Sample records for real-time dynamic modeling

  1. Real-Time Dynamic Modeling - Data Information Requirements and Flight Test Results

    NASA Technical Reports Server (NTRS)

    Morelli, Eugene A.; Smith, Mark S.

    2008-01-01

    Practical aspects of identifying dynamic models for aircraft in real time were studied. Topics include formulation of an equation-error method in the frequency domain to estimate non-dimensional stability and control derivatives in real time, data information content for accurate modeling results, and data information management techniques such as data forgetting, incorporating prior information, and optimized excitation. Real-time dynamic modeling was applied to simulation data and flight test data from a modified F-15B fighter aircraft, and to operational flight data from a subscale jet transport aircraft. Estimated parameter standard errors and comparisons with results from a batch output-error method in the time domain were used to demonstrate the accuracy of the identified real-time models.

  2. Real-Time Dynamic Modeling - Data Information Requirements and Flight Test Results

    NASA Technical Reports Server (NTRS)

    Morelli, Eugene A.; Smith, Mark S.

    2010-01-01

    Practical aspects of identifying dynamic models for aircraft in real time were studied. Topics include formulation of an equation-error method in the frequency domain to estimate non-dimensional stability and control derivatives in real time, data information content for accurate modeling results, and data information management techniques such as data forgetting, incorporating prior information, and optimized excitation. Real-time dynamic modeling was applied to simulation data and flight test data from a modified F-15B fighter aircraft, and to operational flight data from a subscale jet transport aircraft. Estimated parameter standard errors, prediction cases, and comparisons with results from a batch output-error method in the time domain were used to demonstrate the accuracy of the identified real-time models.

  3. A channel dynamics model for real-time flood forecasting

    USGS Publications Warehouse

    Hoos, Anne B.; Koussis, Antonis D.; Beale, Guy O.

    1989-01-01

    A new channel dynamics scheme (alternative system predictor in real time (ASPIRE)), designed specifically for real-time river flow forecasting, is introduced to reduce uncertainty in the forecast. ASPIRE is a storage routing model that limits the influence of catchment model forecast errors to the downstream station closest to the catchment. Comparisons with the Muskingum routing scheme in field tests suggest that the ASPIRE scheme can provide more accurate forecasts, probably because discharge observations are used to a maximum advantage and routing reaches (and model errors in each reach) are uncoupled. Using ASPIRE in conjunction with the Kalman filter did not improve forecast accuracy relative to a deterministic updating procedure. Theoretical analysis suggests that this is due to a large process noise to measurement noise ratio.

  4. Real-Time Kinetic Modeling of Voltage-Gated Ion Channels Using Dynamic Clamp

    PubMed Central

    Milescu, Lorin S.; Yamanishi, Tadashi; Ptak, Krzysztof; Mogri, Murtaza Z.; Smith, Jeffrey C.

    2008-01-01

    We propose what to our knowledge is a new technique for modeling the kinetics of voltage-gated ion channels in a functional context, in neurons or other excitable cells. The principle is to pharmacologically block the studied channel type, and to functionally replace it with dynamic clamp, on the basis of a computational model. Then, the parameters of the model are modified in real time (manually or automatically), with the objective of matching the dynamical behavior of the cell (e.g., action potential shape and spiking frequency), but also the transient and steady-state properties of the model (e.g., those derived from voltage-clamp recordings). Through this approach, one may find a model and parameter values that explain both the observed cellular dynamics and the biophysical properties of the channel. We extensively tested the method, focusing on Nav models. Complex Markov models (10–12 states or more) could be accurately integrated in real time at >50 kHz using the transition probability matrix, but not the explicit Euler method. The practicality of the technique was tested with experiments in raphe pacemaker neurons. Through automated real-time fitting, a Hodgkin-Huxley model could be found that reproduced well the action potential shape and the spiking frequency. Adding a virtual axonal compartment with a high density of Nav channels further improved the action potential shape. The computational procedure was implemented in the free QuB software, running under Microsoft Windows and featuring a friendly graphical user interface. PMID:18375511

  5. Dynamic, physical-based landslide susceptibility modelling based on real-time weather data

    NASA Astrophysics Data System (ADS)

    Canli, Ekrem; Glade, Thomas

    2016-04-01

    By now there seem to be a broad consensus that due to human-induced global change the frequency and magnitude of precipitation intensities within extensive rainstorm events is expected to increase in certain parts of the world. Given the fact, that rainfall serves as one of the most common triggers for landslide initiation, also an increased landside activity might be expected. Landslide occurrence is a globally spread phenomenon that clearly needs to be handled by a variety of concepts, methods, and models. However, most of the research done with respect to landslides deals with retrospect cases, thus classical back-analysis approaches do not incorporate real-time data. This is remarkable, as most destructive landslides are related to immediate events due to external triggering factors. Only few works so far addressed real-time dynamic components for spatial landslide susceptibility and hazard assessment. Here we present an approach for integrating real-time web-based rainfall data from different sources into an automated workflow. Rain gauge measurements are interpolated into a continuous raster which in return is directly utilized in a dynamic, physical-based model. We use the Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Analysis (TRIGRS) model that was modified in a way that it is automatically updated with the most recent rainfall raster for producing hourly landslide susceptibility maps on a regional scale. To account for the uncertainties involved in spatial modelling, the model was further adjusted by not only applying single values for given geotechnical parameters, but ranges instead. The values are determined randomly between user-defined thresholds defining the parameter ranges. Consequently, a slope failure probability from a larger number of model runs is computed rather than just the distributed factor of safety. This will ultimately allow a near-real time spatial landslide alert for a given region.

  6. A tool for modeling concurrent real-time computation

    NASA Technical Reports Server (NTRS)

    Sharma, D. D.; Huang, Shie-Rei; Bhatt, Rahul; Sridharan, N. S.

    1990-01-01

    Real-time computation is a significant area of research in general, and in AI in particular. The complexity of practical real-time problems demands use of knowledge-based problem solving techniques while satisfying real-time performance constraints. Since the demands of a complex real-time problem cannot be predicted (owing to the dynamic nature of the environment) powerful dynamic resource control techniques are needed to monitor and control the performance. A real-time computation model for a real-time tool, an implementation of the QP-Net simulator on a Symbolics machine, and an implementation on a Butterfly multiprocessor machine are briefly described.

  7. Faster than Real-Time Dynamic Simulation for Large-Size Power System with Detailed Dynamic Models using High-Performance Computing Platform

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

    Huang, Renke; Jin, Shuangshuang; Chen, Yousu

    This paper presents a faster-than-real-time dynamic simulation software package that is designed for large-size power system dynamic simulation. It was developed on the GridPACKTM high-performance computing (HPC) framework. The key features of the developed software package include (1) faster-than-real-time dynamic simulation for a WECC system (17,000 buses) with different types of detailed generator, controller, and relay dynamic models, (2) a decoupled parallel dynamic simulation algorithm with optimized computation architecture to better leverage HPC resources and technologies, (3) options for HPC-based linear and iterative solvers, (4) hidden HPC details, such as data communication and distribution, to enable development centered on mathematicalmore » models and algorithms rather than on computational details for power system researchers, and (5) easy integration of new dynamic models and related algorithms into the software package.« less

  8. Connectivity-based neurofeedback: Dynamic causal modeling for real-time fMRI☆

    PubMed Central

    Koush, Yury; Rosa, Maria Joao; Robineau, Fabien; Heinen, Klaartje; W. Rieger, Sebastian; Weiskopf, Nikolaus; Vuilleumier, Patrik; Van De Ville, Dimitri; Scharnowski, Frank

    2013-01-01

    Neurofeedback based on real-time fMRI is an emerging technique that can be used to train voluntary control of brain activity. Such brain training has been shown to lead to behavioral effects that are specific to the functional role of the targeted brain area. However, real-time fMRI-based neurofeedback so far was limited to mainly training localized brain activity within a region of interest. Here, we overcome this limitation by presenting near real-time dynamic causal modeling in order to provide feedback information based on connectivity between brain areas rather than activity within a single brain area. Using a visual–spatial attention paradigm, we show that participants can voluntarily control a feedback signal that is based on the Bayesian model comparison between two predefined model alternatives, i.e. the connectivity between left visual cortex and left parietal cortex vs. the connectivity between right visual cortex and right parietal cortex. Our new approach thus allows for training voluntary control over specific functional brain networks. Because most mental functions and most neurological disorders are associated with network activity rather than with activity in a single brain region, this novel approach is an important methodological innovation in order to more directly target functionally relevant brain networks. PMID:23668967

  9. Diffusive real-time dynamics of a particle with Berry curvature

    NASA Astrophysics Data System (ADS)

    Misaki, Kou; Miyashita, Seiji; Nagaosa, Naoto

    2018-02-01

    We study theoretically the influence of Berry phase on the real-time dynamics of the single particle focusing on the diffusive dynamics, i.e., the time dependence of the distribution function. Our model can be applied to the real-time dynamics of intraband relaxation and diffusion of optically excited excitons, trions, or particle-hole pair. We found that the dynamics at the early stage is deeply influenced by the Berry curvature in real space (B ), momentum space (Ω ), and also the crossed space between these two (C ). For example, it is found that Ω induces the rotation of the wave packet and causes the time dependence of the mean square displacement of the particle to be linear in time t at the initial stage; it is qualitatively different from the t3 dependence in the absence of the Berry curvature. It is also found that Ω and C modify the characteristic time scale of the thermal equilibration of momentum distribution. Moreover, the dynamics under various combinations of B ,Ω , and C shows singular behaviors such as the critical slowing down or speeding up of the momentum equilibration and the reversals of the direction of rotations. The relevance of our model for time-resolved experiments in transition metal dichalcogenides is also discussed.

  10. Real-time dynamic simulation of the Cassini spacecraft using DARTS. Part 2: Parallel/vectorized real-time implementation

    NASA Technical Reports Server (NTRS)

    Fijany, A.; Roberts, J. A.; Jain, A.; Man, G. K.

    1993-01-01

    Part 1 of this paper presented the requirements for the real-time simulation of Cassini spacecraft along with some discussion of the DARTS algorithm. Here, in Part 2 we discuss the development and implementation of parallel/vectorized DARTS algorithm and architecture for real-time simulation. Development of the fast algorithms and architecture for real-time hardware-in-the-loop simulation of spacecraft dynamics is motivated by the fact that it represents a hard real-time problem, in the sense that the correctness of the simulation depends on both the numerical accuracy and the exact timing of the computation. For a given model fidelity, the computation should be computed within a predefined time period. Further reduction in computation time allows increasing the fidelity of the model (i.e., inclusion of more flexible modes) and the integration routine.

  11. Real-time simulation of three-dimensional shoulder girdle and arm dynamics.

    PubMed

    Chadwick, Edward K; Blana, Dimitra; Kirsch, Robert F; van den Bogert, Antonie J

    2014-07-01

    Electrical stimulation is a promising technology for the restoration of arm function in paralyzed individuals. Control of the paralyzed arm under electrical stimulation, however, is a challenging problem that requires advanced controllers and command interfaces for the user. A real-time model describing the complex dynamics of the arm would allow user-in-the-loop type experiments where the command interface and controller could be assessed. Real-time models of the arm previously described have not included the ability to model the independently controlled scapula and clavicle, limiting their utility for clinical applications of this nature. The goal of this study therefore was to evaluate the performance and mechanical behavior of a real-time, dynamic model of the arm and shoulder girdle. The model comprises seven segments linked by eleven degrees of freedom and actuated by 138 muscle elements. Polynomials were generated to describe the muscle lines of action to reduce computation time, and an implicit, first-order Rosenbrock formulation of the equations of motion was used to increase simulation step-size. The model simulated flexion of the arm faster than real time, simulation time being 92% of actual movement time on standard desktop hardware. Modeled maximum isometric torque values agreed well with values from the literature, showing that the model simulates the moment-generating behavior of a real human arm. The speed of the model enables experiments where the user controls the virtual arm and receives visual feedback in real time. The ability to optimize potential solutions in simulation greatly reduces the burden on the user during development.

  12. An Optimization Framework for Dynamic, Distributed Real-Time Systems

    NASA Technical Reports Server (NTRS)

    Eckert, Klaus; Juedes, David; Welch, Lonnie; Chelberg, David; Bruggerman, Carl; Drews, Frank; Fleeman, David; Parrott, David; Pfarr, Barbara

    2003-01-01

    Abstract. This paper presents a model that is useful for developing resource allocation algorithms for distributed real-time systems .that operate in dynamic environments. Interesting aspects of the model include dynamic environments, utility and service levels, which provide a means for graceful degradation in resource-constrained situations and support optimization of the allocation of resources. The paper also provides an allocation algorithm that illustrates how to use the model for producing feasible, optimal resource allocations.

  13. Dynamics of symmetry breaking during quantum real-time evolution in a minimal model system.

    PubMed

    Heyl, Markus; Vojta, Matthias

    2014-10-31

    One necessary criterion for the thermalization of a nonequilibrium quantum many-particle system is ergodicity. It is, however, not sufficient in cases where the asymptotic long-time state lies in a symmetry-broken phase but the initial state of nonequilibrium time evolution is fully symmetric with respect to this symmetry. In equilibrium, one particular symmetry-broken state is chosen as a result of an infinitesimal symmetry-breaking perturbation. From a dynamical point of view the question is: Can such an infinitesimal perturbation be sufficient for the system to establish a nonvanishing order during quantum real-time evolution? We study this question analytically for a minimal model system that can be associated with symmetry breaking, the ferromagnetic Kondo model. We show that after a quantum quench from a completely symmetric state the system is able to break its symmetry dynamically and discuss how these features can be observed experimentally.

  14. A simple dynamic engine model for use in a real-time aircraft simulation with thrust vectoring

    NASA Technical Reports Server (NTRS)

    Johnson, Steven A.

    1990-01-01

    A simple dynamic engine model was developed at the NASA Ames Research Center, Dryden Flight Research Facility, for use in thrust vectoring control law development and real-time aircraft simulation. The simple dynamic engine model of the F404-GE-400 engine (General Electric, Lynn, Massachusetts) operates within the aircraft simulator. It was developed using tabular data generated from a complete nonlinear dynamic engine model supplied by the manufacturer. Engine dynamics were simulated using a throttle rate limiter and low-pass filter. Included is a description of a method to account for axial thrust loss resulting from thrust vectoring. In addition, the development of the simple dynamic engine model and its incorporation into the F-18 high alpha research vehicle (HARV) thrust vectoring simulation. The simple dynamic engine model was evaluated at Mach 0.2, 35,000 ft altitude and at Mach 0.7, 35,000 ft altitude. The simple dynamic engine model is within 3 percent of the steady state response, and within 25 percent of the transient response of the complete nonlinear dynamic engine model.

  15. Real-time inverse kinematics and inverse dynamics for lower limb applications using OpenSim

    PubMed Central

    Modenese, L.; Lloyd, D.G.

    2017-01-01

    Real-time estimation of joint angles and moments can be used for rapid evaluation in clinical, sport, and rehabilitation contexts. However, real-time calculation of kinematics and kinetics is currently based on approximate solutions or generic anatomical models. We present a real-time system based on OpenSim solving inverse kinematics and dynamics without simplifications at 2000 frame per seconds with less than 31.5ms of delay. We describe the software architecture, sensitivity analyses to minimise delays and errors, and compare offline and real-time results. This system has the potential to strongly impact current rehabilitation practices enabling the use of personalised musculoskeletal models in real-time. PMID:27723992

  16. Real-time inverse kinematics and inverse dynamics for lower limb applications using OpenSim.

    PubMed

    Pizzolato, C; Reggiani, M; Modenese, L; Lloyd, D G

    2017-03-01

    Real-time estimation of joint angles and moments can be used for rapid evaluation in clinical, sport, and rehabilitation contexts. However, real-time calculation of kinematics and kinetics is currently based on approximate solutions or generic anatomical models. We present a real-time system based on OpenSim solving inverse kinematics and dynamics without simplifications at 2000 frame per seconds with less than 31.5 ms of delay. We describe the software architecture, sensitivity analyses to minimise delays and errors, and compare offline and real-time results. This system has the potential to strongly impact current rehabilitation practices enabling the use of personalised musculoskeletal models in real-time.

  17. Real-time prediction of respiratory motion based on a local dynamic model in an augmented space

    NASA Astrophysics Data System (ADS)

    Hong, S.-M.; Jung, B.-H.; Ruan, D.

    2011-03-01

    Motion-adaptive radiotherapy aims to deliver ablative radiation dose to the tumor target with minimal normal tissue exposure, by accounting for real-time target movement. In practice, prediction is usually necessary to compensate for system latency induced by measurement, communication and control. This work focuses on predicting respiratory motion, which is most dominant for thoracic and abdominal tumors. We develop and investigate the use of a local dynamic model in an augmented space, motivated by the observation that respiratory movement exhibits a locally circular pattern in a plane augmented with a delayed axis. By including the angular velocity as part of the system state, the proposed dynamic model effectively captures the natural evolution of respiratory motion. The first-order extended Kalman filter is used to propagate and update the state estimate. The target location is predicted by evaluating the local dynamic model equations at the required prediction length. This method is complementary to existing work in that (1) the local circular motion model characterizes 'turning', overcoming the limitation of linear motion models; (2) it uses a natural state representation including the local angular velocity and updates the state estimate systematically, offering explicit physical interpretations; (3) it relies on a parametric model and is much less data-satiate than the typical adaptive semiparametric or nonparametric method. We tested the performance of the proposed method with ten RPM traces, using the normalized root mean squared difference between the predicted value and the retrospective observation as the error metric. Its performance was compared with predictors based on the linear model, the interacting multiple linear models and the kernel density estimator for various combinations of prediction lengths and observation rates. The local dynamic model based approach provides the best performance for short to medium prediction lengths under relatively

  18. Real-time prediction of respiratory motion based on a local dynamic model in an augmented space.

    PubMed

    Hong, S-M; Jung, B-H; Ruan, D

    2011-03-21

    Motion-adaptive radiotherapy aims to deliver ablative radiation dose to the tumor target with minimal normal tissue exposure, by accounting for real-time target movement. In practice, prediction is usually necessary to compensate for system latency induced by measurement, communication and control. This work focuses on predicting respiratory motion, which is most dominant for thoracic and abdominal tumors. We develop and investigate the use of a local dynamic model in an augmented space, motivated by the observation that respiratory movement exhibits a locally circular pattern in a plane augmented with a delayed axis. By including the angular velocity as part of the system state, the proposed dynamic model effectively captures the natural evolution of respiratory motion. The first-order extended Kalman filter is used to propagate and update the state estimate. The target location is predicted by evaluating the local dynamic model equations at the required prediction length. This method is complementary to existing work in that (1) the local circular motion model characterizes 'turning', overcoming the limitation of linear motion models; (2) it uses a natural state representation including the local angular velocity and updates the state estimate systematically, offering explicit physical interpretations; (3) it relies on a parametric model and is much less data-satiate than the typical adaptive semiparametric or nonparametric method. We tested the performance of the proposed method with ten RPM traces, using the normalized root mean squared difference between the predicted value and the retrospective observation as the error metric. Its performance was compared with predictors based on the linear model, the interacting multiple linear models and the kernel density estimator for various combinations of prediction lengths and observation rates. The local dynamic model based approach provides the best performance for short to medium prediction lengths under relatively

  19. A real time Pegasus propulsion system model for VSTOL piloted simulation evaluation

    NASA Technical Reports Server (NTRS)

    Mihaloew, J. R.; Roth, S. P.; Creekmore, R.

    1981-01-01

    A real time propulsion system modeling technique suitable for use in man-in-the-loop simulator studies was developd. This technique provides the system accuracy, stability, and transient response required for integrated aircraft and propulsion control system studies. A Pegasus-Harrier propulsion system was selected as a baseline for developing mathematical modeling and simulation techniques for VSTOL. Initially, static and dynamic propulsion system characteristics were modeled in detail to form a nonlinear aerothermodynamic digital computer simulation of a Pegasus engine. From this high fidelity simulation, a real time propulsion model was formulated by applying a piece-wise linear state variable methodology. A hydromechanical and water injection control system was also simulated. The real time dynamic model includes the detail and flexibility required for the evaluation of critical control parameters and propulsion component limits over a limited flight envelope. The model was programmed for interfacing with a Harrier aircraft simulation. Typical propulsion system simulation results are presented.

  20. Making Optic Flow Robust to Dynamic Lighting Conditions for Real-Time Operation

    DTIC Science & Technology

    2016-03-17

    ARL-TR-7629 ● MAR 2016 US Army Research Laboratory Making Optic Flow Robust to Dynamic Lighting Conditions for Real-Time...ARL-TR-7629 ● MAR 2016 US Army Research Laboratory Making Optic Flow Robust to Dynamic Lighting Conditions for Real-Time Operation...SUBTITLE Making Optic Flow Robust to Dynamic Lighting Conditions for Real-Time Operation 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT

  1. Real-time high dynamic range laser scanning microscopy

    NASA Astrophysics Data System (ADS)

    Vinegoni, C.; Leon Swisher, C.; Fumene Feruglio, P.; Giedt, R. J.; Rousso, D. L.; Stapleton, S.; Weissleder, R.

    2016-04-01

    In conventional confocal/multiphoton fluorescence microscopy, images are typically acquired under ideal settings and after extensive optimization of parameters for a given structure or feature, often resulting in information loss from other image attributes. To overcome the problem of selective data display, we developed a new method that extends the imaging dynamic range in optical microscopy and improves the signal-to-noise ratio. Here we demonstrate how real-time and sequential high dynamic range microscopy facilitates automated three-dimensional neural segmentation. We address reconstruction and segmentation performance on samples with different size, anatomy and complexity. Finally, in vivo real-time high dynamic range imaging is also demonstrated, making the technique particularly relevant for longitudinal imaging in the presence of physiological motion and/or for quantification of in vivo fast tracer kinetics during functional imaging.

  2. Real-time electron dynamics for massively parallel excited-state simulations

    NASA Astrophysics Data System (ADS)

    Andrade, Xavier

    The simulation of the real-time dynamics of electrons, based on time dependent density functional theory (TDDFT), is a powerful approach to study electronic excited states in molecular and crystalline systems. What makes the method attractive is its flexibility to simulate different kinds of phenomena beyond the linear-response regime, including strongly-perturbed electronic systems and non-adiabatic electron-ion dynamics. Electron-dynamics simulations are also attractive from a computational point of view. They can run efficiently on massively parallel architectures due to the low communication requirements. Our implementations of electron dynamics, based on the codes Octopus (real-space) and Qball (plane-waves), allow us to simulate systems composed of thousands of atoms and to obtain good parallel scaling up to 1.6 million processor cores. Due to the versatility of real-time electron dynamics and its parallel performance, we expect it to become the method of choice to apply the capabilities of exascale supercomputers for the simulation of electronic excited states.

  3. Hybrid automata models of cardiac ventricular electrophysiology for real-time computational applications.

    PubMed

    Andalam, Sidharta; Ramanna, Harshavardhan; Malik, Avinash; Roop, Parthasarathi; Patel, Nitish; Trew, Mark L

    2016-08-01

    Virtual heart models have been proposed for closed loop validation of safety-critical embedded medical devices, such as pacemakers. These models must react in real-time to off-the-shelf medical devices. Real-time performance can be obtained by implementing models in computer hardware, and methods of compiling classes of Hybrid Automata (HA) onto FPGA have been developed. Models of ventricular cardiac cell electrophysiology have been described using HA which capture the complex nonlinear behavior of biological systems. However, many models that have been used for closed-loop validation of pacemakers are highly abstract and do not capture important characteristics of the dynamic rate response. We developed a new HA model of cardiac cells which captures dynamic behavior and we implemented the model in hardware. This potentially enables modeling the heart with over 1 million dynamic cells, making the approach ideal for closed loop testing of medical devices.

  4. Real-time high dynamic range laser scanning microscopy

    PubMed Central

    Vinegoni, C.; Leon Swisher, C.; Fumene Feruglio, P.; Giedt, R. J.; Rousso, D. L.; Stapleton, S.; Weissleder, R.

    2016-01-01

    In conventional confocal/multiphoton fluorescence microscopy, images are typically acquired under ideal settings and after extensive optimization of parameters for a given structure or feature, often resulting in information loss from other image attributes. To overcome the problem of selective data display, we developed a new method that extends the imaging dynamic range in optical microscopy and improves the signal-to-noise ratio. Here we demonstrate how real-time and sequential high dynamic range microscopy facilitates automated three-dimensional neural segmentation. We address reconstruction and segmentation performance on samples with different size, anatomy and complexity. Finally, in vivo real-time high dynamic range imaging is also demonstrated, making the technique particularly relevant for longitudinal imaging in the presence of physiological motion and/or for quantification of in vivo fast tracer kinetics during functional imaging. PMID:27032979

  5. Coordinated scheduling for dynamic real-time systems

    NASA Technical Reports Server (NTRS)

    Natarajan, Swaminathan; Zhao, Wei

    1994-01-01

    In this project, we addressed issues in coordinated scheduling for dynamic real-time systems. In particular, we concentrated on design and implementation of a new distributed real-time system called R-Shell. The design objective of R-Shell is to provide computing support for space programs that have large, complex, fault-tolerant distributed real-time applications. In R-shell, the approach is based on the concept of scheduling agents, which reside in the application run-time environment, and are customized to provide just those resource management functions which are needed by the specific application. With this approach, we avoid the need for a sophisticated OS which provides a variety of generalized functionality, while still not burdening application programmers with heavy responsibility for resource management. In this report, we discuss the R-Shell approach, summarize the achievement of the project, and describe a preliminary prototype of R-Shell system.

  6. Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes

    PubMed Central

    Bai, Cong; Peng, Zhong-Ren; Lu, Qing-Chang; Sun, Jian

    2015-01-01

    Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes. PMID:26294903

  7. Dynamic Bus Travel Time Prediction Models on Road with Multiple Bus Routes.

    PubMed

    Bai, Cong; Peng, Zhong-Ren; Lu, Qing-Chang; Sun, Jian

    2015-01-01

    Accurate and real-time travel time information for buses can help passengers better plan their trips and minimize waiting times. A dynamic travel time prediction model for buses addressing the cases on road with multiple bus routes is proposed in this paper, based on support vector machines (SVMs) and Kalman filtering-based algorithm. In the proposed model, the well-trained SVM model predicts the baseline bus travel times from the historical bus trip data; the Kalman filtering-based dynamic algorithm can adjust bus travel times with the latest bus operation information and the estimated baseline travel times. The performance of the proposed dynamic model is validated with the real-world data on road with multiple bus routes in Shenzhen, China. The results show that the proposed dynamic model is feasible and applicable for bus travel time prediction and has the best prediction performance among all the five models proposed in the study in terms of prediction accuracy on road with multiple bus routes.

  8. A Practical Approach to Implementing Real-Time Semantics

    NASA Technical Reports Server (NTRS)

    Luettgen, Gerald; Bhat, Girish; Cleaveland, Rance

    1999-01-01

    This paper investigates implementations of process algebras which are suitable for modeling concurrent real-time systems. It suggests an approach for efficiently implementing real-time semantics using dynamic priorities. For this purpose a proces algebra with dynamic priority is defined, whose semantics corresponds one-to-one to traditional real-time semantics. The advantage of the dynamic-priority approach is that it drastically reduces the state-space sizes of the systems in question while preserving all properties of their functional and real-time behavior. The utility of the technique is demonstrated by a case study which deals with the formal modeling and verification of the SCSI-2 bus-protocol. The case study is carried out in the Concurrency Workbench of North Carolina, an automated verification tool in which the process algebra with dynamic priority is implemented. It turns out that the state space of the bus-protocol model is about an order of magnitude smaller than the one resulting from real-time semantics. The accuracy of the model is proved by applying model checking for verifying several mandatory properties of the bus protocol.

  9. Real-Time and High-Fidelity Simulation Environment for Autonomous Ground Vehicle Dynamics

    DTIC Science & Technology

    2013-08-01

    ENGINEERING AND TECHNOLOGY SYMPOSIUM (GVSETS), SET FOR AUG. 21-22, 2013 14. ABSTRACT briefing charts 15. SUBJECT TERMS 16. SECURITY CLASSIFICATION OF: 17...EDL & Aero-Flight DSENDS Airships Planetary & Terrain models SimScape Simulation framework Dshell Flex & Multibody dynamics DARTS 3D...7 DARTS Rigid/Flexible Real-Time Multibody Dynamics Engine Recipient of the NASA Software of the Year Award. Abhinandan Jain, "Robot and

  10. A real-time extension of density matrix embedding theory for non-equilibrium electron dynamics

    NASA Astrophysics Data System (ADS)

    Kretchmer, Joshua S.; Chan, Garnet Kin-Lic

    2018-02-01

    We introduce real-time density matrix embedding theory (DMET), a dynamical quantum embedding theory for computing non-equilibrium electron dynamics in strongly correlated systems. As in the previously developed static DMET, real-time DMET partitions the system into an impurity corresponding to the region of interest coupled to the surrounding environment, which is efficiently represented by a quantum bath of the same size as the impurity. In this work, we focus on a simplified single-impurity time-dependent formulation as a first step toward a multi-impurity theory. The equations of motion of the coupled impurity and bath embedding problem are derived using the time-dependent variational principle. The accuracy of real-time DMET is compared to that of time-dependent complete active space self-consistent field (TD-CASSCF) theory and time-dependent Hartree-Fock (TDHF) theory for a variety of quantum quenches in the single impurity Anderson model (SIAM), in which the Hamiltonian is suddenly changed (quenched) to induce a non-equilibrium state. Real-time DMET shows a marked improvement over the mean-field TDHF, converging to the exact answer even in the non-trivial Kondo regime of the SIAM. However, as expected from analogous behavior in static DMET, the constrained structure of the real-time DMET wavefunction leads to a slower convergence with respect to active space size, in the single-impurity formulation, relative to TD-CASSCF. Our initial results suggest that real-time DMET provides a promising framework to simulate non-equilibrium electron dynamics in which strong electron correlation plays an important role, and lays the groundwork for future multi-impurity formulations.

  11. A real-time extension of density matrix embedding theory for non-equilibrium electron dynamics.

    PubMed

    Kretchmer, Joshua S; Chan, Garnet Kin-Lic

    2018-02-07

    We introduce real-time density matrix embedding theory (DMET), a dynamical quantum embedding theory for computing non-equilibrium electron dynamics in strongly correlated systems. As in the previously developed static DMET, real-time DMET partitions the system into an impurity corresponding to the region of interest coupled to the surrounding environment, which is efficiently represented by a quantum bath of the same size as the impurity. In this work, we focus on a simplified single-impurity time-dependent formulation as a first step toward a multi-impurity theory. The equations of motion of the coupled impurity and bath embedding problem are derived using the time-dependent variational principle. The accuracy of real-time DMET is compared to that of time-dependent complete active space self-consistent field (TD-CASSCF) theory and time-dependent Hartree-Fock (TDHF) theory for a variety of quantum quenches in the single impurity Anderson model (SIAM), in which the Hamiltonian is suddenly changed (quenched) to induce a non-equilibrium state. Real-time DMET shows a marked improvement over the mean-field TDHF, converging to the exact answer even in the non-trivial Kondo regime of the SIAM. However, as expected from analogous behavior in static DMET, the constrained structure of the real-time DMET wavefunction leads to a slower convergence with respect to active space size, in the single-impurity formulation, relative to TD-CASSCF. Our initial results suggest that real-time DMET provides a promising framework to simulate non-equilibrium electron dynamics in which strong electron correlation plays an important role, and lays the groundwork for future multi-impurity formulations.

  12. Electron-phonon thermalization in a scalable method for real-time quantum dynamics

    NASA Astrophysics Data System (ADS)

    Rizzi, Valerio; Todorov, Tchavdar N.; Kohanoff, Jorge J.; Correa, Alfredo A.

    2016-01-01

    We present a quantum simulation method that follows the dynamics of out-of-equilibrium many-body systems of electrons and oscillators in real time. Its cost is linear in the number of oscillators and it can probe time scales from attoseconds to hundreds of picoseconds. Contrary to Ehrenfest dynamics, it can thermalize starting from a variety of initial conditions, including electronic population inversion. While an electronic temperature can be defined in terms of a nonequilibrium entropy, a Fermi-Dirac distribution in general emerges only after thermalization. These results can be used to construct a kinetic model of electron-phonon equilibration based on the explicit quantum dynamics.

  13. A system for EPID-based real-time treatment delivery verification during dynamic IMRT treatment.

    PubMed

    Fuangrod, Todsaporn; Woodruff, Henry C; van Uytven, Eric; McCurdy, Boyd M C; Kuncic, Zdenka; O'Connor, Daryl J; Greer, Peter B

    2013-09-01

    To design and develop a real-time electronic portal imaging device (EPID)-based delivery verification system for dynamic intensity modulated radiation therapy (IMRT) which enables detection of gross treatment delivery errors before delivery of substantial radiation to the patient. The system utilizes a comprehensive physics-based model to generate a series of predicted transit EPID image frames as a reference dataset and compares these to measured EPID frames acquired during treatment. The two datasets are using MLC aperture comparison and cumulative signal checking techniques. The system operation in real-time was simulated offline using previously acquired images for 19 IMRT patient deliveries with both frame-by-frame comparison and cumulative frame comparison. Simulated error case studies were used to demonstrate the system sensitivity and performance. The accuracy of the synchronization method was shown to agree within two control points which corresponds to approximately ∼1% of the total MU to be delivered for dynamic IMRT. The system achieved mean real-time gamma results for frame-by-frame analysis of 86.6% and 89.0% for 3%, 3 mm and 4%, 4 mm criteria, respectively, and 97.9% and 98.6% for cumulative gamma analysis. The system can detect a 10% MU error using 3%, 3 mm criteria within approximately 10 s. The EPID-based real-time delivery verification system successfully detected simulated gross errors introduced into patient plan deliveries in near real-time (within 0.1 s). A real-time radiation delivery verification system for dynamic IMRT has been demonstrated that is designed to prevent major mistreatments in modern radiation therapy.

  14. Physically-Based Modelling and Real-Time Simulation of Fluids.

    NASA Astrophysics Data System (ADS)

    Chen, Jim Xiong

    1995-01-01

    Simulating physically realistic complex fluid behaviors presents an extremely challenging problem for computer graphics researchers. Such behaviors include the effects of driving boats through water, blending differently colored fluids, rain falling and flowing on a terrain, fluids interacting in a Distributed Interactive Simulation (DIS), etc. Such capabilities are useful in computer art, advertising, education, entertainment, and training. We present a new method for physically-based modeling and real-time simulation of fluids in computer graphics and dynamic virtual environments. By solving the 2D Navier -Stokes equations using a CFD method, we map the surface into 3D using the corresponding pressures in the fluid flow field. This achieves realistic real-time fluid surface behaviors by employing the physical governing laws of fluids but avoiding extensive 3D fluid dynamics computations. To complement the surface behaviors, we calculate fluid volume and external boundary changes separately to achieve full 3D general fluid flow. To simulate physical activities in a DIS, we introduce a mechanism which uses a uniform time scale proportional to the clock-time and variable time-slicing to synchronize physical models such as fluids in the networked environment. Our approach can simulate many different fluid behaviors by changing the internal or external boundary conditions. It can model different kinds of fluids by varying the Reynolds number. It can simulate objects moving or floating in fluids. It can also produce synchronized general fluid flows in a DIS. Our model can serve as a testbed to simulate many other fluid phenomena which have never been successfully modeled previously.

  15. Real-time simulation model of the HL-20 lifting body

    NASA Technical Reports Server (NTRS)

    Jackson, E. Bruce; Cruz, Christopher I.; Ragsdale, W. A.

    1992-01-01

    A proposed manned spacecraft design, designated the HL-20, has been under investigation at Langley Research Center. Included in that investigation are flight control design and flying qualities studies utilizing a man-in-the-loop real-time simulator. This report documents the current real-time simulation model of the HL-20 lifting body vehicle, known as version 2.0, presently in use at NASA Langley Research Center. Included are data on vehicle aerodynamics, inertias, geometries, guidance and control laws, and cockpit displays and controllers. In addition, trim case and dynamic check case data is provided. The intent of this document is to provide the reader with sufficient information to develop and validate an equivalent simulation of the HL-20 for use in real-time or analytical studies.

  16. Electron-phonon thermalization in a scalable method for real-time quantum dynamics

    DOE PAGES

    Rizzi, Valerio; Todorov, Tchavdar N.; Kohanoff, Jorge J.; ...

    2016-01-27

    Here, we present a quantum simulation method that follows the dynamics of out-of-equilibrium many-body systems of electrons and oscillators in real time. Its cost is linear in the number of oscillators and it can probe time scales from attoseconds to hundreds of picoseconds. Contrary to Ehrenfest dynamics, it can thermalize starting from a variety of initial conditions, including electronic population inversion. While an electronic temperature can be defined in terms of a nonequilibrium entropy, a Fermi-Dirac distribution in general emerges only after thermalization. These results can be used to construct a kinetic model of electron-phonon equilibration based on the explicitmore » quantum dynamics.« less

  17. Conversion and Validation of Distribution System Model from a QSTS-Based Tool to a Real-Time Dynamic Phasor Simulator

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

    Chamana, Manohar; Prabakar, Kumaraguru; Palmintier, Bryan

    A software process is developed to convert distribution network models from a quasi-static time-series tool (OpenDSS) to a real-time dynamic phasor simulator (ePHASORSIM). The description of this process in this paper would be helpful for researchers who intend to perform similar conversions. The converter could be utilized directly by users of real-time simulators who intend to perform software-in-the-loop or hardware-in-the-loop tests on large distribution test feeders for a range of use cases, including testing functions of advanced distribution management systems against a simulated distribution system. In the future, the developers intend to release the conversion tool as open source tomore » enable use by others.« less

  18. Real-time path planning in dynamic virtual environments using multiagent navigation graphs.

    PubMed

    Sud, Avneesh; Andersen, Erik; Curtis, Sean; Lin, Ming C; Manocha, Dinesh

    2008-01-01

    We present a novel approach for efficient path planning and navigation of multiple virtual agents in complex dynamic scenes. We introduce a new data structure, Multi-agent Navigation Graph (MaNG), which is constructed using first- and second-order Voronoi diagrams. The MaNG is used to perform route planning and proximity computations for each agent in real time. Moreover, we use the path information and proximity relationships for local dynamics computation of each agent by extending a social force model [Helbing05]. We compute the MaNG using graphics hardware and present culling techniques to accelerate the computation. We also address undersampling issues and present techniques to improve the accuracy of our algorithm. Our algorithm is used for real-time multi-agent planning in pursuit-evasion, terrain exploration and crowd simulation scenarios consisting of hundreds of moving agents, each with a distinct goal.

  19. A real-time spiking cerebellum model for learning robot control.

    PubMed

    Carrillo, Richard R; Ros, Eduardo; Boucheny, Christian; Coenen, Olivier J-M D

    2008-01-01

    We describe a neural network model of the cerebellum based on integrate-and-fire spiking neurons with conductance-based synapses. The neuron characteristics are derived from our earlier detailed models of the different cerebellar neurons. We tested the cerebellum model in a real-time control application with a robotic platform. Delays were introduced in the different sensorimotor pathways according to the biological system. The main plasticity in the cerebellar model is a spike-timing dependent plasticity (STDP) at the parallel fiber to Purkinje cell connections. This STDP is driven by the inferior olive (IO) activity, which encodes an error signal using a novel probabilistic low frequency model. We demonstrate the cerebellar model in a robot control system using a target-reaching task. We test whether the system learns to reach different target positions in a non-destructive way, therefore abstracting a general dynamics model. To test the system's ability to self-adapt to different dynamical situations, we present results obtained after changing the dynamics of the robotic platform significantly (its friction and load). The experimental results show that the cerebellar-based system is able to adapt dynamically to different contexts.

  20. Real-Time Parameter Estimation Using Output Error

    NASA Technical Reports Server (NTRS)

    Grauer, Jared A.

    2014-01-01

    Output-error parameter estimation, normally a post- ight batch technique, was applied to real-time dynamic modeling problems. Variations on the traditional algorithm were investigated with the goal of making the method suitable for operation in real time. Im- plementation recommendations are given that are dependent on the modeling problem of interest. Application to ight test data showed that accurate parameter estimates and un- certainties for the short-period dynamics model were available every 2 s using time domain data, or every 3 s using frequency domain data. The data compatibility problem was also solved in real time, providing corrected sensor measurements every 4 s. If uncertainty corrections for colored residuals are omitted, this rate can be increased to every 0.5 s.

  1. A Sarsa(λ)-based control model for real-time traffic light coordination.

    PubMed

    Zhou, Xiaoke; Zhu, Fei; Liu, Quan; Fu, Yuchen; Huang, Wei

    2014-01-01

    Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ)-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ)-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control.

  2. A Sarsa(λ)-Based Control Model for Real-Time Traffic Light Coordination

    PubMed Central

    Zhu, Fei; Liu, Quan; Fu, Yuchen; Huang, Wei

    2014-01-01

    Traffic problems often occur due to the traffic demands by the outnumbered vehicles on road. Maximizing traffic flow and minimizing the average waiting time are the goals of intelligent traffic control. Each junction wants to get larger traffic flow. During the course, junctions form a policy of coordination as well as constraints for adjacent junctions to maximize their own interests. A good traffic signal timing policy is helpful to solve the problem. However, as there are so many factors that can affect the traffic control model, it is difficult to find the optimal solution. The disability of traffic light controllers to learn from past experiences caused them to be unable to adaptively fit dynamic changes of traffic flow. Considering dynamic characteristics of the actual traffic environment, reinforcement learning algorithm based traffic control approach can be applied to get optimal scheduling policy. The proposed Sarsa(λ)-based real-time traffic control optimization model can maintain the traffic signal timing policy more effectively. The Sarsa(λ)-based model gains traffic cost of the vehicle, which considers delay time, the number of waiting vehicles, and the integrated saturation from its experiences to learn and determine the optimal actions. The experiment results show an inspiring improvement in traffic control, indicating the proposed model is capable of facilitating real-time dynamic traffic control. PMID:24592183

  3. Real-time dynamics of high-velocity micro-particle impact

    NASA Astrophysics Data System (ADS)

    Veysset, David; Hsieh, Alex; Kooi, Steve; Maznev, Alex A.; Tang, Shengchang; Olsen, Bradley D.; Nelson, Keith A.

    High-velocity micro-particle impact is important for many areas of science and technology, from space exploration to the development of novel drug delivery platforms. We present real-time observations of supersonic micro-particle impacts using multi-frame imaging. In an all optical laser-induced projectile impact test, a monolayer of micro-particles is placed on a transparent substrate coated with a laser absorbing polymer layer. Ablation of a laser-irradiated polymer region accelerates the micro-particles into free space with speeds up to 1.0 km/s. The particles are monitored during the impact on the target with an ultrahigh-speed multi-frame camera that can record up to 16 images with time resolution as short as 3 ns. In particular, we investigated the high-velocity impact deformation response of poly(urethane urea) (PUU) elastomers to further the fundamental understanding of the molecular influence on dynamical behaviors of PUUs. We show the dynamic-stiffening response of the PUUs and demonstrate the significance of segmental dynamics in the response. We also present movies capturing individual particle impact and penetration in gels, and discuss the observed dynamics. The results will provide an impetus for modeling high-velocity microscale impact responses and high strain rate deformation in polymers, gels, and other materials.

  4. Real-Time Parameter Estimation in the Frequency Domain

    NASA Technical Reports Server (NTRS)

    Morelli, Eugene A.

    2000-01-01

    A method for real-time estimation of parameters in a linear dynamic state-space model was developed and studied. The application is aircraft dynamic model parameter estimation from measured data in flight. Equation error in the frequency domain was used with a recursive Fourier transform for the real-time data analysis. Linear and nonlinear simulation examples and flight test data from the F-18 High Alpha Research Vehicle were used to demonstrate that the technique produces accurate model parameter estimates with appropriate error bounds. Parameter estimates converged in less than one cycle of the dominant dynamic mode, using no a priori information, with control surface inputs measured in flight during ordinary piloted maneuvers. The real-time parameter estimation method has low computational requirements and could be implemented

  5. Nonadiabatic Dynamics for Electrons at Second-Order: Real-Time TDDFT and OSCF2.

    PubMed

    Nguyen, Triet S; Parkhill, John

    2015-07-14

    We develop a new model to simulate nonradiative relaxation and dephasing by combining real-time Hartree-Fock and density functional theory (DFT) with our recent open-systems theory of electronic dynamics. The approach has some key advantages: it has been systematically derived and properly relaxes noninteracting electrons to a Fermi-Dirac distribution. This paper combines the new dissipation theory with an atomistic, all-electron quantum chemistry code and an atom-centered model of the thermal environment. The environment is represented nonempirically and is dependent on molecular structure in a nonlocal way. A production quality, O(N(3)) closed-shell implementation of our theory applicable to realistic molecular systems is presented, including timing information. This scaling implies that the added cost of our nonadiabatic relaxation model, time-dependent open self-consistent field at second order (OSCF2), is computationally inexpensive, relative to adiabatic propagation of real-time time-dependent Hartree-Fock (TDHF) or time-dependent density functional theory (TDDFT). Details of the implementation and numerical algorithm, including factorization and efficiency, are discussed. We demonstrate that OSCF2 approaches the stationary self-consistent field (SCF) ground state when the gap is large relative to k(b)T. The code is used to calculate linear-response spectra including the effects of bath dynamics. Finally, we show how our theory of finite-temperature relaxation can be used to correct ground-state DFT calculations.

  6. Improved real-time dynamics from imaginary frequency lattice simulations

    NASA Astrophysics Data System (ADS)

    Pawlowski, Jan M.; Rothkopf, Alexander

    2018-03-01

    The computation of real-time properties, such as transport coefficients or bound state spectra of strongly interacting quantum fields in thermal equilibrium is a pressing matter. Since the sign problem prevents a direct evaluation of these quantities, lattice data needs to be analytically continued from the Euclidean domain of the simulation to Minkowski time, in general an ill-posed inverse problem. Here we report on a novel approach to improve the determination of real-time information in the form of spectral functions by setting up a simulation prescription in imaginary frequencies. By carefully distinguishing between initial conditions and quantum dynamics one obtains access to correlation functions also outside the conventional Matsubara frequencies. In particular the range between ω0 and ω1 = 2πT, which is most relevant for the inverse problem may be more highly resolved. In combination with the fact that in imaginary frequencies the kernel of the inverse problem is not an exponential but only a rational function we observe significant improvements in the reconstruction of spectral functions, demonstrated in a simple 0+1 dimensional scalar field theory toy model.

  7. Dynamic Beam Solutions for Real-Time Simulation and Control Development of Flexible Rockets

    NASA Technical Reports Server (NTRS)

    Su, Weihua; King, Cecilia K.; Clark, Scott R.; Griffin, Edwin D.; Suhey, Jeffrey D.; Wolf, Michael G.

    2016-01-01

    In this study, flexible rockets are structurally represented by linear beams. Both direct and indirect solutions of beam dynamic equations are sought to facilitate real-time simulation and control development for flexible rockets. The direct solution is completed by numerically integrate the beam structural dynamic equation using an explicit Newmark-based scheme, which allows for stable and fast transient solutions to the dynamics of flexile rockets. Furthermore, in the real-time operation, the bending strain of the beam is measured by fiber optical sensors (FOS) at intermittent locations along the span, while both angular velocity and translational acceleration are measured at a single point by the inertial measurement unit (IMU). Another study in this paper is to find the analytical and numerical solutions of the beam dynamics based on the limited measurement data to facilitate the real-time control development. Numerical studies demonstrate the accuracy of these real-time solutions to the beam dynamics. Such analytical and numerical solutions, when integrated with data processing and control algorithms and mechanisms, have the potential to increase launch availability by processing flight data into the flexible launch vehicle's control system.

  8. Real-time stereo matching using orthogonal reliability-based dynamic programming.

    PubMed

    Gong, Minglun; Yang, Yee-Hong

    2007-03-01

    A novel algorithm is presented in this paper for estimating reliable stereo matches in real time. Based on the dynamic programming-based technique we previously proposed, the new algorithm can generate semi-dense disparity maps using as few as two dynamic programming passes. The iterative best path tracing process used in traditional dynamic programming is replaced by a local minimum searching process, making the algorithm suitable for parallel execution. Most computations are implemented on programmable graphics hardware, which improves the processing speed and makes real-time estimation possible. The experiments on the four new Middlebury stereo datasets show that, on an ATI Radeon X800 card, the presented algorithm can produce reliable matches for 60% approximately 80% of pixels at the rate of 10 approximately 20 frames per second. If needed, the algorithm can be configured for generating full density disparity maps.

  9. Dynamic fiber Bragg grating strain sensor interrogation with real-time measurement

    NASA Astrophysics Data System (ADS)

    Park, Jinwoo; Kwon, Yong Seok; Ko, Myeong Ock; Jeon, Min Yong

    2017-11-01

    We demonstrate a 1550 nm band resonance Fourier-domain mode-locked (FDML) fiber laser with fiber Bragg grating (FBG) array. Using the FDML fiber laser, we successfully demonstrate real-time monitoring of dynamic FBG strain sensor interrogation for structural health monitoring. The resonance FDML fiber laser consists of six multiplexed FBGs, which are arranged in series with delay fiber lengths. It is operated by driving the fiber Fabry-Perot tunable filter (FFP-TF) with a sinusoidal waveform at a frequency corresponding to the round-trip time of the laser cavity. Each FBG forms a laser cavity independently in the FDML fiber laser because the light travels different length for each FBG. The very closely positioned two FBGs in a pair are operated simultaneously with a frequency in the FDML fiber laser. The spatial positions of the sensing pair can be distinguished from the variation of the applied frequency to the FFP-TF. One of the FBGs in the pair is used as a reference signal and the other one is fixed on the piezoelectric transducer stack to apply the dynamic strain. We successfully achieve real-time measurement of the abrupt change of the frequencies applied to the FBG without any signal processing delay. The real-time monitoring system is displayed simultaneously on the monitor for the variation of the two peaks, the modulation interval of the two peaks, and their fast Fourier transform spectrum. The frequency resolution of the dynamic variation could reach up to 0.5 Hz for 2 s integration time. It depends on the integration time to measure the dynamic variation. We believe that the real-time monitoring system will have a potential application for structural health monitoring.

  10. Conversion and Validation of Distribution System Model from a QSTS-Based Tool to a Real-Time Dynamic Phasor Simulator: Preprint

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

    Chamana, Manohar; Prabakar, Kumaraguru; Palmintier, Bryan

    A software process is developed to convert distribution network models from a quasi-static time-series tool (OpenDSS) to a real-time dynamic phasor simulator (ePHASORSIM). The description of this process in this paper would be helpful for researchers who intend to perform similar conversions. The converter could be utilized directly by users of real-time simulators who intend to perform software-in-the-loop or hardware-in-the-loop tests on large distribution test feeders for a range of use cases, including testing functions of advanced distribution management systems against a simulated distribution system. In the future, the developers intend to release the conversion tool as open source tomore » enable use by others.« less

  11. Real-time modulated nanoparticle separation with an ultra-large dynamic range.

    PubMed

    Zeming, Kerwin Kwek; Thakor, Nitish V; Zhang, Yong; Chen, Chia-Hung

    2016-01-07

    Nanoparticles exhibit size-dependent properties which make size-selective purification of proteins, DNA or synthetic nanoparticles essential for bio-analytics, clinical medicine, nano-plasmonics and nano-material sciences. Current purification methods of centrifugation, column chromatography and continuous-flow techniques suffer from particle aggregation, multi-stage process, complex setups and necessary nanofabrication. These increase process costs and time, reduce efficiency and limit dynamic range. Here, we achieve an unprecedented real-time nanoparticle separation (51-1500 nm) using a large-pore (2 μm) deterministic lateral displacement (DLD) device. No external force fields or nanofabrication are required. Instead, we investigated innate long-range electrostatic influences on nanoparticles within a fluid medium at different NaCl ionic concentrations. In this study we account for the electrostatic forces beyond Debye length and showed that they cannot be assumed as negligible especially for precise nanoparticle separation methods such as DLD. Our findings have enabled us to develop a model to simultaneously quantify and modulate the electrostatic force interactions between nanoparticle and micropore. By simply controlling buffer solutions, we achieve dynamic nanoparticle size separation on a single device with a rapid response time (<20 s) and an enlarged dynamic range (>1200%), outperforming standard benchtop centrifuge systems. This novel method and model combines device simplicity, isolation precision and dynamic flexibility, opening opportunities for high-throughput applications in nano-separation for industrial and biological applications.

  12. Holographic entropy and real-time dynamics of quarkonium dissociation in non-Abelian plasma

    DOE PAGES

    Iatrakis, Ioannis; Kharzeev, Dmitri E.

    2016-04-26

    The peak of the heavy quark pair entropy at the deconfinement transition, observed in lattice QCD, suggests that the transition is effectively driven by the increase of the entropy of bound states. The growth of the entropy with the interquark distance leads to the emergent entropic force that induces dissociation of quarkonium states. Since the quark-gluon plasma around the transition point is a strongly coupled system, we use the gauge-gravity duality to study the entropy of heavy quarkonium and the real-time dynamics of its dissociation. In particular, we employ the improved holographic QCD model as a dual description of largemore » N c Yang-Mills theory. Studying the dynamics of the fundamental string between the quarks placed on the boundary, we find that the entropy peaks at the transition point. We also study the real-time dynamics of the system by considering the holographic string falling in the black hole horizon where it equilibrates. As a result, in the vicinity of the deconfinement transition, the dissociation time is found to be less than a fermi, suggesting that the entropic destruction is the dominant dissociation mechanism in this temperature region.« less

  13. Optical Response of Warm Dense Matter Using Real-Time Electron Dynamics

    NASA Astrophysics Data System (ADS)

    Baczewski, Andrew; Shulenburger, Luke; Desjarlais, Michael; Magyar, Rudolph

    2014-03-01

    The extreme temperatures and solid-like densities in warm dense matter present a unique challenge for theory, wherein neither conventional models from condensed matter nor plasma physics capture all of the relevant phenomenology. While Kubo-Greenwood DFT calculations have proven capable of reproducing optical properties of WDM, they require a significant number of virtual orbitals to reach convergence due to their perturbative nature. Real-time TDDFT presents a complementary framework with a number of computationally favorable properties, including reduced cost complexity and better scalability, and has been used to reproduce the optical response of finite and ordered extended systems. We will describe the use of Ehrenfest-TDDFT to evolve coupled electron-nuclear dynamics in WDM systems, and the subsequent evaluation of optical response functions from the real-time electron dynamics. The advantages and disadvantages of this approach will be discussed relative to the current state-of-the-art. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Security Administration under contract DE-AC04-94AL85000.

  14. Dynamics of traffic flow with real-time traffic information

    NASA Astrophysics Data System (ADS)

    Yokoya, Yasushi

    2004-01-01

    We studied dynamics of traffic flow with real-time information provided. Provision of the real-time traffic information based on advancements in telecommunication technology is expected to facilitate the efficient utilization of available road capacity. This system has a potentiality of not only engineering for road usage but also the science of complexity series. In the system, the information plays a role of feedback connecting microscopic and macroscopic phenomena beyond the hierarchical structure of statistical physics. In this paper, we tried to clarify how the information works in a network of traffic flow from the perspective of statistical physics. The dynamical feature of the traffic flow is abstracted by a contrastive study between the nonequilibrium statistical physics and a computer simulation based on cellular automaton. We found that the information disrupts the local equilibrium of traffic flow by a characteristic dissipation process due to interaction between the information and individual vehicles. The dissipative structure was observed in the time evolution of traffic flow driven far from equilibrium as a consequence of the breakdown of the local-equilibrium hypothesis.

  15. VORBrouter: A dynamic data routing system for Real-Time Seismic networks

    NASA Astrophysics Data System (ADS)

    Hansen, T.; Vernon, F.; Lindquist, K.; Orcutt, J.

    2004-12-01

    For anyone who has managed a moderately complex buffered real-time data transport system, the need for reliable adaptive data transport is clear. The ROADNet VORBrouter system, an extension to the ROADNet data catalog system [AGU-2003, Dynamic Dataflow Topology Monitoring for Real-time Seismic Networks], allows dynamic routing of real-time seismic data from sensor to end-user. Traditional networks consist of a series of data buffer computers with data transport interconnections configured by hand. This allows for arbitrarily complex data networks, which can often exceed full comprehension by network administrators, sometimes resulting in data loops or accidental data cutoff. In order to manage data transport systems in the event of a network failure, a network administrator must be called upon to change the data transport paths and to recover the missing data. Using VORBrouter, administrators can sleep at night while still providing 7/24 uninterupted data streams at realistic cost. This software package uses information from the ROADNet data catalog system to route packets around failed link outages and to new consumers in real-time. Dynamic data routing protocols operating on top of the Antelope Data buffering layer allow authorized users to request data sets from their local buffer and to have them delivered from anywhere within the network of buffers. The VORBrouter software also allows for dynamic routing around network outages, and the elimination of duplicate data paths within the network, while maintaining the nearly lossless data transport features exhibited by the underlying Antelope system. We present the design of the VORBrouter system, its features, limitations and some future research directions.

  16. Aircraft Fault Detection Using Real-Time Frequency Response Estimation

    NASA Technical Reports Server (NTRS)

    Grauer, Jared A.

    2016-01-01

    A real-time method for estimating time-varying aircraft frequency responses from input and output measurements was demonstrated. The Bat-4 subscale airplane was used with NASA Langley Research Center's AirSTAR unmanned aerial flight test facility to conduct flight tests and collect data for dynamic modeling. Orthogonal phase-optimized multisine inputs, summed with pilot stick and pedal inputs, were used to excite the responses. The aircraft was tested in its normal configuration and with emulated failures, which included a stuck left ruddervator and an increased command path latency. No prior knowledge of a dynamic model was used or available for the estimation. The longitudinal short period dynamics were investigated in this work. Time-varying frequency responses and stability margins were tracked well using a 20 second sliding window of data, as compared to a post-flight analysis using output error parameter estimation and a low-order equivalent system model. This method could be used in a real-time fault detection system, or for other applications of dynamic modeling such as real-time verification of stability margins during envelope expansion tests.

  17. Dynamic quality of service model for improving performance of multimedia real-time transmission in industrial networks.

    PubMed

    Gopalakrishnan, Ravichandran C; Karunakaran, Manivannan

    2014-01-01

    Nowadays, quality of service (QoS) is very popular in various research areas like distributed systems, multimedia real-time applications and networking. The requirements of these systems are to satisfy reliability, uptime, security constraints and throughput as well as application specific requirements. The real-time multimedia applications are commonly distributed over the network and meet various time constraints across networks without creating any intervention over control flows. In particular, video compressors make variable bit-rate streams that mismatch the constant-bit-rate channels typically provided by classical real-time protocols, severely reducing the efficiency of network utilization. Thus, it is necessary to enlarge the communication bandwidth to transfer the compressed multimedia streams using Flexible Time Triggered- Enhanced Switched Ethernet (FTT-ESE) protocol. FTT-ESE provides automation to calculate the compression level and change the bandwidth of the stream. This paper focuses on low-latency multimedia transmission over Ethernet with dynamic quality-of-service (QoS) management. This proposed framework deals with a dynamic QoS for multimedia transmission over Ethernet with FTT-ESE protocol. This paper also presents distinct QoS metrics based both on the image quality and network features. Some experiments with recorded and live video streams show the advantages of the proposed framework. To validate the solution we have designed and implemented a simulator based on the Matlab/Simulink, which is a tool to evaluate different network architecture using Simulink blocks.

  18. Model-based framework for multi-axial real-time hybrid simulation testing

    NASA Astrophysics Data System (ADS)

    Fermandois, Gaston A.; Spencer, Billie F.

    2017-10-01

    Real-time hybrid simulation is an efficient and cost-effective dynamic testing technique for performance evaluation of structural systems subjected to earthquake loading with rate-dependent behavior. A loading assembly with multiple actuators is required to impose realistic boundary conditions on physical specimens. However, such a testing system is expected to exhibit significant dynamic coupling of the actuators and suffer from time lags that are associated with the dynamics of the servo-hydraulic system, as well as control-structure interaction (CSI). One approach to reducing experimental errors considers a multi-input, multi-output (MIMO) controller design, yielding accurate reference tracking and noise rejection. In this paper, a framework for multi-axial real-time hybrid simulation (maRTHS) testing is presented. The methodology employs a real-time feedback-feedforward controller for multiple actuators commanded in Cartesian coordinates. Kinematic transformations between actuator space and Cartesian space are derived for all six-degrees-offreedom of the moving platform. Then, a frequency domain identification technique is used to develop an accurate MIMO transfer function of the system. Further, a Cartesian-domain model-based feedforward-feedback controller is implemented for time lag compensation and to increase the robustness of the reference tracking for given model uncertainty. The framework is implemented using the 1/5th-scale Load and Boundary Condition Box (LBCB) located at the University of Illinois at Urbana- Champaign. To demonstrate the efficacy of the proposed methodology, a single-story frame subjected to earthquake loading is tested. One of the columns in the frame is represented physically in the laboratory as a cantilevered steel column. For realtime execution, the numerical substructure, kinematic transformations, and controllers are implemented on a digital signal processor. Results show excellent performance of the maRTHS framework when six

  19. Programmable logic construction kits for hyper-real-time neuronal modeling.

    PubMed

    Guerrero-Rivera, Ruben; Morrison, Abigail; Diesmann, Markus; Pearce, Tim C

    2006-11-01

    Programmable logic designs are presented that achieve exact integration of leaky integrate-and-fire soma and dynamical synapse neuronal models and incorporate spike-time dependent plasticity and axonal delays. Highly accurate numerical performance has been achieved by modifying simpler forward-Euler-based circuitry requiring minimal circuit allocation, which, as we show, behaves equivalently to exact integration. These designs have been implemented and simulated at the behavioral and physical device levels, demonstrating close agreement with both numerical and analytical results. By exploiting finely grained parallelism and single clock cycle numerical iteration, these designs achieve simulation speeds at least five orders of magnitude faster than the nervous system, termed here hyper-real-time operation, when deployed on commercially available field-programmable gate array (FPGA) devices. Taken together, our designs form a programmable logic construction kit of commonly used neuronal model elements that supports the building of large and complex architectures of spiking neuron networks for real-time neuromorphic implementation, neurophysiological interfacing, or efficient parameter space investigations.

  20. Real-time dynamic display of registered 4D cardiac MR and ultrasound images using a GPU

    NASA Astrophysics Data System (ADS)

    Zhang, Q.; Huang, X.; Eagleson, R.; Guiraudon, G.; Peters, T. M.

    2007-03-01

    In minimally invasive image-guided surgical interventions, different imaging modalities, such as magnetic resonance imaging (MRI), computed tomography (CT), and real-time three-dimensional (3D) ultrasound (US), can provide complementary, multi-spectral image information. Multimodality dynamic image registration is a well-established approach that permits real-time diagnostic information to be enhanced by placing lower-quality real-time images within a high quality anatomical context. For the guidance of cardiac procedures, it would be valuable to register dynamic MRI or CT with intraoperative US. However, in practice, either the high computational cost prohibits such real-time visualization of volumetric multimodal images in a real-world medical environment, or else the resulting image quality is not satisfactory for accurate guidance during the intervention. Modern graphics processing units (GPUs) provide the programmability, parallelism and increased computational precision to begin to address this problem. In this work, we first outline our research on dynamic 3D cardiac MR and US image acquisition, real-time dual-modality registration and US tracking. Then we describe image processing and optimization techniques for 4D (3D + time) cardiac image real-time rendering. We also present our multimodality 4D medical image visualization engine, which directly runs on a GPU in real-time by exploiting the advantages of the graphics hardware. In addition, techniques such as multiple transfer functions for different imaging modalities, dynamic texture binding, advanced texture sampling and multimodality image compositing are employed to facilitate the real-time display and manipulation of the registered dual-modality dynamic 3D MR and US cardiac datasets.

  1. Transfer of Real-time Dynamic Radiation Environment Assimilation Model; Research to Operation

    NASA Astrophysics Data System (ADS)

    Cho, K. S. F.; Hwang, J.; Shin, D. K.; Kim, G. J.; Morley, S.; Henderson, M. G.; Friedel, R. H.; Reeves, G. D.

    2015-12-01

    Real-time Dynamic Radiation Environment Assimilation Model (rtDREAM) was developed by LANL for nowcast of energetic electrons' flux at the radiation belt to quantify potential risks from radiation damage at the satellites. Assimilated data are from multiple sources including LANL assets (GEO, GPS). For transfer from research to operation of the rtDREAM code, LANL/KSWC/NOAA makes a Memorandum Of Understanding (MOU) on the collaboration between three parts. By this MOU, KWSC/RRA provides all the support for transitioning the research version of DREAM to operations. KASI is primarily responsible for providing all the interfaces between the current scientific output formats of the code and useful space weather products that can be used and accessed through the web. In the second phase, KASI will be responsible in performing the work needed to transform the Van Allen Probes beacon data into "DREAM ready" inputs. KASI will also provide the "operational" code framework and additional data preparation, model output, display and web page codes back to LANL and SWPC. KASI is already a NASA partnering ground station for the Van Allen Probes' space weather beacon data and can here show use and utility of these data for comparison between rtDREAM and observations by web. NOAA has offered to take on some of the data processing tasks specific to the GOES data.

  2. Real-time management of a multipurpose water reservoir with a heteroscedastic inflow model

    NASA Astrophysics Data System (ADS)

    Pianosi, F.; Soncini-Sessa, R.

    2009-10-01

    Stochastic dynamic programming has been extensively used as a method for designing optimal regulation policies for water reservoirs. However, the potential of this method is dramatically reduced by its computational burden, which often forces to introduce strong approximations in the model of the system, especially in the description of the reservoir inflow. In this paper, an approach to partially remedy this problem is proposed and applied to a real world case study. It foresees solving the management problem on-line, using a reduced model of the system and the inflow forecast provided by a dynamic model. By doing so, all the hydrometeorological information that is available in real-time is fully exploited. The model here proposed for the inflow forecasting is a nonlinear, heteroscedastic model that provides both the expected value and the standard deviation of the inflow through dynamic relations. The effectiveness of such model for the purpose of the reservoir regulation is evaluated through simulation and comparison with the results provided by conventional homoscedastic inflow models.

  3. Real-time physics-based 3D biped character animation using an inverted pendulum model.

    PubMed

    Tsai, Yao-Yang; Lin, Wen-Chieh; Cheng, Kuangyou B; Lee, Jehee; Lee, Tong-Yee

    2010-01-01

    We present a physics-based approach to generate 3D biped character animation that can react to dynamical environments in real time. Our approach utilizes an inverted pendulum model to online adjust the desired motion trajectory from the input motion capture data. This online adjustment produces a physically plausible motion trajectory adapted to dynamic environments, which is then used as the desired motion for the motion controllers to track in dynamics simulation. Rather than using Proportional-Derivative controllers whose parameters usually cannot be easily set, our motion tracking adopts a velocity-driven method which computes joint torques based on the desired joint angular velocities. Physically correct full-body motion of the 3D character is computed in dynamics simulation using the computed torques and dynamical model of the character. Our experiments demonstrate that tracking motion capture data with real-time response animation can be achieved easily. In addition, physically plausible motion style editing, automatic motion transition, and motion adaptation to different limb sizes can also be generated without difficulty.

  4. Analysis of real-time numerical integration methods applied to dynamic clamp experiments.

    PubMed

    Butera, Robert J; McCarthy, Maeve L

    2004-12-01

    Real-time systems are frequently used as an experimental tool, whereby simulated models interact in real time with neurophysiological experiments. The most demanding of these techniques is known as the dynamic clamp, where simulated ion channel conductances are artificially injected into a neuron via intracellular electrodes for measurement and stimulation. Methodologies for implementing the numerical integration of the gating variables in real time typically employ first-order numerical methods, either Euler or exponential Euler (EE). EE is often used for rapidly integrating ion channel gating variables. We find via simulation studies that for small time steps, both methods are comparable, but at larger time steps, EE performs worse than Euler. We derive error bounds for both methods, and find that the error can be characterized in terms of two ratios: time step over time constant, and voltage measurement error over the slope factor of the steady-state activation curve of the voltage-dependent gating variable. These ratios reliably bound the simulation error and yield results consistent with the simulation analysis. Our bounds quantitatively illustrate how measurement error restricts the accuracy that can be obtained by using smaller step sizes. Finally, we demonstrate that Euler can be computed with identical computational efficiency as EE.

  5. Spectral functions of a time-periodically driven Falicov-Kimball model: Real-space Floquet dynamical mean-field theory study

    NASA Astrophysics Data System (ADS)

    Qin, Tao; Hofstetter, Walter

    2017-08-01

    We present a systematic study of the spectral functions of a time-periodically driven Falicov-Kimball Hamiltonian. In the high-frequency limit, this system can be effectively described as a Harper-Hofstadter-Falicov-Kimball model. Using real-space Floquet dynamical mean-field theory (DMFT), we take into account the interaction effects and contributions from higher Floquet bands in a nonperturbative way. Our calculations show a high degree of similarity between the interacting driven system and its effective static counterpart with respect to spectral properties. However, as also illustrated by our results, one should bear in mind that Floquet DMFT describes a nonequilibrium steady state, while an effective static Hamiltonian describes an equilibrium state. We further demonstrate the possibility of using real-space Floquet DMFT to study edge states on a cylinder geometry.

  6. Dynamic calibration and analysis of crack tip propagation in energetic materials using real-time radiography

    NASA Astrophysics Data System (ADS)

    Butt, Ali

    Crack propagation in a solid rocket motor environment is difficult to measure directly. This experimental and analytical study evaluated the viability of real-time radiography for detecting bore regression and propellant crack propagation speed. The scope included the quantitative interpretation of crack tip velocity from simulated radiographic images of a burning, center-perforated grain and actual real-time radiographs taken on a rapid-prototyped model that dynamically produced the surface movements modeled in the simulation. The simplified motor simulation portrayed a bore crack that propagated radially at a speed that was 10 times the burning rate of the bore. Comparing the experimental image interpretation with the calibrated surface inputs, measurement accuracies were quantified. The average measurements of the bore radius were within 3% of the calibrated values with a maximum error of 7%. The crack tip speed could be characterized with image processing algorithms, but not with the dynamic calibration data. The laboratory data revealed that noise in the transmitted X-Ray intensity makes sensing the crack tip propagation using changes in the centerline transmitted intensity level impractical using the algorithms employed.

  7. Real time visualization of dynamic magnetic fields with a nanomagnetic ferrolens

    NASA Astrophysics Data System (ADS)

    Markoulakis, Emmanouil; Rigakis, Iraklis; Chatzakis, John; Konstantaras, Antonios; Antonidakis, Emmanuel

    2018-04-01

    Due to advancements in nanomagnetism and latest nanomagnetic materials and devices, a new potential field has been opened up for research and applications which was not possible before. We herein propose a new research field and application for nanomagnetism for the visualization of dynamic magnetic fields in real-time. In short, Nano Magnetic Vision. A new methodology, technique and apparatus were invented and prototyped in order to demonstrate and test this new application. As an application example the visualization of the dynamic magnetic field on a transmitting antenna was chosen. Never seen before high-resolution, photos and real-time color video revealing the actual dynamic magnetic field inside a transmitting radio antenna rod has been captured for the first time. The antenna rod is fed with six hundred volts, orthogonal pulses. This unipolar signal is in the very low frequency (i.e. VLF) range. The signal combined with an extremely short electrical length of the rod, ensures the generation of a relatively strong fluctuating magnetic field, analogue to the signal transmitted, along and inside the antenna. This field is induced into a ferrolens and becomes visible in real-time within the normal human eyes frequency spectrum. The name we have given to the new observation apparatus is, SPIONs Superparamagnetic Ferrolens Microscope (SSFM), a powerful passive scientific observation tool with many other potential applications in the near future.

  8. Real-Time Quantum Dynamics of Long-Range Electronic Excitation Transfer in Plasmonic Nanoantennas.

    PubMed

    Ilawe, Niranjan V; Oviedo, M Belén; Wong, Bryan M

    2017-08-08

    Using large-scale, real-time, quantum dynamics calculations, we present a detailed analysis of electronic excitation transfer (EET) mechanisms in a multiparticle plasmonic nanoantenna system. Specifically, we utilize real-time, time-dependent, density functional tight binding (RT-TDDFTB) to provide a quantum-mechanical description (at an electronic/atomistic level of detail) for characterizing and analyzing these systems, without recourse to classical approximations. We also demonstrate highly long-range electronic couplings in these complex systems and find that the range of these couplings is more than twice the conventional cutoff limit considered by Förster resonance energy transfer (FRET)-based approaches. Furthermore, we attribute these unusually long-ranged electronic couplings to the coherent oscillations of conduction electrons in plasmonic nanoparticles. This long-range nature of plasmonic interactions has important ramifications for EET; in particular, we show that the commonly used "nearest-neighbor" FRET model is inadequate for accurately characterizing EET even in simple plasmonic antenna systems. These findings provide a real-time, quantum-mechanical perspective for understanding EET mechanisms and provide guidance in enhancing plasmonic properties in artificial light-harvesting systems.

  9. Real-time dynamic modelling for the design of a cluster-randomized phase 3 Ebola vaccine trial in Sierra Leone.

    PubMed

    Camacho, A; Eggo, R M; Goeyvaerts, N; Vandebosch, A; Mogg, R; Funk, S; Kucharski, A J; Watson, C H; Vangeneugden, T; Edmunds, W J

    2017-01-23

    Declining incidence and spatial heterogeneity complicated the design of phase 3 Ebola vaccine trials during the tail of the 2013-16 Ebola virus disease (EVD) epidemic in West Africa. Mathematical models can provide forecasts of expected incidence through time and can account for both vaccine efficacy in participants and effectiveness in populations. Determining expected disease incidence was critical to calculating power and determining trial sample size. In real-time, we fitted, forecasted, and simulated a proposed phase 3 cluster-randomized vaccine trial for a prime-boost EVD vaccine in three candidate regions in Sierra Leone. The aim was to forecast trial feasibility in these areas through time and guide study design planning. EVD incidence was highly variable during the epidemic, especially in the declining phase. Delays in trial start date were expected to greatly reduce the ability to discern an effect, particularly as a trial with an effective vaccine would cause the epidemic to go extinct more quickly in the vaccine arm. Real-time updates of the model allowed decision-makers to determine how trial feasibility changed with time. This analysis was useful for vaccine trial planning because we simulated effectiveness as well as efficacy, which is possible with a dynamic transmission model. It contributed to decisions on choice of trial location and feasibility of the trial. Transmission models should be utilised as early as possible in the design process to provide mechanistic estimates of expected incidence, with which decisions about sample size, location, timing, and feasibility can be determined. Copyright © 2016. Published by Elsevier Ltd.

  10. Real-Time Simulation

    NASA Technical Reports Server (NTRS)

    1997-01-01

    Coryphaeus Software, founded in 1989 by former NASA electronic engineer Steve Lakowske, creates real-time 3D software. Designer's Workbench, the company flagship product, is a modeling and simulation tool for the development of both static and dynamic 3D databases. Other products soon followed. Activation, specifically designed for game developers, allows developers to play and test the 3D games before they commit to a target platform. Game publishers can shorten development time and prove the "playability" of the title, maximizing their chances of introducing a smash hit. Another product, EasyT, lets users create massive, realistic representation of Earth terrains that can be viewed and traversed in real time. Finally, EasyScene software control the actions among interactive objects within a virtual world. Coryphaeus products are used on Silican Graphics workstation and supercomputers to simulate real-world performance in synthetic environments. Customers include aerospace, aviation, architectural and engineering firms, game developers, and the entertainment industry.

  11. A meshless EFG-based algorithm for 3D deformable modeling of soft tissue in real-time.

    PubMed

    Abdi, Elahe; Farahmand, Farzam; Durali, Mohammad

    2012-01-01

    The meshless element-free Galerkin method was generalized and an algorithm was developed for 3D dynamic modeling of deformable bodies in real time. The efficacy of the algorithm was investigated in a 3D linear viscoelastic model of human spleen subjected to a time-varying compressive force exerted by a surgical grasper. The model remained stable in spite of the considerably large deformations occurred. There was a good agreement between the results and those of an equivalent finite element model. The computational cost, however, was much lower, enabling the proposed algorithm to be effectively used in real-time applications.

  12. Designing a Dynamic Data Driven Application System for Estimating Real-Time Load of DOC in a River

    NASA Astrophysics Data System (ADS)

    Ouyang, Y.; None

    2011-12-01

    Understanding the dynamics of naturally occurring dissolved organic carbon (DOC) in a river is central to estimating surface water quality, aquatic carbon cycling, and climate change. Currently, determination of DOC in surface water is primarily accomplished by manually collecting samples for laboratory analysis, which requires at least 24 hours. In other words, no effort has been devoted to monitoring real-time variations of DOC in a river due to the lack of suitable and/or cost-effective wireless sensors. However, when considering human health, carbon footprints, and effects of urbanization, industry, and agriculture on water resource supply, timely DOC information may be critical. We have developed here a new paradigm, a dynamic data driven application system (DDDAS), for estimating the real-time load of DOC into a river. This DDDAS consisted of the following four components: (1) a Visual Basic (VB) program for downloading US Geological Survey real-time chlorophyll and discharge data; (2) a STELLA model for evaluating real-time DOC load based on the relationship between chlorophyll a, DOC, and river discharge; (3) a batch file for linking the VB program and STELLA model; and (4) a Microsoft Windows Scheduled Tasks wizard for executing the model and displaying output on a computer screen at selected times. Results show that the real-time load of DOC into the St. Johns River basin near Satsuma, Putnam County, Florida, USA varied over a range from -13,143 to 29,248 kg/h at the selected site in Florida, USA. The negative loads occurred because of the back flow in the estuarine reach of the river. The cumulative load of DOC in the river for the selected site at the end of the simulation (178 hours) was about 1.2 tons. Our results support the utility of the DDDAS developed in this study for estimating the real-time variations of DOC in river ecosystems.

  13. A Dynamic Time Warping Approach to Real-Time Activity Recognition for Food Preparation

    NASA Astrophysics Data System (ADS)

    Pham, Cuong; Plötz, Thomas; Olivier, Patrick

    We present a dynamic time warping based activity recognition system for the analysis of low-level food preparation activities. Accelerometers embedded into kitchen utensils provide continuous sensor data streams while people are using them for cooking. The recognition framework analyzes frames of contiguous sensor readings in real-time with low latency. It thereby adapts to the idiosyncrasies of utensil use by automatically maintaining a template database. We demonstrate the effectiveness of the classification approach by a number of real-world practical experiments on a publically available dataset. The adaptive system shows superior performance compared to a static recognizer. Furthermore, we demonstrate the generalization capabilities of the system by gradually reducing the amount of training samples. The system achieves excellent classification results even if only a small number of training samples is available, which is especially relevant for real-world scenarios.

  14. Real-time dynamics simulation of the Cassini spacecraft using DARTS. Part 1: Functional capabilities and the spatial algebra algorithm

    NASA Technical Reports Server (NTRS)

    Jain, A.; Man, G. K.

    1993-01-01

    This paper describes the Dynamics Algorithms for Real-Time Simulation (DARTS) real-time hardware-in-the-loop dynamics simulator for the National Aeronautics and Space Administration's Cassini spacecraft. The spacecraft model consists of a central flexible body with a number of articulated rigid-body appendages. The demanding performance requirements from the spacecraft control system require the use of a high fidelity simulator for control system design and testing. The DARTS algorithm provides a new algorithmic and hardware approach to the solution of this hardware-in-the-loop simulation problem. It is based upon the efficient spatial algebra dynamics for flexible multibody systems. A parallel and vectorized version of this algorithm is implemented on a low-cost, multiprocessor computer to meet the simulation timing requirements.

  15. Seasonal Influenza Forecasting in Real Time Using the Incidence Decay With Exponential Adjustment Model.

    PubMed

    Nasserie, Tahmina; Tuite, Ashleigh R; Whitmore, Lindsay; Hatchette, Todd; Drews, Steven J; Peci, Adriana; Kwong, Jeffrey C; Friedman, Dara; Garber, Gary; Gubbay, Jonathan; Fisman, David N

    2017-01-01

    Seasonal influenza epidemics occur frequently. Rapid characterization of seasonal dynamics and forecasting of epidemic peaks and final sizes could help support real-time decision-making related to vaccination and other control measures. Real-time forecasting remains challenging. We used the previously described "incidence decay with exponential adjustment" (IDEA) model, a 2-parameter phenomenological model, to evaluate the characteristics of the 2015-2016 influenza season in 4 Canadian jurisdictions: the Provinces of Alberta, Nova Scotia and Ontario, and the City of Ottawa. Model fits were updated weekly with receipt of incident virologically confirmed case counts. Best-fit models were used to project seasonal influenza peaks and epidemic final sizes. The 2015-2016 influenza season was mild and late-peaking. Parameter estimates generated through fitting were consistent in the 2 largest jurisdictions (Ontario and Alberta) and with pooled data including Nova Scotia counts (R 0 approximately 1.4 for all fits). Lower R 0 estimates were generated in Nova Scotia and Ottawa. Final size projections that made use of complete time series were accurate to within 6% of true final sizes, but final size was using pre-peak data. Projections of epidemic peaks stabilized before the true epidemic peak, but these were persistently early (~2 weeks) relative to the true peak. A simple, 2-parameter influenza model provided reasonably accurate real-time projections of influenza seasonal dynamics in an atypically late, mild influenza season. Challenges are similar to those seen with more complex forecasting methodologies. Future work includes identification of seasonal characteristics associated with variability in model performance.

  16. Near real-time traffic routing

    NASA Technical Reports Server (NTRS)

    Yang, Chaowei (Inventor); Xie, Jibo (Inventor); Zhou, Bin (Inventor); Cao, Ying (Inventor)

    2012-01-01

    A near real-time physical transportation network routing system comprising: a traffic simulation computing grid and a dynamic traffic routing service computing grid. The traffic simulator produces traffic network travel time predictions for a physical transportation network using a traffic simulation model and common input data. The physical transportation network is divided into a multiple sections. Each section has a primary zone and a buffer zone. The traffic simulation computing grid includes multiple of traffic simulation computing nodes. The common input data includes static network characteristics, an origin-destination data table, dynamic traffic information data and historical traffic data. The dynamic traffic routing service computing grid includes multiple dynamic traffic routing computing nodes and generates traffic route(s) using the traffic network travel time predictions.

  17. Method for Real-Time Model Based Structural Anomaly Detection

    NASA Technical Reports Server (NTRS)

    Urnes, James M., Sr. (Inventor); Smith, Timothy A. (Inventor); Reichenbach, Eric Y. (Inventor)

    2015-01-01

    A system and methods for real-time model based vehicle structural anomaly detection are disclosed. A real-time measurement corresponding to a location on a vehicle structure during an operation of the vehicle is received, and the real-time measurement is compared to expected operation data for the location to provide a modeling error signal. A statistical significance of the modeling error signal to provide an error significance is calculated, and a persistence of the error significance is determined. A structural anomaly is indicated, if the persistence exceeds a persistence threshold value.

  18. Programming Models for Concurrency and Real-Time

    NASA Astrophysics Data System (ADS)

    Vitek, Jan

    Modern real-time applications are increasingly large, complex and concurrent systems which must meet stringent performance and predictability requirements. Programming those systems require fundamental advances in programming languages and runtime systems. This talk presents our work on Flexotasks, a programming model for concurrent, real-time systems inspired by stream-processing and concurrent active objects. Some of the key innovations in Flexotasks are that it support both real-time garbage collection and region-based memory with an ownership type system for static safety. Communication between tasks is performed by channels with a linear type discipline to avoid copying messages, and by a non-blocking transactional memory facility. We have evaluated our model empirically within two distinct implementations, one based on Purdue’s Ovm research virtual machine framework and the other on Websphere, IBM’s production real-time virtual machine. We have written a number of small programs, as well as a 30 KLOC avionics collision detector application. We show that Flexotasks are capable of executing periodic threads at 10 KHz with a standard deviation of 1.2us and have performance competitive with hand coded C programs.

  19. Real-time Visualization of Tissue Dynamics during Embryonic Development and Malignant Transformation

    NASA Astrophysics Data System (ADS)

    Yamada, Kenneth

    Tissues undergo dramatic changes in organization during embryonic development, as well as during cancer progression and invasion. Recent advances in microscopy now allow us to visualize and track directly the dynamic movements of tissues, their constituent cells, and cellular substructures. This behavior can now be visualized not only in regular tissue culture on flat surfaces (`2D' environments), but also in a variety of 3D environments that may provide physiological cues relevant to understanding dynamics within living organisms. Acquisition of imaging data using various microscopy modalities will provide rich opportunities for determining the roles of physical factors and for computational modeling of complex processes in living tissues. Direct visualization of real-time motility is providing insight into biology spanning multiple spatio-temporal scales. Many cells in our body are known to be in contact with connective tissue and other forms of extracellular matrix. They do so through microscopic cellular adhesions that bind to matrix proteins. In particular, fluorescence microscopy has revealed that cells dynamically probe and bend the matrix at the sites of cell adhesions, and that 3D matrix architecture, stiffness, and elasticity can each regulate migration of the cells. Conversely, cells remodel their local matrix as organs form or tumors invade. Cancer cells can invade tissues using microscopic protrusions that degrade the surrounding matrix; in this case, the local matrix protein concentration is more important for inducing the micro-invasive protrusions than stiffness. On the length scales of tissues, transiently high rates of individual cell movement appear to help establish organ architecture. In fact, isolated cells can self-organize to form tissue structures. In all of these cases, in-depth real-time visualization will ultimately provide the extensive data needed for computer modeling and for testing hypotheses in which physical forces interact

  20. Real-time remote scientific model validation

    NASA Technical Reports Server (NTRS)

    Frainier, Richard; Groleau, Nicolas

    1994-01-01

    This paper describes flight results from the use of a CLIPS-based validation facility to compare analyzed data from a space life sciences (SLS) experiment to an investigator's preflight model. The comparison, performed in real-time, either confirms or refutes the model and its predictions. This result then becomes the basis for continuing or modifying the investigator's experiment protocol. Typically, neither the astronaut crew in Spacelab nor the ground-based investigator team are able to react to their experiment data in real time. This facility, part of a larger science advisor system called Principal Investigator in a Box, was flown on the space shuttle in October, 1993. The software system aided the conduct of a human vestibular physiology experiment and was able to outperform humans in the tasks of data integrity assurance, data analysis, and scientific model validation. Of twelve preflight hypotheses associated with investigator's model, seven were confirmed and five were rejected or compromised.

  1. Using dynamic mode decomposition for real-time background/foreground separation in video

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

    Kutz, Jose Nathan; Grosek, Jacob; Brunton, Steven

    The technique of dynamic mode decomposition (DMD) is disclosed herein for the purpose of robustly separating video frames into background (low-rank) and foreground (sparse) components in real-time. Foreground/background separation is achieved at the computational cost of just one singular value decomposition (SVD) and one linear equation solve, thus producing results orders of magnitude faster than robust principal component analysis (RPCA). Additional techniques, including techniques for analyzing the video for multi-resolution time-scale components, and techniques for reusing computations to allow processing of streaming video in real time, are also described herein.

  2. Modeling ultrafast solvated electronic dynamics using time-dependent density functional theory and polarizable continuum model.

    PubMed

    Liang, Wenkel; Chapman, Craig T; Ding, Feizhi; Li, Xiaosong

    2012-03-01

    A first-principles solvated electronic dynamics method is introduced. Solvent electronic degrees of freedom are coupled to the time-dependent electronic density of a solute molecule by means of the implicit reaction field method, and the entire electronic system is propagated in time. This real-time time-dependent approach, incorporating the polarizable continuum solvation model, is shown to be very effective in describing the dynamical solvation effect in the charge transfer process and yields a consistent absorption spectrum in comparison to the conventional linear response results in solution. © 2012 American Chemical Society

  3. Seasonal Influenza Forecasting in Real Time Using the Incidence Decay With Exponential Adjustment Model

    PubMed Central

    Nasserie, Tahmina; Tuite, Ashleigh R; Whitmore, Lindsay; Hatchette, Todd; Drews, Steven J; Peci, Adriana; Kwong, Jeffrey C; Friedman, Dara; Garber, Gary; Gubbay, Jonathan

    2017-01-01

    Abstract Background Seasonal influenza epidemics occur frequently. Rapid characterization of seasonal dynamics and forecasting of epidemic peaks and final sizes could help support real-time decision-making related to vaccination and other control measures. Real-time forecasting remains challenging. Methods We used the previously described “incidence decay with exponential adjustment” (IDEA) model, a 2-parameter phenomenological model, to evaluate the characteristics of the 2015–2016 influenza season in 4 Canadian jurisdictions: the Provinces of Alberta, Nova Scotia and Ontario, and the City of Ottawa. Model fits were updated weekly with receipt of incident virologically confirmed case counts. Best-fit models were used to project seasonal influenza peaks and epidemic final sizes. Results The 2015–2016 influenza season was mild and late-peaking. Parameter estimates generated through fitting were consistent in the 2 largest jurisdictions (Ontario and Alberta) and with pooled data including Nova Scotia counts (R0 approximately 1.4 for all fits). Lower R0 estimates were generated in Nova Scotia and Ottawa. Final size projections that made use of complete time series were accurate to within 6% of true final sizes, but final size was using pre-peak data. Projections of epidemic peaks stabilized before the true epidemic peak, but these were persistently early (~2 weeks) relative to the true peak. Conclusions A simple, 2-parameter influenza model provided reasonably accurate real-time projections of influenza seasonal dynamics in an atypically late, mild influenza season. Challenges are similar to those seen with more complex forecasting methodologies. Future work includes identification of seasonal characteristics associated with variability in model performance. PMID:29497629

  4. Real-time logic modelling on SpaceWire

    NASA Astrophysics Data System (ADS)

    Zhou, Qiang; Ma, Yunpeng; Fei, Haidong; Wang, Xingyou

    2017-04-01

    A SpaceWire is a standard for on-board satellite networks as the basis for future data-handling architectures. However, it cannot meet the deterministic requirement for safety/time critical application in spacecraft, where the delay of real-time (RT) message streams must be guaranteed. Therefore, SpaceWire-D is developed that provides deterministic delivery over a SpaceWire network. Formal analysis and verification of real-time systems is critical to their development and safe implementation, and is a prerequisite for obtaining their safety certification. Failure to meet specified timing constraints such as deadlines in hard real-time systems may lead to catastrophic results. In this paper, a formal verification method, Real-Time Logic (RTL), has been proposed to specify and verify timing properties of SpaceWire-D network. Based on the principal of SpaceWire-D protocol, we firstly analyze the timing properties of fundamental transactions, such as RMAP WRITE, and RMAP READ. After that, the RMAP WRITE transaction structure is modeled in Real-Time Logic (RTL) and Presburger Arithmetic representations. And then, the associated constraint graph and safety analysis is provided. Finally, it is suggested that RTL method can be useful for the protocol evaluation and provision of recommendation for further protocol evolutions.

  5. Math modeling and computer mechanization for real time simulation of rotary-wing aircraft

    NASA Technical Reports Server (NTRS)

    Howe, R. M.

    1979-01-01

    Mathematical modeling and computer mechanization for real time simulation of rotary wing aircraft is discussed. Error analysis in the digital simulation of dynamic systems, such as rotary wing aircraft is described. The method for digital simulation of nonlinearities with discontinuities, such as exist in typical flight control systems and rotor blade hinges, is discussed.

  6. Real-time dynamics of lattice gauge theories with a few-qubit quantum computer

    NASA Astrophysics Data System (ADS)

    Martinez, Esteban A.; Muschik, Christine A.; Schindler, Philipp; Nigg, Daniel; Erhard, Alexander; Heyl, Markus; Hauke, Philipp; Dalmonte, Marcello; Monz, Thomas; Zoller, Peter; Blatt, Rainer

    2016-06-01

    Gauge theories are fundamental to our understanding of interactions between the elementary constituents of matter as mediated by gauge bosons. However, computing the real-time dynamics in gauge theories is a notorious challenge for classical computational methods. This has recently stimulated theoretical effort, using Feynman’s idea of a quantum simulator, to devise schemes for simulating such theories on engineered quantum-mechanical devices, with the difficulty that gauge invariance and the associated local conservation laws (Gauss laws) need to be implemented. Here we report the experimental demonstration of a digital quantum simulation of a lattice gauge theory, by realizing (1 + 1)-dimensional quantum electrodynamics (the Schwinger model) on a few-qubit trapped-ion quantum computer. We are interested in the real-time evolution of the Schwinger mechanism, describing the instability of the bare vacuum due to quantum fluctuations, which manifests itself in the spontaneous creation of electron-positron pairs. To make efficient use of our quantum resources, we map the original problem to a spin model by eliminating the gauge fields in favour of exotic long-range interactions, which can be directly and efficiently implemented on an ion trap architecture. We explore the Schwinger mechanism of particle-antiparticle generation by monitoring the mass production and the vacuum persistence amplitude. Moreover, we track the real-time evolution of entanglement in the system, which illustrates how particle creation and entanglement generation are directly related. Our work represents a first step towards quantum simulation of high-energy theories using atomic physics experiments—the long-term intention is to extend this approach to real-time quantum simulations of non-Abelian lattice gauge theories.

  7. Real-Time Precise Point Positioning (RTPPP) with raw observations and its application in real-time regional ionospheric VTEC modeling

    NASA Astrophysics Data System (ADS)

    Liu, Teng; Zhang, Baocheng; Yuan, Yunbin; Li, Min

    2018-01-01

    Precise Point Positioning (PPP) is an absolute positioning technology mainly used in post data processing. With the continuously increasing demand for real-time high-precision applications in positioning, timing, retrieval of atmospheric parameters, etc., Real-Time PPP (RTPPP) and its applications have drawn more and more research attention in recent years. This study focuses on the models, algorithms and ionospheric applications of RTPPP on the basis of raw observations, in which high-precision slant ionospheric delays are estimated among others in real time. For this purpose, a robust processing strategy for multi-station RTPPP with raw observations has been proposed and realized, in which real-time data streams and State-Space-Representative (SSR) satellite orbit and clock corrections are used. With the RTPPP-derived slant ionospheric delays from a regional network, a real-time regional ionospheric Vertical Total Electron Content (VTEC) modeling method is proposed based on Adjusted Spherical Harmonic Functions and a Moving-Window Filter. SSR satellite orbit and clock corrections from different IGS analysis centers are evaluated. Ten globally distributed real-time stations are used to evaluate the positioning performances of the proposed RTPPP algorithms in both static and kinematic modes. RMS values of positioning errors in static/kinematic mode are 5.2/15.5, 4.7/17.4 and 12.8/46.6 mm, for north, east and up components, respectively. Real-time slant ionospheric delays from RTPPP are compared with those from the traditional Carrier-to-Code Leveling (CCL) method, in terms of function model, formal precision and between-receiver differences of short baseline. Results show that slant ionospheric delays from RTPPP are more precise and have a much better convergence performance than those from the CCL method in real-time processing. 30 real-time stations from the Asia-Pacific Reference Frame network are used to model the ionospheric VTECs over Australia in real time

  8. Translation of Real-Time Infectious Disease Modeling into Routine Public Health Practice

    PubMed Central

    Chughtai, Abrar A.; Heywood, Anita; Gardner, Lauren M.; Heslop, David J.; MacIntyre, C. Raina

    2017-01-01

    Infectious disease dynamic modeling can support outbreak emergency responses. We conducted a workshop to canvas the needs of stakeholders in Australia for practical, real-time modeling tools for infectious disease emergencies. The workshop was attended by 29 participants who represented government, defense, general practice, and academia stakeholders. We found that modeling is underused in Australia and its potential is poorly understood by practitioners involved in epidemic responses. The development of better modeling tools is desired. Ideal modeling tools for operational use would be easy to use, clearly indicate underlying parameterization and assumptions, and assist with policy and decision making. PMID:28418309

  9. An AD100 implementation of a real-time STOVL aircraft propulsion system

    NASA Technical Reports Server (NTRS)

    Ouzts, Peter J.; Drummond, Colin K.

    1990-01-01

    A real-time dynamic model of the propulsion system for a Short Take-Off and Vertical Landing (STOVL) aircraft was developed for the AD100 simulation environment. The dynamic model was adapted from a FORTRAN based simulation using the dynamic programming capabilities of the AD100 ADSIM simulation language. The dynamic model includes an aerothermal representation of a turbofan jet engine, actuator and sensor models, and a multivariable control system. The AD100 model was tested for agreement with the FORTRAN model and real-time execution performance. The propulsion system model was also linked to an airframe dynamic model to provide an overall STOVL aircraft simulation for the purposes of integrated flight and propulsion control studies. An evaluation of the AD100 system for use as an aircraft simulation environment is included.

  10. Robust Real-Time Musculoskeletal Modeling Driven by Electromyograms.

    PubMed

    Durandau, Guillaume; Farina, Dario; Sartori, Massimo

    2018-03-01

    Current clinical biomechanics involves lengthy data acquisition and time-consuming offline analyses with biomechanical models not operating in real-time for man-machine interfacing. We developed a method that enables online analysis of neuromusculoskeletal function in vivo in the intact human. We used electromyography (EMG)-driven musculoskeletal modeling to simulate all transformations from muscle excitation onset (EMGs) to mechanical moment production around multiple lower-limb degrees of freedom (DOFs). We developed a calibration algorithm that enables adjusting musculoskeletal model parameters specifically to an individual's anthropometry and force-generating capacity. We incorporated the modeling paradigm into a computationally efficient, generic framework that can be interfaced in real-time with any movement data collection system. The framework demonstrated the ability of computing forces in 13 lower-limb muscle-tendon units and resulting moments about three joint DOFs simultaneously in real-time. Remarkably, it was capable of extrapolating beyond calibration conditions, i.e., predicting accurate joint moments during six unseen tasks and one unseen DOF. The proposed framework can dramatically reduce evaluation latency in current clinical biomechanics and open up new avenues for establishing prompt and personalized treatments, as well as for establishing natural interfaces between patients and rehabilitation systems. The integration of EMG with numerical modeling will enable simulating realistic neuromuscular strategies in conditions including muscular/orthopedic deficit, which could not be robustly simulated via pure modeling formulations. This will enable translation to clinical settings and development of healthcare technologies including real-time bio-feedback of internal mechanical forces and direct patient-machine interfacing.

  11. Integration of domain and resource-based reasoning for real-time control in dynamic environments

    NASA Technical Reports Server (NTRS)

    Morgan, Keith; Whitebread, Kenneth R.; Kendus, Michael; Cromarty, Andrew S.

    1993-01-01

    A real-time software controller that successfully integrates domain-based and resource-based control reasoning to perform task execution in a dynamically changing environment is described. The design of the controller is based on the concept of partitioning the process to be controlled into a set of tasks, each of which achieves some process goal. It is assumed that, in general, there are multiple ways (tasks) to achieve a goal. The controller dynamically determines current goals and their current criticality, choosing and scheduling tasks to achieve those goals in the time available. It incorporates rule-based goal reasoning, a TMS-based criticality propagation mechanism, and a real-time scheduler. The controller has been used to build a knowledge-based situation assessment system that formed a major component of a real-time, distributed, cooperative problem solving system built under DARPA contract. It is also being employed in other applications now in progress.

  12. Terrain modeling for real-time simulation

    NASA Astrophysics Data System (ADS)

    Devarajan, Venkat; McArthur, Donald E.

    1993-10-01

    There are many applications, such as pilot training, mission rehearsal, and hardware-in-the- loop simulation, which require the generation of realistic images of terrain and man-made objects in real-time. One approach to meeting this requirement is to drape photo-texture over a planar polygon model of the terrain. The real time system then computes, for each pixel of the output image, the address in a texture map based on the intersection of the line-of-sight vector with the terrain model. High quality image generation requires that the terrain be modeled with a fine mesh of polygons while hardware costs limit the number of polygons which may be displayed for each scene. The trade-off between these conflicting requirements must be made in real-time because it depends on the changing position and orientation of the pilot's eye point or simulated sensor. The traditional approach is to develop a data base consisting of multiple levels of detail (LOD), and then selecting for display LODs as a function of range. This approach could lead to both anomalies in the displayed scene and inefficient use of resources. An approach has been developed in which the terrain is modeled with a set of nested polygons and organized as a tree with each node corresponding to a polygon. This tree is pruned to select the optimum set of nodes for each eye-point position. As the point of view moves, the visibility of some nodes drops below the limit of perception and may be deleted while new points must be added in regions near the eye point. An analytical model has been developed to determine the number of polygons required for display. This model leads to quantitative performance measures of the triangulation algorithm which is useful for optimizing system performance with a limited display capability.

  13. Applying MDA to SDR for Space to Model Real-time Issues

    NASA Technical Reports Server (NTRS)

    Blaser, Tammy M.

    2007-01-01

    NASA space communications systems have the challenge of designing SDRs with highly-constrained Size, Weight and Power (SWaP) resources. A study is being conducted to assess the effectiveness of applying the MDA Platform-Independent Model (PIM) and one or more Platform-Specific Models (PSM) specifically to address NASA space domain real-time issues. This paper will summarize our experiences with applying MDA to SDR for Space to model real-time issues. Real-time issues to be examined, measured, and analyzed are: meeting waveform timing requirements and efficiently applying Real-time Operating System (RTOS) scheduling algorithms, applying safety control measures, and SWaP verification. Real-time waveform algorithms benchmarked with the worst case environment conditions under the heaviest workload will drive the SDR for Space real-time PSM design.

  14. Real-Time Global Nonlinear Aerodynamic Modeling for Learn-To-Fly

    NASA Technical Reports Server (NTRS)

    Morelli, Eugene A.

    2016-01-01

    Flight testing and modeling techniques were developed to accurately identify global nonlinear aerodynamic models for aircraft in real time. The techniques were developed and demonstrated during flight testing of a remotely-piloted subscale propeller-driven fixed-wing aircraft using flight test maneuvers designed to simulate a Learn-To-Fly scenario. Prediction testing was used to evaluate the quality of the global models identified in real time. The real-time global nonlinear aerodynamic modeling algorithm will be integrated and further tested with learning adaptive control and guidance for NASA Learn-To-Fly concept flight demonstrations.

  15. Approaching near real-time biosensing: microfluidic microsphere based biosensor for real-time analyte detection.

    PubMed

    Cohen, Noa; Sabhachandani, Pooja; Golberg, Alexander; Konry, Tania

    2015-04-15

    In this study we describe a simple lab-on-a-chip (LOC) biosensor approach utilizing well mixed microfluidic device and a microsphere-based assay capable of performing near real-time diagnostics of clinically relevant analytes such cytokines and antibodies. We were able to overcome the adsorption kinetics reaction rate-limiting mechanism, which is diffusion-controlled in standard immunoassays, by introducing the microsphere-based assay into well-mixed yet simple microfluidic device with turbulent flow profiles in the reaction regions. The integrated microsphere-based LOC device performs dynamic detection of the analyte in minimal amount of biological specimen by continuously sampling micro-liter volumes of sample per minute to detect dynamic changes in target analyte concentration. Furthermore we developed a mathematical model for the well-mixed reaction to describe the near real time detection mechanism observed in the developed LOC method. To demonstrate the specificity and sensitivity of the developed real time monitoring LOC approach, we applied the device for clinically relevant analytes: Tumor Necrosis Factor (TNF)-α cytokine and its clinically used inhibitor, anti-TNF-α antibody. Based on the reported results herein, the developed LOC device provides continuous sensitive and specific near real-time monitoring method for analytes such as cytokines and antibodies, reduces reagent volumes by nearly three orders of magnitude as well as eliminates the washing steps required by standard immunoassays. Copyright © 2014 Elsevier B.V. All rights reserved.

  16. Real-Time linux dynamic clamp: a fast and flexible way to construct virtual ion channels in living cells.

    PubMed

    Dorval, A D; Christini, D J; White, J A

    2001-10-01

    We describe a system for real-time control of biological and other experiments. This device, based around the Real-Time Linux operating system, was tested specifically in the context of dynamic clamping, a demanding real-time task in which a computational system mimics the effects of nonlinear membrane conductances in living cells. The system is fast enough to represent dozens of nonlinear conductances in real time at clock rates well above 10 kHz. Conductances can be represented in deterministic form, or more accurately as discrete collections of stochastically gating ion channels. Tests were performed using a variety of complex models of nonlinear membrane mechanisms in excitable cells, including simulations of spatially extended excitable structures, and multiple interacting cells. Only in extreme cases does the computational load interfere with high-speed "hard" real-time processing (i.e., real-time processing that never falters). Freely available on the worldwide web, this experimental control system combines good performance. immense flexibility, low cost, and reasonable ease of use. It is easily adapted to any task involving real-time control, and excels in particular for applications requiring complex control algorithms that must operate at speeds over 1 kHz.

  17. Modeling job sites in real time to improve safety during equipment operation

    NASA Astrophysics Data System (ADS)

    Caldas, Carlos H.; Haas, Carl T.; Liapi, Katherine A.; Teizer, Jochen

    2006-03-01

    Real-time three-dimensional (3D) modeling of work zones has received an increasing interest to perform equipment operation faster, safer and more precisely. In addition, hazardous job site environment like they exist on construction sites ask for new devices which can rapidly and actively model static and dynamic objects. Flash LADAR (Laser Detection and Ranging) cameras are one of the recent technology developments which allow rapid spatial data acquisition of scenes. Algorithms that can process and interpret the output of such enabling technologies into threedimensional models have the potential to significantly improve work processes. One particular important application is modeling the location and path of objects in the trajectory of heavy construction equipment navigation. Detecting and mapping people, materials and equipment into a three-dimensional computer model allows analyzing the location, path, and can limit or restrict access to hazardous areas. This paper presents experiments and results of a real-time three-dimensional modeling technique to detect static and moving objects within the field of view of a high-frame update rate laser range scanning device. Applications related to heavy equipment operations on transportation and construction job sites are specified.

  18. Advanced Kalman Filter for Real-Time Responsiveness in Complex Systems

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

    Welch, Gregory Francis; Zhang, Jinghe

    2014-06-10

    Complex engineering systems pose fundamental challenges in real-time operations and control because they are highly dynamic systems consisting of a large number of elements with severe nonlinearities and discontinuities. Today’s tools for real-time complex system operations are mostly based on steady state models, unable to capture the dynamic nature and too slow to prevent system failures. We developed advanced Kalman filtering techniques and the formulation of dynamic state estimation using Kalman filtering techniques to capture complex system dynamics in aiding real-time operations and control. In this work, we looked at complex system issues including severe nonlinearity of system equations, discontinuitiesmore » caused by system controls and network switches, sparse measurements in space and time, and real-time requirements of power grid operations. We sought to bridge the disciplinary boundaries between Computer Science and Power Systems Engineering, by introducing methods that leverage both existing and new techniques. While our methods were developed in the context of electrical power systems, they should generalize to other large-scale scientific and engineering applications.« less

  19. Dynamic ADMM for Real-Time Optimal Power Flow

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

    Dall-Anese, Emiliano; Zhang, Yijian; Hong, Mingyi

    This paper considers distribution networks featuring distributed energy resources (DERs), and develops a dynamic optimization method to maximize given operational objectives in real time while adhering to relevant network constraints. The design of the dynamic algorithm is based on suitable linearization of the AC power flow equations, and it leverages the so-called alternating direction method of multipliers (ADMM). The steps of the ADMM, however, are suitably modified to accommodate appropriate measurements from the distribution network and the DERs. With the aid of these measurements, the resultant algorithm can enforce given operational constraints in spite of inaccuracies in the representation ofmore » the AC power flows, and it avoids ubiquitous metering to gather the state of noncontrollable resources. Optimality and convergence of the proposed algorithm are established in terms of tracking of the solution of a convex surrogate of the AC optimal power flow problem.« less

  20. Real-time high-resolution heterodyne-based measurements of spectral dynamics in fibre lasers

    PubMed Central

    Sugavanam, Srikanth; Fabbri, Simon; Le, Son Thai; Lobach, Ivan; Kablukov, Sergey; Khorev, Serge; Churkin, Dmitry

    2016-01-01

    Conventional tools for measurement of laser spectra (e.g. optical spectrum analysers) capture data averaged over a considerable time period. However, the generation spectrum of many laser types may involve spectral dynamics whose relatively fast time scale is determined by their cavity round trip period, calling for instrumentation featuring both high temporal and spectral resolution. Such real-time spectral characterisation becomes particularly challenging if the laser pulses are long, or they have continuous or quasi-continuous wave radiation components. Here we combine optical heterodyning with a technique of spatio-temporal intensity measurements that allows the characterisation of such complex sources. Fast, round-trip-resolved spectral dynamics of cavity-based systems in real-time are obtained, with temporal resolution of one cavity round trip and frequency resolution defined by its inverse (85 ns and 24 MHz respectively are demonstrated). We also show how under certain conditions for quasi-continuous wave sources, the spectral resolution could be further increased by a factor of 100 by direct extraction of phase information from the heterodyned dynamics or by using double time scales within the spectrogram approach. PMID:26984634

  1. Creating wavelet-based models for real-time synthesis of perceptually convincing environmental sounds

    NASA Astrophysics Data System (ADS)

    Miner, Nadine Elizabeth

    1998-09-01

    This dissertation presents a new wavelet-based method for synthesizing perceptually convincing, dynamic sounds using parameterized sound models. The sound synthesis method is applicable to a variety of applications including Virtual Reality (VR), multi-media, entertainment, and the World Wide Web (WWW). A unique contribution of this research is the modeling of the stochastic, or non-pitched, sound components. This stochastic-based modeling approach leads to perceptually compelling sound synthesis. Two preliminary studies conducted provide data on multi-sensory interaction and audio-visual synchronization timing. These results contributed to the design of the new sound synthesis method. The method uses a four-phase development process, including analysis, parameterization, synthesis and validation, to create the wavelet-based sound models. A patent is pending for this dynamic sound synthesis method, which provides perceptually-realistic, real-time sound generation. This dissertation also presents a battery of perceptual experiments developed to verify the sound synthesis results. These experiments are applicable for validation of any sound synthesis technique.

  2. The Priority Inversion Problem and Real-Time Symbolic Model Checking

    DTIC Science & Technology

    1993-04-23

    real time systems unpredictable in subtle ways. This makes it more difficult to implement and debug such systems. Our work discusses this problem and presents one possible solution. The solution is formalized and verified using temporal logic model checking techniques. In order to perform the verification, the BDD-based symbolic model checking algorithm given in previous works was extended to handle real-time properties using the bounded until operator. We believe that this algorithm, which is based on discrete time, is able to handle many real-time properties

  3. Review of Real-Time Simulator and the Steps Involved for Implementation of a Model from MATLAB/SIMULINK to Real-Time

    NASA Astrophysics Data System (ADS)

    Mikkili, Suresh; Panda, Anup Kumar; Prattipati, Jayanthi

    2015-06-01

    Nowadays the researchers want to develop their model in real-time environment. Simulation tools have been widely used for the design and improvement of electrical systems since the mid twentieth century. The evolution of simulation tools has progressed in step with the evolution of computing technologies. In recent years, computing technologies have improved dramatically in performance and become widely available at a steadily decreasing cost. Consequently, simulation tools have also seen dramatic performance gains and steady cost decreases. Researchers and engineers now have the access to affordable, high performance simulation tools that were previously too cost prohibitive, except for the largest manufacturers. This work has introduced a specific class of digital simulator known as a real-time simulator by answering the questions "what is real-time simulation", "why is it needed" and "how it works". The latest trend in real-time simulation consists of exporting simulation models to FPGA. In this article, the Steps involved for implementation of a model from MATLAB to REAL-TIME are provided in detail.

  4. Real-Time Safety Risk Assessment Based on a Real-Time Location System for Hydropower Construction Sites

    PubMed Central

    Fan, Qixiang; Qiang, Maoshan

    2014-01-01

    The concern for workers' safety in construction industry is reflected in many studies focusing on static safety risk identification and assessment. However, studies on real-time safety risk assessment aimed at reducing uncertainty and supporting quick response are rare. A method for real-time safety risk assessment (RTSRA) to implement a dynamic evaluation of worker safety states on construction site has been proposed in this paper. The method provides construction managers who are in charge of safety with more abundant information to reduce the uncertainty of the site. A quantitative calculation formula, integrating the influence of static and dynamic hazards and that of safety supervisors, is established to link the safety risk of workers with the locations of on-site assets. By employing the hidden Markov model (HMM), the RTSRA provides a mechanism for processing location data provided by the real-time location system (RTLS) and analyzing the probability distributions of different states in terms of false positives and negatives. Simulation analysis demonstrated the logic of the proposed method and how it works. Application case shows that the proposed RTSRA is both feasible and effective in managing construction project safety concerns. PMID:25114958

  5. Real-time safety risk assessment based on a real-time location system for hydropower construction sites.

    PubMed

    Jiang, Hanchen; Lin, Peng; Fan, Qixiang; Qiang, Maoshan

    2014-01-01

    The concern for workers' safety in construction industry is reflected in many studies focusing on static safety risk identification and assessment. However, studies on real-time safety risk assessment aimed at reducing uncertainty and supporting quick response are rare. A method for real-time safety risk assessment (RTSRA) to implement a dynamic evaluation of worker safety states on construction site has been proposed in this paper. The method provides construction managers who are in charge of safety with more abundant information to reduce the uncertainty of the site. A quantitative calculation formula, integrating the influence of static and dynamic hazards and that of safety supervisors, is established to link the safety risk of workers with the locations of on-site assets. By employing the hidden Markov model (HMM), the RTSRA provides a mechanism for processing location data provided by the real-time location system (RTLS) and analyzing the probability distributions of different states in terms of false positives and negatives. Simulation analysis demonstrated the logic of the proposed method and how it works. Application case shows that the proposed RTSRA is both feasible and effective in managing construction project safety concerns.

  6. Change Semantic Constrained Online Data Cleaning Method for Real-Time Observational Data Stream

    NASA Astrophysics Data System (ADS)

    Ding, Yulin; Lin, Hui; Li, Rongrong

    2016-06-01

    Recent breakthroughs in sensor networks have made it possible to collect and assemble increasing amounts of real-time observational data by observing dynamic phenomena at previously impossible time and space scales. Real-time observational data streams present potentially profound opportunities for real-time applications in disaster mitigation and emergency response, by providing accurate and timeliness estimates of environment's status. However, the data are always subject to inevitable anomalies (including errors and anomalous changes/events) caused by various effects produced by the environment they are monitoring. The "big but dirty" real-time observational data streams can rarely achieve their full potential in the following real-time models or applications due to the low data quality. Therefore, timely and meaningful online data cleaning is a necessary pre-requisite step to ensure the quality, reliability, and timeliness of the real-time observational data. In general, a straightforward streaming data cleaning approach, is to define various types of models/classifiers representing normal behavior of sensor data streams and then declare any deviation from this model as normal or erroneous data. The effectiveness of these models is affected by dynamic changes of deployed environments. Due to the changing nature of the complicated process being observed, real-time observational data is characterized by diversity and dynamic, showing a typical Big (Geo) Data characters. Dynamics and diversity is not only reflected in the data values, but also reflected in the complicated changing patterns of the data distributions. This means the pattern of the real-time observational data distribution is not stationary or static but changing and dynamic. After the data pattern changed, it is necessary to adapt the model over time to cope with the changing patterns of real-time data streams. Otherwise, the model will not fit the following observational data streams, which may led

  7. Real-time individualization of the unified model of performance.

    PubMed

    Liu, Jianbo; Ramakrishnan, Sridhar; Laxminarayan, Srinivas; Balkin, Thomas J; Reifman, Jaques

    2017-12-01

    Existing mathematical models for predicting neurobehavioural performance are not suited for mobile computing platforms because they cannot adapt model parameters automatically in real time to reflect individual differences in the effects of sleep loss. We used an extended Kalman filter to develop a computationally efficient algorithm that continually adapts the parameters of the recently developed Unified Model of Performance (UMP) to an individual. The algorithm accomplishes this in real time as new performance data for the individual become available. We assessed the algorithm's performance by simulating real-time model individualization for 18 subjects subjected to 64 h of total sleep deprivation (TSD) and 7 days of chronic sleep restriction (CSR) with 3 h of time in bed per night, using psychomotor vigilance task (PVT) data collected every 2 h during wakefulness. This UMP individualization process produced parameter estimates that progressively approached the solution produced by a post-hoc fitting of model parameters using all data. The minimum number of PVT measurements needed to individualize the model parameters depended upon the type of sleep-loss challenge, with ~30 required for TSD and ~70 for CSR. However, model individualization depended upon the overall duration of data collection, yielding increasingly accurate model parameters with greater number of days. Interestingly, reducing the PVT sampling frequency by a factor of two did not notably hamper model individualization. The proposed algorithm facilitates real-time learning of an individual's trait-like responses to sleep loss and enables the development of individualized performance prediction models for use in a mobile computing platform. © 2017 European Sleep Research Society.

  8. High dynamic range adaptive real-time smart camera: an overview of the HDR-ARTiST project

    NASA Astrophysics Data System (ADS)

    Lapray, Pierre-Jean; Heyrman, Barthélémy; Ginhac, Dominique

    2015-04-01

    Standard cameras capture only a fraction of the information that is visible to the human visual system. This is specifically true for natural scenes including areas of low and high illumination due to transitions between sunlit and shaded areas. When capturing such a scene, many cameras are unable to store the full Dynamic Range (DR) resulting in low quality video where details are concealed in shadows or washed out by sunlight. The imaging technique that can overcome this problem is called HDR (High Dynamic Range) imaging. This paper describes a complete smart camera built around a standard off-the-shelf LDR (Low Dynamic Range) sensor and a Virtex-6 FPGA board. This smart camera called HDR-ARtiSt (High Dynamic Range Adaptive Real-time Smart camera) is able to produce a real-time HDR live video color stream by recording and combining multiple acquisitions of the same scene while varying the exposure time. This technique appears as one of the most appropriate and cheapest solution to enhance the dynamic range of real-life environments. HDR-ARtiSt embeds real-time multiple captures, HDR processing, data display and transfer of a HDR color video for a full sensor resolution (1280 1024 pixels) at 60 frames per second. The main contributions of this work are: (1) Multiple Exposure Control (MEC) dedicated to the smart image capture with alternating three exposure times that are dynamically evaluated from frame to frame, (2) Multi-streaming Memory Management Unit (MMMU) dedicated to the memory read/write operations of the three parallel video streams, corresponding to the different exposure times, (3) HRD creating by combining the video streams using a specific hardware version of the Devebecs technique, and (4) Global Tone Mapping (GTM) of the HDR scene for display on a standard LCD monitor.

  9. A Comparison and Evaluation of Real-Time Software Systems Modeling Languages

    NASA Technical Reports Server (NTRS)

    Evensen, Kenneth D.; Weiss, Kathryn Anne

    2010-01-01

    A model-driven approach to real-time software systems development enables the conceptualization of software, fostering a more thorough understanding of its often complex architecture and behavior while promoting the documentation and analysis of concerns common to real-time embedded systems such as scheduling, resource allocation, and performance. Several modeling languages have been developed to assist in the model-driven software engineering effort for real-time systems, and these languages are beginning to gain traction with practitioners throughout the aerospace industry. This paper presents a survey of several real-time software system modeling languages, namely the Architectural Analysis and Design Language (AADL), the Unified Modeling Language (UML), Systems Modeling Language (SysML), the Modeling and Analysis of Real-Time Embedded Systems (MARTE) UML profile, and the AADL for UML profile. Each language has its advantages and disadvantages, and in order to adequately describe a real-time software system's architecture, a complementary use of multiple languages is almost certainly necessary. This paper aims to explore these languages in the context of understanding the value each brings to the model-driven software engineering effort and to determine if it is feasible and practical to combine aspects of the various modeling languages to achieve more complete coverage in architectural descriptions. To this end, each language is evaluated with respect to a set of criteria such as scope, formalisms, and architectural coverage. An example is used to help illustrate the capabilities of the various languages.

  10. Real-Time Simulation of the X-33 Aerospace Engine

    NASA Technical Reports Server (NTRS)

    Aguilar, Robert

    1999-01-01

    This paper discusses the development and performance of the X-33 Aerospike Engine RealTime Model. This model was developed for the purposes of control law development, six degree-of-freedom trajectory analysis, vehicle system integration testing, and hardware-in-the loop controller verification. The Real-Time Model uses time-step marching solution of non-linear differential equations representing the physical processes involved in the operation of a liquid propellant rocket engine, albeit in a simplified form. These processes include heat transfer, fluid dynamics, combustion, and turbomachine performance. Two engine models are typically employed in order to accurately model maneuvering and the powerpack-out condition where the power section of one engine is used to supply propellants to both engines if one engine malfunctions. The X-33 Real-Time Model is compared to actual hot fire test data and is been found to be in good agreement.

  11. Real Time Fire Reconnaissance Satellite Monitoring System Failure Model

    NASA Astrophysics Data System (ADS)

    Nino Prieto, Omar Ariosto; Colmenares Guillen, Luis Enrique

    2013-09-01

    In this paper the Real Time Fire Reconnaissance Satellite Monitoring System is presented. This architecture is a legacy of the Detection System for Real-Time Physical Variables which is undergoing a patent process in Mexico. The methodologies for this design are the Structured Analysis for Real Time (SA- RT) [8], and the software is carried out by LACATRE (Langage d'aide à la Conception d'Application multitâche Temps Réel) [9,10] Real Time formal language. The system failures model is analyzed and the proposal is based on the formal language for the design of critical systems and Risk Assessment; AltaRica. This formal architecture uses satellites as input sensors and it was adapted from the original model which is a design pattern for physical variation detection in Real Time. The original design, whose task is to monitor events such as natural disasters and health related applications, or actual sickness monitoring and prevention, as the Real Time Diabetes Monitoring System, among others. Some related work has been presented on the Mexican Space Agency (AEM) Creation and Consultation Forums (2010-2011), and throughout the International Mexican Aerospace Science and Technology Society (SOMECYTA) international congress held in San Luis Potosí, México (2012). This Architecture will allow a Real Time Fire Satellite Monitoring, which will reduce the damage and danger caused by fires which consumes the forests and tropical forests of Mexico. This new proposal, permits having a new system that impacts on disaster prevention, by combining national and international technologies and cooperation for the benefit of humankind.

  12. Real-time full-field characterization of transient dissipative soliton dynamics in a mode-locked laser

    NASA Astrophysics Data System (ADS)

    Ryczkowski, P.; Närhi, M.; Billet, C.; Merolla, J.-M.; Genty, G.; Dudley, J. M.

    2018-04-01

    Dissipative solitons are remarkably localized states of a physical system that arise from the dynamical balance between nonlinearity, dispersion and environmental energy exchange. They are the most universal form of soliton that can exist, and are seen in far-from-equilibrium systems in many fields, including chemistry, biology and physics. There has been particular interest in studying their properties in mode-locked lasers, but experiments have been limited by the inability to track the dynamical soliton evolution in real time. Here, we use simultaneous dispersive Fourier transform and time-lens measurements to completely characterize the spectral and temporal evolution of ultrashort dissipative solitons as their dynamics pass through a transient unstable regime with complex break-up and collisions before stabilization. Further insight is obtained from reconstruction of the soliton amplitude and phase and calculation of the corresponding complex-valued eigenvalue spectrum. These findings show how real-time measurements provide new insights into ultrafast transient dynamics in optics.

  13. Modeling Real-Time Applications with Reusable Design Patterns

    NASA Astrophysics Data System (ADS)

    Rekhis, Saoussen; Bouassida, Nadia; Bouaziz, Rafik

    Real-Time (RT) applications, which manipulate important volumes of data, need to be managed with RT databases that deal with time-constrained data and time-constrained transactions. In spite of their numerous advantages, RT databases development remains a complex task, since developers must study many design issues related to the RT domain. In this paper, we tackle this problem by proposing RT design patterns that allow the modeling of structural and behavioral aspects of RT databases. We show how RT design patterns can provide design assistance through architecture reuse of reoccurring design problems. In addition, we present an UML profile that represents patterns and facilitates further their reuse. This profile proposes, on one hand, UML extensions allowing to model the variability of patterns in the RT context and, on another hand, extensions inspired from the MARTE (Modeling and Analysis of Real-Time Embedded systems) profile.

  14. Diagnosing and Reconstructing Real-World Hydroclimatic Dynamics from Time Sequenced Data: The Case of Saltwater Intrusion into Coastal Wetlands in Everglades National Park

    NASA Astrophysics Data System (ADS)

    Huffaker, R.; Munoz-Carpena, R.

    2016-12-01

    There are increasing calls to audit decision-support models used for environmental policy to ensure that they correspond with the reality facing policy makers. Modelers can establish correspondence by providing empirical evidence of real-world dynamic behavior that their models skillfully simulate. We present a pre-modeling diagnostic framework—based on nonlinear dynamic analysis—for detecting and reconstructing real-world environmental dynamics from observed time-sequenced data. Phenomenological (data-driven) modeling—based on machine learning regression techniques—extracts a set of ordinary differential equations governing empirically-diagnosed system dynamics from a single time series, or from multiple time series on causally-interacting variables. We apply the framework to investigate saltwater intrusion into coastal wetlands in Everglades National Park, Florida, USA. We test the following hypotheses posed in the literature linking regional hydrologic variables with global climatic teleconnections: (1) Sea level in Florida Bay drives well level and well salinity in the coastal Everglades; (2) Atlantic Multidecadal Oscillation (AMO) drives sea level, well level and well salinity; and (3) AMO and (El Niño Southern Oscillation) ENSO bi-causally interact. The thinking is that salt water intrusion links ocean-surface salinity with salinity of inland water sources, and sea level with inland water; that AMO and ENSO share a teleconnective relationship (perhaps through the atmosphere); and that AMO and ENSO both influence inland precipitation and thus well levels. Our results support these hypotheses, and we successfully construct a parsimonious phenomenological model that reproduces diagnosed nonlinear dynamics and system interactions. We propose that reconstructed data dynamics be used, along with other expert information, as a rigorous benchmark to guide specification and testing of hydrologic decision support models corresponding with real-world behavior.

  15. Effect of Streamflow Forecast Uncertainty on Real-Time Reservoir Operation

    NASA Astrophysics Data System (ADS)

    Zhao, T.; Cai, X.; Yang, D.

    2010-12-01

    Various hydrological forecast products have been applied to real-time reservoir operation, including deterministic streamflow forecast (DSF), DSF-based probabilistic streamflow forecast (DPSF), and ensemble streamflow forecast (ESF), which represent forecast uncertainty in the form of deterministic forecast error, deterministic forecast error-based uncertainty distribution, and ensemble forecast errors, respectively. Compared to previous studies that treat these forecast products as ad hoc inputs for reservoir operation models, this paper attempts to model the uncertainties involved in the various forecast products and explores their effect on real-time reservoir operation decisions. In hydrology, there are various indices reflecting the magnitude of streamflow forecast uncertainty; meanwhile, few models illustrate the forecast uncertainty evolution process. This research introduces Martingale Model of Forecast Evolution (MMFE) from supply chain management and justifies its assumptions for quantifying the evolution of uncertainty in streamflow forecast as time progresses. Based on MMFE, this research simulates the evolution of forecast uncertainty in DSF, DPSF, and ESF, and applies the reservoir operation models (dynamic programming, DP; stochastic dynamic programming, SDP; and standard operation policy, SOP) to assess the effect of different forms of forecast uncertainty on real-time reservoir operation. Through a hypothetical single-objective real-time reservoir operation model, the results illustrate that forecast uncertainty exerts significant effects. Reservoir operation efficiency, as measured by a utility function, decreases as the forecast uncertainty increases. Meanwhile, these effects also depend on the type of forecast product being used. In general, the utility of reservoir operation with ESF is nearly as high as the utility obtained with a perfect forecast; the utilities of DSF and DPSF are similar to each other but not as efficient as ESF. Moreover

  16. Dynamical jumping real-time fault-tolerant routing protocol for wireless sensor networks.

    PubMed

    Wu, Guowei; Lin, Chi; Xia, Feng; Yao, Lin; Zhang, He; Liu, Bing

    2010-01-01

    In time-critical wireless sensor network (WSN) applications, a high degree of reliability is commonly required. A dynamical jumping real-time fault-tolerant routing protocol (DMRF) is proposed in this paper. Each node utilizes the remaining transmission time of the data packets and the state of the forwarding candidate node set to dynamically choose the next hop. Once node failure, network congestion or void region occurs, the transmission mode will switch to jumping transmission mode, which can reduce the transmission time delay, guaranteeing the data packets to be sent to the destination node within the specified time limit. By using feedback mechanism, each node dynamically adjusts the jumping probabilities to increase the ratio of successful transmission. Simulation results show that DMRF can not only efficiently reduce the effects of failure nodes, congestion and void region, but also yield higher ratio of successful transmission, smaller transmission delay and reduced number of control packets.

  17. "Fast" Is Not "Real-Time": Designing Effective Real-Time AI Systems

    NASA Astrophysics Data System (ADS)

    O'Reilly, Cindy A.; Cromarty, Andrew S.

    1985-04-01

    Realistic practical problem domains (such as robotics, process control, and certain kinds of signal processing) stand to benefit greatly from the application of artificial intelligence techniques. These problem domains are of special interest because they are typified by complex dynamic environments in which the ability to select and initiate a proper response to environmental events in real time is a strict prerequisite to effective environmental interaction. Artificial intelligence systems developed to date have been sheltered from this real-time requirement, however, largely by virtue of their use of simplified problem domains or problem representations. The plethora of colloquial and (in general) mutually inconsistent interpretations of the term "real-time" employed by workers in each of these domains further exacerbates the difficul-ties in effectively applying state-of-the-art problem solving tech-niques to time-critical problems. Indeed, the intellectual waters are by now sufficiently muddied that the pursuit of a rigorous treatment of intelligent real-time performance mandates the redevelopment of proper problem perspective on what "real-time" means, starting from first principles. We present a simple but nonetheless formal definition of real-time performance. We then undertake an analysis of both conventional techniques and AI technology with respect to their ability to meet substantive real-time performance criteria. This analysis provides a basis for specification of problem-independent design requirements for systems that would claim real-time performance. Finally, we discuss the application of these design principles to a pragmatic problem in real-time signal understanding.

  18. Real-time modeling of heat distributions

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

    Hamann, Hendrik F.; Li, Hongfei; Yarlanki, Srinivas

    Techniques for real-time modeling temperature distributions based on streaming sensor data are provided. In one aspect, a method for creating a three-dimensional temperature distribution model for a room having a floor and a ceiling is provided. The method includes the following steps. A ceiling temperature distribution in the room is determined. A floor temperature distribution in the room is determined. An interpolation between the ceiling temperature distribution and the floor temperature distribution is used to obtain the three-dimensional temperature distribution model for the room.

  19. Real-time dynamics of typical and untypical states in nonintegrable systems

    NASA Astrophysics Data System (ADS)

    Richter, Jonas; Jin, Fengping; De Raedt, Hans; Michielsen, Kristel; Gemmer, Jochen; Steinigeweg, Robin

    2018-05-01

    Understanding (i) the emergence of diffusion from truly microscopic principles continues to be a major challenge in experimental and theoretical physics. At the same time, isolated quantum many-body systems have experienced an upsurge of interest in recent years. Since in such systems the realization of a proper initial state is the only possibility to induce a nonequilibrium process, understanding (ii) the largely unexplored role of the specific realization is vitally important. Our work reports a substantial step forward and tackles the two issues (i) and (ii) in the context of typicality, entanglement as well as integrability and nonintegrability. Specifically, we consider the spin-1/2 XXZ chain, where integrability can be broken due to an additional next-nearest neighbor interaction, and study the real-time and real-space dynamics of nonequilibrium magnetization profiles for a class of pure states. Summarizing our main results, we show that signatures of diffusion for strong interactions are equally pronounced for the integrable and nonintegrable case. In both cases, we further find a clear difference between the dynamics of states with and without internal randomness. We provide an explanation of this difference by a detailed analysis of the local density of states.

  20. Application of the Real-Time Time-Dependent Density Functional Theory to Excited-State Dynamics of Molecules and 2D Materials

    NASA Astrophysics Data System (ADS)

    Miyamoto, Yoshiyuki; Rubio, Angel

    2018-04-01

    We review our recent developments in the ab initio simulation of excited-state dynamics within the framework of time-dependent density functional theory (TDDFT). Our targets range from molecules to 2D materials, although the methods are general and can be applied to any other finite and periodic systems. We discuss examples of excited-state dynamics obtained by real-time TDDFT coupled with molecular dynamics (MD) and the Ehrenfest approximation, including photoisomerization in molecules, photoenhancement of the weak interatomic attraction of noble gas atoms, photoenhancement of the weak interlayer interaction of 2D materials, pulse-laser-induced local bond breaking of adsorbed atoms on 2D sheets, modulation of UV light intensity by graphene nanoribbons at terahertz frequencies, and collision of high-speed ions with the 2D material to simulate the images taken by He ion microscopy. We illustrate how the real-time TDDFT approach is useful for predicting and understanding non-equilibrium dynamics in condensed matter. We also discuss recent developments that address the excited-state dynamics of systems out of equilibrium and future challenges in this fascinating field of research.

  1. Real-time photorealistic stereoscopic rendering of fire

    NASA Astrophysics Data System (ADS)

    Rose, Benjamin M.; McAllister, David F.

    2007-02-01

    We propose a method for real-time photorealistic stereo rendering of the natural phenomenon of fire. Applications include the use of virtual reality in fire fighting, military training, and entertainment. Rendering fire in real-time presents a challenge because of the transparency and non-static fluid-like behavior of fire. It is well known that, in general, methods that are effective for monoscopic rendering are not necessarily easily extended to stereo rendering because monoscopic methods often do not provide the depth information necessary to produce the parallax required for binocular disparity in stereoscopic rendering. We investigate the existing techniques used for monoscopic rendering of fire and discuss their suitability for extension to real-time stereo rendering. Methods include the use of precomputed textures, dynamic generation of textures, and rendering models resulting from the approximation of solutions of fluid dynamics equations through the use of ray-tracing algorithms. We have found that in order to attain real-time frame rates, our method based on billboarding is effective. Slicing is used to simulate depth. Texture mapping or 2D images are mapped onto polygons and alpha blending is used to treat transparency. We can use video recordings or prerendered high-quality images of fire as textures to attain photorealistic stereo.

  2. Revealing Real-Time Emotional Responses: a Personalized Assessment based on Heartbeat Dynamics

    NASA Astrophysics Data System (ADS)

    Valenza, Gaetano; Citi, Luca; Lanatá, Antonio; Scilingo, Enzo Pasquale; Barbieri, Riccardo

    2014-05-01

    Emotion recognition through computational modeling and analysis of physiological signals has been widely investigated in the last decade. Most of the proposed emotion recognition systems require relatively long-time series of multivariate records and do not provide accurate real-time characterizations using short-time series. To overcome these limitations, we propose a novel personalized probabilistic framework able to characterize the emotional state of a subject through the analysis of heartbeat dynamics exclusively. The study includes thirty subjects presented with a set of standardized images gathered from the international affective picture system, alternating levels of arousal and valence. Due to the intrinsic nonlinearity and nonstationarity of the RR interval series, a specific point-process model was devised for instantaneous identification considering autoregressive nonlinearities up to the third-order according to the Wiener-Volterra representation, thus tracking very fast stimulus-response changes. Features from the instantaneous spectrum and bispectrum, as well as the dominant Lyapunov exponent, were extracted and considered as input features to a support vector machine for classification. Results, estimating emotions each 10 seconds, achieve an overall accuracy in recognizing four emotional states based on the circumplex model of affect of 79.29%, with 79.15% on the valence axis, and 83.55% on the arousal axis.

  3. Revealing real-time emotional responses: a personalized assessment based on heartbeat dynamics.

    PubMed

    Valenza, Gaetano; Citi, Luca; Lanatá, Antonio; Scilingo, Enzo Pasquale; Barbieri, Riccardo

    2014-05-21

    Emotion recognition through computational modeling and analysis of physiological signals has been widely investigated in the last decade. Most of the proposed emotion recognition systems require relatively long-time series of multivariate records and do not provide accurate real-time characterizations using short-time series. To overcome these limitations, we propose a novel personalized probabilistic framework able to characterize the emotional state of a subject through the analysis of heartbeat dynamics exclusively. The study includes thirty subjects presented with a set of standardized images gathered from the international affective picture system, alternating levels of arousal and valence. Due to the intrinsic nonlinearity and nonstationarity of the RR interval series, a specific point-process model was devised for instantaneous identification considering autoregressive nonlinearities up to the third-order according to the Wiener-Volterra representation, thus tracking very fast stimulus-response changes. Features from the instantaneous spectrum and bispectrum, as well as the dominant Lyapunov exponent, were extracted and considered as input features to a support vector machine for classification. Results, estimating emotions each 10 seconds, achieve an overall accuracy in recognizing four emotional states based on the circumplex model of affect of 79.29%, with 79.15% on the valence axis, and 83.55% on the arousal axis.

  4. Real-time spectral interferometry probes the internal dynamics of femtosecond soliton molecules

    NASA Astrophysics Data System (ADS)

    Herink, G.; Kurtz, F.; Jalali, B.; Solli, D. R.; Ropers, C.

    2017-04-01

    Solitons, particle-like excitations ubiquitous in many fields of physics, have been shown to exhibit bound states akin to molecules. The formation of such temporal soliton bound states and their internal dynamics have escaped direct experimental observation. By means of an emerging time-stretch technique, we resolve the evolution of femtosecond soliton molecules in the cavity of a few-cycle mode-locked laser. We track two- and three-soliton bound states over hundreds of thousands of consecutive cavity roundtrips, identifying fixed points and periodic and aperiodic molecular orbits. A class of trajectories acquires a path-dependent geometrical phase, implying that its dynamics may be topologically protected. These findings highlight the importance of real-time detection in resolving interactions in complex nonlinear systems, including the dynamics of soliton bound states, breathers, and rogue waves.

  5. Dynamic ADMM for Real-Time Optimal Power Flow: Preprint

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

    Dall-Anese, Emiliano; Zhang, Yijian; Hong, Mingyi

    This paper considers distribution networks featuring distributed energy resources (DERs), and develops a dynamic optimization method to maximize given operational objectives in real time while adhering to relevant network constraints. The design of the dynamic algorithm is based on suitable linearizations of the AC power flow equations, and it leverages the so-called alternating direction method of multipliers (ADMM). The steps of the ADMM, however, are suitably modified to accommodate appropriate measurements from the distribution network and the DERs. With the aid of these measurements, the resultant algorithm can enforce given operational constraints in spite of inaccuracies in the representation ofmore » the AC power flows, and it avoids ubiquitous metering to gather the state of non-controllable resources. Optimality and convergence of the propose algorithm are established in terms of tracking of the solution of a convex surrogate of the AC optimal power flow problem.« less

  6. Real-Time System for Water Modeling and Management

    NASA Astrophysics Data System (ADS)

    Lee, J.; Zhao, T.; David, C. H.; Minsker, B.

    2012-12-01

    Working closely with the Texas Commission on Environmental Quality (TCEQ) and the University of Texas at Austin (UT-Austin), we are developing a real-time system for water modeling and management using advanced cyberinfrastructure, data integration and geospatial visualization, and numerical modeling. The state of Texas suffered a severe drought in 2011 that cost the state $7.62 billion in agricultural losses (crops and livestock). Devastating situations such as this could potentially be avoided with better water modeling and management strategies that incorporate state of the art simulation and digital data integration. The goal of the project is to prototype a near-real-time decision support system for river modeling and management in Texas that can serve as a national and international model to promote more sustainable and resilient water systems. The system uses National Weather Service current and predicted precipitation data as input to the Noah-MP Land Surface model, which forecasts runoff, soil moisture, evapotranspiration, and water table levels given land surface features. These results are then used by a river model called RAPID, along with an error model currently under development at UT-Austin, to forecast stream flows in the rivers. Model forecasts are visualized as a Web application for TCEQ decision makers, who issue water diversion (withdrawal) permits and any needed drought restrictions; permit holders; and reservoir operation managers. Users will be able to adjust model parameters to predict the impacts of alternative curtailment scenarios or weather forecasts. A real-time optimization system under development will help TCEQ to identify optimal curtailment strategies to minimize impacts on permit holders and protect health and safety. To develop the system we have implemented RAPID as a remotely-executed modeling service using the Cyberintegrator workflow system with input data downloaded from the North American Land Data Assimilation System. The

  7. Safety analytics for integrating crash frequency and real-time risk modeling for expressways.

    PubMed

    Wang, Ling; Abdel-Aty, Mohamed; Lee, Jaeyoung

    2017-07-01

    To find crash contributing factors, there have been numerous crash frequency and real-time safety studies, but such studies have been conducted independently. Until this point, no researcher has simultaneously analyzed crash frequency and real-time crash risk to test whether integrating them could better explain crash occurrence. Therefore, this study aims at integrating crash frequency and real-time safety analyses using expressway data. A Bayesian integrated model and a non-integrated model were built: the integrated model linked the crash frequency and the real-time models by adding the logarithm of the estimated expected crash frequency in the real-time model; the non-integrated model independently estimated the crash frequency and the real-time crash risk. The results showed that the integrated model outperformed the non-integrated model, as it provided much better model results for both the crash frequency and the real-time models. This result indicated that the added component, the logarithm of the expected crash frequency, successfully linked and provided useful information to the two models. This study uncovered few variables that are not typically included in the crash frequency analysis. For example, the average daily standard deviation of speed, which was aggregated based on speed at 1-min intervals, had a positive effect on crash frequency. In conclusion, this study suggested a methodology to improve the crash frequency and real-time models by integrating them, and it might inspire future researchers to understand crash mechanisms better. Copyright © 2017 Elsevier Ltd. All rights reserved.

  8. Real-Time Reliability Verification for UAV Flight Control System Supporting Airworthiness Certification.

    PubMed

    Xu, Haiyang; Wang, Ping

    2016-01-01

    In order to verify the real-time reliability of unmanned aerial vehicle (UAV) flight control system and comply with the airworthiness certification standard, we proposed a model-based integration framework for modeling and verification of time property. Combining with the advantages of MARTE, this framework uses class diagram to create the static model of software system, and utilizes state chart to create the dynamic model. In term of the defined transformation rules, the MARTE model could be transformed to formal integrated model, and the different part of the model could also be verified by using existing formal tools. For the real-time specifications of software system, we also proposed a generating algorithm for temporal logic formula, which could automatically extract real-time property from time-sensitive live sequence chart (TLSC). Finally, we modeled the simplified flight control system of UAV to check its real-time property. The results showed that the framework could be used to create the system model, as well as precisely analyze and verify the real-time reliability of UAV flight control system.

  9. Real-Time Reliability Verification for UAV Flight Control System Supporting Airworthiness Certification

    PubMed Central

    Xu, Haiyang; Wang, Ping

    2016-01-01

    In order to verify the real-time reliability of unmanned aerial vehicle (UAV) flight control system and comply with the airworthiness certification standard, we proposed a model-based integration framework for modeling and verification of time property. Combining with the advantages of MARTE, this framework uses class diagram to create the static model of software system, and utilizes state chart to create the dynamic model. In term of the defined transformation rules, the MARTE model could be transformed to formal integrated model, and the different part of the model could also be verified by using existing formal tools. For the real-time specifications of software system, we also proposed a generating algorithm for temporal logic formula, which could automatically extract real-time property from time-sensitive live sequence chart (TLSC). Finally, we modeled the simplified flight control system of UAV to check its real-time property. The results showed that the framework could be used to create the system model, as well as precisely analyze and verify the real-time reliability of UAV flight control system. PMID:27918594

  10. Intelligent data management for real-time spacecraft monitoring

    NASA Technical Reports Server (NTRS)

    Schwuttke, Ursula M.; Gasser, Les; Abramson, Bruce

    1992-01-01

    Real-time AI systems have begun to address the challenge of restructuring problem solving to meet real-time constraints by making key trade-offs that pursue less than optimal strategies with minimal impact on system goals. Several approaches for adapting to dynamic changes in system operating conditions are known. However, simultaneously adapting system decision criteria in a principled way has been difficult. Towards this end, a general technique for dynamically making such trade-offs using a combination of decision theory and domain knowledge has been developed. Multi-attribute utility theory (MAUT), a decision theoretic approach for making one-time decisions is discussed and dynamic trade-off evaluation is described as a knowledge-based extension of MAUT that is suitable for highly dynamic real-time environments, and provides an example of dynamic trade-off evaluation applied to a specific data management trade-off in a real-world spacecraft monitoring application.

  11. Dynamic Factor Analysis Models with Time-Varying Parameters

    ERIC Educational Resources Information Center

    Chow, Sy-Miin; Zu, Jiyun; Shifren, Kim; Zhang, Guangjian

    2011-01-01

    Dynamic factor analysis models with time-varying parameters offer a valuable tool for evaluating multivariate time series data with time-varying dynamics and/or measurement properties. We use the Dynamic Model of Activation proposed by Zautra and colleagues (Zautra, Potter, & Reich, 1997) as a motivating example to construct a dynamic factor…

  12. Real-Time Interactive Tree Animation.

    PubMed

    Quigley, Ed; Yu, Yue; Huang, Jingwei; Lin, Winnie; Fedkiw, Ronald

    2018-05-01

    We present a novel method for posing and animating botanical tree models interactively in real time. Unlike other state of the art methods which tend to produce trees that are overly flexible, bending and deforming as if they were underwater plants, our approach allows for arbitrarily high stiffness while still maintaining real-time frame rates without spurious artifacts, even on quite large trees with over ten thousand branches. This is accomplished by using an articulated rigid body model with as-stiff-as-desired rotational springs in conjunction with our newly proposed simulation technique, which is motivated both by position based dynamics and the typical algorithms for articulated rigid bodies. The efficiency of our algorithm allows us to pose and animate trees with millions of branches or alternatively simulate a small forest comprised of many highly detailed trees. Even using only a single CPU core, we can simulate ten thousand branches in real time while still maintaining quite crisp user interactivity. This has allowed us to incorporate our framework into a commodity game engine to run interactively even on a low-budget tablet. We show that our method is amenable to the incorporation of a large variety of desirable effects such as wind, leaves, fictitious forces, collisions, fracture, etc.

  13. Platform for real-time simulation of dynamic systems and hardware-in-the-loop for control algorithms.

    PubMed

    de Souza, Isaac D T; Silva, Sergio N; Teles, Rafael M; Fernandes, Marcelo A C

    2014-10-15

    The development of new embedded algorithms for automation and control of industrial equipment usually requires the use of real-time testing. However, the equipment required is often expensive, which means that such tests are often not viable. The objective of this work was therefore to develop an embedded platform for the distributed real-time simulation of dynamic systems. This platform, called the Real-Time Simulator for Dynamic Systems (RTSDS), could be applied in both industrial and academic environments. In industrial applications, the RTSDS could be used to optimize embedded control algorithms. In the academic sphere, it could be used to support research into new embedded solutions for automation and control and could also be used as a tool to assist in undergraduate and postgraduate teaching related to the development of projects concerning on-board control systems.

  14. Platform for Real-Time Simulation of Dynamic Systems and Hardware-in-the-Loop for Control Algorithms

    PubMed Central

    de Souza, Isaac D. T.; Silva, Sergio N.; Teles, Rafael M.; Fernandes, Marcelo A. C.

    2014-01-01

    The development of new embedded algorithms for automation and control of industrial equipment usually requires the use of real-time testing. However, the equipment required is often expensive, which means that such tests are often not viable. The objective of this work was therefore to develop an embedded platform for the distributed real-time simulation of dynamic systems. This platform, called the Real-Time Simulator for Dynamic Systems (RTSDS), could be applied in both industrial and academic environments. In industrial applications, the RTSDS could be used to optimize embedded control algorithms. In the academic sphere, it could be used to support research into new embedded solutions for automation and control and could also be used as a tool to assist in undergraduate and postgraduate teaching related to the development of projects concerning on-board control systems. PMID:25320906

  15. D Model Visualization Enhancements in Real-Time Game Engines

    NASA Astrophysics Data System (ADS)

    Merlo, A.; Sánchez Belenguer, C.; Vendrell Vidal, E.; Fantini, F.; Aliperta, A.

    2013-02-01

    This paper describes two procedures used to disseminate tangible cultural heritage through real-time 3D simulations providing accurate-scientific representations. The main idea is to create simple geometries (with low-poly count) and apply two different texture maps to them: a normal map and a displacement map. There are two ways to achieve models that fit with normal or displacement maps: with the former (normal maps), the number of polygons in the reality-based model may be dramatically reduced by decimation algorithms and then normals may be calculated by rendering them to texture solutions (baking). With the latter, a LOD model is needed; its topology has to be quad-dominant for it to be converted to a good quality subdivision surface (with consistent tangency and curvature all over). The subdivision surface is constructed using methodologies for the construction of assets borrowed from character animation: these techniques have been recently implemented in many entertainment applications known as "retopology". The normal map is used as usual, in order to shade the surface of the model in a realistic way. The displacement map is used to finish, in real-time, the flat faces of the object, by adding the geometric detail missing in the low-poly models. The accuracy of the resulting geometry is progressively refined based on the distance from the viewing point, so the result is like a continuous level of detail, the only difference being that there is no need to create different 3D models for one and the same object. All geometric detail is calculated in real-time according to the displacement map. This approach can be used in Unity, a real-time 3D engine originally designed for developing computer games. It provides a powerful rendering engine, fully integrated with a complete set of intuitive tools and rapid workflows that allow users to easily create interactive 3D contents. With the release of Unity 4.0, new rendering features have been added, including Direct

  16. Stress Analysis and Fatigue Behaviour of PTFE-Bronze Layered Journal Bearing under Real-Time Dynamic Loading

    NASA Astrophysics Data System (ADS)

    Duman, M. S.; Kaplan, E.; Cuvalcı, O.

    2018-01-01

    The present paper is based on experimental studies and numerical simulations on the surface fatigue failure of the PTFE-bronze layered journal bearings under real-time loading. ‘Permaglide Plain Bearings P10’ type journal bearings were experimentally tested under different real time dynamic loadings by using real time journal bearing test system in our laboratory. The journal bearing consists of a PTFE-bronze layer approximately 0.32 mm thick on the steel support layer with 2.18 mm thick. Two different approaches have been considered with in experiments: (i) under real- time constant loading with varying bearing widths, (ii) under different real-time loadings at constant bearing widths. Fatigue regions, micro-crack dispersion and stress distributions occurred at the journal bearing were experimentally and theoretically investigated. The relation between fatigue region and pressure distributions were investigated by determining the circumferential pressure distribution under real-time dynamic loadings for the position of every 10° crank angles. In the theoretical part; stress and deformation distributions at the surface of the journal bearing analysed by using finite element methods to determine the relationship between stress and fatigue behaviour. As a result of this study, the maximum oil pressure and fatigue cracks were observed in the most heavily loaded regions of the bearing surface. Experimental results show that PTFE-Bronze layered journal bearings fatigue behaviour is better than the bearings include white metal alloy.

  17. Real-space and real-time dynamics of CRISPR-Cas9 visualized by high-speed atomic force microscopy.

    PubMed

    Shibata, Mikihiro; Nishimasu, Hiroshi; Kodera, Noriyuki; Hirano, Seiichi; Ando, Toshio; Uchihashi, Takayuki; Nureki, Osamu

    2017-11-10

    The CRISPR-associated endonuclease Cas9 binds to a guide RNA and cleaves double-stranded DNA with a sequence complementary to the RNA guide. The Cas9-RNA system has been harnessed for numerous applications, such as genome editing. Here we use high-speed atomic force microscopy (HS-AFM) to visualize the real-space and real-time dynamics of CRISPR-Cas9 in action. HS-AFM movies indicate that, whereas apo-Cas9 adopts unexpected flexible conformations, Cas9-RNA forms a stable bilobed structure and interrogates target sites on the DNA by three-dimensional diffusion. These movies also provide real-time visualization of the Cas9-mediated DNA cleavage process. Notably, the Cas9 HNH nuclease domain fluctuates upon DNA binding, and subsequently adopts an active conformation, where the HNH active site is docked at the cleavage site in the target DNA. Collectively, our HS-AFM data extend our understanding of the action mechanism of CRISPR-Cas9.

  18. Logic Model Checking of Time-Periodic Real-Time Systems

    NASA Technical Reports Server (NTRS)

    Florian, Mihai; Gamble, Ed; Holzmann, Gerard

    2012-01-01

    In this paper we report on the work we performed to extend the logic model checker SPIN with built-in support for the verification of periodic, real-time embedded software systems, as commonly used in aircraft, automobiles, and spacecraft. We first extended the SPIN verification algorithms to model priority based scheduling policies. Next, we added a library to support the modeling of periodic tasks. This library was used in a recent application of the SPIN model checker to verify the engine control software of an automobile, to study the feasibility of software triggers for unintended acceleration events.

  19. Event-driven Monte Carlo: Exact dynamics at all time scales for discrete-variable models

    NASA Astrophysics Data System (ADS)

    Mendoza-Coto, Alejandro; Díaz-Méndez, Rogelio; Pupillo, Guido

    2016-06-01

    We present an algorithm for the simulation of the exact real-time dynamics of classical many-body systems with discrete energy levels. In the same spirit of kinetic Monte Carlo methods, a stochastic solution of the master equation is found, with no need to define any other phase-space construction. However, unlike existing methods, the present algorithm does not assume any particular statistical distribution to perform moves or to advance the time, and thus is a unique tool for the numerical exploration of fast and ultra-fast dynamical regimes. By decomposing the problem in a set of two-level subsystems, we find a natural variable step size, that is well defined from the normalization condition of the transition probabilities between the levels. We successfully test the algorithm with known exact solutions for non-equilibrium dynamics and equilibrium thermodynamical properties of Ising-spin models in one and two dimensions, and compare to standard implementations of kinetic Monte Carlo methods. The present algorithm is directly applicable to the study of the real-time dynamics of a large class of classical Markovian chains, and particularly to short-time situations where the exact evolution is relevant.

  20. A real-time ionospheric model based on GNSS Precise Point Positioning

    NASA Astrophysics Data System (ADS)

    Tu, Rui; Zhang, Hongping; Ge, Maorong; Huang, Guanwen

    2013-09-01

    This paper proposes a method of real-time monitoring and modeling the ionospheric Total Electron Content (TEC) by Precise Point Positioning (PPP). Firstly, the ionospheric TEC and receiver’s Differential Code Biases (DCB) are estimated with the undifferenced raw observation in real-time, then the ionospheric TEC model is established based on the Single Layer Model (SLM) assumption and the recovered ionospheric TEC. In this study, phase observations with high precision are directly used instead of phase smoothed code observations. In addition, the DCB estimation is separated from the establishment of the ionospheric model which will limit the impacts of the SLM assumption impacts. The ionospheric model is established at every epoch for real time application. The method is validated with three different GNSS networks on a local, regional, and global basis. The results show that the method is feasible and effective, the real-time ionosphere and DCB results are very consistent with the IGS final products, with a bias of 1-2 TECU and 0.4 ns respectively.

  1. Efficient implementation of a real-time estimation system for thalamocortical hidden Parkinsonian properties

    NASA Astrophysics Data System (ADS)

    Yang, Shuangming; Deng, Bin; Wang, Jiang; Li, Huiyan; Liu, Chen; Fietkiewicz, Chris; Loparo, Kenneth A.

    2017-01-01

    Real-time estimation of dynamical characteristics of thalamocortical cells, such as dynamics of ion channels and membrane potentials, is useful and essential in the study of the thalamus in Parkinsonian state. However, measuring the dynamical properties of ion channels is extremely challenging experimentally and even impossible in clinical applications. This paper presents and evaluates a real-time estimation system for thalamocortical hidden properties. For the sake of efficiency, we use a field programmable gate array for strictly hardware-based computation and algorithm optimization. In the proposed system, the FPGA-based unscented Kalman filter is implemented into a conductance-based TC neuron model. Since the complexity of TC neuron model restrains its hardware implementation in parallel structure, a cost efficient model is proposed to reduce the resource cost while retaining the relevant ionic dynamics. Experimental results demonstrate the real-time capability to estimate thalamocortical hidden properties with high precision under both normal and Parkinsonian states. While it is applied to estimate the hidden properties of the thalamus and explore the mechanism of the Parkinsonian state, the proposed method can be useful in the dynamic clamp technique of the electrophysiological experiments, the neural control engineering and brain-machine interface studies.

  2. Optimizing Real-Time Vaccine Allocation in a Stochastic SIR Model

    PubMed Central

    Nguyen, Chantal; Carlson, Jean M.

    2016-01-01

    Real-time vaccination following an outbreak can effectively mitigate the damage caused by an infectious disease. However, in many cases, available resources are insufficient to vaccinate the entire at-risk population, logistics result in delayed vaccine deployment, and the interaction between members of different cities facilitates a wide spatial spread of infection. Limited vaccine, time delays, and interaction (or coupling) of cities lead to tradeoffs that impact the overall magnitude of the epidemic. These tradeoffs mandate investigation of optimal strategies that minimize the severity of the epidemic by prioritizing allocation of vaccine to specific subpopulations. We use an SIR model to describe the disease dynamics of an epidemic which breaks out in one city and spreads to another. We solve a master equation to determine the resulting probability distribution of the final epidemic size. We then identify tradeoffs between vaccine, time delay, and coupling, and we determine the optimal vaccination protocols resulting from these tradeoffs. PMID:27043931

  3. Real-time dynamics of matrix quantum mechanics beyond the classical approximation

    NASA Astrophysics Data System (ADS)

    Buividovich, Pavel; Hanada, Masanori; Schäfer, Andreas

    2018-03-01

    We describe a numerical method which allows to go beyond the classical approximation for the real-time dynamics of many-body systems by approximating the many-body Wigner function by the most general Gaussian function with time-dependent mean and dispersion. On a simple example of a classically chaotic system with two degrees of freedom we demonstrate that this Gaussian state approximation is accurate for significantly smaller field strengths and longer times than the classical one. Applying this approximation to matrix quantum mechanics, we demonstrate that the quantum Lyapunov exponents are in general smaller than their classical counterparts, and even seem to vanish below some temperature. This behavior resembles the finite-temperature phase transition which was found for this system in Monte-Carlo simulations, and ensures that the system does not violate the Maldacena-Shenker-Stanford bound λL < 2πT, which inevitably happens for classical dynamics at sufficiently small temperatures.

  4. Real-time Social Internet Data to Guide Forecasting Models

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

    Del Valle, Sara Y.

    Our goal is to improve decision support by monitoring and forecasting events using social media, mathematical models, and quantifying model uncertainty. Our approach is real-time, data-driven forecasts with quantified uncertainty: Not just for weather anymore. Information flow from human observations of events through an Internet system and classification algorithms is used to produce quantitatively uncertain forecast. In summary, we want to develop new tools to extract useful information from Internet data streams, develop new approaches to assimilate real-time information into predictive models, validate approaches by forecasting events, and our ultimate goal is to develop an event forecasting system using mathematicalmore » approaches and heterogeneous data streams.« less

  5. ARTEMIS: Ares Real Time Environments for Modeling, Integration, and Simulation

    NASA Technical Reports Server (NTRS)

    Hughes, Ryan; Walker, David

    2009-01-01

    This slide presentation reviews the use of ARTEMIS in the development and testing of the ARES launch vehicles. Ares Real Time Environment for Modeling, Simulation and Integration (ARTEMIS) is the real time simulation supporting Ares I hardware-in-the-loop (HWIL) testing. ARTEMIS accurately models all Ares/Orion/Ground subsystems which interact with Ares avionics components from pre-launch through orbit insertion The ARTEMIS System integration Lab, and the STIF architecture is reviewed. The functional components of ARTEMIS are outlined. An overview of the models and a block diagram is presented.

  6. Forecasting Hourly Water Demands With Seasonal Autoregressive Models for Real-Time Application

    NASA Astrophysics Data System (ADS)

    Chen, Jinduan; Boccelli, Dominic L.

    2018-02-01

    Consumer water demands are not typically measured at temporal or spatial scales adequate to support real-time decision making, and recent approaches for estimating unobserved demands using observed hydraulic measurements are generally not capable of forecasting demands and uncertainty information. While time series modeling has shown promise for representing total system demands, these models have generally not been evaluated at spatial scales appropriate for representative real-time modeling. This study investigates the use of a double-seasonal time series model to capture daily and weekly autocorrelations to both total system demands and regional aggregated demands at a scale that would capture demand variability across a distribution system. Emphasis was placed on the ability to forecast demands and quantify uncertainties with results compared to traditional time series pattern-based demand models as well as nonseasonal and single-seasonal time series models. Additional research included the implementation of an adaptive-parameter estimation scheme to update the time series model when unobserved changes occurred in the system. For two case studies, results showed that (1) for the smaller-scale aggregated water demands, the log-transformed time series model resulted in improved forecasts, (2) the double-seasonal model outperformed other models in terms of forecasting errors, and (3) the adaptive adjustment of parameters during forecasting improved the accuracy of the generated prediction intervals. These results illustrate the capabilities of time series modeling to forecast both water demands and uncertainty estimates at spatial scales commensurate for real-time modeling applications and provide a foundation for developing a real-time integrated demand-hydraulic model.

  7. Dynamical Behaviors in Complex-Valued Love Model With or Without Time Delays

    NASA Astrophysics Data System (ADS)

    Deng, Wei; Liao, Xiaofeng; Dong, Tao

    2017-12-01

    In this paper, a novel version of nonlinear model, i.e. a complex-valued love model with two time delays between two individuals in a love affair, has been proposed. A notable feature in this model is that we separate the emotion of one individual into real and imaginary parts to represent the variation and complexity of psychophysiological emotion in romantic relationship instead of just real domain, and make our model much closer to reality. This is because love is a complicated cognitive and social phenomenon, full of complexity, diversity and unpredictability, which refers to the coexistence of different aspects of feelings, states and attitudes ranging from joy and trust to sadness and disgust. By analyzing associated characteristic equation of linearized equations for our model, it is found that the Hopf bifurcation occurs when the sum of time delays passes through a sequence of critical value. Stability of bifurcating cyclic love dynamics is also derived by applying the normal form theory and the center manifold theorem. In addition, it is also shown that, for some appropriate chosen parameters, chaotic behaviors can appear even without time delay.

  8. A Real-Time Assimilative Model for IRI

    NASA Astrophysics Data System (ADS)

    Reinisch, B. W.; Huang, X.; Galkin, I.; Bilitza, D.

    2012-04-01

    Ionospheric models are mostly unable to correctly predict the effects of space weather events and atmospheric disturbances on the ionosphere. This is especially true for the International Reference Ionosphere (IRI) which by design is a monthly median (climatological) model [Bilitza et al., 2011]. We propose a Real-Time Assimilative Model "RTAM" for IRI that is ingesting, initially, the available real-time Digisonde GIRO [Reinisch and Galkin, 2011] data streams: foF2/hmF2, MUF3000F2, foF1/hmF1, and foE/hmF2 [Galkin et al., 2011]. Deviations of these characteristics, especially foF2, from the monthly median values are the main cause for errors in the IRI model prediction. The assimilative modeling will provide a high-resolution, global picture of the ionospheric response to various short-term events observed during periods of storm activity or the impact of gravity waves coupling the ionosphere to the lower atmosphere, including timelines of the vertical restructuring of the plasma distribution. GIRO currently provides reliable real-time data from 42 stations at a cadence of 15 min or 5 min. The number of stations is rapidly growing and is likely to soon be complemented by satellite borne topside sounders. IRI uses the characteristics predictions based on CCIR/URSI maps of coefficients. The diurnal variation of the foF2 characteristic, for example, is presented by the Fourier series Σ6 foF 2(T, φ,λ,χ) = a0(φ,λ,χ)+ (an(φ,λ,χ)cosnT + bn(φ,λ,χ)sin nT), n=1 where T is Universal Time in hours, and φ, λ, χ are the geographic latitude, longitude, and modified dip latitude, respectively. The coefficients an are in turn expanded as functions φ, λ, χ resulting in a set of 24 global maps of 988 coefficients each, one for each month of the year and for two levels of solar activity, R12=10 and 100, where R12 is the 12-month running-mean of the monthly sunspot number Rm (2*12*988 = 23,712 coefficients in all) [ITU-R, 2011]. For a given point in time, 988

  9. Virtual sensor models for real-time applications

    NASA Astrophysics Data System (ADS)

    Hirsenkorn, Nils; Hanke, Timo; Rauch, Andreas; Dehlink, Bernhard; Rasshofer, Ralph; Biebl, Erwin

    2016-09-01

    Increased complexity and severity of future driver assistance systems demand extensive testing and validation. As supplement to road tests, driving simulations offer various benefits. For driver assistance functions the perception of the sensors is crucial. Therefore, sensors also have to be modeled. In this contribution, a statistical data-driven sensor-model, is described. The state-space based method is capable of modeling various types behavior. In this contribution, the modeling of the position estimation of an automotive radar system, including autocorrelations, is presented. For rendering real-time capability, an efficient implementation is presented.

  10. Real-time GIS data model and sensor web service platform for environmental data management.

    PubMed

    Gong, Jianya; Geng, Jing; Chen, Zeqiang

    2015-01-09

    Effective environmental data management is meaningful for human health. In the past, environmental data management involved developing a specific environmental data management system, but this method often lacks real-time data retrieving and sharing/interoperating capability. With the development of information technology, a Geospatial Service Web method is proposed that can be employed for environmental data management. The purpose of this study is to determine a method to realize environmental data management under the Geospatial Service Web framework. A real-time GIS (Geographic Information System) data model and a Sensor Web service platform to realize environmental data management under the Geospatial Service Web framework are proposed in this study. The real-time GIS data model manages real-time data. The Sensor Web service platform is applied to support the realization of the real-time GIS data model based on the Sensor Web technologies. To support the realization of the proposed real-time GIS data model, a Sensor Web service platform is implemented. Real-time environmental data, such as meteorological data, air quality data, soil moisture data, soil temperature data, and landslide data, are managed in the Sensor Web service platform. In addition, two use cases of real-time air quality monitoring and real-time soil moisture monitoring based on the real-time GIS data model in the Sensor Web service platform are realized and demonstrated. The total time efficiency of the two experiments is 3.7 s and 9.2 s. The experimental results show that the method integrating real-time GIS data model and Sensor Web Service Platform is an effective way to manage environmental data under the Geospatial Service Web framework.

  11. Dynamic model of time-dependent complex networks.

    PubMed

    Hill, Scott A; Braha, Dan

    2010-10-01

    The characterization of the "most connected" nodes in static or slowly evolving complex networks has helped in understanding and predicting the behavior of social, biological, and technological networked systems, including their robustness against failures, vulnerability to deliberate attacks, and diffusion properties. However, recent empirical research of large dynamic networks (characterized by irregular connections that evolve rapidly) has demonstrated that there is little continuity in degree centrality of nodes over time, even when their degree distributions follow a power law. This unexpected dynamic centrality suggests that the connections in these systems are not driven by preferential attachment or other known mechanisms. We present an approach to explain real-world dynamic networks and qualitatively reproduce these dynamic centrality phenomena. This approach is based on a dynamic preferential attachment mechanism, which exhibits a sharp transition from a base pure random walk scheme.

  12. Real-time inextensible surgical thread simulation.

    PubMed

    Xu, Lang; Liu, Qian

    2018-03-27

    This paper discusses a real-time simulation method of inextensible surgical thread based on the Cosserat rod theory using position-based dynamics (PBD). The method realizes stable twining and knotting of surgical thread while including inextensibility, bending, twisting and coupling effects. The Cosserat rod theory is used to model the nonlinear elastic behavior of surgical thread. The surgical thread model is solved with PBD to achieve a real-time, extremely stable simulation. Due to the one-dimensional linear structure of surgical thread, the direct solution of the distance constraint based on tridiagonal matrix algorithm is used to enhance stretching resistance in every constraint projection iteration. In addition, continuous collision detection and collision response guarantee a large time step and high performance. Furthermore, friction is integrated into the constraint projection process to stabilize the twining of multiple threads and complex contact situations. Through comparisons with existing methods, the surgical thread maintains constant length under large deformation after applying the direct distance constraint in our method. The twining and knotting of multiple threads correspond to stable solutions to contact and friction forces. A surgical suture scene is also modeled to demonstrate the practicality and simplicity of our method. Our method achieves stable and fast simulation of inextensible surgical thread. Benefiting from the unified particle framework, the rigid body, elastic rod, and soft body can be simultaneously simulated. The method is appropriate for applications in virtual surgery that require multiple dynamic bodies.

  13. Real-time stylistic prediction for whole-body human motions.

    PubMed

    Matsubara, Takamitsu; Hyon, Sang-Ho; Morimoto, Jun

    2012-01-01

    The ability to predict human motion is crucial in several contexts such as human tracking by computer vision and the synthesis of human-like computer graphics. Previous work has focused on off-line processes with well-segmented data; however, many applications such as robotics require real-time control with efficient computation. In this paper, we propose a novel approach called real-time stylistic prediction for whole-body human motions to satisfy these requirements. This approach uses a novel generative model to represent a whole-body human motion including rhythmic motion (e.g., walking) and discrete motion (e.g., jumping). The generative model is composed of a low-dimensional state (phase) dynamics and a two-factor observation model, allowing it to capture the diversity of motion styles in humans. A real-time adaptation algorithm was derived to estimate both state variables and style parameter of the model from non-stationary unlabeled sequential observations. Moreover, with a simple modification, the algorithm allows real-time adaptation even from incomplete (partial) observations. Based on the estimated state and style, a future motion sequence can be accurately predicted. In our implementation, it takes less than 15 ms for both adaptation and prediction at each observation. Our real-time stylistic prediction was evaluated for human walking, running, and jumping behaviors. Copyright © 2011 Elsevier Ltd. All rights reserved.

  14. Real Time Data Management for Estimating Probabilities of Incidents and Near Misses

    NASA Astrophysics Data System (ADS)

    Stanitsas, P. D.; Stephanedes, Y. J.

    2011-08-01

    Advances in real-time data collection, data storage and computational systems have led to development of algorithms for transport administrators and engineers that improve traffic safety and reduce cost of road operations. Despite these advances, problems in effectively integrating real-time data acquisition, processing, modelling and road-use strategies at complex intersections and motorways remain. These are related to increasing system performance in identification, analysis, detection and prediction of traffic state in real time. This research develops dynamic models to estimate the probability of road incidents, such as crashes and conflicts, and incident-prone conditions based on real-time data. The models support integration of anticipatory information and fee-based road use strategies in traveller information and management. Development includes macroscopic/microscopic probabilistic models, neural networks, and vector autoregressions tested via machine vision at EU and US sites.

  15. VTI Driving Simulator: Mathematical Model of a Four-wheeled Vehicle for Simulation in Real Time. VTI Rapport 267A.

    ERIC Educational Resources Information Center

    Nordmark, Staffan

    1984-01-01

    This report contains a theoretical model for describing the motion of a passenger car. The simulation program based on this model is used in conjunction with an advanced driving simulator and run in real time. The mathematical model is complete in the sense that the dynamics of the engine, transmission and steering system is described in some…

  16. Real-time face and gesture analysis for human-robot interaction

    NASA Astrophysics Data System (ADS)

    Wallhoff, Frank; Rehrl, Tobias; Mayer, Christoph; Radig, Bernd

    2010-05-01

    Human communication relies on a large number of different communication mechanisms like spoken language, facial expressions, or gestures. Facial expressions and gestures are one of the main nonverbal communication mechanisms and pass large amounts of information between human dialog partners. Therefore, to allow for intuitive human-machine interaction, a real-time capable processing and recognition of facial expressions, hand and head gestures are of great importance. We present a system that is tackling these challenges. The input features for the dynamic head gestures and facial expressions are obtained from a sophisticated three-dimensional model, which is fitted to the user in a real-time capable manner. Applying this model different kinds of information are extracted from the image data and afterwards handed over to a real-time capable data-transferring framework, the so-called Real-Time DataBase (RTDB). In addition to the head and facial-related features, also low-level image features regarding the human hand - optical flow, Hu-moments are stored into the RTDB for the evaluation process of hand gestures. In general, the input of a single camera is sufficient for the parallel evaluation of the different gestures and facial expressions. The real-time capable recognition of the dynamic hand and head gestures are performed via different Hidden Markov Models, which have proven to be a quick and real-time capable classification method. On the other hand, for the facial expressions classical decision trees or more sophisticated support vector machines are used for the classification process. These obtained results of the classification processes are again handed over to the RTDB, where other processes (like a Dialog Management Unit) can easily access them without any blocking effects. In addition, an adjustable amount of history can be stored by the RTDB buffer unit.

  17. Real Time Tracking of Magmatic Intrusions by means of Ground Deformation Modeling during Volcanic Crises.

    PubMed

    Cannavò, Flavio; Camacho, Antonio G; González, Pablo J; Mattia, Mario; Puglisi, Giuseppe; Fernández, José

    2015-06-09

    Volcano observatories provide near real-time information and, ultimately, forecasts about volcano activity. For this reason, multiple physical and chemical parameters are continuously monitored. Here, we present a new method to efficiently estimate the location and evolution of magmatic sources based on a stream of real-time surface deformation data, such as High-Rate GPS, and a free-geometry magmatic source model. The tool allows tracking inflation and deflation sources in time, providing estimates of where a volcano might erupt, which is important in understanding an on-going crisis. We show a successful simulated application to the pre-eruptive period of May 2008, at Mount Etna (Italy). The proposed methodology is able to track the fast dynamics of the magma migration by inverting the real-time data within seconds. This general method is suitable for integration in any volcano observatory. The method provides first order unsupervised and realistic estimates of the locations of magmatic sources and of potential eruption sites, information that is especially important for civil protection purposes.

  18. Real Time Tracking of Magmatic Intrusions by means of Ground Deformation Modeling during Volcanic Crises

    PubMed Central

    Cannavò, Flavio; Camacho, Antonio G.; González, Pablo J.; Mattia, Mario; Puglisi, Giuseppe; Fernández, José

    2015-01-01

    Volcano observatories provide near real-time information and, ultimately, forecasts about volcano activity. For this reason, multiple physical and chemical parameters are continuously monitored. Here, we present a new method to efficiently estimate the location and evolution of magmatic sources based on a stream of real-time surface deformation data, such as High-Rate GPS, and a free-geometry magmatic source model. The tool allows tracking inflation and deflation sources in time, providing estimates of where a volcano might erupt, which is important in understanding an on-going crisis. We show a successful simulated application to the pre-eruptive period of May 2008, at Mount Etna (Italy). The proposed methodology is able to track the fast dynamics of the magma migration by inverting the real-time data within seconds. This general method is suitable for integration in any volcano observatory. The method provides first order unsupervised and realistic estimates of the locations of magmatic sources and of potential eruption sites, information that is especially important for civil protection purposes. PMID:26055494

  19. Real-Time State Estimation and Long-Term Model Adaptation: A Two-Sided Approach toward Personalized Diagnosis of Glucose and Insulin Levels

    PubMed Central

    Eberle, Claudia; Ament, Christoph

    2012-01-01

    Background With continuous glucose sensors (CGSs), it is possible to obtain a dynamical signal of the patient’s subcutaneous glucose concentration in real time. How could that information be exploited? We suggest a model-based diagnosis system with a twofold objective: real-time state estimation and long-term model parameter identification. Methods To obtain a dynamical model, Bergman’s nonlinear minimal model (considering plasma glucose G, insulin I, and interstitial insulin X) is extended by two states describing first and second insulin response. Furthermore, compartments for oral glucose and subcutaneous insulin inputs as well as for subcutaneous glucose measurement are added. The observability of states and external inputs as well as the identifiability of model parameters are assessed using the empirical observability Gramian. Signals are estimated for different nondiabetic and diabetic scenarios by unscented Kalman filter. Results (1) Observability of different state subsets is evaluated, e.g., from CGSs, {G, I} or {G, X} can be observed and the set {G, I, X} cannot. (2) Model parameters are included, e.g., it is possible to estimate the second-phase insulin response gain kG2 additionally. This can be used for model adaptation and as a diagnostic parameter that is almost zero for diabetes patients. (3) External inputs are considered, e.g., oral glucose is theoretically observable for nondiabetic patients, but estimation scenarios show that the time delay of 1 h limits application. Conclusions A real-time estimation of states (such as plasma insulin I) and parameters (such as kG2) is possible, which allows an improved real-time state prediction and a personalized model. PMID:23063042

  20. Real-time implementation of biofidelic SA1 model for tactile feedback.

    PubMed

    Russell, A F; Armiger, R S; Vogelstein, R J; Bensmaia, S J; Etienne-Cummings, R

    2009-01-01

    In order for the functionality of an upper-limb prosthesis to approach that of a real limb it must be able to, accurately and intuitively, convey sensory feedback to the limb user. This paper presents results of the real-time implementation of a 'biofidelic' model that describes mechanotransduction in Slowly Adapting Type 1 (SA1) afferent fibers. The model accurately predicts the timing of action potentials for arbitrary force or displacement stimuli and its output can be used as stimulation times for peripheral nerve stimulation by a neuroprosthetic device. The model performance was verified by comparing the predicted action potential (or spike) outputs against measured spike outputs for different vibratory stimuli. Furthermore experiments were conducted to show that, like real SA1 fibers, the model's spike rate varies according to input pressure and that a periodic 'tapping' stimulus evokes periodic spike outputs.

  1. Real-Time Onboard Global Nonlinear Aerodynamic Modeling from Flight Data

    NASA Technical Reports Server (NTRS)

    Brandon, Jay M.; Morelli, Eugene A.

    2014-01-01

    Flight test and modeling techniques were developed to accurately identify global nonlinear aerodynamic models onboard an aircraft. The techniques were developed and demonstrated during piloted flight testing of an Aermacchi MB-326M Impala jet aircraft. Advanced piloting techniques and nonlinear modeling techniques based on fuzzy logic and multivariate orthogonal function methods were implemented with efficient onboard calculations and flight operations to achieve real-time maneuver monitoring and analysis, and near-real-time global nonlinear aerodynamic modeling and prediction validation testing in flight. Results demonstrated that global nonlinear aerodynamic models for a large portion of the flight envelope were identified rapidly and accurately using piloted flight test maneuvers during a single flight, with the final identified and validated models available before the aircraft landed.

  2. Real-time Nyquist signaling with dynamic precision and flexible non-integer oversampling.

    PubMed

    Schmogrow, R; Meyer, M; Schindler, P C; Nebendahl, B; Dreschmann, M; Meyer, J; Josten, A; Hillerkuss, D; Ben-Ezra, S; Becker, J; Koos, C; Freude, W; Leuthold, J

    2014-01-13

    We demonstrate two efficient processing techniques for Nyquist signals, namely computation of signals using dynamic precision as well as arbitrary rational oversampling factors. With these techniques along with massively parallel processing it becomes possible to generate and receive high data rate Nyquist signals with flexible symbol rates and bandwidths, a feature which is highly desirable for novel flexgrid networks. We achieved maximum bit rates of 252 Gbit/s in real-time.

  3. Boat, wake, and wave real-time simulation

    NASA Astrophysics Data System (ADS)

    Świerkowski, Leszek; Gouthas, Efthimios; Christie, Chad L.; Williams, Owen M.

    2009-05-01

    We describe the extension of our real-time scene generation software VIRSuite to include the dynamic simulation of small boats and their wakes within an ocean environment. Extensive use has been made of the programmabilty available in the current generation of GPUs. We have demonstrated that real-time simulation is feasible, even including such complexities as dynamical calculation of the boat motion, wake generation and calculation of an FFTgenerated sea state.

  4. V/STOL tilt rotor aircraft study mathematical model for a real time simulation of a tilt rotor aircraft (Boeing Vertol Model 222), volume 8

    NASA Technical Reports Server (NTRS)

    Rosenstein, H.; Mcveigh, M. A.; Mollenkof, P. A.

    1973-01-01

    A mathematical model for a real time simulation of a tilt rotor aircraft was developed. The mathematical model is used for evaluating aircraft performance and handling qualities. The model is based on an eleven degree of freedom total force representation. The rotor is treated as a point source of forces and moments with appropriate response time lags and actuator dynamics. The aerodynamics of the wing, tail, rotors, landing gear, and fuselage are included.

  5. Real-time simulation of a spiking neural network model of the basal ganglia circuitry using general purpose computing on graphics processing units.

    PubMed

    Igarashi, Jun; Shouno, Osamu; Fukai, Tomoki; Tsujino, Hiroshi

    2011-11-01

    Real-time simulation of a biologically realistic spiking neural network is necessary for evaluation of its capacity to interact with real environments. However, the real-time simulation of such a neural network is difficult due to its high computational costs that arise from two factors: (1) vast network size and (2) the complicated dynamics of biologically realistic neurons. In order to address these problems, mainly the latter, we chose to use general purpose computing on graphics processing units (GPGPUs) for simulation of such a neural network, taking advantage of the powerful computational capability of a graphics processing unit (GPU). As a target for real-time simulation, we used a model of the basal ganglia that has been developed according to electrophysiological and anatomical knowledge. The model consists of heterogeneous populations of 370 spiking model neurons, including computationally heavy conductance-based models, connected by 11,002 synapses. Simulation of the model has not yet been performed in real-time using a general computing server. By parallelization of the model on the NVIDIA Geforce GTX 280 GPU in data-parallel and task-parallel fashion, faster-than-real-time simulation was robustly realized with only one-third of the GPU's total computational resources. Furthermore, we used the GPU's full computational resources to perform faster-than-real-time simulation of three instances of the basal ganglia model; these instances consisted of 1100 neurons and 33,006 synapses and were synchronized at each calculation step. Finally, we developed software for simultaneous visualization of faster-than-real-time simulation output. These results suggest the potential power of GPGPU techniques in real-time simulation of realistic neural networks. Copyright © 2011 Elsevier Ltd. All rights reserved.

  6. Real-time forecasting of an epidemic using a discrete time stochastic model: a case study of pandemic influenza (H1N1-2009).

    PubMed

    Nishiura, Hiroshi

    2011-02-16

    Real-time forecasting of epidemics, especially those based on a likelihood-based approach, is understudied. This study aimed to develop a simple method that can be used for the real-time epidemic forecasting. A discrete time stochastic model, accounting for demographic stochasticity and conditional measurement, was developed and applied as a case study to the weekly incidence of pandemic influenza (H1N1-2009) in Japan. By imposing a branching process approximation and by assuming the linear growth of cases within each reporting interval, the epidemic curve is predicted using only two parameters. The uncertainty bounds of the forecasts are computed using chains of conditional offspring distributions. The quality of the forecasts made before the epidemic peak appears largely to depend on obtaining valid parameter estimates. The forecasts of both weekly incidence and final epidemic size greatly improved at and after the epidemic peak with all the observed data points falling within the uncertainty bounds. Real-time forecasting using the discrete time stochastic model with its simple computation of the uncertainty bounds was successful. Because of the simplistic model structure, the proposed model has the potential to additionally account for various types of heterogeneity, time-dependent transmission dynamics and epidemiological details. The impact of such complexities on forecasting should be explored when the data become available as part of the disease surveillance.

  7. Real-time forecasting of an epidemic using a discrete time stochastic model: a case study of pandemic influenza (H1N1-2009)

    PubMed Central

    2011-01-01

    Background Real-time forecasting of epidemics, especially those based on a likelihood-based approach, is understudied. This study aimed to develop a simple method that can be used for the real-time epidemic forecasting. Methods A discrete time stochastic model, accounting for demographic stochasticity and conditional measurement, was developed and applied as a case study to the weekly incidence of pandemic influenza (H1N1-2009) in Japan. By imposing a branching process approximation and by assuming the linear growth of cases within each reporting interval, the epidemic curve is predicted using only two parameters. The uncertainty bounds of the forecasts are computed using chains of conditional offspring distributions. Results The quality of the forecasts made before the epidemic peak appears largely to depend on obtaining valid parameter estimates. The forecasts of both weekly incidence and final epidemic size greatly improved at and after the epidemic peak with all the observed data points falling within the uncertainty bounds. Conclusions Real-time forecasting using the discrete time stochastic model with its simple computation of the uncertainty bounds was successful. Because of the simplistic model structure, the proposed model has the potential to additionally account for various types of heterogeneity, time-dependent transmission dynamics and epidemiological details. The impact of such complexities on forecasting should be explored when the data become available as part of the disease surveillance. PMID:21324153

  8. A deformable surface model for real-time water drop animation.

    PubMed

    Zhang, Yizhong; Wang, Huamin; Wang, Shuai; Tong, Yiying; Zhou, Kun

    2012-08-01

    A water drop behaves differently from a large water body because of its strong viscosity and surface tension under the small scale. Surface tension causes the motion of a water drop to be largely determined by its boundary surface. Meanwhile, viscosity makes the interior of a water drop less relevant to its motion, as the smooth velocity field can be well approximated by an interpolation of the velocity on the boundary. Consequently, we propose a fast deformable surface model to realistically animate water drops and their flowing behaviors on solid surfaces. Our system efficiently simulates water drop motions in a Lagrangian fashion, by reducing 3D fluid dynamics over the whole liquid volume to a deformable surface model. In each time step, the model uses an implicit mean curvature flow operator to produce surface tension effects, a contact angle operator to change droplet shapes on solid surfaces, and a set of mesh connectivity updates to handle topological changes and improve mesh quality over time. Our numerical experiments demonstrate a variety of physically plausible water drop phenomena at a real-time rate, including capillary waves when water drops collide, pinch-off of water jets, and droplets flowing over solid materials. The whole system performs orders-of-magnitude faster than existing simulation approaches that generate comparable water drop effects.

  9. A New Real - Time Fault Detection Methodology for Systems Under Test. Phase 1

    NASA Technical Reports Server (NTRS)

    Johnson, Roger W.; Jayaram, Sanjay; Hull, Richard A.

    1998-01-01

    The purpose of this research is focussed on the identification/demonstration of critical technology innovations that will be applied to various applications viz. Detection of automated machine Health Monitoring (BM, real-time data analysis and control of Systems Under Test (SUT). This new innovation using a High Fidelity Dynamic Model-based Simulation (BFDMS) approach will be used to implement a real-time monitoring, Test and Evaluation (T&E) methodology including the transient behavior of the system under test. The unique element of this process control technique is the use of high fidelity, computer generated dynamic models to replicate the behavior of actual Systems Under Test (SUT). It will provide a dynamic simulation capability that becomes the reference truth model, from which comparisons are made with the actual raw/conditioned data from the test elements.

  10. Waste collection multi objective model with real time traceability data.

    PubMed

    Faccio, Maurizio; Persona, Alessandro; Zanin, Giorgia

    2011-12-01

    Waste collection is a highly visible municipal service that involves large expenditures and difficult operational problems, plus it is expensive to operate in terms of investment costs (i.e. vehicles fleet), operational costs (i.e. fuel, maintenances) and environmental costs (i.e. emissions, noise and traffic congestions). Modern traceability devices, like volumetric sensors, identification RFID (Radio Frequency Identification) systems, GPRS (General Packet Radio Service) and GPS (Global Positioning System) technology, permit to obtain data in real time, which is fundamental to implement an efficient and innovative waste collection routing model. The basic idea is that knowing the real time data of each vehicle and the real time replenishment level at each bin makes it possible to decide, in function of the waste generation pattern, what bin should be emptied and what should not, optimizing different aspects like the total covered distance, the necessary number of vehicles and the environmental impact. This paper describes a framework about the traceability technology available in the optimization of solid waste collection, and introduces an innovative vehicle routing model integrated with the real time traceability data, starting the application in an Italian city of about 100,000 inhabitants. The model is tested and validated using simulation and an economical feasibility study is reported at the end of the paper. Copyright © 2011 Elsevier Ltd. All rights reserved.

  11. Real-time image processing for non-contact monitoring of dynamic displacements using smartphone technologies

    NASA Astrophysics Data System (ADS)

    Min, Jae-Hong; Gelo, Nikolas J.; Jo, Hongki

    2016-04-01

    The newly developed smartphone application, named RINO, in this study allows measuring absolute dynamic displacements and processing them in real time using state-of-the-art smartphone technologies, such as high-performance graphics processing unit (GPU), in addition to already powerful CPU and memories, embedded high-speed/ resolution camera, and open-source computer vision libraries. A carefully designed color-patterned target and user-adjustable crop filter enable accurate and fast image processing, allowing up to 240fps for complete displacement calculation and real-time display. The performances of the developed smartphone application are experimentally validated, showing comparable accuracy with those of conventional laser displacement sensor.

  12. Model Checking Real Time Java Using Java PathFinder

    NASA Technical Reports Server (NTRS)

    Lindstrom, Gary; Mehlitz, Peter C.; Visser, Willem

    2005-01-01

    The Real Time Specification for Java (RTSJ) is an augmentation of Java for real time applications of various degrees of hardness. The central features of RTSJ are real time threads; user defined schedulers; asynchronous events, handlers, and control transfers; a priority inheritance based default scheduler; non-heap memory areas such as immortal and scoped, and non-heap real time threads whose execution is not impeded by garbage collection. The Robust Software Systems group at NASA Ames Research Center has JAVA PATHFINDER (JPF) under development, a Java model checker. JPF at its core is a state exploring JVM which can examine alternative paths in a Java program (e.g., via backtracking) by trying all nondeterministic choices, including thread scheduling order. This paper describes our implementation of an RTSJ profile (subset) in JPF, including requirements, design decisions, and current implementation status. Two examples are analyzed: jobs on a multiprogramming operating system, and a complex resource contention example involving autonomous vehicles crossing an intersection. The utility of JPF in finding logic and timing errors is illustrated, and the remaining challenges in supporting all of RTSJ are assessed.

  13. Real-Time Aircraft Cosmic Ray Radiation Exposure Predictions from the NAIRAS Model

    NASA Astrophysics Data System (ADS)

    Mertens, C. J.; Tobiska, W.; Kress, B. T.; Xu, X.

    2012-12-01

    The Nowcast of Atmospheric Ionizing Radiation for Aviation Safety (NAIRAS) is a prototype operational model for predicting commercial aircraft radiation exposure from galactic and solar cosmic rays. NAIRAS predictions are currently streaming live from the project's public website, and the exposure rate nowcast is also available on the SpaceWx smartphone app for iPhone, IPad, and Android. Cosmic rays are the primary source of human exposure to high linear energy transfer radiation at aircraft altitudes, which increases the risk of cancer and other adverse health effects. Thus, the NAIRAS model addresses an important national need with broad societal, public health and economic benefits. There is also interest in extending NAIRAS to the LEO environment to address radiation hazard issues for the emerging commercial spaceflight industry. The processes responsible for the variability in the solar wind, interplanetary magnetic field, solar energetic particle spectrum, and the dynamical response of the magnetosphere to these space environment inputs, strongly influence the composition and energy distribution of the atmospheric ionizing radiation field. Real-time observations are required at a variety of locations within the geospace environment. The NAIRAS model is driven by real-time input data from ground-, atmospheric-, and space-based platforms. During the development of the NAIRAS model, new science questions and observational data gaps were identified that must be addressed in order to obtain a more reliable and robust operational model of atmospheric radiation exposure. The focus of this talk is to present the current capabilities of the NAIRAS model, discuss future developments in aviation radiation modeling and instrumentation, and propose strategies and methodologies of bridging known gaps in current modeling and observational capabilities.

  14. Functional Fault Modeling Conventions and Practices for Real-Time Fault Isolation

    NASA Technical Reports Server (NTRS)

    Ferrell, Bob; Lewis, Mark; Perotti, Jose; Oostdyk, Rebecca; Brown, Barbara

    2010-01-01

    The purpose of this paper is to present the conventions, best practices, and processes that were established based on the prototype development of a Functional Fault Model (FFM) for a Cryogenic System that would be used for real-time Fault Isolation in a Fault Detection, Isolation, and Recovery (FDIR) system. The FDIR system is envisioned to perform health management functions for both a launch vehicle and the ground systems that support the vehicle during checkout and launch countdown by using a suite of complimentary software tools that alert operators to anomalies and failures in real-time. The FFMs were created offline but would eventually be used by a real-time reasoner to isolate faults in a Cryogenic System. Through their development and review, a set of modeling conventions and best practices were established. The prototype FFM development also provided a pathfinder for future FFM development processes. This paper documents the rationale and considerations for robust FFMs that can easily be transitioned to a real-time operating environment.

  15. Geographically distributed real-time digital simulations using linear prediction

    DOE PAGES

    Liu, Ren; Mohanpurkar, Manish; Panwar, Mayank; ...

    2016-07-04

    Real time simulation is a powerful tool for analyzing, planning, and operating modern power systems. For analyzing the ever evolving power systems and understanding complex dynamic and transient interactions larger real time computation capabilities are essential. These facilities are interspersed all over the globe and to leverage unique facilities geographically-distributed real-time co-simulation in analyzing the power systems is pursued and presented. However, the communication latency between different simulator locations may lead to inaccuracy in geographically distributed real-time co-simulations. In this paper, the effect of communication latency on geographically distributed real-time co-simulation is introduced and discussed. In order to reduce themore » effect of the communication latency, a real-time data predictor, based on linear curve fitting is developed and integrated into the distributed real-time co-simulation. Two digital real time simulators are used to perform dynamic and transient co-simulations with communication latency and predictor. Results demonstrate the effect of the communication latency and the performance of the real-time data predictor to compensate it.« less

  16. Geographically distributed real-time digital simulations using linear prediction

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

    Liu, Ren; Mohanpurkar, Manish; Panwar, Mayank

    Real time simulation is a powerful tool for analyzing, planning, and operating modern power systems. For analyzing the ever evolving power systems and understanding complex dynamic and transient interactions larger real time computation capabilities are essential. These facilities are interspersed all over the globe and to leverage unique facilities geographically-distributed real-time co-simulation in analyzing the power systems is pursued and presented. However, the communication latency between different simulator locations may lead to inaccuracy in geographically distributed real-time co-simulations. In this paper, the effect of communication latency on geographically distributed real-time co-simulation is introduced and discussed. In order to reduce themore » effect of the communication latency, a real-time data predictor, based on linear curve fitting is developed and integrated into the distributed real-time co-simulation. Two digital real time simulators are used to perform dynamic and transient co-simulations with communication latency and predictor. Results demonstrate the effect of the communication latency and the performance of the real-time data predictor to compensate it.« less

  17. Real-Time IRI driven by GIRO data

    NASA Astrophysics Data System (ADS)

    Galkin, Ivan; Huang, Xueqin; Reinisch, Bodo; Bilitza, Dieter; Vesnin, Artem

    Real-time extensions of the empirical International Reference Ionosphere (IRI) model are based on assimilative techniques that preserve the IRI formalism which is optimized for the description of climatological ionospheric features. The Global Ionosphere Radio Observatory (GIRO) team has developed critical parts of an IRI Real Time Assimilative Model (IRTAM) for the global ionospheric plasma distribution using measured data available in real time from ~50 ionosondes of the GIRO network, The current assimilation results present global assimilative maps of foF2 and hmF2 that reproduce available data at the sensor sites and smoothly return to the climatological specifications when and where the data are missing, and are free from artificial sharp gradients and short-lived artifacts when viewed in time progression. Animated real-time maps of foF2 and hmF2 are published with a few minutes latency at http://giro.uml.edu/IRTAM/. Our real-time IRI modeling uses morphing, a technique that transforms the climatological ionospheric specifications to match the observations by iteratively computing corrections to the original coefficients of the diurnal/spatial expansions, used in IRI to map the key ionospheric characteristics, while keeping the IRI expansion basis formalism intact. Computation of the updated coefficient set for a given point in time includes analysis of the latest 24-hour history of observations, which allows the morphing technique to sense evolving ionospheric dynamics even with a sparse sensor network. A Non-linear Error Compensation Technique for Associative Restoration (NECTAR), one of the features in our morphing approach, has been in operation at the Lowell GIRO Data Center since 2013. The cornerstone of NECTAR is a recurrent neural network optimizer that is responsible for smoothing the transitions between the grid cells where observations are available. NECTAR has proved suitable for real-time operations that require the assimilation code to be

  18. Integration of Dynamic Models in Range Operations

    NASA Technical Reports Server (NTRS)

    Bardina, Jorge; Thirumalainambi, Rajkumar

    2004-01-01

    This work addresses the various model interactions in real-time to make an efficient internet based decision making tool for Shuttle launch. The decision making tool depends on the launch commit criteria coupled with physical models. Dynamic interaction between a wide variety of simulation applications and techniques, embedded algorithms, and data visualizations are needed to exploit the full potential of modeling and simulation. This paper also discusses in depth details of web based 3-D graphics and applications to range safety. The advantages of this dynamic model integration are secure accessibility and distribution of real time information to other NASA centers.

  19. Real-time computing platform for spiking neurons (RT-spike).

    PubMed

    Ros, Eduardo; Ortigosa, Eva M; Agís, Rodrigo; Carrillo, Richard; Arnold, Michael

    2006-07-01

    A computing platform is described for simulating arbitrary networks of spiking neurons in real time. A hybrid computing scheme is adopted that uses both software and hardware components to manage the tradeoff between flexibility and computational power; the neuron model is implemented in hardware and the network model and the learning are implemented in software. The incremental transition of the software components into hardware is supported. We focus on a spike response model (SRM) for a neuron where the synapses are modeled as input-driven conductances. The temporal dynamics of the synaptic integration process are modeled with a synaptic time constant that results in a gradual injection of charge. This type of model is computationally expensive and is not easily amenable to existing software-based event-driven approaches. As an alternative we have designed an efficient time-based computing architecture in hardware, where the different stages of the neuron model are processed in parallel. Further improvements occur by computing multiple neurons in parallel using multiple processing units. This design is tested using reconfigurable hardware and its scalability and performance evaluated. Our overall goal is to investigate biologically realistic models for the real-time control of robots operating within closed action-perception loops, and so we evaluate the performance of the system on simulating a model of the cerebellum where the emulation of the temporal dynamics of the synaptic integration process is important.

  20. [A review of progress of real-time tumor tracking radiotherapy technology based on dynamic multi-leaf collimator].

    PubMed

    Liu, Fubo; Li, Guangjun; Shen, Jiuling; Li, Ligin; Bai, Sen

    2017-02-01

    While radiation treatment to patients with tumors in thorax and abdomen is being performed, further improvement of radiation accuracy is restricted by the tumor intra-fractional motion due to respiration. Real-time tumor tracking radiation is an optimal solution to tumor intra-fractional motion. A review of the progress of real-time dynamic multi-leaf collimator(DMLC) tracking is provided in the present review, including DMLC tracking method, time lag of DMLC tracking system, and dosimetric verification.

  1. Modeling heterogeneous processor scheduling for real time systems

    NASA Technical Reports Server (NTRS)

    Leathrum, J. F.; Mielke, R. R.; Stoughton, J. W.

    1994-01-01

    A new model is presented to describe dataflow algorithms implemented in a multiprocessing system. Called the resource/data flow graph (RDFG), the model explicitly represents cyclo-static processor schedules as circuits of processor arcs which reflect the order that processors execute graph nodes. The model also allows the guarantee of meeting hard real-time deadlines. When unfolded, the model identifies statically the processor schedule. The model therefore is useful for determining the throughput and latency of systems with heterogeneous processors. The applicability of the model is demonstrated using a space surveillance algorithm.

  2. Real time digital propulsion system simulation for manned flight simulators

    NASA Technical Reports Server (NTRS)

    Mihaloew, J. R.; Hart, C. E.

    1978-01-01

    A real time digital simulation of a STOL propulsion system was developed which generates significant dynamics and internal variables needed to evaluate system performance and aircraft interactions using manned flight simulators. The simulation ran at a real-to-execution time ratio of 8.8. The model was used in a piloted NASA flight simulator program to evaluate the simulation technique and the propulsion system digital control. The simulation is described and results shown. Limited results of the flight simulation program are also presented.

  3. Real-time flutter boundary prediction based on time series models

    NASA Astrophysics Data System (ADS)

    Gu, Wenjing; Zhou, Li

    2018-03-01

    For the purpose of predicting the flutter boundary in real time during flutter flight tests, two time series models accompanied with corresponding stability criterion are adopted in this paper. The first method simplifies a long nonstationary response signal as many contiguous intervals and each is considered to be stationary. The traditional AR model is then established to represent each interval of signal sequence. While the second employs a time-varying AR model to characterize actual measured signals in flutter test with progression variable speed (FTPVS). To predict the flutter boundary, stability parameters are formulated by the identified AR coefficients combined with Jury's stability criterion. The behavior of the parameters is examined using both simulated and wind-tunnel experiment data. The results demonstrate that both methods show significant effectiveness in predicting the flutter boundary at lower speed level. A comparison between the two methods is also given in this paper.

  4. Real-time sensor validation and fusion for distributed autonomous sensors

    NASA Astrophysics Data System (ADS)

    Yuan, Xiaojing; Li, Xiangshang; Buckles, Bill P.

    2004-04-01

    Multi-sensor data fusion has found widespread applications in industrial and research sectors. The purpose of real time multi-sensor data fusion is to dynamically estimate an improved system model from a set of different data sources, i.e., sensors. This paper presented a systematic and unified real time sensor validation and fusion framework (RTSVFF) based on distributed autonomous sensors. The RTSVFF is an open architecture which consists of four layers - the transaction layer, the process fusion layer, the control layer, and the planning layer. This paradigm facilitates distribution of intelligence to the sensor level and sharing of information among sensors, controllers, and other devices in the system. The openness of the architecture also provides a platform to test different sensor validation and fusion algorithms and thus facilitates the selection of near optimal algorithms for specific sensor fusion application. In the version of the model presented in this paper, confidence weighted averaging is employed to address the dynamic system state issue noted above. The state is computed using an adaptive estimator and dynamic validation curve for numeric data fusion and a robust diagnostic map for decision level qualitative fusion. The framework is then applied to automatic monitoring of a gas-turbine engine, including a performance comparison of the proposed real-time sensor fusion algorithms and a traditional numerical weighted average.

  5. Change and Anomaly Detection in Real-Time GPS Data

    NASA Astrophysics Data System (ADS)

    Granat, R.; Pierce, M.; Gao, X.; Bock, Y.

    2008-12-01

    The California Real-Time Network (CRTN) is currently generating real-time GPS position data at a rate of 1-2Hz at over 80 locations. The CRTN data presents the possibility of studying dynamical solid earth processes in a way that complements existing seismic networks. To realize this possibility we have developed a prototype system for detecting changes and anomalies in the real-time data. Through this system, we can can correlate changes in multiple stations in order to detect signals with geographical extent. Our approach involves developing a statistical model for each GPS station in the network, and then using those models to segment the time series into a number of discrete states described by the model. We use a hidden Markov model (HMM) to describe the behavior of each station; fitting the model to the data requires neither labeled training examples nor a priori information about the system. As such, HMMs are well suited to this problem domain, in which the data remains largely uncharacterized. There are two main components to our approach. The first is the model fitting algorithm, regularized deterministic annealing expectation- maximization (RDAEM), which provides robust, high-quality results. The second is a web service infrastructure that connects the data to the statistical modeling analysis and allows us to easily present the results of that analysis through a web portal interface. This web service approach facilitates the automatic updating of station models to keep pace with dynamical changes in the data. Our web portal interface is critical to the process of interpreting the data. A Google Maps interface allows users to visually interpret state changes not only on individual stations but across the entire network. Users can drill down from the map interface to inspect detailed results for individual stations, download the time series data, and inspect fitted models. Alternatively, users can use the web portal look at the evolution of changes on the

  6. Quantitative real-time imaging of glutathione

    USDA-ARS?s Scientific Manuscript database

    Glutathione plays many important roles in biological processes; however, the dynamic changes of glutathione concentrations in living cells remain largely unknown. Here, we report a reversible reaction-based fluorescent probe—designated as RealThiol (RT)—that can quantitatively monitor the real-time ...

  7. Low-cost, efficient wireless intelligent sensors (LEWIS) measuring real-time reference-free dynamic displacements

    NASA Astrophysics Data System (ADS)

    Ozdagli, A. I.; Liu, B.; Moreu, F.

    2018-07-01

    According to railroad managers, displacement of railroad bridges under service loads is an important parameter in the condition assessment and performance evaluation. However, measuring bridge responses in the field is often costly and labor-intensive. This paper proposes a low-cost, efficient wireless intelligent sensor (LEWIS) platform that can compute in real-time the dynamic transverse displacements of railroad bridges under service loads. This sensing platform drives on an open-source Arduino ecosystem and combines low-cost microcontrollers with affordable accelerometers and wireless transmission modules. The proposed LEWIS system is designed to reconstruct dynamic displacements from acceleration measurements onboard, eliminating the need for offline post-processing, and to transmit the data in real-time to a base station where the inspector at the bridge can see the displacements while the train is crossing, or to a remote office if so desired by internet. Researchers validated the effectiveness of the new LEWIS by conducting a series of laboratory experiments. A shake table setup simulated transverse bridge displacements measured on the field and excited the proposed platform, a commercially available wired expensive accelerometer, and reference LVDT displacement sensor. The responses obtained from the wireless system were compared to the displacements reconstructed from commercial accelerometer readings and the reference LVDT. The results of the laboratory experiments demonstrate that the proposed system is capable of reconstructing transverse displacements of railroad bridges under revenue service traffic accurately and transmitting the data in real-time wirelessly. In conclusion, the platform presented in this paper can be used in the performance assessment of railroad bridge network cost-effectively and accurately. Future work includes collecting real-time reference-free displacements of one railroad bridge in Colorado under train crossings to further

  8. RealTime Physics: Active learning laboratory

    NASA Astrophysics Data System (ADS)

    Thornton, Ronald K.; Sokoloff, David R.

    1997-03-01

    Our research shows that student learning of physics concepts in introductory physics courses is enhanced by the use of special guided discovery laboratory curricula which embody the results of educational research and which are supported by the use of the Tools for Scientific Thinking microcomputer-based laboratory (MBL) tools. In this paper we first describe the general characteristics of the research-based RealTime Physics laboratory curricula developed for use in introductory physics classes in colleges, universities and high schools. We then describe RealTime Physics Mechanics in detail. Finally we examine student learning of dynamics in traditional physics courses and in courses using RealTime Physics Mechanics, primarily by the use of correlated questions on the Force and Motion Conceptual Evaluation. We present considerable evidence that students who use the new laboratory curricula demonstrate significantly improved learning and retention of dynamics concepts compared to students taught by traditional methods.

  9. Real time implementation and control validation of the wind energy conversion system

    NASA Astrophysics Data System (ADS)

    Sattar, Adnan

    The purpose of the thesis is to analyze dynamic and transient characteristics of wind energy conversion systems including the stability issues in real time environment using the Real Time Digital Simulator (RTDS). There are different power system simulation tools available in the market. Real time digital simulator (RTDS) is one of the powerful tools among those. RTDS simulator has a Graphical User Interface called RSCAD which contains detail component model library for both power system and control relevant analysis. The hardware is based upon the digital signal processors mounted in the racks. RTDS simulator has the advantage of interfacing the real world signals from the external devices, hence used to test the protection and control system equipments. Dynamic and transient characteristics of the fixed and variable speed wind turbine generating systems (WTGSs) are analyzed, in this thesis. Static Synchronous Compensator (STATCOM) as a flexible ac transmission system (FACTS) device is used to enhance the fault ride through (FRT) capability of the fixed speed wind farm. Two level voltage source converter based STATCOM is modeled in both VSC small time-step and VSC large time-step of RTDS. The simulation results of the RTDS model system are compared with the off-line EMTP software i.e. PSCAD/EMTDC. A new operational scheme for a MW class grid-connected variable speed wind turbine driven permanent magnet synchronous generator (VSWT-PMSG) is developed. VSWT-PMSG uses fully controlled frequency converters for the grid interfacing and thus have the ability to control the real and reactive powers simultaneously. Frequency converters are modeled in the VSC small time-step of the RTDS and three phase realistic grid is adopted with RSCAD simulation through the use of optical analogue digital converter (OADC) card of the RTDS. Steady state and LVRT characteristics are carried out to validate the proposed operational scheme. Simulation results show good agreement with real

  10. Chip-Based Dynamic Real-Time Quantification of Drug-Induced Cytotoxicity in Human Tumor Cells

    PubMed Central

    Wlodkowic, Donald; Skommer, Joanna; McGuinness, Dagmara; Faley, Shannon; Kolch, Walter; Darzynkiewicz, Zbigniew; Cooper, Jonathan M.

    2013-01-01

    Cell cytotoxicity tests are among the most common bioassays using flow cytometry and fluorescence imaging analysis. The permeability of plasma membranes to charged fluorescent probes serves, in these assays, as a marker distinguishing live from dead cells. Since it is generally assumed that probes, such as propidium iodide (PI) or 7-amino-actinomycin D (7-AAD), are themselves cytotoxic, they are currently generally used only as the end-point markers of assays for live versus dead cells. In the current study, we provide novel insights into potential applications of these classical plasma membrane integrity markers in the dynamic tracking of drug-induced cytotoxicity. We show that treatment of a number of different human tumor cell lines in cultures for up to 72 h with the PI, 7-AAD, SYTOX Green (SY-G), SYTOX Red (SYR), TO-PRO, and YO-PRO had no effect on cell viability assessed by the integrity of plasma membrane, cell cycle progression, and rate of proliferation. We subsequently explore the potential of dynamic labeling with these markers in real-time analysis, by comparing results from both conventional cytometry and microfluidic chips. Considering the simplicity of the staining protocols and their low cost combined with the potential for real-time data collection, we show how that real-time fluorescent imaging and Lab-on-a-Chip platforms have the potential to be used for automated drug screening routines. PMID:19572560

  11. Real-time emissions from construction equipment compared with model predictions.

    PubMed

    Heidari, Bardia; Marr, Linsey C

    2015-02-01

    The construction industry is a large source of greenhouse gases and other air pollutants. Measuring and monitoring real-time emissions will provide practitioners with information to assess environmental impacts and improve the sustainability of construction. We employed a portable emission measurement system (PEMS) for real-time measurement of carbon dioxide (CO), nitrogen oxides (NOx), hydrocarbon, and carbon monoxide (CO) emissions from construction equipment to derive emission rates (mass of pollutant emitted per unit time) and emission factors (mass of pollutant emitted per unit volume of fuel consumed) under real-world operating conditions. Measurements were compared with emissions predicted by methodologies used in three models: NONROAD2008, OFFROAD2011, and a modal statistical model. Measured emission rates agreed with model predictions for some pieces of equipment but were up to 100 times lower for others. Much of the difference was driven by lower fuel consumption rates than predicted. Emission factors during idling and hauling were significantly different from each other and from those of other moving activities, such as digging and dumping. It appears that operating conditions introduce considerable variability in emission factors. Results of this research will aid researchers and practitioners in improving current emission estimation techniques, frameworks, and databases.

  12. Distributed simulation using a real-time shared memory network

    NASA Technical Reports Server (NTRS)

    Simon, Donald L.; Mattern, Duane L.; Wong, Edmond; Musgrave, Jeffrey L.

    1993-01-01

    The Advanced Control Technology Branch of the NASA Lewis Research Center performs research in the area of advanced digital controls for aeronautic and space propulsion systems. This work requires the real-time implementation of both control software and complex dynamical models of the propulsion system. We are implementing these systems in a distributed, multi-vendor computer environment. Therefore, a need exists for real-time communication and synchronization between the distributed multi-vendor computers. A shared memory network is a potential solution which offers several advantages over other real-time communication approaches. A candidate shared memory network was tested for basic performance. The shared memory network was then used to implement a distributed simulation of a ramjet engine. The accuracy and execution time of the distributed simulation was measured and compared to the performance of the non-partitioned simulation. The ease of partitioning the simulation, the minimal time required to develop for communication between the processors and the resulting execution time all indicate that the shared memory network is a real-time communication technique worthy of serious consideration.

  13. Diagnosis of delay-deadline failures in real time discrete event models.

    PubMed

    Biswas, Santosh; Sarkar, Dipankar; Bhowal, Prodip; Mukhopadhyay, Siddhartha

    2007-10-01

    In this paper a method for fault detection and diagnosis (FDD) of real time systems has been developed. A modeling framework termed as real time discrete event system (RTDES) model is presented and a mechanism for FDD of the same has been developed. The use of RTDES framework for FDD is an extension of the works reported in the discrete event system (DES) literature, which are based on finite state machines (FSM). FDD of RTDES models are suited for real time systems because of their capability of representing timing faults leading to failures in terms of erroneous delays and deadlines, which FSM-based ones cannot address. The concept of measurement restriction of variables is introduced for RTDES and the consequent equivalence of states and indistinguishability of transitions have been characterized. Faults are modeled in terms of an unmeasurable condition variable in the state map. Diagnosability is defined and the procedure of constructing a diagnoser is provided. A checkable property of the diagnoser is shown to be a necessary and sufficient condition for diagnosability. The methodology is illustrated with an example of a hydraulic cylinder.

  14. An ex vivo laser-induced spinal cord injury model to assess mechanisms of axonal degeneration in real-time.

    PubMed

    Okada, Starlyn L M; Stivers, Nicole S; Stys, Peter K; Stirling, David P

    2014-11-25

    Injured CNS axons fail to regenerate and often retract away from the injury site. Axons spared from the initial injury may later undergo secondary axonal degeneration. Lack of growth cone formation, regeneration, and loss of additional myelinated axonal projections within the spinal cord greatly limits neurological recovery following injury. To assess how central myelinated axons of the spinal cord respond to injury, we developed an ex vivo living spinal cord model utilizing transgenic mice that express yellow fluorescent protein in axons and a focal and highly reproducible laser-induced spinal cord injury to document the fate of axons and myelin (lipophilic fluorescent dye Nile Red) over time using two-photon excitation time-lapse microscopy. Dynamic processes such as acute axonal injury, axonal retraction, and myelin degeneration are best studied in real-time. However, the non-focal nature of contusion-based injuries and movement artifacts encountered during in vivo spinal cord imaging make differentiating primary and secondary axonal injury responses using high resolution microscopy challenging. The ex vivo spinal cord model described here mimics several aspects of clinically relevant contusion/compression-induced axonal pathologies including axonal swelling, spheroid formation, axonal transection, and peri-axonal swelling providing a useful model to study these dynamic processes in real-time. Major advantages of this model are excellent spatiotemporal resolution that allows differentiation between the primary insult that directly injures axons and secondary injury mechanisms; controlled infusion of reagents directly to the perfusate bathing the cord; precise alterations of the environmental milieu (e.g., calcium, sodium ions, known contributors to axonal injury, but near impossible to manipulate in vivo); and murine models also offer an advantage as they provide an opportunity to visualize and manipulate genetically identified cell populations and subcellular

  15. Queueing analysis of a canonical model of real-time multiprocessors

    NASA Technical Reports Server (NTRS)

    Krishna, C. M.; Shin, K. G.

    1983-01-01

    A logical classification of multiprocessor structures from the point of view of control applications is presented. A computation of the response time distribution for a canonical model of a real time multiprocessor is presented. The multiprocessor is approximated by a blocking model. Two separate models are derived: one created from the system's point of view, and the other from the point of view of an incoming task.

  16. 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.

  17. Real-time modeling and simulation of distribution feeder and distributed resources

    NASA Astrophysics Data System (ADS)

    Singh, Pawan

    The analysis of the electrical system dates back to the days when analog network analyzers were used. With the advent of digital computers, many programs were written for power-flow and short circuit analysis for the improvement of the electrical system. Real-time computer simulations can answer many what-if scenarios in the existing or the proposed power system. In this thesis, the standard IEEE 13-Node distribution feeder is developed and validated on a real-time platform OPAL-RT. The concept and the challenges of the real-time simulation are studied and addressed. Distributed energy resources include some of the commonly used distributed generation and storage devices like diesel engine, solar photovoltaic array, and battery storage system are modeled and simulated on a real-time platform. A microgrid encompasses a portion of an electric power distribution which is located downstream of the distribution substation. Normally, the microgrid operates in paralleled mode with the grid; however, scheduled or forced isolation can take place. In such conditions, the microgrid must have the ability to operate stably and autonomously. The microgrid can operate in grid connected and islanded mode, both the operating modes are studied in the last chapter. Towards the end, a simple microgrid controller modeled and simulated on the real-time platform is developed for energy management and protection for the microgrid.

  18. Emergent Auditory Feature Tuning in a Real-Time Neuromorphic VLSI System.

    PubMed

    Sheik, Sadique; Coath, Martin; Indiveri, Giacomo; Denham, Susan L; Wennekers, Thomas; Chicca, Elisabetta

    2012-01-01

    Many sounds of ecological importance, such as communication calls, are characterized by time-varying spectra. However, most neuromorphic auditory models to date have focused on distinguishing mainly static patterns, under the assumption that dynamic patterns can be learned as sequences of static ones. In contrast, the emergence of dynamic feature sensitivity through exposure to formative stimuli has been recently modeled in a network of spiking neurons based on the thalamo-cortical architecture. The proposed network models the effect of lateral and recurrent connections between cortical layers, distance-dependent axonal transmission delays, and learning in the form of Spike Timing Dependent Plasticity (STDP), which effects stimulus-driven changes in the pattern of network connectivity. In this paper we demonstrate how these principles can be efficiently implemented in neuromorphic hardware. In doing so we address two principle problems in the design of neuromorphic systems: real-time event-based asynchronous communication in multi-chip systems, and the realization in hybrid analog/digital VLSI technology of neural computational principles that we propose underlie plasticity in neural processing of dynamic stimuli. The result is a hardware neural network that learns in real-time and shows preferential responses, after exposure, to stimuli exhibiting particular spectro-temporal patterns. The availability of hardware on which the model can be implemented, makes this a significant step toward the development of adaptive, neurobiologically plausible, spike-based, artificial sensory systems.

  19. Emergent Auditory Feature Tuning in a Real-Time Neuromorphic VLSI System

    PubMed Central

    Sheik, Sadique; Coath, Martin; Indiveri, Giacomo; Denham, Susan L.; Wennekers, Thomas; Chicca, Elisabetta

    2011-01-01

    Many sounds of ecological importance, such as communication calls, are characterized by time-varying spectra. However, most neuromorphic auditory models to date have focused on distinguishing mainly static patterns, under the assumption that dynamic patterns can be learned as sequences of static ones. In contrast, the emergence of dynamic feature sensitivity through exposure to formative stimuli has been recently modeled in a network of spiking neurons based on the thalamo-cortical architecture. The proposed network models the effect of lateral and recurrent connections between cortical layers, distance-dependent axonal transmission delays, and learning in the form of Spike Timing Dependent Plasticity (STDP), which effects stimulus-driven changes in the pattern of network connectivity. In this paper we demonstrate how these principles can be efficiently implemented in neuromorphic hardware. In doing so we address two principle problems in the design of neuromorphic systems: real-time event-based asynchronous communication in multi-chip systems, and the realization in hybrid analog/digital VLSI technology of neural computational principles that we propose underlie plasticity in neural processing of dynamic stimuli. The result is a hardware neural network that learns in real-time and shows preferential responses, after exposure, to stimuli exhibiting particular spectro-temporal patterns. The availability of hardware on which the model can be implemented, makes this a significant step toward the development of adaptive, neurobiologically plausible, spike-based, artificial sensory systems. PMID:22347163

  20. Comparison of three-way and four-way calibration for the real-time quantitative analysis of drug hydrolysis in complex dynamic samples by excitation-emission matrix fluorescence.

    PubMed

    Yin, Xiao-Li; Gu, Hui-Wen; Liu, Xiao-Lu; Zhang, Shan-Hui; Wu, Hai-Long

    2018-03-05

    Multiway calibration in combination with spectroscopic technique is an attractive tool for online or real-time monitoring of target analyte(s) in complex samples. However, how to choose a suitable multiway calibration method for the resolution of spectroscopic-kinetic data is a troubling problem in practical application. In this work, for the first time, three-way and four-way fluorescence-kinetic data arrays were generated during the real-time monitoring of the hydrolysis of irinotecan (CPT-11) in human plasma by excitation-emission matrix fluorescence. Alternating normalization-weighted error (ANWE) and alternating penalty trilinear decomposition (APTLD) were used as three-way calibration for the decomposition of the three-way kinetic data array, whereas alternating weighted residual constraint quadrilinear decomposition (AWRCQLD) and alternating penalty quadrilinear decomposition (APQLD) were applied as four-way calibration to the four-way kinetic data array. The quantitative results of the two kinds of calibration models were fully compared from the perspective of predicted real-time concentrations, spiked recoveries of initial concentration, and analytical figures of merit. The comparison study demonstrated that both three-way and four-way calibration models could achieve real-time quantitative analysis of the hydrolysis of CPT-11 in human plasma under certain conditions. However, it was also found that both of them possess some critical advantages and shortcomings during the process of dynamic analysis. The conclusions obtained in this paper can provide some helpful guidance for the reasonable selection of multiway calibration models to achieve the real-time quantitative analysis of target analyte(s) in complex dynamic systems. Copyright © 2017 Elsevier B.V. All rights reserved.

  1. Dynamic Modeling from Flight Data with Unknown Time Skews

    NASA Technical Reports Server (NTRS)

    Morelli, Eugene A.

    2016-01-01

    A method for estimating dynamic model parameters from flight data with unknown time skews is described and demonstrated. The method combines data reconstruction, nonlinear optimization, and equation-error parameter estimation in the frequency domain to accurately estimate both dynamic model parameters and the relative time skews in the data. Data from a nonlinear F-16 aircraft simulation with realistic noise, instrumentation errors, and arbitrary time skews were used to demonstrate the approach. The approach was further evaluated using flight data from a subscale jet transport aircraft, where the measured data were known to have relative time skews. Comparison of modeling results obtained from time-skewed and time-synchronized data showed that the method accurately estimates both dynamic model parameters and relative time skew parameters from flight data with unknown time skews.

  2. Modeling solvation effects in real-space and real-time within density functional approaches

    NASA Astrophysics Data System (ADS)

    Delgado, Alain; Corni, Stefano; Pittalis, Stefano; Rozzi, Carlo Andrea

    2015-10-01

    The Polarizable Continuum Model (PCM) can be used in conjunction with Density Functional Theory (DFT) and its time-dependent extension (TDDFT) to simulate the electronic and optical properties of molecules and nanoparticles immersed in a dielectric environment, typically liquid solvents. In this contribution, we develop a methodology to account for solvation effects in real-space (and real-time) (TD)DFT calculations. The boundary elements method is used to calculate the solvent reaction potential in terms of the apparent charges that spread over the van der Waals solute surface. In a real-space representation, this potential may exhibit a Coulomb singularity at grid points that are close to the cavity surface. We propose a simple approach to regularize such singularity by using a set of spherical Gaussian functions to distribute the apparent charges. We have implemented the proposed method in the Octopus code and present results for the solvation free energies and solvatochromic shifts for a representative set of organic molecules in water.

  3. Modeling solvation effects in real-space and real-time within density functional approaches

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

    Delgado, Alain; Centro de Aplicaciones Tecnológicas y Desarrollo Nuclear, Calle 30 # 502, 11300 La Habana; Corni, Stefano

    2015-10-14

    The Polarizable Continuum Model (PCM) can be used in conjunction with Density Functional Theory (DFT) and its time-dependent extension (TDDFT) to simulate the electronic and optical properties of molecules and nanoparticles immersed in a dielectric environment, typically liquid solvents. In this contribution, we develop a methodology to account for solvation effects in real-space (and real-time) (TD)DFT calculations. The boundary elements method is used to calculate the solvent reaction potential in terms of the apparent charges that spread over the van der Waals solute surface. In a real-space representation, this potential may exhibit a Coulomb singularity at grid points that aremore » close to the cavity surface. We propose a simple approach to regularize such singularity by using a set of spherical Gaussian functions to distribute the apparent charges. We have implemented the proposed method in the OCTOPUS code and present results for the solvation free energies and solvatochromic shifts for a representative set of organic molecules in water.« less

  4. Dynamic I/O Power Management for Hard Real-Time Systems

    DTIC Science & Technology

    2005-01-01

    recently emerged as an attractive alternative to inflexible hardware solutions. DPM for hard real - time systems has received relatively little attention...In particular, energy-driven I/O device scheduling for real - time systems has not been considered before. We present the first online DPM algorithm...which we call Low Energy Device Scheduler (LEDES), for hard real - time systems . LEDES takes as inputs a predetermined task schedule and a device-usage

  5. Integrating real-time and manual monitored data to predict hillslope soil moisture dynamics with high spatio-temporal resolution using linear and non-linear models

    USDA-ARS?s Scientific Manuscript database

    Spatio-temporal variability of soil moisture (') is a challenge that remains to be better understood. A trade-off exists between spatial coverage and temporal resolution when using the manual and real-time ' monitoring methods. This restricted the comprehensive and intensive examination of ' dynamic...

  6. High Fidelity, “Faster than Real-Time” Simulator for Predicting Power System Dynamic Behavior - Final Technical Report

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

    Flueck, Alex

    The “High Fidelity, Faster than Real­Time Simulator for Predicting Power System Dynamic Behavior” was designed and developed by Illinois Institute of Technology with critical contributions from Electrocon International, Argonne National Laboratory, Alstom Grid and McCoy Energy. Also essential to the project were our two utility partners: Commonwealth Edison and AltaLink. The project was a success due to several major breakthroughs in the area of large­scale power system dynamics simulation, including (1) a validated faster than real­ time simulation of both stable and unstable transient dynamics in a large­scale positive sequence transmission grid model, (2) a three­phase unbalanced simulation platform formore » modeling new grid devices, such as independently controlled single­phase static var compensators (SVCs), (3) the world’s first high fidelity three­phase unbalanced dynamics and protection simulator based on Electrocon’s CAPE program, and (4) a first­of­its­ kind implementation of a single­phase induction motor model with stall capability. The simulator results will aid power grid operators in their true time of need, when there is a significant risk of cascading outages. The simulator will accelerate performance and enhance accuracy of dynamics simulations, enabling operators to maintain reliability and steer clear of blackouts. In the long­term, the simulator will form the backbone of the newly conceived hybrid real­time protection and control architecture that will coordinate local controls, wide­area measurements, wide­area controls and advanced real­time prediction capabilities. The nation’s citizens will benefit in several ways, including (1) less down time from power outages due to the faster­than­real­time simulator’s predictive capability, (2) higher levels of reliability due to the detailed dynamics plus protection simulation capability, and (3) more resiliency due to the three­ phase unbalanced simulator

  7. Hard real-time closed-loop electrophysiology with the Real-Time eXperiment Interface (RTXI)

    PubMed Central

    George, Ansel; Dorval, Alan D.; Christini, David J.

    2017-01-01

    The ability to experimentally perturb biological systems has traditionally been limited to static pre-programmed or operator-controlled protocols. In contrast, real-time control allows dynamic probing of biological systems with perturbations that are computed on-the-fly during experimentation. Real-time control applications for biological research are available; however, these systems are costly and often restrict the flexibility and customization of experimental protocols. The Real-Time eXperiment Interface (RTXI) is an open source software platform for achieving hard real-time data acquisition and closed-loop control in biological experiments while retaining the flexibility needed for experimental settings. RTXI has enabled users to implement complex custom closed-loop protocols in single cell, cell network, animal, and human electrophysiology studies. RTXI is also used as a free and open source, customizable electrophysiology platform in open-loop studies requiring online data acquisition, processing, and visualization. RTXI is easy to install, can be used with an extensive range of external experimentation and data acquisition hardware, and includes standard modules for implementing common electrophysiology protocols. PMID:28557998

  8. FPGA-based Fused Smart Sensor for Real-Time Plant-Transpiration Dynamic Estimation

    PubMed Central

    Millan-Almaraz, Jesus Roberto; de Jesus Romero-Troncoso, Rene; Guevara-Gonzalez, Ramon Gerardo; Contreras-Medina, Luis Miguel; Carrillo-Serrano, Roberto Valentin; Osornio-Rios, Roque Alfredo; Duarte-Galvan, Carlos; Rios-Alcaraz, Miguel Angel; Torres-Pacheco, Irineo

    2010-01-01

    Plant transpiration is considered one of the most important physiological functions because it constitutes the plants evolving adaptation to exchange moisture with a dry atmosphere which can dehydrate or eventually kill the plant. Due to the importance of transpiration, accurate measurement methods are required; therefore, a smart sensor that fuses five primary sensors is proposed which can measure air temperature, leaf temperature, air relative humidity, plant out relative humidity and ambient light. A field programmable gate array based unit is used to perform signal processing algorithms as average decimation and infinite impulse response filters to the primary sensor readings in order to reduce the signal noise and improve its quality. Once the primary sensor readings are filtered, transpiration dynamics such as: transpiration, stomatal conductance, leaf-air-temperature-difference and vapor pressure deficit are calculated in real time by the smart sensor. This permits the user to observe different primary and calculated measurements at the same time and the relationship between these which is very useful in precision agriculture in the detection of abnormal conditions. Finally, transpiration related stress conditions can be detected in real time because of the use of online processing and embedded communications capabilities. PMID:22163656

  9. A Circuit Model of Real Time Human Body Hydration.

    PubMed

    Asogwa, Clement Ogugua; Teshome, Assefa K; Collins, Stephen F; Lai, Daniel T H

    2016-06-01

    Changes in human body hydration leading to excess fluid losses or overload affects the body fluid's ability to provide the necessary support for healthy living. We propose a time-dependent circuit model of real-time human body hydration, which models the human body tissue as a signal transmission medium. The circuit model predicts the attenuation of a propagating electrical signal. Hydration rates are modeled by a time constant τ, which characterizes the individual specific metabolic function of the body part measured. We define a surrogate human body anthropometric parameter θ by the muscle-fat ratio and comparing it with the body mass index (BMI), we find theoretically, the rate of hydration varying from 1.73 dB/min, for high θ and low τ to 0.05 dB/min for low θ and high τ. We compare these theoretical values with empirical measurements and show that real-time changes in human body hydration can be observed by measuring signal attenuation. We took empirical measurements using a vector network analyzer and obtained different hydration rates for various BMI, ranging from 0.6 dB/min for 22.7 [Formula: see text] down to 0.04 dB/min for 41.2 [Formula: see text]. We conclude that the galvanic coupling circuit model can predict changes in the volume of the body fluid, which are essential in diagnosing and monitoring treatment of body fluid disorder. Individuals with high BMI would have higher time-dependent biological characteristic, lower metabolic rate, and lower rate of hydration.

  10. Multiple Input Design for Real-Time Parameter Estimation in the Frequency Domain

    NASA Technical Reports Server (NTRS)

    Morelli, Eugene

    2003-01-01

    A method for designing multiple inputs for real-time dynamic system identification in the frequency domain was developed and demonstrated. The designed inputs are mutually orthogonal in both the time and frequency domains, with reduced peak factors to provide good information content for relatively small amplitude excursions. The inputs are designed for selected frequency ranges, and therefore do not require a priori models. The experiment design approach was applied to identify linear dynamic models for the F-15 ACTIVE aircraft, which has multiple control effectors.

  11. Green's Functions from Real-Time Bold-Line Monte Carlo Calculations: Spectral Properties of the Nonequilibrium Anderson Impurity Model

    NASA Astrophysics Data System (ADS)

    Cohen, Guy; Gull, Emanuel; Reichman, David R.; Millis, Andrew J.

    2014-04-01

    The nonequilibrium spectral properties of the Anderson impurity model with a chemical potential bias are investigated within a numerically exact real-time quantum Monte Carlo formalism. The two-time correlation function is computed in a form suitable for nonequilibrium dynamical mean field calculations. Additionally, the evolution of the model's spectral properties are simulated in an alternative representation, defined by a hypothetical but experimentally realizable weakly coupled auxiliary lead. The voltage splitting of the Kondo peak is confirmed and the dynamics of its formation after a coupling or gate quench are studied. This representation is shown to contain additional information about the dot's population dynamics. Further, we show that the voltage-dependent differential conductance gives a reasonable qualitative estimate of the equilibrium spectral function, but significant qualitative differences are found including incorrect trends and spurious temperature dependent effects.

  12. A real-time architecture for time-aware agents.

    PubMed

    Prouskas, Konstantinos-Vassileios; Pitt, Jeremy V

    2004-06-01

    This paper describes the specification and implementation of a new three-layer time-aware agent architecture. This architecture is designed for applications and environments where societies of humans and agents play equally active roles, but interact and operate in completely different time frames. The architecture consists of three layers: the April real-time run-time (ART) layer, the time aware layer (TAL), and the application agents layer (AAL). The ART layer forms the underlying real-time agent platform. An original online, real-time, dynamic priority-based scheduling algorithm is described for scheduling the computation time of agent processes, and it is shown that the algorithm's O(n) complexity and scalable performance are sufficient for application in real-time domains. The TAL layer forms an abstraction layer through which human and agent interactions are temporally unified, that is, handled in a common way irrespective of their temporal representation and scale. A novel O(n2) interaction scheduling algorithm is described for predicting and guaranteeing interactions' initiation and completion times. The time-aware predicting component of a workflow management system is also presented as an instance of the AAL layer. The described time-aware architecture addresses two key challenges in enabling agents to be effectively configured and applied in environments where humans and agents play equally active roles. It provides flexibility and adaptability in its real-time mechanisms while placing them under direct agent control, and it temporally unifies human and agent interactions.

  13. A Second Order Semi-Discrete Cosserat Rod Model Suitable for Dynamic Simulations in Real Time

    NASA Astrophysics Data System (ADS)

    Lang, Holger; Linn, Joachim

    2009-09-01

    We present an alternative approach for a semi-discrete viscoelastic Cosserat rod model that allows both fast dynamic computations within milliseconds and accurate results compared to detailed finite element solutions. The model is able to represent extension, shearing, bending and torsion. For inner dissipation, a consistent damping potential from Antman is chosen. The continuous equations of motion, which consist a system of nonlinear hyperbolic partial differential algebraic equations, are derived from a two dimensional variational principle. The semi-discrete balance equations are obtained by spatial finite difference schemes on a staggered grid and standard index reduction techniques. The right-hand side of the model and its Jacobian can be chosen free of higher algebraic (e.g. root) or transcendent (e.g. trigonometric or exponential) functions and is therefore extremely cheap to evaluate numerically. For the time integration of the system, we use well established stiff solvers. As our model yields computational times within milliseconds, it is suitable for interactive manipulation. It reflects structural mechanics solutions sufficiently correct, as comparison with detailed finite element results shows.

  14. Quasi-dynamical analysis and real-time tissue temperature monitoring during laser vaporization

    NASA Astrophysics Data System (ADS)

    Wang, Hui; Ray, Aditi; Jebens, Dave; Chia, Ray; Hasenberg, Tom

    2014-03-01

    Vaporization and coagulation are two fundamental processes that can be performed during laser-tissue ablation. We demonstrated a method allowing quasi-dynamically observing of the cross-sectional images of tissue response during ablation. The results showed that coagulation depth is relatively constant during vaporization, which supports the excellent hemostasis of green laser benign prostate hyperplasia (BPH) treatment. We also verified a new technology for real-time, in situ tissue temperature monitoring, which may be promising for in vivo tissue vaporization degree feedback during laser ablation to improve the vaporization efficiency and avoid complications.

  15. Research in Distributed Real-Time Systems

    NASA Technical Reports Server (NTRS)

    Mukkamala, R.

    1997-01-01

    This document summarizes the progress we have made on our study of issues concerning the schedulability of real-time systems. Our study has produced several results in the scalability issues of distributed real-time systems. In particular, we have used our techniques to resolve schedulability issues in distributed systems with end-to-end requirements. During the next year (1997-98), we propose to extend the current work to address the modeling and workload characterization issues in distributed real-time systems. In particular, we propose to investigate the effect of different workload models and component models on the design and the subsequent performance of distributed real-time systems.

  16. Effects of rotor model degradation on the accuracy of rotorcraft real time simulation

    NASA Technical Reports Server (NTRS)

    Houck, J. A.; Bowles, R. L.

    1976-01-01

    The effects are studied of degrading a rotating blade element rotor mathematical model to meet various real-time simulation requirements of rotorcraft. Three methods of degradation were studied: reduction of number of blades, reduction of number of blade segments, and increasing the integration interval, which has the corresponding effect of increasing blade azimuthal advance angle. The three degradation methods were studied through static trim comparisons, total rotor force and moment comparisons, single blade force and moment comparisons over one complete revolution, and total vehicle dynamic response comparisons. Recommendations are made concerning model degradation which should serve as a guide for future users of this mathematical model, and in general, they are in order of minimum impact on model validity: (1) reduction of number of blade segments, (2) reduction of number of blades, and (3) increase of integration interval and azimuthal advance angle. Extreme limits are specified beyond which the rotating blade element rotor mathematical model should not be used.

  17. Real-time visualization of the vibrational wavepacket dynamics in electronically excited pyrimidine via femtosecond time-resolved photoelectron imaging

    NASA Astrophysics Data System (ADS)

    Li, Shuai; Long, Jinyou; Ling, Fengzi; Wang, Yanmei; Song, Xinli; Zhang, Song; Zhang, Bing

    2017-07-01

    The vibrational wavepacket dynamics at the very early stages of the S1-T1 intersystem crossing in photoexcited pyrimidine is visualized in real time by femtosecond time-resolved photoelectron imaging and time-resolved mass spectroscopy. A coherent superposition of the vibrational states is prepared by the femtosecond pump pulse at 315.3 nm, resulting in a vibrational wavepacket. The composition of the prepared wavepacket is directly identified by a sustained quantum beat superimposed on the parent-ion transient, possessing a frequency in accord with the energy separation between the 6a1 and 6b2 states. The dephasing time of the vibrational wavepacket is determined to be 82 ps. More importantly, the variable Franck-Condon factors between the wavepacket components and the dispersed cation vibrational levels are experimentally illustrated to identify the dark state and follow the energy-flow dynamics on the femtosecond time scale. The time-dependent intensities of the photoelectron peaks originated from the 6a1 vibrational state exhibit a clear quantum beating pattern with similar periodicity but a phase shift of π rad with respect to those from the 6b2 state, offering an unambiguous picture of the restricted intramolecular vibrational energy redistribution dynamics in the 6a1/6b2 Fermi resonance.

  18. A New Model for Real-Time Regional Vertical Total Electron Content and Differential Code Bias Estimation Using IGS Real-Time Service (IGS-RTS) Products

    NASA Astrophysics Data System (ADS)

    Abdelazeem, Mohamed; Çelik, Rahmi N.; El-Rabbany, Ahmed

    2016-04-01

    The international global navigation satellite system (GNSS) real-time service (IGS-RTS) products have been used extensively for real-time precise point positioning and ionosphere modeling applications. In this study, we develop a regional model for real-time vertical total electron content (RT-VTEC) and differential code bias (RT-DCB) estimation over Europe using the IGS-RTS satellite orbit and clock products. The developed model has a spatial and temporal resolution of 1°×1° and 15 minutes, respectively. GPS observations from a regional network consisting of 60 IGS and EUREF reference stations are processed in the zero-difference mode using the Bernese-5.2 software package in order to extract the geometry-free linear combination of the smoothed code observations. The spherical harmonic expansion function is used to model the VTEC, the receiver and the satellite DCBs. To validate the proposed model, the RT-VTEC values are computed and compared with the final IGS-global ionospheric map (IGS-GIM) counterparts in three successive days under high solar activity including one of an extreme geomagnetic activity. The real-time satellite DCBs are also estimated and compared with the IGS-GIM counterparts. Moreover, the real-time receiver DCB for six IGS stations are obtained and compared with the IGS-GIM counterparts. The examined stations are located in different latitudes with different receiver types. The findings reveal that the estimated RT-VTEC values show agreement with the IGS-GIM counterparts with root mean-square-errors (RMSEs) values less than 2 TEC units. In addition, RMSEs of both the satellites and receivers DCBs are less than 0.85 ns and 0.65 ns, respectively in comparison with the IGS-GIM.

  19. Real time wave forecasting using wind time history and numerical model

    NASA Astrophysics Data System (ADS)

    Jain, Pooja; Deo, M. C.; Latha, G.; Rajendran, V.

    Operational activities in the ocean like planning for structural repairs or fishing expeditions require real time prediction of waves over typical time duration of say a few hours. Such predictions can be made by using a numerical model or a time series model employing continuously recorded waves. This paper presents another option to do so and it is based on a different time series approach in which the input is in the form of preceding wind speed and wind direction observations. This would be useful for those stations where the costly wave buoys are not deployed and instead only meteorological buoys measuring wind are moored. The technique employs alternative artificial intelligence approaches of an artificial neural network (ANN), genetic programming (GP) and model tree (MT) to carry out the time series modeling of wind to obtain waves. Wind observations at four offshore sites along the east coast of India were used. For calibration purpose the wave data was generated using a numerical model. The predicted waves obtained using the proposed time series models when compared with the numerically generated waves showed good resemblance in terms of the selected error criteria. Large differences across the chosen techniques of ANN, GP, MT were not noticed. Wave hindcasting at the same time step and the predictions over shorter lead times were better than the predictions over longer lead times. The proposed method is a cost effective and convenient option when a site-specific information is desired.

  20. Real-time maneuver optimization of space-based robots in a dynamic environment: Theory and on-orbit experiments

    NASA Astrophysics Data System (ADS)

    Chamitoff, Gregory E.; Saenz-Otero, Alvar; Katz, Jacob G.; Ulrich, Steve; Morrell, Benjamin J.; Gibbens, Peter W.

    2018-01-01

    This paper presents the development of a real-time path-planning optimization approach to controlling the motion of space-based robots. The algorithm is capable of planning three dimensional trajectories for a robot to navigate within complex surroundings that include numerous static and dynamic obstacles, path constraints and performance limitations. The methodology employs a unique transformation that enables rapid generation of feasible solutions for complex geometries, making it suitable for application to real-time operations and dynamic environments. This strategy was implemented on the Synchronized Position Hold Engage Reorient Experimental Satellite (SPHERES) test-bed on the International Space Station (ISS), and experimental testing was conducted onboard the ISS during Expedition 17 by the first author. Lessons learned from the on-orbit tests were used to further refine the algorithm for future implementations.

  1. Adaptive Anchoring Model: How Static and Dynamic Presentations of Time Series Influence Judgments and Predictions.

    PubMed

    Kusev, Petko; van Schaik, Paul; Tsaneva-Atanasova, Krasimira; Juliusson, Asgeir; Chater, Nick

    2018-01-01

    When attempting to predict future events, people commonly rely on historical data. One psychological characteristic of judgmental forecasting of time series, established by research, is that when people make forecasts from series, they tend to underestimate future values for upward trends and overestimate them for downward ones, so-called trend-damping (modeled by anchoring on, and insufficient adjustment from, the average of recent time series values). Events in a time series can be experienced sequentially (dynamic mode), or they can also be retrospectively viewed simultaneously (static mode), not experienced individually in real time. In one experiment, we studied the influence of presentation mode (dynamic and static) on two sorts of judgment: (a) predictions of the next event (forecast) and (b) estimation of the average value of all the events in the presented series (average estimation). Participants' responses in dynamic mode were anchored on more recent events than in static mode for all types of judgment but with different consequences; hence, dynamic presentation improved prediction accuracy, but not estimation. These results are not anticipated by existing theoretical accounts; we develop and present an agent-based model-the adaptive anchoring model (ADAM)-to account for the difference between processing sequences of dynamically and statically presented stimuli (visually presented data). ADAM captures how variation in presentation mode produces variation in responses (and the accuracy of these responses) in both forecasting and judgment tasks. ADAM's model predictions for the forecasting and judgment tasks fit better with the response data than a linear-regression time series model. Moreover, ADAM outperformed autoregressive-integrated-moving-average (ARIMA) and exponential-smoothing models, while neither of these models accounts for people's responses on the average estimation task. Copyright © 2017 The Authors. Cognitive Science published by Wiley

  2. Rapid Modeling of and Response to Large Earthquakes Using Real-Time GPS Networks (Invited)

    NASA Astrophysics Data System (ADS)

    Crowell, B. W.; Bock, Y.; Squibb, M. B.

    2010-12-01

    Real-time GPS networks have the advantage of capturing motions throughout the entire earthquake cycle (interseismic, seismic, coseismic, postseismic), and because of this, are ideal for real-time monitoring of fault slip in the region. Real-time GPS networks provide the perfect supplement to seismic networks, which operate with lower noise and higher sampling rates than GPS networks, but only measure accelerations or velocities, putting them at a supreme disadvantage for ascertaining the full extent of slip during a large earthquake in real-time. Here we report on two examples of rapid modeling of recent large earthquakes near large regional real-time GPS networks. The first utilizes Japan’s GEONET consisting of about 1200 stations during the 2003 Mw 8.3 Tokachi-Oki earthquake about 100 km offshore Hokkaido Island and the second investigates the 2010 Mw 7.2 El Mayor-Cucapah earthquake recorded by more than 100 stations in the California Real Time Network. The principal components of strain were computed throughout the networks and utilized as a trigger to initiate earthquake modeling. Total displacement waveforms were then computed in a simulated real-time fashion using a real-time network adjustment algorithm that fixes a station far away from the rupture to obtain a stable reference frame. Initial peak ground displacement measurements can then be used to obtain an initial size through scaling relationships. Finally, a full coseismic model of the event can be run minutes after the event, given predefined fault geometries, allowing emergency first responders and researchers to pinpoint the regions of highest damage. Furthermore, we are also investigating using total displacement waveforms for real-time moment tensor inversions to look at spatiotemporal variations in slip.

  3. Versatile Software Package For Near Real-Time Analysis of Experimental Data

    NASA Technical Reports Server (NTRS)

    Wieseman, Carol D.; Hoadley, Sherwood T.

    1998-01-01

    This paper provides an overview of a versatile software package developed for time- and frequency-domain analyses of experimental wind-tunnel data. This package, originally developed for analyzing data in the NASA Langley Transonic Dynamics Tunnel (TDT), is applicable for analyzing any time-domain data. A Matlab-based software package, TDT-analyzer, provides a compendium of commonly-required dynamic analysis functions in a user-friendly interactive and batch processing environment. TDT-analyzer has been used extensively to provide on-line near real-time and post-test examination and reduction of measured data acquired during wind tunnel tests of aeroelastically-scaled models of aircraft and rotorcraft as well as a flight test of the NASA High Alpha Research Vehicle (HARV) F-18. The package provides near real-time results in an informative and timely manner far exceeding prior methods of data reduction at the TDT.

  4. The Ionosphere Real-Time Assimilative Model, IRTAM - A Status Report

    NASA Astrophysics Data System (ADS)

    Reinisch, Bodo; Galkin, Ivan; Huang, Xueqin; Vesnin, Artem; Bilitza, Dieter

    2014-05-01

    Ionospheric models are generally unable to correctly predict the effects of space weather events on the ionosphere. Taking advantage of today's real-time availability of measured electron density profiles of the bottomside ionosphere, we have developed a technique "IRTAM" to specify real-time foF2 and hmF2 global maps. The measured data arrive at the Lowell GIRO Data Center (LGDC) from some ~70 ionosonde stations of the Global Ionosphere Radio Observatory (GIRO) [Reinisch and Galkin, 2011], usually at a 15 min cadence, and are ingested in LGDC's databases (http://ulcar.uml.edu/DIDBase/). We use the International Reference Ionosphere (IRI) electron density model [Bilitza et al., 2011] as the background model. It is an empirical monthly median model that critically depends on the correct values of the F2 layer peak height hmF2 and density NmF2 (or critical frequency foF2). The IRI model uses the so-called CCIR (or URSI) coefficients for the specification of the median foF2 and hmF2 maps. IRTAM assimilates the measured GIRO data in IRI by "adjusting" the CCIR coefficients on-the-fly. The updated maps of foF2 and hmF2 for the last 24 hours before now-time are continuously displayed on http://giro.uml.edu/RTAM [Galkin et al., 2012]. The "adjusted" bottomside profiles can be extended to the topside by using the new Vary-Chap topside profile model [Nsumei et al., 2012] which extends the profile from hmF2 to the plasmasphere. References Bilitza D., L.-A. McKinnell, B. Reinisch, and T. Fuller-Rowell (2011), The International Reference Ionosphere (IRI) today and in the future, J. Geodesy, 85:909-920, DOI 10.1007/s00190-010-0427-x Galkin, I. A., B. W. Reinisch, X. Huang, and D. Bilitza (2012), Assimilation of GIRO Data into a Real-Time IRI, Radio Sci., 47, RS0L07, doi:10.1029/2011RS004952. Nsumei, P., B. W. Reinisch, X. Huang, and D. Bilitza (2012), New Vary-Chap profile of the topside ionosphere electron density distribution for use with the IRI Model and the GIRO real time

  5. Modeling Nonstationary Emotion Dynamics in Dyads using a Time-Varying Vector-Autoregressive Model.

    PubMed

    Bringmann, Laura F; Ferrer, Emilio; Hamaker, Ellen L; Borsboom, Denny; Tuerlinckx, Francis

    2018-01-01

    Emotion dynamics are likely to arise in an interpersonal context. Standard methods to study emotions in interpersonal interaction are limited because stationarity is assumed. This means that the dynamics, for example, time-lagged relations, are invariant across time periods. However, this is generally an unrealistic assumption. Whether caused by an external (e.g., divorce) or an internal (e.g., rumination) event, emotion dynamics are prone to change. The semi-parametric time-varying vector-autoregressive (TV-VAR) model is based on well-studied generalized additive models, implemented in the software R. The TV-VAR can explicitly model changes in temporal dependency without pre-existing knowledge about the nature of change. A simulation study is presented, showing that the TV-VAR model is superior to the standard time-invariant VAR model when the dynamics change over time. The TV-VAR model is applied to empirical data on daily feelings of positive affect (PA) from a single couple. Our analyses indicate reliable changes in the male's emotion dynamics over time, but not in the female's-which were not predicted by her own affect or that of her partner. This application illustrates the usefulness of using a TV-VAR model to detect changes in the dynamics in a system.

  6. Real-time and interactive virtual Doppler ultrasound

    NASA Astrophysics Data System (ADS)

    Hirji, Samira; Downey, Donal B.; Holdsworth, David W.; Steinman, David A.

    2005-04-01

    This paper describes our "virtual" Doppler ultrasound (DUS) system, in which colour DUS (CDUS) images and DUS spectrograms are generated on-the-fly and displayed in real-time in response to position and orientation cues provided by a magnetically tracked handheld probe. As the presence of complex flow often confounds the interpretation of Doppler ultrasound data, this system will serve to be a fundamental tool for training sonographers and gaining insight into the relationship between ambiguous DUS images and complex blood flow dynamics. Recently, we demonstrated that DUS spectra could be realistically simulated in real-time, by coupling a semi-empirical model of the DUS physics to a 3-D computational fluid dynamics (CFD) model of a clinically relevant flow field. Our system is an evolution of this approach where a motion-tracking device is used to continuously update the origin and orientation of a slice passing through a CFD model of a stenosed carotid bifurcation. After calibrating our CFD model onto a physical representation of a human neck, virtual CDUS images from an instantaneous slice are then displayed at a rate of approximately 15 Hz by simulating, on-the-fly, an array of DUS spectra and colour coding the resulting spectral mean velocity using a traditional Doppler colour scale. Mimicking a clinical examination, the operator can freeze the CDUS image on-screen, and a spectrogram corresponding to the selected sample volume location is rendered at a higher frame rate of at least 30 Hz. All this is achieved using an inexpensive desktop workstation and commodity graphics card.

  7. Application of troposphere model from NWP and GNSS data into real-time precise positioning

    NASA Astrophysics Data System (ADS)

    Wilgan, Karina; Hadas, Tomasz; Kazmierski, Kamil; Rohm, Witold; Bosy, Jaroslaw

    2016-04-01

    The tropospheric delay empirical models are usually functions of meteorological parameters (temperature, pressure and humidity). The application of standard atmosphere parameters or global models, such as GPT (global pressure/temperature) model or UNB3 (University of New Brunswick, version 3) model, may not be sufficient, especially for positioning in non-standard weather conditions. The possible solution is to use regional troposphere models based on real-time or near-real time measurements. We implement a regional troposphere model into the PPP (Precise Point Positioning) software GNSS-WARP (Wroclaw Algorithms for Real-time Positioning) developed at Wroclaw University of Environmental and Life Sciences. The software is capable of processing static and kinematic multi-GNSS data in real-time and post-processing mode and takes advantage of final IGS (International GNSS Service) products as well as IGS RTS (Real-Time Service) products. A shortcoming of PPP technique is the time required for the solution to converge. One of the reasons is the high correlation among the estimated parameters: troposphere delay, receiver clock offset and receiver height. To efficiently decorrelate these parameters, a significant change in satellite geometry is required. Alternative solution is to introduce the external high-quality regional troposphere delay model to constrain troposphere estimates. The proposed model consists of zenith total delays (ZTD) and mapping functions calculated from meteorological parameters from Numerical Weather Prediction model WRF (Weather Research and Forecasting) and ZTDs from ground-based GNSS stations using the least-squares collocation software COMEDIE (Collocation of Meteorological Data for Interpretation and Estimation of Tropospheric Pathdelays) developed at ETH Zurich.

  8. Modeling biological pathway dynamics with timed automata.

    PubMed

    Schivo, Stefano; Scholma, Jetse; Wanders, Brend; Urquidi Camacho, Ricardo A; van der Vet, Paul E; Karperien, Marcel; Langerak, Rom; van de Pol, Jaco; Post, Janine N

    2014-05-01

    Living cells are constantly subjected to a plethora of environmental stimuli that require integration into an appropriate cellular response. This integration takes place through signal transduction events that form tightly interconnected networks. The understanding of these networks requires capturing their dynamics through computational support and models. ANIMO (analysis of Networks with Interactive Modeling) is a tool that enables the construction and exploration of executable models of biological networks, helping to derive hypotheses and to plan wet-lab experiments. The tool is based on the formalism of Timed Automata, which can be analyzed via the UPPAAL model checker. Thanks to Timed Automata, we can provide a formal semantics for the domain-specific language used to represent signaling networks. This enforces precision and uniformity in the definition of signaling pathways, contributing to the integration of isolated signaling events into complex network models. We propose an approach to discretization of reaction kinetics that allows us to efficiently use UPPAAL as the computational engine to explore the dynamic behavior of the network of interest. A user-friendly interface hides the use of Timed Automata from the user, while keeping the expressive power intact. Abstraction to single-parameter kinetics speeds up construction of models that remain faithful enough to provide meaningful insight. The resulting dynamic behavior of the network components is displayed graphically, allowing for an intuitive and interactive modeling experience.

  9. The design of real time infrared image generation software based on Creator and Vega

    NASA Astrophysics Data System (ADS)

    Wang, Rui-feng; Wu, Wei-dong; Huo, Jun-xiu

    2013-09-01

    Considering the requirement of high reality and real-time quality dynamic infrared image of an infrared image simulation, a method to design real-time infrared image simulation application on the platform of VC++ is proposed. This is based on visual simulation software Creator and Vega. The functions of Creator are introduced simply, and the main features of Vega developing environment are analyzed. The methods of infrared modeling and background are offered, the designing flow chart of the developing process of IR image real-time generation software and the functions of TMM Tool and MAT Tool and sensor module are explained, at the same time, the real-time of software is designed.

  10. Real-time characterization of partially observed epidemics using surrogate models.

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

    Safta, Cosmin; Ray, Jaideep; Lefantzi, Sophia

    We present a statistical method, predicated on the use of surrogate models, for the 'real-time' characterization of partially observed epidemics. Observations consist of counts of symptomatic patients, diagnosed with the disease, that may be available in the early epoch of an ongoing outbreak. Characterization, in this context, refers to estimation of epidemiological parameters that can be used to provide short-term forecasts of the ongoing epidemic, as well as to provide gross information on the dynamics of the etiologic agent in the affected population e.g., the time-dependent infection rate. The characterization problem is formulated as a Bayesian inverse problem, and epidemiologicalmore » parameters are estimated as distributions using a Markov chain Monte Carlo (MCMC) method, thus quantifying the uncertainty in the estimates. In some cases, the inverse problem can be computationally expensive, primarily due to the epidemic simulator used inside the inversion algorithm. We present a method, based on replacing the epidemiological model with computationally inexpensive surrogates, that can reduce the computational time to minutes, without a significant loss of accuracy. The surrogates are created by projecting the output of an epidemiological model on a set of polynomial chaos bases; thereafter, computations involving the surrogate model reduce to evaluations of a polynomial. We find that the epidemic characterizations obtained with the surrogate models is very close to that obtained with the original model. We also find that the number of projections required to construct a surrogate model is O(10)-O(10{sup 2}) less than the number of samples required by the MCMC to construct a stationary posterior distribution; thus, depending upon the epidemiological models in question, it may be possible to omit the offline creation and caching of surrogate models, prior to their use in an inverse problem. The technique is demonstrated on synthetic data as well as

  11. Real-time interferometric diagnostics of rubidium plasma

    NASA Astrophysics Data System (ADS)

    Djotyan, G. P.; Bakos, J. S.; Kedves, M. Á.; Ráczkevi, B.; Dzsotjan, D.; Varga-Umbrich, K.; Sörlei, Zs.; Szigeti, J.; Ignácz, P.; Lévai, P.; Czitrovszky, A.; Nagy, A.; Dombi, P.; Rácz, P.

    2018-03-01

    A method of interferometric real-time diagnostics is developed and applied to rubidium plasma created by strong laser pulses in the femtosecond duration range at different initial rubidium vapor densities using a Michelson-type interferometer. A cosine fit with an exponentially decaying relative phase is applied to the obtained time-dependent interferometry signals to measure the density-length product of the created plasma and its recombination time constant. The presented technique may be applicable for real-time measurements of rubidium plasma dynamics in the AWAKE experiment at CERN, as well as for real-time diagnostics of plasmas created in different gaseous media and on surfaces of solid targets.

  12. Real-time Fatigue and Free-Living Physical Activity in Hematopoietic Stem Cell Transplantation Cancer Survivors and Healthy Controls: A Preliminary Examination of the Temporal, Dynamic Relationship.

    PubMed

    Hacker, Eileen Danaher; Kim, Inah; Park, Chang; Peters, Tara

    Fatigue and physical inactivity, critical problems facing cancer survivors, impact overall health and functioning. Our group designed a novel methodology to evaluate the temporal, dynamic patterns in real-world settings. Using real-time technology, the temporal, dynamic relationship between real-time fatigue and free-living is described and compared in cancer survivors who were treated with hematopoietic stem cell transplantation (n = 25) and age- and gender-matched healthy controls (n = 25). Subjects wore wrist actigraphs on their nondominant hand to assess free-living physical activity, measured in 1-minute epochs, over 7 days. Subjects entered real-time fatigue assessments directly into the subjective event marker of the actigraph 5 times per day. Running averages of mean 1-minute activity counts 30, 60, and 120 minutes before and after each real-time fatigue score were correlated with real-time fatigue using generalized estimating equations, RESULTS:: A strong inverse relationship exists between real-time fatigue and subsequent free-living physical activity. This inverse relationship suggests that increasing real-time fatigue limits subsequent physical activity (B range= -0.002 to -0.004; P < .001). No significant differences in the dynamic patterns of real-time fatigue and free-living physical activity were found between groups. To our knowledge, this is the first study to document the temporal and potentially causal relationship between real-time fatigue and free-living physical activity in real-world setting. These findings suggest that fatigue drives the subsequent physical activity and the relationship may not be bidirectional. Understanding the temporal, dynamic relationship may have important health implications for developing interventions to address fatigue in cancer survivors.

  13. Reasoning about real-time systems with temporal interval logic constraints on multi-state automata

    NASA Technical Reports Server (NTRS)

    Gabrielian, Armen

    1991-01-01

    Models of real-time systems using a single paradigm often turn out to be inadequate, whether the paradigm is based on states, rules, event sequences, or logic. A model-based approach to reasoning about real-time systems is presented in which a temporal interval logic called TIL is employed to define constraints on a new type of high level automata. The combination, called hierarchical multi-state (HMS) machines, can be used to model formally a real-time system, a dynamic set of requirements, the environment, heuristic knowledge about planning-related problem solving, and the computational states of the reasoning mechanism. In this framework, mathematical techniques were developed for: (1) proving the correctness of a representation; (2) planning of concurrent tasks to achieve goals; and (3) scheduling of plans to satisfy complex temporal constraints. HMS machines allow reasoning about a real-time system from a model of how truth arises instead of merely depending of what is true in a system.

  14. A real-time computational model for estimating kinematics of ankle ligaments.

    PubMed

    Zhang, Mingming; Davies, T Claire; Zhang, Yanxin; Xie, Sheng Quan

    2016-01-01

    An accurate assessment of ankle ligament kinematics is crucial in understanding the injury mechanisms and can help to improve the treatment of an injured ankle, especially when used in conjunction with robot-assisted therapy. A number of computational models have been developed and validated for assessing the kinematics of ankle ligaments. However, few of them can do real-time assessment to allow for an input into robotic rehabilitation programs. An ankle computational model was proposed and validated to quantify the kinematics of ankle ligaments as the foot moves in real-time. This model consists of three bone segments with three rotational degrees of freedom (DOFs) and 12 ankle ligaments. This model uses inputs for three position variables that can be measured from sensors in many ankle robotic devices that detect postures within the foot-ankle environment and outputs the kinematics of ankle ligaments. Validation of this model in terms of ligament length and strain was conducted by comparing it with published data on cadaver anatomy and magnetic resonance imaging. The model based on ligament lengths and strains is in concurrence with those from the published studies but is sensitive to ligament attachment positions. This ankle computational model has the potential to be used in robot-assisted therapy for real-time assessment of ligament kinematics. The results provide information regarding the quantification of kinematics associated with ankle ligaments related to the disability level and can be used for optimizing the robotic training trajectory.

  15. A Distributed Web-based Solution for Ionospheric Model Real-time Management, Monitoring, and Short-term Prediction

    NASA Astrophysics Data System (ADS)

    Kulchitsky, A.; Maurits, S.; Watkins, B.

    2006-12-01

    With the widespread availability of the Internet today, many people can monitor various scientific research activities. It is important to accommodate this interest providing on-line access to dynamic and illustrative Web-resources, which could demonstrate different aspects of ongoing research. It is especially important to explain and these research activities for high school and undergraduate students, thereby providing more information for making decisions concerning their future studies. Such Web resources are also important to clarify scientific research for the general public, in order to achieve better awareness of research progress in various fields. Particularly rewarding is dissemination of information about ongoing projects within Universities and research centers to their local communities. The benefits of this type of scientific outreach are mutual, since development of Web-based automatic systems is prerequisite for many research projects targeting real-time monitoring and/or modeling of natural conditions. Continuous operation of such systems provide ongoing research opportunities for the statistically massive validation of the models, as well. We have developed a Web-based system to run the University of Alaska Fairbanks Polar Ionospheric Model in real-time. This model makes use of networking and computational resources at the Arctic Region Supercomputing Center. This system was designed to be portable among various operating systems and computational resources. Its components can be installed across different computers, separating Web servers and computational engines. The core of the system is a Real-Time Management module (RMM) written Python, which facilitates interactions of remote input data transfers, the ionospheric model runs, MySQL database filling, and PHP scripts for the Web-page preparations. The RMM downloads current geophysical inputs as soon as they become available at different on-line depositories. This information is processed to

  16. Breaking Computational Barriers: Real-time Analysis and Optimization with Large-scale Nonlinear Models via Model Reduction

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

    Carlberg, Kevin Thomas; Drohmann, Martin; Tuminaro, Raymond S.

    2014-10-01

    Model reduction for dynamical systems is a promising approach for reducing the computational cost of large-scale physics-based simulations to enable high-fidelity models to be used in many- query (e.g., Bayesian inference) and near-real-time (e.g., fast-turnaround simulation) contexts. While model reduction works well for specialized problems such as linear time-invariant systems, it is much more difficult to obtain accurate, stable, and efficient reduced-order models (ROMs) for systems with general nonlinearities. This report describes several advances that enable nonlinear reduced-order models (ROMs) to be deployed in a variety of time-critical settings. First, we present an error bound for the Gauss-Newton with Approximatedmore » Tensors (GNAT) nonlinear model reduction technique. This bound allows the state-space error for the GNAT method to be quantified when applied with the backward Euler time-integration scheme. Second, we present a methodology for preserving classical Lagrangian structure in nonlinear model reduction. This technique guarantees that important properties--such as energy conservation and symplectic time-evolution maps--are preserved when performing model reduction for models described by a Lagrangian formalism (e.g., molecular dynamics, structural dynamics). Third, we present a novel technique for decreasing the temporal complexity --defined as the number of Newton-like iterations performed over the course of the simulation--by exploiting time-domain data. Fourth, we describe a novel method for refining projection-based reduced-order models a posteriori using a goal-oriented framework similar to mesh-adaptive h -refinement in finite elements. The technique allows the ROM to generate arbitrarily accurate solutions, thereby providing the ROM with a 'failsafe' mechanism in the event of insufficient training data. Finally, we present the reduced-order model error surrogate (ROMES) method for statistically quantifying reduced- order-model errors

  17. Resolving dynamics of cell signaling via real-time imaging of the immunological synapse.

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

    Stevens, Mark A.; Pfeiffer, Janet R.; Wilson, Bridget S.

    2009-10-01

    This highly interdisciplinary team has developed dual-color, total internal reflection microscopy (TIRF-M) methods that enable us to optically detect and track in real time protein migration and clustering at membrane interfaces. By coupling TIRF-M with advanced analysis techniques (image correlation spectroscopy, single particle tracking) we have captured subtle changes in membrane organization that characterize immune responses. We have used this approach to elucidate the initial stages of cell activation in the IgE signaling network of mast cells and the Toll-like receptor (TLR-4) response in macrophages stimulated by bacteria. To help interpret these measurements, we have undertaken a computational modeling effortmore » to connect the protein motion and lipid interactions. This work provides a deeper understanding of the initial stages of cellular response to external agents, including dynamics of interaction of key components in the signaling network at the 'immunological synapse,' the contact region of the cell and its adversary.« less

  18. Computer considerations for real time simulation of a generalized rotor model

    NASA Technical Reports Server (NTRS)

    Howe, R. M.; Fogarty, L. E.

    1977-01-01

    Scaled equations were developed to meet requirements for real time computer simulation of the rotor system research aircraft. These equations form the basis for consideration of both digital and hybrid mechanization for real time simulation. For all digital simulation estimates of the required speed in terms of equivalent operations per second are developed based on the complexity of the equations and the required intergration frame rates. For both conventional hybrid simulation and hybrid simulation using time-shared analog elements the amount of required equipment is estimated along with a consideration of the dynamic errors. Conventional hybrid mechanization using analog simulation of those rotor equations which involve rotor-spin frequencies (this consititutes the bulk of the equations) requires too much analog equipment. Hybrid simulation using time-sharing techniques for the analog elements appears possible with a reasonable amount of analog equipment. All-digital simulation with affordable general-purpose computers is not possible because of speed limitations, but specially configured digital computers do have the required speed and consitute the recommended approach.

  19. Processor tradeoffs in distributed real-time systems

    NASA Technical Reports Server (NTRS)

    Krishna, C. M.; Shin, Kang G.; Bhandari, Inderpal S.

    1987-01-01

    The problem of the optimization of the design of real-time distributed systems is examined with reference to a class of computer architectures similar to the continuously reconfigurable multiprocessor flight control system structure, CM2FCS. Particular attention is given to the impact of processor replacement and the burn-in time on the probability of dynamic failure and mean cost. The solution is obtained numerically and interpreted in the context of real-time applications.

  20. GNSS global real-time augmentation positioning: Real-time precise satellite clock estimation, prototype system construction and performance analysis

    NASA Astrophysics Data System (ADS)

    Chen, Liang; Zhao, Qile; Hu, Zhigang; Jiang, Xinyuan; Geng, Changjiang; Ge, Maorong; Shi, Chuang

    2018-01-01

    Lots of ambiguities in un-differenced (UD) model lead to lower calculation efficiency, which isn't appropriate for the high-frequency real-time GNSS clock estimation, like 1 Hz. Mixed differenced model fusing UD pseudo-range and epoch-differenced (ED) phase observations has been introduced into real-time clock estimation. In this contribution, we extend the mixed differenced model for realizing multi-GNSS real-time clock high-frequency updating and a rigorous comparison and analysis on same conditions are performed to achieve the best real-time clock estimation performance taking the efficiency, accuracy, consistency and reliability into consideration. Based on the multi-GNSS real-time data streams provided by multi-GNSS Experiment (MGEX) and Wuhan University, GPS + BeiDou + Galileo global real-time augmentation positioning prototype system is designed and constructed, including real-time precise orbit determination, real-time precise clock estimation, real-time Precise Point Positioning (RT-PPP) and real-time Standard Point Positioning (RT-SPP). The statistical analysis of the 6 h-predicted real-time orbits shows that the root mean square (RMS) in radial direction is about 1-5 cm for GPS, Beidou MEO and Galileo satellites and about 10 cm for Beidou GEO and IGSO satellites. Using the mixed differenced estimation model, the prototype system can realize high-efficient real-time satellite absolute clock estimation with no constant clock-bias and can be used for high-frequency augmentation message updating (such as 1 Hz). The real-time augmentation message signal-in-space ranging error (SISRE), a comprehensive accuracy of orbit and clock and effecting the users' actual positioning performance, is introduced to evaluate and analyze the performance of GPS + BeiDou + Galileo global real-time augmentation positioning system. The statistical analysis of real-time augmentation message SISRE is about 4-7 cm for GPS, whlile 10 cm for Beidou IGSO/MEO, Galileo and about 30 cm

  1. Online gaming for learning optimal team strategies in real time

    NASA Astrophysics Data System (ADS)

    Hudas, Gregory; Lewis, F. L.; Vamvoudakis, K. G.

    2010-04-01

    This paper first presents an overall view for dynamical decision-making in teams, both cooperative and competitive. Strategies for team decision problems, including optimal control, zero-sum 2-player games (H-infinity control) and so on are normally solved for off-line by solving associated matrix equations such as the Riccati equation. However, using that approach, players cannot change their objectives online in real time without calling for a completely new off-line solution for the new strategies. Therefore, in this paper we give a method for learning optimal team strategies online in real time as team dynamical play unfolds. In the linear quadratic regulator case, for instance, the method learns the Riccati equation solution online without ever solving the Riccati equation. This allows for truly dynamical team decisions where objective functions can change in real time and the system dynamics can be time-varying.

  2. A real-time prediction model for post-irradiation malignant cervical lymph nodes.

    PubMed

    Lo, W-C; Cheng, P-W; Shueng, P-W; Hsieh, C-H; Chang, Y-L; Liao, L-J

    2018-04-01

    To establish a real-time predictive scoring model based on sonographic characteristics for identifying malignant cervical lymph nodes (LNs) in cancer patients after neck irradiation. One-hundred forty-four irradiation-treated patients underwent ultrasonography and ultrasound-guided fine-needle aspirations (USgFNAs), and the resultant data were used to construct a real-time and computerised predictive scoring model. This scoring system was further compared with our previously proposed prediction model. A predictive scoring model, 1.35 × (L axis) + 2.03 × (S axis) + 2.27 × (margin) + 1.48 × (echogenic hilum) + 3.7, was generated by stepwise multivariate logistic regression analysis. Neck LNs were considered to be malignant when the score was ≥ 7, corresponding to a sensitivity of 85.5%, specificity of 79.4%, positive predictive value (PPV) of 82.3%, negative predictive value (NPV) of 83.1%, and overall accuracy of 82.6%. When this new model and the original model were compared, the areas under the receiver operating characteristic curve (c-statistic) were 0.89 and 0.81, respectively (P < .05). A real-time sonographic predictive scoring model was constructed to provide prompt and reliable guidance for USgFNA biopsies to manage cervical LNs after neck irradiation. © 2017 John Wiley & Sons Ltd.

  3. Real time acousto-ultrasonic NDE technique for monitoring damage in ceramic composites under dynamic loads

    NASA Technical Reports Server (NTRS)

    Tiwari, Anil

    1995-01-01

    Research effort was directed towards developing a near real-time, acousto-ultrasonic (AU), nondestructive evaluation (NDE) tool to study the failure mechanisms of ceramic composites. Progression of damage is monitored in real-time by observing the changes in the received AU signal during the actual test. During the real-time AU test, the AU signals are generated and received by the AU transducers attached to the specimen while it is being subjected to increasing quasi-static loads or cyclic loads (10 Hz, R = 1.0). The received AU signals for 64 successive pulses were gated in the time domain (T = 40.96 micro sec) and then averaged every second over ten load cycles and stored in a computer file during fatigue tests. These averaged gated signals are representative of the damage state of the specimen at that point of its fatigue life. This is also the first major attempt in the development and application of real-time AU for continuously monitoring damage accumulation during fatigue without interrupting the test. The present work has verified the capability of the AU technique to assess the damage state in silicon carbide/calcium aluminosilicate (SiC/CAS) and silicon carbide/ magnesium aluminosilicate (SiC/MAS) ceramic composites. Continuous monitoring of damage initiation and progression under quasi-static ramp loading in tension to failure of unidirectional and cross-ply SiC/CAS and quasi-isotropic SiC/MAS ceramic composite specimens at room temperature was accomplished using near real-time AU parameters. The AU technique was shown to be able to detect the stress levels for the onset and saturation of matrix cracks, respectively. The critical cracking stress level is used as a design stress for brittle matrix composites operating at elevated temperatures. The AU technique has found that the critical cracking stress level is 10-15% below the level presently obtained for design purposes from analytical models. An acousto-ultrasonic stress-strain response (AUSSR) model

  4. A coupled duration-focused architecture for real-time music-to-score alignment.

    PubMed

    Cont, Arshia

    2010-06-01

    The capacity for real-time synchronization and coordination is a common ability among trained musicians performing a music score that presents an interesting challenge for machine intelligence. Compared to speech recognition, which has influenced many music information retrieval systems, music's temporal dynamics and complexity pose challenging problems to common approximations regarding time modeling of data streams. In this paper, we propose a design for a real-time music-to-score alignment system. Given a live recording of a musician playing a music score, the system is capable of following the musician in real time within the score and decoding the tempo (or pace) of its performance. The proposed design features two coupled audio and tempo agents within a unique probabilistic inference framework that adaptively updates its parameters based on the real-time context. Online decoding is achieved through the collaboration of the coupled agents in a Hidden Hybrid Markov/semi-Markov framework, where prediction feedback of one agent affects the behavior of the other. We perform evaluations for both real-time alignment and the proposed temporal model. An implementation of the presented system has been widely used in real concert situations worldwide and the readers are encouraged to access the actual system and experiment the results.

  5. Acting to gain information: Real-time reasoning meets real-time perception

    NASA Technical Reports Server (NTRS)

    Rosenschein, Stan

    1994-01-01

    Recent advances in intelligent reactive systems suggest new approaches to the problem of deriving task-relevant information from perceptual systems in real time. The author will describe work in progress aimed at coupling intelligent control mechanisms to real-time perception systems, with special emphasis on frame rate visual measurement systems. A model for integrated reasoning and perception will be discussed, and recent progress in applying these ideas to problems of sensor utilization for efficient recognition and tracking will be described.

  6. Real-time contaminant sensing and control in civil infrastructure systems

    NASA Astrophysics Data System (ADS)

    Rimer, Sara; Katopodes, Nikolaos

    2014-11-01

    A laboratory-scale prototype has been designed and implemented to test the feasibility of real-time contaminant sensing and control in civil infrastructure systems. A blower wind tunnel is the basis of the prototype design, with propylene glycol smoke as the ``contaminant.'' A camera sensor and compressed-air vacuum nozzle system is set up at the test section portion of the prototype to visually sense and then control the contaminant; a real-time controller is programmed to read in data from the camera sensor and administer pressure to regulators controlling the compressed air operating the vacuum nozzles. A computational fluid dynamics model is being integrated in with this prototype to inform the correct pressure to supply to the regulators in order to optimally control the contaminant's removal from the prototype. The performance of the prototype has been evaluated against the computational fluid dynamics model and is discussed in this presentation. Furthermore, the initial performance of the sensor-control system implemented in the test section of the prototype is discussed. NSF-CMMI 0856438.

  7. Validation of Real-time Modeling of Coronal Mass Ejections Using the WSA-ENLIL+Cone Heliospheric Model

    NASA Astrophysics Data System (ADS)

    Romano, M.; Mays, M. L.; Taktakishvili, A.; MacNeice, P. J.; Zheng, Y.; Pulkkinen, A. A.; Kuznetsova, M. M.; Odstrcil, D.

    2013-12-01

    Modeling coronal mass ejections (CMEs) is of great interest to the space weather research and forecasting communities. We present recent validation work of real-time CME arrival time predictions at different satellites using the WSA-ENLIL+Cone three-dimensional MHD heliospheric model available at the Community Coordinated Modeling Center (CCMC) and performed by the Space Weather Research Center (SWRC). SWRC is an in-house research-based operations team at the CCMC which provides interplanetary space weather forecasting for NASA's robotic missions and performs real-time model validation. The quality of model operation is evaluated by comparing its output to a measurable parameter of interest such as the CME arrival time and geomagnetic storm strength. The Kp index is calculated from the relation given in Newell et al. (2007), using solar wind parameters predicted by the WSA-ENLIL+Cone model at Earth. The CME arrival time error is defined as the difference between the predicted arrival time and the observed in-situ CME shock arrival time at the ACE, STEREO A, or STEREO B spacecraft. This study includes all real-time WSA-ENLIL+Cone model simulations performed between June 2011-2013 (over 400 runs) at the CCMC/SWRC. We report hit, miss, false alarm, and correct rejection statistics for all three spacecraft. For hits we show the average absolute CME arrival time error, and the dependence of this error on CME input parameters such as speed, width, and direction. We also present the predicted geomagnetic storm strength (using the Kp index) error for Earth-directed CMEs.

  8. Modeling Real-Time Coordination of Distributed Expertise and Event Response in NASA Mission Control Center Operations

    NASA Astrophysics Data System (ADS)

    Onken, Jeffrey

    This dissertation introduces a multidisciplinary framework for the enabling of future research and analysis of alternatives for control centers for real-time operations of safety-critical systems. The multidisciplinary framework integrates functional and computational models that describe the dynamics in fundamental concepts of previously disparate engineering and psychology research disciplines, such as group performance and processes, supervisory control, situation awareness, events and delays, and expertise. The application in this dissertation is the real-time operations within the NASA Mission Control Center in Houston, TX. This dissertation operationalizes the framework into a model and simulation, which simulates the functional and computational models in the framework according to user-configured scenarios for a NASA human-spaceflight mission. The model and simulation generates data according to the effectiveness of the mission-control team in supporting the completion of mission objectives and detecting, isolating, and recovering from anomalies. Accompanying the multidisciplinary framework is a proof of concept, which demonstrates the feasibility of such a framework. The proof of concept demonstrates that variability occurs where expected based on the models. The proof of concept also demonstrates that the data generated from the model and simulation is useful for analyzing and comparing MCC configuration alternatives because an investigator can give a diverse set of scenarios to the simulation and the output compared in detail to inform decisions about the effect of MCC configurations on mission operations performance.

  9. A Model for Real-Time Data Reputation Via Cyber Telemetry

    DTIC Science & Technology

    2016-06-01

    TIME DATA REPUTATION VIA CYBER TELEMETRY by Beau M. Houser June 2016 Thesis Advisor: Dorothy E. Denning Co-Advisor: Phyllis Schneck...information is estimated to average 1 hour per response, including the time for reviewing instruction, searching existing data sources, gathering and...Master’s Thesis 4. TITLE AND SUBTITLE A MODEL FOR REAL- TIME DATA REPUTATION VIA CYBER TELEMETRY 5. FUNDING NUMBERS 6. AUTHOR(S) Beau M

  10. CD-SEM real time bias correction using reference metrology based modeling

    NASA Astrophysics Data System (ADS)

    Ukraintsev, V.; Banke, W.; Zagorodnev, G.; Archie, C.; Rana, N.; Pavlovsky, V.; Smirnov, V.; Briginas, I.; Katnani, A.; Vaid, A.

    2018-03-01

    Accuracy of patterning impacts yield, IC performance and technology time to market. Accuracy of patterning relies on optical proximity correction (OPC) models built using CD-SEM inputs and intra die critical dimension (CD) control based on CD-SEM. Sub-nanometer measurement uncertainty (MU) of CD-SEM is required for current technologies. Reported design and process related bias variation of CD-SEM is in the range of several nanometers. Reference metrology and numerical modeling are used to correct SEM. Both methods are slow to be used for real time bias correction. We report on real time CD-SEM bias correction using empirical models based on reference metrology (RM) data. Significant amount of currently untapped information (sidewall angle, corner rounding, etc.) is obtainable from SEM waveforms. Using additional RM information provided for specific technology (design rules, materials, processes) CD extraction algorithms can be pre-built and then used in real time for accurate CD extraction from regular CD-SEM images. The art and challenge of SEM modeling is in finding robust correlation between SEM waveform features and bias of CD-SEM as well as in minimizing RM inputs needed to create accurate (within the design and process space) model. The new approach was applied to improve CD-SEM accuracy of 45 nm GATE and 32 nm MET1 OPC 1D models. In both cases MU of the state of the art CD-SEM has been improved by 3x and reduced to a nanometer level. Similar approach can be applied to 2D (end of line, contours, etc.) and 3D (sidewall angle, corner rounding, etc.) cases.

  11. An access control model with high security for distributed workflow and real-time application

    NASA Astrophysics Data System (ADS)

    Han, Ruo-Fei; Wang, Hou-Xiang

    2007-11-01

    The traditional mandatory access control policy (MAC) is regarded as a policy with strict regulation and poor flexibility. The security policy of MAC is so compelling that few information systems would adopt it at the cost of facility, except some particular cases with high security requirement as military or government application. However, with the increasing requirement for flexibility, even some access control systems in military application have switched to role-based access control (RBAC) which is well known as flexible. Though RBAC can meet the demands for flexibility but it is weak in dynamic authorization and consequently can not fit well in the workflow management systems. The task-role-based access control (T-RBAC) is then introduced to solve the problem. It combines both the advantages of RBAC and task-based access control (TBAC) which uses task to manage permissions dynamically. To satisfy the requirement of system which is distributed, well defined with workflow process and critically for time accuracy, this paper will analyze the spirit of MAC, introduce it into the improved T&RBAC model which is based on T-RBAC. At last, a conceptual task-role-based access control model with high security for distributed workflow and real-time application (A_T&RBAC) is built, and its performance is simply analyzed.

  12. Real-Time Hardware-in-the-Loop Simulation of Ares I Launch Vehicle

    NASA Technical Reports Server (NTRS)

    Tobbe, Patrick; Matras, Alex; Walker, David; Wilson, Heath; Fulton, Chris; Alday, Nathan; Betts, Kevin; Hughes, Ryan; Turbe, Michael

    2009-01-01

    The Ares Real-Time Environment for Modeling, Integration, and Simulation (ARTEMIS) has been developed for use by the Ares I launch vehicle System Integration Laboratory at the Marshall Space Flight Center. The primary purpose of the Ares System Integration Laboratory is to test the vehicle avionics hardware and software in a hardware - in-the-loop environment to certify that the integrated system is prepared for flight. ARTEMIS has been designed to be the real-time simulation backbone to stimulate all required Ares components for verification testing. ARTE_VIIS provides high -fidelity dynamics, actuator, and sensor models to simulate an accurate flight trajectory in order to ensure realistic test conditions. ARTEMIS has been designed to take advantage of the advances in underlying computational power now available to support hardware-in-the-loop testing to achieve real-time simulation with unprecedented model fidelity. A modular realtime design relying on a fully distributed computing architecture has been implemented.

  13. Real-time PCR machine system modeling and a systematic approach for the robust design of a real-time PCR-on-a-chip system.

    PubMed

    Lee, Da-Sheng

    2010-01-01

    Chip-based DNA quantification systems are widespread, and used in many point-of-care applications. However, instruments for such applications may not be maintained or calibrated regularly. Since machine reliability is a key issue for normal operation, this study presents a system model of the real-time Polymerase Chain Reaction (PCR) machine to analyze the instrument design through numerical experiments. Based on model analysis, a systematic approach was developed to lower the variation of DNA quantification and achieve a robust design for a real-time PCR-on-a-chip system. Accelerated lift testing was adopted to evaluate the reliability of the chip prototype. According to the life test plan, this proposed real-time PCR-on-a-chip system was simulated to work continuously for over three years with similar reproducibility in DNA quantification. This not only shows the robustness of the lab-on-a-chip system, but also verifies the effectiveness of our systematic method for achieving a robust design.

  14. Real-time PCR Machine System Modeling and a Systematic Approach for the Robust Design of a Real-time PCR-on-a-Chip System

    PubMed Central

    Lee, Da-Sheng

    2010-01-01

    Chip-based DNA quantification systems are widespread, and used in many point-of-care applications. However, instruments for such applications may not be maintained or calibrated regularly. Since machine reliability is a key issue for normal operation, this study presents a system model of the real-time Polymerase Chain Reaction (PCR) machine to analyze the instrument design through numerical experiments. Based on model analysis, a systematic approach was developed to lower the variation of DNA quantification and achieve a robust design for a real-time PCR-on-a-chip system. Accelerated lift testing was adopted to evaluate the reliability of the chip prototype. According to the life test plan, this proposed real-time PCR-on-a-chip system was simulated to work continuously for over three years with similar reproducibility in DNA quantification. This not only shows the robustness of the lab-on-a-chip system, but also verifies the effectiveness of our systematic method for achieving a robust design. PMID:22315563

  15. Interdyad Differences in Early Mother-Infant Face-to-Face Communication: Real-Time Dynamics and Developmental Pathways

    ERIC Educational Resources Information Center

    Lavelli, Manuela; Fogel, Alan

    2013-01-01

    A microgenetic research design with a multiple case study method and a combination of quantitative and qualitative analyses was used to investigate interdyad differences in real-time dynamics and developmental change processes in mother-infant face-to-face communication over the first 3 months of life. Weekly observations of 24 mother-infant dyads…

  16. Near Real{time Data Assimilation for the HYSPLIT Aerosol Dispersion Model

    NASA Astrophysics Data System (ADS)

    Kalpakis, K.; Yang, S.; Yesha, Y.

    2010-12-01

    Konstantinos Kalpakis, Shiming Yang, and Yaacov Yesha Department of Computer Science and Electrical Engineering University of Maryland Baltimore County 1000 Hilltop Circle, Baltimore, MD, U.S.A. {kalpakis, shiming1, yayeshag}@csee.umbc.edu ABSTRACT We are working on an IBM-funded project seeking to develop a prototype system for real-time plume dispersion and fire and smoke detection and monitoring. Our prototype system utilizes HYSPLIT and observation data from various sources. HYSPLIT is a model developed by NOAA's Air Resources Laboratory for forecasting aerosol trajectories, dispersion, and concentration from emission sources. It is used extensively by NOAA to routinely provide a number of data products. We develop a data assimilation system for assimilating observational data into the forecasting model in order to improve its forecasting accuracy. Our system is based on the Local Ensemble Transform Kalman Filter (LETKF) algorithm and it is computationally efficient. We evaluate our data assimilation system with real in-situ observational data, and find that our system improves upon HYSPLIT's forecast by reducing the normalized mean squared error and the bias. We are also experimenting with assimilating MODIS data with HYSPLIT model forecasts. To this end, we extrapolate ground concentrations from MODIS Aerosol Optical Depth (AOD) data. Our extrapolation approach relies on spatially localized linear regressions of aerosol concentrations from ground stations in the Air Quality System (AQS) network and MODIS AOD data. We expect that assimilating the extrapolated concentrations leads into further improvements of HYSPLIT forecasts. Furthermore, we are investigating using additional sources of in-situ and remotely sensed observations, such as GOES AOD 30-minute data, and UAV data from the Ikhana AMS fire missions. These sources provide higher spatial resolution and more frequent temporal coverage. Moreover, GOES and UAVs provide near-real time data which should be

  17. Real-Time Description of the Electronic Dynamics for a Molecule Close to a Plasmonic Nanoparticle

    PubMed Central

    2016-01-01

    The optical properties of molecules close to plasmonic nanostructures greatly differ from their isolated molecule counterparts. To theoretically investigate such systems from a quantum-chemistry perspective, one has to take into account that the plasmonic nanostructure (e.g., a metal nanoparticle–NP) is often too large to be treated atomistically. Therefore, a multiscale description, where the molecule is treated by an ab initio approach and the metal NP by a lower level description, is needed. Here we present an extension of one such multiscale model [Corni, S.; Tomasi, J. J. Chem. Phys.2001, 114, 3739], originally inspired by the polarizable continuum model, to a real-time description of the electronic dynamics of the molecule and of the NP. In particular, we adopt a time-dependent configuration interaction (TD CI) approach for the molecule, the metal NP is described as a continuous dielectric of complex shape characterized by a Drude–Lorentz dielectric function, and the molecule–NP electromagnetic coupling is treated by an equation-of-motion (EOM) extension of the quasi-static boundary element method (BEM). The model includes the effects of both the mutual molecule–NP time-dependent polarization and the modification of the probing electromagnetic field due to the plasmonic resonances of the NP. Finally, such an approach is applied to the investigation of the light absorption of a model chromophore, LiCN, in the presence of a metal–NP of complex shape. PMID:28035246

  18. Dynamic thermal signature prediction for real-time scene generation

    NASA Astrophysics Data System (ADS)

    Christie, Chad L.; Gouthas, Efthimios (Themie); Williams, Owen M.; Swierkowski, Leszek

    2013-05-01

    At DSTO, a real-time scene generation framework, VIRSuite, has been developed in recent years, within which trials data are predominantly used for modelling the radiometric properties of the simulated objects. Since in many cases the data are insufficient, a physics-based simulator capable of predicting the infrared signatures of objects and their backgrounds has been developed as a new VIRSuite module. It includes transient heat conduction within the materials, and boundary conditions that take into account the heat fluxes due to solar radiation, wind convection and radiative transfer. In this paper, an overview is presented, covering both the steady-state and transient performance.

  19. Internal models of target motion: expected dynamics overrides measured kinematics in timing manual interceptions.

    PubMed

    Zago, Myrka; Bosco, Gianfranco; Maffei, Vincenzo; Iosa, Marco; Ivanenko, Yuri P; Lacquaniti, Francesco

    2004-04-01

    Prevailing views on how we time the interception of a moving object assume that the visual inputs are informationally sufficient to estimate the time-to-contact from the object's kinematics. Here we present evidence in favor of a different view: the brain makes the best estimate about target motion based on measured kinematics and an a priori guess about the causes of motion. According to this theory, a predictive model is used to extrapolate time-to-contact from expected dynamics (kinetics). We projected a virtual target moving vertically downward on a wide screen with different randomized laws of motion. In the first series of experiments, subjects were asked to intercept this target by punching a real ball that fell hidden behind the screen and arrived in synchrony with the visual target. Subjects systematically timed their motor responses consistent with the assumption of gravity effects on an object's mass, even when the visual target did not accelerate. With training, the gravity model was not switched off but adapted to nonaccelerating targets by shifting the time of motor activation. In the second series of experiments, there was no real ball falling behind the screen. Instead the subjects were required to intercept the visual target by clicking a mousebutton. In this case, subjects timed their responses consistent with the assumption of uniform motion in the absence of forces, even when the target actually accelerated. Overall, the results are in accord with the theory that motor responses evoked by visual kinematics are modulated by a prior of the target dynamics. The prior appears surprisingly resistant to modifications based on performance errors.

  20. Real-time simulation of large-scale floods

    NASA Astrophysics Data System (ADS)

    Liu, Q.; Qin, Y.; Li, G. D.; Liu, Z.; Cheng, D. J.; Zhao, Y. H.

    2016-08-01

    According to the complex real-time water situation, the real-time simulation of large-scale floods is very important for flood prevention practice. Model robustness and running efficiency are two critical factors in successful real-time flood simulation. This paper proposed a robust, two-dimensional, shallow water model based on the unstructured Godunov- type finite volume method. A robust wet/dry front method is used to enhance the numerical stability. An adaptive method is proposed to improve the running efficiency. The proposed model is used for large-scale flood simulation on real topography. Results compared to those of MIKE21 show the strong performance of the proposed model.

  1. Real-time predictive seasonal influenza model in Catalonia, Spain

    PubMed Central

    Basile, Luca; Oviedo de la Fuente, Manuel; Torner, Nuria; Martínez, Ana; Jané, Mireia

    2018-01-01

    Influenza surveillance is critical to monitoring the situation during epidemic seasons and predictive mathematic models may aid the early detection of epidemic patterns. The objective of this study was to design a real-time spatial predictive model of ILI (Influenza Like Illness) incidence rate in Catalonia using one- and two-week forecasts. The available data sources used to select explanatory variables to include in the model were the statutory reporting disease system and the sentinel surveillance system in Catalonia for influenza incidence rates, the official climate service in Catalonia for meteorological data, laboratory data and Google Flu Trend. Time series for every explanatory variable with data from the last 4 seasons (from 2010–2011 to 2013–2014) was created. A pilot test was conducted during the 2014–2015 season to select the explanatory variables to be included in the model and the type of model to be applied. During the 2015–2016 season a real-time model was applied weekly, obtaining the intensity level and predicted incidence rates with 95% confidence levels one and two weeks away for each health region. At the end of the season, the confidence interval success rate (CISR) and intensity level success rate (ILSR) were analysed. For the 2015–2016 season a CISR of 85.3% at one week and 87.1% at two weeks and an ILSR of 82.9% and 82% were observed, respectively. The model described is a useful tool although it is hard to evaluate due to uncertainty. The accuracy of prediction at one and two weeks was above 80% globally, but was lower during the peak epidemic period. In order to improve the predictive power, new explanatory variables should be included. PMID:29513710

  2. Real-Time Systems

    DTIC Science & Technology

    1992-02-01

    Postgraduate School Autonomous Under Vehicle (AUV) are then examined. Autonomous underwater vehicle (AUV), hard real-time system, real - time operating system , real-time programming language, real-time system, soft real-time system.

  3. Optimal dynamic voltage scaling for wireless sensor nodes with real-time constraints

    NASA Astrophysics Data System (ADS)

    Cassandras, Christos G.; Zhuang, Shixin

    2005-11-01

    Sensors are increasingly embedded in manufacturing systems and wirelessly networked to monitor and manage operations ranging from process and inventory control to tracking equipment and even post-manufacturing product monitoring. In building such sensor networks, a critical issue is the limited and hard to replenish energy in the devices involved. Dynamic voltage scaling is a technique that controls the operating voltage of a processor to provide desired performance while conserving energy and prolonging the overall network's lifetime. We consider such power-limited devices processing time-critical tasks which are non-preemptive, aperiodic and have uncertain arrival times. We treat voltage scaling as a dynamic optimization problem whose objective is to minimize energy consumption subject to hard or soft real-time execution constraints. In the case of hard constraints, we build on prior work (which engages a voltage scaling controller at task completion times) by developing an intra-task controller that acts at all arrival times of incoming tasks. We show that this optimization problem can be decomposed into two simpler ones whose solution leads to an algorithm that does not actually require solving any nonlinear programming problems. In the case of soft constraints, this decomposition must be partly relaxed, but it still leads to a scalable (linear in the number of tasks) algorithm. Simulation results are provided to illustrate performance improvements in systems with intra-task controllers compared to uncontrolled systems or those using inter-task control.

  4. Spatiotemporal Segmentation and Modeling of the Mitral Valve in Real-Time 3D Echocardiographic Images.

    PubMed

    Pouch, Alison M; Aly, Ahmed H; Lai, Eric K; Yushkevich, Natalie; Stoffers, Rutger H; Gorman, Joseph H; Cheung, Albert T; Gorman, Joseph H; Gorman, Robert C; Yushkevich, Paul A

    2017-09-01

    Transesophageal echocardiography is the primary imaging modality for preoperative assessment of mitral valves with ischemic mitral regurgitation (IMR). While there are well known echocardiographic insights into the 3D morphology of mitral valves with IMR, such as annular dilation and leaflet tethering, less is understood about how quantification of valve dynamics can inform surgical treatment of IMR or predict short-term recurrence of the disease. As a step towards filling this knowledge gap, we present a novel framework for 4D segmentation and geometric modeling of the mitral valve in real-time 3D echocardiography (rt-3DE). The framework integrates multi-atlas label fusion and template-based medial modeling to generate quantitatively descriptive models of valve dynamics. The novelty of this work is that temporal consistency in the rt-3DE segmentations is enforced during both the segmentation and modeling stages with the use of groupwise label fusion and Kalman filtering. The algorithm is evaluated on rt-3DE data series from 10 patients: five with normal mitral valve morphology and five with severe IMR. In these 10 data series that total 207 individual 3DE images, each 3DE segmentation is validated against manual tracing and temporal consistency between segmentations is demonstrated. The ultimate goal is to generate accurate and consistent representations of valve dynamics that can both visually and quantitatively provide insight into normal and pathological valve function.

  5. Random graph models for dynamic networks

    NASA Astrophysics Data System (ADS)

    Zhang, Xiao; Moore, Cristopher; Newman, Mark E. J.

    2017-10-01

    Recent theoretical work on the modeling of network structure has focused primarily on networks that are static and unchanging, but many real-world networks change their structure over time. There exist natural generalizations to the dynamic case of many static network models, including the classic random graph, the configuration model, and the stochastic block model, where one assumes that the appearance and disappearance of edges are governed by continuous-time Markov processes with rate parameters that can depend on properties of the nodes. Here we give an introduction to this class of models, showing for instance how one can compute their equilibrium properties. We also demonstrate their use in data analysis and statistical inference, giving efficient algorithms for fitting them to observed network data using the method of maximum likelihood. This allows us, for example, to estimate the time constants of network evolution or infer community structure from temporal network data using cues embedded both in the probabilities over time that node pairs are connected by edges and in the characteristic dynamics of edge appearance and disappearance. We illustrate these methods with a selection of applications, both to computer-generated test networks and real-world examples.

  6. Absorption dynamics and delay time in complex potentials

    NASA Astrophysics Data System (ADS)

    Villavicencio, Jorge; Romo, Roberto; Hernández-Maldonado, Alberto

    2018-05-01

    The dynamics of absorption is analyzed by using an exactly solvable model that deals with an analytical solution to Schrödinger’s equation for cutoff initial plane waves incident on a complex absorbing potential. A dynamical absorption coefficient which allows us to explore the dynamical loss of particles from the transient to the stationary regime is derived. We find that the absorption process is characterized by the emission of a series of damped periodic pulses in time domain, associated with damped Rabi-type oscillations with a characteristic frequency, ω = (E + ε)/ℏ, where E is the energy of the incident waves and ‑ε is energy of the quasidiscrete state of the system induced by the absorptive part of the Hamiltonian; the width γ of this resonance governs the amplitude of the pulses. The resemblance of the time-dependent absorption coefficient with a real decay process is discussed, in particular the transition from exponential to nonexponential regimes, a well-known feature of quantum decay. We have also analyzed the effect of the absorptive part of the potential on the dynamical delay time, which behaves differently from the one observed in attractive real delta potentials, exhibiting two regimes: time advance and time delay.

  7. Real-time validation of the Dst Predictor model

    USGS Publications Warehouse

    McCollough, James P.; Young, Shawn L.; Rigler, E. Joshua; Simpson, Hal A.

    2015-01-01

    The Dst Predictor model, which has been running real-time in the Space Weather Analysis and Forecast System (SWAFS), provides 1-hour and 4-hour forecasts of the Dst index. This is useful for awareness of impending geomagnetic activity, as well as driving other real-time models that use Dst as an input. In this report, we examine the performance of this forecast model in detail. When validating indices it should be noted that performance is only with respect to a reference index as they are derived quantities assumed to reflect a state of the magnetosphere that cannot be directly measured. In this case U.S. Geological Survey (USGS) Definitive Dst is the reference index (Section 3). Whether or not the model better reflects the actual activity level is nearly impossible to discern and is outside the scope of this report. We evaluate the performance of the model by computing continuous predictant skill scores against USGS Definitive Dst values as “observations” (Section 4.2). The two sets of data are not well-correlated for both 1-hour and 4-hour forecasts. The Dst Predictor Prediction Efficiency for both the 1- and 4-hour forecasts suggests poor performance versus the climatological mean. However, the skill score against a nowcast persistence model is positive, suggesting value added by the Dst Predictor model. We further examine statistics for storm times (Section 4.3) with similar results: nowcast persistence performs worse than Dst Predictor.  Dst Predictor is superior to the nowcast persistence model for the metric used in this study. We recommend continued use of the DstPredictor model for 1-and4-hour Dst predictions along with active study of other Dst forecast models that do not rely on nowcast inputs (Section 6). The lack of certified requirements makes further recommendations difficult. A study of how the error in Dst translates to error in models and a better understanding of operational needs for magnetic storm warning are needed to determine

  8. V/STOL tilt rotor study. Volume 5: A mathematical model for real time flight simulation of the Bell model 301 tilt rotor research aircraft

    NASA Technical Reports Server (NTRS)

    Harendra, P. B.; Joglekar, M. J.; Gaffey, T. M.; Marr, R. L.

    1973-01-01

    A mathematical model for real-time flight simulation of a tilt rotor research aircraft was developed. The mathematical model was used to support the aircraft design, pilot training, and proof-of-concept aspects of the development program. The structure of the mathematical model is indicated by a block diagram. The mathematical model differs from that for a conventional fixed wing aircraft principally in the added requirement to represent the dynamics and aerodynamics of the rotors, the interaction of the rotor wake with the airframe, and the rotor control and drive systems. The constraints imposed on the mathematical model are defined.

  9. Real-time monitoring of capacity loss for vanadium redox flow battery

    NASA Astrophysics Data System (ADS)

    Wei, Zhongbao; Bhattarai, Arjun; Zou, Changfu; Meng, Shujuan; Lim, Tuti Mariana; Skyllas-Kazacos, Maria

    2018-06-01

    The long-term operation of the vanadium redox flow battery is accompanied by ion diffusion across the separator and side reactions, which can lead to electrolyte imbalance and capacity loss. The accurate online monitoring of capacity loss is therefore valuable for the reliable and efficient operation of vanadium redox flow battery system. In this paper, a model-based online monitoring method is proposed to detect capacity loss in the vanadium redox flow battery in real time. A first-order equivalent circuit model is built to capture the dynamics of the vanadium redox flow battery. The model parameters are online identified from the onboard measureable signals with the recursive least squares, in seeking to keep a high modeling accuracy and robustness under a wide range of working scenarios. Based on the online adapted model, an observer is designed with the extended Kalman Filter to keep tracking both the capacity and state of charge of the battery in real time. Experiments are conducted on a lab-scale battery system. Results suggest that the online adapted model is able to simulate the battery behavior with high accuracy. The capacity loss as well as the state of charge can be estimated accurately in a real-time manner.

  10. Crash Frequency Modeling Using Real-Time Environmental and Traffic Data and Unbalanced Panel Data Models

    PubMed Central

    Chen, Feng; Chen, Suren; Ma, Xiaoxiang

    2016-01-01

    Traffic and environmental conditions (e.g., weather conditions), which frequently change with time, have a significant impact on crash occurrence. Traditional crash frequency models with large temporal scales and aggregated variables are not sufficient to capture the time-varying nature of driving environmental factors, causing significant loss of critical information on crash frequency modeling. This paper aims at developing crash frequency models with refined temporal scales for complex driving environments, with such an effort providing more detailed and accurate crash risk information which can allow for more effective and proactive traffic management and law enforcement intervention. Zero-inflated, negative binomial (ZINB) models with site-specific random effects are developed with unbalanced panel data to analyze hourly crash frequency on highway segments. The real-time driving environment information, including traffic, weather and road surface condition data, sourced primarily from the Road Weather Information System, is incorporated into the models along with site-specific road characteristics. The estimation results of unbalanced panel data ZINB models suggest there are a number of factors influencing crash frequency, including time-varying factors (e.g., visibility and hourly traffic volume) and site-varying factors (e.g., speed limit). The study confirms the unique significance of the real-time weather, road surface condition and traffic data to crash frequency modeling. PMID:27322306

  11. System for real-time generation of georeferenced terrain models

    NASA Astrophysics Data System (ADS)

    Schultz, Howard J.; Hanson, Allen R.; Riseman, Edward M.; Stolle, Frank; Zhu, Zhigang; Hayward, Christopher D.; Slaymaker, Dana

    2001-02-01

    A growing number of law enforcement applications, especially in the areas of border security, drug enforcement and anti- terrorism require high-resolution wide area surveillance from unmanned air vehicles. At the University of Massachusetts we are developing an aerial reconnaissance system capable of generating high resolution, geographically registered terrain models (in the form of a seamless mosaic) in real-time from a single down-looking digital video camera. The efficiency of the processing algorithms, as well as the simplicity of the hardware, will provide the user with the ability to produce and roam through stereoscopic geo-referenced mosaic images in real-time, and to automatically generate highly accurate 3D terrain models offline in a fraction of the time currently required by softcopy conventional photogrammetry systems. The system is organized around a set of integrated sensor and software components. The instrumentation package is comprised of several inexpensive commercial-off-the-shelf components, including a digital video camera, a differential GPS, and a 3-axis heading and reference system. At the heart of the system is a set of software tools for image registration, mosaic generation, geo-location and aircraft state vector recovery. Each process is designed to efficiently handle the data collected by the instrument package. Particular attention is given to minimizing geospatial errors at each stage, as well as modeling propagation of errors through the system. Preliminary results for an urban and forested scene are discussed in detail.

  12. Real-time video quality monitoring

    NASA Astrophysics Data System (ADS)

    Liu, Tao; Narvekar, Niranjan; Wang, Beibei; Ding, Ran; Zou, Dekun; Cash, Glenn; Bhagavathy, Sitaram; Bloom, Jeffrey

    2011-12-01

    The ITU-T Recommendation G.1070 is a standardized opinion model for video telephony applications that uses video bitrate, frame rate, and packet-loss rate to measure the video quality. However, this model was original designed as an offline quality planning tool. It cannot be directly used for quality monitoring since the above three input parameters are not readily available within a network or at the decoder. And there is a great room for the performance improvement of this quality metric. In this article, we present a real-time video quality monitoring solution based on this Recommendation. We first propose a scheme to efficiently estimate the three parameters from video bitstreams, so that it can be used as a real-time video quality monitoring tool. Furthermore, an enhanced algorithm based on the G.1070 model that provides more accurate quality prediction is proposed. Finally, to use this metric in real-world applications, we present an example emerging application of real-time quality measurement to the management of transmitted videos, especially those delivered to mobile devices.

  13. Real-time flutter identification

    NASA Technical Reports Server (NTRS)

    Roy, R.; Walker, R.

    1985-01-01

    The techniques and a FORTRAN 77 MOdal Parameter IDentification (MOPID) computer program developed for identification of the frequencies and damping ratios of multiple flutter modes in real time are documented. Physically meaningful model parameterization was combined with state of the art recursive identification techniques and applied to the problem of real time flutter mode monitoring. The performance of the algorithm in terms of convergence speed and parameter estimation error is demonstrated for several simulated data cases, and the results of actual flight data analysis from two different vehicles are presented. It is indicated that the algorithm is capable of real time monitoring of aircraft flutter characteristics with a high degree of reliability.

  14. Real-Time Station Grouping under Dynamic Traffic for IEEE 802.11ah

    PubMed Central

    Tian, Le; Latré, Steven

    2017-01-01

    RAW grouping under dynamic traffic in real time, which is a major leap towards applying RAW mechanism in real-life IoT networks. PMID:28677617

  15. Real-Time Station Grouping under Dynamic Traffic for IEEE 802.11ah.

    PubMed

    Tian, Le; Khorov, Evgeny; Latré, Steven; Famaey, Jeroen

    2017-07-04

    RAW grouping under dynamic traffic in real time, which is a major leap towards applying RAW mechanism in real-life IoT networks.

  16. 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

  17. Dynamical analysis of an n‑H‑T cosmological quintessence real gas model with a general equation of state

    NASA Astrophysics Data System (ADS)

    Ivanov, Rossen I.; Prodanov, Emil M.

    2018-01-01

    The cosmological dynamics of a quintessence model based on real gas with general equation of state is presented within the framework of a three-dimensional dynamical system describing the time evolution of the number density, the Hubble parameter and the temperature. Two global first integrals are found and examples for gas with virial expansion and van der Waals gas are presented. The van der Waals system is completely integrable. In addition to the unbounded trajectories, stemming from the presence of the conserved quantities, stable periodic solutions (closed orbits) also exist under certain conditions and these represent models of a cyclic Universe. The cyclic solutions exhibit regions characterized by inflation and deflation, while the open trajectories are characterized by inflation in a “fly-by” near an unstable critical point.

  18. 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

  19. Electron dynamics in complex environments with real-time time dependent density functional theory in a QM-MM framework.

    PubMed

    Morzan, Uriel N; Ramírez, Francisco F; Oviedo, M Belén; Sánchez, Cristián G; Scherlis, Damián A; Lebrero, Mariano C González

    2014-04-28

    This article presents a time dependent density functional theory (TDDFT) implementation to propagate the Kohn-Sham equations in real time, including the effects of a molecular environment through a Quantum-Mechanics Molecular-Mechanics (QM-MM) hamiltonian. The code delivers an all-electron description employing Gaussian basis functions, and incorporates the Amber force-field in the QM-MM treatment. The most expensive parts of the computation, comprising the commutators between the hamiltonian and the density matrix-required to propagate the electron dynamics-, and the evaluation of the exchange-correlation energy, were migrated to the CUDA platform to run on graphics processing units, which remarkably accelerates the performance of the code. The method was validated by reproducing linear-response TDDFT results for the absorption spectra of several molecular species. Two different schemes were tested to propagate the quantum dynamics: (i) a leap-frog Verlet algorithm, and (ii) the Magnus expansion to first-order. These two approaches were confronted, to find that the Magnus scheme is more efficient by a factor of six in small molecules. Interestingly, the presence of iron was found to seriously limitate the length of the integration time step, due to the high frequencies associated with the core-electrons. This highlights the importance of pseudopotentials to alleviate the cost of the propagation of the inner states when heavy nuclei are present. Finally, the methodology was applied to investigate the shifts induced by the chemical environment on the most intense UV absorption bands of two model systems of general relevance: the formamide molecule in water solution, and the carboxy-heme group in Flavohemoglobin. In both cases, shifts of several nanometers are observed, consistently with the available experimental data.

  20. Real and financial market interactions in a multiplier-accelerator model: Nonlinear dynamics, multistability and stylized facts

    NASA Astrophysics Data System (ADS)

    Cavalli, F.; Naimzada, A.; Pecora, N.

    2017-10-01

    In the present paper, we investigate the dynamics of a model in which the real part of the economy, described within a multiplier-accelerator framework, interacts with a financial market with heterogeneous speculators, in order to study the channels through which the two sectors influence each other. Employing analytical and numerical tools, we investigate stability conditions as well as bifurcations and possible periodic, quasi-periodic, and chaotic dynamics, enlightening how the degree of market interaction, together with the accelerator parameter and the intervention of the fiscal authority, may affect the business cycle and the course of the financial market. In particular, we show that even if the steady state is locally stable, multistability phenomena can occur, with several and complex dynamic structures coexisting with the steady state. Finally, simulations reveal that the proposed model is able to explain several statistical properties and stylized facts observed in real financial markets, including persistent high volatility, fat-tailed return distributions, volatility clustering, and positive autocorrelation of absolute returns.

  1. Real and financial market interactions in a multiplier-accelerator model: Nonlinear dynamics, multistability and stylized facts.

    PubMed

    Cavalli, F; Naimzada, A; Pecora, N

    2017-10-01

    In the present paper, we investigate the dynamics of a model in which the real part of the economy, described within a multiplier-accelerator framework, interacts with a financial market with heterogeneous speculators, in order to study the channels through which the two sectors influence each other. Employing analytical and numerical tools, we investigate stability conditions as well as bifurcations and possible periodic, quasi-periodic, and chaotic dynamics, enlightening how the degree of market interaction, together with the accelerator parameter and the intervention of the fiscal authority, may affect the business cycle and the course of the financial market. In particular, we show that even if the steady state is locally stable, multistability phenomena can occur, with several and complex dynamic structures coexisting with the steady state. Finally, simulations reveal that the proposed model is able to explain several statistical properties and stylized facts observed in real financial markets, including persistent high volatility, fat-tailed return distributions, volatility clustering, and positive autocorrelation of absolute returns.

  2. Dynamic fluctuation of proteins watched in real time

    PubMed Central

    Ormos, Pál

    2008-01-01

    The dynamic nature of protein function is a fundamental concept in the physics of proteins. Although the basic general ideas are well accepted most experimental evidence has an indirect nature. The detailed characterization of the dynamics is necessary for the understanding in detail. The dynamic fluctuations thought crucial for the function span an extremely broad time, starting from the picosecond regime. Recently, a few new experimental techniques emerged that permit the observation of dynamical phenomena directly. Notably, pulsed infrared (IR) spectroscopy has been applied with great success to observe structural changes with picosecond time resolution. Using two-dimensional-IR vibrational echo chemical exchange spectroscopy Ishikawa and co-workers [Ishikawa et al. (2008), Proc. Natl. Acad. Sci. U.S.A. 101, 14402–14407] managed to observe the transition between well defined conformational substrates of carbonmonoxy myoglobin directly. This is an important step in improving our insight into the details of protein function. PMID:19436491

  3. Formal Verification of a Power Controller Using the Real-Time Model Checker UPPAAL

    NASA Technical Reports Server (NTRS)

    Havelund, Klaus; Larsen, Kim Guldstrand; Skou, Arne

    1999-01-01

    A real-time system for power-down control in audio/video components is modeled and verified using the real-time model checker UPPAAL. The system is supposed to reside in an audio/video component and control (read from and write to) links to neighbor audio/video components such as TV, VCR and remote-control. In particular, the system is responsible for the powering up and down of the component in between the arrival of data, and in order to do so in a safe way without loss of data, it is essential that no link interrupts are lost. Hence, a component system is a multitasking system with hard real-time requirements, and we present techniques for modeling time consumption in such a multitasked, prioritized system. The work has been carried out in a collaboration between Aalborg University and the audio/video company B&O. By modeling the system, 3 design errors were identified and corrected, and the following verification confirmed the validity of the design but also revealed the necessity for an upper limit of the interrupt frequency. The resulting design has been implemented and it is going to be incorporated as part of a new product line.

  4. OSSOS: X. How to use a Survey Simulator: Statistical Testing of Dynamical Models Against the Real Kuiper Belt

    NASA Astrophysics Data System (ADS)

    Lawler, Samantha M.; Kavelaars, J. J.; Alexandersen, Mike; Bannister, Michele T.; Gladman, Brett; Petit, Jean-Marc; Shankman, Cory

    2018-05-01

    All surveys include observational biases, which makes it impossible to directly compare properties of discovered trans-Neptunian Objects (TNOs) with dynamical models. However, by carefully keeping track of survey pointings on the sky, detection limits, tracking fractions, and rate cuts, the biases from a survey can be modelled in Survey Simulator software. A Survey Simulator takes an intrinsic orbital model (from, for example, the output of a dynamical Kuiper belt emplacement simulation) and applies the survey biases, so that the biased simulated objects can be directly compared with real discoveries. This methodology has been used with great success in the Outer Solar System Origins Survey (OSSOS) and its predecessor surveys. In this chapter, we give four examples of ways to use the OSSOS Survey Simulator to gain knowledge about the true structure of the Kuiper Belt. We demonstrate how to statistically compare different dynamical model outputs with real TNO discoveries, how to quantify detection biases within a TNO population, how to measure intrinsic population sizes, and how to use upper limits from non-detections. We hope this will provide a framework for dynamical modellers to statistically test the validity of their models.

  5. A discrete mechanics framework for real time virtual surgical simulations with application to virtual laparoscopic nephrectomy.

    PubMed

    Zhou, Xiangmin; Zhang, Nan; Sha, Desong; Shen, Yunhe; Tamma, Kumar K; Sweet, Robert

    2009-01-01

    The inability to render realistic soft-tissue behavior in real time has remained a barrier to face and content aspects of validity for many virtual reality surgical training systems. Biophysically based models are not only suitable for training purposes but also for patient-specific clinical applications, physiological modeling and surgical planning. When considering the existing approaches for modeling soft tissue for virtual reality surgical simulation, the computer graphics-based approach lacks predictive capability; the mass-spring model (MSM) based approach lacks biophysically realistic soft-tissue dynamic behavior; and the finite element method (FEM) approaches fail to meet the real-time requirement. The present development stems from physics fundamental thermodynamic first law; for a space discrete dynamic system directly formulates the space discrete but time continuous governing equation with embedded material constitutive relation and results in a discrete mechanics framework which possesses a unique balance between the computational efforts and the physically realistic soft-tissue dynamic behavior. We describe the development of the discrete mechanics framework with focused attention towards a virtual laparoscopic nephrectomy application.

  6. Demand response-enabled model predictive HVAC load control in buildings using real-time electricity pricing

    NASA Astrophysics Data System (ADS)

    Avci, Mesut

    A practical cost and energy efficient model predictive control (MPC) strategy is proposed for HVAC load control under dynamic real-time electricity pricing. The MPC strategy is built based on a proposed model that jointly minimizes the total energy consumption and hence, cost of electricity for the user, and the deviation of the inside temperature from the consumer's preference. An algorithm that assigns temperature set-points (reference temperatures) to price ranges based on the consumer's discomfort tolerance index is developed. A practical parameter prediction model is also designed for mapping between the HVAC load and the inside temperature. The prediction model and the produced temperature set-points are integrated as inputs into the MPC controller, which is then used to generate signal actions for the AC unit. To investigate and demonstrate the effectiveness of the proposed approach, a simulation based experimental analysis is presented using real-life pricing data. An actual prototype for the proposed HVAC load control strategy is then built and a series of prototype experiments are conducted similar to the simulation studies. The experiments reveal that the MPC strategy can lead to significant reductions in overall energy consumption and cost savings for the consumer. Results suggest that by providing an efficient response strategy for the consumers, the proposed MPC strategy can enable the utility providers to adopt efficient demand management policies using real-time pricing. Finally, a cost-benefit analysis is performed to display the economic feasibility of implementing such a controller as part of a building energy management system, and the payback period is identified considering cost of prototype build and cost savings to help the adoption of this controller in the building HVAC control industry.

  7. Real-time monitoring of a microbial electrolysis cell using an electrical equivalent circuit model.

    PubMed

    Hussain, S A; Perrier, M; Tartakovsky, B

    2018-04-01

    Efforts in developing microbial electrolysis cells (MECs) resulted in several novel approaches for wastewater treatment and bioelectrosynthesis. Practical implementation of these approaches necessitates the development of an adequate system for real-time (on-line) monitoring and diagnostics of MEC performance. This study describes a simple MEC equivalent electrical circuit (EEC) model and a parameter estimation procedure, which enable such real-time monitoring. The proposed approach involves MEC voltage and current measurements during its operation with periodic power supply connection/disconnection (on/off operation) followed by parameter estimation using either numerical or analytical solution of the model. The proposed monitoring approach is demonstrated using a membraneless MEC with flow-through porous electrodes. Laboratory tests showed that changes in the influent carbon source concentration and composition significantly affect MEC total internal resistance and capacitance estimated by the model. Fast response of these EEC model parameters to changes in operating conditions enables the development of a model-based approach for real-time monitoring and fault detection.

  8. REAL-TIME MODEL-BASED ELECTRICAL POWERED WHEELCHAIR CONTROL

    PubMed Central

    Wang, Hongwu; Salatin, Benjamin; Grindle, Garrett G.; Ding, Dan; Cooper, Rory A.

    2009-01-01

    The purpose of this study was to evaluate the effects of three different control methods on driving speed variation and wheel-slip of an electric-powered wheelchair (EPW). A kinematic model as well as 3-D dynamic model was developed to control the velocity and traction of the wheelchair. A smart wheelchair platform was designed and built with a computerized controller and encoders to record wheel speeds and to detect the slip. A model based, a proportional-integral-derivative (PID) and an open-loop controller were applied with the EPW driving on four different surfaces at three specified speeds. The speed errors, variation, rise time, settling time and slip coefficient were calculated and compared for a speed step-response input. Experimental results showed that model based control performed best on all surfaces across the speeds. PMID:19733494

  9. CHIMERA II - A real-time multiprocessing environment for sensor-based robot control

    NASA Technical Reports Server (NTRS)

    Stewart, David B.; Schmitz, Donald E.; Khosla, Pradeep K.

    1989-01-01

    A multiprocessing environment for a wide variety of sensor-based robot system, providing the flexibility, performance, and UNIX-compatible interface needed for fast development of real-time code is addressed. The requirements imposed on the design of a programming environment for sensor-based robotic control is outlined. The details of the current hardware configuration are presented, along with the details of the CHIMERA II software. Emphasis is placed on the kernel, low-level interboard communication, user interface, extended file system, user-definable and dynamically selectable real-time schedulers, remote process synchronization, and generalized interprocess communication. A possible implementation of a hierarchical control model, the NASA/NBS standard reference model for telerobot control system is demonstrated.

  10. Motion-adapted catheter navigation with real-time instantiation and improved visualisation

    PubMed Central

    Kwok, Ka-Wai; Wang, Lichao; Riga, Celia; Bicknell, Colin; Cheshire, Nicholas; Yang, Guang-Zhong

    2014-01-01

    The improvements to catheter manipulation by the use of robot-assisted catheter navigation for endovascular procedures include increased precision, stability of motion and operator comfort. However, navigation through the vasculature under fluoroscopic guidance is still challenging, mostly due to physiological motion and when tortuous vessels are involved. In this paper, we propose a motion-adaptive catheter navigation scheme based on shape modelling to compensate for these dynamic effects, permitting predictive and dynamic navigations. This allows for timed manipulations synchronised with the vascular motion. The technical contribution of the paper includes the following two aspects. Firstly, a dynamic shape modelling and real-time instantiation scheme based on sparse data obtained intra-operatively is proposed for improved visualisation of the 3D vasculature during endovascular intervention. Secondly, a reconstructed frontal view from the catheter tip using the derived dynamic model is used as an interventional aid to user guidance. To demonstrate the practical value of the proposed framework, a simulated aortic branch cannulation procedure is used with detailed user validation to demonstrate the improvement in navigation quality and efficiency. PMID:24744817

  11. Defect Dynamics in Artificial Colloidal Ice: Real-Time Observation, Manipulation, and Logic Gate.

    PubMed

    Loehr, Johannes; Ortiz-Ambriz, Antonio; Tierno, Pietro

    2016-10-14

    We study the defect dynamics in a colloidal spin ice system realized by filling a square lattice of topographic double well islands with repulsively interacting magnetic colloids. We focus on the contraction of defects in the ground state, and contraction or expansion in a metastable biased state. Combining real-time experiments with simulations, we prove that these defects behave like emergent topological monopoles obeying a Coulomb law with an additional line tension. We further show how to realize a completely resettable "nor" gate, which provides guidelines for fabrication of nanoscale logic devices based on the motion of topological magnetic monopoles.

  12. Subsystem real-time time dependent density functional theory.

    PubMed

    Krishtal, Alisa; Ceresoli, Davide; Pavanello, Michele

    2015-04-21

    We present the extension of Frozen Density Embedding (FDE) formulation of subsystem Density Functional Theory (DFT) to real-time Time Dependent Density Functional Theory (rt-TDDFT). FDE is a DFT-in-DFT embedding method that allows to partition a larger Kohn-Sham system into a set of smaller, coupled Kohn-Sham systems. Additional to the computational advantage, FDE provides physical insight into the properties of embedded systems and the coupling interactions between them. The extension to rt-TDDFT is done straightforwardly by evolving the Kohn-Sham subsystems in time simultaneously, while updating the embedding potential between the systems at every time step. Two main applications are presented: the explicit excitation energy transfer in real time between subsystems is demonstrated for the case of the Na4 cluster and the effect of the embedding on optical spectra of coupled chromophores. In particular, the importance of including the full dynamic response in the embedding potential is demonstrated.

  13. Real Time Land-Surface Hydrologic Modeling Over Continental US

    NASA Technical Reports Server (NTRS)

    Houser, Paul R.

    1998-01-01

    The land surface component of the hydrological cycle is fundamental to the overall functioning of the atmospheric and climate processes. Spatially and temporally variable rainfall and available energy, combined with land surface heterogeneity cause complex variations in all processes related to surface hydrology. The characterization of the spatial and temporal variability of water and energy cycles are critical to improve our understanding of land surface-atmosphere interaction and the impact of land surface processes on climate extremes. Because the accurate knowledge of these processes and their variability is important for climate predictions, most Numerical Weather Prediction (NWP) centers have incorporated land surface schemes in their models. However, errors in the NWP forcing accumulate in the surface and energy stores, leading to incorrect surface water and energy partitioning and related processes. This has motivated the NWP to impose ad hoc corrections to the land surface states to prevent this drift. A proposed methodology is to develop Land Data Assimilation schemes (LDAS), which are uncoupled models forced with observations, and not affected by NWP forcing biases. The proposed research is being implemented as a real time operation using an existing Surface Vegetation Atmosphere Transfer Scheme (SVATS) model at a 40 km degree resolution across the United States to evaluate these critical science questions. The model will be forced with real time output from numerical prediction models, satellite data, and radar precipitation measurements. Model parameters will be derived from the existing GIS vegetation and soil coverages. The model results will be aggregated to various scales to assess water and energy balances and these will be validated with various in-situ observations.

  14. Real-Time and Near Real-Time Data for Space Weather Applications and Services

    NASA Astrophysics Data System (ADS)

    Singer, H. J.; Balch, C. C.; Biesecker, D. A.; Matsuo, T.; Onsager, T. G.

    2015-12-01

    Space weather can be defined as conditions in the vicinity of Earth and in the interplanetary environment that are caused primarily by solar processes and influenced by conditions on Earth and its atmosphere. Examples of space weather are the conditions that result from geomagnetic storms, solar particle events, and bursts of intense solar flare radiation. These conditions can have impacts on modern-day technologies such as GPS or electric power grids and on human activities such as astronauts living on the International Space Station or explorers traveling to the moon or Mars. While the ultimate space weather goal is accurate prediction of future space weather conditions, for many applications and services, we rely on real-time and near-real time observations and model results for the specification of current conditions. In this presentation, we will describe the space weather system and the need for real-time and near-real time data that drive the system, characterize conditions in the space environment, and are used by models for assimilation and validation. Currently available data will be assessed and a vision for future needs will be given. The challenges for establishing real-time data requirements, as well as acquiring, processing, and disseminating the data will be described, including national and international collaborations. In addition to describing how the data are used for official government products, we will also give examples of how these data are used by both the public and private sector for new applications that serve the public.

  15. Real-time inversions for finite fault slip models and rupture geometry based on high-rate GPS data

    USGS Publications Warehouse

    Minson, Sarah E.; Murray, Jessica R.; Langbein, John O.; Gomberg, Joan S.

    2015-01-01

    We present an inversion strategy capable of using real-time high-rate GPS data to simultaneously solve for a distributed slip model and fault geometry in real time as a rupture unfolds. We employ Bayesian inference to find the optimal fault geometry and the distribution of possible slip models for that geometry using a simple analytical solution. By adopting an analytical Bayesian approach, we can solve this complex inversion problem (including calculating the uncertainties on our results) in real time. Furthermore, since the joint inversion for distributed slip and fault geometry can be computed in real time, the time required to obtain a source model of the earthquake does not depend on the computational cost. Instead, the time required is controlled by the duration of the rupture and the time required for information to propagate from the source to the receivers. We apply our modeling approach, called Bayesian Evidence-based Fault Orientation and Real-time Earthquake Slip, to the 2011 Tohoku-oki earthquake, 2003 Tokachi-oki earthquake, and a simulated Hayward fault earthquake. In all three cases, the inversion recovers the magnitude, spatial distribution of slip, and fault geometry in real time. Since our inversion relies on static offsets estimated from real-time high-rate GPS data, we also present performance tests of various approaches to estimating quasi-static offsets in real time. We find that the raw high-rate time series are the best data to use for determining the moment magnitude of the event, but slightly smoothing the raw time series helps stabilize the inversion for fault geometry.

  16. Temporal Specification and Verification of Real-Time Systems.

    DTIC Science & Technology

    1991-08-30

    of concrete real - time systems can be modeled adequately. Specification: We present two conservative extensions of temporal logic that allow for the...logic. We present both model-checking algorithms for the automatic verification of finite-state real - time systems and proof methods for the deductive verification of real - time systems .

  17. EcoPAD, an interactive platform for near real-time ecological forecasting by assimilating data into model

    NASA Astrophysics Data System (ADS)

    MA, S.; Huang, Y.; Stacy, M.; Jiang, J.; Sundi, N.; Ricciuto, D. M.; Hanson, P. J.; Luo, Y.; Saruta, V.

    2017-12-01

    Ecological forecasting is critical in various aspects of our coupled human-nature systems, such as disaster risk reduction, natural resource management and climate change mitigation. Novel advancements are in urgent need to deepen our understandings of ecosystem dynamics, boost the predictive capacity of ecology, and provide timely and effective information for decision-makers in a rapidly changing world. Our study presents a smart system - Ecological Platform for Assimilation of Data (EcoPAD) - which streamlines web request-response, data management, model execution, result storage and visualization. EcoPAD allows users to (i) estimate model parameters or state variables, (ii) quantify uncertainty of estimated parameters and projected states of ecosystems, (iii) evaluate model structures, (iv) assess sampling strategies, (v) conduct ecological forecasting, and (vi) detect ecosystem acclimation to climate change. One of the key innovations of the web-based EcoPAD is the automated near- or real-time forecasting of ecosystem dynamics with uncertainty fully quantified. The user friendly webpage enables non-modelers to explore their data for simulation and data assimilation. As a case study, we applied EcoPAD to the Spruce and Peatland Responses Under Climatic and Environmental Change Experiment (SPRUCE), a whole ecosystem warming and CO2 enrichment treatment project in the northern peatland, assimilated multiple data streams into a process based ecosystem model, enhanced timely feedback between modelers and experimenters, ultimately improved ecosystem forecasting and made better use of current knowledge. Built in a framework with flexible API, EcoPAD is easily portable and will benefit scientific communities, policy makers as well as the general public.

  18. Bayesian dynamic modeling of time series of dengue disease case counts.

    PubMed

    Martínez-Bello, Daniel Adyro; López-Quílez, Antonio; Torres-Prieto, Alexander

    2017-07-01

    The aim of this study is to model the association between weekly time series of dengue case counts and meteorological variables, in a high-incidence city of Colombia, applying Bayesian hierarchical dynamic generalized linear models over the period January 2008 to August 2015. Additionally, we evaluate the model's short-term performance for predicting dengue cases. The methodology shows dynamic Poisson log link models including constant or time-varying coefficients for the meteorological variables. Calendar effects were modeled using constant or first- or second-order random walk time-varying coefficients. The meteorological variables were modeled using constant coefficients and first-order random walk time-varying coefficients. We applied Markov Chain Monte Carlo simulations for parameter estimation, and deviance information criterion statistic (DIC) for model selection. We assessed the short-term predictive performance of the selected final model, at several time points within the study period using the mean absolute percentage error. The results showed the best model including first-order random walk time-varying coefficients for calendar trend and first-order random walk time-varying coefficients for the meteorological variables. Besides the computational challenges, interpreting the results implies a complete analysis of the time series of dengue with respect to the parameter estimates of the meteorological effects. We found small values of the mean absolute percentage errors at one or two weeks out-of-sample predictions for most prediction points, associated with low volatility periods in the dengue counts. We discuss the advantages and limitations of the dynamic Poisson models for studying the association between time series of dengue disease and meteorological variables. The key conclusion of the study is that dynamic Poisson models account for the dynamic nature of the variables involved in the modeling of time series of dengue disease, producing useful

  19. Real-time observation of X-ray diffraction patterns with the Lixiscope

    NASA Technical Reports Server (NTRS)

    Chung, D. Y.; Tsang, T.; Yin, L. I.; Anderson, J. R.

    1981-01-01

    The feasibility of the Lixiscope (Low Intensity X-ray Imaging Scope) is demonstrated for real-time observation of transmission Laue patterns. Making use of the high-gain capability of microchannel plate (MCP) visible-light image intensifier tubes, X-ray images are converted to visible-light images by a scintillator. Pb discs are taped to the center of the Lixiscope input face, and crystal samples are held on a goniometer stage with modeling clay. With a compact size to facilitate off axis viewing, and real-time viewing to allow instantaneous response, the Lixiscope may prove useful in dynamic studies of the effects of plastic flows, stresses, high pressures, and low temperatures.

  20. Capability of a Mobile Monitoring System to Provide Real-Time Data Broadcasting and Near Real-Time Source Attribution

    NASA Astrophysics Data System (ADS)

    Erickson, M.; Olaguer, J.; Wijesinghe, A.; Colvin, J.; Neish, B.; Williams, J.

    2014-12-01

    It is becoming increasingly important to understand the emissions and health effects of industrial facilities. Many areas have no or limited sustained monitoring capabilities, making it difficult to quantify the major pollution sources affecting human health, especially in fence line communities. Developments in real-time monitoring and micro-scale modeling offer unique ways to tackle these complex issues. This presentation will demonstrate the capability of coupling real-time observations with micro-scale modeling to provide real-time information and near real-time source attribution. The Houston Advanced Research Center constructed the Mobile Acquisition of Real-time Concentrations (MARC) laboratory. MARC consists of a Ford E-350 passenger van outfitted with a Proton Transfer Reaction Mass Spectrometer (PTR-MS) and meteorological equipment. This allows for the fast measurement of various VOCs important to air quality. The data recorded from the van is uploaded to an off-site database and the information is broadcast to a website in real-time. This provides for off-site monitoring of MARC's observations, which allows off-site personnel to provide immediate input to the MARC operators on how to best achieve project objectives. The information stored in the database can also be used to provide near real-time source attribution. An inverse model has been used to ascertain the amount, location, and timing of emissions based on MARC measurements in the vicinity of industrial sites. The inverse model is based on a 3D micro-scale Eulerian forward and adjoint air quality model known as the HARC model. The HARC model uses output from the Quick Urban and Industrial Complex (QUIC) wind model and requires a 3D digital model of the monitored facility based on lidar or industrial permit data. MARC is one of the instrument platforms deployed during the 2014 Benzene and other Toxics Exposure Study (BEE-TEX) in Houston, TX. The main goal of the study is to quantify and explain the

  1. [Dynamic road vehicle emission inventory simulation study based on real time traffic information].

    PubMed

    Huang, Cheng; Liu, Juan; Chen, Chang-Hong; Zhang, Jian; Liu, Deng-Guo; Zhu, Jing-Yu; Huang, Wei-Ming; Chao, Yuan

    2012-11-01

    The vehicle activity survey, including traffic flow distribution, driving condition, and vehicle technologies, were conducted in Shanghai. The databases of vehicle flow, VSP distribution and vehicle categories were established according to the surveyed data. Based on this, a dynamic vehicle emission inventory simulation method was designed by using the real time traffic information data, such as traffic flow and average speed. Some roads in Shanghai city were selected to conduct the hourly vehicle emission simulation as a case study. The survey results show that light duty passenger car and taxi are major vehicles on the roads of Shanghai city, accounting for 48% - 72% and 15% - 43% of the total flow in each hour, respectively. VSP distribution has a good relationship with the average speed. The peak of VSP distribution tends to move to high load section and become lower with the increase of average speed. Vehicles achieved Euro 2 and Euro 3 standards are majorities of current vehicle population in Shanghai. Based on the calibration of vehicle travel mileage data, the proportions of Euro 2 and Euro 3 standard vehicles take up 11% - 70% and 17% - 51% in the real-world situation, respectively. The emission simulation results indicate that the ratios of emission peak and valley for the pollutants of CO, VOC, NO(x) and PM are 3.7, 4.6, 9.6 and 19.8, respectively. CO and VOC emissions mainly come from light-duty passenger car and taxi, which has a good relationship with the traffic flow. NO(x) and PM emissions are mainly from heavy-duty bus and public buses and mainly concentrate in the morning and evening peak hours. The established dynamic vehicle emission simulation method can reflect the change of actual road emission and output high emission road sectors and hours in real time. The method can provide an important technical means and decision-making basis for transportation environment management.

  2. A dynamical systems perspective for a real-time response to a marine oil spill.

    PubMed

    García-Garrido, V J; Ramos, A; Mancho, A M; Coca, J; Wiggins, S

    2016-11-15

    This paper discusses the combined use of tools from dynamical systems theory and remote sensing techniques and shows how they are effective instruments which may greatly contribute to the decision making protocols of the emergency services for the real-time management of oil spills. This work presents the successful interplay of these techniques for a recent situation, the sinking of the Oleg Naydenov fishing ship that took place in Spain, close to the Canary Islands, in April 2015. Copyright © 2016. Published by Elsevier Ltd.

  3. Bayesian dynamic modeling of time series of dengue disease case counts

    PubMed Central

    López-Quílez, Antonio; Torres-Prieto, Alexander

    2017-01-01

    The aim of this study is to model the association between weekly time series of dengue case counts and meteorological variables, in a high-incidence city of Colombia, applying Bayesian hierarchical dynamic generalized linear models over the period January 2008 to August 2015. Additionally, we evaluate the model’s short-term performance for predicting dengue cases. The methodology shows dynamic Poisson log link models including constant or time-varying coefficients for the meteorological variables. Calendar effects were modeled using constant or first- or second-order random walk time-varying coefficients. The meteorological variables were modeled using constant coefficients and first-order random walk time-varying coefficients. We applied Markov Chain Monte Carlo simulations for parameter estimation, and deviance information criterion statistic (DIC) for model selection. We assessed the short-term predictive performance of the selected final model, at several time points within the study period using the mean absolute percentage error. The results showed the best model including first-order random walk time-varying coefficients for calendar trend and first-order random walk time-varying coefficients for the meteorological variables. Besides the computational challenges, interpreting the results implies a complete analysis of the time series of dengue with respect to the parameter estimates of the meteorological effects. We found small values of the mean absolute percentage errors at one or two weeks out-of-sample predictions for most prediction points, associated with low volatility periods in the dengue counts. We discuss the advantages and limitations of the dynamic Poisson models for studying the association between time series of dengue disease and meteorological variables. The key conclusion of the study is that dynamic Poisson models account for the dynamic nature of the variables involved in the modeling of time series of dengue disease, producing useful

  4. Analytical model for real time, noninvasive estimation of blood glucose level.

    PubMed

    Adhyapak, Anoop; Sidley, Matthew; Venkataraman, Jayanti

    2014-01-01

    The paper presents an analytical model to estimate blood glucose level from measurements made non-invasively and in real time by an antenna strapped to a patient's wrist. Some promising success has been shown by the RIT ETA Lab research group that an antenna's resonant frequency can track, in real time, changes in glucose concentration. Based on an in-vitro study of blood samples of diabetic patients, the paper presents a modified Cole-Cole model that incorporates a factor to represent the change in glucose level. A calibration technique using the input impedance technique is discussed and the results show a good estimation as compared to the glucose meter readings. An alternate calibration methodology has been developed that is based on the shift in the antenna resonant frequency using an equivalent circuit model containing a shunt capacitor to represent the shift in resonant frequency with changing glucose levels. Work under progress is the optimization of the technique with a larger sample of patients.

  5. System-level power optimization for real-time distributed embedded systems

    NASA Astrophysics Data System (ADS)

    Luo, Jiong

    well. Variable-frequency links have been designed by circuit designers for both parallel and serial links, which can adaptively regulate the supply voltage of transceivers to a desired link frequency, to exploit the variations in bandwidth requirement for power savings. We propose solutions for simultaneous dynamic voltage scaling of processors and links. The proposed solution considers real-time scheduling, flow control, and packet routing jointly. It can trade off the power consumption on processors and communication links via efficient slack allocation, and lead to more power savings than dynamic voltage scaling on processors alone. For battery-operated systems, the battery lifespan is an important concern. Due to the effects of discharge rate and battery recovery, the discharge pattern of batteries has an impact on the battery lifespan. Battery models indicate that even under the same average power consumption, reducing peak power current and variance in the power profile can increase the battery efficiency and thereby prolong battery lifetime. To take advantage of these effects, we propose battery-driven scheduling techniques for embedded applications, to reduce the peak power and the variance in the power profile of the overall system under real-time constraints. The proposed scheduling algorithms are also beneficial in addressing reliability and signal integrity concerns by effectively controlling peak power and variance of the power profile.

  6. Global Real-Time Ocean Forecast System

    Science.gov Websites

    services. Marine Modeling and Analysis Branch Logo Click here to go to the MMAB home page Global Real-Time 17 Oct 2017 at 0Z, the Global RTOFS model has been upgraded to version 1.1.2. Changes include: The ). The global operational Real-Time Ocean Forecast System (Global RTOFS) at the National Centers for

  7. VERSE - Virtual Equivalent Real-time Simulation

    NASA Technical Reports Server (NTRS)

    Zheng, Yang; Martin, Bryan J.; Villaume, Nathaniel

    2005-01-01

    Distributed real-time simulations provide important timing validation and hardware in the- loop results for the spacecraft flight software development cycle. Occasionally, the need for higher fidelity modeling and more comprehensive debugging capabilities - combined with a limited amount of computational resources - calls for a non real-time simulation environment that mimics the real-time environment. By creating a non real-time environment that accommodates simulations and flight software designed for a multi-CPU real-time system, we can save development time, cut mission costs, and reduce the likelihood of errors. This paper presents such a solution: Virtual Equivalent Real-time Simulation Environment (VERSE). VERSE turns the real-time operating system RTAI (Real-time Application Interface) into an event driven simulator that runs in virtual real time. Designed to keep the original RTAI architecture as intact as possible, and therefore inheriting RTAI's many capabilities, VERSE was implemented with remarkably little change to the RTAI source code. This small footprint together with use of the same API allows users to easily run the same application in both real-time and virtual time environments. VERSE has been used to build a workstation testbed for NASA's Space Interferometry Mission (SIM PlanetQuest) instrument flight software. With its flexible simulation controls and inexpensive setup and replication costs, VERSE will become an invaluable tool in future mission development.

  8. Modeling Optical Spectra of Large Organic Systems Using Real-Time Propagation of Semiempirical Effective Hamiltonians.

    PubMed

    Ghosh, Soumen; Andersen, Amity; Gagliardi, Laura; Cramer, Christopher J; Govind, Niranjan

    2017-09-12

    We present an implementation of a time-dependent semiempirical method (INDO/S) in NWChem using real-time (RT) propagation to address, in principle, the entire spectrum of valence electronic excitations. Adopting this model, we study the UV/vis spectra of medium-sized systems such as P3B2 and f-coronene, and in addition much larger systems such as ubiquitin in the gas phase and the betanin chromophore in the presence of two explicit solvents (water and methanol). RT-INDO/S provides qualitatively and often quantitatively accurate results when compared with RT- TDDFT or experimental spectra. Even though we only consider the INDO/S Hamiltonian in this work, our implementation provides a framework for performing electron dynamics in large systems using semiempirical Hartree-Fock Hamiltonians in general.

  9. Real-time monitoring system of composite aircraft wings utilizing Fibre Bragg Grating sensor

    NASA Astrophysics Data System (ADS)

    Vorathin, E.; Hafizi, Z. M.; Che Ghani, S. A.; Lim, K. S.

    2016-10-01

    Embedment of Fibre Bragg Grating (FBG) sensor in composite aircraft wings leads to the advancement of structural condition monitoring. The monitored aircraft wings have the capability to give real-time response under critical loading circumstances. The main objective of this paper is to develop a real-time FBG monitoring system for composite aircraft wings to view real-time changes when the structure undergoes some static loadings and dynamic impact. The implementation of matched edge filter FBG interrogation system to convert wavelength variations to strain readings shows that the structure is able to response instantly in real-time when undergoing few loadings and dynamic impact. This smart monitoring system is capable of updating the changes instantly in real-time and shows the weight induced on the composite aircraft wings instantly without any error. It also has a good agreement with acoustic emission (AE) sensor in the dynamic test.

  10. Three axis electronic flight motion simulator real time control system design and implementation

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

    Gao, Zhiyuan; Miao, Zhonghua, E-mail: zhonghua-miao@163.com; Wang, Xiaohua

    2014-12-15

    A three axis electronic flight motion simulator is reported in this paper including the modelling, the controller design as well as the hardware implementation. This flight motion simulator could be used for inertial navigation test and high precision inertial navigation system with good dynamic and static performances. A real time control system is designed, several control system implementation problems were solved including time unification with parallel port interrupt, high speed finding-zero method of rotary inductosyn, zero-crossing management with continuous rotary, etc. Tests were carried out to show the effectiveness of the proposed real time control system.

  11. Three axis electronic flight motion simulator real time control system design and implementation.

    PubMed

    Gao, Zhiyuan; Miao, Zhonghua; Wang, Xuyong; Wang, Xiaohua

    2014-12-01

    A three axis electronic flight motion simulator is reported in this paper including the modelling, the controller design as well as the hardware implementation. This flight motion simulator could be used for inertial navigation test and high precision inertial navigation system with good dynamic and static performances. A real time control system is designed, several control system implementation problems were solved including time unification with parallel port interrupt, high speed finding-zero method of rotary inductosyn, zero-crossing management with continuous rotary, etc. Tests were carried out to show the effectiveness of the proposed real time control system.

  12. An FPGA Platform for Real-Time Simulation of Spiking Neuronal Networks

    PubMed Central

    Pani, Danilo; Meloni, Paolo; Tuveri, Giuseppe; Palumbo, Francesca; Massobrio, Paolo; Raffo, Luigi

    2017-01-01

    In the last years, the idea to dynamically interface biological neurons with artificial ones has become more and more urgent. The reason is essentially due to the design of innovative neuroprostheses where biological cell assemblies of the brain can be substituted by artificial ones. For closed-loop experiments with biological neuronal networks interfaced with in silico modeled networks, several technological challenges need to be faced, from the low-level interfacing between the living tissue and the computational model to the implementation of the latter in a suitable form for real-time processing. Field programmable gate arrays (FPGAs) can improve flexibility when simple neuronal models are required, obtaining good accuracy, real-time performance, and the possibility to create a hybrid system without any custom hardware, just programming the hardware to achieve the required functionality. In this paper, this possibility is explored presenting a modular and efficient FPGA design of an in silico spiking neural network exploiting the Izhikevich model. The proposed system, prototypically implemented on a Xilinx Virtex 6 device, is able to simulate a fully connected network counting up to 1,440 neurons, in real-time, at a sampling rate of 10 kHz, which is reasonable for small to medium scale extra-cellular closed-loop experiments. PMID:28293163

  13. Real time damage detection using recursive principal components and time varying auto-regressive modeling

    NASA Astrophysics Data System (ADS)

    Krishnan, M.; Bhowmik, B.; Hazra, B.; Pakrashi, V.

    2018-02-01

    In this paper, a novel baseline free approach for continuous online damage detection of multi degree of freedom vibrating structures using Recursive Principal Component Analysis (RPCA) in conjunction with Time Varying Auto-Regressive Modeling (TVAR) is proposed. In this method, the acceleration data is used to obtain recursive proper orthogonal components online using rank-one perturbation method, followed by TVAR modeling of the first transformed response, to detect the change in the dynamic behavior of the vibrating system from its pristine state to contiguous linear/non-linear-states that indicate damage. Most of the works available in the literature deal with algorithms that require windowing of the gathered data owing to their data-driven nature which renders them ineffective for online implementation. Algorithms focussed on mathematically consistent recursive techniques in a rigorous theoretical framework of structural damage detection is missing, which motivates the development of the present framework that is amenable for online implementation which could be utilized along with suite experimental and numerical investigations. The RPCA algorithm iterates the eigenvector and eigenvalue estimates for sample covariance matrices and new data point at each successive time instants, using the rank-one perturbation method. TVAR modeling on the principal component explaining maximum variance is utilized and the damage is identified by tracking the TVAR coefficients. This eliminates the need for offline post processing and facilitates online damage detection especially when applied to streaming data without requiring any baseline data. Numerical simulations performed on a 5-dof nonlinear system under white noise excitation and El Centro (also known as 1940 Imperial Valley earthquake) excitation, for different damage scenarios, demonstrate the robustness of the proposed algorithm. The method is further validated on results obtained from case studies involving

  14. Real-time observation of the conformational dynamics of mitochondrial Hsp70 by spFRET

    PubMed Central

    Sikor, Martin; Mapa, Koyeli; von Voithenberg, Lena Voith; Mokranjac, Dejana; Lamb, Don C

    2013-01-01

    The numerous functions of the important class of molecular chaperones, heat shock proteins 70 (Hsp70), rely on cycles of intricate conformational changes driven by ATP-hydrolysis and regulated by cochaperones and substrates. Here, we used Förster resonance energy transfer to study the conformational dynamics of individual molecules of Ssc1, a mitochondrial Hsp70, in real time. The intrinsic dynamics of the substrate-binding domain of Ssc1 was observed to be uncoupled from the dynamic interactions between substrate- and nucleotide-binding domains. Analysis of the fluctuations in the interdomain separation revealed frequent transitions to a nucleotide-free state. The nucleotide-exchange factor Mge1 did not induce ADP release, as expected, but rather facilitated binding of ATP. These results indicate that the conformational cycle of Ssc1 is more elaborate than previously thought and provide insight into how the Hsp70s can perform a wide variety of functions. PMID:23624933

  15. Real-time observation of the conformational dynamics of mitochondrial Hsp70 by spFRET.

    PubMed

    Sikor, Martin; Mapa, Koyeli; von Voithenberg, Lena Voith; Mokranjac, Dejana; Lamb, Don C

    2013-05-29

    The numerous functions of the important class of molecular chaperones, heat shock proteins 70 (Hsp70), rely on cycles of intricate conformational changes driven by ATP-hydrolysis and regulated by cochaperones and substrates. Here, we used Förster resonance energy transfer to study the conformational dynamics of individual molecules of Ssc1, a mitochondrial Hsp70, in real time. The intrinsic dynamics of the substrate-binding domain of Ssc1 was observed to be uncoupled from the dynamic interactions between substrate- and nucleotide-binding domains. Analysis of the fluctuations in the interdomain separation revealed frequent transitions to a nucleotide-free state. The nucleotide-exchange factor Mge1 did not induce ADP release, as expected, but rather facilitated binding of ATP. These results indicate that the conformational cycle of Ssc1 is more elaborate than previously thought and provide insight into how the Hsp70s can perform a wide variety of functions.

  16. Next Generation Real-Time Systems: Investigating the Potential of Partial-Solution Tasks.

    DTIC Science & Technology

    1994-12-01

    insufficient for dealing with the complexities of next-generation real - time systems . New methods of intelligent control must be developed for guaranteeing...on-time task completion for real - time systems that are faced with unpredictable and dynamically changing requirements. Implementing real-time...tasks by experimentally measuring the change in performance of 11 simulated real - time systems when converted from all-or-nothing tasks to partial

  17. Suzuki-Trotter Formula for Real-Time Dependent LDA I: Electron Dynamics

    NASA Astrophysics Data System (ADS)

    Sugino, Osamu; Miyamoto, Yoshiyuki

    1998-03-01

    To investigate various physical and chemical processes where electron dynamics play a role (e.g. collisions or photochemical reactions), solving the real-time Schrödinger equation is essentially important. ihbar fracpartialφpartial t=H φ Trial of solving eqn. (1) from first principles has begun very recently(K. Yabana and G. F. Bertch, Phys. Rev. B54) 4484 (1996)., and it is now in the stage of establishing efficient, stable, and accurate method for numerical calculation. In this talk, we present several improvements in the method of solving eqn. (1) within the density functional theory: (A) higher order Suzuki-Trotter formula(M. Suzuki, Phys. Lett. A146) 319 (1990). to integrate eqn. (1) keeping the orthonormality of the wavefunctions, (B) special interpolation scheme for the self-consistent potential to reduce the drift in the total-energy, and (C) the preconditioning techniques to increase the time step for the simulation. We will demonstrate numerical stability and efficiency using several cluster calculations, and will address the accuracy by comparing the computed cross sections for atom-electron collisions with experiment.

  18. Seeing real-space dynamics of liquid water through inelastic x-ray scattering

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

    Iwashita, Takuya; Wu, Bin; Chen, Wei-Ren

    Water is ubiquitous on earth, but we know little about the real-space motion of molecules in liquid water. We demonstrate that high-resolution inelastic x-ray scattering measurement over a wide range of momentum and energy transfer makes it possible to probe real-space, real-time dynamics of water molecules through the so-called Van Hove function. Water molecules are found to be strongly correlated in space and time with coupling between the first and second nearest-neighbor molecules. The local dynamic correlation of molecules observed here is crucial to a fundamental understanding of the origin of the physical properties of water, including viscosity. The resultsmore » also suggest that the quantum-mechanical nature of hydrogen bonds could influence its dynamics. Finally, the approach used here offers a powerful experimental method for investigating real-space dynamics of liquids.« less

  19. Seeing real-space dynamics of liquid water through inelastic x-ray scattering

    DOE PAGES

    Iwashita, Takuya; Wu, Bin; Chen, Wei-Ren; ...

    2017-12-22

    Water is ubiquitous on earth, but we know little about the real-space motion of molecules in liquid water. We demonstrate that high-resolution inelastic x-ray scattering measurement over a wide range of momentum and energy transfer makes it possible to probe real-space, real-time dynamics of water molecules through the so-called Van Hove function. Water molecules are found to be strongly correlated in space and time with coupling between the first and second nearest-neighbor molecules. The local dynamic correlation of molecules observed here is crucial to a fundamental understanding of the origin of the physical properties of water, including viscosity. The resultsmore » also suggest that the quantum-mechanical nature of hydrogen bonds could influence its dynamics. Finally, the approach used here offers a powerful experimental method for investigating real-space dynamics of liquids.« less

  20. Seeing real-space dynamics of liquid water through inelastic x-ray scattering.

    PubMed

    Iwashita, Takuya; Wu, Bin; Chen, Wei-Ren; Tsutsui, Satoshi; Baron, Alfred Q R; Egami, Takeshi

    2017-12-01

    Water is ubiquitous on earth, but we know little about the real-space motion of molecules in liquid water. We demonstrate that high-resolution inelastic x-ray scattering measurement over a wide range of momentum and energy transfer makes it possible to probe real-space, real-time dynamics of water molecules through the so-called Van Hove function. Water molecules are found to be strongly correlated in space and time with coupling between the first and second nearest-neighbor molecules. The local dynamic correlation of molecules observed here is crucial to a fundamental understanding of the origin of the physical properties of water, including viscosity. The results also suggest that the quantum-mechanical nature of hydrogen bonds could influence its dynamics. The approach used here offers a powerful experimental method for investigating real-space dynamics of liquids.

  1. Real-Time CORBA

    DTIC Science & Technology

    2000-10-01

    control systems and prototyped the approach by porting the ILU ORB from Xerox to the Lynx real - time operating system . They then provided a distributed...compliant real - time operating system , a real-time ORB, and an ODMG-compliant real-time ODBMS [12]. The MITRE system is an infrastructure for...the server’s local operating system can handle. For instance, on a node controlled by the VXWorks real - time operating system with 256 local

  2. Model for Correlating Real-Time Survey Results to Contaminant Concentrations - 12183

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

    Walker, Stuart A.

    2012-07-01

    The U.S. Environmental Protection Agency (EPA) Superfund program is developing a new Counts Per Minute (CPM) calculator to correlate real-time survey results, which are often expressed as counts per minute, to contaminant concentrations that are more typically provided in risk assessments or for cleanup levels, usually expressed in pCi/g or pCi/m{sup 2}. Currently there is no EPA guidance for Superfund sites on correlating count per minute field survey readings back to risk, dose, or other ARAR based concentrations. The CPM calculator is a web-based model that estimates a gamma detector response for a given level of contamination. The intent ofmore » the CPM calculator is to facilitate more real-time measurements within a Superfund response framework. The draft of the CPM calculator is still undergoing internal EPA review. This will be followed by external peer review. It is expected that the CPM calculator will at least be in peer review by the time of WM2012 and possibly finalized at that time. The CPM calculator should facilitate greater use of real-time measurement at Superfund sites. The CPM calculator may also standardize the process of converting lab data to real time measurements. It will thus lessen the amount of lab sampling that is needed for site characterization and confirmation surveys, but it will not remove the need for sampling. (authors)« less

  3. Design and Implementation of Real-Time Vehicular Camera for Driver Assistance and Traffic Congestion Estimation

    PubMed Central

    Son, Sanghyun; Baek, Yunju

    2015-01-01

    As society has developed, the number of vehicles has increased and road conditions have become complicated, increasing the risk of crashes. Therefore, a service that provides safe vehicle control and various types of information to the driver is urgently needed. In this study, we designed and implemented a real-time traffic information system and a smart camera device for smart driver assistance systems. We selected a commercial device for the smart driver assistance systems, and applied a computer vision algorithm to perform image recognition. For application to the dynamic region of interest, dynamic frame skip methods were implemented to perform parallel processing in order to enable real-time operation. In addition, we designed and implemented a model to estimate congestion by analyzing traffic information. The performance of the proposed method was evaluated using images of a real road environment. We found that the processing time improved by 15.4 times when all the proposed methods were applied in the application. Further, we found experimentally that there was little or no change in the recognition accuracy when the proposed method was applied. Using the traffic congestion estimation model, we also found that the average error rate of the proposed model was 5.3%. PMID:26295230

  4. Design and Implementation of Real-Time Vehicular Camera for Driver Assistance and Traffic Congestion Estimation.

    PubMed

    Son, Sanghyun; Baek, Yunju

    2015-08-18

    As society has developed, the number of vehicles has increased and road conditions have become complicated, increasing the risk of crashes. Therefore, a service that provides safe vehicle control and various types of information to the driver is urgently needed. In this study, we designed and implemented a real-time traffic information system and a smart camera device for smart driver assistance systems. We selected a commercial device for the smart driver assistance systems, and applied a computer vision algorithm to perform image recognition. For application to the dynamic region of interest, dynamic frame skip methods were implemented to perform parallel processing in order to enable real-time operation. In addition, we designed and implemented a model to estimate congestion by analyzing traffic information. The performance of the proposed method was evaluated using images of a real road environment. We found that the processing time improved by 15.4 times when all the proposed methods were applied in the application. Further, we found experimentally that there was little or no change in the recognition accuracy when the proposed method was applied. Using the traffic congestion estimation model, we also found that the average error rate of the proposed model was 5.3%.

  5. Draft Forecasts from Real-Time Runs of Physics-Based Models - A Road to the Future

    NASA Technical Reports Server (NTRS)

    Hesse, Michael; Rastatter, Lutz; MacNeice, Peter; Kuznetsova, Masha

    2008-01-01

    The Community Coordinated Modeling Center (CCMC) is a US inter-agency activity aiming at research in support of the generation of advanced space weather models. As one of its main functions, the CCMC provides to researchers the use of space science models, even if they are not model owners themselves. The second focus of CCMC activities is on validation and verification of space weather models, and on the transition of appropriate models to space weather forecast centers. As part of the latter activity, the CCMC develops real-time simulation systems that stress models through routine execution. A by-product of these real-time calculations is the ability to derive model products, which may be useful for space weather operators. After consultations with NOAA/SEC and with AFWA, CCMC has developed a set of tools as a first step to make real-time model output useful to forecast centers. In this presentation, we will discuss the motivation for this activity, the actions taken so far, and options for future tools from model output.

  6. Time-varying correlations in global real estate markets: A multivariate GARCH with spatial effects approach

    NASA Astrophysics Data System (ADS)

    Gu, Huaying; Liu, Zhixue; Weng, Yingliang

    2017-04-01

    The present study applies the multivariate generalized autoregressive conditional heteroscedasticity (MGARCH) with spatial effects approach for the analysis of the time-varying conditional correlations and contagion effects among global real estate markets. A distinguishing feature of the proposed model is that it can simultaneously capture the spatial interactions and the dynamic conditional correlations compared with the traditional MGARCH models. Results reveal that the estimated dynamic conditional correlations have exhibited significant increases during the global financial crisis from 2007 to 2009, thereby suggesting contagion effects among global real estate markets. The analysis further indicates that the returns of the regional real estate markets that are in close geographic and economic proximities exhibit strong co-movement. In addition, evidence of significantly positive leverage effects in global real estate markets is also determined. The findings have significant implications on global portfolio diversification opportunities and risk management practices.

  7. Hamiltonian model and dynamic analyses for a hydro-turbine governing system with fractional item and time-lag

    NASA Astrophysics Data System (ADS)

    Xu, Beibei; Chen, Diyi; Zhang, Hao; Wang, Feifei; Zhang, Xinguang; Wu, Yonghong

    2017-06-01

    This paper focus on a Hamiltonian mathematical modeling for a hydro-turbine governing system including fractional item and time-lag. With regards to hydraulic pressure servo system, a universal dynamical model is proposed, taking into account the viscoelastic properties and low-temperature impact toughness of constitutive materials as well as the occurrence of time-lag in the signal transmissions. The Hamiltonian model of the hydro-turbine governing system is presented using the method of orthogonal decomposition. Furthermore, a novel Hamiltonian function that provides more detailed energy information is presented, since the choice of the Hamiltonian function is the key issue by putting the whole dynamical system to the theory framework of the generalized Hamiltonian system. From the numerical experiments based on a real large hydropower station, we prove that the Hamiltonian function can describe the energy variation of the hydro-turbine suitably during operation. Moreover, the effect of the fractional α and the time-lag τ on the dynamic variables of the hydro-turbine governing system are explored and their change laws identified, respectively. The physical meaning between fractional calculus and time-lag are also discussed in nature. All of the above theories and numerical results are expected to provide a robust background for the safe operation and control of large hydropower stations.

  8. MicROS-drt: supporting real-time and scalable data distribution in distributed robotic systems.

    PubMed

    Ding, Bo; Wang, Huaimin; Fan, Zedong; Zhang, Pengfei; Liu, Hui

    A primary requirement in distributed robotic software systems is the dissemination of data to all interested collaborative entities in a timely and scalable manner. However, providing such a service in a highly dynamic and resource-limited robotic environment is a challenging task, and existing robot software infrastructure has limitations in this aspect. This paper presents a novel robot software infrastructure, micROS-drt, which supports real-time and scalable data distribution. The solution is based on a loosely coupled data publish-subscribe model with the ability to support various time-related constraints. And to realize this model, a mature data distribution standard, the data distribution service for real-time systems (DDS), is adopted as the foundation of the transport layer of this software infrastructure. By elaborately adapting and encapsulating the capability of the underlying DDS middleware, micROS-drt can meet the requirement of real-time and scalable data distribution in distributed robotic systems. Evaluation results in terms of scalability, latency jitter and transport priority as well as the experiment on real robots validate the effectiveness of this work.

  9. PRAIS: Distributed, real-time knowledge-based systems made easy

    NASA Technical Reports Server (NTRS)

    Goldstein, David G.

    1990-01-01

    This paper discusses an architecture for real-time, distributed (parallel) knowledge-based systems called the Parallel Real-time Artificial Intelligence System (PRAIS). PRAIS strives for transparently parallelizing production (rule-based) systems, even when under real-time constraints. PRAIS accomplishes these goals by incorporating a dynamic task scheduler, operating system extensions for fact handling, and message-passing among multiple copies of CLIPS executing on a virtual blackboard. This distributed knowledge-based system tool uses the portability of CLIPS and common message-passing protocols to operate over a heterogeneous network of processors.

  10. Solar Potential Analysis and Integration of the Time-Dependent Simulation Results for Semantic 3d City Models Using Dynamizers

    NASA Astrophysics Data System (ADS)

    Chaturvedi, K.; Willenborg, B.; Sindram, M.; Kolbe, T. H.

    2017-10-01

    Semantic 3D city models play an important role in solving complex real-world problems and are being adopted by many cities around the world. A wide range of application and simulation scenarios directly benefit from the adoption of international standards such as CityGML. However, most of the simulations involve properties, whose values vary with respect to time, and the current generation semantic 3D city models do not support time-dependent properties explicitly. In this paper, the details of solar potential simulations are provided operating on the CityGML standard, assessing and estimating solar energy production for the roofs and facades of the 3D building objects in different ways. Furthermore, the paper demonstrates how the time-dependent simulation results are better-represented inline within 3D city models utilizing the so-called Dynamizer concept. This concept not only allows representing the simulation results in standardized ways, but also delivers a method to enhance static city models by such dynamic property values making the city models truly dynamic. The dynamizer concept has been implemented as an Application Domain Extension of the CityGML standard within the OGC Future City Pilot Phase 1. The results are given in this paper.

  11. Indirect rotor position sensing in real time for brushless permanent magnet motor drives

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

    Ertugrul, N.; Acarnley, P.P.

    1998-07-01

    This paper describes a modern solution to real-time rotor position estimation of brushless permanent magnet (PM) motor drives. The position estimation scheme, based on flux linkage and line-current estimation, is implemented in real time by using the abc reference frame, and it is tested dynamically. The position estimation model of the test motor, development of hardware, and basic operation of the digital signal processor (DSP) are discussed. The overall position estimation strategy is accomplished with a fast DSP (TMS320C30). The method is a shaft position sensorless method that is applicable to a wide range of excitation types in brushless PMmore » motors without any restriction on the motor model and the current excitation. Both rectangular and sinewave-excited brushless PM motor drives are examined, and the results are given to demonstrate the effectiveness of the method with dynamic loads in closed estimated position loop.« less

  12. Real-Time Monitoring and Prediction of the Pilot Vehicle System (PVS) Closed-Loop Stability

    NASA Astrophysics Data System (ADS)

    Mandal, Tanmay Kumar

    Understanding human control behavior is an important step for improving the safety of future aircraft. Considerable resources are invested during the design phase of an aircraft to ensure that the aircraft has desirable handling qualities. However, human pilots exhibit a wide range of control behaviors that are a function of external stimulus, aircraft dynamics, and human psychological properties (such as workload, stress factor, confidence, and sense of urgency factor). This variability is difficult to address comprehensively during the design phase and may lead to undesirable pilot-aircraft interaction, such as pilot-induced oscillations (PIO). This creates the need to keep track of human pilot performance in real-time to monitor the pilot vehicle system (PVS) stability. This work focused on studying human pilot behavior for the longitudinal axis of a remotely controlled research aircraft and using human-in-the-loop (HuIL) simulations to obtain information about the human controlled system (HCS) stability. The work in this dissertation is divided into two main parts: PIO analysis and human control model parameters estimation. To replicate different flight conditions, this study included time delay and elevator rate limiting phenomena, typical of actuator dynamics during the experiments. To study human control behavior, this study employed the McRuer model for single-input single-output manual compensatory tasks. McRuer model is a lead-lag controller with time delay which has been shown to adequately model manual compensatory tasks. This dissertation presents a novel technique to estimate McRuer model parameters in real-time and associated validation using HuIL simulations to correctly predict HCS stability. The McRuer model parameters were estimated in real-time using a Kalman filter approach. The estimated parameters were then used to analyze the stability of the closed-loop HCS and verify them against the experimental data. Therefore, the main contribution of

  13. Path Flow Estimation Using Time Varying Coefficient State Space Model

    NASA Astrophysics Data System (ADS)

    Jou, Yow-Jen; Lan, Chien-Lun

    2009-08-01

    The dynamic path flow information is very crucial in the field of transportation operation and management, i.e., dynamic traffic assignment, scheduling plan, and signal timing. Time-dependent path information, which is important in many aspects, is nearly impossible to be obtained. Consequently, researchers have been seeking estimation methods for deriving valuable path flow information from less expensive traffic data, primarily link traffic counts of surveillance systems. This investigation considers a path flow estimation problem involving the time varying coefficient state space model, Gibbs sampler, and Kalman filter. Numerical examples with part of a real network of the Taipei Mass Rapid Transit with real O-D matrices is demonstrated to address the accuracy of proposed model. Results of this study show that this time-varying coefficient state space model is very effective in the estimation of path flow compared to time-invariant model.

  14. Parallel processing of real-time dynamic systems simulation on OSCAR (Optimally SCheduled Advanced multiprocessoR)

    NASA Technical Reports Server (NTRS)

    Kasahara, Hironori; Honda, Hiroki; Narita, Seinosuke

    1989-01-01

    Parallel processing of real-time dynamic systems simulation on a multiprocessor system named OSCAR is presented. In the simulation of dynamic systems, generally, the same calculation are repeated every time step. However, we cannot apply to Do-all or the Do-across techniques for parallel processing of the simulation since there exist data dependencies from the end of an iteration to the beginning of the next iteration and furthermore data-input and data-output are required every sampling time period. Therefore, parallelism inside the calculation required for a single time step, or a large basic block which consists of arithmetic assignment statements, must be used. In the proposed method, near fine grain tasks, each of which consists of one or more floating point operations, are generated to extract the parallelism from the calculation and assigned to processors by using optimal static scheduling at compile time in order to reduce large run time overhead caused by the use of near fine grain tasks. The practicality of the scheme is demonstrated on OSCAR (Optimally SCheduled Advanced multiprocessoR) which has been developed to extract advantageous features of static scheduling algorithms to the maximum extent.

  15. Immunity-Based Optimal Estimation Approach for a New Real Time Group Elevator Dynamic Control Application for Energy and Time Saving

    PubMed Central

    Baygin, Mehmet; Karakose, Mehmet

    2013-01-01

    Nowadays, the increasing use of group elevator control systems owing to increasing building heights makes the development of high-performance algorithms necessary in terms of time and energy saving. Although there are many studies in the literature about this topic, they are still not effective enough because they are not able to evaluate all features of system. In this paper, a new approach of immune system-based optimal estimate is studied for dynamic control of group elevator systems. The method is mainly based on estimation of optimal way by optimizing all calls with genetic, immune system and DNA computing algorithms, and it is evaluated with a fuzzy system. The system has a dynamic feature in terms of the situation of calls and the option of the most appropriate algorithm, and it also adaptively works in terms of parameters such as the number of floors and cabins. This new approach which provides both time and energy saving was carried out in real time. The experimental results comparatively demonstrate the effects of method. With dynamic and adaptive control approach in this study carried out, a significant progress on group elevator control systems has been achieved in terms of time and energy efficiency according to traditional methods. PMID:23935433

  16. Designers Workbench: Towards Real-Time Immersive Modeling

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

    Kuester, F; Duchaineau, M A; Hamann, B

    2001-10-03

    This paper introduces the DesignersWorkbench, a semi-immersive virtual environment for two-handed modeling, sculpting and analysis tasks. The paper outlines the fundamental tools, design metaphors and hardware components required for an intuitive real-time modeling system. As companies focus on streamlining productivity to cope with global competition, the migration to computer-aided design (CAD), computer-aided manufacturing (CAM), and computer-aided engineering (CAE) systems has established a new backbone of modern industrial product development. However, traditionally a product design frequently originates from a clay model that, after digitization, forms the basis for the numerical description of CAD primitives. The DesignersWorkbench aims at closing this technologymore » or ''digital gap'' experienced by design and CAD engineers by transforming the classical design paradigm into its filly integrated digital and virtual analog allowing collaborative development in a semi-immersive virtual environment. This project emphasizes two key components from the classical product design cycle: freeform modeling and analysis. In the freeform modeling stage, content creation in the form of two-handed sculpting of arbitrary objects using polygonal, volumetric or mathematically defined primitives is emphasized, whereas the analysis component provides the tools required for pre- and post-processing steps for finite element analysis tasks applied to the created models.« less

  17. Designers workbench: toward real-time immersive modeling

    NASA Astrophysics Data System (ADS)

    Kuester, Falko; Duchaineau, Mark A.; Hamann, Bernd; Joy, Kenneth I.; Ma, Kwan-Liu

    2000-05-01

    This paper introduces the Designers Workbench, a semi- immersive virtual environment for two-handed modeling, sculpting and analysis tasks. The paper outlines the fundamental tools, design metaphors and hardware components required for an intuitive real-time modeling system. As companies focus on streamlining productivity to cope with global competition, the migration to computer-aided design (CAD), computer-aided manufacturing, and computer-aided engineering systems has established a new backbone of modern industrial product development. However, traditionally a product design frequently originates form a clay model that, after digitization, forms the basis for the numerical description of CAD primitives. The Designers Workbench aims at closing this technology or 'digital gap' experienced by design and CAD engineers by transforming the classical design paradigm into its fully integrate digital and virtual analog allowing collaborative development in a semi- immersive virtual environment. This project emphasizes two key components form the classical product design cycle: freeform modeling and analysis. In the freedom modeling stage, content creation in the form of two-handed sculpting of arbitrary objects using polygonal, volumetric or mathematically defined primitives is emphasized, whereas the analysis component provides the tools required for pre- and post-processing steps for finite element analysis tasks applied to the created models.

  18. Real-time metabolome profiling of the metabolic switch between starvation and growth.

    PubMed

    Link, Hannes; Fuhrer, Tobias; Gerosa, Luca; Zamboni, Nicola; Sauer, Uwe

    2015-11-01

    Metabolic systems are often the first networks to respond to environmental changes, and the ability to monitor metabolite dynamics is key for understanding these cellular responses. Because monitoring metabolome changes is experimentally tedious and demanding, dynamic data on time scales from seconds to hours are scarce. Here we describe real-time metabolome profiling by direct injection of living bacteria, yeast or mammalian cells into a high-resolution mass spectrometer, which enables automated monitoring of about 300 compounds in 15-30-s cycles over several hours. We observed accumulation of energetically costly biomass metabolites in Escherichia coli in carbon starvation-induced stationary phase, as well as the rapid use of these metabolites upon growth resumption. By combining real-time metabolome profiling with modeling and inhibitor experiments, we obtained evidence for switch-like feedback inhibition in amino acid biosynthesis and for control of substrate availability through the preferential use of the metabolically cheaper one-step salvaging pathway over costly ten-step de novo purine biosynthesis during growth resumption.

  19. The Slow Developmental Time Course of Real-Time Spoken Word Recognition

    ERIC Educational Resources Information Center

    Rigler, Hannah; Farris-Trimble, Ashley; Greiner, Lea; Walker, Jessica; Tomblin, J. Bruce; McMurray, Bob

    2015-01-01

    This study investigated the developmental time course of spoken word recognition in older children using eye tracking to assess how the real-time processing dynamics of word recognition change over development. We found that 9-year-olds were slower to activate the target words and showed more early competition from competitor words than…

  20. Robust Real-Time Music Transcription with a Compositional Hierarchical Model.

    PubMed

    Pesek, Matevž; Leonardis, Aleš; Marolt, Matija

    2017-01-01

    The paper presents a new compositional hierarchical model for robust music transcription. Its main features are unsupervised learning of a hierarchical representation of input data, transparency, which enables insights into the learned representation, as well as robustness and speed which make it suitable for real-world and real-time use. The model consists of multiple layers, each composed of a number of parts. The hierarchical nature of the model corresponds well to hierarchical structures in music. The parts in lower layers correspond to low-level concepts (e.g. tone partials), while the parts in higher layers combine lower-level representations into more complex concepts (tones, chords). The layers are learned in an unsupervised manner from music signals. Parts in each layer are compositions of parts from previous layers based on statistical co-occurrences as the driving force of the learning process. In the paper, we present the model's structure and compare it to other hierarchical approaches in the field of music information retrieval. We evaluate the model's performance for the multiple fundamental frequency estimation. Finally, we elaborate on extensions of the model towards other music information retrieval tasks.

  1. Real-Time Network Management

    DTIC Science & Technology

    1998-07-01

    Report No. WH97JR00-A002 Sponsored by REAL-TIME NETWORK MANAGEMENT FINAL TECHNICAL REPORT K CD July 1998 CO CO O W O Defense Advanced...Approved for public release; distribution unlimited. t^GquALmmsPEami Report No. WH97JR00-A002 REAL-TIME NETWORK MANAGEMENT Synectics Corporation...2.1.2.1 WAN-class Networks 12 2.1.2.2 IEEE 802.3-class Networks 13 2.2 Task 2 - Object Modeling for Architecture 14 2.2.1 Managed Objects 14 2.2.2

  2. Real-time control data wrangling for development of mathematical control models of technological processes

    NASA Astrophysics Data System (ADS)

    Vasilyeva, N. V.; Koteleva, N. I.; Fedorova, E. R.

    2018-05-01

    The relevance of the research is due to the need to stabilize the composition of the melting products of copper-nickel sulfide raw materials in the Vanyukov furnace. The goal of this research is to identify the most suitable methods for the aggregation of the real time data for the development of a mathematical model for control of the technological process of melting copper-nickel sulfide raw materials in the Vanyukov furnace. Statistical methods of analyzing the historical data of the real technological object and the correlation analysis of process parameters are described. Factors that exert the greatest influence on the main output parameter (copper content in matte) and ensure the physical-chemical transformations are revealed. An approach to the processing of the real time data for the development of a mathematical model for control of the melting process is proposed. The stages of processing the real time information are considered. The adopted methodology for the aggregation of data suitable for the development of a control model for the technological process of melting copper-nickel sulfide raw materials in the Vanyukov furnace allows us to interpret the obtained results for their further practical application.

  3. Designing Real-Time Systems in Ada (Trademark).

    DTIC Science & Technology

    1986-01-01

    e a. T * .K Ada .e 6 4J (FINAL REPORT) Real - Time Systems in Ada* Abstract Real-time software differs from other kinds of software in the sense that it...1-2 1.2.2 Functional Focus ...... ................ 1-2 1.3 ROLE OF ADA IN REAL - TIME SYSTEMS DESIGN. ..... 1-3 1.4 SCOPE OF THIS...MODELS OF REAL TIME SYSTEMS 8.1 REQUIREMENTS FOR TEMPORAL BEHAVIOR ANALYSIS . 8-1 8.2 METHODS OF TEMPORAL BEHAVIOR ANALYSIS.... ....... 8-4 8.3

  4. Real Time Optima Tracking Using Harvesting Models of the Genetic Algorithm

    NASA Technical Reports Server (NTRS)

    Baskaran, Subbiah; Noever, D.

    1999-01-01

    Tracking optima in real time propulsion control, particularly for non-stationary optimization problems is a challenging task. Several approaches have been put forward for such a study including the numerical method called the genetic algorithm. In brief, this approach is built upon Darwinian-style competition between numerical alternatives displayed in the form of binary strings, or by analogy to 'pseudogenes'. Breeding of improved solution is an often cited parallel to natural selection in.evolutionary or soft computing. In this report we present our results of applying a novel model of a genetic algorithm for tracking optima in propulsion engineering and in real time control. We specialize the algorithm to mission profiling and planning optimizations, both to select reduced propulsion needs through trajectory planning and to explore time or fuel conservation strategies.

  5. X-ray absorption in insulators with non-Hermitian real-time time-dependent density functional theory.

    PubMed

    Fernando, Ranelka G; Balhoff, Mary C; Lopata, Kenneth

    2015-02-10

    Non-Hermitian real-time time-dependent density functional theory was used to compute the Si L-edge X-ray absorption spectrum of α-quartz using an embedded finite cluster model and atom-centered basis sets. Using tuned range-separated functionals and molecular orbital-based imaginary absorbing potentials, the excited states spanning the pre-edge to ∼20 eV above the ionization edge were obtained in good agreement with experimental data. This approach is generalizable to TDDFT studies of core-level spectroscopy and dynamics in a wide range of materials.

  6. Real Time Revisited

    NASA Astrophysics Data System (ADS)

    Allen, Phillip G.

    1985-12-01

    The call for abolishing photo reconnaissance in favor of real time is once more being heard. Ten years ago the same cries were being heard with the introduction of the Charge Coupled Device (CCD). The real time system problems that existed then and stopped real time proliferation have not been solved. The lack of an organized program by either DoD or industry has hampered any efforts to solve the problems, and as such, very little has happened in real time in the last ten years. Real time is not a replacement for photo, just as photo is not a replacement for infra-red or radar. Operational real time sensors can be designed only after their role has been defined and improvements made to the weak links in the system. Plodding ahead on a real time reconnaissance suite without benefit of evaluation of utility will allow this same paper to be used ten years from now.

  7. On Using the Weimer Statistical Model for Real-Time Ionospheric Specifications and Forecasts

    NASA Astrophysics Data System (ADS)

    Bekerat, H. A.; Schunk, R. W.; Scherliess, L.

    2002-12-01

    The Weimer statistical model (Weimer, 2001) for the high-latitude convection pattern was tested with regard to its ability to produce real-time convection patterns. This work is being conducted under the polar section of GAIM (Global Assimilation of Ionospheric Measurements). The method adopted involves the comparison of the cross-track ion drift velocities measured by DMSP satellites with those calculated from the Weimer model. Starting with a Weimer pattern obtained using real-time IMF and solar wind data at the time of a DMSP satellite pass in the high-latitude ionosphere, the cross-track ion drift velocities along the DMSP track were calculated from the Weimer convection model and compared to those measured by the DMSP satellite. Then, in order to improve the agreement between the measurement and the model, two of the input parameters to the model, the IMF clock-angle and the solar wind speed, were varied to get the pattern that gives the best agreement with the DMSP satellite measurements. Four months of data (March, July, September, and December 1998) were used to test the Weimer model. The result shows that the agreement between the measurement and the Weimer model is improved by using this procedure. The Weimer model is good in a statistical sense, it was able to produce the large-scale structure in most cases. However, it is not good enough to be used for real-time ionospheric specifications and forecasts because it failed to produce a lot of the mesoscale structure measured along most DMSP satellite passes. Reference Weimer, D. R., J. Geophys. Res., 106, 407,2001

  8. Using Indirect Turbulence Measurements for Real-Time Parameter Estimation in Turbulent Air

    NASA Technical Reports Server (NTRS)

    Martos, Borja; Morelli, Eugene A.

    2012-01-01

    The use of indirect turbulence measurements for real-time estimation of parameters in a linear longitudinal dynamics model in atmospheric turbulence was studied. It is shown that measuring the atmospheric turbulence makes it possible to treat the turbulence as a measured explanatory variable in the parameter estimation problem. Commercial off-the-shelf sensors were researched and evaluated, then compared to air data booms. Sources of colored noise in the explanatory variables resulting from typical turbulence measurement techniques were identified and studied. A major source of colored noise in the explanatory variables was identified as frequency dependent upwash and time delay. The resulting upwash and time delay corrections were analyzed and compared to previous time shift dynamic modeling research. Simulation data as well as flight test data in atmospheric turbulence were used to verify the time delay behavior. Recommendations are given for follow on flight research and instrumentation.

  9. Real-time optical measurement of the dynamic body surface for use in guided radiotherapy

    NASA Astrophysics Data System (ADS)

    Price, G. J.; Parkhurst, J. M.; Sharrock, P. J.; Moore, C. J.

    2012-01-01

    Optical measurements are increasingly used in radiotherapy. In this paper we present, in detail, the design and implementation of a multi-channel optical system optimized for fast, high spatial resolution, dynamic body surface measurement in guided therapy. We include all algorithmic modifications and calibration procedures required to create a robust, practical system for clinical use. Comprehensive static and dynamic phantom validation measurements in the radiotherapy treatment room show: conformance with simultaneously measured cone beam CT data to within 1 mm over 62% ± 8% of the surface and 2 mm over 90% ± 3%; agreement with the measured radius of a precision geometrical phantom to within 1 mm; and true real-time performance with image capture through to surface display at 23 Hz. An example patient dataset is additionally included, indicating similar performance in the clinic.

  10. Real-time Experiment Interface for Biological Control Applications

    PubMed Central

    Lin, Risa J.; Bettencourt, Jonathan; White, John A.; Christini, David J.; Butera, Robert J.

    2013-01-01

    The Real-time Experiment Interface (RTXI) is a fast and versatile real-time biological experimentation system based on Real-Time Linux. RTXI is open source and free, can be used with an extensive range of experimentation hardware, and can be run on Linux or Windows computers (when using the Live CD). RTXI is currently used extensively for two experiment types: dynamic patch clamp and closed-loop stimulation pattern control in neural and cardiac single cell electrophysiology. RTXI includes standard plug-ins for implementing commonly used electrophysiology protocols with synchronized stimulation, event detection, and online analysis. These and other user-contributed plug-ins can be found on the website (http://www.rtxi.org). PMID:21096883

  11. Real time eye tracking using Kalman extended spatio-temporal context learning

    NASA Astrophysics Data System (ADS)

    Munir, Farzeen; Minhas, Fayyaz ul Amir Asfar; Jalil, Abdul; Jeon, Moongu

    2017-06-01

    Real time eye tracking has numerous applications in human computer interaction such as a mouse cursor control in a computer system. It is useful for persons with muscular or motion impairments. However, tracking the movement of the eye is complicated by occlusion due to blinking, head movement, screen glare, rapid eye movements, etc. In this work, we present the algorithmic and construction details of a real time eye tracking system. Our proposed system is an extension of Spatio-Temporal context learning through Kalman Filtering. Spatio-Temporal Context Learning offers state of the art accuracy in general object tracking but its performance suffers due to object occlusion. Addition of the Kalman filter allows the proposed method to model the dynamics of the motion of the eye and provide robust eye tracking in cases of occlusion. We demonstrate the effectiveness of this tracking technique by controlling the computer cursor in real time by eye movements.

  12. Real-Time Model and Simulation Architecture for Half- and Full-Bridge Modular Multilevel Converters

    NASA Astrophysics Data System (ADS)

    Ashourloo, Mojtaba

    This work presents an equivalent model and simulation architecture for real-time electromagnetic transient analysis of either half-bridge or full-bridge modular multilevel converter (MMC) with 400 sub-modules (SMs) per arm. The proposed CPU/FPGA-based architecture is optimized for the parallel implementation of the presented MMC model on the FPGA and is beneficiary of a high-throughput floating-point computational engine. The developed real-time simulation architecture is capable of simulating MMCs with 400 SMs per arm at 825 nanoseconds. To address the difficulties of the sorting process implementation, a modified Odd-Even Bubble sorting is presented in this work. The comparison of the results under various test scenarios reveals that the proposed real-time simulator is representing the system responses in the same way of its corresponding off-line counterpart obtained from the PSCAD/EMTDC program.

  13. Interdisciplinary Modeling and Dynamics of Archipelago Straits

    DTIC Science & Technology

    2009-01-01

    modeling, tidal modeling and multi-dynamics nested domains and non-hydrostatic modeling WORK COMPLETED Realistic Multiscale Simulations, Real-time...six state variables (chlorophyll, nitrate , ammonium, detritus, phytoplankton, and zooplankton) were needed to initialize simulations. Using biological...parameters from literature, climatology from World Ocean Atlas data for nitrate and chlorophyll profiles extracted from satellite data, a first

  14. LANL* V1.0: a radiation belt drift shell model suitable for real-time and reanalysis applications

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

    Koller, Josep; Reeves, Geoffrey D; Friedel, Reiner H W

    2008-01-01

    Space weather modeling, forecasts, and predictions, especially for the radiation belts in the inner magnetosphere, require detailed information about the Earth's magnetic field. Results depend on the magnetic field model and the L* (pron. L-star) values which are used to describe particle drift shells. Space wather models require integrating particle motions along trajectories that encircle the Earth. Numerical integration typically takes on the order of 10{sup 5} calls to a magnetic field model which makes the L* calculations very slow, in particular when using a dynamic and more accurate magnetic field model. Researchers currently tend to pick simplistic models overmore » more accurate ones but also risking large inaccuracies and even wrong conclusions. For example, magnetic field models affect the calculation of electron phase space density by applying adiabatic invariants including the drift shell value L*. We present here a new method using a surrogate model based on a neural network technique to replace the time consuming L* calculations made with modern magnetic field models. The advantage of surrogate models (or meta-models) is that they can compute the same output in a fraction of the time while adding only a marginal error. Our drift shell model LANL* (Los Alamos National Lab L-star) is based on L* calculation using the TSK03 model. The surrogate model has currently been tested and validated only for geosynchronous regions but the method is generally applicable to any satellite orbit. Computations with the new model are several million times faster compared to the standard integration method while adding less than 1% error. Currently, real-time applications for forecasting and even nowcasting inner magnetospheric space weather is limited partly due to the long computing time of accurate L* values. Without them, real-time applications are limited in accuracy. Reanalysis application of past conditions in the inner magnetosphere are used to understand

  15. Evaluation on real-time dynamic performance of BDS in PPP, RTK, and INS tightly aided modes

    NASA Astrophysics Data System (ADS)

    Gao, Zhouzheng; Li, Tuan; Zhang, Hongping; Ge, Maorong; Schuh, Harald

    2018-05-01

    Since China's BeiDou satellite navigation system (BDS) began to provide regional navigation service for Asia-Pacific region after 2012, more new generation BDS satellites have been launched to further expand BDS's coverage to be global. In this contribution, precise positioning models based on BDS and the corresponding mathematical algorithms are presented in detail. Then, an evaluation on BDS's real-time dynamic positioning and navigation performance is presented in Precise Point Positioning (PPP), Real-time Kinematic (RTK), Inertial Navigation System (INS) tightly aided PPP and RTK modes by processing a set of land-borne vehicle experiment data. Results indicate that BDS positioning Root Mean Square (RMS) in north, east, and vertical components are 2.0, 2.7, and 7.6 cm in RTK mode and 7.8, 14.7, and 24.8 cm in PPP mode, which are close to GPS positioning accuracy. Meanwhile, with the help of INS, about 38.8%, 67.5%, and 66.5% improvements can be obtained by using PPP/INS tight-integration mode. Such enhancements in RTK/INS tight-integration mode are 14.1%, 34.0%, and 41.9%. Moreover, the accuracy of velocimetry and attitude determination can be improved to be better than 1 cm/s and 0.1°, respectively. Besides, the continuity and reliability of BDS in both PPP and RTK modes can also be ameliorated significantly by INS during satellite signal missing periods.

  16. Real time tracking by LOPF algorithm with mixture model

    NASA Astrophysics Data System (ADS)

    Meng, Bo; Zhu, Ming; Han, Guangliang; Wu, Zhiguo

    2007-11-01

    A new particle filter-the Local Optimum Particle Filter (LOPF) algorithm is presented for tracking object accurately and steadily in visual sequences in real time which is a challenge task in computer vision field. In order to using the particles efficiently, we first use Sobel algorithm to extract the profile of the object. Then, we employ a new Local Optimum algorithm to auto-initialize some certain number of particles from these edge points as centre of the particles. The main advantage we do this in stead of selecting particles randomly in conventional particle filter is that we can pay more attentions on these more important optimum candidates and reduce the unnecessary calculation on those negligible ones, in addition we can overcome the conventional degeneracy phenomenon in a way and decrease the computational costs. Otherwise, the threshold is a key factor that affecting the results very much. So here we adapt an adaptive threshold choosing method to get the optimal Sobel result. The dissimilarities between the target model and the target candidates are expressed by a metric derived from the Bhattacharyya coefficient. Here, we use both the counter cue to select the particles and the color cur to describe the targets as the mixture target model. The effectiveness of our scheme is demonstrated by real visual tracking experiments. Results from simulations and experiments with real video data show the improved performance of the proposed algorithm when compared with that of the standard particle filter. The superior performance is evident when the target encountering the occlusion in real video where the standard particle filter usually fails.

  17. Data-adaptive Harmonic Decomposition and Real-time Prediction of Arctic Sea Ice Extent

    NASA Astrophysics Data System (ADS)

    Kondrashov, Dmitri; Chekroun, Mickael; Ghil, Michael

    2017-04-01

    Decline in the Arctic sea ice extent (SIE) has profound socio-economic implications and is a focus of active scientific research. Of particular interest is prediction of SIE on subseasonal time scales, i.e. from early summer into fall, when sea ice coverage in Arctic reaches its minimum. However, subseasonal forecasting of SIE is very challenging due to the high variability of ocean and atmosphere over Arctic in summer, as well as shortness of observational data and inadequacies of the physics-based models to simulate sea-ice dynamics. The Sea Ice Outlook (SIO) by Sea Ice Prediction Network (SIPN, http://www.arcus.org/sipn) is a collaborative effort to facilitate and improve subseasonal prediction of September SIE by physics-based and data-driven statistical models. Data-adaptive Harmonic Decomposition (DAH) and Multilayer Stuart-Landau Models (MSLM) techniques [Chekroun and Kondrashov, 2017], have been successfully applied to the nonlinear stochastic modeling, as well as retrospective and real-time forecasting of Multisensor Analyzed Sea Ice Extent (MASIE) dataset in key four Arctic regions. In particular, DAH-MSLM predictions outperformed most statistical models and physics-based models in real-time 2016 SIO submissions. The key success factors are associated with DAH ability to disentangle complex regional dynamics of MASIE by data-adaptive harmonic spatio-temporal patterns that reduce the data-driven modeling effort to elemental MSLMs stacked per frequency with fixed and small number of model coefficients to estimate.

  18. Real time optimal guidance of low-thrust spacecraft: an application of nonlinear model predictive control.

    PubMed

    Arrieta-Camacho, Juan José; Biegler, Lorenz T

    2005-12-01

    Real time optimal guidance is considered for a class of low thrust spacecraft. In particular, nonlinear model predictive control (NMPC) is utilized for computing the optimal control actions required to transfer a spacecraft from a low Earth orbit to a mission orbit. The NMPC methodology presented is able to cope with unmodeled disturbances. The dynamics of the transfer are modeled using a set of modified equinoctial elements because they do not exhibit singularities for zero inclination and zero eccentricity. The idea behind NMPC is the repeated solution of optimal control problems; at each time step, a new control action is computed. The optimal control problem is solved using a direct method-fully discretizing the equations of motion. The large scale nonlinear program resulting from the discretization procedure is solved using IPOPT--a primal-dual interior point algorithm. Stability and robustness characteristics of the NMPC algorithm are reviewed. A numerical example is presented that encourages further development of the proposed methodology: the transfer from low-Earth orbit to a molniya orbit.

  19. On Real-Time Systems Using Local Area Networks.

    DTIC Science & Technology

    1987-07-01

    87-35 July, 1987 CS-TR-1892 On Real - Time Systems Using Local Area Networks*I VShem-Tov Levi Department of Computer Science Satish K. Tripathit...1892 On Real - Time Systems Using Local Area Networks* Shem-Tov Levi Department of Computer Science Satish K. Tripathit Department of Computer Science...constraints and the clock systems that feed the time to real - time systems . A model for real-time system based on LAN communication is presented in

  20. Global, real-time ionosphere specification for end-user communication and navigation products

    NASA Astrophysics Data System (ADS)

    Tobiska, W.; Carlson, H. C.; Schunk, R. W.; Thompson, D. C.; Sojka, J. J.; Scherliess, L.; Zhu, L.; Gardner, L. C.

    2010-12-01

    Space weather’s effects upon the near-Earth environment are due to dynamic changes in the energy transfer processes from the Sun’s photons, particles, and fields. Of the space environment domains that are affected by space weather, the ionosphere is the key region that affects communication and navigation systems. The Utah State University (USU) Space Weather Center (SWC) is a developer and producer of commercial space weather applications. A key system-level component for providing timely information about the effects of space weather is the Global Assimilation of Ionospheric Measurements (GAIM) system. GAIM, operated by SWC, improves real-time communication and navigation systems by continuously ingesting up to 10,000 slant TEC measurements every 15-minutes from approximately 500 stations. Using a Kalman filter, the background output from the physics-based Ionosphere Forecast Model (IFM) is adjusted to more accurately represent the actual ionosphere. An improved ionosphere leads to more useful derivative products. For example, SWC runs operational code, using GAIM, to calculate and report the global radio high frequency (HF) signal strengths for 24 world cities. This product is updated every 15 minutes at http://spaceweather.usu.edu and used by amateur radio operators. SWC also developed and provides through Apple iTunes the widely used real-time space weather iPhone app called SpaceWx for public space weather education. SpaceWx displays the real-time solar, heliosphere, magnetosphere, thermosphere, and ionosphere drivers to changes in the total electron content, for example. This smart phone app is tip of the “iceberg” of automated systems that provide space weather data; it permits instant understanding of the environment surrounding Earth as it dynamically changes. SpaceWx depends upon a distributed network that connects satellite and ground-based data streams with algorithms to quickly process the measurements into geophysical data, incorporate those

  1. Real-time micro-modelling of city evacuations

    NASA Astrophysics Data System (ADS)

    Löhner, Rainald; Haug, Eberhard; Zinggerling, Claudio; Oñate, Eugenio

    2018-01-01

    A methodology to integrate geographical information system (GIS) data with large-scale pedestrian simulations has been developed. Advances in automatic data acquisition and archiving from GIS databases, automatic input for pedestrian simulations, as well as scalable pedestrian simulation tools have made it possible to simulate pedestrians at the individual level for complete cities in real time. An example that simulates the evacuation of the city of Barcelona demonstrates that this is now possible. This is the first step towards a fully integrated crowd prediction and management tool that takes into account not only data gathered in real time from cameras, cell phones or other sensors, but also merges these with advanced simulation tools to predict the future state of the crowd.

  2. Real-Time MENTAT programming language and architecture

    NASA Technical Reports Server (NTRS)

    Grimshaw, Andrew S.; Silberman, Ami; Liu, Jane W. S.

    1989-01-01

    Real-time MENTAT, a programming environment designed to simplify the task of programming real-time applications in distributed and parallel environments, is described. It is based on the same data-driven computation model and object-oriented programming paradigm as MENTAT. It provides an easy-to-use mechanism to exploit parallelism, language constructs for the expression and enforcement of timing constraints, and run-time support for scheduling and exciting real-time programs. The real-time MENTAT programming language is an extended C++. The extensions are added to facilitate automatic detection of data flow and generation of data flow graphs, to express the timing constraints of individual granules of computation, and to provide scheduling directives for the runtime system. A high-level view of the real-time MENTAT system architecture and programming language constructs is provided.

  3. REAL-TIME MODELING OF MOTOR VEHICLE EMISSIONS FOR ESTIMATING HUMAN EXPOSURES NEAR ROADWAYS

    EPA Science Inventory

    The United States Environmental Protection Agency's (EPA) National Exposure Research Laboratory is developing a real-time model of motor vehicle emissions to improve the methodology for modeling human exposure to motor vehicle emissions. The overall project goal is to develop ...

  4. Continuous piecewise-linear, reduced-order electrochemical model for lithium-ion batteries in real-time applications

    NASA Astrophysics Data System (ADS)

    Farag, Mohammed; Fleckenstein, Matthias; Habibi, Saeid

    2017-02-01

    Model-order reduction and minimization of the CPU run-time while maintaining the model accuracy are critical requirements for real-time implementation of lithium-ion electrochemical battery models. In this paper, an isothermal, continuous, piecewise-linear, electrode-average model is developed by using an optimal knot placement technique. The proposed model reduces the univariate nonlinear function of the electrode's open circuit potential dependence on the state of charge to continuous piecewise regions. The parameterization experiments were chosen to provide a trade-off between extensive experimental characterization techniques and purely identifying all parameters using optimization techniques. The model is then parameterized in each continuous, piecewise-linear, region. Applying the proposed technique cuts down the CPU run-time by around 20%, compared to the reduced-order, electrode-average model. Finally, the model validation against real-time driving profiles (FTP-72, WLTP) demonstrates the ability of the model to predict the cell voltage accurately with less than 2% error.

  5. Real-time co-simulation of adjustable-speed pumped storage hydro for transient stability analysis

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

    Mohanpurkar, Manish; Ouroua, Abdelhamid; Hovsapian, Rob

    Pumped storage hydro (PSH) based generation of electricity is a proven grid level storage technique. A new configuration i.e., adjustable speed PSH (AS-PSH) power plant is modeled and discussed in this paper. Hydrodynamic models are created using partial differential equations and the governor topology adopted from an existing, operational AS-PSH unit. Physics-based simulation of both hydrodynamics and power system dynamics has been studied individually in the past. This article demonstrates a co-simulation of an AS-PSH unit between penstock hydrodynamics and power system events in a real-time environment. Co-simulation provides an insight into the dynamic and transient operation of AS-PSH connectedmore » to a bulk power system network. The two modes of AS-PSH operation presented in this paper are turbine and pump modes. A general philosophy of operating in turbine mode is prevalent in the field when the prices of electricity are high and in the pumping mode when prices are low. However, recently there is renewed interest in operating PSH to also provide ancillary services. A real-time co-simulation at sub-second regime of AS-PSH connected to the IEEE 14 bus test system is performed using digital real-time simulator and the results are discussed.« less

  6. Real-time co-simulation of adjustable-speed pumped storage hydro for transient stability analysis

    DOE PAGES

    Mohanpurkar, Manish; Ouroua, Abdelhamid; Hovsapian, Rob; ...

    2017-09-12

    Pumped storage hydro (PSH) based generation of electricity is a proven grid level storage technique. A new configuration i.e., adjustable speed PSH (AS-PSH) power plant is modeled and discussed in this paper. Hydrodynamic models are created using partial differential equations and the governor topology adopted from an existing, operational AS-PSH unit. Physics-based simulation of both hydrodynamics and power system dynamics has been studied individually in the past. This article demonstrates a co-simulation of an AS-PSH unit between penstock hydrodynamics and power system events in a real-time environment. Co-simulation provides an insight into the dynamic and transient operation of AS-PSH connectedmore » to a bulk power system network. The two modes of AS-PSH operation presented in this paper are turbine and pump modes. A general philosophy of operating in turbine mode is prevalent in the field when the prices of electricity are high and in the pumping mode when prices are low. However, recently there is renewed interest in operating PSH to also provide ancillary services. A real-time co-simulation at sub-second regime of AS-PSH connected to the IEEE 14 bus test system is performed using digital real-time simulator and the results are discussed.« less

  7. Dynamic performances analysis of a real vehicle driving

    NASA Astrophysics Data System (ADS)

    Abdullah, M. A.; Jamil, J. F.; Salim, M. A.

    2015-12-01

    Vehicle dynamic is the effects of movement of a vehicle generated from the acceleration, braking, ride and handling activities. The dynamic behaviours are determined by the forces from tire, gravity and aerodynamic which acting on the vehicle. This paper emphasizes the analysis of vehicle dynamic performance of a real vehicle. Real driving experiment on the vehicle is conducted to determine the effect of vehicle based on roll, pitch, and yaw, longitudinal, lateral and vertical acceleration. The experiment is done using the accelerometer to record the reading of the vehicle dynamic performance when the vehicle is driven on the road. The experiment starts with weighing a car model to get the center of gravity (COG) to place the accelerometer sensor for data acquisition (DAQ). The COG of the vehicle is determined by using the weight of the vehicle. A rural route is set to launch the experiment and the road conditions are determined for the test. The dynamic performance of the vehicle are depends on the road conditions and driving maneuver. The stability of a vehicle can be controlled by the dynamic performance analysis.

  8. Real time animation of space plasma phenomena

    NASA Technical Reports Server (NTRS)

    Jordan, K. F.; Greenstadt, E. W.

    1987-01-01

    In pursuit of real time animation of computer simulated space plasma phenomena, the code was rewritten for the Massively Parallel Processor (MPP). The program creates a dynamic representation of the global bowshock which is based on actual spacecraft data and designed for three dimensional graphic output. This output consists of time slice sequences which make up the frames of the animation. With the MPP, 16384, 512 or 4 frames can be calculated simultaneously depending upon which characteristic is being computed. The run time was greatly reduced which promotes the rapid sequence of images and makes real time animation a foreseeable goal. The addition of more complex phenomenology in the constructed computer images is now possible and work proceeds to generate these images.

  9. Inferential modeling and predictive feedback control in real-time motion compensation using the treatment couch during radiotherapy

    NASA Astrophysics Data System (ADS)

    Qiu, Peng; D'Souza, Warren D.; McAvoy, Thomas J.; Liu, K. J. Ray

    2007-09-01

    Tumor motion induced by respiration presents a challenge to the reliable delivery of conformal radiation treatments. Real-time motion compensation represents the technologically most challenging clinical solution but has the potential to overcome the limitations of existing methods. The performance of a real-time couch-based motion compensation system is mainly dependent on two aspects: the ability to infer the internal anatomical position and the performance of the feedback control system. In this paper, we propose two novel methods for the two aspects respectively, and then combine the proposed methods into one system. To accurately estimate the internal tumor position, we present partial-least squares (PLS) regression to predict the position of the diaphragm using skin-based motion surrogates. Four radio-opaque markers were placed on the abdomen of patients who underwent fluoroscopic imaging of the diaphragm. The coordinates of the markers served as input variables and the position of the diaphragm served as the output variable. PLS resulted in lower prediction errors compared with standard multiple linear regression (MLR). The performance of the feedback control system depends on the system dynamics and dead time (delay between the initiation and execution of the control action). While the dynamics of the system can be inverted in a feedback control system, the dead time cannot be inverted. To overcome the dead time of the system, we propose a predictive feedback control system by incorporating forward prediction using least-mean-square (LMS) and recursive least square (RLS) filtering into the couch-based control system. Motion data were obtained using a skin-based marker. The proposed predictive feedback control system was benchmarked against pure feedback control (no forward prediction) and resulted in a significant performance gain. Finally, we combined the PLS inference model and the predictive feedback control to evaluate the overall performance of the

  10. Monitoring of Viral Induced Cell Death Using Real Time Cell Analysis

    DTIC Science & Technology

    2016-11-01

    studies have shown that real- time cell analysis (RTCA) platforms such as the xCELLigence can be used to gather quantitative measurements of viral...Teng, Z., Kuang, X., Wang, J., Zhang, X. Real- time cell analysis – A new method for dynamic, quantitative measurement of infectious viruses and...cytopathogenicity. A) Real- time monitoring of BSR cells infected with a 1:10 dilution series of Gan Gan virus. The curve is an average of eight

  11. Computational Modeling and Real-Time Control of Patient-Specific Laser Treatment of Cancer

    PubMed Central

    Fuentes, D.; Oden, J. T.; Diller, K. R.; Hazle, J. D.; Elliott, A.; Shetty, A.; Stafford, R. J.

    2014-01-01

    An adaptive feedback control system is presented which employs a computational model of bioheat transfer in living tissue to guide, in real-time, laser treatments of prostate cancer monitored by magnetic resonance thermal imaging (MRTI). The system is built on what can be referred to as cyberinfrastructure - a complex structure of high-speed network, large-scale parallel computing devices, laser optics, imaging, visualizations, inverse-analysis algorithms, mesh generation, and control systems that guide laser therapy to optimally control the ablation of cancerous tissue. The computational system has been successfully tested on in-vivo, canine prostate. Over the course of an 18 minute laser induced thermal therapy (LITT) performed at M.D. Anderson Cancer Center (MDACC) in Houston, Texas, the computational models were calibrated to intra-operative real time thermal imaging treatment data and the calibrated models controlled the bioheat transfer to within 5°C of the predetermined treatment plan. The computational arena is in Austin, Texas and managed at the Institute for Computational Engineering and Sciences (ICES). The system is designed to control the bioheat transfer remotely while simultaneously providing real-time remote visualization of the on-going treatment. Post operative histology of the canine prostate reveal that the damage region was within the targeted 1.2cm diameter treatment objective. PMID:19148754

  12. Computational modeling and real-time control of patient-specific laser treatment of cancer.

    PubMed

    Fuentes, D; Oden, J T; Diller, K R; Hazle, J D; Elliott, A; Shetty, A; Stafford, R J

    2009-04-01

    An adaptive feedback control system is presented which employs a computational model of bioheat transfer in living tissue to guide, in real-time, laser treatments of prostate cancer monitored by magnetic resonance thermal imaging. The system is built on what can be referred to as cyberinfrastructure-a complex structure of high-speed network, large-scale parallel computing devices, laser optics, imaging, visualizations, inverse-analysis algorithms, mesh generation, and control systems that guide laser therapy to optimally control the ablation of cancerous tissue. The computational system has been successfully tested on in vivo, canine prostate. Over the course of an 18 min laser-induced thermal therapy performed at M.D. Anderson Cancer Center (MDACC) in Houston, Texas, the computational models were calibrated to intra-operative real-time thermal imaging treatment data and the calibrated models controlled the bioheat transfer to within 5 degrees C of the predetermined treatment plan. The computational arena is in Austin, Texas and managed at the Institute for Computational Engineering and Sciences (ICES). The system is designed to control the bioheat transfer remotely while simultaneously providing real-time remote visualization of the on-going treatment. Post-operative histology of the canine prostate reveal that the damage region was within the targeted 1.2 cm diameter treatment objective.

  13. Fast interactive real-time volume rendering of real-time three-dimensional echocardiography: an implementation for low-end computers

    NASA Technical Reports Server (NTRS)

    Saracino, G.; Greenberg, N. L.; Shiota, T.; Corsi, C.; Lamberti, C.; Thomas, J. D.

    2002-01-01

    Real-time three-dimensional echocardiography (RT3DE) is an innovative cardiac imaging modality. However, partly due to lack of user-friendly software, RT3DE has not been widely accepted as a clinical tool. The object of this study was to develop and implement a fast and interactive volume renderer of RT3DE datasets designed for a clinical environment where speed and simplicity are not secondary to accuracy. Thirty-six patients (20 regurgitation, 8 normal, 8 cardiomyopathy) were imaged using RT3DE. Using our newly developed software, all 3D data sets were rendered in real-time throughout the cardiac cycle and assessment of cardiac function and pathology was performed for each case. The real-time interactive volume visualization system is user friendly and instantly provides consistent and reliable 3D images without expensive workstations or dedicated hardware. We believe that this novel tool can be used clinically for dynamic visualization of cardiac anatomy.

  14. Hard Real-Time: C++ Versus RTSJ

    NASA Technical Reports Server (NTRS)

    Dvorak, Daniel L.; Reinholtz, William K.

    2004-01-01

    In the domain of hard real-time systems, which language is better: C++ or the Real-Time Specification for Java (RTSJ)? Although ordinary Java provides a more productive programming environment than C++ due to its automatic memory management, that benefit does not apply to RTSJ when using NoHeapRealtimeThread and non-heap memory areas. As a result, RTSJ programmers must manage non-heap memory explicitly. While that's not a deterrent for veteran real-time programmers-where explicit memory management is common-the lack of certain language features in RTSJ (and Java) makes that manual memory management harder to accomplish safely than in C++. This paper illustrates the problem for practitioners in the context of moving data and managing memory in a real-time producer/consumer pattern. The relative ease of implementation and safety of the C++ programming model suggests that RTSJ has a struggle ahead in the domain of hard real-time applications, despite its other attractive features.

  15. Dynamic vehicle routing with time windows in theory and practice.

    PubMed

    Yang, Zhiwei; van Osta, Jan-Paul; van Veen, Barry; van Krevelen, Rick; van Klaveren, Richard; Stam, Andries; Kok, Joost; Bäck, Thomas; Emmerich, Michael

    2017-01-01

    The vehicle routing problem is a classical combinatorial optimization problem. This work is about a variant of the vehicle routing problem with dynamically changing orders and time windows. In real-world applications often the demands change during operation time. New orders occur and others are canceled. In this case new schedules need to be generated on-the-fly. Online optimization algorithms for dynamical vehicle routing address this problem but so far they do not consider time windows. Moreover, to match the scenarios found in real-world problems adaptations of benchmarks are required. In this paper, a practical problem is modeled based on the procedure of daily routing of a delivery company. New orders by customers are introduced dynamically during the working day and need to be integrated into the schedule. A multiple ant colony algorithm combined with powerful local search procedures is proposed to solve the dynamic vehicle routing problem with time windows. The performance is tested on a new benchmark based on simulations of a working day. The problems are taken from Solomon's benchmarks but a certain percentage of the orders are only revealed to the algorithm during operation time. Different versions of the MACS algorithm are tested and a high performing variant is identified. Finally, the algorithm is tested in situ: In a field study, the algorithm schedules a fleet of cars for a surveillance company. We compare the performance of the algorithm to that of the procedure used by the company and we summarize insights gained from the implementation of the real-world study. The results show that the multiple ant colony algorithm can get a much better solution on the academic benchmark problem and also can be integrated in a real-world environment.

  16. Crystallization Dynamics of Organolead Halide Perovskite by Real-Time X-ray Diffraction.

    PubMed

    Miyadera, Tetsuhiko; Shibata, Yosei; Koganezawa, Tomoyuki; Murakami, Takurou N; Sugita, Takeshi; Tanigaki, Nobutaka; Chikamatsu, Masayuki

    2015-08-12

    We analyzed the crystallization process of the CH3NH3PbI3 perovskite by observing real-time X-ray diffraction immediately after combining a PbI2 thin film with a CH3NH3I solution. A detailed analysis of the transformation kinetics demonstrated the fractal diffusion of the CH3NH3I solution into the PbI2 film. Moreover, the perovskite crystal was found to be initially oriented based on the PbI2 crystal orientation but to gradually transition to a random orientation. The fluctuating characteristics of the crystallization process of perovskites, such as fractal penetration and orientational transformation, should be controlled to allow the fabrication of high-quality perovskite crystals. The characteristic reaction dynamics observed in this study should assist in establishing reproducible fabrication processes for perovskite solar cells.

  17. Velocity-gauge real-time TDDFT within a numerical atomic orbital basis set

    NASA Astrophysics Data System (ADS)

    Pemmaraju, C. D.; Vila, F. D.; Kas, J. J.; Sato, S. A.; Rehr, J. J.; Yabana, K.; Prendergast, David

    2018-05-01

    The interaction of laser fields with solid-state systems can be modeled efficiently within the velocity-gauge formalism of real-time time dependent density functional theory (RT-TDDFT). In this article, we discuss the implementation of the velocity-gauge RT-TDDFT equations for electron dynamics within a linear combination of atomic orbitals (LCAO) basis set framework. Numerical results obtained from our LCAO implementation, for the electronic response of periodic systems to both weak and intense laser fields, are compared to those obtained from established real-space grid and Full-Potential Linearized Augmented Planewave approaches. Potential applications of the LCAO based scheme in the context of extreme ultra-violet and soft X-ray spectroscopies involving core-electronic excitations are discussed.

  18. 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.

  19. A real-time photo-realistic rendering algorithm of ocean color based on bio-optical model

    NASA Astrophysics Data System (ADS)

    Ma, Chunyong; Xu, Shu; Wang, Hongsong; Tian, Fenglin; Chen, Ge

    2016-12-01

    A real-time photo-realistic rendering algorithm of ocean color is introduced in the paper, which considers the impact of ocean bio-optical model. The ocean bio-optical model mainly involves the phytoplankton, colored dissolved organic material (CDOM), inorganic suspended particle, etc., which have different contributions to absorption and scattering of light. We decompose the emergent light of the ocean surface into the reflected light from the sun and the sky, and the subsurface scattering light. We establish an ocean surface transmission model based on ocean bidirectional reflectance distribution function (BRDF) and the Fresnel law, and this model's outputs would be the incident light parameters of subsurface scattering. Using ocean subsurface scattering algorithm combined with bio-optical model, we compute the scattering light emergent radiation in different directions. Then, we blend the reflection of sunlight and sky light to implement the real-time ocean color rendering in graphics processing unit (GPU). Finally, we use two kinds of radiance reflectance calculated by Hydrolight radiative transfer model and our algorithm to validate the physical reality of our method, and the results show that our algorithm can achieve real-time highly realistic ocean color scenes.

  20. Delay-dependent stability and added damping of SDOF real-time dynamic hybrid testing

    NASA Astrophysics Data System (ADS)

    Chi, Fudong; Wang, Jinting; Jin, Feng

    2010-09-01

    It is well-recognized that a transfer system response delay that reduces the test stability inevitably exists in real-time dynamic hybrid testing (RTDHT). This paper focuses on the delay-dependent stability and added damping of SDOF systems in RTDHT. The exponential delay term is transferred into a rational fraction by the Padé approximation, and the delay-dependent stability conditions and instability mechanism of SDOF RTDHT systems are investigated by the root locus technique. First, the stability conditions are discussed separately for the cases of stiffness, mass, and damping experimental substructure. The use of root locus plots shows that the added damping effect and instability mechanism for mass are different from those for stiffness. For the stiffness experimental substructure case, the instability results from the inherent mode because of an obvious negative damping effect of the delay. For the mass case, the delay introduces an equivalent positive damping into the inherent mode, and instability occurs at an added high frequency mode. Then, the compound stability condition is investigated for a general case and the results show that the mass ratio may have both upper and lower limits to remain stable. Finally, a high-emulational virtual shaking table model is built to validate the stability conclusions.

  1. Dynamic and Thermal Turbulent Time Scale Modelling for Homogeneous Shear Flows

    NASA Technical Reports Server (NTRS)

    Schwab, John R.; Lakshminarayana, Budugur

    1994-01-01

    A new turbulence model, based upon dynamic and thermal turbulent time scale transport equations, is developed and applied to homogeneous shear flows with constant velocity and temperature gradients. The new model comprises transport equations for k, the turbulent kinetic energy; tau, the dynamic time scale; k(sub theta), the fluctuating temperature variance; and tau(sub theta), the thermal time scale. It offers conceptually parallel modeling of the dynamic and thermal turbulence at the two equation level, and eliminates the customary prescription of an empirical turbulent Prandtl number, Pr(sub t), thus permitting a more generalized prediction capability for turbulent heat transfer in complex flows and geometries. The new model also incorporates constitutive relations, based upon invariant theory, that allow the effects of nonequilibrium to modify the primary coefficients for the turbulent shear stress and heat flux. Predictions of the new model, along with those from two other similar models, are compared with experimental data for decaying homogeneous dynamic and thermal turbulence, homogeneous turbulence with constant temperature gradient, and homogeneous turbulence with constant temperature gradient and constant velocity gradient. The new model offers improvement in agreement with the data for most cases considered in this work, although it was no better than the other models for several cases where all the models performed poorly.

  2. Real-time individualized training vectors for experiential learning.

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

    Willis, Matt; Tucker, Eilish Marie; Raybourn, Elaine Marie

    2011-01-01

    Military training utilizing serious games or virtual worlds potentially generate data that can be mined to better understand how trainees learn in experiential exercises. Few data mining approaches for deployed military training games exist. Opportunities exist to collect and analyze these data, as well as to construct a full-history learner model. Outcomes discussed in the present document include results from a quasi-experimental research study on military game-based experiential learning, the deployment of an online game for training evidence collection, and results from a proof-of-concept pilot study on the development of individualized training vectors. This Lab Directed Research & Development (LDRD)more » project leveraged products within projects, such as Titan (Network Grand Challenge), Real-Time Feedback and Evaluation System, (America's Army Adaptive Thinking and Leadership, DARWARS Ambush! NK), and Dynamic Bayesian Networks to investigate whether machine learning capabilities could perform real-time, in-game similarity vectors of learner performance, toward adaptation of content delivery, and quantitative measurement of experiential learning.« less

  3. IGBT Switching Characteristic Curve Embedded Half-Bridge MMC Modelling and Real Time Simulation Realization

    NASA Astrophysics Data System (ADS)

    Zhengang, Lu; Hongyang, Yu; Xi, Yang

    2017-05-01

    The Modular Multilevel Converter (MMC) is one of the most attractive topologies in recent years for medium or high voltage industrial applications, such as high voltage dc transmission (HVDC) and medium voltage varying speed motor drive. The wide adoption of MMCs in industry is mainly due to its flexible expandability, transformer-less configuration, common dc bus, high reliability from redundancy, and so on. But, when the sub module number of MMC is more, the test of MMC controller will cost more time and effort. Hardware in the loop test based on real time simulator will save a lot of time and money caused by the MMC test. And due to the flexible of HIL, it becomes more and more popular in the industry area. The MMC modelling method remains an important issue for the MMC HIL test. Specifically, the VSC model should realistically reflect the nonlinear device switching characteristics, switching and conduction losses, tailing current, and diode reverse recovery behaviour of a realistic converter. In this paper, an IGBT switching characteristic curve embedded half-bridge MMC modelling method is proposed. This method is based on the switching curve referring and sample circuit calculation, and it is sample for implementation. Based on the proposed method, a FPGA real time simulation is carried out with 200ns sample time. The real time simulation results show the proposed method is correct.

  4. Real-time fault diagnosis for propulsion systems

    NASA Technical Reports Server (NTRS)

    Merrill, Walter C.; Guo, Ten-Huei; Delaat, John C.; Duyar, Ahmet

    1991-01-01

    Current research toward real time fault diagnosis for propulsion systems at NASA-Lewis is described. The research is being applied to both air breathing and rocket propulsion systems. Topics include fault detection methods including neural networks, system modeling, and real time implementations.

  5. Real-time simulation of an F110/STOVL turbofan engine

    NASA Technical Reports Server (NTRS)

    Drummond, Colin K.; Ouzts, Peter J.

    1989-01-01

    A traditional F110-type turbofan engine model was extended to include a ventral nozzle and two thrust-augmenting ejectors for Short Take-Off Vertical Landing (STOVL) aircraft applications. Development of the real-time F110/STOVL simulation required special attention to the modeling approach to component performance maps, the low pressure turbine exit mixing region, and the tailpipe dynamic approximation. Simulation validation derives by comparing output from the ADSIM simulation with the output for a validated F110/STOVL General Electric Aircraft Engines FORTRAN deck. General Electric substantiated basic engine component characteristics through factory testing and full scale ejector data.

  6. Real-time scheduling using minimum search

    NASA Technical Reports Server (NTRS)

    Tadepalli, Prasad; Joshi, Varad

    1992-01-01

    In this paper we consider a simple model of real-time scheduling. We present a real-time scheduling system called RTS which is based on Korf's Minimin algorithm. Experimental results show that the schedule quality initially improves with the amount of look-ahead search and tapers off quickly. So it sppears that reasonably good schedules can be produced with a relatively shallow search.

  7. Computation offloading for real-time health-monitoring devices.

    PubMed

    Kalantarian, Haik; Sideris, Costas; Tuan Le; Hosseini, Anahita; Sarrafzadeh, Majid

    2016-08-01

    Among the major challenges in the development of real-time wearable health monitoring systems is to optimize battery life. One of the major techniques with which this objective can be achieved is computation offloading, in which portions of computation can be partitioned between the device and other resources such as a server or cloud. In this paper, we describe a novel dynamic computation offloading scheme for real-time wearable health monitoring devices that adjusts the partitioning of data between the wearable device and mobile application as a function of desired classification accuracy.

  8. Time evolution of linearized gauge field fluctuations on a real-time lattice

    NASA Astrophysics Data System (ADS)

    Kurkela, A.; Lappi, T.; Peuron, J.

    2016-12-01

    Classical real-time lattice simulations play an important role in understanding non-equilibrium phenomena in gauge theories and are used in particular to model the prethermal evolution of heavy-ion collisions. Due to instabilities, small quantum fluctuations on top of the classical background may significantly affect the dynamics of the system. In this paper we argue for the need for a numerical calculation of a system of classical gauge fields and small linearized fluctuations in a way that keeps the separation between the two manifest. We derive and test an explicit algorithm to solve these equations on the lattice, maintaining gauge invariance and Gauss' law.

  9. Using an external surrogate for predictor model training in real-time motion management of lung tumors.

    PubMed

    Rottmann, Joerg; Berbeco, Ross

    2014-12-01

    Precise prediction of respiratory motion is a prerequisite for real-time motion compensation techniques such as beam, dynamic couch, or dynamic multileaf collimator tracking. Collection of tumor motion data to train the prediction model is required for most algorithms. To avoid exposure of patients to additional dose from imaging during this procedure, the feasibility of training a linear respiratory motion prediction model with an external surrogate signal is investigated and its performance benchmarked against training the model with tumor positions directly. The authors implement a lung tumor motion prediction algorithm based on linear ridge regression that is suitable to overcome system latencies up to about 300 ms. Its performance is investigated on a data set of 91 patient breathing trajectories recorded from fiducial marker tracking during radiotherapy delivery to the lung of ten patients. The expected 3D geometric error is quantified as a function of predictor lookahead time, signal sampling frequency and history vector length. Additionally, adaptive model retraining is evaluated, i.e., repeatedly updating the prediction model after initial training. Training length for this is gradually increased with incoming (internal) data availability. To assess practical feasibility model calculation times as well as various minimum data lengths for retraining are evaluated. Relative performance of model training with external surrogate motion data versus tumor motion data is evaluated. However, an internal-external motion correlation model is not utilized, i.e., prediction is solely driven by internal motion in both cases. Similar prediction performance was achieved for training the model with external surrogate data versus internal (tumor motion) data. Adaptive model retraining can substantially boost performance in the case of external surrogate training while it has little impact for training with internal motion data. A minimum adaptive retraining data length of

  10. A Dynamic Bioinspired Neural Network Based Real-Time Path Planning Method for Autonomous Underwater Vehicles

    PubMed Central

    2017-01-01

    Real-time path planning for autonomous underwater vehicle (AUV) is a very difficult and challenging task. Bioinspired neural network (BINN) has been used to deal with this problem for its many distinct advantages: that is, no learning process is needed and realization is also easy. However, there are some shortcomings when BINN is applied to AUV path planning in a three-dimensional (3D) unknown environment, including complex computing problem when the environment is very large and repeated path problem when the size of obstacles is bigger than the detection range of sensors. To deal with these problems, an improved dynamic BINN is proposed in this paper. In this proposed method, the AUV is regarded as the core of the BINN and the size of the BINN is based on the detection range of sensors. Then the BINN will move with the AUV and the computing could be reduced. A virtual target is proposed in the path planning method to ensure that the AUV can move to the real target effectively and avoid big-size obstacles automatically. Furthermore, a target attractor concept is introduced to improve the computing efficiency of neural activities. Finally, some experiments are conducted under various 3D underwater environments. The experimental results show that the proposed BINN based method can deal with the real-time path planning problem for AUV efficiently. PMID:28255297

  11. A Dynamic Bioinspired Neural Network Based Real-Time Path Planning Method for Autonomous Underwater Vehicles.

    PubMed

    Ni, Jianjun; Wu, Liuying; Shi, Pengfei; Yang, Simon X

    2017-01-01

    Real-time path planning for autonomous underwater vehicle (AUV) is a very difficult and challenging task. Bioinspired neural network (BINN) has been used to deal with this problem for its many distinct advantages: that is, no learning process is needed and realization is also easy. However, there are some shortcomings when BINN is applied to AUV path planning in a three-dimensional (3D) unknown environment, including complex computing problem when the environment is very large and repeated path problem when the size of obstacles is bigger than the detection range of sensors. To deal with these problems, an improved dynamic BINN is proposed in this paper. In this proposed method, the AUV is regarded as the core of the BINN and the size of the BINN is based on the detection range of sensors. Then the BINN will move with the AUV and the computing could be reduced. A virtual target is proposed in the path planning method to ensure that the AUV can move to the real target effectively and avoid big-size obstacles automatically. Furthermore, a target attractor concept is introduced to improve the computing efficiency of neural activities. Finally, some experiments are conducted under various 3D underwater environments. The experimental results show that the proposed BINN based method can deal with the real-time path planning problem for AUV efficiently.

  12. On the real-time estimation of the wheel-rail contact force by means of a new nonlinear estimator design model

    NASA Astrophysics Data System (ADS)

    Strano, Salvatore; Terzo, Mario

    2018-05-01

    The dynamics of the railway vehicles is strongly influenced by the interaction between the wheel and the rail. This kind of contact is affected by several conditioning factors such as vehicle speed, wear, adhesion level and, moreover, it is nonlinear. As a consequence, the modelling and the observation of this kind of phenomenon are complex tasks but, at the same time, they constitute a fundamental step for the estimation of the adhesion level or for the vehicle condition monitoring. This paper presents a novel technique for the real time estimation of the wheel-rail contact forces based on an estimator design model that takes into account the nonlinearities of the interaction by means of a fitting model functional to reproduce the contact mechanics in a wide range of slip and to be easily integrated in a complete model based estimator for railway vehicle.

  13. Exposure Time Optimization for Highly Dynamic Star Trackers

    PubMed Central

    Wei, Xinguo; Tan, Wei; Li, Jian; Zhang, Guangjun

    2014-01-01

    Under highly dynamic conditions, the star-spots on the image sensor of a star tracker move across many pixels during the exposure time, which will reduce star detection sensitivity and increase star location errors. However, this kind of effect can be compensated well by setting an appropriate exposure time. This paper focuses on how exposure time affects the star tracker under highly dynamic conditions and how to determine the most appropriate exposure time for this case. Firstly, the effect of exposure time on star detection sensitivity is analyzed by establishing the dynamic star-spot imaging model. Then the star location error is deduced based on the error analysis of the sub-pixel centroiding algorithm. Combining these analyses, the effect of exposure time on attitude accuracy is finally determined. Some simulations are carried out to validate these effects, and the results show that there are different optimal exposure times for different angular velocities of a star tracker with a given configuration. In addition, the results of night sky experiments using a real star tracker agree with the simulation results. The summarized regularities in this paper should prove helpful in the system design and dynamic performance evaluation of the highly dynamic star trackers. PMID:24618776

  14. Improved Short-Term Clock Prediction Method for Real-Time Positioning.

    PubMed

    Lv, Yifei; Dai, Zhiqiang; Zhao, Qile; Yang, Sheng; Zhou, Jinning; Liu, Jingnan

    2017-06-06

    The application of real-time precise point positioning (PPP) requires real-time precise orbit and clock products that should be predicted within a short time to compensate for the communication delay or data gap. Unlike orbit correction, clock correction is difficult to model and predict. The widely used linear model hardly fits long periodic trends with a small data set and exhibits significant accuracy degradation in real-time prediction when a large data set is used. This study proposes a new prediction model for maintaining short-term satellite clocks to meet the high-precision requirements of real-time clocks and provide clock extrapolation without interrupting the real-time data stream. Fast Fourier transform (FFT) is used to analyze the linear prediction residuals of real-time clocks. The periodic terms obtained through FFT are adopted in the sliding window prediction to achieve a significant improvement in short-term prediction accuracy. This study also analyzes and compares the accuracy of short-term forecasts (less than 3 h) by using different length observations. Experimental results obtained from International GNSS Service (IGS) final products and our own real-time clocks show that the 3-h prediction accuracy is better than 0.85 ns. The new model can replace IGS ultra-rapid products in the application of real-time PPP. It is also found that there is a positive correlation between the prediction accuracy and the short-term stability of on-board clocks. Compared with the accuracy of the traditional linear model, the accuracy of the static PPP using the new model of the 2-h prediction clock in N, E, and U directions is improved by about 50%. Furthermore, the static PPP accuracy of 2-h clock products is better than 0.1 m. When an interruption occurs in the real-time model, the accuracy of the kinematic PPP solution using 1-h clock prediction product is better than 0.2 m, without significant accuracy degradation. This model is of practical significance

  15. Near Real-time Ecological Forecasting of Peatland Responses to Warming and CO2 Treatment through EcoPAD-SPRUCE

    NASA Astrophysics Data System (ADS)

    Huang, Y.; Jiang, J.; Stacy, M.; Ricciuto, D. M.; Hanson, P. J.; Sundi, N.; Luo, Y.

    2016-12-01

    Ecological forecasting is critical in various aspects of our coupled human-nature systems, such as disaster risk reduction, natural resource management and climate change mitigation. Novel advancements are in urgent need to deepen our understandings of ecosystem dynamics, boost the predictive capacity of ecology, and provide timely and effective information for decision-makers in a rapidly changing world. Our Ecological Platform for Assimilation of Data (EcoPAD) facilitates the integration of current best knowledge from models, manipulative experimentations, observations and other modern techniques and provides both near real-time and long-term forecasting of ecosystem dynamics. As a case study, the web-based EcoPAD platform synchronizes real- or near real-time field measurements from the Spruce and Peatland Responses Under Climatic and Environmental Change Experiment (SPRUCE), a whole ecosystem warming and CO2 enrichment treatment experiment, assimilates multiple data streams into process based models, enhances timely feedback between modelers and experimenters, and ultimately improves ecosystem forecasting and makes best utilization of current knowledge. In addition to enable users to (i) estimate model parameters or state variables, (ii) quantify uncertainty of estimated parameters and projected states of ecosystems, (iii) evaluate model structures, (iv) assess sampling strategies, and (v) conduct ecological forecasting, EcoPAD-SPRUCE automated the workflow from real-time data acquisition, model simulation to result visualization. EcoPAD-SPRUCE promotes seamless feedback between modelers and experimenters, hand in hand to make better forecasting of future changes. The framework of EcoPAD-SPRUCE (with flexible API, Application Programming Interface) is easily portable and will benefit scientific communities, policy makers as well as the general public.

  16. Advances in Scientific Possibilities Offered by Real-Time Monitoring Technology.

    PubMed

    Kleiman, Evan M; Nock, Matthew K

    2017-01-01

    There has been a marked increase in research aimed at studying dynamic (e.g., day-to-day, moment-to-moment) changes in mental disorders and related behavior problems. Indeed, the number of scientific papers published that focus on real-time monitoring has been nearly doubling every five years for the past several decades. These methods allow for a more fine-grained description of phenomena of interest as well as for real-world tests of theoretical models of human behavior. Here we comment on the recent study by van Winkel and colleagues (this issue)as an excellent example of the use of real-time monitoring methods to better understand mental disorders. We also discuss the expanding universe of new technologies (e.g., smartphones, wearable biosensors) that can be used to make discoveries about psychopathology and related constructs and describe what we perceive to be some of the most exciting scientific possibilities that can be achieved in the near term by taking advantage of these new and rapidly developing tools.

  17. An Analysis of Input/Output Paradigms for Real-Time Systems

    DTIC Science & Technology

    1990-07-01

    timing and concurrency aspects of real - time systems . This paper illustrates how to build a mathematical model of the schedulability of a real-time...various design alternatives. The primary characteristic that distinguishes real-time system from non- real - time systems is the importance of time. The

  18. Real-time modeling of primitive environments through wavelet sensors and Hebbian learning

    NASA Astrophysics Data System (ADS)

    Vaccaro, James M.; Yaworsky, Paul S.

    1999-06-01

    Modeling the world through sensory input necessarily provides a unique perspective for the observer. Given a limited perspective, objects and events cannot always be encoded precisely but must involve crude, quick approximations to deal with sensory information in a real- time manner. As an example, when avoiding an oncoming car, a pedestrian needs to identify the fact that a car is approaching before ascertaining the model or color of the vehicle. In our methodology, we use wavelet-based sensors with self-organized learning to encode basic sensory information in real-time. The wavelet-based sensors provide necessary transformations while a rank-based Hebbian learning scheme encodes a self-organized environment through translation, scale and orientation invariant sensors. Such a self-organized environment is made possible by combining wavelet sets which are orthonormal, log-scale with linear orientation and have automatically generated membership functions. In earlier work we used Gabor wavelet filters, rank-based Hebbian learning and an exponential modulation function to encode textural information from images. Many different types of modulation are possible, but based on biological findings the exponential modulation function provided a good approximation of first spike coding of `integrate and fire' neurons. These types of Hebbian encoding schemes (e.g., exponential modulation, etc.) are useful for quick response and learning, provide several advantages over contemporary neural network learning approaches, and have been found to quantize data nonlinearly. By combining wavelets with Hebbian learning we can provide a real-time front-end for modeling an intelligent process, such as the autonomous control of agents in a simulated environment.

  19. Modeling Epidemics with Dynamic Small-World Networks

    NASA Astrophysics Data System (ADS)

    Kaski, Kimmo; Saramäki, Jari

    2005-06-01

    In this presentation a minimal model for describing the spreading of an infectious disease, such as influenza, is discussed. Here it is assumed that spreading takes place on a dynamic small-world network comprising short- and long-range infection events. Approximate equations for the epidemic threshold as well as the spreading dynamics are derived and they agree well with numerical discrete time-step simulations. Also the dependence of the epidemic saturation time on the initial conditions is analysed and a comparison with real-world data is made.

  20. Real-time monitoring of metabolic function in liver-on-chip microdevices tracks the dynamics of mitochondrial dysfunction

    PubMed Central

    Bavli, Danny; Prill, Sebastian; Ezra, Elishai; Levy, Gahl; Cohen, Merav; Vinken, Mathieu; Vanfleteren, Jan; Jaeger, Magnus; Nahmias, Yaakov

    2016-01-01

    Microfluidic organ-on-a-chip technology aims to replace animal toxicity testing, but thus far has demonstrated few advantages over traditional methods. Mitochondrial dysfunction plays a critical role in the development of chemical and pharmaceutical toxicity, as well as pluripotency and disease processes. However, current methods to evaluate mitochondrial activity still rely on end-point assays, resulting in limited kinetic and prognostic information. Here, we present a liver-on-chip device capable of maintaining human tissue for over a month in vitro under physiological conditions. Mitochondrial respiration was monitored in real time using two-frequency phase modulation of tissue-embedded phosphorescent microprobes. A computer-controlled microfluidic switchboard allowed contiguous electrochemical measurements of glucose and lactate, providing real-time analysis of minute shifts from oxidative phosphorylation to anaerobic glycolysis, an early indication of mitochondrial stress. We quantify the dynamics of cellular adaptation to mitochondrial damage and the resulting redistribution of ATP production during rotenone-induced mitochondrial dysfunction and troglitazone (Rezulin)-induced mitochondrial stress. We show troglitazone shifts metabolic fluxes at concentrations previously regarded as safe, suggesting a mechanism for its observed idiosyncratic effect. Our microfluidic platform reveals the dynamics and strategies of cellular adaptation to mitochondrial damage, a unique advantage of organ-on-chip technology. PMID:27044092

  1. Modeling and real time simulation of an HVDC inverter feeding a weak AC system based on commutation failure study.

    PubMed

    Mankour, Mohamed; Khiat, Mounir; Ghomri, Leila; Chaker, Abdelkader; Bessalah, Mourad

    2018-06-01

    This paper presents modeling and study of 12-pulse HVDC (High Voltage Direct Current) based on real time simulation where the HVDC inverter is connected to a weak AC system. In goal to study the dynamic performance of the HVDC link, two serious kind of disturbance are applied at HVDC converters where the first one is the single phase to ground AC fault and the second one is the DC link to ground fault. The study is based on two different mode of analysis, which the first is to test the performance of the DC control and the second is focalized to study the effect of the protection function on the system behavior. This real time simulation considers the strength of the AC system to witch is connected and his relativity with the capacity of the DC link. The results obtained are validated by means of RT-lab platform using digital Real time simulator Hypersim (OP-5600), the results carried out show the effect of the DC control and the influence of the protection function to reduce the probability of commutation failures and also for helping inverter to take out from commutation failure even while the DC control fails to eliminate them. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

  2. Simulation model of a gear synchronisation unit for application in a real-time HiL environment

    NASA Astrophysics Data System (ADS)

    Kirchner, Markus; Eberhard, Peter

    2017-05-01

    Gear shifting simulations using the multibody system approach and the finite-element method are standard in the development of transmissions. However, the corresponding models are typically large due to the complex geometries and numerous contacts, which causes long calculation times. The present work sets itself apart from these detailed shifting simulations by proposing a much simpler but powerful synchronisation model which can be computed in real-time while it is still more realistic than a pure rigid multibody model. Therefore, the model is even used as part of a Hardware-in-the-Loop (HiL) test rig. The proposed real-time capable synchronization model combines the rigid multibody system approach with a multiscale simulation approach. The multibody system approach is suitable for the description of the large motions. The multiscale simulation approach is using also the finite-element method suitable for the analysis of the contact processes. An efficient contact search for the claws of a car transmission synchronisation unit is described in detail which shortens the required calculation time of the model considerably. To further shorten the calculation time, the use of a complex pre-synchronisation model with a nonlinear contour is presented. The model has to provide realistic results with the time-step size of the HiL test rig. To reach this specification, a particularly adapted multirate method for the synchronisation model is shown. Measured results of test rigs of the real-time capable synchronisation model are verified on plausibility. The simulation model is then also used in the HiL test rig for a transmission control unit.

  3. Enhancements to the EPANET-RTX (Real-Time Analytics) ...

    EPA Pesticide Factsheets

    Technical brief and software The U.S. Environmental Protection Agency (EPA) developed EPANET-RTX as a collection of object-oriented software libraries comprising the core data access, data transformation, and data synthesis (real-time analytics) components of a real-time hydraulic and water quality modeling system. While EPANET-RTX uses the hydraulic and water quality solvers of EPANET, the object libraries are a self-contained set of building blocks for software developers. “Real-time EPANET” promises to change the way water utilities, commercial vendors, engineers, and the water community think about modeling.

  4. Real-time model learning using Incremental Sparse Spectrum Gaussian Process Regression.

    PubMed

    Gijsberts, Arjan; Metta, Giorgio

    2013-05-01

    Novel applications in unstructured and non-stationary human environments require robots that learn from experience and adapt autonomously to changing conditions. Predictive models therefore not only need to be accurate, but should also be updated incrementally in real-time and require minimal human intervention. Incremental Sparse Spectrum Gaussian Process Regression is an algorithm that is targeted specifically for use in this context. Rather than developing a novel algorithm from the ground up, the method is based on the thoroughly studied Gaussian Process Regression algorithm, therefore ensuring a solid theoretical foundation. Non-linearity and a bounded update complexity are achieved simultaneously by means of a finite dimensional random feature mapping that approximates a kernel function. As a result, the computational cost for each update remains constant over time. Finally, algorithmic simplicity and support for automated hyperparameter optimization ensures convenience when employed in practice. Empirical validation on a number of synthetic and real-life learning problems confirms that the performance of Incremental Sparse Spectrum Gaussian Process Regression is superior with respect to the popular Locally Weighted Projection Regression, while computational requirements are found to be significantly lower. The method is therefore particularly suited for learning with real-time constraints or when computational resources are limited. Copyright © 2012 Elsevier Ltd. All rights reserved.

  5. PERTS: A Prototyping Environment for Real-Time Systems

    NASA Technical Reports Server (NTRS)

    Liu, Jane W. S.; Lin, Kwei-Jay; Liu, C. L.

    1991-01-01

    We discuss an ongoing project to build a Prototyping Environment for Real-Time Systems, called PERTS. PERTS is a unique prototyping environment in that it has (1) tools and performance models for the analysis and evaluation of real-time prototype systems, (2) building blocks for flexible real-time programs and the support system software, (3) basic building blocks of distributed and intelligent real time applications, and (4) an execution environment. PERTS will make the recent and future theoretical advances in real-time system design and engineering readily usable to practitioners. In particular, it will provide an environment for the use and evaluation of new design approaches, for experimentation with alternative system building blocks and for the analysis and performance profiling of prototype real-time systems.

  6. Human systems dynamics: Toward a computational model

    NASA Astrophysics Data System (ADS)

    Eoyang, Glenda H.

    2012-09-01

    A robust and reliable computational model of complex human systems dynamics could support advancements in theory and practice for social systems at all levels, from intrapersonal experience to global politics and economics. Models of human interactions have evolved from traditional, Newtonian systems assumptions, which served a variety of practical and theoretical needs of the past. Another class of models has been inspired and informed by models and methods from nonlinear dynamics, chaos, and complexity science. None of the existing models, however, is able to represent the open, high dimension, and nonlinear self-organizing dynamics of social systems. An effective model will represent interactions at multiple levels to generate emergent patterns of social and political life of individuals and groups. Existing models and modeling methods are considered and assessed against characteristic pattern-forming processes in observed and experienced phenomena of human systems. A conceptual model, CDE Model, based on the conditions for self-organizing in human systems, is explored as an alternative to existing models and methods. While the new model overcomes the limitations of previous models, it also provides an explanatory base and foundation for prospective analysis to inform real-time meaning making and action taking in response to complex conditions in the real world. An invitation is extended to readers to engage in developing a computational model that incorporates the assumptions, meta-variables, and relationships of this open, high dimension, and nonlinear conceptual model of the complex dynamics of human systems.

  7. Internet Teleprescence by Real-Time View-Dependent Image Generation with Omnidirectional Video Camera

    NASA Astrophysics Data System (ADS)

    Morita, Shinji; Yamazawa, Kazumasa; Yokoya, Naokazu

    2003-01-01

    This paper describes a new networked telepresence system which realizes virtual tours into a visualized dynamic real world without significant time delay. Our system is realized by the following three steps: (1) video-rate omnidirectional image acquisition, (2) transportation of an omnidirectional video stream via internet, and (3) real-time view-dependent perspective image generation from the omnidirectional video stream. Our system is applicable to real-time telepresence in the situation where the real world to be seen is far from an observation site, because the time delay from the change of user"s viewing direction to the change of displayed image is small and does not depend on the actual distance between both sites. Moreover, multiple users can look around from a single viewpoint in a visualized dynamic real world in different directions at the same time. In experiments, we have proved that the proposed system is useful for internet telepresence.

  8. Segment Fixed Priority Scheduling for Self Suspending Real Time Tasks

    DTIC Science & Technology

    2016-08-11

    Segment-Fixed Priority Scheduling for Self-Suspending Real -Time Tasks Junsung Kim, Department of Electrical and Computer Engineering, Carnegie...4 2.1 Application of a Multi-Segment Self-Suspending Real -Time Task Model ............................. 5 3 Fixed Priority Scheduling...1 Figure 2: A multi-segment self-suspending real -time task model

  9. Correlations and risk contagion between mixed assets and mixed-asset portfolio VaR measurements in a dynamic view: An application based on time varying copula models

    NASA Astrophysics Data System (ADS)

    Han, Yingying; Gong, Pu; Zhou, Xiang

    2016-02-01

    In this paper, we apply time varying Gaussian and SJC copula models to study the correlations and risk contagion between mixed assets: financial (stock), real estate and commodity (gold) assets in China firstly. Then we study the dynamic mixed-asset portfolio risk through VaR measurement based on the correlations computed by the time varying copulas. This dynamic VaR-copula measurement analysis has never been used on mixed-asset portfolios. The results show the time varying estimations fit much better than the static models, not only for the correlations and risk contagion based on time varying copulas, but also for the VaR-copula measurement. The time varying VaR-SJC copula models are more accurate than VaR-Gaussian copula models when measuring more risky portfolios with higher confidence levels. The major findings suggest that real estate and gold play a role on portfolio risk diversification and there exist risk contagion and flight to quality between mixed-assets when extreme cases happen, but if we take different mixed-asset portfolio strategies with the varying of time and environment, the portfolio risk will be reduced.

  10. A real-time biomimetic acoustic localizing system using time-shared architecture

    NASA Astrophysics Data System (ADS)

    Nourzad Karl, Marianne; Karl, Christian; Hubbard, Allyn

    2008-04-01

    In this paper a real-time sound source localizing system is proposed, which is based on previously developed mammalian auditory models. Traditionally, following the models, which use interaural time delay (ITD) estimates, the amount of parallel computations needed by a system to achieve real-time sound source localization is a limiting factor and a design challenge for hardware implementations. Therefore a new approach using a time-shared architecture implementation is introduced. The proposed architecture is a purely sample-base-driven digital system, and it follows closely the continuous-time approach described in the models. Rather than having dedicated hardware on a per frequency channel basis, a specialized core channel, shared for all frequency bands is used. Having an optimized execution time, which is much less than the system's sample rate, the proposed time-shared solution allows the same number of virtual channels to be processed as the dedicated channels in the traditional approach. Hence, the time-shared approach achieves a highly economical and flexible implementation using minimal silicon area. These aspects are particularly important in efficient hardware implementation of a real time biomimetic sound source localization system.

  11. Model free approach to kinetic analysis of real-time hyperpolarized 13C magnetic resonance spectroscopy data.

    PubMed

    Hill, Deborah K; Orton, Matthew R; Mariotti, Erika; Boult, Jessica K R; Panek, Rafal; Jafar, Maysam; Parkes, Harold G; Jamin, Yann; Miniotis, Maria Falck; Al-Saffar, Nada M S; Beloueche-Babari, Mounia; Robinson, Simon P; Leach, Martin O; Chung, Yuen-Li; Eykyn, Thomas R

    2013-01-01

    Real-time detection of the rates of metabolic flux, or exchange rates of endogenous enzymatic reactions, is now feasible in biological systems using Dynamic Nuclear Polarization Magnetic Resonance. Derivation of reaction rate kinetics from this technique typically requires multi-compartmental modeling of dynamic data, and results are therefore model-dependent and prone to misinterpretation. We present a model-free formulism based on the ratio of total areas under the curve (AUC) of the injected and product metabolite, for example pyruvate and lactate. A theoretical framework to support this novel analysis approach is described, and demonstrates that the AUC ratio is proportional to the forward rate constant k. We show that the model-free approach strongly correlates with k for whole cell in vitro experiments across a range of cancer cell lines, and detects response in cells treated with the pan-class I PI3K inhibitor GDC-0941 with comparable or greater sensitivity. The same result is seen in vivo with tumor xenograft-bearing mice, in control tumors and following drug treatment with dichloroacetate. An important finding is that the area under the curve is independent of both the input function and of any other metabolic pathways arising from the injected metabolite. This model-free approach provides a robust and clinically relevant alternative to kinetic model-based rate measurements in the clinical translation of hyperpolarized (13)C metabolic imaging in humans, where measurement of the input function can be problematic.

  12. Model Free Approach to Kinetic Analysis of Real-Time Hyperpolarized 13C Magnetic Resonance Spectroscopy Data

    PubMed Central

    Mariotti, Erika; Boult, Jessica K. R.; Panek, Rafal; Jafar, Maysam; Parkes, Harold G.; Jamin, Yann; Miniotis, Maria Falck; Al-Saffar, Nada M. S.; Beloueche-Babari, Mounia; Robinson, Simon P.; Leach, Martin O.; Chung, Yuen-Li; Eykyn, Thomas R.

    2013-01-01

    Real-time detection of the rates of metabolic flux, or exchange rates of endogenous enzymatic reactions, is now feasible in biological systems using Dynamic Nuclear Polarization Magnetic Resonance. Derivation of reaction rate kinetics from this technique typically requires multi-compartmental modeling of dynamic data, and results are therefore model-dependent and prone to misinterpretation. We present a model-free formulism based on the ratio of total areas under the curve (AUC) of the injected and product metabolite, for example pyruvate and lactate. A theoretical framework to support this novel analysis approach is described, and demonstrates that the AUC ratio is proportional to the forward rate constant k. We show that the model-free approach strongly correlates with k for whole cell in vitro experiments across a range of cancer cell lines, and detects response in cells treated with the pan-class I PI3K inhibitor GDC-0941 with comparable or greater sensitivity. The same result is seen in vivo with tumor xenograft-bearing mice, in control tumors and following drug treatment with dichloroacetate. An important finding is that the area under the curve is independent of both the input function and of any other metabolic pathways arising from the injected metabolite. This model-free approach provides a robust and clinically relevant alternative to kinetic model-based rate measurements in the clinical translation of hyperpolarized 13C metabolic imaging in humans, where measurement of the input function can be problematic. PMID:24023724

  13. Toward a comprehensive model of antisocial development: a dynamic systems approach.

    PubMed

    Granic, Isabela; Patterson, Gerald R

    2006-01-01

    The purpose of this article is to develop a preliminary comprehensive model of antisocial development based on dynamic systems principles. The model is built on the foundations of behavioral research on coercion theory. First, the authors focus on the principles of multistability, feedback, and nonlinear causality to reconceptualize real-time parent-child and peer processes. Second, they model the mechanisms by which these real-time processes give rise to negative developmental outcomes, which in turn feed back to determine real-time interactions. Third, they examine mechanisms of change and stability in early- and late-onset antisocial trajectories. Finally, novel clinical designs and predictions are introduced. The authors highlight new predictions and present studies that have tested aspects of the model

  14. Towards Real-Time Maneuver Detection: Automatic State and Dynamics Estimation with the Adaptive Optimal Control Based Estimator

    NASA Astrophysics Data System (ADS)

    Lubey, D.; Scheeres, D.

    Tracking objects in Earth orbit is fraught with complications. This is due to the large population of orbiting spacecraft and debris that continues to grow, passive (i.e. no direct communication) and data-sparse observations, and the presence of maneuvers and dynamics mismodeling. Accurate orbit determination in this environment requires an algorithm to capture both a system's state and its state dynamics in order to account for mismodelings. Previous studies by the authors yielded an algorithm called the Optimal Control Based Estimator (OCBE) - an algorithm that simultaneously estimates a system's state and optimal control policies that represent dynamic mismodeling in the system for an arbitrary orbit-observer setup. The stochastic properties of these estimated controls are then used to determine the presence of mismodelings (maneuver detection), as well as characterize and reconstruct the mismodelings. The purpose of this paper is to develop the OCBE into an accurate real-time orbit tracking and maneuver detection algorithm by automating the algorithm and removing its linear assumptions. This results in a nonlinear adaptive estimator. In its original form the OCBE had a parameter called the assumed dynamic uncertainty, which is selected by the user with each new measurement to reflect the level of dynamic mismodeling in the system. This human-in-the-loop approach precludes real-time application to orbit tracking problems due to their complexity. This paper focuses on the Adaptive OCBE, a version of the estimator where the assumed dynamic uncertainty is chosen automatically with each new measurement using maneuver detection results to ensure that state uncertainties are properly adjusted to account for all dynamic mismodelings. The paper also focuses on a nonlinear implementation of the estimator. Originally, the OCBE was derived from a nonlinear cost function then linearized about a nominal trajectory, which is assumed to be ballistic (i.e. the nominal optimal

  15. Fundamental Studies of Solidification in Microgravity Using Real-Time X-Ray Microscopy

    NASA Technical Reports Server (NTRS)

    Curreri, Peter A.; Kaukler, William; Sen, Subhayu; Bhat, Biliyar N.

    1999-01-01

    This research applies a state of the art X-ray Transmission Microscope, XTM, to image (with resolutions up to 3 micrometers) the solidification of metallic or semiconductor alloys in real-time. We have successfully imaged in real-time: interfacial morphologies, phase growth, coalescence, incorporation of phases into the growing interface, and the solute boundary layer in the liquid at the solid-liquid interface. We have also measured true local growth rates and can evaluate segregation structures in the solid; a form of in-situ metallography. During this study, the growth of secondary phase fibers and lamellae from eutectic and monotectic alloys have been imaged during solidification, in real-time, for the first time in bulk metal alloys. Current high resolution X-ray sources and high contrast X-ray detectors have advanced to allow systematic study of solidification dynamics and the resulting microstructure. We have employed a state-of-the-art sub-micron source with acceleration voltages of 10-100 kV to image solidification of metals. One useful strength of the XTM stems from the manner an image is formed. The radiographic image is a shadow formed by x-ray photons that are not absorbed as they pass through the specimen. Composition gradients within the specimen cause variations in absorption of the flux such that the final image represents a spatial integral of composition (or thickness). The ability to image these features in real-time enables more fundamental and detailed understanding of solidification dynamics than has previously been possible. Hence, application of this technique towards microgravity experiments will allow rigorous testing of critical solidification models.

  16. The dynamic radiation environment assimilation model (DREAM)

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

    Reeves, Geoffrey D; Koller, Josef; Tokar, Robert L

    2010-01-01

    The Dynamic Radiation Environment Assimilation Model (DREAM) is a 3-year effort sponsored by the US Department of Energy to provide global, retrospective, or real-time specification of the natural and potential nuclear radiation environments. The DREAM model uses Kalman filtering techniques that combine the strengths of new physical models of the radiation belts with electron observations from long-term satellite systems such as GPS and geosynchronous systems. DREAM includes a physics model for the production and long-term evolution of artificial radiation belts from high altitude nuclear explosions. DREAM has been validated against satellites in arbitrary orbits and consistently produces more accurate resultsmore » than existing models. Tools for user-specific applications and graphical displays are in beta testing and a real-time version of DREAM has been in continuous operation since November 2009.« less

  17. 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

  18. 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.

  19. Accounting for large deformations in real-time simulations of soft tissues based on reduced-order models.

    PubMed

    Niroomandi, S; Alfaro, I; Cueto, E; Chinesta, F

    2012-01-01

    Model reduction techniques have shown to constitute a valuable tool for real-time simulation in surgical environments and other fields. However, some limitations, imposed by real-time constraints, have not yet been overcome. One of such limitations is the severe limitation in time (established in 500Hz of frequency for the resolution) that precludes the employ of Newton-like schemes for solving non-linear models as the ones usually employed for modeling biological tissues. In this work we present a technique able to deal with geometrically non-linear models, based on the employ of model reduction techniques, together with an efficient non-linear solver. Examples of the performance of the technique over some examples will be given. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

  20. Velocity-gauge real-time TDDFT within a numerical atomic orbital basis set

    DOE PAGES

    Pemmaraju, C. D.; Vila, F. D.; Kas, J. J.; ...

    2018-02-07

    The interaction of laser fields with solid-state systems can be modeled efficiently within the velocity-gauge formalism of real-time time dependent density functional theory (RT-TDDFT). In this article, we discuss the implementation of the velocity-gauge RT-TDDFT equations for electron dynamics within a linear combination of atomic orbitals (LCAO) basis set framework. Numerical results obtained from our LCAO implementation, for the electronic response of periodic systems to both weak and intense laser fields, are compared to those obtained from established real-space grid and Full-Potential Linearized Augmented Planewave approaches. As a result, potential applications of the LCAO based scheme in the context ofmore » extreme ultra-violet and soft X-ray spectroscopies involving core-electronic excitations are discussed.« less

  1. Velocity-gauge real-time TDDFT within a numerical atomic orbital basis set

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

    Pemmaraju, C. D.; Vila, F. D.; Kas, J. J.

    The interaction of laser fields with solid-state systems can be modeled efficiently within the velocity-gauge formalism of real-time time dependent density functional theory (RT-TDDFT). In this article, we discuss the implementation of the velocity-gauge RT-TDDFT equations for electron dynamics within a linear combination of atomic orbitals (LCAO) basis set framework. Numerical results obtained from our LCAO implementation, for the electronic response of periodic systems to both weak and intense laser fields, are compared to those obtained from established real-space grid and Full-Potential Linearized Augmented Planewave approaches. As a result, potential applications of the LCAO based scheme in the context ofmore » extreme ultra-violet and soft X-ray spectroscopies involving core-electronic excitations are discussed.« less

  2. Coarse Resolution SAR Imagery to Support Flood Inundation Models in Near Real Time

    NASA Astrophysics Data System (ADS)

    Di Baldassarre, Giuliano; Schumann, Guy; Brandimarte, Luigia; Bates, Paul

    2009-11-01

    In recent years, the availability of new emerging data (e.g. remote sensing, intelligent wireless sensors, etc) has led to a sudden shift from a data-sparse to a data-rich environment for hydrological and hydraulic modelling. Furthermore, the increased socioeconomic relevance of river flood studies has motivated the development of complex methodologies for the simulation of the hydraulic behaviour of river systems. In this context, this study aims at assessing the capability of coarse resolution SAR (Synthetic Aperture Radar) imagery to support and quickly validate flood inundation models in near real time. A hydraulic model of a 98km reach of the River Po (Italy), previously calibrated on a high-magnitude flood event with extensive and high quality field data, is tested using a SAR flood image, acquired and processed in near real time, during the June 2008 low-magnitude event. Specifically, the image is an acquisition by the ENVISAT-ASAR sensor in wide swath mode and has been provided through ESA (European Space Agency) Fast Registration system at no cost 24 hours after the acquisition. The study shows that the SAR image enables validation and improvement of the model in a time shorter than the flood travel time. This increases the reliability of model predictions (e.g. water elevation and inundation width along the river reach) and, consequently, assists flood management authorities in undertaking the necessary prevention activities.

  3. Modeling Interdependent and Periodic Real-World Action Sequences

    PubMed Central

    Kurashima, Takeshi; Althoff, Tim; Leskovec, Jure

    2018-01-01

    Mobile health applications, including those that track activities such as exercise, sleep, and diet, are becoming widely used. Accurately predicting human actions in the real world is essential for targeted recommendations that could improve our health and for personalization of these applications. However, making such predictions is extremely difficult due to the complexities of human behavior, which consists of a large number of potential actions that vary over time, depend on each other, and are periodic. Previous work has not jointly modeled these dynamics and has largely focused on item consumption patterns instead of broader types of behaviors such as eating, commuting or exercising. In this work, we develop a novel statistical model, called TIPAS, for Time-varying, Interdependent, and Periodic Action Sequences. Our approach is based on personalized, multivariate temporal point processes that model time-varying action propensities through a mixture of Gaussian intensities. Our model captures short-term and long-term periodic interdependencies between actions through Hawkes process-based self-excitations. We evaluate our approach on two activity logging datasets comprising 12 million real-world actions (e.g., eating, sleep, and exercise) taken by 20 thousand users over 17 months. We demonstrate that our approach allows us to make successful predictions of future user actions and their timing. Specifically, TIPAS improves predictions of actions, and their timing, over existing methods across multiple datasets by up to 156%, and up to 37%, respectively. Performance improvements are particularly large for relatively rare and periodic actions such as walking and biking, improving over baselines by up to 256%. This demonstrates that explicit modeling of dependencies and periodicities in real-world behavior enables successful predictions of future actions, with implications for modeling human behavior, app personalization, and targeting of health interventions. PMID

  4. Red fluorescent probes for real-time imaging of the cell cycle by dynamic monitoring of the nucleolus and chromosome.

    PubMed

    Wang, Kang-Nan; Chao, Xi-Juan; Liu, Bing; Zhou, Dan-Jie; He, Liang; Zheng, Xiao-Hui; Cao, Qian; Tan, Cai-Ping; Zhang, Chen; Mao, Zong-Wan

    2018-03-08

    Two cationic molecular rotors, 1 and 2, capable of real-time cell-cycle imaging by specifically dynamic monitoring of nucleolus and chromosome changes were developed. A further study shows that fluorescence enhancements in the nucleolus and chromosome are attributed to a combination effect of interaction with nucleic acid and high condensation of the nucleolus and chromosome.

  5. Real-time Ensemble Forecasting of Coronal Mass Ejections using the WSA-ENLIL+Cone Model

    NASA Astrophysics Data System (ADS)

    Mays, M. L.; Taktakishvili, A.; Pulkkinen, A. A.; MacNeice, P. J.; Rastaetter, L.; Kuznetsova, M. M.; Odstrcil, D.

    2013-12-01

    Ensemble forecasting of coronal mass ejections (CMEs) provides significant information in that it provides an estimation of the spread or uncertainty in CME arrival time predictions due to uncertainties in determining CME input parameters. Ensemble modeling of CME propagation in the heliosphere is performed by forecasters at the Space Weather Research Center (SWRC) using the WSA-ENLIL cone model available at the Community Coordinated Modeling Center (CCMC). SWRC is an in-house research-based operations team at the CCMC which provides interplanetary space weather forecasting for NASA's robotic missions and performs real-time model validation. A distribution of n (routinely n=48) CME input parameters are generated using the CCMC Stereo CME Analysis Tool (StereoCAT) which employs geometrical triangulation techniques. These input parameters are used to perform n different simulations yielding an ensemble of solar wind parameters at various locations of interest (satellites or planets), including a probability distribution of CME shock arrival times (for hits), and geomagnetic storm strength (for Earth-directed hits). Ensemble simulations have been performed experimentally in real-time at the CCMC since January 2013. We present the results of ensemble simulations for a total of 15 CME events, 10 of which were performed in real-time. The observed CME arrival was within the range of ensemble arrival time predictions for 5 out of the 12 ensemble runs containing hits. The average arrival time prediction was computed for each of the twelve ensembles predicting hits and using the actual arrival time an average absolute error of 8.20 hours was found for all twelve ensembles, which is comparable to current forecasting errors. Some considerations for the accuracy of ensemble CME arrival time predictions include the importance of the initial distribution of CME input parameters, particularly the mean and spread. When the observed arrivals are not within the predicted range, this

  6. Dynamic response analysis of structure under time-variant interval process model

    NASA Astrophysics Data System (ADS)

    Xia, Baizhan; Qin, Yuan; Yu, Dejie; Jiang, Chao

    2016-10-01

    Due to the aggressiveness of the environmental factor, the variation of the dynamic load, the degeneration of the material property and the wear of the machine surface, parameters related with the structure are distinctly time-variant. Typical model for time-variant uncertainties is the random process model which is constructed on the basis of a large number of samples. In this work, we propose a time-variant interval process model which can be effectively used to deal with time-variant uncertainties with limit information. And then two methods are presented for the dynamic response analysis of the structure under the time-variant interval process model. The first one is the direct Monte Carlo method (DMCM) whose computational burden is relative high. The second one is the Monte Carlo method based on the Chebyshev polynomial expansion (MCM-CPE) whose computational efficiency is high. In MCM-CPE, the dynamic response of the structure is approximated by the Chebyshev polynomials which can be efficiently calculated, and then the variational range of the dynamic response is estimated according to the samples yielded by the Monte Carlo method. To solve the dependency phenomenon of the interval operation, the affine arithmetic is integrated into the Chebyshev polynomial expansion. The computational effectiveness and efficiency of MCM-CPE is verified by two numerical examples, including a spring-mass-damper system and a shell structure.

  7. Lane-changing model with dynamic consideration of driver's propensity

    NASA Astrophysics Data System (ADS)

    Wang, Xiaoyuan; Wang, Jianqiang; Zhang, Jinglei; Ban, Xuegang Jeff

    2015-07-01

    Lane-changing is the driver's selection result of the satisfaction degree in different lane driving conditions. There are many different factors influencing lane-changing behavior, such as diversity, randomicity and difficulty of measurement. So it is hard to accurately reflect the uncertainty of drivers' lane-changing behavior. As a result, the research of lane-changing models is behind that of car-following models. Driver's propensity is her/his emotion state or the corresponding preference of a decision or action toward the real objective traffic situations under the influence of various dynamic factors. It represents the psychological characteristics of the driver in the process of vehicle operation and movement. It is an important factor to influence lane-changing. In this paper, dynamic recognition of driver's propensity is considered during simulation based on its time-varying discipline and the analysis of the driver's psycho-physic characteristics. The Analytic Hierarchy Process (AHP) method is used to quantify the hierarchy of driver's dynamic lane-changing decision-making process, especially the influence of the propensity. The model is validated using real data. Test results show that the developed lane-changing model with the dynamic consideration of a driver's time-varying propensity and the AHP method are feasible and with improved accuracy.

  8. Implementation of real-time energy management strategy based on reinforcement learning for hybrid electric vehicles and simulation validation

    PubMed Central

    Kong, Zehui; Liu, Teng

    2017-01-01

    To further improve the fuel economy of series hybrid electric tracked vehicles, a reinforcement learning (RL)-based real-time energy management strategy is developed in this paper. In order to utilize the statistical characteristics of online driving schedule effectively, a recursive algorithm for the transition probability matrix (TPM) of power-request is derived. The reinforcement learning (RL) is applied to calculate and update the control policy at regular time, adapting to the varying driving conditions. A facing-forward powertrain model is built in detail, including the engine-generator model, battery model and vehicle dynamical model. The robustness and adaptability of real-time energy management strategy are validated through the comparison with the stationary control strategy based on initial transition probability matrix (TPM) generated from a long naturalistic driving cycle in the simulation. Results indicate that proposed method has better fuel economy than stationary one and is more effective in real-time control. PMID:28671967

  9. Implementation of real-time energy management strategy based on reinforcement learning for hybrid electric vehicles and simulation validation.

    PubMed

    Kong, Zehui; Zou, Yuan; Liu, Teng

    2017-01-01

    To further improve the fuel economy of series hybrid electric tracked vehicles, a reinforcement learning (RL)-based real-time energy management strategy is developed in this paper. In order to utilize the statistical characteristics of online driving schedule effectively, a recursive algorithm for the transition probability matrix (TPM) of power-request is derived. The reinforcement learning (RL) is applied to calculate and update the control policy at regular time, adapting to the varying driving conditions. A facing-forward powertrain model is built in detail, including the engine-generator model, battery model and vehicle dynamical model. The robustness and adaptability of real-time energy management strategy are validated through the comparison with the stationary control strategy based on initial transition probability matrix (TPM) generated from a long naturalistic driving cycle in the simulation. Results indicate that proposed method has better fuel economy than stationary one and is more effective in real-time control.

  10. Effects of Real-Time NASA Vegetation Data on Model Forecasts of Severe Weather

    NASA Technical Reports Server (NTRS)

    Case, Jonathan L.; Bell, Jordan R.; LaFontaine, Frank J.; Peters-Lidard, Christa D.

    2012-01-01

    The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Greenness Vegetation Fraction (GVF) dataset, which is updated daily using swaths of Normalized Difference Vegetation Index data from the Moderate Resolution Imaging Spectroradiometer (MODIS) data aboard the NASA-EOS Aqua and Terra satellites. NASA SPoRT started generating daily real-time GVF composites at 1-km resolution over the Continental United States beginning 1 June 2010. A companion poster presentation (Bell et al.) primarily focuses on impact results in an offline configuration of the Noah land surface model (LSM) for the 2010 warm season, comparing the SPoRT/MODIS GVF dataset to the current operational monthly climatology GVF available within the National Centers for Environmental Prediction (NCEP) and Weather Research and Forecasting (WRF) models. This paper/presentation primarily focuses on individual case studies of severe weather events to determine the impacts and possible improvements by using the real-time, high-resolution SPoRT-MODIS GVFs in place of the coarser-resolution NCEP climatological GVFs in model simulations. The NASA-Unified WRF (NU-WRF) modeling system is employed to conduct the sensitivity simulations of individual events. The NU-WRF is an integrated modeling system based on the Advanced Research WRF dynamical core that is designed to represents aerosol, cloud, precipitation, and land processes at satellite-resolved scales in a coupled simulation environment. For this experiment, the coupling between the NASA Land Information System (LIS) and the WRF model is utilized to measure the impacts of the daily SPoRT/MODIS versus the monthly NCEP climatology GVFs. First, a spin-up run of the LIS is integrated for two years using the Noah LSM to ensure that the land surface fields reach an equilibrium state on the 4-km grid mesh used. Next, the spin-up LIS is run in two separate modes beginning on 1 June 2010, one continuing with the climatology GVFs while the

  11. Network protocols for real-time applications

    NASA Technical Reports Server (NTRS)

    Johnson, Marjory J.

    1987-01-01

    The Fiber Distributed Data Interface (FDDI) and the SAE AE-9B High Speed Ring Bus (HSRB) are emerging standards for high-performance token ring local area networks. FDDI was designed to be a general-purpose high-performance network. HSRB was designed specifically for military real-time applications. A workshop was conducted at NASA Ames Research Center in January, 1987 to compare and contrast these protocols with respect to their ability to support real-time applications. This report summarizes workshop presentations and includes an independent comparison of the two protocols. A conclusion reached at the workshop was that current protocols for the upper layers of the Open Systems Interconnection (OSI) network model are inadequate for real-time applications.

  12. Real-Time Confocal Imaging Of The Living Eye

    NASA Astrophysics Data System (ADS)

    Jester, James V.; Cavanagh, H. Dwight; Essepian, John; Shields, William J.; Lemp, Michael A.

    1989-12-01

    In 1986, we adapted the Tandem Scanning Reflected Light Microscope of Petran and Hadraysky to permit non-invasive, confocal imaging of the living eye in real-time. We were first to obtain stable, confocal optical sections in vivo, from human and animal eyes. Using confocal imaging systems we have now studied living, normal volunteers, rabbits, cats and primates sequentially, non-invasively, and in real-time. The continued development of real-time confocal imaging systems will unlock the door to a new field of cell biology involving for the first time the study of dynamic cellular processes in living organ systems. Towards this end we have concentrated our initial studies on three areas (1) evaluation of confocal microscope systems for real-time image acquisition, (2) studies of the living normal cornea (epithelium, stroma, endothelium) in human and other species; and (3) sequential wound-healing responses in the cornea in single animals to lamellar-keratectomy injury (cellular migration, inflammation, scarring). We believe that this instrument represents an important, new paradigm for research in cell biology and pathology and that it will fundamentally alter all experimental and clinical approaches in future years.

  13. Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning.

    PubMed

    Xu, Tao; Xiao, Na; Zhai, Xiaolong; Kwan Chan, Pak; Tin, Chung

    2018-02-01

    Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

  14. A real-time programming system.

    PubMed

    Townsend, H R

    1979-03-01

    The paper describes a Basic Operating and Scheduling System (BOSS) designed for a small computer. User programs are organised as self-contained modular 'processes' and the way in which the scheduler divides the time of the computer equally between them, while arranging for any process which has to respond to an interrupt from a peripheral device to be given the necessary priority, is described in detail. Next the procedures provided by the operating system to organise communication between processes are described, and how they are used to construct dynamically self-modifying real-time systems. Finally, the general philosophy of BOSS and applications to a multi-processor assembly are discussed.

  15. Towards a real-time interface between a biomimetic model of sensorimotor cortex and a robotic arm

    PubMed Central

    Dura-Bernal, Salvador; Chadderdon, George L; Neymotin, Samuel A; Francis, Joseph T; Lytton, William W

    2015-01-01

    Brain-machine interfaces can greatly improve the performance of prosthetics. Utilizing biomimetic neuronal modeling in brain machine interfaces (BMI) offers the possibility of providing naturalistic motor-control algorithms for control of a robotic limb. This will allow finer control of a robot, while also giving us new tools to better understand the brain’s use of electrical signals. However, the biomimetic approach presents challenges in integrating technologies across multiple hardware and software platforms, so that the different components can communicate in real-time. We present the first steps in an ongoing effort to integrate a biomimetic spiking neuronal model of motor learning with a robotic arm. The biomimetic model (BMM) was used to drive a simple kinematic two-joint virtual arm in a motor task requiring trial-and-error convergence on a single target. We utilized the output of this model in real time to drive mirroring motion of a Barrett Technology WAM robotic arm through a user datagram protocol (UDP) interface. The robotic arm sent back information on its joint positions, which was then used by a visualization tool on the remote computer to display a realistic 3D virtual model of the moving robotic arm in real time. This work paves the way towards a full closed-loop biomimetic brain-effector system that can be incorporated in a neural decoder for prosthetic control, to be used as a platform for developing biomimetic learning algorithms for controlling real-time devices. PMID:26709323

  16. Application of real-time database to LAMOST control system

    NASA Astrophysics Data System (ADS)

    Xu, Lingzhe; Xu, Xinqi

    2004-09-01

    The QNX based real time database is one of main features for Large sky Area Multi-Object fiber Spectroscopic Telescope's (LAMOST) control system, which serves as a storage and platform for data flow, recording and updating timely various status of moving components in the telescope structure as well as environmental parameters around it. The database joins harmonically in the administration of the Telescope Control System (TCS). The paper presents methodology and technique tips in designing the EMPRESS database GUI software package, such as the dynamic creation of control widgets, dynamic query and share memory. The seamless connection between EMPRESS and the graphical development tool of QNX"s Photon Application Builder (PhAB) has been realized, and so have the Windows look and feel yet under Unix-like operating system. In particular, the real time feature of the database is analyzed that satisfies the needs of the control system.

  17. Real-time tracking of tumor motions and deformations along the leaf travel direction with the aid of a synchronized dynamic MLC leaf sequencer.

    PubMed

    Tacke, Martin; Nill, Simeon; Oelfke, Uwe

    2007-11-21

    Advanced radiotherapeutical techniques like intensity-modulated radiation therapy (IMRT) are based on an accurate knowledge of the location of the radiation target. An accurate dose delivery, therefore, requires a method to account for the inter- and intrafractional target motion and the target deformation occurring during the course of treatment. A method to compensate in real time for changes in the position and shape of the target is the use of a dynamic multileaf collimator (MLC) technique which can be devised to automatically arrange the treatment field according to real-time image information. So far, various approaches proposed for leaf sequencers have had to rely on a priori known target motion data and have aimed to optimize the overall treatment time. Since for a real-time dose delivery the target motion is not known a priori, the velocity range of the leading leaves is restricted by a safety margin to c x v(max) while the following leaves can travel with an additional maximum speed to compensate for the respective target movements. Another aspect to be considered is the tongue and groove effect. A uniform radiation field can only be achieved if the leaf movements are synchronized. The method presented in this note is the first to combine a synchronizing sequencer and real-time tracking with a dynamic MLC. The newly developed algorithm is capable of online optimizing the leaf velocities by minimizing the overall treatment time while at the same time it synchronizes the leaf trajectories in order to avoid the tongue and groove effect. The simultaneous synchronization is performed with the help of an online-calculated mid-time leaf trajectory which is common for all leaf pairs and which takes into account the real-time target motion and deformation information.

  18. A Conceptual Level Design for a Static Scheduler for Hard Real-Time Systems

    DTIC Science & Technology

    1988-03-01

    The design of hard real - time systems is gaining a great deal of attention in the software engineering field as more and more real-world processes are...for these hard real - time systems . PSDL, as an executable design language, is supported by an execution support system consisting of a static scheduler, dynamic scheduler, and translator.

  19. Model compilation for real-time planning and diagnosis with feedback

    NASA Technical Reports Server (NTRS)

    Barrett, Anthony

    2005-01-01

    This paper describes MEXEC, an implemented micro executive that compiles a device model that can have feedback into a structure for subsequent evaluation. This system computes both the most likely current device mode from n sets of sensor measurements and the n-1 step reconfiguration plan that is most likely to result in reaching a target mode - if such a plan exists. A user tunes the system by increasing n to improve system capability at the cost of real-time performance.

  20. Analysis of real-time mixture cytotoxicity data following repeated exposure using BK/TD models.

    PubMed

    Teng, S; Tebby, C; Barcellini-Couget, S; De Sousa, G; Brochot, C; Rahmani, R; Pery, A R R

    2016-08-15

    Cosmetic products generally consist of multiple ingredients. Thus, cosmetic risk assessment has to deal with mixture toxicity on a long-term scale which means it has to be assessed in the context of repeated exposure. Given that animal testing has been banned for cosmetics risk assessment, in vitro assays allowing long-term repeated exposure and adapted for in vitro - in vivo extrapolation need to be developed. However, most in vitro tests only assess short-term effects and consider static endpoints which hinder extrapolation to realistic human exposure scenarios where concentration in target organs is varies over time. Thanks to impedance metrics, real-time cell viability monitoring for repeated exposure has become possible. We recently constructed biokinetic/toxicodynamic models (BK/TD) to analyze such data (Teng et al., 2015) for three hepatotoxic cosmetic ingredients: coumarin, isoeugenol and benzophenone-2. In the present study, we aim to apply these models to analyze the dynamics of mixture impedance data using the concepts of concentration addition and independent action. Metabolic interactions between the mixture components were investigated, characterized and implemented in the models, as they impacted the actual cellular exposure. Indeed, cellular metabolism following mixture exposure induced a quick disappearance of the compounds from the exposure system. We showed that isoeugenol substantially decreased the metabolism of benzophenone-2, reducing the disappearance of this compound and enhancing its in vitro toxicity. Apart from this metabolic interaction, no mixtures showed any interaction, and all binary mixtures were successfully modeled by at least one model based on exposure to the individual compounds. Copyright © 2016 Elsevier Inc. All rights reserved.

  1. Geomagnetic Observatory Data for Real-Time Applications

    NASA Astrophysics Data System (ADS)

    Love, J. J.; Finn, C. A.; Rigler, E. J.; Kelbert, A.; Bedrosian, P.

    2015-12-01

    The global network of magnetic observatories represents a unique collective asset for the scientific community. Historically, magnetic observatories have supported global magnetic-field mapping projects and fundamental research of the Earth's interior and surrounding space environment. More recently, real-time data streams from magnetic observatories have become an important contributor to multi-sensor, operational monitoring of evolving space weather conditions, especially during magnetic storms. In this context, the U.S. Geological Survey (1) provides real-time observatory data to allied space weather monitoring projects, including those of NOAA, the U.S. Air Force, NASA, several international agencies, and private industry, (2) collaborates with Schlumberger to provide real-time geomagnetic data needed for directional drilling for oil and gas in Alaska, (3) develops products for real-time evaluation of hazards for the electric-power grid industry that are associated with the storm-time induction of geoelectric fields in the Earth's conducting lithosphere. In order to implement strategic priorities established by the USGS Natural Hazards Mission Area and the National Science and Technology Council, and with a focus on developing new real-time products, the USGS is (1) leveraging data management protocols already developed by the USGS Earthquake Program, (2) developing algorithms for mapping geomagnetic activity, a collaboration with NASA and NOAA, (3) supporting magnetotelluric surveys and developing Earth conductivity models, a collaboration with Oregon State University and the NSF's EarthScope Program, (4) studying the use of geomagnetic activity maps and Earth conductivity models for real-time estimation of geoelectric fields, (5) initiating geoelectric monitoring at several observatories, (6) validating real-time estimation algorithms against historical geomagnetic and geoelectric data. The success of these long-term projects is subject to funding constraints

  2. PERTS: A Prototyping Environment for Real-Time Systems

    NASA Technical Reports Server (NTRS)

    Liu, Jane W. S.; Lin, Kwei-Jay; Liu, C. L.

    1993-01-01

    PERTS is a prototyping environment for real-time systems. It is being built incrementally and will contain basic building blocks of operating systems for time-critical applications, tools, and performance models for the analysis, evaluation and measurement of real-time systems and a simulation/emulation environment. It is designed to support the use and evaluation of new design approaches, experimentations with alternative system building blocks, and the analysis and performance profiling of prototype real-time systems.

  3. Design Aids for Real-Time Systems (DARTS)

    NASA Technical Reports Server (NTRS)

    Szulewski, P. A.

    1982-01-01

    Design-Aids for Real-Time Systems (DARTS) is a tool that assists in defining embedded computer systems through tree structured graphics, military standard documentation support, and various analyses including automated Software Science parameter counting and metrics calculation. These analyses provide both static and dynamic design quality feedback which can potentially aid in producing efficient, high quality software systems.

  4. Real-time hierarchically distributed processing network interaction simulation

    NASA Technical Reports Server (NTRS)

    Zimmerman, W. F.; Wu, C.

    1987-01-01

    The Telerobot Testbed is a hierarchically distributed processing system which is linked together through a standard, commercial Ethernet. Standard Ethernet systems are primarily designed to manage non-real-time information transfer. Therefore, collisions on the net (i.e., two or more sources attempting to send data at the same time) are managed by randomly rescheduling one of the sources to retransmit at a later time interval. Although acceptable for transmitting noncritical data such as mail, this particular feature is unacceptable for real-time hierarchical command and control systems such as the Telerobot. Data transfer and scheduling simulations, such as token ring, offer solutions to collision management, but do not appropriately characterize real-time data transfer/interactions for robotic systems. Therefore, models like these do not provide a viable simulation environment for understanding real-time network loading. A real-time network loading model is being developed which allows processor-to-processor interactions to be simulated, collisions (and respective probabilities) to be logged, collision-prone areas to be identified, and network control variable adjustments to be reentered as a means of examining and reducing collision-prone regimes that occur in the process of simulating a complete task sequence.

  5. Assimilation of Real-Time Satellite And Human Sensor Networks for Modeling Natural Disasters

    NASA Astrophysics Data System (ADS)

    Aulov, O.; Halem, M.; Lary, D. J.

    2011-12-01

    We describe the development of underlying technologies needed to address the merging of a web of real time satellite sensor Web (SSW) and Human Sensor Web (HSW) needed to augment the US response to extreme events. As an initial prototyping step and use case scenario, we consider the development of two major system tools that can be transitioned from research to the responding operational agency for mitigating coastal oil spills. These tools consist of the capture of Situation Aware (SA) Social Media (SM) Data, and assimilation of the processed information into forecasting models to provide incident decision managers with interactive virtual spatial temporal animations superimposed with probabilistic data estimates. The system methodologies are equally applicable to the wider class of extreme events such as plume dispersions from volcanoes or massive fires, major floods, hurricane impacts, radioactive isotope dispersions from nuclear accidents, etc. A successful feasibility demonstration of this technology has been shown in the case of the Deepwater Horizon Oil Spill where Human Sensor Networks have been combined with a geophysical model to perform parameter assessments. Flickr images of beached oil were mined from the spill area, geolocated and timestamped and converted into geophysical data. This data was incorporated into General NOAA Operational Modeling Environment (GNOME), a Lagrangian forecast model that uses near real-time surface winds, ocean currents, and satellite shape profiles of oil to generate a forecast of plume movement. As a result, improved estimates of diffusive coefficients and rates of oil spill were determined. Current approaches for providing satellite derived oil distributions are collected from a satellite sensor web of operational and research sensors from many countries, and a manual analysis is performed by NESDIS. A real time SA HSW processing system based on geolocated SM data from sources such as Twitter, Flickr, YouTube etc., greatly

  6. Dynamic coupling of three hydrodynamic models

    NASA Astrophysics Data System (ADS)

    Hartnack, J. N.; Philip, G. T.; Rungoe, M.; Smith, G.; Johann, G.; Larsen, O.; Gregersen, J.; Butts, M. B.

    2008-12-01

    The need for integrated modelling is evidently present within the field of flood management and flood forecasting. Engineers, modellers and managers are faced with flood problems which transcend the classical hydrodynamic fields of urban, river and coastal flooding. Historically the modeller has been faced with having to select one hydrodynamic model to cover all the aspects of the potentially complex dynamics occurring in a flooding situation. Such a single hydrodynamic model does not cover all dynamics of flood modelling equally well. Thus the ideal choice may in fact be a combination of models. Models combining two numerical/hydrodynamic models are becoming more standard, typically these models combine a 1D river model with a 2D overland flow model or alternatively a 1D sewer/collection system model with a 2D overland solver. In complex coastal/urban areas the flood dynamics may include rivers/streams, collection/storm water systems along with the overland flow. The dynamics within all three areas is of the same time scale and there is feedback in the system across the couplings. These two aspects dictate a fully dynamic three way coupling as opposed to running the models sequentially. It will be shown that the main challenges of the three way coupling are time step issues related to the difference in numerical schemes used in the three model components and numerical instabilities caused by the linking of the model components. MIKE FLOOD combines the models MIKE 11, MIKE 21 and MOUSE into one modelling framework which makes it possible to couple any combination of river, urban and overland flow fully dynamically. The MIKE FLOOD framework will be presented with an overview of the coupling possibilities. The flood modelling concept will be illustrated through real life cases in Australia and in Germany. The real life cases reflect dynamics and interactions across all three model components which are not possible to reproduce using a two-way coupling alone. The

  7. A modified elastance model to control mock ventricles in real-time: numerical and experimental validation.

    PubMed

    Colacino, Francesco Maria; Moscato, Francesco; Piedimonte, Fabio; Danieli, Guido; Nicosia, Salvatore; Arabia, Maurizio

    2008-01-01

    This article describes an elastance-based mock ventricle able to reproduce the correct ventricular pressure-volume relationship and its correct interaction with the hydraulic circuit connected to it. A real-time control of the mock ventricle was obtained by a new left ventricular mathematical model including resistive and inductive terms added to the classical Suga-Sagawa elastance model throughout the whole cardiac cycle. A valved piston pump was used to mimic the left ventricle. The pressure measured into the pump chamber was fed back into the mathematical model and the calculated reference left ventricular volume was used to drive the piston. Results show that the classical model is very sensitive to pressure disturbances, especially during the filling phase, while the modified model is able to filter out the oscillations thus eliminating their detrimental effects. The presented model is thus suitable to control mock ventricles in real-time, where sudden pressure disturbances represent a key issue and are not negligible. This real-time controlled mock ventricle is able to reproduce the elastance mechanism of a natural ventricle by mimicking its preload (mean atrial pressure) and afterload (mean aortic pressure) sensitivity, i.e., the Starling law. Therefore, it can be used for designing and testing cardiovascular prostheses due to its capability to reproduce the correct ventricle-vascular system interaction.

  8. Resource Limitation Issues In Real-Time Intelligent Systems

    NASA Astrophysics Data System (ADS)

    Green, Peter E.

    1986-03-01

    This paper examines resource limitation problems that can occur in embedded AI systems which have to run in real-time. It does this by examining two case studies. The first is a system which acoustically tracks low-flying aircraft and has the problem of interpreting a high volume of often ambiguous input data to produce a model of the system's external world. The second is a robotics problem in which the controller for a robot arm has to dynamically plan the order in which to pick up pieces from a conveyer belt and sort them into bins. In this case the system starts with a continuously changing model of its environment and has to select which action to perform next. This latter case emphasizes the issues in designing a system which must operate in an uncertain and rapidly changing environment. The first system uses a distributed HEARSAY methodology running on multiple processors. It is shown, in this case, how the com-binatorial growth of possible interpretation of the input data can require large and unpredictable amounts of computer resources for data interpretation. Techniques are presented which achieve real-time operation by limiting the combinatorial growth of alternate hypotheses and processing those hypotheses that are most likely to lead to meaningful interpretation of the input data. The second system uses a decision tree approach to generate and evaluate possible plans of action. It is shown how the combina-torial growth of possible alternate plans can, as in the previous case, require large and unpredictable amounts of computer time to evalu-ate and select from amongst the alternative. The use of approximate decisions to limit the amount of computer time needed is discussed. The use of concept of using incremental evidence is then introduced and it is shown how this can be used as the basis of systems that can combine heuristic and approximate evidence in making real-time decisions.

  9. A Scheduling Algorithm for Replicated Real-Time Tasks

    NASA Technical Reports Server (NTRS)

    Yu, Albert C.; Lin, Kwei-Jay

    1991-01-01

    We present an algorithm for scheduling real-time periodic tasks on a multiprocessor system under fault-tolerant requirement. Our approach incorporates both the redundancy and masking technique and the imprecise computation model. Since the tasks in hard real-time systems have stringent timing constraints, the redundancy and masking technique are more appropriate than the rollback techniques which usually require extra time for error recovery. The imprecise computation model provides flexible functionality by trading off the quality of the result produced by a task with the amount of processing time required to produce it. It therefore permits the performance of a real-time system to degrade gracefully. We evaluate the algorithm by stochastic analysis and Monte Carlo simulations. The results show that the algorithm is resilient under hardware failures.

  10. Model of Four-Dimensional Sub-Proton Euclidean Space with Real Time for Valence Quarks. Lagrangian Mechanics

    NASA Astrophysics Data System (ADS)

    Kreymer, E. L.

    2018-06-01

    The model of Euclidean space with imaginary time used in sub-hadron physics uses only part of it since this part is isomorphic to Minkowski space and has the velocity limit 0 ≤ ||v Ei|| ≤ 1. The model of four-dimensional Euclidean space with real time (E space), in which 0 ≤ ||v E|| ≤ ∞ is investigated. The vectors of this space have E-invariants, equal or analogous to the invariants of Minkowski space. All relations between physical quantities in E-space, after they are mapped into Minkowski space, satisfy the principles of SRT and are Lorentz-invariant, and the velocity of light corresponds to infinite velocity. Results obtained in the model are different from the physical laws in Minkowski space. Thus, from the model of the Lagrangian mechanics of quarks in a centrally symmetric attractive potential it follows that the energy-mass of a quark decreases with increase of the velocity and is equal to zero for v = ∞. This made it possible to establish the conditions of emission and absorption of gluons by quarks. The effect of emission of gluons by high-energy quarks was discovered experimentally significantly earlier. The model describes for the first time the dynamic coupling of the masses of constituent and current quarks and reveals new possibilities in the study of intrahardon space. The classical trajectory of the oscillation of quarks in protons is described.

  11. A real-time simulator of a turbofan engine

    NASA Technical Reports Server (NTRS)

    Litt, Jonathan S.; Delaat, John C.; Merrill, Walter C.

    1989-01-01

    A real-time digital simulator of a Pratt and Whitney F100 engine has been developed for real-time code verification and for actuator diagnosis during full-scale engine testing. This self-contained unit can operate in an open-loop stand-alone mode or as part of closed-loop control system. It can also be used for control system design and development. Tests conducted in conjunction with the NASA Advanced Detection, Isolation, and Accommodation program show that the simulator is a valuable tool for real-time code verification and as a real-time actuator simulator for actuator fault diagnosis. Although currently a small perturbation model, advances in microprocessor hardware should allow the simulator to evolve into a real-time, full-envelope, full engine simulation.

  12. Can Subjects be Guided to Optimal Decisions The Use of a Real-Time Training Intervention Model

    DTIC Science & Technology

    2016-06-01

    execution of the task and may then be analyzed to determine if there is correlation between designated factors (scores, proportion of time in each...state with their decision performance in real time could allow training systems to be designed to tailor training to the individual decision maker...release; distribution is unlimited CAN SUBJECTS BE GUIDED TO OPTIMAL DECISIONS? THE USE OF A REAL- TIME TRAINING INTERVENTION MODEL by Travis D

  13. Early warning by near-real time disturbance monitoring (Invited)

    NASA Astrophysics Data System (ADS)

    Verbesselt, J.; Zeileis, A.; Herold, M.

    2013-12-01

    Near real-time monitoring of ecosystem disturbances is critical for rapidly assessing and addressing impacts on carbon dynamics, biodiversity, and socio-ecological processes. Satellite remote sensing enables cost-effective and accurate monitoring at frequent time steps over large areas. Yet, generic methods to detect disturbances within newly captured satellite images are lacking. We propose a multi-purpose time-series-based disturbance detection approach that identifies and models stable historical variation to enable change detection within newly acquired data. Satellite image time series of vegetation greenness provide a global record of terrestrial vegetation productivity over the past decades. Here, we assess and demonstrate the method by applying it to (1) real-world satellite greenness image time series between February 2000 and July 2011 covering Somalia to detect drought-related vegetation disturbances (2) landsat image time series to detect forest disturbances. First, results illustrate that disturbances are successfully detected in near real-time while being robust to seasonality and noise. Second, major drought-related disturbance corresponding with most drought-stressed regions in Somalia are detected from mid-2010 onwards. Third, the method can be applied to landsat image time series having a lower temporal data density. Furthermore the method can analyze in-situ or satellite data time series of biophysical indicators from local to global scale since it is fast, does not depend on thresholds and does not require time series gap filling. While the data and methods used are appropriate for proof-of-concept development of global scale disturbance monitoring, specific applications (e.g., drought or deforestation monitoring) mandates integration within an operational monitoring framework. Furthermore, the real-time monitoring method is implemented in open-source environment and is freely available in the BFAST package for R software. Information

  14. Real-time decay of a highly excited charge carrier in the one-dimensional Holstein model

    NASA Astrophysics Data System (ADS)

    Dorfner, F.; Vidmar, L.; Brockt, C.; Jeckelmann, E.; Heidrich-Meisner, F.

    2015-03-01

    We study the real-time dynamics of a highly excited charge carrier coupled to quantum phonons via a Holstein-type electron-phonon coupling. This is a prototypical example for the nonequilibrium dynamics in an interacting many-body system where excess energy is transferred from electronic to phononic degrees of freedom. We use diagonalization in a limited functional space (LFS) to study the nonequilibrium dynamics on a finite one-dimensional chain. This method agrees with exact diagonalization and the time-evolving block-decimation method, in both the relaxation regime and the long-time stationary state, and among these three methods it is the most efficient and versatile one for this problem. We perform a comprehensive analysis of the time evolution by calculating the electron, phonon and electron-phonon coupling energies, and the electronic momentum distribution function. The numerical results are compared to analytical solutions for short times, for a small hopping amplitude and for a weak electron-phonon coupling. In the latter case, the relaxation dynamics obtained from the Boltzmann equation agrees very well with the LFS data. We also study the time dependence of the eigenstates of the single-site reduced density matrix, which defines the so-called optimal phonon modes. We discuss their structure in nonequilibrium and the distribution of their weights. Our analysis shows that the structure of optimal phonon modes contains very useful information for the interpretation of the numerical data.

  15. Real-Time Visualization of Network Behaviors for Situational Awareness

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

    Best, Daniel M.; Bohn, Shawn J.; Love, Douglas V.

    Plentiful, complex, and dynamic data make understanding the state of an enterprise network difficult. Although visualization can help analysts understand baseline behaviors in network traffic and identify off-normal events, visual analysis systems often do not scale well to operational data volumes (in the hundreds of millions to billions of transactions per day) nor to analysis of emergent trends in real-time data. We present a system that combines multiple, complementary visualization techniques coupled with in-stream analytics, behavioral modeling of network actors, and a high-throughput processing platform called MeDICi. This system provides situational understanding of real-time network activity to help analysts takemore » proactive response steps. We have developed these techniques using requirements gathered from the government users for which the tools are being developed. By linking multiple visualization tools to a streaming analytic pipeline, and designing each tool to support a particular kind of analysis (from high-level awareness to detailed investigation), analysts can understand the behavior of a network across multiple levels of abstraction.« less

  16. Real-time Avatar Animation from a Single Image.

    PubMed

    Saragih, Jason M; Lucey, Simon; Cohn, Jeffrey F

    2011-01-01

    A real time facial puppetry system is presented. Compared with existing systems, the proposed method requires no special hardware, runs in real time (23 frames-per-second), and requires only a single image of the avatar and user. The user's facial expression is captured through a real-time 3D non-rigid tracking system. Expression transfer is achieved by combining a generic expression model with synthetically generated examples that better capture person specific characteristics. Performance of the system is evaluated on avatars of real people as well as masks and cartoon characters.

  17. Real-time Avatar Animation from a Single Image

    PubMed Central

    Saragih, Jason M.; Lucey, Simon; Cohn, Jeffrey F.

    2014-01-01

    A real time facial puppetry system is presented. Compared with existing systems, the proposed method requires no special hardware, runs in real time (23 frames-per-second), and requires only a single image of the avatar and user. The user’s facial expression is captured through a real-time 3D non-rigid tracking system. Expression transfer is achieved by combining a generic expression model with synthetically generated examples that better capture person specific characteristics. Performance of the system is evaluated on avatars of real people as well as masks and cartoon characters. PMID:24598812

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

    NASA Astrophysics Data System (ADS)

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

    2012-03-01

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

  19. Use of a Bacterial Luciferase Monitoring System To Estimate Real-Time Dynamics of Intracellular Metabolism in Escherichia coli.

    PubMed

    Shimada, Tomohiro; Tanaka, Kan

    2016-10-01

    Regulation of central carbon metabolism has long been an important research subject in every organism. While the dynamics of metabolic flows during changes in available carbon sources have been estimated based on changes in metabolism-related gene expression, as well as on changes in the metabolome, the flux change itself has scarcely been measured because of technical difficulty, which has made conclusions elusive in many cases. Here, we used a monitoring system employing Vibrio fischeri luciferase to probe the intracellular metabolic condition in Escherichia coli Using a batch culture provided with a limited amount of glucose, we performed a time course analysis, where the predominant carbon source shifts from glucose to acetate, and identified a series of sequential peaks in the luciferase activity (peaks 1 to 4). Two major peaks, peaks 1 and 3, were considered to correspond to the glucose and acetate consuming phases, respectively, based on the glucose, acetate, and dissolved oxygen concentrations in the medium. The pattern of these peaks was changed by the addition of a different carbon source or by an increasing concentration of glucose, which was consistent with the present model. Genetically, mutations involved in glycolysis or the tricarboxylic acid (TCA) cycle/gluconeogenesis specifically affected peak 1 or peak 3, respectively, as expected from the corresponding metabolic phase. Intriguingly, mutants for the acetate excretion pathway showed a phenotype of extended peak 2 and delayed transition to the TCA cycle/gluconeogenesis phase, which suggests that peak 2 represents the metabolic transition phase. These results indicate that the bacterial luciferase monitoring system is useful to understand the real-time dynamics of metabolism in living bacterial cells. Intracellular metabolic flows dynamically change during shifts in available carbon sources. However, because of technical difficulty, the flux change has scarcely been measured in living cells. Here

  20. Electron dynamics in complex environments with real-time time dependent density functional theory in a QM-MM framework

    NASA Astrophysics Data System (ADS)

    Morzan, Uriel N.; Ramírez, Francisco F.; Oviedo, M. Belén; Sánchez, Cristián G.; Scherlis, Damián A.; Lebrero, Mariano C. González

    2014-04-01

    This article presents a time dependent density functional theory (TDDFT) implementation to propagate the Kohn-Sham equations in real time, including the effects of a molecular environment through a Quantum-Mechanics Molecular-Mechanics (QM-MM) hamiltonian. The code delivers an all-electron description employing Gaussian basis functions, and incorporates the Amber force-field in the QM-MM treatment. The most expensive parts of the computation, comprising the commutators between the hamiltonian and the density matrix—required to propagate the electron dynamics—, and the evaluation of the exchange-correlation energy, were migrated to the CUDA platform to run on graphics processing units, which remarkably accelerates the performance of the code. The method was validated by reproducing linear-response TDDFT results for the absorption spectra of several molecular species. Two different schemes were tested to propagate the quantum dynamics: (i) a leap-frog Verlet algorithm, and (ii) the Magnus expansion to first-order. These two approaches were confronted, to find that the Magnus scheme is more efficient by a factor of six in small molecules. Interestingly, the presence of iron was found to seriously limitate the length of the integration time step, due to the high frequencies associated with the core-electrons. This highlights the importance of pseudopotentials to alleviate the cost of the propagation of the inner states when heavy nuclei are present. Finally, the methodology was applied to investigate the shifts induced by the chemical environment on the most intense UV absorption bands of two model systems of general relevance: the formamide molecule in water solution, and the carboxy-heme group in Flavohemoglobin. In both cases, shifts of several nanometers are observed, consistently with the available experimental data.

  1. Investigating the potential of employer-based "real-time" ridesharing.

    DOT National Transportation Integrated Search

    2015-01-01

    The reemergence of ridesharing as a desirable means of travel is partly attributed to the role mobile phone and social networking technologies could play in enabling the real-time (or dynamic) matching of passengers and drivers producing ...

  2. Real-time imaging of subarachnoid hemorrhage in piglets with electrical impedance tomography.

    PubMed

    Dai, Meng; Wang, Liang; Xu, Canhua; Li, Lianfeng; Gao, Guodong; Dong, Xiuzhen

    2010-09-01

    Subarachnoid hemorrhage (SAH) is one of the most severe medical emergencies in neurosurgery. Early detection or diagnosis would significantly reduce the rate of disability and mortality, and improve the prognosis of the patients. Although the present medical imaging techniques generally have high sensitivity to identify bleeding, the use of an additional, non-invasive imaging technique capable of continuously monitoring SAH is required to prevent contingent bleeding or re-bleeding. In this study, electrical impedance tomography (EIT) was applied to detect the onset of SAH modeled on eight piglets in real time, with the subsequent process being monitored continuously. The experimental SAH model was introduced by one-time injection of 5 ml fresh autologous arterial blood into the cisterna magna. Results showed that resistivity variations within the brain caused by the added blood could be detected using the EIT method and may be associated not only with the resistivity difference among brain tissues, but also with variations of cerebrospinal fluid dynamics. In conclusion, EIT has unique potential for use in clinical practice to provide invaluable real-time neuroimaging data for SAH after the improvement of electrode design, anisotropic realistic modeling and instrumentation.

  3. Designing a fuzzy scheduler for hard real-time systems

    NASA Technical Reports Server (NTRS)

    Yen, John; Lee, Jonathan; Pfluger, Nathan; Natarajan, Swami

    1992-01-01

    In hard real-time systems, tasks have to be performed not only correctly, but also in a timely fashion. If timing constraints are not met, there might be severe consequences. Task scheduling is the most important problem in designing a hard real-time system, because the scheduling algorithm ensures that tasks meet their deadlines. However, the inherent nature of uncertainty in dynamic hard real-time systems increases the problems inherent in scheduling. In an effort to alleviate these problems, we have developed a fuzzy scheduler to facilitate searching for a feasible schedule. A set of fuzzy rules are proposed to guide the search. The situation we are trying to address is the performance of the system when no feasible solution can be found, and therefore, certain tasks will not be executed. We wish to limit the number of important tasks that are not scheduled.

  4. Detection of time delays and directional interactions based on time series from complex dynamical systems

    NASA Astrophysics Data System (ADS)

    Ma, Huanfei; Leng, Siyang; Tao, Chenyang; Ying, Xiong; Kurths, Jürgen; Lai, Ying-Cheng; Lin, Wei

    2017-07-01

    Data-based and model-free accurate identification of intrinsic time delays and directional interactions is an extremely challenging problem in complex dynamical systems and their networks reconstruction. A model-free method with new scores is proposed to be generally capable of detecting single, multiple, and distributed time delays. The method is applicable not only to mutually interacting dynamical variables but also to self-interacting variables in a time-delayed feedback loop. Validation of the method is carried out using physical, biological, and ecological models and real data sets. Especially, applying the method to air pollution data and hospital admission records of cardiovascular diseases in Hong Kong reveals the major air pollutants as a cause of the diseases and, more importantly, it uncovers a hidden time delay (about 30-40 days) in the causal influence that previous studies failed to detect. The proposed method is expected to be universally applicable to ascertaining and quantifying subtle interactions (e.g., causation) in complex systems arising from a broad range of disciplines.

  5. Operational modeling system with dynamic-wave routing

    USGS Publications Warehouse

    Ishii, A.L.; Charlton, T.J.; Ortel, T.W.; Vonnahme, C.C.; ,

    1998-01-01

    A near real-time streamflow-simulation system utilizing continuous-simulation rainfall-runoff generation with dynamic-wave routing is being developed by the U.S. Geological Survey in cooperation with the Du Page County Department of Environmental Concerns for a 24-kilometer reach of Salt Creek in Du Page County, Illinois. This system is needed in order to more effectively manage the Elmhurst Quarry Flood Control Facility, an off-line stormwater diversion reservoir located along Salt Creek. Near real time simulation capabilities will enable the testing and evaluation of potential rainfall, diversion, and return-flow scenarios on water-surface elevations along Salt Creek before implementing diversions or return-flows. The climatological inputs for the continuous-simulation rainfall-runoff model, Hydrologic Simulation Program - FORTRAN (HSPF) are obtained by Internet access and from a network of radio-telemetered precipitation gages reporting to a base-station computer. The unit area runoff time series generated from HSPF are the input for the dynamic-wave routing model. Full Equations (FEQ). The Generation and Analysis of Model Simulation Scenarios (GENSCN) interface is used as a pre- and post-processor for managing input data and displaying and managing simulation results. The GENSCN interface includes a variety of graphical and analytical tools for evaluation and quick visualization of the results of operational scenario simulations and thereby makes it possible to obtain the full benefit of the fully distributed dynamic routing results.

  6. Building flexible real-time systems using the Flex language

    NASA Technical Reports Server (NTRS)

    Kenny, Kevin B.; Lin, Kwei-Jay

    1991-01-01

    The design and implementation of a real-time programming language called Flex, which is a derivative of C++, are presented. It is shown how different types of timing requirements might be expressed and enforced in Flex, how they might be fulfilled in a flexible way using different program models, and how the programming environment can help in making binding and scheduling decisions. The timing constraint primitives in Flex are easy to use yet powerful enough to define both independent and relative timing constraints. Program models like imprecise computation and performance polymorphism can carry out flexible real-time programs. In addition, programmers can use a performance measurement tool that produces statistically correct timing models to predict the expected execution time of a program and to help make binding decisions. A real-time programming environment is also presented.

  7. Dynamic Price Vector Formation Model-Based Automatic Demand Response Strategy for PV-Assisted EV Charging Stations

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

    Chen, Qifang; Wang, Fei; Hodge, Bri-Mathias

    A real-time price (RTP)-based automatic demand response (ADR) strategy for PV-assisted electric vehicle (EV) Charging Station (PVCS) without vehicle to grid is proposed. The charging process is modeled as a dynamic linear program instead of the normal day-ahead and real-time regulation strategy, to capture the advantages of both global and real-time optimization. Different from conventional price forecasting algorithms, a dynamic price vector formation model is proposed based on a clustering algorithm to form an RTP vector for a particular day. A dynamic feasible energy demand region (DFEDR) model considering grid voltage profiles is designed to calculate the lower and uppermore » bounds. A deduction method is proposed to deal with the unknown information of future intervals, such as the actual stochastic arrival and departure times of EVs, which make the DFEDR model suitable for global optimization. Finally, both the comparative cases articulate the advantages of the developed methods and the validity in reducing electricity costs, mitigating peak charging demand, and improving PV self-consumption of the proposed strategy are verified through simulation scenarios.« less

  8. Real-Time Global Flood Estimation Using Satellite-Based Precipitation and a Coupled Land Surface and Routing Model

    NASA Technical Reports Server (NTRS)

    Wu, Huan; Adler, Robert F.; Tian, Yudong; Huffman, George J.; Li, Hongyi; Wang, JianJian

    2014-01-01

    A widely used land surface model, the Variable Infiltration Capacity (VIC) model, is coupled with a newly developed hierarchical dominant river tracing-based runoff-routing model to form the Dominant river tracing-Routing Integrated with VIC Environment (DRIVE) model, which serves as the new core of the real-time Global Flood Monitoring System (GFMS). The GFMS uses real-time satellite-based precipitation to derive flood monitoring parameters for the latitude band 50 deg. N - 50 deg. S at relatively high spatial (approximately 12 km) and temporal (3 hourly) resolution. Examples of model results for recent flood events are computed using the real-time GFMS (http://flood.umd.edu). To evaluate the accuracy of the new GFMS, the DRIVE model is run retrospectively for 15 years using both research-quality and real-time satellite precipitation products. Evaluation results are slightly better for the research-quality input and significantly better for longer duration events (3 day events versus 1 day events). Basins with fewer dams tend to provide lower false alarm ratios. For events longer than three days in areas with few dams, the probability of detection is approximately 0.9 and the false alarm ratio is approximately 0.6. In general, these statistical results are better than those of the previous system. Streamflow was evaluated at 1121 river gauges across the quasi-global domain. Validation using real-time precipitation across the tropics (30 deg. S - 30 deg. N) gives positive daily Nash-Sutcliffe Coefficients for 107 out of 375 (28%) stations with a mean of 0.19 and 51% of the same gauges at monthly scale with a mean of 0.33. There were poorer results in higher latitudes, probably due to larger errors in the satellite precipitation input.

  9. Real-time global flood estimation using satellite-based precipitation and a coupled land surface and routing model

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

    Wu, Huan; Adler, Robert F.; Tian, Yudong

    2014-03-01

    A widely used land surface model, the Variable Infiltration Capacity (VIC) model, is coupled with a newly developed hierarchical dominant river tracing-based runoff-routing model to form the Dominant river tracing-Routing Integrated with VIC Environment (DRIVE) model, which serves as the new core of the real-time Global Flood Monitoring System (GFMS). The GFMS uses real-time satellite-based precipitation to derive flood monitoring parameters for the latitude band 50°N–50°S at relatively high spatial (~12 km) and temporal (3 hourly) resolution. Examples of model results for recent flood events are computed using the real-time GFMS (http://flood.umd.edu). To evaluate the accuracy of the new GFMS,more » the DRIVE model is run retrospectively for 15 years using both research-quality and real-time satellite precipitation products. Evaluation results are slightly better for the research-quality input and significantly better for longer duration events (3 day events versus 1 day events). Basins with fewer dams tend to provide lower false alarm ratios. For events longer than three days in areas with few dams, the probability of detection is ~0.9 and the false alarm ratio is ~0.6. In general, these statistical results are better than those of the previous system. Streamflow was evaluated at 1121 river gauges across the quasi-global domain. Validation using real-time precipitation across the tropics (30°S–30°N) gives positive daily Nash-Sutcliffe Coefficients for 107 out of 375 (28%) stations with a mean of 0.19 and 51% of the same gauges at monthly scale with a mean of 0.33. Finally, there were poorer results in higher latitudes, probably due to larger errors in the satellite precipitation input.« less

  10. Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning

    NASA Astrophysics Data System (ADS)

    Xu, Tao; Xiao, Na; Zhai, Xiaolong; Chan, Pak Kwan; Tin, Chung

    2018-02-01

    Objective. Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). Approach. The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. Main results. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. Significance. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

  11. Real-time optical image processing techniques

    NASA Technical Reports Server (NTRS)

    Liu, Hua-Kuang

    1988-01-01

    Nonlinear real-time optical processing on spatial pulse frequency modulation has been pursued through the analysis, design, and fabrication of pulse frequency modulated halftone screens and the modification of micro-channel spatial light modulators (MSLMs). Micro-channel spatial light modulators are modified via the Fabry-Perot method to achieve the high gamma operation required for non-linear operation. Real-time nonlinear processing was performed using the halftone screen and MSLM. The experiments showed the effectiveness of the thresholding and also showed the needs of higher SBP for image processing. The Hughes LCLV has been characterized and found to yield high gamma (about 1.7) when operated in low frequency and low bias mode. Cascading of two LCLVs should also provide enough gamma for nonlinear processing. In this case, the SBP of the LCLV is sufficient but the uniformity of the LCLV needs improvement. These include image correlation, computer generation of holograms, pseudo-color image encoding for image enhancement, and associative-retrieval in neural processing. The discovery of the only known optical method for dynamic range compression of an input image in real-time by using GaAs photorefractive crystals is reported. Finally, a new architecture for non-linear multiple sensory, neural processing has been suggested.

  12. Dependable Real-Time Systems

    DTIC Science & Technology

    1991-09-30

    0196 or 413 545-0720 PI E-mail Address: krithi@nirvan.cs.umass.edu, stankovic(ocs.umass.edu Grant or Contract Title: Dependable Real - Time Systems Grant...Dependable Real - Time Systems " Grant or Contract Number: N00014-85-k-0398 L " Reporting Period: 1 Oct 87 - 30 Sep 91 , 2. Summary of Accomplishments ’ 2.1 Our...in developing a sound approach to scheduling tasks in complex real - time systems , (2) developed a real-time operating system kernel, a preliminary

  13. Computing Quantitative Characteristics of Finite-State Real-Time Systems

    DTIC Science & Technology

    1994-05-04

    Current methods for verifying real - time systems are essentially decision procedures that establish whether the system model satisfies a given...specification. We present a general method for computing quantitative information about finite-state real - time systems . We have developed algorithms that...our technique can be extended to a more general representation of real - time systems , namely, timed transition graphs. The algorithms presented in this

  14. Fractional-order in a macroeconomic dynamic model

    NASA Astrophysics Data System (ADS)

    David, S. A.; Quintino, D. D.; Soliani, J.

    2013-10-01

    In this paper, we applied the Riemann-Liouville approach in order to realize the numerical simulations to a set of equations that represent a fractional-order macroeconomic dynamic model. It is a generalization of a dynamic model recently reported in the literature. The aforementioned equations have been simulated for several cases involving integer and non-integer order analysis, with some different values to fractional order. The time histories and the phase diagrams have been plotted to visualize the effect of fractional order approach. The new contribution of this work arises from the fact that the macroeconomic dynamic model proposed here involves the public sector deficit equation, which renders the model more realistic and complete when compared with the ones encountered in the literature. The results reveal that the fractional-order macroeconomic model can exhibit a real reasonable behavior to macroeconomics systems and might offer greater insights towards the understanding of these complex dynamic systems.

  15. Estimating Real-Time Zenith Tropospheric Delay over Africa Using IGS-RTS Products

    NASA Astrophysics Data System (ADS)

    Abdelazeem, M.

    2017-12-01

    Zenith Tropospheric Delay (ZTD) is a crucial parameter for atmospheric modeling, severe weather monitoring and forecasting applications. Currently, the international global navigation satellite system (GNSS) real-time service (IGS-RTS) products are used extensively in real-time atmospheric modeling applications. The objective of this study is to develop a real time zenith tropospheric delay estimation model over Africa using the IGS-RTS products. The real-time ZTDs are estimated based on the real-time precise point positioning (PPP) solution. GNSS observations from a number of reference stations are processed over a period of 7 days. Then, the estimated real-time ZTDs are compared with the IGS tropospheric products counterparts. The findings indicate that the estimated real-time ZTDs have millimeter level accuracy in comparison with the IGS counterparts.

  16. Space Weather Forecasting at NOAA with Michigan's Geospace Model: Results from the First Year in Real-Time Operations

    NASA Astrophysics Data System (ADS)

    Cash, M. D.; Singer, H. J.; Millward, G. H.; Balch, C. C.; Toth, G.; Welling, D. T.

    2017-12-01

    In October 2016, the first version of the Geospace model was transitioned into real-time operations at NOAA Space Weather Prediction Center (SWPC). The Geospace model is a part of the Space Weather Modeling Framework (SWMF) developed at the University of Michigan, and the model simulates the full time-dependent 3D Geospace environment (Earth's magnetosphere, ring current and ionosphere) and predicts global space weather parameters such as induced magnetic perturbations in space and on Earth's surface. The current version of the Geospace model uses three coupled components of SWMF: the BATS-R-US global magnetosphere model, the Rice Convection Model (RCM) of the inner magnetosphere, and the Ridley Ionosphere electrodynamics Model (RIM). In the operational mode, SWMF/Geospace runs continually in real-time as long as there is new solar wind data arriving from a satellite at L1, either DSCOVR or ACE. We present an analysis of the overall performance of the Geospace model during the first year of real-time operations. Evaluation metrics include Kp, Dst, as well as regional magnetometer stations. We will also present initial results from new products, such as the AE index, available with the recent upgrade to the Geospace model.

  17. Real-Time Imaging System for the OpenPET

    NASA Astrophysics Data System (ADS)

    Tashima, Hideaki; Yoshida, Eiji; Kinouchi, Shoko; Nishikido, Fumihiko; Inadama, Naoko; Murayama, Hideo; Suga, Mikio; Haneishi, Hideaki; Yamaya, Taiga

    2012-02-01

    The OpenPET and its real-time imaging capability have great potential for real-time tumor tracking in medical procedures such as biopsy and radiation therapy. For the real-time imaging system, we intend to use the one-pass list-mode dynamic row-action maximum likelihood algorithm (DRAMA) and implement it using general-purpose computing on graphics processing units (GPGPU) techniques. However, it is difficult to make consistent reconstructions in real-time because the amount of list-mode data acquired in PET scans may be large depending on the level of radioactivity, and the reconstruction speed depends on the amount of the list-mode data. In this study, we developed a system to control the data used in the reconstruction step while retaining quantitative performance. In the proposed system, the data transfer control system limits the event counts to be used in the reconstruction step according to the reconstruction speed, and the reconstructed images are properly intensified by using the ratio of the used counts to the total counts. We implemented the system on a small OpenPET prototype system and evaluated the performance in terms of the real-time tracking ability by displaying reconstructed images in which the intensity was compensated. The intensity of the displayed images correlated properly with the original count rate and a frame rate of 2 frames per second was achieved with average delay time of 2.1 s.

  18. Video enhancement workbench: an operational real-time video image processing system

    NASA Astrophysics Data System (ADS)

    Yool, Stephen R.; Van Vactor, David L.; Smedley, Kirk G.

    1993-01-01

    Video image sequences can be exploited in real-time, giving analysts rapid access to information for military or criminal investigations. Video-rate dynamic range adjustment subdues fluctuations in image intensity, thereby assisting discrimination of small or low- contrast objects. Contrast-regulated unsharp masking enhances differentially shadowed or otherwise low-contrast image regions. Real-time removal of localized hotspots, when combined with automatic histogram equalization, may enhance resolution of objects directly adjacent. In video imagery corrupted by zero-mean noise, real-time frame averaging can assist resolution and location of small or low-contrast objects. To maximize analyst efficiency, lengthy video sequences can be screened automatically for low-frequency, high-magnitude events. Combined zoom, roam, and automatic dynamic range adjustment permit rapid analysis of facial features captured by video cameras recording crimes in progress. When trying to resolve small objects in murky seawater, stereo video places the moving imagery in an optimal setting for human interpretation.

  19. Real-time flood forecasting

    USGS Publications Warehouse

    Lai, C.; Tsay, T.-K.; Chien, C.-H.; Wu, I.-L.

    2009-01-01

    Researchers at the Hydroinformatic Research and Development Team (HIRDT) of the National Taiwan University undertook a project to create a real time flood forecasting model, with an aim to predict the current in the Tamsui River Basin. The model was designed based on deterministic approach with mathematic modeling of complex phenomenon, and specific parameter values operated to produce a discrete result. The project also devised a rainfall-stage model that relates the rate of rainfall upland directly to the change of the state of river, and is further related to another typhoon-rainfall model. The geographic information system (GIS) data, based on precise contour model of the terrain, estimate the regions that were perilous to flooding. The HIRDT, in response to the project's progress, also devoted their application of a deterministic model to unsteady flow of thermodynamics to help predict river authorities issue timely warnings and take other emergency measures.

  20. Enhancement of EarthScope Infrastructure with Real Time Seismogeodesy

    NASA Astrophysics Data System (ADS)

    Bock, Y.; Melgar, D.; Geng, J.; Haase, J. S.; Crowell, B. W.; Squibb, M. B.

    2013-12-01

    Recent great earthquakes and ensuing tsunamis in Sumatra, Chile and Japan have demonstrated the need for accurate ground displacements that fully characterize the great amplitudes and broad dynamic range of motions associated with these complex ruptures. Our ability to model the source processes of these events and their effects, whether in real-time or after the fact, is limited by the weaknesses of both seismic and geodetic networks. Geodetic instruments provide the static component as well as coarse dynamic motions but are much less precise than seismic instruments, especially in the vertical direction. Seismic instruments provide exceptionally-sensitive dynamic motions but typically have difficulty in recovering unbiased near-field low-frequency absolute displacements. We have shown in several publications that an optimal combination of data from collocated GPS and strong motion accelerometers provides seismogeodetic displacement, velocity and point tilt waveforms spanning the full spectrum of seismic motion, without clipping and magnitude saturation. These observations are suitable for earthquake early warning (EEW) through detection of P wave arrivals, rapid assessment of earthquake magnitude, finite-source centroid moment tensor solutions and fault slip models, and tsunami warning, in particular in the near-source regions of large earthquakes. At present, more than 550 real-time GPS stations are operating in Western North America, a majority as part of the EarthScope/PBO effort with a concentration in the Cascadia region and southern California. Unfortunately, there are few collocations of GPS and accelerometers in this region (the exception being in parts of the BARD network in northern California). We have leveraged the considerable infrastructure already invested in the EarthScope project, and funding through NSF and NASA to create advanced software, hardware, and algorithms that make it possible to utilize EarthScope/PBO as an EEW test bed. We have

  1. A high-efficiency real-time digital signal averager for time-of-flight mass spectrometry.

    PubMed

    Wang, Yinan; Xu, Hui; Li, Qingjiang; Li, Nan; Huang, Zhengxu; Zhou, Zhen; Liu, Husheng; Sun, Zhaolin; Xu, Xin; Yu, Hongqi; Liu, Haijun; Li, David D-U; Wang, Xi; Dong, Xiuzhen; Gao, Wei

    2013-05-30

    Analog-to-digital converter (ADC)-based acquisition systems are widely applied in time-of-flight mass spectrometers (TOFMS) due to their ability to record the signal intensity of all ions within the same pulse. However, the acquisition system raises the requirement for data throughput, along with increasing the conversion rate and resolution of the ADC. It is therefore of considerable interest to develop a high-performance real-time acquisition system, which can relieve the limitation of data throughput. We present in this work a high-efficiency real-time digital signal averager, consisting of a signal conditioner, a data conversion module and a signal processing module. Two optimization strategies are implemented using field programmable gate arrays (FPGAs) to enhance the efficiency of the real-time processing. A pipeline procedure is used to reduce the time consumption of the accumulation strategy. To realize continuous data transfer, a high-efficiency transmission strategy is developed, based on a ping-pong procedure. The digital signal averager features good responsiveness, analog bandwidth and dynamic performance. The optimal effective number of bits reaches 6.7 bits. For a 32 µs record length, the averager can realize 100% efficiency with an extraction frequency below 31.23 kHz by modifying the number of accumulation steps. In unit time, the averager yields superior signal-to-noise ratio (SNR) compared with data accumulation in a computer. The digital signal averager is combined with a vacuum ultraviolet single-photon ionization time-of-flight mass spectrometer (VUV-SPI-TOFMS). The efficiency of the real-time processing is tested by analyzing the volatile organic compounds (VOCs) from ordinary printed materials. In these experiments, 22 kinds of compounds are detected, and the dynamic range exceeds 3 orders of magnitude. Copyright © 2013 John Wiley & Sons, Ltd.

  2. Real-time Raman and SRS imaging of living human macrophages reveals cell-to-cell heterogeneity and dynamics of lipid uptake.

    PubMed

    Stiebing, Clara; Meyer, Tobias; Rimke, Ingo; Matthäus, Christian; Schmitt, Michael; Lorkowski, Stefan; Popp, Jürgen

    2017-09-01

    Monitoring living cells in real-time is important in order to unravel complex dynamic processes in life sciences. In particular the dynamics of initiation and progression of degenerative diseases is intensely studied. In atherosclerosis the thickening of arterial walls is related to high lipid levels in the blood stream, which trigger the lipid uptake and formation of droplets as neutral lipid reservoirs in macrophages in the arterial wall. Unregulated lipid uptake finally results in foam cell formation, which is a hallmark of atherosclerosis. In previous studies, the uptake and storage of different fatty acids was monitored by measuring fixed cells. Commonly employed fluorescence staining protocols are often error prone because of cytotoxicity and unspecific fluorescence backgrounds. By following living cells with Raman spectroscopic imaging, lipid uptake of macrophages was studied with real-time data acquisition. Isotopic labeling using deuterated palmitic acid has been combined with spontaneous and stimulated Raman imaging to investigate the dynamic process of fatty acid storage in human macrophages for incubation times from 45 min to 37 h. Striking heterogeneity in the uptake rate and the total concentration of deuterated palmitic acid covering two orders of magnitude is detected in single as well as ensembles of cultured human macrophages. SRS signal of deuterated palmitic acid measured at the CD vibration band after incorporation into living macrophages. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  3. A real-time control framework for urban water reservoirs operation

    NASA Astrophysics Data System (ADS)

    Galelli, S.; Goedbloed, A.; Schwanenberg, D.

    2012-04-01

    Drinking water demand in urban areas is growing parallel to the worldwide urban population, and it is acquiring an increasing part of the total water consumption. Since the delivery of sufficient water volumes in urban areas represents a difficult logistic and economical problem, different metropolitan areas are evaluating the opportunity of constructing relatively small reservoirs within urban areas. Singapore, for example, is developing the so-called 'Four National Taps Strategies', which detects the maximization of water yields from local, urban catchments as one of the most important water sources. However, the peculiar location of these reservoirs can provide a certain advantage from the logistical point of view, but it can pose serious difficulties in their daily management. Urban catchments are indeed characterized by large impervious areas: this results in a change of the hydrological cycle, with decreased infiltration and groundwater recharge, and increased patterns of surface and river discharges, with higher peak flows, volumes and concentration time. Moreover, the high concentrations of nutrients and sediments characterizing urban discharges can cause further water quality problems. In this critical hydrological context, the effective operation of urban water reservoirs must rely on real-time control techniques, which can exploit hydro-meteorological information available in real-time from hydrological and nowcasting models. This work proposes a novel framework for the real-time control of combined water quality and quantity objectives in urban reservoirs. The core of this framework is a non-linear Model Predictive Control (MPC) scheme, which employs the current state of the system, the future discharges furnished by a predictive model and a further model describing the internal dynamics of the controlled sub-system to determine an optimal control sequence over a finite prediction horizon. The main advantage of this scheme stands in its reduced

  4. ControlShell: A real-time software framework

    NASA Technical Reports Server (NTRS)

    Schneider, Stanley A.; Chen, Vincent W.; Pardo-Castellote, Gerardo

    1994-01-01

    The ControlShell system is a programming environment that enables the development and implementation of complex real-time software. It includes many building tools for complex systems, such as a graphical finite state machine (FSM) tool to provide strategic control. ControlShell has a component-based design, providing interface definitions and mechanisms for building real-time code modules along with providing basic data management. Some of the system-building tools incorporated in ControlShell are a graphical data flow editor, a component data requirement editor, and a state-machine editor. It also includes a distributed data flow package, an execution configuration manager, a matrix package, and an object database and dynamic binding facility. This paper presents an overview of ControlShell's architecture and examines the functions of several of its tools.

  5. Study on Development of 1D-2D Coupled Real-time Urban Inundation Prediction model

    NASA Astrophysics Data System (ADS)

    Lee, Seungsoo

    2017-04-01

    In recent years, we are suffering abnormal weather condition due to climate change around the world. Therefore, countermeasures for flood defense are urgent task. In this research, study on development of 1D-2D coupled real-time urban inundation prediction model using predicted precipitation data based on remote sensing technology is conducted. 1 dimensional (1D) sewerage system analysis model which was introduced by Lee et al. (2015) is used to simulate inlet and overflow phenomena by interacting with surface flown as well as flows in conduits. 2 dimensional (2D) grid mesh refinement method is applied to depict road networks for effective calculation time. 2D surface model is coupled with 1D sewerage analysis model in order to consider bi-directional flow between both. Also parallel computing method, OpenMP, is applied to reduce calculation time. The model is estimated by applying to 25 August 2014 extreme rainfall event which caused severe inundation damages in Busan, Korea. Oncheoncheon basin is selected for study basin and observed radar data are assumed as predicted rainfall data. The model shows acceptable calculation speed with accuracy. Therefore it is expected that the model can be used for real-time urban inundation forecasting system to minimize damages.

  6. Data-driven reinforcement learning–based real-time energy management system for plug-in hybrid electric vehicles

    DOE PAGES

    Qi, Xuewei; Wu, Guoyuan; Boriboonsomsin, Kanok; ...

    2016-01-01

    Plug-in hybrid electric vehicles (PHEVs) show great promise in reducing transportation-related fossil fuel consumption and greenhouse gas emissions. Designing an efficient energy management system (EMS) for PHEVs to achieve better fuel economy has been an active research topic for decades. Most of the advanced systems rely either on a priori knowledge of future driving conditions to achieve the optimal but not real-time solution (e.g., using a dynamic programming strategy) or on only current driving situations to achieve a real-time but nonoptimal solution (e.g., rule-based strategy). This paper proposes a reinforcement learning–based real-time EMS for PHEVs to address the trade-off betweenmore » real-time performance and optimal energy savings. The proposed model can optimize the power-split control in real time while learning the optimal decisions from historical driving cycles. Here, a case study on a real-world commute trip shows that about a 12% fuel saving can be achieved without considering charging opportunities; further, an 8% fuel saving can be achieved when charging opportunities are considered, compared with the standard binary mode control strategy.« less

  7. Data-driven reinforcement learning–based real-time energy management system for plug-in hybrid electric vehicles

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

    Qi, Xuewei; Wu, Guoyuan; Boriboonsomsin, Kanok

    Plug-in hybrid electric vehicles (PHEVs) show great promise in reducing transportation-related fossil fuel consumption and greenhouse gas emissions. Designing an efficient energy management system (EMS) for PHEVs to achieve better fuel economy has been an active research topic for decades. Most of the advanced systems rely either on a priori knowledge of future driving conditions to achieve the optimal but not real-time solution (e.g., using a dynamic programming strategy) or on only current driving situations to achieve a real-time but nonoptimal solution (e.g., rule-based strategy). This paper proposes a reinforcement learning–based real-time EMS for PHEVs to address the trade-off betweenmore » real-time performance and optimal energy savings. The proposed model can optimize the power-split control in real time while learning the optimal decisions from historical driving cycles. Here, a case study on a real-world commute trip shows that about a 12% fuel saving can be achieved without considering charging opportunities; further, an 8% fuel saving can be achieved when charging opportunities are considered, compared with the standard binary mode control strategy.« less

  8. Quantitative real-time monitoring of dryer effluent using fiber optic near-infrared spectroscopy.

    PubMed

    Harris, S C; Walker, D S

    2000-09-01

    This paper describes a method for real-time quantitation of the solvents evaporating from a dryer. The vapor stream in the vacuum line of a dryer was monitored in real time using a fiber optic-coupled acousto-optic tunable filter near-infrared (AOTF-NIR) spectrometer. A balance was placed in the dryer, and mass readings were recorded for every scan of the AOTF-NIR. A partial least-squares (PLS) calibration was subsequently built based on change in mass over change in time for solvents typically used in a chemical manufacturing plant. Controlling software for the AOTF-NIR was developed. The software collects spectra, builds the PLS calibration model, and continuously fits subsequently collected spectra to the calibration, allowing the operator to follow the mass loss of solvent from the dryer. The results indicate that solvent loss can be monitored and quantitated in real time using NIR for the optimization of drying times. These time-based mass loss values have also been used to calculate "dynamic" vapor density values for the solvents. The values calculated are in agreement with values determined from the ideal gas law and could prove valuable as tools to measure temperature or pressure indirectly.

  9. Graph-based real-time fault diagnostics

    NASA Technical Reports Server (NTRS)

    Padalkar, S.; Karsai, G.; Sztipanovits, J.

    1988-01-01

    A real-time fault detection and diagnosis capability is absolutely crucial in the design of large-scale space systems. Some of the existing AI-based fault diagnostic techniques like expert systems and qualitative modelling are frequently ill-suited for this purpose. Expert systems are often inadequately structured, difficult to validate and suffer from knowledge acquisition bottlenecks. Qualitative modelling techniques sometimes generate a large number of failure source alternatives, thus hampering speedy diagnosis. In this paper we present a graph-based technique which is well suited for real-time fault diagnosis, structured knowledge representation and acquisition and testing and validation. A Hierarchical Fault Model of the system to be diagnosed is developed. At each level of hierarchy, there exist fault propagation digraphs denoting causal relations between failure modes of subsystems. The edges of such a digraph are weighted with fault propagation time intervals. Efficient and restartable graph algorithms are used for on-line speedy identification of failure source components.

  10. Real-time anomaly detection for very short-term load forecasting

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

    Luo, Jian; Hong, Tao; Yue, Meng

    Although the recent load information is critical to very short-term load forecasting (VSTLF), power companies often have difficulties in collecting the most recent load values accurately and timely for VSTLF applications. This paper tackles the problem of real-time anomaly detection in most recent load information used by VSTLF. This paper proposes a model-based anomaly detection method that consists of two components, a dynamic regression model and an adaptive anomaly threshold. The case study is developed using the data from ISO New England. This paper demonstrates that the proposed method significantly outperforms three other anomaly detection methods including two methods commonlymore » used in the field and one state-of-the-art method used by a winning team of the Global Energy Forecasting Competition 2014. Lastly, a general anomaly detection framework is proposed for the future research.« less

  11. Real-time anomaly detection for very short-term load forecasting

    DOE PAGES

    Luo, Jian; Hong, Tao; Yue, Meng

    2018-01-06

    Although the recent load information is critical to very short-term load forecasting (VSTLF), power companies often have difficulties in collecting the most recent load values accurately and timely for VSTLF applications. This paper tackles the problem of real-time anomaly detection in most recent load information used by VSTLF. This paper proposes a model-based anomaly detection method that consists of two components, a dynamic regression model and an adaptive anomaly threshold. The case study is developed using the data from ISO New England. This paper demonstrates that the proposed method significantly outperforms three other anomaly detection methods including two methods commonlymore » used in the field and one state-of-the-art method used by a winning team of the Global Energy Forecasting Competition 2014. Lastly, a general anomaly detection framework is proposed for the future research.« less

  12. Real-Time Human Detection for Aerial Captured Video Sequences via Deep Models.

    PubMed

    AlDahoul, Nouar; Md Sabri, Aznul Qalid; Mansoor, Ali Mohammed

    2018-01-01

    Human detection in videos plays an important role in various real life applications. Most of traditional approaches depend on utilizing handcrafted features which are problem-dependent and optimal for specific tasks. Moreover, they are highly susceptible to dynamical events such as illumination changes, camera jitter, and variations in object sizes. On the other hand, the proposed feature learning approaches are cheaper and easier because highly abstract and discriminative features can be produced automatically without the need of expert knowledge. In this paper, we utilize automatic feature learning methods which combine optical flow and three different deep models (i.e., supervised convolutional neural network (S-CNN), pretrained CNN feature extractor, and hierarchical extreme learning machine) for human detection in videos captured using a nonstatic camera on an aerial platform with varying altitudes. The models are trained and tested on the publicly available and highly challenging UCF-ARG aerial dataset. The comparison between these models in terms of training, testing accuracy, and learning speed is analyzed. The performance evaluation considers five human actions (digging, waving, throwing, walking, and running). Experimental results demonstrated that the proposed methods are successful for human detection task. Pretrained CNN produces an average accuracy of 98.09%. S-CNN produces an average accuracy of 95.6% with soft-max and 91.7% with Support Vector Machines (SVM). H-ELM has an average accuracy of 95.9%. Using a normal Central Processing Unit (CPU), H-ELM's training time takes 445 seconds. Learning in S-CNN takes 770 seconds with a high performance Graphical Processing Unit (GPU).

  13. Real-time simulation of hand motion for prosthesis control

    PubMed Central

    Blana, Dimitra; Chadwick, Edward K.; van den Bogert, Antonie J.; Murray, Wendy M.

    2016-01-01

    Individuals with hand amputation suffer substantial loss of independence. Performance of sophisticated prostheses is limited by the ability to control them. To achieve natural and simultaneous control of all wrist and hand motions, we propose to use real-time biomechanical simulation to map between residual EMG and motions of the intact hand. Here we describe a musculoskeletal model of the hand using only extrinsic muscles to determine whether real-time performance is possible. Simulation is 1.3 times faster than real time, but the model is locally unstable. Methods are discussed to increase stability and make this approach suitable for prosthesis control. PMID:27868425

  14. High-fidelity real-time maritime scene rendering

    NASA Astrophysics Data System (ADS)

    Shyu, Hawjye; Taczak, Thomas M.; Cox, Kevin; Gover, Robert; Maraviglia, Carlos; Cahill, Colin

    2011-06-01

    The ability to simulate authentic engagements using real-world hardware is an increasingly important tool. For rendering maritime environments, scene generators must be capable of rendering radiometrically accurate scenes with correct temporal and spatial characteristics. When the simulation is used as input to real-world hardware or human observers, the scene generator must operate in real-time. This paper introduces a novel, real-time scene generation capability for rendering radiometrically accurate scenes of backgrounds and targets in maritime environments. The new model is an optimized and parallelized version of the US Navy CRUISE_Missiles rendering engine. It was designed to accept environmental descriptions and engagement geometry data from external sources, render a scene, transform the radiometric scene using the electro-optical response functions of a sensor under test, and output the resulting signal to real-world hardware. This paper reviews components of the scene rendering algorithm, and details the modifications required to run this code in real-time. A description of the simulation architecture and interfaces to external hardware and models is presented. Performance assessments of the frame rate and radiometric accuracy of the new code are summarized. This work was completed in FY10 under Office of Secretary of Defense (OSD) Central Test and Evaluation Investment Program (CTEIP) funding and will undergo a validation process in FY11.

  15. Real-Time Cognitive Computing Architecture for Data Fusion in a Dynamic Environment

    NASA Technical Reports Server (NTRS)

    Duong, Tuan A.; Duong, Vu A.

    2012-01-01

    A novel cognitive computing architecture is conceptualized for processing multiple channels of multi-modal sensory data streams simultaneously, and fusing the information in real time to generate intelligent reaction sequences. This unique architecture is capable of assimilating parallel data streams that could be analog, digital, synchronous/asynchronous, and could be programmed to act as a knowledge synthesizer and/or an "intelligent perception" processor. In this architecture, the bio-inspired models of visual pathway and olfactory receptor processing are combined as processing components, to achieve the composite function of "searching for a source of food while avoiding the predator." The architecture is particularly suited for scene analysis from visual data and odorant.

  16. Finite-dimensional modeling of network-induced delays for real-time control systems

    NASA Technical Reports Server (NTRS)

    Ray, Asok; Halevi, Yoram

    1988-01-01

    In integrated control systems (ICS), a feedback loop is closed by the common communication channel, which multiplexes digital data from the sensor to the controller and from the controller to the actuator along with the data traffic from other control loops and management functions. Due to asynchronous time-division multiplexing in the network access protocols, time-varying delays are introduced in the control loop, which degrade the system dynamic performance and are a potential source of instability. The delayed control system is represented by a finite-dimensional, time-varying, discrete-time model which is less complex than the existing continuous-time models for time-varying delays; this approach allows for simpler schemes for analysis and simulation of the ICS.

  17. Using SCADA Data, Field Studies, and Real-Time Modeling to ...

    EPA Pesticide Factsheets

    EPA has been providing technical assistance to the City of Flint and the State of Michigan in response to the drinking water lead contamination incident. Responders quickly recognized the need for a water distribution system hydraulic model to provide insight on flow patterns and water quality as well as to evaluate changes being made to the system operation to enhance corrosion control and improve chlorine residuals. EPA partnered with the City of Flint and the Michigan Department of Environmental Quality to update and calibrate an existing hydraulic model. The City provided SCADA data, GIS data, customer billing data, valve status data, design diagrams, and information on operations. Team members visited all facilities and updated pump and valve types, sizes, settings, elevations, and pump discharge curves. Several technologies were used to support this work including the EPANET-RTX based Polaris real-time modeling software, WaterGEMS, ArcGIS, EPANET, and RTX:LINK. Field studies were conducted to collect pressure and flow data from more than 25 locations throughout the distribution system. An assessment of the model performance compared model predictions for flow, pressure, and tank levels to SCADA and field data, resulting in error measurements for each data stream over the time period analyzed. Now, the calibrated model can be used with a known confidence in its performance to evaluate hydraulic and water quality problems, and the model can be easily

  18. Real time polymer nanocomposites-based physical nanosensors: theory and modeling.

    PubMed

    Bellucci, Stefano; Shunin, Yuri; Gopeyenko, Victor; Lobanova-Shunina, Tamara; Burlutskaya, Nataly; Zhukovskii, Yuri

    2017-09-01

    Functionalized carbon nanotubes and graphene nanoribbons nanostructures, serving as the basis for the creation of physical pressure and temperature nanosensors, are considered as tools for ecological monitoring and medical applications. Fragments of nanocarbon inclusions with different morphologies, presenting a disordered system, are regarded as models for nanocomposite materials based on carbon nanoсluster suspension in dielectric polymer environments (e.g., epoxy resins). We have formulated the approach of conductivity calculations for carbon-based polymer nanocomposites using the effective media cluster approach, disordered systems theory and conductivity mechanisms analysis, and obtained the calibration dependences. Providing a proper description of electric responses in nanosensoring systems, we demonstrate the implementation of advanced simulation models suitable for real time control nanosystems. We also consider the prospects and prototypes of the proposed physical nanosensor models providing the comparisons with experimental calibration dependences.

  19. Real time polymer nanocomposites-based physical nanosensors: theory and modeling

    NASA Astrophysics Data System (ADS)

    Bellucci, Stefano; Shunin, Yuri; Gopeyenko, Victor; Lobanova-Shunina, Tamara; Burlutskaya, Nataly; Zhukovskii, Yuri

    2017-09-01

    Functionalized carbon nanotubes and graphene nanoribbons nanostructures, serving as the basis for the creation of physical pressure and temperature nanosensors, are considered as tools for ecological monitoring and medical applications. Fragments of nanocarbon inclusions with different morphologies, presenting a disordered system, are regarded as models for nanocomposite materials based on carbon nanoсluster suspension in dielectric polymer environments (e.g., epoxy resins). We have formulated the approach of conductivity calculations for carbon-based polymer nanocomposites using the effective media cluster approach, disordered systems theory and conductivity mechanisms analysis, and obtained the calibration dependences. Providing a proper description of electric responses in nanosensoring systems, we demonstrate the implementation of advanced simulation models suitable for real time control nanosystems. We also consider the prospects and prototypes of the proposed physical nanosensor models providing the comparisons with experimental calibration dependences.

  20. Modeling Temporal Behavior in Large Networks: A Dynamic Mixed-Membership Model

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

    Rossi, R; Gallagher, B; Neville, J

    Given a large time-evolving network, how can we model and characterize the temporal behaviors of individual nodes (and network states)? How can we model the behavioral transition patterns of nodes? We propose a temporal behavior model that captures the 'roles' of nodes in the graph and how they evolve over time. The proposed dynamic behavioral mixed-membership model (DBMM) is scalable, fully automatic (no user-defined parameters), non-parametric/data-driven (no specific functional form or parameterization), interpretable (identifies explainable patterns), and flexible (applicable to dynamic and streaming networks). Moreover, the interpretable behavioral roles are generalizable, computationally efficient, and natively supports attributes. We applied ourmore » model for (a) identifying patterns and trends of nodes and network states based on the temporal behavior, (b) predicting future structural changes, and (c) detecting unusual temporal behavior transitions. We use eight large real-world datasets from different time-evolving settings (dynamic and streaming). In particular, we model the evolving mixed-memberships and the corresponding behavioral transitions of Twitter, Facebook, IP-Traces, Email (University), Internet AS, Enron, Reality, and IMDB. The experiments demonstrate the scalability, flexibility, and effectiveness of our model for identifying interesting patterns, detecting unusual structural transitions, and predicting the future structural changes of the network and individual nodes.« less