Foraging optimally for home ranges

Science.gov (United States)

Mitchell, Michael S.; Powell, Roger A.

2012-01-01

Economic models predict behavior of animals based on the presumption that natural selection has shaped behaviors important to an animal's fitness to maximize benefits over costs. Economic analyses have shown that territories of animals are structured by trade-offs between benefits gained from resources and costs of defending them. Intuitively, home ranges should be similarly structured, but trade-offs are difficult to assess because there are no costs of defense, thus economic models of home-range behavior are rare. We present economic models that predict how home ranges can be efficient with respect to spatially distributed resources, discounted for travel costs, under 2 strategies of optimization, resource maximization and area minimization. We show how constraints such as competitors can influence structure of homes ranges through resource depression, ultimately structuring density of animals within a population and their distribution on a landscape. We present simulations based on these models to show how they can be generally predictive of home-range behavior and the mechanisms that structure the spatial distribution of animals. We also show how contiguous home ranges estimated statistically from location data can be misleading for animals that optimize home ranges on landscapes with patchily distributed resources. We conclude with a summary of how we applied our models to nonterritorial black bears (Ursus americanus) living in the mountains of North Carolina, where we found their home ranges were best predicted by an area-minimization strategy constrained by intraspecific competition within a social hierarchy. Economic models can provide strong inference about home-range behavior and the resources that structure home ranges by offering falsifiable, a priori hypotheses that can be tested with field observations.

A novel comprehensive learning artificial bee colony optimizer for dynamic optimization biological problems

Directory of Open Access Journals (Sweden)

Weixing Su

2017-03-01

Full Text Available There are many dynamic optimization problems in the real world, whose convergence and searching ability is cautiously desired, obviously different from static optimization cases. This requires an optimization algorithm adaptively seek the changing optima over dynamic environments, instead of only finding the global optimal solution in the static environment. This paper proposes a novel comprehensive learning artificial bee colony optimizer (CLABC for optimization in dynamic environments problems, which employs a pool of optimal foraging strategies to balance the exploration and exploitation tradeoff. The main motive of CLABC is to enrich artificial bee foraging behaviors in the ABC model by combining Powell’s pattern search method, life-cycle, and crossover-based social learning strategy. The proposed CLABC is a more bee-colony-realistic model that the bee can reproduce and die dynamically throughout the foraging process and population size varies as the algorithm runs. The experiments for evaluating CLABC are conducted on the dynamic moving peak benchmarks. Furthermore, the proposed algorithm is applied to a real-world application of dynamic RFID network optimization. Statistical analysis of all these cases highlights the significant performance improvement due to the beneficial combination and demonstrates the performance superiority of the proposed algorithm.

Dynamic optimization and differential games

CERN Document Server

Friesz, Terry L

2010-01-01

Dynamic Optimization and Differential Games has been written to address the increasing number of Operations Research and Management Science problems that involve the explicit consideration of time and of gaming among multiple agents. With end-of-chapter exercises throughout, it is a book that can be used both as a reference and as a textbook. It will be useful as a guide to engineers, operations researchers, applied mathematicians and social scientists whose work involves both the theoretical and computational aspects of dynamic optimization and differential games. Included throughout the text are detailed explanations of several original dynamic and game-theoretic mathematical models which are of particular relevance in today's technologically-driven-global economy: revenue management, oligopoly pricing, production planning, supply chain management, dynamic traffic assignment and dynamic congestion pricing. The book emphasizes deterministic theory, computational tools and applications associated with the stu...

Design optimization applied in structural dynamics

NARCIS (Netherlands)

Akcay-Perdahcioglu, Didem; de Boer, Andries; van der Hoogt, Peter; Tiskarna, T

2007-01-01

This paper introduces the design optimization strategies, especially for structures which have dynamic constraints. Design optimization involves first the modeling and then the optimization of the problem. Utilizing the Finite Element (FE) model of a structure directly in an optimization process

Nonlinear dynamic range transformation in visual communication channels.

Science.gov (United States)

Alter-Gartenberg, R

1996-01-01

The article evaluates nonlinear dynamic range transformation in the context of the end-to-end continuous-input/discrete processing/continuous-display imaging process. Dynamic range transformation is required when we have the following: (i) the wide dynamic range encountered in nature is compressed into the relatively narrow dynamic range of the display, particularly for spatially varying irradiance (e.g., shadow); (ii) coarse quantization is expanded to the wider dynamic range of the display; and (iii) nonlinear tone scale transformation compensates for the correction in the camera amplifier.

Picosecond X-ray streak camera dynamic range measurement

Energy Technology Data Exchange (ETDEWEB)

Zuber, C., E-mail: celine.zuber@cea.fr; Bazzoli, S.; Brunel, P.; Gontier, D.; Raimbourg, J.; Rubbelynck, C.; Trosseille, C. [CEA, DAM, DIF, F-91297 Arpajon (France); Fronty, J.-P.; Goulmy, C. [Photonis SAS, Avenue Roger Roncier, BP 520, 19106 Brive Cedex (France)

2016-09-15

Streak cameras are widely used to record the spatio-temporal evolution of laser-induced plasma. A prototype of picosecond X-ray streak camera has been developed and tested by Commissariat à l’Énergie Atomique et aux Énergies Alternatives to answer the Laser MegaJoule specific needs. The dynamic range of this instrument is measured with picosecond X-ray pulses generated by the interaction of a laser beam and a copper target. The required value of 100 is reached only in the configurations combining the slowest sweeping speed and optimization of the streak tube electron throughput by an appropriate choice of high voltages applied to its electrodes.

Transmitted wavefront testing with large dynamic range based on computer-aided deflectometry

Science.gov (United States)

Wang, Daodang; Xu, Ping; Gong, Zhidong; Xie, Zhongmin; Liang, Rongguang; Xu, Xinke; Kong, Ming; Zhao, Jun

2018-06-01

The transmitted wavefront testing technique is demanded for the performance evaluation of transmission optics and transparent glass, in which the achievable dynamic range is a key issue. A computer-aided deflectometric testing method with fringe projection is proposed for the accurate testing of transmitted wavefronts with a large dynamic range. Ray tracing of the modeled testing system is carried out to achieve the virtual ‘null’ testing of transmitted wavefront aberrations. The ray aberration is obtained from the ray tracing result and measured slope, with which the test wavefront aberration can be reconstructed. To eliminate testing system modeling errors, a system geometry calibration based on computer-aided reverse optimization is applied to realize accurate testing. Both numerical simulation and experiments have been carried out to demonstrate the feasibility and high accuracy of the proposed testing method. The proposed testing method can achieve a large dynamic range compared with the interferometric method, providing a simple, low-cost and accurate way for the testing of transmitted wavefronts from various kinds of optics and a large amount of industrial transmission elements.

Optimization of Dynamic Aperture of PEP-X Baseline Design

Energy Technology Data Exchange (ETDEWEB)

Wang, Min-Huey; /SLAC; Cai, Yunhai; /SLAC; Nosochkov, Yuri; /SLAC

2010-08-23

SLAC is developing a long-range plan to transfer the evolving scientific programs at SSRL from the SPEAR3 light source to a much higher performing photon source. Storage ring design is one of the possibilities that would be housed in the 2.2-km PEP-II tunnel. The design goal of PEPX storage ring is to approach an optimal light source design with horizontal emittance less than 100 pm and vertical emittance of 8 pm to reach the diffraction limit of 1-{angstrom} x-ray. The low emittance design requires a lattice with strong focusing leading to high natural chromaticity and therefore to strong sextupoles. The latter caused reduction of dynamic aperture. The dynamic aperture requirement for horizontal injection at injection point is about 10 mm. In order to achieve the desired dynamic aperture the transverse non-linearity of PEP-X is studied. The program LEGO is used to simulate the particle motion. The technique of frequency map is used to analyze the nonlinear behavior. The effect of the non-linearity is tried to minimize at the given constrains of limited space. The details and results of dynamic aperture optimization are discussed in this paper.

Optimization of Dynamic Aperture of PEP-X Baseline Design

International Nuclear Information System (INIS)

Wang, Min-Huey

2010-01-01

SLAC is developing a long-range plan to transfer the evolving scientific programs at SSRL from the SPEAR3 light source to a much higher performing photon source. Storage ring design is one of the possibilities that would be housed in the 2.2-km PEP-II tunnel. The design goal of PEPX storage ring is to approach an optimal light source design with horizontal emittance less than 100 pm and vertical emittance of 8 pm to reach the diffraction limit of 1-(angstrom) x-ray. The low emittance design requires a lattice with strong focusing leading to high natural chromaticity and therefore to strong sextupoles. The latter caused reduction of dynamic aperture. The dynamic aperture requirement for horizontal injection at injection point is about 10 mm. In order to achieve the desired dynamic aperture the transverse non-linearity of PEP-X is studied. The program LEGO is used to simulate the particle motion. The technique of frequency map is used to analyze the nonlinear behavior. The effect of the non-linearity is tried to minimize at the given constrains of limited space. The details and results of dynamic aperture optimization are discussed in this paper.

Dynamic contrast-enhanced MR imaging of endometrial cancer. Optimizing the imaging delay for tumour-myometrium contrast

International Nuclear Information System (INIS)

Park, Sung Bin; Moon, Min Hoan; Sung, Chang Kyu; Oh, Sohee; Lee, Young Ho

2014-01-01

To investigate the optimal imaging delay time of dynamic contrast-enhanced magnetic resonance (MR) imaging in women with endometrial cancer. This prospective single-institution study was approved by the institutional review board, and informed consent was obtained from the participants. Thirty-five women (mean age, 54 years; age range, 29-66 years) underwent dynamic contrast-enhanced MR imaging with a temporal resolution of 25-40 seconds. The signal intensity difference ratios between the myometrium and endometrial cancer were analyzed to investigate the optimal imaging delay time using single change-point analysis. The optimal imaging delay time for appropriate tumour-myometrium contrast ranged from 31.7 to 268.1 seconds. The median optimal imaging delay time was 91.3 seconds, with an interquartile range of 46.2 to 119.5 seconds. The median signal intensity difference ratios between the myometrium and endometrial cancer were 0.03, with an interquartile range of -0.01 to 0.06, on the pre-contrast MR imaging and 0.20, with an interquartile range of 0.15 to 0.25, on the post-contrast MR imaging. An imaging delay of approximately 90 seconds after initiating contrast material injection may be optimal for obtaining appropriate tumour-myometrium contrast in women with endometrial cancer. (orig.)

Dynamic optimization and adaptive controller design

Science.gov (United States)

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.

COMPARISON OF NONLINEAR DYNAMICS OPTIMIZATION METHODS FOR APS-U

Energy Technology Data Exchange (ETDEWEB)

Sun, Y.; Borland, Michael

2017-06-25

Many different objectives and genetic algorithms have been proposed for storage ring nonlinear dynamics performance optimization. These optimization objectives include nonlinear chromaticities and driving/detuning terms, on-momentum and off-momentum dynamic acceptance, chromatic detuning, local momentum acceptance, variation of transverse invariant, Touschek lifetime, etc. In this paper, the effectiveness of several different optimization methods and objectives are compared for the nonlinear beam dynamics optimization of the Advanced Photon Source upgrade (APS-U) lattice. The optimized solutions from these different methods are preliminarily compared in terms of the dynamic acceptance, local momentum acceptance, chromatic detuning, and other performance measures.

Long range personalized cancer treatment strategies incorporating evolutionary dynamics.

Science.gov (United States)

Yeang, Chen-Hsiang; Beckman, Robert A

2016-10-22

Current cancer precision medicine strategies match therapies to static consensus molecular properties of an individual's cancer, thus determining the next therapeutic maneuver. These strategies typically maintain a constant treatment while the cancer is not worsening. However, cancers feature complicated sub-clonal structure and dynamic evolution. We have recently shown, in a comprehensive simulation of two non-cross resistant therapies across a broad parameter space representing realistic tumors, that substantial improvement in cure rates and median survival can be obtained utilizing dynamic precision medicine strategies. These dynamic strategies explicitly consider intratumoral heterogeneity and evolutionary dynamics, including predicted future drug resistance states, and reevaluate optimal therapy every 45 days. However, the optimization is performed in single 45 day steps ("single-step optimization"). Herein we evaluate analogous strategies that think multiple therapeutic maneuvers ahead, considering potential outcomes at 5 steps ahead ("multi-step optimization") or 40 steps ahead ("adaptive long term optimization (ALTO)") when recommending the optimal therapy in each 45 day block, in simulations involving both 2 and 3 non-cross resistant therapies. We also evaluate an ALTO approach for situations where simultaneous combination therapy is not feasible ("Adaptive long term optimization: serial monotherapy only (ALTO-SMO)"). Simulations utilize populations of 764,000 and 1,700,000 virtual patients for 2 and 3 drug cases, respectively. Each virtual patient represents a unique clinical presentation including sizes of major and minor tumor subclones, growth rates, evolution rates, and drug sensitivities. While multi-step optimization and ALTO provide no significant average survival benefit, cure rates are significantly increased by ALTO. Furthermore, in the subset of individual virtual patients demonstrating clinically significant difference in outcome between

Dynamic optimization deterministic and stochastic models

CERN Document Server

Hinderer, Karl; Stieglitz, Michael

2016-01-01

This book explores discrete-time dynamic optimization and provides a detailed introduction to both deterministic and stochastic models. Covering problems with finite and infinite horizon, as well as Markov renewal programs, Bayesian control models and partially observable processes, the book focuses on the precise modelling of applications in a variety of areas, including operations research, computer science, mathematics, statistics, engineering, economics and finance. Dynamic Optimization is a carefully presented textbook which starts with discrete-time deterministic dynamic optimization problems, providing readers with the tools for sequential decision-making, before proceeding to the more complicated stochastic models. The authors present complete and simple proofs and illustrate the main results with numerous examples and exercises (without solutions). With relevant material covered in four appendices, this book is completely self-contained.

Optimal dynamic economic dispatch of generation: A review

International Nuclear Information System (INIS)

Xia, X.; Elaiw, A.M.

2010-01-01

This paper presents a review of the research of the optimal power dynamic dispatch problem. The dynamic dispatch problem differs from the static economic dispatch problem by incorporating generator ramp rate constraints. There are two different formulations of this problem in the literature. The first formulation is the optimal control dynamic dispatch (OCDD) where the power system generation has been modeled as a control system and optimization is done in the optimal control setting with respect to the ramp rates as input variables. The second one is a later formulation known as the dynamic economic dispatch (DED) where optimization is done with respect to the dispatchable powers of the committed generation units. In this paper we first outline the two formulations, then present an overview on the mathematical optimization methods, Artificial Intelligence (AI) techniques and hybrid methods used to solve the problem incorporating extended and complex objective functions or constraints. The DED problem in deregulated electricity markets is also reported. (author)

Dynamic optimization in environmental economics

International Nuclear Information System (INIS)

Moser, Elke; Tragler, Gernot; Veliov, Vladimir M.; Semmler, Willi

2014-01-01

This book contains two chapters with the topics: 1. Chapter: INTERACTIONS BETWEEN ECONOMY AND CLIMATE: (a) Climate Change and Technical Progress: Impact of Informational Constraints. (b) Environmental Policy in a Dynamic Model with Heterogeneous Agents and Voting. (c) Optimal Environmental Policy in the Presence of Multiple Equilibria and Reversible Hysteresis. (d). Modeling the Dynamics of the Transition to a Green Economy. (e) One-Parameter GHG Emission Policy With R and D-Based Growth. (f) Pollution, Public Health Care, and Life Expectancy when Inequality Matters. (g) Uncertain Climate Policy and the Green Paradox. (h) Uniqueness Versus Indeterminacy in the Tragedy of the Commons - A ''Geometric'' Approach. 2. Chapter: OPTIMAL EXTRACTION OF RESOURCES: (j) Dynamic Behavior of Oil Importers and Exporters Under Uncertainty. (k) Robust Control of a Spatially Distributed Commercial Fishery. (l) On the Effect of Resource Exploitation on Growth: Domestic Innovation vs. Technological Diffusion Through Trade. (m) Forest Management and Biodiversity in Size-Structured Forests Under Climate Change. (n) Carbon Taxes and Comparison of Trading Regimes in Fossil Fuels. (o) Landowning, Status and Population Growth. (p) Optimal Harvesting of Size-Structured Biological Populations.

Dynamic programming for QFD in PES optimization

Energy Technology Data Exchange (ETDEWEB)

Sorrentino, R. [Mediterranean Univ. of Reggio Calabria, Reggio Calabria (Italy). Dept. of Computer Science and Electrical Technology

2008-07-01

Quality function deployment (QFD) is a method for linking the needs of the customer with design, development, engineering, manufacturing, and service functions. In the electric power industry, QFD is used to help designers concentrate on the most important technical attributes to develop better electrical services. Most optimization approaches used in QFD analysis have been based on integer or linear programming. These approaches perform well in certain circumstances, but there are problems that hinder their practical use. This paper proposed an approach to optimize Power and Energy Systems (PES). A dynamic programming approach was used along with an extended House of Quality to gather information. Dynamic programming was used to allocate the limited resources to the technical attributes. The approach integrated dynamic programming into the electrical service design process. The dynamic programming approach did not require the full relationship curve between technical attributes and customer satisfaction, or the relationship between technical attributes and cost. It only used a group of discrete points containing information about customer satisfaction, technical attributes, and the cost to find the optimal product design. Therefore, it required less time and resources than other approaches. At the end of the optimization process, the value of each technical attribute, the related cost, and the overall customer satisfaction were obtained at the same time. It was concluded that compared with other optimization methods, the dynamic programming method requires less information and the optimal results are more relevant. 21 refs., 2 tabs., 2 figs.

First principles molecular dynamics without self-consistent field optimization

International Nuclear Information System (INIS)

Souvatzis, Petros; Niklasson, Anders M. N.

2014-01-01

We present a first principles molecular dynamics approach that is based on time-reversible extended Lagrangian Born-Oppenheimer molecular dynamics [A. M. N. Niklasson, Phys. Rev. Lett. 100, 123004 (2008)] in the limit of vanishing self-consistent field optimization. The optimization-free dynamics keeps the computational cost to a minimum and typically provides molecular trajectories that closely follow the exact Born-Oppenheimer potential energy surface. Only one single diagonalization and Hamiltonian (or Fockian) construction are required in each integration time step. The proposed dynamics is derived for a general free-energy potential surface valid at finite electronic temperatures within hybrid density functional theory. Even in the event of irregular functional behavior that may cause a dynamical instability, the optimization-free limit represents a natural starting guess for force calculations that may require a more elaborate iterative electronic ground state optimization. Our optimization-free dynamics thus represents a flexible theoretical framework for a broad and general class of ab initio molecular dynamics simulations

A Dynamic Multistage Hybrid Swarm Intelligence Optimization Algorithm for Function Optimization

Directory of Open Access Journals (Sweden)

Daqing Wu

2012-01-01

Full Text Available A novel dynamic multistage hybrid swarm intelligence optimization algorithm is introduced, which is abbreviated as DM-PSO-ABC. The DM-PSO-ABC combined the exploration capabilities of the dynamic multiswarm particle swarm optimizer (PSO and the stochastic exploitation of the cooperative artificial bee colony algorithm (CABC for solving the function optimization. In the proposed hybrid algorithm, the whole process is divided into three stages. In the first stage, a dynamic multiswarm PSO is constructed to maintain the population diversity. In the second stage, the parallel, positive feedback of CABC was implemented in each small swarm. In the third stage, we make use of the particle swarm optimization global model, which has a faster convergence speed to enhance the global convergence in solving the whole problem. To verify the effectiveness and efficiency of the proposed hybrid algorithm, various scale benchmark problems are tested to demonstrate the potential of the proposed multistage hybrid swarm intelligence optimization algorithm. The results show that DM-PSO-ABC is better in the search precision, and convergence property and has strong ability to escape from the local suboptima when compared with several other peer algorithms.

Optimal Sizing of Energy Storage for Community Microgrids Considering Building Thermal Dynamics

Energy Technology Data Exchange (ETDEWEB)

Liu, Guodong [ORNL; Li, Zhi [ORNL; Starke, Michael R. [ORNL; Ollis, Ben [ORNL; Tomsovic, Kevin [University of Tennessee, Knoxville (UTK)

2017-07-01

This paper proposes an optimization model for the optimal sizing of energy storage in community microgrids considering the building thermal dynamics and customer comfort preference. The proposed model minimizes the annualized cost of the community microgrid, including energy storage investment, purchased energy cost, demand charge, energy storage degradation cost, voluntary load shedding cost and the cost associated with customer discomfort due to room temperature deviation. The decision variables are the power and energy capacity of invested energy storage. In particular, we assume the heating, ventilation and air-conditioning (HVAC) systems can be scheduled intelligently by the microgrid central controller while maintaining the indoor temperature in the comfort range set by customers. For this purpose, the detailed thermal dynamic characteristics of buildings have been integrated into the optimization model. Numerical simulation shows significant cost reduction by the proposed model. The impacts of various costs on the optimal solution are investigated by sensitivity analysis.

Dynamic optimization in environmental economics

Energy Technology Data Exchange (ETDEWEB)

Moser, Elke; Tragler, Gernot; Veliov, Vladimir M. (eds.) [Vienna Univ. of Technology (Austria). Inst. of Mathematical Methods in Economics; Semmler, Willi [The New School for Social Research, New York, NY (United States). Dept. of Economics

2014-11-01

This book contains two chapters with the topics: 1. Chapter: INTERACTIONS BETWEEN ECONOMY AND CLIMATE: (a) Climate Change and Technical Progress: Impact of Informational Constraints. (b) Environmental Policy in a Dynamic Model with Heterogeneous Agents and Voting. (c) Optimal Environmental Policy in the Presence of Multiple Equilibria and Reversible Hysteresis. (d). Modeling the Dynamics of the Transition to a Green Economy. (e) One-Parameter GHG Emission Policy With R and D-Based Growth. (f) Pollution, Public Health Care, and Life Expectancy when Inequality Matters. (g) Uncertain Climate Policy and the Green Paradox. (h) Uniqueness Versus Indeterminacy in the Tragedy of the Commons - A ''Geometric'' Approach. 2. Chapter: OPTIMAL EXTRACTION OF RESOURCES: (j) Dynamic Behavior of Oil Importers and Exporters Under Uncertainty. (k) Robust Control of a Spatially Distributed Commercial Fishery. (l) On the Effect of Resource Exploitation on Growth: Domestic Innovation vs. Technological Diffusion Through Trade. (m) Forest Management and Biodiversity in Size-Structured Forests Under Climate Change. (n) Carbon Taxes and Comparison of Trading Regimes in Fossil Fuels. (o) Landowning, Status and Population Growth. (p) Optimal Harvesting of Size-Structured Biological Populations.

Effects of upper body parameters on biped walking efficiency studied by dynamic optimization

Directory of Open Access Journals (Sweden)

Kang An

2016-12-01

Full Text Available Walking efficiency is one of the considerations for designing biped robots. This article uses the dynamic optimization method to study the effects of upper body parameters, including upper body length and mass, on walking efficiency. Two minimal actuations, hip joint torque and push-off impulse, are used in the walking model, and minimal constraints are set in a free search using the dynamic optimization. Results show that there is an optimal solution of upper body length for the efficient walking within a range of walking speed and step length. For short step length, walking with a lighter upper body mass is found to be more efficient and vice versa. It is also found that for higher speed locomotion, the increase of the upper body length and mass can make the walking gait optimal rather than other kind of gaits. In addition, the typical strategy of an optimal walking gait is that just actuating the swing leg at the beginning of the step.

Low Parametric Sensitivity Realizations with relaxed L2-dynamic-range-scaling constraints

OpenAIRE

Hilaire , Thibault

2009-01-01

This paper presents a new dynamic-range scaling for the implementation of filters/controllers in state-space form. Relaxing the classical L2-scaling constraints by specific fixed-point considerations allows for a higher degree of freedom for the optimal L2-parametric sensitivity problem. However, overflows in the implementation are still prevented. The underlying constrained problem is converted into an unconstrained problem for which a solution can be provided. This leads to realizations whi...

Optimization by record dynamics

DEFF Research Database (Denmark)

Barettin, Daniele; Sibani, Paolo

2014-01-01

Large dynamical changes in thermalizing glassy systems are triggered by trajectories crossing record sized barriers, a behavior revealing the presence of a hierarchical structure in configuration space. The observation is here turned into a novel local search optimization algorithm dubbed record...... dynamics optimization,or RDO. RDO uses the Metropolis rule to accept or reject candidate solutions depending on the value of a parameter akin to the temperature and minimizes the cost function of the problem at hand through cycles where its ‘temperature’ is raised and subsequently decreased in order......), is applied to the same problem as a benchmark. RDO and PT turn out to produce solutions of similar quality for similar numerical effort, but RDO is simpler to program and additionally yields geometrical information on the system’s configuration space which is of interest in many applications. In particular...

High dynamic range image acquisition based on multiplex cameras

Science.gov (United States)

Zeng, Hairui; Sun, Huayan; Zhang, Tinghua

2018-03-01

High dynamic image is an important technology of photoelectric information acquisition, providing higher dynamic range and more image details, and it can better reflect the real environment, light and color information. Currently, the method of high dynamic range image synthesis based on different exposure image sequences cannot adapt to the dynamic scene. It fails to overcome the effects of moving targets, resulting in the phenomenon of ghost. Therefore, a new high dynamic range image acquisition method based on multiplex cameras system was proposed. Firstly, different exposure images sequences were captured with the camera array, using the method of derivative optical flow based on color gradient to get the deviation between images, and aligned the images. Then, the high dynamic range image fusion weighting function was established by combination of inverse camera response function and deviation between images, and was applied to generated a high dynamic range image. The experiments show that the proposed method can effectively obtain high dynamic images in dynamic scene, and achieves good results.

Role of controllability in optimizing quantum dynamics

International Nuclear Information System (INIS)

Wu Rebing; Hsieh, Michael A.; Rabitz, Herschel

2011-01-01

This paper reveals an important role that controllability plays in the complexity of optimizing quantum control dynamics. We show that the loss of controllability generally leads to multiple locally suboptimal controls when gate fidelity in a quantum control system is maximized, which does not happen if the system is controllable. Such local suboptimal controls may attract an optimization algorithm into a local trap when a global optimal solution is sought, even if the target gate can be perfectly realized. This conclusion results from an analysis of the critical topology of the corresponding quantum control landscape, which refers to the gate fidelity objective as a functional of the control fields. For uncontrollable systems, due to SU(2) and SU(3) dynamical symmetries, the control landscape corresponding to an implementable target gate is proven to possess multiple locally optimal critical points, and its ruggedness can be further increased if the target gate is not realizable. These results imply that the optimization of quantum dynamics can be seriously impeded when operating with local search algorithms under these conditions, and thus full controllability is demanded.

Conceptual Design Optimization of an Augmented Stability Aircraft Incorporating Dynamic Response Performance Constraints

Science.gov (United States)

Welstead, Jason

2014-01-01

This research focused on incorporating stability and control into a multidisciplinary de- sign optimization on a Boeing 737-class advanced concept called the D8.2b. A new method of evaluating the aircraft handling performance using quantitative evaluation of the sys- tem to disturbances, including perturbations, continuous turbulence, and discrete gusts, is presented. A multidisciplinary design optimization was performed using the D8.2b transport air- craft concept. The con guration was optimized for minimum fuel burn using a design range of 3,000 nautical miles. Optimization cases were run using xed tail volume coecients, static trim constraints, and static trim and dynamic response constraints. A Cessna 182T model was used to test the various dynamic analysis components, ensuring the analysis was behaving as expected. Results of the optimizations show that including stability and con- trol in the design process drastically alters the optimal design, indicating that stability and control should be included in conceptual design to avoid system level penalties later in the design process.

Optimal lag in dynamical investments

OpenAIRE

Serva, M.

1998-01-01

A portfolio of different stocks and a risk-less security whose composition is dynamically maintained stable by trading shares at any time step leads to a growth of the capital with a nonrandom rate. This is the key for the theory of optimal-growth investment formulated by Kelly. In presence of transaction costs, the optimal composition changes and, more important, it turns out that the frequency of transactions must be reduced. This simple observation leads to the definition of an optimal lag...

Gradient-based optimization in nonlinear structural dynamics

DEFF Research Database (Denmark)

Dou, Suguang

The intrinsic nonlinearity of mechanical structures can give rise to rich nonlinear dynamics. Recently, nonlinear dynamics of micro-mechanical structures have contributed to developing new Micro-Electro-Mechanical Systems (MEMS), for example, atomic force microscope, passive frequency divider......, frequency stabilization, and disk resonator gyroscope. For advanced design of these structures, it is of considerable value to extend current optimization in linear structural dynamics into nonlinear structural dynamics. In this thesis, we present a framework for modelling, analysis, characterization......, and optimization of nonlinear structural dynamics. In the modelling, nonlinear finite elements are used. In the analysis, nonlinear frequency response and nonlinear normal modes are calculated based on a harmonic balance method with higher-order harmonics. In the characterization, nonlinear modal coupling...

Modulation of neuronal dynamic range using two different adaptation mechanisms

Directory of Open Access Journals (Sweden)

Lei Wang

2017-01-01

Full Text Available The capability of neurons to discriminate between intensity of external stimulus is measured by its dynamic range. A larger dynamic range indicates a greater probability of neuronal survival. In this study, the potential roles of adaptation mechanisms (ion currents in modulating neuronal dynamic range were numerically investigated. Based on the adaptive exponential integrate-and-fire model, which includes two different adaptation mechanisms, i.e. subthreshold and suprathreshold (spike-triggered adaptation, our results reveal that the two adaptation mechanisms exhibit rather different roles in regulating neuronal dynamic range. Specifically, subthreshold adaptation acts as a negative factor that observably decreases the neuronal dynamic range, while suprathreshold adaptation has little influence on the neuronal dynamic range. Moreover, when stochastic noise was introduced into the adaptation mechanisms, the dynamic range was apparently enhanced, regardless of what state the neuron was in, e.g. adaptive or non-adaptive. Our model results suggested that the neuronal dynamic range can be differentially modulated by different adaptation mechanisms. Additionally, noise was a non-ignorable factor, which could effectively modulate the neuronal dynamic range.

The analysis on dynamic range of industrial CT system

International Nuclear Information System (INIS)

Wang Huiqian; Wang Jue; Tan Hui

2011-01-01

Concerning the limitations of the definition of the dynamic range of industrial computed tomography (ICT) system, it researches the definition, measuring method and influencing factors of the dynamic range of industrial computed tomography (ICT) system from the concept of quantization and system. First, the character of the input-output curve was analyzed, and the method of obtaining the dynamic range of industrial computed tomography (ICT) system was proposed. Then, an experiment model was designed to gain dynamic range, based on 6 MeV high-energy industrial computed tomography (ICT) system. The results show that the larger the photosurface is, the smaller the dynamic range is, when the other parameters are unchanged. (authors)

Dynamic range meter for radiofrequency amplifiers

Directory of Open Access Journals (Sweden)

Drozd S. S.

2009-04-01

Full Text Available The new measurement setup having increased on 20…30 dB the own dynamic range in comparison with the standard circuit of the dynamic range meter is offered and the rated value of an error bringing by setup in the worst case does not exceed ± 2,8 dB. The measurement setup can be applied also to determinate levels of intermodulation components average power amplifiers and powerful amplifiers of a low-frequency at replacement of the quartz filter on meeting low-frequency the LC-filter and the spectrum analyzer.

Dynamic optimization of a FCC converter unit: numerical analysis

Directory of Open Access Journals (Sweden)

E. Almeida Nt

2011-03-01

Full Text Available Fluidized-bed Catalytic Cracking (FCC is a process subject to frequent variations in the operating conditions (including feed quality and feed rate. The production objectives usually are the maximization of LPG and gasoline production. This fact makes the FCC converter unit an excellent opportunity for real-time optimization. The present work aims to apply a dynamic optimization in an industrial FCC converter unit, using a mechanistic dynamic model, and to carry out a numerical analysis of the solution procedure. A simultaneous approach was used to discretize the system of differential-algebraic equations and the resulting large-scale NLP problem was solved using the IPOPT solver. This study also does a short comparison between the results obtained by a potential dynamic real-time optimization (DRTO against a possible steady-state real-time optimization (RTO application. The results demonstrate that the application of dynamic real-time optimization of a FCC converter unit can bring significant benefits in production.

Efficient dynamic optimization of logic programs

Science.gov (United States)

Laird, Phil

1992-01-01

A summary is given of the dynamic optimization approach to speed up learning for logic programs. The problem is to restructure a recursive program into an equivalent program whose expected performance is optimal for an unknown but fixed population of problem instances. We define the term 'optimal' relative to the source of input instances and sketch an algorithm that can come within a logarithmic factor of optimal with high probability. Finally, we show that finding high-utility unfolding operations (such as EBG) can be reduced to clause reordering.

On Dynamic Range Limitations of CMOS Current Conveyors

DEFF Research Database (Denmark)

Bruun, Erik

1999-01-01

frequency band and for the situation where the conveyor is used over the full bandwidth achievable. Finally, the optimisation of the current input range is related to the distortion characteristics and it is pointed out that to a first order approximation the distortion is independent of the current range.......This paper is concerned with the dynamic range of continuous time CMOS current mode circuits. As a representative current mode device a class AB current conveyor is examined. First, the voltage input range of the high impedance Y input is investigated. Next, the current input range of the low...... impedance X input is investigated. It is compared to the thermal noise in the X to Z signal path in order to evaluate the dynamic range, and the dependencies of the dynamic range on the supply voltage and the transistor lay-out is derived, both for the situation where the conveyor is used over a narrow...

HEVC for high dynamic range services

Science.gov (United States)

Kim, Seung-Hwan; Zhao, Jie; Misra, Kiran; Segall, Andrew

2015-09-01

Displays capable of showing a greater range of luminance values can render content containing high dynamic range information in a way such that the viewers have a more immersive experience. This paper introduces the design aspects of a high dynamic range (HDR) system, and examines the performance of the HDR processing chain in terms of compression efficiency. Specifically it examines the relation between recently introduced Society of Motion Picture and Television Engineers (SMPTE) ST 2084 transfer function and the High Efficiency Video Coding (HEVC) standard. SMPTE ST 2084 is designed to cover the full range of an HDR signal from 0 to 10,000 nits, however in many situations the valid signal range of actual video might be smaller than SMPTE ST 2084 supported range. The above restricted signal range results in restricted range of code values for input video data and adversely impacts compression efficiency. In this paper, we propose a code value remapping method that extends the restricted range code values into the full range code values so that the existing standards such as HEVC may better compress the video content. The paper also identifies related non-normative encoder-only changes that are required for remapping method for a fair comparison with anchor. Results are presented comparing the efficiency of the current approach versus the proposed remapping method for HM-16.2.

Dynamic Range Across Music Genres and the Perception of Dynamic Compression in Hearing-Impaired Listeners

Directory of Open Access Journals (Sweden)

Martin Kirchberger

2016-02-01

Full Text Available Dynamic range compression serves different purposes in the music and hearing-aid industries. In the music industry, it is used to make music louder and more attractive to normal-hearing listeners. In the hearing-aid industry, it is used to map the variable dynamic range of acoustic signals to the reduced dynamic range of hearing-impaired listeners. Hence, hearing-aided listeners will typically receive a dual dose of compression when listening to recorded music. The present study involved an acoustic analysis of dynamic range across a cross section of recorded music as well as a perceptual study comparing the efficacy of different compression schemes. The acoustic analysis revealed that the dynamic range of samples from popular genres, such as rock or rap, was generally smaller than the dynamic range of samples from classical genres, such as opera and orchestra. By comparison, the dynamic range of speech, based on recordings of monologues in quiet, was larger than the dynamic range of all music genres tested. The perceptual study compared the effect of the prescription rule NAL-NL2 with a semicompressive and a linear scheme. Music subjected to linear processing had the highest ratings for dynamics and quality, followed by the semicompressive and the NAL-NL2 setting. These findings advise against NAL-NL2 as a prescription rule for recorded music and recommend linear settings.

Dynamic Range Across Music Genres and the Perception of Dynamic Compression in Hearing-Impaired Listeners

Science.gov (United States)

Kirchberger, Martin

2016-01-01

Dynamic range compression serves different purposes in the music and hearing-aid industries. In the music industry, it is used to make music louder and more attractive to normal-hearing listeners. In the hearing-aid industry, it is used to map the variable dynamic range of acoustic signals to the reduced dynamic range of hearing-impaired listeners. Hence, hearing-aided listeners will typically receive a dual dose of compression when listening to recorded music. The present study involved an acoustic analysis of dynamic range across a cross section of recorded music as well as a perceptual study comparing the efficacy of different compression schemes. The acoustic analysis revealed that the dynamic range of samples from popular genres, such as rock or rap, was generally smaller than the dynamic range of samples from classical genres, such as opera and orchestra. By comparison, the dynamic range of speech, based on recordings of monologues in quiet, was larger than the dynamic range of all music genres tested. The perceptual study compared the effect of the prescription rule NAL-NL2 with a semicompressive and a linear scheme. Music subjected to linear processing had the highest ratings for dynamics and quality, followed by the semicompressive and the NAL-NL2 setting. These findings advise against NAL-NL2 as a prescription rule for recorded music and recommend linear settings. PMID:26868955

Dynamic Range Across Music Genres and the Perception of Dynamic Compression in Hearing-Impaired Listeners.

Science.gov (United States)

Kirchberger, Martin; Russo, Frank A

2016-02-10

Dynamic range compression serves different purposes in the music and hearing-aid industries. In the music industry, it is used to make music louder and more attractive to normal-hearing listeners. In the hearing-aid industry, it is used to map the variable dynamic range of acoustic signals to the reduced dynamic range of hearing-impaired listeners. Hence, hearing-aided listeners will typically receive a dual dose of compression when listening to recorded music. The present study involved an acoustic analysis of dynamic range across a cross section of recorded music as well as a perceptual study comparing the efficacy of different compression schemes. The acoustic analysis revealed that the dynamic range of samples from popular genres, such as rock or rap, was generally smaller than the dynamic range of samples from classical genres, such as opera and orchestra. By comparison, the dynamic range of speech, based on recordings of monologues in quiet, was larger than the dynamic range of all music genres tested. The perceptual study compared the effect of the prescription rule NAL-NL2 with a semicompressive and a linear scheme. Music subjected to linear processing had the highest ratings for dynamics and quality, followed by the semicompressive and the NAL-NL2 setting. These findings advise against NAL-NL2 as a prescription rule for recorded music and recommend linear settings. © The Author(s) 2016.

Research on Dynamic Optimization for Road-friendly Vehicle Suspension

Directory of Open Access Journals (Sweden)

Lu Yongjie

2014-10-01

Full Text Available The heavy vehicle brings large dynamic loads to the road surface, which would reduce vehicle ride comfort and shorten road service life. The structure characteristic of heavy vehicle suspension has a significant impact on vehicle performance. Based on the D'Alembert principle, the dynamics models of independent and integral balanced suspension are proposed considering mass and inertia of balancing rod. The sprung mass acceleration and the tire dynamic force for two kinds of balanced suspension and the traditional quarter vehicle model are compared in frequency-domain and time-domain respectively. It is concluded that a quarter vehicle model simplified for balanced suspension could be used to evaluate the ride comfort of vehicle well, but it has some limitations in assessing the vehicle road-friendliness. Then, the sprung mass acceleration and the road damage coefficients are also analyzed under different vehicle design and running parameters at detail. Some conclusions are obtained: low suspension stiffness, high suspension damping and low tire stiffness are all favorable to improve vehicle performance; there is a saturation range of suspension damping enhancing vehicle performance; improving the road surface roughness and avoiding the no-load running are two effective methods to accomplish the better ride comfort and road-friendliness. The suspension stiffness and damping parameters are chosen for optimal parameters matching of road friendliness based on the approximation optimization method.

VMAT optimization with dynamic collimator rotation.

Science.gov (United States)

Lyu, Qihui; O'Connor, Daniel; Ruan, Dan; Yu, Victoria; Nguyen, Dan; Sheng, Ke

2018-04-16

Although collimator rotation is an optimization variable that can be exploited for dosimetric advantages, existing Volumetric Modulated Arc Therapy (VMAT) optimization uses a fixed collimator angle in each arc and only rotates the collimator between arcs. In this study, we develop a novel integrated optimization method for VMAT, accounting for dynamic collimator angles during the arc motion. Direct Aperture Optimization (DAO) for Dynamic Collimator in VMAT (DC-VMAT) was achieved by adding to the existing dose fidelity objective an anisotropic total variation term for regulating the fluence smoothness, a binary variable for forming simple apertures, and a group sparsity term for controlling collimator rotation. The optimal collimator angle for each beam angle was selected using the Dijkstra's algorithm, where the node costs depend on the estimated fluence map at the current iteration and the edge costs account for the mechanical constraints of multi-leaf collimator (MLC). An alternating optimization strategy was implemented to solve the DAO and collimator angle selection (CAS). Feasibility of DC-VMAT using one full-arc with dynamic collimator rotation was tested on a phantom with two small spherical targets, a brain, a lung and a prostate cancer patient. The plan was compared against a static collimator VMAT (SC-VMAT) plan using three full arcs with 60 degrees of collimator angle separation in patient studies. With the same target coverage, DC-VMAT achieved 20.3% reduction of R50 in the phantom study, and reduced the average max and mean OAR dose by 4.49% and 2.53% of the prescription dose in patient studies, as compared with SC-VMAT. The collimator rotation co-ordinated with the gantry rotation in DC-VMAT plans for deliverability. There were 13 beam angles in the single-arc DC-VMAT plan in patient studies that requires slower gantry rotation to accommodate multiple collimator angles. The novel DC-VMAT approach utilizes the dynamic collimator rotation during arc

High dynamic range coding imaging system

Science.gov (United States)

Wu, Renfan; Huang, Yifan; Hou, Guangqi

2014-10-01

We present a high dynamic range (HDR) imaging system design scheme based on coded aperture technique. This scheme can help us obtain HDR images which have extended depth of field. We adopt Sparse coding algorithm to design coded patterns. Then we utilize the sensor unit to acquire coded images under different exposure settings. With the guide of the multiple exposure parameters, a series of low dynamic range (LDR) coded images are reconstructed. We use some existing algorithms to fuse and display a HDR image by those LDR images. We build an optical simulation model and get some simulation images to verify the novel system.

RADIANCE DOMAIN COMPOSITING FOR HIGH DYNAMIC RANGE IMAGING

Directory of Open Access Journals (Sweden)

M.R. Renu

2013-02-01

Full Text Available High dynamic range imaging aims at creating an image with a range of intensity variations larger than the range supported by a camera sensor. Most commonly used methods combine multiple exposure low dynamic range (LDR images, to obtain the high dynamic range (HDR image. Available methods typically neglect the noise term while finding appropriate weighting functions to estimate the camera response function as well as the radiance map. We look at the HDR imaging problem in a denoising frame work and aim at reconstructing a low noise radiance map from noisy low dynamic range images, which is tone mapped to get the LDR equivalent of the HDR image. We propose a maximum aposteriori probability (MAP based reconstruction of the HDR image using Gibb’s prior to model the radiance map, with total variation (TV as the prior to avoid unnecessary smoothing of the radiance field. To make the computation with TV prior efficient, we extend the majorize-minimize method of upper bounding the total variation by a quadratic function to our case which has a nonlinear term arising from the camera response function. A theoretical justification for doing radiance domain denoising as opposed to image domain denoising is also provided.

Dynamic optimization the calculus of variations and optimal control in economics and management

CERN Document Server

Kamien, Morton I

2012-01-01

Since its initial publication, this text has defined courses in dynamic optimization taught to economics and management science students. The two-part treatment covers the calculus of variations and optimal control. 1998 edition.

Low-power low-noise mixed-mode VLSI ASIC for infinite dynamic range imaging applications

Science.gov (United States)

Turchetta, Renato; Hu, Y.; Zinzius, Y.; Colledani, C.; Loge, A.

1998-11-01

Solid state solutions for imaging are mainly represented by CCDs and, more recently, by CMOS imagers. Both devices are based on the integration of the total charge generated by the impinging radiation, with no processing of the single photon information. The dynamic range of these devices is intrinsically limited by the finite value of noise. Here we present the design of an architecture which allows efficient, in-pixel, noise reduction to a practically zero level, thus allowing infinite dynamic range imaging. A detailed calculation of the dynamic range is worked out, showing that noise is efficiently suppressed. This architecture is based on the concept of single-photon counting. In each pixel, we integrate both the front-end, low-noise, low-power analog part and the digital part. The former consists of a charge preamplifier, an active filter for optimal noise bandwidth reduction, a buffer and a threshold comparator, and the latter is simply a counter, which can be programmed to act as a normal shift register for the readout of the counters' contents. Two different ASIC's based on this concept have been designed for different applications. The first one has been optimized for silicon edge-on microstrips detectors, used in a digital mammography R and D project. It is a 32-channel circuit, with a 16-bit binary static counter.It has been optimized for a relatively large detector capacitance of 5 pF. Noise has been measured to be equal to 100 + 7*Cd (pF) electron rms with the digital part, showing no degradation of the noise performances with respect to the design values. The power consumption is 3.8mW/channel for a peaking time of about 1 microsecond(s) . The second circuit is a prototype for pixel imaging. The total active area is about (250 micrometers )**2. The main differences of the electronic architecture with respect to the first prototype are: i) different optimization of the analog front-end part for low-capacitance detectors, ii) in- pixel 4-bit comparator

Criteria for optimizing cortical hierarchies with continuous ranges

Directory of Open Access Journals (Sweden)

Antje Krumnack

2010-03-01

Full Text Available In a recent paper (Reid et al.; 2009, NeuroImage we introduced a method to calculate optimal hierarchies in the visual network that utilizes continuous, rather than discrete, hierarchical levels, and permits a range of acceptable values rather than attempting to fit fixed hierarchical distances. There, to obtain a hierarchy, the sum of deviations from the constraints that define the hierarchy was minimized using linear optimization. In the short time since publication of that paper we noticed that many colleagues misinterpreted the meaning of the term optimal hierarchy. In particular, a majority of them were under the impression that there was perhaps only one optimal hierarchy, but a substantial difficulty in finding that one. However, there is not only more than one optimal hierarchy but also more than one option for defining optimality. Continuing the line of this work we look at additional options for optimizing the visual hierarchy: minimizing the number of violated constraints and minimizing the maximal size of a constraint violation using linear optimization and mixed integer programming. The implementation of both optimization criteria is explained in detail. In addition, using constraint sets based on the data from Felleman and Van Essen, optimal hierarchies for the visual network are calculated for both optimization methods.

Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis

Directory of Open Access Journals (Sweden)

Tashkova Katerina

2011-10-01

Full Text Available Abstract Background We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. Results We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA, particle-swarm optimization (PSO, and differential evolution (DE, as well as a local-search derivative-based algorithm 717 (A717 to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Conclusions Overall, the global meta-heuristic methods (DASA, PSO, and DE clearly and significantly outperform the local derivative-based method (A717. Among the three meta-heuristics, differential evolution (DE performs best in terms of the objective function, i.e., reconstructing the output, and in terms of

Parameter estimation with bio-inspired meta-heuristic optimization: modeling the dynamics of endocytosis.

Science.gov (United States)

Tashkova, Katerina; Korošec, Peter; Silc, Jurij; Todorovski, Ljupčo; Džeroski, Sašo

2011-10-11

We address the task of parameter estimation in models of the dynamics of biological systems based on ordinary differential equations (ODEs) from measured data, where the models are typically non-linear and have many parameters, the measurements are imperfect due to noise, and the studied system can often be only partially observed. A representative task is to estimate the parameters in a model of the dynamics of endocytosis, i.e., endosome maturation, reflected in a cut-out switch transition between the Rab5 and Rab7 domain protein concentrations, from experimental measurements of these concentrations. The general parameter estimation task and the specific instance considered here are challenging optimization problems, calling for the use of advanced meta-heuristic optimization methods, such as evolutionary or swarm-based methods. We apply three global-search meta-heuristic algorithms for numerical optimization, i.e., differential ant-stigmergy algorithm (DASA), particle-swarm optimization (PSO), and differential evolution (DE), as well as a local-search derivative-based algorithm 717 (A717) to the task of estimating parameters in ODEs. We evaluate their performance on the considered representative task along a number of metrics, including the quality of reconstructing the system output and the complete dynamics, as well as the speed of convergence, both on real-experimental data and on artificial pseudo-experimental data with varying amounts of noise. We compare the four optimization methods under a range of observation scenarios, where data of different completeness and accuracy of interpretation are given as input. Overall, the global meta-heuristic methods (DASA, PSO, and DE) clearly and significantly outperform the local derivative-based method (A717). Among the three meta-heuristics, differential evolution (DE) performs best in terms of the objective function, i.e., reconstructing the output, and in terms of convergence. These results hold for both real and

Optimal dynamic detection of explosives

Energy Technology Data Exchange (ETDEWEB)

Moore, David Steven [Los Alamos National Laboratory; Mcgrane, Shawn D [Los Alamos National Laboratory; Greenfield, Margo T [Los Alamos National Laboratory; Scharff, R J [Los Alamos National Laboratory; Rabitz, Herschel A [PRINCETON UNIV; Roslund, J [PRINCETON UNIV

2009-01-01

The detection of explosives is a notoriously difficult problem, especially at stand-off distances, due to their (generally) low vapor pressure, environmental and matrix interferences, and packaging. We are exploring optimal dynamic detection to exploit the best capabilities of recent advances in laser technology and recent discoveries in optimal shaping of laser pulses for control of molecular processes to significantly enhance the standoff detection of explosives. The core of the ODD-Ex technique is the introduction of optimally shaped laser pulses to simultaneously enhance sensitivity of explosives signatures while reducing the influence of noise and the signals from background interferents in the field (increase selectivity). These goals are being addressed by operating in an optimal nonlinear fashion, typically with a single shaped laser pulse inherently containing within it coherently locked control and probe sub-pulses. With sufficient bandwidth, the technique is capable of intrinsically providing orthogonal broad spectral information for data fusion, all from a single optimal pulse.

Evaluation and improvement of dynamic optimality in electrochemical reactors

International Nuclear Information System (INIS)

Vijayasekaran, B.; Basha, C. Ahmed

2005-01-01

A systematic approach for the dynamic optimization problem statement to improve the dynamic optimality in electrochemical reactors is presented in this paper. The formulation takes an account of the diffusion phenomenon in the electrode/electrolyte interface. To demonstrate the present methodology, the optimal time-varying electrode potential for a coupled chemical-electrochemical reaction scheme, that maximizes the production of the desired product in a batch electrochemical reactor with/without recirculation are determined. The dynamic optimization problem statement, based upon this approach, is a nonlinear differential algebraic system, and its solution provides information about the optimal policy. Optimal control policy at different conditions is evaluated using the best-known Pontryagin's maximum principle. The two-point boundary value problem resulting from the application of the maximum principle is then solved using the control vector iteration technique. These optimal time-varying profiles of electrode potential are then compared to the best uniform operation through the relative improvements of the performance index. The application of the proposed approach to two electrochemical systems, described by ordinary differential equations, shows that the existing electrochemical process control strategy could be improved considerably when the proposed method is incorporated

High Dynamic Range Imaging Using Multiple Exposures

Science.gov (United States)

Hou, Xinglin; Luo, Haibo; Zhou, Peipei; Zhou, Wei

2017-06-01

It is challenging to capture a high-dynamic range (HDR) scene using a low-dynamic range (LDR) camera. This paper presents an approach for improving the dynamic range of cameras by using multiple exposure images of same scene taken under different exposure times. First, the camera response function (CRF) is recovered by solving a high-order polynomial in which only the ratios of the exposures are used. Then, the HDR radiance image is reconstructed by weighted summation of the each radiance maps. After that, a novel local tone mapping (TM) operator is proposed for the display of the HDR radiance image. By solving the high-order polynomial, the CRF can be recovered quickly and easily. Taken the local image feature and characteristic of histogram statics into consideration, the proposed TM operator could preserve the local details efficiently. Experimental result demonstrates the effectiveness of our method. By comparison, the method outperforms other methods in terms of imaging quality.

Optimal Operation of Radial Distribution Systems Using Extended Dynamic Programming

DEFF Research Database (Denmark)

Lopez, Juan Camilo; Vergara, Pedro P.; Lyra, Christiano

2018-01-01

An extended dynamic programming (EDP) approach is developed to optimize the ac steady-state operation of radial electrical distribution systems (EDS). Based on the optimality principle of the recursive Hamilton-Jacobi-Bellman equations, the proposed EDP approach determines the optimal operation o...... approach is illustrated using real-scale systems and comparisons with commercial programming solvers. Finally, generalizations to consider other EDS operation problems are also discussed.......An extended dynamic programming (EDP) approach is developed to optimize the ac steady-state operation of radial electrical distribution systems (EDS). Based on the optimality principle of the recursive Hamilton-Jacobi-Bellman equations, the proposed EDP approach determines the optimal operation...... of the EDS by setting the values of the controllable variables at each time period. A suitable definition for the stages of the problem makes it possible to represent the optimal ac power flow of radial EDS as a dynamic programming problem, wherein the 'curse of dimensionality' is a minor concern, since...

Benchmarking novel approaches for modelling species range dynamics.

Science.gov (United States)

Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H; Moore, Kara A; Zimmermann, Niklaus E

2016-08-01

Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species' range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species' response to climate change but also emphasize several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches

Reconstructing Interlaced High-Dynamic-Range Video Using Joint Learning.

Science.gov (United States)

Inchang Choi; Seung-Hwan Baek; Kim, Min H

2017-11-01

For extending the dynamic range of video, it is a common practice to capture multiple frames sequentially with different exposures and combine them to extend the dynamic range of each video frame. However, this approach results in typical ghosting artifacts due to fast and complex motion in nature. As an alternative, video imaging with interlaced exposures has been introduced to extend the dynamic range. However, the interlaced approach has been hindered by jaggy artifacts and sensor noise, leading to concerns over image quality. In this paper, we propose a data-driven approach for jointly solving two specific problems of deinterlacing and denoising that arise in interlaced video imaging with different exposures. First, we solve the deinterlacing problem using joint dictionary learning via sparse coding. Since partial information of detail in differently exposed rows is often available via interlacing, we make use of the information to reconstruct details of the extended dynamic range from the interlaced video input. Second, we jointly solve the denoising problem by tailoring sparse coding to better handle additive noise in low-/high-exposure rows, and also adopt multiscale homography flow to temporal sequences for denoising. We anticipate that the proposed method will allow for concurrent capture of higher dynamic range video frames without suffering from ghosting artifacts. We demonstrate the advantages of our interlaced video imaging compared with the state-of-the-art high-dynamic-range video methods.

Optimization of multi-response dynamic systems integrating multiple ...

African Journals Online (AJOL)

regression and Taguchi's dynamic signal-to-noise ratio concept ..... algorithm for dynamic multi-response optimization based on goal programming approach. .... problem-solving confirmation, if no grave infringement of model suppositions is ...

Co-occurrence of viruses and mosquitoes at the vectors' optimal climate range: An underestimated risk to temperate regions?

Science.gov (United States)

Blagrove, Marcus S C; Caminade, Cyril; Waldmann, Elisabeth; Sutton, Elizabeth R; Wardeh, Maya; Baylis, Matthew

2017-06-01

Mosquito-borne viruses have been estimated to cause over 100 million cases of human disease annually. Many methodologies have been developed to help identify areas most at risk from transmission of these viruses. However, generally, these methodologies focus predominantly on the effects of climate on either the vectors or the pathogens they spread, and do not consider the dynamic interaction between the optimal conditions for both vector and virus. Here, we use a new approach that considers the complex interplay between the optimal temperature for virus transmission, and the optimal climate for the mosquito vectors. Using published geolocated data we identified temperature and rainfall ranges in which a number of mosquito vectors have been observed to co-occur with West Nile virus, dengue virus or chikungunya virus. We then investigated whether the optimal climate for co-occurrence of vector and virus varies between "warmer" and "cooler" adapted vectors for the same virus. We found that different mosquito vectors co-occur with the same virus at different temperatures, despite significant overlap in vector temperature ranges. Specifically, we found that co-occurrence correlates with the optimal climatic conditions for the respective vector; cooler-adapted mosquitoes tend to co-occur with the same virus in cooler conditions than their warmer-adapted counterparts. We conclude that mosquitoes appear to be most able to transmit virus in the mosquitoes' optimal climate range, and hypothesise that this may be due to proportionally over-extended vector longevity, and other increased fitness attributes, within this optimal range. These results suggest that the threat posed by vector-competent mosquito species indigenous to temperate regions may have been underestimated, whilst the threat arising from invasive tropical vectors moving to cooler temperate regions may be overestimated.

Behaviour - The keystone in optimizing free-ranging ungulate production

Science.gov (United States)

Free-ranging animal behaviour is a keystone to optimizing free-ranging domestic animal production. This chapter focuses on several aspects that emanate from foraging including defining terms, concepts and the complexity that underlie managing animals and landscapes. Behaviour is investigated in li...

Optimized controllers for enhancing dynamic performance of PV interface system

Directory of Open Access Journals (Sweden)

Mahmoud A. Attia

2018-05-01

Full Text Available The dynamic performance of PV interface system can be improved by optimizing the gains of the Proportional–Integral (PI controller. In this work, gravitational search algorithm and harmony search algorithm are utilized to optimal tuning of PI controller gains. Performance comparison between the PV system with optimized PI gains utilizing different techniques are carried out. Finally, the dynamic behavior of the system is studied under hypothetical sudden variations in irradiance. The examination of the proposed techniques for optimal tuning of PI gains is conducted using MATLAB/SIMULINK software package. The main contribution of this work is investigating the dynamic performance of PV interfacing system with application of gravitational search algorithm and harmony search algorithm for optimal PI parameters tuning. Keywords: Photovoltaic power systems, Gravitational search algorithm, Harmony search algorithm, Genetic algorithm, Artificial intelligence

The optimal dynamic immunization under a controlled heterogeneous node-based SIRS model

Science.gov (United States)

Yang, Lu-Xing; Draief, Moez; Yang, Xiaofan

2016-05-01

Dynamic immunizations, under which the state of the propagation network of electronic viruses can be changed by adjusting the control measures, are regarded as an alternative to static immunizations. This paper addresses the optimal dynamical immunization under the widely accepted SIRS assumption. First, based on a controlled heterogeneous node-based SIRS model, an optimal control problem capturing the optimal dynamical immunization is formulated. Second, the existence of an optimal dynamical immunization scheme is shown, and the corresponding optimality system is derived. Next, some numerical examples are given to show that an optimal immunization strategy can be worked out by numerically solving the optimality system, from which it is found that the network topology has a complex impact on the optimal immunization strategy. Finally, the difference between a payoff and the minimum payoff is estimated in terms of the deviation of the corresponding immunization strategy from the optimal immunization strategy. The proposed optimal immunization scheme is justified, because it can achieve a low level of infections at a low cost.

Dynamic Planar Range Maxima Queries

DEFF Research Database (Denmark)

Brodal, Gerth Stølting; Tsakalidis, Konstantinos

2011-01-01

We consider the dynamic two-dimensional maxima query problem. Let P be a set of n points in the plane. A point is maximal if it is not dominated by any other point in P. We describe two data structures that support the reporting of the t maximal points that dominate a given query point, and allow...... for insertions and deletions of points in P. In the pointer machine model we present a linear space data structure with O(logn + t) worst case query time and O(logn) worst case update time. This is the first dynamic data structure for the planar maxima dominance query problem that achieves these bounds...... are integers in the range U = {0, …,2 w  − 1 }. We present a linear space data structure that supports 3-sided range maxima queries in O(logn/loglogn+t) worst case time and updates in O(logn/loglogn) worst case time. These are the first sublogarithmic worst case bounds for all operations in the RAM model....

Dynamic Heat Supply Prediction Using Support Vector Regression Optimized by Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

Meiping Wang

2016-01-01

Full Text Available We developed an effective intelligent model to predict the dynamic heat supply of heat source. A hybrid forecasting method was proposed based on support vector regression (SVR model-optimized particle swarm optimization (PSO algorithms. Due to the interaction of meteorological conditions and the heating parameters of heating system, it is extremely difficult to forecast dynamic heat supply. Firstly, the correlations among heat supply and related influencing factors in the heating system were analyzed through the correlation analysis of statistical theory. Then, the SVR model was employed to forecast dynamic heat supply. In the model, the input variables were selected based on the correlation analysis and three crucial parameters, including the penalties factor, gamma of the kernel RBF, and insensitive loss function, were optimized by PSO algorithms. The optimized SVR model was compared with the basic SVR, optimized genetic algorithm-SVR (GA-SVR, and artificial neural network (ANN through six groups of experiment data from two heat sources. The results of the correlation coefficient analysis revealed the relationship between the influencing factors and the forecasted heat supply and determined the input variables. The performance of the PSO-SVR model is superior to those of the other three models. The PSO-SVR method is statistically robust and can be applied to practical heating system.

Pareto optimization in algebraic dynamic programming.

Science.gov (United States)

Saule, Cédric; Giegerich, Robert

2015-01-01

Pareto optimization combines independent objectives by computing the Pareto front of its search space, defined as the set of all solutions for which no other candidate solution scores better under all objectives. This gives, in a precise sense, better information than an artificial amalgamation of different scores into a single objective, but is more costly to compute. Pareto optimization naturally occurs with genetic algorithms, albeit in a heuristic fashion. Non-heuristic Pareto optimization so far has been used only with a few applications in bioinformatics. We study exact Pareto optimization for two objectives in a dynamic programming framework. We define a binary Pareto product operator [Formula: see text] on arbitrary scoring schemes. Independent of a particular algorithm, we prove that for two scoring schemes A and B used in dynamic programming, the scoring scheme [Formula: see text] correctly performs Pareto optimization over the same search space. We study different implementations of the Pareto operator with respect to their asymptotic and empirical efficiency. Without artificial amalgamation of objectives, and with no heuristics involved, Pareto optimization is faster than computing the same number of answers separately for each objective. For RNA structure prediction under the minimum free energy versus the maximum expected accuracy model, we show that the empirical size of the Pareto front remains within reasonable bounds. Pareto optimization lends itself to the comparative investigation of the behavior of two alternative scoring schemes for the same purpose. For the above scoring schemes, we observe that the Pareto front can be seen as a composition of a few macrostates, each consisting of several microstates that differ in the same limited way. We also study the relationship between abstract shape analysis and the Pareto front, and find that they extract information of a different nature from the folding space and can be meaningfully combined.

Regulation of Dynamical Systems to Optimal Solutions of Semidefinite Programs: Algorithms and Applications to AC Optimal Power Flow

Energy Technology Data Exchange (ETDEWEB)

Dall' Anese, Emiliano; Dhople, Sairaj V.; Giannakis, Georgios B.

2015-07-01

This paper considers a collection of networked nonlinear dynamical systems, and addresses the synthesis of feedback controllers that seek optimal operating points corresponding to the solution of pertinent network-wide optimization problems. Particular emphasis is placed on the solution of semidefinite programs (SDPs). The design of the feedback controller is grounded on a dual e-subgradient approach, with the dual iterates utilized to dynamically update the dynamical-system reference signals. Global convergence is guaranteed for diminishing stepsize rules, even when the reference inputs are updated at a faster rate than the dynamical-system settling time. The application of the proposed framework to the control of power-electronic inverters in AC distribution systems is discussed. The objective is to bridge the time-scale separation between real-time inverter control and network-wide optimization. Optimization objectives assume the form of SDP relaxations of prototypical AC optimal power flow problems.

Image dynamic range test and evaluation of Gaofen-2 dual cameras

Science.gov (United States)

Zhang, Zhenhua; Gan, Fuping; Wei, Dandan

2015-12-01

In order to fully understand the dynamic range of Gaofen-2 satellite data and support the data processing, application and next satellites development, in this article, we evaluated the dynamic range by calculating some statistics such as maximum ,minimum, average and stand deviation of four images obtained at the same time by Gaofen-2 dual cameras in Beijing area; then the maximum ,minimum, average and stand deviation of each longitudinal overlap of PMS1,PMS2 were calculated respectively for the evaluation of each camera's dynamic range consistency; and these four statistics of each latitudinal overlap of PMS1,PMS2 were calculated respectively for the evaluation of the dynamic range consistency between PMS1 and PMS2 at last. The results suggest that there is a wide dynamic range of DN value in the image obtained by PMS1 and PMS2 which contains rich information of ground objects; in general, the consistency of dynamic range between the single camera images is in close agreement, but also a little difference, so do the dual cameras. The consistency of dynamic range between the single camera images is better than the dual cameras'.

Optimal Route Searching with Multiple Dynamical Constraints—A Geometric Algebra Approach

Directory of Open Access Journals (Sweden)

Dongshuang Li

2018-05-01

Full Text Available The process of searching for a dynamic constrained optimal path has received increasing attention in traffic planning, evacuation, and personalized or collaborative traffic service. As most existing multiple constrained optimal path (MCOP methods cannot search for a path given various types of constraints that dynamically change during the search, few approaches for dynamic multiple constrained optimal path (DMCOP with type II dynamics are available for practical use. In this study, we develop a method to solve the DMCOP problem with type II dynamics based on the unification of various types of constraints under a geometric algebra (GA framework. In our method, the network topology and three different types of constraints are represented by using algebraic base coding. With a parameterized optimization of the MCOP algorithm based on a greedy search strategy under the generation-refinement paradigm, this algorithm is found to accurately support the discovery of optimal paths as the constraints of numerical values, nodes, and route structure types are dynamically added to the network. The algorithm was tested with simulated cases of optimal tourism route searches in China’s road networks with various combinations of constraints. The case study indicates that our algorithm can not only solve the DMCOP with different types of constraints but also use constraints to speed up the route filtering.

Molecular dynamics simulations of short-range force systems on 1024-node hypercubes

International Nuclear Information System (INIS)

Plimpton, S.J.

1990-01-01

In this paper, two parallel algorithms for classical molecular dynamics are presented. The first assigns each processor to a subset of particles; the second assigns each to a fixed region of 3d space. The algorithms are implemented on 1024-node hypercubes for problems characterized by short-range forces, diffusion (so that each particle's neighbors change in time), and problem size ranging from 250 to 10000 particles. Timings for the algorithms on the 1024-node NCUBE/ten and the newer NCUBE 2 hypercubes are given. The latter is found to be competitive with a CRAY-XMP, running an optimized serial algorithm. For smaller problems the NCUBE 2 and CRAY-XMP are roughly the same; for larger ones the NCUBE 2 is up to twice as fast. Parallel efficiencies of the algorithms and communication parameters for the two hypercubes are also examined

Measurement configuration optimization for dynamic metrology using Stokes polarimetry

Science.gov (United States)

Liu, Jiamin; Zhang, Chuanwei; Zhong, Zhicheng; Gu, Honggang; Chen, Xiuguo; Jiang, Hao; Liu, Shiyuan

2018-05-01

As dynamic loading experiments such as a shock compression test are usually characterized by short duration, unrepeatability and high costs, high temporal resolution and precise accuracy of the measurements is required. Due to high temporal resolution up to a ten-nanosecond-scale, a Stokes polarimeter with six parallel channels has been developed to capture such instantaneous changes in optical properties in this paper. Since the measurement accuracy heavily depends on the configuration of the probing beam incident angle and the polarizer azimuth angle, it is important to select an optimal combination from the numerous options. In this paper, a systematic error propagation-based measurement configuration optimization method corresponding to the Stokes polarimeter was proposed. The maximal Frobenius norm of the combinatorial matrix of the configuration error propagating matrix and the intrinsic error propagating matrix is introduced to assess the measurement accuracy. The optimal configuration for thickness measurement of a SiO2 thin film deposited on a Si substrate has been achieved by minimizing the merit function. Simulation and experimental results show a good agreement between the optimal measurement configuration achieved experimentally using the polarimeter and the theoretical prediction. In particular, the experimental result shows that the relative error in the thickness measurement can be reduced from 6% to 1% by using the optimal polarizer azimuth angle when the incident angle is 45°. Furthermore, the optimal configuration for the dynamic metrology of a nickel foil under quasi-dynamic loading is investigated using the proposed optimization method.

DYNAMIC OPTIMAL BUDGET ALLOCATION FOR INTEGRATED MARKETING CONSIDERING PERSISTENCE

OpenAIRE

SHIZHONG AI; RONG DU; QIYING HU

2010-01-01

Aiming at forming dynamic optimal integrated marketing policies, we build a budget allocation model considering both current effects and sustained ones. The model includes multiple time periods and multiple marketing tools which interact through a common resource pool as well as through delayed cross influences on each other's sales, reflecting the nature of "integrated marketing" and its dynamics. In our study, marginal analysis is used to illuminate the structure of optimal policy. We deriv...

An Optimization Framework for Dynamic, Distributed Real-Time Systems

Science.gov (United States)

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

2003-01-01

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

Nonlinear Dynamic Analysis and Optimization of Closed-Form Planetary Gear System

Directory of Open Access Journals (Sweden)

Qilin Huang

2013-01-01

Full Text Available A nonlinear purely rotational dynamic model of a multistage closed-form planetary gear set formed by two simple planetary stages is proposed in this study. The model includes time-varying mesh stiffness, excitation fluctuation and gear backlash nonlinearities. The nonlinear differential equations of motion are solved numerically using variable step-size Runge-Kutta. In order to obtain function expression of optimization objective, the nonlinear differential equations of motion are solved analytically using harmonic balance method (HBM. Based on the analytical solution of dynamic equations, the optimization mathematical model which aims at minimizing the vibration displacement of the low-speed carrier and the total mass of the gear transmission system is established. The optimization toolbox in MATLAB program is adopted to obtain the optimal solution. A case is studied to demonstrate the effectiveness of the dynamic model and the optimization method. The results show that the dynamic properties of the closed-form planetary gear transmission system have been improved and the total mass of the gear set has been decreased significantly.

Time course of dynamic range adaptation in the auditory nerve

Science.gov (United States)

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

2012-01-01

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

Practical synchronization on complex dynamical networks via optimal pinning control

Science.gov (United States)

Li, Kezan; Sun, Weigang; Small, Michael; Fu, Xinchu

2015-07-01

We consider practical synchronization on complex dynamical networks under linear feedback control designed by optimal control theory. The control goal is to minimize global synchronization error and control strength over a given finite time interval, and synchronization error at terminal time. By utilizing the Pontryagin's minimum principle, and based on a general complex dynamical network, we obtain an optimal system to achieve the control goal. The result is verified by performing some numerical simulations on Star networks, Watts-Strogatz networks, and Barabási-Albert networks. Moreover, by combining optimal control and traditional pinning control, we propose an optimal pinning control strategy which depends on the network's topological structure. Obtained results show that optimal pinning control is very effective for synchronization control in real applications.

Optimal Piecewise-Linear Approximation of the Quadratic Chaotic Dynamics

Directory of Open Access Journals (Sweden)

J. Petrzela

2012-04-01

Full Text Available This paper shows the influence of piecewise-linear approximation on the global dynamics associated with autonomous third-order dynamical systems with the quadratic vector fields. The novel method for optimal nonlinear function approximation preserving the system behavior is proposed and experimentally verified. This approach is based on the calculation of the state attractor metric dimension inside a stochastic optimization routine. The approximated systems are compared to the original by means of the numerical integration. Real electronic circuits representing individual dynamical systems are derived using classical as well as integrator-based synthesis and verified by time-domain analysis in Orcad Pspice simulator. The universality of the proposed method is briefly discussed, especially from the viewpoint of the higher-order dynamical systems. Future topics and perspectives are also provided

Stochastic quasi-gradient based optimization algorithms for dynamic reliability applications

International Nuclear Information System (INIS)

Bourgeois, F.; Labeau, P.E.

2001-01-01

On one hand, PSA results are increasingly used in decision making, system management and optimization of system design. On the other hand, when severe accidental transients are considered, dynamic reliability appears appropriate to account for the complex interaction between the transitions between hardware configurations, the operator behavior and the dynamic evolution of the system. This paper presents an exploratory work in which the estimation of the system unreliability in a dynamic context is coupled with an optimization algorithm to determine the 'best' safety policy. Because some reliability parameters are likely to be distributed, the cost function to be minimized turns out to be a random variable. Stochastic programming techniques are therefore envisioned to determine an optimal strategy. Monte Carlo simulation is used at all stages of the computations, from the estimation of the system unreliability to that of the stochastic quasi-gradient. The optimization algorithm is illustrated on a HNO 3 supply system

The Adjoint Method for Gradient-based Dynamic Optimization of UV Flash Processes

DEFF Research Database (Denmark)

Ritschel, Tobias Kasper Skovborg; Capolei, Andrea; Jørgensen, John Bagterp

2017-01-01

This paper presents a novel single-shooting algorithm for gradient-based solution of optimal control problems with vapor-liquid equilibrium constraints. Dynamic optimization of UV flash processes is relevant in nonlinear model predictive control of distillation columns, certain two-phase flow pro......-component flash process which demonstrate the importance of the optimization solver, the compiler, and the linear algebra software for the efficiency of dynamic optimization of UV flash processes....

Optimal control of HIV/AIDS dynamic: Education and treatment

Science.gov (United States)

Sule, Amiru; Abdullah, Farah Aini

2014-07-01

A mathematical model which describes the transmission dynamics of HIV/AIDS is developed. The optimal control representing education and treatment for this model is explored. The existence of optimal Control is established analytically by the use of optimal control theory. Numerical simulations suggest that education and treatment for the infected has a positive impact on HIV/AIDS control.

Algorithms for optimal sequencing of dynamic multileaf collimators

Energy Technology Data Exchange (ETDEWEB)

Kamath, Srijit [Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL (United States); Sahni, Sartaj [Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL (United States); Palta, Jatinder [Department of Radiation Oncology, University of Florida, Gainesville, FL (United States); Ranka, Sanjay [Department of Computer and Information Science and Engineering, University of Florida, Gainesville, FL (United States)

2004-01-07

Dynamic multileaf collimator (DMLC) intensity modulated radiation therapy (IMRT) is used to deliver intensity modulated beams using a multileaf collimator (MLC), with the leaves in motion. DMLC-IMRT requires the conversion of a radiation intensity map into a leaf sequence file that controls the movement of the MLC while the beam is on. It is imperative that the intensity map delivered using the leaf sequence file be as close as possible to the intensity map generated by the dose optimization algorithm, while satisfying hardware constraints of the delivery system. Optimization of the leaf-sequencing algorithm has been the subject of several recent investigations. In this work, we present a systematic study of the optimization of leaf-sequencing algorithms for dynamic multileaf collimator beam delivery and provide rigorous mathematical proofs of optimized leaf sequence settings in terms of monitor unit (MU) efficiency under the most common leaf movement constraints that include leaf interdigitation constraint. Our analytical analysis shows that leaf sequencing based on unidirectional movement of the MLC leaves is as MU efficient as bi-directional movement of the MLC leaves.

Algorithms for optimal sequencing of dynamic multileaf collimators

International Nuclear Information System (INIS)

Kamath, Srijit; Sahni, Sartaj; Palta, Jatinder; Ranka, Sanjay

2004-01-01

Dynamic multileaf collimator (DMLC) intensity modulated radiation therapy (IMRT) is used to deliver intensity modulated beams using a multileaf collimator (MLC), with the leaves in motion. DMLC-IMRT requires the conversion of a radiation intensity map into a leaf sequence file that controls the movement of the MLC while the beam is on. It is imperative that the intensity map delivered using the leaf sequence file be as close as possible to the intensity map generated by the dose optimization algorithm, while satisfying hardware constraints of the delivery system. Optimization of the leaf-sequencing algorithm has been the subject of several recent investigations. In this work, we present a systematic study of the optimization of leaf-sequencing algorithms for dynamic multileaf collimator beam delivery and provide rigorous mathematical proofs of optimized leaf sequence settings in terms of monitor unit (MU) efficiency under the most common leaf movement constraints that include leaf interdigitation constraint. Our analytical analysis shows that leaf sequencing based on unidirectional movement of the MLC leaves is as MU efficient as bi-directional movement of the MLC leaves

Optimization of fuel-cell tram operation based on two dimension dynamic programming

Science.gov (United States)

Zhang, Wenbin; Lu, Xuecheng; Zhao, Jingsong; Li, Jianqiu

2018-02-01

This paper proposes an optimal control strategy based on the two-dimension dynamic programming (2DDP) algorithm targeting at minimizing operation energy consumption for a fuel-cell tram. The energy consumption model with the tram dynamics is firstly deduced. Optimal control problem are analyzed and the 2DDP strategy is applied to solve the problem. The optimal tram speed profiles are obtained for each interstation which consist of three stages: accelerate to the set speed with the maximum traction power, dynamically adjust to maintain a uniform speed and decelerate to zero speed with the maximum braking power at a suitable timing. The optimal control curves of all the interstations are connected with the parking time to form the optimal control method of the whole line. The optimized speed profiles are also simplified for drivers to follow.

The importance of functional form in optimal control solutions of problems in population dynamics

Science.gov (United States)

Runge, M.C.; Johnson, F.A.

2002-01-01

Optimal control theory is finding increased application in both theoretical and applied ecology, and it is a central element of adaptive resource management. One of the steps in an adaptive management process is to develop alternative models of system dynamics, models that are all reasonable in light of available data, but that differ substantially in their implications for optimal control of the resource. We explored how the form of the recruitment and survival functions in a general population model for ducks affected the patterns in the optimal harvest strategy, using a combination of analytical, numerical, and simulation techniques. We compared three relationships between recruitment and population density (linear, exponential, and hyperbolic) and three relationships between survival during the nonharvest season and population density (constant, logistic, and one related to the compensatory harvest mortality hypothesis). We found that the form of the component functions had a dramatic influence on the optimal harvest strategy and the ultimate equilibrium state of the system. For instance, while it is commonly assumed that a compensatory hypothesis leads to higher optimal harvest rates than an additive hypothesis, we found this to depend on the form of the recruitment function, in part because of differences in the optimal steady-state population density. This work has strong direct consequences for those developing alternative models to describe harvested systems, but it is relevant to a larger class of problems applying optimal control at the population level. Often, different functional forms will not be statistically distinguishable in the range of the data. Nevertheless, differences between the functions outside the range of the data can have an important impact on the optimal harvest strategy. Thus, development of alternative models by identifying a single functional form, then choosing different parameter combinations from extremes on the likelihood

Evaluation of color encodings for high dynamic range pixels

Science.gov (United States)

Boitard, Ronan; Mantiuk, Rafal K.; Pouli, Tania

2015-03-01

Traditional Low Dynamic Range (LDR) color spaces encode a small fraction of the visible color gamut, which does not encompass the range of colors produced on upcoming High Dynamic Range (HDR) displays. Future imaging systems will require encoding much wider color gamut and luminance range. Such wide color gamut can be represented using floating point HDR pixel values but those are inefficient to encode. They also lack perceptual uniformity of the luminance and color distribution, which is provided (in approximation) by most LDR color spaces. Therefore, there is a need to devise an efficient, perceptually uniform and integer valued representation for high dynamic range pixel values. In this paper we evaluate several methods for encoding colour HDR pixel values, in particular for use in image and video compression. Unlike other studies we test both luminance and color difference encoding in a rigorous 4AFC threshold experiments to determine the minimum bit-depth required. Results show that the Perceptual Quantizer (PQ) encoding provides the best perceptual uniformity in the considered luminance range, however the gain in bit-depth is rather modest. More significant difference can be observed between color difference encoding schemes, from which YDuDv encoding seems to be the most efficient.

Structural optimization for nonlinear dynamic response

DEFF Research Database (Denmark)

Dou, Suguang; Strachan, B. Scott; Shaw, Steven W.

2015-01-01

by a single vibrating mode, or by a pair of internally resonant modes. The approach combines techniques from nonlinear dynamics, computational mechanics and optimization, and it allows one to relate the geometric and material properties of structural elements to terms in the normal form for a given resonance......Much is known about the nonlinear resonant response of mechanical systems, but methods for the systematic design of structures that optimize aspects of these responses have received little attention. Progress in this area is particularly important in the area of micro-systems, where nonlinear...... resonant behaviour is being used for a variety of applications in sensing and signal conditioning. In this work, we describe a computational method that provides a systematic means for manipulating and optimizing features of nonlinear resonant responses of mechanical structures that are described...

Direct Optimal Control of Duffing Dynamics

Science.gov (United States)

Oz, Hayrani; Ramsey, John K.

2002-01-01

The "direct control method" is a novel concept that is an attractive alternative and competitor to the differential-equation-based methods. The direct method is equally well applicable to nonlinear, linear, time-varying, and time-invariant systems. For all such systems, the method yields explicit closed-form control laws based on minimization of a quadratic control performance measure. We present an application of the direct method to the dynamics and optimal control of the Duffing system where the control performance measure is not restricted to a quadratic form and hence may include a quartic energy term. The results we present in this report also constitute further generalizations of our earlier work in "direct optimal control methodology." The approach is demonstrated for the optimal control of the Duffing equation with a softening nonlinear stiffness.

Weather and Climate Manipulation as an Optimal Control for Adaptive Dynamical Systems

Directory of Open Access Journals (Sweden)

Sergei A. Soldatenko

2017-01-01

Full Text Available The weather and climate manipulation is examined as an optimal control problem for the earth climate system, which is considered as a complex adaptive dynamical system. Weather and climate manipulations are actually amorphous operations. Since their objectives are usually formulated vaguely, the expected results are fairly unpredictable and uncertain. However, weather and climate modification is a purposeful process and, therefore, we can formulate operations to manipulate weather and climate as the optimization problem within the framework of the optimal control theory. The complexity of the earth’s climate system is discussed and illustrated using the simplified low-order coupled chaotic dynamical system. The necessary conditions of optimality are derived for the large-scale atmospheric dynamics. This confirms that even a relatively simplified control problem for the atmospheric dynamics requires significant efforts to obtain the solution.

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

International Nuclear Information System (INIS)

Wu, Xia; Wu, Genhua

2014-01-01

Highlights: • A high efficient method for optimization of atomic clusters is developed. • Its performance is studied by optimizing Lennard-Jones clusters and Ag clusters. • The method is proved to be quite efficient. • A new Ag 61 cluster with stacking-fault face-centered cubic motif is found. - Abstract: 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 Ag 61 cluster is found to be stacking-fault face-centered cubic, whose energy is lower than that of previously obtained icosahedron

Bridging developmental systems theory and evolutionary psychology using dynamic optimization.

Science.gov (United States)

Frankenhuis, Willem E; Panchanathan, Karthik; Clark Barrett, H

2013-07-01

Interactions between evolutionary psychologists and developmental systems theorists have been largely antagonistic. This is unfortunate because potential synergies between the two approaches remain unexplored. This article presents a method that may help to bridge the divide, and that has proven fruitful in biology: dynamic optimization. Dynamic optimization integrates developmental systems theorists' focus on dynamics and contingency with the 'design stance' of evolutionary psychology. It provides a theoretical framework as well as a set of tools for exploring the properties of developmental systems that natural selection might favor, given particular evolutionary ecologies. We also discuss limitations of the approach. © 2013 Blackwell Publishing Ltd.

Fast engineering optimization: A novel highly effective control parameterization approach for industrial dynamic processes.

Science.gov (United States)

Liu, Ping; Li, Guodong; Liu, Xinggao

2015-09-01

Control vector parameterization (CVP) is an important approach of the engineering optimization for the industrial dynamic processes. However, its major defect, the low optimization efficiency caused by calculating the relevant differential equations in the generated nonlinear programming (NLP) problem repeatedly, limits its wide application in the engineering optimization for the industrial dynamic processes. A novel highly effective control parameterization approach, fast-CVP, is first proposed to improve the optimization efficiency for industrial dynamic processes, where the costate gradient formulae is employed and a fast approximate scheme is presented to solve the differential equations in dynamic process simulation. Three well-known engineering optimization benchmark problems of the industrial dynamic processes are demonstrated as illustration. The research results show that the proposed fast approach achieves a fine performance that at least 90% of the computation time can be saved in contrast to the traditional CVP method, which reveals the effectiveness of the proposed fast engineering optimization approach for the industrial dynamic processes. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Optimal dynamic performance for high-precision actuators/stages

International Nuclear Information System (INIS)

Preissner, C.; Lee, S.-H.; Royston, T. J.; Shu, D.

2002-01-01

System dynamic performance of actuator/stage groups, such as those found in optical instrument positioning systems and other high-precision applications, is dependent upon both individual component behavior and the system configuration. Experimental modal analysis techniques were implemented to determine the six degree of freedom stiffnesses and damping for individual actuator components. These experimental data were then used in a multibody dynamic computer model to investigate the effect of stage group configuration. Running the computer model through the possible stage configurations and observing the predicted vibratory response determined the optimal stage group configuration. Configuration optimization can be performed for any group of stages, provided there is stiffness and damping data available for the constituent pieces

Optimal Strategy for Integrated Dynamic Inventory Control and Supplier Selection in Unknown Environment via Stochastic Dynamic Programming

International Nuclear Information System (INIS)

Sutrisno; Widowati; Solikhin

2016-01-01

In this paper, we propose a mathematical model in stochastic dynamic optimization form to determine the optimal strategy for an integrated single product inventory control problem and supplier selection problem where the demand and purchasing cost parameters are random. For each time period, by using the proposed model, we decide the optimal supplier and calculate the optimal product volume purchased from the optimal supplier so that the inventory level will be located at some point as close as possible to the reference point with minimal cost. We use stochastic dynamic programming to solve this problem and give several numerical experiments to evaluate the model. From the results, for each time period, the proposed model was generated the optimal supplier and the inventory level was tracked the reference point well. (paper)

Long-Range Coulomb Effect in Intense Laser-Driven Photoelectron Dynamics.

Science.gov (United States)

Quan, Wei; Hao, XiaoLei; Chen, YongJu; Yu, ShaoGang; Xu, SongPo; Wang, YanLan; Sun, RenPing; Lai, XuanYang; Wu, ChengYin; Gong, QiHuang; He, XianTu; Liu, XiaoJun; Chen, Jing

2016-06-03

In strong field atomic physics community, long-range Coulomb interaction has for a long time been overlooked and its significant role in intense laser-driven photoelectron dynamics eluded experimental observations. Here we report an experimental investigation of the effect of long-range Coulomb potential on the dynamics of near-zero-momentum photoelectrons produced in photo-ionization process of noble gas atoms in intense midinfrared laser pulses. By exploring the dependence of photoelectron distributions near zero momentum on laser intensity and wavelength, we unambiguously demonstrate that the long-range tail of the Coulomb potential (i.e., up to several hundreds atomic units) plays an important role in determining the photoelectron dynamics after the pulse ends.

Large portfolio risk management and optimal portfolio allocation with dynamic elliptical copulas

Directory of Open Access Journals (Sweden)

Jin Xisong

2018-02-01

Full Text Available Previous research has focused on the importance of modeling the multivariate distribution for optimal portfolio allocation and active risk management. However, existing dynamic models are not easily applied to high-dimensional problems due to the curse of dimensionality. In this paper, we extend the framework of the Dynamic Conditional Correlation/Equicorrelation and an extreme value approach into a series of Dynamic Conditional Elliptical Copulas. We investigate risk measures such as Value at Risk (VaR and Expected Shortfall (ES for passive portfolios and dynamic optimal portfolios using Mean-Variance and ES criteria for a sample of US stocks over a period of 10 years. Our results suggest that (1 Modeling the marginal distribution is important for dynamic high-dimensional multivariate models. (2 Neglecting the dynamic dependence in the copula causes over-aggressive risk management. (3 The DCC/DECO Gaussian copula and t-copula work very well for both VaR and ES. (4 Grouped t-copulas and t-copulas with dynamic degrees of freedom further match the fat tail. (5 Correctly modeling the dependence structure makes an improvement in portfolio optimization with respect to tail risk. (6 Models driven by multivariate t innovations with exogenously given degrees of freedom provide a flexible and applicable alternative for optimal portfolio risk management.

An Optimized Control for LLC Resonant Converter with Wide Load Range

Science.gov (United States)

Xi, Xia; Qian, Qinsong

2017-05-01

This paper presents an optimized control which makes LLC resonant converters operate with a wider load range and provides good closed-loop performance. The proposed control employs two paralleled digital compensations to guarantee the good closed-loop performance in a wide load range during the steady state, an optimized trajectory control will take over to change the gate-driving signals immediately at the load transients. Finally, the proposed control has been implemented and tested on a 150W 200kHz 400V/24V LLC resonant converter and the result validates the proposed method.

Sub-optimal control of fuzzy linear dynamical systems under granular differentiability concept.

Science.gov (United States)

Mazandarani, Mehran; Pariz, Naser

2018-05-01

This paper deals with sub-optimal control of a fuzzy linear dynamical system. The aim is to keep the state variables of the fuzzy linear dynamical system close to zero in an optimal manner. In the fuzzy dynamical system, the fuzzy derivative is considered as the granular derivative; and all the coefficients and initial conditions can be uncertain. The criterion for assessing the optimality is regarded as a granular integral whose integrand is a quadratic function of the state variables and control inputs. Using the relative-distance-measure (RDM) fuzzy interval arithmetic and calculus of variations, the optimal control law is presented as the fuzzy state variables feedback. Since the optimal feedback gains are obtained as fuzzy functions, they need to be defuzzified. This will result in the sub-optimal control law. This paper also sheds light on the restrictions imposed by the approaches which are based on fuzzy standard interval arithmetic (FSIA), and use strongly generalized Hukuhara and generalized Hukuhara differentiability concepts for obtaining the optimal control law. The granular eigenvalues notion is also defined. Using an RLC circuit mathematical model, it is shown that, due to their unnatural behavior in the modeling phenomenon, the FSIA-based approaches may obtain some eigenvalues sets that might be different from the inherent eigenvalues set of the fuzzy dynamical system. This is, however, not the case with the approach proposed in this study. The notions of granular controllability and granular stabilizability of the fuzzy linear dynamical system are also presented in this paper. Moreover, a sub-optimal control for regulating a Boeing 747 in longitudinal direction with uncertain initial conditions and parameters is gained. In addition, an uncertain suspension system of one of the four wheels of a bus is regulated using the sub-optimal control introduced in this paper. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Topology optimization of continuum structure with dynamic constraints using mode identification

International Nuclear Information System (INIS)

Li, Jianhongyu; Chen, Shenyan; Huang, Hai

2015-01-01

For the problems such as mode exchange and localized modes in topology optimization of continuum structure with dynamic constraints, it is difficult to apply the traditional optimization model which considers fixed order mode frequencies as constraints in optimization calculation. A new optimization model is established, in which the dynamical constraints are changed as frequencies of structural principal vibrations. The order of the principal vibrations is recognized through modal identification in the optimization process, and the constraints are updated to make the optimization calculation execute smoothly. Localized mode elimination techniques are introduced to reduce the localized modes induced by the low density elements, which could improve the optimization efficiency. A new optimization process is designed, which achieves the purpose of overcoming mode exchange problem and localized mode problem at the cost of increasing several structural analyses. Optimization system is developed by using Nastran to perform structural analysis and sensitivity analysis and two-level multipoint approximation algorithm as optimizer. Numerical results verified that the presented method is effective and reasonable.

High-dynamic-range imaging for cloud segmentation

Science.gov (United States)

Dev, Soumyabrata; Savoy, Florian M.; Lee, Yee Hui; Winkler, Stefan

2018-04-01

Sky-cloud images obtained from ground-based sky cameras are usually captured using a fisheye lens with a wide field of view. However, the sky exhibits a large dynamic range in terms of luminance, more than a conventional camera can capture. It is thus difficult to capture the details of an entire scene with a regular camera in a single shot. In most cases, the circumsolar region is overexposed, and the regions near the horizon are underexposed. This renders cloud segmentation for such images difficult. In this paper, we propose HDRCloudSeg - an effective method for cloud segmentation using high-dynamic-range (HDR) imaging based on multi-exposure fusion. We describe the HDR image generation process and release a new database to the community for benchmarking. Our proposed approach is the first using HDR radiance maps for cloud segmentation and achieves very good results.

Optimization of Algorithms Using Extensions of Dynamic Programming

KAUST Repository

AbouEisha, Hassan M.

2017-04-09

We study and answer questions related to the complexity of various important problems such as: multi-frontal solvers of hp-adaptive finite element method, sorting and majority. We advocate the use of dynamic programming as a viable tool to study optimal algorithms for these problems. The main approach used to attack these problems is modeling classes of algorithms that may solve this problem using a discrete model of computation then defining cost functions on this discrete structure that reflect different complexity measures of the represented algorithms. As a last step, dynamic programming algorithms are designed and used to optimize those models (algorithms) and to obtain exact results on the complexity of the studied problems. The first part of the thesis presents a novel model of computation (element partition tree) that represents a class of algorithms for multi-frontal solvers along with cost functions reflecting various complexity measures such as: time and space. It then introduces dynamic programming algorithms for multi-stage and bi-criteria optimization of element partition trees. In addition, it presents results based on optimal element partition trees for famous benchmark meshes such as: meshes with point and edge singularities. New improved heuristics for those benchmark meshes were ob- tained based on insights of the optimal results found by our algorithms. The second part of the thesis starts by introducing a general problem where different problems can be reduced to and show how to use a decision table to model such problem. We describe how decision trees and decision tests for this table correspond to adaptive and non-adaptive algorithms for the original problem. We present exact bounds on the average time complexity of adaptive algorithms for the eight elements sorting problem. Then bounds on adaptive and non-adaptive algorithms for a variant of the majority problem are introduced. Adaptive algorithms are modeled as decision trees whose depth

Optimal reduction of flexible dynamic system

International Nuclear Information System (INIS)

Jankovic, J.

1994-01-01

Dynamic system reduction is basic procedure in various problems of active control synthesis of flexible structures. In this paper is presented direct method for system reduction by explicit extraction of modes included in reduced model form. Criterion for optimal system discrete approximation in synthesis reduced dynamic model is also presented. Subjected method of system decomposition is discussed in relation to the Schur method of solving matrix algebraic Riccati equation as condition for system reduction. By using exposed method procedure of flexible system reduction in addition with corresponding example is presented. Shown procedure is powerful in problems of active control synthesis of flexible system vibrations

Research on the optimal dynamical systems of three-dimensional Navier-Stokes equations based on weighted residual

Science.gov (United States)

Peng, NaiFu; Guan, Hui; Wu, ChuiJie

2016-04-01

In this paper, the theory of constructing optimal dynamical systems based on weighted residual presented by Wu & Sha is applied to three-dimensional Navier-Stokes equations, and the optimal dynamical system modeling equations are derived. Then the multiscale global optimization method based on coarse graining analysis is presented, by which a set of approximate global optimal bases is directly obtained from Navier-Stokes equations and the construction of optimal dynamical systems is realized. The optimal bases show good properties, such as showing the physical properties of complex flows and the turbulent vortex structures, being intrinsic to real physical problem and dynamical systems, and having scaling symmetry in mathematics, etc.. In conclusion, using fewer terms of optimal bases will approach the exact solutions of Navier-Stokes equations, and the dynamical systems based on them show the most optimal behavior.

A dynamic global and local combined particle swarm optimization algorithm

International Nuclear Information System (INIS)

Jiao Bin; Lian Zhigang; Chen Qunxian

2009-01-01

Particle swarm optimization (PSO) algorithm has been developing rapidly and many results have been reported. PSO algorithm has shown some important advantages by providing high speed of convergence in specific problems, but it has a tendency to get stuck in a near optimal solution and one may find it difficult to improve solution accuracy by fine tuning. This paper presents a dynamic global and local combined particle swarm optimization (DGLCPSO) algorithm to improve the performance of original PSO, in which all particles dynamically share the best information of the local particle, global particle and group particles. It is tested with a set of eight benchmark functions with different dimensions and compared with original PSO. Experimental results indicate that the DGLCPSO algorithm improves the search performance on the benchmark functions significantly, and shows the effectiveness of the algorithm to solve optimization problems.

Multi-objective optimization to improve the product range of baking systems

NARCIS (Netherlands)

Hadiyanto, M.; Boom, R.M.; Straten, van G.; Boxtel, van A.J.B.; Esveld, D.C.

2009-01-01

The operational range of a food production system can be used to obtain a variation in certain product characteristics. The range of product characteristics that can be simultaneously realized by an optimal choice of the process conditions is inherently limited. Knowledge of this feasible product

Off-road vehicle dynamics analysis, modelling and optimization

CERN Document Server

Taghavifar, Hamid

2017-01-01

This book deals with the analysis of off-road vehicle dynamics from kinetics and kinematics perspectives and the performance of vehicle traversing over rough and irregular terrain. The authors consider the wheel performance, soil-tire interactions and their interface, tractive performance of the vehicle, ride comfort, stability over maneuvering, transient and steady state conditions of the vehicle traversing, modeling the aforementioned aspects and optimization from energetic and vehicle mobility perspectives. This book brings novel figures for the transient dynamics and original wheel terrain dynamics at on-the-go condition.

Optimal control landscape for the generation of unitary transformations with constrained dynamics

International Nuclear Information System (INIS)

Hsieh, Michael; Wu, Rebing; Rabitz, Herschel; Lidar, Daniel

2010-01-01

The reliable and precise generation of quantum unitary transformations is essential for the realization of a number of fundamental objectives, such as quantum control and quantum information processing. Prior work has explored the optimal control problem of generating such unitary transformations as a surface-optimization problem over the quantum control landscape, defined as a metric for realizing a desired unitary transformation as a function of the control variables. It was found that under the assumption of nondissipative and controllable dynamics, the landscape topology is trap free, which implies that any reasonable optimization heuristic should be able to identify globally optimal solutions. The present work is a control landscape analysis, which incorporates specific constraints in the Hamiltonian that correspond to certain dynamical symmetries in the underlying physical system. It is found that the presence of such symmetries does not destroy the trap-free topology. These findings expand the class of quantum dynamical systems on which control problems are intrinsically amenable to a solution by optimal control.

Entanglement Growth in Quench Dynamics with Variable Range Interactions

Directory of Open Access Journals (Sweden)

J. Schachenmayer

2013-09-01

Full Text Available Studying entanglement growth in quantum dynamics provides both insight into the underlying microscopic processes and information about the complexity of the quantum states, which is related to the efficiency of simulations on classical computers. Recently, experiments with trapped ions, polar molecules, and Rydberg excitations have provided new opportunities to observe dynamics with long-range interactions. We explore nonequilibrium coherent dynamics after a quantum quench in such systems, identifying qualitatively different behavior as the exponent of algebraically decaying spin-spin interactions in a transverse Ising chain is varied. Computing the buildup of bipartite entanglement as well as mutual information between distant spins, we identify linear growth of entanglement entropy corresponding to propagation of quasiparticles for shorter-range interactions, with the maximum rate of growth occurring when the Hamiltonian parameters match those for the quantum phase transition. Counterintuitively, the growth of bipartite entanglement for long-range interactions is only logarithmic for most regimes, i.e., substantially slower than for shorter-range interactions. Experiments with trapped ions allow for the realization of this system with a tunable interaction range, and we show that the different phenomena are robust for finite system sizes and in the presence of noise. These results can act as a direct guide for the generation of large-scale entanglement in such experiments, towards a regime where the entanglement growth can render existing classical simulations inefficient.

A high dynamic range pulse counting detection system for mass spectrometry.

Science.gov (United States)

Collings, Bruce A; Dima, Martian D; Ivosev, Gordana; Zhong, Feng

2014-01-30

A high dynamic range pulse counting system has been developed that demonstrates an ability to operate at up to 2e8 counts per second (cps) on a triple quadrupole mass spectrometer. Previous pulse counting detection systems have typically been limited to about 1e7 cps at the upper end of the systems dynamic range. Modifications to the detection electronics and dead time correction algorithm are described in this paper. A high gain transimpedance amplifier is employed that allows a multi-channel electron multiplier to be operated at a significantly lower bias potential than in previous pulse counting systems. The system utilises a high-energy conversion dynode, a multi-channel electron multiplier, a high gain transimpedance amplifier, non-paralysing detection electronics and a modified dead time correction algorithm. Modification of the dead time correction algorithm is necessary due to a characteristic of the pulse counting electronics. A pulse counting detection system with the capability to count at ion arrival rates of up to 2e8 cps is described. This is shown to provide a linear dynamic range of nearly five orders of magnitude for a sample of aprazolam with concentrations ranging from 0.0006970 ng/mL to 3333 ng/mL while monitoring the m/z 309.1 → m/z 205.2 transition. This represents an upward extension of the detector's linear dynamic range of about two orders of magnitude. A new high dynamic range pulse counting system has been developed demonstrating the ability to operate at up to 2e8 cps on a triple quadrupole mass spectrometer. This provides an upward extension of the detector's linear dynamic range by about two orders of magnitude over previous pulse counting systems. Copyright © 2013 John Wiley & Sons, Ltd.

Mitochondrial uncouplers with an extraordinary dynamic range.

Science.gov (United States)

Lou, Phing-How; Hansen, Birgit S; Olsen, Preben H; Tullin, Søren; Murphy, Michael P; Brand, Martin D

2007-10-01

We have discovered that some weak uncouplers (typified by butylated hydroxytoluene) have a dynamic range of more than 10(6) in vitro: the concentration giving measurable uncoupling is less than one millionth of the concentration causing full uncoupling. They achieve this through a high-affinity interaction with the mitochondrial adenine nucleotide translocase that causes significant but limited uncoupling at extremely low uncoupler concentrations, together with more conventional uncoupling at much higher concentrations. Uncoupling at the translocase is not by a conventional weak acid/anion cycling mechanism since it is also caused by substituted triphenylphosphonium molecules, which are not anionic and cannot protonate. Covalent attachment of the uncoupler to a mitochondrially targeted hydrophobic cation sensitizes it to membrane potential, giving a small additional effect. The wide dynamic range of these uncouplers in isolated mitochondria and intact cells reveals a novel allosteric activation of proton transport through the adenine nucleotide translocase and provides a promising starting point for designing safer uncouplers for obesity therapy.

Aerodynamic shape optimization for alleviating dynamic stall characteristics of helicopter rotor airfoil

Directory of Open Access Journals (Sweden)

Wang Qing

2015-04-01

Full Text Available In order to alleviate the dynamic stall effects in helicopter rotor, the sequential quadratic programming (SQP method is employed to optimize the characteristics of airfoil under dynamic stall conditions based on the SC1095 airfoil. The geometry of airfoil is parameterized by the class-shape-transformation (CST method, and the C-topology body-fitted mesh is then automatically generated around the airfoil by solving the Poisson equations. Based on the grid generation technology, the unsteady Reynolds-averaged Navier-Stokes (RANS equations are chosen as the governing equations for predicting airfoil flow field and the highly-efficient implicit scheme of lower–upper symmetric Gauss–Seidel (LU-SGS is adopted for temporal discretization. To capture the dynamic stall phenomenon of the rotor more accurately, the Spalart–Allmaras turbulence model is employed to close the RANS equations. The optimized airfoil with a larger leading edge radius and camber is obtained. The leading edge vortex and trailing edge separation of the optimized airfoil under unsteady conditions are obviously weakened, and the dynamic stall characteristics of optimized airfoil at different Mach numbers, reduced frequencies and angles of attack are also obviously improved compared with the baseline SC1095 airfoil. It is demonstrated that the optimized method is effective and the optimized airfoil is suitable as the helicopter rotor airfoil.

Optimal Frequency Ranges for Sub-Microsecond Precision Pulsar Timing

Science.gov (United States)

Lam, Michael Timothy; McLaughlin, Maura; Cordes, James; Chatterjee, Shami; Lazio, Joseph

2018-01-01

Precision pulsar timing requires optimization against measurement errors and astrophysical variance from the neutron stars themselves and the interstellar medium. We investigate optimization of arrival time precision as a function of radio frequency and bandwidth. We find that increases in bandwidth that reduce the contribution from receiver noise are countered by the strong chromatic dependence of interstellar effects and intrinsic pulse-profile evolution. The resulting optimal frequency range is therefore telescope and pulsar dependent. We demonstrate the results for five pulsars included in current pulsar timing arrays and determine that they are not optimally observed at current center frequencies. We also find that arrival-time precision can be improved by increases in total bandwidth. Wideband receivers centered at high frequencies can reduce required overall integration times and provide significant improvements in arrival time uncertainty by a factor of $\\sim$$\\sqrt{2}$ in most cases, assuming a fixed integration time. We also discuss how timing programs can be extended to pulsars with larger dispersion measures through the use of higher-frequency observations.

A design of an on-orbit radiometric calibration device for high dynamic range infrared remote sensors

Science.gov (United States)

Sheng, Yicheng; Jin, Weiqi; Dun, Xiong; Zhou, Feng; Xiao, Si

2017-10-01

With the demand of quantitative remote sensing technology growing, high reliability as well as high accuracy radiometric calibration technology, especially the on-orbit radiometric calibration device has become an essential orientation in term of quantitative remote sensing technology. In recent years, global launches of remote sensing satellites are equipped with innovative on-orbit radiometric calibration devices. In order to meet the requirements of covering a very wide dynamic range and no-shielding radiometric calibration system, we designed a projection-type radiometric calibration device for high dynamic range sensors based on the Schmidt telescope system. In this internal radiometric calibration device, we select the EF-8530 light source as the calibration blackbody. EF-8530 is a high emittance Nichrome (Ni-Cr) reference source. It can operate in steady or pulsed state mode at a peak temperature of 973K. The irradiance from the source was projected to the IRFPA. The irradiance needs to ensure that the IRFPA can obtain different amplitude of the uniform irradiance through the narrow IR passbands and cover the very wide dynamic range. Combining the internal on-orbit radiometric calibration device with the specially designed adaptive radiometric calibration algorithms, an on-orbit dynamic non-uniformity correction can be accomplished without blocking the optical beam from outside the telescope. The design optimizes optics, source design, and power supply electronics for irradiance accuracy and uniformity. The internal on-orbit radiometric calibration device not only satisfies a series of indexes such as stability, accuracy, large dynamic range and uniformity of irradiance, but also has the advantages of short heating and cooling time, small volume, lightweight, low power consumption and many other features. It can realize the fast and efficient relative radiometric calibration without shielding the field of view. The device can applied to the design and

Study of optimal exposure windows using 320-Detector rows dynamic volume CT

Directory of Open Access Journals (Sweden)

Gang Sun

2010-12-01

Full Text Available Gang Sun1, Min Li1, Li Li1, Guo-ying Li1, Zhi-wei Jing21Departments of Medical Imaging, 2Medical Statistics, Jinan Military General Hospital, Shandong Province, ChinaAbstract: The purpose of this study was to determine the optimal electrocardiographic (ECG pulsing windows and evaluate the effect on reduced dose and accuracy using 320-detector rows dynamic volume computed tomography (DVCT. A total of 170 patients were prospectively studied. The optimal reconstruction windows were analyzed in 76 patients scanned using retrospective ECG gating. Forty-seven patients were scanned by the predicted triggering windows. The optimal positions of exposure intervals according to different heart rates were evaluated. Optimal image quality, radiation dose, and diagnostic accuracy were then investigated by applying optimal triggering windows. The optimal ECG pulsing windows were determined as follows: when heart rate was <70 beats per minute, the exposure windows should be preset at 60%–80%; for a heart rate 70–90 beats per minute at 70%–90%; and for a heart rate ≥90 beats per minute at 30%–50%. The radiation dose for patients scanned with prospective ECG gating was significantly lower (5.9 versus 12.9 mSv, P < 0.001. However, because two or three heart beats were needed when heart rate was >70 beats per minute, the radiation dose increased with increasing heart rate for both retrospective and prospective ECG gating (r = 0.64, P < 0.001 and r = 0.59, P < 0.001, respectively. On the basis of a per segment analysis, overall sensitivity was 98.0% (49/50, specificity was 99.2% (602/607, the positive predictive value was 90.7% (49/54, and the negative predictive value was 99.8% (602/603. In conclusion, DVCT has the potential to provide high image quality across a wide range of heart rates using an optimized ECG pulsing window. However, it is recommended to control heart rate below 70 beats per minute, if possible, to decrease the radiation dose

Valence electronic structure of cobalt phthalocyanine from an optimally tuned range-separated hybrid functional.

Science.gov (United States)

Brumboiu, Iulia Emilia; Prokopiou, Georgia; Kronik, Leeor; Brena, Barbara

2017-07-28

We analyse the valence electronic structure of cobalt phthalocyanine (CoPc) by means of optimally tuning a range-separated hybrid functional. The tuning is performed by modifying both the amount of short-range exact exchange (α) included in the hybrid functional and the range-separation parameter (γ), with two strategies employed for finding the optimal γ for each α. The influence of these two parameters on the structural, electronic, and magnetic properties of CoPc is thoroughly investigated. The electronic structure is found to be very sensitive to the amount and range in which the exact exchange is included. The electronic structure obtained using the optimal parameters is compared to gas-phase photo-electron data and GW calculations, with the unoccupied states additionally compared with inverse photo-electron spectroscopy measurements. The calculated spectrum with tuned γ, determined for the optimal value of α = 0.1, yields a very good agreement with both experimental results and with GW calculations that well-reproduce the experimental data.

Dynamic ADMM for Real-time Optimal Power Flow: Preprint

Energy Technology Data Exchange (ETDEWEB)

Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2018-02-23

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

High dynamic range imaging sensors and architectures

CERN Document Server

Darmont, Arnaud

2013-01-01

Illumination is a crucial element in many applications, matching the luminance of the scene with the operational range of a camera. When luminance cannot be adequately controlled, a high dynamic range (HDR) imaging system may be necessary. These systems are being increasingly used in automotive on-board systems, road traffic monitoring, and other industrial, security, and military applications. This book provides readers with an intermediate discussion of HDR image sensors and techniques for industrial and non-industrial applications. It describes various sensor and pixel architectures capable

Benefits of incorporating the adaptive dynamic range optimization amplification scheme into an assistive listening device for people with mild or moderate hearing loss.

Science.gov (United States)

Chang, Hung-Yue; Luo, Ching-Hsing; Lo, Tun-Shin; Chen, Hsiao-Chuan; Huang, Kuo-You; Liao, Wen-Huei; Su, Mao-Chang; Liu, Shu-Yu; Wang, Nan-Mai

2017-08-28

This study investigated whether a self-designed assistive listening device (ALD) that incorporates an adaptive dynamic range optimization (ADRO) amplification strategy can surpass a commercially available monaurally worn linear ALD, SM100. Both subjective and objective measurements were implemented. Mandarin Hearing-In-Noise Test (MHINT) scores were the objective measurement, whereas participant satisfaction was the subjective measurement. The comparison was performed in a mixed design (i.e., subjects' hearing status being mild or moderate, quiet versus noisy, and linear versus ADRO scheme). The participants were two groups of hearing-impaired subjects, nine mild and eight moderate, respectively. The results of the ADRO system revealed a significant difference in the MHINT sentence reception threshold (SRT) in noisy environments between monaurally aided and unaided conditions, whereas the linear system did not. The benchmark results showed that the ADRO scheme is effectively beneficial to people who experience mild or moderate hearing loss in noisy environments. The satisfaction rating regarding overall speech quality indicated that the participants were satisfied with the speech quality of both ADRO and linear schemes in quiet environments, and they were more satisfied with ADRO than they with the linear scheme in noisy environments.

Optimization algorithm based on densification and dynamic canonical descent

Science.gov (United States)

Bousson, K.; Correia, S. D.

2006-07-01

Stochastic methods have gained some popularity in global optimization in that most of them do not assume the cost functions to be differentiable. They have capabilities to avoid being trapped by local optima, and may converge even faster than gradient-based optimization methods on some problems. The present paper proposes an optimization method, which reduces the search space by means of densification curves, coupled with the dynamic canonical descent algorithm. The performances of the new method are shown on several known problems classically used for testing optimization algorithms, and proved to outperform competitive algorithms such as simulated annealing and genetic algorithms.

High speed, wide dynamic range analog signal processing for avalanche photodiode

CERN Document Server

Walder, J P; Pangaud, P

2000-01-01

A wide dynamic range multi-gain analog transimpedance amplifier integrated circuit has been developed for avalanche photodiode signal processing. The 96 dB input dynamic range is divided into four ranges of 12-bits each in order to provide 40 MHz analog sampled data to a 12-bits ADC. This concept which has been integrated in both BiCMOS and full complementary bipolar technology along with fitted design techniques will be presented.

High speed, wide dynamic range analog signal processing for avalanche photodiode

International Nuclear Information System (INIS)

Walder, J.P.; El Mamouni, Houmani; Pangaud, Patrick

2000-01-01

A wide dynamic range multi-gain analog transimpedance amplifier integrated circuit has been developed for avalanche photodiode signal processing. The 96 dB input dynamic range is divided into four ranges of 12-bits each in order to provide 40 MHz analog sampled data to a 12-bits ADC. This concept which has been integrated in both BiCMOS and full complementary bipolar technology along with fitted design techniques will be presented

High speed, wide dynamic range analog signal processing for avalanche photodiode

Energy Technology Data Exchange (ETDEWEB)

Walder, J.P. E-mail: walder@in2p3.fr; El Mamouni, Houmani; Pangaud, Patrick

2000-03-11

A wide dynamic range multi-gain analog transimpedance amplifier integrated circuit has been developed for avalanche photodiode signal processing. The 96 dB input dynamic range is divided into four ranges of 12-bits each in order to provide 40 MHz analog sampled data to a 12-bits ADC. This concept which has been integrated in both BiCMOS and full complementary bipolar technology along with fitted design techniques will be presented.

Optimal Fuzzy and Dynamics Design of Ecological Sandwich Panel Vessel Roofs

Directory of Open Access Journals (Sweden)

Heikki Martikka

2011-01-01

Full Text Available In this study the basic engineering principles, goals, and constraints are all combined with fuzzy methodology and applied to optimally design sandwich panel circular plate roofs for large vessels loaded statically and dynamically. These panels are made up of two stiff, strong veneer skins separated by vertical and peripheral stiffener plates. Advantages are high strength, lightweight, and sustainability. In the present approach, first the goals and constraints of the end user are identified and expressed as decision variables which are formulated using the engineering variables for materials, geometry, and function. Then same consistent fuzzy satisfaction functions are formed over the desired ranges to suit the customer's desires. The risk of extreme dynamic loadings exciting resonance is studied by natural frequency and mode analysis by FEM and analytical models. The results show the most critical locations and give guidelines for innovative remedies of the concept before detailed FEM analyses to finalize the design.

Dynamic Programming Approach for Exact Decision Rule Optimization

KAUST Repository

Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

2013-01-01

This chapter is devoted to the study of an extension of dynamic programming approach that allows sequential optimization of exact decision rules relative to the length and coverage. It contains also results of experiments with decision tables from

Energy-Aware Routing Optimization in Dynamic GMPLS Controlled Optical Networks

DEFF Research Database (Denmark)

Wang, Jiayuan; Ricciardi, Sergio; Fagertun, Anna Manolova

2012-01-01

In this paper, routing optimizations based on energy sources are proposed in dynamic GMPLS controlled optical networks. The influences of re-routing and load balancing factors on the algorithm are evaluated, with a focus on different re-routing thresholds. Results from dynamic network simulations...

Regulation of Cortical Dynamic Range by Background Synaptic Noise and Feedforward Inhibition.

Science.gov (United States)

Khubieh, Ayah; Ratté, Stéphanie; Lankarany, Milad; Prescott, Steven A

2016-08-01

The cortex encodes a broad range of inputs. This breadth of operation requires sensitivity to weak inputs yet non-saturating responses to strong inputs. If individual pyramidal neurons were to have a narrow dynamic range, as previously claimed, then staggered all-or-none recruitment of those neurons would be necessary for the population to achieve a broad dynamic range. Contrary to this explanation, we show here through dynamic clamp experiments in vitro and computer simulations that pyramidal neurons have a broad dynamic range under the noisy conditions that exist in the intact brain due to background synaptic input. Feedforward inhibition capitalizes on those noise effects to control neuronal gain and thereby regulates the population dynamic range. Importantly, noise allows neurons to be recruited gradually and occludes the staggered recruitment previously attributed to heterogeneous excitation. Feedforward inhibition protects spike timing against the disruptive effects of noise, meaning noise can enable the gain control required for rate coding without compromising the precise spike timing required for temporal coding. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A Thermodynamic Library for Simulation and Optimization of Dynamic Processes

DEFF Research Database (Denmark)

Ritschel, Tobias Kasper Skovborg; Gaspar, Jozsef; Jørgensen, John Bagterp

2017-01-01

Process system tools, such as simulation and optimization of dynamic systems, are widely used in the process industries for development of operational strategies and control for process systems. These tools rely on thermodynamic models and many thermodynamic models have been developed for different...... compounds and mixtures. However, rigorous thermodynamic models are generally computationally intensive and not available as open-source libraries for process simulation and optimization. In this paper, we describe the application of a novel open-source rigorous thermodynamic library, ThermoLib, which...... is designed for dynamic simulation and optimization of vapor-liquid processes. ThermoLib is implemented in Matlab and C and uses cubic equations of state to compute vapor and liquid phase thermodynamic properties. The novelty of ThermoLib is that it provides analytical first and second order derivatives...

Optimization of multi-response dynamic systems integrating multiple ...

African Journals Online (AJOL)

It also results in better optimization performance than back-propagation neural network-based approach and data mining-based approach reported by the past researchers. Keywords: multiple responses, multiple regression, weighted dynamic signal-to-noise ratio, performance measure modelling, response function ...

Optimal foraging and predator-prey dynamics III

Czech Academy of Sciences Publication Activity Database

Křivan, Vlastimil; Eisner, Jan

2003-01-01

Roč. 63, - (2003), s. 269-279 ISSN 0040-5809 R&D Projects: GA ČR GA201/03/0091; GA MŠk LA 101 Institutional research plan: CEZ:AV0Z5007907 Keywords : Optimal foraging theory * adaptive behavior * predator-prec population dynamics Subject RIV: EH - Ecology, Behaviour Impact factor: 2.261, year: 2003

Confronting dynamics and uncertainty in optimal decision making for conservation

Science.gov (United States)

Williams, Byron K.; Johnson, Fred A.

2013-06-01

The effectiveness of conservation efforts ultimately depends on the recognition that decision making, and the systems that it is designed to affect, are inherently dynamic and characterized by multiple sources of uncertainty. To cope with these challenges, conservation planners are increasingly turning to the tools of decision analysis, especially dynamic optimization methods. Here we provide a general framework for optimal, dynamic conservation and then explore its capacity for coping with various sources and degrees of uncertainty. In broadest terms, the dynamic optimization problem in conservation is choosing among a set of decision options at periodic intervals so as to maximize some conservation objective over the planning horizon. Planners must account for immediate objective returns, as well as the effect of current decisions on future resource conditions and, thus, on future decisions. Undermining the effectiveness of such a planning process are uncertainties concerning extant resource conditions (partial observability), the immediate consequences of decision choices (partial controllability), the outcomes of uncontrolled, environmental drivers (environmental variation), and the processes structuring resource dynamics (structural uncertainty). Where outcomes from these sources of uncertainty can be described in terms of probability distributions, a focus on maximizing the expected objective return, while taking state-specific actions, is an effective mechanism for coping with uncertainty. When such probability distributions are unavailable or deemed unreliable, a focus on maximizing robustness is likely to be the preferred approach. Here the idea is to choose an action (or state-dependent policy) that achieves at least some minimum level of performance regardless of the (uncertain) outcomes. We provide some examples of how the dynamic optimization problem can be framed for problems involving management of habitat for an imperiled species, conservation of a

Confronting dynamics and uncertainty in optimal decision making for conservation

Science.gov (United States)

Williams, Byron K.; Johnson, Fred A.

2013-01-01

The effectiveness of conservation efforts ultimately depends on the recognition that decision making, and the systems that it is designed to affect, are inherently dynamic and characterized by multiple sources of uncertainty. To cope with these challenges, conservation planners are increasingly turning to the tools of decision analysis, especially dynamic optimization methods. Here we provide a general framework for optimal, dynamic conservation and then explore its capacity for coping with various sources and degrees of uncertainty. In broadest terms, the dynamic optimization problem in conservation is choosing among a set of decision options at periodic intervals so as to maximize some conservation objective over the planning horizon. Planners must account for immediate objective returns, as well as the effect of current decisions on future resource conditions and, thus, on future decisions. Undermining the effectiveness of such a planning process are uncertainties concerning extant resource conditions (partial observability), the immediate consequences of decision choices (partial controllability), the outcomes of uncontrolled, environmental drivers (environmental variation), and the processes structuring resource dynamics (structural uncertainty). Where outcomes from these sources of uncertainty can be described in terms of probability distributions, a focus on maximizing the expected objective return, while taking state-specific actions, is an effective mechanism for coping with uncertainty. When such probability distributions are unavailable or deemed unreliable, a focus on maximizing robustness is likely to be the preferred approach. Here the idea is to choose an action (or state-dependent policy) that achieves at least some minimum level of performance regardless of the (uncertain) outcomes. We provide some examples of how the dynamic optimization problem can be framed for problems involving management of habitat for an imperiled species, conservation of a

Confronting dynamics and uncertainty in optimal decision making for conservation

International Nuclear Information System (INIS)

Williams, Byron K; Johnson, Fred A

2013-01-01

The effectiveness of conservation efforts ultimately depends on the recognition that decision making, and the systems that it is designed to affect, are inherently dynamic and characterized by multiple sources of uncertainty. To cope with these challenges, conservation planners are increasingly turning to the tools of decision analysis, especially dynamic optimization methods. Here we provide a general framework for optimal, dynamic conservation and then explore its capacity for coping with various sources and degrees of uncertainty. In broadest terms, the dynamic optimization problem in conservation is choosing among a set of decision options at periodic intervals so as to maximize some conservation objective over the planning horizon. Planners must account for immediate objective returns, as well as the effect of current decisions on future resource conditions and, thus, on future decisions. Undermining the effectiveness of such a planning process are uncertainties concerning extant resource conditions (partial observability), the immediate consequences of decision choices (partial controllability), the outcomes of uncontrolled, environmental drivers (environmental variation), and the processes structuring resource dynamics (structural uncertainty). Where outcomes from these sources of uncertainty can be described in terms of probability distributions, a focus on maximizing the expected objective return, while taking state-specific actions, is an effective mechanism for coping with uncertainty. When such probability distributions are unavailable or deemed unreliable, a focus on maximizing robustness is likely to be the preferred approach. Here the idea is to choose an action (or state-dependent policy) that achieves at least some minimum level of performance regardless of the (uncertain) outcomes. We provide some examples of how the dynamic optimization problem can be framed for problems involving management of habitat for an imperiled species, conservation of a

Nonlinear Dynamic in an Ecological System with Impulsive Effect and Optimal Foraging

Directory of Open Access Journals (Sweden)

Min Zhao

2014-01-01

Full Text Available The population dynamics of a three-species ecological system with impulsive effect are investigated. Using the theories of impulsive equations and small-amplitude perturbation scales, the conditions for the system to be permanent when the number of predators released is less than some critical value can be obtained. Furthermore, because the predator in the system follows the predictions of optimal foraging theory, it follows that optimal foraging promotes species coexistence. In particular, the less beneficial prey can support the predator alone when the more beneficial prey goes extinct. Moreover, the influences of the impulsive effect and optimal foraging on inherent oscillations are studied using simulation, which reveals rich dynamic behaviors such as period-halving bifurcations, a chaotic band, a periodic window, and chaotic crises. In addition, the largest Lyapunov exponent and the power spectra of the strange attractor, which can help analyze the chaotic dynamic behavior of the model, are investigated. This information will be useful for studying the dynamic complexity of ecosystems.

Genetic algorithm optimization for dynamic construction site layout planning

Directory of Open Access Journals (Sweden)

Farmakis Panagiotis M.

2018-02-01

Full Text Available The dynamic construction site layout planning (DCSLP problem refers to the efficient placement and relocation of temporary construction facilities within a dynamically changing construction site environment considering the characteristics of facilities and work interrelationships, the shape and topography of the construction site, and the time-varying project needs. A multi-objective dynamic optimization model is developed for this problem that considers construction and relocation costs of facilities, transportation costs of resources moving from one facility to another or to workplaces, as well as safety and environmental considerations resulting from facilities’ operations and interconnections. The latter considerations are taken into account in the form of preferences or constraints regarding the proximity or remoteness of particular facilities to other facilities or work areas. The analysis of multiple project phases and the dynamic facility relocation from phase to phase highly increases the problem size, which, even in its static form, falls within the NP (for Nondeterministic Polynomial time- hard class of combinatorial optimization problems. For this reason, a genetic algorithm has been implemented for the solution due to its capability to robustly search within a large solution space. Several case studies and operational scenarios have been implemented through the Palisade’s Evolver software for model testing and evaluation. The results indi­cate satisfactory model response to time-varying input data in terms of solution quality and computation time. The model can provide decision support to site managers, allowing them to examine alternative scenarios and fine-tune optimal solutions according to their experience by introducing desirable preferences or constraints in the decision process.

A dynamic feedforward neural network based on gaussian particle swarm optimization and its application for predictive control.

Science.gov (United States)

Han, Min; Fan, Jianchao; Wang, Jun

2011-09-01

A dynamic feedforward neural network (DFNN) is proposed for predictive control, whose adaptive parameters are adjusted by using Gaussian particle swarm optimization (GPSO) in the training process. Adaptive time-delay operators are added in the DFNN to improve its generalization for poorly known nonlinear dynamic systems with long time delays. Furthermore, GPSO adopts a chaotic map with Gaussian function to balance the exploration and exploitation capabilities of particles, which improves the computational efficiency without compromising the performance of the DFNN. The stability of the particle dynamics is analyzed, based on the robust stability theory, without any restrictive assumption. A stability condition for the GPSO+DFNN model is derived, which ensures a satisfactory global search and quick convergence, without the need for gradients. The particle velocity ranges could change adaptively during the optimization process. The results of a comparative study show that the performance of the proposed algorithm can compete with selected algorithms on benchmark problems. Additional simulation results demonstrate the effectiveness and accuracy of the proposed combination algorithm in identifying and controlling nonlinear systems with long time delays.

Review of dynamic optimization methods in renewable natural resource management

Science.gov (United States)

Williams, B.K.

1989-01-01

In recent years, the applications of dynamic optimization procedures in natural resource management have proliferated. A systematic review of these applications is given in terms of a number of optimization methodologies and natural resource systems. The applicability of the methods to renewable natural resource systems are compared in terms of system complexity, system size, and precision of the optimal solutions. Recommendations are made concerning the appropriate methods for certain kinds of biological resource problems.

DFTBaby: A software package for non-adiabatic molecular dynamics simulations based on long-range corrected tight-binding TD-DFT(B)

Science.gov (United States)

Humeniuk, Alexander; Mitrić, Roland

2017-12-01

A software package, called DFTBaby, is published, which provides the electronic structure needed for running non-adiabatic molecular dynamics simulations at the level of tight-binding DFT. A long-range correction is incorporated to avoid spurious charge transfer states. Excited state energies, their analytic gradients and scalar non-adiabatic couplings are computed using tight-binding TD-DFT. These quantities are fed into a molecular dynamics code, which integrates Newton's equations of motion for the nuclei together with the electronic Schrödinger equation. Non-adiabatic effects are included by surface hopping. As an example, the program is applied to the optimization of excited states and non-adiabatic dynamics of polyfluorene. The python and Fortran source code is available at http://www.dftbaby.chemie.uni-wuerzburg.de.

Model-based dynamic control and optimization of gas networks

Energy Technology Data Exchange (ETDEWEB)

Hofsten, Kai

2001-07-01

This work contributes to the research on control, optimization and simulation of gas transmission systems to support the dispatch personnel at gas control centres for the decision makings in the daily operation of the natural gas transportation systems. Different control and optimization strategies have been studied. The focus is on the operation of long distance natural gas transportation systems. Stationary optimization in conjunction with linear model predictive control using state space models is proposed for supply security, the control of quality parameters and minimization of transportation costs for networks offering transportation services. The result from the stationary optimization together with a reformulation of a simplified fluid flow model formulates a linear dynamic optimization model. This model is used in a finite time control and state constrained linear model predictive controller. The deviation from the control and the state reference determined from the stationary optimization is penalized quadratically. Because of the time varying status of infrastructure, the control space is also generally time varying. When the average load is expected to change considerably, a new stationary optimization is performed, giving a new state and control reference together with a new dynamic model that is used for both optimization and state estimation. Another proposed control strategy is a control and output constrained nonlinear model predictive controller for the operation of gas transmission systems. Here, the objective is also the security of the supply, quality control and minimization of transportation costs. An output vector is defined, which together with a control vector are both penalized quadratically from their respective references in the objective function. The nonlinear model predictive controller can be combined with a stationary optimization. At each sampling instant, a non convex nonlinear programming problem is solved giving a local minimum

Optimization of a pH-shift control strategy for producing monoclonal antibodies in Chinese hamster ovary cell cultures using a pH-dependent dynamic model.

Science.gov (United States)

Hogiri, Tomoharu; Tamashima, Hiroshi; Nishizawa, Akitoshi; Okamoto, Masahiro

2018-02-01

To optimize monoclonal antibody (mAb) production in Chinese hamster ovary cell cultures, culture pH should be temporally controlled with high resolution. In this study, we propose a new pH-dependent dynamic model represented by simultaneous differential equations including a minimum of six system component, depending on pH value. All kinetic parameters in the dynamic model were estimated using an evolutionary numerical optimization (real-coded genetic algorithm) method based on experimental time-course data obtained at different pH values ranging from 6.6 to 7.2. We determined an optimal pH-shift schedule theoretically. We validated this optimal pH-shift schedule experimentally and mAb production increased by approximately 40% with this schedule. Throughout this study, it was suggested that the culture pH-shift optimization strategy using a pH-dependent dynamic model is suitable to optimize any pH-shift schedule for CHO cell lines used in mAb production projects. Copyright © 2017 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Optimizing the dynamic response of the H.B. Robinson nuclear plant using multiobjective particle swarm optimization

International Nuclear Information System (INIS)

Elsays, Mostafa A.; Naguib Aly, M.; Badawi, Alya A.

2009-01-01

In this paper, the Particle Swarm Optimization (PSO) algorithm is modified to deal with Multiobjective Optimization Problems (MOPs). A mathematical model for predicting the dynamic response of the H. B. Robinson nuclear power plant, which represents an Initial Value Problem (IVP) of Ordinary Differential Equations (ODEs), is solved using Runge-Kutta formula. The resulted data values are represented as a system of nonlinear algebraic equations by interpolation schemes for data fitting. This system of fitted nonlinear algebraic equations represents a nonlinear multiobjective optimization problem. A Multiobjective Particle Swarm Optimizer (MOPSO) which is based on the Pareto optimality concept is developed and applied to maximize the above mentioned problem. Results show that MOPSO efficiently cope with the problem and finds multiple Pareto optimal solutions. (orig.)

Optimization of a pump-pipe system by dynamic programming

DEFF Research Database (Denmark)

Vidal, Rene Victor Valqui; Ferreira, Jose S.

1984-01-01

In this paper the problem of minimizing the total cost of a pump-pipe system in series is considered. The route of the pipeline and the number of pumping stations are known. The optimization will then consist in determining the control variables, diameter and thickness of the pipe and the size of...... of the pumps. A general mathematical model is formulated and Dynamic Programming is used to find an optimal solution....

Improving the Dynamic Characteristics of Body-in-White Structure Using Structural Optimization

Directory of Open Access Journals (Sweden)

Aizzat S. Yahaya Rashid

2014-01-01

Full Text Available The dynamic behavior of a body-in-white (BIW structure has significant influence on the noise, vibration, and harshness (NVH and crashworthiness of a car. Therefore, by improving the dynamic characteristics of BIW, problems and failures associated with resonance and fatigue can be prevented. The design objectives attempt to improve the existing torsion and bending modes by using structural optimization subjected to dynamic load without compromising other factors such as mass and stiffness of the structure. The natural frequency of the design was modified by identifying and reinforcing the structure at critical locations. These crucial points are first identified by topology optimization using mass and natural frequencies as the design variables. The individual components obtained from the analysis go through a size optimization step to find their target thickness of the structure. The thickness of affected regions of the components will be modified according to the analysis. The results of both optimization steps suggest several design modifications to achieve the target vibration specifications without compromising the stiffness of the structure. A method of combining both optimization approaches is proposed to improve the design modification process.

Optimal Risk Reduction in the Railway Industry by Using Dynamic Programming

OpenAIRE

Michael Todinov; Eberechi Weli

2013-01-01

The paper suggests for the first time the use of dynamic programming techniques for optimal risk reduction in the railway industry. It is shown that by using the concept ‘amount of removed risk by a risk reduction option’, the problem related to optimal allocation of a fixed budget to achieve a maximum risk reduction in the railway industry can be reduced to an optimisation problem from dynamic programming. For n risk reduction options and size of the available risk reduction budget B (expres...

A low-power high dynamic range front-end ASIC for imaging calorimeters

CERN Document Server

Bagliesi, M G; Marrocchesi, P S; Meucci, M; Millucci, V; Morsani, F; Paoletti, R; Pilo, F; Scribano, A; Turini, N; Valle, G D

2002-01-01

High granularity calorimeters with shower imaging capabilities require dedicated front-end electronics. The ICON 4CH and VA4 PMT chip-set is suitable for very high dynamic range systems with strict noise requirements. The ICON 4CH is a 4 channel input, 12 channel output ASIC designed for use in a multi-anode photomultiplier system with very large dynamic range and low-noise requirements. Each of the four input signals to the ASIC is split equally into three branches by a current conveyor. Each of the three branches is scaled differently: 1:1, 1:8 and 1:80. The signal is read out by a 12 channel low noise/low power high dynamic range charge sensitive preamplifier-shaper circuit (VA4-PMT chip), with simultaneous sample- and-hold, multiplexed analog read-out, calibration facilities. Tests performed in our lab with a PMT are reported in terms of linearity, dynamic range and cross-talk of the system. (5 refs).

Extending the Dynamic Range of a Time Projection Chamber

Science.gov (United States)

Estee, Justin; S πRIT Collaboration

2017-09-01

The use of Time Projection Chambers (TPCs) in intermediate heavy ion reactions faces some challenges in addressing the energy losses that range from the small energy loss of relativistic pions to the large energy loss of slow moving heavy ions. A typical trade-off can be to set the smallest desired signals to be well within the lower limits of the dynamic range of the electronics while allowing for some larger signals to saturate the electronics. With wire plane anodes, signals from readout pads further away from the track remain unsaturated and allow signals from tracks with saturated pads to be accurately recovered. We illustrate this technique using data from the SAMURAI Pion-Reconstruction and Ion-Tracker (S πRIT) TPC , which recently measured pions and light charged particles in collisions of Sn+Sn isotopes. Our method exploits knowledge of how the induced charge distribution depends on the distance from the track to smoothly extend dynamic range even when some of the pads in the track are saturated. To accommodate the analysis of slow moving heavy ions, we have extended the Bichsel energy loss distributions to handle slower moving ions as well. In this talk, I will discuss a combined approach which successfully extends the dynamic range of the TPC electronics. This work is supported by the U.S. DOE under Grant Nos. DE-SC0014530, DE-NA0002923, US NSF Grant No. PHY-1565546 and the Japan MEXT KAKENHI Grant No. 24105004.

Dynamic modeling and optimal joint torque coordination of advanced robotic systems

Science.gov (United States)

Kang, Hee-Jun

The development is documented of an efficient dynamic modeling algorithm and the subsequent optimal joint input load coordination of advanced robotic systems for industrial application. A closed-form dynamic modeling algorithm for the general closed-chain robotic linkage systems is presented. The algorithm is based on the transfer of system dependence from a set of open chain Lagrangian coordinates to any desired system generalized coordinate set of the closed-chain. Three different techniques for evaluation of the kinematic closed chain constraints allow the representation of the dynamic modeling parameters in terms of system generalized coordinates and have no restriction with regard to kinematic redundancy. The total computational requirement of the closed-chain system model is largely dependent on the computation required for the dynamic model of an open kinematic chain. In order to improve computational efficiency, modification of an existing open-chain KIC based dynamic formulation is made by the introduction of the generalized augmented body concept. This algorithm allows a 44 pct. computational saving over the current optimized one (O(N4), 5995 when N = 6). As means of resolving redundancies in advanced robotic systems, local joint torque optimization is applied for effectively using actuator power while avoiding joint torque limits. The stability problem in local joint torque optimization schemes is eliminated by using fictitious dissipating forces which act in the necessary null space. The performance index representing the global torque norm is shown to be satisfactory. In addition, the resulting joint motion trajectory becomes conservative, after a transient stage, for repetitive cyclic end-effector trajectories. The effectiveness of the null space damping method is shown. The modular robot, which is built of well defined structural modules from a finite-size inventory and is controlled by one general computer system, is another class of evolving

Optimal Dynamics of Intermittent Water Supply

Science.gov (United States)

Lieb, Anna; Wilkening, Jon; Rycroft, Chris

2014-11-01

In many urban areas of the developing world, piped water is supplied only intermittently, as valves direct water to different parts of the water distribution system at different times. The flow is transient, and may transition between free-surface and pressurized, resulting in complex dynamical features with important consequences for water suppliers and users. These consequences include degradation of distribution system components, compromised water quality, and inequitable water availability. The goal of this work is to model the important dynamics and identify operating conditions that mitigate certain negative effects of intermittent water supply. Specifically, we will look at valve parameters occurring as boundary conditions in a network model of transient, transition flow through closed pipes. Optimization will be used to find boundary values to minimize pressure gradients and ensure equitable water availability.

Optimal Acceleration-Velocity-Bounded Trajectory Planning in Dynamic Crowd Simulation

Directory of Open Access Journals (Sweden)

Fu Yue-wen

2014-01-01

Full Text Available Creating complex and realistic crowd behaviors, such as pedestrian navigation behavior with dynamic obstacles, is a difficult and time consuming task. In this paper, we study one special type of crowd which is composed of urgent individuals, normal individuals, and normal groups. We use three steps to construct the crowd simulation in dynamic environment. The first one is that the urgent individuals move forward along a given path around dynamic obstacles and other crowd members. An optimal acceleration-velocity-bounded trajectory planning method is utilized to model their behaviors, which ensures that the durations of the generated trajectories are minimal and the urgent individuals are collision-free with dynamic obstacles (e.g., dynamic vehicles. In the second step, a pushing model is adopted to simulate the interactions between urgent members and normal ones, which ensures that the computational cost of the optimal trajectory planning is acceptable. The third step is obligated to imitate the interactions among normal members using collision avoidance behavior and flocking behavior. Various simulation results demonstrate that these three steps give realistic crowd phenomenon just like the real world.

Dynamic Portfolio Optimization with Transaction Costs and State-Dependent Drift

DEFF Research Database (Denmark)

Palczewski, Jan; Poulsen, Rolf; Schenk-Hoppe, Klaus Reiner

2015-01-01

The problem of dynamic portfolio choice with transaction costs is often addressed by constructing a Markov Chain approximation of the continuous time price processes. Using this approximation, we present an efficient numerical method to determine optimal portfolio strategies under time- and state......-dependent drift and proportional transaction costs. This scenario arises when investors have behavioral biases or the actual drift is unknown and needs to be estimated. Our numerical method solves dynamic optimal portfolio problems with an exponential utility function for time-horizons of up to 40 years....... It is applied to measure the value of information and the loss from transaction costs using the indifference principle....

Focusing light through dynamical samples using fast continuous wavefront optimization.

Science.gov (United States)

Blochet, B; Bourdieu, L; Gigan, S

2017-12-01

We describe a fast continuous optimization wavefront shaping system able to focus light through dynamic scattering media. A micro-electro-mechanical system-based spatial light modulator, a fast photodetector, and field programmable gate array electronics are combined to implement a continuous optimization of a wavefront with a single-mode optimization rate of 4.1 kHz. The system performances are demonstrated by focusing light through colloidal solutions of TiO 2 particles in glycerol with tunable temporal stability.

Optimization of rotor blades for combined structural, dynamic, and aerodynamic properties

Science.gov (United States)

He, Cheng-Jian; Peters, David A.

1990-01-01

Optimal helicopter blade design with computer-based mathematical programming has received more and more attention in recent years. Most of the research has focused on optimum dynamic characteristics of rotor blades to reduce vehicle vibration. There is also work on optimization of aerodynamic performance and on composite structural design. This research has greatly increased our understanding of helicopter optimum design in each of these aspects. Helicopter design is an inherently multidisciplinary process involving strong interactions among various disciplines which can appropriately include aerodynamics; dynamics, both flight dynamics and structural dynamics; aeroelasticity: vibrations and stability; and even acoustics. Therefore, the helicopter design process must satisfy manifold requirements related to the aforementioned diverse disciplines. In our present work, we attempt to combine several of these important effects in a unified manner. First, we design a blade with optimum aerodynamic performance by proper layout of blade planform and spanwise twist. Second, the blade is designed to have natural frequencies that are placed away from integer multiples of the rotor speed for a good dynamic characteristics. Third, the structure is made as light as possible with sufficient rotational inertia to allow for autorotational landing, with safe stress margins and flight fatigue life at each cross-section, and with aeroelastical stability and low vibrations. Finally, a unified optimization refines the solution.

A dynamic inertia weight particle swarm optimization algorithm

International Nuclear Information System (INIS)

Jiao Bin; Lian Zhigang; Gu Xingsheng

2008-01-01

Particle swarm optimization (PSO) algorithm has been developing rapidly and has been applied widely since it was introduced, as it is easily understood and realized. This paper presents an improved particle swarm optimization algorithm (IPSO) to improve the performance of standard PSO, which uses the dynamic inertia weight that decreases according to iterative generation increasing. It is tested with a set of 6 benchmark functions with 30, 50 and 150 different dimensions and compared with standard PSO. Experimental results indicate that the IPSO improves the search performance on the benchmark functions significantly

Optimal sensitometric curves of Kodak EDR2 film for dynamic intensity modulated radiation therapy verification.

Science.gov (United States)

Suriyapee, S; Pitaxtarnin, N; Oonsiri, S; Jumpangern, C; Israngkul Na Ayuthaya, I

2008-01-01

To investigate the optimal sensitometric curves of extended dose range (EDR2) radiographic film in terms of depth, field size, dose range and processing conditions for dynamic intensity modulated radiation therapy (IMRT) dosimetry verification with 6 MV X-ray beams. A Varian Clinac 23 EX linear accelerator with 6 MV X-ray beam was used to study the response of Kodak EDR2 film. Measurements were performed at depths of 5, 10 and 15 cm in MedTec virtual water phantom and with field sizes of 2x2, 3x3, 10x10 and 15x15 cm(2). Doses ranging from 20 to 450 cGy were used. The film was developed with the Kodak RP X-OMAT Model M6B automatic film processor. Film response was measured with the Vidar model VXR-16 scanner. Sensitometric curves were applied to the dose profiles measured with film at 5 cm in the virtual water phantom with field sizes of 2x2 and 10x10 cm(2) and compared with ion chamber data. Scanditronix/Wellhofer OmniPro(TM) IMRT software was used for the evaluation of the IMRT plan calculated by Eclipse treatment planning. Investigation of the reproducibility and accuracy of the film responses, which depend mainly on the film processor, was carried out by irradiating one film nine times with doses of 20 to 450 cGy. A maximum standard deviation of 4.9% was found which decreased to 1.9% for doses between 20 and 200 cGy. The sensitometric curves for various field sizes at fixed depth showed a maximum difference of 4.2% between 2x2 and 15x15 cm(2) at 5 cm depth with a dose of 450 cGy. The shallow depth tended to show a greater effect of field size responses than the deeper depths. The sensitometric curves for various depths at fixed field size showed slightly different film responses; the difference due to depth was within 1.8% for all field sizes studied. Both field size and depth effect were reduced when the doses were lower than 450 cGy. The difference was within 2.5% in the dose range from 20 to 300 cGy for all field sizes and depths studied. Dose profiles

Dynamic optimization of distributed biological systems using robust and efficient numerical techniques.

Science.gov (United States)

Vilas, Carlos; Balsa-Canto, Eva; García, Maria-Sonia G; Banga, Julio R; Alonso, Antonio A

2012-07-02

Systems biology allows the analysis of biological systems behavior under different conditions through in silico experimentation. The possibility of perturbing biological systems in different manners calls for the design of perturbations to achieve particular goals. Examples would include, the design of a chemical stimulation to maximize the amplitude of a given cellular signal or to achieve a desired pattern in pattern formation systems, etc. Such design problems can be mathematically formulated as dynamic optimization problems which are particularly challenging when the system is described by partial differential equations.This work addresses the numerical solution of such dynamic optimization problems for spatially distributed biological systems. The usual nonlinear and large scale nature of the mathematical models related to this class of systems and the presence of constraints on the optimization problems, impose a number of difficulties, such as the presence of suboptimal solutions, which call for robust and efficient numerical techniques. Here, the use of a control vector parameterization approach combined with efficient and robust hybrid global optimization methods and a reduced order model methodology is proposed. The capabilities of this strategy are illustrated considering the solution of a two challenging problems: bacterial chemotaxis and the FitzHugh-Nagumo model. In the process of chemotaxis the objective was to efficiently compute the time-varying optimal concentration of chemotractant in one of the spatial boundaries in order to achieve predefined cell distribution profiles. Results are in agreement with those previously published in the literature. The FitzHugh-Nagumo problem is also efficiently solved and it illustrates very well how dynamic optimization may be used to force a system to evolve from an undesired to a desired pattern with a reduced number of actuators. The presented methodology can be used for the efficient dynamic optimization of

Application of numerical optimization techniques to control system design for nonlinear dynamic models of aircraft

Science.gov (United States)

Lan, C. Edward; Ge, Fuying

1989-01-01

Control system design for general nonlinear flight dynamic models is considered through numerical simulation. The design is accomplished through a numerical optimizer coupled with analysis of flight dynamic equations. The general flight dynamic equations are numerically integrated and dynamic characteristics are then identified from the dynamic response. The design variables are determined iteratively by the optimizer to optimize a prescribed objective function which is related to desired dynamic characteristics. Generality of the method allows nonlinear effects to aerodynamics and dynamic coupling to be considered in the design process. To demonstrate the method, nonlinear simulation models for an F-5A and an F-16 configurations are used to design dampers to satisfy specifications on flying qualities and control systems to prevent departure. The results indicate that the present method is simple in formulation and effective in satisfying the design objectives.

Adaptive dynamic programming with applications in optimal control

CERN Document Server

Liu, Derong; Wang, Ding; Yang, Xiong; Li, Hongliang

2017-01-01

This book covers the most recent developments in adaptive dynamic programming (ADP). The text begins with a thorough background review of ADP making sure that readers are sufficiently familiar with the fundamentals. In the core of the book, the authors address first discrete- and then continuous-time systems. Coverage of discrete-time systems starts with a more general form of value iteration to demonstrate its convergence, optimality, and stability with complete and thorough theoretical analysis. A more realistic form of value iteration is studied where value function approximations are assumed to have finite errors. Adaptive Dynamic Programming also details another avenue of the ADP approach: policy iteration. Both basic and generalized forms of policy-iteration-based ADP are studied with complete and thorough theoretical analysis in terms of convergence, optimality, stability, and error bounds. Among continuous-time systems, the control of affine and nonaffine nonlinear systems is studied using the ADP app...

Optimal Input Design for Aircraft Parameter Estimation using Dynamic Programming Principles

Science.gov (United States)

Morelli, Eugene A.; Klein, Vladislav

1990-01-01

A new technique was developed for designing optimal flight test inputs for aircraft parameter estimation experiments. The principles of dynamic programming were used for the design in the time domain. This approach made it possible to include realistic practical constraints on the input and output variables. A description of the new approach is presented, followed by an example for a multiple input linear model describing the lateral dynamics of a fighter aircraft. The optimal input designs produced by the new technique demonstrated improved quality and expanded capability relative to the conventional multiple input design method.

The MOLDY short-range molecular dynamics package

Science.gov (United States)

Ackland, G. J.; D'Mellow, K.; Daraszewicz, S. L.; Hepburn, D. J.; Uhrin, M.; Stratford, K.

2011-12-01

We describe a parallelised version of the MOLDY molecular dynamics program. This Fortran code is aimed at systems which may be described by short-range potentials and specifically those which may be addressed with the embedded atom method. This includes a wide range of transition metals and alloys. MOLDY provides a range of options in terms of the molecular dynamics ensemble used and the boundary conditions which may be applied. A number of standard potentials are provided, and the modular structure of the code allows new potentials to be added easily. The code is parallelised using OpenMP and can therefore be run on shared memory systems, including modern multicore processors. Particular attention is paid to the updates required in the main force loop, where synchronisation is often required in OpenMP implementations of molecular dynamics. We examine the performance of the parallel code in detail and give some examples of applications to realistic problems, including the dynamic compression of copper and carbon migration in an iron-carbon alloy. Program summaryProgram title: MOLDY Catalogue identifier: AEJU_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEJU_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License version 2 No. of lines in distributed program, including test data, etc.: 382 881 No. of bytes in distributed program, including test data, etc.: 6 705 242 Distribution format: tar.gz Programming language: Fortran 95/OpenMP Computer: Any Operating system: Any Has the code been vectorised or parallelized?: Yes. OpenMP is required for parallel execution RAM: 100 MB or more Classification: 7.7 Nature of problem: Moldy addresses the problem of many atoms (of order 10 6) interacting via a classical interatomic potential on a timescale of microseconds. It is designed for problems where statistics must be gathered over a number of equivalent runs, such as

On Revenue-Optimal Dynamic Auctions for Bidders with Interdependent Values

Science.gov (United States)

Constantin, Florin; Parkes, David C.

In a dynamic market, being able to update one's value based on information available to other bidders currently in the market can be critical to having profitable transactions. This is nicely captured by the model of interdependent values (IDV): a bidder's value can explicitly depend on the private information of other bidders. In this paper we present preliminary results about the revenue properties of dynamic auctions for IDV bidders. We adopt a computational approach to design single-item revenue-optimal dynamic auctions with known arrivals and departures but (private) signals that arrive online. In leveraging a characterization of truthful auctions, we present a mixed-integer programming formulation of the design problem. Although a discretization is imposed on bidder signals the solution is a mechanism applicable to continuous signals. The formulation size grows exponentially in the dependence of bidders' values on other bidders' signals. We highlight general properties of revenue-optimal dynamic auctions in a simple parametrized example and study the sensitivity of prices and revenue to model parameters.

Dynamic range studies of the RCA streak tube in the LLL streak camera

International Nuclear Information System (INIS)

Thomas, S.W.; Phillips, G.E.

1979-01-01

As indicated by tests on several cameras, the dynamic range of the Lawrence Livermore Laboratory streak-camera system appears to be about two orders of magnitude greater than those reported for other systems for 10- to 200-ps pulses. The lack of a fine mesh grid in the RCA streak tube used in these cameras probably contributes to a lower system dynamic noise and therefore raises the dynamic range. A developmental tube with a mesh grid was tested and supports this conjecture. Order-of-magnitude variations in input slit width do not affect the spot size on the phosphor or the dynamic range of the RCA tube. (author)

Dynamic range compression in a liquid argon calorimeter

International Nuclear Information System (INIS)

Cleland, W.E.; Lissauer, D.; Radeka, V.; Rescia, S.; Takai, H.; Wingerter-Seez, I.

1996-01-01

The anticipated range of particle energies at the LHC, coupled with the need for precision, low noise calorimetry makes severe demands on the dynamic range of the calorimeter readout. A common approach to this problem is to use shapers with two or more gain scales. In this paper, the authors describe their experience with a new approach in which a preamplifier with dynamic gain compression is used. An unavoidable consequence of dynamic gain adjustment is that the peaking time of the shaper output signal becomes amplitude dependent. The authors have carried out a test of such a readout system in the RD3 calorimeter, a liquid argon device with accordion geometry. The calibration system is used to determine both the gain of the individual channels as well as to map the shape of the waveform as a function of signal amplitude. A new procedure for waveform analysis, in which the fitted parameters describe the impulse response of the system, permits a straightforward translation of the calibration waveform to the waveform generated by a particle crossing the ionization gap. They find that the linearity and resolution of the calorimeter is equivalent to that obtained with linear preamplifiers, up to an energy of 200 GeV

On (dynamic) range minimum queries in external memory

DEFF Research Database (Denmark)

Arge, L.; Fischer, Johannes; Sanders, Peter

2013-01-01

We study the one-dimensional range minimum query (RMQ) problem in the external memory model. We provide the first space-optimal solution to the batched static version of the problem. On an instance with N elements and Q queries, our solution takes Θ(sort(N + Q)) = Θ( N+QB log M /B N+QB ) I...

Quantitative high dynamic range beam profiling for fluorescence microscopy

International Nuclear Information System (INIS)

Mitchell, T. J.; Saunter, C. D.; O’Nions, W.; Girkin, J. M.; Love, G. D.

2014-01-01

Modern developmental biology relies on optically sectioning fluorescence microscope techniques to produce non-destructive in vivo images of developing specimens at high resolution in three dimensions. As optimal performance of these techniques is reliant on the three-dimensional (3D) intensity profile of the illumination employed, the ability to directly record and analyze these profiles is of great use to the fluorescence microscopist or instrument builder. Though excitation beam profiles can be measured indirectly using a sample of fluorescent beads and recording the emission along the microscope detection path, we demonstrate an alternative approach where a miniature camera sensor is used directly within the illumination beam. Measurements taken using our approach are solely concerned with the illumination optics as the detection optics are not involved. We present a miniature beam profiling device and high dynamic range flux reconstruction algorithm that together are capable of accurately reproducing quantitative 3D flux maps over a large focal volume. Performance of this beam profiling system is verified within an optical test bench and demonstrated for fluorescence microscopy by profiling the low NA illumination beam of a single plane illumination microscope. The generality and success of this approach showcases a widely flexible beam amplitude diagnostic tool for use within the life sciences

Dynamic range extension of BPM at the NSLS

International Nuclear Information System (INIS)

Bordoley, M.

1993-01-01

In order to overcome range limitations, the existing Beam Position Monitor (BPM) receiver was modified, extending the dynamic range from 35 dB to 60 dB. The modifications include the insertion of an RF PIN attenuator, RF amplifier, and control circuitry in line with the RF link to add an extra 25dB to the existing AGC loop. This stand alone 25dB RF gain control stage is integrated into the present system without any change to the existing receiver

Optimal Passive Dynamics for Physical Interaction: Catching a Mass

Directory of Open Access Journals (Sweden)

Kevin Kemper

2013-05-01

Full Text Available For manipulation tasks in uncertain environments, intentionally designed series impedance in mechanical systems can provide significant benefits that cannot be achieved in software. Traditionally, the design of actuated systems revolves around sizing torques, speeds, and control strategies without considering the system’s passive dynamics. However, the passive dynamics of the mechanical system, including inertia, stiffness, and damping along with other parameters such as torque and stroke limits often impose performance limitations that cannot be overcome with software control. In this paper, we develop relationships between an actuator’s passive dynamics and the resulting performance for the purpose of better understanding how to tune the passive dynamics for catching an unexpected object. We use a mathematically optimal controller subject to force limitations to stop the incoming object without breaking contact and bouncing. The use of an optimal controller is important so that our results directly reflect the physical system’s performance. We analytically calculate the maximum velocity that can be caught by a realistic actuator with limitations such as force and stroke limits. The results show that in order to maximize the velocity of an object that can be caught without exceeding the actuator’s torque and stroke limits, a soft spring along with a strong damper will be desired.

Dynamic Programming Approach for Exact Decision Rule Optimization

KAUST Repository

Amin, Talha

2013-01-01

This chapter is devoted to the study of an extension of dynamic programming approach that allows sequential optimization of exact decision rules relative to the length and coverage. It contains also results of experiments with decision tables from UCI Machine Learning Repository. © Springer-Verlag Berlin Heidelberg 2013.

Markdown Optimization via Approximate Dynamic Programming

Directory of Open Access Journals (Sweden)

Cos?gun

2013-02-01

Full Text Available We consider the markdown optimization problem faced by the leading apparel retail chain. Because of substitution among products the markdown policy of one product affects the sales of other products. Therefore, markdown policies for product groups having a significant crossprice elasticity among each other should be jointly determined. Since the state space of the problem is very huge, we use Approximate Dynamic Programming. Finally, we provide insights on the behavior of how each product price affects the markdown policy.

Feature Optimization for Long-Range Visual Homing in Changing Environments

Directory of Open Access Journals (Sweden)

Qidan Zhu

2014-02-01

Full Text Available This paper introduces a feature optimization method for robot long-range feature-based visual homing in changing environments. To cope with the changing environmental appearance, the optimization procedure is introduced to distinguish the most relevant features for feature-based visual homing, including the spatial distribution, selection and updating. In the previous research on feature-based visual homing, less effort has been spent on the way to improve the feature distribution to get uniformly distributed features, which are closely related to homing performance. This paper presents a modified feature extraction algorithm to decrease the influence of anisotropic feature distribution. In addition, the feature selection and updating mechanisms, which have hardly drawn any attention in the domain of feature-based visual homing, are crucial in improving homing accuracy and in maintaining the representation of changing environments. To verify the feasibility of the proposal, several comprehensive evaluations are conducted. The results indicate that the feature optimization method can find optimal feature sets for feature-based visual homing, and adapt the appearance representation to the changing environments as well.

Dynamic optimization and robust explicit model predictive control of hydrogen storage tank

KAUST Repository

Panos, C.

2010-09-01

We present a general framework for the optimal design and control of a metal-hydride bed under hydrogen desorption operation. The framework features: (i) a detailed two-dimension dynamic process model, (ii) a design and operational dynamic optimization step, and (iii) an explicit/multi-parametric model predictive controller design step. For the controller design, a reduced order approximate model is obtained, based on which nominal and robust multi-parametric controllers are designed. © 2010 Elsevier Ltd.

Dynamic optimization and robust explicit model predictive control of hydrogen storage tank

KAUST Repository

Panos, C.; Kouramas, K.I.; Georgiadis, M.C.; Pistikopoulos, E.N.

2010-01-01

We present a general framework for the optimal design and control of a metal-hydride bed under hydrogen desorption operation. The framework features: (i) a detailed two-dimension dynamic process model, (ii) a design and operational dynamic optimization step, and (iii) an explicit/multi-parametric model predictive controller design step. For the controller design, a reduced order approximate model is obtained, based on which nominal and robust multi-parametric controllers are designed. © 2010 Elsevier Ltd.

Communication: Time-dependent optimized coupled-cluster method for multielectron dynamics

Science.gov (United States)

Sato, Takeshi; Pathak, Himadri; Orimo, Yuki; Ishikawa, Kenichi L.

2018-02-01

Time-dependent coupled-cluster method with time-varying orbital functions, called time-dependent optimized coupled-cluster (TD-OCC) method, is formulated for multielectron dynamics in an intense laser field. We have successfully derived the equations of motion for CC amplitudes and orthonormal orbital functions based on the real action functional, and implemented the method including double excitations (TD-OCCD) and double and triple excitations (TD-OCCDT) within the optimized active orbitals. The present method is size extensive and gauge invariant, a polynomial cost-scaling alternative to the time-dependent multiconfiguration self-consistent-field method. The first application of the TD-OCC method of intense-laser driven correlated electron dynamics in Ar atom is reported.

Optimal Dynamic Pricing for Perishable Assets with Nonhomogeneous Demand

OpenAIRE

Wen Zhao; Yu-Sheng Zheng

2000-01-01

We consider a dynamic pricing model for selling a given stock of a perishable product over a finite time horizon. Customers, whose reservation price distribution changes over time, arrive according to a nonhomogeneous Poisson process. We show that at any given time, the optimal price decreases with inventory. We also identify a sufficient condition under which the optimal price decreases over time for a given inventory level. This sufficient condition requires that the willingness of a custom...

Dynamical arrest in dense short-ranged attractive colloids

International Nuclear Information System (INIS)

Foffi, G; Sciortino, F; Zaccarelli, E; Tartaglia, P

2004-01-01

We study thermodynamic and dynamic properties of model colloidal systems interacting with a hard core repulsion and a short-range attraction, and provide an overall picture of their phase diagrams which shows a very rich phenomenology. We focus on the slow dynamic properties of this model, investigating in detail the glass transition lines (both repulsive and attractive), the glass-glass transitions and the location of the higher order singularities. We discuss the relative location of the glass lines and of the metastable liquid-gas binodal, an issue relevant for the understanding of low density arrested states of matter

Dynamic programming approach to optimization of approximate decision rules

KAUST Repository

Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

2013-01-01

This paper is devoted to the study of an extension of dynamic programming approach which allows sequential optimization of approximate decision rules relative to the length and coverage. We introduce an uncertainty measure R(T) which is the number

Hierarchical tone mapping for high dynamic range image visualization

Science.gov (United States)

Qiu, Guoping; Duan, Jiang

2005-07-01

In this paper, we present a computationally efficient, practically easy to use tone mapping techniques for the visualization of high dynamic range (HDR) images in low dynamic range (LDR) reproduction devices. The new method, termed hierarchical nonlinear linear (HNL) tone-mapping operator maps the pixels in two hierarchical steps. The first step allocates appropriate numbers of LDR display levels to different HDR intensity intervals according to the pixel densities of the intervals. The second step linearly maps the HDR intensity intervals to theirs allocated LDR display levels. In the developed HNL scheme, the assignment of LDR display levels to HDR intensity intervals is controlled by a very simple and flexible formula with a single adjustable parameter. We also show that our new operators can be used for the effective enhancement of ordinary images.

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

Science.gov (United States)

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

2016-08-03

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.

Optimization of multi-stage dynamic treatment regimes utilizing accumulated data.

Science.gov (United States)

Huang, Xuelin; Choi, Sangbum; Wang, Lu; Thall, Peter F

2015-11-20

In medical therapies involving multiple stages, a physician's choice of a subject's treatment at each stage depends on the subject's history of previous treatments and outcomes. The sequence of decisions is known as a dynamic treatment regime or treatment policy. We consider dynamic treatment regimes in settings where each subject's final outcome can be defined as the sum of longitudinally observed values, each corresponding to a stage of the regime. Q-learning, which is a backward induction method, is used to first optimize the last stage treatment then sequentially optimize each previous stage treatment until the first stage treatment is optimized. During this process, model-based expectations of outcomes of late stages are used in the optimization of earlier stages. When the outcome models are misspecified, bias can accumulate from stage to stage and become severe, especially when the number of treatment stages is large. We demonstrate that a modification of standard Q-learning can help reduce the accumulated bias. We provide a computational algorithm, estimators, and closed-form variance formulas. Simulation studies show that the modified Q-learning method has a higher probability of identifying the optimal treatment regime even in settings with misspecified models for outcomes. It is applied to identify optimal treatment regimes in a study for advanced prostate cancer and to estimate and compare the final mean rewards of all the possible discrete two-stage treatment sequences. Copyright © 2015 John Wiley & Sons, Ltd.

Optimizing spread dynamics on graphs by message passing

International Nuclear Information System (INIS)

Altarelli, F; Braunstein, A; Dall’Asta, L; Zecchina, R

2013-01-01

Cascade processes are responsible for many important phenomena in natural and social sciences. Simple models of irreversible dynamics on graphs, in which nodes activate depending on the state of their neighbors, have been successfully applied to describe cascades in a large variety of contexts. Over the past decades, much effort has been devoted to understanding the typical behavior of the cascades arising from initial conditions extracted at random from some given ensemble. However, the problem of optimizing the trajectory of the system, i.e. of identifying appropriate initial conditions to maximize (or minimize) the final number of active nodes, is still considered to be practically intractable, with the only exception being models that satisfy a sort of diminishing returns property called submodularity. Submodular models can be approximately solved by means of greedy strategies, but by definition they lack cooperative characteristics which are fundamental in many real systems. Here we introduce an efficient algorithm based on statistical physics for the optimization of trajectories in cascade processes on graphs. We show that for a wide class of irreversible dynamics, even in the absence of submodularity, the spread optimization problem can be solved efficiently on large networks. Analytic and algorithmic results on random graphs are complemented by the solution of the spread maximization problem on a real-world network (the Epinions consumer reviews network). (paper)

Optimizing spread dynamics on graphs by message passing

Science.gov (United States)

Altarelli, F.; Braunstein, A.; Dall'Asta, L.; Zecchina, R.

2013-09-01

Cascade processes are responsible for many important phenomena in natural and social sciences. Simple models of irreversible dynamics on graphs, in which nodes activate depending on the state of their neighbors, have been successfully applied to describe cascades in a large variety of contexts. Over the past decades, much effort has been devoted to understanding the typical behavior of the cascades arising from initial conditions extracted at random from some given ensemble. However, the problem of optimizing the trajectory of the system, i.e. of identifying appropriate initial conditions to maximize (or minimize) the final number of active nodes, is still considered to be practically intractable, with the only exception being models that satisfy a sort of diminishing returns property called submodularity. Submodular models can be approximately solved by means of greedy strategies, but by definition they lack cooperative characteristics which are fundamental in many real systems. Here we introduce an efficient algorithm based on statistical physics for the optimization of trajectories in cascade processes on graphs. We show that for a wide class of irreversible dynamics, even in the absence of submodularity, the spread optimization problem can be solved efficiently on large networks. Analytic and algorithmic results on random graphs are complemented by the solution of the spread maximization problem on a real-world network (the Epinions consumer reviews network).

Risk-Constrained Dynamic Programming for Optimal Mars Entry, Descent, and Landing

Science.gov (United States)

Ono, Masahiro; Kuwata, Yoshiaki

2013-01-01

A chance-constrained dynamic programming algorithm was developed that is capable of making optimal sequential decisions within a user-specified risk bound. This work handles stochastic uncertainties over multiple stages in the CEMAT (Combined EDL-Mobility Analyses Tool) framework. It was demonstrated by a simulation of Mars entry, descent, and landing (EDL) using real landscape data obtained from the Mars Reconnaissance Orbiter. Although standard dynamic programming (DP) provides a general framework for optimal sequential decisionmaking under uncertainty, it typically achieves risk aversion by imposing an arbitrary penalty on failure states. Such a penalty-based approach cannot explicitly bound the probability of mission failure. A key idea behind the new approach is called risk allocation, which decomposes a joint chance constraint into a set of individual chance constraints and distributes risk over them. The joint chance constraint was reformulated into a constraint on an expectation over a sum of an indicator function, which can be incorporated into the cost function by dualizing the optimization problem. As a result, the chance-constraint optimization problem can be turned into an unconstrained optimization over a Lagrangian, which can be solved efficiently using a standard DP approach.

Chaotic system optimal tracking using data-based synchronous method with unknown dynamics and disturbances

International Nuclear Information System (INIS)

Song Ruizhuo; Wei Qinglai

2017-01-01

We develop an optimal tracking control method for chaotic system with unknown dynamics and disturbances. The method allows the optimal cost function and the corresponding tracking control to update synchronously. According to the tracking error and the reference dynamics, the augmented system is constructed. Then the optimal tracking control problem is defined. The policy iteration (PI) is introduced to solve the min-max optimization problem. The off-policy adaptive dynamic programming (ADP) algorithm is then proposed to find the solution of the tracking Hamilton–Jacobi–Isaacs (HJI) equation online only using measured data and without any knowledge about the system dynamics. Critic neural network (CNN), action neural network (ANN), and disturbance neural network (DNN) are used to approximate the cost function, control, and disturbance. The weights of these networks compose the augmented weight matrix, and the uniformly ultimately bounded (UUB) of which is proven. The convergence of the tracking error system is also proven. Two examples are given to show the effectiveness of the proposed synchronous solution method for the chaotic system tracking problem. (paper)

Large Portfolio Risk Management and Optimal Portfolio Allocation with Dynamic Copulas

OpenAIRE

Thorsten Lehnert; Xisong Jin

2011-01-01

Previous research focuses on the importance of modeling the multivariate distribution for optimal portfolio allocation and active risk management. However, available dynamic models are not easily applied for high-dimensional problems due to the curse of dimensionality. In this paper, we extend the framework of the Dynamic Conditional Correlation/Equicorrelation and an extreme value approach into a series of Dynamic Conditional Elliptical Copulas. We investigate risk measures like Value at Ris...

Wide dynamic range beam profile monitor

International Nuclear Information System (INIS)

Lee, D.M.; Brown, D.; Hardekopf, R.; Bilskie, J.R.; van Dyck, O.B.V.

1985-01-01

An economical harp multiplexer system has been developed to achieve a wide dynamic range. The harp system incorporates a pneumatically actuated harp detector with ceramic boards and carbon wires; a high-sensitivity multiplexer packaged in a double-wide NIM module; and flat, shielded ribbon cable consisting of individual twisted pairs. The system multiplexes 30 wires in each of the x and y planes simultaneously and operates with or without computer control. The system has operated in beams of 100 nA to 1 mA, 1- to 120-Hz repetition rate, with a signal-to-noise ratio of greater than 10/1

On the equivalent static loads approach for dynamic response structural optimization

DEFF Research Database (Denmark)

Stolpe, Mathias

2014-01-01

The equivalent static loads algorithm is an increasingly popular approach to solve dynamic response structural optimization problems. The algorithm is based on solving a sequence of related static response structural optimization problems with the same objective and constraint functions...... as the original problem. The optimization theoretical foundation of the algorithm is mainly developed in Park and Kang (J Optim Theory Appl 118(1):191–200, 2003). In that article it is shown, for a certain class of problems, that if the equivalent static loads algorithm terminates then the KKT conditions...

Wolf, Canis lupus, visits to white-tailed deer, Odocoileus virginianus, summer ranges: Optimal foraging?

Science.gov (United States)

Demma, D.J.; Mech, L.D.

2009-01-01

We tested whether Wolf (Canis lupus) visits to individual female White-tailed Deer (Odocoileus virginianus) summer ranges during 2003 and 2004 in northeastern Minnesota were in accord with optimal-foraging theory. Using GPS collars with 10- to 30-minute location attempts on four Wolves and five female deer, plus eleven VHF-collared female deer in the Wolves' territory, provided new insights into the frequency of Wolf visits to summer ranges of female deer. Wolves made a mean 0.055 visits/day to summer ranges of deer three years and older, significantly more than their 0.032 mean visits/day to ranges of two-year-old deer, which generally produce fewer fawns, and most Wolf visits to ranges of older deer were much longer than those to ranges of younger deer. Because fawns comprise the major part of the Wolf's summer diet, this Wolf behavior accords with optimal-foraging theory.

Optimal control of dissipative nonlinear dynamical systems with triggers of coupled singularities

International Nuclear Information System (INIS)

Hedrih, K

2008-01-01

This paper analyses the controllability of motion of nonconservative nonlinear dynamical systems in which triggers of coupled singularities exist or appear. It is shown that the phase plane method is useful for the analysis of nonlinear dynamics of nonconservative systems with one degree of freedom of control strategies and also shows the way it can be used for controlling the relative motion in rheonomic systems having equivalent scleronomic conservative or nonconservative system For the system with one generalized coordinate described by nonlinear differential equation of nonlinear dynamics with trigger of coupled singularities, the functions of system potential energy and conservative force must satisfy some conditions defined by a Theorem on the existence of a trigger of coupled singularities and the separatrix in the form of 'an open a spiral form' of number eight. Task of the defined dynamical nonconservative system optimal control is: by using controlling force acting to the system, transfer initial state of the nonlinear dynamics of the system into the final state of the nonlinear dynamics in the minimal time for that optimal control task

Optimal control of dissipative nonlinear dynamical systems with triggers of coupled singularities

Science.gov (United States)

Stevanović Hedrih, K.

2008-02-01

This paper analyses the controllability of motion of nonconservative nonlinear dynamical systems in which triggers of coupled singularities exist or appear. It is shown that the phase plane method is useful for the analysis of nonlinear dynamics of nonconservative systems with one degree of freedom of control strategies and also shows the way it can be used for controlling the relative motion in rheonomic systems having equivalent scleronomic conservative or nonconservative system For the system with one generalized coordinate described by nonlinear differential equation of nonlinear dynamics with trigger of coupled singularities, the functions of system potential energy and conservative force must satisfy some conditions defined by a Theorem on the existence of a trigger of coupled singularities and the separatrix in the form of "an open a spiral form" of number eight. Task of the defined dynamical nonconservative system optimal control is: by using controlling force acting to the system, transfer initial state of the nonlinear dynamics of the system into the final state of the nonlinear dynamics in the minimal time for that optimal control task

Optimized maritime emergency resource allocation under dynamic demand.

Directory of Open Access Journals (Sweden)

Wenfen Zhang

Full Text Available Emergency resource is important for people evacuation and property rescue when accident occurs. The relief efforts could be promoted by a reasonable emergency resource allocation schedule in advance. As the marine environment is complicated and changeful, the place, type, severity of maritime accident is uncertain and stochastic, bringing about dynamic demand of emergency resource. Considering dynamic demand, how to make a reasonable emergency resource allocation schedule is challenging. The key problem is to determine the optimal stock of emergency resource for supplier centers to improve relief efforts. This paper studies the dynamic demand, and which is defined as a set. Then a maritime emergency resource allocation model with uncertain data is presented. Afterwards, a robust approach is developed and used to make sure that the resource allocation schedule performs well with dynamic demand. Finally, a case study shows that the proposed methodology is feasible in maritime emergency resource allocation. The findings could help emergency manager to schedule the emergency resource allocation more flexibly in terms of dynamic demand.

Effects of sample injection amount and time-of-flight mass spectrometric detection dynamic range on metabolome analysis by high-performance chemical isotope labeling LC-MS.

Science.gov (United States)

Zhou, Ruokun; Li, Liang

2015-04-06

The effect of sample injection amount on metabolome analysis in a chemical isotope labeling (CIL) liquid chromatography-mass spectrometry (LC-MS) platform was investigated. The performance of time-of-flight (TOF) mass spectrometers with and without a high-dynamic-range (HD) detection system was compared in the analysis of (12)C2/(13)C2-dansyl labeled human urine samples. An average of 1635 ± 21 (n = 3) peak pairs or putative metabolites was detected using the HD-TOF-MS, compared to 1429 ± 37 peak pairs from a conventional or non-HD TOF-MS. In both instruments, signal saturation was observed. However, in the HD-TOF-MS, signal saturation was mainly caused by the ionization process, while in the non-HD TOF-MS, it was caused by the detection process. To extend the MS detection range in the non-HD TOF-MS, an automated switching from using (12)C to (13)C-natural abundance peaks for peak ratio calculation when the (12)C peaks are saturated has been implemented in IsoMS, a software tool for processing CIL LC-MS data. This work illustrates that injecting an optimal sample amount is important to maximize the metabolome coverage while avoiding the sample carryover problem often associated with over-injection. A TOF mass spectrometer with an enhanced detection dynamic range can also significantly increase the number of peak pairs detected. In chemical isotope labeling (CIL) LC-MS, relative metabolite quantification is done by measuring the peak ratio of a (13)C2-/(12)C2-labeled peak pair for a given metabolite present in two comparative samples. The dynamic range of peak ratio measurement does not need to be very large, as only subtle changes of metabolite concentrations are encountered in most metabolomic studies where relative metabolome quantification of different groups of samples is performed. However, the absolute concentrations of different metabolites can be very different, requiring a technique to provide a wide detection dynamic range to allow the detection of as

Multidisciplinary Design Optimization Techniques: Implications and Opportunities for Fluid Dynamics Research

Science.gov (United States)

Zang, Thomas A.; Green, Lawrence L.

1999-01-01

A challenge for the fluid dynamics community is to adapt to and exploit the trend towards greater multidisciplinary focus in research and technology. The past decade has witnessed substantial growth in the research field of Multidisciplinary Design Optimization (MDO). MDO is a methodology for the design of complex engineering systems and subsystems that coherently exploits the synergism of mutually interacting phenomena. As evidenced by the papers, which appear in the biannual AIAA/USAF/NASA/ISSMO Symposia on Multidisciplinary Analysis and Optimization, the MDO technical community focuses on vehicle and system design issues. This paper provides an overview of the MDO technology field from a fluid dynamics perspective, giving emphasis to suggestions of specific applications of recent MDO technologies that can enhance fluid dynamics research itself across the spectrum, from basic flow physics to full configuration aerodynamics.

Image Alignment for Multiple Camera High Dynamic Range Microscopy.

Science.gov (United States)

Eastwood, Brian S; Childs, Elisabeth C

2012-01-09

This paper investigates the problem of image alignment for multiple camera high dynamic range (HDR) imaging. HDR imaging combines information from images taken with different exposure settings. Combining information from multiple cameras requires an alignment process that is robust to the intensity differences in the images. HDR applications that use a limited number of component images require an alignment technique that is robust to large exposure differences. We evaluate the suitability for HDR alignment of three exposure-robust techniques. We conclude that image alignment based on matching feature descriptors extracted from radiant power images from calibrated cameras yields the most accurate and robust solution. We demonstrate the use of this alignment technique in a high dynamic range video microscope that enables live specimen imaging with a greater level of detail than can be captured with a single camera.

Discrete Adjoint-Based Design Optimization of Unsteady Turbulent Flows on Dynamic Unstructured Grids

Science.gov (United States)

Nielsen, Eric J.; Diskin, Boris; Yamaleev, Nail K.

2009-01-01

An adjoint-based methodology for design optimization of unsteady turbulent flows on dynamic unstructured grids is described. The implementation relies on an existing unsteady three-dimensional unstructured grid solver capable of dynamic mesh simulations and discrete adjoint capabilities previously developed for steady flows. The discrete equations for the primal and adjoint systems are presented for the backward-difference family of time-integration schemes on both static and dynamic grids. The consistency of sensitivity derivatives is established via comparisons with complex-variable computations. The current work is believed to be the first verified implementation of an adjoint-based optimization methodology for the true time-dependent formulation of the Navier-Stokes equations in a practical computational code. Large-scale shape optimizations are demonstrated for turbulent flows over a tiltrotor geometry and a simulated aeroelastic motion of a fighter jet.

Fuzzy Constrained Predictive Optimal Control of High Speed Train with Actuator Dynamics

Directory of Open Access Journals (Sweden)

Xi Wang

2016-01-01

Full Text Available We investigate the problem of fuzzy constrained predictive optimal control of high speed train considering the effect of actuator dynamics. The dynamics feature of the high speed train is modeled as a cascade of cars connected by flexible couplers, and the formulation is mathematically transformed into a Takagi-Sugeno (T-S fuzzy model. The goal of this study is to design a state feedback control law at each decision step to enhance safety, comfort, and energy efficiency of high speed train subject to safety constraints on the control input. Based on Lyapunov stability theory, the problem of optimizing an upper bound on the cruise control cost function subject to input constraints is reduced to a convex optimization problem involving linear matrix inequalities (LMIs. Furthermore, we analyze the influences of second-order actuator dynamics on the fuzzy constrained predictive controller, which shows risk of potentially deteriorating the overall system. Employing backstepping method, an actuator compensator is proposed to accommodate for the influence of the actuator dynamics. The experimental results show that with the proposed approach high speed train can track the desired speed, the relative coupler displacement between the neighbouring cars is stable at the equilibrium state, and the influence of actuator dynamics is reduced, which demonstrate the validity and effectiveness of the proposed approaches.

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

Science.gov (United States)

Cassandras, Christos G.; Zhuang, Shixin

2005-11-01

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

Volatile decision dynamics: experiments, stochastic description, intermittency control and traffic optimization

Science.gov (United States)

Helbing, Dirk; Schönhof, Martin; Kern, Daniel

2002-06-01

The coordinated and efficient distribution of limited resources by individual decisions is a fundamental, unsolved problem. When individuals compete for road capacities, time, space, money, goods, etc, they normally make decisions based on aggregate rather than complete information, such as TV news or stock market indices. In related experiments, we have observed a volatile decision dynamics and far-from-optimal payoff distributions. We have also identified methods of information presentation that can considerably improve the overall performance of the system. In order to determine optimal strategies of decision guidance by means of user-specific recommendations, a stochastic behavioural description is developed. These strategies manage to increase the adaptibility to changing conditions and to reduce the deviation from the time-dependent user equilibrium, thereby enhancing the average and individual payoffs. Hence, our guidance strategies can increase the performance of all users by reducing overreaction and stabilizing the decision dynamics. These results are highly significant for predicting decision behaviour, for reaching optimal behavioural distributions by decision support systems and for information service providers. One of the promising fields of application is traffic optimization.

Probing the role of long-range interactions in the dynamics of a long-range Kitaev chain

Science.gov (United States)

Dutta, Anirban; Dutta, Amit

2017-09-01

We study the role of long-range interactions (more precisely, the long-range superconducting gap term) on the nonequilibrium dynamics considering a long-range p -wave superconducting chain in which the superconducting term decays with distance between two sites in a power-law fashion characterized by an exponent α . We show that the Kibble-Zurek scaling exponent, dictating the power-law decay of the defect density in the final state reached following a slow (in comparison to the time scale associated with the minimum gap in the spectrum of the Hamiltonian) quenching of the chemical potential μ across a quantum critical point, depends nontrivially on the exponent α as long as α 2 , we find that the exponent saturates to the corresponding well-known value of 1 /2 expected for the short-range model. Furthermore, studying the dynamical quantum phase transitions manifested in the nonanalyticities in the rate function of the return possibility I (t ) in subsequent temporal evolution following a sudden change in μ , we show the existence of a new region; in this region, we find three instants of cusp singularities in I (t ) associated with a single sector of Fisher zeros. Notably, the width of this region shrinks as α increases and vanishes in the limit α →2 , indicating that this special region is an artifact of the long-range nature of the Hamiltonian.

Application of Dynamic Mutated Particle Swarm Optimization Algorithm to Design Water Distribution Networks

Directory of Open Access Journals (Sweden)

Kazem Mohammadi- Aghdam

2015-10-01

Full Text Available This paper proposes the application of a new version of the heuristic particle swarm optimization (PSO method for designing water distribution networks (WDNs. The optimization problem of looped water distribution networks is recognized as an NP-hard combinatorial problem which cannot be easily solved using traditional mathematical optimization techniques. In this paper, the concept of dynamic swarm size is considered in an attempt to increase the convergence speed of the original PSO algorithm. In this strategy, the size of the swarm is dynamically changed according to the iteration number of the algorithm. Furthermore, a novel mutation approach is introduced to increase the diversification property of the PSO and to help the algorithm to avoid trapping in local optima. The new version of the PSO algorithm is called dynamic mutated particle swarm optimization (DMPSO. The proposed DMPSO is then applied to solve WDN design problems. Finally, two illustrative examples are used for comparison to verify the efficiency of the proposed DMPSO as compared to other intelligent algorithms.

Optimal dynamic premium control in non-life insurance. Maximizing dividend pay-outs

DEFF Research Database (Denmark)

Højgaard, Bjarne

2002-01-01

In this paper we consider the problem of finding optimal dynamic premium policies in non-life insurance. The reserve of a company is modeled using the classical Cramér-Lundberg model with premium rates calculated via the expected value principle. The company controls dynamically the relative safety...... loading with the possibility of gaining or loosing customers. It distributes dividends according to a 'barrier strategy' and the objective of the company is to find an optimal premium policy and dividend barrier maximizing the expected total, discounted pay-out of dividends. In the case of exponential...

Neural network for adapting nuclear power plant control for wide-range operation

International Nuclear Information System (INIS)

Ku, C.C.; Lee, K.Y.; Edwards, R.M.

1991-01-01

A new concept of using neural networks has been evaluated for optimal control of a nuclear reactor. The neural network uses the architecture of a standard backpropagation network; however, a new dynamic learning algorithm has been developed to capture the underlying system dynamics. The learning algorithm is based on parameter estimation for dynamic systems. The approach is demonstrated on an optimal reactor temperature controller by adjusting the feedback gains for wide-range operation. Application of optimal control to a reactor has been considered for improving temperature response using a robust fifth-order reactor power controller. Conventional gain scheduling can be employed to extend the range of good performance to accommodate large changes in power where nonlinear characteristics significantly modify the dynamics of the power plant. Gain scheduling is developed based on expected parameter variations, and it may be advantageous to further adapt feedback gains on-line to better match actual plant performance. A neural network approach is used here to adapt the gains to better accommodate plant uncertainties and thereby achieve improved robustness characteristics

Increasing Linear Dynamic Range of a CMOS Image Sensor

Science.gov (United States)

Pain, Bedabrata

2007-01-01

A generic design and a corresponding operating sequence have been developed for increasing the linear-response dynamic range of a complementary metal oxide/semiconductor (CMOS) image sensor. The design provides for linear calibrated dual-gain pixels that operate at high gain at a low signal level and at low gain at a signal level above a preset threshold. Unlike most prior designs for increasing dynamic range of an image sensor, this design does not entail any increase in noise (including fixed-pattern noise), decrease in responsivity or linearity, or degradation of photometric calibration. The figure is a simplified schematic diagram showing the circuit of one pixel and pertinent parts of its column readout circuitry. The conventional part of the pixel circuit includes a photodiode having a small capacitance, CD. The unconventional part includes an additional larger capacitance, CL, that can be connected to the photodiode via a transfer gate controlled in part by a latch. In the high-gain mode, the signal labeled TSR in the figure is held low through the latch, which also helps to adapt the gain on a pixel-by-pixel basis. Light must be coupled to the pixel through a microlens or by back illumination in order to obtain a high effective fill factor; this is necessary to ensure high quantum efficiency, a loss of which would minimize the efficacy of the dynamic- range-enhancement scheme. Once the level of illumination of the pixel exceeds the threshold, TSR is turned on, causing the transfer gate to conduct, thereby adding CL to the pixel capacitance. The added capacitance reduces the conversion gain, and increases the pixel electron-handling capacity, thereby providing an extension of the dynamic range. By use of an array of comparators also at the bottom of the column, photocharge voltages on sampling capacitors in each column are compared with a reference voltage to determine whether it is necessary to switch from the high-gain to the low-gain mode. Depending upon

Dynamic optimization of combined harvesting of a two-species fishery

International Nuclear Information System (INIS)

Chaudhuri, K.

1986-06-01

In the present paper, the author considers the problem of dynamic optimization of the exploitation policy connected with the combined harvesting of two competing fish species, each of which obeys the logistic growth law. The singular extremal trajectory in the phase plane is derived by taking the harvesting effort as a dynamic variable. Biological or bioeconomic interpretations of the constraints required for this singular extremal are also given. (author)

An optimal maintenance policy for machine replacement problem using dynamic programming

Directory of Open Access Journals (Sweden)

Mohsen Sadegh Amalnik

2017-06-01

Full Text Available In this article, we present an acceptance sampling plan for machine replacement problem based on the backward dynamic programming model. Discount dynamic programming is used to solve a two-state machine replacement problem. We plan to design a model for maintenance by consid-ering the quality of the item produced. The purpose of the proposed model is to determine the optimal threshold policy for maintenance in a finite time horizon. We create a decision tree based on a sequential sampling including renew, repair and do nothing and wish to achieve an optimal threshold for making decisions including renew, repair and continue the production in order to minimize the expected cost. Results show that the optimal policy is sensitive to the data, for the probability of defective machines and parameters defined in the model. This can be clearly demonstrated by a sensitivity analysis technique.

TH-EF-BRB-02: Feasibility of Optimization for Dynamic Trajectory Radiotherapy

Energy Technology Data Exchange (ETDEWEB)

Fix, MK; Frei, D; Volken, W; Terribilini, D; Aebersold, DM; Manser, P [Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, and University of Bern, Berne (Switzerland)

2016-06-15

Purpose: Over the last years, volumetric modulated arc therapy (VMAT) has been widely introduced into clinical routine using a coplanar delivery technique. However, VMAT might be improved by including dynamic couch and collimator rotations, leading to dynamic trajectory radiotherapy (DTRT). In this work the feasibility and the potential benefit of DTRT was investigated. Methods: A general framework for the optimization was developed using the Eclipse Scripting Research Application Programming Interface (ESRAPI). Based on contoured target and organs at risk (OARs), the structures are extracted using the ESRAPI. Sampling potential beam directions, regularly distributed on a sphere using a Fibanocci-lattice, the fractional volume-overlap of each OAR and the target is determined and used to establish dynamic gantry-couch movements. Then, for each gantry-couch track the most suitable collimator angle is determined for each control point by optimizing the area between the MLC leaves and the target contour. The resulting dynamic trajectories are used as input to perform the optimization using a research version of the VMAT optimization algorithm and the ESRAPI. The feasibility of this procedure was tested for a clinically motivated head and neck case. Resulting dose distributions for the VMAT plan and for the dynamic trajectory treatment plan were compared based on DVH-parameters. Results: While the DVH for the target is virtually preserved, improvements in maximum dose for the DTRT plan were achieved for all OARs except for the inner-ear, where maximum dose remains the same. The major improvements in maximum dose were 6.5% of the prescribed dose (66 Gy) for the parotid and 5.5% for the myelon and the eye. Conclusion: The result of this work suggests that DTRT has a great potential to reduce dose to OARs with similar target coverage when compared to conventional VMAT treatment plans. This work was supported by Varian Medical Systems. This work was supported by Varian

Low Power High Dynamic Range A/D Conversion Channel

DEFF Research Database (Denmark)

Marker-Villumsen, Niels; Rombach, Pirmin

in the conversion channel in order to avoid distortion for large input signals. In combination with a low resolution A/D converter (ADC) and a digital gain block, the adaptive A/D conversion channel achieves an extended dynamic range beyond that of the ADC. This in turn reduces the current consumption......This work concerns the analysis of an adaptive analog-to-digital (A/D) conversion channel for use with a micro electromechanical system (MEMS) microphone for audio applications. The adaptive A/D conversion channel uses an automatic gain control (AGC) for adjusting the analog preamplifier gain...... of the conversion channel in comparison to a static A/D conversion channel; this at the cost of a reduced peak signal-to-noise ratio (SNR). The adaptive A/D conversion channel compensates for the change in analog gain by a digital gain, thus achieving a constant channel gain in the full dynamic range. However...

Gamut mapping in a high-dynamic-range color space

Science.gov (United States)

Preiss, Jens; Fairchild, Mark D.; Ferwerda, James A.; Urban, Philipp

2014-01-01

In this paper, we present a novel approach of tone mapping as gamut mapping in a high-dynamic-range (HDR) color space. High- and low-dynamic-range (LDR) images as well as device gamut boundaries can simultaneously be represented within such a color space. This enables a unified transformation of the HDR image into the gamut of an output device (in this paper called HDR gamut mapping). An additional aim of this paper is to investigate the suitability of a specific HDR color space to serve as a working color space for the proposed HDR gamut mapping. For the HDR gamut mapping, we use a recent approach that iteratively minimizes an image-difference metric subject to in-gamut images. A psychophysical experiment on an HDR display shows that the standard reproduction workflow of two subsequent transformations - tone mapping and then gamut mapping - may be improved by HDR gamut mapping.

The dynamical core of the Aeolus 1.0 statistical-dynamical atmosphere model: validation and parameter optimization

Science.gov (United States)

Totz, Sonja; Eliseev, Alexey V.; Petri, Stefan; Flechsig, Michael; Caesar, Levke; Petoukhov, Vladimir; Coumou, Dim

2018-02-01

We present and validate a set of equations for representing the atmosphere's large-scale general circulation in an Earth system model of intermediate complexity (EMIC). These dynamical equations have been implemented in Aeolus 1.0, which is a statistical-dynamical atmosphere model (SDAM) and includes radiative transfer and cloud modules (Coumou et al., 2011; Eliseev et al., 2013). The statistical dynamical approach is computationally efficient and thus enables us to perform climate simulations at multimillennia timescales, which is a prime aim of our model development. Further, this computational efficiency enables us to scan large and high-dimensional parameter space to tune the model parameters, e.g., for sensitivity studies.Here, we present novel equations for the large-scale zonal-mean wind as well as those for planetary waves. Together with synoptic parameterization (as presented by Coumou et al., 2011), these form the mathematical description of the dynamical core of Aeolus 1.0.We optimize the dynamical core parameter values by tuning all relevant dynamical fields to ERA-Interim reanalysis data (1983-2009) forcing the dynamical core with prescribed surface temperature, surface humidity and cumulus cloud fraction. We test the model's performance in reproducing the seasonal cycle and the influence of the El Niño-Southern Oscillation (ENSO). We use a simulated annealing optimization algorithm, which approximates the global minimum of a high-dimensional function.With non-tuned parameter values, the model performs reasonably in terms of its representation of zonal-mean circulation, planetary waves and storm tracks. The simulated annealing optimization improves in particular the model's representation of the Northern Hemisphere jet stream and storm tracks as well as the Hadley circulation.The regions of high azonal wind velocities (planetary waves) are accurately captured for all validation experiments. The zonal-mean zonal wind and the integrated lower

Extending the dynamic range of silicon photomultipliers without increasing pixel count

International Nuclear Information System (INIS)

Johnson, Kurtis F.

2010-01-01

A silicon photomultiplier, sometimes called 'multipixel photon counter', which we here refer to as a 'SiPM', is a photo-sensitive device built from an avalanche photodiode array of pixels on a common silicon substrate, such that it can detect single photon events. The dimensions of a pixel may vary from 20 to 100 μm and their density can be greater than 1000 per square millimeter. Each pixel in a SiPM operates in Geiger mode and is coupled to the output by a quenching resistor. Although each pixel operates in digital mode, the SiPM is an analog device because all the pixels are read in parallel, making it possible to generate signals within a dynamic range from a single photon to a large number of photons, ultimately limited by the number of pixels on the chip. In this note we describe a simple and general method of increasing the dynamic range of a SiPM beyond that one may naively assume from the shape of the cumulative distribution function of the SiPM response to the average number of photons per pixel. We show that by rendering the incoming flux of photons to be non-uniform in a prescribed manner, a significant increase in dynamic range is achievable. Such re-distribution of the incoming flux may be accomplished with simple, non-focusing lenses, prisms, interference films, mirrors or attenuating films. Almost any optically non-inert interceding device can increase the dynamic range of the SiPM.

A one-layer recurrent neural network for constrained pseudoconvex optimization and its application for dynamic portfolio optimization.

Science.gov (United States)

Liu, Qingshan; Guo, Zhishan; Wang, Jun

2012-02-01

In this paper, a one-layer recurrent neural network is proposed for solving pseudoconvex optimization problems subject to linear equality and bound constraints. Compared with the existing neural networks for optimization (e.g., the projection neural networks), the proposed neural network is capable of solving more general pseudoconvex optimization problems with equality and bound constraints. Moreover, it is capable of solving constrained fractional programming problems as a special case. The convergence of the state variables of the proposed neural network to achieve solution optimality is guaranteed as long as the designed parameters in the model are larger than the derived lower bounds. Numerical examples with simulation results illustrate the effectiveness and characteristics of the proposed neural network. In addition, an application for dynamic portfolio optimization is discussed. Copyright © 2011 Elsevier Ltd. All rights reserved.

Binaural model-based dynamic-range compression.

Science.gov (United States)

Ernst, Stephan M A; Kortlang, Steffen; Grimm, Giso; Bisitz, Thomas; Kollmeier, Birger; Ewert, Stephan D

2018-01-26

Binaural cues such as interaural level differences (ILDs) are used to organise auditory perception and to segregate sound sources in complex acoustical environments. In bilaterally fitted hearing aids, dynamic-range compression operating independently at each ear potentially alters these ILDs, thus distorting binaural perception and sound source segregation. A binaurally-linked model-based fast-acting dynamic compression algorithm designed to approximate the normal-hearing basilar membrane (BM) input-output function in hearing-impaired listeners is suggested. A multi-center evaluation in comparison with an alternative binaural and two bilateral fittings was performed to assess the effect of binaural synchronisation on (a) speech intelligibility and (b) perceived quality in realistic conditions. 30 and 12 hearing impaired (HI) listeners were aided individually with the algorithms for both experimental parts, respectively. A small preference towards the proposed model-based algorithm in the direct quality comparison was found. However, no benefit of binaural-synchronisation regarding speech intelligibility was found, suggesting a dominant role of the better ear in all experimental conditions. The suggested binaural synchronisation of compression algorithms showed a limited effect on the tested outcome measures, however, linking could be situationally beneficial to preserve a natural binaural perception of the acoustical environment.

Online Energy Management of Plug-In Hybrid Electric Vehicles for Prolongation of All-Electric Range Based on Dynamic Programming

Directory of Open Access Journals (Sweden)

Zeyu Chen

2015-01-01

Full Text Available The employed energy management strategy plays an important role in energy saving performance and exhausted emission reduction of plug-in hybrid electric vehicles (HEVs. An application of dynamic programming for optimization of power allocation is implemented in this paper with certain driving cycle and a limited driving range. Considering the DP algorithm can barely be used in real-time control because of its huge computational task and the dependence on a priori driving cycle, several online useful control rules are established based on the offline optimization results of DP. With the above efforts, an online energy management strategy is proposed finally. The presented energy management strategy concerns the prolongation of all-electric driving range as well as the energy saving performance. A simulation study is deployed to evaluate the control performance of the proposed energy management approach. All-electric range of the plug-in HEV can be prolonged by up to 2.86% for a certain driving condition. The energy saving performance is relative to the driving distance. The presented energy management strategy brings a little higher energy cost when driving distance is short, but for a long driving distance, it can reduce the energy consumption by up to 5.77% compared to the traditional CD-CS strategy.

Dynamic emulation modelling for the optimal operation of water systems: an overview

Science.gov (United States)

Castelletti, A.; Galelli, S.; Giuliani, M.

2014-12-01

Despite sustained increase in computing power over recent decades, computational limitations remain a major barrier to the effective and systematic use of large-scale, process-based simulation models in rational environmental decision-making. Whereas complex models may provide clear advantages when the goal of the modelling exercise is to enhance our understanding of the natural processes, they introduce problems of model identifiability caused by over-parameterization and suffer from high computational burden when used in management and planning problems. As a result, increasing attention is now being devoted to emulation modelling (or model reduction) as a way of overcoming these limitations. An emulation model, or emulator, is a low-order approximation of the process-based model that can be substituted for it in order to solve high resource-demanding problems. In this talk, an overview of emulation modelling within the context of the optimal operation of water systems will be provided. Particular emphasis will be given to Dynamic Emulation Modelling (DEMo), a special type of model complexity reduction in which the dynamic nature of the original process-based model is preserved, with consequent advantages in a wide range of problems, particularly feedback control problems. This will be contrasted with traditional non-dynamic emulators (e.g. response surface and surrogate models) that have been studied extensively in recent years and are mainly used for planning purposes. A number of real world numerical experiences will be used to support the discussion ranging from multi-outlet water quality control in water reservoir through erosion/sedimentation rebalancing in the operation of run-off-river power plants to salinity control in lake and reservoirs.

A high speed, wide dynamic range digitizer circuit for photomultiplier tubes

International Nuclear Information System (INIS)

Yarema, R.J.; Foster, G.W.; Knickerbocker, K.; Sarraj, M.; Tschirhart, R.; Whitmore, J.; Zimmerman, T.; Lindgren, M.

1995-01-01

A circuit has been designed for digitizing PMT signals over a wide dynamic range (17-18 bits) with 8 bits of resolution at rates up to 53 MHz. Output from the circuit is in a floating point format with a 4 bit exponent and an 8 bit mantissa. The heart of the circuit is a full custom integrated circuit called the QIE (Charge Integrator and Encoder). The design of the QIE and associated circuitry reported here permits operation over a 17 bit dynamic range. Test results of a multirange device are presented for the first time. (orig.)

An Adaptive Genetic Algorithm with Dynamic Population Size for Optimizing Join Queries

OpenAIRE

Vellev, Stoyan

2008-01-01

The problem of finding the optimal join ordering executing a query to a relational database management system is a combinatorial optimization problem, which makes deterministic exhaustive solution search unacceptable for queries with a great number of joined relations. In this work an adaptive genetic algorithm with dynamic population size is proposed for optimizing large join queries. The performance of the algorithm is compared with that of several classical non-determinis...

Doubly Robust Estimation of Optimal Dynamic Treatment Regimes

DEFF Research Database (Denmark)

Barrett, Jessica K; Henderson, Robin; Rosthøj, Susanne

2014-01-01

We compare methods for estimating optimal dynamic decision rules from observational data, with particular focus on estimating the regret functions defined by Murphy (in J. R. Stat. Soc., Ser. B, Stat. Methodol. 65:331-355, 2003). We formulate a doubly robust version of the regret-regression appro......We compare methods for estimating optimal dynamic decision rules from observational data, with particular focus on estimating the regret functions defined by Murphy (in J. R. Stat. Soc., Ser. B, Stat. Methodol. 65:331-355, 2003). We formulate a doubly robust version of the regret......-regression approach of Almirall et al. (in Biometrics 66:131-139, 2010) and Henderson et al. (in Biometrics 66:1192-1201, 2010) and demonstrate that it is equivalent to a reduced form of Robins' efficient g-estimation procedure (Robins, in Proceedings of the Second Symposium on Biostatistics. Springer, New York, pp....... 189-326, 2004). Simulation studies suggest that while the regret-regression approach is most efficient when there is no model misspecification, in the presence of misspecification the efficient g-estimation procedure is more robust. The g-estimation method can be difficult to apply in complex...

Bidirectional Dynamic Diversity Evolutionary Algorithm for Constrained Optimization

Directory of Open Access Journals (Sweden)

Weishang Gao

2013-01-01

Full Text Available Evolutionary algorithms (EAs were shown to be effective for complex constrained optimization problems. However, inflexible exploration-exploitation and improper penalty in EAs with penalty function would lead to losing the global optimum nearby or on the constrained boundary. To determine an appropriate penalty coefficient is also difficult in most studies. In this paper, we propose a bidirectional dynamic diversity evolutionary algorithm (Bi-DDEA with multiagents guiding exploration-exploitation through local extrema to the global optimum in suitable steps. In Bi-DDEA potential advantage is detected by three kinds of agents. The scale and the density of agents will change dynamically according to the emerging of potential optimal area, which play an important role of flexible exploration-exploitation. Meanwhile, a novel double optimum estimation strategy with objective fitness and penalty fitness is suggested to compute, respectively, the dominance trend of agents in feasible region and forbidden region. This bidirectional evolving with multiagents can not only effectively avoid the problem of determining penalty coefficient but also quickly converge to the global optimum nearby or on the constrained boundary. By examining the rapidity and veracity of Bi-DDEA across benchmark functions, the proposed method is shown to be effective.

Distributed Optimal Consensus Control for Nonlinear Multiagent System With Unknown Dynamic.

Science.gov (United States)

Zhang, Jilie; Zhang, Huaguang; Feng, Tao

2017-08-01

This paper focuses on the distributed optimal cooperative control for continuous-time nonlinear multiagent systems (MASs) with completely unknown dynamics via adaptive dynamic programming (ADP) technology. By introducing predesigned extra compensators, the augmented neighborhood error systems are derived, which successfully circumvents the system knowledge requirement for ADP. It is revealed that the optimal consensus protocols actually work as the solutions of the MAS differential game. Policy iteration algorithm is adopted, and it is theoretically proved that the iterative value function sequence strictly converges to the solution of the coupled Hamilton-Jacobi-Bellman equation. Based on this point, a novel online iterative scheme is proposed, which runs based on the data sampled from the augmented system and the gradient of the value function. Neural networks are employed to implement the algorithm and the weights are updated, in the least-square sense, to the ideal value, which yields approximated optimal consensus protocols. Finally, a numerical example is given to illustrate the effectiveness of the proposed scheme.

Sensitivity and Dynamic Range Considerations for Homodyne Detection Systems

DEFF Research Database (Denmark)

Jaggard, Dwight L.; King, Ray J

1973-01-01

The effects of modulation frequency, RF reference power, and external bias upon the sensitivity and dynamic range of microwave homodyne detection systems was measured for point contact diodes and low l/f noise Schottky and backward diodes. The measurements were made at 4.89 GHz using a signal...... to noise ratio of 3 dB and a detection system bandwidth of 10 Hz. Maximum sensitivities of -135, -150, and -145 dBm, and dynamic ranges of 92, 110, and 124 dB were measured for the point contact, Schottky, and backward diodes at modulation frequencies of 30, 30, and 3 kHz, respectively. It was found...... that the level of RF reference signal needed to obtain the maximum sensitivity was equal to or somewhat above the point where the diode changes from square law to linear detection. The results are significant in that previously reported homodyne sensitivities (not necessarily maximum) were on the order of -90...

Thermal and dynamic range characterization of a photonics-based RF amplifier

Science.gov (United States)

Noque, D. F.; Borges, R. M.; Muniz, A. L. M.; Bogoni, A.; Cerqueira S., Arismar, Jr.

2018-05-01

This work reports a thermal and dynamic range characterization of an ultra-wideband photonics-based RF amplifier for microwave and mm-waves future 5G optical-wireless networks. The proposed technology applies the four-wave mixing nonlinear effect to provide RF amplification in analog and digital radio-over-fiber systems. The experimental analysis from 300 kHz to 50 GHz takes into account different figures of merit, such as RF gain, spurious-free dynamic range and RF output power stability as a function of temperature. The thermal characterization from -10 to +70 °C demonstrates a 27 dB flat photonics-assisted RF gain over the entire frequency range under real operational conditions of a base station for illustrating the feasibility of the photonics-assisted RF amplifier for 5G networks.

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

Science.gov (United States)

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.

Optimal dynamic pricing and replenishment policy for perishable items with inventory-level-dependent demand

Science.gov (United States)

Lu, Lihao; Zhang, Jianxiong; Tang, Wansheng

2016-04-01

An inventory system for perishable items with limited replenishment capacity is introduced in this paper. The demand rate depends on the stock quantity displayed in the store as well as the sales price. With the goal to realise profit maximisation, an optimisation problem is addressed to seek for the optimal joint dynamic pricing and replenishment policy which is obtained by solving the optimisation problem with Pontryagin's maximum principle. A joint mixed policy, in which the sales price is a static decision variable and the replenishment rate remains to be a dynamic decision variable, is presented to compare with the joint dynamic policy. Numerical results demonstrate the advantages of the joint dynamic one, and further show the effects of different system parameters on the optimal joint dynamic policy and the maximal total profit.

Nonlinear dynamics optimization with particle swarm and genetic algorithms for SPEAR3 emittance upgrade

International Nuclear Information System (INIS)

Huang, Xiaobiao; Safranek, James

2014-01-01

Nonlinear dynamics optimization is carried out for a low emittance upgrade lattice of SPEAR3 in order to improve its dynamic aperture and Touschek lifetime. Two multi-objective optimization algorithms, a genetic algorithm and a particle swarm algorithm, are used for this study. The performance of the two algorithms are compared. The result shows that the particle swarm algorithm converges significantly faster to similar or better solutions than the genetic algorithm and it does not require seeding of good solutions in the initial population. These advantages of the particle swarm algorithm may make it more suitable for many accelerator optimization applications

Nonlinear dynamics optimization with particle swarm and genetic algorithms for SPEAR3 emittance upgrade

Energy Technology Data Exchange (ETDEWEB)

Huang, Xiaobiao, E-mail: xiahuang@slac.stanford.edu; Safranek, James

2014-09-01

Nonlinear dynamics optimization is carried out for a low emittance upgrade lattice of SPEAR3 in order to improve its dynamic aperture and Touschek lifetime. Two multi-objective optimization algorithms, a genetic algorithm and a particle swarm algorithm, are used for this study. The performance of the two algorithms are compared. The result shows that the particle swarm algorithm converges significantly faster to similar or better solutions than the genetic algorithm and it does not require seeding of good solutions in the initial population. These advantages of the particle swarm algorithm may make it more suitable for many accelerator optimization applications.

Optimally combining dynamical decoupling and quantum error correction.

Science.gov (United States)

Paz-Silva, Gerardo A; Lidar, D A

2013-01-01

Quantum control and fault-tolerant quantum computing (FTQC) are two of the cornerstones on which the hope of realizing a large-scale quantum computer is pinned, yet only preliminary steps have been taken towards formalizing the interplay between them. Here we explore this interplay using the powerful strategy of dynamical decoupling (DD), and show how it can be seamlessly and optimally integrated with FTQC. To this end we show how to find the optimal decoupling generator set (DGS) for various subspaces relevant to FTQC, and how to simultaneously decouple them. We focus on stabilizer codes, which represent the largest contribution to the size of the DGS, showing that the intuitive choice comprising the stabilizers and logical operators of the code is in fact optimal, i.e., minimizes a natural cost function associated with the length of DD sequences. Our work brings hybrid DD-FTQC schemes, and their potentially considerable advantages, closer to realization.

Developing a computationally efficient dynamic multilevel hybrid optimization scheme using multifidelity model interactions.

Energy Technology Data Exchange (ETDEWEB)

Hough, Patricia Diane (Sandia National Laboratories, Livermore, CA); Gray, Genetha Anne (Sandia National Laboratories, Livermore, CA); Castro, Joseph Pete Jr. (; .); Giunta, Anthony Andrew

2006-01-01

Many engineering application problems use optimization algorithms in conjunction with numerical simulators to search for solutions. The formulation of relevant objective functions and constraints dictate possible optimization algorithms. Often, a gradient based approach is not possible since objective functions and constraints can be nonlinear, nonconvex, non-differentiable, or even discontinuous and the simulations involved can be computationally expensive. Moreover, computational efficiency and accuracy are desirable and also influence the choice of solution method. With the advent and increasing availability of massively parallel computers, computational speed has increased tremendously. Unfortunately, the numerical and model complexities of many problems still demand significant computational resources. Moreover, in optimization, these expenses can be a limiting factor since obtaining solutions often requires the completion of numerous computationally intensive simulations. Therefore, we propose a multifidelity optimization algorithm (MFO) designed to improve the computational efficiency of an optimization method for a wide range of applications. In developing the MFO algorithm, we take advantage of the interactions between multi fidelity models to develop a dynamic and computational time saving optimization algorithm. First, a direct search method is applied to the high fidelity model over a reduced design space. In conjunction with this search, a specialized oracle is employed to map the design space of this high fidelity model to that of a computationally cheaper low fidelity model using space mapping techniques. Then, in the low fidelity space, an optimum is obtained using gradient or non-gradient based optimization, and it is mapped back to the high fidelity space. In this paper, we describe the theory and implementation details of our MFO algorithm. We also demonstrate our MFO method on some example problems and on two applications: earth penetrators and

A Low-Power High-Dynamic-Range Receiver System for In-Probe 3-D Ultrasonic Imaging.

Science.gov (United States)

Attarzadeh, Hourieh; Xu, Ye; Ytterdal, Trond

2017-10-01

In this paper, a dual-mode low-power, high dynamic-range receiver circuit is designed for the interface with a capacitive micromachined ultrasonic transducer. The proposed ultrasound receiver chip enables the development of an in-probe digital beamforming imaging system. The flexibility of having two operation modes offers a high dynamic range with minimum power sacrifice. A prototype of the chip containing one receive channel, with one variable transimpedance amplifier (TIA) and one analog to digital converter (ADC) circuit is implemented. Combining variable gain TIA functionality with ADC gain settings achieves an enhanced overall high dynamic range, while low power dissipation is maintained. The chip is designed and fabricated in a 65 nm standard CMOS process technology. The test chip occupies an area of 76[Formula: see text] 170 [Formula: see text]. A total average power range of 60-240 [Formula: see text] for a sampling frequency of 30 MHz, and a center frequency of 5 MHz is measured. An instantaneous dynamic range of 50.5 dB with an overall dynamic range of 72 dB is obtained from the receiver circuit.

A high speed, wide dynamic range digitizer circuit for photomultiplier tubes

Energy Technology Data Exchange (ETDEWEB)

Yarema, R.J.; Foster, G.W.; Knickerbocker, K.; Sarraj, M.; Tschirhart, R.; Whitmore, J.; Zimmerman, T. [Fermi National Accelerator Lab., Batavia, IL (United States); Lindgren, M. [Univ. of California, Los Angeles, CA (United States). Physics Dept.

1994-06-01

High energy physics experiments running at high interaction rates frequently require long record lengths for determining a level 1 trigger. The easiest way to provide a long event record is by digital means. In applications requiring wide dynamic range, however, digitization of an analog signal to obtain the digital record has been impossible due to lack of high speed, wide range FADCs. One such application is the readout of thousands of photomultiplier tubes in fixed target and colliding beam experiment calorimeters. A circuit has been designed for digitizing PMT signals over a wide dynamic range (17--18 bits) with 8 bits of resolution at rates up to 53 MHz. Output from the circuit is in a floating point format with a 4 bit exponent and an 8 bit mantissa. The heart of the circuit is a full custom integrated circuit called the QIE (Charge Integrator and Encoder). The design of the QIE and associated circuitry reported here permits operation over a 17 bit dynamic range. Tests of the circuit with a PMT input and a pulsed laser have provided respectable results with little off line correction. Performance of the circuit for demanding applications can be significantly enhanced with additional off line correction. Circuit design, packaging issues, and test results of a multirange device are presented for the first time.

A high speed, wide dynamic range digitizer circuit for photomultiplier tubes

International Nuclear Information System (INIS)

Yarema, R.J.; Foster, G.W.; Knickerbocker, K.; Sarraj, M.; Tschirhart, R.; Whitmore, J.; Zimmerman, T.; Lindgren, M.

1994-06-01

High energy physics experiments running at high interaction rates frequently require long record lengths for determining a level 1 trigger. The easiest way to provide a long event record is by digital means. In applications requiring wide dynamic range, however, digitization of an analog signal to obtain the digital record has been impossible due to lack of high speed, wide range FADCs. One such application is the readout of thousands of photomultiplier tubes in fixed target and colliding beam experiment calorimeters. A circuit has been designed for digitizing PMT signals over a wide dynamic range (17--18 bits) with 8 bits of resolution at rates up to 53 MHz. Output from the circuit is in a floating point format with a 4 bit exponent and an 8 bit mantissa. The heart of the circuit is a full custom integrated circuit called the QIE (Charge Integrator and Encoder). The design of the QIE and associated circuitry reported here permits operation over a 17 bit dynamic range. Tests of the circuit with a PMT input and a pulsed laser have provided respectable results with little off line correction. Performance of the circuit for demanding applications can be significantly enhanced with additional off line correction. Circuit design, packaging issues, and test results of a multirange device are presented for the first time

A dynamic optimization on economic energy efficiency in development: A numerical case of China

International Nuclear Information System (INIS)

Wang, Dong

2014-01-01

This paper is based on dynamic optimization methodology to investigate the economic energy efficiency issues in developing countries. The paper introduces some definitions about energy efficiency both in economics and physics, and establishes a quantitative way for measuring the economic energy efficiency. The linkage between economic energy efficiency, energy consumption and other macroeconomic variables is demonstrated primarily. Using the methodology of dynamic optimization, a maximum problem of economic energy efficiency over time, which is subjected to the extended Solow growth model and instantaneous investment rate, is modelled. In this model, the energy consumption is set as a control variable and the capital is regarded as a state variable. The analytic solutions can be derived and the diagrammatic analysis provides saddle-point equilibrium. A numerical simulation based on China is also presented; meanwhile, the optimal paths of investment and energy consumption can be drawn. The dynamic optimization encourages governments in developing countries to pursue higher economic energy efficiency by controlling the energy consumption and regulating the investment state as it can conserve energy without influencing the achievement of steady state in terms of Solow model. If that, a sustainable development will be achieved. - Highlights: • A new definition on economic energy efficiency is proposed mathematically. • A dynamic optimization modelling links economic energy efficiency with other macroeconomic variables in long run. • Economic energy efficiency is determined by capital stock level and energy consumption. • Energy saving is a key solution for improving economic energy efficiency

Optimization of Measurements on Dynamically Sensitive Structures Using a Reliability Approach

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune

Design of a measuring program devoted to parameter identification of structural dynamic systems described by random fields is considered. The design problem is formulated as an optimization problem to minimize the total expected costs due to failure and costs of a measuring program. Design variab...... variables are the numbers of measuring points, the locations of these points and the required number of sample records. An example with a simply supported plane, vibrating beam is considered and tentative results are presented.......Design of a measuring program devoted to parameter identification of structural dynamic systems described by random fields is considered. The design problem is formulated as an optimization problem to minimize the total expected costs due to failure and costs of a measuring program. Design...

Optimization of Measurements on Dynamically Sensitive Structures Using a Reliability Approach

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune

1990-01-01

Design of measuring program devoted to parameter identification of structural dynamic systems described by random fields is considered. The design problem is formulated as an optimization problem to minimize the total expected costs due to failure and costs of masuring program. Design variables a...... are the numbers of measuring points, the locations of these points and the required number of sample records. An example with a simply supported plane, vibrating beam is considered and tentative results are presented.......Design of measuring program devoted to parameter identification of structural dynamic systems described by random fields is considered. The design problem is formulated as an optimization problem to minimize the total expected costs due to failure and costs of masuring program. Design variables...

Dynamic optimization of a biped model: Energetic walking gaits with different mechanical and gait parameters

Directory of Open Access Journals (Sweden)

Kang An

2015-05-01

Full Text Available Energy consumption is one of the problems for bipedal robots walking. For the purpose of studying the parameter effects on the design of energetic walking bipeds with strong adaptability, we use a dynamic optimization method on our new walking model to first investigate the effects of the mechanical parameters, including mass and length distribution, on the walking efficiency. Then, we study the energetic walking gait features with the combinations of walking speed and step length. Our walking model is designed upon Srinivasan’s model. Dynamic optimization is used for a free search with minimal constraints. The results show that the cost of transport of a certain gait increases with the increase in the mass and length distribution parameters, except for that the cost of transport decreases with big length distribution parameter and long step length. We can also find a corresponding range of walking speed and step length, in which the variation in one of the two parameters has no obvious effect on the cost of transport. With fixed mechanical parameters, the cost of transport increases with the increase in the walking speed. There is a speed–step length relationship for walking with minimal cost of transport. The hip torque output strategy is adjusted in two situations to meet the walking requirements.

Optimized Bayesian dynamic advising theory and algorithms

CERN Document Server

Karny, Miroslav

2006-01-01

Written by one of the world's leading groups in the area of Bayesian identification, control, and decision making, this book provides the theoretical and algorithmic basis of optimized probabilistic advising. Starting from abstract ideas and formulations, and culminating in detailed algorithms, the book comprises a unified treatment of an important problem of the design of advisory systems supporting supervisors of complex processes. It introduces the theoretical and algorithmic basis of developed advising, relying on novel and powerful combination black-box modelling by dynamic mixture models

SEWER NETWORK DISCHARGE OPTIMIZATION USING THE DYNAMIC PROGRAMMING

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Viorel MINZU

2015-12-01

Full Text Available It is necessary to adopt an optimal control that allows an efficient usage of the existing sewer networks, in order to avoid the building of new retention facilities. The main objective of the control action is to minimize the overflow volume of a sewer network. This paper proposes a method to apply a solution obtained by discrete dynamic programming through a realistic closed loop system.

Comparison of kinematic and dynamic leg trajectory optimization techniques for biped robot locomotion

Science.gov (United States)

Khusainov, R.; Klimchik, A.; Magid, E.

2017-01-01

The paper presents comparison analysis of two approaches in defining leg trajectories for biped locomotion. The first one operates only with kinematic limitations of leg joints and finds the maximum possible locomotion speed for given limits. The second approach defines leg trajectories from the dynamic stability point of view and utilizes ZMP criteria. We show that two methods give different trajectories and demonstrate that trajectories based on pure dynamic optimization cannot be realized due to joint limits. Kinematic optimization provides unstable solution which can be balanced by upper body movement.

A dynamic range upgrade for neutron backscattering spectroscopy

International Nuclear Information System (INIS)

Cook, J.C.; Petry, W.; Heidemann, A.; Barthelemy, J.F.

1992-01-01

We report on an instrumental development of the cold neutron backscattering spectrometer IN10 at the Institut Laue-Langevin which has led to a significant increase in its dynamic range. Thermal expansion of a variety of neutron monochromator crystals is used instead of a mechanical oscillation of the monochromator, yielding an increase in the energy transfer range by nearly two orders of magnitude in an elastic wave vector transfer range of 0.07≤Q (A -1 )≤2.0. Using this new configuration, first inelastic measurements have been performed using the (200) reflections from KCl and NaCl monochromators with crystal temperatures between 80 K and 700 K. The thermal expansion of these crystals in this temperature range gives rise to energy transfer ranges (neutron energy gain) of -16<ℎω(μeV)<+83 for KCl and -530<ℎω(μeV)<-420 for NaCl with energy resolution (FWHM) of around 0.6 and 1.4 μeV for KCl and NaCl respectively. These figures represent the highest energy resolution currently available at these energy and wave vector transfers. (orig.)

Dynamical optimization techniques for the calculation of electronic structure in solids

International Nuclear Information System (INIS)

Benedek, R.; Min, B.I.; Garner, J.

1989-01-01

The method of dynamical simulated annealing, recently introduced by Car and Parrinello, provides a new tool for electronic structure computation as well as for molecular dynamics simulation. In this paper, we explore an optimization technique that is complementary to dynamical simulated annealing, the method of steepest descents (SD). As an illustration, SD is applied to calculate the total energy of diamond-Si, a system previously treated by Car and Parrinello. The adaptation of SD to treat metallic systems is discussed and a numerical application is presented. (author) 18 refs., 3 figs

Energy Optimization in Smart Homes Using Customer Preference and Dynamic Pricing

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Muhammad Babar Rasheed

2016-07-01

Full Text Available In this paper, we present an energy optimization technique to schedule three types of household appliances (user dependent, interactive schedulable and unschedulable in response to the dynamic behaviours of customers, electricity prices and weather conditions. Our optimization technique schedules household appliances in real time to optimally control their energy consumption, such that the electricity bills of end users are reduced while not compromising on user comfort. More specifically, we use the binary multiple knapsack problem formulation technique to design an objective function, which is solved via the constraint optimization technique. Simulation results show that average aggregated energy savings with and without considering the human presence control system are 11.77% and 5.91%, respectively.

A parameters optimization method for planar joint clearance model and its application for dynamics simulation of reciprocating compressor

Science.gov (United States)

Hai-yang, Zhao; Min-qiang, Xu; Jin-dong, Wang; Yong-bo, Li

2015-05-01

In order to improve the accuracy of dynamics response simulation for mechanism with joint clearance, a parameter optimization method for planar joint clearance contact force model was presented in this paper, and the optimized parameters were applied to the dynamics response simulation for mechanism with oversized joint clearance fault. By studying the effect of increased clearance on the parameters of joint clearance contact force model, the relation of model parameters between different clearances was concluded. Then the dynamic equation of a two-stage reciprocating compressor with four joint clearances was developed using Lagrange method, and a multi-body dynamic model built in ADAMS software was used to solve this equation. To obtain a simulated dynamic response much closer to that of experimental tests, the parameters of joint clearance model, instead of using the designed values, were optimized by genetic algorithms approach. Finally, the optimized parameters were applied to simulate the dynamics response of model with oversized joint clearance fault according to the concluded parameter relation. The dynamics response of experimental test verified the effectiveness of this application.

Extensions of Dynamic Programming: Decision Trees, Combinatorial Optimization, and Data Mining

KAUST Repository

Hussain, Shahid

2016-01-01

This thesis is devoted to the development of extensions of dynamic programming to the study of decision trees. The considered extensions allow us to make multi-stage optimization of decision trees relative to a sequence of cost functions, to count the number of optimal trees, and to study relationships: cost vs cost and cost vs uncertainty for decision trees by construction of the set of Pareto-optimal points for the corresponding bi-criteria optimization problem. The applications include study of totally optimal (simultaneously optimal relative to a number of cost functions) decision trees for Boolean functions, improvement of bounds on complexity of decision trees for diagnosis of circuits, study of time and memory trade-off for corner point detection, study of decision rules derived from decision trees, creation of new procedure (multi-pruning) for construction of classifiers, and comparison of heuristics for decision tree construction. Part of these extensions (multi-stage optimization) was generalized to well-known combinatorial optimization problems: matrix chain multiplication, binary search trees, global sequence alignment, and optimal paths in directed graphs.

Extensions of Dynamic Programming: Decision Trees, Combinatorial Optimization, and Data Mining

KAUST Repository

Hussain, Shahid

2016-07-10

This thesis is devoted to the development of extensions of dynamic programming to the study of decision trees. The considered extensions allow us to make multi-stage optimization of decision trees relative to a sequence of cost functions, to count the number of optimal trees, and to study relationships: cost vs cost and cost vs uncertainty for decision trees by construction of the set of Pareto-optimal points for the corresponding bi-criteria optimization problem. The applications include study of totally optimal (simultaneously optimal relative to a number of cost functions) decision trees for Boolean functions, improvement of bounds on complexity of decision trees for diagnosis of circuits, study of time and memory trade-off for corner point detection, study of decision rules derived from decision trees, creation of new procedure (multi-pruning) for construction of classifiers, and comparison of heuristics for decision tree construction. Part of these extensions (multi-stage optimization) was generalized to well-known combinatorial optimization problems: matrix chain multiplication, binary search trees, global sequence alignment, and optimal paths in directed graphs.

Dynamic programming for optimization of timber production and grazing in ponderosa pine

Science.gov (United States)

Kurt H. Riitters; J. Douglas Brodie; David W. Hann

1982-01-01

Dynamic programming procedures are presented for optimizing thinning and rotation of even-aged ponderosa pine by using the four descriptors: age, basal area, number of trees, and time since thinning. Because both timber yield and grazing yield are functions of stand density, the two outputs-forage and timber-can both be optimized. The soil expectation values for single...

Optimal Stochastic Control Problem for General Linear Dynamical Systems in Neuroscience

Directory of Open Access Journals (Sweden)

Yan Chen

2017-01-01

Full Text Available This paper considers a d-dimensional stochastic optimization problem in neuroscience. Suppose the arm’s movement trajectory is modeled by high-order linear stochastic differential dynamic system in d-dimensional space, the optimal trajectory, velocity, and variance are explicitly obtained by using stochastic control method, which allows us to analytically establish exact relationships between various quantities. Moreover, the optimal trajectory is almost a straight line for a reaching movement; the optimal velocity bell-shaped and the optimal variance are consistent with the experimental Fitts law; that is, the longer the time of a reaching movement, the higher the accuracy of arriving at the target position, and the results can be directly applied to designing a reaching movement performed by a robotic arm in a more general environment.

Global optimization for quantum dynamics of few-fermion systems

Science.gov (United States)

Li, Xikun; Pecak, Daniel; Sowiński, Tomasz; Sherson, Jacob; Nielsen, Anne E. B.

2018-03-01

Quantum state preparation is vital to quantum computation and quantum information processing tasks. In adiabatic state preparation, the target state is theoretically obtained with nearly perfect fidelity if the control parameter is tuned slowly enough. As this, however, leads to slow dynamics, it is often desirable to be able to carry out processes more rapidly. In this work, we employ two global optimization methods to estimate the quantum speed limit for few-fermion systems confined in a one-dimensional harmonic trap. Such systems can be produced experimentally in a well-controlled manner. We determine the optimized control fields and achieve a reduction in the ramping time of more than a factor of four compared to linear ramping. We also investigate how robust the fidelity is to small variations of the control fields away from the optimized shapes.

Quantum optimal control theory and dynamic coupling in the spin-boson model

International Nuclear Information System (INIS)

Jirari, H.; Poetz, W.

2006-01-01

A Markovian master equation describing the evolution of open quantum systems in the presence of a time-dependent external field is derived within the Bloch-Redfield formalism. It leads to a system-bath interaction which depends on the control field. Optimal control theory is used to select control fields which allow accelerated or decelerated system relaxation, or suppression of relaxation (dissipation) altogether, depending on the dynamics we impose on the quantum system. The control-dissipation correlation and the nonperturbative treatment of the control field are essential for reaching this goal. The optimal control problem is formulated within Pontryagin's minimum principle and the resulting optimal differential system is solved numerically. As an application, we study the dynamics of a spin-boson model in the strong coupling regime under the influence of an external control field. We show how trapping the system in unstable quantum states and transfer of population can be achieved by optimized control of the dissipative quantum system. We also used optimal control theory to find the driving field that generates the quantum Z gate. In several cases studied, we find that the selected optimal field which reduces the purity loss significantly is a multicomponent low-frequency field including higher harmonics, all of which lie below the phonon cutoff frequency. Finally, in the undriven case we present an analytic result for the Lamb shift at zero temperature

Transmission dynamic range in chest radiology

International Nuclear Information System (INIS)

Lemmers, H.E.A.S.J.; Schultze Kool, L.J.; van Elburg, H.J.; Boelens, F.

1989-01-01

Due to the large difference in transmission between the lung area and the mediastinum, the human chest is a challenging object for radiographic imaging. This study is performed in order to define the dynamic range needed for a chest imaging chain. Eight hundred seventy-five consecutive outpatients were imaged with a prototype AMBER (advanced multiple beam equalization radiography) unit at 141 kVp. The equalization facility was disabled, allowing for the simultaneous capture of a film image and a digital dataset representing the local patient transmission in fields of approximately 2x2 cm. The datasets were analyzed to obtain the relation between the average transmission distribution in a subset of the population and physical parameters characterizing this subset, such as body weight or length

Comparison of linear intrascan and interscan dynamic ranges of Orbitrap and ion-mobility time-of-flight mass spectrometers.

Science.gov (United States)

Kaufmann, Anton; Walker, Stephan

2017-11-30

The linear intrascan and interscan dynamic ranges of mass spectrometers are important in metabolome and residue analysis. A large linear dynamic range is mandatory if both low- and high-abundance ions have to be detected and quantitated in heavy matrix samples. These performance criteria, as provided by modern high-resolution mass spectrometry (HRMS), were systematically investigated. The comparison included two generations of Orbitraps, and an ion mobility quadrupole time-of-flight (QTOF) system In addition, different scan modes, as provided by the utilized instruments, were investigated. Calibration curves of different compounds covering a concentration range of five orders of magnitude were measured to evaluate the linear interscan dynamic range. The linear intrascan dynamic range and the resulting mass accuracy were evaluated by repeating these measurements in the presence of a very intense background. Modern HRMS instruments can show linear dynamic ranges of five orders of magnitude. Often, however, the linear dynamic range is limited by the detection capability (sensitivity and selectivity) and by the electrospray ionization. Orbitraps, as opposed to TOF instruments, show a reduced intrascan dynamic range. This is due to the limited C-trap and Orbitrap capacity. The tested TOF instrument shows poorer mass accuracies than the Orbitraps. In contrast, hyphenation with an ion-mobility device seems not to affect the linear dynamic range. The linear dynamic range of modern HRMS instrumentation has been significantly improved. This also refers to the virtual absence of systematic mass shifts at high ion abundances. The intrascan dynamic range of the current Orbitrap technology may still be a limitation when analyzing complex matrix extracts. On the other hand, the linear dynamic range is not only limited by the detector technology, but can also be shortened by peripheral devices, where the ionization and transfer of ions take place. Copyright © 2017 John Wiley

Product quality driven design of bakery operations using dynamic optimization

NARCIS (Netherlands)

Hadiyanto, M.; Esveld, D.C.; Boom, R.M.; Straten, van G.; Boxtel, van A.J.B.

2008-01-01

Abstract Quality driven design uses specified product qualities as a starting point for process design. By backward reasoning the required process conditions and processing system were found. In this work dynamic optimization was used as a tool to generate processing solutions for baking processes

Fractional quantum mechanics on networks: Long-range dynamics and quantum transport.

Science.gov (United States)

Riascos, A P; Mateos, José L

2015-11-01

In this paper we study the quantum transport on networks with a temporal evolution governed by the fractional Schrödinger equation. We generalize the dynamics based on continuous-time quantum walks, with transitions to nearest neighbors on the network, to the fractional case that allows long-range displacements. By using the fractional Laplacian matrix of a network, we establish a formalism that combines a long-range dynamics with the quantum superposition of states; this general approach applies to any type of connected undirected networks, including regular, random, and complex networks, and can be implemented from the spectral properties of the Laplacian matrix. We study the fractional dynamics and its capacity to explore the network by means of the transition probability, the average probability of return, and global quantities that characterize the efficiency of this quantum process. As a particular case, we explore analytically these quantities for circulant networks such as rings, interacting cycles, and complete graphs.

Ckmeans.1d.dp: Optimal k-means Clustering in One Dimension by Dynamic Programming.

Science.gov (United States)

Wang, Haizhou; Song, Mingzhou

2011-12-01

The heuristic k -means algorithm, widely used for cluster analysis, does not guarantee optimality. We developed a dynamic programming algorithm for optimal one-dimensional clustering. The algorithm is implemented as an R package called Ckmeans.1d.dp . We demonstrate its advantage in optimality and runtime over the standard iterative k -means algorithm.

Territorial dynamics and stable home range formation for central place foragers.

Directory of Open Access Journals (Sweden)

Jonathan R Potts

Full Text Available Uncovering the mechanisms behind territory formation is a fundamental problem in behavioural ecology. The broad nature of the underlying conspecific avoidance processes are well documented across a wide range of taxa. Scent marking in particular is common to a large range of terrestrial mammals and is known to be fundamental for communication. However, despite its importance, exact quantification of the time-scales over which scent cues and messages persist remains elusive. Recent work by the present authors has begun to shed light on this problem by modelling animals as random walkers with scent-mediated interaction processes. Territories emerge as dynamic objects that continually change shape and slowly move without settling to a fixed location. As a consequence, the utilisation distribution of such an animal results in a slowly increasing home range, as shown for urban foxes (Vulpes vulpes. For certain other species, however, home ranges reach a stable state. The present work shows that stable home ranges arise when, in addition to scent-mediated conspecific avoidance, each animal moves as a central place forager. That is, the animal's movement has a random aspect but is also biased towards a fixed location, such as a den or nest site. Dynamic territories emerge but the probability distribution of the territory border locations reaches a steady state, causing stable home ranges to emerge from the territorial dynamics. Approximate analytic expressions for the animal's probability density function are derived. A programme is given for using these expressions to quantify both the strength of the animal's movement bias towards the central place and the time-scale over which scent messages persist. Comparisons are made with previous theoretical work modelling central place foragers with conspecific avoidance. Some insights into the mechanisms behind allometric scaling laws of animal space use are also given.

[Gestational weight gain and optimal ranges in Chinese mothers giving singleton and full-term births in 2013].

Science.gov (United States)

Wang, J; Duan, Y F; Pang, X H; Jiang, S; Yin, S A; Yang, Z Y; Lai, J Q

2018-01-06

Objective: To analyze the status of gestational weight gain (GWG) among Chinese mothers who gave singleton and full-term births, and to look at optimal GWG ranges. Methods: In 2013, using the multi-stage stratified and population proportional cluster sampling method, we investigated 8 323 mother-child pairs at their 0-24 months postpartum from 55 counties (cities/districts) of 30 provinces (except Tibet) in mainland China. Questionnaire was used to collect data on body weight before pregnancy and delivery, diseases during gestation, hemorrhage or not at postpartum, child birth weight and length, and other information about pregnant outcomes. We measured mother's body weight and height, and child's body weight and length. Based on 'Chinese Adult Body Weight Standard', we divided mothers into four groups according to their body weight before pregnancy: low weight (BMImothers and children, and according to P25-P75 of GWG among mothers who had good pregnant outcomes and good anthropometry, and whose children had good anthropometry. The status of GWG was assessed by the new optimal ranges. Results: P50 (P25-P75) of GWG among the 8 323 mothers was 15.0 (10.0-19.0) kg. According to the proposed optimal GWG ranges of IOM, the proportions of inadequate, optimal and excessive GWG accounted for 27.2% (2 263 mothers), 36.2% (3 016 mothers) and 36.6% (3 044 mothers). The optimal GWG ranges for low weight, normal weight, overweight and obesity were 11.5-18.0, 10.0-15.0, 8.0-14.0 and 5.0-11.5 kg. Based on these optimal GWG ranges established in this study, the rates of inadequate, optimal and excessive GWG were 15.7% (1 303 mothers), 45.0% (3 744 mothers) and 39.3% (3 276 mothers), and these rates were significantly different from that defined by the IOM standards (χ2=345.36, Pmothers is 15.0 kg, which is at a relatively higher level. This study suggests the optimal GWG ranges for Chinese women who give singleton and full-term babies, which appears lower than IOM's.

Clustering Molecular Dynamics Trajectories for Optimizing Docking Experiments

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Renata De Paris

2015-01-01

Full Text Available Molecular dynamics simulations of protein receptors have become an attractive tool for rational drug discovery. However, the high computational cost of employing molecular dynamics trajectories in virtual screening of large repositories threats the feasibility of this task. Computational intelligence techniques have been applied in this context, with the ultimate goal of reducing the overall computational cost so the task can become feasible. Particularly, clustering algorithms have been widely used as a means to reduce the dimensionality of molecular dynamics trajectories. In this paper, we develop a novel methodology for clustering entire trajectories using structural features from the substrate-binding cavity of the receptor in order to optimize docking experiments on a cloud-based environment. The resulting partition was selected based on three clustering validity criteria, and it was further validated by analyzing the interactions between 20 ligands and a fully flexible receptor (FFR model containing a 20 ns molecular dynamics simulation trajectory. Our proposed methodology shows that taking into account features of the substrate-binding cavity as input for the k-means algorithm is a promising technique for accurately selecting ensembles of representative structures tailored to a specific ligand.

Calibration Modeling Methodology to Optimize Performance for Low Range Applications

Science.gov (United States)

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.

Optimized design of a low-resistance electrical conductor for the multimegahertz range

Science.gov (United States)

Kurs, André; Kesler, Morris; Johnson, Steven G.

2011-04-01

We propose a design for a conductive wire composed of several mutually insulated coaxial conducting shells. With the help of numerical optimization, it is possible to obtain electrical resistances significantly lower than those of a heavy-gauge copper wire or litz wire in the 2-20 MHz range. Moreover, much of the reduction in resistance can be achieved for just a few shells; in contrast, litz wire would need to contain ˜104 strands to perform comparably in this frequency range.

Seasonal source-sink dynamics at the edge of a species' range

Science.gov (United States)

Kanda, L.L.; Fuller, T.K.; Sievert, P.R.; Kellogg, R.L.

2009-01-01

The roles of dispersal and population dynamics in determining species' range boundaries recently have received theoretical attention but little empirical work. Here we provide data on survival, reproduction, and movement for a Virginia opossum (Didelphis virginiana) population at a local distributional edge in central Massachusetts (USA). Most juvenile females that apparently exploited anthropogenic resources survived their first winter, whereas those using adjacent natural resources died of starvation. In spring, adult females recolonized natural areas. A life-table model suggests that a population exploiting anthropogenic resources may grow, acting as source to a geographically interlaced sink of opossums using only natural resources, and also providing emigrants for further range expansion to new human-dominated landscapes. In a geographical model, this source-sink dynamic is consistent with the local distribution identified through road-kill surveys. The Virginia opossum's exploitation of human resources likely ameliorates energetically restrictive winters and may explain both their local distribution and their northward expansion in unsuitable natural climatic regimes. Landscape heterogeneity, such as created by urbanization, may result in source-sink dynamics at highly localized scales. Differential fitness and individual dispersal movements within local populations are key to generating regional distributions, and thus species ranges, that exceed expectations. ?? 2009 by the Ecological Society of America.

Seasonal source-sink dynamics at the edge of a species' range.

Science.gov (United States)

Kanda, L Leann; Fuller, Todd K; Sievert, Paul R; Kellogg, Robert L

2009-06-01

The roles of dispersal and population dynamics in determining species' range boundaries recently have received theoretical attention but little empirical work. Here we provide data on survival, reproduction, and movement for a Virginia opossum (Didelphis virginiana) population at a local distributional edge in central Massachusetts (USA). Most juvenile females that apparently exploited anthropogenic resources survived their first winter, whereas those using adjacent natural resources died of starvation. In spring, adult females recolonized natural areas. A life-table model suggests that a population exploiting anthropogenic resources may grow, acting as source to a geographically interlaced sink of opossums using only natural resources, and also providing emigrants for further range expansion to new human-dominated landscapes. In a geographical model, this source-sink dynamic is consistent with the local distribution identified through road-kill surveys. The Virginia opossum's exploitation of human resources likely ameliorates energetically restrictive winters and may explain both their local distribution and their northward expansion in unsuitable natural climatic regimes. Landscape heterogeneity, such as created by urbanization, may result in source-sink dynamics at highly localized scales. Differential fitness and individual dispersal movements within local populations are key to generating regional distributions, and thus species ranges, that exceed expectations.

TaPT: Temperature-Aware Dynamic Cache Optimization for Embedded Systems

Directory of Open Access Journals (Sweden)

Tosiron Adegbija

2017-12-01

Full Text Available Embedded systems have stringent design constraints, which has necessitated much prior research focus on optimizing energy consumption and/or performance. Since embedded systems typically have fewer cooling options, rising temperature, and thus temperature optimization, is an emergent concern. Most embedded systems only dissipate heat by passive convection, due to the absence of dedicated thermal management hardware mechanisms. The embedded system’s temperature not only affects the system’s reliability, but can also affect the performance, power, and cost. Thus, embedded systems require efficient thermal management techniques. However, thermal management can conflict with other optimization objectives, such as execution time and energy consumption. In this paper, we focus on managing the temperature using a synergy of cache optimization and dynamic frequency scaling, while also optimizing the execution time and energy consumption. This paper provides new insights on the impact of cache parameters on efficient temperature-aware cache tuning heuristics. In addition, we present temperature-aware phase-based tuning, TaPT, which determines Pareto optimal clock frequency and cache configurations for fine-grained execution time, energy, and temperature tradeoffs. TaPT enables autonomous system optimization and also allows designers to specify temperature constraints and optimization priorities. Experiments show that TaPT can effectively reduce execution time, energy, and temperature, while imposing minimal hardware overhead.

The high dynamic range pixel array detector (HDR-PAD): Concept and design

Energy Technology Data Exchange (ETDEWEB)

Shanks, Katherine S.; Philipp, Hugh T.; Weiss, Joel T.; Becker, Julian; Tate, Mark W. [Laboratory of Atomic and Solid State Physics, Cornell University, Ithaca, NY 14853 (United States); Gruner, Sol M., E-mail: smg26@cornell.edu [Laboratory of Atomic and Solid State Physics, Cornell University, Ithaca, NY 14853 (United States); Cornell High Energy Synchrotron Source (CHESS), Cornell University, Ithaca, NY 14853 (United States)

2016-07-27

Experiments at storage ring light sources as well as at next-generation light sources increasingly require detectors capable of high dynamic range operation, combining low-noise detection of single photons with large pixel well depth. XFEL sources in particular provide pulse intensities sufficiently high that a purely photon-counting approach is impractical. The High Dynamic Range Pixel Array Detector (HDR-PAD) project aims to provide a dynamic range extending from single-photon sensitivity to 10{sup 6} photons/pixel in a single XFEL pulse while maintaining the ability to tolerate a sustained flux of 10{sup 11} ph/s/pixel at a storage ring source. Achieving these goals involves the development of fast pixel front-end electronics as well as, in the XFEL case, leveraging the delayed charge collection due to plasma effects in the sensor. A first prototype of essential electronic components of the HDR-PAD readout ASIC, exploring different options for the pixel front-end, has been fabricated. Here, the HDR-PAD concept and preliminary design will be described.

Optimal environmental policy and the dynamic property in LDCs

Directory of Open Access Journals (Sweden)

Masahiro Yabuta

2002-01-01

Full Text Available This paper has provided a model framework of foreign assistance policy in the context of dynamic optimal control and investigated the environmental policies in LDCs that received some financial support from abroad. The model framework features a specific behavior of the social planner who determines the level of voluntary expenditure for preservation of natural environment. Because more financial needs for natural environmental protection means less allowance of growth-oriented investment, the social planner confronts a trade-off problem between economic growth and environmental preservation. To tackle with this clearly, we have built a dynamic model with two control variables: per-capita consumption and voluntary expenditure for natural environment.

Perceptual Effects of Dynamic Range Compression in Popular Music Recordings

DEFF Research Database (Denmark)

Hjortkjær, Jens; Walther-Hansen, Mads

2014-01-01

There is a widespread belief that the increasing use of dynamic range compression in music mastering (the loudnesswar) deteriorates sound quality but experimental evidence of perceptual effects is lacking. In this study, normal hearing listeners were asked to evaluate popular music recordings in ...

High Dynamic Optimized Carrier Loop Improvement for Tracking Doppler Rates

Directory of Open Access Journals (Sweden)

Amirhossein Fereidountabar

2015-01-01

Full Text Available Mathematical analysis and optimization of a carrier tracking loop are presented. Due to fast changing of the carrier frequency in some satellite systems, such as Low Earth Orbit (LEO or Global Positioning System (GPS, or some planes like Unmanned Aerial Vehicles (UAVs, high dynamic tracking loops play a very important role. In this paper an optimized tracking loop consisting of a third-order Phase Locked Loop (PLL assisted by a second-order Frequency Locked Loop (FLL for UAVs is proposed and discussed. Based on this structure an optimal loop has been designed. The main advantages of this approach are the reduction of the computation complexity and smaller phase error. The paper shows the simulation results, comparing them with a previous work.

Nonlinear mapping of the luminance in dual-layer high dynamic range displays

Science.gov (United States)

Guarnieri, Gabriele; Ramponi, Giovanni; Bonfiglio, Silvio; Albani, Luigi

2009-02-01

It has long been known that the human visual system (HVS) has a nonlinear response to luminance. This nonlinearity can be quantified using the concept of just noticeable difference (JND), which represents the minimum amplitude of a specified test pattern an average observer can discern from a uniform background. The JND depends on the background luminance following a threshold versus intensity (TVI) function. It is possible to define a curve which maps physical luminances into a perceptually linearized domain. This mapping can be used to optimize a digital encoding, by minimizing the visibility of quantization noise. It is also commonly used in medical applications to display images adapting to the characteristics of the display device. High dynamic range (HDR) displays, which are beginning to appear on the market, can display luminance levels outside the range in which most standard mapping curves are defined. In particular, dual-layer LCD displays are able to extend the gamut of luminance offered by conventional liquid crystals towards the black region; in such areas suitable and HVS-compliant luminance transformations need to be determined. In this paper we propose a method, which is primarily targeted to the extension of the DICOM curve used in medical imaging, but also has a more general application. The method can be modified in order to compensate for the ambient light, which can be significantly greater than the black level of an HDR display and consequently reduce the visibility of the details in dark areas.

New numerical methods for open-loop and feedback solutions to dynamic optimization problems

Science.gov (United States)

Ghosh, Pradipto

The topic of the first part of this research is trajectory optimization of dynamical systems via computational swarm intelligence. Particle swarm optimization is a nature-inspired heuristic search method that relies on a group of potential solutions to explore the fitness landscape. Conceptually, each particle in the swarm uses its own memory as well as the knowledge accumulated by the entire swarm to iteratively converge on an optimal or near-optimal solution. It is relatively straightforward to implement and unlike gradient-based solvers, does not require an initial guess or continuity in the problem definition. Although particle swarm optimization has been successfully employed in solving static optimization problems, its application in dynamic optimization, as posed in optimal control theory, is still relatively new. In the first half of this thesis particle swarm optimization is used to generate near-optimal solutions to several nontrivial trajectory optimization problems including thrust programming for minimum fuel, multi-burn spacecraft orbit transfer, and computing minimum-time rest-to-rest trajectories for a robotic manipulator. A distinct feature of the particle swarm optimization implementation in this work is the runtime selection of the optimal solution structure. Optimal trajectories are generated by solving instances of constrained nonlinear mixed-integer programming problems with the swarming technique. For each solved optimal programming problem, the particle swarm optimization result is compared with a nearly exact solution found via a direct method using nonlinear programming. Numerical experiments indicate that swarm search can locate solutions to very great accuracy. The second half of this research develops a new extremal-field approach for synthesizing nearly optimal feedback controllers for optimal control and two-player pursuit-evasion games described by general nonlinear differential equations. A notable revelation from this development

Optimal protocols for Hamiltonian and Schrödinger dynamics

International Nuclear Information System (INIS)

Schmiedl, Tim; Dieterich, Eckhard; Dieterich, Peter-Simon; Seifert, Udo

2009-01-01

For systems in an externally controllable time dependent potential, the optimal protocol minimizes the mean work spent in a finite time transition between given initial and final values of a control parameter. For an initially thermalized ensemble, we consider both Hamiltonian evolution for classical systems and Schrödinger evolution for quantum systems. In both cases, we show that for harmonic potentials, the optimal work is given by the adiabatic work even in the limit of short transition times. This result is counter-intuitive because the adiabatic work is substantially smaller than the work for an instantaneous jump. We also perform numerical calculations for the optimal protocol for Hamiltonian dynamics in an anharmonic quartic potential. For a two-level spin system, we give examples where the adiabatic work can be reached in either a finite or an arbitrarily short transition time depending on the allowed parameter space

Cascadia, an ultracompact seismic instrument with over 200dB of dynamic range

Science.gov (United States)

Parker, Tim; Devanney, Peter; Bainbridge, Geoff; Townsend, Bruce

2017-04-01

Integration of geophysical instrumentation is clearly a way to lower overall station cost, make installations less complex, reduce installation time, increase station utility and value to a wider group of researchers, data miners and monitoring groups. Initiatives to expand early earthquake warning networks and observatories can use these savings for increasing station density. Integration of mature instrument systems such as broadband sensors and accelerometers used in strong motion studies has to be done with care to preserve the low noise and low frequency performance while providing over 200dB of dynamic range. Understanding the instrument complexities and deployment challenges allows the engineering teams to optimize the packaging to make installation and servicing cost effective, simple, routine and ultimately more reliable. We discuss early results from testing both in the lab and in the field of a newly released instrument called the Cascadia that integrates a broadband seismometer with a class A (USGS rating) accelerometer in a small stainless steel sonde suited for dense arrays in either ad hoc direct bury field deployments or in observatory quality shallow boreholes.

Optimal Interest-Rate Setting in a Dynamic IS/AS Model

DEFF Research Database (Denmark)

Jensen, Henrik

2011-01-01

This note deals with interest-rate setting in a simple dynamic macroeconomic setting. The purpose is to present some basic and central properties of an optimal interest-rate rule. The model framework predates the New-Keynesian paradigm of the late 1990s and onwards (it is accordingly dubbed “Old...

Multi-input wide dynamic range ADC system for use with nuclear detectors

Energy Technology Data Exchange (ETDEWEB)

Austin, R W [National Aeronautics and Space Administration, Huntsville, Ala. (USA). George C. Marshall Space Flight Center

1976-04-15

A wide dynamic range, eight input analog-to-digital converter system has been developed for use in nuclear experiments. The system consists of eight dual-range sample and hold modules, an eight input multiplexer, a ten-bit analog-to-digital converter, and the associated control logic.

Exploring the Environment/Energy Pareto Optimal Front of an Office Room Using Computational Fluid Dynamics-Based Interactive Optimization Method

Directory of Open Access Journals (Sweden)

Kangji Li

2017-02-01

Full Text Available This paper is concerned with the development of a high-resolution and control-friendly optimization framework in enclosed environments that helps improve thermal comfort, indoor air quality (IAQ, and energy costs of heating, ventilation and air conditioning (HVAC system simultaneously. A computational fluid dynamics (CFD-based optimization method which couples algorithms implemented in Matlab with CFD simulation is proposed. The key part of this method is a data interactive mechanism which efficiently passes parameters between CFD simulations and optimization functions. A two-person office room is modeled for the numerical optimization. The multi-objective evolutionary algorithm—non-dominated-and-crowding Sorting Genetic Algorithm II (NSGA-II—is realized to explore the environment/energy Pareto front of the enclosed space. Performance analysis will demonstrate the effectiveness of the presented optimization method.

Multi-exposure high dynamic range image synthesis with camera shake correction

Science.gov (United States)

Li, Xudong; Chen, Yongfu; Jiang, Hongzhi; Zhao, Huijie

2017-10-01

Machine vision plays an important part in industrial online inspection. Owing to the nonuniform illuminance conditions and variable working distances, the captured image tends to be over-exposed or under-exposed. As a result, when processing the image such as crack inspection, the algorithm complexity and computing time increase. Multiexposure high dynamic range (HDR) image synthesis is used to improve the quality of the captured image, whose dynamic range is limited. Inevitably, camera shake will result in ghost effect, which blurs the synthesis image to some extent. However, existed exposure fusion algorithms assume that the input images are either perfectly aligned or captured in the same scene. These assumptions limit the application. At present, widely used registration based on Scale Invariant Feature Transform (SIFT) is usually time consuming. In order to rapidly obtain a high quality HDR image without ghost effect, we come up with an efficient Low Dynamic Range (LDR) images capturing approach and propose a registration method based on ORiented Brief (ORB) and histogram equalization which can eliminate the illumination differences between the LDR images. The fusion is performed after alignment. The experiment results demonstrate that the proposed method is robust to illumination changes and local geometric distortion. Comparing with other exposure fusion methods, our method is more efficient and can produce HDR images without ghost effect by registering and fusing four multi-exposure images.

A Dynamic Optimization Method of Indoor Fire Evacuation Route Based on Real-time Situation Awareness

Directory of Open Access Journals (Sweden)

DING Yulin

2016-12-01

Full Text Available How to provide safe and effective evacuation routes is an important safeguard to correctly guide evacuation and reduce the casualties during the fire situation rapidly evolving in complex indoor environment. The traditional static path finding method is difficult to adjust the path adaptively according to the changing fire situation, which lead to the evacuation decision-making blindness and hysteresis. This paper proposes a dynamic method which can dynamically optimize the indoor evacuation routes based on the real-time situation awareness. According to the real-time perception of fire situation parameters and the changing indoor environment information, the evacuation route is optimized dynamically. The integrated representation of multisource indoor fire monitoring sensor observations oriented fire emergency evacuation is presented at first, real-time fire threat situation information inside building is then extracted from the observation data of multi-source sensors, which is used to constrain the dynamical optimization of the topology of the evacuation route. Finally, the simulation experiments prove that this method can improve the accuracy and efficiency of indoor evacuation routing.

An Optimization Principle for Deriving Nonequilibrium Statistical Models of Hamiltonian Dynamics

Science.gov (United States)

Turkington, Bruce

2013-08-01

A general method for deriving closed reduced models of Hamiltonian dynamical systems is developed using techniques from optimization and statistical estimation. Given a vector of resolved variables, selected to describe the macroscopic state of the system, a family of quasi-equilibrium probability densities on phase space corresponding to the resolved variables is employed as a statistical model, and the evolution of the mean resolved vector is estimated by optimizing over paths of these densities. Specifically, a cost function is constructed to quantify the lack-of-fit to the microscopic dynamics of any feasible path of densities from the statistical model; it is an ensemble-averaged, weighted, squared-norm of the residual that results from submitting the path of densities to the Liouville equation. The path that minimizes the time integral of the cost function determines the best-fit evolution of the mean resolved vector. The closed reduced equations satisfied by the optimal path are derived by Hamilton-Jacobi theory. When expressed in terms of the macroscopic variables, these equations have the generic structure of governing equations for nonequilibrium thermodynamics. In particular, the value function for the optimization principle coincides with the dissipation potential that defines the relation between thermodynamic forces and fluxes. The adjustable closure parameters in the best-fit reduced equations depend explicitly on the arbitrary weights that enter into the lack-of-fit cost function. Two particular model reductions are outlined to illustrate the general method. In each example the set of weights in the optimization principle contracts into a single effective closure parameter.

Dynamic Modeling, Model-Based Control, and Optimization of Solid Oxide Fuel Cells

Science.gov (United States)

Spivey, Benjamin James

2011-07-01

Solid oxide fuel cells are a promising option for distributed stationary power generation that offers efficiencies ranging from 50% in stand-alone applications to greater than 80% in cogeneration. To advance SOFC technology for widespread market penetration, the SOFC should demonstrate improved cell lifetime and load-following capability. This work seeks to improve lifetime through dynamic analysis of critical lifetime variables and advanced control algorithms that permit load-following while remaining in a safe operating zone based on stress analysis. Control algorithms typically have addressed SOFC lifetime operability objectives using unconstrained, single-input-single-output control algorithms that minimize thermal transients. Existing SOFC controls research has not considered maximum radial thermal gradients or limits on absolute temperatures in the SOFC. In particular, as stress analysis demonstrates, the minimum cell temperature is the primary thermal stress driver in tubular SOFCs. This dissertation presents a dynamic, quasi-two-dimensional model for a high-temperature tubular SOFC combined with ejector and prereformer models. The model captures dynamics of critical thermal stress drivers and is used as the physical plant for closed-loop control simulations. A constrained, MIMO model predictive control algorithm is developed and applied to control the SOFC. Closed-loop control simulation results demonstrate effective load-following, constraint satisfaction for critical lifetime variables, and disturbance rejection. Nonlinear programming is applied to find the optimal SOFC size and steady-state operating conditions to minimize total system costs.

Note: A high dynamic range, linear response transimpedance amplifier.

Science.gov (United States)

Eckel, S; Sushkov, A O; Lamoreaux, S K

2012-02-01

We have built a high dynamic range (nine decade) transimpedance amplifier with a linear response. The amplifier uses junction-gate field effect transistors (JFETs) to switch between three different resistors in the feedback of a low input bias current operational amplifier. This allows for the creation of multiple outputs, each with a linear response and a different transimpedance gain. The overall bandwidth of the transimpedance amplifier is set by the bandwidth of the most sensitive range. For our application, we demonstrate a three-stage amplifier with transimpedance gains of approximately 10(9)Ω, 3 × 10(7)Ω, and 10(4)Ω with a bandwidth of 100 Hz.

Applications of sub-optimality in dynamic programming to location and construction of nuclear fuel processing plant

International Nuclear Information System (INIS)

Thiriet, L.; Deledicq, A.

1968-09-01

First, the point of applying Dynamic Programming to optimization and Operational Research problems in chemical industries are recalled, as well as the conditions in which a dynamic program is illustrated by a sequential graph. A new algorithm for the determination of sub-optimal politics in a sequential graph is then developed. Finally, the applications of sub-optimality concept is shown when taking into account the indirect effects related to possible strategies, or in the case of stochastic choices and of problems of the siting of plants... application examples are given. (authors) [fr

Optimizing zonal advection of the Advanced Research WRF (ARW) dynamics for Intel MIC

Science.gov (United States)

Mielikainen, Jarno; Huang, Bormin; Huang, Allen H.

2014-10-01

The Weather Research and Forecast (WRF) model is the most widely used community weather forecast and research model in the world. There are two distinct varieties of WRF. The Advanced Research WRF (ARW) is an experimental, advanced research version featuring very high resolution. The WRF Nonhydrostatic Mesoscale Model (WRF-NMM) has been designed for forecasting operations. WRF consists of dynamics code and several physics modules. The WRF-ARW core is based on an Eulerian solver for the fully compressible nonhydrostatic equations. In the paper, we will use Intel Intel Many Integrated Core (MIC) architecture to substantially increase the performance of a zonal advection subroutine for optimization. It is of the most time consuming routines in the ARW dynamics core. Advection advances the explicit perturbation horizontal momentum equations by adding in the large-timestep tendency along with the small timestep pressure gradient tendency. We will describe the challenges we met during the development of a high-speed dynamics code subroutine for MIC architecture. Furthermore, lessons learned from the code optimization process will be discussed. The results show that the optimizations improved performance of the original code on Xeon Phi 5110P by a factor of 2.4x.

Policy Gradient Adaptive Dynamic Programming for Data-Based Optimal Control.

Science.gov (United States)

Luo, Biao; Liu, Derong; Wu, Huai-Ning; Wang, Ding; Lewis, Frank L

2017-10-01

The model-free optimal control problem of general discrete-time nonlinear systems is considered in this paper, and a data-based policy gradient adaptive dynamic programming (PGADP) algorithm is developed to design an adaptive optimal controller method. By using offline and online data rather than the mathematical system model, the PGADP algorithm improves control policy with a gradient descent scheme. The convergence of the PGADP algorithm is proved by demonstrating that the constructed Q -function sequence converges to the optimal Q -function. Based on the PGADP algorithm, the adaptive control method is developed with an actor-critic structure and the method of weighted residuals. Its convergence properties are analyzed, where the approximate Q -function converges to its optimum. Computer simulation results demonstrate the effectiveness of the PGADP-based adaptive control method.

Stereo Vision-Based High Dynamic Range Imaging Using Differently-Exposed Image Pair

Directory of Open Access Journals (Sweden)

Won-Jae Park

2017-06-01

Full Text Available In this paper, a high dynamic range (HDR imaging method based on the stereo vision system is presented. The proposed method uses differently exposed low dynamic range (LDR images captured from a stereo camera. The stereo LDR images are first converted to initial stereo HDR images using the inverse camera response function estimated from the LDR images. However, due to the limited dynamic range of the stereo LDR camera, the radiance values in under/over-exposed regions of the initial main-view (MV HDR image can be lost. To restore these radiance values, the proposed stereo matching and hole-filling algorithms are applied to the stereo HDR images. Specifically, the auxiliary-view (AV HDR image is warped by using the estimated disparity between initial the stereo HDR images and then effective hole-filling is applied to the warped AV HDR image. To reconstruct the final MV HDR, the warped and hole-filled AV HDR image is fused with the initial MV HDR image using the weight map. The experimental results demonstrate objectively and subjectively that the proposed stereo HDR imaging method provides better performance compared to the conventional method.

Dynamic Simulation and Optimization of Nuclear Hydrogen Production Systems

Energy Technology Data Exchange (ETDEWEB)

Paul I. Barton; Mujid S. Kaximi; Georgios Bollas; Patricio Ramirez Munoz

2009-07-31

This project is part of a research effort to design a hydrogen plant and its interface with a nuclear reactor. This project developed a dynamic modeling, simulation and optimization environment for nuclear hydrogen production systems. A hybrid discrete/continuous model captures both the continuous dynamics of the nuclear plant, the hydrogen plant, and their interface, along with discrete events such as major upsets. This hybrid model makes us of accurate thermodynamic sub-models for the description of phase and reaction equilibria in the thermochemical reactor. Use of the detailed thermodynamic models will allow researchers to examine the process in detail and have confidence in the accurary of the property package they use.

Wavepacket dynamics in one-dimensional system with long-range correlated disorder

Science.gov (United States)

Yamada, Hiroaki S.

2018-03-01

We numerically investigate dynamical property in the one-dimensional tight-binding model with long-range correlated disorder having power spectrum 1 /fα (α: spectrum exponent) generated by Fourier filtering method. For relatively small α MSD) of the initially localized wavepacket shows ballistic spread and localizes as time elapses. It is shown that α-dependence of the dynamical localization length determined by the MSD exhibits a simple scaling law in the localization regime for the relatively weak disorder strength W. Furthermore, scaled MSD by the dynamical localization length almost obeys an universal function from the ballistic to the localization regime in the various combinations of the parameters α and W.

Sorting method to extend the dynamic range of the Shack-Hartmann wave-front sensor

International Nuclear Information System (INIS)

Lee, Junwon; Shack, Roland V.; Descour, Michael R.

2005-01-01

We propose a simple and powerful algorithm to extend the dynamic range of a Shack-Hartmann wave-front sensor. In a conventional Shack-Hartmann wave-front sensor the dynamic range is limited by the f-number of a lenslet, because the focal spot is required to remain in the area confined by the single lenslet. The sorting method proposed here eliminates such a limitation and extends the dynamic range by tagging each spot in a special sequence. Since the sorting method is a simple algorithm that does not change the measurement configuration, there is no requirement for extra hardware, multiple measurements, or complicated algorithms. We not only present the theory and a calculation example of the sorting method but also actually implement measurement of a highly aberrated wave front from nonrotational symmetric optics

The Value of Optimization in Dynamic Ride-Sharing: a Simulation Study in Metro Atlanta

NARCIS (Netherlands)

N.A.H. Agatz (Niels); A. Erera (Alan); M.W.P. Savelsbergh (Martin); X. Wang (Xing)

2010-01-01

textabstractSmartphone technology enables dynamic ride-sharing systems that bring together people with similar itineraries and time schedules to share rides on short-notice. This paper considers the problem of matching drivers and riders in this dynamic setting. We develop optimization-based

Optimal diabatic dynamics of Majorana-based quantum gates

Science.gov (United States)

Rahmani, Armin; Seradjeh, Babak; Franz, Marcel

2017-08-01

In topological quantum computing, unitary operations on qubits are performed by adiabatic braiding of non-Abelian quasiparticles, such as Majorana zero modes, and are protected from local environmental perturbations. In the adiabatic regime, with timescales set by the inverse gap of the system, the errors can be made arbitrarily small by performing the process more slowly. To enhance the performance of quantum information processing with Majorana zero modes, we apply the theory of optimal control to the diabatic dynamics of Majorana-based qubits. While we sacrifice complete topological protection, we impose constraints on the optimal protocol to take advantage of the nonlocal nature of topological information and increase the robustness of our gates. By using the Pontryagin's maximum principle, we show that robust equivalent gates to perfect adiabatic braiding can be implemented in finite times through optimal pulses. In our implementation, modifications to the device Hamiltonian are avoided. Focusing on thermally isolated systems, we study the effects of calibration errors and external white and 1 /f (pink) noise on Majorana-based gates. While a noise-induced antiadiabatic behavior, where a slower process creates more diabatic excitations, prohibits indefinite enhancement of the robustness of the adiabatic scheme, our fast optimal protocols exhibit remarkable stability to noise and have the potential to significantly enhance the practical performance of Majorana-based information processing.

A New Method Based on Simulation-Optimization Approach to Find Optimal Solution in Dynamic Job-shop Scheduling Problem with Breakdown and Rework

Directory of Open Access Journals (Sweden)

Farzad Amirkhani

2017-03-01

The proposed method is implemented on classical job-shop problems with objective of makespan and results are compared with mixed integer programming model. Moreover, the appropriate dispatching priorities are achieved for dynamic job-shop problem minimizing a multi-objective criteria. The results show that simulation-based optimization are highly capable to capture the main characteristics of the shop and produce optimal/near-optimal solutions with highly credibility degree.

Optimal Detection Range of RFID Tag for RFID-based Positioning System Using the k-NN Algorithm

Directory of Open Access Journals (Sweden)

Joon Heo

2009-06-01

Full Text Available Positioning technology to track a moving object is an important and essential component of ubiquitous computing environments and applications. An RFID-based positioning system using the k-nearest neighbor (k-NN algorithm can determine the position of a moving reader from observed reference data. In this study, the optimal detection range of an RFID-based positioning system was determined on the principle that tag spacing can be derived from the detection range. It was assumed that reference tags without signal strength information are regularly distributed in 1-, 2- and 3-dimensional spaces. The optimal detection range was determined, through analytical and numerical approaches, to be 125% of the tag-spacing distance in 1-dimensional space. Through numerical approaches, the range was 134% in 2-dimensional space, 143% in 3-dimensional space.

Dynamic stochastic optimization

CERN Document Server

Ermoliev, Yuri; Pflug, Georg

2004-01-01

Uncertainties and changes are pervasive characteristics of modern systems involving interactions between humans, economics, nature and technology. These systems are often too complex to allow for precise evaluations and, as a result, the lack of proper management (control) may create significant risks. In order to develop robust strategies we need approaches which explic­ itly deal with uncertainties, risks and changing conditions. One rather general approach is to characterize (explicitly or implicitly) uncertainties by objec­ tive or subjective probabilities (measures of confidence or belief). This leads us to stochastic optimization problems which can rarely be solved by using the standard deterministic optimization and optimal control methods. In the stochastic optimization the accent is on problems with a large number of deci­ sion and random variables, and consequently the focus ofattention is directed to efficient solution procedures rather than to (analytical) closed-form solu­ tions. Objective an...

An optimal maintenance policy for machine replacement problem using dynamic programming

OpenAIRE

Mohsen Sadegh Amalnik; Morteza Pourgharibshahi

2017-01-01

In this article, we present an acceptance sampling plan for machine replacement problem based on the backward dynamic programming model. Discount dynamic programming is used to solve a two-state machine replacement problem. We plan to design a model for maintenance by consid-ering the quality of the item produced. The purpose of the proposed model is to determine the optimal threshold policy for maintenance in a finite time horizon. We create a decision tree based on a sequential sampling inc...

Automatic Generation of Wide Dynamic Range Image without Pseudo-Edge Using Integration of Multi-Steps Exposure Images

Science.gov (United States)

Migiyama, Go; Sugimura, Atsuhiko; Osa, Atsushi; Miike, Hidetoshi

Recently, digital cameras are offering technical advantages rapidly. However, the shot image is different from the sight image generated when that scenery is seen with the naked eye. There are blown-out highlights and crushed blacks in the image that photographed the scenery of wide dynamic range. The problems are hardly generated in the sight image. These are contributory cause of difference between the shot image and the sight image. Blown-out highlights and crushed blacks are caused by the difference of dynamic range between the image sensor installed in a digital camera such as CCD and CMOS and the human visual system. Dynamic range of the shot image is narrower than dynamic range of the sight image. In order to solve the problem, we propose an automatic method to decide an effective exposure range in superposition of edges. We integrate multi-step exposure images using the method. In addition, we try to erase pseudo-edges using the process to blend exposure values. Afterwards, we get a pseudo wide dynamic range image automatically.

Distributed Optimization based Dynamic Tariff for Congestion Management in Distribution Networks

DEFF Research Database (Denmark)

Huang, Shaojun; Wu, Qiuwei; Zhao, Haoran

2017-01-01

This paper proposes a distributed optimization based dynamic tariff (DDT) method for congestion management in distribution networks with high penetration of electric vehicles (EVs) and heat pumps (HPs). The DDT method employs a decomposition based optimization method to have aggregators explicitly...... is able to minimize the overall energy consumption cost and line loss cost, which is different from previous decomposition-based methods such as multiagent system methods. In addition, a reconditioning method and an integral controller are introduced to improve convergence of the distributed optimization...... where challenges arise due to multiple congestion points, multiple types of flexible demands and network constraints. The case studies demonstrate the efficacy of the DDT method for congestion management in distribution networks....

Optimal Control Method of Robot End Position and Orientation Based on Dynamic Tracking Measurement

Science.gov (United States)

Liu, Dalong; Xu, Lijuan

2018-01-01

In order to improve the accuracy of robot pose positioning and control, this paper proposed a dynamic tracking measurement robot pose optimization control method based on the actual measurement of D-H parameters of the robot, the parameters is taken with feedback compensation of the robot, according to the geometrical parameters obtained by robot pose tracking measurement, improved multi sensor information fusion the extended Kalan filter method, with continuous self-optimal regression, using the geometric relationship between joint axes for kinematic parameters in the model, link model parameters obtained can timely feedback to the robot, the implementation of parameter correction and compensation, finally we can get the optimal attitude angle, realize the robot pose optimization control experiments were performed. 6R dynamic tracking control of robot joint robot with independent research and development is taken as experimental subject, the simulation results show that the control method improves robot positioning accuracy, and it has the advantages of versatility, simplicity, ease of operation and so on.

Conditions for characterizing the structure of optimal strategies in infinite-horizon dynamic programs

International Nuclear Information System (INIS)

Porteus, E.

1982-01-01

The study of infinite-horizon nonstationary dynamic programs using the operator approach is continued. The point of view here differs slightly from that taken by others, in that Denardo's local income function is not used as a starting point. Infinite-horizon values are defined as limits of finite-horizon values, as the horizons get long. Two important conditions of an earlier paper are weakened, yet the optimality equations, the optimality criterion, and the existence of optimal ''structured'' strategies are still obtained

Fast optimization of binary clusters using a novel dynamic lattice searching method

International Nuclear Information System (INIS)

Wu, Xia; Cheng, Wen

2014-01-01

Global optimization of binary clusters has been a difficult task despite of much effort and many efficient methods. Directing toward two types of elements (i.e., homotop problem) in binary clusters, two classes of virtual dynamic lattices are constructed and a modified dynamic lattice searching (DLS) method, i.e., binary DLS (BDLS) method, is developed. However, it was found that the BDLS can only be utilized for the optimization of binary clusters with small sizes because homotop problem is hard to be solved without atomic exchange operation. Therefore, the iterated local search (ILS) method is adopted to solve homotop problem and an efficient method based on the BDLS method and ILS, named as BDLS-ILS, is presented for global optimization of binary clusters. In order to assess the efficiency of the proposed method, binary Lennard-Jones clusters with up to 100 atoms are investigated. Results show that the method is proved to be efficient. Furthermore, the BDLS-ILS method is also adopted to study the geometrical structures of (AuPd) 79 clusters with DFT-fit parameters of Gupta potential

Hybrid Approximate Dynamic Programming Approach for Dynamic Optimal Energy Flow in the Integrated Gas and Power Systems

DEFF Research Database (Denmark)

Shuai, Hang; Ai, Xiaomeng; Wen, Jinyu

2017-01-01

This paper proposes a hybrid approximate dynamic programming (ADP) approach for the multiple time-period optimal power flow in integrated gas and power systems. ADP successively solves Bellman's equation to make decisions according to the current state of the system. So, the updated near future...

Numerical Simulation of a Tumor Growth Dynamics Model Using Particle Swarm Optimization.

Science.gov (United States)

Wang, Zhijun; Wang, Qing

Tumor cell growth models involve high-dimensional parameter spaces that require computationally tractable methods to solve. To address a proposed tumor growth dynamics mathematical model, an instance of the particle swarm optimization method was implemented to speed up the search process in the multi-dimensional parameter space to find optimal parameter values that fit experimental data from mice cancel cells. The fitness function, which measures the difference between calculated results and experimental data, was minimized in the numerical simulation process. The results and search efficiency of the particle swarm optimization method were compared to those from other evolutional methods such as genetic algorithms.

Nonlinear dynamic simulation of optimal depletion of crude oil in the lower 48 United States

International Nuclear Information System (INIS)

Ruth, M.; Cleveland, C.J.

1993-01-01

This study combines the economic theory of optimal resource use with econometric estimates of demand and supply parameters to develop a nonlinear dynamic model of crude oil exploration, development, and production in the lower 48 United States. The model is simulated with the graphical programming language STELLA, for the years 1985 to 2020. The procedure encourages use of economic theory and econometrics in combination with nonlinear dynamic simulation to enhance our understanding of complex interactions present in models of optimal resource use. (author)

Dynamic Optimization Design of Cranes Based on Human–Crane–Rail System Dynamics and Annoyance Rate

Directory of Open Access Journals (Sweden)

Yunsheng Xin

2017-01-01

Full Text Available The operators of overhead traveling cranes experience discomfort as a result of the vibrations of crane structures. These vibrations are produced by defects in the rails on which the cranes move. To improve the comfort of operators, a nine-degree-of-freedom (nine-DOF mathematical model of a “human–crane–rail” system was constructed. Based on the theoretical guidance provided in ISO 2631-1, an annoyance rate model was established, and quantization results were determined. A dynamic optimization design method for overhead traveling cranes is proposed. A particle swarm optimization (PSO algorithm was used to optimize the crane structural design, with the structure parameters as the basic variables, the annoyance rate model as the objective function, and the acceleration amplitude and displacement amplitude of the crane as the constraint conditions. The proposed model and method were used to optimize the design of a double-girder 100 t–28.5 m casting crane, and the optimal parameters are obtained. The results show that optimization decreases the human annoyance rate from 28.3% to 9.8% and the root mean square of the weighted acceleration of human vibration from 0.59 m/s2 to 0.38 m/s2. These results demonstrate the effectiveness and practical applicability of the models and method proposed in this paper.

Numerical analysis for finite-range multitype stochastic contact financial market dynamic systems

International Nuclear Information System (INIS)

Yang, Ge; Wang, Jun; Fang, Wen

2015-01-01

In an attempt to reproduce and study the dynamics of financial markets, a random agent-based financial price model is developed and investigated by the finite-range multitype contact dynamic system, in which the interaction and dispersal of different types of investment attitudes in a stock market are imitated by viruses spreading. With different parameters of birth rates and finite-range, the normalized return series are simulated by Monte Carlo simulation method and numerical studied by power-law distribution analysis and autocorrelation analysis. To better understand the nonlinear dynamics of the return series, a q-order autocorrelation function and a multi-autocorrelation function are also defined in this work. The comparisons of statistical behaviors of return series from the agent-based model and the daily historical market returns of Shanghai Composite Index and Shenzhen Component Index indicate that the proposed model is a reasonable qualitative explanation for the price formation process of stock market systems

Numerical analysis for finite-range multitype stochastic contact financial market dynamic systems

Science.gov (United States)

Yang, Ge; Wang, Jun; Fang, Wen

2015-04-01

In an attempt to reproduce and study the dynamics of financial markets, a random agent-based financial price model is developed and investigated by the finite-range multitype contact dynamic system, in which the interaction and dispersal of different types of investment attitudes in a stock market are imitated by viruses spreading. With different parameters of birth rates and finite-range, the normalized return series are simulated by Monte Carlo simulation method and numerical studied by power-law distribution analysis and autocorrelation analysis. To better understand the nonlinear dynamics of the return series, a q-order autocorrelation function and a multi-autocorrelation function are also defined in this work. The comparisons of statistical behaviors of return series from the agent-based model and the daily historical market returns of Shanghai Composite Index and Shenzhen Component Index indicate that the proposed model is a reasonable qualitative explanation for the price formation process of stock market systems.

Numerical analysis for finite-range multitype stochastic contact financial market dynamic systems

Energy Technology Data Exchange (ETDEWEB)

Yang, Ge; Wang, Jun [School of Science, Beijing Jiaotong University, Beijing 100044 (China); Fang, Wen, E-mail: fangwen@bjtu.edu.cn [School of Economics and Management, Beijing Jiaotong University, Beijing 100044 (China)

2015-04-15

In an attempt to reproduce and study the dynamics of financial markets, a random agent-based financial price model is developed and investigated by the finite-range multitype contact dynamic system, in which the interaction and dispersal of different types of investment attitudes in a stock market are imitated by viruses spreading. With different parameters of birth rates and finite-range, the normalized return series are simulated by Monte Carlo simulation method and numerical studied by power-law distribution analysis and autocorrelation analysis. To better understand the nonlinear dynamics of the return series, a q-order autocorrelation function and a multi-autocorrelation function are also defined in this work. The comparisons of statistical behaviors of return series from the agent-based model and the daily historical market returns of Shanghai Composite Index and Shenzhen Component Index indicate that the proposed model is a reasonable qualitative explanation for the price formation process of stock market systems.

Energy and ancillary service dispatch through dynamic optimal power flow

International Nuclear Information System (INIS)

Costa, A.L.; Costa, A. Simoes

2007-01-01

This paper presents an approach based on dynamic optimal power flow (DOPF) to clear both energy and spinning reserve day-ahead markets. A competitive environment is assumed, where agents can offer active power for both demand supply and ancillary services. The DOPF jointly determines the optimal solutions for both energy dispatch and reserve allocation. A non-linear representation for the electrical network is employed, which is able to take transmission losses and power flow limits into account. An attractive feature of the proposed approach is that the final optimal solution will automatically meet physical constraints such as generating limits and ramp rate restrictions. In addition, the proposed framework allows the definition of multiple zones in the network for each time interval, in order to ensure a more adequate distribution of reserves throughout the power system. (author)

Complex fluid network optimization and control integrative design based on nonlinear dynamic model

International Nuclear Information System (INIS)

Sui, Jinxue; Yang, Li; Hu, Yunan

2016-01-01

In view of distribution according to complex fluid network’s needs, this paper proposed one optimization computation method of the nonlinear programming mathematical model based on genetic algorithm. The simulation result shows that the overall energy consumption of the optimized fluid network has a decrease obviously. The control model of the fluid network is established based on nonlinear dynamics. We design the control law based on feedback linearization, take the optimal value by genetic algorithm as the simulation data, can also solve the branch resistance under the optimal value. These resistances can provide technical support and reference for fluid network design and construction, so can realize complex fluid network optimization and control integration design.

Genetic algorithm enhanced by machine learning in dynamic aperture optimization

Science.gov (United States)

Li, Yongjun; Cheng, Weixing; Yu, Li Hua; Rainer, Robert

2018-05-01

With the aid of machine learning techniques, the genetic algorithm has been enhanced and applied to the multi-objective optimization problem presented by the dynamic aperture of the National Synchrotron Light Source II (NSLS-II) Storage Ring. During the evolution processes employed by the genetic algorithm, the population is classified into different clusters in the search space. The clusters with top average fitness are given "elite" status. Intervention on the population is implemented by repopulating some potentially competitive candidates based on the experience learned from the accumulated data. These candidates replace randomly selected candidates among the original data pool. The average fitness of the population is therefore improved while diversity is not lost. Maintaining diversity ensures that the optimization is global rather than local. The quality of the population increases and produces more competitive descendants accelerating the evolution process significantly. When identifying the distribution of optimal candidates, they appear to be located in isolated islands within the search space. Some of these optimal candidates have been experimentally confirmed at the NSLS-II storage ring. The machine learning techniques that exploit the genetic algorithm can also be used in other population-based optimization problems such as particle swarm algorithm.

Photonic limiters with enhanced dynamic range

Science.gov (United States)

Kononchuk, Rodion; Limberopoulos, Nicholaos; Anisimov, Igor; Vitebskiy, Ilya; Chabanov, Andrey

2018-02-01

Optical limiters transmit low intensity input light while blocking input light with the intensity exceeding certain limiting threshold. Conventional passive limiters utilize nonlinear optical materials, which are transparent at low light intensity and turn absorptive at high intensity. Strong nonlinear absorption, though, can result in over- heating and destruction of the limiter. Another problem is that the limiting threshold provided by the available optical material with nonlinear absorption is too high for many applications. To address the above problems, the nonlinear material can be incorporated in a photonic structure with engineered dispersion. At low intensity, the photonic structure can display resonant transmission via localized mode(s), while at high intensity the resonant transmission can disappear, and the entire stack can become highly re ective (not absorptive) within a broad frequency range. In the proposed design, the transition from the resonant transmission at low intensity to nearly total re ectivity at high intensity does not rely on nonlinear absorption; instead, it requires only a modest change in the refractive index of the nonlinear material. The latter implies a dramatic increase in the dynamic range of the limiter. The main idea is to eliminate the high-intensity resonant transmission by decoupling the localized (resonant) modes from the input light, rather than suppressing those modes using nonlinear absorption. Similar approach can be used for light modulation and switching.

Optimizing and Diversifying the Electric Range of Plug-in Hybrid Electric Vehicles for U.S. Drivers

International Nuclear Information System (INIS)

Lin, Zhenhong

2012-01-01

To provide useful information for automakers to design successful plug-in hybrid electric vehicle (PHEV) products and for energy and environmental analysts to understand the social impact of PHEVs, this paper addresses the question of how many of the U.S. consumers, if buying a PHEV, would prefer what electric ranges. The Market-oriented Optimal Range for PHEV (MOR-PHEV) model is developed to optimize the PHEV electric range for each of 36,664 sampled individuals representing U.S. new vehicle drivers. The optimization objective is the minimization of the sum of costs on battery, gasoline, electricity and refueling hassle. Assuming no battery subsidy, the empirical results suggest that: 1) the optimal PHEV electric range approximates two thirds of one s typical daily driving distance in the near term, defined as $450/kWh battery delivered price and $4/gallon gasoline price. 2) PHEVs are not ready to directly compete with HEVs at today s situation, defined by the $600/kWh battery delivered price and the $3-$4/gallon gasoline price, but can do so in the near term. 3) PHEV10s will be favored by the market over longer-range PHEVs in the near term, but longer-range PHEVs can dominate the PHEV market if gasoline prices reach as high as $5-$6 per gallon and/or battery delivered prices reach as low as $150-$300/kWh. 4) PHEVs can become much more attractive against HEVs in the near term if the electric range can be extended by only 10% with multiple charges per day, possible with improved charging infrastructure or adapted charging behavior. 5) the impact of a $100/kWh decrease in battery delivered prices on the competiveness of PHEVs against HEVs can be offset by about $1.25/gallon decrease in gasoline prices, or about 7/kWh increase in electricity prices. This also means that the impact of a $1/gallon decrease in gasoline prices can be offset by about 5/kWh decrease in electricity prices.

Dynamic regime of coherent population trapping and optimization of frequency modulation parameters in atomic clocks.

Science.gov (United States)

Yudin, V I; Taichenachev, A V; Basalaev, M Yu; Kovalenko, D V

2017-02-06

We theoretically investigate the dynamic regime of coherent population trapping (CPT) in the presence of frequency modulation (FM). We have formulated the criteria for quasi-stationary (adiabatic) and dynamic (non-adiabatic) responses of atomic system driven by this FM. Using the density matrix formalism for Λ system, the error signal is exactly calculated and optimized. It is shown that the optimal FM parameters correspond to the dynamic regime of atomic-field interaction, which significantly differs from conventional description of CPT resonances in the frame of quasi-stationary approach (under small modulation frequency). Obtained theoretical results are in good qualitative agreement with different experiments. Also we have found CPT-analogue of Pound-Driver-Hall regime of frequency stabilization.

Modeling and Optimal Control of a Class of Warfare Hybrid Dynamic Systems Based on Lanchester (n,1 Attrition Model

Directory of Open Access Journals (Sweden)

Xiangyong Chen

2014-01-01

hybrid dynamic systems is established based on Lanchester equation in a (n,1 battle, where a heterogeneous force of n different troop types faces a homogeneous force. This model can be characterized by the interaction of continuous-time models (governed by Lanchester equation, and discrete event systems (described by variable tactics. Furthermore, an expository discussion is presented on an optimal variable tactics control problem for warfare hybrid dynamic system. The optimal control strategies are designed based on dynamic programming and differential game theory. As an example of the consequences of this optimal control problem, we take the (2, 1 case and solve the optimal strategies in a (2, 1 case. Simulation results show the feasibility of warfare hybrid system model and the effectiveness of the optimal control strategies designed.

Mangrove microclimates alter seedling dynamics at the range edge.

Science.gov (United States)

Devaney, John L; Lehmann, Michael; Feller, Ilka C; Parker, John D

2017-10-01

Recent climate warming has led to asynchronous species migrations, with major consequences for ecosystems worldwide. In woody communities, localized microclimates have the potential to create feedback mechanisms that can alter the rate of species range shifts attributed to macroclimate drivers alone. Mangrove encroachment into saltmarsh in many areas is driven by a reduction in freeze events, and this encroachment can further modify local climate, but the subsequent impacts on mangrove seedling dynamics are unknown. We monitored microclimate conditions beneath mangrove canopies and adjacent open saltmarsh at a freeze-sensitive mangrove-saltmarsh ecotone and assessed survival of experimentally transplanted mangrove seedlings. Mangrove canopies buffered night time cooling during the winter, leading to interspecific differences in freeze damage on mangrove seedlings. However, mangrove canopies also altered biotic interactions. Herbivore damage was higher under canopies, leading to greater mangrove seedling mortality beneath canopies relative to saltmarsh. While warming-induced expansion of mangroves can lead to positive microclimate feedbacks, simultaneous fluctuations in biotic drivers can also alter seedling dynamics. Thus, climate change can drive divergent feedback mechanisms through both abiotic and biotic channels, highlighting the importance of vegetation-microclimate interactions as important moderators of climate driven range shifts. © 2017 by the Ecological Society of America.

On the existence of the optimal order for wavefunction extrapolation in Born-Oppenheimer molecular dynamics

Energy Technology Data Exchange (ETDEWEB)

Fang, Jun; Wang, Han, E-mail: wang-han@iapcm.ac.cn [Institute of Applied Physics and Computational Mathematics, Beijing (China); CAEP Software Center for High Performance Numerical Simulation, Beijing (China); Gao, Xingyu; Song, Haifeng [Institute of Applied Physics and Computational Mathematics, Beijing (China); CAEP Software Center for High Performance Numerical Simulation, Beijing (China); Laboratory of Computational Physics, Beijing (China)

2016-06-28

Wavefunction extrapolation greatly reduces the number of self-consistent field (SCF) iterations and thus the overall computational cost of Born-Oppenheimer molecular dynamics (BOMD) that is based on the Kohn–Sham density functional theory. Going against the intuition that the higher order of extrapolation possesses a better accuracy, we demonstrate, from both theoretical and numerical perspectives, that the extrapolation accuracy firstly increases and then decreases with respect to the order, and an optimal extrapolation order in terms of minimal number of SCF iterations always exists. We also prove that the optimal order tends to be larger when using larger MD time steps or more strict SCF convergence criteria. By example BOMD simulations of a solid copper system, we show that the optimal extrapolation order covers a broad range when varying the MD time step or the SCF convergence criterion. Therefore, we suggest the necessity for BOMD simulation packages to open the user interface and to provide more choices on the extrapolation order. Another factor that may influence the extrapolation accuracy is the alignment scheme that eliminates the discontinuity in the wavefunctions with respect to the atomic or cell variables. We prove the equivalence between the two existing schemes, thus the implementation of either of them does not lead to essential difference in the extrapolation accuracy.

Enhanced Microgrid Dynamic Performance Using a Modulated Power Filter Based on Enhanced Bacterial Foraging Optimization

Directory of Open Access Journals (Sweden)

Ahmed M. Othman

2017-06-01

Full Text Available This paper presents a design of microgrid (MG with enhanced dynamic performance. Distributed energy resources (DER are widely used in MGs to match the various load types and profiles. DERs include solar PV cells, wind energy sources, fuel cells, batteries, micro gas-engines and storage elements. MG will include AC/DC circuits, developed power electronics devices, inverters and power electronic controllers. A novel modulated power filters (MPF device will be applied in MG design. Enhanced bacterial foraging optimization (EBFO will be proposed to optimize and set the MPF parameters to enhance and tune the MG dynamic response. Recent dynamic control is applied to minimize the harmonic reference content. EBFO will adapt the gains of MPF dynamic control. The present research achieves an enhancement of MG dynamic performance, in addition to ensuring improvements in the power factor, bus voltage profile and power quality. MG operation will be evaluated by the dynamic response to be fine-tuned by MPF based on EBFO. Digital simulations have validated the results to show the effectiveness and efficient improvement by the proposed strategy.

Optimization of the multilinear compression function applied to calorimetry

International Nuclear Information System (INIS)

Cattaneo, P.W.Paolo Walter

2002-01-01

The energy dynamic range required by a calorimeter with high speed readout may exceed existing ADC capability. A solution may be a dynamic compressor matching the energy span to the ADC range, such as to contribute at most a predefinite amount to the calorimeter resolution. A multilinear compression function is the easiest to implement, therefore it is interesting to optimize the input to output relation and fix the break points

Image Alignment for Multiple Camera High Dynamic Range Microscopy

OpenAIRE

Eastwood, Brian S.; Childs, Elisabeth C.

2012-01-01

This paper investigates the problem of image alignment for multiple camera high dynamic range (HDR) imaging. HDR imaging combines information from images taken with different exposure settings. Combining information from multiple cameras requires an alignment process that is robust to the intensity differences in the images. HDR applications that use a limited number of component images require an alignment technique that is robust to large exposure differences. We evaluate the suitability fo...

Optimization of structures subjected to dynamic load: deterministic and probabilistic methods

Directory of Open Access Journals (Sweden)

Élcio Cassimiro Alves

Full Text Available Abstract This paper deals with the deterministic and probabilistic optimization of structures against bending when submitted to dynamic loads. The deterministic optimization problem considers the plate submitted to a time varying load while the probabilistic one takes into account a random loading defined by a power spectral density function. The correlation between the two problems is made by one Fourier Transformed. The finite element method is used to model the structures. The sensitivity analysis is performed through the analytical method and the optimization problem is dealt with by the method of interior points. A comparison between the deterministic optimisation and the probabilistic one with a power spectral density function compatible with the time varying load shows very good results.

Expanding the dynamic measurement range for polymeric nanoparticle pH sensors

DEFF Research Database (Denmark)

Sun, Honghao; Almdal, Kristoffer; Andresen, Thomas Lars

2011-01-01

Conventional optical nanoparticle pH sensors that are designed for ratiometric measurements in cells have been based on utilizing one sensor fluorophore and one reference fluorophore in each nanoparticle, which results in a relatively narrow dynamic measurement range. This results in substantial...

High Dynamic Range adaptive ΔΣ-based Focal Plane Array architecture

KAUST Repository

Yao, Shun; Kavusi, Sam; Salama, Khaled N.

2012-01-01

In this paper, an Adaptive Delta-Sigma based architecture for High Dynamic Range (HDR) Focal Plane Arrays is presented. The noise shaping effect of the Delta-Sigma modulation in the low end, and the distortion noise induced in the high end of Photo

Dynamic optimization approach for integrated supplier selection and tracking control of single product inventory system with product discount

Science.gov (United States)

Sutrisno; Widowati; Heru Tjahjana, R.

2017-01-01

In this paper, we propose a mathematical model in the form of dynamic/multi-stage optimization to solve an integrated supplier selection problem and tracking control problem of single product inventory system with product discount. The product discount will be stated as a piece-wise linear function. We use dynamic programming to solve this proposed optimization to determine the optimal supplier and the optimal product volume that will be purchased from the optimal supplier for each time period so that the inventory level tracks a reference trajectory given by decision maker with minimal total cost. We give a numerical experiment to evaluate the proposed model. From the result, the optimal supplier was determined for each time period and the inventory level follows the given reference well.

Lithium-ion battery dynamic model for wide range of operating conditions

DEFF Research Database (Denmark)

Stroe, Ana-Irina; Stroe, Daniel-Ioan; Swierczynski, Maciej Jozef

2017-01-01

In order to analyze the dynamic behavior of a Lithium-ion (Li-ion) battery and to determine their suitability for various applications, battery models are needed. An equivalent electrical circuit model is the most common way of representing the behavior of a Li-ion battery. There are different...... characterization tests performed for a wide range of operating conditions (temperature, load current and state-of-charge) on a commercial available 13Ah high-power lithium titanate oxide battery cell. The obtained results were used to parametrize the proposed dynamic model of the battery cell. To assess...

Merging spatially variant physical process models under an optimized systems dynamics framework.

Energy Technology Data Exchange (ETDEWEB)

Cain, William O. (University of Texas at Austin, Austin, TX); Lowry, Thomas Stephen; Pierce, Suzanne A.; Tidwell, Vincent Carroll

2007-10-01

The complexity of water resource issues, its interconnectedness to other systems, and the involvement of competing stakeholders often overwhelm decision-makers and inhibit the creation of clear management strategies. While a range of modeling tools and procedures exist to address these problems, they tend to be case specific and generally emphasize either a quantitative and overly analytic approach or present a qualitative dialogue-based approach lacking the ability to fully explore consequences of different policy decisions. The integration of these two approaches is needed to drive toward final decisions and engender effective outcomes. Given these limitations, the Computer Assisted Dispute Resolution system (CADRe) was developed to aid in stakeholder inclusive resource planning. This modeling and negotiation system uniquely addresses resource concerns by developing a spatially varying system dynamics model as well as innovative global optimization search techniques to maximize outcomes from participatory dialogues. Ultimately, the core system architecture of CADRe also serves as the cornerstone upon which key scientific innovation and challenges can be addressed.

An optimal frequency range for assessing the pressure reactivity index in patients with traumatic brain injury.

Science.gov (United States)

Howells, Tim; Johnson, Ulf; McKelvey, Tomas; Enblad, Per

2015-02-01

The objective of this study was to identify the optimal frequency range for computing the pressure reactivity index (PRx). PRx is a clinical method for assessing cerebral pressure autoregulation based on the correlation of spontaneous variations of arterial blood pressure (ABP) and intracranial pressure (ICP). Our hypothesis was that optimizing the methodology for computing PRx in this way could produce a more stable, reliable and clinically useful index of autoregulation status. The patients studied were a series of 131 traumatic brain injury patients. Pressure reactivity indices were computed in various frequency bands during the first 4 days following injury using bandpass filtering of the input ABP and ICP signals. Patient outcome was assessed using the extended Glasgow Outcome Scale (GOSe). The optimization criterion was the strength of the correlation with GOSe of the mean index value over the first 4 days following injury. Stability of the indices was measured as the mean absolute deviation of the minute by minute index value from 30-min moving averages. The optimal index frequency range for prediction of outcome was identified as 0.018-0.067 Hz (oscillations with periods from 55 to 15 s). The index based on this frequency range correlated with GOSe with ρ=-0.46 compared to -0.41 for standard PRx, and reduced the 30-min variation by 23%.

Optimal Reference Strain Structure for Studying Dynamic Responses of Flexible Rockets

Science.gov (United States)

Tsushima, Natsuki; Su, Weihua; Wolf, Michael G.; Griffin, Edwin D.; Dumoulin, Marie P.

2017-01-01

In the proposed paper, the optimal design of reference strain structures (RSS) will be performed targeting for the accurate observation of the dynamic bending and torsion deformation of a flexible rocket. It will provide the detailed description of the finite-element (FE) model of a notional flexible rocket created in MSC.Patran. The RSS will be attached longitudinally along the side of the rocket and to track the deformation of the thin-walled structure under external loads. An integrated surrogate-based multi-objective optimization approach will be developed to find the optimal design of the RSS using the FE model. The Kriging method will be used to construct the surrogate model. For the data sampling and the performance evaluation, static/transient analyses will be performed with MSC.Natran/Patran. The multi-objective optimization will be solved with NSGA-II to minimize the difference between the strains of the launch vehicle and RSS. Finally, the performance of the optimal RSS will be evaluated by checking its strain-tracking capability in different numerical simulations of the flexible rocket.

Stochastic optimal foraging: tuning intensive and extensive dynamics in random searches.

Directory of Open Access Journals (Sweden)

Frederic Bartumeus

Full Text Available Recent theoretical developments had laid down the proper mathematical means to understand how the structural complexity of search patterns may improve foraging efficiency. Under information-deprived scenarios and specific landscape configurations, Lévy walks and flights are known to lead to high search efficiencies. Based on a one-dimensional comparative analysis we show a mechanism by which, at random, a searcher can optimize the encounter with close and distant targets. The mechanism consists of combining an optimal diffusivity (optimally enhanced diffusion with a minimal diffusion constant. In such a way the search dynamics adequately balances the tension between finding close and distant targets, while, at the same time, shifts the optimal balance towards relatively larger close-to-distant target encounter ratios. We find that introducing a multiscale set of reorientations ensures both a thorough local space exploration without oversampling and a fast spreading dynamics at the large scale. Lévy reorientation patterns account for these properties but other reorientation strategies providing similar statistical signatures can mimic or achieve comparable efficiencies. Hence, the present work unveils general mechanisms underlying efficient random search, beyond the Lévy model. Our results suggest that animals could tune key statistical movement properties (e.g. enhanced diffusivity, minimal diffusion constant to cope with the very general problem of balancing out intensive and extensive random searching. We believe that theoretical developments to mechanistically understand stochastic search strategies, such as the one here proposed, are crucial to develop an empirically verifiable and comprehensive animal foraging theory.

High dynamic range isotope ratio measurements using an analog electron multiplier

Czech Academy of Sciences Publication Activity Database

Williams, P.; Lorinčík, Jan; Franzreb, K.; Herwig, R.

2013-01-01

Roč. 45, č. 1 (2013), s. 549-552 ISSN 0142-2421 R&D Projects: GA MŠk ME 894 Institutional support: RVO:67985882 Keywords : Isotope ratios * electron multiplier * dynamic range Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering Impact factor: 1.393, year: 2013

Sensitivity analysis and optimization of system dynamics models : Regression analysis and statistical design of experiments

NARCIS (Netherlands)

Kleijnen, J.P.C.

1995-01-01

This tutorial discusses what-if analysis and optimization of System Dynamics models. These problems are solved, using the statistical techniques of regression analysis and design of experiments (DOE). These issues are illustrated by applying the statistical techniques to a System Dynamics model for

Investigation and optimization of transverse non-linear beam dynamics in the high-energy storage ring HESR

Energy Technology Data Exchange (ETDEWEB)

Welsch, Dominic Markus

2010-03-10

The High-Energy Storage Ring (HESR) is part of the upcoming Facility for Antiproton and Ion Research (FAIR) which is planned as a major extension to the present facility of the Helmholtzzentrum fuer Schwerionenforschung (GSI) in Darmstadt. The HESR will provide antiprotons in the momentum range from 1.5 to 15 GeV/c for the internal target experiment PANDA. The demanding requirements of PANDA in terms of beam quality and luminosity together with a limited production rate of antiprotons call for a long beam life time and a minimum of beam loss. Therefore, an effective closed orbit correction and a sufficiently large dynamic aperture of the HESR are crucial. With this thesis I present my work on both of these topics. The expected misalignments of beam guiding magnets have been estimated and used to simulate the closed orbit in the HESR. A closed orbit correction scheme has been developed for different ion optical settings of the HESR and numerical simulations have been performed to validate the scheme. The proposed closed orbit correction method which uses the orbit response matrix has been benchmarked at the Cooler Synchrotron COSY of the Forschungszentrum Juelich. A chromaticity correction scheme for the HESR consisting of sextupole magnets has been developed to reduce tune spread and thus to minimize the emittance growth caused by betatron resonances. The chromaticity correction scheme has been optimized through dynamic aperture calculations. The estimated field errors of the HESR dipole and quadrupole magnets have been included in the non-linear beam dynamics studies. Investigations concerning their optimization have been carried out. The ion optical settings of the HESR have been improved using dynamic aperture calculations and the technique of frequency map analysis. The related diffusion coefficient was also used to predict long-term stability based on short-term particle tracking. With a reasonable reduction of the quadrupole magnets field errors and a

Optimization with Extremal Dynamics

International Nuclear Information System (INIS)

Boettcher, Stefan; Percus, Allon G.

2001-01-01

We explore a new general-purpose heuristic for finding high-quality solutions to hard discrete optimization problems. The method, called extremal optimization, is inspired by self-organized criticality, a concept introduced to describe emergent complexity in physical systems. Extremal optimization successively updates extremely undesirable variables of a single suboptimal solution, assigning them new, random values. Large fluctuations ensue, efficiently exploring many local optima. We use extremal optimization to elucidate the phase transition in the 3-coloring problem, and we provide independent confirmation of previously reported extrapolations for the ground-state energy of ±J spin glasses in d=3 and 4

Enhancing the dynamic range of Ultrasound Imaging Velocimetry using interleaved imaging

NARCIS (Netherlands)

Poelma, C.; Fraser, K.H.

2013-01-01

In recent years, non-invasive velocity field measurement based on correlation of ultrasound images has been introduced as a promising technique for fundamental research into disease processes, as well as a diagnostic tool. A major drawback of the method is the relatively limited dynamic range when

A highly sensitive RF-to-DC power converter with an extended dynamic range

KAUST Repository

Almansouri, Abdullah Saud Mohammed

2017-10-24

This paper proposes a highly sensitive RF-to-DC power converter with an extended dynamic range that is designed to operate at the medical band 433 MHz and simulated using 0.18 μm CMOS technology. Compared to the conventional fully cross-coupled rectifier, the proposed design offers 3.2× the dynamic range. It is also highly sensitive and requires −18 dBm of input power to produce a 1 V-output voltage when operating with a 100 kΩ load. Furthermore, the proposed design offers an open circuit sensitivity of −23.4 dBm and a peak power conversion efficiency of 67%.

A framework for reactive optimization in mobile ad hoc networks

DEFF Research Database (Denmark)

McClary, Dan; Syrotiuk, Violet; Kulahci, Murat

2008-01-01

We present a framework to optimize the performance of a mobile ad hoc network over a wide range of operating conditions. It includes screening experiments to quantify the parameters and interactions among parameters influential to throughput. Profile-driven regression is applied to obtain a model....... The predictive accuracy of the model is monitored and used to update the model dynamically. The results indicate the framework may be useful for the optimization of dynamic systems of high dimension....

Robust image registration for multiple exposure high dynamic range image synthesis

Science.gov (United States)

Yao, Susu

2011-03-01

Image registration is an important preprocessing technique in high dynamic range (HDR) image synthesis. This paper proposed a robust image registration method for aligning a group of low dynamic range images (LDR) that are captured with different exposure times. Illumination change and photometric distortion between two images would result in inaccurate registration. We propose to transform intensity image data into phase congruency to eliminate the effect of the changes in image brightness and use phase cross correlation in the Fourier transform domain to perform image registration. Considering the presence of non-overlapped regions due to photometric distortion, evolutionary programming is applied to search for the accurate translation parameters so that the accuracy of registration is able to be achieved at a hundredth of a pixel level. The proposed algorithm works well for under and over-exposed image registration. It has been applied to align LDR images for synthesizing high quality HDR images..

Numerical optimization of piezolaminated beams under static and dynamic excitations

Directory of Open Access Journals (Sweden)

Rajan L. Wankhade

2017-06-01

Full Text Available Shape and vibration controls of smart structures in structural applications have gained much attraction due to their ability of actuation and sensing. The response of structure to bending, vibration, and buckling can be controlled by the use of this ability of a piezoelectric material. In the present work, the static and dynamic control of smart piezolaminated beams is presented. The optimal locations of piezoelectric patches are found out and then a detailed analysis is performed using finite element modeling considering the higher order shear deformation theory. In the first part, for an extension mode, the piezolaminated beam with stacking sequence PZT5/Al/PZT5 is considered. The length of the beam is 100 mm, whereas the thickness of an aluminum core is 16 mm and that of the piezo layer is of 1 mm. The PZT actuators are positioned with an identical poling direction along the thickness and are excited by a direct current voltage of 10 V. For the shear mode, the stacking sequence Al/PZT5/Al is adopted. The length of the beam is kept the same as the extension mechanism i.e. 100 mm, whereas the thickness of the aluminum core is 8 mm and that of the piezo layer is of 2 mm. The actuator is excited by a direct current voltage of 20 V. In the second part, the control of the piezolaminated beam with an optimal location of the actuator is investigated under a dynamic excitation. Electromechanical loading is considered in the finite element formulation for the analysis purpose. Results are provided for beams with different boundary conditions and loading for future references. Both the extension and shear actuation mechanisms are employed for the piezolaminated beam. These results may be used to identify the response of a beam under static and dynamic excitations. From the present work, the optimal location of a piezoelectric patch can be easily identified for the corresponding boundary condition of the beam.

METAHEURISTIC OPTIMIZATION METHODS FOR PARAMETERS ESTIMATION OF DYNAMIC SYSTEMS

Directory of Open Access Journals (Sweden)

V. Panteleev Andrei

2017-01-01

Full Text Available The article considers the usage of metaheuristic methods of constrained global optimization: “Big Bang - Big Crunch”, “Fireworks Algorithm”, “Grenade Explosion Method” in parameters of dynamic systems estimation, described with algebraic-differential equations. Parameters estimation is based upon the observation results from mathematical model behavior. Their values are derived after criterion minimization, which describes the total squared error of state vector coordinates from the deduced ones with precise values observation at different periods of time. Paral- lelepiped type restriction is imposed on the parameters values. Used for solving problems, metaheuristic methods of constrained global extremum don’t guarantee the result, but allow to get a solution of a rather good quality in accepta- ble amount of time. The algorithm of using metaheuristic methods is given. Alongside with the obvious methods for solving algebraic-differential equation systems, it is convenient to use implicit methods for solving ordinary differen- tial equation systems. Two ways of solving the problem of parameters evaluation are given, those parameters differ in their mathematical model. In the first example, a linear mathematical model describes the chemical action parameters change, and in the second one, a nonlinear mathematical model describes predator-prey dynamics, which characterize the changes in both kinds’ population. For each of the observed examples there are calculation results from all the three methods of optimization, there are also some recommendations for how to choose methods parameters. The obtained numerical results have demonstrated the efficiency of the proposed approach. The deduced parameters ap- proximate points slightly differ from the best known solutions, which were deduced differently. To refine the results one should apply hybrid schemes that combine classical methods of optimization of zero, first and second orders and

Morphing-Based Shape Optimization in Computational Fluid Dynamics

Science.gov (United States)

Rousseau, Yannick; Men'Shov, Igor; Nakamura, Yoshiaki

In this paper, a Morphing-based Shape Optimization (MbSO) technique is presented for solving Optimum-Shape Design (OSD) problems in Computational Fluid Dynamics (CFD). The proposed method couples Free-Form Deformation (FFD) and Evolutionary Computation, and, as its name suggests, relies on the morphing of shape and computational domain, rather than direct shape parameterization. Advantages of the FFD approach compared to traditional parameterization are first discussed. Then, examples of shape and grid deformations by FFD are presented. Finally, the MbSO approach is illustrated and applied through an example: the design of an airfoil for a future Mars exploration airplane.

Dynamic mesh optimization based on the spring analogy

Directory of Open Access Journals (Sweden)

Schmidt Jonas

2014-01-01

Full Text Available We present an implementation of the spring analogy for three dimensional meshes in OpenFOAM. All parameters of the spring system are treated as fields that can either be pre-defined by the user, or updated at each time step according to specified geometrical regions or diffusion equations. The purpose of the method is to provide a pre-processing tool for mesh optimization. We study three simple test cases, a deformed block, an airfoil and a hill, and we analyze the evolution of skewness, non-orthogonality and aspect ratio during the approach of dynamic equilibrium.

Dynamic Feedforward Control of a Diesel Engine Based on Optimal Transient Compensation Maps

Directory of Open Access Journals (Sweden)

Giorgio Mancini

2014-08-01

Full Text Available To satisfy the increasingly stringent emission regulations and a demand for an ever lower fuel consumption, diesel engines have become complex systems with many interacting actuators. As a consequence, these requirements are pushing control and calibration to their limits. The calibration procedure nowadays is still based mainly on engineering experience, which results in a highly iterative process to derive a complete engine calibration. Moreover, automatic tools are available only for stationary operation, to obtain control maps that are optimal with respect to some predefined objective function. Therefore, the exploitation of any leftover potential during transient operation is crucial. This paper proposes an approach to derive a transient feedforward (FF control system in an automated way. It relies on optimal control theory to solve a dynamic optimization problem for fast transients. A partially physics-based model is thereby used to replace the engine. From the optimal solutions, the relevant information is extracted and stored in maps spanned by the engine speed and the torque gradient. These maps complement the static control maps by accounting for the dynamic behavior of the engine. The procedure is implemented on a real engine and experimental results are presented along with the development of the methodology.

Optimal placement of excitations and sensors for verification of large dynamical systems

Science.gov (United States)

Salama, M.; Rose, T.; Garba, J.

1987-01-01

The computationally difficult problem of the optimal placement of excitations and sensors to maximize the observed measurements is studied within the framework of combinatorial optimization, and is solved numerically using a variation of the simulated annealing heuristic algorithm. Results of numerical experiments including a square plate and a 960 degrees-of-freedom Control of Flexible Structure (COFS) truss structure, are presented. Though the algorithm produces suboptimal solutions, its generality and simplicity allow the treatment of complex dynamical systems which would otherwise be difficult to handle.

In-Vivo High Dynamic Range Vector Flow Imaging

DEFF Research Database (Denmark)

Villagómez Hoyos, Carlos Armando; Stuart, Matthias Bo; Jensen, Jørgen Arendt

2015-01-01

example with a high dynamic velocity range. Velocities with an order of magnitude apart are detected on the femoral artery of a 41 years old healthy individual. Three distinct heart cycles are captured during a 3 secs acquisition. The estimated vector velocities are compared against each other within...... the heart cycle. The relative standard deviation of the measured velocity magnitude between the three peak systoles was found to be 5.11% with a standard deviation on the detected angle of 1.06◦ . In the diastole, it was 1.46% and 6.18◦ , respectively. Results proves that the method is able to estimate flow...

A high linearity current mode multiplier/divider with a wide dynamic range

International Nuclear Information System (INIS)

Liao Pengfei; Luo Ping; Zhang Bo; Li Zhaoji

2012-01-01

A high linearity current mode multiplier/divider (CMM/D) with a wide dynamic range is presented. The proposed CMM/D is based on the voltage—current characteristic of the diode, thus wide dynamic range is achieved. In addition, high linearity is achieved because high accuracy current mirrors are adopted and the output current is insensitive to the temperature and device parameters of the fabrication process. Furthermore, no extra bias current for all input signals is required and thus power saving is realized. With proper selection of establishing the input terminal, the proposed circuit can perform as a multifunction circuit to be operated as a multiplier/divider, without changing its topology. The proposed circuit is implemented in a 0.25 μm BCD process and the chip area is 0.26 × 0.24 mm 2 . The simulation and measurement results show that the maximum static linearity error is ±1.8% and the total harmonic distortion is 0.4% while the input current ranges from 0 to 200 μA. (semiconductor integrated circuits)

The Patch-Levy-Based Bees Algorithm Applied to Dynamic Optimization Problems

Directory of Open Access Journals (Sweden)

Wasim A. Hussein

2017-01-01

Full Text Available Many real-world optimization problems are actually of dynamic nature. These problems change over time in terms of the objective function, decision variables, constraints, and so forth. Therefore, it is very important to study the performance of a metaheuristic algorithm in dynamic environments to assess the robustness of the algorithm to deal with real-word problems. In addition, it is important to adapt the existing metaheuristic algorithms to perform well in dynamic environments. This paper investigates a recently proposed version of Bees Algorithm, which is called Patch-Levy-based Bees Algorithm (PLBA, on solving dynamic problems, and adapts it to deal with such problems. The performance of the PLBA is compared with other BA versions and other state-of-the-art algorithms on a set of dynamic multimodal benchmark problems of different degrees of difficulties. The results of the experiments show that PLBA achieves better results than the other BA variants. The obtained results also indicate that PLBA significantly outperforms some of the other state-of-the-art algorithms and is competitive with others.

Technique for increasing dynamic range of space-borne ion composition instruments

International Nuclear Information System (INIS)

Burch, J.L.; Miller, G.P.; Santos, A. de los; Pollock, C.J.; Pope, S.E.; Valek, P. W.; Young, D.T.

2005-01-01

The dynamic range of ion composition spectrometers is limited by several factors, including saturation of particle counters and spillover of signals from highly dominant species into channels tuned to minor species. Instruments designed for composition measurements of hot plasmas in space can suffer greatly from both of these problems because of the wide energy range required and the wide disparity in fluxes encountered in various regions of interest. In order to detect minor ions in regions of very weak fluxes, geometry factors need to be as large as possible within the mass and volume resources available. As a result, problems with saturation by the dominant fluxes and spillover to minor-ion channels in plasma regions with intense fluxes become especially acute. This article reports on a technique for solving the dynamic-range problem in the few eV to several keV energy/charge range that is of central importance for space physics research where the dominant ion is of low mass/charge (typically H + ), and the minor ions are of higher mass/charge (typically O + ). The technique involves employing a radio-frequency modulation of the deflection electric field in the back section of an electrostatic analyzer in a time-of-flight instrument. This technique is shown to reduce H + counts by a controllable amount of up to factors of 1000 while reducing O + counts by only a few percent that can be calibrated

Microspatial ecotone dynamics at a shifting range limit: plant-soil variation across salt marsh-mangrove interfaces.

Science.gov (United States)

Yando, E S; Osland, M J; Hester, M W

2018-05-01

Ecotone dynamics and shifting range limits can be used to advance our understanding of the ecological implications of future range expansions in response to climate change. In the northern Gulf of Mexico, the salt marsh-mangrove ecotone is an area where range limits and ecotone dynamics can be studied in tandem as recent decreases in winter temperature extremes have allowed for mangrove expansion at the expense of salt marsh. In this study, we assessed aboveground and belowground plant-soil dynamics across the salt marsh-mangrove ecotone quantifying micro-spatial patterns in horizontal extent. Specifically, we studied vegetation and rooting dynamics of large and small trees, the impact of salt marshes (e.g. species and structure) on mangroves, and the influence of vegetation on soil properties along transects from underneath the mangrove canopy into the surrounding salt marsh. Vegetation and rooting dynamics differed in horizontal reach, and there was a positive relationship between mangrove tree height and rooting extent. We found that the horizontal expansion of mangrove roots into salt marsh extended up to eight meters beyond the aboveground boundary. Variation in vegetation structure and local hydrology appear to control mangrove seedling dynamics. Finally, soil carbon density and organic matter did not differ within locations across the salt marsh-mangrove interface. By studying aboveground and belowground variation across the ecotone, we can better predict the ecological effects of continued range expansion in response to climate change.

Microspatial ecotone dynamics at a shifting range limit: plant–soil variation across salt marsh–mangrove interfaces

Science.gov (United States)

Yando, Erik S.; Osland, Michael J.; Hester, Mark H.

2018-01-01

Ecotone dynamics and shifting range limits can be used to advance our understanding of the ecological implications of future range expansions in response to climate change. In the northern Gulf of Mexico, the salt marsh–mangrove ecotone is an area where range limits and ecotone dynamics can be studied in tandem as recent decreases in winter temperature extremes have allowed for mangrove expansion at the expense of salt marsh. In this study, we assessed aboveground and belowground plant–soil dynamics across the salt marsh–mangrove ecotone quantifying micro-spatial patterns in horizontal extent. Specifically, we studied vegetation and rooting dynamics of large and small trees, the impact of salt marshes (e.g. species and structure) on mangroves, and the influence of vegetation on soil properties along transects from underneath the mangrove canopy into the surrounding salt marsh. Vegetation and rooting dynamics differed in horizontal reach, and there was a positive relationship between mangrove tree height and rooting extent. We found that the horizontal expansion of mangrove roots into salt marsh extended up to eight meters beyond the aboveground boundary. Variation in vegetation structure and local hydrology appear to control mangrove seedling dynamics. Finally, soil carbon density and organic matter did not differ within locations across the salt marsh-mangrove interface. By studying aboveground and belowground variation across the ecotone, we can better predict the ecological effects of continued range expansion in response to climate change.

Increasing the Lifetime of Mobile WSNs via Dynamic Optimization of Sensor Node Communication Activity

Directory of Open Access Journals (Sweden)

Dayan Adionel Guimarães

2016-09-01

Full Text Available In this paper, a simple and flexible method for increasing the lifetime of fixed or mobile wireless sensor networks is proposed. Based on past residual energy information reported by the sensor nodes, the sink node or another central node dynamically optimizes the communication activity levels of the sensor nodes to save energy without sacrificing the data throughput. The activity levels are defined to represent portions of time or time-frequency slots in a frame, during which the sensor nodes are scheduled to communicate with the sink node to report sensory measurements. Besides node mobility, it is considered that sensors’ batteries may be recharged via a wireless power transmission or equivalent energy harvesting scheme, bringing to the optimization problem an even more dynamic character. We report large increased lifetimes over the non-optimized network and comparable or even larger lifetime improvements with respect to an idealized greedy algorithm that uses both the real-time channel state and the residual energy information.

Increasing the Lifetime of Mobile WSNs via Dynamic Optimization of Sensor Node Communication Activity.

Science.gov (United States)

Guimarães, Dayan Adionel; Sakai, Lucas Jun; Alberti, Antonio Marcos; de Souza, Rausley Adriano Amaral

2016-09-20

In this paper, a simple and flexible method for increasing the lifetime of fixed or mobile wireless sensor networks is proposed. Based on past residual energy information reported by the sensor nodes, the sink node or another central node dynamically optimizes the communication activity levels of the sensor nodes to save energy without sacrificing the data throughput. The activity levels are defined to represent portions of time or time-frequency slots in a frame, during which the sensor nodes are scheduled to communicate with the sink node to report sensory measurements. Besides node mobility, it is considered that sensors' batteries may be recharged via a wireless power transmission or equivalent energy harvesting scheme, bringing to the optimization problem an even more dynamic character. We report large increased lifetimes over the non-optimized network and comparable or even larger lifetime improvements with respect to an idealized greedy algorithm that uses both the real-time channel state and the residual energy information.

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

Science.gov (United States)

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.

An Optimization Method for Virtual Globe Ocean Surface Dynamic Visualization

Directory of Open Access Journals (Sweden)

HUANG Wumeng

2016-12-01

Full Text Available The existing visualization method in the virtual globe mainly uses the projection grid to organize the ocean grid. This special grid organization has the defects in reflecting the difference characteristics of different ocean areas. The method of global ocean visualization based on global discrete grid can make up the defect of the projection grid method by matching with the discrete space of the virtual globe, so it is more suitable for the virtual ocean surface simulation application.But the available global discrete grids method has many problems which limiting its application such as the low efficiency of rendering and loading, the need of repairing grid crevices. To this point, we propose an optimization for the global discrete grids method. At first, a GPU-oriented multi-scale grid model of ocean surface which develops on the foundation of global discrete grids was designed to organize and manage the ocean surface grids. Then, in order to achieve the wind-drive wave dynamic rendering, this paper proposes a dynamic wave rendering method based on the multi-scale ocean surface grid model to support real-time wind field updating. At the same time, considering the effect of repairing grid crevices on the system efficiency, this paper presents an efficient method for repairing ocean surface grid crevices based on the characteristics of ocean grid and GPU technology. At last, the feasibility and validity of the method are verified by the comparison experiment. The experimental results show that the proposed method is efficient, stable and fast, and can compensate for the lack of function of the existing methods, so the application range is more extensive.

Optimal Linear Responses for Markov Chains and Stochastically Perturbed Dynamical Systems

Science.gov (United States)

Antown, Fadi; Dragičević, Davor; Froyland, Gary

2018-03-01

The linear response of a dynamical system refers to changes to properties of the system when small external perturbations are applied. We consider the little-studied question of selecting an optimal perturbation so as to (i) maximise the linear response of the equilibrium distribution of the system, (ii) maximise the linear response of the expectation of a specified observable, and (iii) maximise the linear response of the rate of convergence of the system to the equilibrium distribution. We also consider the inhomogeneous, sequential, or time-dependent situation where the governing dynamics is not stationary and one wishes to select a sequence of small perturbations so as to maximise the overall linear response at some terminal time. We develop the theory for finite-state Markov chains, provide explicit solutions for some illustrative examples, and numerically apply our theory to stochastically perturbed dynamical systems, where the Markov chain is replaced by a matrix representation of an approximate annealed transfer operator for the random dynamical system.

UMER: An analog computer for dynamics of swarms interacting via long-range forces

International Nuclear Information System (INIS)

Kishek, R.A.; Bai, G.; Bernal, S.; Feldman, D.; Godlove, T.F.; Haber, I.; O'Shea, P.G.; Quinn, B.; Papadopoulos, C.; Reiser, M.; Stratakis, D.; Tian, K.; Tobin, C.J.; Walter, M.

2006-01-01

Some of the most challenging and interesting problems in nature involve large numbers of objects or particles mutually interacting through long-range forces. Examples range from galaxies and plasmas to flocks of birds and traffic flow on a highway. Even in cases where the form of the interacting force is precisely known, such as the 1/r 2 -dependent Coulomb and gravitational forces, such problems present a formidable theoretical and modeling challenge for large numbers of interacting bodies. This paper reports on a newly constructed, scaled particle accelerator that will serve as an experimental testbed for the dynamics of swarms interacting through long-range forces. Primarily designed for intense beam dynamics studies for advanced accelerators, the University of Maryland Electron Ring (UMER) design is described in detail and an update on commissioning is provided. An example application to a system other than a charged particle beam is discussed

Pair-Wise and Many-Body Dispersive Interactions Coupled to an Optimally Tuned Range-Separated Hybrid Functional.

Science.gov (United States)

Agrawal, Piyush; Tkatchenko, Alexandre; Kronik, Leeor

2013-08-13

We propose a nonempirical, pair-wise or many-body dispersion-corrected, optimally tuned range-separated hybrid functional. This functional retains the advantages of the optimal-tuning approach in the prediction of the electronic structure. At the same time, it gains accuracy in the prediction of binding energies for dispersively bound systems, as demonstrated on the S22 and S66 benchmark sets of weakly bound dimers.

Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune

The design of measurement programs devoted to parameter identification of structural dynamic systems is considered. The design problem is formulated as an optimization problem to minimize the total expected cost that is the cost of failure and the cost of the measurement program. All...... the calculations are based on a priori knowledge and engineering judgement. One of the contribution of the approach is that the optimal number of sensors can be estimated. This is shown in a numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement program...

Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune

The design of a measured program devoted to parameter identification of structural dynamic systems is considered, the design problem is formulated as an optimization problem due to minimize the total expected cost of the measurement program. All the calculations are based on a priori knowledge...... and engineering judgement. One of the contribution of the approach is that the optimal nmber of sensors can be estimated. This is sown in an numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement program for estimating the modal damping parameters...

Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune

1993-01-01

The design of a measurement program devoted to parameter identification of structural dynamic systems is considered. The design problem is formulated as an optimization problem to minimize the total expected cost that is the cost of failure and the cost of the measurement program. All...... the calculations are based on a priori knowledge and engineering judgement. One of the contribution of the approach is that the optimal number of sensory can be estimated. This is shown in an numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement...

Optimal Design of Measurement Programs for the Parameter Identification of Dynamic Systems

DEFF Research Database (Denmark)

Kirkegaard, Poul Henning; Sørensen, John Dalsgaard; Brincker, Rune

1991-01-01

The design of a measurement program devoted to parameter identification of structural dynamic systems is considered. The design problem is formulated as an optimization problem to minimize the total expected cost, i.e. the cost of failure and the cost of the measurement program. All...... the calculations are based on a priori knowledge and engineering judgement. One of the contributions of the approach is that the optimal number of sensors can be estimated. This is shown in a numerical example where the proposed approach is demonstrated. The example is concerned with design of a measurement...

Optimal dynamic water allocation: Irrigation extractions and environmental tradeoffs in the Murray River, Australia

Science.gov (United States)

Grafton, R. Quentin; Chu, Hoang Long; Stewardson, Michael; Kompas, Tom

2011-12-01

A key challenge in managing semiarid basins, such as in the Murray-Darling in Australia, is to balance the trade-offs between the net benefits of allocating water for irrigated agriculture, and other uses, versus the costs of reduced surface flows for the environment. Typically, water planners do not have the tools to optimally and dynamically allocate water among competing uses. We address this problem by developing a general stochastic, dynamic programming model with four state variables (the drought status, the current weather, weather correlation, and current storage) and two controls (environmental release and irrigation allocation) to optimally allocate water between extractions and in situ uses. The model is calibrated to Australia's Murray River that generates: (1) a robust qualitative result that "pulse" or artificial flood events are an optimal way to deliver environmental flows over and above conveyance of base flows; (2) from 2001 to 2009 a water reallocation that would have given less to irrigated agriculture and more to environmental flows would have generated between half a billion and over 3 billion U.S. dollars in overall economic benefits; and (3) water markets increase optimal environmental releases by reducing the losses associated with reduced water diversions.

Dynamic programming approach for partial decision rule optimization

KAUST Repository

Amin, Talha

2012-10-04

This paper is devoted to the study of an extension of dynamic programming approach which allows optimization of partial decision rules relative to the length or coverage. We introduce an uncertainty measure J(T) which is the difference between number of rows in a decision table T and number of rows with the most common decision for T. For a nonnegative real number γ, we consider γ-decision rules (partial decision rules) that localize rows in subtables of T with uncertainty at most γ. Presented algorithm constructs a directed acyclic graph Δ γ(T) which nodes are subtables of the decision table T given by systems of equations of the kind "attribute = value". This algorithm finishes the partitioning of a subtable when its uncertainty is at most γ. The graph Δ γ(T) allows us to describe the whole set of so-called irredundant γ-decision rules. We can optimize such set of rules according to length or coverage. This paper contains also results of experiments with decision tables from UCI Machine Learning Repository.

Dynamic programming approach for partial decision rule optimization

KAUST Repository

Amin, Talha M.; Chikalov, Igor; Moshkov, Mikhail; Zielosko, Beata

2012-01-01

This paper is devoted to the study of an extension of dynamic programming approach which allows optimization of partial decision rules relative to the length or coverage. We introduce an uncertainty measure J(T) which is the difference between number of rows in a decision table T and number of rows with the most common decision for T. For a nonnegative real number γ, we consider γ-decision rules (partial decision rules) that localize rows in subtables of T with uncertainty at most γ. Presented algorithm constructs a directed acyclic graph Δ γ(T) which nodes are subtables of the decision table T given by systems of equations of the kind "attribute = value". This algorithm finishes the partitioning of a subtable when its uncertainty is at most γ. The graph Δ γ(T) allows us to describe the whole set of so-called irredundant γ-decision rules. We can optimize such set of rules according to length or coverage. This paper contains also results of experiments with decision tables from UCI Machine Learning Repository.

Optimization of Regional Geodynamic Models for Mantle Dynamics

Science.gov (United States)

Knepley, M.; Isaac, T.; Jadamec, M. A.

2016-12-01

The SubductionGenerator program is used to construct high resolution, 3D regional thermal structures for mantle convection simulations using a variety of data sources, including sea floor ages and geographically referenced 3D slab locations based on seismic observations. The initial bulk temperature field is constructed using a half-space cooling model or plate cooling model, and related smoothing functions based on a diffusion length-scale analysis. In this work, we seek to improve the 3D thermal model and test different model geometries and dynamically driven flow fields using constraints from observed seismic velocities and plate motions. Through a formal adjoint analysis, we construct the primal-dual version of the multi-objective PDE-constrained optimization problem for the plate motions and seismic misfit. We have efficient, scalable preconditioners for both the forward and adjoint problems based upon a block preconditioning strategy, and a simple gradient update is used to improve the control residual. The full optimal control problem is formulated on a nested hierarchy of grids, allowing a nonlinear multigrid method to accelerate the solution.

Optimal Design of a High Efficiency LLC Resonant Converter with a Narrow Frequency Range for Voltage Regulation

Directory of Open Access Journals (Sweden)

Junhao Luo

2018-05-01

Full Text Available As a key factor in the design of a voltage-adjustable LLC resonant converter, frequency regulation range is very important to the optimization of magnetic components and efficiency improvement. This paper presents a novel optimal design method for LLC resonant converters, which can narrow the frequency variation range and ensure high efficiency under the premise of a required gain achievement. A simplified gain model was utilized to simplify the calculation and the expected efficiency was initially set as 96.5%. The restricted area of parameter optimization design can be obtained by taking the intersection of the gain requirement, the efficiency requirement, and three restrictions of ZVS (Zero Voltage Switch. The proposed method was verified by simulation and experiments of a 150 W prototype. The results show that the proposed method can achieve ZVS from full-load to no-load conditions and can reach 1.6 times the normalized voltage gain in the frequency variation range of 18 kHz with a peak efficiency of up to 96.3%. Moreover, the expected efficiency is adjustable, which means a converter with a higher efficiency can be designed. The proposed method can also be used for the design of large-power LLC resonant converters to obtain a wide output voltage range and higher efficiency.

Sensitivity of the Speech Intelligibility Index to the Assumed Dynamic Range

Science.gov (United States)

Jin, In-Ki; Kates, James M.; Arehart, Kathryn H.

2017-01-01

Purpose: This study aims to evaluate the sensitivity of the speech intelligibility index (SII) to the assumed speech dynamic range (DR) in different languages and with different types of stimuli. Method: Intelligibility prediction uses the absolute transfer function (ATF) to map the SII value to the predicted intelligibility for a given stimuli.…

Optimized balance rehabilitation training strategy for the elderly through an evaluation of balance characteristics in response to dynamic motions

Science.gov (United States)

Jung, HoHyun; Chun, Keyoung Jin; Hong, Jaesoo; Lim, Dohyung

2015-01-01

Balance is important in daily activities and essential for maintaining an independent lifestyle in the elderly. Recent studies have shown that balance rehabilitation training can improve the balance ability of the elderly, and diverse balance rehabilitation training equipment has been developed. However, there has been little research into optimized strategies for balance rehabilitation training. To provide an optimized strategy, we analyzed the balance characteristics of participants in response to the rotation of a base plate on multiple axes. Seven male adults with no musculoskeletal or nervous system-related diseases (age: 25.5±1.7 years; height: 173.9±6.4 cm; body mass: 71.3±6.5 kg; body mass index: 23.6±2.4 kg/m2) were selected to investigate the balance rehabilitation training using customized rehabilitation equipment. Rotation of the base plate of the equipment was controlled to induce dynamic rotation of participants in the anterior–posterior, right-diagonal, medial–lateral, and left-diagonal directions. We used a three-dimensional motion capture system employing infrared cameras and the Pedar Flexible Insoles System to characterize the major lower-extremity joint angles, center of body mass, and center of pressure. We found statistically significant differences between the changes in joint angles in the lower extremities in response to dynamic rotation of the participants (P0.05). These results indicate that optimizing rotation control of the base plate of balance rehabilitation training equipment to induce anterior–posterior and medial–lateral dynamic rotation preferentially can lead to effective balance training. Additional tests with varied speeds and ranges of angles of base plate rotation are expected to be useful as well as an analysis of the balance characteristics considering a balance index that reflects the muscle activity and cooperative characteristics. PMID:26508847

Empirical study of long-range connections in a road network offers new ingredient for navigation optimization models

Science.gov (United States)

Wang, Pu; Liu, Like; Li, Xiamiao; Li, Guanliang; González, Marta C.

2014-01-01

Navigation problem in lattices with long-range connections has been widely studied to understand the design principles for optimal transport networks; however, the travel cost of long-range connections was not considered in previous models. We define long-range connection in a road network as the shortest path between a pair of nodes through highways and empirically analyze the travel cost properties of long-range connections. Based on the maximum speed allowed in each road segment, we observe that the time needed to travel through a long-range connection has a characteristic time Th ˜ 29 min, while the time required when using the alternative arterial road path has two different characteristic times Ta ˜ 13 and 41 min and follows a power law for times larger than 50 min. Using daily commuting origin-destination matrix data, we additionally find that the use of long-range connections helps people to save about half of the travel time in their daily commute. Based on the empirical results, we assign a more realistic travel cost to long-range connections in two-dimensional square lattices, observing dramatically different minimum average shortest path but similar optimal navigation conditions.

Dynamic optimization of maintenance and improvement planning for water main system: Periodic replacement approach

Energy Technology Data Exchange (ETDEWEB)

Kim, Jong Woo; Choi, Go Bong; Lee, Jong Min [Seoul National University, Seoul (Korea, Republic of); Suh, Jung Chul [Samchully Corporation, Seoul (Korea, Republic of)

2016-01-15

This paper proposes a Markov decision process (MDP) based approach to derive an optimal schedule of maintenance, rehabilitation and replacement of the water main system. The scheduling problem utilizes auxiliary information of a pipe such as the current state, cost, and deterioration model. The objective function and detailed algorithm of dynamic programming are modified to solve the periodic replacement problem. The optimal policy evaluated by the proposed algorithm is compared to several existing policies via Monte Carlo simulations. The proposed decision framework provides a systematic way to obtain an optimal policy.

Optimizing meridional advection of the Advanced Research WRF (ARW) dynamics for Intel Xeon Phi coprocessor

Science.gov (United States)

Mielikainen, Jarno; Huang, Bormin; Huang, Allen H.-L.

2015-05-01

The most widely used community weather forecast and research model in the world is the Weather Research and Forecast (WRF) model. Two distinct varieties of WRF exist. The one we are interested is the Advanced Research WRF (ARW) is an experimental, advanced research version featuring very high resolution. The WRF Nonhydrostatic Mesoscale Model (WRF-NMM) has been designed for forecasting operations. WRF consists of dynamics code and several physics modules. The WRF-ARW core is based on an Eulerian solver for the fully compressible nonhydrostatic equations. In the paper, we optimize a meridional (north-south direction) advection subroutine for Intel Xeon Phi coprocessor. Advection is of the most time consuming routines in the ARW dynamics core. It advances the explicit perturbation horizontal momentum equations by adding in the large-timestep tendency along with the small timestep pressure gradient tendency. We will describe the challenges we met during the development of a high-speed dynamics code subroutine for MIC architecture. Furthermore, lessons learned from the code optimization process will be discussed. The results show that the optimizations improved performance of the original code on Xeon Phi 7120P by a factor of 1.2x.

Dynamic PET of human liver inflammation: impact of kinetic modeling with optimization-derived dual-blood input function.

Science.gov (United States)

Wang, Guobao; Corwin, Michael T; Olson, Kristin A; Badawi, Ramsey D; Sarkar, Souvik

2018-05-30

The hallmark of nonalcoholic steatohepatitis is hepatocellular inflammation and injury in the setting of hepatic steatosis. Recent work has indicated that dynamic 18F-FDG PET with kinetic modeling has the potential to assess hepatic inflammation noninvasively, while static FDG-PET did not show a promise. Because the liver has dual blood supplies, kinetic modeling of dynamic liver PET data is challenging in human studies. The objective of this study is to evaluate and identify a dual-input kinetic modeling approach for dynamic FDG-PET of human liver inflammation. Fourteen human patients with nonalcoholic fatty liver disease were included in the study. Each patient underwent one-hour dynamic FDG-PET/CT scan and had liver biopsy within six weeks. Three models were tested for kinetic analysis: traditional two-tissue compartmental model with an image-derived single-blood input function (SBIF), model with population-based dual-blood input function (DBIF), and modified model with optimization-derived DBIF through a joint estimation framework. The three models were compared using Akaike information criterion (AIC), F test and histopathologic inflammation reference. The results showed that the optimization-derived DBIF model improved the fitting of liver time activity curves and achieved lower AIC values and higher F values than the SBIF and population-based DBIF models in all patients. The optimization-derived model significantly increased FDG K1 estimates by 101% and 27% as compared with traditional SBIF and population-based DBIF. K1 by the optimization-derived model was significantly associated with histopathologic grades of liver inflammation while the other two models did not provide a statistical significance. In conclusion, modeling of DBIF is critical for kinetic analysis of dynamic liver FDG-PET data in human studies. The optimization-derived DBIF model is more appropriate than SBIF and population-based DBIF for dynamic FDG-PET of liver inflammation. © 2018

Utilizing multiple state variables to improve the dynamic range of analog switching in a memristor

International Nuclear Information System (INIS)

Jeong, YeonJoo; Kim, Sungho; Lu, Wei D.

2015-01-01

Memristors and memristive systems have been extensively studied for data storage and computing applications such as neuromorphic systems. To act as synapses in neuromorphic systems, the memristor needs to exhibit analog resistive switching (RS) behavior with incremental conductance change. In this study, we show that the dynamic range of the analog RS behavior can be significantly enhanced in a tantalum-oxide-based memristor. By controlling different state variables enabled by different physical effects during the RS process, the gradual filament expansion stage can be selectively enhanced without strongly affecting the abrupt filament length growth stage. Detailed physics-based modeling further verified the observed experimental effects and revealed the roles of oxygen vacancy drift and diffusion processes, and how the diffusion process can be selectively enhanced during the filament expansion stage. These findings lead to more desirable and reliable memristor behaviors for analog computing applications. Additionally, the ability to selectively control different internal physical processes demonstrated in the current study provides guidance for continued device optimization of memristor devices in general

Modelling of Rabies Transmission Dynamics Using Optimal Control Analysis

Directory of Open Access Journals (Sweden)

Joshua Kiddy K. Asamoah

2017-01-01

Full Text Available We examine an optimal way of eradicating rabies transmission from dogs into the human population, using preexposure prophylaxis (vaccination and postexposure prophylaxis (treatment due to public education. We obtain the disease-free equilibrium, the endemic equilibrium, the stability, and the sensitivity analysis of the optimal control model. Using the Latin hypercube sampling (LHS, the forward-backward sweep scheme and the fourth-order Range-Kutta numerical method predict that the global alliance for rabies control’s aim of working to eliminate deaths from canine rabies by 2030 is attainable through mass vaccination of susceptible dogs and continuous use of pre- and postexposure prophylaxis in humans.

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

Science.gov (United States)

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

2015-04-01

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

Internatonial Conference on Modeling, Optimization and Dynamics 2010 and the 5th Bioeconomy Conference 2012

CERN Document Server

Zilberman, David

2014-01-01

This volume explores the emerging and current, cutting-edge theories and methods of modeling, optimization, dynamics and bioeconomy. It provides an overview of the main issues, results and open questions in these fields as well as covers applications to biology, economy, energy, industry, physics, psychology and finance. The majority of the contributed papers for this volume come from the participants of the International Conference on Modeling, Optimization and Dynamics (ICMOD 2010), a satellite conference of EURO Mathematical Physics and MathematicsIV Lisbon 2010, which took place at Faculty of Sciences of University of Porto, Portugal, and from the Berkeley Bioeconomy Conference 2012, at the University of California, Berkeley, USA.

Impacts of land cover data selection and trait parameterisation on dynamic modelling of species' range expansion.

Directory of Open Access Journals (Sweden)

Risto K Heikkinen

Full Text Available Dynamic models for range expansion provide a promising tool for assessing species' capacity to respond to climate change by shifting their ranges to new areas. However, these models include a number of uncertainties which may affect how successfully they can be applied to climate change oriented conservation planning. We used RangeShifter, a novel dynamic and individual-based modelling platform, to study two potential sources of such uncertainties: the selection of land cover data and the parameterization of key life-history traits. As an example, we modelled the range expansion dynamics of two butterfly species, one habitat specialist (Maniola jurtina and one generalist (Issoria lathonia. Our results show that projections of total population size, number of occupied grid cells and the mean maximal latitudinal range shift were all clearly dependent on the choice made between using CORINE land cover data vs. using more detailed grassland data from three alternative national databases. Range expansion was also sensitive to the parameterization of the four considered life-history traits (magnitude and probability of long-distance dispersal events, population growth rate and carrying capacity, with carrying capacity and magnitude of long-distance dispersal showing the strongest effect. Our results highlight the sensitivity of dynamic species population models to the selection of existing land cover data and to uncertainty in the model parameters and indicate that these need to be carefully evaluated before the models are applied to conservation planning.

Optimal interdependence enhances robustness of complex systems

OpenAIRE

Singh, R. K.; Sinha, Sitabhra

2017-01-01

While interdependent systems have usually been associated with increased fragility, we show that strengthening the interdependence between dynamical processes on different networks can make them more robust. By coupling the dynamics of networks that in isolation exhibit catastrophic collapse with extinction of nodal activity, we demonstrate system-wide persistence of activity for an optimal range of interdependence between the networks. This is related to the appearance of attractors of the g...

Optimal dynamic pricing and replenishment policies for deteriorating items

Directory of Open Access Journals (Sweden)

Masoud Rabbani

2014-08-01

Full Text Available Marketing strategies and proper inventory replenishment policies are often incorporated by enterprises to stimulate demand and maximize profit. The aim of this paper is to represent an integrated model for dynamic pricing and inventory control of deteriorating items. To reflect the dynamic characteristic of the problem, the selling price is defined as a time-dependent function of the initial selling price and the discount rate. In this regard, the price is exponentially discounted to compensate negative impact of the deterioration. The planning horizon is assumed to be infinite and the deterioration rate is time-dependent. In addition to price, the demand rate is dependent on advertisement as a powerful marketing tool. Several theoretical results and an iterative solution algorithm are developed to provide the optimal solution. Finally, to show validity of the model and illustrate the solution procedure, numerical results are presented.

Enhancement tuning and control for high dynamic range images in multi-scale locally adaptive contrast enhancement algorithms

Science.gov (United States)

Cvetkovic, Sascha D.; Schirris, Johan; de With, Peter H. N.

2009-01-01

For real-time imaging in surveillance applications, visibility of details is of primary importance to ensure customer confidence. If we display High Dynamic-Range (HDR) scenes whose contrast spans four or more orders of magnitude on a conventional monitor without additional processing, results are unacceptable. Compression of the dynamic range is therefore a compulsory part of any high-end video processing chain because standard monitors are inherently Low- Dynamic Range (LDR) devices with maximally two orders of display dynamic range. In real-time camera processing, many complex scenes are improved with local contrast enhancements, bringing details to the best possible visibility. In this paper, we show how a multi-scale high-frequency enhancement scheme, in which gain is a non-linear function of the detail energy, can be used for the dynamic range compression of HDR real-time video camera signals. We also show the connection of our enhancement scheme to the processing way of the Human Visual System (HVS). Our algorithm simultaneously controls perceived sharpness, ringing ("halo") artifacts (contrast) and noise, resulting in a good balance between visibility of details and non-disturbance of artifacts. The overall quality enhancement, suitable for both HDR and LDR scenes, is based on a careful selection of the filter types for the multi-band decomposition and a detailed analysis of the signal per frequency band.

Fast and robust wavelet-based dynamic range compression and contrast enhancement model with color restoration

Science.gov (United States)

Unaldi, Numan; Asari, Vijayan K.; Rahman, Zia-ur

2009-05-01

Recently we proposed a wavelet-based dynamic range compression algorithm to improve the visual quality of digital images captured from high dynamic range scenes with non-uniform lighting conditions. The fast image enhancement algorithm that provides dynamic range compression, while preserving the local contrast and tonal rendition, is also a good candidate for real time video processing applications. Although the colors of the enhanced images produced by the proposed algorithm are consistent with the colors of the original image, the proposed algorithm fails to produce color constant results for some "pathological" scenes that have very strong spectral characteristics in a single band. The linear color restoration process is the main reason for this drawback. Hence, a different approach is required for the final color restoration process. In this paper the latest version of the proposed algorithm, which deals with this issue is presented. The results obtained by applying the algorithm to numerous natural images show strong robustness and high image quality.

Optimal Dynamic Strategies for Index Tracking and Algorithmic Trading

Science.gov (United States)

Ward, Brian

In this thesis we study dynamic strategies for index tracking and algorithmic trading. Tracking problems have become ever more important in Financial Engineering as investors seek to precisely control their portfolio risks and exposures over different time horizons. This thesis analyzes various tracking problems and elucidates the tracking errors and strategies one can employ to minimize those errors and maximize profit. In Chapters 2 and 3, we study the empirical tracking properties of exchange traded funds (ETFs), leveraged ETFs (LETFs), and futures products related to spot gold and the Chicago Board Option Exchange (CBOE) Volatility Index (VIX), respectively. These two markets provide interesting and differing examples for understanding index tracking. We find that static strategies work well in the nonleveraged case for gold, but fail to track well in the corresponding leveraged case. For VIX, tracking via neither ETFs, nor futures\\ portfolios succeeds, even in the nonleveraged case. This motivates the need for dynamic strategies, some of which we construct in these two chapters and further expand on in Chapter 4. There, we analyze a framework for index tracking and risk exposure control through financial derivatives. We derive a tracking condition that restricts our exposure choices and also define a slippage process that characterizes the deviations from the index over longer horizons. The framework is applied to a number of models, for example, Black Scholes model and Heston model for equity index tracking, as well as the Square Root (SQR) model and the Concatenated Square Root (CSQR) model for VIX tracking. By specifying how each of these models fall into our framework, we are able to understand the tracking errors in each of these models. Finally, Chapter 5 analyzes a tracking problem of a different kind that arises in algorithmic trading: schedule following for optimal execution. We formulate and solve a stochastic control problem to obtain the optimal

A Quasi-Dynamic Optimal Control Strategy for Non-Linear Multivariable Processes Based upon Non-Quadratic Objective Functions

Directory of Open Access Journals (Sweden)

Jens G. Balchen

1984-10-01

Full Text Available The problem of systematic derivation of a quasi-dynamic optimal control strategy for a non-linear dynamic process based upon a non-quadratic objective function is investigated. The wellknown LQG-control algorithm does not lead to an optimal solution when the process disturbances have non-zero mean. The relationships between the proposed control algorithm and LQG-control are presented. The problem of how to constrain process variables by means of 'penalty' - terms in the objective function is dealt with separately.

Dynameomics: a multi-dimensional analysis-optimized database for dynamic protein data.

Science.gov (United States)

Kehl, Catherine; Simms, Andrew M; Toofanny, Rudesh D; Daggett, Valerie

2008-06-01

The Dynameomics project is our effort to characterize the native-state dynamics and folding/unfolding pathways of representatives of all known protein folds by way of molecular dynamics simulations, as described by Beck et al. (in Protein Eng. Des. Select., the first paper in this series). The data produced by these simulations are highly multidimensional in structure and multi-terabytes in size. Both of these features present significant challenges for storage, retrieval and analysis. For optimal data modeling and flexibility, we needed a platform that supported both multidimensional indices and hierarchical relationships between related types of data and that could be integrated within our data warehouse, as described in the accompanying paper directly preceding this one. For these reasons, we have chosen On-line Analytical Processing (OLAP), a multi-dimensional analysis optimized database, as an analytical platform for these data. OLAP is a mature technology in the financial sector, but it has not been used extensively for scientific analysis. Our project is further more unusual for its focus on the multidimensional and analytical capabilities of OLAP rather than its aggregation capacities. The dimensional data model and hierarchies are very flexible. The query language is concise for complex analysis and rapid data retrieval. OLAP shows great promise for the dynamic protein analysis for bioengineering and biomedical applications. In addition, OLAP may have similar potential for other scientific and engineering applications involving large and complex datasets.

A comparative analysis of particle swarm optimization and differential evolution algorithms for parameter estimation in nonlinear dynamic systems

International Nuclear Information System (INIS)

Banerjee, Amit; Abu-Mahfouz, Issam

2014-01-01

The use of evolutionary algorithms has been popular in recent years for solving the inverse problem of identifying system parameters given the chaotic response of a dynamical system. The inverse problem is reformulated as a minimization problem and population-based optimizers such as evolutionary algorithms have been shown to be efficient solvers of the minimization problem. However, to the best of our knowledge, there has been no published work that evaluates the efficacy of using the two most popular evolutionary techniques – particle swarm optimization and differential evolution algorithm, on a wide range of parameter estimation problems. In this paper, the two methods along with their variants (for a total of seven algorithms) are applied to fifteen different parameter estimation problems of varying degrees of complexity. Estimation results are analyzed using nonparametric statistical methods to identify if an algorithm is statistically superior to others over the class of problems analyzed. Results based on parameter estimation quality suggest that there are significant differences between the algorithms with the newer, more sophisticated algorithms performing better than their canonical versions. More importantly, significant differences were also found among variants of the particle swarm optimizer and the best performing differential evolution algorithm

Optimization of a continuous hybrid impeller mixer via computational fluid dynamics.

Science.gov (United States)

Othman, N; Kamarudin, S K; Takriff, M S; Rosli, M I; Engku Chik, E M F; Meor Adnan, M A K

2014-01-01

This paper presents the preliminary steps required for conducting experiments to obtain the optimal operating conditions of a hybrid impeller mixer and to determine the residence time distribution (RTD) using computational fluid dynamics (CFD). In this paper, impeller speed and clearance parameters are examined. The hybrid impeller mixer consists of a single Rushton turbine mounted above a single pitched blade turbine (PBT). Four impeller speeds, 50, 100, 150, and 200 rpm, and four impeller clearances, 25, 50, 75, and 100 mm, were the operation variables used in this study. CFD was utilized to initially screen the parameter ranges to reduce the number of actual experiments needed. Afterward, the residence time distribution (RTD) was determined using the respective parameters. Finally, the Fluent-predicted RTD and the experimentally measured RTD were compared. The CFD investigations revealed that an impeller speed of 50 rpm and an impeller clearance of 25 mm were not viable for experimental investigations and were thus eliminated from further analyses. The determination of RTD using a k-ε turbulence model was performed using CFD techniques. The multiple reference frame (MRF) was implemented and a steady state was initially achieved followed by a transient condition for RTD determination.

Dynamic whole body PET parametric imaging: I. Concept, acquisition protocol optimization and clinical application

Science.gov (United States)

Karakatsanis, Nicolas A.; Lodge, Martin A.; Tahari, Abdel K.; Zhou, Y.; Wahl, Richard L.; Rahmim, Arman

2013-01-01

Static whole body PET/CT, employing the standardized uptake value (SUV), is considered the standard clinical approach to diagnosis and treatment response monitoring for a wide range of oncologic malignancies. Alternative PET protocols involving dynamic acquisition of temporal images have been implemented in the research setting, allowing quantification of tracer dynamics, an important capability for tumor characterization and treatment response monitoring. Nonetheless, dynamic protocols have been confined to single bed-coverage limiting the axial field-of-view to ~15–20 cm, and have not been translated to the routine clinical context of whole-body PET imaging for the inspection of disseminated disease. Here, we pursue a transition to dynamic whole body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. We investigate solutions to address the challenges of: (i) long acquisitions, (ii) small number of dynamic frames per bed, and (iii) non-invasive quantification of kinetics in the plasma. In the present study, a novel dynamic (4D) whole body PET acquisition protocol of ~45min total length is presented, composed of (i) an initial 6-min dynamic PET scan (24 frames) over the heart, followed by (ii) a sequence of multi-pass multi-bed PET scans (6 passes x 7 bed positions, each scanned for 45sec). Standard Patlak linear graphical analysis modeling was employed, coupled with image-derived plasma input function measurements. Ordinary least squares (OLS) Patlak estimation was used as the baseline regression method to quantify the physiological parameters of tracer uptake rate Ki and total blood distribution volume V on an individual voxel basis. Extensive Monte Carlo simulation studies, using a wide set of published kinetic FDG parameters and GATE and XCAT platforms, were conducted to optimize the acquisition protocol from a range of 10 different clinically

Dynamic whole-body PET parametric imaging: I. Concept, acquisition protocol optimization and clinical application.

Science.gov (United States)

Karakatsanis, Nicolas A; Lodge, Martin A; Tahari, Abdel K; Zhou, Y; Wahl, Richard L; Rahmim, Arman

2013-10-21

Static whole-body PET/CT, employing the standardized uptake value (SUV), is considered the standard clinical approach to diagnosis and treatment response monitoring for a wide range of oncologic malignancies. Alternative PET protocols involving dynamic acquisition of temporal images have been implemented in the research setting, allowing quantification of tracer dynamics, an important capability for tumor characterization and treatment response monitoring. Nonetheless, dynamic protocols have been confined to single-bed-coverage limiting the axial field-of-view to ~15-20 cm, and have not been translated to the routine clinical context of whole-body PET imaging for the inspection of disseminated disease. Here, we pursue a transition to dynamic whole-body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. We investigate solutions to address the challenges of: (i) long acquisitions, (ii) small number of dynamic frames per bed, and (iii) non-invasive quantification of kinetics in the plasma. In the present study, a novel dynamic (4D) whole-body PET acquisition protocol of ~45 min total length is presented, composed of (i) an initial 6 min dynamic PET scan (24 frames) over the heart, followed by (ii) a sequence of multi-pass multi-bed PET scans (six passes × seven bed positions, each scanned for 45 s). Standard Patlak linear graphical analysis modeling was employed, coupled with image-derived plasma input function measurements. Ordinary least squares Patlak estimation was used as the baseline regression method to quantify the physiological parameters of tracer uptake rate Ki and total blood distribution volume V on an individual voxel basis. Extensive Monte Carlo simulation studies, using a wide set of published kinetic FDG parameters and GATE and XCAT platforms, were conducted to optimize the acquisition protocol from a range of ten different clinically

Dynamic whole-body PET parametric imaging: I. Concept, acquisition protocol optimization and clinical application

International Nuclear Information System (INIS)

Karakatsanis, Nicolas A; Lodge, Martin A; Tahari, Abdel K; Zhou, Y; Wahl, Richard L; Rahmim, Arman

2013-01-01

Static whole-body PET/CT, employing the standardized uptake value (SUV), is considered the standard clinical approach to diagnosis and treatment response monitoring for a wide range of oncologic malignancies. Alternative PET protocols involving dynamic acquisition of temporal images have been implemented in the research setting, allowing quantification of tracer dynamics, an important capability for tumor characterization and treatment response monitoring. Nonetheless, dynamic protocols have been confined to single-bed-coverage limiting the axial field-of-view to ∼15–20 cm, and have not been translated to the routine clinical context of whole-body PET imaging for the inspection of disseminated disease. Here, we pursue a transition to dynamic whole-body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. We investigate solutions to address the challenges of: (i) long acquisitions, (ii) small number of dynamic frames per bed, and (iii) non-invasive quantification of kinetics in the plasma. In the present study, a novel dynamic (4D) whole-body PET acquisition protocol of ∼45 min total length is presented, composed of (i) an initial 6 min dynamic PET scan (24 frames) over the heart, followed by (ii) a sequence of multi-pass multi-bed PET scans (six passes × seven bed positions, each scanned for 45 s). Standard Patlak linear graphical analysis modeling was employed, coupled with image-derived plasma input function measurements. Ordinary least squares Patlak estimation was used as the baseline regression method to quantify the physiological parameters of tracer uptake rate K i and total blood distribution volume V on an individual voxel basis. Extensive Monte Carlo simulation studies, using a wide set of published kinetic FDG parameters and GATE and XCAT platforms, were conducted to optimize the acquisition protocol from a range of ten different

Dynamic whole-body PET parametric imaging: I. Concept, acquisition protocol optimization and clinical application

Science.gov (United States)

Karakatsanis, Nicolas A.; Lodge, Martin A.; Tahari, Abdel K.; Zhou, Y.; Wahl, Richard L.; Rahmim, Arman

2013-10-01

Static whole-body PET/CT, employing the standardized uptake value (SUV), is considered the standard clinical approach to diagnosis and treatment response monitoring for a wide range of oncologic malignancies. Alternative PET protocols involving dynamic acquisition of temporal images have been implemented in the research setting, allowing quantification of tracer dynamics, an important capability for tumor characterization and treatment response monitoring. Nonetheless, dynamic protocols have been confined to single-bed-coverage limiting the axial field-of-view to ˜15-20 cm, and have not been translated to the routine clinical context of whole-body PET imaging for the inspection of disseminated disease. Here, we pursue a transition to dynamic whole-body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. We investigate solutions to address the challenges of: (i) long acquisitions, (ii) small number of dynamic frames per bed, and (iii) non-invasive quantification of kinetics in the plasma. In the present study, a novel dynamic (4D) whole-body PET acquisition protocol of ˜45 min total length is presented, composed of (i) an initial 6 min dynamic PET scan (24 frames) over the heart, followed by (ii) a sequence of multi-pass multi-bed PET scans (six passes × seven bed positions, each scanned for 45 s). Standard Patlak linear graphical analysis modeling was employed, coupled with image-derived plasma input function measurements. Ordinary least squares Patlak estimation was used as the baseline regression method to quantify the physiological parameters of tracer uptake rate Ki and total blood distribution volume V on an individual voxel basis. Extensive Monte Carlo simulation studies, using a wide set of published kinetic FDG parameters and GATE and XCAT platforms, were conducted to optimize the acquisition protocol from a range of ten different clinically

Tuning Range Optimization of a Planar Inverted F Antenna for LTE Low Frequency Bands

DEFF Research Database (Denmark)

Barrio, Samantha Caporal Del; Pelosi, Mauro; Franek, Ondrej

2011-01-01

This paper presents a Planar Inverted F Antenna (PIFA) tuned with a fixed capacitor to the low frequency bands supported by the Long Term Evolution (LTE) technology. The tuning range is investigated and optimized with respect to the bandwidth and the efficiency of the resulting antenna. Simulatio...... and mock-ups are presented....

Dynamic range enhancement and amplitude regeneration in single pump fibre optic parametric amplifiers using DPSK modulation

DEFF Research Database (Denmark)

Peucheret, Christophe; Lorenzen, Michael Rodas; Seoane, Jorge

2008-01-01

Input power dynamic range enhancement and amplitude regeneration of highly distorted signals are demonstrated experimentally for 40 Gbit/s RZ-DPSK in a single-pump fibre parametric amplifier with 22 dB smallsignal gain.......Input power dynamic range enhancement and amplitude regeneration of highly distorted signals are demonstrated experimentally for 40 Gbit/s RZ-DPSK in a single-pump fibre parametric amplifier with 22 dB smallsignal gain....

Optimal control of quantum dissipative dynamics: Analytic solution for cooling the three-level Λ system

International Nuclear Information System (INIS)

Sklarz, Shlomo E.; Tannor, David J.; Khaneja, Navin

2004-01-01

We study the problem of optimal control of dissipative quantum dynamics. Although under most circumstances dissipation leads to an increase in entropy (or a decrease in purity) of the system, there is an important class of problems for which dissipation with external control can decrease the entropy (or increase the purity) of the system. An important example is laser cooling. In such systems, there is an interplay of the Hamiltonian part of the dynamics, which is controllable, and the dissipative part of the dynamics, which is uncontrollable. The strategy is to control the Hamiltonian portion of the evolution in such a way that the dissipation causes the purity of the system to increase rather than decrease. The goal of this paper is to find the strategy that leads to maximal purity at the final time. Under the assumption that Hamiltonian control is complete and arbitrarily fast, we provide a general framework by which to calculate optimal cooling strategies. These assumptions lead to a great simplification, in which the control problem can be reformulated in terms of the spectrum of eigenvalues of ρ, rather than ρ itself. By combining this formulation with the Hamilton-Jacobi-Bellman theorem we are able to obtain an equation for the globally optimal cooling strategy in terms of the spectrum of the density matrix. For the three-level Λ system, we provide a complete analytic solution for the optimal cooling strategy. For this system it is found that the optimal strategy does not exploit system coherences and is a 'greedy' strategy, in which the purity is increased maximally at each instant

Optimal Control via Integrating the Dynamics of Magnetorheological Dampers and Structures

Directory of Open Access Journals (Sweden)

Amir Fayezioghani

2015-03-01

Full Text Available Magnetorheological (MR dampers have the advantage of being tuned by low voltages. This has attracted many researchers to develop semi-active control of structures in theory and practice. Most of the control strategies first obtain the desired forces of dampers without taking their dynamics into consideration and then determine the input voltages according to those forces. As a result, these strategies may face situations where the desired forces cannot be produced by the dampers. In this article, by integrating the equations of the dynamics of MR dampers and the structural motion, and solving them in one set, a more concise semi-active optimal control strategy is presented, so as to bypass the aforementioned drawback. Next, a strong database that can be utilized to form a controller for more realistic implementations is produced. As an illustrative example, the optimal voltages of the dampers of a six-storey shear building are obtained under the scaled El-Centro earthquake and used to train a set of integrated analysis-adaptive neuro-fuzzy inference systems (ANFISs as a controller. Results show that the overall performance of the proposed strategy is higher than most of the other conventional methods.

Extended-Range High-Resolution Dynamical Downscaling over a Continental-Scale Domain

Science.gov (United States)

Husain, S. Z.; Separovic, L.; Yu, W.; Fernig, D.

2014-12-01

High-resolution mesoscale simulations, when applied for downscaling meteorological fields over large spatial domains and for extended time periods, can provide valuable information for many practical application scenarios including the weather-dependent renewable energy industry. In the present study, a strategy has been proposed to dynamically downscale coarse-resolution meteorological fields from Environment Canada's regional analyses for a period of multiple years over the entire Canadian territory. The study demonstrates that a continuous mesoscale simulation over the entire domain is the most suitable approach in this regard. Large-scale deviations in the different meteorological fields pose the biggest challenge for extended-range simulations over continental scale domains, and the enforcement of the lateral boundary conditions is not sufficient to restrict such deviations. A scheme has therefore been developed to spectrally nudge the simulated high-resolution meteorological fields at the different model vertical levels towards those embedded in the coarse-resolution driving fields derived from the regional analyses. A series of experiments were carried out to determine the optimal nudging strategy including the appropriate nudging length scales, nudging vertical profile and temporal relaxation. A forcing strategy based on grid nudging of the different surface fields, including surface temperature, soil-moisture, and snow conditions, towards their expected values obtained from a high-resolution offline surface scheme was also devised to limit any considerable deviation in the evolving surface fields due to extended-range temporal integrations. The study shows that ensuring large-scale atmospheric similarities helps to deliver near-surface statistical scores for temperature, dew point temperature and horizontal wind speed that are better or comparable to the operational regional forecasts issued by Environment Canada. Furthermore, the meteorological fields

Dynamic Vehicle Routing Problems with Enhanced Ant Colony Optimization

Directory of Open Access Journals (Sweden)

Haitao Xu

2018-01-01

Full Text Available As we all know, there are a great number of optimization problems in the world. One of the relatively complicated and high-level problems is the vehicle routing problem (VRP. Dynamic vehicle routing problem (DVRP is a major variant of VRP, and it is closer to real logistic scene. In DVRP, the customers’ demands appear with time, and the unserved customers’ points must be updated and rearranged while carrying out the programming paths. Owing to the complexity and significance of the problem, DVRP applications have grabbed the attention of researchers in the past two decades. In this paper, we have two main contributions to solving DVRP. Firstly, DVRP is solved with enhanced Ant Colony Optimization (E-ACO, which is the traditional Ant Colony Optimization (ACO fusing improved K-means and crossover operation. K-means can divide the region with the most reasonable distance, while ACO using crossover is applied to extend search space and avoid falling into local optimum prematurely. Secondly, several new evaluation benchmarks are proposed, which can objectively and comprehensively estimate the proposed method. In the experiment, the results for different scale problems are compared to those of previously published papers. Experimental results show that the algorithm is feasible and efficient.

Dynamic programming approach to optimization of approximate decision rules

KAUST Repository

Amin, Talha

2013-02-01

This paper is devoted to the study of an extension of dynamic programming approach which allows sequential optimization of approximate decision rules relative to the length and coverage. We introduce an uncertainty measure R(T) which is the number of unordered pairs of rows with different decisions in the decision table T. For a nonnegative real number β, we consider β-decision rules that localize rows in subtables of T with uncertainty at most β. Our algorithm constructs a directed acyclic graph Δβ(T) which nodes are subtables of the decision table T given by systems of equations of the kind "attribute = value". This algorithm finishes the partitioning of a subtable when its uncertainty is at most β. The graph Δβ(T) allows us to describe the whole set of so-called irredundant β-decision rules. We can describe all irredundant β-decision rules with minimum length, and after that among these rules describe all rules with maximum coverage. We can also change the order of optimization. The consideration of irredundant rules only does not change the results of optimization. This paper contains also results of experiments with decision tables from UCI Machine Learning Repository. © 2012 Elsevier Inc. All rights reserved.

Multiobjective genetic algorithm optimization of the beam dynamics in linac drivers for free electron lasers

Directory of Open Access Journals (Sweden)

R. Bartolini

2012-03-01

Full Text Available Linac driven free electron lasers (FELs operating in the x-ray region require a high brightness electron beam in order to reach saturation within a reasonable distance in the undulator train or to enable sophisticated seeding schemes using external lasers. The beam dynamics optimization is usually a time consuming process in which many parameters of the accelerator and the compression system have to be controlled simultaneously. The requirements on the electron beam quality may also vary significantly with the particular application. For example, the beam dynamics optimization strategy for self-amplified spontaneous emission operation and seeded operation are rather different: seeded operation requires a more careful control of the beam uniformity over a relatively large portion of the longitudinal current distribution of the electron bunch and is therefore more challenging from an accelerator physics point of view. Multiobjective genetic algorithms are particularly well suited when the optimization of many parameters is targeting several objectives simultaneously, often with conflicting requirements. In this paper we propose a novel optimization strategy based on a combination of multiobjective optimization with a fast computation of the FEL performance. The application to the proposed UK’s New Light Source is reported and the benefits of this method are highlighted.

Four-bar linkage-based automatic tool changer: Dynamic modeling and torque optimization

International Nuclear Information System (INIS)

Lee, Sangho; Seo, TaeWon; Kim, Jong-Won; Kim, Jongwon

2017-01-01

An Automatic tool changer (ATC) is a device used in a tapping machine to reduce process time. This paper presents the optimization of a Peak torque reduction mechanism (PTRM) for an ATC. It is necessary to reduce the fatigue load and energy consumed, which is related to the peak torque. The PTRM uses a torsion spring to reduce the peak torque and was applied to a novel ATC mechanism, which was modeled using inverse dynamics. Optimization of the PTRM is required to minimize the peak torque. The design parameters are the initial angle and stiffness of the torsion spring, and the objective function is the peak torque of the input link. The torque was simulated, and the peak torque was decreased by 10 %. The energy consumed was reduced by the optimization.

Four-bar linkage-based automatic tool changer: Dynamic modeling and torque optimization

Energy Technology Data Exchange (ETDEWEB)

Lee, Sangho; Seo, TaeWon [Yeungnam University, Gyeongsan (Korea, Republic of); Kim, Jong-Won; Kim, Jongwon [Seoul National University, Seoul (Korea, Republic of)

2017-05-15

An Automatic tool changer (ATC) is a device used in a tapping machine to reduce process time. This paper presents the optimization of a Peak torque reduction mechanism (PTRM) for an ATC. It is necessary to reduce the fatigue load and energy consumed, which is related to the peak torque. The PTRM uses a torsion spring to reduce the peak torque and was applied to a novel ATC mechanism, which was modeled using inverse dynamics. Optimization of the PTRM is required to minimize the peak torque. The design parameters are the initial angle and stiffness of the torsion spring, and the objective function is the peak torque of the input link. The torque was simulated, and the peak torque was decreased by 10 %. The energy consumed was reduced by the optimization.

Dynamic optimal foraging theory explains vertical migrations of bigeye tuna

DEFF Research Database (Denmark)

Thygesen, Uffe Høgsbro; Sommer, Lene; Evans, Karen

2016-01-01

Bigeye tuna are known for remarkable daytime vertical migrations between deep water, where food is abundant but the water is cold, and the surface, where water is warm but food is relatively scarce. Here we investigate if these dive patterns can be explained by dynamic optimal foraging theory...... behaves such as to maximize its energy gains. The model therefore provides insight into the processes underlying observed behavioral patterns and allows generating predictions of foraging behavior in unobserved environments...

Analysis of Ant Colony Optimization and Population-Based Evolutionary Algorithms on Dynamic Problems

DEFF Research Database (Denmark)

Lissovoi, Andrei

the dynamic optimum for finite alphabets up to size μ, while MMAS is able to do so for any finite alphabet size. Parallel Evolutionary Algorithms on Maze. We prove that while a (1 + λ) EA is unable to track the optimum of the dynamic fitness function Maze for offspring population size up to λ = O(n1-ε......This thesis presents new running time analyses of nature-inspired algorithms on various dynamic problems. It aims to identify and analyse the features of algorithms and problem classes which allow efficient optimization to occur in the presence of dynamic behaviour. We consider the following...... settings: λ-MMAS on Dynamic Shortest Path Problems. We investigate how in-creasing the number of ants simulated per iteration may help an ACO algorithm to track optimum in a dynamic problem. It is shown that while a constant number of ants per-vertex is sufficient to track some oscillations, there also...

Multi objective optimization of foam-filled circular tubes for quasi-static and dynamic responses

Directory of Open Access Journals (Sweden)

Fauzan Djamaluddin

Full Text Available AbstractFuel consumption and safety are currently key aspects in automobile design. The foam-filled thin-walled aluminium tube represents a potentially effective material for use in the automotive industry, due to its energy absorption capability and light weight. Multi-objective crashworthiness design optimization for foam-filled double cylindrical tubes is presented in this paper. The double structures are impacted by a rigid wall simulating quasi-static and dynamic loadings. The optimal parameters under consideration are the minimum peak crushing force and maximum specific energy absorption, using the non-dominated sorting genetic algorithm-II (NSGA-II technique. Radial basis functions (RBF and D-Optimal are adopted to determine the more complex crashworthiness functional objectives. The comparison is performed by finite element analysis of the impact crashworthiness characteristics in tubes under static and dynamic loads. Finally, the optimum crashworthiness performance of empty and foam-filled double tubes is investigated and compared to the traditional single foam-filled tube. The results indicate that the foam-filled double aluminium circular tube can be recommended for crashworthy structures.

Empirical study of long-range connections in a road network offers new ingredient for navigation optimization models

International Nuclear Information System (INIS)

Wang, Pu; Liu, Like; Li, Xiamiao; Li, Guanliang; González, Marta C

2014-01-01

Navigation problem in lattices with long-range connections has been widely studied to understand the design principles for optimal transport networks; however, the travel cost of long-range connections was not considered in previous models. We define long-range connection in a road network as the shortest path between a pair of nodes through highways and empirically analyze the travel cost properties of long-range connections. Based on the maximum speed allowed in each road segment, we observe that the time needed to travel through a long-range connection has a characteristic time T h  ∼ 29 min, while the time required when using the alternative arterial road path has two different characteristic times T a  ∼ 13 and 41 min and follows a power law for times larger than 50 min. Using daily commuting origin–destination matrix data, we additionally find that the use of long-range connections helps people to save about half of the travel time in their daily commute. Based on the empirical results, we assign a more realistic travel cost to long-range connections in two-dimensional square lattices, observing dramatically different minimum average shortest path 〈l〉 but similar optimal navigation conditions. (paper)

A Method of Dynamic Extended Reactive Power Optimization in Distribution Network Containing Photovoltaic-Storage System

Science.gov (United States)

Wang, Wu; Huang, Wei; Zhang, Yongjun

2018-03-01

The grid-integration of Photovoltaic-Storage System brings some undefined factors to the network. In order to make full use of the adjusting ability of Photovoltaic-Storage System (PSS), this paper puts forward a reactive power optimization model, which are used to construct the objective function based on power loss and the device adjusting cost, including energy storage adjusting cost. By using Cataclysmic Genetic Algorithm to solve this optimization problem, and comparing with other optimization method, the result proved that: the method of dynamic extended reactive power optimization this article puts forward, can enhance the effect of reactive power optimization, including reducing power loss and device adjusting cost, meanwhile, it gives consideration to the safety of voltage.

Density matrix renormalization group with efficient dynamical electron correlation through range separation

DEFF Research Database (Denmark)

Hedegård, Erik D.; Knecht, Stefan; Kielberg, Jesper Skau

2015-01-01

We present a new hybrid multiconfigurational method based on the concept of range-separation that combines the density matrix renormalization group approach with density functional theory. This new method is designed for the simultaneous description of dynamical and static electroncorrelation...... effects in multiconfigurational electronic structure problems....

Stochastic optimal control in infinite dimension dynamic programming and HJB equations

CERN Document Server

Fabbri, Giorgio; Święch, Andrzej

2017-01-01

Providing an introduction to stochastic optimal control in infinite dimension, this book gives a complete account of the theory of second-order HJB equations in infinite-dimensional Hilbert spaces, focusing on its applicability to associated stochastic optimal control problems. It features a general introduction to optimal stochastic control, including basic results (e.g. the dynamic programming principle) with proofs, and provides examples of applications. A complete and up-to-date exposition of the existing theory of viscosity solutions and regular solutions of second-order HJB equations in Hilbert spaces is given, together with an extensive survey of other methods, with a full bibliography. In particular, Chapter 6, written by M. Fuhrman and G. Tessitore, surveys the theory of regular solutions of HJB equations arising in infinite-dimensional stochastic control, via BSDEs. The book is of interest to both pure and applied researchers working in the control theory of stochastic PDEs, and in PDEs in infinite ...

POTENTIALS OF IMAGE BASED ACTIVE RANGING TO CAPTURE DYNAMIC SCENES

Directory of Open Access Journals (Sweden)

B. Jutzi

2012-09-01

Full Text Available Obtaining a 3D description of man-made and natural environments is a basic task in Computer Vision and Remote Sensing. To this end, laser scanning is currently one of the dominating techniques to gather reliable 3D information. The scanning principle inherently needs a certain time interval to acquire the 3D point cloud. On the other hand, new active sensors provide the possibility of capturing range information by images with a single measurement. With this new technique image-based active ranging is possible which allows capturing dynamic scenes, e.g. like walking pedestrians in a yard or moving vehicles. Unfortunately most of these range imaging sensors have strong technical limitations and are not yet sufficient for airborne data acquisition. It can be seen from the recent development of highly specialized (far-range imaging sensors – so called flash-light lasers – that most of the limitations could be alleviated soon, so that future systems will be equipped with improved image size and potentially expanded operating range. The presented work is a first step towards the development of methods capable for application of range images in outdoor environments. To this end, an experimental setup was set up for investigating these proposed possibilities. With the experimental setup a measurement campaign was carried out and first results will be presented within this paper.

Optimization of control poison management by dynamic programming

International Nuclear Information System (INIS)

Ponzoni Filho, P.

1974-01-01

A dynamic programming approach was used to optimize the poison distribution in the core of a nuclear power plant between reloading. This method was applied to a 500 M We PWR subject to two different fuel management policies. The beginning of a stage is marked by a fuel management decision. The state vector of the system is defined by the burnups in the three fuel zones of the core. The change of the state vector is computed in several time steps. A criticality conserving poison management pattern is chosen at the beginning of each step. The burnups at the end of a step are obtained by means of depletion calculations, assuming constant neutron distribution during the step. The violation of burnup and power peaking constraints during the step eliminates the corresponding end states. In the case of identical end states, all except that which produced the largest amount of energy, are eliminated. Among the several end states one is selected for the subsequent stage, when it is subjected to a fuel management decision. This selection is based on an optimally criterion previously chosen, such as: discharged fuel burnup maximization, energy generation cost minimization, etc. (author)

Combined Optimal Control System for excavator electric drive

Science.gov (United States)

Kurochkin, N. S.; Kochetkov, V. P.; Platonova, E. V.; Glushkin, E. Y.; Dulesov, A. S.

2018-03-01

The article presents a synthesis of the combined optimal control algorithms of the AC drive rotation mechanism of the excavator. Synthesis of algorithms consists in the regulation of external coordinates - based on the theory of optimal systems and correction of the internal coordinates electric drive using the method "technical optimum". The research shows the advantage of optimal combined control systems for the electric rotary drive over classical systems of subordinate regulation. The paper presents a method for selecting the optimality criterion of coefficients to find the intersection of the range of permissible values of the coordinates of the control object. There is possibility of system settings by choosing the optimality criterion coefficients, which allows one to select the required characteristics of the drive: the dynamic moment (M) and the time of the transient process (tpp). Due to the use of combined optimal control systems, it was possible to significantly reduce the maximum value of the dynamic moment (M) and at the same time - reduce the transient time (tpp).

First full dynamic range calibration of the JUNGFRAU photon detector

Science.gov (United States)

Redford, S.; Andrä, M.; Barten, R.; Bergamaschi, A.; Brückner, M.; Dinapoli, R.; Fröjdh, E.; Greiffenberg, D.; Lopez-Cuenca, C.; Mezza, D.; Mozzanica, A.; Ramilli, M.; Ruat, M.; Ruder, C.; Schmitt, B.; Shi, X.; Thattil, D.; Tinti, G.; Vetter, S.; Zhang, J.

2018-01-01

The JUNGFRAU detector is a charge integrating hybrid silicon pixel detector developed at the Paul Scherrer Institut for photon science applications, in particular for the upcoming free electron laser SwissFEL. With a high dynamic range, analogue readout, low noise and three automatically switching gains, JUNGFRAU promises excellent performance not only at XFELs but also at synchrotrons in areas such as protein crystallography, ptychography, pump-probe and time resolved measurements. To achieve its full potential, the detector must be calibrated on a pixel-by-pixel basis. This contribution presents the current status of the JUNGFRAU calibration project, in which a variety of input charge sources are used to parametrise the energy response of the detector across four orders of magnitude of dynamic range. Building on preliminary studies, the first full calibration procedure of a JUNGFRAU 0.5 Mpixel module is described. The calibration is validated using alternative sources of charge deposition, including laboratory experiments and measurements at ESRF and LCLS. The findings from these measurements are presented. Calibrated modules have already been used in proof-of-principle style protein crystallography experiments at the SLS. A first look at selected results is shown. Aspects such as the conversion of charge to number of photons, treatment of multi-size pixels and the origin of non-linear response are also discussed.

Computer Program for Analysis, Design and Optimization of Propulsion, Dynamics, and Kinematics of Multistage Rockets

Science.gov (United States)