Multi-disciplinary techniques for understanding time-varying space-based imagery
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.
A GPU-Accelerated Approach for Feature Tracking in Time-Varying Imagery Datasets.
Peng, Chao; Sahani, Sandip; Rushing, John
2017-10-01
We propose a novel parallel connected component labeling (CCL) algorithm along with efficient out-of-core data management to detect and track feature regions of large time-varying imagery datasets. Our approach contributes to the big data field with parallel algorithms tailored for GPU architectures. We remove the data dependency between frames and achieve pixel-level parallelism. Due to the large size, the entire dataset cannot fit into cached memory. Frames have to be streamed through the memory hierarchy (disk to CPU main memory and then to GPU memory), partitioned, and processed as batches, where each batch is small enough to fit into the GPU. To reconnect the feature regions that are separated due to data partitioning, we present a novel batch merging algorithm to extract the region connection information across multiple batches in a parallel fashion. The information is organized in a memory-efficient structure and supports fast indexing on the GPU. Our experiment uses a commodity workstation equipped with a single GPU. The results show that our approach can efficiently process a weather dataset composed of terabytes of time-varying radar images. The advantages of our approach are demonstrated by comparing to the performance of an efficient CPU cluster implementation which is being used by the weather scientists.
Sun, Bo; Sunkavalli, Kalyan; Ramamoorthi, Ravi; Belhumeur, Peter N; Nayar, Shree K
2007-01-01
The properties of virtually all real-world materials change with time, causing their bidirectional reflectance distribution functions (BRDFs) to be time varying. However, none of the existing BRDF models and databases take time variation into consideration; they represent the appearance of a material at a single time instance. In this paper, we address the acquisition, analysis, modeling, and rendering of a wide range of time-varying BRDFs (TVBRDFs). We have developed an acquisition system that is capable of sampling a material's BRDF at multiple time instances, with each time sample acquired within 36 sec. We have used this acquisition system to measure the BRDFs of a wide range of time-varying phenomena, which include the drying of various types of paints (watercolor, spray, and oil), the drying of wet rough surfaces (cement, plaster, and fabrics), the accumulation of dusts (household and joint compound) on surfaces, and the melting of materials (chocolate). Analytic BRDF functions are fit to these measurements and the model parameters' variations with time are analyzed. Each category exhibits interesting and sometimes nonintuitive parameter trends. These parameter trends are then used to develop analytic TVBRDF models. The analytic TVBRDF models enable us to apply effects such as paint drying and dust accumulation to arbitrary surfaces and novel materials.
DEFF Research Database (Denmark)
Christoffersen, Peter; Feunoua, Bruno; Jeon, Yoontae
We estimate a continuous-time model with stochastic volatility and dynamic crash probability for the S&P 500 index and find that market illiquidity dominates other factors in explaining the stock market crash risk. While the crash probability is time-varying, its dynamic depends only weakly...
Tobacco imagery on prime time UK television.
Lyons, Ailsa; McNeill, Ann; Britton, John
2014-05-01
Smoking in films is a common and well documented cause of youth smoking experimentation and uptake and hence a significant health hazard. The extent of exposure of young people to tobacco imagery in television programming has to date been far less investigated. We have therefore measured the extent to which tobacco content occurs in prime time UK television, and estimated exposure of UK youth. The occurrence of tobacco, categorised as actual tobacco use, implied tobacco use, tobacco paraphernalia, other reference to tobacco, tobacco brand appearances or any of these, occurring in all prime time broadcasting on the five most popularly viewed UK television stations during 3 separate weeks in 2010 were measured by 1-minute interval coding. Youth exposure to tobacco content in the UK was estimated using media viewing figures. Actual tobacco use, predominantly cigarette smoking, occurred in 73 of 613 (12%) programmes, particularly in feature films and reality TV. Brand appearances were rare, occurring in only 18 programmes, of which 12 were news or other factual genres, and 6 were episodes of the same British soap opera. Tobacco occurred with similar frequency before as after 21:00, the UK watershed for programmes suitable for youth. The estimated number of incidences of exposure of the audience aged less than 18 years for any tobacco, actual tobacco use and tobacco branding were 59 million, 16 million and 3 million, respectively on average per week. Television programming is a source of significant exposure of youth to tobacco imagery, before and after the watershed. Tobacco branding is particularly common in Coronation Street, a soap opera popular among youth audiences. More stringent controls on tobacco in prime time television therefore have the potential to reduce the uptake of youth smoking in the UK.
Tobacco imagery on prime time UK television
Lyons, Ailsa; McNeill, Ann; Britton, John
2014-01-01
Background Smoking in films is a common and well documented cause of youth smoking experimentation and uptake and hence a significant health hazard. The extent of exposure of young people to tobacco imagery in television programming has to date been far less investigated. We have therefore measured the extent to which tobacco content occurs in prime time UK television, and estimated exposure of UK youth. Methods The occurrence of tobacco, categorised as actual tobacco use, implied tobacco use, tobacco paraphernalia, other reference to tobacco, tobacco brand appearances or any of these, occurring in all prime time broadcasting on the five most popularly viewed UK television stations during 3 separate weeks in 2010 were measured by 1-minute interval coding. Youth exposure to tobacco content in the UK was estimated using media viewing figures. Findings Actual tobacco use, predominantly cigarette smoking, occurred in 73 of 613 (12%) programmes, particularly in feature films and reality TV. Brand appearances were rare, occurring in only 18 programmes, of which 12 were news or other factual genres, and 6 were episodes of the same British soap opera. Tobacco occurred with similar frequency before as after 21:00, the UK watershed for programmes suitable for youth. The estimated number of incidences of exposure of the audience aged less than 18 years for any tobacco, actual tobacco use and tobacco branding were 59 million, 16 million and 3 million, respectively on average per week. Conclusions Television programming is a source of significant exposure of youth to tobacco imagery, before and after the watershed. Tobacco branding is particularly common in Coronation Street, a soap opera popular among youth audiences. More stringent controls on tobacco in prime time television therefore have the potential to reduce the uptake of youth smoking in the UK. PMID:23479113
Fractal analysis of time varying data
Vo-Dinh, Tuan; Sadana, Ajit
2002-01-01
Characteristics of time varying data, such as an electrical signal, are analyzed by converting the data from a temporal domain into a spatial domain pattern. Fractal analysis is performed on the spatial domain pattern, thereby producing a fractal dimension D.sub.F. The fractal dimension indicates the regularity of the time varying data.
Components in time-varying graphs.
Nicosia, Vincenzo; Tang, John; Musolesi, Mirco; Russo, Giovanni; Mascolo, Cecilia; Latora, Vito
2012-06-01
Real complex systems are inherently time-varying. Thanks to new communication systems and novel technologies, today it is possible to produce and analyze social and biological networks with detailed information on the time of occurrence and duration of each link. However, standard graph metrics introduced so far in complex network theory are mainly suited for static graphs, i.e., graphs in which the links do not change over time, or graphs built from time-varying systems by aggregating all the links as if they were concurrent in time. In this paper, we extend the notion of connectedness, and the definitions of node and graph components, to the case of time-varying graphs, which are represented as time-ordered sequences of graphs defined over a fixed set of nodes. We show that the problem of finding strongly connected components in a time-varying graph can be mapped into the problem of discovering the maximal-cliques in an opportunely constructed static graph, which we name the affine graph. It is, therefore, an NP-complete problem. As a practical example, we have performed a temporal component analysis of time-varying graphs constructed from three data sets of human interactions. The results show that taking time into account in the definition of graph components allows to capture important features of real systems. In particular, we observe a large variability in the size of node temporal in- and out-components. This is due to intrinsic fluctuations in the activity patterns of individuals, which cannot be detected by static graph analysis.
Time varying controllers in discrete-time decentralized control
Deliu, C.; Deliu, C.; Stoorvogel, Antonie Arij; Saberi, Ali; Roy, Sandip; Malek, Babak
2009-01-01
In this paper, we consider the problem of finding a time-varying controller which can stabilize a decentralized discrete-time system. In continuous-time, it was already known that time-varying decentralized controllers can achieve stabilization in cases where time-invariant decentralized controllers
Real-time people and vehicle detection from UAV imagery
Gaszczak, Anna; Breckon, Toby P.; Han, Jiwan
2011-01-01
A generic and robust approach for the real-time detection of people and vehicles from an Unmanned Aerial Vehicle (UAV) is an important goal within the framework of fully autonomous UAV deployment for aerial reconnaissance and surveillance. Here we present an approach for the automatic detection of vehicles based on using multiple trained cascaded Haar classifiers with secondary confirmation in thermal imagery. Additionally we present a related approach for people detection in thermal imagery based on a similar cascaded classification technique combining additional multivariate Gaussian shape matching. The results presented show the successful detection of vehicle and people under varying conditions in both isolated rural and cluttered urban environments with minimal false positive detection. Performance of the detector is optimized to reduce the overall false positive rate by aiming at the detection of each object of interest (vehicle/person) at least once in the environment (i.e. per search patter flight path) rather than every object in each image frame. Currently the detection rate for people is ~70% and cars ~80% although the overall episodic object detection rate for each flight pattern exceeds 90%.
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...
Stoorvogel, Antonie Arij; Saberi, Ali; Zhang, Meirong
2016-01-01
This paper studies synchronization among identical agents that are coupled through a time-varying network with nonuniform time-varying communication delay. Given an arbitrary upper bound for the delays, a controller design methodology without exact knowledge of the network topology is proposed so
Conceptual Modeling of Time-Varying Information
DEFF Research Database (Denmark)
Gregersen, Heidi; Jensen, Christian Søndergaard
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...
Time varying arctic climate change amplification
Energy Technology Data Exchange (ETDEWEB)
Chylek, Petr [Los Alamos National Laboratory; Dubey, Manvendra K [Los Alamos National Laboratory; Lesins, Glen [DALLHOUSIE U; Wang, Muyin [NOAA/JISAO
2009-01-01
During the past 130 years the global mean surface air temperature has risen by about 0.75 K. Due to feedbacks -- including the snow/ice albedo feedback -- the warming in the Arctic is expected to proceed at a faster rate than the global average. Climate model simulations suggest that this Arctic amplification produces warming that is two to three times larger than the global mean. Understanding the Arctic amplification is essential for projections of future Arctic climate including sea ice extent and melting of the Greenland ice sheet. We use the temperature records from the Arctic stations to show that (a) the Arctic amplification is larger at latitudes above 700 N compared to those within 64-70oN belt, and that, surprisingly; (b) the ratio of the Arctic to global rate of temperature change is not constant but varies on the decadal timescale. This time dependence will affect future projections of climate changes in the Arctic.
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
Time-frequency representation based on time-varying ...
Indian Academy of Sciences (India)
defined in a time-frequency space and represents the evolution of signal power as a function of both time and ... the physical meaning of the intrinsic mode function (IMF) resulting from the EMD sifting process and the ... In the case of the basis function approach, each of its time-varying coefficients is expressed as a weighted ...
Rumor Detection over Varying Time Windows.
Kwon, Sejeong; Cha, Meeyoung; Jung, Kyomin
2017-01-01
This study determines the major difference between rumors and non-rumors and explores rumor classification performance levels over varying time windows-from the first three days to nearly two months. A comprehensive set of user, structural, linguistic, and temporal features was examined and their relative strength was compared from near-complete date of Twitter. Our contribution is at providing deep insight into the cumulative spreading patterns of rumors over time as well as at tracking the precise changes in predictive powers across rumor features. Statistical analysis finds that structural and temporal features distinguish rumors from non-rumors over a long-term window, yet they are not available during the initial propagation phase. In contrast, user and linguistic features are readily available and act as a good indicator during the initial propagation phase. Based on these findings, we suggest a new rumor classification algorithm that achieves competitive accuracy over both short and long time windows. These findings provide new insights for explaining rumor mechanism theories and for identifying features of early rumor detection.
Time-frequency representation based on time-varying ...
Indian Academy of Sciences (India)
A parametric time-frequency representation is presented based on timevarying autoregressive model (TVAR), followed by applications to non-stationary vibration signal processing. The identiﬁcation of time-varying model coefﬁcients and the determination of model order, are addressed by means of neural networks and ...
Modelling tourists arrival using time varying parameter
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.
Fast natural color mapping for night-time imagery
Hogervorst, M.A.; Toet, A.
2010-01-01
We present a new method to render multi-band night-time imagery (images from sensors whose sensitive range does not necessarily coincide with the visual part of the electromagnetic spectrum, e.g. image intensifiers, thermal camera's) in natural daytime colors. The color mapping is derived from the
Timed arrays wideband and time varying antenna arrays
Haupt, Randy L
2015-01-01
Introduces timed arrays and design approaches to meet the new high performance standards The author concentrates on any aspect of an antenna array that must be viewed from a time perspective. The first chapters briefly introduce antenna arrays and explain the difference between phased and timed arrays. Since timed arrays are designed for realistic time-varying signals and scenarios, the book also reviews wideband signals, baseband and passband RF signals, polarization and signal bandwidth. Other topics covered include time domain, mutual coupling, wideband elements, and dispersion. The auth
Tracking time-varying coefficient-functions
DEFF Research Database (Denmark)
Nielsen, Henrik Aalborg; Nielsen, Torben Skov; Joensen, Alfred K.
2000-01-01
A method for adaptive and recursive estimation in a class of non-linear autoregressive models with external input is proposed. The model class considered is conditionally parametric ARX-models (CPARX-models), which is conventional ARX-models in which the parameters are replaced by smooth, but oth......A method for adaptive and recursive estimation in a class of non-linear autoregressive models with external input is proposed. The model class considered is conditionally parametric ARX-models (CPARX-models), which is conventional ARX-models in which the parameters are replaced by smooth...... 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...
Decker, A. J.
1982-01-01
The use of a Nd:YAG laser to record holographic motion pictures of time-varying reflecting objects and time-varying phase objects is discussed. Sample frames from both types of holographic motion pictures are presented. The holographic system discussed is intended for three-dimensional flow visualization of the time-varying flows that occur in jet-engine components.
Alliance and outcome in varying imagery procedures for PTSD: a study of within-person processes.
Hoffart, Asle; Øktedalen, Tuva; Langkaas, Tomas Formo; Wampold, Bruce E
2013-10-01
The present study examined both the intraindividual relationship between alliance components (task, goal, and bond) and subsequent posttraumatic stress disorder (PTSD) symptoms over the course of therapy and the interindividual relationships between the initial level of the alliance components and overall PTSD outcome. PTSD patients (n = 65) were randomized to either standard prolonged exposure, which includes imaginal exposure (IE) to the traumatic memory, or modified prolonged exposure, where imagery rescripting (IR) of the memory replaced IE as the imagery component of prolonged exposure in a 10-week residential program. They were assessed repeatedly (weekly) on alliance and PTSD symptom measures. The centering method of detrending (Curran & Bauer, 2011) was used to separate the variance related to the intraindividual process of change during treatment (within-person component) from the variance related to initial individual differences (between-person component). The hypothesis of a negative within-person effect of the alliance components agreement about the tasks of therapy and bond on subsequent PTSD symptoms was supported for the component task agreement. As expected, this effect was stronger in IE than in IR. Moreover, there was a negative relationship between interindividual differences in initial Task and Bond scale scores and slope of PTSD symptoms over the course of therapy. By contrast, within-person variations in PTSD symptoms did not predict subsequent alliance components. The present results suggest the importance of agreement about therapy tasks during the process of IE or IR within prolonged exposure for PTSD patients, particularly in IE.
Time-varying interaction leads to amplitude death in coupled ...
Indian Academy of Sciences (India)
A new form of time-varying interaction in coupled oscillators is introduced. In this interaction, each individual oscillator has always time-independent self-feedback while its interaction with other oscillators are modulated with time-varying function. This interaction gives rise to a phenomenon called amplitude death even in ...
Dynamics of nonlinear oscillators with time-varying conjugate coupling
Indian Academy of Sciences (India)
We explore the dynamical consequences of time-varying conjugate coupling in a system of nonlinear oscillators. We analyze the behavior of coupled ... Conjugate coupling; time varying coupling. PACS Nos 05.45.Xt. 1. Introduction ..... MDS acknowledges the financial support from DST,. New Delhi. References. [1] L Glass ...
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....
Time varying voltage combustion control and diagnostics sensor
Chorpening, Benjamin T [Morgantown, WV; Thornton, Jimmy D [Morgantown, WV; Huckaby, E David [Morgantown, WV; Fincham, William [Fairmont, WV
2011-04-19
A time-varying voltage is applied to an electrode, or a pair of electrodes, of a sensor installed in a fuel nozzle disposed adjacent the combustion zone of a continuous combustion system, such as of the gas turbine engine type. The time-varying voltage induces a time-varying current in the flame which is measured and used to determine flame capacitance using AC electrical circuit analysis. Flame capacitance is used to accurately determine the position of the flame from the sensor and the fuel/air ratio. The fuel and/or air flow rate (s) is/are then adjusted to provide reduced flame instability problems such as flashback, combustion dynamics and lean blowout, as well as reduced emissions. The time-varying voltage may be an alternating voltage and the time-varying current may be an alternating current.
Time-Varying FOPDT System Identification with Unknown Disturbance Input
DEFF Research Database (Denmark)
Sun, Zhen; Yang, Zhenyu
2012-01-01
The Time-Varying First Order Plus Dead Time (TV-FOPDT) model is an extension of the conventional FOPDT by allowing the system parameters, which are primarily defined on the transfer function description, i.e., the DC-gain, time constant and time delay, to be time dependent. The TV-FOPDT identific...
Capturing change: the duality of time-lapse imagery to acquire data and depict ecological dynamics
Brinley Buckley, Emma M.; Allen, Craig R.; Forsberg, Michael; Farrell, Michael; Caven, Andrew J.
2017-01-01
We investigate the scientific and communicative value of time-lapse imagery by exploring applications for data collection and visualization. Time-lapse imagery has a myriad of possible applications to study and depict ecosystems and can operate at unique temporal and spatial scales to bridge the gap between large-scale satellite imagery projects and observational field research. Time-lapse data sequences, linking time-lapse imagery with data visualization, have the ability to make data come alive for a wider audience by connecting abstract numbers to images that root data in time and place. Utilizing imagery from the Platte Basin Timelapse Project, water inundation and vegetation phenology metrics are quantified via image analysis and then paired with passive monitoring data, including streamflow and water chemistry. Dynamic and interactive time-lapse data sequences elucidate the visible and invisible ecological dynamics of a significantly altered yet internationally important river system in central Nebraska.
Capturing change: the duality of time-lapse imagery to acquire data and depict ecological dynamics
Directory of Open Access Journals (Sweden)
Emma M. Brinley Buckley
2017-09-01
Full Text Available We investigate the scientific and communicative value of time-lapse imagery by exploring applications for data collection and visualization. Time-lapse imagery has a myriad of possible applications to study and depict ecosystems and can operate at unique temporal and spatial scales to bridge the gap between large-scale satellite imagery projects and observational field research. Time-lapse data sequences, linking time-lapse imagery with data visualization, have the ability to make data come alive for a wider audience by connecting abstract numbers to images that root data in time and place. Utilizing imagery from the Platte Basin Timelapse Project, water inundation and vegetation phenology metrics are quantified via image analysis and then paired with passive monitoring data, including streamflow and water chemistry. Dynamic and interactive time-lapse data sequences elucidate the visible and invisible ecological dynamics of a significantly altered yet internationally important river system in central Nebraska.
Harmonic analysis of dense time series of landsat imagery for modeling change in forest conditions
Barry Tyler. Wilson
2015-01-01
This study examined the utility of dense time series of Landsat imagery for small area estimation and mapping of change in forest conditions over time. The study area was a region in north central Wisconsin for which Landsat 7 ETM+ imagery and field measurements from the Forest Inventory and Analysis program are available for the decade of 2003 to 2012. For the periods...
Design of 2D Time-Varying Vector Fields
Chen, Guoning
2012-10-01
Design of time-varying vector fields, i.e., vector fields that can change over time, has a wide variety of important applications in computer graphics. Existing vector field design techniques do not address time-varying vector fields. In this paper, we present a framework for the design of time-varying vector fields, both for planar domains as well as manifold surfaces. Our system supports the creation and modification of various time-varying vector fields with desired spatial and temporal characteristics through several design metaphors, including streamlines, pathlines, singularity paths, and bifurcations. These design metaphors are integrated into an element-based design to generate the time-varying vector fields via a sequence of basis field summations or spatial constrained optimizations at the sampled times. The key-frame design and field deformation are also introduced to support other user design scenarios. Accordingly, a spatial-temporal constrained optimization and the time-varying transformation are employed to generate the desired fields for these two design scenarios, respectively. We apply the time-varying vector fields generated using our design system to a number of important computer graphics applications that require controllable dynamic effects, such as evolving surface appearance, dynamic scene design, steerable crowd movement, and painterly animation. Many of these are difficult or impossible to achieve via prior simulation-based methods. In these applications, the time-varying vector fields have been applied as either orientation fields or advection fields to control the instantaneous appearance or evolving trajectories of the dynamic effects. © 1995-2012 IEEE.
Estimation of Time Varying Autoregressive Symmetric Alpha Stable
National Aeronautics and Space Administration — In this work, we present a novel method for modeling time-varying autoregressive impulsive signals driven by symmetric alpha stable distributions. The proposed...
Modeling non-Gaussian time-varying vector autoregressive process
National Aeronautics and Space Administration — We present a novel and general methodology for modeling time-varying vector autoregressive processes which are widely used in many areas such as modeling of chemical...
Electricity futures prices: time varying sensitivity to fundamentals
Fleten, Stein-Erik; Huisman, Ronald; Kilic, Mehtap; Pennings, Enrico; Westgaard, Sjur
2014-01-01
This paper provides insight into the time-varying relation between electricity futures prices and fundamentals in the form of contract prices for fossil fuels. As supply curves are not constant and different producers have different marginal costs of production, we argue that the relation between the prices of electricity futures and those of underlying fundamentals such as natural gas, coal and emission rights varies over time. We test this view by applying a model that linearly relates elec...
Do Time-Varying Covariances, Volatility Comovement and Spillover Matter?
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...
Directory of Open Access Journals (Sweden)
Masahito Mihara
Full Text Available Accumulating evidence indicates that motor imagery and motor execution share common neural networks. Accordingly, mental practices in the form of motor imagery have been implemented in rehabilitation regimes of stroke patients with favorable results. Because direct monitoring of motor imagery is difficult, feedback of cortical activities related to motor imagery (neurofeedback could help to enhance efficacy of mental practice with motor imagery. To determine the feasibility and efficacy of a real-time neurofeedback system mediated by near-infrared spectroscopy (NIRS, two separate experiments were performed. Experiment 1 was used in five subjects to evaluate whether real-time cortical oxygenated hemoglobin signal feedback during a motor execution task correlated with reference hemoglobin signals computed off-line. Results demonstrated that the NIRS-mediated neurofeedback system reliably detected oxygenated hemoglobin signal changes in real-time. In Experiment 2, 21 subjects performed motor imagery of finger movements with feedback from relevant cortical signals and irrelevant sham signals. Real neurofeedback induced significantly greater activation of the contralateral premotor cortex and greater self-assessment scores for kinesthetic motor imagery compared with sham feedback. These findings suggested the feasibility and potential effectiveness of a NIRS-mediated real-time neurofeedback system on performance of kinesthetic motor imagery. However, these results warrant further clinical trials to determine whether this system could enhance the effects of mental practice in stroke patients.
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 ...
Time-varying interaction leads to amplitude death in coupled ...
Indian Academy of Sciences (India)
2013-09-05
Sep 5, 2013 ... A new form of time-varying interaction in coupled oscillators is introduced. In this interaction, each individual oscillator has always time-independent self-feedback while its interac- tion with other ..... this work, and acknowl- edge the kind hospitality and financial support from the MPI-PKS Dresden, Germany.
Scattering of a TEM wave from a time varying surface
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.
Importance-driven time-varying data visualization.
Wang, Chaoli; Yu, Hongfeng; Ma, Kwan-Liu
2008-01-01
The ability to identify and present the most essential aspects of time-varying data is critically important in many areas of science and engineering. This paper introduces an importance-driven approach to time-varying volume data visualization for enhancing that ability. By conducting a block-wise analysis of the data in the joint feature-temporal space, we derive an importance curve for each data block based on the formulation of conditional entropy from information theory. Each curve characterizes the local temporal behavior of the respective block, and clustering the importance curves of all the volume blocks effectively classifies the underlying data. Based on different temporal trends exhibited by importance curves and their clustering results, we suggest several interesting and effective visualization techniques to reveal the important aspects of time-varying data.
Time varying market efficiency of the GCC stock markets
Charfeddine, Lanouar; Khediri, Karim Ben
2016-02-01
This paper investigates the time-varying levels of weak-form market efficiency for the GCC stock markets over the period spanning from May 2005 to September 2013. We use two empirical approaches: (1) the generalized autoregressive conditional heteroscedasticity in mean (GARCH-M) model with state space time varying parameter (Kalman filter), and (2) a rolling technique sample test of the fractional long memory parameter d. As long memory estimation methods, we use the detrended fluctuation analysis (DFA) technique, the modified R/S statistic, the exact local whittle (ELW) and the feasible Exact Local Whittle (FELW) methods. Moreover, we use the Bai and Perron (1998, 2003) multiple structural breaks technique to test and date the time varying behavior of stock market efficiency. Empirical results show that GCC markets have different degrees of time-varying efficiency, and also have experiencing periods of efficiency improvement. Results also show evidence of structural breaks in all GCC markets. Moreover, we observe that the recent financial shocks such as Arab spring and subprime crises have a significant impact on the time path evolution of market efficiency.
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.
Bayesian classification in a time-varying environment
Swain, P. H.
1978-01-01
The problem of classifying a pattern based on multiple observation made in a time-varying environment is analyzed. The identity of the pattern may itself change. A Bayesian solution is derived, after which the conditions of the physical situation are invoked to produce a cascade classifier model. Experimental results based on remote sensing data demonstrate the effectiveness of the classifier.
Time Varying Market Integration and Expected Rteurns in Emerging Markets
de Jong, F.C.J.M.; de Roon, F.A.
2001-01-01
We use a simple model in which the expected returns in emerging markets depend on their systematic risk as measured by their beta relative to the world portfolio as well as on the level of integration in that market.The level of integration is a time-varying variable that depends on the market value
Precoder and decoder prediction in time-varying MIMO channel
DEFF Research Database (Denmark)
Nguyen, Tuan Hung; Leus, Geert; Khaled, Nadia
2005-01-01
the performance of a prediction scheme for multiple input multiple output (MIMO) systems that apply spatial multiplexing. We aim at predicting the future precoder/decoder directly without going through the prediction of the channel matrix. The results show that in a slowly time varying channel an increase...
Electricity Futures Prices : Time Varying Sensitivity to Fundamentals
S-E. Fleten (Stein-Erik); R. Huisman (Ronald); M. Kilic (Mehtap); H.P.G. Pennings (Enrico); S. Westgaard (Sjur)
2014-01-01
textabstractThis paper provides insight in the time-varying relation between electricity futures prices and fundamentals in the form of prices of contracts for fossil fuels. As supply curves are not constant and different producers have different marginal costs of production, we argue that the
How feedback, motor imagery, and reward influence brain self-regulation using real-time fMRI.
Sepulveda, Pradyumna; Sitaram, Ranganatha; Rana, Mohit; Montalba, Cristian; Tejos, Cristian; Ruiz, Sergio
2016-09-01
The learning process involved in achieving brain self-regulation is presumed to be related to several factors, such as type of feedback, reward, mental imagery, duration of training, among others. Explicitly instructing participants to use mental imagery and monetary reward are common practices in real-time fMRI (rtfMRI) neurofeedback (NF), under the assumption that they will enhance and accelerate the learning process. However, it is still not clear what the optimal strategy is for improving volitional control. We investigated the differential effect of feedback, explicit instructions and monetary reward while training healthy individuals to up-regulate the blood-oxygen-level dependent (BOLD) signal in the supplementary motor area (SMA). Four groups were trained in a two-day rtfMRI-NF protocol: GF with NF only, GF,I with NF + explicit instructions (motor imagery), GF,R with NF + monetary reward, and GF,I,R with NF + explicit instructions (motor imagery) + monetary reward. Our results showed that GF increased significantly their BOLD self-regulation from day-1 to day-2 and GF,R showed the highest BOLD signal amplitude in SMA during the training. The two groups who were instructed to use motor imagery did not show a significant learning effect over the 2 days. The additional factors, namely motor imagery and reward, tended to increase the intersubject variability in the SMA during the course of training. Whole brain univariate and functional connectivity analyses showed common as well as distinct patterns in the four groups, representing the varied influences of feedback, reward, and instructions on the brain. Hum Brain Mapp 37:3153-3171, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
The value premium and time-varying volatility
Li, X.; Brooks, C.; Miffre, J.
2009-01-01
Numerous studies have documented the failure of the static and conditional capital asset pricing models to explain the difference in returns between value and growth stocks. This paper examines the post-1963 value premium by employing a model that captures the time-varying total risk of the value-minus-growth portfolios. Our results show that the time-series of value premia is strongly and positively correlated with its volatility. This conclusion is robust to the criterion used to sort stock...
Online dynamic mode decomposition for time-varying systems
Zhang, Hao; Rowley, Clarence; Deem, Eric; Cattafesta, Louis
2017-11-01
Dynamic mode decomposition (DMD) is a popular technique for modal decomposition, flow analysis, and reduced-order modeling. In situations where a system is time varying, one would like to update the system's description online as time evolves. This work provides an efficient method for computing the DMD matrix in real time, updating the approximation of a system's dynamics as new data becomes available. The algorithm does not require storage of past data, and computes the exact DMD matrix using rank-1 updates. A weighting factor that places less weight on older data can be incorporated in a straightforward manner, making the method particularly well suited to time-varying systems. The efficiency of the method is compared against several existing DMD algorithms: for problems in which the state dimension is less than about 200, the proposed algorithm is the most efficient for real-time computation, and it can be orders of magnitude more efficient than the standard DMD algorithm. The method is demonstrated on several examples, including a time-varying linear system and a more complex example using data from a wind tunnel experiment. Supported by AFOSR Grant FA9550-14-1-0289, and by DARPA award HR0011-16-C-0116.
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.
Modeling information diffusion in time-varying community networks
Cui, Xuelian; Zhao, Narisa
2017-12-01
Social networks are rarely static, and they typically have time-varying network topologies. A great number of studies have modeled temporal networks and explored social contagion processes within these models; however, few of these studies have considered community structure variations. In this paper, we present a study of how the time-varying property of a modular structure influences the information dissemination. First, we propose a continuous-time Markov model of information diffusion where two parameters, mobility rate and community attractiveness, are introduced to address the time-varying nature of the community structure. The basic reproduction number is derived, and the accuracy of this model is evaluated by comparing the simulation and theoretical results. Furthermore, numerical results illustrate that generally both the mobility rate and community attractiveness significantly promote the information diffusion process, especially in the initial outbreak stage. Moreover, the strength of this promotion effect is much stronger when the modularity is higher. Counterintuitively, it is found that when all communities have the same attractiveness, social mobility no longer accelerates the diffusion process. In addition, we show that the local spreading in the advantage group has been greatly enhanced due to the agglomeration effect caused by the social mobility and community attractiveness difference, which thus increases the global spreading.
Morphable Word Clouds for Time-Varying Text Data Visualization.
Chi, Ming-Te; Lin, Shih-Syun; Chen, Shiang-Yi; Lin, Chao-Hung; Lee, Tong-Yee
2015-12-01
A word cloud is a visual representation of a collection of text documents that uses various font sizes, colors, and spaces to arrange and depict significant words. The majority of previous studies on time-varying word clouds focuses on layout optimization and temporal trend visualization. However, they do not fully consider the spatial shapes and temporal motions of word clouds, which are important factors for attracting people's attention and are also important cues for human visual systems in capturing information from time-varying text data. This paper presents a novel method that uses rigid body dynamics to arrange multi-temporal word-tags in a specific shape sequence under various constraints. Each word-tag is regarded as a rigid body in dynamics. With the aid of geometric, aesthetic, and temporal coherence constraints, the proposed method can generate a temporally morphable word cloud that not only arranges word-tags in their corresponding shapes but also smoothly transforms the shapes of word clouds over time, thus yielding a pleasing time-varying visualization. Using the proposed frame-by-frame and morphable word clouds, people can observe the overall story of a time-varying text data from the shape transition, and people can also observe the details from the word clouds in frames. Experimental results on various data demonstrate the feasibility and flexibility of the proposed method in morphable word cloud generation. In addition, an application that uses the proposed word clouds in a simulated exhibition demonstrates the usefulness of the proposed method.
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....
New stability conditions for nonlinear time varying delay systems
Elmadssia, S.; Saadaoui, K.; Benrejeb, M.
2016-07-01
In this paper, new practical stability conditions for a class of nonlinear time varying delay systems are proposed. The study is based on the use of a specific state space description, known as the Benrejeb characteristic arrow form matrix, and aggregation techniques to obtain delay-dependent stability conditions. Application of this method to delayed Lurie-Postnikov nonlinear systems is given. Illustrative examples are presented to show the effectiveness of the proposed approach.
Asset-Liability Management under time-varying Investment Opportunities
Ferstl, Robert; Weissensteiner, Alex
2009-01-01
In this paper, we propose multi-stage stochastic linear programming for asset-liability management under time-varying investment opportunities. We use a first-order unrestricted vector autoregressive process to model predictability in the asset returns and the state variables, where - additional to equity returns and dividend-price ratios - Nelson/Siegel parameters are included to account for the evolution of the yield curve. As objective function we minimize conditional value at risk of the ...
Social contagions on time-varying community networks
Liu, Mian-Xin; Wang, Wei; Liu, Ying; Tang, Ming; Cai, Shi-Min; Zhang, Hai-Feng
2017-05-01
Time-varying community structures exist widely in real-world networks. However, previous studies on the dynamics of spreading seldom took this characteristic into account, especially those on social contagions. To study the effects of time-varying community structures on social contagions, we propose a non-Markovian social contagion model on time-varying community networks based on the activity-driven network model. A mean-field theory is developed to analyze the proposed model. Through theoretical analyses and numerical simulations, two hierarchical features of the behavior adoption processes are found. That is, when community strength is relatively large, the behavior can easily spread in one of the communities, while in the other community the spreading only occurs at higher behavioral information transmission rates. Meanwhile, in spatial-temporal evolution processes, hierarchical orders are observed for the behavior adoption. Moreover, under different information transmission rates, three distinctive patterns are demonstrated in the change of the whole network's final adoption proportion along with the growing community strength. Within a suitable range of transmission rate, an optimal community strength can be found that can maximize the final adoption proportion. Finally, compared with the average activity potential, the promoting or inhibiting of social contagions is much more influenced by the number of edges generated by active nodes.
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
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
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...... factors. The squared correlation coefficient times the sample size has a limiting chi-squared distribution. The test can be made robust to serial correlation in the idiosyncratic errors. We find evidence for factor loadings variance in over half of the variables in a dataset for the US economy, while...
Ice sheet growth with laterally varying bedrock relaxation time
van der Wal, Wouter; Vizcaino Rubio, Pablo; De Boer, Bas; van de Wal, Roderik
2017-04-01
Isostatic response of the bedrock, or glacial isostatic adjustment (GIA) in included in most ice sheet models. This is important because the surface elevation determines the mass balance and thereby implicitly also the strength of the mass balance feedback where higher surface elevation yields lower temperatures implying less melt and vice versa. Usually a single relaxation time or a set of relaxation times is used to model the response everywhere on Earth or at least for an entire ice sheet. In reality the viscosity in the Earth's mantle, and hence the relaxation time experienced by the ice, varies with location. Seismic studies indicate that several regions that were covered by ice during the last glacial cycle are underlain by mantle in which viscosity varies with orders of magnitude, such as Antarctica and North America. The question is whether such a variation of viscosity influences ice evolution. Several GIA models exist that can deal with 3D viscosity, but their large computation times make it nearly impossible to couple them to ice sheet models. Here we use the ANICE ice-sheet model (de Boer et al. 2013) with a simple bedrock-relaxation model in which a different relaxation time is used for separate regions. A temperature anomaly is applied to grow a schematic ice sheet on a flat earth, with other forcing mechanisms neglected. It is shown that in locations with a fast relaxation time of 300 years the equilibrium ice sheet is significantly thinner and narrower but also ice thickness in neighbouring regions (with the more standard relaxation time of 3000 years) is affected.
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.
Sport Transition of JPSS VIIRS Imagery for Night-time Applications
Fuell, Kevin; LeRoy, Anita; Smith, Matt; Miller, Steve; Kann, Diedre; Bernhardt, David; Reydell, Nezette; Cox, Robert
2014-01-01
The NASA/Short-term Prediction, Research, and Transition (SPoRT) Program and NOAA/Cooperative Institute for Research in the Atmosphere (CIRA) work within the NOAA/Joint Polar Satellite System (JPSS) Proving Ground to demonstrate the unique capabilities of the VIIRS instrument. Very similar to MODIS, the VIIRS instrument provides many high-resolution visible and infrared channels in a broad spectrum. In addition, VIIRS is equipped with a low-light sensor that is able to detect light emissions from the land and atmosphere as well as reflected sunlight by the lunar surface. This band is referred to as the Day-Night Band due to the sunlight being used at night to see cloud and topographic features just as one would typically see in day-time visible imagery. NWS forecast offices that collaborate with SPoRT and CIRA have utilized MODIS imagery in operations, but have longed for more frequent passes of polar-orbiting data. The VIIRS instrument enhances SPoRT collaborations with WFOs by providing another day and night-time pass, and at times two additional passes due to its large swath width. This means that multi-spectral, RGB imagery composites are more readily available to prepare users for their use in GOES-R era and high-resolution imagery for use in high-latitudes is more frequently able to supplement standard GOES imagery within the SPoRT Hybrid GEO-LEO product. The transition of VIIRS also introduces the new Day-Night Band capability to forecast operations. An Intensive Evaluation Period (IEP) was conducted in Summer 2013 with a group of "Front Range" NWS offices related to VIIRS night-time imagery. VIIRS single-channel imagery is able to better analyze the specific location of fire hotspots and other land features, as well as provide a more true measurement of various cloud and aerosol properties than geostationary measurements, especially at night. Viewed within the SPoRT Hybrid imagery, the VIIRS data allows forecasters to better interpret the more frequent, but
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.
Study of selected phenotype switching strategies in time varying environment
Energy Technology Data Exchange (ETDEWEB)
Horvath, Denis, E-mail: horvath.denis@gmail.com [Centre of Interdisciplinary Biosciences, Institute of Physics, Faculty of Science, P.J. Šafárik University in Košice, Jesenná 5, 040 01 Košice (Slovakia); Brutovsky, Branislav, E-mail: branislav.brutovsky@upjs.sk [Department of Biophysics, Institute of Physics, P.J. Šafárik University in Košice, Jesenná 5, 040 01 Košice (Slovakia)
2016-03-22
Population heterogeneity plays an important role across many research, as well as the real-world, problems. The population heterogeneity relates to the ability of a population to cope with an environment change (or uncertainty) preventing its extinction. However, this ability is not always desirable as can be exemplified by an intratumor heterogeneity which positively correlates with the development of resistance to therapy. Causation of population heterogeneity is therefore in biology and medicine an intensively studied topic. In this paper the evolution of a specific strategy of population diversification, the phenotype switching, is studied at a conceptual level. The presented simulation model studies evolution of a large population of asexual organisms in a time-varying environment represented by a stochastic Markov process. Each organism disposes with a stochastic or nonlinear deterministic switching strategy realized by discrete-time models with evolvable parameters. We demonstrate that under rapidly varying exogenous conditions organisms operate in the vicinity of the bet-hedging strategy, while the deterministic patterns become relevant as the environmental variations are less frequent. Statistical characterization of the steady state regimes of the populations is done using the Hellinger and Kullback–Leibler functional distances and the Hamming distance. - Highlights: • Relation between phenotype switching and environment is studied. • The Markov chain Monte Carlo based model is developed. • Stochastic and deterministic strategies of phenotype switching are utilized. • Statistical measures of the dynamic heterogeneity reveal universal properties. • The results extend to higher lattice dimensions.
Study of selected phenotype switching strategies in time varying environment
Horvath, Denis; Brutovsky, Branislav
2016-03-01
Population heterogeneity plays an important role across many research, as well as the real-world, problems. The population heterogeneity relates to the ability of a population to cope with an environment change (or uncertainty) preventing its extinction. However, this ability is not always desirable as can be exemplified by an intratumor heterogeneity which positively correlates with the development of resistance to therapy. Causation of population heterogeneity is therefore in biology and medicine an intensively studied topic. In this paper the evolution of a specific strategy of population diversification, the phenotype switching, is studied at a conceptual level. The presented simulation model studies evolution of a large population of asexual organisms in a time-varying environment represented by a stochastic Markov process. Each organism disposes with a stochastic or nonlinear deterministic switching strategy realized by discrete-time models with evolvable parameters. We demonstrate that under rapidly varying exogenous conditions organisms operate in the vicinity of the bet-hedging strategy, while the deterministic patterns become relevant as the environmental variations are less frequent. Statistical characterization of the steady state regimes of the populations is done using the Hellinger and Kullback-Leibler functional distances and the Hamming distance.
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
Visualization of Time-Varying Weather Ensembles across Multiple Resolutions.
Biswas, Ayan; Lin, Guang; Liu, Xiaotong; Shen, Han-Wei
2017-01-01
Uncertainty quantification in climate ensembles is an important topic for the domain scientists, especially for decision making in the real-world scenarios. With powerful computers, simulations now produce time-varying and multi-resolution ensemble data sets. It is of extreme importance to understand the model sensitivity given the input parameters such that more computation power can be allocated to the parameters with higher influence on the output. Also, when ensemble data is produced at different resolutions, understanding the accuracy of different resolutions helps the total time required to produce a desired quality solution with improved storage and computation cost. In this work, we propose to tackle these non-trivial problems on the Weather Research and Forecasting (WRF) model output. We employ a moment independent sensitivity measure to quantify and analyze parameter sensitivity across spatial regions and time domain. A comparison of clustering structures across three resolutions enables the users to investigate the sensitivity variation over the spatial regions of the five input parameters. The temporal trend in the sensitivity values is explored via an MDS view linked with a line chart for interactive brushing. The spatial and temporal views are connected to provide a full exploration system for complete spatio-temporal sensitivity analysis. To analyze the accuracy across varying resolutions, we formulate a Bayesian approach to identify which regions are better predicted at which resolutions compared to the observed precipitation. This information is aggregated over the time domain and finally encoded in an output image through a custom color map that guides the domain experts towards an adaptive grid implementation given a cost model. Users can select and further analyze the spatial and temporal error patterns for multi-resolution accuracy analysis via brushing and linking on the produced image. In this work, we collaborate with a domain expert whose
Colley, Ian D; Keller, Peter E; Halpern, Andrea R
2017-08-11
Sensorimotor synchronization (SMS) is prevalent and readily studied in musical settings, as most people are able to perceive and synchronize with a beat (e.g. by finger tapping). We took an individual differences approach to understanding SMS to real music characterized by expressive timing (i.e. fluctuating beat regularity). Given the dynamic nature of SMS, we hypothesized that individual differences in working memory and auditory imagery-both fluid cognitive processes-would predict SMS at two levels: 1) mean absolute asynchrony (a measure of synchronization error), and 2) anticipatory timing (i.e. predicting, rather than reacting to beat intervals). In Experiment 1, participants completed two working memory tasks, four auditory imagery tasks, and an SMS-tapping task. Hierarchical regression models were used to predict SMS performance, with results showing dissociations among imagery types in relation to mean absolute asynchrony, and evidence of a role for working memory in anticipatory timing. In Experiment 2, a new sample of participants completed an expressive timing perception task to examine the role of imagery in perception without action. Results suggest that imagery vividness is important for perceiving and control is important for synchronizing with, irregular but ecologically valid musical time series. Working memory is implicated in synchronizing by anticipating events in the series.
Time-varying trends of global vegetation activity
Pan, N.; Feng, X.; Fu, B.
2016-12-01
Vegetation plays an important role in regulating the energy change, water cycle and biochemical cycle in terrestrial ecosystems. Monitoring the dynamics of vegetation activity and understanding their driving factors have been an important issue in global change research. Normalized Difference Vegetation Index (NDVI), an indicator of vegetation activity, has been widely used in investigating vegetation changes at regional and global scales. Most studies utilized linear regression or piecewise linear regression approaches to obtain an averaged changing rate over a certain time span, with an implicit assumption that the trend didn't change over time during that period. However, no evidence shows that this assumption is right for the non-linear and non-stationary NDVI time series. In this study, we adopted the multidimensional ensemble empirical mode decomposition (MEEMD) method to extract the time-varying trends of NDVI from original signals without any a priori assumption of their functional form. Our results show that vegetation trends are spatially and temporally non-uniform during 1982-2013. Most vegetated area exhibited greening trends in the 1980s. Nevertheless, the area with greening trends decreased over time since the early 1990s, and the greening trends have stalled or even reversed in many places. Regions with browning trends were mainly located in southern low latitudes in the 1980s, whose area decreased before the middle 1990s and then increased at an accelerated rate. The greening-to-browning reversals were widespread across all continents except Oceania (43% of the vegetated areas), most of which happened after the middle 1990s. In contrast, the browning-to-greening reversals occurred in smaller area and earlier time. The area with monotonic greening and browning trends accounted for 33% and 5% of the vegetated area, respectively. By performing partial correlation analyses between NDVI and climatic elements (temperature, precipitation and cloud cover
Harris, T.; Schafer, R.; Hulslander, D.; O'Connor, A. S.; Wolfe, J.
2014-12-01
With the increasing diversity and long temporal record of satellite-based Earth imagery, we have new opportunities to better understand and predict Earth surface processes and activities. Satellite-based imagery is an increasingly important resource for analyzing changes in vegetation and land use, as well as monitoring the evolution of hazards and environmental conditions. A key requirement for exploitation of this imagery is visualization and extraction of multimodal data over space and time. Analysis of this imagery requires four primary components: 1) Assignment of acquisition time, spatial reference, and parameter descriptions, 2) Preprocessing including radiometric calibration, generation of derived parameters such as NDVI, and normalization to a common spatial grid, 3) Cataloging and access for discovering and extracting data through space, parameter, and time, and 4) Visualization techniques including animation, parameter-time, space-time, and space-frequency plots. Using ENVI, we will demonstrate how Landsat, MODIS, and Suomi NPP VIIRS data products can be prepared and visualized for exploring the evolution of processes and activities. Visual animation through a temporal stack of imagery is used to quickly understand trends in urban growth, vegetation, and land use. After exploring the temporal stack of images, spatio-temporal and periodic relationships are visualized using space-time and space-frequency representations of the data. Satellite-based imagery is a primary source of data for understanding global changes over time. To understand processes and activities, it is now increasingly important for data exploitation tools such as ENVI to easily extract data from multiple satellite-based sensors and visualize this multimodal data in both space and time.
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.
Time-varying vector fields and their flows
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.
Ultrasound Background Cancellation Based on Time-Varying Synthesis
Mijares-Chan, Jose Juan; Thomas, Gabriel
Fault detection based on ultrasonic imaging is a common technique used in non destructive testing. Correct interpretation of the scans requires training so that responses from unwanted echoes such as the background are discriminated from echoes corresponding to faults. Thus, enhancement in the form of displaying the desired echoes without the background response can offer an advantage for detection or further quantification of the fault. A fast way to achieve this goal and detect the background signatures and isolate them from the fault ones is to use time-frequency analysis. When time-varying filtering is used, the tendency is to recover the echoes coming from the faults. These echoes are reconstructed with no phase distortion because the system is linear and the scans c in which the background was cancelled in different specimens where faults were located very close to the surface buried within the initial pulse response and close to each other deeper in the specimen. This technique uses a single reference scan fast enough so that to finish the processing earlier than the time required to acquire a new scan.
Quantifying catchment-scale mixing and its effect on time-varying travel time distributions
Van Der Velde, Y.; Torfs, P. J J F; Van Der Zee, S. E A T M; Uijlenhoet, R.
2012-01-01
Travel time distributions are often used to characterize catchment discharge behavior, catchment vulnerability to pollution and pollutant loads from catchments to downstream waters. However, these distributions vary with time because they are a function of rainfall and evapotranspiration. It is
Etiology of phenotype switching strategy in time varying stochastic environment
Horvath, Denis; Brutovsky, Branislav
2016-11-01
In the paper, we present the two-state discrete-time Markovian model to study the impact of the two alternative switching strategies on the fitness of the population evolving in time varying environment. The first strategy, referred as the 'responsive switching', enables the cell to make transition into the state conferring to it higher fitness in the instant environment. If the alternative strategy, termed 'random switching' is applied, the cell undergoes transition into the new state not regarding the instant environment. Each strategy comes with the respective cost for its physical realization. Within the framework of evolutionary model, mutations occur as random events which change parameters of the probabilistic models corresponding to the respective switching strategies. Most of the general trends of population averages can be easily understood at the intuitive level, with a few exceptions related to the cases when too low mutation noise hampers population to follow rapid environmental changes. On the other hand, the more detailed study of the parameter distributions reveals much more complex structure than expected. The simulation results may help to understand, at the conceptual level, relation between the population heterogeneity and its environment that could find important implications in various areas, such as cancer therapy or development of risk diversifying strategies.
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.
Robust Adaptive OFDM with Diversity for Time-Varying Channels
Directory of Open Access Journals (Sweden)
Bala Erdem
2007-01-01
Full Text Available The performance of an orthogonal frequency-division multiplexing (OFDM system can be significantly increased by using adaptive modulation and transmit diversity. An accurate estimate of the channel, however, is required at the transmitter to realize this benefit. Due to the time-varying nature of the channel, this estimate may be outdated by the time it is used for detection. This results in a mismatch between the actual channel and its estimate as seen by the transmitter. In this paper, we investigate adaptive OFDM with transmit and receive diversities, and evaluate the detrimental effects of this channel mismatch. We also describe a robust scheme based on using past estimates of the channel. We show that the effects of the mismatch can be significantly reduced with a combination of diversity and multiple channel estimates. In addition, to reduce the amount of feedback, the subband approach is introduced where a common channel estimate for a number of subcarriers is fedback to the transmitter, and the effect of this method on the achievable rate is analyzed.
Perception of acoustically presented time series with varied intervals.
Wackermann, Jiří; Pacer, Jakob; Wittmann, Marc
2014-03-01
Data from three experiments on serial perception of temporal intervals in the supra-second domain are reported. Sequences of short acoustic signals ("pips") separated by periods of silence were presented to the observers. Two types of time series, geometric or alternating, were used, where the modulus 1+δ of the inter-pip series and the base duration Tb (range from 1.1 to 6s) were varied as independent parameters. The observers had to judge whether the series were accelerating, decelerating, or uniform (3 paradigm), or to distinguish regular from irregular sequences (2 paradigm). "Intervals of subjective uniformity" (isus) were obtained by fitting Gaussian psychometric functions to individual subjects' responses. Progression towards longer base durations (Tb=4.4 or 6s) shifts the isus towards negative δs, i.e., accelerating series. This finding is compatible with the phenomenon of "subjective shortening" of past temporal intervals, which is naturally accounted for by the lossy integration model of internal time representation. The opposite effect observed for short durations (Tb=1.1 or 1.5s) remains unexplained by the lossy integration model, and presents a challenge for further research. © 2013 Elsevier B.V. All rights reserved.
EEG correlates of time-varying BOLD functional connectivity
Chang, Catie; Liu, Zhongming; Chen, Michael C.; Liu, Xiao; Duyn, Jeff H.
2013-01-01
Recent resting-state fMRI studies have shown that the apparent functional connectivity (FC) between brain regions may undergo changes on time-scales of seconds to minutes, the basis and importance of which are largely unknown. Here, we examine the electrophysiological correlates of within-scan FC variations during a condition of eyes-closed rest. A sliding window analysis of simultaneous EEG-fMRI data was performed to examine whether temporal variations in coupling between three major networks (default mode; DMN, dorsal attention; DAN, and salience network; SN) are associated with temporal variations in mental state, as assessed from the amplitude of alpha and theta oscillations in the EEG. In our dataset, alpha power showed a significant inverse relationship with the strength of connectivity between DMN and DAN. In addition, alpha power covaried with the spatial extent of anticorrelation between DMN and DAN, with higher alpha power associated with larger anticorrelation extent. Results suggest an electrical signature of the time-varying FC between the DAN and DMN, potentially reflecting neural and state-dependent variations. PMID:23376790
Stability of stationary and time-varying nongyrotropic particle distributions
Directory of Open Access Journals (Sweden)
A. L. Brinca
Full Text Available The ubiquity of nongyrotropic particle populations in space plasmas warrants the study of their characteristics, in particular their stability. The unperturbed nongyrotropic distribution functions in homogeneous media without sources and sinks (closed phase space must be rotating and time-varying (TNG, whereas consideration of open phase spaces allows for the occurrence of homogeneous and stationary distributions (SNG. The free energy brought about by the introduction of gyrophase organization in a particle population can destabilize otherwise thoroughly stable magnetoplasmas (or, a fortiori, enhance pre-existing gyrotropic instabilities and feed intense wave growth both in TNG and SNG environments: The nongyrotropic (electron or ion species can originate unstable coupling among the gyrotropic characteristic waves. The stability properties of these two types of homogeneous nongyrotropy shall be contrasted for parallel (with respect to the ambient magnetic field and perpendicular propagation, and their potential role as wave activity sources shall be illustrated resorting to solutions of the appropriate dispersion equations and numerical simulations.
Key words. Space plasma physics (waves and instabilities · Magnetospheric physics (plasma waves and instabilities · Interplanetary physics (plasma waves and turbulence
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.
Innovation diffusion on time-varying activity driven networks
Rizzo, Alessandro; Porfiri, Maurizio
2016-01-01
Since its introduction in the 1960s, the theory of innovation diffusion has contributed to the advancement of several research fields, such as marketing management and consumer behavior. The 1969 seminal paper by Bass [F.M. Bass, Manag. Sci. 15, 215 (1969)] introduced a model of product growth for consumer durables, which has been extensively used to predict innovation diffusion across a range of applications. Here, we propose a novel approach to study innovation diffusion, where interactions among individuals are mediated by the dynamics of a time-varying network. Our approach is based on the Bass' model, and overcomes key limitations of previous studies, which assumed timescale separation between the individual dynamics and the evolution of the connectivity patterns. Thus, we do not hypothesize homogeneous mixing among individuals or the existence of a fixed interaction network. We formulate our approach in the framework of activity driven networks to enable the analysis of the concurrent evolution of the interaction and individual dynamics. Numerical simulations offer a systematic analysis of the model behavior and highlight the role of individual activity on market penetration when targeted advertisement campaigns are designed, or a competition between two different products takes place.
Opinion formation with time-varying bounded confidence.
Zhang, YunHong; Liu, QiPeng; Zhang, SiYing
2017-01-01
When individuals in social groups communicate with one another and are under the influence of neighbors' opinions, they typically revise their own opinions to adapt to such peer opinions. The individual threshold of bounded confidence will thus be affected by both a change in individual confidence and by neighbor influence. Individuals thus update their own opinions with new bounded confidence, while their updated opinions also influence their neighbors' opinions. Based on this reasoned factual assumption, we propose an opinion dynamics model with time-varying bounded confidence. A directed network is formed by the rule of the individual bounded confidence threshold. The threshold of individual bounded confidence involves both confidence variation and the in/out degree of the individual node. When the confidence variation is greater, an individual's confidence in persisting in his own opinion in interactions is weaker, and the individual is more likely to adopt neighbors' opinions. In networks, the in/out degree is determined by individual neighbors. Our main research involves the process of opinion evolution and the basic laws of opinion cluster formation. Group opinions converge exponentially to consensus with stable neighbors. An individual opinion evolution is determined by the average neighbor opinion effect strength. We also explore the conditions involved in forming a stable neighbor relationship and the influence of the confidence variation in the convergence of the threshold of bounded confidence. The results show that the influence on opinion evolution is greater with increased confidence variation.
Time-varying multiplex network: Intralayer and interlayer synchronization
Rakshit, Sarbendu; Majhi, Soumen; Bera, Bidesh K.; Sinha, Sudeshna; Ghosh, Dibakar
2017-12-01
A large class of engineered and natural systems, ranging from transportation networks to neuronal networks, are best represented by multiplex network architectures, namely a network composed of two or more different layers where the mutual interaction in each layer may differ from other layers. Here we consider a multiplex network where the intralayer coupling interactions are switched stochastically with a characteristic frequency. We explore the intralayer and interlayer synchronization of such a time-varying multiplex network. We find that the analytically derived necessary condition for intralayer and interlayer synchronization, obtained by the master stability function approach, is in excellent agreement with our numerical results. Interestingly, we clearly find that the higher frequency of switching links in the layers enhances both intralayer and interlayer synchrony, yielding larger windows of synchronization. Further, we quantify the resilience of synchronous states against random perturbations, using a global stability measure based on the concept of basin stability, and this reveals that intralayer coupling strength is most crucial for determining both intralayer and interlayer synchrony. Lastly, we investigate the robustness of interlayer synchronization against a progressive demultiplexing of the multiplex structure, and we find that for rapid switching of intralayer links, the interlayer synchronization persists even when a large number of interlayer nodes are disconnected.
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....
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...... 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 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....
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...
Input–Output Finite Time Stabilization of Time-Varying Impulsive Positive Hybrid Systems under MDADT
Lihong Yao; Junmin Li
2017-01-01
Time-varying impulsive positive hybrid systems based on finite state machines (FSMs) are considered in this paper, and the concept of input–output finite time stability (IO-FTS) is extended for this type of hybrid system. The IO-FTS analysis of the single linear time-varying system is given first. Then, the sufficient conditions of IO-FTS for hybrid systems are proposed via the mode-dependent average dwell time (MDADT) technique. Moreover, the output feedback controller which can stabilize th...
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......, 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....
Real-time access of large volume imagery through low-bandwidth links
Phillips, James; Grohs, Karl; Brower, Bernard; Kelly, Lawrence; Carlisle, Lewis; Pellechia, Matthew
2010-04-01
Providing current, time-sensitive imagery and geospatial information to deployed tactical military forces or first responders continues to be a challenge. This challenge is compounded through rapid increases in sensor collection volumes, both with larger arrays and higher temporal capture rates. Focusing on the needs of these military forces and first responders, ITT developed a system called AGILE (Advanced Geospatial Imagery Library Enterprise) Access as an innovative approach based on standard off-the-shelf techniques to solving this problem. The AGILE Access system is based on commercial software called Image Access Solutions (IAS) and incorporates standard JPEG 2000 processing. Our solution system is implemented in an accredited, deployable form, incorporating a suite of components, including an image database, a web-based search and discovery tool, and several software tools that act in concert to process, store, and disseminate imagery from airborne systems and commercial satellites. Currently, this solution is operational within the U.S. Government tactical infrastructure and supports disadvantaged imagery users in the field. This paper presents the features and benefits of this system to disadvantaged users as demonstrated in real-world operational environments.
MODIS Rapid Response: On-the-ground, real time applications of scientific satellite imagery
Schmaltz, J. E.; Riebeek, H.; Kendall, J. D.
2009-12-01
Since 2001, NASA’s MODIS Rapid Response Project has been providing fire detections and imagery in near real time for a wide variety of application users. The project web site provides MODIS imagery in true color and false color band combinations, a vegetation index, and land surface temperature - in both uncorrected swath format and geographically corrected subset regions within a few hours of data acquisition. The uncorrected swath format data is available worldwide. Geographically corrected subset images cover the world's land areas and adjoining waters, as well as the entire Arctic and Antarctic. Images are available twice daily, in the morning from the Terra satellite and in the afternoon from the Aqua satellite. A wide range of user communities access this information to get a rapid, 250 meter-resolution overview of ground conditions for fire management, crop and famine monitoring and forecasting, disaster response (floods, storms), dust and aerosol monitoring, aviation (tracking volcanic ash), monitoring sea ice conditions, environmental monitoring, and more. The scientific community uses imagery to locate phenomena of interest prior to ordering and processing data and to support the day-to-day planning of field campaigns. Rapid Response imagery is used extensively to support education and public outreach, both by NASA and other organizations, and is frequently found in newspapers, books, TV, and the web. California wildfires, 26 October 2003, Terra MODIS
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.
Stochastic skyline route planning under time-varying uncertainty
DEFF Research Database (Denmark)
Yang, Bin; Guo, Chenjuan; Jensen, Christian S.
2014-01-01
Different uses of a road network call for the consideration of different travel costs: in route planning, travel time and distance are typically considered, and green house gas (GHG) emissions are increasingly being considered. Further, travel costs such as travel time and GHG emissions are time...
Recurrence of particles in static and time varying oval billiards
Energy Technology Data Exchange (ETDEWEB)
Leonel, Edson D., E-mail: edleonel@rc.unesp.br [Departamento de Estatística, Matemática Aplicada e Computação – UNESP, Univ Estadual Paulista, Av. 24A, 1515, Bela Vista, 13506-900, Rio Claro, SP (Brazil); Dettmann, Carl P. [School of Mathematics, University of Bristol, Bristol BS8 1TW (United Kingdom)
2012-04-16
Dynamical properties are studied for escaping particles, injected through a hole in an oval billiard. The dynamics is considered for both static and periodically moving boundaries. For the static boundary, two different decays for the recurrence time distribution were observed after exponential decay for short times: A changeover to: (i) power law or; (ii) stretched exponential. Both slower decays are due to sticky orbits trapped near KAM islands, with the stretched exponential apparently associated with a single group of large islands. For time dependent case, survival probability leads to the conclusion that sticky orbits are less evident compared with the static case. -- Highlights: ► We consider properties of escaping particles in an oval billiard. ► Two different decays for the recurrence time distribution were observed following an exponential decay for short times: a power law or stretched exponential. ► Time-dependent boundaries suppress the slower decay at later times.
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...
Hashemi, Mahnaz; Ghaisari, Jafar; Askari, Javad
2015-07-01
This paper investigates an adaptive controller for a class of Multi Input Multi Output (MIMO) nonlinear systems with unknown parameters, bounded time delays and in the presence of unknown time varying actuator failures. The type of considered actuator failure is one in which some inputs may be stuck at some time varying values where the values, times and patterns of the failures are unknown. The proposed approach is constructed based on a backstepping design method. The boundedness of all the closed-loop signals is guaranteed and the tracking errors are proved to converge to a small neighborhood of the origin. The proposed approach is employed for a double inverted pendulums benchmark and a chemical reactor system. The simulation results show the effectiveness of the proposed method. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.
Input–Output Finite Time Stabilization of Time-Varying Impulsive Positive Hybrid Systems under MDADT
Directory of Open Access Journals (Sweden)
Lihong Yao
2017-11-01
Full Text Available Time-varying impulsive positive hybrid systems based on finite state machines (FSMs are considered in this paper, and the concept of input–output finite time stability (IO-FTS is extended for this type of hybrid system. The IO-FTS analysis of the single linear time-varying system is given first. Then, the sufficient conditions of IO-FTS for hybrid systems are proposed via the mode-dependent average dwell time (MDADT technique. Moreover, the output feedback controller which can stabilize the non-autonomous hybrid systems is derived, and the obtained results are presented in a linear programming form. Finally, a numerical example is provided to show the theoretical results.
Finite-Time Stabilization of Uncertain Switched Positive Linear Systems with Time-Varying Delays
Directory of Open Access Journals (Sweden)
Tianjian Yu
2015-01-01
Full Text Available This paper is concerned with finite-time stabilization (FTS analysis for a class of uncertain switched positive linear systems with time-varying delays. First, a new definition of finite-time boundedness (FTB is introduced for switched positive system. This definition can simplify FTS analysis. Taking interval and polytopic uncertainties into account, a robust state feedback controller is built such that the switched positive linear system is finite-time bounded. Finally, an example is employed to illustrate the validities of obtained results.
Constructing seasonally adjusted data with time-varying confidence intervals
S.J. Koopman (Siem Jan); Ph.H.B.F. Franses (Philip Hans)
2001-01-01
textabstractSeasonal adjustment methods transform observed time series data into estimated data, where these estimated data are constructed such that they show no or almost no seasonal variation. An advantage of model-based methods is that these can provide confidence intervals around the seasonally
Time-varying determinants of long-run house prices
Dröes, M.; van de Minne, A.
2015-01-01
The determinants of house prices change over time. This paper documents these changes using long-run historical data from Amsterdam from the year 1825 onwards. Because many houses in Amsterdam have survived until this day, we can construct a long-run repeat sales index and examine its determinants.
Multireceiver Acoustic Communications in Time-Varying Environments
2014-06-01
Water currents and tidal currents create instability in the position of nodes, which can make the topology dynamic. Multipath propagation causes time...analysis of underwater acoustic MIMO communications,”OCEANS, Sydney, NSW, 2010, pp. 1–8. [9] Wines lab (2013). Wireless networks and embedded
Poverty index with time-varying consumption and income distributions
Chattopadhyay, Amit K.; Kumar, T. Krishna; Mallick, Sushanta K.
2017-03-01
Starting from a stochastic agent-based model to represent market exchange in a developing economy, we study time variations of the probability density function of income with simultaneous variation of the consumption deprivation (CD), where CD represents the shortfall in consumption from the saturation level of an essential commodity, cereal. Together, these two models combine income-expenditure-based market dynamics with time variations in consumption due to income. In this new unified theoretical structure, exchange of trade in assets is only allowed when the income exceeds consumption-deprivation while CD itself is endogenously obtained from a separate kinetic model. Our results reveal that the nature of time variation of the CD function leads to a downward trend in the threshold level of consumption of basic necessities, suggesting a possible dietary transition in terms of lower saturation level of food-grain consumption, possibly through an improvement in the level of living. The new poverty index, defined as CD, is amenable to approximate probabilistic prediction within a short time horizon. A major achievement of this work is the intrinsic independence of the poverty index from an exogenous poverty line, making it more objective for policy formulation as opposed to existing poverty indices in the literature.
Time-varying properties of renal autoregulatory mechanisms
DEFF Research Database (Denmark)
Zou, Rui; Cupples, Will A; Yip, K P
2002-01-01
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...
Network Coded Cooperation Over Time-Varying Channels
DEFF Research Database (Denmark)
Khamfroush, Hana; Roetter, Daniel Enrique Lucani; Barros, João
2014-01-01
for WiFi using Aalborg University’s Raspberry Pi testbed. We compare our results with random linear network coding (RLNC) broadcasting schemes showing that our heuristics can provide up to 2x gains in completion time and up to 4x gains in terms of reliably serviced data packets....
Agile architecture to enable real-time tactical access to persistent imagery surveillance collection
Rajan, Sreekanth D.; Kasner, James H.; Loya, Elena C.
2004-08-01
This paper presents the constructs for a transformational paradigm within a standards-based architectural framework, which enables extremely quick and accurate visualization of large imagery sets directly from airborne intelligence and surveillance collection assets. The architecture we present handles the dissemination and "on-demand" visualization of JPEG2000 encoded geospatial imagery while providing dramatic improvements in reconnaissance and surveillance operations where low-latency access and time-critical visualization of targets are of substantial importance. This innovative framework, known as the "advanced wavelet architecture" (AWA), has been developed using open standards and nonproprietary formats, within the Commercial and Government Systems Division of Eastman Kodak Company. Numerous software and hardware applications have been developed as a result of the AWA research and development activities.
Template-Based Estimation of Time-Varying Tempo
Directory of Open Access Journals (Sweden)
Peeters Geoffroy
2007-01-01
Full Text Available We present a novel approach to automatic estimation of tempo over time. This method aims at detecting tempo at the tactus level for percussive and nonpercussive audio. The front-end of our system is based on a proposed reassigned spectral energy flux for the detection of musical events. The dominant periodicities of this flux are estimated by a proposed combination of discrete Fourier transform and frequency-mapped autocorrelation function. The most likely meter, beat, and tatum over time are then estimated jointly using proposed meter/beat subdivision templates and a Viterbi decoding algorithm. The performances of our system have been evaluated on four different test sets among which three were used during the ISMIR 2004 tempo induction contest. The performances obtained are close to the best results of this contest.
Runaway domain wall and space-time varying α
International Nuclear Information System (INIS)
Chiba, Takeshi; Yamaguchi, Masahide
2011-01-01
Recently spatial as well as temporal variations of the fine structure constant α have been reported. We show that a ''runaway domain wall , which arises for the scalar field potential without minima, can account for such variations simultaneously. The time variation is induced by a runaway potential and the spatial variation is induced by the formation of a domain wall. The model is consistent with the current cosmological data and can be tested by the future experiments to test the equivalence principle
Acute Exposure Guideline Levels (AEGLs) for Time Varying Toxic Plumes
2014-09-12
loading rates between the density values given as Arho(b-1,k) and Arho(b,k). The line labeled ‘ extrap .’above b = 1 in Table 3 records the derived...exposure times and an inverse quadratic law for densities lower than 8.26 mg/m3. The line labeled ‘ extrap .’ at the bottom of the table gives the...6 (labeled “ extrap .” above) are simply duplicated from the adjacent band b = 5. This exponent is also used to define the lowest density value Brho
Time-varying effects in the analysis of customer loyalty
DEFF Research Database (Denmark)
Guillen, Montserrat; Perch Nielsen, Jens; Scheike, Thomas
2011-01-01
are fixed over time, but rather that the parameters may fluctuate. Our results suggest that the kind of contracts held by customers and the concurrence of an external competitor strongly influence customer loyalty right after that cancellation, but those factors become much less significant some months......Insurance customers usually hold more than one contract with the same insurer. A generalization of classical survival analysis methods is used to examine the risk of losing a customer once an initial insurance policy cancellation has occurred. This method does not assume that the model parameters...... later. Our study shows how predictions of the probability of losing a customer can be readjusted and improves the way companies manage business risk....
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.
Discrete-time recurrent neural networks with time-varying delays: Exponential stability analysis
Liu, Yurong; Wang, Zidong; Serrano, Alan; Liu, Xiaohui
2007-03-01
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.
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
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.
USGS Provision of Near Real Time Remotely Sensed Imagery for Emergency Response
Jones, B. K.
2014-12-01
The use of remotely sensed imagery in the aftermath of a disaster can have an important impact on the effectiveness of the response for many types of disasters such as floods, earthquakes, volcanic eruptions, landslides, and other natural or human-induced disasters. Ideally, responders in areas that are commonly affected by disasters would have access to archived remote sensing imagery plus the ability to easily obtain the new post event data products. The cost of obtaining and storing the data and the lack of trained professionals who can process the data into a mapping product oftentimes prevent this from happening. USGS Emergency Operations provides remote sensing and geospatial support to emergency managers by providing access to satellite images from numerous domestic and international space agencies including those affiliated with the International Charter Space and Major Disasters and their space-based assets and by hosting and distributing thousands of near real time event related images and map products through the Hazards Data Distribution System (HDDS). These data may include digital elevation models, hydrographic models, base satellite images, vector data layers such as roads, aerial photographs, and other pre and post disaster data. These layers are incorporated into a Web-based browser and data delivery service, the Hazards Data Distribution System (HDDS). The HDDS can be made accessible either to the general public or to specific response agencies. The HDDS concept anticipates customer requirements and provides rapid delivery of data and services. This presentation will provide an overview of remotely sensed imagery that is currently available to support emergency response operations and examples of products that have been created for past events that have provided near real time situational awareness for responding agencies.
Shattock, Andrew J; Kerr, Cliff C; Stuart, Robyn M; Masaki, Emiko; Fraser, Nicole; Benedikt, Clemens; Gorgens, Marelize; Wilson, David P; Gray, Richard T
2016-01-01
International investment in the response to HIV and AIDS has plateaued and its future level is uncertain. With many countries committed to ending the epidemic, it is essential to allocate available resources efficiently over different response periods to maximize impact. The objective of this study is to propose a technique to determine the optimal allocation of funds over time across a set of HIV programmes to achieve desirable health outcomes. We developed a technique to determine the optimal time-varying allocation of funds (1) when the future annual HIV budget is pre-defined and (2) when the total budget over a period is pre-defined, but the year-on-year budget is to be optimally determined. We use this methodology with Optima, an HIV transmission model that uses non-linear relationships between programme spending and associated programmatic outcomes to quantify the expected epidemiological impact of spending. We apply these methods to data collected from Zambia to determine the optimal distribution of resources to fund the right programmes, for the right people, at the right time. Considering realistic implementation and ethical constraints, we estimate that the optimal time-varying redistribution of the 2014 Zambian HIV budget between 2015 and 2025 will lead to a 7.6% (7.3% to 7.8%) decrease in cumulative new HIV infections compared with a baseline scenario where programme allocations remain at 2014 levels. This compares to a 5.1% (4.6% to 5.6%) reduction in new infections using an optimal allocation with constant programme spending that recommends unrealistic programmatic changes. Contrasting priorities for programme funding arise when assessing outcomes for a five-year funding period over 5-, 10- and 20-year time horizons. Countries increasingly face the need to do more with the resources available. The methodology presented here can aid decision-makers in planning as to when to expand or contract programmes and to which coverage levels to maximize impact.
Improving EEG-Based Motor Imagery Classification for Real-Time Applications Using the QSA Method
Batres-Mendoza, Patricia; Guerra-Hernandez, Erick I.; Almanza-Ojeda, Dora L.; Montoro-Sanjose, Carlos R.
2017-01-01
We present an improvement to the quaternion-based signal analysis (QSA) technique to extract electroencephalography (EEG) signal features with a view to developing real-time applications, particularly in motor imagery (IM) cognitive processes. The proposed methodology (iQSA, improved QSA) extracts features such as the average, variance, homogeneity, and contrast of EEG signals related to motor imagery in a more efficient manner (i.e., by reducing the number of samples needed to classify the signal and improving the classification percentage) compared to the original QSA technique. Specifically, we can sample the signal in variable time periods (from 0.5 s to 3 s, in half-a-second intervals) to determine the relationship between the number of samples and their effectiveness in classifying signals. In addition, to strengthen the classification process a number of boosting-technique-based decision trees were implemented. The results show an 82.30% accuracy rate for 0.5 s samples and 73.16% for 3 s samples. This is a significant improvement compared to the original QSA technique that offered results from 33.31% to 40.82% without sampling window and from 33.44% to 41.07% with sampling window, respectively. We can thus conclude that iQSA is better suited to develop real-time applications. PMID:29348744
Zhang, Xiaoyong; Zhang, Zhijie; Chang, Yuguang; Chen, Zhengchao
2015-12-01
Accurate data on the spatial distribution and potential growth estimation of human population are playing pivotal role in addressing and mitigating heavy lose caused by earthquake. Traditional demographic data is limited in its spatial resolution and is extremely hard to update. With the accessibility of massive DMSP/OLS night time imagery, it is possible to model population distribution at the county level across China. In order to compare and improve the continuity and consistency of time-series DMSP night-time satellite imagery obtained by different satellites in same year or different years by the same satellite from 2002-2010, normalized method was deployed for the inter-correction among imageries. And we referred to the reference F162007 Jixi city, whose social-economic has been relatively stable. Through binomial model, with average R2 0.90, then derived the correction factor of each year. The normalization obviously improved consistency comparing to previous data, which enhanced the correspondent accuracy of model. Then conducted the model of population density between average night-time light intensity in eight-economic districts. According to the two parameters variation law of consecutive years, established the prediction model of next following years with R2of slope and constant typically 0.85 to 0.95 in different regions. To validate the model, taking the year of 2005 as example, retrieved quantitatively population distribution in per square kilometer based on the model, then compared the results to the statistical data based on census, the difference of the result is acceptable. In summary, the estimation model facilitates the quick estimation and prediction in relieving the damage to people, which is significant in decision-making.
Modeling hyporheic exchange and in-stream transport with time-varying transit time distributions
Ball, A.; Harman, C. J.; Ward, A. S.
2014-12-01
Transit time distributions (TTD) are used to understand in-stream transport and exchange with the hyporheic zone by quantifying the probability of water (and of dissolved material) taking time T to traverse the stream reach control volume. However, many studies using this method assume a TTD that is time-invariant, despite the time-variability of the streamflow. Others assume that storage is 'randomly sampled' or 'well-mixed' with a fixed volume or fixed exchange rate. Here we present a formulation for a time-variable TTD that relaxes both the time-invariant and 'randomly sampled' assumptions and only requires a few parameters. The framework is applied to transient storage, representing some combination of in-stream and hyporheic storage, along a stream reach. This approach does not assume that hyporheic and dead-zone storage is fixed or temporally-invariant, and allows for these stores to be sampled in more physically representative ways determined by the system itself. Instead of using probability distributions of age, probability distributions of storage (ranked by age) called Ω functions are used to describe how the off-stream storage is sampled in the outflow. Here the Ω function approach is used to describe hyporheic exchange during diurnal fluctuations in streamflow in a gaining reach of the H.J. Andrews Experimental Forest. The breakthrough curves of salt slugs injected four hours apart over a 28-hour period show a systematic variation in transit time distribution. This new approach allows us to relate these salt slug TTDs to a corresponding time-variation in the Ω function, which can then be related to changes in in-stream storage and hyporheic zone mobilization under varying flow conditions. Thus, we can gain insights into how channel storage and hyporheic exchange are changing through time without having to specify difficult to measure or unmeasurable quantities of our system, such as total storage.
Nguyen, Hoai-Nam
2014-01-01
A comprehensive development of interpolating control, this monograph demonstrates the reduced computational complexity of a ground-breaking technique compared with the established model predictive control. The text deals with the regulation problem for linear, time-invariant, discrete-time uncertain dynamical systems having polyhedral state and control constraints, with and without disturbances, and under state or output feedback. For output feedback a non-minimal state-space representation is used with old inputs and outputs as state variables. Constrained Control of Uncertain, Time-Varying, Discrete-time Systems details interpolating control in both its implicit and explicit forms. In the former at most two linear-programming or one quadratic-programming problem are solved on-line at each sampling instant to yield the value of the control variable. In the latter the control law is shown to be piecewise affine in the state, and so the state space is partitioned into polyhedral cells so that at each sampling ...
Real-time changes in corticospinal excitability related to motor imagery of a force control task
DEFF Research Database (Denmark)
Tatemoto, Tsuyoshi; Tsuchiya, Junko; Numata, Atsuki
2017-01-01
Objective To investigate real-time excitability changes in corticospinal pathways related to motor imagery in a changing force control task, using transcranial magnetic stimulation (TMS). Methods Ten healthy volunteers learnt to control the contractile force of isometric right wrist dorsiflexion...... in order to track an on-screen sine wave form. Participants performed the trained task 40 times with actual muscle contraction in order to construct the motor image. They were then instructed to execute the task without actual muscle contraction, but by imagining contraction of the right wrist...... (Increasing phase), the peak value of the sine wave, during the gradual reduction (Decreasing phase), and after completion of the task. The MEP ratio, as the ratio of imaged MEPs to resting-state, was compared between pre- and post-training at each time point. Results In the ECR muscle, the MEP ratio...
Synchronization stability of general complex dynamical networks with time-varying delays
International Nuclear Information System (INIS)
Li Kun; Guan Shuguang; Gong Xiaofeng; Lai, C.-H.
2008-01-01
The synchronization problem of some general complex dynamical networks with time-varying delays is investigated. Both time-varying delays in the network couplings and time-varying delays in the dynamical nodes are considered. The novel delay-dependent criteria in terms of linear matrix inequalities (LMI) are derived based on free-weighting matrices technique and appropriate Lyapunov functional proposed recently. Numerical examples are given to illustrate the effectiveness and advantage of the proposed synchronization criteria
Panel Discussion: Near Real Time Imagery Intelligence How Will We Do It?
Andraitis, Arthur A.; Crane, Alfred C.; Daniels, George; Graham, Johnny; LaGesse, Francis R.
1987-02-01
This afternoon's panel discussion will address near real time imagery and intelligence--how will we do it? Our moderator is Arthur Andraitis, a consultant in intelligence reconnaissance systems and international marketing. He was commissioned in the United States Air Force out of the University of Idaho, and entered the Air Force in 1955 where he became an Image Intelligence Officer serving in a variety of intelligence and reconnaisance related assignments, including two tours each in Asia and Europe supporting tactical theater and national level operations. He also suffered through two Pentagon tours--one as Branch Chief of the Imagery Branch for the Assistant Chief of Staff for Intelligence. He was the U. S. National Coordinator for two NATO intelligence and reconnaissance panels, and served several assignments in support of special operations, which included a year with the special forces in Viet Nam where he flew many missions in L-19s, 01 and assault helicopters. He has been an advisor on intelligence and reconnaissance matters to several foreign countries. In 1978 he retired from the United States Air Force, went to work for Itek, and then became an independent consultant in intelligence and reconaissance systems. I would like to introduce Art Andraitis.
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.
Identification of time-varying nonlinear systems using differential evolution algorithm
DEFF Research Database (Denmark)
Perisic, Nevena; Green, Peter L; Worden, Keith
2013-01-01
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...
Exponential stability of nonlinear time-varying differential equations and applications
Directory of Open Access Journals (Sweden)
N. M. Linh
2001-05-01
Full Text Available In this paper, we give sufficient conditions for the exponential stability of a class of nonlinear time-varying differential equations. We use the Lyapunov method with functions that are not necessarily differentiable; hence we extend previous results. We also provide an application to exponential stability for nonlinear time-varying control systems.
Real-time person detection in low-resolution thermal infrared imagery with MSER and CNNs
Herrmann, Christian; Müller, Thomas; Willersinn, Dieter; Beyerer, Jürgen
2016-10-01
LWIR imagery applications and is capable of fast classification. Evaluation on several different LWIR person detection datasets shows an error rate reduction of up to 80 percent compared to previous approaches consisting of MSER, local image descriptors and a standard classifier such as an SVM or boosted decision trees. Further time measurements show that the proposed processing chain is capable of real-time person detection in LWIR camera streams.
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.
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
Krishnan, M.; Bhowmik, B.; Hazra, B.; Pakrashi, V.
2018-02-01
In this paper, a novel baseline free approach for continuous online damage detection of multi degree of freedom vibrating structures using Recursive Principal Component Analysis (RPCA) in conjunction with Time Varying Auto-Regressive Modeling (TVAR) is proposed. In this method, the acceleration data is used to obtain recursive proper orthogonal components online using rank-one perturbation method, followed by TVAR modeling of the first transformed response, to detect the change in the dynamic behavior of the vibrating system from its pristine state to contiguous linear/non-linear-states that indicate damage. Most of the works available in the literature deal with algorithms that require windowing of the gathered data owing to their data-driven nature which renders them ineffective for online implementation. Algorithms focussed on mathematically consistent recursive techniques in a rigorous theoretical framework of structural damage detection is missing, which motivates the development of the present framework that is amenable for online implementation which could be utilized along with suite experimental and numerical investigations. The RPCA algorithm iterates the eigenvector and eigenvalue estimates for sample covariance matrices and new data point at each successive time instants, using the rank-one perturbation method. TVAR modeling on the principal component explaining maximum variance is utilized and the damage is identified by tracking the TVAR coefficients. This eliminates the need for offline post processing and facilitates online damage detection especially when applied to streaming data without requiring any baseline data. Numerical simulations performed on a 5-dof nonlinear system under white noise excitation and El Centro (also known as 1940 Imperial Valley earthquake) excitation, for different damage scenarios, demonstrate the robustness of the proposed algorithm. The method is further validated on results obtained from case studies involving
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.
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.
The stability of multichannel sound systems with time-varying mixing matrices.
Schlecht, Sebastian J; Habets, Emanuël A P
2016-07-01
Various time-varying algorithms have been applied in multichannel sound systems to improve the system's stability and, among these, frequency shifting has been demonstrated to reach the maximum stability improvement achievable by time-variation in general. However, the modulation artifacts have been found to diminish the gain improvement unusable for a higher number of channels and high-quality applications such as music reproduction. This paper proposes alternatively time-varying mixing matrices, which is an efficient algorithm corresponding to symmetric up and down frequency shifting. It is shown with a statistical approach that time-varying mixing matrices can as well achieve maximum stability improvement for a higher number of channels. A listening test demonstrates the improved quality of time-varying mixing matrices over frequency shifting.
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.
Timing Is Important: Unmanned Aircraft vs. Satellite Imagery in Plant Invasion Monitoring
Directory of Open Access Journals (Sweden)
Jana Müllerová
2017-05-01
Full Text Available The rapid spread of invasive plants makes their management increasingly difficult. Remote sensing offers a means of fast and efficient monitoring, but still the optimal methodologies remain to be defined. The seasonal dynamics and spectral characteristics of the target invasive species are important factors, since, at certain time of the vegetation season (e.g., at flowering or senescing, plants are often more distinct (or more visible beneath the canopy. Our aim was to establish fast, repeatable and a cost-efficient, computer-assisted method applicable over larger areas, to reduce the costs of extensive field campaigns. To achieve this goal, we examined how the timing of monitoring affects the detection of noxious plant invaders in Central Europe, using two model herbaceous species with markedly different phenological, structural, and spectral characteristics. They are giant hogweed (Heracleum mantegazzianum, a species with very distinct flowering phase, and the less distinct knotweeds (Fallopia japonica, F. sachalinensis, and their hybrid F. × bohemica. The variety of data generated, such as imagery from purposely-designed, unmanned aircraft vehicle (UAV, and VHR satellite, and aerial color orthophotos enabled us to assess the effects of spectral, spatial, and temporal resolution (i.e., the target species' phenological state for successful recognition. The demands for both spatial and spectral resolution depended largely on the target plant species. In the case that a species was sampled at the most distinct phenological phase, high accuracy was achieved even with lower spectral resolution of our low-cost UAV. This demonstrates that proper timing can to some extent compensate for the lower spectral resolution. The results of our study could serve as a basis for identifying priorities for management, targeted at localities with the greatest risk of invasive species' spread and, once eradicated, to monitor over time any return. The best mapping
Timing does matter: examining imagery's impact on the temporal origins of false beliefs.
Bays, Rebecca B; Foley, Mary Ann; Zabrucky, Karen M
2013-01-01
In the current study imagination inflation effects were revisited, giving special attention to decreases in confidence ratings following imagery. Reexamining false beliefs, 151 participants were instructed to rate their confidence that they experienced specific childhood events before and after imagery. No significant imagery effects emerged when examining differences in confidence ratings. However, imagery differentially enhanced (26.27%) and diminished (15.45%) belief ratings for specific events. Content analysis of participants' imagery descriptions revealed that only diminished false beliefs were distinguishable from genuine belief accounts, containing less affective and contextual detail as well as fewer words, but remaining comparable in the presence of cognitive operations. These findings suggest that deflation effects provide a route to studying the potentially positive impact of imagery on false beliefs. Because diminished false beliefs cannot be mistaken as veridical memories reconstructed during imagery, they are less subject to criticisms of traditional false belief studies using self-report measures. Copyright © 2012 Elsevier B.V. All rights reserved.
Lee, Catherine; Betensky, Rebecca A
2018-03-15
Relating time-varying biomarkers of Alzheimer's disease to time-to-event using a Cox model is complicated by the fact that Alzheimer's disease biomarkers are sparsely collected, typically only at study entry; this is problematic since Cox regression with time-varying covariates requires observation of the covariate process at all failure times. The analysis might be simplified by using study entry as the time origin and treating the time-varying covariate measured at study entry as a fixed baseline covariate. In this paper, we first derive conditions under which using an incorrect time origin of study entry results in consistent estimation of regression parameters when the time-varying covariate is continuous and fully observed. We then derive conditions under which treating the time-varying covariate as fixed at study entry results in consistent estimation. We provide methods for estimating the regression parameter when a functional form can be assumed for the time-varying biomarker, which is measured only at study entry. We demonstrate our analytical results in a simulation study and apply our methods to data from the Rush Religious Orders Study and Memory and Aging Project and data from the Alzheimer's Disease Neuroimaging Initiative. Copyright © 2017 John Wiley & Sons, Ltd.
DEFF Research Database (Denmark)
Chon, Ki H; Zhong, Yuru; Moore, Leon C
2008-01-01
The extent to which renal blood flow dynamics vary in time and whether such variation contributes substantively to dynamic complexity have emerged as important questions. Data from Sprague-Dawley rats (SDR) and spontaneously hypertensive rats (SHR) were analyzed by time-varying transfer functions...... (TVTF) and time-varying coherence functions (TVCF). Both TVTF and TVCF allow quantification of nonstationarity in the frequency ranges associated with the autoregulatory mechanisms. TVTF analysis shows that autoregulatory gain in SDR and SHR varies in time and that SHR exhibit significantly more...... nonstationarity than SDR. TVTF gain in the frequency range associated with the myogenic mechanism was significantly higher in SDR than in SHR, but no statistical difference was found with tubuloglomerular (TGF) gain. Furthermore, TVCF analysis revealed that the coherence in both strains is significantly...
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.
Browning, D. M.; Tweedie, C. E.; Rango, A.
2013-12-01
Spatially extensive grasslands and savannas in arid and semi-arid ecosystems (i.e., rangelands) require cost-effective, accurate, and consistent approaches for monitoring plant phenology. Remotely sensed imagery offers these capabilities; however contributions of exposed soil due to modest vegetation cover, susceptibility of vegetation to drought, and lack of robust scaling relationships challenge biophysical retrievals using moderate- and coarse-resolution satellite imagery. To evaluate methods for characterizing plant phenology of common rangeland species and to link field measurements to remotely sensed metrics of land surface phenology, we devised a hierarchical study spanning multiple spatial scales. We collect data using weekly standardized field observations on focal plants, daily phenocam estimates of vegetation greenness, and very high spatial resolution imagery from an Unmanned Aerial System (UAS) throughout the growing season. Field observations of phenological condition and vegetation cover serve to verify phenocam greenness indices along with indices derived from time series UAS imagery. UAS imagery is classified using object-oriented image analysis to identify species-specific image objects for which greenness indices are derived. Species-specific image objects facilitate comparisons with phenocam greenness indices and scaling spectral responses to footprints of Landsat and MODIS pixels. Phenocam greenness curves indicated rapid canopy development for the widespread deciduous shrub Prosopis glandulosa over 14 (in April 2012) to 16 (in May 2013) days. The modest peak in greenness for the dominant perennial grass Bouteloua eriopoda occurred in October 2012 following peak summer rainfall. Weekly field estimates of canopy development closely coincided with daily patterns in initial growth and senescence for both species. Field observations improve the precision of the timing of phenophase transitions relative to inflection points calculated from phenocam
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)
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 MULTIPRODUCT HEDGE RATIO ESTIMATION IN THE SOYBEAN COMPLEX: A SIMPLIFIED APPROACH
Manfredo, Mark R.; Garcia, Philip; Leuthold, Raymond M.
2000-01-01
In developing optimal hedge ratios for the soybean processing margin, many authors have illustrated the importance of considering the interactions between the cash and futures prices for soybeans, soybean oil, and soybean meal. Conditional as well as time-varying hedge ratios have been examined, but in the case of multiproduct time-varying hedge ratios, the difficulty in estimation has been found to often outweigh any improvement in hedging effectiveness. This research examines the hedging ef...
Balog, J. D.; Box, J. E.; Pfeffer, W. T.; Hood, E. W.; Fagre, D. B.; Anker, C.; O'Neel, S.
2010-12-01
The Extreme Ice Survey (EIS) uses time-lapse photography, conventional photography, and video to document rapid change in the Earth's glacial ice. The EIS team currently has 38 time-lapse cameras at sites in Greenland, Iceland, Alaska, the Rocky Mountains and Nepal. EIS supplements this ongoing record with annual repeat photography in British Columbia, Iceland, the Alps, and Bolivia. EIS imagery supplies basic knowledge in glacier dynamics to the science community, as well as compelling, engaging narratives to the general public about the immediacy of the Anthropocene and climate change. Visual materials from EIS have impacted more than 150 million people, ranging from White House staff, the U. S. Congress and government agency officials to globally influential corporate officers and all age strata of the general public. Media products include a National Geographic/NOVA special, two National Geographic magazine articles, a feature in Parade magazine (circulation 71 million), and numerous presentations on CNN, NBC, BBC and National Public Radio. Columbia Glacier, Alaska, June 2006, May 2007, June 2008 terminus indicated.
Li, Jing; Zipper, Carl E; Donovan, Patricia F; Wynne, Randolph H; Oliphant, Adam J
2015-09-01
Surface mining disturbances have attracted attention globally due to extensive influence on topography, land use, ecosystems, and human populations in mineral-rich regions. We analyzed a time series of Landsat satellite imagery to produce a 28-year disturbance history for surface coal mining in a segment of eastern USA's central Appalachian coalfield, southwestern Virginia. The method was developed and applied as a three-step sequence: vegetation index selection, persistent vegetation identification, and mined-land delineation by year of disturbance. The overall classification accuracy and kappa coefficient were 0.9350 and 0.9252, respectively. Most surface coal mines were identified correctly by location and by time of initial disturbance. More than 8 % of southwestern Virginia's >4000-km(2) coalfield area was disturbed by surface coal mining over the 28-year period. Approximately 19.5 % of the Appalachian coalfield surface within the most intensively mined county (Wise County) has been disturbed by mining. Mining disturbances expanded steadily and progressively over the study period. Information generated can be applied to gain further insight concerning mining influences on ecosystems and other essential environmental features.
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...
Jia, Xingyu; Liu, Zhigang; Tao, Long; Deng, Zhongwen
2017-10-16
Frequency scanning interferometry (FSI) with a single external cavity diode laser (ECDL) and time-invariant Kalman filtering is an effective technique for measuring the distance of a dynamic target. However, due to the hysteresis of the piezoelectric ceramic transducer (PZT) actuator in the ECDL, the optical frequency sweeps of the ECDL exhibit different behaviors, depending on whether the frequency is increasing or decreasing. Consequently, the model parameters of Kalman filter appear time varying in each iteration, which produces state estimation errors with time-invariant filtering. To address this, in this paper, a time-varying Kalman filter is proposed to model the instantaneous movement of a target relative to the different optical frequency tuning durations of the ECDL. The combination of the FSI method with the time-varying Kalman filter was theoretically analyzed, and the simulation and experimental results show the proposed method greatly improves the performance of dynamic FSI measurements.
Vector-field statistics for the analysis of time varying clinical gait data.
Donnelly, C J; Alexander, C; Pataky, T C; Stannage, K; Reid, S; Robinson, M A
2017-01-01
In clinical settings, the time varying analysis of gait data relies heavily on the experience of the individual(s) assessing these biological signals. Though three dimensional kinematics are recognised as time varying waveforms (1D), exploratory statistical analysis of these data are commonly carried out with multiple discrete or 0D dependent variables. In the absence of an a priori 0D hypothesis, clinicians are at risk of making type I and II errors in their analyis of time varying gait signatures in the event statistics are used in concert with prefered subjective clinical assesment methods. The aim of this communication was to determine if vector field waveform statistics were capable of providing quantitative corroboration to practically significant differences in time varying gait signatures as determined by two clinically trained gait experts. The case study was a left hemiplegic Cerebral Palsy (GMFCS I) gait patient following a botulinum toxin (BoNT-A) injection to their left gastrocnemius muscle. When comparing subjective clinical gait assessments between two testers, they were in agreement with each other for 61% of the joint degrees of freedom and phases of motion analysed. For tester 1 and tester 2, they were in agreement with the vector-field analysis for 78% and 53% of the kinematic variables analysed. When the subjective analyses of tester 1 and tester 2 were pooled together and then compared to the vector-field analysis, they were in agreement for 83% of the time varying kinematic variables analysed. These outcomes demonstrate that in principle, vector-field statistics corroborates with what a team of clinical gait experts would classify as practically meaningful pre- versus post time varying kinematic differences. The potential for vector-field statistics to be used as a useful clinical tool for the objective analysis of time varying clinical gait data is established. Future research is recommended to assess the usefulness of vector-field analyses
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 Biased Proportional Guidance with Seeker’s Field-of-View Limit
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 ...
Sojourn time asymptotics in Processor Sharing queues with varying service rate
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
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.
Resting-state time-varying analysis reveals aberrant variations of functional connectivity in autism
Directory of Open Access Journals (Sweden)
Zhijun Yao
2016-09-01
Full Text Available Recently, studies based on time-varying functional connectivity have unveiled brain states diversity in some neuropsychiatric disorders, such as schizophrenia and major depressive disorder. However, time-varying functional connectivity analysis of resting-state functional Magnetic Resonance Imaging (fMRI have been rarely performed on the Autism Spectrum Disorder (ASD. Hence, we performed time-varying connectivity analysis on resting-state fMRI data to investigate brain states mutation in ASD children. ASD showed an imbalance of connectivity state and aberrant ratio of connectivity with different strengths in the whole brain network, and decreased connectivity associated precuneus/posterior cingulate gyrus with medial prefrontal gyrus in default mode network. As compared to typical development children, weak relevance condition (the strength of a large number of connectivities in the state was less than means minus standard deviation of all connection strength was maintained for a longer time between brain areas of ASD children, and ratios of weak connectivity in brain states varied dramatically in the ASD. In the ASD, the abnormal brain state might be related to repetitive behaviors and stereotypical interests, and macroscopically reflect disruption of gamma-aminobutyric acid at the cellular level. The detection of brain states based on time-varying functional connectivity analysis of resting-state fMRI might be conducive for diagnosis and early intervention of ASD before obvious clinical symptoms.
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.
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.
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.
Global dissipativity analysis on uncertain neural networks with mixed time-varying delays
Song, Qiankun; Cao, Jinde
2008-12-01
In this paper, the problems of global dissipativity and global exponential dissipativity are investigated for uncertain neural networks with discrete time-varying delay and distributed time-varying delay as well as general activation functions. By constructing appropriate Lyapunov-Krasovskii functionals and employing Newton-Leibniz formulation and linear matrix inequality (LMI) technique, several new criteria for checking the global dissipativity and global exponential dissipativity of the addressed neural networks are established in terms of LMI, which can be checked numerically using the effective LMI toolbox in MATLAB. Illustrated examples are given to show the effectiveness and decreased conservatism of the proposed criteria in comparison with some existing results. It is noteworthy that the traditional assumptions on the differentiability of the time-varying delays and the boundedness of its derivative are removed.
Dual Extended Kalman Filter for the Identification of Time-Varying Human Manual Control Behavior
Popovici, Alexandru; Zaal, Peter M. T.; Pool, Daan M.
2017-01-01
A Dual Extended Kalman Filter was implemented for the identification of time-varying human manual control behavior. Two filters that run concurrently were used, a state filter that estimates the equalization dynamics, and a parameter filter that estimates the neuromuscular parameters and time delay. Time-varying parameters were modeled as a random walk. The filter successfully estimated time-varying human control behavior in both simulated and experimental data. Simple guidelines are proposed for the tuning of the process and measurement covariance matrices and the initial parameter estimates. The tuning was performed on simulation data, and when applied on experimental data, only an increase in measurement process noise power was required in order for the filter to converge and estimate all parameters. A sensitivity analysis to initial parameter estimates showed that the filter is more sensitive to poor initial choices of neuromuscular parameters than equalization parameters, and bad choices for initial parameters can result in divergence, slow convergence, or parameter estimates that do not have a real physical interpretation. The promising results when applied to experimental data, together with its simple tuning and low dimension of the state-space, make the use of the Dual Extended Kalman Filter a viable option for identifying time-varying human control parameters in manual tracking tasks, which could be used in real-time human state monitoring and adaptive human-vehicle haptic interfaces.
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.
Time-varying long term memory in the European Union stock markets
Sensoy, Ahmet; Tabak, Benjamin M.
2015-10-01
This paper proposes a new efficiency index to model time-varying inefficiency in stock markets. We focus on European stock markets and show that they have different degrees of time-varying efficiency. We observe that the 2008 global financial crisis has an adverse effect on almost all EU stock markets. However, the Eurozone sovereign debt crisis has a significant adverse effect only on the markets in France, Spain and Greece. For the late members, joining EU does not have a uniform effect on stock market efficiency. Our results have important implications for policy makers, investors, risk managers and academics.
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
Robust stability for uncertain stochastic fuzzy BAM neural networks with time-varying delays
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.
Trajectory optimization for real-time guidance. I - Time-varying LQR on a parallel processor
Psiaki, Mark L.; Park, Kihong
1990-01-01
A key algorithmic element of a real-time trajectory optimization hardware/software implementation, the quadratic program (QP) solver element, is presented. The purpose of the effort is to make nonlinear trajectory optimization fast enough to provide real-time commands during guidance of a vehicle such as an aeromaneuvering orbiter. Many methods of nonlinear programming require the solution of a QP at each iteration. In the trajectory optimization case the QP has a special dynamic programming structure, a LQR-like structure. QP algorithm speed is increased by taking advantage of this special structure and by parallel implementation.
Yan, L.; Xiong, L.; Liu, D.; Hu, T.; Xu, C. Y.
2016-12-01
The basic IID assumption of the traditional flood frequency analysis has been challenged by nonstationarity. The most popular practice for analyzing nonstationarity of flood series is to use a fixed single-type probability distribution incorporated with the time-varying moments. However, the type of probability distribution could be both complex because of distinct flood populations and time-varying under changing environments. To allow the investigation of this complex nature, the time-varying two-component mixture distributions (TTMD) method is proposed in this study by considering the time variations of not only the moments of its component distributions but also the weighting coefficients. Having identified the existence of mixed flood populations based on circular statistics, the proposed TTMD was applied to model the annual maximum flood series (AMFS) of two stations in the Weihe River basin (WRB), with the model parameters calibrated by the meta-heuristic maximum likelihood (MHML) method. The performance of TTMD was evaluated by different diagnostic plots and indexes and compared with stationary single-type distributions, stationary mixture distributions and time-varying single-type distributions. The results highlighted the advantages of using TTMD models and physically-based covariates in nonstationary flood frequency analysis. Besides, the optimal TTMD models were considered to be capable of settling the issue of nonstationarity and capturing the mixed flood populations satisfactorily. It is concluded that the TTMD model is a good alternative in the nonstationary frequency analysis and can be applied to other regions with mixed flood populations.
A New Time-varying Concept of Risk in a Changing Climate
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.
Rakkiyappan, Rajan; Chandrasekar, Arunachalam; Cao, Jinde
2015-09-01
This paper presents a new design scheme for the passivity and passification of a class of memristor-based recurrent neural networks (MRNNs) with additive time-varying delays. The predictable assumptions on the boundedness and Lipschitz continuity of activation functions are formulated. The systems considered here are based on a different time-delay model suggested recently, which includes additive time-varying delay components in the state. The connection between the time-varying delay and its upper bound is considered when estimating the upper bound of the derivative of Lyapunov functional. It is recognized that the passivity condition can be expressed in a linear matrix inequality (LMI) format and by using characteristic function method. For state feedback passification, it is verified that it is apathetic to use immediate or delayed state feedback. By constructing a Lyapunov-Krasovskii functional and employing Jensen's inequality and reciprocal convex combination technique together with a tighter estimation of the upper bound of the cross-product terms derived from the derivatives of the Lyapunov functional, less conventional delay-dependent passivity criteria are established in terms of LMIs. Moreover, second-order reciprocally convex approach is employed for deriving the upper bound for terms with inverses of squared convex parameters. The model based on the memristor with additive time-varying delays widens the application scope for the design of neural networks. Finally, pertinent examples are given to show the advantages of the derived passivity criteria and the significant improvement of the theoretical approaches.
Time-varying boundaries for diffusion models of decision making and response time
Zhang, S.; Lee, M.D.; Vandekerckhove, J.; Maris, G.; Wagenmakers, E.-J.
2014-01-01
Diffusion models are widely-used and successful accounts of the time course of two-choice decision making. Most diffusion models assume constant boundaries, which are the threshold levels of evidence that must be sampled from a stimulus to reach a decision. We summarize theoretical results from
Failure Modes in Capacitors When Tested Under a Time-Varying Stress
Liu, David (Donhang)
2011-01-01
Steady step surge testing (SSST) is widely applied to screen out potential power-on failures in solid tantalum capacitors. The test simulates the power supply's on and off characteristics. Power-on failure has been the prevalent failure mechanism for solid tantalum capacitors for decoupling applications. On the other hand, the SSST can also be reviewed as an electrically destructive test under a time-varying stress. It consists of rapidly charging the capacitor with incremental voltage increases, through a low resistance in series, until the capacitor under test is electrically shorted. Highly accelerated life testing (HALT) is usually a time-efficient method for determining the failure mechanism in capacitors; however, a destructive test under a time-varying stress like SSST is even more effective. It normally takes days to complete a HALT test, but it only takes minutes for a time-varying stress test to produce failures. The advantage of incorporating specific time-varying stress into a statistical model is significant in providing an alternative life test method for quickly revealing the failure modes in capacitors. In this paper, a time-varying stress has been incorporated into the Weibull model to characterize the failure modes. The SSST circuit and transient conditions to correctly test the capacitors is discussed. Finally, the SSST was applied for testing polymer aluminum capacitors (PA capacitors), Ta capacitors, and multi-layer ceramic capacitors with both precious metal electrode (PME) and base-metal-electrodes (BME). It appears that testing results are directly associated to the dielectric layer breakdown in PA and Ta capacitors and are independent on the capacitor values, the way the capacitors being built, and the manufactures. The testing results also reveal that ceramic capacitors exhibit breakdown voltages more than 20 times the rated voltage, and the breakdown voltages are inverse proportional to the dielectric layer thickness. The possibility of
Visualisation of time-varying respiratory system elastance in experimental ARDS animal models.
van Drunen, Erwin J; Chiew, Yeong Shiong; Pretty, Christopher; Shaw, Geoffrey M; Lambermont, Bernard; Janssen, Nathalie; Chase, J Geoffrey; Desaive, Thomas
2014-03-02
Patients with acute respiratory distress syndrome (ARDS) risk lung collapse, severely altering the breath-to-breath respiratory mechanics. Model-based estimation of respiratory mechanics characterising patient-specific condition and response to treatment may be used to guide mechanical ventilation (MV). This study presents a model-based approach to monitor time-varying patient-ventilator interaction to guide positive end expiratory pressure (PEEP) selection. The single compartment lung model was extended to monitor dynamic time-varying respiratory system elastance, Edrs, within each breathing cycle. Two separate animal models were considered, each consisting of three fully sedated pure pietrain piglets (oleic acid ARDS and lavage ARDS). A staircase recruitment manoeuvre was performed on all six subjects after ARDS was induced. The Edrs was mapped across each breathing cycle for each subject. Six time-varying, breath-specific Edrs maps were generated, one for each subject. Each Edrs map shows the subject-specific response to mechanical ventilation (MV), indicating the need for a model-based approach to guide MV. This method of visualisation provides high resolution insight into the time-varying respiratory mechanics to aid clinical decision making. Using the Edrs maps, minimal time-varying elastance was identified, which can be used to select optimal PEEP. Real-time continuous monitoring of in-breath mechanics provides further insight into lung physiology. Therefore, there is potential for this new monitoring method to aid clinicians in guiding MV treatment. These are the first such maps generated and they thus show unique results in high resolution. The model is limited to a constant respiratory resistance throughout inspiration which may not be valid in some cases. However, trends match clinical expectation and the results highlight both the subject-specificity of the model, as well as significant inter-subject variability.
Time-varying Concurrent Risk of Extreme Droughts and Heatwaves in California
Sarhadi, A.; Diffenbaugh, N. S.; Ausin, M. C.
2016-12-01
Anthropogenic global warming has changed the nature and the risk of extreme climate phenomena such as droughts and heatwaves. The concurrent of these nature-changing climatic extremes may result in intensifying undesirable consequences in terms of human health and destructive effects in water resources. The present study assesses the risk of concurrent extreme droughts and heatwaves under dynamic nonstationary conditions arising from climate change in California. For doing so, a generalized fully Bayesian time-varying multivariate risk framework is proposed evolving through time under dynamic human-induced environment. In this methodology, an extreme, Bayesian, dynamic copula (Gumbel) is developed to model the time-varying dependence structure between the two different climate extremes. The time-varying extreme marginals are previously modeled using a Generalized Extreme Value (GEV) distribution. Bayesian Markov Chain Monte Carlo (MCMC) inference is integrated to estimate parameters of the nonstationary marginals and copula using a Gibbs sampling method. Modelled marginals and copula are then used to develop a fully Bayesian, time-varying joint return period concept for the estimation of concurrent risk. Here we argue that climate change has increased the chance of concurrent droughts and heatwaves over decades in California. It is also demonstrated that a time-varying multivariate perspective should be incorporated to assess realistic concurrent risk of the extremes for water resources planning and management in a changing climate in this area. The proposed generalized methodology can be applied for other stochastic nature-changing compound climate extremes that are under the influence of climate change.
Time-Varying FIR Equalization for MIMO Transmission over Doubly Selective Channels
Barhumi, Imad; Moonen, Marc
2010-12-01
We propose time-varying FIR equalization techniques for spatial multiplexing-based multiple-input multiple-output (MIMO) transmission over doubly selective channels. The doubly selective channel is approximated using the basis expansion model (BEM), and equalized by means of time-varying FIR filters designed according to the BEM. By doing so, the time-varying deconvolution problem is converted into a two-dimensional time-invariant deconvolution problem in the time-invariant coefficients of the channel BEM and the time-invariant coefficients of the equalizer BEM. The timevarying FIR equalizers are derived based on either the matched filtering criterion, or the linear minimum mean-square error (MMSE) or the zero-forcing (ZF) criteria. In addition to the linear equalizers, the decision feedback equalizer (DFE) is proposed. The DFE can be designed according to two different scenarios. In the first scenario, the DFE is based on feeding back previously estimated symbols from one particular antenna at a time. Whereas, in the second scenario, the previously estimated symbols from all transmit antennas are fed back together. The performance of the proposed equalizers in the context of MIMO transmission is analyzed in terms of numerical simulations.
Time-Varying FIR Equalization for MIMO Transmission over Doubly Selective Channels
Directory of Open Access Journals (Sweden)
Marc Moonen
2010-01-01
Full Text Available We propose time-varying FIR equalization techniques for spatial multiplexing-based multiple-input multiple-output (MIMO transmission over doubly selective channels. The doubly selective channel is approximated using the basis expansion model (BEM, and equalized by means of time-varying FIR filters designed according to the BEM. By doing so, the time-varying deconvolution problem is converted into a two-dimensional time-invariant deconvolution problem in the time-invariant coefficients of the channel BEM and the time-invariant coefficients of the equalizer BEM. The timevarying FIR equalizers are derived based on either the matched filtering criterion, or the linear minimum mean-square error (MMSE or the zero-forcing (ZF criteria. In addition to the linear equalizers, the decision feedback equalizer (DFE is proposed. The DFE can be designed according to two different scenarios. In the first scenario, the DFE is based on feeding back previously estimated symbols from one particular antenna at a time. Whereas, in the second scenario, the previously estimated symbols from all transmit antennas are fed back together. The performance of the proposed equalizers in the context of MIMO transmission is analyzed in terms of numerical simulations.
Optimal synchronization in small-world biological neural networks with time-varying weights
International Nuclear Information System (INIS)
Zheng Hongyu; Luo Xiaoshu
2009-01-01
In this paper, a new model of small-world biological neural networks based on biophysical Hodgkin-Huxley neurons with time-varying weights is proposed. Then the synchronization phenomenon of small-world biological neural networks evoked by the learning rate is studied. The study shows that there exists an optimal synchronization state by changing the learning rate.
OFDM receiver for fast time-varying channels using block-sparse Bayesian learning
DEFF Research Database (Denmark)
Barbu, Oana-Elena; Manchón, Carles Navarro; Rom, Christian
2016-01-01
We propose an iterative algorithm for OFDM receivers operating over fast time-varying channels. The design relies on the assumptions that the channel response can be characterized by a few non-negligible separable multipath components, and the temporal variation of each component gain can be well...
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.
Modeling the Time-Varying Nature of Student Exceptionality Classification on Achievement Growth
Nese, Joseph F. T.; Stevens, Joseph J.; Schulte, Ann C.; Tindal, Gerald; Elliott, Stephen N.
2017-01-01
Our purpose was to examine different approaches to modeling the time-varying nature of exceptionality classification. Using longitudinal data from one state's mathematics achievement test for 28,829 students in Grades 3 to 8, we describe the reclassification rate within special education and between general and special education, and compare four…
Perfect fluid Bianchi Type-I cosmological models with time varying G ...
Indian Academy of Sciences (India)
Bianchi Type-I cosmological models containing perfect fluid with time varying and have been presented. The solutions obtained represent an expansion scalar bearing a constant ratio to the anisotropy in the direction of space-like unit vector . Of the two models obtained, one has negative vacuum energy density, ...
DEFF Research Database (Denmark)
Sandberg, Rickard; Kruse, Robinson
Building upon the work of Vogelsang (1998) and Harvey and Leybourne (2007) we derive tests that are invariant to the order of integration when the null hypothesis of linearity is tested in time-varying smooth transition models. As heteroscedasticity may lead to spurious rejections of the null...
Adaptive path following for Unmanned Aerial Vehicles in time-varying unknown wind environments
Zhou, Bingyu; Satyavada, Harish; Baldi, S.; Sun, J.; Rajamani, R.
2017-01-01
In this paper, an adaptive control scheme for Unmanned Aerial Vehicles (UAVs) path following under slowly time-varying wind is developed. The proposed control strategy integrates the path following law based on the vector field method with an adaptive term counteracting the effect of wind's
Modified Hubble law, the time-varying Hubble parameter and the problem of dark energy
Liu, Jian-Miin
2005-01-01
In the framework of the solvable model of cosmology constructed in the Earth-related coordinate system, we derive the modified Hubble law. This law carries the slowly time-varying Hubble parameter. The modified Hubble law eliminates the need for dark energy.
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
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
Time-varying coefficient estimation in SURE models. Application to portfolio management
DEFF Research Database (Denmark)
Casas, Isabel; Ferreira, Eva; Orbe, Susan
This paper provides a detailed analysis of the asymptotic properties of a kernel estimator for a Seemingly Unrelated Regression Equations model with time-varying coefficients (tv-SURE) under very general conditions. Theoretical results together with a simulation study differentiates the cases for...
Time-varying market integration and expected returns in emerging mrkets
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
Control of the tokamak safety factor profile with time-varying constraints using MPC
Maljaars, E.; Felici, F.; M.R. de Baar,; van Dongen, J.; Hogeweij, G. M. D.; P. J. M. Geelen,; Steinbuch, M.
2015-01-01
A controller is designed for the tokamak safety factor profile that takes real-time-varying operational and physics limits into account. This so-called model predictive controller (MPC) employs a prediction model in order to compute optimal control inputs that satisfy the given limits. The use of
Prediction of the eigenvectors for spatial multiplexing MIMO systems in time-varying channels
DEFF Research Database (Denmark)
Nguyen, Hung Tuan; Leus, Geert; Khaled, Nadia
2005-01-01
the performance of a prediction scheme for multiple input multiple output (MIMO) systems that apply spatial multiplexing. We aim at predicting the future precoder/decoder directly without going through the prediction of the channel matrix. The results show that in a slowly time varying channel an increase...
The Role of Thermal Properties in Periodic Time-Varying Phenomena
Marin, E.
2007-01-01
The role played by physical parameters governing the transport of heat in periodical time-varying phenomena within solids is discussed. Starting with a brief look at the conduction heat transport mechanism, the equations governing heat conduction under static, stationary and non-stationary conditions, and the physical parameters involved, are…
Low-Complexity Block Turbo Equalization for OFDM Systems in Time-Varying Channels
Fang, K.; Rugini, L.; Leus, G.
2008-01-01
We propose low-complexity block turbo equalizers for orthogonal frequency-division multiplexing (OFDM) systems in time-varying channels. The presented work is based on a soft minimum mean-squared error (MMSE) block linear equalizer (BLE) that exploits the banded structure of the frequency-domain
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.
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...
Scalable Video Streaming Adaptive to Time-Varying IEEE 802.11 MAC Parameters
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.
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 ...
Tiled Parallel Coordinates for the Visualization of Time-Varying Multichannel EEG Data
Caat, M. ten; Maurits, N.M.; Roerdink, J.B.T.M.
2005-01-01
The field of visualization assists data interpretation in many areas, but some types of data are not manageable by existing visualization techniques. This holds in particular for time-varying multichannel EEG data. No existing technique can simultaneously visualize information from all channels in
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...
Time-varying effect models for ordinal responses with applications in substance abuse research.
Dziak, John J; Li, Runze; Zimmerman, Marc A; Buu, Anne
2014-12-20
Ordinal responses are very common in longitudinal data collected from substance abuse research or other behavioral research. This study develops a new statistical model with free SAS macros that can be applied to characterize time-varying effects on ordinal responses. Our simulation study shows that the ordinal-scale time-varying effects model has very low estimation bias and sometimes offers considerably better performance when fitting data with ordinal responses than a model that treats the response as continuous. Contrary to a common assumption that an ordinal scale with several levels can be treated as continuous, our results indicate that it is not so much the number of levels on the ordinal scale but rather the skewness of the distribution that makes a difference on relative performance of linear versus ordinal models. We use longitudinal data from a well-known study on youth at high risk for substance abuse as a motivating example to demonstrate that the proposed model can characterize the time-varying effect of negative peer influences on alcohol use in a way that is more consistent with the developmental theory and existing literature, in comparison with the linear time-varying effect model. Copyright © 2014 John Wiley & Sons, Ltd.
Dynamic coupling design for nonlinear output agreement and time-varying flow control
Buerger, Mathias; De Persis, Claudio
This paper studies the problem of output agreement in networks of nonlinear dynamical systems under time-varying disturbances, using dynamic diffusive couplings. Necessary conditions are derived for general networks of nonlinear systems, and these conditions are explicitly interpreted as conditions
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.
Global exponential stability of BAM neural networks with time-varying delays: The discrete-time case
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.
Brochard, Renaud; Dufour, Andre; Despres, Olivier
2004-01-01
Recently, the relationship between music and nonmusical cognitive abilities has been highly debated. It has been documented that formal music training would improve verbal, mathematical or visuospatial performance in children. In the experiments described here, we tested if visual perception and imagery abilities were enhanced in adult musicians…
Implementation of a near real-time burned area detection algorithm calibrated for VIIRS imagery
Brenna Schwert; Carl Albury; Jess Clark; Abigail Schaaf; Shawn Urbanski; Bryce Nordgren
2016-01-01
There is a need to implement methods for rapid burned area detection using a suitable replacement for Moderate Resolution Imaging Spectroradiometer (MODIS) imagery to meet future mapping and monitoring needs (Roy and Boschetti 2009, Tucker and Yager 2011). The Visible Infrared Imaging Radiometer Suite (VIIRS) sensor onboard the Suomi-National Polar-orbiting Partnership...
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.
Comparison of Guidance Modes for the AUV "Slocum Glider" in Time-Varying Ocean Flows
Eichhorn, Mike; Woithe, Hans Christian; Kremer, Ulrich
2017-01-01
This paper presents possibilities for the reliable guidance of an AUV "Slocum Glider" in time-varying ocean flows. The presented guidance modes consider the restricted information during a real mission about the actual position and ocean current conditions as well as the available control modes of a glider. A faster-than-real-time, full software stack simulator for the Slocum glider will be described in order to test the developed guidance modes under real mission conditions.
Problems with Time-Varying Extra Dimensions or "Cardassian Expansion" as Alternatives to Dark Energy
Cline, J M; Cline, James M.
2003-01-01
It has recently been proposed that the Universe might be accelerating as a consequence of extradimensions with time varying size. We show that although these scenarios can lead to acceleration, they run into serious difficulty when taking into account limits on the time variation of the four dimensional Newton's constant. On the other hand, models of ``Cardassian'' expansion based on extra dimensions violate the weak energy condition for the bulk stress energy, for parameters that give an accelerating universe.
Classificaiton and Discrimination of Sources with Time-Varying Frequency and Spatial Spectra
2007-04-01
Atmospheric Administration, July 1973. [15] U. Madhow and M. Honig, " MMSE interference suppression for direct-sequence spread spectrum CDMA," IEEE Trans...varying and time- invariant polarizations will lead to the same performance if their corresponding covariance matrices are identical. Consider, for example...assuming fixed, time- invariant polarization of -y = 45 degrees, and thereby, the source polarization diversity cannot be utilized in DOA estimation using
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.
Zhang, Lei; Weng, Qihao
2016-03-01
Information on impervious surface distribution and dynamics is useful for understanding urbanization and its impacts on hydrological cycle, water management, surface energy balances, urban heat island, and biodiversity. Numerous methods have been developed and successfully applied to estimate impervious surfaces. Previous methods of impervious surface estimation mainly focused on the spectral differences between impervious surfaces and other land covers. Moreover, the accuracy of estimation from single or multi-temporal images was often limited by the mixed pixel problem in coarse- or medium-resolution imagery or by the intra-class spectral variability problem in high resolution imagery. Time series satellite imagery provides potential to resolve the above problems as well as the spectral confusion with similar surface characteristics due to phenological change, inter-annual climatic variability, and long-term changes of vegetation. Since Landsat time series has a long record with an effective spatial resolution, this study aimed at estimating and mapping impervious surfaces by analyzing temporal spectral differences between impervious and pervious surfaces that were extracted from dense time series Landsat imagery. Specifically, this study developed an efficient method to extract annual impervious surfaces from time series Landsat data and applied it to the Pearl River Delta, southern China, from 1988 to 2013. The annual classification accuracy yielded from 71% to 91% for all classes, while the mapping accuracy of impervious surfaces ranged from 80.5% to 94.5%. Furthermore, it is found that the use of more than 50% of Scan Line Corrector (SLC)-off images after 2003 did not substantially reduced annual classification accuracy, which ranged from 78% to 91%. It is also worthy to note that more than 80% of classification accuracies were achieved in both 2002 and 2010 despite of more than 40% of cloud cover detected in these two years. These results suggested that the
Local inertial oscillations in the surface ocean generated by time-varying winds
Chen, Shengli; Polton, Jeff A.; Hu, Jianyu; Xing, Jiuxing
2015-12-01
A new relationship is presented to give a review study on the evolution of inertial oscillations in the surface ocean locally generated by time-varying wind stress. The inertial oscillation is expressed as the superposition of a previous oscillation and a newly generated oscillation, which depends upon the time-varying wind stress. This relationship is employed to investigate some idealized wind change events. For a wind series varying temporally with different rates, the induced inertial oscillation is dominated by the wind with the greatest variation. The resonant wind, which rotates anti-cyclonically at the local inertial frequency with time, produces maximal amplitude of inertial oscillations, which grows monotonically. For the wind rotating at non-inertial frequencies, the responses vary periodically, with wind injecting inertial energy when it is in phase with the currents, but removing inertial energy when it is out of phase. The wind rotating anti-cyclonically with time is much more favorable to generate inertial oscillations than the cyclonic rotating wind. The wind with a frequency closer to the inertial frequency generates stronger inertial oscillations. For a diurnal wind, the induced inertial oscillation is dependent on latitude and is most significant at 30 °. This relationship is also applied to examine idealized moving cyclones. The inertial oscillation is much stronger on the right-hand side of the cyclone path than on the left-hand side (in the northern hemisphere). This is due to the wind being anti-cyclonic with time on the right-hand side, but cyclonic on the other side. The inertial oscillation varies with the cyclone translation speed. The optimal translation speed generating the greatest inertial oscillations is 2 m/s at the latitude of 10 ° and gradually increases to 6 m/s at the latitude of 30 °.
Multimodal Pilot Behavior in Multi-Axis Tracking Tasks with Time-Varying Motion Cueing Gains
Zaal, P. M. T; Pool, D. M.
2014-01-01
In a large number of motion-base simulators, adaptive motion filters are utilized to maximize the use of the available motion envelope of the motion system. However, not much is known about how the time-varying characteristics of such adaptive filters affect pilots when performing manual aircraft control. This paper presents the results of a study investigating the effects of time-varying motion filter gains on pilot control behavior and performance. An experiment was performed in a motion-base simulator where participants performed a simultaneous roll and pitch tracking task, while the roll and/or pitch motion filter gains changed over time. Results indicate that performance increases over time with increasing motion gains. This increase is a result of a time-varying adaptation of pilots' equalization dynamics, characterized by increased visual and motion response gains and decreased visual lead time constants. Opposite trends are found for decreasing motion filter gains. Even though the trends in both controlled axes are found to be largely the same, effects are less significant in roll. In addition, results indicate minor cross-coupling effects between pitch and roll, where a cueing variation in one axis affects the behavior adopted in the other axis.
A river water quality model for time varying BOD discharge concentration
Directory of Open Access Journals (Sweden)
Oppenheimer Seth F.
1999-01-01
Full Text Available We consider a model for biochemical oxygen demand (BOD in a semi-infinite river where the BOD is prescribed by a time varying function at the left endpoint. That is, we study the problem with a time varying boundary loading. We obtain the well-posedness for the model when the boundary loading is smooth in time. We also obtain various qualitative results such as ordering, positivity, and boundedness. Of greatest interest, we show that a periodic loading function admits a unique asymptotically attracting periodic solution. For non-smooth loading functions, we obtain weak solutions. Finally, for certain special cases, we show how to obtain explicit solutions in the form of infinite series.
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.
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
Time-varying metamaterials based on graphene-wrapped microwires: Modeling and potential applications
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.
Analysis of local ionospheric time varying characteristics with singular value decomposition
DEFF Research Database (Denmark)
Jakobsen, Jakob Anders; Knudsen, Per; Jensen, Anna B. O.
2010-01-01
in Denmark located in the midlatitude region. The station separation between the three stations is 132–208 km (the time series of the TEC can be freely downloaded at http://www.heisesgade.dk). For each year, a SVD has been performed on the TEC time series in order to identify the three time varying (daily...... filter processing making it more robust, but can also be used as starting values in the initialization phase in case of gaps in the data stream. Furthermore, the models can be used to detect variations from the normal local ionospheric activity....
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.
Tracking control of time-varying knee exoskeleton disturbed by interaction torque.
Li, Zhan; Ma, Wenhao; Yin, Ziguang; Guo, Hongliang
2017-11-01
Knee exoskeletons have been increasingly applied as assistive devices to help lower-extremity impaired people to make their knee joints move through providing external movement compensation. Tracking control of knee exoskeletons guided by human intentions often encounters time-varying (time-dependent) issues and the disturbance interaction torque, which may dramatically put an influence up on their dynamic behaviors. Inertial and viscous parameters of knee exoskeletons can be estimated to be time-varying due to unexpected mechanical vibrations and contact interactions. Moreover, the interaction torque produced from knee joint of wearers has an evident disturbance effect on regular motions of knee exoskeleton. All of these points can increase difficultly of accurate control of knee exoskeletons to follow desired joint angle trajectories. This paper proposes a novel control strategy for controlling knee exoskeleton with time-varying inertial and viscous coefficients disturbed by interaction torque. Such designed controller is able to make the tracking error of joint angle of knee exoskeletons exponentially converge to zero. Meanwhile, the proposed approach is robust to guarantee the tracking error bounded when the interaction torque exists. Illustrative simulation and experiment results are presented to show efficiency of the proposed controller. Additionally, comparisons with gradient dynamic (GD) approach and other methods are also presented to demonstrate efficiency and superiority of the proposed control strategy for tracking joint angle of knee exoskeleton. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.
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.
Guedes, R.M.C.; Calliari, L.J.; Holland, K.T.; Plant, N.G.; Pereira, P.S.; Alves, F.N.A.
2011-01-01
Time-exposure intensity (averaged) images are commonly used to locate the nearshore sandbar position (xb), based on the cross-shore locations of maximum pixel intensity (xi) of the bright bands in the images. It is not known, however, how the breaking patterns seen in Variance images (i.e. those created through standard deviation of pixel intensity over time) are related to the sandbar locations. We investigated the suitability of both Time-exposure and Variance images for sandbar detection within a multiple bar system on the southern coast of Brazil, and verified the relation between wave breaking patterns, observed as bands of high intensity in these images and cross-shore profiles of modeled wave energy dissipation (xD). Not only is Time-exposure maximum pixel intensity location (xi-Ti) well related to xb, but also to the maximum pixel intensity location of Variance images (xi-Va), although the latter was typically located 15m offshore of the former. In addition, xi-Va was observed to be better associated with xD even though xi-Ti is commonly assumed as maximum wave energy dissipation. Significant wave height (Hs) and water level (??) were observed to affect the two types of images in a similar way, with an increase in both Hs and ?? resulting in xi shifting offshore. This ??-induced xi variability has an opposite behavior to what is described in the literature, and is likely an indirect effect of higher waves breaking farther offshore during periods of storm surges. Multiple regression models performed on xi, Hs and ?? allowed the reduction of the residual errors between xb and xi, yielding accurate estimates with most residuals less than 10m. Additionally, it was found that the sandbar position was best estimated using xi-Ti (xi-Va) when xb was located shoreward (seaward) of its mean position, for both the first and the second bar. Although it is unknown whether this is an indirect hydrodynamic effect or is indeed related to the morphology, we found that this
Huang, Huan; Baddour, Natalie; Liang, Ming
2018-02-01
Under normal operating conditions, bearings often run under time-varying rotational speed conditions. Under such circumstances, the bearing vibrational signal is non-stationary, which renders ineffective the techniques used for bearing fault diagnosis under constant running conditions. One of the conventional methods of bearing fault diagnosis under time-varying speed conditions is resampling the non-stationary signal to a stationary signal via order tracking with the measured variable speed. With the resampled signal, the methods available for constant condition cases are thus applicable. However, the accuracy of the order tracking is often inadequate and the time-varying speed is sometimes not measurable. Thus, resampling-free methods are of interest for bearing fault diagnosis under time-varying rotational speed for use without tachometers. With the development of time-frequency analysis, the time-varying fault character manifests as curves in the time-frequency domain. By extracting the Instantaneous Fault Characteristic Frequency (IFCF) from the Time-Frequency Representation (TFR) and converting the IFCF, its harmonics, and the Instantaneous Shaft Rotational Frequency (ISRF) into straight lines, the bearing fault can be detected and diagnosed without resampling. However, so far, the extraction of the IFCF for bearing fault diagnosis is mostly based on the assumption that at each moment the IFCF has the highest amplitude in the TFR, which is not always true. Hence, a more reliable T-F curve extraction approach should be investigated. Moreover, if the T-F curves including the IFCF, its harmonic, and the ISRF can be all extracted from the TFR directly, no extra processing is needed for fault diagnosis. Therefore, this paper proposes an algorithm for multiple T-F curve extraction from the TFR based on a fast path optimization which is more reliable for T-F curve extraction. Then, a new procedure for bearing fault diagnosis under unknown time-varying speed
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).
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)
Cai, Zuowei; Huang, Lihong; Zhang, Lingling
2015-05-01
This paper investigates the problem of exponential synchronization of time-varying delayed neural networks with discontinuous neuron activations. Under the extended Filippov differential inclusion framework, by designing discontinuous state-feedback controller and using some analytic techniques, new testable algebraic criteria are obtained to realize two different kinds of global exponential synchronization of the drive-response system. Moreover, we give the estimated rate of exponential synchronization which depends on the delays and system parameters. The obtained results extend some previous works on synchronization of delayed neural networks not only with continuous activations but also with discontinuous activations. Finally, numerical examples are provided to show the correctness of our analysis via computer simulations. Our method and theoretical results have a leading significance in the design of synchronized neural network circuits involving discontinuous factors and time-varying delays. Copyright © 2015 Elsevier Ltd. All rights reserved.
Passivity and passification of memristor-based recurrent neural networks with time-varying delays.
Guo, Zhenyuan; Wang, Jun; Yan, Zheng
2014-11-01
This paper presents new theoretical results on the passivity and passification of a class of memristor-based recurrent neural networks (MRNNs) with time-varying delays. The casual assumptions on the boundedness and Lipschitz continuity of neuronal activation functions are relaxed. By constructing appropriate Lyapunov-Krasovskii functionals and using the characteristic function technique, passivity conditions are cast in the form of linear matrix inequalities (LMIs), which can be checked numerically using an LMI toolbox. Based on these conditions, two procedures for designing passification controllers are proposed, which guarantee that MRNNs with time-varying delays are passive. Finally, two illustrative examples are presented to show the characteristics of the main results in detail.
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.
Almost Sure Stability and Stabilization for Hybrid Stochastic Systems with Time-Varying Delays
Directory of Open Access Journals (Sweden)
Hua Yang
2012-01-01
Full Text Available The problems of almost sure (a.s. stability and a.s. stabilization are investigated for hybrid stochastic systems (HSSs with time-varying delays. The different time-varying delays in the drift part and in the diffusion part are considered. Based on nonnegative semimartingale convergence theorem, Hölder’s inequality, Doob’s martingale inequality, and Chebyshev’s inequality, some sufficient conditions are proposed to guarantee that the underlying nonlinear hybrid stochastic delay systems (HSDSs are almost surely (a.s. stable. With these conditions, a.s. stabilization problem for a class of nonlinear HSDSs is addressed through designing linear state feedback controllers, which are obtained in terms of the solutions to a set of linear matrix inequalities (LMIs. Two numerical simulation examples are given to show the usefulness of the results derived.
Identification of time-varying neural dynamics from spiking activities using Chebyshev polynomials.
Song Xu; Yang Li; Xudong Wang; Chan, Rosa H M
2016-08-01
Neural plasticity, elicited by processes such as development and learning, is an important biological attribute which can be viewed as a time-varying property of the nervous system. In this paper, we investigated the novel use of Chebyshev polynomials to estimate the changes in model parameters efficiently for time-varying dynamical systems with binary inputs and outputs. A forward orthogonal least square (FOLS) algorithm selected the significant model terms. Extensive simulations showed that the proposed algorithm identified the system changes more accurately in comparison with adaptive filter. This approach can be applied to identify not only gradual but also abrupt temporal evolutions of neural dynamics underlying nervous system activity with high sensitivity and accuracy by observing input and output spike trains only.
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
Event-triggered platoon control of vehicles with time-varying delay and probabilistic faults
Wei, Yue; Liyuan, Wang; Ge, Guo
2017-03-01
This paper investigates event-triggered platoon control of vehicles with probabilistic faults (i.e., sensor and actuator) and time-varying communication delay. A novel platoon model is established, in which the effect of time-varying delay, event-triggered scheme and probabilistic faults are involved. Based on the new model, criteria for the exponential stability and criteria for co-designing both the output feedback and the trigger parameters are derived by using Lyapunov functional. The obtained controller is complemented by additional conditions established for guaranteeing string stability and zero steady state velocity errors, yielding a useful string stable platoon control method. The effectiveness and advantage of the presented methodology are demonstrated by both numerical simulations and experiments with laboratory scale Arduino cars.
Uwate, Y; Nishio, Y; Stoop, R
2009-01-01
We explore the synchronization and switching behavior of a system of two identical van der Pol oscillators coupled by a stochastically timevarying resistor. Triggered by the time-varying resistor, the system of oscillators switches between synchronized and anti-synchronized behavior. We find that the preference of the synchronized/antisynchronized state is determined by the ratio of the probabilities of the two resistor states. The length of the phases of maintained resistor states, however, ...
Passivity of memristive BAM neural networks with leakage and additive time-varying delays
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.
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
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
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.
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....
Stochastic motion of test particle implies that G varies with time
Momeni, D.
2010-01-01
The aim of this letter is to propose a new description to the time varying gravitational constant problem, which naturally implements the Dirac's large numbers hypothesis in a new proposed holographic scenario for the origin of gravity as an entropic force. We survey the effect of the Stochastic motion of the test particle in Verlinde's scenario for gravity\\cite{Verlinde}. Firstly we show that we must get the equipartition values for $t\\rightarrow\\infty$ which leads to the usual Newtonian gra...
Perfect fluid Bianchi Type-I cosmological models with time varying G ...
Indian Academy of Sciences (India)
(27). From eq. (27), we observe that Λ is a constant in the absence of matter (Tij = 0) implying that matter is essential for a time varying Λ. In the field eqs (4), Λ accounts for vacuum energy with its energy density ρv and isotropic pressure pv satisfying the equation of state pv = −ρv = −. Λ. 8πG . The usual conservation law for ...
Time-Varying Estimation of Crop Insurance Program in Altering North Dakota Farm Economic Structure
Coleman, Jane A.; Shaik, Saleem
2009-01-01
This study examines how federal farm policies, specifically crop insurance, have affected the farm economic structure of North Dakota’s agriculture sector. The system of derived input demand equations is estimated to quantify the changes in North Dakota farmers’ input use when they purchase crop insurance. Further, the cumulative rolling regression technique is applied to capture the varying effects of the farm policies over time. Empirical results from the system of input demand functions in...
Time-Varying Risk, Interest Rates, and Exchange Rates in General Equilibrium
Fernando Alvarez; Andrew Atkeson; Patrick J. Kehoe
2009-01-01
Under mild assumptions, the data indicate that fluctuations in nominal interest rate differentials across currencies are primarily fluctuations in time-varying risk. This finding is an immediate implication of the fact that exchange rates are roughly random walks. If most fluctuations in interest differentials are thought to be driven by monetary policy, then the data call for a theory which explains how changes in monetary policy change risk. Here, we propose such a theory based on a general...
Ma, Linlin; Liang, Yanping; Chen, Jian
2016-01-01
This paper studies the stabilization problem for damping multimachine power system with time-varying delays and sector saturating actuator. The multivariable proportional plus derivative (PD) type stabilizer is designed by transforming the problem of PD controller design to that of state feedback stabilizer design for a system in descriptor form. A new sufficient condition of closed-loop multimachine power system asymptomatic stability is derived based on the Lyapunov theory. Computer simulat...
International Nuclear Information System (INIS)
Lou, X.; Cui, B.
2008-01-01
In this paper we consider the problem of exponential stability for recurrent neural networks with multiple time varying delays and reaction-diffusion terms. The activation functions are supposed to be bounded and globally Lipschitz continuous. By means of Lyapunov functional, sufficient conditions are derived, which guarantee global exponential stability of the delayed neural network. Finally, a numerical example is given to show the correctness of our analysis. (author)
Synchronization in an array of linearly coupled networks with time-varying delay
Wang, Weiwei; Cao, Jinde
2006-07-01
This paper studies the dynamics of a system of linearly coupled identical connected neural networks with time-varying delay. Some sufficient conditions for synchronization of such a system are obtained based on Lyapunov functional method and matrix inequality techniques, which can be checked numerically very efficiently by using the Matlab toolbox. Finally, an example is provided to demonstrate the effectiveness of the proposed results.
Directory of Open Access Journals (Sweden)
Selina Christin Wriessnegger
2014-06-01
Full Text Available Motor imagery (MI is a commonly used paradigm for the study of motor learning or cognitive aspects of action control. The rationale for using MI training to promote the relearning of motor function arises from research on the functional correlates that MI shares with the execution of physical movements. While most of the previous studies investigating MI were based on simple movements in the present study a more attractive mental practice was used to investigate cortical activation during MI. We measured cerebral responses with functional magnetic resonance imaging (fMRI in twenty three healthy volunteers as they imagined playing soccer or tennis before and after a short physical sports exercise. Our results demonstrated that only 10 minutes of training are enough to boost motor imagery patterns in motor related brain regions including premotor cortex and supplementary motor area (SMA but also fronto-parietal and subcortical structures. This supports previous findings that motor imagery has beneficial effects especially in combination with motor execution when used in motor rehabilitation or motor learning processes. We conclude that sports MI combined with an interactive game environment could be a promising additional tool in future rehabilitation programs aiming to improve upper or lower limb functions or support neuroplasticity.
Chiew, Yeong Shiong; Pretty, Christopher; Docherty, Paul D; Lambermont, Bernard; Shaw, Geoffrey M; Desaive, Thomas; Chase, J Geoffrey
2015-01-01
Respiratory mechanics models can aid in optimising patient-specific mechanical ventilation (MV), but the applications are limited to fully sedated MV patients who have little or no spontaneously breathing efforts. This research presents a time-varying elastance (E(drs)) model that can be used in spontaneously breathing patients to determine their respiratory mechanics. A time-varying respiratory elastance model is developed with a negative elastic component (E(demand)), to describe the driving pressure generated during a patient initiated breathing cycle. Data from 22 patients who are partially mechanically ventilated using Pressure Support (PS) and Neurally Adjusted Ventilatory Assist (NAVA) are used to investigate the physiology relevance of the time-varying elastance model and its clinical potential. E(drs) of every breathing cycle for each patient at different ventilation modes are presented for comparison. At the start of every breathing cycle initiated by patient, E(drs) is 25 cmH2Os/l and thus can be used as an acute respiratory distress syndrome (ARDS) severity indicator. The E(drs) model captures unique dynamic respiratory mechanics for spontaneously breathing patients with respiratory failure. The model is fully general and is applicable to both fully controlled and partially assisted MV modes.
Directory of Open Access Journals (Sweden)
Yeong Shiong Chiew
Full Text Available BACKGROUND: Respiratory mechanics models can aid in optimising patient-specific mechanical ventilation (MV, but the applications are limited to fully sedated MV patients who have little or no spontaneously breathing efforts. This research presents a time-varying elastance (E(drs model that can be used in spontaneously breathing patients to determine their respiratory mechanics. METHODS: A time-varying respiratory elastance model is developed with a negative elastic component (E(demand, to describe the driving pressure generated during a patient initiated breathing cycle. Data from 22 patients who are partially mechanically ventilated using Pressure Support (PS and Neurally Adjusted Ventilatory Assist (NAVA are used to investigate the physiology relevance of the time-varying elastance model and its clinical potential. E(drs of every breathing cycle for each patient at different ventilation modes are presented for comparison. RESULTS: At the start of every breathing cycle initiated by patient, E(drs is 25 cmH2Os/l and thus can be used as an acute respiratory distress syndrome (ARDS severity indicator. CONCLUSION: The E(drs model captures unique dynamic respiratory mechanics for spontaneously breathing patients with respiratory failure. The model is fully general and is applicable to both fully controlled and partially assisted MV modes.
From calls to communities: a model for time-varying social networks
Laurent, Guillaume; Saramäki, Jari; Karsai, Márton
2015-11-01
Social interactions vary in time and appear to be driven by intrinsic mechanisms that shape the emergent structure of social networks. Large-scale empirical observations of social interaction structure have become possible only recently, and modelling their dynamics is an actual challenge. Here we propose a temporal network model which builds on the framework of activity-driven time-varying networks with memory. The model integrates key mechanisms that drive the formation of social ties - social reinforcement, focal closure and cyclic closure, which have been shown to give rise to community structure and small-world connectedness in social networks. We compare the proposed model with a real-world time-varying network of mobile phone communication, and show that they share several characteristics from heterogeneous degrees and weights to rich community structure. Further, the strong and weak ties that emerge from the model follow similar weight-topology correlations as real-world social networks, including the role of weak ties.
Sakthivel, R.; Karthik Raja, U.; Mathiyalagan, K.; Leelamani, A.
2012-03-01
This paper is concerned with the problem of robust stabilization and H∞ control for a class of uncertain stochastic neural networks with time-varying delays and time-varying norm-bounded parameter uncertainties. The delay is of a time-varying nature, and the activation functions are assumed to be neither differentiable nor strictly monotonic. Moreover, the description of the activation functions is more general than the commonly used Lipschitz conditions. By using the Lyapunov function approach together with the linear matrix inequality (LMI) technique, for the robust stabilization we propose a state feedback controller to ensure that the closed loop system is robustly asymptotically stable in the mean square for all admissible parameter uncertainties. For the robust H∞ control problem, a state feedback controller is designed such that in addition to the requirement of robust stability, a prescribed H∞ performance level is to be satisfied. The results obtained are formulated in terms of LMIs which can be easily checked by the MATLAB LMI control toolbox. Numerical examples are presented to illustrate the effectiveness of the obtained method and the improvement over some existing results.
Joint optimization of green vehicle scheduling and routing problem with time-varying speeds
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
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.
An Explicit MOT-TD-VIE Solver for Time Varying Media
Sayed, Sadeed Bin
2016-03-15
An explicit marching on-in-time (MOT) scheme for solving the time domain electric field integral equation enforced on volumes with time varying dielectric permittivity is proposed. Unknowns of the integral equation and the constitutive relation, i.e., flux density and field intensity, are discretized using full and half Schaubert-Wilton-Glisson functions in space. Temporal interpolation is carried out using band limited approximate prolate spherical wave functions. The discretized coupled system of integral equation and constitutive relation is integrated in time using a PE(CE)m type linear multistep scheme. Unlike the existing MOT methods, the resulting explicit MOT scheme allows for straightforward incorporation of the time variation in the dielectric permittivity.
Fluctuating interaction network and time-varying stability of a natural fish community
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.
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
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.
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.
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 w...... 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....
Gould, Harvey; Maddi, Jason; Dinneen, Timothy
2000-06-01
Time-invariant electric field gradients have long been used to deflect beams of molecules and neutral atoms. However, time-varying electric field gradients can also be used to accelerate, slow [1,2], cool [2], or bunch these same beams. The possible applications include slowing and cooling thermal beams of molecules and atoms, launching cold atoms from a trap into a fountain, beam transport, and measuring atomic dipole polarizabilities. [1] H.L. Bethlem, G. Berden, and G Meijer, Phys. Rev. Lett. 83, 1588 (1999). [2] J. A. Maddi, T.P. Dinneen, and H. Gould, Phys. Rev. A60, 3882 (1999).
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....
Modelling Conditional and Unconditional Heteroskedasticity with Smoothly Time-Varying Structure
DEFF Research Database (Denmark)
Amado, Christina; Teräsvirta, Timo
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...... 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...
Prediction of oil expression by uniaxial compression using time-varying oilseed properties
DEFF Research Database (Denmark)
Bargale, P. C.; Wulfsohn, Dvoralai; Irudayaraj, J.
2000-01-01
A mathematical simulation of uniaxial compression of oilseeds for oil extraction was developed based upon combining Terzaghi's theory of consolidation for saturated soils with Darcy's law for unsaturated flow, while incorporating the time-varying nature of the coefficients of permeability...... and consolidation. The model was validated for extruded soy and for sunflower seeds. Material parameters were determined experimentally and predictions of oil recovery rates made for several levels of temperature, pressure and initial sample depth. Results indicated that while the model predicted the values of oil...... of experimental permeability data in the very early stages of pressing (t time, when compared...
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.
Asymptotic theory of time varying networks with burstiness and heterogeneous activation patterns
Burioni, Raffaella; Ubaldi, Enrico; Vezzani, Alessandro
2017-05-01
The recent availability of large-scale, time-resolved and high quality digital datasets has allowed for a deeper understanding of the structure and properties of many real-world networks. The empirical evidence of a temporal dimension prompted the switch of paradigm from a static representation of networks to a time varying one. In this work we briefly review the framework of time-varying-networks in real world social systems, especially focusing on the activity-driven paradigm. We develop a framework that allows for the encoding of three generative mechanisms that seem to play a central role in the social networks’ evolution: the individual’s propensity to engage in social interactions, its strategy in allocate these interactions among its alters and the burstiness of interactions amongst social actors. The functional forms and probability distributions encoding these mechanisms are typically data driven. A natural question arises if different classes of strategies and burstiness distributions, with different local scale behavior and analogous asymptotics can lead to the same long time and large scale structure of the evolving networks. We consider the problem in its full generality, by investigating and solving the system dynamics in the asymptotic limit, for general classes of ties allocation mechanisms and waiting time probability distributions. We show that the asymptotic network evolution is driven by a few characteristics of these functional forms, that can be extracted from direct measurements on large datasets.
Estimation of Bid Curves in Power Exchanges using Time-varying Simultaneous-Equations Models
Ofuji, Kenta; Yamaguchi, Nobuyuki
Simultaneous-equations model (SEM) is generally used in economics to estimate interdependent endogenous variables such as price and quantity in a competitive, equilibrium market. In this paper, we have attempted to apply SEM to JEPX (Japan Electric Power eXchange) spot market, a single-price auction market, using the publicly available data of selling and buying bid volumes, system price and traded quantity. The aim of this analysis is to understand the magnitude of influences to the auctioned prices and quantity from the selling and buying bids, than to forecast prices and quantity for risk management purposes. In comparison with the Ordinary Least Squares (OLS) estimation where the estimation results represent average values that are independent of time, we employ a time-varying simultaneous-equations model (TV-SEM) to capture structural changes inherent in those influences, using State Space models with Kalman filter stepwise estimation. The results showed that the buying bid volumes has that highest magnitude of influences among the factors considered, exhibiting time-dependent changes, ranging as broad as about 240% of its average. The slope of the supply curve also varies across time, implying the elastic property of the supply commodity, while the demand curve remains comparatively inelastic and stable over time.
Chung, Tammy; Maisto, Stephen A.
2016-01-01
Introduction 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. Method 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. Results 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. Conclusions 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. PMID:26894550
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.
Cox models with dynamic ridge penalties on time-varying effects of the covariates.
Perperoglou, Aris
2014-01-15
Analysis of long-term follow-up survival studies require more sophisticated approaches than the proportional hazards model. To account for the dynamic behaviour of fixed covariates, penalized Cox models can be employed in models with interactions of the covariates and known time functions. In this work, I discuss some of the suggested methods and emphasize on the use of a ridge penalty in survival models. I review different strategies for choosing an optimal penalty weight and argue for the use of the computationally efficient restricted maximum likelihood (REML)-type method. A ridge penalty term can be subtracted from the likelihood when modelling time-varying effects in order to control the behaviour of the time functions. I suggest using flexible time functions such as B-splines and constrain the behaviour of these by adding proper penalties. I present the basic methods and illustrate different penalty weights in two different datasets. Copyright © 2013 John Wiley & Sons, Ltd.
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
Bit-level plane image encryption based on coupled map lattice with time-varying delay
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.
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.
Murugesan, Sugeerth; Bouchard, Kristofer; Chang, Edward; Dougherty, Max; Hamann, Bernd; Weber, Gunther H
2017-06-06
There exists a need for effective and easy-to-use software tools supporting the analysis of complex Electrocorticography (ECoG) data. Understanding how epileptic seizures develop or identifying diagnostic indicators for neurological diseases require the in-depth analysis of neural activity data from ECoG. Such data is multi-scale and is of high spatio-temporal resolution. Comprehensive analysis of this data should be supported by interactive visual analysis methods that allow a scientist to understand functional patterns at varying levels of granularity and comprehend its time-varying behavior. We introduce a novel multi-scale visual analysis system, ECoG ClusterFlow, for the detailed exploration of ECoG data. Our system detects and visualizes dynamic high-level structures, such as communities, derived from the time-varying connectivity network. The system supports two major views: 1) an overview summarizing the evolution of clusters over time and 2) an electrode view using hierarchical glyph-based design to visualize the propagation of clusters in their spatial, anatomical context. We present case studies that were performed in collaboration with neuroscientists and neurosurgeons using simulated and recorded epileptic seizure data to demonstrate our system's effectiveness. ECoG ClusterFlow supports the comparison of spatio-temporal patterns for specific time intervals and allows a user to utilize various clustering algorithms. Neuroscientists can identify the site of seizure genesis and its spatial progression during various the stages of a seizure. Our system serves as a fast and powerful means for the generation of preliminary hypotheses that can be used as a basis for subsequent application of rigorous statistical methods, with the ultimate goal being the clinical treatment of epileptogenic zones.
Dynamic linear models to explore time-varying suspended sediment-discharge rating curves
Ahn, Kuk-Hyun; Yellen, Brian; Steinschneider, Scott
2017-06-01
This study presents a new method to examine long-term dynamics in sediment yield using time-varying sediment-discharge rating curves. Dynamic linear models (DLMs) are introduced as a time series filter that can assess how the relationship between streamflow and sediment concentration or load changes over time in response to a wide variety of natural and anthropogenic watershed disturbances or long-term changes. The filter operates by updating parameter values using a recursive Bayesian design that responds to 1 day-ahead forecast errors while also accounting for observational noise. The estimated time series of rating curve parameters can then be used to diagnose multiscale (daily-decadal) variability in sediment yield after accounting for fluctuations in streamflow. The technique is applied in a case study examining changes in turbidity load, a proxy for sediment load, in the Esopus Creek watershed, part of the New York City drinking water supply system. The results show that turbidity load exhibits a complex array of variability across time scales. The DLM highlights flood event-driven positive hysteresis, where turbidity load remained elevated for months after large flood events, as a major component of dynamic behavior in the rating curve relationship. The DLM also produces more accurate 1 day-ahead loading forecasts compared to other static and time-varying rating curve methods. The results suggest that DLMs provide a useful tool for diagnosing changes in sediment-discharge relationships over time and may help identify variability in sediment concentrations and loads that can be used to inform dynamic water quality management.
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.
Shiyko, Mariya P; Burkhalter, Jack; Li, Runze; Park, Bernard J
2014-10-01
The goal of this article is to introduce to social and behavioral scientists the generalized time-varying effect model (TVEM), a semiparametric approach for investigating time-varying effects of a treatment. The method is best suited for data collected intensively over time (e.g., experience sampling or ecological momentary assessments) and addresses questions pertaining to effects of treatment changing dynamically with time. Thus, of interest is the description of timing, magnitude, and (nonlinear) patterns of the effect. Our presentation focuses on practical aspects of the model. A step-by-step demonstration is presented in the context of an empirical study designed to evaluate effects of surgical treatment on quality of life among early stage lung cancer patients during posthospitalization recovery (N = 59; 61% female, M age = 66.1 years). Frequency and level of distress associated with physical symptoms were assessed twice daily over a 2-week period, providing a total of 1,544 momentary assessments. Traditional analyses (analysis of covariance [ANCOVA], repeated-measures ANCOVA, and multilevel modeling) yielded findings of no group differences. In contrast, generalized TVEM identified a pattern of the effect that varied in time and magnitude. Group differences manifested after Day 4. Generalized TVEM is a flexible statistical approach that offers insight into the complexity of treatment effects and allows modeling of nonnormal outcomes. The practical demonstration, shared syntax, and availability of a free set of macros aim to encourage researchers to apply TVEM to complex data and stimulate important scientific discoveries. PsycINFO Database Record (c) 2014 APA, all rights reserved.
Time-Varying Transition Probability Matrix Estimation and Its Application to Brand Share Analysis
Chiba, Tomoaki; Akaho, Shotaro; Murata, Noboru
2017-01-01
In a product market or stock market, different products or stocks compete for the same consumers or purchasers. We propose a method to estimate the time-varying transition matrix of the product share using a multivariate time series of the product share. The method is based on the assumption that each of the observed time series of shares is a stationary distribution of the underlying Markov processes characterized by transition probability matrices. We estimate transition probability matrices for every observation under natural assumptions. We demonstrate, on a real-world dataset of the share of automobiles, that the proposed method can find intrinsic transition of shares. The resulting transition matrices reveal interesting phenomena, for example, the change in flows between TOYOTA group and GM group for the fiscal year where TOYOTA group’s sales beat GM’s sales, which is a reasonable scenario. PMID:28076383
Robust formation tracking control of mobile robots via one-to-one time-varying communication
Dasdemir, Janset; Loría, Antonio
2014-09-01
We solve the formation tracking control problem for mobile robots via linear control, under the assumption that each agent communicates only with one 'leader' robot and with one follower, hence forming a spanning-tree topology. We assume that the communication may be interrupted on intervals of time. As in the classical tracking control problem for non-holonomic systems, the swarm is driven by a fictitious robot which moves about freely and which is a leader to one robot only. Our control approach is decentralised and the control laws are linear with time-varying gains; in particular, this accounts for the case when position measurements may be lost over intervals of time. For both velocity-controlled and force-controlled systems, we establish uniform global exponential stability, hence consensus formation tracking, for the error system under a condition of persistency of excitation on the reference angular velocity of the virtual leader and on the control gains.
Optimal protocol for maximum work extraction in a feedback process with a time-varying potential
Kwon, Chulan
2017-12-01
The nonequilibrium nature of information thermodynamics is characterized by the inequality or non-negativity of the total entropy change of the system, memory, and reservoir. Mutual information change plays a crucial role in the inequality, in particular if work is extracted and the paradox of Maxwell's demon is raised. We consider the Brownian information engine where the protocol set of the harmonic potential is initially chosen by the measurement and varies in time. We confirm the inequality of the total entropy change by calculating, in detail, the entropic terms including the mutual information change. We rigorously find the optimal values of the time-dependent protocol for maximum extraction of work both for the finite-time and the quasi-static process.
Specification and testing of Multiplicative Time-Varying GARCH models with applications
DEFF Research Database (Denmark)
Amado, Cristina; Teräsvirta, Timo
2017-01-01
In this article, we develop a specification technique for building multiplicative time-varying GARCH models of Amado and Teräsvirta (2008, 2013). The variance is decomposed into an unconditional and a conditional component such that the unconditional variance component is allowed to evolve smoothly...... over time. This nonstationary component is defined as a linear combination of logistic transition functions with time as the transition variable. The appropriate number of transition functions is determined by a sequence of specification tests. For that purpose, a coherent modelling strategy based...... on statistical inference is presented. It is heavily dependent on Lagrange multiplier type misspecification tests. The tests are easily implemented as they are entirely based on auxiliary regressions. Finite-sample properties of the strategy and tests are examined by simulation. The modelling strategy...
Time-Varying Transition Probability Matrix Estimation and Its Application to Brand Share Analysis.
Chiba, Tomoaki; Hino, Hideitsu; Akaho, Shotaro; Murata, Noboru
2017-01-01
In a product market or stock market, different products or stocks compete for the same consumers or purchasers. We propose a method to estimate the time-varying transition matrix of the product share using a multivariate time series of the product share. The method is based on the assumption that each of the observed time series of shares is a stationary distribution of the underlying Markov processes characterized by transition probability matrices. We estimate transition probability matrices for every observation under natural assumptions. We demonstrate, on a real-world dataset of the share of automobiles, that the proposed method can find intrinsic transition of shares. The resulting transition matrices reveal interesting phenomena, for example, the change in flows between TOYOTA group and GM group for the fiscal year where TOYOTA group's sales beat GM's sales, which is a reasonable scenario.
Mitigation of time-varying distortions in Nyquist-WDM systems using machine learning
Granada Torres, Jhon J.; Varughese, Siddharth; Thomas, Varghese A.; Chiuchiarelli, Andrea; Ralph, Stephen E.; Cárdenas Soto, Ana M.; Guerrero González, Neil
2017-11-01
We propose a machine learning-based nonsymmetrical demodulation technique relying on clustering to mitigate time-varying distortions derived from several impairments such as IQ imbalance, bias drift, phase noise and interchannel interference. Experimental results show that those impairments cause centroid movements in the received constellations seen in time-windows of 10k symbols in controlled scenarios. In our demodulation technique, the k-means algorithm iteratively identifies the cluster centroids in the constellation of the received symbols in short time windows by means of the optimization of decision thresholds for a minimum BER. We experimentally verified the effectiveness of this computationally efficient technique in multicarrier 16QAM Nyquist-WDM systems over 270 km links. Our nonsymmetrical demodulation technique outperforms the conventional QAM demodulation technique, reducing the OSNR requirement up to ∼0.8 dB at a BER of 1 × 10-2 for signals affected by interchannel interference.
Parameter Estimation of a Closed Loop Coupled Tank Time Varying System using Recursive Methods
International Nuclear Information System (INIS)
Basir, Siti Nora; Yussof, Hanafiah; Shamsuddin, Syamimi; Selamat, Hazlina; Zahari, Nur Ismarrubie
2013-01-01
This project investigates the direct identification of closed loop plant using discrete-time approach. The uses of Recursive Least Squares (RLS), Recursive Instrumental Variable (RIV) and Recursive Instrumental Variable with Centre-Of-Triangle (RIV + COT) in the parameter estimation of closed loop time varying system have been considered. The algorithms were applied in a coupled tank system that employs covariance resetting technique where the time of parameter changes occur is unknown. The performances of all the parameter estimation methods, RLS, RIV and RIV + COT were compared. The estimation of the system whose output was corrupted with white and coloured noises were investigated. Covariance resetting technique successfully executed when the parameters change. RIV + COT gives better estimates than RLS and RIV in terms of convergence and maximum overshoot
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 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 FOPDT Modeling and On-line Parameter Identification
DEFF Research Database (Denmark)
Yang, Zhenyu; Sun, Zhen
2013-01-01
A type of Time-Varying First-Order Plus Dead-Time (TV-FOPDT) model is extended from SISO format into a MISO version by explicitly taking the disturbance input into consideration. Correspondingly, a set of on-line parameter identification algorithms oriented to MISO TV-FOPDT model are proposed based...... on the Mixed-Integer-Nonlinear Programming, Least-Mean-Square and sliding window techniques. The proposed approaches can simultaneously estimate the time-dependent system parameters, as well as the unknown disturbance input if it is the case, in an on-line manner. The proposed concepts and algorithms...... are firstly illustrated through a numerical example, and then applied to investigate transient superheat dynamic modeling in a supermarket refrigeration system....
Induction of Oxidation in Living Cells by Time-Varying Electromagnetic Fields
Stolc, Viktor
2015-01-01
We are studying how biological systems can harness quantum effects of time varying electromagnetic (EM) waves as the time-setting basis for universal biochemical organization via the redox cycle. The effects of extremely weak EM field on the biochemical redox cycle can be monitored through real-time detection of oxidation-induced light emissions of reporter molecules in living cells. It has been shown that EM fields can also induce changes in fluid transport rates through capillaries (approximately 300 microns inner diameter) by generating annular proton gradients. This effect may be relevant to understanding cardiovascular dis-function in spaceflight, beyond the ionosphere. Importantly, we show that these EM effects can be attenuated using an active EM field cancellation device. Central for NASA's Human Research Program is the fact that the absence of ambient EM field in spaceflight can also have a detrimental influence, namely via increased oxidative damage, on DNA replication, which controls heredity.
Modal Vibration Control in Periodic Time-Varying Structures with Focus on Rotor-Blade Systems
DEFF Research Database (Denmark)
Christensen, Rene Hardam; Santos, Ilmar
2003-01-01
to be overcome. Among others it is necessary, that the control scheme is capable to cope with non-linear time-varying dynamical system behaviour. However, rotating at constant speed the mathematical model becomes periodic time-variant. In this framework the present paper gives a contribution to design procedures...... is reformulated using complex mode theory. Next, a linear constant gain controller for the reformulated system is designed by linear control technique. Finally, this constant gain controller is transformed to a time-periodic form by applying reverse modal transformation. The non-measurable states are estimated......The demands for high efficiency machines initiate a demand for monitoring and active control of vibrations to improve machinery performance and to prolong machinery lifetime. Applying active control to reduce vibrations in flexible bladed rotor-systems imply that several difficulties have...
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
Inferring the mesoscale structure of layered, edge-valued, and time-varying networks
Peixoto, Tiago P.
2015-10-01
Many network systems are composed of interdependent but distinct types of interactions, which cannot be fully understood in isolation. These different types of interactions are often represented as layers, attributes on the edges, or as a time dependence of the network structure. Although they are crucial for a more comprehensive scientific understanding, these representations offer substantial challenges. Namely, it is an open problem how to precisely characterize the large or mesoscale structure of network systems in relation to these additional aspects. Furthermore, the direct incorporation of these features invariably increases the effective dimension of the network description, and hence aggravates the problem of overfitting, i.e., the use of overly complex characterizations that mistake purely random fluctuations for actual structure. In this work, we propose a robust and principled method to tackle these problems, by constructing generative models of modular network structure, incorporating layered, attributed and time-varying properties, as well as a nonparametric Bayesian methodology to infer the parameters from data and select the most appropriate model according to statistical evidence. We show that the method is capable of revealing hidden structure in layered, edge-valued, and time-varying networks, and that the most appropriate level of granularity with respect to the additional dimensions can be reliably identified. We illustrate our approach on a variety of empirical systems, including a social network of physicians, the voting correlations of deputies in the Brazilian national congress, the global airport network, and a proximity network of high-school students.
Reusable Launch Vehicle Attitude Control Using a Time-Varying Sliding Mode Control Technique
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.
International Nuclear Information System (INIS)
Katou, Kanemitsu
1981-01-01
It is shown that the transport equations for the electromagnetic wave energy density W sub(k) and momentum density P sub(k) in transparent, dispersive, space- and time-varying media are given by dW sub(k)/dt = ωsub(k)sup(-1)deltaωsub(k)/delta t W sub(k) + 2γsub(k)W sub(k) and by dP sub(k)/dt = -k -1 .deltaωsub(k)/delta r P sub(k) + 2γsub(k)P sub(k), respectively, where d/dt denotes the total time derivative along the ray trajectory and γsub(k) is the growth rate. The terms ωsub(k)sup(-1)deltaωsub(k)/delta t W sub(k) and -k -1 .deltaωsub(k)/delta r P sub(k) result from the fact that the wave energy and momentum density are not adiabatic invariants in space- and time-varying media. It is assumed that the geometric optics approximation and the nonlocal linear response theory are valid. (author)
Adaptive neural control of nonlinear MIMO systems with time-varying output constraints.
Meng, Wenchao; Yang, Qinmin; Sun, Youxian
2015-05-01
In this paper, adaptive neural control is investigated for a class of unknown multiple-input multiple-output nonlinear systems with time-varying asymmetric output constraints. To ensure constraint satisfaction, we employ a system transformation technique to transform the original constrained (in the sense of the output restrictions) system into an equivalent unconstrained one, whose stability is sufficient to solve the output constraint problem. It is shown that output tracking is achieved without violation of the output constraint. More specifically, we can shape the system performance arbitrarily on transient and steady-state stages with the output evolving in predefined time-varying boundaries all the time. A single neural network, whose weights are tuned online, is used in our design to approximate the unknown functions in the system dynamics, while the singularity problem of the control coefficient matrix is avoided without assumption on the prior knowledge of control input's bound. All the signals in the closed-loop system are proved to be semiglobally uniformly ultimately bounded via Lyapunov synthesis. Finally, the merits of the proposed controller are verified in the simulation environment.
Time-varying land subsidence detected by radar altimetry: California, Taiwan and north China.
Hwang, Cheinway; Yang, Yuande; Kao, Ricky; Han, Jiancheng; Shum, C K; Galloway, Devin L; Sneed, Michelle; Hung, Wei-Chia; Cheng, Yung-Sheng; Li, Fei
2016-06-21
Contemporary applications of radar altimetry include sea-level rise, ocean circulation, marine gravity, and icesheet elevation change. Unlike InSAR and GNSS, which are widely used to map surface deformation, altimetry is neither reliant on highly temporally-correlated ground features nor as limited by the available spatial coverage, and can provide long-term temporal subsidence monitoring capability. Here we use multi-mission radar altimetry with an approximately 23 year data-span to quantify land subsidence in cropland areas. Subsidence rates from TOPEX/POSEIDON, JASON-1, ENVISAT, and JASON-2 during 1992-2015 show time-varying trends with respect to displacement over time in California's San Joaquin Valley and central Taiwan, possibly related to changes in land use, climatic conditions (drought) and regulatory measures affecting groundwater use. Near Hanford, California, subsidence rates reach 18 cm yr(-1) with a cumulative subsidence of 206 cm, which potentially could adversely affect operations of the planned California High-Speed Rail. The maximum subsidence rate in central Taiwan is 8 cm yr(-1). Radar altimetry also reveals time-varying subsidence in the North China Plain consistent with the declines of groundwater storage and existing water infrastructure detected by the Gravity Recovery And Climate Experiment (GRACE) satellites, with rates reaching 20 cm yr(-1) and cumulative subsidence as much as 155 cm.
Klotz, Justin R; Obuz, Serhat; Kan, Zhen; Dixon, Warren E
2018-02-01
A decentralized controller is designed for leader-based synchronization of communication-delayed networked agents. The agents have heterogeneous dynamics modeled by uncertain, nonlinear Euler-Lagrange equations of motion affected by heterogeneous, unknown, exogenous disturbances. The developed controller requires only one-hop (delayed) communication from network neighbors and the communication delays are assumed to be heterogeneous, uncertain, and time-varying. Each agent uses an estimate of communication delay to provide feedback of estimated recent tracking error. Simulation results are provided to demonstrate the improved performance of the developed controller over other popular control designs.
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.
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.
Directory of Open Access Journals (Sweden)
Lun Zhai
2014-01-01
Full Text Available A parametric learning based robust iterative learning control (ILC scheme is applied to the time varying delay multiple-input and multiple-output (MIMO linear systems. The convergence conditions are derived by using the H∞ and linear matrix inequality (LMI approaches, and the convergence speed is analyzed as well. A practical identification strategy is applied to optimize the learning laws and to improve the robustness and performance of the control system. Numerical simulations are illustrated to validate the above concepts.
A time-varying copula mixture for hedging the clean spark spread with wind power futures
DEFF Research Database (Denmark)
Christensen, Troels Sønderby; Pircalabu, Anca; Høg, Esben
2018-01-01
trading in the spot clean spark spread and wind power futures. To facilitate hedging decisions, we propose a time-varying copula mixture for the joint behavior of the spot clean spark spread and the daily wind index. The model describes the data surprisingly well, both in terms of the marginals...... and the dependence structure, while being straightforward and easy to implement. Based on Monte Carlo simulations from the proposed model, the results indicate that significant benefits can be achieved by using wind power futures to hedge the spot clean spark spread. Moreover, a comparison study shows...
Deformation of Brillouin gain spectrum shape caused by strain varying linearly with respect to time
Naruse, Hiroshi; Komatsu, Ayako; Tateda, Mitsuhiro
2015-09-01
The shape of the Brillouin gain spectrum (BGS) that is produced in an optical fiber undergoing strain varying linearly with respect to time, which is a typical example of temporally non-uniform strain, is theoretically derived through an analysis similar to that by which the BGS under spatially non-uniform strain would be derived. The BGS shape that is theoretically derived agrees well with the shape experimentally observed. The characteristics of the BGS deformation and strain measurement error under the temporally linear strain are discussed based on their similarity to the BGS shape derived under spatially linear strain.
Directory of Open Access Journals (Sweden)
Yueyang Li
2014-01-01
Full Text Available This paper investigates the H∞ fixed-lag fault estimator design for linear discrete time-varying (LDTV systems with intermittent measurements, which is described by a Bernoulli distributed random variable. Through constructing a novel partially equivalent dynamic system, the fault estimator design is converted into a deterministic quadratic minimization problem. By applying the innovation reorganization technique and the projection formula in Krein space, a necessary and sufficient condition is obtained for the existence of the estimator. The parameter matrices of the estimator are derived by recursively solving two standard Riccati equations. An illustrative example is provided to show the effectiveness and applicability of the proposed algorithm.
International Nuclear Information System (INIS)
Liang Jinling; Cao Jinde
2003-01-01
In this Letter, the problems of boundedness and stability for a general class of non-autonomous recurrent neural networks with variable coefficients and time-varying delays are analyzed via employing Young inequality technique and Lyapunov method. Some simple sufficient conditions are given for boundedness and stability of the solutions for the recurrent neural networks. These results generalize and improve the previous works, and they are easy to check and apply in practice. Two illustrative examples and their numerical simulations are also given to demonstrate the effectiveness of the proposed results
International Nuclear Information System (INIS)
Zhu Xunlin; Wang Youyi
2009-01-01
This Letter studies the exponential stability for a class of neural networks (NNs) with both discrete and distributed time-varying delays. Under weaker assumptions on the activation functions, by defining a more general type of Lyapunov functionals and developing a new convex combination technique, new less conservative and less complex stability criteria are established to guarantee the global exponential stability of the discussed NNs. The obtained conditions are dependent on both discrete and distributed delays, are expressed in terms of linear matrix inequalities (LMIs), and contain fewer decision variables. Numerical examples are given to illustrate the effectiveness and the less conservatism of the proposed conditions.
Gong, Shuqing; Yang, Shaofu; Guo, Zhenyuan; Huang, Tingwen
2018-06-01
The paper is concerned with the synchronization problem of inertial memristive neural networks with time-varying delay. First, by choosing a proper variable substitution, inertial memristive neural networks described by second-order differential equations can be transformed into first-order differential equations. Then, a novel controller with a linear diffusive term and discontinuous sign term is designed. By using the controller, the sufficient conditions for assuring the global exponential synchronization of the derive and response neural networks are derived based on Lyapunov stability theory and some inequality techniques. Finally, several numerical simulations are provided to substantiate the effectiveness of the theoretical results. Copyright © 2018 Elsevier Ltd. All rights reserved.
Directory of Open Access Journals (Sweden)
Linlin Ma
2016-01-01
Full Text Available This paper studies the stabilization problem for damping multimachine power system with time-varying delays and sector saturating actuator. The multivariable proportional plus derivative (PD type stabilizer is designed by transforming the problem of PD controller design to that of state feedback stabilizer design for a system in descriptor form. A new sufficient condition of closed-loop multimachine power system asymptomatic stability is derived based on the Lyapunov theory. Computer simulation of a two-machine power system has verified the effectiveness and efficiency of the proposed approach.
Gold as an Infl ation Hedge in a Time-Varying Coefficient Framework
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...
Gold as an Infl ation Hedge in a Time-Varying Coeffi cient Framework
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...
Combined time-varying forecast based on the proper scoring approach for wind power generation
DEFF Research Database (Denmark)
Chen, Xingying; Jiang, Yu; Yu, Kun
2017-01-01
Compared with traditional point forecasts, combined forecast have been proposed as an effective method to provide more accurate forecasts than individual model. However, the literature and research focus on wind-power combined forecasts are relatively limited. Here, based on forecasting error...... distribution, a proper scoring approach is applied to combine plausible models to form an overall time-varying model for the next day forecasts, rather than weights-based combination. To validate the effectiveness of the proposed method, real data of 3 years were used for testing. Simulation results...... demonstrate that the proposed method improves the accuracy of overall forecasts, even compared with a numerical weather prediction....
Su, Weiwei; Chen, Yiming
2009-05-01
In this paper, the global exponential stability is investigated for a class of stochastic interval neural networks with time-varying delays. The parameter uncertainties are assumed to be bounded in given compact sets. Based on Lyapunov stable theory and stochastic analysis approaches, the delay-dependent criteria are derived to ensure the global, robust, exponential stability of the addressed system in the mean square. The criteria can be checked easily by the LMI control toolbox in Matlab. A numerical example is given to illustrate the effectiveness and improvement over some existing results.
Global asymptotic stability analysis for neutral stochastic neural networks with time-varying delays
Su, Weiwei; Chen, Yiming
2009-04-01
In this paper, the global asymptotic stability is investigated for a class of neutral stochastic neural networks with time-varying delays and norm-bounded uncertainties. Based on Lyapunov stability theory and stochastic analysis approaches, delay-dependent criteria are derived to ensure the global, robust, asymptotic stability of the addressed system in the mean square for all admissible parameter uncertainties. The criteria can be checked easily by the LMI Control Toolbox in Matlab. A numerical example is given to illustrate the feasibility and effectiveness of the results.
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.)
DEFF Research Database (Denmark)
Olsen, Jørgen Lundegaard
index (NDVI), which combines red and near infrared (NIR) spectral regions. From NDVI data a greening of the Sahel have been identified since the 80s and attributed to increasing trends in annual rainfall for large parts of the region. One part of this thesis analyses time series of parameterized MODIS...... NDVI using the unique field data set from the Widou Thiengoly test site in northern Senegal. The field data have been collected under controlled grazing intensities. From this data a very clear effect of grazing on plant species composition and NPP/NDVI relationships is found. It is suggested...... that the varying NPP/NDVI relationships, combined with the large increase in livestock of the Sahel in recent decades, means that the greening of the Sahel cannot uncritically be interpreted as a positive trend in vegetation productivity due to increasing rainfall. It can also represent grazing induced changes...
2018-01-01
This paper mainly studies the globally fixed-time synchronization of a class of coupled neutral-type neural networks with mixed time-varying delays via discontinuous feedback controllers. Compared with the traditional neutral-type neural network model, the model in this paper is more general. A class of general discontinuous feedback controllers are designed. With the help of the definition of fixed-time synchronization, the upper right-hand derivative and a defined simple Lyapunov function, some easily verifiable and extensible synchronization criteria are derived to guarantee the fixed-time synchronization between the drive and response systems. Finally, two numerical simulations are given to verify the correctness of the results. PMID:29370248
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Mingwen Zheng
Full Text Available This paper mainly studies the globally fixed-time synchronization of a class of coupled neutral-type neural networks with mixed time-varying delays via discontinuous feedback controllers. Compared with the traditional neutral-type neural network model, the model in this paper is more general. A class of general discontinuous feedback controllers are designed. With the help of the definition of fixed-time synchronization, the upper right-hand derivative and a defined simple Lyapunov function, some easily verifiable and extensible synchronization criteria are derived to guarantee the fixed-time synchronization between the drive and response systems. Finally, two numerical simulations are given to verify the correctness of the results.
Zheng, Mingwen; Li, Lixiang; Peng, Haipeng; Xiao, Jinghua; Yang, Yixian; Zhang, Yanping; Zhao, Hui
2018-01-01
This paper mainly studies the globally fixed-time synchronization of a class of coupled neutral-type neural networks with mixed time-varying delays via discontinuous feedback controllers. Compared with the traditional neutral-type neural network model, the model in this paper is more general. A class of general discontinuous feedback controllers are designed. With the help of the definition of fixed-time synchronization, the upper right-hand derivative and a defined simple Lyapunov function, some easily verifiable and extensible synchronization criteria are derived to guarantee the fixed-time synchronization between the drive and response systems. Finally, two numerical simulations are given to verify the correctness of the results.
Calculation of rectal dose surface histograms in the presence of time varying deformations
International Nuclear Information System (INIS)
Roeske, John C.; Spelbring, Danny R.; Vijayakumar, S.; Forman, Jeffrey D.; Chen, George T.Y.
1996-01-01
Purpose: Dose volume (DVH) and dose surface histograms (DSH) of the bladder and rectum are usually calculated from a single treatment planning scan. These DVHs and DSHs will eventually be correlated with complications to determine parameters for normal tissue complication probabilities (NTCP). However, from day to day, the size and shape of the rectum and bladder may vary. The purpose of this study is to compare a more accurate estimate of the time integrated DVHs and DSHs of the rectum (in the presence of daily variations in rectal shape) to initial DVHs/DSHs. Methods: 10 patients were scanned once per week during the course of fractionated radiotherapy, typically accumulating a total of six scans. The rectum and bladder were contoured on each of the studies. The model used to assess effects of rectal contour deformation is as follows: the contour on a given axial slice (see figure) is boxed within a rectangle. A line drawn parallel to the AP axis through the rectangle equally partitions the box. Starting at the intersection of the vertical line and the rectal contour, points on the contour are marked off representing the same rectal dose point, even in the presence of distortion. Corresponding numbered points are used to sample the dose matrix and create a composite DSH. The model assumes uniform stretching of the rectal contour for any given axial cut, and no twist of the structure or vertical displacement. A similar model is developed for the bladder with spherical symmetry. Results: Normalized DSHs (nDSH) for each CT scan were calculated as well as the time averaged nDSH over all scans. These were compared with the nDSH from the initial planning scan. Individual nDSHs differed by 8% surface area irradiated at the 80% dose level, to as much as 20% surface area in the 70-100% dose range. DSH variations are due to position and shape changes in the rectum during different CT scans. The spatial distribution of dose is highly variable, and depends on the field
Modeling Nonstationary Emotion Dynamics in Dyads using a Time-Varying Vector-Autoregressive Model.
Bringmann, Laura F; Ferrer, Emilio; Hamaker, Ellen L; Borsboom, Denny; Tuerlinckx, Francis
2018-03-05
Emotion dynamics are likely to arise in an interpersonal context. Standard methods to study emotions in interpersonal interaction are limited because stationarity is assumed. This means that the dynamics, for example, time-lagged relations, are invariant across time periods. However, this is generally an unrealistic assumption. Whether caused by an external (e.g., divorce) or an internal (e.g., rumination) event, emotion dynamics are prone to change. The semi-parametric time-varying vector-autoregressive (TV-VAR) model is based on well-studied generalized additive models, implemented in the software R. The TV-VAR can explicitly model changes in temporal dependency without pre-existing knowledge about the nature of change. A simulation study is presented, showing that the TV-VAR model is superior to the standard time-invariant VAR model when the dynamics change over time. The TV-VAR model is applied to empirical data on daily feelings of positive affect (PA) from a single couple. Our analyses indicate reliable changes in the male's emotion dynamics over time, but not in the female's-which were not predicted by her own affect or that of her partner. This application illustrates the usefulness of using a TV-VAR model to detect changes in the dynamics in a system.
The estimation of time-varying risks in asset pricing modelling using B-Spline method
Nurjannah; Solimun; Rinaldo, Adji
2017-12-01
Asset pricing modelling has been extensively studied in the past few decades to explore the risk-return relationship. The asset pricing literature typically assumed a static risk-return relationship. However, several studies found few anomalies in the asset pricing modelling which captured the presence of the risk instability. The dynamic model is proposed to offer a better model. The main problem highlighted in the dynamic model literature is that the set of conditioning information is unobservable and therefore some assumptions have to be made. Hence, the estimation requires additional assumptions about the dynamics of risk. To overcome this problem, the nonparametric estimators can also be used as an alternative for estimating risk. The flexibility of the nonparametric setting avoids the problem of misspecification derived from selecting a functional form. This paper investigates the estimation of time-varying asset pricing model using B-Spline, as one of nonparametric approach. The advantages of spline method is its computational speed and simplicity, as well as the clarity of controlling curvature directly. The three popular asset pricing models will be investigated namely CAPM (Capital Asset Pricing Model), Fama-French 3-factors model and Carhart 4-factors model. The results suggest that the estimated risks are time-varying and not stable overtime which confirms the risk instability anomaly. The results is more pronounced in Carhart’s 4-factors model.
Study on the Variation of Groundwater Level under Time-varying Recharge
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.
Adaptive sliding control of non-autonomous active suspension systems with time-varying loadings
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.
Propagation of a laser beam in a time-varying waveguide. [plasma heating for controlled fusion
Chapman, J. M.; Kevorkian, J.
1978-01-01
The propagation of an axisymmetric laser beam in a plasma column having a radially parabolic electron density distribution is reported. For the case of an axially uniform waveguide it is found that the basic characteristics of alternating focusing and defocusing beams are maintained. However, the intensity distribution is changed at the foci and outer-beam regions. The features of paraxial beam propagation are discussed with reference to axially varying waveguides. Laser plasma coupling is considered noting the case where laser heating produces a density distribution radially parabolic near the axis and the energy absorbed over the focal length of the plasma is small. It is found that: (1) beam-propagation stability is governed by the relative magnitude of the density fluctuations existing in the axial variation of the waveguides due to laser heating, and (2) for beam propagation in a time-varying waveguide, the global instability of the propagation is a function of the initial fluctuation growth rate as compared to the initial time rate of change in the radial curvature of the waveguide.
H∞state estimation of stochastic memristor-based neural networks with time-varying delays.
Bao, Haibo; Cao, Jinde; Kurths, Jürgen; Alsaedi, Ahmed; Ahmad, Bashir
2018-03-01
This paper addresses the problem of H ∞ state estimation for a class of stochastic memristor-based neural networks with time-varying delays. Under the framework of Filippov solution, the stochastic memristor-based neural networks are transformed into systems with interval parameters. The present paper is the first to investigate the H ∞ state estimation problem for continuous-time Itô-type stochastic memristor-based neural networks. By means of Lyapunov functionals and some stochastic technique, sufficient conditions are derived to ensure that the estimation error system is asymptotically stable in the mean square with a prescribed H ∞ performance. An explicit expression of the state estimator gain is given in terms of linear matrix inequalities (LMIs). Compared with other results, our results reduce control gain and control cost effectively. Finally, numerical simulations are provided to demonstrate the efficiency of the theoretical results. Copyright © 2018 Elsevier Ltd. All rights reserved.
Linear Time Varying Approach to Satellite Attitude Control Using only Electromagnetic Actuation
DEFF Research Database (Denmark)
Wisniewski, Rafal
1997-01-01
, lightweight, and power efficient actuators is therefore crucial and viable. This paper discusses linear attitude control strategies for a low earth orbit satellite actuated by a set of mutually perpendicular electromagnetic coils. The principle is to use the interaction between the Earth's magnetic field...... and the magnetic field generated by the coils. A key challenge is the fact that the mechanical torque can only be produced in a plane perpendicular to the local geomagnetic field vector, therefore the satellite is not controllable when considered at fixed time. Availability of design methods for time varying...... systems is limited, nevertheless, a solution of the Riccati equation gives an excellent frame for investigations provided in this paper. An observation that geomagnetic field changes approximately periodically when a satellite is on a near polar orbit is used throughout this paper. Three types of attitude...
Linear Time Varying Approach to Satellite Attitude Control Using only Electromagnetic Actuation
DEFF Research Database (Denmark)
Wisniewski, Rafal
2000-01-01
, lightweight, and power efficient actuators is therefore crucial and viable. This paper discusser linear attitude control strategies for a low earth orbit satellite actuated by a set of mutually perpendicular electromagnetic coils. The principle is to use the interaction between the Earth's magnetic field...... and the magnetic field generated by the coils. A key challenge is the fact that the mechanical torque can only be produced in a plane perpendicular to the local geomagnetic field vector, therefore the satellite is not controllable at fixed time. Avaliability of design methods for time varying systems is limited......, nevertheless, a solution of the riccati equation gives an excellent frame for investigations provided in this paper. An observation that geomagnetic field changes approximately periodically when satellite is on a near polar orbit is used throughout this paper. Three types of attitude controllers are proposed...
Song, Zhibao; Zhai, Junyong
2018-02-22
This paper addresses the problem of adaptive output-feedback control for a class of switched stochastic time-delay nonlinear systems with uncertain output function, where both the control coefficients and time-varying delay are unknown. The drift and diffusion terms are subject to unknown homogeneous growth condition. By virtue of adding a power integrator technique, an adaptive output-feedback controller is designed to render that the closed-loop system is bounded in probability, and the state of switched stochastic nonlinear system can be globally regulated to the origin almost surely. A numerical example is provided to demonstrate the validity of the proposed control method. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
Stability analysis of switched stochastic neural networks with time-varying delays.
Wu, Xiaotai; Tang, Yang; Zhang, Wenbing
2014-03-01
This paper is concerned with the global exponential stability of switched stochastic neural networks with time-varying delays. Firstly, the stability of switched stochastic delayed neural networks with stable subsystems is investigated by utilizing the mathematical induction method, the piecewise Lyapunov function and the average dwell time approach. Secondly, by utilizing the extended comparison principle from impulsive systems, the stability of stochastic switched delayed neural networks with both stable and unstable subsystems is analyzed and several easy to verify conditions are derived to ensure the exponential mean square stability of switched delayed neural networks with stochastic disturbances. The effectiveness of the proposed results is illustrated by two simulation examples. Copyright © 2013 Elsevier Ltd. All rights reserved.
End-of-the-year economic growth and time-varying expected returns
DEFF Research Database (Denmark)
Møller, Stig V.; Rangvid, Jesper
2015-01-01
We show that macroeconomic growth at the end of the year (fourth quarter or December) strongly influences expected returns on risky financial assets, whereas economic growth during the rest of the year does not. We find this pattern for many different asset classes, across different time periods...... quarters of the year. Our findings suggest that expected returns, risk aversion, and economic growth are particularly related at the end of the year, when we also expect consumers׳ portfolio adjustments to be concentrated......., and for US and international data. We also show that movements in the surplus consumption ratio of Campbell and Cochrane (1999) , a theoretically well-founded measure of time-varying risk aversion linked to macroeconomic growth, influence expected returns stronger during the fourth quarter than the other...
The Oil Price and Exchange Rate Relationship Revisited: A time-varying VAR parameter approach
Directory of Open Access Journals (Sweden)
Vincent Brémond
2016-07-01
Full Text Available The aim of this paper is to study the relationship between the effective exchange rate of the dollar and the oil price dynamics from 1976 to 2013. We explore the links between financial factors (exchange rate, monetary policy, international liquidity and the oil price volatility. Using a Bayesian time-varying parameter vector auto-regressive estimation we demonstrate that the “historical coincidence” of oil and financial crises can be explained by the specificities of the relationship between these two commodities. The results of this paper are twofold. The US Dollar effective exchange rate elasticity of crude oil prices is not constant across time and remains negative from 1989: a depreciation of the effective exchange rate of the dollar triggers an increase of crude oil prices. This paper also demonstrates the contagion of financial commodities markets development upon the global economy.
Accelerating Time-Varying Hardware Volume Rendering Using TSP Trees and Color-Based Error Metrics
Ellsworth, David; Chiang, Ling-Jen; Shen, Han-Wei; Kwak, Dochan (Technical Monitor)
2000-01-01
This paper describes a new hardware volume rendering algorithm for time-varying data. The algorithm uses the Time-Space Partitioning (TSP) tree data structure to identify regions within the data that have spatial or temporal coherence. By using this coherence, the rendering algorithm can improve performance when the volume data is larger than the texture memory capacity by decreasing the amount of textures required. This coherence can also allow improved speed by appropriately rendering flat-shaded polygons instead of textured polygons, and by not rendering transparent regions. To reduce the polygonization overhead caused by the use of the hierarchical data structure, we introduce an optimization method using polygon templates. The paper also introduces new color-based error metrics, which more accurately identify coherent regions compared to the earlier scalar-based metrics. By showing experimental results from runs using different data sets and error metrics, we demonstrate that the new methods give substantial improvements in volume rendering performance.
Stochastic Motion of Test Particle Implies That G Varies with Time
Momeni, Davood
2011-08-01
The aim of this letter is to propose a new description to the time varying gravitational constant problem, which naturally implements the Dirac's large numbers hypothesis in a new proposed holographic scenario for the origin of gravity as an entropic force. We survey the effect of the Stochastic motion of the test particle in Verlinde's scenario for gravity (Verlinde in arXiv:1001.0785 , 2010). Firstly we show that we must get the equipartition values for t→∞ which leads to the usual Newtonian gravitational constant. Secondly, the stochastic (Brownian) essence of the motion of the test particle, modifies the Newton's 2nd law. The direct result is that the Newtonian constant has been time dependence in resemblance as Setare and Momeni ( arXiv:1004.0589 , 2010).
A Time-Varied Probabilistic ON/OFF Switching Algorithm for Cellular Networks
Rached, Nadhir B.
2018-01-11
In this letter, we develop a time-varied probabilistic on/off switching planning method for cellular networks to reduce their energy consumption. It consists in a risk-aware optimization approach that takes into consideration the randomness of the user profile associated with each base station (BS). The proposed approach jointly determines (i) the instants of time at which the current active BS configuration must be updated due to an increase or decrease of the network traffic load, and (ii) the set of minimum BSs to be activated to serve the networks’ subscribers. Probabilistic metrics modeling the traffic profile variation are developed to trigger this dynamic on/off switching operation. Selected simulation results are then performed to validate the proposed algorithm for different system parameters.
Correlation-based characterisation of time-varying dynamical complexity in the Earth's magnetosphere
Donner, Reik V.; Balasis, George; Kurths, Jürgen
2014-05-01
The dynamical behaviour of the magnetosphere is known to be a sensitive indicator for the response of the system to solar wind coupling. Since the solar activity commonly displays very interesting non-stationary and multi-scale dynamics, the magnetospheric response also exhibits a high degree of dynamical complexity associated with fundamentally different characteristics during periods of quiescence and magnetic storms. The resulting temporal complexity profile has been explored regarding several approaches from applied statistics, dynamical systems theory and statistical mechanics. Here, we propose an alternative way of looking at time-varying dynamical complexity of nonlinear geophysical time series utilising subtle but significant changes in the linear auto-correlation structure of the recorded data. Our approach is demonstrated to sensitively trace the dynamic signatures associated with intense magnetic storms, and to display reasonable skills in distinguishing between quiescence and storm periods. The potentials and methodological limitations of this new viewpoint are discussed in some detail.
Asymptotical stability of stochastic neural networks with multiple time-varying delays
Zhou, Xianghui; Zhou, Wuneng; Dai, Anding; Yang, Jun; Xie, Lili
2015-03-01
The stochastic neural networks can be considered as an expansion of cellular neural networks and Hopfield neural networks. In real world, the neural networks are prone to be instable due to time delay and external disturbance. In this paper, we consider the asymptotic stability for the stochastic neural networks with multiple time-varying delays. By employing a Lyapunov-Krasovskii function, a sufficient condition which guarantees the asymptotic stability of the state trajectory in the mean square is obtained. The criteria proposed can be verified readily by utilising the linear matrix inequality toolbox in Matlab, and no parameters to be tuned. In the end, two numerical examples are provided to demonstrate the effectiveness of the proposed method.
Periodic solution for state-dependent impulsive shunting inhibitory CNNs with time-varying delays.
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.
Korayem, M H; Nekoo, S R
2015-01-01
This article investigates finite-time optimal and suboptimal controls for time-varying systems with state and control nonlinearities. The state-dependent Riccati equation (SDRE) controller was the main framework. A finite-time constraint imposed on the equation changes it to a differential equation, known as the state-dependent differential Riccati equation (SDDRE) and this equation was applied to the problem reported in this study that provides general formulation and stability analysis. The following four solution methods were developed for solving the SDDRE; backward integration, state transition matrix (STM) and the Lyapunov based method. In the Lyapunov approach, both positive and negative definite solutions to related SDRE were used to provide suboptimal gain for the SDDRE. Finite-time suboptimal control is applied for robotic manipulator, as finite-time constraint strongly decreases state error and operation time. General state-dependent coefficient (SDC) parameterizations for rigid and flexible joint arms (prismatic or revolute joints) are introduced. By including nonlinear control inputs in the formulation, the actuator׳s limits can be inserted directly to the state-space equation of a manipulator. A finite-time SDRE was implemented on a 6R manipulator both in theory and experimentally. And a reduced 3R arm was modeled and tested as a flexible joint robot (FJR). Evaluations of load carrying capacity and operation time were investigated to assess the capability of this approach, both of which showed significant improvement. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
Vasilenko, Sara A; Piper, Megan E; Lanza, Stephanie T; Liu, Xiaoyu; Yang, Jingyun; Li, Runze
2014-05-01
Researchers have increasingly begun to gather ecological momentary assessment (EMA) data on smoking, but new statistical methods are necessary to fully unlock information from such data. In this paper, we use a new technique, the logistic time-varying effect model (logistic TVEM), to examine the odds of smoking in the 2 weeks after a quit attempt. Data are from a subsample of participants from a randomized, placebo-controlled trial of smoking cessation pharmacotherapies who achieved initial abstinence (N = 1,106, 58% female). Participants completed up to 4 EMA assessments per day during the 2 weeks after their quit day. Predictors include baseline nicotine dependence, EMA measures of craving and negative affect, and whether an individual was assigned to a placebo, monotherapy, or combination therapy condition. Time-varying effects of these predictors were estimated using logistic TVEM. Cravings were a significant predictor of smoking throughout the entire 2 weeks postquit, whereas the effect of baseline dependence became nonsignificant by the second week, and the effect of negative affect increased over time. Individuals in the monotherapy and combination therapy conditions had decreased odds of smoking compared with placebo in the first week postquit, but these differences were nonsignificant in the second week. Findings suggest that pharmacotherapies are more effective compared with placebo earlier in a quit attempt, when the effect of baseline nicotine dependence on smoking is stronger, whereas the effect of craving and negative affect increased over time. Future cessation therapies may be more successful by providing additional support in the second week after quit attempt.
Time-varying subspace dimensionality: Useful as a seismic signal detection method?
Rowe, C. A.; Stead, R. J.; Begnaud, M. L.
2012-12-01
We explore the application of dimensional analysis to the problem of anomaly detection in multichannel time series. These techniques, which have been used for real-time load management in large computer systems, revolve around the time-varying dimensionality estimates of the signal subspace. Our application is to multiple channels of incoming seismic waveform data, as from a large array or across a network. Subspace analysis has been applied to seismic data before, but the routine use of the method is for the identification of a particular signal type, and requires a priori information about the range of signals for which the algorithm is searching. In this paradigm, a known but variable source (such as a mining region or aftershock sequence) provides known waveforms that are assumed to span the space occupied by incoming events of interest. Singular value decomposition or principal components analysis of the identified waveforms will allow for the selection of basis vectors that define the subspace onto which incoming signals are projected, to determine whether they belong to the source population of interest. In our application we do not seek to compare incoming signals to previously identified waveforms, but instead we seek to detect anomalies from the background behavior across an array or network. The background seismic levels will describe a signal space whose dimension may change markedly when an earthquake or other signal of interest occurs. We explore a variety of means by which we can evaluate the time-varying dimensionality of the signal space, and we compare the detection performance to other standard event detection methods.
Ai, Jinquan; Gao, Wei; Gao, Zhiqiang; Shi, Runhe; Zhang, Chao
2017-04-01
Spartina alterniflora is an aggressive invasive plant species that replaces native species, changes the structure and function of the ecosystem across coastal wetlands in China, and is thus a major conservation concern. Mapping the spread of its invasion is a necessary first step for the implementation of effective ecological management strategies. The performance of a phenology-based approach for S. alterniflora mapping is explored in the coastal wetland of the Yangtze Estuary using a time series of GaoFen satellite no. 1 wide field of view camera (GF-1 WFV) imagery. First, a time series of the normalized difference vegetation index (NDVI) was constructed to evaluate the phenology of S. alterniflora. Two phenological stages (the senescence stage from November to mid-December and the green-up stage from late April to May) were determined as important for S. alterniflora detection in the study area based on NDVI temporal profiles, spectral reflectance curves of S. alterniflora and its coexistent species, and field surveys. Three phenology feature sets representing three major phenology-based detection strategies were then compared to map S. alterniflora: (1) the single-date imagery acquired within the optimal phenological window, (2) the multitemporal imagery, including four images from the two important phenological windows, and (3) the monthly NDVI time series imagery. Support vector machines and maximum likelihood classifiers were applied on each phenology feature set at different training sample sizes. For all phenology feature sets, the overall results were produced consistently with high mapping accuracies under sufficient training samples sizes, although significantly improved classification accuracies (10%) were obtained when the monthly NDVI time series imagery was employed. The optimal single-date imagery had the lowest accuracies of all detection strategies. The multitemporal analysis demonstrated little reduction in the overall accuracy compared with the
Controlling nonclassical properties of the two-photon process by a time-varying field
International Nuclear Information System (INIS)
Fei, Jia; Shuang-Yuan, Xie; Ya-Ping, Yang
2009-01-01
The interactions between a two-level atom and a field via two-photon transition without rotating wave approximation have been investigated. We emphasize the dynamic behaviors of the atomic population inversion, the field squeezing, and the atomic dipole squeezing numerically when the field frequency varies with time in the forms of sine and rectangle. Some interesting phenomena are discovered and discussed. The good periodic character of the atomic population inversion in the standard two-photon Jaynes–Cummings model is weakened by the influence of the sine field frequency modulation. The rectangular field frequency modulation can change the correlation among different oscillations suddenly and induce new collapse-revival processes of the atomic population inversion. The field squeezing increases at the beginning of time, but then decreases and loses as the time increases after it reaches the maximum due to the sine modulation. The effects of the rectangular modulation on the field squeezing depend mostly on the appearance time of the modulation. The atomic dipole squeezing is weakened under the influence of the sine or rectangular modulation. Our results indicate that it is possible to perform the dynamic controlling of the system properties by changing the parameters of the system with time. This implies that one can dynamically control a quantum information process by choosing the system modulation properly. (general)
Effect of varying spatial orientations on build time requirements for FDM process: A case study
Directory of Open Access Journals (Sweden)
Sandeep Rathee
2017-04-01
Full Text Available In this research, effect of varying spatial orientations on the build time requirements for fused deposition modelling process is studied. Constructive solid geometry cylindrical primitive is taken as work piece and modeling is accomplished for it. Response surface methodology is used to design the experiments and obtain statistical models for build time requirements corresponding to different orientations of the given primitive in modeller build volume. Contour width, air gap, slice height, raster width, raster angle and angle of orientation are treated as process parameters. Percentage contribution of individual process parameter is found to change for build time corresponding to different spatial orientations. Also, the average of build time requirement changes with spatial orientation. This paper attempts to clearly discuss and describe the observations with an aim to develop a clear understanding of effect of spatial variations on the build time for Fused Deposition Modelling process. This work is an integral part of process layout optimization and these results can effectively aid designers specially while tackling nesting issues.
Blinking model and synchronization in small-world networks with a time-varying coupling
Belykh, Igor V.; Belykh, Vladimir N.; Hasler, Martin
2004-08-01
The paper proposes a new type of small-world networks of cells with chaotic behavior. This network consists of a regular lattice of cells with constant 2 K-nearest neighbor couplings and time-dependent on-off couplings between any other pair of cells. In each time interval of duration τ such a coupling is switched on with probability p and the corresponding switching random variables are independent for different links and for different times. At each moment, the coupling structure corresponds to a small-world graph, but the shortcuts change from time interval to time interval, which is a good model for many real-world dynamical networks. It is to be distinguished from networks that have randomly chosen shortcuts, fixed in time. Here, we apply the Connection Graph Stability method, developed in the companion paper (“Connection graph stability method for synchronized coupled chaotic systems”, see this issue), to the study of global synchronization in this network with the time-varying coupling structure, in the case where the on-off switching is fast with respect to the characteristic synchronization time of the network. The synchronization thresholds are explicitly linked with the average path length of the coupling graph and with the probability p of shortcut switchings in this blinking model. We prove that for the blinking model, a few random shortcut additions significantly lower the synchronization threshold together with the effective characteristic path length. Short interactions between cells, as in the blinking model, are important in practice. To cite prominent examples, computers networked over the Internet interact by sending packets of information, and neurons in our brain interact by sending short pulses, called spikes. The rare interaction between arbitrary nodes in the network greatly facilitates synchronization without loading the network much. In this respect, we believe that it is more efficient than a structure of fixed random connections.
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.
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.
A multiscale MDCT image-based breathing lung model with time-varying regional ventilation
Yin, Youbing; Choi, Jiwoong; Hoffman, Eric A.; Tawhai, Merryn H.; Lin, Ching-Long
2013-07-01
A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung. For the first time, the algorithm is applied to three multi-detector row computed tomography (MDCT) volumetric lung images of the same individual. A key technique in linking global and local variables over multiple images is an in-house mass-preserving image registration method. Throughout breathing cycles, cubic interpolation is employed to ensure C1 continuity in constructing time-varying regional ventilation at the whole lung level, flow rate fractions exiting the terminal airways, and airway deformation. The imaged exit airway flow rate fractions are derived from regional ventilation with the aid of a three-dimensional (3D) and one-dimensional (1D) coupled airway tree that connects the airways to the alveolar tissue. An in-house parallel large-eddy simulation (LES) technique is adopted to capture turbulent-transitional-laminar flows in both normal and deep breathing conditions. The results obtained by the proposed algorithm when using three lung volume images are compared with those using only one or two volume images. The three-volume-based lung model produces physiologically-consistent time-varying pressure and ventilation distribution. The one-volume-based lung model under-predicts pressure drop and yields un-physiological lobar ventilation. The two-volume-based model can account for airway deformation and non-uniform regional ventilation to some extent, but does not capture the non-linear features of the lung.
Timing of continuous motor imagery: the two-thirds power law originates in trajectory planning.
Karklinsky, Matan; Flash, Tamar
2015-04-01
The two-thirds power law, v = γκ(-1/3), expresses a robust local relationship between the geometrical and temporal aspects of human movement, represented by curvature κ and speed v, with a piecewise constant γ. This law is equivalent to moving at a constant equi-affine speed and thus constitutes an important example of motor invariance. Whether this kinematic regularity reflects central planning or peripheral biomechanical effects has been strongly debated. Motor imagery, i.e., forming mental images of a motor action, allows unique access to the temporal structure of motor planning. Earlier studies have shown that imagined discrete movements obey Fitts's law and their durations are well correlated with those of actual movements. Hence, it is natural to examine whether the temporal properties of continuous imagined movements comply with the two-thirds power law. A novel experimental paradigm for recording sparse imagery data from a continuous cyclic tracing task was developed. Using the likelihood ratio test, we concluded that for most subjects the distributions of the marked positions describing the imagined trajectory were significantly better explained by the two-thirds power law than by a constant Euclidean speed or by two other power law models. With nonlinear regression, the β parameter values in a generalized power law, v = γκ(-β), were inferred from the marked position records. This resulted in highly variable yet mostly positive β values. Our results imply that imagined trajectories do follow the two-thirds power law. Our findings therefore support the conclusion that the coupling between velocity and curvature originates in centrally represented motion planning. Copyright © 2015 the American Physiological Society.
Chen, Hua; Chen, Kun
2013-07-01
The distributions of coalescence times and ancestral lineage numbers play an essential role in coalescent modeling and ancestral inference. Both exact distributions of coalescence times and ancestral lineage numbers are expressed as the sum of alternating series, and the terms in the series become numerically intractable for large samples. More computationally attractive are their asymptotic distributions, which were derived in Griffiths (1984) for populations with constant size. In this article, we derive the asymptotic distributions of coalescence times and ancestral lineage numbers for populations with temporally varying size. For a sample of size n, denote by Tm the mth coalescent time, when m + 1 lineages coalesce into m lineages, and An(t) the number of ancestral lineages at time t back from the current generation. Similar to the results in Griffiths (1984), the number of ancestral lineages, An(t), and the coalescence times, Tm, are asymptotically normal, with the mean and variance of these distributions depending on the population size function, N(t). At the very early stage of the coalescent, when t → 0, the number of coalesced lineages n - An(t) follows a Poisson distribution, and as m → n, $$n\\left(n-1\\right){T}_{m}/2N\\left(0\\right)$$ follows a gamma distribution. We demonstrate the accuracy of the asymptotic approximations by comparing to both exact distributions and coalescent simulations. Several applications of the theoretical results are also shown: deriving statistics related to the properties of gene genealogies, such as the time to the most recent common ancestor (TMRCA) and the total branch length (TBL) of the genealogy, and deriving the allele frequency spectrum for large genealogies. With the advent of genomic-level sequencing data for large samples, the asymptotic distributions are expected to have wide applications in theoretical and methodological development for population genetic inference.
International Nuclear Information System (INIS)
Kumar, V.; Mukherjee, S.
1977-01-01
In the present paper a general time-dependent inelastic analysis procedure for three-dimensional bodies subjected to arbitrary time varying mechanical and thermal loads using these state variable theories is presented. For the purpose of illustrations, the problems of hollow spheres, cylinders and solid circular shafts subjected to various combinations of internal and external pressures, axial force (or constraint) and torque are analyzed using the proposed solution procedure. Various cyclic thermal and mechanical loading histories with rectangular or sawtooth type waves with or without hold-time are considered. Numerical results for these geometrical shapes for various such loading histories are presented using Hart's theory (Journal of Engineering Materials and Technology 1976). The calculations are performed for nickel in the temperature range of 25 0 C to 400 0 C. For integrating forward in time, a method of solving a stiff system of ordinary differential equations is employed which corrects the step size and order of the method automatically. The limit loads for hollow spheres and cylinders are calculated using the proposed method and Hart's theory, and comparisons are made against the known theoretical results. The numerical results for other loading histories are discussed in the context of Hart's state variable type constitutive relations. The significance of phenomena such as strain rate sensitivity, Bauschinger's effect, crep recovery, history dependence and material softening with regard to these multiaxial problems are discussed in the context of Hart's theory
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
Schmidt, Christoph; Piper, Diana; Pester, Britta; Mierau, Andreas; Witte, Herbert
2018-05-01
Identification of module structure in brain functional networks is a promising way to obtain novel insights into neural information processing, as modules correspond to delineated brain regions in which interactions are strongly increased. Tracking of network modules in time-varying brain functional networks is not yet commonly considered in neuroscience despite its potential for gaining an understanding of the time evolution of functional interaction patterns and associated changing degrees of functional segregation and integration. We introduce a general computational framework for extracting consensus partitions from defined time windows in sequences of weighted directed edge-complete networks and show how the temporal reorganization of the module structure can be tracked and visualized. Part of the framework is a new approach for computing edge weight thresholds for individual networks based on multiobjective optimization of module structure quality criteria as well as an approach for matching modules across time steps. By testing our framework using synthetic network sequences and applying it to brain functional networks computed from electroencephalographic recordings of healthy subjects that were exposed to a major balance perturbation, we demonstrate the framework's potential for gaining meaningful insights into dynamic brain function in the form of evolving network modules. The precise chronology of the neural processing inferred with our framework and its interpretation helps to improve the currently incomplete understanding of the cortical contribution for the compensation of such balance perturbations.
Spatial patterns of ENSO's interannual influences on lilacs vary with time and periodicity
Fu, Congsheng; Ji, Zhenming; Wei, Zhongwang
2017-04-01
The influences of solar activity and large-scale climate modes (e.g. the El Niño/Southern Oscillation - 'ENSO') have been identified in many geophysical processes. However, few studies have attempted to investigate the frequency characteristics and corresponding spatial patterns of the interannual influence of either solar activity or large-scale climate modes on phenology. In this study, the influences of solar activity (represented by sunspot number 'SSN') and ENSO on the first leaf and bloom dates of the common lilac and cloned lilac in the United States were analyzed for time series spanning ≥ 33 years using the wavelet coherence method. The spatial patterns in the influence of ENSO on the first leaf and bloom dates were investigated for different times and periodicities, using time series of ≥ 20 years. The combined influences of solar activity and ENSO on the first leaf and bloom dates of lilacs were identified for most of the stations with records spanning ≥ 33 years. In the 11-year band, both increasing solar activity (SSN) and El Niño caused delays in the first leaf and bloom events of the cloned lilac during the 1980s in the northeastern United States. The frequency characteristics and the spatial patterns of the influence of ENSO on the first leaf day and first bloom day were essentially consistent, and such spatial patterns vary with time and periodicity.
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.
Investigation on the coloured noise in GPS-derived position with time-varying seasonal signals
Gruszczynska, Marta; Klos, Anna; Bos, Machiel Simon; Bogusz, Janusz
2016-04-01
The seasonal signals in the GPS-derived time series arise from real geophysical signals related to tidal (residual) or non-tidal (loadings from atmosphere, ocean and continental hydrosphere, thermo elastic strain, etc.) effects and numerical artefacts including aliasing from mismodelling in short periods or repeatability of the GPS satellite constellation with respect to the Sun (draconitics). Singular Spectrum Analysis (SSA) is a method for investigation of nonlinear dynamics, suitable to either stationary or non-stationary data series without prior knowledge about their character. The aim of SSA is to mathematically decompose the original time series into a sum of slowly varying trend, seasonal oscillations and noise. In this presentation we will explore the ability of SSA to subtract the time-varying seasonal signals in GPS-derived North-East-Up topocentric components and show properties of coloured noise from residua. For this purpose we used data from globally distributed IGS (International GNSS Service) permanent stations processed by the JPL (Jet Propulsion Laboratory) in a PPP (Precise Point Positioning) mode. After introducing a threshold of 13 years, 264 stations left with a maximum length reaching 23 years. The data was initially pre-processed for outliers, offsets and gaps. The SSA was applied to pre-processed series to estimate the time-varying seasonal signals. We adopted a 3-years window as the optimal dimension of its size determined with the Akaike's Information Criteria (AIC) values. A Fisher-Snedecor test corrected for the presence of temporal correlation was used to determine the statistical significance of reconstructed components. This procedure showed that first four components describing annual and semi-annual signals, are significant at a 99.7% confidence level, which corresponds to 3-sigma criterion. We compared the non-parametric SSA approach with a commonly chosen parametric Least-Squares Estimation that assumes constant amplitudes and
Broderson, D.; Dierking, C.; Stevens, E.; Heinrichs, T. A.; Cherry, J. E.
2016-12-01
The Geographic Information Network of Alaska (GINA) at the University of Alaska Fairbanks (UAF) uses two direct broadcast antennas to receive data from a number of polar-orbiting weather satellites, including the Suomi National Polar Partnership (S-NPP) satellite. GINA uses data from S-NPP's Visible Infrared Imaging Radiometer Suite (VIIRS) to generate a variety of multispectral imagery products developed with the needs of the National Weather Service operational meteorologist in mind. Multispectral products have two primary advantages over single-channel products. First, they can more clearly highlight some terrain and meteorological features which are less evident in the component single channels. Second, multispectral present the information from several bands through just one image, thereby sparing the meteorologist unnecessary time interrogating the component single bands individually. With 22 channels available from the VIIRS instrument, the number of possible multispectral products is theoretically huge. A small number of products will be emphasized in this presentation, with the products chosen based on their proven utility in the forecasting environment. Multispectral products can be generated upstream of the end user or by the end user at their own workstation. The advantage and disadvantages of both approaches will be outlined. Lastly, the technique of improving the appearance of multispectral imagery by correcting for atmospheric reflectance at the shorter wavelengths will be described.
Stability analysis and backward whirl investigation of cracked rotors with time-varying stiffness
AL-Shudeifat, Mohammad A.
2015-07-01
The dynamic stability of dynamical systems with time-periodic stiffness is addressed here. Cracked rotor systems with time-periodic stiffness are well-known examples of such systems. Time-varying area moments of inertia at the cracked element cross-section of a cracked rotor have been used to formulate the time-periodic finite element stiffness matrix. The semi-infinite coefficient matrix obtained by applying the harmonic balance (HB) solution to the finite element (FE) equations of motion is employed here to study the dynamic stability of the system. Consequently, the sign of the determinant of a scaled version of a sub-matrix of this semi-infinite coefficient matrix at a finite number of harmonics in the HB solution is found to be sufficient for identifying the major unstable zones of the system in the parameter plane. Specifically, it is found that the negative determinant always corresponds to unstable zones in all of the systems considered. This approach is applied to a parametrically excited Mathieu's equation, a two degree-of-freedom linear time-periodic dynamical system, a cracked Jeffcott rotor and a finite element model of the cracked rotor system. Compared to the corresponding results obtained by Floquet's theory, the sign of the determinant of the scaled sub-matrix is found to be an efficient tool for identifying the major unstable zones of the linear time-periodic parametrically excited systems, especially large-scale FE systems. Moreover, it is found that the unstable zones for a FE cracked rotor with an open transverse crack model only appear at the backward whirl. The theoretical and experimental results have been found to agree well for verifying that the open crack model excites the backward whirl amplitudes at the critical backward whirling rotational speeds.
Bifurcation onset delay in magnetic bearing systems by time varying stiffness
Ghazavi, M. R.; Sun, Q.
2017-06-01
We study the nonlinear dynamics behaviours of a rigid rotor supported by magnetic bearings. In particular, we consider the effect of rotor unbalanced mass and geometric coupling. Existing works in literature have mostly focused on a single value of parameter or a smaller range of the nonlinearities introduced by rotor imbalance and geometric coupling. This is partly due to the use of a linear PD controller which limits the system performance. In this paper, we use a nonlinear PD controller by adopting a time varying stiffness term. The control gains are chosen according to the stability chart for a Mathieu's equation. Consequently, we observe a delay in the onset of bifurcation indicating an improved rotor performance.
Directory of Open Access Journals (Sweden)
Gill R. Tsouri
2009-01-01
Full Text Available A method of overloading subcarriers by multiple transmitters to secure OFDM in wireless time-varying channels is proposed and analyzed. The method is based on reverse piloting, superposition modulation, and joint decoding. It makes use of channel randomness, reciprocity, and fast decorrelation in space to secure OFDM with low overheads on encryption, decryption, and key distribution. These properties make it a good alternative to traditional software-based information security algorithms in systems where the costs associated with such algorithms are an implementation obstacle. A necessary and sufficient condition for achieving information theoretic security in accordance with channel and system parameters is derived. Security by complexity is assessed for cases where the condition for information theoretic security is not satisfied. In addition, practical means for implementing the method are derived including generating robust joint constellations, decoding data with low complexity, and mitigating the effects of imperfections due to mobility, power control errors, and synchronization errors.
Pinning synchronization of memristor-based neural networks with time-varying delays.
Yang, Zhanyu; Luo, Biao; Liu, Derong; Li, Yueheng
2017-09-01
In this paper, the synchronization of memristor-based neural networks with time-varying delays via pinning control is investigated. A novel pinning method is introduced to synchronize two memristor-based neural networks which denote drive system and response system, respectively. The dynamics are studied by theories of differential inclusions and nonsmooth analysis. In addition, some sufficient conditions are derived to guarantee asymptotic synchronization and exponential synchronization of memristor-based neural networks via the presented pinning control. Furthermore, some improvements about the proposed control method are also discussed in this paper. Finally, the effectiveness of the obtained results is demonstrated by numerical simulations. Copyright © 2017 Elsevier Ltd. All rights reserved.
Multistability and instability analysis of recurrent neural networks with time-varying delays.
Zhang, Fanghai; Zeng, Zhigang
2018-01-01
This paper provides new theoretical results on the multistability and instability analysis of recurrent neural networks with time-varying delays. It is shown that such n-neuronal recurrent neural networks have exactly [Formula: see text] equilibria, [Formula: see text] of which are locally exponentially stable and the others are unstable, where k 0 is a nonnegative integer such that k 0 ≤n. By using the combination method of two different divisions, recurrent neural networks can possess more dynamic properties. This method improves and extends the existing results in the literature. Finally, one numerical example is provided to show the superiority and effectiveness of the presented results. Copyright © 2017 Elsevier Ltd. All rights reserved.
Time-varied magnetic field enhances transport of magnetic nanoparticles in viscous gel.
MacDonald, Cristin; Friedman, Gary; Alamia, John; Barbee, Kenneth; Polyak, Boris
2010-01-01
The potential of magnetic nanoparticles (MNPs) to deliver various forms of therapy has not been fully realized, in part due to difficulties in transporting the carriers through soft tissue to different target sites. The aim of this study was to demonstrate that transport of MNPs through a viscous gel can be controlled by a combined AC (time-varying) magnetic field and static field gradient. MNP velocity and transport efficiency were measured in a viscous gel at various settings of magnetic field and magnetite loadings. Combined application of an AC magnetic field with the static field gradient resulted in a nearly 30-fold increase in MNP transport efficiency in viscous gel for 30% (w/w) magnetite-loaded particles as compared with static field conditions. The 'oscillating' effect of an AC magnetic field greatly improves the ability to transport MNPs within soft media by decreasing the effective viscosity of the gel.
Lin, Wen-Juan; He, Yong; Zhang, Chuan-Ke; Wu, Min
2018-01-01
This paper is concerned with the stability analysis of neural networks with a time-varying delay. To assess system stability accurately, the conservatism reduction of stability criteria has attracted many efforts, among which estimating integral terms as exact as possible is a key issue. At first, this paper develops a new relaxed integral inequality to reduce the estimation gap of popular Wirtinger-based inequality (WBI). Then, for showing the advantages of the proposed inequality over several existing inequalities that also improve the WBI, four stability criteria are derived through different inequalities and the same Lyapunov-Krasovskii functional (LKF), and the conservatism comparison of them is analyzed theoretically. Moreover, an improved criterion is established by combining the proposed inequality and an augmented LKF with delay-product-type terms. Finally, several numerical examples are used to demonstrate the advantages of the proposed method.
Liu, Shuang; Wang, Jin-Jin; Liu, Jin-Jie; Li, Ya-Qian
2015-10-01
In the present work, we investigate the nonlinear parametrically excited vibration and active control of a gear pair system involving backlash, time-varying meshing stiffness and static transmission error. Firstly, a gear pair model is established in a strongly nonlinear form, and its nonlinear vibration characteristics are systematically investigated through different approaches. Several complicated phenomena such as period doubling bifurcation, anti period doubling bifurcation and chaos can be observed under the internal parametric excitation. Then, an active compensation controller is designed to suppress the vibration, including the chaos. Finally, the effectiveness of the proposed controller is verified numerically. Project supported by the National Natural Science Foundation of China (Grant No. 61104040), the Natural Science Foundation of Hebei Province, China (Grant No. E2012203090), and the University Innovation Team of Hebei Province Leading Talent Cultivation Project, China (Grant No. LJRC013).
Efficiency or speculation? A time-varying analysis of European sovereign debt
Ferreira, Paulo
2018-01-01
The outbreak of the Greek debt crisis caused turmoil in European markets and drew attention to the problem of public debt and its consequences. The increase in the return rates of sovereign debts was one of these consequences. However, like any other asset, sovereign debt returns are expected to have a memoryless behaviour. Analysing a total of 15 European countries (Eurozone and non-Eurozone), and applying a time-varying analysis of the Hurst exponent, we found evidence of long-range memory in sovereign bonds. When analysing the spreads between each bond and the German one, it is possible to conclude that Eurozone countries' spreads show more evidence of long-range dependence. Considering the Eurozone countries most affected by the Eurozone crisis, that long-range dependence is more evident, but started before the crisis, which could be interpreted as possible speculation by investors.
Directory of Open Access Journals (Sweden)
Li XinBin
2010-01-01
Full Text Available Global phase synchronization for a class of dynamical complex networks composed of multiinput multioutput pendulum-like systems with time-varying coupling delays is investigated. The problem of the global phase synchronization for the complex networks is equivalent to the problem of the asymptotical stability for the corresponding error dynamical networks. For reducing the conservation, no linearization technique is involved, but by Kronecker product, the problem of the asymptotical stability of the high dimensional error dynamical networks is reduced to the same problem of a class of low dimensional error systems. The delay-dependent criteria guaranteeing global asymptotical stability for the error dynamical complex networks in terms of Liner Matrix Inequalities (LMIs are derived based on free-weighting matrices technique and Lyapunov function. According to the convex characterization, a simple criterion is proposed. A numerical example is provided to demonstrate the effectiveness of the proposed results.
Gu, Huaying; Liu, Zhixue; Weng, Yingliang
2017-04-01
The present study applies the multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) with spatial effects approach for the analysis of the time-varying conditional correlations and contagion effects among global real estate markets. A distinguishing feature of the proposed model is that it can simultaneously capture the spatial interactions and the dynamic conditional correlations compared with the traditional MGARCH models. Results reveal that the estimated dynamic conditional correlations have exhibited significant increases during the global financial crisis from 2007 to 2009, thereby suggesting contagion effects among global real estate markets. The analysis further indicates that the returns of the regional real estate markets that are in close geographic and economic proximities exhibit strong co-movement. In addition, evidence of significantly positive leverage effects in global real estate markets is also determined. The findings have significant implications on global portfolio diversification opportunities and risk management practices.
Ghumare, Eshwar; Schrooten, Maarten; Vandenberghe, Rik; Dupont, Patrick
2015-08-01
Kalman filter approaches are widely applied to derive time varying effective connectivity from electroencephalographic (EEG) data. For multi-trial data, a classical Kalman filter (CKF) designed for the estimation of single trial data, can be implemented by trial-averaging the data or by averaging single trial estimates. A general linear Kalman filter (GLKF) provides an extension for multi-trial data. In this work, we studied the performance of the different Kalman filtering approaches for different values of signal-to-noise ratio (SNR), number of trials and number of EEG channels. We used a simulated model from which we calculated scalp recordings. From these recordings, we estimated cortical sources. Multivariate autoregressive model parameters and partial directed coherence was calculated for these estimated sources and compared with the ground-truth. The results showed an overall superior performance of GLKF except for low levels of SNR and number of trials.
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 Entry Heating Profile Replication with a Rotating Arc Jet Test Article
Grinstead, Jay Henderson; Venkatapathy, Ethiraj; Noyes, Eric A.; Mach, Jeffrey J.; Empey, Daniel M.; White, Todd R.
2014-01-01
A new approach for arc jet testing of thermal protection materials at conditions approximating the time-varying conditions of atmospheric entry was developed and demonstrated. The approach relies upon the spatial variation of heat flux and pressure over a cylindrical test model. By slowly rotating a cylindrical arc jet test model during exposure to an arc jet stream, each point on the test model will experience constantly changing applied heat flux. The predicted temporal profile of heat flux at a point on a vehicle can be replicated by rotating the cylinder at a prescribed speed and direction. An electromechanical test model mechanism was designed, built, and operated during an arc jet test to demonstrate the technique.
On-line statistical processing of radiation detector pulse trains with time-varying count rates
International Nuclear Information System (INIS)
Apostolopoulos, G.
2008-01-01
Statistical analysis is of primary importance for the correct interpretation of nuclear measurements, due to the inherent random nature of radioactive decay processes. This paper discusses the application of statistical signal processing techniques to the random pulse trains generated by radiation detectors. The aims of the presented algorithms are: (i) continuous, on-line estimation of the underlying time-varying count rate θ(t) and its first-order derivative dθ/dt; (ii) detection of abrupt changes in both of these quantities and estimation of their new value after the change point. Maximum-likelihood techniques, based on the Poisson probability distribution, are employed for the on-line estimation of θ and dθ/dt. Detection of abrupt changes is achieved on the basis of the generalized likelihood ratio statistical test. The properties of the proposed algorithms are evaluated by extensive simulations and possible applications for on-line radiation monitoring are discussed
Passivity analysis of memristor-based impulsive inertial neural networks with time-varying delays.
Wan, Peng; Jian, Jigui
2018-03-01
This paper focuses on delay-dependent passivity analysis for a class of memristive impulsive inertial neural networks with time-varying delays. By choosing proper variable transformation, the memristive inertial neural networks can be rewritten as first-order differential equations. The memristive model presented here is regarded as a switching system rather than employing the theory of differential inclusion and set-value map. Based on matrix inequality and Lyapunov-Krasovskii functional method, several delay-dependent passivity conditions are obtained to ascertain the passivity of the addressed networks. In addition, the results obtained here contain those on the passivity for the addressed networks without impulse effects as special cases and can also be generalized to other neural networks with more complex pulse interference. Finally, one numerical example is presented to show the validity of the obtained results. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.
Randomized gradient-free method for multiagent optimization over time-varying networks.
Yuan, Deming; Ho, Daniel W C
2015-06-01
In this brief, we consider the multiagent optimization over a network where multiple agents try to minimize a sum of nonsmooth but Lipschitz continuous functions, subject to a convex state constraint set. The underlying network topology is modeled as time varying. We propose a randomized derivative-free method, where in each update, the random gradient-free oracles are utilized instead of the subgradients (SGs). In contrast to the existing work, we do not require that agents are able to compute the SGs of their objective functions. We establish the convergence of the method to an approximate solution of the multiagent optimization problem within the error level depending on the smoothing parameter and the Lipschitz constant of each agent's objective function. Finally, a numerical example is provided to demonstrate the effectiveness of the method.
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.
Prediction of oil expression by uniaxial compression using time-varying oilseed properties
DEFF Research Database (Denmark)
Bargale, P. C.; Wulfsohn, Dvoralai; Irudayaraj, J.
2000-01-01
recovery for extruded soybean very well, the predictions were not satisfactory for sunflower seed samples. The higher error was attributed to material non-homogeneity and the presence of hulls in the sunflower seeds, which increased errors in measurement of the medium permeability function. The lack......A mathematical simulation of uniaxial compression of oilseeds for oil extraction was developed based upon combining Terzaghi's theory of consolidation for saturated soils with Darcy's law for unsaturated flow, while incorporating the time-varying nature of the coefficients of permeability...... and consolidation. The model was validated for extruded soy and for sunflower seeds. Material parameters were determined experimentally and predictions of oil recovery rates made for several levels of temperature, pressure and initial sample depth. Results indicated that while the model predicted the values of oil...
A First-order Prediction-Correction Algorithm for Time-varying (Constrained) Optimization: Preprint
Energy Technology Data Exchange (ETDEWEB)
Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Simonetto, Andrea [Universite catholique de Louvain
2017-07-25
This paper focuses on the design of online algorithms based on prediction-correction steps to track the optimal solution of a time-varying constrained problem. Existing prediction-correction methods have been shown to work well for unconstrained convex problems and for settings where obtaining the inverse of the Hessian of the cost function can be computationally affordable. The prediction-correction algorithm proposed in this paper addresses the limitations of existing methods by tackling constrained problems and by designing a first-order prediction step that relies on the Hessian of the cost function (and do not require the computation of its inverse). Analytical results are established to quantify the tracking error. Numerical simulations corroborate the analytical results and showcase performance and benefits of the algorithms.
Synchronization criterion for Lur'e type complex dynamical networks with time-varying delay
International Nuclear Information System (INIS)
Ji, D.H.; Park, Ju H.; Yoo, W.J.; Won, S.C.; Lee, S.M.
2010-01-01
In this Letter, the synchronization problem for a class of complex dynamical networks in which every identical node is a Lur'e system with time-varying delay is considered. A delay-dependent synchronization criterion is derived for the synchronization of complex dynamical network that represented by Lur'e system with sector restricted nonlinearities. The derived criterion is a sufficient condition for absolute stability of error dynamics between the each nodes and the isolated node. Using a convex representation of the nonlinearity for error dynamics, the stability condition based on the discretized Lyapunov-Krasovskii functional is obtained via LMI formulation. The proposed delay-dependent synchronization criterion is less conservative than the existing ones. The effectiveness of our work is verified through numerical examples.
Li, Tao; Song, Aiguo; Fei, Shumin
2011-10-01
The article is concerned with asymptotical stability for Cohen-Grossberg neural networks with both interval time-varying (0 ≤ τ0 ≤ τ(t) ≤ τ m ) and distributed delays, in which two types of distributed delays are treated: one is bounded while the other is unbounded. Through partitioning the delay intervals [0, τ0] and [τ0, τ m ], and choosing two augmented Lyapunov-Krasovskii functionals, some sufficient conditions are obtained to guarantee the global stability by employing the simplified free-weighting matrix method and convex combination. These stability criteria are presented in terms of linear matrix inequalities (LMIs) and can be easily checked by resorting to LMI in Matlab toolbox. Finally, three numerical examples are given to illustrate the effectiveness and reduced conservatism of the theoretical results.
International Nuclear Information System (INIS)
Xu Shengyuan; Lam, James; Ho, Daniel W.C.
2005-01-01
This Letter is concerned with the problem of robust stability analysis for interval neural networks with multiple time-varying delays and parameter uncertainties. The parameter uncertainties are assumed to be bounded in given compact sets and the activation functions are supposed to be bounded and globally Lipschitz continuous. A sufficient condition is obtained by means of Lyapunov functionals, which guarantees the existence, uniqueness and global asymptotic stability of the delayed neural network for all admissible uncertainties. This condition is in terms of a linear matrix inequality (LMI), which can be easily checked by using recently developed algorithms in solving LMIs. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed method
The co-movement of monetary policy and its time-varying nature: A DCCA approach
Rohit, Abhishek; Mitra, Subrata Kumar
2018-02-01
Employing a novel methodology of DCCA cross-correlation coefficient (ρDCCA), this study attempts to provide fresh evidences for the co-movement of monetary policies of the advanced (AEs) as well as the emerging economies (EMEs) vis-à-vis the United States. A higher degree of monetary co-movement as measured by ρDCCA values, is identified for the AEs as compared to the EMEs. Lower co-movement of monetary policy is especially noticeable in the short run for EMEs. We further investigate the time-varying nature of such co-movements for the AEs by splitting the period (1980-2014) into four sub periods and also by performing a rolling window estimation for the entire period to reveal smoother dynamics. Significant evidence of higher monetary coordination is revealed for sub-periods with stronger trade and financial linkages.
Time-varying wing-twist improves aerodynamic efficiency of forward flight in butterflies.
Zheng, Lingxiao; Hedrick, Tyson L; Mittal, Rajat
2013-01-01
Insect wings can undergo significant chordwise (camber) as well as spanwise (twist) deformation during flapping flight but the effect of these deformations is not well understood. The shape and size of butterfly wings leads to particularly large wing deformations, making them an ideal test case for investigation of these effects. Here we use computational models derived from experiments on free-flying butterflies to understand the effect of time-varying twist and camber on the aerodynamic performance of these insects. High-speed videogrammetry is used to capture the wing kinematics, including deformation, of a Painted Lady butterfly (Vanessa cardui) in untethered, forward flight. These experimental results are then analyzed computationally using a high-fidelity, three-dimensional, unsteady Navier-Stokes flow solver. For comparison to this case, a set of non-deforming, flat-plate wing (FPW) models of wing motion are synthesized and subjected to the same analysis along with a wing model that matches the time-varying wing-twist observed for the butterfly, but has no deformation in camber. The simulations show that the observed butterfly wing (OBW) outperforms all the flat-plate wings in terms of usable force production as well as the ratio of lift to power by at least 29% and 46%, respectively. This increase in efficiency of lift production is at least three-fold greater than reported for other insects. Interestingly, we also find that the twist-only-wing (TOW) model recovers much of the performance of the OBW, demonstrating that wing-twist, and not camber is key to forward flight in these insects. The implications of this on the design of flapping wing micro-aerial vehicles are discussed.
Time-varying wing-twist improves aerodynamic efficiency of forward flight in butterflies.
Directory of Open Access Journals (Sweden)
Lingxiao Zheng
Full Text Available Insect wings can undergo significant chordwise (camber as well as spanwise (twist deformation during flapping flight but the effect of these deformations is not well understood. The shape and size of butterfly wings leads to particularly large wing deformations, making them an ideal test case for investigation of these effects. Here we use computational models derived from experiments on free-flying butterflies to understand the effect of time-varying twist and camber on the aerodynamic performance of these insects. High-speed videogrammetry is used to capture the wing kinematics, including deformation, of a Painted Lady butterfly (Vanessa cardui in untethered, forward flight. These experimental results are then analyzed computationally using a high-fidelity, three-dimensional, unsteady Navier-Stokes flow solver. For comparison to this case, a set of non-deforming, flat-plate wing (FPW models of wing motion are synthesized and subjected to the same analysis along with a wing model that matches the time-varying wing-twist observed for the butterfly, but has no deformation in camber. The simulations show that the observed butterfly wing (OBW outperforms all the flat-plate wings in terms of usable force production as well as the ratio of lift to power by at least 29% and 46%, respectively. This increase in efficiency of lift production is at least three-fold greater than reported for other insects. Interestingly, we also find that the twist-only-wing (TOW model recovers much of the performance of the OBW, demonstrating that wing-twist, and not camber is key to forward flight in these insects. The implications of this on the design of flapping wing micro-aerial vehicles are discussed.
Time-Varying Wing-Twist Improves Aerodynamic Efficiency of Forward Flight in Butterflies
Zheng, Lingxiao; Hedrick, Tyson L.; Mittal, Rajat
2013-01-01
Insect wings can undergo significant chordwise (camber) as well as spanwise (twist) deformation during flapping flight but the effect of these deformations is not well understood. The shape and size of butterfly wings leads to particularly large wing deformations, making them an ideal test case for investigation of these effects. Here we use computational models derived from experiments on free-flying butterflies to understand the effect of time-varying twist and camber on the aerodynamic performance of these insects. High-speed videogrammetry is used to capture the wing kinematics, including deformation, of a Painted Lady butterfly (Vanessa cardui) in untethered, forward flight. These experimental results are then analyzed computationally using a high-fidelity, three-dimensional, unsteady Navier-Stokes flow solver. For comparison to this case, a set of non-deforming, flat-plate wing (FPW) models of wing motion are synthesized and subjected to the same analysis along with a wing model that matches the time-varying wing-twist observed for the butterfly, but has no deformation in camber. The simulations show that the observed butterfly wing (OBW) outperforms all the flat-plate wings in terms of usable force production as well as the ratio of lift to power by at least 29% and 46%, respectively. This increase in efficiency of lift production is at least three-fold greater than reported for other insects. Interestingly, we also find that the twist-only-wing (TOW) model recovers much of the performance of the OBW, demonstrating that wing-twist, and not camber is key to forward flight in these insects. The implications of this on the design of flapping wing micro-aerial vehicles are discussed. PMID:23341923
Design and implementation of multi-signal and time-varying neural reconstructions.
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.
Long-term prediction of the Arctic ionospheric TEC based on time-varying periodograms.
Liu, Jingbin; Chen, Ruizhi; Wang, Zemin; An, Jiachun; Hyyppä, Juha
2014-01-01
Knowledge of the polar ionospheric total electron content (TEC) and its future variations is of scientific and engineering relevance. In this study, a new method is developed to predict Arctic mean TEC on the scale of a solar cycle using previous data covering 14 years. The Arctic TEC is derived from global positioning system measurements using the spherical cap harmonic analysis mapping method. The study indicates that the variability of the Arctic TEC results in highly time-varying periodograms, which are utilized for prediction in the proposed method. The TEC time series is divided into two components of periodic oscillations and the average TEC. The newly developed method of TEC prediction is based on an extrapolation method that requires no input of physical observations of the time interval of prediction, and it is performed in both temporally backward and forward directions by summing the extrapolation of the two components. The backward prediction indicates that the Arctic TEC variability includes a 9 years period for the study duration, in addition to the well-established periods. The long-term prediction has an uncertainty of 4.8-5.6 TECU for different period sets.
Visualizing Robustness of Critical Points for 2D Time-Varying Vector Fields
Wang, B.
2013-06-01
Analyzing critical points and their temporal evolutions plays a crucial role in understanding the behavior of vector fields. A key challenge is to quantify the stability of critical points: more stable points may represent more important phenomena or vice versa. The topological notion of robustness is a tool which allows us to quantify rigorously the stability of each critical point. Intuitively, the robustness of a critical point is the minimum amount of perturbation necessary to cancel it within a local neighborhood, measured under an appropriate metric. In this paper, we introduce a new analysis and visualization framework which enables interactive exploration of robustness of critical points for both stationary and time-varying 2D vector fields. This framework allows the end-users, for the first time, to investigate how the stability of a critical point evolves over time. We show that this depends heavily on the global properties of the vector field and that structural changes can correspond to interesting behavior. We demonstrate the practicality of our theories and techniques on several datasets involving combustion and oceanic eddy simulations and obtain some key insights regarding their stable and unstable features. © 2013 The Author(s) Computer Graphics Forum © 2013 The Eurographics Association and Blackwell Publishing Ltd.
The time-varying association between perceived stress and hunger within and between days.
Huh, Jimi; Shiyko, Mariya; Keller, Stefan; Dunton, Genevieve; Schembre, Susan M
2015-06-01
Examine the association between perceived stress and hunger continuously over a week in free-living individuals. Forty five young adults (70% women, 30% overweight/obese) ages 18 to 24 years (Mean = 20.7, SD = 1.5), with BMI between 17.4 and 36.3 kg/m(2) (Mean = 23.6, SD = 4.0) provided between 513 and 577 concurrent ratings of perceived stress and hunger for 7 days via hourly, text messaging assessments and real-time eating records. Time-varying effect modeling was used to explore whether the within-day fluctuations in stress are related to perceived hunger assessed on a momentary basis. A generally positive stress-hunger relationship was confirmed, but we found that the strength of the relationship was not linear. Rather, the magnitude of the association between perceived stress and hunger changed throughout the day such that only during specific time intervals were stress and hunger significantly related. Specifically, the strength of the positive association peaked during late afternoon hours on weekdays (β = 0.31, p hunger associations that peak in the afternoon or evening hours. While we are unable to infer causality from these analyses, our findings provide empirical evidence for a potentially high-risk time of day for stress-induced eating. Replication of these findings in larger, more diverse samples will aid with the design and implementation of real-time intervention studies aimed at reducing stress-eating. Copyright © 2015 Elsevier Ltd. All rights reserved.
Fusilli, L.; Collins, M. O.; Laneve, G.; Palombo, A.; Pignatti, S.; Santini, F.
2013-02-01
The objective of this research study is to assess the capability of time-series of MODIS imagery to provide information suitable for enhancing the understanding of the temporal cycles shown by the abnormal growth of the floating macrophytes in order to support monitoring and management action of Lake Victoria water resources. The proliferation of invasive plants and aquatic weeds is of growing concern. Starting from 1989, Lake Victoria has been interested by the high infestation of water hyacinth with significant socio-economic impact on riparian populations. In this paper, we describe an approach based on the time-series of MODIS to derive the temporal behaviour, the abundance and distribution of the floating macrophytes in the Winam Gulf (Kenyan portion of the Lake Victoria) and its possible links to the concentrations of the main water constituencies. To this end, we consider the NDVI values computed from the MODIS imagery time-series from 2000 to 2009 to identify the floating macrophytes cover and an appropriate bio-optical model to retrieve, by means of an inverse procedure, the concentrations of chlorophyll a, coloured dissolved organic matter and total suspended solid. The maps of the floating vegetation based on the NDVI values allow us to assess the spatial and temporal dynamics of the weeds with high time resolution. A floating vegetation index (FVI) has been introduced for describing the weeds pollution level. The results of the analysis show a consistent temporal relation between the water constituent concentrations within the Winam Gulf and the FVI, especially in the proximity of the greatest proliferation of floating vegetation in the last 10 years that occurred between the second half of 2006 and the first half of 2007.The adopted approach will be useful to implement an automatic system for monitoring and predicting the floating macrophytes proliferation in Lake Victoria.
Directory of Open Access Journals (Sweden)
Johansson Håkan
2006-01-01
Full Text Available This paper deals with reconstruction of nonuniformly sampled bandlimited continuous-time signals using time-varying discrete-time finite-length impulse response (FIR filters. The main theme of the paper is to show how a slight oversampling should be utilized for designing the reconstruction filters in a proper manner. Based on a time-frequency function, it is shown that the reconstruction problem can be posed as one that resembles an ordinary filter design problem, both for deterministic signals and random processes. From this fact, an analytic least-square design technique is then derived. Furthermore, for an important special case, corresponding to periodic nonuniform sampling, it is shown that the reconstruction problem alternatively can be posed as a filter bank design problem, thus with requirements on a distortion transfer function and a number of aliasing transfer functions. This eases the design and offers alternative practical design methods as discussed in the paper. Several design examples are included that illustrate the benefits of the proposed design techniques over previously existing techniques.
Directory of Open Access Journals (Sweden)
Islam S.M. Khalil
2016-06-01
Full Text Available Targeted therapy using magnetic microparticles and nanoparticles has the potential to mitigate the negative side-effects associated with conventional medical treatment. Major technological challenges still need to be addressed in order to translate these particles into in vivo applications. For example, magnetic particles need to be navigated controllably in vessels against flowing streams of body fluid. This paper describes the motion control of paramagnetic microparticles in the flowing streams of fluidic channels with time-varying flow rates (maximum flow is 35 ml.hr−1. This control is designed using a magnetic-based proportional-derivative (PD control system to compensate for the time-varying flow inside the channels (with width and depth of 2 mm and 1.5 mm, respectively. First, we achieve point-to-point motion control against and along flow rates of 4 ml.hr−1, 6 ml.hr−1, 17 ml.hr−1, and 35 ml.hr−1. The average speeds of single microparticle (with average diameter of 100 μm against flow rates of 6 ml.hr−1 and 30 ml.hr−1 are calculated to be 45 μm.s−1 and 15 μm.s−1, respectively. Second, we implement PD control with disturbance estimation and compensation. This control decreases the steady-state error by 50%, 70%, 73%, and 78% at flow rates of 4 ml.hr−1, 6 ml.hr−1, 17 ml.hr−1, and 35 ml.hr−1, respectively. Finally, we consider the problem of finding the optimal path (minimal kinetic energy between two points using calculus of variation, against the mentioned flow rates. Not only do we find that an optimal path between two collinear points with the direction of maximum flow (middle of the fluidic channel decreases the rise time of the microparticles, but we also decrease the input current that is supplied to the electromagnetic coils by minimizing the kinetic energy of the microparticles, compared to a PD control with disturbance compensation.
Time-varying magnetotail magnetic flux calculation: a test of the method
Directory of Open Access Journals (Sweden)
M. A. Shukhtina
2009-04-01
Full Text Available We modified the Petrinec and Russell (1996 algorithm to allow the computation of time-varying magnetotail magnetic flux based on simultaneous spacecraft measurements in the magnetotail and near-Earth solar wind. In view of many assumptions made we tested the algorithm against MHD simulation in the artificial event, which provides the input from two artificial spacecraft to compute the magnetic flux F values with our algorithm; the latter are compared with flux values, obtained by direct integration in the tail cross-section. The comparison shows similar time variations of predicted and simulated fluxes as well as their good correlation (cc>0.9 for the input taken from the tail lobe, which somewhat degrades if using the "measurements" from the central plasma sheet. The regression relationship between the predicted and computed flux values is rather stable allowing one to correct the absolute value of predicted magnetic flux.
We conclude that this method is a perspective tool to monitor the tail magnetic flux which is one of the main global magnetotail parameters.
Time-varying magnetotail magnetic flux calculation: a test of the method
Directory of Open Access Journals (Sweden)
M. A. Shukhtina
2009-04-01
Full Text Available We modified the Petrinec and Russell (1996 algorithm to allow the computation of time-varying magnetotail magnetic flux based on simultaneous spacecraft measurements in the magnetotail and near-Earth solar wind. In view of many assumptions made we tested the algorithm against MHD simulation in the artificial event, which provides the input from two artificial spacecraft to compute the magnetic flux F values with our algorithm; the latter are compared with flux values, obtained by direct integration in the tail cross-section. The comparison shows similar time variations of predicted and simulated fluxes as well as their good correlation (cc>0.9 for the input taken from the tail lobe, which somewhat degrades if using the "measurements" from the central plasma sheet. The regression relationship between the predicted and computed flux values is rather stable allowing one to correct the absolute value of predicted magnetic flux. We conclude that this method is a perspective tool to monitor the tail magnetic flux which is one of the main global magnetotail parameters.
Directory of Open Access Journals (Sweden)
Forouzan Amir R
2007-01-01
Full Text Available Line selection (LS, tone selection (TS, and joint tone-line selection (JTLS partial crosstalk cancellers have been proposed to reduce the online computational complexity of far-end crosstalk (FEXT cancellers in digital subscriber lines (DSL. However, when the crosstalk profile changes rapidly over time, there is an additional requirement that the partial crosstalk cancellers, particularly the LS and JTLS schemes, should also provide a low preprocessing complexity. This is in contrast to the case for perfect crosstalk cancellers. In this paper, we propose two novel channel matrix inversion methods, the approximate inverse (AI and reduced inverse (RI schemes, which reduce the recurrent complexity of the LS and JTLS schemes. Moreover, we propose two new classes of JTLS algorithms, the subsort and Lagrange JTLS algorithms, with significantly lower computational complexity than the recently proposed optimal greedy JTLS scheme. The computational complexity analysis of our algorithms shows that they provide much lower recurrent complexities than the greedy JTLS algorithm, allowing them to work efficiently in very fast time-varying crosstalk environments. Moreover, the analytical and simulation results demonstrate that our techniques are close to the optimal solution from the crosstalk cancellation point of view. The results also reveal that partial crosstalk cancellation is more beneficial in upstream DSL, particularly for short loops.
Stochastic Power Control for Time-Varying Long-Term Fading Wireless Networks
Directory of Open Access Journals (Sweden)
Charalambous Charalambos D
2006-01-01
Full Text Available A new time-varying (TV long-term fading (LTF channel model which captures both the space and time variations of wireless systems is developed. The proposed TV LTF model is based on a stochastic differential equation driven by Brownian motion. This model is more realistic than the static models usually encountered in the literature. It allows viewing the wireless channel as a dynamical system, thus enabling well-developed tools of adaptive and nonadaptive estimation and identification techniques to be applied to this class of problems. In contrast with the traditional models, the statistics of the proposed model are shown to be TV, but converge in steady state to their static counterparts. Moreover, optimal power control algorithms (PCAs based on the new model are proposed. A centralized PCA is shown to reduce to a simple linear programming problem if predictable power control strategies (PPCS are used. In addition, an iterative distributed stochastic PCA is used to solve for the optimization problem using stochastic approximations. The latter solely requires each mobile to know its received signal-to-interference ratio. Generalizations of the power control problem based on convex optimization techniques are provided if PPCS are not assumed. Numerical results show that there are potentially large gains to be achieved by using TV stochastic models, and the distributed stochastic PCA provides better power stability and consumption than the distributed deterministic PCA.
Control of the tokamak safety factor profile with time-varying constraints using MPC
International Nuclear Information System (INIS)
Maljaars, E.; Felici, F.; De Baar, M.R.; Geelen, P.J.M.; Steinbuch, M.; Van Dongen, J.; Hogeweij, G.M.D.
2015-01-01
A controller is designed for the tokamak safety factor profile that takes real-time-varying operational and physics limits into account. This so-called model predictive controller (MPC) employs a prediction model in order to compute optimal control inputs that satisfy the given limits. The use of linearized models around a reference trajectory results in a quadratic programming problem that can easily be solved online. The performance of the controller is analysed in a set of ITER L-mode scenarios simulated with the non-linear plasma transport code RAPTOR. It is shown that the controller can reduce the tracking error due to an overestimation or underestimation of the modelled transport, while making a trade-off between residual error and amount of controller action. It is also shown that the controller can account for a sudden decrease in the available actuator power, while providing warnings ahead of time about expected violations of operational and physics limits. This controller can be extended and implemented in existing tokamaks in the near future. (paper)
From dynamical systems with time-varying delay to circle maps and Koopman operators
Müller, David; Otto, Andreas; Radons, Günter
2017-06-01
In this paper, we investigate the influence of the retarded access by a time-varying delay on the dynamics of delay systems. We show that there are two universality classes of delays, which lead to fundamental differences in dynamical quantities such as the Lyapunov spectrum. Therefore, we introduce an operator theoretic framework, where the solution operator of the delay system is decomposed into the Koopman operator describing the delay access and an operator similar to the solution operator known from systems with constant delay. The Koopman operator corresponds to an iterated map, called access map, which is defined by the iteration of the delayed argument of the delay equation. The dynamics of this one-dimensional iterated map determines the universality classes of the infinite-dimensional state dynamics governed by the delay differential equation. In this way, we connect the theory of time-delay systems with the theory of circle maps and the framework of the Koopman operator. In this paper, we extend our previous work [A. Otto, D. Müller, and G. Radons, Phys. Rev. Lett. 118, 044104 (2017), 10.1103/PhysRevLett.118.044104] by elaborating the mathematical details and presenting further results also on the Lyapunov vectors.
St-Onge, Guillaume; Young, Jean-Gabriel; Laurence, Edward; Murphy, Charles; Dubé, Louis J.
2018-02-01
We present a degree-based theoretical framework to study the susceptible-infected-susceptible (SIS) dynamics on time-varying (rewired) configuration model networks. Using this framework on a given degree distribution, we provide a detailed analysis of the stationary state using the rewiring rate to explore the whole range of the time variation of the structure relative to that of the SIS process. This analysis is suitable for the characterization of the phase transition and leads to three main contributions: (1) We obtain a self-consistent expression for the absorbing-state threshold, able to capture both collective and hub activation. (2) We recover the predictions of a number of existing approaches as limiting cases of our analysis, providing thereby a unifying point of view for the SIS dynamics on random networks. (3) We obtain bounds for the critical exponents of a number of quantities in the stationary state. This allows us to reinterpret the concept of hub-dominated phase transition. Within our framework, it appears as a heterogeneous critical phenomenon: observables for different degree classes have a different scaling with the infection rate. This phenomenon is followed by the successive activation of the degree classes beyond the epidemic threshold.
On the link between oil price and exchange rate: A time-varying VAR parameter approach
International Nuclear Information System (INIS)
Bremond, Vincent; Razafindrabe, Tovonony; Hache, Emmanuel
2015-07-01
The aim of this paper is to study the relationship between the effective exchange rate of the dollar and the oil price dynamics from 1976 to 2013. In this context, we propose to explore the economic literature dedicated to financial channels factors (exchange rate, monetary policy, and international liquidity) that could affect the oil price dynamics. In addition to oil prices and the effective exchange rate of the dollar, we use the dry cargo index as a proxy for the real economic activity and prices for precious and industrial raw materials. Using a Bayesian time-varying parameter vector auto-regressive estimation, our main results show that the US Dollar effective exchange rate elasticity of the crude oil prices is not constant across the time and remains negative from 1989. It then highlights that a depreciation of the effective exchange rate of the dollar leads to an increase of the crude oil prices. Our paper also demonstrates the growing influence of financial and commodities markets development upon the global economy. (authors)
Interactive exploration of large-scale time-varying data using dynamic tracking graphs
Widanagamaachchi, W.
2012-10-01
Exploring and analyzing the temporal evolution of features in large-scale time-varying datasets is a common problem in many areas of science and engineering. One natural representation of such data is tracking graphs, i.e., constrained graph layouts that use one spatial dimension to indicate time and show the "tracks" of each feature as it evolves, merges or disappears. However, for practical data sets creating the corresponding optimal graph layouts that minimize the number of intersections can take hours to compute with existing techniques. Furthermore, the resulting graphs are often unmanageably large and complex even with an ideal layout. Finally, due to the cost of the layout, changing the feature definition, e.g. by changing an iso-value, or analyzing properly adjusted sub-graphs is infeasible. To address these challenges, this paper presents a new framework that couples hierarchical feature definitions with progressive graph layout algorithms to provide an interactive exploration of dynamically constructed tracking graphs. Our system enables users to change feature definitions on-the-fly and filter features using arbitrary attributes while providing an interactive view of the resulting tracking graphs. Furthermore, the graph display is integrated into a linked view system that provides a traditional 3D view of the current set of features and allows a cross-linked selection to enable a fully flexible spatio-temporal exploration of data. We demonstrate the utility of our approach with several large-scale scientific simulations from combustion science. © 2012 IEEE.
Directory of Open Access Journals (Sweden)
Caisheng Wei
2017-03-01
Full Text Available A novel low-complexity adaptive control method, capable of guaranteeing the transient and steady-state tracking performance in the presence of unknown nonlinearities and actuator saturation, is investigated for the longitudinal dynamics of a generic hypersonic flight vehicle. In order to attenuate the negative effects of classical predefined performance function for unknown initial tracking errors, a modified predefined performance function with time-varying design parameters is presented. Under the newly developed predefined performance function, two novel adaptive controllers with low-complexity computation are proposed for velocity and altitude subsystems of the hypersonic flight vehicle, respectively. Wherein, different from neural network-based approximation, a least square support vector machine with only two design parameters is utilized to approximate the unknown hypersonic dynamics. And the relevant ideal weights are obtained by solving a linear system without resorting to specialized optimization algorithms. Based on the approximation by least square support vector machine, only two adaptive scalars are required to be updated online in the parameter projection method. Besides, a new finite-time-convergent differentiator, with a quite simple structure, is proposed to estimate the unknown generated state variables in the newly established normal output-feedback formulation of altitude subsystem. Moreover, it is also employed to obtain accurate estimations for the derivatives of virtual controllers in a recursive design. This avoids the inherent drawback of backstepping — “explosion of terms” and makes the proposed control method achievable for the hypersonic flight vehicle. Further, the compensation design is employed when the saturations of the actuator occur. Finally, the numerical simulations validate the efficiency of the proposed finite-time-convergent differentiator and control method.
Decomposition Algorithm for Global Reachability on a Time-Varying Graph
Kuwata, Yoshiaki
2010-01-01
A decomposition algorithm has been developed for global reachability analysis on a space-time grid. By exploiting the upper block-triangular structure, the planning problem is decomposed into smaller subproblems, which is much more scalable than the original approach. Recent studies have proposed the use of a hot-air (Montgolfier) balloon for possible exploration of Titan and Venus because these bodies have thick haze or cloud layers that limit the science return from an orbiter, and the atmospheres would provide enough buoyancy for balloons. One of the important questions that needs to be addressed is what surface locations the balloon can reach from an initial location, and how long it would take. This is referred to as the global reachability problem, where the paths from starting locations to all possible target locations must be computed. The balloon could be driven with its own actuation, but its actuation capability is fairly limited. It would be more efficient to take advantage of the wind field and ride the wind that is much stronger than what the actuator could produce. It is possible to pose the path planning problem as a graph search problem on a directed graph by discretizing the spacetime world and the vehicle actuation. The decomposition algorithm provides reachability analysis of a time-varying graph. Because the balloon only moves in the positive direction in time, the adjacency matrix of the graph can be represented with an upper block-triangular matrix, and this upper block-triangular structure can be exploited to decompose a large graph search problem. The new approach consumes a much smaller amount of memory, which also helps speed up the overall computation when the computing resource has a limited physical memory compared to the problem size.
An estimation of crude oil import demand in Turkey: Evidence from time-varying parameters approach
International Nuclear Information System (INIS)
Ozturk, Ilhan; Arisoy, Ibrahim
2016-01-01
The aim of this study is to model crude oil import demand and estimate the price and income elasticities of imported crude oil in Turkey based on a time-varying parameters (TVP) approach with the aim of obtaining accurate and more robust estimates of price and income elasticities. This study employs annual time series data of domestic oil consumption, real GDP, and oil price for the period 1966–2012. The empirical results indicate that both the income and price elasticities are in line with the theoretical expectations. However, the income elasticity is statistically significant while the price elasticity is statistically insignificant. The relatively high value of income elasticity (1.182) from this study suggests that crude oil import in Turkey is more responsive to changes in income level. This result indicates that imported crude oil is a normal good and rising income levels will foster higher consumption of oil based equipments, vehicles and services by economic agents. The estimated income elasticity of 1.182 suggests that imported crude oil consumption grows at a higher rate than income. This in turn reduces oil intensity over time. Therefore, crude oil import during the estimation period is substantially driven by income. - Highlights: • We estimated the price and income elasticities of imported crude oil in Turkey. • Income elasticity is statistically significant and it is 1.182. • The price elasticity is statistically insignificant. • Crude oil import in Turkey is more responsive to changes in income level. • Crude oil import during the estimation period is substantially driven by income.
Early diagnostic of concurrent gear degradation processes progressing under time-varying loads
Guilbault, Raynald; Lalonde, Sébastien
2016-08-01
This study develops a gear diagnostic procedure for the detection of multi- and concurrent degradation processes evolving under time-varying loads. Instead of a conventional comparison between a descriptor and an alarm level, this procedure bases its detection strategy on a descriptor evolution tracking; a lasting descriptor increase denotes the presence of ongoing degradation mechanisms. The procedure works from time domain residual signals prepared in the frequency domain, and accepts any gear conditions as reference signature. To extract the load fluctuation repercussions, the procedure integrates a scaling factor. The investigation first examines a simplification assuming a linear connection between the load and the dynamic response amplitudes. However, while generally valuable, the precision losses associated with large load variations may mask the contribution of tiny flaws. To better reflect the real non-linear relation, the paper reformulates the scaling factor; a power law with an exponent value of 0.85 produces noticeable improvements of the load effect extraction. To reduce the consequences of remaining oscillations, the procedure also includes a filtering phase. During the validation program, a synthetic wear progression assuming a commensurate relation between the wear depth and friction assured controlled evolutions of the surface degradation influence, whereas the fillet crack growth remained entirely determined by the operation conditions. Globally, the tested conditions attest that the final strategy provides accurate monitoring of coexisting isolated damages and general surface deterioration, and that its tracking-detection capacities are unaffected by severe time variations of external loads. The procedure promptly detects the presence of evolving abnormal phenomena. The tests show that the descriptor curve shapes virtually describe the constant wear progression superimposed on the crack length evolution. At the tooth fracture, the mean values of
Marmorino, George O.; Smith, Geoffrey B.; Miller, W. D.
2017-09-01
A pair of time-lagged satellite images of surface algae in the Great Barrier Reef lagoon is used to investigate characteristics of the horizontal velocity field at a spatial resolution as small as 4 m. A distinctive feature is the occurrence of surface patches that are relatively clear of algae and which grow in size. These patches are interpreted as resulting from the horizontally diverging motion associated with boils. The surface divergence in such boils can be as large as 0.01 s-1, as deduced directly from the imagery. Overall, root-mean-squared values of divergence, vorticity, and strain rate are 45, 58, and 170, respectively, when normalized by the Coriolis parameter. By observing the algae and its fluid environment simultaneously, the analysis thus provides a glimpse of how underlying hydrodynamic processes help shape the distribution of surface algae - under the calm winds that favor the formation of dense surface aggregations.
Zhang, Ruikun; Hou, Zhongsheng; Chi, Ronghu; Ji, Honghai
2015-06-01
In this work, an adaptive iterative learning control (AILC) scheme is proposed to address a class of nonlinearly parameterised systems with both unknown time-varying delays and input saturations. By incorporating a saturation function, a novel iterative learning control mechanism is constructed with a feedback term in the time domain and a fully saturated adaptive learning term in the iteration domain, which is used to estimate the unknown time-varying system uncertainty. A new time-weighted Lyapunov-Krasovskii-like composite energy function (LKL-CEF) is designed for the convergence analysis where time-weighted inputs, states and estimates of system uncertainty are all considered. Despite the existence of time-varying parametric uncertainties, time-varying delays, input saturations and local Lipschitz nonlinearities, the learning convergence is guaranteed with rigorous mathematical analysis. Simulation results verify the correctness and effectiveness of the proposed method further.
Visual Predictive Check in Models with Time-Varying Input Function.
Largajolli, Anna; Bertoldo, Alessandra; Campioni, Marco; Cobelli, Claudio
2015-11-01
The nonlinear mixed effects models are commonly used modeling techniques in the pharmaceutical research as they enable the characterization of the individual profiles together with the population to which the individuals belong. To ensure a correct use of them is fundamental to provide powerful diagnostic tools that are able to evaluate the predictive performance of the models. The visual predictive check (VPC) is a commonly used tool that helps the user to check by visual inspection if the model is able to reproduce the variability and the main trend of the observed data. However, the simulation from the model is not always trivial, for example, when using models with time-varying input function (IF). In this class of models, there is a potential mismatch between each set of simulated parameters and the associated individual IF which can cause an incorrect profile simulation. We introduce a refinement of the VPC by taking in consideration a correlation term (the Mahalanobis or normalized Euclidean distance) that helps the association of the correct IF with the individual set of simulated parameters. We investigate and compare its performance with the standard VPC in models of the glucose and insulin system applied on real and simulated data and in a simulated pharmacokinetic/pharmacodynamic (PK/PD) example. The newly proposed VPC performance appears to be better with respect to the standard VPC especially for the models with big variability in the IF where the probability of simulating incorrect profiles is higher.
Cao, Jiguo
2012-01-01
Ordinary differential equations (ODEs) are widely used in biomedical research and other scientific areas to model complex dynamic systems. It is an important statistical problem to estimate parameters in ODEs from noisy observations. In this article we propose a method for estimating the time-varying coefficients in an ODE. Our method is a variation of the nonlinear least squares where penalized splines are used to model the functional parameters and the ODE solutions are approximated also using splines. We resort to the implicit function theorem to deal with the nonlinear least squares objective function that is only defined implicitly. The proposed penalized nonlinear least squares method is applied to estimate a HIV dynamic model from a real dataset. Monte Carlo simulations show that the new method can provide much more accurate estimates of functional parameters than the existing two-step local polynomial method which relies on estimation of the derivatives of the state function. Supplemental materials for the article are available online.
Time-varying span efficiency through the wingbeat of desert locusts.
Henningsson, Per; Bomphrey, Richard J
2012-06-07
The flight performance of animals depends greatly on the efficacy with which they generate aerodynamic forces. Accordingly, maximum range, load-lifting capacity and peak accelerations during manoeuvres are all constrained by the efficiency of momentum transfer to the wake. Here, we use high-speed particle image velocimetry (1 kHz) to record flow velocities in the near wake of desert locusts (Schistocerca gregaria, Forskål). We use the measured flow fields to calculate time-varying span efficiency throughout the wing stroke cycle. The locusts are found to operate at a maximum span efficiency of 79 per cent, typically at a plateau of about 60 per cent for the majority of the downstroke, but at lower values during the upstroke. Moreover, the calculated span efficiencies are highest when the largest lift forces are being generated (90% of the total lift is generated during the plateau of span efficiency) suggesting that the combination of wing kinematics and morphology in locust flight perform most efficiently when doing the most work.
Hermans, Thomas; Oware, Erasmus; Caers, Jef
2016-09-01
Time-lapse applications of electrical methods have grown significantly over the last decade. However, the quantitative interpretation of tomograms in terms of physical properties, such as salinity, temperature or saturation, remains difficult. In many applications, geophysical models are transformed into hydrological models, but this transformation suffers from spatially and temporally varying resolution resulting from the regularization used by the deterministic inversion. In this study, we investigate a prediction-focused approach (PFA) to directly estimate subsurface physical properties with electrical resistance data, circumventing the need for classic tomographic inversions. First, we generate a prior set of resistance data and physical property forecast through hydrogeological and geophysical simulations mimicking the field experiment. We reduce the dimension of both the data and the forecast through principal component analysis in order to keep the most informative part of both sets in a reduced dimension space. Then, we apply canonical correlation analysis to explore the relationship between the data and the forecast in their reduced dimension space. If a linear relationship can be established, the posterior distribution of the forecast can be directly sampled using a Gaussian process regression where the field data scores are the conditioning data. In this paper, we demonstrate PFA for various physical property distributions. We also develop a framework to propagate the estimated noise level in the reduced dimension space. We validate the results by a Monte Carlo study on the posterior distribution and demonstrate that PFA yields accurate uncertainty for the cases studied.
Energy Technology Data Exchange (ETDEWEB)
Alexander S. Rattner; Donna Post Guillen; Alark Joshi
2012-12-01
Photo- and physically-realistic techniques are often insufficient for visualization of simulation results, especially for 3D and time-varying datasets. Substantial research efforts have been dedicated to the development of non-photorealistic and illustration-inspired visualization techniques for compact and intuitive presentation of such complex datasets. While these efforts have yielded valuable visualization results, a great deal of work has been reproduced in studies as individual research groups often develop purpose-built platforms. Additionally, interoperability between illustrative visualization software is limited due to specialized processing and rendering architectures employed in different studies. In this investigation, a generalized framework for illustrative visualization is proposed, and implemented in marmotViz, a ParaView plugin, enabling its use on variety of computing platforms with various data file formats and mesh geometries. Detailed descriptions of the region-of-interest identification and feature-tracking algorithms incorporated into this tool are provided. Additionally, implementations of multiple illustrative effect algorithms are presented to demonstrate the use and flexibility of this framework. By providing a framework and useful underlying functionality, the marmotViz tool can act as a springboard for future research in the field of illustrative visualization.
Knowledge diffusion in complex networks by considering time-varying information channels
Zhu, He; Ma, Jing
2018-03-01
In this article, based on a model of epidemic spreading, we explore the knowledge diffusion process with an innovative mechanism for complex networks by considering time-varying information channels. To cover the knowledge diffusion process in homogeneous and heterogeneous networks, two types of networks (the BA network and the ER network) are investigated. The mean-field theory is used to theoretically draw the knowledge diffusion threshold. Numerical simulation demonstrates that the knowledge diffusion threshold is almost linearly correlated with the mean of the activity rate. In addition, under the influence of the activity rate and distinct from the classic Susceptible-Infected-Susceptible (SIS) model, the density of knowers almost linearly grows with the spreading rate. Finally, in consideration of the ubiquitous mechanism of innovation, we further study the evolution of knowledge in our proposed model. The results suggest that compared with the effect of the spreading rate, the average knowledge version of the population is affected more by the innovation parameter and the mean of the activity rate. Furthermore, in the BA network, the average knowledge version of individuals with higher degree is always newer than those with lower degree.
Multiobjective Resource-Constrained Project Scheduling with a Time-Varying Number of Tasks
Abello, Manuel Blanco
2014-01-01
In resource-constrained project scheduling (RCPS) problems, ongoing tasks are restricted to utilizing a fixed number of resources. This paper investigates a dynamic version of the RCPS problem where the number of tasks varies in time. Our previous work investigated a technique called mapping of task IDs for centroid-based approach with random immigrants (McBAR) that was used to solve the dynamic problem. However, the solution-searching ability of McBAR was investigated over only a few instances of the dynamic problem. As a consequence, only a small number of characteristics of McBAR, under the dynamics of the RCPS problem, were found. Further, only a few techniques were compared to McBAR with respect to its solution-searching ability for solving the dynamic problem. In this paper, (a) the significance of the subalgorithms of McBAR is investigated by comparing McBAR to several other techniques; and (b) the scope of investigation in the previous work is extended. In particular, McBAR is compared to a technique called, Estimation Distribution Algorithm (EDA). As with McBAR, EDA is applied to solve the dynamic problem, an application that is unique in the literature. PMID:24883398
Identification of a Time-Varying, Box-Jenkins Model of Intrinsic Joint Compliance.
Guarin, Diego L; Kearney, Robert E
2017-08-01
The mechanical properties of a joint are determined by the combination of intrinsic and reflex mechanisms. However, in some situations the reflex contributions are small so that intrinsic mechanisms play the dominant role in the control of posture and movement. The intrinsic mechanisms, characterized by the joint compliance, can be described well by a second order, linear model for small perturbations around an operating point defined by mean position and torque. However, the compliance parameters depend strongly on the operating point. Thus, for functional activities, such as walking, where position and torque undergo large, rapid changes, the joint compliance will also present large, fast changes and so will appear to be Time-Varying (TV). Therefore, a TV system identification algorithm must be used to characterize these changes. This paper introduces a novel TV system identification algorithm that achieves this. The method extends an instrumental-variable based algorithm for the identification of linear, TV, parametric, Box-Jenkins models to use periodic data. Simulation studies demonstrate that the new algorithm accurately tracks the changes in intrinsic joint compliance expected during walking. Moreover, the method performs well with the complex noise encountered in practice. Consequently the new method should be a valuable tool for the study of joint mechanics during functional activities.
Microhardness of composite resins at different depths varying the post-irradiation time
Directory of Open Access Journals (Sweden)
Juliane Cristina Ciccone-Nogueira
2007-08-01
Full Text Available OBJECTIVE: The purpose of this study was to assess the microhardness of posterior composite resins at different depths varying the post-irradiation time. MATERIALS AND METHODS: For each composite resin [Solitaire 2 (SO - Heraus Kulzer, P60 (P - 3M, Prodigy Condesable (PC - Kerr, Surefil (S - Dentsply and Alert (A - Pentron], 6 specimens (3 mm in diameter; 4mm high were prepared using a black polyurethane cylindrical matrix. The resins were inserted in a bulk increment and light cured for 40 seconds. Microhardness was analyzed at different depths (top, 0.4 mm, 1.0 mm, 2.0mm, 3.0 mm and 4.0 mm and at two moments (20 minutes and 24 hours after light-curing. Data were analyzed by ANOVA and Tukey's test (p<0.05. RESULTS: Overall, microhardness means decreased significantly with the increase of depth, being lower in the first moment tested. P, S and PC showed the highest microhardness means. CONCLUSION: It may be concluded that the tested composite resins presented a gradual decrease of microhardness as depth increased and this drop was more accentuated for depths beyond 2 mm. For all materials, higher microhardness means were recorded 24 hours after light activation. P60 yielded the best results at the different depths evaluated.
Directory of Open Access Journals (Sweden)
Zhang Han
2009-01-01
Full Text Available We address the problem of superimposed trainings- (STs- based linearly time-varying (LTV channel estimation and symbol detection for orthogonal frequency-division multiplexing access (OFDMA systems at the uplink receiver. The LTV channel coefficients are modeled by truncated discrete Fourier bases (DFBs. By judiciously designing the superimposed pilot symbols, we estimate the LTV channel transfer functions over the whole frequency band by using a weighted average procedure, thereby providing validity for adaptive resource allocation. We also present a performance analysis of the channel estimation approach to derive a closed-form expression for the channel estimation variances. In addition, an iterative symbol detector is presented to mitigate the superimposed training effects on information sequence recovery. By the iterative mitigation procedure, the demodulator achieves a considerable gain in signal-interference ratio and exhibits a nearly indistinguishable symbol error rate (SER performance from that of frequency-division multiplexed trainings. Compared to existing frequency-division multiplexed training schemes, the proposed algorithm does not entail any additional bandwidth while with the advantage for system adaptive resource allocation.
The Fast Simulation of Scattering Characteristics from a Simplified Time Varying Sea Surface
Directory of Open Access Journals (Sweden)
Yiwen Wei
2015-01-01
Full Text Available This paper aims at applying a simplified sea surface model into the physical optics (PO method to accelerate the scattering calculation from 1D time varying sea surface. To reduce the number of the segments and make further improvement on the efficiency of PO method, a simplified sea surface is proposed. In this simplified sea surface, the geometry of long waves is locally approximated by tilted facets that are much longer than the electromagnetic wavelength. The capillary waves are considered to be sinusoidal line superimposing on the long waves. The wavenumber of the sinusoidal waves is supposed to satisfy the resonant condition of Bragg waves which is dominant in all the scattered short wave components. Since the capillary wave is periodical within one facet, an analytical integration of the PO term can be performed. The backscattering coefficient obtained from a simplified sea surface model agrees well with that obtained from a realistic sea surface. The Doppler shifts and width also agree well with the realistic model since the capillary waves are taken into consideration. The good agreements indicate that the simplified model is reasonable and valid in predicting both the scattering coefficients and the Doppler spectra.
Directory of Open Access Journals (Sweden)
Johann A. Briffa
2014-06-01
Full Text Available In this study, the authors consider time-varying block (TVB codes, which generalise a number of previous synchronisation error-correcting codes. They also consider various practical issues related to maximum a posteriori (MAP decoding of these codes. Specifically, they give an expression for the expected distribution of drift between transmitter and receiver because of synchronisation errors. They determine an appropriate choice for state space limits based on the drift probability distribution. In turn, they obtain an expression for the decoder complexity under given channel conditions in terms of the state space limits used. For a given state space, they also give a number of optimisations that reduce the algorithm complexity with no further loss of decoder performance. They also show how the MAP decoder can be used in the absence of known frame boundaries, and demonstrate that an appropriate choice of decoder parameters allows the decoder to approach the performance when frame boundaries are known, at the expense of some increase in complexity. Finally, they express some existing constructions as TVB codes, comparing performance with published results and showing that improved performance is possible by taking advantage of the flexibility of TVB codes.
Mapping Flooded Rice Paddies Using Time Series of MODIS Imagery in the Krishna River Basin, India
Directory of Open Access Journals (Sweden)
Pardhasaradhi Teluguntla
2015-07-01
Full Text Available Rice is one of the major crops cultivated predominantly in flooded paddies, thus a large amount of water is consumed during its growing season. Accurate paddy rice maps are therefore important inputs for improved estimates of actual evapotranspiration in the agricultural landscape. The main objective of this study was to obtain flooded paddy rice maps using multi-temporal images of Moderate Resolution Imaging Spectroradiometer (MODIS in the Krishna River Basin, India. First, ground-based spectral samples collected by a field spectroradiometer, CROPSCAN, were used to demonstrate unique contrasts between the Normalized Difference Vegetation Index (NDVI and the Land Surface Water Index (LSWI observed during the transplanting season of rice. The contrast between Enhanced Vegetation Index (EVI and Land Surface Water Index (LSWI from MODIS time series data was then used to generate classification decision rules to map flooded rice paddies, for the transplanting seasons of Kharif and Rabi rice crops in the Krishna River Basin. Consistent with ground spectral observations, the relationship of the MODIS EVI vs. LSWI of paddy rice fields showed distinct features from other crops during the transplanting seasons. The MODIS-derived maps were validated against extensive reference data collected from multiple land use field surveys. The accuracy of the paddy rice maps, when determined using field plot data, was approximately 78%. The MODIS-derived rice crop areas were also compared with the areas reported by Department of Agriculture (DOA, Government of India (Government Statistics. The estimated root mean square difference (RMSD of rice area estimated using MODIS and those reported by the Department of Agriculture over 10 districts varied between 3.4% and 6.6% during 10 years of our study period. Some of the major factors responsible for this difference include high noise of the MODIS images during the prolonged monsoon seasons (typically June–October and
High-Resolution Gravity and Time-Varying Gravity Field Recovery using GRACE and CHAMP
Shum, C. K.
2002-01-01
This progress report summarizes the research work conducted under NASA's Solid Earth and Natural Hazards Program 1998 (SENH98) entitled High Resolution Gravity and Time Varying Gravity Field Recovery Using GRACE (Gravity Recovery and Climate Experiment) and CHAMP (Challenging Mini-satellite Package for Geophysical Research and Applications), which included a no-cost extension time period. The investigation has conducted pilot studies to use the simulated GRACE and CHAMP data and other in situ and space geodetic observable, satellite altimeter data, and ocean mass variation data to study the dynamic processes of the Earth which affect climate change. Results from this investigation include: (1) a new method to use the energy approach for expressing gravity mission data as in situ measurements with the possibility to enhance the spatial resolution of the gravity signal; (2) the method was tested using CHAMP and validated with the development of a mean gravity field model using CHAMP data, (3) elaborate simulation to quantify errors of tides and atmosphere and to recover hydrological and oceanic signals using GRACE, results show that there are significant aliasing effect and errors being amplified in the GRACE resonant geopotential and it is not trivial to remove these errors, and (4) quantification of oceanic and ice sheet mass changes in a geophysical constraint study to assess their contributions to global sea level change, while the results improved significant over the use of previous studies using only the SLR (Satellite Laser Ranging)-determined zonal gravity change data, the constraint could be further improved with additional information on mantle rheology, PGR (Post-Glacial Rebound) and ice loading history. A list of relevant presentations and publications is attached, along with a summary of the SENH investigation generated in 2000.
A Loudness Model for Time-Varying Sounds Incorporating Binaural Inhibition
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Brian C. J. Moore
2016-12-01
Full Text Available This article describes a model of loudness for time-varying sounds that incorporates the concept of binaural inhibition, namely, that the signal applied to one ear can reduce the internal response to a signal at the other ear. For each ear, the model includes the following: a filter to allow for the effects of transfer of sound through the outer and middle ear; a short-term spectral analysis with greater frequency resolution at low than at high frequencies; calculation of an excitation pattern, representing the magnitudes of the outputs of the auditory filters as a function of center frequency; application of a compressive nonlinearity to the output of each auditory filter; and smoothing over time of the resulting instantaneous specific loudness pattern using an averaging process resembling an automatic gain control. The resulting short-term specific loudness patterns are used to calculate broadly tuned binaural inhibition functions, the amount of inhibition depending on the relative short-term specific loudness at the two ears. The inhibited specific loudness patterns are summed across frequency to give an estimate of the short-term loudness for each ear. The overall short-term loudness is calculated as the sum of the short-term loudness values for the two ears. The long-term loudness for each ear is calculated by smoothing the short-term loudness for that ear, again by a process resembling automatic gain control, and the overall loudness impression is obtained by summing the long-term loudness across ears. The predictions of the model are more accurate than those of an earlier model that did not incorporate binaural inhibition.
International Nuclear Information System (INIS)
Stefanou, G.D.
1978-01-01
The work described herein relates to the prediction of stresses in materials which exhibit time varying strains with particular reference to the ligaments of perforated circular concrete slabs, subjected to long-term radial prestress and uniform elevated temperature. The perforations are reinforced with steel liners and arranged in a square central lattice symmetrical about two orthogonal axes. Special reference is made to the distribution of stress in the standpipe region of prestressed concrete cylindrical pressure or containment vessels for gas cooled reactors. In order to assess the stress distribution around the perforated zone of a circular slab, a method of analysis was developed by the author, based on the ''Equivalent Elastic Modulus'' of the perforated zone and the ''Effective Modulus Method'', utilizing experimental data obtained from tests performed on model specimens. The object of this paper is to extend the above method of analysis into the perforated region, and assess the long-term stresses in the ligaments. The proposed method is accomplished by an application of the Finite Element Method for the elastic plane stress case. Comparisons of experimental results and theoretical predictions by the proposed method, and other analytical methods are made for a series of perforated concrete slabs subjected to radial in-plane loading: 10,342 kN/m 2 (1,5000 psi), and uniform elevated temperature of 80 0 C. The investigation, though in general terms, could be applied to the perforated region of cylindrical pressure vessels for nuclear reactors. Finally the paper describes briefly in Appendix 3 a direct solution procedure for calculating time dependent stresses in concrete structures based on the principles of variational calculus. Analytical predictions obtained by the proposed method which is a step-by-step analysis, are compared with the variational principle method. (author)
Whorton, E.; Headman, A.; Shean, D. E.; McCann, E.
2017-12-01
Understanding the implications of glacier recession on water resources in the western U.S. requires quantifying glacier mass change across large regions over several decades. Very few glaciers in North America have long-term continuous field measurements of glacier mass balance. However, systematic aerial photography campaigns began in 1957 on many glaciers in the western U.S. and Alaska. These historical, vertical aerial stereo-photographs documenting glacier evolution have recently become publically available. Digital elevation models (DEM) of the transient glacier surface preserved in each imagery timestamp can be derived, then differenced to calculate glacier volume and mass change to improve regional geodetic solutions of glacier mass balance. In order to batch process these data, we use Python-based algorithms and Agisoft Photoscan structure from motion (SfM) photogrammetry software to semi-automate DEM creation, and orthorectify and co-register historical aerial imagery in a high-performance computing environment. Scanned photographs are rotated to reduce scaling issues, cropped to the same size to remove fiducials, and batch histogram equalization is applied to improve image quality and aid pixel-matching algorithms using the Python library OpenCV. Processed photographs are then passed to Photoscan through the Photoscan Python library to create DEMs and orthoimagery. To extend the period of record, the elevation products are co-registered to each other, airborne LiDAR data, and DEMs derived from sub-meter commercial satellite imagery. With the exception of the placement of ground control points, the process is entirely automated with Python. Current research is focused on: one, applying these algorithms to create geodetic mass balance time series for the 90 photographed glaciers in Washington State and two, evaluating the minimal amount of positional information required in Photoscan to prevent distortion effects that cannot be addressed during co
Time-varying loss forecast for an earthquake scenario in Basel, Switzerland
Herrmann, Marcus; Zechar, Jeremy D.; Wiemer, Stefan
2014-05-01
When an unexpected earthquake occurs, people suddenly want advice on how to cope with the situation. The 2009 L'Aquila quake highlighted the significance of public communication and pushed the usage of scientific methods to drive alternative risk mitigation strategies. For instance, van Stiphout et al. (2010) suggested a new approach for objective evacuation decisions on short-term: probabilistic risk forecasting combined with cost-benefit analysis. In the present work, we apply this approach to an earthquake sequence that simulated a repeat of the 1356 Basel earthquake, one of the most damaging events in Central Europe. A recent development to benefit society in case of an earthquake are probabilistic forecasts of the aftershock occurrence. But seismic risk delivers a more direct expression of the socio-economic impact. To forecast the seismic risk on short-term, we translate aftershock probabilities to time-varying seismic hazard and combine this with time-invariant loss estimation. Compared with van Stiphout et al. (2010), we use an advanced aftershock forecasting model and detailed settlement data to allow us spatial forecasts and settlement-specific decision-making. We quantify the risk forecast probabilistically in terms of human loss. For instance one minute after the M6.6 mainshock, the probability for an individual to die within the next 24 hours is 41 000 times higher than the long-term average; but the absolute value remains at minor 0.04 %. The final cost-benefit analysis adds value beyond a pure statistical approach: it provides objective statements that may justify evacuations. To deliver supportive information in a simple form, we propose a warning approach in terms of alarm levels. Our results do not justify evacuations prior to the M6.6 mainshock, but in certain districts afterwards. The ability to forecast the short-term seismic risk at any time-and with sufficient data anywhere-is the first step of personal decision-making and raising risk
2017-12-08
Application of a Statistical Linear Time -Varying System Model of High Grazing Angle Sea Clutter for Computing Interference Power i REPORT DOCUMENTATION...for this collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data...code) b. ABSTRACT c. THIS PAGE 18. NUMBER OF PAGES 17. LIMITATION OF ABSTRACT Application of a Statistical Linear Time -Varying System Model of High
Time-varying sodium absorption in the Type Ia supernova 2013gh
Ferretti, R.; Amanullah, R.; Goobar, A.; Johansson, J.; Vreeswijk, P. M.; Butler, R. P.; Cao, Y.; Cenko, S. B.; Doran, G.; Filippenko, A. V.; Freeland, E.; Hosseinzadeh, G.; Howell, D. A.; Lundqvist, P.; Mattila, S.; Nordin, J.; Nugent, P. E.; Petrushevska, T.; Valenti, S.; Vogt, S.; Wozniak, P.
2016-07-01
Context. Temporal variability of narrow absorption lines in high-resolution spectra of Type Ia supernovae (SNe Ia) is studied to search for circumstellar matter. Time series which resolve the profiles of absorption lines such as Na I D or Ca II H&K are expected to reveal variations due to photoionisation and subsequent recombination of the gases. The presence, composition, and geometry of circumstellar matter may hint at the elusive progenitor system of SNe Ia and could also affect the observed reddening law. Aims: To date, there are few known cases of time-varying Na I D absorption in SNe Ia, all of which occurred during relatively late phases of the supernova (SN) evolution. Photoionisation, however, is predicted to occur during the early phases of SNe Ia, when the supernovae peak in the ultraviolet. We attempt, therefore, to observe early-time absorption-line variations by obtaining high-resolution spectra of SNe before maximum light. Methods: We have obtained photometry and high-resolution spectroscopy of SNe Ia 2013gh and iPTF 13dge, to search for absorption-line variations. Furthermore, we study interstellar absorption features in relation to the observed photometric colours of the SNe. Results: Both SNe display deep Na I D and Ca II H&K absorption features. Furthermore, small but significant variations are detected in a feature of the Na I D profile of SN 2013gh. The variations are consistent with either geometric effects of rapidly moving or patchy gas clouds or photoionisation of Na I gas at R ≈ 1019 cm from the explosion. Conclusions: Our analysis indicates that it is necessary to focus on early phases to detect photoionisation effects of gases in the circumstellar medium of SNe Ia. Different absorbers such as Na I and Ca II can be used to probe for matter at different distances from the SNe. The nondetection of variations during early phases makes it possible to put limits on the abundance of the species at those distances. Full Tables 2 and 3 are only
Higham, Timothy E; Russell, Anthony P
2012-02-01
Autotomy (voluntary loss of an appendage) is common among diverse groups of vertebrates and invertebrates, and much attention has been given to ecological and developmental aspects of tail autotomy in lizards. Although most studies have focused on the ramifications for the lizard (behavior, biomechanics, energetics, etc.), the tail itself can exhibit interesting behaviors once segregated from the body. For example, recent work highlighted the ability of leopard gecko tails to jump and flip, in addition to being able to swing back and forth. Little is known, however, about the control mechanisms underlying these movements. Using electromyography, we examined the time-varying in vivo motor patterns at four sites (two proximal and two distal) in the tail of the leopard gecko, Eublepharis macularius, following autotomy. Using these data we tested the hypothesis that the disparity in movements results simply from overlapping pattern generators within the tail. We found that burst duration, but not cycle duration, of the rhythmic swings reached a plateau at approximately 150 s following autotomy. This is likely because of physiological changes related to muscle fatigue and ischemia. For flips and jumps, burst and cycle duration exhibited no regular pattern. The coefficient of variation in motor patterns was significantly greater for jumps and flips than for rhythmic swings. This supports the conclusion that the different tail behaviors do not stem from overlapping pattern generators, but that they rely upon independent neural circuits. The signal controlling jumps and flips may be modified by sensory information from the environment. Finally, we found that jumps and flips are initiated using relatively synchronous activity between the two sides of the tail. In contrast, alternating activation of the right and left sides of the tail result in rhythmic swings. The mechanism underlying this change in tail behavior is comparable to locomotor gait changes in vertebrates.
On the time-varying trend in global-mean surface temperature
Energy Technology Data Exchange (ETDEWEB)
Wu, Zhaohua [Florida State University, Department of Meteorology and Center for Ocean-Atmospheric Prediction Studies, Tallahassee, FL (United States); Huang, Norden E. [National Central University, Research Center for Adaptive Data Analysis Center, Chungli (China); Wallace, John M.; Smoliak, Brian V. [University of Washington, Department of Atmospheric Sciences, Seattle, WA (United States); Chen, Xianyao [State Oceanic Administration, The First Institute of Oceanography, Qingdao (China)
2011-08-15
The Earth has warmed at an unprecedented pace in the decades of the 1980s and 1990s (IPCC in Climate change 2007: the scientific basis, Cambridge University Press, Cambridge, 2007). In Wu et al. (Proc Natl Acad Sci USA 104:14889-14894, 2007) we showed that the rapidity of the warming in the late twentieth century was a result of concurrence of a secular warming trend and the warming phase of a multidecadal ({proportional_to}65-year period) oscillatory variation and we estimated the contribution of the former to be about 0.08 C per decade since {proportional_to}1980. Here we demonstrate the robustness of those results and discuss their physical links, considering in particular the shape of the secular trend and the spatial patterns associated with the secular trend and the multidecadal variability. The shape of the secular trend and rather globally-uniform spatial pattern associated with it are both suggestive of a response to the buildup of well-mixed greenhouse gases. In contrast, the multidecadal variability tends to be concentrated over the extratropical Northern Hemisphere and particularly over the North Atlantic, suggestive of a possible link to low frequency variations in the strength of the thermohaline circulation. Depending upon the assumed importance of the contributions of ocean dynamics and the time-varying aerosol emissions to the observed trends in global-mean surface temperature, we estimate that up to one third of the late twentieth century warming could have been a consequence of natural variability. (orig.)
Effects of sleep inertia after daytime naps vary with executive load and time of day.
Groeger, John A; Lo, June C Y; Burns, Christopher G; Dijk, Derk-Jan
2011-04-01
The effects of executive load on working memory performance during sleep inertia after morning or afternoon naps were assessed using a mixed design with nap/wake as a between-subjects factor and morning/afternoon condition as a within-subject factor. Thirty-two healthy adults (mean 22.5 ± 3.0 years) attended two laboratory sessions after a night of restricted sleep (6 hrs), and at first visit, were randomly assigned to the Nap or Wake group. Working memory (n-back) and subjective workload were assessed approximately 5 and 25 minutes after 90-minute morning and afternoon nap opportunities and at the corresponding times in the Wake condition. Actigraphically assessed nocturnal sleep duration, subjective sleepiness, and psychomotor vigilance performance before daytime assessments did not vary across conditions. Afternoon naps showed shorter EEG assessed sleep latencies, longer sleep duration, and more Slow Wave Sleep than morning naps. Working memory performance deteriorated, and subjective mental workload increased at higher executive loadings. After afternoon naps, participants performed less well on more executive-function intensive working memory tasks (i.e., 3-back), but waking and napping participants performed equally well on simpler tasks. After some 30 minutes of cognitive activity, there were no longer performance differences between the waking and napping groups. Subjective Task Difficulty and Mental Effort requirements were less affected by sleep inertia and dissociated from objective measures when participants had napped in the afternoon. We conclude that executive functions take longer to return to asymptotic performance after sleep than does performance of simpler tasks which are less reliant on executive functions. (PsycINFO Database Record (c) 2011 APA, all rights reserved).
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.
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
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.
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.
DEFF Research Database (Denmark)
Olsen, Jørgen Lundegaard
NDVI using the unique field data set from the Widou Thiengoly test site in northern Senegal. The field data have been collected under controlled grazing intensities. From this data a very clear effect of grazing on plant species composition and NPP/NDVI relationships is found. It is suggested...... that the varying NPP/NDVI relationships, combined with the large increase in livestock of the Sahel in recent decades, means that the greening of the Sahel cannot uncritically be interpreted as a positive trend in vegetation productivity due to increasing rainfall. It can also represent grazing induced changes...
Handling Interfaces and Time-varying Properties in Radionuclide Transport Models
International Nuclear Information System (INIS)
Robinson, Peter; Watson, Claire
2010-12-01
This report documents studies undertaken by Quintessa during 2010 in preparation for the SR-Site review that will be initiated by SSM in 2011. The studies relate to consequence analysis calculations, that is to the calculation of radionuclide release and transport if a canister is breached. A sister report documents modelling work undertaken to investigate the coupled processes relevant to copper corrosion and buffer erosion. The Q eq concept is an important part of SKB's current methodology for radionuclide transport using one-dimensional transport modelling; it is used in particular to model transport at the buffer/fracture interface. Quintessa's QPAC code has been used to investigate the Q eq approach and to explore the importance of heterogeneity in the fracture and spalling on the deposition hole surface. The key conclusions are that: - The basic approach to calculating Q eq values is sound and can be reproduced in QPAC. - The fracture resistance dominates over the diffusive resistance in the buffer except for the highest velocity cases. - Heterogeneity in the fracture, in terms of uncorrelated random variations in the fracture aperture, tends to reduce releases, so the use of a constant average aperture approach is conservative. - Narrow channels could lead to the same release as larger fractures with the same pore velocity, so a channel enhancement factor of √10 should be considered. - A spalling zone that increases the area of contact between flowing water and the buffer has the potential to increase the release significantly and changes the functional dependence of Q eq frac on the flowing velocity. Quintessa's AMBER software has previously been used to reproduce SKB's one-dimensional transport calculations and AMBER allows the use of time varying properties. This capability has been used to investigate the effects of glacial episodes on radionuclide transport. The main parameters that could be affected are sorption coefficients and flow rates. For both
Poverty assessment using DMSP/OLS night-time light satellite imagery at a provincial scale in China
Wang, Wen; Cheng, Hui; Zhang, Li
2012-04-01
All countries around the world and many international bodies, including the United Nations Development Program (UNDP), United Nations Food and Agricultural Organization (FAO), the International Fund for Agricultural Development (IFAD) and the International Labor Organization (ILO), have to eliminate rural poverty. Estimation of regional poverty level is a key issue for making strategies to eradicate poverty. Most of previous studies on regional poverty evaluations are based on statistics collected typically in administrative units. This paper has discussed the deficiencies of traditional studies, and attempted to research regional poverty evaluation issues using 3-year DMSP/OLS night-time light satellite imagery. In this study, we adopted 17 socio-economic indexes to establish an integrated poverty index (IPI) using principal component analysis (PCA), which was proven to provide a good descriptor of poverty levels in 31 regions at a provincial scale in China. We also explored the relationship between DMSP/OLS night-time average light index and the poverty index using regression analysis in SPSS and a good positive linear correlation was modelled, with R2 equal to 0.854. We then looked at provincial poverty problems in China based on this correlation. The research results indicated that the DMSP/OLS night-time light data can assist analysing provincial poverty evaluation issues.
Schumann, G.; di Baldassarre, G.; Alsdorf, D.; Bates, P. D.
2009-04-01
In February 2000, the Shuttle Radar Topography Mission (SRTM) measured the elevation of most of the Earth's surface with spatially continuous sampling and an absolute vertical accuracy greater than 9 m. The vertical error has been shown to change with topographic complexity, being less important over flat terrain. This allows water surface slopes to be measured and associated discharge volumes to be estimated for open channels in large basins, such as the Amazon. Building on these capabilities, this paper demonstrates that near real-time coarse resolution radar imagery of a recent flood event on a 98 km reach of the River Po (Northern Italy) combined with SRTM terrain height data leads to a water slope remarkably similar to that derived by combining the radar image with highly accurate airborne laser altimetry. Moreover, it is shown that this space-borne flood wave approximation compares well to a hydraulic model and thus allows the performance of the latter, calibrated on a previous event, to be assessed when applied to an event of different magnitude in near real-time. These results are not only of great importance to real-time flood management and flood forecasting but also support the upcoming Surface Water and Ocean Topography (SWOT) mission that will routinely provide water levels and slopes with higher precision around the globe.
Calhoun, Tracy; Melendrez, Dave
2014-01-01
-of-a-kind imagery assets and skill sets, such as ground-based fixed and tracking cameras, crew-in the-loop imaging applications, and the integration of custom or commercial-off-the-shelf sensors onboard spacecraft. For spaceflight applications, the Integration 2 Team leverages modeling, analytical, and scientific resources along with decades of experience and lessons learned to assist the customer in optimizing engineering imagery acquisition and management schemes for any phase of flight - launch, ascent, on-orbit, descent, and landing. The Integration 2 Team guides the customer in using NASA's world-class imagery analysis teams, which specialize in overcoming inherent challenges associated with spaceflight imagery sets. Precision motion tracking, two-dimensional (2D) and three-dimensional (3D) photogrammetry, image stabilization, 3D modeling of imagery data, lighting assessment, and vehicle fiducial marking assessments are available. During a mission or test, the Integration 2 Team provides oversight of imagery operations to verify fulfillment of imagery requirements. The team oversees the collection, screening, and analysis of imagery to build a set of imagery findings. It integrates and corroborates the imagery findings with other mission data sets, generating executive summaries to support time-critical mission decisions.
Modeling the time-varying interaction between surface water and groundwater bodies
Gliege, Steffen; Steidl, Jörg; Lischeid, Gunnar; Merz, Christoph
2016-04-01
The countless kettle holes (small lakes) in the Late Pleistocene landscapes of Northern Europe have important ecological and hydrological functions. On the one hand they act as depressions in which water and solutes of mainly agriculturally used catchments accumulate. On the other hand they operate as biochemical reactors with respect to greenhouse gas emissions, carbon sequestration, and as major sinks for nutrients and contaminants. Even small kettle holes often are hydraulically connected to the uppermost groundwater system: Groundwater discharges into the kettle hole on one side, and the aquifer is recharged from the kettle hole water body on the other side. Thus kettle hole biogeochemical processes are both affected by groundwater and vice versa. Groundwater flow direction and velocity into and out of the kettle hole often is not stable over time. Groundwater flow direction might reverse at the downstream part, resulting in repeated recycling of groundwater and corresponding solute turnover within the kettle holes. A sound understanding of this intricate interplay is a necessary prerequisite for better understanding of the biogeochemistry of this terrestrial-aquatic interface. A numerical experiment was used to quantify the lateral solute exchange between a kettle hole and the surrounding groundwater. A vertical cross section through the real existing catchment of a kettle hole was chosen. Glacial till represents the lower boundary. The heterogeneity of the subsurface was reproduced by various parameterizations of the soil hydraulic properties as well as varying the thickness of the unconfined aquifer or the lateral boundary conditions. In total 24 different parameterizations were implemented in the modeling software HydroGeoSphere (HGS). HGS is suitable to calculate the fluid exchange between surface and subsurface simultaneously and in a physically based way. The simulation runs were done for the period from November 1994 to October 2014. All results were
Combining Multi-Sensor Measurements and Models to Constrain Time-Varying Aerosol Fire Emissions
Cohen, J. B.
2013-12-01
. This data has been used in connection with a new analytical technique to derive the temporally and spatially varying component of the emissions. Combining this result with the Kalman Filter annual base emissions and the modelling system shows that fires can be reproduced more accurately than many other methods, including using straight Fire Radiative Power estimations. Finally, this new combined product is analyzed using measurements from the CALIPSO sensor to quantify further properties of these fires, particularly in terms of radiative forcing and vertical distribution. The results are compared against other studies of fires and the impacts on the radiative balance are quantified. One conclusion is that emissions of both BC and OC from these fires are currently underestimated and this method provides a means by which to quantify this underestimation, both in terms of absolute amount as well as space and time. A second conclusion is that this method provides a strong rationale for why relying solely on a Fire Radiative Power approach may not be appropriate, especially in a cloud-covered region such as Southeast Asia. Finally, the limitations of the use of multiple-sensors and this approach in general are detailed by looking more in-depth at the massive biomass-burning episode in June of 2013 that occurred in Southeast Asia.
Hallett, Paul; Stobart, Ron; Valentine, Tracy; George, Timothy; Morris, Nathan; Newton, Adrian; McKenzie, Blair
2014-05-01
When plant breeders develop modern cereal varieties for the sustainable intensification of agriculture, insufficient thought is given to the impact of tillage on soil physical conditions for crop production. In earlier work, we demonstrated that barley varieties that perform best in ploughed soil (the approach traditionally used for breeding trials) were not the same as those performing best under shallow non-inversion or zero-tillage. We also found that the Quantitative Trait Loci (QTL) associated with improved phosphorus uptake, and hence useful for marker assisted breeding, were not robust between different tillage regimes. The impact of the soil environment had greater impact than the genetics in GxE interactions. It is obvious that soil tillage should be considered when breeding the next generation of crops. Tillage may also have important impacts on carbon storage, but we found that despite greater soil carbon at shallow depths under non-inversion tillage, the carbon stored throughout the soil profile was not affected by tillage. Studies on soil tillage impacts to crop productivity and soil quality are often performed in one season, on single sites that have had insufficient time to develop. Our current research explores multiple sites, on different soils, with temporal measurements of soil physical conditions under contrasting tillage regimes. We use the oldest established contemporary tillage experiments in the United Kingdom, with all sites sharing ploughed and shallow (7cm) non-inversion tillage treatments. In eastern Scotland (Mid Pilmore), the site also has zero tillage and deep ploughing (40 cm) treatments, and was established 11 years ago. In east England there are two sites, both also having a deep non-inversion tillage treatment, and they were established 6 (New Farm Systems) and 8 (STAR) years ago. We measure a range of crop and soil properties at sowing, one month after sowing and post-harvest, including rapid lab based assays that allow high
Near Real-Time Dissemination of Geo-Referenced Imagery by an Enterprise Server
National Research Council Canada - National Science Library
Brown, Alison; Gilbert, Chris; Holland, Heather; Lu, Yan
2006-01-01
.... The payload is connected through a data link to a ground-based server that can process the georegistered data in near-real-time using our GeoReferenced Information Manager (GRIM) Enterprise Server...
Dietary adaptation of FADS genes in Europe varied across time and geography
Ye, Kaixiong; Gao, Feng; Wang, David; Bar-Yosef, Ofer; Keinan, Alon
2017-01-01
Fatty acid desaturase (FADS) genes encode rate-limiting enzymes for the biosynthesis of omega-6 and omega-3 long chain polyunsaturated fatty acids (LCPUFAs). This biosynthesis is essential for individuals subsisting on LCPUFAs-poor diets (e.g. plant-based). Positive selection on FADS genes has been reported in multiple populations, but its presence and pattern in Europeans remain elusive. Here, using ancient and modern DNA, we demonstrate that positive selection acted on the same FADS variants both before and after the advent of farming in Europe, but on opposite (i.e. alternative) alleles. Selection in recent farmers also varied geographically, with the strongest signal in Southern Europe. These varying selection patterns concur with anthropological evidence of varying diets, and with the association of farming-adaptive alleles with higher FADS1 expression and thus enhanced LCPUFAs biosynthesis. Genome-wide association studies reveal that farming-adaptive alleles not only increase LCPUFAs, but also affect other lipid levels and protect against several inflammatory diseases. PMID:29094686
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.
The Investigation of EM Scattering from the Time-Varying Overturning Wave Crest Model by the IEM
Directory of Open Access Journals (Sweden)
Xiao Meng
2016-01-01
Full Text Available Investigation of the electromagnetic (EM scattering of time-varying overturning wave crests is a worthwhile endeavor. Overturning wave crest is one of the reasons of sea spike generation, which increases the probability of false radar alarms and reduces the performance of multitarget detection in the environment. A three-dimensional (3D time-varying overturning wave crest model is presented in this paper; this 3D model is an improvement of the traditional two-dimensional (2D time-varying overturning wave crest model. The integral equation method (IEM was employed to investigate backward scattering radar cross sections (RCS at various incident angles of the 3D overturning wave crest model. The super phenomenon, where the intensity of horizontal polarization scattering is greater than that of vertical polarization scattering, is an important feature of sea spikes. Simulation results demonstrate that super phenomena may occur in some time samples as variations in the overturning wave crest.
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)
Directory of Open Access Journals (Sweden)
Chien-Yu Lu
2009-01-01
Full Text Available This paper examines a passivity analysis for a class of discrete-time recurrent neural networks (DRNNs with norm-bounded time-varying parameter uncertainties and interval time-varying delay. The activation functions are assumed to be globally Lipschitz continuous. Based on an appropriate type of Lyapunov functional, sufficient passivity conditions for the DRNNs are derived in terms of a family of linear matrix inequalities (LMIs. Two numerical examples are given to illustrate the effectiveness and applicability.
Schmidt, M.; Lucas, R.; Bunting, P.; Verbesselt, J.; Armston, J.
2015-01-01
High spatio-temporal resolution optical remote sensing data provide unprecedented opportunities to monitor and detect forest disturbance and loss. To demonstrate this potential, a 12-year time series (2000 to 2011) with an 8-day interval of a 30 m spatial resolution data was generated by the use of
Effects of time-varying β in SNLS3 on constraining interacting dark energy models
International Nuclear Information System (INIS)
Wang, Shuang; Wang, Yong-Zhen; Geng, Jia-Jia; Zhang, Xin
2014-01-01
It has been found that, for the Supernova Legacy Survey three-year (SNLS3) data, there is strong evidence for the redshift evolution of the color-luminosity parameter β. In this paper, adopting the w-cold-dark-matter (wCDM) model and considering its interacting extensions (with three kinds of interaction between dark sectors), we explore the evolution of β and its effects on parameter estimation. In addition to the SNLS3 data, we also use the latest Planck distance priors data, the galaxy clustering data extracted from sloan digital sky survey data release 7 and baryon oscillation spectroscopic survey, as well as the direct measurement of Hubble constant H 0 from the Hubble Space Telescope observation. We find that, for all the interacting dark energy (IDE) models, adding a parameter of β can reduce χ 2 by ∝34, indicating that a constant β is ruled out at 5.8σ confidence level. Furthermore, it is found that varying β can significantly change the fitting results of various cosmological parameters: for all the dark energy models considered in this paper, varying β yields a larger fractional CDM densities Ω c0 and a larger equation of state w; on the other side, varying β yields a smaller reduced Hubble constant h for the wCDM model, but it has no impact on h for the three IDE models. This implies that there is a degeneracy between h and coupling parameter γ. Our work shows that the evolution of β is insensitive to the interaction between dark sectors, and then highlights the importance of considering β's evolution in the cosmology fits. (orig.)
Dynamics modeling for sugar cane sucrose estimation using time series satellite imagery
Zhao, Yu; Justina, Diego Della; Kazama, Yoriko; Rocha, Jansle Vieira; Graziano, Paulo Sergio; Lamparelli, Rubens Augusto Camargo
2016-10-01
Sugarcane, as one of the most mainstay crop in Brazil, plays an essential role in ethanol production. To monitor sugarcane crop growth and predict sugarcane sucrose content, remote sensing technology plays an essential role while accurate and timely crop growth information is significant, in particularly for large scale farming. We focused on the issues of sugarcane sucrose content estimation using time-series satellite image. Firstly, we calculated the spectral features and vegetation indices to make them be correspondence to the sucrose accumulation biological mechanism. Secondly, we improved the statistical regression model considering more other factors. The evaluation was performed and we got precision of 90% which is about 20% higher than the conventional method. The validation results showed that prediction accuracy using our sugarcane growth modeling and improved mix model is satisfied.
Importance of neutral processes varies in time and space: Evidence from dryland stream ecosystems.
Directory of Open Access Journals (Sweden)
Xiaoli Dong
Full Text Available Many ecosystems experience strong temporal variability in environmental conditions; yet, a clear picture of how niche and neutral processes operate to determine community assembly in temporally variable systems remains elusive. In this study, we constructed neutral metacommunity models to assess the relative importance of neutral processes in a spatially and temporally variable ecosystem. We analyzed macroinvertebrate community data spanning multiple seasons and years from 20 sites in a Sonoran Desert river network in Arizona. The model goodness-of-fit was used to infer the importance of neutral processes. Averaging over eight stream flow conditions across three years, we found that neutral processes were more important in perennial streams than in non-perennial streams (intermittent and ephemeral streams. Averaging across perennial and non-perennial streams, we found that neutral processes were more important during very high flow and in low flow periods; whereas, at very low flows, the relative importance of neutral processes varied greatly. These findings were robust to the choice of model parameter values. Our study suggested that the net effect of disturbance on the relative importance of niche and neutral processes in community assembly varies non-monotonically with the severity of disturbance. In contrast to the prevailing view that disturbance promotes niche processes, we found that neutral processes could become more important when the severity of disturbance is beyond a certain threshold such that all organisms are adversely affected regardless of their biological traits and strategies.
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.
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.
Hu, Xie; Wang, Teng; Pierson, Thomas C.; Lu, Zhong; Kim, Jin-Woo; Cecere, Thomas H.
2016-01-01
Detection of slow or limited landslide movement within broad areas of forested terrain has long been problematic, particularly for the Cascade landslide complex (Washington) located along the Columbia River Gorge. Although parts of the landslide complex have been found reactivated in recent years, the timing and magnitude of motion have not been systematically monitored or interpreted. Here we apply novel time-series strategies to study the spatial distribution and temporal behavior of the landslide movement between 2007 and 2011 using InSAR images from two overlapping L-band ALOS PALSAR-1 satellite tracks. Our results show that the reactivated part has moved approximately 700 mm downslope during the 4-year observation period, while other parts of the landslide complex have generally remained stable. However, we also detect about 300 mm of seasonal downslope creep in a terrain block upslope of the Cascade landslide complex—terrain previously thought to be stable. The temporal oscillation of the seasonal movement can be correlated with precipitation, implying that seasonal movement here is hydrology-driven. The seasonal movement also has a frequency similar to GPS-derived regional ground oscillations due to mass loading by stored rainfall and subsequent rebound but with much smaller magnitude, suggesting different hydrological loading effects. From the time-series amplitude information on terrain upslope of the headscarp, we also re-evaluate the incipient motion related to the 2008 Greenleaf Basin rock avalanche, not previously recognized by traditional SAR/InSAR methods. The approach used in this study can be used to identify active landslides in forested terrain, to track the seasonal movement of landslides, and to identify previously unknown landslide hazards.
Federal Laboratory Consortium — The Imagery Data Base Facility supports AFRL and other government organizations by providing imagery interpretation and analysis to users for data selection, imagery...
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
New results on stability analysis of neural networks with time-varying delays
Energy Technology Data Exchange (ETDEWEB)
Hua Changchun [Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004 (China)]. E-mail: cch@ysu.edu.cn; Long Chengnian [Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004 (China); Guan Xinping [Institute of Electrical Engineering, Yanshan University, Qinhuangdao 066004 (China)
2006-04-03
In this Letter the time delay dependent stability problem is investigated for a class of time delay neural networks. By constructing novel Lyapunov Krasovskii functional, we propose the new stability results for time delay neural network. The sufficient conditions obtained in this Letter are looser than those in the former literature. Specially, our results include the time delay independent results obtained in some existing literature. The stability conditions are all in the form of linear matrix inequalities (LMIs), which can be computed and optimized easily. Finally, numerical examples are given to show the superiority of the main results.
Dynamics of a physiologically structured population in a time-varying environment
DEFF Research Database (Denmark)
Heilmann, Irene Louise Torpe; Starke, Jens; Andersen, Ken Haste
2016-01-01
Physiologically structured population models have become a valuable tool to model the dynamics of populations. In a stationary environment such models can exhibit equilibrium solutions as well as periodic solutions. However, for many organisms the environment is not stationary, but varies more...... or less regularly. In order to understand the interaction between an external environmental forcing and the internal dynamics in a population, we examine the response of a physiologically structured population model to a periodic variation in the food resource. We explore the addition of forcing in two...... cases: (A) where the population dynamics is in equilibrium in a stationary environment, and (B) where the population dynamics exhibits a periodic solution in a stationary environment. When forcing is applied in case A, the solutions are mainly periodic. In case B the forcing signal interacts...
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.
Near real time detection of deforestation in the Brazilian Amazon using MODIS imagery
Directory of Open Access Journals (Sweden)
Egídio Arai
2007-06-01
Full Text Available The objective of this paper is to provide near real time information about deforestation detection (DETER in the entire Brazilian Amazon using MODIS high temporal resolution images. It is part of the operational deforestation monitoring project to estimate the annual deforestation rate in the Brazilian Amazon (PRODES. A rapid deforestation detection method was designed to support land use policies in this region. In order to evaluate the proposed method a test site was selected covering a Landsat ETM+ scene (227/68 located in Mato Grosso State. For this purpose a multitemporal series of MODIS surface reflectance images (MOD09 and the corresponding ETM+ images from June to October 2002 were analyzed. It was found that small deforested areas (lower than 15 ha were detected by MODIS images with lower accuracy when compared with ETM+ images. As the deforested areas increase MODIS and ETM+ results tend to converge. This procedure showed to be adequate to operationally detect and monitor deforested areas and has been used since 2004 as part of a government plan to control the Amazon deforestation.
Near real time detection of deforestation in the Brazilian Amazon using MODIS imagery
Directory of Open Access Journals (Sweden)
Maurício A. Moreira
2006-08-01
Full Text Available The objective of this paper is to provide near real time information about deforestation detection (DETER in the entire Brazilian Amazon using MODIS high temporal resolution images. It is part of the operational deforestation monitoring project to estimate the annual deforestation rate in the Brazilian Amazon (PRODES. A rapid deforestation detection method was designed to support land use policies in this region. In order to evaluate the proposed method a test site was selected covering a Landsat ETM+ scene (227/68 located in Mato Grosso State. For this purpose a multitemporal series of MODIS surface reflectance images (MOD09 and the corresponding ETM+ images from June to October 2002 were analyzed. It was found that small deforested areas (lower than 15 ha were detected by MODIS images with lower accuracy when compared with ETM+ images. As the deforested areas increase MODIS and ETM+ results tend to converge. This procedure showed to be adequate to operationally detect and monitor deforested areas and has been used since 2004 as part of a government plan to control the Amazon deforestation.
Gleason, C. J.; Smith, L. C.; Finnegan, D. C.; LeWinter, A. L.; Pitcher, L. H.; Chu, V. W.
2015-06-01
River systems in remote environments are often challenging to monitor and understand where traditional gauging apparatus are difficult to install or where safety concerns prohibit field measurements. In such cases, remote sensing, especially terrestrial time-lapse imaging platforms, offer a means to better understand these fluvial systems. One such environment is found at the proglacial Isortoq River in southwestern Greenland, a river with a constantly shifting floodplain and remote Arctic location that make gauging and in situ measurements all but impossible. In order to derive relevant hydraulic parameters for this river, two true color (RGB) cameras were installed in July 2011, and these cameras collected over 10 000 half hourly time-lapse images of the river by September of 2012. Existing approaches for extracting hydraulic parameters from RGB imagery require manual or supervised classification of images into water and non-water areas, a task that was impractical for the volume of data in this study. As such, automated image filters were developed that removed images with environmental obstacles (e.g., shadows, sun glint, snow) from the processing stream. Further image filtering was accomplished via a novel automated histogram similarity filtering process. This similarity filtering allowed successful (mean accuracy 79.6 %) supervised classification of filtered images from training data collected from just 10 % of those images. Effective width, a hydraulic parameter highly correlated with discharge in braided rivers, was extracted from these classified images, producing a hydrograph proxy for the Isortoq River between 2011 and 2012. This hydrograph proxy shows agreement with historic flooding observed in other parts of Greenland in July 2012 and offers promise that the imaging platform and processing methodology presented here will be useful for future monitoring studies of remote rivers.
Gleason, C. J.; Smith, L. C.; Finnegan, D. C.; LeWinter, A. L.; Pitcher, L. H.; Chu, V. W.
2015-01-01
River systems in remote environments are often challenging to monitor and understand where traditional gauging apparatus are difficult to install or where safety concerns prohibit field measurements. In such cases, remote sensing, especially terrestrial time lapse imaging platforms, offer a means to better understand these fluvial systems. One such environment is found at the proglacial Isortoq River in southwest Greenland, a river with a constantly shifting floodplain and remote Arctic location that make gauging and in situ measurements all but impossible. In order to derive relevant hydraulic parameters for this river, two RGB cameras were installed in July of 2011, and these cameras collected over 10 000 half hourly time-lapse images of the river by September of 2012. Existing approaches for extracting hydraulic parameters from RGB imagery require manual or supervised classification of images into water and non-water areas, a task that was impractical for the volume of data in this study. As such, automated image filters were developed that removed images with environmental obstacles (e.g. shadows, sun glint, snow) from the processing stream. Further image filtering was accomplished via a novel automated histogram similarity filtering process. This similarity filtering allowed successful (mean accuracy 79.6%) supervised classification of filtered images from training data collected from just 10% of those images. Effective width, a hydraulic parameter highly correlated with discharge in braided rivers, was extracted from these classified images, producing a hydrograph proxy for the Isortoq River between 2011 and 2012. This hydrograph proxy shows agreement with historic flooding observed in other parts of Greenland in July 2012 and offers promise that the imaging platform and processing methodology presented here will be useful for future monitoring studies of remote rivers.
Xie, Yanhua; Weng, Qihao
2017-06-01
Accurate, up-to-date, and consistent information of urban extents is vital for numerous applications central to urban planning, ecosystem management, and environmental assessment and monitoring. However, current large-scale urban extent products are not uniform with respect to definition, spatial resolution, temporal frequency, and thematic representation. This study aimed to enhance, spatiotemporally, time-series DMSP/OLS nighttime light (NTL) data for detecting large-scale urban changes. The enhanced NTL time series from 1992 to 2013 were firstly generated by implementing global inter-calibration, vegetation-based spatial adjustment, and urban archetype-based temporal modification. The dataset was then used for updating and backdating urban changes for the contiguous U.S.A. (CONUS) and China by using the Object-based Urban Thresholding method (i.e., NTL-OUT method, Xie and Weng, 2016b). The results showed that the updated urban extents were reasonably accurate, with city-scale RMSE (root mean square error) of 27 km2 and Kappa of 0.65 for CONUS, and 55 km2 and 0.59 for China, respectively. The backdated urban extents yielded similar accuracy, with RMSE of 23 km2 and Kappa of 0.63 in CONUS, while 60 km2 and 0.60 in China. The accuracy assessment further revealed that the spatial enhancement greatly improved the accuracy of urban updating and backdating by significantly reducing RMSE and slightly increasing Kappa values. The temporal enhancement also reduced RMSE, and improved the spatial consistency between estimated and reference urban extents. Although the utilization of enhanced NTL data successfully detected urban size change, relatively low locational accuracy of the detected urban changes was observed. It is suggested that the proposed methodology would be more effective for updating and backdating global urban maps if further fusion of NTL data with higher spatial resolution imagery was implemented.
Routing of radioactive shipments in networks with time-varying costs and curfews
International Nuclear Information System (INIS)
Bowler, L.A.; Mahmassani, H.S.
1998-09-01
This research examines routing of radioactive shipments in highway networks with time-dependent travel times and population densities. A time-dependent least-cost path (TDLCP) algorithm that uses a label-correcting approach is adapted to include curfews and waiting at nodes. A method is developed to estimate time-dependent population densities, which are required to estimate risk associated with the use of a particular highway link at a particular time. The TDLCP algorithm is implemented for example networks and used to examine policy questions related to radioactive shipments. It is observed that when only Interstate highway facilities are used to transport these materials, a shipment must go through many cities and has difficulty avoiding all of them during their rush hour periods. Decreases in risk, increased departure time flexibility, and modest increases in travel times are observed when primary and/or secondary roads are included in the network. Based on the results of the example implementation, the suitability of the TDLCP algorithm for strategic nuclear material and general radioactive material shipments is demonstrated
Routing of radioactive shipments in networks with time-varying costs and curfews
Energy Technology Data Exchange (ETDEWEB)
Bowler, L.A.; Mahmassani, H.S. [Univ. of Texas, Austin, TX (United States). Dept. of Civil Engineering
1998-09-01
This research examines routing of radioactive shipments in highway networks with time-dependent travel times and population densities. A time-dependent least-cost path (TDLCP) algorithm that uses a label-correcting approach is adapted to include curfews and waiting at nodes. A method is developed to estimate time-dependent population densities, which are required to estimate risk associated with the use of a particular highway link at a particular time. The TDLCP algorithm is implemented for example networks and used to examine policy questions related to radioactive shipments. It is observed that when only Interstate highway facilities are used to transport these materials, a shipment must go through many cities and has difficulty avoiding all of them during their rush hour periods. Decreases in risk, increased departure time flexibility, and modest increases in travel times are observed when primary and/or secondary roads are included in the network. Based on the results of the example implementation, the suitability of the TDLCP algorithm for strategic nuclear material and general radioactive material shipments is demonstrated.
High-k shallow traps observed by charge pumping with varying discharging times
Energy Technology Data Exchange (ETDEWEB)
Ho, Szu-Han; Chen, Ching-En; Tseng, Tseung-Yuen [Department of Electronics Engineering, National Chiao Tung University, Hsinchu 300, Taiwan (China); Chang, Ting-Chang, E-mail: tcchang@mail.phys.nsysu.edu.tw [Department of Physics, National Sun Yat-Sen University, Kaohsiung 804, Taiwan (China); Advanced Optoelectronics Technology Center, National Cheng Kung University, Tainan, Taiwan (China); Lu, Ying-Hsin; Lo, Wen-Hung; Tsai, Jyun-Yu; Liu, Kuan-Ju [Department of Physics, National Sun Yat-Sen University, Kaohsiung 804, Taiwan (China); Wang, Bin-Wei; Cao, Xi-Xin [Department of Embedded System Engineering, Peking University, Beijing, P.R.China (China); Chen, Hua-Mao [Department of Photonics and Institute of Electro-Optical Engineering, National Chiao Tung University, Hsinchu, Taiwan (China); Cheng, Osbert; Huang, Cheng-Tung; Chen, Tsai-Fu [Device Department, United Microelectronics Corporation, Tainan Science Park, Taiwan (China)
2013-11-07
In this paper, we investigate the influence of falling time and base level time on high-k bulk shallow traps measured by charge pumping technique in n-channel metal-oxide-semiconductor field-effect transistors with HfO{sub 2}/metal gate stacks. N{sub T}-V{sub high} {sub level} characteristic curves with different duty ratios indicate that the electron detrapping time dominates the value of N{sub T} for extra contribution of I{sub cp} traps. N{sub T} is the number of traps, and I{sub cp} is charge pumping current. By fitting discharge formula at different temperatures, the results show that extra contribution of I{sub cp} traps at high voltage are in fact high-k bulk shallow traps. This is also verified through a comparison of different interlayer thicknesses and different Ti{sub x}N{sub 1−x} metal gate concentrations. Next, N{sub T}-V{sub high} {sub level} characteristic curves with different falling times (t{sub falling} {sub time}) and base level times (t{sub base} {sub level}) show that extra contribution of I{sub cp} traps decrease with an increase in t{sub falling} {sub time}. By fitting discharge formula for different t{sub falling} {sub time}, the results show that electrons trapped in high-k bulk shallow traps first discharge to the channel and then to source and drain during t{sub falling} {sub time}. This current cannot be measured by the charge pumping technique. Subsequent measurements of N{sub T} by charge pumping technique at t{sub base} {sub level} reveal a remainder of electrons trapped in high-k bulk shallow traps.
Implications of cosmic strings with time-varying tension on the CMB and large scale structure
International Nuclear Information System (INIS)
Ichikawa, Kazuhide; Takahashi, Tomo; Yamaguchi, Masahide
2006-01-01
We investigate cosmological evolution and implications of cosmic strings with time-dependent tension. We derive basic equations of time development of the correlation length and the velocity of such strings, based on the one-scale model. Then, we find that, in the case where the tension depends on some power of the cosmic time, cosmic strings with time-dependent tension goes into the scaling solution if the power is lower than a critical value. We also discuss cosmic microwave background anisotropy and matter power spectra produced by these strings. The constraints on their tensions from the Wilkinson microwave anisotropy probe (WMAP) 3 yr data and Sloan digital sky survey (SDSS) data are also given
Relaxation of the vibrational distribution function in N2 time varying discharges
International Nuclear Information System (INIS)
Capitelli, M.; Gorse, C.; Ricard, A.
1981-01-01
Relaxation of the electron and vibrational distribution functions have been calculated in function of residence time in nitrogen electrical discharges and post-discharges. In the discharge the vibrational temperature get bigger with the residence time for t -2 s. In the post-discharge the vibrational distribution is evolving in such a manner that the high levels are overpopulated as the low vibrational level population is dropping
Local regularity for time-dependent tug-of-war games with varying probabilities
Parviainen, Mikko; Ruosteenoja, Eero
2016-07-01
We study local regularity properties of value functions of time-dependent tug-of-war games. For games with constant probabilities we get local Lipschitz continuity. For more general games with probabilities depending on space and time we obtain Hölder and Harnack estimates. The games have a connection to the normalized p (x , t)-parabolic equation ut = Δu + (p (x , t) - 2) Δ∞N u.
WBC reduction filtration efficacy performed at varying time intervals post-collection.
Hinojosa, Ricardo; Bryant, Barbara J
2011-12-01
A multisite blood center experienced unacceptable post-leukoreduction filtration white blood cell (WBC) counts at a few centers. Since prefiltration storage time and temperature were suspect, whole blood (WB) units were stored in transport shippers for at least 2 hours, cooling toward 1-6 ° C, before filtration. This study compared the effect of storage times in transport shippers on the residual WBC counts of leukoreduced units. Collection and filtration of WB units were accomplished with the use of the Fenwal Express System with Integral Sepacell RZ-2000 WB Leukocyte Reduction Filter. Units were collected and placed in transport shippers containing ice. Leukoreduction filtration was performed at designated intervals post-collection. Acceptable leukoreduction was defined as < 5 × 10(6) residual WBC. Fifty donor units were selected randomly over 3 months. Units were held in transport shippers, and WBC reduction was performed at designated post-collection intervals. Storage times ranged from 28 to 458 minutes. All residual WBC counts were acceptable. Storage time of WB units in transport shippers did not play a role in the efficacy of the leukoreduction. This study demonstrated the 2-hour storage time before leukoreduction filtration could be eliminated resulting in time savings and increased efficacy in the component production laboratory. © 2011 American Association of Blood Banks.
Theory of electromagnetic cyclotron wave growth in a time-varying magnetoplasma
International Nuclear Information System (INIS)
Gail, W.B.
1990-01-01
The time-dependent growth rate for parallel propagating electromagnetic cyclotron waves is derived for a magnetoplasma which is characterized by a time dependent compressional perturbation superimposed on an equilibrium configuration. Such perturbations are commonly observed in the Earth's magnetosphere as a consequence of resonant field line oscillations, solar-wind disturbances, and other phenomena. The time dependencies of the magnetic field, thermal plasma density, energetic particle distribution function, and resonance condition are first related through a single dimensionless time parameter b(t) using the ideal MHD assumption. For cases in which the particle distribution can be described by F(α, E) = f(E)sin a(E) α, the time dependent wave growth rate is then given by γ≅ γ 0 (1 + Λ) where γ 0 is the equilibrium growth rate and Λ(b) is a function of the equilibrium parameters and the time parameter b. The term |Λ| is generally small compared to 1, and the effect is a small modulation of the equilibrium growth rate by Λ. If the particle distribution is locally near marginal stability, however, |Λ| is large compared to 1, and the growth rate modulation can be much larger than for a distribution which is not near marginal stability. The results suggest that particle populations which are near marginal stability may be strongly influenced by perturbations in the magnetic field and plasma. Marginally stable distributions may thus play an important role in magnetospheric dynamics as well as determination of radiation belt characteristics
Monitoring Population Evolution in China Using Time-Series DMSP/OLS Nightlight Imagery
Directory of Open Access Journals (Sweden)
Sisi Yu
2018-01-01
Full Text Available Accurate and detailed monitoring of population distribution and evolution is of great significance in formulating a population planning strategy in China. The Defense Meteorological Satellite Program’s Operational Linescan System (DMSP/OLS nighttime lights time-series (NLT image products offer a good opportunity for detecting the population distribution owing to its high correlation to human activities. However, their detection capability is greatly limited owing to a lack of in-flight calibration. At present, the synergistic use of systematically-corrected NLT products and population spatialization is rarely applied. This work proposed a methodology to improve the application precision and versatility of NLT products, explored a feasible approach to quantitatively spatialize the population to grid units of 1 km × 1 km , and revealed the spatio-temporal characteristics of population distribution from 2000 to 2010. Results indicated that, (1 after inter-calibration, geometric, incompatibility and discontinuity corrections, and adjustment based on vegetation information, the incompatibility and discontinuity of NTL products were successfully solved. Accordingly, detailed actual residential areas and luminance differences between the urban core and the peripheral regions could be obtained. (2 The population spatialization method could effectively acquire population information at per km 2 with high accuracy and exhibit more details in the evolution of population distribution. (3 Obvious differences in spatio-temporal characteristics existed in four economic regions, from the aspects of population distribution and dynamics, as well as population-weighted centroids. The eastern region was the most populous with the largest increased magnitude, followed by the central, northeastern, and western regions. The population-weighted centroids of the eastern, western, and northeastern regions moved along the southwest direction, while the population
Temnothorax rugatulus ant colonies consistently vary in nest structure across time and context.
Directory of Open Access Journals (Sweden)
Nicholas DiRienzo
Full Text Available A host of animals build architectural constructions. Such constructions frequently vary with environmental and individual/colony conditions, and their architecture directly influences behavior and fitness. The nests of ant colonies drive and enable many of their collective behaviors, and as such are part of their 'extended phenotype'. Since ant colonies have been recently shown to differ in behavior and life history strategy, we ask whether colonies differ in another trait: the architecture of the constructions they create. We allowed Temnothorax rugatulus rock ants, who create nests by building walls within narrow rock gaps, to repeatedly build nest walls in a fixed crevice but under two environmental conditions. We find that colonies consistently differ in their architecture across environments and over nest building events. Colony identity explained 12-40% of the variation in nest architecture, while colony properties and environmental conditions explained 5-20%, as indicated by the condition and marginal R2 values. When their nest boxes were covered, which produced higher humidity and lower airflow, colonies built thicker, longer, and heavier walls. Colonies also built more robust walls when they had more brood, suggesting a protective function of wall thickness. This is, to our knowledge, the first study to explicitly investigate the repeatability of nestbuilding behavior in a controlled environment. Our results suggest that colonies may face tradeoffs, perhaps between factors such as active vs. passive nest defense, and that selection may act on individual construction rules as a mechanisms to mediate colony-level behavior.
The time varying structure of a river plume: Observations with an autonomous glider.
Chant, R. J.; Glenn, S. M.; Gong, D.
2004-12-01
During the 2004 LaTTE (Lagrangian Transport and Transformation Experiment) pilot study we deployed a Slocum Autonomous glider on a 10-day mission to run repeated transects across the Hudson River Plume in the vicinity of Sandy Hook. The glider completed 13 cross-plume surveys during the mission with horizontal resolution of approximately 100 meters. Wind forcing was highly variable and fluctuated between upwelling and downwelling conditions at 1-2 day intervals. Tidal forcing decreased markedly from spring to neap tide conditions and river discharge averaged approximately 500 m3/s during the survey. The plume responded rapidly to the variable wind forcing. During upwelling conditions the plume thinned and extended over 30 km from shore, while during downwelling winds the plume thickened and was compressed at the shore. However, during both upwellling and downwelling conditions the plume remained detached from the bottom. The cross-sectional area of the plume also tended to vary with the wind forcing. However, a significant increase in the plume's area during the last half of the mission does not appear to be related to either wind forcing or river discharge. Instead, we suggest that the plumes structure could be impacted by spring neap variability which is known to control stratification and freshwater fluxes out of the Hudson River Estuary. This presentation will relate the structure of the plume to wind forcing, river flow and the spring/neap cycle.
A time-varying subjective quality model for mobile streaming videos with stalling events
Ghadiyaram, Deepti; Pan, Janice; Bovik, Alan C.
2015-09-01
Over-the-top mobile video streaming is invariably influenced by volatile network conditions which cause playback interruptions (stalling events), thereby impairing users' quality of experience (QoE). Developing models that can accurately predict users' QoE could enable the more efficient design of quality-control protocols for video streaming networks that reduce network operational costs while still delivering high-quality video content to the customers. Existing objective models that predict QoE are based on global video features, such as the number of stall events and their lengths, and are trained and validated on a small pool of ad hoc video datasets, most of which are not publicly available. The model we propose in this work goes beyond previous models as it also accounts for the fundamental effect that a viewer's recent level of satisfaction or dissatisfaction has on their overall viewing experience. In other words, the proposed model accounts for and adapts to the recency, or hysteresis effect caused by a stall event in addition to accounting for the lengths, frequency of occurrence, and the positions of stall events - factors that interact in a complex way to affect a user's QoE. On the recently introduced LIVE-Avvasi Mobile Video Database, which consists of 180 distorted videos of varied content that are afflicted solely with over 25 unique realistic stalling events, we trained and validated our model to accurately predict the QoE, attaining standout QoE prediction performance.
Vina Fitriana; Rujito Agus Suwignyo; Siti Fauziah
2017-01-01
This study aimed to obtain data about far-reaching changes on the total area of mangrove at Air Telang Beach Protected Forest through the interpretation of Landsat 7 imagery data using open source software (Ilwis 2000) in years 2000, 2003, 2006, 2009 and 2012. In the first phase, mangrove identification was conducted through cropped imagery data based on the research area which is path 124 raw 62 using RGB543 composite band. Then, mangrove and non-mangrove area are separated using unsupervise...
Grammer, Jennie K; Purtell, Kelly M; Coffman, Jennifer L; Ornstein, Peter A
2011-01-01
Although much is known about the development of memory strategies and metamemory during childhood, evidence for linkages between these memory skills, either concurrently or over time, has been limited. Drawing from a longitudinal investigation of the development of memory, repeated assessments of children's (N=107) strategy use and declarative metamemory were made to examine the development of these skills and the relations between them over time. Latent curve models were used first to estimate the trajectories of children's strategy use and metamemory and then to examine predictors of children's performance in each of these domains. Children's metamemory at the beginning of Grade 1 was linked to child- and home-level factors, whereas the development of both skills was related to maternal education level. Additional modeling of the longitudinal relations between strategic sorting and metacognitive knowledge indicated that metamemory at earlier time points was predictive of subsequent strategy use. Copyright © 2010 Elsevier Inc. All rights reserved.
Optimization of a simplified automobile finite element model using time varying injury metrics.
Gaewsky, James P; Danelson, Kerry A; Weaver, Caitlin M; Stitzel, Joel D
2014-01-01
In 2011, frontal crashes resulted in 55% of passenger car injuries with 10,277 fatalities and 866,000 injuries in the United States. To better understand frontal crash injury mechanisms, human body finite element models (FEMs) can be used to reconstruct Crash Injury Research and Engineering Network (CIREN) cases. A limitation of this method is the paucity of vehicle FEMs; therefore, we developed a functionally equivalent simplified vehicle model. The New Car Assessment Program (NCAP) data for our selected vehicle was from a frontal collision with Hybrid III (H3) Anthropomorphic Test Device (ATD) occupant. From NCAP test reports, the vehicle geometry was created and the H3 ATD was positioned. The material and component properties optimized using a variation study process were: steering column shear bolt fracture force and stroke resistance, seatbelt pretensioner force, frontal and knee bolster airbag stiffness, and belt friction through the D-ring. These parameters were varied using three successive Latin Hypercube Designs of Experiments with 130-200 simulations each. The H3 injury response was compared to the reported NCAP frontal test results for the head, chest and pelvis accelerations, and seat belt and femur forces. The phase, magnitude, and comprehensive error factors, from a Sprague and Geers analysis were calculated for each injury metric and then combined to determine the simulations with the best match to the crash test. The Sprague and Geers analyses typically yield error factors ranging from 0 to 1 with lower scores being more optimized. The total body injury response error factor for the most optimized simulation from each round of the variation study decreased from 0.466 to 0.395 to 0.360. This procedure to optimize vehicle FEMs is a valuable tool to conduct future CIREN case reconstructions in a variety of vehicles.
Individualistic and time-varying tree-ring growth to climate sensitivity.
Directory of Open Access Journals (Sweden)
Marco Carrer
Full Text Available The development of dendrochronological time series in order to analyze climate-growth relationships usually involves first a rigorous selection of trees and then the computation of the mean tree-growth measurement series. This study suggests a change in the perspective, passing from an analysis of climate-growth relationships that typically focuses on the mean response of a species to investigating the whole range of individual responses among sample trees. Results highlight that this new approach, tested on a larch and stone pine tree-ring dataset, outperforms, in terms of information obtained, the classical one, with significant improvements regarding the strength, distribution and time-variability of the individual tree-ring growth response to climate. Moreover, a significant change over time of the tree sensitivity to climatic variability has been detected. Accordingly, the best-responder trees at any one time may not always have been the best-responders and may not continue to be so. With minor adjustments to current dendroecological protocol and adopting an individualistic approach, we can improve the quality and reliability of the ecological inferences derived from the climate-growth relationships.
Time-Varying Degree of Wage Indexation and the New Keynesian Wage Phillips Curve
J.A. Attey (Jonathan)
2016-01-01
textabstractCost-of-Living-Adjustment (COLA) coverage figures suggest a time variation in the degree of wage indexation. In spite of this observation, most current literature conveniently assume a constant degree of indexation as this variable is not directly observable. This study intends to
Effect of Varying Toasting Time of Soybean Meal on Organ and ...
African Journals Online (AJOL)
Ninety Anak broiler chicks were used at four weeks of age in a 28 day feeding trial to assess the effect of toasting time of soybean on organ and carcass characteristics of finisher broiler birds. The birds were assigned to five dietary treatments containing raw soybean as control and full fat soybean toasted for 5, 10, 15 and 20 ...
Early marketing matters : A time-varying parameter approach to persistence modeling
Osinga, E.C.; Leeflang, P.S.H.; Wieringa, J.E.
Are persistent marketing effects most likely to appear right after the introduction of a product? The authors give an affirmative answer to this question by developing a model that explicitly reports how persistent and transient marketing effects evolve over time. The proposed model provides
Grammer, Jennie K.; Purtell, Kelly M.; Coffman, Jennifer L.; Ornstein, Peter A.
2011-01-01
Although much is known about the development of memory strategies and metamemory during childhood, evidence for linkages between these memory skills, either concurrently or over time, has been limited. Drawing from a longitudinal investigation of the development of memory, repeated assessments of children's (N = 107) strategy use and declarative…
Global stability analysis of Cohen-Grossberg neural networks with time varying delays
International Nuclear Information System (INIS)
Arik, Sabri; Orman, Zeynep
2005-01-01
This Letter presents some sufficient conditions for the existence, uniqueness and global asymptotic and exponential stability of the equilibrium point for Cohen-Grossberg neural networks with time delays. The results establish a relationship between the network parameters of the neural system independently of the delay parameters. The results are also compared with the previously reported results in the literature
Effects of varying feeding times on fertility and hatchability of broiler ...
African Journals Online (AJOL)
This study investigated the effects of feeding times on total egg production, fertility and hatchability of broiler chicken breeders in a tropical environment. The experiment was conducted using 240 Marshal Broiler breeder flocks for eight weeks between 40 to 48 weeks of age. The birds were randomly assigned to 3 treatment ...
Kalman filtering and smoothing for model-based signal extraction that depend on time-varying spectra
Koopman, S.J.; Wong, S.Y.
2011-01-01
We develop a flexible semi-parametric method for the introduction of time-varying parameters in a model-based signal extraction procedure. Dynamic model specifications for the parameters in the model are not required. We show that signal extraction based on Kalman filtering and smoothing can be made
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.
Suweken, G.; van Horssen, W.T.
2002-01-01
In this paper the weakly nonlinear, transversal vibrations of a conveyor belt will be considered. The belt is assumed to move with a low and time-varying speed. Using Kirchhoff's approach a single equation of motion will be derived from a coupled system of partial differential equations describing
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)
Active control of time-varying broadband noise and vibrations using a sliding-window Kalman filter
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
CSIR Research Space (South Africa)
Masina, BN
2011-07-01
Full Text Available damage study on diamond tools at varying laser heating time and temperature by Raman spectroscopy and SEM BN Masina1, BW Mwakikunga2, M Elayaperumal2, A Forbes1, and R Bodkin3 1CSIR National Laser Centre, PO BOX 395, Pretoria 0001, South Africa 2CSIR...
Shen, Bo; Wang, Zidong; Liu, Xiaohui
2011-01-01
In this paper, new synchronization and state estimation problems are considered for an array of coupled discrete time-varying stochastic complex networks over a finite horizon. A novel concept of bounded H(∞) synchronization is proposed to handle the time-varying nature of the complex networks. Such a concept captures the transient behavior of the time-varying complex network over a finite horizon, where the degree of bounded synchronization is quantified in terms of the H(∞)-norm. A general sector-like nonlinear function is employed to describe the nonlinearities existing in the network. By utilizing a time-varying real-valued function and the Kronecker product, criteria are established that ensure the bounded H(∞) synchronization in terms of a set of recursive linear matrix inequalities (RLMIs), where the RLMIs can be computed recursively by employing available MATLAB toolboxes. The bounded H(∞) state estimation problem is then studied for the same complex network, where the purpose is to design a state estimator to estimate the network states through available output measurements such that, over a finite horizon, the dynamics of the estimation error is guaranteed to be bounded with a given disturbance attenuation level. Again, an RLMI approach is developed for the state estimation problem. Finally, two simulation examples are exploited to show the effectiveness of the results derived in this paper.
Directory of Open Access Journals (Sweden)
Hui Zhou
2017-02-01
Full Text Available The “magnetic window” is considered a promising means to eliminate reentry communication blackout. However, the turbulence of plasma sheath results in phase jitter and amplitude turbulence of electromagnetic (EM wave and may influence the eliminating effect. Therefore, the effect of fluctuating property of reentry plasma sheath on EM wave propagation when a magnetic field is used for eliminating blackout is investigated. For this purpose, a time-varying electron density model, which includes both temporal variation and spatial turbulence, is proposed. Hybrid matrix method is also employed to investigate the interaction between time-varying magnetized plasma and EM wave. The EM wave transmission coefficients in time-varying magnetized and unmagnetized plasmas are likewise compared. Simulation results show that amplitude variation and phase jitter also exist on transmitted EM wave, and the turbulent deviation increases as the degree of plasma fluctuates. Meanwhile, the fluctuation of transmitted EM wave attenuates at low-frequency passband and increases at high-frequency passband with the increasing magnetic field. That is, comparing with unmagnetized time-varying plasma, the fluctuation effect can be mitigated by using a magnetic field when the EM wave frequency is at low-frequency passband. However, the mitigating effect can be influenced by the nonuniformity of magnetic field.
Husken, T.F.; Cruyff, M.J.L.F.; van der Heijden, P.G.M.
2017-01-01
The objective of capture-recapture analysis is to estimate the size of an elusive population, for which the zero-truncated Poisson model is a basic model. We extend this model to the more general recurrent events model to include cyclical eects and time-varying covariates. An application to police
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
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
Directory of Open Access Journals (Sweden)
Hong Zhang
2014-01-01
Full Text Available This paper is concerned with a nonautonomous fishing model with a time-varying delay. Under proper conditions, we employ a novel argument to establish a criterion on the global exponential stability of positive almost periodic solutions of the model with almost periodic coefficients and delays. Moreover, an example and its numerical simulation are given to illustrate the main results.
Douglass, Sara; Umaña-Taylor, Adriana J.
2016-01-01
Previous research has established that family ethnic socialization messages promote ethnic-racial identity (ERI) development, yet it is unknown whether these effects remain constant throughout adolescence. The current study examined the time-varying effects of family ethnic socialization on ERI exploration and resolution among Latino adolescents…
Varying plant density and harvest time to optimize cowpea leaf yield and nutrient content
Ohler, T. A.; Nielsen, S. S.; Mitchell, C. A.
1996-01-01
Plant density and harvest time were manipulated to optimize vegetative (foliar) productivity of cowpea [Vigna unguiculata (L.) Walp.] canopies for future dietary use in controlled ecological life-support systems as vegetables or salad greens. Productivity was measured as total shoot and edible dry weights (DW), edible yield rate [(EYR) grams DW per square meter per day], shoot harvest index [(SHI) grams DW per edible gram DW total shoot], and yield-efficiency rate [(YER) grams DW edible per square meter per day per grams DW nonedible]. Cowpeas were grown in a greenhouse for leaf-only harvest at 14, 28, 42, 56, 84, or 99 plants/m2 and were harvested 20, 30, 40, or 50 days after planting (DAP). Shoot and edible dry weights increased as plant density and time to harvest increased. A maximum of 1189 g shoot DW/m2 and 594 g edible DW/m2 were achieved at an estimated plant density of 85 plants/m2 and harvest 50 DAP. EYR also increased as plant density and time to harvest increased. An EYR of 11 g m-2 day-1 was predicted to occur at 86 plants/m2 and harvest 50 DAP. SHI and YER were not affected by plant density. However, the highest values of SHI (64%) and YER (1.3 g m-2 day-1 g-1) were attained when cowpeas were harvested 20 DAP. The average fat and ash contents [dry-weight basis (dwb)] of harvested leaves remained constant regardless of harvest time. Average protein content increased from 25% DW at 30 DAP to 45% DW at 50 DAP. Carbohydrate content declined from 50% DW at 30 DAP to 45% DW at 50 DAP. Total dietary fiber content (dwb) of the leaves increased from 19% to 26% as time to harvest increased from 20 to 50 days.
Optimal harvesting of fish stocks under a time-varying discount rate.
Duncan, Stephen; Hepburn, Cameron; Papachristodoulou, Antonis
2011-01-21
Optimal control theory has been extensively used to determine the optimal harvesting policy for renewable resources such as fish stocks. In such optimisations, it is common to maximise the discounted utility of harvesting over time, employing a constant time discount rate. However, evidence from human and animal behaviour suggests that we have evolved to employ discount rates which fall over time, often referred to as "hyperbolic discounting". This increases the weight on benefits in the distant future, which may appear to provide greater protection of resources for future generations, but also creates challenges of time-inconsistent plans. This paper examines harvesting plans when the discount rate declines over time. With a declining discount rate, the planner reduces stock levels in the early stages (when the discount rate is high) and intends to compensate by allowing the stock level to recover later (when the discount rate will be lower). Such a plan may be feasible and optimal, provided that the planner remains committed throughout. However, in practice there is a danger that such plans will be re-optimized and adjusted in the future. It is shown that repeatedly restarting the optimization can drive the stock level down to the point where the optimal policy is to harvest the stock to extinction. In short, a key contribution of this paper is to identify the surprising severity of the consequences flowing from incorporating a rather trivial, and widely prevalent, "non-rational" aspect of human behaviour into renewable resource management models. These ideas are related to the collapse of the Peruvian anchovy fishery in the 1970's. Copyright © 2010 Elsevier Ltd. All rights reserved.
Li, Shukai; Yang, Lixing; Gao, Ziyou; Li, Keping
2014-11-01
In this paper, the stabilization strategies of a general nonlinear car-following model with reaction-time delay of the drivers are investigated. The reaction-time delay of the driver is time varying and bounded. By using the Lyapunov stability theory, the sufficient condition for the existence of the state feedback control strategy for the stability of the car-following model is given in the form of linear matrix inequality, under which the traffic jam can be well suppressed with respect to the varying reaction-time delay. Moreover, by considering the external disturbance for the running cars, the robust state feedback control strategy is designed, which ensures robust stability and a smaller prescribed H∞ disturbance attenuation level for the traffic flow. Numerical examples are given to illustrate the effectiveness of the proposed methods. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.
DEFF Research Database (Denmark)
Kriegbaum, Margit; Christensen, Ulla; Andersen, Per Kragh
2013-01-01
Marriage is associated with lower risk of coronary heart disease, but it is unknown if the association depends on time since break-up with a partner. In this study we included both married and unmarried couples to study if the association between broken partnership (BP) and first time incident...
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
using a pseudo-value approach. For a grid of time points, the possibly unobserved binary event status is replaced by a jackknife pseudo-value based on the Aalen-Johansen method. We combine a stagewise regression technique with the pseudo-value approach to provide variable selection while allowing......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...... between covariates and the cumulative incidence of one of the events. With a suitable link function, direct regression models allow for a straightforward interpretation of covariate effects on the cumulative incidence. In practice, where data can be right-censored, these regression models are implemented...
International Nuclear Information System (INIS)
EI-Ahiad, N.M.; Lotfi, S.A.; Marzook, E.A.
2008-01-01
Today everyone in the society is exposed to different levels of electromagnetic radiations produced by most electric devices used in our daily life. Effects of 5 times exposure per week to 10 μT magnetic field (MF) 15,30 and 45 minutes for six weeks on behavioural changes, neurotransmitters and hematological parameter s were studied. The behavioural changes of rats, induced by exposure to MF,appeared as fast movement, aggressive response, more activity and less feeding. Long exposure time to MF leads to a significant decrease in body weight, epinephrine, Hb values and RBCs and WBCs counts. On the other hand, MF exposure results in insignificant changes in serum testosterone, platelets level and nor epinephrine. It could be concluded that exposure to magnetic fields may affect the brain neurotransmitters levels and some blood parameters
Time-varying extreme value dependence with application to leading European stock markets
Castro-Camilo, Daniela
2018-03-09
Extremal dependence between international stock markets is of particular interest in today’s global financial landscape. However, previous studies have shown this dependence is not necessarily stationary over time. We concern ourselves with modeling extreme value dependence when that dependence is changing over time, or other suitable covariate. Working within a framework of asymptotic dependence, we introduce a regression model for the angular density of a bivariate extreme value distribution that allows us to assess how extremal dependence evolves over a covariate. We apply the proposed model to assess the dynamics governing extremal dependence of some leading European stock markets over the last three decades, and find evidence of an increase in extremal dependence over recent years.
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.
Tracking of time-varying genomic regulatory networks with a LASSO-Kalman smoother
Khan, Jehandad; Bouaynaya, Nidhal; Fathallah-Shaykh, Hassan M
2014-01-01
It is widely accepted that cellular requirements and environmental conditions dictate the architecture of genetic regulatory networks. Nonetheless, the status quo in regulatory network modeling and analysis assumes an invariant network topology over time. In this paper, we refocus on a dynamic perspective of genetic networks, one that can uncover substantial topological changes in network structure during biological processes such as developmental growth. We propose a novel outlook on the inf...
2013-03-21
2008; Hoening 2002). Later, in 1952, Dr. Ranajit Ghosh discovered what is now known in the military as VX while conducting research into pesticides ...nutrient content utilized in land applications such as farming . The amount of solids that gets wasted is dependent on each facility’s solid retention time...to occur, the toxic OPs may follow disposed waste sludge where it may be applied as fertilizer in agricultural areas. Furthermore, should