Time-varying properties of renal autoregulatory mechanisms

DEFF Research Database (Denmark)

Zou, Rui; Cupples, Will A; Yip, K P

2002-01-01

In order to assess the possible time-varying properties of renal autoregulation, time-frequency and time-scaling methods were applied to renal blood flow under broad-band forced arterial blood pressure fluctuations and single-nephron renal blood flow with spontaneous oscillations obtained from...... normotensive (Sprague-Dawley, Wistar, and Long-Evans) rats, and spontaneously hypertensive rats. Time-frequency analyses of normotensive and hypertensive blood flow data obtained from either the whole kidney or the single-nephron show that indeed both the myogenic and tubuloglomerular feedback (TGF) mechanisms...... have time-varying characteristics. Furthermore, we utilized the Renyi entropy to measure the complexity of blood-flow dynamics in the time-frequency plane in an effort to discern differences between normotensive and hypertensive recordings. We found a clear difference in Renyi entropy between...

Time-varying value of electric energy efficiency

Energy Technology Data Exchange (ETDEWEB)

Mims, Natalie A.; Eckman, Tom; Goldman, Charles

2017-06-30

Electric energy efficiency resources save energy and may reduce peak demand. Historically, quantification of energy efficiency benefits has largely focused on the economic value of energy savings during the first year and lifetime of the installed measures. Due in part to the lack of publicly available research on end-use load shapes (i.e., the hourly or seasonal timing of electricity savings) and energy savings shapes, consideration of the impact of energy efficiency on peak demand reduction (i.e., capacity savings) has been more limited. End-use load research and the hourly valuation of efficiency savings are used for a variety of electricity planning functions, including load forecasting, demand-side management and evaluation, capacity and demand response planning, long-term resource planning, renewable energy integration, assessing potential grid modernization investments, establishing rates and pricing, and customer service. This study reviews existing literature on the time-varying value of energy efficiency savings, provides examples in four geographically diverse locations of how consideration of the time-varying value of efficiency savings impacts the calculation of power system benefits, and identifies future research needs to enhance the consideration of the time-varying value of energy efficiency in cost-effectiveness screening analysis. Findings from this study include: -The time-varying value of individual energy efficiency measures varies across the locations studied because of the physical and operational characteristics of the individual utility system (e.g., summer or winter peaking, load factor, reserve margin) as well as the time periods during which savings from measures occur. -Across the four locations studied, some of the largest capacity benefits from energy efficiency are derived from the deferral of transmission and distribution system infrastructure upgrades. However, the deferred cost of such upgrades also exhibited the greatest range

Derivation of the scan time requirement for maintaining a consistent PET image quality

International Nuclear Information System (INIS)

Kim, Jin Su; Lee, Jae Sung; Kim, Seok-Ki

2015-01-01

Objectives: the image quality of PET for larger patients is relatively poor, even though the injection dose is optimized considering the NECR characteristics of the PET scanner. This poor image quality is due to the lower level of maximum NECR that can be achieved in these large patients. The aim of this study was to optimize the PET scan time to obtain a consistent PET image quality regardless of the body size, based on the relationship between the patient specific NECR (pNECR) and body weight. Methods: eighty patients (M/F=53/27, body weight: 059 ± 1 kg) underwent whole-body FDG PET scans using a Philips GEMINI GS PET/CT scanner after an injection of 0.14 mCi/kg FDG. The relationship between the scatter fraction (SF) and body weight was determined by repeated Monte Carlo simulations using a NEMA scatter phantom, the size of which varied according to the relationship between the abdominal circumference and body weight. Using this information, the pNECR was calculated from the prompt and delayed PET sinograms to obtain the prediction equation of NECR vs. body weight. The time scaling factor (F TS ) for the scan duration was finally derived to make PET images with equivalent SNR levels. Results: the SF and NECR had the following nonlinear relationships with the body weight: SF=0.15 ⋅ body weight 0.3 and NECR = 421.36 (body weight) −0.84 . The equation derived for F TS was 0.01⋅ body weight + 0.2, which means that, for example, a 120-kg person should be scanned 1.8 times longer than a 70 kg person, or the scan time for a 40-kg person can be reduced by 30%. Conclusion: the equation of the relative time demand derived in this study will be useful for maintaining consistent PET image quality in clinics

Pemodelan Markov Switching Dengan Time-varying Transition Probability

OpenAIRE

Savitri, Anggita Puri; Warsito, Budi; Rahmawati, Rita

2016-01-01

Exchange rate or currency is an economic variable which reflects country's state of economy. It fluctuates over time because of its ability to switch the condition or regime caused by economic and political factors. The changes in the exchange rate are depreciation and appreciation. Therefore, it could be modeled using Markov Switching with Time-Varying Transition Probability which observe the conditional changes and use information variable. From this model, time-varying transition probabili...

Experimental evidence for amplitude death induced by a time-varying interaction

Energy Technology Data Exchange (ETDEWEB)

Suresh, K. [Centre for Nonlinear Dynamics, School of Physics, Bharathidasan University, Tiruchirappalli 620024, Tamil Nadu (India); Shrimali, M.D. [Department of Physics, Central University of Rajasthan, NH-8, Bandar Sindri, Ajmer 305 801 (India); Prasad, Awadhesh [Department of Physics and Astrophysics, University of Delhi, Delhi 110 007 (India); Thamilmaran, K., E-mail: maran.cnld@gmail.com [Centre for Nonlinear Dynamics, School of Physics, Bharathidasan University, Tiruchirappalli 620024, Tamil Nadu (India)

2014-08-01

In this paper, we study the time-varying interaction in coupled oscillatory systems. For this purpose, we have designed a novel time-varying resistive network using an analog switch and inverter circuits. We have applied this time-varying resistive network to mutually coupled identical Chua's oscillators. When the resistances are varied in time, we find that amplitude death arises in coupled identical oscillators. This has been observed numerically as well as verified through hardware experiments. - Highlights: • We have implemented the time-varying interaction in coupled oscillatory systems. • We have designed a novel time-varying resistive network using an analog switch and inverter circuits. • When the resistances are varied in time, we find that amplitude death arises in coupled identical oscillators.

IMPROVED REAL-TIME SCAN MATCHING USING CORNER FEATURES

Directory of Open Access Journals (Sweden)

H. A. Mohamed

2016-06-01

Full Text Available The automation of unmanned vehicle operation has gained a lot of research attention, in the last few years, because of its numerous applications. The vehicle localization is more challenging in indoor environments where absolute positioning measurements (e.g. GPS are typically unavailable. Laser range finders are among the most widely used sensors that help the unmanned vehicles to localize themselves in indoor environments. Typically, automatic real-time matching of the successive scans is performed either explicitly or implicitly by any localization approach that utilizes laser range finders. Many accustomed approaches such as Iterative Closest Point (ICP, Iterative Matching Range Point (IMRP, Iterative Dual Correspondence (IDC, and Polar Scan Matching (PSM handles the scan matching problem in an iterative fashion which significantly affects the time consumption. Furthermore, the solution convergence is not guaranteed especially in cases of sharp maneuvers or fast movement. This paper proposes an automated real-time scan matching algorithm where the matching process is initialized using the detected corners. This initialization step aims to increase the convergence probability and to limit the number of iterations needed to reach convergence. The corner detection is preceded by line extraction from the laser scans. To evaluate the probability of line availability in indoor environments, various data sets, offered by different research groups, have been tested and the mean numbers of extracted lines per scan for these data sets are ranging from 4.10 to 8.86 lines of more than 7 points. The set of all intersections between extracted lines are detected as corners regardless of the physical intersection of these line segments in the scan. To account for the uncertainties of the detected corners, the covariance of the corners is estimated using the extracted lines variances. The detected corners are used to estimate the transformation parameters

Quantitative analysis of treatment process time and throughput capacity for spot scanning proton therapy

International Nuclear Information System (INIS)

Suzuki, Kazumichi; Sahoo, Narayan; Zhang, Xiaodong; Poenisch, Falk; Mackin, Dennis S.; Liu, Amy Y.; Wu, Richard; Zhu, X. Ronald; Gillin, Michael T.; Palmer, Matthew B.; Frank, Steven J.; Lee, Andrew K.

2016-01-01

Purpose: To determine the patient throughput and the overall efficiency of the spot scanning system by analyzing treatment time, equipment availability, and maximum daily capacity for the current spot scanning port at Proton Therapy Center Houston and to assess the daily throughput capacity for a hypothetical spot scanning proton therapy center. Methods: At their proton therapy center, the authors have been recording in an electronic medical record system all treatment data, including disease site, number of fields, number of fractions, delivered dose, energy, range, number of spots, and number of layers for every treatment field. The authors analyzed delivery system downtimes that had been recorded for every equipment failure and associated incidents. These data were used to evaluate the patient census, patient distribution as a function of the number of fields and total target volume, and equipment clinical availability. The duration of each treatment session from patient walk-in to patient walk-out of the spot scanning treatment room was measured for 64 patients with head and neck, central nervous system, thoracic, and genitourinary cancers. The authors retrieved data for total target volume and the numbers of layers and spots for all fields from treatment plans for a total of 271 patients (including the above 64 patients). A sensitivity analysis of daily throughput capacity was performed by varying seven parameters in a throughput capacity model. Results: The mean monthly equipment clinical availability for the spot scanning port in April 2012–March 2015 was 98.5%. Approximately 1500 patients had received spot scanning proton therapy as of March 2015. The major disease sites treated in September 2012–August 2014 were the genitourinary system (34%), head and neck (30%), central nervous system (21%), and thorax (14%), with other sites accounting for the remaining 1%. Spot scanning beam delivery time increased with total target volume and accounted for

Analysis of time-varying psoriasis lesion image patterns

DEFF Research Database (Denmark)

Maletti, Gabriela Mariel; Ersbøll, Bjarne Kjær; Nielsen, Allan Aasbjerg

2004-01-01

The multivariate alteration detection transform is applied to pairs of within and between time varying registered psoriasis image patterns. Color band contribution to the variates explaining maximal change is analyzed.......The multivariate alteration detection transform is applied to pairs of within and between time varying registered psoriasis image patterns. Color band contribution to the variates explaining maximal change is analyzed....

Finite-time stability of neutral-type neural networks with random time-varying delays

Science.gov (United States)

Ali, M. Syed; Saravanan, S.; Zhu, Quanxin

2017-11-01

This paper is devoted to the finite-time stability analysis of neutral-type neural networks with random time-varying delays. The randomly time-varying delays are characterised by Bernoulli stochastic variable. This result can be extended to analysis and design for neutral-type neural networks with random time-varying delays. On the basis of this paper, we constructed suitable Lyapunov-Krasovskii functional together and established a set of sufficient linear matrix inequalities approach to guarantee the finite-time stability of the system concerned. By employing the Jensen's inequality, free-weighting matrix method and Wirtinger's double integral inequality, the proposed conditions are derived and two numerical examples are addressed for the effectiveness of the developed techniques.

Entropy Rate of Time-Varying Wireless Networks

DEFF Research Database (Denmark)

Cika, Arta; Badiu, Mihai Alin; Coon, Justin P.

2018-01-01

In this paper, we present a detailed framework to analyze the evolution of the random topology of a time-varying wireless network via the information theoretic notion of entropy rate. We consider a propagation channel varying over time with random node positions in a closed space and Rayleigh...... fading affecting the connections between nodes. The existence of an edge between two nodes at given locations is modeled by a Markov chain, enabling memory effects in network dynamics. We then derive a lower and an upper bound on the entropy rate of the spatiotemporal network. The entropy rate measures...

Time-Varying Value of Energy Efficiency in Michigan

Energy Technology Data Exchange (ETDEWEB)

Mims, Natalie; Eckman, Tom; Schwartz, Lisa C.

2018-04-02

Quantifying the time-varying value of energy efficiency is necessary to properly account for all of its benefits and costs and to identify and implement efficiency resources that contribute to a low-cost, reliable electric system. Historically, most quantification of the benefits of efficiency has focused largely on the economic value of annual energy reduction. Due to the lack of statistically representative metered end-use load shape data in Michigan (i.e., the hourly or seasonal timing of electricity savings), the ability to confidently characterize the time-varying value of energy efficiency savings in the state, especially for weather-sensitive measures such as central air conditioning, is limited. Still, electric utilities in Michigan can take advantage of opportunities to incorporate the time-varying value of efficiency into their planning. For example, end-use load research and hourly valuation of efficiency savings can be used for a variety of electricity planning functions, including load forecasting, demand-side management and evaluation, capacity planning, long-term resource planning, renewable energy integration, assessing potential grid modernization investments, establishing rates and pricing, and customer service (KEMA 2012). In addition, accurately calculating the time-varying value of efficiency may help energy efficiency program administrators prioritize existing offerings, set incentive or rebate levels that reflect the full value of efficiency, and design new programs.

Multivariate time-varying volatility modeling using probabilistic fuzzy systems

NARCIS (Netherlands)

Basturk, N.; Almeida, R.J.; Golan, R.; Kaymak, U.

2016-01-01

Methods to accurately analyze financial risk have drawn considerable attention in financial institutions. One difficulty in financial risk analysis is the fact that banks and other financial institutions invest in several assets which show time-varying volatilities and hence time-varying financial

Long memory of financial time series and hidden Markov models with time-varying parameters

DEFF Research Database (Denmark)

Nystrup, Peter; Madsen, Henrik; Lindström, Erik

Hidden Markov models are often used to capture stylized facts of daily returns and to infer the hidden state of financial markets. Previous studies have found that the estimated models change over time, but the implications of the time-varying behavior for the ability to reproduce the stylized...... facts have not been thoroughly examined. This paper presents an adaptive estimation approach that allows for the parameters of the estimated models to be time-varying. It is shown that a two-state Gaussian hidden Markov model with time-varying parameters is able to reproduce the long memory of squared...... daily returns that was previously believed to be the most difficult fact to reproduce with a hidden Markov model. Capturing the time-varying behavior of the parameters also leads to improved one-step predictions....

Overcoming Spurious Regression Using time-Varying Fourier ...

African Journals Online (AJOL)

Non-stationary time series data have been traditionally analyzed in the frequency domain by assuming constant amplitudes regardless of the timelag. A new approach called time-varying amplitude method (TVAM) is presented here. Oscillations are analyzed for changes in the magnitude of Fourier Coefficients which are ...

Vesicle biomechanics in a time-varying magnetic field.

Science.gov (United States)

Ye, Hui; Curcuru, Austen

2015-01-01

Cells exhibit distortion when exposed to a strong electric field, suggesting that the field imposes control over cellular biomechanics. Closed pure lipid bilayer membranes (vesicles) have been widely used for the experimental and theoretical studies of cellular biomechanics under this electrodeformation. An alternative method used to generate an electric field is by electromagnetic induction with a time-varying magnetic field. References reporting the magnetic control of cellular mechanics have recently emerged. However, theoretical analysis of the cellular mechanics under a time-varying magnetic field is inadequate. We developed an analytical theory to investigate the biomechanics of a modeled vesicle under a time-varying magnetic field. Following previous publications and to simplify the calculation, this model treated the inner and suspending media as lossy dielectrics, the membrane thickness set at zero, and the electric resistance of the membrane assumed to be negligible. This work provided the first analytical solutions for the surface charges, electric field, radial pressure, overall translational forces, and rotational torques introduced on a vesicle by the time-varying magnetic field. Frequency responses of these measures were analyzed, particularly the frequency used clinically by transcranial magnetic stimulation (TMS). The induced surface charges interacted with the electric field to produce a biomechanical impact upon the vesicle. The distribution of the induced surface charges depended on the orientation of the coil and field frequency. The densities of these charges were trivial at low frequency ranges, but significant at high frequency ranges. The direction of the radial force on the vesicle was dependent on the conductivity ratio between the vesicle and the medium. At relatively low frequencies (biomechanics under a time-varying magnetic field. Biological effects of clinical TMS are not likely to occur via alteration of the biomechanics of brain

Fat mass measured by DXA varies with scan velocity

DEFF Research Database (Denmark)

Black, Eva; Petersen, Liselotte; Kreutzer, Martin

2002-01-01

To study the influence of scan velocities of DXA on the measured size of fat mass, lean body mass, bone mineral content and density, and total body weight.......To study the influence of scan velocities of DXA on the measured size of fat mass, lean body mass, bone mineral content and density, and total body weight....

Modelling Time-Varying Volatility in Financial Returns

DEFF Research Database (Denmark)

Amado, Cristina; Laakkonen, Helinä

2014-01-01

The “unusually uncertain” phase in the global financial markets has inspired many researchers to study the effects of ambiguity (or “Knightian uncertainty”) on the decisions made by investors and their implications for the capital markets. We contribute to this literature by using a modified...... version of the time-varying GARCH model of Amado and Teräsvirta (2013) to analyze whether the increasing uncertainty has caused excess volatility in the US and European government bond markets. In our model, volatility is multiplicatively decomposed into two time-varying conditional components: the first...... being captured by a stable GARCH(1,1) process and the second driven by the level of uncertainty in the financial market....

Identification of time-varying nonlinear systems using differential evolution algorithm

DEFF Research Database (Denmark)

Perisic, Nevena; Green, Peter L; Worden, Keith

2013-01-01

(DE) algorithm for the identification of time-varying systems. DE is an evolutionary optimisation method developed to perform direct search in a continuous space without requiring any derivative estimation. DE is modified so that the objective function changes with time to account for the continuing......, thus identification of time-varying systems with nonlinearities can be a very challenging task. In order to avoid conventional least squares and gradient identification methods which require uni-modal and double differentiable objective functions, this work proposes a modified differential evolution...... inclusion of new data within an error metric. This paper presents results of identification of a time-varying SDOF system with Coulomb friction using simulated noise-free and noisy data for the case of time-varying friction coefficient, stiffness and damping. The obtained results are promising and the focus...

Temporal Prediction Errors Affect Short-Term Memory Scanning Response Time.

Science.gov (United States)

Limongi, Roberto; Silva, Angélica M

2016-11-01

The Sternberg short-term memory scanning task has been used to unveil cognitive operations involved in time perception. Participants produce time intervals during the task, and the researcher explores how task performance affects interval production - where time estimation error is the dependent variable of interest. The perspective of predictive behavior regards time estimation error as a temporal prediction error (PE), an independent variable that controls cognition, behavior, and learning. Based on this perspective, we investigated whether temporal PEs affect short-term memory scanning. Participants performed temporal predictions while they maintained information in memory. Model inference revealed that PEs affected memory scanning response time independently of the memory-set size effect. We discuss the results within the context of formal and mechanistic models of short-term memory scanning and predictive coding, a Bayes-based theory of brain function. We state the hypothesis that our finding could be associated with weak frontostriatal connections and weak striatal activity.

RTSPM: real-time Linux control software for scanning probe microscopy.

Science.gov (United States)

Chandrasekhar, V; Mehta, M M

2013-01-01

Real time computer control is an essential feature of scanning probe microscopes, which have become important tools for the characterization and investigation of nanometer scale samples. Most commercial (and some open-source) scanning probe data acquisition software uses digital signal processors to handle the real time data processing and control, which adds to the expense and complexity of the control software. We describe here scan control software that uses a single computer and a data acquisition card to acquire scan data. The computer runs an open-source real time Linux kernel, which permits fast acquisition and control while maintaining a responsive graphical user interface. Images from a simulated tuning-fork based microscope as well as a standard topographical sample are also presented, showing some of the capabilities of the software.

Time-varying linear control for tiltrotor aircraft

Directory of Open Access Journals (Sweden)

Jing ZHANG

2018-04-01

Full Text Available Tiltrotor aircraft have three flight modes: helicopter mode, airplane mode, and transition mode. A tiltrotor has characteristics of highly nonlinear, time-varying flight dynamics and inertial/control couplings in its transition mode. It can transit from the helicopter mode to the airplane mode by tilting its nacelles, and an effective controller is crucial to accomplish tilting transition missions. Longitudinal dynamic characteristics of the tiltrotor are described by a nonlinear Lagrange-form model, which takes into account inertial/control couplings and aerodynamic interferences. Reference commands for airspeed velocity and attitude in the transition mode are calculated dynamically by visiting a command library which is founded in advance by analyzing the flight envelope of the tiltrotor. A Time-Varying Linear (TVL model is obtained using a Taylor-expansion based online linearization technique from the nonlinear model. Subsequently, based on an optimal control concept, an online optimization based control method with input constraints considered is proposed. To validate the proposed control method, three typical tilting transition missions are simulated using the nonlinear model of XV-15 tiltrotor aircraft. Simulation results show that the controller can be used to control the tiltrotor throughout its operating envelop which includes a transition flight, and can also deal with vertical gust disturbances. Keywords: Constrained optimal control, Inertia/control couplings, Tiltrotor aircraft, Time-varying control, Transition mode

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

Science.gov (United States)

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.

Scaling properties in time-varying networks with memory

Science.gov (United States)

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.

Testing for time-varying loadings in dynamic factor models

DEFF Research Database (Denmark)

Mikkelsen, Jakob Guldbæk

Abstract: In this paper we develop a test for time-varying factor loadings in factor models. The test is simple to compute and is constructed from estimated factors and residuals using the principal components estimator. The hypothesis is tested by regressing the squared residuals on the squared...... there is evidence of time-varying loadings on the risk factors underlying portfolio returns for around 80% of the portfolios....

Line shapes and time dynamics of the Förster resonances between two Rydberg atoms in a time-varying electric field

KAUST Repository

Yakshina, E. A.

2016-10-21

The observation of the Stark-tuned Förster resonances between Rydberg atoms excited by narrowband cw laser radiation requires usage of a Stark-switching technique in order to excite the atoms first in a fixed electric field and then to induce the interactions in a varied electric field, which is scanned across the Förster resonance. In our experiments with a few cold Rb Rydberg atoms, we have found that the transients at the edges of the electric pulses strongly affect the line shapes of the Förster resonances, since the population transfer at the resonances occurs on a time scale of ∼100 ns, which is comparable with the duration of the transients. For example, a short-term ringing at a certain frequency causes additional radio-frequency-assisted Förster resonances, while nonsharp edges lead to asymmetry. The intentional application of the radio-frequency field induces transitions between collective states, whose line shape depends on the interaction strengths and time. Spatial averaging over the atom positions in a single interaction volume yields a cusped line shape of the Förster resonance. We present a detailed experimental and theoretical analysis of the line shape and time dynamics of the Stark-tuned Förster resonances Rb(nP3/2)+Rb(nP3/2)→Rb(nS1/2)+Rb([n+1]S1/2) for two Rb Rydberg atoms interacting in a time-varying electric field.

Line shapes and time dynamics of the Förster resonances between two Rydberg atoms in a time-varying electric field

KAUST Repository

Yakshina, E. A.; Tretyakov, D. B.; Beterov, I. I.; Entin, V. M.; Andreeva, C.; Cinins, A.; Markovski, A.; Iftikhar, Z.; Ekers, Aigars; Ryabtsev, I. I.

2016-01-01

The observation of the Stark-tuned Förster resonances between Rydberg atoms excited by narrowband cw laser radiation requires usage of a Stark-switching technique in order to excite the atoms first in a fixed electric field and then to induce the interactions in a varied electric field, which is scanned across the Förster resonance. In our experiments with a few cold Rb Rydberg atoms, we have found that the transients at the edges of the electric pulses strongly affect the line shapes of the Förster resonances, since the population transfer at the resonances occurs on a time scale of ∼100 ns, which is comparable with the duration of the transients. For example, a short-term ringing at a certain frequency causes additional radio-frequency-assisted Förster resonances, while nonsharp edges lead to asymmetry. The intentional application of the radio-frequency field induces transitions between collective states, whose line shape depends on the interaction strengths and time. Spatial averaging over the atom positions in a single interaction volume yields a cusped line shape of the Förster resonance. We present a detailed experimental and theoretical analysis of the line shape and time dynamics of the Stark-tuned Förster resonances Rb(nP3/2)+Rb(nP3/2)→Rb(nS1/2)+Rb([n+1]S1/2) for two Rb Rydberg atoms interacting in a time-varying electric field.

Time-Varying Periodicity in Intraday Volatility

DEFF Research Database (Denmark)

Andersen, Torben Gustav; Thyrsgaard, Martin; Todorov, Viktor

We develop a nonparametric test for deciding whether return volatility exhibits time-varying intraday periodicity using a long time-series of high-frequency data. Our null hypothesis, commonly adopted in work on volatility modeling, is that volatility follows a stationary process combined...... with a constant time-of-day periodic component. We first construct time-of-day volatility estimates and studentize the high-frequency returns with these periodic components. If the intraday volatility periodicity is invariant over time, then the distribution of the studentized returns should be identical across...... with estimating volatility moments through their sample counterparts. Critical values are computed via easy-to-implement simulation. In an empirical application to S&P 500 index returns, we find strong evidence for variation in the intraday volatility pattern driven in part by the current level of volatility...

Finite-Time Stability of Large-Scale Systems with Interval Time-Varying Delay in Interconnection

Directory of Open Access Journals (Sweden)

T. La-inchua

2017-01-01

Full Text Available We investigate finite-time stability of a class of nonlinear large-scale systems with interval time-varying delays in interconnection. Time-delay functions are continuous but not necessarily differentiable. Based on Lyapunov stability theory and new integral bounding technique, finite-time stability of large-scale systems with interval time-varying delays in interconnection is derived. The finite-time stability criteria are delays-dependent and are given in terms of linear matrix inequalities which can be solved by various available algorithms. Numerical examples are given to illustrate effectiveness of the proposed method.

Modeling information diffusion in time-varying community networks

Science.gov (United States)

Cui, Xuelian; Zhao, Narisa

2017-12-01

Social networks are rarely static, and they typically have time-varying network topologies. A great number of studies have modeled temporal networks and explored social contagion processes within these models; however, few of these studies have considered community structure variations. In this paper, we present a study of how the time-varying property of a modular structure influences the information dissemination. First, we propose a continuous-time Markov model of information diffusion where two parameters, mobility rate and community attractiveness, are introduced to address the time-varying nature of the community structure. The basic reproduction number is derived, and the accuracy of this model is evaluated by comparing the simulation and theoretical results. Furthermore, numerical results illustrate that generally both the mobility rate and community attractiveness significantly promote the information diffusion process, especially in the initial outbreak stage. Moreover, the strength of this promotion effect is much stronger when the modularity is higher. Counterintuitively, it is found that when all communities have the same attractiveness, social mobility no longer accelerates the diffusion process. In addition, we show that the local spreading in the advantage group has been greatly enhanced due to the agglomeration effect caused by the social mobility and community attractiveness difference, which thus increases the global spreading.

Do Time-Varying Covariances, Volatility Comovement and Spillover Matter?

OpenAIRE

Lakshmi Balasubramanyan

2005-01-01

Financial markets and their respective assets are so intertwined; analyzing any single market in isolation ignores important information. We investigate whether time varying volatility comovement and spillover impact the true variance-covariance matrix under a time-varying correlation set up. Statistically significant volatility spillover and comovement between US, UK and Japan is found. To demonstrate the importance of modelling volatility comovement and spillover, we look at a simple portfo...

Newtonian cosmology with a time-varying constant of gravitation

International Nuclear Information System (INIS)

McVittie, G.C.

1978-01-01

Newtonian cosmology is based on the Eulerian equations of fluid mechanics combined with Poisson's equation modified by the introduction of a time-varying G. Spherically symmetric model universes are worked out with instantaneously uniform densities. They are indeterminate unless instantaneous uniformity of the pressure is imposed. When G varies as an inverse power of the time, the models can in some cases be shown to depend on the solution of a second-order differential equation which also occurs in the Friedmann models of general relativity. In Section 3, a method for 'passing through' a singularity of this equation is proposed which entails making four arbitrary mathematical assumptions. When G varies as (time) -1 , models with initially cycloidal motion are possible, each cycle becoming longer as time progresses. Finally, gravitation becomes so weak that the model expands to infinity. Kinetic and potential energies for the whole model are derived from the basic equations; their sum is not constant. (author)

Modeling of Electricity Demand for Azerbaijan: Time-Varying Coefficient Cointegration Approach

Directory of Open Access Journals (Sweden)

Jeyhun I. Mikayilov

2017-11-01

Full Text Available Recent literature has shown that electricity demand elasticities may not be constant over time and this has investigated using time-varying estimation methods. As accurate modeling of electricity demand is very important in Azerbaijan, which is a transitional country facing significant change in its economic outlook, we analyze whether the response of electricity demand to income and price is varying over time in this economy. We employed the Time-Varying Coefficient cointegration approach, a cutting-edge time-varying estimation method. We find evidence that income elasticity demonstrates sizeable variation for the period of investigation ranging from 0.48% to 0.56%. The study has some useful policy implications related to the income and price aspects of the electricity consumption in Azerbaijan.

Time-varying correlation and common structures in volatility

NARCIS (Netherlands)

Liu, Yang

2016-01-01

This thesis studies time series properties of the covariance structure of multivariate asset returns. First, the time-varying feature of correlation is investigated at the intraday level with a new correlation model incorporating the intraday correlation dynamics. Second, the thesis develops a

Visualizing time-varying harmonics using filter banks

NARCIS (Netherlands)

Duque, C.A.; Da Silveira, P.M.; Ribeiro, P.F.

2011-01-01

Although it is well known that Fourier analysis is in reality only accurately applicable to steady state waveforms, it is a widely used tool to study and monitor time-varying signals, such as are commonplace in electrical power systems. The disadvantages of Fourier analysis, such as frequency

The optimization of scan timing for contrast-enhanced magnetic resonance angiography

International Nuclear Information System (INIS)

Lee, Jong Min; Chang, Yong Min; Ryeom, Hun Kyu; Lee, Sang Kwon; Kim, Yong Sun; Kang, Duk Sik; Tirman, Philip J.

2000-01-01

To determine the optimal scan timing for contrast-enhanced magnetic resonance angiography and to evaluate a new timing method based on the arteriovenous circulation time. Eighty-nine contrast-enhanced magnetic resonance angiographic examinations were performed mainly in the extremities. A 1.5T scanner with a 3-D turbo-FLASH sequence was used, and during each study, two consecutive arterial phases and one venous phase were acquired. Scan delay time was calculated from the time-intensity curve by the traditional (n = 48) and/or the new (n = 41) method. This latter was based on arteriovenous circulation time rather than peak arterial enhancement time, as used in the traditional method. The numbers of first-phase images showing a properly enhanced arterial phase were compared between the two methods. Mean scan delay time was 5.4 sec longer with the new method than with the traditional. Properly enhanced first-phase images were found in 65% of cases (31/48) using the traditional timing method, and 95% (39/41) using the new method. When cases in which there was mismatch between the target vessel and the Time-intensity curve acquisition site are excluded, erroneous acquisition occurred in seven cases with the traditional method, but in none with the new method. The calculation of scan delay time on the basis of arteriovenous circulation time provides better timing for arterial phase acquisition than the traditional method

Stabilization of the Wave Equation with Boundary Time-Varying Delay

Directory of Open Access Journals (Sweden)

Hao Li

2014-01-01

Full Text Available We study the stabilization of the wave equation with variable coefficients in a bounded domain and a time-varying delay term in the time-varying, weakly nonlinear boundary feedbacks. By the Riemannian geometry methods and a suitable assumption of nonlinearity, we obtain the uniform decay of the energy of the closed loop system.

Investigating Time-Varying Drivers of Grid Project Emissions Impacts

Energy Technology Data Exchange (ETDEWEB)

Barrett, Emily L.; Thayer, Brandon L.; Pal, Seemita; Studarus, Karen E.

2017-11-15

The emissions consequences of smart grid technologies depend heavily on their context and vary not only by geographical location, but by time of year. The same technology operated to meet the same objective may increase the emissions associated with energy generation for part of the year and decrease emissions during other times. The Grid Project Impact Quantification (GridPIQ) tool provides the ability to estimate these seasonal variations and garner insight into the time-varying drivers of grid project emissions impacts. This work leverages GridPIQ to examine the emissions implications across years and seasons of adding energy storage technology to reduce daily peak demand in California and New York.

Nonlinear recurrent neural networks for finite-time solution of general time-varying linear matrix equations.

Science.gov (United States)

Xiao, Lin; Liao, Bolin; Li, Shuai; Chen, Ke

2018-02-01

In order to solve general time-varying linear matrix equations (LMEs) more efficiently, this paper proposes two nonlinear recurrent neural networks based on two nonlinear activation functions. According to Lyapunov theory, such two nonlinear recurrent neural networks are proved to be convergent within finite-time. Besides, by solving differential equation, the upper bounds of the finite convergence time are determined analytically. Compared with existing recurrent neural networks, the proposed two nonlinear recurrent neural networks have a better convergence property (i.e., the upper bound is lower), and thus the accurate solutions of general time-varying LMEs can be obtained with less time. At last, various different situations have been considered by setting different coefficient matrices of general time-varying LMEs and a great variety of computer simulations (including the application to robot manipulators) have been conducted to validate the better finite-time convergence of the proposed two nonlinear recurrent neural networks. Copyright © 2017 Elsevier Ltd. All rights reserved.

Long Memory of Financial Time Series and Hidden Markov Models with Time-Varying Parameters

DEFF Research Database (Denmark)

Nystrup, Peter; Madsen, Henrik; Lindström, Erik

2016-01-01

Hidden Markov models are often used to model daily returns and to infer the hidden state of financial markets. Previous studies have found that the estimated models change over time, but the implications of the time-varying behavior have not been thoroughly examined. This paper presents an adaptive...... to reproduce with a hidden Markov model. Capturing the time-varying behavior of the parameters also leads to improved one-step density forecasts. Finally, it is shown that the forecasting performance of the estimated models can be further improved using local smoothing to forecast the parameter variations....

A Novel Real-Time Reference Key Frame Scan Matching Method

Directory of Open Access Journals (Sweden)

Haytham Mohamed

2017-05-01

Full Text Available Unmanned aerial vehicles represent an effective technology for indoor search and rescue operations. Typically, most indoor missions’ environments would be unknown, unstructured, and/or dynamic. Navigation of UAVs in such environments is addressed by simultaneous localization and mapping approach using either local or global approaches. Both approaches suffer from accumulated errors and high processing time due to the iterative nature of the scan matching method. Moreover, point-to-point scan matching is prone to outlier association processes. This paper proposes a low-cost novel method for 2D real-time scan matching based on a reference key frame (RKF. RKF is a hybrid scan matching technique comprised of feature-to-feature and point-to-point approaches. This algorithm aims at mitigating errors accumulation using the key frame technique, which is inspired from video streaming broadcast process. The algorithm depends on the iterative closest point algorithm during the lack of linear features which is typically exhibited in unstructured environments. The algorithm switches back to the RKF once linear features are detected. To validate and evaluate the algorithm, the mapping performance and time consumption are compared with various algorithms in static and dynamic environments. The performance of the algorithm exhibits promising navigational, mapping results and very short computational time, that indicates the potential use of the new algorithm with real-time systems.

Continuous time modelling with individually varying time intervals for oscillating and non-oscillating processes.

Science.gov (United States)

Voelkle, Manuel C; Oud, Johan H L

2013-02-01

When designing longitudinal studies, researchers often aim at equal intervals. In practice, however, this goal is hardly ever met, with different time intervals between assessment waves and different time intervals between individuals being more the rule than the exception. One of the reasons for the introduction of continuous time models by means of structural equation modelling has been to deal with irregularly spaced assessment waves (e.g., Oud & Delsing, 2010). In the present paper we extend the approach to individually varying time intervals for oscillating and non-oscillating processes. In addition, we show not only that equal intervals are unnecessary but also that it can be advantageous to use unequal sampling intervals, in particular when the sampling rate is low. Two examples are provided to support our arguments. In the first example we compare a continuous time model of a bivariate coupled process with varying time intervals to a standard discrete time model to illustrate the importance of accounting for the exact time intervals. In the second example the effect of different sampling intervals on estimating a damped linear oscillator is investigated by means of a Monte Carlo simulation. We conclude that it is important to account for individually varying time intervals, and encourage researchers to conceive of longitudinal studies with different time intervals within and between individuals as an opportunity rather than a problem. © 2012 The British Psychological Society.

Lyapunov Functions to Caputo Fractional Neural Networks with Time-Varying Delays

Directory of Open Access Journals (Sweden)

Ravi Agarwal

2018-05-01

Full Text Available One of the main properties of solutions of nonlinear Caputo fractional neural networks is stability and often the direct Lyapunov method is used to study stability properties (usually these Lyapunov functions do not depend on the time variable. In connection with the Lyapunov fractional method we present a brief overview of the most popular fractional order derivatives of Lyapunov functions among Caputo fractional delay differential equations. These derivatives are applied to various types of neural networks with variable coefficients and time-varying delays. We show that quadratic Lyapunov functions and their Caputo fractional derivatives are not applicable in some cases when one studies stability properties. Some sufficient conditions for stability of equilibrium of nonlinear Caputo fractional neural networks with time dependent transmission delays, time varying self-regulating parameters of all units and time varying functions of the connection between two neurons in the network are obtained. The cases of time varying Lipschitz coefficients as well as nonLipschitz activation functions are studied. We illustrate our theory on particular nonlinear Caputo fractional neural networks.

Contrast enhancement technique in brain 3D-CTA studies. Optimizing the amount of contrast medium according to scan time based on TDC

International Nuclear Information System (INIS)

Terasawa, Kazuaki; Hatcho, Atsushi

2008-01-01

In three-dimensional CT angiography (3D-CTA), good reproducibility can be obtained by maintaining the maximum CT numbers (HU) at a specified level. However, the correlation between the scan time and the injection time showed that the maximum CT numbers increased and varied due to the additional contrast enhancement effect from recirculation of the injected contrast medium for longer injection times when the dose of iodinated contrast medium per unit time (mgI/s) was maintained at a specified level based on the time-density curve (TDC) of the phantom. The amount of contrast medium employed at our hospital has been optimized based on an iodinated contrast medium dose per unit time providing a contrast enhancement effect of 300 HU in the middle cerebral artery. Using this standard, a TDC phantom was employed to obtain an iodinated contrast medium dose per unit time, permitting equivalent maximum CT values (used as standard values) to be obtained by changing the injection time. A contrast-enhancement technique that accounts for the variation in the scan time was evaluated. Strong correlations were observed between the scan time and the injection time (R 2 =0.969) and between the injection time and the dose of iodinated contrast medium per unit body weight (R 2 =0.994). We conclude that adjusting the dose of iodinated contrast medium per unit body weight per unit time according to the scan time permits optimization of the contrast-enhancement technique. (author)

The necessity for a time local dimension in systems with time-varying attractors

DEFF Research Database (Denmark)

Særmark, Knud H; Ashkenazy, Y; Levitan, J

1997-01-01

We show that a simple non-linear system for ordinary differential equations may possess a time-varying attractor dimension. This indicates that it is infeasible to characterize EEG and MEG time series with a single time global dimension. We suggest another measure for the description of non...

Impact of the planning CT scan time on the reflection of the lung tumor motion

International Nuclear Information System (INIS)

Kim, Su San; Choi, Eun Kyung; Yi, Byong Yong; Ha, Sung Whan

2004-01-01

To evaluate the reflection of tumor motion according to the planning CT scan time. A model of N-shape, which moved along the longitudinal axis during the ventilation caused by a mechanical ventilator, was produced. The model was scanned by planning CT, while setting the relative CT scan time (T; CT scan time/ventilatory period) to 0.33, 0.50, 0.67, 0.75, 1.00, 1.33 T, and 1.53 T. In addition, three patients with non-small cell lung cancer who received stereotactic radiosurgery in the Department of Radiation Oncology, Asan Medical Center from 03/19/2002 to 05/21/2002 were scanned. Slow (IQ Premier, Picker, scan time 2.0 seconds per slice) and fast CT scans (Light Speed, GE Medical System, with a scan time of 0.8 second per slice) were performed for each patient. The magnitude of reflected movement of the N-shaped model was evaluated by measuring the transverse length, which reflected the movement of the declined bar of the model at each slice. For patients' scans, all CT data sets were registered using a stereotactic body frame scale with the gross tumor volumes delineated in one CT image set. The volume and three-dimensional diameter of the gross tumor volume were measured and analyzed between the slow and fast CT scans. The reflection degree of longitudinal movement of the model increased in proportion to the relative CT scan times below 1.00 T, but remained constant above 1.00 T. Assuming the mean value of scanned transverse lengths with CT scan time 1.00 T to be 100%, CT scans with scan times of 0.33, 0.50, 0.67, and 0.75 T missed the tumor motion by 30, 27, 20, and 7.0% respectively. Slow (scan time 2.0 sec) and Fast (scan time 0.8 sec) CT scans of three patients with longitudinal movement of 3, 5, and 10 mm measured by fluoroscopy revealed the increases in the diameter along the longitudinal axis increased by 6.3, 17, and 23% in the slow CT scans. As the relative CT scan time increased, the reflection of the respiratory tumor movement on planning CT also

Flexible time-varying filter banks

Science.gov (United States)

Tuncer, Temel E.; Nguyen, Truong Q.

1993-09-01

Linear phase maximally flat FIR Butterworth filter approximations are discussed and a new filter design method is introduced. This variable cutoff filter design method uses the cosine modulated versions of a prototype filter. The design procedure is simple and different variants of this procedure can be used to obtain close to optimum linear phase filters. Using this method, flexible time-varying filter banks with good reconstruction error are introduced. These types of oversampled filter banks have small magnitude error which can be easily controlled by the appropriate choice of modulation frequency. This error can be further decreased by magnitude equalization without increasing the computational complexity considerably. Two dimensional design examples are also given.

A log-Weibull spatial scan statistic for time to event data.

Science.gov (United States)

Usman, Iram; Rosychuk, Rhonda J

2018-06-13

Spatial scan statistics have been used for the identification of geographic clusters of elevated numbers of cases of a condition such as disease outbreaks. These statistics accompanied by the appropriate distribution can also identify geographic areas with either longer or shorter time to events. Other authors have proposed the spatial scan statistics based on the exponential and Weibull distributions. We propose the log-Weibull as an alternative distribution for the spatial scan statistic for time to events data and compare and contrast the log-Weibull and Weibull distributions through simulation studies. The effect of type I differential censoring and power have been investigated through simulated data. Methods are also illustrated on time to specialist visit data for discharged patients presenting to emergency departments for atrial fibrillation and flutter in Alberta during 2010-2011. We found northern regions of Alberta had longer times to specialist visit than other areas. We proposed the spatial scan statistic for the log-Weibull distribution as a new approach for detecting spatial clusters for time to event data. The simulation studies suggest that the test performs well for log-Weibull data.

A New Time-varying Concept of Risk in a Changing Climate

Science.gov (United States)

Sarhadi, Ali; Ausín, María Concepción; Wiper, Michael P.

2016-10-01

In a changing climate arising from anthropogenic global warming, the nature of extreme climatic events is changing over time. Existing analytical stationary-based risk methods, however, assume multi-dimensional extreme climate phenomena will not significantly vary over time. To strengthen the reliability of infrastructure designs and the management of water systems in the changing environment, multidimensional stationary risk studies should be replaced with a new adaptive perspective. The results of a comparison indicate that current multi-dimensional stationary risk frameworks are no longer applicable to projecting the changing behaviour of multi-dimensional extreme climate processes. Using static stationary-based multivariate risk methods may lead to undesirable consequences in designing water system infrastructures. The static stationary concept should be replaced with a flexible multi-dimensional time-varying risk framework. The present study introduces a new multi-dimensional time-varying risk concept to be incorporated in updating infrastructure design strategies under changing environments arising from human-induced climate change. The proposed generalized time-varying risk concept can be applied for all stochastic multi-dimensional systems that are under the influence of changing environments.

A New Time-varying Concept of Risk in a Changing Climate.

Science.gov (United States)

Sarhadi, Ali; Ausín, María Concepción; Wiper, Michael P

2016-10-20

In a changing climate arising from anthropogenic global warming, the nature of extreme climatic events is changing over time. Existing analytical stationary-based risk methods, however, assume multi-dimensional extreme climate phenomena will not significantly vary over time. To strengthen the reliability of infrastructure designs and the management of water systems in the changing environment, multidimensional stationary risk studies should be replaced with a new adaptive perspective. The results of a comparison indicate that current multi-dimensional stationary risk frameworks are no longer applicable to projecting the changing behaviour of multi-dimensional extreme climate processes. Using static stationary-based multivariate risk methods may lead to undesirable consequences in designing water system infrastructures. The static stationary concept should be replaced with a flexible multi-dimensional time-varying risk framework. The present study introduces a new multi-dimensional time-varying risk concept to be incorporated in updating infrastructure design strategies under changing environments arising from human-induced climate change. The proposed generalized time-varying risk concept can be applied for all stochastic multi-dimensional systems that are under the influence of changing environments.

Time-Varying Networks of Inter-Ictal Discharging Reveal Epileptogenic Zone.

Science.gov (United States)

Zhang, Luyan; Liang, Yi; Li, Fali; Sun, Hongbin; Peng, Wenjing; Du, Peishan; Si, Yajing; Song, Limeng; Yu, Liang; Xu, Peng

2017-01-01

The neuronal synchronous discharging may cause an epileptic seizure. Currently, most of the studies conducted to investigate the mechanism of epilepsy are based on EEGs or functional magnetic resonance imaging (fMRI) recorded during the ictal discharging or the resting-state, and few studies have probed into the dynamic patterns during the inter-ictal discharging that are much easier to record in clinical applications. Here, we propose a time-varying network analysis based on adaptive directed transfer function to uncover the dynamic brain network patterns during the inter-ictal discharging. In addition, an algorithm based on the time-varying outflow of information derived from the network analysis is developed to detect the epileptogenic zone. The analysis performed revealed the time-varying network patterns during different stages of inter-ictal discharging; the epileptogenic zone was activated prior to the discharge onset then worked as the source to propagate the activity to other brain regions. Consistence between the epileptogenic zones detected by our proposed approach and the actual epileptogenic zones proved that time-varying network analysis could not only reveal the underlying neural mechanism of epilepsy, but also function as a useful tool in detecting the epileptogenic zone based on the EEGs in the inter-ictal discharging.

Frequency variations of gravity waves interacting with a time-varying tide

Energy Technology Data Exchange (ETDEWEB)

Huang, C.M.; Zhang, S.D.; Yi, F.; Huang, K.M.; Gan, Q.; Gong, Y. [Wuhan Univ., Hubei (China). School of Electronic Information; Ministry of Education, Wuhan, Hubei (China). Key Lab. of Geospace Environment and Geodesy; State Observatory for Atmospheric Remote Sensing, Wuhan, Hubei (China); Zhang, Y.H. [Nanjing Univ. of Information Science and Technology (China). College of Hydrometeorolgy

2013-11-01

Using a nonlinear, 2-D time-dependent numerical model, we simulate the propagation of gravity waves (GWs) in a time-varying tide. Our simulations show that when aGW packet propagates in a time-varying tidal-wind environment, not only its intrinsic frequency but also its ground-based frequency would change significantly. The tidal horizontal-wind acceleration dominates the GW frequency variation. Positive (negative) accelerations induce frequency increases (decreases) with time. More interestingly, tidal-wind acceleration near the critical layers always causes the GW frequency to increase, which may partially explain the observations that high-frequency GW components are more dominant in the middle and upper atmosphere than in the lower atmosphere. The combination of the increased ground-based frequency of propagating GWs in a time-varying tidal-wind field and the transient nature of the critical layer induced by a time-varying tidal zonal wind creates favorable conditions for GWs to penetrate their originally expected critical layers. Consequently, GWs have an impact on the background atmosphere at much higher altitudes than expected, which indicates that the dynamical effects of tidal-GW interactions are more complicated than usually taken into account by GW parameterizations in global models.

Modeling polar cap F-region patches using time varying convection

International Nuclear Information System (INIS)

Sojka, J.J.; Bowline, M.D.; Schunk, R.W.; Decker, D.T.; Valladares, C.E.; Sheehan, R.; Anderson, D.N.; Heelis, R.A.

1993-01-01

Here the authors present the results of computerized simulations of the polar cap regions which were able to model the formation of polar cap patches. They used the Utah State University Time-Dependent Ionospheric Model (TDIM) and the Phillips Laboratory (PL) F-region models in this work. By allowing a time varying magnetospheric electric field in the models, they were able to generate the patches. This time varying field generates a convection in the ionosphere. This convection is similar to convective changes observed in the ionosphere at times of southward pointing interplanetary magnetic field, due to changes in the B y component of the IMF

Computing Conditional VaR using Time-varying CopulasComputing Conditional VaR using Time-varying Copulas

Directory of Open Access Journals (Sweden)

Beatriz Vaz de Melo Mendes

2005-12-01

Full Text Available It is now widespread the use of Value-at-Risk (VaR as a canonical measure at risk. Most accurate VaR measures make use of some volatility model such as GARCH-type models. However, the pattern of volatility dynamic of a portfolio follows from the (univariate behavior of the risk assets, as well as from the type and strength of the associations among them. Moreover, the dependence structure among the components may change conditionally t past observations. Some papers have attempted to model this characteristic by assuming a multivariate GARCH model, or by considering the conditional correlation coefficient, or by incorporating some possibility for switches in regimes. In this paper we address this problem using time-varying copulas. Our modeling strategy allows for the margins to follow some FIGARCH type model while the copula dependence structure changes over time.

Flexible Demand Management under Time-Varying Prices

Science.gov (United States)

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

Electromagnetic radiation in a time-varying background medium

NARCIS (Netherlands)

Budko, N.V.

2009-01-01

Analytical solutions are presented for the electromagnetic radiation by an arbitrary pulsed source into a homogeneous time-varying background medium. In the constant-impedance case an explicit radiation formula is obtained for the synchronous permittivity and permeability described by any positive

Housing Cycles in Switzerland - A Time-Varying Approach

OpenAIRE

Drechsel, Dirk

2015-01-01

In light of the strong increase of house prices in Switzerland, we analyze the effects of mortgage rate shocks, changes in the interplay between housing demand and supply and GDP growth on house prices for the time period 1981- 2014. We employ Bayesian time-varying coefficients vector autoregressions to allow different monetary and immigration regimes over time. A number of structural changes, such as regulatory changes in the aftermath of the 1990s real estate crisis, the introduction of fre...

Measurement of periodically varying ECE spectra using a Michelson interferometer

International Nuclear Information System (INIS)

Laurent, L.; Rodriguez, L.; Talvard, M.

1987-01-01

In some tokamak experiments the ECE spectrum is periodically varying. If the modulation frequency is small enough (less than 10 Hz) the plasma can be considered as quasi-stationary during the typical scan time of most of the Michelson interferometers. It is possible to measure simply ECE spectra at different times of the oscillation. We present here a technique which allows to measure smaller fluctuations at larger frequencies. However the analysis requires a large number of periods of oscillation at constant frequency and a scanning mirror moving at constant velocity

Time varying, multivariate volume data reduction

Energy Technology Data Exchange (ETDEWEB)

Ahrens, James P [Los Alamos National Laboratory; Fout, Nathaniel [UC DAVIS; Ma, Kwan - Liu [UC DAVIS

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

A Tentative Application Of Morphological Filters To Time-Varying Images

Science.gov (United States)

Billard, D.; Poquillon, B.

1989-03-01

In this paper, morphological filters, which are commonly used to process either 2D or multidimensional static images, are generalized to the analysis of time-varying image sequence. The introduction of the time dimension induces then interesting prop-erties when designing such spatio-temporal morphological filters. In particular, the specification of spatio-temporal structuring ele-ments (equivalent to time-varying spatial structuring elements) can be adjusted according to the temporal variations of the image sequences to be processed : this allows to derive specific morphological transforms to perform noise filtering or moving objects discrimination on dynamic images viewed by a non-stationary sensor. First, a brief introduction to the basic principles underlying morphological filters will be given. Then, a straightforward gener-alization of these principles to time-varying images will be pro-posed. This will lead us to define spatio-temporal opening and closing and to introduce some of their possible applications to process dynamic images. At last, preliminary results obtained us-ing a natural forward looking infrared (FUR) image sequence are presented.

Projected space-time and varying speed of light

International Nuclear Information System (INIS)

Iovane, G.; Bellucci, S.; Benedetto, E.

2008-01-01

In this paper starting from El Naschie's Cantorian space-time and our model of projected Universe, we consider its properties in connection with varying speed of light. A possible way-out of the related problem is provided by the Fantappie group approach

An Explicit MOT-TD-VIE Solver for Time Varying Media

KAUST Repository

Sayed, Sadeed Bin; Ulku, Huseyin Arda; Bagci, Hakan

2016-01-01

An explicit marching on-in-time (MOT) scheme for solving the time domain electric field integral equation enforced on volumes with time varying dielectric permittivity is proposed. Unknowns of the integral equation and the constitutive relation, i

Epidemic spreading in time-varying community networks.

Science.gov (United States)

Ren, Guangming; Wang, Xingyuan

2014-06-01

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 qc. The epidemic will survive when q > qc and die when q epidemic spreading in complex networks with community structure.

Time-varying Concurrent Risk of Extreme Droughts and Heatwaves in California

Science.gov (United States)

Sarhadi, A.; Diffenbaugh, N. S.; Ausin, M. C.

2016-12-01

Anthropogenic global warming has changed the nature and the risk of extreme climate phenomena such as droughts and heatwaves. The concurrent of these nature-changing climatic extremes may result in intensifying undesirable consequences in terms of human health and destructive effects in water resources. The present study assesses the risk of concurrent extreme droughts and heatwaves under dynamic nonstationary conditions arising from climate change in California. For doing so, a generalized fully Bayesian time-varying multivariate risk framework is proposed evolving through time under dynamic human-induced environment. In this methodology, an extreme, Bayesian, dynamic copula (Gumbel) is developed to model the time-varying dependence structure between the two different climate extremes. The time-varying extreme marginals are previously modeled using a Generalized Extreme Value (GEV) distribution. Bayesian Markov Chain Monte Carlo (MCMC) inference is integrated to estimate parameters of the nonstationary marginals and copula using a Gibbs sampling method. Modelled marginals and copula are then used to develop a fully Bayesian, time-varying joint return period concept for the estimation of concurrent risk. Here we argue that climate change has increased the chance of concurrent droughts and heatwaves over decades in California. It is also demonstrated that a time-varying multivariate perspective should be incorporated to assess realistic concurrent risk of the extremes for water resources planning and management in a changing climate in this area. The proposed generalized methodology can be applied for other stochastic nature-changing compound climate extremes that are under the influence of climate change.

Electricity Futures Prices : Time Varying Sensitivity to Fundamentals

NARCIS (Netherlands)

S-E. Fleten (Stein-Erik); R. Huisman (Ronald); M. Kilic (Mehtap); H.P.G. Pennings (Enrico); S. Westgaard (Sjur)

2014-01-01

textabstractThis paper provides insight in the time-varying relation between electricity futures prices and fundamentals in the form of prices of contracts for fossil fuels. As supply curves are not constant and different producers have different marginal costs of production, we argue that the

Discrete-Time Sliding-Mode Control of Uncertain Systems with Time-Varying Delays via Descriptor Approach

Directory of Open Access Journals (Sweden)

Maode Yan

2008-01-01

Full Text Available This paper considers the problem of robust discrete-time sliding-mode control (DT-SMC design for a class of uncertain linear systems with time-varying delays. By applying a descriptor model transformation and Moon's inequality for bounding cross terms, a delay-dependent sufficient condition for the existence of stable sliding surface is given in terms of linear matrix inequalities (LMIs. Based on this existence condition, the synthesized sliding mode controller can guarantee the sliding-mode reaching condition of the specified discrete-time sliding surface for all admissible uncertainties and time-varying delays. An illustrative example verifies the effectiveness of the proposed method.

Synchronization of uncertain time-varying network based on sliding mode control technique

Science.gov (United States)

Lü, Ling; Li, Chengren; Bai, Suyuan; Li, Gang; Rong, Tingting; Gao, Yan; Yan, Zhe

2017-09-01

We research synchronization of uncertain time-varying network based on sliding mode control technique. The sliding mode control technique is first modified so that it can be applied to network synchronization. Further, by choosing the appropriate sliding surface, the identification law of uncertain parameter, the adaptive law of the time-varying coupling matrix element and the control input of network are designed, it is sure that the uncertain time-varying network can synchronize effectively the synchronization target. At last, we perform some numerical simulations to demonstrate the effectiveness of the proposed results.

Conceptual Modeling of Time-Varying Information

DEFF Research Database (Denmark)

Gregersen, Heidi; Jensen, Christian S.

2004-01-01

A wide range of database applications manage information that varies over time. Many of the underlying database schemas of these were designed using the Entity-Relationship (ER) model. In the research community as well as in industry, it is common knowledge that the temporal aspects of the mini......-world are important, but difficult to capture using the ER model. Several enhancements to the ER model have been proposed in an attempt to support the modeling of temporal aspects of information. Common to the existing temporally extended ER models, few or no specific requirements to the models were given...

A time-varying magnetic flux concentrator

International Nuclear Information System (INIS)

Kibret, B; Premaratne, M; Lewis, P M; Thomson, R; Fitzgerald, P B

2016-01-01

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. (paper)

Electron dynamics in solid state via time varying wavevectors

Science.gov (United States)

Khaneja, Navin

2018-06-01

In this paper, we study electron wavepacket dynamics in electric and magnetic fields. We rigorously derive the semiclassical equations of electron dynamics in electric and magnetic fields. We do it both for free electron and electron in a periodic potential. We do this by introducing time varying wavevectors k(t). In the presence of magnetic field, our wavepacket reproduces the classical cyclotron orbits once the origin of the Schröedinger equation is correctly chosen to be center of cyclotron orbit. In the presence of both electric and magnetic fields, our equations for wavepacket dynamics differ from classical Lorentz force equations. We show that in a periodic potential, on application of electric field, the electron wave function adiabatically follows the wavefunction of a time varying Bloch wavevector k(t), with its energies suitably shifted with time. We derive the effective mass equation and discuss conduction in conductors and insulators.

Time varying determinants of bond flows to emerging markets

Directory of Open Access Journals (Sweden)

Yasemin Erduman

2016-06-01

Full Text Available This paper investigates the time varying nature of the determinants of bond flows with a focus on the global financial crisis period. We estimate a time varying regression model using Bayesian estimation methods, where the posterior distribution is approximated by Gibbs sampling algorithm. Our findings suggest that the interest rate differential is the most significant pull factor of portfolio bond flows, along with the inflation rate, while the growth rate does not play a significant role. Among the push factors, global liquidity is the most important driver of bond flows. It matters the most, when unconventional monetary easing policies were first announced; and its importance as a determinant of portfolio bond flows decreases over time, starting with the Eurozone crisis, and diminishes with the tapering talk. Global risk appetite and the risk perception towards the emerging countries also have relatively small and stable significant effects on bond flows.

Global stabilization of linear continuous time-varying systems with bounded controls

International Nuclear Information System (INIS)

Phat, V.N.

2004-08-01

This paper deals with the problem of global stabilization of a class of linear continuous time-varying systems with bounded controls. Based on the controllability of the nominal system, a sufficient condition for the global stabilizability is proposed without solving any Riccati differential equation. Moreover, we give sufficient conditions for the robust stabilizability of perturbation/uncertain linear time-varying systems with bounded controls. (author)

An integrative time-varying frequency detection and channel sounding method for dynamic plasma sheath

Science.gov (United States)

Shi, Lei; Yao, Bo; Zhao, Lei; Liu, Xiaotong; Yang, Min; Liu, Yanming

2018-01-01

The plasma sheath-surrounded hypersonic vehicle is a dynamic and time-varying medium and it is almost impossible to calculate time-varying physical parameters directly. The in-fight detection of the time-varying degree is important to understand the dynamic nature of the physical parameters and their effect on re-entry communication. In this paper, a constant envelope zero autocorrelation (CAZAC) sequence based on time-varying frequency detection and channel sounding method is proposed to detect the plasma sheath electronic density time-varying property and wireless channel characteristic. The proposed method utilizes the CAZAC sequence, which has excellent autocorrelation and spread gain characteristics, to realize dynamic time-varying detection/channel sounding under low signal-to-noise ratio in the plasma sheath environment. Theoretical simulation under a typical time-varying radio channel shows that the proposed method is capable of detecting time-variation frequency up to 200 kHz and can trace the channel amplitude and phase in the time domain well under -10 dB. Experimental results conducted in the RF modulation discharge plasma device verified the time variation detection ability in practical dynamic plasma sheath. Meanwhile, nonlinear phenomenon of dynamic plasma sheath on communication signal is observed thorough channel sounding result.

Finite-Time Reentry Attitude Control Using Time-Varying Sliding Mode and Disturbance Observer

Directory of Open Access Journals (Sweden)

Xuzhong Wu

2015-01-01

Full Text Available This paper presents the finite-time attitude control problem for reentry vehicle with redundant actuators in consideration of planet uncertainties and external disturbances. Firstly, feedback linearization technique is used to cancel the nonlinearities of equations of motion to construct a basic mode for attitude controller. Secondly, two kinds of time-varying sliding mode control methods with disturbance observer are integrated with the basic mode in order to enhance the control performance and system robustness. One method is designed based on boundary layer technique and the other is a novel second-order sliding model control method. The finite-time stability analyses of both resultant closed-loop systems are carried out. Furthermore, after attitude controller produces the torque commands, an optimization control allocation approach is introduced to allocate them into aerodynamic surface deflections and on-off reaction control system thrusts. Finally, the numerical simulation results demonstrate that both of the time-varying sliding mode control methods are robust to uncertainties and disturbances without chattering phenomenon. Moreover, the proposed second-order sliding mode control method possesses better control accuracy.

Finite-time and fixed-time synchronization analysis of inertial memristive neural networks with time-varying delays.

Science.gov (United States)

Wei, Ruoyu; Cao, Jinde; Alsaedi, Ahmed

2018-02-01

This paper investigates the finite-time synchronization and fixed-time synchronization problems of inertial memristive neural networks with time-varying delays. By utilizing the Filippov discontinuous theory and Lyapunov stability theory, several sufficient conditions are derived to ensure finite-time synchronization of inertial memristive neural networks. Then, for the purpose of making the setting time independent of initial condition, we consider the fixed-time synchronization. A novel criterion guaranteeing the fixed-time synchronization of inertial memristive neural networks is derived. Finally, three examples are provided to demonstrate the effectiveness of our main results.

Method for determining scan timing based on analysis of formation process of the time-density curve

International Nuclear Information System (INIS)

Yamaguchi, Isao; Ishida, Tomokazu; Kidoya, Eiji; Higashimura, Kyoji; Suzuki, Masayuki

2005-01-01

A strict determination of scan timing is needed for dynamic multi-phase scanning and 3D-CT angiography (3D-CTA) by multi-detector row CT (MDCT). In the present study, contrast media arrival time (T AR ) was measured in the abdominal aorta at the bifurcation of the celiac artery for confirmation of circulatory differences in patients. In addition, we analyzed the process of formation of the time-density curve (TDC) and examined factors that affect the time to peak aortic enhancement (T PA ). Mean T AR was 15.57±3.75 s. TDCs were plotted for each duration of injection. The rising portions of TDCs were superimposed on one another. TDCs with longer injection durations were piled up upon one another. Rise angle was approximately constant in response to each flow rate. Rise time (T R ) showed a good correlation with injection duration (T ID ). T R was 1.01 T ID (R 2 =0.994) in the phantom study and 0.94 T lD -0.60 (R 2 =0.988) in the clinical study. In conclusion, for the selection of optimal scan timing it is useful to determine T R at a given point and to determine the time from T AR . (author)

Vector-field statistics for the analysis of time varying clinical gait data.

Science.gov (United States)

Donnelly, C J; Alexander, C; Pataky, T C; Stannage, K; Reid, S; Robinson, M A

2017-01-01

In clinical settings, the time varying analysis of gait data relies heavily on the experience of the individual(s) assessing these biological signals. Though three dimensional kinematics are recognised as time varying waveforms (1D), exploratory statistical analysis of these data are commonly carried out with multiple discrete or 0D dependent variables. In the absence of an a priori 0D hypothesis, clinicians are at risk of making type I and II errors in their analyis of time varying gait signatures in the event statistics are used in concert with prefered subjective clinical assesment methods. The aim of this communication was to determine if vector field waveform statistics were capable of providing quantitative corroboration to practically significant differences in time varying gait signatures as determined by two clinically trained gait experts. The case study was a left hemiplegic Cerebral Palsy (GMFCS I) gait patient following a botulinum toxin (BoNT-A) injection to their left gastrocnemius muscle. When comparing subjective clinical gait assessments between two testers, they were in agreement with each other for 61% of the joint degrees of freedom and phases of motion analysed. For tester 1 and tester 2, they were in agreement with the vector-field analysis for 78% and 53% of the kinematic variables analysed. When the subjective analyses of tester 1 and tester 2 were pooled together and then compared to the vector-field analysis, they were in agreement for 83% of the time varying kinematic variables analysed. These outcomes demonstrate that in principle, vector-field statistics corroborates with what a team of clinical gait experts would classify as practically meaningful pre- versus post time varying kinematic differences. The potential for vector-field statistics to be used as a useful clinical tool for the objective analysis of time varying clinical gait data is established. Future research is recommended to assess the usefulness of vector-field analyses

Time-varying economic dominance in financial markets: A bistable dynamics approach

Science.gov (United States)

He, Xue-Zhong; Li, Kai; Wang, Chuncheng

2018-05-01

By developing a continuous-time heterogeneous agent financial market model of multi-assets traded by fundamental and momentum investors, we provide a potential mechanism for generating time-varying dominance between fundamental and non-fundamental in financial markets. We show that investment constraints lead to the coexistence of a locally stable fundamental steady state and a locally stable limit cycle around the fundamental, characterized by a Bautin bifurcation. This provides a mechanism for market prices to switch stochastically between the two persistent but very different market states, leading to the coexistence and time-varying dominance of seemingly controversial efficient market and price momentum over different time periods. The model also generates other financial market stylized facts, such as spillover effects in both momentum and volatility, market booms, crashes, and correlation reduction due to cross-sectional momentum trading. Empirical evidence based on the U.S. market supports the main findings. The mechanism developed in this paper can be used to characterize time-varying economic dominance in economics and finance in general.

Optimal critic learning for robot control in time-varying environments.

Science.gov (United States)

Wang, Chen; Li, Yanan; Ge, Shuzhi Sam; Lee, Tong Heng

2015-10-01

In this paper, optimal critic learning is developed for robot control in a time-varying environment. The unknown environment is described as a linear system with time-varying parameters, and impedance control is employed for the interaction control. Desired impedance parameters are obtained in the sense of an optimal realization of the composite of trajectory tracking and force regulation. Q -function-based critic learning is developed to determine the optimal impedance parameters without the knowledge of the system dynamics. The simulation results are presented and compared with existing methods, and the efficacy of the proposed method is verified.

Epidemic spreading in time-varying community networks

Energy Technology Data Exchange (ETDEWEB)

Ren, Guangming, E-mail: wangxy@dlut.edu.cn, E-mail: ren-guang-ming@163.com [School of Electronic and Information, Guangdong Polytechnic Normal University, Guangzhou 510665 (China); Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024 (China); Wang, Xingyuan, E-mail: wangxy@dlut.edu.cn, E-mail: ren-guang-ming@163.com [Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024 (China)

2014-06-15

The spreading processes of many infectious diseases have comparable time scale as the network evolution. Here, we present a simple networks model with time-varying community structure, and investigate susceptible-infected-susceptible epidemic spreading processes in this model. By both theoretic analysis and numerical simulations, we show that the efficiency of epidemic spreading in this model depends intensively on the mobility rate q of the individuals among communities. We also find that there exists a mobility rate threshold q{sub c}. The epidemic will survive when q > q{sub c} and die when q < q{sub c}. These results can help understanding the impacts of human travel on the epidemic spreading in complex networks with community structure.

Epidemic spreading in time-varying community networks

International Nuclear Information System (INIS)

Ren, Guangming; Wang, Xingyuan

2014-01-01

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 c . The epidemic will survive when q > q c and die when q  c . These results can help understanding the impacts of human travel on the epidemic spreading in complex networks with community structure

Reducing task-based fMRI scanning time using simultaneous multislice echo planar imaging

Energy Technology Data Exchange (ETDEWEB)

Kiss, Mate [Hungarian Academy of Sciences, Brain Imaging Centre, Research Centre for Natural Sciences, Budapest (Hungary); Janos Szentagothai PhD School, MR Research Centre, Budapest (Hungary); National Institute of Clinical Neuroscience, Department of Neuroradiology, Budapest (Hungary); Hermann, Petra; Vidnyanszky, Zoltan; Gal, Viktor [Hungarian Academy of Sciences, Brain Imaging Centre, Research Centre for Natural Sciences, Budapest (Hungary)

2018-03-15

To maintain alertness and to remain motionless during scanning represent a substantial challenge for patients/subjects involved in both clinical and research functional magnetic resonance imaging (fMRI) examinations. Therefore, availability and application of new data acquisition protocols allowing the shortening of scan time without compromising the data quality and statistical power are of major importance. Higher order category-selective visual cortical areas were identified individually, and rapid event-related fMRI design was used to compare three different sampling rates (TR = 2000, 1000, and 410 ms, using state-of-the-art simultaneous multislice imaging) and four different scanning lengths to match the statistical power of the traditional scanning methods to high sampling-rate design. The results revealed that ∝ 4 min of the scan time with 1 Hz (TR = 1000 ms) sampling rate and ∝ 2 min scanning at ∝ 2.5 Hz (TR = 410 ms) sampling rate provide similar localization sensitivity and selectivity to that obtained with 11-min session at conventional, 0.5 Hz (TR = 2000 ms) sampling rate. Our findings suggest that task-based fMRI examination of clinical population prone to distress such as presurgical mapping experiments might substantially benefit from the reduced (20-40%) scanning time that can be achieved by the application of simultaneous multislice sequences. (orig.)

TIME-VARYING DYNAMICAL STAR FORMATION RATE

Energy Technology Data Exchange (ETDEWEB)

Lee, Eve J.; Chang, Philip; Murray, Norman, E-mail: evelee@berkeley.edu [Canadian Institute for Theoretical Astrophysics, 60 St. George Street, University of Toronto, Toronto, ON M5S 3H8 (Canada)

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.

Time-varying and time-invariant dimensions of depression in children and adolescents: Implications for cross-informant agreement.

Science.gov (United States)

Cole, David A; Martin, Joan M; Jacquez, Farrah M; Tram, Jane M; Zelkowitz, Rachel; Nick, Elizabeth A; Rights, Jason D

2017-07-01

The longitudinal structure of depression in children and adolescents was examined by applying a Trait-State-Occasion structural equation model to 4 waves of self, teacher, peer, and parent reports in 2 age groups (9 to 13 and 13 to 16 years old). Analyses revealed that the depression latent variable consisted of 2 longitudinal factors: a time-invariant dimension that was completely stable over time and a time-varying dimension that was not perfectly stable over time. Different sources of information were differentially sensitive to these 2 dimensions. Among adolescents, self- and parent reports better reflected the time-invariant aspects. For children and adolescents, peer and teacher reports better reflected the time-varying aspects. Relatively high cross-informant agreement emerged for the time-invariant dimension in both children and adolescents. Cross-informant agreement for the time-varying dimension was high for adolescents but very low for children. Implications emerge for theoretical models of depression and for its measurement, especially when attempting to predict changes in depression in the context of longitudinal studies. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

PCA-based detection of damage in time-varying systems

Science.gov (United States)

Bellino, A.; Fasana, A.; Garibaldi, L.; Marchesiello, S.

2010-10-01

When performing Structural Health Monitoring, it is well known that the natural frequencies do not depend only on the damage but also on environmental conditions, such as temperature and humidity. The Principal Component Analysis is used to take this problem into account, because it allows eliminating the effect of external factors. The purpose of the present work is to show that this technique can be successfully used not only for time-invariant systems, but also for time-varying ones. Referring to the latter, one of the most studied systems which shows these characteristics is the bridge with crossing loads, such as the case of the railway bridge studied in present paper; in this case, the mass and the velocity of the train can be considered as "environmental" factors.This paper, after a brief description of the PCA method and one example of its application on time-invariant systems, presents the great potentialities of the methodology when applied to time-varying systems. The results show that this method is able to better detect the presence of damage and also to properly distinguish among different levels of crack depths.

Modelling Conditional and Unconditional Heteroskedasticity with Smoothly Time-Varying Structure

DEFF Research Database (Denmark)

Amado, Christina; Teräsvirta, Timo

multiplier type misspecification tests. Finite-sample properties of these procedures and tests are examined by simulation. An empirical application to daily stock returns and another one to daily exchange rate returns illustrate the functioning and properties of our modelling strategy in practice......In this paper, we propose two parametric alternatives to the standard GARCH model. They allow the conditional variance to have a smooth time-varying structure of either ad- ditive or multiplicative type. The suggested parameterizations describe both nonlinearity and structural change...... in the conditional and unconditional variances where the transition between regimes over time is smooth. A modelling strategy for these new time-varying parameter GARCH models is developed. It relies on a sequence of Lagrange multiplier tests, and the adequacy of the estimated models is investigated by Lagrange...

On the synchronization of neural networks containing time-varying delays and sector nonlinearity

International Nuclear Information System (INIS)

Yan, J.-J.; Lin, J.-S.; Hung, M.-L.; Liao, T.-L.

2007-01-01

We present a systematic design procedure for synchronization of neural networks subject to time-varying delays and sector nonlinearity in the control input. Based on the drive-response concept and the Lyapunov stability theorem, a memoryless decentralized control law is proposed which guarantees exponential synchronization even when input nonlinearity is present. The supplementary requirement that the time-derivative of time-varying delays must be smaller than one is released for the proposed control scheme. A four-dimensional Hopfield neural network with time-varying delays is presented as the illustrative example to demonstrate the effectiveness of the proposed synchronization scheme

Asymptotic stability of discrete-time systems with time-varying delay subject to saturation nonlinearities

International Nuclear Information System (INIS)

Chen, S.-F.

2009-01-01

The asymptotic stability problem for discrete-time systems with time-varying delay subject to saturation nonlinearities is addressed in this paper. In terms of linear matrix inequalities (LMIs), a delay-dependent sufficient condition is derived to ensure the asymptotic stability. A numerical example is given to demonstrate the theoretical results.

Study on scan timing using a test injection method in head CTA

International Nuclear Information System (INIS)

Sekito, Yuichi; Sanada, Hidenori

2005-01-01

In head computed tomographic angiography (CTA), circulation from arterial phase to venous phase is more rapid than that in other regions. Therefore, it is necessary to determine correct scan timing to obtain ideal CTA images. A test injection method makes it possible to set correct scan timing from the time density curve (TDC) for each subject. The method, however, has a weak point that is a time lag in an arrival time at peak point of contrast medium on TDC between the test injection and the primary examination because of the difference in total volume of contrast medium used. The purpose of this study calculated the delay time on the TDC in both scans. We used the test injection method and the bolus tracking method in the primary examination. The average errors in start time (Δt1) and slope change time (Δt2) of the contrast medium on the TDC between test injection and primary examination were 0.15 sec and 3.05 sec, respectively. The results indicated that it was important to grasp the delay time in start time and peak arrival time of the contrast medium between test injection and primary examination to obtain ideal images in head CTA. (author)

Sub-nanosecond time-resolved near-field scanning magneto-optical microscope.

Science.gov (United States)

Rudge, J; Xu, H; Kolthammer, J; Hong, Y K; Choi, B C

2015-02-01

We report on the development of a new magnetic microscope, time-resolved near-field scanning magneto-optical microscope, which combines a near-field scanning optical microscope and magneto-optical contrast. By taking advantage of the high temporal resolution of time-resolved Kerr microscope and the sub-wavelength spatial resolution of a near-field microscope, we achieved a temporal resolution of ∼50 ps and a spatial resolution of microscope, the magnetic field pulse induced gyrotropic vortex dynamics occurring in 1 μm diameter, 20 nm thick CoFeB circular disks has been investigated. The microscope provides sub-wavelength resolution magnetic images of the gyrotropic motion of the vortex core at a resonance frequency of ∼240 MHz.

Testing and estimating time-varying elasticities of Swiss gasoline demand

International Nuclear Information System (INIS)

Neto, David

2012-01-01

This paper is intended to test and estimate time-varying elasticities for gasoline demand in Switzerland. For this purpose, a smooth time-varying cointegrating parameters model is investigated in order to describe smooth mutations of the Swiss gasoline demand. The methodology, based on Chebyshev polynomials, is rigorously outlined. Our empirical finding states that the time-invariance assumption does not hold for long-run price and income elasticities. Furthermore they highlight that gasoline demand passed through some periods of sensitivity and non sensitivity with respect to the price. Our empirical statements are of great importance to assess the performance of a gasoline tax as an instrument for CO 2 reduction policy. Indeed, such an instrument can contribute to reduce emissions of greenhouse gases only if the demand is not fully inelastic with respect to the price. Our results suggest that such a carbon-tax would not be always suitable since the price elasticity is found not stable over time and not always significant.

Time-Varying Biased Proportional Guidance with Seeker’s Field-of-View Limit

OpenAIRE

Yang, Zhe; Wang, Hui; Lin, Defu

2016-01-01

Traditional guidance laws with range-to-go information or time-to-go estimation may not be implemented in passive homing missiles since passive seekers cannot measure relative range directly. A time-varying biased proportional guidance law, which only uses line-of-sight (LOS) rate and look angle information, is proposed to satisfy both impact angle constraint and seeker’s field-of-view (FOV) limit. In the proposed guidance law, two time-varying bias terms are applied to divide the trajectory ...

Simple Model with Time-Varying Fine-Structure ``Constant''

Science.gov (United States)

Berman, M. S.

2009-10-01

Extending the original version written in colaboration with L.A. Trevisan, we study the generalisation of Dirac's LNH, so that time-variation of the fine-structure constant, due to varying electrical and magnetic permittivities is included along with other variations (cosmological and gravitational ``constants''), etc. We consider the present Universe, and also an inflationary scenario. Rotation of the Universe is a given possibility in this model.

Scattering of a TEM wave from a time varying surface

Science.gov (United States)

Elcrat, Alan R.; Harder, T. Mark; Stonebraker, John T.

1990-03-01

A solution is given for reflection of a plane wave with TEM polarization from a planar surface with time varying properties. These properties are given in terms of the currents on the surface. The solution is obtained by numerically solving a system of differential-delay equations in the time domain.

Contact Dynamics of EHL Contacts under Time Varying Conditions

NARCIS (Netherlands)

Venner, Cornelis H.; Popovici, G.; Wijnant, Ysbrand H.; Dalmaz, G.; Lubrecht, A.A.; Priest, M

2004-01-01

By means of numerical simulations of two situations with time varying operating conditions it is shown that the dynamic behaviour of Elasto-Hydrodynamically Lubricated contacts in terms of vibrations can be characterized as: Changes in the mutual approach lead to film thickness changes in the inlet

The extinction probability in systems randomly varying in time

Directory of Open Access Journals (Sweden)

Imre Pázsit

2017-09-01

Full Text Available The extinction probability of a branching process (a neutron chain in a multiplying medium is calculated for a system randomly varying in time. The evolution of the first two moments of such a process was calculated previously by the authors in a system randomly shifting between two states of different multiplication properties. The same model is used here for the investigation of the extinction probability. It is seen that the determination of the extinction probability is significantly more complicated than that of the moments, and it can only be achieved by pure numerical methods. The numerical results indicate that for systems fluctuating between two subcritical or two supercritical states, the extinction probability behaves as expected, but for systems fluctuating between a supercritical and a subcritical state, there is a crucial and unexpected deviation from the predicted behaviour. The results bear some significance not only for neutron chains in a multiplying medium, but also for the evolution of biological populations in a time-varying environment.

Reconstruction of a time-averaged midposition CT scan for radiotherapy planning of lung cancer patients using deformable registration.

Science.gov (United States)

Wolthaus, J W H; Sonke, J J; van Herk, M; Damen, E M F

2008-09-01

lower lobe lung tumors move with amplitudes of up to 2 cm due to respiration. To reduce respiration imaging artifacts in planning CT scans, 4D imaging techniques are used. Currently, we use a single (midventilation) frame of the 4D data set for clinical delineation of structures and radiotherapy planning. A single frame, however, often contains artifacts due to breathing irregularities, and is noisier than a conventional CT scan since the exposure per frame is lower. Moreover, the tumor may be displaced from the mean tumor position due to hysteresis. The aim of this work is to develop a framework for the acquisition of a good quality scan representing all scanned anatomy in the mean position by averaging transformed (deformed) CT frames, i.e., canceling out motion. A nonrigid registration method is necessary since motion varies over the lung. 4D and inspiration breath-hold (BH) CT scans were acquired for 13 patients. An iterative multiscale motion estimation technique was applied to the 4D CT scan, similar to optical flow but using image phase (gray-value transitions from bright to dark and vice versa) instead. From the (4D) deformation vector field (DVF) derived, the local mean position in the respiratory cycle was computed and the 4D DVF was modified to deform all structures of the original 4D CT scan to this mean position. A 3D midposition (MidP) CT scan was then obtained by (arithmetic or median) averaging of the deformed 4D CT scan. Image registration accuracy, tumor shape deviation with respect to the BH CT scan, and noise were determined to evaluate the image fidelity of the MidP CT scan and the performance of the technique. Accuracy of the used deformable image registration method was comparable to established automated locally rigid registration and to manual landmark registration (average difference to both methods noise of individual 4D CT scan frames. We implemented an accurate method to estimate the motion of structures in a 4D CT scan. Subsequently, a

Tolerable Time-Varying Overflow on Grass-Covered Slopes

Directory of Open Access Journals (Sweden)

Steven A. Hughes

2015-03-01

Full Text Available Engineers require estimates of tolerable overtopping limits for grass-covered levees, dikes, and embankments that might experience steady overflow. Realistic tolerance estimates can be used for both resilient design and risk assessment. A simple framework is developed for estimating tolerable overtopping on grass-covered slopes caused by slowly-varying (in time overtopping discharge (e.g., events like storm surges or river flood waves. The framework adapts the well-known Hewlett curves of tolerable limiting velocity as a function of overflow duration. It has been hypothesized that the form of the Hewlett curves suggests that the grass erosion process is governed by the flow work on the slope above a critical threshold velocity (referred to as excess work, and the tolerable erosional limit is reached when the cumulative excess work exceeds a given value determined from the time-dependent Hewlett curves. The cumulative excess work is expressed in terms of overflow discharge above a critical discharge that slowly varies in time, similar to a discharge hydrograph. The methodology is easily applied using forecast storm surge hydrographs at specific locations where wave action is minimal. For preliminary planning purposes, when storm surge hydrographs are unavailable, hypothetical equations for the water level and overflow discharge hydrographs are proposed in terms of the values at maximum overflow and the total duration of overflow. An example application is given to illustrate use of the methodology.

Finite-Time H∞ Filtering for Linear Continuous Time-Varying Systems with Uncertain Observations

Directory of Open Access Journals (Sweden)

Huihong Zhao

2012-01-01

Full Text Available This paper is concerned with the finite-time H∞ filtering problem for linear continuous time-varying systems with uncertain observations and ℒ2-norm bounded noise. The design of finite-time H∞ filter is equivalent to the problem that a certain indefinite quadratic form has a minimum and the filter is such that the minimum is positive. The quadratic form is related to a Krein state-space model according to the Krein space linear estimation theory. By using the projection theory in Krein space, the finite-time H∞ filtering problem is solved. A numerical example is given to illustrate the performance of the H∞ filter.

Scanning-time evaluation of Digimarc Barcode

Science.gov (United States)

Gerlach, Rebecca; Pinard, Dan; Weaver, Matt; Alattar, Adnan

2015-03-01

This paper presents a speed comparison between the use of Digimarc® Barcodes and the Universal Product Code (UPC) for customer checkout at point of sale (POS). The recently introduced Digimarc Barcode promises to increase the speed of scanning packaged goods at POS. When this increase is exploited by workforce optimization systems, the retail industry could potentially save billions of dollars. The Digimarc Barcode is based on Digimarc's watermarking technology, and it is imperceptible, very robust, and does not require any special ink, material, or printing processes. Using an image-based scanner, a checker can quickly scan consumer packaged goods (CPG) embedded with the Digimarc Barcode without the need to reorient the packages with respect to the scanner. Faster scanning of packages saves money and enhances customer satisfaction. It reduces the length of the queues at checkout, reduces the cost of cashier labor, and makes self-checkout more convenient. This paper quantifies the increase in POS scanning rates resulting from the use of the Digimarc Barcode versus the traditional UPC. It explains the testing methodology, describes the experimental setup, and analyzes the obtained results. It concludes that the Digimarc Barcode increases number of items per minute (IPM) scanned at least 50% over traditional UPC.

Two-dimensional phononic crystals with time-varying properties: a multiple scattering analysis

International Nuclear Information System (INIS)

Wright, D W; Cobbold, R S C

2010-01-01

Multiple scattering theory is a versatile two- and three-dimensional method for characterizing the acoustic wave transmission through many scatterers. It provides analytical solutions to wave propagation in scattering structures, and its computational complexity grows logarithmically with the number of scatterers. In this paper we show how the 2D method can be adapted to include the effects of time-varying material parameters. Specifically, a new T-matrix is defined to include the effects of frequency modulation that occurs in time-varying phononic crystals. Solutions were verified against finite difference time domain (FDTD) simulations and showed excellent agreement. This new method enables fast characterization of time-varying phononic crystals without the need to resort to lengthy FDTD simulations. Also, the method of combining T-matrices to form the T-supermatrix remains unchanged provided that the new matrix definitions are used. The method is quite compatible with existing implementations of multiple scattering theory and could be readily extended to three-dimensional multiple scattering theory

Time-varying output performances of piezoelectric vibration energy harvesting under nonstationary random vibrations

Science.gov (United States)

Yoon, Heonjun; Kim, Miso; Park, Choon-Su; Youn, Byeng D.

2018-01-01

Piezoelectric vibration energy harvesting (PVEH) has received much attention as a potential solution that could ultimately realize self-powered wireless sensor networks. Since most ambient vibrations in nature are inherently random and nonstationary, the output performances of PVEH devices also randomly change with time. However, little attention has been paid to investigating the randomly time-varying electroelastic behaviors of PVEH systems both analytically and experimentally. The objective of this study is thus to make a step forward towards a deep understanding of the time-varying performances of PVEH devices under nonstationary random vibrations. Two typical cases of nonstationary random vibration signals are considered: (1) randomly-varying amplitude (amplitude modulation; AM) and (2) randomly-varying amplitude with randomly-varying instantaneous frequency (amplitude and frequency modulation; AM-FM). In both cases, this study pursues well-balanced correlations of analytical predictions and experimental observations to deduce the relationships between the time-varying output performances of the PVEH device and two primary input parameters, such as a central frequency and an external electrical resistance. We introduce three correlation metrics to quantitatively compare analytical prediction and experimental observation, including the normalized root mean square error, the correlation coefficient, and the weighted integrated factor. Analytical predictions are in an excellent agreement with experimental observations both mechanically and electrically. This study provides insightful guidelines for designing PVEH devices to reliably generate electric power under nonstationary random vibrations.

Time-varying effect moderation using the structural nested mean model: estimation using inverse-weighted regression with residuals

Science.gov (United States)

Almirall, Daniel; Griffin, Beth Ann; McCaffrey, Daniel F.; Ramchand, Rajeev; Yuen, Robert A.; Murphy, Susan A.

2014-01-01

This article considers the problem of examining time-varying causal effect moderation using observational, longitudinal data in which treatment, candidate moderators, and possible confounders are time varying. The structural nested mean model (SNMM) is used to specify the moderated time-varying causal effects of interest in a conditional mean model for a continuous response given time-varying treatments and moderators. We present an easy-to-use estimator of the SNMM that combines an existing regression-with-residuals (RR) approach with an inverse-probability-of-treatment weighting (IPTW) strategy. The RR approach has been shown to identify the moderated time-varying causal effects if the time-varying moderators are also the sole time-varying confounders. The proposed IPTW+RR approach provides estimators of the moderated time-varying causal effects in the SNMM in the presence of an additional, auxiliary set of known and measured time-varying confounders. We use a small simulation experiment to compare IPTW+RR versus the traditional regression approach and to compare small and large sample properties of asymptotic versus bootstrap estimators of the standard errors for the IPTW+RR approach. This article clarifies the distinction between time-varying moderators and time-varying confounders. We illustrate the methodology in a case study to assess if time-varying substance use moderates treatment effects on future substance use. PMID:23873437

Identification of Time Varying Civil Engineering Structures using Multivariate Recursive Time Domain Models

DEFF Research Database (Denmark)

Andersen, P.; Skjærbæk, P. S.; Kirkegaard, Poul Henning

with the smoothed quanties which have been obtained from SARCOF. The results show the usefulness of the technique for identification of a time varying civil engineering structure. It is found that all the techniques give reliable estiates of the frequencies of the two lowest modes and the first mode shape. Only...

Stochastic analysis of epidemics on adaptive time varying networks

Science.gov (United States)

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.

Non-Cartesian MRI scan time reduction through sparse sampling

NARCIS (Netherlands)

Wajer, F.T.A.W.

2001-01-01

Non-Cartesian MRI Scan-Time Reduction through Sparse Sampling Magnetic resonance imaging (MRI) signals are measured in the Fourier domain, also called k-space. Samples of the MRI signal can not be taken at will, but lie along k-space trajectories determined by the magnetic field gradients. MRI

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

Science.gov (United States)

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.

Adaptive Neural Network Control for Nonlinear Hydraulic Servo-System with Time-Varying State Constraints

Directory of Open Access Journals (Sweden)

Shu-Min Lu

2017-01-01

Full Text Available An adaptive neural network control problem is addressed for a class of nonlinear hydraulic servo-systems with time-varying state constraints. In view of the low precision problem of the traditional hydraulic servo-system which is caused by the tracking errors surpassing appropriate bound, the previous works have shown that the constraint for the system is a good way to solve the low precision problem. Meanwhile, compared with constant constraints, the time-varying state constraints are more general in the actual systems. Therefore, when the states of the system are forced to obey bounded time-varying constraint conditions, the high precision tracking performance of the system can be easily realized. In order to achieve this goal, the time-varying barrier Lyapunov function (TVBLF is used to prevent the states from violating time-varying constraints. By the backstepping design, the adaptive controller will be obtained. A radial basis function neural network (RBFNN is used to estimate the uncertainties. Based on analyzing the stability of the hydraulic servo-system, we show that the error signals are bounded in the compacts sets; the time-varying state constrains are never violated and all singles of the hydraulic servo-system are bounded. The simulation and experimental results show that the tracking accuracy of system is improved and the controller has fast tracking ability and strong robustness.

Endogenous time-varying risk aversion and asset returns.

Science.gov (United States)

Berardi, Michele

2016-01-01

Stylized facts about statistical properties for short horizon returns in financial markets have been identified in the literature, but a satisfactory understanding for their manifestation is yet to be achieved. In this work, we show that a simple asset pricing model with representative agent is able to generate time series of returns that replicate such stylized facts if the risk aversion coefficient is allowed to change endogenously over time in response to unexpected excess returns under evolutionary forces. The same model, under constant risk aversion, would instead generate returns that are essentially Gaussian. We conclude that an endogenous time-varying risk aversion represents a very parsimonious way to make the model match real data on key statistical properties, and therefore deserves careful consideration from economists and practitioners alike.

Estimating time-varying exposure-outcome associations using case-control data: logistic and case-cohort analyses.

Science.gov (United States)

Keogh, Ruth H; Mangtani, Punam; Rodrigues, Laura; Nguipdop Djomo, Patrick

2016-01-05

Traditional analyses of standard case-control studies using logistic regression do not allow estimation of time-varying associations between exposures and the outcome. We present two approaches which allow this. The motivation is a study of vaccine efficacy as a function of time since vaccination. Our first approach is to estimate time-varying exposure-outcome associations by fitting a series of logistic regressions within successive time periods, reusing controls across periods. Our second approach treats the case-control sample as a case-cohort study, with the controls forming the subcohort. In the case-cohort analysis, controls contribute information at all times they are at risk. Extensions allow left truncation, frequency matching and, using the case-cohort analysis, time-varying exposures. Simulations are used to investigate the methods. The simulation results show that both methods give correct estimates of time-varying effects of exposures using standard case-control data. Using the logistic approach there are efficiency gains by reusing controls over time and care should be taken over the definition of controls within time periods. However, using the case-cohort analysis there is no ambiguity over the definition of controls. The performance of the two analyses is very similar when controls are used most efficiently under the logistic approach. Using our methods, case-control studies can be used to estimate time-varying exposure-outcome associations where they may not previously have been considered. The case-cohort analysis has several advantages, including that it allows estimation of time-varying associations as a continuous function of time, while the logistic regression approach is restricted to assuming a step function form for the time-varying association.

Structural nested mean models for assessing time-varying effect moderation.

Science.gov (United States)

Almirall, Daniel; Ten Have, Thomas; Murphy, Susan A

2010-03-01

This article considers the problem of assessing causal effect moderation in longitudinal settings in which treatment (or exposure) is time varying and so are the covariates said to moderate its effect. Intermediate causal effects that describe time-varying causal effects of treatment conditional on past covariate history are introduced and considered as part of Robins' structural nested mean model. Two estimators of the intermediate causal effects, and their standard errors, are presented and discussed: The first is a proposed two-stage regression estimator. The second is Robins' G-estimator. The results of a small simulation study that begins to shed light on the small versus large sample performance of the estimators, and on the bias-variance trade-off between the two estimators are presented. The methodology is illustrated using longitudinal data from a depression study.

Time to Computerized Tomography Scan, Age, and Mortality in Acute Stroke.

Science.gov (United States)

Myint, Phyo Kyaw; Kidd, Andrew C; Kwok, Chun Shing; Musgrave, Stanley D; Redmayne, Oliver; Metcalf, Anthony K; Ngeh, Joseph; Nicolson, Anne; Owusu-Agyei, Peter; Shekhar, Raj; Walsh, Kevin; Day, Diana J; Warburton, Elizabeth A; Bachmann, Max O; Potter, John F

2016-12-01

Time to computerized tomography (CT) is important to institute appropriate and timely hyperacute management in stroke. We aimed to evaluate mortality outcomes in relation to age and time to CT scan. We used routinely collected data in 8 National Health Service trusts in East of England between September 2008 and April 2011. Stroke cases were prospectively identified and confirmed. Odds ratios (ORs) for unadjusted and adjusted models for age categories (24 hours) and in-hospital and early (<7 days) mortality outcomes were calculated. Of the 7693 patients (mean age 76.1 years, 50% male) included, 1151 (16%) died as inpatients and 336 (4%) died within 7 days. Older patients and those admitted from care home had a significantly longer time from admission until CT (P < .001). Patients who had earlier CT scans were admitted to stroke units more frequently (P < .001) but had higher in-patient (P < .001) and 7-day mortality (P < .001). Whereas older age was associated with increased odds of mortality outcomes, longer time to CT was associated with significantly reduced mortality within 7 days (corresponding ORs for the above time periods were 1.00, .61 [95% confidence interval {CI}: .39-.95], .39 [.24-.64], and .16 [.08-.33]) and in-hospital mortality (ORs 1.00, .86 [.64-1.15], .57 [.42-.78] and .71 [.52-.98]). Older age was associated with a significantly longer time to CT. However, using CT scan time as a benchmarking tool in stroke may have inherent limitations and does not appear to be a suitable quality marker. Copyright © 2016 National Stroke Association. Published by Elsevier Inc. All rights reserved.

P-scan, a new system for ultrasonic weld inspection

International Nuclear Information System (INIS)

Lund, S.A.; Iversen, S.E.; Holst, H.

1978-01-01

The P-scan method is explained. It is described how the new P-scan system improves the ultrasonic method by adding means for visualization, data storage and documentation. Three different scanners are described: One designed for manual operation, another for automatic operation and a third for semiautomatic operation. The p'scan image of an ultrasonically examined test plate is presented and discussed. The variable Display Level (i.e. the inspection sensitivity) facility is described. The main advantage of this facility is the fact that the level can be varied at any time after the inspection. (orig.) [de

Local inertial oscillations in the surface ocean generated by time-varying winds

Science.gov (United States)

Chen, Shengli; Polton, Jeff A.; Hu, Jianyu; Xing, Jiuxing

2015-12-01

A new relationship is presented to give a review study on the evolution of inertial oscillations in the surface ocean locally generated by time-varying wind stress. The inertial oscillation is expressed as the superposition of a previous oscillation and a newly generated oscillation, which depends upon the time-varying wind stress. This relationship is employed to investigate some idealized wind change events. For a wind series varying temporally with different rates, the induced inertial oscillation is dominated by the wind with the greatest variation. The resonant wind, which rotates anti-cyclonically at the local inertial frequency with time, produces maximal amplitude of inertial oscillations, which grows monotonically. For the wind rotating at non-inertial frequencies, the responses vary periodically, with wind injecting inertial energy when it is in phase with the currents, but removing inertial energy when it is out of phase. The wind rotating anti-cyclonically with time is much more favorable to generate inertial oscillations than the cyclonic rotating wind. The wind with a frequency closer to the inertial frequency generates stronger inertial oscillations. For a diurnal wind, the induced inertial oscillation is dependent on latitude and is most significant at 30 °. This relationship is also applied to examine idealized moving cyclones. The inertial oscillation is much stronger on the right-hand side of the cyclone path than on the left-hand side (in the northern hemisphere). This is due to the wind being anti-cyclonic with time on the right-hand side, but cyclonic on the other side. The inertial oscillation varies with the cyclone translation speed. The optimal translation speed generating the greatest inertial oscillations is 2 m/s at the latitude of 10 ° and gradually increases to 6 m/s at the latitude of 30 °.

Network Coded Cooperation Over Time-Varying Channels

DEFF Research Database (Denmark)

Khamfroush, Hana; Roetter, Daniel Enrique Lucani; Barros, João

2014-01-01

transmissions, e.g., in terms of the rate of packet transmission or the energy consumption. A comprehensive analysis of the MDP solution is carried out under different network conditions to extract optimal rules of packet transmission. Inspired by the extracted rules, we propose two near-optimal heuristics......In this paper, we investigate the optimal design of cooperative network-coded strategies for a three-node wireless network with time-varying, half-duplex erasure channels. To this end, we formulate the problem of minimizing the total cost of transmitting M packets from source to two receivers...... as a Markov Decision Process (MDP). The actions of the MDP model include the source and the type of transmission to be used in a given time slot given perfect knowledge of the system state. The cost of packet transmission is defined such that it can incorporate the difference between broadcast and unicast...

A behavioral asset pricing model with a time-varying second moment

International Nuclear Information System (INIS)

Chiarella, Carl; He Xuezhong; Wang, Duo

2006-01-01

We develop a simple behavioral asset pricing model with fundamentalists and chartists in order to study price behavior in financial markets when chartists estimate both conditional mean and variance by using a weighted averaging process. Through a stability, bifurcation, and normal form analysis, the market impact of the weighting process and time-varying second moment are examined. It is found that the fundamental price becomes stable (unstable) when the activities from both types of traders are balanced (unbalanced). When the fundamental price becomes unstable, the weighting process leads to different price dynamics, depending on whether the chartists act as either trend followers or contrarians. It is also found that a time-varying second moment of the chartists does not change the stability of the fundamental price, but it does influence the stability of the bifurcations. The bifurcation becomes stable (unstable) when the chartists are more (less) concerned about the market risk characterized by the time-varying second moment. Different routes to complicated price dynamics are also observed. The analysis provides an analytical foundation for the statistical analysis of the corresponding stochastic version of this type of behavioral model

Estimating time-varying exposure-outcome associations using case-control data: logistic and case-cohort analyses

Directory of Open Access Journals (Sweden)

Ruth H. Keogh

2016-01-01

Full Text Available Abstract Background Traditional analyses of standard case-control studies using logistic regression do not allow estimation of time-varying associations between exposures and the outcome. We present two approaches which allow this. The motivation is a study of vaccine efficacy as a function of time since vaccination. Methods Our first approach is to estimate time-varying exposure-outcome associations by fitting a series of logistic regressions within successive time periods, reusing controls across periods. Our second approach treats the case-control sample as a case-cohort study, with the controls forming the subcohort. In the case-cohort analysis, controls contribute information at all times they are at risk. Extensions allow left truncation, frequency matching and, using the case-cohort analysis, time-varying exposures. Simulations are used to investigate the methods. Results The simulation results show that both methods give correct estimates of time-varying effects of exposures using standard case-control data. Using the logistic approach there are efficiency gains by reusing controls over time and care should be taken over the definition of controls within time periods. However, using the case-cohort analysis there is no ambiguity over the definition of controls. The performance of the two analyses is very similar when controls are used most efficiently under the logistic approach. Conclusions Using our methods, case-control studies can be used to estimate time-varying exposure-outcome associations where they may not previously have been considered. The case-cohort analysis has several advantages, including that it allows estimation of time-varying associations as a continuous function of time, while the logistic regression approach is restricted to assuming a step function form for the time-varying association.

Does aspiration of bones and joints affect results of later bone scanning

International Nuclear Information System (INIS)

Canale, S.T.; Harkness, R.M.; Thomas, P.A.; Massie, J.D.

1985-01-01

To determine the effect, if any, of needle aspiration on /sup 99m/Tc bone scanning, three different areas of 15 dogs were first aspirated and then imaged with technetium bone scintigraphy. The hip joint was aspirated, the distal femoral metaphysis was drilled and aspirated, and the tibial periosteum was scraped with an 18- or 20-gauge needle. Varying amounts of trauma were inflicted to simulate varying difficulties at aspiration. /sup 99m/Tc bone scans were obtained from 5 h to 10 days later. There was no evidence of focal technetium uptake after any hip joint aspiration. This was consistent regardless of the amount of trauma inflicted or the time from aspiration to bone scanning. Metaphyseal cortical drilling and tibial periosteal scraping occasionally caused some focal uptake when scanning was delayed greater than 2 days. When osteomyelitis or pyarthrosis is clinically suspected, joint aspiration can be performed without fear of producing a false- positive bone scan

Robust stabilisation of time-varying delay systems with probabilistic uncertainties

Science.gov (United States)

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.

Robust Stabilization of Discrete-Time Systems with Time-Varying Delay: An LMI Approach

Directory of Open Access Journals (Sweden)

Valter J. S. Leite

2008-01-01

Full Text Available Sufficient linear matrix inequality (LMI conditions to verify the robust stability and to design robust state feedback gains for the class of linear discrete-time systems with time-varying delay and polytopic uncertainties are presented. The conditions are obtained through parameter-dependent Lyapunov-Krasovskii functionals and use some extra variables, which yield less conservative LMI conditions. Both problems, robust stability analysis and robust synthesis, are formulated as convex problems where all system matrices can be affected by uncertainty. Some numerical examples are presented to illustrate the advantages of the proposed LMI conditions.

The optimal manufacturing batch size with rework under time-varying demand process for a finite time horizon

Science.gov (United States)

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.

Robust stability analysis of uncertain stochastic neural networks with interval time-varying delay

International Nuclear Information System (INIS)

Feng Wei; Yang, Simon X.; Fu Wei; Wu Haixia

2009-01-01

This paper addresses the stability analysis problem for uncertain stochastic neural networks with interval time-varying delays. The parameter uncertainties are assumed to be norm bounded, and the delay factor is assumed to be time-varying and belong to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. A sufficient condition is derived such that for all admissible uncertainties, the considered neural network is robustly, globally, asymptotically stable in the mean square. Some stability criteria are formulated by means of the feasibility of a linear matrix inequality (LMI), which can be effectively solved by some standard numerical packages. Finally, numerical examples are provided to demonstrate the usefulness of the proposed criteria.

Nonlinearly Activated Neural Network for Solving Time-Varying Complex Sylvester Equation.

Science.gov (United States)

Li, Shuai; Li, Yangming

2013-10-28

The Sylvester equation is often encountered in mathematics and control theory. For the general time-invariant Sylvester equation problem, which is defined in the domain of complex numbers, the Bartels-Stewart algorithm and its extensions are effective and widely used with an O(n³) time complexity. When applied to solving the time-varying Sylvester equation, the computation burden increases intensively with the decrease of sampling period and cannot satisfy continuous realtime calculation requirements. For the special case of the general Sylvester equation problem defined in the domain of real numbers, gradient-based recurrent neural networks are able to solve the time-varying Sylvester equation in real time, but there always exists an estimation error while a recently proposed recurrent neural network by Zhang et al [this type of neural network is called Zhang neural network (ZNN)] converges to the solution ideally. The advancements in complex-valued neural networks cast light to extend the existing real-valued ZNN for solving the time-varying real-valued Sylvester equation to its counterpart in the domain of complex numbers. In this paper, a complex-valued ZNN for solving the complex-valued Sylvester equation problem is investigated and the global convergence of the neural network is proven with the proposed nonlinear complex-valued activation functions. Moreover, a special type of activation function with a core function, called sign-bi-power function, is proven to enable the ZNN to converge in finite time, which further enhances its advantage in online processing. In this case, the upper bound of the convergence time is also derived analytically. Simulations are performed to evaluate and compare the performance of the neural network with different parameters and activation functions. Both theoretical analysis and numerical simulations validate the effectiveness of the proposed method.

Delay-Dependent Exponential Stability for Discrete-Time BAM Neural Networks with Time-Varying Delays

Directory of Open Access Journals (Sweden)

Yonggang Chen

2008-01-01

Full Text Available This paper considers the delay-dependent exponential stability for discrete-time BAM neural networks with time-varying delays. By constructing the new Lyapunov functional, the improved delay-dependent exponential stability criterion is derived in terms of linear matrix inequality (LMI. Moreover, in order to reduce the conservativeness, some slack matrices are introduced in this paper. Two numerical examples are presented to show the effectiveness and less conservativeness of the proposed method.

Sojourn time asymptotics in Processor Sharing queues with varying service rate

NARCIS (Netherlands)

Egorova, R.; Mandjes, M.R.H.; Zwart, B.

2007-01-01

Abstract This paper addresses the sojourn time asymptotics for a GI/GI/⋅ queue operating under the Processor Sharing (PS) discipline with stochastically varying service rate. Our focus is on the logarithmic estimates of the tail of sojourn-time distribution, under the assumption that the job-size

A Method of Time-Varying Rayleigh Channel Tracking in MIMO Radio System

Institute of Scientific and Technical Information of China (English)

GONG Yan-fei; HE Zi-shu; HAN Chun-lin

2005-01-01

A method of MIMO channel tracking based on Kalman filter and MMSE-DFE is proposed. The Kalman filter tracks the time-varying channel by using the MMSE-DFE decision and the MMSE-DFE conducts the next decision by using the channel estimates produced by the Kalman filter. Polynomial fitting is used to bridge the gap between the channel estimates produced by the Kalman filter and those needed for the DFE decision. Computer simulation demonstrates that this method can track the MIMO time-varying channel effectively.

Models of quality-adjusted life years when health varies over time

DEFF Research Database (Denmark)

Hansen, Kristian Schultz; Østerdal, Lars Peter Raahave

2006-01-01

Qualityadjusted life year (QALY) models are widely used for economic evaluation in the health care sector. In the first part of the paper, we establish an overview of QALY models where health varies over time and provide a theoretical analysis of model identification and parameter estimation from...... time tradeoff (TTO) and standard gamble (SG) scores. We investigate deterministic and probabilistic models and consider five different families of discounting functions in all. The second part of the paper discusses four issues recurrently debated in the literature. This discussion includes questioning...... of these two can be used to disentangle risk aversion from discounting. We find that caution must be taken when drawing conclusions from models with chronic health states to situations where health varies over time. One notable difference is that in the former case, risk aversion may be indistinguishable from...

Time-varying causality between energy consumption, CO2 emissions, and economic growth: evidence from US states.

Science.gov (United States)

Tzeremes, Panayiotis

2018-02-01

This study is the first attempt to investigate the relationship between CO 2 emissions, energy consumption, and economic growth at a state level, for the 50 US states, through a time-varying causality approach using annual data over the periods 1960-2010. The time-varying causality test facilitates the better understanding of the causal relationship between the covariates owing to the fact that it might identify causalities when the time-constant hypothesis is rejected. Our findings indicate the existence of a time-varying causality at the state level. Specifically, the results probe eight bidirectional time-varying causalities between energy consumption and CO 2 emission, six cases of two-way time-varying causalities between economic growth and energy consumption, and five bidirectional time-varying causalities between economic growth and CO 2 emission. Moreover, we examine the traditional environmental Kuznets curve hypothesis for the states. Notably, our results do not endorse the validity of the EKC, albeit the majority of states support an inverted N-shaped relationship. Lastly, we can identify multiple policy implications based on the empirical results.

Multi-disciplinary techniques for understanding time-varying space-based imagery

Science.gov (United States)

Casasent, D.; Sanderson, A.; Kanade, T.

1984-06-01

A multidisciplinary program for space-based image processing is reported. This project combines optical and digital processing techniques and pattern recognition, image understanding and artificial intelligence methodologies. Time change image processing was recognized as the key issue to be addressed. Three time change scenarios were defined based on the frame rate of the data change. This report details the recent research on: various statistical and deterministic image features, recognition of sub-pixel targets in time varying imagery, and 3-D object modeling and recognition.

Robustness analysis of the Zhang neural network for online time-varying quadratic optimization

International Nuclear Information System (INIS)

Zhang Yunong; Ruan Gongqin; Li Kene; Yang Yiwen

2010-01-01

A general type of recurrent neural network (termed as Zhang neural network, ZNN) has recently been proposed by Zhang et al for the online solution of time-varying quadratic-minimization (QM) and quadratic-programming (QP) problems. Global exponential convergence of the ZNN could be achieved theoretically in an ideal error-free situation. In this paper, with the normal differentiation and dynamics-implementation errors considered, the robustness properties of the ZNN model are investigated for solving these time-varying problems. In addition, linear activation functions and power-sigmoid activation functions could be applied to such a perturbed ZNN model. Both theoretical-analysis and computer-simulation results demonstrate the good ZNN robustness and superior performance for online time-varying QM and QP problem solving, especially when using power-sigmoid activation functions.

Topology preserving non-rigid image registration using time-varying elasticity model for MRI brain volumes.

Science.gov (United States)

Ahmad, Sahar; Khan, Muhammad Faisal

2015-12-01

In this paper, we present a new non-rigid image registration method that imposes a topology preservation constraint on the deformation. We propose to incorporate the time varying elasticity model into the deformable image matching procedure and constrain the Jacobian determinant of the transformation over the entire image domain. The motion of elastic bodies is governed by a hyperbolic partial differential equation, generally termed as elastodynamics wave equation, which we propose to use as a deformation model. We carried out clinical image registration experiments on 3D magnetic resonance brain scans from IBSR database. The results of the proposed registration approach in terms of Kappa index and relative overlap computed over the subcortical structures were compared against the existing topology preserving non-rigid image registration methods and non topology preserving variant of our proposed registration scheme. The Jacobian determinant maps obtained with our proposed registration method were qualitatively and quantitatively analyzed. The results demonstrated that the proposed scheme provides good registration accuracy with smooth transformations, thereby guaranteeing the preservation of topology. Copyright © 2015 Elsevier Ltd. All rights reserved.

Exponential stability of fuzzy cellular neural networks with constant and time-varying delays

International Nuclear Information System (INIS)

Liu Yanqing; Tang Wansheng

2004-01-01

In this Letter, the global stability of delayed fuzzy cellular neural networks (FCNN) with either constant delays or time varying delays is proposed. Firstly, we give the existence and uniqueness of the equilibrium point by using the theory of topological degree and the properties of nonsingular M-matrix and the sufficient conditions for ascertaining the global exponential stability by constructing a suitable Lyapunov functional. Secondly, the criteria for guaranteeing the global exponential stability of FCNN with time varying delays are given and the estimation of exponential convergence rate with regard to speed of vary of delays is presented by constructing a suitable Lyapunov functional

Tracking control of time-varying knee exoskeleton disturbed by interaction torque.

Science.gov (United States)

Li, Zhan; Ma, Wenhao; Yin, Ziguang; Guo, Hongliang

2017-11-01

Knee exoskeletons have been increasingly applied as assistive devices to help lower-extremity impaired people to make their knee joints move through providing external movement compensation. Tracking control of knee exoskeletons guided by human intentions often encounters time-varying (time-dependent) issues and the disturbance interaction torque, which may dramatically put an influence up on their dynamic behaviors. Inertial and viscous parameters of knee exoskeletons can be estimated to be time-varying due to unexpected mechanical vibrations and contact interactions. Moreover, the interaction torque produced from knee joint of wearers has an evident disturbance effect on regular motions of knee exoskeleton. All of these points can increase difficultly of accurate control of knee exoskeletons to follow desired joint angle trajectories. This paper proposes a novel control strategy for controlling knee exoskeleton with time-varying inertial and viscous coefficients disturbed by interaction torque. Such designed controller is able to make the tracking error of joint angle of knee exoskeletons exponentially converge to zero. Meanwhile, the proposed approach is robust to guarantee the tracking error bounded when the interaction torque exists. Illustrative simulation and experiment results are presented to show efficiency of the proposed controller. Additionally, comparisons with gradient dynamic (GD) approach and other methods are also presented to demonstrate efficiency and superiority of the proposed control strategy for tracking joint angle of knee exoskeleton. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Forced solitary Rossby waves under the influence of slowly varying topography with time

International Nuclear Information System (INIS)

Yang Hong-Wei; Yin Bao-Shu; Yang De-Zhou; Xu Zhen-Hua

2011-01-01

By using a weakly nonlinear and perturbation method, the generalized inhomogeneous Korteweg—de Vries (KdV)—Burgers equation is derived, which governs the evolution of the amplitude of Rossby waves under the influence of dissipation and slowly varying topography with time. The analysis indicates that dissipation and slowly varying topography with time are important factors in causing variation in the mass and energy of solitary waves. (general)

Scanning probe microscope simulator for the assessment of noise in scanning probe microscopy controllers

International Nuclear Information System (INIS)

Wutscher, T.; Niebauer, J.; Giessibl, F. J.

2013-01-01

We present an electronic circuit that allows to calibrate and troubleshoot scanning probe microscopy (SPM) controllers with respect to their noise performance. The control signal in an SPM is typically highly nonlinear—the tunneling current in scanning tunneling microscopy (STM) varies exponentially with distance. The exponential current-versus-voltage characteristics of diodes allow to model the current dependence in STM. Additional inputs allow to simulate the effects of external perturbations and the reactions of the control electronics. We characterized the noise performance of the feedback controller using the apparent topography roughness of recorded images. For a comparison of different STM controllers, an optimal gain parameter was determined by exploring settling times through a rectangular perturbation signal. We used the circuit to directly compare the performance of two types of SPM controllers used in our laboratory

Stability of Nonlinear Systems with Unknown Time-varying Feedback Delay

Science.gov (United States)

Chunodkar, Apurva A.; Akella, Maruthi R.

2013-12-01

This paper considers the problem of stabilizing a class of nonlinear systems with unknown bounded delayed feedback wherein the time-varying delay is 1) piecewise constant 2) continuous with a bounded rate. We also consider application of these results to the stabilization of rigid-body attitude dynamics. In the first case, the time-delay in feedback is modeled specifically as a switch among an arbitrarily large set of unknown constant values with a known strict upper bound. The feedback is a linear function of the delayed states. In the case of linear systems with switched delay feedback, a new sufficiency condition for average dwell time result is presented using a complete type Lyapunov-Krasovskii (L-K) functional approach. Further, the corresponding switched system with nonlinear perturbations is proven to be exponentially stable inside a well characterized region of attraction for an appropriately chosen average dwell time. In the second case, the concept of the complete type L-K functional is extended to a class of nonlinear time-delay systems with unknown time-varying time-delay. This extension ensures stability robustness to time-delay in the control design for all values of time-delay less than the known upper bound. Model-transformation is used in order to partition the nonlinear system into a nominal linear part that is exponentially stable with a bounded perturbation. We obtain sufficient conditions which ensure exponential stability inside a region of attraction estimate. A constructive method to evaluate the sufficient conditions is presented together with comparison with the corresponding constant and piecewise constant delay. Numerical simulations are performed to illustrate the theoretical results of this paper.

Robustness Analysis of Hybrid Stochastic Neural Networks with Neutral Terms and Time-Varying Delays

Directory of Open Access Journals (Sweden)

Chunmei Wu

2015-01-01

Full Text Available We analyze the robustness of global exponential stability of hybrid stochastic neural networks subject to neutral terms and time-varying delays simultaneously. Given globally exponentially stable hybrid stochastic neural networks, we characterize the upper bounds of contraction coefficients of neutral terms and time-varying delays by using the transcendental equation. Moreover, we prove theoretically that, for any globally exponentially stable hybrid stochastic neural networks, if additive neutral terms and time-varying delays are smaller than the upper bounds arrived, then the perturbed neural networks are guaranteed to also be globally exponentially stable. Finally, a numerical simulation example is given to illustrate the presented criteria.

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

Science.gov (United States)

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.

Global exponential stability of BAM neural networks with time-varying delays: The discrete-time case

Science.gov (United States)

Raja, R.; Marshal Anthoni, S.

2011-02-01

This paper deals with the problem of stability analysis for a class of discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays. By employing the Lyapunov functional and linear matrix inequality (LMI) approach, a new sufficient conditions is proposed for the global exponential stability of discrete-time BAM neural networks. The proposed LMI based results can be easily checked by LMI control toolbox. Moreover, an example is also provided to demonstrate the effectiveness of the proposed method.

Efficient Imaging and Real-Time Display of Scanning Ion Conductance Microscopy Based on Block Compressive Sensing

Science.gov (United States)

Li, Gongxin; Li, Peng; Wang, Yuechao; Wang, Wenxue; Xi, Ning; Liu, Lianqing

2014-07-01

Scanning Ion Conductance Microscopy (SICM) is one kind of Scanning Probe Microscopies (SPMs), and it is widely used in imaging soft samples for many distinctive advantages. However, the scanning speed of SICM is much slower than other SPMs. Compressive sensing (CS) could improve scanning speed tremendously by breaking through the Shannon sampling theorem, but it still requires too much time in image reconstruction. Block compressive sensing can be applied to SICM imaging to further reduce the reconstruction time of sparse signals, and it has another unique application that it can achieve the function of image real-time display in SICM imaging. In this article, a new method of dividing blocks and a new matrix arithmetic operation were proposed to build the block compressive sensing model, and several experiments were carried out to verify the superiority of block compressive sensing in reducing imaging time and real-time display in SICM imaging.

Overlapping quadratic optimal control of linear time-varying commutative systems

Czech Academy of Sciences Publication Activity Database

Bakule, Lubomír; Rodellar, J.; Rossell, J. M.

2002-01-01

Roč. 40, č. 5 (2002), s. 1611-1627 ISSN 0363-0129 R&D Projects: GA AV ČR IAA2075802 Institutional research plan: CEZ:AV0Z1075907 Keywords : overlapping * optimal control * linear time-varying systems Subject RIV: BC - Control Systems Theory Impact factor: 1.441, year: 2002

An Explicit MOT-TD-VIE Solver for Time Varying Media

KAUST Repository

Sayed, Sadeed Bin

2016-03-15

An explicit marching on-in-time (MOT) scheme for solving the time domain electric field integral equation enforced on volumes with time varying dielectric permittivity is proposed. Unknowns of the integral equation and the constitutive relation, i.e., flux density and field intensity, are discretized using full and half Schaubert-Wilton-Glisson functions in space. Temporal interpolation is carried out using band limited approximate prolate spherical wave functions. The discretized coupled system of integral equation and constitutive relation is integrated in time using a PE(CE)m type linear multistep scheme. Unlike the existing MOT methods, the resulting explicit MOT scheme allows for straightforward incorporation of the time variation in the dielectric permittivity.

Time-varying Capital Requirements and Disclosure Rules

DEFF Research Database (Denmark)

Kragh, Jonas; Rangvid, Jesper

, implying that resilience in the banking system is also increased. The increase in capital ratios is partly due to a modest reduction in lending. Using a policy changes, we show that banks react stronger to changes in capital requirements when these are public. Our results further suggest that the impact......Unique and confidential Danish data allow us to identify how changes in disclosure requirements and bank-specific time-varying capital requirements affect banks' lending and capital accumu-lation decisions. We find that banks increase their capital ratios after capital requirements are increased...... of capital requirements differ for small and large banks. Large banks raise their capital ratios more, reduce lending less, and accumulate more new capital compared to small banks....

Time-varying vector fields and their flows

CERN Document Server

Jafarpour, Saber

2014-01-01

This short book provides a comprehensive and unified treatment of time-varying vector fields under a variety of regularity hypotheses, namely finitely differentiable, Lipschitz, smooth, holomorphic, and real analytic. The presentation of this material in the real analytic setting is new, as is the manner in which the various hypotheses are unified using functional analysis. Indeed, a major contribution of the book is the coherent development of locally convex topologies for the space of real analytic sections of a vector bundle, and the development of this in a manner that relates easily to classically known topologies in, for example, the finitely differentiable and smooth cases. The tools used in this development will be of use to researchers in the area of geometric functional analysis.

Delay-Dependent Guaranteed Cost Control of an Interval System with Interval Time-Varying Delay

Directory of Open Access Journals (Sweden)

Xiao Min

2009-01-01

Full Text Available This paper concerns the problem of the delay-dependent robust stability and guaranteed cost control for an interval system with time-varying delay. The interval system with matrix factorization is provided and leads to less conservative conclusions than solving a square root. The time-varying delay is assumed to belong to an interval and the derivative of the interval time-varying delay is not a restriction, which allows a fast time-varying delay; also its applicability is broad. Based on the Lyapunov-Ktasovskii approach, a delay-dependent criterion for the existence of a state feedback controller, which guarantees the closed-loop system stability, the upper bound of cost function, and disturbance attenuation lever for all admissible uncertainties as well as out perturbation, is proposed in terms of linear matrix inequalities (LMIs. The criterion is derived by free weighting matrices that can reduce the conservatism. The effectiveness has been verified in a number example and the compute results are presented to validate the proposed design method.

Discrete-time recurrent neural networks with time-varying delays: Exponential stability analysis

International Nuclear Information System (INIS)

Liu, Yurong; Wang, Zidong; Serrano, Alan; Liu, Xiaohui

2007-01-01

This Letter is concerned with the analysis problem of exponential stability for a class of discrete-time recurrent neural networks (DRNNs) with time delays. The delay is of the time-varying nature, and the activation functions are assumed to be neither differentiable nor strict monotonic. Furthermore, the description of the activation functions is more general than the recently commonly used Lipschitz conditions. Under such mild conditions, we first prove the existence of the equilibrium point. Then, by employing a Lyapunov-Krasovskii functional, a unified linear matrix inequality (LMI) approach is developed to establish sufficient conditions for the DRNNs to be globally exponentially stable. It is shown that the delayed DRNNs are globally exponentially stable if a certain LMI is solvable, where the feasibility of such an LMI can be easily checked by using the numerically efficient Matlab LMI Toolbox. A simulation example is presented to show the usefulness of the derived LMI-based stability condition

Global exponential stability of uncertain fuzzy BAM neural networks with time-varying delays

International Nuclear Information System (INIS)

Syed Ali, M.; Balasubramaniam, P.

2009-01-01

In this paper, the Takagi-Sugeno (TS) fuzzy model representation is extended to the stability analysis for uncertain Bidirectional Associative Memory (BAM) neural networks with time-varying delays using linear matrix inequality (LMI) theory. A novel LMI-based stability criterion is obtained by LMI optimization algorithms to guarantee the exponential stability of uncertain BAM neural networks with time-varying delays which are represented by TS fuzzy models. Finally, the proposed stability conditions are demonstrated with numerical examples.

Time-varying market integration and expected returns in emerging mrkets

NARCIS (Netherlands)

de Jong, F.C.J.M.; de Roon, F.

2001-01-01

We use a simple model in which the expected returns in emerging markets depend on their systematicrisk as measured by their beta relative to the world portfolio as well as on the level ofintegration in that market. The level of integration is a time-varying variable that depends on themarket value

Estimation of time-varying reactivity by the H∞ optimal linear filter

International Nuclear Information System (INIS)

Suzuki, Katsuo; Shimazaki, Junya; Watanabe, Koiti

1995-01-01

The problem of estimating the time-varying net reactivity from flux measurements is solved for a point reactor kinetics model using a linear filtering technique in an H ∞ settings. In order to sue this technique, an appropriate dynamical model of the reactivity is constructed that can be embedded into the reactor model as one of its variables. A filter, which minimizes the H ∞ norm of the estimation error power spectrum, operates on neutron density measurements corrupted by noise and provides an estimate of the dynamic net reactivity. Computer simulations are performed to reveal the basic characteristics of the H ∞ optimal filter. The results of the simulation indicate that the filter can be used to determine the time-varying reactivity from neutron density measurements that have been corrupted by noise

Globally Asymptotic Stability of Stochastic Nonlinear Systems with Time-Varying Delays via Output Feedback Control

Directory of Open Access Journals (Sweden)

Mingzhu Song

2016-01-01

Full Text Available We address the problem of globally asymptotic stability for a class of stochastic nonlinear systems with time-varying delays. By the backstepping method and Lyapunov theory, we design a linear output feedback controller recursively based on the observable linearization for a class of stochastic nonlinear systems with time-varying delays to guarantee that the closed-loop system is globally asymptotically stable in probability. In particular, we extend the deterministic nonlinear system to stochastic nonlinear systems with time-varying delays. Finally, an example and its simulations are given to illustrate the theoretical results.

Closed-Loop Autofocus Scheme for Scanning Electron Microscope

Directory of Open Access Journals (Sweden)

Cui Le

2015-01-01

Full Text Available In this paper, we present a full scale autofocus approach for scanning electron microscope (SEM. The optimal focus (in-focus position of the microscope is achieved by maximizing the image sharpness using a vision-based closed-loop control scheme. An iterative optimization algorithm has been designed using the sharpness score derived from image gradient information. The proposed method has been implemented and validated using a tungsten gun SEM at various experimental conditions like varying raster scan speed, magnification at real-time. We demonstrate that the proposed autofocus technique is accurate, robust and fast.

Reconstruction of a time-averaged midposition CT scan for radiotherapy planning of lung cancer patients using deformable registration

International Nuclear Information System (INIS)

Wolthaus, J. W. H.; Sonke, J.-J.; Herk, M. van; Damen, E. M. F.

2008-01-01

Purpose: lower lobe lung tumors move with amplitudes of up to 2 cm due to respiration. To reduce respiration imaging artifacts in planning CT scans, 4D imaging techniques are used. Currently, we use a single (midventilation) frame of the 4D data set for clinical delineation of structures and radiotherapy planning. A single frame, however, often contains artifacts due to breathing irregularities, and is noisier than a conventional CT scan since the exposure per frame is lower. Moreover, the tumor may be displaced from the mean tumor position due to hysteresis. The aim of this work is to develop a framework for the acquisition of a good quality scan representing all scanned anatomy in the mean position by averaging transformed (deformed) CT frames, i.e., canceling out motion. A nonrigid registration method is necessary since motion varies over the lung. Methods and Materials: 4D and inspiration breath-hold (BH) CT scans were acquired for 13 patients. An iterative multiscale motion estimation technique was applied to the 4D CT scan, similar to optical flow but using image phase (gray-value transitions from bright to dark and vice versa) instead. From the (4D) deformation vector field (DVF) derived, the local mean position in the respiratory cycle was computed and the 4D DVF was modified to deform all structures of the original 4D CT scan to this mean position. A 3D midposition (MidP) CT scan was then obtained by (arithmetic or median) averaging of the deformed 4D CT scan. Image registration accuracy, tumor shape deviation with respect to the BH CT scan, and noise were determined to evaluate the image fidelity of the MidP CT scan and the performance of the technique. Results: Accuracy of the used deformable image registration method was comparable to established automated locally rigid registration and to manual landmark registration (average difference to both methods <0.5 mm for all directions) for the tumor region. From visual assessment, the registration was good

Soil erosion under multiple time-varying rainfall events

Science.gov (United States)

Heng, B. C. Peter; Barry, D. Andrew; Jomaa, Seifeddine; Sander, Graham C.

2010-05-01

Soil erosion is a function of many factors and process interactions. An erosion event produces changes in surface soil properties such as texture and hydraulic conductivity. These changes in turn alter the erosion response to subsequent events. Laboratory-scale soil erosion studies have typically focused on single independent rainfall events with constant rainfall intensities. This study investigates the effect of multiple time-varying rainfall events on soil erosion using the EPFL erosion flume. The rainfall simulator comprises ten Veejet nozzles mounted on oscillating bars 3 m above a 6 m × 2 m flume. Spray from the nozzles is applied onto the soil surface in sweeps; rainfall intensity is thus controlled by varying the sweeping frequency. Freshly-prepared soil with a uniform slope was subjected to five rainfall events at daily intervals. In each 3-h event, rainfall intensity was ramped up linearly to a maximum of 60 mm/h and then stepped down to zero. Runoff samples were collected and analysed for particle size distribution (PSD) as well as total sediment concentration. We investigate whether there is a hysteretic relationship between sediment concentration and discharge within each event and how this relationship changes from event to event. Trends in the PSD of the eroded sediment are discussed and correlated with changes in sediment concentration. Close-up imagery of the soil surface following each event highlight changes in surface soil structure with time. This study enhances our understanding of erosion processes in the field, with corresponding implications for soil erosion modelling.

Exponential stability of switched linear systems with time-varying delay

Directory of Open Access Journals (Sweden)

Satiracoo Pairote

2007-11-01

Full Text Available We use a Lyapunov-Krasovskii functional approach to establish the exponential stability of linear systems with time-varying delay. Our delay-dependent condition allows to compute simultaneously the two bounds that characterize the exponential stability rate of the solution. A simple procedure for constructing switching rule is also presented.

Relay selection in cooperative communication systems over continuous time-varying fading channel

Directory of Open Access Journals (Sweden)

Ke Geng

2017-02-01

Full Text Available In this paper, we study relay selection under outdated channel state information (CSI in a decode-and-forward (DF cooperative system. Unlike previous researches on cooperative communication under outdated CSI, we consider that the channel varies continuously over time, i.e., the channel not only changes between relay selection and data transmission but also changes during data transmission. Thus the level of accuracy of the CSI used in relay selection degrades with data transmission. We first evaluate the packet error rate (PER of the cooperative system under continuous time-varying fading channel, and find that the PER performance deteriorates more seriously under continuous time-varying fading channel than when the channel is assumed to be constant during data transmission. Then, we propose a repeated relay selection (RRS strategy to improve the PER performance, in which the forwarded data is divided into multiple segments and relay is reselected before the transmission of each segment based on the updated CSI. Finally, we propose a combined relay selection (CRS strategy which takes advantage of three different relay selection strategies to further mitigate the impact of outdated CSI.

One-dimensional radionuclide transport under time-varying conditions

International Nuclear Information System (INIS)

Gelbard, F.; Olague, N.E.; Longsine, D.E.

1990-01-01

This paper discusses new analytical and numerical solutions presented for one-dimensional radionuclide transport under time-varying fluid-flow conditions including radioactive decay. The analytical solution assumes that all radionuclides have identical retardation factors, and is limited to instantaneous releases. The numerical solution does not have these limitations, but is tested against the limiting case given for the analytical solution. Reasonable agreement between the two solutions was found. Examples are given for the transport of a three-member radionuclide chain transported over distances and flow rates comparable to those reported for Yucca Mountain, the proposed disposal site for high-level nuclear waste

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

International Nuclear Information System (INIS)

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

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

Compensating Unknown Time-Varying Delay in Opto-Electronic Platform Tracking Servo System

Directory of Open Access Journals (Sweden)

Ruihong Xie

2017-05-01

Full Text Available This paper investigates the problem of compensating miss-distance delay in opto-electronic platform tracking servo system. According to the characteristic of LOS (light-of-sight motion, we setup the Markovian process model and compensate this unknown time-varying delay by feed-forward forecasting controller based on robust H∞ control. Finally, simulation based on double closed-loop PI (Proportion Integration control system indicates that the proposed method is effective for compensating unknown time-varying delay. Tracking experiments on the opto-electronic platform indicate that RMS (root-mean-square error is 1.253 mrad when tracking 10° 0.2 Hz signal.

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

Science.gov (United States)

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.

Multi-pulse chaotic motions of a rotor-active magnetic bearing system with time-varying stiffness

International Nuclear Information System (INIS)

Zhang, W.; Yao, M.H.; Zhan, X.P.

2006-01-01

In this paper, we investigate the Shilnikov type multi-pulse chaotic dynamics for a rotor-active magnetic bearings (AMB) system with 8-pole legs and the time-varying stiffness. The stiffness in the AMB is considered as the time-varying in a periodic form. The dimensionless equation of motion for the rotor-AMB system with the time-varying stiffness in the horizontal and vertical directions is a two-degree-of-freedom nonlinear system with quadratic and cubic nonlinearities and parametric excitation. The asymptotic perturbation method is used to obtain the averaged equations in the case of primary parametric resonance and 1/2 subharmonic resonance. It is found from the numerical results that there are the phenomena of the Shilnikov type multi-pulse chaotic motions for the rotor-AMB system. A new jumping phenomenon is discovered in the rotor-AMB system with the time-varying stiffness

Dual Extended Kalman Filter for the Identification of Time-Varying Human Manual Control Behavior

Science.gov (United States)

Popovici, Alexandru; Zaal, Peter M. T.; Pool, Daan M.

2017-01-01

A Dual Extended Kalman Filter was implemented for the identification of time-varying human manual control behavior. Two filters that run concurrently were used, a state filter that estimates the equalization dynamics, and a parameter filter that estimates the neuromuscular parameters and time delay. Time-varying parameters were modeled as a random walk. The filter successfully estimated time-varying human control behavior in both simulated and experimental data. Simple guidelines are proposed for the tuning of the process and measurement covariance matrices and the initial parameter estimates. The tuning was performed on simulation data, and when applied on experimental data, only an increase in measurement process noise power was required in order for the filter to converge and estimate all parameters. A sensitivity analysis to initial parameter estimates showed that the filter is more sensitive to poor initial choices of neuromuscular parameters than equalization parameters, and bad choices for initial parameters can result in divergence, slow convergence, or parameter estimates that do not have a real physical interpretation. The promising results when applied to experimental data, together with its simple tuning and low dimension of the state-space, make the use of the Dual Extended Kalman Filter a viable option for identifying time-varying human control parameters in manual tracking tasks, which could be used in real-time human state monitoring and adaptive human-vehicle haptic interfaces.

Time Varying Market Integration and Expected Rteurns in Emerging Markets

NARCIS (Netherlands)

de Jong, F.C.J.M.; de Roon, F.A.

2001-01-01

We use a simple model in which the expected returns in emerging markets depend on their systematic risk as measured by their beta relative to the world portfolio as well as on the level of integration in that market.The level of integration is a time-varying variable that depends on the market value

A new time-varying harmonic decomposition structure based on recursive hanning window

NARCIS (Netherlands)

Martins, C.H.; Silva, L.R.M.; Duque, C.A.; Cerqueira, A.S.; Teixeira, E.C.; Ribeiro, P.F.

2012-01-01

Analysis of power quality phenomena under time-varying conditions has become an important subject as the complexity of the grid increases. As a consequence, several methods have been developed/applied also to study power quality parameters during transient conditions such as time-frequency methods.

Uniform stability for time-varying infinite-dimensional discrete linear systems

International Nuclear Information System (INIS)

Kubrusly, C.S.

1988-09-01

Stability for time-varying discrete linear systems in a Banach space is investigated. On the one hand, it established a fairly complete collection of necessary and sufficient conditions for uniform asymptotic equistability for input-free systems. This includes uniform and strong power equistability, and uniform and strong l p -equistability, among other technical conditions which also play essential role in stability theory. On other hand, it is shown that uniform asymptotic equistability for input-free systems is equivalent to each of the following concepts of uniform stability for forced systems: l p -input l p -state, c o -input c o -state, bounded-input bounded-state, l p>1 -input bounded-state, c sub (o)-input bounded-state, and convergent-input bounded-state; which are also equivalent to their nonuniform counterparts. For time-varying convergent systems, the above is also equivalent to convergent-input convergent-state stability. The proofs presented here are all ''elementary'' in the sense that they are based essentially only on the Banach-Steinhaus theorem. (autor) [pt

Neutron fluctuations in a medium randomly varying in time

International Nuclear Information System (INIS)

Lenard, Pal; Imre, Pazsit

2005-01-01

The master equation approach, which has traditionally been used for the calculation of neutron fluctuations in zero power systems with constant parameters, is extended to a case when the parameters of the system change randomly in time. We consider a forward type master equation for the probability distribution of the number of particles in a multiplying system whose properties jump randomly between two discrete states, both with and without an external source. The first two factorial moments are calculated, including the covariance. This model can be considered the unification of stochastic methods that were used either in a constant multiplying medium via the master equation technique, or in a fluctuating medium via the Langevin technique. In contrast to these methods, the one presented here can calculate the inherent noise in time-varying systems. The results obtained show a much richer characteristics of the zero power noise than that in constant systems. Even the concept of criticality has to be given a probabilistic interpretation. The asymptotic behaviour of the variance will be also qualitatively different from that in constant systems. The covariance of the neutron number in a subcritical system with a source, and the corresponding power spectrum, shows both the inherent and parametrically induced noise components. The results are relevant in medium power subcritical systems where the zero power noise is still significant, but they also have a bearing on all types of branching processes, such as evolution of biological systems, spreading of epidemics etc., which are set in a time-varying environment. (authors)

Neutron fluctuations in a medium randomly varying in time

Energy Technology Data Exchange (ETDEWEB)

Lenard, Pal [KFKI Atomic Energy Research Institute, Budapest (Hungary); Imre, Pazsit [Chalmers Univ. of Technology, Dept. of Nuclear Engineering, SE, Goteborg (Sweden)

2005-07-01

The master equation approach, which has traditionally been used for the calculation of neutron fluctuations in zero power systems with constant parameters, is extended to a case when the parameters of the system change randomly in time. We consider a forward type master equation for the probability distribution of the number of particles in a multiplying system whose properties jump randomly between two discrete states, both with and without an external source. The first two factorial moments are calculated, including the covariance. This model can be considered the unification of stochastic methods that were used either in a constant multiplying medium via the master equation technique, or in a fluctuating medium via the Langevin technique. In contrast to these methods, the one presented here can calculate the inherent noise in time-varying systems. The results obtained show a much richer characteristics of the zero power noise than that in constant systems. Even the concept of criticality has to be given a probabilistic interpretation. The asymptotic behaviour of the variance will be also qualitatively different from that in constant systems. The covariance of the neutron number in a subcritical system with a source, and the corresponding power spectrum, shows both the inherent and parametrically induced noise components. The results are relevant in medium power subcritical systems where the zero power noise is still significant, but they also have a bearing on all types of branching processes, such as evolution of biological systems, spreading of epidemics etc., which are set in a time-varying environment. (authors)

Optimal Consumption and Investment under Time-Varying Relative Risk Aversion

DEFF Research Database (Denmark)

Steffensen, Mogens

2011-01-01

We consider the continuous time consumption-investment problem originally formalized and solved by Merton in case of constant relative risk aversion. We present a complete solution for the case where relative risk aversion with respect to consumption varies with time, having in mind an investor...... with age-dependent risk aversion. This provides a new motivation for life-cycle investment rules. We study the optimal consumption and investment rules, in particular in the case where the relative risk aversion with respect to consumption is increasing with age....

Detection of dynamically varying interaural time differences

DEFF Research Database (Denmark)

Kohlrausch, Armin; Le Goff, Nicolas; Breebaart, Jeroen

2010-01-01

of fringes surrounding the probe is equal to the addition of the effects of the individual fringes. In this contribution, we present behavioral data for the same experimental condition, called dynamically varying ITD detection, but for a wider range of probe and fringe durations. Probe durations varied...

Mean Square Exponential Stability of Stochastic Switched System with Interval Time-Varying Delays

Directory of Open Access Journals (Sweden)

Manlika Rajchakit

2012-01-01

Full Text Available This paper is concerned with mean square exponential stability of switched stochastic system with interval time-varying delays. The time delay is any continuous function belonging to a given interval, but not necessary to be differentiable. By constructing a suitable augmented Lyapunov-Krasovskii functional combined with Leibniz-Newton’s formula, a switching rule for the mean square exponential stability of switched stochastic system with interval time-varying delays and new delay-dependent sufficient conditions for the mean square exponential stability of the switched stochastic system are first established in terms of LMIs. Numerical example is given to show the effectiveness of the obtained result.

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

International Nuclear Information System (INIS)

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

2016-01-01

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. (paper)

Tracking time-varying coefficient-functions

DEFF Research Database (Denmark)

Nielsen, Henrik Aalborg; Nielsen, Torben Skov; Joensen, Alfred K.

2000-01-01

is a combination of recursive least squares with exponential forgetting and local polynomial regression. It is argued, that it is appropriate to let the forgetting factor vary with the value of the external signal which is the argument of the coefficient functions. Some of the key properties of the modified method...... are studied by simulation...

Time-varying coefficient estimation in SURE models. Application to portfolio management

DEFF Research Database (Denmark)

Casas, Isabel; Ferreira, Eva; Orbe, Susan

This paper provides a detailed analysis of the asymptotic properties of a kernel estimator for a Seemingly Unrelated Regression Equations model with time-varying coefficients (tv-SURE) under very general conditions. Theoretical results together with a simulation study differentiates the cases...

Effects of varying feeding times on fertility and hatchability of broiler ...

African Journals Online (AJOL)

Effects of varying feeding times on fertility and hatchability of broiler chicken breeders in a tropical environment. ... Journal Home > Vol 65, No 4 (2017) > ... Prior to the eighth week data collection, the birds were allowed to get accustomed to ...

Technical Note: Using experimentally determined proton spot scanning timing parameters to accurately model beam delivery time.

Science.gov (United States)

Shen, Jiajian; Tryggestad, Erik; Younkin, James E; Keole, Sameer R; Furutani, Keith M; Kang, Yixiu; Herman, Michael G; Bues, Martin

2017-10-01

To accurately model the beam delivery time (BDT) for a synchrotron-based proton spot scanning system using experimentally determined beam parameters. A model to simulate the proton spot delivery sequences was constructed, and BDT was calculated by summing times for layer switch, spot switch, and spot delivery. Test plans were designed to isolate and quantify the relevant beam parameters in the operation cycle of the proton beam therapy delivery system. These parameters included the layer switch time, magnet preparation and verification time, average beam scanning speeds in x- and y-directions, proton spill rate, and maximum charge and maximum extraction time for each spill. The experimentally determined parameters, as well as the nominal values initially provided by the vendor, served as inputs to the model to predict BDTs for 602 clinical proton beam deliveries. The calculated BDTs (T BDT ) were compared with the BDTs recorded in the treatment delivery log files (T Log ): ∆t = T Log -T BDT . The experimentally determined average layer switch time for all 97 energies was 1.91 s (ranging from 1.9 to 2.0 s for beam energies from 71.3 to 228.8 MeV), average magnet preparation and verification time was 1.93 ms, the average scanning speeds were 5.9 m/s in x-direction and 19.3 m/s in y-direction, the proton spill rate was 8.7 MU/s, and the maximum proton charge available for one acceleration is 2.0 ± 0.4 nC. Some of the measured parameters differed from the nominal values provided by the vendor. The calculated BDTs using experimentally determined parameters matched the recorded BDTs of 602 beam deliveries (∆t = -0.49 ± 1.44 s), which were significantly more accurate than BDTs calculated using nominal timing parameters (∆t = -7.48 ± 6.97 s). An accurate model for BDT prediction was achieved by using the experimentally determined proton beam therapy delivery parameters, which may be useful in modeling the interplay effect and patient throughput. The model may

Synchronization of Hierarchical Time-Varying Neural Networks Based on Asynchronous and Intermittent Sampled-Data Control.

Science.gov (United States)

Xiong, Wenjun; Patel, Ragini; Cao, Jinde; Zheng, Wei Xing

In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.In this brief, our purpose is to apply asynchronous and intermittent sampled-data control methods to achieve the synchronization of hierarchical time-varying neural networks. The asynchronous and intermittent sampled-data controllers are proposed for two reasons: 1) the controllers may not transmit the control information simultaneously and 2) the controllers cannot always exist at any time . The synchronization is then discussed for a kind of hierarchical time-varying neural networks based on the asynchronous and intermittent sampled-data controllers. Finally, the simulation results are given to illustrate the usefulness of the developed criteria.

Modal Vibration Control in Periodic Time-Varying Structures with Focus on Rotor Blade Systems

DEFF Research Database (Denmark)

Christensen, Rene Hardam; Santos, Ilmar

2004-01-01

of active modal controllers. The main aim is to reduce vibrations in periodic time-varying structures. Special emphasis is given to vibration control of coupled bladed rotor systems. A state feedback modal control law is developed based on modal analysis in periodic time-varying structures. The first step...... in the procedure is a transformation of the model into a time-invariant modal form by applying the modal matrices, which are also periodic time-variant. Due to coupled rotor and blade motions complex vibration modes occur in the modal transformed state space model. This implies that the modal transformed model...

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

Science.gov (United States)

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. Published by Elsevier Inc.

Fluctuating interaction network and time-varying stability of a natural fish community

Science.gov (United States)

Ushio, Masayuki; Hsieh, Chih-Hao; Masuda, Reiji; Deyle, Ethan R.; Ye, Hao; Chang, Chun-Wei; Sugihara, George; Kondoh, Michio

2018-02-01

Ecological theory suggests that large-scale patterns such as community stability can be influenced by changes in interspecific interactions that arise from the behavioural and/or physiological responses of individual species varying over time. Although this theory has experimental support, evidence from natural ecosystems is lacking owing to the challenges of tracking rapid changes in interspecific interactions (known to occur on timescales much shorter than a generation time) and then identifying the effect of such changes on large-scale community dynamics. Here, using tools for analysing nonlinear time series and a 12-year-long dataset of fortnightly collected observations on a natural marine fish community in Maizuru Bay, Japan, we show that short-term changes in interaction networks influence overall community dynamics. Among the 15 dominant species, we identify 14 interspecific interactions to construct a dynamic interaction network. We show that the strengths, and even types, of interactions change with time; we also develop a time-varying stability measure based on local Lyapunov stability for attractor dynamics in non-equilibrium nonlinear systems. We use this dynamic stability measure to examine the link between the time-varying interaction network and community stability. We find seasonal patterns in dynamic stability for this fish community that broadly support expectations of current ecological theory. Specifically, the dominance of weak interactions and higher species diversity during summer months are associated with higher dynamic stability and smaller population fluctuations. We suggest that interspecific interactions, community network structure and community stability are dynamic properties, and that linking fluctuating interaction networks to community-level dynamic properties is key to understanding the maintenance of ecological communities in nature.

Exponential stability for stochastic delayed recurrent neural networks with mixed time-varying delays and impulses: the continuous-time case

International Nuclear Information System (INIS)

Karthik Raja, U; Leelamani, A; Raja, R; Samidurai, R

2013-01-01

In this paper, the exponential stability for a class of stochastic neural networks with time-varying delays and impulsive effects is considered. By constructing suitable Lyapunov functionals and by using the linear matrix inequality optimization approach, we obtain sufficient delay-dependent criteria to ensure the exponential stability of stochastic neural networks with time-varying delays and impulses. Two numerical examples with simulation results are provided to illustrate the effectiveness of the obtained results over those already existing in the literature. (paper)

A discrete time-varying internal model-based approach for high precision tracking of a multi-axis servo gantry.

Science.gov (United States)

Zhang, Zhen; Yan, Peng; Jiang, Huan; Ye, Peiqing

2014-09-01

In this paper, we consider the discrete time-varying internal model-based control design for high precision tracking of complicated reference trajectories generated by time-varying systems. Based on a novel parallel time-varying internal model structure, asymptotic tracking conditions for the design of internal model units are developed, and a low order robust time-varying stabilizer is further synthesized. In a discrete time setting, the high precision tracking control architecture is deployed on a Voice Coil Motor (VCM) actuated servo gantry system, where numerical simulations and real time experimental results are provided, achieving the tracking errors around 3.5‰ for frequency-varying signals. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

Real-time Kalman filter implementation for active feedforward control of time-varying broadband noise and vibrations

NARCIS (Netherlands)

Ophem, S. van; Berkhoff, A.P.

2012-01-01

Tracking behavior and the rate of convergence are critical properties in active noise control applications with time-varying disturbance spectra. As compared to the standard filtered-reference Least Mean Square (LMS) algorithm, improved convergence can be obtained with schemes based on

Estimation of Time-Varying Coherence and Its Application in Understanding Brain Functional Connectivity

Directory of Open Access Journals (Sweden)

Cheng Liu

2010-01-01

Full Text Available Time-varying coherence is a powerful tool for revealing functional dynamics between different regions in the brain. In this paper, we address ways of estimating evolutionary spectrum and coherence using the general Cohen's class distributions. We show that the intimate connection between the Cohen's class-based spectra and the evolutionary spectra defined on the locally stationary time series can be linked by the kernel functions of the Cohen's class distributions. The time-varying spectra and coherence are further generalized with the Stockwell transform, a multiscale time-frequency representation. The Stockwell measures can be studied in the framework of the Cohen's class distributions with a generalized frequency-dependent kernel function. A magnetoencephalography study using the Stockwell coherence reveals an interesting temporal interaction between contralateral and ipsilateral motor cortices under the multisource interference task.

Robust outer synchronization between two nonlinear complex networks with parametric disturbances and mixed time-varying delays

Science.gov (United States)

Zhang, Chuan; Wang, Xingyuan; Luo, Chao; Li, Junqiu; Wang, Chunpeng

2018-03-01

In this paper, we focus on the robust outer synchronization problem between two nonlinear complex networks with parametric disturbances and mixed time-varying delays. Firstly, a general complex network model is proposed. Besides the nonlinear couplings, the network model in this paper can possess parametric disturbances, internal time-varying delay, discrete time-varying delay and distributed time-varying delay. Then, according to the robust control strategy, linear matrix inequality and Lyapunov stability theory, several outer synchronization protocols are strictly derived. Simple linear matrix controllers are designed to driver the response network synchronize to the drive network. Additionally, our results can be applied on the complex networks without parametric disturbances. Finally, by utilizing the delayed Lorenz chaotic system as the dynamics of all nodes, simulation examples are given to demonstrate the effectiveness of our theoretical results.

Improvement of and Parameter Identification for the Bimodal Time-Varying Modified Kanai-Tajimi Power Spectral Model

Directory of Open Access Journals (Sweden)

Huiguo Chen

2017-01-01

Full Text Available Based on the Kanai-Tajimi power spectrum filtering method proposed by Du Xiuli et al., a genetic algorithm and a quadratic optimization identification technique are employed to improve the bimodal time-varying modified Kanai-Tajimi power spectral model and the parameter identification method proposed by Vlachos et al. Additionally, a method for modeling time-varying power spectrum parameters for ground motion is proposed. The 8244 Orion and Chi-Chi earthquake accelerograms are selected as examples for time-varying power spectral model parameter identification and ground motion simulations to verify the feasibility and effectiveness of the improved bimodal time-varying modified Kanai-Tajimi power spectral model. The results of this study provide important references for designing ground motion inputs for seismic analyses of major engineering structures.

Estimating time-varying RSA to examine psychophysiological linkage of marital dyads.

Science.gov (United States)

Gates, Kathleen M; Gatzke-Kopp, Lisa M; Sandsten, Maria; Blandon, Alysia Y

2015-08-01

One of the primary tenets of polyvagal theory dictates that parasympathetic influence on heart rate, often estimated by respiratory sinus arrhythmia (RSA), shifts rapidly in response to changing environmental demands. The current standard analytic approach of aggregating RSA estimates across time to arrive at one value fails to capture this dynamic property within individuals. By utilizing recent methodological developments that enable precise RSA estimates at smaller time intervals, we demonstrate the utility of computing time-varying RSA for assessing psychophysiological linkage (or synchrony) in husband-wife dyads using time-locked data collected in a naturalistic setting. © 2015 Society for Psychophysiological Research.

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

Science.gov (United States)

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.

Conditional CAPM: Time-varying Betas in the Brazilian Market

Directory of Open Access Journals (Sweden)

Frances Fischberg Blank

2014-10-01

Full Text Available The conditional CAPM is characterized by time-varying market beta. Based on state-space models approach, beta behavior can be modeled as a stochastic process dependent on conditioning variables related to business cycle and estimated using Kalman filter. This paper studies alternative models for portfolios sorted by size and book-to-market ratio in the Brazilian stock market and compares their adjustment to data. Asset pricing tests based on time-series and cross-sectional approaches are also implemented. A random walk process combined with conditioning variables is the preferred model, reducing pricing errors compared to unconditional CAPM, but the errors are still significant. Cross-sectional test show that book-to-market ratio becomes less relevant, but past returns still capture cross-section variation

Wavelet ridge diagnosis of time-varying elliptical signals with application to an oceanic eddy

OpenAIRE

Lilly , J. M.; Gascard , Jean-Claude

2006-01-01

International audience; A method for diagnosing the physical properties of a time-varying ellipse is presented. This essentially involves extending the notion of instantaneous frequency to the bivariate case. New complications, and possibilities, arise from the fact that there are several meaningful forms in which a time-varying ellipse may be represented. A perturbation analysis valid for the near-circular case clarifies these issues. Diagnosis of the ellipse properties may then be performed...

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

International Nuclear Information System (INIS)

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. 11 refs

A simple analytical model for dynamics of time-varying target leverage ratios

Science.gov (United States)

Lo, C. F.; Hui, C. H.

2012-03-01

In this paper we have formulated a simple theoretical model for the dynamics of the time-varying target leverage ratio of a firm under some assumptions based upon empirical observations. In our theoretical model the time evolution of the target leverage ratio of a firm can be derived self-consistently from a set of coupled Ito's stochastic differential equations governing the leverage ratios of an ensemble of firms by the nonlinear Fokker-Planck equation approach. The theoretically derived time paths of the target leverage ratio bear great resemblance to those used in the time-dependent stationary-leverage (TDSL) model [Hui et al., Int. Rev. Financ. Analy. 15, 220 (2006)]. Thus, our simple model is able to provide a theoretical foundation for the selected time paths of the target leverage ratio in the TDSL model. We also examine how the pace of the adjustment of a firm's target ratio, the volatility of the leverage ratio and the current leverage ratio affect the dynamics of the time-varying target leverage ratio. Hence, with the proposed dynamics of the time-dependent target leverage ratio, the TDSL model can be readily applied to generate the default probabilities of individual firms and to assess the default risk of the firms.

Delay-Dependent Guaranteed Cost H∞ Control of an Interval System with Interval Time-Varying Delay

Directory of Open Access Journals (Sweden)

Zhongke Shi

2009-01-01

Full Text Available This paper concerns the problem of the delay-dependent robust stability and guaranteed cost H∞ control for an interval system with time-varying delay. The interval system with matrix factorization is provided and leads to less conservative conclusions than solving a square root. The time-varying delay is assumed to belong to an interval and the derivative of the interval time-varying delay is not a restriction, which allows a fast time-varying delay; also its applicability is broad. Based on the Lyapunov-Ktasovskii approach, a delay-dependent criterion for the existence of a state feedback controller, which guarantees the closed-loop system stability, the upper bound of cost function, and disturbance attenuation lever for all admissible uncertainties as well as out perturbation, is proposed in terms of linear matrix inequalities (LMIs. The criterion is derived by free weighting matrices that can reduce the conservatism. The effectiveness has been verified in a number example and the compute results are presented to validate the proposed design method.

Observation of time-varying photoconductivity and persistent photoconductivity in porous silicon

DEFF Research Database (Denmark)

Frello, T.; Veje, E.; Leistiko, Otto

1996-01-01

We have observed time-varying photoconductivity and persistent photoconductivity in porous silicon, both with time-evolution scales of the order of several minutes or hours. The time evolutions depend on the wavelength and the intensity of the illuminating light. The data indicate the presence...... of at least two competing mechanisms, one is tentatively related to photoinduced creation of charge carriers in the silicon substrate followed by diffusion into the porous silicon layer, and the other is tentatively related to desorption of hydrogen from the porous silicon. ©1996 American Institute of Physics....

Evaluation of the Effect of Light and Scanning Time Delay on The Image Quality of Intra Oral Photostimulable Phosphor Plates.

Science.gov (United States)

Eskandarloo, Amir; Yousefi, Arman; Soheili, Setareh; Ghazikhanloo, Karim; Amini, Payam; Mohammadpoor, Haniyeh

2017-01-01

Nowadays, digital radiography is widely used in dental practice. One of the most common types is Photo Stimulated Phosphor Plate (PSP). The aims of this experimental study were to evaluate the impacts of different combinations of storage conditions and varying delays in reading of digital images captured using PSPs. Standardized images of a step wedges were obtained using PSPs from the Digora digital systems. Plates were exposed and immediately scanned to produce the baseline gold standard. The plates were re-exposed and stored in four different storage conditions: white light, yellow light, natural light environment and dark room, then scanned after 10 and 30 minutes and 4 and 8 hours. Objective analysis was conducted by density measurements and the data were analyzed statistically using GEE test. Subjective analysis was performed by two oral and maxillofacial radiologists and the results were analyzed using McNemar's test. The results from GEE analysis show that in the natural light environment, the densities in 10 minutes did not differ from the baseline. The mean densities decreased significantly during the time in all environments. The mean densities in step 2 for the dark room environment decreased with a slighter slope in comparison to yellow environment significantly. PSP images showed significant decrease in the density in plates scanned for 10 minutes or longer after exposure which may not be detected clinically. The yellow light environment had a different impact on the quality of PSP images. The spatial resolution did not change significantly with time.

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

Science.gov (United States)

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.

Monopoly models with time-varying demand function

Science.gov (United States)

Cavalli, Fausto; Naimzada, Ahmad

2018-05-01

We study a family of monopoly models for markets characterized by time-varying demand functions, in which a boundedly rational agent chooses output levels on the basis of a gradient adjustment mechanism. After presenting the model for a generic framework, we analytically study the case of cyclically alternating demand functions. We show that both the perturbation size and the agent's reactivity to profitability variation signals can have counterintuitive roles on the resulting period-2 cycles and on their stability. In particular, increasing the perturbation size can have both a destabilizing and a stabilizing effect on the resulting dynamics. Moreover, in contrast with the case of time-constant demand functions, the agent's reactivity is not just destabilizing, but can improve stability, too. This means that a less cautious behavior can provide better performance, both with respect to stability and to achieved profits. We show that, even if the decision mechanism is very simple and is not able to always provide the optimal production decisions, achieved profits are very close to those optimal. Finally, we show that in agreement with the existing empirical literature, the price series obtained simulating the proposed model exhibit a significant deviation from normality and large volatility, in particular when underlying deterministic dynamics become unstable and complex.

Time-varying parameter models for catchments with land use change: the importance of model structure

Science.gov (United States)

Pathiraja, Sahani; Anghileri, Daniela; Burlando, Paolo; Sharma, Ashish; Marshall, Lucy; Moradkhani, Hamid

2018-05-01

Rapid population and economic growth in Southeast Asia has been accompanied by extensive land use change with consequent impacts on catchment hydrology. Modeling methodologies capable of handling changing land use conditions are therefore becoming ever more important and are receiving increasing attention from hydrologists. A recently developed data-assimilation-based framework that allows model parameters to vary through time in response to signals of change in observations is considered for a medium-sized catchment (2880 km2) in northern Vietnam experiencing substantial but gradual land cover change. We investigate the efficacy of the method as well as the importance of the chosen model structure in ensuring the success of a time-varying parameter method. The method was used with two lumped daily conceptual models (HBV and HyMOD) that gave good-quality streamflow predictions during pre-change conditions. Although both time-varying parameter models gave improved streamflow predictions under changed conditions compared to the time-invariant parameter model, persistent biases for low flows were apparent in the HyMOD case. It was found that HyMOD was not suited to representing the modified baseflow conditions, resulting in extreme and unrealistic time-varying parameter estimates. This work shows that the chosen model can be critical for ensuring the time-varying parameter framework successfully models streamflow under changing land cover conditions. It can also be used to determine whether land cover changes (and not just meteorological factors) contribute to the observed hydrologic changes in retrospective studies where the lack of a paired control catchment precludes such an assessment.

Time-varying parameter models for catchments with land use change: the importance of model structure

Directory of Open Access Journals (Sweden)

S. Pathiraja

2018-05-01

Full Text Available Rapid population and economic growth in Southeast Asia has been accompanied by extensive land use change with consequent impacts on catchment hydrology. Modeling methodologies capable of handling changing land use conditions are therefore becoming ever more important and are receiving increasing attention from hydrologists. A recently developed data-assimilation-based framework that allows model parameters to vary through time in response to signals of change in observations is considered for a medium-sized catchment (2880 km2 in northern Vietnam experiencing substantial but gradual land cover change. We investigate the efficacy of the method as well as the importance of the chosen model structure in ensuring the success of a time-varying parameter method. The method was used with two lumped daily conceptual models (HBV and HyMOD that gave good-quality streamflow predictions during pre-change conditions. Although both time-varying parameter models gave improved streamflow predictions under changed conditions compared to the time-invariant parameter model, persistent biases for low flows were apparent in the HyMOD case. It was found that HyMOD was not suited to representing the modified baseflow conditions, resulting in extreme and unrealistic time-varying parameter estimates. This work shows that the chosen model can be critical for ensuring the time-varying parameter framework successfully models streamflow under changing land cover conditions. It can also be used to determine whether land cover changes (and not just meteorological factors contribute to the observed hydrologic changes in retrospective studies where the lack of a paired control catchment precludes such an assessment.

Response-only modal identification using random decrement algorithm with time-varying threshold level

International Nuclear Information System (INIS)

Lin, Chang Sheng; Tseng, Tse Chuan

2014-01-01

Modal Identification from response data only is studied for structural systems under nonstationary ambient vibration. The topic of this paper is the estimation of modal parameters from nonstationary ambient vibration data by applying the random decrement algorithm with time-varying threshold level. In the conventional random decrement algorithm, the threshold level for evaluating random dec signatures is defined as the standard deviation value of response data of the reference channel. The distortion of random dec signatures may be, however, induced by the error involved in noise from the original response data in practice. To improve the accuracy of identification, a modification of the sampling procedure in random decrement algorithm is proposed for modal-parameter identification from the nonstationary ambient response data. The time-varying threshold level is presented for the acquisition of available sample time history to perform averaging analysis, and defined as the temporal root-mean-square function of structural response, which can appropriately describe a wide variety of nonstationary behaviors in reality, such as the time-varying amplitude (variance) of a nonstationary process in a seismic record. Numerical simulations confirm the validity and robustness of the proposed modal-identification method from nonstationary ambient response data under noisy conditions.

Robust pre-specified time synchronization of chaotic systems by employing time-varying switching surfaces in the sliding mode control scheme

Science.gov (United States)

Khanzadeh, Alireza; Pourgholi, Mahdi

2016-08-01

In the conventional chaos synchronization methods, the time at which two chaotic systems are synchronized, is usually unknown and depends on initial conditions. In this work based on Lyapunov stability theory a sliding mode controller with time-varying switching surfaces is proposed to achieve chaos synchronization at a pre-specified time for the first time. The proposed controller is able to synchronize chaotic systems precisely at any time when we want. Moreover, by choosing the time-varying switching surfaces in a way that the reaching phase is eliminated, the synchronization becomes robust to uncertainties and exogenous disturbances. Simulation results are presented to show the effectiveness of the proposed method of stabilizing and synchronizing chaotic systems with complete robustness to uncertainty and disturbances exactly at a pre-specified time.

Robust pre-specified time synchronization of chaotic systems by employing time-varying switching surfaces in the sliding mode control scheme

International Nuclear Information System (INIS)

Khanzadeh, Alireza; Pourgholi, Mahdi

2016-01-01

In the conventional chaos synchronization methods, the time at which two chaotic systems are synchronized, is usually unknown and depends on initial conditions. In this work based on Lyapunov stability theory a sliding mode controller with time-varying switching surfaces is proposed to achieve chaos synchronization at a pre-specified time for the first time. The proposed controller is able to synchronize chaotic systems precisely at any time when we want. Moreover, by choosing the time-varying switching surfaces in a way that the reaching phase is eliminated, the synchronization becomes robust to uncertainties and exogenous disturbances. Simulation results are presented to show the effectiveness of the proposed method of stabilizing and synchronizing chaotic systems with complete robustness to uncertainty and disturbances exactly at a pre-specified time. (paper)

Forecast Accuracy and Economic Gains from Bayesian Model Averaging using Time Varying Weights

NARCIS (Netherlands)

L.F. Hoogerheide (Lennart); R.H. Kleijn (Richard); H.K. van Dijk (Herman); M.J.C.M. Verbeek (Marno)

2009-01-01

textabstractSeveral Bayesian model combination schemes, including some novel approaches that simultaneously allow for parameter uncertainty, model uncertainty and robust time varying model weights, are compared in terms of forecast accuracy and economic gains using financial and macroeconomic time

The time-varying role of the family in student time use and achievement

Directory of Open Access Journals (Sweden)

Marie C. Hull

2017-10-01

Full Text Available Abstract In this paper, I use a unique dataset linking administrative school data with birth records to quantify the importance of time-varying family factors for child achievement and time use. Specifically, I take a model of academic achievement commonly used in the test score literature, and I augment it to include a family-year effect. Identification comes from the large number of sibling pairs observed in the same year. While prior literature has focused on specific shocks, such as job loss, I capture the full set of innovations that are shared across siblings in a given year. The distributions of fixed effects reveal that annual family innovations, relative to what was expected based on the previous year, are more important than teacher assignment for student achievement and also play a substantial role in the time students spend on homework, free reading, and television. JEL Classification I21, J13, J24

A real-time 3D scanning system for pavement distortion inspection

International Nuclear Information System (INIS)

Li, Qingguang; Yao, Ming; Yao, Xun; Xu, Bugao

2010-01-01

Pavement distortions, such as rutting and shoving, are the common pavement distress problems that need to be inspected and repaired in a timely manner to ensure ride quality and traffic safety. This paper introduces a real-time, low-cost inspection system devoted to detecting these distress features using high-speed 3D transverse scanning techniques. The detection principle is the dynamic generation and characterization of the 3D pavement profile based on structured light triangulation. To improve the accuracy of the system, a multi-view coplanar scheme is employed in the calibration procedure so that more feature points can be used and distributed across the field of view of the camera. A sub-pixel line extraction method is applied for the laser stripe location, which includes filtering, edge detection and spline interpolation. The pavement transverse profile is then generated from the laser stripe curve and approximated by line segments. The second-order derivatives of the segment endpoints are used to identify the feature points of possible distortions. The system can output the real-time measurements and 3D visualization of rutting and shoving distress in a scanned pavement

Time-varying metamaterials based on graphene-wrapped microwires: Modeling and potential applications

Science.gov (United States)

Salary, Mohammad Mahdi; Jafar-Zanjani, Samad; Mosallaei, Hossein

2018-03-01

The successful realization of metamaterials and metasurfaces requires the judicious choice of constituent elements. In this paper, we demonstrate the implementation of time-varying metamaterials in the terahertz frequency regime by utilizing graphene-wrapped microwires as building blocks and modulation of graphene conductivity through exterior electrical gating. These elements enable enhancement of light-graphene interaction by utilizing optical resonances associated with Mie scattering, yielding a large tunability and modulation depth. We develop a semianalytical framework based on transition-matrix formulation for modeling and analysis of periodic and aperiodic arrays of such time-varying building blocks. The proposed method is validated against full-wave numerical results obtained using the finite-difference time-domain method. It provides an ideal tool for mathematical synthesis and analysis of space-time gradient metamaterials, eliminating the need for computationally expensive numerical models. Moreover, it allows for a wider exploration of exotic space-time scattering phenomena in time-modulated metamaterials. We apply the method to explore the role of modulation parameters in the generation of frequency harmonics and their emerging wavefronts. Several potential applications of such platforms are demonstrated, including frequency conversion, holographic generation of frequency harmonics, and spatiotemporal manipulation of light. The presented results provide key physical insights to design time-modulated functional metadevices using various building blocks and open up new directions in the emerging paradigm of time-modulated metamaterials.

Real-Time Imaging with Frequency Scanning Array Antenna for Industrial Inspection Applications at W band

Science.gov (United States)

Larumbe, Belen; Laviada, Jaime; Ibáñez-Loinaz, Asier; Teniente, Jorge

2018-01-01

A real-time imaging system based on a frequency scanning antenna for conveyor belt setups is presented in this paper. The frequency scanning antenna together with an inexpensive parabolic reflector operates at the W band enabling the detection of details with dimensions in the order of 2 mm. In addition, a low level of sidelobes is achieved by optimizing unequal dividers to window the power distribution for sidelobe reduction. Furthermore, the quality of the images is enhanced by the radiation pattern properties. The performance of the system is validated by showing simulation as well as experimental results obtained in real time, proving the feasibility of these kinds of frequency scanning antennas for cost-effective imaging applications.

Parametric output-only identification of time-varying structures using a kernel recursive extended least squares TARMA approach

Science.gov (United States)

Ma, Zhi-Sai; Liu, Li; Zhou, Si-Da; Yu, Lei; Naets, Frank; Heylen, Ward; Desmet, Wim

2018-01-01

The problem of parametric output-only identification of time-varying structures in a recursive manner is considered. A kernelized time-dependent autoregressive moving average (TARMA) model is proposed by expanding the time-varying model parameters onto the basis set of kernel functions in a reproducing kernel Hilbert space. An exponentially weighted kernel recursive extended least squares TARMA identification scheme is proposed, and a sliding-window technique is subsequently applied to fix the computational complexity for each consecutive update, allowing the method to operate online in time-varying environments. The proposed sliding-window exponentially weighted kernel recursive extended least squares TARMA method is employed for the identification of a laboratory time-varying structure consisting of a simply supported beam and a moving mass sliding on it. The proposed method is comparatively assessed against an existing recursive pseudo-linear regression TARMA method via Monte Carlo experiments and shown to be capable of accurately tracking the time-varying dynamics. Furthermore, the comparisons demonstrate the superior achievable accuracy, lower computational complexity and enhanced online identification capability of the proposed kernel recursive extended least squares TARMA approach.

Time-varying exchange rate pass-through: experiences of some industrial countries

OpenAIRE

Toshitaka Sekine

2006-01-01

This paper estimates exchange rate pass-through of six major industrial countries using a time-varying parameter with stochastic volatility model. Exchange rate pass-through is divided into impacts of exchange rate fluctuations to import prices (first-stage pass-through) and those of import price movements to consumer prices (second-stage pass-through). The paper finds that both stages of pass-through have declined over time for all the sample countries. The decline in second-stage pass-throu...

A delay-dependent LMI approach to dynamics analysis of discrete-time recurrent neural networks with time-varying delays

International Nuclear Information System (INIS)

Song, Qiankun; Wang, Zidong

2007-01-01

In this Letter, the analysis problem for the existence and stability of periodic solutions is investigated for a class of general discrete-time recurrent neural networks with time-varying delays. For the neural networks under study, a generalized activation function is considered, and the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. By employing the latest free-weighting matrix method, an appropriate Lyapunov-Krasovskii functional is constructed and several sufficient conditions are established to ensure the existence, uniqueness, and globally exponential stability of the periodic solution for the addressed neural network. The conditions are dependent on both the lower bound and upper bound of the time-varying time delays. Furthermore, the conditions are expressed in terms of the linear matrix inequalities (LMIs), which can be checked numerically using the effective LMI toolbox in MATLAB. Two simulation examples are given to show the effectiveness and less conservatism of the proposed criteria

Achieving Synchronization in Arrays of Coupled Differential Systems with Time-Varying Couplings

Directory of Open Access Journals (Sweden)

Xinlei Yi

2013-01-01

Full Text Available We study complete synchronization of the complex dynamical networks described by linearly coupled ordinary differential equation systems (LCODEs. Here, the coupling is timevarying in both network structure and reaction dynamics. Inspired by our previous paper (Lu et al. (2007-2008, the extended Hajnal diameter is introduced and used to measure the synchronization in a general differential system. Then we find that the Hajnal diameter of the linear system induced by the time-varying coupling matrix and the largest Lyapunov exponent of the synchronized system play the key roles in synchronization analysis of LCODEs with identity inner coupling matrix. As an application, we obtain a general sufficient condition guaranteeing directed time-varying graph to reach consensus. Example with numerical simulation is provided to show the effectiveness of the theoretical results.

Nonlinear systems time-varying parameter estimation: Application to induction motors

Energy Technology Data Exchange (ETDEWEB)

Kenne, Godpromesse [Laboratoire d' Automatique et d' Informatique Appliquee (LAIA), Departement de Genie Electrique, IUT FOTSO Victor, Universite de Dschang, B.P. 134 Bandjoun (Cameroon); Ahmed-Ali, Tarek [Ecole Nationale Superieure des Ingenieurs des Etudes et Techniques d' Armement (ENSIETA), 2 Rue Francois Verny, 29806 Brest Cedex 9 (France); Lamnabhi-Lagarrigue, F. [Laboratoire des Signaux et Systemes (L2S), C.N.R.S-SUPELEC, Universite Paris XI, 3 Rue Joliot Curie, 91192 Gif-sur-Yvette (France); Arzande, Amir [Departement Energie, Ecole Superieure d' Electricite-SUPELEC, 3 Rue Joliot Curie, 91192 Gif-sur-Yvette (France)

2008-11-15

In this paper, an algorithm for time-varying parameter estimation for a large class of nonlinear systems is presented. The proof of the convergence of the estimates to their true values is achieved using Lyapunov theories and does not require that the classical persistent excitation condition be satisfied by the input signal. Since the induction motor (IM) is widely used in several industrial sectors, the algorithm developed is potentially useful for adjusting the controller parameters of variable speed drives. The method proposed is simple and easily implementable in real-time. The application of this approach to on-line estimation of the rotor resistance of IM shows a rapidly converging estimate in spite of measurement noise, discretization effects, parameter uncertainties (e.g. inaccuracies on motor inductance values) and modeling inaccuracies. The robustness analysis for this IM application also revealed that the proposed scheme is insensitive to the stator resistance variations within a wide range. The merits of the proposed algorithm in the case of on-line time-varying rotor resistance estimation are demonstrated via experimental results in various operating conditions of the induction motor. The experimental results obtained demonstrate that the application of the proposed algorithm to update on-line the parameters of an adaptive controller (e.g. IM and synchronous machines adaptive control) can improve the efficiency of the industrial process. The other interesting features of the proposed method include fault detection/estimation and adaptive control of IM and synchronous machines. (author)

Rate Control for Network-Coded Multipath Relaying with Time-Varying Connectivity

Science.gov (United States)

2010-12-10

Armen Babikyan, Nathaniel M. Jones, Thomas H. Shake, and Andrew P. Worthen MIT Lincoln Laboratory 244 Wood Street Lexington, MA 02420 DDRE, 1777...delay U U U U SAR 11 Zach Sweet 781-981-5997 1 Rate Control for Network-Coded Multipath Relaying with Time-Varying Connectivity Brooke Shrader, Armen

The Scalp Time-Varying Networks of N170: Reference, Latency, and Information Flow

Directory of Open Access Journals (Sweden)

Yin Tian

2018-04-01

Full Text Available Using the scalp time-varying network method, the present study is the first to investigate the temporal influence of the reference on N170, a negative event-related potential component (ERP appeared about 170 ms that is elicited by facial recognition, in the network levels. Two kinds of scalp electroencephalogram (EEG references, namely, AR (average of all recording channels and reference electrode standardization technique (REST, were comparatively investigated via the time-varying processing of N170. Results showed that the latency and amplitude of N170 were significantly different between REST and AR, with the former being earlier and smaller. In particular, the information flow from right temporal-parietal P8 to left P7 in the time-varying network was earlier in REST than that in AR, and this phenomenon was reproduced by simulation, in which the performance of REST was closer to the true case at source level. These findings indicate that reference plays a crucial role in ERP data interpretation, and importantly, the newly developed approximate zero-reference REST would be a superior choice for precise evaluation of the scalp spatio-temporal changes relating to various cognitive events.

Precision controlled atomic resolution scanning transmission electron microscopy using spiral scan pathways

Science.gov (United States)

Sang, Xiahan; Lupini, Andrew R.; Ding, Jilai; Kalinin, Sergei V.; Jesse, Stephen; Unocic, Raymond R.

2017-03-01

Atomic-resolution imaging in an aberration-corrected scanning transmission electron microscope (STEM) can enable direct correlation between atomic structure and materials functionality. The fast and precise control of the STEM probe is, however, challenging because the true beam location deviates from the assigned location depending on the properties of the deflectors. To reduce these deviations, i.e. image distortions, we use spiral scanning paths, allowing precise control of a sub-Å sized electron probe within an aberration-corrected STEM. Although spiral scanning avoids the sudden changes in the beam location (fly-back distortion) present in conventional raster scans, it is not distortion-free. “Archimedean” spirals, with a constant angular frequency within each scan, are used to determine the characteristic response at different frequencies. We then show that such characteristic functions can be used to correct image distortions present in more complicated constant linear velocity spirals, where the frequency varies within each scan. Through the combined application of constant linear velocity scanning and beam path corrections, spiral scan images are shown to exhibit less scan distortion than conventional raster scan images. The methodology presented here will be useful for in situ STEM imaging at higher temporal resolution and for imaging beam sensitive materials.

Research on Adaptive Neural Network Control System Based on Nonlinear U-Model with Time-Varying Delay

Directory of Open Access Journals (Sweden)

Fengxia Xu

2014-01-01

Full Text Available U-model can approximate a large class of smooth nonlinear time-varying delay system to any accuracy by using time-varying delay parameters polynomial. This paper proposes a new approach, namely, U-model approach, to solving the problems of analysis and synthesis for nonlinear systems. Based on the idea of discrete-time U-model with time-varying delay, the identification algorithm of adaptive neural network is given for the nonlinear model. Then, the controller is designed by using the Newton-Raphson formula and the stability analysis is given for the closed-loop nonlinear systems. Finally, illustrative examples are given to show the validity and applicability of the obtained results.

Robust stability for uncertain stochastic fuzzy BAM neural networks with time-varying delays

Science.gov (United States)

Syed Ali, M.; Balasubramaniam, P.

2008-07-01

In this Letter, by utilizing the Lyapunov functional and combining with the linear matrix inequality (LMI) approach, we analyze the global asymptotic stability of uncertain stochastic fuzzy Bidirectional Associative Memory (BAM) neural networks with time-varying delays which are represented by the Takagi-Sugeno (TS) fuzzy models. A new class of uncertain stochastic fuzzy BAM neural networks with time varying delays has been studied and sufficient conditions have been derived to obtain conservative result in stochastic settings. The developed results are more general than those reported in the earlier literatures. In addition, the numerical examples are provided to illustrate the applicability of the result using LMI toolbox in MATLAB.

Robust stability for uncertain stochastic fuzzy BAM neural networks with time-varying delays

International Nuclear Information System (INIS)

Syed Ali, M.; Balasubramaniam, P.

2008-01-01

In this Letter, by utilizing the Lyapunov functional and combining with the linear matrix inequality (LMI) approach, we analyze the global asymptotic stability of uncertain stochastic fuzzy Bidirectional Associative Memory (BAM) neural networks with time-varying delays which are represented by the Takagi-Sugeno (TS) fuzzy models. A new class of uncertain stochastic fuzzy BAM neural networks with time varying delays has been studied and sufficient conditions have been derived to obtain conservative result in stochastic settings. The developed results are more general than those reported in the earlier literatures. In addition, the numerical examples are provided to illustrate the applicability of the result using LMI toolbox in MATLAB

Modeling the time--varying subjective quality of HTTP video streams with rate adaptations.

Science.gov (United States)

Chen, Chao; Choi, Lark Kwon; de Veciana, Gustavo; Caramanis, Constantine; Heath, Robert W; Bovik, Alan C

2014-05-01

Newly developed hypertext transfer protocol (HTTP)-based video streaming technologies enable flexible rate-adaptation under varying channel conditions. Accurately predicting the users' quality of experience (QoE) for rate-adaptive HTTP video streams is thus critical to achieve efficiency. An important aspect of understanding and modeling QoE is predicting the up-to-the-moment subjective quality of a video as it is played, which is difficult due to hysteresis effects and nonlinearities in human behavioral responses. This paper presents a Hammerstein-Wiener model for predicting the time-varying subjective quality (TVSQ) of rate-adaptive videos. To collect data for model parameterization and validation, a database of longer duration videos with time-varying distortions was built and the TVSQs of the videos were measured in a large-scale subjective study. The proposed method is able to reliably predict the TVSQ of rate adaptive videos. Since the Hammerstein-Wiener model has a very simple structure, the proposed method is suitable for online TVSQ prediction in HTTP-based streaming.

Robust stability of uncertain Markovian jumping Cohen-Grossberg neural networks with mixed time-varying delays

International Nuclear Information System (INIS)

Sheng Li; Yang Huizhong

2009-01-01

This paper considers the robust stability of a class of uncertain Markovian jumping Cohen-Grossberg neural networks (UMJCGNNs) with mixed time-varying delays. The parameter uncertainties are norm-bounded and the mixed time-varying delays comprise discrete and distributed time delays. Based on the Lyapunov stability theory and linear matrix inequality (LMI) technique, some robust stability conditions guaranteeing the global robust convergence of the equilibrium point are derived. An example is given to show the effectiveness of the proposed results.

The time-varying shortest path problem with fuzzy transit costs and speedup

Directory of Open Access Journals (Sweden)

Rezapour Hassan

2016-08-01

Full Text Available In this paper, we focus on the time-varying shortest path problem, where the transit costs are fuzzy numbers. Moreover, we consider this problem in which the transit time can be shortened at a fuzzy speedup cost. Speedup may also be a better decision to find the shortest path from a source vertex to a specified vertex.

Audiovisual biofeedback improves image quality and reduces scan time for respiratory-gated 3D MRI

Science.gov (United States)

Lee, D.; Greer, P. B.; Arm, J.; Keall, P.; Kim, T.

2014-03-01

The purpose of this study was to test the hypothesis that audiovisual (AV) biofeedback can improve image quality and reduce scan time for respiratory-gated 3D thoracic MRI. For five healthy human subjects respiratory motion guidance in MR scans was provided using an AV biofeedback system, utilizing real-time respiratory motion signals. To investigate the improvement of respiratory-gated 3D MR images between free breathing (FB) and AV biofeedback (AV), each subject underwent two imaging sessions. Respiratory-related motion artifacts and imaging time were qualitatively evaluated in addition to the reproducibility of external (abdominal) motion. In the results, 3D MR images in AV biofeedback showed more anatomic information such as a clear distinction of diaphragm, lung lobes and sharper organ boundaries. The scan time was reduced from 401±215 s in FB to 334±94 s in AV (p-value 0.36). The root mean square variation of the displacement and period of the abdominal motion was reduced from 0.4±0.22 cm and 2.8±2.5 s in FB to 0.1±0.15 cm and 0.9±1.3 s in AV (p-value of displacement audiovisual biofeedback improves image quality and reduces scan time for respiratory-gated 3D MRI. These results suggest that AV biofeedback has the potential to be a useful motion management tool in medical imaging and radiation therapy procedures.

Detection of random alterations to time-varying musical instrument spectra.

Science.gov (United States)

Horner, Andrew; Beauchamp, James; So, Richard

2004-09-01

The time-varying spectra of eight musical instrument sounds were randomly altered by a time-invariant process to determine how detection of spectral alteration varies with degree of alteration, instrument, musical experience, and spectral variation. Sounds were resynthesized with centroids equalized to the original sounds, with frequencies harmonically flattened, and with average spectral error levels of 8%, 16%, 24%, 32%, and 48%. Listeners were asked to discriminate the randomly altered sounds from reference sounds resynthesized from the original data. For all eight instruments, discrimination was very good for the 32% and 48% error levels, moderate for the 16% and 24% error levels, and poor for the 8% error levels. When the error levels were 16%, 24%, and 32%, the scores of musically experienced listeners were found to be significantly better than the scores of listeners with no musical experience. Also, in this same error level range, discrimination was significantly affected by the instrument tested. For error levels of 16% and 24%, discrimination scores were significantly, but negatively correlated with measures of spectral incoherence and normalized centroid deviation on unaltered instrument spectra, suggesting that the presence of dynamic spectral variations tends to increase the difficulty of detecting spectral alterations. Correlation between discrimination and a measure of spectral irregularity was comparatively low.

Positive Almost Periodic Solutions for a Time-Varying Fishing Model with Delay

Directory of Open Access Journals (Sweden)

Xia Li

2011-01-01

Full Text Available This paper is concerned with a time-varying fishing model with delay. By means of the continuation theorem of coincidence degree theory, we prove that it has at least one positive almost periodic solution.

Visualizing time: how linguistic metaphors are incorporated into displaying instruments in the process of interpreting time-varying signals

Science.gov (United States)

Garcia-Belmonte, Germà

2017-06-01

Spatial visualization is a well-established topic of education research that has allowed improving science and engineering students' skills on spatial relations. Connections have been established between visualization as a comprehension tool and instruction in several scientific fields. Learning about dynamic processes mainly relies upon static spatial representations or images. Visualization of time is inherently problematic because time can be conceptualized in terms of two opposite conceptual metaphors based on spatial relations as inferred from conventional linguistic patterns. The situation is particularly demanding when time-varying signals are recorded using displaying electronic instruments, and the image should be properly interpreted. This work deals with the interplay between linguistic metaphors, visual thinking and scientific instrument mediation in the process of interpreting time-varying signals displayed by electronic instruments. The analysis draws on a simplified version of a communication system as example of practical signal recording and image visualization in a physics and engineering laboratory experience. Instrumentation delivers meaningful signal representations because it is designed to incorporate a specific and culturally favored time view. It is suggested that difficulties in interpreting time-varying signals are linked with the existing dual perception of conflicting time metaphors. The activation of specific space-time conceptual mapping might allow for a proper signal interpretation. Instruments play then a central role as visualization mediators by yielding an image that matches specific perception abilities and practical purposes. Here I have identified two ways of understanding time as used in different trajectories through which students are located. Interestingly specific displaying instruments belonging to different cultural traditions incorporate contrasting time views. One of them sees time in terms of a dynamic metaphor

Real-time scanning charged-particle microscope image composition with correction of drift.

Science.gov (United States)

Cizmar, Petr; Vladár, András E; Postek, Michael T

2011-04-01

In this article, a new scanning electron microscopy (SEM) image composition technique is described, which can significantly reduce drift related image corruptions. Drift distortion commonly causes blur and distortions in the SEM images. Such corruption ordinarily appears when conventional image-acquisition methods, i.e., "slow scan" and "fast scan," are applied. The damage is often very significant; it may render images unusable for metrology applications, especially where subnanometer accuracy is required. The described correction technique works with a large number of quickly taken frames, which are properly aligned and then composed into a single image. Such image contains much less noise than the individual frames, while the blur and deformation is minimized. This technique also provides useful information about changes of the sample position in time, which may be applied to investigate the drift properties of the instrument without a need of additional equipment.

Perfect fluid Bianchi Type-I cosmological models with time varying G ...

Indian Academy of Sciences (India)

Abstract. Bianchi Type-I cosmological models containing perfect fluid with time vary- ing G and Λ have been presented. The solutions obtained represent an expansion scalar θ bearing a constant ratio to the anisotropy in the direction of space-like unit vector λi. Of the two models obtained, one has negative vacuum energy ...

Inferring time-varying network topologies from gene expression data.

Science.gov (United States)

Rao, Arvind; Hero, Alfred O; States, David J; Engel, James Douglas

2007-01-01

Most current methods for gene regulatory network identification lead to the inference of steady-state networks, that is, networks prevalent over all times, a hypothesis which has been challenged. There has been a need to infer and represent networks in a dynamic, that is, time-varying fashion, in order to account for different cellular states affecting the interactions amongst genes. In this work, we present an approach, regime-SSM, to understand gene regulatory networks within such a dynamic setting. The approach uses a clustering method based on these underlying dynamics, followed by system identification using a state-space model for each learnt cluster--to infer a network adjacency matrix. We finally indicate our results on the mouse embryonic kidney dataset as well as the T-cell activation-based expression dataset and demonstrate conformity with reported experimental evidence.

Simulation of multicomponent losses in electron beam melting and refining at varying scan frequencies

International Nuclear Information System (INIS)

Powell, A.; Szekely, J.; Van Den Avyle, J.; Damkroger, B.

1995-01-01

A two-stage model is presented to describe alloy element evaporation rates from molten metal due to transient local heating by an electron beam. The first stage is a simulation of transient phenomena near the melt surface due to periodic heating by a scanning beam, the output of which is the relationship between operating parameters, surface temperature, and evaporation rate. At high scan rates, this can be done using a simple one-dimensional heat transfer model of the surface layer; at lower scan rates, a more complex three-dimensional model with fluid flow and periodic boundary conditions is necessary. The second stage couples this evaporation-surface temperature relationship with a larger steady state heat transfer and fluid flow model of an entire melting hearth or mold, in order to calculate local and total evaporation rates. Predictions are compared with experimental results from Sandia's 310-kW electron beam melting furnace, in which evaporation rates and vapor compositions were studied in pure titanium and Ti-6%Al-4%V alloy. Evaporation rates were estimated from rate of condensation on a substrate held over the hearth, and were characterized as a function of beam power (150 and 225 kW), scan frequency (30, 115 and 450 Hz) and background pressure (10 -3 , 10 -4 and 10 -5 torr)

Time-Varying Dynamic Properties of Offshore Wind Turbines Evaluated by Modal Testing

DEFF Research Database (Denmark)

Damgaard, Mads; Andersen, J. K. F.; Ibsen, Lars Bo

2014-01-01

resonance of the wind turbine structure. In this paper, free vibration tests and a numerical Winkler type approach are used to evaluate the dynamic properties of a total of 30 offshore wind turbines located in the North Sea. Analyses indicate time-varying eigenfrequencies and damping ratios of the lowest...... structural eigenmode. Isolating the oscillation oil damper performance, moveable seabed conditions may lead to the observed time dependency....

Complexity Variability Assessment of Nonlinear Time-Varying Cardiovascular Control

Science.gov (United States)

Valenza, Gaetano; Citi, Luca; Garcia, Ronald G.; Taylor, Jessica Noggle; Toschi, Nicola; Barbieri, Riccardo

2017-02-01

The application of complex systems theory to physiology and medicine has provided meaningful information about the nonlinear aspects underlying the dynamics of a wide range of biological processes and their disease-related aberrations. However, no studies have investigated whether meaningful information can be extracted by quantifying second-order moments of time-varying cardiovascular complexity. To this extent, we introduce a novel mathematical framework termed complexity variability, in which the variance of instantaneous Lyapunov spectra estimated over time serves as a reference quantifier. We apply the proposed methodology to four exemplary studies involving disorders which stem from cardiology, neurology and psychiatry: Congestive Heart Failure (CHF), Major Depression Disorder (MDD), Parkinson’s Disease (PD), and Post-Traumatic Stress Disorder (PTSD) patients with insomnia under a yoga training regime. We show that complexity assessments derived from simple time-averaging are not able to discern pathology-related changes in autonomic control, and we demonstrate that between-group differences in measures of complexity variability are consistent across pathologies. Pathological states such as CHF, MDD, and PD are associated with an increased complexity variability when compared to healthy controls, whereas wellbeing derived from yoga in PTSD is associated with lower time-variance of complexity.

Novel criteria for exponential synchronization of inner time-varying complex networks with coupling delay

International Nuclear Information System (INIS)

Zhang Qun-Jiao; Zhao Jun-Chan

2012-01-01

This paper mainly investigates the exponential synchronization of an inner time-varying complex network with coupling delay. Firstly, the synchronization of complex networks is decoupled into the stability of the corresponding dynamical systems. Based on the Lyapunov function theory, some sufficient conditions to guarantee its stability with any given convergence rate are derived, thus the synchronization of the networks is achieved. Finally, the results are illustrated by a simple time-varying network model with a coupling delay. All involved numerical simulations verify the correctness of the theoretical analysis. (general)

Simulations of hybrid system varying solar radiation and microturbine response time

Directory of Open Access Journals (Sweden)

Yolanda Fernández Ribaya

2015-07-01

Full Text Available Hybrid power systems, such as combinations of renewable power sources with intermittent power production and non-renewable power sources, theoretically increase the reliability and thus integration of renewable sources in the electrical system. However, a recent increase in the number of hybrid installations has sparked interest in the effects of their connection to the grid, especially in remote areas. This paper analyses a photovoltaic-gas microturbine hybrid system dimensioned to be installed in La Paz (Mexico.The research presented in this paper studies and quantifies the effects on the total electric power produced, varying both the solar radiation and the gas microturbine response time. The gas microturbine and the photovoltaic panels are modelled using Matlab/Simulink software, obtaining a platform where different tests to simulate real conditions have been executed. They consist of diverse ramps of irradiance that replicate solar radiation variations, and different microturbine response times reproduced by the time constants of a first order transfer function that models the microturbine dynamic response. The results obtained show that when radiation varies quickly it does not produce significant differences in the power guarantee or the microturbine gas consumption, to any microturbine response time. However, these two parameters are highly variable with smooth radiance variations. The maximum total power variation decreases greatly as the radiation variation gets lower. In addition, by decreasing the microturbine response time, it is possible to appreciably increase the power guarantee although the maximum power variation and gas consumption increase. Only in cases of low radiation variation is there no appreciable difference in the maximum power variation obtained by the different turbine response times.

Simulations of hybrid system varying solar radiation and microturbine response time

Energy Technology Data Exchange (ETDEWEB)

Fernández Ribaya, Yolanda, E-mail: fernandezryolanda@uniovi.es; Álvarez, Eduardo; Paredes Sánchez, José Pablo; Xiberta Bernat, Jorge [Department of Energy E.I.M.E.M., University of Oviedo. 13 Independencia Street 2" n" d floor, 36004, Oviedo (Spain)

2015-07-15

Hybrid power systems, such as combinations of renewable power sources with intermittent power production and non-renewable power sources, theoretically increase the reliability and thus integration of renewable sources in the electrical system. However, a recent increase in the number of hybrid installations has sparked interest in the effects of their connection to the grid, especially in remote areas. This paper analyses a photovoltaic-gas microturbine hybrid system dimensioned to be installed in La Paz (Mexico).The research presented in this paper studies and quantifies the effects on the total electric power produced, varying both the solar radiation and the gas microturbine response time. The gas microturbine and the photovoltaic panels are modelled using Matlab/Simulink software, obtaining a platform where different tests to simulate real conditions have been executed. They consist of diverse ramps of irradiance that replicate solar radiation variations, and different microturbine response times reproduced by the time constants of a first order transfer function that models the microturbine dynamic response. The results obtained show that when radiation varies quickly it does not produce significant differences in the power guarantee or the microturbine gas consumption, to any microturbine response time. However, these two parameters are highly variable with smooth radiance variations. The maximum total power variation decreases greatly as the radiation variation gets lower. In addition, by decreasing the microturbine response time, it is possible to appreciably increase the power guarantee although the maximum power variation and gas consumption increase. Only in cases of low radiation variation is there no appreciable difference in the maximum power variation obtained by the different turbine response times.

Noise level estimation in weakly nonlinear slowly time-varying systems

International Nuclear Information System (INIS)

Aerts, J R M; Dirckx, J J J; Lataire, J; Pintelon, R

2008-01-01

Recently, a method using multisine excitation was proposed for estimating the frequency response, the nonlinear distortions and the disturbing noise of weakly nonlinear time-invariant systems. This method has been demonstrated on the measurement of nonlinear distortions in the vibration of acoustically driven systems such as a latex membrane, which is a good example of a time-invariant system [1]. However, not all systems are perfectly time invariant, e.g. biomechanical systems. This time variation can be misinterpreted as an elevated noise floor, and the classical noise estimation method gives a wrong result. Two improved methods to retrieve the correct noise information from the measurements are presented. Both of them make use of multisine excitations. First, it is demonstrated that the improved methods give the same result as the classical noise estimation method when applied to a time-invariant system (high-quality microphone membrane). Next, it is demonstrated that the new methods clearly give an improved estimate of the noise level on time-varying systems. As an application example results for the vibration response of an eardrum are shown

Stability Control of Force-Reflected Nonlinear Multilateral Teleoperation System under Time-Varying Delays

Directory of Open Access Journals (Sweden)

Da Sun

2016-01-01

Full Text Available A novel control algorithm based on the modified wave-variable controllers is proposed to achieve accurate position synchronization and reasonable force tracking of the nonlinear single-master-multiple-slave teleoperation system and simultaneously guarantee overall system’s stability in the presence of large time-varying delays. The system stability in different scenarios of human and environment situations has been analyzed. The proposed method is validated through experimental work based on the 3-DOF trilateral teleoperation system consisting of three different manipulators. The experimental results clearly demonstrate the feasibility of the proposed algorithm to achieve high transparency and robust stability in nonlinear single-master-multiple-slave teleoperation system in the presence of time-varying delays.

A hepatitis C virus infection model with time-varying drug effectiveness: solution and analysis.

Directory of Open Access Journals (Sweden)

Jessica M Conway

2014-08-01

Full Text Available Simple models of therapy for viral diseases such as hepatitis C virus (HCV or human immunodeficiency virus assume that, once therapy is started, the drug has a constant effectiveness. More realistic models have assumed either that the drug effectiveness depends on the drug concentration or that the effectiveness varies over time. Here a previously introduced varying-effectiveness (VE model is studied mathematically in the context of HCV infection. We show that while the model is linear, it has no closed-form solution due to the time-varying nature of the effectiveness. We then show that the model can be transformed into a Bessel equation and derive an analytic solution in terms of modified Bessel functions, which are defined as infinite series, with time-varying arguments. Fitting the solution to data from HCV infected patients under therapy has yielded values for the parameters in the model. We show that for biologically realistic parameters, the predicted viral decay on therapy is generally biphasic and resembles that predicted by constant-effectiveness (CE models. We introduce a general method for determining the time at which the transition between decay phases occurs based on calculating the point of maximum curvature of the viral decay curve. For the parameter regimes of interest, we also find approximate solutions for the VE model and establish the asymptotic behavior of the system. We show that the rate of second phase decay is determined by the death rate of infected cells multiplied by the maximum effectiveness of therapy, whereas the rate of first phase decline depends on multiple parameters including the rate of increase of drug effectiveness with time.

Control-focused, nonlinear and time-varying modelling of dielectric elastomer actuators with frequency response analysis

International Nuclear Information System (INIS)

Jacobs, William R; Dodd, Tony J; Anderson, Sean R; Wilson, Emma D; Porrill, John; Assaf, Tareq; Rossiter, Jonathan

2015-01-01

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. (paper)

A Kalman-filter based approach to identification of time-varying gene regulatory networks.

Directory of Open Access Journals (Sweden)

Jie Xiong

Full Text Available MOTIVATION: Conventional identification methods for gene regulatory networks (GRNs have overwhelmingly adopted static topology models, which remains unchanged over time to represent the underlying molecular interactions of a biological system. However, GRNs are dynamic in response to physiological and environmental changes. Although there is a rich literature in modeling static or temporally invariant networks, how to systematically recover these temporally changing networks remains a major and significant pressing challenge. The purpose of this study is to suggest a two-step strategy that recovers time-varying GRNs. RESULTS: It is suggested in this paper to utilize a switching auto-regressive model to describe the dynamics of time-varying GRNs, and a two-step strategy is proposed to recover the structure of time-varying GRNs. In the first step, the change points are detected by a Kalman-filter based method. The observed time series are divided into several segments using these detection results; and each time series segment belonging to two successive demarcating change points is associated with an individual static regulatory network. In the second step, conditional network structure identification methods are used to reconstruct the topology for each time interval. This two-step strategy efficiently decouples the change point detection problem and the topology inference problem. Simulation results show that the proposed strategy can detect the change points precisely and recover each individual topology structure effectively. Moreover, computation results with the developmental data of Drosophila Melanogaster show that the proposed change point detection procedure is also able to work effectively in real world applications and the change point estimation accuracy exceeds other existing approaches, which means the suggested strategy may also be helpful in solving actual GRN reconstruction problem.

Audiovisual biofeedback improves image quality and reduces scan time for respiratory-gated 3D MRI

International Nuclear Information System (INIS)

Lee, D; Keall, P; Kim, T; Greer, P B; Arm, J

2014-01-01

The purpose of this study was to test the hypothesis that audiovisual (AV) biofeedback can improve image quality and reduce scan time for respiratory-gated 3D thoracic MRI. For five healthy human subjects respiratory motion guidance in MR scans was provided using an AV biofeedback system, utilizing real-time respiratory motion signals. To investigate the improvement of respiratory-gated 3D MR images between free breathing (FB) and AV biofeedback (AV), each subject underwent two imaging sessions. Respiratory-related motion artifacts and imaging time were qualitatively evaluated in addition to the reproducibility of external (abdominal) motion. In the results, 3D MR images in AV biofeedback showed more anatomic information such as a clear distinction of diaphragm, lung lobes and sharper organ boundaries. The scan time was reduced from 401±215 s in FB to 334±94 s in AV (p-value 0.36). The root mean square variation of the displacement and period of the abdominal motion was reduced from 0.4±0.22 cm and 2.8±2.5 s in FB to 0.1±0.15 cm and 0.9±1.3 s in AV (p-value of displacement <0.01 and p-value of period 0.12). This study demonstrated that audiovisual biofeedback improves image quality and reduces scan time for respiratory-gated 3D MRI. These results suggest that AV biofeedback has the potential to be a useful motion management tool in medical imaging and radiation therapy procedures.

Joint optimization of green vehicle scheduling and routing problem with time-varying speeds

Science.gov (United States)

Zhang, Dezhi; Wang, Xin; Ni, Nan; Zhang, Zhuo

2018-01-01

Based on an analysis of the congestion effect and changes in the speed of vehicle flow during morning and evening peaks in a large- or medium-sized city, the piecewise function is used to capture the rules of the time-varying speed of vehicles, which are very important in modelling their fuel consumption and CO2 emission. A joint optimization model of the green vehicle scheduling and routing problem with time-varying speeds is presented in this study. Extra wages during nonworking periods and soft time-window constraints are considered. A heuristic algorithm based on the adaptive large neighborhood search algorithm is also presented. Finally, a numerical simulation example is provided to illustrate the optimization model and its algorithm. Results show that, (1) the shortest route is not necessarily the route that consumes the least energy, (2) the departure time influences the vehicle fuel consumption and CO2 emissions and the optimal departure time saves on fuel consumption and reduces CO2 emissions by up to 5.4%, and (3) extra driver wages have significant effects on routing and departure time slot decisions. PMID:29466370

Mendelian randomization analysis of a time-varying exposure for binary disease outcomes using functional data analysis methods.

Science.gov (United States)

Cao, Ying; Rajan, Suja S; Wei, Peng

2016-12-01

A Mendelian randomization (MR) analysis is performed to analyze the causal effect of an exposure variable on a disease outcome in observational studies, by using genetic variants that affect the disease outcome only through the exposure variable. This method has recently gained popularity among epidemiologists given the success of genetic association studies. Many exposure variables of interest in epidemiological studies are time varying, for example, body mass index (BMI). Although longitudinal data have been collected in many cohort studies, current MR studies only use one measurement of a time-varying exposure variable, which cannot adequately capture the long-term time-varying information. We propose using the functional principal component analysis method to recover the underlying individual trajectory of the time-varying exposure from the sparsely and irregularly observed longitudinal data, and then conduct MR analysis using the recovered curves. We further propose two MR analysis methods. The first assumes a cumulative effect of the time-varying exposure variable on the disease risk, while the second assumes a time-varying genetic effect and employs functional regression models. We focus on statistical testing for a causal effect. Our simulation studies mimicking the real data show that the proposed functional data analysis based methods incorporating longitudinal data have substantial power gains compared to standard MR analysis using only one measurement. We used the Framingham Heart Study data to demonstrate the promising performance of the new methods as well as inconsistent results produced by the standard MR analysis that relies on a single measurement of the exposure at some arbitrary time point. © 2016 WILEY PERIODICALS, INC.

End-of-the-year economic growth and time-varying expected returns

DEFF Research Database (Denmark)

Møller, Stig V.; Rangvid, Jesper

2015-01-01

We show that macroeconomic growth at the end of the year (fourth quarter or December) strongly influences expected returns on risky financial assets, whereas economic growth during the rest of the year does not. We find this pattern for many different asset classes, across different time periods......, and for US and international data. We also show that movements in the surplus consumption ratio of Campbell and Cochrane (1999) , a theoretically well-founded measure of time-varying risk aversion linked to macroeconomic growth, influence expected returns stronger during the fourth quarter than the other...

Novel criteria for global exponential periodicity and stability of recurrent neural networks with time-varying delays

International Nuclear Information System (INIS)

Song Qiankun

2008-01-01

In this paper, the global exponential periodicity and stability of recurrent neural networks with time-varying delays are investigated by applying the idea of vector Lyapunov function, M-matrix theory and inequality technique. We assume neither the global Lipschitz conditions on these activation functions nor the differentiability on these time-varying delays, which were needed in other papers. Several novel criteria are found to ascertain the existence, uniqueness and global exponential stability of periodic solution for recurrent neural network with time-varying delays. Moreover, the exponential convergence rate index is estimated, which depends on the system parameters. Some previous results are improved and generalized, and an example is given to show the effectiveness of our method

Online Support Vector Regression with Varying Parameters for Time-Dependent Data

International Nuclear Information System (INIS)

Omitaomu, Olufemi A.; Jeong, Myong K.; Badiru, Adedeji B.

2011-01-01

Support vector regression (SVR) is a machine learning technique that continues to receive interest in several domains including manufacturing, engineering, and medicine. In order to extend its application to problems in which datasets arrive constantly and in which batch processing of the datasets is infeasible or expensive, an accurate online support vector regression (AOSVR) technique was proposed. The AOSVR technique efficiently updates a trained SVR function whenever a sample is added to or removed from the training set without retraining the entire training data. However, the AOSVR technique assumes that the new samples and the training samples are of the same characteristics; hence, the same value of SVR parameters is used for training and prediction. This assumption is not applicable to data samples that are inherently noisy and non-stationary such as sensor data. As a result, we propose Accurate On-line Support Vector Regression with Varying Parameters (AOSVR-VP) that uses varying SVR parameters rather than fixed SVR parameters, and hence accounts for the variability that may exist in the samples. To accomplish this objective, we also propose a generalized weight function to automatically update the weights of SVR parameters in on-line monitoring applications. The proposed function allows for lower and upper bounds for SVR parameters. We tested our proposed approach and compared results with the conventional AOSVR approach using two benchmark time series data and sensor data from nuclear power plant. The results show that using varying SVR parameters is more applicable to time dependent data.

Robust Moving Horizon H∞ Control of Discrete Time-Delayed Systems with Interval Time-Varying Delays

Directory of Open Access Journals (Sweden)

F. Yıldız Tascikaraoglu

2014-01-01

Full Text Available In this study, design of a delay-dependent type moving horizon state-feedback control (MHHC is considered for a class of linear discrete-time system subject to time-varying state delays, norm-bounded uncertainties, and disturbances with bounded energies. The closed-loop robust stability and robust performance problems are considered to overcome the instability and poor disturbance rejection performance due to the existence of parametric uncertainties and time-delay appeared in the system dynamics. Utilizing a discrete-time Lyapunov-Krasovskii functional, some delay-dependent linear matrix inequality (LMI based conditions are provided. It is shown that if one can find a feasible solution set for these LMI conditions iteratively at each step of run-time, then we can construct a control law which guarantees the closed-loop asymptotic stability, maximum disturbance rejection performance, and closed-loop dissipativity in view of the actuator limitations. Two numerical examples with simulations on a nominal and uncertain discrete-time, time-delayed systems, are presented at the end, in order to demonstrate the efficiency of the proposed method.

Unsynchronized scanning with a low-cost laser range finder for real-time range imaging

Science.gov (United States)

Hatipoglu, Isa; Nakhmani, Arie

2017-06-01

Range imaging plays an essential role in many fields: 3D modeling, robotics, heritage, agriculture, forestry, reverse engineering. One of the most popular range-measuring technologies is laser scanner due to its several advantages: long range, high precision, real-time measurement capabilities, and no dependence on lighting conditions. However, laser scanners are very costly. Their high cost prevents widespread use in applications. Due to the latest developments in technology, now, low-cost, reliable, faster, and light-weight 1D laser range finders (LRFs) are available. A low-cost 1D LRF with a scanning mechanism, providing the ability of laser beam steering for additional dimensions, enables to capture a depth map. In this work, we present an unsynchronized scanning with a low-cost LRF to decrease scanning period and reduce vibrations caused by stop-scan in synchronized scanning. Moreover, we developed an algorithm for alignment of unsynchronized raw data and proposed range image post-processing framework. The proposed technique enables to have a range imaging system for a fraction of the price of its counterparts. The results prove that the proposed method can fulfill the need for a low-cost laser scanning for range imaging for static environments because the most significant limitation of the method is the scanning period which is about 2 minutes for 55,000 range points (resolution of 250x220 image). In contrast, scanning the same image takes around 4 minutes in synchronized scanning. Once faster, longer range, and narrow beam LRFs are available, the methods proposed in this work can produce better results.

Real-time depth monitoring and control of laser machining through scanning beam delivery system

International Nuclear Information System (INIS)

Ji, Yang; Grindal, Alexander W; Fraser, James M; Webster, Paul J L

2015-01-01

Scanning optics enable many laser applications in manufacturing because their low inertia allows rapid movement of the process beam across the sample. We describe our method of inline coherent imaging for real-time (up to 230 kHz) micron-scale (7–8 µm axial resolution) tracking and control of laser machining depth through a scanning galvo-telecentric beam delivery system. For 1 cm trench etching in stainless steel, we collect high speed intrapulse and interpulse morphology which is useful for further understanding underlying mechanisms or comparison with numerical models. We also collect overall sweep-to-sweep depth penetration which can be used for feedback depth control. For trench etching in silicon, we show the relationship of etch rate with average power and scan speed by computer processing of depth information without destructive sample post-processing. We also achieve three-dimensional infrared continuous wave (modulated) laser machining of a 3.96 × 3.96 × 0.5 mm 3 (length × width × maximum depth) pattern on steel with depth feedback. To the best of our knowledge, this is the first successful demonstration of direct real-time depth monitoring and control of laser machining with scanning optics. (paper)

Modelling tourists arrival using time varying parameter

Science.gov (United States)

Suciptawati, P.; Sukarsa, K. G.; Kencana, Eka N.

2017-06-01

The importance of tourism and its related sectors to support economic development and poverty reduction in many countries increase researchers’ attentions to study and model tourists’ arrival. This work is aimed to demonstrate time varying parameter (TVP) technique to model the arrival of Korean’s tourists to Bali. The number of Korean tourists whom visiting Bali for period January 2010 to December 2015 were used to model the number of Korean’s tourists to Bali (KOR) as dependent variable. The predictors are the exchange rate of Won to IDR (WON), the inflation rate in Korea (INFKR), and the inflation rate in Indonesia (INFID). Observing tourists visit to Bali tend to fluctuate by their nationality, then the model was built by applying TVP and its parameters were approximated using Kalman Filter algorithm. The results showed all of predictor variables (WON, INFKR, INFID) significantly affect KOR. For in-sample and out-of-sample forecast with ARIMA’s forecasted values for the predictors, TVP model gave mean absolute percentage error (MAPE) as much as 11.24 percent and 12.86 percent, respectively.

New results on global exponential stability of recurrent neural networks with time-varying delays

International Nuclear Information System (INIS)

Xu Shengyuan; Chu Yuming; Lu Junwei

2006-01-01

This Letter provides new sufficient conditions for the existence, uniqueness and global exponential stability of the equilibrium point of recurrent neural networks with time-varying delays by employing Lyapunov functions and using the Halanay inequality. The time-varying delays are not necessarily differentiable. Both Lipschitz continuous activation functions and monotone nondecreasing activation functions are considered. The derived stability criteria are expressed in terms of linear matrix inequalities (LMIs), which can be checked easily by resorting to recently developed algorithms solving LMIs. Furthermore, the proposed stability results are less conservative than some previous ones in the literature, which is demonstrated via some numerical examples

New results on global exponential stability of recurrent neural networks with time-varying delays

Energy Technology Data Exchange (ETDEWEB)

Xu Shengyuan [Department of Automation, Nanjing University of Science and Technology, Nanjing 210094 (China)]. E-mail: syxu02@yahoo.com.cn; Chu Yuming [Department of Mathematics, Huzhou Teacher' s College, Huzhou, Zhejiang 313000 (China); Lu Junwei [School of Electrical and Automation Engineering, Nanjing Normal University, 78 Bancang Street, Nanjing, 210042 (China)

2006-04-03

This Letter provides new sufficient conditions for the existence, uniqueness and global exponential stability of the equilibrium point of recurrent neural networks with time-varying delays by employing Lyapunov functions and using the Halanay inequality. The time-varying delays are not necessarily differentiable. Both Lipschitz continuous activation functions and monotone nondecreasing activation functions are considered. The derived stability criteria are expressed in terms of linear matrix inequalities (LMIs), which can be checked easily by resorting to recently developed algorithms solving LMIs. Furthermore, the proposed stability results are less conservative than some previous ones in the literature, which is demonstrated via some numerical examples.

Quantum theory for magnons and phonons interactions under time-varying magnetic fields

International Nuclear Information System (INIS)

Guerreiro, S.C.

1971-01-01

The magnon-fonon interaction in a ferromagnetic material submited to a time-varying magnetic field is studied by quantum methods. This problem has already been solved by semi-classical methods, and one of its results is that under certain conditions a state of lattice vibrations may be completely converted into spin oscillations. The main proporties of magnetoelastic waves in static magnetic fields and extend the quantum treatment for the time varying magnetic field case is revised. Field operators whose equations of motion are analogous to the classical ones are introduced. Their equations, which appear as a linear system of first order coupled equations, are converted into equations for complex functions by an expansion of the field operators in a time t as linear combinations of the same operators in a time t 0 prior to the variation of the magnetic field. The quantity g vector obtained from the classical solution is quantized and shown to be the linear momentum density of the magnetoelastic system, the quantum field spin density operator is deduced for the two interacting fields, and finally the results are used to study the magnetization and lattice displacement vector fields in the case of a system described by a coherent state of one of its normal modes

An estimation of U.S. gasoline demand. A smooth time-varying cointegration approach

International Nuclear Information System (INIS)

Park, Sung Y.; Zhao, Guochang

2010-01-01

In this paper the U.S. gasoline demand from 1976 to 2008 is estimated using a time-varying cointegrating regression. We find that price elasticity increased rapidly during the late 1970s and then decreased until 1987. After a relatively small-scaled 'increase-decrease' cycle from 1987 to 2000, the price elasticity rose again after 2000. The time-varying change of the elasticities may be explained by the proportion of gasoline consumption to income and fluctuation of the degree of necessity. The result of the error correction model shows that a deviation from a long-run equilibrium is corrected quickly, and the welfare analysis illustrates there may be a gain by shifting the tax scheme from income tax to gasoline tax. (author)

An estimation of U.S. gasoline demand. A smooth time-varying cointegration approach

Energy Technology Data Exchange (ETDEWEB)

Park, Sung Y. [Department of Economics, University of Illinois, Urbana, IL 61801 (United States); The Wang Yanan Institute for Studies in Economics, Xiamen University, Xiamen, Fujian 361005 (China); Zhao, Guochang [Research School of Economics, College of Business and Economics, The Australian National University, Canberra, ACT 2601 (Australia)

2010-01-15

In this paper the U.S. gasoline demand from 1976 to 2008 is estimated using a time-varying cointegrating regression. We find that price elasticity increased rapidly during the late 1970s and then decreased until 1987. After a relatively small-scaled 'increase-decrease' cycle from 1987 to 2000, the price elasticity rose again after 2000. The time-varying change of the elasticities may be explained by the proportion of gasoline consumption to income and fluctuation of the degree of necessity. The result of the error correction model shows that a deviation from a long-run equilibrium is corrected quickly, and the welfare analysis illustrates there may be a gain by shifting the tax scheme from income tax to gasoline tax. (author)

Time-frequency analysis of time-varying modulated signals based on improved energy separation by iterative generalized demodulation

Science.gov (United States)

Feng, Zhipeng; Chu, Fulei; Zuo, Ming J.

2011-03-01

Energy separation algorithm is good at tracking instantaneous changes in frequency and amplitude of modulated signals, but it is subject to the constraints of mono-component and narrow band. In most cases, time-varying modulated vibration signals of machinery consist of multiple components, and have so complicated instantaneous frequency trajectories on time-frequency plane that they overlap in frequency domain. For such signals, conventional filters fail to obtain mono-components of narrow band, and their rectangular decomposition of time-frequency plane may split instantaneous frequency trajectories thus resulting in information loss. Regarding the advantage of generalized demodulation method in decomposing multi-component signals into mono-components, an iterative generalized demodulation method is used as a preprocessing tool to separate signals into mono-components, so as to satisfy the requirements by energy separation algorithm. By this improvement, energy separation algorithm can be generalized to a broad range of signals, as long as the instantaneous frequency trajectories of signal components do not intersect on time-frequency plane. Due to the good adaptability of energy separation algorithm to instantaneous changes in signals and the mono-component decomposition nature of generalized demodulation, the derived time-frequency energy distribution has fine resolution and is free from cross term interferences. The good performance of the proposed time-frequency analysis is illustrated by analyses of a simulated signal and the on-site recorded nonstationary vibration signal of a hydroturbine rotor during a shut-down transient process, showing that it has potential to analyze time-varying modulated signals of multi-components.

Some properties of zero power neutron noise in a time-varying medium with delayed neutrons

International Nuclear Information System (INIS)

Kitamura, Y.; Pal, L.; Pazsit, I.; Yamamoto, A.; Yamane, Y.

2008-01-01

The temporal evolution of the distribution of the number of neutrons in a time-varying multiplying system, producing only prompt neutrons, was treated recently with the master equation technique by some of the present authors. Such a treatment gives account of both the so-called zero power reactor noise and the power reactor noise simultaneously. In particular, the first two moments of the neutron number, as well as the concept of criticality for time-varying systems, were investigated and discussed. The present paper extends these investigations to the case when delayed neutrons are also taken into account. Due to the complexity of the description, only the expectation of the neutron number is calculated. The concept of criticality of a time-varying system is also generalized to systems with delayed neutrons. The temporal behaviour of the expectation of the number of neutrons and its asymptotic properties are displayed and discussed

Resonant e+e- production by time-varying electromagnetic field

International Nuclear Information System (INIS)

Farakos, K.; Koutsoumbas, G.; Tiktopoulos, G.

1990-01-01

As pointed out by Cornwall and Tiktopoulos (CT) strong, time-varying electric fields may produce e + e - pairs in a resonant fashion. This effect could be related to the sharp peaks in the e + e - spectrum observed in the GSI heavy-ion collision experiments. We attempt to go beyond the case of spatially uniform fields discussed by CT. We find that resonant e + e - production indeed takes place for electric fields derived from four-potentials of the form A 1 =A 2 =A 0 =0, A 3 =δ(t)b(x 3 ) provided by b(x) has discontinuities with a jump at least equal to π. (orig.)

Emergence of synchronization and regularity in firing patterns in time-varying neural hypernetworks

Science.gov (United States)

Rakshit, Sarbendu; Bera, Bidesh K.; Ghosh, Dibakar; Sinha, Sudeshna

2018-05-01

We study synchronization of dynamical systems coupled in time-varying network architectures, composed of two or more network topologies, corresponding to different interaction schemes. As a representative example of this class of time-varying hypernetworks, we consider coupled Hindmarsh-Rose neurons, involving two distinct types of networks, mimicking interactions that occur through the electrical gap junctions and the chemical synapses. Specifically, we consider the connections corresponding to the electrical gap junctions to form a small-world network, while the chemical synaptic interactions form a unidirectional random network. Further, all the connections in the hypernetwork are allowed to change in time, modeling a more realistic neurobiological scenario. We model this time variation by rewiring the links stochastically with a characteristic rewiring frequency f . We find that the coupling strength necessary to achieve complete neuronal synchrony is lower when the links are switched rapidly. Further, the average time required to reach the synchronized state decreases as synaptic coupling strength and/or rewiring frequency increases. To quantify the local stability of complete synchronous state we use the Master Stability Function approach, and for global stability we employ the concept of basin stability. The analytically derived necessary condition for synchrony is in excellent agreement with numerical results. Further we investigate the resilience of the synchronous states with respect to increasing network size, and we find that synchrony can be maintained up to larger network sizes by increasing either synaptic strength or rewiring frequency. Last, we find that time-varying links not only promote complete synchronization, but also have the capacity to change the local dynamics of each single neuron. Specifically, in a window of rewiring frequency and synaptic coupling strength, we observe that the spiking behavior becomes more regular.

Time-Varying Distortions of Binaural Information by Bilateral Hearing Aids

Science.gov (United States)

Rodriguez, Francisco A.; Portnuff, Cory D. F.; Goupell, Matthew J.; Tollin, Daniel J.

2016-01-01

In patients with bilateral hearing loss, the use of two hearing aids (HAs) offers the potential to restore the benefits of binaural hearing, including sound source localization and segregation. However, existing evidence suggests that bilateral HA users’ access to binaural information, namely interaural time and level differences (ITDs and ILDs), can be compromised by device processing. Our objective was to characterize the nature and magnitude of binaural distortions caused by modern digital behind-the-ear HAs using a variety of stimuli and HA program settings. Of particular interest was a common frequency-lowering algorithm known as nonlinear frequency compression, which has not previously been assessed for its effects on binaural information. A binaural beamforming algorithm was also assessed. Wide dynamic range compression was enabled in all programs. HAs were placed on a binaural manikin, and stimuli were presented from an arc of loudspeakers inside an anechoic chamber. Stimuli were broadband noise bursts, 10-Hz sinusoidally amplitude-modulated noise bursts, or consonant–vowel–consonant speech tokens. Binaural information was analyzed in terms of ITDs, ILDs, and interaural coherence, both for whole stimuli and in a time-varying sense (i.e., within a running temporal window) across four different frequency bands (1, 2, 4, and 6 kHz). Key findings were: (a) Nonlinear frequency compression caused distortions of high-frequency envelope ITDs and significantly reduced interaural coherence. (b) For modulated stimuli, all programs caused time-varying distortion of ILDs. (c) HAs altered the relationship between ITDs and ILDs, introducing large ITD–ILD conflicts in some cases. Potential perceptual consequences of measured distortions are discussed. PMID:27698258

Stagewise pseudo-value regression for time-varying effects on the cumulative incidence

DEFF Research Database (Denmark)

Zöller, Daniela; Schmidtmann, Irene; Weinmann, Arndt

2016-01-01

In a competing risks setting, the cumulative incidence of an event of interest describes the absolute risk for this event as a function of time. For regression analysis, one can either choose to model all competing events by separate cause-specific hazard models or directly model the association...... for time-varying effects. This is implemented by coupling variable selection between the grid times, but determining estimates separately. The effect estimates are regularized to also allow for model fitting with a low to moderate number of observations. This technique is illustrated in an application...

Linking the fractional derivative and the Lomnitz creep law to non-Newtonian time-varying viscosity

Science.gov (United States)

Pandey, Vikash; Holm, Sverre

2016-09-01

Many of the most interesting complex media are non-Newtonian and exhibit time-dependent behavior of thixotropy and rheopecty. They may also have temporal responses described by power laws. The material behavior is represented by the relaxation modulus and the creep compliance. On the one hand, it is shown that in the special case of a Maxwell model characterized by a linearly time-varying viscosity, the medium's relaxation modulus is a power law which is similar to that of a fractional derivative element often called a springpot. On the other hand, the creep compliance of the time-varying Maxwell model is identified as Lomnitz's logarithmic creep law, making this possibly its first direct derivation. In this way both fractional derivatives and Lomnitz's creep law are linked to time-varying viscosity. A mechanism which yields fractional viscoelasticity and logarithmic creep behavior has therefore been found. Further, as a result of this linking, the curve-fitting parameters involved in the fractional viscoelastic modeling, and the Lomnitz law gain physical interpretation.

Pollinator effectiveness varies with experimental shifts in flowering time.

Science.gov (United States)

Rafferty, Nicole E; Ives, Anthony R

2012-04-01

The earlier flowering times exhibited by many plant species are a conspicuous sign of climate change. Altered phenologies have caused concern that species could suffer population declines if they flower at times when effective pollinators are unavailable. For two perennial wildflowers, Tradescantia ohiensis and Asclepias incarnata, we used an experimental approach to explore how changing phenology affects the taxonomic composition of the pollinator assemblage and the effectiveness of individual pollinator taxa. After finding in the previous year that fruit set varied with flowering time, we manipulated flowering onset in greenhouses, placed plants in the field over the span of five weeks, and measured pollinator effectiveness as the number of seeds produced after a single visit to a flower. The average effectiveness of pollinators and the expected rates of pollination success were lower for plants of both species flowering earlier than for plants flowering at historical times, suggesting there could be reproductive costs to earlier flowering. Whereas for A. incarnata, differences in average seed set among weeks were due primarily to changes in the composition of the pollinator assemblage, the differences for T. ohiensis were driven by the combined effects of compositional changes and increases over time in the effectiveness of some pollinator taxa. Both species face the possibility of temporal mismatch between the availability of the most effective pollinators and the onset of flowering, and changes in the effectiveness of individual pollinator taxa through time may add an unexpected element to the reproductive consequences of such mismatches.

Consumer responses to time varying prices for electricity

International Nuclear Information System (INIS)

Thorsnes, Paul; Williams, John; Lawson, Rob

2012-01-01

We report new experimental evidence of the household response to weekday differentials in peak and off-peak electricity prices. The data come from Auckland, New Zealand, where peak residential electricity consumption occurs in winter for heating. Peak/off-peak price differentials ranged over four randomly selected groups from 1.0 to 3.5. On average, there was no response except in winter. In winter, participant households reduced electricity consumption by at least 10%, took advantage of lower off-peak prices but did not respond to the peak price differentials. Response varied with house and household size, time spent away from home, and whether water was heated with electricity. - Highlights: ► Seasonal effects in winter. ► High conservation effect from information. ► Higher peak prices no effect on peak use. ► Low off-peak prices encourage less conservation off-peak.

Combined risk assessment of nonstationary monthly water quality based on Markov chain and time-varying copula.

Science.gov (United States)

Shi, Wei; Xia, Jun

2017-02-01

Water quality risk management is a global hot research linkage with the sustainable water resource development. Ammonium nitrogen (NH 3 -N) and permanganate index (COD Mn ) as the focus indicators in Huai River Basin, are selected to reveal their joint transition laws based on Markov theory. The time-varying moments model with either time or land cover index as explanatory variables is applied to build the time-varying marginal distributions of water quality time series. Time-varying copula model, which takes the non-stationarity in the marginal distribution and/or the time variation in dependence structure between water quality series into consideration, is constructed to describe a bivariate frequency analysis for NH 3 -N and COD Mn series at the same monitoring gauge. The larger first-order Markov joint transition probability indicates water quality state Class V w , Class IV and Class III will occur easily in the water body of Bengbu Sluice. Both marginal distribution and copula models are nonstationary, and the explanatory variable time yields better performance than land cover index in describing the non-stationarities in the marginal distributions. In modelling the dependence structure changes, time-varying copula has a better fitting performance than the copula with the constant or the time-trend dependence parameter. The largest synchronous encounter risk probability of NH 3 -N and COD Mn simultaneously reaching Class V is 50.61%, while the asynchronous encounter risk probability is largest when NH 3 -N and COD Mn is inferior to class V and class IV water quality standards, respectively.

Time of Progression to Osteopenia/Osteoporosis in Chronically HIV-Infected Patients: Screening DXA Scan

Science.gov (United States)

Negredo, Eugenia; Bonjoch, Anna; Gómez-Mateu, Moisés; Estany, Carla; Puig, Jordi; Perez-Alvarez, Nuria; Rosales, Joaquin; di Gregorio, Silvana; del Rio, Luis; Gómez, Guadalupe; Clotet, Bonaventura

2012-01-01

Background Algorithms for bone mineral density (BMD) management in HIV-infected patients are lacking. Our objective was to assess how often a dual-energy x-ray absorptiometry (DXA) scan should be performed by assessing time of progression to osteopenia/osteoporosis. Methods All DXA scans performed between 2000 and 2009 from HIV-infected patients with at least two DXA were included. Time to an event (osteopenia and osteoporosis) was assessed using the Kaplan–Meier method. Strata (tertiles) were defined using baseline minimum T scores. Differences between strata in time to an event were compared with the log-rank test. Results Of 391 patients (1,639 DXAs), 49.6% had osteopenia and 21.7% osteoporosis at their first DXA scan. Of the 112 (28.6%) with normal BMD, 35.7% progressed to osteopenia; median progression time was 6.7 years. These patients were stratified: “low-risk" (baseline minimum T score >−0.2 SD), “middle-risk" (between −0.2 and −0.6 SD), and “high-risk" (from −0.6 to −1 SD); median progression time to osteopenia was 8.7, >7.2, and 1.7 years, respectively (ppatients with osteopenia, 23.7% progressed to osteoporosis; median progression time was >8.5 years. Progression time was >8.2 years in “low-risk" tertile (T score between −1.1 and −1.6 SD), >8.5 years in “middle-risk" (between −1.6 and −2), and 3.2 years in “high-risk" (from −2 to −2.4) (ppatients with bone demineralization could reduce fracture–related morbidity/mortality. PMID:23056229

Computing and visualizing time-varying merge trees for high-dimensional data

Energy Technology Data Exchange (ETDEWEB)

Oesterling, Patrick [Univ. of Leipzig (Germany); Heine, Christian [Univ. of Kaiserslautern (Germany); Weber, Gunther H. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Morozov, Dmitry [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Scheuermann, Gerik [Univ. of Leipzig (Germany)

2017-06-03

We introduce a new method that identifies and tracks features in arbitrary dimensions using the merge tree -- a structure for identifying topological features based on thresholding in scalar fields. This method analyzes the evolution of features of the function by tracking changes in the merge tree and relates features by matching subtrees between consecutive time steps. Using the time-varying merge tree, we present a structural visualization of the changing function that illustrates both features and their temporal evolution. We demonstrate the utility of our approach by applying it to temporal cluster analysis of high-dimensional point clouds.

A novel near real-time laser scanning device for geometrical determination of pleural cavity surface.

Science.gov (United States)

Kim, Michele M; Zhu, Timothy C

2013-02-02

During HPPH-mediated pleural photodynamic therapy (PDT), it is critical to determine the anatomic geometry of the pleural surface quickly as there may be movement during treatment resulting in changes with the cavity. We have developed a laser scanning device for this purpose, which has the potential to obtain the surface geometry in real-time. A red diode laser with a holographic template to create a pattern and a camera with auto-focusing abilities are used to scan the cavity. In conjunction with a calibration with a known surface, we can use methods of triangulation to reconstruct the surface. Using a chest phantom, we are able to obtain a 360 degree scan of the interior in under 1 minute. The chest phantom scan was compared to an existing CT scan to determine its accuracy. The laser-camera separation can be determined through the calibration with 2mm accuracy. The device is best suited for environments that are on the scale of a chest cavity (between 10cm and 40cm). This technique has the potential to produce cavity geometry in real-time during treatment. This would enable PDT treatment dosage to be determined with greater accuracy. Works are ongoing to build a miniaturized device that moves the light source and camera via a fiber-optics bundle commonly used for endoscopy with increased accuracy.

Theory of life time measurements with the scanning electron microscope: steady state

NARCIS (Netherlands)

Berz, F.; Kuiken, H.K.

1976-01-01

A theoretical steady state analysis is given of the scanning electron microscope method of measuring bulk life time in diodes, where the plane of the junction is perpendicular to the surface. The current in the junction is obtained as a function of the beam power, the beam penetration into the

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

International Nuclear Information System (INIS)

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

2012-01-01

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. (general)

Stability in Cohen Grossberg-type bidirectional associative memory neural networks with time-varying delays

Science.gov (United States)

Cao, Jinde; Song, Qiankun

2006-07-01

In this paper, the exponential stability problem is investigated for a class of Cohen-Grossberg-type bidirectional associative memory neural networks with time-varying delays. By using the analysis method, inequality technique and the properties of an M-matrix, several novel sufficient conditions ensuring the existence, uniqueness and global exponential stability of the equilibrium point are derived. Moreover, the exponential convergence rate is estimated. The obtained results are less restrictive than those given in the earlier literature, and the boundedness and differentiability of the activation functions and differentiability of the time-varying delays are removed. Two examples with their simulations are given to show the effectiveness of the obtained results.

Assessing ScanSAR Interferometry for Deformation Studies

Science.gov (United States)

Buckley, S. M.; Gudipati, K.

2007-12-01

There is a trend in civil satellite SAR mission design to implement an imaging strategy that incorporates both stripmap mode and ScanSAR imaging. This represents a compromise between high resolution data collection and a desire for greater spatial coverage and more frequent revisit times. However, mixed mode imaging can greatly reduce the number of stripmap images available for measuring subtle ground deformation. Although ScanSAR-ScanSAR and ScanSAR-stripmap repeat-pass interferometry have been demonstrated, these approaches are infrequently used for single interferogram formation and nonexistent for InSAR time series analysis. For future mission design, e.g., a dedicated US InSAR mission, the effect of various ScanSAR system parameter choices on InSAR time series analysis also remains unexplored. Our objective is to determine the utility of ScanSAR differential interferometry. We will demonstrate the use of ScanSAR interferograms for several previous deformation studies: localized and broad-scale urban land subsidence, tunneling, volcanic surface movements and several examples associated with the seismic cycle. We also investigate the effect of various ScanSAR burst synchronization levels on our ability to detect and make quality measurements of deformation. To avoid the issues associated with Envisat ScanSAR burst alignment and to exploit a decade of InSAR measurements, we simulate ScanSAR data by bursting (throwing away range lines of) ERS-1/2 data. All the burst mode datasets are processed using a Modified SPECAN algorithm. To investigate the effects of burst misalignment, a number of cases with varying degrees of burst overlap are considered. In particular, we look at phase decorrelation as a function of percentage of burst overlap. Coherence clearly reduces as the percentage of overlap decreases and we find a useful threshold of 40-70% burst overlap depending on the study site. In order to get a more generalized understanding for different surface conditions

A Comparison of Evolutionary Algorithms for Tracking Time-Varying Recursive Systems

Directory of Open Access Journals (Sweden)

White Michael S

2003-01-01

Full Text Available A comparison is made of the behaviour of some evolutionary algorithms in time-varying adaptive recursive filter systems. Simulations show that an algorithm including random immigrants outperforms a more conventional algorithm using the breeder genetic algorithm as the mutation operator when the time variation is discontinuous, but neither algorithm performs well when the time variation is rapid but smooth. To meet this deficit, a new hybrid algorithm which uses a hill climber as an additional genetic operator, applied for several steps at each generation, is introduced. A comparison is made of the effect of applying the hill climbing operator a few times to all members of the population or a larger number of times solely to the best individual; it is found that applying to the whole population yields the better results, substantially improved compared with those obtained using earlier methods.

Asymptotic theory of time varying networks with burstiness and heterogeneous activation patterns

Science.gov (United States)

Burioni, Raffaella; Ubaldi, Enrico; Vezzani, Alessandro

2017-05-01

The recent availability of large-scale, time-resolved and high quality digital datasets has allowed for a deeper understanding of the structure and properties of many real-world networks. The empirical evidence of a temporal dimension prompted the switch of paradigm from a static representation of networks to a time varying one. In this work we briefly review the framework of time-varying-networks in real world social systems, especially focusing on the activity-driven paradigm. We develop a framework that allows for the encoding of three generative mechanisms that seem to play a central role in the social networks’ evolution: the individual’s propensity to engage in social interactions, its strategy in allocate these interactions among its alters and the burstiness of interactions amongst social actors. The functional forms and probability distributions encoding these mechanisms are typically data driven. A natural question arises if different classes of strategies and burstiness distributions, with different local scale behavior and analogous asymptotics can lead to the same long time and large scale structure of the evolving networks. We consider the problem in its full generality, by investigating and solving the system dynamics in the asymptotic limit, for general classes of ties allocation mechanisms and waiting time probability distributions. We show that the asymptotic network evolution is driven by a few characteristics of these functional forms, that can be extracted from direct measurements on large datasets.

Study of selected phenotype switching strategies in time varying environment

Energy Technology Data Exchange (ETDEWEB)

Horvath, Denis, E-mail: horvath.denis@gmail.com [Centre of Interdisciplinary Biosciences, Institute of Physics, Faculty of Science, P.J. Šafárik University in Košice, Jesenná 5, 040 01 Košice (Slovakia); Brutovsky, Branislav, E-mail: branislav.brutovsky@upjs.sk [Department of Biophysics, Institute of Physics, P.J. Šafárik University in Košice, Jesenná 5, 040 01 Košice (Slovakia)

2016-03-22

Population heterogeneity plays an important role across many research, as well as the real-world, problems. The population heterogeneity relates to the ability of a population to cope with an environment change (or uncertainty) preventing its extinction. However, this ability is not always desirable as can be exemplified by an intratumor heterogeneity which positively correlates with the development of resistance to therapy. Causation of population heterogeneity is therefore in biology and medicine an intensively studied topic. In this paper the evolution of a specific strategy of population diversification, the phenotype switching, is studied at a conceptual level. The presented simulation model studies evolution of a large population of asexual organisms in a time-varying environment represented by a stochastic Markov process. Each organism disposes with a stochastic or nonlinear deterministic switching strategy realized by discrete-time models with evolvable parameters. We demonstrate that under rapidly varying exogenous conditions organisms operate in the vicinity of the bet-hedging strategy, while the deterministic patterns become relevant as the environmental variations are less frequent. Statistical characterization of the steady state regimes of the populations is done using the Hellinger and Kullback–Leibler functional distances and the Hamming distance. - Highlights: • Relation between phenotype switching and environment is studied. • The Markov chain Monte Carlo based model is developed. • Stochastic and deterministic strategies of phenotype switching are utilized. • Statistical measures of the dynamic heterogeneity reveal universal properties. • The results extend to higher lattice dimensions.

Study of selected phenotype switching strategies in time varying environment

International Nuclear Information System (INIS)

Horvath, Denis; Brutovsky, Branislav

2016-01-01

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. - Highlights: • Relation between phenotype switching and environment is studied. • The Markov chain Monte Carlo based model is developed. • Stochastic and deterministic strategies of phenotype switching are utilized. • Statistical measures of the dynamic heterogeneity reveal universal properties. • The results extend to higher lattice dimensions.

Bank loan components and the time-varying effects of monetary policy shocks

NARCIS (Netherlands)

den Haan, W.J.; Sumner, S.W.; Yamashiro, G.M.

2011-01-01

The impulse response function (IRF) of an aggregate variable is time-varying if the IRFs of its components are different from each other and the relative magnitudes of the components are not constant—two conditions likely to be true in practice. We model the behaviour of loan components and document

Scan path entropy and Arrow plots: Capturing scanning behavior of multiple observers

Directory of Open Access Journals (Sweden)

Ignace T C Hooge

2013-12-01

Full Text Available Designers of visual communication material want their material to attract and retain attention. In marketing research, heat maps, dwell time, and time to AOI first hit are often used as evaluation parameters. Here we present two additional measures 1 scan path entropy to quantify gaze guidance and 2 the arrow plot to visualize the average scan path. Both are based on string representations of scan paths. The latter also incorporates transition matrices and time required for 50% of the observers to first hit AOIs (T50. The new measures were tested in an eye tracking study (48 observers, 39 advertisements. Scan path entropy is a sensible measure for gaze guidance and the new visualization method reveals aspects of the average scan path and gives a better indication in what order global scanning takes place.

Improved Criteria on Delay-Dependent Stability for Discrete-Time Neural Networks with Interval Time-Varying Delays

Directory of Open Access Journals (Sweden)

O. M. Kwon

2012-01-01

Full Text Available The purpose of this paper is to investigate the delay-dependent stability analysis for discrete-time neural networks with interval time-varying delays. Based on Lyapunov method, improved delay-dependent criteria for the stability of the networks are derived in terms of linear matrix inequalities (LMIs by constructing a suitable Lyapunov-Krasovskii functional and utilizing reciprocally convex approach. Also, a new activation condition which has not been considered in the literature is proposed and utilized for derivation of stability criteria. Two numerical examples are given to illustrate the effectiveness of the proposed method.

Output-Only Modal Parameter Recursive Estimation of Time-Varying Structures via a Kernel Ridge Regression FS-TARMA Approach

Directory of Open Access Journals (Sweden)

Zhi-Sai Ma

2017-01-01

Full Text Available Modal parameter estimation plays an important role in vibration-based damage detection and is worth more attention and investigation, as changes in modal parameters are usually being used as damage indicators. This paper focuses on the problem of output-only modal parameter recursive estimation of time-varying structures based upon parameterized representations of the time-dependent autoregressive moving average (TARMA. A kernel ridge regression functional series TARMA (FS-TARMA recursive identification scheme is proposed and subsequently employed for the modal parameter estimation of a numerical three-degree-of-freedom time-varying structural system and a laboratory time-varying structure consisting of a simply supported beam and a moving mass sliding on it. The proposed method is comparatively assessed against an existing recursive pseudolinear regression FS-TARMA approach via Monte Carlo experiments and shown to be capable of accurately tracking the time-varying dynamics in a recursive manner.

Time-Varying Market Integration and Expected Returns in Emerging Markets

OpenAIRE

de Jong, Frank; de Roon, Frans

2001-01-01

We use a simple model in which the expected returns in emerging markets depend on their systematic risk as measured by their beta relative to the world portfolio as well as on the level of integration in that market. The level of integration is a time-varying variable that depends on the market value of the assets that can be held by domestic investors only versus the market value of the assets that can be traded freely. Our empirical analysis for 30 emerging markets shows that there are stro...

Time Varying Market Integration and Expected Rteurns in Emerging Markets

OpenAIRE

Jong, F.C.J.M. de; Roon, F.A. de

2001-01-01

We use a simple model in which the expected returns in emerging markets depend on their systematic risk as measured by their beta relative to the world portfolio as well as on the level of integration in that market.The level of integration is a time-varying variable that depends on the market value of the assets that can be held by domestic investors only versus the market value of the assets that can be traded freely.Our empirical analysis for 30 emerging markets shows that there are strong...

Real-time dose compensation methods for scanned ion beam therapy of moving tumors

International Nuclear Information System (INIS)

Luechtenborg, Robert

2012-01-01

Scanned ion beam therapy provides highly tumor-conformal treatments. So far, only tumors showing no considerable motion during therapy have been treated as tumor motion and dynamic beam delivery interfere, causing dose deteriorations. One proposed technique to mitigate these deteriorations is beam tracking (BT), which adapts the beam position to the moving tumor. Despite application of BT, dose deviations can occur in the case of non-translational motion. In this work, real-time dose compensation combined with beam tracking (RDBT) has been implemented into the control system to compensate these dose changes by adaptation of nominal particle numbers during irradiation. Compared to BT, significantly reduced dose deviations were measured using RDBT. Treatment planning studies for lung cancer patients including the increased biological effectiveness of ions revealed a significantly reduced over-dose level (3/5 patients) as well as significantly improved dose homogeneity (4/5 patients) for RDBT. Based on these findings, real-time dose compensated re-scanning (RDRS) has been proposed that potentially supersedes the technically complex fast energy adaptation necessary for BT and RDBT. Significantly improved conformity compared to re-scanning, i.e., averaging of dose deviations by repeated irradiation, was measured in film irradiations. Simulations comparing RDRS to BT revealed reduced under- and overdoses of the former method.

Projective synchronization of time-varying delayed neural network with adaptive scaling factors

International Nuclear Information System (INIS)

Ghosh, Dibakar; Banerjee, Santo

2013-01-01

Highlights: • Projective synchronization in coupled delayed neural chaotic systems with modulated delay time is introduced. • An adaptive rule for the scaling factors is introduced. • This scheme is highly applicable in secure communication. -- Abstract: In this work, the projective synchronization between two continuous time delayed neural systems with time varying delay is investigated. A sufficient condition for synchronization for the coupled systems with modulated delay is presented analytically with the help of the Krasovskii–Lyapunov approach. The effect of adaptive scaling factors on synchronization are also studied in details. Numerical simulations verify the effectiveness of the analytic results

The effect of a scanning flat fold mirror on a cosmic microwave background B-mode experiment.

Science.gov (United States)

Grainger, William F; North, Chris E; Ade, Peter A R

2011-06-01

We investigate the possibility of using a flat-fold beam steering mirror for a cosmic microwave background B-mode experiment. An aluminium flat-fold mirror is found to add ∼0.075% polarization, which varies in a scan synchronous way. Time-domain simulations of a realistic scanning pattern are performed, and the effect on the power-spectrum illustrated, and a possible method of correction applied. © 2011 American Institute of Physics

Robust convergence of Cohen-Grossberg neural networks with time-varying delays

International Nuclear Information System (INIS)

Xiong Wenjun; Ma Deyi; Liang Jinling

2009-01-01

In this paper, robust convergence is studied for the Cohen-Grossberg neural networks (CGNNs) with time-varying delays. By applying the differential inequality and the Lyapunov method, some delay-independent conditions are derived ensuring the robust CGNNs to converge, globally, uniformly and exponentially, to a ball in the state space with a pre-specified convergence rate. Finally, the effectiveness of our results are verified by an illustrative example.

Specification and testing of Multiplicative Time-Varying GARCH models with applications

DEFF Research Database (Denmark)

Amado, Cristina; Teräsvirta, Timo

2017-01-01

In this article, we develop a specification technique for building multiplicative time-varying GARCH models of Amado and Teräsvirta (2008, 2013). The variance is decomposed into an unconditional and a conditional component such that the unconditional variance component is allowed to evolve smooth...... is illustrated in practice with two real examples: an empirical application to daily exchange rate returns and another one to daily coffee futures returns....

Non-scanning x-ray fluorescence microscope: application to real time micro-imaging

International Nuclear Information System (INIS)

Sakurai, K.; Eba, H.

2000-01-01

So far, x-ray fluorescence (XRF) micro-imaging has been performed by a 2D positional scan of a sample against a collimated beam. Obtaining information on specific elements in a nondestructive manner is an attractive prospect for many scientific applications. Furthermore, a synchrotron micro-beam can enhance the spatial resolution down to 0.1 μm. However, the total measuring time becomes quite long (a few hours to a half day), since one needs a number of scanning points in order to obtain a high-quality image. It is possible to obtain an x-ray image with 1 M pixels and with 20 μm resolution in a very short time of 20 sec - 3 min using a non-scanning XRF microscope, which is based on completely different concept. In the present report, we discuss the application of this technique to real time micro-imaging. The experiments were carried out at BL-4A, Photon Factory, Tsukuba, Japan. We employed a grazing-incidence arrangement to make primary x-rays illuminate the whole sample surface. We adopted parallel-beam optics and extremely-close-geometry in order to detect x-ray fluorescence with a CCD camera. The selective-excitation capability of tunable monochromatic synchrotron radiation is a feasible method for distinguishing the elements of interest. One can obtain an image of each element by differentiating the images obtained above and below the absorption edges of interest. The growth of metallic dendrites from a solution dropped on a substrate was studied successfully. Several different growth patterns, corresponding to concentration and other conditions for diffusion, were observed as x-ray images. Since the present technique requires only 40 sec for each shot, it is possible to record a growing process through repeated exposures like a movie. The authors would like to thank Prof. A. Iida (Photon Factory) for his valuable comments. (author)

Distributed Event-Triggered Control of Multiagent Systems with Time-Varying Topology

Directory of Open Access Journals (Sweden)

Jingwei Ma

2014-01-01

Full Text Available This paper studies the consensus of first-order discrete-time multiagent systems, where the interaction topology is time-varying. The event-triggered control is used to update the control input of each agent, and the event-triggering condition is designed based on the combination of the relative states of each agent to its neighbors. By applying the common Lyapunov function method, a sufficient condition for consensus, which is expressed as a group of linear matrix inequalities, is obtained and the feasibility of these linear matrix inequalities is further analyzed. Simulation examples are provided to explain the effectiveness of the theoretical results.

Solution to the monoenergetic time-dependent neutron transport equation with a time-varying source

International Nuclear Information System (INIS)

Ganapol, B.D.

1986-01-01

Even though fundamental time-dependent neutron transport problems have existed since the inception of neutron transport theory, it has only been recently that a reliable numerical solution to one of the basic problems has been obtained. Experience in generating numerical solutions to time-dependent transport equations has indicated that the multiple collision formulation is the most versatile numerical technique for model problems. The formulation coupled with a moment reconstruction of each collided flux component has led to benchmark-quality (four- to five-digit accuracy) numerical evaluation of the neutron flux in plane infinite geometry for any degree of scattering anisotropy and for both pulsed isotropic and beam sources. As will be shown in this presentation, this solution can serve as a Green's function, thus extending the previous results to more complicated source situations. Here we will be concerned with a time-varying source at the center of an infinite medium. If accurate, such solutions have both pedagogical and practical uses as benchmarks against which other more approximate solutions designed for a wider class of problems can be compared

Scalable Video Streaming Adaptive to Time-Varying IEEE 802.11 MAC Parameters

Science.gov (United States)

Lee, Kyung-Jun; Suh, Doug-Young; Park, Gwang-Hoon; Huh, Jae-Doo

This letter proposes a QoS control method for video streaming service over wireless networks. Based on statistical analysis, the time-varying MAC parameters highly related to channel condition are selected to predict available bitrate. Adaptive bitrate control of scalably-encoded video guarantees continuity in streaming service even if the channel condition changes abruptly.

Distributed Time-Varying Formation Robust Tracking for General Linear Multiagent Systems With Parameter Uncertainties and External Disturbances.

Science.gov (United States)

Hua, Yongzhao; Dong, Xiwang; Li, Qingdong; Ren, Zhang

2017-05-18

This paper investigates the time-varying formation robust tracking problems for high-order linear multiagent systems with a leader of unknown control input in the presence of heterogeneous parameter uncertainties and external disturbances. The followers need to accomplish an expected time-varying formation in the state space and track the state trajectory produced by the leader simultaneously. First, a time-varying formation robust tracking protocol with a totally distributed form is proposed utilizing the neighborhood state information. With the adaptive updating mechanism, neither any global knowledge about the communication topology nor the upper bounds of the parameter uncertainties, external disturbances and leader's unknown input are required in the proposed protocol. Then, in order to determine the control parameters, an algorithm with four steps is presented, where feasible conditions for the followers to accomplish the expected time-varying formation tracking are provided. Furthermore, based on the Lyapunov-like analysis theory, it is proved that the formation tracking error can converge to zero asymptotically. Finally, the effectiveness of the theoretical results is verified by simulation examples.

Reusable Launch Vehicle Attitude Control Using a Time-Varying Sliding Mode Control Technique

Science.gov (United States)

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.

On the Anonymity Risk of Time-Varying User Profiles

Directory of Open Access Journals (Sweden)

Silvia Puglisi

2017-04-01

Full Text Available Websites and applications use personalisation services to profile their users, collect their patterns and activities and eventually use this data to provide tailored suggestions. User preferences and social interactions are therefore aggregated and analysed. Every time a user publishes a new post or creates a link with another entity, either another user, or some online resource, new information is added to the user profile. Exposing private data does not only reveal information about single users’ preferences, increasing their privacy risk, but can expose more about their network that single actors intended. This mechanism is self-evident in social networks where users receive suggestions based on their friends’ activities. We propose an information-theoretic approach to measure the differential update of the anonymity risk of time-varying user profiles. This expresses how privacy is affected when new content is posted and how much third-party services get to know about the users when a new activity is shared. We use actual Facebook data to show how our model can be applied to a real-world scenario.

Modeling intensive longitudinal data with mixtures of nonparametric trajectories and time-varying effects.

Science.gov (United States)

Dziak, John J; Li, Runze; Tan, Xianming; Shiffman, Saul; Shiyko, Mariya P

2015-12-01

Behavioral scientists increasingly collect intensive longitudinal data (ILD), in which phenomena are measured at high frequency and in real time. In many such studies, it is of interest to describe the pattern of change over time in important variables as well as the changing nature of the relationship between variables. Individuals' trajectories on variables of interest may be far from linear, and the predictive relationship between variables of interest and related covariates may also change over time in a nonlinear way. Time-varying effect models (TVEMs; see Tan, Shiyko, Li, Li, & Dierker, 2012) address these needs by allowing regression coefficients to be smooth, nonlinear functions of time rather than constants. However, it is possible that not only observed covariates but also unknown, latent variables may be related to the outcome. That is, regression coefficients may change over time and also vary for different kinds of individuals. Therefore, we describe a finite mixture version of TVEM for situations in which the population is heterogeneous and in which a single trajectory would conceal important, interindividual differences. This extended approach, MixTVEM, combines finite mixture modeling with non- or semiparametric regression modeling, to describe a complex pattern of change over time for distinct latent classes of individuals. The usefulness of the method is demonstrated in an empirical example from a smoking cessation study. We provide a versatile SAS macro and R function for fitting MixTVEMs. (c) 2015 APA, all rights reserved).

Moving scanning emitter tracking by a single observer using time of interception: Observability analysis and algorithm

Directory of Open Access Journals (Sweden)

Yifei ZHANG

2017-06-01

Full Text Available The target motion analysis (TMA for a moving scanning emitter with known fixed scan rate by a single observer using the time of interception (TOI measurements only is investigated in this paper. By transforming the TOI of multiple scan cycles into the direction difference of arrival (DDOA model, the observability analysis for the TMA problem is performed. Some necessary conditions for uniquely identifying the scanning emitter trajectory are obtained. This paper also proposes a weighted instrumental variable (WIV estimator for the scanning emitter TMA, which does not require any initial solution guess and is closed-form and computationally attractive. More importantly, simulations show that the proposed algorithm can provide estimation mean square error close to the Cramer-Rao lower bound (CRLB at moderate noise levels with significantly lower estimation bias than the conventional pseudo-linear least square (PLS estimator.

Delay-dependent exponential stability of cellular neural networks with time-varying delays

International Nuclear Information System (INIS)

Zhang Qiang; Wei Xiaopeng; Xu Jin

2005-01-01

The global exponential stability of cellular neural networks (CNNs) with time-varying delays is analyzed. Two new sufficient conditions ensuring global exponential stability for delayed CNNs are obtained. The conditions presented here are related to the size of delay. The stability results improve the earlier publications. Two examples are given to demonstrate the effectiveness of the obtained results

Pattern formation in individual-based systems with time-varying parameters

Science.gov (United States)

Ashcroft, Peter; Galla, Tobias

2013-12-01

We study the patterns generated in finite-time sweeps across symmetry-breaking bifurcations in individual-based models. Similar to the well-known Kibble-Zurek scenario of defect formation, large-scale patterns are generated when model parameters are varied slowly, whereas fast sweeps produce a large number of small domains. The symmetry breaking is triggered by intrinsic noise, originating from the discrete dynamics at the microlevel. Based on a linear-noise approximation, we calculate the characteristic length scale of these patterns. We demonstrate the applicability of this approach in a simple model of opinion dynamics, a model in evolutionary game theory with a time-dependent fitness structure, and a model of cell differentiation. Our theoretical estimates are confirmed in simulations. In further numerical work, we observe a similar phenomenon when the symmetry-breaking bifurcation is triggered by population growth.

Time of progression to osteopenia/osteoporosis in chronically HIV-infected patients: screening DXA scan.

Directory of Open Access Journals (Sweden)

Eugenia Negredo

Full Text Available BACKGROUND: Algorithms for bone mineral density (BMD management in HIV-infected patients are lacking. Our objective was to assess how often a dual-energy x-ray absorptiometry (DXA scan should be performed by assessing time of progression to osteopenia/osteoporosis. METHODS: All DXA scans performed between 2000 and 2009 from HIV-infected patients with at least two DXA were included. Time to an event (osteopenia and osteoporosis was assessed using the Kaplan-Meier method. Strata (tertiles were defined using baseline minimum T scores. Differences between strata in time to an event were compared with the log-rank test. RESULTS: Of 391 patients (1,639 DXAs, 49.6% had osteopenia and 21.7% osteoporosis at their first DXA scan. Of the 112 (28.6% with normal BMD, 35.7% progressed to osteopenia; median progression time was 6.7 years. These patients were stratified: "low-risk" (baseline minimum T score >-0.2 SD, "middle-risk" (between -0.2 and -0.6 SD, and "high-risk" (from -0.6 to -1 SD; median progression time to osteopenia was 8.7, >7.2, and 1.7 years, respectively (p8.5 years. Progression time was >8.2 years in "low-risk" tertile (T score between -1.1 and -1.6 SD, >8.5 years in "middle-risk" (between -1.6 and -2, and 3.2 years in "high-risk" (from -2 to -2.4 (p<0.0001. CONCLUSIONS: Our results may help to define the BMD testing interval. The lowest T score tertiles would suggest recommending a subsequent DXA in 1-2 years; in the highest tertiles, ≥6 years. Early intervention in patients with bone demineralization could reduce fracture-related morbidity/mortality.

H∞ Consensus for Multiagent Systems with Heterogeneous Time-Varying Delays

Directory of Open Access Journals (Sweden)

Beibei Wang

2013-01-01

Full Text Available We apply the linear matrix inequality method to consensus and H∞ consensus problems of the single integrator multiagent system with heterogeneous delays in directed networks. To overcome the difficulty caused by heterogeneous time-varying delays, we rewrite the multiagent system into a partially reduced-order system and an integral system. As a result, a particular Lyapunov function is constructed to derive sufficient conditions for consensus of multiagent systems with fixed (switched topologies. We also apply this method to the H∞ consensus of multiagent systems with disturbances and heterogeneous delays. Numerical examples are given to illustrate the theoretical results.

Closeness-Centrality-Based Synchronization Criteria for Complex Dynamical Networks With Interval Time-Varying Coupling Delays.

Science.gov (United States)

Park, Myeongjin; Lee, Seung-Hoon; Kwon, Oh-Min; Seuret, Alexandre

2017-09-06

This paper investigates synchronization in complex dynamical networks (CDNs) with interval time-varying delays. The CDNs are representative of systems composed of a large number of interconnected dynamical units, and for the purpose of the mathematical analysis, the leading work is to model them as graphs whose nodes represent the dynamical units. At this time, we take note of the importance of each node in networks. One way, in this paper, is that the closeness-centrality mentioned in the field of social science is grafted onto the CDNs. By constructing a suitable Lyapunov-Krasovskii functional, and utilizing some mathematical techniques, the sufficient and closeness-centrality-based conditions for synchronization stability of the networks are established in terms of linear matrix inequalities. Ultimately, the use of the closeness-centrality can be weighted with regard to not only the interconnection relation among the nodes, which was utilized in the existing works but also more information about nodes. Here, the centrality will be added as the concerned information. Moreover, to avoid the computational burden causing the nonconvex term including the square of the time-varying delay, how to deal with it is applied by estimating it to the convex term including time-varying delay. Finally, two illustrative examples are given to show the advantage of the closeness-centrality in point of the robustness on time-delay.

Automated segmentation of tumors on bone scans using anatomy-specific thresholding

Science.gov (United States)

Chu, Gregory H.; Lo, Pechin; Kim, Hyun J.; Lu, Peiyun; Ramakrishna, Bharath; Gjertson, David; Poon, Cheryce; Auerbach, Martin; Goldin, Jonathan; Brown, Matthew S.

2012-03-01

Quantification of overall tumor area on bone scans may be a potential biomarker for treatment response assessment and has, to date, not been investigated. Segmentation of bone metastases on bone scans is a fundamental step for this response marker. In this paper, we propose a fully automated computerized method for the segmentation of bone metastases on bone scans, taking into account characteristics of different anatomic regions. A scan is first segmented into anatomic regions via an atlas-based segmentation procedure, which involves non-rigidly registering a labeled atlas scan to the patient scan. Next, an intensity normalization method is applied to account for varying levels of radiotracer dosing levels and scan timing. Lastly, lesions are segmented via anatomic regionspecific intensity thresholding. Thresholds are chosen by receiver operating characteristic (ROC) curve analysis against manual contouring by board certified nuclear medicine physicians. A leave-one-out cross validation of our method on a set of 39 bone scans with metastases marked by 2 board-certified nuclear medicine physicians yielded a median sensitivity of 95.5%, and specificity of 93.9%. Our method was compared with a global intensity thresholding method. The results show a comparable sensitivity and significantly improved overall specificity, with a p-value of 0.0069.

Empirical Evidence on Time-Varying Hedging Effectiveness of Emissions Allowances under Departures from the Cost-of-Carry Theory

Directory of Open Access Journals (Sweden)

Kai Chang

2013-01-01

Full Text Available Under departures from the cost-of-carry theory, traded spot prices and conditional volatility disturbed from futures market have significant impacts on futures price of emissions allowances, and then we propose time-varying hedge ratios and hedging effectiveness estimation using ECM-GARCH model. Our empirical results show that conditional variance, conditional covariance, and their correlation between between spot and futures prices exhibit time-varying trends. Conditional volatility of spot prices, conditional volatility disturbed from futures market, and conditional correlation of market noises implied from spot and futures markets have significant effects on time-varying hedge ratios and hedging effectiveness. In the immature emissions allowances market, market participants optimize portfolio sizes between spot and futures assets using historical market information and then achieve higher risk reduction of assets portfolio revenues; accordingly, we can obtain better hedging effectiveness through time-varying hedge ratios with departures from the cost-of-carry theory.

Testing for Change in Mean of Independent Multivariate Observations with Time Varying Covariance

Directory of Open Access Journals (Sweden)

Mohamed Boutahar

2012-01-01

Full Text Available We consider a nonparametric CUSUM test for change in the mean of multivariate time series with time varying covariance. We prove that under the null, the test statistic has a Kolmogorov limiting distribution. The asymptotic consistency of the test against a large class of alternatives which contains abrupt, smooth and continuous changes is established. We also perform a simulation study to analyze the size distortion and the power of the proposed test.

Real-time underwater object detection based on an electrically scanned high-resolution sonar

DEFF Research Database (Denmark)

Henriksen, Lars

1994-01-01

The paper describes an approach to real time detection and tracking of underwater objects, using image sequences from an electrically scanned high-resolution sonar. The use of a high resolution sonar provides a good estimate of the location of the objects, but strains the computers on board, beca...

Decreasing medication turnaround time with digital scanning technology in a canadian health region.

Science.gov (United States)

Neville, Heather; Nodwell, Lisa; Alsharif, Sahar

2014-11-01

Reducing medication turnaround time can improve efficiency, patient safety, and quality of care in the hospital setting. Digital scanning technology (DST) can be used to electronically transmit scanned prescriber orders to a pharmacy computer queue for verification and processing, which may help to improve medication turnaround time. To evaluate medication turnaround time before and after implementation of DST for all medications and for antibiotics only. Medication turnaround times were evaluated retrospectively for periods before (June 6-10, 2011) and after (September 26-30, 2011) implementation of DST at 2 hospital sites in 1 health region. Medication turnaround time was defined as the time from composition of a medication order by the prescriber to its verification by the pharmacy (phase 1) and the time from prescriber composition to administration to the patient by a nurse (total). Median turnaround times were analyzed with SPSS software using the Mann-Whitney U test. In total, 304 and 244 medication orders were audited before and after DST implementation, respectively. Median phase 1 turnaround time for all medications declined significantly, from 2 h 23 min before DST implementation to 1 h 33 min after DST implementation (p < 0.001). Antibiotics were also processed significantly faster (1 h 51 min versus 1 h 9 min, p = 0.015). However, total turnaround time for all medications did not differ significantly (5 h 15 min versus 5 h 0 min, p = 0.42). Implementation of DST was associated with a 50-min decrease in medication turnaround time for the period from when an order was prescribed to the time it was processed by the pharmacy. Regular evaluation of medication turnaround times is recommended to compare with benchmarks, to ensure that hospital standards are being met, and to measure the effects of policy changes and implementation of new technology on medication-use processes.

Robust state estimation for uncertain fuzzy bidirectional associative memory networks with time-varying delays

Science.gov (United States)

Vadivel, P.; Sakthivel, R.; Mathiyalagan, K.; Arunkumar, A.

2013-09-01

This paper addresses the issue of robust state estimation for a class of fuzzy bidirectional associative memory (BAM) neural networks with time-varying delays and parameter uncertainties. By constructing the Lyapunov-Krasovskii functional, which contains the triple-integral term and using the free-weighting matrix technique, a set of sufficient conditions are derived in terms of linear matrix inequalities (LMIs) to estimate the neuron states through available output measurements such that the dynamics of the estimation error system is robustly asymptotically stable. In particular, we consider a generalized activation function in which the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. More precisely, the design of the state estimator for such BAM neural networks can be obtained by solving some LMIs, which are dependent on the size of the time derivative of the time-varying delays. Finally, a numerical example with simulation result is given to illustrate the obtained theoretical results.

Robust state estimation for uncertain fuzzy bidirectional associative memory networks with time-varying delays

International Nuclear Information System (INIS)

Vadivel, P; Sakthivel, R; Mathiyalagan, K; Arunkumar, A

2013-01-01

This paper addresses the issue of robust state estimation for a class of fuzzy bidirectional associative memory (BAM) neural networks with time-varying delays and parameter uncertainties. By constructing the Lyapunov–Krasovskii functional, which contains the triple-integral term and using the free-weighting matrix technique, a set of sufficient conditions are derived in terms of linear matrix inequalities (LMIs) to estimate the neuron states through available output measurements such that the dynamics of the estimation error system is robustly asymptotically stable. In particular, we consider a generalized activation function in which the traditional assumptions on the boundedness, monotony and differentiability of the activation functions are removed. More precisely, the design of the state estimator for such BAM neural networks can be obtained by solving some LMIs, which are dependent on the size of the time derivative of the time-varying delays. Finally, a numerical example with simulation result is given to illustrate the obtained theoretical results. (paper)

A note on "Multicriteria adaptive paths in stochastic, time-varying networks"

DEFF Research Database (Denmark)

Pretolani, Daniele; Nielsen, Lars Relund; Andersen, Kim Allan

In a recent paper, Opasanon and Miller-Hooks study multicriteria adaptive paths in stochastic time-varying networks. They propose a label correcting algorithm for finding the full set of efficient strategies. In this note we show that their algorithm is not correct, since it is based on a property...... that does not hold in general. Opasanon and Miller-Hooks also propose an algorithm for solving a parametric problem. We give a simplified algorithm which is linear in the input size....

Propagation of a laser beam in a time-varying waveguide

International Nuclear Information System (INIS)

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 examined. First, an extended paraxial procedure is developed for the case of an axially uniform waveguide. It is shown that the essential feature of an alternate focusing and defocusing beam is retained, but that the intensity distribution is cumulatively modified at the foci and at the outer portions of the beam as compared to that of the paraxial case. Second, some general features of paraxial beam propagation are examined for the case of axially varying waveguides. Finally, laser plasma coupling is examined for the case when laser heating generates a density distribution that is radially parabolic near the axis and when the energy absorbed over a focal length of a plasma lens is small. It is shown that stable or unstable beam propagation depends upon the relative magnitude of the density fluctuations which exist in the axial variation of the waveguides as a result of laser heating. When the fluctuations are small, the propagation is stable, and a simple algebraic expression is obtained which relates the beam diameter to the axially slow averaged variation in the waveguide. When the fluctuations are large, the propagation stability can be determined only by consistently combining plasma dynamics and beam propagation to interrelate the axial variation of the beam to that of the waveguide. In this case of beam propagation in a time-varying waveguide, it is shown that the global stability of the propagation depends upon the initial fluctuation growth rate compared to the initial time rate of change in the radial curvature of the waveguide

Time-Dependent Response Versus Scan Angle for MODIS Reflective Solar Bands

Science.gov (United States)

Sun, Junqiang; Xiong, Xiaoxiong; Angal, Amit; Chen, Hongda; Wu, Aisheng; Geng, Xu

2014-01-01

The Moderate Resolution Imaging Spectroradiometer (MODIS) instruments currently operate onboard the National Aeronautics and Space Administration (NASA's) Terra and Aqua spacecraft, launched on December 18, 1999 and May 4, 2002, respectively. MODIS has 36 spectral bands, among which 20 are reflective solar bands (RSBs) covering a spectral range from 0.412 to 2.13 µm. The RSBs are calibrated on orbit using a solar diffuser (SD) and an SD stability monitor and with additional measurements from lunar observations via a space view (SV) port. Selected pseudo-invariant desert sites are also used to track the RSB on-orbit gain change, particularly for short-wavelength bands. MODIS views the Earth surface, SV, and the onboard calibrators using a two-sided scan mirror. The response versus scan angle (RVS) of the scan mirror was characterized prior to launch, and its changes are tracked using observations made at different angles of incidence from onboard SD, lunar, and Earth view (EV) measurements. These observations show that the optical properties of the scan mirror have experienced large wavelength-dependent degradation in both the visible and near infrared spectral regions. Algorithms have been developed to track the on-orbit RVS change using the calibrators and the selected desert sites. These algorithms have been applied to both Terra and Aqua MODIS Level 1B (L1B) to improve the EV data accuracy since L1B Collection 4, refined in Collection 5, and further improved in the latest Collection 6 (C6). In C6, two approaches have been used to derive the time-dependent RVS for MODIS RSB. The first approach relies on data collected from sensor onboard calibrators and mirror side ratios from EV observations. The second approach uses onboard calibrators and EV response trending from selected desert sites. This approach is mainly used for the bands with much larger changes in their time-dependent RVS, such as the Terra MODIS bands 1-4, 8, and 9 and the Aqua MODIS bands 8- and 9

Dynamic IQC-Based Control of Uncertain LFT Systems With Time-Varying State Delay.

Science.gov (United States)

Yuan, Chengzhi; Wu, Fen

2016-12-01

This paper presents a new exact-memory delay control scheme for a class of uncertain systems with time-varying state delay under the integral quadratic constraint (IQC) framework. The uncertain system is described as a linear fractional transformation model including a state-delayed linear time-invariant (LTI) system and time-varying structured uncertainties. The proposed exact-memory delay controller consists of a linear state-feedback control law and an additional term that captures the delay behavior of the plant. We first explore the delay stability and the L 2 -gain performance using dynamic IQCs incorporated with quadratic Lyapunov functions. Then, the design of exact-memory controllers that guarantee desired L 2 -gain performance is examined. The resulting delay control synthesis conditions are formulated in terms of linear matrix inequalities, which are convex on all design variables including the scaling matrices associated with the IQC multipliers. The IQC-based exact-memory control scheme provides a novel approach for delay control designs via convex optimization, and advances existing control methods in two important ways: 1) better controlled performance and 2) simplified design procedure with less computational cost. The effectiveness and advantages of the proposed approach have been demonstrated through numerical studies.

Observer-based output feedback control of networked control systems with non-uniform sampling and time-varying delay

Science.gov (United States)

Meng, Su; Chen, Jie; Sun, Jian

2017-10-01

This paper investigates the problem of observer-based output feedback control for networked control systems with non-uniform sampling and time-varying transmission delay. The sampling intervals are assumed to vary within a given interval. The transmission delay belongs to a known interval. A discrete-time model is first established, which contains time-varying delay and norm-bounded uncertainties coming from non-uniform sampling intervals. It is then converted to an interconnection of two subsystems in which the forward channel is delay-free. The scaled small gain theorem is used to derive the stability condition for the closed-loop system. Moreover, the observer-based output feedback controller design method is proposed by utilising a modified cone complementary linearisation algorithm. Finally, numerical examples illustrate the validity and superiority of the proposed method.

Concept and development of measurement method of time sensitivity profile (TSP) in X-ray CT. Comparison of non-helical, single-slice helical, and multi-slice helical scans

International Nuclear Information System (INIS)

Tsujioka, Katsumi; Ida, Yoshihiro; Ohtsubo, Hironori; Takahashi, Yasukata; Niwa, Masayoshi

2000-01-01

We focused on the time element contained in a single CT image, and devised the concept of a time-sensitivity profile (TSP) describing how the time element is translated into an image. We calculated the data collection time range when the helical pitch is changed in non helical scans, single slice helical scans, and multi slice helical scans. We then calculated the time sensitivity profile (TSP) from the weighting applied when the data collection time range is translated into an image. TSP was also measured for each scanning method using our self-made moving phantom. TSPs obtained from the calculation and the experiments were very close. TSP showed interesting characteristics with each scanning method, especially in the case of multi slice helical scanning, in which TSP became shorter as helical pitch increased. We referred to the TSP's FWHM as the effective scanning time. When we conducted multi slice helical scanning at helical pitch 3, the effective scanning time increased to about 24% longer than that of a non helical scan. When we conducted multi slice helical scanning at helical pitch 5 or 6, the effective scanning time was about half that of a non helical scan. The time sensitivity profile (TSP) is a totally new concept that we consider an important element in discussing the time resolution of a CT scanner. The results of this review will provide significant data in determining the scanning parameters when scanning a moving object. (author)

Bone scan and joint scan of hands and feet in rheumatoid arthritis

International Nuclear Information System (INIS)

Carpentier, N.; Verbeke, S.; Perdrisot, R.; Grilo, R.M.; Quenesson, E.; Bonnet, C.; Vergne, P.; Treves, R.; Bertin, P.; Boutros-Toni, F.

2000-01-01

The aim of this study was to determine the ability of joint scan and bone scan of hands and feet, in patients with rheumatoid arthritis, to localize the altered joints. The sensitivity, the specificity, the positive predictive value (PPV) and the negative predictive value (NPV) of joint scan were determined in comparison with clinical joint assessment. Fifteen patients (780 joints) were clinically examined (pain and synovitis); during the same day, a bone scan and a joint scan were realized by oxidronate 99m Tc intravenous injection. Patients were scanned 5 minutes (tissual time, T t ) and 3 hours 1/4 (bone time, T 0 ) after the administration. The uptake of the bi-phosphonate was evaluated with a qualitative method using a grey scale. The uptake of 99m Tc oxidronate was quantitated using an extra-articular region of interest. The sensitivity, specificity, PPV and NPV of the scan at Tt were 46%, 96%, 85% et 78%. The same parameters were 75%, 66%, 53% and 84% for the scan realized at T 0 . The joint scan has showed 22% of false positive. These false positives could be a consequence of an earlier detection of joint alterations by scan. The joint scan should forecast the evolution of joints in patients with rheumatoid arthritis. (author)

The effect of varying incubation times for hypotonic treatment of lymphocytes in dicentric assay technique

International Nuclear Information System (INIS)

Noraisyah Yusof; Noriah Jamal; Rahimah Abdul Rahim; Juliana Mahamad Napiah

2010-01-01

The International Atomic Energy Agency (IAEA) has recommended that incubation time for the hypotonic treatment of lymphocytes in dicentric assay technique to be between 15 to 20 minutes. Incubation time will effect the hypotonic treatment of lymphocytes and thus, the breakage of cytoplasmic membrane. The objective of this study is to examine the effect of varying incubation times for hypotonic treatment of lymphocytes in dicentric assay technique. In this study, we choose to use our standard protocol for dicentric assay technique. However, for the hypotonic treatment of lymphocytes, the incubation times were varied from 10, 15, 20, 25 and 30 minutes respectively. Lymphocytes were then fixed and stained with Giemsa. The cells were then analyzed for clear background that indicates good metaphases. We found that incubation time of 30 minutes gives the best metaphase images. This incubation time is longer than what has been recommended by the IAEA. This maybe explained by the fact that our country's climate is of higher humidity compared with the European countries. (author)

Magnetohydrodynamic flow of a rarefied gas near a time-varying accelerated plate

International Nuclear Information System (INIS)

Mishra, S.P.; Mohapatra, Priti

1975-01-01

The flow of an electrically conducting rarefied gas due to the time-varying motion of an infinite flat plate has been studied in the presence of a uniform magnetic field. The magnetic lines of force are taken to be fixed relative to the fluid. General expressions of the velocity and the skin friction have been compared by means of some qraphs and tables. (author)

Scalar Aharonov–Bohm Phase in Ramsey Atom Interferometry under Time-Varying Potential

Directory of Open Access Journals (Sweden)

Atsuo Morinaga

2016-08-01

Full Text Available In a Ramsey atom interferometer excited by two electromagnetic fields, if atoms are under a time-varying scalar potential during the interrogation time, the phase of the Ramsey fringes shifts owing to the scalar Aharonov–Bohm effect. The phase shift was precisely examined using a Ramsey atom interferometer with a two-photon Raman transition under the second-order Zeeman potential, and a formula for the phase shift was derived. Using the derived formula, the frequency shift due to the scalar Aharonov–Bohm effect in the frequency standards utilizing the Ramsey atom interferometer was discussed.

A Time-Varied Probabilistic ON/OFF Switching Algorithm for Cellular Networks

KAUST Repository

Rached, Nadhir B.; Ghazzai, Hakim; Kadri, Abdullah; Alouini, Mohamed-Slim

2018-01-01

In this letter, we develop a time-varied probabilistic on/off switching planning method for cellular networks to reduce their energy consumption. It consists in a risk-aware optimization approach that takes into consideration the randomness of the user profile associated with each base station (BS). The proposed approach jointly determines (i) the instants of time at which the current active BS configuration must be updated due to an increase or decrease of the network traffic load, and (ii) the set of minimum BSs to be activated to serve the networks’ subscribers. Probabilistic metrics modeling the traffic profile variation are developed to trigger this dynamic on/off switching operation. Selected simulation results are then performed to validate the proposed algorithm for different system parameters.

A Time-Varied Probabilistic ON/OFF Switching Algorithm for Cellular Networks

KAUST Repository

Rached, Nadhir B.

2018-01-11

In this letter, we develop a time-varied probabilistic on/off switching planning method for cellular networks to reduce their energy consumption. It consists in a risk-aware optimization approach that takes into consideration the randomness of the user profile associated with each base station (BS). The proposed approach jointly determines (i) the instants of time at which the current active BS configuration must be updated due to an increase or decrease of the network traffic load, and (ii) the set of minimum BSs to be activated to serve the networks’ subscribers. Probabilistic metrics modeling the traffic profile variation are developed to trigger this dynamic on/off switching operation. Selected simulation results are then performed to validate the proposed algorithm for different system parameters.

Electronically-Scanned Pressure Sensors

Science.gov (United States)

Coe, C. F.; Parra, G. T.; Kauffman, R. C.

1984-01-01

Sensors not pneumatically switched. Electronic pressure-transducer scanning system constructed in modular form. Pressure transducer modules and analog to digital converter module small enough to fit within cavities of average-sized wind-tunnel models. All switching done electronically. Temperature controlled environment maintained within sensor modules so accuracy maintained while ambient temperature varies.

Bone metastases from breast cancer at the time or radical mastectomy as detected by bone scan. Eight-year follow-up.

Science.gov (United States)

Sklaroff, R B; Sklaroff, D M

1976-07-01

Sixty-four women with Stage II breast cancer who had Sr85 bone scans at the time of radical mastectomy were followed for 8 years in a prospective study. Those women with positive scans had a slight, but statistically significant, increased incidence of metastic disease, particularly for metastases to bone.However, 40% of those women with positive bone scans and negative roentgenograms survived 8 years without evidence of any metastatic disease. Therefore, it has not been shown at this time that bone scans should be obtained in order to exclude bone metastasis before regional therapy for breast cancer is instituted. Also, a significant percentage of women with negative bone scans developed both bone and soft tissue metastases. As many as 30% of asymptomatic women with a history of breast cancer and positive bone scans and negative bone roentgenograms may still harbor disease in bone after 8 years.

Analysis on Passivity for Uncertain Neural Networks with Time-Varying Delays

Directory of Open Access Journals (Sweden)

O. M. Kwon

2014-01-01

Full Text Available The problem of passivity analysis for neural networks with time-varying delays and parameter uncertainties is considered. By the consideration of newly constructed Lyapunov-Krasovskii functionals, improved sufficient conditions to guarantee the passivity of the concerned networks are proposed with the framework of linear matrix inequalities (LMIs, which can be solved easily by various efficient convex optimization algorithms. The enhancement of the feasible region of the proposed criteria is shown via two numerical examples by the comparison of maximum allowable delay bounds.

CT scanning in stroke patients: meeting the challenge in the remote and rural district general hospital.

Science.gov (United States)

Todd, A W; Anderson, E M

2009-05-01

National audit data allow crude comparison between centres and indicate that most Scottish hospitals fail to meet current guidelines for CT scanning of the brain in stroke patients. This study identifies some of the reasons for delay in performing CT scans in a largely rural population. This audit study assesses the delays from onset of symptoms, time of admission and request received to CT scan in stroke patients for three different in-patient groups as well as those managed in the community. The reasons for delay in CT scanning varied between different patient groups but for one group of in-patients, changes in booking procedure and introduction of a second CT scanner increased the proportion scanned within 48 hours of request from 65% to 96%. Further developments including the introduction of Saturday and Sunday routine CT scanning, radiologist reporting from home and additional CT scanners placed in remote hospitals may be expected to improve these figures further. Target times of three hours from onset of symptoms to scan to allow thrombolysis may however be impossible to meet for all stroke patients in rural areas.

Vector Autoregressions with Parsimoniously Time Varying Parameters and an Application to Monetary Policy

DEFF Research Database (Denmark)

Callot, Laurent; Kristensen, Johannes Tang

the monetary policy response to inflation and business cycle fluctuations in the US by estimating a parsimoniously time varying parameter Taylor rule.We document substantial changes in the policy response of the Fed in the 1970s and 1980s, and since 2007, but also document the stability of this response...

Time-varying risk aversion. An application to energy hedging

Energy Technology Data Exchange (ETDEWEB)

Cotter, John [Centre for Financial Markets, School of Business, University College Dublin, Blackrock, Co. Dublin (Ireland); Hanly, Jim [School of Accounting and Finance, Dublin Institute of Technology, Dublin 2 (Ireland)

2010-03-15

Risk aversion is a key element of utility maximizing hedge strategies; however, it has typically been assigned an arbitrary value in the literature. This paper instead applies a GARCH-in-Mean (GARCH-M) model to estimate a time-varying measure of risk aversion that is based on the observed risk preferences of energy hedging market participants. The resulting estimates are applied to derive explicit risk aversion based optimal hedge strategies for both short and long hedgers. Out-of-sample results are also presented based on a unique approach that allows us to forecast risk aversion, thereby estimating hedge strategies that address the potential future needs of energy hedgers. We find that the risk aversion based hedges differ significantly from simpler OLS hedges. When implemented in-sample, risk aversion hedges for short hedgers outperform the OLS hedge ratio in a utility based comparison. (author)

Time-varying risk aversion. An application to energy hedging

International Nuclear Information System (INIS)

Cotter, John; Hanly, Jim

2010-01-01

Risk aversion is a key element of utility maximizing hedge strategies; however, it has typically been assigned an arbitrary value in the literature. This paper instead applies a GARCH-in-Mean (GARCH-M) model to estimate a time-varying measure of risk aversion that is based on the observed risk preferences of energy hedging market participants. The resulting estimates are applied to derive explicit risk aversion based optimal hedge strategies for both short and long hedgers. Out-of-sample results are also presented based on a unique approach that allows us to forecast risk aversion, thereby estimating hedge strategies that address the potential future needs of energy hedgers. We find that the risk aversion based hedges differ significantly from simpler OLS hedges. When implemented in-sample, risk aversion hedges for short hedgers outperform the OLS hedge ratio in a utility based comparison. (author)

Development of the compact proton beam therapy system dedicated to spot scanning with real-time tumor-tracking technology

Science.gov (United States)

Umezawa, Masumi; Fujimoto, Rintaro; Umekawa, Tooru; Fujii, Yuusuke; Takayanagi, Taisuke; Ebina, Futaro; Aoki, Takamichi; Nagamine, Yoshihiko; Matsuda, Koji; Hiramoto, Kazuo; Matsuura, Taeko; Miyamoto, Naoki; Nihongi, Hideaki; Umegaki, Kikuo; Shirato, Hiroki

2013-04-01

Hokkaido University and Hitachi Ltd. have started joint development of the Gated Spot Scanning Proton Therapy with Real-Time Tumor-Tracking System by integrating real-time tumor tracking technology (RTRT) and the proton therapy system dedicated to discrete spot scanning techniques under the "Funding Program for World-Leading Innovative R&D on Science and Technology (FIRST Program)". In this development, we have designed the synchrotron-based accelerator system by using the advantages of the spot scanning technique in order to realize a more compact and lower cost proton therapy system than the conventional system. In the gated irradiation, we have focused on the issues to maximize irradiation efficiency and minimize the dose errors caused by organ motion. In order to understand the interplay effect between scanning beam delivery and target motion, we conducted a simulation study. The newly designed system consists of the synchrotron, beam transport system, one compact rotating gantry treatment room with robotic couch, and one experimental room for future research. To improve the irradiation efficiency, the new control function which enables multiple gated irradiations per synchrotron cycle has been applied and its efficacy was confirmed by the irradiation time estimation. As for the interplay effect, we confirmed that the selection of a strict gating width and scan direction enables formation of the uniform dose distribution.

A special case of reduced rank models for identification and modelling of time varying effects in survival analysis.

Science.gov (United States)

Perperoglou, Aris

2016-12-10

Flexible survival models are in need when modelling data from long term follow-up studies. In many cases, the assumption of proportionality imposed by a Cox model will not be valid. Instead, a model that can identify time varying effects of fixed covariates can be used. Although there are several approaches that deal with this problem, it is not always straightforward how to choose which covariates should be modelled having time varying effects and which not. At the same time, it is up to the researcher to define appropriate time functions that describe the dynamic pattern of the effects. In this work, we suggest a model that can deal with both fixed and time varying effects and uses simple hypotheses tests to distinguish which covariates do have dynamic effects. The model is an extension of the parsimonious reduced rank model of rank 1. As such, the number of parameters is kept low, and thus, a flexible set of time functions, such as b-splines, can be used. The basic theory is illustrated along with an efficient fitting algorithm. The proposed method is applied to a dataset of breast cancer patients and compared with a multivariate fractional polynomials approach for modelling time-varying effects. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Study on the Variation of Groundwater Level under Time-varying Recharge

Science.gov (United States)

Wu, Ming-Chang; Hsieh, Ping-Cheng

2017-04-01

The slopes of the suburbs come to important areas by focusing on the work of soil and water conservation in recent years. The water table inside the aquifer is affected by rainfall, geology and topography, which will result in the change of groundwater discharge and water level. Currently, the way to obtain water table information is to set up the observation wells; however, owing to that the cost of equipment and the wells excavated is too expensive, we develop a mathematical model instead, which might help us to simulate the groundwater level variation. In this study, we will discuss the groundwater level change in a sloping unconfined aquifer with impermeable bottom under time-varying rainfall events. Referring to Child (1971), we employ the Boussinesq equation as the governing equation, and apply the General Integral Transforms Method (GITM) to analyzing the groundwater level after linearizing the Boussinesq equation. After comparing the solution with Verhoest & Troch (2000) and Bansal & Das (2010), we get satisfactory results. To sum up, we have presented an alternative approach to solve the linearized Boussinesq equation for the response of groundwater level in a sloping unconfined aquifer. The present analytical results combine the effect of bottom slope and the time-varying recharge pattern on the water table fluctuations. Owing to the limitation and difficulty of measuring the groundwater level directly, we develop such a mathematical model that we can predict or simulate the variation of groundwater level affected by any rainfall events in advance.

Distributed management system of a scanning robot programmed real time in APL language

International Nuclear Information System (INIS)

Liabot, M.-J.

1980-08-01

The aim of this work is to propose an original solution in order to implement the control operating system of a robot designed to travel between the main tank and the safety tank of the SUPERPHENIX reactor for scanning up the welding by ultrasound measurements. The system consists of: - a MITRA mini-computer programmed in APL, that manages the driving unit and defines the scanning strategy (visual unit, cheking board...). - a microprocessor that realizes the connection between the MITRA and the robot on wich the motor commands and the safety fonctions are placed. Such a solution allows to limit input output volume in the MITRA and gives the possibility to program the system in real time in APL language [fr

Visualization of particle trajectories in time-varying electromagnetic fields by CAVE-type virtual reality system

International Nuclear Information System (INIS)

Ohno, Nobuaki; Ohtani, Hiroaki; Horiuchi, Ritoku; Matsuoka, Daisuke

2012-01-01

The particle kinetic effects play an important role in breaking the frozen-in condition and exciting collisionless magnetic reconnection in high temperature plasmas. Because this effect is originating from a complex thermal motion near reconnection point, it is very important to examine particle trajectories using scientific visualization technique, especially in the presence of plasma instability. We developed interactive visualization environment for the particle trajectories in time-varying electromagnetic fields in the CAVE-type virtual reality system based on VFIVE, which is interactive visualization software for the CAVE system. From the analysis of ion trajectories using the particle simulation data, it was found that time-varying electromagnetic fields around the reconnection region accelerate ions toward the downstream region. (author)

Global exponential stability of fuzzy BAM neural networks with time-varying delays

International Nuclear Information System (INIS)

Zhang Qianhong; Luo Wei

2009-01-01

In this paper, a class of fuzzy bidirectional associated memory (BAM) neural networks with time-varying delays are studied. Employing fixed point theorem, matrix theory and inequality analysis, some sufficient conditions are established for the existence, uniqueness and global exponential stability of equilibrium point. The sufficient conditions are easy to verify at pattern recognition and automatic control. Finally, an example is given to show feasibility and effectiveness of our results.

Adaptive modification of the delayed feedback control algorithm with a continuously varying time delay

International Nuclear Information System (INIS)

Pyragas, V.; Pyragas, K.

2011-01-01

We propose a simple adaptive delayed feedback control algorithm for stabilization of unstable periodic orbits with unknown periods. The state dependent time delay is varied continuously towards the period of controlled orbit according to a gradient-descent method realized through three simple ordinary differential equations. We demonstrate the efficiency of the algorithm with the Roessler and Mackey-Glass chaotic systems. The stability of the controlled orbits is proven by computation of the Lyapunov exponents of linearized equations. -- Highlights: → A simple adaptive modification of the delayed feedback control algorithm is proposed. → It enables the control of unstable periodic orbits with unknown periods. → The delay time is varied continuously according to a gradient descend method. → The algorithm is embodied by three simple ordinary differential equations. → The validity of the algorithm is proven by computation of the Lyapunov exponents.

Evolution of colloidal dispersions in novel time-varying optical potentials

Science.gov (United States)

Koss, Brian Alan

Optical traps use forces exerted by a tightly focused light beam to trap objects from tens of nanometers to tens of micrometers in size. Since their introduction in 1986, optical tweezers have become very useful to biology, chemistry, and soft condensed-matter physics. Work presented here, promises to advance optical tweezers not only in fundamental scientific research, but also in applications outside of the laboratory and into the mainstream of miniaturized manufacturing and diagnostics. By providing unprecedented access to the mesoscopic world, a new generation of optical traps, called Dynamic Holographic Optical Tweezers (HOTs) offers revolutionary new opportunities for fundamental and applied research. To demonstrate this technique, HOTs will be used to pump particles via a new method of transport called Optical Peristalsis (OP). OP is efficient method for transporting mesoscopic objects in three dimensions using short repetitive sequences of holographic optical trapping patterns. Transport in this process is analogous to peristaltic pumping, with the configurations of optical traps mimicking states of a peristaltic pump. While not limited to the deterministic particle transport, OP, can also be a platform to investigate the stochastic limit of particle transport. Advances in recent years have demonstrated that a variety of time-varying perturbations can induce drift in a diffusive system without exerting an overall force. Among these, are thermal ratchet models in which the system is subjected to time-varying energy landscapes that break spatiotemporal symmetry and thereby induce drift. Typically, the potential energy landscape is chosen to be the sawtooth potential. This work describes an alternate class of symmetric thermal ratchet models, that are not sawtooth, and demonstrates their efficacy in biasing the diffusion of colloidal spheres in both the stochastic and deterministic limits. Unlike previous models, each state in this thermal ratchet consists of

Robust stability analysis for Markovian jumping interval neural networks with discrete and distributed time-varying delays

International Nuclear Information System (INIS)

Balasubramaniam, P.; Lakshmanan, S.; Manivannan, A.

2012-01-01

Highlights: ► Robust stability analysis for Markovian jumping interval neural networks is considered. ► Both linear fractional and interval uncertainties are considered. ► A new LKF is constructed with triple integral terms. ► MATLAB LMI control toolbox is used to validate theoretical results. ► Numerical examples are given to illustrate the effectiveness of the proposed method. - Abstract: This paper investigates robust stability analysis for Markovian jumping interval neural networks with discrete and distributed time-varying delays. The parameter uncertainties are assumed to be bounded in given compact sets. The delay is assumed to be time-varying and belong to a given interval, which means that the lower and upper bounds of interval time-varying delays are available. Based on the new Lyapunov–Krasovskii functional (LKF), some inequality techniques and stochastic stability theory, new delay-dependent stability criteria have been obtained in terms of linear matrix inequalities (LMIs). Finally, two numerical examples are given to illustrate the less conservative and effectiveness of our theoretical results.

Decentralized H∞ Control of Interconnected Systems with Time-varying Delays

Directory of Open Access Journals (Sweden)

Amal Zouhri

2017-01-01

Full Text Available This paper focuses on the problem of delay dependent stability/stabilization of interconnected systems with time-varying delays. The approach is based on a new Lyapunov-Krasovskii functional. A decentralized delay-dependent stability analysis is performed to characterize linear matrix inequalities (LMIs based on the conditions under which every local subsystem of the linear interconnected delay system is asymptotically stable. Then we design a decentralized state-feedback stabilization scheme such that the family of closedloop feedback subsystems enjoys the delay-dependent asymptotic stability for each subsystem. The decentralized feedback gains are determined by convex optimization over LMIs. All the developed results are tested on a representative example and compared with some recent previous ones.

Distributed leader-follower flocking control for multi-agent dynamical systems with time-varying velocities

NARCIS (Netherlands)

Yu, Wenwu; Chen, Guanrong; Cao, Ming

Using tools from algebraic graph theory and nonsmooth analysis in combination with ideas of collective potential functions, velocity consensus and navigation feedback, a distributed leader-follower flocking algorithm for multi-agent dynamical systems with time-varying velocities is developed where

Frequency Domain Training-Aided Channel Estimation and Equalization in Time-Varying Optical Transmission Systems

DEFF Research Database (Denmark)

Pittalà, Fabio; Msallem, Majdi; Hauske, Fabian N.

2012-01-01

We propose a non-weighted feed-forward equalization method with filter update by averaging channel estimations based on short CAZAC sequences. Three averaging methods are presented and tested by simulations in a time-varying 2×2 MIMO optical system....

H∞ state estimation of generalised neural networks with interval time-varying delays

Science.gov (United States)

Saravanakumar, R.; Syed Ali, M.; Cao, Jinde; Huang, He

2016-12-01

This paper focuses on studying the H∞ state estimation of generalised neural networks with interval time-varying delays. The integral terms in the time derivative of the Lyapunov-Krasovskii functional are handled by the Jensen's inequality, reciprocally convex combination approach and a new Wirtinger-based double integral inequality. A delay-dependent criterion is derived under which the estimation error system is globally asymptotically stable with H∞ performance. The proposed conditions are represented by linear matrix inequalities. Optimal H∞ norm bounds are obtained easily by solving convex problems in terms of linear matrix inequalities. The advantage of employing the proposed inequalities is illustrated by numerical examples.

Robust stability analysis of Takagi—Sugeno uncertain stochastic fuzzy recurrent neural networks with mixed time-varying delays

International Nuclear Information System (INIS)

Ali, M. Syed

2011-01-01

In this paper, the global stability of Takagi—Sugeno (TS) uncertain stochastic fuzzy recurrent neural networks with discrete and distributed time-varying delays (TSUSFRNNs) is considered. A novel LMI-based stability criterion is obtained by using Lyapunov functional theory to guarantee the asymptotic stability of TSUSFRNNs. The proposed stability conditions are demonstrated through numerical examples. Furthermore, the supplementary requirement that the time derivative of time-varying delays must be smaller than one is removed. Comparison results are demonstrated to show that the proposed method is more able to guarantee the widest stability region than the other methods available in the existing literature. (general)

Exponential synchronization of chaotic Lur'e systems with time-varying delay via sampled-data control

International Nuclear Information System (INIS)

Rakkiyappan, R.; Sivasamy, R.; Lakshmanan, S.

2014-01-01

In this paper, we study the exponential synchronization of chaotic Lur'e systems with time-varying delays via sampled-data control by using sector nonlinearties. In order to make full use of information about sampling intervals and interval time-varying delays, new Lyapunov—Krasovskii functionals with triple integral terms are introduced. Based on the convex combination technique, two kinds of synchronization criteria are derived in terms of linear matrix inequalities, which can be efficiently solved via standard numerical software. Finally, three numerical examples are provided to demonstrate the less conservatism and effectiveness of the proposed results

Real time detection of antibody-antigen interaction using a laser scanning confocal imaging-surface plasmon resonance system

International Nuclear Information System (INIS)

Zhang Hong-Yan; Yang Li-Quan; Ning Ting-Yin; Liu Wei-Min; Sun Jia-Yu; Wang Peng-Fei; Meng Lan; Nie Jia-Cai

2012-01-01

A laser scanning confocal imaging-surface plasmon resonance (LSCI-SPR) instrument integrated with a wavelength-dependent surface plasmon resonance (SPR) sensor and a laser scanning confocal microscopy (LSCM) is built to detect the bonding process of human IgG and fluorescent-labeled affinity purified antibodies in real time. The shifts of resonant wavelength at different reaction time stages are obtained by SPR, corresponding well with the changes of the fluorescence intensity collected by using LSCM. The instrument shows the merits of the combination and complementation of the SPR and LSCM, with such advantages as quantificational analysis, high spatial resolution and real time monitor, which are of great importance for practical applications in biosensor and life science. (general)

Multi-Step Time Series Forecasting with an Ensemble of Varied Length Mixture Models.

Science.gov (United States)

Ouyang, Yicun; Yin, Hujun

2018-05-01

Many real-world problems require modeling and forecasting of time series, such as weather temperature, electricity demand, stock prices and foreign exchange (FX) rates. Often, the tasks involve predicting over a long-term period, e.g. several weeks or months. Most existing time series models are inheritably for one-step prediction, that is, predicting one time point ahead. Multi-step or long-term prediction is difficult and challenging due to the lack of information and uncertainty or error accumulation. The main existing approaches, iterative and independent, either use one-step model recursively or treat the multi-step task as an independent model. They generally perform poorly in practical applications. In this paper, as an extension of the self-organizing mixture autoregressive (AR) model, the varied length mixture (VLM) models are proposed to model and forecast time series over multi-steps. The key idea is to preserve the dependencies between the time points within the prediction horizon. Training data are segmented to various lengths corresponding to various forecasting horizons, and the VLM models are trained in a self-organizing fashion on these segments to capture these dependencies in its component AR models of various predicting horizons. The VLM models form a probabilistic mixture of these varied length models. A combination of short and long VLM models and an ensemble of them are proposed to further enhance the prediction performance. The effectiveness of the proposed methods and their marked improvements over the existing methods are demonstrated through a number of experiments on synthetic data, real-world FX rates and weather temperatures.

SU-G-206-06: Analytic Dose Function for CT Scans in Infinite Cylinders as a Function of Scan Length and Cylinder Radius

Energy Technology Data Exchange (ETDEWEB)

Bakalyar, D [Henry Ford Health System, Detroit, MI (United States); Feng, W [New York Presbyterian Hospital, Tenafly, NJ (United States); McKenney, S [Children’s National Medical Center, Washington, DC (United States)

2016-06-15

Purpose: The radiation dose absorbed at a particular radius ρ within the central plane of a long cylinder following a CT scan is a function of the length of the scan L and the cylinder radius R along with kVp and cylinder composition. An analytic function was created that that not only expresses these dependencies but is integrable in closed form over the area of the central plane. This feature facilitates explicit calculation of the planar average dose. The “approach to equilibrium” h(L) discussed in the TG111 report is seamlessly included in this function. Methods: For a cylindrically symmetric radiation field, Monte Carlo calculations were performed to compute the dose distribution to long polyethylene cylinders for scans of varying L for cylinders ranging in radius from 5 to 20 cm. The function was developed from the resultant Monte Carlo data. In addition, the function was successfully fit to data taken from measurements on the 30 cm diameter ICRU/TG200 phantom using a real-time dosimeter. Results: Symmetry and continuity dictate a local extremum at the center which is a minimum for the larger sizes. There are competing effects as the beam penetrates the cylinder from the outside: attenuation, resulting in a decrease; scatter, abruptly increasing at the circumference. This competition may result in an absolute maximum between the center and outer edge leading to a “gull wing” shape for the radial dependence. For the smallest cylinders, scatter may dominate to the extent that there is an absolute maximum at the center. Conclusion: An integrable, analytic function has been developed that provides the radial dependency of dose for the central plane of a scan of length L for cylinders of varying diameter. Equivalently, we have developed h(L,R,ρ).

Multivariate Option Pricing with Time Varying Volatility and Correlations

DEFF Research Database (Denmark)

Rombouts, Jeroen V.K.; Stentoft, Lars Peter

In recent years multivariate models for asset returns have received much attention, in particular this is the case for models with time varying volatility. In this paper we consider models of this class and examine their potential when it comes to option pricing. Specifically, we derive the risk...... neutral dynamics for a general class of multivariate heteroskedastic models, and we provide a feasible way to price options in this framework. Our framework can be used irrespective of the assumed underlying distribution and dynamics, and it nests several important special cases. We provide an application...... to options on the minimum of two indices. Our results show that not only is correlation important for these options but so is allowing this correlation to be dynamic. Moreover, we show that for the general model exposure to correlation risk carries an important premium, and when this is neglected option...

Invariant operator theory for the single-photon energy in time-varying media

International Nuclear Information System (INIS)

Jeong-Ryeol, Choi

2010-01-01

After the birth of quantum mechanics, the notion in physics that the frequency of light is the only factor that determines the energy of a single photon has played a fundamental role. However, under the assumption that the theory of Lewis–Riesenfeld invariants is applicable in quantum optics, it is shown in the present work that this widely accepted notion is valid only for light described by a time-independent Hamiltonian, i.e., for light in media satisfying the conditions, ε(i) = ε(0), μ(t) = μ(0), and σ(t) = 0 simultaneously. The use of the Lewis–Riesenfeld invariant operator method in quantum optics leads to a marvelous result: the energy of a single photon propagating through time-varying linear media exhibits nontrivial time dependence without a change of frequency. (general)

Time-varying predictability in crude-oil markets: the case of GCC countries

International Nuclear Information System (INIS)

El Hedi Arouri, Mohamed; Thanh Huong Dinh; Duc Khuong Nguyen

2010-01-01

This paper uses a time-varying parameter model with generalized autoregressive conditional heteroscedasticity effects to examine the dynamic behavior of crude-oil prices for the period February 7, 1997-January 8, 2010. Using data from four countries of the Gulf Cooperation Council, we find evidence of short-term predictability in oil-price changes over time, except for several short sub-periods. However, the hypothesis of convergence towards weak-form informational efficiency is rejected for all markets. In addition, we explore the possibility of structural breaks in the time-paths of the estimated predictability indices and detect only one breakpoint, for the oil markets in Qatar and the United Arab Emirates. Our empirical results therefore call for new empirical research to further gauge the predictability characteristics and the determinants of oil-price changes.

Exponential convergence for a class of delayed cellular neural networks with time-varying coefficients

International Nuclear Information System (INIS)

Liu Bingwen

2008-01-01

In this Letter, we consider a class of delayed cellular neural networks with time-varying coefficients. By applying Lyapunov functional method and differential inequality techniques, we establish new results to ensure that all solutions of the networks converge exponentially to zero point

A comparison of time-varying covariates in two smoking cessation interventions for cardiac patients

NARCIS (Netherlands)

Prenger, Hendrikje Cornelia; Pieterse, Marcel E.; Braakman-Jansen, Louise Marie Antoinette; Bolman, Catherine; Ruitenbeek-Wiggers, L.; de Vries, H.

2013-01-01

The aim of the study was to explore the time-varying contribution of social cognitive determinants of smoking cessation following an intervention on cessation. Secondary analyses were performed on data from two comparable randomized controlled trials on brief smoking cessation interventions for

Hotspot detection using space-time scan statistics on children under five years of age in Depok

Science.gov (United States)

Verdiana, Miranti; Widyaningsih, Yekti

2017-03-01

Some problems that affect the health level in Depok is the high malnutrition rates from year to year and the more spread infectious and non-communicable diseases in some areas. Children under five years old is a vulnerable part of population to get the malnutrition and diseases. Based on this reason, it is important to observe the location and time, where and when, malnutrition in Depok happened in high intensity. To obtain the location and time of the hotspots of malnutrition and diseases that attack children under five years old, space-time scan statistics method can be used. Space-time scan statistic is a hotspot detection method, where the area and time of information and time are taken into account simultaneously in detecting the hotspots. This method detects a hotspot with a cylindrical scanning window: the cylindrical pedestal describes the area, and the height of cylinder describe the time. Cylinders formed is a hotspot candidate that may occur, which require testing of hypotheses, whether a cylinder can be summed up as a hotspot. Hotspot detection in this study carried out by forming a combination of several variables. Some combination of variables provides hotspot detection results that tend to be the same, so as to form groups (clusters). In the case of infant health level in Depok city, Beji health care center region in 2011-2012 is a hotspot. According to the combination of the variables used in the detection of hotspots, Beji health care center is most frequently as a hotspot. Hopefully the local government can take the right policy to improve the health level of children under five in the city of Depok.

A non-contact time-domain scanning brain imaging system: first in-vivo results

Science.gov (United States)

Mazurenka, M.; Di Sieno, L.; Boso, G.; Contini, D.; Pifferi, A.; Dalla Mora, A.; Tosi, A.; Wabnitz, H.; Macdonald, R.

2013-06-01

We present results of first in-vivo tests of an optical non-contact scanning imaging system, intended to study oxidative metabolism related processes in biological tissue by means of time-resolved near-infrared spectroscopy. Our method is a novel realization of the short source-detector separation approach and based on a fast-gated single-photon avalanche diode to detect late photons only. The scanning system is built in quasi-confocal configuration and utilizes polarizationsensitive detection. It scans an area of 4×4 cm2, recording images with 32×32 pixels, thus creating a high density of source-detector pairs. To test the system we performed a range of in vivo measurements of hemodynamic changes in several types of biological tissues, i.e. skin (Valsalva maneuver), muscle (venous and arterial occlusions) and brain (motor and cognitive tasks). Task-related changes in hemoglobin concentrations were clearly detected in skin and muscle. The brain activation shows weaker, but yet detectable changes. These changes were localized in pixels near the motor cortex area (C3). However, it was found that even very short hair substantially impairs the measurement. Thus the applicability of the scanner is limited to hairless parts of body. The results of our first in-vivo tests prove the feasibility of non-contact scanning imaging as a first step towards development of a prototype for biological tissue imaging for various medical applications.

Innovation diffusion on time-varying activity driven networks

Science.gov (United States)

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.

Identifiability of Additive, Time-Varying Actuator and Sensor Faults by State Augmentation

Science.gov (United States)

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.

SU-E-T-755: Timing Characteristics of Proton and Carbon Ion Treatments Using a Synchrotron and Modulated Scanning

International Nuclear Information System (INIS)

Zhao, J; Li, Y; Huang, Z; Deng, Y; Sun, L; Moyers, M; Hsi, W; Wu, X

2015-01-01

Purpose: The time required to deliver a treatment impacts not only the number of patients that can be treated each day but also the accuracy of delivery due to potential movements of patient tissues. Both macroscopic and microscopic timing characteristics of a beam delivery system were studied to examine their impacts on patient treatments. Methods: 35 patients were treated during a clinical trial to demonstrate safety and efficacy of a Siemens Iontris system prior to receiving approval from the Chinese Food and Drug Administration. The system has a variable cycle time and can provide proton beams from 48 to 221 MeV/n and carbon ions from 86 to 430 MeV/n. A modulated scanning beam delivery technique is used where the beam remains stationary at each spot aiming location and is not turned off while the spot quickly moves from one aiming location to the next. The treatment log files for 28 of the trial patients were analyzed to determine several timing characteristics. Results: The average portal time per target dose was 172.5 s/Gy for protons and 150.7 s/Gy for carbon ions. The maximum delivery time for any portal was less than 300 s. The average dwell time per spot was 12 ms for protons and 3.0 ms for carbon ions. The number of aiming positions per energy layer varied from 1 to 258 for protons and 1 to 621 for carbon ions. The average spill time and cycle time per energy layer were 1.20 and 2.68 s for protons and 0.95 and 4.73 s for carbon ions respectively. For 3 of the patients, the beam was gated on and off to reduce the effects of respiration. Conclusion: For a typical target volume of 153 cc as used in this clinical trial, the portal delivery times were acceptable

Time-varying associations between confidence and motivation to abstain from marijuana during treatment among adolescents.

Science.gov (United States)

Chung, Tammy; Maisto, Stephen A

2016-06-01

An important goal of addictions treatment is to develop a positive association between high levels of confidence and motivation to abstain from substance use. This study modeled the time-varying association between confidence and motivation to abstain from marijuana use among youth in treatment, and the time-varying effect of pre-treatment covariates (marijuana abstinence goal and perceived peer marijuana use) on motivation to abstain. 150 adolescents (75% male, 83% White) in community-based intensive outpatient treatment in Pennsylvania completed a pre-treatment assessment of abstinence goal, perceived peer marijuana use, and motivation and confidence to abstain from marijuana. Ratings of motivation and confidence to abstain also were collected after each session. A time-varying effect model (TVEM) was used to characterize changes in the association between confidence and motivation to abstain (lagged), and included covariates representing pre-treatment abstinence goal and perceived peer marijuana use. Confidence and motivation to abstain from marijuana generally increased during treatment. The association between confidence and motivation strengthened across sessions 1-4, and was maintained through later sessions. Pre-treatment abstinence goal had an early time-limited effect (through session 6) on motivation to abstain. Pre-treatment perception of peer marijuana use had a significant effect on motivation to abstain only at session 2. Early treatment sessions represent a critical period during which the association between confidence and motivation to abstain generally increased. The time-limited effects of pre-treatment characteristics suggest the importance of early sessions in addressing abstinence goal and peer substance use that may impact motivation to abstain from marijuana. Copyright © 2016 Elsevier Ltd. All rights reserved.

Time-varying mixed logit model for vehicle merging behavior in work zone merging areas.

Science.gov (United States)

Weng, Jinxian; Du, Gang; Li, Dan; Yu, Yao

2018-08-01

This study aims to develop a time-varying mixed logit model for the vehicle merging behavior in work zone merging areas during the merging implementation period from the time of starting a merging maneuver to that of completing the maneuver. From the safety perspective, vehicle crash probability and severity between the merging vehicle and its surrounding vehicles are regarded as major factors influencing vehicle merging decisions. Model results show that the model with the use of vehicle crash risk probability and severity could provide higher prediction accuracy than previous models with the use of vehicle speeds and gap sizes. It is found that lead vehicle type, through lead vehicle type, through lag vehicle type, crash probability of the merging vehicle with respect to the through lag vehicle, crash severities of the merging vehicle with respect to the through lead and lag vehicles could exhibit time-varying effects on the merging behavior. One important finding is that the merging vehicle could become more and more aggressive in order to complete the merging maneuver as quickly as possible over the elapsed time, even if it has high vehicle crash risk with respect to the through lead and lag vehicles. Copyright © 2018 Elsevier Ltd. All rights reserved.

Detection and characterization of Budd-Chiari syndrome with inferior vena cava obstruction: Comparison of fixed and flexible delayed scan time of computed tomography venography.

Science.gov (United States)

Zhou, Peng-Li; Wu, Gang; Han, Xin-Wei; Bi, Yong-Hua; Zhang, Wen-Guang; Wu, Zheng-Yang

2017-06-01

To compare the results of computed tomography venography (CTV) with a fixed and a flexible delayed scan time for Budd-Chiari syndrome (BCS) with inferior vena cava (IVC) obstruction. A total of 209 consecutive BCS patients with IVC obstruction underwent either a CTV with a fixed delayed scan time of 180s (n=87) or a flexible delayed scan time for good image quality according to IVC blood flow in color Doppler ultrasonography (n=122). The IVC blood flow velocity was measured using a color Doppler ultrasound prior to CT scan. Image quality was classified as either good, moderate, or poor. Image quality, surrounding structures and the morphology of the IVC obstruction were compared between the two groups using a χ 2 -test or paired or unpaired t-tests as appropriate. Inter-observer agreement was assessed using Kappa statistics. There was no significant difference in IVC blood flow velocity between the two groups. Overall image quality, surrounding structures and IVC obstruction morphology delineation on the flexible delayed scan time of CTV images were rated better relative to those obtained by fixed delayed scan time of CTV images (ptime of CTV. There were no significant differences in Kappa statistics between Group A and Group B. The flexible delayed scan time of CTV was associated with better detection and more reliable characterization of BCS with IVC obstruction compared to a fixed delayed scan time. Copyright © 2017 Elsevier B.V. All rights reserved.

Neutron fluctuations in a multiplying medium randomly varying in time

Energy Technology Data Exchange (ETDEWEB)

Pal, L. [KFKI Atomic Energy Research Inst., Budapest (Hungary); Pazsit, I. [Chalmers Univ. of Technology, Goeteborg (Sweden). Dept. of Nuclear Engineering

2006-07-15

The master equation approach, which has traditionally been used for the calculation of neutron fluctuations in multiplying systems with constant parameters, is extended to a case when the parameters of the system change randomly in time. A forward type master equation is considered for the case of a multiplying system whose properties jump randomly between two discrete states, both with and without a stationary external source. The first two factorial moments are calculated, including the covariance. This model can be considered as the unification of stochastic methods that were used either in a constant multiplying medium via the master equation technique, or in a fluctuating medium via the Langevin technique. The results obtained show a much richer characteristic of the zero power noise than that in constant systems. The results are relevant in medium power subcritical nuclear systems where the zero power noise is still significant, but they also have a bearing on all types of branching processes, such as evolution of biological systems, spreading of epidemics etc, which are set in a time-varying environment.

Neutron fluctuations in a multiplying medium randomly varying in time

International Nuclear Information System (INIS)

Pal, L.; Pazsit, I.

2006-01-01

The master equation approach, which has traditionally been used for the calculation of neutron fluctuations in multiplying systems with constant parameters, is extended to a case when the parameters of the system change randomly in time. A forward type master equation is considered for the case of a multiplying system whose properties jump randomly between two discrete states, both with and without a stationary external source. The first two factorial moments are calculated, including the covariance. This model can be considered as the unification of stochastic methods that were used either in a constant multiplying medium via the master equation technique, or in a fluctuating medium via the Langevin technique. The results obtained show a much richer characteristic of the zero power noise than that in constant systems. The results are relevant in medium power subcritical nuclear systems where the zero power noise is still significant, but they also have a bearing on all types of branching processes, such as evolution of biological systems, spreading of epidemics etc, which are set in a time-varying environment

Estimation and Properties of a Time-Varying GQARCH(1,1-M Model

Directory of Open Access Journals (Sweden)

Sofia Anyfantaki

2011-01-01

analysis of these models computationally infeasible. This paper outlines the issues and suggests to employ a Markov chain Monte Carlo algorithm which allows the calculation of a classical estimator via the simulated EM algorithm or a simulated Bayesian solution in only ( computational operations, where is the sample size. Furthermore, the theoretical dynamic properties of a time-varying GQARCH(1,1-M are derived. We discuss them and apply the suggested Bayesian estimation to three major stock markets.

Adaptive Synchronization between Two Different Complex Networks with Time-Varying Delay Coupling

International Nuclear Information System (INIS)

Jian-Rui, Chen; Li-Cheng, Jiao; Jian-She, Wu; Xiao-Hua, Wang

2009-01-01

A new general network model for two complex networks with time-varying delay coupling is presented. Then we investigate its synchronization phenomena. The two complex networks of the model differ in dynamic nodes, the number of nodes and the coupling connections. By using adaptive controllers, a synchronization criterion is derived. Numerical examples are given to demonstrate the effectiveness of the obtained synchronization criterion. This study may widen the application range of synchronization, such as in chaotic secure communication. (general)

Parametric estimation of time varying baselines in airborne interferometric SAR

DEFF Research Database (Denmark)

Mohr, Johan Jacob; Madsen, Søren Nørvang

1996-01-01

A method for estimation of time varying spatial baselines in airborne interferometric synthetic aperture radar (SAR) is described. The range and azimuth distortions between two images acquired with a non-linear baseline are derived. A parametric model of the baseline is then, in a least square...... sense, estimated from image shifts obtained by cross correlation of numerous small patches throughout the image. The method has been applied to airborne EMISAR imagery from the 1995 campaign over the Storstrommen Glacier in North East Greenland conducted by the Danish Center for Remote Sensing. This has...... reduced the baseline uncertainties from several meters to the centimeter level in a 36 km scene. Though developed for airborne SAR the method can easily be adopted to satellite data...

Detecting Changes in Forest Structure over Time with Bi-Temporal Terrestrial Laser Scanning Data

Directory of Open Access Journals (Sweden)

Timo Melkas

2012-10-01

Full Text Available Changes to stems caused by natural forces and timber harvesting constitute an essential input for many forestry-related applications and ecological studies, especially forestry inventories based on the use of permanent sample plots. Conventional field measurement is widely acknowledged as being time-consuming and labor-intensive. More automated and efficient alternatives or supportive methods are needed. Terrestrial laser scanning (TLS has been demonstrated to be a promising method in forestry field inventories. Nevertheless, the applicability of TLS in recording changes in the structure of forest plots has not been studied in detail. This paper presents a fully automated method for detecting changes in forest structure over time using bi-temporal TLS data. The developed method was tested on five densely populated forest plots including 137 trees and 50 harvested trees in point clouds. The present study demonstrated that 90 percent of tree stem changes could be automatically located from single-scan TLS data. These changes accounted for 92 percent of the changed basal area. The results indicate that the processing of TLS data collected at different times to detect tree stem changes can be fully automated.

Adaptive control of chaotic systems with stochastic time varying unknown parameters

Energy Technology Data Exchange (ETDEWEB)

Salarieh, Hassan [Center of Excellence in Design, Robotics and Automation, Department of Mechanical Engineering, Sharif University of Technology, P.O. Box 11365-9567, Azadi Avenue, Tehran (Iran, Islamic Republic of)], E-mail: salarieh@mech.sharif.edu; Alasty, Aria [Center of Excellence in Design, Robotics and Automation, Department of Mechanical Engineering, Sharif University of Technology, P.O. Box 11365-9567, Azadi Avenue, Tehran (Iran, Islamic Republic of)], E-mail: aalasti@sharif.edu

2008-10-15

In this paper based on the Lyapunov stability theorem, an adaptive control scheme is proposed for stabilizing the unstable periodic orbits (UPO) of chaotic systems. It is assumed that the chaotic system has some linearly dependent unknown parameters which are stochastically time varying. The stochastic parameters are modeled through the Weiner process derivative. To demonstrate the effectiveness of the proposed technique it has been applied to the Lorenz, Chen and Rossler dynamical systems, as some case studies. Simulation results indicate that the proposed adaptive controller has a high performance in stabilizing the UPO of chaotic systems in noisy environment.

System and method for compressive scanning electron microscopy

Science.gov (United States)

Reed, Bryan W

2015-01-13

A scanning transmission electron microscopy (STEM) system is disclosed. The system may make use of an electron beam scanning system configured to generate a plurality of electron beam scans over substantially an entire sample, with each scan varying in electron-illumination intensity over a course of the scan. A signal acquisition system may be used for obtaining at least one of an image, a diffraction pattern, or a spectrum from the scans, the image, diffraction pattern, or spectrum representing only information from at least one of a select subplurality or linear combination of all pixel locations comprising the image. A dataset may be produced from the information. A subsystem may be used for mathematically analyzing the dataset to predict actual information that would have been produced by each pixel location of the image.

Impulsive effect on global exponential stability of BAM fuzzy cellular neural networks with time-varying delays

Science.gov (United States)

Li, Kelin

2010-02-01

In this article, a class of impulsive bidirectional associative memory (BAM) fuzzy cellular neural networks (FCNNs) with time-varying delays is formulated and investigated. By employing delay differential inequality and M-matrix theory, some sufficient conditions ensuring the existence, uniqueness and global exponential stability of equilibrium point for impulsive BAM FCNNs with time-varying delays are obtained. In particular, a precise estimate of the exponential convergence rate is also provided, which depends on system parameters and impulsive perturbation intention. It is believed that these results are significant and useful for the design and applications of BAM FCNNs. An example is given to show the effectiveness of the results obtained here.

Volatility spillover and time-varying conditional correlation between DDGS, corn, and soybean meal markets

NARCIS (Netherlands)

Etienne, Xiaoli L.; Trujillo-Barrera, Andrés; Hoffman, Linwood A.

2017-01-01

We find distiller's dried grains with solubles (DDGS) prices to be positively correlated with both corn and soybean meal prices in the long run. However, neither corn nor soybean meal prices respond to deviations from this long-run relationship. We also identify strong time-varying dynamic

Nonlinear isochrones in murine left ventricular pressure-volume loops: how well does the time-varying elastance concept hold?

Science.gov (United States)

Claessens, T E; Georgakopoulos, D; Afanasyeva, M; Vermeersch, S J; Millar, H D; Stergiopulos, N; Westerhof, N; Verdonck, P R; Segers, P

2006-04-01

The linear time-varying elastance theory is frequently used to describe the change in ventricular stiffness during the cardiac cycle. The concept assumes that all isochrones (i.e., curves that connect pressure-volume data occurring at the same time) are linear and have a common volume intercept. Of specific interest is the steepest isochrone, the end-systolic pressure-volume relationship (ESPVR), of which the slope serves as an index for cardiac contractile function. Pressure-volume measurements, achieved with a combined pressure-conductance catheter in the left ventricle of 13 open-chest anesthetized mice, showed a marked curvilinearity of the isochrones. We therefore analyzed the shape of the isochrones by using six regression algorithms (two linear, two quadratic, and two logarithmic, each with a fixed or time-varying intercept) and discussed the consequences for the elastance concept. Our main observations were 1) the volume intercept varies considerably with time; 2) isochrones are equally well described by using quadratic or logarithmic regression; 3) linear regression with a fixed intercept shows poor correlation (R(2) volume intercept of the ESPVR. In conclusion, the linear time-varying elastance fails to provide a sufficiently robust model to account for changes in pressure and volume during the cardiac cycle in the mouse ventricle. A new framework accounting for the nonlinear shape of the isochrones needs to be developed.

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

Science.gov (United States)

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.

Cine viability magnetic resonance imaging of the heart without increased scan time.

Science.gov (United States)

Hassanein, Azza S; Khalifa, Ayman M; Ibrahim, El-Sayed H

2016-02-01

Cardiac magnetic resonance imaging (MRI) provides information about myocardial morphology, function, and viability from cine, tagged, and late gadolinium enhancement (LGE) images, respectively. While the cine and tagged images are acquired in a time-resolved fashion, the LGE images are acquired at a single timeframe. The purpose of this work is to develop a method for generating cine LGE images without additional scan time. The motion field is extracted from the tagged images, and is then used to guide the deformation of the infarcted region from the acquired LGE image at the acquired timeframe to any other timeframe. Major techniques for motion estimation, including harmonic phase (HARP) and optical flow analysis, are tested in this work for motion estimation. The proposed method is tested on numerical phantom and images from four human subjects. The generated cine LGE images showed both viability and wall motion information in the same set of images without additional scan time or image misregistration problems. The band-pass optical flow analysis resulted in the most accurate motion estimation compared to other methods, especially HARP, which fails to track points at the myocardial boundary. Infarct transmurality from the generated images showed good agreement with myocardial strain, and wall thickening showed good agreement with that measured from conventional cine images. In conclusion, the developed technique allows for generating cine LGE images that enable simultaneous display of wall motion and viability information. The generated images could be useful for estimating myocardial contractility reserve and for treatment prognosis. Copyright © 2015 Elsevier Inc. All rights reserved.

Renormalization group theory for percolation in time-varying networks.

Science.gov (United States)

Karschau, Jens; Zimmerling, Marco; Friedrich, Benjamin M

2018-05-22

Motivated by multi-hop communication in unreliable wireless networks, we present a percolation theory for time-varying networks. We develop a renormalization group theory for a prototypical network on a regular grid, where individual links switch stochastically between active and inactive states. The question whether a given source node can communicate with a destination node along paths of active links is equivalent to a percolation problem. Our theory maps the temporal existence of multi-hop paths on an effective two-state Markov process. We show analytically how this Markov process converges towards a memoryless Bernoulli process as the hop distance between source and destination node increases. Our work extends classical percolation theory to the dynamic case and elucidates temporal correlations of message losses. Quantification of temporal correlations has implications for the design of wireless communication and control protocols, e.g. in cyber-physical systems such as self-organized swarms of drones or smart traffic networks.

Effect of a time varying power level in EBR-II on mixed-oxide fuel burnup

International Nuclear Information System (INIS)

Stone, I.Z.; Jost, J.W.; Baker, R.B.

1979-01-01

A refined prediction of burnup of mixed-oxide fuel in EBR-2 is compared with measured data. The calculation utilizes a time-varying power factor and results in a general improvement to previous calculations

Design and implementation of multi-signal and time-varying neural reconstructions.

Science.gov (United States)

Nanda, Sumit; Chen, Hanbo; Das, Ravi; Bhattacharjee, Shatabdi; Cuntz, Hermann; Torben-Nielsen, Benjamin; Peng, Hanchuan; Cox, Daniel N; De Schutter, Erik; Ascoli, Giorgio A

2018-01-23

Several efficient procedures exist to digitally trace neuronal structure from light microscopy, and mature community resources have emerged to store, share, and analyze these datasets. In contrast, the quantification of intracellular distributions and morphological dynamics is not yet standardized. Current widespread descriptions of neuron morphology are static and inadequate for subcellular characterizations. We introduce a new file format to represent multichannel information as well as an open-source Vaa3D plugin to acquire this type of data. Next we define a novel data structure to capture morphological dynamics, and demonstrate its application to different time-lapse experiments. Importantly, we designed both innovations as judicious extensions of the classic SWC format, thus ensuring full back-compatibility with popular visualization and modeling tools. We then deploy the combined multichannel/time-varying reconstruction system on developing neurons in live Drosophila larvae by digitally tracing fluorescently labeled cytoskeletal components along with overall dendritic morphology as they changed over time. This same design is also suitable for quantifying dendritic calcium dynamics and tracking arbor-wide movement of any subcellular substrate of interest.

Time-varying surface electromyography topography as a prognostic tool for chronic low back pain rehabilitation.

Science.gov (United States)

Hu, Yong; Kwok, Jerry Weilun; Tse, Jessica Yuk-Hang; Luk, Keith Dip-Kei

2014-06-01

Nonsurgical rehabilitation therapy is a commonly used strategy to treat chronic low back pain (LBP). The selection of the most appropriate therapeutic options is still a big challenge in clinical practices. Surface electromyography (sEMG) topography has been proposed to be an objective assessment of LBP rehabilitation. The quantitative analysis of dynamic sEMG would provide an objective tool of prognosis for LBP rehabilitation. To evaluate the prognostic value of quantitative sEMG topographic analysis and to verify the accuracy of the performance of proposed time-varying topographic parameters for identifying the patients who have better response toward the rehabilitation program. A retrospective study of consecutive patients. Thirty-eight patients with chronic nonspecific LBP and 43 healthy subjects. The accuracy of the time-varying quantitative sEMG topographic analysis for monitoring LBP rehabilitation progress was determined by calculating the corresponding receiver-operating characteristic (ROC) curves. Physiologic measure was the sEMG during lumbar flexion and extension. Patients who suffered from chronic nonspecific LBP without the history of back surgery and any medical conditions causing acute exacerbation of LBP during the clinical test were enlisted to perform the clinical test during the 12-week physiotherapy (PT) treatment. Low back pain patients were classified into two groups: "responding" and "nonresponding" based on the clinical assessment. The responding group referred to the LBP patients who began to recover after the PT treatment, whereas the nonresponding group referred to some LBP patients who did not recover or got worse after the treatment. The results of the time-varying analysis in the responding group were compared with those in the nonresponding group. In addition, the accuracy of the analysis was analyzed through ROC curves. The time-varying analysis showed discrepancies in the root-mean-square difference (RMSD) parameters between the

Bone scan in pediatrics

International Nuclear Information System (INIS)

Gordon, I.; Peters, A.M.

1987-01-01

In 1984, a survey carried out in 21 countries in Europe showed that bone scintigraphy comprised 16% of all paediatric radioisotope scans. Although the value of bone scans in paediatrics is potentially great, their quality varies greatly, and poor-quality images are giving this valuable technique a bad reputation. The handling of children requires a sensitive staff and the provision of a few simple inexpensive items of distraction. Attempting simply to scan a child between two adult patients in a busy general department is a recipe for an unhappy, uncooperative child with the probable result of poor images. The intravenous injection of isotope should be given adjacent to the gamma camera room, unless dynamic scans are required, so that the child does not associate the camera with the injection. This injection is best carried out by someone competent in paediatric venipunture; the entire procedure should be explained to the child and parent, who should remain with child throughout. It is naive to think that silence makes for a cooperative child. The sensitivity of bone-seeking radioisotope tracers and the marked improvement in gamma camera resolution has allowed the bone scanning to become an integrated technique in the assessment of children suspected of suffering from pathological bone conditions. The tracer most commonly used for routine bone scanning is 99m Tc diphosphonate (MDP); other isotopes used include 99m Tc colloid for bone marrow scans and 67 Ga citrate and 111 In white blood cells ( 111 In WBC) for investigation of inflammatory/infective lesions

A SVDD and K-Means Based Early Warning Method for Dual-Rotor Equipment under Time-Varying Operating Conditions

Directory of Open Access Journals (Sweden)

Zhinong Jiang

2018-01-01

Full Text Available Under frequently time-varying operating conditions, equipment with dual rotors like gas turbines is influenced by two rotors with different rotating speeds. Alarm methods of fixed threshold are unable to consider the influences of time-varying operating conditions. Hence, those methods are not suitable for monitoring dual-rotor equipment. An early warning method for dual-rotor equipment under time-varying operating conditions is proposed in this paper. The influences of time-varying rotating speeds of dual rotors on alarm thresholds have been considered. Firstly, the operating conditions are divided into several limited intervals according to rotating speeds of dual rotors. Secondly, the train data within each interval is processed by SVDD and the allowable ranges (i.e., the alarm threshold of the vibration are determined. The alarm threshold of each interval of operating conditions is obtained. The alarm threshold can be expressed as a sphere, whose controlling parameters are the coordinate of the center and the radius. Then, the cluster center of the test data, whose alarm state is to be judged, can be extracted through K-means. Finally, the alarm state can be obtained by comparing the cluster center with the corresponding sphere. Experiments are conducted to validate the proposed method.

Varied appearance of lymphoma in patients with AIDS

International Nuclear Information System (INIS)

Sider, L.; Weiss, A.

1988-01-01

Lymphoma is frequently present in patients with acquired immunodeficiency (AIDS). But unlike in the general population, the appearance of lymphoma in patients with AIDS is extremely varied. The computed tomographic scans, chest radiographs, and subsequent hospital courses of 15 patients with AIDS-related lymphoma are presented. The patients presented with isolated pleural effusion (six patients), pleural and pericardial effusion (one patient), pulmonary infiltrates (five patients), and mediastinal adenopathy (three patients). This varied manner of presentation of lymphoma in AIDS patients should be recognized if diagnosis is to be made in the earlier stages of presentation

Consequences of varied soil hydraulic and meteorological complexity on unsaturated zone time lag estimates.

Science.gov (United States)

Vero, S E; Ibrahim, T G; Creamer, R E; Grant, J; Healy, M G; Henry, T; Kramers, G; Richards, K G; Fenton, O

2014-12-01

The true efficacy of a programme of agricultural mitigation measures within a catchment to improve water quality can be determined only after a certain hydrologic time lag period (subsequent to implementation) has elapsed. As the biophysical response to policy is not synchronous, accurate estimates of total time lag (unsaturated and saturated) become critical to manage the expectations of policy makers. The estimation of the vertical unsaturated zone component of time lag is vital as it indicates early trends (initial breakthrough), bulk (centre of mass) and total (Exit) travel times. Typically, estimation of time lag through the unsaturated zone is poor, due to the lack of site specific soil physical data, or by assuming saturated conditions. Numerical models (e.g. Hydrus 1D) enable estimates of time lag with varied levels of input data. The current study examines the consequences of varied soil hydraulic and meteorological complexity on unsaturated zone time lag estimates using simulated and actual soil profiles. Results indicated that: greater temporal resolution (from daily to hourly) of meteorological data was more critical as the saturated hydraulic conductivity of the soil decreased; high clay content soils failed to converge reflecting prevalence of lateral component as a contaminant pathway; elucidation of soil hydraulic properties was influenced by the complexity of soil physical data employed (textural menu, ROSETTA, full and partial soil water characteristic curves), which consequently affected time lag ranges; as the importance of the unsaturated zone increases with respect to total travel times the requirements for high complexity/resolution input data become greater. The methodology presented herein demonstrates that decisions made regarding input data and landscape position will have consequences for the estimated range of vertical travel times. Insufficiencies or inaccuracies regarding such input data can therefore mislead policy makers regarding

Detector, collimator and real-time reconstructor for a new scanning-beam digital x-ray (SBDX) prototype.

Science.gov (United States)

Speidel, Michael A; Tomkowiak, Michael T; Raval, Amish N; Dunkerley, David A P; Slagowski, Jordan M; Kahn, Paul; Ku, Jamie; Funk, Tobias

Scanning-beam digital x-ray (SBDX) is an inverse geometry fluoroscopy system for low dose cardiac imaging. The use of a narrow scanned x-ray beam in SBDX reduces detected x-ray scatter and improves dose efficiency, however the tight beam collimation also limits the maximum achievable x-ray fluence. To increase the fluence available for imaging, we have constructed a new SBDX prototype with a wider x-ray beam, larger-area detector, and new real-time image reconstructor. Imaging is performed with a scanning source that generates 40,328 narrow overlapping projections from 71 × 71 focal spot positions for every 1/15 s scan period. A high speed 2-mm thick CdTe photon counting detector was constructed with 320×160 elements and 10.6 cm × 5.3 cm area (full readout every 1.28 μs), providing an 86% increase in area over the previous SBDX prototype. A matching multihole collimator was fabricated from layers of tungsten, brass, and lead, and a multi-GPU reconstructor was assembled to reconstruct the stream of captured detector images into full field-of-view images in real time. Thirty-two tomosynthetic planes spaced by 5 mm plus a multiplane composite image are produced for each scan frame. Noise equivalent quanta on the new SBDX prototype measured 63%-71% higher than the previous prototype. X-ray scatter fraction was 3.9-7.8% when imaging 23.3-32.6 cm acrylic phantoms, versus 2.3-4.2% with the previous prototype. Coronary angiographic imaging at 15 frame/s was successfully performed on the new SBDX prototype, with live display of either a multiplane composite or single plane image.

Fully time-resolved near-field scanning optical microscopy fluorescence imaging

International Nuclear Information System (INIS)

Kwak, Eun-Soo; Vanden Bout, David A.

2003-01-01

Time-correlated single photon counting has been coupled with near-field scanning optical microscopy (NSOM) to record complete fluorescence lifetime decays at each pixel in an NSOM image. The resulting three-dimensional data sets can be binned in the time dimension to create images of photons at particular time delays or images of the fluorescence lifetime. Alternatively, regions of interest identified in the topography and fluorescence images can be used to bin the data in the spatial dimensions resulting in high signal to noise fluorescence decays of particular regions of the sample. The technique has been demonstrated on films of poly(vinylalcohol), doped with the fluorescent dye, cascade blue (CB). The CB segregates into small circular regions of high concentration within the films during the drying process. The lifetime imaging shows that the spots have slightly faster excited state decays due to quenching of the luminescence as a result of the higher concentration. The technique is also used to image the fluorescence lifetime of an annealed film of poly(dihexylfluorene). The samples show high contrast in the total intensity fluorescence image, but the lifetime image reveals the sample to be extremely uniform

Reduction of Cone-Beam CT scan time without compromising the accuracy of the image registration in IGRT

DEFF Research Database (Denmark)

Westberg, Jonas; Jensen, Henrik R; Bertelsen, Anders

2010-01-01

In modern radiotherapy accelerators are equipped with 3D cone-beam CT (CBCT) which is used to verify patient position before treatment. The verification is based on an image registration between the CBCT acquired just before treatment and the CT scan made for the treatment planning. The purpose...... of this study is to minimise the scan time of the CBCT without compromising the accuracy of the image registration in IGRT....

Gold as an Infl ation Hedge in a Time-Varying Coefficient Framework

OpenAIRE

Beckmann, Joscha; Czudaj, Robert

2012-01-01

This study analyzes the question whether gold provides the ability of hedging against inflation from a new perspective. Using data for four major economies, namely the USA, the UK, the Euro Area, and Japan, we allow for nonlinearity and discriminate between long-run and time-varying short-run dynamics. Thus, we conduct a Markov-switching vector error correction model (MS-VECM) approach for a sample period ranging from January 1970 to December 2011. Our main findings are threefold: First, we s...

Unbiasedness and time varying risk premia in the crude oil futures market

International Nuclear Information System (INIS)

Moosa, I.A.; Al-Loughani, N.E.

1994-01-01

This paper presents some empirical evidence on market efficiency and unbiasedness in the crude oil futures market and some related issues. On the basis of monthly observations on spot and futures prices of the West Texas Intermediate (WTI) crude oil, several tests are carried out on the relevant hypotheses. The evidence suggests that futures prices are neither unbiased nor efficient forecasters of spot prices. Furthermore, a GARCH-M(1,1) model reveals the existence of a time varying risk premium. (author)

Tracking time-varying cerebral autoregulation in response to changes in respiratory PaCO2

International Nuclear Information System (INIS)

Liu, Jia; Simpson, M David; Allen, Robert; Yan, Jingyu

2010-01-01

Cerebral autoregulation has been studied by linear filter systems, with arterial blood pressure (ABP) as the input and cerebral blood flow velocity (CBFV—from transcranial Doppler Ultrasound) as the output. The current work extends this by using adaptive filters to investigate the dynamics of time-varying cerebral autoregulation during step-wise changes in arterial PaCO 2 . Cerebral autoregulation was transiently impaired in 11 normal adult volunteers, by switching inspiratory air to a CO 2 /air mixture (5% CO 2 , 30% O 2 and 65% N 2 ) for approximately 2 min and then back to the ambient air, causing step-wise changes in end-tidal CO 2 (EtCO 2 ). Simultaneously, ABP and CBFV were recorded continuously. Simulated data corresponding to the same protocol were also generated using an established physiological model, in order to refine the signal analysis methods. Autoregulation was quantified by the time-varying phase lead, estimated from the adaptive filter model. The adaptive filter was able to follow rapid changes in autoregulation, as was confirmed in the simulated data. In the recorded signals, there was a slow decrease in autoregulatory function following the step-wise increase in PaCO 2 (but this did not reach a steady state within approximately 2 min of recording), with a more rapid change in autoregulation on return to normocapnia. Adaptive filter modelling was thus able to demonstrate time-varying autoregulation. It was further noted that impairment and recovery of autoregulation during transient increases in EtCO 2 occur in an asymmetric manner, which should be taken into account when designing experimental protocols for the study of autoregulation

The relationship between global oil price shocks and China's output: A time-varying analysis

International Nuclear Information System (INIS)

Cross, Jamie; Nguyen, Bao H.

2017-01-01

We employ a class of time-varying Bayesian vector autoregressive (VAR) models on new standard dataset of China's GDP constructed by to examine the relationship between China's economic growth and global oil market fluctuations between 1992Q1 and 2015Q3. We find that: (1) the time varying parameter VAR with stochastic volatility provides a better fit as compared to it's constant counterparts; (2) the impacts of intertemporal global oil price shocks on China's output are often small and temporary in nature; (3) oil supply and specific oil demand shocks generally produce negative movements in China's GDP growth whilst oil demand shocks tend to have positive effects; (4) domestic output shocks have no significant impact on price or quantity movements within the global oil market. The results are generally robust to three commonly employed indicators of global economic activity: Kilian's global real economic activity index, the metal price index and the global industrial production index, and two alternative oil price metrics: the US refiners' acquisition cost for imported crude oil and the West Texas Intermediate price of crude oil. - Highlights: • A class of time-varying BVARs is used to examine the relationship between China's economic growth and global oil market fluctuations. • The impacts of intertemporal global oil price shocks on China's output are often small and temporary in nature. • Oil supply and specific oil demand shocks generally produce negative movements in China's GDP growth while oil demand shocks tend to have positive effects. • Domestic output shocks have no significant impact on price or quantity movements within the global oil market.

Research on the FDTD method of scattering effects of obliquely incident electromagnetic waves in time-varying plasma sheath on collision and plasma frequencies

Science.gov (United States)

Chen, Wei; Guo, Li-xin; Li, Jiang-ting

2017-04-01

This study analyzes the scattering characteristics of obliquely incident electromagnetic (EM) waves in a time-varying plasma sheath. The finite-difference time-domain algorithm is applied. According to the empirical formula of the collision frequency in a plasma sheath, the plasma frequency, temperature, and pressure are assumed to vary with time in the form of exponential rise. Some scattering problems of EM waves are discussed by calculating the radar cross section (RCS) of the time-varying plasma. The laws of the RCS varying with time are summarized at the L and S wave bands.

On exponential stability of bidirectional associative memory neural networks with time-varying delays

International Nuclear Information System (INIS)

Park, Ju H.; Lee, S.M.; Kwon, O.M.

2009-01-01

For bidirectional associate memory neural networks with time-varying delays, the problems of determining the exponential stability and estimating the exponential convergence rate are investigated by employing the Lyapunov functional method and linear matrix inequality (LMI) technique. A novel criterion for the stability, which give information on the delay-dependent property, is derived. A numerical example is given to demonstrate the effectiveness of the obtained results.

Modal Analysis in Periodic, Time-Varying Systems with emphasis to the Coupling between Flexible Rotating Beams and Non-Rotating Flexible Structures

DEFF Research Database (Denmark)

Saracho, C. M.; Santos, Ilmar

2003-01-01

The analysis of dynamical response of a system built by a non-rotating structure coupled to flexible rotating beams is the purpose of this work. The effect of rotational speed upon the beam natural frequencies is well-known, so that an increase in the angular speeds leads to an increase in beam...... natural frequencies, the so-called centrifugal stiffening. The equations of motion of such a global system present matrices with time-depending coefficients, which vary periodically with the angular rotor speed, and introduce parametric vibrations into the system response. The principles of modal analysis...... for time-invariant linear systems are expanded to investigate time-varying systems. Concepts as eigenvalues and eigenvectors, which in this special case are also time-varying, are used to analyse the dynamical response of global system. The time-varying frequencies and modes are also illustrated....

Geographic prediction of tuberculosis clusters in Fukuoka, Japan, using the space-time scan statistic

Energy Technology Data Exchange (ETDEWEB)

Daisuke Onozuka; Akihito Hagihara [Fukuoka Institute of Health and Environmental Sciences, Fukuoka (Japan). Department of Information Science

2007-07-01

Tuberculosis (TB) has reemerged as a global public health epidemic in recent years. Although evaluating local disease clusters leads to effective prevention and control of TB, there are few, if any, spatiotemporal comparisons for epidemic diseases. TB cases among residents in Fukuoka Prefecture between 1999 and 2004 (n = 9,119) were geocoded at the census tract level (n = 109) based on residence at the time of diagnosis. The spatial and space-time scan statistics were then used to identify clusters of census tracts with elevated proportions of TB cases. In the purely spatial analyses, the most likely clusters were in the Chikuho coal mining area (in 1999, 2002, 2003, 2004), the Kita-Kyushu industrial area (in 2000), and the Fukuoka urban area (in 2001). In the space-time analysis, the most likely cluster was the Kita-Kyushu industrial area (in 2000). The north part of Fukuoka Prefecture was the most likely to have a cluster with a significantly high occurrence of TB. The spatial and space-time scan statistics are effective ways of describing circular disease clusters. Since, in reality, infectious diseases might form other cluster types, the effectiveness of the method may be limited under actual practice. The sophistication of the analytical methodology, however, is a topic for future study. 48 refs., 3 figs., 3 tabs.

Geographic prediction of tuberculosis clusters in Fukuoka, Japan, using the space-time scan statistic

Directory of Open Access Journals (Sweden)

Onozuka Daisuke

2007-04-01

Full Text Available Abstract Background Tuberculosis (TB has reemerged as a global public health epidemic in recent years. Although evaluating local disease clusters leads to effective prevention and control of TB, there are few, if any, spatiotemporal comparisons for epidemic diseases. Methods TB cases among residents in Fukuoka Prefecture between 1999 and 2004 (n = 9,119 were geocoded at the census tract level (n = 109 based on residence at the time of diagnosis. The spatial and space-time scan statistics were then used to identify clusters of census tracts with elevated proportions of TB cases. Results In the purely spatial analyses, the most likely clusters were in the Chikuho coal mining area (in 1999, 2002, 2003, 2004, the Kita-Kyushu industrial area (in 2000, and the Fukuoka urban area (in 2001. In the space-time analysis, the most likely cluster was the Kita-Kyushu industrial area (in 2000. The north part of Fukuoka Prefecture was the most likely to have a cluster with a significantly high occurrence of TB. Conclusion The spatial and space-time scan statistics are effective ways of describing circular disease clusters. Since, in reality, infectious diseases might form other cluster types, the effectiveness of the method may be limited under actual practice. The sophistication of the analytical methodology, however, is a topic for future study.

Global exponential stability of BAM neural networks with time-varying delays and diffusion terms

International Nuclear Information System (INIS)

Wan Li; Zhou Qinghua

2007-01-01

The stability property of bidirectional associate memory (BAM) neural networks with time-varying delays and diffusion terms are considered. By using the method of variation parameter and inequality technique, the delay-independent sufficient conditions to guarantee the uniqueness and global exponential stability of the equilibrium solution of such networks are established

Global exponential stability of BAM neural networks with time-varying delays and diffusion terms

Science.gov (United States)

Wan, Li; Zhou, Qinghua

2007-11-01

The stability property of bidirectional associate memory (BAM) neural networks with time-varying delays and diffusion terms are considered. By using the method of variation parameter and inequality technique, the delay-independent sufficient conditions to guarantee the uniqueness and global exponential stability of the equilibrium solution of such networks are established.

A compensation controller based on a regional pole-assignment method for AMD control systems with a time-varying delay

Science.gov (United States)

Li, Zuohua; Chen, Chaojun; Teng, Jun; Wang, Ying

2018-04-01

Active mass damper/driver (AMD) control system has been proposed as an effective tool for high-rise buildings to resist strong dynamic loads. However, such disadvantage as time-varying delay in AMD control systems impedes their application in practices. Time-varying delay, which has an effect on the performance and stability of single-degree-of-freedom (SDOF) and multi-degree-of-freedom (MDOF) systems, is considered in the paper. In addition, a new time-delay compensation controller based on regional pole-assignment method is presented. To verify its effectiveness, the proposed method is applied to a numerical example of a ten-storey frame and an experiment of a single span four-storey steel frame. Both numerical and experimental results demonstrate that the proposed method can enhance the performances of an AMD control system with time-varying delays.

Study on time-varying velocity measurement with self-mixing laser diode based on Discrete Chirp-Fourier Transform

International Nuclear Information System (INIS)

Zhang Zhaoyun; Gao Yang; Zhao Xinghai; Zhao Xiang

2011-01-01

Laser's optical output power and frequency are modulated when the optical beam is back-scattered into the active cavity of the laser. By signal processing, the Doppler frequency can be acquired, and the target's velocity can be calculated. Based on these properties, an interferometry velocity sensor can be designed. When target move in time-varying velocity mode, it is difficult to extract the target's velocity. Time-varying velocity measurement by self-mixing laser diode is explored. A mathematics model was proposed for the time-varying velocity (invariable acceleration) measurement by self-mixing laser diode. Based on this model, a Discrete Chirp-Fourier Transform (DCFT) method was applied, DCFT is analogous to DFT. We show that when the signal length N is prime, the magnitudes of all the side lobes are 1, whereas the magnitudes of the main lobe is √N, And the coordinates of the main lobe shows the target's velocity and acceleration information. The simulation results prove the validity of the algorithm even in the situation of low SNR when N is prime.

Bit-level plane image encryption based on coupled map lattice with time-varying delay

Science.gov (United States)

Lv, Xiupin; Liao, Xiaofeng; Yang, Bo

2018-04-01

Most of the existing image encryption algorithms had two basic properties: confusion and diffusion in a pixel-level plane based on various chaotic systems. Actually, permutation in a pixel-level plane could not change the statistical characteristics of an image, and many of the existing color image encryption schemes utilized the same method to encrypt R, G and B components, which means that the three color components of a color image are processed three times independently. Additionally, dynamical performance of a single chaotic system degrades greatly with finite precisions in computer simulations. In this paper, a novel coupled map lattice with time-varying delay therefore is applied in color images bit-level plane encryption to solve the above issues. Spatiotemporal chaotic system with both much longer period in digitalization and much excellent performances in cryptography is recommended. Time-varying delay embedded in coupled map lattice enhances dynamical behaviors of the system. Bit-level plane image encryption algorithm has greatly reduced the statistical characteristics of an image through the scrambling processing. The R, G and B components cross and mix with one another, which reduces the correlation among the three components. Finally, simulations are carried out and all the experimental results illustrate that the proposed image encryption algorithm is highly secure, and at the same time, also demonstrates superior performance.

Investigation of optimal scanning protocol for X-ray computed tomography polymer gel dosimetry

Energy Technology Data Exchange (ETDEWEB)

Sellakumar, P. [Bangalore Institute of Oncology, 44-45/2, II Cross, RRMR Extension, Bangalore 560 027 (India)], E-mail: psellakumar@rediffmail.com; James Jebaseelan Samuel, E. [School of Science and Humanities, VIT University, Vellore 632 014 (India); Supe, Sanjay S. [Department of Radiation Physics, Kidwai Memorial Institute of Oncology, Hosur Road, Bangalore 560 027 (India)

2007-11-15

X-ray computed tomography is one of the potential tool used to evaluate the polymer gel dosimeters in three dimensions. The purpose of this study is to investigate the factors which affect the image noise for X-ray CT polymer gel dosimetry. A cylindrical water filled phantom was imaged with single slice Siemens Somatom Emotion CT scanner. The imaging parameters like tube voltage, tube current, slice scan time, slice thickness and reconstruction algorithm were varied independently to study the dependence of noise on each other. Reductions of noise with number of images to be averaged and spatial uniformity of the image were also investigated. Normoxic polymer gel PAGAT was manufactured and irradiated using Siemens Primus linear accelerator. The radiation induced change in CT number was evaluated using X-ray CT scanner. From this study it is clear that image noise is reduced with increase in tube voltage, tube current, slice scan time, slice thickness and also reduced with increasing the number of images averaged. However to reduce the tube load and total scan time, it was concluded that tube voltage of 130 kV, tube current of 200 mA, scan time of 1.5 s, slice thickness of 3 mm for high dose gradient and 5 mm for low dose gradient were optimal scanning protocols for this scanner. Optimum number of images to be averaged was concluded to be 25 for X-ray CT polymer gel dosimetry. Choice of reconstruction algorithm was also critical. From the study it is also clear that CT number increase with imaging tube voltage and shows the energy dependency of polymer gel dosimeter. Hence for evaluation of polymer gel dosimeters with X-ray CT scanner needs the optimization of scanning protocols to reduce the image noise.

Pinning synchronization of memristor-based neural networks with time-varying delays.

Science.gov (United States)

Yang, Zhanyu; Luo, Biao; Liu, Derong; Li, Yueheng

2017-09-01

In this paper, the synchronization of memristor-based neural networks with time-varying delays via pinning control is investigated. A novel pinning method is introduced to synchronize two memristor-based neural networks which denote drive system and response system, respectively. The dynamics are studied by theories of differential inclusions and nonsmooth analysis. In addition, some sufficient conditions are derived to guarantee asymptotic synchronization and exponential synchronization of memristor-based neural networks via the presented pinning control. Furthermore, some improvements about the proposed control method are also discussed in this paper. Finally, the effectiveness of the obtained results is demonstrated by numerical simulations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Time-varying multiplex network: Intralayer and interlayer synchronization

Science.gov (United States)

Rakshit, Sarbendu; Majhi, Soumen; Bera, Bidesh K.; Sinha, Sudeshna; Ghosh, Dibakar

2017-12-01

A large class of engineered and natural systems, ranging from transportation networks to neuronal networks, are best represented by multiplex network architectures, namely a network composed of two or more different layers where the mutual interaction in each layer may differ from other layers. Here we consider a multiplex network where the intralayer coupling interactions are switched stochastically with a characteristic frequency. We explore the intralayer and interlayer synchronization of such a time-varying multiplex network. We find that the analytically derived necessary condition for intralayer and interlayer synchronization, obtained by the master stability function approach, is in excellent agreement with our numerical results. Interestingly, we clearly find that the higher frequency of switching links in the layers enhances both intralayer and interlayer synchrony, yielding larger windows of synchronization. Further, we quantify the resilience of synchronous states against random perturbations, using a global stability measure based on the concept of basin stability, and this reveals that intralayer coupling strength is most crucial for determining both intralayer and interlayer synchrony. Lastly, we investigate the robustness of interlayer synchronization against a progressive demultiplexing of the multiplex structure, and we find that for rapid switching of intralayer links, the interlayer synchronization persists even when a large number of interlayer nodes are disconnected.

Time-varying bispectral analysis of visually evoked multi-channel EEG

Science.gov (United States)

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.

Multiple types of synchronization analysis for discontinuous Cohen-Grossberg neural networks with time-varying delays.

Science.gov (United States)

Li, Jiarong; Jiang, Haijun; Hu, Cheng; Yu, Zhiyong

2018-03-01

This paper is devoted to the exponential synchronization, finite time synchronization, and fixed-time synchronization of Cohen-Grossberg neural networks (CGNNs) with discontinuous activations and time-varying delays. Discontinuous feedback controller and Novel adaptive feedback controller are designed to realize global exponential synchronization, finite time synchronization and fixed-time synchronization by adjusting the values of the parameters ω in the controller. Furthermore, the settling time of the fixed-time synchronization derived in this paper is less conservative and more accurate. Finally, some numerical examples are provided to show the effectiveness and flexibility of the results derived in this paper. Copyright © 2018 Elsevier Ltd. All rights reserved.

A receding horizon scheme for discrete-time polytopic linear parameter varying systems in networked architectures

International Nuclear Information System (INIS)

Franzè, Giuseppe; Lucia, Walter; Tedesco, Francesco

2014-01-01

This paper proposes a Model Predictive Control (MPC) strategy to address regulation problems for constrained polytopic Linear Parameter Varying (LPV) systems subject to input and state constraints in which both plant measurements and command signals in the loop are sent through communication channels subject to time-varying delays (Networked Control System (NCS)). The results here proposed represent a significant extension to the LPV framework of a recent Receding Horizon Control (RHC) scheme developed for the so-called robust case. By exploiting the parameter availability, the pre-computed sequences of one- step controllable sets inner approximations are less conservative than the robust counterpart. The resulting framework guarantees asymptotic stability and constraints fulfilment regardless of plant uncertainties and time-delay occurrences. Finally, experimental results on a laboratory two-tank test-bed show the effectiveness of the proposed approach

Registration accuracy and image quality of time averaged mid-position CT scans for liver SBRT

NARCIS (Netherlands)

Kruis, Matthijs F.; van de Kamer, Jeroen B.; Sonke, Jan-Jakob; Jansen, Edwin P. M.; van Herk, Marcel

2013-01-01

The purpose was to validate the accuracy of motion models derived from deformable registration from four-dimensional computed tomography (4DCT) and breath-hold contrast enhanced computed tomography (BHCCT) scans for liver SBRT. Additionally, the image quality of the time averaged mid-position (MidP)

Time-varying volatility in Malaysian stock exchange: An empirical study using multiple-volatility-shift fractionally integrated model

Science.gov (United States)

Cheong, Chin Wen

2008-02-01

This article investigated the influences of structural breaks on the fractionally integrated time-varying volatility model in the Malaysian stock markets which included the Kuala Lumpur composite index and four major sectoral indices. A fractionally integrated time-varying volatility model combined with sudden changes is developed to study the possibility of structural change in the empirical data sets. Our empirical results showed substantial reduction in fractional differencing parameters after the inclusion of structural change during the Asian financial and currency crises. Moreover, the fractionally integrated model with sudden change in volatility performed better in the estimation and specification evaluations.

Global exponential stability of reaction-diffusion recurrent neural networks with time-varying delays

International Nuclear Information System (INIS)

Liang Jinling; Cao Jinde

2003-01-01

Employing general Halanay inequality, we analyze the global exponential stability of a class of reaction-diffusion recurrent neural networks with time-varying delays. Several new sufficient conditions are obtained to ensure existence, uniqueness and global exponential stability of the equilibrium point of delayed reaction-diffusion recurrent neural networks. The results extend and improve the earlier publications. In addition, an example is given to show the effectiveness of the obtained result

Improving Delay-Range-Dependent Stability Condition for Systems with Interval Time-Varying Delay

Directory of Open Access Journals (Sweden)

Wei Qian

2013-01-01

Full Text Available This paper discusses the delay-range-dependent stability for systems with interval time-varying delay. Through defining the new Lyapunov-Krasovskii functional and estimating the derivative of the LKF by introducing new vectors, using free matrices and reciprocally convex approach, the new delay-range-dependent stability conditions are obtained. Two well-known examples are given to illustrate the less conservatism of the proposed theoretical results.

Passivity of memristive BAM neural networks with leakage and additive time-varying delays

Science.gov (United States)

Wang, Weiping; Wang, Meiqi; Luo, Xiong; Li, Lixiang; Zhao, Wenbing; Liu, Linlin; Ping, Yuan

2018-02-01

This paper investigates the passivity of memristive bidirectional associate memory neural networks (MBAMNNs) with leakage and additive time-varying delays. Based on some useful inequalities and appropriate Lyapunov-Krasovskii functionals (LKFs), several delay-dependent conditions for passivity performance are obtained in linear matrix inequalities (LMIs). Moreover, the leakage delays as well as additive delays are considered separately. Finally, numerical simulations are provided to demonstrate the feasibility of the theoretical results.

On the time-averaging of ultrafine particle number size spectra in vehicular plumes

Directory of Open Access Journals (Sweden)

X. H. Yao

2006-01-01

Full Text Available Ultrafine vehicular particle (<100 nm number size distributions presented in the literature are mostly averages of long scan-time (~30 s or more spectra mainly due to the non-availability of commercial instruments that can measure particle distributions in the <10 nm to 100 nm range faster than 30 s even though individual researchers have built faster (1–2.5 s scanning instruments. With the introduction of the Engine Exhaust Particle Sizer (EEPS in 2004, high time-resolution (1 full 32-channel spectrum per second particle size distribution data become possible and allow atmospheric researchers to study the characteristics of ultrafine vehicular particles in rapidly and perhaps randomly varying high concentration environments such as roadside, on-road and tunnel. In this study, particle size distributions in these environments were found to vary as rapidly as one second frequently. This poses the question on the generality of using averages of long scan-time spectra for dynamic and/or mechanistic studies in rapidly and perhaps randomly varying high concentration environments. One-second EEPS data taken at roadside, on roads and in tunnels by a mobile platform are time-averaged to yield 5, 10, 30 and 120 s distributions to answer this question.

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

Directory of Open Access Journals (Sweden)

Emma Delgado

2016-04-01

Full Text Available We describe the application of a generic stability framework for a teleoperation system under time-varying delay conditions, as addressed in a previous work, to a scaled-four-channel (γ-4C control scheme. Described is how varying delays are dealt with by means of dynamic encapsulation, giving rise to mu-test conditions for robust stability and offering an appealing frequency technique to deal with the stability robustness of the architecture. We discuss ideal transparency problems and we adapt classical solutions so that controllers are proper, without single or double differentiators, and thus avoid the negative effects of noise. The control scheme was fine-tuned and tested for complete stability to zero of the whole state, while seeking a practical solution to the trade-off between stability and transparency in the Internet-based teleoperation. These ideas were tested on an Internet-based application with two Omni devices at remote laboratory locations via simulations and real remote experiments that achieved robust stability, while performing well in terms of position synchronization and force transparency.

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

Science.gov (United States)

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

2016-04-26

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.

Transport methods: general. 2. Monte Carlo Particle Transport in Media with Exponentially Varying Time-Dependent Cross Sections

International Nuclear Information System (INIS)

Brown, Forrest B.; Martin, William R.

2001-01-01

We have investigated Monte Carlo schemes for analyzing particle transport through media with exponentially varying time-dependent cross sections. For such media, the cross sections are represented in the form Σ(t) = Σ 0 e -at (1) or equivalently as Σ(x) = Σ 0 e -bx (2) where b = av and v is the particle speed. For the following discussion, the parameters a and b may be either positive, for exponentially decreasing cross sections, or negative, for exponentially increasing cross sections. For most time-dependent Monte Carlo applications, the time and spatial variations of the cross-section data are handled by means of a stepwise procedure, holding the cross sections constant for each region over a small time interval Δt, performing the Monte Carlo random walk over the interval Δt, updating the cross sections, and then repeating for a series of time intervals. Continuously varying spatial- or time-dependent cross sections can be treated in a rigorous Monte Carlo fashion using delta-tracking, but inefficiencies may arise if the range of cross-section variation is large. In this paper, we present a new method for sampling collision distances directly for cross sections that vary exponentially in space or time. The method is exact and efficient and has direct application to Monte Carlo radiation transport methods. To verify that the probability density function (PDF) is correct and that the random-sampling procedure yields correct results, numerical experiments were performed using a one-dimensional Monte Carlo code. The physical problem consisted of a beam source impinging on a purely absorbing infinite slab, with a slab thickness of 1 cm and Σ 0 = 1 cm -1 . Monte Carlo calculations with 10 000 particles were run for a range of the exponential parameter b from -5 to +20 cm -1 . Two separate Monte Carlo calculations were run for each choice of b, a continuously varying case using the random-sampling procedures described earlier, and a 'conventional' case where the

Online Estimation of Time-Varying Volatility Using a Continuous-Discrete LMS Algorithm

Directory of Open Access Journals (Sweden)

Jacques Oksman

2008-09-01

Full Text Available The following paper addresses a problem of inference in financial engineering, namely, online time-varying volatility estimation. The proposed method is based on an adaptive predictor for the stock price, built from an implicit integration formula. An estimate for the current volatility value which minimizes the mean square prediction error is calculated recursively using an LMS algorithm. The method is then validated on several synthetic examples as well as on real data. Throughout the illustration, the proposed method is compared with both UKF and offline volatility estimation.

New Results on Passivity Analysis of Stochastic Neural Networks with Time-Varying Delay and Leakage Delay

Directory of Open Access Journals (Sweden)

YaJun Li

2015-01-01

Full Text Available The passivity problem for a class of stochastic neural networks systems (SNNs with varying delay and leakage delay has been further studied in this paper. By constructing a more effective Lyapunov functional, employing the free-weighting matrix approach, and combining with integral inequality technic and stochastic analysis theory, the delay-dependent conditions have been proposed such that SNNs are asymptotically stable with guaranteed performance. The time-varying delay is divided into several subintervals and two adjustable parameters are introduced; more information about time delay is utilised and less conservative results have been obtained. Examples are provided to illustrate the less conservatism of the proposed method and simulations are given to show the impact of leakage delay on stability of SNNs.

Tracking time-varying parameters with local regression

DEFF Research Database (Denmark)

Joensen, Alfred Karsten; Nielsen, Henrik Aalborg; Nielsen, Torben Skov

2000-01-01

This paper shows that the recursive least-squares (RLS) algorithm with forgetting factor is a special case of a varying-coe\\$cient model, and a model which can easily be estimated via simple local regression. This observation allows us to formulate a new method which retains the RLS algorithm, bu......, but extends the algorithm by including polynomial approximations. Simulation results are provided, which indicates that this new method is superior to the classical RLS method, if the parameter variations are smooth....

Time Distribution Using SpaceWire in the SCaN Testbed on ISS

Science.gov (United States)

Lux, James P.

2012-01-01

A paper describes an approach for timekeeping and time transfer among the devices on the CoNNeCT project s SCaN Testbed. It also describes how the clocks may be synchronized with an external time reference; e.g., time tags from the International Space Station (ISS) or RF signals received by a radio (TDRSS time service or GPS). All the units have some sort of counter that is fed by an oscillator at some convenient frequency. The basic problem in timekeeping is relating the counter value to some external time standard such as UTC. With SpaceWire, there are two approaches possible: one is to just use SpaceWire to send a message, and use an external wire for the sync signal. This is much the same as with the RS- 232 messages and l pps line from a GPS receiver. However, SpaceWire has an additional capability that was added to make it easier - it can insert and receive a special "timecode" word in the data stream.

Alleviating Border Effects in Wavelet Transforms for Nonlinear Time-varying Signal Analysis

Directory of Open Access Journals (Sweden)

SU, H.

2011-08-01

Full Text Available Border effects are very common in many finite signals analysis and processing approaches using convolution operation. Alleviating the border effects that can occur in the processing of finite-length signals using wavelet transform is considered in this paper. Traditional methods for alleviating the border effects are suitable to compression or coding applications. We propose an algorithm based on Fourier series which is proved to be appropriate to the application of time-frequency analysis of nonlinear signals. Fourier series extension method preserves the time-varying characteristics of the signals. A modified signal duration expression for measuring the extent of border effects region is presented. The proposed algorithm is confirmed to be efficient to alleviate the border effects in comparison to the current methods through the numerical examples.

Evaluation of optimized magnetic resonance perfusion imaging scanning time window after contrast agent injection for differentiating benign and malignant breast lesions.

Science.gov (United States)

Dong, Jie; Wang, Dawei; Ma, Zhenshen; Deng, Guodong; Wang, Lanhua; Zhang, Jiandong

2017-03-01

The aim of the study was evaluate the 3.0 T magnetic resonance (MR) perfusion imaging scanning time window following contrast injection for differentiating benign and malignant breast lesions and to determine the optimum scanning time window for increased scanner usage efficiency and reduced diagnostic adverse risk factors. A total of 52 women with breast abnormalities were selected for conventional MR imaging and T1 dynamic-enhanced imaging. Quantitative parameters [volume transfer constant (K trans ), rate constant (K ep ) and extravascular extracellular volume fraction (V e )] were calculated at phases 10, 20, 30, 40 and 50, which represented time windows at 5, 10, 15, 20 and 25 min, respectively, following injection of contrast agent. The association of the parameters at different phases with benign and malignant tumor diagnosis was analyzed. MR perfusion imaging was verified as an effective modality in the diagnosis of breast malignancies and the best scanning time window was identified: i) Values of K trans and K ep at all phases were statistically significant in differentiating benign and malignant tumors (P0.05); ii) values of V e in benign tumors increased with phase number, but achieved no obvious changes at different phases in malignant tumors; iii) the optimum scanning time window of breast perfusion imaging with 3.0 T MR was between phases 10 and 30 (i.e., between 5 and 15 min after contrast agent injection). The variation trend of V e values at different phases may serve as a diagnostic reference for differentiating benign and malignant breast abnormalities. The most efficient scanning time window was indicated to be 5 min after contrast injection, based on the observation that the V e value only had statistical significance in diagnosis at stage 10. However, the optimal scanning time window is from 5 to 15 min following the injection of contrast agent, since that the variation trend of V e is able to serve as a diagnostic reference.

Identification and Sensitivity Analysis for Average Causal Mediation Effects with Time-Varying Treatments and Mediators: Investigating the Underlying Mechanisms of Kindergarten Retention Policy.

Science.gov (United States)

Park, Soojin; Steiner, Peter M; Kaplan, David

2018-06-01

Considering that causal mechanisms unfold over time, it is important to investigate the mechanisms over time, taking into account the time-varying features of treatments and mediators. However, identification of the average causal mediation effect in the presence of time-varying treatments and mediators is often complicated by time-varying confounding. This article aims to provide a novel approach to uncovering causal mechanisms in time-varying treatments and mediators in the presence of time-varying confounding. We provide different strategies for identification and sensitivity analysis under homogeneous and heterogeneous effects. Homogeneous effects are those in which each individual experiences the same effect, and heterogeneous effects are those in which the effects vary over individuals. Most importantly, we provide an alternative definition of average causal mediation effects that evaluates a partial mediation effect; the effect that is mediated by paths other than through an intermediate confounding variable. We argue that this alternative definition allows us to better assess at least a part of the mediated effect and provides meaningful and unique interpretations. A case study using ECLS-K data that evaluates kindergarten retention policy is offered to illustrate our proposed approach.

Time-varying surrogate data to assess nonlinearity in nonstationary time series: application to heart rate variability.

Science.gov (United States)

Faes, Luca; Zhao, He; Chon, Ki H; Nollo, Giandomenico

2009-03-01

We propose a method to extend to time-varying (TV) systems the procedure for generating typical surrogate time series, in order to test the presence of nonlinear dynamics in potentially nonstationary signals. The method is based on fitting a TV autoregressive (AR) model to the original series and then regressing the model coefficients with random replacements of the model residuals to generate TV AR surrogate series. The proposed surrogate series were used in combination with a TV sample entropy (SE) discriminating statistic to assess nonlinearity in both simulated and experimental time series, in comparison with traditional time-invariant (TIV) surrogates combined with the TIV SE discriminating statistic. Analysis of simulated time series showed that using TIV surrogates, linear nonstationary time series may be erroneously regarded as nonlinear and weak TV nonlinearities may remain unrevealed, while the use of TV AR surrogates markedly increases the probability of a correct interpretation. Application to short (500 beats) heart rate variability (HRV) time series recorded at rest (R), after head-up tilt (T), and during paced breathing (PB) showed: 1) modifications of the SE statistic that were well interpretable with the known cardiovascular physiology; 2) significant contribution of nonlinear dynamics to HRV in all conditions, with significant increase during PB at 0.2 Hz respiration rate; and 3) a disagreement between TV AR surrogates and TIV surrogates in about a quarter of the series, suggesting that nonstationarity may affect HRV recordings and bias the outcome of the traditional surrogate-based nonlinearity test.

Delay-Dependent Asymptotic Stability of Cohen-Grossberg Models with Multiple Time-Varying Delays

Directory of Open Access Journals (Sweden)

Xiaofeng Liao

2007-01-01

Full Text Available Dynamical behavior of a class of Cohen-Grossberg models with multiple time-varying delays is studied in detail. Sufficient delay-dependent criteria to ensure local and global asymptotic stabilities of the equilibrium of this network are derived by constructing suitable Lyapunov functionals. The obtained conditions are shown to be less conservative and restrictive than those reported in the known literature. Some numerical examples are included to demonstrate our results.

Some new results for recurrent neural networks with varying-time coefficients and delays

International Nuclear Information System (INIS)

Jiang Haijun; Teng Zhidong

2005-01-01

In this Letter, we consider the recurrent neural networks with varying-time coefficients and delays. By constructing new Lyapunov functional, introducing ingeniously many real parameters and applying the technique of Young inequality, we establish a series of criteria on the boundedness, global exponential stability and the existence of periodic solutions. In these criteria, we do not require that the response functions are differentiable, bounded and monotone nondecreasing. Some previous works are improved and extended

Fault Detection for Non-Gaussian Stochastic Systems with Time-Varying Delay

Directory of Open Access Journals (Sweden)

Tao Li

2013-01-01

Full Text Available Fault detection (FD for non-Gaussian stochastic systems with time-varying delay is studied. The available information for the addressed problem is the input and the measured output probability density functions (PDFs of the system. In this framework, firstly, by constructing an augmented Lyapunov functional, which involves some slack variables and a tuning parameter, a delay-dependent condition for the existence of FD observer is derived in terms of linear matrix inequality (LMI and the fault can be detected through a threshold. Secondly, in order to improve the detection sensitivity performance, the optimal algorithm is applied to minimize the threshold value. Finally, paper-making process example is given to demonstrate the applicability of the proposed approach.

Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets

International Nuclear Information System (INIS)

Lu, Fengbin; Qiao, Han; Wang, Shouyang; Lai, Kin Keung; Li, Yuze

2017-01-01

This paper proposes a new time-varying coefficient vector autoregressions (VAR) model, in which the coefficient is a linear function of dynamic lagged correlation. The proposed model allows for flexibility in choices of dynamic correlation models (e.g. dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (GARCH) models, Markov-switching GARCH models and multivariate stochastic volatility models), which indicates that it can describe many types of time-varying causal effects. Time-varying causal relations between West Texas Intermediate (WTI) crude oil and the US Standard and Poor’s 500 (S&P 500) stock markets are examined by the proposed model. The empirical results show that their causal relations evolve with time and display complex characters. Both positive and negative causal effects of the WTI on the S&P 500 in the subperiods have been found and confirmed by the traditional VAR models. Similar results have been obtained in the causal effects of S&P 500 on WTI. In addition, the proposed model outperforms the traditional VAR model.

Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets

Energy Technology Data Exchange (ETDEWEB)

Lu, Fengbin, E-mail: fblu@amss.ac.cn [Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190 (China); Qiao, Han, E-mail: qiaohan@ucas.ac.cn [School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190 (China); Wang, Shouyang, E-mail: sywang@amss.ac.cn [School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190 (China); Lai, Kin Keung, E-mail: mskklai@cityu.edu.hk [Department of Management Sciences, City University of Hong Kong (Hong Kong); Li, Yuze, E-mail: richardyz.li@mail.utoronto.ca [Department of Industrial Engineering, University of Toronto (Canada)

2017-01-15

This paper proposes a new time-varying coefficient vector autoregressions (VAR) model, in which the coefficient is a linear function of dynamic lagged correlation. The proposed model allows for flexibility in choices of dynamic correlation models (e.g. dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (GARCH) models, Markov-switching GARCH models and multivariate stochastic volatility models), which indicates that it can describe many types of time-varying causal effects. Time-varying causal relations between West Texas Intermediate (WTI) crude oil and the US Standard and Poor’s 500 (S&P 500) stock markets are examined by the proposed model. The empirical results show that their causal relations evolve with time and display complex characters. Both positive and negative causal effects of the WTI on the S&P 500 in the subperiods have been found and confirmed by the traditional VAR models. Similar results have been obtained in the causal effects of S&P 500 on WTI. In addition, the proposed model outperforms the traditional VAR model.

Output-only modal parameter estimator of linear time-varying structural systems based on vector TAR model and least squares support vector machine

Science.gov (United States)

Zhou, Si-Da; Ma, Yuan-Chen; Liu, Li; Kang, Jie; Ma, Zhi-Sai; Yu, Lei

2018-01-01

Identification of time-varying modal parameters contributes to the structural health monitoring, fault detection, vibration control, etc. of the operational time-varying structural systems. However, it is a challenging task because there is not more information for the identification of the time-varying systems than that of the time-invariant systems. This paper presents a vector time-dependent autoregressive model and least squares support vector machine based modal parameter estimator for linear time-varying structural systems in case of output-only measurements. To reduce the computational cost, a Wendland's compactly supported radial basis function is used to achieve the sparsity of the Gram matrix. A Gamma-test-based non-parametric approach of selecting the regularization factor is adapted for the proposed estimator to replace the time-consuming n-fold cross validation. A series of numerical examples have illustrated the advantages of the proposed modal parameter estimator on the suppression of the overestimate and the short data. A laboratory experiment has further validated the proposed estimator.

Active control of time-varying broadband noise and vibrations using a sliding-window Kalman filter

NARCIS (Netherlands)

van Ophem, S.; Berkhoff, Arthur P.; Sas, P.; Moens, D.; Denayer, H.

2014-01-01

Recently, a multiple-input/multiple-output Kalman filter technique was presented to control time-varying broadband noise and vibrations. By describing the feed-forward broadband active noise control problem in terms of a state estimation problem it was possible to achieve a faster rate of

Compensation for the distortion in satellite laser range predictions due to varying pulse travel times

Science.gov (United States)

Paunonen, Matti

1993-01-01

A method for compensating for the effect of the varying travel time of a transmitted laser pulse to a satellite is described. The 'observed minus predicted' range differences then appear to be linear, which makes data screening or use in range gating more effective.

Quality Assurance By Laser Scanning And Imaging Techniques

Science.gov (United States)

SchmalfuB, Harald J.; Schinner, Karl Ludwig

1989-03-01

Laser scanning systems are well established in the world of fast industrial in-process quality inspection systems. The materials inspected by laser scanning systems are e.g. "endless" sheets of steel, paper, textile, film or foils. The web width varies from 50 mm up to 5000 mm or more. The web speed depends strongly on the production process and can reach several hundred meters per minute. The continuous data flow in one of different channels of the optical receiving system exceeds ten Megapixels/sec. Therefore it is clear that the electronic evaluation system has to process these data streams in real time and no image storage is possible. But sometimes (e.g. first installation of the system, change of the defect classification) it would be very helpful to have the possibility for a visual look on the original, i.e. not processed sensor data. At first we show the principle set up of a standard laser scanning system. Then we will introduce a large image memory especially designed for the needs of high-speed inspection sensors. This image memory co-operates with the standard on-line evaluation electronics and provides therefore an easy comparison between processed and non-processed data. We will discuss the basic system structure and we will show the first industrial results.

A new flexible monochromator setup for quick scanning x-ray absorption spectroscopy

Energy Technology Data Exchange (ETDEWEB)

Stoetzel, J.; Luetzenkirchen-Hecht, D.; Frahm, R. [Fachbereich C, Physik, Bergische Universitaet Wuppertal, Gaussstr. 20, 42097 Wuppertal (Germany)

2010-07-15

A new monochromator setup for quick scanning x-ray absorption spectroscopy in the subsecond time regime is presented. Novel driving mechanics allow changing the energy range of the acquired spectra by remote control during data acquisition for the first time, thus dramatically increasing the flexibility and convenience of this method. Completely new experiments are feasible due to the fact that time resolution, edge energy, and energy range of the acquired spectra can be changed continuously within seconds without breaking the vacuum of the monochromator vessel and even without interrupting the measurements. The advanced mechanics are explained in detail and the performance is characterized with x-ray absorption spectra of pure metal foils. The energy scale was determined by a fast and accurate angular encoder system measuring the Bragg angle of the monochromator crystal with subarcsecond resolution. The Bragg angle range covered by the oscillating crystal can currently be changed from 0 deg. to 3.0 deg. within 20 s, while the mechanics are capable to move with frequencies of up to ca. 35 Hz, leading to ca. 14 ms/spectrum time resolution. A new software package allows performing programmed scan sequences, which enable the user to measure stepwise with alternating parameters in predefined time segments. Thus, e.g., switching between edges scanned with the same energy range is possible within one in situ experiment, while also the time resolution can be varied simultaneously. This progress makes the new system extremely user friendly and efficient to use for time resolved x-ray absorption spectroscopy at synchrotron radiation beamlines.

Investigation of the influence of image reconstruction filter and scan parameters on operation of automatic tube current modulation systems for different CT scanners

International Nuclear Information System (INIS)

Sookpeng, Supawitoo; Martin, Colin J.; Gentle, David J.

2015-01-01

Variation in the user selected CT scanning parameters under automatic tube current modulation (ATCM) between hospitals has a substantial influence on the radiation doses and image quality for patients. The aim of this study was to investigate the effect of changing image reconstruction filter and scan parameter settings on tube current, dose and image quality for various CT scanners operating under ATCM. The scan parameters varied were pitch factor, rotation time, collimator configuration, kVp, image thickness and image filter convolution (FC) used for reconstruction. The Toshiba scanner varies the tube current to achieve a set target noise. Changes in the FC setting and image thickness for the first reconstruction were the major factors affecting patient dose. A two-step change in FC from smoother to sharper filters doubles the dose, but is counterbalanced by an improvement in spatial resolution. In contrast, Philips and Siemens scanners maintained tube current values similar to those for a reference image and patient, and the tube current only varied slightly for changes in individual CT scan parameters. The selection of a sharp filter increased the image noise, while use of iDose iterative reconstruction reduced the noise. Since the principles used by CT manufacturers for ATCM vary, it is important that parameters which affect patient dose and image quality for each scanner are made clear to operator to aid in optimisation. (authors)

Optimal routing of hazardous substances in time-varying, stochastic transportation networks

International Nuclear Information System (INIS)

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

Delay-Dependent Stability Criteria of Uncertain Periodic Switched Recurrent Neural Networks with Time-Varying Delays

Directory of Open Access Journals (Sweden)

Xing Yin

2011-01-01

uncertain periodic switched recurrent neural networks with time-varying delays. When uncertain discrete-time recurrent neural network is a periodic system, it is expressed as switched neural network for the finite switching state. Based on the switched quadratic Lyapunov functional approach (SQLF and free-weighting matrix approach (FWM, some linear matrix inequality criteria are found to guarantee the delay-dependent asymptotical stability of these systems. Two examples illustrate the exactness of the proposed criteria.

Errors in 'BED'-derived estimates of HIV incidence will vary by place, time and age.

Directory of Open Access Journals (Sweden)

Timothy B Hallett

2009-05-01

Full Text Available The BED Capture Enzyme Immunoassay, believed to distinguish recent HIV infections, is being used to estimate HIV incidence, although an important property of the test--how specificity changes with time since infection--has not been not measured.We construct hypothetical scenarios for the performance of BED test, consistent with current knowledge, and explore how this could influence errors in BED estimates of incidence using a mathematical model of six African countries. The model is also used to determine the conditions and the sample sizes required for the BED test to reliably detect trends in HIV incidence.If the chance of misclassification by BED increases with time since infection, the overall proportion of individuals misclassified could vary widely between countries, over time, and across age-groups, in a manner determined by the historic course of the epidemic and the age-pattern of incidence. Under some circumstances, changes in BED estimates over time can approximately track actual changes in incidence, but large sample sizes (50,000+ will be required for recorded changes to be statistically significant.The relationship between BED test specificity and time since infection has not been fully measured, but, if it decreases, errors in estimates of incidence could vary by place, time and age-group. This means that post-assay adjustment procedures using parameters from different populations or at different times may not be valid. Further research is urgently needed into the properties of the BED test, and the rate of misclassification in a wide range of populations.

SU-E-I-60: The Correct Selection of Pitch and Rotation Time for Optimal CT Scanning : The Big Misconception

International Nuclear Information System (INIS)

Ranallo, F; Szczykutowicz, T

2014-01-01

Purpose: To provide correct guidance in the proper selection of pitch and rotation time for optimal CT imaging with multi-slice scanners. Methods: There exists a widespread misconception concerning the role of pitch in patient dose with modern multi-slice scanners, particularly with the use of mA modulation techniques. We investigated the relationship of pitch and rotation time to image quality, dose, and scan duration, with CT scanners from different manufacturers in a way that clarifies this misconception. This source of this misconception may concern the role of pitch in single slice CT scanners. Results: We found that the image noise and dose are generally independent of the selected effective mAs (mA*time/ pitch) with manual mA technique settings and are generally independent of the selected pitch and /or rotation time with automatic mA modulation techniques. However we did find that on certain scanners the use of a pitch just above 0.5 provided images of equal image noise at a lower dose compared to the use of a pitch just below 1.0. Conclusion: The misconception that the use of a lower pitch over-irradiates patients by wasting dose is clearly false. The use of a lower pitch provides images of equal or better image quality at the same patient dose, whether using manual mA or automatic mA modulation techniques. By decreasing the pitch and the rotation times by equal amounts, both helical and patient motion artifacts can be reduced without affecting the exam time. The use of lower helical pitch also allows better scanning of larger patients by allowing a greater scan effective mAs, if the exam time can be extended. The one caution with the use of low pitch is not related to patient dose, but to the length of the scan time if the rotation time is not set short enough. Partial Research funding from GE HealthCare

Time-varying monetary-policy rules and financial stress: Does financial instability matter for monetary policy?

Czech Academy of Sciences Publication Activity Database

Baxa, Jaromír; Horváth, R.; Vašíček, B.

2013-01-01

Roč. 9, č. 1 (2013), s. 117-138 ISSN 1572-3089 Institutional support: RVO:67985556 Keywords : Financial stress * Time-varying parameter model * Endogenous regressors Subject RIV: AH - Economics Impact factor: 2.932, year: 2013 http://library.utia.cas.cz/separaty/2013/E/baxa-0395375.pdf

Adaptive fuzzy dynamic surface control of nonlinear systems with input saturation and time-varying output constraints

Science.gov (United States)

Edalati, L.; Khaki Sedigh, A.; Aliyari Shooredeli, M.; Moarefianpour, A.

2018-02-01

This paper deals with the design of adaptive fuzzy dynamic surface control for uncertain strict-feedback nonlinear systems with asymmetric time-varying output constraints in the presence of input saturation. To approximate the unknown nonlinear functions and overcome the problem of explosion of complexity, a Fuzzy logic system is combined with the dynamic surface control in the backstepping design technique. To ensure the output constraints satisfaction, an asymmetric time-varying Barrier Lyapunov Function (BLF) is used. Moreover, by applying the minimal learning parameter technique, the number of the online parameters update for each subsystem is reduced to 2. Hence, the semi-globally uniformly ultimately boundedness (SGUUB) of all the closed-loop signals with appropriate tracking error convergence is guaranteed. The effectiveness of the proposed control is demonstrated by two simulation examples.

Analysis of nonlinear systems with time varying inputs and its application to gain scheduling

Directory of Open Access Journals (Sweden)

J.-T. Lim

1996-01-01

Full Text Available An analytical framework for analysis of a class of nonlinear systems with time varying inputs is presented. It is shown that the trajectories of the transformed nonlinear systems are uniformly bounded with an ultimate bound under certain conditions shown in this paper. The result obtained is useful for applications, in particular, analysis and design of gain scheduling.

H∞ Control for a Networked Control Model of Systems with Two Additive Time-Varying Delays

Directory of Open Access Journals (Sweden)

Hanyong Shao

2014-01-01

Full Text Available This paper is concerned with H∞ control for a networked control model of systems with two additive time-varying delays. A new Lyapunov functional is constructed to make full use of the information of the delays, and for the derivative of the Lyapunov functional a novel technique is employed to compute a tighter upper bound, which is dependent on the two time-varying delays instead of the upper bounds of them. Then the convex polyhedron method is proposed to check the upper bound of the derivative of the Lyapunov functional. The resulting stability criteria have fewer matrix variables but less conservatism than some existing ones. The stability criteria are applied to designing a state feedback controller, which guarantees that the closed-loop system is asymptotically stable with a prescribed H∞ disturbance attenuation level. Finally examples are given to show the advantages of the stability criteria and the effectiveness of the proposed control method.

Linear Parameter Varying Versus Linear Time Invariant Reduced Order Controller Design of Turboprop Aircraft Dynamics

Directory of Open Access Journals (Sweden)

Widowati

2012-07-01

Full Text Available The applicability of parameter varying reduced order controllers to aircraft model is proposed. The generalization of the balanced singular perturbation method of linear time invariant (LTI system is used to reduce the order of linear parameter varying (LPV system. Based on the reduced order model the low-order LPV controller is designed by using synthesis technique. The performance of the reduced order controller is examined by applying it to lateral-directional control of aircraft model having 20th order. Furthermore, the time responses of the closed loop system with reduced order LPV controllers and reduced order LTI controller is compared. From the simulation results, the 8th order LPV controller can maintain stability and to provide the same level of closed-loop systems performance as the full-order LPV controller. It is different with the reduced-order LTI controller that cannot maintain stability and performance for all allowable parameter trajectories.

Periodic solution for state-dependent impulsive shunting inhibitory CNNs with time-varying delays.

Science.gov (United States)

Şaylı, Mustafa; Yılmaz, Enes

2015-08-01

In this paper, we consider existence and global exponential stability of periodic solution for state-dependent impulsive shunting inhibitory cellular neural networks with time-varying delays. By means of B-equivalence method, we reduce these state-dependent impulsive neural networks system to an equivalent fix time impulsive neural networks system. Further, by using Mawhin's continuation theorem of coincide degree theory and employing a suitable Lyapunov function some new sufficient conditions for existence and global exponential stability of periodic solution are obtained. Previous results are improved and extended. Finally, we give an illustrative example with numerical simulations to demonstrate the effectiveness of our theoretical results. Copyright © 2015 Elsevier Ltd. All rights reserved.

CT scans in young people in Northern England: trends and patterns 1993-2002

Energy Technology Data Exchange (ETDEWEB)

Pearce, Mark S.; Salotti, Jane A.; Metcalf, Wenhua [Newcastle University, Sir James Spence Institute, Royal Victoria Infirmary, Institute of Health and Society, Newcastle upon Tyne (United Kingdom); McHugh, Kieran [Great Ormond Street Hospital for Children NHS Trust, London (United Kingdom); Kim, Kwang P. [Kyung Hee University, Department of Nuclear Engineering, Gyeongi-Do (Korea, Republic of); Craft, Alan W. [Newcastle University, Northern Institute of Cancer Research, Sir James Spence Institute, Royal Victoria Infirmary, Newcastle upon Tyne (United Kingdom); Parker, Louise [Dalhousie University and Cancer Care Nova Scotia, Departments of Medicine and Paediatrics, Population Cancer Research Program, Halifax, NS (Canada); Ron, Elaine [National Cancer Institute, Radiation Epidemiology Branch, Division of Cancer Epidemiology and Genetics, Bethesda, MD (United States)

2011-07-15

Although CT can be greatly beneficial, its relatively high radiation doses have caused public health concerns. To assess patterns in CT usage among patients aged less than 22 years in Northern England during the period 1993-2002. Electronic data were obtained from radiology information systems of all nine National Health Service trusts in the region. A total of 38,681 scans had been performed in 20,483 patients aged less than 22 years. The number of CT examinations rose, with the steepest increase between 1997 and 2000. The number of patients scanned per year increased less dramatically, with 2.24/1,000 population aged less than 22 years having one scan or more in 1993 compared to 3.54/1,000 in 2002. This reflects an increase in the median number of scans per patient, which rose from 1 in 1993 to 2 by 1999. More than 70% of CT examinations were of the head, with the number of head examinations varying with time and patient age. The frequency of CT scans in this population more than doubled during the study period. This is partly, but not wholly, explained by an increase in the number of scans per patient. (orig.)

Time-Varying Transition Probability Matrix Estimation and Its Application to Brand Share Analysis.

Directory of Open Access Journals (Sweden)

Tomoaki Chiba

Full Text Available In a product market or stock market, different products or stocks compete for the same consumers or purchasers. We propose a method to estimate the time-varying transition matrix of the product share using a multivariate time series of the product share. The method is based on the assumption that each of the observed time series of shares is a stationary distribution of the underlying Markov processes characterized by transition probability matrices. We estimate transition probability matrices for every observation under natural assumptions. We demonstrate, on a real-world dataset of the share of automobiles, that the proposed method can find intrinsic transition of shares. The resulting transition matrices reveal interesting phenomena, for example, the change in flows between TOYOTA group and GM group for the fiscal year where TOYOTA group's sales beat GM's sales, which is a reasonable scenario.

Time-Varying Transition Probability Matrix Estimation and Its Application to Brand Share Analysis.

Science.gov (United States)

Chiba, Tomoaki; Hino, Hideitsu; Akaho, Shotaro; Murata, Noboru

2017-01-01

In a product market or stock market, different products or stocks compete for the same consumers or purchasers. We propose a method to estimate the time-varying transition matrix of the product share using a multivariate time series of the product share. The method is based on the assumption that each of the observed time series of shares is a stationary distribution of the underlying Markov processes characterized by transition probability matrices. We estimate transition probability matrices for every observation under natural assumptions. We demonstrate, on a real-world dataset of the share of automobiles, that the proposed method can find intrinsic transition of shares. The resulting transition matrices reveal interesting phenomena, for example, the change in flows between TOYOTA group and GM group for the fiscal year where TOYOTA group's sales beat GM's sales, which is a reasonable scenario.

Almost Periodic Solution for Memristive Neural Networks with Time-Varying Delays

Directory of Open Access Journals (Sweden)

Huaiqin Wu

2013-01-01

Full Text Available This paper is concerned with the dynamical stability analysis for almost periodic solution of memristive neural networks with time-varying delays. Under the framework of Filippov solutions, by applying the inequality analysis techniques, the existence and asymptotically almost periodic behavior of solutions are discussed. Based on the differential inclusions theory and Lyapunov functional approach, the stability issues of almost periodic solution are investigated, and a sufficient condition for the existence, uniqueness, and global exponential stability of the almost periodic solution is established. Moreover, as a special case, the condition which ensures the global exponential stability of a unique periodic solution is also presented for the considered memristive neural networks. Two examples are given to illustrate the validity of the theoretical results.

Single server queueing networks with varying service times and renewal input

Directory of Open Access Journals (Sweden)

Pierre Le Gall

2000-01-01

Full Text Available Using recent results in tandem queues and queueing networks with renewal input, when successive service times of the same customer are varying (and when the busy periods are frequently not broken up in large networks, the local queueing delay of a single server queueing network is evaluated utilizing new concepts of virtual and actual delays (respectively. It appears that because of an important property, due to the underlying tandem queue effect, the usual queueing standards (related to long queues cannot protect against significant overloads in the buffers due to some possible “agglutination phenomenon” (related to short queues. Usual network management methods and traffic simulation methods should be revised, and should monitor the partial traffic streams loads (and not only the server load.

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

Science.gov (United States)

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.

Time-Varying Hydraulic Gradient Model of Paste-Like Tailings in Long-Distance Pipeline Transportation

Directory of Open Access Journals (Sweden)

Li Yang

2017-01-01

Full Text Available Paste-like tailings slurry (PTLS is always simplified as a Bingham plastic fluid, leading to excessive computational errors in the calculation of the hydraulic gradient. In the case of paste-like tailings in long-distance pipeline transportation, to explore a high-precision and reliable hydraulic gradient formula, the rheological behavior of paste-like tailings slurry was analyzed, a time-varying hydraulic gradient model was constructed, and a series of laboratory shear tests were conducted. The results indicate that the PTLS shows noticeable shear-thinning characteristics in constant shear tests; the calculated hydraulic gradient declined by about 56%, from 4.44 MPa·km−1 to 1.95 MPa·km−1 within 253 s, and remained constant for the next four hours during the pipeline transportation. Comparing with the balance hydraulic gradient obtained in a semi-industrial loop test, the computational errors of those calculated by using the time-varying hydraulic gradient model, Jinchuan formula, and Shanxi formula are 15%, 78%, and 130%, respectively. Therefore, our model is a feasible and high-precision solution for the calculation of the hydraulic gradient of paste-like tailings in long-distance pipeline transportation.

Gossip Consensus Algorithm Based on Time-Varying Influence Factors and Weakly Connected Graph for Opinion Evolution in Social Networks

Directory of Open Access Journals (Sweden)

Lingyun Li

2013-01-01

Full Text Available We provide a new gossip algorithm to investigate the problem of opinion consensus with the time-varying influence factors and weakly connected graph among multiple agents. What is more, we discuss not only the effect of the time-varying factors and the randomized topological structure but also the spread of misinformation and communication constrains described by probabilistic quantized communication in the social network. Under the underlying weakly connected graph, we first denote that all opinion states converge to a stochastic consensus almost surely; that is, our algorithm indeed achieves the consensus with probability one. Furthermore, our results show that the mean of all the opinion states converges to the average of the initial states when time-varying influence factors satisfy some conditions. Finally, we give a result about the square mean error between the dynamic opinion states and the benchmark without quantized communication.

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

Science.gov (United States)

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. Copyright © 2014 the authors 0270-6474/14/3416046-12$15.00/0.

Reduction of Cone-Beam CT scan time without compromising the accuracy of the image registration in IGRT

International Nuclear Information System (INIS)

Westberg, Jonas; Jensen, Henrik R.; Bertelsen, Anders; Brink, Carsten

2010-01-01

Background. In modern radiotherapy accelerators are equipped with 3D cone-beam CT (CBCT) which is used to verify patient position before treatment. The verification is based on an image registration between the CBCT acquired just before treatment and the CT scan made for the treatment planning. The purpose of this study is to minimise the scan time of the CBCT without compromising the accuracy of the image registration in IGRT. Material and methods. Fast scans were simulated by reducing the number of acquired projection images, i.e. new reconstructions based on a subset of the original projections were made. The deviation between the registrations of these new reconstructions and the original registration was measured as function of the amount of reduction. Results and Discussion. Twenty nine head and neck (HandN) and 11 stereotactic lung patients were included in the study. The mean of the registration deviation did not differ significantly from zero independently of the number of projections included in the reconstruction. Except for the smallest subset of reconstructions (10% and 25% of the original projection for the lung and HandN patients, respectively) the standard deviation of the registration differences was constant. The standard deviations were approximately 0.1 mm and 0.2 mm for the HandN and lung group, respectively. Based on these results an in-house developed solution, able to reduce the Cone-Beam CT scan time, has been implemented clinically

A Novel Time-Varying Friction Compensation Method for Servomechanism

Directory of Open Access Journals (Sweden)

Bin Feng

2015-01-01

Full Text Available Friction is an inevitable nonlinear phenomenon existing in servomechanisms. Friction errors often affect their motion and contour accuracies during the reverse motion. To reduce friction errors, a novel time-varying friction compensation method is proposed to solve the problem that the traditional friction compensation methods hardly deal with. This problem leads to an unsatisfactory friction compensation performance and the motion and contour accuracies cannot be maintained effectively. In this method, a trapezoidal compensation pulse is adopted to compensate for the friction errors. A generalized regression neural network algorithm is used to generate the optimal pulse amplitude function. The optimal pulse duration function and the pulse amplitude function can be established by the pulse characteristic parameter learning and then the optimal friction compensation pulse can be generated. The feasibility of friction compensation method was verified on a high-precision X-Y worktable. The experimental results indicated that the motion and contour accuracies were improved greatly with reduction of the friction errors, in different working conditions. Moreover, the overall friction compensation performance indicators were decreased by more than 54% and this friction compensation method can be implemented easily on most of servomechanisms in industry.

Gold as an Infl ation Hedge in a Time-Varying Coeffi cient Framework

OpenAIRE

Joscha Beckmann; Robert Czudaj

2012-01-01

This study analyzes the question whether gold provides the ability of hedging against inflation from a new perspective. Using data for four major economies, namely the USA, the UK, the Euro Area, and Japan, we allow for nonlinearity and discriminate between long-run and time-varying short-run dynamics. Thus, we conduct a Markov-switching vector error correction model (MS-VECM) approach for a sample period ranging from January 1970 to December 2011. Our main findings are threefold: First, we s...

On global exponential stability of high-order neural networks with time-varying delays

International Nuclear Information System (INIS)

Zhang Baoyong; Xu Shengyuan; Li Yongmin; Chu Yuming

2007-01-01

This Letter investigates the problem of stability analysis for a class of high-order neural networks with time-varying delays. The delays are bounded but not necessarily differentiable. Based on the Lyapunov stability theory together with the linear matrix inequality (LMI) approach and the use of Halanay inequality, sufficient conditions guaranteeing the global exponential stability of the equilibrium point of the considered neural networks are presented. Two numerical examples are provided to demonstrate the effectiveness of the proposed stability criteria

On global exponential stability of high-order neural networks with time-varying delays

Energy Technology Data Exchange (ETDEWEB)

Zhang Baoyong [School of Automation, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu (China)]. E-mail: baoyongzhang@yahoo.com.cn; Xu Shengyuan [School of Automation, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu (China)]. E-mail: syxu02@yahoo.com.cn; Li Yongmin [School of Automation, Nanjing University of Science and Technology, Nanjing 210094, Jiangsu (China) and Department of Mathematics, Huzhou Teacher' s College, Huzhou 313000, Zhejiang (China)]. E-mail: ymlwww@163.com; Chu Yuming [Department of Mathematics, Huzhou Teacher' s College, Huzhou 313000, Zhejiang (China)

2007-06-18

This Letter investigates the problem of stability analysis for a class of high-order neural networks with time-varying delays. The delays are bounded but not necessarily differentiable. Based on the Lyapunov stability theory together with the linear matrix inequality (LMI) approach and the use of Halanay inequality, sufficient conditions guaranteeing the global exponential stability of the equilibrium point of the considered neural networks are presented. Two numerical examples are provided to demonstrate the effectiveness of the proposed stability criteria.

Difference in differences for stayers with a time-varying qualification: health expenditure elasticity of the elderly.

Science.gov (United States)

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. Copyright © 2014 John Wiley & Sons, Ltd.

Velocity distribution of electrons in time-varying low-temperature plasmas: progress in theoretical procedures over the past 70 years

Science.gov (United States)

Makabe, Toshiaki

2018-03-01

A time-varying low-temperature plasma sustained by electrical powers with various kinds of fRequencies has played a key role in the historical development of new technologies, such as gas lasers, ozonizers, micro display panels, dry processing of materials, medical care, and so on, since World War II. Electrons in a time-modulated low-temperature plasma have a proper velocity spectrum, i.e. velocity distribution dependent on the microscopic quantum characteristics of the feed gas molecule and on the external field strength and the frequency. In order to solve and evaluate the time-varying velocity distribution, we have mostly two types of theoretical methods based on the classical and linear Boltzmann equations, namely, the expansion method using the orthogonal function and the procedure of non-expansional temporal evolution. Both methods have been developed discontinuously and progressively in synchronization with those technological developments. In this review, we will explore the historical development of the theoretical procedure to evaluate the electron velocity distribution in a time-varying low-temperature plasma over the past 70 years.

Time-varying coefficient vector autoregressions model based on dynamic correlation with an application to crude oil and stock markets.

Science.gov (United States)

Lu, Fengbin; Qiao, Han; Wang, Shouyang; Lai, Kin Keung; Li, Yuze

2017-01-01

This paper proposes a new time-varying coefficient vector autoregressions (VAR) model, in which the coefficient is a linear function of dynamic lagged correlation. The proposed model allows for flexibility in choices of dynamic correlation models (e.g. dynamic conditional correlation generalized autoregressive conditional heteroskedasticity (GARCH) models, Markov-switching GARCH models and multivariate stochastic volatility models), which indicates that it can describe many types of time-varying causal effects. Time-varying causal relations between West Texas Intermediate (WTI) crude oil and the US Standard and Poor's 500 (S&P 500) stock markets are examined by the proposed model. The empirical results show that their causal relations evolve with time and display complex characters. Both positive and negative causal effects of the WTI on the S&P 500 in the subperiods have been found and confirmed by the traditional VAR models. Similar results have been obtained in the causal effects of S&P 500 on WTI. In addition, the proposed model outperforms the traditional VAR model. Copyright © 2016 Elsevier Ltd. All rights reserved.

Software requirements definition Shipping Cask Analysis System (SCANS)

International Nuclear Information System (INIS)

Johnson, G.L.; Serbin, R.

1985-01-01

The US Nuclear Regulatory Commission (NRC) staff reviews the technical adequacy of applications for certification of designs of shipping casks for spent nuclear fuel. In order to confirm an acceptable design, the NRC staff may perform independent calculations. The current NRC procedure for confirming cask design analyses is laborious and tedious. Most of the work is currently done by hand or through the use of a remote computer network. The time required to certify a cask can be long. The review process may vary somewhat with the engineer doing the reviewing. Similarly, the documentation on the results of the review can also vary with the reviewer. To increase the efficiency of this certification process, LLNL was requested to design and write an integrated set of user-oriented, interactive computer programs for a personal microcomputer. The system is known as the NRC Shipping Cask Analysis System (SCANS). The computer codes and the software system supporting these codes are being developed and maintained for the NRC by LLNL. The objective of this system is generally to lessen the time and effort needed to review an application. Additionally, an objective of the system is to assure standardized methods and documentation of the confirmatory analyses used in the review of these cask designs. A software system should be designed based on NRC-defined requirements contained in a requirements document. The requirements document is a statement of a project's wants and needs as the users and implementers jointly understand them. The requirements document states the desired end products (i.e. WHAT's) of the project, not HOW the project provides them. This document describes the wants and needs for the SCANS system. 1 fig., 3 tabs