation demand. Analysts wishing to quantify environmental quality impacts face the difficult issue of isolating them from unobserved variables. Quality changes may occur in space, varying between sites, or in time, varying b...

  14. THE EFFECT OF A TIME-VARYING ACCRETION DISK SIZE ON QUASAR MICROLENSING LIGHT CURVES

    SciTech Connect

    Blackburne, Jeffrey A.; Kochanek, Christopher S. E-mail: ckochanek@astronomy.ohio-state.ed

    2010-08-01

    Microlensing perturbations to the magnification of gravitationally lensed quasar images are dependent on the angular size of the quasar. If quasar variability at visible wavelengths is caused by a change in the area of the accretion disk, it will affect the microlensing magnification. We derive the expected signal, assuming that the luminosity scales with some power of the disk area, and estimate its amplitude using simulations. We discuss the prospects for detecting the effect in real-world data and for using it to estimate the logarithmic slope of the luminosity's dependence on disk area. Such an estimate would provide a direct test of the standard thin accretion disk model. We tried fitting six seasons of the light curves of the lensed quasar HE 0435-1223 including this effect as a modification to the Kochanek et al. approach to estimating time delays. We find a dramatic improvement in the goodness of fit and relatively plausible parameters, but a robust estimate will require a full numerical calculation in order to correctly model the strong correlations between the structure of the microlensing magnification patterns and the magnitude of the effect. We also comment briefly on the effect of this phenomenon for the stability of time-delay estimates.

  15. Mixed effects models for recurrent events data with partially observed time-varying covariates: Ecological momentary assessment of smoking.

    PubMed

    Rathbun, Stephen L; Shiffman, Saul

    2016-03-01

    Cigarette smoking is a prototypical example of a recurrent event. The pattern of recurrent smoking events may depend on time-varying covariates including mood and environmental variables. Fixed effects and frailty models for recurrent events data assume that smokers have a common association with time-varying covariates. We develop a mixed effects version of a recurrent events model that may be used to describe variation among smokers in how they respond to those covariates, potentially leading to the development of individual-based smoking cessation therapies. Our method extends the modified EM algorithm of Steele (1996) for generalized mixed models to recurrent events data with partially observed time-varying covariates. It is offered as an alternative to the method of Rizopoulos, Verbeke, and Lesaffre (2009) who extended Steele's (1996) algorithm to a joint-model for the recurrent events data and time-varying covariates. Our approach does not require a model for the time-varying covariates, but instead assumes that the time-varying covariates are sampled according to a Poisson point process with known intensity. Our methods are well suited to data collected using Ecological Momentary Assessment (EMA), a method of data collection widely used in the behavioral sciences to collect data on emotional state and recurrent events in the every-day environments of study subjects using electronic devices such as Personal Digital Assistants (PDA) or smart phones. PMID:26410189

  16. Mixed Effects Models for Recurrent Events Data with Partially Observed Time-Varying Covariates: Ecological Momentary Assessment of Smoking

    PubMed Central

    Rathbun, Stephen L.; Shiffman, Saul

    2015-01-01

    Summary Cigarette smoking is a prototypical example of a recurrent event. The pattern of recurrent smoking events may depend on time-varying covariates including mood and environmental variables. Fixed effects and frailty models for recurrent events data assume that smokers have a common association with time-varying covariates. We develop a mixed effects version of a recurrent events model that may be used to describe variation among smokers in how they respond to those covariates, potentially leading to the development of individual-based smoking cessation therapies. Our method extends the modified EM algorithm of Steele (1996) for generalized mixed models to recurrent events data with partially observed time-varying covariates. It is offered as an alternative to the method of Rizopoulos, Verbeke and Lesaffre (2009) who extended Steele’s (1996) algorithm to a joint-model for the recurrent events data and time-varying covariates. Our approach does not require a model for the time-varying covariates, but instead assumes that the time-varying covariates are sampled according to a Poisson point process with known intensity. Our methods are well suited to data collected using Ecological Momentary Assessment (EMA), a method of data collection widely used in the behavioral sciences to collect data on emotional state and recurrent events in the every-day environments of study subjects using electronic devices such as Personal Digital Assistants (PDA) or smart phones. PMID:26410189

  17. Time-varying loss forecast for an earthquake scenario in Basel, Switzerland

    NASA Astrophysics Data System (ADS)

    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

  18. Deceleration and Trapping of Polar Molecules using Time-varying Electric Fields

    NASA Astrophysics Data System (ADS)

    Bethlem, Hendrick L.

    2004-03-01

    Over the last two decades, physicists have steadily learned to control the motion of particles, ranging from neutrons, to ions, atoms and finally molecules. These methods have led to a renaissance in atomic physics and have the potential to do the same for molecular physics. Ultracold atoms are used in time standards and in precision tests of quantum electrodynamics and various other fundamental physics theories. Atom cooling methods have also made possible the realization of Bose-Einstein condensation in dilute atomic vapors and the atom laser. Not surprisingly, physicists and chemists now want to perform the same tricks with molecules. But molecules have much more to offer than simply extending the experiments already performed with atoms to more complex species. For instance, the dipole-dipole interaction in a molecular Bose-Einstein condensate gives a molecular condensate new and intriguing properties. Polar Fermi gases may be used to observe the superfluid transition. Cooling molecules will also make it possible to improve the resolution of various fundamental physics studies. For instance, specific molecules such as YbF and PbO are considered ideal for testing the time reversal symmetry postulate and chiral molecules are being used to study parity violation. Furthermore, cold molecules offer various interesting possibilities for chemistry. Cooling molecules to ultracold temperatures gives access to an exotic regime for chemical reactivity, where the thermal de Broglie wavelength exceeds the size of the collision complex. Similarly, the formation of long-lived, transiently bound molecular complexes enables reactions to occur via tunnelling through reaction barriers, thus opening novel routes for low-temperature chemistry. Over the last few years we have been involved in a project to decelerate a pulsed beam of dipolar molecules by time-varying electric fields. A polar molecule experiences a force in an inhomogeneous electric field. Using this force neutral

  19. Time-varying sodium absorption in the Type Ia supernova 2013gh

    NASA Astrophysics Data System (ADS)

    Ferretti, R.; Amanullah, R.; Goobar, A.; Johansson, J.; Vreeswijk, P. M.; Butler, R. P.; Cao, Y.; Cenko, S. B.; Doran, G.; Filippenko, A. V.; Freeland, E.; Hosseinzadeh, G.; Howell, D. A.; Lundqvist, P.; Mattila, S.; Nordin, J.; Nugent, P. E.; Petrushevska, T.; Valenti, S.; Vogt, S.; Wozniak, P.

    2016-07-01

    Context. Temporal variability of narrow absorption lines in high-resolution spectra of Type Ia supernovae (SNe Ia) is studied to search for circumstellar matter. Time series which resolve the profiles of absorption lines such as Na I D or Ca II H&K are expected to reveal variations due to photoionisation and subsequent recombination of the gases. The presence, composition, and geometry of circumstellar matter may hint at the elusive progenitor system of SNe Ia and could also affect the observed reddening law. Aims: To date, there are few known cases of time-varying Na I D absorption in SNe Ia, all of which occurred during relatively late phases of the supernova (SN) evolution. Photoionisation, however, is predicted to occur during the early phases of SNe Ia, when the supernovae peak in the ultraviolet. We attempt, therefore, to observe early-time absorption-line variations by obtaining high-resolution spectra of SNe before maximum light. Methods: We have obtained photometry and high-resolution spectroscopy of SNe Ia 2013gh and iPTF 13dge, to search for absorption-line variations. Furthermore, we study interstellar absorption features in relation to the observed photometric colours of the SNe. Results: Both SNe display deep Na I D and Ca II H&K absorption features. Furthermore, small but significant variations are detected in a feature of the Na I D profile of SN 2013gh. The variations are consistent with either geometric effects of rapidly moving or patchy gas clouds or photoionisation of Na I gas at R ≈ 1019 cm from the explosion. Conclusions: Our analysis indicates that it is necessary to focus on early phases to detect photoionisation effects of gases in the circumstellar medium of SNe Ia. Different absorbers such as Na I and Ca II can be used to probe for matter at different distances from the SNe. The nondetection of variations during early phases makes it possible to put limits on the abundance of the species at those distances. Full Tables 2 and 3 are only

  20. Pulse-delay effects in the angular distribution of near-threshold EUV + IR two-photon ionization of Ne

    NASA Astrophysics Data System (ADS)

    Mondal, S.; Fukuzawa, H.; Motomura, K.; Tachibana, T.; Nagaya, K.; Sakai, T.; Matsunami, K.; Yase, S.; Yao, M.; Wada, S.; Hayashita, H.; Saito, N.; Callegari, C.; Prince, K. C.; Miron, C.; Nagasono, M.; Togashi, T.; Yabashi, M.; Ishikawa, K. L.; Kazansky, A. K.; Kabachnik, N. M.; Ueda, K.

    2014-01-01

    Photoelectron angular distributions (PADs) from two-photon near-threshold ionization of Ne atoms by the combined action of femtosecond pulses from an extreme ultraviolet (EUV) free-electron laser and infrared (IR) laser have been studied experimentally and theoretically. Solutions of the time-dependent Schrödinger equation indicate that the PADs strongly depend on the time delay between EUV and IR pulses. The experimental results obtained for two extreme cases of completely overlapping and nonoverlapping pulses fully confirm the prediction, illustrating that the measurements of the time-delay dependence of the PAD provide a tool for investigating the fundamental problem of the relative importance of the resonant and nonresonant pathways in the two-color two-photon processes.

  1. pth moment exponential stochastic synchronization of coupled memristor-based neural networks with mixed delays via delayed impulsive control.

    PubMed

    Yang, Xinsong; Cao, Jinde; Qiu, Jianlong

    2015-05-01

    This paper concerns the pth moment synchronization in an array of generally coupled memristor-based neural networks with time-varying discrete delays, unbounded distributed delays, as well as stochastic perturbations. Hybrid controllers are designed to cope with the uncertainties caused by the state-dependent parameters: (a) state feedback controllers combined with delayed impulsive controller; (b) adaptive controller combined with delayed impulsive controller. Based on an impulsive differential inequality, the properties of random variables, the framework of Filippov solution, and Lyapunov functional method, sufficient conditions are derived to guarantee that the considered coupled memristor-based neural networks can be pth moment globally exponentially synchronized onto an isolated node under both of the two classes of hybrid impulsive controllers. Finally, numerical simulations are given to show the effectiveness of the theoretical results. PMID:25703512

  2. Optimal JPEG2000 rate control mechanism applicable for super low delay distribution of HDTV programs

    NASA Astrophysics Data System (ADS)

    Naito, S.; Koike, A.

    2006-01-01

    JPEG2000 technology has been adopted even for encoding motion pictures because of its high coding performance and the scalability of the stream format. Since it includes the additional advantage of employing intra frame coding technology such as JPEG2000, it allows drastic reduction in the latency accompanied by encoding and decoding process can be extremely reduced. On the other hand, a low delay transmission has been required especially for a FPU (Field Pick-up Unit) terminal or a piece of wireless camera equipment which may be utilized for a real-time remote hookup. In many such terminals, compression coding was conducted by typical MPEG-2 video, and the codec latency of more than 300 msec was forced basically from its coding algorithm. In this paper, HDTV is assumed to be a typical video application, and an optimal rate control mechanism for the JPEG2000 encoder is introduced as a key technology to achieve a low delay in transmission while maintaining high coding performance. Our study introduces advanced key technologies as yet unrecognized officially. Coding experiments using those technologies confirmed that significant coding delay elimination was achieved when compared to conventional encoding schemes.

  3. Benefits of preserving stationary and time-varying formant structure in alternative representations of speech: Implications for cochlear implants

    PubMed Central

    Nittrouer, Susan; Lowenstein, Joanna H.; Wucinich, Taylor; Tarr, Eric

    2014-01-01

    Cochlear implants have improved speech recognition for deaf individuals, but further modifications are required before performance will match that of normal-hearing listeners. In this study, the hypotheses were tested that (1) implant processing would benefit from efforts to preserve the structure of the low-frequency formants and (2) time-varying aspects of that structure would be especially beneficial. Using noise-vocoded and sine-wave stimuli with normal-hearing listeners, two experiments examined placing boundaries between static spectral channels to optimize representation of the first two formants and preserving time-varying formant structure. Another hypothesis tested in this study was that children might benefit more than adults from strategies that preserve formant structure, especially time-varying structure. Sixty listeners provided data to each experiment: 20 adults and 20 children at each of 5 and 7 years old. Materials were consonant-vowel-consonant words, four-word syntactically correct, meaningless sentences, and five-word syntactically correct, meaningful sentences. Results showed that listeners of all ages benefited from having channel boundaries placed to optimize information about the first two formants, and benefited even more from having time-varying structure. Children showed greater gains than adults only for time-varying formant structure. Results suggest that efforts would be well spent trying to design processing strategies that preserve formant structure. PMID:25324085

  4. Benefits of preserving stationary and time-varying formant structure in alternative representations of speech: implications for cochlear implants.

    PubMed

    Nittrouer, Susan; Lowenstein, Joanna H; Wucinich, Taylor; Tarr, Eric

    2014-10-01

    Cochlear implants have improved speech recognition for deaf individuals, but further modifications are required before performance will match that of normal-hearing listeners. In this study, the hypotheses were tested that (1) implant processing would benefit from efforts to preserve the structure of the low-frequency formants and (2) time-varying aspects of that structure would be especially beneficial. Using noise-vocoded and sine-wave stimuli with normal-hearing listeners, two experiments examined placing boundaries between static spectral channels to optimize representation of the first two formants and preserving time-varying formant structure. Another hypothesis tested in this study was that children might benefit more than adults from strategies that preserve formant structure, especially time-varying structure. Sixty listeners provided data to each experiment: 20 adults and 20 children at each of 5 and 7 years old. Materials were consonant-vowel-consonant words, four-word syntactically correct, meaningless sentences, and five-word syntactically correct, meaningful sentences. Results showed that listeners of all ages benefited from having channel boundaries placed to optimize information about the first two formants, and benefited even more from having time-varying structure. Children showed greater gains than adults only for time-varying formant structure. Results suggest that efforts would be well spent trying to design processing strategies that preserve formant structure. PMID:25324085

  5. Structure and composition of the distant lunar exosphere: Constraints from ARTEMIS observations of ion acceleration in time-varying fields

    NASA Astrophysics Data System (ADS)

    Halekas, J. S.; Poppe, A. R.; Farrell, W. M.; McFadden, J. P.

    2016-06-01

    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.

  6. Exponential Stability of the Energy of the Wave Equation with Variable Coefficients and a Boundary Distributed Delay

    NASA Astrophysics Data System (ADS)

    Liu, Wenjun

    2014-11-01

    In this paper, we consider a wave equation with space variable coefficients. Due to physical considerations, a distributed delay damping is acted on the part of the boundary. Under suitable assumptions, we prove the exponential stability of the energy based on the use of Riemannian geometry method, the perturbed energy argument, and some observability inequalities. From the applications point of view, our results may provide some qualitative analysis and intuition for the researchers in fields such as engineering, biophysics, and mechanics. And the method is rather general and can be adapted to other evolution systems with variable coefficients (e. g. elasticity plates) as well.

  7. The optimal manufacturing batch size with rework under time-varying demand process for a finite time horizon

    NASA Astrophysics Data System (ADS)

    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.

  8. Mapping transverse velocity of particles in capillary vessels by time-varying laser speckle through perturbation analyses

    PubMed Central

    Wang, Yi; Ma, Zhenhe; Wang, Ruikang

    2015-01-01

    We propose a cross-correlation method to map the transverse velocities of particles moving in capillary vessels using full-field time-varying laser speckle technique. The mapping is achieved by a semi-random perturbation model that describes the intensity fluctuation of time-varying laser speckle signals. When passing through probing volume, moving particles encode a random perturbation into the observed laser speckle pattern. We calculate the transverse flow velocity by cross-correlating the temporal envelopes of the perturbation signals. The proposed method is experimentally verified by the use of polymer microsphere suspension in a glass capillary. PMID:25927742

  9. A numerical study on the time-varying attitudes and aerodynamics of freely falling conical graupel

    NASA Astrophysics Data System (ADS)

    Chueh, Chih-Che; Wang, Pao K.

    2016-04-01

    The flow fields and dynamic motions of conical graupel of diameters 0.5-5mm falling in air of 800 hPa and -20°C are studied by solving the transient Navier-Stokes equations numerically for flow past the conical graupel and the body dynamics equations representing the 6-degrees-of-freedom motion that determines the position and orientation of the graupel in response to the hydrodynamic force of the flow fields. The shape of conical graupel made through a simple but practical existing mathematical equation allows us to have an uneven mass distribution, which is generally believed to have great influence on ice particles' orientations while falling when inertial force becomes increasingly dominant over other effects. The simulated motions include vertical fall, lateral translation, sailing, rotation and pendulum swing. The computed flow fields are characterized in terms of streamtrace patterns as well as the vorticity magnitude fields, and the corresponding motion of the conical graupel is physically featured by looking upon the graupel surface distributions of pressure coefficient, torques contributed by both pressure as well as viscous effects. Tumbling occurs when an initial orientation of the graupel is 160° about Y axis, and the torque contributed by the pressure effect is dominant over that contributed by the viscous effect.

  10. Global distribution of polymorphisms associated with delayed Plasmodium falciparum parasite clearance following artemisinin treatment: genotyping of archive blood samples.

    PubMed

    Murai, Kenji; Culleton, Richard; Hisaoka, Teruhiko; Endo, Hiroyoshi; Mita, Toshihiro

    2015-06-01

    The recent emergence and spread of artemisinin-resistant Plasmodium falciparum isolates is a growing concern for global malaria-control efforts. A recent genome-wide analysis study identified two SNPs at genomic positions MAL10-688956 and MAL13-1718319, which are linked to delayed clearance of parasites following artemisinin combination therapy (ACT). It is expected that continuous artemisinin pressure will affect the distribution of these SNPs. Here, we investigate the worldwide distribution of these SNPs using a large number of archived samples in order to generate baseline data from the period before the emergence of ACT resistance. The presence of SNPs in MAL10-688956 and MAL13-1718319 was assessed by nested PCR RFLP and direct DNA sequencing using 653 global P. falciparum samples obtained before the reported emergence of ACT resistance. SNPs at MAL10-688956 and MAL13-1718319 associated with delayed parasite clearance following ACT administration were observed in 8% and 3% of parasites, respectively, mostly in Cambodia and Thailand. Parasites harbouring both SNPs were found in only eight (1%) isolates, all of which were from Cambodia and Thailand. Linkage disequilibrium was detected between MAL10-688956 and MAL13-1718319, suggesting that this SNP combination may have been selected by ACT drug pressure. Neither of the SNPs associated with delayed parasite clearance were observed in samples from Africa or South America. Baseline information of the geographical difference of MAL10-688956 and MAL13-1718319 SNPs provides a solid basis for assessing whether these SNPs are selected by artemisinin-based combination therapies. PMID:25449286

  11. Analytical Solutions of Heat-Conduction Problems with Time-Varying Heat-Transfer Coefficients

    NASA Astrophysics Data System (ADS)

    Kudinov, V. A.; Eremin, A. V.; Stefanyuk, E. V.

    2015-05-01

    The problem on heat conduction of an infinite plate with a heat-transfer coefficient changing linearly with time for third-kind boundary conditions was solved analytically based on determination of the front of a temperature disturbance in this plate and introduction of additional boundary conditions. On the basis of the solution obtained, graphs of the distribution of isotherms in the indicated plate and the velocities of their movement along a spatial variable in it were constructed. As a result of the solution of the inverse problem on the heat conduction of the infinite plate with the use of the results of numerical calculation of the change in its temperature at any point on the indicated spatial coordinate, the Predvoditelev number was identified with an accuracy of 2%, which made it possible to determine the time dependence of the heat-transfer coefficient of the plate.

  12. Metaheuristics for multi products inventory routing problem with time varying demand

    NASA Astrophysics Data System (ADS)

    Moin, Noor Hasnah; Ab Halim, Huda Zuhrah; Yuliana, Titi

    2014-07-01

    This paper addresses the inventory routing problem (IRP) with a many-to-one distribution network, consisting of a single depot, an assembly plant, and geographically dispersed suppliers where a capacitated homogeneous vehicle delivers a distinct product from the suppliers to fulfill the demand specified by the assembly plant over the planning horizon. The inventory holding cost is assumed to be product specific and only incurred at the assembly plant. Two metaheuristics comprise of artificial bee colony (ABC) and scatter search (SS) algorithms are proposed to solve the problem. Computational testing on instances which represents small, medium, and large data sets show that the ABC algorithm performs slightly better when compared the SS overall except for fifty suppliers problems.

  13. Smoothed Particle Hydrodynamics with Time Varying, Piecewise Constant Smoothing Length Profiles

    NASA Astrophysics Data System (ADS)

    Børve, S.; Omang, M.; Trulsen, J.

    2000-12-01

    Smoothed Particle Hydrodynamics (SPH) has proven to be a very useful numerical tool in studying a number of widely different astrophysical problems. Still, used on many other types of problems the method faces problems concerning efficiency and accuracy compared to that of modern grid-based methods. Essential to efficiency is maintaining a near-optimal particle distribution and smoothing length profile that reflects the physics of the problem. This means, directing computer resources towards those regions and time intervals where the action is taking place and not being wasted where nothing is happening. In the literature researchers have tried to achieve these goals by combining the Lagrangian nature of the SPH method with a smoothing length profile varying smoothly in space and time. To make the SPH method better suited for accurately describing a wider range of problems, a scheme containing two novel features is proposed. First, the scheme assumes a piecewise constant smoothing length profile. To avoid substantial errors near steps in the smoothing length profile, alternative forms of the SPH equations of motion is used. Secondly, a predictive attitude towards optimizing the particle distribution is introduced by activating a mass, momentum and internal energy conservation regularization process at intervals. The main challenge faced by the scheme has been to put the newly optimized smoothing length profile into use without severely altering the underlying physics. To achieve this, the entire set of particles is redefined in the process. The basic ideas behind this scheme is briefly described. Finally, the results from several hydrodynamical and magnetohydrodynamical tests in one and two dimensions are presented. This work is funded by the Research Council of Norway.

  14. Control-focused, nonlinear and time-varying modelling of dielectric elastomer actuators with frequency response analysis

    NASA Astrophysics Data System (ADS)

    Jacobs, William R.; Wilson, Emma D.; Assaf, Tareq; Rossiter, Jonathan; Dodd, Tony J.; Porrill, John; Anderson, Sean R.

    2015-05-01

    Current models of dielectric elastomer actuators (DEAs) are mostly constrained to first principal descriptions that are not well suited to the application of control design due to their computational complexity. In this work we describe an integrated framework for the identification of control focused, data driven and time-varying DEA models that allow advanced analysis of nonlinear system dynamics in the frequency-domain. Experimentally generated input-output data (voltage-displacement) was used to identify control-focused, nonlinear and time-varying dynamic models of a set of film-type DEAs. The model description used was the nonlinear autoregressive with exogenous input structure. Frequency response analysis of the DEA dynamics was performed using generalized frequency response functions, providing insight and a comparison into the time-varying dynamics across a set of DEA actuators. The results demonstrated that models identified within the presented framework provide a compact and accurate description of the system dynamics. The frequency response analysis revealed variation in the time-varying dynamic behaviour of DEAs fabricated to the same specifications. These results suggest that the modelling and analysis framework presented here is a potentially useful tool for future work in guiding DEA actuator design and fabrication for application domains such as soft robotics.

  15. Gearbox fault diagnosis using adaptive zero phase time-varying filter based on multi-scale chirplet sparse signal decomposition

    NASA Astrophysics Data System (ADS)

    Wu, Chunyan; Liu, Jian; Peng, Fuqiang; Yu, Dejie; Li, Rong

    2013-07-01

    When used for separating multi-component non-stationary signals, the adaptive time-varying filter(ATF) based on multi-scale chirplet sparse signal decomposition(MCSSD) generates phase shift and signal distortion. To overcome this drawback, the zero phase filter is introduced to the mentioned filter, and a fault diagnosis method for speed-changing gearbox is proposed. Firstly, the gear meshing frequency of each gearbox is estimated by chirplet path pursuit. Then, according to the estimated gear meshing frequencies, an adaptive zero phase time-varying filter(AZPTF) is designed to filter the original signal. Finally, the basis for fault diagnosis is acquired by the envelope order analysis to the filtered signal. The signal consisting of two time-varying amplitude modulation and frequency modulation(AM-FM) signals is respectively analyzed by ATF and AZPTF based on MCSSD. The simulation results show the variances between the original signals and the filtered signals yielded by AZPTF based on MCSSD are 13.67 and 41.14, which are far less than variances (323.45 and 482.86) between the original signals and the filtered signals obtained by ATF based on MCSSD. The experiment results on the vibration signals of gearboxes indicate that the vibration signals of the two speed-changing gearboxes installed on one foundation bed can be separated by AZPTF effectively. Based on the demodulation information of the vibration signal of each gearbox, the fault diagnosis can be implemented. Both simulation and experiment examples prove that the proposed filter can extract a mono-component time-varying AM-FM signal from the multi-component time-varying AM-FM signal without distortion.

  16. Multi-Level Anomaly Detection on Time-Varying Graph Data

    SciTech Connect

    Bridges, Robert A; Collins, John P; Ferragut, Erik M; Laska, Jason A; Sullivan, Blair D

    2015-01-01

    This work presents a novel modeling and analysis framework for graph sequences which addresses the challenge of detecting and contextualizing anomalies in labelled, streaming graph data. We introduce a generalization of the BTER model of Seshadhri et al. by adding flexibility to community structure, and use this model to perform multi-scale graph anomaly detection. Specifically, probability models describing coarse subgraphs are built by aggregating probabilities at finer levels, and these closely related hierarchical models simultaneously detect deviations from expectation. This technique provides insight into a graph's structure and internal context that may shed light on a detected event. Additionally, this multi-scale analysis facilitates intuitive visualizations by allowing users to narrow focus from an anomalous graph to particular subgraphs or nodes causing the anomaly. For evaluation, two hierarchical anomaly detectors are tested against a baseline Gaussian method on a series of sampled graphs. We demonstrate that our graph statistics-based approach outperforms both a distribution-based detector and the baseline in a labeled setting with community structure, and it accurately detects anomalies in synthetic and real-world datasets at the node, subgraph, and graph levels. To illustrate the accessibility of information made possible via this technique, the anomaly detector and an associated interactive visualization tool are tested on NCAA football data, where teams and conferences that moved within the league are identified with perfect recall, and precision greater than 0.786.

  17. A new framework and software to estimate time-varying reproduction numbers during epidemics.

    PubMed

    Cori, Anne; Ferguson, Neil M; Fraser, Christophe; Cauchemez, Simon

    2013-11-01

    The quantification of transmissibility during epidemics is essential to designing and adjusting public health responses. Transmissibility can be measured by the reproduction number R, the average number of secondary cases caused by an infected individual. Several methods have been proposed to estimate R over the course of an epidemic; however, they are usually difficult to implement for people without a strong background in statistical modeling. Here, we present a ready-to-use tool for estimating R from incidence time series, which is implemented in popular software including Microsoft Excel (Microsoft Corporation, Redmond, Washington). This tool produces novel, statistically robust analytical estimates of R and incorporates uncertainty in the distribution of the serial interval (the time between the onset of symptoms in a primary case and the onset of symptoms in secondary cases). We applied the method to 5 historical outbreaks; the resulting estimates of R are consistent with those presented in the literature. This tool should help epidemiologists quantify temporal changes in the transmission intensity of future epidemics by using surveillance data. PMID:24043437

  18. Electromagnetic scattering and Doppler spectrum simulation of time-varying oil-covered nonlinear sea surface

    NASA Astrophysics Data System (ADS)

    Yang, Pengju; Guo, Lixin; Jia, Chungang

    2016-01-01

    Based on the model of Lombardini et al. [J. Atmos. Ocean. Technol. 6(6), 882-890 (1989)], which can predict the hydrodynamic damping of rough sea surfaces in the presence of oil films, the influence of sea slicks on the sea surface roughness spectrum and sea surface geometrical structure is examined briefly in the present study. On this basis, the influence of sea slicks on the angular distribution of the bistatic scattering coefficient of sea surfaces and the Doppler spectrum signature of backscattered radar sea-echo is investigated in detail based on a frequency-domain numerical method of the parallel fast multiple method. Simulation results show that Doppler spectrum signatures including Doppler shift and spectral bandwidth of radar sea-echo are significantly affected by sea slicks, which are qualitatively consistent with wave-tank or open sea measurements. Moreover, simulation results indicate that the Doppler spectrum signature is a promising technique for remote sensing of oil films floating on sea surfaces.

  19. Multiobjective resource-constrained project scheduling with a time-varying number of tasks.

    PubMed

    Abello, Manuel Blanco; Michalewicz, Zbigniew

    2014-01-01

    In resource-constrained project scheduling (RCPS) problems, ongoing tasks are restricted to utilizing a fixed number of resources. This paper investigates a dynamic version of the RCPS problem where the number of tasks varies in time. Our previous work investigated a technique called mapping of task IDs for centroid-based approach with random immigrants (McBAR) that was used to solve the dynamic problem. However, the solution-searching ability of McBAR was investigated over only a few instances of the dynamic problem. As a consequence, only a small number of characteristics of McBAR, under the dynamics of the RCPS problem, were found. Further, only a few techniques were compared to McBAR with respect to its solution-searching ability for solving the dynamic problem. In this paper, (a) the significance of the subalgorithms of McBAR is investigated by comparing McBAR to several other techniques; and (b) the scope of investigation in the previous work is extended. In particular, McBAR is compared to a technique called, Estimation Distribution Algorithm (EDA). As with McBAR, EDA is applied to solve the dynamic problem, an application that is unique in the literature. PMID:24883398

  20. Multiobjective Resource-Constrained Project Scheduling with a Time-Varying Number of Tasks

    PubMed Central

    Abello, Manuel Blanco

    2014-01-01

    In resource-constrained project scheduling (RCPS) problems, ongoing tasks are restricted to utilizing a fixed number of resources. This paper investigates a dynamic version of the RCPS problem where the number of tasks varies in time. Our previous work investigated a technique called mapping of task IDs for centroid-based approach with random immigrants (McBAR) that was used to solve the dynamic problem. However, the solution-searching ability of McBAR was investigated over only a few instances of the dynamic problem. As a consequence, only a small number of characteristics of McBAR, under the dynamics of the RCPS problem, were found. Further, only a few techniques were compared to McBAR with respect to its solution-searching ability for solving the dynamic problem. In this paper, (a) the significance of the subalgorithms of McBAR is investigated by comparing McBAR to several other techniques; and (b) the scope of investigation in the previous work is extended. In particular, McBAR is compared to a technique called, Estimation Distribution Algorithm (EDA). As with McBAR, EDA is applied to solve the dynamic problem, an application that is unique in the literature. PMID:24883398

  1. A Lightweight Remote Parallel Visualization Platform for Interactive Massive Time-varying Climate Data Analysis

    NASA Astrophysics Data System (ADS)

    Li, J.; Zhang, T.; Huang, Q.; Liu, Q.

    2014-12-01

    Today's climate datasets are featured with large volume, high degree of spatiotemporal complexity and evolving fast overtime. As visualizing large volume distributed climate datasets is computationally intensive, traditional desktop based visualization applications fail to handle the computational intensity. Recently, scientists have developed remote visualization techniques to address the computational issue. Remote visualization techniques usually leverage server-side parallel computing capabilities to perform visualization tasks and deliver visualization results to clients through network. In this research, we aim to build a remote parallel visualization platform for visualizing and analyzing massive climate data. Our visualization platform was built based on Paraview, which is one of the most popular open source remote visualization and analysis applications. To further enhance the scalability and stability of the platform, we have employed cloud computing techniques to support the deployment of the platform. In this platform, all climate datasets are regular grid data which are stored in NetCDF format. Three types of data access methods are supported in the platform: accessing remote datasets provided by OpenDAP servers, accessing datasets hosted on the web visualization server and accessing local datasets. Despite different data access methods, all visualization tasks are completed at the server side to reduce the workload of clients. As a proof of concept, we have implemented a set of scientific visualization methods to show the feasibility of the platform. Preliminary results indicate that the framework can address the computation limitation of desktop based visualization applications.

  2. Combining Multi-Sensor Measurements and Models to Constrain Time-Varying Aerosol Fire Emissions

    NASA Astrophysics Data System (ADS)

    Cohen, J. B.

    2013-12-01

    . This data has been used in connection with a new analytical technique to derive the temporally and spatially varying component of the emissions. Combining this result with the Kalman Filter annual base emissions and the modelling system shows that fires can be reproduced more accurately than many other methods, including using straight Fire Radiative Power estimations. Finally, this new combined product is analyzed using measurements from the CALIPSO sensor to quantify further properties of these fires, particularly in terms of radiative forcing and vertical distribution. The results are compared against other studies of fires and the impacts on the radiative balance are quantified. One conclusion is that emissions of both BC and OC from these fires are currently underestimated and this method provides a means by which to quantify this underestimation, both in terms of absolute amount as well as space and time. A second conclusion is that this method provides a strong rationale for why relying solely on a Fire Radiative Power approach may not be appropriate, especially in a cloud-covered region such as Southeast Asia. Finally, the limitations of the use of multiple-sensors and this approach in general are detailed by looking more in-depth at the massive biomass-burning episode in June of 2013 that occurred in Southeast Asia.

  3. Exact model reduction with delays: closed-form distributions and extensions to fully bi-directional monomolecular reactions

    PubMed Central

    Leier, Andre; Barrio, Manuel; Marquez-Lago, Tatiana T.

    2014-01-01

    In order to systematically understand the qualitative and quantitative behaviour of chemical reaction networks, scientists must derive and analyse associated mathematical models. However, biochemical systems are often very large, with reactions occurring at multiple time scales, as evidenced by signalling pathways and gene expression kinetics. Owing to the associated computational costs, it is then many times impractical, if not impossible, to solve or simulate these systems with an appropriate level of detail. By consequence, there is a growing interest in developing techniques for the simplification or reduction of complex biochemical systems. Here, we extend our recently presented methodology on exact reduction of linear chains of reactions with delay distributions in two ways. First, we report that it is now possible to deal with fully bi-directional monomolecular systems, including degradations, synthesis and generalized bypass reactions. Second, we provide all derivations of associated delays in analytical, closed form. Both advances have a major impact on further reducing computational costs, while still retaining full accuracy. Thus, we expect our new methodology to respond to current simulation needs in pharmaceutical, chemical and biological research. PMID:24694895

  4. Exposure to time varying magnetic fields associated with magnetic resonance imaging reduces fentanyl-induced analgesia in mice

    SciTech Connect

    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.

  5. Continuous higher-order sliding mode control with time-varying gain for a class of uncertain nonlinear systems.

    PubMed

    Han, Yaozhen; Liu, Xiangjie

    2016-05-01

    This paper presents a continuous higher-order sliding mode (HOSM) control scheme with time-varying gain for a class of uncertain nonlinear systems. The proposed controller is derived from the concept of geometric homogeneity and super-twisting algorithm, and includes two parts, the first part of which achieves smooth finite time stabilization of pure integrator chains. The second part conquers the twice differentiable uncertainty and realizes system robustness by employing super-twisting algorithm. Particularly, time-varying switching control gain is constructed to reduce the switching control action magnitude to the minimum possible value while keeping the property of finite time convergence. Examples concerning the perturbed triple integrator chains and excitation control for single-machine infinite bus power system are simulated respectively to demonstrate the effectiveness and applicability of the proposed approach. PMID:26920085

  6. Iterative solutions for one-dimensional diffusion with time varying surface composition and composition-dependent diffusion coefficient

    NASA Technical Reports Server (NTRS)

    Chow, M.; Houska, C. R.

    1980-01-01

    Solutions are given for one-dimensional diffusion problems with a time varying surface composition and also a composition dependent diffusion coefficient. The most general solution does not require special mathematical functions to fit the variation in surface composition or D(C). In another solution, a series expansion may be used to fit the time dependent surface concentration. These solutions make use of iterative calculations that converge rapidly and are highly stable. Computer times are much shorter than that required for finite difference calculations and can efficiently make use of interactive graphics terminals. Existing gas carburization data were used to provide an illustration of an iterative approach with a time varying carbon composition at the free surface.

  7. Proximal and Time-Varying Effects of Cigarette, Alcohol, Marijuana and other Hard Drug Use on Adolescent Dating Aggression

    PubMed Central

    Reyes, H. Luz McNaughton; Foshee, Vangie A.; 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 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. PMID:24636688

  8. Robustness of controllability and observability of linear time-varying systems with application to the emergency control of power systems

    SciTech Connect

    Sastry, S.S.; Desoer, C.A.

    1980-01-01

    Fixed point methods from nonlinear anaysis are used to establish conditions under which the uniform complete controllability of linear time-varying systems is preserved under non-linear perturbations in the state dynamics and the zero-input uniform complete observability of linear time-varying systems is preserved under non-linear perturbation in the state dynamics and output read out map. Algorithms for computing the specific input to steer the perturbed systems from a given initial state to a given final state are also presented. As an application, a very specific emergency control of an interconnected power system is formulated as a steering problem and it is shown that this emergency control is indeed possible in finite time.

  9. Time-varying correlations between delta EEG power and heart rate variability in midlife women: The SWAN Sleep Study

    PubMed Central

    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.

    2014-01-01

    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 (Mage =52.1, SD =2.2). Delta EEG-HF-HRV correlations in Non-Rapid 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. 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. PMID:25431173

  10. Accounting for unobserved time-varying quality in recreation demand: An application to a Sonoran Desert wilderness

    NASA Astrophysics Data System (ADS)

    Weber, Matthew A.; Mozumder, Pallab; Berrens, Robert P.

    2012-05-01

    Environmental variables can be important factors in recreation demand. Analysts wishing to quantify environmental quality impacts face the difficult issue of isolating them from unobserved variables. Quality changes may occur in space, varying between sites, or in time, varying between occasions. In this zonal travel cost analysis, fixed effects are used to control for time-varying factors at a single site, adapting a technique previously applied to control for unobserved factors across sites. Graphical analysis and a second stage regression on time-specific constants are used as diagnostic tools to guide a demand specification directly including both environmental and access predictors. The approach is developed and applied using a multiyear panel data set for a wilderness destination in the Sonoran Desert featuring a perennial stream. Empirical estimates are also provided for the recreational value of a trip day to a Sonoran Desert site with instream flows.

  11. A Low-Power, Dual-Wavelength Photoplethysmogram (PPG) SoC With Static and Time-Varying Interferer Removal.

    PubMed

    Winokur, Eric S; O'Dwyer, Tom; Sodini, Charles G

    2015-08-01

    This paper presents a low-power, reflectance-mode photoplethysmogram (PPG) front end with up to 100 μA of static interferer current removal and 87 dB attenuation of time-varying interferers. The chip nominally consumes 425 μW including signal chain circuits, red and IR LED drive power, clocks, digitization and I/O. Measured data shows the noise of the PPG signal to be dominated by the photodiode sensor photon shot noise. PMID:25373112

  12. Nonlinear finite element model updating of an infilled frame based on identified time-varying modal parameters during an earthquake

    NASA Astrophysics Data System (ADS)

    Asgarieh, Eliyar; Moaveni, Babak; Stavridis, Andreas

    2014-11-01

    A model updating methodology is proposed for calibration of nonlinear finite element (FE) models simulating the behavior of real-world complex civil structures subjected to seismic excitations. In the proposed methodology, parameters of hysteretic material models assigned to elements (or substructures) of a nonlinear FE model are updated by minimizing an objective function. The objective function used in this study is the misfit between the experimentally identified time-varying modal parameters of the structure and those of the FE model at selected time instances along the response time history. The time-varying modal parameters are estimated using the deterministic-stochastic subspace identification method which is an input-output system identification approach. The performance of the proposed updating method is evaluated through numerical and experimental applications on a large-scale three-story reinforced concrete frame with masonry infills. The test structure was subjected to seismic base excitations of increasing amplitude at a large outdoor shake-table. A nonlinear FE model of the test structure has been calibrated to match the time-varying modal parameters of the test structure identified from measured data during a seismic base excitation. The accuracy of the proposed nonlinear FE model updating procedure is quantified in numerical and experimental applications using different error metrics. The calibrated models predict the exact simulated response very accurately in the numerical application, while the updated models match the measured response reasonably well in the experimental application.

  13. Characteristics of time-varying intracranial pressure on blood flow through cerebral artery: A fluid-structure interaction approach.

    PubMed

    Syed, Hasson; Unnikrishnan, Vinu U; Olcmen, Semih

    2016-02-01

    Elevated intracranial pressure is a major contributor to morbidity and mortality in severe head injuries. Wall shear stresses in the artery can be affected by increased intracranial pressures and may lead to the formation of cerebral aneurysms. Earlier research on cerebral arteries and aneurysms involves using constant mean intracranial pressure values. Recent advancements in intracranial pressure monitoring techniques have led to measurement of the intracranial pressure waveform. By incorporating a time-varying intracranial pressure waveform in place of constant intracranial pressures in the analysis of cerebral arteries helps in understanding their effects on arterial deformation and wall shear stress. To date, such a robust computational study on the effect of increasing intracranial pressures on the cerebral arterial wall has not been attempted to the best of our knowledge. In this work, fully coupled fluid-structure interaction simulations are carried out to investigate the effect of the variation in intracranial pressure waveforms on the cerebral arterial wall. Three different time-varying intracranial pressure waveforms and three constant intracranial pressure profiles acting on the cerebral arterial wall are analyzed and compared with specified inlet velocity and outlet pressure conditions. It has been found that the arterial wall experiences deformation depending on the time-varying intracranial pressure waveforms, while the wall shear stress changes at peak systole for all the intracranial pressure profiles. PMID:26701867

  14. Neural-Dynamic-Method-Based Dual-Arm CMG Scheme With Time-Varying Constraints Applied to Humanoid Robots.

    PubMed

    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. PMID:26340789

  15. Exploratory time varying lagged regression: modeling association of cognitive and functional trajectories with expected clinic visits in older adults

    PubMed Central

    Şentürk, Damla; Ghosh, Samiran; Nguyen, Danh V.

    2014-01-01

    Motivated by a longitudinal study on factors affecting the frequency of clinic visits of older adults, an exploratory time varying lagged regression analysis is proposed to relate a longitudinal response to multiple cross-sectional and longitudinal predictors from time varying lags. Regression relations are allowed to vary with time through smooth varying coefficient functions. The main goal of the proposal is to detect deviations from a concurrent varying coefficient model potentially in a subset of the longitudinal predictors with nonzero estimated lags. The proposed methodology is geared towards irregular and infrequent data where different longitudinal variables may be observed at different frequencies, possibly at unsynchronized time points and contaminated with additive measurement error. Furthermore, to cope with the curse of dimensionality which limits related current modeling approaches, a sequential model building procedure is proposed to explore and select the time varying lags of the longitudinal predictors. The estimation procedure is based on estimation of the moments of the predictor and response trajectories by pooling information from all subjects. The finite sample properties of the proposed estimation algorithm are studied under various lag structures and correlation levels among the predictor processes in simulation studies. Application to the clinic visits data show the effect of cognitive and functional impairment scores from varying lags on the frequency of the clinic visits throughout the study. PMID:24436504

  16. Effect of sliding friction on the dynamics of spur gear pair with realistic time-varying stiffness

    NASA Astrophysics Data System (ADS)

    He, Song; Gunda, Rajendra; Singh, Rajendra

    2007-04-01

    The chief objective of this article is to propose a new method of incorporating the sliding friction and realistic time-varying stiffness into an analytical (multi-degree-of-freedom) spur gear model and to evaluate their effects. An accurate finite element/contact mechanics analysis code is employed, in the "static" mode, to compute the mesh stiffness at every time instant under a range of loading conditions. Here, the time-varying stiffness is calculated as an effective function which may also include the effect of profile modifications. The realistic mesh stiffness is then incorporated into the linear time-varying spur gear model with the contributions of sliding friction. Proposed methods are illustrated via two spur gear examples and validated by using the finite element in the "dynamic" mode as experimental results. A key question whether the sliding friction is indeed the source of the off-line-of-action forces and motions is then answered by our analytical model. Finally, the effect of the profile modification on the dynamic transmission error has been analytically examined under the influence of sliding friction. For instance, the linear tip relief introduces an amplification in the off-line-of-action forces and motions due to an out of phase relationship between the normal load and friction forces.

  17. Delayed Choice in Feynman's Neutron Scattering Off a Crystal Experiment: The Effect of Information on the Neutron Distribution

    NASA Astrophysics Data System (ADS)

    Snyder, Douglas

    2014-03-01

    Feynman (Lect. on Phys., v. 3, 1965, ps. 3-7 to 3-9) maintained in his neutron scattering off a crystal experiment that which-way info can exist even if one does not perform a measurement. This interaction involves a spin flip for both the neutron and nucleus that the neutron scatters off. With the flip, the spin of the nucleus that the neutron scattered off becomes different than the spin direction of all the other nuclei in the crystal that the neutron could have scattered off. The spins of all the other nuclei are the same. It may be possible to eliminate the ww info as long as particle detections have not been made. Through spin-lattice relaxation after the neutron-nucleus interaction occurs, the spin flip of the nucleus would reverse before any detection is made. It would no longer be possible to determine which nucleus the neutron scattered off. The result is only interference in the distribution of the neutrons. This change from ww info to interference would be affected by a change in info regarding the nuclei in the crystal since there is no physical process whereby the change in the nuclei can affect the distribution of the neutrons. Altering relaxation duration relative to neutron detection time could provide a delayed choice. Another possibility would be to shut off the uniform, strong, external magnetic field B, that initially aligns all of the spins of the nuclei along the same axis, after the spin flip and before the neutron is detected. Ww info would be eliminated since the spin directions of all the nuclei would quickly become essentially random. Maintaining or turning off B could be a delayed choice.

  18. Fault-induced delayed voltage recovery in a long inhomogeneous power-distribution feeder

    NASA Astrophysics Data System (ADS)

    Stolbova, Irina; Backhaus, Scott; Chertkov, Michael

    2015-02-01

    We analyze the dynamics of a distribution circuit loaded with many induction motors and subjected to sudden changes in voltage at the beginning of the circuit. As opposed to earlier work by Duclut et al. [Phys. Rev. E 87, 062802 (2013), 10.1103/PhysRevE.87.062802], the motors are disordered, i.e., the mechanical torque applied to the motors varies in a random manner along the circuit. In spite of the disorder, many of the qualitative features of a homogeneous circuit persist, e.g., long-range motor-motor interactions mediated by circuit voltage and electrical power flows result in coexistence of the spatially extended and propagating normal and stalled phases. We also observed a new phenomenon absent in the case without inhomogeneity or disorder. Specifically, the transition front between the normal and stalled phases becomes somewhat random, even when the front is moving very slowly or is even stationary. Motors within the blurred domain appear in a normal or stalled state depending on the local configuration of the disorder. We quantify the effects of the disorder and discuss the statistics of distribution dynamics, e.g., the front position and width, total active and reactive consumption of the feeder, and maximum clearing time.

  19. Fault-induced delayed voltage recovery in a long inhomogeneous power-distribution feeder.

    PubMed

    Stolbova, Irina; Backhaus, Scott; Chertkov, Michael

    2015-02-01

    We analyze the dynamics of a distribution circuit loaded with many induction motors and subjected to sudden changes in voltage at the beginning of the circuit. As opposed to earlier work by Duclut et al. [Phys. Rev. E 87, 062802 (2013)], the motors are disordered, i.e., the mechanical torque applied to the motors varies in a random manner along the circuit. In spite of the disorder, many of the qualitative features of a homogeneous circuit persist, e.g., long-range motor-motor interactions mediated by circuit voltage and electrical power flows result in coexistence of the spatially extended and propagating normal and stalled phases. We also observed a new phenomenon absent in the case without inhomogeneity or disorder. Specifically, the transition front between the normal and stalled phases becomes somewhat random, even when the front is moving very slowly or is even stationary. Motors within the blurred domain appear in a normal or stalled state depending on the local configuration of the disorder. We quantify the effects of the disorder and discuss the statistics of distribution dynamics, e.g., the front position and width, total active and reactive consumption of the feeder, and maximum clearing time. PMID:25768557

  20. Characterization of time-varying macroscopic electro-chemo-mechanical behavior of SOFC subjected to Ni-sintering in cermet microstructures

    NASA Astrophysics Data System (ADS)

    Muramatsu, M.; Terada, K.; Kawada, T.; Yashiro, K.; Takahashi, K.; Takase, S.

    2015-10-01

    In order to perform stress analyses of a solid oxide fuel cell (SOFC) under operation, we propose a characterization method of its time-varying macroscopic electro-chemo-mechanical behavior of electrodes by considering the time-varying geometries of anode microstructures due to Ni-sintering. The phase-field method is employed to simulate the micro-scale morphology change with time, from which the time-variation of the amount of triple-phase boundaries is directly predicted. Then, to evaluate the time-variation of the macroscopic oxygen ionic and electronic conductivities and the inelastic properties of the anode electrode, numerical material tests based on the homogenization method are conducted for each state of sintered microstructures. In these homogenization analyses, we also have to consider the dependencies of the properties of constituent materials on the temperature and/or the oxygen potential that is supposed to change within an operation period. To predict the oxygen potential distribution in an overall SOFC structure under long-period operation, which determines reduction-induced expansive/contractive deformation of oxide materials, an unsteady problem of macroscopic oxygen ionic and electronic conductions is solved. Using the calculated stress-free strains and the homogenized mechanical properties, both of which depend on the operational environment, we carry out the macroscopic stress analysis of the SOFC.

  1. Applications of the Time-Varying Multi-Hazard Index to Armed Conflicts and GDP Growth Rate

    NASA Astrophysics Data System (ADS)

    Isanuk, M.; Skorik, A.; Lerner-Lam, A.

    2004-12-01

    The time-varying Multi-Hazard Index has many potential applications for comparisons against quantitative measures of sustainable development. We have compared the time-varying severity of multiple natural hazards against time-varying socio-economic data for selected countries. Our analysis compares Gross Domestic Product (GDP) growth and armed conflict occurrence against multiple hazard severity as measured by an empirical time-varying multiple hazard index. The purpose of these analyses is to establish and characterize correlations between the Multi-Hazard Index and trends in GDP and conflicts over the past 25 years. To analyze the relationship between natural hazards and armed conflicts, the Multi-Hazard Index was correlated against the number of conflicts at each intensity level for individual countries. A preliminary analysis was performed studying the apparent relationship as well as the possible existence of time lags. In a similar although more quantitative analysis, the GDP data was correlated against the Multi-Hazard Index for a particular country at different time lags. Analysis involving the conflict datasets yielded varying results from country to country. Colombia shows the strongest correlation, with all positive values of the Multi-Hazard Index followed by an escalation in conflict intensity. The results for other countries are more difficult to interpret as certain years show increases in the number of conflicts at one intensity level and a decrease for other intensity levels. Some issues that need to be addressed include the coding of the intensity for the conflict data, the dating for both conflicts and hazards, and the use of national boundaries as geographic extents. The degree of correlation between GDP growth and the Multi-Hazard Index varies from country to country as well. Our calculations for Honduras show an extremely high correlation, for example, implying a strong economic sensitivity to natural hazards, whereas for China no significant

  2. Full-field tracking and measuring of particle motion in capillary vessels by using time-varying laser speckle

    NASA Astrophysics Data System (ADS)

    Zhang, Luying; Wang, Bo; Wang, Yi

    2016-03-01

    We propose a random perturbation model to describe the variation of laser speckle patterns caused by moving particles in capillary vessels. When passing through probing volume, moving particles encode random perturbations into observed laser speckle patterns. We extract the perturbation envelopes of time-varying laser speckles for tracking the motion of single particle. And, the full-field transverse velocities of flowing particles are obtained by using cross-correlation between the perturbation envelopes. The proposed method is experimentally verified by the use of polymer-microsphere suspension in a glass capillary.

  3. A review of methodological factors in performance assessments of time-varying aircraft noise effects. [with annotated bibliography

    NASA Technical Reports Server (NTRS)

    Coates, G. D.; Alluisi, E. A.; Adkins, C. J., Jr.

    1977-01-01

    Literature on the effects of general noise on human performance is reviewed in an attempt to identify (1) those characteristics of noise that have been found to affect human performance; (2) those characteristics of performance most likely to be affected by the presence of noise, and (3) those characteristics of the performance situation typically associated with noise effects. Based on the characteristics identified, a theoretical framework is proposed that will permit predictions of possible effects of time-varying aircraft-type noise on complex human performance. An annotated bibliography of 50 articles is included.

  4. Time-Varying Characteristics Analysis and Fuzzy Controller Systematic Design Method for Pressurized Water Reactor Power Control

    SciTech Connect

    Liu Shengzhi; Zhang Naiyao; Cui Zhenhua

    2004-11-15

    In this paper a systematic design method of fuzzy control systems is applied to the pressurized water reactor's (PWR) power control. The paper includes three parts. In the first part, a simplified time-varying linear model of the PWR power system is constructed, and its inner structure and time-varying characteristics are analyzed. That provides a solid basis for study and design of the nuclear reactor power control system. In the second part, a systematic design method of fuzzy control systems is introduced and applied to control the nuclear reactor power process. The design procedures and parameters are given in detail. This systematic design method has some notable advantages. The control of a global fuzzy model can be decomposed into controlling a set of linear submodels. Each submodel controller can be independently designed by using a linear quadratic regulator approach. This systematic design method gives a sufficient and necessary condition to guarantee the stability of fuzzy control systems; thus, better control performance can be obtained due to the accurate control gains. In the third part, the control performance of the nuclear reactor fuzzy control system is examined by simulation experiments, including nuclear reactor power shutdown, start-up, and adjustment operations. The satisfactory experiment results have shown that the systematic design method for fuzzy control systems is effective and feasible.

  5. Robust sensor fault detection and isolation of gas turbine engines subjected to time-varying parameter uncertainties

    NASA Astrophysics Data System (ADS)

    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.

  6. Moving Kriging shape function modeling of vector TARMA models for modal identification of linear time-varying structural systems

    NASA Astrophysics Data System (ADS)

    Yang, Wu; Liu, Li; Zhou, Si-Da; Ma, Zhi-Sai

    2015-10-01

    This work proposes a Moving Kriging (MK) shape function modeling method for modal identification of linear time-varying (LTV) structural systems based on vector time-dependent autoregressive moving average (VTARMA) models. It aims to avoid the functional subspaces selection of the conventional functional series VTARMA (FS-VTARMA) models. Instead of the common basis functions, it constructs the time-varying coefficients on the time nodes with the MK shape functions in a compact support domain. The merit of the MK shape function is to determine its shape parameters upon vector random vibration signals adaptively. Model identification is effectively dealt with through an optimization scheme that decomposes the identification problem into two subproblems: estimating model parameters via two-stage least squares (2SLS) method and estimating shape function parameters via a discrete-continuous-variable hybrid optimization. In addition, the model order selection is achieved by the optimization scheme. This method has been validated by a Monte Carlo study of simulation case and further by an experimental test case, and the performance and potential advantages are illustrated.

  7. The uncertain role of diversity dependence in species diversification and the need to incorporate time-varying carrying capacities.

    PubMed

    Marshall, Charles R; Quental, Tiago B

    2016-04-01

    There is no agreement among palaeobiologists or biologists as to whether, or to what extent, there are limits on diversification and species numbers. Here, we posit that part of the disagreement stems from: (i) the lack of explicit criteria for defining the relevant species pools, which may be defined phylogenetically, ecologically or geographically; (ii) assumptions that must be made when extrapolating from population-level logistic growth to macro-evolutionary diversification; and (iii) too much emphasis being placed on fixed carrying capacities, rather than taking into account the opportunities for increased species richness on evolutionary timescales, for example, owing to increased biologically available energy, increased habitat complexity and the ability of many clades to better extract resources from the environment, or to broaden their resource base. Thus, we argue that a more effective way of assessing the evidence for and against the ideas of bound versus unbound diversification is through appropriate definition of the relevant species pools, and through explicit modelling of diversity-dependent diversification with time-varying carrying capacities. Here, we show that time-varying carrying capacities, either increases or decreases, can be accommodated through changing intrinsic diversification rates (diversity-independent effects), or changing the effects of crowding (diversity-dependent effects). PMID:26977059

  8. Estimating the Time-Varying Joint Effects of Obesity and Smoking on All-Cause Mortality Using Marginal Structural Models.

    PubMed

    Banack, Hailey R; Kaufman, Jay S

    2016-01-15

    Obesity and smoking are independently associated with a higher mortality risk, but previous studies have reported conflicting results about the relationship between these 2 time-varying exposures. Using prospective longitudinal data (1987-2007) from the Atherosclerosis Risk in Communities Study, our objective in the present study was to estimate the joint effects of obesity and smoking on all-cause mortality and investigate whether there were additive or multiplicative interactions. We fit a joint marginal structural Poisson model to account for time-varying confounding affected by prior exposure to obesity and smoking. The incidence rate ratios from the joint model were 2.00 (95% confidence interval (CI): 1.79, 2.24) for the effect of smoking on mortality among nonobese persons, 1.31 (95% CI: 1.13, 1.51) for the effect of obesity on mortality among nonsmokers, and 1.97 (95% CI: 1.73, 2.22) for the joint effect of smoking and obesity on mortality. The negative product term from the exponential model revealed a submultiplicative interaction between obesity and smoking (β = -0.28, 95% CI: -0.45, -0.11; P < 0.001). The relative excess risk of interaction was -0.34 (95% CI: -0.60, -0.07), indicating the presence of subadditive interaction. These results provide important information for epidemiologists, clinicians, and public health practitioners about the harmful impact of smoking and obesity. PMID:26656480

  9. Flocking for multi-agent systems with unknown nonlinear time-varying uncertainties under a fixed undirected graph

    NASA Astrophysics Data System (ADS)

    Luo, Jie; Cao, Chengyu

    2015-05-01

    This paper presents a flocking algorithm for networked multi-agent systems with unknown, nonlinear, time-varying uncertainties by integrating cooperative control and ? adaptive control methods. An ideal multi-agent system without uncertainties is introduced first. The cooperative control law, based on an artificial potential function, is designed to make the ideal multi-agent system achieve flocking under a fixed and connected undirected graph. Information of ideal states, instead of real states, is exchanged among agents through a communication network. The presence of uncertainties will lead to the degeneration of the performance or even destabilize the entire multi-agent system. The ? adaptive control law is therefore introduced to handle unknown, nonlinear, time-varying uncertainties. By integrating the cooperative control law with the adaptive control law, the real multi-agent system stays close to the ideal multi-agent system which achieves flocking asymptotically under a connected graph. Simulation results of two-dimensional flocking with uncertainties are provided to demonstrate the presented flocking algorithm.

  10. Difference in differences for stayers with a time-varying qualification: health expenditure elasticity of the elderly.

    PubMed

    Lee, Myoung-Jae; Kim, Young-Sook

    2014-09-01

    In difference in differences, a treatment is applied only to a qualified group at some time point. The qualification may be time-constant as in gender, or time-varying as in residential location. When the qualification is time-varying, there appear four groups: the newly qualified (in-movers), the already qualified (in-stayers), the newly disqualified (out-movers), and the already disqualified (out-stayers). A change in qualification may affect the response variable of interest even when the treatment effect is zero, which is an 'untreated moving effect'. Also, when the treatment effect is not zero, it may be different across the four groups. The conventional difference in differences fails to remove untreated moving effects and ignores the possible treatment effect heterogeneity across the groups. This paper shows how to account for untreated moving effects and proposes 'the effect on in-stayers' as the main effect of interest. Our proposal can be implemented with least squares estimator for panel models or with nonparametric methods. An empirical analysis is provided using Korean data for the effects of the basic elder pension on health-care expenditure. PMID:24733617

  11. Steady-state response of a geared rotor system with slant cracked shaft and time-varying mesh stiffness

    NASA Astrophysics Data System (ADS)

    Han, Qinkai; Zhao, Jingshan; Lu, Wenxiu; Peng, Zhike; Chu, Fulei

    2014-04-01

    The dynamic behavior of geared rotor system with defects is helpful for the failure diagnosis and state detecting of the system. Extensive efforts have been devoted to study the dynamic behaviors of geared systems with tooth root cracks. When surface cracks (especially for slant cracks) appear on the transmission shaft, the dynamic characteristics of the system have not gained sufficient attentions. Due to the parametric excitations induced by slant crack breathing and time-varying mesh stiffness, the steady-state response of the cracked geared rotor system differs distinctly from that of the uncracked system. Thus, utilizing the direct spectral method (DSM), the forced response spectra of a geared rotor system with slant cracked shaft and time-varying mesh stiffness under transmission error, unbalance force and torsional excitations are, respectively, obtained and discussed in detail. The effects of crack types (straight or slant crack) and crack depth on the forced response spectra of the system without and with torsional excitation are considered in the analysis. In addition, how the frequency response characteristics change after considering the crack is also investigated. It is shown that the torsional excitations have significant influence on the forced response spectra of slant cracked system. Sub-critical resonances are also found in the frequency response curves. The results could be used for shaft crack detection in geared rotor system.

  12. A Signal-Processing-Based Approach to Time-Varying Graph Analysis for Dynamic Brain Network Identification

    PubMed Central

    Mutlu, Ali Yener; Bernat, Edward; Aviyente, Selin

    2012-01-01

    In recent years, there has been a growing need to analyze the functional connectivity of the human brain. Previous studies have focused on extracting static or time-independent functional networks to describe the long-term behavior of brain activity. However, a static network is generally not sufficient to represent the long term communication patterns of the brain and is considered as an unreliable snapshot of functional connectivity. In this paper, we propose a dynamic network summarization approach to describe the time-varying evolution of connectivity patterns in functional brain activity. The proposed approach is based on first identifying key event intervals by quantifying the change in the connectivity patterns across time and then summarizing the activity in each event interval by extracting the most informative network using principal component decomposition. The proposed method is evaluated for characterizing time-varying network dynamics from event-related potential (ERP) data indexing the error-related negativity (ERN) component related to cognitive control. The statistically significant connectivity patterns for each interval are presented to illustrate the dynamic nature of functional connectivity. PMID:22934122

  13. Using time-varying global sensitivity analysis to understand the importance of different uncertainty sources in hydrological modelling

    NASA Astrophysics Data System (ADS)

    Pianosi, Francesca; Wagener, Thorsten

    2016-04-01

    Simulations from environmental models are affected by potentially large uncertainties stemming from various sources, including model parameters and observational uncertainty in the input/output data. Understanding the relative importance of such sources of uncertainty is essential to support model calibration, validation and diagnostic evaluation, and to prioritize efforts for uncertainty reduction. Global Sensitivity Analysis (GSA) provides the theoretical framework and the numerical tools to gain this understanding. However, in traditional applications of GSA, model outputs are an aggregation of the full set of simulated variables. This aggregation of propagated uncertainties prior to GSA may lead to a significant loss of information and may cover up local behaviour that could be of great interest. In this work, we propose a time-varying version of a recently developed density-based GSA method, called PAWN, as a viable option to reduce this loss of information. We apply our approach to a medium-complexity hydrological model in order to address two questions: [1] Can we distinguish between the relative importance of parameter uncertainty versus data uncertainty in time? [2] Do these influences change in catchments with different characteristics? The results present the first quantitative investigation on the relative importance of parameter and data uncertainty across time. They also provide a demonstration of the value of time-varying GSA to investigate the propagation of uncertainty through numerical models and therefore guide additional data collection needs and model calibration/assessment.

  14. Time delay occultation data of the Helios spacecraft for probing the electron density distribution in the solar corona

    NASA Technical Reports Server (NTRS)

    Edenhofer, P.; Lueneburg, E.; Esposito, P. B.; Martin, W. L.; Zygielbaum, A. I.; Hansen, R. T.; Hansen, S. F.

    1978-01-01

    S-band time delay measurements were collected from the spacecraft Helios A and B during three solar occultations in 1975/76 within heliocentric distances of about 3 and 215 earth radius in terms of range, Doppler frequency shift, and electron content. Characteristic features of measurement and data processing are described. Typical data sets are discussed to probe the electron density distribution near the sun (west and east limb as well) including the outer and extended corona. Steady-state and dynamical aspects of the solar corona are presented and compared with earth-bound-K-coronagraph measurements. Using a weighted least squares estimation, parameters of an average coronal electron density profile are derived in a preliminary analysis to yield electron densities at r = 3, 65, 215 earth radius. Transient phenomena are discussed and a velocity of propagation v is nearly equal to 900 km/s is determined for plasma ejecta from a solar flare observed during an extraordinary set of Helios B electron content measurements.

  15. Visualizing time: how linguistic metaphors are incorporated into displaying instruments in the process of interpreting time-varying signals

    NASA Astrophysics Data System (ADS)

    Garcia-Belmonte, Germà

    2016-04-01

    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

  16. Motivating Action and Maintaining Change: The Time-Varying Role of Homework Following a Brief Couples' Intervention.

    PubMed

    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. PMID:26456167

  17. SER performance of enhanced spatial multiplexing codes with ZF/MRC receiver in time-varying Rayleigh fading channels.

    PubMed

    Lee, In-Ho

    2014-01-01

    We propose enhanced spatial multiplexing codes (E-SMCs) to enable various encoding rates. The symbol error rate (SER) performance of the E-SMC is investigated when zero-forcing (ZF) and maximal-ratio combining (MRC) techniques are used at a receiver. The proposed E-SMC allows a transmitted symbol to be repeated over time to achieve further diversity gain at the cost of the encoding rate. With the spatial correlation between transmit antennas, SER equations for M-ary QAM and PSK constellations are derived by using a moment generating function (MGF) approximation of a signal-to-noise ratio (SNR), based on the assumption of independent zero-forced SNRs. Analytic and simulated results are compared for time-varying and spatially correlated Rayleigh fading channels that are modelled as first-order Markovian channels. Furthermore, we can find an optimal block length for the E-SMC that meets a required SER. PMID:25114969

  18. SER Performance of Enhanced Spatial Multiplexing Codes with ZF/MRC Receiver in Time-Varying Rayleigh Fading Channels

    PubMed Central

    Lee, In-Ho

    2014-01-01

    We propose enhanced spatial multiplexing codes (E-SMCs) to enable various encoding rates. The symbol error rate (SER) performance of the E-SMC is investigated when zero-forcing (ZF) and maximal-ratio combining (MRC) techniques are used at a receiver. The proposed E-SMC allows a transmitted symbol to be repeated over time to achieve further diversity gain at the cost of the encoding rate. With the spatial correlation between transmit antennas, SER equations for M-ary QAM and PSK constellations are derived by using a moment generating function (MGF) approximation of a signal-to-noise ratio (SNR), based on the assumption of independent zero-forced SNRs. Analytic and simulated results are compared for time-varying and spatially correlated Rayleigh fading channels that are modelled as first-order Markovian channels. Furthermore, we can find an optimal block length for the E-SMC that meets a required SER. PMID:25114969

  19. Examining the use of a time-varying loudness algorithm for quantifying characteristics of nonlinearly propagated noise (L).

    PubMed

    Swift, S Hales; Gee, Kent L

    2011-05-01

    A previous letter by Gee et al. [J. Acoust. Soc. Am. 121, EL1-EL7 (2007)] revealed likely shortcomings in using common, stationary (long-term) spectrum-based measures to quantify the perception of nonlinearly propagated noise. Here, the Glasberg and Moore [J. Audio Eng. Soc. 50, 331-342 (2002)] algorithm for time-varying loudness is investigated. Their short-term loudness, when applied to a shock-containing broadband signal and a phase-randomized signal with equivalent long-term spectrum, does not show a significant difference in loudness between the signals. Further analysis and discussion focus on the possible utility of the instantaneous loudness and the need for additional investigation in this area. PMID:21568378

  20. Disrupted bandcount doubling in an AC-DC boost PFC circuit modeled by a time varying map

    NASA Astrophysics Data System (ADS)

    Avrutin, Viktor; Zhusubaliyev, Zhanybai T.; El Aroudi, Abdelali; Fournier-Prunaret, Danièle; Garcia, Germain; Mosekilde, Erik

    2016-02-01

    Power factor correction converters are used in many applications as AC-DC power supplies aiming at maintaining a near unity power factor. Systems of this type are known to exhibit nonlinear phenomena such as sub-harmonic oscillations and chaotic regimes that cannot be described by traditional 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 a sequence of bifurcation similar to a bandcount doubling cascade on the low frequency. However, the observed scenario appears in some sense incomplete, with some gaps in the bifurcation diagram, whose appearance to our knowledge has never been reported before. We show that these gaps are caused by high frequency oscillations.

  1. Motions of charged particles in the Magnetosphere under the influence of a time-varying large scale convection electric field

    NASA Technical Reports Server (NTRS)

    Smith, P. H.; Bewtra, N. K.; Hoffman, R. A.

    1979-01-01

    The motions of charged particles under the influence of the geomagnetic and electric fields were quite complex in the region of the inner magnetosphere. The Volland-Stern type large scale convection electric field was used successfully to predict both the plasmapause location and particle enhancements determined from Explorer 45 measurements. A time dependence in this electric field was introduced based on the variation in Kp for actual magnetic storm conditions. The particle trajectories were computed as they change in this time-varying electric field. Several storm fronts of particles of different magnetic moments were allowed to be injected into the inner magnetosphere from L = 10 in the equatorial plane. The motions of these fronts are presented in a movie format.

  2. Turbulent Inflow Precursor Method with Time-Varying Direction for Large-Eddy Simulations and Applications to Wind Farms

    NASA Astrophysics Data System (ADS)

    Munters, Wim; Meneveau, Charles; Meyers, Johan

    2016-05-01

    A major challenge in turbulence-resolving flow simulations is the generation of unsteady and coherent turbulent inflow conditions. Precursor methods have proven to be reliable inflow generators but are limited in applicability and flexibility especially when attempting to couple boundary-layer dynamics with large-scale temporal variations in the direction of the inflow. Here, we propose a methodology that is capable of providing fully developed turbulent inflow for time-varying mean-flow directions. The method is a generalization of a concurrent precursor inflow technique, in which a fully developed boundary-layer simulation that uses periodic boundary conditions is dynamically rotated with the large-scale wind direction that drives the simulation in the domain of interest. The proposed inflow method is applied to large-eddy simulations of boundary-layer flow through the Horns Rev wind farm when subjected to a sinusoidal variation in wind direction at the hourly time scale.

  3. A new angular resampling algorithm for the bearing fault diagnosis under the time-varying rotational speed

    NASA Astrophysics Data System (ADS)

    Wang, Tianyang; Cheng, Weidong; Li, Jianvong; Chu, Fulei

    2015-07-01

    Order tracking is one of the most effective algorithms to eliminate the effect of time-varying rotational speed on the rotary machines. However, this algorithm is not suitable for the faulty rolling bearing unless the peak time of the fault-induced impulse is set as zero which cannot be met in the real engineering. The traditional resampling process will cause uneven intervals between the adjacent impulse peaks in the angular domain and then affect the envelope analysis-based diagnosis result. To solve this problem, a new resampling algorithm with three parts is proposed: (a) linearly fitting the instantaneous rotational speed measured by the tachometer, (b) resampling the vibration signal from the time domain to the angular domain using the traditional method, (c) calculating the envelope deformation amount and then compensating the resampled result. The effectiveness of the proposed method has been validated by both the simulated and experimental bearing vibration signals.

  4. Bayesian inference of interaction properties of noisy dynamical systems with time-varying coupling: capabilities and limitations

    NASA Astrophysics Data System (ADS)

    Wilting, Jens; Lehnertz, Klaus

    2015-08-01

    We investigate a recently published analysis framework based on Bayesian inference for the time-resolved characterization of interaction properties of noisy, coupled dynamical systems. It promises wide applicability and a better time resolution than well-established methods. At the example of representative model systems, we show that the analysis framework has the same weaknesses as previous methods, particularly when investigating interacting, structurally different non-linear oscillators. We also inspect the tracking of time-varying interaction properties and propose a further modification of the algorithm, which improves the reliability of obtained results. We exemplarily investigate the suitability of this algorithm to infer strength and direction of interactions between various regions of the human brain during an epileptic seizure. Within the limitations of the applicability of this analysis tool, we show that the modified algorithm indeed allows a better time resolution through Bayesian inference when compared to previous methods based on least square fits.

  5. Impaired timing adjustments in response to time-varying auditory perturbation during connected speech production in persons who stutter.

    PubMed

    Cai, Shanqing; Beal, Deryk S; Ghosh, Satrajit S; Guenther, Frank H; Perkell, Joseph S

    2014-02-01

    Auditory feedback (AF), the speech signal received by a speaker's own auditory system, contributes to the online control of speech movements. Recent studies based on AF perturbation provided evidence for abnormalities in the integration of auditory error with ongoing articulation and phonation in persons who stutter (PWS), but stopped short of examining connected speech. This is a crucial limitation considering the importance of sequencing and timing in stuttering. In the current study, we imposed time-varying perturbations on AF while PWS and fluent participants uttered a multisyllabic sentence. Two distinct types of perturbations were used to separately probe the control of the spatial and temporal parameters of articulation. While PWS exhibited only subtle anomalies in the AF-based spatial control, their AF-based fine-tuning of articulatory timing was substantially weaker than normal, especially in early parts of the responses, indicating slowness in the auditory-motor integration for temporal control. PMID:24486601

  6. Electrohydrodynamics of Charge Separation in Droplet-Based Ion Sources with Time-Varying Electrical and Mechanical Actuation

    PubMed Central

    Forbes, Thomas P.; Degertekin, F. Levent; Fedorov, Andrei G.

    2010-01-01

    Charge transport and separation in mechanically-driven, droplet-based ion sources are investigated using computational analysis and supporting experiments. A first-principles model of electrohydrodynamics (EHD) and charge migration is formulated and implemented using FLUENT CFD software for jet/droplet formation. For validation, classical experiments of electrospraying from a thin capillary are simulated, specifically, the transient EHD cone-jet formation of a fluid with finite electrical conductivity, and the Taylor cone formation in a perfectly electrically-conducting fluid. The model is also used to investigate the microscopic physics of droplet charging in mechanically-driven droplet-based ion sources, such as AMUSE (Array of Micromachined UltraSonic Electrospray). Here, AMUSE is subject to DC and AC electric fields of varying amplitude and phase, with respect to a time-varying mechanical force driving the droplet formation. For the DC-charging case, a linear relationship is demonstrated between the charge carried by each droplet and an applied electric field magnitude, in agreement with previously reported experiments. For the AC-charging case, a judiciously-chosen phase-shift in the time-varying mechanical (driving ejection) and electrical (driving charge transport) signals allows for a significantly increased amount of charge, of desired polarity, to be pumped into a droplet upon ejection. Complementary experimental measurements of electrospray electrical current and charge-per-droplet, produced by the AMUSE ion source, are performed and support theoretical predictions for both DC and AC-charging cases. The theoretical model and simulation tools provide a versatile and general analytical framework for fundamental investigations of coupled electrohydrodynamics and charge transport. The model also allows for the exploration of different configurations and operating modes to optimize charge separation in atmospheric pressure electrohydrodynamic ion sources

  7. TIME-VARYING FLAME IONIZATION SENSING APPLIED TO NATURAL GAS AND PROPANE BLENDS IN A PRESSURIZED LEAN PREMIXED (LPM) COMBUSTOR

    SciTech Connect

    D. L. Straub; B. T. Chorpening; E. D. Huckaby; J. D. Thornton; W. L. Fincham

    2008-06-13

    In-situ monitoring of combustion phenomena is a critical need for optimal operation and control of advanced gas turbine combustion systems. The concept described in this paper is based on naturally occurring flame ionization processes that accompany the combustion of hydrocarbon fuels. Previous work has shown that flame ionization techniques may be applied to detect flashback, lean blowout, and some aspects of thermo-acoustic combustion instabilities. Previous work has focused on application of DC electric fields. By application of time-varying electric fields, significant improvements to sensor capabilities have been observed. These data have been collected in a lean premixed combustion test rig operating at 0.51-0.76 MPa (5-7.5 atm) with air preheated to 588 K (600°F). Five percent of the total fuel flow is injected through the centerbody tip as a diffusion pilot. The fuel composition is varied independently by blending approximately 5% (volume) propane with the pipeline natural gas. The reference velocity through the premixing annulus is kept constant for all conditions at a nominal value of 70 m/s. The fuel-air equivalence ratio is varied independently from 0.46 – 0.58. Relative to the DC field version, the time-varying combustion control and diagnostic sensor (TV-CCADS) shows a significant improvement in the correlation between the measured flame ionization current and local fuel-air equivalence ratio. In testing with different fuel compositions, the triangle wave data show the most distinct change in flame ionization current in response to an increase in propane content. Continued development of this sensor technology will improve the capability to control advanced gas turbine combustion systems, and help address issues associated with variations in fuel supplies.

  8. Modeling Nonlinear Time-Dependent Treatment Effects: An Application of the Generalized Time-Varying Effect Model (TVEM)

    PubMed Central

    Shiyko, Mariya P.; Burkhalter, Jack; Li, Runze; Park, Bernard J.

    2014-01-01

    Objective The goal of this paper is to introduce to social and behavioral scientists the generalized time-varying effect model (TVEM), a semi-parametric approach for investigating time-varying effects of a treatment. The method is best suited for data collected intensively over time, e.g., experience sampling or ecological momentary assessment, and addresses questions pertaining to effects of treatment changing dynamically with time. Thus, of interest is the description of timing, magnitude, and (non-linear) pattern of the effect. Method Our presentation focuses on practical aspects of the model. A step-by step demonstration is presented in the context of an empirical study designed to evaluate effects of surgical treatment on quality of life among early stage lung cancer patients during post-hospitalization recovery (N = 59, 61% female, Mean age = 66.1). Frequency and level of distress associated with physical symptoms were assessed twice daily over a two-week period, providing a total of 1,544 momentary assessments. Results Traditional analyses (ANCOVA, repeated-measures ANCOVA, and multilevel modeling) yielded findings of no group differences. In contrast, generalized TVEM identified a pattern of the effect that varied in time and magnitude. Group differences manifested after day four. Conclusions Generalized TVEM is a flexible statistical approach that offers insight into the complexity of treatment effects and allows modeling of non-normal outcomes. The practical demonstration, shared syntax, and availability of a free set of macros aim to encourage researchers to apply TVEM to complex data and stimulate important scientific discoveries. PMID:24364799

  9. The Immediate Affect of Information in a Delayed Choice on a Distant Distribution as Seen in Different Inertial Reference Frames: The ``Effect'' May Occur Before the ``Cause''

    NASA Astrophysics Data System (ADS)

    Snyder, Douglas

    2015-03-01

    An experiment is described in the laboratory reference frame that relies on delayed choices for idler photons that immediately affects the distribution of signal photons with which the idler photons are initially entangled. The delayed choices on the idler photons concern whether to maintain or instead eliminate the entanglement between the paired idler and signal photons before any measurements are made. Eliminating the entanglement is done through eliminating the which-way information carried by the idler photon. If the entanglement is maintained, the result is which-way information in the distribution of the signal photons. If the entanglement is instead eliminated, the result is the elimination of which-way information and the presence of interference in the distribution of the signal photons. In other inertial reference frames, the change in state in the signal photon may occur before the delayed choice on the paired idler photon is made. A Minkowski diagram depicts the situation for the laboratory reference frame and another inertial reference frame where the change in state in the signal photon occurs before the delayed choice on the paired idler photon.

  10. Gravity currents produced by constant and time varying inflow in a circular cross-section channel: Experiments and theory

    NASA Astrophysics Data System (ADS)

    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 < β < 2) where it is open to the atmosphere. This fluid is displaced by the intruding current and outflows either at the same or at the opposite end-side of the 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

  11. State-Space Analysis of Time-Varying Higher-Order Spike Correlation for Multiple Neural Spike Train Data

    PubMed Central

    Shimazaki, Hideaki; Amari, Shun-ichi; Brown, Emery N.; Grün, Sonja

    2012-01-01

    Precise spike coordination between the spiking activities of multiple neurons is suggested as an indication of coordinated network activity in active cell assemblies. Spike correlation analysis aims to identify such cooperative network activity by detecting excess spike synchrony in simultaneously recorded multiple neural spike sequences. Cooperative activity is expected to organize dynamically during behavior and cognition; therefore currently available analysis techniques must be extended to enable the estimation of multiple time-varying spike interactions between neurons simultaneously. In particular, new methods must take advantage of the simultaneous observations of multiple neurons by addressing their higher-order dependencies, which cannot be revealed by pairwise analyses alone. In this paper, we develop a method for estimating time-varying spike interactions by means of a state-space analysis. Discretized parallel spike sequences are modeled as multi-variate binary processes using a log-linear model that provides a well-defined measure of higher-order spike correlation in an information geometry framework. We construct a recursive Bayesian filter/smoother for the extraction of spike interaction parameters. This method can simultaneously estimate the dynamic pairwise spike interactions of multiple single neurons, thereby extending the Ising/spin-glass model analysis of multiple neural spike train data to a nonstationary analysis. Furthermore, the method can estimate dynamic higher-order spike interactions. To validate the inclusion of the higher-order terms in the model, we construct an approximation method to assess the goodness-of-fit to spike data. In addition, we formulate a test method for the presence of higher-order spike correlation even in nonstationary spike data, e.g., data from awake behaving animals. The utility of the proposed methods is tested using simulated spike data with known underlying correlation dynamics. Finally, we apply the methods

  12. Cyclo-stationary linear parameter time-varying subspace realization method applied for identification of horizontal-axis wind turbines

    NASA Astrophysics Data System (ADS)

    Velazquez, Antonio; Swartz, R. Andrew

    2013-04-01

    Wind energy is becoming increasingly important worldwide as an alternative renewable energy source. Economical, maintenance and operation are critical issues for large slender dynamic structures, especially for remote offshore wind farms. Health monitoring systems are very promising instruments to assure reliability and good performance of the structure. These sensing and control technologies are typically informed by models based on mechanics or data-driven identification techniques in the time and/or frequency domain. Frequency response functions are popular but are difficult to realize autonomously for structures of higher order and having overlapping frequency content. Instead, time-domain techniques have shown powerful advantages from a practical point of view (e.g. embedded algorithms in wireless-sensor networks), being more suitable to differentiate closely-related modes. Customarily, time-varying effects are often neglected or dismissed to simplify the analysis, but such is not the case for wind loaded structures with spinning multibodies. A more complex scenario is constituted when dealing with both periodic mechanisms responsible for the vibration shaft of the rotor-blade system, and the wind tower substructure interaction. Transformations of the cyclic effects on the vibration data can be applied to isolate inertia quantities different from rotating-generated forces that are typically non-stationary in nature. After applying these transformations, structural identification can be carried out by stationary techniques via data-correlated Eigensystem realizations. In this paper an exploration of a periodic stationary or cyclo-stationary subspace identification technique is presented here by means of a modified Eigensystem Realization Algorithm (ERA) via Stochastic Subspace Identification (SSI) and Linear Parameter Time-Varying (LPTV) techniques. Structural response is assumed under stationary ambient excitation produced by a Gaussian (white) noise assembled

  13. The Prospective, Observational, Multicenter, Major Trauma Transfusion (PROMMTT) Study: Comparative Effectiveness of a Time-varying Treatment with Competing Risks

    PubMed Central

    Holcomb, John B.; del Junco, Deborah J.; Fox, Erin E.; Wade, Charles E.; Cohen, Mitchell J.; Schreiber, Martin A.; Alarcon, Louis H.; Bai, Yu; Brasel, Karen J.; Bulger, Eileen M.; Cotton, Bryan A.; Matijevic, Nena; Muskat, Peter; Myers, John G.; Phelan, Herb A.; White, Christopher E.; Zhang, Jiajie; Rahbar, Mohammad H.

    2013-01-01

    Context Hemorrhagic shock is the leading potentially preventable cause of death after injury. Transfusion of early and increased ratios of plasma and platelets to red blood cells (RBCs) has been associated with decreased mortality; however conflicting reports and the time-varying nature of transfusions and hemorrhagic death raise concern for the validity of the clinical conclusions drawn from the retrospective data. Objective To relate in-hospital mortality to: 1) early transfusion of plasma and/or platelets and 2) time-varying plasma:RBC and platelet:RBC ratios. Design Prospective cohort study documenting the timing of transfusions during active resuscitation and patient outcomes. Data were analyzed using time-dependent proportional hazards models. Setting Ten US Level 1 trauma centers. Patients Adult trauma patients surviving for 30 minutes after admission, transfused at least 1 unit RBC within 6 hours of admission (n=1245, the original study group) and at least 3 total units (of RBC, plasma or platelets) within 24 hours (n=905, the analysis group). Main outcome measure In-hospital mortality Results Plasma:RBC and platelet:RBC ratios were not constant over the first 24 hours (p<.001 for both). In a multivariable time-dependent Cox model, increased ratios of plasma:RBC (adjusted hazard ratio, HR=0.31, 95% CI=0.16–0.58) and platelets:RBC (adjusted HR=0.55, 95% CI=0.31–0.98) were independently associated with decreased 6-hour mortality, when hemorrhagic death predominated. In the first 6 hours, patients with ratios < 1:2 were 3–4 times more likely to die than patients with ratios ≥1:1. After 24 hours, plasma and platelet ratios were unassociated with mortality, when competing risks from non-hemorrhagic causes prevailed. Conclusions Higher plasma and platelet ratios early in resuscitation were associated with decreased mortality in patients transfused at least three units of blood products during the first 24 hours after admission. Among survivors at 24 hours

  14. State-space analysis of time-varying higher-order spike correlation for multiple neural spike train data.

    PubMed

    Shimazaki, Hideaki; Amari, Shun-Ichi; Brown, Emery N; Grün, Sonja

    2012-01-01

    Precise spike coordination between the spiking activities of multiple neurons is suggested as an indication of coordinated network activity in active cell assemblies. Spike correlation analysis aims to identify such cooperative network activity by detecting excess spike synchrony in simultaneously recorded multiple neural spike sequences. Cooperative activity is expected to organize dynamically during behavior and cognition; therefore currently available analysis techniques must be extended to enable the estimation of multiple time-varying spike interactions between neurons simultaneously. In particular, new methods must take advantage of the simultaneous observations of multiple neurons by addressing their higher-order dependencies, which cannot be revealed by pairwise analyses alone. In this paper, we develop a method for estimating time-varying spike interactions by means of a state-space analysis. Discretized parallel spike sequences are modeled as multi-variate binary processes using a log-linear model that provides a well-defined measure of higher-order spike correlation in an information geometry framework. We construct a recursive Bayesian filter/smoother for the extraction of spike interaction parameters. This method can simultaneously estimate the dynamic pairwise spike interactions of multiple single neurons, thereby extending the Ising/spin-glass model analysis of multiple neural spike train data to a nonstationary analysis. Furthermore, the method can estimate dynamic higher-order spike interactions. To validate the inclusion of the higher-order terms in the model, we construct an approximation method to assess the goodness-of-fit to spike data. In addition, we formulate a test method for the presence of higher-order spike correlation even in nonstationary spike data, e.g., data from awake behaving animals. The utility of the proposed methods is tested using simulated spike data with known underlying correlation dynamics. Finally, we apply the methods

  15. Inhibition of Cancer Cell Growth by Exposure to a Specific Time-Varying Electromagnetic Field Involves T-Type Calcium Channels

    PubMed Central

    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 Ca2+ influx which could be blocked by inhibitors of voltage-gated T-type Ca2+ channels. Blocking Ca2+ 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 Ca2+ 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. PMID:25875081

  16. Evaluating principal surrogate endpoints with time-to-event data accounting for time-varying treatment efficacy

    PubMed Central

    Gabriel, Erin E.; Gilbert, Peter B.

    2014-01-01

    Principal surrogate (PS) endpoints are relatively inexpensive and easy to measure study outcomes that can be used to reliably predict treatment effects on clinical endpoints of interest. Few statistical methods for assessing the validity of potential PSs utilize time-to-event clinical endpoint information and to our knowledge none allow for the characterization of time-varying treatment effects. We introduce the time-dependent and surrogate-dependent treatment efficacy curve, \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}${\\mathrm {TE}}(t|s)$\\end{document}, and a new augmented trial design for assessing the quality of a biomarker as a PS. We propose a novel Weibull model and an estimated maximum likelihood method for estimation of the \\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{upgreek} \\usepackage{mathrsfs} \\setlength{\\oddsidemargin}{-69pt} \\begin{document} }{}${\\mathrm {TE}}(t|s)$\\end{document} curve. We describe the operating characteristics of our methods via simulations. We analyze data from the Diabetes Control and Complications Trial, in which we find evidence of a biomarker with value as a PS. PMID:24337534

  17. Time-varying signal analysis to detect high-altitude periodic breathing in climbers ascending to extreme altitude.

    PubMed

    Garde, A; Giraldo, B F; Jané, R; Latshang, T D; Turk, A J; Hess, T; Bosch, M M; Barthelmes, D; Merz, T M; Hefti, J Pichler; Schoch, O D; Bloch, K E

    2015-08-01

    This work investigates the performance of cardiorespiratory analysis detecting periodic breathing (PB) in chest wall recordings in mountaineers climbing to extreme altitude. The breathing patterns of 34 mountaineers were monitored unobtrusively by inductance plethysmography, ECG and pulse oximetry using a portable recorder during climbs at altitudes between 4497 and 7546 m on Mt. Muztagh Ata. The minute ventilation (VE) and heart rate (HR) signals were studied, to identify visually scored PB, applying time-varying spectral, coherence and entropy analysis. In 411 climbing periods, 30-120 min in duration, high values of mean power (MP(VE)) and slope (MSlope(VE)) of the modulation frequency band of VE, accurately identified PB, with an area under the ROC curve of 88 and 89%, respectively. Prolonged stay at altitude was associated with an increase in PB. During PB episodes, higher peak power of ventilatory (MP(VE)) and cardiac (MP(LF)(HR) ) oscillations and cardiorespiratory coherence (MP(LF)(Coher)), but reduced ventilation entropy (SampEn(VE)), was observed. Therefore, the characterization of cardiorespiratory dynamics by the analysis of VE and HR signals accurately identifies PB and effects of altitude acclimatization, providing promising tools for investigating physiologic effects of environmental exposures and diseases. PMID:25820153

  18. An efficient early warning system for typhoon storm surge based on time-varying advisories by coupled ADCIRC and SWAN

    NASA Astrophysics Data System (ADS)

    Suh, Seung Won; Lee, Hwa Young; Kim, Hyeon Jeong; Fleming, Jason G.

    2015-05-01

    In order to mitigate storm surge impacts, precise surge guidance computations for forecasters must be finished within a short period of time to allow them to provide early warning to the public. For this purpose, a coupled ADCIRC and SWAN model was applied based on multiple scenario-based, deterministic model runs for each time-varying meteorological forecast advisory on a relatively lightweight mesh with 57 k nodes covering the North Western Pacific (NWP) ocean. The mesh was designed to achieve an optimal combination of speed and accuracy on a cost-effective parallel computer with 64 cores. These models were applied for two events in 2012: typhoon Bolaven (on the west coast of Korea) and typhoon Sanba (on the south coast of Korea). The surge results for a 72-h forecast yielded relative surge height error of 34.1 to 46.4 % in ADCIRC + SWAN. The surge results from a meteorological forecast 24 h from landfall improved to 21.7 to 26.8 %. Furthermore, surge elevation results progressively approached measured values (i.e., improved) with each successive typhoon advisory owing to diminishing uncertainties in the meteorological input. In conclusion, this new efficient early warning forecast guidance workflow successfully achieved its goals of real-time storm surge simulations for forecasters, early warning, and understanding of ocean dynamics.

  19. Design and analysis strategies for digital repetitive control systems with time-varying reference/disturbance period

    NASA Astrophysics Data System (ADS)

    Costa-Castelló, R.; Olm, J. M.; Ramos, G. A.

    2011-07-01

    This article analyses stability and performance features of different design schemes for digital repetitive control systems subject to references/disturbances that exhibit non-uniform frequency. Aiming at maintaining a constant value for the ratio T p /T s , T p being the period of the reference/disturbance signal and T s being the sampling period, two approaches are proposed. The first one deals with the real-time adaptation of T s to the actual changes of T p ; stability is studied by means of an LMI gridding method and also using robust control techniques. The second one propounds the introduction of an additional compensator that annihilates the effect of the time-varying sampling in the closed-loop system and forces its behaviour to coincide with that of an a priori selected nominal sampling period; the internal stability of the compensator-plant subsystem is checked by means of LMI gridding. The theoretical results are experimentally tested and compared through a mechatronic plant model.

  20. A Time Varying Evaluation of Identity Theory and Father Involvement for Full Custody, Shared Custody, and No Custody Divorced Fathers

    PubMed Central

    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