Towards optimal dosing of coumarin derivatives: the role of pharmacogenetics

NARCIS (Netherlands)

van Schie, R.M.F.

2013-01-01

Coumarin derivatives are effective in the prevention and treatment of thromboembolic diseases. Examples of indications are atrial fibrillation and venous thromboembolism. Although coumarins are on the market for decades, it is still challenging to find the optimal dosage for each patient since

Optimal investment strategies and hedging of derivatives in the presence of transaction costs (Invited Paper)

Science.gov (United States)

Muratore-Ginanneschi, Paolo

2005-05-01

Investment strategies in multiplicative Markovian market models with transaction costs are defined using growth optimal criteria. The optimal strategy is shown to consist in holding the amount of capital invested in stocks within an interval around an ideal optimal investment. The size of the holding interval is determined by the intensity of the transaction costs and the time horizon. The inclusion of financial derivatives in the models is also considered. All the results presented in this contributions were previously derived in collaboration with E. Aurell.

First and second order derivatives for optimizing parallel RF excitation waveforms

Science.gov (United States)

Majewski, Kurt; Ritter, Dieter

2015-09-01

For piecewise constant magnetic fields, the Bloch equations (without relaxation terms) can be solved explicitly. This way the magnetization created by an excitation pulse can be written as a concatenation of rotations applied to the initial magnetization. For fixed gradient trajectories, the problem of finding parallel RF waveforms, which minimize the difference between achieved and desired magnetization on a number of voxels, can thus be represented as a finite-dimensional minimization problem. We use quaternion calculus to formulate this optimization problem in the magnitude least squares variant and specify first and second order derivatives of the objective function. We obtain a small tip angle approximation as first order Taylor development from the first order derivatives and also develop algorithms for first and second order derivatives for this small tip angle approximation. All algorithms are accompanied by precise floating point operation counts to assess and compare the computational efforts. We have implemented these algorithms as callback functions of an interior-point solver. We have applied this numerical optimization method to example problems from the literature and report key observations.

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.

First and second order derivatives for optimizing parallel RF excitation waveforms.

Science.gov (United States)

Majewski, Kurt; Ritter, Dieter

2015-09-01

For piecewise constant magnetic fields, the Bloch equations (without relaxation terms) can be solved explicitly. This way the magnetization created by an excitation pulse can be written as a concatenation of rotations applied to the initial magnetization. For fixed gradient trajectories, the problem of finding parallel RF waveforms, which minimize the difference between achieved and desired magnetization on a number of voxels, can thus be represented as a finite-dimensional minimization problem. We use quaternion calculus to formulate this optimization problem in the magnitude least squares variant and specify first and second order derivatives of the objective function. We obtain a small tip angle approximation as first order Taylor development from the first order derivatives and also develop algorithms for first and second order derivatives for this small tip angle approximation. All algorithms are accompanied by precise floating point operation counts to assess and compare the computational efforts. We have implemented these algorithms as callback functions of an interior-point solver. We have applied this numerical optimization method to example problems from the literature and report key observations. Copyright © 2015 Elsevier Inc. All rights reserved.

Deriving the Normalized Min-Sum Algorithm from Cooperative Optimization

OpenAIRE

Huang, Xiaofei

2006-01-01

The normalized min-sum algorithm can achieve near-optimal performance at decoding LDPC codes. However, it is a critical question to understand the mathematical principle underlying the algorithm. Traditionally, people thought that the normalized min-sum algorithm is a good approximation to the sum-product algorithm, the best known algorithm for decoding LDPC codes and Turbo codes. This paper offers an alternative approach to understand the normalized min-sum algorithm. The algorithm is derive...

Development and optimization of the synthesis of new thiazolidin-4-one derivatives of ibuprofen.

Science.gov (United States)

Vasincu, Ioana; Apotrosoaei, Maria; Panzariu, Andreea; Buron, F; Routier, S; Profire, Lenuta

2014-01-01

Ibuprofen, an important nonsteroidal anti-inflammatory agent, is one of the most prescribed drugs for the treatment of pain and inflammation from various rheumatic diseases, but some side effects can occur on long-term use. The method for synthesis optimization of new derivatives of Ibuprofen with thiazolidin-4-one moiety, with improved pharmacological and toxicological profile. To optimize the derivatization method of free carboxyl group of Ibuprofen (2-(4-isobutylphenyl)propionic acid) the reaction conditions were varied (reagent ratio, catalyst, reaction medium). The most favorable method was proved to be the reaction between ibuprofen hydrazone and mercaptoacetic acid, in excess, at 80-85 degrees C, for 6 h with 96% conversion rate. The synthesis of 2-phenyl-3-[2-(4-(isobutyl)phenyl)-2-methyl]acetamido-thiazolidin-4-one derivative was optimized in view of applying it as a general procedure for the synthesis of other derivatives with related structure. The chemical structure and molecular weight of the synthesized compound were confirmed by spectral methods (IR, 1H NMR, 13C NMR, HR-MS).

Derivative-free generation and interpolation of convex Pareto optimal IMRT plans

Science.gov (United States)

Hoffmann, Aswin L.; Siem, Alex Y. D.; den Hertog, Dick; Kaanders, Johannes H. A. M.; Huizenga, Henk

2006-12-01

In inverse treatment planning for intensity-modulated radiation therapy (IMRT), beamlet intensity levels in fluence maps of high-energy photon beams are optimized. Treatment plan evaluation criteria are used as objective functions to steer the optimization process. Fluence map optimization can be considered a multi-objective optimization problem, for which a set of Pareto optimal solutions exists: the Pareto efficient frontier (PEF). In this paper, a constrained optimization method is pursued to iteratively estimate the PEF up to some predefined error. We use the property that the PEF is convex for a convex optimization problem to construct piecewise-linear upper and lower bounds to approximate the PEF from a small initial set of Pareto optimal plans. A derivative-free Sandwich algorithm is presented in which these bounds are used with three strategies to determine the location of the next Pareto optimal solution such that the uncertainty in the estimated PEF is maximally reduced. We show that an intelligent initial solution for a new Pareto optimal plan can be obtained by interpolation of fluence maps from neighbouring Pareto optimal plans. The method has been applied to a simplified clinical test case using two convex objective functions to map the trade-off between tumour dose heterogeneity and critical organ sparing. All three strategies produce representative estimates of the PEF. The new algorithm is particularly suitable for dynamic generation of Pareto optimal plans in interactive treatment planning.

Derivative-free generation and interpolation of convex Pareto optimal IMRT plans

International Nuclear Information System (INIS)

Hoffmann, Aswin L; Siem, Alex Y D; Hertog, Dick den; Kaanders, Johannes H A M; Huizenga, Henk

2006-01-01

In inverse treatment planning for intensity-modulated radiation therapy (IMRT), beamlet intensity levels in fluence maps of high-energy photon beams are optimized. Treatment plan evaluation criteria are used as objective functions to steer the optimization process. Fluence map optimization can be considered a multi-objective optimization problem, for which a set of Pareto optimal solutions exists: the Pareto efficient frontier (PEF). In this paper, a constrained optimization method is pursued to iteratively estimate the PEF up to some predefined error. We use the property that the PEF is convex for a convex optimization problem to construct piecewise-linear upper and lower bounds to approximate the PEF from a small initial set of Pareto optimal plans. A derivative-free Sandwich algorithm is presented in which these bounds are used with three strategies to determine the location of the next Pareto optimal solution such that the uncertainty in the estimated PEF is maximally reduced. We show that an intelligent initial solution for a new Pareto optimal plan can be obtained by interpolation of fluence maps from neighbouring Pareto optimal plans. The method has been applied to a simplified clinical test case using two convex objective functions to map the trade-off between tumour dose heterogeneity and critical organ sparing. All three strategies produce representative estimates of the PEF. The new algorithm is particularly suitable for dynamic generation of Pareto optimal plans in interactive treatment planning

Proportional–Integral–Derivative (PID Controller Tuning using Particle Swarm Optimization Algorithm

Directory of Open Access Journals (Sweden)

J. S. Bassi

2012-08-01

Full Text Available The proportional-integral-derivative (PID controllers are the most popular controllers used in industry because of their remarkable effectiveness, simplicity of implementation and broad applicability. However, manual tuning of these controllers is time consuming, tedious and generally lead to poor performance. This tuning which is application specific also deteriorates with time as a result of plant parameter changes. This paper presents an artificial intelligence (AI method of particle swarm optimization (PSO algorithm for tuning the optimal proportional-integral derivative (PID controller parameters for industrial processes. This approach has superior features, including easy implementation, stable convergence characteristic and good computational efficiency over the conventional methods. Ziegler- Nichols, tuning method was applied in the PID tuning and results were compared with the PSO-Based PID for optimum control. Simulation results are presented to show that the PSO-Based optimized PID controller is capable of providing an improved closed-loop performance over the Ziegler- Nichols tuned PID controller Parameters. Compared to the heuristic PID tuning method of Ziegler-Nichols, the proposed method was more efficient in improving the step response characteristics such as, reducing the steady-states error; rise time, settling time and maximum overshoot in speed control of DC motor.

Employing Sensitivity Derivatives for Robust Optimization under Uncertainty in CFD

Science.gov (United States)

Newman, Perry A.; Putko, Michele M.; Taylor, Arthur C., III

2004-01-01

A robust optimization is demonstrated on a two-dimensional inviscid airfoil problem in subsonic flow. Given uncertainties in statistically independent, random, normally distributed flow parameters (input variables), an approximate first-order statistical moment method is employed to represent the Computational Fluid Dynamics (CFD) code outputs as expected values with variances. These output quantities are used to form the objective function and constraints. The constraints are cast in probabilistic terms; that is, the probability that a constraint is satisfied is greater than or equal to some desired target probability. Gradient-based robust optimization of this stochastic problem is accomplished through use of both first and second-order sensitivity derivatives. For each robust optimization, the effect of increasing both input standard deviations and target probability of constraint satisfaction are demonstrated. This method provides a means for incorporating uncertainty when considering small deviations from input mean values.

The Enterprise Derivative Application: Flexible Software for Optimizing Manufacturing Processes

Energy Technology Data Exchange (ETDEWEB)

Ward, Richard C [ORNL; Allgood, Glenn O [ORNL; Knox, John R [ORNL

2008-11-01

The Enterprise Derivative Application (EDA) implements the enterprise-derivative analysis for optimization of an industrial process (Allgood and Manges, 2001). It is a tool to help industry planners choose the most productive way of manufacturing their products while minimizing their cost. Developed in MS Access, the application allows users to input initial data ranging from raw material to variable costs and enables the tracking of specific information as material is passed from one process to another. Energy-derivative analysis is based on calculation of sensitivity parameters. For the specific application to a steel production process these include: the cost to product sensitivity, the product to energy sensitivity, the energy to efficiency sensitivity, and the efficiency to cost sensitivity. Using the EDA, for all processes the user can display a particular sensitivity or all sensitivities can be compared for all processes. Although energy-derivative analysis was originally designed for use by the steel industry, it is flexible enough to be applied to many other industrial processes. Examples of processes where energy-derivative analysis would prove useful are wireless monitoring of processes in the petroleum cracking industry and wireless monitoring of motor failure for determining the optimum time to replace motor parts. One advantage of the MS Access-based application is its flexibility in defining the process flow and establishing the relationships between parent and child process and products resulting from a process. Due to the general design of the program, a process can be anything that occurs over time with resulting output (products). So the application can be easily modified to many different industrial and organizational environments. Another advantage is the flexibility of defining sensitivity parameters. Sensitivities can be determined between all possible variables in the process flow as a function of time. Thus the dynamic development of the

Topology optimization based on spline-based meshfree method using topological derivatives

International Nuclear Information System (INIS)

Hur, Junyoung; Youn, Sung-Kie; Kang, Pilseong

2017-01-01

Spline-based meshfree method (SBMFM) is originated from the Isogeometric analysis (IGA) which integrates design and analysis through Non-uniform rational B-spline (NURBS) basis functions. SBMFM utilizes trimming technique of CAD system by representing the domain using NURBS curves. In this work, an explicit boundary topology optimization using SBMFM is presented with an effective boundary update scheme. There have been similar works in this subject. However unlike the previous works where semi-analytic method for calculating design sensitivities is employed, the design update is done by using topological derivatives. In this research, the topological derivative is used to derive the sensitivity of boundary curves and for the creation of new holes. Based on the values of topological derivatives, the shape of boundary curves is updated. Also, the topological change is achieved by insertion and removal of the inner holes. The presented approach is validated through several compliance minimization problems.

Topology optimization based on spline-based meshfree method using topological derivatives

Energy Technology Data Exchange (ETDEWEB)

Hur, Junyoung; Youn, Sung-Kie [KAIST, Daejeon (Korea, Republic of); Kang, Pilseong [Korea Research Institute of Standards and Science, Daejeon (Korea, Republic of)

2017-05-15

Spline-based meshfree method (SBMFM) is originated from the Isogeometric analysis (IGA) which integrates design and analysis through Non-uniform rational B-spline (NURBS) basis functions. SBMFM utilizes trimming technique of CAD system by representing the domain using NURBS curves. In this work, an explicit boundary topology optimization using SBMFM is presented with an effective boundary update scheme. There have been similar works in this subject. However unlike the previous works where semi-analytic method for calculating design sensitivities is employed, the design update is done by using topological derivatives. In this research, the topological derivative is used to derive the sensitivity of boundary curves and for the creation of new holes. Based on the values of topological derivatives, the shape of boundary curves is updated. Also, the topological change is achieved by insertion and removal of the inner holes. The presented approach is validated through several compliance minimization problems.

Derived heuristics-based consistent optimization of material flow in a gold processing plant

Science.gov (United States)

Myburgh, Christie; Deb, Kalyanmoy

2018-01-01

Material flow in a chemical processing plant often follows complicated control laws and involves plant capacity constraints. Importantly, the process involves discrete scenarios which when modelled in a programming format involves if-then-else statements. Therefore, a formulation of an optimization problem of such processes becomes complicated with nonlinear and non-differentiable objective and constraint functions. In handling such problems using classical point-based approaches, users often have to resort to modifications and indirect ways of representing the problem to suit the restrictions associated with classical methods. In a particular gold processing plant optimization problem, these facts are demonstrated by showing results from MATLAB®'s well-known fmincon routine. Thereafter, a customized evolutionary optimization procedure which is capable of handling all complexities offered by the problem is developed. Although the evolutionary approach produced results with comparatively less variance over multiple runs, the performance has been enhanced by introducing derived heuristics associated with the problem. In this article, the development and usage of derived heuristics in a practical problem are presented and their importance in a quick convergence of the overall algorithm is demonstrated.

Derivative Trade Optimizing Model Utilizing GP Based on Behavioral Finance Theory

Science.gov (United States)

Matsumura, Koki; Kawamoto, Masaru

This paper proposed a new technique which makes the strategy trees for the derivative (option) trading investment decision based on the behavioral finance theory and optimizes it using evolutionary computation, in order to achieve high profitability. The strategy tree uses a technical analysis based on a statistical, experienced technique for the investment decision. The trading model is represented by various technical indexes, and the strategy tree is optimized by the genetic programming(GP) which is one of the evolutionary computations. Moreover, this paper proposed a method using the prospect theory based on the behavioral finance theory to set psychological bias for profit and deficit and attempted to select the appropriate strike price of option for the higher investment efficiency. As a result, this technique produced a good result and found the effectiveness of this trading model by the optimized dealings strategy.

RF cavity design exploiting a new derivative-free trust region optimization approach

Directory of Open Access Journals (Sweden)

Abdel-Karim S.O. Hassan

2015-11-01

Full Text Available In this article, a novel derivative-free (DF surrogate-based trust region optimization approach is proposed. In the proposed approach, quadratic surrogate models are constructed and successively updated. The generated surrogate model is then optimized instead of the underlined objective function over trust regions. Truncated conjugate gradients are employed to find the optimal point within each trust region. The approach constructs the initial quadratic surrogate model using few data points of order O(n, where n is the number of design variables. The proposed approach adopts weighted least squares fitting for updating the surrogate model instead of interpolation which is commonly used in DF optimization. This makes the approach more suitable for stochastic optimization and for functions subject to numerical error. The weights are assigned to give more emphasis to points close to the current center point. The accuracy and efficiency of the proposed approach are demonstrated by applying it to a set of classical bench-mark test problems. It is also employed to find the optimal design of RF cavity linear accelerator with a comparison analysis with a recent optimization technique.

New scale-down methodology from commercial to lab scale to optimize plant-derived soft gel capsule formulations on a commercial scale.

Science.gov (United States)

Oishi, Sana; Kimura, Shin-Ichiro; Noguchi, Shuji; Kondo, Mio; Kondo, Yosuke; Shimokawa, Yoshiyuki; Iwao, Yasunori; Itai, Shigeru

2018-01-15

A new scale-down methodology from commercial rotary die scale to laboratory scale was developed to optimize a plant-derived soft gel capsule formulation and eventually manufacture superior soft gel capsules on a commercial scale, in order to reduce the time and cost for formulation development. Animal-derived and plant-derived soft gel film sheets were prepared using an applicator on a laboratory scale and their physicochemical properties, such as tensile strength, Young's modulus, and adhesive strength, were evaluated. The tensile strength of the animal-derived and plant-derived soft gel film sheets was 11.7 MPa and 4.41 MPa, respectively. The Young's modulus of the animal-derived and plant-derived soft gel film sheets was 169 MPa and 17.8 MPa, respectively, and both sheets showed a similar adhesion strength of approximately 4.5-10 MPa. Using a D-optimal mixture design, plant-derived soft gel film sheets were prepared and optimized by varying their composition, including variations in the mass of κ-carrageenan, ι-carrageenan, oxidized starch and heat-treated starch. The physicochemical properties of the sheets were evaluated to determine the optimal formulation. Finally, plant-derived soft gel capsules were manufactured using the rotary die method and the prepared soft gel capsules showed equivalent or superior physical properties compared with pre-existing soft gel capsules. Therefore, we successfully developed a new scale-down methodology to optimize the formulation of plant-derived soft gel capsules on a commercial scale. Copyright © 2017 Elsevier B.V. All rights reserved.

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

Optimization of some electrochemical etching parameters for cellulose derivatives

International Nuclear Information System (INIS)

Chowdhury, Annis; Gammage, R.B.

1978-01-01

Electrochemical etching of fast neutron induced recoil particle tracks in cellulose derivatives and other polymers provides an inexpensive and sensitive means of fast neutron personnel dosimetry. A study of the shape, clarity, and size of the tracks in Transilwrap polycarbonate indicated that the optimum normality of the potassium hydroxide etching solution is 9 N. Optimizations have also been attempted for cellulose nitrate, triacetate, and acetobutyrate with respect to such electrochemical etching parameters as frequency, voltage gradient, and concentration of the etching solution. The measurement of differential leakage currents between the undamaged and the neutron damaged foils aided in the selection of optimum frequencies. (author)

Development and Validation of RP-LC Method for the Determination of Cinnarizine/Piracetam and Cinnarizine/Heptaminol Acefyllinate in Presence of Cinnarizine Reported Degradation Products

Directory of Open Access Journals (Sweden)

Ola M. EL-Houssini

2013-01-01

Full Text Available Specific stability indicating reverse-phase liquid chromatography (RP-LC assay method (SIAM was developed for the determination of cinnarizine (Cinn/piracetam (Pira and cinnarizine (Cinn/heptaminol acefyllinate (Hept in the presence of the reported degradation products of Cinn. A C 18 column and gradient mobile phase was applied for good resolution of all peaks. The detection was achieved at 210 nm and 254 nm for Cinn/Pira and Cinn/Hept, respectively. The responses were linear over concentration ranges of 20-200, 20-1000 and 25-1000 μgmL −1 for Cinn, Pira, and Hept respectively. The proposed method was validated for linearity, accuracy, repeatability, intermediate precision, and robustness via statistical analysis of the data. The method was shown to be precise, accurate, reproducible, sensitive, and selective for the analysis of Cinn/Pira and Cinn/Hept in laboratory prepared mixtures and in pharmaceutical formulations.

Development and Validation of RP-LC Method for the Determination of Cinnarizine/Piracetam and Cinnarizine/Heptaminol Acefyllinate in Presence of Cinnarizine Reported Degradation Products

Science.gov (United States)

EL-Houssini, Ola M.; Zawilla, Nagwan H.; Mohammad, Mohammad A.

2013-01-01

Specific stability indicating reverse-phase liquid chromatography (RP-LC) assay method (SIAM) was developed for the determination of cinnarizine (Cinn)/piracetam (Pira) and cinnarizine (Cinn)/heptaminol acefyllinate (Hept) in the presence of the reported degradation products of Cinn. A C18 column and gradient mobile phase was applied for good resolution of all peaks. The detection was achieved at 210 nm and 254 nm for Cinn/Pira and Cinn/Hept, respectively. The responses were linear over concentration ranges of 20–200, 20–1000 and 25–1000 μgmL−1 for Cinn, Pira, and Hept respectively. The proposed method was validated for linearity, accuracy, repeatability, intermediate precision, and robustness via statistical analysis of the data. The method was shown to be precise, accurate, reproducible, sensitive, and selective for the analysis of Cinn/Pira and Cinn/Hept in laboratory prepared mixtures and in pharmaceutical formulations. PMID:24137049

5-Alkyl-6-benzyl-2-(2-oxo-2-phenylethylsulfanyl)pyrimidin-4(3H)-ones, a series of anti-HIV-1 agents of the dihydro-alkoxy-benzyl-oxopyrimidine family with peculiar structure-activity relationship profile.

Science.gov (United States)

Nawrozkij, Maxim B; Rotili, Dante; Tarantino, Domenico; Botta, Giorgia; Eremiychuk, Alexandre S; Musmuca, Ira; Ragno, Rino; Samuele, Alberta; Zanoli, Samantha; Armand-Ugón, Mercedes; Clotet-Codina, Imma; Novakov, Ivan A; Orlinson, Boris S; Maga, Giovanni; Esté, José A; Artico, Marino; Mai, Antonello

2008-08-14

A series of dihydro-alkylthio-benzyl-oxopyrimidines (S-DABOs) bearing a 2-aryl-2-oxoethylsulfanyl chain at pyrimidine C2, an alkyl group at C5, and a 2,6-dichloro-, 2-chloro-6-fluoro-, and 2,6-difluoro-benzyl substitution at C6 (oxophenethyl- S-DABOs, 6-8) is here described. The new compounds showed low micromolar to low nanomolar (in one case subnanomolar) inhibitory activity against wt HIV-1. Against clinically relevant HIV-1 mutants (K103N, Y181C, and Y188L) as well as in enzyme (wt and K103N, Y181I, and L100I mutated RTs) assays, compounds carrying an ethyl/ iso-propyl group at C5 and a 2,6-dichloro-/2-chloro-6-fluoro-benzyl moiety at C6 were the most potent derivatives, also characterized by low fold resistance ratio. Interestingly, the structure-activity relationship (SAR) data drawn from this DABO series are more related to HEPT than to DABO derivatives. These findings were at least in part rationalized by the description of a fair superimposition between the 6-8 and TNK-651 (a HEPT analogue) binding modes in both WT and Y181C RTs.

Optimal allocation of energy storage in a co-optimized electricity market: Benefits assessment and deriving indicators for economic storage ventures

International Nuclear Information System (INIS)

Krishnan, Venkat; Das, Trishna

2015-01-01

This paper presents a framework for optimally allocating storage technologies in a power system. This decision support tool helps in quantitatively answering the questions on “where to and how much to install” considering the profits from arbitrage opportunities in a co-optimized electricity market. The developed framework is illustrated on a modified IEEE (Institute of Electrical and Electronics Engineers) 24 bus RTS (Reliability Test System), and the framework finds the optimal allocation solution and the revenues storage earns at each of these locations. Bulk energy storage, CAES (compressed air energy storage) is used as the representative storage technology, and the benefits of optimally allocated storage integration onto the grid are compared with transmission expansion solution. The paper also discusses about system-level indicators to identify candidate locations for economical storage ventures, which are derived based on the optimal storage allocation solution; and applies the market price based storage venture indicators on MISO (Mid-continental Independent System Operator) and PJM (Pennsylvania-New Jersey-Maryland Interconnection) electricity markets. - Highlights: • Storage optimal allocation framework based on high-fidelity storage dispatch model. • Storage with transmission addresses energy and ancillary issues under high renewables. • Bulk storage earns higher revenues from co-optimization (∼10× energy only market). • Grid offers distributed opportunities for investing in a strategic mix of storage. • Storage opportunities depend on cross-arbitrage, as seen from MISO (Mid-continental Independent System Operator) and PJM (Pennsylvania-New Jersey-Maryland Interconnection) markets

Design of proportional-integral-derivative type optimal controller for a nuclear reactor

International Nuclear Information System (INIS)

Pal, Jayanta

1976-01-01

A theoretic approach to the design of a proportional integral derivative (PID) type optimal controller for a nuclear reactor is considered. A linearized version of the state-space model of a nuclear-reactor-plant is investigated which shows very 'sluggish' response (settling time of the order of 600 seconds) to changes in the power demand and frequency. It is shown that with a judicious choice of state variables a PID type optimal controller realisation is possible. A controller is designed to minimise the effects of (a) a sudden increase or decrease in the electrical power demand (b) change in frequency at grid. The above controller, designed for a tracking problem, reduces the steady-state error (in response to a step input) to zero and the dynamics of the system become 'faster' (setting time of the order of 100 seconds). The controller is also insensitive to changes in system parameters. The superiority in the performance of the system with the optimal PID controller as compared with that of the conventional regulator is conclusively established. (author)

Laplace-Fourier-domain dispersion analysis of an average derivative optimal scheme for scalar-wave equation

Science.gov (United States)

Chen, Jing-Bo

2014-06-01

By using low-frequency components of the damped wavefield, Laplace-Fourier-domain full waveform inversion (FWI) can recover a long-wavelength velocity model from the original undamped seismic data lacking low-frequency information. Laplace-Fourier-domain modelling is an important foundation of Laplace-Fourier-domain FWI. Based on the numerical phase velocity and the numerical attenuation propagation velocity, a method for performing Laplace-Fourier-domain numerical dispersion analysis is developed in this paper. This method is applied to an average-derivative optimal scheme. The results show that within the relative error of 1 per cent, the Laplace-Fourier-domain average-derivative optimal scheme requires seven gridpoints per smallest wavelength and smallest pseudo-wavelength for both equal and unequal directional sampling intervals. In contrast, the classical five-point scheme requires 23 gridpoints per smallest wavelength and smallest pseudo-wavelength to achieve the same accuracy. Numerical experiments demonstrate the theoretical analysis.

Journal of Chemical Sciences | Indian Academy of Sciences

Indian Academy of Sciences (India)

Topological estimation of cytotoxic activity of some anti-HIV agents: HEPT analogues · Vijay K Agrawal Kamlesh Mishra Ruchi Sharma P V Khadikar · More Details Abstract Fulltext PDF. QSAR studies on anti-HIV cytotoxic activities of a series of HEPT(1-[(2-hydroxyethoxy) methyl]-6-(phenylthio)-thymine) analogues have ...

Design of two-channel filter bank using nature inspired optimization based fractional derivative constraints.

Science.gov (United States)

Kuldeep, B; Singh, V K; Kumar, A; Singh, G K

2015-01-01

In this article, a novel approach for 2-channel linear phase quadrature mirror filter (QMF) bank design based on a hybrid of gradient based optimization and optimization of fractional derivative constraints is introduced. For the purpose of this work, recently proposed nature inspired optimization techniques such as cuckoo search (CS), modified cuckoo search (MCS) and wind driven optimization (WDO) are explored for the design of QMF bank. 2-Channel QMF is also designed with particle swarm optimization (PSO) and artificial bee colony (ABC) nature inspired optimization techniques. The design problem is formulated in frequency domain as sum of L2 norm of error in passband, stopband and transition band at quadrature frequency. The contribution of this work is the novel hybrid combination of gradient based optimization (Lagrange multiplier method) and nature inspired optimization (CS, MCS, WDO, PSO and ABC) and its usage for optimizing the design problem. Performance of the proposed method is evaluated by passband error (ϕp), stopband error (ϕs), transition band error (ϕt), peak reconstruction error (PRE), stopband attenuation (As) and computational time. The design examples illustrate the ingenuity of the proposed method. Results are also compared with the other existing algorithms, and it was found that the proposed method gives best result in terms of peak reconstruction error and transition band error while it is comparable in terms of passband and stopband error. Results show that the proposed method is successful for both lower and higher order 2-channel QMF bank design. A comparative study of various nature inspired optimization techniques is also presented, and the study singles out CS as a best QMF optimization technique. Copyright © 2014 ISA. Published by Elsevier Ltd. All rights reserved.

A method for stochastic constrained optimization using derivative-free surrogate pattern search and collocation

International Nuclear Information System (INIS)

Sankaran, Sethuraman; Audet, Charles; Marsden, Alison L.

2010-01-01

Recent advances in coupling novel optimization methods to large-scale computing problems have opened the door to tackling a diverse set of physically realistic engineering design problems. A large computational overhead is associated with computing the cost function for most practical problems involving complex physical phenomena. Such problems are also plagued with uncertainties in a diverse set of parameters. We present a novel stochastic derivative-free optimization approach for tackling such problems. Our method extends the previously developed surrogate management framework (SMF) to allow for uncertainties in both simulation parameters and design variables. The stochastic collocation scheme is employed for stochastic variables whereas Kriging based surrogate functions are employed for the cost function. This approach is tested on four numerical optimization problems and is shown to have significant improvement in efficiency over traditional Monte-Carlo schemes. Problems with multiple probabilistic constraints are also discussed.

Synthesis of polyhydroxylated cyclopentanes from bromodeoxyaldonolactones

DEFF Research Database (Denmark)

Horneman, Anne Marie

-azido-7-bromo-5,6-di-O-acetyl-2,3,7-trideoxy-D-arabino-hept-2-en ono-1,4-lactone (38) was prepared starting from 1. Additionally, compound 3 was converted into the C-4 epimer 35 by base catalysed epimerisation.The eight 7-bromo-7-deoxy-hept-2-enono-1,4-lactones were submitted to tributyltin hydride...

A derived heuristics based multi-objective optimization procedure for micro-grid scheduling

Science.gov (United States)

Li, Xin; Deb, Kalyanmoy; Fang, Yanjun

2017-06-01

With the availability of different types of power generators to be used in an electric micro-grid system, their operation scheduling as the load demand changes with time becomes an important task. Besides satisfying load balance constraints and the generator's rated power, several other practicalities, such as limited availability of grid power and restricted ramping of power output from generators, must all be considered during the operation scheduling process, which makes it difficult to decide whether the optimization results are accurate and satisfactory. In solving such complex practical problems, heuristics-based customized optimization algorithms are suggested. However, due to nonlinear and complex interactions of variables, it is difficult to come up with heuristics in such problems off-hand. In this article, a two-step strategy is proposed in which the first task deciphers important heuristics about the problem and the second task utilizes the derived heuristics to solve the original problem in a computationally fast manner. Specifically, the specific operation scheduling is considered from a two-objective (cost and emission) point of view. The first task develops basic and advanced level knowledge bases offline from a series of prior demand-wise optimization runs and then the second task utilizes them to modify optimized solutions in an application scenario. Results on island and grid connected modes and several pragmatic formulations of the micro-grid operation scheduling problem clearly indicate the merit of the proposed two-step procedure.

Benchmarking of the maintenance cost in HEPT Centers

CERN Document Server

Béjar-Alonso, Isabel; Rühl, I; CERN. Geneva. ST Division

2002-01-01

This article is the follow up of the paper "Analyse of maintenance cost in ST" presented at the 4th Workshop in Chamonix. Last year the equipment was grouped into families and the ratio of the maintenance cost over the replacement value for each family was calculated. This was done to make an evaluation of the level of maintenance compared with other similar laboratories. This paper shows the result of this comparison. The paper tries to highlight the problem evaluating the level of maintenance and the use of resources. With scarce resources available the division has to make sure that they are allocated and followed up in the best possible and optimal way. "Input" or "quantitative" measurements will therefore have to be combined with performance indicators. This is the only way to measure and evaluate the effect the use of resources has on the output

Photoinjector optimization using a derivative-free, model-based trust-region algorithm for the Argonne Wakefield Accelerator

Science.gov (United States)

Neveu, N.; Larson, J.; Power, J. G.; Spentzouris, L.

2017-07-01

Model-based, derivative-free, trust-region algorithms are increasingly popular for optimizing computationally expensive numerical simulations. A strength of such methods is their efficient use of function evaluations. In this paper, we use one such algorithm to optimize the beam dynamics in two cases of interest at the Argonne Wakefield Accelerator (AWA) facility. First, we minimize the emittance of a 1 nC electron bunch produced by the AWA rf photocathode gun by adjusting three parameters: rf gun phase, solenoid strength, and laser radius. The algorithm converges to a set of parameters that yield an emittance of 1.08 μm. Second, we expand the number of optimization parameters to model the complete AWA rf photoinjector (the gun and six accelerating cavities) at 40 nC. The optimization algorithm is used in a Pareto study that compares the trade-off between emittance and bunch length for the AWA 70MeV photoinjector.

Rapid formation of complexity in the total synthesis of natural products enabled by oxabicyclo[2.2.1]heptene building blocks.

Science.gov (United States)

Schindler, Corinna S; Carreira, Erick M

2009-11-01

This critical review showcases examples of rapid formation of complexity in total syntheses starting from 7-oxabicyclo[2.2.1]hept-5-ene derivatives. An overview of methods allowing synthetic access to these building blocks is provided and their application in recently developed synthetic transformations to structurally complex systems is illustrated. In addition, the facile access to a novel oxabicyclo[2.2.1]heptene derived building block is presented which significantly enlarges the possibilities of previously known chemical transformations and is highlighted in the enantioselective route to the core of the banyaside and suomilide natural products (107 references).

Derivation of Optimal Cropping Pattern in Part of Hirakud Command using Cuckoo Search

Science.gov (United States)

Rath, Ashutosh; Biswal, Sudarsan; Samantaray, Sandeep; Swain, Prakash Chandra, PROF.

2017-08-01

The economicgrowth of a Nation depends on agriculture which relies on the obtainable water resources, available land and crops. The contribution of water in an appropriate quantity at appropriate time plays avitalrole to increase the agricultural production. Optimal utilization of available resources can be achieved by proper planning and management of water resources projects and adoption of appropriate technology. In the present work, the command area of Sambalpur distribrutary System is taken up for investigation. Further, adoption of a fixed cropping pattern causes the reduction of yield. The present study aims at developing different crop planning strategies to increase the net benefit from the command area with minimum investment. Optimization models are developed for Kharif season using LINDO and Cuckoo Search (CS) algorithm for maximization of the net benefits. In process of development of Optimization model the factors such as cultivable land, seeds, fertilizers, man power, water cost, etc. are taken as constraints. The irrigation water needs of major crops and the total available water through canals in the command of Sambalpur Distributary are estimated. LINDO and Cuckoo Search models are formulated and used to derive the optimal cropping pattern yielding maximum net benefits. The net benefits of Rs.585.0 lakhs in Kharif Season are obtained by adopting LINGO and 596.07 lakhs from Cuckoo Search, respectively, whereas the net benefits of 447.0 lakhs is received by the farmers of the locality with the adopting present cropping pattern.

A novel simple QSAR model for the prediction of anti-HIV activity using multiple linear regression analysis.

Science.gov (United States)

Afantitis, Antreas; Melagraki, Georgia; Sarimveis, Haralambos; Koutentis, Panayiotis A; Markopoulos, John; Igglessi-Markopoulou, Olga

2006-08-01

A quantitative-structure activity relationship was obtained by applying Multiple Linear Regression Analysis to a series of 80 1-[2-hydroxyethoxy-methyl]-6-(phenylthio) thymine (HEPT) derivatives with significant anti-HIV activity. For the selection of the best among 37 different descriptors, the Elimination Selection Stepwise Regression Method (ES-SWR) was utilized. The resulting QSAR model (R (2) (CV) = 0.8160; S (PRESS) = 0.5680) proved to be very accurate both in training and predictive stages.

An inequality for detecting financial fraud, derived from the Markowitz Optimal Portfolio Theory

Science.gov (United States)

Bard, Gregory V.

2016-12-01

The Markowitz Optimal Portfolio Theory, published in 1952, is well-known, and was often taught because it blends Lagrange Multipliers, matrices, statistics, and mathematical finance. However, the theory faded from prominence in American investing, as Business departments at US universities shifted from techniques based on mathematics, finance, and statistics, to focus instead on leadership, public speaking, interpersonal skills, advertising, etc… The author proposes a new application of Markowitz's Theory: the detection of a fairly broad category of financial fraud (called "Ponzi schemes" in American newspapers) by looking at a particular inequality derived from the Markowitz Optimal Portfolio Theory, relating volatility and expected rate of return. For example, one recent Ponzi scheme was that of Bernard Madoff, uncovered in December 2008, which comprised fraud totaling 64,800,000,000 US dollars [23]. The objective is to compare investments with the "efficient frontier" as predicted by Markowitz's theory. Violations of the inequality should be impossible in theory; therefore, in practice, violations might indicate fraud.

Derivation of Optimal Operating Rules for Large-scale Reservoir Systems Considering Multiple Trade-off

Science.gov (United States)

Zhang, J.; Lei, X.; Liu, P.; Wang, H.; Li, Z.

2017-12-01

Flood control operation of multi-reservoir systems such as parallel reservoirs and hybrid reservoirs often suffer from complex interactions and trade-off among tributaries and the mainstream. The optimization of such systems is computationally intensive due to nonlinear storage curves, numerous constraints and complex hydraulic connections. This paper aims to derive the optimal flood control operating rules based on the trade-off among tributaries and the mainstream using a new algorithm known as weighted non-dominated sorting genetic algorithm II (WNSGA II). WNSGA II could locate the Pareto frontier in non-dominated region efficiently due to the directed searching by weighted crowding distance, and the results are compared with those of conventional operating rules (COR) and single objective genetic algorithm (GA). Xijiang river basin in China is selected as a case study, with eight reservoirs and five flood control sections within four tributaries and the mainstream. Furthermore, the effects of inflow uncertainty have been assessed. Results indicate that: (1) WNSGA II could locate the non-dominated solutions faster and provide better Pareto frontier than the traditional non-dominated sorting genetic algorithm II (NSGA II) due to the weighted crowding distance; (2) WNSGA II outperforms COR and GA on flood control in the whole basin; (3) The multi-objective operating rules from WNSGA II deal with the inflow uncertainties better than COR. Therefore, the WNSGA II can be used to derive stable operating rules for large-scale reservoir systems effectively and efficiently.

Structure activity relationships of quinoxalin-2-one derivatives as platelet-derived growth factor-beta receptor (PDGFbeta R) inhibitors, derived from molecular modeling.

Science.gov (United States)

Mori, Yoshikazu; Hirokawa, Takatsugu; Aoki, Katsuyuki; Satomi, Hisanori; Takeda, Shuichi; Aburada, Masaki; Miyamoto, Ken-ichi

2008-05-01

We previously reported a quinoxalin-2-one compound (Compound 1) that had inhibitory activity equivalent to existing platelet-derived growth factor-beta receptor (PDGFbeta R) inhibitors. Lead optimization of Compound 1 to increase its activity and selectivity, using structural information regarding PDGFbeta R-ligand interactions, is urgently needed. Here we present models of the PDGFbeta R kinase domain complexed with quinoxalin-2-one derivatives. The models were constructed using comparative modeling, molecular dynamics (MD) and ligand docking. In particular, conformations derived from MD, and ligand binding site information presented by alpha-spheres in the pre-docking processing, allowed us to identify optimal protein structures for docking of target ligands. By carrying out molecular modeling and MD of PDGFbeta R in its inactive state, we obtained two structural models having good Compound 1 binding potentials. In order to distinguish the optimal candidate, we evaluated the structural activity relationships (SAR) between the ligand-binding free energies and inhibitory activity values (IC50 values) for available quinoxalin-2-one derivatives. Consequently, a final model with a high SAR was identified. This model included a molecular interaction between the hydrophobic pocket behind the ATP binding site and the substitution region of the quinoxalin-2-one derivatives. These findings should prove useful in lead optimization of quinoxalin-2-one derivatives as PDGFb R inhibitors.

Preparation of 2H- and 13C-labelled precursors of 2-hydroxy-1, 3-butadiene

International Nuclear Information System (INIS)

Turecek, F.

1987-01-01

2-exo-Vinylbicyclo[2.2.1]hept-5-en-2-ols, specifically labelled with 2 H at C-3 and in the vinyl group were prepared from bicyclo[2.2.1]hept-5-en-2-one in several steps. [4- 13 C]oct-1-en-3-one was prepared in five steps from 13 CO 2 . These compounds serve as precursors for the preparation of specifically labelled neutral and ionized 2-hydroxy-1, 3-butadienes. (author)

Design Optimization of Internal Flow Devices

DEFF Research Database (Denmark)

Madsen, Jens Ingemann

The power of computational fluid dynamics is boosted through the use of automated design optimization methodologies. The thesis considers both derivative-based search optimization and the use of response surface methodologies.......The power of computational fluid dynamics is boosted through the use of automated design optimization methodologies. The thesis considers both derivative-based search optimization and the use of response surface methodologies....

Derivation of optimal joint operating rules for multi-purpose multi-reservoir water-supply system

Science.gov (United States)

Tan, Qiao-feng; Wang, Xu; Wang, Hao; Wang, Chao; Lei, Xiao-hui; Xiong, Yi-song; Zhang, Wei

2017-08-01

The derivation of joint operating policy is a challenging task for a multi-purpose multi-reservoir system. This study proposed an aggregation-decomposition model to guide the joint operation of multi-purpose multi-reservoir system, including: (1) an aggregated model based on the improved hedging rule to ensure the long-term water-supply operating benefit; (2) a decomposed model to allocate the limited release to individual reservoirs for the purpose of maximizing the total profit of the facing period; and (3) a double-layer simulation-based optimization model to obtain the optimal time-varying hedging rules using the non-dominated sorting genetic algorithm II, whose objectives were to minimize maximum water deficit and maximize water supply reliability. The water-supply system of Li River in Guangxi Province, China, was selected for the case study. The results show that the operating policy proposed in this study is better than conventional operating rules and aggregated standard operating policy for both water supply and hydropower generation due to the use of hedging mechanism and effective coordination among multiple objectives.

Optimization of simultaneous saccharification and fermentation conditions with amphipathic lignin derivatives for concentrated bioethanol production.

Science.gov (United States)

Cheng, Ningning; Koda, Keiichi; Tamai, Yutaka; Yamamoto, Yoko; Takasuka, Taichi E; Uraki, Yasumitsu

2017-05-01

Amphipathic lignin derivatives (A-LDs) prepared from the black liquor of soda pulping of Japanese cedar are strong accelerators for bioethanol production under a fed-batch simultaneous enzymatic saccharification and fermentation (SSF) process. To improve the bioethanol production concentration, conditions such as reaction temperature, stirring program, and A-LDs loadings were optimized in both small scale and large scale fed-batch SSF. The fed-batch SSF in the presence of 3.0g/L A-LDs at 38°C gave the maximum ethanol production and a high enzyme recovery rate. Furthermore, a jar-fermenter equipped with a powerful mechanical stirrer was designed for 1.5L-scale fed-batch SSF to achieve rigorous mixing during high substrate loading. Finally, the 1.5L fed-batch SSF with a substrate loading of 30% (w/v) produced a high ethanol concentration of 87.9g/L in the presence of A-LDs under optimized conditions. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Synthesis, characterization and evaluation of biological activities of some 2,3-diaryl bicyclo methanones

Directory of Open Access Journals (Sweden)

Thirunarayanan Ganesamoorthy

2016-06-01

Full Text Available Sixteen (3,4-dichlorophenyl-3-(substituted phenylbicyclo[2.2.1]hept-5-ene-2-yl methanone derivatives have been synthesized by an aqueous phase fly-ash catalyzed [4+2] cycloaddition Diels-Alder reaction of cyclopentadiene and 3,4-dichloro phenyl chalcones. The yields of the methanones were greater than 60%. The synthesized methanones were characterized by their physical constants and spectral data. The antimicrobial and antioxidant activities of the synthesized methanones were evaluated using a variety of bacterial and fungal species and DPPH radical scavenging methods.

Approximate analytical solution of diffusion equation with fractional time derivative using optimal homotopy analysis method

Directory of Open Access Journals (Sweden)

S. Das

2013-12-01

Full Text Available In this article, optimal homotopy-analysis method is used to obtain approximate analytic solution of the time-fractional diffusion equation with a given initial condition. The fractional derivatives are considered in the Caputo sense. Unlike usual Homotopy analysis method, this method contains at the most three convergence control parameters which describe the faster convergence of the solution. Effects of parameters on the convergence of the approximate series solution by minimizing the averaged residual error with the proper choices of parameters are calculated numerically and presented through graphs and tables for different particular cases.

Thermal rearrangement of 7-methylbicyclo

Science.gov (United States)

Bender; Leber; Lirio; Smith

2000-08-25

The gas-phase thermal rearrangement of exo-7-methylbicyclo[3.2.0]hept-2-ene yields almost exclusively 5-methylnorbornene products. Inversion (i) of configuration dominates this [1,3] sigmatropic shift although some retention (r) is also observed. Because the [1,3] migration can only occur suprafacially (s) in this geometrically constrained system, the si/sr ratio of 7 observed for the migration of C7 in exo-7-methylbicyclo[3.2.0]hept-2-ene indicates that the orbital symmetry rules are somewhat permissive for the [1,3] sigmatropic migration of carbon.

Optimized Production of Coal Fly Ash Derived Synthetic Zeolites for Mercury Removal from Wastewater

Science.gov (United States)

Tauanov, Z.; Shah, D.; Itskos, G.; Inglezakis, V.

2017-09-01

Coal fly ash (CFA) derived synthetic zeolites have become popular with recent advances and its ever-expanding range of applications, particularly as an adsorbent for water and gas purification and as a binder or additive in the construction industry and agriculture. Among these applications, perpetual interest has been in utilization of CFA derived synthetic zeolites for removal of heavy metals from wastewater. We herein focus on utilization of locally available CFA for efficient adsorption of mercury from wastewater. To this end, experimental conditions were investigated so that to produce synthetic zeolites from Kazakhstani CFAs with conversion into zeolite up to 78%, which has remarkably high magnetite content. In particular, the effect of synthesis reaction temperature, reaction time, and loading of adsorbent were systematically investigated and optimized. All produced synthetic zeolites and the respective CFAs were characterized using XRD, XRF, PSA and porosimetric instruments to obtain microstructural and mineralogical data. Furthermore, the synthesized zeolites were studied for the removal of mercury from aqueous solutions. A comparison of removal eficiency and its relationship to the physical and chemical properties of the synthetic zeolites were analyzed and interpreted.

Polycyclic aromatic hydrocarbons degradation by marine-derived basidiomycetes: optimization of the degradation process.

Science.gov (United States)

Vieira, Gabriela A L; Magrini, Mariana Juventina; Bonugli-Santos, Rafaella C; Rodrigues, Marili V N; Sette, Lara D

2018-05-03

Pyrene and benzo[a]pyrene (BaP) are high molecular weight polycyclic aromatic hydrocarbons (PAHs) recalcitrant to microbial attack. Although studies related to the microbial degradation of PAHs have been carried out in the last decades, little is known about degradation of these environmental pollutants by fungi from marine origin. Therefore, this study aimed to select one PAHs degrader among three marine-derived basidiomycete fungi and to study its pyrene detoxification/degradation. Marasmiellus sp. CBMAI 1062 showed higher levels of pyrene and BaP degradation and was subjected to studies related to pyrene degradation optimization using experimental design, acute toxicity, organic carbon removal (TOC), and metabolite evaluation. The experimental design resulted in an efficient pyrene degradation, reducing the experiment time while the PAH concentration applied in the assays was increased. The selected fungus was able to degrade almost 100% of pyrene (0.08mgmL -1 ) after 48h of incubation under saline condition, without generating toxic compounds and with a TOC reduction of 17%. Intermediate metabolites of pyrene degradation were identified, suggesting that the fungus degraded the compound via the cytochrome P450 system and epoxide hydrolases. These results highlight the relevance of marine-derived fungi in the field of PAH bioremediation, adding value to the blue biotechnology. Copyright © 2018. Published by Elsevier Editora Ltda.

Three column intermittent simulated moving bed chromatography: 3. Cascade operation for center-cut separations.

Science.gov (United States)

Jermann, Simon; Meijssen, Mattheus; Mazzotti, Marco

2015-01-23

A general design methodology for chromatographic three fraction separation by application of the three column intermittent simulated moving bed (3C-ISMB) cascade is proposed and experimentally validated by studying the purification of an intermediately retained stereoisomer of nadolol, from an equimolar mixture of its four stereoisomers. The theoretical part shows that the 3C-ISMB cascade can be easily designed by applying Triangle Theory. Moreover, a re-scaling approach for the second stage is proposed so as to account for the fact that the feed flow rates to stage 2 are generally higher as compared to stage 1 due to dilution in the latter. Scaling the columns of the second stage accordingly enables to run both stages under optimal conditions with respect to switching time and step ratio, which is an important advantage as compared to integrated ternary processes. The experimental part starts with studying the linear adsorption behavior of nadolol in heptane/ethanol/DEA on Chiralpak AD for varying ratios of heptane and ethanol. Based on that, a solvent composition of Hept/EtOH/DEA 30/70/0.3 (v/v/v) is selected and the competitive multi-component Langmuir isotherm of the quaternary mixture is determined by frontal analysis. The resulting isotherm parameters are used to design several first stage experiments aiming at removal of the most retained component. The resulting ternary intermediate product is reprocessed in several second stage experiments studying various configurations. Finally, the dilution of the intermediate product with Hept/DEA yielding a solvent composition of Hept/EtOH/DEA 60/40/0.3 (v/v/v) is examined showing that the resulting increase in retention is beneficial for final product purities. Moreover, the reduction in viscosity compensates for the dilution as it enables higher flow rates. Dilution of the intermediate product is hence the best option, yielding highest overall cascade productivity (2.10gl(-1)h(-1)) and highest product purity (97

New natural shapes of non-Gaussianity from high-derivative interactions and their optimal limits from WMAP 9-year data

International Nuclear Information System (INIS)

Behbahani, Siavosh R.; Mirbabayi, Mehrdad; Senatore, Leonardo; Smith, Kendrick M.

2014-01-01

Given the fantastic experimental effort, it is important to thoroughly explore the signature space of inflationary models. The fact that higher derivative operators do not renormalize lower derivative ones allows us to find a large class of technically natural single-clock inflationary models where, in the context of the Effective Field Theory of Inflation, the leading interactions have many derivatives. We systematically explore the 3-point function induced by these models and their overlap with the standard equilateral and orthogonal templates. We find that in order to satisfactorily cover the signature space of these models, two new additional templates need to be included. We then perform the optimal analysis of the WMAP 9-year data for the resulting four templates, finding that the overall significance of a non-zero signal is between 2–2.5σ, depending on the choice of parameter space, partially driven by the preference for nonzero f NL orth in WMAP9

Optimization Design of Structures Subjected to Transient Loads Using First and Second Derivatives of Dynamic Displacement and Stress

Directory of Open Access Journals (Sweden)

Qimao Liu

2012-01-01

Full Text Available This paper developed an effective optimization method, i.e., gradient-Hessian matrix-based method or second order method, of frame structures subjected to the transient loads. An algorithm of first and second derivatives of dynamic displacement and stress with respect to design variables is formulated based on the Newmark method. The inequality time-dependent constraint problem is converted into a sequence of appropriately formed time-independent unconstrained problems using the integral interior point penalty function method. The gradient and Hessian matrixes of the integral interior point penalty functions are also computed. Then the Marquardt's method is employed to solve unconstrained problems. The numerical results show that the optimal design method proposed in this paper can obtain the local optimum design of frame structures and sometimes is more efficient than the augmented Lagrange multiplier method.

Structure of the 8He exotic nucleus by the direct reactions 8He(p, p')8He, 8He(p,d)7He and 8He(p,t)6He

International Nuclear Information System (INIS)

Skaza, Flore

2004-01-01

The elastic and inelastic scattering of an 8 He beam on a proton target have been measured at GANIL. The first 8 He beam produced by the SPIRAL facility at an energy of 15.6 A.MeV impinged on a proton target. The experimental setup was composed by the eight telescopes MUST array dedicated to the measure of the light charged particles, by a scintillator plastic wall for the detection of heavy projectile, and by two beam tracking detectors CATS for the measure event by event of the incident position and angle of the beam on the target. This setup allowed also to measure the one and two neutron transfer reactions 8 He(p,d) 7 He and 8 He(p,t) 6 He. The excitation energy spectrum for 6,7,8 He and the angular distributions associated to each reaction have been measured. The observed excited states are in agreement with the data of the literature. We indicate the presence of a first excited state for 7 He at 0.9 MeV and we give for the first time the position of a second excited state in 8 He at 5.4 MeV; the presence of such state was just suggested in a previous experiment. CCBA calculations allowed to extract a spectroscopic factor of 4.4 ± 1.4 for the pick-up of one neutron from 8 He to 7 He. This value is in agreement with a closed p3/2 sub-shell for 8 He. To analyse the angular distributions for elastic and inelastic scattering, it was necessary to take into account in the formalism used to describe the reactions, via coupled channels reactions calculations, the couplings to the one neutron transfer reaction. (author) [fr

Ser derivation and power optimization of a two-way multirelay cooperative communication system

International Nuclear Information System (INIS)

Rehman, S.U.; Shah, S.I.; Fareed, M.M.

2014-01-01

In this paper, we consider Rayleigh fading based cooperative communication system with AaF (Amplify and Forward) relaying using multiple relays. We take spectrally efficient two-way model of cooperative communication terminals and formulate performance evaluation framework in terms of SER (Symbol Error Rate). We not only consider fading channel for this performance evaluation but also consider the effect of relay terminal location into our model which does not require any CSI (Channel State Information) at transmitting nodes. We have proposed power allocation framework for these nodes and analytically derived SER performance results. We have numerically evaluated this framework for power optimization as well as minimizing required SER. Significant performance improvement as compared with equal power sharing among the cooperating terminals is achieved using our proposed framework. It is shown that virtual cooperative antenna configurations is able to demonstrate up to 3dB gain as compared with co-located antenna configurations. Thus incorporating relay location information for performance evaluation results significant power savings. (author)

Optimization of hydrolysis conditions, isolation, and identification of neuroprotective peptides derived from seahorse Hippocampus trimaculatus.

Science.gov (United States)

Pangestuti, Ratih; Ryu, Bomi; Himaya, Swa; Kim, Se-Kwon

2013-08-01

Hippocampus trimaculatus is one of the most heavily traded seahorse species for traditional medicine purposes in many countries. In the present study, we showed neuroprotective effects of peptide derived from H. trimaculatus against amyloid-β42 (Aβ42) toxicity which are central to the pathogenesis of Alzheimer's diseases (AD). Firstly, H. trimaculatus was separately hydrolyzed by four different enzymes and tested for their protective effect on Aβ42-induced neurotoxicity in differentiated PC12 cells. Pronase E hydrolysate exerted highest protection with cell viability value of 88.33 ± 3.33 %. Furthermore, we used response surface methodology to optimize pronase E hydrolysis conditions and found that temperature at 36.69 °C with the hydrolysis time 20.01 h, enzyme to substrate (E/S) ratio of 2.02 % and pH 7.34 were the most optimum conditions. Following several purification steps, H. trimaculatus-derived neuroprotective peptides (HTP-1) sequence was identified as Gly-Thr-Glu-Asp-Glu-Leu-Asp-Lys (906.4 Da). HTP-1 protected PC12 cells from Aβ42-induced neuronal death with the cell viability value of 85.52 ± 2.22 % and up-regulated pro-survival gene (Bcl-2) expressions. These results suggest that HTP-1 has the potential to be used in treatment of neurodegenerative diseases, particularly AD. Identification, characterization, and synthesis of bioactive components derived from H. trimaculatus have the potential to replace or at least complement the use of seahorse as traditional medicine, which further may become an approach to minimize seahorse exploitation in traditional medicine.

Optimal operation of batch membrane processes

CERN Document Server

Paulen, Radoslav

2016-01-01

This study concentrates on a general optimization of a particular class of membrane separation processes: those involving batch diafiltration. Existing practices are explained and operational improvements based on optimal control theory are suggested. The first part of the book introduces the theory of membrane processes, optimal control and dynamic optimization. Separation problems are defined and mathematical models of batch membrane processes derived. The control theory focuses on problems of dynamic optimization from a chemical-engineering point of view. Analytical and numerical methods that can be exploited to treat problems of optimal control for membrane processes are described. The second part of the text builds on this theoretical basis to establish solutions for membrane models of increasing complexity. Each chapter starts with a derivation of optimal operation and continues with case studies exemplifying various aspects of the control problems under consideration. The authors work their way from th...

Performance optimization of queueing systems with perturbation realization

KAUST Repository

Xia, Li

2012-04-01

After the intensive studies of queueing theory in the past decades, many excellent results in performance analysis have been obtained, and successful examples abound. However, exploring special features of queueing systems directly in performance optimization still seems to be a territory not very well cultivated. Recent progresses of perturbation analysis (PA) and sensitivity-based optimization provide a new perspective of performance optimization of queueing systems. PA utilizes the structural information of queueing systems to efficiently extract the performance sensitivity information from a sample path of system. This paper gives a brief review of PA and performance optimization of queueing systems, focusing on a fundamental concept called perturbation realization factors, which captures the special dynamic feature of a queueing system. With the perturbation realization factors as building blocks, the performance derivative formula and performance difference formula can be obtained. With performance derivatives, gradient-based optimization can be derived, while with performance difference, policy iteration and optimality equations can be derived. These two fundamental formulas provide a foundation for performance optimization of queueing systems from a sensitivity-based point of view. We hope this survey may provide some inspirations on this promising research topic. © 2011 Elsevier B.V. All rights reserved.

An Efficient Power Regeneration and Drive Method of an Induction Motor by Means of an Optimal Torque Derived by Variational Method

Science.gov (United States)

Inoue, Kaoru; Ogata, Kenji; Kato, Toshiji

When the motor speed is reduced by using a regenerative brake, the mechanical energy of rotation is converted to the electrical energy. When the regenerative torque is large, the corresponding current increases so that the copper loss also becomes large. On the other hand, the damping effect of rotation increases according to the time elapse when the regenerative torque is small. In order to use the limited energy effectively, an optimal regenerative torque should be discussed in order to regenerate electrical energy as much as possible. This paper proposes a design methodology of a regenerative torque for an induction motor to maximize the regenerative electric energy by means of the variational method. Similarly, an optimal torque for acceleration is derived in order to minimize the energy to drive. Finally, an efficient motor drive system with the proposed optimal torque and the power storage system stabilizing the DC link voltage will be proposed. The effectiveness of the proposed methods are illustrated by both simulations and experiments.

Optimal control for chemical engineers

CERN Document Server

Upreti, Simant Ranjan

2013-01-01

Optimal Control for Chemical Engineers gives a detailed treatment of optimal control theory that enables readers to formulate and solve optimal control problems. With a strong emphasis on problem solving, the book provides all the necessary mathematical analyses and derivations of important results, including multiplier theorems and Pontryagin's principle.The text begins by introducing various examples of optimal control, such as batch distillation and chemotherapy, and the basic concepts of optimal control, including functionals and differentials. It then analyzes the notion of optimality, de

Implementing optimal thinning strategies

Science.gov (United States)

Kurt H. Riitters; J. Douglas Brodie

1984-01-01

Optimal thinning regimes for achieving several management objectives were derived from two stand-growth simulators by dynamic programming. Residual mean tree volumes were then plotted against stand density management diagrams. The results supported the use of density management diagrams for comparing, checking, and implementing the results of optimization analyses....

Optimal Computing Budget Allocation for Particle Swarm Optimization in Stochastic Optimization.

Science.gov (United States)

Zhang, Si; Xu, Jie; Lee, Loo Hay; Chew, Ek Peng; Wong, Wai Peng; Chen, Chun-Hung

2017-04-01

Particle Swarm Optimization (PSO) is a popular metaheuristic for deterministic optimization. Originated in the interpretations of the movement of individuals in a bird flock or fish school, PSO introduces the concept of personal best and global best to simulate the pattern of searching for food by flocking and successfully translate the natural phenomena to the optimization of complex functions. Many real-life applications of PSO cope with stochastic problems. To solve a stochastic problem using PSO, a straightforward approach is to equally allocate computational effort among all particles and obtain the same number of samples of fitness values. This is not an efficient use of computational budget and leaves considerable room for improvement. This paper proposes a seamless integration of the concept of optimal computing budget allocation (OCBA) into PSO to improve the computational efficiency of PSO for stochastic optimization problems. We derive an asymptotically optimal allocation rule to intelligently determine the number of samples for all particles such that the PSO algorithm can efficiently select the personal best and global best when there is stochastic estimation noise in fitness values. We also propose an easy-to-implement sequential procedure. Numerical tests show that our new approach can obtain much better results using the same amount of computational effort.

Radioiodsodestannylation. Convenient synthesis of a high affinity thromboxane A2/prostaglandin H2 receptor antagonist

International Nuclear Information System (INIS)

Mais, D.E.; Hamanaka, Nobuyuki

1991-01-01

Radioiodination of methyl-7-[(2R, 2S, 5R)-6,6-dimethyl-3-(4-trimethylstannylbenzenesulfononylamino3S) bicyclo[3.1.1]hept-2-yl]-5(Z)-heptenoate with [ 125 I] Na using a modification of the chloramine-T method in organic solvent is simple with high yields and site specific. The product, following hydrolysis of the ester, 7-[(2R, 2S, 3S, 5R)-6,6-dimethyl-3-(4[ 125 I]-iodobenzenesulfonylamino) bicyclo[3.1.1]hept-2-yl]-5(Z)-heptenoic acid [( 125 I]-ISAP), was purified by HPLC. The high specific activity and specific binding will make the ligand a useful tool for the characterization of thromboxane A 2 /prostaglandin H 2 receptors. (author)

SER Derivation and Power Optimization of a Two-Way MultiRelay Cooperative Communication System

Directory of Open Access Journals (Sweden)

Shakeel-Ur-Rehman Rehman

2014-01-01

Full Text Available In this paper, we consider Rayleigh fading based cooperative communication system with AaF (Amplify and Forward relaying using multiple relays. We take spectrally efficient two-way model of cooperative communication terminals and formulate performance evaluation framework in terms of SER (Symbol Error Rate. We not only consider fading channel for this performance evaluation but also consider the effect of relay terminal location into our model which does not require any CSI (Channel State Information at transmitting nodes. We have proposed power allocation framework for these nodes and analytically derived SER performance results. We have numerically evaluated this framework for power optimization as well as minimizing required SER. Significant performance improvement as compared with equal power sharing among the cooperating terminals is achieved using our proposed framework. It is shown that virtual cooperative antenna configurations is able to demonstrate up to 3dB gain as compared with co-located antenna configurations. Thus incorporating relay location information for performance evaluation results significant power savings

Supply-Chain Optimization Template

Science.gov (United States)

Quiett, William F.; Sealing, Scott L.

2009-01-01

The Supply-Chain Optimization Template (SCOT) is an instructional guide for identifying, evaluating, and optimizing (including re-engineering) aerospace- oriented supply chains. The SCOT was derived from the Supply Chain Council s Supply-Chain Operations Reference (SCC SCOR) Model, which is more generic and more oriented toward achieving a competitive advantage in business.

A Comparative Theoretical and Computational Study on Robust Counterpart Optimization: I. Robust Linear Optimization and Robust Mixed Integer Linear Optimization

Science.gov (United States)

Li, Zukui; Ding, Ran; Floudas, Christodoulos A.

2011-01-01

Robust counterpart optimization techniques for linear optimization and mixed integer linear optimization problems are studied in this paper. Different uncertainty sets, including those studied in literature (i.e., interval set; combined interval and ellipsoidal set; combined interval and polyhedral set) and new ones (i.e., adjustable box; pure ellipsoidal; pure polyhedral; combined interval, ellipsoidal, and polyhedral set) are studied in this work and their geometric relationship is discussed. For uncertainty in the left hand side, right hand side, and objective function of the optimization problems, robust counterpart optimization formulations induced by those different uncertainty sets are derived. Numerical studies are performed to compare the solutions of the robust counterpart optimization models and applications in refinery production planning and batch process scheduling problem are presented. PMID:21935263

Derivative load voltage and particle swarm optimization to determine optimum sizing and placement of shunt capacitor in improving line losses

Directory of Open Access Journals (Sweden)

Mohamed Milad Baiek

2016-12-01

Full Text Available The purpose of this research is to study optimal size and placement of shunt capacitor in order to minimize line loss. Derivative load bus voltage was calculated to determine the sensitive load buses which further being optimum with the placement of shunt capacitor. Particle swarm optimization (PSO was demonstrated on the IEEE 14 bus power system to find optimum size of shunt capacitor in reducing line loss. The objective function was applied to determine the proper placement of capacitor and get satisfied solutions towards constraints. The simulation was run over Matlab under two scenarios namely base case and increasing 100% load. Derivative load bus voltage was simulated to determine the most sensitive load bus. PSO was carried out to determine the optimum sizing of shunt capacitor at the most sensitive bus. The results have been determined that the most sensitive bus was bus number 14 for the base case and increasing 100% load. The optimum sizing was 8.17 Mvar for the base case and 23.98 Mvar for increasing load about 100%. Line losses were able to reduce approximately 0.98% for the base case and increasing 100% load reduced about 3.16%. The proposed method was also proven as a better result compared with harmony search algorithm (HSA method. HSA method recorded loss reduction ratio about 0.44% for the base case and 2.67% when the load was increased by 100% while PSO calculated loss reduction ratio about 1.12% and 4.02% for the base case and increasing 100% load respectively. The result of this study will support the previous study and it is concluded that PSO was successfully able to solve some engineering problems as well as to find a solution in determining shunt capacitor sizing on the power system simply and accurately compared with other evolutionary optimization methods.

Optimization of automation: III. Development of optimization method for determining automation rate in nuclear power plants

International Nuclear Information System (INIS)

Lee, Seung Min; Kim, Jong Hyun; Kim, Man Cheol; Seong, Poong Hyun

2016-01-01

Highlights: • We propose an appropriate automation rate that enables the best human performance. • We analyze the shortest working time considering Situation Awareness Recovery (SAR). • The optimized automation rate is estimated by integrating the automation and ostracism rate estimation methods. • The process to derive the optimized automation rate is demonstrated through case studies. - Abstract: Automation has been introduced in various industries, including the nuclear field, because it is commonly believed that automation promises greater efficiency, lower workloads, and fewer operator errors through reducing operator errors and enhancing operator and system performance. However, the excessive introduction of automation has deteriorated operator performance due to the side effects of automation, which are referred to as Out-of-the-Loop (OOTL), and this is critical issue that must be resolved. Thus, in order to determine the optimal level of automation introduction that assures the best human operator performance, a quantitative method of optimizing the automation is proposed in this paper. In order to propose the optimization method for determining appropriate automation levels that enable the best human performance, the automation rate and ostracism rate, which are estimation methods that quantitatively analyze the positive and negative effects of automation, respectively, are integrated. The integration was conducted in order to derive the shortest working time through considering the concept of situation awareness recovery (SAR), which states that the automation rate with the shortest working time assures the best human performance. The process to derive the optimized automation rate is demonstrated through an emergency operation scenario-based case study. In this case study, four types of procedures are assumed through redesigning the original emergency operating procedure according to the introduced automation and ostracism levels. Using the

Optimal Provision of Public Goods

DEFF Research Database (Denmark)

Kreiner, Claus Thustrup; Verdelin, Nicolaj

2012-01-01

The standard approach to the optimal provision of public goods highlights the importance of distortionary taxation and distributional concerns. A new approach neutralizes distributional concerns by adjusting the income tax schedule. We demonstrate that both approaches are derived from the same...... basic formula. We also take the new approach further by deriving an intuitive formula for the optimal level of public goods, without imposing strong assumptions on preferences. This formula shows that distortionary taxation has a role to play, as in the standard approach. However, the main determinants...

Optimality conditions for the numerical solution of optimization problems with PDE constraints :

Energy Technology Data Exchange (ETDEWEB)

Aguilo Valentin, Miguel Alejandro; Ridzal, Denis

2014-03-01

A theoretical framework for the numerical solution of partial di erential equation (PDE) constrained optimization problems is presented in this report. This theoretical framework embodies the fundamental infrastructure required to e ciently implement and solve this class of problems. Detail derivations of the optimality conditions required to accurately solve several parameter identi cation and optimal control problems are also provided in this report. This will allow the reader to further understand how the theoretical abstraction presented in this report translates to the application.

Nanomaterials derived from metal-organic frameworks

Science.gov (United States)

Dang, Song; Zhu, Qi-Long; Xu, Qiang

2018-01-01

The thermal transformation of metal-organic frameworks (MOFs) generates a variety of nanostructured materials, including carbon-based materials, metal oxides, metal chalcogenides, metal phosphides and metal carbides. These derivatives of MOFs have characteristics such as high surface areas, permanent porosities and controllable functionalities that enable their good performance in sensing, gas storage, catalysis and energy-related applications. Although progress has been made to tune the morphologies of MOF-derived structures at the nanometre scale, it remains crucial to further our knowledge of the relationship between morphology and performance. In this Review, we summarize the synthetic strategies and optimized methods that enable control over the size, morphology, composition and structure of the derived nanomaterials. In addition, we compare the performance of materials prepared by the MOF-templated strategy and other synthetic methods. Our aim is to reveal the relationship between the morphology and the physico-chemical properties of MOF-derived nanostructures to optimize their performance for applications such as sensing, catalysis, and energy storage and conversion.

Topology optimization of turbulent flows

DEFF Research Database (Denmark)

Dilgen, Cetin B.; Dilgen, Sumer B.; Fuhrman, David R.

2018-01-01

The aim of this work is to present a fast and viable approach for taking into account turbulence in topology optimization of complex fluid flow systems, without resorting to any simplifying assumptions in the derivation of discrete adjoints. Topology optimization is an iterative gradient...

HEK293 cell culture media study towards bioprocess optimization: Animal derived component free and animal derived component containing platforms.

Science.gov (United States)

Liste-Calleja, Leticia; Lecina, Martí; Cairó, Jordi Joan

2014-04-01

The increasing demand for biopharmaceuticals produced in mammalian cells has lead industries to enhance bioprocess volumetric productivity through different strategies. Among those strategies, cell culture media development is of major interest. In the present work, several commercially available culture media for Human Embryonic Kidney cells (HEK293) were evaluated in terms of maximal specific growth rate and maximal viable cell concentration supported. The main objective was to provide different cell culture platforms which are suitable for a wide range of applications depending on the type and the final use of the product obtained. Performing simple media supplementations with and without animal derived components, an enhancement of cell concentration from 2 × 10(6) cell/mL to 17 × 10(6) cell/mL was achieved in batch mode operation. Additionally, the media were evaluated for adenovirus production as a specific application case of HEK293 cells. None of the supplements interfered significantly with the adenovirus infection although some differences were encountered in viral productivity. To the best of our knowledge, the high cell density achieved in the work presented has never been reported before in HEK293 batch cell cultures and thus, our results are greatly promising to further study cell culture strategies in bioreactor towards bioprocess optimization. Copyright © 2013 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

Isolation and expansion of adipose-derived stem cells for tissue engineering

DEFF Research Database (Denmark)

Fink, Trine; Rasmussen, Jeppe Grøndahl; Lund, Pia

2011-01-01

For treatment of cardiac failure with bone marrow-derived mesenchymal stem cells, several clinical trials are ongoing. However, more attention is gathering on the use of adipose tissue-derived stem cells (ASCs). This paper describes the optimization of isolation and propagation of ASCs for subseq......For treatment of cardiac failure with bone marrow-derived mesenchymal stem cells, several clinical trials are ongoing. However, more attention is gathering on the use of adipose tissue-derived stem cells (ASCs). This paper describes the optimization of isolation and propagation of ASCs...

Linguistic Derivations and Filtering. Minimalism and Optimality Theory

NARCIS (Netherlands)

Broekhuis, H.; Vogel, R.

2013-01-01

This volume focuses on the role of the postulated derivational and filtering devices in current linguistic theory and aims to promote the exchange of ideas between the proponents of MP and OT in order to evaluate the role of these devices in the two frameworks. It sheds more light on the tenability

Multiresponse optimization of a UPLC method for the simultaneous determination of tryptophan and 15 tryptophan-derived compounds using a Box-Behnken design with a desirability function.

Science.gov (United States)

Setyaningsih, Widiastuti; Saputro, Irfan E; Carrera, Ceferino A; Palma, Miguel; Barroso, Carmelo G

2017-06-15

A Box-Behnken design was used in conjunction with multiresponse optimization based on the desirability function to carry out the simultaneous separation of tryptophan and 15 derivatives by Ultra Performance Liquid Chromatography. The gradient composition of the mobile phase and the flow rate were optimized with respect to the resolution of severely overlapping chromatographic peaks and the total run time. Two different stationary phases were evaluated (hybrid silica and a solid-core-based C 18 column). The methods were validated and a suitable sensitivity was found for all compounds in the concentration range 1-100μgL -1 (R 2 >0.999). High levels of repeatability and intermediate precision (CV less than 0.25% and 1.7% on average for the retention time and the signal area, respectively) were obtained. The new method was applied to the determination tryptophan and its derivatives in black pigmented glutinous and non-glutinous rice grain samples. Copyright © 2016 Elsevier Ltd. All rights reserved.

A New Approach for Optimal Sizing of Standalone Photovoltaic Systems

OpenAIRE

Khatib, Tamer; Mohamed, Azah; Sopian, K.; Mahmoud, M.

2012-01-01

This paper presents a new method for determining the optimal sizing of standalone photovoltaic (PV) system in terms of optimal sizing of PV array and battery storage. A standalone PV system energy flow is first analysed, and the MATLAB fitting tool is used to fit the resultant sizing curves in order to derive general formulas for optimal sizing of PV array and battery. In deriving the formulas for optimal sizing of PV array and battery, the data considered are based on five sites in Malaysia...

On the formulation and numerical simulation of distributed-order fractional optimal control problems

Science.gov (United States)

Zaky, M. A.; Machado, J. A. Tenreiro

2017-11-01

In a fractional optimal control problem, the integer order derivative is replaced by a fractional order derivative. The fractional derivative embeds implicitly the time delays in an optimal control process. The order of the fractional derivative can be distributed over the unit interval, to capture delays of distinct sources. The purpose of this paper is twofold. Firstly, we derive the generalized necessary conditions for optimal control problems with dynamics described by ordinary distributed-order fractional differential equations (DFDEs). Secondly, we propose an efficient numerical scheme for solving an unconstrained convex distributed optimal control problem governed by the DFDE. We convert the problem under consideration into an optimal control problem governed by a system of DFDEs, using the pseudo-spectral method and the Jacobi-Gauss-Lobatto (J-G-L) integration formula. Next, we present the numerical solutions for a class of optimal control problems of systems governed by DFDEs. The convergence of the proposed method is graphically analyzed showing that the proposed scheme is a good tool for the simulation of distributed control problems governed by DFDEs.

Simulated Annealing-based Optimal Proportional-Integral-Derivative (PID) Controller Design: A Case Study on Nonlinear Quadcopter Dynamics

Science.gov (United States)

Nemirsky, Kristofer Kevin

In this thesis, the history and evolution of rotor aircraft with simulated annealing-based PID application were reviewed and quadcopter dynamics are presented. The dynamics of a quadcopter were then modeled, analyzed, and linearized. A cascaded loop architecture with PID controllers was used to stabilize the plant dynamics, which was improved upon through the application of simulated annealing (SA). A Simulink model was developed to test the controllers and verify the functionality of the proposed control system design. In addition, the data that the Simulink model provided were compared with flight data to present the validity of derived dynamics as a proper mathematical model representing the true dynamics of the quadcopter system. Then, the SA-based global optimization procedure was applied to obtain optimized PID parameters. It was observed that the tuned gains through the SA algorithm produced a better performing PID controller than the original manually tuned one. Next, we investigated the uncertain dynamics of the quadcopter setup. After adding uncertainty to the gyroscopic effects associated with pitch-and-roll rate dynamics, the controllers were shown to be robust against the added uncertainty. A discussion follows to summarize SA-based algorithm PID controller design and performance outcomes. Lastly, future work on SA application on multi-input-multi-output (MIMO) systems is briefly discussed.

Optimally cloned binary coherent states

Science.gov (United States)

Müller, C. R.; Leuchs, G.; Marquardt, Ch.; Andersen, U. L.

2017-10-01

Binary coherent state alphabets can be represented in a two-dimensional Hilbert space. We capitalize this formal connection between the otherwise distinct domains of qubits and continuous variable states to map binary phase-shift keyed coherent states onto the Bloch sphere and to derive their quantum-optimal clones. We analyze the Wigner function and the cumulants of the clones, and we conclude that optimal cloning of binary coherent states requires a nonlinearity above second order. We propose several practical and near-optimal cloning schemes and compare their cloning fidelity to the optimal cloner.

Optimizing Combinations of Flavonoids Deriving from Astragali Radix in Activating the Regulatory Element of Erythropoietin by a Feedback System Control Scheme

Directory of Open Access Journals (Sweden)

Hui Yu

2013-01-01

Full Text Available Identifying potent drug combination from a herbal mixture is usually quite challenging, due to a large number of possible trials. Using an engineering approach of the feedback system control (FSC scheme, we identified the potential best combinations of four flavonoids, including formononetin, ononin, calycosin, and calycosin-7-O-β-D-glucoside deriving from Astragali Radix (AR; Huangqi, which provided the best biological action at minimal doses. Out of more than one thousand possible combinations, only tens of trials were required to optimize the flavonoid combinations that stimulated a maximal transcriptional activity of hypoxia response element (HRE, a critical regulator for erythropoietin (EPO transcription, in cultured human embryonic kidney fibroblast (HEK293T. By using FSC scheme, 90% of the work and time can be saved, and the optimized flavonoid combinations increased the HRE mediated transcriptional activity by ~3-fold as compared with individual flavonoid, while the amount of flavonoids was reduced by ~10-fold. Our study suggests that the optimized combination of flavonoids may have strong effect in activating the regulatory element of erythropoietin at very low dosage, which may be used as new source of natural hematopoietic agent. The present work also indicates that the FSC scheme is able to serve as an efficient and model-free approach to optimize the drug combination of different ingredients within a herbal decoction.

Optimal conversion of an atomic to a molecular Bose-Einstein condensate

International Nuclear Information System (INIS)

Hornung, Thomas; Gordienko, Sergei; Vivie-Riedle, Regina de; Verhaar, Boudewijn J.

2002-01-01

The work in this article extends the optimal control framework of variational calculus to optimize the conversion of a Bose-Einstein condensate of atoms to one of molecules. It represents the derivation of the closed form optimal control equations for a system governed by a nonlinear Schroedinger equation and its successful application. It was necessary to derive a density matrix formulation of the coupled Gross-Pitaevskii equations to optimize STIRAP-like Raman light fields, to overcome dissipation

Molecular Docking Study on Galantamine Derivatives as Cholinesterase Inhibitors.

Science.gov (United States)

Atanasova, Mariyana; Yordanov, Nikola; Dimitrov, Ivan; Berkov, Strahil; Doytchinova, Irini

2015-06-01

A training set of 22 synthetic galantamine derivatives binding to acetylcholinesterase was docked by GOLD and the protocol was optimized in terms of scoring function, rigidity/flexibility of the binding site, presence/absence of a water molecule inside and radius of the binding site. A moderate correlation was found between the affinities of compounds expressed as pIC50 values and their docking scores. The optimized docking protocol was validated by an external test set of 11 natural galantamine derivatives and the correlation coefficient between the docking scores and the pIC50 values was 0.800. The derived relationship was used to analyze the interactions between galantamine derivatives and AChE. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comments on `A discrete optimal control problem for descriptor systems'

DEFF Research Database (Denmark)

Ravn, Hans

1990-01-01

In the above-mentioned work (see ibid., vol.34, p.177-81 (1989)), necessary and sufficient optimality conditions are derived for a discrete-time optimal problem, as well as other specific cases of implicit and explicit dynamic systems. The commenter corrects a mistake and demonstrates that there ......In the above-mentioned work (see ibid., vol.34, p.177-81 (1989)), necessary and sufficient optimality conditions are derived for a discrete-time optimal problem, as well as other specific cases of implicit and explicit dynamic systems. The commenter corrects a mistake and demonstrates...

On optimal soft-decision demodulation. [in digital communication system

Science.gov (United States)

Lee, L.-N.

1976-01-01

A necessary condition is derived for optimal J-ary coherent demodulation of M-ary (M greater than 2) signals. Optimality is defined as maximality of the symmetric cutoff rate of the resulting discrete memoryless channel. Using a counterexample, it is shown that the condition derived is generally not sufficient for optimality. This condition is employed as the basis for an iterative optimization method to find the optimal demodulator decision regions from an initial 'good guess'. In general, these regions are found to be bounded by hyperplanes in likelihood space; the corresponding regions in signal space are found to have hyperplane asymptotes for the important case of additive white Gaussian noise. Some examples are presented, showing that the regions in signal space bounded by these asymptotic hyperplanes define demodulator decision regions that are virtually optimal.

On the optimal scope of negligence

NARCIS (Netherlands)

Dari-Mattiacci, G.

2005-01-01

This article studies the optimal scope of negligence, considering which of the parties’ precautionary measures should be included in the determination of negligence and which instead should be omitted. The analysis shows that the optimal scope of negligence balances the gains derived from improved

Inflation Aversion and the Optimal Inflation Tax

OpenAIRE

Gaowang Wang; Heng-fu Zou

2011-01-01

The optimal inflation tax is reexamined in the framework of dynamic second best economy populated by individuals with inflation aversion. A simple formula for the optimal inflation rate is derived. Different from the literature, it is shown that if the marginal excess burden of other distorting taxes approaches zero, Friedman's rule for optimum quantity of money is not optimal, and the optimal inflation tax is negative; if the marginal excess burden of other taxes is nonzero, the optimal infl...

Strain and culture medium optimization for production enhancement of prodiginines from marine-derived Streptomyces sp. GQQ-10

Science.gov (United States)

Li, Xueping; Zhang, Guojian; Zhu, Tianjiao; Li, Dehai; Gu, Qianqun

2012-09-01

A mutant (GQQ-M6) of a Sponge-Derived streptomyces sp. GQQ-10 obtained by UV-induced mutation was used for producing prodiginines (PGs). Single factor experiments and orthogonal array design (OAD) methods were employed for medium optimization. In the single factor method, the effects of soluble starch, glucose, soybean flour, yeast extract and sodium acetate on PGs production were investigated individually. In the subsequent OAD experiments, the concentrations of these 5 key nutritional components combined with salinity were further adjusted. The mutant strain GQQ-M6 gave a 2.2-fold higher PGs production than that of the parent strain; OAD experiments offered a PGs yield of 61mg L-1, which was 10 times higher than that of the initial GQQ-10 strain under the original cultivation mode.

Modeling of frequency-domain scalar wave equation with the average-derivative optimal scheme based on a multigrid-preconditioned iterative solver

Science.gov (United States)

Cao, Jian; Chen, Jing-Bo; Dai, Meng-Xue

2018-01-01

An efficient finite-difference frequency-domain modeling of seismic wave propagation relies on the discrete schemes and appropriate solving methods. The average-derivative optimal scheme for the scalar wave modeling is advantageous in terms of the storage saving for the system of linear equations and the flexibility for arbitrary directional sampling intervals. However, using a LU-decomposition-based direct solver to solve its resulting system of linear equations is very costly for both memory and computational requirements. To address this issue, we consider establishing a multigrid-preconditioned BI-CGSTAB iterative solver fit for the average-derivative optimal scheme. The choice of preconditioning matrix and its corresponding multigrid components is made with the help of Fourier spectral analysis and local mode analysis, respectively, which is important for the convergence. Furthermore, we find that for the computation with unequal directional sampling interval, the anisotropic smoothing in the multigrid precondition may affect the convergence rate of this iterative solver. Successful numerical applications of this iterative solver for the homogenous and heterogeneous models in 2D and 3D are presented where the significant reduction of computer memory and the improvement of computational efficiency are demonstrated by comparison with the direct solver. In the numerical experiments, we also show that the unequal directional sampling interval will weaken the advantage of this multigrid-preconditioned iterative solver in the computing speed or, even worse, could reduce its accuracy in some cases, which implies the need for a reasonable control of directional sampling interval in the discretization.

Optimization of rotational radiotherapy treatment planning

International Nuclear Information System (INIS)

Tulovsky, Vladimir; Ringor, Michael; Papiez, Lech

1995-01-01

Purpose: Rotational therapy treatment planning for rotationally symmetric geometry of tumor and healthy tissue provides an important example of testing various approaches to optimizing dose distributions for therapeutic x-ray irradiations. In this article, dose distribution optimization is formulated as a variational problem. This problem is solved analytically and numerically. Methods and Materials: The classical Lagrange method is used to derive equations and inequalities that give necessary conditions for minimizing the mean-square deviation between the ideal dose distribution and the achievable dose distribution. The solution of the resulting integral equation with Cauchy kernel is used to derive analytical formulas for the minimizing irradiation intensity function. Results: The solutions are evaluated numerically and the graphs of the minimizing intensity functions and the corresponding dose distributions are presented. Conclusions: The optimal solutions obtained using the mean-square criterion lead to significant underdosage in some areas of the tumor volume. Possible solutions to this shortcoming are investigated and medically more appropriate criteria for optimization are proposed for future investigations

Optimizing towing processes at airports

OpenAIRE

Du, Jia Yan

2015-01-01

This work addresses the optimization of push-back and towing processes at airports, as an important part of the turnaround process. A vehicle routing based scheduling model is introduced to find a cost optimal assignment of jobs to towing tractors in daily operations. A second model derives an investment strategy to optimize tractor fleet size and mix in the long-run. Column generation heuristics are proposed as solution procedures. The thesis concludes with a case study of a major European ...

Optimal taxation with home production

OpenAIRE

Olovsson, Conny

2014-01-01

Optimal taxes for Europe and the U.S. are derived in a realistically calibrated model in which agents buy consumption goods and services and use home capital and labor to produce household services. The optimal tax rate on services is substantially lower than the tax rate on goods. Specifically, the planner cannot tax home production directly and instead lowers the tax rate on market services to increase the relative price of home production. The optimal tax rate on the return to home capital...

Designing optimal sampling schemes for field visits

CSIR Research Space (South Africa)

Debba, Pravesh

2008-10-01

Full Text Available This is a presentation of a statistical method for deriving optimal spatial sampling schemes. The research focuses on ground verification of minerals derived from hyperspectral data. Spectral angle mapper (SAM) and spectral feature fitting (SFF...

Pareto optimality in infinite horizon linear quadratic differential games

NARCIS (Netherlands)

Reddy, P.V.; Engwerda, J.C.

2013-01-01

In this article we derive conditions for the existence of Pareto optimal solutions for linear quadratic infinite horizon cooperative differential games. First, we present a necessary and sufficient characterization for Pareto optimality which translates to solving a set of constrained optimal

Guided randomness in optimization

CERN Document Server

Clerc, Maurice

2015-01-01

The performance of an algorithm used depends on the GNA. This book focuses on the comparison of optimizers, it defines a stress-outcome approach which can be derived all the classic criteria (median, average, etc.) and other more sophisticated.   Source-codes used for the examples are also presented, this allows a reflection on the ""superfluous chance,"" succinctly explaining why and how the stochastic aspect of optimization could be avoided in some cases.

Applications of automatic differentiation in topology optimization

DEFF Research Database (Denmark)

Nørgaard, Sebastian A.; Sagebaum, Max; Gauger, Nicolas R.

2017-01-01

The goal of this article is to demonstrate the applicability and to discuss the advantages and disadvantages of automatic differentiation in topology optimization. The technique makes it possible to wholly or partially automate the evaluation of derivatives for optimization problems and is demons...

Energy Optimal Path Planning: Integrating Coastal Ocean Modelling with Optimal Control

Science.gov (United States)

Subramani, D. N.; Haley, P. J., Jr.; Lermusiaux, P. F. J.

2016-02-01

A stochastic optimization methodology is formulated for computing energy-optimal paths from among time-optimal paths of autonomous vehicles navigating in a dynamic flow field. To set up the energy optimization, the relative vehicle speed and headings are considered to be stochastic, and new stochastic Dynamically Orthogonal (DO) level-set equations that govern their stochastic time-optimal reachability fronts are derived. Their solution provides the distribution of time-optimal reachability fronts and corresponding distribution of time-optimal paths. An optimization is then performed on the vehicle's energy-time joint distribution to select the energy-optimal paths for each arrival time, among all stochastic time-optimal paths for that arrival time. The accuracy and efficiency of the DO level-set equations for solving the governing stochastic level-set reachability fronts are quantitatively assessed, including comparisons with independent semi-analytical solutions. Energy-optimal missions are studied in wind-driven barotropic quasi-geostrophic double-gyre circulations, and in realistic data-assimilative re-analyses of multiscale coastal ocean flows. The latter re-analyses are obtained from multi-resolution 2-way nested primitive-equation simulations of tidal-to-mesoscale dynamics in the Middle Atlantic Bight and Shelbreak Front region. The effects of tidal currents, strong wind events, coastal jets, and shelfbreak fronts on the energy-optimal paths are illustrated and quantified. Results showcase the opportunities for longer-duration missions that intelligently utilize the ocean environment to save energy, rigorously integrating ocean forecasting with optimal control of autonomous vehicles.

Optimal Wentzell Boundary Control of Parabolic Equations

International Nuclear Information System (INIS)

Luo, Yousong

2017-01-01

This paper deals with a class of optimal control problems governed by an initial-boundary value problem of a parabolic equation. The case of semi-linear boundary control is studied where the control is applied to the system via the Wentzell boundary condition. The differentiability of the state variable with respect to the control is established and hence a necessary condition is derived for the optimal solution in the case of both unconstrained and constrained problems. The condition is also sufficient for the unconstrained convex problems. A second order condition is also derived.

Optimal Wentzell Boundary Control of Parabolic Equations

Energy Technology Data Exchange (ETDEWEB)

Luo, Yousong, E-mail: yousong.luo@rmit.edu.au [RMIT University, School of Mathematical and Geospatial Sciences (Australia)

2017-04-15

This paper deals with a class of optimal control problems governed by an initial-boundary value problem of a parabolic equation. The case of semi-linear boundary control is studied where the control is applied to the system via the Wentzell boundary condition. The differentiability of the state variable with respect to the control is established and hence a necessary condition is derived for the optimal solution in the case of both unconstrained and constrained problems. The condition is also sufficient for the unconstrained convex problems. A second order condition is also derived.

Topological estimation of cytotoxic activity of some anti-HIV agents ...

Indian Academy of Sciences (India)

Unknown

2Research Division, Laxmi Fumigation and Pest Control Pvt. Ltd., 3, Khatipura, Indore 452 007, ... Structural details and cytotoxic activity (pCC50) of the compounds (HEPT analogues) ..... The regression parameters and the quality of corre-.

Optimal Control for the Degenerate Elliptic Logistic Equation

International Nuclear Information System (INIS)

Delgado, M.; Montero, J.A.; Suarez, A.

2002-01-01

We consider the optimal control of harvesting the diffusive degenerate elliptic logistic equation. Under certain assumptions, we prove the existence and uniqueness of an optimal control. Moreover, the optimality system and a characterization of the optimal control are also derived. The sub-supersolution method, the singular eigenvalue problem and differentiability with respect to the positive cone are the techniques used to obtain our results

A New Approach for Optimal Sizing of Standalone Photovoltaic Systems

Directory of Open Access Journals (Sweden)

Tamer Khatib

2012-01-01

Full Text Available This paper presents a new method for determining the optimal sizing of standalone photovoltaic (PV system in terms of optimal sizing of PV array and battery storage. A standalone PV system energy flow is first analysed, and the MATLAB fitting tool is used to fit the resultant sizing curves in order to derive general formulas for optimal sizing of PV array and battery. In deriving the formulas for optimal sizing of PV array and battery, the data considered are based on five sites in Malaysia, which are Kuala Lumpur, Johor Bharu, Ipoh, Kuching, and Alor Setar. Based on the results of the designed example for a PV system installed in Kuala Lumpur, the proposed method gives satisfactory optimal sizing results.

The Theory of Optimal Taxation

DEFF Research Database (Denmark)

Sørensen, Peter Birch

The theory of optimal taxation has often been criticized for being of little practical policy relevance, due to a lack of robust theoretical results. This paper argues that recent advances in optimal tax theory has made that theory easier to apply and may help to explain some current trends...... in international tax policy. Covering the taxation of labour income and capital income as well as indirect taxation, the paper also illustrates how some of the key results in optimal tax theory may be derived in a simple, heuristic manner....

Optimization with Multivalued Mappings Theory, Applications and Algorithms

CERN Document Server

Dempe, Stephan

2006-01-01

Focussing on optimization problems involving multivalued mappings in constraints or as the objective function, this book includes the formulation of optimality conditions using different kinds of generalized derivatives for set-valued mappings, among the other related topics.

On the efficiency of chaos optimization algorithms for global optimization

International Nuclear Information System (INIS)

Yang Dixiong; Li Gang; Cheng Gengdong

2007-01-01

Chaos optimization algorithms as a novel method of global optimization have attracted much attention, which were all based on Logistic map. However, we have noticed that the probability density function of the chaotic sequences derived from Logistic map is a Chebyshev-type one, which may affect the global searching capacity and computational efficiency of chaos optimization algorithms considerably. Considering the statistical property of the chaotic sequences of Logistic map and Kent map, the improved hybrid chaos-BFGS optimization algorithm and the Kent map based hybrid chaos-BFGS algorithm are proposed. Five typical nonlinear functions with multimodal characteristic are tested to compare the performance of five hybrid optimization algorithms, which are the conventional Logistic map based chaos-BFGS algorithm, improved Logistic map based chaos-BFGS algorithm, Kent map based chaos-BFGS algorithm, Monte Carlo-BFGS algorithm, mesh-BFGS algorithm. The computational performance of the five algorithms is compared, and the numerical results make us question the high efficiency of the chaos optimization algorithms claimed in some references. It is concluded that the efficiency of the hybrid optimization algorithms is influenced by the statistical property of chaotic/stochastic sequences generated from chaotic/stochastic algorithms, and the location of the global optimum of nonlinear functions. In addition, it is inappropriate to advocate the high efficiency of the global optimization algorithms only depending on several numerical examples of low-dimensional functions

Optimal Hedging with the Vector Autoregressive Model

NARCIS (Netherlands)

L. Gatarek (Lukasz); S.G. Johansen (Soren)

2014-01-01

markdownabstract__Abstract__ We derive the optimal hedging ratios for a portfolio of assets driven by a Cointegrated Vector Autoregressive model with general cointegration rank. Our hedge is optimal in the sense of minimum variance portfolio. We consider a model that allows for the hedges to be

On a linear-quadratic problem with Caputo derivative

Directory of Open Access Journals (Sweden)

Dariusz Idczak

2016-01-01

Full Text Available In this paper, we study a linear-quadratic optimal control problem with a fractional control system containing a Caputo derivative of unknown function. First, we derive the formulas for the differential and gradient of the cost functional under given constraints. Next, we prove an existence result and derive a maximum principle. Finally, we describe the gradient and projection of the gradient methods for the problem under consideration.

Linearly constrained minimax optimization

DEFF Research Database (Denmark)

Madsen, Kaj; Schjær-Jacobsen, Hans

1978-01-01

We present an algorithm for nonlinear minimax optimization subject to linear equality and inequality constraints which requires first order partial derivatives. The algorithm is based on successive linear approximations to the functions defining the problem. The resulting linear subproblems...

Rapid Optimal Generation Algorithm for Terrain Following Trajectory Based on Optimal Control

Institute of Scientific and Technical Information of China (English)

杨剑影; 张海; 谢邦荣; 尹健

2004-01-01

Based on the optimal control theory, a 3-dimensionnal direct generation algorithm is proposed for anti-ground low altitude penetration tasks under complex terrain. By optimizing the terrain following(TF) objective function,terrain coordinate system, missile dynamic model and control vector, the TF issue is turning into the improved optimal control problem whose mathmatical model is simple and need not solve the second order terrain derivative. Simulation results prove that this method is reasonable and feasible. The TF precision is in the scope from 0.3 m to 3.0 m,and the planning time is less than 30 min. This method have the strongpionts such as rapidness, precision and has great application value.

Optimal design of unit hydrographs using probability distribution and ...

Indian Academy of Sciences (India)

R. Narasimhan (Krishtel eMaging) 1461 1996 Oct 15 13:05:22

optimization formulation is solved using binary-coded genetic algorithms. The number of variables to ... Unit hydrograph; rainfall-runoff; hydrology; genetic algorithms; optimization; probability ..... Application of the model. Data derived from the ...

Optimization of Moving Coil Actuators for Digital Displacement Machines

DEFF Research Database (Denmark)

Nørgård, Christian; Bech, Michael Møller; Roemer, Daniel Beck

2016-01-01

This paper focuses on deriving an optimal moving coil actuator design, used as force pro-ducing element in hydraulic on/off valves for Digital Displacement machines. Different moving coil actuator geometry topologies (permanent magnet placement and magnetiza-tion direction) are optimized for actu......This paper focuses on deriving an optimal moving coil actuator design, used as force pro-ducing element in hydraulic on/off valves for Digital Displacement machines. Different moving coil actuator geometry topologies (permanent magnet placement and magnetiza-tion direction) are optimized...... for actuating annular seat valves in a digital displacement machine. The optimization objectives are to the minimize the actuator power, the valve flow losses and the height of the actuator. Evaluation of the objective function involves static finite element simulation and simulation of an entire operation...... designs requires approximately 20 W on average and may be realized in 20 mm × Ø 22.5 mm (height × diameter) for a 20 kW pressure chamber. The optimization is carried out using the multi-objective Generalized Differential Evolu-tion optimization algorithm GDE3 which successfully handles constrained multi-objective...

Using GIS data and satellite derived irradiance to optimize siting of PV installations in Switzerland

Science.gov (United States)

Kahl, Annelen; Nguyen, Viet-Anh; Bartlett, Stuart; Sossan, Fabrizio; Lehning, Michael

2016-04-01

For a successful distribution strategy of PV installations, it does not suffice to choose the locations with highest annual total irradiance. Attention needs to be given to spatial correlation patterns of insolation to avoid large system-wide variations, which can cause extended deficits in supply or might even damage the electrical network. One alternative goal instead is to seek configurations that provide the smoothest energy production, with the most reliable and predictable supply. Our work investigates several scenarios, each pursuing a different strategy for a future renewable Switzerland without nuclear power. Based on an estimate for necessary installed capacity for solar power [Bartlett, 2015] we first use heuristics to pre-select realistic placements for PV installations. Then we apply optimization methods to find a subset of locations that provides the best possible combined electricity production. For the first part of the selection process, we use a DEM to exclude high elevation zones which would be difficult to access and which are prone to natural hazards. Then we use land surface cover information to find all zones with potential roof area, deemed suitable for installation of solar panels. The optimization employs Principal Component Analysis of satellite derived irradiance data (Surface Incoming Shortwave Radiation (SIS), based on Meteosat Second Generation sensors) to incorporate a spatial aspect into the selection process that does not simply maximize annual total production but rather provides the most robust supply, by combining regions with anti-correlated cloud cover patterns. Depending on the initial assumptions and constraints, the resulting distribution schemes for PV installations vary with respect to required surface area, annual total and lowest short-term production, and illustrate how important it is to clearly define priorities and policies for a future renewable Switzerland.

Quad-rotor flight path energy optimization

Science.gov (United States)

Kemper, Edward

Quad-Rotor unmanned areal vehicles (UAVs) have been a popular area of research and development in the last decade, especially with the advent of affordable microcontrollers like the MSP 430 and the Raspberry Pi. Path-Energy Optimization is an area that is well developed for linear systems. In this thesis, this idea of path-energy optimization is extended to the nonlinear model of the Quad-rotor UAV. The classical optimization technique is adapted to the nonlinear model that is derived for the problem at hand, coming up with a set of partial differential equations and boundary value conditions to solve these equations. Then, different techniques to implement energy optimization algorithms are tested using simulations in Python. First, a purely nonlinear approach is used. This method is shown to be computationally intensive, with no practical solution available in a reasonable amount of time. Second, heuristic techniques to minimize the energy of the flight path are tested, using Ziegler-Nichols' proportional integral derivative (PID) controller tuning technique. Finally, a brute force look-up table based PID controller is used. Simulation results of the heuristic method show that both reliable control of the system and path-energy optimization are achieved in a reasonable amount of time.

Optimal power allocation of a sensor node under different rate constraints

KAUST Repository

Ayala Solares, Jose Roberto; Rezki, Zouheir; Alouini, Mohamed-Slim

2012-01-01

The optimal transmit power of a sensor node while satisfying different rate constraints is derived. First, an optimization problem with an instantaneous transmission rate constraint is addressed. Next, the optimal power is analyzed, but now

Optimal Power Allocation Algorithm for Radar Network Systems Based on Low Probability of Intercept Optimization(in English

Directory of Open Access Journals (Sweden)

Shi Chen-guang

2014-08-01

Full Text Available A novel optimal power allocation algorithm for radar network systems is proposed for Low Probability of Intercept (LPI technology in modern electronic warfare. The algorithm is based on the LPI optimization. First, the Schleher intercept factor for a radar network is derived, and then the Schleher intercept factor is minimized by optimizing the transmission power allocation among netted radars in the network to guarantee target-tracking performance. Furthermore, the Nonlinear Programming Genetic Algorithm (NPGA is used to solve the resulting nonconvex, nonlinear, and constrained optimization problem. Numerical simulation results show the effectiveness of the proposed algorithm.

Simulation of global oceanic upper layers forced at the surface by an optimal bulk formulation derived from multi-campaign measurements.

Science.gov (United States)

Garric, G.; Pirani, A.; Belamari, S.; Caniaux, G.

2006-12-01

order to improve the air/sea interface for the future MERCATOR global ocean operational system, we have implemented the new bulk formulation developed by METEO-FRANCE (French Meteo office) in the MERCATOR 2 degree global ocean-ice coupled model (ORCA2/LIM). A single bulk formulation for the drag, temperature and moisture exchange coefficients is derived from an extended consistent database gathering 10 years of measurements issued from five experiments dedicated to air-sea fluxes estimates (SEMAPHORE, CATCH, FETCH, EQUALANT99 and POMME) in various oceanic basins (from Northern to equatorial Atlantic). The available database (ALBATROS) cover the widest range of atmospheric and oceanic conditions, from very light (0.3 m/s) to very strong (up to 29 m/s) wind speeds, and from unstable to extremely stable atmospheric boundary layer stratification. We have defined a work strategy to test this new formulation in a global oceanic context, by using this multi- campaign bulk formulation to derive air-sea fluxes from base meteorological variables produces by the ECMWF (European Centre for Medium Range and Weather Forecast) atmospheric forecast model, in order to get surface boundary conditions for ORCA2/LIM. The simulated oceanic upper layers forced at the surface by the previous air/sea interface are compared to those forced by the optimal bulk formulation. Consecutively with generally weaker transfer coefficient, the latter formulation reduces the cold bias in the equatorial Pacific and increases the too weak summer sea ice extent in Antarctica. Compared to a recent mixed layer depth (MLD) climatology, the optimal bulk formulation reduces also the too deep simulated MLDs. Comparison with in situ temperature and salinity profiles in different areas allowed us to evaluate the impact of changing the air/sea interface in the vertical structure.

Kinetics and Optimization of Lipophilic Kojic Acid Derivative Synthesis in Polar Aprotic Solvent Using Lipozyme RMIM and Its Rheological Study

Directory of Open Access Journals (Sweden)

Nurazwa Ishak

2018-02-01

Full Text Available The synthesis of kojic acid derivative (KAD from kojic and palmitic acid (C16:0 in the presence of immobilized lipase from Rhizomucor miehei (commercially known as Lipozyme RMIM, was studied using a shake flask system. Kojic acid is a polyfunctional heterocycles that acts as a source of nucleophile in this reaction allowing the formation of a lipophilic KAD. In this study, the source of biocatalyst, Lipozyme RMIM, was derived from the lipase of Rhizomucor miehei immobilized on weak anion exchange macro-porous Duolite ES 562 by the adsorption technique. The effects of solvents, enzyme loading, reaction temperature, and substrate molar ratio on the reaction rate were investigated. In one-factor-at-a-time (OFAT experiments, a high reaction rate (30.6 × 10−3 M·min−1 of KAD synthesis was recorded using acetone, enzyme loading of 1.25% (w/v, reaction time of 12 h, temperature of 50 °C and substrate molar ratio of 5:1. Thereafter, a yield of KAD synthesis was optimized via the response surface methodology (RSM whereby the optimized molar ratio (fatty acid: kojic acid, enzyme loading, reaction temperature and reaction time were 6.74, 1.97% (w/v, 45.9 °C, and 20 h respectively, giving a high yield of KAD (64.47%. This condition was reevaluated in a 0.5 L stirred tank reactor (STR where the agitation effects of two impellers; Rushton turbine (RT and pitch-blade turbine (PBT, were investigated. In the STR, a very high yield of KAD synthesis (84.12% was achieved using RT at 250 rpm, which was higher than the shake flask, thus indicating better mixing quality in STR. In a rheological study, a pseudoplastic behavior of KAD mixture was proposed for potential application in lotion formulation.

Kinetics and Optimization of Lipophilic Kojic Acid Derivative Synthesis in Polar Aprotic Solvent Using Lipozyme RMIM and Its Rheological Study.

Science.gov (United States)

Ishak, Nurazwa; Lajis, Ahmad Firdaus B; Mohamad, Rosfarizan; Ariff, Arbakariya B; Mohamed, Mohd Shamzi; Halim, Murni; Wasoh, Helmi

2018-02-24

The synthesis of kojic acid derivative (KAD) from kojic and palmitic acid (C16:0) in the presence of immobilized lipase from Rhizomucor miehei (commercially known as Lipozyme RMIM), was studied using a shake flask system. Kojic acid is a polyfunctional heterocycles that acts as a source of nucleophile in this reaction allowing the formation of a lipophilic KAD. In this study, the source of biocatalyst, Lipozyme RMIM, was derived from the lipase of Rhizomucor miehei immobilized on weak anion exchange macro-porous Duolite ES 562 by the adsorption technique. The effects of solvents, enzyme loading, reaction temperature, and substrate molar ratio on the reaction rate were investigated. In one-factor-at-a-time (OFAT) experiments, a high reaction rate (30.6 × 10 -3 M·min -1 ) of KAD synthesis was recorded using acetone, enzyme loading of 1.25% ( w / v ), reaction time of 12 h, temperature of 50 °C and substrate molar ratio of 5:1. Thereafter, a yield of KAD synthesis was optimized via the response surface methodology (RSM) whereby the optimized molar ratio (fatty acid: kojic acid), enzyme loading, reaction temperature and reaction time were 6.74, 1.97% ( w / v ), 45.9 °C, and 20 h respectively, giving a high yield of KAD (64.47%). This condition was reevaluated in a 0.5 L stirred tank reactor (STR) where the agitation effects of two impellers; Rushton turbine (RT) and pitch-blade turbine (PBT), were investigated. In the STR, a very high yield of KAD synthesis (84.12%) was achieved using RT at 250 rpm, which was higher than the shake flask, thus indicating better mixing quality in STR. In a rheological study, a pseudoplastic behavior of KAD mixture was proposed for potential application in lotion formulation.

Deterministic global optimization an introduction to the diagonal approach

CERN Document Server

Sergeyev, Yaroslav D

2017-01-01

This book begins with a concentrated introduction into deterministic global optimization and moves forward to present new original results from the authors who are well known experts in the field. Multiextremal continuous problems that have an unknown structure with Lipschitz objective functions and functions having the first Lipschitz derivatives defined over hyperintervals are examined. A class of algorithms using several Lipschitz constants is introduced which has its origins in the DIRECT (DIviding RECTangles) method. This new class is based on an efficient strategy that is applied for the search domain partitioning. In addition a survey on derivative free methods and methods using the first derivatives is given for both one-dimensional and multi-dimensional cases. Non-smooth and smooth minorants and acceleration techniques that can speed up several classes of global optimization methods with examples of applications and problems arising in numerical testing of global optimization algorithms are discussed...

Practical methods of optimization

CERN Document Server

Fletcher, R

2013-01-01

Fully describes optimization methods that are currently most valuable in solving real-life problems. Since optimization has applications in almost every branch of science and technology, the text emphasizes their practical aspects in conjunction with the heuristics useful in making them perform more reliably and efficiently. To this end, it presents comparative numerical studies to give readers a feel for possibile applications and to illustrate the problems in assessing evidence. Also provides theoretical background which provides insights into how methods are derived. This edition offers rev

Energy-Efficient Optimization for HARQ Schemes over Time-Correlated Fading Channels

KAUST Repository

Shi, Zheng; Ma, Shaodan; Yang, Guanghua; Alouini, Mohamed-Slim

2018-01-01

in the optimization, which further differentiates this work from prior ones. Using a unified expression of asymptotic outage probabilities, optimal transmission powers and optimal rate are derived in closed-forms to maximize the energy efficiency while satisfying

Optimal design of NPC and Active-NPC transformerless PV inverters

DEFF Research Database (Denmark)

Saridakis, Stefanos; Koutroulis, Eftichios; Blaabjerg, Frede

2012-01-01

Targeting at a cost-effective deployment of grid-connected PhotoVoltaic (PV) systems, this paper presents a new methodology for the optimal design of transformerless PV inverters, which are based on the Neutral Point Clamped (NPC) and the Active-Neutral Point Clamped (ANPC) topologies. The design...... optimization results demonstrate that a different set of optimal values of the PV inverter switching frequency and output filter components are derived for the NPC and ANPC topologies, respectively, as well as for each of the PV inverter installation sites under study. The NPC and ANPC PV inverter structures......, which are derived using the proposed design optimization methodology exhibit lower Levelized Cost Of generated Electricity (LCOE) and manufacturing cost and they are simultaneously capable to inject more energy into the electric grid than the corresponding non-optimized PV inverters. Thus, the proposed...

Reliability Based Optimization of Structural Systems

DEFF Research Database (Denmark)

Sørensen, John Dalsgaard

1987-01-01

The optimization problem to design structural systems such that the reliability is satisfactory during the whole lifetime of the structure is considered in this paper. Some of the quantities modelling the loads and the strength of the structure are modelled as random variables. The reliability...... is estimated using first. order reliability methods ( FORM ). The design problem is formulated as the optimization problem to minimize a given cost function such that the reliability of the single elements satisfies given requirements or such that the systems reliability satisfies a given requirement....... For these optimization problems it is described how a sensitivity analysis can be performed. Next, new optimization procedures to solve the optimization problems are presented. Two of these procedures solve the system reliability based optimization problem sequentially using quasi-analytical derivatives. Finally...

Optimal and sub-optimal post-detection timing estimators for PET

International Nuclear Information System (INIS)

Hero, A.O.; Antoniadis, N.; Clinthorne, N.; Rogers, W.L.; Hutchins, G.D.

1990-01-01

In this paper the authors derive linear and non-linear approximations to the post-detection likelihood function for scintillator interaction time in nuclear particle detection systems. The likelihood function is the optimal statistic for performing detection and estimation of scintillator events and event times. The authors derive the likelihood function approximations from a statistical model for the post-detection waveform which is common in the optical communications literature and takes account of finite detector bandwidth, random gains, and thermal noise. They then present preliminary simulation results for the associated approximate maximum likelihood timing estimators which indicate that significant MSE improvements may be achieved for low post-detection signal-to-noise ratio

Optimal dynamic control of resources in a distributed system

Science.gov (United States)

Shin, Kang G.; Krishna, C. M.; Lee, Yann-Hang

1989-01-01

The authors quantitatively formulate the problem of controlling resources in a distributed system so as to optimize a reward function and derive optimal control strategies using Markov decision theory. The control variables treated are quite general; they could be control decisions related to system configuration, repair, diagnostics, files, or data. Two algorithms for resource control in distributed systems are derived for time-invariant and periodic environments, respectively. A detailed example to demonstrate the power and usefulness of the approach is provided.

Optimizing culture medium composition to improve oligodendrocyte progenitor cell yields in vitro from subventricular zone-derived neural progenitor cell neurospheres.

Directory of Open Access Journals (Sweden)

Paula G Franco

Full Text Available Neural Stem and Progenitor Cells (NSC/NPC are gathering tangible recognition for their uses in cell therapy and cell replacement therapies for human disease, as well as a model system to continue research on overall neural developmental processes in vitro. The Subventricular Zone is one of the largest NSC/NPC niches in the developing mammalian Central Nervous System, and persists through to adulthood. Oligodendrocyte progenitor cell (OPC enriched cultures are usefull tools for in vitro studies as well as for cell replacement therapies for treating demyelination diseases. We used Subventricular Zone-derived NSC/NPC primary cultures from newborn mice and compared the effects of different growth factor combinations on cell proliferation and OPC yield. The Platelet Derived Growth Factor-AA and BB homodimers had a positive and significant impact on OPC generation. Furthermore, heparin addition to the culture media contributed to further increase overall culture yields. The OPC generated by this protocol were able to mature into Myelin Basic Protein-expressing cells and to interact with neurons in an in vitro co-culture system. As a whole, we describe an optimized in vitro method for increasing OPC.

The optimization, kinetics and mechanism of m-cresol degradation via catalytic wet peroxide oxidation with sludge-derived carbon catalyst

Energy Technology Data Exchange (ETDEWEB)

Wang, Yamin [Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023 (China); University of Chinese Academy of Sciences, Beijing 100049 (China); Wei, Huangzhao; Zhao, Ying [Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023 (China); Sun, Wenjing [Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023 (China); University of Chinese Academy of Sciences, Beijing 100049 (China); Sun, Chenglin, E-mail: clsun@dicp.ac.cn [Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian 116023 (China)

2017-03-15

Highlights: • The sludge derived carbon modified with 0 °C acid was used as catalyst in CWPO. • RSM was used to optimize CWPO reaction conditions of m-cresol for the first time. • The kinetic model was disclosed to be correlated with residue target concentration. • The proposed degradation pathways of m-cresol were well proven by DFT method. - Abstract: The sludge-derived carbon catalyst modified with 0 °C HNO{sub 3} solution was tested in catalytic wet peroxide oxidation of m-cresol (100 mg L{sup −1}) with systematical mathematical models and theoretical calculation for the first time. The reaction conditions were optimized by response surface methodology (RSM) as T = 60 °C, initial pH = 3.0, C{sub 0,H2O2(30%)} = 1.20 g L{sup −1} (lower than the stoichiometric amount of 1.80 g L{sup −1}) and C{sub cat} = 0.80 g L{sup −1}, with 96% of m-cresol and 47% of TOC converted after 16 min and 120 min of reaction, respectively, and ξ (mg TOC/g H{sub 2}O{sub 2} fed) = 83.6 mg/g. The end time of the first kinetic period in m-cresol model was disclosed to be correlated with the fixed residue m-cresol concentration of about 33%. Furthermore, the kinetic constants in models of TOC and H{sub 2}O{sub 2} exactly provide convincing proof of three-dimensional response surfaces analysis by RSM, which showed the influence of the interaction between organics and H{sub 2}O{sub 2} on effective H{sub 2}O{sub 2} utilization. The reaction intermediates over time were identified by gas chromatography–mass spectrometer based on kinetics analysis. Four degradation pathways for m-cresol were proposed, of which the possibility and feasibility were well proven by frontier molecule orbital theory and atomic charge distribution via density functional theory method.

Portfolio Optimization under Local-Stochastic Volatility: Coefficient Taylor Series Approximations & Implied Sharpe Ratio

OpenAIRE

Lorig, Matthew; Sircar, Ronnie

2015-01-01

We study the finite horizon Merton portfolio optimization problem in a general local-stochastic volatility setting. Using model coefficient expansion techniques, we derive approximations for the both the value function and the optimal investment strategy. We also analyze the `implied Sharpe ratio' and derive a series approximation for this quantity. The zeroth-order approximation of the value function and optimal investment strategy correspond to those obtained by Merton (1969) when the risky...

Optimal power allocation of a sensor node under different rate constraints

KAUST Repository

Ayala Solares, Jose Roberto

2012-06-01

The optimal transmit power of a sensor node while satisfying different rate constraints is derived. First, an optimization problem with an instantaneous transmission rate constraint is addressed. Next, the optimal power is analyzed, but now with an average transmission rate constraint. The optimal solution for a class of fading channels, in terms of system parameters, is presented and a suboptimal solution is also proposed for an easier, yet efficient, implementation. Insightful asymptotical analysis for both schemes, considering a Rayleigh fading channel, are shown. Finally, the optimal power allocation for a sensor node in a cognitive radio environment is analyzed where an optimum solution for a class of fading channels is again derived. In all cases, numerical results are provided for either Rayleigh or Nakagami-m fading channels. © 2012 IEEE.

Optimal moment determination in POME-copula based hydrometeorological dependence modelling

Science.gov (United States)

Liu, Dengfeng; Wang, Dong; Singh, Vijay P.; Wang, Yuankun; Wu, Jichun; Wang, Lachun; Zou, Xinqing; Chen, Yuanfang; Chen, Xi

2017-07-01

Copula has been commonly applied in multivariate modelling in various fields where marginal distribution inference is a key element. To develop a flexible, unbiased mathematical inference framework in hydrometeorological multivariate applications, the principle of maximum entropy (POME) is being increasingly coupled with copula. However, in previous POME-based studies, determination of optimal moment constraints has generally not been considered. The main contribution of this study is the determination of optimal moments for POME for developing a coupled optimal moment-POME-copula framework to model hydrometeorological multivariate events. In this framework, margins (marginals, or marginal distributions) are derived with the use of POME, subject to optimal moment constraints. Then, various candidate copulas are constructed according to the derived margins, and finally the most probable one is determined, based on goodness-of-fit statistics. This optimal moment-POME-copula framework is applied to model the dependence patterns of three types of hydrometeorological events: (i) single-site streamflow-water level; (ii) multi-site streamflow; and (iii) multi-site precipitation, with data collected from Yichang and Hankou in the Yangtze River basin, China. Results indicate that the optimal-moment POME is more accurate in margin fitting and the corresponding copulas reflect a good statistical performance in correlation simulation. Also, the derived copulas, capturing more patterns which traditional correlation coefficients cannot reflect, provide an efficient way in other applied scenarios concerning hydrometeorological multivariate modelling.

Optimal hedging with the cointegrated vector autoregressive model

DEFF Research Database (Denmark)

Gatarek, Lukasz; Johansen, Søren

We derive the optimal hedging ratios for a portfolio of assets driven by a Coin- tegrated Vector Autoregressive model (CVAR) with general cointegration rank. Our hedge is optimal in the sense of minimum variance portfolio. We consider a model that allows for the hedges to be cointegrated with the...

Using spatial information about recurrence risk for robust optimization of dose-painting prescription functions

International Nuclear Information System (INIS)

Bender, Edward T.

2012-01-01

Purpose: To develop a robust method for deriving dose-painting prescription functions using spatial information about the risk for disease recurrence. Methods: Spatial distributions of radiobiological model parameters are derived from distributions of recurrence risk after uniform irradiation. These model parameters are then used to derive optimal dose-painting prescription functions given a constant mean biologically effective dose. Results: An estimate for the optimal dose distribution can be derived based on spatial information about recurrence risk. Dose painting based on imaging markers that are moderately or poorly correlated with recurrence risk are predicted to potentially result in inferior disease control when compared the same mean biologically effective dose delivered uniformly. A robust optimization approach may partially mitigate this issue. Conclusions: The methods described here can be used to derive an estimate for a robust, patient-specific prescription function for use in dose painting. Two approximate scaling relationships were observed: First, the optimal choice for the maximum dose differential when using either a linear or two-compartment prescription function is proportional to R, where R is the Pearson correlation coefficient between a given imaging marker and recurrence risk after uniform irradiation. Second, the predicted maximum possible gain in tumor control probability for any robust optimization technique is nearly proportional to the square of R.

Ecological optimization for generalized irreversible Carnot refrigerators

International Nuclear Information System (INIS)

Chen Lingen; Zhu Xiaoqin; Sun Fengrui; Wu Chih

2005-01-01

The optimal ecological performance of a Newton's law generalized irreversible Carnot refrigerator with the losses of heat resistance, heat leakage and internal irreversibility is derived by taking an ecological optimization criterion as the objective, which consists of maximizing a function representing the best compromise between the exergy output rate and exergy loss rate (entropy production rate) of the refrigerator. Numerical examples are given to show the effects of heat leakage and internal irreversibility on the optimal performance of generalized irreversible refrigerators

Correlation risk and optimal portfolio choice

OpenAIRE

Buraschi, Andrea; Porchia, Paolo; Trojani, Fabio

2010-01-01

We develop a new framework for multivariate intertemporal portfolio choice that allows us to derive optimal portfolio implications for economies in which the degree of correlation across industries, countries, or asset classes is stochastic. Optimal portfolios include distinct hedging components against both stochastic volatility and correlation risk. We find that the hedging demand is typically larger than in univariate models, and it includes an economically significant covariance hedging...

MEAN OF MEDIAN ABSOLUTE DERIVATION TECHNIQUE MEAN ...

African Journals Online (AJOL)

eobe

development of mean of median absolute derivation technique based on the based on the based on .... of noise mean to estimate the speckle noise variance. Noise mean property ..... Foraging Optimization,” International Journal of. Advanced ...

Optimal Stochastic Advertising Strategies for the U.S. Beef Industry

OpenAIRE

Kun C. Lee; Stanley Schraufnagel; Earl O. Heady

1982-01-01

An important decision variable in the promotional strategy for the beef sector is the optimal level of advertising expenditures over time. Optimal stochastic and deterministic advertising expenditures are derived for the U.S. beef industry for the period `1966 through 1980. They are compared with historical levels and gains realized by optimal advertising strategies are measured. Finally, the optimal advertising expenditures in the future are forecasted.

Optimal Long-Term Financial Contracting

OpenAIRE

Peter M. DeMarzo; Michael J. Fishman

2007-01-01

We develop an agency model of financial contracting. We derive long-term debt, a line of credit, and equity as optimal securities, capturing the debt coupon and maturity; the interest rate and limits on the credit line; inside versus outside equity; dividend policy; and capital structure dynamics. The optimal debt-equity ratio is history dependent, but debt and credit line terms are independent of the amount financed and, in some cases, the severity of the agency problem. In our model, the ag...

Post Pareto optimization-A case

Science.gov (United States)

Popov, Stoyan; Baeva, Silvia; Marinova, Daniela

2017-12-01

Simulation performance may be evaluated according to multiple quality measures that are in competition and their simultaneous consideration poses a conflict. In the current study we propose a practical framework for investigating such simulation performance criteria, exploring the inherent conflicts amongst them and identifying the best available tradeoffs, based upon multi-objective Pareto optimization. This approach necessitates the rigorous derivation of performance criteria to serve as objective functions and undergo vector optimization. We demonstrate the effectiveness of our proposed approach by applying it with multiple stochastic quality measures. We formulate performance criteria of this use-case, pose an optimization problem, and solve it by means of a simulation-based Pareto approach. Upon attainment of the underlying Pareto Frontier, we analyze it and prescribe preference-dependent configurations for the optimal simulation training.

ON THE DERIVATIVE OF SMOOTH MEANINGFUL FUNCTIONS

Directory of Open Access Journals (Sweden)

Sanjo Zlobec

2011-02-01

Full Text Available The derivative of a function f in n variables at a point x* is one of the most important tools in mathematical modelling. If this object exists, it is represented by the row n-tuple f(x* = [∂f/∂xi(x*] called the gradient of f at x*, abbreviated: “the gradient”. The evaluation of f(x* is usually done in two stages, first by calculating the n partials and then their values at x = x*. In this talk we give an alternative approach. We show that one can characterize the gradient without differentiation! The idea is to fix an arbitrary row n-tuple G and answer the following question: What is a necessary and sufficient condition such that G is the gradient of a given f at a given x*? The answer is given after adjusting the quadratic envelope property introduced in [3]. We work with smooth, i.e., continuously differentiable, functions with a Lipschitz derivative on a compact convex set with a non-empty interior. Working with this class of functions is not a serious restriction. In fact, loosely speaking, “almost all” smooth meaningful functions used in modelling of real life situations are expected to have a bounded “acceleration” hence they belong to this class. In particular, the class contains all twice differentiable functions [1]. An important property of the functions from this class is that every f can be represented as the difference of some convex function and a convex quadratic function. This decomposition was used in [3] to characterize the zero derivative points. There we obtained reformulations and augmentations of some well known classic results on optimality such as Fermats extreme value theorem (known from high school and the Lagrange multiplier theorem from calculus [2, 3]. In this talk we extend the results on zero derivative points to characterize the relation G = f(x*, where G is an arbitrary n-tuple. Some special cases: If G = O, we recover the results on zero derivative points. For functions of a single

Chromatographic-mass spectrometric analysis of ethanol extract of ...

African Journals Online (AJOL)

Purpose: This study analyzes the chemical composition of ethanol root extracts of Maesa perlaria var. formosana by .... obtained over a scanning range of 50 to 550 amu at 2 scans/s. .... 142.53 (2,2,6-Trimethyl-bicyclo[4.1.0]hept-1-yl)-methanol.

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.

Optimal energy management strategy for battery powered electric vehicles

International Nuclear Information System (INIS)

Xi, Jiaqi; Li, Mian; Xu, Min

2014-01-01

Highlights: • The power usage for battery-powered electrical vehicles with in-wheel motors is maximized. • The battery and motor dynamics are examined emphasized on the power conversion and utilization. • The optimal control strategy is derived and verified by simulations. • An analytic expression of the optimal operating point is obtained. - Abstract: Due to limited energy density of batteries, energy management has always played a critical role in improving the overall energy efficiency of electric vehicles. In this paper, a key issue within the energy management problem will be carefully tackled, i.e., maximizing the power usage of batteries for battery-powered electrical vehicles with in-wheel motors. To this end, the battery and motor dynamics will be thoroughly examined with particular emphasis on the power conversion and power utilization. The optimal control strategy will then be derived based on the analysis. One significant contribution of this work is that an analytic expression for the optimal operating point in terms of the component and environment parameters can be obtained. Owing to this finding, the derived control strategy is also rendered a simple structure for real-time implementation. Simulation results demonstrate that the proposed strategy works both adaptively and robustly under different driving scenarios

Optimal conversion of an atomic to a molecular Bose-Einstein condensate

NARCIS (Netherlands)

Hornung, T.; Gordienko, S.; Vivie-Riedle, de R.; Verhaar, B.J.

2002-01-01

The work in this article extends the optimal control framework of variational calculus to optimize the conversion of a Bose-Einstein condensate of atoms to one of molecules. It represents the derivation of the closed form optimal control equations for a system governed by a nonlinear Schrödinger

An optimal U.S. biodiesel fuel subsidy

International Nuclear Information System (INIS)

Wu Huiting; Colson, Gregory; Escalante, Cesar; Wetzstein, Michael

2012-01-01

Enhanced environmental quality, fuel security, and economic development, along with reduced prices of blended diesel, are often used as justifications for a U.S. federal excise tax exemption on biodiesel fuels. However, the possible effect of increased overall consumption of fuel in response to lower total prices, mitigating the environmental and fuel security benefits, are generally not considered. Taking this price response into account, the optimal U.S biodiesel subsidy is derived. Estimated values of the optimal subsidy are close to the recently expired subsidy, revealing the subsidy's environmental and security benefits. However, further positive environmental and security benefits from the biodiesel tax-exemption subsidy may be obtained if the subsidy is combined with a federal excise tax on petroleum diesel. - Highlights: ► Taking price response into account, the optimal theoretical U.S biodiesel subsidy is derived. ► Estimated values of the optimal subsidy are close to the recently expired subsidy, revealing the subsidy's environmental and security benefits. ► Further positive environmental and security benefits from the biodiesel tax-exemption subsidy may be obtained if the subsidy is combined with a federal excise tax on petroleum diesel.

Portfolio Optimization with Stochastic Dividends and Stochastic Volatility

Science.gov (United States)

Varga, Katherine Yvonne

2015-01-01

We consider an optimal investment-consumption portfolio optimization model in which an investor receives stochastic dividends. As a first problem, we allow the drift of stock price to be a bounded function. Next, we consider a stochastic volatility model. In each problem, we use the dynamic programming method to derive the Hamilton-Jacobi-Bellman…

Pre-ejection period by radial artery tonometry supplements echo doppler findings during biventricular pacemaker optimization

Directory of Open Access Journals (Sweden)

Qamruddin Salima

2011-07-01

Full Text Available Abstract Background Biventricular (Biv pacemaker echo optimization has been shown to improve cardiac output however is not routinely used due to its complexity. We investigated the role of a simple method involving computerized pre-ejection time (PEP assessment by radial artery tonometry in guiding Biv pacemaker optimization. Methods Blinded echo and radial artery tonometry were performed simultaneously in 37 patients, age 69.1 ± 12.8 years, left ventricular (LV ejection fraction (EF 33 ± 10%, during Biv pacemaker optimization. Effect of optimization on echo derived velocity time integral (VTI, ejection time (ET, myocardial performance index (MPI, radial artery tonometry derived PEP and echo-radial artery tonometry derived PEP/VTI and PEP/ET indices was evaluated. Results Significant improvement post optimization was achieved in LV ET (286.9 ± 37.3 to 299 ± 34.6 ms, p Conclusion An acute shortening of PEP by radial artery tonometry occurs post Biv pacemaker optimization and correlates with improvement in hemodynamics by echo Doppler and may provide a cost-efficient approach to assist with Biv pacemaker echo optimization.

Generalized massive optimal data compression

Science.gov (United States)

Alsing, Justin; Wandelt, Benjamin

2018-05-01

In this paper, we provide a general procedure for optimally compressing N data down to n summary statistics, where n is equal to the number of parameters of interest. We show that compression to the score function - the gradient of the log-likelihood with respect to the parameters - yields n compressed statistics that are optimal in the sense that they preserve the Fisher information content of the data. Our method generalizes earlier work on linear Karhunen-Loéve compression for Gaussian data whilst recovering both lossless linear compression and quadratic estimation as special cases when they are optimal. We give a unified treatment that also includes the general non-Gaussian case as long as mild regularity conditions are satisfied, producing optimal non-linear summary statistics when appropriate. As a worked example, we derive explicitly the n optimal compressed statistics for Gaussian data in the general case where both the mean and covariance depend on the parameters.

Influence of cellulose derivative and ethylene glycol on optimization of lornoxicam transdermal formulation.

Science.gov (United States)

Shahzad, Yasser; Khan, Qalandar; Hussain, Talib; Shah, Syed Nisar Hussain

2013-10-01

Lornoxicam containing topically applied lotions were formulated and optimized with the aim to deliver it transdermally. The formulated lotions were evaluated for pH, viscosity and in vitro permeation studies through silicone membrane using Franz diffusion cells. Data were fitted to linear, quadratic and cubic models and best fit model was selected to investigate the influence of variables, namely hydroxypropyl methylcellulose (HPMC) and ethylene glycol (EG) on permeation of lornoxicam from topically applied lotion formulations. The best fit quadratic model revealed that low level of HPMC and intermediate level of EG in the formulation was optimum for enhancing the drug flux across silicone membrane. FT-IR analysis confirmed absence of drug-polymer interactions. Selected optimized lotion formulation was then subjected to accelerated stability testing, sensatory perception testing and in vitro permeation across rabbit skin. The drug flux from the optimized lotion across rabbit skin was significantly better that that from the control formulation. Furthermore, sensatory perception test rated a higher acceptability while lotion was stable over stability testing period. Therefore, use of Box-Wilson statistical design successfully elaborated the influence of formulation variables on permeation of lornoxicam form topical formulations, thus, helped in optimization of the lotion formulation. Copyright © 2013 Elsevier B.V. All rights reserved.

Optimal management of non-Markovian biological populations

Science.gov (United States)

Williams, B.K.

2007-01-01

Wildlife populations typically are described by Markovian models, with population dynamics influenced at each point in time by current but not previous population levels. Considerable work has been done on identifying optimal management strategies under the Markovian assumption. In this paper we generalize this work to non-Markovian systems, for which population responses to management are influenced by lagged as well as current status and/or controls. We use the maximum principle of optimal control theory to derive conditions for the optimal management such a system, and illustrate the effects of lags on the structure of optimal habitat strategies for a predator-prey system.

Portfolio Optimization and Mortgage Choice

Directory of Open Access Journals (Sweden)

Maj-Britt Nordfang

2017-01-01

Full Text Available This paper studies the optimal mortgage choice of an investor in a simple bond market with a stochastic interest rate and access to term life insurance. The study is based on advances in stochastic control theory, which provides analytical solutions to portfolio problems with a stochastic interest rate. We derive the optimal portfolio of a mortgagor in a simple framework and formulate stylized versions of mortgage products offered in the market today. This allows us to analyze the optimal investment strategy in terms of optimal mortgage choice. We conclude that certain extreme investors optimally choose either a traditional fixed rate mortgage or an adjustable rate mortgage, while investors with moderate risk aversion and income prefer a mix of the two. By matching specific investor characteristics to existing mortgage products, our study provides a better understanding of the complex and yet restricted mortgage choice faced by many household investors. In addition, the simple analytical framework enables a detailed analysis of how changes to market, income and preference parameters affect the optimal mortgage choice.

Statistical identifiability and convergence evaluation for nonlinear pharmacokinetic models with particle swarm optimization.

Science.gov (United States)

Kim, Seongho; Li, Lang

2014-02-01

The statistical identifiability of nonlinear pharmacokinetic (PK) models with the Michaelis-Menten (MM) kinetic equation is considered using a global optimization approach, which is particle swarm optimization (PSO). If a model is statistically non-identifiable, the conventional derivative-based estimation approach is often terminated earlier without converging, due to the singularity. To circumvent this difficulty, we develop a derivative-free global optimization algorithm by combining PSO with a derivative-free local optimization algorithm to improve the rate of convergence of PSO. We further propose an efficient approach to not only checking the convergence of estimation but also detecting the identifiability of nonlinear PK models. PK simulation studies demonstrate that the convergence and identifiability of the PK model can be detected efficiently through the proposed approach. The proposed approach is then applied to clinical PK data along with a two-compartmental model. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Inequality and Optimal Redistributive Tax and Transfer Policies

OpenAIRE

Howell H Zee

1999-01-01

This paper explores the revenue-raising aspect of progressive taxation and derives, on the basis of a simple model, the optimal degree of tax progressivity where the tax revenue is used exclusively to finance (perfectly) targeted transfers to the poor. The paper shows that not only would it be optimal to finance the targeted transfers with progressive taxation, but that the optimal progressivity increases unambiguously with growing income inequality. This conclusion holds up under different a...

Optimal swimming of a sheet.

Science.gov (United States)

Montenegro-Johnson, Thomas D; Lauga, Eric

2014-06-01

Propulsion at microscopic scales is often achieved through propagating traveling waves along hairlike organelles called flagella. Taylor's two-dimensional swimming sheet model is frequently used to provide insight into problems of flagellar propulsion. We derive numerically the large-amplitude wave form of the two-dimensional swimming sheet that yields optimum hydrodynamic efficiency: the ratio of the squared swimming speed to the rate-of-working of the sheet against the fluid. Using the boundary element method, we show that the optimal wave form is a front-back symmetric regularized cusp that is 25% more efficient than the optimal sine wave. This optimal two-dimensional shape is smooth, qualitatively different from the kinked form of Lighthill's optimal three-dimensional flagellum, not predicted by small-amplitude theory, and different from the smooth circular-arc-like shape of active elastic filaments.

Optimal quadrature rules for odd-degree spline spaces and their application to tensor-product-based isogeometric analysis

KAUST Repository

Barton, Michael

2016-03-14

We introduce optimal quadrature rules for spline spaces that are frequently used in Galerkin discretizations to build mass and stiffness matrices. Using the homotopy continuation concept (Bartoň and Calo, 2016) that transforms optimal quadrature rules from source spaces to target spaces, we derive optimal rules for splines defined on finite domains. Starting with the classical Gaussian quadrature for polynomials, which is an optimal rule for a discontinuous odd-degree space, we derive rules for target spaces of higher continuity. We further show how the homotopy methodology handles cases where the source and target rules require different numbers of optimal quadrature points. We demonstrate it by deriving optimal rules for various odd-degree spline spaces, particularly with non-uniform knot sequences and non-uniform multiplicities. We also discuss convergence of our rules to their asymptotic counterparts, that is, the analogues of the midpoint rule of Hughes et al. (2010), that are exact and optimal for infinite domains. For spaces of low continuities, we numerically show that the derived rules quickly converge to their asymptotic counterparts as the weights and nodes of a few boundary elements differ from the asymptotic values.

Optimal quadrature rules for odd-degree spline spaces and their application to tensor-product-based isogeometric analysis

KAUST Repository

Barton, Michael; Calo, Victor M.

2016-01-01

We introduce optimal quadrature rules for spline spaces that are frequently used in Galerkin discretizations to build mass and stiffness matrices. Using the homotopy continuation concept (Bartoň and Calo, 2016) that transforms optimal quadrature rules from source spaces to target spaces, we derive optimal rules for splines defined on finite domains. Starting with the classical Gaussian quadrature for polynomials, which is an optimal rule for a discontinuous odd-degree space, we derive rules for target spaces of higher continuity. We further show how the homotopy methodology handles cases where the source and target rules require different numbers of optimal quadrature points. We demonstrate it by deriving optimal rules for various odd-degree spline spaces, particularly with non-uniform knot sequences and non-uniform multiplicities. We also discuss convergence of our rules to their asymptotic counterparts, that is, the analogues of the midpoint rule of Hughes et al. (2010), that are exact and optimal for infinite domains. For spaces of low continuities, we numerically show that the derived rules quickly converge to their asymptotic counterparts as the weights and nodes of a few boundary elements differ from the asymptotic values.

Optimal Provision of Public Goods

DEFF Research Database (Denmark)

Kreiner, Claus Thustrup; Verdelin, Nicolaj

There currently exist two competing approaches in the literature on the optimal provision of public goods. The standard approach highlights the importance of distortionary taxation and distributional concerns. The new approach neutralizes distributional concerns by adjusting the non-linear income...... tax, and finds that this reinvigorates the simple Samuelson rule when preferences are separable in goods and leisure. We provide a synthesis by demonstrating that both approaches derive from the same basic formula. We further develop the new approach by deriving a general, intuitive formula...

Scalable algorithms for optimal control of stochastic PDEs

KAUST Repository

Ghattas, Omar

2016-01-07

We present methods for the optimal control of systems governed by partial differential equations with infinite-dimensional uncertain parameters. We consider an objective function that involves the mean and variance of the control objective, leading to a risk-averse optimal control formulation. To make the optimal control problem computationally tractable, we employ a local quadratic approximation of the objective with respect to the uncertain parameter. This enables computation of the mean and variance of the control objective analytically. The resulting risk-averse optimization problem is formulated as a PDE-constrained optimization problem with constraints given by the forward and adjoint PDEs for the first and second-order derivatives of the quantity of interest with respect to the uncertain parameter, and with an objective that involves the trace of a covariance-preconditioned Hessian (of the objective with respect to the uncertain parameters) operator. A randomized trace estimator is used to make tractable the trace computation. Adjoint-based techniques are used to derive an expression for the infinite-dimensional gradient of the risk-averse objective function via the Lagrangian, leading to a quasi-Newton method for solution of the optimal control problem. A specific problem of optimal control of a linear elliptic PDE that describes flow of a fluid in a porous medium with uncertain permeability field is considered. We present numerical results to study the consequences of the local quadratic approximation and the efficiency of the method.

Scalable algorithms for optimal control of stochastic PDEs

KAUST Repository

Ghattas, Omar; Alexanderian, Alen; Petra, Noemi; Stadler, Georg

2016-01-01

We present methods for the optimal control of systems governed by partial differential equations with infinite-dimensional uncertain parameters. We consider an objective function that involves the mean and variance of the control objective, leading to a risk-averse optimal control formulation. To make the optimal control problem computationally tractable, we employ a local quadratic approximation of the objective with respect to the uncertain parameter. This enables computation of the mean and variance of the control objective analytically. The resulting risk-averse optimization problem is formulated as a PDE-constrained optimization problem with constraints given by the forward and adjoint PDEs for the first and second-order derivatives of the quantity of interest with respect to the uncertain parameter, and with an objective that involves the trace of a covariance-preconditioned Hessian (of the objective with respect to the uncertain parameters) operator. A randomized trace estimator is used to make tractable the trace computation. Adjoint-based techniques are used to derive an expression for the infinite-dimensional gradient of the risk-averse objective function via the Lagrangian, leading to a quasi-Newton method for solution of the optimal control problem. A specific problem of optimal control of a linear elliptic PDE that describes flow of a fluid in a porous medium with uncertain permeability field is considered. We present numerical results to study the consequences of the local quadratic approximation and the efficiency of the method.

Composition of the Essential Oil of Aristolochia Manshurientsis Kom

Science.gov (United States)

Zhao, Xiuhong; Xin, Guang; Zhao, Lichun; Xiao, Zhigang; Xue, Bai

2018-03-01

This study demonstrated the chemical constituents of the essential oil of Aristolochia manshurientsis Kom and improved the essential oil efficiency by the enzyme-assisted extraction followed by hydrodistillation. The essential oils of Aristolochia manshurientsis Kom acquired by hydrodistillation after the solvent extraction with and without the assistance of cellulase have been investigated by gas chromatography/Mass spectrometry (GC-MS). The predominant constituents of both types of essential oils are camphene, 1,7,7-trimethyl-bicyclo [2.2.1] hept-2-yl acetate, 1,6-dimethyl-4-(1-methylethyl) naphthalene, caryophyllene oxide, borneol, and (-)-Spathulenol. The enzyme-assisted extraction not only increased extracting efficiency of the essential oil from 4.93% to 9.36%, but also facilitated the extraction of additional eight compounds such as 2-methano(-6,6-dimethyl) bicycle [3.1.1] hept-2-ene, (+)--terpineol and 1-propyl-3-(propen-1-yl) adamantane, which were not identified from the non-enzyme extraction sample.

Self-consistent adjoint analysis for topology optimization of electromagnetic waves

Science.gov (United States)

Deng, Yongbo; Korvink, Jan G.

2018-05-01

In topology optimization of electromagnetic waves, the Gâteaux differentiability of the conjugate operator to the complex field variable results in the complexity of the adjoint sensitivity, which evolves the original real-valued design variable to be complex during the iterative solution procedure. Therefore, the self-inconsistency of the adjoint sensitivity is presented. To enforce the self-consistency, the real part operator has been used to extract the real part of the sensitivity to keep the real-value property of the design variable. However, this enforced self-consistency can cause the problem that the derived structural topology has unreasonable dependence on the phase of the incident wave. To solve this problem, this article focuses on the self-consistent adjoint analysis of the topology optimization problems for electromagnetic waves. This self-consistent adjoint analysis is implemented by splitting the complex variables of the wave equations into the corresponding real parts and imaginary parts, sequentially substituting the split complex variables into the wave equations with deriving the coupled equations equivalent to the original wave equations, where the infinite free space is truncated by the perfectly matched layers. Then, the topology optimization problems of electromagnetic waves are transformed into the forms defined on real functional spaces instead of complex functional spaces; the adjoint analysis of the topology optimization problems is implemented on real functional spaces with removing the variational of the conjugate operator; the self-consistent adjoint sensitivity is derived, and the phase-dependence problem is avoided for the derived structural topology. Several numerical examples are implemented to demonstrate the robustness of the derived self-consistent adjoint analysis.

Thermodynamic metrics and optimal paths.

Science.gov (United States)

Sivak, David A; Crooks, Gavin E

2012-05-11

A fundamental problem in modern thermodynamics is how a molecular-scale machine performs useful work, while operating away from thermal equilibrium without excessive dissipation. To this end, we derive a friction tensor that induces a Riemannian manifold on the space of thermodynamic states. Within the linear-response regime, this metric structure controls the dissipation of finite-time transformations, and bestows optimal protocols with many useful properties. We discuss the connection to the existing thermodynamic length formalism, and demonstrate the utility of this metric by solving for optimal control parameter protocols in a simple nonequilibrium model.

Thermodynamics of Gas Turbine Cycles with Analytic Derivatives in OpenMDAO

Science.gov (United States)

Gray, Justin; Chin, Jeffrey; Hearn, Tristan; Hendricks, Eric; Lavelle, Thomas; Martins, Joaquim R. R. A.

2016-01-01

A new equilibrium thermodynamics analysis tool was built based on the CEA method using the OpenMDAO framework. The new tool provides forward and adjoint analytic derivatives for use with gradient based optimization algorithms. The new tool was validated against the original CEA code to ensure an accurate analysis and the analytic derivatives were validated against finite-difference approximations. Performance comparisons between analytic and finite difference methods showed a significant speed advantage for the analytic methods. To further test the new analysis tool, a sample optimization was performed to find the optimal air-fuel equivalence ratio, , maximizing combustion temperature for a range of different pressures. Collectively, the results demonstrate the viability of the new tool to serve as the thermodynamic backbone for future work on a full propulsion modeling tool.

Optimal diversification of the securities portfolio

Directory of Open Access Journals (Sweden)

Валентина Михайловна Андриенко

2016-09-01

Full Text Available The article deals with problems of the theory and methods of forming the optimal portfolio of financial markets. The analytical review of methods in their historical development is given. Recommendations on the use of a particular method depends on the specific conditions are formulated. The classical and alternative methods are considered. The main attention is paid to the analysis of the investment portfolio of derivative securities in B/S-market modelThe article deals with problems of the theory and methods of forming the optimal portfolio of financial markets. The analytical review of methods in their historical development is given. Recommendations on the use of a particular method depends on the specific conditions are formulated. The classical and alternative methods are considered. The main attention is paid to the analysis of the investment portfolio of derivative securities in -market model

Galerkin approximations of nonlinear optimal control problems in Hilbert spaces

Directory of Open Access Journals (Sweden)

Mickael D. Chekroun

2017-07-01

Full Text Available Nonlinear optimal control problems in Hilbert spaces are considered for which we derive approximation theorems for Galerkin approximations. Approximation theorems are available in the literature. The originality of our approach relies on the identification of a set of natural assumptions that allows us to deal with a broad class of nonlinear evolution equations and cost functionals for which we derive convergence of the value functions associated with the optimal control problem of the Galerkin approximations. This convergence result holds for a broad class of nonlinear control strategies as well. In particular, we show that the framework applies to the optimal control of semilinear heat equations posed on a general compact manifold without boundary. The framework is then shown to apply to geoengineering and mitigation of greenhouse gas emissions formulated here in terms of optimal control of energy balance climate models posed on the sphere $\\mathbb{S}^2$.

Optimal Robust Fault Detection for Linear Discrete Time Systems

Directory of Open Access Journals (Sweden)

Nike Liu

2008-01-01

Full Text Available This paper considers robust fault-detection problems for linear discrete time systems. It is shown that the optimal robust detection filters for several well-recognized robust fault-detection problems, such as ℋ−/ℋ∞, ℋ2/ℋ∞, and ℋ∞/ℋ∞ problems, are the same and can be obtained by solving a standard algebraic Riccati equation. Optimal filters are also derived for many other optimization criteria and it is shown that some well-studied and seeming-sensible optimization criteria for fault-detection filter design could lead to (optimal but useless fault-detection filters.

Second-order Optimality Conditions for Optimal Control of the Primitive Equations of the Ocean with Periodic Inputs

International Nuclear Information System (INIS)

Tachim Medjo, T.

2011-01-01

We investigate in this article the Pontryagin's maximum principle for control problem associated with the primitive equations (PEs) of the ocean with periodic inputs. We also derive a second-order sufficient condition for optimality. This work is closely related to Wang (SIAM J. Control Optim. 41(2):583-606, 2002) and He (Acta Math. Sci. Ser. B Engl. Ed. 26(4):729-734, 2006), in which the authors proved similar results for the three-dimensional Navier-Stokes (NS) systems.

Dynamical System Approaches to Combinatorial Optimization

DEFF Research Database (Denmark)

Starke, Jens

2013-01-01

of large times as an asymptotically stable point of the dynamics. The obtained solutions are often not globally optimal but good approximations of it. Dynamical system and neural network approaches are appropriate methods for distributed and parallel processing. Because of the parallelization......Several dynamical system approaches to combinatorial optimization problems are described and compared. These include dynamical systems derived from penalty methods; the approach of Hopfield and Tank; self-organizing maps, that is, Kohonen networks; coupled selection equations; and hybrid methods...... thereof can be used as models for many industrial problems like manufacturing planning and optimization of flexible manufacturing systems. This is illustrated for an example in distributed robotic systems....

Auditory-like filterbank: An optimal speech processor for efficient ...

Indian Academy of Sciences (India)

The transmitter and the receiver in a communication system have to be designed optimally with respect to one another to ensure reliable and efficient communication. Following this principle, we derive an optimal filterbank for processing speech signal in the listener's auditory system (receiver), so that maximum information ...

Constrained Dynamic Optimality and Binomial Terminal Wealth

DEFF Research Database (Denmark)

Pedersen, J. L.; Peskir, G.

2018-01-01

with interest rate $r \\in {R}$). Letting $P_{t,x}$ denote a probability measure under which $X^u$ takes value $x$ at time $t,$ we study the dynamic version of the nonlinear optimal control problem $\\inf_u\\, Var{t,X_t^u}(X_T^u)$ where the infimum is taken over admissible controls $u$ subject to $X_t^u \\ge e...... a martingale method combined with Lagrange multipliers, we derive the dynamically optimal control $u_*^d$ in closed form and prove that the dynamically optimal terminal wealth $X_T^d$ can only take two values $g$ and $\\beta$. This binomial nature of the dynamically optimal strategy stands in sharp contrast...... with other known portfolio selection strategies encountered in the literature. A direct comparison shows that the dynamically optimal (time-consistent) strategy outperforms the statically optimal (time-inconsistent) strategy in the problem....

Bone marrow-derived cells for cardiovascular cell therapy: an optimized GMP method based on low-density gradient improves cell purity and function.

Science.gov (United States)

Radrizzani, Marina; Lo Cicero, Viviana; Soncin, Sabrina; Bolis, Sara; Sürder, Daniel; Torre, Tiziano; Siclari, Francesco; Moccetti, Tiziano; Vassalli, Giuseppe; Turchetto, Lucia

2014-09-27

Cardiovascular cell therapy represents a promising field, with several approaches currently being tested. The advanced therapy medicinal product (ATMP) for the ongoing METHOD clinical study ("Bone marrow derived cell therapy in the stable phase of chronic ischemic heart disease") consists of fresh mononuclear cells (MNC) isolated from autologous bone marrow (BM) through density gradient centrifugation on standard Ficoll-Paque. Cells are tested for safety (sterility, endotoxin), identity/potency (cell count, CD45/CD34/CD133, viability) and purity (contaminant granulocytes and platelets). BM-MNC were isolated by density gradient centrifugation on Ficoll-Paque. The following process parameters were optimized throughout the study: gradient medium density; gradient centrifugation speed and duration; washing conditions. A new manufacturing method was set up, based on gradient centrifugation on low density Ficoll-Paque, followed by 2 washing steps, of which the second one at low speed. It led to significantly higher removal of contaminant granulocytes and platelets, improving product purity; the frequencies of CD34+ cells, CD133+ cells and functional hematopoietic and mesenchymal precursors were significantly increased. The methodological optimization described here resulted in a significant improvement of ATMP quality, a crucial issue to clinical applications in cardiovascular cell therapy.

Optimization methods in structural design

CERN Document Server

Rothwell, Alan

2017-01-01

This book offers an introduction to numerical optimization methods in structural design. Employing a readily accessible and compact format, the book presents an overview of optimization methods, and equips readers to properly set up optimization problems and interpret the results. A ‘how-to-do-it’ approach is followed throughout, with less emphasis at this stage on mathematical derivations. The book features spreadsheet programs provided in Microsoft Excel, which allow readers to experience optimization ‘hands-on.’ Examples covered include truss structures, columns, beams, reinforced shell structures, stiffened panels and composite laminates. For the last three, a review of relevant analysis methods is included. Exercises, with solutions where appropriate, are also included with each chapter. The book offers a valuable resource for engineering students at the upper undergraduate and postgraduate level, as well as others in the industry and elsewhere who are new to these highly practical techniques.Whi...

Characterization of sugar beet pulp derived oligosaccharides

NARCIS (Netherlands)

Leijdekkers, M.

2015-01-01

Abstract

This thesis aimed at characterizing complex mixtures of sugar beet pulp derived oligosaccharides, in order to be able to monitor and optimize the enzymatic saccharification of sugar beet pulp.

Hydrophilic interaction chromatography with on-line evaporative

Risk Management and Financial Derivatives: An Overview

NARCIS (Netherlands)

S.M. Hammoudeh (Shawkat); M.J. McAleer (Michael)

2012-01-01

textabstractRisk management is crucial for optimal portfolio management. One of the fastest growing areas in empirical finance is the expansion of financial derivatives. The purpose of this special issue on “Risk Management and Financial Derivatives” is to highlight some areas in which novel

Optimal construction and delivery of dual-functioning lentiviral vectors for type I collagen-suppressed chondrogenesis in synovium-derived mesenchymal stem cells.

Science.gov (United States)

Zhang, Feng; Yao, Yongchang; Zhou, Ruijie; Su, Kai; Citra, Fudiman; Wang, Dong-An

2011-06-01

This study aims to deliver both transforming growth factor β3 (TGF-β3) and shRNA targeting type I collagen (Col I) by optimal construction and application of various dual-functioning lentiviral vectors to induce Col I-suppressed chondrogenesis in synovium-derived mesenchymal stem cells (SMSCs). We constructed four lentiviral vectors (LV-1, LV-2, LV-3 and LV-4) with various arrangements of the two expression cassettes in different positions and orientations. Col I inhibition efficiency and chondrogenic markers were assessed with qPCR, ELISA and staining techniques. Among the four vectors, LV-1 has two distant and reversely oriented cassettes, LV-2 has two distant and same-oriented cassettes, LV-3 has two proximal and reversely oriented cassettes, and LV-4 has two proximal and same-oriented cassettes. Col I and chondrogenic markers, including type II collagen (Col II), aggrecan and glycosaminoglycan (GAG), were examined in SMSCs cultured in 3-D alginate hydrogel. All of the four vectors showed distinct effects in Col I level as well as diverse inductive efficiencies in upregulation of the cartilaginous markers. Based on real-time PCR results, LV-1 was optimal towards Col I-suppressed chondrogenesis. LV-1 vector is competent to promote Col I-suppressed chondrogenesis in SMSCs.

Substituent effects on mono-substituted and poly-substituted nitriles; Efeitos dos substituintes em nitrilas mono- e polissubstituidas

Energy Technology Data Exchange (ETDEWEB)

Sofia, Raquel C.R.; Carneiro, Paulo I.B.; Rittner, Roberto [Universidade Estadual de Campinas, SP (Brazil). Inst. de Quimica; Fabi, Marino T [Rhodia S.A., Sao Paulo, SP (Brazil)

1992-12-31

This work studies various mono substituted aliphatic nitriles, Y C H{sub 2} (Y=H, F, Cl, Br, I, OMe, S Me, SEt{sub 2}, Me and Ph), and some reference nitriles (Y=Et, n-Pr, n-Bu, n-Am, n-Hex and n-Hept) 12 refs., 3 tabs.

Energy-optimal electrical excitation of nerve fibers.

Science.gov (United States)

Jezernik, Saso; Morari, Manfred

2005-04-01

We derive, based on an analytical nerve membrane model and optimal control theory of dynamical systems, an energy-optimal stimulation current waveform for electrical excitation of nerve fibers. Optimal stimulation waveforms for nonleaky and leaky membranes are calculated. The case with a leaky membrane is a realistic case. Finally, we compare the waveforms and energies necessary for excitation of a leaky membrane in the case where the stimulation waveform is a square-wave current pulse, and in the case of energy-optimal stimulation. The optimal stimulation waveform is an exponentially rising waveform and necessitates considerably less energy to excite the nerve than a square-wave pulse (especially true for larger pulse durations). The described theoretical results can lead to drastically increased battery lifetime and/or decreased energy transmission requirements for implanted biomedical systems.

Optimal Set-Point Synthesis in HVAC Systems

DEFF Research Database (Denmark)

Komareji, Mohammad; Stoustrup, Jakob; Rasmussen, Henrik

2007-01-01

This paper presents optimal set-point synthesis for a heating, ventilating, and air-conditioning (HVAC) system. This HVAC system is made of two heat exchangers: an air-to-air heat exchanger and a water-to-air heat exchanger. The objective function is composed of the electrical power for different...... components, encompassing fans, primary/secondary pump, tertiary pump, and air-to-air heat exchanger wheel; and a fraction of thermal power used by the HVAC system. The goals that have to be achieved by the HVAC system appear as constraints in the optimization problem. To solve the optimization problem......, a steady state model of the HVAC system is derived while different supplying hydronic circuits are studied for the water-to-air heat exchanger. Finally, the optimal set-points and the optimal supplying hydronic circuit are resulted....

An integrated optimization approach for a hybrid energy system in electric vehicles

International Nuclear Information System (INIS)

Hung, Yi-Hsuan; Wu, Chien-Hsun

2012-01-01

Highlights: ► Second-order control-oriented dynamics for a battery/supercapacitor EV is modeled. ► Multiple for-loop programming and global searchwith constraints are main design principles of integrated optimization algorithm (IOA). ► Optimal hybridization is derived based on maximizing energy storage capacity. ► Optimal energy management in three EV operation modes is searched based on minimizing total consumed power. ► Simulation results prove that 6+% of total energy is saved by the IOA method. -- Abstract: This paper develops a simple but innovative integrated optimization approach (IOA) for deriving the best solutions of component sizing and control strategies of a hybrid energy system (HES) which consists of a lithium battery and a supercapacitor module. To implement IOA, a multiple for-loop structure with a preset cost function is needed to globally calculate the best hybridization and energy management of the HES. For system hybridization, the optimal size ratio is evaluated by maximizing the HES energy stored capacity at various costs. For energy management, the optimal power distribution combined with a three-mode rule-based strategy is searched to minimize the total consumed energy. Combining above two for-loop structures and giving a time-dependent test scenario, the IOA is derived by minimizing the accumulated HES power. Simulation results show that 6% of the total HES energy can be saved in the IOA case compared with the original system in two driving cycles: ECE and UDDS, and two vehicle weights, respectively. It proves that the IOA effectively derives the maximum energy storage capacity and the minimum energy consumption of the HES at the same time. Experimental verification will be carried out in the near future.

Alchemical derivatives of reaction energetics

Science.gov (United States)

Sheppard, Daniel; Henkelman, Graeme; von Lilienfeld, O. Anatole

2010-08-01

Based on molecular grand canonical ensemble density functional theory, we present a theoretical description of how reaction barriers and enthalpies change as atoms in the system are subjected to alchemical transformations, from one element into another. The change in the energy barrier for the umbrella inversion of ammonia is calculated along an alchemical path in which the molecule is transformed into water, and the change in the enthalpy of protonation for methane is calculated as the molecule is transformed into a neon atom via ammonia, water, and hydrogen fluoride. Alchemical derivatives are calculated analytically from the electrostatic potential in the unperturbed system, and compared to numerical derivatives calculated with finite difference interpolation of the pseudopotentials for the atoms being transformed. Good agreement is found between the analytical and numerical derivatives. Alchemical derivatives are also shown to be predictive for integer changes in atomic numbers for oxygen binding to a 79 atom palladium nanoparticle, illustrating their potential use in gradient-based optimization algorithms for the rational design of catalysts.

Optimal design of the heat pipe using TLBO (teaching–learning-based optimization) algorithm

International Nuclear Information System (INIS)

Rao, R.V.; More, K.C.

2015-01-01

Heat pipe is a highly efficient and reliable heat transfer component. It is a closed container designed to transfer a large amount of heat in system. Since the heat pipe operates on a closed two-phase cycle, the heat transfer capacity is greater than for solid conductors. Also, the thermal response time is less than with solid conductors. The three major elemental parts of the rotating heat pipe are: a cylindrical evaporator, a truncated cone condenser, and a fixed amount of working fluid. In this paper, a recently proposed new stochastic advanced optimization algorithm called TLBO (Teaching–Learning-Based Optimization) algorithm is used for single objective as well as multi-objective design optimization of heat pipe. It is easy to implement, does not make use of derivatives and it can be applied to unconstrained or constrained problems. Two examples of heat pipe are presented in this paper. The results of application of TLBO algorithm for the design optimization of heat pipe are compared with the NPGA (Niched Pareto Genetic Algorithm), GEM (Grenade Explosion Method) and GEO (Generalized External optimization). It is found that the TLBO algorithm has produced better results as compared to those obtained by using NPGA, GEM and GEO algorithms. - Highlights: • The TLBO (Teaching–Learning-Based Optimization) algorithm is used for the design and optimization of a heat pipe. • Two examples of heat pipe design and optimization are presented. • The TLBO algorithm is proved better than the other optimization algorithms in terms of results and the convergence

A derivative-free approach for the estimation of porosity and permeability using time-lapse seismic and production data

International Nuclear Information System (INIS)

Dadashpour, Mohsen; Kleppe, Jon; Landrø, Martin; Echeverria Ciaurri, David; Mukerji, Tapan

2010-01-01

In this study, we apply a derivative-free optimization algorithm to estimate porosity and permeability from time-lapse seismic data and production data from a real reservoir (Norne field). In some circumstances, obtaining gradient information (exact and/or approximate) can be problematic e.g. derivatives are not available from a commercial simulator, or results are needed within a very short time frame. Derivative-free optimization approaches can be very time consuming because they often require many simulations. Typically, one iteration roughly needs as many simulations as the number of optimization variables. In this work, we propose two ways to significantly increase the efficiency of an optimization methodology in model inversion problems. First, by principal component analysis we decrease the number of optimization variables while keeping geostatistical consistency, and second, noticing that some optimization methods are very amenable to being parallelized, we apply them within a distributed computing framework. If we combine all this, the model inversion approach can be robust, fairly efficient and very simple to implement. In this paper, we apply the methodology to two cases: a semi-synthetic model with noisy data, and a case based entirely on field data. The results show that the derivative-free approach presented is robust against noise in the data

Optimal control of LQR for discrete time-varying systems with input delays

Science.gov (United States)

Yin, Yue-Zhu; Yang, Zhong-Lian; Yin, Zhi-Xiang; Xu, Feng

2018-04-01

In this work, we consider the optimal control problem of linear quadratic regulation for discrete time-variant systems with single input and multiple input delays. An innovative and simple method to derive the optimal controller is given. The studied problem is first equivalently converted into a problem subject to a constraint condition. Last, with the established duality, the problem is transformed into a static mathematical optimisation problem without input delays. The optimal control input solution to minimise performance index function is derived by solving this optimisation problem with two methods. A numerical simulation example is carried out and its results show that our two approaches are both feasible and very effective.

Channel Estimation and Optimal Power Allocation for a Multiple-Antenna OFDM System

Directory of Open Access Journals (Sweden)

Yao Kung

2002-01-01

Full Text Available We propose combining channel estimation and optimal power allocation approaches for a multiple-antenna orthogonal frequency division multiplexing (OFDM system in high-speed transmission applications. We develop a least-square channel estimation approach, derive the performance bound of the estimator, and investigate the optimal training sequences for initial channel acquisition. Based on the channel estimates, the optimal power allocation solution which maximizes the bandwidth efficiency is derived under power and quality of service (Qos (symbol error rate constraints. It is shown that combining channel tracking and adaptive power allocation can dramatically enhance the outage capacity of an OFDM multiple-antenna system when severing fading occurs.

Optimal adaptive control for quantum metrology with time-dependent Hamiltonians

Science.gov (United States)

Pang, Shengshi; Jordan, Andrew N.

2017-01-01

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

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

Science.gov (United States)

Pang, Shengshi; Jordan, Andrew N

2017-03-09

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

Optimal design of water supply networks for enhancing seismic reliability

International Nuclear Information System (INIS)

Yoo, Do Guen; Kang, Doosun; Kim, Joong Hoon

2016-01-01

The goal of the present study is to construct a reliability evaluation model of a water supply system taking seismic hazards and present techniques to enhance hydraulic reliability of the design into consideration. To maximize seismic reliability with limited budgets, an optimal design model is developed using an optimization technique called harmony search (HS). The model is applied to actual water supply systems to determine pipe diameters that can maximize seismic reliability. The reliabilities between the optimal design and existing designs were compared and analyzed. The optimal design would both enhance reliability by approximately 8.9% and have a construction cost of approximately 1.3% less than current pipe construction cost. In addition, the reinforcement of the durability of individual pipes without considering the system produced ineffective results in terms of both cost and reliability. Therefore, to increase the supply ability of the entire system, optimized pipe diameter combinations should be derived. Systems in which normal status hydraulic stability and abnormal status available demand could be maximally secured if configured through the optimal design. - Highlights: • We construct a seismic reliability evaluation model of water supply system. • We present technique to enhance hydraulic reliability in the aspect of design. • Harmony search algorithm is applied in optimal designs process. • The effects of the proposed optimal design are improved reliability about by 9%. • Optimized pipe diameter combinations should be derived indispensably.

Optimal sizing method for stand-alone photovoltaic power systems

Energy Technology Data Exchange (ETDEWEB)

Groumpos, P P; Papageorgiou, G

1987-01-01

The total life-cycle cost of stand-alone photovoltaic (SAPV) power systems is mathematically formulated. A new optimal sizing algorithm for the solar array and battery capacity is developed. The optimum value of a balancing parameter, M, for the optimal sizing of SAPV system components is derived. The proposed optimal sizing algorithm is used in an illustrative example, where a more economical life-cycle cost has bene obtained. The question of cost versus reliability is briefly discussed.

Optimization of biomass fuelled systems for distributed power generation using Particle Swarm Optimization

International Nuclear Information System (INIS)

Lopez, P. Reche; Reyes, N. Ruiz; Gonzalez, M. Gomez; Jurado, F.

2008-01-01

With sufficient territory and abundant biomass resources Spain appears to have suitable conditions to develop biomass utilization technologies. As an important decentralized power technology, biomass gasification and power generation has a potential market in making use of biomass wastes. This paper addresses biomass fuelled generation of electricity in the specific aspect of finding the best location and the supply area of the electric generation plant for three alternative technologies (gas motor, gas turbine and fuel cell-microturbine hybrid power cycle), taking into account the variables involved in the problem, such as the local distribution of biomass resources, transportation costs, distance to existing electric lines, etc. For each technology, not only optimal location and supply area of the biomass plant, but also net present value and generated electric power are determined by an own binary variant of Particle Swarm Optimization (PSO). According to the values derived from the optimization algorithm, the most profitable technology can be chosen. Computer simulations show the good performance of the proposed binary PSO algorithm to optimize biomass fuelled systems for distributed power generation. (author)

Numerical optimization of Combined Heat and Power Organic Rankine Cycles – Part A: Design optimization

International Nuclear Information System (INIS)

Martelli, Emanuele; Capra, Federico; Consonni, Stefano

2015-01-01

This two-part paper proposes an approach based on state-of-the-art numerical optimization methods for simultaneously determining the most profitable design and part-load operation of Combined Heat and Power Organic Rankine Cycles. Compared to the usual design practice, the important advantages of the proposed approach are (i) to consider the part-load performance of the ORC at the design stage, (ii) to optimize not only the cycle variables, but also the main turbine design variables (number of stages, stage loads, rotational speed). In this first part (Part A), the design model and the optimization algorithm are presented and tested on a real-world test case. PGS-COM, a recently proposed hybrid derivative-free algorithm, allows to efficiently tackle the challenging non-smooth black-box problem. - Highlights: • Algorithm for the simultaneous optimization Organic Rakine Cycle and turbine. • Thermodynamic and economic models of boiler, cycle, turbine are developed. • Non-smooth black-box optimization problem is successfully tackled with PGS-COM. • Test cases show that the algorithm returns optimal solutions within 4 min. • Toluene outperforms MDM (a siloxane) in terms of efficiency and costs.

optBINS: Optimal Binning for histograms

Science.gov (United States)

Knuth, Kevin H.

2018-03-01

optBINS (optimal binning) determines the optimal number of bins in a uniform bin-width histogram by deriving the posterior probability for the number of bins in a piecewise-constant density model after assigning a multinomial likelihood and a non-informative prior. The maximum of the posterior probability occurs at a point where the prior probability and the the joint likelihood are balanced. The interplay between these opposing factors effectively implements Occam's razor by selecting the most simple model that best describes the data.

Verbenone-releasing flakes protect individual Pinus contorta trees from attack by Dendroctonus ponderosae and Dendroctonus valens (Coleoptera: Curculionidae, Scolytinae)

Science.gov (United States)

Nancy E. Gillette; John D. Stein; Donald R. Owen; Jeffrey N. Webster; Gary O. Fiddler; Sylvia R. Mori; David L. Wood

2006-01-01

In a study site in interior northern California, twenty individual lodgepole pines Pinus contorta were sprayed with a suspension of DISRUPT Micro-Flake ® Verbenone (4,6,6-trimethylbicyclo(3.1)hept-3-en-2-one) Bark Beetle Anti-Aggregant flakes (Hercon Environmental, Emigsville, Pennsylvania) in water, with sticker and...

Shearlets and Optimally Sparse Approximations

DEFF Research Database (Denmark)

Kutyniok, Gitta; Lemvig, Jakob; Lim, Wang-Q

2012-01-01

Multivariate functions are typically governed by anisotropic features such as edges in images or shock fronts in solutions of transport-dominated equations. One major goal both for the purpose of compression as well as for an efficient analysis is the provision of optimally sparse approximations...... optimally sparse approximations of this model class in 2D as well as 3D. Even more, in contrast to all other directional representation systems, a theory for compactly supported shearlet frames was derived which moreover also satisfy this optimality benchmark. This chapter shall serve as an introduction...... to and a survey about sparse approximations of cartoon-like images by band-limited and also compactly supported shearlet frames as well as a reference for the state-of-the-art of this research field....

Hydroxyethylamine derivatives as HIV-1 protease inhibitors: a predictive QSAR modelling study based on Monte Carlo optimization.

Science.gov (United States)

Bhargava, S; Adhikari, N; Amin, S A; Das, K; Gayen, S; Jha, T

2017-12-01

Application of HIV-1 protease inhibitors (as an anti-HIV regimen) may serve as an attractive strategy for anti-HIV drug development. Several investigations suggest that there is a crucial need to develop a novel protease inhibitor with higher potency and reduced toxicity. Monte Carlo optimized QSAR study was performed on 200 hydroxyethylamine derivatives with antiprotease activity. Twenty-one QSAR models with good statistical qualities were developed from three different splits with various combinations of SMILES and GRAPH based descriptors. The best models from different splits were selected on the basis of statistically validated characteristics of the test set and have the following statistical parameters: r 2 = 0.806, Q 2 = 0.788 (split 1); r 2 = 0.842, Q 2 = 0.826 (split 2); r 2 = 0.774, Q 2 = 0.755 (split 3). The structural attributes obtained from the best models were analysed to understand the structural requirements of the selected series for HIV-1 protease inhibitory activity. On the basis of obtained structural attributes, 11 new compounds were designed, out of which five compounds were found to have better activity than the best active compound in the series.

An Optimal Investment Strategy and Multiperiod Deposit Insurance Pricing Model for Commercial Banks

Directory of Open Access Journals (Sweden)

Grant E. Muller

2018-01-01

Full Text Available We employ the method of stochastic optimal control to derive the optimal investment strategy for maximizing an expected exponential utility of a commercial bank’s capital at some future date T>0. In addition, we derive a multiperiod deposit insurance (DI pricing model that incorporates the explicit solution of the optimal control problem and an asset value reset rule comparable to the typical practice of insolvency resolution by insuring agencies. By way of numerical simulations, we study the effects of changes in the DI coverage horizon, the risk associated with the asset portfolio of the bank, and the bank’s initial leverage level (deposit-to-asset ratio on the DI premium while the optimal investment strategy is followed.

Optimal portfolio choice under loss aversion

NARCIS (Netherlands)

A.B. Berkelaar (Arjan); R.R.P. Kouwenberg (Roy)

2000-01-01

textabstractProspect theory and loss aversion play a dominant role in behavioral finance. In this paper we derive closed-form solutions for optimal portfolio choice under loss aversion. When confronted with gains a loss averse investor behaves similar to a portfolio insurer. When confronted with

Brownian Optimal Stopping and Random Walks

International Nuclear Information System (INIS)

Lamberton, D.

2002-01-01

One way to compute the value function of an optimal stopping problem along Brownian paths consists of approximating Brownian motion by a random walk. We derive error estimates for this type of approximation under various assumptions on the distribution of the approximating random walk

Belief Propagation Algorithm for Portfolio Optimization Problems.

Science.gov (United States)

Shinzato, Takashi; Yasuda, Muneki

2015-01-01

The typical behavior of optimal solutions to portfolio optimization problems with absolute deviation and expected shortfall models using replica analysis was pioneeringly estimated by S. Ciliberti et al. [Eur. Phys. B. 57, 175 (2007)]; however, they have not yet developed an approximate derivation method for finding the optimal portfolio with respect to a given return set. In this study, an approximation algorithm based on belief propagation for the portfolio optimization problem is presented using the Bethe free energy formalism, and the consistency of the numerical experimental results of the proposed algorithm with those of replica analysis is confirmed. Furthermore, the conjecture of H. Konno and H. Yamazaki, that the optimal solutions with the absolute deviation model and with the mean-variance model have the same typical behavior, is verified using replica analysis and the belief propagation algorithm.

Belief Propagation Algorithm for Portfolio Optimization Problems.

Directory of Open Access Journals (Sweden)

Takashi Shinzato

Full Text Available The typical behavior of optimal solutions to portfolio optimization problems with absolute deviation and expected shortfall models using replica analysis was pioneeringly estimated by S. Ciliberti et al. [Eur. Phys. B. 57, 175 (2007]; however, they have not yet developed an approximate derivation method for finding the optimal portfolio with respect to a given return set. In this study, an approximation algorithm based on belief propagation for the portfolio optimization problem is presented using the Bethe free energy formalism, and the consistency of the numerical experimental results of the proposed algorithm with those of replica analysis is confirmed. Furthermore, the conjecture of H. Konno and H. Yamazaki, that the optimal solutions with the absolute deviation model and with the mean-variance model have the same typical behavior, is verified using replica analysis and the belief propagation algorithm.

Texture mapping via optimal mass transport.

Science.gov (United States)

Dominitz, Ayelet; Tannenbaum, Allen

2010-01-01

In this paper, we present a novel method for texture mapping of closed surfaces. Our method is based on the technique of optimal mass transport (also known as the "earth-mover's metric"). This is a classical problem that concerns determining the optimal way, in the sense of minimal transportation cost, of moving a pile of soil from one site to another. In our context, the resulting mapping is area preserving and minimizes angle distortion in the optimal mass sense. Indeed, we first begin with an angle-preserving mapping (which may greatly distort area) and then correct it using the mass transport procedure derived via a certain gradient flow. In order to obtain fast convergence to the optimal mapping, we incorporate a multiresolution scheme into our flow. We also use ideas from discrete exterior calculus in our computations.

An Indirect Simulation-Optimization Model for Determining Optimal TMDL Allocation under Uncertainty

Directory of Open Access Journals (Sweden)

Feng Zhou

2015-11-01

Full Text Available An indirect simulation-optimization model framework with enhanced computational efficiency and risk-based decision-making capability was developed to determine optimal total maximum daily load (TMDL allocation under uncertainty. To convert the traditional direct simulation-optimization model into our indirect equivalent model framework, we proposed a two-step strategy: (1 application of interval regression equations derived by a Bayesian recursive regression tree (BRRT v2 algorithm, which approximates the original hydrodynamic and water-quality simulation models and accurately quantifies the inherent nonlinear relationship between nutrient load reductions and the credible interval of algal biomass with a given confidence interval; and (2 incorporation of the calibrated interval regression equations into an uncertain optimization framework, which is further converted to our indirect equivalent framework by the enhanced-interval linear programming (EILP method and provides approximate-optimal solutions at various risk levels. The proposed strategy was applied to the Swift Creek Reservoir’s nutrient TMDL allocation (Chesterfield County, VA to identify the minimum nutrient load allocations required from eight sub-watersheds to ensure compliance with user-specified chlorophyll criteria. Our results indicated that the BRRT-EILP model could identify critical sub-watersheds faster than the traditional one and requires lower reduction of nutrient loadings compared to traditional stochastic simulation and trial-and-error (TAE approaches. This suggests that our proposed framework performs better in optimal TMDL development compared to the traditional simulation-optimization models and provides extreme and non-extreme tradeoff analysis under uncertainty for risk-based decision making.

Topology optimization in acoustics and elasto-acoustics via a level-set method

Science.gov (United States)

Desai, J.; Faure, A.; Michailidis, G.; Parry, G.; Estevez, R.

2018-04-01

Optimizing the shape and topology (S&T) of structures to improve their acoustic performance is quite challenging. The exact position of the structural boundary is usually of critical importance, which dictates the use of geometric methods for topology optimization instead of standard density approaches. The goal of the present work is to investigate different possibilities for handling topology optimization problems in acoustics and elasto-acoustics via a level-set method. From a theoretical point of view, we detail two equivalent ways to perform the derivation of surface-dependent terms and propose a smoothing technique for treating problems of boundary conditions optimization. In the numerical part, we examine the importance of the surface-dependent term in the shape derivative, neglected in previous studies found in the literature, on the optimal designs. Moreover, we test different mesh adaptation choices, as well as technical details related to the implicit surface definition in the level-set approach. We present results in two and three-space dimensions.

Reexamination of optimal quantum state estimation of pure states

International Nuclear Information System (INIS)

Hayashi, A.; Hashimoto, T.; Horibe, M.

2005-01-01

A direct derivation is given for the optimal mean fidelity of quantum state estimation of a d-dimensional unknown pure state with its N copies given as input, which was first obtained by Hayashi in terms of an infinite set of covariant positive operator valued measures (POVM's) and by Bruss and Macchiavello establishing a connection to optimal quantum cloning. An explicit condition for POVM measurement operators for optimal estimators is obtained, by which we construct optimal estimators with finite POVMs using exact quadratures on a hypersphere. These finite optimal estimators are not generally universal, where universality means the fidelity is independent of input states. However, any optimal estimator with finite POVM for M(>N) copies is universal if it is used for N copies as input

Paratingent Derivative Applied to the Measure of the Sensitivity in Multiobjective Differential Programming

Directory of Open Access Journals (Sweden)

F. García

2013-01-01

Full Text Available We analyse the sensitivity of differential programs of the form subject to where and are maps whose respective images lie in ordered Banach spaces. Following previous works on multiobjective programming, the notion of -optimal solution is used. The behaviour of some nonsingleton sets of -optimal solutions according to changes of the parameter in the problem is analysed. The main result of the work states that the sensitivity of the program is measured by a Lagrange multiplier plus a projection of its derivative. This sensitivity is measured by means of the paratingent derivative.

Energy optimization methodology of multi-chiller plant in commercial buildings

International Nuclear Information System (INIS)

Thangavelu, Sundar Raj; Myat, Aung; Khambadkone, Ashwin

2017-01-01

This study investigates the potential energy savings in commercial buildings through optimized operation of a multi-chiller plant. The cooling load contributes 45–60% of total power consumption in commercial and office buildings, especially at tropics. The chiller plant operation is not optimal in most of the existing buildings because the chiller plant is either operated at design condition irrespective of the cooling load or optimized locally due to lack of overall chiller plant behavior. In this study, an overall energy model of chiller plant is developed to capture the thermal behavior of all systems and their interactions including the power consumption. An energy optimization methodology is proposed to derive optimized operation decisions for chiller plant at regular intervals based on building thermal load and weather condition. The benefits of proposed energy optimization methodology are examined using case study problems covering different chiller plant configurations. The case studies result confirmed the energy savings achieved through optimized operations is up to 40% for moderate size chiller plant and around 20% for small chiller plant which consequently reduces the energy cost and greenhouse gas emissions. - Highlights: • Energy optimization methodology improves the performance of multi-chiller plant. • Overall energy model of chiller plant accounts all equipment and the interactions. • Operation decisions are derived at regular interval based on time-varying factors. • Three case studies confirmed 20 to 40% of energy savings than conventional method.

Optimization of mixed quantum-classical dynamics: Time-derivative coupling terms and selected couplings

International Nuclear Information System (INIS)

Pittner, Jiri; Lischka, Hans; Barbatti, Mario

2009-01-01

The usage of time-derivative non-adiabatic coupling terms and partially coupled time-dependent equations are investigated to accelerate non-adiabatic dynamics simulations at multireference configuration interaction (MRCI) level. The quality of the results and computational costs are compared against non-adiabatic benchmark dynamics calculations using non-adiabatic coupling vectors. In the comparison between the time-derivative couplings and coupling vectors, deviations in the adiabatic population of individual trajectories were observed in regions of rapid variation of the coupling terms. They, however, affected the average adiabatic population to only about 5%. For small multiconfiguration spaces, dynamics with time-derivative couplings are significantly faster than those with coupling vectors. This relation inverts for larger configuration spaces. The use of the partially coupled equations approach speeds up the simulations significantly while keeping the deviations in the population below few percent. Imidazole and the methaniminium cation are used as test examples

Management of nuclear PRs activity with optimal conditions

International Nuclear Information System (INIS)

Ohnishi, Teruaki

1997-01-01

A methodology is proposed to derive optimal conditions for the activity of nuclear public relations (PRs). With the use of data-bases available at present, expressions were derived which connect the budget allocated for the PRs activity with the intensity of stimulus for four types of activity of the advertisement in the press, the exclusive publicity, the pamphlet and the advertisement on television. Optimal conditions for the activity were determined by introducing a model describing a relation between the intensity of stimulus and the extent of the change of public's attitude to nuclear energy, namely the effect of PRs activity, and also by giving the optimal ratio of allocation of the budget among the four types of activity as a function of cost versus effectiveness of each type. Those optimal conditions, being for the ratio of allocation of the budget, the execution time and the intensity of each type of activity at that time, vary depending on the number of household in a target region, the target class of demography, the duration time of activity, and the amount of budget for the activity. It becomes clear from numerical calculation that the optimal conditions and the effect of activity show quite strong non-linearity with respect to the variation of those variables, and that the effect of PRs activity averaged over all public in the target region becomes to be maximum, in Japan, when the activity is executed with the optimal conditions determined for the target class of middle- and advanced-aged women. The management of nuclear PRs activity becomes possible by introducing such a method of fixation of optimal conditions for the activity as described here. (author)

Network synchronization: optimal and pessimal scale-free topologies

International Nuclear Information System (INIS)

Donetti, Luca; Hurtado, Pablo I; Munoz, Miguel A

2008-01-01

By employing a recently introduced optimization algorithm we construct optimally synchronizable (unweighted) networks for any given scale-free degree distribution. We explore how the optimization process affects degree-degree correlations and observe a generic tendency toward disassortativity. Still, we show that there is not a one-to-one correspondence between synchronizability and disassortativity. On the other hand, we study the nature of optimally un-synchronizable networks, that is, networks whose topology minimizes the range of stability of the synchronous state. The resulting 'pessimal networks' turn out to have a highly assortative string-like structure. We also derive a rigorous lower bound for the Laplacian eigenvalue ratio controlling synchronizability, which helps understanding the impact of degree correlations on network synchronizability

Analytic Optimization of Near-Field Optical Chirality Enhancement

Science.gov (United States)

2017-01-01

We present an analytic derivation for the enhancement of local optical chirality in the near field of plasmonic nanostructures by tuning the far-field polarization of external light. We illustrate the results by means of simulations with an achiral and a chiral nanostructure assembly and demonstrate that local optical chirality is significantly enhanced with respect to circular polarization in free space. The optimal external far-field polarizations are different from both circular and linear. Symmetry properties of the nanostructure can be exploited to determine whether the optimal far-field polarization is circular. Furthermore, the optimal far-field polarization depends on the frequency, which results in complex-shaped laser pulses for broadband optimization. PMID:28239617

Optimal estimation of the intensity function of a spatial point process

DEFF Research Database (Denmark)

Guan, Yongtao; Jalilian, Abdollah; Waagepetersen, Rasmus

easily computable estimating functions. We derive the optimal estimating function in a class of first-order estimating functions. The optimal estimating function depends on the solution of a certain Fredholm integral equation and reduces to the likelihood score in case of a Poisson process. We discuss...

Maximal imaginery eigenvalues in optimal systems

Directory of Open Access Journals (Sweden)

David Di Ruscio

1991-07-01

Full Text Available In this note we present equations that uniquely determine the maximum possible imaginary value of the closed loop eigenvalues in an LQ-optimal system, irrespective of how the state weight matrix is chosen, provided a real symmetric solution of the algebraic Riccati equation exists. In addition, the corresponding state weight matrix and the solution to the algebraic Riccati equation are derived for a class of linear systems. A fundamental lemma for the existence of a real symmetric solution to the algebraic Riccati equation is derived for this class of linear systems.

On the Optimal Detection and Error Performance Analysis of the Hardware Impaired Systems

KAUST Repository

Javed, Sidrah; Amin, Osama; Ikki, Salama S.; Alouini, Mohamed-Slim

2018-01-01

The conventional minimum Euclidean distance (MED) receiver design is based on the assumption of ideal hardware transceivers and proper Gaussian noise in communication systems. Throughout this study, an accurate statistical model of various hardware impairments (HWIs) is presented. Then, an optimal maximum likelihood (ML) receiver is derived considering the distinct characteristics of the HWIs comprised of additive improper Gaussian noise and signal distortion. Next, the average error probability performance of the proposed optimal ML receiver is analyzed and tight bounds are derived. Finally, different numerical and simulation results are presented to support the superiority of the proposed ML receiver over MED receiver and the tightness of the derived bounds.

On the Optimal Detection and Error Performance Analysis of the Hardware Impaired Systems

KAUST Repository

Javed, Sidrah

2018-01-15

The conventional minimum Euclidean distance (MED) receiver design is based on the assumption of ideal hardware transceivers and proper Gaussian noise in communication systems. Throughout this study, an accurate statistical model of various hardware impairments (HWIs) is presented. Then, an optimal maximum likelihood (ML) receiver is derived considering the distinct characteristics of the HWIs comprised of additive improper Gaussian noise and signal distortion. Next, the average error probability performance of the proposed optimal ML receiver is analyzed and tight bounds are derived. Finally, different numerical and simulation results are presented to support the superiority of the proposed ML receiver over MED receiver and the tightness of the derived bounds.

Machine assisted reaction optimization: A self-optimizing reactor system for continuous-flow photochemical reactions

KAUST Repository

Poscharny, K.; Fabry, D.C.; Heddrich, S.; Sugiono, E.; Liauw, M.A.; Rueping, Magnus

2018-01-01

A methodology for the synthesis of oxetanes from benzophenone and furan derivatives is presented. UV-light irradiation in batch and flow systems allowed the [2 + 2] cycloaddition reaction to proceed and a broad range of oxetanes could be synthesized in manual and automated fashion. The identification of high-yielding reaction parameters was achieved through a new self-optimizing photoreactor system.

Machine assisted reaction optimization: A self-optimizing reactor system for continuous-flow photochemical reactions

KAUST Repository

Poscharny, K.

2018-04-07

A methodology for the synthesis of oxetanes from benzophenone and furan derivatives is presented. UV-light irradiation in batch and flow systems allowed the [2 + 2] cycloaddition reaction to proceed and a broad range of oxetanes could be synthesized in manual and automated fashion. The identification of high-yielding reaction parameters was achieved through a new self-optimizing photoreactor system.

Optimal control of a qubit in an optical cavity

International Nuclear Information System (INIS)

Deffner, Sebastian

2014-01-01

We study quantum information processing by means of optimal control theory. To this end, we analyze the damped Jaynes–Cummings model, and derive optimal control protocols that minimize the heating or energy dispersion rates, and controls that drive the system at the quantum speed limit. Special emphasis is put on analyzing the subtleties of optimal control theory for our system. In particular, it is shown how two fundamentally different approaches to the quantum speed limit can be reconciled by carefully formulating the problem. (paper)

Quantum approximate optimization algorithm for MaxCut: A fermionic view

Science.gov (United States)

Wang, Zhihui; Hadfield, Stuart; Jiang, Zhang; Rieffel, Eleanor G.

2018-02-01

Farhi et al. recently proposed a class of quantum algorithms, the quantum approximate optimization algorithm (QAOA), for approximately solving combinatorial optimization problems (E. Farhi et al., arXiv:1411.4028; arXiv:1412.6062; arXiv:1602.07674). A level-p QAOA circuit consists of p steps; in each step a classical Hamiltonian, derived from the cost function, is applied followed by a mixing Hamiltonian. The 2 p times for which these two Hamiltonians are applied are the parameters of the algorithm, which are to be optimized classically for the best performance. As p increases, parameter optimization becomes inefficient due to the curse of dimensionality. The success of the QAOA approach will depend, in part, on finding effective parameter-setting strategies. Here we analytically and numerically study parameter setting for the QAOA applied to MaxCut. For the level-1 QAOA, we derive an analytical expression for a general graph. In principle, expressions for higher p could be derived, but the number of terms quickly becomes prohibitive. For a special case of MaxCut, the "ring of disagrees," or the one-dimensional antiferromagnetic ring, we provide an analysis for an arbitrarily high level. Using a fermionic representation, the evolution of the system under the QAOA translates into quantum control of an ensemble of independent spins. This treatment enables us to obtain analytical expressions for the performance of the QAOA for any p . It also greatly simplifies the numerical search for the optimal values of the parameters. By exploring symmetries, we identify a lower-dimensional submanifold of interest; the search effort can be accordingly reduced. This analysis also explains an observed symmetry in the optimal parameter values. Further, we numerically investigate the parameter landscape and show that it is a simple one in the sense of having no local optima.

Suitable or optimal noise benefits in signal detection

International Nuclear Information System (INIS)

Liu, Shujun; Yang, Ting; Tang, Mingchun; Wang, Pin; Zhang, Xinzheng

2016-01-01

Highlights: • Six intervals of additive noises divided according to the two constraints. • Derivation of the suitable additive noise to meet the two constraints. • Formulation of the suitable noise for improvability or nonimprovability. • Optimal noises to minimize P FA , maximize P D and maximize the overall improvement. - Abstract: We present an effective way to generate the suitable or the optimal additive noises which can achieve the three goals of the noise enhanced detectability, i.e., the maximum detection probability (P D ), the minimum false alarm probability (P FA ) and the maximum overall improvement of P D and P FA , without increasing P FA and decreasing P D in a binary hypothesis testing problem. The mechanism of our method is that we divide the discrete vectors into six intervals and choose the useful or partial useful vectors from these intervals to form the additive noise according to different requirements. The form of the optimal noise is derived and proven as a randomization of no more than two discrete vectors in our way. Moreover, how to choose suitable and optimal noises from the six intervals are given. Finally, numerous examples are presented to illustrate the theoretical analysis, where the background noises are Gaussian, symmetric and asymmetric Gaussian mixture noise, respectively.

Model Risk in Portfolio Optimization

Directory of Open Access Journals (Sweden)

David Stefanovits

2014-08-01

Full Text Available We consider a one-period portfolio optimization problem under model uncertainty. For this purpose, we introduce a measure of model risk. We derive analytical results for this measure of model risk in the mean-variance problem assuming we have observations drawn from a normal variance mixture model. This model allows for heavy tails, tail dependence and leptokurtosis of marginals. The results show that mean-variance optimization is seriously compromised by model uncertainty, in particular, for non-Gaussian data and small sample sizes. To mitigate these shortcomings, we propose a method to adjust the sample covariance matrix in order to reduce model risk.

Joint fundamental frequency and order estimation using optimal filtering

Directory of Open Access Journals (Sweden)

Jakobsson Andreas

2011-01-01

Full Text Available Abstract In this paper, the problem of jointly estimating the number of harmonics and the fundamental frequency of periodic signals is considered. We show how this problem can be solved using a number of methods that either are or can be interpreted as filtering methods in combination with a statistical model selection criterion. The methods in question are the classical comb filtering method, a maximum likelihood method, and some filtering methods based on optimal filtering that have recently been proposed, while the model selection criterion is derived herein from the maximum a posteriori principle. The asymptotic properties of the optimal filtering methods are analyzed and an order-recursive efficient implementation is derived. Finally, the estimators have been compared in computer simulations that show that the optimal filtering methods perform well under various conditions. It has previously been demonstrated that the optimal filtering methods perform extremely well with respect to fundamental frequency estimation under adverse conditions, and this fact, combined with the new results on model order estimation and efficient implementation, suggests that these methods form an appealing alternative to classical methods for analyzing multi-pitch signals.

Aerodynamic design applying automatic differentiation and using robust variable fidelity optimization

Science.gov (United States)

Takemiya, Tetsushi

, and that (2) the AMF terminates optimization erroneously when the optimization problems have constraints. The first problem is due to inaccuracy in computing derivatives in the AMF, and the second problem is due to erroneous treatment of the trust region ratio, which sets the size of the domain for an optimization in the AMF. In order to solve the first problem of the AMF, automatic differentiation (AD) technique, which reads the codes of analysis models and automatically generates new derivative codes based on some mathematical rules, is applied. If derivatives are computed with the generated derivative code, they are analytical, and the required computational time is independent of the number of design variables, which is very advantageous for realistic aerospace engineering problems. However, if analysis models implement iterative computations such as computational fluid dynamics (CFD), which solves system partial differential equations iteratively, computing derivatives through the AD requires a massive memory size. The author solved this deficiency by modifying the AD approach and developing a more efficient implementation with CFD, and successfully applied the AD to general CFD software. In order to solve the second problem of the AMF, the governing equation of the trust region ratio, which is very strict against the violation of constraints, is modified so that it can accept the violation of constraints within some tolerance. By accepting violations of constraints during the optimization process, the AMF can continue optimization without terminating immaturely and eventually find the true optimum design point. With these modifications, the AMF is referred to as "Robust AMF," and it is applied to airfoil and wing aerodynamic design problems using Euler CFD software. The former problem has 21 design variables, and the latter 64. In both problems, derivatives computed with the proposed AD method are first compared with those computed with the finite

Optimal Distributed Controller Synthesis for Chain Structures: Applications to Vehicle Formations

OpenAIRE

Khorsand, Omid; Alam, Assad; Gattami, Ather

2012-01-01

We consider optimal distributed controller synthesis for an interconnected system subject to communication constraints, in linear quadratic settings. Motivated by the problem of finite heavy duty vehicle platooning, we study systems composed of interconnected subsystems over a chain graph. By decomposing the system into orthogonal modes, the cost function can be separated into individual components. Thereby, derivation of the optimal controllers in state-space follows immediately. The optimal...

Asymptotic Normality of the Optimal Solution in Multiresponse Surface Mathematical Programming

OpenAIRE

Díaz-García, José A.; Caro-Lopera, Francisco J.

2015-01-01

An explicit form for the perturbation effect on the matrix of regression coeffi- cients on the optimal solution in multiresponse surface methodology is obtained in this paper. Then, the sensitivity analysis of the optimal solution is studied and the critical point characterisation of the convex program, associated with the optimum of a multiresponse surface, is also analysed. Finally, the asymptotic normality of the optimal solution is derived by the standard methods.

Optimal Control of Interdependent Epidemics in Complex Networks

OpenAIRE

Chen, Juntao; Zhang, Rui; Zhu, Quanyan

2017-01-01

Optimal control of interdependent epidemics spreading over complex networks is a critical issue. We first establish a framework to capture the coupling between two epidemics, and then analyze the system's equilibrium states by categorizing them into three classes, and deriving their stability conditions. The designed control strategy globally optimizes the trade-off between the control cost and the severity of epidemics in the network. A gradient descent algorithm based on a fixed point itera...

Optimal refueling principle of research and test reactors and its application

International Nuclear Information System (INIS)

Peng Feng; Sun Shouhua; Bu Yongxi

1993-01-01

Based on basic formula for core refueling, the optimal refueling principle for cores with fuel assemblies of different burnup are suggested. Some conclusions derived from this principle are given. Calculation formula for different refueling scheme and computation programme are derived and used for the HFETR typical core loading with different refueling scheme. With the suggested core fuel consuming index, core fuel managements of 24 cycles in 10 years operation of HFETR were analyzed. Results show that the application of optimal refueling principle can greatly save the fuel consuming. Direction of HFETR core fuel management research was also di cussed

Qualitative Analysis of Plant-Derived Samples by Liquid ...

African Journals Online (AJOL)

Purpose: Currently, mass spectrometry has become an effective method for the qualitative analysis of plant-derived samples. Precursor and product ions can be obtained by tandem mass spectrometry, supplying rich information for determining the structural formulas of compounds. In this work, we review the optimization of ...

PID control for chaotic synchronization using particle swarm optimization

International Nuclear Information System (INIS)

Chang, W.-D.

2009-01-01

In this paper, we attempt to use the proportional-integral-derivative (PID) controller to achieve the chaos synchronization for delayed discrete chaotic systems. Three PID control gains can be optimally determined by means of using a novel optimization algorithm, called the particle swarm optimization (PSO). The algorithm is motivated from the organism behavior of fish schooling and bird flocking, and involves the social psychology principles in socio-cognition human agents and evolutionary computations. It has a good numerical convergence for solving optimization problem. To show the validity of the PSO-based PID control for chaos synchronization, several cases with different initial populations are considered and some simulation results are shown.

PID control for chaotic synchronization using particle swarm optimization

Energy Technology Data Exchange (ETDEWEB)

Chang, W.-D. [Department of Computer and Communication, Shu-Te University, Kaohsiung 824, Taiwan (China)], E-mail: wdchang@mail.stu.edu.tw

2009-01-30

In this paper, we attempt to use the proportional-integral-derivative (PID) controller to achieve the chaos synchronization for delayed discrete chaotic systems. Three PID control gains can be optimally determined by means of using a novel optimization algorithm, called the particle swarm optimization (PSO). The algorithm is motivated from the organism behavior of fish schooling and bird flocking, and involves the social psychology principles in socio-cognition human agents and evolutionary computations. It has a good numerical convergence for solving optimization problem. To show the validity of the PSO-based PID control for chaos synchronization, several cases with different initial populations are considered and some simulation results are shown.

Hybrid Design Optimization of High Voltage Pulse Transformers for Klystron Modulators

CERN Document Server

Sylvain, Candolfi; Davide, Aguglia; Jerome, Cros

2015-01-01

This paper presents a hybrid optimization methodology for the design of high voltage pulse transformers used in klystron modulators. The optimization process is using simplified 2D FEA design models of the 3D transformer structure. Each intermediate optimal solution is evaluated by 3D FEA and correction coefficients of the 2D FEA models are derived. A new optimization process using 2D FEA models is then performed. The convergence of this hybrid optimal design methodology is obtained with a limited number of time consuming 3D FEA simulations. The method is applied to the optimal design of a monolithic high voltage pulse transformer for the CLIC klystron modulator.

On some other preferred method for optimizing the welded joint

Directory of Open Access Journals (Sweden)

Pejović Branko B.

2016-01-01

Full Text Available The paper shows an example of performed optimization of sizes in terms of welding costs in a characteristic loaded welded joint. Hence, in the first stage, the variables and constant parameters are defined, and mathematical shape of the optimization function is determined. The following stage of the procedure defines and places the most important constraint functions that limit the design of structures, that the technologist and the designer should take into account. Subsequently, a mathematical optimization model of the problem is derived, that is efficiently solved by a proposed method of geometric programming. Further, a mathematically based thorough optimization algorithm is developed of the proposed method, with a main set of equations defining the problem that are valid under certain conditions. Thus, the primary task of optimization is reduced to the dual task through a corresponding function, which is easier to solve than the primary task of the optimized objective function. The main reason for this is a derived set of linear equations. Apparently, a correlation is used between the optimal primary vector that minimizes the objective function and the dual vector that maximizes the dual function. The method is illustrated on a computational practical example with a different number of constraint functions. It is shown that for the case of a lower level of complexity, a solution is reached through an appropriate maximization of the dual function by mathematical analysis and differential calculus.

Optimal contracts for wind power producers in electricity markets

KAUST Repository

Bitar, E.

2010-12-01

This paper is focused on optimal contracts for an independent wind power producer in conventional electricity markets. Starting with a simple model of the uncertainty in the production of power from a wind turbine farm and a model for the electric energy market, we derive analytical expressions for optimal contract size and corresponding expected optimal profit. We also address problems involving overproduction penalties, cost of reserves, and utility of additional sensor information. We obtain analytical expressions for marginal profits from investing in local generation and energy storage. ©2010 IEEE.

Topology Optimization for Minimizing the Resonant Response of Plates with Constrained Layer Damping Treatment

Directory of Open Access Journals (Sweden)

Zhanpeng Fang

2015-01-01

Full Text Available A topology optimization method is proposed to minimize the resonant response of plates with constrained layer damping (CLD treatment under specified broadband harmonic excitations. The topology optimization problem is formulated and the square of displacement resonant response in frequency domain at the specified point is considered as the objective function. Two sensitivity analysis methods are investigated and discussed. The derivative of modal damp ratio is not considered in the conventional sensitivity analysis method. An improved sensitivity analysis method considering the derivative of modal damp ratio is developed to improve the computational accuracy of the sensitivity. The evolutionary structural optimization (ESO method is used to search the optimal layout of CLD material on plates. Numerical examples and experimental results show that the optimal layout of CLD treatment on the plate from the proposed topology optimization using the conventional sensitivity analysis or the improved sensitivity analysis can reduce the displacement resonant response. However, the optimization method using the improved sensitivity analysis can produce a higher modal damping ratio than that using the conventional sensitivity analysis and develop a smaller displacement resonant response.

Exergetic optimization of a thermoacoustic engine using the particle swarm optimization method

International Nuclear Information System (INIS)

Chaitou, Hussein; Nika, Philippe

2012-01-01

Highlights: ► Optimization of a thermoacoustic engine using the particle swarm optimization method. ► Exergetic efficiency, acoustic power and their product are the optimized functions. ► PSO method is used successfully for the first time in the TA research. ► The powerful PSO tool is advised to be more involved in the TA research and design. ► EE times AP optimized function is highly recommended to design any new TA devices. - Abstract: Thermoacoustic engines convert heat energy into acoustic energy. Then, the acoustic energy can be used to pump heat or to generate electricity. It is well-known that the acoustic energy and therefore the exergetic efficiency depend on parameters such as the stack’s hydraulic radius, the stack’s position in the resonator and the traveling–standing-wave ratio. In this paper, these three parameters are investigated in order to study and analyze the best value of the produced acoustic energy, the exergetic efficiency and the product of the acoustic energy by the exergetic efficiency of a thermoacoustic engine with a parallel-plate stack. The dimensionless expressions of the thermoacoustic equations are derived and calculated. Then, the Particle Swarm Optimization method (PSO) is introduced and used for the first time in the thermoacoustic research. The use of the PSO method and the optimization of the acoustic energy multiplied by the exergetic efficiency are novel contributions to this domain of research. This paper discusses some significant conclusions which are useful for the design of new thermoacoustic engines.

On the Equivalence of Quadratic Optimization Problems Commonly Used in Portfolio Theory

OpenAIRE

Taras Bodnar; Nestor Parolya; Wolfgang Schmid

2012-01-01

In the paper, we consider three quadratic optimization problems which are frequently applied in portfolio theory, i.e, the Markowitz mean-variance problem as well as the problems based on the mean-variance utility function and the quadratic utility.Conditions are derived under which the solutions of these three optimization procedures coincide and are lying on the efficient frontier, the set of mean-variance optimal portfolios. It is shown that the solutions of the Markowitz optimization prob...

Centralized Stochastic Optimal Control of Complex Systems

Energy Technology Data Exchange (ETDEWEB)

Malikopoulos, Andreas [ORNL

2015-01-01

In this paper we address the problem of online optimization of the supervisory power management control in parallel hybrid electric vehicles (HEVs). We model HEV operation as a controlled Markov chain using the long-run expected average cost per unit time criterion, and we show that the control policy yielding the Pareto optimal solution minimizes the average cost criterion online. The effectiveness of the proposed solution is validated through simulation and compared to the solution derived with dynamic programming using the average cost criterion.

Fuel optimization for low-thrust Earth-Moon transfer via indirect optimal control

Science.gov (United States)

Pérez-Palau, Daniel; Epenoy, Richard

2018-02-01

The problem of designing low-energy transfers between the Earth and the Moon has attracted recently a major interest from the scientific community. In this paper, an indirect optimal control approach is used to determine minimum-fuel low-thrust transfers between a low Earth orbit and a Lunar orbit in the Sun-Earth-Moon Bicircular Restricted Four-Body Problem. First, the optimal control problem is formulated and its necessary optimality conditions are derived from Pontryagin's Maximum Principle. Then, two different solution methods are proposed to overcome the numerical difficulties arising from the huge sensitivity of the problem's state and costate equations. The first one consists in the use of continuation techniques. The second one is based on a massive exploration of the set of unknown variables appearing in the optimality conditions. The dimension of the search space is reduced by considering adapted variables leading to a reduction of the computational time. The trajectories found are classified in several families according to their shape, transfer duration and fuel expenditure. Finally, an analysis based on the dynamical structure provided by the invariant manifolds of the two underlying Circular Restricted Three-Body Problems, Earth-Moon and Sun-Earth is presented leading to a physical interpretation of the different families of trajectories.

Free terminal time optimal control problem for the treatment of HIV infection

Directory of Open Access Journals (Sweden)

Amine Hamdache

2016-01-01

to provide the explicit formulations of the optimal controls. The corresponding optimality system with the additional transversality condition for the terminal time is derived and solved numerically using an adapted iterative method with a Runge-Kutta fourth order scheme and a gradient method routine.

An implementation of particle swarm optimization to evaluate optimal under-voltage load shedding in competitive electricity markets

Science.gov (United States)

Hosseini-Bioki, M. M.; Rashidinejad, M.; Abdollahi, A.

2013-11-01

Load shedding is a crucial issue in power systems especially under restructured electricity environment. Market-driven load shedding in reregulated power systems associated with security as well as reliability is investigated in this paper. A technoeconomic multi-objective function is introduced to reveal an optimal load shedding scheme considering maximum social welfare. The proposed optimization problem includes maximum GENCOs and loads' profits as well as maximum loadability limit under normal and contingency conditions. Particle swarm optimization (PSO) as a heuristic optimization technique, is utilized to find an optimal load shedding scheme. In a market-driven structure, generators offer their bidding blocks while the dispatchable loads will bid their price-responsive demands. An independent system operator (ISO) derives a market clearing price (MCP) while rescheduling the amount of generating power in both pre-contingency and post-contingency conditions. The proposed methodology is developed on a 3-bus system and then is applied to a modified IEEE 30-bus test system. The obtained results show the effectiveness of the proposed methodology in implementing the optimal load shedding satisfying social welfare by maintaining voltage stability margin (VSM) through technoeconomic analyses.

Network synchronization: optimal and pessimal scale-free topologies

Energy Technology Data Exchange (ETDEWEB)

Donetti, Luca [Departamento de Electronica y Tecnologia de Computadores and Instituto de Fisica Teorica y Computacional Carlos I, Facultad de Ciencias, Universidad de Granada, 18071 Granada (Spain); Hurtado, Pablo I; Munoz, Miguel A [Departamento de Electromagnetismo y Fisica de la Materia and Instituto Carlos I de Fisica Teorica y Computacional Facultad de Ciencias, Universidad de Granada, 18071 Granada (Spain)], E-mail: mamunoz@onsager.ugr.es

2008-06-06

By employing a recently introduced optimization algorithm we construct optimally synchronizable (unweighted) networks for any given scale-free degree distribution. We explore how the optimization process affects degree-degree correlations and observe a generic tendency toward disassortativity. Still, we show that there is not a one-to-one correspondence between synchronizability and disassortativity. On the other hand, we study the nature of optimally un-synchronizable networks, that is, networks whose topology minimizes the range of stability of the synchronous state. The resulting 'pessimal networks' turn out to have a highly assortative string-like structure. We also derive a rigorous lower bound for the Laplacian eigenvalue ratio controlling synchronizability, which helps understanding the impact of degree correlations on network synchronizability.

Probabilistic Cloning of Three Real States with Optimal Success Probabilities

Science.gov (United States)

Rui, Pin-shu

2017-06-01

We investigate the probabilistic quantum cloning (PQC) of three real states with average probability distribution. To get the analytic forms of the optimal success probabilities we assume that the three states have only two pairwise inner products. Based on the optimal success probabilities, we derive the explicit form of 1 →2 PQC for cloning three real states. The unitary operation needed in the PQC process is worked out too. The optimal success probabilities are also generalized to the M→ N PQC case.

A Nonlinear Fuel Optimal Reaction Jet Control Law

National Research Council Canada - National Science Library

Breitfeller, Eric

2002-01-01

We derive a nonlinear fuel optimal attitude control system (ACS) that drives the final state to the desired state according to a cost function that weights the final state angular error relative to the angular rate error...

Infinite-horizon optimal control problems in economics

International Nuclear Information System (INIS)

Aseev, Sergei M; Besov, Konstantin O; Kryazhimskii, Arkadii V

2012-01-01

This paper extends optimal control theory to a class of infinite-horizon problems that arise in studying models of optimal dynamic allocation of economic resources. In a typical problem of this sort the initial state is fixed, no constraints are imposed on the behaviour of the admissible trajectories at large times, and the objective functional is given by a discounted improper integral. We develop the method of finite-horizon approximations in a broad context and use it to derive complete versions of the Pontryagin maximum principle for such problems. We provide sufficient conditions for the normality of infinite-horizon optimal control problems and for the validity of the 'standard' limit transversality conditions with time going to infinity. As a meaningful example, we consider a new two-sector model of optimal economic growth subject to a random jump in prices. Bibliography: 53 titles.

The physics of an optimal basketball free throw

OpenAIRE

Barzykina, Irina

2017-01-01

A physical model is developed, which suggests a pathway to determining the optimal release conditions for a basketball free throw. Theoretical framework is supported by Monte Carlo simulations and a series of free throws performed and analysed at Southbank International School. The model defines a smile-shaped success region in angle-velocity space where a free throw will score. A formula for the minimum throwing angle is derived analytically. The optimal throwing conditions are determined nu...

The concept of 'optimal' path in classical mechanics

International Nuclear Information System (INIS)

Passos, E.J.V. de; Cruz, F.F. de S.

1986-01-01

The significance of the concept of 'optimal' path in the framework of classical mechanics is discussed. The derivation of the local harmonic approximation and self-consistent collective coordinate method equations of the optimal path is based on a careful study of the concepts of local maximal decoupling and global maximal decoupling respectively. This exhibits the nature of the differences between these two theories and allows one to establish the conditions under which they become equivalent. (author)

Techniques for optimizing nanotips derived from frozen taylor cones

Science.gov (United States)

Hirsch, Gregory

2017-12-05

Optimization techniques are disclosed for producing sharp and stable tips/nanotips relying on liquid Taylor cones created from electrically conductive materials with high melting points. A wire substrate of such a material with a preform end in the shape of a regular or concave cone, is first melted with a focused laser beam. Under the influence of a high positive potential, a Taylor cone in a liquid/molten state is formed at that end. The cone is then quenched upon cessation of the laser power, thus freezing the Taylor cone. The tip of the frozen Taylor cone is reheated by the laser to allow its precise localized melting and shaping. Tips thus obtained yield desirable end-forms suitable as electron field emission sources for a variety of applications. In-situ regeneration of the tip is readily accomplished. These tips can also be employed as regenerable bright ion sources using field ionization/desorption of introduced chemical species.

Study on optimal performance and working temperatures of endoreversible forward and reverse Carnot cycles

Energy Technology Data Exchange (ETDEWEB)

Chen, W.Z.; Sun, F.R.; Cheng, S.M.; Chen, L.G. [Huazhong Univ. of Sceince and Technology, Wuhan (China). Dept. of Power Engineering

1995-12-01

The connection between the expressions of optimization performances of Carnot heat engines, refrigerators and heat pumps, which operate subject to irreversible heat flow, is studied. We consider the endoreversible forward and reverse. Carnot cycles and analyse the expressions which relate efficiency, refrigeration and heating coefficients to power, refrigeration and heating rates, respectively. It is found and proved that when one of the optimal relations is derived the others are also determined, and give the unified formulation of the related optimal working temperatures of the forward and reverse Carnot cycles by isentropic temperature ratio exponent. Finally, several new optimal performance relations are derived for forward and reverse Carnot cycles under nonlinear heat transfer, and some major results in the references are easily deduced and unified in this paper. (author)

A Collaborative Neurodynamic Approach to Multiple-Objective Distributed Optimization.

Science.gov (United States)

Yang, Shaofu; Liu, Qingshan; Wang, Jun

2018-04-01

This paper is concerned with multiple-objective distributed optimization. Based on objective weighting and decision space decomposition, a collaborative neurodynamic approach to multiobjective distributed optimization is presented. In the approach, a system of collaborative neural networks is developed to search for Pareto optimal solutions, where each neural network is associated with one objective function and given constraints. Sufficient conditions are derived for ascertaining the convergence to a Pareto optimal solution of the collaborative neurodynamic system. In addition, it is proved that each connected subsystem can generate a Pareto optimal solution when the communication topology is disconnected. Then, a switching-topology-based method is proposed to compute multiple Pareto optimal solutions for discretized approximation of Pareto front. Finally, simulation results are discussed to substantiate the performance of the collaborative neurodynamic approach. A portfolio selection application is also given.

Multi-Objective Optimization in Physical Synthesis of Integrated Circuits

CERN Document Server

A Papa, David

2013-01-01

This book introduces techniques that advance the capabilities and strength of modern software tools for physical synthesis, with the ultimate goal to improve the quality of leading-edge semiconductor products.  It provides a comprehensive introduction to physical synthesis and takes the reader methodically from first principles through state-of-the-art optimizations used in cutting edge industrial tools. It explains how to integrate chip optimizations in novel ways to create powerful circuit transformations that help satisfy performance requirements. Broadens the scope of physical synthesis optimization to include accurate transformations operating between the global and local scales; Integrates groups of related transformations to break circular dependencies and increase the number of circuit elements that can be jointly optimized to escape local minima;  Derives several multi-objective optimizations from first observations through complete algorithms and experiments; Describes integrated optimization te...

Optimal Investment and Reinsurance for Insurers with Uncertain Time-Horizon

Directory of Open Access Journals (Sweden)

Ailing Gu

2014-01-01

state hits the barrier. The objective of the insurer is to maximize the expected discounted exponential utility of her terminal wealth. By dynamic programming approach and Feynman-Kac representation theorem, we derive the expressions for optimal value functions and optimal investment-reinsurance strategies in two special cases. Furthermore, an example is considered under the diffusion-approximation model, which shows some interesting results.

A multidimensional pseudospectral method for optimal control of quantum ensembles

International Nuclear Information System (INIS)

Ruths, Justin; Li, Jr-Shin

2011-01-01

In our previous work, we have shown that the pseudospectral method is an effective and flexible computation scheme for deriving pulses for optimal control of quantum systems. In practice, however, quantum systems often exhibit variation in the parameters that characterize the system dynamics. This leads us to consider the control of an ensemble (or continuum) of quantum systems indexed by the system parameters that show variation. We cast the design of pulses as an optimal ensemble control problem and demonstrate a multidimensional pseudospectral method with several challenging examples of both closed and open quantum systems from nuclear magnetic resonance spectroscopy in liquid. We give particular attention to the ability to derive experimentally viable pulses of minimum energy or duration.

Optimal Cross-Layer Design for Energy Efficient D2D Sharing Systems

KAUST Repository

Alabbasi, Abdulrahman

2016-11-23

In this paper, we propose a cross-layer design, which optimizes the energy efficiency of a potential future 5G spectrum-sharing environment, in two sharing scenarios. In the first scenario, underlying sharing is considered. We propose and minimize a modified energy per good bit (MEPG) metric, with respect to the spectrum sharing user’s transmission power and media access frame length. The cellular users, legacy users, are protected by an outage probability constraint. To optimize the non-convex targeted problem, we utilize the generalized convexity theory and verify the problem’s strictly pseudoconvex structure. We also derive analytical expressions of the optimal resources. In the second scenario, we minimize a generalized MEPG function while considering a probabilistic activity of cellular users and its impact on the MEPG performance of the spectrum sharing users. Finally, we derive the associated optimal resource allocation of this problem. Selected numerical results show the improvement of the proposed system compared with other systems.

Image denoising: Learning the noise model via nonsmooth PDE-constrained optimization

KAUST Repository

Reyes, Juan Carlos De los

2013-11-01

We propose a nonsmooth PDE-constrained optimization approach for the determination of the correct noise model in total variation (TV) image denoising. An optimization problem for the determination of the weights corresponding to different types of noise distributions is stated and existence of an optimal solution is proved. A tailored regularization approach for the approximation of the optimal parameter values is proposed thereafter and its consistency studied. Additionally, the differentiability of the solution operator is proved and an optimality system characterizing the optimal solutions of each regularized problem is derived. The optimal parameter values are numerically computed by using a quasi-Newton method, together with semismooth Newton type algorithms for the solution of the TV-subproblems. © 2013 American Institute of Mathematical Sciences.

Image denoising: Learning the noise model via nonsmooth PDE-constrained optimization

KAUST Repository

Reyes, Juan Carlos De los; Schö nlieb, Carola-Bibiane

2013-01-01

We propose a nonsmooth PDE-constrained optimization approach for the determination of the correct noise model in total variation (TV) image denoising. An optimization problem for the determination of the weights corresponding to different types of noise distributions is stated and existence of an optimal solution is proved. A tailored regularization approach for the approximation of the optimal parameter values is proposed thereafter and its consistency studied. Additionally, the differentiability of the solution operator is proved and an optimality system characterizing the optimal solutions of each regularized problem is derived. The optimal parameter values are numerically computed by using a quasi-Newton method, together with semismooth Newton type algorithms for the solution of the TV-subproblems. © 2013 American Institute of Mathematical Sciences.

Accelerated Optimization in the PDE Framework: Formulations for the Manifold of Diffeomorphisms

KAUST Repository

Sundaramoorthi, Ganesh

2018-04-04

We consider the problem of optimization of cost functionals on the infinite-dimensional manifold of diffeomorphisms. We present a new class of optimization methods, valid for any optimization problem setup on the space of diffeomorphisms by generalizing Nesterov accelerated optimization to the manifold of diffeomorphisms. While our framework is general for infinite dimensional manifolds, we specifically treat the case of diffeomorphisms, motivated by optical flow problems in computer vision. This is accomplished by building on a recent variational approach to a general class of accelerated optimization methods by Wibisono, Wilson and Jordan, which applies in finite dimensions. We generalize that approach to infinite dimensional manifolds. We derive the surprisingly simple continuum evolution equations, which are partial differential equations, for accelerated gradient descent, and relate it to simple mechanical principles from fluid mechanics. Our approach has natural connections to the optimal mass transport problem. This is because one can think of our approach as an evolution of an infinite number of particles endowed with mass (represented with a mass density) that moves in an energy landscape. The mass evolves with the optimization variable, and endows the particles with dynamics. This is different than the finite dimensional case where only a single particle moves and hence the dynamics does not depend on the mass. We derive the theory, compute the PDEs for accelerated optimization, and illustrate the behavior of these new accelerated optimization schemes.

Accelerated Optimization in the PDE Framework: Formulations for the Manifold of Diffeomorphisms

KAUST Repository

Sundaramoorthi, Ganesh; Yezzi, Anthony

2018-01-01

We consider the problem of optimization of cost functionals on the infinite-dimensional manifold of diffeomorphisms. We present a new class of optimization methods, valid for any optimization problem setup on the space of diffeomorphisms by generalizing Nesterov accelerated optimization to the manifold of diffeomorphisms. While our framework is general for infinite dimensional manifolds, we specifically treat the case of diffeomorphisms, motivated by optical flow problems in computer vision. This is accomplished by building on a recent variational approach to a general class of accelerated optimization methods by Wibisono, Wilson and Jordan, which applies in finite dimensions. We generalize that approach to infinite dimensional manifolds. We derive the surprisingly simple continuum evolution equations, which are partial differential equations, for accelerated gradient descent, and relate it to simple mechanical principles from fluid mechanics. Our approach has natural connections to the optimal mass transport problem. This is because one can think of our approach as an evolution of an infinite number of particles endowed with mass (represented with a mass density) that moves in an energy landscape. The mass evolves with the optimization variable, and endows the particles with dynamics. This is different than the finite dimensional case where only a single particle moves and hence the dynamics does not depend on the mass. We derive the theory, compute the PDEs for accelerated optimization, and illustrate the behavior of these new accelerated optimization schemes.

Temperature Scaling Law for Quantum Annealing Optimizers.

Science.gov (United States)

Albash, Tameem; Martin-Mayor, Victor; Hen, Itay

2017-09-15

Physical implementations of quantum annealing unavoidably operate at finite temperatures. We point to a fundamental limitation of fixed finite temperature quantum annealers that prevents them from functioning as competitive scalable optimizers and show that to serve as optimizers annealer temperatures must be appropriately scaled down with problem size. We derive a temperature scaling law dictating that temperature must drop at the very least in a logarithmic manner but also possibly as a power law with problem size. We corroborate our results by experiment and simulations and discuss the implications of these to practical annealers.

Optimal Control of Heterogeneous Systems with Endogenous Domain of Heterogeneity

International Nuclear Information System (INIS)

Belyakov, Anton O.; Tsachev, Tsvetomir; Veliov, Vladimir M.

2011-01-01

The paper deals with optimal control of heterogeneous systems, that is, families of controlled ODEs parameterized by a parameter running over a domain called domain of heterogeneity. The main novelty in the paper is that the domain of heterogeneity is endogenous: it may depend on the control and on the state of the system. This extension is crucial for several economic applications and turns out to rise interesting mathematical problems. A necessary optimality condition is derived, where one of the adjoint variables satisfies a differential inclusion (instead of equation) and the maximization of the Hamiltonian takes the form of “min-max”. As a consequence, a Pontryagin-type maximum principle is obtained under certain regularity conditions for the optimal control. A formula for the derivative of the objective function with respect to the control from L ∞ is presented together with a sufficient condition for its existence. A stylized economic example is investigated analytically and numerically.

A modular approach to large-scale design optimization of aerospace systems

Science.gov (United States)

Hwang, John T.

Gradient-based optimization and the adjoint method form a synergistic combination that enables the efficient solution of large-scale optimization problems. Though the gradient-based approach struggles with non-smooth or multi-modal problems, the capability to efficiently optimize up to tens of thousands of design variables provides a valuable design tool for exploring complex tradeoffs and finding unintuitive designs. However, the widespread adoption of gradient-based optimization is limited by the implementation challenges for computing derivatives efficiently and accurately, particularly in multidisciplinary and shape design problems. This thesis addresses these difficulties in two ways. First, to deal with the heterogeneity and integration challenges of multidisciplinary problems, this thesis presents a computational modeling framework that solves multidisciplinary systems and computes their derivatives in a semi-automated fashion. This framework is built upon a new mathematical formulation developed in this thesis that expresses any computational model as a system of algebraic equations and unifies all methods for computing derivatives using a single equation. The framework is applied to two engineering problems: the optimization of a nanosatellite with 7 disciplines and over 25,000 design variables; and simultaneous allocation and mission optimization for commercial aircraft involving 330 design variables, 12 of which are integer variables handled using the branch-and-bound method. In both cases, the framework makes large-scale optimization possible by reducing the implementation effort and code complexity. The second half of this thesis presents a differentiable parametrization of aircraft geometries and structures for high-fidelity shape optimization. Existing geometry parametrizations are not differentiable, or they are limited in the types of shape changes they allow. This is addressed by a novel parametrization that smoothly interpolates aircraft

Optimal Pid Controller Design Using Adaptive Vurpso Algorithm

Science.gov (United States)

Zirkohi, Majid Moradi

2015-04-01

The purpose of this paper is to improve theVelocity Update Relaxation Particle Swarm Optimization algorithm (VURPSO). The improved algorithm is called Adaptive VURPSO (AVURPSO) algorithm. Then, an optimal design of a Proportional-Integral-Derivative (PID) controller is obtained using the AVURPSO algorithm. An adaptive momentum factor is used to regulate a trade-off between the global and the local exploration abilities in the proposed algorithm. This operation helps the system to reach the optimal solution quickly and saves the computation time. Comparisons on the optimal PID controller design confirm the superiority of AVURPSO algorithm to the optimization algorithms mentioned in this paper namely the VURPSO algorithm, the Ant Colony algorithm, and the conventional approach. Comparisons on the speed of convergence confirm that the proposed algorithm has a faster convergence in a less computation time to yield a global optimum value. The proposed AVURPSO can be used in the diverse areas of optimization problems such as industrial planning, resource allocation, scheduling, decision making, pattern recognition and machine learning. The proposed AVURPSO algorithm is efficiently used to design an optimal PID controller.

Regression analysis as a design optimization tool

Science.gov (United States)

Perley, R.

1984-01-01

The optimization concepts are described in relation to an overall design process as opposed to a detailed, part-design process where the requirements are firmly stated, the optimization criteria are well established, and a design is known to be feasible. The overall design process starts with the stated requirements. Some of the design criteria are derived directly from the requirements, but others are affected by the design concept. It is these design criteria that define the performance index, or objective function, that is to be minimized within some constraints. In general, there will be multiple objectives, some mutually exclusive, with no clear statement of their relative importance. The optimization loop that is given adjusts the design variables and analyzes the resulting design, in an iterative fashion, until the objective function is minimized within the constraints. This provides a solution, but it is only the beginning. In effect, the problem definition evolves as information is derived from the results. It becomes a learning process as we determine what the physics of the system can deliver in relation to the desirable system characteristics. As with any learning process, an interactive capability is a real attriubute for investigating the many alternatives that will be suggested as learning progresses.

Defending against the Advanced Persistent Threat: An Optimal Control Approach

Directory of Open Access Journals (Sweden)

Pengdeng Li

2018-01-01

Full Text Available The new cyberattack pattern of advanced persistent threat (APT has posed a serious threat to modern society. This paper addresses the APT defense problem, that is, the problem of how to effectively defend against an APT campaign. Based on a novel APT attack-defense model, the effectiveness of an APT defense strategy is quantified. Thereby, the APT defense problem is modeled as an optimal control problem, in which an optimal control stands for a most effective APT defense strategy. The existence of an optimal control is proved, and an optimality system is derived. Consequently, an optimal control can be figured out by solving the optimality system. Some examples of the optimal control are given. Finally, the influence of some factors on the effectiveness of an optimal control is examined through computer experiments. These findings help organizations to work out policies of defending against APTs.

LMI optimization approach to stabilization of time-delay chaotic systems

International Nuclear Information System (INIS)

Park, Ju H.; Kwon, O.M.

2005-01-01

Based on the Lyapunov stability theory and linear matrix inequality (LMI) technique, this paper proposes a novel control method for stabilization of a class of time-delay chaotic systems. A stabilization criterion is derived in terms of LMIs which can be easily solved by efficient convex optimization algorithms. A numerical example is included to show the advantage of the result derived

Necessary and Sufficient Conditions for Pareto Optimality in Infinite Horizon Cooperative Differential Games - Replaced by CentER DP 2011-041

NARCIS (Netherlands)

Reddy, P.V.; Engwerda, J.C.

2010-01-01

In this article we derive necessary and sufficient conditions for the existence of Pareto optimal solutions for an N player cooperative infinite horizon differential game. Firstly, we write the problem of finding Pareto candidates as solving N constrained optimal control subproblems. We derive some

Topology optimization of hyperelastic structures using a level set method

Science.gov (United States)

Chen, Feifei; Wang, Yiqiang; Wang, Michael Yu; Zhang, Y. F.

2017-12-01

Soft rubberlike materials, due to their inherent compliance, are finding widespread implementation in a variety of applications ranging from assistive wearable technologies to soft material robots. Structural design of such soft and rubbery materials necessitates the consideration of large nonlinear deformations and hyperelastic material models to accurately predict their mechanical behaviour. In this paper, we present an effective level set-based topology optimization method for the design of hyperelastic structures that undergo large deformations. The method incorporates both geometric and material nonlinearities where the strain and stress measures are defined within the total Lagrange framework and the hyperelasticity is characterized by the widely-adopted Mooney-Rivlin material model. A shape sensitivity analysis is carried out, in the strict sense of the material derivative, where the high-order terms involving the displacement gradient are retained to ensure the descent direction. As the design velocity enters into the shape derivative in terms of its gradient and divergence terms, we develop a discrete velocity selection strategy. The whole optimization implementation undergoes a two-step process, where the linear optimization is first performed and its optimized solution serves as the initial design for the subsequent nonlinear optimization. It turns out that this operation could efficiently alleviate the numerical instability and facilitate the optimization process. To demonstrate the validity and effectiveness of the proposed method, three compliance minimization problems are studied and their optimized solutions present significant mechanical benefits of incorporating the nonlinearities, in terms of remarkable enhancement in not only the structural stiffness but also the critical buckling load.

Optimization Technology of the LHS-1 Strain for Degrading Gallnut Water Extract and Appraisal of Benzene Ring Derivatives from Fermented Gallnut Water Extract Pyrolysis by Py-GC/MS

Directory of Open Access Journals (Sweden)

Chengzhang Wang

2017-12-01

Full Text Available Gallnut water extract (GWE enriches 80~90% of gallnut tannic acid (TA. In order to study the biodegradation of GWE into gallic acid (GA, the LHS-1 strain, a variant of Aspergillus niger, was chosen to determine the optimal degradation parameters for maximum production of GA by the response surface method. Pyrolysis–gas chromatography–mass spectrometry (Py-GC/MS was first applied to appraise benzene ring derivatives of fermented GWE (FGWE pyrolysis by comparison with the pyrolytic products of a tannic acid standard sample (TAS and GWE. The results showed that optimum conditions were at 31 °C and pH of 5, with a 50-h incubation period and 0.1 g·L−1 of TA as substrate. The maximum yields of GA and tannase were 63~65 mg·mL−1 and 1.17 U·mL−1, respectively. Over 20 kinds of compounds were identified as linear hydrocarbons and benzene ring derivatives based on GA and glucose. The key benzene ring derivatives were 3,4,5-trimethoxybenzoic acid methyl ester, 3-methoxy-1,2-benzenediol, and 4-hydroxy-3,5-dimethoxy-benzoic acid hydrazide.

Optimization Technology of the LHS-1 Strain for Degrading Gallnut Water Extract and Appraisal of Benzene Ring Derivatives from Fermented Gallnut Water Extract Pyrolysis by Py-GC/MS.

Science.gov (United States)

Wang, Chengzhang; Li, Wenjun

2017-12-20

Gallnut water extract (GWE) enriches 80~90% of gallnut tannic acid (TA). In order to study the biodegradation of GWE into gallic acid (GA), the LHS-1 strain, a variant of Aspergillus niger , was chosen to determine the optimal degradation parameters for maximum production of GA by the response surface method. Pyrolysis-gas chromatography-mass spectrometry (Py-GC/MS) was first applied to appraise benzene ring derivatives of fermented GWE (FGWE) pyrolysis by comparison with the pyrolytic products of a tannic acid standard sample (TAS) and GWE. The results showed that optimum conditions were at 31 °C and pH of 5, with a 50-h incubation period and 0.1 g·L -1 of TA as substrate. The maximum yields of GA and tannase were 63~65 mg·mL -1 and 1.17 U·mL -1 , respectively. Over 20 kinds of compounds were identified as linear hydrocarbons and benzene ring derivatives based on GA and glucose. The key benzene ring derivatives were 3,4,5-trimethoxybenzoic acid methyl ester, 3-methoxy-1,2-benzenediol, and 4-hydroxy-3,5-dimethoxy-benzoic acid hydrazide.

Optimal Bilinear Control of Gross--Pitaevskii Equations

KAUST Repository

Hintermü ller, Michael; Marahrens, Daniel; Markowich, Peter A.; Sparber, Christof

2013-01-01

A mathematical framework for optimal bilinear control of nonlinear Schrödinger equations of Gross--Pitaevskii type arising in the description of Bose--Einstein condensates is presented. The obtained results generalize earlier efforts found in the literature in several aspects. In particular, the cost induced by the physical workload over the control process is taken into account rather than the often used L^2- or H^1-norms for the cost of the control action. Well-posedness of the problem and existence of an optimal control are proved. In addition, the first order optimality system is rigorously derived. Also a numerical solution method is proposed, which is based on a Newton-type iteration, and used to solve several coherent quantum control problems.

Optimal policies of non-cross-resistant chemotherapy on Goldie and Coldman's cancer model.

Science.gov (United States)

Chen, Jeng-Huei; Kuo, Ya-Hui; Luh, Hsing Paul

2013-10-01

Mathematical models can be used to study the chemotherapy on tumor cells. Especially, in 1979, Goldie and Coldman proposed the first mathematical model to relate the drug sensitivity of tumors to their mutation rates. Many scientists have since referred to this pioneering work because of its simplicity and elegance. Its original idea has also been extended and further investigated in massive follow-up studies of cancer modeling and optimal treatment. Goldie and Coldman, together with Guaduskas, later used their model to explain why an alternating non-cross-resistant chemotherapy is optimal with a simulation approach. Subsequently in 1983, Goldie and Coldman proposed an extended stochastic based model and provided a rigorous mathematical proof to their earlier simulation work when the extended model is approximated by its quasi-approximation. However, Goldie and Coldman's analytic study of optimal treatments majorly focused on a process with symmetrical parameter settings, and presented few theoretical results for asymmetrical settings. In this paper, we recast and restate Goldie, Coldman, and Guaduskas' model as a multi-stage optimization problem. Under an asymmetrical assumption, the conditions under which a treatment policy can be optimal are derived. The proposed framework enables us to consider some optimal policies on the model analytically. In addition, Goldie, Coldman and Guaduskas' work with symmetrical settings can be treated as a special case of our framework. Based on the derived conditions, this study provides an alternative proof to Goldie and Coldman's work. In addition to the theoretical derivation, numerical results are included to justify the correctness of our work. Copyright © 2013 Elsevier Inc. All rights reserved.

Infinite-horizon optimal control problems in economics

Energy Technology Data Exchange (ETDEWEB)

Aseev, Sergei M; Besov, Konstantin O; Kryazhimskii, Arkadii V

2012-04-30

This paper extends optimal control theory to a class of infinite-horizon problems that arise in studying models of optimal dynamic allocation of economic resources. In a typical problem of this sort the initial state is fixed, no constraints are imposed on the behaviour of the admissible trajectories at large times, and the objective functional is given by a discounted improper integral. We develop the method of finite-horizon approximations in a broad context and use it to derive complete versions of the Pontryagin maximum principle for such problems. We provide sufficient conditions for the normality of infinite-horizon optimal control problems and for the validity of the 'standard' limit transversality conditions with time going to infinity. As a meaningful example, we consider a new two-sector model of optimal economic growth subject to a random jump in prices. Bibliography: 53 titles.

Automatic differentiation for gradient-based optimization of radiatively heated microelectronics manufacturing equipment

Energy Technology Data Exchange (ETDEWEB)

Moen, C.D.; Spence, P.A.; Meza, J.C.; Plantenga, T.D.

1996-12-31

Automatic differentiation is applied to the optimal design of microelectronic manufacturing equipment. The performance of nonlinear, least-squares optimization methods is compared between numerical and analytical gradient approaches. The optimization calculations are performed by running large finite-element codes in an object-oriented optimization environment. The Adifor automatic differentiation tool is used to generate analytic derivatives for the finite-element codes. The performance results support previous observations that automatic differentiation becomes beneficial as the number of optimization parameters increases. The increase in speed, relative to numerical differences, has a limited value and results are reported for two different analysis codes.

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...

Topology optimization and lattice Boltzmann methods

DEFF Research Database (Denmark)

Nørgaard, Sebastian Arlund

This thesis demonstrates the application of the lattice Boltzmann method for topology optimization problems. Specifically, the focus is on problems in which time-dependent flow dynamics have significant impact on the performance of the devices to be optimized. The thesis introduces new topology...... a discrete adjoint approach. To handle the complexity of the discrete adjoint approach more easily, a method for computing it based on automatic differentiation is introduced, which can be adapted to any lattice Boltzmann type method. For example, while it is derived in the context of an isothermal lattice...... Boltzmann model, it is shown that the method can be easily extended to a thermal model as well. Finally, the predicted behavior of an optimized design is compared to the equiva-lent prediction from a commercial finite element solver. It is found that the weakly compressible nature of the lattice Boltzmann...

Optimizing Performance Parameters of Chemically-Derived Graphene/p-Si Heterojunction Solar Cell.

Science.gov (United States)

Batra, Kamal; Nayak, Sasmita; Behura, Sanjay K; Jani, Omkar

2015-07-01

Chemically-derived graphene have been synthesized by modified Hummers method and reduced using sodium borohydride. To explore the potential for photovoltaic applications, graphene/p-silicon (Si) heterojunction devices were fabricated using a simple and cost effective technique called spin coating. The SEM analysis shows the formation of graphene oxide (GO) flakes which become smooth after reduction. The absence of oxygen containing functional groups, as observed in FT-IR spectra, reveals the reduction of GO, i.e., reduced graphene oxide (rGO). It was further confirmed by Raman analysis, which shows slight reduction in G-band intensity with respect to D-band. Hall effect measurement confirmed n-type nature of rGO. Therefore, an effort has been made to simu- late rGO/p-Si heterojunction device by using the one-dimensional solar cell capacitance software, considering the experimentally derived parameters. The detail analysis of the effects of Si thickness, graphene thickness and temperature on the performance of the device has been presented.

Constrained optimization of test intervals using a steady-state genetic algorithm

International Nuclear Information System (INIS)

Martorell, S.; Carlos, S.; Sanchez, A.; Serradell, V.

2000-01-01

There is a growing interest from both the regulatory authorities and the nuclear industry to stimulate the use of Probabilistic Risk Analysis (PRA) for risk-informed applications at Nuclear Power Plants (NPPs). Nowadays, special attention is being paid on analyzing plant-specific changes to Test Intervals (TIs) within the Technical Specifications (TSs) of NPPs and it seems to be a consensus on the need of making these requirements more risk-effective and less costly. Resource versus risk-control effectiveness principles formally enters in optimization problems. This paper presents an approach for using the PRA models in conducting the constrained optimization of TIs based on a steady-state genetic algorithm (SSGA) where the cost or the burden is to be minimized while the risk or performance is constrained to be at a given level, or vice versa. The paper encompasses first with the problem formulation, where the objective function and constraints that apply in the constrained optimization of TIs based on risk and cost models at system level are derived. Next, the foundation of the optimizer is given, which is derived by customizing a SSGA in order to allow optimizing TIs under constraints. Also, a case study is performed using this approach, which shows the benefits of adopting both PRA models and genetic algorithms, in particular for the constrained optimization of TIs, although it is also expected a great benefit of using this approach to solve other engineering optimization problems. However, care must be taken in using genetic algorithms in constrained optimization problems as it is concluded in this paper

OPTIMAL CORRELATION ESTIMATORS FOR QUANTIZED SIGNALS

International Nuclear Information System (INIS)

Johnson, M. D.; Chou, H. H.; Gwinn, C. R.

2013-01-01

Using a maximum-likelihood criterion, we derive optimal correlation strategies for signals with and without digitization. We assume that the signals are drawn from zero-mean Gaussian distributions, as is expected in radio-astronomical applications, and we present correlation estimators both with and without a priori knowledge of the signal variances. We demonstrate that traditional estimators of correlation, which rely on averaging products, exhibit large and paradoxical noise when the correlation is strong. However, we also show that these estimators are fully optimal in the limit of vanishing correlation. We calculate the bias and noise in each of these estimators and discuss their suitability for implementation in modern digital correlators.

OPTIMAL CORRELATION ESTIMATORS FOR QUANTIZED SIGNALS

Energy Technology Data Exchange (ETDEWEB)

Johnson, M. D.; Chou, H. H.; Gwinn, C. R., E-mail: michaeltdh@physics.ucsb.edu, E-mail: cgwinn@physics.ucsb.edu [Department of Physics, University of California, Santa Barbara, CA 93106 (United States)

2013-03-10

Using a maximum-likelihood criterion, we derive optimal correlation strategies for signals with and without digitization. We assume that the signals are drawn from zero-mean Gaussian distributions, as is expected in radio-astronomical applications, and we present correlation estimators both with and without a priori knowledge of the signal variances. We demonstrate that traditional estimators of correlation, which rely on averaging products, exhibit large and paradoxical noise when the correlation is strong. However, we also show that these estimators are fully optimal in the limit of vanishing correlation. We calculate the bias and noise in each of these estimators and discuss their suitability for implementation in modern digital correlators.

CT radiation dose and image quality optimization using a porcine model.

Science.gov (United States)

Zarb, Francis; McEntee, Mark F; Rainford, Louise

2013-01-01

To evaluate potential radiation dose savings and resultant image quality effects with regard to optimization of commonly performed computed tomography (CT) studies derived from imaging a porcine (pig) model. Imaging protocols for 4 clinical CT suites were developed based on the lowest milliamperage and kilovoltage, the highest pitch that could be set from current imaging protocol parameters, or both. This occurred before significant changes in noise, contrast, and spatial resolution were measured objectively on images produced from a quality assurance CT phantom. The current and derived phantom protocols were then applied to scan a porcine model for head, abdomen, and chest CT studies. Further optimized protocols were developed based on the same methodology as in the phantom study. The optimization achieved with respect to radiation dose and image quality was evaluated following data collection of radiation dose recordings and image quality review. Relative visual grading analysis of image quality criteria adapted from the European guidelines on radiology quality criteria for CT were used for studies completed with both the phantom-based or porcine-derived imaging protocols. In 5 out of 16 experimental combinations, the current clinical protocol was maintained. In 2 instances, the phantom protocol reduced radiation dose by 19% to 38%. In the remaining 9 instances, the optimization based on the porcine model further reduced radiation dose by 17% to 38%. The porcine model closely reflects anatomical structures in humans, allowing the grading of anatomical criteria as part of image quality review without radiation risks to human subjects. This study demonstrates that using a porcine model to evaluate CT optimization resulted in more radiation dose reduction than when imaging protocols were tested solely on quality assurance phantoms.

Optimization of a Compton-suppression system by escape-peak ratio

International Nuclear Information System (INIS)

Niu, H.; Chao, J.H.; Wu, S.-C.

1996-01-01

A Compton-suppression system consisting of an HPGe central detector surrounded by eight BGO scintillators in an annular geometry was assembled. This system is dedicated to in-beam γ-ray measurements. The ratios of full-energy to single-escape peak and full-energy of double-escape peak, at γ-rays of 2754, 4443 and 6130 keV, were used to derive associated suppression factors in order to optimize detection conditions of the system. The suppression factors derived both from the escape peak ratios and the corresponding peak-to-Compton ratios of the γ-ray spectra are compared and discussed. This optimization technique may be of great significance for analyzing complicated spectra, where high-energy γ-rays are considered for analytical use. (Author)

On the Determinants of Optimal Border Taxes for a Small Open Economy

DEFF Research Database (Denmark)

Munk, Knud Jørgen; Rasmussen, Bo Sandemann

of the primary factor and domestic consumption of the export good cannot be taxed is nevertheless a constraint; this insight provides the key to understanding what determines the optimal tariff structure. The optimal border tax structure is derived for both exogenous and endogenous labour supply, and the results...... are interpreted in the spirit of the Corlett-Hague results for the optimal tax structure in a closed economy and compared with results from CGE models....

A Pilot Study Assessing ECG versus ECHO Ventriculoventricular Optimization in Pediatric Resynchronization Patients.

Science.gov (United States)

Punn, Rajesh; Hanisch, Debra; Motonaga, Kara S; Rosenthal, David N; Ceresnak, Scott R; Dubin, Anne M

2016-02-01

Cardiac resynchronization therapy indications and management are well described in adults. Echocardiography (ECHO) has been used to optimize mechanical synchrony in these patients; however, there are issues with reproducibility and time intensity. Pediatric patients add challenges, with diverse substrates and limited capacity for cooperation. Electrocardiographic (ECG) methods to assess electrical synchrony are expeditious but have not been extensively studied in children. We sought to compare ECHO and ECG CRT optimization in children. Prospective, pediatric, single-center cross-over trial comparing ECHO and ECG optimization with CRT. Patients were assigned to undergo either ECHO or ECG optimization, followed for 6 months, and crossed-over to the other assignment for another 6 months. ECHO pulsed-wave tissue Doppler and 12-lead ECG were obtained for 5 VV delays. ECG optimization was defined as the shortest QRSD and ECHO optimization as the lowest dyssynchrony index. ECHOs/ECGs were interpreted by readers blinded to optimization technique. After each 6 month period, these data were collected: ejection fraction, velocimetry-derived cardiac index, quality of life, ECHO-derived stroke distance, M-mode dyssynchrony, study cost, and time. Outcomes for each optimization method were compared. From June 2012 to December 2013, 19 patients enrolled. Mean age was 9.1 ± 4.3 years; 14 (74%) had structural heart disease. The mean time for optimization was shorter using ECG than ECHO (9 ± 1 min vs. 68 ± 13 min, P cost for charges was $4,400 ± 700 less for ECG. No other outcome differed between groups. ECHO optimization of synchrony was not superior to ECG optimization in this pilot study. ECG optimization required less time and cost than ECHO optimization. © 2015 Wiley Periodicals, Inc.

Optimal phase estimation with arbitrary a priori knowledge

International Nuclear Information System (INIS)

Demkowicz-Dobrzanski, Rafal

2011-01-01

The optimal-phase estimation strategy is derived when partial a priori knowledge on the estimated phase is available. The solution is found with the help of the most famous result from the entanglement theory: the positive partial transpose criterion. The structure of the optimal measurements, estimators, and the optimal probe states is analyzed. This Rapid Communication provides a unified framework bridging the gap in the literature on the subject which until now dealt almost exclusively with two extreme cases: almost perfect knowledge (local approach based on Fisher information) and no a priori knowledge (global approach based on covariant measurements). Special attention is paid to a natural a priori probability distribution arising from a diffusion process.

Power Link Optimization for a Neurostimulator in Nasal Cavity

Directory of Open Access Journals (Sweden)

Seunghyun Lee

2017-01-01

Full Text Available This paper examines system optimization for wirelessly powering a small implant embedded in tissue. For a given small receiver in a multilayer tissue model, the transmitter is abstracted as a sheet of tangential current density for which the optimal distribution is analytically found. This proposes a new design methodology for wireless power transfer systems. That is, from the optimal current distribution, the maximum achievable efficiency is derived first. Next, various design parameters are determined to achieve the target efficiency. Based on this design methodology, a centimeter-sized neurostimulator inside the nasal cavity is demonstrated. For this centimeter-sized implant, the optimal distribution resembles that of a coil source and the optimal frequency is around 15 MHz. While the existing solution showed an efficiency of about 0.3 percent, the proposed system could enhance the efficiency fivefold.

Optimal design and uncertainty quantification in blood flow simulations for congenital heart disease

Science.gov (United States)

Marsden, Alison

2009-11-01

Recent work has demonstrated substantial progress in capabilities for patient-specific cardiovascular flow simulations. Recent advances include increasingly complex geometries, physiological flow conditions, and fluid structure interaction. However inputs to these simulations, including medical image data, catheter-derived pressures and material properties, can have significant uncertainties associated with them. For simulations to predict clinically useful and reliable output information, it is necessary to quantify the effects of input uncertainties on outputs of interest. In addition, blood flow simulation tools can now be efficiently coupled to shape optimization algorithms for surgery design applications, and these tools should incorporate uncertainty information. We present a unified framework to systematically and efficient account for uncertainties in simulations using adaptive stochastic collocation. In addition, we present a framework for derivative-free optimization of cardiovascular geometries, and layer these tools to perform optimization under uncertainty. These methods are demonstrated using simulations and surgery optimization to improve hemodynamics in pediatric cardiology applications.

Trajectory planning of mobile robots using indirect solution of optimal control method in generalized point-to-point task

Science.gov (United States)

Nazemizadeh, M.; Rahimi, H. N.; Amini Khoiy, K.

2012-03-01

This paper presents an optimal control strategy for optimal trajectory planning of mobile robots by considering nonlinear dynamic model and nonholonomic constraints of the system. The nonholonomic constraints of the system are introduced by a nonintegrable set of differential equations which represent kinematic restriction on the motion. The Lagrange's principle is employed to derive the nonlinear equations of the system. Then, the optimal path planning of the mobile robot is formulated as an optimal control problem. To set up the problem, the nonlinear equations of the system are assumed as constraints, and a minimum energy objective function is defined. To solve the problem, an indirect solution of the optimal control method is employed, and conditions of the optimality derived as a set of coupled nonlinear differential equations. The optimality equations are solved numerically, and various simulations are performed for a nonholonomic mobile robot to illustrate effectiveness of the proposed method.

Optimal quantum control of Bose-Einstein condensates in magnetic microtraps: Comparison of gradient-ascent-pulse-engineering and Krotov optimization schemes

Science.gov (United States)

Jäger, Georg; Reich, Daniel M.; Goerz, Michael H.; Koch, Christiane P.; Hohenester, Ulrich

2014-09-01

We study optimal quantum control of the dynamics of trapped Bose-Einstein condensates: The targets are to split a condensate, residing initially in a single well, into a double well, without inducing excitation, and to excite a condensate from the ground state to the first-excited state of a single well. The condensate is described in the mean-field approximation of the Gross-Pitaevskii equation. We compare two optimization approaches in terms of their performance and ease of use; namely, gradient-ascent pulse engineering (GRAPE) and Krotov's method. Both approaches are derived from the variational principle but differ in the way the control is updated, additional costs are accounted for, and second-order-derivative information can be included. We find that GRAPE produces smoother control fields and works in a black-box manner, whereas Krotov with a suitably chosen step-size parameter converges faster but can produce sharp features in the control fields.

Analysis of neighborhood behavior in lead optimization and array design.

Science.gov (United States)

Papadatos, George; Cooper, Anthony W J; Kadirkamanathan, Visakan; Macdonald, Simon J F; McLay, Iain M; Pickett, Stephen D; Pritchard, John M; Willett, Peter; Gillet, Valerie J

2009-02-01

Neighborhood behavior describes the extent to which small structural changes defined by a molecular descriptor are likely to lead to small property changes. This study evaluates two methods for the quantification of neighborhood behavior: the optimal diagonal method of Patterson et al. and the optimality criterion method of Horvath and Jeandenans. The methods are evaluated using twelve different types of fingerprint (both 2D and 3D) with screening data derived from several lead optimization projects at GlaxoSmithKline. The principal focus of the work is the design of chemical arrays during lead optimization, and the study hence considers not only biological activity but also important drug properties such as metabolic stability, permeability, and lipophilicity. Evidence is provided to suggest that the optimality criterion method may provide a better quantitative description of neighborhood behavior than the optimal diagonal method.

Thermodynamic optimization of geometry in engineering flow systems

Energy Technology Data Exchange (ETDEWEB)

Bejan, A.; Jones, J.A. [Duke Univ., Durham, NC (United States)

2000-07-01

This review draws attention to an emerging body of work that relies on global thermodynamic optimization in the pursuit of flow system architecture. Exergy analysis establishes the theoretical performance limit. Thermodynamic optimization (or entropy generation minimization) brings the design as closely as permissible to the theoretical limit. The design is destined to remain imperfect because of constraints (finite sizes, times, and costs). Improvements are registered by spreading the imperfection (e.g., flow resistances) through the system. Resistances compete against each other and must be optimized together. Optimal spreading means spatial distribution, geometric form, topology, and geography. System architecture springs out of constrained global optimization. The principle is illustrated by simple examples: the optimization of dimensions, spacings, and the distribution (allocation) of heat transfer surface to the two heat exchangers of a power plant. Similar opportunities for deducing flow architecture exist in more complex systems for power and refrigeration. Examples show that the complete structure of heat exchangers for environmental control systems of aircraft can be derived based on this principle. (authors)

Algae Derived Biofuel

Energy Technology Data Exchange (ETDEWEB)

Jahan, Kauser [Rowan Univ., Glassboro, NJ (United States)

2015-03-31

One of the most promising fuel alternatives is algae biodiesel. Algae reproduce quickly, produce oils more efficiently than crop plants, and require relatively few nutrients for growth. These nutrients can potentially be derived from inexpensive waste sources such as flue gas and wastewater, providing a mutual benefit of helping to mitigate carbon dioxide waste. Algae can also be grown on land unsuitable for agricultural purposes, eliminating competition with food sources. This project focused on cultivating select algae species under various environmental conditions to optimize oil yield. Membrane studies were also conducted to transfer carbon di-oxide more efficiently. An LCA study was also conducted to investigate the energy intensive steps in algae cultivation.

Design optimization for permanent magnet machine with efficient slot per pole ratio

Science.gov (United States)

Potnuru, Upendra Kumar; Rao, P. Mallikarjuna

2018-04-01

This paper presents a methodology for the enhancement of a Brush Less Direct Current motor (BLDC) with 6Poles and 8slots. In particular; it is focused on amulti-objective optimization using a Genetic Algorithmand Grey Wolf Optimization developed in MATLAB. The optimization aims to maximize the maximum output power value and minimize the total losses of a motor. This paper presents an application of the MATLAB optimization algorithms to brushless DC (BLDC) motor design, with 7 design parameters chosen to be free. The optimal design parameters of the motor derived by GA are compared with those obtained by Grey Wolf Optimization technique. A comparative report on the specified enhancement approaches appearsthat Grey Wolf Optimization technique has a better convergence.

Cisplatin and derivatives with radiation therapy: for what clinical use?

International Nuclear Information System (INIS)

Durdux, C.

2004-01-01

Since its discovery by Rosenberg in 1965, cisplatin and its derivatives have appeared as the most important chemotherapeutic agents, particularly for their radiosensitizing properties and their clinical use with radiation. In spite of numerous preclinical and clinical studies, optimal schedules of platin and radiotherapy combination have to be defined. The first part of this overview will describe biological mechanisms of interaction between radiation therapy and platinum derivatives. The second part will report the major clinical impact of their association. (author)

FORTRAN subroutine for computing the optimal estimate of f(x)

International Nuclear Information System (INIS)

Gaffney, P.W.

1980-10-01

A FORTRAN subroutine called RANGE is presented that is designed to compute the optimal estimate of a function f given values of the function at n distinct points x 1 2 < ... < x/sub n/ and given a bound on one of the derivatives of f. We donate this estimate by Ω. It is optimal in the sense that the error abs value (f - Ω) has the smallest possible error bound

Optimal Design of Modern Transformerless PV Inverter Topologies

DEFF Research Database (Denmark)

Saridakis, Stefanos; Koutroulis, Eftichios; Blaabjerg, Frede

2013-01-01

the operational lifetime period of the PV installation, is also considered in the optimization process. According to the results of the proposed design method, different optimal values of the PV inverter design variables are derived for each PV inverter topology and installation site. The H5, H6, neutral point...... clamped, active-neutral point clamped and conergy-NPC PV inverters designed using the proposed optimization process feature lower levelized cost of generated electricity and lifetime cost, longer mean time between failures and inject more PV-generated energy into the electric grid than their nonoptimized......The design optimization of H5, H6, neutral point clamped, active-neutral point clamped, and conergy-NPC transformerless photovoltaic (PV) inverters is presented in this paper. The components reliability in terms of the corresponding malfunctions, affecting the PV inverter maintenance cost during...

Design, synthesis and optimization of bis-amide derivatives as CSF1R inhibitors.

Science.gov (United States)

Ramachandran, Sreekanth A; Jadhavar, Pradeep S; Miglani, Sandeep K; Singh, Manvendra P; Kalane, Deepak P; Agarwal, Anil K; Sathe, Balaji D; Mukherjee, Kakoli; Gupta, Ashu; Haldar, Srijan; Raja, Mohd; Singh, Siddhartha; Pham, Son M; Chakravarty, Sarvajit; Quinn, Kevin; Belmar, Sebastian; Alfaro, Ivan E; Higgs, Christopher; Bernales, Sebastian; Herrera, Francisco J; Rai, Roopa

2017-05-15

Signaling via the receptor tyrosine kinase CSF1R is thought to play an important role in recruitment and differentiation of tumor-associated macrophages (TAMs). TAMs play pro-tumorigenic roles, including the suppression of anti-tumor immune response, promotion of angiogenesis and tumor cell metastasis. Because of the role of this signaling pathway in the tumor microenvironment, several small molecule CSF1R kinase inhibitors are undergoing clinical evaluation for cancer therapy, either as a single agent or in combination with other cancer therapies, including immune checkpoint inhibitors. Herein we describe our lead optimization effort that resulted in the identification of a potent, cellular active and orally bioavailable bis-amide CSF1R inhibitor. Docking and biochemical analysis allowed the removal of a metabolically labile and poorly permeable methyl piperazine group from an early lead compound. Optimization led to improved metabolic stability and Caco2 permeability, which in turn resulted in good oral bioavailability in mice. Copyright © 2017 Elsevier Ltd. All rights reserved.

Optimal Caching in Multicast 5G Networks with Opportunistic Spectrum Access

KAUST Repository

Emara, Mostafa

2018-01-15

Cache-enabled small base station (SBS) densification is foreseen as a key component of 5G cellular networks. This architecture enables storing popular files at the network edge (i.e., SBS caches), which empowers local communication and alleviates traffic congestions at the core/backhaul network. This paper develops a mathematical framework, based on stochastic geometry, to characterize the hit probability of a cache-enabled multicast 5G network with SBS multi-channel capabilities and opportunistic spectrum access. To this end, we first derive the hit probability by characterizing opportunistic spectrum access success probabilities, service distance distributions, and coverage probabilities. The optimal caching distribution to maximize the hit probability is then computed. The performance and trade-offs of the derived optimal caching distributions are then assessed and compared with two widely employed caching distribution schemes, namely uniform and Zipf caching, through numerical results and extensive simulations. It is shown that the Zipf caching almost optimal only in scenarios with large number of available channels and large cache sizes.

A Visualization Technique for Accessing Solution Pool in Interactive Methods of Multiobjective Optimization

OpenAIRE

Filatovas, Ernestas; Podkopaev, Dmitry; Kurasova, Olga

2015-01-01

Interactive methods of multiobjective optimization repetitively derive Pareto optimal solutions based on decision maker’s preference information and present the obtained solutions for his/her consideration. Some interactive methods save the obtained solutions into a solution pool and, at each iteration, allow the decision maker considering any of solutions obtained earlier. This feature contributes to the flexibility of exploring the Pareto optimal set and learning about the op...

Optimizing the marketing interventions mix in intermediate-term CRM

NARCIS (Netherlands)

R.T. Rust (Roland); P.C. Verhoef (Peter)

2005-01-01

textabstractWe provide a fully personalized model for optimizing multiple marketing interventions in intermediate-term customer relationship management (CRM). We derive theoretically based propositions on the moderating effects of past customer behavior and conduct a longitudinal validation test to

Discounted cost model for condition-based maintenance optimization

International Nuclear Information System (INIS)

Weide, J.A.M. van der; Pandey, M.D.; Noortwijk, J.M. van

2010-01-01

This paper presents methods to evaluate the reliability and optimize the maintenance of engineering systems that are damaged by shocks or transients arriving randomly in time and overall degradation is modeled as a cumulative stochastic point process. The paper presents a conceptually clear and comprehensive derivation of formulas for computing the discounted cost associated with a maintenance policy combining both condition-based and age-based criteria for preventive maintenance. The proposed discounted cost model provides a more realistic basis for optimizing the maintenance policies than those based on the asymptotic, non-discounted cost rate criterion.

Optimal stride frequencies in running at different speeds

NARCIS (Netherlands)

Van Oeveren, Ben T.; De Ruiter, Cornelis J.; Beek, Peter J.; Van Dieën, Jaap H.

2017-01-01

During running at a constant speed, the optimal stride frequency (SF) can be derived from the u-shaped relationship between SF and heart rate (HR). Changing SF towards the optimum of this relationship is beneficial for energy expenditure and may positively change biomechanics of running. In the

Optimal control for power-off landing of a small-scale helicopter : a pseudospectral approach

NARCIS (Netherlands)

Taamallah, S.; Bombois, X.; Hof, Van den P.M.J.

2012-01-01

We derive optimal power-off landing trajectories, for the case of a small-scale helicopter UAV. These open-loop optimal trajectories represent the solution to the minimization of a cost objective, given system dynamics, controls and states equality and inequality constraints. The plant dynamics

Portfolio theory of optimal isometric force production: Variability predictions and nonequilibrium fluctuation-dissipation theorem

NARCIS (Netherlands)

Frank, T.D.; Patanarapeelert, K.; Beek, P.J.

2008-01-01

We derive a fundamental relationship between the mean and the variability of isometric force. The relationship arises from an optimal collection of active motor units such that the force variability assumes a minimum (optimal isometric force). The relationship is shown to be independent of the

PWR fuel management optimization

International Nuclear Information System (INIS)

Dumas, Michel.

1981-10-01

This report is aimed to the optimization of the refueling pattern of a nuclear reactor. At the beginning of a reactor cycle a batch of fuel assemblies is available: the physical properties of the assemblies are known: the mathematical problem is to determine the refueling pattern which maximizes the reactivity or which provides the flattest possible power distribution. The state of the core is mathematically characterized by a system of partial derivative equations, its smallest eigenvalue and the associated eigenvector. After a study of the convexity properties of the problem, two algorithms are proposed. The first one exhanges assemblies to improve the starting configurations. The enumeration of the exchanges is limited to the 2 by 2, 3 by 3, 4 by 4 permutations. The second one builds a solution in two steps: in the first step the discrete variables are replaced by continuous variables. The non linear optimization problem obtained is solved by ''the Method of Approximation Programming'' and in the second step, the refuelling pattern which provides the best approximation of the optimal power distribution is searched by a Branch an d Bound Method [fr

The Inverse Optimal Control Problem for a Three-Loop Missile Autopilot

Science.gov (United States)

Hwang, Donghyeok; Tahk, Min-Jea

2018-04-01

The performance characteristics of the autopilot must have a fast response to intercept a maneuvering target and reasonable robustness for system stability under the effect of un-modeled dynamics and noise. By the conventional approach, the three-loop autopilot design is handled by time constant, damping factor and open-loop crossover frequency to achieve the desired performance requirements. Note that the general optimal theory can be also used to obtain the same gain as obtained from the conventional approach. The key idea of using optimal control technique for feedback gain design revolves around appropriate selection and interpretation of the performance index for which the control is optimal. This paper derives an explicit expression, which relates the weight parameters appearing in the quadratic performance index to the design parameters such as open-loop crossover frequency, phase margin, damping factor, or time constant, etc. Since all set of selection of design parameters do not guarantee existence of optimal control law, explicit inequalities, which are named the optimality criteria for the three-loop autopilot (OC3L), are derived to find out all set of design parameters for which the control law is optimal. Finally, based on OC3L, an efficient gain selection procedure is developed, where time constant is set to design objective and open-loop crossover frequency and phase margin as design constraints. The effectiveness of the proposed technique is illustrated through numerical simulations.

Optimizing the marketing interventions mix in intermediate-term CRM

NARCIS (Netherlands)

Rust, RT; Verhoef, PC

2005-01-01

W e provide a fully personalized model for optimizing multiple marketing interventions in intermediate-term customer relationship management (CRM). We derive theoretically based propositions on the moderating effects of past customer behavior and conduct a longitudinal validation test to compare the

Neutron density optimal control of A-1 reactor analoque model

International Nuclear Information System (INIS)

Grof, V.

1975-01-01

Two applications are described of the optimal control of a reactor analog model. Both cases consider the control of neutron density. Control loops containing the on-line controlled process, the reactor of the first Czechoslovak nuclear power plant A-1, are simulated on an analog computer. Two versions of the optimal control algorithm are derived using modern control theory (Pontryagin's maximum principle, the calculus of variations, and Kalman's estimation theory), the minimum time performance index, and the quadratic performance index. The results of the optimal control analysis are compared with the A-1 reactor conventional control. (author)

Optimizing microwave photodetection: input-output theory

Science.gov (United States)

Schöndorf, M.; Govia, L. C. G.; Vavilov, M. G.; McDermott, R.; Wilhelm, F. K.

2018-04-01

High fidelity microwave photon counting is an important tool for various areas from background radiation analysis in astronomy to the implementation of circuit quantum electrodynamic architectures for the realization of a scalable quantum information processor. In this work we describe a microwave photon counter coupled to a semi-infinite transmission line. We employ input-output theory to examine a continuously driven transmission line as well as traveling photon wave packets. Using analytic and numerical methods, we calculate the conditions on the system parameters necessary to optimize measurement and achieve high detection efficiency. With this we can derive a general matching condition depending on the different system rates, under which the measurement process is optimal.

Optimal design of constant-stress accelerated degradation tests using the M-optimality criterion

International Nuclear Information System (INIS)

Wang, Han; Zhao, Yu; Ma, Xiaobing; Wang, Hongyu

2017-01-01

In this paper, we propose the M-optimality criterion for designing constant-stress accelerated degradation tests (ADTs). The newly proposed criterion concentrates on the degradation mechanism equivalence rather than evaluation precision or prediction accuracy which is usually considered in traditional optimization criteria. Subject to the constraints of total sample number, test termination time as well as the stress region, an optimum constant-stress ADT plan is derived by determining the combination of stress levels and the number of samples allocated to each stress level, when the degradation path comes from inverse Gaussian (IG) process model with covariates and random effects. A numerical example is presented to verify the robustness of our proposed optimum plan and compare its efficiency with other test plans. Results show that, with a slightly relaxed requirement of evaluation precision and prediction accuracy, our proposed optimum plan reduces the dispersion of the estimated acceleration factor between the usage stress level and a higher accelerated stress level, which makes an important contribution to reliability demonstration and assessment tests. - Highlights: • We establish the necessary conditions for degradation mechanism equivalence of ADTs. • We propose the M-optimality criterion for designing constant-stress ADT plans. • The M-optimality plan reduces the dispersion of the estimated accelerated factors. • An electrical connector with its stress relaxation data is used for illustration.

Optimization Models for Petroleum Field Exploitation

Energy Technology Data Exchange (ETDEWEB)

Jonsbraaten, Tore Wiig

1998-12-31

This thesis presents and discusses various models for optimal development of a petroleum field. The objective of these optimization models is to maximize, under many uncertain parameters, the project`s expected net present value. First, an overview of petroleum field optimization is given from the point of view of operations research. Reservoir equations for a simple reservoir system are derived and discretized and included in optimization models. Linear programming models for optimizing production decisions are discussed and extended to mixed integer programming models where decisions concerning platform, wells and production strategy are optimized. Then, optimal development decisions under uncertain oil prices are discussed. The uncertain oil price is estimated by a finite set of price scenarios with associated probabilities. The problem is one of stochastic mixed integer programming, and the solution approach is to use a scenario and policy aggregation technique developed by Rockafellar and Wets although this technique was developed for continuous variables. Stochastic optimization problems with focus on problems with decision dependent information discoveries are also discussed. A class of ``manageable`` problems is identified and an implicit enumeration algorithm for finding optimal decision policy is proposed. Problems involving uncertain reservoir properties but with a known initial probability distribution over possible reservoir realizations are discussed. Finally, a section on Nash-equilibrium and bargaining in an oil reservoir management game discusses the pool problem arising when two lease owners have access to the same underlying oil reservoir. Because the oil tends to migrate, both lease owners have incentive to drain oil from the competitors part of the reservoir. The discussion is based on a numerical example. 107 refs., 31 figs., 14 tabs.

Reference-shaping adaptive control by using gradient descent optimizers.

Directory of Open Access Journals (Sweden)

Baris Baykant Alagoz

Full Text Available This study presents a model reference adaptive control scheme based on reference-shaping approach. The proposed adaptive control structure includes two optimizer processes that perform gradient descent optimization. The first process is the control optimizer that generates appropriate control signal for tracking of the controlled system output to a reference model output. The second process is the adaptation optimizer that performs for estimation of a time-varying adaptation gain, and it contributes to improvement of control signal generation. Numerical update equations derived for adaptation gain and control signal perform gradient descent optimization in order to decrease the model mismatch errors. To reduce noise sensitivity of the system, a dead zone rule is applied to the adaptation process. Simulation examples show the performance of the proposed Reference-Shaping Adaptive Control (RSAC method for several test scenarios. An experimental study demonstrates application of method for rotor control.

Optimal Wonderful Life Utility Functions in Multi-Agent Systems

Science.gov (United States)

Wolpert, David H.; Tumer, Kagan; Swanson, Keith (Technical Monitor)

2000-01-01

The mathematics of Collective Intelligence (COINs) is concerned with the design of multi-agent systems so as to optimize an overall global utility function when those systems lack centralized communication and control. Typically in COINs each agent runs a distinct Reinforcement Learning (RL) algorithm, so that much of the design problem reduces to how best to initialize/update each agent's private utility function, as far as the ensuing value of the global utility is concerned. Traditional team game solutions to this problem assign to each agent the global utility as its private utility function. In previous work we used the COIN framework to derive the alternative Wonderful Life Utility (WLU), and experimentally established that having the agents use it induces global utility performance up to orders of magnitude superior to that induced by use of the team game utility. The WLU has a free parameter (the clamping parameter) which we simply set to zero in that previous work. Here we derive the optimal value of the clamping parameter, and demonstrate experimentally that using that optimal value can result in significantly improved performance over that of clamping to zero, over and above the improvement beyond traditional approaches.

Optimized thermal amplification in a radiative transistor

Energy Technology Data Exchange (ETDEWEB)

Prod' homme, Hugo; Ordonez-Miranda, Jose; Ezzahri, Younes, E-mail: younes.ezzahri@univ-poitiers.fr; Drevillon, Jeremie; Joulain, Karl [Institut Pprime, CNRS, Université de Poitiers, ISAE-ENSMA, F-86962 Futuroscope Chasseneuil (France)

2016-05-21

The thermal performance of a far-field radiative transistor made up of a VO{sub 2} base in between a blackbody collector and a blackbody emitter is theoretically studied and optimized. This is done by using the grey approximation on the emissivity of VO{sub 2} and deriving analytical expressions for the involved heat fluxes and transistor amplification factor. It is shown that this amplification factor can be maximized by tuning the base temperature close to its critical one, which is determined by the temperature derivative of the VO{sub 2} emissivity and the equilibrium temperatures of the collector and emitter. This maximization is the result of the presence of two bi-stable temperatures appearing during the heating and cooling processes of the VO{sub 2} base and enables a thermal switching (temperature jump) characterized by a sizeable variation of the collector-to-base and base-to-emitter heat fluxes associated with a slight change of the applied power to the base. This switching effect leads to the optimization of the amplification factor and therefore it could be used for thermal modulation purposes.

Optimizing production under uncertainty

DEFF Research Database (Denmark)

Rasmussen, Svend

This Working Paper derives criteria for optimal production under uncertainty based on the state-contingent approach (Chambers and Quiggin, 2000), and discusses po-tential problems involved in applying the state-contingent approach in a normative context. The analytical approach uses the concept...... of state-contingent production functions and a definition of inputs including both sort of input, activity and alloca-tion technology. It also analyses production decisions where production is combined with trading in state-contingent claims such as insurance contracts. The final part discusses...

Thermo-economic optimization of an endoreversible four-heat-reservoir absorption-refrigerator

International Nuclear Information System (INIS)

Qin Xiaoyong; Chen Lingen; Sun Fengrui; Wu Chih

2005-01-01

Based on an endoreversible four-heat-reservoir absorption-refrigeration-cycle model, the optimal thermo-economic performance of an absorption-refrigerator is analyzed and optimized assuming a linear (Newtonian) heat-transfer law applies. The optimal relation between the thermo-economic criterion and the coefficient of performance (COP), the maximum thermo-economic criterion, and the COP and specific cooling load for the maximum thermo-economic criterion of the cycle are derived using finite-time thermodynamics. Moreover, the effects of the cycle parameters on the thermo-economic performance of the cycle are studied by numerical examples

A numerical scheme for optimal transition paths of stochastic chemical kinetic systems

International Nuclear Information System (INIS)

Liu Di

2008-01-01

We present a new framework for finding the optimal transition paths of metastable stochastic chemical kinetic systems with large system size. The optimal transition paths are identified to be the most probable paths according to the Large Deviation Theory of stochastic processes. Dynamical equations for the optimal transition paths are derived using the variational principle. A modified Minimum Action Method (MAM) is proposed as a numerical scheme to solve the optimal transition paths. Applications to Gene Regulatory Networks such as the toggle switch model and the Lactose Operon Model in Escherichia coli are presented as numerical examples

Optimized Estimation of Surface Layer Characteristics from Profiling Measurements

Directory of Open Access Journals (Sweden)

Doreene Kang

2016-01-01

Full Text Available New sampling techniques such as tethered-balloon-based measurements or small unmanned aerial vehicles are capable of providing multiple profiles of the Marine Atmospheric Surface Layer (MASL in a short time period. It is desirable to obtain surface fluxes from these measurements, especially when direct flux measurements are difficult to obtain. The profiling data is different from the traditional mean profiles obtained at two or more fixed levels in the surface layer from which surface fluxes of momentum, sensible heat, and latent heat are derived based on Monin-Obukhov Similarity Theory (MOST. This research develops an improved method to derive surface fluxes and the corresponding MASL mean profiles of wind, temperature, and humidity with a least-squares optimization method using the profiling measurements. This approach allows the use of all available independent data. We use a weighted cost function based on the framework of MOST with the cost being optimized using a quasi-Newton method. This approach was applied to seven sets of data collected from the Monterey Bay. The derived fluxes and mean profiles show reasonable results. An empirical bias analysis is conducted using 1000 synthetic datasets to evaluate the robustness of the method.

Design, implementation, and experimental validation of optimal power split control for hybrid electric trucks

NARCIS (Netherlands)

Keulen, T. van; Mullem, D. van; Jager, B. van; Kessels, J.T.B.A.; Steinbuch, M.

2012-01-01

Hybrid electric vehicles require an algorithm that controls the power split between the internal combustion engine and electric machine(s), and the opening and closing of the clutch. Optimal control theory is applied to derive a methodology for a real-time optimal-control-based power split

Optimizing Acquisition Parameters for MASW in Shallow Water

NARCIS (Netherlands)

Diaferia, G.; Kruiver, P.P.; Drijkoningen, G.G.

2013-01-01

Analogous to the use of Rayleigh waves in MASW on land, Scholte waves can be used to derive shear wave velocity profiles for the subsurface under water. These profiles are useful for dredging operations, offshore wind farms, oil rigs and pipelines. We have determined the optimal acquisition set up

Optimal recombination in genetic algorithms for combinatorial optimization problems: Part II

Directory of Open Access Journals (Sweden)

Eremeev Anton V.

2014-01-01

Full Text Available This paper surveys results on complexity of the optimal recombination problem (ORP, which consists in finding the best possible offspring as a result of a recombination operator in a genetic algorithm, given two parent solutions. In Part II, we consider the computational complexity of ORPs arising in genetic algorithms for problems on permutations: the Travelling Salesman Problem, the Shortest Hamilton Path Problem and the Makespan Minimization on Single Machine and some other related problems. The analysis indicates that the corresponding ORPs are NP-hard, but solvable by faster algorithms, compared to the problems they are derived from.

Design of Optimal Hybrid Position/Force Controller for a Robot Manipulator Using Neural Networks

Directory of Open Access Journals (Sweden)

Vikas Panwar

2007-01-01

Full Text Available The application of quadratic optimization and sliding-mode approach is considered for hybrid position and force control of a robot manipulator. The dynamic model of the manipulator is transformed into a state-space model to contain two sets of state variables, where one describes the constrained motion and the other describes the unconstrained motion. The optimal feedback control law is derived solving matrix differential Riccati equation, which is obtained using Hamilton Jacobi Bellman optimization. The optimal feedback control law is shown to be globally exponentially stable using Lyapunov function approach. The dynamic model uncertainties are compensated with a feedforward neural network. The neural network requires no preliminary offline training and is trained with online weight tuning algorithms that guarantee small errors and bounded control signals. The application of the derived control law is demonstrated through simulation with a 4-DOF robot manipulator to track an elliptical planar constrained surface while applying the desired force on the surface.

multi scale analysis of a function by neural networks elementary derivatives functions

International Nuclear Information System (INIS)

Chikhi, A.; Gougam, A.; Chafa, F.

2006-01-01

Recently, the wavelet network has been introduced as a special neural network supported by the wavelet theory . Such networks constitute a tool for function approximation problems as it has been already proved in reference . Our present work deals with this model, treating a multi scale analysis of a function. We have then used a linear expansion of a given function in wavelets, neglecting the usual translation parameters. We investigate two training operations. The first one consists on an optimization of the output synaptic layer, the second one, optimizing the output function with respect to scale parameters. We notice a temporary merging of the scale parameters leading to some interesting results : new elementary derivatives units emerge, representing a new elementary task, which is the derivative of the output task

Optimal utilization of energy resources

Energy Technology Data Exchange (ETDEWEB)

Hudson, E. A.

1977-10-15

General principles that should guide the extraction of New Zealand's energy resources are presented. These principles are based on the objective of promoting the general economic and social benefit obtained from the use of the extracted fuel. For a single resource, the central question to be answered is, simply, what quantity of energy should be extracted in each year of the resource's lifetime. For the energy system as a whole the additional question must be answered of what mix of fuels should be used in any year. The analysis of optimal management of a single energy resource is specifically discussed. The general principles for optimal resource extraction are derived, and then applied to the examination of the characteristics of the optimal time paths of energy quantity and price; to the appraisal of the efficiency, in resource management, of various market structures; to the evaluation of various energy pricing policies; and to the examination of circumstances in which market organization is inefficient and the guidelines for corrective government policy in such cases.

Optimal utilization of energy resources

Energy Technology Data Exchange (ETDEWEB)

Hudson, E.A.

1977-10-15

General principles that should guide the extraction of New Zealand's energy resources are presented. These principles are based on the objective of promoting the general economic and social benefit obtained from the use of the extracted fuel. For a single resource, the central question to be answered is, simply, what quantity of energy should be extracted in each year of the resource's lifetime. For the energy system as a whole the additional question must be answered of what mix of fuels should be used in any year. The analysis of optimal management of a single energy resource is specifically discussed. The general principles for optimal resource extraction are derived, and then applied to the examination of the characteristics of the optimal time paths of energy quantity and price; to the appraisal of the efficiency, in resource management, of various market structures; to the evaluation of various energy pricing policies; and to the examination of circumstances in which market organization is inefficient and the guidelines for corrective government policy in such cases.

Optimal Labor Contracts with Asymmetric Information and More than Two Types of Agent

Directory of Open Access Journals (Sweden)

Daniela Elena MARINESCU

2012-05-01

Full Text Available In the paper we discuss the optimal labor agreements between workers and firms in the situation of asymmetric information. Using a standard adverse selection model, we analyze the optimality of the labor contracts when it is the firm which has private information affecting the results of the contractual relationship. We propose an alternative procedure to solve the optimization problem, using the informational rents as variables. In the last part of the paper we derive and comment the features of the optimal labor contracts in asymmetric information.

Application of Multi-Objective Human Learning Optimization Method to Solve AC/DC Multi-Objective Optimal Power Flow Problem

Science.gov (United States)

Cao, Jia; Yan, Zheng; He, Guangyu

2016-06-01

This paper introduces an efficient algorithm, multi-objective human learning optimization method (MOHLO), to solve AC/DC multi-objective optimal power flow problem (MOPF). Firstly, the model of AC/DC MOPF including wind farms is constructed, where includes three objective functions, operating cost, power loss, and pollutant emission. Combining the non-dominated sorting technique and the crowding distance index, the MOHLO method can be derived, which involves individual learning operator, social learning operator, random exploration learning operator and adaptive strategies. Both the proposed MOHLO method and non-dominated sorting genetic algorithm II (NSGAII) are tested on an improved IEEE 30-bus AC/DC hybrid system. Simulation results show that MOHLO method has excellent search efficiency and the powerful ability of searching optimal. Above all, MOHLO method can obtain more complete pareto front than that by NSGAII method. However, how to choose the optimal solution from pareto front depends mainly on the decision makers who stand from the economic point of view or from the energy saving and emission reduction point of view.

Second-Order Necessary Optimality Conditions for Some State-Constrained Control Problems of Semilinear Elliptic Equations

International Nuclear Information System (INIS)

Casas, E.; Troeltzsch, F.

1999-01-01

In this paper we are concerned with some optimal control problems governed by semilinear elliptic equations. The case of a boundary control is studied. We consider pointwise constraints on the control and a finite number of equality and inequality constraints on the state. The goal is to derive first- and second-order optimality conditions satisfied by locally optimal solutions of the problem

Optimization of CW Fiber Lasers With Strong Nonlinear Cavity Dynamics

Science.gov (United States)

Shtyrina, O. V.; Efremov, S. A.; Yarutkina, I. A.; Skidin, A. S.; Fedoruk, M. P.

2018-04-01

In present work the equation for the saturated gain is derived from one-level gain equations describing the energy evolution inside the laser cavity. It is shown how to derive the parameters of the mathematical model from the experimental results. The numerically-estimated energy and spectrum of the signal are in good agreement with the experiment. Also, the optimization of the output energy is performed for a given set of model parameters.

Optimized methods for preparation of 6I-(ω-sulfanyl-alkylene-sulfanyl-β-cyclodextrin derivatives

Directory of Open Access Journals (Sweden)

Eva Bednářová

2016-02-01

Full Text Available A general high-yielding method for the preparation of monosubstituted β-cyclodextrin derivatives which have attached a thiol group in position 6 is described. The thiol group is attached through linkers of different lengths and repeating units (ethylene glycol or methylene. The target compounds were characterized by IR, MS and NMR spectra. A simple method for their complete conversion to the corresponding disulfides as well as a method for the reduction of the disulfides back to the thiols is presented. Both, thiols and disulfides are derivatives usable for well-defined covalent attachment of cyclodextrin to gold or polydopamine-coated solid surfaces.

A derivation of the explicit structure of inner matrices for H∞-optimization

International Nuclear Information System (INIS)

Suzuki, Katsuo; Shimazaki, Junya; Shinohara, Yoshikuni

1991-05-01

One of the most important computational procedure in the solution of the H∞-minimization problems is the derivation of inner matrices. This report describes in detail Shaked's method to enable to obtain an explicit expression of the inner matrix and also summarizes in the form of computational procedure resulting from this method. In addition, a simple numerical example solved by this method is shown. (J.P.N.)

A one-layer recurrent neural network for constrained nonsmooth optimization.

Science.gov (United States)

Liu, Qingshan; Wang, Jun

2011-10-01

This paper presents a novel one-layer recurrent neural network modeled by means of a differential inclusion for solving nonsmooth optimization problems, in which the number of neurons in the proposed neural network is the same as the number of decision variables of optimization problems. Compared with existing neural networks for nonsmooth optimization problems, the global convexity condition on the objective functions and constraints is relaxed, which allows the objective functions and constraints to be nonconvex. It is proven that the state variables of the proposed neural network are convergent to optimal solutions if a single design parameter in the model is larger than a derived lower bound. Numerical examples with simulation results substantiate the effectiveness and illustrate the characteristics of the proposed neural network.

Optimal drawdown patterns for strategic petroleum reserves

Energy Technology Data Exchange (ETDEWEB)

Kuenne, R E; Blankenship, J W; McCoy, P F

1979-01-01

An optimization model is described for determining optimal drawdown trajectories for strategic petroleum reserves during an embargo. Development of the model includes the derivation of a GNP response function which relates GNP (used as a measure of social welfare) and crude oil supply reductions. Two alternative forms of this function are used with the model. Simple algorithms are presented which give rapid solutions for the model. The pattern is one of saving some of the reserve to protect against a possible second embargo occurring beforee refill, and of allocating the remainder during the first embargo subperiod so as to equalize monthly marginal benefits. 6 references.

Optimally Stopped Optimization

Science.gov (United States)

Vinci, Walter; Lidar, Daniel

We combine the fields of heuristic optimization and optimal stopping. We propose a strategy for benchmarking randomized optimization algorithms that minimizes the expected total cost for obtaining a good solution with an optimal number of calls to the solver. To do so, rather than letting the objective function alone define a cost to be minimized, we introduce a further cost-per-call of the algorithm. We show that this problem can be formulated using optimal stopping theory. The expected cost is a flexible figure of merit for benchmarking probabilistic solvers that can be computed when the optimal solution is not known, and that avoids the biases and arbitrariness that affect other measures. The optimal stopping formulation of benchmarking directly leads to a real-time, optimal-utilization strategy for probabilistic optimizers with practical impact. We apply our formulation to benchmark the performance of a D-Wave 2X quantum annealer and the HFS solver, a specialized classical heuristic algorithm designed for low tree-width graphs. On a set of frustrated-loop instances with planted solutions defined on up to N = 1098 variables, the D-Wave device is between one to two orders of magnitude faster than the HFS solver.

Enabling quaternion derivatives: the generalized HR calculus

Science.gov (United States)

Xu, Dongpo; Jahanchahi, Cyrus; Took, Clive C.; Mandic, Danilo P.

2015-01-01

Quaternion derivatives exist only for a very restricted class of analytic (regular) functions; however, in many applications, functions of interest are real-valued and hence not analytic, a typical case being the standard real mean square error objective function. The recent HR calculus is a step forward and provides a way to calculate derivatives and gradients of both analytic and non-analytic functions of quaternion variables; however, the HR calculus can become cumbersome in complex optimization problems due to the lack of rigorous product and chain rules, a consequence of the non-commutativity of quaternion algebra. To address this issue, we introduce the generalized HR (GHR) derivatives which employ quaternion rotations in a general orthogonal system and provide the left- and right-hand versions of the quaternion derivative of general functions. The GHR calculus also solves the long-standing problems of product and chain rules, mean-value theorem and Taylor's theorem in the quaternion field. At the core of the proposed GHR calculus is quaternion rotation, which makes it possible to extend the principle to other functional calculi in non-commutative settings. Examples in statistical learning theory and adaptive signal processing support the analysis. PMID:26361555

An Optimal Portfolio and Capital Management Strategy for Basel III Compliant Commercial Banks

Directory of Open Access Journals (Sweden)

Grant E. Muller

2014-01-01

Full Text Available We model a Basel III compliant commercial bank that operates in a financial market consisting of a treasury security, a marketable security, and a loan and we regard the interest rate in the market as being stochastic. We find the investment strategy that maximizes an expected utility of the bank’s asset portfolio at a future date. This entails obtaining formulas for the optimal amounts of bank capital invested in different assets. Based on the optimal investment strategy, we derive a model for the Capital Adequacy Ratio (CAR, which the Basel Committee on Banking Supervision (BCBS introduced as a measure against banks’ susceptibility to failure. Furthermore, we consider the optimal investment strategy subject to a constant CAR at the minimum prescribed level. We derive a formula for the bank’s asset portfolio at constant (minimum CAR value and present numerical simulations on different scenarios. Under the optimal investment strategy, the CAR is above the minimum prescribed level. The value of the asset portfolio is improved if the CAR is at its (constant minimum value.

Enhancing product robustness in reliability-based design optimization

International Nuclear Information System (INIS)

Zhuang, Xiaotian; Pan, Rong; Du, Xiaoping

2015-01-01

Different types of uncertainties need to be addressed in a product design optimization process. In this paper, the uncertainties in both product design variables and environmental noise variables are considered. The reliability-based design optimization (RBDO) is integrated with robust product design (RPD) to concurrently reduce the production cost and the long-term operation cost, including quality loss, in the process of product design. This problem leads to a multi-objective optimization with probabilistic constraints. In addition, the model uncertainties associated with a surrogate model that is derived from numerical computation methods, such as finite element analysis, is addressed. A hierarchical experimental design approach, augmented by a sequential sampling strategy, is proposed to construct the response surface of product performance function for finding optimal design solutions. The proposed method is demonstrated through an engineering example. - Highlights: • A unifying framework for integrating RBDO and RPD is proposed. • Implicit product performance function is considered. • The design problem is solved by sequential optimization and reliability assessment. • A sequential sampling technique is developed for improving design optimization. • The comparison with traditional RBDO is provided

Understanding PSA and its derivatives in prediction of tumor volume: Addressing health disparities in prostate cancer risk stratification.

Science.gov (United States)

Chinea, Felix M; Lyapichev, Kirill; Epstein, Jonathan I; Kwon, Deukwoo; Smith, Paul Taylor; Pollack, Alan; Cote, Richard J; Kryvenko, Oleksandr N

2017-03-28

To address health disparities in risk stratification of U.S. Hispanic/Latino men by characterizing influences of prostate weight, body mass index, and race/ethnicity on the correlation of PSA derivatives with Gleason score 6 (Grade Group 1) tumor volume in a diverse cohort. Using published PSA density and PSA mass density cutoff values, men with higher body mass indices and prostate weights were less likely to have a tumor volume PSA derivatives when predicting for tumor volume. In receiver operator characteristic analysis, area under the curve values for all PSA derivatives varied across race/ethnicity with lower optimal cutoff values for Hispanic/Latino (PSA=2.79, PSA density=0.06, PSA mass=0.37, PSA mass density=0.011) and Non-Hispanic Black (PSA=3.75, PSA density=0.07, PSA mass=0.46, PSA mass density=0.008) compared to Non-Hispanic White men (PSA=4.20, PSA density=0.11 PSA mass=0.53, PSA mass density=0.014). We retrospectively analyzed 589 patients with low-risk prostate cancer at radical prostatectomy. Pre-operative PSA, patient height, body weight, and prostate weight were used to calculate all PSA derivatives. Receiver operating characteristic curves were constructed for each PSA derivative per racial/ethnic group to establish optimal cutoff values predicting for tumor volume ≥0.5 cm3. Increasing prostate weight and body mass index negatively influence PSA derivatives for predicting tumor volume. PSA derivatives' ability to predict tumor volume varies significantly across race/ethnicity. Hispanic/Latino and Non-Hispanic Black men have lower optimal cutoff values for all PSA derivatives, which may impact risk assessment for prostate cancer.

A Transistor Sizing Tool for Optimization of Analog CMOS Circuits: TSOp

OpenAIRE

Y.C.Wong; Syafeeza A. R; N. A. Hamid

2015-01-01

Optimization of a circuit by transistor sizing is often a slow, tedious and iterative manual process which relies on designer intuition. It is highly desirable to automate the transistor sizing process towards being able to rapidly design high performance integrated circuit. Presented here is a simple but effective algorithm for automatically optimizing the circuit parameters by exploiting the relationships among the genetic algorithm's coefficient values derived from the analog circuit desig...

Optimal quantum state estimation with use of the no-signaling principle

International Nuclear Information System (INIS)

Han, Yeong-Deok; Bae, Joonwoo; Wang Xiangbin; Hwang, Won-Young

2010-01-01

A simple derivation of the optimal state estimation of a quantum bit was obtained by using the no-signaling principle. In particular, the no-signaling principle determines a unique form of the guessing probability independent of figures of merit, such as the fidelity or information gain. This proves that the optimal estimation for a quantum bit can be achieved by the same measurement for almost all figures of merit.

Efficient Minimax Design of Networks without Using Derivatives

DEFF Research Database (Denmark)

Madsen, Kaj; Nielsen, Niels Ole; Schjær-Jacobsen, Hans

1975-01-01

., which makes the gradient computation by the adjoint network method or related methods rather complicated, and often numerical errors are introduced in the gradients. Consequently, the algorithm is found to be of particular relevance in optimum design of practical microwave networks. The relative...... design results. Finally, optimum broad-band design of a practical coaxial transferred-electron reflection-type amplilier is carried out by means of the proposed method. The results are supported by experimental verification.......A new minimax network optimization algorithm not requiring derivatives has been developed. It is based on successive linear approximations to the nonlinear functions defining the problem. Adequate modeling of distributed parameter circuits for optimization purposes often involves parasitic, etc...

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

Extended Kalman Filter Modifications Based on an Optimization View Point

OpenAIRE

Skoglund, Martin; Hendeby, Gustaf; Axehill, Daniel

2015-01-01

The extended Kalman filter (EKF) has been animportant tool for state estimation of nonlinear systems sinceits introduction. However, the EKF does not possess the same optimality properties as the Kalman filter, and may perform poorly. By viewing the EKF as an optimization problem it is possible to, in many cases, improve its performance and robustness. The paper derives three variations of the EKF by applying different optimisation algorithms to the EKF costfunction and relate these to the it...

Performance Analysis and Optimization of Millimeter Wave Networks with Dual-Hop Relaying

KAUST Repository

Chelli, Ali

2017-11-16

In this paper, we use dual-hop relaying to overcome the signal blockage problem that occurs for millimeter waves (mmWaves) due to obstacles located in the propagation environment. Using device-to-device communication, a device in the neighborhood of the transmitter and the receiver can play the role of a relay by amplifying the signal from the source device and forwarding it to the destination device. We consider that both the relay and the destination devices are subject to interference. We study the performance of this mmWave network and derive an exact and asymptotic expressions for the bit error probability (BEP). The exact BEP expression is validated by Monte Carlo simulations. The asymptotic BEP allows determining the diversity order and the coding gain of the communication system. Additionally, we investigate the power allocation optimization subject to a power constraint and derive an analytical expression for the optimal power. Numerical results illustrate the gain achieved in terms of BEP thanks to optimal power allocation.

Optimal Performance Simulation of a Metal Fiber Filter for Capturing Radioactive Aerosols

International Nuclear Information System (INIS)

Lee, Seung Uk; Lee, Chan Hyun; Park, Min Chan; Lee, Jaek Eun

2016-01-01

In this study, the metal fiber filter used for removing radioactive aerosol is systematically dissected and studied in order to figure out the optimal design which can be applied to the actual operation conditions in nuclear heating, ventilation and air conditioning (HVAC) systems for particle collection. In order to derive the optimal design for metal fiber HEPA filter, a numerical model is developed and its results are compared to experimental data to test reliability. Moreover, sensitivity analysis is performed using important parameters to determine which parameters have large influence on the filter performance. Using the model developed in this study, optimal design parameters for pleated metal fiber filters are derived which include fiber diameter less than 4 μm, solidity larger than 0.2, filter thickness larger than 1 mm, and face velocity lower than 5 cm/s. With these conditions, the metal filter qualified for the HEPA filter standard which specified 99.97% efficiency in the 0.3 μm particle size range.

An optimal control strategy for hybrid actuator systems: Application to an artificial muscle with electric motor assist.

Science.gov (United States)

Ishihara, Koji; Morimoto, Jun

2018-03-01

Humans use multiple muscles to generate such joint movements as an elbow motion. With multiple lightweight and compliant actuators, joint movements can also be efficiently generated. Similarly, robots can use multiple actuators to efficiently generate a one degree of freedom movement. For this movement, the desired joint torque must be properly distributed to each actuator. One approach to cope with this torque distribution problem is an optimal control method. However, solving the optimal control problem at each control time step has not been deemed a practical approach due to its large computational burden. In this paper, we propose a computationally efficient method to derive an optimal control strategy for a hybrid actuation system composed of multiple actuators, where each actuator has different dynamical properties. We investigated a singularly perturbed system of the hybrid actuator model that subdivided the original large-scale control problem into smaller subproblems so that the optimal control outputs for each actuator can be derived at each control time step and applied our proposed method to our pneumatic-electric hybrid actuator system. Our method derived a torque distribution strategy for the hybrid actuator by dealing with the difficulty of solving real-time optimal control problems. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Optimal Control via Reinforcement Learning with Symbolic Policy Approximation

NARCIS (Netherlands)

Kubalìk, Jiřì; Alibekov, Eduard; Babuska, R.; Dochain, Denis; Henrion, Didier; Peaucelle, Dimitri

2017-01-01

Model-based reinforcement learning (RL) algorithms can be used to derive optimal control laws for nonlinear dynamic systems. With continuous-valued state and input variables, RL algorithms have to rely on function approximators to represent the value function and policy mappings. This paper

A Dynamic Programming Approach for Pricing Weather Derivatives under Issuer Default Risk

Directory of Open Access Journals (Sweden)

Wolfgang Karl Härdle

2017-10-01

Full Text Available Weather derivatives are contingent claims with payoff based on a pre-specified weather index. Firms exposed to weather risk can transfer it to financial markets via weather derivatives. We develop a utility-based model for pricing baskets of weather derivatives under default risk on the issuer side in over-the-counter markets. In our model, agents maximise the expected utility of their terminal wealth, while they dynamically rebalance their weather portfolios over a finite investment horizon. Using dynamic programming approach, we obtain semi-closed forms for the equilibrium prices of weather derivatives and for the optimal strategies of the agents. We give an example on how to price rainfall derivatives on selected stations in China in the universe of a financial investor and a weather exposed crop insurer.

Coronary CT Angiography Derived Fractional Flow Reserve

DEFF Research Database (Denmark)

Nørgaard, Bjarne Linde; Jensen, Jesper Møller; Blanke, Philipp

2017-01-01

Purpose of Review: To summarize the scientific basis of CT derived fractional flow reserve (FFRCT) and present an updated review on the evidence from clinical trials and real-world observational data Recent Findings: In prospective multicenter studies of patients with stable coronary artery disea...... of patients with stable CAD. The optimal FFRCT testing interpretation strategy, as well as the relative cost-efficiency of FFRCT against standard noninvasive functional testing, need further investigation....

Optimal Mortgage Refinancing: A Closed Form Solution.

Science.gov (United States)

Agarwal, Sumit; Driscoll, John C; Laibson, David I

2013-06-01

We derive the first closed-form optimal refinancing rule: Refinance when the current mortgage interest rate falls below the original rate by at least [Formula: see text] In this formula W (.) is the Lambert W -function, [Formula: see text] ρ is the real discount rate, λ is the expected real rate of exogenous mortgage repayment, σ is the standard deviation of the mortgage rate, κ/M is the ratio of the tax-adjusted refinancing cost and the remaining mortgage value, and τ is the marginal tax rate. This expression is derived by solving a tractable class of refinancing problems. Our quantitative results closely match those reported by researchers using numerical methods.

Performance characteristics and parametric optimization of an irreversible magnetic Ericsson heat-pump

International Nuclear Information System (INIS)

Wei Fang; Lin Guoxing; Chen Jincan; Brueck, Ekkes

2011-01-01

Taking into account the finite-rate heat transfer in the heat-transfer processes, heat leak between the two external heat reservoirs, regenerative loss, regeneration time, and internal irreversibility due to dissipation of the cycle working substance, an irreversible magnetic Ericsson heat-pump cycle is presented. On the basis of the thermodynamic properties of magnetic materials, the performance characteristics of the irreversible magnetic Ericsson heat-pump are investigated and the relationship between the optimal heating load and the coefficient of performance (COP) is derived. Moreover, the maximum heating load and the corresponding COP as well as the maximum COP and the corresponding heating load are obtained. Furthermore, the other optimal performance characteristics are discussed in detail. The results obtained here may provide some new information for the optimal parameter design and the development of real magnetic Ericsson heat-pumps. -- Research Highlights: →The effects of multi-irreversibilities on the performance of a magnetic heat-pump are revealed. →Mathematical expressions of the heating load and the COP are derived and the optimal performance and operating parameters are analyzed and discussed. →Several important performance bounds are determined.

Design and optimization of flexible multi-generation systems

DEFF Research Database (Denmark)

Lythcke-Jørgensen, Christoffer Ernst

variations and dynamics, and energy system analysis, which fails to consider process integration synergies in local systems. The primary objective of the thesis is to derive a methodology for linking process design practices with energy system analysis for enabling coherent and holistic design optimization...... of flexible multi-generation system. In addition, the case study results emphasize the importance of considering flexible operation, systematic process integration, and systematic assessment of uncertainties in the design optimization. It is recommended that future research focus on assessing system impacts...... from flexible multi-generation systems and performance improvements from storage options....

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.

Optimal Energy Efficiency Fairness of Nodes in Wireless Powered Communication Networks.

Science.gov (United States)

Zhang, Jing; Zhou, Qingjie; Ng, Derrick Wing Kwan; Jo, Minho

2017-09-15

In wireless powered communication networks (WPCNs), it is essential to research energy efficiency fairness in order to evaluate the balance of nodes for receiving information and harvesting energy. In this paper, we propose an efficient iterative algorithm for optimal energy efficiency proportional fairness in WPCN. The main idea is to use stochastic geometry to derive the mean proportionally fairness utility function with respect to user association probability and receive threshold. Subsequently, we prove that the relaxed proportionally fairness utility function is a concave function for user association probability and receive threshold, respectively. At the same time, a sub-optimal algorithm by exploiting alternating optimization approach is proposed. Through numerical simulations, we demonstrate that our sub-optimal algorithm can obtain a result close to optimal energy efficiency proportional fairness with significant reduction of computational complexity.

PID control design for chaotic synchronization using a tribes optimization approach

Energy Technology Data Exchange (ETDEWEB)

Santos Coelho, Leandro dos [Industrial and Systems Engineering Graduate Program, LAS/PPGEPS, Pontifical Catholic University of Parana, PUCPR, Imaculada Conceicao, 1155, 80215-901 Curitiba, Parana (Brazil)], E-mail: leandro.coelho@pucpr.br; Andrade Bernert, Diego Luis de [Industrial and Systems Engineering Graduate Program, LAS/PPGEPS, Pontifical Catholic University of Parana, PUCPR, Imaculada Conceicao, 1155, 80215-901 Curitiba, Parana (Brazil)], E-mail: dbernert@gmail.com

2009-10-15

Recently, the investigation of synchronization and control problems for discrete chaotic systems has stimulated a wide range of research activity including both theoretical studies and practical applications. This paper deals with the tuning of a proportional-integral-derivative (PID) controller using a modified Tribes optimization algorithm based on truncated chaotic Zaslavskii map (MTribes) for synchronization of two identical discrete chaotic systems subject the different initial conditions. The Tribes algorithm is inspired by the social behavior of bird flocking and is also an optimization adaptive procedure that does not require sociometric or swarm size parameter tuning. Numerical simulations are given to show the effectiveness of the proposed synchronization method. In addition, some comparisons of the MTribes optimization algorithm with other continuous optimization methods, including classical Tribes algorithm and particle swarm optimization approaches, are presented.

PID control design for chaotic synchronization using a tribes optimization approach

International Nuclear Information System (INIS)

Santos Coelho, Leandro dos; Andrade Bernert, Diego Luis de

2009-01-01

Recently, the investigation of synchronization and control problems for discrete chaotic systems has stimulated a wide range of research activity including both theoretical studies and practical applications. This paper deals with the tuning of a proportional-integral-derivative (PID) controller using a modified Tribes optimization algorithm based on truncated chaotic Zaslavskii map (MTribes) for synchronization of two identical discrete chaotic systems subject the different initial conditions. The Tribes algorithm is inspired by the social behavior of bird flocking and is also an optimization adaptive procedure that does not require sociometric or swarm size parameter tuning. Numerical simulations are given to show the effectiveness of the proposed synchronization method. In addition, some comparisons of the MTribes optimization algorithm with other continuous optimization methods, including classical Tribes algorithm and particle swarm optimization approaches, are presented.

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.

Verification and Optimization of a PLC Control Schedule

NARCIS (Netherlands)

Brinksma, Hendrik; Mader, Angelika H.; Havelund, K.; Penix, J.; Visser, W.

We report on the use of the SPIN model checker for both the verification of a process control program and the derivation of optimal control schedules. This work was carried out as part of a case study for the EC VHS project (Verification of Hybrid Systems), in which the program for a Programmable

Energy based optimization of viscous–friction dampers on cables

International Nuclear Information System (INIS)

Weber, F; Boston, C

2010-01-01

This investigation optimizes numerically a viscous–friction damper connected to a cable close to one cable anchor for fastest reduction of the total mechanical cable energy during a free vibration decay test. The optimization parameters are the viscous coefficient of the viscous part and the ratio between the friction force and displacement amplitude of the friction part of the transverse damper. Results demonstrate that an almost pure friction damper with negligibly small viscous damping generates fastest cable energy reduction over the entire decay. The ratio between the friction force and displacement amplitude of the optimal friction damper differs from that derived from the energy equivalent optimal viscous damper. The reason for this is that the nonlinearity of the friction damper causes energy spillover from the excited to higher modes of the order of 10%, i.e. cables with attached friction dampers vibrate at several frequencies. This explains why the energy equivalent approach does not yield the optimal friction damper. Analysis of the simulation data demonstrates that the optimally tuned friction damper dissipates the same energy per cycle as if each modal component of the cable were damped by its corresponding optimal linear viscous damper

Multi-objective optimization of HVAC system with an evolutionary computation algorithm

International Nuclear Information System (INIS)

Kusiak, Andrew; Tang, Fan; Xu, Guanglin

2011-01-01

A data-mining approach for the optimization of a HVAC (heating, ventilation, and air conditioning) system is presented. A predictive model of the HVAC system is derived by data-mining algorithms, using a dataset collected from an experiment conducted at a research facility. To minimize the energy while maintaining the corresponding IAQ (indoor air quality) within a user-defined range, a multi-objective optimization model is developed. The solutions of this model are set points of the control system derived with an evolutionary computation algorithm. The controllable input variables - supply air temperature and supply air duct static pressure set points - are generated to reduce the energy use. The results produced by the evolutionary computation algorithm show that the control strategy saves energy by optimizing operations of an HVAC system. -- Highlights: → A data-mining approach for the optimization of a heating, ventilation, and air conditioning (HVAC) system is presented. → The data used in the project has been collected from an experiment conducted at an energy research facility. → The approach presented in the paper leads to accomplishing significant energy savings without compromising the indoor air quality. → The energy savings are accomplished by computing set points for the supply air temperature and the supply air duct static pressure.

Optimal power and distribution control for weakly-coupled-core reactor

International Nuclear Information System (INIS)

Oohori, Takahumi; Kaji, Ikuo

1977-01-01

A numerical procedure has been devised for obtaining the optimal power and distribution control for a weakly-coupled-core reactor. Several difficulties were encountered in solving this optimization problem: (1) nonlinearity of the reactor kinetics equations; (2) neutron-leakage interaction between the cores; (3) localized power changes occurring in addition to the total power changes; (4) constraints imposed on the states - e.g. reactivity, reactor period. To obviate these difficulties, use is made of the generalized Newton method to convert the problem into an iterative sequence of linear programming problems, after approximating the differential equations and the integral performance criterion by a set of discrete algebraic equations. In this procedure, a heuristic but effective method is used for deriving an initial approximation, which is then made to converge toward the optimal solution. Delayed-neutron one-group point reactor models embodying transient temperature feed-back to the reactivity are used in obtaining the kinetics equations for the weakly-coupled-core reactor. The criterion adopted for determining the optimality is a norm relevant to the deviations of neutron density from the desired trajectories or else to the time derivatives of the neutron density; uniform control intervals are prescribed. Examples are given of two coupled-core reactors with typical parameters to illustrate the results obtained with this procedure. A comparison is also made between the coupled-core reactor and the one-point reactor. (auth.)

Group search optimiser-based optimal bidding strategies with no Karush-Kuhn-Tucker optimality conditions

Science.gov (United States)

Yadav, Naresh Kumar; Kumar, Mukesh; Gupta, S. K.

2017-03-01

General strategic bidding procedure has been formulated in the literature as a bi-level searching problem, in which the offer curve tends to minimise the market clearing function and to maximise the profit. Computationally, this is complex and hence, the researchers have adopted Karush-Kuhn-Tucker (KKT) optimality conditions to transform the model into a single-level maximisation problem. However, the profit maximisation problem with KKT optimality conditions poses great challenge to the classical optimisation algorithms. The problem has become more complex after the inclusion of transmission constraints. This paper simplifies the profit maximisation problem as a minimisation function, in which the transmission constraints, the operating limits and the ISO market clearing functions are considered with no KKT optimality conditions. The derived function is solved using group search optimiser (GSO), a robust population-based optimisation algorithm. Experimental investigation is carried out on IEEE 14 as well as IEEE 30 bus systems and the performance is compared against differential evolution-based strategic bidding, genetic algorithm-based strategic bidding and particle swarm optimisation-based strategic bidding methods. The simulation results demonstrate that the obtained profit maximisation through GSO-based bidding strategies is higher than the other three methods.

Use of Mathematical Optimization Models to Derive Healthy and Safe Fish Intake

DEFF Research Database (Denmark)

Persson, Maria; Fagt, Sisse; Pires, Sara Monteiro

2018-01-01

Recommended fish intake differs substantially from observed fish intake. In Denmark, ∼15% of the population consumes the state-recommended fish intake. How much fish individuals eat varies greatly, and this variation cannot be captured by considering the fish intake of the average population. We...... and 55 g/wk, respectively. Using fish intake as an example, we show how quadratic programming models may be used to advise individual consumers how to optimize their diet, taking both benefits and risks into account. This approach has the potential to increase compliance with dietary guidelines...

Derivation of orthogonal leads from the 12-lead electrocardiogram. Performance of an atrial-based transform for the derivation of P loops.

Science.gov (United States)

Guillem, M Salud; Sahakian, Alan V; Swiryn, Steven

2008-01-01

The objective of this study was the evaluation of the accuracy of Dower inverse transform for the derivation of the P wave in orthogonal leads. We tested the accuracy of Dower transform on the P wave and compared it with a P-wave-optimized transform in a database of 123 simultaneous recordings of electrocardiograms and vectorcardiograms. This new transform achieved a lower error when we compared derived vs true measured P waves (mean +/- SD, 12.2 +/- 8.0 VRMS) than Dower transform (14.4 +/- 9.5 Root mean squared voltage) and higher correlation values (Rx, 0.93 +/- 0.12; Ry, 0.90 +/- 0.27; Rz, 0.91 +/- 0.18; vs Dower: Rx, 0.88 +/- 0.15; Ry, 0.91 +/- 0.26; Rz, 0.85 +/- 0.23). We conclude that derivation of orthogonal leads for the P wave can be improved by using an atrial-based transform matrix.

Pilot power optimization for AF relaying using maximum likelihood channel estimation

KAUST Repository

Wang, Kezhi

2014-09-01

Bit error rates (BERs) for amplify-and-forward (AF) relaying systems with two different pilot-symbol-aided channel estimation methods, disintegrated channel estimation (DCE) and cascaded channel estimation (CCE), are derived in Rayleigh fading channels. Based on these BERs, the pilot powers at the source and at the relay are optimized when their total transmitting powers are fixed. Numerical results show that the optimized system has a better performance than other conventional nonoptimized allocation systems. They also show that the optimal pilot power in variable gain is nearly the same as that in fixed gain for similar system settings. andcopy; 2014 IEEE.

Two-Way Multiple Relays Channel: Achievable Rate Region and Optimal Resources

Directory of Open Access Journals (Sweden)

Zouhair Al-Qudah

2016-01-01

Full Text Available This paper considers a communication model containing two users that exchange their information with the help of multiple parallel relay nodes. To avoid interference at these common nodes, two users are required to transmit over the different frequency bands. Based on this scenario, the achievable rate region is initially derived. Next, an optimization scheme is described to choose the best relays that can be used by each user. Then, two power allocation optimization schemes are investigated to allocate the proper average power value to each node. Finally, comparisons between these two optimization schemes are carried out through some numerical examples.

Optimal power allocation for SM-OFDM systems with imperfect channel estimation

International Nuclear Information System (INIS)

Yu, Feng; Song, Lijun; Lei, Xia; Xiao, Yue; Jiang, Zhao Xiang; Jin, Maozhu

2016-01-01

This paper analyses the bit error rate (BER) of the spatial modulation orthogonal frequency division multiplex (SM-OFDM) system and derives the optimal power allocation between the data and the pilot symbols by minimizing the upper bound for the BER operating with imperfect channel estimation. Furthermore, we prove the proposed optimal power allocation scheme applies to all generalized linear interpolation techniques with the minimum mean square error (MMSE) channel estimation . Simulation results show that employing the proposed optimal power allocation provides a substantial gain in terms of the average BER performance for the SM-OFDM system compared to its equal-power-allocation counterpart.

Optimally eating a stochastic cake. A recursive utility approach

International Nuclear Information System (INIS)

Epaulard, Anne; Pommeret, Aude

2003-01-01

In this short paper, uncertainties on resource stock and on technical progress are introduced into an intertemporal equilibrium model of optimal extraction of a non-renewable resource. The representative consumer maximizes a recursive utility function which disentangles between intertemporal elasticity of substitution and risk aversion. A closed-form solution is derived for both the optimal extraction and price paths. The value of the intertemporal elasticity of substitution relative to unity is then crucial in understanding extraction. Moreover, this model leads to a non-renewable resource price following a geometric Brownian motion

The Optimal Strategy to Research Pension Funds in China Based on the Loss Function

OpenAIRE

Gao, Jian-wei; Guo, Hong-zhen; Ye, Yan-cheng

2007-01-01

Based on the theory of actuarial present value, a pension fund investment goal can be formulated as an objective function. The mean-variance model is extended by defining the objective loss function. Furthermore, using the theory of stochastic optimal control, an optimal investment model is established under the minimum expectation of loss function. In the light of the Hamilton-Jacobi-Bellman (HJB) equation, the analytic solution of the optimal investment strategy problem is derived.

Simultaneous Optimization of Decisions Using a Linear Utility Function.

Science.gov (United States)

Vos, Hans J.

1990-01-01

An approach is presented to simultaneously optimize decision rules for combinations of elementary decisions through a framework derived from Bayesian decision theory. The developed linear utility model for selection-mastery decisions was applied to a sample of 43 first year medical students to illustrate the procedure. (SLD)

Improving beamforming by optimization of acoustic array microphone positions

NARCIS (Netherlands)

Malgoezar, A.M.N.; Snellen, M.; Sijtsma, P.; Simons, D.G.

2016-01-01

Assigning proper positions to microphones within arrays is essential in order to reduce or eliminate side- and grating lobes in 2D beamform images. In this paper an objective function is derived providing a measure for the presence of artificial sources. Using the global optimization method

Blackjack in Holland Casino's : Basic, optimal and winning strategies

NARCIS (Netherlands)

van der Genugten, B.B.

1995-01-01

This paper considers the cardgame Blackjack according to the rules of Holland Casino's in the Netherlands. Expected gains of strategies are derived with simulation and also with analytic tools. New effiency concepts based on the gains of the basic and the optimal strategy are introduced. A general

Optimal number of coarse-grained sites in different components of large biomolecular complexes.

Science.gov (United States)

Sinitskiy, Anton V; Saunders, Marissa G; Voth, Gregory A

2012-07-26

The computational study of large biomolecular complexes (molecular machines, cytoskeletal filaments, etc.) is a formidable challenge facing computational biophysics and biology. To achieve biologically relevant length and time scales, coarse-grained (CG) models of such complexes usually must be built and employed. One of the important early stages in this approach is to determine an optimal number of CG sites in different constituents of a complex. This work presents a systematic approach to this problem. First, a universal scaling law is derived and numerically corroborated for the intensity of the intrasite (intradomain) thermal fluctuations as a function of the number of CG sites. Second, this result is used for derivation of the criterion for the optimal number of CG sites in different parts of a large multibiomolecule complex. In the zeroth-order approximation, this approach validates the empirical rule of taking one CG site per fixed number of atoms or residues in each biomolecule, previously widely used for smaller systems (e.g., individual biomolecules). The first-order corrections to this rule are derived and numerically checked by the case studies of the Escherichia coli ribosome and Arp2/3 actin filament junction. In different ribosomal proteins, the optimal number of amino acids per CG site is shown to differ by a factor of 3.5, and an even wider spread may exist in other large biomolecular complexes. Therefore, the method proposed in this paper is valuable for the optimal construction of CG models of such complexes.

Topology optimization using the finite volume method

DEFF Research Database (Denmark)

Gersborg-Hansen, Allan; Bendsøe, Martin P.; Sigmund, Ole

2005-01-01

in this presentation is focused on a prototype model for topology optimization of steady heat diffusion. This allows for a study of the basic ingredients in working with FVM methods when dealing with topology optimization problems. The FVM and FEM based formulations differ both in how one computes the design...... derivative of the system matrix $\\mathbf K$ and in how one computes the discretized version of certain objective functions. Thus for a cost function for minimum dissipated energy (like minimum compliance for an elastic structure) one obtains an expression $ c = \\mathbf u^\\T \\tilde{\\mathbf K} \\mathbf u...... the arithmetic and harmonic average with the latter being the well known Reuss lower bound. [1] Bendsøe, MP and Sigmund, O 2004: Topology Optimization - Theory, Methods, and Applications. Berlin Heidelberg: Springer Verlag [2] Versteeg, HK and Malalasekera, W 1995: An introduction to Computational Fluid Dynamics...

Topology optimization using the finite volume method

DEFF Research Database (Denmark)

in this presentation is focused on a prototype model for topology optimization of steady heat diffusion. This allows for a study of the basic ingredients in working with FVM methods when dealing with topology optimization problems. The FVM and FEM based formulations differ both in how one computes the design...... derivative of the system matrix K and in how one computes the discretized version of certain objective functions. Thus for a cost function for minimum dissipated energy (like minimum compliance for an elastic structure) one obtains an expression c = u^\\T \\tilde{K}u $, where \\tilde{K} is different from K...... the well known Reuss lower bound. [1] Bendsøe, M.P.; Sigmund, O. 2004: Topology Optimization - Theory, Methods, and Applications. Berlin Heidelberg: Springer Verlag [2] Versteeg, H. K.; W. Malalasekera 1995: An introduction to Computational Fluid Dynamics: the Finite Volume Method. London: Longman...

Using remote sensing images to design optimal field sampling schemes

CSIR Research Space (South Africa)

Debba, Pravesh

2008-08-01

Full Text Available sampling schemes case studies Optimized field sampling representing the overall distribution of a particular mineral Deriving optimal exploration target zones CONTINUUM REMOVAL for vegetation [13, 27, 46]. The convex hull transform is a method... of normalizing spectra [16, 41]. The convex hull technique is anal- ogous to fitting a rubber band over a spectrum to form a continuum. Figure 5 shows the concept of the convex hull transform. The differ- ence between the hull and the orig- inal spectrum...

FEM for time-fractional diffusion equations, novel optimal error analyses

OpenAIRE

Mustapha, Kassem

2016-01-01

A semidiscrete Galerkin finite element method applied to time-fractional diffusion equations with time-space dependent diffusivity on bounded convex spatial domains will be studied. The main focus is on achieving optimal error results with respect to both the convergence order of the approximate solution and the regularity of the initial data. By using novel energy arguments, for each fixed time $t$, optimal error bounds in the spatial $L^2$- and $H^1$-norms are derived for both cases: smooth...

Treating autoimmune disorders with venom-derived peptides.

Science.gov (United States)

Shen, Bingzheng; Cao, Zhijian; Li, Wenxin; Sabatier, Jean-Marc; Wu, Yingliang

2017-09-01

The effective treatment of autoimmune diseases remains a challenge. Voltage-gated potassium Kv1.3 channels, which are expressed in lymphocytes, are a new therapeutic target for treating autoimmune disease. Consequently, Kv1.3 channel-inhibiting venom-derived peptides are a prospective resource for new drug discovery and clinical application. Area covered: Preclinical and clinical studies have produced a wealth of information on Kv1.3 channel-inhibiting venom-derived peptides, especially from venomous scorpions and sea anemones. This review highlights the advances in screening and design of these peptides with diverse structures and potencies. It focuses on representative strategies for improving peptide selectivity and discusses the preclinical research on those venom-derived peptides as well as their clinical developmental status. Expert opinion: Encouraging results indicate that peptides isolated from the venom of venomous animals are a large resource for discovering immunomodulators that act on Kv1.3 channels. Since the structural diversity of venom-derived peptides determines the variety of their pharmacological activities, the design and optimization of venom-peptides for improved Kv1.3 channel-specificity has been advanced through some representative strategies, such as peptide chemical modification, amino acid residue truncation and binding interface modulation. These advances should further accelerate research, development and the future clinical application of venom-derived peptides selectively targeting Kv1.3 channels.

An analytical method for optimal design of MR valve structures

International Nuclear Information System (INIS)

Nguyen, Q H; Choi, S B; Lee, Y S; Han, M S

2009-01-01

This paper proposes an analytical methodology for the optimal design of a magnetorheological (MR) valve structure. The MR valve structure is constrained in a specific volume and the optimization problem identifies geometric dimensions of the valve structure that maximize the yield stress pressure drop of a MR valve or the yield stress damping force of a MR damper. In this paper, the single-coil and two-coil annular MR valve structures are considered. After describing the schematic configuration and operating principle of a typical MR valve and damper, a quasi-static model is derived based on the Bingham model of a MR fluid. The magnetic circuit of the valve and damper is then analyzed by applying Kirchoff's law and the magnetic flux conservation rule. Based on quasi-static modeling and magnetic circuit analysis, the optimization problem of the MR valve and damper is built. In order to reduce the computation load, the optimization problem is simplified and a procedure to obtain the optimal solution of the simplified optimization problem is presented. The optimal solution of the simplified optimization problem of the MR valve structure constrained in a specific volume is then obtained and compared with the solution of the original optimization problem and the optimal solution obtained from the finite element method

Quasivelocities and Optimal Control for underactuated Mechanical Systems

International Nuclear Information System (INIS)

Colombo, L.; Martin de Diego, D.

2010-01-01

This paper is concerned with the application of the theory of quasivelocities for optimal control for underactuated mechanical systems. Using this theory, we convert the original problem in a variational second-order lagrangian system subjected to constraints. The equations of motion are geometrically derived using an adaptation of the classical Skinner and Rusk formalism.

Optimal Power Allocation of a Wireless Sensor Node under Different Rate Constraints

KAUST Repository

Solares, Jose

2011-07-01

Wireless sensor networks consist of the placement of sensors over a broad area in order to acquire data. Depending on the application, different design criteria should be considered in the construction of the sensors but among all of them, the battery life-cycle is of crucial interest. Power minimization is a problem that has been addressed from different approaches which include an analysis from an architectural perspective and with bit error rate and/or discrete instantaneous transmission rate constraints, among others. In this work, the optimal transmit power of a sensor node while satisfying different rate constraints is derived. First, an optimization problem with an instantaneous transmission rate constraint is addressed. Next, the optimal power is analyzed, but now with an average transmission rate constraint. The optimal solution for a class of fading channels, in terms of system parameters, is presented and a suboptimal solution is also proposed for an easier, yet efficient, implementation. Insightful asymptotical analysis for both schemes, considering a Rayleigh fading channel, are shown. Furthermore, the optimal power allocation for a sensor node in a cognitive radio environment is analyzed where an optimum solution for a class of fading channels is again derived. In all cases, numerical results are provided for either Rayleigh or Nakagami-m fading channels. The results obtained are extended to scenarios where we have either one transmitter-multiple receivers or multiple transmitters-one receiver.

Level set method for optimal shape design of MRAM core. Micromagnetic approach

International Nuclear Information System (INIS)

Melicher, Valdemar; Cimrak, Ivan; Keer, Roger van

2008-01-01

We aim at optimizing the shape of the magnetic core in MRAM memories. The evolution of the magnetization during the writing process is described by the Landau-Lifshitz equation (LLE). The actual shape of the core in one cell is characterized by the coefficient γ. Cost functional f=f(γ) expresses the quality of the writing process having in mind the competition between the full-select and the half-select element. We derive an explicit form of the derivative F=∂f/∂γ which allows for the use of gradient-type methods for the actual computation of the optimized shape (e.g., steepest descend method). The level set method (LSM) is employed for the representation of the piecewise constant coefficient γ

Discrete optimization in architecture architectural & urban layout

CERN Document Server

Zawidzki, Machi

2016-01-01

This book presents three projects that demonstrate the fundamental problems of architectural design and urban composition – the layout design, evaluation and optimization. Part I describes the functional layout design of a residential building, and an evaluation of the quality of a town square (plaza). The algorithm for the functional layout design is based on backtracking using a constraint satisfaction approach combined with coarse grid discretization. The algorithm for the town square evaluation is based on geometrical properties derived directly from its plan. Part II introduces a crowd-simulation application for the analysis of escape routes on floor plans, and optimization of a floor plan for smooth crowd flow. The algorithms presented employ agent-based modeling and cellular automata.

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.

A superlinear interior points algorithm for engineering design optimization

Science.gov (United States)

Herskovits, J.; Asquier, J.

1990-01-01

We present a quasi-Newton interior points algorithm for nonlinear constrained optimization. It is based on a general approach consisting of the iterative solution in the primal and dual spaces of the equalities in Karush-Kuhn-Tucker optimality conditions. This is done in such a way to have primal and dual feasibility at each iteration, which ensures satisfaction of those optimality conditions at the limit points. This approach is very strong and efficient, since at each iteration it only requires the solution of two linear systems with the same matrix, instead of quadratic programming subproblems. It is also particularly appropriate for engineering design optimization inasmuch at each iteration a feasible design is obtained. The present algorithm uses a quasi-Newton approximation of the second derivative of the Lagrangian function in order to have superlinear asymptotic convergence. We discuss theoretical aspects of the algorithm and its computer implementation.

A one-layer recurrent neural network for non-smooth convex optimization subject to linear inequality constraints

International Nuclear Information System (INIS)

Liu, Xiaolan; Zhou, Mi

2016-01-01

In this paper, a one-layer recurrent network is proposed for solving a non-smooth convex optimization subject to linear inequality constraints. Compared with the existing neural networks for optimization, the proposed neural network is capable of solving more general convex optimization with linear inequality constraints. 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.

Optimal control systems in hydro power plants

International Nuclear Information System (INIS)

Babunski, Darko L.

2012-01-01

The aim of the research done in this work is focused on obtaining the optimal models of hydro turbine including auxiliary equipment, analysis of governors for hydro power plants and analysis and design of optimal control laws that can be easily applicable in real hydro power plants. The methodology of the research and realization of the set goals consist of the following steps: scope of the models of hydro turbine, and their modification using experimental data; verification of analyzed models and comparison of advantages and disadvantages of analyzed models, with proposal of turbine model for design of control low; analysis of proportional-integral-derivative control with fixed parameters and gain scheduling and nonlinear control; analysis of dynamic characteristics of turbine model including control and comparison of parameters of simulated system with experimental data; design of optimal control of hydro power plant considering proposed cost function and verification of optimal control law with load rejection measured data. The hydro power plant models, including model of power grid are simulated in case of island ing and restoration after breakup and load rejection with consideration of real loading and unloading of hydro power plant. Finally, simulations provide optimal values of control parameters, stability boundaries and results easily applicable to real hydro power plants. (author)

The Optimal Strategy to Research Pension Funds in China Based on the Loss Function

Directory of Open Access Journals (Sweden)

Jian-wei Gao

2007-10-01

Full Text Available Based on the theory of actuarial present value, a pension fund investment goal can be formulated as an objective function. The mean-variance model is extended by defining the objective loss function. Furthermore, using the theory of stochastic optimal control, an optimal investment model is established under the minimum expectation of loss function. In the light of the Hamilton-Jacobi-Bellman (HJB equation, the analytic solution of the optimal investment strategy problem is derived.

Portfolio theory of optimal isometric force production: Variability predictions and nonequilibrium fluctuation dissipation theorem

Science.gov (United States)

Frank, T. D.; Patanarapeelert, K.; Beek, P. J.

2008-05-01

We derive a fundamental relationship between the mean and the variability of isometric force. The relationship arises from an optimal collection of active motor units such that the force variability assumes a minimum (optimal isometric force). The relationship is shown to be independent of the explicit motor unit properties and of the dynamical features of isometric force production. A constant coefficient of variation in the asymptotic regime and a nonequilibrium fluctuation-dissipation theorem for optimal isometric force are predicted.

Portfolio theory of optimal isometric force production: Variability predictions and nonequilibrium fluctuation-dissipation theorem

International Nuclear Information System (INIS)

Frank, T.D.; Patanarapeelert, K.; Beek, P.J.

2008-01-01

We derive a fundamental relationship between the mean and the variability of isometric force. The relationship arises from an optimal collection of active motor units such that the force variability assumes a minimum (optimal isometric force). The relationship is shown to be independent of the explicit motor unit properties and of the dynamical features of isometric force production. A constant coefficient of variation in the asymptotic regime and a nonequilibrium fluctuation-dissipation theorem for optimal isometric force are predicted

Production and Optimization of Direct Coal Liquefaction derived Low Carbon-Footprint Transportation Fuels

Energy Technology Data Exchange (ETDEWEB)

Steven Markovich

2010-06-30

This report summarizes works conducted under DOE Contract No. DE-FC26-05NT42448. The work scope was divided into two categories - (a) experimental program to pretreat and refine a coal derived syncrude sample to meet transportation fuels requirements; (b) system analysis of a commercial scale direct coal liquefaction facility. The coal syncrude was derived from a bituminous coal by Headwaters CTL, while the refining study was carried out under a subcontract to Axens North America. The system analysis included H{sub 2} production cost via six different options, conceptual process design, utilities requirements, CO{sub 2} emission and overall plant economy. As part of the system analysis, impact of various H{sub 2} production options was evaluated. For consistence the comparison was carried out using the DOE H2A model. However, assumptions in the model were updated using Headwaters database. Results of Tier 2 jet fuel specifications evaluation by the Fuels & Energy Branch, US Air Force Research Laboratory (AFRL/RZPF) located at Wright Patterson Air Force Base (Ohio) are also discussed in this report.

Optimizing Ship Speed to Minimize Total Fuel Consumption with Multiple Time Windows

Directory of Open Access Journals (Sweden)

Jae-Gon Kim

2016-01-01

Full Text Available We study the ship speed optimization problem with the objective of minimizing the total fuel consumption. We consider multiple time windows for each port call as constraints and formulate the problem as a nonlinear mixed integer program. We derive intrinsic properties of the problem and develop an exact algorithm based on the properties. Computational experiments show that the suggested algorithm is very efficient in finding an optimal solution.

PI Stabilization for Congestion Control of AQM Routers with Tuning Parameter Optimization

Directory of Open Access Journals (Sweden)

S. Chebli

2016-09-01

Full Text Available In this paper, we consider the problem of stabilizing network using a new proportional- integral (PI based congestion controller in active queue management (AQM router; with appropriate model approximation in the first order delay systems, we seek a stability region of the controller by using the Hermite- Biehler theorem, which isapplicable to quasipolynomials. A Genetic Algorithm technique is employed to derive optimal or near optimal PI controller parameters.

Deterministic methods for multi-control fuel loading optimization

Science.gov (United States)

Rahman, Fariz B. Abdul

We have developed a multi-control fuel loading optimization code for pressurized water reactors based on deterministic methods. The objective is to flatten the fuel burnup profile, which maximizes overall energy production. The optimal control problem is formulated using the method of Lagrange multipliers and the direct adjoining approach for treatment of the inequality power peaking constraint. The optimality conditions are derived for a multi-dimensional multi-group optimal control problem via calculus of variations. Due to the Hamiltonian having a linear control, our optimal control problem is solved using the gradient method to minimize the Hamiltonian and a Newton step formulation to obtain the optimal control. We are able to satisfy the power peaking constraint during depletion with the control at beginning of cycle (BOC) by building the proper burnup path forward in time and utilizing the adjoint burnup to propagate the information back to the BOC. Our test results show that we are able to achieve our objective and satisfy the power peaking constraint during depletion using either the fissile enrichment or burnable poison as the control. Our fuel loading designs show an increase of 7.8 equivalent full power days (EFPDs) in cycle length compared with 517.4 EFPDs for the AP600 first cycle.

Optimal data replication: A new approach to optimizing parallel EM algorithms on a mesh-connected multiprocessor for 3D PET image reconstruction

International Nuclear Information System (INIS)

Chen, C.M.; Lee, S.Y.

1995-01-01

The EM algorithm promises an estimated image with the maximal likelihood for 3D PET image reconstruction. However, due to its long computation time, the EM algorithm has not been widely used in practice. While several parallel implementations of the EM algorithm have been developed to make the EM algorithm feasible, they do not guarantee an optimal parallelization efficiency. In this paper, the authors propose a new parallel EM algorithm which maximizes the performance by optimizing data replication on a mesh-connected message-passing multiprocessor. To optimize data replication, the authors have formally derived the optimal allocation of shared data, group sizes, integration and broadcasting of replicated data as well as the scheduling of shared data accesses. The proposed parallel EM algorithm has been implemented on an iPSC/860 with 16 PEs. The experimental and theoretical results, which are consistent with each other, have shown that the proposed parallel EM algorithm could improve performance substantially over those using unoptimized data replication

Optimizing Cooperative Cognitive Radio Networks with Opportunistic Access

KAUST Repository

Zafar, Ammar; Alouini, Mohamed-Slim; Chen, Yunfei; Radaydeh, Redha M.

2012-01-01

Optimal resource allocation for cooperative cognitive radio networks with opportunistic access to the licensed spectrum is studied. Resource allocation is based on minimizing the symbol error rate at the receiver. Both the cases of all-participate relaying and selective relaying are considered. The objective function is derived and the constraints are detailed for both scenarios. It is then shown that the objective functions and the constraints are nonlinear and nonconvex functions of the parameters of interest, that is, source and relay powers, symbol time, and sensing time. Therefore, it is difficult to obtain closed-form solutions for the optimal resource allocation. The optimization problem is then solved using numerical techniques. Numerical results show that the all-participate system provides better performance than its selection counterpart, at the cost of greater resources. © 2012 Ammar Zafar et al.

Optimizing Cooperative Cognitive Radio Networks with Opportunistic Access

KAUST Repository

Zafar, Ammar

2012-09-16

Optimal resource allocation for cooperative cognitive radio networks with opportunistic access to the licensed spectrum is studied. Resource allocation is based on minimizing the symbol error rate at the receiver. Both the cases of all-participate relaying and selective relaying are considered. The objective function is derived and the constraints are detailed for both scenarios. It is then shown that the objective functions and the constraints are nonlinear and nonconvex functions of the parameters of interest, that is, source and relay powers, symbol time, and sensing time. Therefore, it is difficult to obtain closed-form solutions for the optimal resource allocation. The optimization problem is then solved using numerical techniques. Numerical results show that the all-participate system provides better performance than its selection counterpart, at the cost of greater resources. © 2012 Ammar Zafar et al.

Biomass derived porous nitrogen doped carbon for electrochemical devices

Directory of Open Access Journals (Sweden)

Litao Yan

2017-04-01

Full Text Available Biomass derived porous nanostructured nitrogen doped carbon (PNC has been extensively investigated as the electrode material for electrochemical catalytic reactions and rechargeable batteries. Biomass with and without containing nitrogen could be designed and optimized to prepare PNC via hydrothermal carbonization, pyrolysis, and other methods. The presence of nitrogen in carbon can provide more active sites for ion absorption, improve the electronic conductivity, increase the bonding between carbon and sulfur, and enhance the electrochemical catalytic reaction. The synthetic methods of natural biomass derived PNC, heteroatomic co- or tri-doping into biomass derived carbon and the application of biomass derived PNC in rechargeable Li/Na batteries, high energy density Li–S batteries, supercapacitors, metal-air batteries and electrochemical catalytic reaction (oxygen reduction and evolution reactions, hydrogen evolution reaction are summarized and discussed in this review. Biomass derived PNCs deliver high performance electrochemical storage properties for rechargeable batteries/supercapacitors and superior electrochemical catalytic performance toward hydrogen evolution, oxygen reduction and evolution, as promising electrodes for electrochemical devices including battery technologies, fuel cell and electrolyzer. Keywords: Biomass, Nitrogen doped carbon, Batteries, Fuel cell, Electrolyzer

Polymer Derived Yttrium Silicate Ablative TPS Materials for Next-Generation Exploration Missions, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — Through the proposed NASA SBIR program, NanoSonic will optimize its HybridSil® derived yttrium silicates to serve as next-generation reinforcement for carbon and...

Optimization principles and the figure of merit for triboelectric generators.

Science.gov (United States)

Peng, Jun; Kang, Stephen Dongmin; Snyder, G Jeffrey

2017-12-01

Energy harvesting with triboelectric nanogenerators is a burgeoning field, with a growing portfolio of creative application schemes attracting much interest. Although power generation capabilities and its optimization are one of the most important subjects, a satisfactory elemental model that illustrates the basic principles and sets the optimization guideline remains elusive. We use a simple model to clarify how the energy generation mechanism is electrostatic induction but with a time-varying character that makes the optimal matching for power generation more restrictive. By combining multiple parameters into dimensionless variables, we pinpoint the optimum condition with only two independent parameters, leading to predictions of the maximum limit of power density, which allows us to derive the triboelectric material and device figure of merit. We reveal the importance of optimizing device capacitance, not only load resistance, and minimizing the impact of parasitic capacitance. Optimized capacitances can lead to an overall increase in power density of more than 10 times.

Optimal propulsive flapping in Stokes flows.

Science.gov (United States)

Was, Loïc; Lauga, Eric

2014-03-01

Swimming fish and flying insects use the flapping of fins and wings to generate thrust. In contrast, microscopic organisms typically deform their appendages in a wavelike fashion. Since a flapping motion with two degrees of freedom is able, in theory, to produce net forces from a time-periodic actuation at all Reynolds numbers, we compute in this paper the optimal flapping kinematics of a rigid spheroid in a Stokes flow. The hydrodynamics for the force generation and energetics of the flapping motion is solved exactly. We then compute analytically the gradient of a flapping efficiency in the space of all flapping gaits and employ it to derive numerically the optimal flapping kinematics as a function of the shape of the flapper and the amplitude of the motion. The kinematics of optimal flapping are observed to depend weakly on the flapper shape and are very similar to the figure-eight motion observed in the motion of insect wings. Our results suggest that flapping could be a exploited experimentally as a propulsion mechanism valid across the whole range of Reynolds numbers.

Optimal propulsive flapping in Stokes flows

International Nuclear Information System (INIS)

Was, Loïc; Lauga, Eric

2014-01-01

Swimming fish and flying insects use the flapping of fins and wings to generate thrust. In contrast, microscopic organisms typically deform their appendages in a wavelike fashion. Since a flapping motion with two degrees of freedom is able, in theory, to produce net forces from a time-periodic actuation at all Reynolds numbers, we compute in this paper the optimal flapping kinematics of a rigid spheroid in a Stokes flow. The hydrodynamics for the force generation and energetics of the flapping motion is solved exactly. We then compute analytically the gradient of a flapping efficiency in the space of all flapping gaits and employ it to derive numerically the optimal flapping kinematics as a function of the shape of the flapper and the amplitude of the motion. The kinematics of optimal flapping are observed to depend weakly on the flapper shape and are very similar to the figure-eight motion observed in the motion of insect wings. Our results suggest that flapping could be a exploited experimentally as a propulsion mechanism valid across the whole range of Reynolds numbers. (paper)

Time-optimal control of reactor power

International Nuclear Information System (INIS)

Bernard, J.A.

1987-01-01

Control laws that permit adjustments in reactor power to be made in minimum time and without overshoot have been formulated and demonstrated. These control laws which are derived from the standard and alternate dynamic period equations, are closed-form expressions of general applicability. These laws were deduced by noting that if a system is subject to one or more operating constraints, then the time-optimal response is to move the system along these constraints. Given that nuclear reactors are subject to limitations on the allowed reactor period, a time-optimal control law would step the period from infinity to the minimum allowed value, hold the period at that value for the duration of the transient, and then step the period back to infinity. The change in reactor would therefore be accomplished in minimum time. The resulting control laws are superior to other forms of time-optimal control because they are general-purpose, closed-form expressions that are both mathematically tractable and readily implanted. Moreover, these laws include provisions for the use of feedback. The results of simulation studies and actual experiments on the 5 MWt MIT Research Reactor in which these time-optimal control laws were used successfully to adjust the reactor power are presented

Optimal inventory management and order book modeling

KAUST Repository

Baradel, Nicolas

2018-02-16

We model the behavior of three agent classes acting dynamically in a limit order book of a financial asset. Namely, we consider market makers (MM), high-frequency trading (HFT) firms, and institutional brokers (IB). Given a prior dynamic of the order book, similar to the one considered in the Queue-Reactive models [14, 20, 21], the MM and the HFT define their trading strategy by optimizing the expected utility of terminal wealth, while the IB has a prescheduled task to sell or buy many shares of the considered asset. We derive the variational partial differential equations that characterize the value functions of the MM and HFT and explain how almost optimal control can be deduced from them. We then provide a first illustration of the interactions that can take place between these different market participants by simulating the dynamic of an order book in which each of them plays his own (optimal) strategy.

Optimized theory for simple and molecular fluids.

Science.gov (United States)

Marucho, M; Montgomery Pettitt, B

2007-03-28

An optimized closure approximation for both simple and molecular fluids is presented. A smooth interpolation between Perkus-Yevick and hypernetted chain closures is optimized by minimizing the free energy self-consistently with respect to the interpolation parameter(s). The molecular version is derived from a refinement of the method for simple fluids. In doing so, a method is proposed which appropriately couples an optimized closure with the variant of the diagrammatically proper integral equation recently introduced by this laboratory [K. M. Dyer et al., J. Chem. Phys. 123, 204512 (2005)]. The simplicity of the expressions involved in this proposed theory has allowed the authors to obtain an analytic expression for the approximate excess chemical potential. This is shown to be an efficient tool to estimate, from first principles, the numerical value of the interpolation parameters defining the aforementioned closure. As a preliminary test, representative models for simple fluids and homonuclear diatomic Lennard-Jones fluids were analyzed, obtaining site-site correlation functions in excellent agreement with simulation data.

Hydrodynamics and burn of optimally imploded deuterium-tritium spheres

International Nuclear Information System (INIS)

Mason, R.J.; Morse, R.L.

1975-01-01

The phenomenology of optimized laser-driven DT sphere implosions leading to efficient thermonuclear burn is reviewed. The optimal laser deposition profile for spheres is heuristically derived. The performance of a 7.5 μg sphere, exposed to its optimal 5.3 kJ pulse, is scrutinized in detail. The timing requirements for efficient central ignition of propagating burn in the sphere are carefully explored. The difficulties stemming from superthermal electron production and thermal flux limitation are discussed. The hydro-burn performance of spheres is characterized as a function of the pulse energy, peak power, time scale, pulse exponent, wavelength, and on the degree of flux limitation. The optimal pulse parameters are determined for spheres with masses ranging from 40 ng to 250 μg, requiring from 50 J to 150 kJ of input energy, and the corresponding optimal performance levels are calculated. Discussion is given to the hydro-burn performance of new structured fusion targets, in which the DT is contained as a gas or frozen as an ice shell inside a high Z pusher-tamper layer

Optimization of the variational basis in the three body problem

International Nuclear Information System (INIS)

Simenog, I.V.; Pushkash, O.M.; Bestuzheva, A.B.

1995-01-01

The procedure of variational oscillator basis optimization is proposed to the calculation the energy spectra of three body systems. The hierarchy of basis functions is derived and energies of ground and excited states for three gravitating particles is obtained with high accuracy. 12 refs

Design optimization of brushed permanent magnet D C motor by genetic algorithm

CERN Document Server

Amini, S

2002-01-01

Because of field winding replacement with permanent magnet in brushed permanent magnet D C (PMDC) motors, field losses are eliminated and the structure of the motor is more simple. Efficiency of these motors is therefore increased and the manufacturing process is simplified. Hence, these motors are commonly used in low power applications and their design and optimization is an important consideration. Genetic algorithms are proposed for design optimization of PMD motors because of their independence to objective function structure and its derivative. In this paper genetic algorithms are evaluated for PMDC motor design optimization. an introduction is first presented about PMDC motors, general design procedure and elements of their optimization. Genetic algorithms are then briefly described. Finally results of optimization by genetic algorithms are compared with the one obtained using a conventional method.

Design optimization of brushed permanent magnet D C motor by genetic algorithm

International Nuclear Information System (INIS)

Amini, S.; Oraee, H.

2002-01-01

Because of field winding replacement with permanent magnet in brushed permanent magnet D C (PMDC) motors, field losses are eliminated and the structure of the motor is more simple. Efficiency of these motors is therefore increased and the manufacturing process is simplified. Hence, these motors are commonly used in low power applications and their design and optimization is an important consideration. Genetic algorithms are proposed for design optimization of PMD motors because of their independence to objective function structure and its derivative. In this paper genetic algorithms are evaluated for PMDC motor design optimization. an introduction is first presented about PMDC motors, general design procedure and elements of their optimization. Genetic algorithms are then briefly described. Finally results of optimization by genetic algorithms are compared with the one obtained using a conventional method

Synthesis of Side Chain Liquid Crystal Polymers by Living Ring Opening Metathesis Polymerization. 3. Influence of Molecular Weight, Interconnecting Unit and Substituent on the Mesomorphic behavior of Polymers with Laterally Attached Mesogens

Science.gov (United States)

1992-04-08

polymethylsiloxanes, 6 -7 polyacrylates ,2,4,5 polymethacrylates, 1 ,3 and polychloroacrylates, 5 exhibit only nematic mesophases regardless of the...corresponding carboxyl chloride. Potassium bicyclo[2.2.1]hept-2-ene-5- carboxylate was prepared by titrating a methanolic solution of the carboxylic acid...Esterification of the Corresponding Benzyl Bromides. Monomers 1I-n were prepared in 47-88% yield using the following procedure. A mixture of potassium bicyclo

Effect of silane coupling agents on basalt fiber-epoxidized vegetable oil matrix composite materials analyzed by the single fiber fragmentation technique

OpenAIRE

Samper Madrigal, María Dolores; Petrucci, R.; Sánchez Nacher, Lourdes; Balart Gimeno, Rafael Antonio; Kenny, J. M.

2015-01-01

The fiber-matrix interfacial shear strength (IFSS) of biobased epoxy composites reinforced with basalt fiber was investigated by the fragmentation method. Basalt fibers were modified with four different silanes, (3-aminopropyl)trimethoxysilane, [3-(2-aminoethylamino)propyl]-trimethoxysilane, trimethoxy[2-(7-oxabicyclo[4.1.0]hept-3-yl)ethyl]silane and (3-glycidyloxypropyl)trimethoxysilane to improve the adhesion between the basalt fiber and the resin. The analysis of the fiber tensile strength...

Optimal fossil-fuel taxation with backstop technologies and tenure risk

Energy Technology Data Exchange (ETDEWEB)

Strand, Jon [World Bank, Development Economics Group, Washington DC 20433 (United States); Department of Economics, University of Oslo (Norway)

2010-03-15

The paper derives the global welfare-optimizing time path for a tax on fossil fuels causing a negative stock externality (climate change), under increasing marginal extraction cost, and in the presence of an unlimited backstop resource causing no externality. In a basic competitive case, the optimal tax equals the Pigou rate, equivalent to the present discounted value of marginal damage costs. We consider two separate types of tenure insecurity for resource owners, and their impact on the tax implementing the optimal policy. When insecure control is with respect to future ownership to the resource, competitive extraction is higher than otherwise, and the efficiency-implementing tax exceeds the Pigou rate. When tenure insecurity instead implies possible expropriation ('holdup') of investment in extraction capacity, it deters extraction, and the optimal tax is lower than the Pigou rate. (author)

Optimal design of a magneto-rheological brake absorber for torsional vibration control

International Nuclear Information System (INIS)

Nguyen, Q H; Choi, S B

2012-01-01

This research presents an optimal design of a magneto-rheological (MR) brake absorber for torsional vibration control of a rotating shaft. Firstly, the configuration of an MR brake absorber for torsional vibration control of a rotating shaft system is proposed. Then, the braking torque of the MR brake is derived based on the Bingham plastic model of the MR fluid. By assuming that the behaviour of the MR brake absorber is similar to that of a dry friction torsional damper, the optimal braking torque to control the torsional vibration is determined and validated by simulation. The optimal design problem of the MR brake absorber is then developed and a procedure to solve the optimal problem is proposed. Based on the proposed optimal design procedure, the optimal design of a specific rotating shaft system is performed. Vibration control performance of the shaft system employing the optimized MR brake absorber is then investigated through simulation and discussion on the results is given. (paper)

Optimal design of a magneto-rheological brake absorber for torsional vibration control

Science.gov (United States)

Nguyen, Q. H.; Choi, S. B.

2012-02-01

This research presents an optimal design of a magneto-rheological (MR) brake absorber for torsional vibration control of a rotating shaft. Firstly, the configuration of an MR brake absorber for torsional vibration control of a rotating shaft system is proposed. Then, the braking torque of the MR brake is derived based on the Bingham plastic model of the MR fluid. By assuming that the behaviour of the MR brake absorber is similar to that of a dry friction torsional damper, the optimal braking torque to control the torsional vibration is determined and validated by simulation. The optimal design problem of the MR brake absorber is then developed and a procedure to solve the optimal problem is proposed. Based on the proposed optimal design procedure, the optimal design of a specific rotating shaft system is performed. Vibration control performance of the shaft system employing the optimized MR brake absorber is then investigated through simulation and discussion on the results is given.

Convex optimization problem prototyping for image reconstruction in computed tomography with the Chambolle–Pock algorithm

DEFF Research Database (Denmark)

Sidky, Emil Y.; Jørgensen, Jakob Heide; Pan, Xiaochuan

2012-01-01

The primal–dual optimization algorithm developed in Chambolle and Pock (CP) (2011 J. Math. Imag. Vis. 40 1–26) is applied to various convex optimization problems of interest in computed tomography (CT) image reconstruction. This algorithm allows for rapid prototyping of optimization problems...... for the purpose of designing iterative image reconstruction algorithms for CT. The primal–dual algorithm is briefly summarized in this paper, and its potential for prototyping is demonstrated by explicitly deriving CP algorithm instances for many optimization problems relevant to CT. An example application...

Optimization of in vitro cell labeling methods for human umbilical cord-derived mesenchymal stem cells.

Science.gov (United States)

Tao, R; Sun, T-J; Han, Y-Q; Xu, G; Liu, J; Han, Y-F

2014-01-01

Human umbilical cord-derived mesenchymal stem cells (hUCMSCs) are a novel source of seed cells for cell therapy and tissue engineering. However, in vitro labeling methods for hUCMSCs need to be optimized for better detection of transplanted cells. To identify the most stable and efficient method for labeling hUCMSCs in vitro. hUCMSCs were isolated using a modified enzymatic digestion procedure and cultured. hUCMSCs of passage three (P3) were then labeled with BrdU, PKH26, or lentivirus-GFP and passaged further. Cells from the first labeled passage (LP1), the fourth labeled passage (LP4) and later passages were observed using a fluorescence microscope. The differentiation potential of LP4 cells was assessed by induction with adipogenic and osteogenic medium. Flow cytometry was used to measure the percentage of labeled cells and the percentage of apoptotic or dead cells. The labeling efficiencies of the three hUCMSC-labeling methods were compared in vitro. BrdU, PKH26, and lentivirus-GFP all labeled LP1 cells with high intensity and clarity. However, the BrdU labeling of the LP4 cells was vague and not localized to the cell nuclei; LP9 cells were not detected under a fluorescence microscope. There was also a significant decrease in the fluorescence intensity of PKH26-labeled LP4 cells, and LP11 cells were not detected under a fluorescence microscope. However, the fluorescence of LP4 cells labeled with lentivirus-GFP remained strong, and cells labeled with lentivirus-GFP were detected up to LP14 under a fluorescence microscope. Statistical analyses indicated that percentages of LP1 cells labeled with PKH26 and lentivirus-GFP were significantly higher than that of cells labeled with BrdU (p 0.05) was observed between the death rates of labeled and unlabeled cells. Lentivirus-GFP is a valid method for long-term in vitro labeling, and it may be used as a long-term hUCMSC tracker following transplantation in vivo.

Extracellular matrix-derived hydrogels for dental stem cell delivery.

Science.gov (United States)

Viswanath, Aiswarya; Vanacker, Julie; Germain, Loïc; Leprince, Julian G; Diogenes, Anibal; Shakesheff, Kevin M; White, Lisa J; des Rieux, Anne

2017-01-01

Decellularized mammalian extracellular matrices (ECM) have been widely accepted as an ideal substrate for repair and remodelling of numerous tissues in clinical and pre-clinical studies. Recent studies have demonstrated the ability of ECM scaffolds derived from site-specific homologous tissues to direct cell differentiation. The present study investigated the suitability of hydrogels derived from different source tissues: bone, spinal cord and dentine, as suitable carriers to deliver human apical papilla derived mesenchymal stem cells (SCAP) for spinal cord regeneration. Bone, spinal cord, and dentine ECM hydrogels exhibited distinct structural, mechanical, and biological characteristics. All three hydrogels supported SCAP viability and proliferation. However, only spinal cord and bone derived hydrogels promoted the expression of neural lineage markers. The specific environment of ECM scaffolds significantly affected the differentiation of SCAP to a neural lineage, with stronger responses observed with spinal cord ECM hydrogels, suggesting that site-specific tissues are more likely to facilitate optimal stem cell behavior for constructive spinal cord regeneration. © 2016 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 105A: 319-328, 2017. © 2016 Wiley Periodicals, Inc.

What is the optimal architecture for visual information routing?

Science.gov (United States)

Wolfrum, Philipp; von der Malsburg, Christoph

2007-12-01

Analyzing the design of networks for visual information routing is an underconstrained problem due to insufficient anatomical and physiological data. We propose here optimality criteria for the design of routing networks. For a very general architecture, we derive the number of routing layers and the fanout that minimize the required neural circuitry. The optimal fanout l is independent of network size, while the number k of layers scales logarithmically (with a prefactor below 1), with the number n of visual resolution units to be routed independently. The results are found to agree with data of the primate visual system.

An L∞/L1-Constrained Quadratic Optimization Problem with Applications to Neural Networks

International Nuclear Information System (INIS)

Leizarowitz, Arie; Rubinstein, Jacob

2003-01-01

Pattern formation in associative neural networks is related to a quadratic optimization problem. Biological considerations imply that the functional is constrained in the L ∞ norm and in the L 1 norm. We consider such optimization problems. We derive the Euler-Lagrange equations, and construct basic properties of the maximizers. We study in some detail the case where the kernel of the quadratic functional is finite-dimensional. In this case the optimization problem can be fully characterized by the geometry of a certain convex and compact finite-dimensional set

Ant colony optimization as a descriptor selection in QSPR modeling: Estimation of the λmax of anthraquinones-based dyes

OpenAIRE

Morteza Atabati; Kobra Zarei; Azam Borhani

2016-01-01

Quantitative structure–property relationship (QSPR) studies based on ant colony optimization (ACO) were carried out for the prediction of λmax of 9,10-anthraquinone derivatives. ACO is a meta-heuristic algorithm, which is derived from the observation of real ants and proposed to feature selection. After optimization of 3D geometry of structures by the semi-empirical quantum-chemical calculation at AM1 level, different descriptors were calculated by the HyperChem and Dragon softwares (1514 des...

Surrogate-Based Optimization of Biogeochemical Transport Models

Science.gov (United States)

Prieß, Malte; Slawig, Thomas

2010-09-01

First approaches towards a surrogate-based optimization method for a one-dimensional marine biogeochemical model of NPZD type are presented. The model, developed by Oschlies and Garcon [1], simulates the distribution of nitrogen, phytoplankton, zooplankton and detritus in a water column and is driven by ocean circulation data. A key issue is to minimize the misfit between the model output and given observational data. Our aim is to reduce the overall optimization cost avoiding expensive function and derivative evaluations by using a surrogate model replacing the high-fidelity model in focus. This in particular becomes important for more complex three-dimensional models. We analyse a coarsening in the discretization of the model equations as one way to create such a surrogate. Here the numerical stability crucially depends upon the discrete stepsize in time and space and the biochemical terms. We show that for given model parameters the level of grid coarsening can be choosen accordingly yielding a stable and satisfactory surrogate. As one example of a surrogate-based optimization method we present results of the Aggressive Space Mapping technique (developed by John W. Bandler [2, 3]) applied to the optimization of this one-dimensional biogeochemical transport model.

Transmit power optimization for green multihop relaying over Nakagami-m fading channels

KAUST Repository

Randrianantenaina, Itsikiantsoa

2014-03-01

In this paper, we investigate the optimal transmit power strategy to maximize the energy efficiency of a multihop relaying network. Considering the communication between a source and a destination through multiple Amplify-and-Forward relays, we first give the expression of the total instantaneous system energy consumption. Then, we define the energy efficiency in our context and obtain its expression in closed-form when the communication is over Nakagami-m fading channels. The analysis yields to the derivation of a global transmit power strategy where each individual node is contributing to the end-to-end overall energy efficiency. Numercial results are presented to illustrate the analysis. Comparison with Monte Carlo simulation results confirms the accuracy of our derivations, and assesses the gains of the proposed power optimization strategy. © 2014 IEEE.

Transmit power optimization for green multihop relaying over Nakagami-m fading channels

KAUST Repository

Randrianantenaina, Itsikiantsoa; Benjillali, Mustapha; Alouini, Mohamed-Slim

2014-01-01

In this paper, we investigate the optimal transmit power strategy to maximize the energy efficiency of a multihop relaying network. Considering the communication between a source and a destination through multiple Amplify-and-Forward relays, we first give the expression of the total instantaneous system energy consumption. Then, we define the energy efficiency in our context and obtain its expression in closed-form when the communication is over Nakagami-m fading channels. The analysis yields to the derivation of a global transmit power strategy where each individual node is contributing to the end-to-end overall energy efficiency. Numercial results are presented to illustrate the analysis. Comparison with Monte Carlo simulation results confirms the accuracy of our derivations, and assesses the gains of the proposed power optimization strategy. © 2014 IEEE.

Optimizing the Usability of Brain-Computer Interfaces.

Science.gov (United States)

Zhang, Yin; Chase, Steve M

2018-03-22

Brain-computer interfaces are in the process of moving from the laboratory to the clinic. These devices act by reading neural activity and using it to directly control a device, such as a cursor on a computer screen. An open question in the field is how to map neural activity to device movement in order to achieve the most proficient control. This question is complicated by the fact that learning, especially the long-term skill learning that accompanies weeks of practice, can allow subjects to improve performance over time. Typical approaches to this problem attempt to maximize the biomimetic properties of the device in order to limit the need for extensive training. However, it is unclear if this approach would ultimately be superior to performance that might be achieved with a nonbiomimetic device once the subject has engaged in extended practice and learned how to use it. Here we approach this problem using ideas from optimal control theory. Under the assumption that the brain acts as an optimal controller, we present a formal definition of the usability of a device and show that the optimal postlearning mapping can be written as the solution of a constrained optimization problem. We then derive the optimal mappings for particular cases common to most brain-computer interfaces. Our results suggest that the common approach of creating biomimetic interfaces may not be optimal when learning is taken into account. More broadly, our method provides a blueprint for optimal device design in general control-theoretic contexts.

Constraining neutron guide optimizations with phase-space considerations

Energy Technology Data Exchange (ETDEWEB)

Bertelsen, Mads, E-mail: mads.bertelsen@gmail.com; Lefmann, Kim

2016-09-11

We introduce a method named the Minimalist Principle that serves to reduce the parameter space for neutron guide optimization when the required beam divergence is limited. The reduced parameter space will restrict the optimization to guides with a minimal neutron intake that are still theoretically able to deliver the maximal possible performance. The geometrical constraints are derived using phase-space propagation from moderator to guide and from guide to sample, while assuming that the optimized guides will achieve perfect transport of the limited neutron intake. Guide systems optimized using these constraints are shown to provide performance close to guides optimized without any constraints, however the divergence received at the sample is limited to the desired interval, even when the neutron transport is not limited by the supermirrors used in the guide. As the constraints strongly limit the parameter space for the optimizer, two control parameters are introduced that can be used to adjust the selected subspace, effectively balancing between maximizing neutron transport and avoiding background from unnecessary neutrons. One parameter is needed to describe the expected focusing abilities of the guide to be optimized, going from perfectly focusing to no correlation between position and velocity. The second parameter controls neutron intake into the guide, so that one can select exactly how aggressively the background should be limited. We show examples of guides optimized using these constraints which demonstrates the higher signal to noise than conventional optimizations. Furthermore the parameter controlling neutron intake is explored which shows that the simulated optimal neutron intake is close to the analytically predicted, when assuming that the guide is dominated by multiple scattering events.

Construction and Optimization of a Heterologous Pathway for Protocatechuate Catabolism in Escherichia coli Enables Bioconversion of Model Aromatic Compounds.

Science.gov (United States)

Clarkson, Sonya M; Giannone, Richard J; Kridelbaugh, Donna M; Elkins, James G; Guss, Adam M; Michener, Joshua K

2017-09-15

The production of biofuels from lignocellulose yields a substantial lignin by-product stream that currently has few applications. Biological conversion of lignin-derived compounds into chemicals and fuels has the potential to improve the economics of lignocellulose-derived biofuels, but few microbes are able both to catabolize lignin-derived aromatic compounds and to generate valuable products. While Escherichia coli has been engineered to produce a variety of fuels and chemicals, it is incapable of catabolizing most aromatic compounds. Therefore, we engineered E. coli to catabolize protocatechuate, a common intermediate in lignin degradation, as the sole source of carbon and energy via heterologous expression of a nine-gene pathway from Pseudomonas putida KT2440. We next used experimental evolution to select for mutations that increased growth with protocatechuate more than 2-fold. Increasing the strength of a single ribosome binding site in the heterologous pathway was sufficient to recapitulate the increased growth. After optimization of the core pathway, we extended the pathway to enable catabolism of a second model compound, 4-hydroxybenzoate. These engineered strains will be useful platforms to discover, characterize, and optimize pathways for conversions of lignin-derived aromatics. IMPORTANCE Lignin is a challenging substrate for microbial catabolism due to its polymeric and heterogeneous chemical structure. Therefore, engineering microbes for improved catabolism of lignin-derived aromatic compounds will require the assembly of an entire network of catabolic reactions, including pathways from genetically intractable strains. Constructing defined pathways for aromatic compound degradation in a model host would allow rapid identification, characterization, and optimization of novel pathways. We constructed and optimized one such pathway in E. coli to enable catabolism of a model aromatic compound, protocatechuate, and then extended the pathway to a related

Performance and robustness of optimal fractional fuzzy PID controllers for pitch control of a wind turbine using chaotic optimization algorithms.

Science.gov (United States)

Asgharnia, Amirhossein; Shahnazi, Reza; Jamali, Ali

2018-05-11

The most studied controller for pitch control of wind turbines is proportional-integral-derivative (PID) controller. However, due to uncertainties in wind turbine modeling and wind speed profiles, the need for more effective controllers is inevitable. On the other hand, the parameters of PID controller usually are unknown and should be selected by the designer which is neither a straightforward task nor optimal. To cope with these drawbacks, in this paper, two advanced controllers called fuzzy PID (FPID) and fractional-order fuzzy PID (FOFPID) are proposed to improve the pitch control performance. Meanwhile, to find the parameters of the controllers the chaotic evolutionary optimization methods are used. Using evolutionary optimization methods not only gives us the unknown parameters of the controllers but also guarantees the optimality based on the chosen objective function. To improve the performance of the evolutionary algorithms chaotic maps are used. All the optimization procedures are applied to the 2-mass model of 5-MW wind turbine model. The proposed optimal controllers are validated using simulator FAST developed by NREL. Simulation results demonstrate that the FOFPID controller can reach to better performance and robustness while guaranteeing fewer fatigue damages in different wind speeds in comparison to FPID, fractional-order PID (FOPID) and gain-scheduling PID (GSPID) controllers. Copyright © 2018 ISA. Published by Elsevier Ltd. All rights reserved.

Modelling on optimal portfolio with exchange rate based on discontinuous stochastic process

Science.gov (United States)

Yan, Wei; Chang, Yuwen

2016-12-01

Considering the stochastic exchange rate, this paper is concerned with the dynamic portfolio selection in financial market. The optimal investment problem is formulated as a continuous-time mathematical model under mean-variance criterion. These processes follow jump-diffusion processes (Weiner process and Poisson process). Then the corresponding Hamilton-Jacobi-Bellman(HJB) equation of the problem is presented and its efferent frontier is obtained. Moreover, the optimal strategy is also derived under safety-first criterion.

Deriving Optimal End of Day Storage for Pumped-Storage Power Plants in the Joint Energy and Reserve Day-Ahead Scheduling

Directory of Open Access Journals (Sweden)

Manuel Chazarra

2017-06-01

Full Text Available This paper presents a new methodology to maximise the income and derive the optimal end of day storage of closed-loop and daily-cycle pumped-storage hydropower plants. The plants participate in the day-ahead energy market as a price-taker and in the secondary regulation reserve market as a price-maker, in the context of the Iberian electricity system. The real-time use of the committed reserves is considered in the model formulation. The operation of the plants with the proposed methodology is compared to the ones that use an end of day storage of an empty reservoir or half of the storage capacity. Results show that the proposed methodology increases the maximum theoretical income in all the plants analysed both if they only participate in the day-ahead energy market and if they also participate in the secondary regulation service. It is also shown that the increase in the maximum theoretical income strongly depends on the size of the plant. In addition, it is proven that the end of day storages change notably in the new reserve-driven strategies of pumped-storage hydropower plants and that the proposed methodology is even more recommended if the secondary regulation service is considered.

The necessary and sufficient conditions of the optimality for hyperbolic systems with non-differentiable performance functional

International Nuclear Information System (INIS)

Kowalewski, A.

1982-11-01

In this paper an optimal control problem with non-differentiable cost function for distributed parameter system is solved. As an example an optimal control problem for system described by a linear partial differential of hyperbolic type with the Neuman's boundary condition is considered. By use of the Milutin-Dubovicki method, necessary and sufficient conditions of optimality with non-differentiable performance functional and constrained control are derived for Neuman's problem. (author)

A Space-Mapping Framework for Engineering Optimization: Theory and Implementation

DEFF Research Database (Denmark)

Koziel, Slawomir; Bandler, John W.; Madsen, Kaj

2006-01-01

a region of interest. Output space mapping ensures the matching of responses and first-order derivatives between the mapped coarse model and the fine model at the current iteration point in the optimization process. We provide theoretical results that show the importance of the explicit use of sensitivity...... information to the convergence properties of our family of algorithms. Our algorithm is demonstrated on the optimization of a microstrip band-pass filter, a band-pass filter with double-coupled resonators and a seven-section impedance transformer. We describe the novel user-oriented software package SMF...

Optimized Hypernetted-Chain Solutions for Helium -4 Surfaces and Metal Surfaces

Science.gov (United States)

Qian, Guo-Xin

This thesis is a study of inhomogeneous Bose systems such as liquid ('4)He slabs and inhomogeneous Fermi systems such as the electron gas in metal films, at zero temperature. Using a Jastrow-type many-body wavefunction, the ground state energy is expressed by means of Bogoliubov-Born-Green-Kirkwood -Yvon and Hypernetted-Chain techniques. For Bose systems, Euler-Lagrange equations are derived for the one- and two -body functions and systematic approximation methods are physically motivated. It is shown that the optimized variational method includes a self-consistent summation of ladder- and ring-diagrams of conventional many-body theory. For Fermi systems, a linear potential model is adopted to generate the optimized Hartree-Fock basis. Euler-Lagrange equations are derived for the two-body correlations which serve to screen the strong bare Coulomb interaction. The optimization of the pair correlation leads to an expression of correlation energy in which the state averaged RPA part is separated. Numerical applications are presented for the density profile and pair distribution function for both ('4)He surfaces and metal surfaces. Both the bulk and surface energies are calculated in good agreement with experiments.

Optimal designs for population pharmacokinetic studies of oral artesunate in patients with uncomplicated falciparum malaria

Directory of Open Access Journals (Sweden)

Lindegardh Niklas

2011-07-01

Full Text Available Abstract Background Currently, population pharmacokinetic (PK studies of anti-malarial drugs are designed primarily by the logistical and ethical constraints of taking blood samples from patients, and the statistical models that are fitted to the data are not formally considered. This could lead to imprecise estimates of the target PK parameters, and/or designs insufficient to estimate all of the parameters. Optimal design methodology has been developed to determine blood sampling schedules that will yield precise parameter estimates within the practical constraints of sampling the study populations. In this work optimal design methods were used to determine sampling designs for typical future population PK studies of dihydroartemisinin, the principal biologically active metabolite of oral artesunate. Methods Optimal designs were derived using freely available software and were based on appropriate structural PK models from an analysis of data or the literature and key sampling constraints identified in a questionnaire sent to active malaria researchers (3-4 samples per patient, at least 15 minutes between samples. The derived optimal designs were then evaluated via simulation-estimation. Results The derived optimal sampling windows were 17 to 29 minutes, 30 to 57 minutes, 2.5 to 3.7 hours and 5.8 to 6.6 hours for non-pregnant adults; 16 to 29 minutes, 31 minutes to 1 hour, 2.0 to 3.4 hours and 5.5 to 6.6 hours for designs with non-pregnant adults and children and 35 to 59 minutes, 1.2 to 3.4 hours, 3.4 to 4.9 hours and 6.0 to 8.0 hours for pregnant women. The optimal designs resulted in acceptable precision of the PK parameters. Conclusions The proposed sampling designs in this paper are robust and efficient and should be considered in future PK studies of oral artesunate where only three or four blood samples can be collected.

Discovery of imidazopyridine derivatives as highly potent respiratory syncytial virus fusion inhibitors.

Science.gov (United States)

Feng, Song; Hong, Di; Wang, Baoxia; Zheng, Xiufang; Miao, Kun; Wang, Lisha; Yun, Hongying; Gao, Lu; Zhao, Shuhai; Shen, Hong C

2015-03-12

A series of imidazolepyridine derivatives were designed and synthesized according to the established docking studies. The imidazopyridine derivatives were found to have good potency and physical-chemical properties. Several highly potent compounds such as 8ji, 8jl, and 8jm were identified with single nanomolar activities. The most potent compound 8jm showed an IC50 of 3 nM, lower microsome clearance and no CYP inhibition. The profile of 8jm appeared to be superior to BMS433771, and supported further optimization.

Multiple energy supply risks, optimal reserves, and optimal domestic production capacities

International Nuclear Information System (INIS)

Zweifel, P.; Ferrari, M.

1992-01-01

This study starts from the observation that today's Western trading nations are exposed to multiple risks of energy supplies, e.g. simultaneous shortage of oil and electricity supplies. To cope with these risks, oil can be stockpiled as well as domestic capacity for power production built up. Adopting the viewpoint of a policy maker who aims at minimizing the expected cost of security of supply, optimal simultaneous adjustments of oil stocks and electric production capacities to exogenous changes such as economic growth are derived. Against this benchmark, one-dimensional rules such as 'oil reserves for 90 days' turn out to be not only suboptimal but also to foster adjustments that exacerbate suboptimality. 9 refs., 1 tabs

OPTIMAL EXPERIMENT DESIGN FOR MAGNETIC RESONANCE FINGERPRINTING

OpenAIRE

Zhao, Bo; Haldar, Justin P.; Setsompop, Kawin; Wald, Lawrence L.

2016-01-01

Magnetic resonance (MR) fingerprinting is an emerging quantitative MR imaging technique that simultaneously acquires multiple tissue parameters in an efficient experiment. In this work, we present an estimation-theoretic framework to evaluate and design MR fingerprinting experiments. More specifically, we derive the Cram��r-Rao bound (CRB), a lower bound on the covariance of any unbiased estimator, to characterize parameter estimation for MR fingerprinting. We then formulate an optimal experi...

Optimization of space-time material layout for 1D wave propagation with varying mass and stiffness parameters

DEFF Research Database (Denmark)

Jensen, Jakob Søndergaard

2010-01-01

Results are presented for optimal layout of materials in the spatial and temporal domains for a 1D structure subjected to transient wave propagation. A general optimization procedure is outlined including derivation of design sensitivities for the case when the mass density and stiffness vary...

Optimal estimate of a pure qubit state from Uhlmann-Josza fidelity

Energy Technology Data Exchange (ETDEWEB)

Aoki, Manuel Avila, E-mail: manvlk@yahoo.com [Centro Universitario UAEM Valle de Chalco, UAEMex, Edo. de Mexico (Mexico)

2012-04-15

In the framework of collective measurements, efforts have been made to reconstruct one-qubit states. Such schemes find an obstacle in the no-cloning theorem, which prevents full reconstruction of a quantum state. Quantum Mechanics thus restricts to obtain estimates of the reconstruction of a pure qubit. We discuss the optimal estimate on the basis of the Uhlmann-Josza fidelity, respecting the limitations imposed by the no-cloning theorem. We derive a realistic optimal expression for the average fidelity. Our formalism also introduces an optimization parameter L. Values close to zero imply full reconstruction of the qubit (i. e., the classical limit), while larger L's represent good quantum optimization of the qubit estimate. The parameter L is interpreted as the degree of quantumness of the average fidelity associated with the reconstruction. (author)

Bi-Criteria Optimization of Decision Trees with Applications to Data Analysis

KAUST Repository

Chikalov, Igor

2017-10-19

This paper is devoted to the study of bi-criteria optimization problems for decision trees. We consider different cost functions such as depth, average depth, and number of nodes. We design algorithms that allow us to construct the set of Pareto optimal points (POPs) for a given decision table and the corresponding bi-criteria optimization problem. These algorithms are suitable for investigation of medium-sized decision tables. We discuss three examples of applications of the created tools: the study of relationships among depth, average depth and number of nodes for decision trees for corner point detection (such trees are used in computer vision for object tracking), study of systems of decision rules derived from decision trees, and comparison of different greedy algorithms for decision tree construction as single- and bi-criteria optimization algorithms.

Optimal Network QoS over the Internet of Vehicles for E-Health Applications

Directory of Open Access Journals (Sweden)

Di Lin

2016-01-01

Full Text Available Wireless technologies are pervasive to support ubiquitous healthcare applications. However, a critical issue of using wireless communications under a healthcare scenario is the electromagnetic interference (EMI caused by RF transmission, and a high level of EMI may lead to a critical malfunction of medical sensors. In consideration of EMI on medical sensors, we study the optimization of quality of service (QoS within the whole Internet of vehicles for E-health and propose a novel model to optimize the QoS by allocating the transmit power of each user. Our results show that the optimal power control policy depends on the objective of optimization problems: a greedy policy is optimal to maximize the summation of QoS of each user, whereas a fair policy is optimal to maximize the product of QoS of each user. Algorithms are taken to derive the optimal policies, and numerical results of optimizing QoS are presented for both objectives and QoS constraints.

Machine Learning Techniques in Optimal Design

Science.gov (United States)

Cerbone, Giuseppe

1992-01-01

Many important applications can be formalized as constrained optimization tasks. For example, we are studying the engineering domain of two-dimensional (2-D) structural design. In this task, the goal is to design a structure of minimum weight that bears a set of loads. A solution to a design problem in which there is a single load (L) and two stationary support points (S1 and S2) consists of four members, E1, E2, E3, and E4 that connect the load to the support points is discussed. In principle, optimal solutions to problems of this kind can be found by numerical optimization techniques. However, in practice [Vanderplaats, 1984] these methods are slow and they can produce different local solutions whose quality (ratio to the global optimum) varies with the choice of starting points. Hence, their applicability to real-world problems is severely restricted. To overcome these limitations, we propose to augment numerical optimization by first performing a symbolic compilation stage to produce: (a) objective functions that are faster to evaluate and that depend less on the choice of the starting point and (b) selection rules that associate problem instances to a set of recommended solutions. These goals are accomplished by successive specializations of the problem class and of the associated objective functions. In the end, this process reduces the problem to a collection of independent functions that are fast to evaluate, that can be differentiated symbolically, and that represent smaller regions of the overall search space. However, the specialization process can produce a large number of sub-problems. This is overcome by deriving inductively selection rules which associate problems to small sets of specialized independent sub-problems. Each set of candidate solutions is chosen to minimize a cost function which expresses the tradeoff between the quality of the solution that can be obtained from the sub-problem and the time it takes to produce it. The overall solution

Sensorless optimal sinusoidal brushless direct current for hard disk drives

Science.gov (United States)

Soh, C. S.; Bi, C.

2009-04-01

Initiated by the availability of digital signal processors and emergence of new applications, market demands for permanent magnet synchronous motors have been surging. As its back-emf is sinusoidal, the drive current should also be sinusoidal for reducing the torque ripple. However, in applications like hard disk drives, brushless direct current (BLDC) drive is adopted instead of sinusoidal drive for simplification. The adoption, however, comes at the expense of increased harmonics, losses, torque pulsations, and acoustics. In this paper, we propose a sensorless optimal sinusoidal BLDC drive. First and foremost, the derivation for an optimal sinusoidal drive is presented, and a power angle control scheme is proposed to achieve an optimal sinusoidal BLDC. The scheme maintains linear relationship between the motor speed and drive voltage. In an attempt to execute the sensorless drive, an innovative power angle measurement scheme is devised, which takes advantage of the freewheeling diodes and measures the power angle through the detection of diode voltage drops. The objectives as laid out will be presented and discussed in this paper, supported by derivations, simulations, and experimental results. The proposed scheme is straightforward, brings about the benefits of sensorless sinusoidal drive, negates the need for current sensors by utilizing the freewheeling diodes, and does not incur additional cost.

Optimization in Quaternion Dynamic Systems: Gradient, Hessian, and Learning Algorithms.

Science.gov (United States)

Xu, Dongpo; Xia, Yili; Mandic, Danilo P

2016-02-01

The optimization of real scalar functions of quaternion variables, such as the mean square error or array output power, underpins many practical applications. Solutions typically require the calculation of the gradient and Hessian. However, real functions of quaternion variables are essentially nonanalytic, which are prohibitive to the development of quaternion-valued learning systems. To address this issue, we propose new definitions of quaternion gradient and Hessian, based on the novel generalized Hamilton-real (GHR) calculus, thus making a possible efficient derivation of general optimization algorithms directly in the quaternion field, rather than using the isomorphism with the real domain, as is current practice. In addition, unlike the existing quaternion gradients, the GHR calculus allows for the product and chain rule, and for a one-to-one correspondence of the novel quaternion gradient and Hessian with their real counterparts. Properties of the quaternion gradient and Hessian relevant to numerical applications are also introduced, opening a new avenue of research in quaternion optimization and greatly simplified the derivations of learning algorithms. The proposed GHR calculus is shown to yield the same generic algorithm forms as the corresponding real- and complex-valued algorithms. Advantages of the proposed framework are illuminated over illustrative simulations in quaternion signal processing and neural networks.

Hooke–Jeeves Method-used Local Search in a Hybrid Global Optimization Algorithm

Directory of Open Access Journals (Sweden)

V. D. Sulimov

2014-01-01

Full Text Available Modern methods for optimization investigation of complex systems are based on development and updating the mathematical models of systems because of solving the appropriate inverse problems. Input data desirable for solution are obtained from the analysis of experimentally defined consecutive characteristics for a system or a process. Causal characteristics are the sought ones to which equation coefficients of mathematical models of object, limit conditions, etc. belong. The optimization approach is one of the main ones to solve the inverse problems. In the main case it is necessary to find a global extremum of not everywhere differentiable criterion function. Global optimization methods are widely used in problems of identification and computation diagnosis system as well as in optimal control, computing to-mography, image restoration, teaching the neuron networks, other intelligence technologies. Increasingly complicated systems of optimization observed during last decades lead to more complicated mathematical models, thereby making solution of appropriate extreme problems significantly more difficult. A great deal of practical applications may have the problem con-ditions, which can restrict modeling. As a consequence, in inverse problems the criterion functions can be not everywhere differentiable and noisy. Available noise means that calculat-ing the derivatives is difficult and unreliable. It results in using the optimization methods without calculating the derivatives.An efficiency of deterministic algorithms of global optimization is significantly restrict-ed by their dependence on the extreme problem dimension. When the number of variables is large they use the stochastic global optimization algorithms. As stochastic algorithms yield too expensive solutions, so this drawback restricts their applications. Developing hybrid algo-rithms that combine a stochastic algorithm for scanning the variable space with deterministic local search

Synthesis and Fungicidal Activity of β-Carboline Alkaloids and Their Derivatives

Directory of Open Access Journals (Sweden)

Zhibin Li

2015-07-01

Full Text Available A series of β-Carboline derivatives were designed, synthesized, and evaluated for their fungicidal activities in this study. Several derivatives electively exhibited fungicidal activities against some fungi. Especially, compound F5 exhibited higher fungicidal activity against Rhizoctonia solani (53.35% than commercial antiviral agent validamycin (36.4%; compound F16 exhibited high fungicidal activity against Oospora citriaurantii ex Persoon (43.28%. Some of the alkaloids and their derivatives (compounds F4 and F25 exhibited broad-spectrum fungicidal activity. Specifically, compound F4 exhibited excellent high broad-spectrum fungicidal activity in vitro, and the curative and protection activities against P. litchi in vivo reached 92.59% and 59.26%, respectively. The new derivative, F4, with optimized physicochemical properties, obviously exhibited higher activities both in vitro and in vivo; therefore, F4 may be used as a new lead structure for the development of fungicidal drugs.

Spatio-temporal optimal law enforcement using Stackelberg games

International Nuclear Information System (INIS)

Naja, R.; Mouawad, N.; Ghandour, A.

2017-01-01

Every year, road accidents claim the lives of around 1.2 million worldwide (USDOT-NHTSA,2012). Deploying speed traps helps bounding vehicles speed and reducing collisions. Nevertheless, deterministic speed traps deployment in both spatial and temporal domains, allow drivers to learn and anticipate covered areas. In thispaper, we present a novel framework that provides randomized speed traps deployment schedule. It uses game theory in order to model drivers and law enforcers behavior. In this context, Stackelberg security game is used to derive best strategies to deploy. The game optimal solution maximizes law enforcer utility. This research work aims to optimize the deployment of speed traps on Lebanese highways according to the accidents probability input data. This work complements the near real time accident map provided by the Lebanese National Council for Scientific Research and designs an optimal speed trap map targeting Lebanese highways.(author)

Skin appendage-derived stem cells: cell biology and potential for wound repair.

Science.gov (United States)

Xie, Jiangfan; Yao, Bin; Han, Yutong; Huang, Sha; Fu, Xiaobing

2016-01-01

Stem cells residing in the epidermis and skin appendages are imperative for skin homeostasis and regeneration. These stem cells also participate in the repair of the epidermis after injuries, inducing restoration of tissue integrity and function of damaged tissue. Unlike epidermis-derived stem cells, comprehensive knowledge about skin appendage-derived stem cells remains limited. In this review, we summarize the current knowledge of skin appendage-derived stem cells, including their fundamental characteristics, their preferentially expressed biomarkers, and their potential contribution involved in wound repair. Finally, we will also discuss current strategies, future applications, and limitations of these stem cells, attempting to provide some perspectives on optimizing the available therapy in cutaneous repair and regeneration.

Shape Optimization of Swimming Sheets

Energy Technology Data Exchange (ETDEWEB)

Wilkening, J.; Hosoi, A.E.

2005-03-01

The swimming behavior of a flexible sheet which moves by propagating deformation waves along its body was first studied by G. I. Taylor in 1951. In addition to being of theoretical interest, this problem serves as a useful model of the locomotion of gastropods and various micro-organisms. Although the mechanics of swimming via wave propagation has been studied extensively, relatively little work has been done to define or describe optimal swimming by this mechanism.We carry out this objective for a sheet that is separated from a rigid substrate by a thin film of viscous Newtonian fluid. Using a lubrication approximation to model the dynamics, we derive the relevant Euler-Lagrange equations to optimize swimming speed and efficiency. The optimization equations are solved numerically using two different schemes: a limited memory BFGS method that uses cubic splines to represent the wave profile, and a multi-shooting Runge-Kutta approach that uses the Levenberg-Marquardt method to vary the parameters of the equations until the constraints are satisfied. The former approach is less efficient but generalizes nicely to the non-lubrication setting. For each optimization problem we obtain a one parameter family of solutions that becomes singular in a self-similar fashion as the parameter approaches a critical value. We explore the validity of the lubrication approximation near this singular limit by monitoring higher order corrections to the zeroth order theory and by comparing the results with finite element solutions of the full Stokes equations.

OCOPTR, Minimization of Nonlinear Function, Variable Metric Method, Derivative Calculation. DRVOCR, Minimization of Nonlinear Function, Variable Metric Method, Derivative Calculation

International Nuclear Information System (INIS)

Nazareth, J. L.

1979-01-01

1 - Description of problem or function: OCOPTR and DRVOCR are computer programs designed to find minima of non-linear differentiable functions f: R n →R with n dimensional domains. OCOPTR requires that the user only provide function values (i.e. it is a derivative-free routine). DRVOCR requires the user to supply both function and gradient information. 2 - Method of solution: OCOPTR and DRVOCR use the variable metric (or quasi-Newton) method of Davidon (1975). For OCOPTR, the derivatives are estimated by finite differences along a suitable set of linearly independent directions. For DRVOCR, the derivatives are user- supplied. Some features of the codes are the storage of the approximation to the inverse Hessian matrix in lower trapezoidal factored form and the use of an optimally-conditioned updating method. Linear equality constraints are permitted subject to the initial Hessian factor being chosen correctly. 3 - Restrictions on the complexity of the problem: The functions to which the routine is applied are assumed to be differentiable. The routine also requires (n 2 /2) + 0(n) storage locations where n is the problem dimension

Enhanced adipogenic differentiation of bovine bone marrow-derived mesenchymal stem cells

Science.gov (United States)

Until now, the isolation and characterization of bovine bone marrow-derived mesenchymal stem cells (bBM-MSCs) have not been established, which prompted us to optimize the differentiation protocol for bBM-MSCs. In this study, bBM-MSCs were freshly isolated from three 6-month-old cattle and used for p...

Optimal Power Constrained Distributed Detection over a Noisy Multiaccess Channel

Directory of Open Access Journals (Sweden)

Zhiwen Hu

2015-01-01

Full Text Available The problem of optimal power constrained distributed detection over a noisy multiaccess channel (MAC is addressed. Under local power constraints, we define the transformation function for sensor to realize the mapping from local decision to transmitted waveform. The deflection coefficient maximization (DCM is used to optimize the performance of power constrained fusion system. Using optimality conditions, we derive the closed-form solution to the considered problem. Monte Carlo simulations are carried out to evaluate the performance of the proposed new method. Simulation results show that the proposed method could significantly improve the detection performance of the fusion system with low signal-to-noise ratio (SNR. We also show that the proposed new method has a robust detection performance for broad SNR region.

Optimization of MIMO Systems Capacity Using Large Random Matrix Methods

Directory of Open Access Journals (Sweden)

Philippe Loubaton

2012-11-01

Full Text Available This paper provides a comprehensive introduction of large random matrix methods for input covariance matrix optimization of mutual information of MIMO systems. It is first recalled informally how large system approximations of mutual information can be derived. Then, the optimization of the approximations is discussed, and important methodological points that are not necessarily covered by the existing literature are addressed, including the strict concavity of the approximation, the structure of the argument of its maximum, the accuracy of the large system approach with regard to the number of antennas, or the justification of iterative water-filling optimization algorithms. While the existing papers have developed methods adapted to a specific model, this contribution tries to provide a unified view of the large system approximation approach.

Real Time Optimal Control of Supercapacitor Operation for Frequency Response

Energy Technology Data Exchange (ETDEWEB)

Luo, Yusheng; Panwar, Mayank; Mohanpurkar, Manish; Hovsapian, Rob

2016-07-01

Supercapacitors are gaining wider applications in power systems due to fast dynamic response. Utilizing supercapacitors by means of power electronics interfaces for power compensation is a proven effective technique. For applications such as requency restoration if the cost of supercapacitors maintenance as well as the energy loss on the power electronics interfaces are addressed. It is infeasible to use traditional optimization control methods to mitigate the impacts of frequent cycling. This paper proposes a Front End Controller (FEC) using Generalized Predictive Control featuring real time receding optimization. The optimization constraints are based on cost and thermal management to enhance to the utilization efficiency of supercapacitors. A rigorous mathematical derivation is conducted and test results acquired from Digital Real Time Simulator are provided to demonstrate effectiveness.