Integrated model reference adaptive control and time-varying angular rate estimation for micro-machined gyroscopes

NASA Astrophysics Data System (ADS)

Tsai, Nan-Chyuan; Sue, Chung-Yang

2010-02-01

Owing to the imposed but undesired accelerations such as quadrature error and cross-axis perturbation, the micro-machined gyroscope would not be unconditionally retained at resonant mode. Once the preset resonance is not sustained, the performance of the micro-gyroscope is accordingly degraded. In this article, a direct model reference adaptive control loop which is integrated with a modified disturbance estimating observer (MDEO) is proposed to guarantee the resonant oscillations at drive mode and counterbalance the undesired disturbance mainly caused by quadrature error and cross-axis perturbation. The parameters of controller are on-line innovated by the dynamic error between the MDEO output and expected response. In addition, Lyapunov stability theory is employed to examine the stability of the closed-loop control system. Finally, the efficacy of numerical evaluation on the exerted time-varying angular rate, which is to be detected and measured by the gyroscope, is verified by intensive simulations.

Fuzzy Adaptive Cubature Kalman Filter for Integrated Navigation Systems.

PubMed

Tseng, Chien-Hao; Lin, Sheng-Fuu; Jwo, Dah-Jing

2016-07-26

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.

Fuzzy Adaptive Cubature Kalman Filter for Integrated Navigation Systems

PubMed Central

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

Integrated Power Adapter: Isolated Converter with Integrated Passives and Low Material Stress

DOE Office of Scientific and Technical Information (OSTI.GOV)

None

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 materialsmore » 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.« less

Cultural adaptation and translation of measures: an integrated method.

PubMed

Sidani, Souraya; Guruge, Sepali; Miranda, Joyal; Ford-Gilboe, Marilyn; Varcoe, Colleen

2010-04-01

Differences in the conceptualization and operationalization of health-related concepts may exist across cultures. Such differences underscore the importance of examining conceptual equivalence when adapting and translating instruments. In this article, we describe an integrated method for exploring conceptual equivalence within the process of adapting and translating measures. The integrated method involves five phases including selection of instruments for cultural adaptation and translation; assessment of conceptual equivalence, leading to the generation of a set of items deemed to be culturally and linguistically appropriate to assess the concept of interest in the target community; forward translation; back translation (optional); and pre-testing of the set of items. Strengths and limitations of the proposed integrated method are discussed. (c) 2010 Wiley Periodicals, Inc.

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.

Considerations about expected a posteriori estimation in adaptive testing: adaptive a priori, adaptive correction for bias, and adaptive integration interval.

PubMed

Raiche, Gilles; Blais, Jean-Guy

2009-01-01

In a computerized adaptive test, we would like to obtain an acceptable precision of the proficiency level estimate using an optimal number of items. Unfortunately, decreasing the number of items is accompanied by a certain degree of bias when the true proficiency level differs significantly from the a priori estimate. The authors suggest that it is possible to reduced the bias, and even the standard error of the estimate, by applying to each provisional estimation one or a combination of the following strategies: adaptive correction for bias proposed by Bock and Mislevy (1982), adaptive a priori estimate, and adaptive integration interval.

Crossmodal Adaptation in Right Posterior Superior Temporal Sulcus during Face–Voice Emotional Integration

PubMed Central

Latinus, Marianne; Noguchi, Takao; Garrod, Oliver; Crabbe, Frances; Belin, Pascal

2014-01-01

The integration of emotional information from the face and voice of other persons is known to be mediated by a number of “multisensory” cerebral regions, such as the right posterior superior temporal sulcus (pSTS). However, whether multimodal integration in these regions is attributable to interleaved populations of unisensory neurons responding to face or voice or rather by multimodal neurons receiving input from the two modalities is not fully clear. Here, we examine this question using functional magnetic resonance adaptation and dynamic audiovisual stimuli in which emotional information was manipulated parametrically and independently in the face and voice via morphing between angry and happy expressions. Healthy human adult subjects were scanned while performing a happy/angry emotion categorization task on a series of such stimuli included in a fast event-related, continuous carryover design. Subjects integrated both face and voice information when categorizing emotion—although there was a greater weighting of face information—and showed behavioral adaptation effects both within and across modality. Adaptation also occurred at the neural level: in addition to modality-specific adaptation in visual and auditory cortices, we observed for the first time a crossmodal adaptation effect. Specifically, fMRI signal in the right pSTS was reduced in response to a stimulus in which facial emotion was similar to the vocal emotion of the preceding stimulus. These results suggest that the integration of emotional information from face and voice in the pSTS involves a detectable proportion of bimodal neurons that combine inputs from visual and auditory cortices. PMID:24828635

Real-time adaptive ramp metering : phase I, MILOS proof of concept (multi-objective, integrated, large-scale, optimized system).

DOT National Transportation Integrated Search

2006-12-01

Over the last several years, researchers at the University of Arizonas ATLAS Center have developed an adaptive ramp : metering system referred to as MILOS (Multi-Objective, Integrated, Large-Scale, Optimized System). The goal of this project : is ...

Real-time range acquisition by adaptive structured light.

PubMed

Koninckx, Thomas P; Van Gool, Luc

2006-03-01

The goal of this paper is to provide a "self-adaptive" system for real-time range acquisition. Reconstructions are based on a single frame structured light illumination. Instead of using generic, static coding that is supposed to work under all circumstances, system adaptation is proposed. This occurs on-the-fly and renders the system more robust against instant scene variability and creates suitable patterns at startup. A continuous trade-off between speed and quality is made. A weighted combination of different coding cues--based upon pattern color, geometry, and tracking--yields a robust way to solve the correspondence problem. The individual coding cues are automatically adapted within a considered family of patterns. The weights to combine them are based on the average consistency with the result within a small time-window. The integration itself is done by reformulating the problem as a graph cut. Also, the camera-projector configuration is taken into account for generating the projection patterns. The correctness of the range maps is not guaranteed, but an estimation of the uncertainty is provided for each part of the reconstruction. Our prototype is implemented using unmodified consumer hardware only and, therefore, is cheap. Frame rates vary between 10 and 25 fps, dependent on scene complexity.

Adaptive multitaper time-frequency spectrum estimation

NASA Astrophysics Data System (ADS)

Pitton, James W.

1999-11-01

In earlier work, Thomson's adaptive multitaper spectrum estimation method was extended to the nonstationary case. This paper reviews the time-frequency multitaper method and the adaptive procedure, and explores some properties of the eigenvalues and eigenvectors. The variance of the adaptive estimator is used to construct an adaptive smoother, which is used to form a high resolution estimate. An F-test for detecting and removing sinusoidal components in the time-frequency spectrum is also given.

Crossmodal adaptation in right posterior superior temporal sulcus during face-voice emotional integration.

PubMed

Watson, Rebecca; Latinus, Marianne; Noguchi, Takao; Garrod, Oliver; Crabbe, Frances; Belin, Pascal

2014-05-14

The integration of emotional information from the face and voice of other persons is known to be mediated by a number of "multisensory" cerebral regions, such as the right posterior superior temporal sulcus (pSTS). However, whether multimodal integration in these regions is attributable to interleaved populations of unisensory neurons responding to face or voice or rather by multimodal neurons receiving input from the two modalities is not fully clear. Here, we examine this question using functional magnetic resonance adaptation and dynamic audiovisual stimuli in which emotional information was manipulated parametrically and independently in the face and voice via morphing between angry and happy expressions. Healthy human adult subjects were scanned while performing a happy/angry emotion categorization task on a series of such stimuli included in a fast event-related, continuous carryover design. Subjects integrated both face and voice information when categorizing emotion-although there was a greater weighting of face information-and showed behavioral adaptation effects both within and across modality. Adaptation also occurred at the neural level: in addition to modality-specific adaptation in visual and auditory cortices, we observed for the first time a crossmodal adaptation effect. Specifically, fMRI signal in the right pSTS was reduced in response to a stimulus in which facial emotion was similar to the vocal emotion of the preceding stimulus. These results suggest that the integration of emotional information from face and voice in the pSTS involves a detectable proportion of bimodal neurons that combine inputs from visual and auditory cortices. Copyright © 2014 the authors 0270-6474/14/346813-09$15.00/0.

Adaptive integral robust control and application to electromechanical servo systems.

PubMed

Deng, Wenxiang; Yao, Jianyong

2017-03-01

This paper proposes a continuous adaptive integral robust control with robust integral of the sign of the error (RISE) feedback for a class of uncertain nonlinear systems, in which the RISE feedback gain is adapted online to ensure the robustness against disturbances without the prior bound knowledge of the additive disturbances. In addition, an adaptive compensation integrated with the proposed adaptive RISE feedback term is also constructed to further reduce design conservatism when the system also exists parametric uncertainties. Lyapunov analysis reveals the proposed controllers could guarantee the tracking errors are asymptotically converging to zero with continuous control efforts. To illustrate the high performance nature of the developed controllers, numerical simulations are provided. At the end, an application case of an actual electromechanical servo system driven by motor is also studied, with some specific design consideration, and comparative experimental results are obtained to verify the effectiveness of the proposed controllers. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Integrating adaptive management and ecosystem services concepts to improve natural resource management: Challenges and opportunities

USGS Publications Warehouse

Epanchin-Niell, Rebecca S.; Boyd, James W.; Macauley, Molly K.; Scarlett, Lynn; Shapiro, Carl D.; Williams, Byron K.

2018-05-07

Executive Summary—OverviewNatural resource managers must make decisions that affect broad-scale ecosystem processes involving large spatial areas, complex biophysical interactions, numerous competing stakeholder interests, and highly uncertain outcomes. Natural and social science information and analyses are widely recognized as important for informing effective management. Chief among the systematic approaches for improving the integration of science into natural resource management are two emergent science concepts, adaptive management and ecosystem services. Adaptive management (also referred to as “adaptive decision making”) is a deliberate process of learning by doing that focuses on reducing uncertainties about management outcomes and system responses to improve management over time. Ecosystem services is a conceptual framework that refers to the attributes and outputs of ecosystems (and their components and functions) that have value for humans.This report explores how ecosystem services can be moved from concept into practice through connection to a decision framework—adaptive management—that accounts for inherent uncertainties. Simultaneously, the report examines the value of incorporating ecosystem services framing and concepts into adaptive management efforts.Adaptive management and ecosystem services analyses have not typically been used jointly in decision making. However, as frameworks, they have a natural—but to date underexplored—affinity. Both are policy and decision oriented in that they attempt to represent the consequences of resource management choices on outcomes of interest to stakeholders. Both adaptive management and ecosystem services analysis take an empirical approach to the analysis of ecological systems. This systems orientation is a byproduct of the fact that natural resource actions affect ecosystems—and corresponding societal outcomes—often across large geographic scales. Moreover, because both frameworks focus on

Scale-adaptive compressive tracking with feature integration

NASA Astrophysics Data System (ADS)

Liu, Wei; Li, Jicheng; Chen, Xiao; Li, Shuxin

2016-05-01

Numerous tracking-by-detection methods have been proposed for robust visual tracking, among which compressive tracking (CT) has obtained some promising results. A scale-adaptive CT method based on multifeature integration is presented to improve the robustness and accuracy of CT. We introduce a keypoint-based model to achieve the accurate scale estimation, which can additionally give a prior location of the target. Furthermore, by the high efficiency of data-independent random projection matrix, multiple features are integrated into an effective appearance model to construct the naïve Bayes classifier. At last, an adaptive update scheme is proposed to update the classifier conservatively. Experiments on various challenging sequences demonstrate substantial improvements by our proposed tracker over CT and other state-of-the-art trackers in terms of dealing with scale variation, abrupt motion, deformation, and illumination changes.

Minimizing the effect of process mismatch in a neuromorphic system using spike-timing-dependent adaptation.

PubMed

Cameron, Katherine; Murray, Alan

2008-05-01

This paper investigates whether spike-timing-dependent plasticity (STDP) can minimize the effect of mismatch within the context of a depth-from-motion algorithm. To improve noise rejection, this algorithm contains a spike prediction element, whose performance is degraded by analog very large scale integration (VLSI) mismatch. The error between the actual spike arrival time and the prediction is used as the input to an STDP circuit, to improve future predictions. Before STDP adaptation, the error reflects the degree of mismatch within the prediction circuitry. After STDP adaptation, the error indicates to what extent the adaptive circuitry can minimize the effect of transistor mismatch. The circuitry is tested with static and varying prediction times and chip results are presented. The effect of noisy spikes is also investigated. Under all conditions the STDP adaptation is shown to improve performance.

Adaptation to shift work: physiologically based modeling of the effects of lighting and shifts' start time.

PubMed

Postnova, Svetlana; Robinson, Peter A; Postnov, Dmitry D

2013-01-01

Shift work has become an integral part of our life with almost 20% of the population being involved in different shift schedules in developed countries. However, the atypical work times, especially the night shifts, are associated with reduced quality and quantity of sleep that leads to increase of sleepiness often culminating in accidents. It has been demonstrated that shift workers' sleepiness can be improved by a proper scheduling of light exposure and optimizing shifts timing. Here, an integrated physiologically-based model of sleep-wake cycles is used to predict adaptation to shift work in different light conditions and for different shift start times for a schedule of four consecutive days of work. The integrated model combines a model of the ascending arousal system in the brain that controls the sleep-wake switch and a human circadian pacemaker model. To validate the application of the integrated model and demonstrate its utility, its dynamics are adjusted to achieve a fit to published experimental results showing adaptation of night shift workers (n = 8) in conditions of either bright or regular lighting. Further, the model is used to predict the shift workers' adaptation to the same shift schedule, but for conditions not considered in the experiment. The model demonstrates that the intensity of shift light can be reduced fourfold from that used in the experiment and still produce good adaptation to night work. The model predicts that sleepiness of the workers during night shifts on a protocol with either bright or regular lighting can be significantly improved by starting the shift earlier in the night, e.g.; at 21:00 instead of 00:00. Finally, the study predicts that people of the same chronotype, i.e. with identical sleep times in normal conditions, can have drastically different responses to shift work depending on their intrinsic circadian and homeostatic parameters.

Adaptation to Shift Work: Physiologically Based Modeling of the Effects of Lighting and Shifts’ Start Time

PubMed Central

Postnova, Svetlana; Robinson, Peter A.; Postnov, Dmitry D.

2013-01-01

Shift work has become an integral part of our life with almost 20% of the population being involved in different shift schedules in developed countries. However, the atypical work times, especially the night shifts, are associated with reduced quality and quantity of sleep that leads to increase of sleepiness often culminating in accidents. It has been demonstrated that shift workers’ sleepiness can be improved by a proper scheduling of light exposure and optimizing shifts timing. Here, an integrated physiologically-based model of sleep-wake cycles is used to predict adaptation to shift work in different light conditions and for different shift start times for a schedule of four consecutive days of work. The integrated model combines a model of the ascending arousal system in the brain that controls the sleep-wake switch and a human circadian pacemaker model. To validate the application of the integrated model and demonstrate its utility, its dynamics are adjusted to achieve a fit to published experimental results showing adaptation of night shift workers (n = 8) in conditions of either bright or regular lighting. Further, the model is used to predict the shift workers’ adaptation to the same shift schedule, but for conditions not considered in the experiment. The model demonstrates that the intensity of shift light can be reduced fourfold from that used in the experiment and still produce good adaptation to night work. The model predicts that sleepiness of the workers during night shifts on a protocol with either bright or regular lighting can be significantly improved by starting the shift earlier in the night, e.g.; at 21∶00 instead of 00∶00. Finally, the study predicts that people of the same chronotype, i.e. with identical sleep times in normal conditions, can have drastically different responses to shift work depending on their intrinsic circadian and homeostatic parameters. PMID:23308206

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.

Integrated watershed analysis: adapting to changing times

Treesearch

Gordon H. Reeves

2013-01-01

Resource managers are increasingly required to conduct integrated analyses of aquatic and terrestrial ecosystems before undertaking any activities. Th ere are a number of research studies on the impacts of management actions on these ecosystems, as well as a growing body of knowledge about ecological processes that aff ect them, particularly aquatic ecosystems, which...

Design Specifications for Adaptive Real-Time Systems

DTIC Science & Technology

1991-12-01

TICfl \\ E CT E Design Specifications for JAN’\\ 1992 Adaptive Real - Time Systems fl Randall W. Lichota U, Alice H. Muntz - December 1991 \\ \\\\/ 0 / r...268-2056 Technical Report CMU/SEI-91-TR-20 ESD-91-TR-20 December 1991 Design Specifications for Adaptive Real - Time Systems Randall W. Lichota Hughes...Design Specifications for Adaptive Real - Time Systems Abstract: The design specification method described in this report treats a software

Integrating Adaptive Games in Student-Centered Virtual Learning Environments

ERIC Educational Resources Information Center

del Blanco, Angel; Torrente, Javier; Moreno-Ger, Pablo; Fernandez-Manjon, Baltasar

2010-01-01

The increasing adoption of e-Learning technology is facing new challenges, such as how to produce student-centered systems that can be adapted to each student's needs. In this context, educational video games are proposed as an ideal medium to facilitate adaptation and tracking of students' performance for assessment purposes, but integrating the…

Cooperative Drought Adaptation: Integrating Infrastructure Development, Conservation, and Water Transfers into Adaptive Policy Pathways

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.

An 'injury-time integral' model for extrapolating from acute to chronic effects of phosgene.

PubMed

Hatch, G; Kodavanti, U; Crissman, K; Slade, R; Costa, D

2001-06-01

The present study compares acute and subchronic episodic exposures to phosgene to test the applicability of the 'concentrationxtime' (CxT) product as a measure of exposure dose, and to relate acute toxicity and adaptive responses to chronic toxicity. Rats (male Fischer 344) were exposed (six hours/day) to air or 0.1, 0.2, 0.5 and 1.0 ppm of phosgene one time or on a repeated regimen for up to 12 weeks as follows: 0.1 ppm (five days/week), 0.2 ppm (five days/week), 0.5 ppm (two days/week), or 1.0 ppm (one day/week) (note that the CxT for the three highest exposures was the same). Animals were sacrificed at 4, 8, and 12 weeks during the exposure and after four weeks recovery. Bronchoalveolar lavage (BAL) was performed 18 hours after the last exposure for each time period and the BAL supernatant assayed for protein. Elevated BAL fluid protein was defined as 'acute injury', diminished response after repeated exposure was defined as 'adaptation', and increased lung hydroxyproline or trichrome staining for collagen was defined as 'chronic injury'. Results indicated that exposures that cause maximal chronic injury involve high exposure concentrations and longer times between exposures, not high CxT products. A conceptual model is presented that explains the lack of CxT correlation by the fact that adaptation reduces an 'injury-time integral' as phosgene exposure is lengthened from acute to subchronic. At high exposure concentrations, the adaptive response appears to be overwhelmed, causing a continued injury-time integral, which appears to be related to appearance of chronic injury. The adaptive response is predicted to disappear if the time between exposures is lengthened, leading to a continued high injury-time integral and chronic injury. It has generally been assumed that long, continuous exposures of rodents is a conservative approach for detecting possible chronic effects. The present study suggests that such an approach my not be conservative, but might actually

Integrating evolutionary and functional approaches to infer adaptation at specific loci.

PubMed

Storz, Jay F; Wheat, Christopher W

2010-09-01

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.

Space-time adaptive solution of inverse problems with the discrete adjoint method

NASA Astrophysics Data System (ADS)

Alexe, Mihai; Sandu, Adrian

2014-08-01

This paper develops a framework for the construction and analysis of discrete adjoint sensitivities in the context of time dependent, adaptive grid, adaptive step models. Discrete adjoints are attractive in practice since they can be generated with low effort using automatic differentiation. However, this approach brings several important challenges. The space-time adjoint of the forward numerical scheme may be inconsistent with the continuous adjoint equations. A reduction in accuracy of the discrete adjoint sensitivities may appear due to the inter-grid transfer operators. Moreover, the optimization algorithm may need to accommodate state and gradient vectors whose dimensions change between iterations. This work shows that several of these potential issues can be avoided through a multi-level optimization strategy using discontinuous Galerkin (DG) hp-adaptive discretizations paired with Runge-Kutta (RK) time integration. We extend the concept of dual (adjoint) consistency to space-time RK-DG discretizations, which are then shown to be well suited for the adaptive solution of time-dependent inverse problems. Furthermore, we prove that DG mesh transfer operators on general meshes are also dual consistent. This allows the simultaneous derivation of the discrete adjoint for both the numerical solver and the mesh transfer logic with an automatic code generation mechanism such as algorithmic differentiation (AD), potentially speeding up development of large-scale simulation codes. The theoretical analysis is supported by numerical results reported for a two-dimensional non-stationary inverse problem.

Adaptation disrupts motion integration in the primate dorsal stream

PubMed Central

Patterson, Carlyn A.; Wissig, Stephanie C.; Kohn, Adam

2014-01-01

Summary Sensory systems adjust continuously to the environment. The effects of recent sensory experience—or adaptation—are typically assayed by recording in a relevant subcortical or cortical network. However, adaptation effects cannot be localized to a single, local network. Adjustments in one circuit or area will alter the input provided to others, with unclear consequences for computations implemented in the downstream circuit. Here we show that prolonged adaptation with drifting gratings, which alters responses in the early visual system, impedes the ability of area MT neurons to integrate motion signals in plaid stimuli. Perceptual experiments reveal a corresponding loss of plaid coherence. A simple computational model shows how the altered representation of motion signals in early cortex can derail integration in MT. Our results suggest that the effects of adaptation cascade through the visual system, derailing the downstream representation of distinct stimulus attributes. PMID:24507198

Is Integration Always most Adaptive? The Role of Cultural Identity in Academic Achievement and in Psychological Adaptation of Immigrant Students in Germany.

PubMed

Schotte, Kristin; Stanat, Petra; Edele, Aileen

2018-01-01

Immigrant adaptation research views identification with the mainstream context as particularly beneficial for sociocultural adaptation, including academic achievement, and identification with the ethnic context as particularly beneficial for psychological adaptation. A strong identification with both contexts is considered most beneficial for both outcomes (integration hypothesis). However, it is unclear whether the integration hypothesis applies in assimilative contexts, across different outcomes, and across different immigrant groups. This study investigates the association of cultural identity with several indicators of academic achievement and psychological adaptation in immigrant adolescents (N = 3894, 51% female, M age = 16.24, SD age  = 0.71) in Germany. Analyses support the integration hypothesis for aspects of psychological adaptation but not for academic achievement. Moreover, for some outcomes, findings vary across immigrant groups from Turkey (n = 809), the former Soviet Union (n = 712), and heterogeneous other countries (n = 2373). The results indicate that the adaptive potential of identity integration is limited in assimilative contexts, such as Germany, and that it may vary across different outcomes and groups. As each identification is positively associated with at least one outcome, however, both identification dimensions seem to be important for the adaptation of immigrant adolescents.

A two-hop based adaptive routing protocol for real-time wireless sensor networks.

PubMed

Rachamalla, Sandhya; Kancherla, Anitha Sheela

2016-01-01

One of the most important and challenging issues in wireless sensor networks (WSNs) is to optimally manage the limited energy of nodes without degrading the routing efficiency. In this paper, we propose an energy-efficient adaptive routing mechanism for WSNs, which saves energy of nodes by removing the much delayed packets without degrading the real-time performance of the used routing protocol. It uses the adaptive transmission power algorithm which is based on the attenuation of the wireless link to improve the energy efficiency. The proposed routing mechanism can be associated with any geographic routing protocol and its performance is evaluated by integrating with the well known two-hop based real-time routing protocol, PATH and the resulting protocol is energy-efficient adaptive routing protocol (EE-ARP). The EE-ARP performs well in terms of energy consumption, deadline miss ratio, packet drop and end-to-end delay.

Design of time-pulse coded optoelectronic neuronal elements for nonlinear transformation and integration

NASA Astrophysics Data System (ADS)

Krasilenko, Vladimir G.; Nikolsky, Alexander I.; Lazarev, Alexander A.; Lazareva, Maria V.

2008-03-01

In the paper the actuality of neurophysiologically motivated neuron arrays with flexibly programmable functions and operations with possibility to select required accuracy and type of nonlinear transformation and learning are shown. We consider neurons design and simulation results of multichannel spatio-time algebraic accumulation - integration of optical signals. Advantages for nonlinear transformation and summation - integration are shown. The offered circuits are simple and can have intellectual properties such as learning and adaptation. The integrator-neuron is based on CMOS current mirrors and comparators. The performance: consumable power - 100...500 μW, signal period- 0.1...1ms, input optical signals power - 0.2...20 μW time delays - less 1μs, the number of optical signals - 2...10, integration time - 10...100 of signal periods, accuracy or integration error - about 1%. Various modifications of the neuron-integrators with improved performance and for different applications are considered in the paper.

Adaptive output-feedback control for switched stochastic uncertain nonlinear systems with time-varying delay.

PubMed

Song, Zhibao; Zhai, Junyong

2018-04-01

This paper addresses the problem of adaptive output-feedback control for a class of switched stochastic time-delay nonlinear systems with uncertain output function, where both the control coefficients and time-varying delay are unknown. The drift and diffusion terms are subject to unknown homogeneous growth condition. By virtue of adding a power integrator technique, an adaptive output-feedback controller is designed to render that the closed-loop system is bounded in probability, and the state of switched stochastic nonlinear system can be globally regulated to the origin almost surely. A numerical example is provided to demonstrate the validity of the proposed control method. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Efficient adaptive pseudo-symplectic numerical integration techniques for Landau-Lifshitz dynamics

NASA Astrophysics Data System (ADS)

d'Aquino, M.; Capuano, F.; Coppola, G.; Serpico, C.; Mayergoyz, I. D.

2018-05-01

Numerical time integration schemes for Landau-Lifshitz magnetization dynamics are considered. Such dynamics preserves the magnetization amplitude and, in the absence of dissipation, also implies the conservation of the free energy. This property is generally lost when time discretization is performed for the numerical solution. In this work, explicit numerical schemes based on Runge-Kutta methods are introduced. The schemes are termed pseudo-symplectic in that they are accurate to order p, but preserve magnetization amplitude and free energy to order q > p. An effective strategy for adaptive time-stepping control is discussed for schemes of this class. Numerical tests against analytical solutions for the simulation of fast precessional dynamics are performed in order to point out the effectiveness of the proposed methods.

Distributed Adaptive Finite-Time Approach for Formation-Containment Control of Networked Nonlinear Systems Under Directed Topology.

PubMed

Wang, Yujuan; Song, Yongduan; Ren, Wei

2017-07-06

This paper presents a distributed adaptive finite-time control solution to the formation-containment problem for multiple networked systems with uncertain nonlinear dynamics and directed communication constraints. By integrating the special topology feature of the new constructed symmetrical matrix, the technical difficulty in finite-time formation-containment control arising from the asymmetrical Laplacian matrix under single-way directed communication is circumvented. Based upon fractional power feedback of the local error, an adaptive distributed control scheme is established to drive the leaders into the prespecified formation configuration in finite time. Meanwhile, a distributed adaptive control scheme, independent of the unavailable inputs of the leaders, is designed to keep the followers within a bounded distance from the moving leaders and then to make the followers enter the convex hull shaped by the formation of the leaders in finite time. The effectiveness of the proposed control scheme is confirmed by the simulation.

Firing patterns in the adaptive exponential integrate-and-fire model.

PubMed

Naud, Richard; Marcille, Nicolas; Clopath, Claudia; Gerstner, Wulfram

2008-11-01

For simulations of large spiking neuron networks, an accurate, simple and versatile single-neuron modeling framework is required. Here we explore the versatility of a simple two-equation model: the adaptive exponential integrate-and-fire neuron. We show that this model generates multiple firing patterns depending on the choice of parameter values, and present a phase diagram describing the transition from one firing type to another. We give an analytical criterion to distinguish between continuous adaption, initial bursting, regular bursting and two types of tonic spiking. Also, we report that the deterministic model is capable of producing irregular spiking when stimulated with constant current, indicating low-dimensional chaos. Lastly, the simple model is fitted to real experiments of cortical neurons under step current stimulation. The results provide support for the suitability of simple models such as the adaptive exponential integrate-and-fire neuron for large network simulations.

Integrating Climate Change Adaptation into Public Health Practice: Using Adaptive Management to Increase Adaptive Capacity and Build Resilience

PubMed Central

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

Adaptive Counseling and Therapy: An Integrative, Eclectic Model.

ERIC Educational Resources Information Center

Howard, George S.; And Others

1986-01-01

Presents an integrative model, Adaptive Counseling and Therapy (ACT), for selecting a progression of therapist styles as clients move through developmental stages during the course of counseling and psychotherapy. ACT is intended to be useful to practitioners in case conceptualization and in the application of effective treatment planning.…

A parallel time integrator for noisy nonlinear oscillatory systems

NASA Astrophysics Data System (ADS)

Subber, Waad; Sarkar, Abhijit

2018-06-01

In this paper, we adapt a parallel time integration scheme to track the trajectories of noisy non-linear dynamical systems. Specifically, we formulate a parallel algorithm to generate the sample path of nonlinear oscillator defined by stochastic differential equations (SDEs) using the so-called parareal method for ordinary differential equations (ODEs). The presence of Wiener process in SDEs causes difficulties in the direct application of any numerical integration techniques of ODEs including the parareal algorithm. The parallel implementation of the algorithm involves two SDEs solvers, namely a fine-level scheme to integrate the system in parallel and a coarse-level scheme to generate and correct the required initial conditions to start the fine-level integrators. For the numerical illustration, a randomly excited Duffing oscillator is investigated in order to study the performance of the stochastic parallel algorithm with respect to a range of system parameters. The distributed implementation of the algorithm exploits Massage Passing Interface (MPI).

Predictable and Adaptable Complex Real-Time Systems

DTIC Science & Technology

1993-09-30

Predictable and Adaptable Complex Real - Time Systems Grant or Contract Number: N00014-92-J-1048 Reporting Period: 1 Oct 91 - 30 Sep 93 1... Real - Time Systems Grant or Contract Number: N00014-92-J-1048 Reporting Period: 1 Oct 91 - 30 Sep 93 2. Summary of Technical Progress Our...cs.umass.edu Grant or Contract Title: Predictable and Adaptable Complex Real - Time Systems Grant or Contract Number: N00014-92-J-1048 Reporting Period: 1 Oct 91

Effectiveness of Adaptive Contextual Learning Model of Integrated Science by Integrating Digital Age Literacy on Grade VIII Students

NASA Astrophysics Data System (ADS)

Asrizal, A.; Amran, A.; Ananda, A.; Festiyed, F.

2018-04-01

Educational graduates should have good competencies to compete in the 21st century. Integrated learning is a good way to develop competence of students in this century. Besides that, literacy skills are very important for students to get success in their learning and daily life. For this reason, integrated science learning and literacy skills are important in 2013 curriculum. However, integrated science learning and integration of literacy in learning can’t be implemented well. Solution of this problem is to develop adaptive contextual learning model by integrating digital age literacy. The purpose of the research is to determine the effectiveness of adaptive contextual learning model to improve competence of grade VIII students in junior high school. This research is a part of the research and development or R&D. Research design which used in limited field testing was before and after treatment. The research instruments consist of three parts namely test sheet of learning outcome for assessing knowledge competence, observation sheet for assessing attitudes, and performance sheet for assessing skills of students. Data of student’s competence were analyzed by three kinds of analysis, namely descriptive statistics, normality test and homogeneity test, and paired comparison test. From the data analysis result, it can be stated that the implementation of adaptive contextual learning model of integrated science by integrating digital age literacy is effective to improve the knowledge, attitude, and literacy skills competences of grade VIII students in junior high school at 95% confidence level.

Deep Impact Sequence Planning Using Multi-Mission Adaptable Planning Tools With Integrated Spacecraft Models

NASA Technical Reports Server (NTRS)

Wissler, Steven S.; Maldague, Pierre; Rocca, Jennifer; Seybold, Calina

2006-01-01

The Deep Impact mission was ambitious and challenging. JPL's well proven, easily adaptable multi-mission sequence planning tools combined with integrated spacecraft subsystem models enabled a small operations team to develop, validate, and execute extremely complex sequence-based activities within very short development times. This paper focuses on the core planning tool used in the mission, APGEN. It shows how the multi-mission design and adaptability of APGEN made it possible to model spacecraft subsystems as well as ground assets throughout the lifecycle of the Deep Impact project, starting with models of initial, high-level mission objectives, and culminating in detailed predictions of spacecraft behavior during mission-critical activities.

Adaptive time-variant models for fuzzy-time-series forecasting.

PubMed

Wong, Wai-Keung; Bai, Enjian; Chu, Alice Wai-Ching

2010-12-01

A fuzzy time series has been applied to the prediction of enrollment, temperature, stock indices, and other domains. Related studies mainly focus on three factors, namely, the partition of discourse, the content of forecasting rules, and the methods of defuzzification, all of which greatly influence the prediction accuracy of forecasting models. These studies use fixed analysis window sizes for forecasting. In this paper, an adaptive time-variant fuzzy-time-series forecasting model (ATVF) is proposed to improve forecasting accuracy. The proposed model automatically adapts the analysis window size of fuzzy time series based on the prediction accuracy in the training phase and uses heuristic rules to generate forecasting values in the testing phase. The performance of the ATVF model is tested using both simulated and actual time series including the enrollments at the University of Alabama, Tuscaloosa, and the Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX). The experiment results show that the proposed ATVF model achieves a significant improvement in forecasting accuracy as compared to other fuzzy-time-series forecasting models.

Floral pathway integrator gene expression mediates gradual transmission of environmental and endogenous cues to flowering time.

PubMed

van Dijk, Aalt D J; Molenaar, Jaap

2017-01-01

The appropriate timing of flowering is crucial for the reproductive success of plants. Hence, intricate genetic networks integrate various environmental and endogenous cues such as temperature or hormonal statues. These signals integrate into a network of floral pathway integrator genes. At a quantitative level, it is currently unclear how the impact of genetic variation in signaling pathways on flowering time is mediated by floral pathway integrator genes. Here, using datasets available from literature, we connect Arabidopsis thaliana flowering time in genetic backgrounds varying in upstream signalling components with the expression levels of floral pathway integrator genes in these genetic backgrounds. Our modelling results indicate that flowering time depends in a quite linear way on expression levels of floral pathway integrator genes. This gradual, proportional response of flowering time to upstream changes enables a gradual adaptation to changing environmental factors such as temperature and light.

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.

Complexity and network dynamics in physiological adaptation: an integrated view.

PubMed

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. Published by Elsevier Inc.

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.

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…

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.

Investigation of Adaptive-threshold Approaches for Determining Area-Time Integrals from Satellite Infrared Data to Estimate Convective Rain Volumes

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.

Adaptive Urban Signal Control and Integration (AUSCI) : evaluation final report

DOT National Transportation Integrated Search

2000-10-01

This report presents an evaluation of the Adaptive Urban Signal Control and Integration (AUSCI) Intelligent Transportation System (ITS) Field Operational Test in Minneapolis, Minnesota. The project involved a 56-intersection portion of Minneapolis, e...

Face Adaptation Effects: Reviewing the Impact of Adapting Information, Time, and Transfer

PubMed Central

Strobach, Tilo; Carbon, Claus-Christian

2013-01-01

The ability to adapt is essential to live and survive in an ever-changing environment such as the human ecosystem. Here we review the literature on adaptation effects of face stimuli to give an overview of existing findings in this area, highlight gaps in its research literature, initiate new directions in face adaptation research, and help to design future adaptation studies. Furthermore, this review should lead to better understanding of the processing characteristics as well as the mental representations of face-relevant information. The review systematizes studies at a behavioral level in respect of a framework which includes three dimensions representing the major characteristics of studies in this field of research. These dimensions comprise (1) the specificity of adapting face information, e.g., identity, gender, or age aspects of the material to be adapted to (2) aspects of timing (e.g., the sustainability of adaptation effects) and (3) transfer relations between face images presented during adaptation and adaptation tests (e.g., images of the same or different identities). The review concludes with options for how to combine findings across different dimensions to demonstrate the relevance of our framework for future studies. PMID:23760550

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.

A new generation of real-time DOS technology for mission-oriented system integration and operation

NASA Technical Reports Server (NTRS)

Jensen, E. Douglas

1988-01-01

Information is given on system integration and operation (SIO) requirements and a new generation of technical approaches for SIO. Real-time, distribution, survivability, and adaptability requirements and technical approaches are covered. An Alpha operating system program management overview is outlined.

Rod phototransduction determines the trade-off of temporal integration and speed of vision in dark-adapted toads.

PubMed

Haldin, Charlotte; Nymark, Soile; Aho, Ann-Christine; Koskelainen, Ari; Donner, Kristian

2009-05-06

Human vision is approximately 10 times less sensitive than toad vision on a cool night. Here, we investigate (1) how far differences in the capacity for temporal integration underlie such differences in sensitivity and (2) whether the response kinetics of the rod photoreceptors can explain temporal integration at the behavioral level. The toad was studied as a model that allows experimentation at different body temperatures. Sensitivity, integration time, and temporal accuracy of vision were measured psychophysically by recording snapping at worm dummies moving at different velocities. Rod photoresponses were studied by ERG recording across the isolated retina. In both types of experiments, the general timescale of vision was varied by using two temperatures, 15 and 25 degrees C. Behavioral integration times were 4.3 s at 15 degrees C and 0.9 s at 25 degrees C, and rod integration times were 4.2-4.3 s at 15 degrees C and 1.0-1.3 s at 25 degrees C. Maximal behavioral sensitivity was fivefold lower at 25 degrees C than at 15 degrees C, which can be accounted for by inability of the "warm" toads to integrate light over longer times than the rods. However, the long integration time at 15 degrees C, allowing high sensitivity, degraded the accuracy of snapping toward quickly moving worms. We conclude that temporal integration explains a considerable part of all variation in absolute visual sensitivity. The strong correlation between rods and behavior suggests that the integration time of dark-adapted vision is set by rod phototransduction at the input to the visual system. This implies that there is an inexorable trade-off between temporal integration and resolution.

Adaptive proximate time-optimal servomechanisms - Continuous time case

NASA Technical Reports Server (NTRS)

Workman, M. L.; Kosut, R. L.; Franklin, G. F.

1987-01-01

A Proximate Time-Optimal Servo (PTOS) is developed, along with conditions for its stability. An algorithm is proposed for adapting the PTOS (APTOS) to improve performance in the face of uncertain plant parameters. Under ideal conditions APTOS is shown to be uniformly asymptotically stable. Simulation results demonstrate the predicted performance.

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.

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

Time course of dynamic range adaptation in the auditory nerve

PubMed Central

Wang, Grace I.; Dean, Isabel; Delgutte, Bertrand

2012-01-01

Auditory adaptation to sound-level statistics occurs as early as in the auditory nerve (AN), the first stage of neural auditory processing. In addition to firing rate adaptation characterized by a rate decrement dependent on previous spike activity, AN fibers show dynamic range adaptation, which is characterized by a shift of the rate-level function or dynamic range toward the most frequently occurring levels in a dynamic stimulus, thereby improving the precision of coding of the most common sound levels (Wen B, Wang GI, Dean I, Delgutte B. J Neurosci 29: 13797–13808, 2009). We investigated the time course of dynamic range adaptation by recording from AN fibers with a stimulus in which the sound levels periodically switch from one nonuniform level distribution to another (Dean I, Robinson BL, Harper NS, McAlpine D. J Neurosci 28: 6430–6438, 2008). Dynamic range adaptation occurred rapidly, but its exact time course was difficult to determine directly from the data because of the concomitant firing rate adaptation. To characterize the time course of dynamic range adaptation without the confound of firing rate adaptation, we developed a phenomenological “dual adaptation” model that accounts for both forms of AN adaptation. When fitted to the data, the model predicts that dynamic range adaptation occurs as rapidly as firing rate adaptation, over 100–400 ms, and the time constants of the two forms of adaptation are correlated. These findings suggest that adaptive processing in the auditory periphery in response to changes in mean sound level occurs rapidly enough to have significant impact on the coding of natural sounds. PMID:22457465

The first patient treatment of electromagnetic-guided real time adaptive radiotherapy using MLC tracking for lung SABR.

PubMed

Booth, Jeremy T; Caillet, Vincent; Hardcastle, Nicholas; O'Brien, Ricky; Szymura, Kathryn; Crasta, Charlene; Harris, Benjamin; Haddad, Carol; Eade, Thomas; Keall, Paul J

2016-10-01

Real time adaptive radiotherapy that enables smaller irradiated volumes may reduce pulmonary toxicity. We report on the first patient treatment of electromagnetic-guided real time adaptive radiotherapy delivered with MLC tracking for lung stereotactic ablative body radiotherapy. A clinical trial was developed to investigate the safety and feasibility of MLC tracking in lung. The first patient was an 80-year old man with a single left lower lobe lung metastasis to be treated with SABR to 48Gy in 4 fractions. In-house software was integrated with a standard linear accelerator to adapt the treatment beam shape and position based on electromagnetic transponders implanted in the lung. MLC tracking plans were compared against standard ITV-based treatment planning. MLC tracking plan delivery was reconstructed in the patient to confirm safe delivery. Real time adaptive radiotherapy delivered with MLC tracking compared to standard ITV-based planning reduced the PTV by 41% (18.7-11cm 3 ) and the mean lung dose by 30% (202-140cGy), V20 by 35% (2.6-1.5%) and V5 by 9% (8.9-8%). An emerging technology, MLC tracking, has been translated into the clinic and used to treat lung SABR patients for the first time. This milestone represents an important first step for clinical real-time adaptive radiotherapy that could reduce pulmonary toxicity in lung radiotherapy. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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.

A spiking neural integrator model of the adaptive control of action by the medial prefrontal cortex.

PubMed

Bekolay, Trevor; Laubach, Mark; Eliasmith, Chris

2014-01-29

Subjects performing simple reaction-time tasks can improve reaction times by learning the expected timing of action-imperative stimuli and preparing movements in advance. Success or failure on the previous trial is often an important factor for determining whether a subject will attempt to time the stimulus or wait for it to occur before initiating action. The medial prefrontal cortex (mPFC) has been implicated in enabling the top-down control of action depending on the outcome of the previous trial. Analysis of spike activity from the rat mPFC suggests that neural integration is a key mechanism for adaptive control in precisely timed tasks. We show through simulation that a spiking neural network consisting of coupled neural integrators captures the neural dynamics of the experimentally recorded mPFC. Errors lead to deviations in the normal dynamics of the system, a process that could enable learning from past mistakes. We expand on this coupled integrator network to construct a spiking neural network that performs a reaction-time task by following either a cue-response or timing strategy, and show that it performs the task with similar reaction times as experimental subjects while maintaining the same spiking dynamics as the experimentally recorded mPFC.

Quantum stopping times stochastic integral in the interacting Fock space

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kang, Yuanbao, E-mail: kangyuanb@163.com

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 amore » 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.« less

Fuzzy adaptive integration scheme for low-cost SINS/GPS navigation system

NASA Astrophysics Data System (ADS)

Nourmohammadi, Hossein; Keighobadi, Jafar

2018-01-01

Due to weak stand-alone accuracy as well as poor run-to-run stability of micro-electro mechanical system (MEMS)-based inertial sensors, special approaches are required to integrate low-cost strap-down inertial navigation system (SINS) with global positioning system (GPS), particularly in long-term applications. This paper aims to enhance long-term performance of conventional SINS/GPS navigation systems using a fuzzy adaptive integration scheme. The main concept behind the proposed adaptive integration is the good performance of attitude-heading reference system (AHRS) in low-accelerated motions and its degradation in maneuvered or accelerated motions. Depending on vehicle maneuvers, gravity-based attitude angles can be intelligently utilized to improve orientation estimation in the SINS. Knowledge-based fuzzy inference system is developed for decision-making between the AHRS and the SINS according to vehicle maneuvering conditions. Inertial measurements are the main input data of the fuzzy system to determine the maneuvering level during the vehicle motions. Accordingly, appropriate weighting coefficients are produced to combine the SINS/GPS and the AHRS, efficiently. The assessment of the proposed integrated navigation system is conducted via real data in airborne tests.

A New Adaptive H-Infinity Filtering Algorithm for the GPS/INS Integrated Navigation

PubMed Central

Jiang, Chen; Zhang, Shu-Bi; Zhang, Qiu-Zhao

2016-01-01

The Kalman filter is an optimal estimator with numerous applications in technology, especially in systems with Gaussian distributed noise. Moreover, the adaptive Kalman filtering algorithms, based on the Kalman filter, can control the influence of dynamic model errors. In contrast to the adaptive Kalman filtering algorithms, the H-infinity filter is able to address the interference of the stochastic model by minimization of the worst-case estimation error. In this paper, a novel adaptive H-infinity filtering algorithm, which integrates the adaptive Kalman filter and the H-infinity filter in order to perform a comprehensive filtering algorithm, is presented. In the proposed algorithm, a robust estimation method is employed to control the influence of outliers. In order to verify the proposed algorithm, experiments with real data of the Global Positioning System (GPS) and Inertial Navigation System (INS) integrated navigation, were conducted. The experimental results have shown that the proposed algorithm has multiple advantages compared to the other filtering algorithms. PMID:27999361

A New Adaptive H-Infinity Filtering Algorithm for the GPS/INS Integrated Navigation.

PubMed

Jiang, Chen; Zhang, Shu-Bi; Zhang, Qiu-Zhao

2016-12-19

The Kalman filter is an optimal estimator with numerous applications in technology, especially in systems with Gaussian distributed noise. Moreover, the adaptive Kalman filtering algorithms, based on the Kalman filter, can control the influence of dynamic model errors. In contrast to the adaptive Kalman filtering algorithms, the H-infinity filter is able to address the interference of the stochastic model by minimization of the worst-case estimation error. In this paper, a novel adaptive H-infinity filtering algorithm, which integrates the adaptive Kalman filter and the H-infinity filter in order to perform a comprehensive filtering algorithm, is presented. In the proposed algorithm, a robust estimation method is employed to control the influence of outliers. In order to verify the proposed algorithm, experiments with real data of the Global Positioning System (GPS) and Inertial Navigation System (INS) integrated navigation, were conducted. The experimental results have shown that the proposed algorithm has multiple advantages compared to the other filtering algorithms.

Real-time adaptive finite element solution of time-dependent Kohn-Sham equation

NASA Astrophysics Data System (ADS)

Bao, Gang; Hu, Guanghui; Liu, Di

2015-01-01

In our previous paper (Bao et al., 2012 [1]), a general framework of using adaptive finite element methods to solve the Kohn-Sham equation has been presented. This work is concerned with solving the time-dependent Kohn-Sham equations. The numerical methods are studied in the time domain, which can be employed to explain both the linear and the nonlinear effects. A Crank-Nicolson scheme and linear finite element space are employed for the temporal and spatial discretizations, respectively. To resolve the trouble regions in the time-dependent simulations, a heuristic error indicator is introduced for the mesh adaptive methods. An algebraic multigrid solver is developed to efficiently solve the complex-valued system derived from the semi-implicit scheme. A mask function is employed to remove or reduce the boundary reflection of the wavefunction. The effectiveness of our method is verified by numerical simulations for both linear and nonlinear phenomena, in which the effectiveness of the mesh adaptive methods is clearly demonstrated.

Impact of adaptation currents on synchronization of coupled exponential integrate-and-fire neurons.

PubMed

Ladenbauer, Josef; Augustin, Moritz; Shiau, LieJune; Obermayer, Klaus

2012-01-01

The ability of spiking neurons to synchronize their activity in a network depends on the response behavior of these neurons as quantified by the phase response curve (PRC) and on coupling properties. The PRC characterizes the effects of transient inputs on spike timing and can be measured experimentally. Here we use the adaptive exponential integrate-and-fire (aEIF) neuron model to determine how subthreshold and spike-triggered slow adaptation currents shape the PRC. Based on that, we predict how synchrony and phase locked states of coupled neurons change in presence of synaptic delays and unequal coupling strengths. We find that increased subthreshold adaptation currents cause a transition of the PRC from only phase advances to phase advances and delays in response to excitatory perturbations. Increased spike-triggered adaptation currents on the other hand predominantly skew the PRC to the right. Both adaptation induced changes of the PRC are modulated by spike frequency, being more prominent at lower frequencies. Applying phase reduction theory, we show that subthreshold adaptation stabilizes synchrony for pairs of coupled excitatory neurons, while spike-triggered adaptation causes locking with a small phase difference, as long as synaptic heterogeneities are negligible. For inhibitory pairs synchrony is stable and robust against conduction delays, and adaptation can mediate bistability of in-phase and anti-phase locking. We further demonstrate that stable synchrony and bistable in/anti-phase locking of pairs carry over to synchronization and clustering of larger networks. The effects of adaptation in aEIF neurons on PRCs and network dynamics qualitatively reflect those of biophysical adaptation currents in detailed Hodgkin-Huxley-based neurons, which underscores the utility of the aEIF model for investigating the dynamical behavior of networks. Our results suggest neuronal spike frequency adaptation as a mechanism synchronizing low frequency oscillations in

Impact of Adaptation Currents on Synchronization of Coupled Exponential Integrate-and-Fire Neurons

PubMed Central

Ladenbauer, Josef; Augustin, Moritz; Shiau, LieJune; Obermayer, Klaus

2012-01-01

The ability of spiking neurons to synchronize their activity in a network depends on the response behavior of these neurons as quantified by the phase response curve (PRC) and on coupling properties. The PRC characterizes the effects of transient inputs on spike timing and can be measured experimentally. Here we use the adaptive exponential integrate-and-fire (aEIF) neuron model to determine how subthreshold and spike-triggered slow adaptation currents shape the PRC. Based on that, we predict how synchrony and phase locked states of coupled neurons change in presence of synaptic delays and unequal coupling strengths. We find that increased subthreshold adaptation currents cause a transition of the PRC from only phase advances to phase advances and delays in response to excitatory perturbations. Increased spike-triggered adaptation currents on the other hand predominantly skew the PRC to the right. Both adaptation induced changes of the PRC are modulated by spike frequency, being more prominent at lower frequencies. Applying phase reduction theory, we show that subthreshold adaptation stabilizes synchrony for pairs of coupled excitatory neurons, while spike-triggered adaptation causes locking with a small phase difference, as long as synaptic heterogeneities are negligible. For inhibitory pairs synchrony is stable and robust against conduction delays, and adaptation can mediate bistability of in-phase and anti-phase locking. We further demonstrate that stable synchrony and bistable in/anti-phase locking of pairs carry over to synchronization and clustering of larger networks. The effects of adaptation in aEIF neurons on PRCs and network dynamics qualitatively reflect those of biophysical adaptation currents in detailed Hodgkin-Huxley-based neurons, which underscores the utility of the aEIF model for investigating the dynamical behavior of networks. Our results suggest neuronal spike frequency adaptation as a mechanism synchronizing low frequency oscillations in

Advancing flood risk analysis by integrating adaptive behaviour in large-scale flood risk assessments

NASA Astrophysics Data System (ADS)

Haer, T.; Botzen, W.; Aerts, J.

2016-12-01

In the last four decades the global population living in the 1/100 year-flood zone has doubled from approximately 500 million to a little less than 1 billion people. Urbanization in low lying -flood prone- cities further increases the exposed assets, such as buildings and infrastructure. Moreover, climate change will further exacerbate flood risk in the future. Accurate flood risk assessments are important to inform policy-makers and society on current- and future flood risk levels. However, these assessment suffer from a major flaw in the way they estimate flood vulnerability and adaptive behaviour of individuals and governments. Current flood risk projections commonly assume that either vulnerability remains constant, or try to mimic vulnerability through incorporating an external scenario. Such a static approach leads to a misrepresentation of future flood risk, as humans respond adaptively to flood events, flood risk communication, and incentives to reduce risk. In our study, we integrate adaptive behaviour in a large-scale European flood risk framework through an agent-based modelling approach. This allows for the inclusion of heterogeneous agents, which dynamically respond to each other and a changing environment. We integrate state-of-the-art flood risk maps based on climate scenarios (RCP's), and socio-economic scenarios (SSP's), with government and household agents, which behave autonomously based on (micro-)economic behaviour rules. We show for the first time that excluding adaptive behaviour leads to a major misrepresentation of future flood risk. The methodology is applied to flood risk, but has similar implications for other research in the field of natural hazards. While more research is needed, this multi-disciplinary study advances our understanding of how future flood risk will develop.

Dynamics of the exponential integrate-and-fire model with slow currents and adaptation.

PubMed

Barranca, Victor J; Johnson, Daniel C; Moyher, Jennifer L; Sauppe, Joshua P; Shkarayev, Maxim S; Kovačič, Gregor; Cai, David

2014-08-01

In order to properly capture spike-frequency adaptation with a simplified point-neuron model, we study approximations of Hodgkin-Huxley (HH) models including slow currents by exponential integrate-and-fire (EIF) models that incorporate the same types of currents. We optimize the parameters of the EIF models under the external drive consisting of AMPA-type conductance pulses using the current-voltage curves and the van Rossum metric to best capture the subthreshold membrane potential, firing rate, and jump size of the slow current at the neuron's spike times. Our numerical simulations demonstrate that, in addition to these quantities, the approximate EIF-type models faithfully reproduce bifurcation properties of the HH neurons with slow currents, which include spike-frequency adaptation, phase-response curves, critical exponents at the transition between a finite and infinite number of spikes with increasing constant external drive, and bifurcation diagrams of interspike intervals in time-periodically forced models. Dynamics of networks of HH neurons with slow currents can also be approximated by corresponding EIF-type networks, with the approximation being at least statistically accurate over a broad range of Poisson rates of the external drive. For the form of external drive resembling realistic, AMPA-like synaptic conductance response to incoming action potentials, the EIF model affords great savings of computation time as compared with the corresponding HH-type model. Our work shows that the EIF model with additional slow currents is well suited for use in large-scale, point-neuron models in which spike-frequency adaptation is important.

Cooperative drought adaptation: Integrating infrastructure development, conservation, and water transfers into adaptive policy pathways

NASA Astrophysics Data System (ADS)

Zeff, Harrison B.; Herman, Jonathan D.; Reed, Patrick M.; Characklis, Gregory W.

2016-09-01

A considerable fraction of urban water supply capacity serves primarily as a hedge against drought. Water utilities can reduce their dependence on firm capacity and forestall the development of new supplies using short-term drought management actions, such as conservation and transfers. Nevertheless, new supplies will often be needed, especially as demands rise due to population growth and economic development. Planning decisions regarding when and how to integrate new supply projects are fundamentally shaped by the way in which short-term adaptive drought management strategies are employed. To date, the challenges posed by long-term infrastructure sequencing and adaptive short-term drought management are treated independently, neglecting important feedbacks between planning and management actions. This work contributes a risk-based framework that uses continuously updating risk-of-failure (ROF) triggers to capture the feedbacks between short-term drought management actions (e.g., conservation and water transfers) and the selection and sequencing of a set of regional supply infrastructure options over the long term. Probabilistic regional water supply pathways are discovered for four water utilities in the "Research Triangle" region of North Carolina. Furthermore, this study distinguishes the status-quo planning path of independent action (encompassing utility-specific conservation and new supply infrastructure only) from two cooperative formulations: "weak" cooperation, which combines utility-specific conservation and infrastructure development with regional transfers, and "strong" cooperation, which also includes jointly developed regional infrastructure to support transfers. Results suggest that strong cooperation aids utilities in meeting their individual objectives at substantially lower costs and with less overall development. These benefits demonstrate how an adaptive, rule-based decision framework can coordinate integrated solutions that would not be

Integrating Adaptability into Special Operations Forces Intermediate Level Education

DTIC Science & Technology

2010-10-01

This model is based on the Experiential Learning Theory (ELT), which states that learning occurs by the transfer of experience into knowledge ( Kolb ...Report 529. Arlington, VA. Kolb , D.A., Boyatzis, R.E., & Mainemelis, C. (2000). Experiential Learning Theory : Previous research and new dimensions. In...adaptive thinking materials. Integrating this information will provide some continuity among concepts for instruction. Experiential Learning Model

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.

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

Integration and timing of basic and clinical sciences education.

PubMed

Bandiera, Glen; Boucher, Andree; Neville, Alan; Kuper, Ayelet; Hodges, Brian

2013-05-01

Medical education has traditionally been compartmentalized into basic and clinical sciences, with the latter being viewed as the skillful application of the former. Over time, the relevance of basic sciences has become defined by their role in supporting clinical problem solving rather than being, of themselves, a defining knowledge base of physicians. As part of the national Future of Medical Education in Canada (FMEC MD) project, a comprehensive empirical environmental scan identified the timing and integration of basic sciences as a key pressing issue for medical education. Using the literature review, key informant interviews, stakeholder meetings, and subsequent consultation forums from the FMEC project, this paper details the empirical basis for focusing on the role of basic science, the evidentiary foundations for current practices, and the implications for medical education. Despite a dearth of definitive relevant studies, opinions about how best to integrate the sciences remain strong. Resource allocation, political power, educational philosophy, and the shift from a knowledge-based to a problem-solving profession all influence the debate. There was little disagreement that both sciences are important, that many traditional models emphasized deep understanding of limited basic science disciplines at the expense of other relevant content such as social sciences, or that teaching the sciences contemporaneously rather than sequentially has theoretical and practical merit. Innovations in integrated curriculum design have occurred internationally. Less clear are the appropriate balance of the sciences, the best integration model, and solutions to the political and practical challenges of integrated curricula. New curricula tend to emphasize integration, development of more diverse physician competencies, and preparation of physicians to adapt to evolving technology and patients' expectations. Refocusing the basic/clinical dichotomy to a foundational

Time-of-flight depth image enhancement using variable integration time

NASA Astrophysics Data System (ADS)

Kim, Sun Kwon; Choi, Ouk; Kang, Byongmin; Kim, James Dokyoon; Kim, Chang-Yeong

2013-03-01

Time-of-Flight (ToF) cameras are used for a variety of applications because it delivers depth information at a high frame rate. These cameras, however, suffer from challenging problems such as noise and motion artifacts. To increase signal-to-noise ratio (SNR), the camera should calculate a distance based on a large amount of infra-red light, which needs to be integrated over a long time. On the other hand, the integration time should be short enough to suppress motion artifacts. We propose a ToF depth imaging method to combine advantages of short and long integration times exploiting an imaging fusion scheme proposed for color imaging. To calibrate depth differences due to the change of integration times, a depth transfer function is estimated by analyzing the joint histogram of depths in the two images of different integration times. The depth images are then transformed into wavelet domains and fused into a depth image with suppressed noise and low motion artifacts. To evaluate the proposed method, we captured a moving bar of a metronome with different integration times. The experiment shows the proposed method could effectively remove the motion artifacts while preserving high SNR comparable to the depth images acquired during long integration time.

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

Reframing the challenges to integrated care: a complex-adaptive systems perspective.

PubMed

Tsasis, Peter; Evans, Jenna M; Owen, Susan

2012-01-01

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. 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. 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. 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 requires policies and management practices that promote system

Integration of Online Parameter Identification and Neural Network for In-Flight Adaptive Control

NASA Technical Reports Server (NTRS)

Hageman, Jacob J.; Smith, Mark S.; 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.

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.

Postreceptoral chromatic-adaptation mechanisms in the red-green and blue-yellow systems using simple reaction times

NASA Astrophysics Data System (ADS)

Medina, José M.; Díaz, José A.

2006-05-01

Simple visual-reaction times (VRT) were measured for a variety of stimuli selected along red-green (L-M axis) and blue-yellow [S-(L+M) axis] directions in the isoluminant plane under different adaptation stimuli. Data were plotted in terms of the RMS cone contrast in contrast-threshold units. For each opponent system, a modified Piéron function was fitted in each experimental configuration and on all adaptation stimuli. A single function did not account for all the data, confirming the existence of separate postreceptoral adaptation mechanisms in each opponent system under suprathreshold conditions. The analysis of the VRT-hazard functions suggested that both color-opponent mechanisms present a well-defined, transient-sustained structure at marked suprathreshold conditions. The influence of signal polarity and chromatic adaptation on each color axis proves the existence of asymmetries in the integrated hazard functions, suggesting separate detection mechanisms for each pole (red, green, blue, and yellow detectors).

Integrated and adaptive management of water resources: Tensions, legacies, and the next best thing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Engle, Nathan L.; Johns, Owen R.; Lemos, Maria Carmen

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.more » 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.« less

Wavelet and adaptive methods for time dependent problems and applications in aerosol dynamics

NASA Astrophysics Data System (ADS)

Guo, Qiang

Time dependent partial differential equations (PDEs) are widely used as mathematical models of environmental problems. Aerosols are now clearly identified as an important factor in many environmental aspects of climate and radiative forcing processes, as well as in the health effects of air quality. The mathematical models for the aerosol dynamics with respect to size distribution are nonlinear partial differential and integral equations, which describe processes of condensation, coagulation and deposition. Simulating the general aerosol dynamic equations on time, particle size and space exhibits serious difficulties because the size dimension ranges from a few nanometer to several micrometer while the spatial dimension is usually described with kilometers. Therefore, it is an important and challenging task to develop efficient techniques for solving time dependent dynamic equations. In this thesis, we develop and analyze efficient wavelet and adaptive methods for the time dependent dynamic equations on particle size and further apply them to the spatial aerosol dynamic systems. Wavelet Galerkin method is proposed to solve the aerosol dynamic equations on time and particle size due to the fact that aerosol distribution changes strongly along size direction and the wavelet technique can solve it very efficiently. Daubechies' wavelets are considered in the study due to the fact that they possess useful properties like orthogonality, compact support, exact representation of polynomials to a certain degree. Another problem encountered in the solution of the aerosol dynamic equations results from the hyperbolic form due to the condensation growth term. We propose a new characteristic-based fully adaptive multiresolution numerical scheme for solving the aerosol dynamic equation, which combines the attractive advantages of adaptive multiresolution technique and the characteristics method. On the aspect of theoretical analysis, the global existence and uniqueness of

Wavefront correction and high-resolution in vivo OCT imaging with an objective integrated multi-actuator adaptive lens

PubMed Central

Bonora, Stefano; Jian, Yifan; Zhang, Pengfei; Zam, Azhar; Pugh, Edward N.; Zawadzki, Robert J.; Sarunic, Marinko V.

2015-01-01

Adaptive optics is rapidly transforming microscopy and high-resolution ophthalmic imaging. The adaptive elements commonly used to control optical wavefronts are liquid crystal spatial light modulators and deformable mirrors. We introduce a novel Multi-actuator Adaptive Lens that can correct aberrations to high order, and which has the potential to increase the spread of adaptive optics to many new applications by simplifying its integration with existing systems. Our method combines an adaptive lens with an imaged-based optimization control that allows the correction of images to the diffraction limit, and provides a reduction of hardware complexity with respect to existing state-of-the-art adaptive optics systems. The Multi-actuator Adaptive Lens design that we present can correct wavefront aberrations up to the 4th order of the Zernike polynomial characterization. The performance of the Multi-actuator Adaptive Lens is demonstrated in a wide field microscope, using a Shack-Hartmann wavefront sensor for closed loop control. The Multi-actuator Adaptive Lens and image-based wavefront-sensorless control were also integrated into the objective of a Fourier Domain Optical Coherence Tomography system for in vivo imaging of mouse retinal structures. The experimental results demonstrate that the insertion of the Multi-actuator Objective Lens can generate arbitrary wavefronts to correct aberrations down to the diffraction limit, and can be easily integrated into optical systems to improve the quality of aberrated images. PMID:26368169

Wavefront correction and high-resolution in vivo OCT imaging with an objective integrated multi-actuator adaptive lens.

PubMed

Bonora, Stefano; Jian, Yifan; Zhang, Pengfei; Zam, Azhar; Pugh, Edward N; Zawadzki, Robert J; Sarunic, Marinko V

2015-08-24

Adaptive optics is rapidly transforming microscopy and high-resolution ophthalmic imaging. The adaptive elements commonly used to control optical wavefronts are liquid crystal spatial light modulators and deformable mirrors. We introduce a novel Multi-actuator Adaptive Lens that can correct aberrations to high order, and which has the potential to increase the spread of adaptive optics to many new applications by simplifying its integration with existing systems. Our method combines an adaptive lens with an imaged-based optimization control that allows the correction of images to the diffraction limit, and provides a reduction of hardware complexity with respect to existing state-of-the-art adaptive optics systems. The Multi-actuator Adaptive Lens design that we present can correct wavefront aberrations up to the 4th order of the Zernike polynomial characterization. The performance of the Multi-actuator Adaptive Lens is demonstrated in a wide field microscope, using a Shack-Hartmann wavefront sensor for closed loop control. The Multi-actuator Adaptive Lens and image-based wavefront-sensorless control were also integrated into the objective of a Fourier Domain Optical Coherence Tomography system for in vivo imaging of mouse retinal structures. The experimental results demonstrate that the insertion of the Multi-actuator Objective Lens can generate arbitrary wavefronts to correct aberrations down to the diffraction limit, and can be easily integrated into optical systems to improve the quality of aberrated images.

Adaptive treatment-length optimization in spatiobiologically integrated radiotherapy

NASA Astrophysics Data System (ADS)

Ajdari, Ali; Ghate, Archis; Kim, Minsun

2018-04-01

Recent theoretical research on spatiobiologically integrated radiotherapy has focused on optimization models that adapt fluence-maps to the evolution of tumor state, for example, cell densities, as observed in quantitative functional images acquired over the treatment course. We propose an optimization model that adapts the length of the treatment course as well as the fluence-maps to such imaged tumor state. Specifically, after observing the tumor cell densities at the beginning of a session, the treatment planner solves a group of convex optimization problems to determine an optimal number of remaining treatment sessions, and a corresponding optimal fluence-map for each of these sessions. The objective is to minimize the total number of tumor cells remaining (TNTCR) at the end of this proposed treatment course, subject to upper limits on the biologically effective dose delivered to the organs-at-risk. This fluence-map is administered in future sessions until the next image is available, and then the number of sessions and the fluence-map are re-optimized based on the latest cell density information. We demonstrate via computer simulations on five head-and-neck test cases that such adaptive treatment-length and fluence-map planning reduces the TNTCR and increases the biological effect on the tumor while employing shorter treatment courses, as compared to only adapting fluence-maps and using a pre-determined treatment course length based on one-size-fits-all guidelines.

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.

Simulating and evaluating an adaptive and integrated traffic lights control system for smart city application

NASA Astrophysics Data System (ADS)

Djuana, E.; Rahardjo, K.; Gozali, F.; Tan, S.; Rambung, R.; Adrian, D.

2018-01-01

A city could be categorized as a smart city when the information technology has been developed to the point that the administration could sense, understand, and control every resource to serve its people and sustain the development of the city. One of the smart city aspects is transportation and traffic management. This paper presents a research project to design an adaptive traffic lights control system as a part of the smart system for optimizing road utilization and reducing congestion. Research problems presented include: (1) Congestion in one direction toward an intersection due to dynamic traffic condition from time to time during the day, while the timing cycles in traffic lights system are mostly static; (2) No timing synchronization among traffic lights in adjacent intersections that is causing unsteady flows; (3) Difficulties in traffic condition monitoring on the intersection and the lack of facility for remotely controlling traffic lights. In this research, a simulator has been built to model the adaptivity and integration among different traffic lights controllers in adjacent intersections, and a case study consisting of three sets of intersections along Jalan K. H. Hasyim Ashari has been simulated. It can be concluded that timing slots synchronization among traffic lights is crucial for maintaining a steady traffic flow.

Adaptation and Integration of Recent Refugees to the United States.

ERIC Educational Resources Information Center

Forbes, Susan S.

This booklet is an overview report on refugee integration and adaptation in the United States. The introduction discusses briefly the Refugee Act of 1980, and is followed by three sections of text. The first part summarizes information on the extent of refugee economic and social adjustment and analyzes factors that have facilitated and impeded…

ITMS: Individualized Teaching Material System: Adaptive Integration of Web Pages Distributed in Some Servers.

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…

Challenges in Incorporating Climate Change Adaptation into Integrated Water Resources Management

NASA Astrophysics Data System (ADS)

Kirshen, P. H.; Cardwell, H.; Kartez, J.; Merrill, S.

2011-12-01

Over the last few decades, integrated water resources management (IWRM), under various names, has become the accepted philosophy for water management in the USA. While much is still to be learned about how to actually carry it out, implementation is slowly moving forward - spurred by both legislation and the demands of stakeholders. New challenges to IWRM have arisen because of climate change. Climate change has placed increased demands on the creativities of planners and engineers because they now must design systems that will function over decades of hydrologic uncertainties that dwarf any previous hydrologic or other uncertainties. Climate and socio-economic monitoring systems must also now be established to determine when the future climate has changed sufficiently to warrant undertaking adaptation. The requirements for taking some actions now and preserving options for future actions as well as the increased risk of social inequities in climate change impacts and adaptation are challenging experts in stakeholder participation. To meet these challenges, an integrated methodology is essential that builds upon scenario analysis, risk assessment, statistical decision theory, participatory planning, and consensus building. This integration will create cross-disciplinary boundaries for these disciplines to overcome.

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.

Real time microcontroller implementation of an adaptive myoelectric filter.

PubMed

Bagwell, P J; Chappell, P H

1995-03-01

This paper describes a real time digital adaptive filter for processing myoelectric signals. The filter time constant is automatically selected by the adaptation algorithm, giving a significant improvement over linear filters for estimating the muscle force and controlling a prosthetic device. Interference from mains sources often produces problems for myoelectric processing, and so 50 Hz and all harmonic frequencies are reduced by an averaging filter and differential process. This makes practical electrode placement and contact less critical and time consuming. An economic real time implementation is essential for a prosthetic controller, and this is achieved using an Intel 80C196KC microcontroller.

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

Simulation Based Evaluation of Integrated Adaptive Control and Flight Planning Technologies

NASA Technical Reports Server (NTRS)

Campbell, Stefan Forrest; Kaneshige, John T.

2008-01-01

The objective of this work is to leverage NASA resources to enable effective evaluation of resilient aircraft technologies through simulation. This includes examining strengths and weaknesses of adaptive controllers, emergency flight planning algorithms, and flight envelope determination algorithms both individually and as an integrated package.

Performance Optimizing Adaptive Control with Time-Varying Reference Model Modification

NASA Technical Reports Server (NTRS)

Nguyen, Nhan T.; Hashemi, Kelley E.

2017-01-01

This paper presents a new adaptive control approach that involves a performance optimization objective. The control synthesis involves the design of a performance optimizing adaptive controller from a subset of control inputs. The resulting effect of the performance optimizing adaptive controller is to modify the initial reference model into a time-varying reference model which satisfies the performance optimization requirement obtained from an optimal control problem. The time-varying reference model modification is accomplished by the real-time solutions of the time-varying Riccati and Sylvester equations coupled with the least-squares parameter estimation of the sensitivities of the performance metric. The effectiveness of the proposed method is demonstrated by an application of maneuver load alleviation control for a flexible aircraft.

Real-time Adaptive EEG Source Separation using Online Recursive Independent Component Analysis

PubMed Central

Hsu, Sheng-Hsiou; Mullen, Tim; Jung, Tzyy-Ping; Cauwenberghs, Gert

2016-01-01

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: (a) suitability for accurate and efficient source identification in high-density (64-channel) realistically-simulated EEG data; (b) capability to detect and adapt to non-stationarity in 64-ch simulated EEG data; and (c) 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

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.

Integrated Adaptive Scenarios for Ariculture: Synergies and Tradeoffs.

NASA Astrophysics Data System (ADS)

Malek, K.; Rajagopalan, K.; Adam, J. C.; Brady, M.; Stockle, C.; Liu, M.; Kruger, C. E.

2017-12-01

A wide variety of factors can drive adaptation of the agricultural production sector in response to climate change. Warming and increased growing season length can lead to adoption of newer plant varieties as well as increases in double cropping systems. Changes in expectations of drought frequency or economic factors could lead to adoption of new technology (such as irrigation technology or water trading systems) or crop choices with a view of reducing farm-level risk, and these choices can result in unintended system wide effects. These are all examples of producer adaptation decisions made with a long-term (multiple decades) view. In addition, producers respond to short-term (current year) shocks - such as drought events - through management strategies that include deficit irrigation, fallowing, nutrient management, and engaging in water trading. The effects of these short- and long-term decisions are not independent, and can drive or be driven by the other. For example, investment in new irrigation systems (long-term) can be driven by expectations of short-term crop productivity losses in drought years. Similarly, the capacity to manage for short-term shocks will depend on crop type and variety as well as adopted irrigation technologies. Our overarching objective is to understand the synergies and tradeoffs that exist when combining three potential long-term adaptation strategies and two short-term adaptation strategies, with a view of understanding the synergies and tradeoffs. We apply the integrated crop-hydrology modeling framework VIC-CropSyst, along with the water management module Yakima RiverWare to address these questions over our test area, the Yakima River basin. We consider adoption of a) more efficient irrigation technologies, slower growing crop varieties, and increased prevalence of double cropping systems as long-term adaptation strategies; and b) fallowing and deficit irrigation as short-term responses to droughts. We evaluate the individual and

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.

Building health behavior models to guide the development of just-in-time adaptive interventions: A pragmatic framework

PubMed Central

Nahum-Shani, Inbal; Hekler, Eric B.; Spruijt-Metz, Donna

2016-01-01

Advances in wireless devices and mobile technology offer many opportunities for delivering just-in-time adaptive interventions (JITAIs)--suites of interventions that adapt over time to an individual’s changing status and circumstances with the goal to address the individual’s need for support, whenever this need arises. A major challenge confronting behavioral scientists aiming to develop a JITAI concerns the selection and integration of existing empirical, theoretical and practical evidence into a scientific model that can inform the construction of a JITAI and help identify scientific gaps. The purpose of this paper is to establish a pragmatic framework that can be used to organize existing evidence into a useful model for JITAI construction. This framework involves clarifying the conceptual purpose of a JITAI, namely the provision of just-in-time support via adaptation, as well as describing the components of a JITAI and articulating a list of concrete questions to guide the establishment of a useful model for JITAI construction. The proposed framework includes an organizing scheme for translating the relatively static scientific models underlying many health behavior interventions into a more dynamic model that better incorporates the element of time. This framework will help to guide the next generation of empirical work to support the creation of effective JITAIs. PMID:26651462

Driver's behavioral adaptation to adaptive cruise control (ACC): the case of speed and time headway.

PubMed

Bianchi Piccinini, Giulio Francesco; Rodrigues, Carlos Manuel; Leitão, Miguel; Simões, Anabela

2014-06-01

The Adaptive Cruise Control is an Advanced Driver Assistance System (ADAS) that allows maintaining given headway and speed, according to settings pre-defined by the users. Despite the potential benefits associated to the utilization of ACC, previous studies warned against negative behavioral adaptations that might occur while driving with the system activated. Unfortunately, up to now, there are no unanimous results about the effects induced by the usage of ACC on speed and time headway to the vehicle in front. Also, few studies were performed including actual users of ACC among the subjects. This research aimed to investigate the effect of the experience gained with ACC on speed and time headway for a group of users of the system. In addition, it explored the impact of ACC usage on speed and time headway for ACC users and regular drivers. A matched sample driving simulator study was planned as a two-way (2×2) repeated measures mixed design, with the experience with ACC as between-subjects factor and the driving condition (with ACC and manually) as within-subjects factor. The results show that the usage of ACC brought a small but not significant reduction of speed and, especially, the maintenance of safer time headways, being the latter result greater for ACC users, probably as a consequence of their experience in using the system. The usage of ACC did not cause any negative behavioral adaptations to the system regarding speed and time headway. Based on this research work, the Adaptive Cruise Control showed the potential to improve road safety for what concerns the speed and the time headway maintained by the drivers. The speed of the surrounding traffic and the minimum time headway settable through the ACC seem to have an important effect on the road safety improvement achievable with the system. Copyright © 2014 Elsevier Ltd. All rights reserved.

Perceptual Learning of Time-Compressed Speech: More than Rapid Adaptation

PubMed Central

Banai, Karen; Lavner, Yizhar

2012-01-01

Background Time-compressed speech, a form of rapidly presented speech, is harder to comprehend than natural speech, especially for non-native speakers. Although it is possible to adapt to time-compressed speech after a brief exposure, it is not known whether additional perceptual learning occurs with further practice. Here, we ask whether multiday training on time-compressed speech yields more learning than that observed during the initial adaptation phase and whether the pattern of generalization following successful learning is different than that observed with initial adaptation only. Methodology/Principal Findings Two groups of non-native Hebrew speakers were tested on five different conditions of time-compressed speech identification in two assessments conducted 10–14 days apart. Between those assessments, one group of listeners received five practice sessions on one of the time-compressed conditions. Between the two assessments, trained listeners improved significantly more than untrained listeners on the trained condition. Furthermore, the trained group generalized its learning to two untrained conditions in which different talkers presented the trained speech materials. In addition, when the performance of the non-native speakers was compared to that of a group of naïve native Hebrew speakers, performance of the trained group was equivalent to that of the native speakers on all conditions on which learning occurred, whereas performance of the untrained non-native listeners was substantially poorer. Conclusions/Significance Multiday training on time-compressed speech results in significantly more perceptual learning than brief adaptation. Compared to previous studies of adaptation, the training induced learning is more stimulus specific. Taken together, the perceptual learning of time-compressed speech appears to progress from an initial, rapid adaptation phase to a subsequent prolonged and more stimulus specific phase. These findings are consistent with

Technical note: A device for obtaining time-integrated samples of ruminal fluid

USGS Publications Warehouse

Corley, R. N.; Murphy, M.R.; Lucena, J.; Panno, S.V.

1999-01-01

A device was adapted to allow for time-integrated sampling of fluid from the rumen via a cannula. The sampler consisted of a cup-shaped ceramic filter positioned in the ventral rumen of a cannulated cow and attached to a tube through which fluid entering the filter was removed continuously using a peristaltic pump. Rate of ruminal fluid removal using the device was monitored over two 36-h periods (at 6-h intervals) and was not affected (P > .05) by time, indicating that the system was not susceptible to clogging during this period. Two cows having ad libitum access to a totally mixed ration were used in a split-block design to evaluate the utility of the system for obtaining time-integrated samples of ruminal fluid. Ruminal fluid VFA concentration and pattern in samples collected in two replicated 8-h periods by the time-integrated sampler (at 1-h intervals) were compared with composite samples collected using a conventional suction-strainer device (at 30-min intervals). Each 8-h collection period started 2 h before or 6 h after feeding. Results indicated that total VFA concentration was not affected (P > .05) by the sampling method. Volatile fatty acid patterns were likewise unaffected (P > .05) except that acetate was 2.5% higher (P < .05) in samples collected 2 h before feeding and valerate was 5% higher (P < .05) in samples collected 6 h after feeding by the suction-strainer device. Although significant, these differences were not considered physiologically important. We concluded that use of the ceramic filter improved the sampling of ruminal fluid by simplifying the technique and allowing time-integrated samples to be obtained.

Time scale matters: genetic analysis does not support adaptation-by-time as the mechanism for adaptive seasonal declines in kokanee reproductive life span

PubMed Central

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

Adaptive time steps in trajectory surface hopping simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Spörkel, Lasse, E-mail: spoerkel@kofo.mpg.de; Thiel, Walter, E-mail: thiel@kofo.mpg.de

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 energymore » 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.« less

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.

Sensory adaptation for timing perception.

PubMed

Roseboom, Warrick; Linares, Daniel; Nishida, Shin'ya

2015-04-22

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.

Real-time control system for adaptive resonator

DOE Office of Scientific and Technical Information (OSTI.GOV)

Flath, L; An, J; Brase, J

2000-07-24

Sustained operation of high average power solid-state lasers currently requires an adaptive resonator to produce the optimal beam quality. We describe the architecture of a real-time adaptive control system for correcting intra-cavity aberrations in a heat capacity laser. Image data collected from a wavefront sensor are processed and used to control phase with a high-spatial-resolution deformable mirror. Our controller takes advantage of recent developments in low-cost, high-performance processor technology. A desktop-based computational engine and object-oriented software architecture replaces the high-cost rack-mount embedded computers of previous systems.

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

Three Authentic Curriculum-Integration Approaches to Bird Adaptations That Incorporate Technology and Thinking Skills

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…

A new time-adaptive discrete bionic wavelet transform for enhancing speech from adverse noise environment

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.

On the performance of voltage stepping for the simulation of adaptive, nonlinear integrate-and-fire neuronal networks.

PubMed

Kaabi, Mohamed Ghaith; Tonnelier, Arnaud; Martinez, Dominique

2011-05-01

In traditional event-driven strategies, spike timings are analytically given or calculated with arbitrary precision (up to machine precision). Exact computation is possible only for simplified neuron models, mainly the leaky integrate-and-fire model. In a recent paper, Zheng, Tonnelier, and Martinez (2009) introduced an approximate event-driven strategy, named voltage stepping, that allows the generic simulation of nonlinear spiking neurons. Promising results were achieved in the simulation of single quadratic integrate-and-fire neurons. Here, we assess the performance of voltage stepping in network simulations by considering more complex neurons (quadratic integrate-and-fire neurons with adaptation) coupled with multiple synapses. To handle the discrete nature of synaptic interactions, we recast voltage stepping in a general framework, the discrete event system specification. The efficiency of the method is assessed through simulations and comparisons with a modified time-stepping scheme of the Runge-Kutta type. We demonstrated numerically that the original order of voltage stepping is preserved when simulating connected spiking neurons, independent of the network activity and connectivity.

A fully integrated, wide-load-range, high-power-conversion-efficiency switched capacitor DC-DC converter with adaptive bias comparator for ultra-low-power power management integrated circuit

NASA Astrophysics Data System (ADS)

Asano, Hiroki; Hirose, Tetsuya; Kojima, Yuta; Kuroki, Nobutaka; Numa, Masahiro

2018-04-01

In this paper, we present a wide-load-range switched-capacitor DC-DC buck converter with an adaptive bias comparator for ultra-low-power power management integrated circuit. The proposed converter is based on a conventional one and modified to operate in a wide load range by developing a load current monitor used in an adaptive bias comparator. Measurement results demonstrated that our proposed converter generates a 1.0 V output voltage from a 3.0 V input voltage at a load of up to 100 µA, which is 20 times higher than that of the conventional one. The power conversion efficiency was higher than 60% in the load range from 0.8 to 100 µA.

Systems integration of innate and adaptive immunity.

PubMed

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. Copyright © 2015. Published by Elsevier Ltd.

Spacer capture and integration by a type I-F Cas1-Cas2-3 CRISPR adaptation complex.

PubMed

Fagerlund, Robert D; Wilkinson, Max E; Klykov, Oleg; Barendregt, Arjan; Pearce, F Grant; Kieper, Sebastian N; Maxwell, Howard W R; Capolupo, Angela; Heck, Albert J R; Krause, Kurt L; Bostina, Mihnea; Scheltema, Richard A; Staals, Raymond H J; Fineran, Peter C

2017-06-27

CRISPR-Cas adaptive immune systems capture DNA fragments from invading bacteriophages and plasmids and integrate them as spacers into bacterial CRISPR arrays. In type I-E and II-A CRISPR-Cas systems, this adaptation process is driven by Cas1-Cas2 complexes. Type I-F systems, however, contain a unique fusion of Cas2, with the type I effector helicase and nuclease for invader destruction, Cas3. By using biochemical, structural, and biophysical methods, we present a structural model of the 400-kDa Cas1 4 -Cas2-3 2 complex from Pectobacterium atrosepticum with bound protospacer substrate DNA. Two Cas1 dimers assemble on a Cas2 domain dimeric core, which is flanked by two Cas3 domains forming a groove where the protospacer binds to Cas1-Cas2. We developed a sensitive in vitro assay and demonstrated that Cas1-Cas2-3 catalyzed spacer integration into CRISPR arrays. The integrase domain of Cas1 was necessary, whereas integration was independent of the helicase or nuclease activities of Cas3. Integration required at least partially duplex protospacers with free 3'-OH groups, and leader-proximal integration was stimulated by integration host factor. In a coupled capture and integration assay, Cas1-Cas2-3 processed and integrated protospacers independent of Cas3 activity. These results provide insight into the structure of protospacer-bound type I Cas1-Cas2-3 adaptation complexes and their integration mechanism.

Building health behavior models to guide the development of just-in-time adaptive interventions: A pragmatic framework.

PubMed

Nahum-Shani, Inbal; Hekler, Eric B; Spruijt-Metz, Donna

2015-12-01

Advances in wireless devices and mobile technology offer many opportunities for delivering just-in-time adaptive interventions (JITAIs)-suites of interventions that adapt over time to an individual's changing status and circumstances with the goal to address the individual's need for support, whenever this need arises. A major challenge confronting behavioral scientists aiming to develop a JITAI concerns the selection and integration of existing empirical, theoretical and practical evidence into a scientific model that can inform the construction of a JITAI and help identify scientific gaps. The purpose of this paper is to establish a pragmatic framework that can be used to organize existing evidence into a useful model for JITAI construction. This framework involves clarifying the conceptual purpose of a JITAI, namely, the provision of just-in-time support via adaptation, as well as describing the components of a JITAI and articulating a list of concrete questions to guide the establishment of a useful model for JITAI construction. The proposed framework includes an organizing scheme for translating the relatively static scientific models underlying many health behavior interventions into a more dynamic model that better incorporates the element of time. This framework will help to guide the next generation of empirical work to support the creation of effective JITAIs. (PsycINFO Database Record (c) 2015 APA, all rights reserved).

The determination of dark adaptation time using electroretinography in conscious miniature Schnauzer dogs.

PubMed

Yu, Hyung-Ah; Jeong, Man-Bok; Park, Shin-Ae; Kim, Won-Tae; Kim, Se-Eun; Chae, Je-Min; Yi, Na-Young; Seo, Kang-Moon

2007-12-01

The optimal dark adaptation time of electroretinograms (ERG's) performed on conscious dogs were determined using a commercially available ERG unit with a contact lens electrode and a built-in light source (LED-electrode). The ERG recordings were performed on nine healthy Miniature Schnauzer dogs. The bilateral ERG's at seven different dark adaptation times at an intensity of 2.5 cd.s/m(2) was performed. Signal averaging (4 flashes of light stimuli) was adopted to reduce electrophysiologic noise. As the dark adaptation time increased, a significant increase in the mean a-wave amplitudes was observed in comparison to base-line levels up to 10 min (p < 0.05). Thereafter, no significant differences in amplitude occurred over the dark adaptation time. Moreover, at this time the mean amplitude was 60.30 +/- 18.47 microV. However, no significant changes were observed for the implicit times of the a-wave. The implicit times and amplitude of the b-wave increased significantly up to 20 min of dark adaptation (p < 0.05). Beyond this time, the mean b-wave amplitudes was 132.92 +/- 17.79 microV. The results of the present study demonstrate that, the optimal dark adaptation time when performing ERG's, should be at least 20 min in conscious Miniature Schnauzer dogs.

Adaptation in families of children with Down syndrome in East Asian countries: an integrative review.

PubMed

Choi, Hyunkyung; Van Riper, Marcia

2017-08-01

The purpose of this integrative literature review was to understand the experiences of East Asian families of children with Down syndrome and identify factors affecting their adaptation in the Resiliency Model of Family Stress, Adjustment and Adaptation. Socio-cultural factors influence how well families adapt following the birth of a child with Down syndrome. Existing literature in this area has focused primarily on families from Western cultures. This is problematic because nurses care for families from all over the world. Therefore, the focus of this review is on families of children with Down syndrome living in East Asia, where Confucianism is dominant. Integrative literature review. Online databases (i.e. PubMed, CINAHL and PsycINFO) and a public search engine (i.e. Google Scholar) were used along with manual searches of reference lists and major journals. Studies were limited to original publications written in English and published between 1990-2014. Two authors independently performed integrative review processes proposed by Whittemore and Knafl and a quality assessment using the Mixed Methods Appraisal Tool. Like families in Western cultures, some East Asian families of children with Down syndrome adapted well and even thrived while others struggled. Various socio-cultural factors, including some associated with Confucianism, played a role in how individuals, dyads and families adapted. An understanding of socio-cultural influences can help nurses implement culturally sensitive family-centred interventions with families of children with Down syndrome. It may also facilitate policy changes concerning resources for these families. © 2016 John Wiley & Sons Ltd.

An adaptive time-stepping strategy for solving the phase field crystal model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Zhengru, E-mail: zrzhang@bnu.edu.cn; Ma, Yuan, E-mail: yuner1022@gmail.com; Qiao, Zhonghua, E-mail: zqiao@polyu.edu.hk

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. Themore » numerical experiments demonstrate that the CPU time is significantly saved for long time simulations.« less

Implementing the Integrated Strategy for the Cultural Adaptation of Evidence-Based Interventions: An Illustration.

PubMed

Sidani, Souraya; Ibrahim, Sarah; Lok, Jana; Fan, Lifeng; Fox, Mary

2018-01-01

Background Persons' cultural beliefs about a health problem can affect their perceived acceptability of evidence-based interventions, undermining evidence-based interventions' adherence, and uptake to manage the problem. Cultural adaptation has the potential to enhance the acceptability, uptake, and adherence to evidence-based interventions. Purpose To illustrate the implementation of the first two phases of the integrated strategy for cultural adaptation by examining Chinese Canadians' perceptions of chronic insomnia and evidence-based behavioral therapies for insomnia. Methods Chinese Canadians ( n = 14) with chronic insomnia attended a group session during which they completed established instruments measuring beliefs about sleep and insomnia, and their perceptions of factors that contribute to chronic insomnia. Participants rated the acceptability of evidence-based behavioral therapies and discussed their cultural perspectives regarding chronic insomnia and its treatment. Results Participants actively engaged in the activities planned for the first two phases of the integrated strategy and identified the most significant factor contributing to chronic insomnia and the evidence-based intervention most acceptable for their cultural group. Conclusions The protocol for implementing the two phases of the integrated strategy for cultural adaptation of evidence-based interventions was feasible, acceptable, and useful in identifying culturally relevant evidence-based interventions.

From classical to quantum and back: Hamiltonian adaptive resolution path integral, ring polymer, and centroid molecular dynamics

NASA Astrophysics Data System (ADS)

Kreis, Karsten; Kremer, Kurt; Potestio, Raffaello; Tuckerman, Mark E.

2017-12-01

Path integral-based methodologies play a crucial role for the investigation of nuclear quantum effects by means of computer simulations. However, these techniques are significantly more demanding than corresponding classical simulations. To reduce this numerical effort, we recently proposed a method, based on a rigorous Hamiltonian formulation, which restricts the quantum modeling to a small but relevant spatial region within a larger reservoir where particles are treated classically. In this work, we extend this idea and show how it can be implemented along with state-of-the-art path integral simulation techniques, including path-integral molecular dynamics, which allows for the calculation of quantum statistical properties, and ring-polymer and centroid molecular dynamics, which allow the calculation of approximate quantum dynamical properties. To this end, we derive a new integration algorithm that also makes use of multiple time-stepping. The scheme is validated via adaptive classical-path-integral simulations of liquid water. Potential applications of the proposed multiresolution method are diverse and include efficient quantum simulations of interfaces as well as complex biomolecular systems such as membranes and proteins.

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.

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.

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

Integrated direct/indirect adaptive robust motion trajectory tracking control of pneumatic cylinders

NASA Astrophysics Data System (ADS)

Meng, Deyuan; Tao, Guoliang; Zhu, Xiaocong

2013-09-01

This paper studies the precision motion trajectory tracking control of a pneumatic cylinder driven by a proportional-directional control valve. An integrated direct/indirect adaptive robust controller is proposed. The controller employs a physical model based indirect-type parameter estimation to obtain reliable estimates of unknown model parameters, and utilises a robust control method with dynamic compensation type fast adaptation to attenuate the effects of parameter estimation errors, unmodelled dynamics and disturbances. Due to the use of projection mapping, the robust control law and the parameter adaption algorithm can be designed separately. Since the system model uncertainties are unmatched, the recursive backstepping technology is adopted to design the robust control law. Extensive comparative experimental results are presented to illustrate the effectiveness of the proposed controller and its performance robustness to parameter variations and sudden disturbances.

The determination of dark adaptation time using electroretinography in conscious Miniature Schnauzer dogs

PubMed Central

Yu, Hyung-Ah; Jeong, Man-Bok; Park, Shin-Ae; Kim, Won-Tae; Kim, Se-Eun; Chae, Je-Min; Yi, Na-Young

2007-01-01

The optimal dark adaptation time of electroretinograms (ERG's) performed on conscious dogs were determined using a commercially available ERG unit with a contact lens electrode and a built-in light source (LED-electrode). The ERG recordings were performed on nine healthy Miniature Schnauzer dogs. The bilateral ERG's at seven different dark adaptation times at an intensity of 2.5 cd·s/m2 was performed. Signal averaging (4 flashes of light stimuli) was adopted to reduce electrophysiologic noise. As the dark adaptation time increased, a significant increase in the mean a-wave amplitudes was observed in comparison to base-line levels up to 10 min (p < 0.05). Thereafter, no significant differences in amplitude occured over the dark adaptation time. Moreover, at this time the mean amplitude was 60.30 ± 18.47 µV. However, no significant changes were observed for the implicit times of the a-wave. The implicit times and amplitude of the b-wave increased significantly up to 20 min of dark adaptation (p < 0.05). Beyond this time, the mean b-wave amplitudes was 132.92 ± 17.79 µV. The results of the present study demonstrate that, the optimal dark adaptation time when performing ERG's, should be at least 20 min in conscious Miniature Schnauzer dogs. PMID:17993756

Real-time Space-time Integration in GIScience and Geography

PubMed Central

Richardson, Douglas B.

2013-01-01

Space-time integration has long been the topic of study and speculation in geography. However, in recent years an entirely new form of space-time integration has become possible in GIS and GIScience: real-time space-time integration and interaction. While real-time spatiotemporal data is now being generated almost ubiquitously, and its applications in research and commerce are widespread and rapidly accelerating, the ability to continuously create and interact with fused space-time data in geography and GIScience is a recent phenomenon, made possible by the invention and development of real-time interactive (RTI) GPS/GIS technology and functionality in the late 1980s and early 1990s. This innovation has since functioned as a core change agent in geography, cartography, GIScience and many related fields, profoundly realigning traditional relationships and structures, expanding research horizons, and transforming the ways geographic data is now collected, mapped, modeled, and used, both in geography and in science and society more broadly. Real-time space-time interactive functionality remains today the underlying process generating the current explosion of fused spatiotemporal data, new geographic research initiatives, and myriad geospatial applications in governments, businesses, and society. This essay addresses briefly the development of these real-time space-time functions and capabilities; their impact on geography, cartography, and GIScience; and some implications for how discovery and change can occur in geography and GIScience, and how we might foster continued innovation in these fields. PMID:24587490

Real-time Space-time Integration in GIScience and Geography.

PubMed

Richardson, Douglas B

2013-01-01

Space-time integration has long been the topic of study and speculation in geography. However, in recent years an entirely new form of space-time integration has become possible in GIS and GIScience: real-time space-time integration and interaction. While real-time spatiotemporal data is now being generated almost ubiquitously, and its applications in research and commerce are widespread and rapidly accelerating, the ability to continuously create and interact with fused space-time data in geography and GIScience is a recent phenomenon, made possible by the invention and development of real-time interactive (RTI) GPS/GIS technology and functionality in the late 1980s and early 1990s. This innovation has since functioned as a core change agent in geography, cartography, GIScience and many related fields, profoundly realigning traditional relationships and structures, expanding research horizons, and transforming the ways geographic data is now collected, mapped, modeled, and used, both in geography and in science and society more broadly. Real-time space-time interactive functionality remains today the underlying process generating the current explosion of fused spatiotemporal data, new geographic research initiatives, and myriad geospatial applications in governments, businesses, and society. This essay addresses briefly the development of these real-time space-time functions and capabilities; their impact on geography, cartography, and GIScience; and some implications for how discovery and change can occur in geography and GIScience, and how we might foster continued innovation in these fields.

Integrating Climate Change Adaptation into Disaster Risk Reduction in Urban Contexts: Perceptions and Practice

PubMed Central

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

Variable-camber systems integration and operational performance of the AFTI/F-111 mission adaptive wing

NASA Technical Reports Server (NTRS)

Smith, John W.; Lock, Wilton P.; Payne, Gordon A.

1992-01-01

The advanced fighter technology integration, the AFTI/F-111 aircraft, is a preproduction F-111A testbed research airplane that was fitted with a smooth variable-camber mission adaptive wing. The camber was positioned and controlled by flexing the upper skins through rotary actuators and linkages driven by power drive units. The wing camber and control system are described. The measured servoactuator frequency responses are presented along with analytical predictions derived from the integrated characteristics of the control elements. A mission adaptive wing system chronology is used to illustrate and assess the reliability and dependability of the servoactuator system during 1524 hours of ground tests and 145 hours of flight testing.

Adaptive time stepping for fluid-structure interaction solvers

DOE PAGES

Mayr, M.; Wall, W. A.; Gee, M. W.

2017-12-22

In this work, a novel adaptive time stepping scheme for fluid-structure interaction (FSI) problems is proposed that allows for controlling the accuracy of the time-discrete solution. Furthermore, it eases practical computations by providing an efficient and very robust time step size selection. This has proven to be very useful, especially when addressing new physical problems, where no educated guess for an appropriate time step size is available. The fluid and the structure field, but also the fluid-structure interface are taken into account for the purpose of a posteriori error estimation, rendering it easy to implement and only adding negligible additionalmore » cost. The adaptive time stepping scheme is incorporated into a monolithic solution framework, but can straightforwardly be applied to partitioned solvers as well. The basic idea can be extended to the coupling of an arbitrary number of physical models. Accuracy and efficiency of the proposed method are studied in a variety of numerical examples ranging from academic benchmark tests to complex biomedical applications like the pulsatile blood flow through an abdominal aortic aneurysm. Finally, the demonstrated accuracy of the time-discrete solution in combination with reduced computational cost make this algorithm very appealing in all kinds of FSI applications.« less

Adaptive time stepping for fluid-structure interaction solvers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mayr, M.; Wall, W. A.; Gee, M. W.

In this work, a novel adaptive time stepping scheme for fluid-structure interaction (FSI) problems is proposed that allows for controlling the accuracy of the time-discrete solution. Furthermore, it eases practical computations by providing an efficient and very robust time step size selection. This has proven to be very useful, especially when addressing new physical problems, where no educated guess for an appropriate time step size is available. The fluid and the structure field, but also the fluid-structure interface are taken into account for the purpose of a posteriori error estimation, rendering it easy to implement and only adding negligible additionalmore » cost. The adaptive time stepping scheme is incorporated into a monolithic solution framework, but can straightforwardly be applied to partitioned solvers as well. The basic idea can be extended to the coupling of an arbitrary number of physical models. Accuracy and efficiency of the proposed method are studied in a variety of numerical examples ranging from academic benchmark tests to complex biomedical applications like the pulsatile blood flow through an abdominal aortic aneurysm. Finally, the demonstrated accuracy of the time-discrete solution in combination with reduced computational cost make this algorithm very appealing in all kinds of FSI applications.« less

Machine remaining useful life prediction: An integrated adaptive neuro-fuzzy and high-order particle filtering approach

NASA Astrophysics Data System (ADS)

Chen, Chaochao; Vachtsevanos, George; Orchard, Marcos E.

2012-04-01

Machine prognosis can be considered as the generation of long-term predictions that describe the evolution in time of a fault indicator, with the purpose of estimating the remaining useful life (RUL) of a failing component/subsystem so that timely maintenance can be performed to avoid catastrophic failures. This paper proposes an integrated RUL prediction method using adaptive neuro-fuzzy inference systems (ANFIS) and high-order particle filtering, which forecasts the time evolution of the fault indicator and estimates the probability density function (pdf) of RUL. The ANFIS is trained and integrated in a high-order particle filter as a model describing the fault progression. The high-order particle filter is used to estimate the current state and carry out p-step-ahead predictions via a set of particles. These predictions are used to estimate the RUL pdf. The performance of the proposed method is evaluated via the real-world data from a seeded fault test for a UH-60 helicopter planetary gear plate. The results demonstrate that it outperforms both the conventional ANFIS predictor and the particle-filter-based predictor where the fault growth model is a first-order model that is trained via the ANFIS.

Adaptations for vision in dim light: impulse responses and bumps in nocturnal spider photoreceptor cells (Cupiennius salei Keys).

PubMed

Pirhofer-Walzl, Karin; Warrant, Eric; Barth, Friedrich G

2007-10-01

The photoreceptor cells of the nocturnal spider Cupiennius salei were investigated by intracellular electrophysiology. (1) The responses of photoreceptor cells of posterior median (PM) and anterior median (AM) eyes to short (2 ms) light pulses showed long integration times in the dark-adapted and shorter integration times in the light-adapted state. (2) At very low light intensities, the photoreceptors responded to single photons with discrete potentials, called bumps, of high amplitude (2-20 mV). When measured in profoundly dark-adapted photoreceptor cells of the PM eyes these bumps showed an integration time of 128 +/- 35 ms (n = 7) whereas in dark-adapted photoreceptor cells of AM eyes the integration time was 84 +/- 13 ms (n = 8), indicating that the AM eyes are intrinsically faster than the PM eyes. (3) Long integration times, which improve visual reliability in dim light, and large responses to single photons in the dark-adapted state, contribute to a high visual sensitivity in Cupiennius at night. This conclusion is underlined by a calculation of sensitivity that accounts for both anatomical and physiological characteristics of the eye.

Integrable Time-Dependent Quantum Hamiltonians

NASA Astrophysics Data System (ADS)

Sinitsyn, Nikolai A.; Yuzbashyan, Emil A.; Chernyak, Vladimir Y.; Patra, Aniket; Sun, Chen

2018-05-01

We formulate a set of conditions under which the nonstationary Schrödinger equation with a time-dependent Hamiltonian is exactly solvable analytically. The main requirement is the existence of a non-Abelian gauge field with zero curvature in the space of system parameters. Known solvable multistate Landau-Zener models satisfy these conditions. Our method provides a strategy to incorporate time dependence into various quantum integrable models while maintaining their integrability. We also validate some prior conjectures, including the solution of the driven generalized Tavis-Cummings model.

Adjustment of Adaptive Gain with Bounded Linear Stability Analysis to Improve Time-Delay Margin for Metrics-Driven Adaptive Control

NASA Technical Reports Server (NTRS)

Bakhtiari-Nejad, Maryam; Nguyen, Nhan T.; Krishnakumar, Kalmanje Srinvas

2009-01-01

This paper presents the application of Bounded Linear Stability Analysis (BLSA) method for metrics driven adaptive control. The bounded linear stability analysis method is used for analyzing stability of adaptive control models, without linearizing the adaptive laws. Metrics-driven adaptive control introduces a notion that adaptation should be driven by some stability metrics to achieve robustness. By the application of bounded linear stability analysis method the adaptive gain is adjusted during the adaptation in order to meet certain phase margin requirements. Analysis of metrics-driven adaptive control is evaluated for a linear damaged twin-engine generic transport model of aircraft. The analysis shows that the system with the adjusted adaptive gain becomes more robust to unmodeled dynamics or time delay.

Between-Trial Forgetting Due to Interference and Time in Motor Adaptation.

PubMed

Kim, Sungshin; Oh, Youngmin; Schweighofer, Nicolas

2015-01-01

Learning a motor task with temporally spaced presentations or with other tasks intermixed between presentations reduces performance during training, but can enhance retention post training. These two effects are known as the spacing and contextual interference effect, respectively. Here, we aimed at testing a unifying hypothesis of the spacing and contextual interference effects in visuomotor adaptation, according to which forgetting between trials due to either spaced presentations or interference by another task will promote between-trial forgetting, which will depress performance during acquisition, but will promote retention. We first performed an experiment with three visuomotor adaptation conditions: a short inter-trial-interval (ITI) condition (SHORT-ITI); a long ITI condition (LONG-ITI); and an alternating condition with two alternated opposite tasks (ALT), with the same single-task ITI as in LONG-ITI. In the SHORT-ITI condition, there was fastest increase in performance during training and largest immediate forgetting in the retention tests. In contrast, in the ALT condition, there was slowest increase in performance during training and little immediate forgetting in the retention tests. Compared to these two conditions, in the LONG-ITI, we found intermediate increase in performance during training and intermediate immediate forgetting. To account for these results, we fitted to the data six possible adaptation models with one or two time scales, and with interference in the fast, or in the slow, or in both time scales. Model comparison confirmed that two time scales and some degree of interferences in either time scale are needed to account for our experimental results. In summary, our results suggest that retention following adaptation is modulated by the degree of between-trial forgetting, which is due to time-based decay in single adaptation task and interferences in multiple adaptation tasks.

Finite-Time Adaptive Control for a Class of Nonlinear Systems With Nonstrict Feedback Structure.

PubMed

Sun, Yumei; Chen, Bing; Lin, Chong; Wang, Honghong

2017-09-18

This paper focuses on finite-time adaptive neural tracking control for nonlinear systems in nonstrict feedback form. A semiglobal finite-time practical stability criterion is first proposed. Correspondingly, the finite-time adaptive neural control strategy is given by using this criterion. Unlike the existing results on adaptive neural/fuzzy control, the proposed adaptive neural controller guarantees that the tracking error converges to a sufficiently small domain around the origin in finite time, and other closed-loop signals are bounded. At last, two examples are used to test the validity of our results.

Sparse time-frequency decomposition based on dictionary adaptation.

PubMed

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. © 2016 The Author(s).

Use of adaptive cruise control functions on motorways and urban roads: Changes over time in an on-road study.

PubMed

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. Copyright © 2015 Elsevier Ltd and The Ergonomics Society. All rights reserved.

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.

Adaptive Time Stepping for Transient Network Flow Simulation in Rocket Propulsion Systems

NASA Technical Reports Server (NTRS)

Majumdar, Alok K.; Ravindran, S. S.

2017-01-01

Fluid and thermal transients found in rocket propulsion systems such as propellant feedline system is a complex process involving fast phases followed by slow phases. Therefore their time accurate computation requires use of short time step initially followed by the use of much larger time step. Yet there are instances that involve fast-slow-fast phases. In this paper, we present a feedback control based adaptive time stepping algorithm, and discuss its use in network flow simulation of fluid and thermal transients. The time step is automatically controlled during the simulation by monitoring changes in certain key variables and by feedback. In order to demonstrate the viability of time adaptivity for engineering problems, we applied it to simulate water hammer and cryogenic chill down in pipelines. Our comparison and validation demonstrate the accuracy and efficiency of this adaptive strategy.

Disentangling Complexity in Bayesian Automatic Adaptive Quadrature

NASA Astrophysics Data System (ADS)

Adam, Gheorghe; Adam, Sanda

2018-02-01

The paper describes a Bayesian automatic adaptive quadrature (BAAQ) solution for numerical integration which is simultaneously robust, reliable, and efficient. Detailed discussion is provided of three main factors which contribute to the enhancement of these features: (1) refinement of the m-panel automatic adaptive scheme through the use of integration-domain-length-scale-adapted quadrature sums; (2) fast early problem complexity assessment - enables the non-transitive choice among three execution paths: (i) immediate termination (exceptional cases); (ii) pessimistic - involves time and resource consuming Bayesian inference resulting in radical reformulation of the problem to be solved; (iii) optimistic - asks exclusively for subrange subdivision by bisection; (3) use of the weaker accuracy target from the two possible ones (the input accuracy specifications and the intrinsic integrand properties respectively) - results in maximum possible solution accuracy under minimum possible computing time.

Adaptive integral feedback controller for pitch and yaw channels of an AUV with actuator saturations.

PubMed

Sarhadi, Pouria; Noei, Abolfazl Ranjbar; Khosravi, Alireza

2016-11-01

Input saturations and uncertain dynamics are among the practical challenges in control of autonomous vehicles. Adaptive control is known as a proper method to deal with the uncertain dynamics of these systems. Therefore, incorporating the ability to confront with input saturation in adaptive controllers can be valuable. In this paper, an adaptive autopilot is presented for the pitch and yaw channels of an autonomous underwater vehicle (AUV) in the presence of input saturations. This will be performed by combination of a model reference adaptive control (MRAC) with integral state feedback with a modern anti-windup (AW) compensator. MRAC with integral state feedback is commonly used in autonomous vehicles. However, some proper modifications need to be taken into account in order to cope with the saturation problem. To this end, a Riccati-based anti-windup (AW) compensator is employed. The presented technique is applied to the non-linear six degrees of freedom (DOF) model of an AUV and the obtained results are compared with that of its baseline method. Several simulation scenarios are executed in the pitch and yaw channels to evaluate the controller performance. Moreover, effectiveness of proposed adaptive controller is comprehensively investigated by implementing Monte Carlo simulations. The obtained results verify the performance of proposed method. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Adaptive exponential integrate-and-fire model as an effective description of neuronal activity.

PubMed

Brette, Romain; Gerstner, Wulfram

2005-11-01

We introduce a two-dimensional integrate-and-fire model that combines an exponential spike mechanism with an adaptation equation, based on recent theoretical findings. We describe a systematic method to estimate its parameters with simple electrophysiological protocols (current-clamp injection of pulses and ramps) and apply it to a detailed conductance-based model of a regular spiking neuron. Our simple model predicts correctly the timing of 96% of the spikes (+/-2 ms) of the detailed model in response to injection of noisy synaptic conductances. The model is especially reliable in high-conductance states, typical of cortical activity in vivo, in which intrinsic conductances were found to have a reduced role in shaping spike trains. These results are promising because this simple model has enough expressive power to reproduce qualitatively several electrophysiological classes described in vitro.

An Adaptive Intelligent Integrated Lighting Control Approach for High-Performance Office Buildings

NASA Astrophysics Data System (ADS)

Karizi, Nasim

An acute and crucial societal problem is the energy consumed in existing commercial buildings. There are 1.5 million commercial buildings in the U.S. with only about 3% being built each year. Hence, existing buildings need to be properly operated and maintained for several decades. Application of integrated centralized control systems in buildings could lead to more than 50% energy savings. This research work demonstrates an innovative adaptive integrated lighting control approach which could achieve significant energy savings and increase indoor comfort in high performance office buildings. In the first phase of the study, a predictive algorithm was developed and validated through experiments in an actual test room. The objective was to regulate daylight on a specified work plane by controlling the blind slat angles. Furthermore, a sensor-based integrated adaptive lighting controller was designed in Simulink which included an innovative sensor optimization approach based on genetic algorithm to minimize the number of sensors and efficiently place them in the office. The controller was designed based on simple integral controllers. The objective of developed control algorithm was to improve the illuminance situation in the office through controlling the daylight and electrical lighting. To evaluate the performance of the system, the controller was applied on experimental office model in Lee et al.'s research study in 1998. The result of the developed control approach indicate a significantly improvement in lighting situation and 1-23% and 50-78% monthly electrical energy savings in the office model, compared to two static strategies when the blinds were left open and closed during the whole year respectively.

Asynchronous adaptive time step in quantitative cellular automata modeling

PubMed Central

Zhu, Hao; Pang, Peter YH; Sun, Yan; Dhar, Pawan

2004-01-01

Background The behaviors of cells in metazoans are context dependent, thus large-scale multi-cellular modeling is often necessary, for which cellular automata are natural candidates. Two related issues are involved in cellular automata based multi-cellular modeling: how to introduce differential equation based quantitative computing to precisely describe cellular activity, and upon it, how to solve the heavy time consumption issue in simulation. Results Based on a modified, language based cellular automata system we extended that allows ordinary differential equations in models, we introduce a method implementing asynchronous adaptive time step in simulation that can considerably improve efficiency yet without a significant sacrifice of accuracy. An average speedup rate of 4–5 is achieved in the given example. Conclusions Strategies for reducing time consumption in simulation are indispensable for large-scale, quantitative multi-cellular models, because even a small 100 × 100 × 100 tissue slab contains one million cells. Distributed and adaptive time step is a practical solution in cellular automata environment. PMID:15222901

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.

Integrated System Design: Promoting the Capacity of Sociotechnical Systems for Adaptation through Extensions of Cognitive Work Analysis

PubMed Central

Naikar, Neelam; Elix, Ben

2016-01-01

This paper proposes an approach for integrated system design, which has the intent of facilitating high levels of effectiveness in sociotechnical systems by promoting their capacity for adaptation. Building on earlier ideas and empirical observations, this approach recognizes that to create adaptive systems it is necessary to integrate the design of all of the system elements, including the interfaces, teams, training, and automation, such that workers are supported in adapting their behavior as well as their structure, or organization, in a coherent manner. Current approaches for work analysis and design are limited in regard to this fundamental objective, especially in cases when workers are confronted with unforeseen events. A suitable starting point is offered by cognitive work analysis (CWA), but while this framework can support actors in adapting their behavior, it does not necessarily accommodate adaptations in their structure. Moreover, associated design approaches generally focus on individual system elements, and those that consider multiple elements appear limited in their ability to facilitate integration, especially in the manner intended here. The proposed approach puts forward the set of possibilities for work organization in a system as the central mechanism for binding the design of its various elements, so that actors can adapt their structure as well as their behavior—in a unified fashion—to handle both familiar and novel conditions. Accordingly, this paper demonstrates how the set of possibilities for work organization in a system may be demarcated independently of the situation, through extensions of CWA, and how it may be utilized in design. This lynchpin, conceptualized in the form of a diagram of work organization possibilities (WOP), is important for preserving a system's inherent capacity for adaptation. Future research should focus on validating these concepts and establishing the feasibility of implementing them in industrial

Integrated System Design: Promoting the Capacity of Sociotechnical Systems for Adaptation through Extensions of Cognitive Work Analysis.

PubMed

Naikar, Neelam; Elix, Ben

2016-01-01

This paper proposes an approach for integrated system design, which has the intent of facilitating high levels of effectiveness in sociotechnical systems by promoting their capacity for adaptation. Building on earlier ideas and empirical observations, this approach recognizes that to create adaptive systems it is necessary to integrate the design of all of the system elements, including the interfaces, teams, training, and automation, such that workers are supported in adapting their behavior as well as their structure, or organization, in a coherent manner. Current approaches for work analysis and design are limited in regard to this fundamental objective, especially in cases when workers are confronted with unforeseen events. A suitable starting point is offered by cognitive work analysis (CWA), but while this framework can support actors in adapting their behavior, it does not necessarily accommodate adaptations in their structure. Moreover, associated design approaches generally focus on individual system elements, and those that consider multiple elements appear limited in their ability to facilitate integration, especially in the manner intended here. The proposed approach puts forward the set of possibilities for work organization in a system as the central mechanism for binding the design of its various elements, so that actors can adapt their structure as well as their behavior-in a unified fashion-to handle both familiar and novel conditions. Accordingly, this paper demonstrates how the set of possibilities for work organization in a system may be demarcated independently of the situation, through extensions of CWA, and how it may be utilized in design. This lynchpin, conceptualized in the form of a diagram of work organization possibilities (WOP), is important for preserving a system's inherent capacity for adaptation. Future research should focus on validating these concepts and establishing the feasibility of implementing them in industrial contexts.

Infrared and visible images registration with adaptable local-global feature integration for rail inspection

NASA Astrophysics Data System (ADS)

Tang, Chaoqing; Tian, Gui Yun; Chen, Xiaotian; Wu, Jianbo; Li, Kongjing; Meng, Hongying

2017-12-01

Active thermography provides infrared images that contain sub-surface defect information, while visible images only reveal surface information. Mapping infrared information to visible images offers more comprehensive visualization for decision-making in rail inspection. However, the common information for registration is limited due to different modalities in both local and global level. For example, rail track which has low temperature contrast reveals rich details in visible images, but turns blurry in the infrared counterparts. This paper proposes a registration algorithm called Edge-Guided Speeded-Up-Robust-Features (EG-SURF) to address this issue. Rather than sequentially integrating local and global information in matching stage which suffered from buckets effect, this algorithm adaptively integrates local and global information into a descriptor to gather more common information before matching. This adaptability consists of two facets, an adaptable weighting factor between local and global information, and an adaptable main direction accuracy. The local information is extracted using SURF while the global information is represented by shape context from edges. Meanwhile, in shape context generation process, edges are weighted according to local scale and decomposed into bins using a vector decomposition manner to provide more accurate descriptor. The proposed algorithm is qualitatively and quantitatively validated using eddy current pulsed thermography scene in the experiments. In comparison with other algorithms, better performance has been achieved.

Determinants of International Students' Adaptation: Examining Effects of Integrative Motivation, Instrumental Motivation and Second Language Proficiency

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,…

Optimized quantum sensing with a single electron spin using real-time adaptive measurements.

PubMed

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.

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 Implicit Non-Equilibrium Radiation Diffusion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Philip, Bobby; Wang, Zhen; Berrill, Mark A

2013-01-01

We describe methods for accurate and efficient long term time integra- tion of non-equilibrium radiation diffusion systems: implicit time integration for effi- cient long term time integration of stiff multiphysics systems, local control theory based step size control to minimize the required global number of time steps while control- ling accuracy, dynamic 3D adaptive mesh refinement (AMR) to minimize memory and computational costs, Jacobian Free Newton-Krylov methods on AMR grids for efficient nonlinear solution, and optimal multilevel preconditioner components that provide level independent solver convergence.

The adaptive significance of adult neurogenesis: an integrative approach

PubMed Central

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

Adaptation to Climatic Hazards in the Savannah Ecosystem: Improving Adaptation Policy and Action

NASA Astrophysics Data System (ADS)

Yiran, Gerald A. B.; Stringer, Lindsay C.

2017-10-01

People in Ghana's savannah ecosystem have historically experienced a range of climatic hazards that have affected their livelihoods. In view of current climate variability and change, and projected increases in extreme events, adaptation to climate risks is vital. Policies have been put in place to enhance adaptation across sub-Saharan Africa in accordance with international agreements. At the same time, local people, through experience, have learned to adapt. This paper examines current policy actions and their implementation alongside an assessment of barriers to local adaptation. In doing so it links adaptation policy and practice. Policy documents were analysed that covered key livelihood sectors, which were identified as climate sensitive. These included agriculture, water, housing and health policies, as well as the National Climate Change Policy. In-depth interviews and focus group discussions were also held with key stakeholders in the Upper East Region of Ghana. Analyses were carried using thematic content analysis. Although policies and actions complement each other, their integration is weak. Financial, institutional, social, and technological barriers hinder successful local implementation of some policy actions, while lack of local involvement in policy formulation also hinders adaptation practice. Integration of local perspectives into policy needs to be strengthened in order to enhance adaptation. Coupled with this is a need to consider adaptation to climate change in development policies and to pursue efforts to reduce or remove the key barriers to implementation at the local level.

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

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.

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…

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.

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.

Adaptive Tunable Laser Spectrometer for Space Applications

NASA Technical Reports Server (NTRS)

Flesch, Gregory; Keymeulen, Didier

2010-01-01

An architecture and process for the rapid prototyping and subsequent development of an adaptive tunable laser absorption spectrometer (TLS) are described. Our digital hardware/firmware/software platform is both reconfigurable at design time as well as autonomously adaptive in real-time for both post-integration and post-launch situations. The design expands the range of viable target environments and enhances tunable laser spectrometer performance in extreme and even unpredictable environments. Through rapid prototyping with a commercial RTOS/FPGA platform, we have implemented a fully operational tunable laser spectrometer (using a highly sensitive second harmonic technique). With this prototype, we have demonstrated autonomous real-time adaptivity in the lab with simulated extreme environments.

Markov chains of infinite order and asymptotic satisfaction of balance: application to the adaptive integration method.

PubMed

Earl, David J; Deem, Michael W

2005-04-14

Adaptive Monte Carlo methods can be viewed as implementations of Markov chains with infinite memory. We derive a general condition for the convergence of a Monte Carlo method whose history dependence is contained within the simulated density distribution. In convergent cases, our result implies that the balance condition need only be satisfied asymptotically. As an example, we show that the adaptive integration method converges.

Variable self-powered light detection CMOS chip with real-time adaptive tracking digital output based on a novel on-chip sensor.

PubMed

Wang, HongYi; Fan, Youyou; Lu, Zhijian; Luo, Tao; Fu, Houqiang; Song, Hongjiang; Zhao, Yuji; Christen, Jennifer Blain

2017-10-02

This paper provides a solution for a self-powered light direction detection with digitized output. Light direction sensors, energy harvesting photodiodes, real-time adaptive tracking digital output unit and other necessary circuits are integrated on a single chip based on a standard 0.18 µm CMOS process. Light direction sensors proposed have an accuracy of 1.8 degree over a 120 degree range. In order to improve the accuracy, a compensation circuit is presented for photodiodes' forward currents. The actual measurement precision of output is approximately 7 ENOB. Besides that, an adaptive under voltage protection circuit is designed for variable supply power which may undulate with temperature and process.

Adaptation of ICT Integration Approach Scale to Kosovo Culture: A Study of Validity and Reliability Analysis

ERIC Educational Resources Information Center

Kervan, Serdan; Tezci, Erdogan

2018-01-01

The aim of this study is to adapt ICT integration approach scale to Kosovo culture, which measures ICT integration approaches of university faculty to teaching and learning process. The scale developed in Turkish has been translated into Albanian to provide linguistic equivalence. The survey was given to a total of 303 instructors [161 (53.1%)…

Higher-order time integration of Coulomb collisions in a plasma using Langevin equations

DOE PAGES

Dimits, A. M.; Cohen, B. I.; Caflisch, R. E.; ...

2013-02-08

The extension of Langevin-equation Monte-Carlo algorithms for Coulomb collisions from the conventional Euler-Maruyama time integration to the next higher order of accuracy, the Milstein scheme, has been developed, implemented, and tested. This extension proceeds via a formulation of the angular scattering directly as stochastic differential equations in the two fixed-frame spherical-coordinate velocity variables. Results from the numerical implementation show the expected improvement [O(Δt) vs. O(Δt 1/2)] in the strong convergence rate both for the speed |v| and angular components of the scattering. An important result is that this improved convergence is achieved for the angular component of the scattering ifmore » and only if the “area-integral” terms in the Milstein scheme are included. The resulting Milstein scheme is of value as a step towards algorithms with both improved accuracy and efficiency. These include both algorithms with improved convergence in the averages (weak convergence) and multi-time-level schemes. The latter have been shown to give a greatly reduced cost for a given overall error level when compared with conventional Monte-Carlo schemes, and their performance is improved considerably when the Milstein algorithm is used for the underlying time advance versus the Euler-Maruyama algorithm. A new method for sampling the area integrals is given which is a simplification of an earlier direct method and which retains high accuracy. Lastly, this method, while being useful in its own right because of its relative simplicity, is also expected to considerably reduce the computational requirements for the direct conditional sampling of the area integrals that is needed for adaptive strong integration.« less

Finite-Time Stabilization and Adaptive Control of Memristor-Based Delayed Neural Networks.

PubMed

Wang, Leimin; Shen, Yi; Zhang, Guodong

Finite-time stability problem has been a hot topic in control and system engineering. This paper deals with the finite-time stabilization issue of memristor-based delayed neural networks (MDNNs) via two control approaches. First, in order to realize the stabilization of MDNNs in finite time, a delayed state feedback controller is proposed. Then, a novel adaptive strategy is applied to the delayed controller, and finite-time stabilization of MDNNs can also be achieved by using the adaptive control law. Some easily verified algebraic criteria are derived to ensure the stabilization of MDNNs in finite time, and the estimation of the settling time functional is given. Moreover, several finite-time stability results as our special cases for both memristor-based neural networks (MNNs) without delays and neural networks are given. Finally, three examples are provided for the illustration of the theoretical results.Finite-time stability problem has been a hot topic in control and system engineering. This paper deals with the finite-time stabilization issue of memristor-based delayed neural networks (MDNNs) via two control approaches. First, in order to realize the stabilization of MDNNs in finite time, a delayed state feedback controller is proposed. Then, a novel adaptive strategy is applied to the delayed controller, and finite-time stabilization of MDNNs can also be achieved by using the adaptive control law. Some easily verified algebraic criteria are derived to ensure the stabilization of MDNNs in finite time, and the estimation of the settling time functional is given. Moreover, several finite-time stability results as our special cases for both memristor-based neural networks (MNNs) without delays and neural networks are given. Finally, three examples are provided for the illustration of the theoretical results.

Adaptation to visual or auditory time intervals modulates the perception of visual apparent motion

PubMed Central

Zhang, Huihui; Chen, Lihan; Zhou, Xiaolin

2012-01-01

It is debated whether sub-second timing is subserved by a centralized mechanism or by the intrinsic properties of task-related neural activity in specific modalities (Ivry and Schlerf, 2008). By using a temporal adaptation task, we investigated whether adapting to different time intervals conveyed through stimuli in different modalities (i.e., frames of a visual Ternus display, visual blinking discs, or auditory beeps) would affect the subsequent implicit perception of visual timing, i.e., inter-stimulus interval (ISI) between two frames in a Ternus display. The Ternus display can induce two percepts of apparent motion (AM), depending on the ISI between the two frames: “element motion” for short ISIs, in which the endmost disc is seen as moving back and forth while the middle disc at the overlapping or central position remains stationary; “group motion” for longer ISIs, in which both discs appear to move in a manner of lateral displacement as a whole. In Experiment 1, participants adapted to either the typical “element motion” (ISI = 50 ms) or the typical “group motion” (ISI = 200 ms). In Experiments 2 and 3, participants adapted to a time interval of 50 or 200 ms through observing a series of two paired blinking discs at the center of the screen (Experiment 2) or hearing a sequence of two paired beeps (with pitch 1000 Hz). In Experiment 4, participants adapted to sequences of paired beeps with either low pitches (500 Hz) or high pitches (5000 Hz). After adaptation in each trial, participants were presented with a Ternus probe in which the ISI between the two frames was equal to the transitional threshold of the two types of motions, as determined by a pretest. Results showed that adapting to the short time interval in all the situations led to more reports of “group motion” in the subsequent Ternus probes; adapting to the long time interval, however, caused no aftereffect for visual adaptation but significantly more reports of group motion for

A dosimetric comparison of real-time adaptive and non-adaptive radiotherapy: A multi-institutional study encompassing robotic, gimbaled, multileaf collimator and couch tracking.

PubMed

Colvill, Emma; Booth, Jeremy; Nill, Simeon; Fast, Martin; Bedford, James; Oelfke, Uwe; Nakamura, Mitsuhiro; Poulsen, Per; Worm, Esben; Hansen, Rune; Ravkilde, Thomas; Scherman Rydhög, Jonas; Pommer, Tobias; Munck Af Rosenschold, Per; Lang, Stephanie; Guckenberger, Matthias; Groh, Christian; Herrmann, Christian; Verellen, Dirk; Poels, Kenneth; Wang, Lei; Hadsell, Michael; Sothmann, Thilo; Blanck, Oliver; Keall, Paul

2016-04-01

A study of real-time adaptive radiotherapy systems was performed to test the hypothesis that, across delivery systems and institutions, the dosimetric accuracy is improved with adaptive treatments over non-adaptive radiotherapy in the presence of patient-measured tumor motion. Ten institutions with robotic(2), gimbaled(2), MLC(4) or couch tracking(2) used common materials including CT and structure sets, motion traces and planning protocols to create a lung and a prostate plan. For each motion trace, the plan was delivered twice to a moving dosimeter; with and without real-time adaptation. Each measurement was compared to a static measurement and the percentage of failed points for γ-tests recorded. For all lung traces all measurement sets show improved dose accuracy with a mean 2%/2mm γ-fail rate of 1.6% with adaptation and 15.2% without adaptation (p<0.001). For all prostate the mean 2%/2mm γ-fail rate was 1.4% with adaptation and 17.3% without adaptation (p<0.001). The difference between the four systems was small with an average 2%/2mm γ-fail rate of <3% for all systems with adaptation for lung and prostate. The investigated systems all accounted for realistic tumor motion accurately and performed to a similar high standard, with real-time adaptation significantly outperforming non-adaptive delivery methods. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

A Compact Bulk Acousto-Optic Time Integrating Correlator.

DTIC Science & Technology

1984-11-01

AD-A156 668 A COMPACT BULK ACOUSTO - OPTIC TIME INTEGRATING 1/1 CORRELATOR(U) ELECTRONICS RESEARCH LAB ADELAIDE (AUSTRALIA) D A FOGG NOV 84 ERL-9323-TR...DEFENCE RESEARCH CENTRE SALISBURY SOUTH AUSTRALIA TECHNICAL REPORT ER L-0323-TR A COMPACT BULK ACOUSTO - OPTIC TIME INTEGRATING CORRELATOR D.A.B. FOGG...LABORATORY TECHNICAL REPORT ERL-0323-TR A COMPACT BULK ACOUSTO - OPTIC TIME INTEGRATING CORRELATOR D.A.B. Fogg SUMMARY This report describes the design and

An Adaptive Low-Cost INS/GNSS Tightly-Coupled Integration Architecture Based on Redundant Measurement Noise Covariance Estimation.

PubMed

Li, Zheng; Zhang, Hai; Zhou, Qifan; Che, Huan

2017-09-05

The main objective of the introduced study is to design an adaptive Inertial Navigation System/Global Navigation Satellite System (INS/GNSS) tightly-coupled integration system that can provide more reliable navigation solutions by making full use of an adaptive Kalman filter (AKF) and satellite selection algorithm. To achieve this goal, we develop a novel redundant measurement noise covariance estimation (RMNCE) theorem, which adaptively estimates measurement noise properties by analyzing the difference sequences of system measurements. The proposed RMNCE approach is then applied to design both a modified weighted satellite selection algorithm and a type of adaptive unscented Kalman filter (UKF) to improve the performance of the tightly-coupled integration system. In addition, an adaptive measurement noise covariance expanding algorithm is developed to mitigate outliers when facing heavy multipath and other harsh situations. Both semi-physical simulation and field experiments were conducted to evaluate the performance of the proposed architecture and were compared with state-of-the-art algorithms. The results validate that the RMNCE provides a significant improvement in the measurement noise covariance estimation and the proposed architecture can improve the accuracy and reliability of the INS/GNSS tightly-coupled systems. The proposed architecture can effectively limit positioning errors under conditions of poor GNSS measurement quality and outperforms all the compared schemes.

An Adaptive Low-Cost INS/GNSS Tightly-Coupled Integration Architecture Based on Redundant Measurement Noise Covariance Estimation

PubMed Central

Li, Zheng; Zhang, Hai; Zhou, Qifan; Che, Huan

2017-01-01

The main objective of the introduced study is to design an adaptive Inertial Navigation System/Global Navigation Satellite System (INS/GNSS) tightly-coupled integration system that can provide more reliable navigation solutions by making full use of an adaptive Kalman filter (AKF) and satellite selection algorithm. To achieve this goal, we develop a novel redundant measurement noise covariance estimation (RMNCE) theorem, which adaptively estimates measurement noise properties by analyzing the difference sequences of system measurements. The proposed RMNCE approach is then applied to design both a modified weighted satellite selection algorithm and a type of adaptive unscented Kalman filter (UKF) to improve the performance of the tightly-coupled integration system. In addition, an adaptive measurement noise covariance expanding algorithm is developed to mitigate outliers when facing heavy multipath and other harsh situations. Both semi-physical simulation and field experiments were conducted to evaluate the performance of the proposed architecture and were compared with state-of-the-art algorithms. The results validate that the RMNCE provides a significant improvement in the measurement noise covariance estimation and the proposed architecture can improve the accuracy and reliability of the INS/GNSS tightly-coupled systems. The proposed architecture can effectively limit positioning errors under conditions of poor GNSS measurement quality and outperforms all the compared schemes. PMID:28872629

Role of recoverin in rod photoreceptor light adaptation.

PubMed

Morshedian, Ala; Woodruff, Michael L; Fain, Gordon L

2018-04-15

Recoverin is a small molecular-weight, calcium-binding protein in rod outer segments that can modulate the rate of rhodopsin phosphorylation. We describe two additional and perhaps more important functions during photoreceptor light adaptation. Recoverin influences the rate of change of adaptation. In wild-type rods, sensitivity and response integration time adapt with similar time constants of 150-200 ms. In Rv-/- rods lacking recoverin, sensitivity declines faster and integration time is already shorter and not significantly altered. During steady light exposure, rod circulating current slowly increases during a time course of tens of seconds, gradually extending the operating range of the rod. In Rv-/- rods, this mechanism is deleted, steady-state currents are already larger and rods saturate at brighter intensities. We propose that recoverin modulates spontaneous and light-activated phophodiesterase-6, the phototransduction effector enzyme, to increase sensitivity in dim light but improve responsiveness to change in brighter illumination. Recoverin is a small molecular-weight, calcium-binding protein in rod outer segments that binds to G-protein receptor kinase 1 and can alter the rate of rhodopsin phosphorylation. A change in phosphorylation should change the lifetime of light-activated rhodopsin and the gain of phototransduction, but deletion of recoverin has little effect on the sensitivity of rods either in the dark or in dim-to-moderate background light. We describe two additional functions perhaps of greater physiological significance. (i) When the ambient intensity increases, sensitivity and integration time decrease in wild-type (WT) rods with similar time constants of 150-200 ms. Recoverin is part of the mechanism controlling this process because, in Rv-/- rods lacking recoverin, sensitivity declines more rapidly and integration time is already shorter and not further altered. (ii) During steady light exposure, WT rod circulating current slowly

A 3D image sensor with adaptable charge subtraction scheme for background light suppression

NASA Astrophysics Data System (ADS)

Shin, Jungsoon; Kang, Byongmin; Lee, Keechang; Kim, James D. K.

2013-02-01

We present a 3D ToF (Time-of-Flight) image sensor with adaptive charge subtraction scheme for background light suppression. The proposed sensor can alternately capture high resolution color image and high quality depth map in each frame. In depth-mode, the sensor requires enough integration time for accurate depth acquisition, but saturation will occur in high background light illumination. We propose to divide the integration time into N sub-integration times adaptively. In each sub-integration time, our sensor captures an image without saturation and subtracts the charge to prevent the pixel from the saturation. In addition, the subtraction results are cumulated N times obtaining a final result image without background illumination at full integration time. Experimental results with our own ToF sensor show high background suppression performance. We also propose in-pixel storage and column-level subtraction circuit for chiplevel implementation of the proposed method. We believe the proposed scheme will enable 3D sensors to be used in out-door environment.

Adaptive fixed-time control for cluster synchronisation of coupled complex networks with uncertain disturbances

NASA Astrophysics Data System (ADS)

Jiang, Shengqin; Lu, Xiaobo; Cai, Guoliang; Cai, Shuiming

2017-12-01

This paper focuses on the cluster synchronisation problem of coupled complex networks with uncertain disturbances under an adaptive fixed-time control strategy. To begin with, complex dynamical networks with community structure which are subject to uncertain disturbances are taken into account. Then, a novel adaptive control strategy combined with fixed-time techniques is proposed to guarantee the nodes in the communities to desired states in a settling time. In addition, the stability of complex error systems is theoretically proved based on Lyapunov stability theorem. At last, two examples are presented to verify the effectiveness of the proposed adaptive fixed-time control.

A Personalized Predictive Framework for Multivariate Clinical Time Series via Adaptive Model Selection.

PubMed

Liu, Zitao; Hauskrecht, Milos

2017-11-01

Building of an accurate predictive model of clinical time series for a patient is critical for understanding of the patient condition, its dynamics, and optimal patient management. Unfortunately, this process is not straightforward. First, patient-specific variations are typically large and population-based models derived or learned from many different patients are often unable to support accurate predictions for each individual patient. Moreover, time series observed for one patient at any point in time may be too short and insufficient to learn a high-quality patient-specific model just from the patient's own data. To address these problems we propose, develop and experiment with a new adaptive forecasting framework for building multivariate clinical time series models for a patient and for supporting patient-specific predictions. The framework relies on the adaptive model switching approach that at any point in time selects the most promising time series model out of the pool of many possible models, and consequently, combines advantages of the population, patient-specific and short-term individualized predictive models. We demonstrate that the adaptive model switching framework is very promising approach to support personalized time series prediction, and that it is able to outperform predictions based on pure population and patient-specific models, as well as, other patient-specific model adaptation strategies.

Influences of selective adaptation on perception of audiovisual speech

PubMed Central

Dias, James W.; Cook, Theresa C.; Rosenblum, Lawrence D.

2016-01-01

Research suggests that selective adaptation in speech is a low-level process dependent on sensory-specific information shared between the adaptor and test-stimuli. However, previous research has only examined how adaptors shift perception of unimodal test stimuli, either auditory or visual. In the current series of experiments, we investigated whether adaptation to cross-sensory phonetic information can influence perception of integrated audio-visual phonetic information. We examined how selective adaptation to audio and visual adaptors shift perception of speech along an audiovisual test continuum. This test-continuum consisted of nine audio-/ba/-visual-/va/ stimuli, ranging in visual clarity of the mouth. When the mouth was clearly visible, perceivers “heard” the audio-visual stimulus as an integrated “va” percept 93.7% of the time (e.g., McGurk & MacDonald, 1976). As visibility of the mouth became less clear across the nine-item continuum, the audio-visual “va” percept weakened, resulting in a continuum ranging in audio-visual percepts from /va/ to /ba/. Perception of the test-stimuli was tested before and after adaptation. Changes in audiovisual speech perception were observed following adaptation to visual-/va/ and audiovisual-/va/, but not following adaptation to auditory-/va/, auditory-/ba/, or visual-/ba/. Adaptation modulates perception of integrated audio-visual speech by modulating the processing of sensory-specific information. The results suggest that auditory and visual speech information are not completely integrated at the level of selective adaptation. PMID:27041781

Just-in-time adaptive classifiers-part II: designing the classifier.

PubMed

Alippi, Cesare; Roveri, Manuel

2008-12-01

Aging effects, environmental changes, thermal drifts, and soft and hard faults affect physical systems by changing their nature and behavior over time. To cope with a process evolution adaptive solutions must be envisaged to track its dynamics; in this direction, adaptive classifiers are generally designed by assuming the stationary hypothesis for the process generating the data with very few results addressing nonstationary environments. This paper proposes a methodology based on k-nearest neighbor (NN) classifiers for designing adaptive classification systems able to react to changing conditions just-in-time (JIT), i.e., exactly when it is needed. k-NN classifiers have been selected for their computational-free training phase, the possibility to easily estimate the model complexity k and keep under control the computational complexity of the classifier through suitable data reduction mechanisms. A JIT classifier requires a temporal detection of a (possible) process deviation (aspect tackled in a companion paper) followed by an adaptive management of the knowledge base (KB) of the classifier to cope with the process change. The novelty of the proposed approach resides in the general framework supporting the real-time update of the KB of the classification system in response to novel information coming from the process both in stationary conditions (accuracy improvement) and in nonstationary ones (process tracking) and in providing a suitable estimate of k. It is shown that the classification system grants consistency once the change targets the process generating the data in a new stationary state, as it is the case in many real applications.

Improving the Usability of Integrated Assessment for Adaptation Practice: Insights from the U.S. Southeast Energy Sector

DOE Office of Scientific and Technical Information (OSTI.GOV)

de Bremond, Ariane; Preston, Benjamin; Rice, Jennie S.

2014-10-01

Energy systems comprise a key sector of the U.S. economy, and one that has been identified as potentially vulnerable to the effects of climate variability and change. However, understanding of adaptation processes in energy companies and private entities more broadly is limited. It is unclear, for example, the extent to which energy companies are well-served by existing knowledge and tools emerging from the impacts, adaptation and vulnerability (IAV) and integrated assessment modeling (IAM) communities and/or what experiments, analyses, and model results have practical utility for informing adaptation in the energy sector. As part of a regional IAM development project, wemore » investigated available evidence of adaptation processes in the energy sector, with a particular emphasis on the U.S. Southeast and Gulf Coast region. A mixed methods approach of literature review and semi-structured interviews with key informants from energy utilities was used to compare existing knowledge from the IAV community with that of regional stakeholders. That comparison revealed that much of the IAV literature on the energy sector is climate-centric and therefore disconnected from the more integrated decision-making processes and institutional perspectives of energy utilities. Increasing the relevance of research and assessment for the energy sector will necessitate a greater investment in integrated assessment and modeling efforts that respond to practical decision-making needs as well as greater collaboration between energy utilities and researchers in the design, execution, and communication of those efforts.« less

Intuitive control of mobile robots: an architecture for autonomous adaptive dynamic behaviour integration.

PubMed

Melidis, Christos; Iizuka, Hiroyuki; Marocco, Davide

2018-05-01

In this paper, we present a novel approach to human-robot control. Taking inspiration from behaviour-based robotics and self-organisation principles, we present an interfacing mechanism, with the ability to adapt both towards the user and the robotic morphology. The aim is for a transparent mechanism connecting user and robot, allowing for a seamless integration of control signals and robot behaviours. Instead of the user adapting to the interface and control paradigm, the proposed architecture allows the user to shape the control motifs in their way of preference, moving away from the case where the user has to read and understand an operation manual, or it has to learn to operate a specific device. Starting from a tabula rasa basis, the architecture is able to identify control patterns (behaviours) for the given robotic morphology and successfully merge them with control signals from the user, regardless of the input device used. The structural components of the interface are presented and assessed both individually and as a whole. Inherent properties of the architecture are presented and explained. At the same time, emergent properties are presented and investigated. As a whole, this paradigm of control is found to highlight the potential for a change in the paradigm of robotic control, and a new level in the taxonomy of human in the loop systems.

Integrated care in the emergency department: a complex adaptive systems perspective.

PubMed

Nugus, Peter; Carroll, Katherine; Hewett, David G; Short, Alison; Forero, Roberto; Braithwaite, Jeffrey

2010-12-01

Emergency clinicians undertake boundary-work as they facilitate patient trajectories through the Emergency Department (ED). Emergency clinicians must manage the constantly-changing dynamics at the boundaries of the ED and other hospital departments and organizations whose services emergency clinicians seek to integrate. Integrating the care that differing clinical groups provide, the services EDs offer, and patients' needs across this journey is challenging. The journey is usually accounted for in a linear way - as a "continuity of care" problem. In this paper, we instead conceptualize integrated care in the ED using a complex adaptive systems (CAS) perspective. A CAS perspective accounts for the degree to which other departments and units outside of the ED are integrated, and appropriately described, using CAS concepts and language. One year of ethnographic research was conducted, combining observation and semi-structured interviews, in the EDs of two tertiary referral hospitals in Sydney, Australia. We found the CAS approach to be salient to analyzing integrated care in the ED because the processes of categorization, diagnosis and discharge are primarily about the linkages between services, and the communication and negotiation required to enact those linkages, however imperfectly they occur in practice. Emergency clinicians rapidly process large numbers of high-need patients, in a relatively efficient system of care inadequately explained by linear models. A CAS perspective exposes integrated care as management of the patient trajectory within porous, shifting and negotiable boundaries. Copyright © 2010 Elsevier Ltd. All rights reserved.

Spike-frequency adaptation in the inferior colliculus.

PubMed

Ingham, Neil J; McAlpine, David

2004-02-01

We investigated spike-frequency adaptation of neurons sensitive to interaural phase disparities (IPDs) in the inferior colliculus (IC) of urethane-anesthetized guinea pigs using a stimulus paradigm designed to exclude the influence of adaptation below the level of binaural integration. The IPD-step stimulus consists of a binaural 3,000-ms tone, in which the first 1,000 ms is held at a neuron's least favorable ("worst") IPD, adapting out monaural components, before being stepped rapidly to a neuron's most favorable ("best") IPD for 300 ms. After some variable interval (1-1,000 ms), IPD is again stepped to the best IPD for 300 ms, before being returned to a neuron's worst IPD for the remainder of the stimulus. Exponential decay functions fitted to the response to best-IPD steps revealed an average adaptation time constant of 52.9 +/- 26.4 ms. Recovery from adaptation to best IPD steps showed an average time constant of 225.5 +/- 210.2 ms. Recovery time constants were not correlated with adaptation time constants. During the recovery period, adaptation to a 2nd best-IPD step followed similar kinetics to adaptation during the 1st best-IPD step. The mean adaptation time constant at stimulus onset (at worst IPD) was 34.8 +/- 19.7 ms, similar to the 38.4 +/- 22.1 ms recorded to contralateral stimulation alone. Individual time constants after stimulus onset were correlated with each other but not with time constants during the best-IPD step. We conclude that such binaurally derived measures of adaptation reflect processes that occur above the level of exclusively monaural pathways, and subsequent to the site of primary binaural interaction.

Method and apparatus for adaptive force and position control of manipulators

NASA Technical Reports Server (NTRS)

Seraji, Homayoun (Inventor)

1989-01-01

The present invention discloses systematic methods and apparatus for the design of real time controllers. Real-time control employs adaptive force/position by use of feedforward and feedback controllers, with the feedforward controller being the inverse of the linearized model of robot dynamics and containing only proportional-double-derivative terms is disclosed. The feedback controller, of the proportional-integral-derivative type, ensures that manipulator joints follow reference trajectories and the feedback controller achieves robust tracking of step-plus-exponential trajectories, all in real time. The adaptive controller includes adaptive force and position control within a hybrid control architecture. The adaptive controller, for force control, achieves tracking of desired force setpoints, and the adaptive position controller accomplishes tracking of desired position trajectories. Circuits in the adaptive feedback and feedforward controllers are varied by adaptation laws.

Exponential integrators in time-dependent density-functional calculations

NASA Astrophysics Data System (ADS)

Kidd, Daniel; Covington, Cody; Varga, Kálmán

2017-12-01

The integrating factor and exponential time differencing methods are implemented and tested for solving the time-dependent Kohn-Sham equations. Popular time propagation methods used in physics, as well as other robust numerical approaches, are compared to these exponential integrator methods in order to judge the relative merit of the computational schemes. We determine an improvement in accuracy of multiple orders of magnitude when describing dynamics driven primarily by a nonlinear potential. For cases of dynamics driven by a time-dependent external potential, the accuracy of the exponential integrator methods are less enhanced but still match or outperform the best of the conventional methods tested.

Phenotypic plasticity of nest timing in a post-glacial landscape: how do reptiles adapt to seasonal time constraints?

PubMed

Edge, Christopher B; Rollinson, Njal; Brooks, Ronald J; Congdon, Justin D; Iverson, John B; Janzen, Fredric J; Litzgus, Jacqueline D

2017-02-01

Life histories evolve in response to constraints on the time available for growth and development. Nesting date and its plasticity in response to spring temperature may therefore be important components of fitness in oviparous ectotherms near their northern range limit, as reproducing early provides more time for embryos to complete development before winter. We used data collected over several decades to compare air temperature and nest date plasticity in populations of painted turtles and snapping turtles from a relatively warm environment (southeastern Michigan) near the southern extent of the last glacial maximum to a relatively cool environment (central Ontario) near the northern extent of post-glacial recolonization. For painted turtles, population-level differences in reaction norm elevation for two phenological traits were consistent with adaptation to time constraints, but no differences in reaction norm slopes were observed. For snapping turtle populations, the difference in reaction norm elevation for a single phenological trait was in the opposite direction of what was expected under adaptation to time constraints, and no difference in reaction norm slope was observed. Finally, among-individual variation in individual plasticity for nesting date was detected only in the northern population of snapping turtles, suggesting that reaction norms are less canalized in this northern population. Overall, we observed evidence of phenological adaptation, and possibly maladaptation, to time constraints in long-lived reptiles. Where present, (mal)adaptation occurred by virtue of differences in reaction norm elevation, not reaction norm slope. Glacial history, generation time, and genetic constraint may all play an important role in the evolution of phenological timing and its plasticity in long-lived reptiles. © 2016 by the Ecological Society of America.

Kedalion: NASA's Adaptable and Agile Hardware/Software Integration and Test Lab

NASA Technical Reports Server (NTRS)

Mangieri, Mark L.; Vice, Jason

2011-01-01

NASA fs Kedalion engineering analysis lab at Johnson Space Center is on the forefront of validating and using many contemporary avionics hardware/software development and integration techniques, which represent new paradigms to heritage NASA culture. Kedalion has validated many of the Orion hardware/software engineering techniques borrowed from the adjacent commercial aircraft avionics solution space, with the intention to build upon such techniques to better align with today fs aerospace market. Using agile techniques, commercial products, early rapid prototyping, in-house expertise and tools, and customer collaboration, Kedalion has demonstrated that cost effective contemporary paradigms hold the promise to serve future NASA endeavors within a diverse range of system domains. Kedalion provides a readily adaptable solution for medium/large scale integration projects. The Kedalion lab is currently serving as an in-line resource for the project and the Multipurpose Crew Vehicle (MPCV) program.

Multisensory integration: flexible use of general operations

PubMed Central

van Atteveldt, Nienke; Murray, Micah M.; Thut, Gregor; Schroeder, Charles

2014-01-01

Research into the anatomical substrates and “principles” for integrating inputs from separate sensory surfaces has yielded divergent findings. This suggests that multisensory integration is flexible and context-dependent, and underlines the need for dynamically adaptive neuronal integration mechanisms. We propose that flexible multisensory integration can be explained by a combination of canonical, population-level integrative operations, such as oscillatory phase-resetting and divisive normalization. These canonical operations subsume multisensory integration into a fundamental set of principles as to how the brain integrates all sorts of information, and they are being used proactively and adaptively. We illustrate this proposition by unifying recent findings from different research themes such as timing, behavioral goal and experience-related differences in integration. PMID:24656248

Two-dimensional phase unwrapping using robust derivative estimation and adaptive integration.

PubMed

Strand, Jarle; Taxt, Torfinn

2002-01-01

The adaptive integration (ADI) method for two-dimensional (2-D) phase unwrapping is presented. The method uses an algorithm for noise robust estimation of partial derivatives, followed by a noise robust adaptive integration process. The ADI method can easily unwrap phase images with moderate noise levels, and the resulting images are congruent modulo 2pi with the observed, wrapped, input images. In a quantitative evaluation, both the ADI and the BLS methods (Strand et al.) were better than the least-squares methods of Ghiglia and Romero (GR), and of Marroquin and Rivera (MRM). In a qualitative evaluation, the ADI, the BLS, and a conjugate gradient version of the MRM method (MRMCG), were all compared using a synthetic image with shear, using 115 magnetic resonance images, and using 22 fiber-optic interferometry images. For the synthetic image and the interferometry images, the ADI method gave consistently visually better results than the other methods. For the MR images, the MRMCG method was best, and the ADI method second best. The ADI method was less sensitive to the mask definition and the block size than the BLS method, and successfully unwrapped images with shears that were not marked in the masks. The computational requirements of the ADI method for images of nonrectangular objects were comparable to only two iterations of many least-squares-based methods (e.g., GR). We believe the ADI method provides a powerful addition to the ensemble of tools available for 2-D phase unwrapping.

An adaptive bit synchronization algorithm under time-varying environment.

NASA Technical Reports Server (NTRS)

Chow, L. R.; Owen, H. A., Jr.; Wang, P. P.

1973-01-01

This paper presents an adaptive estimation algorithm for bit synchronization, assuming that the parameters of the incoming data process are time-varying. Experiment results have proved that this synchronizer is workable either judged by the amount of data required or the speed of convergence.

Planning for an uncertain future - Monitoring, integration, and adaptation

USGS Publications Warehouse

Webb, Richard M. T.; 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.

Resilience thinking: integrating resilience, adaptability and transformability

Treesearch

Carl Folke; Stephen R. Carpenter; Brian Walker; Marten Scheffer; Terry Chapin; Johan Rockstrom

2010-01-01

Resilience thinking addresses the dynamics and development of complex social-ecological systems (SES). Three aspects are central: resilience, adaptability and transformability. These aspects interrelate across multiple scales. Resilience in this context is the capacity of a SES to continually change and adapt yet remain within critical thresholds. Adaptability is part...

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.

Association between stride time fractality and gait adaptability during unperturbed and asymmetric walking.

PubMed

Ducharme, Scott W; Liddy, Joshua J; Haddad, Jeffrey M; Busa, Michael A; Claxton, Laura J; van Emmerik, Richard E A

2018-04-01

Human locomotion is an inherently complex activity that requires the coordination and control of neurophysiological and biomechanical degrees of freedom across various spatiotemporal scales. Locomotor patterns must constantly be altered in the face of changing environmental or task demands, such as heterogeneous terrains or obstacles. Variability in stride times occurring at short time scales (e.g., 5-10 strides) is statistically correlated to larger fluctuations occurring over longer time scales (e.g., 50-100 strides). This relationship, known as fractal dynamics, is thought to represent the adaptive capacity of the locomotor system. However, this has not been tested empirically. Thus, the purpose of this study was to determine if stride time fractality during steady state walking associated with the ability of individuals to adapt their gait patterns when locomotor speed and symmetry are altered. Fifteen healthy adults walked on a split-belt treadmill at preferred speed, half of preferred speed, and with one leg at preferred speed and the other at half speed (2:1 ratio asymmetric walking). The asymmetric belt speed condition induced gait asymmetries that required adaptation of locomotor patterns. The slow speed manipulation was chosen in order to determine the impact of gait speed on stride time fractal dynamics. Detrended fluctuation analysis was used to quantify the correlation structure, i.e., fractality, of stride times. Cross-correlation analysis was used to measure the deviation from intended anti-phasing between legs as a measure of gait adaptation. Results revealed no association between unperturbed walking fractal dynamics and gait adaptability performance. However, there was a quadratic relationship between perturbed, asymmetric walking fractal dynamics and adaptive performance during split-belt walking, whereby individuals who exhibited fractal scaling exponents that deviated from 1/f performed the poorest. Compared to steady state preferred walking

Impact of learning adaptability and time management disposition on study engagement among Chinese baccalaureate nursing students.

PubMed

Liu, Jing-Ying; Liu, Yan-Hui; Yang, Ji-Peng

2014-01-01

The aim of this study was to explore the relationships among study engagement, learning adaptability, and time management disposition in a sample of Chinese baccalaureate nursing students. A convenient sample of 467 baccalaureate nursing students was surveyed in two universities in Tianjin, China. Students completed a questionnaire that included their demographic information, Chinese Utrecht Work Engagement Scale-Student Questionnaire, Learning Adaptability Scale, and Adolescence Time Management Disposition Scale. One-way analysis of variance tests were used to assess the relationship between certain characteristics of baccalaureate nursing students. Pearson correlation was performed to test the correlation among study engagement, learning adaptability, and time management disposition. Hierarchical linear regression analyses were performed to explore the mediating role of time management disposition. The results revealed that study engagement (F = 7.20, P < .01) and learning adaptability (F = 4.41, P < .01) differed across grade groups. Learning adaptability (r = 0.382, P < .01) and time management disposition (r = 0.741, P < .01) were positively related with study engagement. Time management disposition had a partially mediating effect on the relationship between study engagement and learning adaptability. The findings implicate that educators should not only promote interventions to increase engagement of baccalaureate nursing students but also focus on development, investment in adaptability, and time management. Copyright © 2014 Elsevier Inc. All rights reserved.

Adaptive vibration control of structures under earthquakes

NASA Astrophysics Data System (ADS)

Lew, Jiann-Shiun; Juang, Jer-Nan; Loh, Chin-Hsiung

2017-04-01

techniques, for structural vibration suppression under earthquakes. Various control strategies have been developed to protect structures from natural hazards and improve the comfort of occupants in buildings. However, there has been little development of adaptive building control with the integration of real-time system identification and control design. Generalized predictive control, which combines the process of real-time system identification and the process of predictive control design, has received widespread acceptance and has been successfully applied to various test-beds. This paper presents a formulation of the predictive control scheme for adaptive vibration control of structures under earthquakes. Comprehensive simulations are performed to demonstrate and validate the proposed adaptive control technique for earthquake-induced vibration of a building.

Adaption to extreme rainfall with open urban drainage system: an integrated hydrological cost-benefit analysis.

PubMed

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.

Adaption to Extreme Rainfall with Open Urban Drainage System: An Integrated Hydrological Cost-Benefit Analysis

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.

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.

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.

Conditional adaptive Bayesian spectral analysis of nonstationary biomedical time series.

PubMed

Bruce, Scott A; Hall, Martica H; Buysse, Daniel J; Krafty, Robert T

2018-03-01

Many studies of biomedical time series signals aim to measure the association between frequency-domain properties of time series and clinical and behavioral covariates. However, the time-varying dynamics of these associations are largely ignored due to a lack of methods that can assess the changing nature of the relationship through time. This article introduces a method for the simultaneous and automatic analysis of the association between the time-varying power spectrum and covariates, which we refer to as conditional adaptive Bayesian spectrum analysis (CABS). The procedure adaptively partitions the grid of time and covariate values into an unknown number of approximately stationary blocks and nonparametrically estimates local spectra within blocks through penalized splines. CABS is formulated in a fully Bayesian framework, in which the number and locations of partition points are random, and fit using reversible jump Markov chain Monte Carlo techniques. Estimation and inference averaged over the distribution of partitions allows for the accurate analysis of spectra with both smooth and abrupt changes. The proposed methodology is used to analyze the association between the time-varying spectrum of heart rate variability and self-reported sleep quality in a study of older adults serving as the primary caregiver for their ill spouse. © 2017, The International Biometric Society.

Adaptation of the phase of the human linear vestibulo-ocular reflex (LVOR) and effects on the oculomotor neural integrator

NASA Technical Reports Server (NTRS)

Hegemann, S.; Shelhamer, M.; Kramer, P. D.; Zee, D. S.

2000-01-01

The phase of the translational linear VOR (LVOR) can be adaptively modified by exposure to a visual-vestibular mismatch. We extend here our earlier work on LVOR phase adaptation, and discuss the role of the oculomotor neural integrator. Ten subjects were oscillated laterally at 0.5 Hz, 0.3 g peak acceleration, while sitting upright on a linear sled. LVOR was assessed before and after adaptation with subjects tracking the remembered location of a target at 1 m in the dark. Phase and gain were measured by fitting sine waves to the desaccaded eye movements, and comparing sled and eye position. To adapt LVOR phase, the subject viewed a computer-generated stereoscopic visual display, at a virtual distance of 1 m, that moved so as to require either a phase lead or a phase lag of 53 deg. Adaptation lasted 20 min, during which subjects were oscillated at 0.5 Hz/0.3 g. Four of five subjects produced an adaptive change in the lag condition (range 4-45 deg), and each of five produced a change in the lead condition (range 19-56 deg), as requested. Changes in drift on eccentric gaze suggest that the oculomotor velocity-to-position integrator may be involved in the phase changes.

Physical constraints on biological integral control design for homeostasis and sensory adaptation.

PubMed

Ang, Jordan; McMillen, David R

2013-01-22

Synthetic biology includes an effort to use design-based approaches to create novel controllers, biological systems aimed at regulating the output of other biological processes. The design of such controllers can be guided by results from control theory, including the strategy of integral feedback control, which is central to regulation, sensory adaptation, and long-term robustness. Realization of integral control in a synthetic network is an attractive prospect, but the nature of biochemical networks can make the implementation of even basic control structures challenging. Here we present a study of the general challenges and important constraints that will arise in efforts to engineer biological integral feedback controllers or to analyze existing natural systems. Constraints arise from the need to identify target output values that the combined process-plus-controller system can reach, and to ensure that the controller implements a good approximation of integral feedback control. These constraints depend on mild assumptions about the shape of input-output relationships in the biological components, and thus will apply to a variety of biochemical systems. We summarize our results as a set of variable constraints intended to provide guidance for the design or analysis of a working biological integral feedback controller. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.

An experimental study of wall adaptation and interference assessment using Cauchy integral formula

NASA Technical Reports Server (NTRS)

Murthy, A. V.

1991-01-01

This paper summarizes the results of an experimental study of combined wall adaptation and residual interference assessment using the Cauchy integral formula. The experiments were conducted on a supercritical airfoil model in the Langley 0.3-m Transonic Cryogenic Tunnel solid flexible wall test section. The ratio of model chord to test section height was about 0.7. The method worked satisfactorily in reducing the blockage interference and demonstrated the primary requirement for correcting for the blockage effects at high model incidences to correctly determine high lift characteristics. The studies show that the method has potential for reducing the residual interference to considerably low levels. However, corrections to blockage and upwash velocities gradients may still be required for the final adapted wall shapes.

Evolution of time-keeping mechanisms: early emergence and adaptation to photoperiod

PubMed Central

Hut, R. A.; Beersma, D. G. M.

2011-01-01

Virtually all species have developed cellular oscillations and mechanisms that synchronize these cellular oscillations to environmental cycles. Such environmental cycles in biotic (e.g. food availability and predation risk) or abiotic (e.g. temperature and light) factors may occur on a daily, annual or tidal time scale. Internal timing mechanisms may facilitate behavioural or physiological adaptation to such changes in environmental conditions. These timing mechanisms commonly involve an internal molecular oscillator (a ‘clock’) that is synchronized (‘entrained’) to the environmental cycle by receptor mechanisms responding to relevant environmental signals (‘Zeitgeber’, i.e. German for time-giver). To understand the evolution of such timing mechanisms, we have to understand the mechanisms leading to selective advantage. Although major advances have been made in our understanding of the physiological and molecular mechanisms driving internal cycles (proximate questions), studies identifying mechanisms of natural selection on clock systems (ultimate questions) are rather limited. Here, we discuss the selective advantage of a circadian system and how its adaptation to day length variation may have a functional role in optimizing seasonal timing. We discuss various cases where selective advantages of circadian timing mechanisms have been shown and cases where temporarily loss of circadian timing may cause selective advantage. We suggest an explanation for why a circadian timing system has emerged in primitive life forms like cyanobacteria and we evaluate a possible molecular mechanism that enabled these bacteria to adapt to seasonal variation in day length. We further discuss how the role of the circadian system in photoperiodic time measurement may explain differential selection pressures on circadian period when species are exposed to changing climatic conditions (e.g. global warming) or when they expand their geographical range to different latitudes or

Adaptive Neurotechnology for Making Neural Circuits Functional .

NASA Astrophysics Data System (ADS)

Jung, Ranu

2008-03-01

Two of the most important trends in recent technological developments are that technology is increasingly integrated with biological systems and that it is increasingly adaptive in its capabilities. Neuroprosthetic systems that provide lost sensorimotor function after a neural disability offer a platform to investigate this interplay between biological and engineered systems. Adaptive neurotechnology (hardware and software) could be designed to be biomimetic, guided by the physical and programmatic constraints observed in biological systems, and allow for real-time learning, stability, and error correction. An example will present biomimetic neural-network hardware that can be interfaced with the isolated spinal cord of a lower vertebrate to allow phase-locked real-time neural control. Another will present adaptive neural network control algorithms for functional electrical stimulation of the peripheral nervous system to provide desired movements of paralyzed limbs in rodents or people. Ultimately, the frontier lies in being able to utilize the adaptive neurotechnology to promote neuroplasticity in the living system on a long-time scale under co-adaptive conditions.

Adaptation and Integration of Permanent Immigrants Seminar (4th, Geneva, Switzerland, May 8-11, 1979).

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…

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.

Space-time mesh adaptation for solute transport in randomly heterogeneous porous media.

PubMed

Dell'Oca, Aronne; Porta, Giovanni Michele; Guadagnini, Alberto; Riva, Monica

2018-05-01

We assess the impact of an anisotropic space and time grid adaptation technique on our ability to solve numerically solute transport in heterogeneous porous media. Heterogeneity is characterized in terms of the spatial distribution of hydraulic conductivity, whose natural logarithm, Y, is treated as a second-order stationary random process. We consider nonreactive transport of dissolved chemicals to be governed by an Advection Dispersion Equation at the continuum scale. The flow field, which provides the advective component of transport, is obtained through the numerical solution of Darcy's law. A suitable recovery-based error estimator is analyzed to guide the adaptive discretization. We investigate two diverse strategies guiding the (space-time) anisotropic mesh adaptation. These are respectively grounded on the definition of the guiding error estimator through the spatial gradients of: (i) the concentration field only; (ii) both concentration and velocity components. We test the approach for two-dimensional computational scenarios with moderate and high levels of heterogeneity, the latter being expressed in terms of the variance of Y. As quantities of interest, we key our analysis towards the time evolution of section-averaged and point-wise solute breakthrough curves, second centered spatial moment of concentration, and scalar dissipation rate. As a reference against which we test our results, we consider corresponding solutions associated with uniform space-time grids whose level of refinement is established through a detailed convergence study. We find a satisfactory comparison between results for the adaptive methodologies and such reference solutions, our adaptive technique being associated with a markedly reduced computational cost. Comparison of the two adaptive strategies tested suggests that: (i) defining the error estimator relying solely on concentration fields yields some advantages in grasping the key features of solute transport taking place within

Issues in measure-preserving three dimensional flow integrators: Self-adjointness, reversibility, and non-uniform time stepping

DOE PAGES

Finn, John M.

2015-03-01

Properties of integration schemes for solenoidal fields in three dimensions are studied, with a focus on integrating magnetic field lines in a plasma using adaptive time stepping. It is shown that implicit midpoint (IM) and a scheme we call three-dimensional leapfrog (LF) can do a good job (in the sense of preserving KAM tori) of integrating fields that are reversible, or (for LF) have a 'special divergence-free' property. We review the notion of a self-adjoint scheme, showing that such schemes are at least second order accurate and can always be formed by composing an arbitrary scheme with its adjoint. Wemore » also review the concept of reversibility, showing that a reversible but not exactly volume-preserving scheme can lead to a fractal invariant measure in a chaotic region, although this property may not often be observable. We also show numerical results indicating that the IM and LF schemes can fail to preserve KAM tori when the reversibility property (and the SDF property for LF) of the field is broken. We discuss extensions to measure preserving flows, the integration of magnetic field lines in a plasma and the integration of rays for several plasma waves. The main new result of this paper relates to non-uniform time stepping for volume-preserving flows. We investigate two potential schemes, both based on the general method of Ref. [11], in which the flow is integrated in split time steps, each Hamiltonian in two dimensions. The first scheme is an extension of the method of extended phase space, a well-proven method of symplectic integration with non-uniform time steps. This method is found not to work, and an explanation is given. The second method investigated is a method based on transformation to canonical variables for the two split-step Hamiltonian systems. This method, which is related to the method of non-canonical generating functions of Ref. [35], appears to work very well.« less

Issues in measure-preserving three dimensional flow integrators: Self-adjointness, reversibility, and non-uniform time stepping

DOE Office of Scientific and Technical Information (OSTI.GOV)

Finn, John M., E-mail: finn@lanl.gov

2015-03-15

Properties of integration schemes for solenoidal fields in three dimensions are studied, with a focus on integrating magnetic field lines in a plasma using adaptive time stepping. It is shown that implicit midpoint (IM) and a scheme we call three-dimensional leapfrog (LF) can do a good job (in the sense of preserving KAM tori) of integrating fields that are reversible, or (for LF) have a “special divergence-free” (SDF) property. We review the notion of a self-adjoint scheme, showing that such schemes are at least second order accurate and can always be formed by composing an arbitrary scheme with its adjoint.more » We also review the concept of reversibility, showing that a reversible but not exactly volume-preserving scheme can lead to a fractal invariant measure in a chaotic region, although this property may not often be observable. We also show numerical results indicating that the IM and LF schemes can fail to preserve KAM tori when the reversibility property (and the SDF property for LF) of the field is broken. We discuss extensions to measure preserving flows, the integration of magnetic field lines in a plasma and the integration of rays for several plasma waves. The main new result of this paper relates to non-uniform time stepping for volume-preserving flows. We investigate two potential schemes, both based on the general method of Feng and Shang [Numer. Math. 71, 451 (1995)], in which the flow is integrated in split time steps, each Hamiltonian in two dimensions. The first scheme is an extension of the method of extended phase space, a well-proven method of symplectic integration with non-uniform time steps. This method is found not to work, and an explanation is given. The second method investigated is a method based on transformation to canonical variables for the two split-step Hamiltonian systems. This method, which is related to the method of non-canonical generating functions of Richardson and Finn [Plasma Phys. Controlled Fusion 54, 014004

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.

Model reference tracking control of an aircraft: a robust adaptive approach

NASA Astrophysics Data System (ADS)

Tanyer, Ilker; Tatlicioglu, Enver; Zergeroglu, Erkan

2017-05-01

This work presents the design and the corresponding analysis of a nonlinear robust adaptive controller for model reference tracking of an aircraft that has parametric uncertainties in its system matrices and additive state- and/or time-dependent nonlinear disturbance-like terms in its dynamics. Specifically, robust integral of the sign of the error feedback term and an adaptive term is fused with a proportional integral controller. Lyapunov-based stability analysis techniques are utilised to prove global asymptotic convergence of the output tracking error. Extensive numerical simulations are presented to illustrate the performance of the proposed robust adaptive controller.

Responding to climate change in New York State: the ClimAID integrated assessment for effective climate change adaptation in New York State. Final report.

PubMed

2011-12-01

Climate change is already beginning to affect New York State, and these impacts are projected to grow. At the same time, the state has the ability to develop adaptation strategies to prepare for and respond to climate risks now and in the future. The ClimAID assessment provides information on climate change impacts and adaptation for eight sectors in New York State: water resources, coastal zones, ecosystems, agriculture, energy, transportation,telecommunications, and public health. Observed climate trends and future climate projections were developed for seven regions across the state. Within each of the sectors, climate risks, vulnerabilities, and adaptation strategies are identified. Integrating themes across all of the sectors are equity and environmental justice and economics.Case studies are used to examine specific vulnerabilities and potential adaptation strategies in each of the eight sectors. These case studies also illustrate the linkages among climate vulnerabilities, risks, and adaptation, and demonstrate specific monitoring needs. Stakeholder participation was critical to the ClimAID assessment process to ensure relevance to decision makers across the state.

Adaptive tracking of a time-varying field with a quantum sensor

NASA Astrophysics Data System (ADS)

Bonato, Cristian; Berry, Dominic W.

2017-05-01

Sensors based on single spins can enable magnetic-field detection with very high sensitivity and spatial resolution. Previous work has concentrated on sensing of a constant magnetic field or a periodic signal. Here, we instead investigate the problem of estimating a field with nonperiodic variation described by a Wiener process. We propose and study, by numerical simulations, an adaptive tracking protocol based on Bayesian estimation. The tracking protocol updates the probability distribution for the magnetic field based on measurement outcomes and adapts the choice of sensing time and phase in real time. By taking the statistical properties of the signal into account, our protocol strongly reduces the required measurement time. This leads to a reduction of the error in the estimation of a time-varying signal by up to a factor of four compare with protocols that do not take this information into account.

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 a...

A CMOS merged CDR and continuous-time adaptive equalizer

NASA Astrophysics Data System (ADS)

Sánchez-Azqueta, C.; Aguirre, J.; Gimeno, C.; Aldea, C.; Celma, S.

2015-06-01

We present a low-voltage merged CDR and cntinuous-time adaptive equalizer capable to compensate the attenu- ation of a SI-POF channel while at the same time synchronizing and regenerating the incoming signal in a single stage. The system operates at 1.25 Gbps for NRZ modulation through a 50-m SI-POF channel and it is designed in standard 0.18-μm CMOS fed at 1 V with a power consumption of 43.4 mW.

Status of the GTC adaptive optics: integration in laboratory

NASA Astrophysics Data System (ADS)

Reyes García-Talavera, M.; Béjar, V. J. S.; López, J. C.; López, R. L.; Martín, C.; Martín, Y.; Montilla, I.; Núñez, M.; Puga, M.; Rodríguez, L. F.; Tenegi, F.; Tubío, O.; Bello, D.; Cavaller, L.; Prieto, G.; Rosado, M.

2016-07-01

Since the beginning of the development of the Gran Telescopio Canarias (GTC), an Adaptive Optics (AO) system was considered necessary to exploit the full diffraction-limited potential of the telescope. The GTC AO system designed during the last years is based on a single deformable mirror conjugated to the telescope pupil, and a Shack-Hartmann wavefront sensor with 20 x 20 subapertures, using an OCAM2 camera. The GTCAO system will provide a corrected beam with a Strehl Ratio (SR) of 0.65 in K-band with bright natural guide stars. Most of the subsystems have been manufactured and delivered. The upgrade for the operation with a Laser Guide Star (LGS) system has been recently approved. The present status of the GTCAO system, currently in its laboratory integration phase, is summarized in this paper.

Artisticc: An Art and Science Integration Project to Enquire into Community Level Adaptation to Climate Change

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

A numerical study of adaptive space and time discretisations for Gross–Pitaevskii equations

PubMed Central

Thalhammer, Mechthild; Abhau, Jochen

2012-01-01

As a basic principle, benefits of adaptive discretisations are an improved balance between required accuracy and efficiency as well as an enhancement of the reliability of numerical computations. In this work, the capacity of locally adaptive space and time discretisations for the numerical solution of low-dimensional nonlinear Schrödinger equations is investigated. The considered model equation is related to the time-dependent Gross–Pitaevskii equation arising in the description of Bose–Einstein condensates in dilute gases. The performance of the Fourier-pseudo spectral method constrained to uniform meshes versus the locally adaptive finite element method and of higher-order exponential operator splitting methods with variable time stepsizes is studied. Numerical experiments confirm that a local time stepsize control based on a posteriori local error estimators or embedded splitting pairs, respectively, is effective in different situations with an enhancement either in efficiency or reliability. As expected, adaptive time-splitting schemes combined with fast Fourier transform techniques are favourable regarding accuracy and efficiency when applied to Gross–Pitaevskii equations with a defocusing nonlinearity and a mildly varying regular solution. However, the numerical solution of nonlinear Schrödinger equations in the semi-classical regime becomes a demanding task. Due to the highly oscillatory and nonlinear nature of the problem, the spatial mesh size and the time increments need to be of the size of the decisive parameter 0<ε≪1, especially when it is desired to capture correctly the quantitative behaviour of the wave function itself. The required high resolution in space constricts the feasibility of numerical computations for both, the Fourier pseudo-spectral and the finite element method. Nevertheless, for smaller parameter values locally adaptive time discretisations facilitate to determine the time stepsizes sufficiently small in order that the

A numerical study of adaptive space and time discretisations for Gross-Pitaevskii equations.

PubMed

Thalhammer, Mechthild; Abhau, Jochen

2012-08-15

As a basic principle, benefits of adaptive discretisations are an improved balance between required accuracy and efficiency as well as an enhancement of the reliability of numerical computations. In this work, the capacity of locally adaptive space and time discretisations for the numerical solution of low-dimensional nonlinear Schrödinger equations is investigated. The considered model equation is related to the time-dependent Gross-Pitaevskii equation arising in the description of Bose-Einstein condensates in dilute gases. The performance of the Fourier-pseudo spectral method constrained to uniform meshes versus the locally adaptive finite element method and of higher-order exponential operator splitting methods with variable time stepsizes is studied. Numerical experiments confirm that a local time stepsize control based on a posteriori local error estimators or embedded splitting pairs, respectively, is effective in different situations with an enhancement either in efficiency or reliability. As expected, adaptive time-splitting schemes combined with fast Fourier transform techniques are favourable regarding accuracy and efficiency when applied to Gross-Pitaevskii equations with a defocusing nonlinearity and a mildly varying regular solution. However, the numerical solution of nonlinear Schrödinger equations in the semi-classical regime becomes a demanding task. Due to the highly oscillatory and nonlinear nature of the problem, the spatial mesh size and the time increments need to be of the size of the decisive parameter [Formula: see text], especially when it is desired to capture correctly the quantitative behaviour of the wave function itself. The required high resolution in space constricts the feasibility of numerical computations for both, the Fourier pseudo-spectral and the finite element method. Nevertheless, for smaller parameter values locally adaptive time discretisations facilitate to determine the time stepsizes sufficiently small in order that

Alertness Modulates Conflict Adaptation and Feature Integration in an Opposite Way

PubMed Central

Chen, Jia; Huang, Xiting; Chen, Antao

2013-01-01

Previous studies show that the congruency sequence effect can result from both the conflict adaptation effect (CAE) and feature integration effect which can be observed as the repetition priming effect (RPE) and feature overlap effect (FOE) depending on different experimental conditions. Evidence from neuroimaging studies suggests that a close correlation exists between the neural mechanisms of alertness-related modulations and the congruency sequence effect. However, little is known about whether and how alertness mediates the congruency sequence effect. In Experiment 1, the Attentional Networks Test (ANT) and a modified flanker task were used to evaluate whether the alertness of the attentional functions had a correlation with the CAE and RPE. In Experimental 2, the ANT and another modified flanker task were used to investigate whether alertness of the attentional functions correlate with the CAE and FOE. In Experiment 1, through the correlative analysis, we found a significant positive correlation between alertness and the CAE, and a negative correlation between the alertness and the RPE. Moreover, a significant negative correlation existed between CAE and RPE. In Experiment 2, we found a marginally significant negative correlation between the CAE and the RPE, but the correlation between alertness and FOE, CAE and FOE was not significant. These results suggest that alertness can modulate conflict adaptation and feature integration in an opposite way. Participants at the high alerting level group may tend to use the top-down cognitive processing strategy, whereas participants at the low alerting level group tend to use the bottom-up processing strategy. PMID:24250824

Analysing a Chinese Regional Integrated Healthcare Organisation Reform Failure using a Complex Adaptive System Approach.

PubMed

Tang, Wenxi; Wei, Lai; Zhang, Liang

2017-06-19

China's organised health system has remained outdated for decades. Current health systems in many less market-oriented countries still adhere to traditional administrative-based directives and linear planning. Furthermore, they neglect the responsiveness and feedback of institutions and professionals, which often results in reform failure in integrated care. Complex adaptive system theory (CAS) provides a new perspective and methodology for analysing the health system and policy implementation. We observed the typical case of Qianjiang's Integrated Health Organization Reform (IHO) for 2 years to analyse integrated care reforms using CAS theory. Via questionnaires and interviews, we observed 32 medical institutions and 344 professionals. We compared their cooperative behaviours from both organisational and inter-professional levels between 2013 and 2015, and further investigated potential reasons for why medical institutions and professionals did not form an effective IHO. We discovered how interested parties in the policy implementation process influenced reform outcome, and by theoretical induction, proposed a new semi-organised system and corresponding policy analysis flowchart that potentially suits the actual realisation of CAS. The reform did not achieve its desired effect. The Qianjiang IHO was loosely integrated rather than closely integrated, and the cooperation levels between organisations and professionals were low. This disappointing result was due to low mutual trust among IHO members, with the main contributing factors being insufficient financial incentives and the lack of a common vision. The traditional organised health system is old-fashioned. Rather than being completely organised or adaptive, the health system is currently more similar to a semi-organised syste m. Medical institutions and professionals operate in a middle ground between complete adherence to administrative orders from state-run health systems and completely adapting to the market

Analysing a Chinese Regional Integrated Healthcare Organisation Reform Failure using a Complex Adaptive System Approach

PubMed Central

Wei, Lai; Zhang, Liang

2017-01-01

Introduction: China’s organised health system has remained outdated for decades. Current health systems in many less market-oriented countries still adhere to traditional administrative-based directives and linear planning. Furthermore, they neglect the responsiveness and feedback of institutions and professionals, which often results in reform failure in integrated care. Complex adaptive system theory (CAS) provides a new perspective and methodology for analysing the health system and policy implementation. Methods: We observed the typical case of Qianjiang’s Integrated Health Organization Reform (IHO) for 2 years to analyse integrated care reforms using CAS theory. Via questionnaires and interviews, we observed 32 medical institutions and 344 professionals. We compared their cooperative behaviours from both organisational and inter-professional levels between 2013 and 2015, and further investigated potential reasons for why medical institutions and professionals did not form an effective IHO. We discovered how interested parties in the policy implementation process influenced reform outcome, and by theoretical induction, proposed a new semi-organised system and corresponding policy analysis flowchart that potentially suits the actual realisation of CAS. Results: The reform did not achieve its desired effect. The Qianjiang IHO was loosely integrated rather than closely integrated, and the cooperation levels between organisations and professionals were low. This disappointing result was due to low mutual trust among IHO members, with the main contributing factors being insufficient financial incentives and the lack of a common vision. Discussion and Conclusions: The traditional organised health system is old-fashioned. Rather than being completely organised or adaptive, the health system is currently more similar to a semi-organised system. Medical institutions and professionals operate in a middle ground between complete adherence to administrative orders from

A long time low drift integrator with temperature control

NASA Astrophysics Data System (ADS)

Zhang, Donglai; Yan, Xiaolan; Zhang, Enchao; Pan, Shimin

2016-10-01

The output of an operational amplifier always contains signals that could not have been predicted, even with knowledge of the input and an accurately determined closed-loop transfer function. These signals lead to integrator zero-drift over time. A new type of integrator system with a long-term low-drift characteristic has therefore been designed. The integrator system is composed of a temperature control module and an integrator module. The aluminum printed circuit board of the integrator is glued to a thermoelectric cooler to maintain the electronic components at a stable temperature. The integration drift is automatically compensated using an analog-to-digital converter/proportional integration/digital-to-analog converter control circuit. Performance testing in a standard magnet shows that the proposed integrator, which has an integration time constant of 10 ms, has a low integration drift (<5 mV) over 1000 s after repeated measurements. The integrator can be used for magnetic flux measurements in most tokamaks and in the wire rope nondestructive test.

A long time low drift integrator with temperature control.

PubMed

Zhang, Donglai; Yan, Xiaolan; Zhang, Enchao; Pan, Shimin

2016-10-01

The output of an operational amplifier always contains signals that could not have been predicted, even with knowledge of the input and an accurately determined closed-loop transfer function. These signals lead to integrator zero-drift over time. A new type of integrator system with a long-term low-drift characteristic has therefore been designed. The integrator system is composed of a temperature control module and an integrator module. The aluminum printed circuit board of the integrator is glued to a thermoelectric cooler to maintain the electronic components at a stable temperature. The integration drift is automatically compensated using an analog-to-digital converter/proportional integration/digital-to-analog converter control circuit. Performance testing in a standard magnet shows that the proposed integrator, which has an integration time constant of 10 ms, has a low integration drift (<5 mV) over 1000 s after repeated measurements. The integrator can be used for magnetic flux measurements in most tokamaks and in the wire rope nondestructive test.

Blood Pressure Regulation: Every Adaptation is an Integration?

PubMed Central

Joyner, Michael J.; Limberg, Jacqueline K.

2013-01-01

This focused review serves to explore relevant issues in regard to blood pressure regulation and by doing so, provides the initial stimulus paper for the Thematic Review series “Blood Pressure Regulation” to be published in the European Journal of Applied Physiology over the coming months. In this introduction, we highlight how variable normal blood pressure can be and challenge the reader to take another look at some key concepts related to blood pressure regulation. We point out that there is frequently an underappreciated balance between peripheral vasodilation and systemic blood pressure regulation and ask the question: Are changes in blood pressure, in effect, reasonable and integrated adaptations to the physiological challenge at hand? We conclude with the idea that blood pressure regulatory systems are both flexible and redundant; ensuring a wide variety of activities associated with life can be accompanied by a perfusion pressure that can serve multiple masters. PMID:23558925

Feature integration across space, time, and orientation

PubMed Central

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

Application of real-time machine learning to myoelectric prosthesis control: A case series in adaptive switching.

PubMed

Edwards, Ann L; Dawson, Michael R; Hebert, Jacqueline S; Sherstan, Craig; Sutton, Richard S; Chan, K Ming; Pilarski, Patrick M

2016-10-01

Myoelectric prostheses currently used by amputees can be difficult to control. Machine learning, and in particular learned predictions about user intent, could help to reduce the time and cognitive load required by amputees while operating their prosthetic device. The goal of this study was to compare two switching-based methods of controlling a myoelectric arm: non-adaptive (or conventional) control and adaptive control (involving real-time prediction learning). Case series study. We compared non-adaptive and adaptive control in two different experiments. In the first, one amputee and one non-amputee subject controlled a robotic arm to perform a simple task; in the second, three able-bodied subjects controlled a robotic arm to perform a more complex task. For both tasks, we calculated the mean time and total number of switches between robotic arm functions over three trials. Adaptive control significantly decreased the number of switches and total switching time for both tasks compared with the conventional control method. Real-time prediction learning was successfully used to improve the control interface of a myoelectric robotic arm during uninterrupted use by an amputee subject and able-bodied subjects. Adaptive control using real-time prediction learning has the potential to help decrease both the time and the cognitive load required by amputees in real-world functional situations when using myoelectric prostheses. © The International Society for Prosthetics and Orthotics 2015.

Transit light curves with finite integration time: Fisher information analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

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 curvemore » 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.« less

Hippocampal “Time Cells”: Time versus Path Integration

PubMed Central

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

Performance optimization of PM-16QAM transmission system enabled by real-time self-adaptive coding.

PubMed

Qu, Zhen; Li, Yao; Mo, Weiyang; Yang, Mingwei; Zhu, Shengxiang; Kilper, Daniel C; Djordjevic, Ivan B

2017-10-15

We experimentally demonstrate self-adaptive coded 5×100  Gb/s WDM polarization multiplexed 16 quadrature amplitude modulation transmission over a 100 km fiber link, which is enabled by a real-time control plane. The real-time optical signal-to-noise ratio (OSNR) is measured using an optical performance monitoring device. The OSNR measurement is processed and fed back using control plane logic and messaging to the transmitter side for code adaptation, where the binary data are adaptively encoded with three types of low-density parity-check (LDPC) codes with code rates of 0.8, 0.75, and 0.7 of large girth. The total code-adaptation latency is measured to be 2273 ms. Compared with transmission without adaptation, average net capacity improvements of 102%, 36%, and 7.5% are obtained, respectively, by adaptive LDPC coding.

Software Testbed for Developing and Evaluating Integrated Autonomous Subsystems

NASA Technical Reports Server (NTRS)

Ong, James; Remolina, Emilio; Prompt, Axel; Robinson, Peter; Sweet, Adam; Nishikawa, David

2015-01-01

To implement fault tolerant autonomy in future space systems, it will be necessary to integrate planning, adaptive control, and state estimation subsystems. However, integrating these subsystems is difficult, time-consuming, and error-prone. This paper describes Intelliface/ADAPT, a software testbed that helps researchers develop and test alternative strategies for integrating planning, execution, and diagnosis subsystems more quickly and easily. The testbed's architecture, graphical data displays, and implementations of the integrated subsystems support easy plug and play of alternate components to support research and development in fault-tolerant control of autonomous vehicles and operations support systems. Intelliface/ADAPT controls NASA's Advanced Diagnostics and Prognostics Testbed (ADAPT), which comprises batteries, electrical loads (fans, pumps, and lights), relays, circuit breakers, invertors, and sensors. During plan execution, an experimentor can inject faults into the ADAPT testbed by tripping circuit breakers, changing fan speed settings, and closing valves to restrict fluid flow. The diagnostic subsystem, based on NASA's Hybrid Diagnosis Engine (HyDE), detects and isolates these faults to determine the new state of the plant, ADAPT. Intelliface/ADAPT then updates its model of the ADAPT system's resources and determines whether the current plan can be executed using the reduced resources. If not, the planning subsystem generates a new plan that reschedules tasks, reconfigures ADAPT, and reassigns the use of ADAPT resources as needed to work around the fault. The resource model, planning domain model, and planning goals are expressed using NASA's Action Notation Modeling Language (ANML). Parts of the ANML model are generated automatically, and other parts are constructed by hand using the Planning Model Integrated Development Environment, a visual Eclipse-based IDE that accelerates ANML model development. Because native ANML planners are currently

Adaptation and learning: characteristic time scales of performance dynamics.

PubMed

Newell, Karl M; Mayer-Kress, Gottfried; Hong, S Lee; Liu, Yeou-Teh

2009-12-01

A multiple time scales landscape model is presented that reveals structures of performance dynamics that were not resolved in the traditional power law analysis of motor learning. It shows the co-existence of separate processes during and between practice sessions that evolve in two independent dimensions characterized by time scales that differ by about an order of magnitude. Performance along the slow persistent dimension of learning improves often as much and sometimes more during rest (memory consolidation and/or insight generation processes) than during a practice session itself. In contrast, the process characterized by the fast, transient dimension of adaptation reverses direction between practice sessions, thereby significantly degrading performance at the beginning of the next practice session (warm-up decrement). The theoretical model fits qualitatively and quantitatively the data from Snoddy's [Snoddy, G. S. (1926). Learning and stability. Journal of Applied Psychology, 10, 1-36] classic learning study of mirror tracing and other averaged and individual data sets, and provides a new account of the processes of change in adaptation and learning. 2009 Elsevier B.V. All rights reserved.

Real-Time Adaptive Control of Flow-Induced Cavity Tones

NASA Technical Reports Server (NTRS)

Kegerise, Michael A.; Cabell, Randolph H.; Cattafesta, Louis N.

2004-01-01

An adaptive generalized predictive control (GPC) algorithm was formulated and applied to the cavity flow-tone problem. The algorithm employs gradient descent to update the GPC coefficients at each time step. The adaptive control algorithm demonstrated multiple Rossiter mode suppression at fixed Mach numbers ranging from 0.275 to 0.38. The algorithm was also able t o maintain suppression of multiple cavity tones as the freestream Mach number was varied over a modest range (0.275 to 0.29). Controller performance was evaluated with a measure of output disturbance rejection and an input sensitivity transfer function. The results suggest that disturbances entering the cavity flow are colocated with the control input at the cavity leading edge. In that case, only tonal components of the cavity wall-pressure fluctuations can be suppressed and arbitrary broadband pressure reduction is not possible. In the control-algorithm development, the cavity dynamics are treated as linear and time invariant (LTI) for a fixed Mach number. The experimental results lend support this treatment.

GENERIC Integrators: Structure Preserving Time Integration for Thermodynamic Systems

NASA Astrophysics Data System (ADS)

Öttinger, Hans Christian

2018-04-01

Thermodynamically admissible evolution equations for non-equilibrium systems are known to possess a distinct mathematical structure. Within the GENERIC (general equation for the non-equilibrium reversible-irreversible coupling) framework of non-equilibrium thermodynamics, which is based on continuous time evolution, we investigate the possibility of preserving all the structural elements in time-discretized equations. Our approach, which follows Moser's [1] construction of symplectic integrators for Hamiltonian systems, is illustrated for the damped harmonic oscillator. Alternative approaches are sketched.

Adaptive neural control for a class of nonlinear time-varying delay systems with unknown hysteresis.

PubMed

Liu, Zhi; Lai, Guanyu; Zhang, Yun; Chen, Xin; Chen, Chun Lung Philip

2014-12-01

This paper investigates the fusion of unknown direction hysteresis model with adaptive neural control techniques in face of time-delayed continuous time nonlinear systems without strict-feedback form. Compared with previous works on the hysteresis phenomenon, the direction of the modified Bouc-Wen hysteresis model investigated in the literature is unknown. To reduce the computation burden in adaptation mechanism, an optimized adaptation method is successfully applied to the control design. Based on the Lyapunov-Krasovskii method, two neural-network-based adaptive control algorithms are constructed to guarantee that all the system states and adaptive parameters remain bounded, and the tracking error converges to an adjustable neighborhood of the origin. In final, some numerical examples are provided to validate the effectiveness of the proposed control methods.

Adaptive HIFU noise cancellation for simultaneous therapy and imaging using an integrated HIFU/imaging transducer

PubMed Central

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

Adaptive HIFU noise cancellation for simultaneous therapy and imaging using an integrated HIFU/imaging transducer.

PubMed

Jeong, Jong Seob; Cannata, Jonathan Matthew; Shung, K Kirk

2010-04-07

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

From dinosaurs to modern bird diversity: extending the time scale of adaptive radiation.

PubMed

Moen, Daniel; Morlon, Hélène

2014-05-01

What explains why some groups of organisms, like birds, are so species rich? And what explains their extraordinary ecological diversity, ranging from large, flightless birds to small migratory species that fly thousand of kilometers every year? These and similar questions have spurred great interest in adaptive radiation, the diversification of ecological traits in a rapidly speciating group of organisms. Although the initial formulation of modern concepts of adaptive radiation arose from consideration of the fossil record, rigorous attempts to identify adaptive radiation in the fossil record are still uncommon. Moreover, most studies of adaptive radiation concern groups that are less than 50 million years old. Thus, it is unclear how important adaptive radiation is over temporal scales that span much larger portions of the history of life. In this issue, Benson et al. test the idea of a "deep-time" adaptive radiation in dinosaurs, compiling and using one of the most comprehensive phylogenetic and body-size datasets for fossils. Using recent phylogenetic statistical methods, they find that in most clades of dinosaurs there is a strong signal of an "early burst" in body-size evolution, a predicted pattern of adaptive radiation in which rapid trait evolution happens early in a group's history and then slows down. They also find that body-size evolution did not slow down in the lineage leading to birds, hinting at why birds survived to the present day and diversified. This paper represents one of the most convincing attempts at understanding deep-time adaptive radiations.

Alpha: A real-time decentralized operating system for mission-oriented system integration and operation

NASA Technical Reports Server (NTRS)

Jensen, E. Douglas

1988-01-01

Alpha is a new kind of operating system that is unique in two highly significant ways. First, it is decentralized transparently providing reliable resource management across physically dispersed nodes, so that distributed applications programming can be done largely as though it were centralized. And second, it provides comprehensive, high technology support for real-time system integration and operation, an application area which consists predominately of aperiodic activities having critical time constraints such as deadlines. Alpha is extremely adaptable so that it can be easily optimized for a wide range of problem-specific functionality, performance, and cost. Alpha is the first systems effort of the Archons Project, and the prototype was created at Carnegie-Mellon University directly on modified Sun multiprocessor workstation hardware. It has been demonstrated with a real-time C(sup 2) application. Continuing research is leading to a series of enhanced follow-ons to Alpha; these are portable but initially hosted on Concurrent's MASSCOMP line of multiprocessor products.

Adaptive multiresolution modeling of groundwater flow in heterogeneous porous media

NASA Astrophysics Data System (ADS)

Malenica, Luka; Gotovac, Hrvoje; Srzic, Veljko; Andric, Ivo

2016-04-01

Proposed methodology was originally developed by our scientific team in Split who designed multiresolution approach for analyzing flow and transport processes in highly heterogeneous porous media. The main properties of the adaptive Fup multi-resolution approach are: 1) computational capabilities of Fup basis functions with compact support capable to resolve all spatial and temporal scales, 2) multi-resolution presentation of heterogeneity as well as all other input and output variables, 3) accurate, adaptive and efficient strategy and 4) semi-analytical properties which increase our understanding of usually complex flow and transport processes in porous media. The main computational idea behind this approach is to separately find the minimum number of basis functions and resolution levels necessary to describe each flow and transport variable with the desired accuracy on a particular adaptive grid. Therefore, each variable is separately analyzed, and the adaptive and multi-scale nature of the methodology enables not only computational efficiency and accuracy, but it also describes subsurface processes closely related to their understood physical interpretation. The methodology inherently supports a mesh-free procedure, avoiding the classical numerical integration, and yields continuous velocity and flux fields, which is vitally important for flow and transport simulations. In this paper, we will show recent improvements within the proposed methodology. Since "state of the art" multiresolution approach usually uses method of lines and only spatial adaptive procedure, temporal approximation was rarely considered as a multiscale. Therefore, novel adaptive implicit Fup integration scheme is developed, resolving all time scales within each global time step. It means that algorithm uses smaller time steps only in lines where solution changes are intensive. Application of Fup basis functions enables continuous time approximation, simple interpolation calculations across

Adaptive integral backstepping sliding mode control for opto-electronic tracking system based on modified LuGre friction model

NASA Astrophysics Data System (ADS)

Yue, Fengfa; Li, Xingfei; Chen, Cheng; Tan, Wenbin

2017-12-01

In order to improve the control accuracy and stability of opto-electronic tracking system fixed on reef or airport under friction and external disturbance conditions, adaptive integral backstepping sliding mode control approach with friction compensation is developed to achieve accurate and stable tracking for fast moving target. The nonlinear observer and slide mode controller based on modified LuGre model with friction compensation can effectively reduce the influence of nonlinear friction and disturbance of this servo system. The stability of the closed-loop system is guaranteed by Lyapunov theory. The steady-state error of the system is eliminated by integral action. The adaptive integral backstepping sliding mode controller and its performance are validated by a nonlinear modified LuGre dynamic model of the opto-electronic tracking system in simulation and practical experiments. The experiment results demonstrate that the proposed controller can effectively realise the accuracy and stability control of opto-electronic tracking system.

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

PubMed

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

2014-05-01

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

Time-integrated directional detection of dark matter

NASA Astrophysics Data System (ADS)

O'Hare, Ciaran A. J.; Kavanagh, Bradley J.; Green, Anne M.

2017-10-01

The analysis of signals in directional dark matter (DM) detectors typically assumes that the directions of nuclear recoils can be measured in the Galactic rest frame. However, this is not possible with all directional detection technologies. In nuclear emulsions, for example, the recoil events must be detected and measured after the exposure time of the experiment. Unless the entire detector is mounted and rotated with the sidereal day, the recoils cannot be reoriented in the Galactic rest frame. We examine the effect of this "time integration" on the primary goals of directional detection, namely: (1) confirming that the recoils are anisotropic; (2) measuring the median recoil direction to confirm their Galactic origin; and (3) probing below the neutrino floor. We show that after time integration the DM recoil distribution retains a preferred direction and is distinct from that of Solar neutrino-induced recoils. Many of the advantages of directional detection are therefore preserved and it is not crucial to mount and rotate the detector. Rejecting isotropic backgrounds requires a factor of 2 more signal events compared with an experiment with event time information, whereas a factor of 1.5-3 more events are needed to measure a median direction in agreement with the expectation for DM. We also find that there is still effectively no neutrino floor in a time-integrated directional experiment. However to reach a cross section an order of magnitude below the floor, a factor of ˜8 larger exposure is required than with a conventional directional experiment. We also examine how the sensitivity is affected for detectors with only 2D recoil track readout, and/or no head-tail measurement. As for non-time-integrated experiments, 2D readout is not a major disadvantage, though a lack of head-tail sensitivity is.

A video-based real-time adaptive vehicle-counting system for urban roads.

PubMed

Liu, Fei; Zeng, Zhiyuan; Jiang, Rong

2017-01-01

In developing nations, many expanding cities are facing challenges that result from the overwhelming numbers of people and vehicles. Collecting real-time, reliable and precise traffic flow information is crucial for urban traffic management. The main purpose of this paper is to develop an adaptive model that can assess the real-time vehicle counts on urban roads using computer vision technologies. This paper proposes an automatic real-time background update algorithm for vehicle detection and an adaptive pattern for vehicle counting based on the virtual loop and detection line methods. In addition, a new robust detection method is introduced to monitor the real-time traffic congestion state of road section. A prototype system has been developed and installed on an urban road for testing. The results show that the system is robust, with a real-time counting accuracy exceeding 99% in most field scenarios.

A video-based real-time adaptive vehicle-counting system for urban roads

PubMed Central

2017-01-01

In developing nations, many expanding cities are facing challenges that result from the overwhelming numbers of people and vehicles. Collecting real-time, reliable and precise traffic flow information is crucial for urban traffic management. The main purpose of this paper is to develop an adaptive model that can assess the real-time vehicle counts on urban roads using computer vision technologies. This paper proposes an automatic real-time background update algorithm for vehicle detection and an adaptive pattern for vehicle counting based on the virtual loop and detection line methods. In addition, a new robust detection method is introduced to monitor the real-time traffic congestion state of road section. A prototype system has been developed and installed on an urban road for testing. The results show that the system is robust, with a real-time counting accuracy exceeding 99% in most field scenarios. PMID:29135984

Cross-cultural adaptation of research instruments: language, setting, time and statistical considerations.

PubMed

Gjersing, Linn; Caplehorn, John R M; Clausen, Thomas

2010-02-10

Research questionnaires are not always translated appropriately before they are used in new temporal, cultural or linguistic settings. The results based on such instruments may therefore not accurately reflect what they are supposed to measure. This paper aims to illustrate the process and required steps involved in the cross-cultural adaptation of a research instrument using the adaptation process of an attitudinal instrument as an example. A questionnaire was needed for the implementation of a study in Norway 2007. There was no appropriate instruments available in Norwegian, thus an Australian-English instrument was cross-culturally adapted. The adaptation process included investigation of conceptual and item equivalence. Two forward and two back-translations were synthesized and compared by an expert committee. Thereafter the instrument was pretested and adjusted accordingly. The final questionnaire was administered to opioid maintenance treatment staff (n=140) and harm reduction staff (n=180). The overall response rate was 84%. The original instrument failed confirmatory analysis. Instead a new two-factor scale was identified and found valid in the new setting. The failure of the original scale highlights the importance of adapting instruments to current research settings. It also emphasizes the importance of ensuring that concepts within an instrument are equal between the original and target language, time and context. If the described stages in the cross-cultural adaptation process had been omitted, the findings would have been misleading, even if presented with apparent precision. Thus, it is important to consider possible barriers when making a direct comparison between different nations, cultures and times.

Channel Noise-Enhanced Synchronization Transitions Induced by Time Delay in Adaptive Neuronal Networks with Spike-Timing-Dependent Plasticity

NASA Astrophysics Data System (ADS)

Xie, Huijuan; Gong, Yubing; Wang, Baoying

In this paper, we numerically study the effect of channel noise on synchronization transitions induced by time delay in adaptive scale-free Hodgkin-Huxley neuronal networks with spike-timing-dependent plasticity (STDP). It is found that synchronization transitions by time delay vary as channel noise intensity is changed and become most pronounced when channel noise intensity is optimal. This phenomenon depends on STDP and network average degree, and it can be either enhanced or suppressed as network average degree increases depending on channel noise intensity. These results show that there are optimal channel noise and network average degree that can enhance the synchronization transitions by time delay in the adaptive neuronal networks. These findings could be helpful for better understanding of the regulation effect of channel noise on synchronization of neuronal networks. They could find potential implications for information transmission in neural systems.

Photorefractive Integrators and Correlators

DTIC Science & Technology

1992-12-01

The use of photorefractive crystals as optically addressed time integrating spatial light modulators in acousto - optic signal processing applications...adaptive acousto - optic processor. These results demonstrated the feasibility of using photorefractives for such applications.... Photorefractive, Acousto - optic processor.

Time step rescaling recovers continuous-time dynamical properties for discrete-time Langevin integration of nonequilibrium systems.

PubMed

Sivak, David A; Chodera, John D; Crooks, Gavin E

2014-06-19

When simulating molecular systems using deterministic equations of motion (e.g., Newtonian dynamics), such equations are generally numerically integrated according to a well-developed set of algorithms that share commonly agreed-upon desirable properties. However, for stochastic equations of motion (e.g., Langevin dynamics), there is still broad disagreement over which integration algorithms are most appropriate. While multiple desiderata have been proposed throughout the literature, consensus on which criteria are important is absent, and no published integration scheme satisfies all desiderata simultaneously. Additional nontrivial complications stem from simulating systems driven out of equilibrium using existing stochastic integration schemes in conjunction with recently developed nonequilibrium fluctuation theorems. Here, we examine a family of discrete time integration schemes for Langevin dynamics, assessing how each member satisfies a variety of desiderata that have been enumerated in prior efforts to construct suitable Langevin integrators. We show that the incorporation of a novel time step rescaling in the deterministic updates of position and velocity can correct a number of dynamical defects in these integrators. Finally, we identify a particular splitting (related to the velocity Verlet discretization) that has essentially universally appropriate properties for the simulation of Langevin dynamics for molecular systems in equilibrium, nonequilibrium, and path sampling contexts.

Rapid and highly integrated FPGA-based Shack-Hartmann wavefront sensor for adaptive optics system

NASA Astrophysics Data System (ADS)

Chen, Yi-Pin; Chang, Chia-Yuan; Chen, Shean-Jen

2018-02-01

In this study, a field programmable gate array (FPGA)-based Shack-Hartmann wavefront sensor (SHWS) programmed on LabVIEW can be highly integrated into customized applications such as adaptive optics system (AOS) for performing real-time wavefront measurement. Further, a Camera Link frame grabber embedded with FPGA is adopted to enhance the sensor speed reacting to variation considering its advantage of the highest data transmission bandwidth. Instead of waiting for a frame image to be captured by the FPGA, the Shack-Hartmann algorithm are implemented in parallel processing blocks design and let the image data transmission synchronize with the wavefront reconstruction. On the other hand, we design a mechanism to control the deformable mirror in the same FPGA and verify the Shack-Hartmann sensor speed by controlling the frequency of the deformable mirror dynamic surface deformation. Currently, this FPGAbead SHWS design can achieve a 266 Hz cyclic speed limited by the camera frame rate as well as leaves 40% logic slices for additionally flexible design.

Verification and Validation Methodology of Real-Time Adaptive Neural Networks for Aerospace Applications

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.

Multirate Particle-in-Cell Time Integration Techniques of Vlasov-Maxwell Equations for Collisionless Kinetic Plasma Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Guangye; Chacon, Luis; Knoll, Dana Alan

2015-07-31

A multi-rate PIC formulation was developed that employs large timesteps for slow field evolution, and small (adaptive) timesteps for particle orbit integrations. Implementation is based on a JFNK solver with nonlinear elimination and moment preconditioning. The approach is free of numerical instabilities (ω peΔt >>1, and Δx >> λ D), and requires many fewer dofs (vs. explicit PIC) for comparable accuracy in challenging problems. Significant gains (vs. conventional explicit PIC) may be possible for large scale simulations. The paper is organized as follows: Vlasov-Maxwell Particle-in-cell (PIC) methods for plasmas; Explicit, semi-implicit, and implicit time integrations; Implicit PIC formulation (Jacobian-Free Newton-Krylovmore » (JFNK) with nonlinear elimination allows different treatments of disparate scales, discrete conservation properties (energy, charge, canonical momentum, etc.)); Some numerical examples; and Summary.« less

Advanced time integration algorithms for dislocation dynamics simulations of work hardening

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sills, Ryan B.; Aghaei, Amin; Cai, Wei

Efficient time integration is a necessity for dislocation dynamics simulations of work hardening to achieve experimentally relevant strains. In this work, an efficient time integration scheme using a high order explicit method with time step subcycling and a newly-developed collision detection algorithm are evaluated. First, time integrator performance is examined for an annihilating Frank–Read source, showing the effects of dislocation line collision. The integrator with subcycling is found to significantly out-perform other integration schemes. The performance of the time integration and collision detection algorithms is then tested in a work hardening simulation. The new algorithms show a 100-fold speed-up relativemore » to traditional schemes. As a result, subcycling is shown to improve efficiency significantly while maintaining an accurate solution, and the new collision algorithm allows an arbitrarily large time step size without missing collisions.« less

Advanced time integration algorithms for dislocation dynamics simulations of work hardening

DOE PAGES

Sills, Ryan B.; Aghaei, Amin; Cai, Wei

2016-04-25

Efficient time integration is a necessity for dislocation dynamics simulations of work hardening to achieve experimentally relevant strains. In this work, an efficient time integration scheme using a high order explicit method with time step subcycling and a newly-developed collision detection algorithm are evaluated. First, time integrator performance is examined for an annihilating Frank–Read source, showing the effects of dislocation line collision. The integrator with subcycling is found to significantly out-perform other integration schemes. The performance of the time integration and collision detection algorithms is then tested in a work hardening simulation. The new algorithms show a 100-fold speed-up relativemore » to traditional schemes. As a result, subcycling is shown to improve efficiency significantly while maintaining an accurate solution, and the new collision algorithm allows an arbitrarily large time step size without missing collisions.« less

Incorporating immigrants: integrating theoretical frameworks of adaptation.

PubMed

Treas, Judith

2015-03-01

To encourage research on immigrants and aging by analyzing theoretical commonalities in the two fields and identifying potential contributions of aging theories, specifically to the understanding of neglected age differences in the pace of immigrant incorporation. Survey of the historical development of assimilation theory and its successors and systematic comparison of key concepts in aging and immigrant incorporation theories. Studies of immigrants, as well as of the life course, trace their origins to the Chicago School at the turn of the 20th century. Today, both theoretical perspectives emphasize adaptation as a time-dependent, multidimensional, nonlinear, and multidirectional process. Immigrant incorporation theories have not fully engaged with a key concern of aging theory-why there are age differences. Insights from cognitive aging and developmental biology, life-span developmental psychology, and age stratification and the life course suggest explanations for age differences in the speed of immigrant incorporation. Theories of adaptation to aging and theories of immigrant incorporation developed so independently that they neglected the subject they have in common, namely, older immigrants. Because they address similar conceptual problems and share key assumptions, a productive dialogue between two vibrant fields is long overdue. © The Author 2014. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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.

The Role of Identity Integration in Hedonic Adaptation to a Beneficial Life Change: The Example of "Coming Out" for Lesbians and Gay Men.

PubMed

Coulombe, Simon; de la Sablonnière, Roxane

2015-01-01

After apparently beneficial life changes, people are expected to experience elevated well-being. However, research suggests that some individuals adapt quickly to change, so their well-being increases little in the long-term. We propose this phenomenon is explained by the integration of the changes into identity, in interaction with perceived valence of the changes. We hypothesized that higher integration would be associated with smaller increases in well-being for changes perceived as positive. For changes perceived as negative, higher integration would be associated with larger increases in well-being. Lesbians and gay men (N = 80) completed a questionnaire on well-being, perceived valence of coming out and its integration into identity. Moderated regressions supported the hypotheses, revealing the importance of considering identity integration and perceived valence in research on adaptation to changes. The results question the merits of interventions promoting identity integration.

Adaptation of Chinese Graduate Students to the Academic Integrity Requirements of a U.S. University: A Mixed Methods Research

ERIC Educational Resources Information Center

Jian, Hu

2012-01-01

The purpose of this mixed method study was to investigate how graduates originating from mainland China adapt to the U.S. academic integrity requirements. In the first, quantitative phase of the study, the research questions focused on understanding the state of academic integrity in China. This guiding question was divided into two sub-questions,…

A robust data fusion scheme for integrated navigation systems employing fault detection methodology augmented with fuzzy adaptive filtering

NASA Astrophysics Data System (ADS)

Ushaq, Muhammad; Fang, Jiancheng

2013-10-01

Integrated navigation systems for various applications, generally employs the centralized Kalman filter (CKF) wherein all measured sensor data are communicated to a single central Kalman filter. The advantage of CKF is that there is a minimal loss of information and high precision under benign conditions. But CKF may suffer computational overloading, and poor fault tolerance. The alternative is the federated Kalman filter (FKF) wherein the local estimates can deliver optimal or suboptimal state estimate as per certain information fusion criterion. FKF has enhanced throughput and multiple level fault detection capability. The Standard CKF or FKF require that the system noise and the measurement noise are zero-mean and Gaussian. Moreover it is assumed that covariance of system and measurement noises remain constant. But if the theoretical and actual statistical features employed in Kalman filter are not compatible, the Kalman filter does not render satisfactory solutions and divergence problems also occur. To resolve such problems, in this paper, an adaptive Kalman filter scheme strengthened with fuzzy inference system (FIS) is employed to adapt the statistical features of contributing sensors, online, in the light of real system dynamics and varying measurement noises. The excessive faults are detected and isolated by employing Chi Square test method. As a case study, the presented scheme has been implemented on Strapdown Inertial Navigation System (SINS) integrated with the Celestial Navigation System (CNS), GPS and Doppler radar using FKF. Collectively the overall system can be termed as SINS/CNS/GPS/Doppler integrated navigation system. The simulation results have validated the effectiveness of the presented scheme with significantly enhanced precision, reliability and fault tolerance. Effectiveness of the scheme has been tested against simulated abnormal errors/noises during different time segments of flight. It is believed that the presented scheme can be

Asian International Students at an Australian University: Mapping the Paths between Integrative Motivation, Competence in L2 Communication, Cross-Cultural Adaptation and Persistence with Structural Equation Modelling

ERIC Educational Resources Information Center

Yu, Baohua

2013-01-01

This study examined the interrelationships of integrative motivation, competence in second language (L2) communication, sociocultural adaptation, academic adaptation and persistence of international students at an Australian university. Structural equation modelling demonstrated that the integrative motivation of international students has a…

Adaptive Actor-Critic Design-Based Integral Sliding-Mode Control for Partially Unknown Nonlinear Systems With Input Disturbances.

PubMed

Fan, Quan-Yong; Yang, Guang-Hong

2016-01-01

This paper is concerned with the problem of integral sliding-mode control for a class of nonlinear systems with input disturbances and unknown nonlinear terms through the adaptive actor-critic (AC) control method. The main objective is to design a sliding-mode control methodology based on the adaptive dynamic programming (ADP) method, so that the closed-loop system with time-varying disturbances is stable and the nearly optimal performance of the sliding-mode dynamics can be guaranteed. In the first step, a neural network (NN)-based observer and a disturbance observer are designed to approximate the unknown nonlinear terms and estimate the input disturbances, respectively. Based on the NN approximations and disturbance estimations, the discontinuous part of the sliding-mode control is constructed to eliminate the effect of the disturbances and attain the expected equivalent sliding-mode dynamics. Then, the ADP method with AC structure is presented to learn the optimal control for the sliding-mode dynamics online. Reconstructed tuning laws are developed to guarantee the stability of the sliding-mode dynamics and the convergence of the weights of critic and actor NNs. Finally, the simulation results are presented to illustrate the effectiveness of the proposed method.

Real-Time Robust Adaptive Modeling and Scheduling for an Electronic Commerce Server

NASA Astrophysics Data System (ADS)

Du, Bing; Ruan, Chun

With the increasing importance and pervasiveness of Internet services, it is becoming a challenge for the proliferation of electronic commerce services to provide performance guarantees under extreme overload. This paper describes a real-time optimization modeling and scheduling approach for performance guarantee of electronic commerce servers. We show that an electronic commerce server may be simulated as a multi-tank system. A robust adaptive server model is subject to unknown additive load disturbances and uncertain model matching. Overload control techniques are based on adaptive admission control to achieve timing guarantees. We evaluate the performance of the model using a complex simulation that is subjected to varying model parameters and massive overload.

Effects of Differentially Time-Consuming Tests on Computer-Adaptive Test Scores

ERIC Educational Resources Information Center

Bridgeman, Brent; Cline, Frederick

2004-01-01

Time limits on some computer-adaptive tests (CATs) are such that many examinees have difficulty finishing, and some examinees may be administered tests with more time-consuming items than others. Results from over 100,000 examinees suggested that about half of the examinees must guess on the final six questions of the analytical section of the…

Acculturation Strategy, Integration Paradoxes and Educational Adaptation--A Case Study of Chinese Visiting Scholar's Family in the United States

ERIC Educational Resources Information Center

Weidong, Li; Chen, Sisi

2017-01-01

In this case study, we developed a theoretical framework for examining the relationship between acculturation strategy and educational adaptation. By interviews and observations of one Chinese visiting scholar's family in the United States, we found that the family utilized "integration" as the acculturation strategy to adapt to the US…

Prediction of adaptation difficulties by country of origin, cumulate psychosocial stressors and attitude toward integrating: A Swedish study of first-generation immigrants from Somalia, Vietnam and China

PubMed Central

Zolkowska, Krystyna; McNeil, Thomas F

2015-01-01

Background: Different types of accumulated stress have been found to have negative consequences for immigrants’ capacity to adapt to the new environment. It remains unclear which factors have the greatest influence. Aims: The study investigated whether immigrants’ experience of great difficulty in adapting to a new country could best be explained by (1) country of origin, (2) exposure to accumulated stressors before arrival or (3) after arrival in the new country and/or (4) reserved attitude toward integrating into the new society. Methods: The 119 first-generation immigrants from Somalia, Vietnam and China, living in Malmö, Sweden, were interviewed in a standardized manner. Results: Experiencing great difficulty in adapting to Sweden was independent of length of residence, but significantly related to all four influences, studied one at a time. Country of origin was also related to stressors and attitude. When the effects of the other influences were mutually controlled for, only exposure to accumulated stressors in Sweden (and especially experiencing discrimination/xenophobia/racism) accounted for great adaptation difficulty. Stressors in Sweden had a greater effect if the immigrant had been exposed to stressors earlier. Conclusions: Immigrants’ long-term experiences of great difficulty in adapting to a new country were explained primarily by exposure to accumulated stressors while moving to and living in the new country, rather than by their backgrounds or attitudes toward integrating. This suggests promoting strategies to avoid discrimination and other stressors in the host country. PMID:24927925

Prediction of adaptation difficulties by country of origin, cumulate psychosocial stressors and attitude toward integrating: a Swedish study of first-generation immigrants from Somalia, Vietnam and China.

PubMed

Johnsson, Ewa; Zolkowska, Krystyna; McNeil, Thomas F

2015-03-01

Different types of accumulated stress have been found to have negative consequences for immigrants' capacity to adapt to the new environment. It remains unclear which factors have the greatest influence. The study investigated whether immigrants' experience of great difficulty in adapting to a new country could best be explained by (1) country of origin, (2) exposure to accumulated stressors before arrival or (3) after arrival in the new country and/or (4) reserved attitude toward integrating into the new society. The 119 first-generation immigrants from Somalia, Vietnam and China, living in Malmö, Sweden, were interviewed in a standardized manner. Experiencing great difficulty in adapting to Sweden was independent of length of residence, but significantly related to all four influences, studied one at a time. Country of origin was also related to stressors and attitude. When the effects of the other influences were mutually controlled for, only exposure to accumulated stressors in Sweden (and especially experiencing discrimination/xenophobia/racism) accounted for great adaptation difficulty. Stressors in Sweden had a greater effect if the immigrant had been exposed to stressors earlier. Immigrants' long-term experiences of great difficulty in adapting to a new country were explained primarily by exposure to accumulated stressors while moving to and living in the new country, rather than by their backgrounds or attitudes toward integrating. This suggests promoting strategies to avoid discrimination and other stressors in the host country. © The Author(s) 2014.

An Adaptive INS-Aided PLL Tracking Method for GNSS Receivers in Harsh Environments.

PubMed

Cong, Li; Li, Xin; Jin, Tian; Yue, Song; Xue, Rui

2016-01-23

As the weak link in global navigation satellite system (GNSS) signal processing, the phase-locked loop (PLL) is easily influenced with frequent cycle slips and loss of lock as a result of higher vehicle dynamics and lower signal-to-noise ratios. With inertial navigation system (INS) aid, PLLs' tracking performance can be improved. However, for harsh environments with high dynamics and signal attenuation, the traditional INS-aided PLL with fixed loop parameters has some limitations to improve the tracking adaptability. In this paper, an adaptive INS-aided PLL capable of adjusting its noise bandwidth and coherent integration time has been proposed. Through theoretical analysis, the relation between INS-aided PLL phase tracking error and carrier to noise density ratio (C/N₀), vehicle dynamics, aiding information update time, noise bandwidth, and coherent integration time has been built. The relation formulae are used to choose the optimal integration time and bandwidth for a given application under the minimum tracking error criterion. Software and hardware simulation results verify the correctness of the theoretical analysis, and demonstrate that the adaptive tracking method can effectively improve the PLL tracking ability and integrated GNSS/INS navigation performance. For harsh environments, the tracking sensitivity is increased by 3 to 5 dB, velocity errors are decreased by 36% to 50% and position errors are decreased by 6% to 24% when compared with other INS-aided PLL methods.

Adaptive NN Control Using Integral Barrier Lyapunov Functionals for Uncertain Nonlinear Block-Triangular Constraint Systems.

PubMed

Liu, Yan-Jun; Tong, Shaocheng; Chen, C L Philip; Li, Dong-Juan

2017-11-01

A neural network (NN) adaptive control design problem is addressed for a class of uncertain multi-input-multi-output (MIMO) nonlinear systems in block-triangular form. The considered systems contain uncertainty dynamics and their states are enforced to subject to bounded constraints as well as the couplings among various inputs and outputs are inserted in each subsystem. To stabilize this class of systems, a novel adaptive control strategy is constructively framed by using the backstepping design technique and NNs. The novel integral barrier Lyapunov functionals (BLFs) are employed to overcome the violation of the full state constraints. The proposed strategy can not only guarantee the boundedness of the closed-loop system and the outputs are driven to follow the reference signals, but also can ensure all the states to remain in the predefined compact sets. Moreover, the transformed constraints on the errors are used in the previous BLF, and accordingly it is required to determine clearly the bounds of the virtual controllers. Thus, it can relax the conservative limitations in the traditional BLF-based controls for the full state constraints. This conservatism can be solved in this paper and it is for the first time to control this class of MIMO systems with the full state constraints. The performance of the proposed control strategy can be verified through a simulation example.

Adaptive iterative learning control of a class of nonlinear time-delay systems with unknown backlash-like hysteresis input and control direction.

PubMed

Wei, Jianming; Zhang, Youan; Sun, Meimei; Geng, Baoliang

2017-09-01

This paper presents an adaptive iterative learning control scheme for a class of nonlinear systems with unknown time-varying delays and control direction preceded by unknown nonlinear backlash-like hysteresis. Boundary layer function is introduced to construct an auxiliary error variable, which relaxes the identical initial condition assumption of iterative learning control. For the controller design, integral Lyapunov function candidate is used, which avoids the possible singularity problem by introducing hyperbolic tangent funciton. After compensating for uncertainties with time-varying delays by combining appropriate Lyapunov-Krasovskii function with Young's inequality, an adaptive iterative learning control scheme is designed through neural approximation technique and Nussbaum function method. On the basis of the hyperbolic tangent function's characteristics, the system output is proved to converge to a small neighborhood of the desired trajectory by constructing Lyapunov-like composite energy function (CEF) in two cases, while keeping all the closed-loop signals bounded. Finally, a simulation example is presented to verify the effectiveness of the proposed approach. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

A model of interval timing by neural integration.

PubMed

Simen, Patrick; Balci, Fuat; de Souza, Laura; Cohen, Jonathan D; Holmes, Philip

2011-06-22

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.

A model of interval timing by neural integration

PubMed Central

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

Adaptive and Adaptable Automation Design: A Critical Review of the Literature and Recommendations for Future Research

NASA Technical Reports Server (NTRS)

Prinzel, Lawrence J., III; Kaber, David B.

2006-01-01

This report presents a review of literature on approaches to adaptive and adaptable task/function allocation and adaptive interface technologies for effective human management of complex systems that are likely to be issues for the Next Generation Air Transportation System, and a focus of research under the Aviation Safety Program, Integrated Intelligent Flight Deck Project. Contemporary literature retrieved from an online database search is summarized and integrated. The major topics include the effects of delegation-type, adaptable automation on human performance, workload and situation awareness, the effectiveness of various automation invocation philosophies and strategies to function allocation in adaptive systems, and the role of user modeling in adaptive interface design and the performance implications of adaptive interface technology.

Exact subthreshold integration with continuous spike times in discrete-time neural network simulations.

PubMed

Morrison, Abigail; Straube, Sirko; Plesser, Hans Ekkehard; Diesmann, Markus

2007-01-01

Very large networks of spiking neurons can be simulated efficiently in parallel under the constraint that spike times are bound to an equidistant time grid. Within this scheme, the subthreshold dynamics of a wide class of integrate-and-fire-type neuron models can be integrated exactly from one grid point to the next. However, the loss in accuracy caused by restricting spike times to the grid can have undesirable consequences, which has led to interest in interpolating spike times between the grid points to retrieve an adequate representation of network dynamics. We demonstrate that the exact integration scheme can be combined naturally with off-grid spike events found by interpolation. We show that by exploiting the existence of a minimal synaptic propagation delay, the need for a central event queue is removed, so that the precision of event-driven simulation on the level of single neurons is combined with the efficiency of time-driven global scheduling. Further, for neuron models with linear subthreshold dynamics, even local event queuing can be avoided, resulting in much greater efficiency on the single-neuron level. These ideas are exemplified by two implementations of a widely used neuron model. We present a measure for the efficiency of network simulations in terms of their integration error and show that for a wide range of input spike rates, the novel techniques we present are both more accurate and faster than standard techniques.

Weekly Time Course of Neuro-Muscular Adaptation to Intensive Strength Training.

PubMed

Brown, Niklas; Bubeck, Dieter; Haeufle, Daniel F B; Weickenmeier, Johannes; Kuhl, Ellen; Alt, Wilfried; Schmitt, Syn

2017-01-01

Detailed description of the time course of muscular adaptation is rarely found in literature. Thus, models of muscular adaptation are difficult to validate since no detailed data of adaptation are available. In this article, as an initial step toward a detailed description and analysis of muscular adaptation, we provide a case report of 8 weeks of intense strength training with two active, male participants. Muscular adaptations were analyzed on a morphological level with MRI scans of the right quadriceps muscle and the calculation of muscle volume, on a voluntary strength level by isometric voluntary contractions with doublet stimulation (interpolated twitch technique) and on a non-voluntary level by resting twitch torques. Further, training volume and isokinetic power were closely monitored during the training phase. Data were analyzed weekly for 1 week prior to training, pre-training, 8 weeks of training and 2 weeks of detraining (no strength training). Results show a very individual adaptation to the intense strength training protocol. While training volume and isokinetic power increased linearly during the training phase, resting twitch parameters decreased for both participants after the first week of training and stayed below baseline until de-training. Voluntary activation level showed an increase in the first 4 weeks of training, while maximum voluntary contraction showed only little increase compared to baseline. Muscle volume increased for both subjects. Especially training status seemed to influence the acute reaction to intense strength training. Fatigue had a major influence on performance and could only be overcome by one participant. The results give a first detailed insight into muscular adaptation to intense strength training on various levels, providing a basis of data for a validation of muscle fatigue and adaptation models.

Diversity and disparity through time in the adaptive radiation of Antarctic notothenioid fishes.

PubMed

Colombo, M; Damerau, M; Hanel, R; Salzburger, W; Matschiner, M

2015-02-01

According to theory, adaptive radiation is triggered by ecological opportunity that can arise through the colonization of new habitats, the extinction of antagonists or the origin of key innovations. In the course of an adaptive radiation, diversification and morphological evolution are expected to slow down after an initial phase of rapid adaptation to vacant ecological niches, followed by speciation. Such 'early bursts' of diversification are thought to occur because niche space becomes increasingly filled over time. The diversification of Antarctic notothenioid fishes into over 120 species has become one of the prime examples of adaptive radiation in the marine realm and has likely been triggered by an evolutionary key innovation in the form of the emergence of antifreeze glycoproteins. Here, we test, using a novel time-calibrated phylogeny of 49 species and five traits that characterize notothenioid body size and shape as well as buoyancy adaptations and habitat preferences, whether the notothenioid adaptive radiation is compatible with an early burst scenario. Extensive Bayesian model comparison shows that phylogenetic age estimates are highly dependent on model choice and that models with unlinked gene trees are generally better supported and result in younger age estimates. We find strong evidence for elevated diversification rates in Antarctic notothenioids compared to outgroups, yet no sign of rate heterogeneity in the course of the radiation, except that the notothenioid family Artedidraconidae appears to show secondarily elevated diversification rates. We further observe an early burst in trophic morphology, suggesting that the notothenioid radiation proceeds in stages similar to other prominent examples of adaptive radiation. © 2014 The Authors. Journal of Evolutionary Biology published by John Wiley & Sons Ltd on behalf of European Society for Evolutionary Biology.

Linear servomotor probe drive system with real-time self-adaptive position control for the Alcator C-Mod tokamak

NASA Astrophysics Data System (ADS)

Brunner, D.; Kuang, A. Q.; LaBombard, B.; Burke, W.

2017-07-01

A new servomotor drive system has been developed for the horizontal reciprocating probe on the Alcator C-Mod tokamak. Real-time measurements of plasma temperature and density—through use of a mirror Langmuir probe bias system—combined with a commercial linear servomotor and controller enable self-adaptive position control. Probe surface temperature and its rate of change are computed in real time and used to control probe insertion depth. It is found that a universal trigger threshold can be defined in terms of these two parameters; if the probe is triggered to retract when crossing the trigger threshold, it will reach the same ultimate surface temperature, independent of velocity, acceleration, or scrape-off layer heat flux scale length. In addition to controlling the probe motion, the controller is used to monitor and control all aspects of the integrated probe drive system.

The genomic basis of circadian and circalunar timing adaptations in a midge.

PubMed

Kaiser, Tobias S; Poehn, Birgit; Szkiba, David; Preussner, Marco; Sedlazeck, Fritz J; Zrim, Alexander; Neumann, Tobias; Nguyen, Lam-Tung; Betancourt, Andrea J; Hummel, Thomas; Vogel, Heiko; Dorner, Silke; Heyd, Florian; von Haeseler, Arndt; Tessmar-Raible, Kristin

2016-12-01

Organisms use endogenous clocks to anticipate regular environmental cycles, such as days and tides. Natural variants resulting in differently timed behaviour or physiology, known as chronotypes in humans, have not been well characterized at the molecular level. We sequenced the genome of Clunio marinus, a marine midge whose reproduction is timed by circadian and circalunar clocks. Midges from different locations show strain-specific genetic timing adaptations. We examined genetic variation in five C. marinus strains from different locations and mapped quantitative trait loci for circalunar and circadian chronotypes. The region most strongly associated with circadian chronotypes generates strain-specific differences in the abundance of calcium/calmodulin-dependent kinase II.1 (CaMKII.1) splice variants. As equivalent variants were shown to alter CaMKII activity in Drosophila melanogaster, and C. marinus (Cma)-CaMKII.1 increases the transcriptional activity of the dimer of the circadian proteins Cma-CLOCK and Cma-CYCLE, we suggest that modulation of alternative splicing is a mechanism for natural adaptation in circadian timing.

Highly integrated digital electronic control: Digital flight control, aircraft model identification, and adaptive engine control

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 SDR-Based Real-Time Testbed for GNSS Adaptive Array Anti-Jamming Algorithms Accelerated by GPU.

PubMed

Xu, Hailong; Cui, Xiaowei; Lu, Mingquan

2016-03-11

Nowadays, software-defined radio (SDR) has become a common approach to evaluate new algorithms. However, in the field of Global Navigation Satellite System (GNSS) adaptive array anti-jamming, previous work has been limited due to the high computational power demanded by adaptive algorithms, and often lack flexibility and configurability. In this paper, the design and implementation of an SDR-based real-time testbed for GNSS adaptive array anti-jamming accelerated by a Graphics Processing Unit (GPU) are documented. This testbed highlights itself as a feature-rich and extendible platform with great flexibility and configurability, as well as high computational performance. Both Space-Time Adaptive Processing (STAP) and Space-Frequency Adaptive Processing (SFAP) are implemented with a wide range of parameters. Raw data from as many as eight antenna elements can be processed in real-time in either an adaptive nulling or beamforming mode. To fully take advantage of the parallelism resource provided by the GPU, a batched method in programming is proposed. Tests and experiments are conducted to evaluate both the computational and anti-jamming performance. This platform can be used for research and prototyping, as well as a real product in certain applications.

An SDR-Based Real-Time Testbed for GNSS Adaptive Array Anti-Jamming Algorithms Accelerated by GPU

PubMed Central

Xu, Hailong; Cui, Xiaowei; Lu, Mingquan

2016-01-01

Nowadays, software-defined radio (SDR) has become a common approach to evaluate new algorithms. However, in the field of Global Navigation Satellite System (GNSS) adaptive array anti-jamming, previous work has been limited due to the high computational power demanded by adaptive algorithms, and often lack flexibility and configurability. In this paper, the design and implementation of an SDR-based real-time testbed for GNSS adaptive array anti-jamming accelerated by a Graphics Processing Unit (GPU) are documented. This testbed highlights itself as a feature-rich and extendible platform with great flexibility and configurability, as well as high computational performance. Both Space-Time Adaptive Processing (STAP) and Space-Frequency Adaptive Processing (SFAP) are implemented with a wide range of parameters. Raw data from as many as eight antenna elements can be processed in real-time in either an adaptive nulling or beamforming mode. To fully take advantage of the parallelism resource provided by the GPU, a batched method in programming is proposed. Tests and experiments are conducted to evaluate both the computational and anti-jamming performance. This platform can be used for research and prototyping, as well as a real product in certain applications. PMID:26978363

Adaptive sliding mode control for finite-time stability of quad-rotor UAVs with parametric uncertainties.

PubMed

Mofid, Omid; Mobayen, Saleh

2018-01-01

Adaptive control methods are developed for stability and tracking control of flight systems in the presence of parametric uncertainties. This paper offers a design technique of adaptive sliding mode control (ASMC) for finite-time stabilization of unmanned aerial vehicle (UAV) systems with parametric uncertainties. Applying the Lyapunov stability concept and finite-time convergence idea, the recommended control method guarantees that the states of the quad-rotor UAV are converged to the origin with a finite-time convergence rate. Furthermore, an adaptive-tuning scheme is advised to guesstimate the unknown parameters of the quad-rotor UAV at any moment. Finally, simulation results are presented to exhibit the helpfulness of the offered technique compared to the previous methods. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Controlled Aeroelastic Response and Airfoil Shaping Using Adaptive Materials and Integrated Systems

NASA Technical Reports Server (NTRS)

Pinkerton, Jennifer L.; McGowan, Anna-Maria R.; Moses, Robert W.; Scott, Robert C.; Heeg, Jennifer

1996-01-01

This paper presents an overview of several activities of the Aeroelasticity Branch at the NASA Langley Research Center in the area of applying adaptive materials and integrated systems for controlling both aircraft aeroelastic response and airfoil shape. The experimental results of four programs are discussed: the Piezoelectric Aeroelastic Response Tailoring Investigation (PARTI); the Adaptive Neural Control of Aeroelastic Response (ANCAR) program; the Actively Controlled Response of Buffet Affected Tails (ACROBAT) program; and the Airfoil THUNDER Testing to Ascertain Characteristics (ATTACH) project. The PARTI program demonstrated active flutter control and significant rcductions in aeroelastic response at dynamic pressures below flutter using piezoelectric actuators. The ANCAR program seeks to demonstrate the effectiveness of using neural networks to schedule flutter suppression control laws. Th,e ACROBAT program studied the effectiveness of a number of candidate actuators, including a rudder and piezoelectric actuators, to alleviate vertical tail buffeting. In the ATTACH project, the feasibility of using Thin-Layer Composite-Uimorph Piezoelectric Driver and Sensor (THUNDER) wafers to control airfoil aerodynamic characteristics was investigated. Plans for future applications are also discussed.

Time-Lapse Measurement of Wellbore Integrity

NASA Astrophysics Data System (ADS)

Duguid, A.

2017-12-01

Well integrity is becoming more important as wells are used longer or repurposed. For CO2, shale gas, and other projects it has become apparent that wells represent the most likely unintended migration pathway for fluids out of the reservoir. Comprehensive logging programs have been employed to determine the condition of legacy wells in North America. These studies provide examples of assessment technologies. Logging programs have included pulsed neutron logging, ultrasonic well mapping, and cement bond logging. While these studies provide examples of what can be measured, they have only conducted a single round of logging and cannot show if the well has changed over time. Recent experience with time-lapse logging of three monitoring wells at a US Department of Energy sponsored CO2 project has shown the full value of similar tools. Time-lapse logging has shown that well integrity changes over time can be identified. It has also shown that the inclusion of and location of monitoring technologies in the well and the choice of construction materials must be carefully considered. Two of the wells were approximately eight years old at the time of study; they were constructed with steel and fiberglass casing sections and had lines on the outside of the casing running to the surface. The third well was 68 years old when it was studied and was originally constructed as a production well. Repeat logs were collected six or eight years after initial logging. Time-lapse logging showed the evolution of the wells. The results identified locations where cement degraded over time and locations that showed little change. The ultrasonic well maps show clearly that the lines used to connect the monitoring technology to the surface are visible and have a local effect on cement isolation. Testing and sampling was conducted along with logging. It provided insight into changes identified in the time-lapse log results. Point permeability testing was used to provide an in-situ point

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.

Robust control for a biaxial servo with time delay system based on adaptive tuning technique.

PubMed

Chen, Tien-Chi; Yu, Chih-Hsien

2009-07-01

A robust control method for synchronizing a biaxial servo system motion is proposed in this paper. A new network based cross-coupled control and adaptive tuning techniques are used together to cancel out the skew error. The conventional fixed gain PID cross-coupled controller (CCC) is replaced with the adaptive cross-coupled controller (ACCC) in the proposed control scheme to maintain biaxial servo system synchronization motion. Adaptive-tuning PID (APID) position and velocity controllers provide the necessary control actions to maintain synchronization while following a variable command trajectory. A delay-time compensator (DTC) with an adaptive controller was augmented to set the time delay element, effectively moving it outside the closed loop, enhancing the stability of the robust controlled system. This scheme provides strong robustness with respect to uncertain dynamics and disturbances. The simulation and experimental results reveal that the proposed control structure adapts to a wide range of operating conditions and provides promising results under parameter variations and load changes.

A novel adaptive finite time controller for bilateral teleoperation system

NASA Astrophysics Data System (ADS)

Wang, Ziwei; Chen, Zhang; Liang, Bin; Zhang, Bo

2018-03-01

Most bilateral teleoperation researches focus on the system stability within time-delays. However, practical teleoperation tasks require high performances besides system stability, such as convergence rate and accuracy. This paper investigates bilateral teleoperation controller design with transient performances. To ensure the transient performances and system stability simultaneously, an adaptive non-singular fast terminal mode controller is proposed to achieve practical finite-time stability considering system uncertainties and time delays. In addition, a novel switching scheme is introduced, in which way the singularity problem of conventional terminal sliding manifold is avoided. Finally, numerical simulations demonstrate the effectiveness and validity of the proposed method.

Heating in Integrable Time-Periodic Systems

NASA Astrophysics Data System (ADS)

Ishii, Takashi; Kuwahara, Tomotaka; Mori, Takashi; Hatano, Naomichi

2018-06-01

We investigate a heating phenomenon in periodically driven integrable systems that can be mapped to free-fermion models. We find that heating to the high-temperature state, which is a typical scenario in nonintegrable systems, can also appear in integrable time-periodic systems; the amount of energy absorption rises drastically near a frequency threshold where the Floquet-Magnus expansion diverges. As the driving period increases, we also observe that the effective temperatures of the generalized Gibbs ensemble for conserved quantities go to infinity. By the use of the scaling analysis, we reveal that, in the limit of infinite system size and driving period, the steady state after a long time is equivalent to the infinite-temperature state. We obtain the asymptotic behavior L-1 and T-2 as to how the steady state approaches the infinite-temperature state as the system size L and the driving period T increase.

Implementation and Evaluation of Multiple Adaptive Control Technologies for a Generic Transport Aircraft Simulation

NASA Technical Reports Server (NTRS)

Campbell, Stefan F.; Kaneshige, John T.; Nguyen, Nhan T.; Krishakumar, Kalmanje S.

2010-01-01

Presented here is the evaluation of multiple adaptive control technologies for a generic transport aircraft simulation. For this study, seven model reference adaptive control (MRAC) based technologies were considered. Each technology was integrated into an identical dynamic-inversion control architecture and tuned using a methodology based on metrics and specific design requirements. Simulation tests were then performed to evaluate each technology s sensitivity to time-delay, flight condition, model uncertainty, and artificially induced cross-coupling. The resulting robustness and performance characteristics were used to identify potential strengths, weaknesses, and integration challenges of the individual adaptive control technologies

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 Numerical Algorithms in Space Weather Modeling

NASA Technical Reports Server (NTRS)

Toth, Gabor; vanderHolst, Bart; Sokolov, Igor V.; DeZeeuw, Darren; Gombosi, Tamas I.; Fang, Fang; Manchester, Ward B.; Meng, Xing; Nakib, Dalal; Powell, Kenneth G.;

Real-time real-sky dual-conjugate adaptive optics experiment

NASA Astrophysics Data System (ADS)

Knutsson, Per; Owner-Petersen, Mette

2006-06-01

The current status of a real-time real-sky dual-conjugate adaptive optics experiment is presented. This experiment is a follow-up on a lab experiment at Lund Observatory that demonstrated dual-conjugate adaptive optics on a static atmosphere. The setup is to be placed at Lund Observatory. This means that the setup will be available 24h a day and does not have to share time with other instruments. The optical design of the experiment is finalized. A siderostat will be used to track the guide object and all other optical components are placed on an optical table. A small telescope, 35 cm aperture, is used and following this a tip-tilt mirror and two deformable mirrors are placed. The wave-front sensor is a Shack-Hartmann sensor using a SciMeasure Li'l Joe CCD39 camera system. The maximum update rate of the setup will be 0.5 kHz and the control system will be running under Linux. The effective wavelength will be 750 nm. All components in the setup have been acquired and the completion of the setup is underway. Collaborating partners in this project are the Applied Optics Group at National University of Ireland, Galway and the Swedish Defense Research Agency.

Real-time tracking control of electro-hydraulic force servo systems using offline feedback control and adaptive control.

PubMed

Shen, Gang; Zhu, Zhencai; Zhao, Jinsong; Zhu, Weidong; Tang, Yu; Li, Xiang

2017-03-01

This paper focuses on an application of an electro-hydraulic force tracking controller combined with an offline designed feedback controller (ODFC) and an online adaptive compensator in order to improve force tracking performance of an electro-hydraulic force servo system (EHFS). A proportional-integral controller has been employed and a parameter-based force closed-loop transfer function of the EHFS is identified by a continuous system identification algorithm. By taking the identified system model as a nominal plant model, an H ∞ offline design method is employed to establish an optimized feedback controller with consideration of the performance, control efforts, and robustness of the EHFS. In order to overcome the disadvantage of the offline designed controller and cope with the varying dynamics of the EHFS, an online adaptive compensator with a normalized least-mean-square algorithm is cascaded to the force closed-loop system of the EHFS compensated by the ODFC. Some comparative experiments are carried out on a real-time EHFS using an xPC rapid prototype technology, and the proposed controller yields a better force tracking performance improvement. Copyright © 2016. Published by Elsevier Ltd.

Real time optimization algorithm for wavefront sensorless adaptive optics OCT (Conference Presentation)

NASA Astrophysics Data System (ADS)

Verstraete, Hans R. G. W.; Heisler, Morgan; Ju, Myeong Jin; Wahl, Daniel J.; Bliek, Laurens; Kalkman, Jeroen; Bonora, Stefano; Sarunic, Marinko V.; Verhaegen, Michel; Jian, Yifan

2017-02-01

Optical Coherence Tomography (OCT) has revolutionized modern ophthalmology, providing depth resolved images of the retinal layers in a system that is suited to a clinical environment. A limitation of the performance and utilization of the OCT systems has been the lateral resolution. Through the combination of wavefront sensorless adaptive optics with dual variable optical elements, we present a compact lens based OCT system that is capable of imaging the photoreceptor mosaic. We utilized a commercially available variable focal length lens to correct for a wide range of defocus commonly found in patient eyes, and a multi-actuator adaptive lens after linearization of the hysteresis in the piezoelectric actuators for aberration correction to obtain near diffraction limited imaging at the retina. A parallel processing computational platform permitted real-time image acquisition and display. The Data-based Online Nonlinear Extremum seeker (DONE) algorithm was used for real time optimization of the wavefront sensorless adaptive optics OCT, and the performance was compared with a coordinate search algorithm. Cross sectional images of the retinal layers and en face images of the cone photoreceptor mosaic acquired in vivo from research volunteers before and after WSAO optimization are presented. Applying the DONE algorithm in vivo for wavefront sensorless AO-OCT demonstrates that the DONE algorithm succeeds in drastically improving the signal while achieving a computational time of 1 ms per iteration, making it applicable for high speed real time applications.

Online adaptive optimal control for continuous-time nonlinear systems with completely unknown dynamics

NASA Astrophysics Data System (ADS)

Lv, Yongfeng; Na, Jing; Yang, Qinmin; Wu, Xing; Guo, Yu

2016-01-01

An online adaptive optimal control is proposed for continuous-time nonlinear systems with completely unknown dynamics, which is achieved by developing a novel identifier-critic-based approximate dynamic programming algorithm with a dual neural network (NN) approximation structure. First, an adaptive NN identifier is designed to obviate the requirement of complete knowledge of system dynamics, and a critic NN is employed to approximate the optimal value function. Then, the optimal control law is computed based on the information from the identifier NN and the critic NN, so that the actor NN is not needed. In particular, a novel adaptive law design method with the parameter estimation error is proposed to online update the weights of both identifier NN and critic NN simultaneously, which converge to small neighbourhoods around their ideal values. The closed-loop system stability and the convergence to small vicinity around the optimal solution are all proved by means of the Lyapunov theory. The proposed adaptation algorithm is also improved to achieve finite-time convergence of the NN weights. Finally, simulation results are provided to exemplify the efficacy of the proposed methods.

Adapting the Quebecois method for assessing implementation to the French National Alzheimer Plan 2008–2012: lessons for gerontological services integration

PubMed Central

Somme, Dominique; Trouvé, Hélène; Perisset, Catherine; Corvol, Aline; Ankri, Joël; Saint-Jean, Olivier; de Stampa, Matthieu

2014-01-01

Introduction Many countries face ageing-related demographic and epidemiological challenges, notably neurodegenerative disorders, due to the multiple care services they require, thereby pleading for a more integrated system of care. The integrated Quebecois method issued from the Programme of Research to Integrate Services for the Maintenance of Autonomy inspired a French pilot experiment and the National Alzheimer Plan 2008–2012. Programme of Research to Integrate Services for the Maintenance of Autonomy method implementation was rated with an evaluation grid adapted to assess its successive degrees of completion. Discussion The approaching end of the president's term led to the method's institutionalization (2011–2012), before the implementation study ended. When the government changed, the study was interrupted. The results extracted from that ‘lost’ study (presented herein) have, nonetheless, ‘found’ some key lessons. Key lessons/conclusion It was possible to implement a Quebecois integrated-care method in France. We describe the lessons and pitfalls encountered in adapting this evaluation tool. This process is necessarily multidisciplinary and requires a test phase. A simple tool for quantitative assessment of integration was obtained. The first assessment of the tool was unsatisfactory but requires further studies. In the meantime, we recommend using mixed methodologies to assess the services integration level. PMID:24959112

Prisms to travel in time: Investigation of time-space association through prismatic adaptation effect on mental time travel.

PubMed

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. Copyright © 2016 Elsevier B.V. All rights reserved.

Adaptive nitrogen and integrated weed management in conservation agriculture: impacts on agronomic productivity, greenhouse gas emissions, and herbicide residues.

PubMed

Oyeogbe, Anthony Imoudu; Das, T K; Bhatia, Arti; Singh, Shashi Bala

2017-04-01

Increasing nitrogen (N) immobilization and weed interference in the early phase of implementation of conservation agriculture (CA) affects crop yields. Yet, higher fertilizer and herbicide use to improve productivity influences greenhouse gase emissions and herbicide residues. These tradeoffs precipitated a need for adaptive N and integrated weed management in CA-based maize (Zea mays L.)-wheat [Triticum aestivum (L.) emend Fiori & Paol] cropping system in the Indo-Gangetic Plains (IGP) to optimize N availability and reduce weed proliferation. Adaptive N fertilization was based on soil test value and normalized difference vegetation index measurement (NDVM) by GreenSeeker™ technology, while integrated weed management included brown manuring (Sesbania aculeata L. co-culture, killed at 25 days after sowing), herbicide mixture, and weedy check (control, i.e., without weed management). Results indicated that the 'best-adaptive N rate' (i.e., 50% basal + 25% broadcast at 25 days after sowing + supplementary N guided by NDVM) increased maize and wheat grain yields by 20 and 14% (averaged for 2 years), respectively, compared with whole recommended N applied at sowing. Weed management by brown manuring (during maize) and herbicide mixture (during wheat) resulted in 10 and 21% higher grain yields (averaged for 2 years), respectively, over the weedy check. The NDVM in-season N fertilization and brown manuring affected N 2 O and CO 2 emissions, but resulted in improved carbon storage efficiency, while herbicide residuals in soil were significantly lower in the maize season than in wheat cropping. This study concludes that adaptive N and integrated weed management enhance synergy between agronomic productivity, fertilizer and herbicide efficiency, and greenhouse gas mitigation.

Adaptive Monte Carlo methods

NASA Astrophysics Data System (ADS)

Fasnacht, Marc

We develop adaptive Monte Carlo methods for the calculation of the free energy as a function of a parameter of interest. The methods presented are particularly well-suited for systems with complex energy landscapes, where standard sampling techniques have difficulties. The Adaptive Histogram Method uses a biasing potential derived from histograms recorded during the simulation to achieve uniform sampling in the parameter of interest. The Adaptive Integration method directly calculates an estimate of the free energy from the average derivative of the Hamiltonian with respect to the parameter of interest and uses it as a biasing potential. We compare both methods to a state of the art method, and demonstrate that they compare favorably for the calculation of potentials of mean force of dense Lennard-Jones fluids. We use the Adaptive Integration Method to calculate accurate potentials of mean force for different types of simple particles in a Lennard-Jones fluid. Our approach allows us to separate the contributions of the solvent to the potential of mean force from the effect of the direct interaction between the particles. With contributions of the solvent determined, we can find the potential of mean force directly for any other direct interaction without additional simulations. We also test the accuracy of the Adaptive Integration Method on a thermodynamic cycle, which allows us to perform a consistency check between potentials of mean force and chemical potentials calculated using the Adaptive Integration Method. The results demonstrate a high degree of consistency of the method.

An innovative information fusion method with adaptive Kalman filter for integrated INS/GPS navigation of autonomous vehicles

NASA Astrophysics Data System (ADS)

Liu, Yahui; Fan, Xiaoqian; Lv, Chen; Wu, Jian; Li, Liang; Ding, Dawei

2018-02-01

Information fusion method of INS/GPS navigation system based on filtering technology is a research focus at present. In order to improve the precision of navigation information, a navigation technology based on Adaptive Kalman Filter with attenuation factor is proposed to restrain noise in this paper. The algorithm continuously updates the measurement noise variance and processes noise variance of the system by collecting the estimated and measured values, and this method can suppress white noise. Because a measured value closer to the current time would more accurately reflect the characteristics of the noise, an attenuation factor is introduced to increase the weight of the current value, in order to deal with the noise variance caused by environment disturbance. To validate the effectiveness of the proposed algorithm, a series of road tests are carried out in urban environment. The GPS and IMU data of the experiments were collected and processed by dSPACE and MATLAB/Simulink. Based on the test results, the accuracy of the proposed algorithm is 20% higher than that of a traditional Adaptive Kalman Filter. It also shows that the precision of the integrated navigation can be improved due to the reduction of the influence of environment noise.

Exponential Methods for the Time Integration of Schroedinger Equation

DOE Office of Scientific and Technical Information (OSTI.GOV)

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.

Effect of eccentricity and light level on the timing of light adaptation mechanisms.

PubMed

Barrionuevo, Pablo A; Matesanz, Beatriz M; Gloriani, Alejandro H; Arranz, Isabel; Issolio, Luis; Mar, Santiago; Aparicio, Juan A

2018-04-01

We explored the complexity of the light adaptation process, assessing adaptation recovery (Ar) at different eccentricities and light levels. Luminance thresholds were obtained with transient background fields at mesopic and photopic light levels for temporal retinal eccentricities (0°-15°) with test/background stimulus size of 0.5°/1° using a staircase procedure in a two-channel Maxwellian view optical system. Ar was obtained in comparison with steady data [Vis. Res.125, 12 (2016)VISRAM0042-698910.1016/j.visres.2016.04.008]. Light level proportionally affects Ar only at fovea. Photopic extrafoveal thresholds were one log unit higher for transient conditions. Adaptation was equally fast at low light levels for different retinal locations with variations mainly affected by noise. These results evidence different timing in the mechanisms of adaptation involved.

Adaptive Monocular Visual-Inertial SLAM for Real-Time Augmented Reality Applications in Mobile Devices.

PubMed

Piao, Jin-Chun; Kim, Shin-Dug

2017-11-07

Simultaneous localization and mapping (SLAM) is emerging as a prominent issue in computer vision and next-generation core technology for robots, autonomous navigation and augmented reality. In augmented reality applications, fast camera pose estimation and true scale are important. In this paper, we present an adaptive monocular visual-inertial SLAM method for real-time augmented reality applications in mobile devices. First, the SLAM system is implemented based on the visual-inertial odometry method that combines data from a mobile device camera and inertial measurement unit sensor. Second, we present an optical-flow-based fast visual odometry method for real-time camera pose estimation. Finally, an adaptive monocular visual-inertial SLAM is implemented by presenting an adaptive execution module that dynamically selects visual-inertial odometry or optical-flow-based fast visual odometry. Experimental results show that the average translation root-mean-square error of keyframe trajectory is approximately 0.0617 m with the EuRoC dataset. The average tracking time is reduced by 7.8%, 12.9%, and 18.8% when different level-set adaptive policies are applied. Moreover, we conducted experiments with real mobile device sensors, and the results demonstrate the effectiveness of performance improvement using the proposed method.

Adaptive Monocular Visual–Inertial SLAM for Real-Time Augmented Reality Applications in Mobile Devices

PubMed Central

Piao, Jin-Chun; Kim, Shin-Dug

2017-01-01

Simultaneous localization and mapping (SLAM) is emerging as a prominent issue in computer vision and next-generation core technology for robots, autonomous navigation and augmented reality. In augmented reality applications, fast camera pose estimation and true scale are important. In this paper, we present an adaptive monocular visual–inertial SLAM method for real-time augmented reality applications in mobile devices. First, the SLAM system is implemented based on the visual–inertial odometry method that combines data from a mobile device camera and inertial measurement unit sensor. Second, we present an optical-flow-based fast visual odometry method for real-time camera pose estimation. Finally, an adaptive monocular visual–inertial SLAM is implemented by presenting an adaptive execution module that dynamically selects visual–inertial odometry or optical-flow-based fast visual odometry. Experimental results show that the average translation root-mean-square error of keyframe trajectory is approximately 0.0617 m with the EuRoC dataset. The average tracking time is reduced by 7.8%, 12.9%, and 18.8% when different level-set adaptive policies are applied. Moreover, we conducted experiments with real mobile device sensors, and the results demonstrate the effectiveness of performance improvement using the proposed method. PMID:29112143

An Integrated Method to Analyze Farm Vulnerability to Climatic and Economic Variability According to Farm Configurations and Farmers' Adaptations.

PubMed

Martin, Guillaume; Magne, Marie-Angélina; Cristobal, Magali San

2017-01-01

The need to adapt to decrease farm vulnerability to adverse contextual events has been extensively discussed on a theoretical basis. We developed an integrated and operational method to assess farm vulnerability to multiple and interacting contextual changes and explain how this vulnerability can best be reduced according to farm configurations and farmers' technical adaptations over time. Our method considers farm vulnerability as a function of the raw measurements of vulnerability variables (e.g., economic efficiency of production), the slope of the linear regression of these measurements over time, and the residuals of this linear regression. The last two are extracted from linear mixed models considering a random regression coefficient (an intercept common to all farms), a global trend (a slope common to all farms), a random deviation from the general mean for each farm, and a random deviation from the general trend for each farm. Among all possible combinations, the lowest farm vulnerability is obtained through a combination of high values of measurements, a stable or increasing trend and low variability for all vulnerability variables considered. Our method enables relating the measurements, trends and residuals of vulnerability variables to explanatory variables that illustrate farm exposure to climatic and economic variability, initial farm configurations and farmers' technical adaptations over time. We applied our method to 19 cattle (beef, dairy, and mixed) farms over the period 2008-2013. Selected vulnerability variables, i.e., farm productivity and economic efficiency, varied greatly among cattle farms and across years, with means ranging from 43.0 to 270.0 kg protein/ha and 29.4-66.0% efficiency, respectively. No farm had a high level, stable or increasing trend and low residuals for both farm productivity and economic efficiency of production. Thus, the least vulnerable farms represented a compromise among measurement value, trend, and variability of

An Integrated Method to Analyze Farm Vulnerability to Climatic and Economic Variability According to Farm Configurations and Farmers’ Adaptations

PubMed Central

Martin, Guillaume; Magne, Marie-Angélina; Cristobal, Magali San

2017-01-01

The need to adapt to decrease farm vulnerability to adverse contextual events has been extensively discussed on a theoretical basis. We developed an integrated and operational method to assess farm vulnerability to multiple and interacting contextual changes and explain how this vulnerability can best be reduced according to farm configurations and farmers’ technical adaptations over time. Our method considers farm vulnerability as a function of the raw measurements of vulnerability variables (e.g., economic efficiency of production), the slope of the linear regression of these measurements over time, and the residuals of this linear regression. The last two are extracted from linear mixed models considering a random regression coefficient (an intercept common to all farms), a global trend (a slope common to all farms), a random deviation from the general mean for each farm, and a random deviation from the general trend for each farm. Among all possible combinations, the lowest farm vulnerability is obtained through a combination of high values of measurements, a stable or increasing trend and low variability for all vulnerability variables considered. Our method enables relating the measurements, trends and residuals of vulnerability variables to explanatory variables that illustrate farm exposure to climatic and economic variability, initial farm configurations and farmers’ technical adaptations over time. We applied our method to 19 cattle (beef, dairy, and mixed) farms over the period 2008–2013. Selected vulnerability variables, i.e., farm productivity and economic efficiency, varied greatly among cattle farms and across years, with means ranging from 43.0 to 270.0 kg protein/ha and 29.4–66.0% efficiency, respectively. No farm had a high level, stable or increasing trend and low residuals for both farm productivity and economic efficiency of production. Thus, the least vulnerable farms represented a compromise among measurement value, trend, and

Integrated analysis considered mitigation cost, damage cost and adaptation cost in Northeast Asia

NASA Astrophysics Data System (ADS)

Park, J. H.; Lee, D. K.; Kim, H. G.; Sung, S.; Jung, T. Y.

2015-12-01

Various studies show that raising the temperature as well as storms, cold snap, raining and drought caused by climate change. And variety disasters have had a damage to mankind. The world risk report(2012, The Nature Conservancy) and UNU-EHS (the United Nations University Institute for Environment and Human Security) reported that more and more people are exposed to abnormal weather such as floods, drought, earthquakes, typhoons and hurricanes over the world. In particular, the case of Korea, we influenced by various pollutants which are occurred in Northeast Asian countries, China and Japan, due to geographical meteorological characteristics. These contaminants have had a significant impact on air quality with the pollutants generated in Korea. Recently, around the world continued their effort to reduce greenhouse gas and to improve air quality in conjunction with the national or regional development goals priority. China is also working on various efforts in accordance with the international flows to cope with climate change and air pollution. In the future, effect of climate change and air quality in Korea and Northeast Asia will be change greatly according to China's growth and mitigation policies. The purpose of this study is to minimize the damage caused by climate change on the Korean peninsula through an integrated approach taking into account the mitigation and adaptation plan. This study will suggest a climate change strategy at the national level by means of a comprehensive economic analysis of the impacts and mitigation of climate change. In order to quantify the impact and damage cost caused by climate change scenarios in a regional scale, it should be priority variables selected in accordance with impact assessment of climate change. The sectoral impact assessment was carried out on the basis of selected variables and through this, to derive the methodology how to estimate damage cost and adaptation cost. And then, the methodology was applied in Korea

A new heterogeneous asynchronous explicit-implicit time integrator for nonsmooth dynamics

NASA Astrophysics Data System (ADS)

Fekak, Fatima-Ezzahra; Brun, Michael; Gravouil, Anthony; Depale, Bruno

2017-07-01

In computational structural dynamics, particularly in the presence of nonsmooth behavior, the choice of the time-step and the time integrator has a critical impact on the feasibility of the simulation. Furthermore, in some cases, as in the case of a bridge crane under seismic loading, multiple time-scales coexist in the same problem. In that case, the use of multi-time scale methods is suitable. Here, we propose a new explicit-implicit heterogeneous asynchronous time integrator (HATI) for nonsmooth transient dynamics with frictionless unilateral contacts and impacts. Furthermore, we present a new explicit time integrator for contact/impact problems where the contact constraints are enforced using a Lagrange multiplier method. In other words, the aim of this paper consists in using an explicit time integrator with a fine time scale in the contact area for reproducing high frequency phenomena, while an implicit time integrator is adopted in the other parts in order to reproduce much low frequency phenomena and to optimize the CPU time. In a first step, the explicit time integrator is tested on a one-dimensional example and compared to Moreau-Jean's event-capturing schemes. The explicit algorithm is found to be very accurate and the scheme has generally a higher order of convergence than Moreau-Jean's schemes and provides also an excellent energy behavior. Then, the two time scales explicit-implicit HATI is applied to the numerical example of a bridge crane under seismic loading. The results are validated in comparison to a fine scale full explicit computation. The energy dissipated in the implicit-explicit interface is well controlled and the computational time is lower than a full-explicit simulation.

Universal Hitting Time Statistics for Integrable Flows

NASA Astrophysics Data System (ADS)

Dettmann, Carl P.; Marklof, Jens; Strömbergsson, Andreas

2017-02-01

The perceived randomness in the time evolution of "chaotic" dynamical systems can be characterized by universal probabilistic limit laws, which do not depend on the fine features of the individual system. One important example is the Poisson law for the times at which a particle with random initial data hits a small set. This was proved in various settings for dynamical systems with strong mixing properties. The key result of the present study is that, despite the absence of mixing, the hitting times of integrable flows also satisfy universal limit laws which are, however, not Poisson. We describe the limit distributions for "generic" integrable flows and a natural class of target sets, and illustrate our findings with two examples: the dynamics in central force fields and ellipse billiards. The convergence of the hitting time process follows from a new equidistribution theorem in the space of lattices, which is of independent interest. Its proof exploits Ratner's measure classification theorem for unipotent flows, and extends earlier work of Elkies and McMullen.

Coastal Hazards and Integration of Impacts in Local Adaptation Planning

NASA Astrophysics Data System (ADS)

Knudsen, P.; Sorensen, C.; Molgaard, M. R.; Broge, N. H.; Andersen, O. B.

2016-12-01

Data on sea and groundwater levels, precipitation, land subsidence, geology, and geotechnical soil properties are combined with information on flood and erosion protection measures to analyze water-related impacts from climate change at an exposed coastal location. Future sea extremes will have a large impact but several coupled effects in the hydrological system need to be considered as well to provide for optimal protection and mitigation efforts. For instance, the investment and maintenance costs of securing functional water and wastewater pipes are significantly reduced by incorporating knowledge about climate change. The translation of regional sea level rise evidence and projections to concrete impact measures should take into account the potentially affected stakeholders who must collaborate on common and shared adaptation solutions. Here, knowledge integration across levels of governance and between research, private and public institutions, and the local communities provides: understanding of the immediate and potential future challenges; appreciation of different stakeholder motives, business agendas, legislative constraints etc., and a common focus on how to cost-efficiently adapt to and manage impacts of climate change. By construction of a common working platform that is updated with additional data and knowledge, e.g. from future regional models or extreme events, advances in sea level research can more readily be translated into concrete and local impact measures in a way that handles uncertainties in the future climate and urban development as well as suiting the varying stakeholder needs.

A Neural Mechanism for Time-Window Separation Resolves Ambiguity of Adaptive Coding

PubMed Central

Hildebrandt, K. Jannis; Ronacher, Bernhard; Hennig, R. Matthias; Benda, Jan

2015-01-01

The senses of animals are confronted with changing environments and different contexts. Neural adaptation is one important tool to adjust sensitivity to varying intensity ranges. For instance, in a quiet night outdoors, our hearing is more sensitive than when we are confronted with the plurality of sounds in a large city during the day. However, adaptation also removes available information on absolute sound levels and may thus cause ambiguity. Experimental data on the trade-off between benefits and loss through adaptation is scarce and very few mechanisms have been proposed to resolve it. We present an example where adaptation is beneficial for one task—namely, the reliable encoding of the pattern of an acoustic signal—but detrimental for another—the localization of the same acoustic stimulus. With a combination of neurophysiological data, modeling, and behavioral tests, we show that adaptation in the periphery of the auditory pathway of grasshoppers enables intensity-invariant coding of amplitude modulations, but at the same time, degrades information available for sound localization. We demonstrate how focusing the response of localization neurons to the onset of relevant signals separates processing of localization and pattern information temporally. In this way, the ambiguity of adaptive coding can be circumvented and both absolute and relative levels can be processed using the same set of peripheral neurons. PMID:25761097

Performance Enhancement of a USV INS/CNS/DVL Integration Navigation System Based on an Adaptive Information Sharing Factor Federated Filter

PubMed Central

Wang, Qiuying; Cui, Xufei; Li, Yibing; Ye, Fang

2017-01-01

To improve the ability of autonomous navigation for Unmanned Surface Vehicles (USVs), multi-sensor integrated navigation based on Inertial Navigation System (INS), Celestial Navigation System (CNS) and Doppler Velocity Log (DVL) is proposed. The CNS position and the DVL velocity are introduced as the reference information to correct the INS divergence error. The autonomy of the integrated system based on INS/CNS/DVL is much better compared with the integration based on INS/GNSS alone. However, the accuracy of DVL velocity and CNS position are decreased by the measurement noise of DVL and bad weather, respectively. Hence, the INS divergence error cannot be estimated and corrected by the reference information. To resolve the problem, the Adaptive Information Sharing Factor Federated Filter (AISFF) is introduced to fuse data. The information sharing factor of the Federated Filter is adaptively adjusted to maintaining multiple component solutions usable as back-ups, which can improve the reliability of overall system. The effectiveness of this approach is demonstrated by simulation and experiment, the results show that for the INS/CNS/DVL integrated system, when the DVL velocity accuracy is decreased and the CNS cannot work under bad weather conditions, the INS/CNS/DVL integrated system can operate stably based on the AISFF method. PMID:28165369

Performance Enhancement of a USV INS/CNS/DVL Integration Navigation System Based on an Adaptive Information Sharing Factor Federated Filter.

PubMed

Wang, Qiuying; Cui, Xufei; Li, Yibing; Ye, Fang

2017-02-03

To improve the ability of autonomous navigation for Unmanned Surface Vehicles (USVs), multi-sensor integrated navigation based on Inertial Navigation System (INS), Celestial Navigation System (CNS) and Doppler Velocity Log (DVL) is proposed. The CNS position and the DVL velocity are introduced as the reference information to correct the INS divergence error. The autonomy of the integrated system based on INS/CNS/DVL is much better compared with the integration based on INS/GNSS alone. However, the accuracy of DVL velocity and CNS position are decreased by the measurement noise of DVL and bad weather, respectively. Hence, the INS divergence error cannot be estimated and corrected by the reference information. To resolve the problem, the Adaptive Information Sharing Factor Federated Filter (AISFF) is introduced to fuse data. The information sharing factor of the Federated Filter is adaptively adjusted to maintaining multiple component solutions usable as back-ups, which can improve the reliability of overall system. The effectiveness of this approach is demonstrated by simulation and experiment, the results show that for the INS/CNS/DVL integrated system, when the DVL velocity accuracy is decreased and the CNS cannot work under bad weather conditions, the INS/CNS/DVL integrated system can operate stably based on the AISFF method.

Personality traits, future time perspective and adaptive behavior in adolescence.

PubMed

Gomes Carvalho, Renato Gil; Novo, Rosa Ferreira

2015-04-24

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.

Neural-Network-Based Robust Optimal Tracking Control for MIMO Discrete-Time Systems With Unknown Uncertainty Using Adaptive Critic Design.

PubMed

Liu, Lei; Wang, Zhanshan; Zhang, Huaguang

2018-04-01

This paper is concerned with the robust optimal tracking control strategy for a class of nonlinear multi-input multi-output discrete-time systems with unknown uncertainty via adaptive critic design (ACD) scheme. The main purpose is to establish an adaptive actor-critic control method, so that the cost function in the procedure of dealing with uncertainty is minimum and the closed-loop system is stable. Based on the neural network approximator, an action network is applied to generate the optimal control signal and a critic network is used to approximate the cost function, respectively. In contrast to the previous methods, the main features of this paper are: 1) the ACD scheme is integrated into the controllers to cope with the uncertainty and 2) a novel cost function, which is not in quadric form, is proposed so that the total cost in the design procedure is reduced. It is proved that the optimal control signals and the tracking errors are uniformly ultimately bounded even when the uncertainty exists. Finally, a numerical simulation is developed to show the effectiveness of the present approach.

Integration and Evaluation of Microscope Adapter for the Ultra-Compact Imaging Spectrometer

NASA Astrophysics Data System (ADS)

Smith-Dryden, S. D.; Blaney, D. L.; Van Gorp, B.; Mouroulis, P.; Green, R. O.; Sellar, R. G.; Rodriguez, J.; Wilson, D.

2012-12-01

Petrologic, diagenetic, impact and weathering processes often happen at scales that are not observable from orbit. On Earth, one of the most common things that a scientist does when trying to understand detailed geologic history is to create a thin section of the rock and study the mineralogy and texture. Unfortunately, sample preparation and manipulation with advanced instrumentation may be a resource intensive proposition (e.g. time, power, complexity) in-situ. Getting detailed mineralogy and textural information without sample preparation is highly desirable. Visible to short wavelength microimaging spectroscopy has the potential to provide this information without sample preparation. Wavelengths between 500-2600 nm are sensitive to a wide range of minerals including mafic, carbonates, clays, and sulfates. The Ultra-Compact Imaging Spectrometer (UCIS) has been developed as a low mass (<2.0 kg), low power (~5.2 W) Offner spectrometer, ideal for use on Mars rover or other in-situ platforms. The UCIS instrument with its HgCdTe detector provides a spectral resolution of 10 nm with a range of 500-2600 nm, in addition to a 30 degree field of view and a 1.35 mrad instantaneous field of view. (Van Gorp et al. 2011). To explore applications of this technology for microscale investigations, an f/10 microimaging adapter has been designed and integrated to allow imaging of samples. The spatial coverage of the instrument is 2.56 cm with sampling of 67.5 microns (380 spatial pixels). Because the adapter is slow relative to the UCIS detector, strong sample illumination is required. Light from the lamp box was directed through optical fiber bundles, and directed onto the sample at a high angle of incidence to provide dark field imaging. For data collection, a mineral sample is mounted on the microscope adapter and scanned by the detector as it is moved horizontally via actuator. Data from the instrument is stored as a xyz cube end product with one spectral and two spatial

Adaptive real-time dual-comb spectroscopy.

PubMed

Ideguchi, Takuro; Poisson, Antonin; Guelachvili, Guy; Picqué, Nathalie; Hänsch, Theodor W

2014-02-27

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.

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.

Adaptive real-time dual-comb spectroscopy

PubMed Central

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

Fuzzy adaptive interacting multiple model nonlinear filter for integrated navigation sensor fusion.

PubMed

Tseng, Chien-Hao; Chang, Chih-Wen; Jwo, Dah-Jing

2011-01-01

In this paper, the application of the fuzzy interacting multiple model unscented Kalman filter (FUZZY-IMMUKF) approach to integrated navigation processing for the maneuvering vehicle is presented. The unscented Kalman filter (UKF) employs a set of sigma points through deterministic sampling, such that a linearization process is not necessary, and therefore the errors caused by linearization as in the traditional extended Kalman filter (EKF) can be avoided. The nonlinear filters naturally suffer, to some extent, the same problem as the EKF for which the uncertainty of the process noise and measurement noise will degrade the performance. As a structural adaptation (model switching) mechanism, the interacting multiple model (IMM), which describes a set of switching models, can be utilized for determining the adequate value of process noise covariance. The fuzzy logic adaptive system (FLAS) is employed to determine the lower and upper bounds of the system noise through the fuzzy inference system (FIS). The resulting sensor fusion strategy can efficiently deal with the nonlinear problem for the vehicle navigation. The proposed FUZZY-IMMUKF algorithm shows remarkable improvement in the navigation estimation accuracy as compared to the relatively conventional approaches such as the UKF and IMMUKF.

Adaptive density trajectory cluster based on time and space distance

NASA Astrophysics Data System (ADS)

Liu, Fagui; Zhang, Zhijie

2017-10-01

There are some hotspot problems remaining in trajectory cluster for discovering mobile behavior regularity, such as the computation of distance between sub trajectories, the setting of parameter values in cluster algorithm and the uncertainty/boundary problem of data set. As a result, based on the time and space, this paper tries to define the calculation method of distance between sub trajectories. The significance of distance calculation for sub trajectories is to clearly reveal the differences in moving trajectories and to promote the accuracy of cluster algorithm. Besides, a novel adaptive density trajectory cluster algorithm is proposed, in which cluster radius is computed through using the density of data distribution. In addition, cluster centers and number are selected by a certain strategy automatically, and uncertainty/boundary problem of data set is solved by designed weighted rough c-means. Experimental results demonstrate that the proposed algorithm can perform the fuzzy trajectory cluster effectively on the basis of the time and space distance, and obtain the optimal cluster centers and rich cluster results information adaptably for excavating the features of mobile behavior in mobile and sociology network.

A model for homeopathic remedy effects: low dose nanoparticles, allostatic cross-adaptation, and time-dependent sensitization in a complex adaptive system

PubMed Central

2012-01-01

Background This paper proposes a novel model for homeopathic remedy action on living systems. Research indicates that homeopathic remedies (a) contain measurable source and silica nanoparticles heterogeneously dispersed in colloidal solution; (b) act by modulating biological function of the allostatic stress response network (c) evoke biphasic actions on living systems via organism-dependent adaptive and endogenously amplified effects; (d) improve systemic resilience. Discussion The proposed active components of homeopathic remedies are nanoparticles of source substance in water-based colloidal solution, not bulk-form drugs. Nanoparticles have unique biological and physico-chemical properties, including increased catalytic reactivity, protein and DNA adsorption, bioavailability, dose-sparing, electromagnetic, and quantum effects different from bulk-form materials. Trituration and/or liquid succussions during classical remedy preparation create “top-down” nanostructures. Plants can biosynthesize remedy-templated silica nanostructures. Nanoparticles stimulate hormesis, a beneficial low-dose adaptive response. Homeopathic remedies prescribed in low doses spaced intermittently over time act as biological signals that stimulate the organism’s allostatic biological stress response network, evoking nonlinear modulatory, self-organizing change. Potential mechanisms include time-dependent sensitization (TDS), a type of adaptive plasticity/metaplasticity involving progressive amplification of host responses, which reverse direction and oscillate at physiological limits. To mobilize hormesis and TDS, the remedy must be appraised as a salient, but low level, novel threat, stressor, or homeostatic disruption for the whole organism. Silica nanoparticles adsorb remedy source and amplify effects. Properly-timed remedy dosing elicits disease-primed compensatory reversal in direction of maladaptive dynamics of the allostatic network, thus promoting resilience and recovery from

A model for homeopathic remedy effects: low dose nanoparticles, allostatic cross-adaptation, and time-dependent sensitization in a complex adaptive system.

PubMed

Bell, Iris R; Koithan, Mary

2012-10-22

This paper proposes a novel model for homeopathic remedy action on living systems. Research indicates that homeopathic remedies (a) contain measurable source and silica nanoparticles heterogeneously dispersed in colloidal solution; (b) act by modulating biological function of the allostatic stress response network (c) evoke biphasic actions on living systems via organism-dependent adaptive and endogenously amplified effects; (d) improve systemic resilience. The proposed active components of homeopathic remedies are nanoparticles of source substance in water-based colloidal solution, not bulk-form drugs. Nanoparticles have unique biological and physico-chemical properties, including increased catalytic reactivity, protein and DNA adsorption, bioavailability, dose-sparing, electromagnetic, and quantum effects different from bulk-form materials. Trituration and/or liquid succussions during classical remedy preparation create "top-down" nanostructures. Plants can biosynthesize remedy-templated silica nanostructures. Nanoparticles stimulate hormesis, a beneficial low-dose adaptive response. Homeopathic remedies prescribed in low doses spaced intermittently over time act as biological signals that stimulate the organism's allostatic biological stress response network, evoking nonlinear modulatory, self-organizing change. Potential mechanisms include time-dependent sensitization (TDS), a type of adaptive plasticity/metaplasticity involving progressive amplification of host responses, which reverse direction and oscillate at physiological limits. To mobilize hormesis and TDS, the remedy must be appraised as a salient, but low level, novel threat, stressor, or homeostatic disruption for the whole organism. Silica nanoparticles adsorb remedy source and amplify effects. Properly-timed remedy dosing elicits disease-primed compensatory reversal in direction of maladaptive dynamics of the allostatic network, thus promoting resilience and recovery from disease. Homeopathic

Real-time implementing wavefront reconstruction for adaptive optics

NASA Astrophysics Data System (ADS)

Wang, Caixia; Li, Mei; Wang, Chunhong; Zhou, Luchun; Jiang, Wenhan

2004-12-01

The capability of real time wave-front reconstruction is important for an adaptive optics (AO) system. The bandwidth of system and the real-time processing ability of the wave-front processor is mainly affected by the speed of calculation. The system requires enough number of subapertures and high sampling frequency to compensate atmospheric turbulence. The number of reconstruction operation is increased accordingly. Since the performance of AO system improves with the decrease of calculation latency, it is necessary to study how to increase the speed of wavefront reconstruction. There are two methods to improve the real time of the reconstruction. One is to convert the wavefront reconstruction matrix, such as by wavelet or FFT. The other is enhancing the performance of the processing element. Analysis shows that the latency cutting is performed with the cost of reconstruction precision by the former method. In this article, the latter method is adopted. From the characteristic of the wavefront reconstruction algorithm, a systolic array by FPGA is properly designed to implement real-time wavefront reconstruction. The system delay is reduced greatly by the utilization of pipeline and parallel processing. The minimum latency of reconstruction is the reconstruction calculation of one subaperture.

A New Approach to Interference Excision in Radio Astronomy: Real-Time Adaptive Cancellation

NASA Astrophysics Data System (ADS)

Barnbaum, Cecilia; Bradley, Richard F.

1998-11-01

Every year, an increasing amount of radio-frequency (RF) spectrum in the VHF, UHF, and microwave bands is being utilized to support new commercial and military ventures, and all have the potential to interfere with radio astronomy observations. Such services already cause problems for radio astronomy even in very remote observing sites, and the potential for this form of light pollution to grow is alarming. Preventive measures to eliminate interference through FCC legislation and ITU agreements can be effective; however, many times this approach is inadequate and interference excision at the receiver is necessary. Conventional techniques such as RF filters, RF shielding, and postprocessing of data have been only somewhat successful, but none has been sufficient. Adaptive interference cancellation is a real-time approach to interference excision that has not been used before in radio astronomy. We describe here, for the first time, adaptive interference cancellation in the context of radio astronomy instrumentation, and we present initial results for our prototype receiver. In the 1960s, analog adaptive interference cancelers were developed that obtain a high degree of cancellation in problems of radio communications and radar. However, analog systems lack the dynamic range, noised performance, and versatility required by radio astronomy. The concept of digital adaptive interference cancellation was introduced in the mid-1960s as a way to reduce unwanted noise in low-frequency (audio) systems. Examples of such systems include the canceling of maternal ECG in fetal electrocardiography and the reduction of engine noise in the passenger compartments of automobiles. These audio-frequency applications require bandwidths of only a few tens of kilohertz. Only recently has high-speed digital filter technology made high dynamic range adaptive canceling possible in a bandwidth as large as a few megahertz, finally opening the door to application in radio astronomy. We have

Interspike interval correlation in a stochastic exponential integrate-and-fire model with subthreshold and spike-triggered adaptation.

PubMed

Shiau, LieJune; Schwalger, Tilo; Lindner, Benjamin

2015-06-01

We study the spike statistics of an adaptive exponential integrate-and-fire neuron stimulated by white Gaussian current noise. We derive analytical approximations for the coefficient of variation and the serial correlation coefficient of the interspike interval assuming that the neuron operates in the mean-driven tonic firing regime and that the stochastic input is weak. Our result for the serial correlation coefficient has the form of a geometric sequence and is confirmed by the comparison to numerical simulations. The theory predicts various patterns of interval correlations (positive or negative at lag one, monotonically decreasing or oscillating) depending on the strength of the spike-triggered and subthreshold components of the adaptation current. In particular, for pure subthreshold adaptation we find strong positive ISI correlations that are usually ascribed to positive correlations in the input current. Our results i) provide an alternative explanation for interspike-interval correlations observed in vivo, ii) may be useful in fitting point neuron models to experimental data, and iii) may be instrumental in exploring the role of adaptation currents for signal detection and signal transmission in single neurons.

Robust adaptive uniform exact tracking control for uncertain Euler-Lagrange system

NASA Astrophysics Data System (ADS)

Yang, Yana; Hua, Changchun; Li, Junpeng; Guan, Xinping

2017-12-01

This paper offers a solution to the robust adaptive uniform exact tracking control for uncertain nonlinear Euler-Lagrange (EL) system. An adaptive finite-time tracking control algorithm is designed by proposing a novel nonsingular integral terminal sliding-mode surface. Moreover, a new adaptive parameter tuning law is also developed by making good use of the system tracking errors and the adaptive parameter estimation errors. Thus, both the trajectory tracking and the parameter estimation can be achieved in a guaranteed time adjusted arbitrarily based on practical demands, simultaneously. Additionally, the control result for the EL system proposed in this paper can be extended to high-order nonlinear systems easily. Finally, a test-bed 2-DOF robot arm is set-up to demonstrate the performance of the new control algorithm.

Decentralized adaptive control

NASA Technical Reports Server (NTRS)

Oh, B. J.; Jamshidi, M.; Seraji, H.

1988-01-01

A decentralized adaptive control is proposed to stabilize and track the nonlinear, interconnected subsystems with unknown parameters. The adaptation of the controller gain is derived by using model reference adaptive control theory based on Lyapunov's direct method. The adaptive gains consist of sigma, proportional, and integral combination of the measured and reference values of the corresponding subsystem. The proposed control is applied to the joint control of a two-link robot manipulator, and the performance in computer simulation corresponds with what is expected in theoretical development.

Pitch Adaptation Patterns in Bimodal Cochlear Implant Users: Over Time and After Experience

PubMed Central

Reiss, Lina A.J.; Ito, Rindy A.; Eggleston, Jessica L.; Liao, Selena; Becker, Jillian J.; Lakin, Carrie E.; Warren, Frank M.; McMenomey, Sean O.

2014-01-01

Background Pitch plasticity has been observed in Hybrid cochlear implant (CI) users. Does pitch plasticity also occur in bimodal CI users with traditional long-electrode CIs, and is pitch adaptation pattern associated with electrode discrimination or speech recognition performance? Objective Characterize pitch adaptation patterns in long-electrode CI users, correlate these patterns with electrode discrimination and speech perception outcomes, and analyze which subject factors are associated with the different patterns. Methods Electric-to-acoustic pitch matches were obtained in 19 subjects over time from CI activation to at least 12 months after activation, and in a separate group of 18 subjects in a single visit after at least 24 months of CI experience. Audiometric thresholds, electrode discrimination performance, and speech perception scores were also measured. Results Subjects measured over time had pitch adaptation patterns that fit one of the following categories: 1) “Pitch-adapting”, i.e. the mismatch between perceived electrode pitch and the corresponding frequency-to-electrode allocations decreased; 2) “Pitch-dropping”, i.e. the pitches of multiple electrodes dropped and converged to a similar low pitch; 3) “Pitch-unchanging”, i.e. electrode pitches did not change. Subjects measured after CI experience had a parallel set of adaptation patterns: 1) “Matched-pitch”, i.e. the electrode pitch was matched to the frequency allocation; 2) “Low-pitch”, i.e. the pitches of multiple electrodes were all around the lowest frequency allocation; 3) “Nonmatched-pitch”, i.e. the pitch patterns were compressed relative to the frequency allocations and did not fit either the matched-pitch or low-pitch categories. Unlike Hybrid CI users which were mostly in the pitch-adapting/matched-pitch category, the majority of bimodal CI users were in the latter two categories, pitch-dropping/low-pitch or pitch-unchanging/nonmatched-pitch. Subjects with pitch-adapting

Evaluation of atomic pressure in the multiple time-step integration algorithm.

PubMed

Andoh, Yoshimichi; Yoshii, Noriyuki; Yamada, Atsushi; Okazaki, Susumu

2017-04-15

In molecular dynamics (MD) calculations, reduction in calculation time per MD loop is essential. A multiple time-step (MTS) integration algorithm, the RESPA (Tuckerman and Berne, J. Chem. Phys. 1992, 97, 1990-2001), enables reductions in calculation time by decreasing the frequency of time-consuming long-range interaction calculations. However, the RESPA MTS algorithm involves uncertainties in evaluating the atomic interaction-based pressure (i.e., atomic pressure) of systems with and without holonomic constraints. It is not clear which intermediate forces and constraint forces in the MTS integration procedure should be used to calculate the atomic pressure. In this article, we propose a series of equations to evaluate the atomic pressure in the RESPA MTS integration procedure on the basis of its equivalence to the Velocity-Verlet integration procedure with a single time step (STS). The equations guarantee time-reversibility even for the system with holonomic constrants. Furthermore, we generalize the equations to both (i) arbitrary number of inner time steps and (ii) arbitrary number of force components (RESPA levels). The atomic pressure calculated by our equations with the MTS integration shows excellent agreement with the reference value with the STS, whereas pressures calculated using the conventional ad hoc equations deviated from it. Our equations can be extended straightforwardly to the MTS integration algorithm for the isothermal NVT and isothermal-isobaric NPT ensembles. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Features: Real-Time Adaptive Feature and Document Learning for Web Search.

ERIC Educational Resources Information Center

Chen, Zhixiang; Meng, Xiannong; Fowler, Richard H.; Zhu, Binhai

2001-01-01

Describes Features, an intelligent Web search engine that is able to perform real-time adaptive feature (i.e., keyword) and document learning. Explains how Features learns from users' document relevance feedback and automatically extracts and suggests indexing keywords relevant to a search query, and learns from users' keyword relevance feedback…

Integrated multiple-model adaptive fault identification and reconfigurable fault-tolerant control for Lead-Wing close formation systems

NASA Astrophysics Data System (ADS)

Liu, Chun; Jiang, Bin; Zhang, Ke

2018-03-01

This paper investigates the attitude and position tracking control problem for Lead-Wing close formation systems in the presence of loss of effectiveness and lock-in-place or hardover failure. In close formation flight, Wing unmanned aerial vehicle movements are influenced by vortex effects of the neighbouring Lead unmanned aerial vehicle. This situation allows modelling of aerodynamic coupling vortex-effects and linearisation based on optimal close formation geometry. Linearised Lead-Wing close formation model is transformed into nominal robust H-infinity models with respect to Mach hold, Heading hold, and Altitude hold autopilots; static feedback H-infinity controller is designed to guarantee effective tracking of attitude and position while manoeuvring Lead unmanned aerial vehicle. Based on H-infinity control design, an integrated multiple-model adaptive fault identification and reconfigurable fault-tolerant control scheme is developed to guarantee asymptotic stability of close-loop systems, error signal boundedness, and attitude and position tracking properties. Simulation results for Lead-Wing close formation systems validate the efficiency of the proposed integrated multiple-model adaptive control algorithm.

Performance evaluation of GPU parallelization, space-time adaptive algorithms, and their combination for simulating cardiac electrophysiology.

PubMed

Sachetto Oliveira, Rafael; Martins Rocha, Bernardo; Burgarelli, Denise; Meira, Wagner; Constantinides, Christakis; Weber Dos Santos, Rodrigo

2018-02-01

The use of computer models as a tool for the study and understanding of the complex phenomena of cardiac electrophysiology has attained increased importance nowadays. At the same time, the increased complexity of the biophysical processes translates into complex computational and mathematical models. To speed up cardiac simulations and to allow more precise and realistic uses, 2 different techniques have been traditionally exploited: parallel computing and sophisticated numerical methods. In this work, we combine a modern parallel computing technique based on multicore and graphics processing units (GPUs) and a sophisticated numerical method based on a new space-time adaptive algorithm. We evaluate each technique alone and in different combinations: multicore and GPU, multicore and GPU and space adaptivity, multicore and GPU and space adaptivity and time adaptivity. All the techniques and combinations were evaluated under different scenarios: 3D simulations on slabs, 3D simulations on a ventricular mouse mesh, ie, complex geometry, sinus-rhythm, and arrhythmic conditions. Our results suggest that multicore and GPU accelerate the simulations by an approximate factor of 33×, whereas the speedups attained by the space-time adaptive algorithms were approximately 48. Nevertheless, by combining all the techniques, we obtained speedups that ranged between 165 and 498. The tested methods were able to reduce the execution time of a simulation by more than 498× for a complex cellular model in a slab geometry and by 165× in a realistic heart geometry simulating spiral waves. The proposed methods will allow faster and more realistic simulations in a feasible time with no significant loss of accuracy. Copyright © 2017 John Wiley & Sons, Ltd.

Adaptive Network Dynamics - Modeling and Control of Time-Dependent Social Contacts

PubMed Central

Schwartz, Ira B.; Shaw, Leah B.; Shkarayev, Maxim S.

2013-01-01

Real networks consisting of social contacts do not possess static connections. That is, social connections may be time dependent due to a variety of individual behavioral decisions based on current network connections. Examples of adaptive networks occur in epidemics, where information about infectious individuals may change the rewiring of healthy people, or in the recruitment of individuals to a cause or fad, where rewiring may optimize recruitment of susceptible individuals. In this paper, we will review some of the dynamical properties of adaptive networks, and show how they predict novel phenomena as well as yield insight into new controls. The applications will be control of epidemic outbreaks and terrorist recruitment modeling. PMID:25414913

Learning-Based Adaptive Optimal Tracking Control of Strict-Feedback Nonlinear Systems.

PubMed

Gao, Weinan; Jiang, Zhong-Ping; Weinan Gao; Zhong-Ping Jiang; Gao, Weinan; Jiang, Zhong-Ping

2018-06-01

This paper proposes a novel data-driven control approach to address the problem of adaptive optimal tracking for a class of nonlinear systems taking the strict-feedback form. Adaptive dynamic programming (ADP) and nonlinear output regulation theories are integrated for the first time to compute an adaptive near-optimal tracker without any a priori knowledge of the system dynamics. Fundamentally different from adaptive optimal stabilization problems, the solution to a Hamilton-Jacobi-Bellman (HJB) equation, not necessarily a positive definite function, cannot be approximated through the existing iterative methods. This paper proposes a novel policy iteration technique for solving positive semidefinite HJB equations with rigorous convergence analysis. A two-phase data-driven learning method is developed and implemented online by ADP. The efficacy of the proposed adaptive optimal tracking control methodology is demonstrated via a Van der Pol oscillator with time-varying exogenous signals.

Dynamic models of farmers adaptation to climate change (case of rice farmers in Cemoro Watershed, Central Java, Indonesia)

NASA Astrophysics Data System (ADS)

Sugihardjo; Sutrisno, J.; Setyono, P.; Suntoro

2018-03-01

Farming activities are generally very sensitive to climate change variations. Global climate change will result in changes of patterns and distribution of rainfall. The impact of changing patterns and distribution of rainfall is the occurrence of early season shifts and periods of planting. Therefore, farmers need to adapt to the occurrence of climate change to avoid the decrease productivity on the farm land. This study aims to examine the impacts of climate change adaptation that farmers practiced on the farming productivity. The analysis is conducted dynamically using the Powersim 2.5. The result of analysis shows that the use of Planting Calendar and Integrated Crops Management technology can increase the rice productivity of certain area unity. Both technologies are the alternatives for farmers to adapt to climate change. Both farmers who adapt to climate change and do not adapt to climate change, experience an increase in rice production, time after time. However, farmers who adapt to climate change, increase their production faster than farmers who do not adapt to climate change. The use of the Planting Calendar and Integrated Crops Management strategy together as a farmers’ adaptation strategy is able to increase production compared to non-adaptive farmers.

A major locus controls local adaptation and adaptive life history variation in a perennial plant.

PubMed

Wang, Jing; Ding, Jihua; Tan, Biyue; Robinson, Kathryn M; Michelson, Ingrid H; Johansson, Anna; Nystedt, Björn; Scofield, Douglas G; Nilsson, Ove; Jansson, Stefan; Street, Nathaniel R; Ingvarsson, Pär K

2018-06-04

The initiation of growth cessation and dormancy represent critical life-history trade-offs between survival and growth and have important fitness effects in perennial plants. Such adaptive life-history traits often show strong local adaptation along environmental gradients but, despite their importance, the genetic architecture of these traits remains poorly understood. We integrate whole genome re-sequencing with environmental and phenotypic data from common garden experiments to investigate the genomic basis of local adaptation across a latitudinal gradient in European aspen (Populus tremula). A single genomic region containing the PtFT2 gene mediates local adaptation in the timing of bud set and explains 65% of the observed genetic variation in bud set. This locus is the likely target of a recent selective sweep that originated right before or during colonization of northern Scandinavia following the last glaciation. Field and greenhouse experiments confirm that variation in PtFT2 gene expression affects the phenotypic variation in bud set that we observe in wild natural populations. Our results reveal a major effect locus that determines the timing of bud set and that has facilitated rapid adaptation to shorter growing seasons and colder climates in European aspen. The discovery of a single locus explaining a substantial fraction of the variation in a key life-history trait is remarkable, given that such traits are generally considered to be highly polygenic. These findings provide a dramatic illustration of how loci of large-effect for adaptive traits can arise and be maintained over large geographical scales in natural populations.

Discrete-time switching periodic adaptive control for time-varying parameters with unknown periodicity

NASA Astrophysics Data System (ADS)

Yu, Miao; Huang, Deqing; Yang, Wanqiu

2018-06-01

In this paper, we address the problem of unknown periodicity for a class of discrete-time nonlinear parametric systems without assuming any growth conditions on the nonlinearities. The unknown periodicity hides in the parametric uncertainties, which is difficult to estimate with existing techniques. By incorporating a logic-based switching mechanism, we identify the period and bound of unknown parameter simultaneously. Lyapunov-based analysis is given to demonstrate that a finite number of switchings can guarantee the asymptotic tracking for the nonlinear parametric systems. The simulation result also shows the efficacy of the proposed switching periodic adaptive control approach.

Reliable and efficient a posteriori error estimation for adaptive IGA boundary element methods for weakly-singular integral equations

PubMed Central

Feischl, Michael; Gantner, Gregor; Praetorius, Dirk

2015-01-01

We consider the Galerkin boundary element method (BEM) for weakly-singular integral equations of the first-kind in 2D. We analyze some residual-type a posteriori error estimator which provides a lower as well as an upper bound for the unknown Galerkin BEM error. The required assumptions are weak and allow for piecewise smooth parametrizations of the boundary, local mesh-refinement, and related standard piecewise polynomials as well as NURBS. In particular, our analysis gives a first contribution to adaptive BEM in the frame of isogeometric analysis (IGABEM), for which we formulate an adaptive algorithm which steers the local mesh-refinement and the multiplicity of the knots. Numerical experiments underline the theoretical findings and show that the proposed adaptive strategy leads to optimal convergence. PMID:26085698

Robust and Adaptive Online Time Series Prediction with Long Short-Term Memory

PubMed Central

Tao, Qing

2017-01-01

Online time series prediction is the mainstream method in a wide range of fields, ranging from speech analysis and noise cancelation to stock market analysis. However, the data often contains many outliers with the increasing length of time series in real world. These outliers can mislead the learned model if treated as normal points in the process of prediction. To address this issue, in this paper, we propose a robust and adaptive online gradient learning method, RoAdam (Robust Adam), for long short-term memory (LSTM) to predict time series with outliers. This method tunes the learning rate of the stochastic gradient algorithm adaptively in the process of prediction, which reduces the adverse effect of outliers. It tracks the relative prediction error of the loss function with a weighted average through modifying Adam, a popular stochastic gradient method algorithm for training deep neural networks. In our algorithm, the large value of the relative prediction error corresponds to a small learning rate, and vice versa. The experiments on both synthetic data and real time series show that our method achieves better performance compared to the existing methods based on LSTM. PMID:29391864

Robust and Adaptive Online Time Series Prediction with Long Short-Term Memory.

PubMed

Yang, Haimin; Pan, Zhisong; Tao, Qing

2017-01-01

Online time series prediction is the mainstream method in a wide range of fields, ranging from speech analysis and noise cancelation to stock market analysis. However, the data often contains many outliers with the increasing length of time series in real world. These outliers can mislead the learned model if treated as normal points in the process of prediction. To address this issue, in this paper, we propose a robust and adaptive online gradient learning method, RoAdam (Robust Adam), for long short-term memory (LSTM) to predict time series with outliers. This method tunes the learning rate of the stochastic gradient algorithm adaptively in the process of prediction, which reduces the adverse effect of outliers. It tracks the relative prediction error of the loss function with a weighted average through modifying Adam, a popular stochastic gradient method algorithm for training deep neural networks. In our algorithm, the large value of the relative prediction error corresponds to a small learning rate, and vice versa. The experiments on both synthetic data and real time series show that our method achieves better performance compared to the existing methods based on LSTM.

Effects of integration time on in-water radiometric profiles.

PubMed

D'Alimonte, Davide; Zibordi, Giuseppe; Kajiyama, Tamito

2018-03-05

This work investigates the effects of integration time on in-water downward irradiance E d , upward irradiance E u and upwelling radiance L u profile data acquired with free-fall hyperspectral systems. Analyzed quantities are the subsurface value and the diffuse attenuation coefficient derived by applying linear and non-linear regression schemes. Case studies include oligotrophic waters (Case-1), as well as waters dominated by Colored Dissolved Organic Matter (CDOM) and Non-Algal Particles (NAP). Assuming a 24-bit digitization, measurements resulting from the accumulation of photons over integration times varying between 8 and 2048ms are evaluated at depths corresponding to: 1) the beginning of each integration interval (Fst); 2) the end of each integration interval (Lst); 3) the averages of Fst and Lst values (Avg); and finally 4) the values weighted accounting for the diffuse attenuation coefficient of water (Wgt). Statistical figures show that the effects of integration time can bias results well above 5% as a function of the depth definition. Results indicate the validity of the Wgt depth definition and the fair applicability of the Avg one. Instead, both the Fst and Lst depths should not be adopted since they may introduce pronounced biases in E u and L u regression products for highly absorbing waters. Finally, the study reconfirms the relevance of combining multiple radiometric casts into a single profile to increase precision of regression products.

Quantum Dynamics with Short-Time Trajectories and Minimal Adaptive Basis Sets.

PubMed

Saller, Maximilian A C; Habershon, Scott

2017-07-11

Methods for solving the time-dependent Schrödinger equation via basis set expansion of the wave function can generally be categorized as having either static (time-independent) or dynamic (time-dependent) basis functions. We have recently introduced an alternative simulation approach which represents a middle road between these two extremes, employing dynamic (classical-like) trajectories to create a static basis set of Gaussian wavepackets in regions of phase-space relevant to future propagation of the wave function [J. Chem. Theory Comput., 11, 8 (2015)]. Here, we propose and test a modification of our methodology which aims to reduce the size of basis sets generated in our original scheme. In particular, we employ short-time classical trajectories to continuously generate new basis functions for short-time quantum propagation of the wave function; to avoid the continued growth of the basis set describing the time-dependent wave function, we employ Matching Pursuit to periodically minimize the number of basis functions required to accurately describe the wave function. Overall, this approach generates a basis set which is adapted to evolution of the wave function while also being as small as possible. In applications to challenging benchmark problems, namely a 4-dimensional model of photoexcited pyrazine and three different double-well tunnelling problems, we find that our new scheme enables accurate wave function propagation with basis sets which are around an order-of-magnitude smaller than our original trajectory-guided basis set methodology, highlighting the benefits of adaptive strategies for wave function propagation.

Adaptive Output-Feedback Neural Control of Switched Uncertain Nonlinear Systems With Average Dwell Time.

PubMed

Long, Lijun; Zhao, Jun

2015-07-01

This paper investigates the problem of adaptive neural tracking control via output-feedback for a class of switched uncertain nonlinear systems without the measurements of the system states. The unknown control signals are approximated directly by neural networks. A novel adaptive neural control technique for the problem studied is set up by exploiting the average dwell time method and backstepping. A switched filter and different update laws are designed to reduce the conservativeness caused by adoption of a common observer and a common update law for all subsystems. The proposed controllers of subsystems guarantee that all closed-loop signals remain bounded under a class of switching signals with average dwell time, while the output tracking error converges to a small neighborhood of the origin. As an application of the proposed design method, adaptive output feedback neural tracking controllers for a mass-spring-damper system are constructed.

Conflict adaptation in patients diagnosed with schizophrenia.

PubMed

Abrahamse, Elger; Ruitenberg, Marit; Boddewyn, Sarah; Oreel, Edith; de Schryver, Maarten; Morrens, Manuel; van Dijck, Jean-Philippe

2017-11-01

Cognitive control impairments may contribute strongly to the overall cognitive deficits observed in patients diagnosed with schizophrenia. In the current study we explore a specific cognitive control function referred to as conflict adaptation. Previous studies on conflict adaptation in schizophrenia showed equivocal results, and, moreover, were plagued by confounded research designs. Here we assessed for the first time conflict adaptation in schizophrenia with a design that avoided the major confounds of feature integration and stimulus-response contingency learning. Sixteen patients diagnosed with schizophrenia and sixteen healthy, matched controls performed a vocal Stroop task to determine the congruency sequence effect - a marker of conflict adaptation. A reliable congruency sequence effect was observed for both healthy controls and patients diagnosed with schizophrenia. These findings indicate that schizophrenia is not necessarily accompanied by impaired conflict adaptation. As schizophrenia has been related to abnormal functioning in core conflict adaptation areas such as anterior cingulate and dorsolateral prefrontal cortex, further research is required to better understand the precise impact of such abnormal brain functioning at the behavioral level. Copyright © 2017 Elsevier B.V. All rights reserved.

Adaptation of sensor morphology: an integrative view of perception from biologically inspired robotics perspective

PubMed Central

Nurzaman, Surya G.

2016-01-01

Sensor morphology, the morphology of a sensing mechanism which plays a role of shaping the desired response from physical stimuli from surroundings to generate signals usable as sensory information, is one of the key common aspects of sensing processes. This paper presents a structured review of researches on bioinspired sensor morphology implemented in robotic systems, and discusses the fundamental design principles. Based on literature review, we propose two key arguments: first, owing to its synthetic nature, biologically inspired robotics approach is a unique and powerful methodology to understand the role of sensor morphology and how it can evolve and adapt to its task and environment. Second, a consideration of an integrative view of perception by looking into multidisciplinary and overarching mechanisms of sensor morphology adaptation across biology and engineering enables us to extract relevant design principles that are important to extend our understanding of the unfinished concepts in sensing and perception. PMID:27499843

Tightly Coupled Integration of GPS Ambiguity Fixed Precise Point Positioning and MEMS-INS through a Troposphere-Constrained Adaptive Kalman Filter

PubMed Central

Han, Houzeng; Xu, Tianhe; Wang, Jian

2016-01-01

Precise Point Positioning (PPP) makes use of the undifferenced pseudorange and carrier phase measurements with ionospheric-free (IF) combinations to achieve centimeter-level positioning accuracy. Conventionally, the IF ambiguities are estimated as float values. To improve the PPP positioning accuracy and shorten the convergence time, the integer phase clock model with between-satellites single-difference (BSSD) operation is used to recover the integer property. However, the continuity and availability of stand-alone PPP is largely restricted by the observation environment. The positioning performance will be significantly degraded when GPS operates under challenging environments, if less than five satellites are present. A commonly used approach is integrating a low cost inertial sensor to improve the positioning performance and robustness. In this study, a tightly coupled (TC) algorithm is implemented by integrating PPP with inertial navigation system (INS) using an Extended Kalman filter (EKF). The navigation states, inertial sensor errors and GPS error states are estimated together. The troposphere constrained approach, which utilizes external tropospheric delay as virtual observation, is applied to further improve the ambiguity-fixed height positioning accuracy, and an improved adaptive filtering strategy is implemented to improve the covariance modelling considering the realistic noise effect. A field vehicular test with a geodetic GPS receiver and a low cost inertial sensor was conducted to validate the improvement on positioning performance with the proposed approach. The results show that the positioning accuracy has been improved with inertial aiding. Centimeter-level positioning accuracy is achievable during the test, and the PPP/INS TC integration achieves a fast re-convergence after signal outages. For troposphere constrained solutions, a significant improvement for the height component has been obtained. The overall positioning accuracies of the height

Health risk in the context of climate change and adaptation - Concept and mapping as an integrated approach

NASA Astrophysics Data System (ADS)

Kienberger, S.; Notenbaert, A.; Zeil, P.; Bett, B.; Hagenlocher, M.; Omolo, A.

2012-04-01

Climate change has been stated as being one of the greatest challenges to global health in the current century. Climate change impacts on human health and the socio-economic and related poverty consequences are however still poorly understood. While epidemiological issues are strongly coupled with environmental and climatic parameters, the social and economic circumstances of populations might be of equal or even greater importance when trying to identify vulnerable populations and design appropriate and well-targeted adaptation measures. The inter-linkage between climate change, human health risk and socio-economic impacts remains an important - but largely outstanding - research field. We present an overview on how risk is traditionally being conceptualised in the human health domain and reflect critically on integrated approaches as being currently used in the climate change context. The presentation will also review existing approaches, and how they can be integrated towards adaptation tools. Following this review, an integrated risk concept is being presented, which has been currently adapted under the EC FP7 research project (HEALTHY FUTURES; http://www.healthyfutures.eu/). In this approach, health risk is not only defined through the disease itself (as hazard) but also by the inherent vulnerability of the system, population or region under study. It is in fact the interaction of environment and society that leads to the development of diseases and the subsequent risk of being negatively affected by it. In this conceptual framework vulnerability is being attributed to domains of lack of resilience as well as underlying preconditions determining susceptibilities. To fulfil a holistic picture vulnerability can be associated to social, economic, environmental, institutional, cultural and physical dimensions. The proposed framework also establishes the important nexus to adaptation and how different measures can be related to avoid disease outbreaks, reduce

Integrated Detection and Prediction of Influenza Activity for Real-Time Surveillance: Algorithm Design

PubMed Central

2017-01-01

Background Influenza is a viral respiratory disease capable of causing epidemics that represent a threat to communities worldwide. The rapidly growing availability of electronic “big data” from diagnostic and prediagnostic sources in health care and public health settings permits advance of a new generation of methods for local detection and prediction of winter influenza seasons and influenza pandemics. Objective The aim of this study was to present a method for integrated detection and prediction of influenza virus activity in local settings using electronically available surveillance data and to evaluate its performance by retrospective application on authentic data from a Swedish county. Methods An integrated detection and prediction method was formally defined based on a design rationale for influenza detection and prediction methods adapted for local surveillance. The novel method was retrospectively applied on data from the winter influenza season 2008-09 in a Swedish county (population 445,000). Outcome data represented individuals who met a clinical case definition for influenza (based on International Classification of Diseases version 10 [ICD-10] codes) from an electronic health data repository. Information from calls to a telenursing service in the county was used as syndromic data source. Results The novel integrated detection and prediction method is based on nonmechanistic statistical models and is designed for integration in local health information systems. The method is divided into separate modules for detection and prediction of local influenza virus activity. The function of the detection module is to alert for an upcoming period of increased load of influenza cases on local health care (using influenza-diagnosis data), whereas the function of the prediction module is to predict the timing of the activity peak (using syndromic data) and its intensity (using influenza-diagnosis data). For detection modeling, exponential regression was used

From Dinosaurs to Modern Bird Diversity: Extending the Time Scale of Adaptive Radiation

PubMed Central

Moen, Daniel; Morlon, Hélène

2014-01-01

What explains why some groups of organisms, like birds, are so species rich? And what explains their extraordinary ecological diversity, ranging from large, flightless birds to small migratory species that fly thousand of kilometers every year? These and similar questions have spurred great interest in adaptive radiation, the diversification of ecological traits in a rapidly speciating group of organisms. Although the initial formulation of modern concepts of adaptive radiation arose from consideration of the fossil record, rigorous attempts to identify adaptive radiation in the fossil record are still uncommon. Moreover, most studies of adaptive radiation concern groups that are less than 50 million years old. Thus, it is unclear how important adaptive radiation is over temporal scales that span much larger portions of the history of life. In this issue, Benson et al. test the idea of a “deep-time” adaptive radiation in dinosaurs, compiling and using one of the most comprehensive phylogenetic and body-size datasets for fossils. Using recent phylogenetic statistical methods, they find that in most clades of dinosaurs there is a strong signal of an “early burst” in body-size evolution, a predicted pattern of adaptive radiation in which rapid trait evolution happens early in a group's history and then slows down. They also find that body-size evolution did not slow down in the lineage leading to birds, hinting at why birds survived to the present day and diversified. This paper represents one of the most convincing attempts at understanding deep-time adaptive radiations. PMID:24802950

An adaptable navigation strategy for Virtual Microscopy from mobile platforms.

PubMed

Corredor, Germán; Romero, Eduardo; Iregui, Marcela

2015-04-01

Real integration of Virtual Microscopy with the pathologist service workflow requires the design of adaptable strategies for any hospital service to interact with a set of Whole Slide Images. Nowadays, mobile devices have the actual potential of supporting an online pervasive network of specialists working together. However, such devices are still very limited. This article introduces a novel highly adaptable strategy for streaming and visualizing WSI from mobile devices. The presented approach effectively exploits and extends the granularity of the JPEG2000 standard and integrates it with different strategies to achieve a lossless, loosely-coupled, decoder and platform independent implementation, adaptable to any interaction model. The performance was evaluated by two expert pathologists interacting with a set of 20 virtual slides. The method efficiently uses the available device resources: the memory usage did not exceed a 7% of the device capacity while the decoding times were smaller than the 200 ms per Region of Interest, i.e., a window of 256×256 pixels. This model is easily adaptable to other medical imaging scenarios. Copyright © 2015 Elsevier Inc. All rights reserved.

Anterior Cingulate Cortex Instigates Adaptive Switches in Choice by Integrating Immediate and Delayed Components of Value in Ventromedial Prefrontal Cortex

PubMed Central

Guitart-Masip, Marc; Kurth-Nelson, Zeb; Dolan, Raymond J.

2014-01-01

Actions can lead to an immediate reward or punishment and a complex set of delayed outcomes. Adaptive choice necessitates the brain track and integrate both of these potential consequences. Here, we designed a sequential task whereby the decision to exploit or forego an available offer was contingent on comparing immediate value and a state-dependent future cost of expending a limited resource. Crucially, the dynamics of the task demanded frequent switches in policy based on an online computation of changing delayed consequences. We found that human subjects choose on the basis of a near-optimal integration of immediate reward and delayed consequences, with the latter computed in a prefrontal network. Within this network, anterior cingulate cortex (ACC) was dynamically coupled to ventromedial prefrontal cortex (vmPFC) when adaptive switches in choice were required. Our results suggest a choice architecture whereby interactions between ACC and vmPFC underpin an integration of immediate and delayed components of value to support flexible policy switching that accommodates the potential delayed consequences of an action. PMID:24573291

Anterior cingulate cortex instigates adaptive switches in choice by integrating immediate and delayed components of value in ventromedial prefrontal cortex.

PubMed

Economides, Marcos; Guitart-Masip, Marc; Kurth-Nelson, Zeb; Dolan, Raymond J

2014-02-26

Actions can lead to an immediate reward or punishment and a complex set of delayed outcomes. Adaptive choice necessitates the brain track and integrate both of these potential consequences. Here, we designed a sequential task whereby the decision to exploit or forego an available offer was contingent on comparing immediate value and a state-dependent future cost of expending a limited resource. Crucially, the dynamics of the task demanded frequent switches in policy based on an online computation of changing delayed consequences. We found that human subjects choose on the basis of a near-optimal integration of immediate reward and delayed consequences, with the latter computed in a prefrontal network. Within this network, anterior cingulate cortex (ACC) was dynamically coupled to ventromedial prefrontal cortex (vmPFC) when adaptive switches in choice were required. Our results suggest a choice architecture whereby interactions between ACC and vmPFC underpin an integration of immediate and delayed components of value to support flexible policy switching that accommodates the potential delayed consequences of an action.

Probabilistic inference under time pressure leads to a cortical-to-subcortical shift in decision evidence integration.

PubMed

Oh-Descher, Hanna; Beck, Jeffrey M; Ferrari, Silvia; Sommer, Marc A; Egner, Tobias

2017-11-15

Real-life decision-making often involves combining multiple probabilistic sources of information under finite time and cognitive resources. To mitigate these pressures, people "satisfice", foregoing a full evaluation of all available evidence to focus on a subset of cues that allow for fast and "good-enough" decisions. Although this form of decision-making likely mediates many of our everyday choices, very little is known about the way in which the neural encoding of cue information changes when we satisfice under time pressure. Here, we combined human functional magnetic resonance imaging (fMRI) with a probabilistic classification task to characterize neural substrates of multi-cue decision-making under low (1500 ms) and high (500 ms) time pressure. Using variational Bayesian inference, we analyzed participants' choices to track and quantify cue usage under each experimental condition, which was then applied to model the fMRI data. Under low time pressure, participants performed near-optimally, appropriately integrating all available cues to guide choices. Both cortical (prefrontal and parietal cortex) and subcortical (hippocampal and striatal) regions encoded individual cue weights, and activity linearly tracked trial-by-trial variations in the amount of evidence and decision uncertainty. Under increased time pressure, participants adaptively shifted to using a satisficing strategy by discounting the least informative cue in their decision process. This strategic change in decision-making was associated with an increased involvement of the dopaminergic midbrain, striatum, thalamus, and cerebellum in representing and integrating cue values. We conclude that satisficing the probabilistic inference process under time pressure leads to a cortical-to-subcortical shift in the neural drivers of decisions. Copyright © 2017 Elsevier Inc. All rights reserved.

Optimal adaptive control for quantum metrology with time-dependent Hamiltonians.

PubMed

Pang, Shengshi; Jordan, Andrew N

2017-03-09

Quantum metrology has been studied for a wide range of systems with time-independent Hamiltonians. For systems with time-dependent Hamiltonians, however, due to the complexity of dynamics, little has been known about quantum metrology. Here we investigate quantum metrology with time-dependent Hamiltonians to bridge this gap. We obtain the optimal quantum Fisher information for parameters in time-dependent Hamiltonians, and show proper Hamiltonian control is generally necessary to optimize the Fisher information. We derive the optimal Hamiltonian control, which is generally adaptive, and the measurement scheme to attain the optimal Fisher information. In a minimal example of a qubit in a rotating magnetic field, we find a surprising result that the fundamental limit of T 2 time scaling of quantum Fisher information can be broken with time-dependent Hamiltonians, which reaches T 4 in estimating the rotation frequency of the field. We conclude by considering level crossings in the derivatives of the Hamiltonians, and point out additional control is necessary for that case.

Optimal adaptive control for quantum metrology with time-dependent Hamiltonians

PubMed Central

Pang, Shengshi; Jordan, Andrew N.

2017-01-01

Quantum metrology has been studied for a wide range of systems with time-independent Hamiltonians. For systems with time-dependent Hamiltonians, however, due to the complexity of dynamics, little has been known about quantum metrology. Here we investigate quantum metrology with time-dependent Hamiltonians to bridge this gap. We obtain the optimal quantum Fisher information for parameters in time-dependent Hamiltonians, and show proper Hamiltonian control is generally necessary to optimize the Fisher information. We derive the optimal Hamiltonian control, which is generally adaptive, and the measurement scheme to attain the optimal Fisher information. In a minimal example of a qubit in a rotating magnetic field, we find a surprising result that the fundamental limit of T2 time scaling of quantum Fisher information can be broken with time-dependent Hamiltonians, which reaches T4 in estimating the rotation frequency of the field. We conclude by considering level crossings in the derivatives of the Hamiltonians, and point out additional control is necessary for that case. PMID:28276428

Mechanisms for Rapid Adaptive Control of Motion Processing in Macaque Visual Cortex.

PubMed

McLelland, Douglas; Baker, Pamela M; Ahmed, Bashir; Kohn, Adam; Bair, Wyeth

2015-07-15

signals over a shorter time window when visual motion is fast and a longer window when motion is slow. We investigated the mechanisms underlying this useful adaptation by recording from neurons as they responded to stimuli moving in two different directions at different speeds. Computer simulations of our results enabled us to rule out several candidate theories in favor of a model that integrates across multiple parallel channels that operate at different time scales. Copyright © 2015 the authors 0270-6474/15/3510268-13$15.00/0.

A Developmental Study of Shape Integration Over Space and Time.

ERIC Educational Resources Information Center

Enns, James T.; Girgus, Joan S.

1986-01-01

Three experiments with observers aged 6 to 21 years of age examined the integration of shape information over successive glances. Results indicated age-related improvements in the sequential integration of shape information, both when integration occurs through successive glimpses over space and when information is separated only in time. (HOD)

Adaptive spatial combining for passive time-reversed communications.

PubMed

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.

Decentralized model reference adaptive control of large flexible structures

NASA Technical Reports Server (NTRS)

Lee, Fu-Ming; Fong, I-Kong; Lin, Yu-Hwan

1988-01-01

A decentralized model reference adaptive control (DMRAC) method is developed for large flexible structures (LFS). The development follows that of a centralized model reference adaptive control for LFS that have been shown to be feasible. The proposed method is illustrated using a simply supported beam with collocated actuators and sensors. Results show that the DMRAC can achieve either output regulation or output tracking with adequate convergence, provided the reference model inputs and their time derivatives are integrable, bounded, and approach zero as t approaches infinity.

Intermediate view reconstruction using adaptive disparity search algorithm for real-time 3D processing

NASA Astrophysics Data System (ADS)

Bae, Kyung-hoon; Park, Changhan; Kim, Eun-soo

2008-03-01

In this paper, intermediate view reconstruction (IVR) using adaptive disparity search algorithm (ASDA) is for realtime 3-dimensional (3D) processing proposed. The proposed algorithm can reduce processing time of disparity estimation by selecting adaptive disparity search range. Also, the proposed algorithm can increase the quality of the 3D imaging. That is, by adaptively predicting the mutual correlation between stereo images pair using the proposed algorithm, the bandwidth of stereo input images pair can be compressed to the level of a conventional 2D image and a predicted image also can be effectively reconstructed using a reference image and disparity vectors. From some experiments, stereo sequences of 'Pot Plant' and 'IVO', it is shown that the proposed algorithm improves the PSNRs of a reconstructed image to about 4.8 dB by comparing with that of conventional algorithms, and reduces the Synthesizing time of a reconstructed image to about 7.02 sec by comparing with that of conventional algorithms.

The GFZ real-time GNSS precise positioning service system and its adaption for COMPASS

NASA Astrophysics Data System (ADS)

Li, Xingxing; Ge, Maorong; Zhang, Hongping; Nischan, Thomas; Wickert, Jens

2013-03-01

Motivated by the IGS real-time Pilot Project, GFZ has been developing its own real-time precise positioning service for various applications. An operational system at GFZ is now broadcasting real-time orbits, clocks, global ionospheric model, uncalibrated phase delays and regional atmospheric corrections for standard PPP, PPP with ambiguity fixing, single-frequency PPP and regional augmented PPP. To avoid developing various algorithms for different applications, we proposed a uniform algorithm and implemented it into our real-time software. In the new processing scheme, we employed un-differenced raw observations with atmospheric delays as parameters, which are properly constrained by real-time derived global ionospheric model or regional atmospheric corrections and by the empirical characteristics of the atmospheric delay variation in time and space. The positioning performance in terms of convergence time and ambiguity fixing depends mainly on the quality of the received atmospheric information and the spatial and temporal constraints. The un-differenced raw observation model can not only integrate PPP and NRTK into a seamless positioning service, but also syncretize these two techniques into a unique model and algorithm. Furthermore, it is suitable for both dual-frequency and sing-frequency receivers. Based on the real-time data streams from IGS, EUREF and SAPOS reference networks, we can provide services of global precise point positioning (PPP) with 5-10 cm accuracy, PPP with ambiguity-fixing of 2-5 cm accuracy, PPP using single-frequency receiver with accuracy of better than 50 cm and PPP with regional augmentation for instantaneous ambiguity resolution of 1-3 cm accuracy. We adapted the system for current COMPASS to provide PPP service. COMPASS observations from a regional network of nine stations are used for precise orbit determination and clock estimation in simulated real-time mode, the orbit and clock products are applied for real-time precise point

Hard real-time beam scheduler enables adaptive images in multi-probe systems

NASA Astrophysics Data System (ADS)

Tobias, Richard J.

2014-03-01

Real-time embedded-system concepts were adapted to allow an imaging system to responsively control the firing of multiple probes. Large-volume, operator-independent (LVOI) imaging would increase the diagnostic utility of ultrasound. An obstacle to this innovation is the inability of current systems to drive multiple transducers dynamically. Commercial systems schedule scanning with static lists of beams to be fired and processed; here we allow an imager to adapt to changing beam schedule demands, as an intelligent response to incoming image data. An example of scheduling changes is demonstrated with a flexible duplex mode two-transducer application mimicking LVOI imaging. Embedded-system concepts allow an imager to responsively control the firing of multiple probes. Operating systems use powerful dynamic scheduling algorithms, such as fixed priority preemptive scheduling. Even real-time operating systems lack the timing constraints required for ultrasound. Particularly for Doppler modes, events must be scheduled with sub-nanosecond precision, and acquired data is useless without this requirement. A successful scheduler needs unique characteristics. To get close to what would be needed in LVOI imaging, we show two transducers scanning different parts of a subjects leg. When one transducer notices flow in a region where their scans overlap, the system reschedules the other transducer to start flow mode and alter its beams to get a view of the observed vessel and produce a flow measurement. The second transducer does this in a focused region only. This demonstrates key attributes of a successful LVOI system, such as robustness against obstructions and adaptive self-correction.

Lost in translation: The challenge of adapting integrated approaches for worker health and safety for low- and middle-income countries.

PubMed

Sorensen, Glorian; Nagler, Eve M; Pawar, Pratibha; Gupta, Prakash C; Pednekar, Mangesh S; Wagner, Gregory R

2017-01-01

To describe the process of adapting an intervention integrating occupational safety and health (OSH) and health promotion for manufacturing worksites in India and the challenges faced in implementing it; and explore how globalization trends may influence the implementation of these integrated approaches in India and other low- and middle-income countries (LMICs). This study-conducted in 22 manufacturing worksites in Mumbai, India-adapted and implemented an evidence-based intervention tested in the U.S. that integrated OSH and tobacco control. The systematic adaptation process included formative research and pilot testing, to ensure that the tested intervention was tailored to the local setting. We used qualitative methods and process evaluation to assess the extent to which this intervention was implemented, and to explore barriers to implementation. While participating worksites agreed to implement this intervention, not all components of the adapted intervention were implemented fully in the 10 worksites assigned to the intervention condition. We found that the OSH infrastructure in India focused predominantly on regulatory compliance, medical screening (secondary prevention) and the treatment of injuries. We observed generally low levels of leadership support and commitment to OSH, evidenced by minimal management participation in the intervention, reluctance to discuss OSH issues with the study team or workers, and little receptivity to recommendations resulting from the industrial hygienist's reports. India presents one example of a LMIC with a rising burden of non-communicable diseases and intensified exposures to both physical and organizational hazards on the job. Our experiences highlight the importance of national and global trends that shape workers' experiences on the job and their related health outcomes. Beyond a singular focus on prevention of non-communicable diseases, coordinated national and international efforts are needed to address worker health

Lost in translation: The challenge of adapting integrated approaches for worker health and safety for low- and middle-income countries

PubMed Central

Nagler, Eve M.; Pawar, Pratibha; Gupta, Prakash C.; Pednekar, Mangesh S.; Wagner, Gregory R.

2017-01-01

Objectives To describe the process of adapting an intervention integrating occupational safety and health (OSH) and health promotion for manufacturing worksites in India and the challenges faced in implementing it; and explore how globalization trends may influence the implementation of these integrated approaches in India and other low- and middle-income countries (LMICs). Methods This study—conducted in 22 manufacturing worksites in Mumbai, India—adapted and implemented an evidence-based intervention tested in the U.S. that integrated OSH and tobacco control. The systematic adaptation process included formative research and pilot testing, to ensure that the tested intervention was tailored to the local setting. We used qualitative methods and process evaluation to assess the extent to which this intervention was implemented, and to explore barriers to implementation. Results While participating worksites agreed to implement this intervention, not all components of the adapted intervention were implemented fully in the 10 worksites assigned to the intervention condition. We found that the OSH infrastructure in India focused predominantly on regulatory compliance, medical screening (secondary prevention) and the treatment of injuries. We observed generally low levels of leadership support and commitment to OSH, evidenced by minimal management participation in the intervention, reluctance to discuss OSH issues with the study team or workers, and little receptivity to recommendations resulting from the industrial hygienist’s reports. Conclusion India presents one example of a LMIC with a rising burden of non-communicable diseases and intensified exposures to both physical and organizational hazards on the job. Our experiences highlight the importance of national and global trends that shape workers’ experiences on the job and their related health outcomes. Beyond a singular focus on prevention of non-communicable diseases, coordinated national and

ADAPTIVE REAL-TIME CARDIAC MRI USING PARADISE: VALIDATION BY THE PHYSIOLOGICALLY IMPROVED NCAT PHANTOM

PubMed Central

Sharif, Behzad; Bresler, Yoram

2013-01-01

Patient-Adaptive Reconstruction and Acquisition Dynamic Imaging with Sensitivity Encoding (PARADISE) is a dynamic MR imaging scheme that optimally combines parallel imaging and model-based adaptive acquisition. In this work, we propose the application of PARADISE to real-time cardiac MRI. We introduce a physiologically improved version of a realistic four-dimensional cardiac-torso (NCAT) phantom, which incorporates natural beat-to-beat heart rate and motion variations. Cardiac cine imaging using PARADISE is simulated and its performance is analyzed by virtue of the improved phantom. Results verify the effectiveness of PARADISE for high resolution un-gated real-time cardiac MRI and its superiority over conventional acquisition methods. PMID:24398475

Integral equation methods for computing likelihoods and their derivatives in the stochastic integrate-and-fire model.

PubMed

Paninski, Liam; Haith, Adrian; Szirtes, Gabor

2008-02-01

We recently introduced likelihood-based methods for fitting stochastic integrate-and-fire models to spike train data. The key component of this method involves the likelihood that the model will emit a spike at a given time t. Computing this likelihood is equivalent to computing a Markov first passage time density (the probability that the model voltage crosses threshold for the first time at time t). Here we detail an improved method for computing this likelihood, based on solving a certain integral equation. This integral equation method has several advantages over the techniques discussed in our previous work: in particular, the new method has fewer free parameters and is easily differentiable (for gradient computations). The new method is also easily adaptable for the case in which the model conductance, not just the input current, is time-varying. Finally, we describe how to incorporate large deviations approximations to very small likelihoods.

Performance Analysis of Hierarchical Group Key Management Integrated with Adaptive Intrusion Detection in Mobile ad hoc Networks

DTIC Science & Technology

2016-04-05

applications in wireless networks such as military battlefields, emergency response, mobile commerce , online gaming, and collaborative work are based on the...www.elsevier.com/locate/peva Performance analysis of hierarchical group key management integrated with adaptive intrusion detection in mobile ad hoc...Accepted 19 September 2010 Available online 26 September 2010 Keywords: Mobile ad hoc networks Intrusion detection Group communication systems Group

Optimal distribution of integration time for intensity measurements in Stokes polarimetry.

PubMed

Li, Xiaobo; Liu, Tiegen; Huang, Bingjing; Song, Zhanjie; Hu, Haofeng

2015-10-19

We consider the typical Stokes polarimetry system, which performs four intensity measurements to estimate a Stokes vector. We show that if the total integration time of intensity measurements is fixed, the variance of the Stokes vector estimator depends on the distribution of the integration time at four intensity measurements. Therefore, by optimizing the distribution of integration time, the variance of the Stokes vector estimator can be decreased. In this paper, we obtain the closed-form solution of the optimal distribution of integration time by employing Lagrange multiplier method. According to the theoretical analysis and real-world experiment, it is shown that the total variance of the Stokes vector estimator can be significantly decreased about 40% in the case discussed in this paper. The method proposed in this paper can effectively decrease the measurement variance and thus statistically improves the measurement accuracy of the polarimetric system.

Efficient integration of spectral features for vehicle tracking utilizing an adaptive sensor

NASA Astrophysics Data System (ADS)

Uzkent, Burak; Hoffman, Matthew J.; Vodacek, Anthony

2015-03-01

Object tracking in urban environments is an important and challenging problem that is traditionally tackled using visible and near infrared wavelengths. By inserting extended data such as spectral features of the objects one can improve the reliability of the identification process. However, huge increase in data created by hyperspectral imaging is usually prohibitive. To overcome the complexity problem, we propose a persistent air-to-ground target tracking system inspired by a state-of-the-art, adaptive, multi-modal sensor. The adaptive sensor is capable of providing panchromatic images as well as the spectra of desired pixels. This addresses the data challenge of hyperspectral tracking by only recording spectral data as needed. Spectral likelihoods are integrated into a data association algorithm in a Bayesian fashion to minimize the likelihood of misidentification. A framework for controlling spectral data collection is developed by incorporating motion segmentation information and prior information from a Gaussian Sum filter (GSF) movement predictions from a multi-model forecasting set. An intersection mask of the surveillance area is extracted from OpenStreetMap source and incorporated into the tracking algorithm to perform online refinement of multiple model set. The proposed system is tested using challenging and realistic scenarios generated in an adverse environment.

An adaptive three-stage extended Kalman filter for nonlinear discrete-time system in presence of unknown inputs.

PubMed

Xiao, Mengli; Zhang, Yongbo; Wang, Zhihua; Fu, Huimin

2018-04-01

Considering the performances of conventional Kalman filter may seriously degrade when it suffers stochastic faults and unknown input, which is very common in engineering problems, a new type of adaptive three-stage extended Kalman filter (AThSEKF) is proposed to solve state and fault estimation in nonlinear discrete-time system under these conditions. The three-stage UV transformation and adaptive forgetting factor are introduced for derivation, and by comparing with the adaptive augmented state extended Kalman filter, it is proven to be uniformly asymptotically stable. Furthermore, the adaptive three-stage extended Kalman filter is applied to a two-dimensional radar tracking scenario to illustrate the effect, and the performance is compared with that of conventional three stage extended Kalman filter (ThSEKF) and the adaptive two-stage extended Kalman filter (ATEKF). The results show that the adaptive three-stage extended Kalman filter is more effective than these two filters when facing the nonlinear discrete-time systems with information of unknown inputs not perfectly known. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

The Crank Nicolson Time Integrator for EMPHASIS.

DOE Office of Scientific and Technical Information (OSTI.GOV)

McGregor, Duncan Alisdair Odum; Love, Edward; Kramer, Richard Michael Jack

2018-03-01

We investigate the use of implicit time integrators for finite element time domain approxi- mations of Maxwell's equations in vacuum. We discretize Maxwell's equations in time using Crank-Nicolson and in 3D space using compatible finite elements. We solve the system by taking a single step of Newton's method and inverting the Eddy-Current Schur complement allowing for the use of standard preconditioning techniques. This approach also generalizes to more complex material models that can include the Unsplit PML. We present verification results and demonstrate performance at CFL numbers up to 1000.

Spatiotemporal topology and temporal sequence identification with an adaptive time-delay neural network

NASA Astrophysics Data System (ADS)

Lin, Daw-Tung; Ligomenides, Panos A.; Dayhoff, Judith E.

1993-08-01

Inspired from the time delays that occur in neurobiological signal transmission, we describe an adaptive time delay neural network (ATNN) which is a powerful dynamic learning technique for spatiotemporal pattern transformation and temporal sequence identification. The dynamic properties of this network are formulated through the adaptation of time-delays and synapse weights, which are adjusted on-line based on gradient descent rules according to the evolution of observed inputs and outputs. We have applied the ATNN to examples that possess spatiotemporal complexity, with temporal sequences that are completed by the network. The ATNN is able to be applied to pattern completion. Simulation results show that the ATNN learns the topology of a circular and figure eight trajectories within 500 on-line training iterations, and reproduces the trajectory dynamically with very high accuracy. The ATNN was also trained to model the Fourier series expansion of the sum of different odd harmonics. The resulting network provides more flexibility and efficiency than the TDNN and allows the network to seek optimal values for time-delays as well as optimal synapse weights.

Adaptive Proactive Inhibitory Control for Embedded Real-Time Applications

PubMed Central

Yang, Shufan; McGinnity, T. Martin; Wong-Lin, KongFatt

2012-01-01

Psychologists have studied the inhibitory control of voluntary movement for many years. In particular, the countermanding of an impending action has been extensively studied. In this work, we propose a neural mechanism for adaptive inhibitory control in a firing-rate type model based on current findings in animal electrophysiological and human psychophysical experiments. We then implement this model on a field-programmable gate array (FPGA) prototyping system, using dedicated real-time hardware circuitry. Our results show that the FPGA-based implementation can run in real-time while achieving behavioral performance qualitatively suggestive of the animal experiments. Implementing such biological inhibitory control in an embedded device can lead to the development of control systems that may be used in more realistic cognitive robotics or in neural prosthetic systems aiding human movement control. PMID:22701420

Deriving adaptive operating rules of hydropower reservoirs using time-varying parameters generated by the EnKF

NASA Astrophysics Data System (ADS)

Feng, Maoyuan; Liu, Pan; Guo, Shenglian; Shi, Liangsheng; Deng, Chao; Ming, Bo

2017-08-01

Operating rules have been used widely to decide reservoir operations because of their capacity for coping with uncertain inflow. However, stationary operating rules lack adaptability; thus, under changing environmental conditions, they cause inefficient reservoir operation. This paper derives adaptive operating rules based on time-varying parameters generated using the ensemble Kalman filter (EnKF). A deterministic optimization model is established to obtain optimal water releases, which are further taken as observations of the reservoir simulation model. The EnKF is formulated to update the operating rules sequentially, providing a series of time-varying parameters. To identify the index that dominates the variations of the operating rules, three hydrologic factors are selected: the reservoir inflow, ratio of future inflow to current available water, and available water. Finally, adaptive operating rules are derived by fitting the time-varying parameters with the identified dominant hydrologic factor. China's Three Gorges Reservoir was selected as a case study. Results show that (1) the EnKF has the capability of capturing the variations of the operating rules, (2) reservoir inflow is the factor that dominates the variations of the operating rules, and (3) the derived adaptive operating rules are effective in improving hydropower benefits compared with stationary operating rules. The insightful findings of this study could be used to help adapt reservoir operations to mitigate the effects of changing environmental conditions.