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Sample records for adaptive performance optimization

  1. Adaptive Optimization of Aircraft Engine Performance Using Neural Networks

    NASA Technical Reports Server (NTRS)

    Simon, Donald L.; Long, Theresa W.

    1995-01-01

    Preliminary results are presented on the development of an adaptive neural network based control algorithm to enhance aircraft engine performance. This work builds upon a previous National Aeronautics and Space Administration (NASA) effort known as Performance Seeking Control (PSC). PSC is an adaptive control algorithm which contains a model of the aircraft's propulsion system which is updated on-line to match the operation of the aircraft's actual propulsion system. Information from the on-line model is used to adapt the control system during flight to allow optimal operation of the aircraft's propulsion system (inlet, engine, and nozzle) to improve aircraft engine performance without compromising reliability or operability. Performance Seeking Control has been shown to yield reductions in fuel flow, increases in thrust, and reductions in engine fan turbine inlet temperature. The neural network based adaptive control, like PSC, will contain a model of the propulsion system which will be used to calculate optimal control commands on-line. Hopes are that it will be able to provide some additional benefits above and beyond those of PSC. The PSC algorithm is computationally intensive, it is valid only at near steady-state flight conditions, and it has no way to adapt or learn on-line. These issues are being addressed in the development of the optimal neural controller. Specialized neural network processing hardware is being developed to run the software, the algorithm will be valid at steady-state and transient conditions, and will take advantage of the on-line learning capability of neural networks. Future plans include testing the neural network software and hardware prototype against an aircraft engine simulation. In this paper, the proposed neural network software and hardware is described and preliminary neural network training results are presented.

  2. A concept for adaptive performance optimization on commercial transport aircraft

    NASA Technical Reports Server (NTRS)

    Jackson, Michael R.; Enns, Dale F.

    1995-01-01

    An adaptive control method is presented for the minimization of drag during flight for transport aircraft. The minimization of drag is achieved by taking advantage of the redundant control capability available in the pitch axis, with the horizontal tail used as the primary surface and symmetric deflection of the ailerons and cruise flaps used as additional controls. The additional control surfaces are excited with sinusoidal signals, while the altitude and velocity loops are closed with guidance and control laws. A model of the throttle response as a function of the additional control surfaces is formulated and the parameters in the model are estimated from the sensor measurements using a least squares estimation method. The estimated model is used to determine the minimum drag positions of the control surfaces. The method is presented for the optimization of one and two additional control surfaces. The adaptive control method is extended to optimize rate of climb with the throttle fixed. Simulations that include realistic disturbances are presented, as well as the results of a Monte Carlo simulation analysis that shows the effects of changing the disturbance environment and the excitation signal parameters.

  3. Direct adaptive performance optimization of subsonic transports: A periodic perturbation technique

    NASA Technical Reports Server (NTRS)

    Espana, Martin D.; Gilyard, Glenn

    1995-01-01

    Aircraft performance can be optimized at the flight condition by using available redundancy among actuators. Effective use of this potential allows improved performance beyond limits imposed by design compromises. Optimization based on nominal models does not result in the best performance of the actual aircraft at the actual flight condition. An adaptive algorithm for optimizing performance parameters, such as speed or fuel flow, in flight based exclusively on flight data is proposed. The algorithm is inherently insensitive to model inaccuracies and measurement noise and biases and can optimize several decision variables at the same time. An adaptive constraint controller integrated into the algorithm regulates the optimization constraints, such as altitude or speed, without requiring and prior knowledge of the autopilot design. The algorithm has a modular structure which allows easy incorporation (or removal) of optimization constraints or decision variables to the optimization problem. An important part of the contribution is the development of analytical tools enabling convergence analysis of the algorithm and the establishment of simple design rules. The fuel-flow minimization and velocity maximization modes of the algorithm are demonstrated on the NASA Dryden B-720 nonlinear flight simulator for the single- and multi-effector optimization cases.

  4. In-flight adaptive performance optimization (APO) control using redundant control effectors of an aircraft

    NASA Technical Reports Server (NTRS)

    Gilyard, Glenn B. (Inventor)

    1999-01-01

    Practical application of real-time (or near real-time) Adaptive Performance Optimization (APO) is provided for a transport aircraft in steady climb, cruise, turn descent or other flight conditions based on measurements and calculations of incremental drag from a forced response maneuver of one or more redundant control effectors defined as those in excess of the minimum set of control effectors required to maintain the steady flight condition in progress. The method comprises the steps of applying excitation in a raised-cosine form over an interval of from 100 to 500 sec. at the rate of 1 to 10 sets/sec of excitation, and data for analysis is gathered in sets of measurements made during the excitation to calculate lift and drag coefficients C.sub.L and C.sub.D from two equations, one for each coefficient. A third equation is an expansion of C.sub.D as a function of parasitic drag, induced drag, Mach and altitude drag effects, and control effector drag, and assumes a quadratic variation of drag with positions .delta..sub.i of redundant control effectors i=1 to n. The third equation is then solved for .delta..sub.iopt the optimal position of redundant control effector i, which is then used to set the control effector i for optimum performance during the remainder of said steady flight or until monitored flight conditions change by some predetermined amount as determined automatically or a predetermined minimum flight time has elapsed.

  5. On the estimation algorithm used in adaptive performance optimization of turbofan engines

    NASA Technical Reports Server (NTRS)

    Espana, Martin D.; Gilyard, Glenn B.

    1993-01-01

    The performance seeking control algorithm is designed to continuously optimize the performance of propulsion systems. The performance seeking control algorithm uses a nominal model of the propulsion system and estimates, in flight, the engine deviation parameters characterizing the engine deviations with respect to nominal conditions. In practice, because of measurement biases and/or model uncertainties, the estimated engine deviation parameters may not reflect the engine's actual off-nominal condition. This factor has a necessary impact on the overall performance seeking control scheme exacerbated by the open-loop character of the algorithm. The effects produced by unknown measurement biases over the estimation algorithm are evaluated. This evaluation allows for identification of the most critical measurements for application of the performance seeking control algorithm to an F100 engine. An equivalence relation between the biases and engine deviation parameters stems from an observability study; therefore, it is undecided whether the estimated engine deviation parameters represent the actual engine deviation or whether they simply reflect the measurement biases. A new algorithm, based on the engine's (steady-state) optimization model, is proposed and tested with flight data. When compared with previous Kalman filter schemes, based on local engine dynamic models, the new algorithm is easier to design and tune and it reduces the computational burden of the onboard computer.

  6. Robust Optimal Adaptive Control Method with Large Adaptive Gain

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.

    2009-01-01

    In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly. However, a large adaptive gain can lead to high-frequency oscillations which can adversely affect robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient stability robustness. Simulations were conducted for a damaged generic transport aircraft with both standard adaptive control and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model while maintaining a sufficient time delay margin.

  7. Adaptive control schemes for improving dynamic performance of efficiency-optimized induction motor drives.

    PubMed

    Kumar, Navneet; Raj Chelliah, Thanga; Srivastava, S P

    2015-07-01

    Model Based Control (MBC) is one of the energy optimal controllers used in vector-controlled Induction Motor (IM) for controlling the excitation of motor in accordance with torque and speed. MBC offers energy conservation especially at part-load operation, but it creates ripples in torque and speed during load transition, leading to poor dynamic performance of the drive. This study investigates the opportunity for improving dynamic performance of a three-phase IM operating with MBC and proposes three control schemes: (i) MBC with a low pass filter (ii) torque producing current (iqs) injection in the output of speed controller (iii) Variable Structure Speed Controller (VSSC). The pre and post operation of MBC during load transition is also analyzed. The dynamic performance of a 1-hp, three-phase squirrel-cage IM with mine-hoist load diagram is tested. Test results are provided for the conventional field-oriented (constant flux) control and MBC (adjustable excitation) with proposed schemes. The effectiveness of proposed schemes is also illustrated for parametric variations. The test results and subsequent analysis confer that the motor dynamics improves significantly with all three proposed schemes in terms of overshoot/undershoot peak amplitude of torque and DC link power in addition to energy saving during load transitions. PMID:25820090

  8. Optimization of adaptive-optics systems closed-loop bandwidth settings to maximize imaging-system performance.

    PubMed

    Brigantic, R T; Roggemann, M C; Welsh, B M; Bauer, K W

    1998-02-10

    We present the results of research aimed at optimizing adaptive-optics closed-loop bandwidth settings to maximize imaging-system performance. The optimum closed-loop bandwidth settings are determined as a function of target-object light levels and atmospheric seeing conditions. Our work shows that, for bright objects, the optimum closed-loop bandwidth is near the Greenwood frequency. However, for dim objects without the use of a laser beacon the preferred closed-loop bandwidth settings are a small fraction of the Greenwood frequency. In addition, under low light levels selection of the proper closed-loop bandwidth is more critical for achieving maximum performance than it is under high light levels. We also present a strategy for selecting the closed-loop bandwidth to provide robust system performance for different target-object light levels.

  9. Adaptive critics for dynamic optimization.

    PubMed

    Kulkarni, Raghavendra V; Venayagamoorthy, Ganesh Kumar

    2010-06-01

    A novel action-dependent adaptive critic design (ACD) is developed for dynamic optimization. The proposed combination of a particle swarm optimization-based actor and a neural network critic is demonstrated through dynamic sleep scheduling of wireless sensor motes for wildlife monitoring. The objective of the sleep scheduler is to dynamically adapt the sleep duration to node's battery capacity and movement pattern of animals in its environment in order to obtain snapshots of the animal on its trajectory uniformly. Simulation results show that the sleep time of the node determined by the actor critic yields superior quality of sensory data acquisition and enhanced node longevity. PMID:20223635

  10. Adaptive cuckoo search algorithm for unconstrained optimization.

    PubMed

    Ong, Pauline

    2014-01-01

    Modification of the intensification and diversification approaches in the recently developed cuckoo search algorithm (CSA) is performed. The alteration involves the implementation of adaptive step size adjustment strategy, and thus enabling faster convergence to the global optimal solutions. The feasibility of the proposed algorithm is validated against benchmark optimization functions, where the obtained results demonstrate a marked improvement over the standard CSA, in all the cases. PMID:25298971

  11. Adaptive cuckoo search algorithm for unconstrained optimization.

    PubMed

    Ong, Pauline

    2014-01-01

    Modification of the intensification and diversification approaches in the recently developed cuckoo search algorithm (CSA) is performed. The alteration involves the implementation of adaptive step size adjustment strategy, and thus enabling faster convergence to the global optimal solutions. The feasibility of the proposed algorithm is validated against benchmark optimization functions, where the obtained results demonstrate a marked improvement over the standard CSA, in all the cases.

  12. Sensory adaptation as optimal resource allocation.

    PubMed

    Gepshtein, Sergei; Lesmes, Luis A; Albright, Thomas D

    2013-03-12

    Visual adaptation is expected to improve visual performance in the new environment. This expectation has been contradicted by evidence that adaptation sometimes decreases sensitivity for the adapting stimuli, and sometimes it changes sensitivity for stimuli very different from the adapting ones. We hypothesize that this pattern of results can be explained by a process that optimizes sensitivity for many stimuli, rather than changing sensitivity only for those stimuli whose statistics have changed. To test this hypothesis, we measured visual sensitivity across a broad range of spatiotemporal modulations of luminance, while varying the distribution of stimulus speeds. The manipulation of stimulus statistics caused a large-scale reorganization of visual sensitivity, forming the orderly pattern of sensitivity gains and losses. This pattern is predicted by a theory of distribution of receptive field characteristics in the visual system.

  13. Adaptive hybrid optimal quantum control for imprecisely characterized systems.

    PubMed

    Egger, D J; Wilhelm, F K

    2014-06-20

    Optimal quantum control theory carries a huge promise for quantum technology. Its experimental application, however, is often hindered by imprecise knowledge of the input variables, the quantum system's parameters. We show how to overcome this by adaptive hybrid optimal control, using a protocol named Ad-HOC. This protocol combines open- and closed-loop optimal control by first performing a gradient search towards a near-optimal control pulse and then an experimental fidelity estimation with a gradient-free method. For typical settings in solid-state quantum information processing, adaptive hybrid optimal control enhances gate fidelities by an order of magnitude, making optimal control theory applicable and useful. PMID:24996074

  14. Extragalactic Fields Optimized for Adaptive Optics

    NASA Astrophysics Data System (ADS)

    Damjanov, Ivana; Abraham, Roberto G.; Glazebrook, Karl; McGregor, Peter; Rigaut, Francois; McCarthy, Patrick J.; Brinchmann, Jarle; Cuillandre, Jean-Charles; Mellier, Yannick; McCracken, Henry Joy; Hudelot, Patrick; Monet, David

    2011-03-01

    In this article we present the coordinates of 67 55' × 55' patches of sky that have the rare combination of both high stellar surface density (>=0.5 arcmin-2 with 13 < R < 16.5 mag) and low extinction (E(B - V)<=0.1). These fields are ideal for adaptive-optics-based follow-up of extragalactic targets. One region of sky, situated near Baade's Window, contains most of the patches we have identified. Our optimal field, centered at R.A.: 7h24m3s, decl.: -1°27'15'', has an additional advantage of being accessible from both hemispheres. We propose a figure of merit for quantifying real-world adaptive optics performance and use this to analyze the performance of multiconjugate adaptive optics in these fields. We also compare our results with those that would be obtained in existing deep fields. In some cases adaptive optics observations undertaken in the fields given in this article would be orders of magnitude more efficient than equivalent observations undertaken in existing deep fields.

  15. Cyclone performance and optimization

    SciTech Connect

    Leith, D.

    1990-09-15

    The objectives of this project are: to characterize the gas flow pattern within cyclones, to revise the theory for cyclone performance on the basis of these findings, and to design and test cyclones whose dimensions have been optimized using revised performance theory. This work is important because its successful completion will aid in the technology for combustion of coal in pressurized, fluidized beds. This quarter, an empirical model for predicting pressure drop across a cyclone was developed through a statistical analysis of pressure drop data for 98 cyclone designs. The model is shown to perform better than the pressure drop models of First (1950), Alexander (1949), Barth (1956), Stairmand (1949), and Shepherd-Lapple (1940). This model is used with the efficiency model of Iozia and Leith (1990) to develop an optimization curve which predicts the minimum pressure drop and the dimension rations of the optimized cyclone for a given aerodynamic cut diameter, d{sub 50}. The effect of variation in cyclone height, cyclone diameter, and flow on the optimization curve is determined. The optimization results are used to develop a design procedure for optimized cyclones. 37 refs., 10 figs., 4 tabs.

  16. Adaptive Optics Communications Performance Analysis

    NASA Technical Reports Server (NTRS)

    Srinivasan, M.; Vilnrotter, V.; Troy, M.; Wilson, K.

    2004-01-01

    The performance improvement obtained through the use of adaptive optics for deep-space communications in the presence of atmospheric turbulence is analyzed. Using simulated focal-plane signal-intensity distributions, uncoded pulse-position modulation (PPM) bit-error probabilities are calculated assuming the use of an adaptive focal-plane detector array as well as an adaptively sized single detector. It is demonstrated that current practical adaptive optics systems can yield performance gains over an uncompensated system ranging from approximately 1 dB to 6 dB depending upon the PPM order and background radiation level.

  17. Adaptive approximation models in optimization

    SciTech Connect

    Voronin, A.N.

    1995-05-01

    The paper proposes a method for optimization of functions of several variables that substantially reduces the number of objective function evaluations compared to traditional methods. The method is based on the property of iterative refinement of approximation models of the optimand function in approximation domains that contract to the extremum point. It does not require subjective specification of the starting point, step length, or other parameters of the search procedure. The method is designed for efficient optimization of unimodal functions of several (not more than 10-15) variables and can be applied to find the global extremum of polymodal functions and also for optimization of scalarized forms of vector objective functions.

  18. Russian Loanword Adaptation in Persian; Optimal Approach

    ERIC Educational Resources Information Center

    Kambuziya, Aliye Kord Zafaranlu; Hashemi, Eftekhar Sadat

    2011-01-01

    In this paper we analyzed some of the phonological rules of Russian loanword adaptation in Persian, on the view of Optimal Theory (OT) (Prince & Smolensky, 1993/2004). It is the first study of phonological process on Russian loanwords adaptation in Persian. By gathering about 50 current Russian loanwords, we selected some of them to analyze. We…

  19. Cyclone performance and optimization

    SciTech Connect

    Leith, D.

    1990-06-15

    The objectives of this project are: to characterize the gas flow pattern within cyclones, to revise the theory for cyclone performance on the basis of these findings, and to design and test cyclones whose dimensions have been optimized using revised performance theory. This work is important because its successful completion will aid in the technology for combustion of coal in pressurized, fluidized beds. During the past quarter, we have nearly completed modeling work that employs the flow field measurements made during the past six months. In addition, we have begun final work using the results of this project to develop improved design methods for cyclones. This work involves optimization using the Iozia-Leith efficiency model and the Dirgo pressure drop model. This work will be completed this summer. 9 figs.

  20. Dynamic optimization and adaptive controller design

    NASA Astrophysics Data System (ADS)

    Inamdar, S. R.

    2010-10-01

    In this work I present a new type of controller which is an adaptive tracking controller which employs dynamic optimization for optimizing current value of controller action for the temperature control of nonisothermal continuously stirred tank reactor (CSTR). We begin with a two-state model of nonisothermal CSTR which are mass and heat balance equations and then add cooling system dynamics to eliminate input multiplicity. The initial design value is obtained using local stability of steady states where approach temperature for cooling action is specified as a steady state and a design specification. Later we make a correction in the dynamics where material balance is manipulated to use feed concentration as a system parameter as an adaptive control measure in order to avoid actuator saturation for the main control loop. The analysis leading to design of dynamic optimization based parameter adaptive controller is presented. The important component of this mathematical framework is reference trajectory generation to form an adaptive control measure.

  1. Adaptation and optimization of biological transport networks.

    PubMed

    Hu, Dan; Cai, David

    2013-09-27

    It has been hypothesized that topological structures of biological transport networks are consequences of energy optimization. Motivated by experimental observation, we propose that adaptation dynamics may underlie this optimization. In contrast to the global nature of optimization, our adaptation dynamics responds only to local information and can naturally incorporate fluctuations in flow distributions. The adaptation dynamics minimizes the global energy consumption to produce optimal networks, which may possess hierarchical loop structures in the presence of strong fluctuations in flow distribution. We further show that there may exist a new phase transition as there is a critical open probability of sinks, above which there are only trees for network structures whereas below which loops begin to emerge.

  2. Cyclone performance and optimization

    SciTech Connect

    Leith, D.

    1989-06-15

    The objectives of this project are: to characterize the gas flow pattern within cyclones, to revise the theory for cyclone performance on the basis of these findings, and to design and test cyclones whose dimensions have been optimized using revised performance theory. This work is important because its successful completion will aid in the technology for combustion of coal in pressurized, fluidized beds. We have now received all the equipment necessary for the flow visualization studies described over the last two progress reports. We have begun more detailed studies of the gas flow pattern within cyclones as detailed below. Third, we have begun studies of the effect of particle concentration on cyclone performance. This work is critical to application of our results to commercial operations. 1 fig.

  3. Hybrid and adaptive meta-model-based global optimization

    NASA Astrophysics Data System (ADS)

    Gu, J.; Li, G. Y.; Dong, Z.

    2012-01-01

    As an efficient and robust technique for global optimization, meta-model-based search methods have been increasingly used in solving complex and computation intensive design optimization problems. In this work, a hybrid and adaptive meta-model-based global optimization method that can automatically select appropriate meta-modelling techniques during the search process to improve search efficiency is introduced. The search initially applies three representative meta-models concurrently. Progress towards a better performing model is then introduced by selecting sample data points adaptively according to the calculated values of the three meta-models to improve modelling accuracy and search efficiency. To demonstrate the superior performance of the new algorithm over existing search methods, the new method is tested using various benchmark global optimization problems and applied to a real industrial design optimization example involving vehicle crash simulation. The method is particularly suitable for design problems involving computation intensive, black-box analyses and simulations.

  4. Optimized micromirror arrays for adaptive optics

    NASA Astrophysics Data System (ADS)

    Michalicek, M. Adrian; Comtois, John H.; Hetherington, Dale L.

    1999-01-01

    This paper describes the design, layout, fabrication, and surface characterization of highly optimized surface micromachined micromirror devices. Design considerations and fabrication capabilities are presented. These devices are fabricated in the state-of-the-art, four-level, planarized, ultra-low-stress polysilicon process available at Sandia National Laboratories known as the Sandia Ultra-planar Multi-level MEMS Technology (SUMMiT). This enabling process permits the development of micromirror devices with near-ideal characteristics that have previously been unrealizable in standard three-layer polysilicon processes. The reduced 1 μm minimum feature sizes and 0.1 μm mask resolution make it possible to produce dense wiring patterns and irregularly shaped flexures. Likewise, mirror surfaces can be uniquely distributed and segmented in advanced patterns and often irregular shapes in order to minimize wavefront error across the pupil. The ultra-low-stress polysilicon and planarized upper layer allow designers to make larger and more complex micromirrors of varying shape and surface area within an array while maintaining uniform performance of optical surfaces. Powerful layout functions of the AutoCAD editor simplify the design of advanced micromirror arrays and make it possible to optimize devices according to the capabilities of the fabrication process. Micromirrors fabricated in this process have demonstrated a surface variance across the array from only 2-3 nm to a worst case of roughly 25 nm while boasting active surface areas of 98% or better. Combining the process planarization with a ``planarized-by-design'' approach will produce micromirror array surfaces that are limited in flatness only by the surface deposition roughness of the structural material. Ultimately, the combination of advanced process and layout capabilities have permitted the fabrication of highly optimized micromirror arrays for adaptive optics.

  5. Cyclone performance and optimization

    SciTech Connect

    Leith, D.

    1989-03-15

    The objectives of this project are: to characterize the gas flow pattern within cyclones, to revise the theory for cyclone performance on the basis of these findings, and to design and test cyclones whose dimensions have been optimized using revised performance theory. This work is important because its successful completion will aid in the technology for combustion of coal in pressurized, fluidized beds. This quarter, we have been hampered somewhat by flow delivery of the bubble generation system and arc lighting system placed on order last fall. This equipment is necessary to map the flow field within cyclones using the techniques described in last quarter's report. Using the bubble generator, we completed this quarter a study of the natural length'' of cyclones of 18 different configurations, each configuration operated at five different gas flows. Results suggest that the equation by Alexander for natural length is incorrect; natural length as measured with the bubble generation system is always below the bottom of the cyclones regardless of the cyclone configuration or gas flow, within the limits of the experimental cyclones tested. This finding is important because natural length is a term in equations used to predict cyclone efficiency. 1 tab.

  6. Adaptive stimulus optimization for sensory systems neuroscience.

    PubMed

    DiMattina, Christopher; Zhang, Kechen

    2013-01-01

    In this paper, we review several lines of recent work aimed at developing practical methods for adaptive on-line stimulus generation for sensory neurophysiology. We consider various experimental paradigms where on-line stimulus optimization is utilized, including the classical optimal stimulus paradigm where the goal of experiments is to identify a stimulus which maximizes neural responses, the iso-response paradigm which finds sets of stimuli giving rise to constant responses, and the system identification paradigm where the experimental goal is to estimate and possibly compare sensory processing models. We discuss various theoretical and practical aspects of adaptive firing rate optimization, including optimization with stimulus space constraints, firing rate adaptation, and possible network constraints on the optimal stimulus. We consider the problem of system identification, and show how accurate estimation of non-linear models can be highly dependent on the stimulus set used to probe the network. We suggest that optimizing stimuli for accurate model estimation may make it possible to successfully identify non-linear models which are otherwise intractable, and summarize several recent studies of this type. Finally, we present a two-stage stimulus design procedure which combines the dual goals of model estimation and model comparison and may be especially useful for system identification experiments where the appropriate model is unknown beforehand. We propose that fast, on-line stimulus optimization enabled by increasing computer power can make it practical to move sensory neuroscience away from a descriptive paradigm and toward a new paradigm of real-time model estimation and comparison.

  7. Adaptive stimulus optimization for sensory systems neuroscience

    PubMed Central

    DiMattina, Christopher; Zhang, Kechen

    2013-01-01

    In this paper, we review several lines of recent work aimed at developing practical methods for adaptive on-line stimulus generation for sensory neurophysiology. We consider various experimental paradigms where on-line stimulus optimization is utilized, including the classical optimal stimulus paradigm where the goal of experiments is to identify a stimulus which maximizes neural responses, the iso-response paradigm which finds sets of stimuli giving rise to constant responses, and the system identification paradigm where the experimental goal is to estimate and possibly compare sensory processing models. We discuss various theoretical and practical aspects of adaptive firing rate optimization, including optimization with stimulus space constraints, firing rate adaptation, and possible network constraints on the optimal stimulus. We consider the problem of system identification, and show how accurate estimation of non-linear models can be highly dependent on the stimulus set used to probe the network. We suggest that optimizing stimuli for accurate model estimation may make it possible to successfully identify non-linear models which are otherwise intractable, and summarize several recent studies of this type. Finally, we present a two-stage stimulus design procedure which combines the dual goals of model estimation and model comparison and may be especially useful for system identification experiments where the appropriate model is unknown beforehand. We propose that fast, on-line stimulus optimization enabled by increasing computer power can make it practical to move sensory neuroscience away from a descriptive paradigm and toward a new paradigm of real-time model estimation and comparison. PMID:23761737

  8. Neurophysiology of performance monitoring and adaptive behavior.

    PubMed

    Ullsperger, Markus; Danielmeier, Claudia; Jocham, Gerhard

    2014-01-01

    Successful goal-directed behavior requires not only correct action selection, planning, and execution but also the ability to flexibly adapt behavior when performance problems occur or the environment changes. A prerequisite for determining the necessity, type, and magnitude of adjustments is to continuously monitor the course and outcome of one's actions. Feedback-control loops correcting deviations from intended states constitute a basic functional principle of adaptation at all levels of the nervous system. Here, we review the neurophysiology of evaluating action course and outcome with respect to their valence, i.e., reward and punishment, and initiating short- and long-term adaptations, learning, and decisions. Based on studies in humans and other mammals, we outline the physiological principles of performance monitoring and subsequent cognitive, motivational, autonomic, and behavioral adaptation and link them to the underlying neuroanatomy, neurochemistry, psychological theories, and computational models. We provide an overview of invasive and noninvasive systemic measures, such as electrophysiological, neuroimaging, and lesion data. We describe how a wide network of brain areas encompassing frontal cortices, basal ganglia, thalamus, and monoaminergic brain stem nuclei detects and evaluates deviations of actual from predicted states indicating changed action costs or outcomes. This information is used to learn and update stimulus and action values, guide action selection, and recruit adaptive mechanisms that compensate errors and optimize goal achievement.

  9. Development of a digital adaptive optimal linear regulator flight controller

    NASA Technical Reports Server (NTRS)

    Berry, P.; Kaufman, H.

    1975-01-01

    Digital adaptive controllers have been proposed as a means for retaining uniform handling qualities over the flight envelope of a high-performance aircraft. Towards such an implementation, an explicit adaptive controller, which makes direct use of online parameter identification, has been developed and applied to the linearized lateral equations of motion for a typical fighter aircraft. The system is composed of an online weighted least-squares parameter identifier, a Kalman state filter, and a model following control law designed using optimal linear regulator theory. Simulation experiments with realistic measurement noise indicate that the proposed adaptive system has the potential for onboard implementation.

  10. Optimal fully adaptive wormhole routing for meshes

    SciTech Connect

    Schwiebert, L.; Jayasimha, D.N.

    1993-12-31

    A deadlock-free fully adaptive routing algorithm for 2D meshes which is optimal in the number of virtual channels required and in the number of restrictions placed on the use of these virtual channels is presented. The routing algorithm imposes less than half as many routing restrictions as any previous fully adaptive routing algorithm. It is also proved that, ignoring symmetry, this routing algorithm is the only fully adaptive routing algorithm that achieves both of these goals. The implementation of the routing algorithm requires relatively simple router control logic. The new algorithm is extended, in a straightforward manner to arbitrary dimension meshes. It needs only 4n-2 virtual channels, the minimum number for an n-dimensional mesh. All previous algorithms require an exponential number of virtual channels in the dimension of the mesh.

  11. MPQC: Performance Analysis and Optimization

    SciTech Connect

    Sarje, Abhinav; Williams, Samuel; Bailey, David

    2012-11-30

    MPQC (Massively Parallel Quantum Chemistry) is a widely used computational quantum chemistry code. It is capable of performing a number of computations commonly occurring in quantum chemistry. In order to achieve better performance of MPQC, in this report we present a detailed performance analysis of this code. We then perform loop and memory access optimizations, and measure performance improvements by comparing the performance of the optimized code with that of the original MPQC code. We observe that the optimized MPQC code achieves a significant improvement in the performance through a better utilization of vector processing and memory hierarchies.

  12. An Adaptive Unified Differential Evolution Algorithm for Global Optimization

    SciTech Connect

    Qiang, Ji; Mitchell, Chad

    2014-11-03

    In this paper, we propose a new adaptive unified differential evolution algorithm for single-objective global optimization. Instead of the multiple mutation strate- gies proposed in conventional differential evolution algorithms, this algorithm employs a single equation unifying multiple strategies into one expression. It has the virtue of mathematical simplicity and also provides users the flexibility for broader exploration of the space of mutation operators. By making all control parameters in the proposed algorithm self-adaptively evolve during the process of optimization, it frees the application users from the burden of choosing appro- priate control parameters and also improves the performance of the algorithm. In numerical tests using thirteen basic unimodal and multimodal functions, the proposed adaptive unified algorithm shows promising performance in compari- son to several conventional differential evolution algorithms.

  13. Structured near-optimal channel-adapted quantum error correction

    NASA Astrophysics Data System (ADS)

    Fletcher, Andrew S.; Shor, Peter W.; Win, Moe Z.

    2008-01-01

    We present a class of numerical algorithms which adapt a quantum error correction scheme to a channel model. Given an encoding and a channel model, it was previously shown that the quantum operation that maximizes the average entanglement fidelity may be calculated by a semidefinite program (SDP), which is a convex optimization. While optimal, this recovery operation is computationally difficult for long codes. Furthermore, the optimal recovery operation has no structure beyond the completely positive trace-preserving constraint. We derive methods to generate structured channel-adapted error recovery operations. Specifically, each recovery operation begins with a projective error syndrome measurement. The algorithms to compute the structured recovery operations are more scalable than the SDP and yield recovery operations with an intuitive physical form. Using Lagrange duality, we derive performance bounds to certify near-optimality.

  14. Adaptive Wing Camber Optimization: A Periodic Perturbation Approach

    NASA Technical Reports Server (NTRS)

    Espana, Martin; Gilyard, Glenn

    1994-01-01

    Available redundancy among aircraft control surfaces allows for effective wing camber modifications. As shown in the past, this fact can be used to improve aircraft performance. To date, however, algorithm developments for in-flight camber optimization have been limited. This paper presents a perturbational approach for cruise optimization through in-flight camber adaptation. The method uses, as a performance index, an indirect measurement of the instantaneous net thrust. As such, the actual performance improvement comes from the integrated effects of airframe and engine. The algorithm, whose design and robustness properties are discussed, is demonstrated on the NASA Dryden B-720 flight simulator.

  15. Direct aperture optimization for online adaptive radiation therapy

    SciTech Connect

    Mestrovic, Ante; Milette, Marie-Pierre; Nichol, Alan; Clark, Brenda G.; Otto, Karl

    2007-05-15

    This paper is the first investigation of using direct aperture optimization (DAO) for online adaptive radiation therapy (ART). A geometrical model representing the anatomy of a typical prostate case was created. To simulate interfractional deformations, four different anatomical deformations were created by systematically deforming the original anatomy by various amounts (0.25, 0.50, 0.75, and 1.00 cm). We describe a series of techniques where the original treatment plan was adapted in order to correct for the deterioration of dose distribution quality caused by the anatomical deformations. We found that the average time needed to adapt the original plan to arrive at a clinically acceptable plan is roughly half of the time needed for a complete plan regeneration, for all four anatomical deformations. Furthermore, through modification of the DAO algorithm the optimization search space was reduced and the plan adaptation was significantly accelerated. For the first anatomical deformation (0.25 cm), the plan adaptation was six times more efficient than the complete plan regeneration. For the 0.50 and 0.75 cm deformations, the optimization efficiency was increased by a factor of roughly 3 compared to the complete plan regeneration. However, for the anatomical deformation of 1.00 cm, the reduction of the optimization search space during plan adaptation did not result in any efficiency improvement over the original (nonmodified) plan adaptation. The anatomical deformation of 1.00 cm demonstrates the limit of this approach. We propose an innovative approach to online ART in which the plan adaptation and radiation delivery are merged together and performed concurrently--adaptive radiation delivery (ARD). A fundamental advantage of ARD is the fact that radiation delivery can start almost immediately after image acquisition and evaluation. Most of the original plan adaptation is done during the radiation delivery, so the time spent adapting the original plan does not

  16. Optimal Bayesian Adaptive Design for Test-Item Calibration.

    PubMed

    van der Linden, Wim J; Ren, Hao

    2015-06-01

    An optimal adaptive design for test-item calibration based on Bayesian optimality criteria is presented. The design adapts the choice of field-test items to the examinees taking an operational adaptive test using both the information in the posterior distributions of their ability parameters and the current posterior distributions of the field-test parameters. Different criteria of optimality based on the two types of posterior distributions are possible. The design can be implemented using an MCMC scheme with alternating stages of sampling from the posterior distributions of the test takers' ability parameters and the parameters of the field-test items while reusing samples from earlier posterior distributions of the other parameters. Results from a simulation study demonstrated the feasibility of the proposed MCMC implementation for operational item calibration. A comparison of performances for different optimality criteria showed faster calibration of substantial numbers of items for the criterion of D-optimality relative to A-optimality, a special case of c-optimality, and random assignment of items to the test takers.

  17. Predictive optimized adaptive PSS in a single machine infinite bus.

    PubMed

    Milla, Freddy; Duarte-Mermoud, Manuel A

    2016-07-01

    Power System Stabilizer (PSS) devices are responsible for providing a damping torque component to generators for reducing fluctuations in the system caused by small perturbations. A Predictive Optimized Adaptive PSS (POA-PSS) to improve the oscillations in a Single Machine Infinite Bus (SMIB) power system is discussed in this paper. POA-PSS provides the optimal design parameters for the classic PSS using an optimization predictive algorithm, which adapts to changes in the inputs of the system. This approach is part of small signal stability analysis, which uses equations in an incremental form around an operating point. Simulation studies on the SMIB power system illustrate that the proposed POA-PSS approach has better performance than the classical PSS. In addition, the effort in the control action of the POA-PSS is much less than that of other approaches considered for comparison.

  18. Optimal Control Modification for Robust Adaptation of Singularly Perturbed Systems with Slow Actuators

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.; Ishihara, Abraham; Stepanyan, Vahram; Boskovic, Jovan

    2009-01-01

    Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. The model matching conditions in the transformed time coordinate results in increase in the feedback gain and modification of the adaptive law.

  19. Performance and physiologic adaptations to resistance training.

    PubMed

    Deschenes, Michael R; Kraemer, William J

    2002-11-01

    Weight lifting, or resistance training, is a potent stimulus to the neuromuscular system. Depending on the specific program design, resistance training can enhance strength, power, or local muscular endurance. These improvements in performance are directly related to the physiologic adaptations elicited through prolonged resistance training. Optimal resistance training programs are individualized to meet specific training goals. When trained properly (i.e., similar intensity and volume), these functional and physiologic adaptations are similarly impressive among women and the aged as they are among young men. Yet, in contrast to relative measurements, sex and age differences exist in the absolute magnitude of adaptation. Of equal importance, perhaps most notably among the elderly, are the important health benefits that may also be derived from resistance training. For example, bone density, insulin sensitivity, and co-morbidities associated with obesity can be effectively managed with resistance exercise when it is conducted on a regular basis. The extent of the functional and health benefits to be accrued from resistance training depend on factors such as initial performance and health status, along with the specification of program design variables such as frequency, duration, intensity, volume, and rest intervals. PMID:12409807

  20. Support Vector Machine Based on Adaptive Acceleration Particle Swarm Optimization

    PubMed Central

    Abdulameer, Mohammed Hasan; Othman, Zulaiha Ali

    2014-01-01

    Existing face recognition methods utilize particle swarm optimizer (PSO) and opposition based particle swarm optimizer (OPSO) to optimize the parameters of SVM. However, the utilization of random values in the velocity calculation decreases the performance of these techniques; that is, during the velocity computation, we normally use random values for the acceleration coefficients and this creates randomness in the solution. To address this problem, an adaptive acceleration particle swarm optimization (AAPSO) technique is proposed. To evaluate our proposed method, we employ both face and iris recognition based on AAPSO with SVM (AAPSO-SVM). In the face and iris recognition systems, performance is evaluated using two human face databases, YALE and CASIA, and the UBiris dataset. In this method, we initially perform feature extraction and then recognition on the extracted features. In the recognition process, the extracted features are used for SVM training and testing. During the training and testing, the SVM parameters are optimized with the AAPSO technique, and in AAPSO, the acceleration coefficients are computed using the particle fitness values. The parameters in SVM, which are optimized by AAPSO, perform efficiently for both face and iris recognition. A comparative analysis between our proposed AAPSO-SVM and the PSO-SVM technique is presented. PMID:24790584

  1. Support vector machine based on adaptive acceleration particle swarm optimization.

    PubMed

    Abdulameer, Mohammed Hasan; Sheikh Abdullah, Siti Norul Huda; Othman, Zulaiha Ali

    2014-01-01

    Existing face recognition methods utilize particle swarm optimizer (PSO) and opposition based particle swarm optimizer (OPSO) to optimize the parameters of SVM. However, the utilization of random values in the velocity calculation decreases the performance of these techniques; that is, during the velocity computation, we normally use random values for the acceleration coefficients and this creates randomness in the solution. To address this problem, an adaptive acceleration particle swarm optimization (AAPSO) technique is proposed. To evaluate our proposed method, we employ both face and iris recognition based on AAPSO with SVM (AAPSO-SVM). In the face and iris recognition systems, performance is evaluated using two human face databases, YALE and CASIA, and the UBiris dataset. In this method, we initially perform feature extraction and then recognition on the extracted features. In the recognition process, the extracted features are used for SVM training and testing. During the training and testing, the SVM parameters are optimized with the AAPSO technique, and in AAPSO, the acceleration coefficients are computed using the particle fitness values. The parameters in SVM, which are optimized by AAPSO, perform efficiently for both face and iris recognition. A comparative analysis between our proposed AAPSO-SVM and the PSO-SVM technique is presented. PMID:24790584

  2. Optimal Control Modification Adaptive Law for Time-Scale Separated Systems

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.

    2010-01-01

    Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. A model matching conditions in the transformed time coordinate results in an increase in the actuator command that effectively compensate for the slow actuator dynamics. Simulations demonstrate effectiveness of the method.

  3. Optimizing rotary drill performance

    SciTech Connect

    Schivley, G.P. Jr.

    1995-12-31

    Data is presented showing Penetration Rate (PR) versus Force-on-the-Bit (FB) and Bit Angular Speed (N). Using this data, it is shown how FB and N each uniquely contribute to the PR for any particular drilling situation. This data represents many mining situations; including coal, copper, gold, iron ore and limestone quarrying. The important relationship between Penetration per Revolution (P/R) and the height of the cutting elements of the bit (CH) is discussed. Drill performance is then reviewed, considering the effect of FB and N on bit life. All this leads to recommendations for the operating values of FB and N for drilling situations where the rock is not highly abrasive and bit replacements are because of catastrophic failure of the bit cone bearings. The contribution of compressed air to the drilling process is discussed. It is suggested that if the air issuing from the bit jets is supersonic that may enhance the sweeping of the hole bottom. Also, it is shown that not just uphole air velocity is enough to provide adequate transport of the rock cuttings up the annulus of a drilled hole. In addition, air volume flow rate must be considered to assure there is adequate particle spacing so the mechanism of aerodynamic drag can effectively lift the cuttings up and out of the hole annulus.

  4. A Tutorial on Adaptive Design Optimization

    PubMed Central

    Myung, Jay I.; Cavagnaro, Daniel R.; Pitt, Mark A.

    2013-01-01

    Experimentation is ubiquitous in the field of psychology and fundamental to the advancement of its science, and one of the biggest challenges for researchers is designing experiments that can conclusively discriminate the theoretical hypotheses or models under investigation. The recognition of this challenge has led to the development of sophisticated statistical methods that aid in the design of experiments and that are within the reach of everyday experimental scientists. This tutorial paper introduces the reader to an implementable experimentation methodology, dubbed Adaptive Design Optimization, that can help scientists to conduct “smart” experiments that are maximally informative and highly efficient, which in turn should accelerate scientific discovery in psychology and beyond. PMID:23997275

  5. Performance Optimization and Auto-Tuning

    SciTech Connect

    Howison, Mark

    2012-10-01

    In the broader computational research community, one subject of recent research is the problem of adapting algorithms to make effective use of multi- and many-core processors. Effective use of these architectures, which have complex memory hierarchies with many layers of cache, typically involves a careful examination of how an algorithm moves data through the memory hierarchy. Unfortunately, there is often a non-obvious relationship between algorithmic parameters like blocking strategies, and their impact on memory utilization, and, in turn, the relationship with runtime performance. Auto-tuning is an empirical method used to discover optimal values for tunable algorithmic parameters under such circumstances. The challenge is compounded by the fact that the settings that produce the best performance for a given problem and a given platform may not be the best for a different problem on the same platform, or the same problem on a different platform. The high performance visualization research community has begun to explore and adapt the principles of auto-tuning for the purpose of optimizing codes on modern multi- and many-core processors. This report focuses on how performance optimization studies reveal a dramatic variation in performance for two fundamental visualization algorithms: one based on a stencil operation having structured, uniform memory access, and the other is ray casting volume rendering, which uses unstructured memory access patterns. The two case studies highlighted in this report show the extra effort required to optimize such codes by adjusting the tunable algorithmic parameters can return substantial gains in performance. Additionally, these case studies also explore the potential impact of and the interaction between algorithmic optimizations and tunable algorithmic parameters, along with the potential performance gains resulting from leveraging architecture-specific features.

  6. Adaptive Mallow's optimization for weighted median filters

    NASA Astrophysics Data System (ADS)

    Rachuri, Raghu; Rao, Sathyanarayana S.

    2002-05-01

    This work extends the idea of spectral optimization for the design of Weighted Median filters and employ adaptive filtering that updates the coefficients of the FIR filter from which the weights of the median filters are derived. Mallows' theory of non-linear smoothers [1] has proven to be of great theoretical significance providing simple design guidelines for non-linear smoothers. It allows us to find a set of positive weights for a WM filter whose sample selection probabilities (SSP's) are as close as possible to a SSP set predetermined by Mallow's. Sample selection probabilities have been used as a basis for designing stack smoothers as they give a measure of the filter's detail preserving ability and give non-negative filter weights. We will extend this idea to design weighted median filters admitting negative weights. The new method first finds the linear FIR filter coefficients adaptively, which are then used to determine the weights of the median filter. WM filters can be designed to have band-pass, high-pass as well as low-pass frequency characteristics. Unlike the linear filters, however, the weighted median filters are robust in the presence of impulsive noise, as shown by the simulation results.

  7. Adaptive neuro-fuzzy estimation of optimal lens system parameters

    NASA Astrophysics Data System (ADS)

    Petković, Dalibor; Pavlović, Nenad T.; Shamshirband, Shahaboddin; Mat Kiah, Miss Laiha; Badrul Anuar, Nor; Idna Idris, Mohd Yamani

    2014-04-01

    Due to the popularization of digital technology, the demand for high-quality digital products has become critical. The quantitative assessment of image quality is an important consideration in any type of imaging system. Therefore, developing a design that combines the requirements of good image quality is desirable. Lens system design represents a crucial factor for good image quality. Optimization procedure is the main part of the lens system design methodology. Lens system optimization is a complex non-linear optimization task, often with intricate physical constraints, for which there is no analytical solutions. Therefore lens system design provides ideal problems for intelligent optimization algorithms. There are many tools which can be used to measure optical performance. One very useful tool is the spot diagram. The spot diagram gives an indication of the image of a point object. In this paper, one optimization criterion for lens system, the spot size radius, is considered. This paper presents new lens optimization methods based on adaptive neuro-fuzzy inference strategy (ANFIS). This intelligent estimator is implemented using Matlab/Simulink and the performances are investigated.

  8. Network inference via adaptive optimal design

    PubMed Central

    2012-01-01

    Background Current research in network reverse engineering for genetic or metabolic networks very often does not include a proper experimental and/or input design. In this paper we address this issue in more detail and suggest a method that includes an iterative design of experiments based, on the most recent data that become available. The presented approach allows a reliable reconstruction of the network and addresses an important issue, i.e., the analysis and the propagation of uncertainties as they exist in both the data and in our own knowledge. These two types of uncertainties have their immediate ramifications for the uncertainties in the parameter estimates and, hence, are taken into account from the very beginning of our experimental design. Findings The method is demonstrated for two small networks that include a genetic network for mRNA synthesis and degradation and an oscillatory network describing a molecular network underlying adenosine 3’-5’ cyclic monophosphate (cAMP) as observed in populations of Dyctyostelium cells. In both cases a substantial reduction in parameter uncertainty was observed. Extension to larger scale networks is possible but needs a more rigorous parameter estimation algorithm that includes sparsity as a constraint in the optimization procedure. Conclusion We conclude that a careful experiment design very often (but not always) pays off in terms of reliability in the inferred network topology. For large scale networks a better parameter estimation algorithm is required that includes sparsity as an additional constraint. These algorithms are available in the literature and can also be used in an adaptive optimal design setting as demonstrated in this paper. PMID:22999252

  9. Expected treatment dose construction and adaptive inverse planning optimization: Implementation for offline head and neck cancer adaptive radiotherapy

    SciTech Connect

    Yan Di; Liang Jian

    2013-02-15

    Purpose: To construct expected treatment dose for adaptive inverse planning optimization, and evaluate it on head and neck (h and n) cancer adaptive treatment modification. Methods: Adaptive inverse planning engine was developed and integrated in our in-house adaptive treatment control system. The adaptive inverse planning engine includes an expected treatment dose constructed using the daily cone beam (CB) CT images in its objective and constrains. Feasibility of the adaptive inverse planning optimization was evaluated retrospectively using daily CBCT images obtained from the image guided IMRT treatment of 19 h and n cancer patients. Adaptive treatment modification strategies with respect to the time and the number of adaptive inverse planning optimization during the treatment course were evaluated using the cumulative treatment dose in organs of interest constructed using all daily CBCT images. Results: Expected treatment dose was constructed to include both the delivered dose, to date, and the estimated dose for the remaining treatment during the adaptive treatment course. It was used in treatment evaluation, as well as in constructing the objective and constraints for adaptive inverse planning optimization. The optimization engine is feasible to perform planning optimization based on preassigned treatment modification schedule. Compared to the conventional IMRT, the adaptive treatment for h and n cancer illustrated clear dose-volume improvement for all critical normal organs. The dose-volume reductions of right and left parotid glands, spine cord, brain stem and mandible were (17 {+-} 6)%, (14 {+-} 6)%, (11 {+-} 6)%, (12 {+-} 8)%, and (5 {+-} 3)% respectively with the single adaptive modification performed after the second treatment week; (24 {+-} 6)%, (22 {+-} 8)%, (21 {+-} 5)%, (19 {+-} 8)%, and (10 {+-} 6)% with three weekly modifications; and (28 {+-} 5)%, (25 {+-} 9)%, (26 {+-} 5)%, (24 {+-} 8)%, and (15 {+-} 9)% with five weekly modifications. Conclusions

  10. An adaptive immune optimization algorithm with dynamic lattice searching operation for fast optimization of atomic clusters

    NASA Astrophysics Data System (ADS)

    Wu, Xia; Wu, Genhua

    2014-08-01

    Geometrical optimization of atomic clusters is performed by a development of adaptive immune optimization algorithm (AIOA) with dynamic lattice searching (DLS) operation (AIOA-DLS method). By a cycle of construction and searching of the dynamic lattice (DL), DLS algorithm rapidly makes the clusters more regular and greatly reduces the potential energy. DLS can thus be used as an operation acting on the new individuals after mutation operation in AIOA to improve the performance of the AIOA. The AIOA-DLS method combines the merit of evolutionary algorithm and idea of dynamic lattice. The performance of the proposed method is investigated in the optimization of Lennard-Jones clusters within 250 atoms and silver clusters described by many-body Gupta potential within 150 atoms. Results reported in the literature are reproduced, and the motif of Ag61 cluster is found to be stacking-fault face-centered cubic, whose energy is lower than that of previously obtained icosahedron.

  11. Optimization under uncertainty: Adaptive variance reduction, adaptive metamodeling, and investigation of robustness measures

    NASA Astrophysics Data System (ADS)

    Medina, Juan Camilo

    This dissertation offers computational and theoretical advances for optimization under uncertainty problems that utilize a probabilistic framework for addressing such uncertainties, and adopt a probabilistic performance as objective function. Emphasis is placed on applications that involve potentially complex numerical and probability models. A generalized approach is adopted, treating the system model as a "black-box" and relying on stochastic simulation for evaluating the probabilistic performance. This approach can impose, though, an elevated computational cost, and two of the advances offered in this dissertation aim at decreasing the computational burden associated with stochastic simulation when integrated with optimization applications. The first one develops an adaptive implementation of importance sampling (a popular variance reduction technique) by sharing information across the iterations of the numerical optimization algorithm. The system model evaluations from the current iteration are utilized to formulate importance sampling densities for subsequent iterations with only a small additional computational effort. The characteristics of these densities as well as the specific model parameters these densities span are explicitly optimized. The second advancement focuses on adaptive tuning of a kriging metamodel to replace the computationally intensive system model. A novel implementation is considered, establishing a metamodel with respect to both the uncertain model parameters as well as the design variables, offering significant computational savings. Additionally, the adaptive selection of certain characteristics of the metamodel, such as support points or order of basis functions, is considered by utilizing readily available information from the previous iteration of the optimization algorithm. The third advancement extends to a different application and considers the assessment of the appropriateness of different candidate robust designs. A novel

  12. Adaptive Flight Control Design with Optimal Control Modification on an F-18 Aircraft Model

    NASA Technical Reports Server (NTRS)

    Burken, John J.; Nguyen, Nhan T.; Griffin, Brian J.

    2010-01-01

    In the presence of large uncertainties, a control system needs to be able to adapt rapidly to regain performance. Fast adaptation is referred to as the implementation of adaptive control with a large adaptive gain to reduce the tracking error rapidly; however, a large adaptive gain can lead to high-frequency oscillations which can adversely affect the robustness of an adaptive control law. A new adaptive control modification is presented that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. The modification is based on the minimization of the Y2 norm of the tracking error, which is formulated as an optimal control problem. The optimality condition is used to derive the modification using the gradient method. The optimal control modification results in a stable adaptation and allows a large adaptive gain to be used for better tracking while providing sufficient robustness. A damping term (v) is added in the modification to increase damping as needed. Simulations were conducted on a damaged F-18 aircraft (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) with both the standard baseline dynamic inversion controller and the adaptive optimal control modification technique. The results demonstrate the effectiveness of the proposed modification in tracking a reference model.

  13. Adaptive, predictive controller for optimal process control

    SciTech Connect

    Brown, S.K.; Baum, C.C.; Bowling, P.S.; Buescher, K.L.; Hanagandi, V.M.; Hinde, R.F. Jr.; Jones, R.D.; Parkinson, W.J.

    1995-12-01

    One can derive a model for use in a Model Predictive Controller (MPC) from first principles or from experimental data. Until recently, both methods failed for all but the simplest processes. First principles are almost always incomplete and fitting to experimental data fails for dimensions greater than one as well as for non-linear cases. Several authors have suggested the use of a neural network to fit the experimental data to a multi-dimensional and/or non-linear model. Most networks, however, use simple sigmoid functions and backpropagation for fitting. Training of these networks generally requires large amounts of data and, consequently, very long training times. In 1993 we reported on the tuning and optimization of a negative ion source using a special neural network[2]. One of the properties of this network (CNLSnet), a modified radial basis function network, is that it is able to fit data with few basis functions. Another is that its training is linear resulting in guaranteed convergence and rapid training. We found the training to be rapid enough to support real-time control. This work has been extended to incorporate this network into an MPC using the model built by the network for predictive control. This controller has shown some remarkable capabilities in such non-linear applications as continuous stirred exothermic tank reactors and high-purity fractional distillation columns[3]. The controller is able not only to build an appropriate model from operating data but also to thin the network continuously so that the model adapts to changing plant conditions. The controller is discussed as well as its possible use in various of the difficult control problems that face this community.

  14. Spacecraft Component Adaptive Layout Environment (SCALE): An efficient optimization tool

    NASA Astrophysics Data System (ADS)

    Fakoor, Mahdi; Ghoreishi, Seyed Mohammad Navid; Sabaghzadeh, Hossein

    2016-11-01

    For finding the optimum layout of spacecraft subsystems, important factors such as the center of gravity, moments of inertia, thermal distribution, natural frequencies, etc. should be taken into account. This large number of effective parameters makes the optimum layout process of spacecraft subsystems complex and time consuming. In this paper, an automatic tool, based on multi-objective optimization methods, is proposed for a three dimensional layout of spacecraft subsystems. In this regard, an efficient Spacecraft Component Adaptive Layout Environment (SCALE) is produced by integration of some modeling, FEM, and optimization software. SCALE automatically provides optimal solutions for a three dimensional layout of spacecraft subsystems with considering important constraints such as center of gravity, moment of inertia, thermal distribution, natural frequencies and structural strength. In order to show the superiority and efficiency of SCALE, layout of a telecommunication spacecraft and a remote sensing spacecraft are performed. The results show that, the objective functions values for obtained layouts by using SCALE are in a much better condition than traditional one i.e. Reference Baseline Solution (RBS) which is proposed by the engineering system team. This indicates the good performance and ability of SCALE for finding the optimal layout of spacecraft subsystems.

  15. Implementation of modal optimization system of Subaru-188 adaptive optics

    NASA Astrophysics Data System (ADS)

    Hattori, Masayuki; Golota, Taras; Olivier, Guyon; Dinkins, Matthew; Oya, Shin; Colley, Stephen; Eldred, Michael; Watanabe, Makoto; Itoh, Meguru; Saito, Yoshihiko; Hayano, Yutaka; Takami, Hideki; Iye, Masanori

    2006-06-01

    Subaru AO-188 is a curvature adaptive optics system with 188 elements. It has been developed by NAOJ (National Astronomical Observatory of Japan) in recent years, as the upgrade from the existing 36-element AO system currently in operation at Subaru telescope. In this upgrade, the control scheme is also changed from zonal control to modal control. This paper presents development and implementation of the modal optimization system for this new AO-188. Also, we will introduce some special features and attempt in our implementation, such as consideration of resonance of deformable mirror at the lower order modes, and extension of the scheme for the optimization of the magnitude of membrane mirror in wave front sensor. Those are simple but shall be useful enhancement for the better performance to the conservative configuration with conventional modal control, and possibly useful in other extended operation modes or control schemes recently in research and development as well.

  16. Cockpit Adaptive Automation and Pilot Performance

    NASA Technical Reports Server (NTRS)

    Parasuraman, Raja

    2001-01-01

    The introduction of high-level automated systems in the aircraft cockpit has provided several benefits, e.g., new capabilities, enhanced operational efficiency, and reduced crew workload. At the same time, conventional 'static' automation has sometimes degraded human operator monitoring performance, increased workload, and reduced situation awareness. Adaptive automation represents an alternative to static automation. In this approach, task allocation between human operators and computer systems is flexible and context-dependent rather than static. Adaptive automation, or adaptive task allocation, is thought to provide for regulation of operator workload and performance, while preserving the benefits of static automation. In previous research we have reported beneficial effects of adaptive automation on the performance of both pilots and non-pilots of flight-related tasks. For adaptive systems to be viable, however, such benefits need to be examined jointly in the context of a single set of tasks. The studies carried out under this project evaluated a systematic method for combining different forms of adaptive automation. A model for effective combination of different forms of adaptive automation, based on matching adaptation to operator workload was proposed and tested. The model was evaluated in studies using IFR-rated pilots flying a general-aviation simulator. Performance, subjective, and physiological (heart rate variability, eye scan-paths) measures of workload were recorded. The studies compared workload-based adaptation to to non-adaptive control conditions and found evidence for systematic benefits of adaptive automation. The research provides an empirical basis for evaluating the effectiveness of adaptive automation in the cockpit. The results contribute to the development of design principles and guidelines for the implementation of adaptive automation in the cockpit, particularly in general aviation, and in other human-machine systems. Project goals

  17. To optimize performance, begin at the pulverizers

    SciTech Connect

    Storm, R.F.; Storm, S.K.

    2007-02-15

    A systematic, performance driven maintenance program for optimizing combustion can achieve great results. The challenge for O & M staff is deciding which proven strategy and tactics for reducing NOx and improving plant reliability to adapt and implement. The structured approach presented here has proven its worth at several plants that have wrestled with such problems. Based on experience gained by Storm Technologies, the article explores opportunities for raising efficiency of pulverized coal fired boilers by improving the performance of its pulverizers. In summary, significant ways to optimise performance are: increasing the fineness of coal particles to enhance release of fuel-bound nitrogen and to improve fuel balance, and reducing the total airflow and excess air to reduce thermal NOx production. 6 figs., 2 tabs.

  18. An optimized index of human cardiovascular adaptation to simulated weightlessness

    NASA Technical Reports Server (NTRS)

    Wang, M.; Hassebrook, L.; Evans, J.; Varghese, T.; Knapp, C.

    1996-01-01

    Prolonged exposure to weightlessness is known to produce a variety of cardiovascular changes, some of which may influence the astronaut's performance during a mission. In order to find a reliable indicator of cardiovascular adaptation to weightlessness, we analyzed data from nine male subjects after a 24-hour period of normal activity and after a period of simulated weightlessness produced by two hours in a launch position followed by 20 hours of 6 degrees head-down tilt plus pharmacologically induced diuresis (furosemide). Heart rate, arterial pressure, thoracic fluid index, and radial flow were analyzed. Autoregressive spectral estimation and decomposition were used to obtain the spectral components of each variable from the subjects in the supine position during pre- and post-simulated weightlessness. We found a significant decrease in heart rate power and an increase in thoracic fluid index power in the high frequency region (0.2-0.45 Hz) and significant increases in radial flow and arterial pressure powers in the low frequency region (<0.2 Hz) in response to simulated weightlessness. However, due to the variability among subjects, any single variable appeared limited as a dependable index of cardiovascular adaptation to weightlessness. The backward elimination algorithm was then used to select the best discriminatory features from these spectral components. Fisher's linear discriminant and Bayes' quadratic discriminant were used to combine the selected features to obtain an optimal index of adaptation to simulated weightlessness. Results showed that both techniques provided improved discriminant performance over any single variable and thus have the potential for use as an index to track adaptation and prescribe countermeasures to the effects of weightlessness.

  19. Multidimensional Adaptive Testing with Optimal Design Criteria for Item Selection

    ERIC Educational Resources Information Center

    Mulder, Joris; van der Linden, Wim J.

    2009-01-01

    Several criteria from the optimal design literature are examined for use with item selection in multidimensional adaptive testing. In particular, it is examined what criteria are appropriate for adaptive testing in which all abilities are intentional, some should be considered as a nuisance, or the interest is in the testing of a composite of the…

  20. Adaptive optimization and control using neural networks

    SciTech Connect

    Mead, W.C.; Brown, S.K.; Jones, R.D.; Bowling, P.S.; Barnes, C.W.

    1993-10-22

    Recent work has demonstrated the ability of neural-network-based controllers to optimize and control machines with complex, non-linear, relatively unknown control spaces. We present a brief overview of neural networks via a taxonomy illustrating some capabilities of different kinds of neural networks. We present some successful control examples, particularly the optimization and control of a small-angle negative ion source.

  1. (Too) optimistic about optimism: the belief that optimism improves performance.

    PubMed

    Tenney, Elizabeth R; Logg, Jennifer M; Moore, Don A

    2015-03-01

    A series of experiments investigated why people value optimism and whether they are right to do so. In Experiments 1A and 1B, participants prescribed more optimism for someone implementing decisions than for someone deliberating, indicating that people prescribe optimism selectively, when it can affect performance. Furthermore, participants believed optimism improved outcomes when a person's actions had considerable, rather than little, influence over the outcome (Experiment 2). Experiments 3 and 4 tested the accuracy of this belief; optimism improved persistence, but it did not improve performance as much as participants expected. Experiments 5A and 5B found that participants overestimated the relationship between optimism and performance even when their focus was not on optimism exclusively. In summary, people prescribe optimism when they believe it has the opportunity to improve the chance of success-unfortunately, people may be overly optimistic about just how much optimism can do.

  2. Adaptive-optics performance of Antarctic telescopes.

    PubMed

    Lawrence, Jon S

    2004-02-20

    The performance of natural guide star adaptive-optics systems for telescopes located on the Antarctic plateau is evaluated and compared with adaptive-optics systems operated with the characteristic mid-latitude atmosphere found at Mauna Kea. A 2-m telescope with tip-tilt correction and an 8-m telescope equipped with a high-order adaptive-optics system are considered. Because of the large isoplanatic angle of the South Pole atmosphere, the anisoplanatic error associated with an adaptive-optics correction is negligible, and the achievable resolution is determined only by the fitting error associated with the number of corrected wave-front modes, which depends on the number of actuators on the deformable mirror. The usable field of view of an adaptive-optics equipped Antarctic telescope is thus orders of magnitude larger than for a similar telescope located at a mid-latitude site; this large field of view obviates the necessity for multiconjugate adaptive-optics systems that use multiple laser guide stars. These results, combined with the low infrared sky backgrounds, indicate that the Antarctic plateau is the best site on Earth at which to perform high-resolution imaging with large telescopes, either over large fields of view or with appreciable sky coverage. Preliminary site-testing results obtained recently from the Dome Concordia station indicate that this site is far superior to even the South Pole. PMID:15008551

  3. Adaptation and optimal chemotactic strategy for {ital E. coli}

    SciTech Connect

    Strong, S.P.; Bialek, William; Koberle, R. Freedman, B.

    1998-04-01

    Extending the classic works of Berg and Purcell on the biophysics of bacterial chemotaxis, we find the optimal chemotactic strategy for the peritrichous bacterium {ital E. coli} in the high and low signal to noise ratio limits. The optimal strategy depends on properties of the environment and properties of the individual bacterium, and is therefore highly adaptive. We review experiments relevant to testing both the form of the proposed strategy and its adaptability, and propose extensions of them which could test the limits of the adaptability in this simplest sensory processing system. {copyright} {ital 1998} {ital The American Physical Society}

  4. Adaptive control based on retrospective cost optimization

    NASA Technical Reports Server (NTRS)

    Santillo, Mario A. (Inventor); Bernstein, Dennis S. (Inventor)

    2012-01-01

    A discrete-time adaptive control law for stabilization, command following, and disturbance rejection that is effective for systems that are unstable, MIMO, and/or nonminimum phase. The adaptive control algorithm includes guidelines concerning the modeling information needed for implementation. This information includes the relative degree, the first nonzero Markov parameter, and the nonminimum-phase zeros. Except when the plant has nonminimum-phase zeros whose absolute value is less than the plant's spectral radius, the required zero information can be approximated by a sufficient number of Markov parameters. No additional information about the poles or zeros need be known. Numerical examples are presented to illustrate the algorithm's effectiveness in handling systems with errors in the required modeling data, unknown latency, sensor noise, and saturation.

  5. Constraint optimized weight adaptation for Gaussian mixture reduction

    NASA Astrophysics Data System (ADS)

    Chen, H. D.; Chang, K. C.; Smith, Chris

    2010-04-01

    Gaussian mixture model (GMM) has been used in many applications for dynamic state estimation such as target tracking or distributed fusion. However, the number of components in the mixture distribution tends to grow rapidly when multiple GMMs are combined. In order to keep the computational complexity bounded, it is necessary to approximate a Gaussian mixture by one with reduced number of components. Gaussian mixture reduction is traditionally conducted by recursively selecting two components that appear to be most similar to each other and merging them. Different definitions on similarity measure have been used in literature. For the case of one-dimensional Gaussian mixtures, Kmeans algorithms and some variations are recently proposed to cluster Gaussian mixture components in groups, use a center component to represent all in each group, readjust parameters in the center components, and finally perform weight optimization. In this paper, we focus on multi-dimensional Gaussian mixture models. With a variety of reduction algorithms and possible combinations, we developed a hybrid algorithm with constraint optimized weight adaptation to minimize the integrated squared error (ISE). In additions, with extensive simulations, we showed that the proposed algorithm provides an efficient and effective Gaussian mixture reduction performance in various random scenarios.

  6. Camelina: Adaptation and performance of genotypes

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Camelina (Camelina sativa L. Crantz) has shown potential as an alternative and biofuel crop in cereal-based cropping systems. Our study investigated the adaption, performance, and yield stability among camelina genotypes across diverse US Pacific Northwest (PNW) environments. Seven named camelina ge...

  7. An Optimal Control Modification to Model-Reference Adaptive Control for Fast Adaptation

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.; Krishnakumar, Kalmanje; Boskovic, Jovan

    2008-01-01

    This paper presents a method that can achieve fast adaptation for a class of model-reference adaptive control. It is well-known that standard model-reference adaptive control exhibits high-gain control behaviors when a large adaptive gain is used to achieve fast adaptation in order to reduce tracking error rapidly. High gain control creates high-frequency oscillations that can excite unmodeled dynamics and can lead to instability. The fast adaptation approach is based on the minimization of the squares of the tracking error, which is formulated as an optimal control problem. The necessary condition of optimality is used to derive an adaptive law using the gradient method. This adaptive law is shown to result in uniform boundedness of the tracking error by means of the Lyapunov s direct method. Furthermore, this adaptive law allows a large adaptive gain to be used without causing undesired high-gain control effects. The method is shown to be more robust than standard model-reference adaptive control. Simulations demonstrate the effectiveness of the proposed method.

  8. Identifying performance bottlenecks on modern microarchitectures using an adaptable probe

    SciTech Connect

    Griem, Gorden; Oliker, Leonid; Shalf, John; Yelick, Katherine

    2004-01-20

    The gap between peak and delivered performance for scientific applications running on microprocessor-based systems has grown considerably in recent years. The inability to achieve the desired performance even on a single processor is often attributed to an inadequate memory system, but without identification or quantification of a specific bottleneck. In this work, we use an adaptable synthetic benchmark to isolate application characteristics that cause a significant drop in performance, giving application programmers and architects information about possible optimizations. Our adaptable probe, called sqmat, uses only four parameters to capture key characteristics of scientific workloads: working-set size, computational intensity, indirection, and irregularity. This paper describes the implementation of sqmat and uses its tunable parameters to evaluate four leading 64-bit microprocessors that are popular building blocks for current high performance systems: Intel Itanium2, AMD Opteron, IBM Power3, and IBM Power4.

  9. An adaptive response surface method for crashworthiness optimization

    NASA Astrophysics Data System (ADS)

    Shi, Lei; Yang, Ren-Jye; Zhu, Ping

    2013-11-01

    Response surface-based design optimization has been commonly used for optimizing large-scale design problems in the automotive industry. However, most response surface models are built by a limited number of design points without considering data uncertainty. In addition, the selection of a response surface in the literature is often arbitrary. This article uses a Bayesian metric to systematically select the best available response surface among several candidates in a library while considering data uncertainty. An adaptive, efficient response surface strategy, which minimizes the number of computationally intensive simulations, was developed for design optimization of large-scale complex problems. This methodology was demonstrated by a crashworthiness optimization example.

  10. On-sky demonstration of optimal control for adaptive optics at Palomar Observatory.

    PubMed

    Tesch, Jonathan; Truong, Tuan; Burruss, Rick; Gibson, Steve

    2015-04-01

    High-order adaptive optics systems often suffer from significant computational latency, which ultimately limits the temporal error rejection bandwidth when classical controllers are employed. This Letter presents results from an on-sky, real-time implementation of an optimal controller on the PALM-3000 adaptive optics system at Palomar Observatory. The optimal controller is computed directly from open-loop wavefront measurements using a multichannel subspace system identification algorithm, and mitigates latency by explicitly predicting incident turbulence. Experimental results show a significant reduction in the residual wavefront error over the controlled spatial modes, illustrating the superior performance of the optimal control approach versus the nominal integral control architecture.

  11. Frequency domain synthesis of optimal inputs for adaptive identification and control

    NASA Technical Reports Server (NTRS)

    Fu, Li-Chen; Sastry, Shankar

    1987-01-01

    The input design problem of selecting appropriate inputs for use in SISO adaptive identification and model reference adaptive control algorithms is considered. Averaging theory is used to characterize the optimal inputs in the frequency domain. The design problem is formulated as an optimization problem which maximizes the smallest eigenvalue of the average information matrix over power constrained signals, and the global optimal solution is obtained using a convergent numerical algorithm. A bound on the frequency search range required in the design algorithm has been determined in terms of the desired performance.

  12. A Structure-Adaptive Hybrid RBF-BP Classifier with an Optimized Learning Strategy

    PubMed Central

    Wen, Hui; Xie, Weixin; Pei, Jihong

    2016-01-01

    This paper presents a structure-adaptive hybrid RBF-BP (SAHRBF-BP) classifier with an optimized learning strategy. SAHRBF-BP is composed of a structure-adaptive RBF network and a BP network of cascade, where the number of RBF hidden nodes is adjusted adaptively according to the distribution of sample space, the adaptive RBF network is used for nonlinear kernel mapping and the BP network is used for nonlinear classification. The optimized learning strategy is as follows: firstly, a potential function is introduced into training sample space to adaptively determine the number of initial RBF hidden nodes and node parameters, and a form of heterogeneous samples repulsive force is designed to further optimize each generated RBF hidden node parameters, the optimized structure-adaptive RBF network is used for adaptively nonlinear mapping the sample space; then, according to the number of adaptively generated RBF hidden nodes, the number of subsequent BP input nodes can be determined, and the overall SAHRBF-BP classifier is built up; finally, different training sample sets are used to train the BP network parameters in SAHRBF-BP. Compared with other algorithms applied to different data sets, experiments show the superiority of SAHRBF-BP. Especially on most low dimensional and large number of data sets, the classification performance of SAHRBF-BP outperforms other training SLFNs algorithms. PMID:27792737

  13. EUVL mask performance and optimization

    NASA Astrophysics Data System (ADS)

    Davydova, Natalia; de Kruif, Robert; van Setten, Eelco; Connolly, Brid; Mehagnoul, Karolien; Zimmerman, John; Harned, Noreen; Kalk, Franklin

    2012-02-01

    EUV lithography requires an exposure system with complex reflective optics and an equally complex EUV dedicated reflective mask. The required high level of reflectivity is obtained by using multilayers. The multilayer of the system optics and the mask are tuned to each other. The mask is equipped with an additional patterned absorber layer. The EUV mask is an optical element with many parameters that contribute to the final image and overlay quality on the wafer and the productivity of the system. Several of these parameters can be tuned for optimal overlay, imaging and productivity results. This should be done with care because of possible interaction between parameters. We will present an overview of the EUV mask contributors to the imaging, overlay and productivity performance for the 27 nm node and below, such as multilayer and absorber stack composition, reflectivity and reflectivity uniformity. These parameters will be reviewed in the context of real-life scanner parameters for the ASML NXE:3100 and NXE:3300 system configurations. The predictions will be compared to actual exposure results on NXE:3100 systems (NA=0.25) for various masks and extrapolated to the NXE:3300 (NA=0.33). In particular, we will present extensive multilayer and absorber actinic spectral reflectance measurements of a state-ofthe art EUV mask over a range of incidence angles corresponding to an NA of 0.33 at multiple positions within the image field. The ML measurements allow calibrating ML stack for imaging simulations. It allows also the estimation of mask-induced apodization effects having impact on overlay. In general, the reflectivity measurements will give detailed variations over the image field of mask parameters such as ML centroid wavelength and absorber reflectivity which contribute to CD uniformity. Such a relation will be established by means of rigorous full stack imaging simulations taking into account optical properties of the coming NXE:3300 system. Based on this

  14. A hybrid method for optimization of the adaptive Goldstein filter

    NASA Astrophysics Data System (ADS)

    Jiang, Mi; Ding, Xiaoli; Tian, Xin; Malhotra, Rakesh; Kong, Weixue

    2014-12-01

    The Goldstein filter is a well-known filter for interferometric filtering in the frequency domain. The main parameter of this filter, alpha, is set as a power of the filtering function. Depending on it, considered areas are strongly or weakly filtered. Several variants have been developed to adaptively determine alpha using different indicators such as the coherence, and phase standard deviation. The common objective of these methods is to prevent areas with low noise from being over filtered while simultaneously allowing stronger filtering over areas with high noise. However, the estimators of these indicators are biased in the real world and the optimal model to accurately determine the functional relationship between the indicators and alpha is also not clear. As a result, the filter always under- or over-filters and is rarely correct. The study presented in this paper aims to achieve accurate alpha estimation by correcting the biased estimator using homogeneous pixel selection and bootstrapping algorithms, and by developing an optimal nonlinear model to determine alpha. In addition, an iteration is also merged into the filtering procedure to suppress the high noise over incoherent areas. The experimental results from synthetic and real data show that the new filter works well under a variety of conditions and offers better and more reliable performance when compared to existing approaches.

  15. Meteorological Data Assimilation by Adaptive Bayesian Optimization.

    NASA Astrophysics Data System (ADS)

    Purser, Robert James

    1992-01-01

    The principal aim of this research is the elucidation of the Bayesian statistical principles that underlie the theory of objective meteorological analysis. In particular, emphasis is given to aspects of data assimilation that can benefit from an iterative numerical strategy. Two such aspects that are given special consideration are statistical validation of the covariance profiles and nonlinear initialization. A new economic algorithm is presented, based on the imposition of a sparse matrix structure for all covariances and precisions held during the computations. It is shown that very large datasets may be accommodated using this structure and a good linear approximation to the analysis equations established without the need to unnaturally fragment the problem. Since the integrity of the system of analysis equations is preserved, it is a relatively straight-forward matter to extend the basic analysis algorithm to one that incorporates a check on the plausibility of the statistical model assumed for background errors--the so-called "validation" problem. Two methods of validation are described within the sparse matrix framework: the first is essentially a direct extension of the Bayesian principles to embrace, not only the regular analysis variables, but also the parameters that determine the precise form of the covariance functions; the second technique is the non-Bayesian method of generalized cross validation adapted for use within the sparse matrix framework. The later part of this study is concerned with the establishment of a consistent dynamical balance within a forecast model--the initialization problem. The formal principles of the modern theory of initialization are reviewed and a critical examination is made of the concept of the "slow manifold". It is demonstrated, in accordance with more complete nonlinear models, that even within a simple three-mode linearized system, the notion that a universal slow manifold exists is untenable. It is therefore argued

  16. Sootblowing optimization for improved boiler performance

    DOEpatents

    James, John Robert; McDermott, John; Piche, Stephen; Pickard, Fred; Parikh, Neel J.

    2012-12-25

    A sootblowing control system that uses predictive models to bridge the gap between sootblower operation and boiler performance goals. The system uses predictive modeling and heuristics (rules) associated with different zones in a boiler to determine an optimal sequence of sootblower operations and achieve boiler performance targets. The system performs the sootblower optimization while observing any operational constraints placed on the sootblowers.

  17. Sootblowing optimization for improved boiler performance

    SciTech Connect

    James, John Robert; McDermott, John; Piche, Stephen; Pickard, Fred; Parikh, Neel J

    2013-07-30

    A sootblowing control system that uses predictive models to bridge the gap between sootblower operation and boiler performance goals. The system uses predictive modeling and heuristics (rules) associated with different zones in a boiler to determine an optimal sequence of sootblower operations and achieve boiler performance targets. The system performs the sootblower optimization while observing any operational constraints placed on the sootblowers.

  18. Performance predictions for the Keck telescope adaptive optics system

    SciTech Connect

    Gavel, D.T.; Olivier, S.S.

    1995-08-07

    The second Keck ten meter telescope (Keck-11) is slated to have an infrared-optimized adaptive optics system in the 1997--1998 time frame. This system will provide diffraction-limited images in the 1--3 micron region and the ability to use a diffraction-limited spectroscopy slit. The AO system is currently in the preliminary design phase and considerable analysis has been performed in order to predict its performance under various seeing conditions. In particular we have investigated the point-spread function, energy through a spectroscopy slit, crowded field contrast, object limiting magnitude, field of view, and sky coverage with natural and laser guide stars.

  19. An adaptive training method for optimal interpolative neural nets.

    PubMed

    Liu, T Z; Yen, C W

    1997-04-01

    In contrast to conventional multilayered feedforward networks which are typically trained by iterative gradient search methods, an optimal interpolative (OI) net can be trained by a noniterative least squares algorithm called RLS-OI. The basic idea of RLS-OI is to use a subset of the training set, whose inputs are called subprototypes, to constrain the OI net solution. A subset of these subprototypes, called prototypes, is then chosen as the parameter vectors of the activation functions of the OI net to satisfy the subprototype constraints in the least squares (LS) sense. By dynamically increasing the numbers of subprototypes and prototypes, RLS-OI evolves the OI net from scratch to the extent sufficient to solve a given classification problem. To improve the performance of RLS-OI, this paper addresses two important problems in OI net training: the selection of the subprototypes and the selection of the prototypes. By choosing subprototypes from poorly classified regions, this paper proposes a new subprototype selection method which is adaptive to the changing classification performance of the growing OI net. This paper also proposes a new prototype selection criterion to reduce the complexity of the OI net. For the same training accuracy, simulation results demonstrate that the proposed approach produces smaller OI net than the RLS-OI algorithm. Experimental results also show that the proposed approach is less sensitive to the variation of the training set than RLS-OI.

  20. Optimal Decision Stimuli for Risky Choice Experiments: An Adaptive Approach.

    PubMed

    Cavagnaro, Daniel R; Gonzalez, Richard; Myung, Jay I; Pitt, Mark A

    2013-02-01

    Collecting data to discriminate between models of risky choice requires careful selection of decision stimuli. Models of decision making aim to predict decisions across a wide range of possible stimuli, but practical limitations force experimenters to select only a handful of them for actual testing. Some stimuli are more diagnostic between models than others, so the choice of stimuli is critical. This paper provides the theoretical background and a methodological framework for adaptive selection of optimal stimuli for discriminating among models of risky choice. The approach, called Adaptive Design Optimization (ADO), adapts the stimulus in each experimental trial based on the results of the preceding trials. We demonstrate the validity of the approach with simulation studies aiming to discriminate Expected Utility, Weighted Expected Utility, Original Prospect Theory, and Cumulative Prospect Theory models. PMID:24532856

  1. Optimal Decision Stimuli for Risky Choice Experiments: An Adaptive Approach

    PubMed Central

    Cavagnaro, Daniel R.; Gonzalez, Richard; Myung, Jay I.; Pitt, Mark A.

    2014-01-01

    Collecting data to discriminate between models of risky choice requires careful selection of decision stimuli. Models of decision making aim to predict decisions across a wide range of possible stimuli, but practical limitations force experimenters to select only a handful of them for actual testing. Some stimuli are more diagnostic between models than others, so the choice of stimuli is critical. This paper provides the theoretical background and a methodological framework for adaptive selection of optimal stimuli for discriminating among models of risky choice. The approach, called Adaptive Design Optimization (ADO), adapts the stimulus in each experimental trial based on the results of the preceding trials. We demonstrate the validity of the approach with simulation studies aiming to discriminate Expected Utility, Weighted Expected Utility, Original Prospect Theory, and Cumulative Prospect Theory models. PMID:24532856

  2. Optimizing Input/Output Using Adaptive File System Policies

    NASA Technical Reports Server (NTRS)

    Madhyastha, Tara M.; Elford, Christopher L.; Reed, Daniel A.

    1996-01-01

    Parallel input/output characterization studies and experiments with flexible resource management algorithms indicate that adaptivity is crucial to file system performance. In this paper we propose an automatic technique for selecting and refining file system policies based on application access patterns and execution environment. An automatic classification framework allows the file system to select appropriate caching and pre-fetching policies, while performance sensors provide feedback used to tune policy parameters for specific system environments. To illustrate the potential performance improvements possible using adaptive file system policies, we present results from experiments involving classification-based and performance-based steering.

  3. Performance of adaptive optics at Lick Observatory

    SciTech Connect

    Olivier, S.S.; An, J.; Avicola, K.

    1994-03-01

    A prototype adaptive optics system has been developed at Lawrence Livermore National Laboratory (LLNL) for use at Lick Observatory. This system is based on an ITEX 69-actuator continuous-surface deformable mirror, a Kodak fast-framing intensified CCD camera, and a Mercury VME board containing four Intel i860 processors. The system has been tested using natural reference stars on the 40-inch Nickel telescope at Lick Observatory yielding up to a factor of 10 increase in image peak intensity and a factor of 6 reduction in image full width at half maximum (FWHM). These results are consistent with theoretical expectations. In order to improve performance, the intensified CCD camera will be replaced by a high-quantum-efficiency low-noise fast CCD camera built for LLNL by Adaptive Optics Associates using a chip developed by Lincoln Laboratory, and the 69-actuator deformable mirror will be replaced by a 127-actuator deformable mirror developed at LLNL. With these upgrades, the system should perform well in median seeing conditions on the 120-inch Shane telescope for observing wavelengths longer than {approximately}1 {mu}m and using natural reference stars brighter than m{sub R} {approximately} 10 or using the laser currently being developed at LLNL for use at Lick Observatory to generate a sodium-layer reference star.

  4. Individually designed PALs vs. power optimized PALs adaptation comparison.

    PubMed

    Muždalo, Nataša Vujko; Mihelčič, Matjaž

    2015-03-01

    The practice shows that in everyday life we encounter ever-growing demand for better visual acuity at all viewing distances. The presbyopic population needs correction to far, near and intermediate distance with different dioptric powers. PAL lenses seem to be a comfortable solution. The object of the present study is the analysis of the factors determining adaptation to progressive addition lenses (PAL) of the first-time users. Only novice test persons were chosen in order to avoid the bias of previously worn particular lens design. For optimal results with this type of lens, several individual parameters must be considered: correct refraction, precise ocular and facial measures, and proper mounting of lenses into the frame. Nevertheless, first time wearers encounter various difficulties in the process of adapting to this type of glasses and adaptation time differs greatly between individual users. The question that arises is how much the individual parameters really affect the ease of adaptation and comfort when wearing progressive glasses. To clarify this, in the present study, the individual PAL lenses--Rodenstock's Impression FreeSign (with inclusion of all parameters related to the user's eye and spectacle frame: prescription, pupillary distance, fitting height, back vertex distance, pantoscopic angle and curvature of the frame) were compared to power optimized PAL--Rodenstock's Multigressiv MyView (respecting only prescription power and pupillary distance). Adaptation process was monitored over a period of four weeks. The collected results represent scores of user's subjective impressions, where the users themselves rated their adaptation to new progressive glasses and the degree of subjective visual impression. The results show that adaptation time to fully individually fit PAL is easier and quickly. The information obtained from users is valuable in everyday optometry practice because along with the manufacturer's specifications, the user's experience can

  5. Individually designed PALs vs. power optimized PALs adaptation comparison.

    PubMed

    Muždalo, Nataša Vujko; Mihelčič, Matjaž

    2015-03-01

    The practice shows that in everyday life we encounter ever-growing demand for better visual acuity at all viewing distances. The presbyopic population needs correction to far, near and intermediate distance with different dioptric powers. PAL lenses seem to be a comfortable solution. The object of the present study is the analysis of the factors determining adaptation to progressive addition lenses (PAL) of the first-time users. Only novice test persons were chosen in order to avoid the bias of previously worn particular lens design. For optimal results with this type of lens, several individual parameters must be considered: correct refraction, precise ocular and facial measures, and proper mounting of lenses into the frame. Nevertheless, first time wearers encounter various difficulties in the process of adapting to this type of glasses and adaptation time differs greatly between individual users. The question that arises is how much the individual parameters really affect the ease of adaptation and comfort when wearing progressive glasses. To clarify this, in the present study, the individual PAL lenses--Rodenstock's Impression FreeSign (with inclusion of all parameters related to the user's eye and spectacle frame: prescription, pupillary distance, fitting height, back vertex distance, pantoscopic angle and curvature of the frame) were compared to power optimized PAL--Rodenstock's Multigressiv MyView (respecting only prescription power and pupillary distance). Adaptation process was monitored over a period of four weeks. The collected results represent scores of user's subjective impressions, where the users themselves rated their adaptation to new progressive glasses and the degree of subjective visual impression. The results show that adaptation time to fully individually fit PAL is easier and quickly. The information obtained from users is valuable in everyday optometry practice because along with the manufacturer's specifications, the user's experience can

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

    NASA Astrophysics Data System (ADS)

    Bonato, C.; Blok, M. S.; Dinani, H. T.; Berry, D. W.; Markham, M. L.; Twitchen, D. J.; Hanson, R.

    2016-03-01

    Quantum sensors based on single solid-state spins promise a unique combination of sensitivity and spatial resolution. The key challenge in sensing is to achieve minimum estimation uncertainty within a given time and with high dynamic range. Adaptive strategies have been proposed to achieve optimal performance, but their implementation in solid-state systems has been hindered by the demanding experimental requirements. Here, we realize adaptive d.c. sensing by combining single-shot readout of an electron spin in diamond with fast feedback. By adapting the spin readout basis in real time based on previous outcomes, we demonstrate a sensitivity in Ramsey interferometry surpassing the standard measurement limit. Furthermore, we find by simulations and experiments that adaptive protocols offer a distinctive advantage over the best known non-adaptive protocols when overhead and limited estimation time are taken into account. Using an optimized adaptive protocol we achieve a magnetic field sensitivity of 6.1 ± 1.7 nT Hz-1/2 over a wide range of 1.78 mT. These results open up a new class of experiments for solid-state sensors in which real-time knowledge of the measurement history is exploited to obtain optimal performance.

  7. Performance optimization of thermophotovoltaic systems

    NASA Astrophysics Data System (ADS)

    Schroeder, Kenneth Lee

    1998-12-01

    This research effort addresses the problem of modeling system performance and determining an optimum configuration for a thermophotovoltaic (TPV) power generation system. Specifically, the performance of a 100 watt cylindrical TPV system is modeled as a function of both configuration and geometry. The system parameters which yielded optimum performance in terms of radiant efficiency, system efficiency and power density were evaluated. The model presented employs an iterative type solution and incorporates two principal routines, the IMPROVEsp{copyright} genetic algorithm (GA) and a performance prediction code. The genetic algorithm governs the solution process and seeks to maximize an objective function (i.e system efficiency). The performance model is an energy-based formulation which represents the TPV system as two primary components, the radiant cavity and heat source. The radiant cavity includes the emitter, filter and photovoltaic elements of the system. Physical properties and performance data for the radiant cavity components are evaluated from a database of experimental data. Radiant transfer calculations include provisions for evaluating the effects of optical concentration and multiple reflections, and incorporates the use of ray tracking formulations and view factors calculations for evaluating various flat plate and cylindrical configurations in terms of cavity performance and power generated. In the heat source portion of the performance model, the thermodynamic states of a hydrocarbon fueled recuperative type burner are considered at six discrete points. A self-consistent set of equations for the conservation of energy is used to determine the heat source parameters as a function of the input, effective emitter radiant temperature, thermal recuperation, and heat loss. Evaluations of the equations are performed using a modified version of the NASA Complex Chemical Equilibrium Compositions and Applications (CEA) code. Of the configurations evaluated

  8. Road map to adaptive optimal control. [jet engine control

    NASA Technical Reports Server (NTRS)

    Boyer, R.

    1980-01-01

    A building block control structure leading toward adaptive, optimal control for jet engines is developed. This approach simplifies the addition of new features and allows for easier checkout of the control by providing a baseline system for comparison. Also, it is possible to eliminate certain features that do not have payoff by being selective in the addition of new building blocks to be added to the baseline system. The minimum risk approach specifically addresses the need for active identification of the plant to be controlled in real time and real time optimization of the control for the identified plant.

  9. Adaptive Estimation of Intravascular Shear Rate Based on Parameter Optimization

    NASA Astrophysics Data System (ADS)

    Nitta, Naotaka; Takeda, Naoto

    2008-05-01

    The relationships between the intravascular wall shear stress, controlled by flow dynamics, and the progress of arteriosclerosis plaque have been clarified by various studies. Since the shear stress is determined by the viscosity coefficient and shear rate, both factors must be estimated accurately. In this paper, an adaptive method for improving the accuracy of quantitative shear rate estimation was investigated. First, the parameter dependence of the estimated shear rate was investigated in terms of the differential window width and the number of averaged velocity profiles based on simulation and experimental data, and then the shear rate calculation was optimized. The optimized result revealed that the proposed adaptive method of shear rate estimation was effective for improving the accuracy of shear rate calculation.

  10. Optimal and adaptive methods of processing hydroacoustic signals (review)

    NASA Astrophysics Data System (ADS)

    Malyshkin, G. S.; Sidel'nikov, G. B.

    2014-09-01

    Different methods of optimal and adaptive processing of hydroacoustic signals for multipath propagation and scattering are considered. Advantages and drawbacks of the classical adaptive (Capon, MUSIC, and Johnson) algorithms and "fast" projection algorithms are analyzed for the case of multipath propagation and scattering of strong signals. The classical optimal approaches to detecting multipath signals are presented. A mechanism of controlled normalization of strong signals is proposed to automatically detect weak signals. The results of simulating the operation of different detection algorithms for a linear equidistant array under multipath propagation and scattering are presented. An automatic detector is analyzed, which is based on classical or fast projection algorithms, which estimates the background proceeding from median filtering or the method of bilateral spatial contrast.

  11. Adaptive particle swarm optimization for optimal orbital elements of binary stars

    NASA Astrophysics Data System (ADS)

    Attia, Abdel-Fattah

    2016-10-01

    The paper presents an adaptive particle swarm optimization (APSO) as an alternative method to determine the optimal orbital elements of the star η Bootis of MK type G0 IV. The proposed algorithm transforms the problem of finding periodic orbits into the problem of detecting global minimizers as a function, to get a best fit of Keplerian and Phase curves. The experimental results demonstrate that the proposed approach of APSO generally more accurate than the standard particle swarm optimization (PSO) and other published optimization algorithms, in terms of solution accuracy, convergence speed and algorithm reliability.

  12. Image-quality metrics for characterizing adaptive optics system performance.

    PubMed

    Brigantic, R T; Roggemann, M C; Bauer, K W; Welsh, B M

    1997-09-10

    Adaptive optics system (AOS) performance is a function of the system design, seeing conditions, and light level of the wave-front beacon. It is desirable to optimize the controllable parameters in an AOS to maximize some measure of performance. For this optimization to be useful, it is necessary that a set of image-quality metrics be developed that vary monotonically with the AOS performance under a wide variety of imaging environments. Accordingly, as conditions change, one can be confident that the computed metrics dictate appropriate system settings that will optimize performance. Three such candidate metrics are presented. The first is the Strehl ratio; the second is a novel metric that modifies the Strehl ratio by integration of the modulus of the average system optical transfer function to a noise-effective cutoff frequency at which some specified image spectrum signal-to-noise ratio level is attained; and the third is simply the cutoff frequency just mentioned. It is shown that all three metrics are correlated with the rms error (RMSE) between the measured image and the associated diffraction-limited image. Of these, the Strehl ratio and the modified Strehl ratio exhibit consistently high correlations with the RMSE across a broad range of conditions and system settings. Furthermore, under conditions that yield a constant average system optical transfer function, the modified Strehl ratio can still be used to delineate image quality, whereas the Strehl ratio cannot.

  13. Achieving Optimal Self-Adaptivity for Dynamic Tuning of Organic Semiconductors through Resonance Engineering.

    PubMed

    Tao, Ye; Xu, Lijia; Zhang, Zhen; Chen, Runfeng; Li, Huanhuan; Xu, Hui; Zheng, Chao; Huang, Wei

    2016-08-01

    Current static-state explorations of organic semiconductors for optimal material properties and device performance are hindered by limited insights into the dynamically changed molecular states and charge transport and energy transfer processes upon device operation. Here, we propose a simple yet successful strategy, resonance variation-based dynamic adaptation (RVDA), to realize optimized self-adaptive properties in donor-resonance-acceptor molecules by engineering the resonance variation for dynamic tuning of organic semiconductors. Organic light-emitting diodes hosted by these RVDA materials exhibit remarkably high performance, with external quantum efficiencies up to 21.7% and favorable device stability. Our approach, which supports simultaneous realization of dynamically adapted and selectively enhanced properties via resonance engineering, illustrates a feasible design map for the preparation of smart organic semiconductors capable of dynamic structure and property modulations, promoting the studies of organic electronics from static to dynamic. PMID:27403886

  14. A new adaptive hybrid electromagnetic damper: modelling, optimization, and experiment

    NASA Astrophysics Data System (ADS)

    Asadi, Ehsan; Ribeiro, Roberto; Behrad Khamesee, Mir; Khajepour, Amir

    2015-07-01

    This paper presents the development of a new electromagnetic hybrid damper which provides regenerative adaptive damping force for various applications. Recently, the introduction of electromagnetic technologies to the damping systems has provided researchers with new opportunities for the realization of adaptive semi-active damping systems with the added benefit of energy recovery. In this research, a hybrid electromagnetic damper is proposed. The hybrid damper is configured to operate with viscous and electromagnetic subsystems. The viscous medium provides a bias and fail-safe damping force while the electromagnetic component adds adaptability and the capacity for regeneration to the hybrid design. The electromagnetic component is modeled and analyzed using analytical (lumped equivalent magnetic circuit) and electromagnetic finite element method (FEM) (COMSOL® software package) approaches. By implementing both modeling approaches, an optimization for the geometric aspects of the electromagnetic subsystem is obtained. Based on the proposed electromagnetic hybrid damping concept and the preliminary optimization solution, a prototype is designed and fabricated. A good agreement is observed between the experimental and FEM results for the magnetic field distribution and electromagnetic damping forces. These results validate the accuracy of the modeling approach and the preliminary optimization solution. An analytical model is also presented for viscous damping force, and is compared with experimental results The results show that the damper is able to produce damping coefficients of 1300 and 0-238 N s m-1 through the viscous and electromagnetic components, respectively.

  15. Performance optimization of marine propellers

    NASA Astrophysics Data System (ADS)

    Lee, Chang-Sup; Choi, Young-Dal; Ahn, Byoung-Kwon; Shin, Myoung-Sup; Jang, Hyun-Gil

    2010-12-01

    Recently a Wide Chord Tip (WCT) propeller has been developed and applied to a commercial ship by STX Offshore & Shipbuilding. It is reported that the WCT propeller significantly reduces pressure fluctuations and also ship's noise and vibration. On the sea trial, vibration magnitude in the accommodations at NCR was measured at 0.9mm/sec which is only 10% of international allowable magnitude of vibration (9mm/sec). In this paper, a design method for increasing performance of the marine propellers including the WCT propeller is suggested. It is described to maximize the performance of the propeller by adjusting expanded areas of the propeller blade. Results show that efficiency can be increased up to over 2% through the suggested design method.

  16. Optimizing raid performance with cache

    NASA Technical Reports Server (NTRS)

    Bouzari, Alex

    1994-01-01

    We live in a world of increasingly complex applications and operating systems. Information is increasing at a mind-boggling rate. The consolidation of text, voice, and imaging represents an even greater challenge for our information systems. Which forced us to address three important questions: Where do we store all this information? How do we access it? And, how do we protect it against the threat of loss or damage? Introduced in the 1980s, RAID (Redundant Arrays of Independent Disks) represents a cost-effective solution to the needs of the information age. While fulfilling expectations for high storage, and reliability, RAID is sometimes subject to criticisms in the area of performance. However, there are design elements that can significantly enhance performance. They can be subdivided into two areas: (1) RAID levels or basic architecture. And, (2) enhancement schemes such as intelligent caching, support of tagged command queuing, and use of SCSI-2 Fast and Wide features.

  17. A novel adaptive Cuckoo search for optimal query plan generation.

    PubMed

    Gomathi, Ramalingam; Sharmila, Dhandapani

    2014-01-01

    The emergence of multiple web pages day by day leads to the development of the semantic web technology. A World Wide Web Consortium (W3C) standard for storing semantic web data is the resource description framework (RDF). To enhance the efficiency in the execution time for querying large RDF graphs, the evolving metaheuristic algorithms become an alternate to the traditional query optimization methods. This paper focuses on the problem of query optimization of semantic web data. An efficient algorithm called adaptive Cuckoo search (ACS) for querying and generating optimal query plan for large RDF graphs is designed in this research. Experiments were conducted on different datasets with varying number of predicates. The experimental results have exposed that the proposed approach has provided significant results in terms of query execution time. The extent to which the algorithm is efficient is tested and the results are documented. PMID:25215330

  18. A novel adaptive Cuckoo search for optimal query plan generation.

    PubMed

    Gomathi, Ramalingam; Sharmila, Dhandapani

    2014-01-01

    The emergence of multiple web pages day by day leads to the development of the semantic web technology. A World Wide Web Consortium (W3C) standard for storing semantic web data is the resource description framework (RDF). To enhance the efficiency in the execution time for querying large RDF graphs, the evolving metaheuristic algorithms become an alternate to the traditional query optimization methods. This paper focuses on the problem of query optimization of semantic web data. An efficient algorithm called adaptive Cuckoo search (ACS) for querying and generating optimal query plan for large RDF graphs is designed in this research. Experiments were conducted on different datasets with varying number of predicates. The experimental results have exposed that the proposed approach has provided significant results in terms of query execution time. The extent to which the algorithm is efficient is tested and the results are documented.

  19. A Novel Adaptive Cuckoo Search for Optimal Query Plan Generation

    PubMed Central

    Gomathi, Ramalingam; Sharmila, Dhandapani

    2014-01-01

    The emergence of multiple web pages day by day leads to the development of the semantic web technology. A World Wide Web Consortium (W3C) standard for storing semantic web data is the resource description framework (RDF). To enhance the efficiency in the execution time for querying large RDF graphs, the evolving metaheuristic algorithms become an alternate to the traditional query optimization methods. This paper focuses on the problem of query optimization of semantic web data. An efficient algorithm called adaptive Cuckoo search (ACS) for querying and generating optimal query plan for large RDF graphs is designed in this research. Experiments were conducted on different datasets with varying number of predicates. The experimental results have exposed that the proposed approach has provided significant results in terms of query execution time. The extent to which the algorithm is efficient is tested and the results are documented. PMID:25215330

  20. Trajectory Planning and Optimized Adaptive Control for a Class of Wheeled Inverted Pendulum Vehicle Models.

    PubMed

    Yang, Chenguang; Li, Zhijun; Li, Jing

    2013-02-01

    In this paper, we investigate optimized adaptive control and trajectory generation for a class of wheeled inverted pendulum (WIP) models of vehicle systems. Aiming at shaping the controlled vehicle dynamics to be of minimized motion tracking errors as well as angular accelerations, we employ the linear quadratic regulation optimization technique to obtain an optimal reference model. Adaptive control has then been developed using variable structure method to ensure the reference model to be exactly matched in a finite-time horizon, even in the presence of various internal and external uncertainties. The minimized yaw and tilt angular accelerations help to enhance the vehicle rider's comfort. In addition, due to the underactuated mechanism of WIP, the vehicle forward velocity dynamics cannot be controlled separately from the pendulum tilt angle dynamics. Inspired by the control strategy of human drivers, who usually manipulate the tilt angle to control the forward velocity, we design a neural-network-based adaptive generator of implicit control trajectory (AGICT) of the tilt angle which indirectly "controls" the forward velocity such that it tracks the desired velocity asymptotically. The stability and optimal tracking performance have been rigorously established by theoretic analysis. In addition, simulation studies have been carried out to demonstrate the efficiency of the developed AGICT and optimized adaptive controller.

  1. Pulsed Inductive Plasma Acceleration: Performance Optimization Criteria

    NASA Technical Reports Server (NTRS)

    Polzin, Kurt A.

    2014-01-01

    Optimization criteria for pulsed inductive plasma acceleration are developed using an acceleration model consisting of a set of coupled circuit equations describing the time-varying current in the thruster and a one-dimensional momentum equation. The model is nondimensionalized, resulting in the identification of several scaling parameters that are varied to optimize the performance of the thruster. The analysis reveals the benefits of underdamped current waveforms and leads to a performance optimization criterion that requires the matching of the natural period of the discharge and the acceleration timescale imposed by the inertia of the working gas. In addition, the performance increases when a greater fraction of the propellant is initially located nearer to the inductive acceleration coil. While the dimensionless model uses a constant temperature formulation in calculating performance, the scaling parameters that yield the optimum performance are shown to be relatively invariant if a self-consistent description of energy in the plasma is instead used.

  2. Performance of the optical communication adaptive optics testbed

    NASA Technical Reports Server (NTRS)

    Troy, Mitchell; Roberts, Jennifer; Guiwits, Steve; Azevedo, Steve; Bikkannavar, Siddarayappa; Brack, Gary; Garkanian, Vachik; Palmer, Dean; Platt, Benjamin; Truong, Tuan; Wilson, Keith; Wallace, Kent

    2005-01-01

    We describe the current performance of an adaptive optics testbed for optical communication. This adaptive optics system allows for simulation of night and day-time observing on a 1 meter telescope with a 97 actuator deformable mirror.

  3. An adaptive locally optimal method detecting weak deterministic signals

    NASA Astrophysics Data System (ADS)

    Wang, C. H.

    1983-10-01

    A new method for detecting weak signals in interference and clutter in radar systems is presented. The detector which uses this method is adaptive for an environment varying with time and locally optimal for detecting targets and constant false-alarm ratio (CFAR) for the statistics of interference and clutter varying with time. The loss of CFAR is small, and the detector is also simple in structure. The statistical equivalent transfer characteristic of a rank quantizer which can be used as part of an adaptive locally most powerful detector (ALMP) is obtained. It is shown that the distribution-free Doppler processor of Dillard (1974) is not only a nonparameter detector, but also an ALMP detector under certain conditions.

  4. Modeling for deformable mirrors and the adaptive optics optimization program

    SciTech Connect

    Henesian, M.A.; Haney, S.W.; Trenholme, J.B.; Thomas, M.

    1997-03-18

    We discuss aspects of adaptive optics optimization for large fusion laser systems such as the 192-arm National Ignition Facility (NIF) at LLNL. By way of example, we considered the discrete actuator deformable mirror and Hartmann sensor system used on the Beamlet laser. Beamlet is a single-aperture prototype of the 11-0-5 slab amplifier design for NIF, and so we expect similar optical distortion levels and deformable mirror correction requirements. We are now in the process of developing a numerically efficient object oriented C++ language implementation of our adaptive optics and wavefront sensor code, but this code is not yet operational. Results are based instead on the prototype algorithms, coded-up in an interpreted array processing computer language.

  5. In-flight performance optimization for rotorcraft with redundant controls

    NASA Astrophysics Data System (ADS)

    Ozdemir, Gurbuz Taha

    A conventional helicopter has limits on performance at high speeds because of the limitations of main rotor, such as compressibility issues on advancing side or stall issues on retreating side. Auxiliary lift and thrust components have been suggested to improve performance of the helicopter substantially by reducing the loading on the main rotor. Such a configuration is called the compound rotorcraft. Rotor speed can also be varied to improve helicopter performance. In addition to improved performance, compound rotorcraft and variable RPM can provide a much larger degree of control redundancy. This additional redundancy gives the opportunity to further enhance performance and handling qualities. A flight control system is designed to perform in-flight optimization of redundant control effectors on a compound rotorcraft in order to minimize power required and extend range. This "Fly to Optimal" (FTO) control law is tested in simulation using the GENHEL model. A model of the UH-60, a compound version of the UH-60A with lifting wing and vectored thrust ducted propeller (VTDP), and a generic compound version of the UH-60A with lifting wing and propeller were developed and tested in simulation. A model following dynamic inversion controller is implemented for inner loop control of roll, pitch, yaw, heave, and rotor RPM. An outer loop controller regulates airspeed and flight path during optimization. A Golden Section search method was used to find optimal rotor RPM on a conventional helicopter, where the single redundant control effector is rotor RPM. The FTO builds off of the Adaptive Performance Optimization (APO) method of Gilyard by performing low frequency sweeps on a redundant control for a fixed wing aircraft. A method based on the APO method was used to optimize trim on a compound rotorcraft with several redundant control effectors. The controller can be used to optimize rotor RPM and compound control effectors through flight test or simulations in order to

  6. Circadian clocks optimally adapt to sunlight for reliable synchronization

    PubMed Central

    Hasegawa, Yoshihiko; Arita, Masanori

    2014-01-01

    Circadian oscillation provides selection advantages through synchronization to the daylight cycle. However, a reliable clock must be designed through two conflicting properties: entrainability to synchronize internal time with periodic stimuli such as sunlight, and regularity to oscillate with a precise period. These two aspects do not easily coexist, because better entrainability favours higher sensitivity which may sacrifice regularity. To investigate conditions for satisfying the two properties, we analytically calculated the optimal phase–response curve with a variational method. Our results indicate an existence of a dead zone, i.e. a time period during which input stimuli neither advance nor delay the clock. A dead zone appears only when input stimuli obey the time course of actual solar radiation, but a simple sine curve cannot yield a dead zone. Our calculation demonstrates that every circadian clock with a dead zone is optimally adapted to the daylight cycle. PMID:24352677

  7. Optimal performance of endoreversible quantum refrigerators.

    PubMed

    Correa, Luis A; Palao, José P; Adesso, Gerardo; Alonso, Daniel

    2014-12-01

    The derivation of general performance benchmarks is important in the design of highly optimized heat engines and refrigerators. To obtain them, one may model phenomenologically the leading sources of irreversibility ending up with results that are model independent, but limited in scope. Alternatively, one can take a simple physical system realizing a thermodynamic cycle and assess its optimal operation from a complete microscopic description. We follow this approach in order to derive the coefficient of performance at maximum cooling rate for any endoreversible quantum refrigerator. At striking variance with the universality of the optimal efficiency of heat engines, we find that the cooling performance at maximum power is crucially determined by the details of the specific system-bath interaction mechanism. A closed analytical benchmark is found for endoreversible refrigerators weakly coupled to unstructured bosonic heat baths: an ubiquitous case study in quantum thermodynamics.

  8. A Computational Model of Optimal Vein Graft Adaptation in an Arterial Environment

    NASA Astrophysics Data System (ADS)

    Ramachandra, Abhay B.; Sankaran, Sethuraman; Humphrey, Jay; Marsden, Alison

    2012-11-01

    In coronary artery disease, surgical revascularization using venous bypass grafts is performed to relieve symptoms and prolong life. Coronary bypass graft surgery is performed on approximately 500,000 people every year in the United States, with graft failure rates as high as 50% within 5 years. When a vein graft is implanted in the arterial system it adapts to the high flow rate and high pressure of the arterial environment by changing composition and geometry, and thus stiffness. Hemodynamic loads, resulting in altered wall shear and intramural stresses, are major factors impacting vein graft remodeling. Here, a constrained mixture theory of growth and remodeling for arteries is extended to model the evolution of a vein graft subjected to arterial flow and pressure conditions. A derivative-free optimization method is used to estimate the optimal set of constitutive parameters that best match passive biaxial mouse inferior vena cava data from experiments. Optimization is performed using surrogate management framework, a pattern search method with established convergence theory. The resulting parameter set is used to predict optimal vein adaptation in an arterial environment for two illustrative cases: a) Step change b) Gradual change in loading. Results are compared against vein graft data from the literature and a possible set of mechanisms for sub-optimal vein graft remodeling is suggested.

  9. Optimizing Satellite Communications With Adaptive and Phased Array Antennas

    NASA Technical Reports Server (NTRS)

    Ingram, Mary Ann; Romanofsky, Robert; Lee, Richard Q.; Miranda, Felix; Popovic, Zoya; Langley, John; Barott, William C.; Ahmed, M. Usman; Mandl, Dan

    2004-01-01

    A new adaptive antenna array architecture for low-earth-orbiting satellite ground stations is being investigated. These ground stations are intended to have no moving parts and could potentially be operated in populated areas, where terrestrial interference is likely. The architecture includes multiple, moderately directive phased arrays. The phased arrays, each steered in the approximate direction of the satellite, are adaptively combined to enhance the Signal-to-Noise and Interference-Ratio (SNIR) of the desired satellite. The size of each phased array is to be traded-off with the number of phased arrays, to optimize cost, while meeting a bit-error-rate threshold. Also, two phased array architectures are being prototyped: a spacefed lens array and a reflect-array. If two co-channel satellites are in the field of view of the phased arrays, then multi-user detection techniques may enable simultaneous demodulation of the satellite signals, also known as Space Division Multiple Access (SDMA). We report on Phase I of the project, in which fixed directional elements are adaptively combined in a prototype to demodulate the S-band downlink of the EO-1 satellite, which is part of the New Millennium Program at NASA.

  10. Optimal control for unknown discrete-time nonlinear Markov jump systems using adaptive dynamic programming.

    PubMed

    Zhong, Xiangnan; He, Haibo; Zhang, Huaguang; Wang, Zhanshan

    2014-12-01

    In this paper, we develop and analyze an optimal control method for a class of discrete-time nonlinear Markov jump systems (MJSs) with unknown system dynamics. Specifically, an identifier is established for the unknown systems to approximate system states, and an optimal control approach for nonlinear MJSs is developed to solve the Hamilton-Jacobi-Bellman equation based on the adaptive dynamic programming technique. We also develop detailed stability analysis of the control approach, including the convergence of the performance index function for nonlinear MJSs and the existence of the corresponding admissible control. Neural network techniques are used to approximate the proposed performance index function and the control law. To demonstrate the effectiveness of our approach, three simulation studies, one linear case, one nonlinear case, and one single link robot arm case, are used to validate the performance of the proposed optimal control method.

  11. Optimal control for unknown discrete-time nonlinear Markov jump systems using adaptive dynamic programming.

    PubMed

    Zhong, Xiangnan; He, Haibo; Zhang, Huaguang; Wang, Zhanshan

    2014-12-01

    In this paper, we develop and analyze an optimal control method for a class of discrete-time nonlinear Markov jump systems (MJSs) with unknown system dynamics. Specifically, an identifier is established for the unknown systems to approximate system states, and an optimal control approach for nonlinear MJSs is developed to solve the Hamilton-Jacobi-Bellman equation based on the adaptive dynamic programming technique. We also develop detailed stability analysis of the control approach, including the convergence of the performance index function for nonlinear MJSs and the existence of the corresponding admissible control. Neural network techniques are used to approximate the proposed performance index function and the control law. To demonstrate the effectiveness of our approach, three simulation studies, one linear case, one nonlinear case, and one single link robot arm case, are used to validate the performance of the proposed optimal control method. PMID:25420238

  12. Proficient brain for optimal performance: the MAP model perspective.

    PubMed

    Bertollo, Maurizio; di Fronso, Selenia; Filho, Edson; Conforto, Silvia; Schmid, Maurizio; Bortoli, Laura; Comani, Silvia; Robazza, Claudio

    2016-01-01

    Background. The main goal of the present study was to explore theta and alpha event-related desynchronization/synchronization (ERD/ERS) activity during shooting performance. We adopted the idiosyncratic framework of the multi-action plan (MAP) model to investigate different processing modes underpinning four types of performance. In particular, we were interested in examining the neural activity associated with optimal-automated (Type 1) and optimal-controlled (Type 2) performances. Methods. Ten elite shooters (6 male and 4 female) with extensive international experience participated in the study. ERD/ERS analysis was used to investigate cortical dynamics during performance. A 4 × 3 (performance types × time) repeated measures analysis of variance was performed to test the differences among the four types of performance during the three seconds preceding the shots for theta, low alpha, and high alpha frequency bands. The dependent variables were the ERD/ERS percentages in each frequency band (i.e., theta, low alpha, high alpha) for each electrode site across the scalp. This analysis was conducted on 120 shots for each participant in three different frequency bands and the individual data were then averaged. Results. We found ERS to be mainly associated with optimal-automatic performance, in agreement with the "neural efficiency hypothesis." We also observed more ERD as related to optimal-controlled performance in conditions of "neural adaptability" and proficient use of cortical resources. Discussion. These findings are congruent with the MAP conceptualization of four performance states, in which unique psychophysiological states underlie distinct performance-related experiences. From an applied point of view, our findings suggest that the MAP model can be used as a framework to develop performance enhancement strategies based on cognitive and neurofeedback techniques. PMID:27257557

  13. Enabling occupational performance: optimal experiences in therapy.

    PubMed

    Rebeiro, K L; Polgar, J M

    1999-02-01

    Occupational therapists believe that engagement in occupation contributes to health through an individually balanced use of time, a positive focus for one's physical and mental energy, and the provision of a sense of purpose. Flow is a construct which describes optimal experiences or enjoyment in everyday activities. A review of the literature suggests that the theory of optimal experience is complementary to occupational therapy beliefs and that an understanding of the flow experience may contribute to our understanding of human occupation. Specifically, flow may be useful in understanding those aspects of the occupation, environment and person that contribute to a "just right" challenge, and to enabling occupational performance through enjoyable, structured and purposeful activity. Occupational therapists are encouraged to explore whether optimal experiences facilitate occupational performance for individuals with a disability. Future research could explore whether the occupational opportunities available to persons with a disability provide the degree of challenge required to elicit the optimal experience. Finally, research could explore whether the client-driven selection of meaningful occupation, and therapist enablement of the "just right" challenge, influences optimal experience, occupational performance, and life satisfaction for those with a disability. PMID:10462878

  14. Performance evaluation of a sensorless adaptive optics multiphoton microscope.

    PubMed

    Skorsetz, Martin; Artal, Pablo; Bueno, Juan M

    2016-03-01

    A wavefront sensorless adaptive optics technique was combined with a custom-made multiphoton microscope to correct for specimen-induced aberrations. A liquid-crystal-on-silicon (LCoS) modulator was used to systematically generate Zernike modes during image recording. The performance of the instrument was evaluated in samples providing different nonlinear signals and the benefit of correcting higher order aberrations was always noticeable (in both contrast and resolution). The optimum aberration pattern was stable in time for the samples here involved. For a particular depth location within the sample, the wavefront to be precompensated was independent on the size of the imaged area (up to ∼ 360 × 360 μm(2)). The mode combination optimizing the recorded image depended on the Zernike correction control sequence; however, the final images hardly differed. At deeper locations, a noticeable dominance of spherical aberration was found. The influence of other aberration terms was also compared to the effect of the spherical aberration.

  15. Separator profile selection for optimal battery performance

    NASA Astrophysics Data System (ADS)

    Whear, J. Kevin

    Battery performance, depending on the application, is normally defined by power delivery, electrical capacity, cycling regime and life in service. In order to meet the various performance goals, the Battery Design Engineer can vary things such as grid alloys, paste formulations, number of plates and methods of construction. Another design option available to optimize the battery performance is the separator profile. The goal of this paper is to demonstrate how separator profile selection can be utilized to optimize battery performance and manufacturing efficiencies. Also time will be given to explore novel separator profiles which may bring even greater benefits in the future. All major lead-acid application will be considered including automotive, motive power and stationary.

  16. Optimal performance of a quantum Otto refrigerator

    NASA Astrophysics Data System (ADS)

    Abah, Obinna; Lutz, Eric

    2016-03-01

    We consider a quantum Otto refrigerator cycle of a time-dependent harmonic oscillator. We investigate the coefficient of performance at maximum figure of merit for adiabatic and nonadiabatic frequency modulations. We obtain analytical expressions for the optimal performance both in the high-temperature (classical) regime and in the low-temperature (quantum) limit. We moreover analyze the breakdown of the cooling cycle for strongly nonadiabatic driving protocols and derive analytical estimates for the minimal driving time allowed for cooling.

  17. An adaptive ant colony system algorithm for continuous-space optimization problems.

    PubMed

    Li, Yan-jun; Wu, Tie-jun

    2003-01-01

    Ant colony algorithms comprise a novel category of evolutionary computation methods for optimization problems, especially for sequencing-type combinatorial optimization problems. An adaptive ant colony algorithm is proposed in this paper to tackle continuous-space optimization problems, using a new objective-function-based heuristic pheromone assignment approach for pheromone update to filtrate solution candidates. Global optimal solutions can be reached more rapidly by self-adjusting the path searching behaviors of the ants according to objective values. The performance of the proposed algorithm is compared with a basic ant colony algorithm and a Square Quadratic Programming approach in solving two benchmark problems with multiple extremes. The results indicated that the efficiency and reliability of the proposed algorithm were greatly improved. PMID:12656341

  18. Optimal performance of constrained control systems

    NASA Astrophysics Data System (ADS)

    Harvey, P. Scott, Jr.; Gavin, Henri P.; Scruggs, Jeffrey T.

    2012-08-01

    This paper presents a method to compute optimal open-loop trajectories for systems subject to state and control inequality constraints in which the cost function is quadratic and the state dynamics are linear. For the case in which inequality constraints are decentralized with respect to the controls, optimal Lagrange multipliers enforcing the inequality constraints may be found at any time through Pontryagin’s minimum principle. In so doing, the set of differential algebraic Euler-Lagrange equations is transformed into a nonlinear two-point boundary-value problem for states and costates whose solution meets the necessary conditions for optimality. The optimal performance of inequality constrained control systems is calculable, allowing for comparison to previous, sub-optimal solutions. The method is applied to the control of damping forces in a vibration isolation system subjected to constraints imposed by the physical implementation of a particular controllable damper. An outcome of this study is the best performance achievable given a particular objective, isolation system, and semi-active damper constraints.

  19. Neural network approach to continuous-time direct adaptive optimal control for partially unknown nonlinear systems.

    PubMed

    Vrabie, Draguna; Lewis, Frank

    2009-04-01

    In this paper we present in a continuous-time framework an online approach to direct adaptive optimal control with infinite horizon cost for nonlinear systems. The algorithm converges online to the optimal control solution without knowledge of the internal system dynamics. Closed-loop dynamic stability is guaranteed throughout. The algorithm is based on a reinforcement learning scheme, namely Policy Iterations, and makes use of neural networks, in an Actor/Critic structure, to parametrically represent the control policy and the performance of the control system. The two neural networks are trained to express the optimal controller and optimal cost function which describes the infinite horizon control performance. Convergence of the algorithm is proven under the realistic assumption that the two neural networks do not provide perfect representations for the nonlinear control and cost functions. The result is a hybrid control structure which involves a continuous-time controller and a supervisory adaptation structure which operates based on data sampled from the plant and from the continuous-time performance dynamics. Such control structure is unlike any standard form of controllers previously seen in the literature. Simulation results, obtained considering two second-order nonlinear systems, are provided.

  20. Neural network approach to continuous-time direct adaptive optimal control for partially unknown nonlinear systems.

    PubMed

    Vrabie, Draguna; Lewis, Frank

    2009-04-01

    In this paper we present in a continuous-time framework an online approach to direct adaptive optimal control with infinite horizon cost for nonlinear systems. The algorithm converges online to the optimal control solution without knowledge of the internal system dynamics. Closed-loop dynamic stability is guaranteed throughout. The algorithm is based on a reinforcement learning scheme, namely Policy Iterations, and makes use of neural networks, in an Actor/Critic structure, to parametrically represent the control policy and the performance of the control system. The two neural networks are trained to express the optimal controller and optimal cost function which describes the infinite horizon control performance. Convergence of the algorithm is proven under the realistic assumption that the two neural networks do not provide perfect representations for the nonlinear control and cost functions. The result is a hybrid control structure which involves a continuous-time controller and a supervisory adaptation structure which operates based on data sampled from the plant and from the continuous-time performance dynamics. Such control structure is unlike any standard form of controllers previously seen in the literature. Simulation results, obtained considering two second-order nonlinear systems, are provided. PMID:19362449

  1. Sleep As A Strategy For Optimizing Performance.

    PubMed

    Yarnell, Angela M; Deuster, Patricia

    2016-01-01

    Recovery is an essential component of maintaining, sustaining, and optimizing cognitive and physical performance during and after demanding training and strenuous missions. Getting sufficient amounts of rest and sleep is key to recovery. This article focuses on sleep and discusses (1) why getting sufficient sleep is important, (2) how to optimize sleep, and (3) tools available to help maximize sleep-related performance. Insufficient sleep negatively impacts safety and readiness through reduced cognitive function, more accidents, and increased military friendly-fire incidents. Sufficient sleep is linked to better cognitive performance outcomes, increased vigor, and better physical and athletic performance as well as improved emotional and social functioning. Because Special Operations missions do not always allow for optimal rest or sleep, the impact of reduced rest and sleep on readiness and mission success should be minimized through appropriate preparation and planning. Preparation includes periods of "banking" or extending sleep opportunities before periods of loss, monitoring sleep by using tools like actigraphy to measure sleep and activity, assessing mental effectiveness, exploiting strategic sleep opportunities, and consuming caffeine at recommended doses to reduce fatigue during periods of loss. Together, these efforts may decrease the impact of sleep loss on mission and performance. PMID:27045502

  2. Sleep As A Strategy For Optimizing Performance.

    PubMed

    Yarnell, Angela M; Deuster, Patricia

    2016-01-01

    Recovery is an essential component of maintaining, sustaining, and optimizing cognitive and physical performance during and after demanding training and strenuous missions. Getting sufficient amounts of rest and sleep is key to recovery. This article focuses on sleep and discusses (1) why getting sufficient sleep is important, (2) how to optimize sleep, and (3) tools available to help maximize sleep-related performance. Insufficient sleep negatively impacts safety and readiness through reduced cognitive function, more accidents, and increased military friendly-fire incidents. Sufficient sleep is linked to better cognitive performance outcomes, increased vigor, and better physical and athletic performance as well as improved emotional and social functioning. Because Special Operations missions do not always allow for optimal rest or sleep, the impact of reduced rest and sleep on readiness and mission success should be minimized through appropriate preparation and planning. Preparation includes periods of "banking" or extending sleep opportunities before periods of loss, monitoring sleep by using tools like actigraphy to measure sleep and activity, assessing mental effectiveness, exploiting strategic sleep opportunities, and consuming caffeine at recommended doses to reduce fatigue during periods of loss. Together, these efforts may decrease the impact of sleep loss on mission and performance.

  3. Self-Adaptive Stepsize Search Applied to Optimal Structural Design

    NASA Astrophysics Data System (ADS)

    Nolle, L.; Bland, J. A.

    Structural engineering often involves the design of space frames that are required to resist predefined external forces without exhibiting plastic deformation. The weight of the structure and hence the weight of its constituent members has to be as low as possible for economical reasons without violating any of the load constraints. Design spaces are usually vast and the computational costs for analyzing a single design are usually high. Therefore, not every possible design can be evaluated for real-world problems. In this work, a standard structural design problem, the 25-bar problem, has been solved using self-adaptive stepsize search (SASS), a relatively new search heuristic. This algorithm has only one control parameter and therefore overcomes the drawback of modern search heuristics, i.e. the need to first find a set of optimum control parameter settings for the problem at hand. In this work, SASS outperforms simulated-annealing, genetic algorithms, tabu search and ant colony optimization.

  4. An adaptive image enhancement technique by combining cuckoo search and particle swarm optimization algorithm.

    PubMed

    Ye, Zhiwei; Wang, Mingwei; Hu, Zhengbing; Liu, Wei

    2015-01-01

    Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper. PMID:25784928

  5. An adaptive image enhancement technique by combining cuckoo search and particle swarm optimization algorithm.

    PubMed

    Ye, Zhiwei; Wang, Mingwei; Hu, Zhengbing; Liu, Wei

    2015-01-01

    Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper.

  6. An Adaptive Image Enhancement Technique by Combining Cuckoo Search and Particle Swarm Optimization Algorithm

    PubMed Central

    Ye, Zhiwei; Wang, Mingwei; Hu, Zhengbing; Liu, Wei

    2015-01-01

    Image enhancement is an important procedure of image processing and analysis. This paper presents a new technique using a modified measure and blending of cuckoo search and particle swarm optimization (CS-PSO) for low contrast images to enhance image adaptively. In this way, contrast enhancement is obtained by global transformation of the input intensities; it employs incomplete Beta function as the transformation function and a novel criterion for measuring image quality considering three factors which are threshold, entropy value, and gray-level probability density of the image. The enhancement process is a nonlinear optimization problem with several constraints. CS-PSO is utilized to maximize the objective fitness criterion in order to enhance the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The performance of the proposed method has been compared with other existing techniques such as linear contrast stretching, histogram equalization, and evolutionary computing based image enhancement methods like backtracking search algorithm, differential search algorithm, genetic algorithm, and particle swarm optimization in terms of processing time and image quality. Experimental results demonstrate that the proposed method is robust and adaptive and exhibits the better performance than other methods involved in the paper. PMID:25784928

  7. Optimizing Photon Collection from Point Sources with Adaptive Optics

    NASA Astrophysics Data System (ADS)

    Hill, Alexander; Hervas, David; Nash, Joseph; Graham, Martin; Burgers, Alexander; Paudel, Uttam; Steel, Duncan; Kwiat, Paul

    2015-05-01

    Collection of light from point-like sources is typically poor due to the optical aberrations present with very high numerical-aperture optics. In the case of quantum dots, the emitted mode is nonisotropic and may be quite difficult to couple into single- or even few-mode fiber. Wavefront aberrations can be corrected using adaptive optics at the classical level by analyzing the wavefront directly (e.g., with a Shack-Hartmann sensor); however, these techniques are not feasible at the single-photon level. We present a new technique for adaptive optics with single photons using a genetic algorithm to optimize collection from point emitters with a deformable mirror. We first demonstrate our technique for improving coupling from a subwavelength pinhole, which simulates isotropic emission from a point source. We then apply our technique in situto InAs/GaAs quantum dots, obtaining coupling increases of up to 50% even in the presence of an artificial source of drift.

  8. Performance of keck adaptive optics with sodium laser guide star

    SciTech Connect

    Gavel, D.T.; Olivier, S.; Brase, J.

    1996-03-08

    The Keck telescope adaptive optics system is designed to optimize performance in he 1 to 3 micron region of observation wavelengths (J, H, and K astronomical bands). The system uses a 249 degree of freedom deformable mirror, so that the interactuator spacing is 56 cm as mapped onto the 10 meter aperture. 56 cm is roughly equal to r0 at 1.4 microns, which implies the wavefront fitting error is 0.52 ({lambda}/2{pi})({ital d}/{ital r}{sub 0}){sup 5/6} = 118 nm rms. This is sufficient to produce a system Strehl of 0.74 at 1.4 microns if all other sources of error are negligible, which would be the case with a bright natural guidestar and very high control bandwidth. Other errors associated with the adaptive optics will however contribute to Strehl degradation, namely, servo bandwidth error due to inability to reject all temporal frequencies of the aberrated wavefront, wavefront measurement error due to finite signal-to-noise ratio in the wavefront sensor, and, in the case of a laser guidestar, the so-called cone effect where rays from the guidestar beacon fail to sample some of the upper atmosphere turbulence. Cone effect is mitigated considerably by the use of the very high altitude sodium laser guidestar (90 km altitude), as opposed to Rayleigh beacons at 20 km. However, considering the Keck telescope`s large aperture, this is still the dominating wavefront error contributor in the current adaptive optics system design.

  9. Optimized adaptation algorithm for HEVC/H.265 dynamic adaptive streaming over HTTP using variable segment duration

    NASA Astrophysics Data System (ADS)

    Irondi, Iheanyi; Wang, Qi; Grecos, Christos

    2016-04-01

    Adaptive video streaming using HTTP has become popular in recent years for commercial video delivery. The recent MPEG-DASH standard allows interoperability and adaptability between servers and clients from different vendors. The delivery of the MPD (Media Presentation Description) files in DASH and the DASH client behaviours are beyond the scope of the DASH standard. However, the different adaptation algorithms employed by the clients do affect the overall performance of the system and users' QoE (Quality of Experience), hence the need for research in this field. Moreover, standard DASH delivery is based on fixed segments of the video. However, there is no standard segment duration for DASH where various fixed segment durations have been employed by different commercial solutions and researchers with their own individual merits. Most recently, the use of variable segment duration in DASH has emerged but only a few preliminary studies without practical implementation exist. In addition, such a technique requires a DASH client to be aware of segment duration variations, and this requirement and the corresponding implications on the DASH system design have not been investigated. This paper proposes a segment-duration-aware bandwidth estimation and next-segment selection adaptation strategy for DASH. Firstly, an MPD file extension scheme to support variable segment duration is proposed and implemented in a realistic hardware testbed. The scheme is tested on a DASH client, and the tests and analysis have led to an insight on the time to download next segment and the buffer behaviour when fetching and switching between segments of different playback durations. Issues like sustained buffering when switching between segments of different durations and slow response to changing network conditions are highlighted and investigated. An enhanced adaptation algorithm is then proposed to accurately estimate the bandwidth and precisely determine the time to download the next

  10. Enhancing astronaut performance using sensorimotor adaptability training.

    PubMed

    Bloomberg, Jacob J; Peters, Brian T; Cohen, Helen S; Mulavara, Ajitkumar P

    2015-01-01

    Astronauts experience disturbances in balance and gait function when they return to Earth. The highly plastic human brain enables individuals to modify their behavior to match the prevailing environment. Subjects participating in specially designed variable sensory challenge training programs can enhance their ability to rapidly adapt to novel sensory situations. This is useful in our application because we aim to train astronauts to rapidly formulate effective strategies to cope with the balance and locomotor challenges associated with new gravitational environments-enhancing their ability to "learn to learn." We do this by coupling various combinations of sensorimotor challenges with treadmill walking. A unique training system has been developed that is comprised of a treadmill mounted on a motion base to produce movement of the support surface during walking. This system provides challenges to gait stability. Additional sensory variation and challenge are imposed with a virtual visual scene that presents subjects with various combinations of discordant visual information during treadmill walking. This experience allows them to practice resolving challenging and conflicting novel sensory information to improve their ability to adapt rapidly. Information obtained from this work will inform the design of the next generation of sensorimotor countermeasures for astronauts. PMID:26441561

  11. Enhancing astronaut performance using sensorimotor adaptability training.

    PubMed

    Bloomberg, Jacob J; Peters, Brian T; Cohen, Helen S; Mulavara, Ajitkumar P

    2015-01-01

    Astronauts experience disturbances in balance and gait function when they return to Earth. The highly plastic human brain enables individuals to modify their behavior to match the prevailing environment. Subjects participating in specially designed variable sensory challenge training programs can enhance their ability to rapidly adapt to novel sensory situations. This is useful in our application because we aim to train astronauts to rapidly formulate effective strategies to cope with the balance and locomotor challenges associated with new gravitational environments-enhancing their ability to "learn to learn." We do this by coupling various combinations of sensorimotor challenges with treadmill walking. A unique training system has been developed that is comprised of a treadmill mounted on a motion base to produce movement of the support surface during walking. This system provides challenges to gait stability. Additional sensory variation and challenge are imposed with a virtual visual scene that presents subjects with various combinations of discordant visual information during treadmill walking. This experience allows them to practice resolving challenging and conflicting novel sensory information to improve their ability to adapt rapidly. Information obtained from this work will inform the design of the next generation of sensorimotor countermeasures for astronauts.

  12. Enhancing astronaut performance using sensorimotor adaptability training

    PubMed Central

    Bloomberg, Jacob J.; Peters, Brian T.; Cohen, Helen S.; Mulavara, Ajitkumar P.

    2015-01-01

    Astronauts experience disturbances in balance and gait function when they return to Earth. The highly plastic human brain enables individuals to modify their behavior to match the prevailing environment. Subjects participating in specially designed variable sensory challenge training programs can enhance their ability to rapidly adapt to novel sensory situations. This is useful in our application because we aim to train astronauts to rapidly formulate effective strategies to cope with the balance and locomotor challenges associated with new gravitational environments—enhancing their ability to “learn to learn.” We do this by coupling various combinations of sensorimotor challenges with treadmill walking. A unique training system has been developed that is comprised of a treadmill mounted on a motion base to produce movement of the support surface during walking. This system provides challenges to gait stability. Additional sensory variation and challenge are imposed with a virtual visual scene that presents subjects with various combinations of discordant visual information during treadmill walking. This experience allows them to practice resolving challenging and conflicting novel sensory information to improve their ability to adapt rapidly. Information obtained from this work will inform the design of the next generation of sensorimotor countermeasures for astronauts. PMID:26441561

  13. Performance-Based Adaptive Fuzzy Tracking Control for Networked Industrial Processes.

    PubMed

    Wang, Tong; Qiu, Jianbin; Yin, Shen; Gao, Huijun; Fan, Jialu; Chai, Tianyou

    2016-08-01

    In this paper, the performance-based control design problem for double-layer networked industrial processes is investigated. At the device layer, the prescribed performance functions are first given to describe the output tracking performance, and then by using backstepping technique, new adaptive fuzzy controllers are designed to guarantee the tracking performance under the effects of input dead-zone and the constraint of prescribed tracking performance functions. At operation layer, by considering the stochastic disturbance, actual index value, target index value, and index prediction simultaneously, an adaptive inverse optimal controller in discrete-time form is designed to optimize the overall performance and stabilize the overall nonlinear system. Finally, a simulation example of continuous stirred tank reactor system is presented to show the effectiveness of the proposed control method.

  14. Adaptive Sampling of Spatiotemporal Phenomena with Optimization Criteria

    NASA Technical Reports Server (NTRS)

    Chien, Steve A.; Thompson, David R.; Hsiang, Kian

    2013-01-01

    This work was designed to find a way to optimally (or near optimally) sample spatiotemporal phenomena based on limited sensing capability, and to create a model that can be run to estimate uncertainties, as well as to estimate covariances. The goal was to maximize (or minimize) some function of the overall uncertainty. The uncertainties and covariances were modeled presuming a parametric distribution, and then the model was used to approximate the overall information gain, and consequently, the objective function from each potential sense. These candidate sensings were then crosschecked against operation costs and feasibility. Consequently, an operations plan was derived that combined both operational constraints/costs and sensing gain. Probabilistic modeling was used to perform an approximate inversion of the model, which enabled calculation of sensing gains, and subsequent combination with operational costs. This incorporation of operations models to assess cost and feasibility for specific classes of vehicles is unique.

  15. Performance-optimized clinical IMRT planning on modern CPUs

    NASA Astrophysics Data System (ADS)

    Ziegenhein, Peter; Kamerling, Cornelis Ph; Bangert, Mark; Kunkel, Julian; Oelfke, Uwe

    2013-06-01

    Intensity modulated treatment plan optimization is a computationally expensive task. The feasibility of advanced applications in intensity modulated radiation therapy as every day treatment planning, frequent re-planning for adaptive radiation therapy and large-scale planning research severely depends on the runtime of the plan optimization implementation. Modern computational systems are built as parallel architectures to yield high performance. The use of GPUs, as one class of parallel systems, has become very popular in the field of medical physics. In contrast we utilize the multi-core central processing unit (CPU), which is the heart of every modern computer and does not have to be purchased additionally. In this work we present an ultra-fast, high precision implementation of the inverse plan optimization problem using a quasi-Newton method on pre-calculated dose influence data sets. We redefined the classical optimization algorithm to achieve a minimal runtime and high scalability on CPUs. Using the proposed methods in this work, a total plan optimization process can be carried out in only a few seconds on a low-cost CPU-based desktop computer at clinical resolution and quality. We have shown that our implementation uses the CPU hardware resources efficiently with runtimes comparable to GPU implementations, at lower costs.

  16. Identification of robust adaptation gene regulatory network parameters using an improved particle swarm optimization algorithm.

    PubMed

    Huang, X N; Ren, H P

    2016-01-01

    Robust adaptation is a critical ability of gene regulatory network (GRN) to survive in a fluctuating environment, which represents the system responding to an input stimulus rapidly and then returning to its pre-stimulus steady state timely. In this paper, the GRN is modeled using the Michaelis-Menten rate equations, which are highly nonlinear differential equations containing 12 undetermined parameters. The robust adaption is quantitatively described by two conflicting indices. To identify the parameter sets in order to confer the GRNs with robust adaptation is a multi-variable, multi-objective, and multi-peak optimization problem, which is difficult to acquire satisfactory solutions especially high-quality solutions. A new best-neighbor particle swarm optimization algorithm is proposed to implement this task. The proposed algorithm employs a Latin hypercube sampling method to generate the initial population. The particle crossover operation and elitist preservation strategy are also used in the proposed algorithm. The simulation results revealed that the proposed algorithm could identify multiple solutions in one time running. Moreover, it demonstrated a superior performance as compared to the previous methods in the sense of detecting more high-quality solutions within an acceptable time. The proposed methodology, owing to its universality and simplicity, is useful for providing the guidance to design GRN with superior robust adaptation. PMID:27323043

  17. Morphology optimization for enhanced performance in organic photovoltaics

    NASA Astrophysics Data System (ADS)

    Wodo, Olga; Zola, Jaroslaw; Ganapathysubramanian, Baskar

    2015-03-01

    Organic solar cells have the potential for widespread usage due to their low cost-per-watt and mechanical flexibility. Their wide spread use, however, is bottlenecked primarily by their low solar efficiencies. Experimental evidence suggests that a key property determining the solar efficiency of such devices is the final morphological distribution of the electron-donor and electron-acceptor constituents. By carefully designing the morphology of the device, one could potentially significantly enhance their performance. This is an area of intense experimental effort that is mostly trial-and-error based, and serves as a fertile area for introducing mechanics and computational thinking. In this work, we use optimization techniques coupled with computational modeling to identify the optimal structures for high efficiency solar cells. In particular, we use adaptive population-based incremental learning method linked to graph-based surrogate model to evaluate properties for given structure. We study several different criterions and find optimal structure that that improve the performance of currently hypothesized optimal structures by 29%.

  18. Optimal Control Problem of Feeding Adaptations of Daphnia and Neural Network Simulation

    NASA Astrophysics Data System (ADS)

    Kmet', Tibor; Kmet'ov, Mria

    2010-09-01

    A neural network based optimal control synthesis is presented for solving optimal control problems with control and state constraints and open final time. The optimal control problem is transcribed into nonlinear programming problem, which is implemented with adaptive critic neural network [9] and recurrent neural network for solving nonlinear proprojection equations [10]. The proposed simulation methods is illustrated by the optimal control problem of feeding adaptation of filter feeders of Daphnia. Results show that adaptive critic based systematic approach and neural network solving of nonlinear equations hold promise for obtaining the optimal control with control and state constraints and open final time.

  19. Automated Cache Performance Analysis And Optimization

    SciTech Connect

    Mohror, Kathryn

    2013-12-23

    While there is no lack of performance counter tools for coarse-grained measurement of cache activity, there is a critical lack of tools for relating data layout to cache behavior to application performance. Generally, any nontrivial optimizations are either not done at all, or are done ”by hand” requiring significant time and expertise. To the best of our knowledge no tool available to users measures the latency of memory reference instructions for partic- ular addresses and makes this information available to users in an easy-to-use and intuitive way. In this project, we worked to enable the Open|SpeedShop performance analysis tool to gather memory reference latency information for specific instructions and memory ad- dresses, and to gather and display this information in an easy-to-use and intuitive way to aid performance analysts in identifying problematic data structures in their codes. This tool was primarily designed for use in the supercomputer domain as well as grid, cluster, cloud-based parallel e-commerce, and engineering systems and middleware. Ultimately, we envision a tool to automate optimization of application cache layout and utilization in the Open|SpeedShop performance analysis tool. To commercialize this soft- ware, we worked to develop core capabilities for gathering enhanced memory usage per- formance data from applications and create and apply novel methods for automatic data structure layout optimizations, tailoring the overall approach to support existing supercom- puter and cluster programming models and constraints. In this Phase I project, we focused on infrastructure necessary to gather performance data and present it in an intuitive way to users. With the advent of enhanced Precise Event-Based Sampling (PEBS) counters on recent Intel processor architectures and equivalent technology on AMD processors, we are now in a position to access memory reference information for particular addresses. Prior to the introduction of PEBS counters

  20. Optimal imaging with adaptive mesh refinement in electrical impedance tomography.

    PubMed

    Molinari, Marc; Blott, Barry H; Cox, Simon J; Daniell, Geoffrey J

    2002-02-01

    In non-linear electrical impedance tomography the goodness of fit of the trial images is assessed by the well-established statistical chi2 criterion applied to the measured and predicted datasets. Further selection from the range of images that fit the data is effected by imposing an explicit constraint on the form of the image, such as the minimization of the image gradients. In particular, the logarithm of the image gradients is chosen so that conductive and resistive deviations are treated in the same way. In this paper we introduce the idea of adaptive mesh refinement to the 2D problem so that the local scale of the mesh is always matched to the scale of the image structures. This improves the reconstruction resolution so that the image constraint adopted dominates and is not perturbed by the mesh discretization. The avoidance of unnecessary mesh elements optimizes the speed of reconstruction without degrading the resulting images. Starting with a mesh scale length of the order of the electrode separation it is shown that, for data obtained at presently achievable signal-to-noise ratios of 60 to 80 dB, one or two refinement stages are sufficient to generate high quality images.

  1. Adaptive Tempering Monte Carlo Optimization of Calcium Clusters.

    NASA Astrophysics Data System (ADS)

    Dong, X.; Blaisten-Barojas, E.

    2006-03-01

    The global minimum energy structures of calcium clusters with 15 to 34 atoms were obtained by the Adaptive Tempering Monte Carlo (ATMC) method. The cluster binding energy was obtained within a tight binding approach with parameters reported in previous work[1]. The ATMC optimization process is fast and drives the system across configuration space very effectively reaching the global minimum within a small number of tempering events. The structure of six cluster sizes 15, 16, 18, 21, 23 and 25 corresponding to the global minimum has not been reported in the literature for any other metals. Three clusters Ca15, Ca21 and Ca23 are relatively more stable than the others in this size range. Melting of these clusters are further studied with the weighted histogram analysis method and the free energy profile is predicted. The melting transition is monitored with a novel structural order parameter that reflects the mobility of surface atoms, their bonding order and bonding directionality. [1] X. Dong, G. M. Wang, E. Blaisten-Barojas, Phys. Rev. B 70, 205409 (2004).

  2. Adaptive Portfolio Optimization for Multiple Electricity Markets Participation.

    PubMed

    Pinto, Tiago; Morais, Hugo; Sousa, Tiago M; Sousa, Tiago; Vale, Zita; Praca, Isabel; Faia, Ricardo; Pires, Eduardo Jose Solteiro

    2016-08-01

    The increase of distributed energy resources, mainly based on renewable sources, requires new solutions that are able to deal with this type of resources' particular characteristics (namely, the renewable energy sources intermittent nature). The smart grid concept is increasing its consensus as the most suitable solution to facilitate the small players' participation in electric power negotiations while improving energy efficiency. The opportunity for players' participation in multiple energy negotiation environments (smart grid negotiation in addition to the already implemented market types, such as day-ahead spot markets, balancing markets, intraday negotiations, bilateral contracts, forward and futures negotiations, and among other) requires players to take suitable decisions on whether to, and how to participate in each market type. This paper proposes a portfolio optimization methodology, which provides the best investment profile for a market player, considering different market opportunities. The amount of power that each supported player should negotiate in each available market type in order to maximize its profits, considers the prices that are expected to be achieved in each market, in different contexts. The price forecasts are performed using artificial neural networks, providing a specific database with the expected prices in the different market types, at each time. This database is then used as input by an evolutionary particle swarm optimization process, which originates the most advantage participation portfolio for the market player. The proposed approach is tested and validated with simulations performed in multiagent simulator of competitive electricity markets, using real electricity markets data from the Iberian operator-MIBEL.

  3. Importance of eccentric actions in performance adaptations to resistance training.

    PubMed

    Dudley, G A; Tesch, P A; Miller, B J; Buchanan, P

    1991-06-01

    The inability of the exercises presently used during space-flight to maintain muscle strength and mass may reflect the absence of eccentric (ecc) muscle actions. This study examined the importance of ecc actions in performance adaptations to resistance training. Middle-aged males performed 4-5 sets of 6-12 repetitions (rep) per set of the leg press and leg extension exercises 2 d each week for 19 weeks. Group CON/ECC (n = 9) performed each rep with concentric (con) and ecc actions, group CON (n = 8) with only con actions. Group CON/CON (n = 10) performed twice as many sets with only con actions. The resistance per set was selected to induce failure within the prescribed number of rep. Eight subjects did not train and served as controls. The increase in the three rep maximum (3RM) after training, in general, showed a hierarchy such that CON/ECC greater than CON/CON greater than CON. The differences (p less than 0.05) were: leg press 3RM with con and ecc actions, CON/ECC greater than CON/CON greater than CON (26 greater than 15 greater than 8%); leg press 3RM with only con actions, CON/ECC or CON/CON greater than CON (22 or 18 greater than 14%); and leg extension 3RM with con and ecc actions, CON/ECC greater than CON (29 greater than 16%). These differences (p less than 0.05) were still evident after 1 month of de-training. The results indicate that omission of ecc actions from resistance training compromises increases in strength, probably because intensity is not optimal.(ABSTRACT TRUNCATED AT 250 WORDS)

  4. Adaptive surrogate model based multi-objective transfer trajectory optimization between different libration points

    NASA Astrophysics Data System (ADS)

    Peng, Haijun; Wang, Wei

    2016-10-01

    An adaptive surrogate model-based multi-objective optimization strategy that combines the benefits of invariant manifolds and low-thrust control toward developing a low-computational-cost transfer trajectory between libration orbits around the L1 and L2 libration points in the Sun-Earth system has been proposed in this paper. A new structure for a multi-objective transfer trajectory optimization model that divides the transfer trajectory into several segments and gives the dominations for invariant manifolds and low-thrust control in different segments has been established. To reduce the computational cost of multi-objective transfer trajectory optimization, a mixed sampling strategy-based adaptive surrogate model has been proposed. Numerical simulations show that the results obtained from the adaptive surrogate-based multi-objective optimization are in agreement with the results obtained using direct multi-objective optimization methods, and the computational workload of the adaptive surrogate-based multi-objective optimization is only approximately 10% of that of direct multi-objective optimization. Furthermore, the generating efficiency of the Pareto points of the adaptive surrogate-based multi-objective optimization is approximately 8 times that of the direct multi-objective optimization. Therefore, the proposed adaptive surrogate-based multi-objective optimization provides obvious advantages over direct multi-objective optimization methods.

  5. On the optimal reconstruction and control of adaptive optical systems with mirror dynamics.

    PubMed

    Correia, Carlos; Raynaud, Henri-François; Kulcsár, Caroline; Conan, Jean-Marc

    2010-02-01

    In adaptive optics (AO) the deformable mirror (DM) dynamics are usually neglected because, in general, the DM can be considered infinitely fast. Such assumption may no longer apply for the upcoming Extremely Large Telescopes (ELTs) with DM that are several meters in diameter with slow and/or resonant responses. For such systems an important challenge is to design an optimal regulator minimizing the variance of the residual phase. In this contribution, the general optimal minimum-variance (MV) solution to the full dynamical reconstruction and control problem of AO systems (AOSs) is established. It can be looked upon as the parent solution from which simpler (used hitherto) suboptimal solutions can be derived as special cases. These include either partial DM-dynamics-free solutions or solutions derived from the static minimum-variance reconstruction (where both atmospheric disturbance and DM dynamics are neglected altogether). Based on a continuous stochastic model of the disturbance, a state-space approach is developed that yields a fully optimal MV solution in the form of a discrete-time linear-quadratic-Gaussian (LQG) regulator design. From this LQG standpoint, the control-oriented state-space model allows one to (1) derive the optimal state-feedback linear regulator and (2) evaluate the performance of both the optimal and the sub-optimal solutions. Performance results are given for weakly damped second-order oscillatory DMs with large-amplitude resonant responses, in conditions representative of an ELT AO system. The highly energetic optical disturbance caused on the tip/tilt (TT) modes by the wind buffeting is considered. Results show that resonant responses are correctly handled with the MV regulator developed here. The use of sub-optimal regulators results in prohibitive performance losses in terms of residual variance; in addition, the closed-loop system may become unstable for resonant frequencies in the range of interest. PMID:20126246

  6. Adaptable Learning Pathway Generation with Ant Colony Optimization

    ERIC Educational Resources Information Center

    Wong, Lung-Hsiang; Looi, Chee-Kit

    2009-01-01

    One of the new major directions in research on web-based educational systems is the notion of adaptability: the educational system adapts itself to the learning profile, preferences and ability of the student. In this paper, we look into the issues of providing adaptability with respect to learning pathways. We explore the state of the art with…

  7. Robust Brain-Machine Interface Design Using Optimal Feedback Control Modeling and Adaptive Point Process Filtering

    PubMed Central

    Carmena, Jose M.

    2016-01-01

    Much progress has been made in brain-machine interfaces (BMI) using decoders such as Kalman filters and finding their parameters with closed-loop decoder adaptation (CLDA). However, current decoders do not model the spikes directly, and hence may limit the processing time-scale of BMI control and adaptation. Moreover, while specialized CLDA techniques for intention estimation and assisted training exist, a unified and systematic CLDA framework that generalizes across different setups is lacking. Here we develop a novel closed-loop BMI training architecture that allows for processing, control, and adaptation using spike events, enables robust control and extends to various tasks. Moreover, we develop a unified control-theoretic CLDA framework within which intention estimation, assisted training, and adaptation are performed. The architecture incorporates an infinite-horizon optimal feedback-control (OFC) model of the brain’s behavior in closed-loop BMI control, and a point process model of spikes. The OFC model infers the user’s motor intention during CLDA—a process termed intention estimation. OFC is also used to design an autonomous and dynamic assisted training technique. The point process model allows for neural processing, control and decoder adaptation with every spike event and at a faster time-scale than current decoders; it also enables dynamic spike-event-based parameter adaptation unlike current CLDA methods that use batch-based adaptation on much slower adaptation time-scales. We conducted closed-loop experiments in a non-human primate over tens of days to dissociate the effects of these novel CLDA components. The OFC intention estimation improved BMI performance compared with current intention estimation techniques. OFC assisted training allowed the subject to consistently achieve proficient control. Spike-event-based adaptation resulted in faster and more consistent performance convergence compared with batch-based methods, and was robust to

  8. Robust Brain-Machine Interface Design Using Optimal Feedback Control Modeling and Adaptive Point Process Filtering.

    PubMed

    Shanechi, Maryam M; Orsborn, Amy L; Carmena, Jose M

    2016-04-01

    Much progress has been made in brain-machine interfaces (BMI) using decoders such as Kalman filters and finding their parameters with closed-loop decoder adaptation (CLDA). However, current decoders do not model the spikes directly, and hence may limit the processing time-scale of BMI control and adaptation. Moreover, while specialized CLDA techniques for intention estimation and assisted training exist, a unified and systematic CLDA framework that generalizes across different setups is lacking. Here we develop a novel closed-loop BMI training architecture that allows for processing, control, and adaptation using spike events, enables robust control and extends to various tasks. Moreover, we develop a unified control-theoretic CLDA framework within which intention estimation, assisted training, and adaptation are performed. The architecture incorporates an infinite-horizon optimal feedback-control (OFC) model of the brain's behavior in closed-loop BMI control, and a point process model of spikes. The OFC model infers the user's motor intention during CLDA-a process termed intention estimation. OFC is also used to design an autonomous and dynamic assisted training technique. The point process model allows for neural processing, control and decoder adaptation with every spike event and at a faster time-scale than current decoders; it also enables dynamic spike-event-based parameter adaptation unlike current CLDA methods that use batch-based adaptation on much slower adaptation time-scales. We conducted closed-loop experiments in a non-human primate over tens of days to dissociate the effects of these novel CLDA components. The OFC intention estimation improved BMI performance compared with current intention estimation techniques. OFC assisted training allowed the subject to consistently achieve proficient control. Spike-event-based adaptation resulted in faster and more consistent performance convergence compared with batch-based methods, and was robust to parameter

  9. Bi-Objective Optimal Control Modification Adaptive Control for Systems with Input Uncertainty

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.

    2012-01-01

    This paper presents a new model-reference adaptive control method based on a bi-objective optimal control formulation for systems with input uncertainty. A parallel predictor model is constructed to relate the predictor error to the estimation error of the control effectiveness matrix. In this work, we develop an optimal control modification adaptive control approach that seeks to minimize a bi-objective linear quadratic cost function of both the tracking error norm and predictor error norm simultaneously. The resulting adaptive laws for the parametric uncertainty and control effectiveness uncertainty are dependent on both the tracking error and predictor error, while the adaptive laws for the feedback gain and command feedforward gain are only dependent on the tracking error. The optimal control modification term provides robustness to the adaptive laws naturally from the optimal control framework. Simulations demonstrate the effectiveness of the proposed adaptive control approach.

  10. SSD-Optimized Workload Placement with Adaptive Learning and Classification in HPC Environments

    SciTech Connect

    Wan, Lipeng; Lu, Zheng; Cao, Qing; Wang, Feiyi; Oral, H Sarp; Settlemyer, Bradley W

    2014-01-01

    In recent years, non-volatile memory devices such as SSD drives have emerged as a viable storage solution due to their increasing capacity and decreasing cost. Due to the unique capability and capacity requirements in large scale HPC (High Performance Computing) storage environment, a hybrid config- uration (SSD and HDD) may represent one of the most available and balanced solutions considering the cost and performance. Under this setting, effective data placement as well as movement with controlled overhead become a pressing challenge. In this paper, we propose an integrated object placement and movement framework and adaptive learning algorithms to address these issues. Specifically, we present a method that shuffle data objects across storage tiers to optimize the data access performance. The method also integrates an adaptive learning algorithm where real- time classification is employed to predict the popularity of data object accesses, so that they can be placed on, or migrate between SSD or HDD drives in the most efficient manner. We discuss preliminary results based on this approach using a simulator we developed to show that the proposed methods can dynamically adapt storage placements and access pattern as workloads evolve to achieve the best system level performance such as throughput.

  11. Integrated optimal allocation model for complex adaptive system of water resources management (I): Methodologies

    NASA Astrophysics Data System (ADS)

    Zhou, Yanlai; Guo, Shenglian; Xu, Chong-Yu; Liu, Dedi; Chen, Lu; Ye, Yushi

    2015-12-01

    Due to the adaption, dynamic and multi-objective characteristics of complex water resources system, it is a considerable challenge to manage water resources in an efficient, equitable and sustainable way. An integrated optimal allocation model is proposed for complex adaptive system of water resources management. The model consists of three modules: (1) an agent-based module for revealing evolution mechanism of complex adaptive system using agent-based, system dynamic and non-dominated sorting genetic algorithm II methods, (2) an optimal module for deriving decision set of water resources allocation using multi-objective genetic algorithm, and (3) a multi-objective evaluation module for evaluating the efficiency of the optimal module and selecting the optimal water resources allocation scheme using project pursuit method. This study has provided a theoretical framework for adaptive allocation, dynamic allocation and multi-objective optimization for a complex adaptive system of water resources management.

  12. Asymptotic Linearity of Optimal Control Modification Adaptive Law with Analytical Stability Margins

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.

    2010-01-01

    Optimal control modification has been developed to improve robustness to model-reference adaptive control. For systems with linear matched uncertainty, optimal control modification adaptive law can be shown by a singular perturbation argument to possess an outer solution that exhibits a linear asymptotic property. Analytical expressions of phase and time delay margins for the outer solution can be obtained. Using the gradient projection operator, a free design parameter of the adaptive law can be selected to satisfy stability margins.

  13. Performance evaluation of a sensorless adaptive optics multiphoton microscope.

    PubMed

    Skorsetz, Martin; Artal, Pablo; Bueno, Juan M

    2016-03-01

    A wavefront sensorless adaptive optics technique was combined with a custom-made multiphoton microscope to correct for specimen-induced aberrations. A liquid-crystal-on-silicon (LCoS) modulator was used to systematically generate Zernike modes during image recording. The performance of the instrument was evaluated in samples providing different nonlinear signals and the benefit of correcting higher order aberrations was always noticeable (in both contrast and resolution). The optimum aberration pattern was stable in time for the samples here involved. For a particular depth location within the sample, the wavefront to be precompensated was independent on the size of the imaged area (up to ∼ 360 × 360 μm(2)). The mode combination optimizing the recorded image depended on the Zernike correction control sequence; however, the final images hardly differed. At deeper locations, a noticeable dominance of spherical aberration was found. The influence of other aberration terms was also compared to the effect of the spherical aberration. PMID:26469361

  14. Optimizing the Adaptive Stochastic Resonance and Its Application in Fault Diagnosis

    NASA Astrophysics Data System (ADS)

    Liu, Xiaole; Yang, Jianhua; Liu, Houguang; Cheng, Gang; Chen, Xihui; Xu, Dan

    2015-10-01

    This paper presents an adaptive stochastic resonance method based on the improved artificial fish swarm algorithm. By this method, we can enhance the weak characteristic signal which is submerged in a heavy noise. We can also adaptively lead the stochastic resonance to be optimized to the greatest extent. The effectiveness of the proposed method is verified by both numerical simulation and lab experimental vibration signals including normal, a chipped tooth and a missing tooth of planetary gearboxes under the loaded condition. Both theoretical and experimental results show that this method can effectively extract weak characteristics in a heavy noise. In the experiment, each weak fault feature is extracted successfully from the fault planetary gear. When compared with the ensemble empirical mode decomposition (EEMD) method, the method proposed in this paper has been found to give remarkable performance.

  15. Adaptive Virtual Reality Training to Optimize Military Medical Skills Acquisition and Retention.

    PubMed

    Siu, Ka-Chun; Best, Bradley J; Kim, Jong Wook; Oleynikov, Dmitry; Ritter, Frank E

    2016-05-01

    The Department of Defense has pursued the integration of virtual reality simulation into medical training and applications to fulfill the need to train 100,000 military health care personnel annually. Medical personnel transitions, both when entering an operational area and returning to the civilian theater, are characterized by the need to rapidly reacquire skills that are essential but have decayed through disuse or infrequent use. Improved efficiency in reacquiring such skills is critical to avoid the likelihood of mistakes that may result in mortality and morbidity. We focus here on a study testing a theory of how the skills required for minimally invasive surgery for military surgeons are learned and retained. Our adaptive virtual reality surgical training system will incorporate an intelligent mechanism for tracking performance that will recognize skill deficiencies and generate an optimal adaptive training schedule. Our design is modeling skill acquisition based on a skill retention theory. The complexity of appropriate training tasks is adjusted according to the level of retention and/or surgical experience. Based on preliminary work, our system will improve the capability to interactively assess the level of skills learning and decay, optimizes skill relearning across levels of surgical experience, and positively impact skill maintenance. Our system could eventually reduce mortality and morbidity by providing trainees with the reexperience they need to help make a transition between operating theaters. This article reports some data that will support adaptive tutoring of minimally invasive surgery and similar surgical skills. PMID:27168575

  16. Adaptive sequentially space-filling metamodeling applied in optimal water quantity allocation at basin scale

    NASA Astrophysics Data System (ADS)

    Mousavi, S. Jamshid; Shourian, M.

    2010-03-01

    Global optimization models in many problems suffer from high computational costs due to the need for performing high-fidelity simulation models for objective function evaluations. Metamodeling is a useful approach to dealing with this problem in which a fast surrogate model replaces the detailed simulation model. However, training of the surrogate model needs enough input-output data which in case of absence of observed data, each of them must be obtained by running the simulation model and may still cause computational difficulties. In this paper a new metamodeling approach called adaptive sequentially space filling (ASSF) is presented by which the regions in the search space that need more training data are sequentially identified and the process of design of experiments is performed adaptively. Performance of the ASSF approach is tested against a benchmark function optimization problem and optimum basin-scale water allocation problems, in which the MODSIM river basin decision support system is approximated. Results show the ASSF model with fewer actual function evaluations is able to find comparable solutions to other metamodeling techniques using random sampling and evolution control strategies.

  17. Flight Test of an Adaptive Configuration Optimization System for Transport Aircraft

    NASA Technical Reports Server (NTRS)

    Gilyard, Glenn B.; Georgie, Jennifer; Barnicki, Joseph S.

    1999-01-01

    A NASA Dryden Flight Research Center program explores the practical application of real-time adaptive configuration optimization for enhanced transport performance on an L-1011 aircraft. This approach is based on calculation of incremental drag from forced-response, symmetric, outboard aileron maneuvers. In real-time operation, the symmetric outboard aileron deflection is directly optimized, and the horizontal stabilator and angle of attack are indirectly optimized. A flight experiment has been conducted from an onboard research engineering test station, and flight research results are presented herein. The optimization system has demonstrated the capability of determining the minimum drag configuration of the aircraft in real time. The drag-minimization algorithm is capable of identifying drag to approximately a one-drag-count level. Optimizing the symmetric outboard aileron position realizes a drag reduction of 2-3 drag counts (approximately 1 percent). Algorithm analysis of maneuvers indicate that two-sided raised-cosine maneuvers improve definition of the symmetric outboard aileron drag effect, thereby improving analysis results and consistency. Ramp maneuvers provide a more even distribution of data collection as a function of excitation deflection than raised-cosine maneuvers provide. A commercial operational system would require airdata calculations and normal output of current inertial navigation systems; engine pressure ratio measurements would be optional.

  18. Adaptive function allocation reduces performance costs of static automation

    NASA Technical Reports Server (NTRS)

    Parasuraman, Raja; Mouloua, Mustapha; Molloy, Robert; Hilburn, Brian

    1993-01-01

    Adaptive automation offers the option of flexible function allocation between the pilot and on-board computer systems. One of the important claims for the superiority of adaptive over static automation is that such systems do not suffer from some of the drawbacks associated with conventional function allocation. Several experiments designed to test this claim are reported in this article. The efficacy of adaptive function allocation was examined using a laboratory flight-simulation task involving multiple functions of tracking, fuel-management, and systems monitoring. The results show that monitoring inefficiency represents one of the performance costs of static automation. Adaptive function allocation can reduce the performance cost associated with long-term static automation.

  19. Monitoring the Performance of a Neuro-Adaptive Controller

    NASA Technical Reports Server (NTRS)

    Schumann, Johann; Gupta, Pramod

    2004-01-01

    Traditional control has proven to be ineffective to deal with catastrophic changes or slow degradation of complex, highly nonlinear systems like aircraft or spacecraft, robotics, or flexible manufacturing systems. Control systems which can adapt toward changes in the plant have been proposed as they offer many advantages (e.g., better performance, controllability of aircraft despite of a damaged wing). In the last few years, use of neural networks in adaptive controllers (neuro-adaptive control) has been studied actively. Neural networks of various architectures have been used successfully for online learning adaptive controllers. In such a typical control architecture, the neural network receives as an input the current deviation between desired and actual plant behavior and, by on-line training, tries to minimize this discrepancy (e.g.; by producing a control augmentation signal). Even though neuro-adaptive controllers offer many advantages, they have not been used in mission- or safety-critical applications, because performance and safety guarantees cannot b e provided at development time-a major prerequisite for safety certification (e.g., by the FAA or NASA). Verification and Validation (V&V) of an adaptive controller requires the development of new analysis techniques which can demonstrate that the control system behaves safely under all operating conditions. Because of the requirement to adapt toward unforeseen changes during operation, i.e., in real time, design-time V&V is not sufficient.

  20. Finite-horizon control-constrained nonlinear optimal control using single network adaptive critics.

    PubMed

    Heydari, Ali; Balakrishnan, Sivasubramanya N

    2013-01-01

    To synthesize fixed-final-time control-constrained optimal controllers for discrete-time nonlinear control-affine systems, a single neural network (NN)-based controller called the Finite-horizon Single Network Adaptive Critic is developed in this paper. Inputs to the NN are the current system states and the time-to-go, and the network outputs are the costates that are used to compute optimal feedback control. Control constraints are handled through a nonquadratic cost function. Convergence proofs of: 1) the reinforcement learning-based training method to the optimal solution; 2) the training error; and 3) the network weights are provided. The resulting controller is shown to solve the associated time-varying Hamilton-Jacobi-Bellman equation and provide the fixed-final-time optimal solution. Performance of the new synthesis technique is demonstrated through different examples including an attitude control problem wherein a rigid spacecraft performs a finite-time attitude maneuver subject to control bounds. The new formulation has great potential for implementation since it consists of only one NN with single set of weights and it provides comprehensive feedback solutions online, though it is trained offline.

  1. Finite-horizon control-constrained nonlinear optimal control using single network adaptive critics.

    PubMed

    Heydari, Ali; Balakrishnan, Sivasubramanya N

    2013-01-01

    To synthesize fixed-final-time control-constrained optimal controllers for discrete-time nonlinear control-affine systems, a single neural network (NN)-based controller called the Finite-horizon Single Network Adaptive Critic is developed in this paper. Inputs to the NN are the current system states and the time-to-go, and the network outputs are the costates that are used to compute optimal feedback control. Control constraints are handled through a nonquadratic cost function. Convergence proofs of: 1) the reinforcement learning-based training method to the optimal solution; 2) the training error; and 3) the network weights are provided. The resulting controller is shown to solve the associated time-varying Hamilton-Jacobi-Bellman equation and provide the fixed-final-time optimal solution. Performance of the new synthesis technique is demonstrated through different examples including an attitude control problem wherein a rigid spacecraft performs a finite-time attitude maneuver subject to control bounds. The new formulation has great potential for implementation since it consists of only one NN with single set of weights and it provides comprehensive feedback solutions online, though it is trained offline. PMID:24808214

  2. Enhancing Functional Performance using Sensorimotor Adaptability Training Programs

    NASA Technical Reports Server (NTRS)

    Bloomberg, J. J.; Mulavara, A. P.; Peters, B. T.; Brady, R.; Audas, C.; Ruttley, T. M.; Cohen, H. S.

    2009-01-01

    During the acute phase of adaptation to novel gravitational environments, sensorimotor disturbances have the potential to disrupt the ability of astronauts to perform functional tasks. The goal of this project is to develop a sensorimotor adaptability (SA) training program designed to facilitate recovery of functional capabilities when astronauts transition to different gravitational environments. The project conducted a series of studies that investigated the efficacy of treadmill training combined with a variety of sensory challenges designed to increase adaptability including alterations in visual flow, body loading, and support surface stability.

  3. Adaptive dynamic programming for finite-horizon optimal control of discrete-time nonlinear systems with ε-error bound.

    PubMed

    Wang, Fei-Yue; Jin, Ning; Liu, Derong; Wei, Qinglai

    2011-01-01

    In this paper, we study the finite-horizon optimal control problem for discrete-time nonlinear systems using the adaptive dynamic programming (ADP) approach. The idea is to use an iterative ADP algorithm to obtain the optimal control law which makes the performance index function close to the greatest lower bound of all performance indices within an ε-error bound. The optimal number of control steps can also be obtained by the proposed ADP algorithms. A convergence analysis of the proposed ADP algorithms in terms of performance index function and control policy is made. In order to facilitate the implementation of the iterative ADP algorithms, neural networks are used for approximating the performance index function, computing the optimal control policy, and modeling the nonlinear system. Finally, two simulation examples are employed to illustrate the applicability of the proposed method. PMID:20876014

  4. Adaptability in the workplace: development of a taxonomy of adaptive performance.

    PubMed

    Pulakos, E D; Arad, S; Donovan, M A; Plamondon, K E

    2000-08-01

    The purpose of this research was to develop a taxonomy of adaptive job performance and examine the implications of this taxonomy for understanding, predicting, and training adaptive behavior in work settings. Two studies were conducted to address this issue. In Study 1, over 1,000 critical incidents from 21 different jobs were content analyzed to identify an 8-dimension taxonomy of adaptive performance. Study 2 reports the development and administration of an instrument, the Job Adaptability Inventory, that was used to empirically examine the proposed taxonomy in 24 different jobs. Exploratory factor analyses using data from 1,619 respondents supported the proposed 8-dimension taxonomy from Study 1. Subsequent confirmatory factor analyses on the remainder of the sample (n = 1,715) indicated a good fit for the 8-factor model. Results and implications are discussed. PMID:10948805

  5. Research on web performance optimization principles and models

    NASA Astrophysics Data System (ADS)

    Wang, Xin

    2013-03-01

    The Internet high speed development, causes Web the optimized question to be getting more and more prominent, therefore the Web performance optimizes into inevitably. the first principle of Web Performance Optimization is to understand, to know that income will have to pay, and return is diminishing; Simultaneously the probability will decrease Web the performance, and will start from the highest level to optimize obtained biggest. Web Technical models to improve the performance are: sharing costs, high-speed caching, profiles, parallel processing, simplified treatment. Based on this study, given the crucial Web performance optimization recommendations, which improve the performance of Web usage, accelerate the efficient use of Internet has an important significance.

  6. Modeling-Error-Driven Performance-Seeking Direct Adaptive Control

    NASA Technical Reports Server (NTRS)

    Kulkarni, Nilesh V.; Kaneshige, John; Krishnakumar, Kalmanje; Burken, John

    2008-01-01

    This paper presents a stable discrete-time adaptive law that targets modeling errors in a direct adaptive control framework. The update law was developed in our previous work for the adaptive disturbance rejection application. The approach is based on the philosophy that without modeling errors, the original control design has been tuned to achieve the desired performance. The adaptive control should, therefore, work towards getting this performance even in the face of modeling uncertainties/errors. In this work, the baseline controller uses dynamic inversion with proportional-integral augmentation. Dynamic inversion is carried out using the assumed system model. On-line adaptation of this control law is achieved by providing a parameterized augmentation signal to the dynamic inversion block. The parameters of this augmentation signal are updated to achieve the nominal desired error dynamics. Contrary to the typical Lyapunov-based adaptive approaches that guarantee only stability, the current approach investigates conditions for stability as well as performance. A high-fidelity F-15 model is used to illustrate the overall approach.

  7. Optical Design and Optimization of Translational Reflective Adaptive Optics Ophthalmoscopes

    NASA Astrophysics Data System (ADS)

    Sulai, Yusufu N. B.

    The retina serves as the primary detector for the biological camera that is the eye. It is composed of numerous classes of neurons and support cells that work together to capture and process an image formed by the eye's optics, which is then transmitted to the brain. Loss of sight due to retinal or neuro-ophthalmic disease can prove devastating to one's quality of life, and the ability to examine the retina in vivo is invaluable in the early detection and monitoring of such diseases. Adaptive optics (AO) ophthalmoscopy is a promising diagnostic tool in early stages of development, still facing significant challenges before it can become a clinical tool. The work in this thesis is a collection of projects with the overarching goal of broadening the scope and applicability of this technology. We begin by providing an optical design approach for AO ophthalmoscopes that reduces the aberrations that degrade the performance of the AO correction. Next, we demonstrate how to further improve image resolution through the use of amplitude pupil apodization and non-common path aberration correction. This is followed by the development of a viewfinder which provides a larger field of view for retinal navigation. Finally, we conclude with the development of an innovative non-confocal light detection scheme which improves the non-invasive visualization of retinal vasculature and reveals the cone photoreceptor inner segments in healthy and diseased eyes.

  8. An adaptive differential evolution algorithm with novel mutation and crossover strategies for global numerical optimization.

    PubMed

    Islam, Sk Minhazul; Das, Swagatam; Ghosh, Saurav; Roy, Subhrajit; Suganthan, Ponnuthurai Nagaratnam

    2012-04-01

    Differential evolution (DE) is one of the most powerful stochastic real parameter optimizers of current interest. In this paper, we propose a new mutation strategy, a fitness-induced parent selection scheme for the binomial crossover of DE, and a simple but effective scheme of adapting two of its most important control parameters with an objective of achieving improved performance. The new mutation operator, which we call DE/current-to-gr_best/1, is a variant of the classical DE/current-to-best/1 scheme. It uses the best of a group (whose size is q% of the population size) of randomly selected solutions from current generation to perturb the parent (target) vector, unlike DE/current-to-best/1 that always picks the best vector of the entire population to perturb the target vector. In our modified framework of recombination, a biased parent selection scheme has been incorporated by letting each mutant undergo the usual binomial crossover with one of the p top-ranked individuals from the current population and not with the target vector with the same index as used in all variants of DE. A DE variant obtained by integrating the proposed mutation, crossover, and parameter adaptation strategies with the classical DE framework (developed in 1995) is compared with two classical and four state-of-the-art adaptive DE variants over 25 standard numerical benchmarks taken from the IEEE Congress on Evolutionary Computation 2005 competition and special session on real parameter optimization. Our comparative study indicates that the proposed schemes improve the performance of DE by a large magnitude such that it becomes capable of enjoying statistical superiority over the state-of-the-art DE variants for a wide variety of test problems. Finally, we experimentally demonstrate that, if one or more of our proposed strategies are integrated with existing powerful DE variants such as jDE and JADE, their performances can also be enhanced.

  9. Compensation of modal dispersion in multimode fiber systems using adaptive optics via convex optimization

    NASA Astrophysics Data System (ADS)

    Panicker, Rahul Alex

    Multimode fibers (MMF) are widely deployed in local-, campus-, and storage-area-networks. Achievable data rates and transmission distances are, however, limited by the phenomenon of modal dispersion. We propose a system to compensate for modal dispersion using adaptive optics. This leads to a 10- to 100-fold improvement in performance over current standards. We propose a provably optimal technique for minimizing inter-symbol interference (ISI) in MMF systems using adaptive optics via convex optimization. We use a spatial light modulator (SLM) to shape the spatial profile of light launched into an MMF. We derive an expression for the system impulse response in terms of the SLM reflectance and the field patterns of the MMF principal modes. Finding optimal SLM settings to minimize ISI, subject to physical constraints, is posed as an optimization problem. We observe that our problem can be cast as a second-order cone program, which is a convex optimization problem. Its global solution can, therefore, be found with minimal computational complexity. Simulations show that this technique opens up an eye pattern originally closed due to ISI. We then propose fast, low-complexity adaptive algorithms for optimizing the SLM settings. We show that some of these converge to the global optimum in the absence of noise. We also propose modified versions of these algorithms to improve resilience to noise and speed of convergence. Next, we experimentally compare the proposed adaptive algorithms in 50-mum graded-index (GRIN) MMFs using a liquid-crystal SLM. We show that continuous-phase sequential coordinate ascent (CPSCA) gives better bit-error-ratio performance than 2- or 4-phase sequential coordinate ascent, in concordance with simulations. We evaluate the bandwidth characteristics of CPSCA, and show that a single SLM is able to simultaneously compensate over up to 9 wavelength-division-multiplexed (WDM) 10-Gb/s channels, spaced by 50 GHz, over a total bandwidth of 450 GHz. We also

  10. Multi-objective parameter optimization of common land model using adaptive surrogate modeling

    NASA Astrophysics Data System (ADS)

    Gong, W.; Duan, Q.; Li, J.; Wang, C.; Di, Z.; Dai, Y.; Ye, A.; Miao, C.

    2015-05-01

    Parameter specification usually has significant influence on the performance of land surface models (LSMs). However, estimating the parameters properly is a challenging task due to the following reasons: (1) LSMs usually have too many adjustable parameters (20 to 100 or even more), leading to the curse of dimensionality in the parameter input space; (2) LSMs usually have many output variables involving water/energy/carbon cycles, so that calibrating LSMs is actually a multi-objective optimization problem; (3) Regional LSMs are expensive to run, while conventional multi-objective optimization methods need a large number of model runs (typically ~105-106). It makes parameter optimization computationally prohibitive. An uncertainty quantification framework was developed to meet the aforementioned challenges, which include the following steps: (1) using parameter screening to reduce the number of adjustable parameters, (2) using surrogate models to emulate the responses of dynamic models to the variation of adjustable parameters, (3) using an adaptive strategy to improve the efficiency of surrogate modeling-based optimization; (4) using a weighting function to transfer multi-objective optimization to single-objective optimization. In this study, we demonstrate the uncertainty quantification framework on a single column application of a LSM - the Common Land Model (CoLM), and evaluate the effectiveness and efficiency of the proposed framework. The result indicate that this framework can efficiently achieve optimal parameters in a more effective way. Moreover, this result implies the possibility of calibrating other large complex dynamic models, such as regional-scale LSMs, atmospheric models and climate models.

  11. The 15-meter antenna performance optimization using an interdisciplinary approach

    NASA Astrophysics Data System (ADS)

    Grantham, William L.; Schroeder, Lyle C.; Bailey, Marion C.; Campbell, Thomas G.

    1988-05-01

    A 15-meter diameter deployable antenna has been built and is being used as an experimental test system with which to develop interdisciplinary controls, structures, and electromagnetics technology for large space antennas. The program objective is to study interdisciplinary issues important in optimizing large space antenna performance for a variety of potential users. The 15-meter antenna utilizes a hoop column structural concept with a gold-plated molybdenum mesh reflector. One feature of the design is the use of adjustable control cables to improve the paraboloid reflector shape. Manual adjustment of the cords after initial deployment improved surface smoothness relative to the build accuracy from 0.140 in. RMS to 0.070 in. Preliminary structural dynamics tests and near-field electromagnetic tests were made. The antenna is now being modified for further testing. Modifications include addition of a precise motorized control cord adjustment system to make the reflector surface smoother and an adaptive feed for electronic compensation of reflector surface distortions. Although the previous test results show good agreement between calculated and measured values, additional work is needed to study modelling limits for each discipline, evaluate the potential of adaptive feed compensation, and study closed-loop control performance in a dynamic environment.

  12. Optimizing Hydronic System Performance in Residential Applications

    SciTech Connect

    Arena, L.; Faakye, O.

    2013-10-01

    Even though new homes constructed with hydronic heat comprise only 3% of the market (US Census Bureau 2009), of the 115 million existing homes in the United States, almost 14 million of those homes (11%) are heated with steam or hot water systems according to 2009 US Census data. Therefore, improvements in hydronic system performance could result in significant energy savings in the US. When operating properly, the combination of a gas-fired condensing boiler with baseboard convectors and an indirect water heater is a viable option for high-efficiency residential space heating in cold climates. Based on previous research efforts, however, it is apparent that these types of systems are typically not designed and installed to achieve maximum efficiency. Furthermore, guidance on proper design and commissioning for heating contractors and energy consultants is hard to find and is not comprehensive. Through modeling and monitoring, CARB sought to determine the optimal combination(s) of components - pumps, high efficiency heat sources, plumbing configurations and controls - that result in the highest overall efficiency for a hydronic system when baseboard convectors are used as the heat emitter. The impact of variable-speed pumps on energy use and system performance was also investigated along with the effects of various control strategies and the introduction of thermal mass.

  13. Burnout and job performance: the moderating role of selection, optimization, and compensation strategies.

    PubMed

    Demerouti, Evangelia; Bakker, Arnold B; Leiter, Michael

    2014-01-01

    The present study aims to explain why research thus far has found only low to moderate associations between burnout and performance. We argue that employees use adaptive strategies that help them to maintain their performance (i.e., task performance, adaptivity to change) at acceptable levels despite experiencing burnout (i.e., exhaustion, disengagement). We focus on the strategies included in the selective optimization with compensation model. Using a sample of 294 employees and their supervisors, we found that compensation is the most successful strategy in buffering the negative associations of disengagement with supervisor-rated task performance and both disengagement and exhaustion with supervisor-rated adaptivity to change. In contrast, selection exacerbates the negative relationship of exhaustion with supervisor-rated adaptivity to change. In total, 42% of the hypothesized interactions proved to be significant. Our study uncovers successful and unsuccessful strategies that people use to deal with their burnout symptoms in order to achieve satisfactory job performance.

  14. Burnout and job performance: the moderating role of selection, optimization, and compensation strategies.

    PubMed

    Demerouti, Evangelia; Bakker, Arnold B; Leiter, Michael

    2014-01-01

    The present study aims to explain why research thus far has found only low to moderate associations between burnout and performance. We argue that employees use adaptive strategies that help them to maintain their performance (i.e., task performance, adaptivity to change) at acceptable levels despite experiencing burnout (i.e., exhaustion, disengagement). We focus on the strategies included in the selective optimization with compensation model. Using a sample of 294 employees and their supervisors, we found that compensation is the most successful strategy in buffering the negative associations of disengagement with supervisor-rated task performance and both disengagement and exhaustion with supervisor-rated adaptivity to change. In contrast, selection exacerbates the negative relationship of exhaustion with supervisor-rated adaptivity to change. In total, 42% of the hypothesized interactions proved to be significant. Our study uncovers successful and unsuccessful strategies that people use to deal with their burnout symptoms in order to achieve satisfactory job performance. PMID:24447224

  15. Real-sky adaptive optics experiments on optimal control of tip-tilt modes

    NASA Astrophysics Data System (ADS)

    Doelman, Niek; Fraanje, Rufus; den Breeje, Remco

    2011-09-01

    In recent years various researchers have concentrated on control performance improvement for adaptive optics systems by using more sophisticated design methods. These approaches account for the inherent spatial and temporal correlations in the wavefront sensor data. Several control schemes have been proposed, of which the common essence is the minimization of a criterion function, yielding so-called 'optimal' or LQG control solutions. These are in some cases also referred to as 'predictive control'. Following the H2-optimal control design approach proposed by Hinnen [JOSA A Vol. 24, 2007], a real-sky experiment has been carried out on the McMath-Pierce solar telescope on Kitt Peak, Arizona. The purpose of the experiment was to validate the favourable results of optimal control, as obtained in simulations and laboratory experiments, on a real-time AO system on a telescope with real-sky turbulence. During the experimental week, it appeared that the deformable mirror did not have sufficient stroke to cope with the strong wavefront aberrations as measured by the AO wavefront sensor. Therefore, it was decided to focus on optimal control of the lower aberration modes tip and tilt only (using the separate TT-mirror). The control experiments demonstrate that for the particular AO system and seeing conditions (Nov 14, 2010) real-time optimal control can reduce the tip and tilt amplitudes by an additional factor of about 2 (RMS), compared to the common integrator control of the tip and tilt modes. For the low frequency band the improvement ranges from 10 to 20 dB. This performance agrees reasonably well with the predicted performance which is based on off-line analysis of the WFS data. The paper will discuss the experimental results in detail and also address important aspects like the non-stationarity of the wavefront aberrations, coupled versus decoupled tip-tilt control and measures to increase the robustness of the controller.

  16. Performance Benefits Associated with Context-Dependent Arm Pointing Adaptation

    NASA Technical Reports Server (NTRS)

    Seidler, R. D.; Bloomberg, J. J.; Stelmach, George E.

    2000-01-01

    Our previous work has demonstrated that head orientation can be used as a contextual cue to switch between mUltiple adaptive states. Subjects were assigned to one of three groups: the head orientation group tilted the head towards the right shoulder when drawing under a 0.5 gain of display and towards the left shoulder when drawing under a 1.5 gain of display; the target orientation group had the home & target positions rotated counterclockwise when drawing under the 0.5 gain and clockwise for the l.5 gain; the arm posture group changed the elbow angle of the arm they were not drawing with from full flexion to full extension with 0.5 and l.5 gain display changes. The head orientation cue was effectively associated with the multiple gains, in comparison to the control conditions. The purpose of the current investigation was to determine whether this context-dependent adaptation results in any savings in terms of performance measures such as movement duration and movement smoothness when subjects switch between multiple adaptive states. Subjects in the head adaptation group demonstrated reduced movement duration and increased movement smoothness (measured via normalized j erk scores) in comparison to the two control groups when switching between the 0.5 and 1.5 gain. of display. This work has demonstrated not only that subjects can acquire context-dependent adaptation, but also that it results in a significant savings of performance upon transfer between adaptive states

  17. GASIFICATION PLANT COST AND PERFORMANCE OPTIMIZATION

    SciTech Connect

    Samuel S. Tam

    2002-05-01

    The goal of this series of design and estimating efforts was to start from the as-built design and actual operating data from the DOE sponsored Wabash River Coal Gasification Repowering Project and to develop optimized designs for several coal and petroleum coke IGCC power and coproduction projects. First, the team developed a design for a grass-roots plant equivalent to the Wabash River Coal Gasification Repowering Project to provide a starting point and a detailed mid-year 2000 cost estimate based on the actual as-built plant design and subsequent modifications (Subtask 1.1). This unoptimized plant has a thermal efficiency of 38.3% (HHV) and a mid-year 2000 EPC cost of 1,681 $/kW. This design was enlarged and modified to become a Petroleum Coke IGCC Coproduction Plant (Subtask 1.2) that produces hydrogen, industrial grade steam, and fuel gas for an adjacent Gulf Coast petroleum refinery in addition to export power. A structured Value Improving Practices (VIP) approach was applied to reduce costs and improve performance. The base case (Subtask 1.3) Optimized Petroleum Coke IGCC Coproduction Plant increased the power output by 16% and reduced the plant cost by 23%. The study looked at several options for gasifier sparing to enhance availability. Subtask 1.9 produced a detailed report on this availability analyses study. The Subtask 1.3 Next Plant, which retains the preferred spare gasification train approach, only reduced the cost by about 21%, but it has the highest availability (94.6%) and produces power at 30 $/MW-hr (at a 12% ROI). Thus, such a coke-fueled IGCC coproduction plant could fill a near term niche market. In all cases, the emissions performance of these plants is superior to the Wabash River project. Subtasks 1.5A and B developed designs for single-train coal and coke-fueled power plants. This side-by-side comparison of these plants, which contain the Subtask 1.3 VIP enhancements, showed their similarity both in design and cost (1,318 $/kW for the

  18. GASIFICATION PLANT COST AND PERFORMANCE OPTIMIZATION

    SciTech Connect

    Sheldon Kramer

    2003-09-01

    This project developed optimized designs and cost estimates for several coal and petroleum coke IGCC coproduction projects that produced hydrogen, industrial grade steam, and hydrocarbon liquid fuel precursors in addition to power. The as-built design and actual operating data from the DOE sponsored Wabash River Coal Gasification Repowering Project was the starting point for this study that was performed by Bechtel, Global Energy and Nexant under Department of Energy contract DE-AC26-99FT40342. First, the team developed a design for a grass-roots plant equivalent to the Wabash River Coal Gasification Repowering Project to provide a starting point and a detailed mid-year 2000 cost estimate based on the actual as-built plant design and subsequent modifications (Subtask 1.1). This non-optimized plant has a thermal efficiency to power of 38.3% (HHV) and a mid-year 2000 EPC cost of 1,681 $/kW.1 This design was enlarged and modified to become a Petroleum Coke IGCC Coproduction Plant (Subtask 1.2) that produces hydrogen, industrial grade steam, and fuel gas for an adjacent Gulf Coast petroleum refinery in addition to export power. A structured Value Improving Practices (VIP) approach was applied to reduce costs and improve performance. The base case (Subtask 1.3) Optimized Petroleum Coke IGCC Coproduction Plant increased the power output by 16% and reduced the plant cost by 23%. The study looked at several options for gasifier sparing to enhance availability. Subtask 1.9 produced a detailed report on this availability analyses study. The Subtask 1.3 Next Plant, which retains the preferred spare gasification train approach, only reduced the cost by about 21%, but it has the highest availability (94.6%) and produces power at 30 $/MW-hr (at a 12% ROI). Thus, such a coke-fueled IGCC coproduction plant could fill a near term niche market. In all cases, the emissions performance of these plants is superior to the Wabash River project. Subtasks 1.5A and B developed designs for

  19. Adaptive environmental control for optimal results during plant microgravity experiments.

    PubMed

    Kostov, P; Ivanova, T; Dandolov, I; Sapunova, S; Ilieva, I

    2002-01-01

    The SVET Space Greenhouse (SG)--the first and the only automated plant growth facility onboard the MIR Space Station in the period 1990-2000 was developed on a Russian-Bulgarian Project in the 80s. The aim was to study plant growth under microgravity in order to include plants as a link of future Biological Life Support Systems for the long-term manned space missions. An American developed Gas Exchange Measurement System (GEMS) was added to the existing SVET SG equipment in 1995 to monitor more environmental and physiological parameters. A lot of long-duration plant flight experiments were carried out in the SVET+GEMS. They led to significant results in the Fundamental Gravitational Biology field--second-generation wheat seeds were produced in the conditions of microgravity. The new International Space Station (ISS) will provide a perfect opportunity for conducting full life cycle plant experiments in microgravity, including measurement of more vital plant parameters, during the next 15-20 years. Nowadays plant growth facilities for scientific research based on the SVET SG functional principles are developed for the ISS by different countries (Russia, USA, Italy, Japan, etc.). A new Concept for an advanced SVET-3 Space Greenhouse for the ISS, based on the Bulgarian experience and "know-how" is described. The absolute and differential plant chamber air parameters and some plant physiological parameters are measured and processed in real time. Using the transpiration and photosynthesis measurement data the Control Unit evaluates the plant status and performs adaptive environmental control in order to provide the most favorable conditions for plant growth at every stage of plant development in experiments. A conceptual block-diagram of the SVET-3 SG is presented.

  20. Adaptive Performance Seeking Control Using Fuzzy Model Reference Learning Control and Positive Gradient Control

    NASA Technical Reports Server (NTRS)

    Kopasakis, George

    1997-01-01

    Performance Seeking Control attempts to find the operating condition that will generate optimal performance and control the plant at that operating condition. In this paper a nonlinear multivariable Adaptive Performance Seeking Control (APSC) methodology will be developed and it will be demonstrated on a nonlinear system. The APSC is comprised of the Positive Gradient Control (PGC) and the Fuzzy Model Reference Learning Control (FMRLC). The PGC computes the positive gradients of the desired performance function with respect to the control inputs in order to drive the plant set points to the operating point that will produce optimal performance. The PGC approach will be derived in this paper. The feedback control of the plant is performed by the FMRLC. For the FMRLC, the conventional fuzzy model reference learning control methodology is utilized, with guidelines generated here for the effective tuning of the FMRLC controller.

  1. A Reflective Gaussian Coronagraph for Extreme Adaptive Optics: Laboratory Performance

    NASA Astrophysics Data System (ADS)

    Park, Ryeojin; Close, Laird M.; Siegler, Nick; Nielsen, Eric L.; Stalcup, Thomas

    2006-11-01

    We report laboratory results of a coronagraphic test bench to assess the intensity reduction differences between a ``Gaussian'' tapered focal plane coronagraphic mask and a classical hard-edged ``top hat'' function mask at extreme adaptive optics (ExAO) Strehl ratios of ~94%. However, unlike a traditional coronagraph design, we insert a reflective focal plane mask at 45° to the optical axis. We also use an intermediate secondary mask (mask 2) before a final image in order to block additional mask-edge-diffracted light. The test bench simulates the optical train of ground-based telescopes (in particular, the 8.1 m Gemini North Telescope). It includes one spider vane, different mask radii (r = 1.9λ/D, 3.7λ/D, and 7.4λ/D), and two types of reflective focal plane masks (hard-edged top-hat and Gaussian tapered profiles). In order to investigate the relative performance of these competing coronagraphic designs with regard to extrasolar planet detection sensitivity, we utilize the simulation of realistic extrasolar planet populations (Nielsen et al.). With an appropriate translation of our laboratory results to expected telescope performance, a Gaussian tapered mask radius of 3.7λ/D with an additional mask (mask 2) performs best (highest planet detection sensitivity). For a full survey with this optimal design, the simulation predicts that ~30% more planets would be detected than with a top-hat function mask of similar size with mask 2. Using the best design, the point contrast ratio between the stellar point-spread function (PSF) peak and the coronagraphic PSF at 10λ/D (0.4" in the H band if D = 8.1 m) is ~10 times higher than a classical Lyot top-hat coronagraph. Hence, we find that a Gaussian apodized mask with an additional blocking mask is superior (~10 times higher contrast) to the use of a classical Lyot coronagraph for ExAO-like Strehl ratios.

  2. Utilising pseudo-CT data for dose calculation and plan optimization in adaptive radiotherapy.

    PubMed

    Whelan, Brendan; Kumar, Shivani; Dowling, Jason; Begg, Jarrad; Lambert, Jonathan; Lim, Karen; Vinod, Shalini K; Greer, Peter B; Holloway, Lois

    2015-12-01

    To quantify the dose calculation error and resulting optimization uncertainty caused by performing inverse treatment planning on inaccurate electron density data (pseudo-CT) as needed for adaptive radiotherapy and Magnetic Resonance Imaging (MRI) based treatment planning. Planning Computer Tomography (CT) data from 10 cervix cancer patients was used to generate 4 pseudo-CT data sets. Each pseudo-CT was created based on an available method of assigning electron density to an anatomic image. An inversely modulated radiotherapy (IMRT) plan was developed on each planning CT. The dose calculation error caused by each pseudo-CT data set was quantified by comparing the dose calculated each pseudo-CT data set with that calculated on the original planning CT for the same IMRT plan. The optimization uncertainty introduced by the dose calculation error was quantified by re-optimizing the same optimization parameters on each pseudo-CT data set and comparing against the original planning CT. Dose differences were quantified by assessing the Equivalent Uniform Dose (EUD) for targets and relevant organs at risk. Across all pseudo-CT data sets and all organs, the absolute mean dose calculation error was 0.2 Gy, and was within 2 % of the prescription dose in 98.5 % of cases. Then absolute mean optimisation error was 0.3 Gy EUD, indicating that that inverse optimisation is impacted by the dose calculation error. However, the additional uncertainty introduced to plan optimisation is small compared the sources of variation which already exist. Use of inaccurate electron density data for inverse treatment planning results in a dose calculation error, which in turn introduces additional uncertainty into the plan optimization process. In this study, we showed that both of these effects are clinically acceptable for cervix cancer patients using four different pseudo-CT data sets. Dose calculation and inverse optimization on pseudo-CT is feasible for this patient cohort.

  3. Stability and Performance Metrics for Adaptive Flight Control

    NASA Technical Reports Server (NTRS)

    Stepanyan, Vahram; Krishnakumar, Kalmanje; Nguyen, Nhan; VanEykeren, Luarens

    2009-01-01

    This paper addresses the problem of verifying adaptive control techniques for enabling safe flight in the presence of adverse conditions. Since the adaptive systems are non-linear by design, the existing control verification metrics are not applicable to adaptive controllers. Moreover, these systems are in general highly uncertain. Hence, the system's characteristics cannot be evaluated by relying on the available dynamical models. This necessitates the development of control verification metrics based on the system's input-output information. For this point of view, a set of metrics is introduced that compares the uncertain aircraft's input-output behavior under the action of an adaptive controller to that of a closed-loop linear reference model to be followed by the aircraft. This reference model is constructed for each specific maneuver using the exact aerodynamic and mass properties of the aircraft to meet the stability and performance requirements commonly accepted in flight control. The proposed metrics are unified in the sense that they are model independent and not restricted to any specific adaptive control methods. As an example, we present simulation results for a wing damaged generic transport aircraft with several existing adaptive controllers.

  4. Skeletal adaptation to external loads optimizes mechanical properties: fact or fiction

    NASA Technical Reports Server (NTRS)

    Turner, R. T.

    2001-01-01

    The skeleton adapts to a changing mechanical environment but the widely held concept that bone cells are programmed to respond to local mechanical loads to produce an optimal mechanical structure is not consistent with the high frequency of bone fractures. Instead, the author suggests that other important functions of bone compete with mechanical adaptation to determine structure. As a consequence of competing demands, bone architecture never achieves an optimal mechanical structure. c2001 Lippincott Williams & Wilkins, Inc.

  5. Optimized mirror supports, active primary mirrors and adaptive secondaries for the Optical Very Large Array (OVLA)

    NASA Astrophysics Data System (ADS)

    Arnold, Luc

    1994-06-01

    This article first deals with general aspects of optimizing mirror supports. A wide variety of support topologies have been optimized by Nelson et al for unobscured entrance pupils. Optical forces and locations of point supports have been calculated here for annular pupils. Efficient topologies introducing a small amount of defocusing are also proposed for unobscured and annular pupils. Support efficiencies are given for each topology. Wavefront errors are estimated in the case of a defective cell, in order to specify tolerances on forces and geometries. The OVLA active optics is then discussed. The very thin, meniscus-shaped primary will be actively supported by 29 actuators and 3 fixed points. Actuator locations and forces have been calculated to minimize the mirror deflection under its own weight but also to allow a good control of astigmatism. We finally present a study of a concave adaptive secondary for the OVLA telescopes. As an initial result, we propose a defocus adaptive corrector with a variable thickness distribution. Conditions of use are defined, and performances are evaluated.

  6. Automatic carrier landing system for V/STOL aircraft using L1 adaptive and optimal control

    NASA Astrophysics Data System (ADS)

    Hariharapura Ramesh, Shashank

    This thesis presents a framework for developing automatic carrier landing systems for aircraft with vertical or short take-off and landing capability using two different control strategies---gain-scheduled linear optimal control, and L1 adaptive control. The carrier landing sequence of V/STOL aircraft involves large variations in dynamic pressure and aerodynamic coefficients arising because of the transition from aerodynamic-supported to jet-borne flight, descent to the touchdown altitude, and turns performed to align with the runway. Consequently, the dynamics of the aircraft exhibit a highly non-linear dynamical behavior with variations in flight conditions prior to touchdown. Therefore, the implication is the need for non-linear control techniques to achieve automatic landing. Gain-scheduling has been one of the most widely employed techniques for control of aircraft, which involves designing linear controllers for numerous trimmed flight conditions, and interpolating them to achieve a global non-linear control. Adaptive control technique, on the other hand, eliminates the need to schedule the controller parameters as they adapt to changing flight conditions.

  7. Optimization of an adaptive SPECT system with the scanning linear estimator

    NASA Astrophysics Data System (ADS)

    Ghanbari, Nasrin; Clarkson, Eric; Kupinski, Matthew A.; Li, Xin

    2015-08-01

    The adaptive single-photon emission computed tomography (SPECT) system studied here acquires an initial scout image to obtain preliminary information about the object. Then the configuration is adjusted by selecting the size of the pinhole and the magnification that optimize system performance on an ensemble of virtual objects generated to be consistent with the scout data. In this study the object is a lumpy background that contains a Gaussian signal with a variable width and amplitude. The virtual objects in the ensemble are imaged by all of the available configurations and the subsequent images are evaluated with the scanning linear estimator to obtain an estimate of the signal width and amplitude. The ensemble mean squared error (EMSE) on the virtual ensemble between the estimated and the true parameters serves as the performance figure of merit for selecting the optimum configuration. The results indicate that variability in the original object background, noise and signal parameters leads to a specific optimum configuration in each case. A statistical study carried out for a number of objects show that the adaptive system on average performs better than its nonadaptive counterpart.

  8. Impedance adaptation for optimal robot-environment interaction

    NASA Astrophysics Data System (ADS)

    Ge, Shuzhi Sam; Li, Yanan; Wang, Chen

    2014-02-01

    In this paper, impedance adaptation is investigated for robots interacting with unknown environments. Impedance control is employed for the physical interaction between robots and environments, subject to unknown and uncertain environments dynamics. The unknown environments are described as linear systems with unknown dynamics, based on which the desired impedance model is obtained. A cost function that measures the tracking error and interaction force is defined, and the critical impedance parameters are found to minimise it. Without requiring the information of the environments dynamics, the proposed impedance adaptation is feasible in a large number of applications where robots physically interact with unknown environments. The validity of the proposed method is verified through simulation studies.

  9. Optimal affine-invariant matching: performance characterization

    NASA Astrophysics Data System (ADS)

    Costa, Mauro S.; Haralick, Robert M.; Shapiro, Linda G.

    1992-04-01

    The geometric hashing scheme proposed by Lamdan and Wolfson can be very efficient in a model-based matching system, not only in terms of the computational complexity involved, but also in terms of the simplicity of the method. In a recent paper, we discussed errors that can occur with this method due to quantization, stability, symmetry, and noise problems. These errors make the original geometric hashing technique unsuitable for use on the factory floor. Beginning with an explicit noise model, which the original Lamdan and Wolfson technique lacks, we derived an optimal approach that overcomes these problems. We showed that the results obtained with the new algorithm are clearly better than the results from the original method. This paper addresses the performance characterization of the geometric hashing technique, more specifically the affine-invariant point matching, applied to the problem of recognizing and determining the pose of sheet metal parts. The experiments indicate that with a model having 10 to 14 points, with 2 points of the model undetected and 10 extraneous points detected, and with the model points perturbed by Gaussian noise of standard deviation 3 (0.58 of range), the average amount of computation required to obtain an answer is equivalent to trying 11 of the possible three-point bases. The misdetection rate, measured by the percentage of correct bases matches that fail to verify, is 0.9. The percentage of incorrect bases that successfully produced a match that did verify (false alarm rate) is 13. And, finally, 2 of the experiments failed to find a correct match and verify it. Results for experiments with real images are also presented.

  10. Performance of the Gemini Planet Imager's adaptive optics system.

    PubMed

    Poyneer, Lisa A; Palmer, David W; Macintosh, Bruce; Savransky, Dmitry; Sadakuni, Naru; Thomas, Sandrine; Véran, Jean-Pierre; Follette, Katherine B; Greenbaum, Alexandra Z; Ammons, S Mark; Bailey, Vanessa P; Bauman, Brian; Cardwell, Andrew; Dillon, Daren; Gavel, Donald; Hartung, Markus; Hibon, Pascale; Perrin, Marshall D; Rantakyrö, Fredrik T; Sivaramakrishnan, Anand; Wang, Jason J

    2016-01-10

    The Gemini Planet Imager's adaptive optics (AO) subsystem was designed specifically to facilitate high-contrast imaging. A definitive description of the system's algorithms and technologies as built is given. 564 AO telemetry measurements from the Gemini Planet Imager Exoplanet Survey campaign are analyzed. The modal gain optimizer tracks changes in atmospheric conditions. Science observations show that image quality can be improved with the use of both the spatially filtered wavefront sensor and linear-quadratic-Gaussian control of vibration. The error budget indicates that for all targets and atmospheric conditions AO bandwidth error is the largest term.

  11. Adaptive Sensor Optimization and Cognitive Image Processing Using Autonomous Optical Neuroprocessors

    SciTech Connect

    CAMERON, STEWART M.

    2001-10-01

    Measurement and signal intelligence demands has created new requirements for information management and interoperability as they affect surveillance and situational awareness. Integration of on-board autonomous learning and adaptive control structures within a remote sensing platform architecture would substantially improve the utility of intelligence collection by facilitating real-time optimization of measurement parameters for variable field conditions. A problem faced by conventional digital implementations of intelligent systems is the conflict between a distributed parallel structure on a sequential serial interface functionally degrading bandwidth and response time. In contrast, optically designed networks exhibit the massive parallelism and interconnect density needed to perform complex cognitive functions within a dynamic asynchronous environment. Recently, all-optical self-organizing neural networks exhibiting emergent collective behavior which mimic perception, recognition, association, and contemplative learning have been realized using photorefractive holography in combination with sensory systems for feature maps, threshold decomposition, image enhancement, and nonlinear matched filters. Such hybrid information processors depart from the classical computational paradigm based on analytic rules-based algorithms and instead utilize unsupervised generalization and perceptron-like exploratory or improvisational behaviors to evolve toward optimized solutions. These systems are robust to instrumental systematics or corrupting noise and can enrich knowledge structures by allowing competition between multiple hypotheses. This property enables them to rapidly adapt or self-compensate for dynamic or imprecise conditions which would be unstable using conventional linear control models. By incorporating an intelligent optical neuroprocessor in the back plane of an imaging sensor, a broad class of high-level cognitive image analysis problems including geometric

  12. Aerodynamic performance of membrane wings with adaptive compliance

    NASA Astrophysics Data System (ADS)

    Curet, Oscar M.; Carrere, Alexander; Pande, Arjun; Breuer, Kenneth S.

    2012-11-01

    Some flying animals use wing membranes with adaptive compliance to control their aerodynamic performance. In this work we characterize the mechanical properties and aerodynamic performance of a low aspect ratio membrane wing composed of a dielectric film supported on a rigid frame. We test the wing model in a wind tunnel. When a fixed voltage is applied across the wing membrane the camber increases, accompanied by a small increase in lift (less than 2%). However, lift is significantly increased when the wing is forced with an oscillating field at specific frequencies that correspond to the characteristic vortex shedding frequency. We present the results concerning the kinematics and aerodynamic performance of the adaptive wing membrane and the coupling between the vortex shedding and the forced modulation of elastic modulus.

  13. Real-Time Adaptive Least-Squares Drag Minimization for Performance Adaptive Aeroelastic Wing

    NASA Technical Reports Server (NTRS)

    Ferrier, Yvonne L.; Nguyen, Nhan T.; Ting, Eric

    2016-01-01

    This paper contains a simulation study of a real-time adaptive least-squares drag minimization algorithm for an aeroelastic model of a flexible wing aircraft. The aircraft model is based on the NASA Generic Transport Model (GTM). The wing structures incorporate a novel aerodynamic control surface known as the Variable Camber Continuous Trailing Edge Flap (VCCTEF). The drag minimization algorithm uses the Newton-Raphson method to find the optimal VCCTEF deflections for minimum drag in the context of an altitude-hold flight control mode at cruise conditions. The aerodynamic coefficient parameters used in this optimization method are identified in real-time using Recursive Least Squares (RLS). The results demonstrate the potential of the VCCTEF to improve aerodynamic efficiency for drag minimization for transport aircraft.

  14. Performance index and meta-optimization of a direct search optimization method

    NASA Astrophysics Data System (ADS)

    Krus, P.; Ölvander, J.

    2013-10-01

    Design optimization is becoming an increasingly important tool for design, often using simulation as part of the evaluation of the objective function. A measure of the efficiency of an optimization algorithm is of great importance when comparing methods. The main contribution of this article is the introduction of a singular performance criterion, the entropy rate index based on Shannon's information theory, taking both reliability and rate of convergence into account. It can also be used to characterize the difficulty of different optimization problems. Such a performance criterion can also be used for optimization of the optimization algorithms itself. In this article the Complex-RF optimization method is described and its performance evaluated and optimized using the established performance criterion. Finally, in order to be able to predict the resources needed for optimization an objective function temperament factor is defined that indicates the degree of difficulty of the objective function.

  15. Configuration optimization of laser guide stars and wavefront correctors for multi-conjugation adaptive optics

    NASA Astrophysics Data System (ADS)

    Xuan, Li; He, Bin; Hu, Li-Fa; Li, Da-Yu; Xu, Huan-Yu; Zhang, Xing-Yun; Wang, Shao-Xin; Wang, Yu-Kun; Yang, Cheng-Liang; Cao, Zhao-Liang; Mu, Quan-Quan; Lu, Xing-Hai

    2016-09-01

    Multi-conjugation adaptive optics (MCAOs) have been investigated and used in the large aperture optical telescopes for high-resolution imaging with large field of view (FOV). The atmospheric tomographic phase reconstruction and projection of three-dimensional turbulence volume onto wavefront correctors, such as deformable mirrors (DMs) or liquid crystal wavefront correctors (LCWCs), is a very important step in the data processing of an MCAO’s controller. In this paper, a method according to the wavefront reconstruction performance of MCAO is presented to evaluate the optimized configuration of multi laser guide stars (LGSs) and the reasonable conjugation heights of LCWCs. Analytical formulations are derived for the different configurations and are used to generate optimized parameters for MCAO. Several examples are given to demonstrate our LGSs configuration optimization method. Compared with traditional methods, our method has minimum wavefront tomographic error, which will be helpful to get higher imaging resolution at large FOV in MCAO. Project supported by the National Natural Science Foundation of China (Grant Nos. 11174274, 11174279, 61205021, 11204299, 61475152, and 61405194) and the State Key Laboratory of Applied Optics, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences.

  16. Configuration optimization of laser guide stars and wavefront correctors for multi-conjugation adaptive optics

    NASA Astrophysics Data System (ADS)

    Xuan, Li; He, Bin; Hu, Li-Fa; Li, Da-Yu; Xu, Huan-Yu; Zhang, Xing-Yun; Wang, Shao-Xin; Wang, Yu-Kun; Yang, Cheng-Liang; Cao, Zhao-Liang; Mu, Quan-Quan; Lu, Xing-Hai

    2016-09-01

    Multi-conjugation adaptive optics (MCAOs) have been investigated and used in the large aperture optical telescopes for high-resolution imaging with large field of view (FOV). The atmospheric tomographic phase reconstruction and projection of three-dimensional turbulence volume onto wavefront correctors, such as deformable mirrors (DMs) or liquid crystal wavefront correctors (LCWCs), is a very important step in the data processing of an MCAO’s controller. In this paper, a method according to the wavefront reconstruction performance of MCAO is presented to evaluate the optimized configuration of multi laser guide stars (LGSs) and the reasonable conjugation heights of LCWCs. Analytical formulations are derived for the different configurations and are used to generate optimized parameters for MCAO. Several examples are given to demonstrate our LGSs configuration optimization method. Compared with traditional methods, our method has minimum wavefront tomographic error, which will be helpful to get higher imaging resolution at large FOV in MCAO. Project supported by the National Natural Science Foundation of China (Grant Nos. 11174274, 11174279, 61205021, 11204299, 61475152, and 61405194) and the State Key Laboratory of Applied Optics, Changchun Institute of Optics, Fine Mechanics and Physics, Chinese Academy of Sciences.

  17. Adaptation of NASA technology for the optimization of orthopedic knee implants

    NASA Technical Reports Server (NTRS)

    Saravanos, D. A.; Mraz, P. J.; Hopkins, D. A.

    1991-01-01

    The NASA technology originally developed for the optimization of composite structures (engine blades) is adapted and applied to the optimization of orthopedic knee implants. A method is developed enabling the tailoring of the implant for optimal interaction with the environment of the tibia. The shape of the implant components are optimized, such that the stresses in the bone are favorably controlled to minimize bone degradation and prevent failures. A pilot tailoring system is developed and the feasibility of the concept is elevated. The optimization system is expected to provide the means for improving knee prosthesis and individual implant tailoring for each patient.

  18. Multilevel Optimization Framework for Hierarchical Stiffened Shells Accelerated by Adaptive Equivalent Strategy

    NASA Astrophysics Data System (ADS)

    Wang, Bo; Tian, Kuo; Zhao, Haixin; Hao, Peng; Zhu, Tianyu; Zhang, Ke; Ma, Yunlong

    2016-09-01

    In order to improve the post-buckling optimization efficiency of hierarchical stiffened shells, a multilevel optimization framework accelerated by adaptive equivalent strategy is presented in this paper. Firstly, the Numerical-based Smeared Stiffener Method (NSSM) for hierarchical stiffened shells is derived by means of the numerical implementation of asymptotic homogenization (NIAH) method. Based on the NSSM, a reasonable adaptive equivalent strategy for hierarchical stiffened shells is developed from the concept of hierarchy reduction. Its core idea is to self-adaptively decide which hierarchy of the structure should be equivalent according to the critical buckling mode rapidly predicted by NSSM. Compared with the detailed model, the high prediction accuracy and efficiency of the proposed model is highlighted. On the basis of this adaptive equivalent model, a multilevel optimization framework is then established by decomposing the complex entire optimization process into major-stiffener-level and minor-stiffener-level sub-optimizations, during which Fixed Point Iteration (FPI) is employed to accelerate convergence. Finally, the illustrative examples of the multilevel framework is carried out to demonstrate its efficiency and effectiveness to search for the global optimum result by contrast with the single-level optimization method. Remarkably, the high efficiency and flexibility of the adaptive equivalent strategy is indicated by compared with the single equivalent strategy.

  19. Carrier phase estimation for optically coherent QPSK based on Wiener-optimal and adaptive Multi-Symbol Delay Detection (MSDD).

    PubMed

    Sigron, Netta; Tselniker, Igor; Nazarathy, Moshe

    2012-01-30

    The MSDD carrier phase estimation technique is derived here for optically coherent QPSK transmission, introducing the principle of operation while providing intuitive insight in terms of a multi-symbol extension of naïve delay-detection. We derive here for the first time Wiener-optimized and LMS-adapted versions of MSDD, introduce simplified hardware realizations, and evaluate complexity and numerical performance tradeoffs of this highly robust and low-complexity carrier phase recovery method. A multiplier-free carrier phase recovery version of the MSDD provides nearly optimal performance for linewidths up to ~0.5 MHz, whereas for wider linewidths, the Wiener or LMS versions provide optimal performance at about 9 taps, using 1 or 2 complex multipliers per tap.

  20. Optimality and adaptation of phenotypically switching cells in fluctuating environments

    NASA Astrophysics Data System (ADS)

    Belete, Merzu Kebede; Balázsi, Gábor

    2015-12-01

    Stochastic switching between alternative phenotypic states is a common cellular survival strategy during unforeseen environmental fluctuations. Cells can switch between different subpopulations that proliferate at different rates in different environments. Optimal population growth is typically assumed to occur when phenotypic switching rates match environmental switching rates. However, it is not well understood how this optimum behaves as a function of the growth rates of phenotypically different cells. In this study, we use mathematical and computational models to test how the actual parameters associated with optimal population growth differ from those assumed to be optimal. We find that the predicted optimum is practically always valid if the environmental durations are long. However, the regime of validity narrows as environmental durations shorten, especially if subpopulation growth rate differences differ from each other (are asymmetric) in two environments. Furthermore, we study the fate of mutants with switching rates previously predicted to be optimal. We find that mutants which match their phenotypic switching rates with the environmental ones can only sweep the population if the assumed optimum is valid, but not otherwise.

  1. Optimality and adaptation of phenotypically switching cells in fluctuating environments.

    PubMed

    Belete, Merzu Kebede; Balázsi, Gábor

    2015-12-01

    Stochastic switching between alternative phenotypic states is a common cellular survival strategy during unforeseen environmental fluctuations. Cells can switch between different subpopulations that proliferate at different rates in different environments. Optimal population growth is typically assumed to occur when phenotypic switching rates match environmental switching rates. However, it is not well understood how this optimum behaves as a function of the growth rates of phenotypically different cells. In this study, we use mathematical and computational models to test how the actual parameters associated with optimal population growth differ from those assumed to be optimal. We find that the predicted optimum is practically always valid if the environmental durations are long. However, the regime of validity narrows as environmental durations shorten, especially if subpopulation growth rate differences differ from each other (are asymmetric) in two environments. Furthermore, we study the fate of mutants with switching rates previously predicted to be optimal. We find that mutants which match their phenotypic switching rates with the environmental ones can only sweep the population if the assumed optimum is valid, but not otherwise.

  2. Generalized Monge-Kantorovich optimization for grid generation and adaptation in LP

    SciTech Connect

    Delzanno, G L; Finn, J M

    2009-01-01

    The Monge-Kantorovich grid generation and adaptation scheme of is generalized from a variational principle based on L{sub 2} to a variational principle based on L{sub p}. A generalized Monge-Ampere (MA) equation is derived and its properties are discussed. Results for p > 1 are obtained and compared in terms of the quality of the resulting grid. We conclude that for the grid generation application, the formulation based on L{sub p} for p close to unity leads to serious problems associated with the boundary. Results for 1.5 {approx}< p {approx}< 2.5 are quite good, but there is a fairly narrow range around p = 2 where the results are close to optimal with respect to grid distortion. Furthermore, the Newton-Krylov methods used to solve the generalized MA equation perform best for p = 2.

  3. Gasification Plant Cost and Performance Optimization

    SciTech Connect

    Samuel Tam; Alan Nizamoff; Sheldon Kramer; Scott Olson; Francis Lau; Mike Roberts; David Stopek; Robert Zabransky; Jeffrey Hoffmann; Erik Shuster; Nelson Zhan

    2005-05-01

    As part of an ongoing effort of the U.S. Department of Energy (DOE) to investigate the feasibility of gasification on a broader level, Nexant, Inc. was contracted to perform a comprehensive study to provide a set of gasification alternatives for consideration by the DOE. Nexant completed the first two tasks (Tasks 1 and 2) of the ''Gasification Plant Cost and Performance Optimization Study'' for the DOE's National Energy Technology Laboratory (NETL) in 2003. These tasks evaluated the use of the E-GAS{trademark} gasification technology (now owned by ConocoPhillips) for the production of power either alone or with polygeneration of industrial grade steam, fuel gas, hydrocarbon liquids, or hydrogen. NETL expanded this effort in Task 3 to evaluate Gas Technology Institute's (GTI) fluidized bed U-GAS{reg_sign} gasifier. The Task 3 study had three main objectives. The first was to examine the application of the gasifier at an industrial application in upstate New York using a Southeastern Ohio coal. The second was to investigate the GTI gasifier in a stand-alone lignite-fueled IGCC power plant application, sited in North Dakota. The final goal was to train NETL personnel in the methods of process design and systems analysis. These objectives were divided into five subtasks. Subtasks 3.2 through 3.4 covered the technical analyses for the different design cases. Subtask 3.1 covered management activities, and Subtask 3.5 covered reporting. Conceptual designs were developed for several coal gasification facilities based on the fluidized bed U-GAS{reg_sign} gasifier. Subtask 3.2 developed two base case designs for industrial combined heat and power facilities using Southeastern Ohio coal that will be located at an upstate New York location. One base case design used an air-blown gasifier, and the other used an oxygen-blown gasifier in order to evaluate their relative economics. Subtask 3.3 developed an advanced design for an air-blown gasification combined heat and power

  4. High-Performance Reactive Fluid Flow Simulations Using Adaptive Mesh Refinement on Thousands of Processors

    NASA Astrophysics Data System (ADS)

    Calder, A. C.; Curtis, B. C.; Dursi, L. J.; Fryxell, B.; Henry, G.; MacNeice, P.; Olson, K.; Ricker, P.; Rosner, R.; Timmes, F. X.; Tufo, H. M.; Truran, J. W.; Zingale, M.

    We present simulations and performance results of nuclear burning fronts in supernovae on the largest domain and at the finest spatial resolution studied to date. These simulations were performed on the Intel ASCI-Red machine at Sandia National Laboratories using FLASH, a code developed at the Center for Astrophysical Thermonuclear Flashes at the University of Chicago. FLASH is a modular, adaptive mesh, parallel simulation code capable of handling compressible, reactive fluid flows in astrophysical environments. FLASH is written primarily in Fortran 90, uses the Message-Passing Interface library for inter-processor communication and portability, and employs the PARAMESH package to manage a block-structured adaptive mesh that places blocks only where the resolution is required and tracks rapidly changing flow features, such as detonation fronts, with ease. We describe the key algorithms and their implementation as well as the optimizations required to achieve sustained performance of 238 GLOPS on 6420 processors of ASCI-Red in 64-bit arithmetic.

  5. Adaptive prefetching on POWER7: Improving performance and power consumption

    SciTech Connect

    Jimenez, Victor; Cazorla, Francisco; Gioiosa, Roberto; Buyuktosunoglu, Alper; Bose, Pradip; O'Connel, Francis P.; Mealey, Bruce G.

    2014-10-03

    Hardware data prefetch engines are integral parts of many general purpose server-class microprocessors in the field today. Some prefetch engines allow users to change some of their parameters. But, the prefetcher is usually enabled in a default configuration during system bring-up, and dynamic reconfiguration of the prefetch engine is not an autonomic feature of current machines. Conceptually, however, it is easy to infer that commonly used prefetch algorithms—when applied in a fixed mode—will not help performance in many cases. In fact, they may actually degrade performance due to useless bus bandwidth consumption and cache pollution, which in turn, will also waste power. We present an adaptive prefetch scheme that dynamically modifies the prefetch settings in order to adapt to workloads

  6. Optimal joint power-rate adaptation for error resilient video coding

    NASA Astrophysics Data System (ADS)

    Lin, Yuan; Gürses, Eren; Kim, Anna N.; Perkis, Andrew

    2008-01-01

    In recent years digital imaging devices become an integral part of our daily lives due to the advancements in imaging, storage and wireless communication technologies. Power-Rate-Distortion efficiency is the key factor common to all resource constrained portable devices. In addition, especially in real-time wireless multimedia applications, channel adaptive and error resilient source coding techniques should be considered in conjunction with the P-R-D efficiency, since most of the time Automatic Repeat-reQuest (ARQ) and Forward Error Correction (FEC) are either not feasible or costly in terms of bandwidth efficiency delay. In this work, we focus on the scenarios of real-time video communication for resource constrained devices over bandwidth limited and lossy channels, and propose an analytic Power-channel Error-Rate-Distortion (P-E-R-D) model. In particular, probabilities of macroblocks coding modes are intelligently controlled through an optimization process according to their distinct rate-distortion-complexity performance for a given channel error rate. The framework provides theoretical guidelines for the joint analysis of error resilient source coding and resource allocation. Experimental results show that our optimal framework provides consistent rate-distortion performance gain under different power constraints.

  7. Value Iteration Adaptive Dynamic Programming for Optimal Control of Discrete-Time Nonlinear Systems.

    PubMed

    Wei, Qinglai; Liu, Derong; Lin, Hanquan

    2016-03-01

    In this paper, a value iteration adaptive dynamic programming (ADP) algorithm is developed to solve infinite horizon undiscounted optimal control problems for discrete-time nonlinear systems. The present value iteration ADP algorithm permits an arbitrary positive semi-definite function to initialize the algorithm. A novel convergence analysis is developed to guarantee that the iterative value function converges to the optimal performance index function. Initialized by different initial functions, it is proven that the iterative value function will be monotonically nonincreasing, monotonically nondecreasing, or nonmonotonic and will converge to the optimum. In this paper, for the first time, the admissibility properties of the iterative control laws are developed for value iteration algorithms. It is emphasized that new termination criteria are established to guarantee the effectiveness of the iterative control laws. Neural networks are used to approximate the iterative value function and compute the iterative control law, respectively, for facilitating the implementation of the iterative ADP algorithm. Finally, two simulation examples are given to illustrate the performance of the present method.

  8. Sensorimotor Adaptability Training Improves Motor and Dual-Task Performance

    NASA Technical Reports Server (NTRS)

    Bloomberg, J.J.; Peters, B.T.; Mulavara, A.P.; Brady, R.; Batson, C.; Cohen, H.S.

    2009-01-01

    The overall objective of our project is to develop a sensorimotor adaptability (SA) training program designed to facilitate recovery of functional capabilities when astronauts transition to different gravitational environments. The goal of our current study was to determine if SA training using variation in visual flow and support surface motion produces improved performance in a novel sensory environment and demonstrate the retention characteristics of SA training.

  9. Spatial grid services for adaptive spatial query optimization

    NASA Astrophysics Data System (ADS)

    Gao, Bingbo; Xie, Chuanjie; Sheng, Wentao

    2008-10-01

    Spatial information sharing and integration has now become an important issue of Geographical Information Science (GIS). Web Service technologies provide a easy and standard way to share spatial resources over network, and grid technologies which aim at sharing resources such as data, storage, and computational powers can help the sharing go deeper. However, the dynamic characteristic of grid brings complexity to spatial query optimization which is more stressed in GIS domain because spatial operations are both CPU intensive and data intensive. To address this problem, a new grid framework is employed to provide standard spatial services which can also manage and report their state information to the coordinator which is responsible for distributed spatial query optimization.

  10. Prediction-based manufacturing center self-adaptive demand side energy optimization in cyber physical systems

    NASA Astrophysics Data System (ADS)

    Sun, Xinyao; Wang, Xue; Wu, Jiangwei; Liu, Youda

    2014-05-01

    Cyber physical systems(CPS) recently emerge as a new technology which can provide promising approaches to demand side management(DSM), an important capability in industrial power systems. Meanwhile, the manufacturing center is a typical industrial power subsystem with dozens of high energy consumption devices which have complex physical dynamics. DSM, integrated with CPS, is an effective methodology for solving energy optimization problems in manufacturing center. This paper presents a prediction-based manufacturing center self-adaptive energy optimization method for demand side management in cyber physical systems. To gain prior knowledge of DSM operating results, a sparse Bayesian learning based componential forecasting method is introduced to predict 24-hour electric load levels for specific industrial areas in China. From this data, a pricing strategy is designed based on short-term load forecasting results. To minimize total energy costs while guaranteeing manufacturing center service quality, an adaptive demand side energy optimization algorithm is presented. The proposed scheme is tested in a machining center energy optimization experiment. An AMI sensing system is then used to measure the demand side energy consumption of the manufacturing center. Based on the data collected from the sensing system, the load prediction-based energy optimization scheme is implemented. By employing both the PSO and the CPSO method, the problem of DSM in the manufacturing center is solved. The results of the experiment show the self-adaptive CPSO energy optimization method enhances optimization by 5% compared with the traditional PSO optimization method.

  11. Optimization-based wavefront sensorless adaptive optics for multiphoton microscopy.

    PubMed

    Antonello, Jacopo; van Werkhoven, Tim; Verhaegen, Michel; Truong, Hoa H; Keller, Christoph U; Gerritsen, Hans C

    2014-06-01

    Optical aberrations have detrimental effects in multiphoton microscopy. These effects can be curtailed by implementing model-based wavefront sensorless adaptive optics, which only requires the addition of a wavefront shaping device, such as a deformable mirror (DM) to an existing microscope. The aberration correction is achieved by maximizing a suitable image quality metric. We implement a model-based aberration correction algorithm in a second-harmonic microscope. The tip, tilt, and defocus aberrations are removed from the basis functions used for the control of the DM, as these aberrations induce distortions in the acquired images. We compute the parameters of a quadratic polynomial that is used to model the image quality metric directly from experimental input-output measurements. Finally, we apply the aberration correction by maximizing the image quality metric using the least-squares estimate of the unknown aberration.

  12. Translation and adaptation of functional auditory performance indicators (FAPI)

    PubMed Central

    FERREIRA, Karina; MORET, Adriane Lima Mortari; BEVILACQUA, Maria Cecilia; JACOB, Regina de Souza Tangerino

    2011-01-01

    Work with deaf children has gained new attention since the expectation and goal of therapy has expanded to language development and subsequent language learning. Many clinical tests were developed for evaluation of speech sound perception in young children in response to the need for accurate assessment of hearing skills that developed from the use of individual hearing aids or cochlear implants. These tests also allow the evaluation of the rehabilitation program. However, few of these tests are available in Portuguese. Evaluation with the Functional Auditory Performance Indicators (FAPI) generates a child's functional auditory skills profile, which lists auditory skills in an integrated and hierarchical order. It has seven hierarchical categories, including sound awareness, meaningful sound, auditory feedback, sound source localizing, auditory discrimination, short-term auditory memory, and linguistic auditory processing. FAPI evaluation allows the therapist to map the child's hearing profile performance, determine the target for increasing the hearing abilities, and develop an effective therapeutic plan. Objective Since the FAPI is an American test, the inventory was adapted for application in the Brazilian population. Material and Methods The translation was done following the steps of translation and back translation, and reproducibility was evaluated. Four translated versions (two originals and two back-translated) were compared, and revisions were done to ensure language adaptation and grammatical and idiomatic equivalence. Results The inventory was duly translated and adapted. Conclusion Further studies about the application of the translated FAPI are necessary to make the test practicable in Brazilian clinical use. PMID:22230992

  13. Verifiable Adaptive Control with Analytical Stability Margins by Optimal Control Modification

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T.

    2010-01-01

    This paper presents a verifiable model-reference adaptive control method based on an optimal control formulation for linear uncertain systems. A predictor model is formulated to enable a parameter estimation of the system parametric uncertainty. The adaptation is based on both the tracking error and predictor error. Using a singular perturbation argument, it can be shown that the closed-loop system tends to a linear time invariant model asymptotically under an assumption of fast adaptation. A stability margin analysis is given to estimate a lower bound of the time delay margin using a matrix measure method. Using this analytical method, the free design parameter n of the optimal control modification adaptive law can be determined to meet a specification of stability margin for verification purposes.

  14. Issues in the design and optimization of adaptive optics and laser guide stars for the Keck Telescopes

    SciTech Connect

    Max, C.E.; Gavel, D.T.; Olivier, S.S.

    1994-03-01

    We discuss issues in optimizing the design of adaptive optics and laser guide star systems for the Keck Telescope. The initial tip-tilt system will use Keck`s chopping secondary mirror. We describe design constraints, choice of detector, and expected performance of this tip-tilt system as well as its sky coverage. The adaptive optics system is being optimized for wavelengths of I-2.2{mu}m. We are studying adaptive optics concepts which use a wavefront sensor with varying numbers of subapertures, so as to respond to changing turbulence conditions. The goal is to be able to ``gang together`` groups of deformable mirror subapertures under software control, when conditions call for larger subapertures. We present performance predictions as a function of sky coverage and the number of deformable mirror degrees of freedom. We analyze the predicted brightness several candidate laser guide star systems, as a function of laser power and pulse format. These predictions are used to examine the resulting Strehl as a function of observing wavelength and laser type. We discuss laser waste heat and thermal management issues, and conclude with an overview of instruments under design to take advantage of the Keck adaptive optics system.

  15. A mathematical basis for the design and design optimization of adaptive trusses in precision control

    NASA Technical Reports Server (NTRS)

    Das, S. K.; Utku, S.; Chen, G.-S.; Wada, B. K.

    1991-01-01

    A mathematical basis for the optimal design of adaptive trusses to be used in supporting precision equipment is provided. The general theory of adaptive structures is introduced, and the global optimization problem of placing a limited number, q, of actuators, so as to maximally achieve precision control and provide prestress, is stated. Two serialized optimization problems, namely, optimal actuator placement for prestress and optimal actuator placement for precision control, are addressed. In the case of prestressing, the computation of a 'desired' prestress is discussed, the interaction between actuators and redundants in conveying the prestress is shown in its mathematical form, and a methodology for arriving at the optimal placement of actuators and additional redundants is discussed. With regard to precision control, an optimal placement scheme (for q actuators) for maximum 'authority' over the precision points is suggested. The results of the two serialized optimization problems are combined to give a suboptimal solution to the global optimization problem. A method for improving this suboptimal actuator placement scheme by iteration is presented.

  16. An optimal adaptive design to address local regulations in global clinical trials.

    PubMed

    Luo, Xiaolong; Shih, Weichung Joe; Ouyang, S Peter; Delap, Robert J

    2010-01-01

    After multi-regional clinical trials (MRCTs) have demonstrated overall significant effects, evaluation for a region-specific effect is often important. Recent guidance from regulatory authorities regarding evaluation for possible country-specific effects has led to research on statistical designs that incorporate such evaluations in MRCTs. These statistical designs are intended to use the MRCTs to address the requirements for global registration of a medicinal product. Adding a regional requirement could change the probability for declaring positive effect for the region when there is indeed no treatment difference as well as when there is in fact a true difference within the region. In this paper, we first quantify those probability structures based on the guidance issued by the Ministry of Health, Labour and Welfare (MHLW) of Japan. An adaptive design is proposed to consider those probabilities and to optimize the efficiency for regional objectives. This two-stage approach incorporates comprehensive global objectives into an integrated study design and may mitigate the need for a separate local bridging study. A procedure is used to optimize region-specific enrollment based on an objective function. The overall sample size requirement is assessed. We will use simulation analyses to illustrate the performance of the proposed study design. PMID:20872620

  17. Optimization of orthogonal adaptive waveform design in presence of compound Gaussian clutter for MIMO radar.

    PubMed

    Reddy, B Roja; Uttarakumari, M

    2015-01-01

    In this paper, an adaptive algorithm is proposed to develop an orthogonally optimized waveforms with good correlation properties that are suitable for the detection of target in the presence of strong clutter. The joint optimization both at the transmitter and receiver is adapted based on the secondary data and clutter to maximize signal to interference noise ratio (SINR) with target and clutter knowledge. The result shows good correlation properties and better SINR and signal to clutter ratio (SCR) compared to the existing iterative algorithm. The proposed algorithm also shows improved detection even for lower SCR when implemented with GLRT.

  18. Performance Trend of Different Algorithms for Structural Design Optimization

    NASA Technical Reports Server (NTRS)

    Patnaik, Surya N.; Coroneos, Rula M.; Guptill, James D.; Hopkins, Dale A.

    1996-01-01

    Nonlinear programming algorithms play an important role in structural design optimization. Fortunately, several algorithms with computer codes are available. At NASA Lewis Research Center, a project was initiated to assess performance of different optimizers through the development of a computer code CometBoards. This paper summarizes the conclusions of that research. CometBoards was employed to solve sets of small, medium and large structural problems, using different optimizers on a Cray-YMP8E/8128 computer. The reliability and efficiency of the optimizers were determined from the performance of these problems. For small problems, the performance of most of the optimizers could be considered adequate. For large problems however, three optimizers (two sequential quadratic programming routines, DNCONG of IMSL and SQP of IDESIGN, along with the sequential unconstrained minimizations technique SUMT) outperformed others. At optimum, most optimizers captured an identical number of active displacement and frequency constraints but the number of active stress constraints differed among the optimizers. This discrepancy can be attributed to singularity conditions in the optimization and the alleviation of this discrepancy can improve the efficiency of optimizers.

  19. Optimal adaptive two-stage designs for early phase II clinical trials.

    PubMed

    Shan, Guogen; Wilding, Gregory E; Hutson, Alan D; Gerstenberger, Shawn

    2016-04-15

    Simon's optimal two-stage design has been widely used in early phase clinical trials for Oncology and AIDS studies with binary endpoints. With this approach, the second-stage sample size is fixed when the trial passes the first stage with sufficient activity. Adaptive designs, such as those due to Banerjee and Tsiatis (2006) and Englert and Kieser (2013), are flexible in the sense that the second-stage sample size depends on the response from the first stage, and these designs are often seen to reduce the expected sample size under the null hypothesis as compared with Simon's approach. An unappealing trait of the existing designs is that they are not associated with a second-stage sample size, which is a non-increasing function of the first-stage response rate. In this paper, an efficient intelligent process, the branch-and-bound algorithm, is used in extensively searching for the optimal adaptive design with the smallest expected sample size under the null, while the type I and II error rates are maintained and the aforementioned monotonicity characteristic is respected. The proposed optimal design is observed to have smaller expected sample sizes compared to Simon's optimal design, and the maximum total sample size of the proposed adaptive design is very close to that from Simon's method. The proposed optimal adaptive two-stage design is recommended for use in practice to improve the flexibility and efficiency of early phase therapeutic development. PMID:26526165

  20. Fuzzy physical programming for Space Manoeuvre Vehicles trajectory optimization based on hp-adaptive pseudospectral method

    NASA Astrophysics Data System (ADS)

    Chai, Runqi; Savvaris, Al; Tsourdos, Antonios

    2016-06-01

    In this paper, a fuzzy physical programming (FPP) method has been introduced for solving multi-objective Space Manoeuvre Vehicles (SMV) skip trajectory optimization problem based on hp-adaptive pseudospectral methods. The dynamic model of SMV is elaborated and then, by employing hp-adaptive pseudospectral methods, the problem has been transformed to nonlinear programming (NLP) problem. According to the mission requirements, the solutions were calculated for each single-objective scenario. To get a compromised solution for each target, the fuzzy physical programming (FPP) model is proposed. The preference function is established with considering the fuzzy factor of the system such that a proper compromised trajectory can be acquired. In addition, the NSGA-II is tested to obtain the Pareto-optimal solution set and verify the Pareto optimality of the FPP solution. Simulation results indicate that the proposed method is effective and feasible in terms of dealing with the multi-objective skip trajectory optimization for the SMV.

  1. Adaptive Interventions May Optimize Outcomes in Drug Courts: A Pilot Study

    PubMed Central

    Marlowe, Douglas B.; Festinger, David S.; Arabia, Patricia L.; Dugosh, Karen L.; Benasutti, Kathleen M.; Croft, Jason R.

    2009-01-01

    Adaptive interventions apply a priori decision rules for adjusting treatment services in response to participants’ clinical presentation or performance in treatment. This pilot study (N = 30) experimentally examined an adaptive intervention in a misdemeanor drug court. The participants were primarily charged with possession of marijuana (73%) or possession of drug paraphernalia (23%). Results revealed that participants in the adaptive condition had relatively higher graduation rates and required significantly less time to graduate from the program and achieve a final resolution of the case. It took an average of nearly 4 fewer months for participants in the adaptive intervention to resolve their cases as compared to drug court as-usual. Participants in the adaptive condition also reported equivalent satisfaction with the program and therapeutic alliances with their counselors. These data suggest that adaptive interventions may enhance the efficiency and effectiveness of drug courts, and justify examining adaptive interventions in large-scale drug court studies. PMID:19785978

  2. Program optimizations: The interplay between power, performance, and energy

    DOE PAGES

    Leon, Edgar A.; Karlin, Ian; Grant, Ryan E.; Dosanjh, Matthew

    2016-05-16

    Practical considerations for future supercomputer designs will impose limits on both instantaneous power consumption and total energy consumption. Working within these constraints while providing the maximum possible performance, application developers will need to optimize their code for speed alongside power and energy concerns. This paper analyzes the effectiveness of several code optimizations including loop fusion, data structure transformations, and global allocations. A per component measurement and analysis of different architectures is performed, enabling the examination of code optimizations on different compute subsystems. Using an explicit hydrodynamics proxy application from the U.S. Department of Energy, LULESH, we show how code optimizationsmore » impact different computational phases of the simulation. This provides insight for simulation developers into the best optimizations to use during particular simulation compute phases when optimizing code for future supercomputing platforms. Here, we examine and contrast both x86 and Blue Gene architectures with respect to these optimizations.« less

  3. LIFT: analysis of performance in a laser assisted adaptive optics

    NASA Astrophysics Data System (ADS)

    Plantet, Cedric; Meimon, Serge; Conan, Jean-Marc; Neichel, Benoît; Fusco, Thierry

    2014-08-01

    Laser assisted adaptive optics systems rely on Laser Guide Star (LGS) Wave-Front Sensors (WFS) for high order aberration measurements, and rely on Natural Guide Stars (NGS) WFS to complement the measurements on low orders such as tip-tilt and focus. The sky-coverage of the whole system is therefore related to the limiting magnitude of the NGS WFS. We have recently proposed LIFT, a novel phase retrieval WFS technique, that allows a 1 magnitude gain over the usually used 2×2 Shack-Hartmann WFS. After an in-lab validation, LIFT's concept has been demonstrated on sky in open loop on GeMS (the Gemini Multiconjugate adaptive optics System at Gemini South). To complete its validation, LIFT now needs to be operated in closed loop in a laser assisted adaptive optics system. The present work gives a detailed analysis of LIFT's behavior in presence of high order residuals and how to limit aliasing effects on the tip/tilt/focus estimation. Also, we study the high orders' impact on noise propagation. For this purpose, we simulate a multiconjugate adaptive optics loop representative of a GeMS-like 5 LGS configuration. The residual high orders are derived from a Fourier based simulation. We demonstrate that LIFT keeps a high performance gain over the Shack-Hartmann 2×2 whatever the turbulence conditions. Finally, we show the first simulation of a closed loop with LIFT estimating turbulent tip/tilt and focus residuals that could be induced by sodium layer's altitude variations.

  4. Optimized tuner selection for engine performance estimation

    NASA Technical Reports Server (NTRS)

    Simon, Donald L. (Inventor); Garg, Sanjay (Inventor)

    2013-01-01

    A methodology for minimizing the error in on-line Kalman filter-based aircraft engine performance estimation applications is presented. This technique specifically addresses the underdetermined estimation problem, where there are more unknown parameters than available sensor measurements. A systematic approach is applied to produce a model tuning parameter vector of appropriate dimension to enable estimation by a Kalman filter, while minimizing the estimation error in the parameters of interest. Tuning parameter selection is performed using a multi-variable iterative search routine which seeks to minimize the theoretical mean-squared estimation error. Theoretical Kalman filter estimation error bias and variance values are derived at steady-state operating conditions, and the tuner selection routine is applied to minimize these values. The new methodology yields an improvement in on-line engine performance estimation accuracy.

  5. Business owners' optimism and business performance after a natural disaster.

    PubMed

    Bronson, James W; Faircloth, James B; Valentine, Sean R

    2006-12-01

    Previous work indicates that individuals' optimism is related to superior performance in adverse situations. This study examined correlations after flooding for measures of business recovery but found only weak support (very small common variance) for business owners' optimism scores and sales recovery. Using traditional measures of recovery, in this study was little empirical evidence that optimism would be of value in identifying businesses at risk after a natural disaster.

  6. An adaptive metamodel-based global optimization algorithm for black-box type problems

    NASA Astrophysics Data System (ADS)

    Jie, Haoxiang; Wu, Yizhong; Ding, Jianwan

    2015-11-01

    In this article, an adaptive metamodel-based global optimization (AMGO) algorithm is presented to solve unconstrained black-box problems. In the AMGO algorithm, a type of hybrid model composed of kriging and augmented radial basis function (RBF) is used as the surrogate model. The weight factors of hybrid model are adaptively selected in the optimization process. To balance the local and global search, a sub-optimization problem is constructed during each iteration to determine the new iterative points. As numerical experiments, six standard two-dimensional test functions are selected to show the distributions of iterative points. The AMGO algorithm is also tested on seven well-known benchmark optimization problems and contrasted with three representative metamodel-based optimization methods: efficient global optimization (EGO), GutmannRBF and hybrid and adaptive metamodel (HAM). The test results demonstrate the efficiency and robustness of the proposed method. The AMGO algorithm is finally applied to the structural design of the import and export chamber of a cycloid gear pump, achieving satisfactory results.

  7. Design, Performance and Optimization for Multimodal Radar Operation

    PubMed Central

    Bhat, Surendra S.; Narayanan, Ram M.; Rangaswamy, Muralidhar

    2012-01-01

    This paper describes the underlying methodology behind an adaptive multimodal radar sensor that is capable of progressively optimizing its range resolution depending upon the target scattering features. It consists of a test-bed that enables the generation of linear frequency modulated waveforms of various bandwidths. This paper discusses a theoretical approach to optimizing the bandwidth used by the multimodal radar. It also discusses the various experimental results obtained from measurement. The resolution predicted from theory agrees quite well with that obtained from experiments for different target arrangements.

  8. Optimizing Hydronic System Performance in Residential Applications

    SciTech Connect

    2013-10-01

    Even though new homes constructed with hydronic heat comprise only 3% of the market (US Census Bureau 2009), of the 115 million existing homes in the United States, almost 14 million of those homes (11%) are heated with steam or hot water systems according to 2009 US Census data. Therefore, improvements in hydronic system performance could result in significant energy savings in the US.

  9. Using perioperative analytics to optimize OR performance.

    PubMed

    Rempfer, Doug

    2015-06-01

    In the past, the data hospitals gleaned from operating rooms (ORs) tended to be static and lacking in actionable information. Hospitals can improve OR performance by applying OR analytics, such as evaluation of turnover times and expenses, which provide useful intelligence. Having the information is important, but success depends on aligning staff behavior to effectively achieve improvement strategies identified using the analytics.

  10. Adaptive luminance contrast for enhancing reading performance and visual comfort on smartphone displays

    NASA Astrophysics Data System (ADS)

    Na, Nooree; Suk, Hyeon-Jeong

    2014-11-01

    This study developed a model for setting the adaptive luminance contrast between text and background for enhancing reading performance and visual comfort on smartphone displays. The study was carried out in two experiments. In Experiment I, a user test was conducted to identify the optimal luminance contrast with regard to subjects' reading performance, measured by lines of text reading and visual comfort, assessed by self-report after the reading. Based on the empirical results of the test, an ideal adaptive model which decreases the luminance contrast gradually with passage of time was developed. In Experiment II, a validation test involving reading performance, visual comfort, and physiological stress measured by a brainwave analysis using an electroencephalogram confirmed that the proposed adaptive luminance contrast is adequate for prolonged text reading on smartphone displays. The developed model enhances both reading performance and visual comfort as well as reduces the energy consumption of a smartphone; hence, it is expected that this study will be applied to diverse kinds of visual display terminals.

  11. Leaf Area Adjustment As an Optimal Drought-Adaptation Strategy

    NASA Astrophysics Data System (ADS)

    Manzoni, S.; Beyer, F.; Thompson, S. E.; Vico, G.; Weih, M.

    2014-12-01

    Leaf phenology plays a major role in land-atmosphere mass and energy exchanges. Much work has focused on phenological responses to light and temperature, but less to leaf area changes during dry periods. Because the duration of droughts is expected to increase under future climates in seasonally-dry as well as mesic environments, it is crucial to (i) predict drought-related phenological changes and (ii) to develop physiologically-sound models of leaf area dynamics during dry periods. Several optimization criteria have been proposed to model leaf area adjustment as soil moisture decreases. Some theories are based on the plant carbon (C) balance, hypothesizing that leaf area will decline when instantaneous net photosynthetic rates become negative (equivalent to maximization of cumulative C gain). Other theories draw on hydraulic principles, suggesting that leaf area should adjust to either maintain a constant leaf water potential (isohydric behavior) or to avoid leaf water potentials with negative impacts on photosynthesis (i.e., minimization of water stress). Evergreen leaf phenology is considered as a control case. Merging these theories into a unified framework, we quantify the effect of phenological strategy and climate forcing on the net C gain over the entire growing season. By accounting for the C costs of leaf flushing and the gains stemming from leaf photosynthesis, this metric assesses the effectiveness of different phenological strategies, under different climatic scenarios. Evergreen species are favored only when the dry period is relatively short, as they can exploit most of the growing season, and only incur leaf maintenance costs during the short dry period. In contrast, deciduous species that lower maintenance costs by losing leaves are advantaged under drier climates. Moreover, among drought-deciduous species, isohydric behavior leads to lowest C gains. Losing leaves gradually so as to maintain a net C uptake equal to zero during the driest period in

  12. Intelligent adaptive nonlinear flight control for a high performance aircraft with neural networks.

    PubMed

    Savran, Aydogan; Tasaltin, Ramazan; Becerikli, Yasar

    2006-04-01

    This paper describes the development of a neural network (NN) based adaptive flight control system for a high performance aircraft. The main contribution of this work is that the proposed control system is able to compensate the system uncertainties, adapt to the changes in flight conditions, and accommodate the system failures. The underlying study can be considered in two phases. The objective of the first phase is to model the dynamic behavior of a nonlinear F-16 model using NNs. Therefore a NN-based adaptive identification model is developed for three angular rates of the aircraft. An on-line training procedure is developed to adapt the changes in the system dynamics and improve the identification accuracy. In this procedure, a first-in first-out stack is used to store a certain history of the input-output data. The training is performed over the whole data in the stack at every stage. To speed up the convergence rate and enhance the accuracy for achieving the on-line learning, the Levenberg-Marquardt optimization method with a trust region approach is adapted to train the NNs. The objective of the second phase is to develop intelligent flight controllers. A NN-based adaptive PID control scheme that is composed of an emulator NN, an estimator NN, and a discrete time PID controller is developed. The emulator NN is used to calculate the system Jacobian required to train the estimator NN. The estimator NN, which is trained on-line by propagating the output error through the emulator, is used to adjust the PID gains. The NN-based adaptive PID control system is applied to control three angular rates of the nonlinear F-16 model. The body-axis pitch, roll, and yaw rates are fed back via the PID controllers to the elevator, aileron, and rudder actuators, respectively. The resulting control system has learning, adaptation, and fault-tolerant abilities. It avoids the storage and interpolation requirements for the too many controller parameters of a typical flight control

  13. Intelligent adaptive nonlinear flight control for a high performance aircraft with neural networks.

    PubMed

    Savran, Aydogan; Tasaltin, Ramazan; Becerikli, Yasar

    2006-04-01

    This paper describes the development of a neural network (NN) based adaptive flight control system for a high performance aircraft. The main contribution of this work is that the proposed control system is able to compensate the system uncertainties, adapt to the changes in flight conditions, and accommodate the system failures. The underlying study can be considered in two phases. The objective of the first phase is to model the dynamic behavior of a nonlinear F-16 model using NNs. Therefore a NN-based adaptive identification model is developed for three angular rates of the aircraft. An on-line training procedure is developed to adapt the changes in the system dynamics and improve the identification accuracy. In this procedure, a first-in first-out stack is used to store a certain history of the input-output data. The training is performed over the whole data in the stack at every stage. To speed up the convergence rate and enhance the accuracy for achieving the on-line learning, the Levenberg-Marquardt optimization method with a trust region approach is adapted to train the NNs. The objective of the second phase is to develop intelligent flight controllers. A NN-based adaptive PID control scheme that is composed of an emulator NN, an estimator NN, and a discrete time PID controller is developed. The emulator NN is used to calculate the system Jacobian required to train the estimator NN. The estimator NN, which is trained on-line by propagating the output error through the emulator, is used to adjust the PID gains. The NN-based adaptive PID control system is applied to control three angular rates of the nonlinear F-16 model. The body-axis pitch, roll, and yaw rates are fed back via the PID controllers to the elevator, aileron, and rudder actuators, respectively. The resulting control system has learning, adaptation, and fault-tolerant abilities. It avoids the storage and interpolation requirements for the too many controller parameters of a typical flight control

  14. System reliability, performance and trust in adaptable automation.

    PubMed

    Chavaillaz, Alain; Wastell, David; Sauer, Jürgen

    2016-01-01

    The present study examined the effects of reduced system reliability on operator performance and automation management in an adaptable automation environment. 39 operators were randomly assigned to one of three experimental groups: low (60%), medium (80%), and high (100%) reliability of automation support. The support system provided five incremental levels of automation which operators could freely select according to their needs. After 3 h of training on a simulated process control task (AutoCAMS) in which the automation worked infallibly, operator performance and automation management were measured during a 2.5-h testing session. Trust and workload were also assessed through questionnaires. Results showed that although reduced system reliability resulted in lower levels of trust towards automation, there were no corresponding differences in the operators' reliance on automation. While operators showed overall a noteworthy ability to cope with automation failure, there were, however, decrements in diagnostic speed and prospective memory with lower reliability.

  15. Organ sample generator for expected treatment dose construction and adaptive inverse planning optimization

    SciTech Connect

    Nie Xiaobo; Liang Jian; Yan Di

    2012-12-15

    Purpose: To create an organ sample generator (OSG) for expected treatment dose construction and adaptive inverse planning optimization. The OSG generates random samples of organs of interest from a distribution obeying the patient specific organ variation probability density function (PDF) during the course of adaptive radiotherapy. Methods: Principle component analysis (PCA) and a time-varying least-squares regression (LSR) method were used on patient specific geometric variations of organs of interest manifested on multiple daily volumetric images obtained during the treatment course. The construction of the OSG includes the determination of eigenvectors of the organ variation using PCA, and the determination of the corresponding coefficients using time-varying LSR. The coefficients can be either random variables or random functions of the elapsed treatment days depending on the characteristics of organ variation as a stationary or a nonstationary random process. The LSR method with time-varying weighting parameters was applied to the precollected daily volumetric images to determine the function form of the coefficients. Eleven h and n cancer patients with 30 daily cone beam CT images each were included in the evaluation of the OSG. The evaluation was performed using a total of 18 organs of interest, including 15 organs at risk and 3 targets. Results: Geometric variations of organs of interest during h and n cancer radiotherapy can be represented using the first 3 {approx} 4 eigenvectors. These eigenvectors were variable during treatment, and need to be updated using new daily images obtained during the treatment course. The OSG generates random samples of organs of interest from the estimated organ variation PDF of the individual. The accuracy of the estimated PDF can be improved recursively using extra daily image feedback during the treatment course. The average deviations in the estimation of the mean and standard deviation of the organ variation PDF for h

  16. Discrete-time entropy formulation of optimal and adaptive control problems

    NASA Technical Reports Server (NTRS)

    Tsai, Yweting A.; Casiello, Francisco A.; Loparo, Kenneth A.

    1992-01-01

    The discrete-time version of the entropy formulation of optimal control of problems developed by G. N. Saridis (1988) is discussed. Given a dynamical system, the uncertainty in the selection of the control is characterized by the probability distribution (density) function which maximizes the total entropy. The equivalence between the optimal control problem and the optimal entropy problem is established, and the total entropy is decomposed into a term associated with the certainty equivalent control law, the entropy of estimation, and the so-called equivocation of the active transmission of information from the controller to the estimator. This provides a useful framework for studying the certainty equivalent and adaptive control laws.

  17. Optimal control of gene expression for fast proteome adaptation to environmental change.

    PubMed

    Pavlov, Michael Y; Ehrenberg, Måns

    2013-12-17

    Bacterial populations growing in a changing world must adjust their proteome composition in response to alterations in the environment. Rapid proteome responses to growth medium changes are expected to increase the average growth rate and fitness value of these populations. Little is known about the dynamics of proteome change, e.g., whether bacteria use optimal strategies of gene expression for rapid proteome adjustments and if there are lower bounds to the time of proteome adaptation in response to growth medium changes. To begin answering these types of questions, we modeled growing bacteria as stoichiometrically coupled networks of metabolic pathways. These are balanced during steady-state growth in a constant environment but are initially unbalanced after rapid medium shifts due to a shortage of enzymes required at higher concentrations in the new environment. We identified an optimal strategy for rapid proteome adjustment in the absence of protein degradation and found a lower bound to the time of proteome adaptation after medium shifts. This minimal time is determined by the ratio between the Kullback-Leibler distance from the pre- to the postshift proteome and the postshift steady-state growth rate. The dynamics of optimally controlled proteome adaptation has a simple analytical solution. We used detailed numerical modeling to demonstrate that realistic bacterial control systems can emulate this optimal strategy for rapid proteome adaptation. Our results may provide a conceptual link between the physiology and population genetics of growing bacteria. PMID:24297927

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

    NASA Astrophysics Data System (ADS)

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

    2016-01-01

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

  19. Blocking reduction of Landsat Thematic Mapper JPEG browse images using optimal PSNR estimated spectra adaptive postfiltering

    NASA Technical Reports Server (NTRS)

    Linares, Irving; Mersereau, Russell M.; Smith, Mark J. T.

    1994-01-01

    Two representative sample images of Band 4 of the Landsat Thematic Mapper are compressed with the JPEG algorithm at 8:1, 16:1 and 24:1 Compression Ratios for experimental browsing purposes. We then apply the Optimal PSNR Estimated Spectra Adaptive Postfiltering (ESAP) algorithm to reduce the DCT blocking distortion. ESAP reduces the blocking distortion while preserving most of the image's edge information by adaptively postfiltering the decoded image using the block's spectral information already obtainable from each block's DCT coefficients. The algorithm iteratively applied a one dimensional log-sigmoid weighting function to the separable interpolated local block estimated spectra of the decoded image until it converges to the optimal PSNR with respect to the original using a 2-D steepest ascent search. Convergence is obtained in a few iterations for integer parameters. The optimal logsig parameters are transmitted to the decoder as a negligible byte of overhead data. A unique maxima is guaranteed due to the 2-D asymptotic exponential overshoot shape of the surface generated by the algorithm. ESAP is based on a DFT analysis of the DCT basis functions. It is implemented with pixel-by-pixel spatially adaptive separable FIR postfilters. PSNR objective improvements between 0.4 to 0.8 dB are shown together with their corresponding optimal PSNR adaptive postfiltered images.

  20. A self adaptive hybrid enhanced artificial bee colony algorithm for continuous optimization problems.

    PubMed

    Shan, Hai; Yasuda, Toshiyuki; Ohkura, Kazuhiro

    2015-06-01

    The artificial bee colony (ABC) algorithm is one of popular swarm intelligence algorithms that inspired by the foraging behavior of honeybee colonies. To improve the convergence ability, search speed of finding the best solution and control the balance between exploration and exploitation using this approach, we propose a self adaptive hybrid enhanced ABC algorithm in this paper. To evaluate the performance of standard ABC, best-so-far ABC (BsfABC), incremental ABC (IABC), and the proposed ABC algorithms, we implemented numerical optimization problems based on the IEEE Congress on Evolutionary Computation (CEC) 2014 test suite. Our experimental results show the comparative performance of standard ABC, BsfABC, IABC, and the proposed ABC algorithms. According to the results, we conclude that the proposed ABC algorithm is competitive to those state-of-the-art modified ABC algorithms such as BsfABC and IABC algorithms based on the benchmark problems defined by CEC 2014 test suite with dimension sizes of 10, 30, and 50, respectively.

  1. A self adaptive hybrid enhanced artificial bee colony algorithm for continuous optimization problems.

    PubMed

    Shan, Hai; Yasuda, Toshiyuki; Ohkura, Kazuhiro

    2015-06-01

    The artificial bee colony (ABC) algorithm is one of popular swarm intelligence algorithms that inspired by the foraging behavior of honeybee colonies. To improve the convergence ability, search speed of finding the best solution and control the balance between exploration and exploitation using this approach, we propose a self adaptive hybrid enhanced ABC algorithm in this paper. To evaluate the performance of standard ABC, best-so-far ABC (BsfABC), incremental ABC (IABC), and the proposed ABC algorithms, we implemented numerical optimization problems based on the IEEE Congress on Evolutionary Computation (CEC) 2014 test suite. Our experimental results show the comparative performance of standard ABC, BsfABC, IABC, and the proposed ABC algorithms. According to the results, we conclude that the proposed ABC algorithm is competitive to those state-of-the-art modified ABC algorithms such as BsfABC and IABC algorithms based on the benchmark problems defined by CEC 2014 test suite with dimension sizes of 10, 30, and 50, respectively. PMID:25982071

  2. An optimized adaptive optics experimental setup for in vivo retinal imaging

    NASA Astrophysics Data System (ADS)

    Balderas-Mata, S. E.; Valdivieso González, L. G.; Ramírez Zavaleta, G.; López Olazagasti, E.; Tepichin Rodriguez, E.

    2012-10-01

    The use of Adaptive Optics (AO) in ophthalmologic instruments to image human retinas has been probed to improve the imaging lateral resolution, by correcting both static and dynamic aberrations inherent in human eyes. Typically, the configuration of the AO arm uses an infrared beam from a superluminescent diode (SLD), which is focused on the retina, acting as a point source. The back reflected light emerges through the eye optical system bringing with it the aberrations of the cornea. The aberrated wavefront is measured with a Shack - Hartmann wavefront sensor (SHWFS). However, the aberrations in the optical imaging system can reduced the performance of the wave front correction. The aim of this work is to present an optimized first stage AO experimental setup for in vivo retinal imaging. In our proposal, the imaging optical system has been designed in order to reduce spherical aberrations due to the lenses. The ANSI Standard is followed assuring the safety power levels. The performance of the system will be compared with a commercial aberrometer. This system will be used as the AO arm of a flood-illuminated fundus camera system for retinal imaging. We present preliminary experimental results showing the enhancement.

  3. Design of a Performance-Adaptive PID Control System Based on Modeling Performance Assessment

    NASA Astrophysics Data System (ADS)

    Yamamoto, Toru

    In industrial processes represented by petroleum and refinery processes, it is necessary to establish the performance-driven control strategy in order to improve the productivity, which the control performance is firstly evaluated, and the controller is reconstructed. This paper describes a design scheme of performance-adaptive PID controllers which are based on the above control mechanism. According to the proposed control scheme, the system identification works corresponding to the result of modeling performance assessment, and PID parameters are computed using the newly estimated system parameters. In calculating the PID parameters, the desired control performance is considered. The behaviour of the proposed control scheme is numerically examined in some simulation examples.

  4. Adaptive optimal control of highly dissipative nonlinear spatially distributed processes with neuro-dynamic programming.

    PubMed

    Luo, Biao; Wu, Huai-Ning; Li, Han-Xiong

    2015-04-01

    Highly dissipative nonlinear partial differential equations (PDEs) are widely employed to describe the system dynamics of industrial spatially distributed processes (SDPs). In this paper, we consider the optimal control problem of the general highly dissipative SDPs, and propose an adaptive optimal control approach based on neuro-dynamic programming (NDP). Initially, Karhunen-Loève decomposition is employed to compute empirical eigenfunctions (EEFs) of the SDP based on the method of snapshots. These EEFs together with singular perturbation technique are then used to obtain a finite-dimensional slow subsystem of ordinary differential equations that accurately describes the dominant dynamics of the PDE system. Subsequently, the optimal control problem is reformulated on the basis of the slow subsystem, which is further converted to solve a Hamilton-Jacobi-Bellman (HJB) equation. HJB equation is a nonlinear PDE that has proven to be impossible to solve analytically. Thus, an adaptive optimal control method is developed via NDP that solves the HJB equation online using neural network (NN) for approximating the value function; and an online NN weight tuning law is proposed without requiring an initial stabilizing control policy. Moreover, by involving the NN estimation error, we prove that the original closed-loop PDE system with the adaptive optimal control policy is semiglobally uniformly ultimately bounded. Finally, the developed method is tested on a nonlinear diffusion-convection-reaction process and applied to a temperature cooling fin of high-speed aerospace vehicle, and the achieved results show its effectiveness.

  5. Adaptive optimal control of highly dissipative nonlinear spatially distributed processes with neuro-dynamic programming.

    PubMed

    Luo, Biao; Wu, Huai-Ning; Li, Han-Xiong

    2015-04-01

    Highly dissipative nonlinear partial differential equations (PDEs) are widely employed to describe the system dynamics of industrial spatially distributed processes (SDPs). In this paper, we consider the optimal control problem of the general highly dissipative SDPs, and propose an adaptive optimal control approach based on neuro-dynamic programming (NDP). Initially, Karhunen-Loève decomposition is employed to compute empirical eigenfunctions (EEFs) of the SDP based on the method of snapshots. These EEFs together with singular perturbation technique are then used to obtain a finite-dimensional slow subsystem of ordinary differential equations that accurately describes the dominant dynamics of the PDE system. Subsequently, the optimal control problem is reformulated on the basis of the slow subsystem, which is further converted to solve a Hamilton-Jacobi-Bellman (HJB) equation. HJB equation is a nonlinear PDE that has proven to be impossible to solve analytically. Thus, an adaptive optimal control method is developed via NDP that solves the HJB equation online using neural network (NN) for approximating the value function; and an online NN weight tuning law is proposed without requiring an initial stabilizing control policy. Moreover, by involving the NN estimation error, we prove that the original closed-loop PDE system with the adaptive optimal control policy is semiglobally uniformly ultimately bounded. Finally, the developed method is tested on a nonlinear diffusion-convection-reaction process and applied to a temperature cooling fin of high-speed aerospace vehicle, and the achieved results show its effectiveness. PMID:25794375

  6. Optimal speed estimation in natural image movies predicts human performance.

    PubMed

    Burge, Johannes; Geisler, Wilson S

    2015-01-01

    Accurate perception of motion depends critically on accurate estimation of retinal motion speed. Here we first analyse natural image movies to determine the optimal space-time receptive fields (RFs) for encoding local motion speed in a particular direction, given the constraints of the early visual system. Next, from the RF responses to natural stimuli, we determine the neural computations that are optimal for combining and decoding the responses into estimates of speed. The computations show how selective, invariant speed-tuned units might be constructed by the nervous system. Then, in a psychophysical experiment using matched stimuli, we show that human performance is nearly optimal. Indeed, a single efficiency parameter accurately predicts the detailed shapes of a large set of human psychometric functions. We conclude that many properties of speed-selective neurons and human speed discrimination performance are predicted by the optimal computations, and that natural stimulus variation affects optimal and human observers almost identically.

  7. An auto-adaptive optimization approach for targeting nonpoint source pollution control practices

    NASA Astrophysics Data System (ADS)

    Chen, Lei; Wei, Guoyuan; Shen, Zhenyao

    2015-10-01

    To solve computationally intensive and technically complex control of nonpoint source pollution, the traditional genetic algorithm was modified into an auto-adaptive pattern, and a new framework was proposed by integrating this new algorithm with a watershed model and an economic module. Although conceptually simple and comprehensive, the proposed algorithm would search automatically for those Pareto-optimality solutions without a complex calibration of optimization parameters. The model was applied in a case study in a typical watershed of the Three Gorges Reservoir area, China. The results indicated that the evolutionary process of optimization was improved due to the incorporation of auto-adaptive parameters. In addition, the proposed algorithm outperformed the state-of-the-art existing algorithms in terms of convergence ability and computational efficiency. At the same cost level, solutions with greater pollutant reductions could be identified. From a scientific viewpoint, the proposed algorithm could be extended to other watersheds to provide cost-effective configurations of BMPs.

  8. An auto-adaptive optimization approach for targeting nonpoint source pollution control practices.

    PubMed

    Chen, Lei; Wei, Guoyuan; Shen, Zhenyao

    2015-10-21

    To solve computationally intensive and technically complex control of nonpoint source pollution, the traditional genetic algorithm was modified into an auto-adaptive pattern, and a new framework was proposed by integrating this new algorithm with a watershed model and an economic module. Although conceptually simple and comprehensive, the proposed algorithm would search automatically for those Pareto-optimality solutions without a complex calibration of optimization parameters. The model was applied in a case study in a typical watershed of the Three Gorges Reservoir area, China. The results indicated that the evolutionary process of optimization was improved due to the incorporation of auto-adaptive parameters. In addition, the proposed algorithm outperformed the state-of-the-art existing algorithms in terms of convergence ability and computational efficiency. At the same cost level, solutions with greater pollutant reductions could be identified. From a scientific viewpoint, the proposed algorithm could be extended to other watersheds to provide cost-effective configurations of BMPs.

  9. Adaptive optimal stochastic state feedback control of resistive wall modes in tokamaks

    SciTech Connect

    Sun, Z.; Sen, A.K.; Longman, R.W.

    2006-01-15

    An adaptive optimal stochastic state feedback control is developed to stabilize the resistive wall mode (RWM) instability in tokamaks. The extended least-square method with exponential forgetting factor and covariance resetting is used to identify (experimentally determine) the time-varying stochastic system model. A Kalman filter is used to estimate the system states. The estimated system states are passed on to an optimal state feedback controller to construct control inputs. The Kalman filter and the optimal state feedback controller are periodically redesigned online based on the identified system model. This adaptive controller can stabilize the time-dependent RWM in a slowly evolving tokamak discharge. This is accomplished within a time delay of roughly four times the inverse of the growth rate for the time-invariant model used.

  10. Adaptive postural control for joint immobilization during multitask performance.

    PubMed

    Hsu, Wei-Li

    2014-01-01

    Motor abundance is an essential feature of adaptive control. The range of joint combinations enabled by motor abundance provides the body with the necessary freedom to adopt different positions, configurations, and movements that allow for exploratory postural behavior. This study investigated the adaptation of postural control to joint immobilization during multi-task performance. Twelve healthy volunteers (6 males and 6 females; 21-29 yr) without any known neurological deficits, musculoskeletal conditions, or balance disorders participated in this study. The participants executed a targeting task, alone or combined with a ball-balancing task, while standing with free or restricted joint motions. The effects of joint configuration variability on center of mass (COM) stability were examined using uncontrolled manifold (UCM) analysis. The UCM method separates joint variability into two components: the first is consistent with the use of motor abundance, which does not affect COM position (VUCM); the second leads to COM position variability (VORT). The analysis showed that joints were coordinated such that their variability had a minimal effect on COM position. However, the component of joint variability that reflects the use of motor abundance to stabilize COM (VUCM) was significant decreased when the participants performed the combined task with immobilized joints. The component of joint variability that leads to COM variability (VORT) tended to increase with a reduction in joint degrees of freedom. The results suggested that joint immobilization increases the difficulty of stabilizing COM when multiple tasks are performed simultaneously. These findings are important for developing rehabilitation approaches for patients with limited joint movements. PMID:25329477

  11. Effects of creatine supplementation on performance and training adaptations.

    PubMed

    Kreider, Richard B

    2003-02-01

    Creatine has become a popular nutritional supplement among athletes. Recent research has also suggested that there may be a number of potential therapeutic uses of creatine. This paper reviews the available research that has examined the potential ergogenic value of creatine supplementation on exercise performance and training adaptations. Review of the literature indicates that over 500 research studies have evaluated the effects of creatine supplementation on muscle physiology and/or exercise capacity in healthy, trained, and various diseased populations. Short-term creatine supplementation (e.g. 20 g/day for 5-7 days) has typically been reported to increase total creatine content by 10-30% and phosphocreatine stores by 10-40%. Of the approximately 300 studies that have evaluated the potential ergogenic value of creatine supplementation, about 70% of these studies report statistically significant results while remaining studies generally report non-significant gains in performance. No study reports a statistically significant ergolytic effect. For example, short-term creatine supplementation has been reported to improve maximal power/strength (5-15%), work performed during sets of maximal effort muscle contractions (5-15%), single-effort sprint performance (1-5%), and work performed during repetitive sprint performance (5-15%). Moreover, creatine supplementation during training has been reported to promote significantly greater gains in strength, fat free mass, and performance primarily of high intensity exercise tasks. Although not all studies report significant results, the preponderance of scientific evidence indicates that creatine supplementation appears to be a generally effective nutritional ergogenic aid for a variety of exercise tasks in a number of athletic and clinical populations.

  12. Use Alkalinity Monitoring to Optimize Bioreactor Performance.

    PubMed

    Jones, Christopher S; Kult, Keegan J

    2016-05-01

    In recent years, the agricultural community has reduced flow of nitrogen from farmed landscapes to stream networks through the use of woodchip denitrification bioreactors. Although deployment of this practice is becoming more common to treat high-nitrate water from agricultural drainage pipes, information about bioreactor management strategies is sparse. This study focuses on the use of water monitoring, and especially the use of alkalinity monitoring, in five Iowa woodchip bioreactors to provide insights into and to help manage bioreactor chemistry in ways that will produce desirable outcomes. Results reported here for the five bioreactors show average annual nitrate load reductions between 50 and 80%, which is acceptable according to established practice standards. Alkalinity data, however, imply that nitrous oxide formation may have regularly occurred in at least three of the bioreactors that are considered to be closed systems. Nitrous oxide measurements of influent and effluent water provide evidence that alkalinity may be an important indicator of bioreactor performance. Bioreactor chemistry can be managed by manipulation of water throughput in ways that produce adequate nitrate removal while preventing undesirable side effects. We conclude that (i) water should be retained for longer periods of time in bioreactors where nitrous oxide formation is indicated, (ii) measuring only nitrate and sulfate concentrations is insufficient for proper bioreactor operation, and (iii) alkalinity monitoring should be implemented into protocols for bioreactor management. PMID:27136151

  13. Use Alkalinity Monitoring to Optimize Bioreactor Performance.

    PubMed

    Jones, Christopher S; Kult, Keegan J

    2016-05-01

    In recent years, the agricultural community has reduced flow of nitrogen from farmed landscapes to stream networks through the use of woodchip denitrification bioreactors. Although deployment of this practice is becoming more common to treat high-nitrate water from agricultural drainage pipes, information about bioreactor management strategies is sparse. This study focuses on the use of water monitoring, and especially the use of alkalinity monitoring, in five Iowa woodchip bioreactors to provide insights into and to help manage bioreactor chemistry in ways that will produce desirable outcomes. Results reported here for the five bioreactors show average annual nitrate load reductions between 50 and 80%, which is acceptable according to established practice standards. Alkalinity data, however, imply that nitrous oxide formation may have regularly occurred in at least three of the bioreactors that are considered to be closed systems. Nitrous oxide measurements of influent and effluent water provide evidence that alkalinity may be an important indicator of bioreactor performance. Bioreactor chemistry can be managed by manipulation of water throughput in ways that produce adequate nitrate removal while preventing undesirable side effects. We conclude that (i) water should be retained for longer periods of time in bioreactors where nitrous oxide formation is indicated, (ii) measuring only nitrate and sulfate concentrations is insufficient for proper bioreactor operation, and (iii) alkalinity monitoring should be implemented into protocols for bioreactor management.

  14. Architectural modifications for flexible supercapacitor performance optimization

    NASA Astrophysics Data System (ADS)

    Keskinen, Jari; Lehtimäki, Suvi; Dastpak, Arman; Tuukkanen, Sampo; Flyktman, Timo; Kraft, Thomas; Railanmaa, Anna; Lupo, Donald

    2016-09-01

    We have developed material and architectural alternatives for flexible supercapacitors and investigated their effect on practical performance. The substrate alternatives include paperboard as well as various polyethylene terephthalate (PET) films and laminates, with aqueous NaCl electrolyte used in all devices. In all the supercapacitors, activated carbon is used as the active layer and graphite ink as the current collector, with various aluminium or copper structures applied to enhance the current collectors' conductivity. The capacitance of the supercapacitors was between 0.05 F and 0.58 F and their equivalent series resistance (ESR) was from <1 Ω to 14 Ω, depending mainly on the current collector structure. Furthermore, leakage current and selfdischarge rates were defined and compared for the various architectures. The barrier properties of the supercapacitor encapsulation have a clear correlation with leakage current, as was clearly shown by the lower leakage in devices with an aluminium barrier layer. A cycle life test showed that after 40000 charge-discharge cycles the capacitance decreases by less than 10%.

  15. Performance assessment of MEMS adaptive optics in tactical airborne systems

    NASA Astrophysics Data System (ADS)

    Tyson, Robert K.

    1999-09-01

    Tactical airborne electro-optical systems are severely constrained by weight, volume, power, and cost. Micro- electrical-mechanical adaptive optics provide a solution that addresses the engineering realities without compromising spatial and temporal compensation requirements. Through modeling and analysis, we determined that substantial benefits could be gained for laser designators, ladar, countermeasures, and missile seekers. The developments potential exists for improving seeker imagery resolution 20 percent, extending countermeasures keep-out range by a factor of 5, doubling the range for ladar detection and identification, and compensating for supersonic and hypersonic aircraft boundary layers. Innovative concepts are required for atmospheric pat hand boundary layer compensation. We have developed design that perform these tasks using high speed scene-based wavefront sensing, IR aerosol laser guide stars, and extended-object wavefront beacons. We have developed a number of adaptive optics system configurations that met the spatial resolution requirements and we have determined that sensing and signal processing requirements can be met. With the help of micromachined deformable mirrors and sensor, we will be able to integrate the systems into existing airborne pods and missiles as well as next generation electro-optical systems.

  16. On-line re-optimization of prostate IMRT plan for adaptive radiation therapy: A feasibility study and implementation

    NASA Astrophysics Data System (ADS)

    Thongphiew, Danthai

    Prostate cancer is a disease that affected approximately 200,000 men in United States in 2006. Radiation therapy is a non invasive treatment option for this disease and is highly effective. The goal of radiation therapy is to deliver the prescription dose to the tumor (prostate) while sparing the surrounding healthy organs (e.g. bladder, rectum, and femoral heads). One limitation of the radiation therapy is organ position and shape variation from day to day. These variations could be as large as half inch. The conventional solution to this problem is to include some margins surrounding the target when plan the treatment. The development of image guided radiation therapy technique allows in-room correction which potentially eliminates the patient setup error however the uncertainty due to organ deformation still remains. Performing a plan re-optimization will take about half hour which is infeasible to perform an online correction. A technique of performing online re-optimization of intensity modulated radiation therapy is developed for adaptive radiation therapy of prostate cancer. The technique is capable of correction both organ positioning and shape changes within a few minutes. The proposed technique involves (1) 3D on-board imaging of daily anatomy, (2) registering the daily images with original planning CT images and mapping the original dose distribution to the daily anatomy, (3) real time re-optimization of the plan. Finally the leaf sequences are calculated for the treatment delivery. The feasibility of this online adaptive radiation therapy scheme was evaluated by clinical cases. The results demonstrate that it is feasible to perform online re-optimization of the original plan when large position or shape variation occurs.

  17. Performance of the Keck Observatory adaptive optics system

    SciTech Connect

    van Dam, M A; Mignant, D L; Macintosh, B A

    2004-01-19

    In this paper, the adaptive optics (AO) system at the W.M. Keck Observatory is characterized. The authors calculate the error budget of the Keck AO system operating in natural guide star mode with a near infrared imaging camera. By modeling the control loops and recording residual centroids, the measurement noise and band-width errors are obtained. The error budget is consistent with the images obtained. Results of sky performance tests are presented: the AO system is shown to deliver images with average Strehl ratios of up to 0.37 at 1.58 {micro}m using a bright guide star and 0.19 for a magnitude 12 star.

  18. Optimization and vibration suppression of adaptive composite panels using genetic algorithm and disturbance observer technique

    NASA Astrophysics Data System (ADS)

    Yan, Su; Ghasemi-Nejhad, Mehrdad N.

    2003-07-01

    In this paper, a model of the adaptive composite panel surfaces with piezoelectric patches is built using the Rayleigh-Ritz method based on the laminate theory. The interia and stiffness of the actuators are considered in the developed model. An optimal actuator location has been proved to be desirable since the piezoelectric actuators often have limitations of delivering large power oiutputs. Due to its effectiveness in seraching optimal design parameters and obtaining globally optimal solutions, the genetic algorithm has been applied to find optimal locations of piezoelectric actuators for the vibration control of a smart composite beam. In addition, the effects of population size, the crossover probability, and the mutation probability on the convergence of the genetic algorithm are investigated. Meanwhile, linear quadric regulator (LQR) and disturbance observer (DOB) are employed for the vibration suppression of the optimized adaptive composite beam (ACB). The experimental results show the robustness of the DOB, which can successfully suppress the vibrations of the cantilevered ACB according to the optimization results in an uncertain system.

  19. Performance optimization of scientific applications on emerging architectures

    NASA Astrophysics Data System (ADS)

    Dursun, Hikmet

    The shift to many-core architecture design paradigm in computer market has provided unprecedented computational capabilities. This also marks the end of the free-ride era---scientific software must now evolve with new chips. Hence, it is of great importance to develop large legacy-code optimization frameworks to achieve an optimal system architecture-algorithm mapping that maximizes processor utilization and thereby achieves higher application performance. To address this challenge, this thesis studies and develops scalable algorithms for leveraging many-core resources optimally to improve the performance of massively parallel scientific applications. This work presents a systematic approach to optimize scientific codes on emerging architectures, which consists of three major steps: (1) Develop a performance profiling framework to identify application performance bottlenecks on clusters of emerging architectures; (2) explore common algorithmic kernels in a suite of real world scientific applications and develop performance tuning strategies to provide insight into how to maximally utilize underlying hardware; and (3) unify experience in performance optimization to develop a top-down optimization framework for the optimization of scientific applications on emerging high-performance computing platforms. This thesis makes the following contributions. First, we have designed and implemented a performance analysis methodology for Cell-accelerated clusters. Two parallel scientific applications---lattice Boltzmann (LB) flow simulation and atomistic molecular dynamics (MD) simulation---are analyzed and valuable performance insights are gained on a Cell processor based PlayStation3 cluster as well as a hybrid Opteron+Cell based cluster similar to the design of Roadrunner---the first petaflop supercomputer of the world. Second, we have developed a novel parallelization framework for finite-difference time-domain applications. The approach is validated in a seismic

  20. Analytical modeling and active vibration suppression of adaptive composite panels with optimal actuator configurations

    NASA Astrophysics Data System (ADS)

    Yan, Su; Ghasemi-Nejhad, Mehrdad N.

    2007-12-01

    In this paper, models of adaptive composite panels with surface-mounted/embedded piezoelectric patches are analytically built using the Lagrange-Rayleigh-Ritz method (LRRM), verified through experiments and finite element method (FEM), and used in piezoelectric actuator placement optimization and vibration control. Two panels are considered: a cantilevered adaptive composite beam (ACB) and an adaptive circular composite plate (ACCP) with complex boundaries. The inertia and stiffness of the surface-mounted/embedded piezoelectric patches are included in the developed models. To obtain the mode shapes of the ACCP, which are essential to the LRRM modeling, the method of separation of variables is employed and Bessel series and modified Bessel series are introduced. The built models are verified by experiments for the ACB and by the FEM for the ACCP. The actuation configurations of the piezoelectric patches in the panels are optimized based on the introduced analytical model. Finally, with the optimal locations of the piezoelectric patches, the vibration suppression of the ACB and the ACCP is experimentally and numerically carried out, and excellent vibration suppressions for both adaptive panels are obtained.

  1. Seed vigour and crop establishment: extending performance beyond adaptation.

    PubMed

    Finch-Savage, W E; Bassel, G W

    2016-02-01

    Seeds are central to crop production, human nutrition, and food security. A key component of the performance of crop seeds is the complex trait of seed vigour. Crop yield and resource use efficiency depend on successful plant establishment in the field, and it is the vigour of seeds that defines their ability to germinate and establish seedlings rapidly, uniformly, and robustly across diverse environmental conditions. Improving vigour to enhance the critical and yield-defining stage of crop establishment remains a primary objective of the agricultural industry and the seed/breeding companies that support it. Our knowledge of the regulation of seed germination has developed greatly in recent times, yet understanding of the basis of variation in vigour and therefore seed performance during the establishment of crops remains limited. Here we consider seed vigour at an ecophysiological, molecular, and biomechanical level. We discuss how some seed characteristics that serve as adaptive responses to the natural environment are not suitable for agriculture. Past domestication has provided incremental improvements, but further actively directed change is required to produce seeds with the characteristics required both now and in the future. We discuss ways in which basic plant science could be applied to enhance seed performance in crop production. PMID:26585226

  2. Adaptive tracking and compensation of laser spot based on ant colony optimization

    NASA Astrophysics Data System (ADS)

    Yang, Lihong; Ke, Xizheng; Bai, Runbing; Hu, Qidi

    2009-05-01

    Because the effect of atmospheric scattering and atmospheric turbulence on laser signal of atmospheric absorption,laser spot twinkling, beam drift and spot split-up occur ,when laser signal transmits in the atmospheric channel. The phenomenon will be seriously affects the stability and the reliability of laser spot receiving system. In order to reduce the influence of atmospheric turbulence, we adopt optimum control thoughts in the field of artificial intelligence, propose a novel adaptive optical control technology-- model-free optimized adaptive control technology, analyze low-order pattern wave-front error theory, in which an -adaptive optical system is employed to adjust errors, and design its adaptive structure system. Ant colony algorithm is the control core algorithm, which is characteristic of positive feedback, distributed computing and greedy heuristic search. . The ant colony algorithm optimization of adaptive optical phase compensation is simulated. Simulation result shows that, the algorithm can effectively control laser energy distribution, improve laser light beam quality, and enhance signal-to-noise ratio of received signal.

  3. On-line re-optimization of prostate IMRT plans for adaptive radiation therapy

    NASA Astrophysics Data System (ADS)

    Wu, Q. Jackie; Thongphiew, Danthai; Wang, Zhiheng; Mathayomchan, Boonyanit; Chankong, Vira; Yoo, Sua; Lee, W. Robert; Yin, Fang-Fang

    2008-02-01

    For intermediate and high risk prostate cancer, both the prostate gland and seminal vesicles are included in the clinical target volume. Internal motion patterns of these two organs vary, presenting a challenge for adaptive treatment. Adaptive techniques such as isocenter repositioning and soft tissue alignment are effective when tumor volumes only exhibit translational shift, while direct re-optimization of the intensity-modulated radiation therapy (IMRT) plan maybe more desirable when extreme deformation or differential positioning changes of the organs occur. Currently, direct re-optimization of the IMRT plan using beamlet (or fluence map) has not been reported. In this study, we report a novel on-line re-optimization technique that can accomplish plan adjustment on-line. Deformable image registration is used to provide position variation information on each voxel along the three dimensions. The original planned dose distribution is used as the 'goal' dose distribution for adaptation and to ensure planning quality. Fluence maps are re-optimized via linear programming, and a plan solution can be achieved within 2 min. The feasibility of this technique is demonstrated with a clinical case with large deformation. Such on-line ART process can be highly valuable with hypo-fractionated prostate IMRT treatment. Abstract and preliminary data presented at 49th AAPM Annual Meeting, Minneapolis, MN, USA, July 2007.

  4. On-line re-optimization of prostate IMRT plans for adaptive radiation therapy.

    PubMed

    Wu, Q Jackie; Thongphiew, Danthai; Wang, Zhiheng; Mathayomchan, Boonyanit; Chankong, Vira; Yoo, Sua; Lee, W Robert; Yin, Fang-Fang

    2008-02-01

    For intermediate and high risk prostate cancer, both the prostate gland and seminal vesicles are included in the clinical target volume. Internal motion patterns of these two organs vary, presenting a challenge for adaptive treatment. Adaptive techniques such as isocenter repositioning and soft tissue alignment are effective when tumor volumes only exhibit translational shift, while direct re-optimization of the intensity-modulated radiation therapy (IMRT) plan maybe more desirable when extreme deformation or differential positioning changes of the organs occur. Currently, direct re-optimization of the IMRT plan using beamlet (or fluence map) has not been reported. In this study, we report a novel on-line re-optimization technique that can accomplish plan adjustment on-line. Deformable image registration is used to provide position variation information on each voxel along the three dimensions. The original planned dose distribution is used as the 'goal' dose distribution for adaptation and to ensure planning quality. Fluence maps are re-optimized via linear programming, and a plan solution can be achieved within 2 min. The feasibility of this technique is demonstrated with a clinical case with large deformation. Such on-line ART process can be highly valuable with hypo-fractionated prostate IMRT treatment. PMID:18199909

  5. An Adaptive Priority Tuning System for Optimized Local CPU Scheduling using BOINC Clients

    NASA Astrophysics Data System (ADS)

    Mnaouer, Adel B.; Ragoonath, Colin

    2010-11-01

    Volunteer Computing (VC) is a Distributed Computing model which utilizes idle CPU cycles from computing resources donated by volunteers who are connected through the Internet to form a very large-scale, loosely coupled High Performance Computing environment. Distributed Volunteer Computing environments such as the BOINC framework is concerned mainly with the efficient scheduling of the available resources to the applications which require them. The BOINC framework thus contains a number of scheduling policies/algorithms both on the server-side and on the client which work together to maximize the available resources and to provide a degree of QoS in an environment which is highly volatile. This paper focuses on the BOINC client and introduces an adaptive priority tuning client side middleware application which improves the execution times of Work Units (WUs) while maintaining an acceptable Maximum Response Time (MRT) for the end user. We have conducted extensive experimentation of the proposed system and the results show clear speedup of BOINC applications using our optimized middleware as opposed to running using the original BOINC client.

  6. Adaptive Urban Stormwater Management Using a Two-stage Stochastic Optimization Model

    NASA Astrophysics Data System (ADS)

    Hung, F.; Hobbs, B. F.; McGarity, A. E.

    2014-12-01

    In many older cities, stormwater results in combined sewer overflows (CSOs) and consequent water quality impairments. Because of the expense of traditional approaches for controlling CSOs, cities are considering the use of green infrastructure (GI) to reduce runoff and pollutants. Examples of GI include tree trenches, rain gardens, green roofs, and rain barrels. However, the cost and effectiveness of GI are uncertain, especially at the watershed scale. We present a two-stage stochastic extension of the Stormwater Investment Strategy Evaluation (StormWISE) model (A. McGarity, JWRPM, 2012, 111-24) to explicitly model and optimize these uncertainties in an adaptive management framework. A two-stage model represents the immediate commitment of resources ("here & now") followed by later investment and adaptation decisions ("wait & see"). A case study is presented for Philadelphia, which intends to extensively deploy GI over the next two decades (PWD, "Green City, Clean Water - Implementation and Adaptive Management Plan," 2011). After first-stage decisions are made, the model updates the stochastic objective and constraints (learning). We model two types of "learning" about GI cost and performance. One assumes that learning occurs over time, is automatic, and does not depend on what has been done in stage one (basic model). The other considers learning resulting from active experimentation and learning-by-doing (advanced model). Both require expert probability elicitations, and learning from research and monitoring is modelled by Bayesian updating (as in S. Jacobi et al., JWRPM, 2013, 534-43). The model allocates limited financial resources to GI investments over time to achieve multiple objectives with a given reliability. Objectives include minimizing construction and O&M costs; achieving nutrient, sediment, and runoff volume targets; and community concerns, such as aesthetics, CO2 emissions, heat islands, and recreational values. CVaR (Conditional Value at Risk) and

  7. Control Systems with Normalized and Covariance Adaptation by Optimal Control Modification

    NASA Technical Reports Server (NTRS)

    Nguyen, Nhan T. (Inventor); Burken, John J. (Inventor); Hanson, Curtis E. (Inventor)

    2016-01-01

    Disclosed is a novel adaptive control method and system called optimal control modification with normalization and covariance adjustment. The invention addresses specifically to current challenges with adaptive control in these areas: 1) persistent excitation, 2) complex nonlinear input-output mapping, 3) large inputs and persistent learning, and 4) the lack of stability analysis tools for certification. The invention has been subject to many simulations and flight testing. The results substantiate the effectiveness of the invention and demonstrate the technical feasibility for use in modern aircraft flight control systems.

  8. Routing performance analysis and optimization within a massively parallel computer

    DOEpatents

    Archer, Charles Jens; Peters, Amanda; Pinnow, Kurt Walter; Swartz, Brent Allen

    2013-04-16

    An apparatus, program product and method optimize the operation of a massively parallel computer system by, in part, receiving actual performance data concerning an application executed by the plurality of interconnected nodes, and analyzing the actual performance data to identify an actual performance pattern. A desired performance pattern may be determined for the application, and an algorithm may be selected from among a plurality of algorithms stored within a memory, the algorithm being configured to achieve the desired performance pattern based on the actual performance data.

  9. Adaptive-filter/feature-orthogonalization processing string for optimal LLRT mine classfication in side-scan sonar imagery

    NASA Astrophysics Data System (ADS)

    Aridgides, Tom; Libera, Peter; Fernandez, Manuel F.; Dobeck, Gerald J.

    1996-05-01

    An automatic, robust, adaptive clutter suppression, mine detection and classification processing string has been developed and applied to side-scan sonar imagery data. The overall processing string includes data pre-processing, adaptive clutter filtering (ACF), 2D normalization, detection, feature extraction, and classification processing blocks. The data pre-processing block contains automatic gain control and data decimation processing. The ACF technique designs a 2D adaptive range-crossrange linear FIR filter which is optimal in the Least Squares sense, simultaneously suppressing the background clutter while preserving an average peak target signature (normalized shape) computed a priori using training set data. A multiple reference ACF algorithm version was utilized to account for multiple target shapes (due to different mine types, multiple target aspect angles, etc.). The detection block consists of thresholding, clustering of exceedances and limiting their number, and a secondary thresholding process. Following feature extraction, the classification block applies a novel transformation to the data, which orthogonalizes the features and enables an efficient application of the optimal log-likelihood-ratio-test (LLRT) classification rule. The utility of the overall processing string was demonstrated with two side-scan sonar data sets. The ACF/feature orthogonalization based LLRT mine classification processing string provided average probability of correct mine classification and false alarm rate performance similar to that obtained when utilizing an expert sonar operator.

  10. Adaptive regulation of digestive performance in the genus Python.

    PubMed

    Ott, Brian D; Secor, Stephen M

    2007-01-01

    The adaptive interplay between feeding habits and digestive physiology is demonstrated by the Burmese python, which in response to feeding infrequently has evolved the capacity to widely regulate gastrointestinal performance with feeding and fasting. To explore the generality of this physiological trait among pythons, we compared the postprandial responses of metabolism and both intestinal morphology and function among five members of the genus Python: P. brongersmai, P. molurus, P. regius, P. reticulatus and P. sebae. These infrequently feeding pythons inhabit Africa, southeast Asia and Indonesia and vary in body shape from short and stout (P. brongersmai) to long and slender (P. reticulatus). Following the consumption of rodent meals equaling 25% of snake body mass, metabolic rates of pythons peaked at 1.5 days at levels 9.9- to 14.5-fold of standard metabolic rates before returning to prefeeding rates by day 6-8. Specific dynamic action of these meals (317-347 kJ) did not differ among species and equaled 23-27% of the ingested energy. For each species, feeding triggered significant upregulation of intestinal nutrient transport and aminopeptidase-N activity. Concurrently, intestinal mass doubled on average for the five species, in part due to an 85% increase in mucosal thickness, itself a product of 27-59% increases in enterocyte volume. The integrative response of intestinal functional upregulation and tissue hypertrophy enables each of these five python species, regardless of body shape, to modulate intestinal performance to meet the demands of their large infrequent meals.

  11. Improving scanner wafer alignment performance by target optimization

    NASA Astrophysics Data System (ADS)

    Leray, Philippe; Jehoul, Christiane; Socha, Robert; Menchtchikov, Boris; Raghunathan, Sudhar; Kent, Eric; Schoonewelle, Hielke; Tinnemans, Patrick; Tuffy, Paul; Belen, Jun; Wise, Rich

    2016-03-01

    In the process nodes of 10nm and below, the patterning complexity along with the processing and materials required has resulted in a need to optimize alignment targets in order to achieve the required precision, accuracy and throughput performance. Recent industry publications on the metrology target optimization process have shown a move from the expensive and time consuming empirical methodologies, towards a faster computational approach. ASML's Design for Control (D4C) application, which is currently used to optimize YieldStar diffraction based overlay (DBO) metrology targets, has been extended to support the optimization of scanner wafer alignment targets. This allows the necessary process information and design methodology, used for DBO target designs, to be leveraged for the optimization of alignment targets. In this paper, we show how we applied this computational approach to wafer alignment target design. We verify the correlation between predictions and measurements for the key alignment performance metrics and finally show the potential alignment and overlay performance improvements that an optimized alignment target could achieve.

  12. Proficient brain for optimal performance: the MAP model perspective

    PubMed Central

    di Fronso, Selenia; Filho, Edson; Conforto, Silvia; Schmid, Maurizio; Bortoli, Laura; Comani, Silvia; Robazza, Claudio

    2016-01-01

    Background. The main goal of the present study was to explore theta and alpha event-related desynchronization/synchronization (ERD/ERS) activity during shooting performance. We adopted the idiosyncratic framework of the multi-action plan (MAP) model to investigate different processing modes underpinning four types of performance. In particular, we were interested in examining the neural activity associated with optimal-automated (Type 1) and optimal-controlled (Type 2) performances. Methods. Ten elite shooters (6 male and 4 female) with extensive international experience participated in the study. ERD/ERS analysis was used to investigate cortical dynamics during performance. A 4 × 3 (performance types × time) repeated measures analysis of variance was performed to test the differences among the four types of performance during the three seconds preceding the shots for theta, low alpha, and high alpha frequency bands. The dependent variables were the ERD/ERS percentages in each frequency band (i.e., theta, low alpha, high alpha) for each electrode site across the scalp. This analysis was conducted on 120 shots for each participant in three different frequency bands and the individual data were then averaged. Results. We found ERS to be mainly associated with optimal-automatic performance, in agreement with the “neural efficiency hypothesis.” We also observed more ERD as related to optimal-controlled performance in conditions of “neural adaptability” and proficient use of cortical resources. Discussion. These findings are congruent with the MAP conceptualization of four performance states, in which unique psychophysiological states underlie distinct performance-related experiences. From an applied point of view, our findings suggest that the MAP model can be used as a framework to develop performance enhancement strategies based on cognitive and neurofeedback techniques. PMID:27257557

  13. Performance optimization of an MHD generator with physical constraints

    NASA Technical Reports Server (NTRS)

    Pian, C. C. P.; Seikel, G. R.; Smith, J. M.

    1979-01-01

    A method to optimize the Faraday MHD generator performance under a prescribed set of electrical and magnet constraints is described. The results of generator performance calculations using this technique are presented for a very large MHD/steam plant. The differences between the maximum power and maximum net power generators are described. The sensitivity of the generator performance to the various operational parameters are presented.

  14. Crop classification by forward neural network with adaptive chaotic particle swarm optimization.

    PubMed

    Zhang, Yudong; Wu, Lenan

    2011-01-01

    This paper proposes a hybrid crop classifier for polarimetric synthetic aperture radar (SAR) images. The feature sets consisted of span image, the H/A/α decomposition, and the gray-level co-occurrence matrix (GLCM) based texture features. Then, the features were reduced by principle component analysis (PCA). Finally, a two-hidden-layer forward neural network (NN) was constructed and trained by adaptive chaotic particle swarm optimization (ACPSO). K-fold cross validation was employed to enhance generation. The experimental results on Flevoland sites demonstrate the superiority of ACPSO to back-propagation (BP), adaptive BP (ABP), momentum BP (MBP), Particle Swarm Optimization (PSO), and Resilient back-propagation (RPROP) methods. Moreover, the computation time for each pixel is only 1.08 × 10(-7) s.

  15. Integrated optimal allocation model for complex adaptive system of water resources management (II): Case study

    NASA Astrophysics Data System (ADS)

    Zhou, Yanlai; Guo, Shenglian; Xu, Chong-Yu; Liu, Dedi; Chen, Lu; Wang, Dong

    2015-12-01

    Climate change, rapid economic development and increase of the human population are considered as the major triggers of increasing challenges for water resources management. This proposed integrated optimal allocation model (IOAM) for complex adaptive system of water resources management is applied in Dongjiang River basin located in the Guangdong Province of China. The IOAM is calibrated and validated under baseline period 2010 year and future period 2011-2030 year, respectively. The simulation results indicate that the proposed model can make a trade-off between demand and supply for sustainable development of society, economy, ecology and environment and achieve adaptive management of water resources allocation. The optimal scheme derived by multi-objective evaluation is recommended for decision-makers in order to maximize the comprehensive benefits of water resources management.

  16. Adjoint-Based Algorithms for Adaptation and Design Optimizations on Unstructured Grids

    NASA Technical Reports Server (NTRS)

    Nielsen, Eric J.

    2006-01-01

    Schemes based on discrete adjoint algorithms present several exciting opportunities for significantly advancing the current state of the art in computational fluid dynamics. Such methods provide an extremely efficient means for obtaining discretely consistent sensitivity information for hundreds of design variables, opening the door to rigorous, automated design optimization of complex aerospace configuration using the Navier-Stokes equation. Moreover, the discrete adjoint formulation provides a mathematically rigorous foundation for mesh adaptation and systematic reduction of spatial discretization error. Error estimates are also an inherent by-product of an adjoint-based approach, valuable information that is virtually non-existent in today's large-scale CFD simulations. An overview of the adjoint-based algorithm work at NASA Langley Research Center is presented, with examples demonstrating the potential impact on complex computational problems related to design optimization as well as mesh adaptation.

  17. Time reversal versus adaptive optimization for spatiotemporal nanolocalization in a random nanoantenna

    NASA Astrophysics Data System (ADS)

    Differt, Dominik; Hensen, Matthias; Pfeiffer, Walter

    2016-05-01

    Spatiotemporal nanolocalization of ultrashort pulses in a random scattering nanostructure via time reversal and adaptive optimization employing a genetic algorithm and a suitably defined fitness function is studied for two embedded nanoparticles that are separated by only a tenth of the free space wavelength. The nanostructure is composed of resonant core-shell nanoparticles (TiO2 core and Ag shell) placed randomly surrounding these two nanoparticles acting as targets. The time reversal scheme achieves selective nanolocalization only by chance if the incident radiation can couple efficiently to dipolar local modes interacting with the target/emitter particle. Even embedding the structure in a reverberation chamber fails improving the nanolocalization. In contrast, the adaptive optimization strategy reliably yields nanolocalization of the radiation and allows a highly selective excitation of either target position. This demonstrates that random scattering structures are interesting multi-purpose optical nanoantennas to realize highly flexible spatiotemporal optical near-field control.

  18. A single network adaptive critic (SNAC) architecture for optimal control synthesis for a class of nonlinear systems.

    PubMed

    Padhi, Radhakant; Unnikrishnan, Nishant; Wang, Xiaohua; Balakrishnan, S N

    2006-12-01

    Even though dynamic programming offers an optimal control solution in a state feedback form, the method is overwhelmed by computational and storage requirements. Approximate dynamic programming implemented with an Adaptive Critic (AC) neural network structure has evolved as a powerful alternative technique that obviates the need for excessive computations and storage requirements in solving optimal control problems. In this paper, an improvement to the AC architecture, called the "Single Network Adaptive Critic (SNAC)" is presented. This approach is applicable to a wide class of nonlinear systems where the optimal control (stationary) equation can be explicitly expressed in terms of the state and costate variables. The selection of this terminology is guided by the fact that it eliminates the use of one neural network (namely the action network) that is part of a typical dual network AC setup. As a consequence, the SNAC architecture offers three potential advantages: a simpler architecture, lesser computational load and elimination of the approximation error associated with the eliminated network. In order to demonstrate these benefits and the control synthesis technique using SNAC, two problems have been solved with the AC and SNAC approaches and their computational performances are compared. One of these problems is a real-life Micro-Electro-Mechanical-system (MEMS) problem, which demonstrates that the SNAC technique is applicable to complex engineering systems.

  19. Adaptable Metadata Rich IO Methods for Portable High Performance IO

    SciTech Connect

    Lofstead, J.; Zheng, Fang; Klasky, Scott A; Schwan, Karsten

    2009-01-01

    Since IO performance on HPC machines strongly depends on machine characteristics and configuration, it is important to carefully tune IO libraries and make good use of appropriate library APIs. For instance, on current petascale machines, independent IO tends to outperform collective IO, in part due to bottlenecks at the metadata server. The problem is exacerbated by scaling issues, since each IO library scales differently on each machine, and typically, operates efficiently to different levels of scaling on different machines. With scientific codes being run on a variety of HPC resources, efficient code execution requires us to address three important issues: (1) end users should be able to select the most efficient IO methods for their codes, with minimal effort in terms of code updates or alterations; (2) such performance-driven choices should not prevent data from being stored in the desired file formats, since those are crucial for later data analysis; and (3) it is important to have efficient ways of identifying and selecting certain data for analysis, to help end users cope with the flood of data produced by high end codes. This paper employs ADIOS, the ADaptable IO System, as an IO API to address (1)-(3) above. Concerning (1), ADIOS makes it possible to independently select the IO methods being used by each grouping of data in an application, so that end users can use those IO methods that exhibit best performance based on both IO patterns and the underlying hardware. In this paper, we also use this facility of ADIOS to experimentally evaluate on petascale machines alternative methods for high performance IO. Specific examples studied include methods that use strong file consistency vs. delayed parallel data consistency, as that provided by MPI-IO or POSIX IO. Concerning (2), to avoid linking IO methods to specific file formats and attain high IO performance, ADIOS introduces an efficient intermediate file format, termed BP, which can be converted, at small

  20. Orbit design and optimization based on global telecommunication performance metrics

    NASA Technical Reports Server (NTRS)

    Lee, Seungwon; Lee, Charles H.; Kerridge, Stuart; Cheung, Kar-Ming; Edwards, Charles D.

    2006-01-01

    The orbit selection of telecommunications orbiters is one of the critical design processes and should be guided by global telecom performance metrics and mission-specific constraints. In order to aid the orbit selection, we have coupled the Telecom Orbit Analysis and Simulation Tool (TOAST) with genetic optimization algorithms. As a demonstration, we have applied the developed tool to select an optimal orbit for general Mars telecommunications orbiters with the constraint of being a frozen orbit. While a typical optimization goal is to minimize tele-communications down time, several relevant performance metrics are examined: 1) area-weighted average gap time, 2) global maximum of local maximum gap time, 3) global maximum of local minimum gap time. Optimal solutions are found with each of the metrics. Common and different features among the optimal solutions as well as the advantage and disadvantage of each metric are presented. The optimal solutions are compared with several candidate orbits that were considered during the development of Mars Telecommunications Orbiter.

  1. Application of multi-objective controller to optimal tuning of PID gains for a hydraulic turbine regulating system using adaptive grid particle swam optimization.

    PubMed

    Chen, Zhihuan; Yuan, Yanbin; Yuan, Xiaohui; Huang, Yuehua; Li, Xianshan; Li, Wenwu

    2015-05-01

    A hydraulic turbine regulating system (HTRS) is one of the most important components of hydropower plant, which plays a key role in maintaining safety, stability and economical operation of hydro-electrical installations. At present, the conventional PID controller is widely applied in the HTRS system for its practicability and robustness, and the primary problem with respect to this control law is how to optimally tune the parameters, i.e. the determination of PID controller gains for satisfactory performance. In this paper, a kind of multi-objective evolutionary algorithms, named adaptive grid particle swarm optimization (AGPSO) is applied to solve the PID gains tuning problem of the HTRS system. This newly AGPSO optimized method, which differs from a traditional one-single objective optimization method, is designed to take care of settling time and overshoot level simultaneously, in which a set of non-inferior alternatives solutions (i.e. Pareto solution) is generated. Furthermore, a fuzzy-based membership value assignment method is employed to choose the best compromise solution from the obtained Pareto set. An illustrative example associated with the best compromise solution for parameter tuning of the nonlinear HTRS system is introduced to verify the feasibility and the effectiveness of the proposed AGPSO-based optimization approach, as compared with two another prominent multi-objective algorithms, i.e. Non-dominated Sorting Genetic Algorithm II (NSGAII) and Strength Pareto Evolutionary Algorithm II (SPEAII), for the quality and diversity of obtained Pareto solutions set. Consequently, simulation results show that this AGPSO optimized approach outperforms than compared methods with higher efficiency and better quality no matter whether the HTRS system works under unload or load conditions.

  2. Performance optimization of an airbreathing launch vehicle by a sequential trajectory optimization and vehicle design scheme

    NASA Astrophysics Data System (ADS)

    Schoettle, U. M.; Hillesheimer, M.

    1991-08-01

    An iterative multistep procedure for performance optimization of launch vehicles is described, which is being developed to support trade-off and sensitivity studies. Two major steps involved in the automated technique are the optimum trajectory shaping employing approximate control models and the vehicle design. Both aspects are discussed in this paper. Simulation examples are presented, first to demonstrate the approach taken for flight path optimization; second, to verify the coupled trajectory and design optimization procedure; and finally, to assess the impact of different mission requirements on an airbreathing Saenger-type vehicle.

  3. Communication Range Dynamics and Performance Analysis for a Self-Adaptive Transmission Power Controller.

    PubMed

    Lucas Martínez, Néstor; Martínez Ortega, José-Fernán; Hernández Díaz, Vicente; Del Toro Matamoros, Raúl M

    2016-05-12

    The deployment of the nodes in a Wireless Sensor and Actuator Network (WSAN) is typically restricted by the sensing and acting coverage. This implies that the locations of the nodes may be, and usually are, not optimal from the point of view of the radio communication. Additionally, when the transmission power is tuned for those locations, there are other unpredictable factors that can cause connectivity failures, like interferences, signal fading due to passing objects and, of course, radio irregularities. A control-based self-adaptive system is a typical solution to improve the energy consumption while keeping good connectivity. In this paper, we explore how the communication range for each node evolves along the iterations of an energy saving self-adaptive transmission power controller when using different parameter sets in an outdoor scenario, providing a WSAN that automatically adapts to surrounding changes keeping good connectivity. The results obtained in this paper show how the parameters with the best performance keep a k-connected network, where k is in the range of the desired node degree plus or minus a specified tolerance value.

  4. Communication Range Dynamics and Performance Analysis for a Self-Adaptive Transmission Power Controller †

    PubMed Central

    Lucas Martínez, Néstor; Martínez Ortega, José-Fernán; Hernández Díaz, Vicente; del Toro Matamoros, Raúl M.

    2016-01-01

    The deployment of the nodes in a Wireless Sensor and Actuator Network (WSAN) is typically restricted by the sensing and acting coverage. This implies that the locations of the nodes may be, and usually are, not optimal from the point of view of the radio communication. Additionally, when the transmission power is tuned for those locations, there are other unpredictable factors that can cause connectivity failures, like interferences, signal fading due to passing objects and, of course, radio irregularities. A control-based self-adaptive system is a typical solution to improve the energy consumption while keeping good connectivity. In this paper, we explore how the communication range for each node evolves along the iterations of an energy saving self-adaptive transmission power controller when using different parameter sets in an outdoor scenario, providing a WSAN that automatically adapts to surrounding changes keeping good connectivity. The results obtained in this paper show how the parameters with the best performance keep a k-connected network, where k is in the range of the desired node degree plus or minus a specified tolerance value. PMID:27187397

  5. Communication Range Dynamics and Performance Analysis for a Self-Adaptive Transmission Power Controller.

    PubMed

    Lucas Martínez, Néstor; Martínez Ortega, José-Fernán; Hernández Díaz, Vicente; Del Toro Matamoros, Raúl M

    2016-01-01

    The deployment of the nodes in a Wireless Sensor and Actuator Network (WSAN) is typically restricted by the sensing and acting coverage. This implies that the locations of the nodes may be, and usually are, not optimal from the point of view of the radio communication. Additionally, when the transmission power is tuned for those locations, there are other unpredictable factors that can cause connectivity failures, like interferences, signal fading due to passing objects and, of course, radio irregularities. A control-based self-adaptive system is a typical solution to improve the energy consumption while keeping good connectivity. In this paper, we explore how the communication range for each node evolves along the iterations of an energy saving self-adaptive transmission power controller when using different parameter sets in an outdoor scenario, providing a WSAN that automatically adapts to surrounding changes keeping good connectivity. The results obtained in this paper show how the parameters with the best performance keep a k-connected network, where k is in the range of the desired node degree plus or minus a specified tolerance value. PMID:27187397

  6. Beam width and transmitter power adaptive to tracking system performance for free-space optical communication.

    PubMed

    Arnon, S; Rotman, S; Kopeika, N S

    1997-08-20

    The basic free-space optical communication system includes at least two satellites. To communicate between them, the transmitter satellite must track the beacon of the receiver satellite and point the information optical beam in its direction. Optical tracking and pointing systems for free space suffer during tracking from high-amplitude vibration because of background radiation from interstellar objects such as the Sun, Moon, Earth, and stars in the tracking field of view or the mechanical impact from satellite internal and external sources. The vibrations of beam pointing increase the bit error rate and jam communication between the two satellites. One way to overcome this problem is to increase the satellite receiver beacon power. However, this solution requires increased power consumption and weight, both of which are disadvantageous in satellite development. Considering these facts, we derive a mathematical model of a communication system that adapts optimally the transmitter beam width and the transmitted power to the tracking system performance. Based on this model, we investigate the performance of a communication system with discrete element optical phased array transmitter telescope gain. An example for a practical communication system between a Low Earth Orbit Satellite and a Geostationary Earth Orbit Satellite is presented. From the results of this research it can be seen that a four-element adaptive transmitter telescope is sufficient to compensate for vibration amplitude doubling. The benefits of the proposed model are less required transmitter power and improved communication system performance. PMID:18259455

  7. Beam width and transmitter power adaptive to tracking system performance for free-space optical communication.

    PubMed

    Arnon, S; Rotman, S; Kopeika, N S

    1997-08-20

    The basic free-space optical communication system includes at least two satellites. To communicate between them, the transmitter satellite must track the beacon of the receiver satellite and point the information optical beam in its direction. Optical tracking and pointing systems for free space suffer during tracking from high-amplitude vibration because of background radiation from interstellar objects such as the Sun, Moon, Earth, and stars in the tracking field of view or the mechanical impact from satellite internal and external sources. The vibrations of beam pointing increase the bit error rate and jam communication between the two satellites. One way to overcome this problem is to increase the satellite receiver beacon power. However, this solution requires increased power consumption and weight, both of which are disadvantageous in satellite development. Considering these facts, we derive a mathematical model of a communication system that adapts optimally the transmitter beam width and the transmitted power to the tracking system performance. Based on this model, we investigate the performance of a communication system with discrete element optical phased array transmitter telescope gain. An example for a practical communication system between a Low Earth Orbit Satellite and a Geostationary Earth Orbit Satellite is presented. From the results of this research it can be seen that a four-element adaptive transmitter telescope is sufficient to compensate for vibration amplitude doubling. The benefits of the proposed model are less required transmitter power and improved communication system performance.

  8. Optimal adaptation of equivalent factor of equivalent consumption minimization strategy for fuel cell hybrid electric vehicles under active state inequality constraints

    NASA Astrophysics Data System (ADS)

    Han, Jihun; Park, Youngjin; Kum, Dongsuk

    2014-12-01

    Among existing energy management strategies (EMSs) for fuel cell hybrid electric vehicles (FCHEV), the equivalent consumption minimization strategy (ECMS) is often considered as a practical approach because it can be implemented in real-time, while achieving near-optimal performance. However, under real-world driving conditions with uncertainties such as hilly roads, both near-optimality and charge-sustenance of ECMS are not guaranteed unless the equivalent factor (EF) is optimally adjusted in real-time. In this paper, a methodology of extracting the globally optimal EF trajectory from dynamic programming (DP) solution is proposed for the design of EF adaptation strategies. In order to illustrate the performance and process of the extraction method, a FCHEV energy management problem under hilly road conditions is investigated as a case study. The main goal is to learn how EF should be adjusted and the impact of EF adaptation on fuel economy under several hilly road cases. Using the extraction method, the DP-based EF is computed, and its performance is compared with those of Pontryagin's minimum principle (PMP) and conventional ECMS. The results show that the optimal EF adaptation significantly improves fuel economy when the battery SoC constraint becomes active, and thus EF must be properly adjusted under severely hilly road conditions.

  9. Accelerated optimization and automated discovery with covariance matrix adaptation for experimental quantum control

    SciTech Connect

    Roslund, Jonathan; Shir, Ofer M.; Rabitz, Herschel; Baeck, Thomas

    2009-10-15

    Optimization of quantum systems by closed-loop adaptive pulse shaping offers a rich domain for the development and application of specialized evolutionary algorithms. Derandomized evolution strategies (DESs) are presented here as a robust class of optimizers for experimental quantum control. The combination of stochastic and quasi-local search embodied by these algorithms is especially amenable to the inherent topology of quantum control landscapes. Implementation of DES in the laboratory results in efficiency gains of up to {approx}9 times that of the standard genetic algorithm, and thus is a promising tool for optimization of unstable or fragile systems. The statistical learning upon which these algorithms are predicated also provide the means for obtaining a control problem's Hessian matrix with no additional experimental overhead. The forced optimal covariance adaptive learning (FOCAL) method is introduced to enable retrieval of the Hessian matrix, which can reveal information about the landscape's local structure and dynamic mechanism. Exploitation of such algorithms in quantum control experiments should enhance their efficiency and provide additional fundamental insights.

  10. Perturbing engine performance measurements to determine optimal engine control settings

    DOEpatents

    Jiang, Li; Lee, Donghoon; Yilmaz, Hakan; Stefanopoulou, Anna

    2014-12-30

    Methods and systems for optimizing a performance of a vehicle engine are provided. The method includes determining an initial value for a first engine control parameter based on one or more detected operating conditions of the vehicle engine, determining a value of an engine performance variable, and artificially perturbing the determined value of the engine performance variable. The initial value for the first engine control parameter is then adjusted based on the perturbed engine performance variable causing the engine performance variable to approach a target engine performance variable. Operation of the vehicle engine is controlled based on the adjusted initial value for the first engine control parameter. These acts are repeated until the engine performance variable approaches the target engine performance variable.

  11. Reinforcement learning for adaptive optimal control of unknown continuous-time nonlinear systems with input constraints

    NASA Astrophysics Data System (ADS)

    Yang, Xiong; Liu, Derong; Wang, Ding

    2014-03-01

    In this paper, an adaptive reinforcement learning-based solution is developed for the infinite-horizon optimal control problem of constrained-input continuous-time nonlinear systems in the presence of nonlinearities with unknown structures. Two different types of neural networks (NNs) are employed to approximate the Hamilton-Jacobi-Bellman equation. That is, an recurrent NN is constructed to identify the unknown dynamical system, and two feedforward NNs are used as the actor and the critic to approximate the optimal control and the optimal cost, respectively. Based on this framework, the action NN and the critic NN are tuned simultaneously, without the requirement for the knowledge of system drift dynamics. Moreover, by using Lyapunov's direct method, the weights of the action NN and the critic NN are guaranteed to be uniformly ultimately bounded, while keeping the closed-loop system stable. To demonstrate the effectiveness of the present approach, simulation results are illustrated.

  12. Neural-network-observer-based optimal control for unknown nonlinear systems using adaptive dynamic programming

    NASA Astrophysics Data System (ADS)

    Liu, Derong; Huang, Yuzhu; Wang, Ding; Wei, Qinglai

    2013-09-01

    In this paper, an observer-based optimal control scheme is developed for unknown nonlinear systems using adaptive dynamic programming (ADP) algorithm. First, a neural-network (NN) observer is designed to estimate system states. Then, based on the observed states, a neuro-controller is constructed via ADP method to obtain the optimal control. In this design, two NN structures are used: a three-layer NN is used to construct the observer which can be applied to systems with higher degrees of nonlinearity and without a priori knowledge of system dynamics, and a critic NN is employed to approximate the value function. The optimal control law is computed using the critic NN and the observer NN. Uniform ultimate boundedness of the closed-loop system is guaranteed. The actor, critic, and observer structures are all implemented in real-time, continuously and simultaneously. Finally, simulation results are presented to demonstrate the effectiveness of the proposed control scheme.

  13. Error bounds of adaptive dynamic programming algorithms for solving undiscounted optimal control problems.

    PubMed

    Liu, Derong; Li, Hongliang; Wang, Ding

    2015-06-01

    In this paper, we establish error bounds of adaptive dynamic programming algorithms for solving undiscounted infinite-horizon optimal control problems of discrete-time deterministic nonlinear systems. We consider approximation errors in the update equations of both value function and control policy. We utilize a new assumption instead of the contraction assumption in discounted optimal control problems. We establish the error bounds for approximate value iteration based on a new error condition. Furthermore, we also establish the error bounds for approximate policy iteration and approximate optimistic policy iteration algorithms. It is shown that the iterative approximate value function can converge to a finite neighborhood of the optimal value function under some conditions. To implement the developed algorithms, critic and action neural networks are used to approximate the value function and control policy, respectively. Finally, a simulation example is given to demonstrate the effectiveness of the developed algorithms.

  14. Improving the Hydrodynamic Performance of Diffuser Vanes via Shape Optimization

    NASA Technical Reports Server (NTRS)

    Goel, Tushar; Dorney, Daniel J.; Haftka, Raphael T.; Shyy, Wei

    2007-01-01

    The performance of a diffuser in a pump stage depends on its configuration and placement within the stage. The influence of vane shape on the hydrodynamic performance of a diffuser has been studied. The goal of this effort has been to improve the performance of a pump stage by optimizing the shape of the diffuser vanes. The shape of the vanes was defined using Bezier curves and circular arcs. Surrogate model based tools were used to identify regions of the vane that have a strong influence on its performance. Optimization of the vane shape, in the absence of manufacturing, and stress constraints, led to a nearly nine percent reduction in the total pressure losses compared to the baseline design by reducing the extent of the base separation.

  15. Nuclear performance optimization of the molten-salt fusion breeder

    SciTech Connect

    Lee, J.D.; Bandini, B.R.

    1986-06-05

    Improved nuclear analysis, including the treatment of resonance and spatial self-shielding, coupled with an optimization procedure, has resulted in an improved performance estimate for the molten salt blanket. Net U-233 breeding ratio ranges between 0.58 and 0.63, and blanket energy multiplication ranges between 1.8 and 1.9.

  16. Optimization and Performance Modeling of Stencil Computations on Modern Microprocessors

    SciTech Connect

    Datta, Kaushik; Kamil, Shoaib; Williams, Samuel; Oliker, Leonid; Shalf, John; Yelick, Katherine

    2007-06-01

    Stencil-based kernels constitute the core of many important scientific applications on blockstructured grids. Unfortunately, these codes achieve a low fraction of peak performance, due primarily to the disparity between processor and main memory speeds. In this paper, we explore the impact of trends in memory subsystems on a variety of stencil optimization techniques and develop performance models to analytically guide our optimizations. Our work targets cache reuse methodologies across single and multiple stencil sweeps, examining cache-aware algorithms as well as cache-oblivious techniques on the Intel Itanium2, AMD Opteron, and IBM Power5. Additionally, we consider stencil computations on the heterogeneous multicore design of the Cell processor, a machine with an explicitly managed memory hierarchy. Overall our work represents one of the most extensive analyses of stencil optimizations and performance modeling to date. Results demonstrate that recent trends in memory system organization have reduced the efficacy of traditional cache-blocking optimizations. We also show that a cache-aware implementation is significantly faster than a cache-oblivious approach, while the explicitly managed memory on Cell enables the highest overall efficiency: Cell attains 88% of algorithmic peak while the best competing cache-based processor achieves only 54% of algorithmic peak performance.

  17. An optimization study of the motion table performance.

    PubMed

    Hsiao, Y F; Kuo, W M; Chang, Y T; Tarng, Y S

    2010-01-01

    This paper investigates the optimal selection of processing parameters for motion table performance. The main objective of the mechanism of a one-axis servo motor table is to avoid vibration, thereby reducing experimental error. This experimental controller uses a grey-based Taguchi method to make a quality evaluation of three table characteristics; displacement, arriving time, and torsion. It is shown that the multiple response performance characteristics are greatly improved through this study.

  18. Performance optimization of a pneumatic wave energy conversion device

    NASA Astrophysics Data System (ADS)

    Surko, S. W.

    1982-08-01

    The purpose of this study was, for the first time, to optimize the performance of a pneumatic wave energy conversion device. The experiments of Jolly and Newmaster (1979) and Trop and Casey (1980) left a capture chamber and turbine for further investigation. To optimize the system performance the turbine had to be first analyzed so that its power performance curves could be determined. These curves were needed to help define the possible overall performance of the system, and for the impedance matching of the system necessary for performance optimization. With this knowledge, an appropriate generator was purchased and a generator-turbine linkage designed and built. The completed system was then analyzed in the 380 ft wave tank at the U.S. Naval Academy to establish its optimum performance. From the research it is clear that pneumatic wave energy conversion is a promising concept. With several hundred of these devices situated some 100 km off the coast of the Pacific Northwest each device would be producing from 50 to 200 kW which would be transferred back to shore.

  19. An optimal dynamic inversion-based neuro-adaptive approach for treatment of chronic myelogenous leukemia.

    PubMed

    Padhi, Radhakant; Kothari, Mangal

    2007-09-01

    Combining the advanced techniques of optimal dynamic inversion and model-following neuro-adaptive control design, an innovative technique is presented to design an automatic drug administration strategy for effective treatment of chronic myelogenous leukemia (CML). A recently developed nonlinear mathematical model for cell dynamics is used to design the controller (medication dosage). First, a nominal controller is designed based on the principle of optimal dynamic inversion. This controller can treat the nominal model patients (patients who can be described by the mathematical model used here with the nominal parameter values) effectively. However, since the system parameters for a realistic model patient can be different from that of the nominal model patients, simulation studies for such patients indicate that the nominal controller is either inefficient or, worse, ineffective; i.e. the trajectory of the number of cancer cells either shows non-satisfactory transient behavior or it grows in an unstable manner. Hence, to make the drug dosage history more realistic and patient-specific, a model-following neuro-adaptive controller is augmented to the nominal controller. In this adaptive approach, a neural network trained online facilitates a new adaptive controller. The training process of the neural network is based on Lyapunov stability theory, which guarantees both stability of the cancer cell dynamics as well as boundedness of the network weights. From simulation studies, this adaptive control design approach is found to be very effective to treat the CML disease for realistic patients. Sufficient generality is retained in the mathematical developments so that the technique can be applied to other similar nonlinear control design problems as well.

  20. Hull-form optimization of KSUEZMAX to enhance resistance performance

    NASA Astrophysics Data System (ADS)

    Park, Jong-Heon; Choi, Jung-Eun; Chun, Ho-Hwan

    2015-01-01

    This paper deploys optimization techniques to obtain the optimum hull form of KSUEZMAX at the conditions of full-load draft and design speed. The processes have been carried out using a RaPID-HOP program. The bow and the stern hull-forms are optimized separately without altering neither, and the resulting versions of the two are then combined. Objective functions are the minimum values of wave-making and viscous pressure resistance coefficients for the bow and stern. Parametric modification functions for the bow hull-form variation are SAC shape, section shape (U-V type, DLWL type), bulb shape (bulb height and size); and those for the stern are SAC and section shape (U-V type, DLWL type). WAVIS version 1.3 code is used for the potential and the viscous-flow solver. Prior to the optimization, a parametric study has been conducted to observe the effects of design parameters on the objective functions. SQP has been applied for the optimization algorithm. The model tests have been conducted at a towing tank to evaluate the resistance performance of the optimized hull-form. It has been noted that the optimized hull-form brings 2.4% and 6.8% reduction in total and residual resistance coefficients compared to those of the original hull-form. The propulsive efficiency increases by 2.0% and the delivered power is reduced 3.7%, whereas the propeller rotating speed increases slightly by 0.41 rpm.

  1. Dynamic Aberration Correction for Conformal Window of High-Speed Aircraft Using Optimized Model-Based Wavefront Sensorless Adaptive Optics.

    PubMed

    Dong, Bing; Li, Yan; Han, Xin-Li; Hu, Bin

    2016-09-02

    For high-speed aircraft, a conformal window is used to optimize the aerodynamic performance. However, the local shape of the conformal window leads to large amounts of dynamic aberrations varying with look angle. In this paper, deformable mirror (DM) and model-based wavefront sensorless adaptive optics (WSLAO) are used for dynamic aberration correction of an infrared remote sensor equipped with a conformal window and scanning mirror. In model-based WSLAO, aberration is captured using Lukosz mode, and we use the low spatial frequency content of the image spectral density as the metric function. Simulations show that aberrations induced by the conformal window are dominated by some low-order Lukosz modes. To optimize the dynamic correction, we can only correct dominant Lukosz modes and the image size can be minimized to reduce the time required to compute the metric function. In our experiment, a 37-channel DM is used to mimic the dynamic aberration of conformal window with scanning rate of 10 degrees per second. A 52-channel DM is used for correction. For a 128 × 128 image, the mean value of image sharpness during dynamic correction is 1.436 × 10(-5) in optimized correction and is 1.427 × 10(-5) in un-optimized correction. We also demonstrated that model-based WSLAO can achieve convergence two times faster than traditional stochastic parallel gradient descent (SPGD) method.

  2. Dynamic Aberration Correction for Conformal Window of High-Speed Aircraft Using Optimized Model-Based Wavefront Sensorless Adaptive Optics.

    PubMed

    Dong, Bing; Li, Yan; Han, Xin-Li; Hu, Bin

    2016-01-01

    For high-speed aircraft, a conformal window is used to optimize the aerodynamic performance. However, the local shape of the conformal window leads to large amounts of dynamic aberrations varying with look angle. In this paper, deformable mirror (DM) and model-based wavefront sensorless adaptive optics (WSLAO) are used for dynamic aberration correction of an infrared remote sensor equipped with a conformal window and scanning mirror. In model-based WSLAO, aberration is captured using Lukosz mode, and we use the low spatial frequency content of the image spectral density as the metric function. Simulations show that aberrations induced by the conformal window are dominated by some low-order Lukosz modes. To optimize the dynamic correction, we can only correct dominant Lukosz modes and the image size can be minimized to reduce the time required to compute the metric function. In our experiment, a 37-channel DM is used to mimic the dynamic aberration of conformal window with scanning rate of 10 degrees per second. A 52-channel DM is used for correction. For a 128 × 128 image, the mean value of image sharpness during dynamic correction is 1.436 × 10(-5) in optimized correction and is 1.427 × 10(-5) in un-optimized correction. We also demonstrated that model-based WSLAO can achieve convergence two times faster than traditional stochastic parallel gradient descent (SPGD) method. PMID:27598161

  3. Dynamic Aberration Correction for Conformal Window of High-Speed Aircraft Using Optimized Model-Based Wavefront Sensorless Adaptive Optics

    PubMed Central

    Dong, Bing; Li, Yan; Han, Xin-li; Hu, Bin

    2016-01-01

    For high-speed aircraft, a conformal window is used to optimize the aerodynamic performance. However, the local shape of the conformal window leads to large amounts of dynamic aberrations varying with look angle. In this paper, deformable mirror (DM) and model-based wavefront sensorless adaptive optics (WSLAO) are used for dynamic aberration correction of an infrared remote sensor equipped with a conformal window and scanning mirror. In model-based WSLAO, aberration is captured using Lukosz mode, and we use the low spatial frequency content of the image spectral density as the metric function. Simulations show that aberrations induced by the conformal window are dominated by some low-order Lukosz modes. To optimize the dynamic correction, we can only correct dominant Lukosz modes and the image size can be minimized to reduce the time required to compute the metric function. In our experiment, a 37-channel DM is used to mimic the dynamic aberration of conformal window with scanning rate of 10 degrees per second. A 52-channel DM is used for correction. For a 128 × 128 image, the mean value of image sharpness during dynamic correction is 1.436 × 10−5 in optimized correction and is 1.427 × 10−5 in un-optimized correction. We also demonstrated that model-based WSLAO can achieve convergence two times faster than traditional stochastic parallel gradient descent (SPGD) method. PMID:27598161

  4. Performance and optimization of X-ray grating interferometry.

    PubMed

    Thuering, T; Stampanoni, M

    2014-03-01

    The monochromatic and polychromatic performance of a grating interferometer is theoretically analysed. The smallest detectable refraction angle is used as a metric for the efficiency in acquiring a differential phase-contrast image. Analytical formulae for the visibility and the smallest detectable refraction angle are derived for Talbot-type and Talbot-Lau-type interferometers, respectively, providing a framework for the optimization of the geometry. The polychromatic performance of a grating interferometer is investigated analytically by calculating the energy-dependent interference fringe visibility, the spectral acceptance and the polychromatic interference fringe visibility. The optimization of grating interferometry is a crucial step for the design of application-specific systems with maximum performance.

  5. A Study on the Optimization Performance of Fireworks and Cuckoo Search Algorithms in Laser Machining Processes

    NASA Astrophysics Data System (ADS)

    Goswami, D.; Chakraborty, S.

    2014-11-01

    Laser machining is a promising non-contact process for effective machining of difficult-to-process advanced engineering materials. Increasing interest in the use of lasers for various machining operations can be attributed to its several unique advantages, like high productivity, non-contact processing, elimination of finishing operations, adaptability to automation, reduced processing cost, improved product quality, greater material utilization, minimum heat-affected zone and green manufacturing. To achieve the best desired machining performance and high quality characteristics of the machined components, it is extremely important to determine the optimal values of the laser machining process parameters. In this paper, fireworks algorithm and cuckoo search (CS) algorithm are applied for single as well as multi-response optimization of two laser machining processes. It is observed that although almost similar solutions are obtained for both these algorithms, CS algorithm outperforms fireworks algorithm with respect to average computation time, convergence rate and performance consistency.

  6. An Automated, Adaptive Framework for Optimizing Preprocessing Pipelines in Task-Based Functional MRI.

    PubMed

    Churchill, Nathan W; Spring, Robyn; Afshin-Pour, Babak; Dong, Fan; Strother, Stephen C

    2015-01-01

    BOLD fMRI is sensitive to blood-oxygenation changes correlated with brain function; however, it is limited by relatively weak signal and significant noise confounds. Many preprocessing algorithms have been developed to control noise and improve signal detection in fMRI. Although the chosen set of preprocessing and analysis steps (the "pipeline") significantly affects signal detection, pipelines are rarely quantitatively validated in the neuroimaging literature, due to complex preprocessing interactions. This paper outlines and validates an adaptive resampling framework for evaluating and optimizing preprocessing choices by optimizing data-driven metrics of task prediction and spatial reproducibility. Compared to standard "fixed" preprocessing pipelines, this optimization approach significantly improves independent validation measures of within-subject test-retest, and between-subject activation overlap, and behavioural prediction accuracy. We demonstrate that preprocessing choices function as implicit model regularizers, and that improvements due to pipeline optimization generalize across a range of simple to complex experimental tasks and analysis models. Results are shown for brief scanning sessions (<3 minutes each), demonstrating that with pipeline optimization, it is possible to obtain reliable results and brain-behaviour correlations in relatively small datasets.

  7. An Automated, Adaptive Framework for Optimizing Preprocessing Pipelines in Task-Based Functional MRI

    PubMed Central

    Churchill, Nathan W.; Spring, Robyn; Afshin-Pour, Babak; Dong, Fan; Strother, Stephen C.

    2015-01-01

    BOLD fMRI is sensitive to blood-oxygenation changes correlated with brain function; however, it is limited by relatively weak signal and significant noise confounds. Many preprocessing algorithms have been developed to control noise and improve signal detection in fMRI. Although the chosen set of preprocessing and analysis steps (the “pipeline”) significantly affects signal detection, pipelines are rarely quantitatively validated in the neuroimaging literature, due to complex preprocessing interactions. This paper outlines and validates an adaptive resampling framework for evaluating and optimizing preprocessing choices by optimizing data-driven metrics of task prediction and spatial reproducibility. Compared to standard “fixed” preprocessing pipelines, this optimization approach significantly improves independent validation measures of within-subject test-retest, and between-subject activation overlap, and behavioural prediction accuracy. We demonstrate that preprocessing choices function as implicit model regularizers, and that improvements due to pipeline optimization generalize across a range of simple to complex experimental tasks and analysis models. Results are shown for brief scanning sessions (<3 minutes each), demonstrating that with pipeline optimization, it is possible to obtain reliable results and brain-behaviour correlations in relatively small datasets. PMID:26161667

  8. An auto-adaptive optimization approach for targeting nonpoint source pollution control practices

    PubMed Central

    Chen, Lei; Wei, Guoyuan; Shen, Zhenyao

    2015-01-01

    To solve computationally intensive and technically complex control of nonpoint source pollution, the traditional genetic algorithm was modified into an auto-adaptive pattern, and a new framework was proposed by integrating this new algorithm with a watershed model and an economic module. Although conceptually simple and comprehensive, the proposed algorithm would search automatically for those Pareto-optimality solutions without a complex calibration of optimization parameters. The model was applied in a case study in a typical watershed of the Three Gorges Reservoir area, China. The results indicated that the evolutionary process of optimization was improved due to the incorporation of auto-adaptive parameters. In addition, the proposed algorithm outperformed the state-of-the-art existing algorithms in terms of convergence ability and computational efficiency. At the same cost level, solutions with greater pollutant reductions could be identified. From a scientific viewpoint, the proposed algorithm could be extended to other watersheds to provide cost-effective configurations of BMPs. PMID:26487474

  9. Adaptive optimal control of unknown constrained-input systems using policy iteration and neural networks.

    PubMed

    Modares, Hamidreza; Lewis, Frank L; Naghibi-Sistani, Mohammad-Bagher

    2013-10-01

    This paper presents an online policy iteration (PI) algorithm to learn the continuous-time optimal control solution for unknown constrained-input systems. The proposed PI algorithm is implemented on an actor-critic structure where two neural networks (NNs) are tuned online and simultaneously to generate the optimal bounded control policy. The requirement of complete knowledge of the system dynamics is obviated by employing a novel NN identifier in conjunction with the actor and critic NNs. It is shown how the identifier weights estimation error affects the convergence of the critic NN. A novel learning rule is developed to guarantee that the identifier weights converge to small neighborhoods of their ideal values exponentially fast. To provide an easy-to-check persistence of excitation condition, the experience replay technique is used. That is, recorded past experiences are used simultaneously with current data for the adaptation of the identifier weights. Stability of the whole system consisting of the actor, critic, system state, and system identifier is guaranteed while all three networks undergo adaptation. Convergence to a near-optimal control law is also shown. The effectiveness of the proposed method is illustrated with a simulation example. PMID:24808590

  10. Concurrently adjusting interrelated control parameters to achieve optimal engine performance

    SciTech Connect

    Jiang, Li; Lee, Donghoon; Yilmaz, Hakan; Stefanopoulou, Anna

    2015-12-01

    Methods and systems for real-time engine control optimization are provided. A value of an engine performance variable is determined, a value of a first operating condition and a value of a second operating condition of a vehicle engine are detected, and initial values for a first engine control parameter and a second engine control parameter are determined based on the detected first operating condition and the detected second operating condition. The initial values for the first engine control parameter and the second engine control parameter are adjusted based on the determined value of the engine performance variable to cause the engine performance variable to approach a target engine performance variable. In order to cause the engine performance variable to approach the target engine performance variable, adjusting the initial value for the first engine control parameter necessitates a corresponding adjustment of the initial value for the second engine control parameter.

  11. Development of a new adaptive ordinal approach to continuous-variable probabilistic optimization.

    SciTech Connect

    Romero, Vicente JosÔe; Chen, Chun-Hung (George Mason University, Fairfax, VA)

    2006-11-01

    A very general and robust approach to solving continuous-variable optimization problems involving uncertainty in the objective function is through the use of ordinal optimization. At each step in the optimization problem, improvement is based only on a relative ranking of the uncertainty effects on local design alternatives, rather than on precise quantification of the effects. One simply asks ''Is that alternative better or worse than this one?'' -not ''HOW MUCH better or worse is that alternative to this one?'' The answer to the latter question requires precise characterization of the uncertainty--with the corresponding sampling/integration expense for precise resolution. However, in this report we demonstrate correct decision-making in a continuous-variable probabilistic optimization problem despite extreme vagueness in the statistical characterization of the design options. We present a new adaptive ordinal method for probabilistic optimization in which the trade-off between computational expense and vagueness in the uncertainty characterization can be conveniently managed in various phases of the optimization problem to make cost-effective stepping decisions in the design space. Spatial correlation of uncertainty in the continuous-variable design space is exploited to dramatically increase method efficiency. Under many circumstances the method appears to have favorable robustness and cost-scaling properties relative to other probabilistic optimization methods, and uniquely has mechanisms for quantifying and controlling error likelihood in design-space stepping decisions. The method is asymptotically convergent to the true probabilistic optimum, so could be useful as a reference standard against which the efficiency and robustness of other methods can be compared--analogous to the role that Monte Carlo simulation plays in uncertainty propagation.

  12. Convergence and quasi-optimality of adaptive FEM with inhomogeneous Dirichlet data☆

    PubMed Central

    Feischl, M.; Page, M.; Praetorius, D.

    2014-01-01

    We consider the solution of a second order elliptic PDE with inhomogeneous Dirichlet data by means of adaptive lowest-order FEM. As is usually done in practice, the given Dirichlet data are discretized by nodal interpolation. As model example serves the Poisson equation with mixed Dirichlet–Neumann boundary conditions. For error estimation, we use an edge-based residual error estimator which replaces the volume residual contributions by edge oscillations. For 2D, we prove convergence of the adaptive algorithm even with optimal convergence rate. For 2D and 3D, we show convergence if the nodal interpolation operator is replaced by the L2-projection or the Scott–Zhang quasi-interpolation operator. As a byproduct of the proof, we show that the Scott–Zhang operator converges pointwise to a limiting operator as the mesh is locally refined. This property might be of independent interest besides the current application. Finally, numerical experiments conclude the work. PMID:24391306

  13. Joint Robust Transmit/Receive Adaptive Beamforming for MIMO Radar Using Probability-Constrained Optimization

    NASA Astrophysics Data System (ADS)

    Zhang, Weiyu; Vorobyov, Sergiy A.

    2016-01-01

    A joint robust transmit/receive adaptive beamforming for multiple-input multipleoutput (MIMO) radar based on probability-constrained optimization approach is developed in the case of Gaussian and arbitrary distributed mismatch present in both the transmit and receive signal steering vectors. A tight lower bound of the probability constraint is also derived by using duality theory. The formulated probability-constrained robust beamforming problem is nonconvex and NP-hard. However, we reformulate its cost function into a bi-quadratic function while the probability constraint splits into transmit and receive parts. Then, a block coordinate descent method based on second-order cone programming is developed to address the biconvex problem. Simulation results show an improved robustness of the proposed beamforming method as compared to the worst-case and other existing state-of-the-art joint transmit/receive robust adaptive beamforming methods for MIMO radar.

  14. Field of view selection for optimal airborne imaging sensor performance

    NASA Astrophysics Data System (ADS)

    Goss, Tristan M.; Barnard, P. Werner; Fildis, Halidun; Erbudak, Mustafa; Senger, Tolga; Alpman, Mehmet E.

    2014-05-01

    The choice of the Field of View (FOV) of imaging sensors used in airborne targeting applications has major impact on the overall performance of the system. Conducting a market survey from published data on sensors used in stabilized airborne targeting systems shows a trend of ever narrowing FOVs housed in smaller and lighter volumes. This approach promotes the ever increasing geometric resolution provided by narrower FOVs, while it seemingly ignores the influences the FOV selection has on the sensor's sensitivity, the effects of diffraction, the influences of sight line jitter and collectively the overall system performance. This paper presents a trade-off methodology to select the optimal FOV for an imaging sensor that is limited in aperture diameter by mechanical constraints (such as space/volume available and window size) by balancing the influences FOV has on sensitivity and resolution and thereby optimizing the system's performance. The methodology may be applied to staring array based imaging sensors across all wavebands from visible/day cameras through to long wave infrared thermal imagers. Some examples of sensor analysis applying the trade-off methodology are given that highlights the performance advantages that can be gained by maximizing the aperture diameters and choosing the optimal FOV for an imaging sensor used in airborne targeting applications.

  15. Airbag Landing Impact Performance Optimization for the Orion Crew Module

    NASA Technical Reports Server (NTRS)

    Lee, Timothy J.; McKinney, John; Corliss, James M.

    2008-01-01

    This report will discuss the use of advanced simulation techniques to optimize the performance of the proposed Orion Crew Module airbag landing system design. The Boeing Company and the National Aeronautic and Space Administration s Langley Research Center collaborated in the analysis of the proposed airbag landing system for the next generation space shuttle replacement, the Orion spacecraft. Using LS-DYNA to simulate the Crew Module landing impacts, two main objectives were established and achieved: the investigation of potential methods of optimizing the airbag performance in order to reduce rebound on the anti-bottoming bags, lower overall landing loads, and increase overall Crew Module stability; and the determination of the Crew Module stability and load boundaries using the optimized airbag design, based on the potential Crew Module landing pitch angles and ground slopes in both the center of gravity forward and aft configurations. This paper describes the optimization and stability and load boundary studies and presents a summary of the results obtained and key lessons learned from this analysis.

  16. Challenges when performing economic optimization of waste treatment: A review

    SciTech Connect

    Juul, N.; Münster, M.; Ravn, H.; Söderman, M. Ljunggren

    2013-09-15

    Highlights: • Review of main optimization tools in the field of waste management. • Different optimization methods are applied. • Different fractions are analyzed. • There is focus on different parameters in different geographical regions. • More research is needed which encompasses both recycling and energy solutions. - Abstract: Strategic and operational decisions in waste management, in particular with respect to investments in new treatment facilities, are needed due to a number of factors, including continuously increasing amounts of waste, political demands for efficient utilization of waste resources, and the decommissioning of existing waste treatment facilities. Optimization models can assist in ensuring that these investment strategies are economically feasible. Various economic optimization models for waste treatment have been developed which focus on different parameters. Models focusing on transport are one example, but models focusing on energy production have also been developed, as well as models which take into account a plant’s economies of scale, environmental impact, material recovery and social costs. Finally, models combining different criteria for the selection of waste treatment methods in multi-criteria analysis have been developed. A thorough updated review of the existing models is presented, and the main challenges and crucial parameters that need to be taken into account when assessing the economic performance of waste treatment alternatives are identified. The review article will assist both policy-makers and model-developers involved in assessing the economic performance of waste treatment alternatives.

  17. Using condenser performance measurements to optimize condenser cleaning

    SciTech Connect

    Wolff, P.J.; March, A.; Pearson, H.S.

    1996-05-01

    Because plant personnel perform condenser monitoring primarily to determine cleaning schedules, the accuracy and repeatability of a technique should be viewed within the context of a condenser cleaning schedule. Lower accuracy is acceptable if the cleaning schedule arising from that system is identical to a cleaning schedule arising from a technique with higher accuracy. Three condenser performance monitors were implemented and compared within the context of a condenser cleaning schedule to determine the relative advantages of different condenser monitoring techniques. These systems include a novel on-line system that consists of an electromagnetic flowmeter and an RTD mounted in a compact waterproof cylinder, an overall on-line system, and routine plant tests. The fouling measurements from each system are used in an optimization program which automatically computes a cleaning schedule that minitrack the combined cost of cleaning and the cost of increased fuel consumption caused by condenser fouling. The cleaning schedules resulting from each system`s measurements are compared. The optimization routine is also used to evaluate the sensitivity of optimal cleaning schedules to fouling rate and of the cost in dollars for non-optimal cleaning.

  18. Adaptable structural synthesis using advanced analysis and optimization coupled by a computer operating system

    NASA Technical Reports Server (NTRS)

    Sobieszczanski-Sobieski, J.; Bhat, R. B.

    1979-01-01

    A finite element program is linked with a general purpose optimization program in a 'programing system' which includes user supplied codes that contain problem dependent formulations of the design variables, objective function and constraints. The result is a system adaptable to a wide spectrum of structural optimization problems. In a sample of numerical examples, the design variables are the cross-sectional dimensions and the parameters of overall shape geometry, constraints are applied to stresses, displacements, buckling and vibration characteristics, and structural mass is the objective function. Thin-walled, built-up structures and frameworks are included in the sample. Details of the system organization and characteristics of the component programs are given.

  19. A wavelet-optimized, very high order adaptive grid and order numerical method

    NASA Technical Reports Server (NTRS)

    Jameson, Leland

    1996-01-01

    Differencing operators of arbitrarily high order can be constructed by interpolating a polynomial through a set of data followed by differentiation of this polynomial and finally evaluation of the polynomial at the point where a derivative approximation is desired. Furthermore, the interpolating polynomial can be constructed from algebraic, trigonometric, or, perhaps exponential polynomials. This paper begins with a comparison of such differencing operator construction. Next, the issue of proper grids for high order polynomials is addressed. Finally, an adaptive numerical method is introduced which adapts the numerical grid and the order of the differencing operator depending on the data. The numerical grid adaptation is performed on a Chebyshev grid. That is, at each level of refinement the grid is a Chebvshev grid and this grid is refined locally based on wavelet analysis.

  20. A DVH-guided IMRT optimization algorithm for automatic treatment planning and adaptive radiotherapy replanning

    SciTech Connect

    Zarepisheh, Masoud; Li, Nan; Long, Troy; Romeijn, H. Edwin; Tian, Zhen; Jia, Xun; Jiang, Steve B.

    2014-06-15

    Purpose: To develop a novel algorithm that incorporates prior treatment knowledge into intensity modulated radiation therapy optimization to facilitate automatic treatment planning and adaptive radiotherapy (ART) replanning. Methods: The algorithm automatically creates a treatment plan guided by the DVH curves of a reference plan that contains information on the clinician-approved dose-volume trade-offs among different targets/organs and among different portions of a DVH curve for an organ. In ART, the reference plan is the initial plan for the same patient, while for automatic treatment planning the reference plan is selected from a library of clinically approved and delivered plans of previously treated patients with similar medical conditions and geometry. The proposed algorithm employs a voxel-based optimization model and navigates the large voxel-based Pareto surface. The voxel weights are iteratively adjusted to approach a plan that is similar to the reference plan in terms of the DVHs. If the reference plan is feasible but not Pareto optimal, the algorithm generates a Pareto optimal plan with the DVHs better than the reference ones. If the reference plan is too restricting for the new geometry, the algorithm generates a Pareto plan with DVHs close to the reference ones. In both cases, the new plans have similar DVH trade-offs as the reference plans. Results: The algorithm was tested using three patient cases and found to be able to automatically adjust the voxel-weighting factors in order to generate a Pareto plan with similar DVH trade-offs as the reference plan. The algorithm has also been implemented on a GPU for high efficiency. Conclusions: A novel prior-knowledge-based optimization algorithm has been developed that automatically adjust the voxel weights and generate a clinical optimal plan at high efficiency. It is found that the new algorithm can significantly improve the plan quality and planning efficiency in ART replanning and automatic treatment

  1. Partially supervised P300 speller adaptation for eventual stimulus timing optimization: target confidence is superior to error-related potential score as an uncertain label

    NASA Astrophysics Data System (ADS)

    Zeyl, Timothy; Yin, Erwei; Keightley, Michelle; Chau, Tom

    2016-04-01

    Objective. Error-related potentials (ErrPs) have the potential to guide classifier adaptation in BCI spellers, for addressing non-stationary performance as well as for online optimization of system parameters, by providing imperfect or partial labels. However, the usefulness of ErrP-based labels for BCI adaptation has not been established in comparison to other partially supervised methods. Our objective is to make this comparison by retraining a two-step P300 speller on a subset of confident online trials using naïve labels taken from speller output, where confidence is determined either by (i) ErrP scores, (ii) posterior target scores derived from the P300 potential, or (iii) a hybrid of these scores. We further wish to evaluate the ability of partially supervised adaptation and retraining methods to adjust to a new stimulus-onset asynchrony (SOA), a necessary step towards online SOA optimization. Approach. Eleven consenting able-bodied adults attended three online spelling sessions on separate days with feedback in which SOAs were set at 160 ms (sessions 1 and 2) and 80 ms (session 3). A post hoc offline analysis and a simulated online analysis were performed on sessions two and three to compare multiple adaptation methods. Area under the curve (AUC) and symbols spelled per minute (SPM) were the primary outcome measures. Main results. Retraining using supervised labels confirmed improvements of 0.9 percentage points (session 2, p < 0.01) and 1.9 percentage points (session 3, p < 0.05) in AUC using same-day training data over using data from a previous day, which supports classifier adaptation in general. Significance. Using posterior target score alone as a confidence measure resulted in the highest SPM of the partially supervised methods, indicating that ErrPs are not necessary to boost the performance of partially supervised adaptive classification. Partial supervision significantly improved SPM at a novel SOA, showing promise for eventual online SOA

  2. Preliminary flight evaluation of an engine performance optimization algorithm

    NASA Technical Reports Server (NTRS)

    Lambert, H. H.; Gilyard, G. B.; Chisholm, J. D.; Kerr, L. J.

    1991-01-01

    A performance seeking control (PSC) algorithm has undergone initial flight test evaluation in subsonic operation of a PW 1128 engined F-15. This algorithm is designed to optimize the quasi-steady performance of an engine for three primary modes: (1) minimum fuel consumption; (2) minimum fan turbine inlet temperature (FTIT); and (3) maximum thrust. The flight test results have verified a thrust specific fuel consumption reduction of 1 pct., up to 100 R decreases in FTIT, and increases of as much as 12 pct. in maximum thrust. PSC technology promises to be of value in next generation tactical and transport aircraft.

  3. Power and Performance Trade-offs for Space Time Adaptive Processing

    SciTech Connect

    Gawande, Nitin A.; Manzano Franco, Joseph B.; Tumeo, Antonino; Tallent, Nathan R.; Kerbyson, Darren J.; Hoisie, Adolfy

    2015-07-27

    Computational efficiency – performance relative to power or energy – is one of the most important concerns when designing RADAR processing systems. This paper analyzes power and performance trade-offs for a typical Space Time Adaptive Processing (STAP) application. We study STAP implementations for CUDA and OpenMP on two computationally efficient architectures, Intel Haswell Core I7-4770TE and NVIDIA Kayla with a GK208 GPU. We analyze the power and performance of STAP’s computationally intensive kernels across the two hardware testbeds. We also show the impact and trade-offs of GPU optimization techniques. We show that data parallelism can be exploited for efficient implementation on the Haswell CPU architecture. The GPU architecture is able to process large size data sets without increase in power requirement. The use of shared memory has a significant impact on the power requirement for the GPU. A balance between the use of shared memory and main memory access leads to an improved performance in a typical STAP application.

  4. A feature extraction method of the particle swarm optimization algorithm based on adaptive inertia weight and chaos optimization for Brillouin scattering spectra

    NASA Astrophysics Data System (ADS)

    Zhang, Yanjun; Zhao, Yu; Fu, Xinghu; Xu, Jinrui

    2016-10-01

    A novel particle swarm optimization algorithm based on adaptive inertia weight and chaos optimization is proposed for extracting the features of Brillouin scattering spectra. Firstly, the adaptive inertia weight parameter of the velocity is introduced to the basic particle swarm algorithm. Based on the current iteration number of particles and the adaptation value, the algorithm can change the weight coefficient and adjust the iteration speed of searching space for particles, so the local optimization ability can be enhanced. Secondly, the logical self-mapping chaotic search is carried out by using the chaos optimization in particle swarm optimization algorithm, which makes the particle swarm optimization algorithm jump out of local optimum. The novel algorithm is compared with finite element analysis-Levenberg Marquardt algorithm, particle swarm optimization-Levenberg Marquardt algorithm and particle swarm optimization algorithm by changing the linewidth, the signal-to-noise ratio and the linear weight ratio of Brillouin scattering spectra. Then the algorithm is applied to the feature extraction of Brillouin scattering spectra in different temperatures. The simulation analysis and experimental results show that this algorithm has a high fitting degree and small Brillouin frequency shift error for different linewidth, SNR and linear weight ratio. Therefore, this algorithm can be applied to the distributed optical fiber sensing system based on Brillouin optical time domain reflection, which can effectively improve the accuracy of Brillouin frequency shift extraction.

  5. Performance Trades Study for Robust Airfoil Shape Optimization

    NASA Technical Reports Server (NTRS)

    Li, Wu; Padula, Sharon

    2003-01-01

    From time to time, existing aircraft need to be redesigned for new missions with modified operating conditions such as required lift or cruise speed. This research is motivated by the needs of conceptual and preliminary design teams for smooth airfoil shapes that are similar to the baseline design but have improved drag performance over a range of flight conditions. The proposed modified profile optimization method (MPOM) modifies a large number of design variables to search for nonintuitive performance improvements, while avoiding off-design performance degradation. Given a good initial design, the MPOM generates fairly smooth airfoils that are better than the baseline without making drastic shape changes. Moreover, the MPOM allows users to gain valuable information by exploring performance trades over various design conditions. Four simulation cases of airfoil optimization in transonic viscous ow are included to demonstrate the usefulness of the MPOM as a performance trades study tool. Simulation results are obtained by solving fully turbulent Navier-Stokes equations and the corresponding discrete adjoint equations using an unstructured grid computational fluid dynamics code FUN2D.

  6. Threat of resource loss: The role of self-regulation in adaptive task performance.

    PubMed

    Niessen, Cornelia; Jimmieson, Nerina L

    2016-03-01

    Changes at work are often accompanied with the threat of, or actual, resource loss. Through an experiment, we investigated the detrimental effect of the threat of resource loss on adaptive task performance. Self-regulation (i.e., task focus and emotion control) was hypothesized to buffer the negative relationship between the threat of resource loss and adaptive task performance. Adaptation was conceptualized as relearning after a change in task execution rules. Threat of resource loss was manipulated for 100 participants undertaking an air traffic control task. Using discontinuous growth curve modeling, 2 kinds of adaptation--transition adaptation and reacquisition adaptation--were differentiated. The results showed that individuals who experienced the threat of resource loss had a stronger drop in performance (less transition adaptation) and a subsequent slower recovery (less reacquisition adaptation) compared with the control group who experienced no threat. Emotion control (but not task focus) moderated the relationship between the threat of resource loss and transition adaptation. In this respect, individuals who felt threatened but regulated their emotions performed better immediately after the task change (but not later on) compared with those individuals who felt threatened and did not regulate their emotions as well. However, later on, relearning (reacquisition adaptation) under the threat of resource loss was facilitated when individuals concentrated on the task at hand.

  7. Performance Study and Dynamic Optimization Design for Thread Pool Systems

    SciTech Connect

    Dongping Xu

    2004-12-19

    Thread pools have been widely used by many multithreaded applications. However, the determination of the pool size according to the application behavior still remains problematic. To automate this process, in this thesis we have developed a set of performance metrics for quantitatively analyzing thread pool performance. For our experiments, we built a thread pool system which provides a general framework for thread pool research. Based on this simulation environment, we studied the performance impact brought by the thread pool on different multithreaded applications. Additionally, the correlations between internal characterizations of thread pools and their throughput were also examined. We then proposed and evaluated a heuristic algorithm to dynamically determine the optimal thread pool size. The simulation results show that this approach is effective in improving overall application performance.

  8. Multi-Scale Simulation and Optimization of Lithium Battery Performance

    NASA Astrophysics Data System (ADS)

    Golmon, Stephanie L.

    The performance and degradation of lithium batteries strongly depends on electrochemical, mechanical, and thermal phenomena. While a large volume of work has focused on thermal management, mechanical phenomena relevant to battery design are not fully understood. Mechanical degradation of electrode particles has been experimentally linked to capacity fade and failure of batteries; an understanding of the interplay between mechanics and electrochemistry in the battery is necessary in order to improve the overall performance of the battery. A multi-scale model to simulate the coupled electrochemical and mechanical behavior of Li batteries has been developed, which models the porous electrode and separator regions of the battery. The porous electrode includes a liquid electrolyte and solid active materials. A multi-scale finite element approach is used to analyze the electrochemical and mechanical performance. The multi-scale model includes a macro- and micro-scale with analytical volume-averaging methods to relate the scales. The macro-scale model describes Li-ion transport through the electrolyte, electric potentials, and displacements throughout the battery. The micro-scale considers the surface kinetics and electrochemical and mechanical response of a single particle of active material evaluated locally within the cathode region. Both scales are non-linear and dependent on the other. The electrochemical and mechanical response of the battery are highly dependent on the porosity in the electrode, the active material particle size, and discharge rate. Balancing these parameters can improve the overall performance of the battery. A formal design optimization approach with multi-scale adjoint sensitivity analysis is developed to find optimal designs to improve the performance of the battery model. Optimal electrode designs are presented which maximize the capacity of the battery while mitigating stress levels during discharge over a range of discharge rates.

  9. Adaptive dynamic range optimization (ADRO): a digital amplification strategy for hearing aids and cochlear implants.

    PubMed

    Blamey, Peter J

    2005-01-01

    Adaptive dynamic range optimization (ADRO) is an amplification strategy that uses digital signal processing techniques to improve the audibility, comfort, and intelligibility of sounds for people who use cochlear implants and/or hearing aids. The strategy uses statistical analysis to select the most information-rich section of the input dynamic range in multiple-frequency channels. Fuzzy logic rules control the gain in each frequency channel so that the selected section of the dynamic range is presented at an audible and comfortable level. The ADRO processing thus adaptively optimizes the dynamic range of the signal in multiple-frequency channels. Clinical studies show that ADRO can be fitted easily to all degrees of hearing loss for hearing aids and cochlear implants in a direct and intuitive manner, taking the preferences of the listener into account. The result is high acceptance by new and experienced hearing aid users and strong preferences for ADRO compared with alternative amplification strategies. The ADRO processing is particularly well suited to bimodal and hybrid stimulation which combine electric and acoustic stimulation in opposite ears or in the same ear, respectively.

  10. Adaptive Dynamic Range Optimization (ADRO): A Digital Amplification Strategy for Hearing Aids and Cochlear Implants

    PubMed Central

    Blamey, Peter J.

    2005-01-01

    Adaptive dynamic range optimization (ADRO) is an amplification strategy that uses digital signal processing techniques to improve the audibility, comfort, and intelligibility of sounds for people who use cochlear implants and/or hearing aids. The strategy uses statistical analysis to select the most information-rich section of the input dynamic range in multiple-frequency channels. Fuzzy logic rules control the gain in each frequency channel so that the selected section of the dynamic range is presented at an audible and comfortable level. The ADRO processing thus adaptively optimizes the dynamic range of the signal in multiple-frequency channels. Clinical studies show that ADRO can be fitted easily to all degrees of hearing loss for hearing aids and cochlear implants in a direct and intuitive manner, taking the preferences of the listener into account. The result is high acceptance by new and experienced hearing aid users and strong preferences for ADRO compared with alternative amplification strategies. The ADRO processing is particularly well suited to bimodal and hybrid stimulation which combine electric and acoustic stimulation in opposite ears or in the same ear, respectively. PMID:16012705

  11. Multi-optimization Criteria-based Robot Behavioral Adaptability and Motion Planning

    SciTech Connect

    Pin, Francois G.

    2002-06-01

    Robotic tasks are typically defined in Task Space (e.g., the 3-D World), whereas robots are controlled in Joint Space (motors). The transformation from Task Space to Joint Space must consider the task objectives (e.g., high precision, strength optimization, torque optimization), the task constraints (e.g., obstacles, joint limits, non-holonomic constraints, contact or tool task constraints), and the robot kinematics configuration (e.g., tools, type of joints, mobile platform, manipulator, modular additions, locked joints). Commercially available robots are optimized for a specific set of tasks, objectives and constraints and, therefore, their control codes are extremely specific to a particular set of conditions. Thus, there exist a multiplicity of codes, each handling a particular set of conditions, but none suitable for use on robots with widely varying tasks, objectives, constraints, or environments. On the other hand, most DOE missions and tasks are typically ''batches of one''. Attempting to use commercial codes for such work requires significant personnel and schedule costs for re-programming or adding code to the robots whenever a change in task objective, robot configuration, number and type of constraint, etc. occurs. The objective of our project is to develop a ''generic code'' to implement this Task-space to Joint-Space transformation that would allow robot behavior adaptation, in real time (at loop rate), to changes in task objectives, number and type of constraints, modes of controls, kinematics configuration (e.g., new tools, added module). Our specific goal is to develop a single code for the general solution of under-specified systems of algebraic equations that is suitable for solving the inverse kinematics of robots, is useable for all types of robots (mobile robots, manipulators, mobile manipulators, etc.) with no limitation on the number of joints and the number of controlled Task-Space variables, can adapt to real time changes in number and

  12. On the performance of linear decreasing inertia weight particle swarm optimization for global optimization.

    PubMed

    Arasomwan, Martins Akugbe; Adewumi, Aderemi Oluyinka

    2013-01-01

    Linear decreasing inertia weight (LDIW) strategy was introduced to improve on the performance of the original particle swarm optimization (PSO). However, linear decreasing inertia weight PSO (LDIW-PSO) algorithm is known to have the shortcoming of premature convergence in solving complex (multipeak) optimization problems due to lack of enough momentum for particles to do exploitation as the algorithm approaches its terminal point. Researchers have tried to address this shortcoming by modifying LDIW-PSO or proposing new PSO variants. Some of these variants have been claimed to outperform LDIW-PSO. The major goal of this paper is to experimentally establish the fact that LDIW-PSO is very much efficient if its parameters are properly set. First, an experiment was conducted to acquire a percentage value of the search space limits to compute the particle velocity limits in LDIW-PSO based on commonly used benchmark global optimization problems. Second, using the experimentally obtained values, five well-known benchmark optimization problems were used to show the outstanding performance of LDIW-PSO over some of its competitors which have in the past claimed superiority over it. Two other recent PSO variants with different inertia weight strategies were also compared with LDIW-PSO with the latter outperforming both in the simulation experiments conducted. PMID:24324383

  13. Optimization of wind farm performance using low-order models

    NASA Astrophysics Data System (ADS)

    Dabiri, John; Brownstein, Ian

    2015-11-01

    A low order model that captures the dominant flow behaviors in a vertical-axis wind turbine (VAWT) array is used to maximize the power output of wind farms utilizing VAWTs. The leaky Rankine body model (LRB) was shown by Araya et al. (JRSE 2014) to predict the ranking of individual turbine performances in an array to within measurement uncertainty as compared to field data collected from full-scale VAWTs. Further, this model is able to predict array performance with significantly less computational expense than higher fidelity numerical simulations of the flow, making it ideal for use in optimization of wind farm performance. This presentation will explore the ability of the LRB model to rank the relative power output of different wind turbine array configurations as well as the ranking of individual array performance over a variety of wind directions, using various complex configurations tested in the field and simpler configurations tested in a wind tunnel. Results will be presented in which the model is used to determine array fitness in an evolutionary algorithm seeking to find optimal array configurations given a number of turbines, area of available land, and site wind direction profile. Comparison with field measurements will be presented.

  14. USING AN ADAPTER TO PERFORM THE CHALFANT-STYLE CONTAINMENT VESSEL PERIODIC MAINTENANCE LEAK RATE TEST

    SciTech Connect

    Loftin, B.; Abramczyk, G.; Trapp, D.

    2011-06-03

    Recently the Packaging Technology and Pressurized Systems (PT&PS) organization at the Savannah River National Laboratory was asked to develop an adapter for performing the leak-rate test of a Chalfant-style containment vessel. The PT&PS organization collaborated with designers at the Department of Energy's Pantex Plant to develop the adapter currently in use for performing the leak-rate testing on the containment vessels. This paper will give the history of leak-rate testing of the Chalfant-style containment vessels, discuss the design concept for the adapter, give an overview of the design, and will present results of the testing done using the adapter.

  15. Parallel performance optimizations on unstructured mesh-based simulations

    SciTech Connect

    Sarje, Abhinav; Song, Sukhyun; Jacobsen, Douglas; Huck, Kevin; Hollingsworth, Jeffrey; Malony, Allen; Williams, Samuel; Oliker, Leonid

    2015-06-01

    This paper addresses two key parallelization challenges the unstructured mesh-based ocean modeling code, MPAS-Ocean, which uses a mesh based on Voronoi tessellations: (1) load imbalance across processes, and (2) unstructured data access patterns, that inhibit intra- and inter-node performance. Our work analyzes the load imbalance due to naive partitioning of the mesh, and develops methods to generate mesh partitioning with better load balance and reduced communication. Furthermore, we present methods that minimize both inter- and intranode data movement and maximize data reuse. Our techniques include predictive ordering of data elements for higher cache efficiency, as well as communication reduction approaches. We present detailed performance data when running on thousands of cores using the Cray XC30 supercomputer and show that our optimization strategies can exceed the original performance by over 2×. Additionally, many of these solutions can be broadly applied to a wide variety of unstructured grid-based computations.

  16. LAMMPS strong scaling performance optimization on Blue Gene/Q

    SciTech Connect

    Coffman, Paul; Jiang, Wei; Romero, Nichols A.

    2014-11-12

    LAMMPS "Large-scale Atomic/Molecular Massively Parallel Simulator" is an open-source molecular dynamics package from Sandia National Laboratories. Significant performance improvements in strong-scaling and time-to-solution for this application on IBM's Blue Gene/Q have been achieved through computational optimizations of the OpenMP versions of the short-range Lennard-Jones term of the CHARMM force field and the long-range Coulombic interaction implemented with the PPPM (particle-particle-particle mesh) algorithm, enhanced by runtime parameter settings controlling thread utilization. Additionally, MPI communication performance improvements were made to the PPPM calculation by re-engineering the parallel 3D FFT to use MPICH collectives instead of point-to-point. Performance testing was done using an 8.4-million atom simulation scaling up to 16 racks on the Mira system at Argonne Leadership Computing Facility (ALCF). Speedups resulting from this effort were in some cases over 2x.

  17. Adaptive optimization of reference intensity for optical coherence imaging using galvanometric mirror tilting method

    NASA Astrophysics Data System (ADS)

    Kim, Ji-hyun; Han, Jae-Ho; Jeong, Jichai

    2015-09-01

    Integration time and reference intensity are important factors for achieving high signal-to-noise ratio (SNR) and sensitivity in optical coherence tomography (OCT). In this context, we present an adaptive optimization method of reference intensity for OCT setup. The reference intensity is automatically controlled by tilting a beam position using a Galvanometric scanning mirror system. Before sample scanning, the OCT system acquires two dimensional intensity map with normalized intensity and variables in color spaces using false-color mapping. Then, the system increases or decreases reference intensity following the map data for optimization with a given algorithm. In our experiments, the proposed method successfully corrected the reference intensity with maintaining spectral shape, enabled to change integration time without manual calibration of the reference intensity, and prevented image degradation due to over-saturation and insufficient reference intensity. Also, SNR and sensitivity could be improved by increasing integration time with automatic adjustment of the reference intensity. We believe that our findings can significantly aid in the optimization of SNR and sensitivity for optical coherence tomography systems.

  18. Multidisciplinary Design Optimization of a Full Vehicle with High Performance Computing

    NASA Technical Reports Server (NTRS)

    Yang, R. J.; Gu, L.; Tho, C. H.; Sobieszczanski-Sobieski, Jaroslaw

    2001-01-01

    Multidisciplinary design optimization (MDO) of a full vehicle under the constraints of crashworthiness, NVH (Noise, Vibration and Harshness), durability, and other performance attributes is one of the imperative goals for automotive industry. However, it is often infeasible due to the lack of computational resources, robust simulation capabilities, and efficient optimization methodologies. This paper intends to move closer towards that goal by using parallel computers for the intensive computation and combining different approximations for dissimilar analyses in the MDO process. The MDO process presented in this paper is an extension of the previous work reported by Sobieski et al. In addition to the roof crush, two full vehicle crash modes are added: full frontal impact and 50% frontal offset crash. Instead of using an adaptive polynomial response surface method, this paper employs a DOE/RSM method for exploring the design space and constructing highly nonlinear crash functions. Two NMO strategies are used and results are compared. This paper demonstrates that with high performance computing, a conventionally intractable real world full vehicle multidisciplinary optimization problem considering all performance attributes with large number of design variables become feasible.

  19. Face adaptation does not improve performance on search or discrimination tasks.

    PubMed

    Ng, Minna; Boynton, Geoffrey M; Fine, Ione

    2008-01-04

    The face adaptation effect, as described by M. A. Webster and O. H. MacLin (1999), is a robust perceptual shift in the appearance of faces after a brief adaptation period. For example, prolonged exposure to Asian faces causes a Eurasian face to appear distinctly Caucasian. This adaptation effect has been documented for general configural effects, as well as for the facial properties of gender, ethnicity, expression, and identity. We began by replicating the finding that adaptation to ethnicity, gender, and a combination of both features induces selective shifts in category appearance. We then investigated whether this adaptation has perceptual consequences beyond a shift in the perceived category boundary by measuring the effects of adaptation on RSVP, spatial search, and discrimination tasks. Adaptation had no discernable effect on performance for any of these tasks.

  20. Optimizing intramuscular adaptations to aerobic exercise: effects of carbohydrate restriction and protein supplementation on mitochondrial biogenesis.

    PubMed

    Margolis, Lee M; Pasiakos, Stefan M

    2013-11-01

    Mitochondrial biogenesis is a critical metabolic adaptation to aerobic exercise training that results in enhanced mitochondrial size, content, number, and activity. Recent evidence has shown that dietary manipulation can further enhance mitochondrial adaptations to aerobic exercise training, which may delay skeletal muscle fatigue and enhance exercise performance. Specifically, studies have demonstrated that combining carbohydrate restriction (endogenous and exogenous) with a single bout of aerobic exercise potentiates the beneficial effects of exercise on markers of mitochondrial biogenesis. Additionally, studies have demonstrated that high-quality protein supplementation enhances anabolic skeletal muscle intracellular signaling and mitochondrial protein synthesis following a single bout of aerobic exercise. Mitochondrial biogenesis is stimulated by complex intracellular signaling pathways that appear to be primarily regulated by 5'AMP-activated protein kinase and p38 mitogen-activated protein kinase mediated through proliferator-activated γ receptor co-activator 1 α activation, resulting in increased mitochondrial DNA expression and enhanced skeletal muscle oxidative capacity. However, the mechanisms by which concomitant carbohydrate restriction and dietary protein supplementation modulates mitochondrial adaptations to aerobic exercise training remains unclear. This review summarizes intracellular regulation of mitochondrial biogenesis and the effects of carbohydrate restriction and protein supplementation on mitochondrial adaptations to aerobic exercise.

  1. Neural network-based optimal adaptive output feedback control of a helicopter UAV.

    PubMed

    Nodland, David; Zargarzadeh, Hassan; Jagannathan, Sarangapani

    2013-07-01

    Helicopter unmanned aerial vehicles (UAVs) are widely used for both military and civilian operations. Because the helicopter UAVs are underactuated nonlinear mechanical systems, high-performance controller design for them presents a challenge. This paper introduces an optimal controller design via an output feedback for trajectory tracking of a helicopter UAV, using a neural network (NN). The output-feedback control system utilizes the backstepping methodology, employing kinematic and dynamic controllers and an NN observer. The online approximator-based dynamic controller learns the infinite-horizon Hamilton-Jacobi-Bellman equation in continuous time and calculates the corresponding optimal control input by minimizing a cost function, forward-in-time, without using the value and policy iterations. Optimal tracking is accomplished by using a single NN utilized for the cost function approximation. The overall closed-loop system stability is demonstrated using Lyapunov analysis. Finally, simulation results are provided to demonstrate the effectiveness of the proposed control design for trajectory tracking.

  2. A Study on the Self-Adaption Incentive Performance Salary

    NASA Astrophysics Data System (ADS)

    Zhang, Chuanming; Wang, Yang

    In project managing, the performance salary management mode is often used to motivate project managers and other similar staff to improve performance or reduce the cost. But the engineering activities who own a lot of internal and external uncertain factors can not be known by the principle. It is difficult for to develop a suitable incentive target to project managers etch. This paper thinks that the manager self master the maximum of information on engineering activities. So this paper sets up an incentive model: the project managers themselves report performance objectives; owner gives the managers reward or punishment combined with their reported performance and actual performance. The model to ensure that the project manager is only accurate self reported its results to get the maximum profit. At the same time, it cans incentive managers to improve performance or reduce the cost. This paper focuses on setting up the model, analyzing the model parameters. And cite an example analyze them.

  3. Optimal reconstruction for closed-loop ground-layer adaptive optics with elongated spots.

    PubMed

    Béchet, Clémentine; Tallon, Michel; Tallon-Bosc, Isabelle; Thiébaut, Éric; Le Louarn, Miska; Clare, Richard M

    2010-11-01

    The design of the laser-guide-star-based adaptive optics (AO) systems for the Extremely Large Telescopes requires careful study of the issue of elongated spots produced on Shack-Hartmann wavefront sensors. The importance of a correct modeling of the nonuniformity and correlations of the noise induced by this elongation has already been demonstrated for wavefront reconstruction. We report here on the first (to our knowledge) end-to-end simulations of closed-loop ground-layer AO with laser guide stars with such an improved noise model. The results are compared with the level of performance predicted by a classical noise model for the reconstruction. The performance is studied in terms of ensquared energy and confirms that, thanks to the improved noise model, central or side launching of the lasers does not affect the performance with respect to the laser guide stars' flux. These two launching schemes also perform similarly whatever the atmospheric turbulence strength.

  4. Optimal reconstruction for closed-loop ground-layer adaptive optics with elongated spots.

    PubMed

    Béchet, Clémentine; Tallon, Michel; Tallon-Bosc, Isabelle; Thiébaut, Éric; Le Louarn, Miska; Clare, Richard M

    2010-11-01

    The design of the laser-guide-star-based adaptive optics (AO) systems for the Extremely Large Telescopes requires careful study of the issue of elongated spots produced on Shack-Hartmann wavefront sensors. The importance of a correct modeling of the nonuniformity and correlations of the noise induced by this elongation has already been demonstrated for wavefront reconstruction. We report here on the first (to our knowledge) end-to-end simulations of closed-loop ground-layer AO with laser guide stars with such an improved noise model. The results are compared with the level of performance predicted by a classical noise model for the reconstruction. The performance is studied in terms of ensquared energy and confirms that, thanks to the improved noise model, central or side launching of the lasers does not affect the performance with respect to the laser guide stars' flux. These two launching schemes also perform similarly whatever the atmospheric turbulence strength. PMID:21045872

  5. Characterization, performance and optimization of PVDF as a piezoelectric film for advanced space mirror concepts.

    SciTech Connect

    Jones, Gary D.; Assink, Roger Alan; Dargaville, Tim Richard; Chaplya, Pavel Mikhail; Clough, Roger Lee; Elliott, Julie M.; Martin, Jeffrey W.; Mowery, Daniel Michael; Celina, Mathew Christopher

    2005-11-01

    Piezoelectric polymers based on polyvinylidene fluoride (PVDF) are of interest for large aperture space-based telescopes as adaptive or smart materials. Dimensional adjustments of adaptive polymer films depend on controlled charge deposition. Predicting their long-term performance requires a detailed understanding of the piezoelectric material features, expected to suffer due to space environmental degradation. Hence, the degradation and performance of PVDF and its copolymers under various stress environments expected in low Earth orbit has been reviewed and investigated. Various experiments were conducted to expose these polymers to elevated temperature, vacuum UV, {gamma}-radiation and atomic oxygen. The resulting degradative processes were evaluated. The overall materials performance is governed by a combination of chemical and physical degradation processes. Molecular changes are primarily induced via radiative damage, and physical damage from temperature and atomic oxygen exposure is evident as depoling, loss of orientation and surface erosion. The effects of combined vacuum UV radiation and atomic oxygen resulted in expected surface erosion and pitting rates that determine the lifetime of thin films. Interestingly, the piezo responsiveness in the underlying bulk material remained largely unchanged. This study has delivered a comprehensive framework for material properties and degradation sensitivities with variations in individual polymer performances clearly apparent. The results provide guidance for material selection, qualification, optimization strategies, feedback for manufacturing and processing, or alternative materials. Further material qualification should be conducted via experiments under actual space conditions.

  6. Automatic treatment plan re-optimization for adaptive radiotherapy guided with the initial plan DVHs.

    PubMed

    Li, Nan; Zarepisheh, Masoud; Uribe-Sanchez, Andres; Moore, Kevin; Tian, Zhen; Zhen, Xin; Graves, Yan Jiang; Gautier, Quentin; Mell, Loren; Zhou, Linghong; Jia, Xun; Jiang, Steve

    2013-12-21

    Adaptive radiation therapy (ART) can reduce normal tissue toxicity and/or improve tumor control through treatment adaptations based on the current patient anatomy. Developing an efficient and effective re-planning algorithm is an important step toward the clinical realization of ART. For the re-planning process, manual trial-and-error approach to fine-tune planning parameters is time-consuming and is usually considered unpractical, especially for online ART. It is desirable to automate this step to yield a plan of acceptable quality with minimal interventions. In ART, prior information in the original plan is available, such as dose-volume histogram (DVH), which can be employed to facilitate the automatic re-planning process. The goal of this work is to develop an automatic re-planning algorithm to generate a plan with similar, or possibly better, DVH curves compared with the clinically delivered original plan. Specifically, our algorithm iterates the following two loops. An inner loop is the traditional fluence map optimization, in which we optimize a quadratic objective function penalizing the deviation of the dose received by each voxel from its prescribed or threshold dose with a set of fixed voxel weighting factors. In outer loop, the voxel weighting factors in the objective function are adjusted according to the deviation of the current DVH curves from those in the original plan. The process is repeated until the DVH curves are acceptable or maximum iteration step is reached. The whole algorithm is implemented on GPU for high efficiency. The feasibility of our algorithm has been demonstrated with three head-and-neck cancer IMRT cases, each having an initial planning CT scan and another treatment CT scan acquired in the middle of treatment course. Compared with the DVH curves in the original plan, the DVH curves in the resulting plan using our algorithm with 30 iterations are better for almost all structures. The re-optimization process takes about 30 s using

  7. Automatic treatment plan re-optimization for adaptive radiotherapy guided with the initial plan DVHs

    NASA Astrophysics Data System (ADS)

    Li, Nan; Zarepisheh, Masoud; Uribe-Sanchez, Andres; Moore, Kevin; Tian, Zhen; Zhen, Xin; Jiang Graves, Yan; Gautier, Quentin; Mell, Loren; Zhou, Linghong; Jia, Xun; Jiang, Steve

    2013-12-01

    Adaptive radiation therapy (ART) can reduce normal tissue toxicity and/or improve tumor control through treatment adaptations based on the current patient anatomy. Developing an efficient and effective re-planning algorithm is an important step toward the clinical realization of ART. For the re-planning process, manual trial-and-error approach to fine-tune planning parameters is time-consuming and is usually considered unpractical, especially for online ART. It is desirable to automate this step to yield a plan of acceptable quality with minimal interventions. In ART, prior information in the original plan is available, such as dose-volume histogram (DVH), which can be employed to facilitate the automatic re-planning process. The goal of this work is to develop an automatic re-planning algorithm to generate a plan with similar, or possibly better, DVH curves compared with the clinically delivered original plan. Specifically, our algorithm iterates the following two loops. An inner loop is the traditional fluence map optimization, in which we optimize a quadratic objective function penalizing the deviation of the dose received by each voxel from its prescribed or threshold dose with a set of fixed voxel weighting factors. In outer loop, the voxel weighting factors in the objective function are adjusted according to the deviation of the current DVH curves from those in the original plan. The process is repeated until the DVH curves are acceptable or maximum iteration step is reached. The whole algorithm is implemented on GPU for high efficiency. The feasibility of our algorithm has been demonstrated with three head-and-neck cancer IMRT cases, each having an initial planning CT scan and another treatment CT scan acquired in the middle of treatment course. Compared with the DVH curves in the original plan, the DVH curves in the resulting plan using our algorithm with 30 iterations are better for almost all structures. The re-optimization process takes about 30 s using

  8. An adaptive-management framework for optimal control of hiking near golden eagle nests in Denali National Park.

    PubMed

    Martin, Julien; Fackler, Paul L; Nichols, James D; Runge, Michael C; McIntyre, Carol L; Lubow, Bruce L; McCluskie, Maggie C; Schmutz, Joel A

    2011-04-01

    Unintended effects of recreational activities in protected areas are of growing concern. We used an adaptive-management framework to develop guidelines for optimally managing hiking activities to maintain desired levels of territory occupancy and reproductive success of Golden Eagles (Aquila chrysaetos) in Denali National Park (Alaska, U.S.A.). The management decision was to restrict human access (hikers) to particular nesting territories to reduce disturbance. The management objective was to minimize restrictions on hikers while maintaining reproductive performance of eagles above some specified level. We based our decision analysis on predictive models of site occupancy of eagles developed using a combination of expert opinion and data collected from 93 eagle territories over 20 years. The best predictive model showed that restricting human access to eagle territories had little effect on occupancy dynamics. However, when considering important sources of uncertainty in the models, including environmental stochasticity, imperfect detection of hares on which eagles prey, and model uncertainty, restricting access of territories to hikers improved eagle reproduction substantially. An adaptive management framework such as ours may help reduce uncertainty of the effects of hiking activities on Golden Eagles.

  9. An adaptive-management framework for optimal control of hiking near golden eagle nests in Denali National Park

    USGS Publications Warehouse

    Martin, Julien; Fackler, Paul L.; Nichols, James D.; Runge, Michael C.; McIntyre, Carol L.; Lubow, Bruce L.; McCluskie, Maggie C.; Schmutz, Joel A.

    2011-01-01

    Unintended effects of recreational activities in protected areas are of growing concern. We used an adaptive-management framework to develop guidelines for optimally managing hiking activities to maintain desired levels of territory occupancy and reproductive success of Golden Eagles (Aquila chrysaetos) in Denali National Park (Alaska, U.S.A.). The management decision was to restrict human access (hikers) to particular nesting territories to reduce disturbance. The management objective was to minimize restrictions on hikers while maintaining reproductive performance of eagles above some specified level. We based our decision analysis on predictive models of site occupancy of eagles developed using a combination of expert opinion and data collected from 93 eagle territories over 20 years. The best predictive model showed that restricting human access to eagle territories had little effect on occupancy dynamics. However, when considering important sources of uncertainty in the models, including environmental stochasticity, imperfect detection of hares on which eagles prey, and model uncertainty, restricting access of territories to hikers improved eagle reproduction substantially. An adaptive management framework such as ours may help reduce uncertainty of the effects of hiking activities on Golden Eagles

  10. An adaptive-management framework for optimal control of hiking near golden eagle nests in Denali National Park.

    PubMed

    Martin, Julien; Fackler, Paul L; Nichols, James D; Runge, Michael C; McIntyre, Carol L; Lubow, Bruce L; McCluskie, Maggie C; Schmutz, Joel A

    2011-04-01

    Unintended effects of recreational activities in protected areas are of growing concern. We used an adaptive-management framework to develop guidelines for optimally managing hiking activities to maintain desired levels of territory occupancy and reproductive success of Golden Eagles (Aquila chrysaetos) in Denali National Park (Alaska, U.S.A.). The management decision was to restrict human access (hikers) to particular nesting territories to reduce disturbance. The management objective was to minimize restrictions on hikers while maintaining reproductive performance of eagles above some specified level. We based our decision analysis on predictive models of site occupancy of eagles developed using a combination of expert opinion and data collected from 93 eagle territories over 20 years. The best predictive model showed that restricting human access to eagle territories had little effect on occupancy dynamics. However, when considering important sources of uncertainty in the models, including environmental stochasticity, imperfect detection of hares on which eagles prey, and model uncertainty, restricting access of territories to hikers improved eagle reproduction substantially. An adaptive management framework such as ours may help reduce uncertainty of the effects of hiking activities on Golden Eagles. PMID:21342265

  11. An optimal performance control scheme for a 3D crane

    NASA Astrophysics Data System (ADS)

    Maghsoudi, Mohammad Javad; Mohamed, Z.; Husain, A. R.; Tokhi, M. O.

    2016-01-01

    This paper presents an optimal performance control scheme for control of a three dimensional (3D) crane system including a Zero Vibration shaper which considers two control objectives concurrently. The control objectives are fast and accurate positioning of a trolley and minimum sway of a payload. A complete mathematical model of a lab-scaled 3D crane is simulated in Simulink. With a specific cost function the proposed controller is designed to cater both control objectives similar to a skilled operator. Simulation and experimental studies on a 3D crane show that the proposed controller has better performance as compared to a sequentially tuned PID-PID anti swing controller. The controller provides better position response with satisfactory payload sway in both rail and trolley responses. Experiments with different payloads and cable lengths show that the proposed controller is robust to changes in payload with satisfactory responses.

  12. An improved model for TPV performance predictions and optimization

    NASA Astrophysics Data System (ADS)

    Schroeder, K. L.; Rose, M. F.; Burkhalter, J. E.

    1997-03-01

    Previously a model has been presented for calculating the performance of a TPV system. This model has been revised into a general purpose algorithm, improved in fidelity, and is presented here. The basic model is an energy based formulation and evaluates both the radiant and heat source elements of a combustion based system. Improvements in the radiant calculations include the use of ray tracking formulations and view factors for evaluating various flat plate and cylindrical configurations. Calculation of photocell temperature and performance parameters as a function of position and incident power have also been incorporated. Heat source calculations have been fully integrated into the code by the incorporation of a modified version of the NASA Complex Chemical Equilibrium Compositions and Applications (CEA) code. Additionally, coding has been incorporated to allow optimization of various system parameters and configurations. Several examples cases are presented and compared, and an optimum flat plate emitter/filter/photovoltaic configuration is also described.

  13. Robust Multivariable Optimization and Performance Simulation for ASIC Design

    NASA Technical Reports Server (NTRS)

    DuMonthier, Jeffrey; Suarez, George

    2013-01-01

    Application-specific-integrated-circuit (ASIC) design for space applications involves multiple challenges of maximizing performance, minimizing power, and ensuring reliable operation in extreme environments. This is a complex multidimensional optimization problem, which must be solved early in the development cycle of a system due to the time required for testing and qualification severely limiting opportunities to modify and iterate. Manual design techniques, which generally involve simulation at one or a small number of corners with a very limited set of simultaneously variable parameters in order to make the problem tractable, are inefficient and not guaranteed to achieve the best possible results within the performance envelope defined by the process and environmental requirements. What is required is a means to automate design parameter variation, allow the designer to specify operational constraints and performance goals, and to analyze the results in a way that facilitates identifying the tradeoffs defining the performance envelope over the full set of process and environmental corner cases. The system developed by the Mixed Signal ASIC Group (MSAG) at the Goddard Space Flight Center is implemented as a framework of software modules, templates, and function libraries. It integrates CAD tools and a mathematical computing environment, and can be customized for new circuit designs with only a modest amount of effort as most common tasks are already encapsulated. Customization is required for simulation test benches to determine performance metrics and for cost function computation.

  14. Human Performance Optimization: Culture Change and Paradigm Shift.

    PubMed

    Deuster, Patricia A; OʼConnor, Francis G

    2015-11-01

    The term "Human Performance Optimization" (HPO) emerged across the Department of Defense (DoD) around 2006 when the importance of human performance for military success on the battlefield was acknowledged. Likewise, the term Total Force Fitness (TFF) arose as a conceptual framework within DoD in response to the need for a more holistic approach to the unparalleled operational demands with multiple deployments and strains on the United States Armed Forces. Both HPO and TFF are frameworks for enhancing and sustaining the health, well-being, and performance among our warriors and their families; they are fundamental to accomplishing our nation's mission. A demands-resources model for HPO is presented within the context of TFF to assist in operationalizing actions to enhance performance. In addition, the role leaders can serve is discussed; leaders are uniquely postured in the military chain of command to directly influence a culture of fitness for a ready force, and promote the concept that service members are ultimately responsible for their fitness and performance. PMID:26506199

  15. Human Performance Optimization: Culture Change and Paradigm Shift.

    PubMed

    Deuster, Patricia A; OʼConnor, Francis G

    2015-11-01

    The term "Human Performance Optimization" (HPO) emerged across the Department of Defense (DoD) around 2006 when the importance of human performance for military success on the battlefield was acknowledged. Likewise, the term Total Force Fitness (TFF) arose as a conceptual framework within DoD in response to the need for a more holistic approach to the unparalleled operational demands with multiple deployments and strains on the United States Armed Forces. Both HPO and TFF are frameworks for enhancing and sustaining the health, well-being, and performance among our warriors and their families; they are fundamental to accomplishing our nation's mission. A demands-resources model for HPO is presented within the context of TFF to assist in operationalizing actions to enhance performance. In addition, the role leaders can serve is discussed; leaders are uniquely postured in the military chain of command to directly influence a culture of fitness for a ready force, and promote the concept that service members are ultimately responsible for their fitness and performance.

  16. Neural suppression of irrelevant information underlies optimal working memory performance

    PubMed Central

    Zanto, Theodore P.; Gazzaley, Adam

    2009-01-01

    Our ability to focus attention on task-relevant information and ignore distractions is reflected by differential enhancement and suppression of neural activity in sensory cortex (i.e., top-down modulation). Such selective, goal-directed modulation of activity may be intimately related to memory, such that the focus of attention biases the likelihood of successfully maintaining relevant information by limiting interference from irrelevant stimuli. Despite recent studies elucidating the mechanistic overlap between attention and memory, the relationship between top-down modulation of visual processing during working memory (WM) encoding and subsequent recognition performance has not yet been established. Here, we provide neurophysiological evidence in healthy, young adults that top-down modulation of early visual processing (< 200 ms from stimulus onset) is intimately related to subsequent WM performance, such that the likelihood of successfully remembering relevant information is associated with limiting interference from irrelevant stimuli. The consequences of a failure to ignore distractors on recognition performance was replicated for two types of feature-based memory, motion direction and color. Moreover, attention to irrelevant stimuli was reflected neurally during the WM maintenance period as an increased memory load. These results suggest that neural enhancement of relevant information is not the primary determinant of high-level performance, but rather, optimal WM performance is dependent on effectively filtering irrelevant information through neural suppression to prevent overloading a limited memory capacity. PMID:19279242

  17. Examining the Relationship between Learning Organization Characteristics and Change Adaptation, Innovation, and Organizational Performance

    ERIC Educational Resources Information Center

    Kontoghiorghes, Constantine; Awbre, Susan M.; Feurig, Pamela L.

    2005-01-01

    The main purpose of this exploratory study was to examine the relationship between certain learning organization characteristics and change adaptation, innovation, and bottom-line organizational performance. The following learning organization characteristics were found to be the strongest predictors of rapid change adaptation, quick product or…

  18. Perform - A performance optimizing computer program for dynamic systems subject to transient loadings

    NASA Technical Reports Server (NTRS)

    Pilkey, W. D.; Wang, B. P.; Yoo, Y.; Clark, B.

    1973-01-01

    A description and applications of a computer capability for determining the ultimate optimal behavior of a dynamically loaded structural-mechanical system are presented. This capability provides characteristics of the theoretically best, or limiting, design concept according to response criteria dictated by design requirements. Equations of motion of the system in first or second order form include incompletely specified elements whose characteristics are determined in the optimization of one or more performance indices subject to the response criteria in the form of constraints. The system is subject to deterministic transient inputs, and the computer capability is designed to operate with a large linear programming on-the-shelf software package which performs the desired optimization. The report contains user-oriented program documentation in engineering, problem-oriented form. Applications cover a wide variety of dynamics problems including those associated with such diverse configurations as a missile-silo system, impacting freight cars, and an aircraft ride control system.

  19. Carbon Material Optimized Biocathode for Improving Microbial Fuel Cell Performance.

    PubMed

    Tursun, Hairti; Liu, Rui; Li, Jing; Abro, Rashid; Wang, Xiaohui; Gao, Yanmei; Li, Yuan

    2016-01-01

    To improve the performance of microbial fuel cells (MFCs), the biocathode electrode material of double-chamber was optimized. Alongside the basic carbon fiber brush, three carbon materials namely graphite granules, activated carbon granules (ACG) and activated carbon powder, were added to the cathode-chambers to improve power generation. The result shows that the addition of carbon materials increased the amount of available electroactive microbes on the electrode surface and thus promote oxygen reduction rate, which improved the generation performance of the MFCs. The Output current (external resistance = 1000 Ω) greatly increased after addition of the three carbon materials and maximum power densities in current stable phase increased by 47.4, 166.1, and 33.5%, respectively. Additionally, coulombic efficiencies of the MFC increased by 16.3, 64.3, and 20.1%, respectively. These results show that MFC when optimized with ACG show better power generation, higher chemical oxygen demands removal rate and coulombic efficiency. PMID:26858695

  20. Challenges when performing economic optimization of waste treatment: a review.

    PubMed

    Juul, N; Münster, M; Ravn, H; Söderman, M Ljunggren

    2013-09-01

    Strategic and operational decisions in waste management, in particular with respect to investments in new treatment facilities, are needed due to a number of factors, including continuously increasing amounts of waste, political demands for efficient utilization of waste resources, and the decommissioning of existing waste treatment facilities. Optimization models can assist in ensuring that these investment strategies are economically feasible. Various economic optimization models for waste treatment have been developed which focus on different parameters. Models focusing on transport are one example, but models focusing on energy production have also been developed, as well as models which take into account a plant's economies of scale, environmental impact, material recovery and social costs. Finally, models combining different criteria for the selection of waste treatment methods in multi-criteria analysis have been developed. A thorough updated review of the existing models is presented, and the main challenges and crucial parameters that need to be taken into account when assessing the economic performance of waste treatment alternatives are identified. The review article will assist both policy-makers and model-developers involved in assessing the economic performance of waste treatment alternatives.

  1. Challenges when performing economic optimization of waste treatment: a review.

    PubMed

    Juul, N; Münster, M; Ravn, H; Söderman, M Ljunggren

    2013-09-01

    Strategic and operational decisions in waste management, in particular with respect to investments in new treatment facilities, are needed due to a number of factors, including continuously increasing amounts of waste, political demands for efficient utilization of waste resources, and the decommissioning of existing waste treatment facilities. Optimization models can assist in ensuring that these investment strategies are economically feasible. Various economic optimization models for waste treatment have been developed which focus on different parameters. Models focusing on transport are one example, but models focusing on energy production have also been developed, as well as models which take into account a plant's economies of scale, environmental impact, material recovery and social costs. Finally, models combining different criteria for the selection of waste treatment methods in multi-criteria analysis have been developed. A thorough updated review of the existing models is presented, and the main challenges and crucial parameters that need to be taken into account when assessing the economic performance of waste treatment alternatives are identified. The review article will assist both policy-makers and model-developers involved in assessing the economic performance of waste treatment alternatives. PMID:23747136

  2. Carbon Material Optimized Biocathode for Improving Microbial Fuel Cell Performance

    PubMed Central

    Tursun, Hairti; Liu, Rui; Li, Jing; Abro, Rashid; Wang, Xiaohui; Gao, Yanmei; Li, Yuan

    2016-01-01

    To improve the performance of microbial fuel cells (MFCs), the biocathode electrode material of double-chamber was optimized. Alongside the basic carbon fiber brush, three carbon materials namely graphite granules, activated carbon granules (ACG) and activated carbon powder, were added to the cathode-chambers to improve power generation. The result shows that the addition of carbon materials increased the amount of available electroactive microbes on the electrode surface and thus promote oxygen reduction rate, which improved the generation performance of the MFCs. The Output current (external resistance = 1000 Ω) greatly increased after addition of the three carbon materials and maximum power densities in current stable phase increased by 47.4, 166.1, and 33.5%, respectively. Additionally, coulombic efficiencies of the MFC increased by 16.3, 64.3, and 20.1%, respectively. These results show that MFC when optimized with ACG show better power generation, higher chemical oxygen demands removal rate and coulombic efficiency. PMID:26858695

  3. Multiband RF pulses with improved performance via convex optimization.

    PubMed

    Shang, Hong; Larson, Peder E Z; Kerr, Adam; Reed, Galen; Sukumar, Subramaniam; Elkhaled, Adam; Gordon, Jeremy W; Ohliger, Michael A; Pauly, John M; Lustig, Michael; Vigneron, Daniel B

    2016-01-01

    Selective RF pulses are commonly designed with the desired profile as a low pass filter frequency response. However, for many MRI and NMR applications, the spectrum is sparse with signals existing at a few discrete resonant frequencies. By specifying a multiband profile and releasing the constraint on "don't-care" regions, the RF pulse performance can be improved to enable a shorter duration, sharper transition, or lower peak B1 amplitude. In this project, a framework for designing multiband RF pulses with improved performance was developed based on the Shinnar-Le Roux (SLR) algorithm and convex optimization. It can create several types of RF pulses with multiband magnitude profiles, arbitrary phase profiles and generalized flip angles. The advantage of this framework with a convex optimization approach is the flexible trade-off of different pulse characteristics. Designs for specialized selective RF pulses for balanced SSFP hyperpolarized (HP) (13)C MRI, a dualband saturation RF pulse for (1)H MR spectroscopy, and a pre-saturation pulse for HP (13)C study were developed and tested. PMID:26754063

  4. Performance Optimization of NEMO Oceanic Model at High Resolution

    NASA Astrophysics Data System (ADS)

    Epicoco, Italo; Mocavero, Silvia; Aloisio, Giovanni

    2014-05-01

    The NEMO oceanic model is based on the Navier-Stokes equations along with a nonlinear equation of state, which couples the two active tracers (temperature and salinity) to the fluid velocity. The code is written in Fortan 90 and parallelized using MPI. The resolution of the global ocean models used today for climate change studies limits the prediction accuracy. To overcome this limit, a new high-resolution global model, based on NEMO, simulating at 1/16° and 100 vertical levels has been developed at CMCC. The model is computational and memory intensive, so it requires many resources to be run. An optimization activity is needed. The strategy requires a preliminary analysis to highlight scalability bottlenecks. It has been performed on a SandyBridge architecture at CMCC. An efficiency of 48% on 7K cores (the maximum available) has been achieved. The analysis has been also carried out at routine level, so that the improvement actions could be designed for the entire code or for the single kernel. The analysis highlighted for example a loss of performance due to the routine used to implement the north fold algorithm (i.e. handling the points at the north pole of the 3-poles Grids): indeed an optimization of the routine implementation is needed. The folding is achieved considering only the last 4 rows on the top of the global domain and by applying a rotation pivoting on the point in the middle. During the folding, the point on the top left is updated with the value of the point on bottom right and so on. The current version of the parallel algorithm is based on the domain decomposition. Each MPI process takes care of a block of points. Each process can update its points using values belonging to the symmetric process. In the current implementation, each received message is placed in a buffer with a number of elements equal to the total dimension of the global domain. Each process sweeps the entire buffer, but only a part of that computation is really useful for the

  5. GPU-based ultra-fast direct aperture optimization for online adaptive radiation therapy

    NASA Astrophysics Data System (ADS)

    Men, Chunhua; Jia, Xun; Jiang, Steve B.

    2010-08-01

    Online adaptive radiation therapy (ART) has great promise to significantly reduce normal tissue toxicity and/or improve tumor control through real-time treatment adaptations based on the current patient anatomy. However, the major technical obstacle for clinical realization of online ART, namely the inability to achieve real-time efficiency in treatment re-planning, has yet to be solved. To overcome this challenge, this paper presents our work on the implementation of an intensity-modulated radiation therapy (IMRT) direct aperture optimization (DAO) algorithm on the graphics processing unit (GPU) based on our previous work on the CPU. We formulate the DAO problem as a large-scale convex programming problem, and use an exact method called the column generation approach to deal with its extremely large dimensionality on the GPU. Five 9-field prostate and five 5-field head-and-neck IMRT clinical cases with 5 × 5 mm2 beamlet size and 2.5 × 2.5 × 2.5 mm3 voxel size were tested to evaluate our algorithm on the GPU. It takes only 0.7-3.8 s for our implementation to generate high-quality treatment plans on an NVIDIA Tesla C1060 GPU card. Our work has therefore solved a major problem in developing ultra-fast (re-)planning technologies for online ART.

  6. Ambient illumination revisited: A new adaptation-based approach for optimizing medical imaging reading environments

    SciTech Connect

    Chawla, Amarpreet S.; Samei, Ehsan

    2007-01-15

    Ambient lighting in soft-copy reading rooms is currently kept at low values to preserve contrast rendition in the dark regions of a medical image. Low illuminance levels, however, create inadequate viewing conditions and may also cause eye strain. This eye strain may be potentially attributed to notable variations in the luminance adaptation state of the reader's eyes when moving the gaze intermittently between the brighter display and darker surrounding surfaces. This paper presents a methodology to minimize this variation and optimize the lighting conditions of reading rooms by exploiting the properties of liquid crystal displays (LCDs) with low diffuse reflection coefficients and high luminance ratio. First, a computational model was developed to determine a global luminance adaptation value, L{sub adp}, when viewing a medical image on display. The model is based on the diameter of the pupil size, which depends on the luminance of the observed object. Second, this value was compared with the luminance reflected off surrounding surfaces, L{sub s}, under various conditions of room illuminance, E, different values of diffuse reflection coefficients of surrounding surfaces, R{sub s}, and calibration settings of a typical LCD. The results suggest that for typical luminance settings of current LCDs, it is possible to raise ambient illumination to minimize differences in eye adaptation, potentially reducing visual fatigue while also complying with the TG18 specifications for controlled contrast rendition. Specifically, room illumination in the 75-150 lux range and surface diffuse reflection coefficients in the practical range of 0.13-0.22 sr{sup -1} provide an ideal setup for typical LCDs. Future LCDs with lower diffuse reflectivity and with higher inherent luminance ratios can provide further improvement of ergonomic viewing conditions in reading rooms.

  7. Goal orientation and work role performance: predicting adaptive and proactive work role performance through self-leadership strategies.

    PubMed

    Marques-Quinteiro, Pedro; Curral, Luís Alberto

    2012-01-01

    This article explores the relationship between goal orientation, self-leadership dimensions, and adaptive and proactive work role performances. The authors hypothesize that learning orientation, in contrast to performance orientation, positively predicts proactive and adaptive work role performances and that this relationship is mediated by self-leadership behavior-focused strategies. It is posited that self-leadership natural reward strategies and thought pattern strategies are expected to moderate this relationship. Workers (N = 108) from a software company participated in this study. As expected, learning orientation did predict adaptive and proactive work role performance. Moreover, in the relationship between learning orientation and proactive work role performance through self-leadership behavior-focused strategies, a moderated mediation effect was found for self-leadership natural reward and thought pattern strategies. In the end, the authors discuss the results and implications are discussed and future research directions are proposed.

  8. Goal orientation and work role performance: predicting adaptive and proactive work role performance through self-leadership strategies.

    PubMed

    Marques-Quinteiro, Pedro; Curral, Luís Alberto

    2012-01-01

    This article explores the relationship between goal orientation, self-leadership dimensions, and adaptive and proactive work role performances. The authors hypothesize that learning orientation, in contrast to performance orientation, positively predicts proactive and adaptive work role performances and that this relationship is mediated by self-leadership behavior-focused strategies. It is posited that self-leadership natural reward strategies and thought pattern strategies are expected to moderate this relationship. Workers (N = 108) from a software company participated in this study. As expected, learning orientation did predict adaptive and proactive work role performance. Moreover, in the relationship between learning orientation and proactive work role performance through self-leadership behavior-focused strategies, a moderated mediation effect was found for self-leadership natural reward and thought pattern strategies. In the end, the authors discuss the results and implications are discussed and future research directions are proposed. PMID:23094471

  9. Importance of eccentric actions in performance adaptations to resistance training

    NASA Technical Reports Server (NTRS)

    Dudley, Gary A.; Miller, Bruce J.; Buchanan, Paul; Tesch, Per A.

    1991-01-01

    The importance of eccentric (ecc) muscle actions in resistance training for the maintenance of muscle strength and mass in hypogravity was investigated in experiments in which human subjects, divided into three groups, were asked to perform four-five sets of 6 to 12 repetitions (rep) per set of three leg press and leg extension exercises, 2 days each weeks for 19 weeks. One group, labeled 'con', performed each rep with only concentric (con) actions, while group con/ecc with performed each rep with only ecc actions; the third group, con/con, performed twice as many sets with only con actions. Control subjects did not train. It was found that resistance training wih both con and ecc actions induced greater increases in muscle strength than did training with only con actions.

  10. Application of adaptive neuro-fuzzy inference system and cuckoo optimization algorithm for analyzing electro chemical machining process

    NASA Astrophysics Data System (ADS)

    Teimouri, Reza; Sohrabpoor, Hamed

    2013-12-01

    Electrochemical machining process (ECM) is increasing its importance due to some of the specific advantages which can be exploited during machining operation. The process offers several special privileges such as higher machining rate, better accuracy and control, and wider range of materials that can be machined. Contribution of too many predominate parameters in the process, makes its prediction and selection of optimal values really complex, especially while the process is programmized for machining of hard materials. In the present work in order to investigate effects of electrolyte concentration, electrolyte flow rate, applied voltage and feed rate on material removal rate (MRR) and surface roughness (SR) the adaptive neuro-fuzzy inference systems (ANFIS) have been used for creation predictive models based on experimental observations. Then the ANFIS 3D surfaces have been plotted for analyzing effects of process parameters on MRR and SR. Finally, the cuckoo optimization algorithm (COA) was used for selection solutions in which the process reaches maximum material removal rate and minimum surface roughness simultaneously. Results indicated that the ANFIS technique has superiority in modeling of MRR and SR with high prediction accuracy. Also, results obtained while applying of COA have been compared with those derived from confirmatory experiments which validate the applicability and suitability of the proposed techniques in enhancing the performance of ECM process.

  11. Adaptive Particle Swarm Optimizer with Varying Acceleration Coefficients for Finding the Most Stable Conformer of Small Molecules.

    PubMed

    Agrawal, Shikha; Silakari, Sanjay; Agrawal, Jitendra

    2015-11-01

    A novel parameter automation strategy for Particle Swarm Optimization called APSO (Adaptive PSO) is proposed. The algorithm is designed to efficiently control the local search and convergence to the global optimum solution. Parameters c1 controls the impact of the cognitive component on the particle trajectory and c2 controls the impact of the social component. Instead of fixing the value of c1 and c2 , this paper updates the value of these acceleration coefficients by considering time variation of evaluation function along with varying inertia weight factor in PSO. Here the maximum and minimum value of evaluation function is use to gradually decrease and increase the value of c1 and c2 respectively. Molecular energy minimization is one of the most challenging unsolved problems and it can be formulated as a global optimization problem. The aim of the present paper is to investigate the effect of newly developed APSO on the highly complex molecular potential energy function and to check the efficiency of the proposed algorithm to find the global minimum of the function under consideration. The proposed algorithm APSO is therefore applied in two cases: Firstly, for the minimization of a potential energy of small molecules with up to 100 degrees of freedom and finally for finding the global minimum energy conformation of 1,2,3-trichloro-1-flouro-propane molecule based on a realistic potential energy function. The computational results of all the cases show that the proposed method performs significantly better than the other algorithms. PMID:27491033

  12. Adaptive Particle Swarm Optimizer with Varying Acceleration Coefficients for Finding the Most Stable Conformer of Small Molecules.

    PubMed

    Agrawal, Shikha; Silakari, Sanjay; Agrawal, Jitendra

    2015-11-01

    A novel parameter automation strategy for Particle Swarm Optimization called APSO (Adaptive PSO) is proposed. The algorithm is designed to efficiently control the local search and convergence to the global optimum solution. Parameters c1 controls the impact of the cognitive component on the particle trajectory and c2 controls the impact of the social component. Instead of fixing the value of c1 and c2 , this paper updates the value of these acceleration coefficients by considering time variation of evaluation function along with varying inertia weight factor in PSO. Here the maximum and minimum value of evaluation function is use to gradually decrease and increase the value of c1 and c2 respectively. Molecular energy minimization is one of the most challenging unsolved problems and it can be formulated as a global optimization problem. The aim of the present paper is to investigate the effect of newly developed APSO on the highly complex molecular potential energy function and to check the efficiency of the proposed algorithm to find the global minimum of the function under consideration. The proposed algorithm APSO is therefore applied in two cases: Firstly, for the minimization of a potential energy of small molecules with up to 100 degrees of freedom and finally for finding the global minimum energy conformation of 1,2,3-trichloro-1-flouro-propane molecule based on a realistic potential energy function. The computational results of all the cases show that the proposed method performs significantly better than the other algorithms.

  13. Autonomous Propulsion System Technology Being Developed to Optimize Engine Performance Throughout the Lifecycle

    NASA Technical Reports Server (NTRS)

    Litt, Jonathan S.

    2004-01-01

    The goal of the Autonomous Propulsion System Technology (APST) project is to reduce pilot workload under both normal and anomalous conditions. Ongoing work under APST develops and leverages technologies that provide autonomous engine monitoring, diagnosing, and controller adaptation functions, resulting in an integrated suite of algorithms that maintain the propulsion system's performance and safety throughout its life. Engine-to-engine performance variation occurs among new engines because of manufacturing tolerances and assembly practices. As an engine wears, the performance changes as operability limits are reached. In addition to these normal phenomena, other unanticipated events such as sensor failures, bird ingestion, or component faults may occur, affecting pilot workload as well as compromising safety. APST will adapt the controller as necessary to achieve optimal performance for a normal aging engine, and the safety net of APST algorithms will examine and interpret data from a variety of onboard sources to detect, isolate, and if possible, accommodate faults. Situations that cannot be accommodated within the faulted engine itself will be referred to a higher level vehicle management system. This system will have the authority to redistribute the faulted engine's functionality among other engines, or to replan the mission based on this new engine health information. Work is currently underway in the areas of adaptive control to compensate for engine degradation due to aging, data fusion for diagnostics and prognostics of specific sensor and component faults, and foreign object ingestion detection. In addition, a framework is being defined for integrating all the components of APST into a unified system. A multivariable, adaptive, multimode control algorithm has been developed that accommodates degradation-induced thrust disturbances during throttle transients. The baseline controller of the engine model currently being investigated has multiple control

  14. A Self-adaptive Evolutionary Algorithm for Multi-objective Optimization

    NASA Astrophysics Data System (ADS)

    Cao, Ruifen; Li, Guoli; Wu, Yican

    Evolutionary algorithm has gained a worldwide popularity among multi-objective optimization. The paper proposes a self-adaptive evolutionary algorithm (called SEA) for multi-objective optimization. In the SEA, the probability of crossover and mutation,P c and P m , are varied depending on the fitness values of the solutions. Fitness assignment of SEA realizes the twin goals of maintaining diversity in the population and guiding the population to the true Pareto Front; fitness value of individual not only depends on improved density estimation but also depends on non-dominated rank. The density estimation can keep diversity in all instances including when scalars of all objectives are much different from each other. SEA is compared against the Non-dominated Sorting Genetic Algorithm (NSGA-II) on a set of test problems introduced by the MOEA community. Simulated results show that SEA is as effective as NSGA-II in most of test functions, but when scalar of objectives are much different from each other, SEA has better distribution of non-dominated solutions.

  15. Development of an adaptive hp-version finite element method for computational optimal control

    NASA Technical Reports Server (NTRS)

    Hodges, Dewey H.; Warner, Michael S.

    1994-01-01

    In this research effort, the usefulness of hp-version finite elements and adaptive solution-refinement techniques in generating numerical solutions to optimal control problems has been investigated. Under NAG-939, a general FORTRAN code was developed which approximated solutions to optimal control problems with control constraints and state constraints. Within that methodology, to get high-order accuracy in solutions, the finite element mesh would have to be refined repeatedly through bisection of the entire mesh in a given phase. In the current research effort, the order of the shape functions in each element has been made a variable, giving more flexibility in error reduction and smoothing. Similarly, individual elements can each be subdivided into many pieces, depending on the local error indicator, while other parts of the mesh remain coarsely discretized. The problem remains to reduce and smooth the error while still keeping computational effort reasonable enough to calculate time histories in a short enough time for on-board applications.

  16. Adaptive track scheduling to optimize concurrency and vectorization in GeantV

    NASA Astrophysics Data System (ADS)

    Apostolakis, J.; Bandieramonte, M.; Bitzes, G.; Brun, R.; Canal, P.; Carminati, F.; De Fine Licht, J. C.; Duhem, L.; Elvira, V. D.; Gheata, A.; Jun, S. Y.; Lima, G.; Novak, M.; Sehgal, R.; Shadura, O.; Wenzel, S.

    2015-05-01

    The GeantV project is focused on the R&D of new particle transport techniques to maximize parallelism on multiple levels, profiting from the use of both SIMD instructions and co-processors for the CPU-intensive calculations specific to this type of applications. In our approach, vectors of tracks belonging to multiple events and matching different locality criteria must be gathered and dispatched to algorithms having vector signatures. While the transport propagates tracks and changes their individual states, data locality becomes harder to maintain. The scheduling policy has to be changed to maintain efficient vectors while keeping an optimal level of concurrency. The model has complex dynamics requiring tuning the thresholds to switch between the normal regime and special modes, i.e. prioritizing events to allow flushing memory, adding new events in the transport pipeline to boost locality, dynamically adjusting the particle vector size or switching between vector to single track mode when vectorization causes only overhead. This work requires a comprehensive study for optimizing these parameters to make the behaviour of the scheduler self-adapting, presenting here its initial results.

  17. Inference for optimal dynamic treatment regimes using an adaptive m-out-of-n bootstrap scheme.

    PubMed

    Chakraborty, Bibhas; Laber, Eric B; Zhao, Yingqi

    2013-09-01

    A dynamic treatment regime consists of a set of decision rules that dictate how to individualize treatment to patients based on available treatment and covariate history. A common method for estimating an optimal dynamic treatment regime from data is Q-learning which involves nonsmooth operations of the data. This nonsmoothness causes standard asymptotic approaches for inference like the bootstrap or Taylor series arguments to breakdown if applied without correction. Here, we consider the m-out-of-n bootstrap for constructing confidence intervals for the parameters indexing the optimal dynamic regime. We propose an adaptive choice of m and show that it produces asymptotically correct confidence sets under fixed alternatives. Furthermore, the proposed method has the advantage of being conceptually and computationally much simple than competing methods possessing this same theoretical property. We provide an extensive simulation study to compare the proposed method with currently available inference procedures. The results suggest that the proposed method delivers nominal coverage while being less conservative than alternatives. The proposed methods are implemented in the qLearn R-package and have been made available on the Comprehensive R-Archive Network (http://cran.r-project.org/). Analysis of the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) study is used as an illustrative example.

  18. Monte Carlo modelling of multiconjugate adaptive optics performance on the European Extremely Large Telescope

    NASA Astrophysics Data System (ADS)

    Basden, A. G.

    2015-11-01

    The performance of a wide-field adaptive optics system depends on input design parameters. Here we investigate the performance of a multiconjugate adaptive optics system design for the European Extremely Large Telescope, using an end-to-end Monte Carlo adaptive optics simulation tool, DASP (Durham adaptive optics simulation platform). We consider parameters such as the number of laser guide stars, sodium layer depth, wavefront sensor pixel scale, number of deformable mirrors (DMs), mirror conjugation and actuator pitch. We provide potential areas where costs savings can be made, and investigate trade-offs between performance and cost. We conclude that a six-laser guide star system using three DMs seems to be a sweet spot for performance and cost compromise.

  19. Economic performance of irrigation capacity development to adapt to climate in the American Southwest

    NASA Astrophysics Data System (ADS)

    Ward, Frank A.; Crawford, Terry L.

    2016-09-01

    Growing demands for food security to feed increasing populations worldwide have intensified the search for improved performance of irrigation, the world's largest water user. These challenges are raised in the face of climate variability and from growing environmental demands. Adaptation measures in irrigated agriculture include fallowing land, shifting cropping patterns, increased groundwater pumping, reservoir storage capacity expansion, and increased production of risk-averse crops. Water users in the Gila Basin headwaters of the U.S. Lower Colorado Basin have faced a long history of high water supply fluctuations producing low-valued defensive cropping patterns. To date, little research grade analysis has investigated economically viable measures for irrigation development to adjust to variable climate. This gap has made it hard to inform water resource policy decisions on workable measures to adapt to climate in the world's dry rural areas. This paper's contribution is to illustrate, formulate, develop, and apply a new methodology to examine the economic performance from irrigation capacity improvements in the Gila Basin of the American Southwest. An integrated empirical optimization model using mathematical programming is developed to forecast cropping patterns and farm income under two scenarios (1) status quo without added storage capacity and (2) with added storage capacity in which existing barriers to development of higher valued crops are dissolved. We find that storage capacity development can lead to a higher valued portfolio of irrigation production systems as well as more sustained and higher valued farm livelihoods. Results show that compared to scenario (1), scenario (2) increases regional farm income by 30%, in which some sub regions secure income gains exceeding 900% compared to base levels. Additional storage is most economically productive when institutional and technical constraints facing irrigated agriculture are dissolved. Along with

  20. Adaptive Measurement of Well-Being: Maximizing Efficiency and Optimizing User Experience during Individual Assessment.

    PubMed

    Kraatz, Miriam; Sears, Lindsay E; Coberley, Carter R; Pope, James E

    2016-08-01

    Well-being is linked to important societal factors such as health care costs and productivity and has experienced a surge in development activity of both theories and measurement. This study builds on validation of the Well-Being 5 survey and for the first time applies Item Response Theory, a modern and flexible measurement paradigm, to form the basis of adaptive population well-being measurement. Adaptive testing allows survey questions to be administered selectively, thereby reducing the number of questions required of the participant. After the graded response model was fit to a sample of size N = 12,035, theta scores were estimated based on both the full-item bank and a simulation of Computerized Adaptive Testing (CAT). Comparisons of these 2 sets of score estimates with each other and of their correlations with external outcomes of job performance, absenteeism, and hospital admissions demonstrate that the CAT well-being scores maintain accuracy and validity. The simulation indicates that the average survey taker can expect a reduction in number of items administered during the CAT process of almost 50%. An increase in efficiency of this extent is of considerable value because of the time savings during the administration of the survey and the potential improvement of user experience, which in turn can help secure the success of a total population-based well-being improvement program. (Population Health Management 2016;19:284-290).

  1. Adaptive Measurement of Well-Being: Maximizing Efficiency and Optimizing User Experience during Individual Assessment

    PubMed Central

    Kraatz, Miriam; Coberley, Carter R.; Pope, James E.

    2016-01-01

    Abstract Well-being is linked to important societal factors such as health care costs and productivity and has experienced a surge in development activity of both theories and measurement. This study builds on validation of the Well-Being 5 survey and for the first time applies Item Response Theory, a modern and flexible measurement paradigm, to form the basis of adaptive population well-being measurement. Adaptive testing allows survey questions to be administered selectively, thereby reducing the number of questions required of the participant. After the graded response model was fit to a sample of size N = 12,035, theta scores were estimated based on both the full-item bank and a simulation of Computerized Adaptive Testing (CAT). Comparisons of these 2 sets of score estimates with each other and of their correlations with external outcomes of job performance, absenteeism, and hospital admissions demonstrate that the CAT well-being scores maintain accuracy and validity. The simulation indicates that the average survey taker can expect a reduction in number of items administered during the CAT process of almost 50%. An increase in efficiency of this extent is of considerable value because of the time savings during the administration of the survey and the potential improvement of user experience, which in turn can help secure the success of a total population-based well-being improvement program. (Population Health Management 2016;19:284–290) PMID:26674396

  2. Characterizing Decision-Analysis Performances of Risk Prediction Models Using ADAPT Curves

    PubMed Central

    Lee, Wen-Chung; Wu, Yun-Chun

    2016-01-01

    Abstract The area under the receiver operating characteristic curve is a widely used index to characterize the performance of diagnostic tests and prediction models. However, the index does not explicitly acknowledge the utilities of risk predictions. Moreover, for most clinical settings, what counts is whether a prediction model can guide therapeutic decisions in a way that improves patient outcomes, rather than to simply update probabilities. Based on decision theory, the authors propose an alternative index, the “average deviation about the probability threshold” (ADAPT). An ADAPT curve (a plot of ADAPT value against the probability threshold) neatly characterizes the decision-analysis performances of a risk prediction model. Several prediction models can be compared for their ADAPT values at a chosen probability threshold, for a range of plausible threshold values, or for the whole ADAPT curves. This should greatly facilitate the selection of diagnostic tests and prediction models. PMID:26765451

  3. SAXO: the extreme adaptive optics system of SPHERE (I) system overview and global laboratory performance

    NASA Astrophysics Data System (ADS)

    Sauvage, Jean-Francois; Fusco, Thierry; Petit, Cyril; Costille, Anne; Mouillet, David; Beuzit, Jean-Luc; Dohlen, Kjetil; Kasper, Markus; Suarez, Marcos; Soenke, Christian; Baruffolo, Andrea; Salasnich, Bernardo; Rochat, Sylvain; Fedrigo, Enrico; Baudoz, Pierre; Hugot, Emmanuel; Sevin, Arnaud; Perret, Denis; Wildi, Francois; Downing, Mark; Feautrier, Philippe; Puget, Pascal; Vigan, Arthur; O'Neal, Jared; Girard, Julien; Mawet, Dimitri; Schmid, Hans Martin; Roelfsema, Ronald

    2016-04-01

    The direct imaging of exoplanet is a leading field of today's astronomy. The photons coming from the planet carry precious information on the chemical composition of its atmosphere. The second-generation instrument, Spectro-Polarimetric High contrast Exoplanet Research (SPHERE), dedicated to detection, photometry and spectral characterization of Jovian-like planets, is now in operation on the European very large telescope. This instrument relies on an extreme adaptive optics (XAO) system to compensate for atmospheric turbulence as well as for internal errors with an unprecedented accuracy. We demonstrate the high level of performance reached by the SPHERE XAO system (SAXO) during the assembly integration and test (AIT) period. In order to fully characterize the instrument quality, two AIT periods have been mandatory. In the first phase at Observatoire de Paris, the performance of SAXO itself was assessed. In the second phase at IPAG Grenoble Observatory, the operation of SAXO in interaction with the overall instrument has been optimized. In addition to the first two phases, a final check has been performed after the reintegration of the instrument at Paranal Observatory, in the New Integration Hall before integration at the telescope focus. The final performance aimed by the SPHERE instrument with the help of SAXO is among the highest Strehl ratio pretended for an operational instrument (90% in H band, 43% in V band in a realistic turbulence r0, and wind speed condition), a limit R magnitude for loop closure at 15, and a robustness to high wind speeds. The full-width at half-maximum reached by the instrument is 40 mas for infrared in H band and unprecedented 18.5 mas in V band.

  4. Optimizing small wind turbine performance in battery charging applications

    NASA Astrophysics Data System (ADS)

    Drouilhet, Stephen; Muljadi, Eduard; Holz, Richard; Gevorgian, Vahan

    1995-05-01

    Many small wind turbine generators (10 kW or less) consist of a variable speed rotor driving a permanent magnet synchronous generator (alternator). One application of such wind turbines is battery charging, in which the generator is connected through a rectifier to a battery bank. The wind turbine electrical interface is essentially the same whether the turbine is part of a remote power supply for telecommunications, a standalone residential power system, or a hybrid village power system, in short, any system in which the wind generator output is rectified and fed into a DC bus. Field experience with such applications has shown that both the peak power output and the total energy capture of the wind turbine often fall short of expectations based on rotor size and generator rating. In this paper, the authors present a simple analytical model of the typical wind generator battery charging system that allows one to calculate actual power curves if the generator and rotor properties are known. The model clearly illustrates how the load characteristics affect the generator output. In the second part of this paper, the authors present four approaches to maximizing energy capture from wind turbines in battery charging applications. The first of these is to determine the optimal battery bank voltage for a given WTG. The second consists of adding capacitors in series with the generator. The third approach is to place an optimizing DC/DC voltage converter between the rectifier and the battery bank. The fourth is a combination of the series capacitors and the optimizing voltage controller. They also discuss both the limitations and the potential performance gain associated with each of the four configurations.

  5. Aircraft design for mission performance using nonlinear multiobjective optimization methods

    NASA Technical Reports Server (NTRS)

    Dovi, Augustine R.; Wrenn, Gregory A.

    1990-01-01

    A new technique which converts a constrained optimization problem to an unconstrained one where conflicting figures of merit may be simultaneously considered was combined with a complex mission analysis system. The method is compared with existing single and multiobjective optimization methods. A primary benefit from this new method for multiobjective optimization is the elimination of separate optimizations for each objective, which is required by some optimization methods. A typical wide body transport aircraft is used for the comparative studies.

  6. Improving BCI performance through co-adaptation: applications to the P300-speller.

    PubMed

    Mattout, Jérémie; Perrin, Margaux; Bertrand, Olivier; Maby, Emmanuel

    2015-02-01

    A well-known neurophysiological marker that can easily be captured with electroencephalography (EEG) is the so-called P300: a positive signal deflection occurring at about 300 ms after a relevant stimulus. This brain response is particularly salient when the target stimulus is rare among a series of distracting stimuli, whatever the type of sensory input. Therefore, it has been proposed and extensively studied as a possible feature for direct brain-computer communication. The most advanced non-invasive BCI application based on this principle is the P300-speller. However, it is still a matter of debate whether this application will prove relevant to any population of patients. In a series of recent theoretical and empirical studies, we have been using this P300-based paradigm to push forward the performance of non-invasive BCI. This paper summarizes the proposed improvements and obtained results. Importantly, those could be generalized to many kinds of BCI, beyond this particular application. Indeed, they relate to most of the key components of a closed-loop BCI, namely: improving the accuracy of the system by trying to detect and correct for errors automatically; optimizing the computer's speed-accuracy trade-off by endowing it with adaptive behavior; but also simplifying the hardware and time for set-up in the aim of routine use in patients. Our results emphasize the importance of the closed-loop interaction and of the ensuing co-adaptation between the user and the machine whenever possible. Most of our evaluations have been conducted in healthy subjects. We conclude with perspectives for clinical applications.

  7. Improving BCI performance through co-adaptation: applications to the P300-speller.

    PubMed

    Mattout, Jérémie; Perrin, Margaux; Bertrand, Olivier; Maby, Emmanuel

    2015-02-01

    A well-known neurophysiological marker that can easily be captured with electroencephalography (EEG) is the so-called P300: a positive signal deflection occurring at about 300 ms after a relevant stimulus. This brain response is particularly salient when the target stimulus is rare among a series of distracting stimuli, whatever the type of sensory input. Therefore, it has been proposed and extensively studied as a possible feature for direct brain-computer communication. The most advanced non-invasive BCI application based on this principle is the P300-speller. However, it is still a matter of debate whether this application will prove relevant to any population of patients. In a series of recent theoretical and empirical studies, we have been using this P300-based paradigm to push forward the performance of non-invasive BCI. This paper summarizes the proposed improvements and obtained results. Importantly, those could be generalized to many kinds of BCI, beyond this particular application. Indeed, they relate to most of the key components of a closed-loop BCI, namely: improving the accuracy of the system by trying to detect and correct for errors automatically; optimizing the computer's speed-accuracy trade-off by endowing it with adaptive behavior; but also simplifying the hardware and time for set-up in the aim of routine use in patients. Our results emphasize the importance of the closed-loop interaction and of the ensuing co-adaptation between the user and the machine whenever possible. Most of our evaluations have been conducted in healthy subjects. We conclude with perspectives for clinical applications. PMID:25623293

  8. The Adapted Dance Process: Planning, Partnering, and Performing

    ERIC Educational Resources Information Center

    Block, Betty A.; Johnson, Peggy V.

    2011-01-01

    This article contains specific planning, partnering, and performing techniques for fully integrating dancers with special needs into a dance pedagogy program. Each aspect is discussed within the context of the domains of learning. Fundamental partnering strategies are related to each domain as part of the integration process. The authors recommend…

  9. Teachers Adapt Their Instruction According to Students' Academic Performance

    ERIC Educational Resources Information Center

    Nurmi, Jari-Erik; Viljaranta, Jaana; Tolvanen, Asko; Aunola, Kaisa

    2012-01-01

    This study examined the extent to which a student's academic performance in first grade contributes to the active instruction given by a teacher to a particular student. To investigate this, 105 first graders were tested in mathematics and reading in the fall and spring of their first school year. At the same time points, their teachers filled in…

  10. High performance dosimetry calculations using adapted ray-tracing

    NASA Astrophysics Data System (ADS)

    Perrotte, Lancelot; Saupin, Guillaume

    2010-11-01

    When preparing interventions on nuclear sites, it is interesting to study different scenarios, to identify the most appropriate one for the operator(s). Using virtual reality tools is a good way to simulate the potential scenarios. Thus, taking advantage of very efficient computation times can help the user studying different complex scenarios, by immediately evaluating the impact of any changes. In the field of radiation protection, people often use computation codes based on the straight line attenuation method with build-up factors. As for other approaches, geometrical computations (finding all the interactions between radiation rays and the scene objects) remain the bottleneck of the simulation. We present in this paper several optimizations used to speed up these geometrical computations, using innovative GPU ray-tracing algorithms. For instance, we manage to compute every intersectionbetween 600 000 rays and a huge 3D industrial scene in a fraction of second. Moreover, our algorithm works the same way for both static and dynamic scenes, allowing easier study of complex intervention scenarios (where everything moves: the operator(s), the shielding objects, the radiation sources).

  11. Adapt

    NASA Astrophysics Data System (ADS)

    Bargatze, L. F.

    2015-12-01

    Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted

  12. Capsule performance optimization in the national ignition campaign

    NASA Astrophysics Data System (ADS)

    Landen, O. L.; MacGowan, B. J.; Haan, S. W.; Edwards, J.

    2010-08-01

    A capsule performance optimization campaign will be conducted at the National Ignition Facility [1] to substantially increase the probability of ignition. The campaign will experimentally correct for residual uncertainties in the implosion and hohlraum physics used in our radiation-hydrodynamic computational models before proceeding to cryogenic-layered implosions and ignition attempts. The required tuning techniques using a variety of ignition capsule surrogates have been demonstrated at the Omega facility under scaled hohlraum and capsule conditions relevant to the ignition design and shown to meet the required sensitivity and accuracy. In addition, a roll-up of all expected random and systematic uncertainties in setting the key ignition laser and target parameters due to residual measurement, calibration, cross-coupling, surrogacy, and scale-up errors has been derived that meets the required budget.

  13. Capsule Performance Optimization in the National Ignition Campaign

    SciTech Connect

    Landen, O L; MacGowan, B J; Haan, S W; Edwards, J

    2009-10-13

    A capsule performance optimization campaign will be conducted at the National Ignition Facility to substantially increase the probability of ignition. The campaign will experimentally correct for residual uncertainties in the implosion and hohlraum physics used in our radiation-hydrodynamic computational models before proceeding to cryogenic-layered implosions and ignition attempts. The required tuning techniques using a variety of ignition capsule surrogates have been demonstrated at the Omega facility under scaled hohlraum and capsule conditions relevant to the ignition design and shown to meet the required sensitivity and accuracy. In addition, a roll-up of all expected random and systematic uncertainties in setting the key ignition laser and target parameters due to residual measurement, calibration, cross-coupling, surrogacy, and scale-up errors has been derived that meets the required budget.

  14. Capsule performance optimization in the National Ignition Campaign

    SciTech Connect

    Landen, O. L.; Bradley, D. K.; Braun, D. G.; Callahan, D. A.; Celliers, P. M.; Collins, G. W.; Dewald, E. L.; Divol, L.; Glenzer, S. H.; Hamza, A.; Hicks, D. G.; Izumi, N.; Jones, O. S.; Kirkwood, R. K.; Michel, P.; Milovich, J.; Munro, D. H.; Robey, H. F.; Spears, B. K.; Thomas, C. A.

    2010-05-15

    A capsule performance optimization campaign will be conducted at the National Ignition Facility [G. H. Miller et al., Nucl. Fusion 44, 228 (2004)] to substantially increase the probability of ignition by laser-driven hohlraums [J. D. Lindl et al., Phys. Plasmas 11, 339 (2004)]. The campaign will experimentally correct for residual uncertainties in the implosion and hohlraum physics used in our radiation-hydrodynamic computational models before proceeding to cryogenic-layered implosions and ignition attempts. The required tuning techniques using a variety of ignition capsule surrogates have been demonstrated at the OMEGA facility under scaled hohlraum and capsule conditions relevant to the ignition design and shown to meet the required sensitivity and accuracy. In addition, a roll-up of all expected random and systematic uncertainties in setting the key ignition laser and target parameters due to residual measurement, calibration, cross-coupling, surrogacy, and scale-up errors has been derived that meets the required budget.

  15. Capsule performance optimization in the National Ignition Campaigna)

    NASA Astrophysics Data System (ADS)

    Landen, O. L.; Boehly, T. R.; Bradley, D. K.; Braun, D. G.; Callahan, D. A.; Celliers, P. M.; Collins, G. W.; Dewald, E. L.; Divol, L.; Glenzer, S. H.; Hamza, A.; Hicks, D. G.; Hoffman, N.; Izumi, N.; Jones, O. S.; Kirkwood, R. K.; Kyrala, G. A.; Michel, P.; Milovich, J.; Munro, D. H.; Nikroo, A.; Olson, R. E.; Robey, H. F.; Spears, B. K.; Thomas, C. A.; Weber, S. V.; Wilson, D. C.; Marinak, M. M.; Suter, L. J.; Hammel, B. A.; Meyerhofer, D. D.; Atherton, J.; Edwards, J.; Haan, S. W.; Lindl, J. D.; MacGowan, B. J.; Moses, E. I.

    2010-05-01

    A capsule performance optimization campaign will be conducted at the National Ignition Facility [G. H. Miller et al., Nucl. Fusion 44, 228 (2004)] to substantially increase the probability of ignition by laser-driven hohlraums [J. D. Lindl et al., Phys. Plasmas 11, 339 (2004)]. The campaign will experimentally correct for residual uncertainties in the implosion and hohlraum physics used in our radiation-hydrodynamic computational models before proceeding to cryogenic-layered implosions and ignition attempts. The required tuning techniques using a variety of ignition capsule surrogates have been demonstrated at the OMEGA facility under scaled hohlraum and capsule conditions relevant to the ignition design and shown to meet the required sensitivity and accuracy. In addition, a roll-up of all expected random and systematic uncertainties in setting the key ignition laser and target parameters due to residual measurement, calibration, cross-coupling, surrogacy, and scale-up errors has been derived that meets the required budget.

  16. Performance optimized, small structurally integrated ion thruster system

    NASA Technical Reports Server (NTRS)

    Hyman, J., Jr.

    1973-01-01

    A 5-cm structurally integrated ion thruster has been developed for attitude control and stationkeeping of synchronous satellites. As optimized with a conventional ion extraction system, the system demonstrates a thrust T = 0.47 mlb at a beam voltage of 1600 V, total mass efficiency of 76%, and electrical efficiency of 56%. Under the subject contract effort, no significant performance change was noted for operation with two dimensional electrostatic thrust-vectoring grids. Structural integrity with the vectoring grids was demonstrated for shock (+ or - 30 G), sinusoidal (9 G), and random (19.9 G rms) accelerations. System envelope is 31.2 cm long by 13.4 cm flange bolt circle, with a mass of 9.0 Kg, including 6.8 Kg mercury propellant.

  17. Calibration Modeling Methodology to Optimize Performance for Low Range Applications

    NASA Technical Reports Server (NTRS)

    McCollum, Raymond A.; Commo, Sean A.; Parker, Peter A.

    2010-01-01

    Calibration is a vital process in characterizing the performance of an instrument in an application environment and seeks to obtain acceptable accuracy over the entire design range. Often, project requirements specify a maximum total measurement uncertainty, expressed as a percent of full-scale. However in some applications, we seek to obtain enhanced performance at the low range, therefore expressing the accuracy as a percent of reading should be considered as a modeling strategy. For example, it is common to desire to use a force balance in multiple facilities or regimes, often well below its designed full-scale capacity. This paper presents a general statistical methodology for optimizing calibration mathematical models based on a percent of reading accuracy requirement, which has broad application in all types of transducer applications where low range performance is required. A case study illustrates the proposed methodology for the Mars Entry Atmospheric Data System that employs seven strain-gage based pressure transducers mounted on the heatshield of the Mars Science Laboratory mission.

  18. Parallel performance optimizations on unstructured mesh-based simulations

    DOE PAGES

    Sarje, Abhinav; Song, Sukhyun; Jacobsen, Douglas; Huck, Kevin; Hollingsworth, Jeffrey; Malony, Allen; Williams, Samuel; Oliker, Leonid

    2015-06-01

    This paper addresses two key parallelization challenges the unstructured mesh-based ocean modeling code, MPAS-Ocean, which uses a mesh based on Voronoi tessellations: (1) load imbalance across processes, and (2) unstructured data access patterns, that inhibit intra- and inter-node performance. Our work analyzes the load imbalance due to naive partitioning of the mesh, and develops methods to generate mesh partitioning with better load balance and reduced communication. Furthermore, we present methods that minimize both inter- and intranode data movement and maximize data reuse. Our techniques include predictive ordering of data elements for higher cache efficiency, as well as communication reduction approaches.more » We present detailed performance data when running on thousands of cores using the Cray XC30 supercomputer and show that our optimization strategies can exceed the original performance by over 2×. Additionally, many of these solutions can be broadly applied to a wide variety of unstructured grid-based computations.« less

  19. Performance analysis & optimization of well production in unconventional resource plays

    NASA Astrophysics Data System (ADS)

    Sehbi, Baljit Singh

    The Unconventional Resource Plays consisting of the lowest tier of resources (large volumes and most difficult to develop) have been the main focus of US domestic activity during recent times. Horizontal well drilling and hydraulic fracturing completion technology have been primarily responsible for this paradigm shift. The concept of drainage volume is being examined using pressure diffusion along streamlines. We use diffusive time of flight to optimize the number of hydraulic fracture stages in horizontal well application for Tight Gas reservoirs. Numerous field case histories are available in literature for optimizing number of hydraulic fracture stages, although the conclusions are case specific. In contrast, a general method is being presented that can be used to augment field experiments necessary to optimize the number of hydraulic fracture stages. The optimization results for the tight gas example are in line with the results from economic analysis. The fluid flow simulation for Naturally Fractured Reservoirs (NFR) is performed by Dual-Permeability or Dual-Porosity formulations. Microseismic data from Barnett Shale well is used to characterize the hydraulic fracture geometry. Sensitivity analysis, uncertainty assessment, manual & computer assisted history matching are integrated to develop a comprehensive workflow for building reliable reservoir simulation models. We demonstrate that incorporating proper physics of flow is the first step in building reliable reservoir simulation models. Lack of proper physics often leads to unreasonable reservoir parameter estimates. The workflow demonstrates reduced non-uniqueness for the inverse history matching problem. The behavior of near-critical fluids in Liquid Rich Shale plays defies the production behavior observed in conventional reservoir systems. In conventional reservoirs an increased gas-oil ratio is observed as flowing bottom-hole pressure is less than the saturation pressure. The production behavior is

  20. Optimal configuration of redundant inertial sensors for navigation and FDI performance.

    PubMed

    Shim, Duk-Sun; Yang, Cheol-Kwan

    2010-01-01

    This paper considers the optimal sensor configuration for inertial navigation systems which have redundant inertial sensors such as gyroscopes and accelerometers. We suggest a method to determine the optimal sensor configuration which considers both the navigation and FDI performance. Monte Carlo simulations are performed to show the performance of the suggested optimal sensor configuration method.

  1. Performance Modeling and Optimization of a High Energy CollidingBeam Simulation Code

    SciTech Connect

    Shan, Hongzhang; Strohmaier, Erich; Qiang, Ji; Bailey, David H.; Yelick, Kathy

    2006-06-01

    An accurate modeling of the beam-beam interaction is essential to maximizing the luminosity in existing and future colliders. BeamBeam3D was the first parallel code that can be used to study this interaction fully self-consistently on high-performance computing platforms. Various all-to-all personalized communication (AAPC) algorithms dominate its communication patterns, for which we developed a sequence of performance models using a series of micro-benchmarks. We find that for SMP based systems the most important performance constraint is node-adapter contention, while for 3D-Torus topologies good performance models are not possible without considering link contention. The best average model prediction error is very low on SMP based systems with of 3% to 7%. On torus based systems errors of 29% are higher but optimized performance can again be predicted within 8% in some cases. These excellent results across five different systems indicate that this methodology for performance modeling can be applied to a large class of algorithms.

  2. The Astronaut-Athlete: Optimizing Human Performance in Space.

    PubMed

    Hackney, Kyle J; Scott, Jessica M; Hanson, Andrea M; English, Kirk L; Downs, Meghan E; Ploutz-Snyder, Lori L

    2015-12-01

    It is well known that long-duration spaceflight results in deconditioning of neuromuscular and cardiovascular systems, leading to a decline in physical fitness. On reloading in gravitational environments, reduced fitness (e.g., aerobic capacity, muscular strength, and endurance) could impair human performance, mission success, and crew safety. The level of fitness necessary for the performance of routine and off-nominal terrestrial mission tasks remains an unanswered and pressing question for scientists and flight physicians. To mitigate fitness loss during spaceflight, resistance and aerobic exercise are the most effective countermeasure available to astronauts. Currently, 2.5 h·d, 6-7 d·wk is allotted in crew schedules for exercise to be performed on highly specialized hardware on the International Space Station (ISS). Exercise hardware provides up to 273 kg of loading capability for resistance exercise, treadmill speeds between 0.44 and 5.5 m·s, and cycle workloads from 0 and 350 W. Compared to ISS missions, future missions beyond low earth orbit will likely be accomplished with less vehicle volume and power allocated for exercise hardware. Concomitant factors, such as diet and age, will also affect the physiologic responses to exercise training (e.g., anabolic resistance) in the space environment. Research into the potential optimization of exercise countermeasures through use of dietary supplementation, and pharmaceuticals may assist in reducing physiological deconditioning during long-duration spaceflight and have the potential to enhance performance of occupationally related astronaut tasks (e.g., extravehicular activity, habitat construction, equipment repairs, planetary exploration, and emergency response).

  3. The Astronaut-Athlete: Optimizing Human Performance in Space.

    PubMed

    Hackney, Kyle J; Scott, Jessica M; Hanson, Andrea M; English, Kirk L; Downs, Meghan E; Ploutz-Snyder, Lori L

    2015-12-01

    It is well known that long-duration spaceflight results in deconditioning of neuromuscular and cardiovascular systems, leading to a decline in physical fitness. On reloading in gravitational environments, reduced fitness (e.g., aerobic capacity, muscular strength, and endurance) could impair human performance, mission success, and crew safety. The level of fitness necessary for the performance of routine and off-nominal terrestrial mission tasks remains an unanswered and pressing question for scientists and flight physicians. To mitigate fitness loss during spaceflight, resistance and aerobic exercise are the most effective countermeasure available to astronauts. Currently, 2.5 h·d, 6-7 d·wk is allotted in crew schedules for exercise to be performed on highly specialized hardware on the International Space Station (ISS). Exercise hardware provides up to 273 kg of loading capability for resistance exercise, treadmill speeds between 0.44 and 5.5 m·s, and cycle workloads from 0 and 350 W. Compared to ISS missions, future missions beyond low earth orbit will likely be accomplished with less vehicle volume and power allocated for exercise hardware. Concomitant factors, such as diet and age, will also affect the physiologic responses to exercise training (e.g., anabolic resistance) in the space environment. Research into the potential optimization of exercise countermeasures through use of dietary supplementation, and pharmaceuticals may assist in reducing physiological deconditioning during long-duration spaceflight and have the potential to enhance performance of occupationally related astronaut tasks (e.g., extravehicular activity, habitat construction, equipment repairs, planetary exploration, and emergency response). PMID:26595138

  4. Whole cell electrochemistry of electricity-producing microorganisms evidence an adaptation for optimal exocellular electron transport.

    PubMed

    Busalmen, Juan Pablo; Esteve-Nuñez, Abraham; Feliu, Juan Miguel

    2008-04-01

    The mechanism(s) by which electricity-producing microorganisms interact with an electrode is poorly understood. Outer membrane cytochromes and conductive pili are being considered as possible players, but the available information does not concur to a consensus mechanism yet. In this work we demonstrate that Geobacter sulfurreducens cells are able to change the way in which they exchange electrons with an electrode as a response to changes in the applied electrode potential. After several hours of polarization at 0.1 V Ag/AgCl-KCl (saturated), the voltammetric signature of the attached cells showed a single redox pair with a formal redox potential of about -0.08 V as calculated from chronopotentiometric analysis. A similar signal was obtained from cells adapted to 0.4 V. However, new redox couples were detected after conditioning at 0.6 V. A large oxidation process beyond 0.5 V transferring a higher current than that obtained at 0.1 V was found to be associated with two reduction waves at 0.23 and 0.50 V. The apparent equilibrium potential of these new processes was estimated to be at about 0.48 V from programmed current potentiometric results. Importantly, when polarization was lowered again to 0.1 V for 18 additional hours, the signals obtained at 0.6 V were found to greatly diminish in amplitude, whereas those previously found at the lower conditioning potential were recovered. Results clearly show the reversibility of cell adaptation to the electrode potential and pointto the polarization potential as a key variable to optimize energy production from an electricity producing population.

  5. Whole cell electrochemistry of electricity-producing microorganisms evidence an adaptation for optimal exocellular electron transport.

    PubMed

    Busalmen, Juan Pablo; Esteve-Nuñez, Abraham; Feliu, Juan Miguel

    2008-04-01

    The mechanism(s) by which electricity-producing microorganisms interact with an electrode is poorly understood. Outer membrane cytochromes and conductive pili are being considered as possible players, but the available information does not concur to a consensus mechanism yet. In this work we demonstrate that Geobacter sulfurreducens cells are able to change the way in which they exchange electrons with an electrode as a response to changes in the applied electrode potential. After several hours of polarization at 0.1 V Ag/AgCl-KCl (saturated), the voltammetric signature of the attached cells showed a single redox pair with a formal redox potential of about -0.08 V as calculated from chronopotentiometric analysis. A similar signal was obtained from cells adapted to 0.4 V. However, new redox couples were detected after conditioning at 0.6 V. A large oxidation process beyond 0.5 V transferring a higher current than that obtained at 0.1 V was found to be associated with two reduction waves at 0.23 and 0.50 V. The apparent equilibrium potential of these new processes was estimated to be at about 0.48 V from programmed current potentiometric results. Importantly, when polarization was lowered again to 0.1 V for 18 additional hours, the signals obtained at 0.6 V were found to greatly diminish in amplitude, whereas those previously found at the lower conditioning potential were recovered. Results clearly show the reversibility of cell adaptation to the electrode potential and pointto the polarization potential as a key variable to optimize energy production from an electricity producing population. PMID:18504979

  6. Robust active combustion control for the optimization of environmental performance and energy efficiency

    NASA Astrophysics Data System (ADS)

    Demayo, Trevor Nat

    Criteria pollutant regulations, climate change concerns, and energy conservation efforts are placing strict constraints in the design and operation of advanced, stationary combustion systems. To ensure minimal pollutant emissions and maximal efficiency at every instant of operation while preventing reaction blowout, combustion systems need to react and adapt in real-time to external changes. This study describes the development, demonstration, and evaluation of a multivariable feedback control system, designed to maximize the performance of natural gas-fired combustion systems. A feedback sensor array was developed to monitor reaction stability and measure combustion performance as a function of NOx, CO, and O, emissions. Acoustic and UV chemiluminescent emissions were investigated for use as stability indicators. Modulated signals of CH* and CO2* chemiluminescence were found to correlate well with the onset of lean blowout. A variety of emissions sensors were tested and evaluated, including conventional CEMS', micro-fuel cells, a zirconia NOx transducer, and a rapid response predictive NOx sensor based on UV flame chemiluminescence. A dual time-scale controller was designed to actively optimize operating conditions by maximizing a multivariable performance function J using a linear direction set search algorithm. The controller evaluated J under slow, quasi steady-state conditions, while dynamically monitoring the reaction zone at high speed for pre-blowout instabilities or boundary condition violations. To establish the input control parameters, two burner systems were selected: a 30 kW air-swirl, generic research burner, and a 120 kW scaled, fuel-staged, industrial boiler burner. The parameters, chosen to most affect burner performance, consisted of air swirl intensity and excess air for the generic burner, and fuel-staging and excess air for the boiler burner. A set of optimization parameters was also established to ensure efficient and deterministic

  7. Cyclone performance and optimization: First quarterly progress report

    SciTech Connect

    Leith, D.

    1987-12-15

    The objectives of this project are: to characterize the gas flow pattern within cyclones, to revise the theory for cyclone performance on the basis of these findings, and to design and test cyclones whose dimensions have been optimized using revised performance theory. This work is impoortant because its successful completion will aid in the technology for combustion of coal in pressurized, fluidized beds. The project is on or ahead of schedule. During this time, the laboratory scale equipment necessary for this project has been constructed and used to make measurements of the gas flow pattern within cyclones. Tangential gas velocities for a matrix of eleven different cuclones and operating conditions have been measured. For each different test condition tangential velocities over a wide range of axial and radial positions have been measured. In addition, the literature search that began while the proposal for this work was written has been continued. The computer and printer necessary for modeling the experimental results have been ordered and received. 1 fig.

  8. Performance Optimization of the Gasdynamic Mirror Propulsion System

    NASA Technical Reports Server (NTRS)

    Emrich, William J., Jr.; Kammash, Terry

    1999-01-01

    Nuclear fusion appears to be a most promising concept for producing extremely high specific impulse rocket engines. Engines such as these would effectively open up the solar system to human exploration and would virtually eliminate launch window restrictions. A preliminary vehicle sizing and mission study was performed based on the conceptual design of a Gasdynamic Mirror (GDM) fusion propulsion system. This study indicated that the potential specific impulse for this engine is approximately 142,000 sec. with about 22,100 N of thrust using a deuterium-tritium fuel cycle. The engine weight inclusive of the power conversion system was optimized around an allowable engine mass of 1500 Mg assuming advanced superconducting magnets and a Field Reversed Configuration (FRC) end plug at the mirrors. The vehicle habitat, lander, and structural weights are based on a NASA Mars mission study which assumes the use of nuclear thermal propulsion' Several manned missions to various planets were analyzed to determine fuel requirements and launch windows. For all fusion propulsion cases studied, the fuel weight remained a minor component of the total system weight regardless of when the missions commenced. In other words, the use of fusion propulsion virtually eliminates all mission window constraints and effectively allows unlimited manned exploration of the entire solar system. It also mitigates the need to have a large space infrastructure which would be required to support the transfer of massive amounts of fuel and supplies to lower a performing spacecraft.

  9. Production of cold-adapted amylase by marine bacterium Wangia sp. C52: optimization, modeling, and partial characterization.

    PubMed

    Liu, Jianguo; Zhang, Zhiqiang; Liu, Zhiqiang; Zhu, Hu; Dang, Hongyue; Lu, Jianren; Cui, Zhanfeng

    2011-10-01

    The aim of this work was to optimize the fermentation parameters in the shake-flask culture of marine bacterium Wangia sp. C52 to increase cold-adapted amylase production using two statistical experimental methods including Plackett-Burman design, which was applied to find the key ingredients for the best medium composition, and response surface methodology, which was used to determine the optimal concentrations of these components. The results showed starch, tryptone, and initial pH had significant effects on the cold-adapted amylase production. A central composite design was then employed to further optimize these three factors. The experimental results indicated that the optimized composition of medium was 6.38 g  L(-1) starch, 33.84 g  L(-1) tryptone, 3.00 g  L(-1) yeast extract, 30 g  L(-1) NaCl, 0.60 g  L(-1) MgSO(4) and 0.56 g  L(-1) CaCl(2). The optimized cultivation conditions for amylase production were pH 7.18, a temperature of 20°C, and a shaking speed of 180 rpm. Under the proposed optimized conditions, the amylase experimental yield (676.63 U  mL(-1)) closely matched the yield (685.60 U  mL(-1)) predicted by the statistical model. The optimization of the medium contributed to tenfold higher amylase production than that of the control in shake-flask experiments.

  10. Adaptation of the CVT algorithm for catheter optimization in high dose rate brachytherapy

    SciTech Connect

    Poulin, Eric; Fekete, Charles-Antoine Collins; Beaulieu, Luc; Létourneau, Mélanie; Fenster, Aaron; Pouliot, Jean

    2013-11-15

    Purpose: An innovative, simple, and fast method to optimize the number and position of catheters is presented for prostate and breast high dose rate (HDR) brachytherapy, both for arbitrary templates or template-free implants (such as robotic templates).Methods: Eight clinical cases were chosen randomly from a bank of patients, previously treated in our clinic to test our method. The 2D Centroidal Voronoi Tessellations (CVT) algorithm was adapted to distribute catheters uniformly in space, within the maximum external contour of the planning target volume. The catheters optimization procedure includes the inverse planning simulated annealing algorithm (IPSA). Complete treatment plans can then be generated from the algorithm for different number of catheters. The best plan is chosen from different dosimetry criteria and will automatically provide the number of catheters and their positions. After the CVT algorithm parameters were optimized for speed and dosimetric results, it was validated against prostate clinical cases, using clinically relevant dose parameters. The robustness to implantation error was also evaluated. Finally, the efficiency of the method was tested in breast interstitial HDR brachytherapy cases.Results: The effect of the number and locations of the catheters on prostate cancer patients was studied. Treatment plans with a better or equivalent dose distributions could be obtained with fewer catheters. A better or equal prostate V100 was obtained down to 12 catheters. Plans with nine or less catheters would not be clinically acceptable in terms of prostate V100 and D90. Implantation errors up to 3 mm were acceptable since no statistical difference was found when compared to 0 mm error (p > 0.05). No significant difference in dosimetric indices was observed for the different combination of parameters within the CVT algorithm. A linear relation was found between the number of random points and the optimization time of the CVT algorithm. Because the

  11. EXPLOITATION AND OPTIMIZATION OF RESERVOIR PERFORMANCE IN HUNTON FORMATION, OKLAHOMA

    SciTech Connect

    Mohan Kelkar

    2002-09-30

    The main objectives of the proposed study are as follows: (1) To understand and evaluate an unusual primary oil production mechanism which results in decreasing (retrograde) oil cut (ROC) behavior as reservoir pressure declines. (2) To improve calculations of initial oil in place so as to determine the economic feasibility of completing and producing a well. (3) To optimize the location of new wells based on understanding of geological and petrophysical properties heterogeneities. (4) To evaluate various secondary recovery techniques for oil reservoirs producing from fractured formations. (5) To enhance the productivity of producing wells by using new completion techniques. These objectives are important for optimizing field performance from West Carney Field located in Lincoln County, Oklahoma. The field, which was discovered in 1980, produces from Hunton Formation in a shallow-shelf carbonate reservoir. The early development in the field was sporadic. Many of the initial wells were abandoned due to high water production and constraints in surface facilities for disposing excess produced water. The field development began in earnest in 1995 by Altex Resources. They had recognized that production from this field was only possible if large volumes of water can be disposed. Being able to dispose large amounts of water, Altex aggressively drilled several producers. With few exceptions, all these wells exhibited similar characteristics. The initial production indicated trace amount of oil and gas with mostly water as dominant phase. As the reservoir was depleted, the oil cut eventually improved, making the overall production feasible. The decreasing oil cut (ROC) behavior has not been well understood. However, the field has been subjected to intense drilling activity because of prior success of Altex Resources. In this work, we will investigate the primary production mechanism by conducting several core flood experiments. After collecting cores from representative

  12. Neural network-based optimal adaptive output feedback control of a helicopter UAV.

    PubMed

    Nodland, David; Zargarzadeh, Hassan; Jagannathan, Sarangapani

    2013-07-01

    Helicopter unmanned aerial vehicles (UAVs) are widely used for both military and civilian operations. Because the helicopter UAVs are underactuated nonlinear mechanical systems, high-performance controller design for them presents a challenge. This paper introduces an optimal controller design via an output feedback for trajectory tracking of a helicopter UAV, using a neural network (NN). The output-feedback control system utilizes the backstepping methodology, employing kinematic and dynamic controllers and an NN observer. The online approximator-based dynamic controller learns the infinite-horizon Hamilton-Jacobi-Bellman equation in continuous time and calculates the corresponding optimal control input by minimizing a cost function, forward-in-time, without using the value and policy iterations. Optimal tracking is accomplished by using a single NN utilized for the cost function approximation. The overall closed-loop system stability is demonstrated using Lyapunov analysis. Finally, simulation results are provided to demonstrate the effectiveness of the proposed control design for trajectory tracking. PMID:24808521

  13. Capsule Performance Optimization for the National Ignition Facility

    NASA Astrophysics Data System (ADS)

    Landen, Otto

    2009-11-01

    The overall goal of the capsule performance optimization campaign is to maximize the probability of ignition by experimentally correcting for likely residual uncertainties in the implosion and hohlraum physics used in our radiation-hydrodynamic computational models before proceeding to cryogenic-layered implosions and ignition attempts. This will be accomplished using a variety of targets that will set key laser, hohlraum and capsule parameters to maximize ignition capsule implosion velocity, while minimizing fuel adiabat, core shape asymmetry and ablator-fuel mix. The targets include high Z re-emission spheres setting foot symmetry through foot cone power balance [1], liquid Deuterium-filled ``keyhole'' targets setting shock speed and timing through the laser power profile [2], symmetry capsules setting peak cone power balance and hohlraum length [3], and streaked x-ray backlit imploding capsules setting ablator thickness [4]. We will show how results from successful tuning technique demonstration shots performed at the Omega facility under scaled hohlraum and capsule conditions relevant to the ignition design meet the required sensitivity and accuracy. We will also present estimates of all expected random and systematic uncertainties in setting the key ignition laser and target parameters due to residual measurement, calibration, cross-coupling, surrogacy, and scale-up errors, and show that these get reduced after a number of shots and iterations to meet an acceptable level of residual uncertainty. Finally, we will present results from upcoming tuning technique validation shots performed at NIF at near full-scale. Prepared by LLNL under Contract DE-AC52-07NA27344. [4pt] [1] E. Dewald, et. al. Rev. Sci. Instrum. 79 (2008) 10E903. [0pt] [2] T.R. Boehly, et. al., Phys. Plasmas 16 (2009) 056302. [0pt] [3] G. Kyrala, et. al., BAPS 53 (2008) 247. [0pt] [4] D. Hicks, et. al., BAPS 53 (2008) 2.

  14. EXPLOITATION AND OPTIMIZATION OF RESERVOIR PERFORMANCE IN HUNTON FORMATION, OKLAHOMA

    SciTech Connect

    Mohan Kelkar

    2003-01-01

    The main objectives of the proposed study are as follows: (1) To understand and evaluate an unusual primary oil production mechanism which results in decreasing (retrograde) oil cut (ROC) behavior as reservoir pressure declines. (2) To improve calculations of initial oil in place so as to determine the economic feasibility of completing and producing a well. (3) To optimize the location of new wells based on understanding of geological and petrophysical properties heterogeneities. (4) To evaluate various secondary recovery techniques for oil reservoirs producing from fractured formations. (5) To enhance the productivity of producing wells by using new completion techniques. These objectives are important for optimizing field performance from West Carney Field located in Lincoln County, Oklahoma. The field, which was discovered in 1980, produces from Hunton Formation in a shallow-shelf carbonate reservoir. The early development in the field was sporadic. Many of the initial wells were abandoned due to high water production and constraints in surface facilities for disposing excess produced water. The field development began in earnest in 1995 by Altex Resources. They had recognized that production from this field was only possible if large volumes of water can be disposed. Being able to dispose large amounts of water, Altex aggressively drilled several producers. With few exceptions, all these wells exhibited similar characteristics. The initial production indicated trace amount of oil and gas with mostly water as dominant phase. As the reservoir was depleted, the oil cut eventually improved, making the overall production feasible. The decreasing oil cut (ROC) behavior has not been well understood. However, the field has been subjected to intense drilling activity because of prior success of Altex Resources. In this work, we will investigate the primary production mechanism by conducting several core flood experiments. After collecting cores from representative

  15. Performing aggressive code optimization with an ability to rollback changes made by the aggressive optimizations

    DOEpatents

    Gschwind, Michael K

    2013-07-23

    Mechanisms for aggressively optimizing computer code are provided. With these mechanisms, a compiler determines an optimization to apply to a portion of source code and determines if the optimization as applied to the portion of source code will result in unsafe optimized code that introduces a new source of exceptions being generated by the optimized code. In response to a determination that the optimization is an unsafe optimization, the compiler generates an aggressively compiled code version, in which the unsafe optimization is applied, and a conservatively compiled code version in which the unsafe optimization is not applied. The compiler stores both versions and provides them for execution. Mechanisms are provided for switching between these versions during execution in the event of a failure of the aggressively compiled code version. Moreover, predictive mechanisms are provided for predicting whether such a failure is likely.

  16. Adaptive GSA-based optimal tuning of PI controlled servo systems with reduced process parametric sensitivity, robust stability and controller robustness.

    PubMed

    Precup, Radu-Emil; David, Radu-Codrut; Petriu, Emil M; Radac, Mircea-Bogdan; Preitl, Stefan

    2014-11-01

    This paper suggests a new generation of optimal PI controllers for a class of servo systems characterized by saturation and dead zone static nonlinearities and second-order models with an integral component. The objective functions are expressed as the integral of time multiplied by absolute error plus the weighted sum of the integrals of output sensitivity functions of the state sensitivity models with respect to two process parametric variations. The PI controller tuning conditions applied to a simplified linear process model involve a single design parameter specific to the extended symmetrical optimum (ESO) method which offers the desired tradeoff to several control system performance indices. An original back-calculation and tracking anti-windup scheme is proposed in order to prevent the integrator wind-up and to compensate for the dead zone nonlinearity of the process. The minimization of the objective functions is carried out in the framework of optimization problems with inequality constraints which guarantee the robust stability with respect to the process parametric variations and the controller robustness. An adaptive gravitational search algorithm (GSA) solves the optimization problems focused on the optimal tuning of the design parameter specific to the ESO method and of the anti-windup tracking gain. A tuning method for PI controllers is proposed as an efficient approach to the design of resilient control systems. The tuning method and the PI controllers are experimentally validated by the adaptive GSA-based tuning of PI controllers for the angular position control of a laboratory servo system. PMID:25330468

  17. Charging Guidance of Electric Taxis Based on Adaptive Particle Swarm Optimization

    PubMed Central

    Niu, Liyong; Zhang, Di

    2015-01-01

    Electric taxis are playing an important role in the application of electric vehicles. The actual operational data of electric taxis in Shenzhen, China, is analyzed, and, in allusion to the unbalanced time availability of the charging station equipment, the electric taxis charging guidance system is proposed basing on the charging station information and vehicle information. An electric taxis charging guidance model is established and guides the charging based on the positions of taxis and charging stations with adaptive mutation particle swarm optimization. The simulation is based on the actual data of Shenzhen charging stations, and the results show that electric taxis can be evenly distributed to the appropriate charging stations according to the charging pile numbers in charging stations after the charging guidance. The even distribution among the charging stations in the area will be achieved and the utilization of charging equipment will be improved, so the proposed charging guidance method is verified to be feasible. The improved utilization of charging equipment can save public charging infrastructure resources greatly. PMID:26236770

  18. Charging Guidance of Electric Taxis Based on Adaptive Particle Swarm Optimization.

    PubMed

    Niu, Liyong; Zhang, Di

    2015-01-01

    Electric taxis are playing an important role in the application of electric vehicles. The actual operational data of electric taxis in Shenzhen, China, is analyzed, and, in allusion to the unbalanced time availability of the charging station equipment, the electric taxis charging guidance system is proposed basing on the charging station information and vehicle information. An electric taxis charging guidance model is established and guides the charging based on the positions of taxis and charging stations with adaptive mutation particle swarm optimization. The simulation is based on the actual data of Shenzhen charging stations, and the results show that electric taxis can be evenly distributed to the appropriate charging stations according to the charging pile numbers in charging stations after the charging guidance. The even distribution among the charging stations in the area will be achieved and the utilization of charging equipment will be improved, so the proposed charging guidance method is verified to be feasible. The improved utilization of charging equipment can save public charging infrastructure resources greatly.

  19. Charging Guidance of Electric Taxis Based on Adaptive Particle Swarm Optimization.

    PubMed

    Niu, Liyong; Zhang, Di

    2015-01-01

    Electric taxis are playing an important role in the application of electric vehicles. The actual operational data of electric taxis in Shenzhen, China, is analyzed, and, in allusion to the unbalanced time availability of the charging station equipment, the electric taxis charging guidance system is proposed basing on the charging station information and vehicle information. An electric taxis charging guidance model is established and guides the charging based on the positions of taxis and charging stations with adaptive mutation particle swarm optimization. The simulation is based on the actual data of Shenzhen charging stations, and the results show that electric taxis can be evenly distributed to the appropriate charging stations according to the charging pile numbers in charging stations after the charging guidance. The even distribution among the charging stations in the area will be achieved and the utilization of charging equipment will be improved, so the proposed charging guidance method is verified to be feasible. The improved utilization of charging equipment can save public charging infrastructure resources greatly. PMID:26236770

  20. Performance benefits of adaptive, multimicrophone, interference-canceling systems in everyday environments

    NASA Astrophysics Data System (ADS)

    Desloge, Joseph G.; Zimmer, Martin J.; Zurek, Patrick M.

    2001-05-01

    Adaptive multimicrophone systems are currently used for a variety of noise-cancellation applications (such as hearing aids) to preserve signals arriving from a particular (target) direction while canceling other (jammer) signals in the environment. Although the performance of these systems is known to degrade with increasing reverberation, there are few measurements of adaptive performance in everyday reverberant environments. In this study, adaptive performance was compared to that of a simple, nonadaptive cardioid microphone to determine a measure of adaptive benefit. Both systems used recordings (at an Fs of 22050 Hz) from the same two omnidirectional microphones, which were separated by 1 cm. Four classes of environment were considered: outdoors, household, parking garage, and public establishment. Sources were either environmental noises (e.g., household appliances, restaurant noise) or a controlled noise source. In all situations, no target was present (i.e., all signals were jammers) to obtain maximal jammer cancellation. Adaptive processing was based upon the Griffiths-Jim generalized sidelobe canceller using filter lengths up to 400 points. Average intelligibility-weighted adaptive benefit levels at a source distance of 1 m were, at most, 1.5 dB for public establishments, 2 dB for household rooms and the parking garage, and 3 dB outdoors. [Work supported by NIOSH.

  1. Fast simulated annealing and adaptive Monte Carlo sampling based parameter optimization for dense optical-flow deformable image registration of 4DCT lung anatomy

    NASA Astrophysics Data System (ADS)

    Dou, Tai H.; Min, Yugang; Neylon, John; Thomas, David; Kupelian, Patrick; Santhanam, Anand P.

    2016-03-01

    Deformable image registration (DIR) is an important step in radiotherapy treatment planning. An optimal input registration parameter set is critical to achieve the best registration performance with the specific algorithm. Methods In this paper, we investigated a parameter optimization strategy for Optical-flow based DIR of the 4DCT lung anatomy. A novel fast simulated annealing with adaptive Monte Carlo sampling algorithm (FSA-AMC) was investigated for solving the complex non-convex parameter optimization problem. The metric for registration error for a given parameter set was computed using landmark-based mean target registration error (mTRE) between a given volumetric image pair. To reduce the computational time in the parameter optimization process, a GPU based 3D dense optical-flow algorithm was employed for registering the lung volumes. Numerical analyses on the parameter optimization for the DIR were performed using 4DCT datasets generated with breathing motion models and open-source 4DCT datasets. Results showed that the proposed method efficiently estimated the optimum parameters for optical-flow and closely matched the best registration parameters obtained using an exhaustive parameter search method.

  2. Interactive Genetic Algorithm - An Adaptive and Interactive Decision Support Framework for Design of Optimal Groundwater Monitoring Plans

    NASA Astrophysics Data System (ADS)

    Babbar-Sebens, M.; Minsker, B. S.

    2006-12-01

    In the water resources management field, decision making encompasses many kinds of engineering, social, and economic constraints and objectives. Representing all of these problem dependant criteria through models (analytical or numerical) and various formulations (e.g., objectives, constraints, etc.) within an optimization- simulation system can be a very non-trivial issue. Most models and formulations utilized for discerning desirable traits in a solution can only approximate the decision maker's (DM) true preference criteria, and they often fail to consider important qualitative and incomputable phenomena related to the management problem. In our research, we have proposed novel decision support frameworks that allow DMs to actively participate in the optimization process. The DMs explicitly indicate their true preferences based on their subjective criteria and the results of various simulation models and formulations. The feedback from the DMs is then used to guide the search process towards solutions that are "all-rounders" from the perspective of the DM. The two main research questions explored in this work are: a) Does interaction between the optimization algorithm and a DM assist the system in searching for groundwater monitoring designs that are robust from the DM's perspective?, and b) How can an interactive search process be made more effective when human factors, such as human fatigue and cognitive learning processes, affect the performance of the algorithm? The application of these frameworks on a real-world groundwater long-term monitoring (LTM) case study in Michigan highlighted the following salient advantages: a) in contrast to the non-interactive optimization methodology, the proposed interactive frameworks were able to identify low cost monitoring designs whose interpolation maps respected the expected spatial distribution of the contaminants, b) for many same-cost designs, the interactive methodologies were able to propose multiple alternatives

  3. Link performance optimization for digital satellite broadcasting systems

    NASA Astrophysics Data System (ADS)

    de Gaudenzi, R.; Elia, C.; Viola, R.

    The authors introduce the concept of digital direct satellite broadcasting (D-DBS), which allows unprecedented flexibility by providing a large number of audiovisual services. The concept assumes an information rate of 40 Mb/s, which is compatible with practically all present-day transponders. After discussion of the general system concept, the results of transmission system optimization are presented. Channel and interference effects are taken into account. Numerical results show that the scheme with the best performance is trellis-coded 8-PSK (phase shift keying) modulation concatenated with Reed-Solomon block code. For a net data rate of 40 Mb/s a bit error rate of 10-10 can be achieved with an equivalent bit energy to noise density of 9.5 dB, including channel, interference, and demodulator impairments. A link budget analysis shows how a medium-power direct-to-home TV satellite can provide multimedia services to users equipped with small (60-cm) dish antennas.

  4. Development of a real-time transport performance optimization methodology

    NASA Technical Reports Server (NTRS)

    Gilyard, Glenn

    1996-01-01

    The practical application of real-time performance optimization is addressed (using a wide-body transport simulation) based on real-time measurements and calculation of incremental drag from forced response maneuvers. Various controller combinations can be envisioned although this study used symmetric outboard aileron and stabilizer. The approach is based on navigation instrumentation and other measurements found on state-of-the-art transports. This information is used to calculate winds and angle of attack. Thrust is estimated from a representative engine model as a function of measured variables. The lift and drag equations are then used to calculate lift and drag coefficients. An expression for drag coefficient, which is a function of parasite drag, induced drag, and aileron drag, is solved from forced excitation response data. Estimates of the parasite drag, curvature of the aileron drag variation, and minimum drag aileron position are produced. Minimum drag is then obtained by repositioning the symmetric aileron. Simulation results are also presented which evaluate the affects of measurement bias and resolution.

  5. Materials Testing and Performance Optimization for the SAMURAI-TPC

    NASA Astrophysics Data System (ADS)

    Long, K. D.; Lynch, W. G.; Barney, J.; Chajecki, Z.; Estee, J.; Shane, R.; Tangwanchareon, S.; Tsang, M. B.; Yurkon, J.

    2012-10-01

    The SAMURAI time-projection chamber (TPC) will be used to make measurements of pion spectra from heavy ion collisions at RIBF in Japan. Such research provides an opportunity to study supra-saturation density neutron-rich matter in the laboratory, and is critical to understanding the structure of neutron stars. It will provide a complete, 3D picture of the ionization deposited in a gas volume, from which particle types and momenta can be determined. The gas-containment volume is composed of surfaces of aluminum and plastic, as well as halogen-free printed circuit board. During multiplication of the ionized electrons at the anode wire plane of the TPC, UV photons are produced. These cause unwanted discharges when they interact with oxidized aluminum surfaces, which have low work functions. This problem can be addressed by application of a suitable conductive paint or epoxy. Paints were investigated to insure they did not contain any materials capable of inhibiting the performance of the detector gas. These investigations were cross-checked by tests carried out using an existing BRAHMS-TPC. Details on these tests and the materials chosen will be shown. The design and optimization of the gating grid, used to limit data collection to triggered events, will also be discussed.

  6. Nutrition for optimal performance during exercise: carbohydrate and fat.

    PubMed

    Brown, Rachel C

    2002-08-01

    Traditionally, high-carbohydrate diets have been recommended for endurance and ultra-endurance athletes. For many endurance events, the habitual consumption of a high-carbohydrate diet, with supplemental carbohydrate before and during exercise, is appropriate for many athletes. However, there are some situations for which alternative dietary options are beneficial. Diets relatively higher in fat than is currently recommended may be beneficial for exercise in which energy expenditure is high and time for recovery is limited, and for events in which athletes transport their food supply. The number of grueling events that challenge the limits of human endurance is increasing. Such events are also challenging the limits of current dietary recommendations, which may need to be expanded to allow for easier consumption of sufficient calories to minimize loss of lean body mass. The choice of diet for optimal physical performance depends on several factors, including type and duration of exercise, total energy expenditure, time for recovery, dietary preference of the athlete, and whether or not the sporting event is unassisted (and hence athletes are required to transport their food). A variety of diets ranging in macronutrient composition may be recommended based on these parameters.

  7. Preliminary evaluation and comparison of atmospheric turbulence rejection performance for infinite and receding horizon control in adaptive optics systems

    NASA Astrophysics Data System (ADS)

    Konnik, Mikhail V.; De Dona, Jose

    2014-07-01

    Model-based optimal control such as Linear Quadratic Gaussian (LQG) control has been attracting considerable attention for adaptive optics systems. The ability of LQG to handle the complex dynamics of deformable mirrors and its relatively simple implementation makes LQG attractive for large adaptive optics systems. However, LQG has its own share of drawbacks, such as suboptimal handling of constraints on actuators movements and possible numerical problems in case of fast sampling rate discretization of the corresponding matrices. Unlike LQG, the Receding Horizon Control (RHC) technique provides control signals for a deformable mirror that are optimal within the prescribed constraints. This is achieved by reformulating the control problem as an online optimization problem that is solved at each sampling instance. In the unconstrained case, RHC produces the same control signals as LQG. However, when the control signals reach the constraints of actuator's allowable movement in a deformable mirror, RHC finds the control signals that are optimal within those constraints, rather than just clipping the unconstrained optimum as commonly done in LQG control. The article discusses the consequences of high-gain LQG control operation in the case when the constraints on the actuator's movement are reached. It is shown that clipping / saturating the control signals is not only suboptimal, but may be hazardous for the surface of a deformable mirror. The results of numerical simulations indicate that high-gain LQG control can lead to abrupt changes and spikes in the control signal when saturation occurs. The article further discusses a possible link between high-gain LQG and the waffle mode in the closed-loop operation of astronomical adaptive optics systems. Performance evaluation of Receding Horizon Control in terms of atmospheric disturbance rejection and a comparison with Linear Quadratic Gaussian control are performed. The results of the numerical simulations suggest that the

  8. Smart Swarms of Bacteria-Inspired Agents with Performance Adaptable Interactions

    PubMed Central

    Shklarsh, Adi; Ariel, Gil; Schneidman, Elad; Ben-Jacob, Eshel

    2011-01-01

    Collective navigation and swarming have been studied in animal groups, such as fish schools, bird flocks, bacteria, and slime molds. Computer modeling has shown that collective behavior of simple agents can result from simple interactions between the agents, which include short range repulsion, intermediate range alignment, and long range attraction. Here we study collective navigation of bacteria-inspired smart agents in complex terrains, with adaptive interactions that depend on performance. More specifically, each agent adjusts its interactions with the other agents according to its local environment – by decreasing the peers' influence while navigating in a beneficial direction, and increasing it otherwise. We show that inclusion of such performance dependent adaptable interactions significantly improves the collective swarming performance, leading to highly efficient navigation, especially in complex terrains. Notably, to afford such adaptable interactions, each modeled agent requires only simple computational capabilities with short-term memory, which can easily be implemented in simple swarming robots. PMID:21980274

  9. Integer-linear-programing optimization in scalable video multicast with adaptive modulation and coding in wireless networks.

    PubMed

    Lee, Dongyul; Lee, Chaewoo

    2014-01-01

    The advancement in wideband wireless network supports real time services such as IPTV and live video streaming. However, because of the sharing nature of the wireless medium, efficient resource allocation has been studied to achieve a high level of acceptability and proliferation of wireless multimedia. Scalable video coding (SVC) with adaptive modulation and coding (AMC) provides an excellent solution for wireless video streaming. By assigning different modulation and coding schemes (MCSs) to video layers, SVC can provide good video quality to users in good channel conditions and also basic video quality to users in bad channel conditions. For optimal resource allocation, a key issue in applying SVC in the wireless multicast service is how to assign MCSs and the time resources to each SVC layer in the heterogeneous channel condition. We formulate this problem with integer linear programming (ILP) and provide numerical results to show the performance under 802.16 m environment. The result shows that our methodology enhances the overall system throughput compared to an existing algorithm.

  10. Integer-Linear-Programing Optimization in Scalable Video Multicast with Adaptive Modulation and Coding in Wireless Networks

    PubMed Central

    Lee, Chaewoo

    2014-01-01

    The advancement in wideband wireless network supports real time services such as IPTV and live video streaming. However, because of the sharing nature of the wireless medium, efficient resource allocation has been studied to achieve a high level of acceptability and proliferation of wireless multimedia. Scalable video coding (SVC) with adaptive modulation and coding (AMC) provides an excellent solution for wireless video streaming. By assigning different modulation and coding schemes (MCSs) to video layers, SVC can provide good video quality to users in good channel conditions and also basic video quality to users in bad channel conditions. For optimal resource allocation, a key issue in applying SVC in the wireless multicast service is how to assign MCSs and the time resources to each SVC layer in the heterogeneous channel condition. We formulate this problem with integer linear programming (ILP) and provide numerical results to show the performance under 802.16 m environment. The result shows that our methodology enhances the overall system throughput compared to an existing algorithm. PMID:25276862

  11. Ultimately accurate SRAF replacement for practical phases using an adaptive search algorithm based on the optimal gradient method

    NASA Astrophysics Data System (ADS)

    Maeda, Shimon; Nosato, Hirokazu; Matsunawa, Tetsuaki; Miyairi, Masahiro; Nojima, Shigeki; Tanaka, Satoshi; Sakanashi, Hidenori; Murakawa, Masahiro; Saito, Tamaki; Higuchi, Tetsuya; Inoue, Soichi

    2010-04-01

    SRAF (Sub Resolution Assist Feature) technique has been widely used for DOF enhancement. Below 40nm design node, even in the case of using the SRAF technique, the resolution limit is approached due to the use of hyper NA imaging or low k1 lithography conditions especially for the contact layer. As a result, complex layout patterns or random patterns like logic data or intermediate pitch patterns become increasingly sensitive to photo-resist pattern fidelity. This means that the need for more accurate resolution technique is increasing in order to cope with lithographic patterning fidelity issues in low k1 lithography conditions. To face with these issues, new SRAF technique like model based SRAF using an interference map or inverse lithography technique has been proposed. But these approaches don't have enough assurance for accuracy or performance, because the ideal mask generated by these techniques is lost when switching to a manufacturable mask with Manhattan structures. As a result it might be very hard to put these things into practice and production flow. In this paper, we propose the novel method for extremely accurate SRAF placement using an adaptive search algorithm. In this method, the initial position of SRAF is generated by the traditional SRAF placement such as rule based SRAF, and it is adjusted by adaptive algorithm using the evaluation of lithography simulation. This method has three advantages which are preciseness, efficiency and industrial applicability. That is, firstly, the lithography simulation uses actual computational model considering process window, thus our proposed method can precisely adjust the SRAF positions, and consequently we can acquire the best SRAF positions. Secondly, because our adaptive algorithm is based on optimal gradient method, which is very simple algorithm and rectilinear search, the SRAF positions can be adjusted with high efficiency. Thirdly, our proposed method, which utilizes the traditional SRAF placement, is

  12. Introduction beyond a species range: a relationship between population origin, adaptive potential and plant performance

    PubMed Central

    Volis, S; Ormanbekova, D; Yermekbayev, K; Song, M; Shulgina, I

    2014-01-01

    The adaptive potential of a population defines its importance for species survival in changing environmental conditions such as global climate change. Very few empirical studies have examined adaptive potential across species' ranges, namely, of edge vs core populations, and we are unaware of a study that has tested adaptive potential (namely, variation in adaptive traits) and measured performance of such populations in conditions not currently experienced by the species but expected in the future. Here we report the results of a Triticum dicoccoides population study that employed transplant experiments and analysis of quantitative trait variation. Two populations at the opposite edges of the species range (1) were locally adapted; (2) had lower adaptive potential (inferred from the extent of genetic quantitative trait variation) than the two core populations; and (3) were outperformed by the plants from the core population in the novel environment. The fact that plants from the species arid edge performed worse than plants from the more mesic core in extreme drought conditions beyond the present climatic envelope of the species implies that usage of peripheral populations for conservation purposes must be based on intensive sampling of among-population variation. PMID:24690758

  13. Energy-Based Adaptive Focusing: Optimal Ultrasonic Focusing Using Magnetic Resonance Guidance

    NASA Astrophysics Data System (ADS)

    Larrat, B.; Pernot, M.; Montaldo, G.; Fink, M.; Tanter, M.

    2010-03-01

    Adaptive focusing of ultrasonic waves is performed under the guidance of a Magnetic Resonance (MR) system. The technique is based on the maximization of the ultrasonic wave intensity at a target point. The wave intensity is indirectly estimated from the local tissue motion induced at the chosen focus by the acoustic radiation force of the ultrasonic beam. A motion sensitive MR sequence is used to measure the resulting local tissue displacements. Based on the transmission of a set of spatially coded ultrasonic waves, a non iterative inversion process is used to estimate the phase aberrations induced by the propagation medium and to maximize the acoustical intensity at the target. Both programmable and physical aberrating layers introducing strong distortions (up to 2π radians) are recovered within acceptable errors (<0.8 rad). This non invasive technique is shown to accurately correct the phase aberrations in a phantom gel with negligible heat deposition and limited acquisition time. These refocusing performances demonstrate a major potential in the field of MR-Guided Ultrasound Therapy in particular for transcranial brain HIFU.

  14. How to optimize vitamin D supplementation to prevent cancer, based on cellular adaptation and hydroxylase enzymology.

    PubMed

    Vieth, Reinhold

    2009-09-01

    The question of what makes an 'optimal' vitamin D intake is usually equivalent to, 'what serum 25-hydroxyvitamin D [25(OH)D] do we need to stay above to minimize risk of disease?'. This is a simplistic question that ignores the evidence that fluctuating concentrations of 25(OH)D may in themselves be a problem, even if concentrations do exceed a minimum desirable level. Vitamin D metabolism poses unique problems for the regulation of 1,25-dihydroxyvitamin D [1,25(OH)2D] concentrations in the tissues outside the kidney that possess 25(OH)D-1-hydroxylase [CYP27B1] and the catabolic enzyme, 1,25(OH)2D-24-hydroxylase [CYP24]. These enzymes behave according to first-order reaction kinetics. When 25(OH)D declines, the ratio of 1-hydroxylase/24-hydroxylase must increase to maintain tissue 1,25(OH)2D at its set-point level. The mechanisms that regulate this paracrine metabolism are poorly understood. I propose that delay in cellular adaptation, or lag time, in response to fluctuating 25(OH)D concentrations can explain why higher 25(OH)D in regions at high latitude or with low environmental ultraviolet light can be associated with the greater risks reported for prostate and pancreatic cancers. At temperate latitudes, higher summertime 25(OH)D levels are followed by sharper declines in 25(OH)D, causing inappropriately low 1-hydroxylase and high 24-hydroxylase, resulting in tissue 1,25(OH)2D below its ideal set-point. This hypothesis can answer concerns raised by the World Health Organization's International Agency for Research on Cancer about vitamin D and cancer risk. It also explains why higher 25(OH)D concentrations are not good if they fluctuate, and that desirable 25(OH)D concentrations are ones that are both high and stable. PMID:19667164

  15. Adaptation of a Fast Optimal Interpolation Algorithm to the Mapping of Oceangraphic Data

    NASA Technical Reports Server (NTRS)

    Menemenlis, Dimitris; Fieguth, Paul; Wunsch, Carl; Willsky, Alan

    1997-01-01

    A fast, recently developed, multiscale optimal interpolation algorithm has been adapted to the mapping of hydrographic and other oceanographic data. This algorithm produces solution and error estimates which are consistent with those obtained from exact least squares methods, but at a small fraction of the computational cost. Problems whose solution would be completely impractical using exact least squares, that is, problems with tens or hundreds of thousands of measurements and estimation grid points, can easily be solved on a small workstation using the multiscale algorithm. In contrast to methods previously proposed for solving large least squares problems, our approach provides estimation error statistics while permitting long-range correlations, using all measurements, and permitting arbitrary measurement locations. The multiscale algorithm itself, published elsewhere, is not the focus of this paper. However, the algorithm requires statistical models having a very particular multiscale structure; it is the development of a class of multiscale statistical models, appropriate for oceanographic mapping problems, with which we concern ourselves in this paper. The approach is illustrated by mapping temperature in the northeastern Pacific. The number of hydrographic stations is kept deliberately small to show that multiscale and exact least squares results are comparable. A portion of the data were not used in the analysis; these data serve to test the multiscale estimates. A major advantage of the present approach is the ability to repeat the estimation procedure a large number of times for sensitivity studies, parameter estimation, and model testing. We have made available by anonymous Ftp a set of MATLAB-callable routines which implement the multiscale algorithm and the statistical models developed in this paper.

  16. Robust breathing signal extraction from cone beam CT projections based on adaptive and global optimization techniques.

    PubMed

    Chao, Ming; Wei, Jie; Li, Tianfang; Yuan, Yading; Rosenzweig, Kenneth E; Lo, Yeh-Chi

    2016-04-21

    We present a study of extracting respiratory signals from cone beam computed tomography (CBCT) projections within the framework of the Amsterdam Shroud (AS) technique. Acquired prior to the radiotherapy treatment, CBCT projections were preprocessed for contrast enhancement by converting the original intensity images to attenuation images with which the AS image was created. An adaptive robust z-normalization filtering was applied to further augment the weak oscillating structures locally. From the enhanced AS image, the respiratory signal was extracted using a two-step optimization approach to effectively reveal the large-scale regularity of the breathing signals. CBCT projection images from five patients acquired with the Varian Onboard Imager on the Clinac iX System Linear Accelerator (Varian Medical Systems, Palo Alto, CA) were employed to assess the proposed technique. Stable breathing signals can be reliably extracted using the proposed algorithm. Reference waveforms obtained using an air bellows belt (Philips Medical Systems, Cleveland, OH) were exported and compared to those with the AS based signals. The average errors for the enrolled patients between the estimated breath per minute (bpm) and the reference waveform bpm can be as low as -0.07 with the standard deviation 1.58. The new algorithm outperformed the original AS technique for all patients by 8.5% to 30%. The impact of gantry rotation on the breathing signal was assessed with data acquired with a Quasar phantom (Modus Medical Devices Inc., London, Canada) and found to be minimal on the signal frequency. The new technique developed in this work will provide a practical solution to rendering markerless breathing signal using the CBCT projections for thoracic and abdominal patients.

  17. Robust breathing signal extraction from cone beam CT projections based on adaptive and global optimization techniques

    NASA Astrophysics Data System (ADS)

    Chao, Ming; Wei, Jie; Li, Tianfang; Yuan, Yading; Rosenzweig, Kenneth E.; Lo, Yeh-Chi

    2016-04-01

    We present a study of extracting respiratory signals from cone beam computed tomography (CBCT) projections within the framework of the Amsterdam Shroud (AS) technique. Acquired prior to the radiotherapy treatment, CBCT projections were preprocessed for contrast enhancement by converting the original intensity images to attenuation images with which the AS image was created. An adaptive robust z-normalization filtering was applied to further augment the weak oscillating structures locally. From the enhanced AS image, the respiratory signal was extracted using a two-step optimization approach to effectively reveal the large-scale regularity of the breathing signals. CBCT projection images from five patients acquired with the Varian Onboard Imager on the Clinac iX System Linear Accelerator (Varian Medical Systems, Palo Alto, CA) were employed to assess the proposed technique. Stable breathing signals can be reliably extracted using the proposed algorithm. Reference waveforms obtained using an air bellows belt (Philips Medical Systems, Cleveland, OH) were exported and compared to those with the AS based signals. The average errors for the enrolled patients between the estimated breath per minute (bpm) and the reference waveform bpm can be as low as  -0.07 with the standard deviation 1.58. The new algorithm outperformed the original AS technique for all patients by 8.5% to 30%. The impact of gantry rotation on the breathing signal was assessed with data acquired with a Quasar phantom (Modus Medical Devices Inc., London, Canada) and found to be minimal on the signal frequency. The new technique developed in this work will provide a practical solution to rendering markerless breathing signal using the CBCT projections for thoracic and abdominal patients.

  18. Microstructural modeling and design optimization of adaptive thin-film nanocomposite coatings for durability and wear

    NASA Astrophysics Data System (ADS)

    Pearson, James Deon

    Adaptive thin-film nanocomposite coatings comprised of crystalline ductile phases of gold and molybdenum disulfide, and brittle phases of diamond like carbon (DLC) and ytrria stabilized zirconia (YSZ) have been investigated by specialized microstructurally-based finite-element techniques. A new microstructural computational technique for efficiently creating models of nanocomposite coatings with control over composition, grain size, spacing and morphologies has been developed to account for length scales that range from nanometers to millimeters for efficient computations. The continuum mechanics model at the nanometer scale was verified with molecular dynamic models for nanocrystalline diamond. Using this new method, the interrelated effects of microstructural characteristics such as grain shapes and sizes, matrix thicknesses, local material behavior due to interfacial stresses and strains, varying amorphous and crystalline compositions, and transfer film adhesion and thickness on coating behavior have been investigated. A mechanistic model to account for experimentally observed transfer film adhesion modes and changes in thickness was also developed. One of the major objectives of this work is to determine optimal crystalline and amorphous compositions and behavior related to wear and durability over a wide range of thermo-mechanical conditions. The computational predictions, consistent with experimental observations, indicate specific interfacial regions between DLC and ductile metal inclusions are critical regions of stress and strain accumulation that can be precursors to material failure and wear. The predicted results underscore a competition between the effects of superior tribological properties associated with MoS 2 and maintaining manageable stress levels that would not exceed the coating strength. Varying the composition results in tradeoffs between lubrication, toughness, and strength, and the effects of critical stresses and strains can be controlled

  19. Robust breathing signal extraction from cone beam CT projections based on adaptive and global optimization techniques.

    PubMed

    Chao, Ming; Wei, Jie; Li, Tianfang; Yuan, Yading; Rosenzweig, Kenneth E; Lo, Yeh-Chi

    2016-04-21

    We present a study of extracting respiratory signals from cone beam computed tomography (CBCT) projections within the framework of the Amsterdam Shroud (AS) technique. Acquired prior to the radiotherapy treatment, CBCT projections were preprocessed for contrast enhancement by converting the original intensity images to attenuation images with which the AS image was created. An adaptive robust z-normalization filtering was applied to further augment the weak oscillating structures locally. From the enhanced AS image, the respiratory signal was extracted using a two-step optimization approach to effectively reveal the large-scale regularity of the breathing signals. CBCT projection images from five patients acquired with the Varian Onboard Imager on the Clinac iX System Linear Accelerator (Varian Medical Systems, Palo Alto, CA) were employed to assess the proposed technique. Stable breathing signals can be reliably extracted using the proposed algorithm. Reference waveforms obtained using an air bellows belt (Philips Medical Systems, Cleveland, OH) were exported and compared to those with the AS based signals. The average errors for the enrolled patients between the estimated breath per minute (bpm) and the reference waveform bpm can be as low as -0.07 with the standard deviation 1.58. The new algorithm outperformed the original AS technique for all patients by 8.5% to 30%. The impact of gantry rotation on the breathing signal was assessed with data acquired with a Quasar phantom (Modus Medical Devices Inc., London, Canada) and found to be minimal on the signal frequency. The new technique developed in this work will provide a practical solution to rendering markerless breathing signal using the CBCT projections for thoracic and abdominal patients. PMID:27008349

  20. A Geospatial Model for Remedial Design Optimization and Performance Evaluation

    SciTech Connect

    Madrid, V M; Demir, Z; Gregory, S; Valett, J; Halden, R U

    2002-02-19

    invaluable in optimizing and evaluating the remedial design and performance.

  1. Fuzzy Sets in Dynamic Adaptation of Parameters of a Bee Colony Optimization for Controlling the Trajectory of an Autonomous Mobile Robot.

    PubMed

    Amador-Angulo, Leticia; Mendoza, Olivia; Castro, Juan R; Rodríguez-Díaz, Antonio; Melin, Patricia; Castillo, Oscar

    2016-09-09

    A hybrid approach composed by different types of fuzzy systems, such as the Type-1 Fuzzy Logic System (T1FLS), Interval Type-2 Fuzzy Logic System (IT2FLS) and Generalized Type-2 Fuzzy Logic System (GT2FLS) for the dynamic adaptation of the alpha and beta parameters of a Bee Colony Optimization (BCO) algorithm is presented. The objective of the work is to focus on the BCO technique to find the optimal distribution of the membership functions in the design of fuzzy controllers. We use BCO specifically for tuning membership functions of the fuzzy controller for trajectory stability in an autonomous mobile robot. We add two types of perturbations in the model for the Generalized Type-2 Fuzzy Logic System to better analyze its behavior under uncertainty and this shows better results when compared to the original BCO. We implemented various performance indices; ITAE, IAE, ISE, ITSE, RMSE and MSE to measure the performance of the controller. The experimental results show better performances using GT2FLS then by IT2FLS and T1FLS in the dynamic adaptation the parameters for the BCO algorithm.

  2. Fuzzy Sets in Dynamic Adaptation of Parameters of a Bee Colony Optimization for Controlling the Trajectory of an Autonomous Mobile Robot.

    PubMed

    Amador-Angulo, Leticia; Mendoza, Olivia; Castro, Juan R; Rodríguez-Díaz, Antonio; Melin, Patricia; Castillo, Oscar

    2016-01-01

    A hybrid approach composed by different types of fuzzy systems, such as the Type-1 Fuzzy Logic System (T1FLS), Interval Type-2 Fuzzy Logic System (IT2FLS) and Generalized Type-2 Fuzzy Logic System (GT2FLS) for the dynamic adaptation of the alpha and beta parameters of a Bee Colony Optimization (BCO) algorithm is presented. The objective of the work is to focus on the BCO technique to find the optimal distribution of the membership functions in the design of fuzzy controllers. We use BCO specifically for tuning membership functions of the fuzzy controller for trajectory stability in an autonomous mobile robot. We add two types of perturbations in the model for the Generalized Type-2 Fuzzy Logic System to better analyze its behavior under uncertainty and this shows better results when compared to the original BCO. We implemented various performance indices; ITAE, IAE, ISE, ITSE, RMSE and MSE to measure the performance of the controller. The experimental results show better performances using GT2FLS then by IT2FLS and T1FLS in the dynamic adaptation the parameters for the BCO algorithm. PMID:27618062

  3. Fuzzy Sets in Dynamic Adaptation of Parameters of a Bee Colony Optimization for Controlling the Trajectory of an Autonomous Mobile Robot

    PubMed Central

    Amador-Angulo, Leticia; Mendoza, Olivia; Castro, Juan R.; Rodríguez-Díaz, Antonio; Melin, Patricia; Castillo, Oscar

    2016-01-01

    A hybrid approach composed by different types of fuzzy systems, such as the Type-1 Fuzzy Logic System (T1FLS), Interval Type-2 Fuzzy Logic System (IT2FLS) and Generalized Type-2 Fuzzy Logic System (GT2FLS) for the dynamic adaptation of the alpha and beta parameters of a Bee Colony Optimization (BCO) algorithm is presented. The objective of the work is to focus on the BCO technique to find the optimal distribution of the membership functions in the design of fuzzy controllers. We use BCO specifically for tuning membership functions of the fuzzy controller for trajectory stability in an autonomous mobile robot. We add two types of perturbations in the model for the Generalized Type-2 Fuzzy Logic System to better analyze its behavior under uncertainty and this shows better results when compared to the original BCO. We implemented various performance indices; ITAE, IAE, ISE, ITSE, RMSE and MSE to measure the performance of the controller. The experimental results show better performances using GT2FLS then by IT2FLS and T1FLS in the dynamic adaptation the parameters for the BCO algorithm. PMID:27618062

  4. A zonal computational procedure adapted to the optimization of two-dimensional thrust augmentor inlets

    NASA Technical Reports Server (NTRS)

    Lund, T. S.; Tavella, D. A.; Roberts, L.

    1985-01-01

    A viscous-inviscid interaction methodology based on a zonal description of the flowfield is developed as a mean of predicting the performance of two-dimensional thrust augmenting ejectors. An inviscid zone comprising the irrotational flow about the device is patched together with a viscous zone containing the turbulent mixing flow. The inviscid region is computed by a higher order panel method, while an integral method is used for the description of the viscous part. A non-linear, constrained optimization study is undertaken for the design of the inlet region. In this study, the viscous-inviscid analysis is complemented with a boundary layer calculation to account for flow separation from the walls of the inlet region. The thrust-based Reynolds number as well as the free stream velocity are shown to be important parameters in the design of a thrust augmentor inlet.

  5. Performance Bounds on Micro-Doppler Estimation and Adaptive Waveform Design Using OFDM Signals

    SciTech Connect

    Sen, Satyabrata; Barhen, Jacob; Glover, Charles Wayne

    2014-01-01

    We analyze the performance of a wideband orthogonal frequency division multiplexing (OFDM) signal in estimating the micro-Doppler frequency of a target having multiple rotating scatterers (e.g., rotor blades of a helicopter, propellers of a submarine). The presence of rotating scatterers introduces Doppler frequency modulation in the received signal by generating sidebands about the transmitted frequencies. This is called the micro-Doppler effects. The use of a frequency-diverse OFDM signal in this context enables us to independently analyze the micro-Doppler characteristics with respect to a set of orthogonal subcarrier frequencies. Therefore, to characterize the accuracy of micro-Doppler frequency estimation, we compute the Cram er-Rao Bound (CRB) on the angular-velocity estimate of the target while considering the scatterer responses as deterministic but unknown nuisance parameters. Additionally, to improve the accuracy of the estimation procedure, we formulate and solve an optimization problem by minimizing the CRB on the angular-velocity estimate with respect to the transmitting OFDM spectral coefficients. We present several numerical examples to demonstrate the CRB variations at different values of the signal-to-noise ratio (SNR) and the number of OFDM subcarriers. The CRB values not only decrease with the increase in the SNR values, but also reduce as we increase the number of subcarriers implying the significance of frequency-diverse OFDM waveforms. The improvement in estimation accuracy due to the adaptive waveform design is also numerically analyzed. Interestingly, we find that the relative decrease in the CRBs on the angular-velocity estimate is more pronounced for larger number of OFDM subcarriers.

  6. SWAT system performance predictions. Project report. [SWAT (Short-Wavelength Adaptive Techniques)

    SciTech Connect

    Parenti, R.R.; Sasiela, R.J.

    1993-03-10

    In the next phase of Lincoln Laboratory's SWAT (Short-Wavelength Adaptive Techniques) program, the performance of a 241-actuator adaptive-optics system will be measured using a variety of synthetic-beacon geometries. As an aid in this experimental investigation, a detailed set of theoretical predictions has also been assembled. The computational tools that have been applied in this study include a numerical approach in which Monte-Carlo ray-trace simulations of accumulated phase error are developed, and an analytical analysis of the expected system behavior. This report describes the basis of these two computational techniques and compares their estimates of overall system performance. Although their regions of applicability tend to be complementary rather than redundant, good agreement is usually obtained when both sets of results can be derived for the same engagement scenario.... Adaptive optics, Phase conjugation, Atmospheric turbulence Synthetic beacon, Laser guide star.

  7. Performance Enhancing Diets and the PRISE Protocol to Optimize Athletic Performance

    PubMed Central

    Arciero, Paul J.; Ward, Emery

    2015-01-01

    The training regimens of modern-day athletes have evolved from the sole emphasis on a single fitness component (e.g., endurance athlete or resistance/strength athlete) to an integrative, multimode approach encompassing all four of the major fitness components: resistance (R), interval sprints (I), stretching (S), and endurance (E) training. Athletes rarely, if ever, focus their training on only one mode of exercise but instead routinely engage in a multimode training program. In addition, timed-daily protein (P) intake has become a hallmark for all athletes. Recent studies, including from our laboratory, have validated the effectiveness of this multimode paradigm (RISE) and protein-feeding regimen, which we have collectively termed PRISE. Unfortunately, sports nutrition recommendations and guidelines have lagged behind the PRISE integrative nutrition and training model and therefore limit an athletes' ability to succeed. Thus, it is the purpose of this review to provide a clearly defined roadmap linking specific performance enhancing diets (PEDs) with each PRISE component to facilitate optimal nourishment and ultimately optimal athletic performance. PMID:25949823

  8. Optimizing Partial Credit Algorithms to Predict Student Performance

    ERIC Educational Resources Information Center

    Ostrow, Korinn; Donnelly, Chistopher; Heffernan, Neil

    2015-01-01

    As adaptive tutoring systems grow increasingly popular for the completion of classwork and homework, it is crucial to assess the manner in which students are scored within these platforms. The majority of systems, including ASSISTments, return the binary correctness of a student's first attempt at solving each problem. Yet for many teachers,…

  9. EEG/ERP adaptive noise canceller design with controlled search space (CSS) approach in cuckoo and other optimization algorithms.

    PubMed

    Ahirwal, M K; Kumar, Anil; Singh, G K

    2013-01-01

    This paper explores the migration of adaptive filtering with swarm intelligence/evolutionary techniques employed in the field of electroencephalogram/event-related potential noise cancellation or extraction. A new approach is proposed in the form of controlled search space to stabilize the randomness of swarm intelligence techniques especially for the EEG signal. Swarm-based algorithms such as Particles Swarm Optimization, Artificial Bee Colony, and Cuckoo Optimization Algorithm with their variants are implemented to design optimized adaptive noise canceler. The proposed controlled search space technique is tested on each of the swarm intelligence techniques and is found to be more accurate and powerful. Adaptive noise canceler with traditional algorithms such as least-mean-square, normalized least-mean-square, and recursive least-mean-square algorithms are also implemented to compare the results. ERP signals such as simulated visual evoked potential, real visual evoked potential, and real sensorimotor evoked potential are used, due to their physiological importance in various EEG studies. Average computational time and shape measures of evolutionary techniques are observed 8.21E-01 sec and 1.73E-01, respectively. Though, traditional algorithms take negligible time consumption, but are unable to offer good shape preservation of ERP, noticed as average computational time and shape measure difference, 1.41E-02 sec and 2.60E+00, respectively.

  10. Restricted and Adaptive Masculine Gender Performance in White Gay College Men

    ERIC Educational Resources Information Center

    Anderson-Martinez, Richard; Vianden, Jörg

    2014-01-01

    This article presents the results of a qualitative exploration of the performance of masculine gender identities in six gay male students enrolled at a master's comprehensive public institution in the Midwest. This article builds on the work of Laker and Davis (2011) and Rankin (2005). The findings indicate participants adapted their gender…

  11. Advancing adaptive optics technology: Laboratory turbulence simulation and optimization of laser guide stars

    NASA Astrophysics Data System (ADS)

    Rampy, Rachel A.

    Since Galileo's first telescope some 400 years ago, astronomers have been building ever-larger instruments. Yet only within the last two decades has it become possible to realize the potential angular resolutions of large ground-based telescopes, by using adaptive optics (AO) technology to counter the blurring effects of Earth's atmosphere. And only within the past decade have the development of laser guide stars (LGS) extended AO capabilities to observe science targets nearly anywhere in the sky. Improving turbulence simulation strategies and LGS are the two main topics of my research. In the first part of this thesis, I report on the development of a technique for manufacturing phase plates for simulating atmospheric turbulence in the laboratory. The process involves strategic application of clear acrylic paint onto a transparent substrate. Results of interferometric characterization of the plates are described and compared to Kolmogorov statistics. The range of r0 (Fried's parameter) achieved thus far is 0.2--1.2 mm at 650 nm measurement wavelength, with a Kolmogorov power law. These plates proved valuable at the Laboratory for Adaptive Optics at University of California, Santa Cruz, where they have been used in the Multi-Conjugate Adaptive Optics testbed, during integration and testing of the Gemini Planet Imager, and as part of the calibration system of the on-sky AO testbed named ViLLaGEs (Visible Light Laser Guidestar Experiments). I present a comparison of measurements taken by ViLLaGEs of the power spectrum of a plate and the real sky turbulence. The plate is demonstrated to follow Kolmogorov theory well, while the sky power spectrum does so in a third of the data. This method of fabricating phase plates has been established as an effective and low-cost means of creating simulated turbulence. Due to the demand for such devices, they are now being distributed to other members of the AO community. The second topic of this thesis pertains to understanding and

  12. Advancing adaptive optics technology: Laboratory turbulence simulation and optimization of laser guide stars

    NASA Astrophysics Data System (ADS)

    Rampy, Rachel A.

    Since Galileo's first telescope some 400 years ago, astronomers have been building ever-larger instruments. Yet only within the last two decades has it become possible to realize the potential angular resolutions of large ground-based telescopes, by using adaptive optics (AO) technology to counter the blurring effects of Earth's atmosphere. And only within the past decade have the development of laser guide stars (LGS) extended AO capabilities to observe science targets nearly anywhere in the sky. Improving turbulence simulation strategies and LGS are the two main topics of my research. In the first part of this thesis, I report on the development of a technique for manufacturing phase plates for simulating atmospheric turbulence in the laboratory. The process involves strategic application of clear acrylic paint onto a transparent substrate. Results of interferometric characterization of the plates are described and compared to Kolmogorov statistics. The range of r0 (Fried's parameter) achieved thus far is 0.2--1.2 mm at 650 nm measurement wavelength, with a Kolmogorov power law. These plates proved valuable at the Laboratory for Adaptive Optics at University of California, Santa Cruz, where they have been used in the Multi-Conjugate Adaptive Optics testbed, during integration and testing of the Gemini Planet Imager, and as part of the calibration system of the on-sky AO testbed named ViLLaGEs (Visible Light Laser Guidestar Experiments). I present a comparison of measurements taken by ViLLaGEs of the power spectrum of a plate and the real sky turbulence. The plate is demonstrated to follow Kolmogorov theory well, while the sky power spectrum does so in a third of the data. This method of fabricating phase plates has been established as an effective and low-cost means of creating simulated turbulence. Due to the demand for such devices, they are now being distributed to other members of the AO community. The second topic of this thesis pertains to understanding and

  13. Adaptive Effects on Locomotion Performance Following Exposure to a Rotating Virtual Environment

    NASA Technical Reports Server (NTRS)

    Mulavara, A. P.; Richards, J. T.; Marshburn, A. M.; Bucello, R.; Bloomberg, J. J.

    2003-01-01

    adaptive generalization. The purpose of this study was to determine if adaptive modification in locomotor performance could be achieved by viewing simulated self-motion in a passive-immersive virtual ' environment over a prolonged period during treadmill locomotion.

  14. Performance of the Adaptive Collision Source (ACS) Method for Discrete Ordinates in Parallel Environments

    NASA Astrophysics Data System (ADS)

    Walters, William J.; Haghighat, Alireza

    2014-06-01

    A new collision source method has been developed to solve the Linear Boltzmann Equation (LBE) more efficiently by adaptation of the angular quadrature order. The angular adaptation method is unique in that the flux from each scattering source iteration is obtained separately, with potentially a different quadrature order. This allows for an optimal use of processing power, by using a high order quadrature for the first few iterations that need it, before shifting to lower order quadratures for the remaining iterations. This is essentially an extension of the first collision source method, and we call it the adaptive collision source method (ACS). The ACS methodolog y has been implemented in the TITAN discrete ordinates code, and has shown a speedup of 2-3 on a test problem, with very little loss of accuracy (within a provided adaptive tolerance). Further, the code has been extended to work in parallel environments by angular decomposition. Although the method requires increased parallel communication, tests have shown excellent scalability, with parallel fractions of up to 99%.

  15. Intelligent Modeling Combining Adaptive Neuro Fuzzy Inference System and Genetic Algorithm for Optimizing Welding Process Parameters

    NASA Astrophysics Data System (ADS)

    Gowtham, K. N.; Vasudevan, M.; Maduraimuthu, V.; Jayakumar, T.

    2011-04-01

    Modified 9Cr-1Mo ferritic steel is used as a structural material for steam generator components of power plants. Generally, tungsten inert gas (TIG) welding is preferred for welding of these steels in which the depth of penetration achievable during autogenous welding is limited. Therefore, activated flux TIG (A-TIG) welding, a novel welding technique, has been developed in-house to increase the depth of penetration. In modified 9Cr-1Mo steel joints produced by the A-TIG welding process, weld bead width, depth of penetration, and heat-affected zone (HAZ) width play an important role in determining the mechanical properties as well as the performance of the weld joints during service. To obtain the desired weld bead geometry and HAZ width, it becomes important to set the welding process parameters. In this work, adaptative neuro fuzzy inference system is used to develop independent models correlating the welding process parameters like current, voltage, and torch speed with weld bead shape parameters like depth of penetration, bead width, and HAZ width. Then a genetic algorithm is employed to determine the optimum A-TIG welding process parameters to obtain the desired weld bead shape parameters and HAZ width.

  16. Optimized performance for neutron interrogation to detect SNM

    SciTech Connect

    Slaughter, D R; Asztalos, S J; Biltoft, P J; Church, J A; Descalle, M; Hall, J M; Luu, T C; Manatt, D R; Mauger, G J; Norman, E B; Petersen, D C; Pruet, J A; Prussin, S G

    2007-02-14

    A program of simulations and validating experiments was utilized to evaluate a concept for neutron interrogation of commercial cargo containers that would reliably detect special nuclear material (SNM). The goals were to develop an interrogation system capable of detecting a 5 kg solid sphere of high-enriched uranium (HEU) even when deeply embedded in commercial cargo. Performance goals included a minimum detection probability, P{sub d} {ge} 95%, a maximum occurrence of false positive indications, P{sub fA} {le} 0.001, and maximum scan duration of t {le} 1 min. The conditions necessary to meet these goals were demonstrated in experimental measurements even when the SNM is deeply buried in any commercial cargo, and are projected to be met successfully in the most challenging cases of steel or hydrocarbons at areal density {rho}L {le} 150 g/cm{sup 2}. Optimal performance was obtained with a collimated ({Delta}{Theta} = {+-} 15{sup o}) neutron beam at energy E{sub n} = 7 MeV produced by the D(d,n) reaction with the deuteron energy E{sub d} = 4 MeV. Two fission product signatures are utilized to uniquely identify SNM, including delayed neutrons detected in a large array of polyethylene moderated 3He proportional counters and high energy {beta}-delayed fission product {gamma}-radiation detected in a large array of 61 x 61 x 25 cm{sup 3} plastic scintillators. The latter detectors are nearly blind to normal terrestrial background radiation by setting an energy threshold on the detection at E{sub min} {ge} 3 MeV. Detection goals were attained with a low beam current (I{sub d} = 15-65 {micro}A) source up to {rho}L = 75 g/cm{sup 2} utilizing long irradiations, T = 30 sec, and long counting times, t = 30-100 sec. Projecting to a higher beam current, I{sub d} {ge} 600 {micro}A and larger detector array the detection and false alarm goals would be attained even with intervening cargo overburden as large as {rho}L {le} 150 g/cm{sup 2}. The latter cargo thickness corresponds to

  17. Design and adaptation of ocean observing systems at coastal scales, the role of data assimilation in the optimization of measures.

    NASA Astrophysics Data System (ADS)

    Brandini, Carlo; Taddei, Stefano; Fattorini, Maria; Doronzo, Bartolomeo; Lapucci, Chiara; Ortolani, Alberto; Poulain, Pierre Marie

    2015-04-01

    The design and the implementation of observation systems, in the current view, are not limited to the capability to observe some phenomena of particular interest in a given sea area, but must ensure maximum benefits to the analysis/prediction systems that are based on numerical models. The design of these experimental systems takes great advantage from the use of synthetic data, whose characteristics are as close as possible to the observed data (e.g. in-situ), in terms of spatial and temporal variability, particularly when the power spectrum of the observed signal is close to that reproduced by a numerical model. This method, usually referred to as OSSE (Observing System Simulation Experiment), is a preferred way to test numerical data for assimilation into models as if they were real data, with the advantage of defining different datasets for data assimilation at almost no cost. This applies both to the design of fixed networks (such as buoys or coastal radars), and to the improvement of the performance of mobile platforms, such as autonomous marine vehicles, floats or mobile radars, through the optimization of parameters for vehicle guidance, coverage, trajectories or localization of sampling points, according to the adaptive observation concept. In this work we present the results of some experimental activities recently undertaken in the coastal area between the Ligurian and Northern Tyrrhenian seas, that have shown a great vulnerability in recent years, due to a number of marine accidents and environmental issues. In this cross-border area an observation and forecasting system is being installed as part of the SICOMAR project (PO maritime Italy-France), in order to provide real time data at high spatial and time resolution, and to design interoperable, expandable and flexible observing platforms, that can be quickly adapted to the needs of local problems (e.g. accidents at sea). The starting SICOMAR network includes HF coastal radars, FerryBoxes onboard ships

  18. A new multiobjective performance criterion used in PID tuning optimization algorithms

    PubMed Central

    Sahib, Mouayad A.; Ahmed, Bestoun S.

    2015-01-01

    In PID controller design, an optimization algorithm is commonly employed to search for the optimal controller parameters. The optimization algorithm is based on a specific performance criterion which is defined by an objective or cost function. To this end, different objective functions have been proposed in the literature to optimize the response of the controlled system. These functions include numerous weighted time and frequency domain variables. However, for an optimum desired response it is difficult to select the appropriate objective function or identify the best weight values required to optimize the PID controller design. This paper presents a new time domain performance criterion based on the multiobjective Pareto front solutions. The proposed objective function is tested in the PID controller design for an automatic voltage regulator system (AVR) application using particle swarm optimization algorithm. Simulation results show that the proposed performance criterion can highly improve the PID tuning optimization in comparison with traditional objective functions. PMID:26843978

  19. Crop planting date optimization: An approach for climate change adaptation in West Africa

    NASA Astrophysics Data System (ADS)

    Waongo, Moussa; Laux, Patrick; Kunstmann, Harald

    2014-05-01

    Agriculture is the main source of income for population and the main driver of economy in Africa, particularly in West Africa. West African agriculture is dominated by rainfed agriculture. This agricultural system is characterized by smallholder and subsistence farming, and a limited use of crop production inputs such as machines, fertilizers and pesticides. Therefore, crop yield is strongly influenced by climate fluctuation and is more vulnerable to climate change and climate variability. To reduce climate risk on crop production, a development of tailored agricultural management strategies is required. The usage of agricultural management strategies such as tailored crop planting date might contribute both to reduce crop failure and to increased crop production. In addition, unlike aforementioned crop production inputs, the usage of tailored planting dates is costless for farmers. Thus, efforts to improve crop production by optimizing crop planting date can contribute to alleviate food insecurity in West Africa, in the context of climate change. In this study, the process-based crop model GLAM (General Large Area Model for annual crop) in combination with a fuzzy logic approach for planting date have been coupled with a genetic algorithm to derive Optimized Planting Dates (OPDs) for maize cropping in Burkina Faso, West Africa. For a specific location, the derived OPDs correspond to a time window for crop planting. To analyze the performance of the OPDs approach, the derived OPDs has been compared to two well-known planting date methods in West Africa. The results showed a mean OPD ranging from May 1st (South-West) to July 11th (North) across the country. In comparison with well-known methods, the OPD approach yielded earliest planting dates across Burkina Faso. The deviation of OPDs from planting dates derived from the well known methods ranged from 10 days to 20 days for the northern and central region, and less than 10 days for the southern region. With respect

  20. Energy management of a fuel cell/ultracapacitor hybrid power system using an adaptive optimal-control method

    NASA Astrophysics Data System (ADS)

    Lin, Wei-Song; Zheng, Chen-Hong

    2011-03-01

    Energy management of a fuel cell/ultracapacitor hybrid power system aims to optimize energy efficiency while satisfying the operational constraints. The current challenges include ensuring that the non-linear dynamics and energy management of a hybrid power system are consistent with state and input constraints imposed by operational limitations. This paper formulates the requirements for energy management of the hybrid power system as a constrained optimal-control problem, and then transforms the problem into an unconstrained form using the penalty-function method. Radial-basis-function networks are organized in an adaptive optimal-control algorithm to synthesize an optimal strategy for energy management. The obtained optimal strategy was verified in an electric vehicle powered by combining a fuel-cell system and an ultracapacitor bank. Driving-cycle tests were conducted to investigate the fuel consumption, fuel-cell peak power, and instantaneous rate of change in fuel-cell power. The results show that the energy efficiency of the electric vehicle is significantly improved relative to that without using the optimal strategy.

  1. Optimization and performance calculation of dual-rotation propellers

    NASA Technical Reports Server (NTRS)

    Davidson, R. E.

    1981-01-01

    An analysis is given which enables the design of dual-rotation propellers. It relies on the use of a new tip loss factor deduced from T. Theodorsen's measurements coupled with the general methodology of C. N. H. Lock. In addition, it includes the effect of drag in optimizing. Some values for the tip loss factor are calculated for one advance ratio.

  2. Performance of a MEMS-base Adaptive Optics Optical Coherency Tomography System

    SciTech Connect

    Evans, J; Zadwadzki, R J; Jones, S; Olivier, S; Opkpodu, S; Werner, J S

    2008-01-16

    We have demonstrated that a microelectrical mechanical systems (MEMS) deformable mirror can be flattened to < 1 nm RMS within controllable spatial frequencies over a 9.2-mm aperture making it a viable option for high-contrast adaptive optics systems (also known as Extreme Adaptive Optics). The Extreme Adaptive Optics Testbed at UC Santa Cruz is being used to investigate and develop technologies for high-contrast imaging, especially wavefront control. A phase shifting diffraction interferometer (PSDI) measures wavefront errors with sub-nm precision and accuracy for metrology and wavefront control. Consistent flattening, required testing and characterization of the individual actuator response, including the effects of dead and low-response actuators. Stability and repeatability of the MEMS devices was also tested. An error budget for MEMS closed loop performance will summarize MEMS characterization.

  3. Microbial community succession mechanism coupling with adaptive evolution of adsorption performance in chalcopyrite bioleaching.

    PubMed

    Feng, Shoushuai; Yang, Hailin; Wang, Wu

    2015-09-01

    The community succession mechanism of Acidithiobacillus sp. coupling with adaptive evolution of adsorption performance were systematically investigated. Specifically, the μmax of attached and free cells was increased and peak time was moved ahead, indicating both cell growth of Acidithiobacillus ferrooxidans and Acidithiobacillus thiooxidans was promoted. In the mixed strains system, the domination courses of A. thiooxidans was dramatically shortened from 22th day to 15th day, although community structure finally approached to the normal system. Compared to A. ferrooxidans, more positive effects of adaptive evolution on cell growth of A. thiooxidans were shown in either single or mixed strains system. Moreover, higher concentrations of sulfate and ferric ions indicated that both sulfur and iron metabolism was enhanced, especially of A. thiooxidans. Consistently, copper ion production was improved from 65.5 to 88.5 mg/L. This new adaptive evolution and community succession mechanism may be useful for guiding similar bioleaching processes.

  4. Asynchronous multilevel adaptive methods for solving partial differential equations on multiprocessors - Performance results

    NASA Technical Reports Server (NTRS)

    Mccormick, S.; Quinlan, D.

    1989-01-01

    The fast adaptive composite grid method (FAC) is an algorithm that uses various levels of uniform grids (global and local) to provide adaptive resolution and fast solution of PDEs. Like all such methods, it offers parallelism by using possibly many disconnected patches per level, but is hindered by the need to handle these levels sequentially. The finest levels must therefore wait for processing to be essentially completed on all the coarser ones. A recently developed asynchronous version of FAC, called AFAC, completely eliminates this bottleneck to parallelism. This paper describes timing results for AFAC, coupled with a simple load balancing scheme, applied to the solution of elliptic PDEs on an Intel iPSC hypercube. These tests include performance of certain processes necessary in adaptive methods, including moving grids and changing refinement. A companion paper reports on numerical and analytical results for estimating convergence factors of AFAC applied to very large scale examples.

  5. Extreme Adaptive Optics Testbed: Performance and Characterization of a 1024 Deformable Mirror

    SciTech Connect

    Evans, J W; Morzinski, K; Severson, S; Poyneer, L; Macintosh, B; Dillon, D; REza, L; Gavel, D; Palmer, D

    2005-10-30

    We have demonstrated that a microelectrical mechanical systems (MEMS) deformable mirror can be flattened to < 1 nm RMS within controllable spatial frequencies over a 9.2-mm aperture making it a viable option for high-contrast adaptive optics systems (also known as Extreme Adaptive Optics). The Extreme Adaptive Optics Testbed at UC Santa Cruz is being used to investigate and develop technologies for high-contrast imaging, especially wavefront control. A phase shifting diffraction interferometer (PSDI) measures wavefront errors with sub-nm precision and accuracy for metrology and wavefront control. Consistent flattening, required testing and characterization of the individual actuator response, including the effects of dead and low-response actuators. Stability and repeatability of the MEMS devices was also tested. An error budget for MEMS closed loop performance will summarize MEMS characterization.

  6. Improved performance of the laser guide star adaptive optics system at Lick Observatory

    SciTech Connect

    An, J R; Avicola, K; Bauman, B J; Brase, J M; Campbell, E W; Carrano, C; Cooke, J B; Freeze, G J; Friedman, H W; Max, C E; Gates, E L; Gavel, D T; Kanz, V K; Kuklo, T C; Macintosh, B A; Newman, M J; Olivier, S S; Pierce, E L; Waltjen, K E; Watson, A

    1999-07-20

    Results of experiments with the laser guide star adaptive optics system on the 3-meter Shane telescope at Lick Observatory have demonstrated a factor of 4 performance improvement over previous results. Stellar images recorded at a wavelength of 2 {micro}m were corrected to over 40% of the theoretical diffraction-limited peak intensity. For the previous two years, this sodium-layer laser guide star system has corrected stellar images at this wavelength to {approx}10% of the theoretical peak intensity limit. After a campaign to improve the beam quality of the laser system, and to improve calibration accuracy and stability of the adaptive optics system using new techniques for phase retrieval and phase-shifting diffraction interferometry, the system performance has been substantially increased. The next step will be to use the Lick system for astronomical science observations, and to demonstrate this level of performance with the new system being installed on the 10-meter Keck II telescope.

  7. An Agent-Based Optimization Framework for Engineered Complex Adaptive Systems with Application to Demand Response in Electricity Markets

    NASA Astrophysics Data System (ADS)

    Haghnevis, Moeed

    The main objective of this research is to develop an integrated method to study emergent behavior and consequences of evolution and adaptation in engineered complex adaptive systems (ECASs). A multi-layer conceptual framework and modeling approach including behavioral and structural aspects is provided to describe the structure of a class of engineered complex systems and predict their future adaptive patterns. The approach allows the examination of complexity in the structure and the behavior of components as a result of their connections and in relation to their environment. This research describes and uses the major differences of natural complex adaptive systems (CASs) with artificial/engineered CASs to build a framework and platform for ECAS. While this framework focuses on the critical factors of an engineered system, it also enables one to synthetically employ engineering and mathematical models to analyze and measure complexity in such systems. In this way concepts of complex systems science are adapted to management science and system of systems engineering. In particular an integrated consumer-based optimization and agent-based modeling (ABM) platform is presented that enables managers to predict and partially control patterns of behaviors in ECASs. Demonstrated on the U.S. electricity markets, ABM is integrated with normative and subjective decision behavior recommended by the U.S. Department of Energy (DOE) and Federal Energy Regulatory Commission (FERC). The approach integrates social networks, social science, complexity theory, and diffusion theory. Furthermore, it has unique and significant contribution in exploring and representing concrete managerial insights for ECASs and offering new optimized actions and modeling paradigms in agent-based simulation.

  8. Optimism and adaptation to chronic disease: The role of optimism in relation to self-care options of type 1 diabetes mellitus, rheumatoid arthritis and multiple sclerosis.

    PubMed

    Fournier, Marijda; De Ridder, Denise; Bensing, Jozien

    2002-11-01

    OBJECTIVES: To determine the role of optimistic beliefs in adaptation processes of three chronic diseases different in controllability by self-care. It was expected that optimism towards the future would relate to adaptation independently of the controllability of disease. Optimism regarding one's coping ability should be beneficial in controllable diseases. Unrealistic optimism was expected to be beneficial in uncontrollable disease. DESIGN: The cross-sectional design involved 104 patients with type 1 diabetes, 95 patients with rheumatoid arthritis and 98 patients with multiple sclerosis, recruited via their physician at the out-patient department of five hospitals. METHOD: Confirmatory Factor Analysis (LISREL) was employed to confirm a three-dimensional approach of optimism: outcome expectancies, efficacy expectancies and unrealistic thinking. Multi-sample analysis by path modelling was used to examine whether the relationship of the three optimistic beliefs with coping (CISS-21), depression and anxiety (HADS), and physical functioning (SF-36) differs with the controllability based on the self-care options of chronic disease. RESULTS: These show that when chronic disease must be controlled by self-care, physical health depends more strongly on positive efficacy expectancies. In contrast, when self-care options for controlling chronic disease are limited, physical health depends more strongly on positive unrealistic thinking and relates negatively to positive efficacy expectancies. The impact of the three optimistic beliefs on mental health is independent of the controllability by self-care. CONCLUSION: Optimistic beliefs are differently beneficial for physical health dependent on the controllability of chronic disease. Unrealistic beliefs are helpful when patients are confronted with moderately to largely uncontrollable disease where self-care options are limited, in contrast to positive efficacy expectancies that are helpful when patients deal with largely

  9. The Relationship between Optimism and Engagement: The Impact on Student Performance

    ERIC Educational Resources Information Center

    Medlin, Bobby; Faulk, Larry

    2011-01-01

    The concepts of optimism and employee engagement as mechanisms to improving individual performance have been discussed in the management literature. Though studies concerning optimism in the workplace are relatively limited, evidence certainly exists that links the concept to improvement in individual academic and workplace performance.…

  10. Optimizing Human Performance: An Introduction to the HPT Method.

    ERIC Educational Resources Information Center

    Schneider, Edward W.

    2003-01-01

    Discussion of performance analysis and improvement focuses on a performance system that is regulated by feedback from both internal and external sources. Discusses human performance technology (HPT), which focuses on the goals of the organizational structure; and explains the macrosystem, including metrics and standards; the microsystem; and…

  11. [Optimizing performance documentation in gynecology--assistance from the internet].

    PubMed

    Woernle, F; Seufert, R; Brockerhoff, P; Lellé, R J

    1999-01-01

    The documentation of operations in the field of gynecology and obstetrics is regulated by social laws in Germany. Only by optimal encoding of diagnoses and procedures an efficient cashing with the health insurance's can be achieved. This requires profound knowledge of the invoice modalities and usually support by computer systems. The Internet offers in this respect some assistance, which in the following is pointed out and evaluated critically. PMID:10573827

  12. Optimizing Hammermill Performance Through Screen Selection and Hammer Design

    SciTech Connect

    Neal A. Yancey; Tyler L. Westover; Christopher T. Wright

    2013-01-01

    Background: Mechanical preprocessing, which includes particle size reduction and mechanical separation, is one of the primary operations in the feedstock supply system for a lignocellulosic biorefinery. It is the means by which raw biomass from the field or forest is mechanically transformed into an on-spec feedstock with characteristics better suited for the fuel conversion process. Results: This work provides a general overview of the objectives and methodologies of mechanical preprocessing and then presents experimental results illustrating (1) improved size reduction via optimization of hammer mill configuration, (2) improved size reduction via pneumatic-assisted hammer milling, and (3) improved control of particle size and particle size distribution through proper selection of grinder process parameters. Conclusion: Optimal grinder configuration for maximal process throughput and efficiency is strongly dependent on feedstock type and properties, such moisture content. Tests conducted using a HG200 hammer grinder indicate that increasing the tip speed, optimizing hammer geometry, and adding pneumatic assist can increase grinder throughput as much as 400%.

  13. Optimization of laser butt welding parameters with multiple performance characteristics

    NASA Astrophysics Data System (ADS)

    Sathiya, P.; Abdul Jaleel, M. Y.; Katherasan, D.; Shanmugarajan, B.

    2011-04-01

    This paper presents a study carried out on 3.5 kW cooled slab laser welding of 904 L super austenitic stainless steel. The joints have butts welded with different shielding gases, namely argon, helium and nitrogen, at a constant flow rate. Super austenitic stainless steel (SASS) normally contains high amount of Mo, Cr, Ni, N and Mn. The mechanical properties are controlled to obtain good welded joints. The quality of the joint is evaluated by studying the features of weld bead geometry, such as bead width (BW) and depth of penetration (DOP). In this paper, the tensile strength and bead profiles (BW and DOP) of laser welded butt joints made of AISI 904 L SASS are investigated. The Taguchi approach is used as a statistical design of experiment (DOE) technique for optimizing the selected welding parameters. Grey relational analysis and the desirability approach are applied to optimize the input parameters by considering multiple output variables simultaneously. Confirmation experiments have also been conducted for both of the analyses to validate the optimized parameters.

  14. Adaptation to heat and exercise performance under cooler conditions: a new hot topic.

    PubMed

    Corbett, Jo; Neal, Rebecca A; Lunt, Heather C; Tipton, Michael J

    2014-10-01

    Chronic exposure to a stressor elicits adaptations enhancing the tolerance to that stressor. These adaptive responses might also improve tolerance under less stressful conditions. For example, historically there has been much interest in the adaptive responses to high-altitude, or hypoxia, and their ergogenic potential under sea-level, or normoxic, conditions. In contrast, the influence of the adaptive responses to heat on exercise under cooler conditions has received relatively little interest. Heat acclimation/acclimatization (HA) is known to increase work capacity in hot environments. Yet, aerobic exercise performance can progressively deteriorate as ambient temperature increases beyond ~10 °C, indicating a thermal limitation even under relatively cool conditions. The improved thermoregulatory capability induced by HA might attenuate this thermal decrement in a manner similar to that seen when exposed to hotter temperatures. Moreover, the suite of adaptations elicited by HA has the potential to increase maximal oxygen uptake, lactate threshold and economy, and thus may be ergogenic even under conditions where performance is not thermally limited. Indeed, evidence is now emerging to support an ergogenic effect of HA but the number of studies is limited and in some instances lack appropriate control, are confounded by methodological limitations, or do not address the mechanisms of action. Nevertheless, these tantalising insights into the ergogenic potential of heat will likely generate considerable interest in this new 'hot topic'. Future research will need to employ well-designed studies to clarify the exercise conditions under which ergogenic effects of HA are apparent, to elucidate the precise mechanisms, and to optimise HA strategies for performance.

  15. Spatial Cognitive Performance During Adaptation to Conflicting Tilt-Translation Stimuli as a Sensorimotor Spaceflight Analog

    NASA Technical Reports Server (NTRS)

    Kayanickupuram, A. J.; Ramos, K. A.; Cordova, M. L.; Wood, S. J.

    2009-01-01

    The need to resolve new patterns of sensory feedback in altered gravitoinertial environments requires cognitive processes to develop appropriate reference frames for spatial orientation awareness. The purpose of this study was to examine deficits in spatial cognitive performance during adaptation to conflicting tilt-translation stimuli. Fourteen subjects were tilted within a lighted enclosure that simultaneously translated at one of 3 frequencies. Tilt and translation motion was synchronized to maintain the resultant gravitoinertial force aligned with the longitudinal body axis, resulting in a mismatch analogous to spaceflight in which the canals and vision signal tilt while the otoliths do not. Changes in performance on different spatial cognitive tasks were compared 1) without motion, 2) with tilt motion alone (pitch at 0.15, 0.3 and 0.6 Hz or roll at 0.3 Hz), and 3) with conflicting tilt-translation motion. The adaptation paradigm was continued for up to 30 min or until the onset of nausea. The order of the adaptation conditions were counter-balanced across 4 different test sessions. There was a significant effect of stimulus frequency on both motion sickness and spatial cognitive performance. Only 3 of 14 were able to complete the full 30 min protocol at 0.15 Hz, while 7 of 14 completed 0.3 Hz and 13 of 14 completed 0.6 Hz. There were no changes in simple visual-spatial cognitive tests, e.g., mental rotation or match-to-sample. There were significant deficits during 0.15 Hz adaptation in both accuracy and reaction time during a spatial reference task in which subjects are asked to identify a match of a 3D reoriented cube assemblage. Our results are consistent with antidotal reports of cognitive impairment that are common during sensorimotor adaptation with G-transitions. We conclude that these cognitive deficits stem from the ambiguity of spatial reference frames for central processing of inertial motion cues.

  16. Binocular self-calibration performed via adaptive genetic algorithm based on laser line imaging

    NASA Astrophysics Data System (ADS)

    Apolinar Muñoz Rodríguez, J.; Mejía Alanís, Francisco Carlos

    2016-07-01

    An accurate technique to perform binocular self-calibration by means of an adaptive genetic algorithm based on a laser line is presented. In this calibration, the genetic algorithm computes the vision parameters through simulated binary crossover (SBX). To carry it out, the genetic algorithm constructs an objective function from the binocular geometry of the laser line projection. Then, the SBX minimizes the objective function via chromosomes recombination. In this algorithm, the adaptive procedure determines the search space via line position to obtain the minimum convergence. Thus, the chromosomes of vision parameters provide the minimization. The approach of the proposed adaptive genetic algorithm is to calibrate and recalibrate the binocular setup without references and physical measurements. This procedure leads to improve the traditional genetic algorithms, which calibrate the vision parameters by means of references and an unknown search space. It is because the proposed adaptive algorithm avoids errors produced by the missing of references. Additionally, the three-dimensional vision is carried out based on the laser line position and vision parameters. The contribution of the proposed algorithm is corroborated by an evaluation of accuracy of binocular calibration, which is performed via traditional genetic algorithms.

  17. Bi-photon generation with optimized wavefront by means of adaptive optics

    SciTech Connect

    Minozzi, Mattia; Vallone, Giuseppe; Villoresi, Paolo; Bonora, Stefano; Sergienko, Alexander V.

    2014-12-04

    The generation of entangled photon pairs using an optimal pump wavefront was realized in order to achieve a desirable free-space propagation. This optimization exploits a closed loop whis is based on a deformable mirror, a nonlinear crystal for spontaneous parametric down-conversion, the free-space propagation line and the single-photon coincidence electronics.

  18. Global Optimization, Local Adaptation, and the Role of Growth in Distribution Networks

    NASA Astrophysics Data System (ADS)

    Ronellenfitsch, Henrik; Katifori, Eleni

    2016-09-01

    Highly optimized complex transport networks serve crucial functions in many man-made and natural systems such as power grids and plant or animal vasculature. Often, the relevant optimization functional is nonconvex and characterized by many local extrema. In general, finding the global, or nearly global optimum is difficult. In biological systems, it is believed that such an optimal state is slowly achieved through natural selection. However, general coarse grained models for flow networks with local positive feedback rules for the vessel conductivity typically get trapped in low efficiency, local minima. In this work we show how the growth of the underlying tissue, coupled to the dynamical equations for network development, can drive the system to a dramatically improved optimal state. This general model provides a surprisingly simple explanation for the appearance of highly optimized transport networks in biology such as leaf and animal vasculature.

  19. Adaptation for Planting and Irrigation Decisions to Changing Monsoon Regime in Northeast India: Risk-based Hydro-economic Optimization

    NASA Astrophysics Data System (ADS)

    Zhu, T.; Cai, X.

    2013-12-01

    Delay in onset of Indian summer monsoon becomes increasingly frequent. Delayed monsoon and occasional monsoon failures seriously affect agricultural production in the northeast as well as other parts of India. In the Vaishali district of the Bihar State, Monsoon rainfall is very skewed and erratic, often concentrating in shorter durations. Farmers in Vaishali reported that delayed Monsoon affected paddy planting and, consequently delayed cropping cycle, putting crops under the risks of 'terminal heat.' Canal system in the district does not function due to lack of maintenance; irrigation relies almost entirely on groundwater. Many small farmers choose not to irrigate when monsoon onset is delayed due to high diesel price, leading to reduced production or even crop failure. Some farmers adapt to delayed onset of Monsoon by planting short-duration rice, which gives the flexibility for planting the next season crops. Other sporadic autonomous adaptation activities were observed as well, with various levels of success. Adaptation recommendations and effective policy interventions are much needed. To explore robust options to adapt to the changing Monsoon regime, we build a stochastic programming model to optimize revenues of farmer groups categorized by landholding size, subject to stochastic Monsoon onset and rainfall amount. Imperfect probabilistic long-range forecast is used to inform the model onset and rainfall amount probabilities; the 'skill' of the forecasting is measured using probabilities of correctly predicting events in the past derived through hindcasting. Crop production functions are determined using self-calibrating Positive Mathematical Programming approach. The stochastic programming model aims to emulate decision-making behaviors of representative farmer agents through making choices in adaptation, including crop mix, planting dates, irrigation, and use of weather information. A set of technological and policy intervention scenarios are tested

  20. Competitiveness and the Process of Co-adaptation in Team Sport Performance

    PubMed Central

    Passos, Pedro; Araújo, Duarte; Davids, Keith

    2016-01-01

    An evolutionary psycho-biological perspective on competitiveness dynamics is presented, focusing on continuous behavioral co-adaptations to constraints that arise in performance environments. We suggest that an athlete’s behavioral dynamics are constrained by circumstances of competing for the availability of resources, which once obtained offer possibilities for performance success. This defines the influence of the athlete-environment relationship on competitiveness. Constraining factors in performance include proximity to target areas in team sports and the number of other competitors in a location. By pushing the athlete beyond existing limits, competitiveness enhances opportunities for co-adaptation, innovation and creativity, which can lead individuals toward different performance solutions to achieve the same performance goal. Underpinned by an ecological dynamics framework we examine whether competitiveness is a crucial feature to succeed in team sports. Our focus is on intra-team competitiveness, concerning the capacity of individuals within a team to become perceptually attuned to affordances in a given performance context which can increase their likelihood of success. This conceptualization implies a re-consideration of the concept of competitiveness, not as an inherited trait or entity to be acquired, but rather theorizing it as a functional performer-environment relationship that needs to be explored, developed, enhanced and maintained in team games training programs. PMID:27777565

  1. High performance computing for deformable image registration: towards a new paradigm in adaptive radiotherapy.

    PubMed

    Samant, Sanjiv S; Xia, Junyi; Muyan-Ozcelik, Pinar; Owens, John D

    2008-08-01

    The advent of readily available temporal imaging or time series volumetric (4D) imaging has become an indispensable component of treatment planning and adaptive radiotherapy (ART) at many radiotherapy centers. Deformable image registration (DIR) is also used in other areas of medical imaging, including motion corrected image reconstruction. Due to long computation time, clinical applications of DIR in radiation therapy and elsewhere have been limited and consequently relegated to offline analysis. With the recent advances in hardware and software, graphics processing unit (GPU) based computing is an emerging technology for general purpose computation, including DIR, and is suitable for highly parallelized computing. However, traditional general purpose computation on the GPU is limited because the constraints of the available programming platforms. As well, compared to CPU programming, the GPU currently has reduced dedicated processor memory, which can limit the useful working data set for parallelized processing. We present an implementation of the demons algorithm using the NVIDIA 8800 GTX GPU and the new CUDA programming language. The GPU performance will be compared with single threading and multithreading CPU implementations on an Intel dual core 2.4 GHz CPU using the C programming language. CUDA provides a C-like language programming interface, and allows for direct access to the highly parallel compute units in the GPU. Comparisons for volumetric clinical lung images acquired using 4DCT were carried out. Computation time for 100 iterations in the range of 1.8-13.5 s was observed for the GPU with image size ranging from 2.0 x 10(6) to 14.2 x 10(6) pixels. The GPU registration was 55-61 times faster than the CPU for the single threading implementation, and 34-39 times faster for the multithreading implementation. For CPU based computing, the computational time generally has a linear dependence on image size for medical imaging data. Computational efficiency is

  2. Optimizing weather radar observations using an adaptive multiquadric surface fitting algorithm

    NASA Astrophysics Data System (ADS)

    Martens, Brecht; Cabus, Pieter; De Jongh, Inge; Verhoest, Niko

    2013-04-01

    .e. the observed scaling factors C(xα)) on a distance aαK by introducing an offset parameter K, which results in slightly different equations to calculate a and a0. The described technique is currently being used by the Flemish Environmental Agency in an online forecasting system of river discharges within Flanders (Belgium). However, rescaling the radar data using the described algorithm is not always giving rise to an improved weather radar product. Probably one of the main reasons is the parameters K and ? which are implemented as constants. It can be expected that, among others, depending on the characteristics of the rainfall, different values for the parameters should be used. Adaptation of the parameter values is achieved by an online calibration of K and ? at each time step (every 15 minutes), using validated rain gauge measurements as ground truth. Results demonstrate that rescaling radar images using optimized values for K and ? at each time step lead to a significant improvement of the rainfall estimation, which in turn will result in higher quality discharge predictions. Moreover, it is shown that calibrated values for K and ? can be obtained in near-real time. References Cole, S. J., and Moore, R. J. (2008). Hydrological modelling using raingauge- and radar-based estimators of areal rainfall. Journal of Hydrology, 358(3-4), 159-181. Hardy, R.L., (1971) Multiquadric equations of topography and other irregular surfaces, Journal of Geophysical Research, 76(8): 1905-1915. Moore, R. J., Watson, B. C., Jones, D. A. and Black, K. B. (1989). London weather radar local calibration study. Technical report, Institute of Hydrology.

  3. On-sky validation of an optimal LQG control with vibration mitigation: from the CANARY Multi-Object Adaptive Optics demonstrator to the Gemini Multi-Conjugated Adaptive Optics facility.

    NASA Astrophysics Data System (ADS)

    Sivo, Gaetano; Kulcsár, Caroline; Conan, Jean-Marc; Raynaud, Henri-François; Gendron, Éric; Basden, Alastair; Gratadour, Damien; Morris, Tim; Petit, Cyril; Meimon, Serge; Rousset, Gérard; Garrel, Vincent; Neichel, Benoit; van Dam, Marcos; Marin, Eduardo; Carrasco, Rodrigo; Schirmer, Mischa; Rambold, William; Moreno, Cristian; Montes, Vanessa; Hardie, Kayla; Trujillo, Chad

    2015-01-01

    Adaptive optics provides real time correction of wavefront perturbations on ground-based telescopes and allow to reach the diffraction limit performances. Optimizing control and performance is a key issue for ever more demanding instruments on ever larger telescopes affected not only by atmospheric turbulence, but also by vibrations, windshake and tracking errors. Linear Quadratic Gaussian control achieves optimal correction when provided with a temporal model of the disturbance. We present in this paper the first on-sky results of a Kalman filter based LQG control with vibration mitigation on the CANARY instrument at the Nasmyth platform of the 4.2-m William Herschel Telescope (La Palma, Spain). The results demonstrate a clear improvement of performance for full LQG compared with standard integrator control, and assess the additional improvement brought by vibration filtering with a tip-tilt model identified from on-sky data (by 10 points of Strehl ratio), thus validating the strategy retained on the instrument SPHERE (eXtreme-AO system for extra-solar planets detection and characterization) at the VLT. The MOAO on-sky pathfinder CANARY features two AO configurations that have both been tested: single- conjugated AO and multi-object AO with NGS and NGS+ Rayleigh LGS, together with vibration mitigation on tip and tilt modes. We finally present the ongoing development done to commission such a control law on a regular Sodium laser Multi-Conjuagated Adaptive Optics (MCAO) system GeMS at the 8-m Gemini South Telescope. This implementation does not require new hardware and is already available in the real-time computer.

  4. Add-on simple adaptive control improves performance of classical control design

    NASA Astrophysics Data System (ADS)

    Weiss, Haim; Rusnak, Ilan

    2014-12-01

    The Simple Adaptive Control (SAC) controls an augmented plant that comprises the true plant with parallel feed-forward. The Almost Strictly Positive Real (ASPR) property of the augmented plant leads to asymptotic following. Prior publications have shown that, based only on the prior knowledge on stabilizability properties of systems (usually available), the parallel feed-forward configuration (PFC) allows adaptive control of realistic systems, even if they are both unstable and non-minimum phase. However, it was commonly thought that the PFC addition requires a price when compared with good linear time invariant (LTI) designs that do not use any addition to the plant. The paper shows that the use of SAC with PFC as Add-On to LTI system design improves the performance. Although SAC directly controls the augmented error, it always gives improved performance, i.e., smaller tracking error and reduced sensitivity to plant disturbance, with respect to the best LTI controller.

  5. Effects of extended lay-off periods on performance and operator trust under adaptable automation.

    PubMed

    Chavaillaz, Alain; Wastell, David; Sauer, Jürgen

    2016-03-01

    Little is known about the long-term effects of system reliability when operators do not use a system during an extended lay-off period. To examine threats to skill maintenance, 28 participants operated twice a simulation of a complex process control system for 2.5 h, with an 8-month retention interval between sessions. Operators were provided with an adaptable support system, which operated at one of the following reliability levels: 60%, 80% or 100%. Results showed that performance, workload, and trust remained stable at the second testing session, but operators lost self-confidence in their system management abilities. Finally, the effects of system reliability observed at the first testing session were largely found again at the second session. The findings overall suggest that adaptable automation may be a promising means to support operators in maintaining their performance at the second testing session.

  6. Performance study of LMS based adaptive algorithms for unknown system identification

    SciTech Connect

    Javed, Shazia; Ahmad, Noor Atinah

    2014-07-10

    Adaptive filtering techniques have gained much popularity in the modeling of unknown system identification problem. These techniques can be classified as either iterative or direct. Iterative techniques include stochastic descent method and its improved versions in affine space. In this paper we present a comparative study of the least mean square (LMS) algorithm and some improved versions of LMS, more precisely the normalized LMS (NLMS), LMS-Newton, transform domain LMS (TDLMS) and affine projection algorithm (APA). The performance evaluation of these algorithms is carried out using adaptive system identification (ASI) model with random input signals, in which the unknown (measured) signal is assumed to be contaminated by output noise. Simulation results are recorded to compare the performance in terms of convergence speed, robustness, misalignment, and their sensitivity to the spectral properties of input signals. Main objective of this comparative study is to observe the effects of fast convergence rate of improved versions of LMS algorithms on their robustness and misalignment.

  7. Performance study of LMS based adaptive algorithms for unknown system identification

    NASA Astrophysics Data System (ADS)

    Javed, Shazia; Ahmad, Noor Atinah

    2014-07-01

    Adaptive filtering techniques have gained much popularity in the modeling of unknown system identification problem. These techniques can be classified as either iterative or direct. Iterative techniques include stochastic descent method and its improved versions in affine space. In this paper we present a comparative study of the least mean square (LMS) algorithm and some improved versions of LMS, more precisely the normalized LMS (NLMS), LMS-Newton, transform domain LMS (TDLMS) and affine projection algorithm (APA). The performance evaluation of these algorithms is carried out using adaptive system identification (ASI) model with random input signals, in which the unknown (measured) signal is assumed to be contaminated by output noise. Simulation results are recorded to compare the performance in terms of convergence speed, robustness, misalignment, and their sensitivity to the spectral properties of input signals. Main objective of this comparative study is to observe the effects of fast convergence rate of improved versions of LMS algorithms on their robustness and misalignment.

  8. Effects of extended lay-off periods on performance and operator trust under adaptable automation.

    PubMed

    Chavaillaz, Alain; Wastell, David; Sauer, Jürgen

    2016-03-01

    Little is known about the long-term effects of system reliability when operators do not use a system during an extended lay-off period. To examine threats to skill maintenance, 28 participants operated twice a simulation of a complex process control system for 2.5 h, with an 8-month retention interval between sessions. Operators were provided with an adaptable support system, which operated at one of the following reliability levels: 60%, 80% or 100%. Results showed that performance, workload, and trust remained stable at the second testing session, but operators lost self-confidence in their system management abilities. Finally, the effects of system reliability observed at the first testing session were largely found again at the second session. The findings overall suggest that adaptable automation may be a promising means to support operators in maintaining their performance at the second testing session. PMID:26603139

  9. Performance optimization of continuous countercurrent tangential chromatography for antibody capture.

    PubMed

    Dutta, Amit K; Tan, Jasmine; Napadensky, Boris; Zydney, Andrew L; Shinkazh, Oleg

    2016-03-01

    Recent studies have demonstrated that continuous countercurrent tangential chromatography (CCTC) can effectively purify monoclonal antibodies from clarified cell culture fluid. CCTC has the potential to overcome many of the limitations of conventional packed bed protein A chromatography. This paper explores the optimization of CCTC in terms of product yield, impurity removal, overall productivity, and buffer usage. Modeling was based on data from bench-scale process development and CCTC experiments for protein A capture of two clarified Chinese Hamster Ovary cell culture feedstocks containing monoclonal antibodies provided by industrial partners. The impact of resin binding capacity and kinetics, as well as staging strategy and buffer recycling, was assessed. It was found that optimal staging in the binding step provides better yield and increases overall system productivity by 8-16%. Utilization of higher number of stages in the wash and elution steps can lead to significant decreases in buffer usage (∼40% reduction) as well as increased removal of impurities (∼2 log greater removal). Further reductions in buffer usage can be obtained by recycling of buffer in the wash and regeneration steps (∼35%). Preliminary results with smaller particle size resins show that the productivity of the CCTC system can be increased by 2.5-fold up to 190 g of mAb/L of resin/hr due to the reduction in mass transfer limitations in the binding step. These results provide a solid framework for designing and optimizing CCTC technology for capture applications. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:430-439, 2016. PMID:26914276

  10. AP-Cloud: Adaptive Particle-in-Cloud method for optimal solutions to Vlasov-Poisson equation

    NASA Astrophysics Data System (ADS)

    Wang, Xingyu; Samulyak, Roman; Jiao, Xiangmin; Yu, Kwangmin

    2016-07-01

    We propose a new adaptive Particle-in-Cloud (AP-Cloud) method for obtaining optimal numerical solutions to the Vlasov-Poisson equation. Unlike the traditional particle-in-cell (PIC) method, which is commonly used for solving this problem, the AP-Cloud adaptively selects computational nodes or particles to deliver higher accuracy and efficiency when the particle distribution is highly non-uniform. Unlike other adaptive techniques for PIC, our method balances the errors in PDE discretization and Monte Carlo integration, and discretizes the differential operators using a generalized finite difference (GFD) method based on a weighted least square formulation. As a result, AP-Cloud is independent of the geometric shapes of computational domains and is free of artificial parameters. Efficient and robust implementation is achieved through an octree data structure with 2:1 balance. We analyze the accuracy and convergence order of AP-Cloud theoretically, and verify the method using an electrostatic problem of a particle beam with halo. Simulation results show that the AP-Cloud method is substantially more accurate and faster than the traditional PIC, and it is free of artificial forces that are typical for some adaptive PIC techniques.

  11. AP-Cloud: Adaptive particle-in-cloud method for optimal solutions to Vlasov–Poisson equation

    DOE PAGES

    Wang, Xingyu; Samulyak, Roman; Jiao, Xiangmin; Yu, Kwangmin

    2016-04-19

    We propose a new adaptive Particle-in-Cloud (AP-Cloud) method for obtaining optimal numerical solutions to the Vlasov–Poisson equation. Unlike the traditional particle-in-cell (PIC) method, which is commonly used for solving this problem, the AP-Cloud adaptively selects computational nodes or particles to deliver higher accuracy and efficiency when the particle distribution is highly non-uniform. Unlike other adaptive techniques for PIC, our method balances the errors in PDE discretization and Monte Carlo integration, and discretizes the differential operators using a generalized finite difference (GFD) method based on a weighted least square formulation. As a result, AP-Cloud is independent of the geometric shapes ofmore » computational domains and is free of artificial parameters. Efficient and robust implementation is achieved through an octree data structure with 2:1 balance. We analyze the accuracy and convergence order of AP-Cloud theoretically, and verify the method using an electrostatic problem of a particle beam with halo. Here, simulation results show that the AP-Cloud method is substantially more accurate and faster than the traditional PIC, and it is free of artificial forces that are typical for some adaptive PIC techniques.« less

  12. Object Correlation and Maneuver Detection Using Optimal Control Performance Metrics

    NASA Astrophysics Data System (ADS)

    Holzinger, M.; Scheeres, D.

    2010-09-01

    Object correlation and maneuver detection are persistent problems in space surveillance and space object catalog maintenance. This paper demonstrates the utility of using quadratic trajectory control cost, an analog to the trajectory L2-norm in control, as a distance metric with which to both correlate object tracks and detect maneuvers using Uncorrelated Tracks (UCTs), real-time sensor measurement residuals, and prior state uncertainty. State and measurement uncertainty are incorporated into the computation, and distributions of optimal control usage are computed. Both UCT correlation as well as maneuver detection are demonstrated in several scenarios Potential avenues for future research and contributions are summarized.

  13. Effects of Informed Item Selection on Test Performance and Anxiety for Examinees Administered a Self-Adapted Test.

    ERIC Educational Resources Information Center

    Plake, Barbara S.; And Others

    1995-01-01

    No significant differences in performance on a self-adapted test or anxiety were found for college students (n=218) taking a self-adapted test who selected item difficulty without any prior information, inspected an item before selecting, or answered a typical item and received performance feedback. (SLD)

  14. Optimization of piezo-electric PVDF polymers for adaptive optics in space environments.

    SciTech Connect

    Dargaville, Tim Richard; Martin, Jeffrey W.; Clough, Roger Lee; Celina, Mathias Christopher

    2003-07-01

    Piezoelectric polymers based on PVDF are of interest for use in large aperture space-based telescopes similar to the James Web Space Telescope. Dimensional adjustments of polymer films depend on their piezoelectric properties with wireless (electron beam) shape control methods having been successfully demonstrated in the past. Such electron beam controls require a detailed understanding of the piezoelectric material responses. Similarly, space applications demand consistent, predictable, and reliable performance. While PVDF as a generic polymer type is a suitable piezoelectric material, it is also well known that fluorinated polymers are highly radiation-sensitive. Mechanical and other physical properties will suffer under various types of radiation (strong vacuum UV, {gamma}-, X-ray, e-beam, ion-beam) and atomic oxygen exposure. Likewise, extreme temperature fluctuations in space environments will result in annealing effects and cyclic stresses. While the radiative degradation chemistry of polymers is an established field there is little information available on the performance of piezoelectric features in PVDF with respect to their expected changes in these environments. Therefore, understanding such fundamental issues becomes mandatory for the design and deployment of satellite systems utilizing these materials/technology. We have investigated the degradation of PVDF and copolymers under a range of stress environments, and have studied the implications with regard to piezoelectrical properties necessary for reliable operation of thin films in space environments. Initial aging studies using {gamma}- and e-beam irradiation to explore material sensitivities for comparison with expected UV doses have shown complex material changes with lowered Curie temperatures, crystallinity, melting points and significant crosslinking, but little affect on piezoelectric d{sub 33} constants. Similar complexities of the aging processes have been observed in accelerated temperature

  15. Optimizing Performance of Glycopeptide Capture for Plasma Proteomics

    PubMed Central

    Berven, Frode S.; Ahmad, Rushdy; Clauser, Karl R.; Carr, Steven A.

    2010-01-01

    Selective capture of glycopolypeptides followed by release and analysis of the former glycosylation-site peptides has been shown to have promise for reducing complexity of body fluids such as blood for biomarker discovery. In this work, a protocol based on capture of polypeptides containing a N-linked carbohydrate from human plasma using commercially available magnetic beads coupled with hydrazide chemistry was optimized and partially automated through the use of a KingFisher magnetic particle processor. Comparison of bead-based glycocapture at the protein-level vs. peptide-level revealed differences in the specificity, reproducibility and absolute number of former glycosylation-site peptides detected. Evaluation of a range of capture and elution conditions led to an optimized protocol with a 24% intraday and 30% interday CV, and a glycopeptide capture specificity of 99%. Depleting the plasma of 14 high abundance proteins improved detection sensitivity by approximately one order of magnitude compared to non-depleted plasma and resulted in an increase of 24% in the number of identified glycoproteins. The sensitivity of SPEG for detection of glycoproteins in depleted, non-fractionated plasma was found to be in the 10 to 100 pmol/ml range corresponding to glycoprotein levels ranging from 100’s of nanograms/ml to 10’s of micrograms/ml. Despite high capture specificity,the total number of glycoproteins detected and the sensitivity of SPEG in plasma is surprisingly limited. PMID:20235580

  16. Adaptation of lower limb movement patterns when maintaining performance in the presence of muscle fatigue.

    PubMed

    Mudie, Kurt L; Gupta, Amitabh; Green, Simon; Clothier, Peter J

    2016-08-01

    Adaptations in lower limb movement patterns were examined when performance was maintained during a fatiguing repetitive loading task. Forty recreationally active male and female participants performed single-leg hopping to volitional exhaustion at 2.2Hz to a submaximal height. Spatio-temporal characteristics, mechanical characteristics and variability of the knee-ankle and hip-knee joint couplings were determined at 20% increments during the duration of the hopping task. Variability of the knee-ankle and hip-knee couplings in the flexion/extension axis significantly increased during the loading and propulsion phases during the hopping task (p<0.05). Performance (vertical stiffness, hopping frequency and height) did not change significantly during the task (p>0.05), however foot contact time increased progressively during this task (p<0.05) and maximum hop height significantly decreased after the task (p<0.05). The observed increase in variability between adjoining lower limb segments demonstrated the ability of the neuromotor system to adapt and maintain performance even with the onset of fatigue. This finding highlights that during the performance of a rapid and repetitive loading activity, performance can be preserved when there is variability in the neuromotor system.

  17. Adaptation of lower limb movement patterns when maintaining performance in the presence of muscle fatigue.

    PubMed

    Mudie, Kurt L; Gupta, Amitabh; Green, Simon; Clothier, Peter J

    2016-08-01

    Adaptations in lower limb movement patterns were examined when performance was maintained during a fatiguing repetitive loading task. Forty recreationally active male and female participants performed single-leg hopping to volitional exhaustion at 2.2Hz to a submaximal height. Spatio-temporal characteristics, mechanical characteristics and variability of the knee-ankle and hip-knee joint couplings were determined at 20% increments during the duration of the hopping task. Variability of the knee-ankle and hip-knee couplings in the flexion/extension axis significantly increased during the loading and propulsion phases during the hopping task (p<0.05). Performance (vertical stiffness, hopping frequency and height) did not change significantly during the task (p>0.05), however foot contact time increased progressively during this task (p<0.05) and maximum hop height significantly decreased after the task (p<0.05). The observed increase in variability between adjoining lower limb segments demonstrated the ability of the neuromotor system to adapt and maintain performance even with the onset of fatigue. This finding highlights that during the performance of a rapid and repetitive loading activity, performance can be preserved when there is variability in the neuromotor system. PMID:27101562

  18. Selection of optimal sensors for predicting performance of polymer electrolyte membrane fuel cell

    NASA Astrophysics Data System (ADS)

    Mao, Lei; Jackson, Lisa

    2016-10-01

    In this paper, sensor selection algorithms are investigated based on a sensitivity analysis, and the capability of optimal sensors in predicting PEM fuel cell performance is also studied using test data. The fuel cell model is developed for generating the sensitivity matrix relating sensor measurements and fuel cell health parameters. From the sensitivity matrix, two sensor selection approaches, including the largest gap method, and exhaustive brute force searching technique, are applied to find the optimal sensors providing reliable predictions. Based on the results, a sensor selection approach considering both sensor sensitivity and noise resistance is proposed to find the optimal sensor set with minimum size. Furthermore, the performance of the optimal sensor set is studied to predict fuel cell performance using test data from a PEM fuel cell system. Results demonstrate that with optimal sensors, the performance of PEM fuel cell can be predicted with good quality.

  19. Adaptive Scheduling for QoS Virtual Machines under Different Resource Allocation - Performance Effects and Predictability

    NASA Astrophysics Data System (ADS)

    Sodan, Angela C.

    Virtual machines have become an important approach to provide