Ying, Wenjun; Henriquez, Craig S.
2015-01-01
A both space and time adaptive algorithm is presented for simulating electrical wave propagation in the Purkinje system of the heart. The equations governing the distribution of electric potential over the system are solved in time with the method of lines. At each timestep, by an operator splitting technique, the space-dependent but linear diffusion part and the nonlinear but space-independent reactions part in the partial differential equations are integrated separately with implicit schemes, which have better stability and allow larger timesteps than explicit ones. The linear diffusion equation on each edge of the system is spatially discretized with the continuous piecewise linear finite element method. The adaptive algorithm can automatically recognize when and where the electrical wave starts to leave or enter the computational domain due to external current/voltage stimulation, self-excitation, or local change of membrane properties. Numerical examples demonstrating efficiency and accuracy of the adaptive algorithm are presented. PMID:26581455
NASA Astrophysics Data System (ADS)
von Sydow, Lina
2013-10-01
The discontinuous Galerkin method for time integration of the Black-Scholes partial differential equation for option pricing problems is studied and compared with more standard time-integrators. In space an adaptive finite difference discretization is employed. The results show that the dG method are in most cases at least comparable to standard time-integrators and in some cases superior to them. Together with adaptive spatial grids the suggested pricing method shows great qualities.
Data rate management and real time operation: recursive adaptive frame integration of limited data
NASA Astrophysics Data System (ADS)
Rafailov, Michael K.
2006-08-01
Recursive Limited Frame Integration was proposed as a way to improve frame integration performance and mitigate issues related to high data rate needed to support conventional frame integration. The technique uses two thresholds -one tuned for optimum probability of detection, the other to manage required false alarm rate, and places integration process between those thresholds. This configuration allows a non-linear integration process that, along with Signal-to-Noise Ratio (SNR) gain, provides system designers more capability where cost, weight, or power considerations limit system data rate, processing, or memory capability. However, Recursive Frame Integration Limited may have performance issues when single-frame SNR is really low. Recursive Adaptive Limited Frame Integration was proposed as a means to improve limited integration performance with really low single-frame SNR. It combines the benefits of nonlinear recursive limited frame integration and adaptive thresholds with a kind of conventional frame integration. Adding the third threshold may help in managing real time operations. In the paper the Recursive Frame Integration is presented in form of multiple parallel recursive integration. Such an approach can help not only in data rate management but in mitigation of low single frame SNR issue for Recursive Integration as well as in real time operations with frame integration.
Designing Adaptive Low-Dissipative High Order Schemes for Long-Time Integrations. Chapter 1
NASA Technical Reports Server (NTRS)
Yee, Helen C.; Sjoegreen, B.; Mansour, Nagi N. (Technical Monitor)
2001-01-01
A general framework for the design of adaptive low-dissipative high order schemes is presented. It encompasses a rather complete treatment of the numerical approach based on four integrated design criteria: (1) For stability considerations, condition the governing equations before the application of the appropriate numerical scheme whenever it is possible; (2) For consistency, compatible schemes that possess stability properties, including physical and numerical boundary condition treatments, similar to those of the discrete analogue of the continuum are preferred; (3) For the minimization of numerical dissipation contamination, efficient and adaptive numerical dissipation control to further improve nonlinear stability and accuracy should be used; and (4) For practical considerations, the numerical approach should be efficient and applicable to general geometries, and an efficient and reliable dynamic grid adaptation should be used if necessary. These design criteria are, in general, very useful to a wide spectrum of flow simulations. However, the demand on the overall numerical approach for nonlinear stability and accuracy is much more stringent for long-time integration of complex multiscale viscous shock/shear/turbulence/acoustics interactions and numerical combustion. Robust classical numerical methods for less complex flow physics are not suitable or practical for such applications. The present approach is designed expressly to address such flow problems, especially unsteady flows. The minimization of employing very fine grids to overcome the production of spurious numerical solutions and/or instability due to under-resolved grids is also sought. The incremental studies to illustrate the performance of the approach are summarized. Extensive testing and full implementation of the approach is forthcoming. The results shown so far are very encouraging.
Neuronal Spike Timing Adaptation Described with a Fractional Leaky Integrate-and-Fire Model
Teka, Wondimu; Marinov, Toma M.; Santamaria, Fidel
2014-01-01
The voltage trace of neuronal activities can follow multiple timescale dynamics that arise from correlated membrane conductances. Such processes can result in power-law behavior in which the membrane voltage cannot be characterized with a single time constant. The emergent effect of these membrane correlations is a non-Markovian process that can be modeled with a fractional derivative. A fractional derivative is a non-local process in which the value of the variable is determined by integrating a temporal weighted voltage trace, also called the memory trace. Here we developed and analyzed a fractional leaky integrate-and-fire model in which the exponent of the fractional derivative can vary from 0 to 1, with 1 representing the normal derivative. As the exponent of the fractional derivative decreases, the weights of the voltage trace increase. Thus, the value of the voltage is increasingly correlated with the trajectory of the voltage in the past. By varying only the fractional exponent, our model can reproduce upward and downward spike adaptations found experimentally in neocortical pyramidal cells and tectal neurons in vitro. The model also produces spikes with longer first-spike latency and high inter-spike variability with power-law distribution. We further analyze spike adaptation and the responses to noisy and oscillatory input. The fractional model generates reliable spike patterns in response to noisy input. Overall, the spiking activity of the fractional leaky integrate-and-fire model deviates from the spiking activity of the Markovian model and reflects the temporal accumulated intrinsic membrane dynamics that affect the response of the neuron to external stimulation. PMID:24675903
Adaptive neuro-fuzzy inference system for real-time monitoring of integrated-constructed wetlands.
Dzakpasu, Mawuli; Scholz, Miklas; McCarthy, Valerie; Jordan, Siobhán; Sani, Abdulkadir
2015-01-01
Monitoring large-scale treatment wetlands is costly and time-consuming, but required by regulators. Some analytical results are available only after 5 days or even longer. Thus, adaptive neuro-fuzzy inference system (ANFIS) models were developed to predict the effluent concentrations of 5-day biochemical oxygen demand (BOD5) and NH4-N from a full-scale integrated constructed wetland (ICW) treating domestic wastewater. The ANFIS models were developed and validated with a 4-year data set from the ICW system. Cost-effective, quicker and easier to measure variables were selected as the possible predictors based on their goodness of correlation with the outputs. A self-organizing neural network was applied to extract the most relevant input variables from all the possible input variables. Fuzzy subtractive clustering was used to identify the architecture of the ANFIS models and to optimize fuzzy rules, overall, improving the network performance. According to the findings, ANFIS could predict the effluent quality variation quite strongly. Effluent BOD5 and NH4-N concentrations were predicted relatively accurately by other effluent water quality parameters, which can be measured within a few hours. The simulated effluent BOD5 and NH4-N concentrations well fitted the measured concentrations, which was also supported by relatively low mean squared error. Thus, ANFIS can be useful for real-time monitoring and control of ICW systems. PMID:25607665
Accelerated adaptive integration method.
Kaus, Joseph W; Arrar, Mehrnoosh; McCammon, J Andrew
2014-05-15
Conformational changes that occur upon ligand binding may be too slow to observe on the time scales routinely accessible using molecular dynamics simulations. The adaptive integration method (AIM) leverages the notion that when a ligand is either fully coupled or decoupled, according to λ, barrier heights may change, making some conformational transitions more accessible at certain λ values. AIM adaptively changes the value of λ in a single simulation so that conformations sampled at one value of λ seed the conformational space sampled at another λ value. Adapting the value of λ throughout a simulation, however, does not resolve issues in sampling when barriers remain high regardless of the λ value. In this work, we introduce a new method, called Accelerated AIM (AcclAIM), in which the potential energy function is flattened at intermediate values of λ, promoting the exploration of conformational space as the ligand is decoupled from its receptor. We show, with both a simple model system (Bromocyclohexane) and the more complex biomolecule Thrombin, that AcclAIM is a promising approach to overcome high barriers in the calculation of free energies, without the need for any statistical reweighting or additional processors. PMID:24780083
Accelerated Adaptive Integration Method
2015-01-01
Conformational changes that occur upon ligand binding may be too slow to observe on the time scales routinely accessible using molecular dynamics simulations. The adaptive integration method (AIM) leverages the notion that when a ligand is either fully coupled or decoupled, according to λ, barrier heights may change, making some conformational transitions more accessible at certain λ values. AIM adaptively changes the value of λ in a single simulation so that conformations sampled at one value of λ seed the conformational space sampled at another λ value. Adapting the value of λ throughout a simulation, however, does not resolve issues in sampling when barriers remain high regardless of the λ value. In this work, we introduce a new method, called Accelerated AIM (AcclAIM), in which the potential energy function is flattened at intermediate values of λ, promoting the exploration of conformational space as the ligand is decoupled from its receptor. We show, with both a simple model system (Bromocyclohexane) and the more complex biomolecule Thrombin, that AcclAIM is a promising approach to overcome high barriers in the calculation of free energies, without the need for any statistical reweighting or additional processors. PMID:24780083
Continuous-time adaptive critics.
Hanselmann, Thomas; Noakes, Lyle; Zaknich, Anthony
2007-05-01
A continuous-time formulation of an adaptive critic design (ACD) is investigated. Connections to the discrete case are made, where backpropagation through time (BPTT) and real-time recurrent learning (RTRL) are prevalent. Practical benefits are that this framework fits in well with plant descriptions given by differential equations and that any standard integration routine with adaptive step-size does an adaptive sampling for free. A second-order actor adaptation using Newton's method is established for fast actor convergence for a general plant and critic. Also, a fast critic update for concurrent actor-critic training is introduced to immediately apply necessary adjustments of critic parameters induced by actor updates to keep the Bellman optimality correct to first-order approximation after actor changes. Thus, critic and actor updates may be performed at the same time until some substantial error build up in the Bellman optimality or temporal difference equation, when a traditional critic training needs to be performed and then another interval of concurrent actor-critic training may resume. PMID:17526332
Recursive adaptive frame integration limited
NASA Astrophysics Data System (ADS)
Rafailov, Michael K.
2006-05-01
Recursive Frame Integration Limited was proposed as a way to improve frame integration performance and mitigate issues related to high data rate needed for conventional frame integration. The technique applies two thresholds - one tuned for optimum probability of detection, the other to manage required false alarm rate - and allows a non-linear integration process that, along with Signal-to-Noise Ratio (SNR) gain, provides system designers more capability where cost, weight, or power considerations limit system data rate, processing, or memory capability. However, Recursive Frame Integration Limited may have performance issues when single frame SNR is really low. Recursive Adaptive Frame Integration Limited is proposed as a means to improve limited integration performance with really low single frame SNR. It combines the benefits of nonlinear recursive limited frame integration and adaptive thresholds with a kind of conventional frame integration.
Toggweiler, Matthias; Adelmann, Andreas; Arbenz, Peter; Yang, Jianjun
2014-09-15
We show that adaptive time stepping in particle accelerator simulation is an enhancement for certain problems. The new algorithm has been implemented in the OPAL (Object Oriented Parallel Accelerator Library) framework. The idea is to adjust the frequency of costly self-field calculations, which are needed to model Coulomb interaction (space charge) effects. In analogy to a Kepler orbit simulation that requires a higher time step resolution at the close encounter, we propose to choose the time step based on the magnitude of the space charge forces. Inspired by geometric integration techniques, our algorithm chooses the time step proportional to a function of the current phase space state instead of calculating a local error estimate like a conventional adaptive procedure. Building on recent work, a more profound argument is given on how exactly the time step should be chosen. An intermediate algorithm, initially built to allow a clearer analysis by introducing separate time steps for external field and self-field integration, turned out to be useful by its own, for a large class of problems.
NASA Astrophysics Data System (ADS)
Hou, Zuoxun; Ma, Yitao; Zhu, Hongbo; Zheng, Nanning; Shibata, Tadashi
2013-04-01
A very large-scale integration (VLSI) recognition system equipped with an on-chip learning capability has been developed for real-time processing applications. This system can work in two functional modes of operation: adaptive K-means learning mode and recognition mode. In the adaptive K-means learning mode, the variance ratio criterion (VRC) has been employed to evaluate the quality of K-means classification results, and the evaluation algorithm has been implemented on the chip. As a result, it has become possible for the system to autonomously determine the optimum number of clusters (K). In the recognition mode, the nearest-neighbor search algorithm is very efficiently carried out by the fully parallel architecture employed in the chip. In both modes of operation, many hardware resources are shared and the functionality is flexibly altered by the system controller designed as a finite-state machine (FSM). The chip is implemented on Altera Cyclone II FPGA with 46K logic cells. Its operating clock is 25 MHz and the processing times for adaptive learning and recognition with 256 64-dimension feature vectors are about 0.42 ms and 4 µs, respectively. Both adaptive K-means learning and recognition functions have been verified by experiments using the image data from the COIL-100 (Columbia University Object Image Library) database.
Sensory adaptation for timing perception
Roseboom, Warrick; Linares, Daniel; Nishida, Shin'ya
2015-01-01
Recent sensory experience modifies subjective timing perception. For example, when visual events repeatedly lead auditory events, such as when the sound and video tracks of a movie are out of sync, subsequent vision-leads-audio presentations are reported as more simultaneous. This phenomenon could provide insights into the fundamental problem of how timing is represented in the brain, but the underlying mechanisms are poorly understood. Here, we show that the effect of recent experience on timing perception is not just subjective; recent sensory experience also modifies relative timing discrimination. This result indicates that recent sensory history alters the encoding of relative timing in sensory areas, excluding explanations of the subjective phenomenon based only on decision-level changes. The pattern of changes in timing discrimination suggests the existence of two sensory components, similar to those previously reported for visual spatial attributes: a lateral shift in the nonlinear transducer that maps relative timing into perceptual relative timing and an increase in transducer slope around the exposed timing. The existence of these components would suggest that previous explanations of how recent experience may change the sensory encoding of timing, such as changes in sensory latencies or simple implementations of neural population codes, cannot account for the effect of sensory adaptation on timing perception. PMID:25788590
Adaptive Urban Dispersion Integrated Model
Wissink, A; Chand, K; Kosovic, B; Chan, S; Berger, M; Chow, F K
2005-11-03
Numerical simulations represent a unique predictive tool for understanding the three-dimensional flow fields and associated concentration distributions from contaminant releases in complex urban settings (Britter and Hanna 2003). Utilization of the most accurate urban models, based on fully three-dimensional computational fluid dynamics (CFD) that solve the Navier-Stokes equations with incorporated turbulence models, presents many challenges. We address two in this work; first, a fast but accurate way to incorporate the complex urban terrain, buildings, and other structures to enforce proper boundary conditions in the flow solution; second, ways to achieve a level of computational efficiency that allows the models to be run in an automated fashion such that they may be used for emergency response and event reconstruction applications. We have developed a new integrated urban dispersion modeling capability based on FEM3MP (Gresho and Chan 1998, Chan and Stevens 2000), a CFD model from Lawrence Livermore National Lab. The integrated capability incorporates fast embedded boundary mesh generation for geometrically complex problems and full three-dimensional Cartesian adaptive mesh refinement (AMR). Parallel AMR and embedded boundary gridding support are provided through the SAMRAI library (Wissink et al. 2001, Hornung and Kohn 2002). Embedded boundary mesh generation has been demonstrated to be an automatic, fast, and efficient approach for problem setup. It has been used for a variety of geometrically complex applications, including urban applications (Pullen et al. 2005). The key technology we introduce in this work is the application of AMR, which allows the application of high-resolution modeling to certain important features, such as individual buildings and high-resolution terrain (including important vegetative and land-use features). It also allows the urban scale model to be readily interfaced with coarser resolution meso or regional scale models. This talk
NASA Technical Reports Server (NTRS)
Smith, Paul L.; VonderHaar, Thomas H.
1996-01-01
The principal goal of this project is to establish relationships that would allow application of area-time integral (ATI) calculations based upon satellite data to estimate rainfall volumes. The research is being carried out as a collaborative effort between the two participating organizations, with the satellite data analysis to determine values for the ATIs being done primarily by the STC-METSAT scientists and the associated radar data analysis to determine the 'ground-truth' rainfall estimates being done primarily at the South Dakota School of Mines and Technology (SDSM&T). Synthesis of the two separate kinds of data and investigation of the resulting rainfall-versus-ATI relationships is then carried out jointly. The research has been pursued using two different approaches, which for convenience can be designated as the 'fixed-threshold approach' and the 'adaptive-threshold approach'. In the former, an attempt is made to determine a single temperature threshold in the satellite infrared data that would yield ATI values for identifiable cloud clusters which are closely related to the corresponding rainfall amounts as determined by radar. Work on the second, or 'adaptive-threshold', approach for determining the satellite ATI values has explored two avenues: (1) attempt involved choosing IR thresholds to match the satellite ATI values with ones separately calculated from the radar data on a case basis; and (2) an attempt involved a striaghtforward screening analysis to determine the (fixed) offset that would lead to the strongest correlation and lowest standard error of estimate in the relationship between the satellite ATI values and the corresponding rainfall volumes.
Telepresence, time delay, and adaptation
NASA Technical Reports Server (NTRS)
Held, Richard; Durlach, Nathaniel
1989-01-01
Displays are now being used extensively throughout the society. More and more time is spent watching television, movies, computer screens, etc. Furthermore, in an increasing number of cases, the observer interacts with the display and plays the role of operator as well as observer. To a large extent, the normal behavior in the normal environment can also be thought of in these same terms. Taking liberties with Shakespeare, it might be said, all the world's a display and all the individuals in it are operators in and on the display. Within this general context of interactive display systems, a discussion is began with a conceptual overview of a particular class of such systems, namely, teleoperator systems. The notion is considered of telepresence and the factors that limit telepresence, including decorrelation between the: (1) motor output of the teleoperator as sensed directly via the kinesthetic/tactual system, and (2) the motor output of the teleoperator as sensed indirectly via feedback from the slave robot, i.e., via a visual display of the motor actions of the slave robot. Finally, the deleterious effect of time delay (a particular decorrelation) on sensory-motor adaptation (an important phenomenon related to telepresence) is examined.
Parallel time integration software
Energy Science and Technology Software Center (ESTSC)
2014-07-01
This package implements an optimal-scaling multigrid solver for the (non) linear systems that arise from the discretization of problems with evolutionary behavior. Typically, solution algorithms for evolution equations are based on a time-marching approach, solving sequentially for one time step after the other. Parallelism in these traditional time-integrarion techniques is limited to spatial parallelism. However, current trends in computer architectures are leading twards system with more, but not faster. processors. Therefore, faster compute speeds mustmore » come from greater parallelism. One approach to achieve parallelism in time is with multigrid, but extending classical multigrid methods for elliptic poerators to this setting is a significant achievement. In this software, we implement a non-intrusive, optimal-scaling time-parallel method based on multigrid reduction techniques. The examples in the package demonstrate optimality of our multigrid-reduction-in-time algorithm (MGRIT) for solving a variety of parabolic equations in two and three sparial dimensions. These examples can also be used to show that MGRIT can achieve significant speedup in comparison to sequential time marching on modern architectures.« less
Parallel time integration software
2014-07-01
This package implements an optimal-scaling multigrid solver for the (non) linear systems that arise from the discretization of problems with evolutionary behavior. Typically, solution algorithms for evolution equations are based on a time-marching approach, solving sequentially for one time step after the other. Parallelism in these traditional time-integrarion techniques is limited to spatial parallelism. However, current trends in computer architectures are leading twards system with more, but not faster. processors. Therefore, faster compute speeds must come from greater parallelism. One approach to achieve parallelism in time is with multigrid, but extending classical multigrid methods for elliptic poerators to this setting is a significant achievement. In this software, we implement a non-intrusive, optimal-scaling time-parallel method based on multigrid reduction techniques. The examples in the package demonstrate optimality of our multigrid-reduction-in-time algorithm (MGRIT) for solving a variety of parabolic equations in two and three sparial dimensions. These examples can also be used to show that MGRIT can achieve significant speedup in comparison to sequential time marching on modern architectures.
Multimodal integration of time.
Bausenhart, Karin M; de la Rosa, Maria Dolores; Ulrich, Rolf
2014-01-01
Recent studies suggest that the accuracy of duration discrimination for visually presented intervals is strongly impaired by concurrently presented auditory intervals of different duration, but not vice versa. Because these studies rely mostly on accuracy measures, it remains unclear whether this impairment results from changes in perceived duration or rather from a decrease in perceptual sensitivity. We therefore assessed complete psychometric functions in a duration discrimination task to disentangle effects on perceived duration and sensitivity. Specifically, participants compared two empty intervals marked by either visual or auditory pulses. These pulses were either presented unimodally, or accompanied by task-irrelevant pulses in the respective other modality, which defined conflicting intervals of identical, shorter, or longer duration. Participants were instructed to base their temporal judgments solely on the task-relevant modality. Despite this instruction, perceived duration was clearly biased toward the duration of the intervals marked in the task-irrelevant modality. This was not only found for the discrimination of visual intervals, but also, to a lesser extent, for the discrimination of auditory intervals. Discrimination sensitivity, however, was similar between all multimodal conditions, and only improved compared to the presentation of unimodal visual intervals. In a second experiment, evidence for multisensory integration was even found when the task-irrelevant modality did not contain any duration information, thus excluding noncompliant attention allocation as a basis of our results. Our results thus suggest that audiovisual integration of temporally discrepant signals does not impair discrimination sensitivity but rather alters perceived duration, presumably by means of a temporal ventriloquism effect. PMID:24351985
Systems integration of innate and adaptive immunity.
Zak, Daniel E; Aderem, Alan
2015-09-29
The pathogens causing AIDS, malaria, and tuberculosis have proven too complex to be overcome by classical approaches to vaccination. The complexities of human immunology and pathogen-induced modulation of the immune system mandate new approaches to vaccine discovery and design. A new field, systems vaccinology, weds holistic analysis of innate and adaptive immunity within a quantitative framework to enable rational design of new vaccines that elicit tailored protective immune responses. A key step in the approach is to discover relationships between the earliest innate inflammatory responses to vaccination and the subsequent vaccine-induced adaptive immune responses and efficacy. Analysis of these responses in clinical studies is complicated by the inaccessibility of relevant tissue compartments (such as the lymph node), necessitating reliance upon peripheral blood responses as surrogates. Blood transcriptomes, although indirect to vaccine mechanisms, have proven very informative in systems vaccinology studies. The approach is most powerful when innate and adaptive immune responses are integrated with vaccine efficacy, which is possible for malaria with the advent of a robust human challenge model. This is more difficult for AIDS and tuberculosis, given that human challenge models are lacking and efficacy observed in clinical trials has been low or highly variable. This challenge can be met by appropriate clinical trial design for partially efficacious vaccines and by analysis of natural infection cohorts. Ultimately, systems vaccinology is an iterative approach in which mechanistic hypotheses-derived from analysis of clinical studies-are evaluated in model systems, and then used to guide the development of new vaccine strategies. In this review, we will illustrate the above facets of the systems vaccinology approach with case studies. PMID:26102534
Analysis of adaptive algorithms for an integrated communication network
NASA Technical Reports Server (NTRS)
Reed, Daniel A.; Barr, Matthew; Chong-Kwon, Kim
1985-01-01
Techniques were examined that trade communication bandwidth for decreased transmission delays. When the network is lightly used, these schemes attempt to use additional network resources to decrease communication delays. As the network utilization rises, the schemes degrade gracefully, still providing service but with minimal use of the network. Because the schemes use a combination of circuit and packet switching, they should respond to variations in the types and amounts of network traffic. Also, a combination of circuit and packet switching to support the widely varying traffic demands imposed on an integrated network was investigated. The packet switched component is best suited to bursty traffic where some delays in delivery are acceptable. The circuit switched component is reserved for traffic that must meet real time constraints. Selected packet routing algorithms that might be used in an integrated network were simulated. An integrated traffic places widely varying workload demands on a network. Adaptive algorithms were identified, ones that respond to both the transient and evolutionary changes that arise in integrated networks. A new algorithm was developed, hybrid weighted routing, that adapts to workload changes.
Durham adaptive optics real-time controller.
Basden, Alastair; Geng, Deli; Myers, Richard; Younger, Eddy
2010-11-10
The Durham adaptive optics (AO) real-time controller was initially a proof of concept design for a generic AO control system. It has since been developed into a modern and powerful central-processing-unit-based real-time control system, capable of using hardware acceleration (including field programmable gate arrays and graphical processing units), based primarily around commercial off-the-shelf hardware. It is powerful enough to be used as the real-time controller for all currently planned 8 m class telescope AO systems. Here we give details of this controller and the concepts behind it, and report on performance, including latency and jitter, which is less than 10 μs for small AO systems. PMID:21068868
Progress in integrated analysis with adaptive unstructured meshing
NASA Technical Reports Server (NTRS)
Dechaumphai, Pramote
1992-01-01
Design of lightweight structures and thermal protection systems for hypersonic vehicles depend on accurate prediction of aerothermal loads, structural temperatures and their gradients, and structural deformations and stresses. Concentration is on an alternative meshing technique which generates an entirely new adaptive unstructured mesh based on the solution obtained from the earlier mesh. The technique combined with the finite element method has been shown to significantly improve the efficiency and accuracy of the fluid, thermal, and structural analyses. Current capability of the adaptive unstructured meshing technique for the integrated fluid-thermal-structural analysis is described first. The technique was extended to transient thermal analysis of structures with time-dependent adaptive meshing to capture the detailed temperature response with a minimum number of unknowns and computational cost. Both linear and higher-order finite elements are implemented to demonstrate the generality of the technique and to investigate their solution accuracy. Currently, the adaptive meshing technique is being developed for plane structures that can be modeled with membrane elements and built-up structures modeled with membrane and bending elements. The capability of the technique to these different disciplinary problems is demonstrated by several examples.
Space-time adaptive numerical methods for geophysical applications.
Castro, C E; Käser, M; Toro, E F
2009-11-28
In this paper we present high-order formulations of the finite volume and discontinuous Galerkin finite-element methods for wave propagation problems with a space-time adaptation technique using unstructured meshes in order to reduce computational cost without reducing accuracy. Both methods can be derived in a similar mathematical framework and are identical in their first-order version. In their extension to higher order accuracy in space and time, both methods use spatial polynomials of higher degree inside each element, a high-order solution of the generalized Riemann problem and a high-order time integration method based on the Taylor series expansion. The static adaptation strategy uses locally refined high-resolution meshes in areas with low wave speeds to improve the approximation quality. Furthermore, the time step length is chosen locally adaptive such that the solution is evolved explicitly in time by an optimal time step determined by a local stability criterion. After validating the numerical approach, both schemes are applied to geophysical wave propagation problems such as tsunami waves and seismic waves comparing the new approach with the classical global time-stepping technique. The problem of mesh partitioning for large-scale applications on multi-processor architectures is discussed and a new mesh partition approach is proposed and tested to further reduce computational cost. PMID:19840984
Fuzzy Adaptive Cubature Kalman Filter for Integrated Navigation Systems.
Tseng, Chien-Hao; Lin, Sheng-Fuu; Jwo, Dah-Jing
2016-01-01
This paper presents a sensor fusion method based on the combination of cubature Kalman filter (CKF) and fuzzy logic adaptive system (FLAS) for the integrated navigation systems, such as the GPS/INS (Global Positioning System/inertial navigation system) integration. The third-degree spherical-radial cubature rule applied in the CKF has been employed to avoid the numerically instability in the system model. In processing navigation integration, the performance of nonlinear filter based estimation of the position and velocity states may severely degrade caused by modeling errors due to dynamics uncertainties of the vehicle. In order to resolve the shortcoming for selecting the process noise covariance through personal experience or numerical simulation, a scheme called the fuzzy adaptive cubature Kalman filter (FACKF) is presented by introducing the FLAS to adjust the weighting factor of the process noise covariance matrix. The FLAS is incorporated into the CKF framework as a mechanism for timely implementing the tuning of process noise covariance matrix based on the information of degree of divergence (DOD) parameter. The proposed FACKF algorithm shows promising accuracy improvement as compared to the extended Kalman filter (EKF), unscented Kalman filter (UKF), and CKF approaches. PMID:27472336
Variational time integrators in computational solid mechanics
NASA Astrophysics Data System (ADS)
Lew, Adrian Jose
This thesis develops the theory and implementation of variational integrators for computational solid mechanics problems, and to some extent, for fluid mechanics problems as well. Variational integrators for finite dimensional mechanical systems are succinctly reviewed, and used as the foundations for the extension to continuum systems. The latter is accomplished by way of a space-tune formulation for Lagrangian continuum mechanics that unifies the derivation of tyre balance of linear momentum, energy and configurational forces, all of there as Euler-Lagrange equations of an extended Hamilton's principle. In this formulation, energy conservation and the path independence of the J- and L-integrals are conserved quantities emanating from Noether's theorem. Variational integrators for continuum mechanics are constructed by mimicking this variational structure, and a discrete Noether's theorem for rather general space-tune discretizations is presented. Additionally, the algorithms are automatically (multi)symplectic, and the (multi)symplectic form is uniquely defined by the theory. For instance, in nonlinear elastodynamics the algorithms exactly preserve linear and angular momenta, whenever the continuous system does. A class of variational algorithms is constructed, termed asynchronous variational integrators (AVI), which permit: the selection of independent time steps in each element of a finite element mesh, and the local time steps need riot bear an integral relation to each other. The conservation properties of both synchronous and asynchronous variational integrators are discussed in detail. In particular, AVI are found to nearly conserve energy both locally and globally, a distinguishing feature of variational integrators. The possibility of adapting the elemental time step to exactly satisfy the local energy balance equation, obtained from the extended variational principle, is analyzed. The AVI are also extended to include dissipative systems. The excellent
Improving Adaptive Learning Technology through the Use of Response Times
ERIC Educational Resources Information Center
Mettler, Everett; Massey, Christine M.; Kellman, Philip J.
2011-01-01
Adaptive learning techniques have typically scheduled practice using learners' accuracy and item presentation history. We describe an adaptive learning system (Adaptive Response Time Based Sequencing--ARTS) that uses both accuracy and response time (RT) as direct inputs into sequencing. Response times are used to assess learning strength and…
Real-time adaptive video image enhancement
NASA Astrophysics Data System (ADS)
Garside, John R.; Harrison, Chris G.
1999-07-01
As part of a continuing collaboration between the University of Manchester and British Aerospace, a signal processing array has been constructed to demonstrate that it is feasible to compensate a video signal for the degradation caused by atmospheric haze in real-time. Previously reported work has shown good agreement between a simple physical model of light scattering by atmospheric haze and the observed loss of contrast. This model predicts a characteristic relationship between contrast loss in the image and the range from the camera to the scene. For an airborne camera, the slant-range to a point on the ground may be estimated from the airplane's pose, as reported by the inertial navigation system, and the contrast may be obtained from the camera's output. Fusing data from these two streams provides a means of estimating model parameters such as the visibility and the overall illumination of the scene. This knowledge allows the same model to be applied in reverse, thus restoring the contrast lost to atmospheric haze. An efficient approximation of range is vital for a real-time implementation of the method. Preliminary results show that an adaptive approach to fitting the model's parameters, exploiting the temporal correlation between video frames, leads to a robust implementation with a significantly accelerated throughput.
Adaptive multi-sensor integration for mine detection
Baker, J.E.
1997-05-01
State-of-the-art in multi-sensor integration (MSI) application involves extensive research and development time to understand and characterize the application domain; to determine and define the appropriate sensor suite; to analyze, characterize, and calibrate the individual sensor systems; to recognize and accommodate the various sensor interactions; and to develop and optimize robust merging code. Much of this process can benefit from adaptive learning, i.e., an output-based system can take raw sensor data and desired merged results as input and adaptively develop/determine an effective method if interpretation and merger. This approach significantly reduces the time required to apply MSI to a given application, while increasing the quality of the final result and provides a quantitative measure for comparing competing MSI techniques and sensor suites. The ability to automatically develop and optimize MSI techniques for new sensor suites and operating environments makes this approach well suited to the detection of mines and mine-like targets. Perhaps more than any other, this application domain is characterized by diverse, innovative, and dynamic sensor suites, whose nature and interactions are not yet well established. This paper presents such an outcome-based multi-image analysis system. An empirical evaluation of its performance and its application, sensor and domain robustness is presented.
Complexity and network dynamics in physiological adaptation: an integrated view.
Baffy, György; Loscalzo, Joseph
2014-05-28
Living organisms constantly interact with their surroundings and sustain internal stability against perturbations. This dynamic process follows three fundamental strategies (restore, explore, and abandon) articulated in historical concepts of physiological adaptation such as homeostasis, allostasis, and the general adaptation syndrome. These strategies correspond to elementary forms of behavior (ordered, chaotic, and static) in complex adaptive systems and invite a network-based analysis of the operational characteristics, allowing us to propose an integrated framework of physiological adaptation from a complex network perspective. Applicability of this concept is illustrated by analyzing molecular and cellular mechanisms of adaptation in response to the pervasive challenge of obesity, a chronic condition resulting from sustained nutrient excess that prompts chaotic exploration for system stability associated with tradeoffs and a risk of adverse outcomes such as diabetes, cardiovascular disease, and cancer. Deconstruction of this complexity holds the promise of gaining novel insights into physiological adaptation in health and disease. PMID:24751342
Adaptive Controller Adaptation Time and Available Control Authority Effects on Piloting
NASA Technical Reports Server (NTRS)
Trujillo, Anna; Gregory, Irene
2013-01-01
Adaptive control is considered for highly uncertain, and potentially unpredictable, flight dynamics characteristic of adverse conditions. This experiment looked at how adaptive controller adaptation time to recover nominal aircraft dynamics affects pilots and how pilots want information about available control authority transmitted. Results indicate that an adaptive controller that takes three seconds to adapt helped pilots when looking at lateral and longitudinal errors. The controllability ratings improved with the adaptive controller, again the most for the three seconds adaptation time while workload decreased with the adaptive controller. The effects of the displays showing the percentage amount of available safe flight envelope used in the maneuver were dominated by the adaptation time. With the displays, the altitude error increased, controllability slightly decreased, and mental demand increased. Therefore, the displays did require some of the subjects resources but these negatives may be outweighed by pilots having more situation awareness of their aircraft.
NASA Astrophysics Data System (ADS)
Zeff, H. B.; Characklis, G. W.; Reed, P. M.; Herman, J. D.
2015-12-01
Water supply policies that integrate portfolios of short-term management decisions with long-term infrastructure development enable utilities to adapt to a range of future scenarios. An effective mix of short-term management actions can augment existing infrastructure, potentially forestalling new development. Likewise, coordinated expansion of infrastructure such as regional interconnections and shared treatment capacity can increase the effectiveness of some management actions like water transfers. Highly adaptable decision pathways that mix long-term infrastructure options and short-term management actions require decision triggers capable of incorporating the impact of these time-evolving decisions on growing water supply needs. Here, we adapt risk-based triggers to sequence a set of potential infrastructure options in combination with utility-specific conservation actions and inter-utility water transfers. Individual infrastructure pathways can be augmented with conservation or water transfers to reduce the cost of meeting utility objectives, but they can also include cooperatively developed, shared infrastructure that expands regional capacity to transfer water. This analysis explores the role of cooperation among four water utilities in the 'Research Triangle' region of North Carolina by formulating three distinct categories of adaptive policy pathways: independent action (utility-specific conservation and supply infrastructure only), weak cooperation (utility-specific conservation and infrastructure development with regional transfers), and strong cooperation (utility specific conservation and jointly developed of regional infrastructure that supports transfers). Results suggest that strong cooperation aids the utilities in meeting their individual objections at substantially lower costs and with fewer irreversible infrastructure options.
Calculation of plantar pressure time integral, an alternative approach.
Melai, Tom; IJzerman, T Herman; Schaper, Nicolaas C; de Lange, Ton L H; Willems, Paul J B; Meijer, Kenneth; Lieverse, Aloysius G; Savelberg, Hans H C M
2011-07-01
In plantar pressure measurement, both peak pressure and pressure time integral are used as variables to assess plantar loading. However, pressure time integral shows a high concordance with peak pressure. Many researchers and clinicians use Novel software (Novel GmbH Inc., Munich, Germany) that calculates this variable as the summation of the products of peak pressure and duration per time sample, which is not a genuine integral of pressure over time. Therefore, an alternative calculation method was introduced. The aim of this study was to explore the relevance of this alternative method, in different populations. Plantar pressure variables were measured in 76 people with diabetic polyneuropathy, 33 diabetic controls without polyneuropathy and 19 healthy subjects. Peak pressure and pressure time integral were obtained using Novel software. The quotient of the genuine force time integral over contact area was obtained as the alternative pressure time integral calculation. This new alternative method correlated less with peak pressure than the pressure time integral as calculated by Novel. The two methods differed significantly and these differences varied between the foot sole areas and between groups. The largest differences were found under the metatarsal heads in the group with diabetic polyneuropathy. From a theoretical perspective, the alternative approach provides a more valid calculation of the pressure time integral. In addition, this study showed that the alternative calculation is of added value, along peak pressure calculation, to interpret adapted plantar pressures patterns in particular in patients at risk for foot ulceration. PMID:21737281
Optimal integration time in OCT imaging
NASA Astrophysics Data System (ADS)
Martin, Lorenz; Gräub, Stephan; Meier, Christoph
2015-07-01
When measuring static objects with 3D OCT, two opposing trends occur: If the integration time is too short, the measurement is noisy resulting in granulated textures on measured objects. If the integration time is too long, drifts e.g. due to thermal effects or unstable laser sources lead to blurred images. The Allan variance is a scheme to find the optimal integration time in terms of reducing noise without picking up signal drift. A long-term measurement with short integration time of a reference target under realistic conditions is needed to obtain the database for the calculation of the Allan variance. Longer integration times are simulated by taking averages of subsequent samples. The Allan variance being the mean of the squared differences between two consecutive averages is calculated for different integration times. The optimal integration time is achieved for minimal Allan variance. First, the scheme is explained and discussed with simulated data. Then, reference measurements of layers of adhesive tape made with a 3D OCT device are analysed to find the optimal integration time of the device. Finally, the findings are applied to the detection of water inclusions in calcite. With too short integration time the water inclusions appear with a stained surface. With the integration time increased towards the optimal time, the surfaces of the water inclusions get smoother and easier to discriminate from the background. Ready-to-use Octave code for the computation of the Allan variance is provided.
System integration of pattern recognition, adaptive aided, upper limb prostheses
NASA Technical Reports Server (NTRS)
Lyman, J.; Freedy, A.; Solomonow, M.
1975-01-01
The requirements for successful integration of a computer aided control system for multi degree of freedom artificial arms are discussed. Specifications are established for a system which shares control between a human amputee and an automatic control subsystem. The approach integrates the following subsystems: (1) myoelectric pattern recognition, (2) adaptive computer aiding; (3) local reflex control; (4) prosthetic sensory feedback; and (5) externally energized arm with the functions of prehension, wrist rotation, elbow extension and flexion and humeral rotation.
An averaging analysis of discrete-time indirect adaptive control
NASA Technical Reports Server (NTRS)
Phillips, Stephen M.; Kosut, Robert L.; Franklin, Gene F.
1988-01-01
An averaging analysis of indirect, discrete-time, adaptive control systems is presented. The analysis results in a signal-dependent stability condition and accounts for unmodeled plant dynamics as well as exogenous disturbances. This analysis is applied to two discrete-time adaptive algorithms: an unnormalized gradient algorithm and a recursive least-squares (RLS) algorithm with resetting. Since linearization and averaging are used for the gradient analysis, a local stability result valid for small adaptation gains is found. For RLS with resetting, the assumption is that there is a long time between resets. The results for the two algorithms are virtually identical, emphasizing their similarities in adaptive control.
Integrating Learning Styles into Adaptive E-Learning System
ERIC Educational Resources Information Center
Truong, Huong May
2015-01-01
This paper provides an overview and update on my PhD research project which focuses on integrating learning styles into adaptive e-learning system. The project, firstly, aims to develop a system to classify students' learning styles through their online learning behaviour. This will be followed by a study on the complex relationship between…
Induction, adaptation and recovery of lysosomal integrity in green-lipped mussel Perna viridis.
Fang, J K H; Wu, R S S; Zheng, G J; Lam, P K S; Shin, P K S
2008-01-01
Biomarkers are generally applied to detect pollution in environmental monitoring. Such biological responses should accurately reflect the stress over time in a quantitative manner. As such, the initial and maximum responses induced by stress, as well as adaptation and recovery of these biomarkers, need to be fully understood or else erroneous false-negative or false-positive may be arrived. However, most of the biomarker studies only provided information on initially induced responses under different concentrations of toxicants, while biological adaptation and recovery were poorly known. In this study, the time required for induction, adaptation and recovery of lysosomal integrity in green-lipped mussel Perna viridis upon exposure to benzo[a]pyrene was investigated over a period of 62 days. Maximum induction occurred on day 6 when lysosomal integrity was significantly reduced by 51%, and no further change or adaptation was detected thereafter. When mussels were depurated in clean seawater after 18 days of exposure to benzo[a]pyrene, a gradual recovery was observed, with lysosomal integrity returning to its background level and showing a complete recovery after 20 days of depuration. Lysosomal integrity was significantly correlated with the body burden concentrations of benzo[a]pyrene and condition index of the mussels. The relatively fast induction (6 days) and recovery (20 days) without apparent adaptation suggested that lysosomal integrity in P. viridis can serve as a good biomarker in biomonitoring, as its response is not likely to generate both false-negative and false-positive results. PMID:18466928
Managing Climate Risk. Integrating Adaptation into World Bank Group Operations
Van Aalst, M.
2006-08-15
climate conditions. There are several ways in which the World Bank Group can continue helping its clients better manage climate risks to poverty reduction and sustainable development: Integrating climate risk management into the project cycle, by adopting early risk identification (for instance by applying a quick and simple risk-screening tool) and following up throughout the design process if necessary. Integrating climate risk management into country and sector dialogues, especially in countries and sectors that are particularly vulnerable. Enhancing internal support for and coordination of climate risk management by, for example, expanding analytical work and capacity for cross-support by the Global Climate Change Team and the Hazard Management Unit of the World Bank and by actively developing climate risk management activities within regional departments. Supporting the establishment of proper financing mechanisms for adaptation, using, for example, the Investment Framework for Clean Energy and Development. New funding mechanisms created under the United Nations Framework Convention on Climate Change (UNFCCC) and being made operational by the Global Environment Facility (GEF), as well as the Kyoto Protocol, should be used to leverage maximum adaptation results within the Bank's broad range of development activities and investments. By enhancing climate risk management, the World Bank Group will be able to address the growing risks from climate change and, at the same time, make current development investments more resilient to climate variability and extreme weather events. In that way, climate risk management will not only guard the Bank's investments in a changing climate but will also improve the impact of development efforts right now.
Averaging analysis for discrete time and sampled data adaptive systems
NASA Technical Reports Server (NTRS)
Fu, Li-Chen; Bai, Er-Wei; Sastry, Shankar S.
1986-01-01
Earlier continuous time averaging theorems are extended to the nonlinear discrete time case. Theorems for the study of the convergence analysis of discrete time adaptive identification and control systems are used. Instability theorems are also derived and used for the study of robust stability and instability of adaptive control schemes applied to sampled data systems. As a by product, the effects of sampling on unmodeled dynamics in continuous time systems are also studied.
McDowell, Julia Z.; Luber, George
2011-01-01
Background: Climate change is expected to have a range of health impacts, some of which are already apparent. Public health adaptation is imperative, but there has been little discussion of how to increase adaptive capacity and resilience in public health systems. Objectives: We explored possible explanations for the lack of work on adaptive capacity, outline climate–health challenges that may lie outside public health’s coping range, and consider changes in practice that could increase public health’s adaptive capacity. Methods: We conducted a substantive, interdisciplinary literature review focused on climate change adaptation in public health, social learning, and management of socioeconomic systems exhibiting dynamic complexity. Discussion: There are two competing views of how public health should engage climate change adaptation. Perspectives differ on whether climate change will primarily amplify existing hazards, requiring enhancement of existing public health functions, or present categorically distinct threats requiring innovative management strategies. In some contexts, distinctly climate-sensitive health threats may overwhelm public health’s adaptive capacity. Addressing these threats will require increased emphasis on institutional learning, innovative management strategies, and new and improved tools. Adaptive management, an iterative framework that embraces uncertainty, uses modeling, and integrates learning, may be a useful approach. We illustrate its application to extreme heat in an urban setting. Conclusions: Increasing public health capacity will be necessary for certain climate–health threats. Focusing efforts to increase adaptive capacity in specific areas, promoting institutional learning, embracing adaptive management, and developing tools to facilitate these processes are important priorities and can improve the resilience of local public health systems to climate change. PMID:21997387
Bergeron, Bryan; Cline, Andrew; Shipley, Jaime
2012-01-01
We have developed a distributed, standards-based architecture that enables simulation and simulator designers to leverage adaptive learning systems. Our approach, which incorporates an electronic competency record, open source LMS, and open source microcontroller hardware, is a low-cost, pragmatic option to integrating simulators with traditional courseware. PMID:22356955
Integrating Time, Place, and Play
ERIC Educational Resources Information Center
Gallavan, Nancy P.
2004-01-01
"Time, Place, and Play," is a short phrase, but is summarizes three very big concepts--history, geography, and culture--that are part of the elementary social studies curriculum. This article relates the story of how twenty-five elementary and middle school teachers, meeting over several weeks in a university class, designed a unit of study on the…
Adaptive median filtering for preprocessing of time series measurements
NASA Technical Reports Server (NTRS)
Paunonen, Matti
1993-01-01
A median (L1-norm) filtering program using polynomials was developed. This program was used in automatic recycling data screening. Additionally, a special adaptive program to work with asymmetric distributions was developed. Examples of adaptive median filtering of satellite laser range observations and TV satellite time measurements are given. The program proved to be versatile and time saving in data screening of time series measurements.
Remote mission specialist - A study in real-time, adaptive planning
NASA Technical Reports Server (NTRS)
Rokey, Mark J.
1990-01-01
A high-level planning architecture for robotic operations is presented. The remote mission specialist integrates high-level directives with low-level primitives executable by a run-time controller for command of autonomous servicing activities. The planner has been designed to address such issues as adaptive plan generation, real-time performance, and operator intervention.
Discrete-time adaptive control of robot manipulators
NASA Technical Reports Server (NTRS)
Tarokh, M.
1989-01-01
A discrete-time model reference adaptive control scheme is developed for trajectory tracking of robot manipulators. Hyperstability theory is utilized to derive the adaptation laws for the controller gain matrices. It is shown that asymptotic trajectory tracking is achieved despite gross robot parameter variation and uncertainties. The method offers considerable design flexibility and enables the designer to improve the performance of the control system by adjusting free design parameters. The discrete-time adaptation algorithm is extremely simple and is therefore suitable for real-time implementation.
Adaptive learning of Multi-Sensor Integration techniques with genetic algorithms
Baker, J.E.
1994-06-01
This research focuses on automating the time-consuming process of developing and optimizing multi-sensor integration techniques. Our approach is currently based on adaptively learning how to exploit low-level image detail. Although this system is specifically designed to be both sensor and application domain independent, an empirical validation with actual multi-modal sensor data is presented.
Feature integration across space, time, and orientation
Otto, Thomas U.; Öğmen, Haluk; Herzog, Michael H.
2012-01-01
The perception of a visual target can be strongly influenced by flanking stimuli. In static displays, performance on the target improves when the distance to the flanking elements increases- proposedly because feature pooling and integration vanishes with distance. Here, we studied feature integration with dynamic stimuli. We show that features of single elements presented within a continuous motion stream are integrated largely independent of spatial distance (and orientation). Hence, space based models of feature integration cannot be extended to dynamic stimuli. We suggest that feature integration is guided by perceptual grouping operations that maintain the identity of perceptual objects over space and time. PMID:19968428
Stochastic analysis of epidemics on adaptive time varying networks
NASA Astrophysics Data System (ADS)
Kotnis, Bhushan; Kuri, Joy
2013-06-01
Many studies investigating the effect of human social connectivity structures (networks) and human behavioral adaptations on the spread of infectious diseases have assumed either a static connectivity structure or a network which adapts itself in response to the epidemic (adaptive networks). However, human social connections are inherently dynamic or time varying. Furthermore, the spread of many infectious diseases occur on a time scale comparable to the time scale of the evolving network structure. Here we aim to quantify the effect of human behavioral adaptations on the spread of asymptomatic infectious diseases on time varying networks. We perform a full stochastic analysis using a continuous time Markov chain approach for calculating the outbreak probability, mean epidemic duration, epidemic reemergence probability, etc. Additionally, we use mean-field theory for calculating epidemic thresholds. Theoretical predictions are verified using extensive simulations. Our studies have uncovered the existence of an “adaptive threshold,” i.e., when the ratio of susceptibility (or infectivity) rate to recovery rate is below the threshold value, adaptive behavior can prevent the epidemic. However, if it is above the threshold, no amount of behavioral adaptations can prevent the epidemic. Our analyses suggest that the interaction patterns of the infected population play a major role in sustaining the epidemic. Our results have implications on epidemic containment policies, as awareness campaigns and human behavioral responses can be effective only if the interaction levels of the infected populace are kept in check.
Real-time adaptive aircraft scheduling
NASA Technical Reports Server (NTRS)
Kolitz, Stephan E.; Terrab, Mostafa
1990-01-01
One of the most important functions of any air traffic management system is the assignment of ground-holding times to flights, i.e., the determination of whether and by how much the take-off of a particular aircraft headed for a congested part of the air traffic control (ATC) system should be postponed in order to reduce the likelihood and extent of airborne delays. An analysis is presented for the fundamental case in which flights from many destinations must be scheduled for arrival at a single congested airport; the formulation is also useful in scheduling the landing of airborne flights within the extended terminal area. A set of approaches is described for addressing a deterministic and a probabilistic version of this problem. For the deterministic case, where airport capacities are known and fixed, several models were developed with associated low-order polynomial-time algorithms. For general delay cost functions, these algorithms find an optimal solution. Under a particular natural assumption regarding the delay cost function, an extremely fast (O(n ln n)) algorithm was developed. For the probabilistic case, using an estimated probability distribution of airport capacities, a model was developed with an associated low-order polynomial-time heuristic algorithm with useful properties.
Consensus time and conformity in the adaptive voter model
NASA Astrophysics Data System (ADS)
Rogers, Tim; Gross, Thilo
2013-09-01
The adaptive voter model is a paradigmatic model in the study of opinion formation. Here we propose an extension for this model, in which conflicts are resolved by obtaining another opinion, and analytically study the time required for consensus to emerge. Our results shed light on the rich phenomenology of both the original and extended adaptive voter models, including a dynamical phase transition in the scaling behavior of the mean time to consensus.
Adaptive multimode signal reconstruction from time-frequency representations.
Meignen, Sylvain; Oberlin, Thomas; Depalle, Philippe; Flandrin, Patrick; McLaughlin, Stephen
2016-04-13
This paper discusses methods for the adaptive reconstruction of the modes of multicomponent AM-FM signals by their time-frequency (TF) representation derived from their short-time Fourier transform (STFT). The STFT of an AM-FM component or mode spreads the information relative to that mode in the TF plane around curves commonly called ridges. An alternative view is to consider a mode as a particular TF domain termed a basin of attraction. Here we discuss two new approaches to mode reconstruction. The first determines the ridge associated with a mode by considering the location where the direction of the reassignment vector sharply changes, the technique used to determine the basin of attraction being directly derived from that used for ridge extraction. A second uses the fact that the STFT of a signal is fully characterized by its zeros (and then the particular distribution of these zeros for Gaussian noise) to deduce an algorithm to compute the mode domains. For both techniques, mode reconstruction is then carried out by simply integrating the information inside these basins of attraction or domains. PMID:26953184
Local-time representation of path integrals
NASA Astrophysics Data System (ADS)
Jizba, Petr; Zatloukal, Václav
2015-12-01
We derive a local-time path-integral representation for a generic one-dimensional time-independent system. In particular, we show how to rephrase the matrix elements of the Bloch density matrix as a path integral over x -dependent local-time profiles. The latter quantify the time that the sample paths x (t ) in the Feynman path integral spend in the vicinity of an arbitrary point x . Generalization of the local-time representation that includes arbitrary functionals of the local time is also provided. We argue that the results obtained represent a powerful alternative to the traditional Feynman-Kac formula, particularly in the high- and low-temperature regimes. To illustrate this point, we apply our local-time representation to analyze the asymptotic behavior of the Bloch density matrix at low temperatures. Further salient issues, such as connections with the Sturm-Liouville theory and the Rayleigh-Ritz variational principle, are also discussed.
A novel online adaptive time delay identification technique
NASA Astrophysics Data System (ADS)
Bayrak, Alper; Tatlicioglu, Enver
2016-05-01
Time delay is a phenomenon which is common in signal processing, communication, control applications, etc. The special feature of time delay that makes it attractive is that it is a commonly faced problem in many systems. A literature search on time-delay identification highlights the fact that most studies focused on numerical solutions. In this study, a novel online adaptive time-delay identification technique is proposed. This technique is based on an adaptive update law through a minimum-maximum strategy which is firstly applied to time-delay identification. In the design of the adaptive identification law, Lyapunov-based stability analysis techniques are utilised. Several numerical simulations were conducted with Matlab/Simulink to evaluate the performance of the proposed technique. It is numerically demonstrated that the proposed technique works efficiently in identifying both constant and disturbed time delays, and is also robust to measurement noise.
Efficient time integration in dislocation dynamics
NASA Astrophysics Data System (ADS)
Sills, Ryan B.; Cai, Wei
2014-03-01
The efficiencies of one implicit and three explicit time integrators have been compared in line dislocation dynamics simulations using two test cases: a collapsing loop and a Frank-Read (FR) source with a jog. The time-step size and computational efficiency of the explicit integrators is shown to become severely limited due to the presence of so-called stiff modes, which include the oscillatory zig-zag motion of discretization nodes and orientation fluctuations of the jog. In the stability-limited regime dictated by these stiff modes, the implicit integrator shows superior efficiency when using a Jacobian that only accounts for short-range interactions due to elasticity and line tension. However, when a stable dislocation dipole forms during a jogged FR source simulation, even the implicit integrator suffers a substantial drop in the time-step size. To restore computational efficiency, a time-step subcycling algorithm is tested, in which the nodes involved in the dipole are integrated over multiple smaller, local time steps, while the remaining nodes take a single larger, global time step. The time-step subcycling method leads to substantial efficiency gain when combined with either an implicit or an explicit integrator.
Integration, heterochrony, and adaptation in pedal digits of syndactylous marsupials
2008-01-01
Background Marsupial syndactyly is a curious morphology of the foot found in all species of diprotodontian and peramelemorph marsupials. It is traditionally defined as a condition in which digits II and III of the foot are bound by skin and are reduced. Past treatments of marsupial syndactyly have not considered the implications of this unique morphology for broader issues of digit development and evolution, and the ongoing debate regarding its phylogenetic meaning lacks a broad empirical basis. This study undertakes the first interdisciplinary characterisation of syndactyly, using variance/covariance matrix comparisons of morphometric measurements, locomotor indices, ossification sequences, and re-assessment of the largely anecdotal data on the phylogenetic distribution of tarsal/metatarsal articulations and "incipient syndactyly". Results Syndactylous digits have virtually identical variance/covariance matrices and display heterochronic ossification timing with respect to digits IV/V. However, this does not impact on overall locomotor adaptation patterns in the syndactylous foot as determined by analysis of locomotor predictor ratios. Reports of incipient syndactyly in some marsupial clades could not be confirmed; contrary to previous claims, syndactyly does not appear to impact on tarsal bone arrangement. Conclusion The results suggest that marsupial syndactyly originates from a constraint that is rooted in early digit ontogeny and results in evolution of the syndactylous digits as a highly integrated unit. Although convergent evolution appears likely, syndactyly in Diprotodontia and Peramelemorpha may occur through homologous developmental processes. We argue that the term "syndactyly" is a misnomer because the marsupial condition only superficially resembles its name-giving human soft-tissue syndactyly. PMID:18501017
Time domain and frequency domain design techniques for model reference adaptive control systems
NASA Technical Reports Server (NTRS)
Boland, J. S., III
1971-01-01
Some problems associated with the design of model-reference adaptive control systems are considered and solutions to these problems are advanced. The stability of the adapted system is a primary consideration in the development of both the time-domain and the frequency-domain design techniques. Consequentially, the use of Liapunov's direct method forms an integral part of the derivation of the design procedures. The application of sensitivity coefficients to the design of model-reference adaptive control systems is considered. An application of the design techniques is also presented.
Inherent robustness of discrete-time adaptive control systems
NASA Technical Reports Server (NTRS)
Ma, C. C. H.
1986-01-01
Global stability robustness with respect to unmodeled dynamics, arbitrary bounded internal noise, as well as external disturbance is shown to exist for a class of discrete-time adaptive control systems when the regressor vectors of these systems are persistently exciting. Although fast adaptation is definitely undesirable, so far as attaining the greatest amount of global stability robustness is concerned, slow adaptation is shown to be not necessarily beneficial. The entire analysis in this paper holds for systems with slowly varying return difference matrices; the plants in these systems need not be slowly varying.
Integrated modeling of the GMT laser tomography adaptive optics system
NASA Astrophysics Data System (ADS)
Piatrou, Piotr
2014-08-01
Laser Tomography Adaptive Optics (LTAO) is one of adaptive optics systems planned for the Giant Magellan Telescope (GMT). End-to-end simulation tools that are able to cope with the complexity and computational burden of the AO systems to be installed on the extremely large telescopes such as GMT prove to be an integral part of the GMT LTAO system development endeavors. SL95, the Fortran 95 Simulation Library, is one of the software tools successfully used for the LTAO system end-to-end simulations. The goal of SL95 project is to provide a complete set of generic, richly parameterized mathematical models for key elements of the segmented telescope wavefront control systems including both active and adaptive optics as well as the models for atmospheric turbulence, extended light sources like Laser Guide Stars (LGS), light propagation engines and closed-loop controllers. The library is implemented as a hierarchical collection of classes capable of mutual interaction, which allows one to assemble complex wavefront control system configurations with multiple interacting control channels. In this paper we demonstrate the SL95 capabilities by building an integrated end-to-end model of the GMT LTAO system with 7 control channels: LGS tomography with Adaptive Secondary and on-instrument deformable mirrors, tip-tilt and vibration control, LGS stabilization, LGS focus control, truth sensor-based dynamic noncommon path aberration rejection, pupil position control, SLODAR-like embedded turbulence profiler. The rich parameterization of the SL95 classes allows to build detailed error budgets propagating through the system multiple errors and perturbations such as turbulence-, telescope-, telescope misalignment-, segment phasing error-, non-common path-induced aberrations, sensor noises, deformable mirror-to-sensor mis-registration, vibration, temporal errors, etc. We will present a short description of the SL95 architecture, as well as the sample GMT LTAO system simulation
Personality traits, future time perspective and adaptive behavior in adolescence.
Gomes Carvalho, Renato Gil; Novo, Rosa Ferreira
2015-01-01
Several studies provide evidence of the importance of future time perspective (FTP) for individual success. However, little research addresses the relationship between FTP and personality traits, particularly if FTP can mediate their influence on behavior. In this study we analyze the mediating of FTP in the influence of personality traits on the way adolescents live their life at school. Sample consisted in 351 students, aged from 14 to 18 years-old, at different schooling levels. Instruments were the Portuguese version of the MMPI-A, particularly the PSY-5 dimensions (Aggressiveness, Psychoticism, Disconstraint, Neuroticism, Introversion), a FTP questionnaire, and a survey on school life, involving several indicators of achievement, social integration, and overall satisfaction. With the exception of Neuroticism, the results show significant mediation effects (p < .001) of FTP on most relationships between PSY-5 dimensions and school life variables. Concerning Disconstraint, FTP mediated its influence on overall satisfaction (β = -.125) and school achievement (β = -.106). In the case of Introversion, significant mediation effects occurred for interpersonal difficulties (β = .099) and participation in extracurricular activities (β = -.085). FTP was also a mediator of Psychoticism influence in overall satisfaction (β = -.094), interpersonal difficulties (β = .057), and behavior problems (β = .037). Finally, FTP mediated the influence of Aggressiveness on overall satisfaction (β = -.061), interpersonal difficulties (β = .040), achievement (β = -.052), and behavior problems (β = .023). Results are discussed considering the importance of FTP in the impact of some personality structural characteristics in students' school adaptation. PMID:25907852
Real-Time Adaptive Color Segmentation by Neural Networks
NASA Technical Reports Server (NTRS)
Duong, Tuan A.
2004-01-01
Artificial neural networks that would utilize the cascade error projection (CEP) algorithm have been proposed as means of autonomous, real-time, adaptive color segmentation of images that change with time. In the original intended application, such a neural network would be used to analyze digitized color video images of terrain on a remote planet as viewed from an uninhabited spacecraft approaching the planet. During descent toward the surface of the planet, information on the segmentation of the images into differently colored areas would be updated adaptively in real time to capture changes in contrast, brightness, and resolution, all in an effort to identify a safe and scientifically productive landing site and provide control feedback to steer the spacecraft toward that site. Potential terrestrial applications include monitoring images of crops to detect insect invasions and monitoring of buildings and other facilities to detect intruders. The CEP algorithm is reliable and is well suited to implementation in very-large-scale integrated (VLSI) circuitry. It was chosen over other neural-network learning algorithms because it is better suited to realtime learning: It provides a self-evolving neural-network structure, requires fewer iterations to converge and is more tolerant to low resolution (that is, fewer bits) in the quantization of neural-network synaptic weights. Consequently, a CEP neural network learns relatively quickly, and the circuitry needed to implement it is relatively simple. Like other neural networks, a CEP neural network includes an input layer, hidden units, and output units (see figure). As in other neural networks, a CEP network is presented with a succession of input training patterns, giving rise to a set of outputs that are compared with the desired outputs. Also as in other neural networks, the synaptic weights are updated iteratively in an effort to bring the outputs closer to target values. A distinctive feature of the CEP neural
Integrated Decision Support for Global Environmental Change Adaptation
NASA Astrophysics Data System (ADS)
Kumar, S.; Cantrell, S.; Higgins, G. J.; Marshall, J.; VanWijngaarden, F.
2011-12-01
Environmental changes are happening now that has caused concern in many parts of the world; particularly vulnerable are the countries and communities with limited resources and with natural environments that are more susceptible to climate change impacts. Global leaders are concerned about the observed phenomena and events such as Amazon deforestation, shifting monsoon patterns affecting agriculture in the mountain slopes of Peru, floods in Pakistan, water shortages in Middle East, droughts impacting water supplies and wildlife migration in Africa, and sea level rise impacts on low lying coastal communities in Bangladesh. These environmental changes are likely to get exacerbated as the temperatures rise, the weather and climate patterns change, and sea level rise continues. Large populations and billions of dollars of infrastructure could be affected. At Northrop Grumman, we have developed an integrated decision support framework for providing necessary information to stakeholders and planners to adapt to the impacts of climate variability and change at the regional and local levels. This integrated approach takes into account assimilation and exploitation of large and disparate weather and climate data sets, regional downscaling (dynamic and statistical), uncertainty quantification and reduction, and a synthesis of scientific data with demographic and economic data to generate actionable information for the stakeholders and decision makers. Utilizing a flexible service oriented architecture and state-of-the-art visualization techniques, this information can be delivered via tailored GIS portals to meet diverse set of user needs and expectations. This integrated approach can be applied to regional and local risk assessments, predictions and decadal projections, and proactive adaptation planning for vulnerable communities. In this paper we will describe this comprehensive decision support approach with selected applications and case studies to illustrate how this
Optimizing aircraft performance with adaptive, integrated flight/propulsion control
NASA Technical Reports Server (NTRS)
Smith, R. H.; Chisholm, J. D.; Stewart, J. F.
1991-01-01
The Performance-Seeking Control (PSC) integrated flight/propulsion adaptive control algorithm presented was developed in order to optimize total aircraft performance during steady-state engine operation. The PSC multimode algorithm minimizes fuel consumption at cruise conditions, while maximizing excess thrust during aircraft accelerations, climbs, and dashes, and simultaneously extending engine service life through reduction of fan-driving turbine inlet temperature upon engagement of the extended-life mode. The engine models incorporated by the PSC are continually upgraded, using a Kalman filter to detect anomalous operations. The PSC algorithm will be flight-demonstrated by an F-15 at NASA-Dryden.
Active movement restores veridical event-timing after tactile adaptation.
Tomassini, Alice; Gori, Monica; Burr, David; Sandini, Giulio; Morrone, Maria Concetta
2012-10-01
Growing evidence suggests that time in the subsecond range is tightly linked to sensory processing. Event-time can be distorted by sensory adaptation, and many temporal illusions can accompany action execution. In this study, we show that adaptation to tactile motion causes a strong contraction of the apparent duration of tactile stimuli. However, when subjects make a voluntary motor act before judging the duration, it annuls the adaptation-induced temporal distortion, reestablishing veridical event-time. The movement needs to be performed actively by the subject: passive movement of similar magnitude and dynamics has no effect on adaptation, showing that it is the motor commands themselves, rather than reafferent signals from body movement, which reset the adaptation for tactile duration. No other concomitant perceptual changes were reported (such as apparent speed or enhanced temporal discrimination), ruling out a generalized effect of body movement on somatosensory processing. We suggest that active movement resets timing mechanisms in preparation for the new scenario that the movement will cause, eliminating inappropriate biases in perceived time. Our brain seems to utilize the intention-to-move signals to retune its perceptual machinery appropriately, to prepare to extract new temporal information. PMID:22832572
Using Response Times for Item Selection in Adaptive Testing
ERIC Educational Resources Information Center
van der Linden, Wim J.
2008-01-01
Response times on items can be used to improve item selection in adaptive testing provided that a probabilistic model for their distribution is available. In this research, the author used a hierarchical modeling framework with separate first-level models for the responses and response times and a second-level model for the distribution of the…
Demonstration of a time-integrating microdosimeter
NASA Astrophysics Data System (ADS)
Famiano, M. A.; Hamby, D. M.
1997-02-01
A tissue-equivalent spherical proportional counter is used with a modified amplifier system to measure specific energy deposited from a uniform radiation field for short periods of time (on the order of microseconds to milliseconds) in order to extrapolate to dose in sub-micron tissue volumes. The signal is integrated over a variable collection time which is adjusted with a square-wave pulse. Charge from partical passages is collected on the anode during the period in which the integrator is triggered, and the signal decays quickly to zero after the integrator feedback switch resets; the process repeats for every "triggering" pulse. Measurements of energy deposited from X-rays are examined. Spectral characteristics as a function of charge collection time are observed and frequency plots of specific energy and collection time-interval are presented.
Integrated flight/propulsion control - Adaptive engine control system mode
NASA Technical Reports Server (NTRS)
Yonke, W. A.; Terrell, L. A.; Meyers, L. P.
1985-01-01
The adaptive engine control system mode (ADECS) which is developed and tested on an F-15 aircraft with PW1128 engines, using the NASA sponsored highly integrated digital electronic control program, is examined. The operation of the ADECS mode, as well as the basic control logic, the avionic architecture, and the airframe/engine interface are described. By increasing engine pressure ratio (EPR) additional thrust is obtained at intermediate power and above. To modulate the amount of EPR uptrim and to prevent engine stall, information from the flight control system is used. The performance benefits, anticipated from control integration are shown for a range of flight conditions and power settings. It is found that at higher altitudes, the ADECS mode can increase thrust as much as 12 percent, which is used for improved acceleration, improved turn rate, or sustained turn angle.
A discrete-time adaptive control scheme for robot manipulators
NASA Technical Reports Server (NTRS)
Tarokh, M.
1990-01-01
A discrete-time model reference adaptive control scheme is developed for trajectory tracking of robot manipulators. The scheme utilizes feedback, feedforward, and auxiliary signals, obtained from joint angle measurement through simple expressions. Hyperstability theory is utilized to derive the adaptation laws for the controller gain matrices. It is shown that trajectory tracking is achieved despite gross robot parameter variation and uncertainties. The method offers considerable design flexibility and enables the designer to improve the performance of the control system by adjusting free design parameters. The discrete-time adaptation algorithm is extremely simple and is therefore suitable for real-time implementation. Simulations and experimental results are given to demonstrate the performance of the scheme.
Integrated Framework for an Urban Climate Adaptation Tool
NASA Astrophysics Data System (ADS)
Omitaomu, O.; Parish, E. S.; Nugent, P.; Mei, R.; Sylvester, L.; Ernst, K.; Absar, M.
2015-12-01
Cities have an opportunity to become more resilient to future climate change through investments made in urban infrastructure today. However, most cities lack access to credible high-resolution climate change projection information needed to assess and address potential vulnerabilities from future climate variability. Therefore, we present an integrated framework for developing an urban climate adaptation tool (Urban-CAT). Urban-CAT consists of four modules. Firstly, it provides climate projections at different spatial resolutions for quantifying urban landscape. Secondly, this projected data is combined with socio-economic data using leading and lagging indicators for assessing landscape vulnerability to climate extremes (e.g., urban flooding). Thirdly, a neighborhood scale modeling approach is presented for identifying candidate areas for adaptation strategies (e.g., green infrastructure as an adaptation strategy for urban flooding). Finally, all these capabilities are made available as a web-based tool to support decision-making and communication at the neighborhood and city levels. In this paper, we present some of the methods that drive each of the modules and demo some of the capabilities available to-date using the City of Knoxville in Tennessee as a case study.
The adaptive significance of adult neurogenesis: an integrative approach
Konefal, Sarah; Elliot, Mick; Crespi, Bernard
2013-01-01
Adult neurogenesis in mammals is predominantly restricted to two brain regions, the dentate gyrus (DG) of the hippocampus and the olfactory bulb (OB), suggesting that these two brain regions uniquely share functions that mediate its adaptive significance. Benefits of adult neurogenesis across these two regions appear to converge on increased neuronal and structural plasticity that subserves coding of novel, complex, and fine-grained information, usually with contextual components that include spatial positioning. By contrast, costs of adult neurogenesis appear to center on potential for dysregulation resulting in higher risk of brain cancer or psychological dysfunctions, but such costs have yet to be quantified directly. The three main hypotheses for the proximate functions and adaptive significance of adult neurogenesis, pattern separation, memory consolidation, and olfactory spatial, are not mutually exclusive and can be reconciled into a simple general model amenable to targeted experimental and comparative tests. Comparative analysis of brain region sizes across two major social-ecological groups of primates, gregarious (mainly diurnal haplorhines, visually-oriented, and in large social groups) and solitary (mainly noctural, territorial, and highly reliant on olfaction, as in most rodents) suggest that solitary species, but not gregarious species, show positive associations of population densities and home range sizes with sizes of both the hippocampus and OB, implicating their functions in social-territorial systems mediated by olfactory cues. Integrated analyses of the adaptive significance of adult neurogenesis will benefit from experimental studies motivated and structured by ecologically and socially relevant selective contexts. PMID:23882188
Multirate Time Integration for Compressible Atmospheric Flow
NASA Astrophysics Data System (ADS)
Wensch, Jörg; Knoth, Oswald; Galant, Alexander
2008-09-01
We generalise split-explicit Runge-Kutta methods utilised in atmospheric dynamics simulation where fast sub-processes (sound waves) are integrated by small time steps. The inclusion of fixed tendencies of previous stages leads to an improvement of the stability barrier for the acoustics equation by a factor of two. Order and stability analysis is based on the assumption of exact integration of fast subprocesses.
Are integral controllers adapted to the new era of ELT adaptive optics?
NASA Astrophysics Data System (ADS)
Conan, J.-M.; Raynaud, H.-F.; Kulcsár, C.; Meimon, S.
2011-09-01
With ELTs we are now entering a new era in adaptive optics developments. Meeting unprecedented level of performance with incredibly complex systems implies reconsidering AO concepts at all levels, including controller design. Concentrating mainly on temporal aspects, one may wonder if integral controllers remain an adequate solution. This question is all the more important that, with ever larger degrees of freedom, one may be tempted to discard more sophisticated approaches because they are deemed too complex to implement. The respective performance of integrator versus LQG control should therefore be carefully evaluated in the ELT context. We recall for instance the impressive correction improvement brought by such controllers for the rejection of windshake and vibration components. LQG controller significantly outperforms the integrator because its disturbance rejection transfer function closely matches the energy concentration, respectively at low temporal frequencies for windshake, and around localized resonant peaks for vibrations. The application to turbulent modes should also be investigated, especially for very low spatial frequencies now explored on the huge ELT pupil. The questions addressed here are: 1/ How do integral and LQG controllers compare in terms of performance for a given sampling frequency and noise level?; 2/ Could we relax sampling frequency with LQG control?; 3/ Does a mode to mode adaptation of temporal rejection bring significant performance improvement?; 4/ Which modes particularly benefit from this fine tuning of the rejection transfer function? Based on a simplified ELT AO configuration, and through a simple analytical formulation, performance is evaluated for several control approaches. Various assumptions concerning the perturbation parameters (seeing and outer-scale value, windshake amplitude) are considered. Bode's integral theorem allows intuitive understanding of the results. Practical implementation and computation complexity
Planning for an uncertain future - Monitoring, integration, and adaptation
Webb, Richard M. T., (Edited By); Semmens, Darius J.
2009-01-01
The 6.7 billion human inhabitants of the earth have the ability to drastically alter ecosystems and the populations of species that have taken eons to evolve. By better understanding how our actions affect the environment, we stand a better chance of designing successful strategies to manage ecosystems sustainably. Toward this end, the Third Interagency Conference on Research in the Watersheds (ICRW) was convened in Estes Park, CO, on September 8-11, 2008. The Conference provided a forum to present adaptive management as a practical tool for learning how to manage complex ecosystems more sustainably. Further complexity introduced by spatially variable and continuously changing environmental drivers favors this management approach because of its emphasis on adaptation in response to changing conditions or ineffective actions. For climate change in particular, an adaptive approach can more effectively accommodate the uncertainty in future climate scenarios. Scenarios compiled by the Intergovernmental Panel on Climate Change are built on distinct economic, energy, and societal models. The scenarios predict potential changes in greenhouse gases, temperature, precipitation, and atmospheric aerosols, which would have direct or indirect impacts on the timing, volume, and quality of runoff, vegetation, snowpack, stream temperature, groundwater, thawing permafrost, and icecaps. Through presentations and field trips, researchers and stakeholders described how their findings and issues fit into the adaptive management 'learning by doing' paradigm of Assess > Design > Implement > Monitor > Evaluate > Adjust > Assess.
Time Adaptation Shows Duration Selectivity in the Human Parietal Cortex
Hayashi, Masamichi J.; Ditye, Thomas; Harada, Tokiko; Hashiguchi, Maho; Sadato, Norihiro; Carlson, Synnöve; Walsh, Vincent; Kanai, Ryota
2015-01-01
Although psychological and computational models of time estimation have postulated the existence of neural representations tuned for specific durations, empirical evidence of this notion has been lacking. Here, using a functional magnetic resonance imaging (fMRI) adaptation paradigm, we show that the inferior parietal lobule (IPL) (corresponding to the supramarginal gyrus) exhibited reduction in neural activity due to adaptation when a visual stimulus of the same duration was repeatedly presented. Adaptation was strongest when stimuli of identical durations were repeated, and it gradually decreased as the difference between the reference and test durations increased. This tuning property generalized across a broad range of durations, indicating the presence of general time-representation mechanisms in the IPL. Furthermore, adaptation was observed irrespective of the subject’s attention to time. Repetition of a nontemporal aspect of the stimulus (i.e., shape) did not produce neural adaptation in the IPL. These results provide neural evidence for duration-tuned representations in the human brain. PMID:26378440
The Effects of Predator Arrival Timing on Adaptive Radiation (Invited)
NASA Astrophysics Data System (ADS)
Borden, J.; Knope, M. L.; Fukami, T.
2009-12-01
Much of Earth’s biodiversity is thought to have arisen by adaptive radiation, the rapid diversification of a single ancestral species to fill a wide-variety of ecological niches. Both theory and empirical evidence have long supported competition for limited resources as a primary driver of adaptive radiation. While predation has also been postulated to be an important selective force during radiation, empirical evidence is surprisingly scant and its role remains controversial. However, two recent empirical studies suggest that predation can promote divergence during adaptive radiation. Using an experimental laboratory microcosm system, we examined how predator arrival timing affects the rate and extent of diversification during adaptive radiation. We varied the introduction timing of a protozoan predator (Tetrahymena thermophila) into populations of the bacteria Pseudomonas flourescens, which is known for its ability to undergo rapid adaptive radiation in aqueous microcosms. While our results show that predator arrival timing may have a significant impact on the rate, but not extent, of diversification, these results are tenuous and should be interpreted with caution, as the protozoan predators died early in the majority of our treatments, hampering our ability for comparison across treatments. Additionally, the abundance of newly derived bacterial genotypes was markedly lower in all treatments than observed in previous experiments utilizing this microbial experimental evolution system. To address these shortcomings, we will be repeating the experiment in the near future to further explore the impact of predator arrival timing on adaptive radiation. Smooth Morph and small-Wrinkly Spreader Pseudomonas flourescens diversification in the 96 hour treatment. Day 10, diluted to 1e-5.
Local-time representation of path integrals.
Jizba, Petr; Zatloukal, Václav
2015-12-01
We derive a local-time path-integral representation for a generic one-dimensional time-independent system. In particular, we show how to rephrase the matrix elements of the Bloch density matrix as a path integral over x-dependent local-time profiles. The latter quantify the time that the sample paths x(t) in the Feynman path integral spend in the vicinity of an arbitrary point x. Generalization of the local-time representation that includes arbitrary functionals of the local time is also provided. We argue that the results obtained represent a powerful alternative to the traditional Feynman-Kac formula, particularly in the high- and low-temperature regimes. To illustrate this point, we apply our local-time representation to analyze the asymptotic behavior of the Bloch density matrix at low temperatures. Further salient issues, such as connections with the Sturm-Liouville theory and the Rayleigh-Ritz variational principle, are also discussed. PMID:26764662
ADAPTIVE DATA ANALYSIS OF COMPLEX FLUCTUATIONS IN PHYSIOLOGIC TIME SERIES
PENG, C.-K.; COSTA, MADALENA; GOLDBERGER, ARY L.
2009-01-01
We introduce a generic framework of dynamical complexity to understand and quantify fluctuations of physiologic time series. In particular, we discuss the importance of applying adaptive data analysis techniques, such as the empirical mode decomposition algorithm, to address the challenges of nonlinearity and nonstationarity that are typically exhibited in biological fluctuations. PMID:20041035
Hippocampal “Time Cells”: Time versus Path Integration
Kraus, Benjamin J.; Robinson, Robert J.; White, John A.; Eichenbaum, Howard; Hasselmo, Michael E.
2014-01-01
SUMMARY Recent studies have reported the existence of hippocampal “time cells,” neurons that fire at particular moments during periods when behavior and location are relatively constant. However, an alternative explanation of apparent time coding is that hippocampal neurons “path integrate” to encode the distance an animal has traveled. Here, we examined hippocampal neuronal firing patterns as rats ran in place on a treadmill, thus “clamping” behavior and location, while we varied the treadmill speed to distinguish time elapsed from distance traveled. Hippocampal neurons were strongly influenced by time and distance, and less so by minor variations in location. Furthermore, the activity of different neurons reflected integration over time and distance to varying extents, with most neurons strongly influenced by both factors and some significantly influenced by only time or distance. Thus, hippocampal neuronal networks captured both the organization of time and distance in a situation where these dimensions dominated an ongoing experience. PMID:23707613
Adaptive integral dynamic surface control of a hypersonic flight vehicle
NASA Astrophysics Data System (ADS)
Aslam Butt, Waseem; Yan, Lin; Amezquita S., Kendrick
2015-07-01
In this article, non-linear adaptive dynamic surface air speed and flight path angle control designs are presented for the longitudinal dynamics of a flexible hypersonic flight vehicle. The tracking performance of the control design is enhanced by introducing a novel integral term that caters to avoiding a large initial control signal. To ensure feasibility, the design scheme incorporates magnitude and rate constraints on the actuator commands. The uncertain non-linear functions are approximated by an efficient use of the neural networks to reduce the computational load. A detailed stability analysis shows that all closed-loop signals are uniformly ultimately bounded and the ? tracking performance is guaranteed. The robustness of the design scheme is verified through numerical simulations of the flexible flight vehicle model.
Integrated Power Adapter: Isolated Converter with Integrated Passives and Low Material Stress
2010-09-01
ADEPT Project: CPES at Virginia Tech is developing an extremely efficient power converter that could be used in power adapters for small, lightweight laptops and other types of mobile electronic devices. Power adapters convert electrical energy into useable power for an electronic device, and they currently waste a lot of energy when they are plugged into an outlet to power up. CPES at Virginia Tech is integrating high-density capacitors, new magnetic materials, high-frequency integrated circuits, and a constant-flux transformer to create its efficient power converter. The high-density capacitors enable the power adapter to store more energy. The new magnetic materials also increase energy storage, and they can be precisely dispensed using a low-cost ink-jet printer which keeps costs down. The high-frequency integrated circuits can handle more power, and they can handle it more efficiently. And, the constant-flux transformer processes a consistent flow of electrical current, which makes the converter more efficient.
An adaptive robust controller for time delay maglev transportation systems
NASA Astrophysics Data System (ADS)
Milani, Reza Hamidi; Zarabadipour, Hassan; Shahnazi, Reza
2012-12-01
For engineering systems, uncertainties and time delays are two important issues that must be considered in control design. Uncertainties are often encountered in various dynamical systems due to modeling errors, measurement noises, linearization and approximations. Time delays have always been among the most difficult problems encountered in process control. In practical applications of feedback control, time delay arises frequently and can severely degrade closed-loop system performance and in some cases, drives the system to instability. Therefore, stability analysis and controller synthesis for uncertain nonlinear time-delay systems are important both in theory and in practice and many analytical techniques have been developed using delay-dependent Lyapunov function. In the past decade the magnetic and levitation (maglev) transportation system as a new system with high functionality has been the focus of numerous studies. However, maglev transportation systems are highly nonlinear and thus designing controller for those are challenging. The main topic of this paper is to design an adaptive robust controller for maglev transportation systems with time-delay, parametric uncertainties and external disturbances. In this paper, an adaptive robust control (ARC) is designed for this purpose. It should be noted that the adaptive gain is derived from Lyapunov-Krasovskii synthesis method, therefore asymptotic stability is guaranteed.
Real time adaptive filtering for digital X-ray applications.
Bockenbach, Olivier; Mangin, Michel; Schuberth, Sebastian
2006-01-01
Over the last decade, many methods for adaptively filtering a data stream have been proposed. Those methods have applications in two dimensional imaging as well as in three dimensional image reconstruction. Although the primary objective of this filtering technique is to reduce the noise while avoiding to blur the edges, diagnostic, automated segmentation and surgery show a growing interest in enhancing the features contained in the image flow. Most of the methods proposed so far emerged from thorough studies of the physics of the considered modality and therefore show only a marginal capability to be extended across modalities. Moreover, adaptive filtering belongs to the family of processing intensive algorithms. Existing technology has often driven to simplifications and modality specific optimization to sustain the expected performances. In the specific case of real time digital X-ray as used surgery, the system has to sustain a throughput of 30 frames per second. In this study, we take a generalized approach for adaptive filtering based on multiple oriented filters. Mapping the filtering part to the embedded real time image processing while a user/application defined adaptive recombination of the filter outputs allow to change the smoothing and edge enhancement properties of the filter without changing the oriented filter parameters. We have implemented the filtering on a Cell Broadband Engine processor and the adaptive recombination on an off-the-shelf PC, connected via Gigabit Ethernet. This implementation is capable of filtering images of 5122 pixels at a throughput in excess of 40 frames per second while allowing to change the parameters in real time. PMID:17354937
Frequency Adaptability and Waveform Design for OFDM Radar Space-Time Adaptive Processing
Sen, Satyabrata; Glover, Charles Wayne
2012-01-01
We propose an adaptive waveform design technique for an orthogonal frequency division multiplexing (OFDM) radar signal employing a space-time adaptive processing (STAP) technique. We observe that there are inherent variabilities of the target and interference responses in the frequency domain. Therefore, the use of an OFDM signal can not only increase the frequency diversity of our system, but also improve the target detectability by adaptively modifying the OFDM coefficients in order to exploit the frequency-variabilities of the scenario. First, we formulate a realistic OFDM-STAP measurement model considering the sparse nature of the target and interference spectra in the spatio-temporal domain. Then, we show that the optimal STAP-filter weight-vector is equal to the generalized eigenvector corresponding to the minimum generalized eigenvalue of the interference and target covariance matrices. With numerical examples we demonstrate that the resultant OFDM-STAP filter-weights are adaptable to the frequency-variabilities of the target and interference responses, in addition to the spatio-temporal variabilities. Hence, by better utilizing the frequency variabilities, we propose an adaptive OFDM-waveform design technique, and consequently gain a significant amount of STAP-performance improvement.
Resource Management for Real-Time Adaptive Agents
NASA Technical Reports Server (NTRS)
Welch, Lonnie; Chelberg, David; Pfarr, Barbara; Fleeman, David; Parrott, David; Tan, Zhen-Yu; Jain, Shikha; Drews, Frank; Bruggeman, Carl; Shuler, Chris
2003-01-01
Increased autonomy and automation in onboard flight systems offer numerous potential benefits, including cost reduction and greater flexibility. The existence of generic mechanisms for automation is critical for handling unanticipated science events and anomalies where limitations in traditional control software with fixed, predetermined algorithms can mean loss of science data and missed opportunities for observing important terrestrial events. We have developed such a mechanism by adding a Hierarchical Agent-based ReaLTime technology (HART) extension to our Dynamic Resource Management (DRM) middleware. Traditional DRM provides mechanisms to monitor the realtime performance of distributed applications and to move applications among processors to improve real-time performance. In the HART project we have designed and implemented a performance adaptation mechanism to improve reaktime performance. To use this mechanism, applications are developed that can run at various levels of quality. The DRM can choose a setting for the quality level of an application dynamically at run-time in order to manage satellite resource usage more effectively. A groundbased prototype of a satellite system that captures and processes images has also been developed as part of this project to be used as a benchmark for evaluating the resource management framework A significant enhancement of this generic mission-independent framework allows scientists to specify the utility, or "scientific benefit," of science observations under various conditions like cloud cover and compression method. The resource manager then uses these benefit tables to determine in redtime how to set the quality levels for applications to maximize overall system utility as defined by the scientists running the mission. We also show how maintenance functions llke health and safety data can be integrated into the utility framework. Once thls framework has been certified for missions and successfully flight tested it
Adaptive time steps in trajectory surface hopping simulations.
Spörkel, Lasse; Thiel, Walter
2016-05-21
Trajectory surface hopping (TSH) simulations are often performed in combination with active-space multi-reference configuration interaction (MRCI) treatments. Technical problems may arise in such simulations if active and inactive orbitals strongly mix and switch in some particular regions. We propose to use adaptive time steps when such regions are encountered in TSH simulations. For this purpose, we present a computational protocol that is easy to implement and increases the computational effort only in the critical regions. We test this procedure through TSH simulations of a GFP chromophore model (OHBI) and a light-driven rotary molecular motor (F-NAIBP) on semiempirical MRCI potential energy surfaces, by comparing the results from simulations with adaptive time steps to analogous ones with constant time steps. For both test molecules, the number of successful trajectories without technical failures rises significantly, from 53% to 95% for OHBI and from 25% to 96% for F-NAIBP. The computed excited-state lifetime remains essentially the same for OHBI and increases somewhat for F-NAIBP, and there is almost no change in the computed quantum efficiency for internal rotation in F-NAIBP. We recommend the general use of adaptive time steps in TSH simulations with active-space CI methods because this will help to avoid technical problems, increase the overall efficiency and robustness of the simulations, and allow for a more complete sampling. PMID:27208937
Adaptive time steps in trajectory surface hopping simulations
NASA Astrophysics Data System (ADS)
Spörkel, Lasse; Thiel, Walter
2016-05-01
Trajectory surface hopping (TSH) simulations are often performed in combination with active-space multi-reference configuration interaction (MRCI) treatments. Technical problems may arise in such simulations if active and inactive orbitals strongly mix and switch in some particular regions. We propose to use adaptive time steps when such regions are encountered in TSH simulations. For this purpose, we present a computational protocol that is easy to implement and increases the computational effort only in the critical regions. We test this procedure through TSH simulations of a GFP chromophore model (OHBI) and a light-driven rotary molecular motor (F-NAIBP) on semiempirical MRCI potential energy surfaces, by comparing the results from simulations with adaptive time steps to analogous ones with constant time steps. For both test molecules, the number of successful trajectories without technical failures rises significantly, from 53% to 95% for OHBI and from 25% to 96% for F-NAIBP. The computed excited-state lifetime remains essentially the same for OHBI and increases somewhat for F-NAIBP, and there is almost no change in the computed quantum efficiency for internal rotation in F-NAIBP. We recommend the general use of adaptive time steps in TSH simulations with active-space CI methods because this will help to avoid technical problems, increase the overall efficiency and robustness of the simulations, and allow for a more complete sampling.
Discrete-time minimal control synthesis adaptive algorithm
NASA Astrophysics Data System (ADS)
di Bernardo, M.; di Gennaro, F.; Olm, J. M.; Santini, S.
2010-12-01
This article proposes a discrete-time Minimal Control Synthesis (MCS) algorithm for a class of single-input single-output discrete-time systems written in controllable canonical form. As it happens with the continuous-time MCS strategy, the algorithm arises from the family of hyperstability-based discrete-time model reference adaptive controllers introduced in (Landau, Y. (1979), Adaptive Control: The Model Reference Approach, New York: Marcel Dekker, Inc.) and is able to ensure tracking of the states of a given reference model with minimal knowledge about the plant. The control design shows robustness to parameter uncertainties, slow parameter variation and matched disturbances. Furthermore, it is proved that the proposed discrete-time MCS algorithm can be used to control discretised continuous-time plants with the same performance features. Contrary to previous discrete-time implementations of the continuous-time MCS algorithm, here a formal proof of asymptotic stability is given for generic n-dimensional plants in controllable canonical form. The theoretical approach is validated by means of simulation results.
Adaptive Sensing of Time Series with Application to Remote Exploration
NASA Technical Reports Server (NTRS)
Thompson, David R.; Cabrol, Nathalie A.; Furlong, Michael; Hardgrove, Craig; Low, Bryan K. H.; Moersch, Jeffrey; Wettergreen, David
2013-01-01
We address the problem of adaptive informationoptimal data collection in time series. Here a remote sensor or explorer agent throttles its sampling rate in order to track anomalous events while obeying constraints on time and power. This problem is challenging because the agent has limited visibility -- all collected datapoints lie in the past, but its resource allocation decisions require predicting far into the future. Our solution is to continually fit a Gaussian process model to the latest data and optimize the sampling plan on line to maximize information gain. We compare the performance characteristics of stationary and nonstationary Gaussian process models. We also describe an application based on geologic analysis during planetary rover exploration. Here adaptive sampling can improve coverage of localized anomalies and potentially benefit mission science yield of long autonomous traverses.
Sparse time-frequency decomposition based on dictionary adaptation.
Hou, Thomas Y; Shi, Zuoqiang
2016-04-13
In this paper, we propose a time-frequency analysis method to obtain instantaneous frequencies and the corresponding decomposition by solving an optimization problem. In this optimization problem, the basis that is used to decompose the signal is not known a priori. Instead, it is adapted to the signal and is determined as part of the optimization problem. In this sense, this optimization problem can be seen as a dictionary adaptation problem, in which the dictionary is adaptive to one signal rather than a training set in dictionary learning. This dictionary adaptation problem is solved by using the augmented Lagrangian multiplier (ALM) method iteratively. We further accelerate the ALM method in each iteration by using the fast wavelet transform. We apply our method to decompose several signals, including signals with poor scale separation, signals with outliers and polluted by noise and a real signal. The results show that this method can give accurate recovery of both the instantaneous frequencies and the intrinsic mode functions. PMID:26953172
Time delay and integration detectors using charge transfer devices
NASA Technical Reports Server (NTRS)
Mccann, D. H.; White, M. H.; Turly, A. P.
1981-01-01
An imaging system comprises a multi-channel matrix array of CCD devices wherein a number of sensor cells (pixels) in each channel are subdivided and operated in discrete intercoupled groups of subarrays with a readout CCD shift register terminating each end of the channels. Clock voltages, applied to the subarrays, selectively cause charge signal flow in each subarray in either direction independent of the other subarrays. By selective application of four phase clock voltages, either one, two or all three of the sections subarray sections cause charge signal flow in one direction, while the remainder cause charge signal flow in the opposite direction. This creates a form of selective electronic exposure control which provides an effective variable time delay and integration of three, six or nine sensor cells or integration stages. The device is constructed on a semiconductor sustrate with a buried channel and is adapted for front surface imaging through transparent doped tin oxide gates.
Integrated Planning for Telepresence with Time Delays
NASA Technical Reports Server (NTRS)
Johnston, Mark D.; Rabe, Kenneth J.
2006-01-01
Teleoperation of remote robotic systems over time delays in the range of 2-10 seconds poses a unique set of challenges. In the context of a supervisory control system for the JSC Robonaut humanoid robot, we have developed an 'intelligent assistant' that integrates an Artificial Intelligence planner (JSHOP2) with execution monitoring of the state of both the human supervisor and the remote robot. The assistant reasons simultaneously about the world state on both sides of the time delay, which represents a novel application of this technology. The purpose of the assistant is to provide advice to the human supervisor about current and future activities, derived from a sequence of high-level goals to be achieved. To do this, the assistant must simultaneously monitor and react to various data sources, including actions taken by the supervisor who is issuing commands to the robot (e.g. with a data glove), actions taken by the robot, and the environment of the robot, both as currently perceived over the time delay, along with the current sequence of goals. We have developed a 'leader/follower' software architecture to handle the dual time-shifted streams of execution feedback. In this paper we describe the integrated planner and its executive, and how it operates in normal and anomaly situations.
Broom, Donald M
2006-01-01
The term adaptation is used in biology in three different ways. It may refer to changes which occur at the cell and organ level, or at the individual level, or at the level of gene action and evolutionary processes. Adaptation by cells, especially nerve cells helps in: communication within the body, the distinguishing of stimuli, the avoidance of overload and the conservation of energy. The time course and complexity of these mechanisms varies. Adaptive characters of organisms, including adaptive behaviours, increase fitness so this adaptation is evolutionary. The major part of this paper concerns adaptation by individuals and its relationships to welfare. In complex animals, feed forward control is widely used. Individuals predict problems and adapt by acting before the environmental effect is substantial. Much of adaptation involves brain control and animals have a set of needs, located in the brain and acting largely via motivational mechanisms, to regulate life. Needs may be for resources but are also for actions and stimuli which are part of the mechanism which has evolved to obtain the resources. Hence pigs do not just need food but need to be able to carry out actions like rooting in earth or manipulating materials which are part of foraging behaviour. The welfare of an individual is its state as regards its attempts to cope with its environment. This state includes various adaptive mechanisms including feelings and those which cope with disease. The part of welfare which is concerned with coping with pathology is health. Disease, which implies some significant effect of pathology, always results in poor welfare. Welfare varies over a range from very good, when adaptation is effective and there are feelings of pleasure or contentment, to very poor. A key point concerning the concept of individual adaptation in relation to welfare is that welfare may be good or poor while adaptation is occurring. Some adaptation is very easy and energetically cheap and
Essays on agricultural adaptation to climate change and ethanol market integration in the U.S
NASA Astrophysics Data System (ADS)
Aisabokhae, Ruth Ada
Climate factors like precipitation and temperature, being closely intertwined with agriculture, make a changing climate a big concern for the entire human race and its basic survival. Adaptation to climate is a long-running characteristic of agriculture evidenced by the varying types and forms of agricultural enterprises associated with differing climatic conditions. Nevertheless climate change poses a substantial, additional adaptation challenge for agriculture. Mitigation encompasses efforts to reduce the current and future extent of climate change. Biofuels production, for instance, expands agriculture's role in climate change mitigation. This dissertation encompasses adaptation and mitigation strategies as a response to climate change in the U.S. by examining comprehensively scientific findings on agricultural adaptation to climate change; developing information on the costs and benefits of select adaptations to examine what adaptations are most desirable, for which society can further devote its resources; and studying how ethanol prices are interrelated across, and transmitted within the U.S., and the markets that play an important role in these dynamics. Quantitative analysis using the Forestry and Agricultural Sector Optimization Model (FASOM) shows adaptation to be highly beneficial to agriculture. On-farm varietal and other adaptations contributions outweigh a mix shift northwards significantly, implying progressive technical change and significant returns to adaptation research and investment focused on farm management and varietal adaptations could be quite beneficial over time. Northward shift of corn-acre weighted centroids observed indicates that substantial production potential may shift across regions with the possibility of less production in the South, and more in the North, and thereby, potential redistribution of income. Time series techniques employed to study ethanol price dynamics show that the markets studied are co-integrated and strongly
Real-time Adaptive Control Using Neural Generalized Predictive Control
NASA Technical Reports Server (NTRS)
Haley, Pam; Soloway, Don; Gold, Brian
1999-01-01
The objective of this paper is to demonstrate the feasibility of a Nonlinear Generalized Predictive Control algorithm by showing real-time adaptive control on a plant with relatively fast time-constants. Generalized Predictive Control has classically been used in process control where linear control laws were formulated for plants with relatively slow time-constants. The plant of interest for this paper is a magnetic levitation device that is nonlinear and open-loop unstable. In this application, the reference model of the plant is a neural network that has an embedded nominal linear model in the network weights. The control based on the linear model provides initial stability at the beginning of network training. In using a neural network the control laws are nonlinear and online adaptation of the model is possible to capture unmodeled or time-varying dynamics. Newton-Raphson is the minimization algorithm. Newton-Raphson requires the calculation of the Hessian, but even with this computational expense the low iteration rate make this a viable algorithm for real-time control.
Adaptive Sampling of Time Series During Remote Exploration
NASA Technical Reports Server (NTRS)
Thompson, David R.
2012-01-01
This work deals with the challenge of online adaptive data collection in a time series. A remote sensor or explorer agent adapts its rate of data collection in order to track anomalous events while obeying constraints on time and power. This problem is challenging because the agent has limited visibility (all its datapoints lie in the past) and limited control (it can only decide when to collect its next datapoint). This problem is treated from an information-theoretic perspective, fitting a probabilistic model to collected data and optimizing the future sampling strategy to maximize information gain. The performance characteristics of stationary and nonstationary Gaussian process models are compared. Self-throttling sensors could benefit environmental sensor networks and monitoring as well as robotic exploration. Explorer agents can improve performance by adjusting their data collection rate, preserving scarce power or bandwidth resources during uninteresting times while fully covering anomalous events of interest. For example, a remote earthquake sensor could conserve power by limiting its measurements during normal conditions and increasing its cadence during rare earthquake events. A similar capability could improve sensor platforms traversing a fixed trajectory, such as an exploration rover transect or a deep space flyby. These agents can adapt observation times to improve sample coverage during moments of rapid change. An adaptive sampling approach couples sensor autonomy, instrument interpretation, and sampling. The challenge is addressed as an active learning problem, which already has extensive theoretical treatment in the statistics and machine learning literature. A statistical Gaussian process (GP) model is employed to guide sample decisions that maximize information gain. Nonsta tion - ary (e.g., time-varying) covariance relationships permit the system to represent and track local anomalies, in contrast with current GP approaches. Most common GP models
Rapid adaptation of multisensory integration in vestibular pathways.
Carriot, Jerome; Jamali, Mohsen; Cullen, Kathleen E
2015-01-01
Sensing gravity is vital for our perception of spatial orientation, the control of upright posture, and generation of our everyday activities. When an astronaut transitions to microgravity or returns to earth, the vestibular input arising from self-motion will not match the brain's expectation. Our recent neurophysiological studies have provided insight into how the nervous system rapidly reorganizes when vestibular input becomes unreliable by both (1) updating its internal model of the sensory consequences of motion and (2) up-weighting more reliable extra-vestibular information. These neural strategies, in turn, are linked to improvements in sensorimotor performance (e.g., gaze and postural stability, locomotion, orienting) and perception characterized by similar time courses. We suggest that furthering our understanding of the neural mechanisms that underlie sensorimotor adaptation will have important implications for optimizing training programs for astronauts before and after space exploration missions and for the design of goal-oriented rehabilitation for patients. PMID:25932009
Rapid adaptation of multisensory integration in vestibular pathways
Carriot, Jerome; Jamali, Mohsen; Cullen, Kathleen E.
2015-01-01
Sensing gravity is vital for our perception of spatial orientation, the control of upright posture, and generation of our everyday activities. When an astronaut transitions to microgravity or returns to earth, the vestibular input arising from self-motion will not match the brain's expectation. Our recent neurophysiological studies have provided insight into how the nervous system rapidly reorganizes when vestibular input becomes unreliable by both (1) updating its internal model of the sensory consequences of motion and (2) up-weighting more reliable extra-vestibular information. These neural strategies, in turn, are linked to improvements in sensorimotor performance (e.g., gaze and postural stability, locomotion, orienting) and perception characterized by similar time courses. We suggest that furthering our understanding of the neural mechanisms that underlie sensorimotor adaptation will have important implications for optimizing training programs for astronauts before and after space exploration missions and for the design of goal-oriented rehabilitation for patients. PMID:25932009
Adaptive control of systems with unknown time delays
NASA Astrophysics Data System (ADS)
Nelson, James P.
Control systems, on earth or in outer-space, may exhibit time delays in their dynamic behavior. Aerospace control systems must be able to operate in the presence of time delays both internal to the system and in its inputs and outputs. These delays are often introduced via systems controlled through a network, by information, energy or mass transport phenomena, but can also be caused by computer processing time or by the accumulation of time lags in a number of simple dynamic systems connected in series. When a dynamic system is subject to a time delay, unlike other parameters, this affects the temporal characteristics of the system and exact control over system operation cannot be strictly implemented. Systems with significant time delays are difficult to control using standard feedback controllers. The United States Air Force Research Laboratory (AFRL) is considering the use of router-based data networks on-board next generation satellites and in decentralized control architectures. This approach has the potential to introduce non-constant and non-deterministic communications delays into feedback control loops that make use of these data networks. The desire for rapid deployment of new spacecraft architectures will also introduce many other control issues as the rigorous measurement, calibration and performance tests usually conducted on spacecraft systems to develop a highly precise dynamic model will need to be drastically shortened due to the desired abbreviated build and launch schedule. Due to limited testing and system identification, the spacecraft model will have uncertainties/perturbations from the actual plant. This will require a controller that can robustly control the non-linear dynamic model with limited plant knowledge. The problems created by the control of time delay systems and the limited plant knowledge nature of the systems of interest leads us to the concept of adaptive control. Adaptive control makes adjustment of the controllers
Integrated Planning for Telepresence with Time Delays
NASA Technical Reports Server (NTRS)
Johnston, Mark D.; Rabe, Kenneth J.
2006-01-01
Integrated planning and execution of teleoperations in space with time delays is shown. The topics include: 1) The Problem; 2) Future Robot Surgery? 3) Approach Overview; 4) Robonaut; 5) Normal Planning and Execution; 6) Planner Context; 7) Implementation; 8) Use of JSHOP2; 9) Monitoring and Testing GUI; 10) Normal sequence: first the supervisor acts; 11) then the robot; 12) Robot might be late; 13) Supervisor can work ahead; 14) Deviations from Plan; 15) Robot State Change Example; 16) Accomplished goals skipped in replan; 17) Planning continuity; 18) Supervisor Deviation From Plan; 19) Intentional Deviation; and 20) Infeasible states.
Adaptive time-frequency parametrization of epileptic spikes
NASA Astrophysics Data System (ADS)
Durka, Piotr J.
2004-05-01
Adaptive time-frequency approximations of signals have proven to be a valuable tool in electroencephalogram (EEG) analysis and research, where it is believed that oscillatory phenomena play a crucial role in the brain’s information processing. This paper extends this paradigm to the nonoscillating structures such as the epileptic EEG spikes, and presents the advantages of their parametrization in general terms such as amplitude and half-width. A simple detector of epileptic spikes in the space of these parameters, tested on a limited data set, gives very promising results. It also provides a direct distinction between randomly occurring spikes or spike/wave complexes and rhythmic discharges.
Integration of AdaptiSPECT, a small-animal adaptive SPECT imaging system
Chaix, Cécile; Kovalsky, Stephen; Kosmider, Matthew; Barrett, Harrison H.; Furenlid, Lars R.
2015-01-01
AdaptiSPECT is a pre-clinical adaptive SPECT imaging system under final development at the Center for Gamma-ray Imaging. The system incorporates multiple adaptive features: an adaptive aperture, 16 detectors mounted on translational stages, and the ability to switch between a non-multiplexed and a multiplexed imaging configuration. In this paper, we review the design of AdaptiSPECT and its adaptive features. We then describe the on-going integration of the imaging system. PMID:26347197
Quantum stopping times stochastic integral in the interacting Fock space
NASA Astrophysics Data System (ADS)
Kang, Yuanbao
2015-08-01
Following the ideas of Hudson [J. Funct. Anal. 34(2), 266-281 (1979)] and Parthasarathy and Sinha [Probab. Theory Relat. Fields 73, 317-349 (1987)], we define a quantum stopping time (QST, for short) τ in the interacting Fock space (IFS, for short), Γ, over L2(ℝ+), which is actually a spectral measure in [0, ∞] such that τ([0, t]) is an adapted process. Motivated by Parthasarathy and Sinha [Probab. Theory Relat. Fields 73, 317-349 (1987)] and Applebaum [J. Funct. Anal. 65, 273-291 (1986)], we also develop a corresponding quantum stopping time stochastic integral (QSTSI, for abbreviations) on the IFS over a subspace of L2(ℝ+) equipped with a filtration. As an application, such integral provides a useful tool for proving that Γ admits a strong factorisation, i.e., Γ = Γτ] ⊗ Γ[τ, where Γτ] and Γ[τ stand for the part "before τ" and the part "after τ," respectively. Additionally, this integral also gives rise to a natural composition operation among QST to make the space of all QSTs a semigroup.
Quantum stopping times stochastic integral in the interacting Fock space
Kang, Yuanbao
2015-08-15
Following the ideas of Hudson [J. Funct. Anal. 34(2), 266-281 (1979)] and Parthasarathy and Sinha [Probab. Theory Relat. Fields 73, 317-349 (1987)], we define a quantum stopping time (QST, for short) τ in the interacting Fock space (IFS, for short), Γ, over L{sup 2}(ℝ{sup +}), which is actually a spectral measure in [0, ∞] such that τ([0, t]) is an adapted process. Motivated by Parthasarathy and Sinha [Probab. Theory Relat. Fields 73, 317-349 (1987)] and Applebaum [J. Funct. Anal. 65, 273-291 (1986)], we also develop a corresponding quantum stopping time stochastic integral (QSTSI, for abbreviations) on the IFS over a subspace of L{sup 2}(ℝ{sup +}) equipped with a filtration. As an application, such integral provides a useful tool for proving that Γ admits a strong factorisation, i.e., Γ = Γ{sub τ]} ⊗ Γ{sub [τ}, where Γ{sub τ]} and Γ{sub [τ} stand for the part “before τ” and the part “after τ,” respectively. Additionally, this integral also gives rise to a natural composition operation among QST to make the space of all QSTs a semigroup.
Lin, Paul Tinphone; Jameson, Antony, 1934-; Baker, Timothy J.; Martinelli, Luigi
2005-01-01
An implicit multigrid-driven algorithm for two-dimensional incompressible laminar viscous flows has been coupled with a solution adaptation method and a mesh movement method for boundary movement. Time-dependent calculations are performed implicitly by regarding each time step as a steady-state problem in pseudo-time. The method of artificial compressibility is used to solve the flow equations. The solution mesh adaptation method performs local mesh refinement using an incremental Delaunay algorithm and mesh coarsening by means of edge collapse. Mesh movement is achieved by modeling the computational domain as an elastic solid and solving the equilibrium equations for the stress field. The solution adaptation method has been validated by comparison with experimental results and other computational results for low Reynolds number flow over a shedding circular cylinder. Preliminary validation of the mesh movement method has been demonstrated by a comparison with experimental results of an oscillating airfoil and with computational results for an oscillating cylinder.
NASA Astrophysics Data System (ADS)
Piacentino, Michael R.; Berends, David C.; Zhang, David C.; Gudis, Eduardo
2013-05-01
Two of the biggest challenges in designing U×V vision systems are properly representing high dynamic range scene content using low dynamic range components and reducing camera motion blur. SRI's MASI-HDR (Motion Adaptive Signal Integration-High Dynamic Range) is a novel technique for generating blur-reduced video using multiple captures for each displayed frame while increasing the effective camera dynamic range by four bits or more. MASI-HDR processing thus provides high performance video from rapidly moving platforms in real-world conditions in low latency real time, enabling even the most demanding applications on air, ground and water.
Integrating Systems Health Management with Adaptive Controls for a Utility-Scale Wind Turbine
NASA Technical Reports Server (NTRS)
Frost, Susan A.; Goebel, Kai; Trinh, Khanh V.; Balas, Mark J.; Frost, Alan M.
2011-01-01
Increasing turbine up-time and reducing maintenance costs are key technology drivers for wind turbine operators. Components within wind turbines are subject to considerable stresses due to unpredictable environmental conditions resulting from rapidly changing local dynamics. Systems health management has the aim to assess the state-of-health of components within a wind turbine, to estimate remaining life, and to aid in autonomous decision-making to minimize damage. Advanced adaptive controls can provide the mechanism to enable optimized operations that also provide the enabling technology for Systems Health Management goals. The work reported herein explores the integration of condition monitoring of wind turbine blades with contingency management and adaptive controls. Results are demonstrated using a high fidelity simulator of a utility-scale wind turbine.
An Integrated Systems Approach to Designing Climate Change Adaptation Policy in Water Resources
NASA Astrophysics Data System (ADS)
Ryu, D.; Malano, H. M.; Davidson, B.; George, B.
2014-12-01
Climate change projections are characterised by large uncertainties with rainfall variability being the key challenge in designing adaptation policies. Climate change adaptation in water resources shows all the typical characteristics of 'wicked' problems typified by cognitive uncertainty as new scientific knowledge becomes available, problem instability, knowledge imperfection and strategic uncertainty due to institutional changes that inevitably occur over time. Planning that is characterised by uncertainties and instability requires an approach that can accommodate flexibility and adaptive capacity for decision-making. An ability to take corrective measures in the event that scenarios and responses envisaged initially derive into forms at some future stage. We present an integrated-multidisciplinary and comprehensive framework designed to interface and inform science and decision making in the formulation of water resource management strategies to deal with climate change in the Musi Catchment of Andhra Pradesh, India. At the core of this framework is a dialogue between stakeholders, decision makers and scientists to define a set of plausible responses to an ensemble of climate change scenarios derived from global climate modelling. The modelling framework used to evaluate the resulting combination of climate scenarios and adaptation responses includes the surface and groundwater assessment models (SWAT & MODFLOW) and the water allocation modelling (REALM) to determine the water security of each adaptation strategy. Three climate scenarios extracted from downscaled climate models were selected for evaluation together with four agreed responses—changing cropping patterns, increasing watershed development, changing the volume of groundwater extraction and improving irrigation efficiency. Water security in this context is represented by the combination of level of water availability and its associated security of supply for three economic activities (agriculture
Robust time and frequency domain estimation methods in adaptive control
NASA Technical Reports Server (NTRS)
Lamaire, Richard Orville
1987-01-01
A robust identification method was developed for use in an adaptive control system. The type of estimator is called the robust estimator, since it is robust to the effects of both unmodeled dynamics and an unmeasurable disturbance. The development of the robust estimator was motivated by a need to provide guarantees in the identification part of an adaptive controller. To enable the design of a robust control system, a nominal model as well as a frequency-domain bounding function on the modeling uncertainty associated with this nominal model must be provided. Two estimation methods are presented for finding parameter estimates, and, hence, a nominal model. One of these methods is based on the well developed field of time-domain parameter estimation. In a second method of finding parameter estimates, a type of weighted least-squares fitting to a frequency-domain estimated model is used. The frequency-domain estimator is shown to perform better, in general, than the time-domain parameter estimator. In addition, a methodology for finding a frequency-domain bounding function on the disturbance is used to compute a frequency-domain bounding function on the additive modeling error due to the effects of the disturbance and the use of finite-length data. The performance of the robust estimator in both open-loop and closed-loop situations is examined through the use of simulations.
A low-dimensional, time-resolved and adapting model neuron.
Cartling, B
1996-07-01
A low-dimensional, time-resolved and adapting model neuron is formulated and evaluated. The model is an extension of the integrate-and-fire type of model with respect to adaptation and of a recent adapting firing-rate model with respect to time-resolution. It is obtained from detailed conductance-based models by a separation of fast and slow ionic processes of action potential generation. The model explicitly includes firing-rate regulation via the slow afterhyperpolarization phase of action potentials, which is controlled by calcium-sensitive potassium channels. It is demonstrated that the model closely reproduces the firing pattern and excitability behaviour of a detailed multicompartment conductance-based model of a neocortical pyramidal cell. The inclusion of adaptation in a model neuron is important for its capability to generate complex dynamics of networks of interconnected neurons. The time-resolution is required for studies of systems in which the temporal aspects of neural coding are important. The simplicity of the model facilitates analytical studies, insight into neurocomputational mechanisms and simulations of large-scale systems. The capability to generate complex network computations may also make the model useful in practical applications of artificial neural networks. PMID:8891839
Link flexibility: evidence for environment-dependent adaptive foraging in a food web time-series.
Henri, D C; Van Veen, F J F
2016-06-01
Temporal variability in the distribution of feeding links in a food web can be an important stabilizing factor for these complex systems. Adaptive foraging and prey choice have been hypothesized to cause this link flexibility as organisms adjust their behavior to variation in the prey community. Here, we analyze a 10-yr time series of monthly aphid-parasitoid-secondary-parasitoid networks and show that interaction strengths for polyphagous secondary parasitoids are generally biased toward the larger host species within their fundamental niche; however, in months of higher competition for hosts, size-based biases are reduced. The results corroborate a previous hypothesis stating that host selectivity of parasitoids should be correlated to the relative likelihood of egg limitation vs. time limitation. Our results evince adaptation of foraging behavior to varying conditions affects the distribution of host-parasitoid link strengths, where link-rewiring may be integral to stability in complex communities. PMID:27459769
Adaptive finite volume methods for time-dependent P.D.E.S.
Ware, J.; Berzins, M.
1995-12-31
The aim of adaptive methods for time-dependent p.d.e.s is to control the numerical error so that it is less than a user-specified tolerance. This error depends on the spatial discretization method, the spatial mesh, the method of time integration and the timestep. The spatial discretization method and positioning of the spatial mesh points should attempt to ensure that the spatial error is controlled to meet the user`s requirements. It is then desirable to integrate the o.d.e. system in time with sufficient accuracy so that the temporal error does not corrupt the spatial accuracy or the reliability of the spatial error estimates. This paper is concerned with the development of a prototype algorithm of this type, based on a cell-centered triangular finite volume scheme, for two space dimensional convection-dominated problems.
NASA Astrophysics Data System (ADS)
Grothmann, T.; Grecksch, K.; Winges, M.; Siebenhüner, B.
2013-12-01
Several case studies show that social factors like institutions, perceptions and social capital strongly affect social capacities to adapt to climate change. Together with economic and technological development they are important for building social capacities. However, there are almost no methodologies for the systematic assessment of social factors. After reviewing existing methodologies we identify the Adaptive Capacity Wheel (ACW) by Gupta et al. (2010), developed for assessing the adaptive capacity of institutions, as the most comprehensive and operationalised framework to assess social factors. The ACW differentiates 22 criteria to assess 6 dimensions: variety, learning capacity, room for autonomous change, leadership, availability of resources, fair governance. To include important psychological factors we extended the ACW by two dimensions: "adaptation motivation" refers to actors' motivation to realise, support and/or promote adaptation to climate; "adaptation belief" refers to actors' perceptions of realisability and effectiveness of adaptation measures. We applied the extended ACW to assess adaptive capacities of four sectors - water management, flood/coastal protection, civil protection and regional planning - in northwestern Germany. The assessments of adaptation motivation and belief provided a clear added value. The results also revealed some methodological problems in applying the ACW (e.g. overlap of dimensions), for which we propose methodological solutions.
NASA Astrophysics Data System (ADS)
Grothmann, T.; Grecksch, K.; Winges, M.; Siebenhüner, B.
2013-03-01
Several case studies show that "soft social factors" (e.g. institutions, perceptions, social capital) strongly affect social capacities to adapt to climate change. Many soft social factors can probably be changed faster than "hard social factors" (e.g. economic and technological development) and are therefore particularly important for building social capacities. However, there are almost no methodologies for the systematic assessment of soft social factors. Gupta et al. (2010) have developed the Adaptive Capacity Wheel (ACW) for assessing the adaptive capacity of institutions. The ACW differentiates 22 criteria to assess six dimensions: variety, learning capacity, room for autonomous change, leadership, availability of resources, fair governance. To include important psychological factors we extended the ACW by two dimensions: "adaptation motivation" refers to actors' motivation to realise, support and/or promote adaptation to climate. "Adaptation belief" refers to actors' perceptions of realisability and effectiveness of adaptation measures. We applied the extended ACW to assess adaptive capacities of four sectors - water management, flood/coastal protection, civil protection and regional planning - in North Western Germany. The assessments of adaptation motivation and belief provided a clear added value. The results also revealed some methodological problems in applying the ACW (e.g. overlap of dimensions), for which we propose methodological solutions.
Real-Time Adaptive Least-Squares Drag Minimization for Performance Adaptive Aeroelastic Wing
NASA Technical Reports Server (NTRS)
Ferrier, Yvonne L.; Nguyen, Nhan T.; Ting, Eric
2016-01-01
This paper contains a simulation study of a real-time adaptive least-squares drag minimization algorithm for an aeroelastic model of a flexible wing aircraft. The aircraft model is based on the NASA Generic Transport Model (GTM). The wing structures incorporate a novel aerodynamic control surface known as the Variable Camber Continuous Trailing Edge Flap (VCCTEF). The drag minimization algorithm uses the Newton-Raphson method to find the optimal VCCTEF deflections for minimum drag in the context of an altitude-hold flight control mode at cruise conditions. The aerodynamic coefficient parameters used in this optimization method are identified in real-time using Recursive Least Squares (RLS). The results demonstrate the potential of the VCCTEF to improve aerodynamic efficiency for drag minimization for transport aircraft.
Zhao, Guoliang; Li, Hongxing
2013-01-01
This paper proposes new methodologies for the design of adaptive integral-sliding mode control. A tensor product model transformation based adaptive integral-sliding mode control law with respect to uncertainties and perturbations is studied, while upper bounds on the perturbations and uncertainties are assumed to be unknown. The advantage of proposed controllers consists in having a dynamical adaptive control gain to establish a sliding mode right at the beginning of the process. Gain dynamics ensure a reasonable adaptive gain with respect to the uncertainties. Finally, efficacy of the proposed controller is verified by simulations on an uncertain nonlinear system model. PMID:24453897
Real-Time Adaptive Control Allocation Applied to a High Performance Aircraft
NASA Technical Reports Server (NTRS)
Davidson, John B.; Lallman, Frederick J.; Bundick, W. Thomas
2001-01-01
Abstract This paper presents the development and application of one approach to the control of aircraft with large numbers of control effectors. This approach, referred to as real-time adaptive control allocation, combines a nonlinear method for control allocation with actuator failure detection and isolation. The control allocator maps moment (or angular acceleration) commands into physical control effector commands as functions of individual control effectiveness and availability. The actuator failure detection and isolation algorithm is a model-based approach that uses models of the actuators to predict actuator behavior and an adaptive decision threshold to achieve acceptable false alarm/missed detection rates. This integrated approach provides control reconfiguration when an aircraft is subjected to actuator failure, thereby improving maneuverability and survivability of the degraded aircraft. This method is demonstrated on a next generation military aircraft Lockheed-Martin Innovative Control Effector) simulation that has been modified to include a novel nonlinear fluid flow control control effector based on passive porosity. Desktop and real-time piloted simulation results demonstrate the performance of this integrated adaptive control allocation approach.
Integration and bench testing for the GRAVITY Coudé IR adaptive optics (CIAO) wavefront sensor
NASA Astrophysics Data System (ADS)
Deen, C.; Yang, P.; Huber, A.; Suarez-Valles, M.; Hippler, S.; Brandner, W.; Gendron, E.; Clénet, Y.; Kendrew, S.; Glauser, A.; Klein, R.; Laun, W.; Lenzen, R.; Neumann, U.; Panduro, J.; Ramos, J.; Rohloff, R.-R.; Salzinger, A.; Zimmerman, N.; Henning, T.; Perraut, K.; Perrin, G.; Straubmeier, C.; Amorim, A.; Eisenhauer, F.
2014-08-01
GRAVITY, a second generation instrument for the Very Large Telescope Interferometer (VLTI), will provide an astrometric precision of order 10 micro-arcseconds, an imaging resolution of 4 milli-arcseconds, and low/medium resolution spectro-interferometry. These improvements to the VLTI represent a major upgrade to its current infrared interferometric capabilities, allowing detailed study of obscured environments (e.g. the Galactic Center, young dusty planet-forming disks, dense stellar cores, AGN, etc...). Crucial to the final performance of GRAVITY, the Coudé IR Adaptive Optics (CIAO) system will correct for the effects of the atmosphere at each of the VLT Unit Telescopes. CIAO consists of four new infrared Shack-Hartmann wavefront sensors (WFS) and associated real-time computers/software which will provide infrared wavefront sensing from 1.45-2.45 microns, allowing AO corrections even in regions where optically bright reference sources are scarce. We present here the latest progress on the GRAVITY wavefront sensors. We describe the adaptation and testing of a light-weight version of the ESO Standard Platform for Adaptive optics Real Time Applications (SPARTA-Light) software architecture to the needs of GRAVITY. We also describe the latest integration and test milestones for construction of the initial wave front sensor.
Internal Models in Sensorimotor Integration: Perspectives from Adaptive Control Theory
Tin, Chung; Poon, Chi-Sang
2007-01-01
Internal model and adaptive control are empirical and mathematical paradigms that have evolved separately to describe learning control processes in brain systems and engineering systems, respectively. This paper presents a comprehensive appraisal of the correlation between these paradigms with a view to forging a unified theoretical framework that may benefit both disciplines. It is suggested that the classic equilibrium-point theory of impedance control of arm movement is analogous to continuous gain-scheduling or high-gain adaptive control within or across movement trials, respectively, and that the recently proposed inverse internal model is akin to adaptive sliding control originally for robotic manipulator applications. Modular internal models architecture for multiple motor tasks is a form of multi-model adaptive control. Stochastic methods such as generalized predictive control, reinforcement learning, Bayesian learning and Hebbian feedback covariance learning are reviewed and their possible relevance to motor control is discussed. Possible applicability of Luenberger observer and extended Kalman filter to state estimation problems such as sensorimotor prediction or the resolution of vestibular sensory ambiguity is also discussed. The important role played by vestibular system identification in postural control suggests an indirect adaptive control scheme whereby system states or parameters are explicitly estimated prior to the implementation of control. This interdisciplinary framework should facilitate the experimental elucidation of the mechanisms of internal model in sensorimotor systems and the reverse engineering of such neural mechanisms into novel brain-inspired adaptive control paradigms in future. PMID:16135881
Adaptive spatial combining for passive time-reversed communications.
Gomes, João; Silva, António; Jesus, Sérgio
2008-08-01
Passive time reversal has aroused considerable interest in underwater communications as a computationally inexpensive means of mitigating the intersymbol interference introduced by the channel using a receiver array. In this paper the basic technique is extended by adaptively weighting sensor contributions to partially compensate for degraded focusing due to mismatch between the assumed and actual medium impulse responses. Two algorithms are proposed, one of which restores constructive interference between sensors, and the other one minimizes the output residual as in widely used equalization schemes. These are compared with plain time reversal and variants that employ postequalization and channel tracking. They are shown to improve the residual error and temporal stability of basic time reversal with very little added complexity. Results are presented for data collected in a passive time-reversal experiment that was conducted during the MREA'04 sea trial. In that experiment a single acoustic projector generated a 24-PSK (phase-shift keyed) stream at 200400 baud, modulated at 3.6 kHz, and received at a range of about 2 km on a sparse vertical array with eight hydrophones. The data were found to exhibit significant Doppler scaling, and a resampling-based preprocessing method is also proposed here to compensate for that scaling. PMID:18681595
Integrated Planning for Telepresence With Time Delays
NASA Technical Reports Server (NTRS)
Johnston, Mark; Rabe, Kenneth
2009-01-01
A conceptual "intelligent assistant" and an artificial-intelligence computer program that implements the intelligent assistant have been developed to improve control exerted by a human supervisor over a robot that is so distant that communication between the human and the robot involves significant signal-propagation delays. The goal of the effort is not only to help the human supervisor monitor and control the state of the robot, but also to improve the efficiency of the robot by allowing the supervisor to "work ahead". The intelligent assistant is an integrated combination of an artificial-intelligence planner and a monitor of states of both the human supervisor and the remote robot. The novelty of the system lies in the way it uses the planner to reason about the states at both ends of the time delay. The purpose served by the assistant is to provide advice to the human supervisor about current and future activities, derived from a sequence of high-level goals to be achieved.
Parallel implementation of an adaptive and parameter-free N-body integrator
NASA Astrophysics Data System (ADS)
Pruett, C. David; Ingham, William H.; Herman, Ralph D.
2011-05-01
Previously, Pruett et al. (2003) [3] described an N-body integrator of arbitrarily high order M with an asymptotic operation count of O(MN). The algorithm's structure lends itself readily to data parallelization, which we document and demonstrate here in the integration of point-mass systems subject to Newtonian gravitation. High order is shown to benefit parallel efficiency. The resulting N-body integrator is robust, parameter-free, highly accurate, and adaptive in both time-step and order. Moreover, it exhibits linear speedup on distributed parallel processors, provided that each processor is assigned at least a handful of bodies. Program summaryProgram title: PNB.f90 Catalogue identifier: AEIK_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEIK_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC license, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 3052 No. of bytes in distributed program, including test data, etc.: 68 600 Distribution format: tar.gz Programming language: Fortran 90 and OpenMPI Computer: All shared or distributed memory parallel processors Operating system: Unix/Linux Has the code been vectorized or parallelized?: The code has been parallelized but has not been explicitly vectorized. RAM: Dependent upon N Classification: 4.3, 4.12, 6.5 Nature of problem: High accuracy numerical evaluation of trajectories of N point masses each subject to Newtonian gravitation. Solution method: Parallel and adaptive extrapolation in time via power series of arbitrary degree. Running time: 5.1 s for the demo program supplied with the package.
Non-linear adaptive sliding mode switching control with average dwell-time
NASA Astrophysics Data System (ADS)
Yu, Lei; Zhang, Maoqing; Fei, Shumin
2013-03-01
In this article, an adaptive integral sliding mode control scheme is addressed for switched non-linear systems in the presence of model uncertainties and external disturbances. The control law includes two parts: a slide mode controller for the reduced model of the plant and a compensation controller to deal with the non-linear systems with parameter uncertainties. The adaptive updated laws have been derived from the switched multiple Lyapunov function method, also an admissible switching signal with average dwell-time technique is given. The simplicity of the proposed control scheme facilitates its implementation and the overall control scheme guarantees the global asymptotic stability in the Lyapunov sense such that the sliding surface of the control system is well reached. Simulation results are presented to demonstrate the effectiveness and the feasibility of the proposed approach.
Time, Dynamics and Chaos: Integrating Poincare's 'Non-Integrable Systems'
DOE R&D Accomplishments Database
Prigogine, I.
1990-10-01
This report discusses the nature of time. The author attempts to resolve the conflict between the concept of time reversibility in classical and quantum mechanics with the macroscopic world's irreversibility of time. (LSP)
Time, dynamics and chaos. Integrating Poincare's "non-integrable systems"
Prigogine, I.
1990-01-01
This report discusses the nature of time. The author attempts to resolve the conflict between the concept of time reversibility in classical and quantum mechanics with the macroscopic world's irreversibility of time. (LSP)
Evaluating mallard adaptive management models with time series
Conn, P.B.; Kendall, W.L.
2004-01-01
Wildlife practitioners concerned with midcontinent mallard (Anas platyrhynchos) management in the United States have instituted a system of adaptive harvest management (AHM) as an objective format for setting harvest regulations. Under the AHM paradigm, predictions from a set of models that reflect key uncertainties about processes underlying population dynamics are used in coordination with optimization software to determine an optimal set of harvest decisions. Managers use comparisons of the predictive abilities of these models to gauge the relative truth of different hypotheses about density-dependent recruitment and survival, with better-predicting models giving more weight to the determination of harvest regulations. We tested the effectiveness of this strategy by examining convergence rates of 'predictor' models when the true model for population dynamics was known a priori. We generated time series for cases when the a priori model was 1 of the predictor models as well as for several cases when the a priori model was not in the model set. We further examined the addition of different levels of uncertainty into the variance structure of predictor models, reflecting different levels of confidence about estimated parameters. We showed that in certain situations, the model-selection process favors a predictor model that incorporates the hypotheses of additive harvest mortality and weakly density-dependent recruitment, even when the model is not used to generate data. Higher levels of predictor model variance led to decreased rates of convergence to the model that generated the data, but model weight trajectories were in general more stable. We suggest that predictive models should incorporate all sources of uncertainty about estimated parameters, that the variance structure should be similar for all predictor models, and that models with different functional forms for population dynamics should be considered for inclusion in predictor model! sets. All of these
Numerical Integration: One Step at a Time
ERIC Educational Resources Information Center
Yang, Yajun; Gordon, Sheldon P.
2016-01-01
This article looks at the effects that adding a single extra subdivision has on the level of accuracy of some common numerical integration routines. Instead of automatically doubling the number of subdivisions for a numerical integration rule, we investigate what happens with a systematic method of judiciously selecting one extra subdivision for…
Feature Integration across Space, Time, and Orientation
ERIC Educational Resources Information Center
Otto, Thomas U.; Ogmen, Haluk; Herzog, Michael H.
2009-01-01
The perception of a visual target can be strongly influenced by flanking stimuli. In static displays, performance on the target improves when the distance to the flanking elements increases--presumably because feature pooling and integration vanishes with distance. Here, we studied feature integration with dynamic stimuli. We show that features of…
ERIC Educational Resources Information Center
Mitsuhara, Hiroyuki; Kurose, Yoshinobu; Ochi, Youji; Yano, Yoneo
The authors developed a Web-based Adaptive Educational System (Web-based AES) named ITMS (Individualized Teaching Material System). ITMS adaptively integrates knowledge on the distributed Web pages and generates individualized teaching material that has various contents. ITMS also presumes the learners' knowledge levels from the states of their…
Integral ceramic superstructure evaluation using time domain optical coherence tomography
NASA Astrophysics Data System (ADS)
Sinescu, Cosmin; Bradu, Adrian; Topala, Florin I.; Negrutiu, Meda Lavinia; Duma, Virgil-Florin; Podoleanu, Adrian G.
2014-02-01
Optical Coherence Tomography (OCT) is a non-invasive low coherence interferometry technique that includes several technologies (and the corresponding devices and components), such as illumination and detection, interferometry, scanning, adaptive optics, microscopy and endoscopy. From its large area of applications, we consider in this paper a critical aspect in dentistry - to be investigated with a Time Domain (TD) OCT system. The clinical situation of an edentulous mandible is considered; it can be solved by inserting 2 to 6 implants. On these implants a mesostructure will be manufactured and on it a superstructure is needed. This superstructure can be integral ceramic; in this case materials defects could be trapped inside the ceramic layers and those defects could lead to fractures of the entire superstructure. In this paper we demonstrate that a TD-OCT imaging system has the potential to properly evaluate the presence of the defects inside the ceramic layers and those defects can be fixed before inserting the prosthesis inside the oral cavity. Three integral ceramic superstructures were developed by using a CAD/CAM technology. After the milling, the ceramic layers were applied on the core. All the three samples were evaluated by a TD-OCT system working at 1300 nm. For two of the superstructures evaluated, no defects were found in the most stressed areas. The third superstructure presented four ceramic defects in the mentioned areas. Because of those defects the superstructure may fracture. The integral ceramic prosthesis was send back to the dental laboratory to fix the problems related to the material defects found. Thus, TD-OCT proved to be a valuable method for diagnosing the ceramic defects inside the integral ceramic superstructures in order to prevent fractures at this level.
Integration of Online Parameter Identification and Neural Network for In-Flight Adaptive Control
NASA Technical Reports Server (NTRS)
Hageman, Jacob; Smith, Mark; Stachowiak, Susan
2003-01-01
An indirect adaptive system has been constructed for robust control of an aircraft with uncertain aerodynamic characteristics. This system consists of a multilayer perceptron pre-trained neural network, online stability and control derivative identification, a dynamic cell structure online learning neural network, and a model following control system based on the stochastic optimal feedforward and feedback technique. The pre-trained neural network and model following control system have been flight-tested, but the online parameter identification and online learning neural network are new additions used for in-flight adaptation of the control system model. A description of the modification and integration of these two stand-alone software packages into the complete system in preparation for initial flight tests is presented. Open-loop results using both simulation and flight data, as well as closed-loop performance of the complete system in a nonlinear, six-degree-of-freedom, flight validated simulation, are analyzed. Results show that this online learning system, in contrast to the nonlearning system, has the ability to adapt to changes in aerodynamic characteristics in a real-time, closed-loop, piloted simulation, resulting in improved flying qualities.
Nonlinear time-series-based adaptive control applications
NASA Technical Reports Server (NTRS)
Mohler, R. R.; Rajkumar, V.; Zakrzewski, R. R.
1991-01-01
A control design methodology based on a nonlinear time-series reference model is presented. It is indicated by highly nonlinear simulations that such designs successfully stabilize troublesome aircraft maneuvers undergoing large changes in angle of attack as well as large electric power transients due to line faults. In both applications, the nonlinear controller was significantly better than the corresponding linear adaptive controller. For the electric power network, a flexible AC transmission system with series capacitor power feedback control is studied. A bilinear autoregressive moving average reference model is identified from system data, and the feedback control is manipulated according to a desired reference state. The control is optimized according to a predictive one-step quadratic performance index. A similar algorithm is derived for control of rapid changes in aircraft angle of attack over a normally unstable flight regime. In the latter case, however, a generalization of a bilinear time-series model reference includes quadratic and cubic terms in angle of attack.
ROAMing terrain (Real-time Optimally Adapting Meshes)
Duchaineau, M.; Wolinsky, M.; Sigeti, D.E.; Miller, M.C.; Aldrich, C.; Mineev, M.
1997-07-01
Terrain visualization is a difficult problem for applications requiring accurate images of large datasets at high frame rates, such as flight simulation and ground-based aircraft testing using synthetic sensor stimulation. On current graphics hardware, the problem is to maintain dynamic, view-dependent triangle meshes and texture maps that produce good images at the required frame rate. We present an algorithm for constructing triangle meshes that optimizes flexible view-dependent error metrics, produces guaranteed error bounds, achieves specified triangle counts directly, and uses frame-to-frame coherence to operate at high frame rates for thousands of triangles per frame. Our method, dubbed Real-time Optimally Adapting Meshes (ROAM), uses two priority queues to drive split and merge operations that maintain continuous triangulations built from pre-processed bintree triangles. We introduce two additional performance optimizations: incremental triangle stripping and priority-computation deferral lists. ROAM execution time is proportionate to the number of triangle changes per frame, which is typically a few percent of the output mesh size, hence ROAM performance is insensitive to the resolution and extent of the input terrain. Dynamic terrain and simple vertex morphing are supported.
Augmenting synthetic aperture radar with space time adaptive processing
NASA Astrophysics Data System (ADS)
Riedl, Michael; Potter, Lee C.; Ertin, Emre
2013-05-01
Wide-area persistent radar video offers the ability to track moving targets. A shortcoming of the current technology is an inability to maintain track when Doppler shift places moving target returns co-located with strong clutter. Further, the high down-link data rate required for wide-area imaging presents a stringent system bottleneck. We present a multi-channel approach to augment the synthetic aperture radar (SAR) modality with space time adaptive processing (STAP) while constraining the down-link data rate to that of a single antenna SAR system. To this end, we adopt a multiple transmit, single receive (MISO) architecture. A frequency division design for orthogonal transmit waveforms is presented; the approach maintains coherence on clutter, achieves the maximal unaliased band of radial velocities, retains full resolution SAR images, and requires no increase in receiver data rate vis-a-vis the wide-area SAR modality. For Nt transmit antennas and N samples per pulse, the enhanced sensing provides a STAP capability with Nt times larger range bins than the SAR mode, at the cost of O(log N) more computations per pulse. The proposed MISO system and the associated signal processing are detailed, and the approach is numerically demonstrated via simulation of an airborne X-band system.
Dissociating Conflict Adaptation from Feature Integration: A Multiple Regression Approach
ERIC Educational Resources Information Center
Notebaert, Wim; Verguts, Tom
2007-01-01
Congruency effects are typically smaller after incongruent than after congruent trials. One explanation is in terms of higher levels of cognitive control after detection of conflict (conflict adaptation; e.g., M. M. Botvinick, T. S. Braver, D. M. Barch, C. S. Carter, & J. D. Cohen, 2001). An alternative explanation for these results is based on…
Compact integration factor methods for complex domains and adaptive mesh refinement
Liu, Xinfeng; Nie, Qing
2010-01-01
Implicit integration factor (IIF) method, a class of efficient semi-implicit temporal scheme, was introduced recently for stiff reaction-diffusion equations. To reduce cost of IIF, compact implicit integration factor (cIIF) method was later developed for efficient storage and calculation of exponential matrices associated with the diffusion operators in two and three spatial dimensions for Cartesian coordinates with regular meshes. Unlike IIF, cIIF cannot be directly extended to other curvilinear coordinates, such as polar and spherical coordinate, due to the compact representation for the diffusion terms in cIIF. In this paper, we present a method to generalize cIIF for other curvilinear coordinates through examples of polar and spherical coordinates. The new cIIF method in polar and spherical coordinates has similar computational efficiency and stability properties as the cIIF in Cartesian coordinate. In addition, we present a method for integrating cIIF with adaptive mesh refinement (AMR) to take advantage of the excellent stability condition for cIIF. Because the second order cIIF is unconditionally stable, it allows large time steps for AMR, unlike a typical explicit temporal scheme whose time step is severely restricted by the smallest mesh size in the entire spatial domain. Finally, we apply those methods to simulating a cell signaling system described by a system of stiff reaction-diffusion equations in both two and three spatial dimensions using AMR, curvilinear and Cartesian coordinates. Excellent performance of the new methods is observed. PMID:20543883
INCORPORATING CATASTROPHES INTO INTEGRATED ASSESSMENT: SCIENCE, IMPACTS, AND ADAPTATION
Incorporating potential catastrophic consequences into integrated assessment models of climate change has been a top priority of policymakers and modelers alike. We review the current state of scientific understanding regarding three frequently mentioned geophysical catastrophes,...
40 CFR 147.3109 - Timing of mechanical integrity test.
Code of Federal Regulations, 2010 CFR
2010-07-01
... 40 Protection of Environment 22 2010-07-01 2010-07-01 false Timing of mechanical integrity test... Certain Oklahoma Indian Tribes § 147.3109 Timing of mechanical integrity test. The demonstrations of mechanical integrity required by § 146.14(b)(2) of this chapter prior to approval for the operation of...
40 CFR 147.3109 - Timing of mechanical integrity test.
Code of Federal Regulations, 2011 CFR
2011-07-01
... 40 Protection of Environment 23 2011-07-01 2011-07-01 false Timing of mechanical integrity test... Certain Oklahoma Indian Tribes § 147.3109 Timing of mechanical integrity test. The demonstrations of mechanical integrity required by § 146.14(b)(2) of this chapter prior to approval for the operation of...
Adaptive real-time dual-comb spectroscopy.
Ideguchi, Takuro; Poisson, Antonin; Guelachvili, Guy; Picqué, Nathalie; Hänsch, Theodor W
2014-01-01
The spectrum of a laser frequency comb consists of several hundred thousand equally spaced lines over a broad spectral bandwidth. Such frequency combs have revolutionized optical frequency metrology and they now hold much promise for significant advances in a growing number of applications including molecular spectroscopy. Despite an intriguing potential for the measurement of molecular spectra spanning tens of nanometres within tens of microseconds at Doppler-limited resolution, the development of dual-comb spectroscopy is hindered by the demanding stability requirements of the laser combs. Here we overcome this difficulty and experimentally demonstrate a concept of real-time dual-comb spectroscopy, which compensates for laser instabilities by electronic signal processing. It only uses free-running mode-locked lasers without any phase-lock electronics. We record spectra spanning the full bandwidth of near-infrared fibre lasers with Doppler-limited line profiles highly suitable for measurements of concentrations or line intensities. Our new technique of adaptive dual-comb spectroscopy offers a powerful transdisciplinary instrument for analytical sciences. PMID:24572636
Adaptive real-time dual-comb spectroscopy
Ideguchi, Takuro; Poisson, Antonin; Guelachvili, Guy; Picqué, Nathalie; Hänsch, Theodor W.
2014-01-01
The spectrum of a laser frequency comb consists of several hundred thousand equally spaced lines over a broad spectral bandwidth. Such frequency combs have revolutionized optical frequency metrology and they now hold much promise for significant advances in a growing number of applications including molecular spectroscopy. Despite an intriguing potential for the measurement of molecular spectra spanning tens of nanometres within tens of microseconds at Doppler-limited resolution, the development of dual-comb spectroscopy is hindered by the demanding stability requirements of the laser combs. Here we overcome this difficulty and experimentally demonstrate a concept of real-time dual-comb spectroscopy, which compensates for laser instabilities by electronic signal processing. It only uses free-running mode-locked lasers without any phase-lock electronics. We record spectra spanning the full bandwidth of near-infrared fibre lasers with Doppler-limited line profiles highly suitable for measurements of concentrations or line intensities. Our new technique of adaptive dual-comb spectroscopy offers a powerful transdisciplinary instrument for analytical sciences. PMID:24572636
Adaptive real-time dual-comb spectroscopy
NASA Astrophysics Data System (ADS)
Ideguchi, Takuro; Poisson, Antonin; Guelachvili, Guy; Picqué, Nathalie; Hänsch, Theodor W.
2014-02-01
The spectrum of a laser frequency comb consists of several hundred thousand equally spaced lines over a broad spectral bandwidth. Such frequency combs have revolutionized optical frequency metrology and they now hold much promise for significant advances in a growing number of applications including molecular spectroscopy. Despite an intriguing potential for the measurement of molecular spectra spanning tens of nanometres within tens of microseconds at Doppler-limited resolution, the development of dual-comb spectroscopy is hindered by the demanding stability requirements of the laser combs. Here we overcome this difficulty and experimentally demonstrate a concept of real-time dual-comb spectroscopy, which compensates for laser instabilities by electronic signal processing. It only uses free-running mode-locked lasers without any phase-lock electronics. We record spectra spanning the full bandwidth of near-infrared fibre lasers with Doppler-limited line profiles highly suitable for measurements of concentrations or line intensities. Our new technique of adaptive dual-comb spectroscopy offers a powerful transdisciplinary instrument for analytical sciences.
An integrated architecture of adaptive neural network control for dynamic systems
Ke, Liu; Tokar, R.; Mcvey, B.
1994-07-01
In this study, an integrated neural network control architecture for nonlinear dynamic systems is presented. Most of the recent emphasis in the neural network control field has no error feedback as the control input which rises the adaptation problem. The integrated architecture in this paper combines feed forward control and error feedback adaptive control using neural networks. The paper reveals the different internal functionality of these two kinds of neural network controllers for certain input styles, e.g., state feedback and error feedback. Feed forward neural network controllers with state feedback establish fixed control mappings which can not adapt when model uncertainties present. With error feedbacks, neural network controllers learn the slopes or the gains respecting to the error feedbacks, which are error driven adaptive control systems. The results demonstrate that the two kinds of control scheme can be combined to realize their individual advantages. Testing with disturbances added to the plant shows good tracking and adaptation.
ERIC Educational Resources Information Center
Rule, Audrey C.; Barrera, Manuel T., III
2008-01-01
Integration of subject areas with technology and thinking skills is a way to help teachers cope with today's overloaded curriculum and to help students see the connectedness of different curriculum areas. This study compares three authentic approaches to teaching a science unit on bird adaptations for habitat that integrate thinking skills and…
ERIC Educational Resources Information Center
Yu, Baohua; Downing, Kevin
2012-01-01
This study examined the influence of integrative motivation, instrumental motivation and second language (L2) proficiency on socio-cultural/academic adaptation in a sample of two groups of international students studying Chinese in China. Results revealed that the non-Asian student group reported higher levels of integrative motivation,…
Self-Adaptive Spike-Time-Dependent Plasticity of Metal-Oxide Memristors
Prezioso, M.; Merrikh Bayat, F.; Hoskins, B.; Likharev, K.; Strukov, D.
2016-01-01
Metal-oxide memristors have emerged as promising candidates for hardware implementation of artificial synapses – the key components of high-performance, analog neuromorphic networks - due to their excellent scaling prospects. Since some advanced cognitive tasks require spiking neuromorphic networks, which explicitly model individual neural pulses (“spikes”) in biological neural systems, it is crucial for memristive synapses to support the spike-time-dependent plasticity (STDP). A major challenge for the STDP implementation is that, in contrast to some simplistic models of the plasticity, the elementary change of a synaptic weight in an artificial hardware synapse depends not only on the pre-synaptic and post-synaptic signals, but also on the initial weight (memristor’s conductance) value. Here we experimentally demonstrate, for the first time, an STDP behavior that ensures self-adaptation of the average memristor conductance, making the plasticity stable, i.e. insensitive to the initial state of the devices. The experiments have been carried out with 200-nm Al2O3/TiO2−x memristors integrated into 12 × 12 crossbars. The experimentally observed self-adaptive STDP behavior has been complemented with numerical modeling of weight dynamics in a simple system with a leaky-integrate-and-fire neuron with a random spike-train input, using a compact model of memristor plasticity, fitted for quantitatively correct description of our memristors. PMID:26893175
Self-Adaptive Spike-Time-Dependent Plasticity of Metal-Oxide Memristors.
Prezioso, M; Merrikh Bayat, F; Hoskins, B; Likharev, K; Strukov, D
2016-01-01
Metal-oxide memristors have emerged as promising candidates for hardware implementation of artificial synapses - the key components of high-performance, analog neuromorphic networks - due to their excellent scaling prospects. Since some advanced cognitive tasks require spiking neuromorphic networks, which explicitly model individual neural pulses ("spikes") in biological neural systems, it is crucial for memristive synapses to support the spike-time-dependent plasticity (STDP). A major challenge for the STDP implementation is that, in contrast to some simplistic models of the plasticity, the elementary change of a synaptic weight in an artificial hardware synapse depends not only on the pre-synaptic and post-synaptic signals, but also on the initial weight (memristor's conductance) value. Here we experimentally demonstrate, for the first time, an STDP behavior that ensures self-adaptation of the average memristor conductance, making the plasticity stable, i.e. insensitive to the initial state of the devices. The experiments have been carried out with 200-nm Al2O3/TiO2-x memristors integrated into 12 × 12 crossbars. The experimentally observed self-adaptive STDP behavior has been complemented with numerical modeling of weight dynamics in a simple system with a leaky-integrate-and-fire neuron with a random spike-train input, using a compact model of memristor plasticity, fitted for quantitatively correct description of our memristors. PMID:26893175
Self-Adaptive Spike-Time-Dependent Plasticity of Metal-Oxide Memristors
NASA Astrophysics Data System (ADS)
Prezioso, M.; Merrikh Bayat, F.; Hoskins, B.; Likharev, K.; Strukov, D.
2016-02-01
Metal-oxide memristors have emerged as promising candidates for hardware implementation of artificial synapses - the key components of high-performance, analog neuromorphic networks - due to their excellent scaling prospects. Since some advanced cognitive tasks require spiking neuromorphic networks, which explicitly model individual neural pulses (“spikes”) in biological neural systems, it is crucial for memristive synapses to support the spike-time-dependent plasticity (STDP). A major challenge for the STDP implementation is that, in contrast to some simplistic models of the plasticity, the elementary change of a synaptic weight in an artificial hardware synapse depends not only on the pre-synaptic and post-synaptic signals, but also on the initial weight (memristor’s conductance) value. Here we experimentally demonstrate, for the first time, an STDP behavior that ensures self-adaptation of the average memristor conductance, making the plasticity stable, i.e. insensitive to the initial state of the devices. The experiments have been carried out with 200-nm Al2O3/TiO2-x memristors integrated into 12 × 12 crossbars. The experimentally observed self-adaptive STDP behavior has been complemented with numerical modeling of weight dynamics in a simple system with a leaky-integrate-and-fire neuron with a random spike-train input, using a compact model of memristor plasticity, fitted for quantitatively correct description of our memristors.
Exponential time-differencing with embedded Runge–Kutta adaptive step control
Whalen, P.; Brio, M.; Moloney, J.V.
2015-01-01
We have presented the first embedded Runge–Kutta exponential time-differencing (RKETD) methods of fourth order with third order embedding and fifth order with third order embedding for non-Rosenbrock type nonlinear systems. A procedure for constructing RKETD methods that accounts for both order conditions and stability is outlined. In our stability analysis, the fast time scale is represented by a full linear operator in contrast to particular scalar cases considered before. An effective time-stepping strategy based on reducing both ETD function evaluations and rejected steps is described. Comparisons of performance with adaptive-stepping integrating factor (IF) are carried out on a set of canonical partial differential equations: the shock-fronts of Burgers equation, interacting KdV solitons, KS controlled chaos, and critical collapse of two-dimensional NLS.
NASA Astrophysics Data System (ADS)
Ma, Shaokang; Wu, Peijun; Ji, Jinhu; Li, Xuchun
2016-02-01
This article presents a sensorless control approach of salient PMSM with an online parameter identifier. Adaptive Integrator is proposed and utilised for the estimation of active flux and rotor position. As a result, integrator overflow caused by DC offset is avoided. Meanwhile, an online stator resistance identification algorithm using strong tracking filter is employed, and the identified stator resistance is fed back to the estimating algorithm. Thus, the estimating algorithm can calculate the rotor position correctly. Simulations and experimental results validate the feasibility of both adaptive integrator and the parameter identification method.
Optimal Control Modification Adaptive Law for Time-Scale Separated Systems
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.
2010-01-01
Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. A model matching conditions in the transformed time coordinate results in an increase in the actuator command that effectively compensate for the slow actuator dynamics. Simulations demonstrate effectiveness of the method.
Hashemi, Mahnaz; Ghaisari, Jafar; Askari, Javad
2015-07-01
This paper investigates an adaptive controller for a class of Multi Input Multi Output (MIMO) nonlinear systems with unknown parameters, bounded time delays and in the presence of unknown time varying actuator failures. The type of considered actuator failure is one in which some inputs may be stuck at some time varying values where the values, times and patterns of the failures are unknown. The proposed approach is constructed based on a backstepping design method. The boundedness of all the closed-loop signals is guaranteed and the tracking errors are proved to converge to a small neighborhood of the origin. The proposed approach is employed for a double inverted pendulums benchmark and a chemical reactor system. The simulation results show the effectiveness of the proposed method. PMID:25792517
Ma, Huanfei; Lin, Wei; Lai, Ying-Cheng
2013-05-01
Detecting unstable periodic orbits (UPOs) in chaotic systems based solely on time series is a fundamental but extremely challenging problem in nonlinear dynamics. Previous approaches were applicable but mostly for low-dimensional chaotic systems. We develop a framework, integrating approximation theory of neural networks and adaptive synchronization, to address the problem of time-series-based detection of UPOs in high-dimensional chaotic systems. An example of finding UPOs from the classic Mackey-Glass equation is presented. PMID:23767476
Integrated method for chaotic time series analysis
Hively, L.M.; Ng, E.G.
1998-09-29
Methods and apparatus for automatically detecting differences between similar but different states in a nonlinear process monitor nonlinear data are disclosed. Steps include: acquiring the data; digitizing the data; obtaining nonlinear measures of the data via chaotic time series analysis; obtaining time serial trends in the nonlinear measures; and determining by comparison whether differences between similar but different states are indicated. 8 figs.
Integrated method for chaotic time series analysis
Hively, Lee M.; Ng, Esmond G.
1998-01-01
Methods and apparatus for automatically detecting differences between similar but different states in a nonlinear process monitor nonlinear data. Steps include: acquiring the data; digitizing the data; obtaining nonlinear measures of the data via chaotic time series analysis; obtaining time serial trends in the nonlinear measures; and determining by comparison whether differences between similar but different states are indicated.
NASA Astrophysics Data System (ADS)
Palaniswamy, Sumithra; Duraisamy, Prakash; Alam, Mohammad Showkat; Yuan, Xiaohui
2012-04-01
Automatic speech processing systems are widely used in everyday life such as mobile communication, speech and speaker recognition, and for assisting the hearing impaired. In speech communication systems, the quality and intelligibility of speech is of utmost importance for ease and accuracy of information exchange. To obtain an intelligible speech signal and one that is more pleasant to listen, noise reduction is essential. In this paper a new Time Adaptive Discrete Bionic Wavelet Thresholding (TADBWT) scheme is proposed. The proposed technique uses Daubechies mother wavelet to achieve better enhancement of speech from additive non- stationary noises which occur in real life such as street noise and factory noise. Due to the integration of human auditory system model into the wavelet transform, bionic wavelet transform (BWT) has great potential for speech enhancement which may lead to a new path in speech processing. In the proposed technique, at first, discrete BWT is applied to noisy speech to derive TADBWT coefficients. Then the adaptive nature of the BWT is captured by introducing a time varying linear factor which updates the coefficients at each scale over time. This approach has shown better performance than the existing algorithms at lower input SNR due to modified soft level dependent thresholding on time adaptive coefficients. The objective and subjective test results confirmed the competency of the TADBWT technique. The effectiveness of the proposed technique is also evaluated for speaker recognition task under noisy environment. The recognition results show that the TADWT technique yields better performance when compared to alternate methods specifically at lower input SNR.
A time self-adaptive multilevel algorithm for large-eddy simulation
NASA Astrophysics Data System (ADS)
Terracol, M.; Sagaut, P.; Basdevant, C.
2003-01-01
An extension of the multilevel method applied to LES proposed in Terracol et al. [J. Comput. Phys. 167 (2001) 439] is introduced here to reduce the CPU times in unsteady simulation of turbulent flows. Flow variables are decomposed into several wavenumber bands, each band being associated to a computational grid in physical space. The general framework associated to such a decomposition is presented, and a new adapted closure is proposed for the subgrid terms which appear at each filtering level, while the closure at the finest level is performed with a classical LES model. CPU time saving is obtained by the use of V-cycles, as in the multigrid terminology. The main part of the simulation is thus performed on the coarse levels, while the smallest resolved scales are kept frozen (quasi-static approximation [Comput. Methods Appl. Mech. Engrg. 159 (1998) 123]). This allows to reduce significantly the CPU times in comparison with classical LES, while the accuracy of the simulation is preserved by the use of a fine discretization level. To ensure the validity of the quasi-static approximation, a dynamic evaluation of the time during which it remains valid is performed at each level through an a priori error estimation of the small-scales time variation. This leads to a totally self-adaptive method in which both the number of levels and the integration times on each grid level are evaluated dynamically. The method is assessed on a fully unsteady time-developing compressible mixing layer at a low-Reynolds number for which a DNS has also been performed, and in the inviscid case. Finally, a plane channel flow configuration has been considered. In all cases, the results obtained are in good agreement with classical LES performed on a fine grid, with CPU time reduction factors of up to five.
Jeong, Jong Seob; Cannata, Jonathan Matthew; Shung, K Kirk
2010-01-01
It was previously demonstrated that it is feasible to simultaneously perform ultrasound therapy and imaging of a coagulated lesion during treatment with an integrated transducer that is capable of high intensity focused ultrasound (HIFU) and B-mode ultrasound imaging. It was found that coded excitation and fixed notch filtering upon reception could significantly reduce interference caused by the therapeutic transducer. During HIFU sonication, the imaging signal generated with coded excitation and fixed notch filtering had a range side-lobe level of less than −40 dB, while traditional short-pulse excitation and fixed notch filtering produced a range side-lobe level of −20 dB. The shortcoming is, however, that relatively complicated electronics may be needed to utilize coded excitation in an array imaging system. It is for this reason that in this paper an adaptive noise canceling technique is proposed to improve image quality by minimizing not only the therapeutic interference, but also the remnant side-lobe ‘ripples’ when using the traditional short-pulse excitation. The performance of this technique was verified through simulation and experiments using a prototype integrated HIFU/imaging transducer. Although it is known that the remnant ripples are related to the notch attenuation value of the fixed notch filter, in reality, it is difficult to find the optimal notch attenuation value due to the change in targets or the media resulted from motion or different acoustic properties even during one sonication pulse. In contrast, the proposed adaptive noise canceling technique is capable of optimally minimizing both the therapeutic interference and residual ripples without such constraints. The prototype integrated HIFU/imaging transducer is composed of three rectangular elements. The 6 MHz center element is used for imaging and the outer two identical 4 MHz elements work together to transmit the HIFU beam. Two HIFU elements of 14.4 mm × 20.0 mm dimensions
Jeong, Jong Seob; Cannata, Jonathan Matthew; Shung, K Kirk
2010-04-01
It was previously demonstrated that it is feasible to simultaneously perform ultrasound therapy and imaging of a coagulated lesion during treatment with an integrated transducer that is capable of high intensity focused ultrasound (HIFU) and B-mode ultrasound imaging. It was found that coded excitation and fixed notch filtering upon reception could significantly reduce interference caused by the therapeutic transducer. During HIFU sonication, the imaging signal generated with coded excitation and fixed notch filtering had a range side-lobe level of less than -40 dB, while traditional short-pulse excitation and fixed notch filtering produced a range side-lobe level of -20 dB. The shortcoming is, however, that relatively complicated electronics may be needed to utilize coded excitation in an array imaging system. It is for this reason that in this paper an adaptive noise canceling technique is proposed to improve image quality by minimizing not only the therapeutic interference, but also the remnant side-lobe 'ripples' when using the traditional short-pulse excitation. The performance of this technique was verified through simulation and experiments using a prototype integrated HIFU/imaging transducer. Although it is known that the remnant ripples are related to the notch attenuation value of the fixed notch filter, in reality, it is difficult to find the optimal notch attenuation value due to the change in targets or the media resulted from motion or different acoustic properties even during one sonication pulse. In contrast, the proposed adaptive noise canceling technique is capable of optimally minimizing both the therapeutic interference and residual ripples without such constraints. The prototype integrated HIFU/imaging transducer is composed of three rectangular elements. The 6 MHz center element is used for imaging and the outer two identical 4 MHz elements work together to transmit the HIFU beam. Two HIFU elements of 14.4 mm x 20.0 mm dimensions could
NASA Astrophysics Data System (ADS)
Moniem, T. A.
2016-05-01
This article presents a methodology for an integrated Bragg grating using an alloy of GaAs, AlGaAs, and InGaAs with a controllable refractive index to obtain an adaptive Bragg grating suitable for many applications on optical processing and adaptive control systems, such as limitation and filtering. The refractive index of a Bragg grating is controlled by using an external electric field for controlling periodic modulation of the refractive index of the active waveguide region. The designed Bragg grating has refractive indices programmed by using that external electric field. This article presents two approaches for designing the controllable refractive indices active region of a Bragg grating. The first approach is based on the modification of a planar micro-strip structure of the iGaAs traveling wave as the active region, and the second is based on the modification of self-assembled InAs/GaAs quantum dots of an alloy from GaAs and InGaAs with a GaP traveling wave. The overall design and results are discussed through numerical simulation by using the finite-difference time-domain, plane wave expansion, and opto-wave simulation methods to confirm its operation and feasibility.
NASA Astrophysics Data System (ADS)
Blanes, Sergio; Budd, Chris J.
2004-05-01
We present a generalisation of the Levi-Civita and Kustaanheimo-Stiefel regularisation. This allows the use of more general time rescalings. In particular, it is possible to find a regularisation which removes the singularity of the equations and preserves scaling invariance. In addition, these equations can, in certain cases, be integrated with explicit symplectic Runge-Kutta-Nyström methods. The combination of both techniques gives an explicit adaptive symplectic (EASY) integrator. We apply those methods to some perturbations of the Kepler problem and illustrate, by means of some numerical examples, when scaling invariant regularisations are more efficient that the LC/KS regularisation.
Analytical approach to an integrate-and-fire model with spike-triggered adaptation
NASA Astrophysics Data System (ADS)
Schwalger, Tilo; Lindner, Benjamin
2015-12-01
The calculation of the steady-state probability density for multidimensional stochastic systems that do not obey detailed balance is a difficult problem. Here we present the analytical derivation of the stationary joint and various marginal probability densities for a stochastic neuron model with adaptation current. Our approach assumes weak noise but is valid for arbitrary adaptation strength and time scale. The theory predicts several effects of adaptation on the statistics of the membrane potential of a tonically firing neuron: (i) a membrane potential distribution with a convex shape, (ii) a strongly increased probability of hyperpolarized membrane potentials induced by strong and fast adaptation, and (iii) a maximized variability associated with the adaptation current at a finite adaptation time scale.
Magnitude Estimation with Noisy Integrators Linked by an Adaptive Reference
Thurley, Kay
2016-01-01
Judgments of physical stimuli show characteristic biases; relatively small stimuli are overestimated whereas relatively large stimuli are underestimated (regression effect). Such biases likely result from a strategy that seeks to minimize errors given noisy estimates about stimuli that itself are drawn from a distribution, i.e., the statistics of the environment. While being conceptually well described, it is unclear how such a strategy could be implemented neurally. The present paper aims toward answering this question. A theoretical approach is introduced that describes magnitude estimation as two successive stages of noisy (neural) integration. Both stages are linked by a reference memory that is updated with every new stimulus. The model reproduces the behavioral characteristics of magnitude estimation and makes several experimentally testable predictions. Moreover, the model identifies the regression effect as a means of minimizing estimation errors and explains how this optimality strategy depends on the subject's discrimination abilities and on the stimulus statistics. The latter influence predicts another property of magnitude estimation, the so-called range effect. Beyond being successful in describing decision-making, the present work suggests that noisy integration may also be important in processing magnitudes. PMID:26909028
Adapting line integral convolution for fabricating artistic virtual environment
NASA Astrophysics Data System (ADS)
Lee, Jiunn-Shyan; Wang, Chung-Ming
2003-04-01
Vector field occurs not only extensively in scientific applications but also in treasured art such as sculptures and paintings. Artist depicts our natural environment stressing valued directional feature besides color and shape information. Line integral convolution (LIC), developed for imaging vector field in scientific visualization, has potential of producing directional image. In this paper we present several techniques of exploring LIC techniques to generate impressionistic images forming artistic virtual environment. We take advantage of directional information given by a photograph, and incorporate many investigations to the work including non-photorealistic shading technique and statistical detail control. In particular, the non-photorealistic shading technique blends cool and warm colors into the photograph to imitate artists painting convention. Besides, we adopt statistical technique controlling integral length according to image variance to preserve details. Furthermore, we also propose method for generating a series of mip-maps, which revealing constant strokes under multi-resolution viewing and achieving frame coherence in an interactive walkthrough system. The experimental results show merits of emulating satisfyingly and computing efficiently, as a consequence, relying on the proposed technique successfully fabricates a wide category of non-photorealistic rendering (NPR) application such as interactive virtual environment with artistic perception.
Magnitude Estimation with Noisy Integrators Linked by an Adaptive Reference.
Thurley, Kay
2016-01-01
Judgments of physical stimuli show characteristic biases; relatively small stimuli are overestimated whereas relatively large stimuli are underestimated (regression effect). Such biases likely result from a strategy that seeks to minimize errors given noisy estimates about stimuli that itself are drawn from a distribution, i.e., the statistics of the environment. While being conceptually well described, it is unclear how such a strategy could be implemented neurally. The present paper aims toward answering this question. A theoretical approach is introduced that describes magnitude estimation as two successive stages of noisy (neural) integration. Both stages are linked by a reference memory that is updated with every new stimulus. The model reproduces the behavioral characteristics of magnitude estimation and makes several experimentally testable predictions. Moreover, the model identifies the regression effect as a means of minimizing estimation errors and explains how this optimality strategy depends on the subject's discrimination abilities and on the stimulus statistics. The latter influence predicts another property of magnitude estimation, the so-called range effect. Beyond being successful in describing decision-making, the present work suggests that noisy integration may also be important in processing magnitudes. PMID:26909028
NASA Astrophysics Data System (ADS)
Lempert, R.; Fischbach, J.; Groves, D. G.; Bloom, E.; Goshi, B.; Nevills, J.
2011-12-01
The Metropolitan Water District of Southern California's 2010 Integrated Resource Plan Update (IRP) describes a resource investment strategy that would meet projected demand under a range of anticipated climate and demographic conditions through 2035. The IRP also identifies that alternative or additional investments may have to be considered in order to address uncertainty over the next 25 years and posits that an adaptive management strategy is needed to decide when to make these investments. Current water planning methodologies do not, however, offer means to operationalize such an adaptive management strategy, in particular by offering Metropolitan guidance as to the conditions that ought to signal the need to make additional investments as key trends unfold over time. This talk will describe a novel application of robust decision making (RDM) methods to help Metropolitan identify such key indicators- that is the trends the agency should monitor and threshold values for those trends that suggest a need to make additional investments. We ran Metropolitan's water resource planning models in over 1000 cases to explore the performance of the IRP in a wide range of future conditions due uncertainties in future demand, climate, ground water management, and timeliness of project implementation. Cluster-finding "scenario discovery" algorithms applied to the resulting database of simulation model results identifies the key combination of future conditions - the boundaries of the coping range -- associated with success and failure of the IRP. This analysis will not only help Metropolitan implement the adaptive management aspect of its IRP, it provides a widely applicable new approach for making water management plans more cognizant and responsive to a wide range of uncertainties.
NASA Astrophysics Data System (ADS)
Zhou, Yanlai; Guo, Shenglian; Xu, Chong-Yu; Liu, Dedi; Chen, Lu; Ye, Yushi
2015-12-01
Due to the adaption, dynamic and multi-objective characteristics of complex water resources system, it is a considerable challenge to manage water resources in an efficient, equitable and sustainable way. An integrated optimal allocation model is proposed for complex adaptive system of water resources management. The model consists of three modules: (1) an agent-based module for revealing evolution mechanism of complex adaptive system using agent-based, system dynamic and non-dominated sorting genetic algorithm II methods, (2) an optimal module for deriving decision set of water resources allocation using multi-objective genetic algorithm, and (3) a multi-objective evaluation module for evaluating the efficiency of the optimal module and selecting the optimal water resources allocation scheme using project pursuit method. This study has provided a theoretical framework for adaptive allocation, dynamic allocation and multi-objective optimization for a complex adaptive system of water resources management.
Integrative Model of Oxidative Stress Adaptation in the Fungal Pathogen Candida albicans
Komalapriya, Chandrasekaran; Yin, Zhikang; Herrero-de-Dios, Carmen; Jacobsen, Mette D.; Belmonte, Rodrigo C.; Cameron, Gary; Haynes, Ken; Grebogi, Celso; de Moura, Alessandro P. S.; Gow, Neil A. R.; Thiel, Marco; Quinn, Janet
2015-01-01
The major fungal pathogen of humans, Candida albicans, mounts robust responses to oxidative stress that are critical for its virulence. These responses counteract the reactive oxygen species (ROS) that are generated by host immune cells in an attempt to kill the invading fungus. Knowledge of the dynamical processes that instigate C. albicans oxidative stress responses is required for a proper understanding of fungus-host interactions. Therefore, we have adopted an interdisciplinary approach to explore the dynamical responses of C. albicans to hydrogen peroxide (H2O2). Our deterministic mathematical model integrates two major oxidative stress signalling pathways (Cap1 and Hog1 pathways) with the three major antioxidant systems (catalase, glutathione and thioredoxin systems) and the pentose phosphate pathway, which provides reducing equivalents required for oxidative stress adaptation. The model encapsulates existing knowledge of these systems with new genomic, proteomic, transcriptomic, molecular and cellular datasets. Our integrative approach predicts the existence of alternative states for the key regulators Cap1 and Hog1, thereby suggesting novel regulatory behaviours during oxidative stress. The model reproduces both existing and new experimental observations under a variety of scenarios. Time- and dose-dependent predictions of the oxidative stress responses for both wild type and mutant cells have highlighted the different temporal contributions of the various antioxidant systems during oxidative stress adaptation, indicating that catalase plays a critical role immediately following stress imposition. This is the first model to encapsulate the dynamics of the transcriptional response alongside the redox kinetics of the major antioxidant systems during H2O2 stress in C. albicans. PMID:26368573
Integrative Model of Oxidative Stress Adaptation in the Fungal Pathogen Candida albicans.
Komalapriya, Chandrasekaran; Kaloriti, Despoina; Tillmann, Anna T; Yin, Zhikang; Herrero-de-Dios, Carmen; Jacobsen, Mette D; Belmonte, Rodrigo C; Cameron, Gary; Haynes, Ken; Grebogi, Celso; de Moura, Alessandro P S; Gow, Neil A R; Thiel, Marco; Quinn, Janet; Brown, Alistair J P; Romano, M Carmen
2015-01-01
The major fungal pathogen of humans, Candida albicans, mounts robust responses to oxidative stress that are critical for its virulence. These responses counteract the reactive oxygen species (ROS) that are generated by host immune cells in an attempt to kill the invading fungus. Knowledge of the dynamical processes that instigate C. albicans oxidative stress responses is required for a proper understanding of fungus-host interactions. Therefore, we have adopted an interdisciplinary approach to explore the dynamical responses of C. albicans to hydrogen peroxide (H2O2). Our deterministic mathematical model integrates two major oxidative stress signalling pathways (Cap1 and Hog1 pathways) with the three major antioxidant systems (catalase, glutathione and thioredoxin systems) and the pentose phosphate pathway, which provides reducing equivalents required for oxidative stress adaptation. The model encapsulates existing knowledge of these systems with new genomic, proteomic, transcriptomic, molecular and cellular datasets. Our integrative approach predicts the existence of alternative states for the key regulators Cap1 and Hog1, thereby suggesting novel regulatory behaviours during oxidative stress. The model reproduces both existing and new experimental observations under a variety of scenarios. Time- and dose-dependent predictions of the oxidative stress responses for both wild type and mutant cells have highlighted the different temporal contributions of the various antioxidant systems during oxidative stress adaptation, indicating that catalase plays a critical role immediately following stress imposition. This is the first model to encapsulate the dynamics of the transcriptional response alongside the redox kinetics of the major antioxidant systems during H2O2 stress in C. albicans. PMID:26368573
INTEGRATING EVOLUTIONARY AND FUNCTIONAL APPROACHES TO INFER ADAPTATION AT SPECIFIC LOCI
Storz, Jay F.; Wheat, Christopher W.
2010-01-01
Inferences about adaptation at specific loci are often exclusively based on the static analysis of DNA sequence variation. Ideally, population-genetic evidence for positive selection serves as a stepping-off point for experimental studies to elucidate the functional significance of the putatively adaptive variation. We argue that inferences about adaptation at specific loci are best achieved by integrating the indirect, retrospective insights provided by population-genetic analyses with the more direct, mechanistic insights provided by functional experiments. Integrative studies of adaptive genetic variation may sometimes be motivated by experimental insights into molecular function, which then provide the impetus to perform population genetic tests to evaluate whether the functional variation is of adaptive significance. In other cases, studies may be initiated by genome scans of DNA variation to identify candidate loci for recent adaptation. Results of such analyses can then motivate experimental efforts to test whether the identified candidate loci do in fact contribute to functional variation in some fitness-related phenotype. Functional studies can provide corroborative evidence for positive selection at particular loci, and can potentially reveal specific molecular mechanisms of adaptation. PMID:20500215
Finite difference schemes for long-time integration
NASA Technical Reports Server (NTRS)
Haras, Zigo; Taasan, Shlomo
1993-01-01
Finite difference schemes for the evaluation of first and second derivatives are presented. These second order compact schemes were designed for long-time integration of evolution equations by solving a quadratic constrained minimization problem. The quadratic cost function measures the global truncation error while taking into account the initial data. The resulting schemes are applicable for integration times fourfold, or more, longer than similar previously studied schemes. A similar approach was used to obtain improved integration schemes.
40 CFR 147.3109 - Timing of mechanical integrity test.
Code of Federal Regulations, 2012 CFR
2012-07-01
... 40 Protection of Environment 24 2012-07-01 2012-07-01 false Timing of mechanical integrity test... Certain Oklahoma Indian Tribes § 147.3109 Timing of mechanical integrity test. The demonstrations of... Class I well shall, for an existing well, be conducted no more than 90 days prior to application for...
Integrated Climate Change Information for Resilient Adaptation Planning
Awareness is growing that some air, water, and ecosystem impacts from climate change are inevitable due to the long residence times of key greenhouse gases (GHGs), including carbon dioxide (CO_{2}), methane (CH_{4}) and nitrous oxide (N_{2}O), which are in...
Adaptive, real-time hypoxia measurements using an autonomous boat
NASA Astrophysics Data System (ADS)
Kerkez, B.; Wong, B. P.; Balzano, L.; Lipor, J.; Scavia, D.
2015-12-01
We present an autonomous system to measure hypoxia at high spatial resolutions. The approach combines a robotic boat, cloud hosted data services, and a suite of adaptive sampling algorithms to minimize the number of samples required to delineate hypoxic extents. The boat lowers sensors into the water column to provide depth profiles of temperature and oxygen concentrations. An adaptive path-planning algorithm continuously analyzes the in-situ observations and directs the boat to its next measurement location. This significantly reduces number of samples compared to a gridded sampling approach, while simultaneously improving the certainty with which the hypoxic regions are delineated. The method has been evaluated on small lakes throughout Michigan and shows significant promise to scale to the Great Lakes, where hypoxia is common occurrence that adversely affects various stakeholder and ecosystems.
DECREASING COMPUTING TIME WITH SYMPLECTIC CORRECTORS IN ADAPTIVE TIMESTEPPING ROUTINES
Kaib, Nathan A.; Quinn, Thomas; Brasser, Ramon
2011-01-15
It has previously been shown that varying the numerical timestep during a symplectic orbital integration leads to a random walk in energy and angular momentum, destroying the phase space-conserving property of symplectic integrators. Here we show that when altering the timestep symplectic correctors can be used to reduce this error to a negligible level. Furthermore, these correctors can also be employed to avoid a large error introduction when changing the Hamiltonian's partitioning. We have constructed a numerical integrator using this technique that is nearly as accurate as widely used fixed-step routines. In addition, our algorithm is drastically faster for integrations of highly eccentricitic, large semimajor axis orbits, such as those found in the Oort Cloud.
Sea Extremes: Integrated impact assessment in coastal climate adaptation
NASA Astrophysics Data System (ADS)
Sorensen, Carlo; Knudsen, Per; Broge, Niels; Molgaard, Mads; Andersen, Ole
2016-04-01
We investigate effects of sea level rise and a change in precipitation pattern on coastal flooding hazards. Historic and present in situ and satellite data of water and groundwater levels, precipitation, vertical ground motion, geology, and geotechnical soil properties are combined with flood protection measures, topography, and infrastructure to provide a more complete picture of the water-related impact from climate change at an exposed coastal location. Results show that future sea extremes evaluated from extreme value statistics may, indeed, have a large impact. The integrated effects from future storm surges and other geo- and hydro-parameters need to be considered in order to provide for the best protection and mitigation efforts, however. Based on the results we present and discuss a simple conceptual model setup that can e.g. be used for 'translation' of regional sea level rise evidence and projections to concrete impact measures. This may be used by potentially affected stakeholders -often working in different sectors and across levels of governance, in a common appraisal of the challenges faced ahead. The model may also enter dynamic tools to evaluate local impact as sea level research advances and projections for the future are updated.
PFC design via FRIT Approach for Adaptive Output Feedback Control of Discrete-time Systems
NASA Astrophysics Data System (ADS)
Mizumoto, Ikuro; Takagi, Taro; Fukui, Sota; Shah, Sirish L.
This paper deals with a design problem of an adaptive output feedback control for discrete-time systems with a parallel feedforward compensator (PFC) which is designed for making the augmented controlled system ASPR. A PFC design scheme by a FRIT approach with only using an input/output experimental data set will be proposed for discrete-time systems in order to design an adaptive output feedback control system. Furthermore, the effectiveness of the proposed PFC design method will be confirmed through numerical simulations by designing adaptive control system with adaptive NN (Neural Network) for an uncertain discrete-time system.
Adaptation-Induced Compression of Event Time Occurs Only for Translational Motion
Fornaciai, Michele; Arrighi, Roberto; Burr, David C.
2016-01-01
Adaptation to fast motion reduces the perceived duration of stimuli displayed at the same location as the adapting stimuli. Here we show that the adaptation-induced compression of time is specific for translational motion. Adaptation to complex motion, either circular or radial, did not affect perceived duration of subsequently viewed stimuli. Adaptation with multiple patches of translating motion caused compression of duration only when the motion of all patches was in the same direction. These results show that adaptation-induced compression of event-time occurs only for uni-directional translational motion, ruling out the possibility that the neural mechanisms of the adaptation occur at early levels of visual processing. PMID:27003445
Real-Time Adaptive EEG Source Separation Using Online Recursive Independent Component Analysis.
Hsu, Sheng-Hsiou; Mullen, Tim R; Jung, Tzyy-Ping; Cauwenberghs, Gert
2016-03-01
Independent component analysis (ICA) has been widely applied to electroencephalographic (EEG) biosignal processing and brain-computer interfaces. The practical use of ICA, however, is limited by its computational complexity, data requirements for convergence, and assumption of data stationarity, especially for high-density data. Here we study and validate an optimized online recursive ICA algorithm (ORICA) with online recursive least squares (RLS) whitening for blind source separation of high-density EEG data, which offers instantaneous incremental convergence upon presentation of new data. Empirical results of this study demonstrate the algorithm's: 1) suitability for accurate and efficient source identification in high-density (64-channel) realistically-simulated EEG data; 2) capability to detect and adapt to nonstationarity in 64-ch simulated EEG data; and 3) utility for rapidly extracting principal brain and artifact sources in real 61-channel EEG data recorded by a dry and wearable EEG system in a cognitive experiment. ORICA was implemented as functions in BCILAB and EEGLAB and was integrated in an open-source Real-time EEG Source-mapping Toolbox (REST), supporting applications in ICA-based online artifact rejection, feature extraction for real-time biosignal monitoring in clinical environments, and adaptable classifications in brain-computer interfaces. PMID:26685257
Ubiquitous time variability of integrated stellar populations.
Conroy, Charlie; van Dokkum, Pieter G; Choi, Jieun
2015-11-26
Long-period variable stars arise in the final stages of the asymptotic giant branch phase of stellar evolution. They have periods of up to about 1,000 days and amplitudes that can exceed a factor of three in the I-band flux. These stars pulsate predominantly in their fundamental mode, which is a function of mass and radius, and so the pulsation periods are sensitive to the age of the underlying stellar population. The overall number of long-period variables in a population is directly related to their lifetimes, which is difficult to predict from first principles because of uncertainties associated with stellar mass-loss and convective mixing. The time variability of these stars has not previously been taken into account when modelling the spectral energy distributions of galaxies. Here we construct time-dependent stellar population models that include the effects of long-period variable stars, and report the ubiquitous detection of this expected 'pixel shimmer' in the massive metal-rich galaxy M87. The pixel light curves display a variety of behaviours. The observed variation of 0.1 to 1 per cent is very well matched to the predictions of our models. The data provide a strong constraint on the properties of variable stars in an old and metal-rich stellar population, and we infer that the lifetime of long-period variables in M87 is shorter by approximately 30 per cent compared to predictions from the latest stellar evolution models. PMID:26570999
The Time Course of Anticipatory Constraint Integration
Kukona, Anuenue; Fang, Shin-Yi; Aicher, Karen A.; Chen, Helen; Magnuson, James S.
2011-01-01
Several studies have demonstrated that as listeners hear sentences describing events in a scene, their eye movements anticipate upcoming linguistic items predicted by the unfolding relationship between scene and sentence. While this may reflect active prediction based on structural or contextual expectations, the influence of local thematic priming between words has not been fully examined. In Experiment 1, we presented verbs (e.g., arrest) in active (Subject-Verb-Object) sentences with displays containing verb-related patients (e.g., crook) and agents (e.g., policeman). We examined patient and agent fixations following the verb, after the agent role had been filled by another entity, but prior to bottom-up specification of the object. Participants were nearly as likely to fixate agents “anticipatorily” as patients, even though the agent role was already filled. However, the slight patient advantage suggested simultaneous influences of both local priming and active prediction. In Experiment 2, using passives (Object-Verb-Subject), we found stronger, but still graded influences of role prediction when more time elapsed between verb and target, and more syntactic cues were available. We interpret anticipatory fixations as emerging from constraint-based processes that involve both non-predictive thematic priming and active prediction. PMID:21237450
Career Adaptability: An Integrative Construct for Life-Span, Life-Space Theory.
ERIC Educational Resources Information Center
Savickas, Mark L.
1997-01-01
Examines the origin and current status of lifespan, life-space theory and proposes one way in which to integrate its three segments. Discusses a functionalist strategy for theory construction and the outcomes and consequences of this strategy. Discusses future directions for theory development, such as career adaptability and planful attitudes.…
ERIC Educational Resources Information Center
International Migration, 1979
1979-01-01
This document contains working papers prepared for a seminar on Adaptation and Integration of Permanent Immigrants, along with general and specific recommendations formulated by seminar participants. Conclusions and recommendations from each paper are presented in English, French, and Spanish; the conference papers themselves are presented only in…
Integrated and adaptive management of water resources: Tensions, legacies, and the next best thing
Engle, Nathan L.; Johns, Owen R.; Lemos, Maria Carmen; Nelson, Donald
2011-02-01
Integrated water resources management (IWRM) and adaptive management (AM) are two institutional and management paradigms designed to address shortcomings within water systems governance – the limits of hierarchical water institutional arrangements in the case of IWRM and the challenge of making water management decisions under uncertainty in the case of AM. Recently, there has been a trend to merge these paradigms to address the growing complexity of stressors shaping water management, such as globalization and climate change. However, because many of these joint approaches have received little empirical attention, questions remain about how they might work (or not) in practice. Here, we explore a few of these issues using empirical research carried out in Brazil. We focus on highlighting the potentially negative interactions, tensions, and tradeoffs between different institutions/mechanisms perceived as desirable as research and practice attempt to make water systems management simultaneously integrated and adaptive. Our examples pertain mainly on the use of techno-scientific knowledge in water management and governance in Brazil’s IWRM model and how it relates to participation, democracy, deliberation, diversity, and adaptability. We show that a legacy of technical and hierarchical management has shaped the integration of management, and subsequently, the degree to which management might also be adaptive. While integrated systems may be more legitimate and accountable than top-down command and control ones, the mechanisms of IWRM may be at odds with the flexible, experimental, and self-organizing nature of AM.
Robustness via Run-Time Adaptation of Contingent Plans
NASA Technical Reports Server (NTRS)
Bresina, John L.; Washington, Richard; Norvig, Peter (Technical Monitor)
2000-01-01
In this paper, we discuss our approach to making the behavior of planetary rovers more robust for the purpose of increased productivity. Due to the inherent uncertainty in rover exploration, the traditional approach to rover control is conservative, limiting the autonomous operation of the rover and sacrificing performance for safety. Our objective is to increase the science productivity possible within a single uplink by allowing the rover's behavior to be specified with flexible, contingent plans and by employing dynamic plan adaptation during execution. We have deployed a system exhibiting flexible, contingent execution; this paper concentrates on our ongoing efforts on plan adaptation, Plans can be revised in two ways: plan steps may be deleted, with execution continuing with the plan suffix; and the current plan may be merged with an "alternate plan" from an on-board library. The plan revision action is chosen to maximize the expected utility of the plan. Plan merging and action deletion constitute a more conservative general-purpose planning system; in return, our approach is more efficient and more easily verified, two important criteria for deployed rovers.
Adaptive time-delayed stabilization of steady states and periodic orbits.
Selivanov, Anton; Lehnert, Judith; Fradkov, Alexander; Schöll, Eckehard
2015-01-01
We derive adaptive time-delayed feedback controllers that stabilize fixed points and periodic orbits. First, we develop an adaptive controller for stabilization of a steady state by applying the speed-gradient method to an appropriate goal function and prove global asymptotic stability of the resulting system. For an example we show that the advantage of the adaptive controller over the nonadaptive one is in a smaller controller gain. Second, we propose adaptive time-delayed algorithms for stabilization of periodic orbits. Their efficiency is confirmed by local stability analysis. Numerical examples demonstrate the applicability of the proposed controllers. PMID:25679681
Adaptive time-delayed stabilization of steady states and periodic orbits
NASA Astrophysics Data System (ADS)
Selivanov, Anton; Lehnert, Judith; Fradkov, Alexander; Schöll, Eckehard
2015-01-01
We derive adaptive time-delayed feedback controllers that stabilize fixed points and periodic orbits. First, we develop an adaptive controller for stabilization of a steady state by applying the speed-gradient method to an appropriate goal function and prove global asymptotic stability of the resulting system. For an example we show that the advantage of the adaptive controller over the nonadaptive one is in a smaller controller gain. Second, we propose adaptive time-delayed algorithms for stabilization of periodic orbits. Their efficiency is confirmed by local stability analysis. Numerical examples demonstrate the applicability of the proposed controllers.
Climate change adaptation and Integrated Water Resource Management in the water sector
NASA Astrophysics Data System (ADS)
Ludwig, Fulco; van Slobbe, Erik; Cofino, Wim
2014-10-01
Integrated Water Resources Management (IWRM) was introduced in 1980s to better optimise water uses between different water demanding sectors. However, since it was introduced water systems have become more complicated due to changes in the global water cycle as a result of climate change. The realization that climate change will have a significant impact on water availability and flood risks has driven research and policy making on adaptation. This paper discusses the main similarities and differences between climate change adaptation and IWRM. The main difference between the two is the focus on current and historic issues of IWRM compared to the (long-term) future focus of adaptation. One of the main problems of implementing climate change adaptation is the large uncertainties in future projections. Two completely different approaches to adaptation have been developed in response to these large uncertainties. A top-down approach based on large scale biophysical impacts analyses focussing on quantifying and minimizing uncertainty by using a large range of scenarios and different climate and impact models. The main problem with this approach is the propagation of uncertainties within the modelling chain. The opposite is the bottom up approach which basically ignores uncertainty. It focusses on reducing vulnerabilities, often at local scale, by developing resilient water systems. Both these approaches however are unsuitable for integrating into water management. The bottom up approach focuses too much on socio-economic vulnerability and too little on developing (technical) solutions. The top-down approach often results in an “explosion” of uncertainty and therefore complicates decision making. A more promising direction of adaptation would be a risk based approach. Future research should further develop and test an approach which starts with developing adaptation strategies based on current and future risks. These strategies should then be evaluated using a range
Transit light curves with finite integration time: Fisher information analysis
Price, Ellen M.; Rogers, Leslie A.
2014-10-10
Kepler has revolutionized the study of transiting planets with its unprecedented photometric precision on more than 150,000 target stars. Most of the transiting planet candidates detected by Kepler have been observed as long-cadence targets with 30 minute integration times, and the upcoming Transiting Exoplanet Survey Satellite will record full frame images with a similar integration time. Integrations of 30 minutes affect the transit shape, particularly for small planets and in cases of low signal to noise. Using the Fisher information matrix technique, we derive analytic approximations for the variances and covariances on the transit parameters obtained from fitting light curve photometry collected with a finite integration time. We find that binning the light curve can significantly increase the uncertainties and covariances on the inferred parameters when comparing scenarios with constant total signal to noise (constant total integration time in the absence of read noise). Uncertainties on the transit ingress/egress time increase by a factor of 34 for Earth-size planets and 3.4 for Jupiter-size planets around Sun-like stars for integration times of 30 minutes compared to instantaneously sampled light curves. Similarly, uncertainties on the mid-transit time for Earth and Jupiter-size planets increase by factors of 3.9 and 1.4. Uncertainties on the transit depth are largely unaffected by finite integration times. While correlations among the transit depth, ingress duration, and transit duration all increase in magnitude with longer integration times, the mid-transit time remains uncorrelated with the other parameters. We provide code in Python and Mathematica for predicting the variances and covariances at www.its.caltech.edu/∼eprice.
Bounded Linear Stability Analysis - A Time Delay Margin Estimation Approach for Adaptive Control
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.; Ishihara, Abraham K.; Krishnakumar, Kalmanje Srinlvas; Bakhtiari-Nejad, Maryam
2009-01-01
This paper presents a method for estimating time delay margin for model-reference adaptive control of systems with almost linear structured uncertainty. The bounded linear stability analysis method seeks to represent the conventional model-reference adaptive law by a locally bounded linear approximation within a small time window using the comparison lemma. The locally bounded linear approximation of the combined adaptive system is cast in a form of an input-time-delay differential equation over a small time window. The time delay margin of this system represents a local stability measure and is computed analytically by a matrix measure method, which provides a simple analytical technique for estimating an upper bound of time delay margin. Based on simulation results for a scalar model-reference adaptive control system, both the bounded linear stability method and the matrix measure method are seen to provide a reasonably accurate and yet not too conservative time delay margin estimation.
Anelli, Filomena; Ciaramelli, Elisa; Arzy, Shahar; Frassinetti, Francesca
2016-11-01
Accumulating evidence suggests that humans process time and space in similar veins. Humans represent time along a spatial continuum, and perception of temporal durations can be altered through manipulations of spatial attention by prismatic adaptation (PA). Here, we investigated whether PA-induced manipulations of spatial attention can also influence more conceptual aspects of time, such as humans' ability to travel mentally back and forward in time (mental time travel, MTT). Before and after leftward- and rightward-PA, participants projected themselves in the past, present or future time (i.e., self-projection), and, for each condition, determined whether a series of events were located in the past or the future with respect to that specific self-location in time (i.e., self-reference). The results demonstrated that leftward and rightward shifts of spatial attention facilitated recognition of past and future events, respectively. These findings suggest that spatial attention affects the temporal processing of the human self. PMID:27467891
Contextual control of inhibition with reinforcement: Adaptation and timing mechanisms
Bouton, Mark E.; Frohardt, Russell J.; Sunsay, Ceyhun; Waddell, Jaylyn; Morris, Richard W.
2010-01-01
Four experiments with rats studied the effects of switching the context after Pavlovian conditioning. In three conditioned suppression experiments, a large number of conditioning trials created “inhibition with reinforcement” (IWR), in which fear of the conditional stimulus (CS) reached a maximum and then declined despite continued CS – unconditional stimulus pairings. When IWR occurred, a context switch augmented fear of the CS; IWR and augmentation were highly correlated. Neither IWR nor augmentation resulted from inhibition of delay (IOD): In conditioned suppression, IWR and augmentation occurred without IOD (Experiment 3), and in appetitive conditioning (Experiment 4), IOD occurred without IWR or augmentation. IWR may occur in conditioned suppression because the animal adapts to fear of the CS in a context-specific manner. We discuss several implications. PMID:18426305
Automatic multirate methods for ordinary differential equations. [Adaptive time steps
Gear, C.W.
1980-01-01
A study is made of the application of integration methods in which different step sizes are used for different members of a system of equations. Such methods can result in savings if the cost of derivative evaluation is high or if a system is sparse; however, the estimation and control of errors is very difficult and can lead to high overheads. Three approaches are discussed, and it is shown that the least intuitive is the most promising. 2 figures.
On Time Delay Margin Estimation for Adaptive Control and Optimal Control Modification
NASA Technical Reports Server (NTRS)
Nguyen, Nhan T.
2011-01-01
This paper presents methods for estimating time delay margin for adaptive control of input delay systems with almost linear structured uncertainty. The bounded linear stability analysis method seeks to represent an adaptive law by a locally bounded linear approximation within a small time window. The time delay margin of this input delay system represents a local stability measure and is computed analytically by three methods: Pade approximation, Lyapunov-Krasovskii method, and the matrix measure method. These methods are applied to the standard model-reference adaptive control, s-modification adaptive law, and optimal control modification adaptive law. The windowing analysis results in non-unique estimates of the time delay margin since it is dependent on the length of a time window and parameters which vary from one time window to the next. The optimal control modification adaptive law overcomes this limitation in that, as the adaptive gain tends to infinity and if the matched uncertainty is linear, then the closed-loop input delay system tends to a LTI system. A lower bound of the time delay margin of this system can then be estimated uniquely without the need for the windowing analysis. Simulation results demonstrates the feasibility of the bounded linear stability method for time delay margin estimation.
Geenen, V
2012-01-01
The immune system may be considered as a sensory organ able to respond to different kinds of danger signals that are not detected by nervous cells. The immune response is not autonomous but also regulated by the central and peripheral nervous system, as well as by neuropeptides, vitamin D and neuroendocrine axes such as the corticotrope, somatotrope, thyrotrope and gonadotrope axes. During evolution, the thymus emerged concomitantly with recombinase-dependent adaptive immunity as an'immune brain' or a'master class' highly specialized in the orchestration of central immunological self-tolerance. This was an absolute requirement for survival of species because of the high risk of autotoxicity inherent to the stochastic generation of extreme diversity characterizing this novel adaptive type of immune defenses against non-self. The thymus now appears to be an obligatory intersection for the integrated evolution of the major systems of cell-to-cell signalling, the nervous, endocrine and immune systems. The presentation of many self-peptides by thymic major histocompatibility complex (MHC) proteins is controlled by the autoimmune regulator (AIRE) gene/protein and is responsible for the clonal deletion of self-reactive T cells. In the same time, by still unexplained mechanisms, MHC presentation of the same self-peptides in the thymus promotes the generation of self-specific FOXP3+ CD4+CD25+ natural regulatory T cells (nTreg) that are able to inhibit in periphery self-reactive CD4+ and CD8+ T cells having escaped the thymus censorship. Moreover, a thymus dysfunction is more and more established as the primary event driving the development of organ-specific autoimmunity, which is the tribute paid, mainly by mankind, for the preservation of self against non-self. Our novel knowledge about thymus physiology and physiopathology already serves as the basis for the development of various innovative and efficient immunomodulating strategies in pharmacology. PMID:22897070
Uncertainties of reverberation time estimation via adaptively identified room impulse responses.
Wu, Lifu; Qiu, Xiaojun; Burnett, Ian; Guo, Yecai
2016-03-01
This paper investigates the reverberation time estimation methods which employ backward integration of adaptively identified room impulse responses (RIRs). Two kinds of conditions are considered; the first is the "ideal condition" where the anechoic and reverberant signals are both known a priori so that the RIRs can be identified using system identification methods. The second is that only the reverberant speech signal is available, and blind identification of the RIRs via dereverberation is employed for reverberation time estimation. Results show that under the "ideal condition," the average relative errors in 7 octave bands are less than 2% for white noise and 15% for speech, respectively, when both the anechoic and reverberant signals are available. In contrast, under the second condition, the average relative errors of the blindly identified RIR-based reverberation time estimation are around 20%-30% except the 63 Hz octave band. The fluctuation of reverberation times estimated under the second condition is more severe than that under the ideal condition and the relative error for low frequency octave bands is larger than that for high octave bands under both conditions. PMID:27036246
ERIC Educational Resources Information Center
Raiche, Gilles; Blais, Jean-Guy
In a computerized adaptive test (CAT), it would be desirable to obtain an acceptable precision of the proficiency level estimate using an optimal number of items. Decreasing the number of items is accompanied, however, by a certain degree of bias when the true proficiency level differs significantly from the a priori estimate. G. Raiche (2000) has…
A CMOS integrated timing discriminator circuit for fast scintillation counters
Jochmann, M.W.
1998-06-01
Based on a zero-crossing discriminator using a CR differentiation network for pulse shaping, a new CMOS integrated timing discriminator circuit is proposed for fast (t{sub r} {ge} 2 ns) scintillation counters at the cooler synchrotron COSY-Juelich. By eliminating the input signal`s amplitude information by means of an analog continuous-time divider, a normalized pulse shape at the zero-crossing point is gained over a wide dynamic input amplitude range. In combination with an arming comparator and a monostable multivibrator this yields in a highly precise timing discriminator circuit, that is expected to be useful in different time measurement applications. First measurement results of a CMOS integrated logarithmic amplifier, which is part of the analog continuous-time divider, agree well with the corresponding simulations. Moreover, SPICE simulations of the integrated discriminator circuit promise a time walk well below 200 ps (FWHM) over a 40 dB input amplitude dynamic range.
Pereira, Marta; Beggiato, Matthias; Petzoldt, Tibor
2015-09-01
The study aimed at investigating how drivers use Adaptive Cruise Control and its functions in distinct road environments and to verify if changes occur over time. Fifteen participants were invited to drive a vehicle equipped with a Stop & Go Adaptive Cruise Control system on nine occasions. The course remained the same for each test run and included roads on urban and motorway environments. Results showed significant effect of experience for ACC usage percentage, and selection of the shortest time headway value in the urban road environment. This indicates that getting to know a system is not a homogenous process, as mastering the use of all the system's functions can take differing lengths of time in distinct road environments. Results can be used not only for the development of the new generation of systems that integrate ACC functionalities but also for determining the length of training required to operate an ACC system. PMID:25959324
NASA Astrophysics Data System (ADS)
Vanderlinden, J. P.; Baztan, J.
2014-12-01
The prupose of this paper is to present the "Adaptation Research a Transdisciplinary community and policy centered appoach" (ARTisticc) project. ARTisticc's goal is to apply innovative standardized transdisciplinary art and science integrative approaches to foster robust, socially, culturally and scientifically, community centred adaptation to climate change. The approach used in the project is based on the strong understanding that adaptation is: (a) still "a concept of uncertain form"; (b) a concept dealing with uncertainty; (c) a concept that calls for an analysis that goes beyond the traditional disciplinary organization of science, and; (d) an unconventional process in the realm of science and policy integration. The project is centered on case studies in France, Greenland, Russia, India, Canada, Alaska, and Senegal. In every site we jointly develop artwork while we analyzing how natural science, essentially geosciences can be used in order to better adapt in the future, how society adapt to current changes and how memories of past adaptations frames current and future processes. Artforms are mobilized in order to share scientific results with local communities and policy makers, this in a way that respects cultural specificities while empowering stakeholders, ARTISTICC translates these "real life experiments" into stories and artwork that are meaningful to those affected by climate change. The scientific results and the culturally mediated productions will thereafter be used in order to co-construct, with NGOs and policy makers, policy briefs, i.e. robust and scientifically legitimate policy recommendations regarding coastal adaptation. This co-construction process will be in itself analysed with the goal of increasing arts and science's performative functions in the universe of evidence-based policy making. The project involves scientists from natural sciences, the social sciences and the humanities, as well as artitis from the performing arts (playwriters
Exponential Methods for the Time Integration of Schroedinger Equation
Cano, B.; Gonzalez-Pachon, A.
2010-09-30
We consider exponential methods of second order in time in order to integrate the cubic nonlinear Schroedinger equation. We are interested in taking profit of the special structure of this equation. Therefore, we look at symmetry, symplecticity and approximation of invariants of the proposed methods. That will allow to integrate till long times with reasonable accuracy. Computational efficiency is also our aim. Therefore, we make numerical computations in order to compare the methods considered and so as to conclude that explicit Lawson schemes projected on the norm of the solution are an efficient tool to integrate this equation.
Rivera, Claudia
2014-01-01
This paper analyses the perceptions of disaster risk reduction (DRR) practitioners concerning the on-going integration of climate change adaptation (CCA) into their practices in urban contexts in Nicaragua. Understanding their perceptions is important as this will provide information on how this integration can be improved. Exploring the perceptions of practitioners in Nicaragua is important as the country has a long history of disasters, and practitioners have been developing the current DRR planning framework for more than a decade. The analysis is based on semi-structured interviews designed to collect information about practitioners’ understanding of: (a) CCA, (b) the current level of integration of CCA into DRR and urban planning, (c) the opportunities and constraints of this integration, and (d) the potential to adapt cities to climate change. The results revealed that practitioners’ perception is that the integration of CCA into their practice is at an early stage, and that they need to improve their understanding of CCA in terms of a development issue. Three main constraints on improved integration were identified: (a) a recognized lack of understanding of CCA, (b) insufficient guidance on how to integrate it, and (c) the limited opportunities to integrate it into urban planning due to a lack of instruments and capacity in this field. Three opportunities were also identified: (a) practitioners’ awareness of the need to integrate CCA into their practices, (b) the robust structure of the DRR planning framework in the country, which provides a suitable channel for facilitating integration, and (c) the fact that CCA is receiving more attention and financial and technical support from the international community. PMID:24475365
Real-Time Adaptive Foreground/Background Segmentation
NASA Astrophysics Data System (ADS)
Butler, Darren E.; Bove, V. Michael; Sridharan, Sridha
2005-12-01
The automatic analysis of digital video scenes often requires the segmentation of moving objects from a static background. Historically, algorithms developed for this purpose have been restricted to small frame sizes, low frame rates, or offline processing. The simplest approach involves subtracting the current frame from the known background. However, as the background is rarely known beforehand, the key is how to learn and model it. This paper proposes a new algorithm that represents each pixel in the frame by a group of clusters. The clusters are sorted in order of the likelihood that they model the background and are adapted to deal with background and lighting variations. Incoming pixels are matched against the corresponding cluster group and are classified according to whether the matching cluster is considered part of the background. The algorithm has been qualitatively and quantitatively evaluated against three other well-known techniques. It demonstrated equal or better segmentation and proved capable of processing [InlineEquation not available: see fulltext.] PAL video at full frame rate using only 35%-40% of a [InlineEquation not available: see fulltext.] GHz Pentium 4 computer.
NASA Astrophysics Data System (ADS)
Lee, J.; Yoon, M.; Lee, J.
2014-12-01
Current Global Navigation Satellite Systems (GNSS) augmentation systems attempt to consider all possible ionospheric events in their correction computations of worst-case errors. This conservatism can be mitigated by subdividing anomalous conditions and using different values of ionospheric threat-model bounds for each class. A new concept of 'real-time ionospheric threat adaptation' that adjusts the threat model in real time instead of always using the same 'worst-case' model was introduced in my previous research. The concept utilizes predicted values of space weather indices for determining the corresponding threat model based on the pre-defined worst-case threat as a function of space weather indices. Since space weather prediction is not reliable due to prediction errors, prediction errors are needed to be bounded to the required level of integrity of the system being supported. The previous research performed prediction error bounding using disturbance, storm time (Dst) index. The distribution of Dst prediction error over the 15-year data was bounded by applying 'inflated-probability density function (pdf) Gaussian bounding'. Since the error distribution has thick and non-Gaussian tails, investigation on statistical distributions which properly describe heavy tails with less conservatism is required for the system performance. This paper suggests two potential approaches for improving space weather prediction error bounding. First, we suggest using different statistical models when fit the error distribution, such as the Laplacian distribution which has fat tails, and the folded Gaussian cumulative distribution function (cdf) distribution. Second approach is to bound the error distribution by segregating data based on the overall level of solar activity. Bounding errors using only solar minimum period data will have less uncertainty and it may allow the use of 'solar cycle prediction' provided by NASA when implementing to real-time threat adaptation. Lastly
Electromagnetic Detection and Real-Time DMLC Adaptation to Target Rotation During Radiotherapy
Wu Junqing; Ruan, Dan; Cho, Byungchul; Sawant, Amit; Petersen, Jay; Newell, Laurence J.; Cattell, Herbert; Keall, Paul J.
2012-03-01
Purpose: Intrafraction rotation of more than 45 Degree-Sign and 25 Degree-Sign has been observed for lung and prostate tumors, respectively. Such rotation is not routinely adapted to during current radiotherapy, which may compromise tumor dose coverage. The aim of the study was to investigate the geometric and dosimetric performance of an electromagnetically guided real-time dynamic multileaf collimator (DMLC) tracking system to adapt to intrafractional tumor rotation. Materials/Methods: Target rotation was provided by changing the treatment couch angle. The target rotation was measured by a research Calypso system integrated with a real-time DMLC tracking system employed on a Varian linac. The geometric beam-target rotational alignment difference was measured using electronic portal images. The dosimetric accuracy was quantified using a two-dimensional ion chamber array. For each beam, the following five delivery modes were tested: 1) nonrotated target (reference); 2) fixed rotated target with tracking; 3) fixed rotated target without tracking; 4) actively rotating target with tracking; and 5) actively rotating target without tracking. Dosimetric performance of the latter four modes was measured and compared to the reference dose distribution using a 3 mm/3% {gamma}-test. Results: Geometrically, the beam-target rotational alignment difference was 0.3 Degree-Sign {+-} 0.6 Degree-Sign for fixed rotation and 0.3 Degree-Sign {+-} 1.3 Degree-Sign for active rotation. Dosimetrically, the average failure rate for the {gamma}-test for a fixed rotated target was 11% with tracking and 36% without tracking. The average failure rate for an actively rotating target was 9% with tracking and 35% without tracking. Conclusions: For the first time, real-time target rotation has been accurately detected and adapted to during radiation delivery via DMLC tracking. The beam-target rotational alignment difference was mostly within 1 Degree-Sign . Dose distributions to fixed and actively
Jareonsettasin, Prem; Otero-Millan, Jorge; Ward, Bryan K; Roberts, Dale C; Schubert, Michael C; Zee, David S
2016-05-23
A major focus in neurobiology is how the brain adapts its motor behavior to changes in its internal and external environments [1, 2]. Much is known about adaptively optimizing the amplitude and direction of eye and limb movements, for example, but little is known about another essential form of learning, "set-point" adaptation. Set-point adaptation balances tonic activity so that reciprocally acting, agonist and antagonist muscles have a stable platform from which to launch accurate movements. Here, we use the vestibulo-ocular reflex-a simple behavior that stabilizes the position of the eye while the head is moving-to investigate how tonic activity is adapted toward a new set point to prevent eye drift when the head is still [3, 4]. Set-point adaptation was elicited with magneto-hydrodynamic vestibular stimulation (MVS) by placing normal humans in a 7T MRI for 90 min. MVS is ideal for prolonged labyrinthine activation because it mimics constant head acceleration and induces a sustained nystagmus similar to natural vestibular lesions [5, 6]. The MVS-induced nystagmus diminished slowly but incompletely over multiple timescales. We propose a new adaptation hypothesis, using a cascade of imperfect mathematical integrators, that reproduces the response to MVS (and more natural chair rotations), including the gradual decrease in nystagmus as the set point changes over progressively longer time courses. MVS set-point adaptation is a biological model with applications to basic neurophysiological research into all types of movements [7], functional brain imaging [8], and treatment of vestibular and higher-level attentional disorders by introducing new biases to counteract pathological ones [9]. PMID:27185559
Real-time control of geometry and stiffness in adaptive structures
NASA Technical Reports Server (NTRS)
Ramesh, A. V.; Utku, S.; Wada, B. K.
1991-01-01
The basic theory is presented for the geometry, stiffness, and damping control of adaptive structures, with emphasis on adaptive truss structures. Necessary and sufficient conditions are given for stress-free geometry control in statically determinate and indeterminate adaptive discrete structures. Two criteria for selecting the controls are proposed, and their use in real-time control is illustrated by numerical simulation results. It is shown that the stiffness and damping control of adaptive truss structures for vibration suppression is possible by elongation and elongation rate dependent feedback forces from the active elements.
Adaptive tuning of feedback gain in time-delayed feedback control
NASA Astrophysics Data System (ADS)
Lehnert, J.; Hövel, P.; Flunkert, V.; Guzenko, P. Yu.; Fradkov, A. L.; Schöll, E.
2011-12-01
We demonstrate that time-delayed feedback control can be improved by adaptively tuning the feedback gain. This adaptive controller is applied to the stabilization of an unstable fixed point and an unstable periodic orbit embedded in a chaotic attractor. The adaptation algorithm is constructed using the speed-gradient method of control theory. Our computer simulations show that the adaptation algorithm can find an appropriate value of the feedback gain for single and multiple delays. Furthermore, we show that our method is robust to noise and different initial conditions.
Adaptive tuning of feedback gain in time-delayed feedback control.
Lehnert, J; Hövel, P; Flunkert, V; Guzenko, P Yu; Fradkov, A L; Schöll, E
2011-12-01
We demonstrate that time-delayed feedback control can be improved by adaptively tuning the feedback gain. This adaptive controller is applied to the stabilization of an unstable fixed point and an unstable periodic orbit embedded in a chaotic attractor. The adaptation algorithm is constructed using the speed-gradient method of control theory. Our computer simulations show that the adaptation algorithm can find an appropriate value of the feedback gain for single and multiple delays. Furthermore, we show that our method is robust to noise and different initial conditions. PMID:22225348
Does Integration Help Adapt to Climate Change? Case of Increased US Corn Yield Volatility
NASA Astrophysics Data System (ADS)
Verma, M.; Diffenbaugh, N. S.; Hertel, T. W.
2012-12-01
In absence of of new crop varieties or significant shifts in the geography of corn production, US national corn yields variation could double by the year 2040 as a result of climate change and without adaptation this could lead the variability in US corn prices to quadruple (Diffenbaugh et al. 2012). In addition to climate induced price changes, analysis of recent commodity price spikes suggests that interventionist trade policies are partly to blame. Assuming we cannot much influence the future climate outcome, what policies can we undertake to adapt better? Can we use markets to blunt this edge? Diffenbaugh et al. find that sale of corn- ethanol for use in liquid fuel, when governed by quotas such as US Renewable Fuel Standard (RFS), could make US corn prices even more variable; in contrast the same food-fuel market link (we refer to it as intersectoral link) may well dampen price volatility when the sale of corn to ethanol industry is driven by higher future oil prices. The latter however comes at the cost of exposing corn prices to the greater volatility in oil markets. Similarly intervention in corn trade can make US corn prices less or more volatile by distorting international corn price transmission. A negative US corn yield shock shows that domestic corn supply falls and domestic prices to go up irrespective of whether or not markets are integrated. How much the prices go up depends on how much demand adjusts to accommodate the supply shock. Based on the forgoing analysis, one should expect that demand would adjust more readily when markets are integrated and therefore reduce the resulting price fluctuation. Simulation results confirm this response of corn markets. In terms of relative comparisons however a policy driven intersectoral integration is least effective and prices rise much more. Similarly, a positive world oil price shock makes the US oil imports expensive and with oil being used to produce gasoline blends, it increases the price of gasoline
Goedert, Kelly M.; Shah, Priyanka; Foundas, Anne L.; Barrett, A. M.
2013-01-01
Prism adaptation treatment (PAT) is a promising rehabilitative method for functional recovery in persons with spatial neglect. Previous research suggests that PAT improves motor-intentional “aiming” deficits that frequently occur with frontal lesions. To test whether presence of frontal lesions predicted better improvement of spatial neglect after PAT, the current study evaluated neglect-specific improvement in functional activities (assessment with the Catherine Bergego Scale) over time in 21 right-brain-damaged stroke survivors with left-sided spatial neglect. The results demonstrated that neglect patients' functional activities improved after two weeks of PAT and continued improving for four weeks. Such functional improvement did not occur equally in all of the participants: Neglect patients with lesions involving the frontal cortex (n=13) experienced significantly better functional improvement than did those without frontal lesions (n=8). More importantly, voxel-based lesion-behavior mapping (VLBM) revealed that in comparison to the group of patients without frontal lesions, the frontal-lesioned neglect patients had intact regions in the medial temporal areas, the superior temporal areas, and the inferior longitudinal fasciculus. The medial cortical and subcortical areas in the temporal lobe were especially distinguished in the “frontal lesion” group. The findings suggest that the integrity of medial temporal structures may play an important role in supporting functional improvement after PAT. PMID:22941243
Cartesian Off-Body Grid Adaption for Viscous Time- Accurate Flow Simulation
NASA Technical Reports Server (NTRS)
Buning, Pieter G.; Pulliam, Thomas H.
2011-01-01
An improved solution adaption capability has been implemented in the OVERFLOW overset grid CFD code. Building on the Cartesian off-body approach inherent in OVERFLOW and the original adaptive refinement method developed by Meakin, the new scheme provides for automated creation of multiple levels of finer Cartesian grids. Refinement can be based on the undivided second-difference of the flow solution variables, or on a specific flow quantity such as vorticity. Coupled with load-balancing and an inmemory solution interpolation procedure, the adaption process provides very good performance for time-accurate simulations on parallel compute platforms. A method of using refined, thin body-fitted grids combined with adaption in the off-body grids is presented, which maximizes the part of the domain subject to adaption. Two- and three-dimensional examples are used to illustrate the effectiveness and performance of the adaption scheme.
NASA Technical Reports Server (NTRS)
Gupta, Pramod; Loparo, Kenneth; Mackall, Dale; Schumann, Johann; Soares, Fola
2004-01-01
Recent research has shown that adaptive neural based control systems are very effective in restoring stability and control of an aircraft in the presence of damage or failures. The application of an adaptive neural network with a flight critical control system requires a thorough and proven process to ensure safe and proper flight operation. Unique testing tools have been developed as part of a process to perform verification and validation (V&V) of real time adaptive neural networks used in recent adaptive flight control system, to evaluate the performance of the on line trained neural networks. The tools will help in certification from FAA and will help in the successful deployment of neural network based adaptive controllers in safety-critical applications. The process to perform verification and validation is evaluated against a typical neural adaptive controller and the results are discussed.
IMEX-a : an adaptive, fifth order implicit-explicit integration scheme.
Brake, Matthew Robert
2013-05-01
This report presents an efficient and accurate method for integrating a system of ordinary differential equations, particularly those arising from a spatial discretization of partially differential equations. The algorithm developed, termed the IMEX a algorithm, belongs to a class of algorithms known as implicit-explicit (IMEX) methods. The explicit step is based on a fifth order Runge-Kutta explicit step known as the Dormand-Prince algorithm, which adaptively modifies the time step by calculating the error relative to a fourth order estimation. The implicit step, which follows the explicit step, is based on a backward Euler method, a special case of the generalized trapezoidal method. Reasons for choosing both of these methods, along with the algorithm development are presented. In applications that have less stringent accuracy requirements, several other methods are available through the IMEX a toolbox, each of which simplify the fifth order Dormand-Prince explicit step: the third order Bogacki-Shampine method, the second order Midpoint method, and the first order Euler method. The performance of the algorithm is evaluated on to examples. First, a two pawl system with contact is modeled. Results predicted by the IMEX a algorithm are compared to those predicted by six widely used integration schemes. The IMEX a algorithm is demonstrated to be significantly faster (by up to an order of magnitude) and at least as accurate as all of the other methods considered. A second example, an acoustic standing wave, is presented in order to assess the accuracy of the IMEX a algorithm. Finally, sample code is given in order to demonstrate the implementation of the proposed algorithm.
Adaptive spark timing controller for an internal combustion engine
Javaherian, H.
1989-09-19
This patent describes a system for determining the ignition timing value in an ignition control system for an internal combustion engine having cylinders and an output crankshaft rotated during operation of the engine. The ignition control system initiating combustion in each cylinder of the engine at the determined ignition timing value. The system comprising, combination: means for sensing the end of combustion in a cylinder of the engine, the means for sensing including means for determining when an indicator function is at a peak as the crankshaft rotates; means for determining the magnitude of the crankshaft angle after top dead center of the cylinder at which the end of combustion in the cylinder was sensed; and means for establishing the ignition timing value at a start of combustion angle {theta}inew in advance of top dead center of the cylinders having a predetermined relationship to the determined magnitude of the end of combustion angle.
An adaptive time-stepping strategy for solving the phase field crystal model
Zhang, Zhengru; Ma, Yuan; Qiao, Zhonghua
2013-09-15
In this work, we will propose an adaptive time step method for simulating the dynamics of the phase field crystal (PFC) model. The numerical simulation of the PFC model needs long time to reach steady state, and then large time-stepping method is necessary. Unconditionally energy stable schemes are used to solve the PFC model. The time steps are adaptively determined based on the time derivative of the corresponding energy. It is found that the use of the proposed time step adaptivity cannot only resolve the steady state solution, but also the dynamical development of the solution efficiently and accurately. The numerical experiments demonstrate that the CPU time is significantly saved for long time simulations.
Deng, Hua; Li, Han-Xiong; Wu, Yi-Hu
2008-09-01
A new feedback-linearization-based neural network (NN) adaptive control is proposed for unknown nonaffine nonlinear discrete-time systems. An equivalent model in affine-like form is first derived for the original nonaffine discrete-time systems as feedback linearization methods cannot be implemented for such systems. Then, feedback linearization adaptive control is implemented based on the affine-like equivalent model identified with neural networks. Pretraining is not required and the weights of the neural networks used in adaptive control are directly updated online based on the input-output measurement. The dead-zone technique is used to remove the requirement of persistence excitation during the adaptation. With the proposed neural network adaptive control, stability and performance of the closed-loop system are rigorously established. Illustrated examples are provided to validate the theoretical findings. PMID:18779092
Antithetic Integral Feedback Ensures Robust Perfect Adaptation in Noisy Biomolecular Networks.
Briat, Corentin; Gupta, Ankit; Khammash, Mustafa
2016-01-27
The ability to adapt to stimuli is a defining feature of many biological systems and critical to maintaining homeostasis. While it is well appreciated that negative feedback can be used to achieve homeostasis when networks behave deterministically, the effect of noise on their regulatory function is not understood. Here, we combine probability and control theory to develop a theory of biological regulation that explicitly takes into account the noisy nature of biochemical reactions. We introduce tools for the analysis and design of robust homeostatic circuits and propose a new regulation motif, which we call antithetic integral feedback. This motif exploits stochastic noise, allowing it to achieve precise regulation in scenarios where similar deterministic regulation fails. Specifically, antithetic integral feedback preserves the stability of the overall network, steers the population of any regulated species to a desired set point, and adapts perfectly. We suggest that this motif may be prevalent in endogenous biological circuits and useful when creating synthetic circuits. PMID:27136686
Emergence of adaptability to time delay in bipedal locomotion.
Ohgane, Kunishige; Ei, Shin-Ichiro; Kazutoshi, Kudo; Ohtsuki, Tatsuyuki
2004-02-01
Based on neurophysiological evidence, theoretical studies have shown that locomotion is generated by mutual entrainment between the oscillatory activities of central pattern generators (CPGs) and body motion. However, it has also been shown that the time delay in the sensorimotor loop can destabilize mutual entrainment and result in the failure to walk. In this study, a new mechanism called flexible-phase locking is proposed to overcome the time delay. It is realized by employing the Bonhoeffer-Van der Pol formalism - well known as a physiologically faithful neuronal model - for neurons in the CPG. The formalism states that neurons modulate their phase according to the delay so that mutual entrainment is stabilized. Flexible-phase locking derives from the phase dynamics related to an asymptotically stable limit cycle of the neuron. The effectiveness of the mechanism is verified by computer simulations of a bipedal locomotion model. PMID:14999479
NASA Technical Reports Server (NTRS)
Baer-Riedhart, Jennifer L.; Landy, Robert J.
1987-01-01
The highly integrated digital electronic control (HIDEC) program at NASA Ames Research Center, Dryden Flight Research Facility is a multiphase flight research program to quantify the benefits of promising integrated control systems. McDonnell Aircraft Company is the prime contractor, with United Technologies Pratt and Whitney Aircraft, and Lear Siegler Incorporated as major subcontractors. The NASA F-15A testbed aircraft was modified by the HIDEC program by installing a digital electronic flight control system (DEFCS) and replacing the standard F100 (Arab 3) engines with F100 engine model derivative (EMD) engines equipped with digital electronic engine controls (DEEC), and integrating the DEEC's and DEFCS. The modified aircraft provides the capability for testing many integrated control modes involving the flight controls, engine controls, and inlet controls. This paper focuses on the first two phases of the HIDEC program, which are the digital flight control system/aircraft model identification (DEFCS/AMI) phase and the adaptive engine control system (ADECS) phase.
An online novel adaptive filter for denoising time series measurements.
Willis, Andrew J
2006-04-01
A nonstationary form of the Wiener filter based on a principal components analysis is described for filtering time series data possibly derived from noisy instrumentation. The theory of the filter is developed, implementation details are presented and two examples are given. The filter operates online, approximating the maximum a posteriori optimal Bayes reconstruction of a signal with arbitrarily distributed and non stationary statistics. PMID:16649562
Adaptive Haar transforms with arbitrary time and scale splitting
NASA Astrophysics Data System (ADS)
Egiazarian, Karen O.; Astola, Jaakko T.
2001-05-01
The Haar transform is generalized to the case of an arbitrary time and scale splitting. To any binary tree we associate an orthogonal system of Haar-type functions - tree-structured Haar (TSH) functions. Unified fast algorithm for computation of the introduced tree-structured Haar transforms is presented. It requires 2(N - 1) additions and 3N - 2 multiplications, where N is transform order or, equivalently, the number of leaves of the binary tree.
Assessment of Disaster Risk Reduction and Climate Change Adaptation policy integration in Zambia
NASA Astrophysics Data System (ADS)
Pilli-Sihvola, K.; Väätäinen-Chimpuku, S.
2015-12-01
Integration of Disaster Risk Management (DRM) and Climate Change Adaptation (CCA) policies, their implementation measures and the contribution of these to development has been gaining attention recently. Due to the shared objectives of CCA and particularly Disaster Risk Reduction (DRR), a component of DRM, their integration provides many benefits. At the implementation level, DRR and CCA are usually integrated. Policy integration, however, is often lacking. This study presents a novel analysis of the policy integration of DRR and CCA by 1) suggesting a definition for their integration at a general and further at horizontal and vertical levels, 2) using an analysis framework for policy integration cycle, which separates the policy formulation and implementation processes, and 3) applying these to a case study in Zambia. Moreover, the study identifies the key gaps in the integration process, obtains an understanding of identified key factors for creating an enabling environment for the integration, and provides recommendations for further progress. The study is based on a document analysis of the relevant DRM, climate change (CC), agriculture, forestry, water management and meteorology policy documents and Acts, and 21 semi-structured interviews with key stakeholders. Horizontal integration has occurred both ways, as the revised DRM policy draft has incorporated CCA, and the new CC policy draft has incorporated DRR. This is not necessarily an optimal strategy and unless carefully implemented, it may create pressure on institutional structures and duplication of efforts in the implementation. Much less vertical integration takes place, and where it does, no guidance on how potential goal conflicts with sectorial and development objectives ought to be handled. The objectives of the instruments show convergence. At the programme stage, the measures are fully integrated as they can be classified as robust CCA measures, providing benefits in the current and future
Adaptive spark timing controller for an internal combustion engine
Javaherian, H.
1989-09-19
This patent describes a system for controlling the ignition timing angle in the ignition control system for an internal combustion engine having cylinders and an output crankshaft rotated during operation of the engine. The ignition control system initiating combustion in each cylinder of the engine at the determined ignition timing value. The system comprising, in combination: means for determining the start of combustion in a cylinder; means for monitoring the value of an indicator function during rotation of the crankshaft after the start of combustion; means for sensing the fpeak value of the indicator function; means for determining the crankshaft angle at which the value of the indicator function is one half the sume of the values of the indicator function at the start of combustion and the peak value occurring at the end of combustion; and means for controlling the ignition timing angle to initiate combustion in the cylinders to establish the crankshaft angle and therefore the cylinder burn establish the crankshaft angle and therefore the cylinder burn center at a predetermined crankshaft angle.
Shaping the Cities of Tomorrow: Integrating Local Urban Adaptation within an Environmental Framework
NASA Astrophysics Data System (ADS)
Georgescu, M.
2014-12-01
Contemporary methods focused on increasing urban sustainability are largely based on the reduction of greenhouse gas emissions. While these efforts are essential steps forward, continued characterization of urban sustainability solely within a biogeochemical framework, with neglect of the biophysical impact of the built environment, omits regional hydroclimatic forcing of the same order of magnitude as greenhouse gas emissions. Using a suite of continuous, multi-year and multi-member continental scale numerical simulations with the WRF model for the U.S., we examine hydroclimatic impacts for a variety of U.S. urban expansion scenarios (for the year 2100) and urban adaptation futures (cool roofs, green roofs, and a hypothetical hybrid approach integrating biophysical properties of both cool and green roofs), and compare those to experiments utilizing a contemporary urban extent. Widespread adoption of adaptation strategies exhibits regionally and seasonally dependent hydroclimatic impacts. For some regions and seasons, urban-induced warming in excess of 3°C can be completely offset by all adaptation approaches examined. For other regions, widespread adoption of some adaptation approaches leads to significant rainfall decline. Sustainable urban expansion therefore requires an integrated assessment that also incorporates biophysically induced urban impacts, and demands tradeoff assessment of various strategies aimed to ameliorate deleterious consequences of growth (e.g., urban heat island reduction).
Zhou, Qianqian; Panduro, Toke Emil; Thorsen, Bo Jellesmark; Arnbjerg-Nielsen, Karsten
2013-03-01
This paper presents a cross-disciplinary framework for assessment of climate change adaptation to increased precipitation extremes considering pluvial flood risk as well as additional environmental services provided by some of the adaptation options. The ability of adaptation alternatives to cope with extreme rainfalls is evaluated using a quantitative flood risk approach based on urban inundation modeling and socio-economic analysis of corresponding costs and benefits. A hedonic valuation model is applied to capture the local economic gains or losses from more water bodies in green areas. The framework was applied to the northern part of the city of Aarhus, Denmark. We investigated four adaptation strategies that encompassed laissez-faire, larger sewer pipes, local infiltration units, and open drainage system in the urban green structure. We found that when taking into account environmental amenity effects, an integration of open drainage basins in urban recreational areas is likely the best adaptation strategy, followed by pipe enlargement and local infiltration strategies. All three were improvements compared to the fourth strategy of no measures taken. PMID:23334752
NASA Astrophysics Data System (ADS)
Zhou, Qianqian; Panduro, Toke Emil; Thorsen, Bo Jellesmark; Arnbjerg-Nielsen, Karsten
2013-03-01
This paper presents a cross-disciplinary framework for assessment of climate change adaptation to increased precipitation extremes considering pluvial flood risk as well as additional environmental services provided by some of the adaptation options. The ability of adaptation alternatives to cope with extreme rainfalls is evaluated using a quantitative flood risk approach based on urban inundation modeling and socio-economic analysis of corresponding costs and benefits. A hedonic valuation model is applied to capture the local economic gains or losses from more water bodies in green areas. The framework was applied to the northern part of the city of Aarhus, Denmark. We investigated four adaptation strategies that encompassed laissez-faire, larger sewer pipes, local infiltration units, and open drainage system in the urban green structure. We found that when taking into account environmental amenity effects, an integration of open drainage basins in urban recreational areas is likely the best adaptation strategy, followed by pipe enlargement and local infiltration strategies. All three were improvements compared to the fourth strategy of no measures taken.
Reframing the challenges to integrated care: a complex-adaptive systems perspective
Tsasis, Peter; Evans, Jenna M; Owen, Susan
2012-01-01
Introduction Despite over two decades of international experience and research on health systems integration, integrated care has not developed widely. We hypothesized that part of the problem may lie in how we conceptualize the integration process and the complex systems within which integrated care is enacted. This study aims to contribute to discourse regarding the relevance and utility of a complex-adaptive systems (CAS) perspective on integrated care. Methods In the Canadian province of Ontario, government mandated the development of fourteen Local Health Integration Networks in 2006. Against the backdrop of these efforts to integrate care, we collected focus group data from a diverse sample of healthcare professionals in the Greater Toronto Area using convenience and snowball sampling. A semi-structured interview guide was used to elicit participant views and experiences of health systems integration. We use a CAS framework to describe and analyze the data, and to assess the theoretical fit of a CAS perspective with the dominant themes in participant responses. Results Our findings indicate that integration is challenged by system complexity, weak ties and poor alignment among professionals and organizations, a lack of funding incentives to support collaborative work, and a bureaucratic environment based on a command and control approach to management. Using a CAS framework, we identified several characteristics of CAS in our data, including diverse, interdependent and semi-autonomous actors; embedded co-evolutionary systems; emergent behaviours and non-linearity; and self-organizing capacity. Discussion and conclusion One possible explanation for the lack of systems change towards integration is that we have failed to treat the healthcare system as complex-adaptive. The data suggest that future integration initiatives must be anchored in a CAS perspective, and focus on building the system’s capacity to self-organize. We conclude that integrating care
Non-electrical-power temperature-time integrating sensor for RFID based on microfluidics
NASA Astrophysics Data System (ADS)
Schneider, Mike; Hoffmann, Martin
2011-06-01
The integration of RFID tags into packages offers the opportunity to combine logistic advantages of the technology with monitoring different parameters from inside the package at the same time. An essential demand for enhanced product safety especially in pharmacy or food industry is the monitoring of the time-temperature-integral. Thus, completely passive time-temperature-integrators (TTI) requiring no battery, microprocessor nor data logging devices are developed. TTI representing the sterilization process inside an autoclave system is a demanding challenge: a temperature of at least 120 °C have to be maintained over 45 minutes to assure that no unwanted organism remains. Due to increased temperature, the viscosity of a fluid changes and thus the speed of the fluid inside the channel increases. The filled length of the channel represents the time temperature integral affecting the system. Measurements as well as simulations allow drawing conclusions about the influence of the geometrical parameters of the system and provide the possibility of adaptation. Thus a completely passive sensor element for monitoring an integral parameter with waiving of external electrical power supply and data processing technology is demonstrated. Furthermore, it is shown how to adjust the specific TTI parameters of the sensor to different applications and needs by modifying the geometrical parameters of the system.
Time course of adaptation to stimuli presented along cardinal lines in color space
NASA Astrophysics Data System (ADS)
Hughes, Alan; Demarco, Paul J.
2003-12-01
Visual sensitivity is a process that allows the visual system to maintain optimal response over a wide range of ambient light levels and chromaticities. Several studies have used variants of the probe-flash paradigm to show that the time course of adaptation to abrupt changes in ambient luminance depends on both receptoral and postreceptoral mechanisms. Though a few studies have explored how these processes govern adaptation to color changes, most of this effort has targeted the L-M-cone pathway. The purpose of our work was to use the probe-flash paradigm to more fully explore light adaptation in both the L-M- and the S-cone pathways. We measured sensitivity to chromatic probes presented after the onset of a 2-s chromatic flash. Test and flash stimuli were spatially coextensive 2° fields presented in Maxwellian view. Flash stimuli were presented as excursions from white and could extended in one of two directions along an equiluminant L-M-cone or S-cone line. Probes were presented as excursions from the adapting flash chromaticity and could extend either toward the spectrum locus or toward white. For both color lines, the data show a fast and slow adaptation component, although this was less evident in the S-cone data. The fast and slow components were modeled as first- and second-site adaptive processes, respectively. We find that the time course of adaptation is different for the two cardinal pathways. In addition, the time course for S-cone stimulation is polarity dependent. Our results characterize the rapid time course of adaptation in the chromatic pathways and reveal that the mechanics of adaptation within the S-cone pathway are distinct from those in the L-M-cone pathways.
ARTEMIS: Ares Real Time Environments for Modeling, Integration, and Simulation
NASA Technical Reports Server (NTRS)
Hughes, Ryan; Walker, David
2009-01-01
This slide presentation reviews the use of ARTEMIS in the development and testing of the ARES launch vehicles. Ares Real Time Environment for Modeling, Simulation and Integration (ARTEMIS) is the real time simulation supporting Ares I hardware-in-the-loop (HWIL) testing. ARTEMIS accurately models all Ares/Orion/Ground subsystems which interact with Ares avionics components from pre-launch through orbit insertion The ARTEMIS System integration Lab, and the STIF architecture is reviewed. The functional components of ARTEMIS are outlined. An overview of the models and a block diagram is presented.
Integration time in space experiments to test the equivalence principle
NASA Astrophysics Data System (ADS)
Nobili, A. M.; Pegna, R.; Shao, M.; Turyshev, S. G.; Catastini, G.; Anselmi, A.; Spero, R.; Doravari, S.; Comandi, G. L.; Lucchesi, D. M.; De Michele, A.
2014-02-01
The integration time required by space experiments to perform high accuracy tests of the universality of free fall and the weak equivalence principle is a crucial issue. It is inversely proportional to the square of the acceleration to be measured, which is extremely small; the duration of the mission is a severe limitation and experiments in space lack repeatability. An exceedingly long integration time can therefore rule out a mission target. We have evaluated the integration time due to thermal noise from gas damping, Johnson noise and eddy currents—which are independent of the signal frequency—and to internal damping, which is known to decrease with increasing frequency. It is found that at low frequencies thermal noise from internal damping dominates. In the "Galileo Galilei" proposed space experiment to test the equivalence principle to 10-17 the rapid rotation of the satellite (1 Hz) up-converts the signal to a frequency region where thermal noise from internal damping is lower than gas damping and only a factor 2 higher than Johnson noise, with a total integration time of 2.4 to 3.5 hours even in a very conservative estimate. With an adequate readout and additional care in reducing systematics the test could be improved by another order of magnitude, close to 10-18, requiring a hundred times longer—still affordable—integration time of 10 to 14.6 days. μSCOPE, a similar room temperature mission under construction by the French space agency to be launched in 2015, aims at a 10-15 test with an estimated integration time of 1.4 days. Space tests using cold atoms and atom interferometry have been proposed to be performed on the space station (Q-WEP, to 10-14) and on a dedicated mission (STE-QUEST, to 10-15 like μSCOPE). In this case integration is required in order to reduce single shot noise. European Space Agency funded studies report an integration time of several months and a few years respectively.
Griffith, T M; Watson, M A
2005-11-01
Adaptation to local environments may be an important determinant of species' geographic range. However, little is known about which traits contribute to adaptation or whether their further evolution would facilitate range expansion. In this study, we assessed the adaptive value of stress avoidance traits in the common annual Cocklebur (Xanthium strumarium) by performing a reciprocal transplant across a broad latitudinal gradient extending to the species' northern border. Populations were locally adapted and stress avoidance traits accounted for most fitness differences between populations. At the northern border where growing seasons are cooler and shorter, native populations had evolved to reproduce earlier than native populations in the lower latitude gardens. This clinal pattern in reproductive timing corresponded to a shift in selection from favouring later to earlier reproduction. Thus, earlier reproduction is an important adaptation to northern latitudes and constraint on the further evolution of this trait in marginal populations could potentially limit distribution. PMID:16313471
A model of interval timing by neural integration
Simen, Patrick; Balci, Fuat; deSouza, Laura; Cohen, Jonathan D.; Holmes, Philip
2011-01-01
We show that simple assumptions about neural processing lead to a model of interval timing as a temporal integration process, in which a noisy firing-rate representation of time rises linearly on average toward a response threshold over the course of an interval. Our assumptions include: that neural spike trains are approximately independent Poisson processes; that correlations among them can be largely cancelled by balancing excitation and inhibition; that neural populations can act as integrators; and that the objective of timed behavior is maximal accuracy and minimal variance. The model accounts for a variety of physiological and behavioral findings in rodents, monkeys and humans, including ramping firing rates between the onset of reward-predicting cues and the receipt of delayed rewards, and universally scale-invariant response time distributions in interval timing tasks. It furthermore makes specific, well-supported predictions about the skewness of these distributions, a feature of timing data that is usually ignored. The model also incorporates a rapid (potentially one-shot) duration-learning procedure. Human behavioral data support the learning rule’s predictions regarding learning speed in sequences of timed responses. These results suggest that simple, integration-based models should play as prominent a role in interval timing theory as they do in theories of perceptual decision making, and that a common neural mechanism may underlie both types of behavior. PMID:21697374
NASA Astrophysics Data System (ADS)
Bargatze, L. F.
2015-12-01
Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted
Morbey, Yolanda E; Jensen, Evelyn L; Russello, Michael A
2014-01-01
Seasonal declines of fitness-related traits are often attributed to environmental effects or individual-level decisions about reproductive timing and effort, but genetic variation may also play a role. In populations of Pacific salmon (Oncorhynchus spp.), seasonal declines in reproductive life span have been attributed to adaptation-by-time, in which divergent selection for different traits occurs among reproductively isolated temporal components of a population. We evaluated this hypothesis in kokanee (freshwater obligate Oncorhynchus nerka) by testing for temporal genetic structure in neutral and circadian-linked loci. We detected no genetic differences in presumably neutral loci among kokanee with different arrival and maturation dates within a spawning season. Similarly, we detected no temporal genetic structure in OtsClock1b, Omy1009uw, or OmyFbxw11, candidate loci associated with circadian function. The genetic evidence from this study and others indicates a lack of support for adaptation-by-time as an important evolutionary mechanism underlying seasonal declines in reproductive life span and a need for greater consideration of other mechanisms such as time-dependent, adaptive adjustment of reproductive effort. PMID:25478160
NASA Astrophysics Data System (ADS)
Xie, Huijuan; Gong, Yubing; Wang, Qi
2016-06-01
In this paper, we numerically study how time delay induces multiple coherence resonance (MCR) and synchronization transitions (ST) in adaptive Hodgkin-Huxley neuronal networks with spike-timing dependent plasticity (STDP). It is found that MCR induced by time delay STDP can be either enhanced or suppressed as the adjusting rate Ap of STDP changes, and ST by time delay varies with the increase of Ap, and there is optimal Ap by which the ST becomes strongest. It is also found that there are optimal network randomness and network size by which ST by time delay becomes strongest, and when Ap increases, the optimal network randomness and optimal network size increase and related ST is enhanced. These results show that STDP can either enhance or suppress MCR and optimal STDP can enhance ST induced by time delay in the adaptive neuronal networks. These findings provide a new insight into STDP's role for the information processing and transmission in neural systems.
Impact of space-time mesh adaptation on solute transport modeling in porous media
NASA Astrophysics Data System (ADS)
Esfandiar, Bahman; Porta, Giovanni; Perotto, Simona; Guadagnini, Alberto
2015-02-01
We implement a space-time grid adaptation procedure to efficiently improve the accuracy of numerical simulations of solute transport in porous media in the context of model parameter estimation. We focus on the Advection Dispersion Equation (ADE) for the interpretation of nonreactive transport experiments in laboratory-scale heterogeneous porous media. When compared to a numerical approximation based on a fixed space-time discretization, our approach is grounded on a joint automatic selection of the spatial grid and the time step to capture the main (space-time) system dynamics. Spatial mesh adaptation is driven by an anisotropic recovery-based error estimator which enables us to properly select the size, shape, and orientation of the mesh elements. Adaptation of the time step is performed through an ad hoc local reconstruction of the temporal derivative of the solution via a recovery-based approach. The impact of the proposed adaptation strategy on the ability to provide reliable estimates of the key parameters of an ADE model is assessed on the basis of experimental solute breakthrough data measured following tracer injection in a nonuniform porous system. Model calibration is performed in a Maximum Likelihood (ML) framework upon relying on the representation of the ADE solution through a generalized Polynomial Chaos Expansion (gPCE). Our results show that the proposed anisotropic space-time grid adaptation leads to ML parameter estimates and to model results of markedly improved quality when compared to classical inversion approaches based on a uniform space-time discretization.
Analysis of a Real-Time Separation Assurance System with Integrated Time-in-Trail Spacing
NASA Technical Reports Server (NTRS)
Aweiss, Arwa S.; Farrahi, Amir H.; Lauderdale, Todd A.; Thipphavong, Adam S.; Lee, Chu H.
2010-01-01
This paper describes the implementation and analysis of an integrated ground-based separation assurance and time-based metering prototype system into the Center-TRACON Automation System. The integration of this new capability accommodates constraints in four-dimensions: position (x-y), altitude, and meter-fix crossing time. Experiments were conducted to evaluate the performance of the integrated system and its ability to handle traffic levels up to twice that of today. Results suggest that the integrated system reduces the number and magnitude of time-in-trail spacing violations. This benefit was achieved without adversely affecting the resolution success rate of the system. Also, the data suggest that the integrated system is relatively insensitive to an increase in traffic of twice the current levels.
Energy Science and Technology Software Center (ESTSC)
2014-06-01
ARKode is part of a software family called SUNDIALS: SUite of Nonlinear and Differential/ALgebraic equation Solvers [1]. The ARKode solver library provides an adaptive-step time integration package for stiff, nonstiff and multi-rate systems of ordinary differential equations (ODEs) using Runge Kutta methods [2].
Does it pay to delay? Flesh flies show adaptive plasticity in reproductive timing.
Wessels, Frank J; Kristal, Ross; Netter, Fleta; Hatle, John D; Hahn, Daniel A
2011-02-01
Life-history plasticity is widespread among organisms. However, an important question is whether it is adaptive. Most models for plasticity in life-history timing predict that animals, once they have reached the minimal nutritional threshold under poor conditions, will accelerate development or time to reproduction. Adaptive delays in reproduction are not common, especially in short-lived species. Examples of adaptive reproductive delays exist in mammalian populations experiencing strong interspecific (e.g., predation) and intraspecific (e.g., infanticide) competition. But are there other environmental factors that may trigger an adaptive delay in reproductive timing? We show that the short-lived flesh fly Sarcophaga crassipalpis will delay reproduction under nutrient-poor conditions, even though it has already met the minimal nutritional threshold for reproduction. We test whether this delay strategy is an adaptive response allowing the scavenger time to locate more resources by experimentally providing supplemental protein pulses (early, mid and late) throughout the reproductive delay period. Flies receiving additional protein produced more and larger eggs, demonstrating a benefit of the delay. In addition, by tracking the allocation of carbon from the pulses using stable isotopes, we show that flies receiving earlier pulses incorporated more carbon into eggs and somatic tissue than those given a later pulse. These results indicate that the reproductive delay in S. crassipalpis is consistent with adaptive post-threshold plasticity, a nutritionally linked reproductive strategy that has not been reported previously in an invertebrate species. PMID:20953961
Optimized quantum sensing with a single electron spin using real-time adaptive measurements
NASA Astrophysics Data System (ADS)
Bonato, C.; Blok, M. S.; Dinani, H. T.; Berry, D. W.; Markham, M. L.; Twitchen, D. J.; Hanson, R.
2016-03-01
Quantum sensors based on single solid-state spins promise a unique combination of sensitivity and spatial resolution. The key challenge in sensing is to achieve minimum estimation uncertainty within a given time and with high dynamic range. Adaptive strategies have been proposed to achieve optimal performance, but their implementation in solid-state systems has been hindered by the demanding experimental requirements. Here, we realize adaptive d.c. sensing by combining single-shot readout of an electron spin in diamond with fast feedback. By adapting the spin readout basis in real time based on previous outcomes, we demonstrate a sensitivity in Ramsey interferometry surpassing the standard measurement limit. Furthermore, we find by simulations and experiments that adaptive protocols offer a distinctive advantage over the best known non-adaptive protocols when overhead and limited estimation time are taken into account. Using an optimized adaptive protocol we achieve a magnetic field sensitivity of 6.1 ± 1.7 nT Hz-1/2 over a wide range of 1.78 mT. These results open up a new class of experiments for solid-state sensors in which real-time knowledge of the measurement history is exploited to obtain optimal performance.
On the Computation of Integral Curves in Adaptive Mesh Refinement Vector Fields
Deines, Eduard; Weber, Gunther H.; Garth, Christoph; Van Straalen, Brian; Borovikov, Sergey; Martin, Daniel F.; Joy, Kenneth I.
2011-06-27
Integral curves, such as streamlines, streaklines, pathlines, and timelines, are an essential tool in the analysis of vector field structures, offering straightforward and intuitive interpretation of visualization results. While such curves have a long-standing tradition in vector field visualization, their application to Adaptive Mesh Refinement (AMR) simulation results poses unique problems. AMR is a highly effective discretization method for a variety of physical simulation problems and has recently been applied to the study of vector fields in flow and magnetohydrodynamic applications. The cell-centered nature of AMR data and discontinuities in the vector field representation arising from AMR level boundaries complicate the application of numerical integration methods to compute integral curves. In this paper, we propose a novel approach to alleviate these problems and show its application to streamline visualization in an AMR model of the magnetic field of the solar system as well as to a simulation of two incompressible viscous vortex rings merging.
Stability of mixed time integration schemes for transient thermal analysis
NASA Technical Reports Server (NTRS)
Liu, W. K.; Lin, J. I.
1982-01-01
A current research topic in coupled-field problems is the development of effective transient algorithms that permit different time integration methods with different time steps to be used simultaneously in various regions of the problems. The implicit-explicit approach seems to be very successful in structural, fluid, and fluid-structure problems. This paper summarizes this research direction. A family of mixed time integration schemes, with the capabilities mentioned above, is also introduced for transient thermal analysis. A stability analysis and the computer implementation of this technique are also presented. In particular, it is shown that the mixed time implicit-explicit methods provide a natural framework for the further development of efficient, clean, modularized computer codes.
A general time element for orbit integration in Cartesian coordinates
NASA Technical Reports Server (NTRS)
Janin, G.; Bond, V. R.
1981-01-01
Two techniques are discussed for increasing the accuracy of the numerical integration of eccentric orbits in Cartesian coordinates. One involves the use of an independent variable different from time; this increases the efficiency of the numerical integration. The other uses a time element, which reduces the in-track error. A general expression is given of a time element valid for an arbitrary independent variable. It is pointed out that this time element makes it possible to switch the independent variable merely by applying a scaling factor; there is no need to change the differential equations of the motion. Eccentric, true, and elliptic anomalies are used as independent variables in the case of a transfer orbit for a geosynchronous orbit. The elliptic anomaly is shown to perform much better than the other classical anomalies.
Orientation, Evaluation, and Integration of Part-Time Nursing Faculty.
Carlson, Joanne S
2015-01-01
This study helps to quantify and describe orientation, evaluation, and integration practices pertaining to part-time clinical nursing faculty teaching in prelicensure nursing education programs. A researcher designed Web-based survey was used to collect information from a convenience sample of part-time clinical nursing faculty teaching in prelicensure nursing programs. Survey questions focused on the amount and type of orientation, evaluation, and integration practices. Descriptive statistics were used to analyze results. Respondents reported on average four hours of orientation, with close to half reporting no more than two hours. Evaluative feedback was received much more often from students than from full-time faculty. Most respondents reported receiving some degree of mentoring and that it was easy to get help from full-time faculty. Respondents reported being most informed about student evaluation procedures, grading, and the steps to take when students are not meeting course objectives, and less informed about changes to ongoing curriculum and policy. PMID:26151905
Integrable nonlinear parity-time-symmetric optical oscillator
NASA Astrophysics Data System (ADS)
Hassan, Absar U.; Hodaei, Hossein; Miri, Mohammad-Ali; Khajavikhan, Mercedeh; Christodoulides, Demetrios N.
2016-04-01
The nonlinear dynamics of a balanced parity-time-symmetric optical microring arrangement are analytically investigated. By considering gain and loss saturation effects, the pertinent conservation laws are explicitly obtained in the Stokes domain, thus establishing integrability. Our analysis indicates the existence of two regimes of oscillatory dynamics and frequency locking, both of which are analogous to those expected in linear parity-time-symmetric systems. Unlike other saturable parity-time-symmetric systems considered before, the model studied in this work first operates in the symmetric regime and then enters the broken parity-time phase.
NASA Astrophysics Data System (ADS)
Meng, Yang; Gao, Shesheng; Zhong, Yongmin; Hu, Gaoge; Subic, Aleksandar
2016-03-01
The use of the direct filtering approach for INS/GNSS integrated navigation introduces nonlinearity into the system state equation. As the unscented Kalman filter (UKF) is a promising method for nonlinear problems, an obvious solution is to incorporate the UKF concept in the direct filtering approach to address the nonlinearity involved in INS/GNSS integrated navigation. However, the performance of the standard UKF is dependent on the accurate statistical characterizations of system noise. If the noise distributions of inertial instruments and GNSS receivers are not appropriately described, the standard UKF will produce deteriorated or even divergent navigation solutions. This paper presents an adaptive UKF with noise statistic estimator to overcome the limitation of the standard UKF. According to the covariance matching technique, the innovation and residual sequences are used to determine the covariance matrices of the process and measurement noises. The proposed algorithm can estimate and adjust the system noise statistics online, and thus enhance the adaptive capability of the standard UKF. Simulation and experimental results demonstrate that the performance of the proposed algorithm is significantly superior to that of the standard UKF and adaptive-robust UKF under the condition without accurate knowledge on system noise, leading to improved navigation precision.
Factors Related to Adaptation to Cystectomy With Urinary Diversion: An Integrative Review.
Merandy, Kyle
2016-01-01
Patients with bladder (urothelial) cancer undergoing urinary diversion (UD) experience physical changes that require important adjustments in their daily lives. This integrative review aims to identify factors that influence adult adaptation to life after cystectomy with the creation of a UD. A review of primary research articles published between 1990 and 2014 was conducted using the PubMed and CINAHL Plus electronic databases. Results of the studies were summarized into 5 categories: (1) individual and family factors, (2) technical aspects related to the individual's ability to care for his or her UD, (3) perioperative nursing care, (4) educational needs, and (5) symptom experience. Bladder cancer patients treated with a cystectomy with a UD have a complex set of needs during postoperative adaptation to their reconstructed urinary system. This integrative review summarizes existing knowledge of factors that affect adaptation to a UD in patients with bladder cancer and may guide future studies. Research on this is limited and more studies are needed. PMID:27607746
The Weight of Time: Affordances for an Integrated Magnitude System
ERIC Educational Resources Information Center
Lu, Aitao; Mo, Lei; Hodges, Bert H.
2011-01-01
In five experiments we explored the effects of weight on time in different action contexts to test the hypothesis that an integrated magnitude system is tuned to affordances. Larger magnitudes generally seem longer; however, Lu and colleagues (2009) found that if numbers were presented as weights in a range heavy enough to affect lifting, the…
Early Pubertal Timing and Girls' Problem Behavior: Integrating Two Hypotheses
ERIC Educational Resources Information Center
Stattin, Hakan; Kerr, Margaret; Skoog, Therese
2011-01-01
Girls' early pubertal timing has been linked in many studies to behavioral problems such as delinquency and substance use. The theoretical explanations for these links have often involved the girls' peer relationships, but contexts have also been considered important in some explanations. By integrating two theoretical models, the…