An improved partial bundle method for linearly constrained minimax problems

Directory of Open Access Journals (Sweden)

Chunming Tang

2016-02-01

Full Text Available In this paper, we propose an improved partial bundle method for solving linearly constrained minimax problems. In order to reduce the number of component function evaluations, we utilize a partial cutting-planes model to substitute for the traditional one. At each iteration, only one quadratic programming subproblem needs to be solved to obtain a new trial point. An improved descent test criterion is introduced to simplify the algorithm. The method produces a sequence of feasible trial points, and ensures that the objective function is monotonically decreasing on the sequence of stability centers. Global convergence of the algorithm is established. Moreover, we utilize the subgradient aggregation strategy to control the size of the bundle and therefore overcome the difficulty of computation and storage. Finally, some preliminary numerical results show that the proposed method is effective.

Minimum Energy Control of 2D Positive Continuous-Discrete Linear Systems

Directory of Open Access Journals (Sweden)

Kaczorek Tadeusz

2014-09-01

Full Text Available The minimum energy control problem for the 2D positive continuous-discrete linear systems is formulated and solved. Necessary and sufficient conditions for the reachability at the point of the systems are given. Sufficient conditions for the existence of solution to the problem are established. It is shown that if the system is reachable then there exists an optimal input that steers the state from zero boundary conditions to given final state and minimizing the performance index for only one step (q = 1. A procedure for solving of the problem is proposed and illustrated by a numerical example.

Blind Channel Equalization with Colored Source Based on Constrained Optimization Methods

Directory of Open Access Journals (Sweden)

Dayong Zhou

2008-12-01

Full Text Available Tsatsanis and Xu have applied the constrained minimum output variance (CMOV principle to directly blind equalize a linear channel—a technique that has proven effective with white inputs. It is generally assumed in the literature that their CMOV method can also effectively equalize a linear channel with a colored source. In this paper, we prove that colored inputs will cause the equalizer to incorrectly converge due to inadequate constraints. We also introduce a new blind channel equalizer algorithm that is based on the CMOV principle, but with a different constraint that will correctly handle colored sources. Our proposed algorithm works for channels with either white or colored inputs and performs equivalently to the trained minimum mean-square error (MMSE equalizer under high SNR. Thus, our proposed algorithm may be regarded as an extension of the CMOV algorithm proposed by Tsatsanis and Xu. We also introduce several methods to improve the performance of our introduced algorithm in the low SNR condition. Simulation results show the superior performance of our proposed methods.

Stability analysis of switched linear systems defined by graphs

OpenAIRE

Athanasopoulos, Nikolaos; Lazar, Mircea

2015-01-01

We present necessary and sufficient conditions for global exponential stability for switched discrete-time linear systems, under arbitrary switching, which is constrained within a set of admissible transitions. The class of systems studied includes the family of systems under arbitrary switching, periodic systems, and systems with minimum and maximum dwell time specifications. To reach the result, we describe the set of rules that define the admissible transitions with a weighted directed gra...

Stochastic variational approach to minimum uncertainty states

Energy Technology Data Exchange (ETDEWEB)

Illuminati, F.; Viola, L. [Dipartimento di Fisica, Padova Univ. (Italy)

1995-05-21

We introduce a new variational characterization of Gaussian diffusion processes as minimum uncertainty states. We then define a variational method constrained by kinematics of diffusions and Schroedinger dynamics to seek states of local minimum uncertainty for general non-harmonic potentials. (author)

Decoding linear error-correcting codes up to half the minimum distance with Gröbner bases

NARCIS (Netherlands)

Bulygin, S.; Pellikaan, G.R.; Sala, M.; Mora, T.; Perret, L.; Sakata, S.; Traverso, C.

2009-01-01

In this short note we show how one can decode linear error-correcting codes up to half the minimum distance via solving a system of polynomial equations over a finite field. We also explicitly present the reduced Gröbner basis for the system considered.

Rate-compatible protograph LDPC code families with linear minimum distance

Science.gov (United States)

Divsalar, Dariush (Inventor); Dolinar, Jr., Samuel J. (Inventor); Jones, Christopher R. (Inventor)

2012-01-01

Digital communication coding methods are shown, which generate certain types of low-density parity-check (LDPC) codes built from protographs. A first method creates protographs having the linear minimum distance property and comprising at least one variable node with degree less than 3. A second method creates families of protographs of different rates, all structurally identical for all rates except for a rate-dependent designation of certain variable nodes as transmitted or non-transmitted. A third method creates families of protographs of different rates, all structurally identical for all rates except for a rate-dependent designation of the status of certain variable nodes as non-transmitted or set to zero. LDPC codes built from the protographs created by these methods can simultaneously have low error floors and low iterative decoding thresholds.

A generalized fuzzy credibility-constrained linear fractional programming approach for optimal irrigation water allocation under uncertainty

Science.gov (United States)

Zhang, Chenglong; Guo, Ping

2017-10-01

The vague and fuzzy parametric information is a challenging issue in irrigation water management problems. In response to this problem, a generalized fuzzy credibility-constrained linear fractional programming (GFCCFP) model is developed for optimal irrigation water allocation under uncertainty. The model can be derived from integrating generalized fuzzy credibility-constrained programming (GFCCP) into a linear fractional programming (LFP) optimization framework. Therefore, it can solve ratio optimization problems associated with fuzzy parameters, and examine the variation of results under different credibility levels and weight coefficients of possibility and necessary. It has advantages in: (1) balancing the economic and resources objectives directly; (2) analyzing system efficiency; (3) generating more flexible decision solutions by giving different credibility levels and weight coefficients of possibility and (4) supporting in-depth analysis of the interrelationships among system efficiency, credibility level and weight coefficient. The model is applied to a case study of irrigation water allocation in the middle reaches of Heihe River Basin, northwest China. Therefore, optimal irrigation water allocation solutions from the GFCCFP model can be obtained. Moreover, factorial analysis on the two parameters (i.e. λ and γ) indicates that the weight coefficient is a main factor compared with credibility level for system efficiency. These results can be effective for support reasonable irrigation water resources management and agricultural production.

SU-G-BRA-08: Diaphragm Motion Tracking Based On KV CBCT Projections with a Constrained Linear Regression Optimization

Energy Technology Data Exchange (ETDEWEB)

Wei, J [City College of New York, New York, NY (United States); Chao, M [The Mount Sinai Medical Center, New York, NY (United States)

2016-06-15

Purpose: To develop a novel strategy to extract the respiratory motion of the thoracic diaphragm from kilovoltage cone beam computed tomography (CBCT) projections by a constrained linear regression optimization technique. Methods: A parabolic function was identified as the geometric model and was employed to fit the shape of the diaphragm on the CBCT projections. The search was initialized by five manually placed seeds on a pre-selected projection image. Temporal redundancies, the enabling phenomenology in video compression and encoding techniques, inherent in the dynamic properties of the diaphragm motion together with the geometrical shape of the diaphragm boundary and the associated algebraic constraint that significantly reduced the searching space of viable parabolic parameters was integrated, which can be effectively optimized by a constrained linear regression approach on the subsequent projections. The innovative algebraic constraints stipulating the kinetic range of the motion and the spatial constraint preventing any unphysical deviations was able to obtain the optimal contour of the diaphragm with minimal initialization. The algorithm was assessed by a fluoroscopic movie acquired at anteriorposterior fixed direction and kilovoltage CBCT projection image sets from four lung and two liver patients. The automatic tracing by the proposed algorithm and manual tracking by a human operator were compared in both space and frequency domains. Results: The error between the estimated and manual detections for the fluoroscopic movie was 0.54mm with standard deviation (SD) of 0.45mm, while the average error for the CBCT projections was 0.79mm with SD of 0.64mm for all enrolled patients. The submillimeter accuracy outcome exhibits the promise of the proposed constrained linear regression approach to track the diaphragm motion on rotational projection images. Conclusion: The new algorithm will provide a potential solution to rendering diaphragm motion and ultimately

SU-G-BRA-08: Diaphragm Motion Tracking Based On KV CBCT Projections with a Constrained Linear Regression Optimization

International Nuclear Information System (INIS)

Wei, J; Chao, M

2016-01-01

Purpose: To develop a novel strategy to extract the respiratory motion of the thoracic diaphragm from kilovoltage cone beam computed tomography (CBCT) projections by a constrained linear regression optimization technique. Methods: A parabolic function was identified as the geometric model and was employed to fit the shape of the diaphragm on the CBCT projections. The search was initialized by five manually placed seeds on a pre-selected projection image. Temporal redundancies, the enabling phenomenology in video compression and encoding techniques, inherent in the dynamic properties of the diaphragm motion together with the geometrical shape of the diaphragm boundary and the associated algebraic constraint that significantly reduced the searching space of viable parabolic parameters was integrated, which can be effectively optimized by a constrained linear regression approach on the subsequent projections. The innovative algebraic constraints stipulating the kinetic range of the motion and the spatial constraint preventing any unphysical deviations was able to obtain the optimal contour of the diaphragm with minimal initialization. The algorithm was assessed by a fluoroscopic movie acquired at anteriorposterior fixed direction and kilovoltage CBCT projection image sets from four lung and two liver patients. The automatic tracing by the proposed algorithm and manual tracking by a human operator were compared in both space and frequency domains. Results: The error between the estimated and manual detections for the fluoroscopic movie was 0.54mm with standard deviation (SD) of 0.45mm, while the average error for the CBCT projections was 0.79mm with SD of 0.64mm for all enrolled patients. The submillimeter accuracy outcome exhibits the promise of the proposed constrained linear regression approach to track the diaphragm motion on rotational projection images. Conclusion: The new algorithm will provide a potential solution to rendering diaphragm motion and ultimately

Finite-time convergent recurrent neural network with a hard-limiting activation function for constrained optimization with piecewise-linear objective functions.

Science.gov (United States)

Liu, Qingshan; Wang, Jun

2011-04-01

This paper presents a one-layer recurrent neural network for solving a class of constrained nonsmooth optimization problems with piecewise-linear objective functions. The proposed neural network is guaranteed to be globally convergent in finite time to the optimal solutions under a mild condition on a derived lower bound of a single gain parameter in the model. The number of neurons in the neural network is the same as the number of decision variables of the optimization problem. Compared with existing neural networks for optimization, the proposed neural network has a couple of salient features such as finite-time convergence and a low model complexity. Specific models for two important special cases, namely, linear programming and nonsmooth optimization, are also presented. In addition, applications to the shortest path problem and constrained least absolute deviation problem are discussed with simulation results to demonstrate the effectiveness and characteristics of the proposed neural network.

Affine Lie algebraic origin of constrained KP hierarchies

International Nuclear Information System (INIS)

Aratyn, H.; Gomes, J.F.; Zimerman, A.H.

1994-07-01

It is presented an affine sl(n+1) algebraic construction of the basic constrained KP hierarchy. This hierarchy is analyzed using two approaches, namely linear matrix eigenvalue problem on hermitian symmetric space and constrained KP Lax formulation and we show that these approaches are equivalent. The model is recognized to be generalized non-linear Schroedinger (GNLS) hierarchy and it is used as a building block for a new class of constrained KP hierarchies. These constrained KP hierarchies are connected via similarity-Backlund transformations and interpolate between GNLS and multi-boson KP-Toda hierarchies. The construction uncovers origin of the Toda lattice structure behind the latter hierarchy. (author). 23 refs

Minimum error discrimination for an ensemble of linearly independent pure states

International Nuclear Information System (INIS)

Singal, Tanmay; Ghosh, Sibasish

2016-01-01

Inspired by the work done by Belavkin (1975 Stochastics 1 315) and independently by Mochon, (2006 Phys. Rev. A 73 032328), we formulate the problem of minimum error discrimination (MED) of any ensemble of n linearly independent pure states by stripping the problem of its rotational covariance and retaining only the rotationally invariant aspect of the problem. This is done by embedding the optimal conditions in a matrix equality as well as matrix inequality. Employing the implicit function theorem in these conditions we get a set of first-order coupled ordinary nonlinear differential equations which can be used to drag the solution from an initial point (where solution is known) to another point (whose solution is sought). This way of obtaining the solution can be done through a simple Taylor series expansion and analytic continuation when required. Thus, we complete the work done by Belavkin and Mochon by ultimately leading their theory to a solution for the MED problem of linearly independent pure state ensembles. We also compare the computational complexity of our technique with the barrier-type interior point method of SDP and show that our technique is computationally as efficient as (actually, a bit more than) the SDP algorithm, with the added advantage of being much simpler to implement. (paper)

Off-Line Robust Constrained MPC for Linear Time-Varying Systems with Persistent Disturbances

Directory of Open Access Journals (Sweden)

P. Bumroongsri

2014-01-01

Full Text Available An off-line robust constrained model predictive control (MPC algorithm for linear time-varying (LTV systems is developed. A novel feature is the fact that both model uncertainty and bounded additive disturbance are explicitly taken into account in the off-line formulation of MPC. In order to reduce the on-line computational burdens, a sequence of explicit control laws corresponding to a sequence of positively invariant sets is computed off-line. At each sampling time, the smallest positively invariant set containing the measured state is determined and the corresponding control law is implemented in the process. The proposed MPC algorithm can guarantee robust stability while ensuring the satisfaction of input and output constraints. The effectiveness of the proposed MPC algorithm is illustrated by two examples.

Linear-constraint wavefront control for exoplanet coronagraphic imaging systems

Science.gov (United States)

Sun, He; Eldorado Riggs, A. J.; Kasdin, N. Jeremy; Vanderbei, Robert J.; Groff, Tyler Dean

2017-01-01

A coronagraph is a leading technology for achieving high-contrast imaging of exoplanets in a space telescope. It uses a system of several masks to modify the diffraction and achieve extremely high contrast in the image plane around target stars. However, coronagraphic imaging systems are very sensitive to optical aberrations, so wavefront correction using deformable mirrors (DMs) is necessary to avoid contrast degradation in the image plane. Electric field conjugation (EFC) and Stroke minimization (SM) are two primary high-contrast wavefront controllers explored in the past decade. EFC minimizes the average contrast in the search areas while regularizing the strength of the control inputs. Stroke minimization calculates the minimum DM commands under the constraint that a target average contrast is achieved. Recently in the High Contrast Imaging Lab at Princeton University (HCIL), a new linear-constraint wavefront controller based on stroke minimization was developed and demonstrated using numerical simulation. Instead of only constraining the average contrast over the entire search area, the new controller constrains the electric field of each single pixel using linear programming, which could led to significant increases in speed of the wavefront correction and also create more uniform dark holes. As a follow-up of this work, another linear-constraint controller modified from EFC is demonstrated theoretically and numerically and the lab verification of the linear-constraint controllers is reported. Based on the simulation and lab results, the pros and cons of linear-constraint controllers are carefully compared with EFC and stroke minimization.

Prediction of minimum temperatures in an alpine region by linear and non-linear post-processing of meteorological models

Directory of Open Access Journals (Sweden)

R. Barbiero

2007-05-01

Full Text Available Model Output Statistics (MOS refers to a method of post-processing the direct outputs of numerical weather prediction (NWP models in order to reduce the biases introduced by a coarse horizontal resolution. This technique is especially useful in orographically complex regions, where large differences can be found between the NWP elevation model and the true orography. This study carries out a comparison of linear and non-linear MOS methods, aimed at the prediction of minimum temperatures in a fruit-growing region of the Italian Alps, based on the output of two different NWPs (ECMWF T511–L60 and LAMI-3. Temperature, of course, is a particularly important NWP output; among other roles it drives the local frost forecast, which is of great interest to agriculture. The mechanisms of cold air drainage, a distinctive aspect of mountain environments, are often unsatisfactorily captured by global circulation models. The simplest post-processing technique applied in this work was a correction for the mean bias, assessed at individual model grid points. We also implemented a multivariate linear regression on the output at the grid points surrounding the target area, and two non-linear models based on machine learning techniques: Neural Networks and Random Forest. We compare the performance of all these techniques on four different NWP data sets. Downscaling the temperatures clearly improved the temperature forecasts with respect to the raw NWP output, and also with respect to the basic mean bias correction. Multivariate methods generally yielded better results, but the advantage of using non-linear algorithms was small if not negligible. RF, the best performing method, was implemented on ECMWF prognostic output at 06:00 UTC over the 9 grid points surrounding the target area. Mean absolute errors in the prediction of 2 m temperature at 06:00 UTC were approximately 1.2°C, close to the natural variability inside the area itself.

KEELE, Minimization of Nonlinear Function with Linear Constraints, Variable Metric Method

International Nuclear Information System (INIS)

Westley, G.W.

1975-01-01

1 - Description of problem or function: KEELE is a linearly constrained nonlinear programming algorithm for locating a local minimum of a function of n variables with the variables subject to linear equality and/or inequality constraints. 2 - Method of solution: A variable metric procedure is used where the direction of search at each iteration is obtained by multiplying the negative of the gradient vector by a positive definite matrix which approximates the inverse of the matrix of second partial derivatives associated with the function. 3 - Restrictions on the complexity of the problem: Array dimensions limit the number of variables to 20 and the number of constraints to 50. These can be changed by the user

Minimal constrained supergravity

Energy Technology Data Exchange (ETDEWEB)

Cribiori, N. [Dipartimento di Fisica e Astronomia “Galileo Galilei”, Università di Padova, Via Marzolo 8, 35131 Padova (Italy); INFN, Sezione di Padova, Via Marzolo 8, 35131 Padova (Italy); Dall' Agata, G., E-mail: dallagat@pd.infn.it [Dipartimento di Fisica e Astronomia “Galileo Galilei”, Università di Padova, Via Marzolo 8, 35131 Padova (Italy); INFN, Sezione di Padova, Via Marzolo 8, 35131 Padova (Italy); Farakos, F. [Dipartimento di Fisica e Astronomia “Galileo Galilei”, Università di Padova, Via Marzolo 8, 35131 Padova (Italy); INFN, Sezione di Padova, Via Marzolo 8, 35131 Padova (Italy); Porrati, M. [Center for Cosmology and Particle Physics, Department of Physics, New York University, 4 Washington Place, New York, NY 10003 (United States)

2017-01-10

We describe minimal supergravity models where supersymmetry is non-linearly realized via constrained superfields. We show that the resulting actions differ from the so called “de Sitter” supergravities because we consider constraints eliminating directly the auxiliary fields of the gravity multiplet.

Minimal constrained supergravity

International Nuclear Information System (INIS)

Cribiori, N.; Dall'Agata, G.; Farakos, F.; Porrati, M.

2017-01-01

We describe minimal supergravity models where supersymmetry is non-linearly realized via constrained superfields. We show that the resulting actions differ from the so called “de Sitter” supergravities because we consider constraints eliminating directly the auxiliary fields of the gravity multiplet.

Minimal constrained supergravity

Directory of Open Access Journals (Sweden)

N. Cribiori

2017-01-01

Full Text Available We describe minimal supergravity models where supersymmetry is non-linearly realized via constrained superfields. We show that the resulting actions differ from the so called “de Sitter” supergravities because we consider constraints eliminating directly the auxiliary fields of the gravity multiplet.

Mating schemes for optimum contribution selection with constrained rates of inbreeding

NARCIS (Netherlands)

Sonesson, A.K.; Meuwissen, T.H.E.

2000-01-01

The effect of non-random mating on genetic response was compared for populations with discrete generations. Mating followed a selection step where the average coancestry of selected animals was constrained, while genetic response was maximised. Minimum coancestry (MC), Minimum coancestry with a

Modelos lineares e não lineares inteiros para problemas da mochila bidimensional restrita a 2 estágios Linear and nonlinear integer models for constrained two-stage two-dimensional knapsack problems

Directory of Open Access Journals (Sweden)

Horacio Hideki Yanasse

2013-01-01

Full Text Available Neste trabalho revemos alguns modelos lineares e não lineares inteiros para gerar padrões de corte bidimensionais guilhotinados de 2 estágios, incluindo os casos exato e não exato e restrito e irrestrito. Esses problemas são casos particulares do problema da mochila bidimensional. Apresentamos também novos modelos para gerar esses padrões de corte, baseados em adaptações ou extensões de modelos para gerar padrões de corte bidimensionais restritos 1-grupo. Padrões 2 estágios aparecem em diferentes processos de corte, como, por exemplo, em indústrias de móveis e de chapas de madeira. Os modelos são úteis para a pesquisa e o desenvolvimento de métodos de solução mais eficientes, explorando estruturas particulares, a decomposição do modelo, relaxações do modelo etc. Eles também são úteis para a avaliação do desempenho de heurísticas, já que permitem (pelo menos para problemas de tamanho moderado uma estimativa do gap de otimalidade de soluções obtidas por heurísticas. Para ilustrar a aplicação dos modelos, analisamos os resultados de alguns experimentos computacionais com exemplos da literatura e outros gerados aleatoriamente. Os resultados foram produzidos usando um software comercial conhecido e mostram que o esforço computacional necessário para resolver os modelos pode ser bastante diferente.In this work we review some linear and nonlinear integer models to generate two stage two-dimensional guillotine cutting patterns, including the constrained, non constrained, exact and non exact cases. These problems are particular cases of the two dimensional knapsack problems. We also present new models to generate these cutting patterns, based on adaptations and extensions of models that generate one-group constrained two dimensional cutting patterns. Two stage patterns arise in different cutting processes like, for instance, in the furniture industry and wooden hardboards. The models are useful for the research and

A non-linear branch and cut method for solving discrete minimum compliance problems to global optimality

DEFF Research Database (Denmark)

Stolpe, Mathias; Bendsøe, Martin P.

2007-01-01

This paper present some initial results pertaining to a search for globally optimal solutions to a challenging benchmark example proposed by Zhou and Rozvany. This means that we are dealing with global optimization of the classical single load minimum compliance topology design problem with a fixed...... finite element discretization and with discrete design variables. Global optimality is achieved by the implementation of some specially constructed convergent nonlinear branch and cut methods, based on the use of natural relaxations and by applying strengthening constraints (linear valid inequalities...

Linear regression based on Minimum Covariance Determinant (MCD) and TELBS methods on the productivity of phytoplankton

Science.gov (United States)

Gusriani, N.; Firdaniza

2018-03-01

The existence of outliers on multiple linear regression analysis causes the Gaussian assumption to be unfulfilled. If the Least Square method is forcedly used on these data, it will produce a model that cannot represent most data. For that, we need a robust regression method against outliers. This paper will compare the Minimum Covariance Determinant (MCD) method and the TELBS method on secondary data on the productivity of phytoplankton, which contains outliers. Based on the robust determinant coefficient value, MCD method produces a better model compared to TELBS method.

A non-linear branch and cut method for solving discrete minimum compliance problems to global optimality

DEFF Research Database (Denmark)

Stolpe, Mathias; Bendsøe, Martin P.

2007-01-01

This paper present some initial results pertaining to a search for globally optimal solutions to a challenging benchmark example proposed by Zhou and Rozvany. This means that we are dealing with global optimization of the classical single load minimum compliance topology design problem with a fixed...... finite element discretization and with discrete design variables. Global optimality is achieved by the implementation of some specially constructed convergent nonlinear branch and cut methods, based on the use of natural relaxations and by applying strengthening constraints (linear valid inequalities......) and cuts....

Resource-constrained project scheduling: computing lower bounds by solving minimum cut problems

NARCIS (Netherlands)

Möhring, R.H.; Nesetril, J.; Schulz, A.S.; Stork, F.; Uetz, Marc Jochen

1999-01-01

We present a novel approach to compute Lagrangian lower bounds on the objective function value of a wide class of resource-constrained project scheduling problems. The basis is a polynomial-time algorithm to solve the following scheduling problem: Given a set of activities with start-time dependent

Minimum-Cost Reachability for Priced Timed Automata

DEFF Research Database (Denmark)

Behrmann, Gerd; Fehnker, Ansgar; Hune, Thomas Seidelin

2001-01-01

This paper introduces the model of linearly priced timed automata as an extension of timed automata, with prices on both transitions and locations. For this model we consider the minimum-cost reachability problem: i.e. given a linearly priced timed automaton and a target state, determine...... the minimum cost of executions from the initial state to the target state. This problem generalizes the minimum-time reachability problem for ordinary timed automata. We prove decidability of this problem by offering an algorithmic solution, which is based on a combination of branch-and-bound techniques...

Secure Fusion Estimation for Bandwidth Constrained Cyber-Physical Systems Under Replay Attacks.

Science.gov (United States)

Chen, Bo; Ho, Daniel W C; Hu, Guoqiang; Yu, Li; Bo Chen; Ho, Daniel W C; Guoqiang Hu; Li Yu; Chen, Bo; Ho, Daniel W C; Hu, Guoqiang; Yu, Li

2018-06-01

State estimation plays an essential role in the monitoring and supervision of cyber-physical systems (CPSs), and its importance has made the security and estimation performance a major concern. In this case, multisensor information fusion estimation (MIFE) provides an attractive alternative to study secure estimation problems because MIFE can potentially improve estimation accuracy and enhance reliability and robustness against attacks. From the perspective of the defender, the secure distributed Kalman fusion estimation problem is investigated in this paper for a class of CPSs under replay attacks, where each local estimate obtained by the sink node is transmitted to a remote fusion center through bandwidth constrained communication channels. A new mathematical model with compensation strategy is proposed to characterize the replay attacks and bandwidth constrains, and then a recursive distributed Kalman fusion estimator (DKFE) is designed in the linear minimum variance sense. According to different communication frameworks, two classes of data compression and compensation algorithms are developed such that the DKFEs can achieve the desired performance. Several attack-dependent and bandwidth-dependent conditions are derived such that the DKFEs are secure under replay attacks. An illustrative example is given to demonstrate the effectiveness of the proposed methods.

Minimum Time Trajectory Optimization of CNC Machining with Tracking Error Constraints

Directory of Open Access Journals (Sweden)

Qiang Zhang

2014-01-01

Full Text Available An off-line optimization approach of high precision minimum time feedrate for CNC machining is proposed. Besides the ordinary considered velocity, acceleration, and jerk constraints, dynamic performance constraint of each servo drive is also considered in this optimization problem to improve the tracking precision along the optimized feedrate trajectory. Tracking error is applied to indicate the servo dynamic performance of each axis. By using variable substitution, the tracking error constrained minimum time trajectory planning problem is formulated as a nonlinear path constrained optimal control problem. Bang-bang constraints structure of the optimal trajectory is proved in this paper; then a novel constraint handling method is proposed to realize a convex optimization based solution of the nonlinear constrained optimal control problem. A simple ellipse feedrate planning test is presented to demonstrate the effectiveness of the approach. Then the practicability and robustness of the trajectory generated by the proposed approach are demonstrated by a butterfly contour machining example.

Improved solution for ill-posed linear systems using a constrained optimization ruled by a penalty: evaluation in nuclear medicine tomography

International Nuclear Information System (INIS)

Walrand, Stephan; Jamar, François; Pauwels, Stanislas

2009-01-01

Ill-posed linear systems occur in many different fields. A class of regularization methods, called constrained optimization, aims to determine the extremum of a penalty function whilst constraining an objective function to a likely value. We propose here a novel heuristic way to screen the local extrema satisfying the discrepancy principle. A modified version of the Landweber algorithm is used for the iteration process. After finding a local extremum, a bound is performed to the 'farthest' estimate in the data space still satisfying the discrepancy principle. Afterwards, the modified Landweber algorithm is again applied to find a new local extremum. This bound-iteration process is repeated until a satisfying solution is reached. For evaluation in nuclear medicine tomography, a novel penalty function that preserves the edge steps in the reconstructed solution was evaluated on Monte Carlo simulations and using real SPECT acquisitions as well. Surprisingly, the first bound always provided a significantly better solution in a wide range of statistics

Analyzing systemic risk using non-linear marginal expected shortfall and its minimum spanning tree

Science.gov (United States)

Song, Jae Wook; Ko, Bonggyun; Chang, Woojin

2018-02-01

The aim of this paper is to propose a new theoretical framework for analyzing the systemic risk using the marginal expected shortfall (MES) and its correlation-based minimum spanning tree (MST). At first, we develop two parametric models of MES with their closed-form solutions based on the Capital Asset Pricing Model. Our models are derived from the non-symmetric quadratic form, which allows them to consolidate the non-linear relationship between the stock and market returns. Secondly, we discover the evidences related to the utility of our models and the possible association in between the non-linear relationship and the emergence of severe systemic risk by considering the US financial system as a benchmark. In this context, the evolution of MES also can be regarded as a reasonable proxy of systemic risk. Lastly, we analyze the structural properties of the systemic risk using the MST based on the computed series of MES. The topology of MST conveys the presence of sectoral clustering and strong co-movements of systemic risk leaded by few hubs during the crisis. Specifically, we discover that the Depositories are the majority sector leading the connections during the Non-Crisis period, whereas the Broker-Dealers are majority during the Crisis period.

The linear programming bound for binary linear codes

NARCIS (Netherlands)

Brouwer, A.E.

1993-01-01

Combining Delsarte's (1973) linear programming bound with the information that certain weights cannot occur, new upper bounds for dmin (n,k), the maximum possible minimum distance of a binary linear code with given word length n and dimension k, are derived.

Minimum energy control and optimal-satisfactory control of Boolean control network

International Nuclear Information System (INIS)

Li, Fangfei; Lu, Xiwen

2013-01-01

In the literatures, to transfer the Boolean control network from the initial state to the desired state, the expenditure of energy has been rarely considered. Motivated by this, this Letter investigates the minimum energy control and optimal-satisfactory control of Boolean control network. Based on the semi-tensor product of matrices and Floyd's algorithm, minimum energy, constrained minimum energy and optimal-satisfactory control design for Boolean control network are given respectively. A numerical example is presented to illustrate the efficiency of the obtained results.

The generation and acceleration of low emittance flat beams for future linear colliders

Energy Technology Data Exchange (ETDEWEB)

Raubenheimer, Tor O. [Stanford Univ., CA (United States)

1991-11-01

Many future linear collider designs call for electron and positron beams with normalized rms horizontal and vertical emittances of γϵ_x = 3x10^-6 m-rad and γϵ_y = 3x10^-8 m-rad; these are a factor of 10 to 100 below those observed in the Stanford Linear Collider. In this dissertation, we examine the feasibility of achieving beams with these very small vertical emittances. We examine the limitations encountered during both the generation and the subsequent acceleration of such low emittance beams. We consider collective limitations, such as wakefields, space charge effects, scattering processes, and ion trapping; and also how intensity limitations, such as anomalous dispersion, betatron coupling, and pulse-to-pulse beam jitter. In general, the minimum emittance in both the generation and the acceleration stages is limited by the transverse misalignments of the accelerator components. We describe a few techniques of correcting the effect of these errors, thereby easing the alignment tolerances by over an order of magnitude. Finally, we also calculate ``fundamental`` limitations on the minimum vertical emittance; these do not constrain the current designs but may prove important in the future.

The generation and acceleration of low emittance flat beams for future linear colliders

Energy Technology Data Exchange (ETDEWEB)

Raubenheimer, T.O.

1991-11-01

Many future linear collider designs call for electron and positron beams with normalized rms horizontal and vertical emittances of {gamma}{epsilon}{sub x} = 3{times}10{sup {minus}6} m-rad and {gamma}{epsilon}{sub y} = 3{times}10{sup {minus}8} m-rad; these are a factor of 10 to 100 below those observed in the Stanford Linear Collider. In this dissertation, we examine the feasibility of achieving beams with these very small vertical emittances. We examine the limitations encountered during both the generation and the subsequent acceleration of such low emittance beams. We consider collective limitations, such as wakefields, space charge effects, scattering processes, and ion trapping; and also how intensity limitations, such as anomalous dispersion, betatron coupling, and pulse-to-pulse beam jitter. In general, the minimum emittance in both the generation and the acceleration stages is limited by the transverse misalignments of the accelerator components. We describe a few techniques of correcting the effect of these errors, thereby easing the alignment tolerances by over an order of magnitude. Finally, we also calculate fundamental'' limitations on the minimum vertical emittance; these do not constrain the current designs but may prove important in the future.

The generation and acceleration of low emittance flat beams for future linear colliders

International Nuclear Information System (INIS)

Raubenheimer, T.O.

1991-11-01

Many future linear collider designs call for electron and positron beams with normalized rms horizontal and vertical emittances of γε x = 3x10 -6 m-rad and γε y = 3x10 -8 m-rad; these are a factor of 10 to 100 below those observed in the Stanford Linear Collider. In this dissertation, we examine the feasibility of achieving beams with these very small vertical emittances. We examine the limitations encountered during both the generation and the subsequent acceleration of such low emittance beams. We consider collective limitations, such as wakefields, space charge effects, scattering processes, and ion trapping; and also how intensity limitations, such as anomalous dispersion, betatron coupling, and pulse-to-pulse beam jitter. In general, the minimum emittance in both the generation and the acceleration stages is limited by the transverse misalignments of the accelerator components. We describe a few techniques of correcting the effect of these errors, thereby easing the alignment tolerances by over an order of magnitude. Finally, we also calculate ''fundamental'' limitations on the minimum vertical emittance; these do not constrain the current designs but may prove important in the future

Minimum-Cost Reachability for Priced Timed Automata

DEFF Research Database (Denmark)

Behrmann, Gerd; Fehnker, Ansgar; Hune, Thomas Seidelin

2001-01-01

This paper introduces the model of linearly priced timed automata as an extension of timed automata, with prices on both transitions and locations. For this model we consider the minimum-cost reachability problem: i.e. given a linearly priced timed automaton and a target state, determine...... the minimum cost of executions from the initial state to the target state. This problem generalizes the minimum-time reachability problem for ordinary timed automata. We prove decidability of this problem by offering an algorithmic solution, which is based on a combination of branch-and-bound techniques...... and a new notion of priced regions. The latter allows symbolic representation and manipulation of reachable states together with the cost of reaching them....

Scheduling Aircraft Landings under Constrained Position Shifting

Science.gov (United States)

Balakrishnan, Hamsa; Chandran, Bala

2006-01-01

Optimal scheduling of airport runway operations can play an important role in improving the safety and efficiency of the National Airspace System (NAS). Methods that compute the optimal landing sequence and landing times of aircraft must accommodate practical issues that affect the implementation of the schedule. One such practical consideration, known as Constrained Position Shifting (CPS), is the restriction that each aircraft must land within a pre-specified number of positions of its place in the First-Come-First-Served (FCFS) sequence. We consider the problem of scheduling landings of aircraft in a CPS environment in order to maximize runway throughput (minimize the completion time of the landing sequence), subject to operational constraints such as FAA-specified minimum inter-arrival spacing restrictions, precedence relationships among aircraft that arise either from airline preferences or air traffic control procedures that prevent overtaking, and time windows (representing possible control actions) during which each aircraft landing can occur. We present a Dynamic Programming-based approach that scales linearly in the number of aircraft, and describe our computational experience with a prototype implementation on realistic data for Denver International Airport.

Exploring the Metabolic and Perceptual Correlates of Self-Selected Walking Speed under Constrained and Un-Constrained Conditions

Directory of Open Access Journals (Sweden)

David T Godsiff, Shelly Coe, Charlotte Elsworth-Edelsten, Johnny Collett, Ken Howells, Martyn Morris, Helen Dawes

2018-03-01

Full Text Available Mechanisms underpinning self-selected walking speed (SSWS are poorly understood. The present study investigated the extent to which SSWS is related to metabolism, energy cost, and/or perceptual parameters during both normal and artificially constrained walking. Fourteen participants with no pathology affecting gait were tested under standard conditions. Subjects walked on a motorized treadmill at speeds derived from their SSWS as a continuous protocol. RPE scores (CR10 and expired air to calculate energy cost (J.kg-1.m-1 and carbohydrate (CHO oxidation rate (J.kg-1.min-1 were collected during minutes 3-4 at each speed. Eight individuals were re-tested under the same conditions within one week with a hip and knee-brace to immobilize their right leg. Deflection in RPE scores (CR10 and CHO oxidation rate (J.kg-1.min-1 were not related to SSWS (five and three people had deflections in the defined range of SSWS in constrained and unconstrained conditions, respectively (p > 0.05. Constrained walking elicited a higher energy cost (J.kg-1.m-1 and slower SSWS (p 0.05. SSWS did not occur at a minimum energy cost (J.kg-1.m-1 in either condition, however, the size of the minimum energy cost to SSWS disparity was the same (Froude {Fr} = 0.09 in both conditions (p = 0.36. Perceptions of exertion can modify walking patterns and therefore SSWS and metabolism/ energy cost are not directly related. Strategies which minimize perceived exertion may enable faster walking in people with altered gait as our findings indicate they should self-optimize to the same extent under different conditions.

Constraining new physics models with isotope shift spectroscopy

Science.gov (United States)

Frugiuele, Claudia; Fuchs, Elina; Perez, Gilad; Schlaffer, Matthias

2017-07-01

Isotope shifts of transition frequencies in atoms constrain generic long- and intermediate-range interactions. We focus on new physics scenarios that can be most strongly constrained by King linearity violation such as models with B -L vector bosons, the Higgs portal, and chameleon models. With the anticipated precision, King linearity violation has the potential to set the strongest laboratory bounds on these models in some regions of parameter space. Furthermore, we show that this method can probe the couplings relevant for the protophobic interpretation of the recently reported Be anomaly. We extend the formalism to include an arbitrary number of transitions and isotope pairs and fit the new physics coupling to the currently available isotope shift measurements.

Chance-constrained/stochastic linear programming model for acid rain abatement. I. Complete colinearity and noncolinearity

Energy Technology Data Exchange (ETDEWEB)

Ellis, J H; McBean, E A; Farquhar, G J

1985-01-01

A Linear Programming model is presented for development of acid rain abatement strategies in eastern North America. For a system comprised of 235 large controllable point sources and 83 uncontrolled area sources, it determines the least-cost method of reducing SO/sub 2/ emissions to satisfy maximum wet sulfur deposition limits at 20 sensitive receptor locations. In this paper, the purely deterministic model is extended to a probabilistic form by incorporating the effects of meteorologic variability on the long-range pollutant transport processes. These processes are represented by source-receptor-specific transfer coefficients. Experiments for quantifying the spatial variability of transfer coefficients showed their distributions to be approximately lognormal with logarithmic standard deviations consistently about unity. Three methods of incorporating second-moment random variable uncertainty into the deterministic LP framework are described: Two-Stage Programming Under Uncertainty, Chance-Constrained Programming and Stochastic Linear Programming. A composite CCP-SLP model is developed which embodies the two-dimensional characteristics of transfer coefficient uncertainty. Two probabilistic formulations are described involving complete colinearity and complete noncolinearity for the transfer coefficient covariance-correlation structure. The completely colinear and noncolinear formulations are considered extreme bounds in a meteorologic sense and yield abatement strategies of largely didactic value. Such strategies can be characterized as having excessive costs and undesirable deposition results in the completely colinear case and absence of a clearly defined system risk level (other than expected-value) in the noncolinear formulation.

A feasible DY conjugate gradient method for linear equality constraints

Science.gov (United States)

LI, Can

2017-09-01

In this paper, we propose a feasible conjugate gradient method for solving linear equality constrained optimization problem. The method is an extension of the Dai-Yuan conjugate gradient method proposed by Dai and Yuan to linear equality constrained optimization problem. It can be applied to solve large linear equality constrained problem due to lower storage requirement. An attractive property of the method is that the generated direction is always feasible and descent direction. Under mild conditions, the global convergence of the proposed method with exact line search is established. Numerical experiments are also given which show the efficiency of the method.

Constrained State Estimation for Individual Localization in Wireless Body Sensor Networks

Directory of Open Access Journals (Sweden)

Xiaoxue Feng

2014-11-01

Full Text Available Wireless body sensor networks based on ultra-wideband radio have recently received much research attention due to its wide applications in health-care, security, sports and entertainment. Accurate localization is a fundamental problem to realize the development of effective location-aware applications above. In this paper the problem of constrained state estimation for individual localization in wireless body sensor networks is addressed. Priori knowledge about geometry among the on-body nodes as additional constraint is incorporated into the traditional filtering system. The analytical expression of state estimation with linear constraint to exploit the additional information is derived. Furthermore, for nonlinear constraint, first-order and second-order linearizations via Taylor series expansion are proposed to transform the nonlinear constraint to the linear case. Examples between the first-order and second-order nonlinear constrained filters based on interacting multiple model extended kalman filter (IMM-EKF show that the second-order solution for higher order nonlinearity as present in this paper outperforms the first-order solution, and constrained IMM-EKF obtains superior estimation than IMM-EKF without constraint. Another brownian motion individual localization example also illustrates the effectiveness of constrained nonlinear iterative least square (NILS, which gets better filtering performance than NILS without constraint.

Constrained State Estimation for Individual Localization in Wireless Body Sensor Networks

Science.gov (United States)

Feng, Xiaoxue; Snoussi, Hichem; Liang, Yan; Jiao, Lianmeng

2014-01-01

Wireless body sensor networks based on ultra-wideband radio have recently received much research attention due to its wide applications in health-care, security, sports and entertainment. Accurate localization is a fundamental problem to realize the development of effective location-aware applications above. In this paper the problem of constrained state estimation for individual localization in wireless body sensor networks is addressed. Priori knowledge about geometry among the on-body nodes as additional constraint is incorporated into the traditional filtering system. The analytical expression of state estimation with linear constraint to exploit the additional information is derived. Furthermore, for nonlinear constraint, first-order and second-order linearizations via Taylor series expansion are proposed to transform the nonlinear constraint to the linear case. Examples between the first-order and second-order nonlinear constrained filters based on interacting multiple model extended kalman filter (IMM-EKF) show that the second-order solution for higher order nonlinearity as present in this paper outperforms the first-order solution, and constrained IMM-EKF obtains superior estimation than IMM-EKF without constraint. Another brownian motion individual localization example also illustrates the effectiveness of constrained nonlinear iterative least square (NILS), which gets better filtering performance than NILS without constraint. PMID:25390408

Constrained state estimation for individual localization in wireless body sensor networks.

Science.gov (United States)

Feng, Xiaoxue; Snoussi, Hichem; Liang, Yan; Jiao, Lianmeng

2014-11-10

Wireless body sensor networks based on ultra-wideband radio have recently received much research attention due to its wide applications in health-care, security, sports and entertainment. Accurate localization is a fundamental problem to realize the development of effective location-aware applications above. In this paper the problem of constrained state estimation for individual localization in wireless body sensor networks is addressed. Priori knowledge about geometry among the on-body nodes as additional constraint is incorporated into the traditional filtering system. The analytical expression of state estimation with linear constraint to exploit the additional information is derived. Furthermore, for nonlinear constraint, first-order and second-order linearizations via Taylor series expansion are proposed to transform the nonlinear constraint to the linear case. Examples between the first-order and second-order nonlinear constrained filters based on interacting multiple model extended kalman filter (IMM-EKF) show that the second-order solution for higher order nonlinearity as present in this paper outperforms the first-order solution, and constrained IMM-EKF obtains superior estimation than IMM-EKF without constraint. Another brownian motion individual localization example also illustrates the effectiveness of constrained nonlinear iterative least square (NILS), which gets better filtering performance than NILS without constraint.

Minimum weight design of prestressed concrete reactor pressure vessels

International Nuclear Information System (INIS)

Boes, R.

1975-01-01

A method of non-linear programming for the minimization of the volume of rotationally symmetric prestressed concrete reactor pressure vessels is presented. It is assumed that the inner shape, the loads and the degree of prestressing are prescribed, whereas the outer shape is to be detemined. Prestressing includes rotational and vertical tension. The objective function minimizes the weight of the PCRV. The constrained minimization problem is converted into an unconstrained problem by the addition of interior penalty functions to the objective function. The minimum is determined by the variable metric method (Davidson-Fletcher-Powell), using both values and derivatives of the modified objective function. The one-dimensional search is approximated by a method of Kund. Optimization variables are scaled. The method is applied to a pressure vessel like for THTR. It is found that the thickness of the cylindrical wall may be reduced considerably for the load cases considered in the optimization. The thickness of the cover is reduced slightly. The largest reduction in wall thickness occurs at the junction of wall and cover. (Auth.)

Sharp spatially constrained inversion

DEFF Research Database (Denmark)

Vignoli, Giulio G.; Fiandaca, Gianluca G.; Christiansen, Anders Vest C A.V.C.

2013-01-01

We present sharp reconstruction of multi-layer models using a spatially constrained inversion with minimum gradient support regularization. In particular, its application to airborne electromagnetic data is discussed. Airborne surveys produce extremely large datasets, traditionally inverted...... by using smoothly varying 1D models. Smoothness is a result of the regularization constraints applied to address the inversion ill-posedness. The standard Occam-type regularized multi-layer inversion produces results where boundaries between layers are smeared. The sharp regularization overcomes...... inversions are compared against classical smooth results and available boreholes. With the focusing approach, the obtained blocky results agree with the underlying geology and allow for easier interpretation by the end-user....

Cosmicflows Constrained Local UniversE Simulations

Science.gov (United States)

Sorce, Jenny G.; Gottlöber, Stefan; Yepes, Gustavo; Hoffman, Yehuda; Courtois, Helene M.; Steinmetz, Matthias; Tully, R. Brent; Pomarède, Daniel; Carlesi, Edoardo

2016-01-01

This paper combines observational data sets and cosmological simulations to generate realistic numerical replicas of the nearby Universe. The latter are excellent laboratories for studies of the non-linear process of structure formation in our neighbourhood. With measurements of radial peculiar velocities in the local Universe (cosmicflows-2) and a newly developed technique, we produce Constrained Local UniversE Simulations (CLUES). To assess the quality of these constrained simulations, we compare them with random simulations as well as with local observations. The cosmic variance, defined as the mean one-sigma scatter of cell-to-cell comparison between two fields, is significantly smaller for the constrained simulations than for the random simulations. Within the inner part of the box where most of the constraints are, the scatter is smaller by a factor of 2 to 3 on a 5 h-1 Mpc scale with respect to that found for random simulations. This one-sigma scatter obtained when comparing the simulated and the observation-reconstructed velocity fields is only 104 ± 4 km s-1, I.e. the linear theory threshold. These two results demonstrate that these simulations are in agreement with each other and with the observations of our neighbourhood. For the first time, simulations constrained with observational radial peculiar velocities resemble the local Universe up to a distance of 150 h-1 Mpc on a scale of a few tens of megaparsecs. When focusing on the inner part of the box, the resemblance with our cosmic neighbourhood extends to a few megaparsecs (<5 h-1 Mpc). The simulations provide a proper large-scale environment for studies of the formation of nearby objects.

Constrained non-linear optimization in 3D reflexion tomography; Problemes d'optimisation non-lineaire avec contraintes en tomographie de reflexion 3D

Energy Technology Data Exchange (ETDEWEB)

Delbos, F

2004-11-01

Reflexion tomography allows the determination of a subsurface velocity model from the travel times of seismic waves. The introduction of a priori information in this inverse problem can lead to the resolution of a constrained non-linear least-squares problem. The goal of the thesis is to improve the resolution techniques of this optimization problem, whose main difficulties are its ill-conditioning, its large scale and an expensive cost function in terms of CPU time. Thanks to a detailed study of the problem and to numerous numerical experiments, we justify the use of a sequential quadratic programming method, in which the tangential quadratic programs are solved by an original augmented Lagrangian method. We show the global linear convergence of the latter. The efficiency and robustness of the approach are demonstrated on several synthetic examples and on two real data cases. (author)

The bounds of feasible space on constrained nonconvex quadratic programming

Science.gov (United States)

Zhu, Jinghao

2008-03-01

This paper presents a method to estimate the bounds of the radius of the feasible space for a class of constrained nonconvex quadratic programmingsE Results show that one may compute a bound of the radius of the feasible space by a linear programming which is known to be a P-problem [N. Karmarkar, A new polynomial-time algorithm for linear programming, Combinatorica 4 (1984) 373-395]. It is proposed that one applies this method for using the canonical dual transformation [D.Y. Gao, Canonical duality theory and solutions to constrained nonconvex quadratic programming, J. Global Optimization 29 (2004) 377-399] for solving a standard quadratic programming problem.

A constrained regularization method for inverting data represented by linear algebraic or integral equations

Science.gov (United States)

Provencher, Stephen W.

1982-09-01

CONTIN is a portable Fortran IV package for inverting noisy linear operator equations. These problems occur in the analysis of data from a wide variety experiments. They are generally ill-posed problems, which means that errors in an unregularized inversion are unbounded. Instead, CONTIN seeks the optimal solution by incorporating parsimony and any statistical prior knowledge into the regularizor and absolute prior knowledge into equallity and inequality constraints. This can be greatly increase the resolution and accuracyh of the solution. CONTIN is very flexible, consisting of a core of about 50 subprograms plus 13 small "USER" subprograms, which the user can easily modify to specify special-purpose constraints, regularizors, operator equations, simulations, statistical weighting, etc. Specjial collections of USER subprograms are available for photon correlation spectroscopy, multicomponent spectra, and Fourier-Bessel, Fourier and Laplace transforms. Numerically stable algorithms are used throughout CONTIN. A fairly precise definition of information content in terms of degrees of freedom is given. The regularization parameter can be automatically chosen on the basis of an F-test and confidence region. The interpretation of the latter and of error estimates based on the covariance matrix of the constrained regularized solution are discussed. The strategies, methods and options in CONTIN are outlined. The program itself is described in the following paper.

Some new ternary linear codes

Directory of Open Access Journals (Sweden)

Rumen Daskalov

2017-07-01

Full Text Available Let an $[n,k,d]_q$ code be a linear code of length $n$, dimension $k$ and minimum Hamming distance $d$ over $GF(q$. One of the most important problems in coding theory is to construct codes with optimal minimum distances. In this paper 22 new ternary linear codes are presented. Two of them are optimal. All new codes improve the respective lower bounds in [11].

Uniqueness conditions for constrained three-way factor decompositions with linearly dependent loadings

NARCIS (Netherlands)

Stegeman, Alwin; De Almeida, Andre L. F.

2009-01-01

In this paper, we derive uniqueness conditions for a constrained version of the parallel factor (Parafac) decomposition, also known as canonical decomposition (Candecomp). Candecomp/Parafac (CP) decomposes a three-way array into a prespecified number of outer product arrays. The constraint is that

Some new quasi-twisted ternary linear codes

Directory of Open Access Journals (Sweden)

Rumen Daskalov

2015-09-01

Full Text Available Let [n, k, d]_q code be a linear code of length n, dimension k and minimum Hamming distance d over GF(q. One of the basic and most important problems in coding theory is to construct codes with best possible minimum distances. In this paper seven quasi-twisted ternary linear codes are constructed. These codes are new and improve the best known lower bounds on the minimum distance in [6].

Implementation Of The Local Minimum Wage In Malang City (A Case Study in Malang City 2014

Directory of Open Access Journals (Sweden)

Dhea Candra Dewi Candra Dewi

2015-04-01

Full Text Available Wage system in a framework of how wages set and defined in order to improve the welfare of worker. The Indonesian government attempt to set a minimum wage in accordance with the eligibility standard of living. The study intend to analize the policy of Local Minimum Wage in Malang City in 2014, its implementation and constraining factors of those Local Minimum Wages. The research uses interactive model analysis as introduced by Miles and Hubermann [6] that consist of data collection, data reduction, data display, and conclusion. Constraining factors seen at the respond given by relevant actors to the policy such as employer organizations, worker unions, wage councils, and local government. Firstly, company as employer organization does not use wage scale system as suggested by the policy. Secondly, lack of communication forum between company and worker union sounds very high. Thirdly, inability of small and big companies to pay minimum standard wages. Lastly, disagreement and different opinion about wage scale applied between local wage council, employer organization and workers union that often occurs in tripartite communication forum.     Keywords: Employers Organization, Local Minimum Wage, Local Wage Council, Policy Implementation, Tripartite Communication forum, Workers Union.

Improved superficial brain hemorrhage visualization in susceptibility weighted images by constrained minimum intensity projection

Science.gov (United States)

Castro, Marcelo A.; Pham, Dzung L.; Butman, John

2016-03-01

Minimum intensity projection is a technique commonly used to display magnetic resonance susceptibility weighted images, allowing the observer to better visualize hemorrhages and vasculature. The technique displays the minimum intensity in a given projection within a thick slab, allowing different connectivity patterns to be easily revealed. Unfortunately, the low signal intensity of the skull within the thick slab can mask superficial tissues near the skull base and other regions. Because superficial microhemorrhages are a common feature of traumatic brain injury, this effect limits the ability to proper diagnose and follow up patients. In order to overcome this limitation, we developed a method to allow minimum intensity projection to properly display superficial tissues adjacent to the skull. Our approach is based on two brain masks, the largest of which includes extracerebral voxels. The analysis of the rind within both masks containing the actual brain boundary allows reclassification of those voxels initially missed in the smaller mask. Morphological operations are applied to guarantee accuracy and topological correctness, and the mean intensity within the mask is assigned to all outer voxels. This prevents bone from dominating superficial regions in the projection, enabling superior visualization of cortical hemorrhages and vessels.

Minimum Bias Trigger in ATLAS

International Nuclear Information System (INIS)

Kwee, Regina

2010-01-01

Since the restart of the LHC in November 2009, ATLAS has collected inelastic pp collisions to perform first measurements on charged particle densities. These measurements will help to constrain various models describing phenomenologically soft parton interactions. Understanding the trigger efficiencies for different event types are therefore crucial to minimize any possible bias in the event selection. ATLAS uses two main minimum bias triggers, featuring complementary detector components and trigger levels. While a hardware based first trigger level situated in the forward regions with 2.2 < |η| < 3.8 has been proven to select pp-collisions very efficiently, the Inner Detector based minimum bias trigger uses a random seed on filled bunches and central tracking detectors for the event selection. Both triggers were essential for the analysis of kinematic spectra of charged particles. Their performance and trigger efficiency measurements as well as studies on possible bias sources will be presented. We also highlight the advantage of these triggers for particle correlation analyses. (author)

Constrained non-linear optimization in 3D reflexion tomography; Problemes d'optimisation non-lineaire avec contraintes en tomographie de reflexion 3D

Energy Technology Data Exchange (ETDEWEB)

Delbos, F.

2004-11-01

Reflexion tomography allows the determination of a subsurface velocity model from the travel times of seismic waves. The introduction of a priori information in this inverse problem can lead to the resolution of a constrained non-linear least-squares problem. The goal of the thesis is to improve the resolution techniques of this optimization problem, whose main difficulties are its ill-conditioning, its large scale and an expensive cost function in terms of CPU time. Thanks to a detailed study of the problem and to numerous numerical experiments, we justify the use of a sequential quadratic programming method, in which the tangential quadratic programs are solved by an original augmented Lagrangian method. We show the global linear convergence of the latter. The efficiency and robustness of the approach are demonstrated on several synthetic examples and on two real data cases. (author)

A Variant of the Topkis-Veinott Method for Solving Inequality Constrained Optimization Problems

International Nuclear Information System (INIS)

Birge, J. R.; Qi, L.; Wei, Z.

2000-01-01

In this paper we give a variant of the Topkis-Veinott method for solving inequality constrained optimization problems. This method uses a linearly constrained positive semidefinite quadratic problem to generate a feasible descent direction at each iteration. Under mild assumptions, the algorithm is shown to be globally convergent in the sense that every accumulation point of the sequence generated by the algorithm is a Fritz-John point of the problem. We introduce a Fritz-John (FJ) function, an FJ1 strong second-order sufficiency condition (FJ1-SSOSC), and an FJ2 strong second-order sufficiency condition (FJ2-SSOSC), and then show, without any constraint qualification (CQ), that (i) if an FJ point z satisfies the FJ1-SSOSC, then there exists a neighborhood N(z) of z such that, for any FJ point y element of N(z) {z } , f 0 (y) ≠ f 0 (z) , where f 0 is the objective function of the problem; (ii) if an FJ point z satisfies the FJ2-SSOSC, then z is a strict local minimum of the problem. The result (i) implies that the entire iteration point sequence generated by the method converges to an FJ point. We also show that if the parameters are chosen large enough, a unit step length can be accepted by the proposed algorithm

Robust self-triggered MPC for constrained linear systems

NARCIS (Netherlands)

Brunner, F.D.; Heemels, W.P.M.H.; Allgöwer, F.

2014-01-01

In this paper we propose a robust self-triggered model predictive control algorithm for linear systems with additive bounded disturbances and hard constraints on the inputs and state. In self-triggered control, at every sampling instant the time until the next sampling instant is computed online

Application of Constrained Linear MPC to a Spray Dryer

DEFF Research Database (Denmark)

Petersen, Lars Norbert; Poulsen, Niels Kjølstad; Niemann, Hans Henrik

2014-01-01

In this paper we develop a linear model predictive control (MPC) algorithm for control of a two stage spray dryer. The states are estimated by a stationary Kalman filter. A non-linear first-principle engineering model is developed to simulate the spray drying process. The model is validated against...... experimental data and able to precisely predict the temperatures, the air humidity and the residual moisture in the dryer. The MPC controls these variables to the target and reject disturbances. Spray drying is a cost-effective method to evaporate water from liquid foods and produces a free flowing powder...

Multiplicative algorithms for constrained non-negative matrix factorization

KAUST Repository

Peng, Chengbin

2012-12-01

Non-negative matrix factorization (NMF) provides the advantage of parts-based data representation through additive only combinations. It has been widely adopted in areas like item recommending, text mining, data clustering, speech denoising, etc. In this paper, we provide an algorithm that allows the factorization to have linear or approximatly linear constraints with respect to each factor. We prove that if the constraint function is linear, algorithms within our multiplicative framework will converge. This theory supports a large variety of equality and inequality constraints, and can facilitate application of NMF to a much larger domain. Taking the recommender system as an example, we demonstrate how a specialized weighted and constrained NMF algorithm can be developed to fit exactly for the problem, and the tests justify that our constraints improve the performance for both weighted and unweighted NMF algorithms under several different metrics. In particular, on the Movielens data with 94% of items, the Constrained NMF improves recall rate 3% compared to SVD50 and 45% compared to SVD150, which were reported as the best two in the top-N metric. © 2012 IEEE.

Aliasing in the Complex Cepstrum of Linear-Phase Signals

DEFF Research Database (Denmark)

Bysted, Tommy Kristensen

1997-01-01

Assuming linear-phase of the associated time signal, this paper presents an approximated analytical description of the unavoidable aliasing in practical use of complex cepstrums. The linear-phase assumption covers two major applications of complex cepstrums which are linear- to minimum-phase FIR......-filter transformation and minimum-phase estimation from amplitude specifications. The description is made in the cepstrum domain, the Fourier transform of the complex cepstrum and in the frequency domain. Two examples are given, one for verification of the derived equations and one using the description to reduce...... aliasing in minimum-phase estimation...

A Primal-Dual Interior Point-Linear Programming Algorithm for MPC

DEFF Research Database (Denmark)

Edlund, Kristian; Sokoler, Leo Emil; Jørgensen, John Bagterp

2009-01-01

Constrained optimal control problems for linear systems with linear constraints and an objective function consisting of linear and l1-norm terms can be expressed as linear programs. We develop an efficient primal-dual interior point algorithm for solution of such linear programs. The algorithm...

Recursive Algorithm For Linear Regression

Science.gov (United States)

Varanasi, S. V.

1988-01-01

Order of model determined easily. Linear-regression algorithhm includes recursive equations for coefficients of model of increased order. Algorithm eliminates duplicative calculations, facilitates search for minimum order of linear-regression model fitting set of data satisfactory.

NP-Hardness of optimizing the sum of Rational Linear Functions over an Asymptotic-Linear-Program

OpenAIRE

Chermakani, Deepak Ponvel

2012-01-01

We convert, within polynomial-time and sequential processing, an NP-Complete Problem into a real-variable problem of minimizing a sum of Rational Linear Functions constrained by an Asymptotic-Linear-Program. The coefficients and constants in the real-variable problem are 0, 1, -1, K, or -K, where K is the time parameter that tends to positive infinity. The number of variables, constraints, and rational linear functions in the objective, of the real-variable problem is bounded by a polynomial ...

Invariant set computation for constrained uncertain discrete-time systems

NARCIS (Netherlands)

Athanasopoulos, N.; Bitsoris, G.

2010-01-01

In this article a novel approach to the determination of polytopic invariant sets for constrained discrete-time linear uncertain systems is presented. First, the problem of stabilizing a prespecified initial condition set in the presence of input and state constraints is addressed. Second, the

Linear and non-linear Modified Gravity forecasts with future surveys

Science.gov (United States)

Casas, Santiago; Kunz, Martin; Martinelli, Matteo; Pettorino, Valeria

2017-12-01

Modified Gravity theories generally affect the Poisson equation and the gravitational slip in an observable way, that can be parameterized by two generic functions (η and μ) of time and space. We bin their time dependence in redshift and present forecasts on each bin for future surveys like Euclid. We consider both Galaxy Clustering and Weak Lensing surveys, showing the impact of the non-linear regime, with two different semi-analytical approximations. In addition to these future observables, we use a prior covariance matrix derived from the Planck observations of the Cosmic Microwave Background. In this work we neglect the information from the cross correlation of these observables, and treat them as independent. Our results show that η and μ in different redshift bins are significantly correlated, but including non-linear scales reduces or even eliminates the correlation, breaking the degeneracy between Modified Gravity parameters and the overall amplitude of the matter power spectrum. We further apply a Zero-phase Component Analysis and identify which combinations of the Modified Gravity parameter amplitudes, in different redshift bins, are best constrained by future surveys. We extend the analysis to two particular parameterizations of μ and η and consider, in addition to Euclid, also SKA1, SKA2, DESI: we find in this case that future surveys will be able to constrain the current values of η and μ at the 2-5% level when using only linear scales (wavevector k < 0 . 15 h/Mpc), depending on the specific time parameterization; sensitivity improves to about 1% when non-linearities are included.

Constrained Optimal Stochastic Control of Non-Linear Wave Energy Point Absorbers

DEFF Research Database (Denmark)

Sichani, Mahdi Teimouri; Chen, Jian-Bing; Kramer, Morten

2014-01-01

to extract energy. Constrains are enforced on the control force to prevent large structural stresses in the floater at specific hot spots with the risk of inducing fatigue damage, or because the demanded control force cannot be supplied by the actuator system due to saturation. Further, constraints...... are enforced on the motion of the floater to prevent it from hitting the bottom of the sea or to make unacceptable jumps out of the water. The applied control law, which is of the feedback type with feedback from the displacement, velocity, and acceleration of the floater, contains two unprovided gain...

A CLASS OF NONMONOTONE TRUST REGION ALGORITHMS FOR LINEARLY CONSTRAINED OPTIMIZATION%线性约束优化的一类非单调信赖域算法

Institute of Scientific and Technical Information of China (English)

葛恒武; 陈中文

2002-01-01

We present a class of nonmonotone trust region algorithms for linearly constrained optimization in this paper.The algorithm may adjust automatically the scope of the monotonicity by the degree that the quadratic model is "trusted".Under the suitable conditions,it is proved that any limit point of the infinite sequence generated by the algorithm is the Kuhn-Tucker point of the primal problem.Finally,some numerical results show that the new algorithm is very effective.

A Reduced Dantzig-Wolfe Decomposition for a Suboptimal Linear MPC

DEFF Research Database (Denmark)

Standardi, Laura; Poulsen, Niels Kjølstad; Jørgensen, John Bagterp

2014-01-01

Linear Model Predictive Control (MPC) is an efficient control technique that repeatedly solves online constrained linear programs. In this work we propose an economic linear MPC strategy for operation of energy systems consisting of multiple and independent power units. These systems cooperate...

Rate-Compatible LDPC Codes with Linear Minimum Distance

Science.gov (United States)

Divsalar, Dariush; Jones, Christopher; Dolinar, Samuel

2009-01-01

A recently developed method of constructing protograph-based low-density parity-check (LDPC) codes provides for low iterative decoding thresholds and minimum distances proportional to block sizes, and can be used for various code rates. A code constructed by this method can have either fixed input block size or fixed output block size and, in either case, provides rate compatibility. The method comprises two submethods: one for fixed input block size and one for fixed output block size. The first mentioned submethod is useful for applications in which there are requirements for rate-compatible codes that have fixed input block sizes. These are codes in which only the numbers of parity bits are allowed to vary. The fixed-output-blocksize submethod is useful for applications in which framing constraints are imposed on the physical layers of affected communication systems. An example of such a system is one that conforms to one of many new wireless-communication standards that involve the use of orthogonal frequency-division modulation

A Globally Convergent Parallel SSLE Algorithm for Inequality Constrained Optimization

Directory of Open Access Journals (Sweden)

Zhijun Luo

2014-01-01

Full Text Available A new parallel variable distribution algorithm based on interior point SSLE algorithm is proposed for solving inequality constrained optimization problems under the condition that the constraints are block-separable by the technology of sequential system of linear equation. Each iteration of this algorithm only needs to solve three systems of linear equations with the same coefficient matrix to obtain the descent direction. Furthermore, under certain conditions, the global convergence is achieved.

Identification of constrained peptides that bind to and preferentially inhibit the activity of the hepatitis C viral RNA-dependent RNA polymerase

International Nuclear Information System (INIS)

Amin, Anthony; Zaccardi, Joe; Mullen, Stanley; Olland, Stephane; Orlowski, Mark; Feld, Boris; Labonte, Patrick; Mak, Paul

2003-01-01

A class of disulfide constrained peptides containing a core motif FPWG was identified from a screen of phage displayed library using the HCV RNA-dependent RNA polymerase (NS5B) as a bait. Surface plasmon resonance studies showed that three highly purified synthetic constrained peptides bound to immobilized NS5B with estimated K d values ranging from 30 to 60 μM. In addition, these peptides inhibited the NS5B activity in vitro with IC 50 ranging from 6 to 48 μM, whereas in contrast they had no inhibitory effect on the enzymatic activities of calf thymus polymerase α, human polymerase β, RSV polymerase, and HIV reverse transcriptase in vitro. Two peptides demonstrated conformation-dependent inhibition since their synthetic linear versions were not inhibitory in the NS5B assay. A constrained peptide with the minimum core motif FPWG retained selective inhibition of NS5B activity with an IC 50 of 50 μM. Alanine scan analyses of a representative constrained peptide, FPWGNTW, indicated that residues F1 and W7 were critical for the inhibitory effect of this peptide, although residues P2 and N5 had some measurable inhibitory effect as well. Further analyses of the mechanism of inhibition indicated that these peptides inhibited the formation of preelongation complexes required for the elongation reaction. However, once the preelongation complex was formed, its activity was refractory to peptide inhibition. Furthermore, the constrained peptide FPWGNTW inhibited de novo initiated RNA synthesis by NS5B from a poly(rC) template. These data indicate that the peptides confer selective inhibition of NS5B activity by binding to the enzyme and perturbing an early step preceding the processive elongation step of RNA synthesis

Fast Combinatorial Algorithm for the Solution of Linearly Constrained Least Squares Problems

Science.gov (United States)

Van Benthem, Mark H.; Keenan, Michael R.

2008-11-11

A fast combinatorial algorithm can significantly reduce the computational burden when solving general equality and inequality constrained least squares problems with large numbers of observation vectors. The combinatorial algorithm provides a mathematically rigorous solution and operates at great speed by reorganizing the calculations to take advantage of the combinatorial nature of the problems to be solved. The combinatorial algorithm exploits the structure that exists in large-scale problems in order to minimize the number of arithmetic operations required to obtain a solution.

Reachable Distance Space: Efficient Sampling-Based Planning for Spatially Constrained Systems

KAUST Repository

Xinyu Tang,; Thomas, S.; Coleman, P.; Amato, N. M.

2010-01-01

reachable distance space (RD-space), in which all configurations lie in the set of constraint-satisfying subspaces. This enables us to directly sample the constrained subspaces with complexity linear in the number of the robot's degrees of freedom

Minimum Delay Moving Object Detection

KAUST Repository

Lao, Dong

2017-11-09

We present a general framework and method for detection of an object in a video based on apparent motion. The object moves relative to background motion at some unknown time in the video, and the goal is to detect and segment the object as soon it moves in an online manner. Due to unreliability of motion between frames, more than two frames are needed to reliably detect the object. Our method is designed to detect the object(s) with minimum delay, i.e., frames after the object moves, constraining the false alarms. Experiments on a new extensive dataset for moving object detection show that our method achieves less delay for all false alarm constraints than existing state-of-the-art.

Minimum Delay Moving Object Detection

KAUST Repository

Lao, Dong

2017-01-08

We present a general framework and method for detection of an object in a video based on apparent motion. The object moves relative to background motion at some unknown time in the video, and the goal is to detect and segment the object as soon it moves in an online manner. Due to unreliability of motion between frames, more than two frames are needed to reliably detect the object. Our method is designed to detect the object(s) with minimum delay, i.e., frames after the object moves, constraining the false alarms. Experiments on a new extensive dataset for moving object detection show that our method achieves less delay for all false alarm constraints than existing state-of-the-art.

Minimum Delay Moving Object Detection

KAUST Repository

Lao, Dong; Sundaramoorthi, Ganesh

2017-01-01

We present a general framework and method for detection of an object in a video based on apparent motion. The object moves relative to background motion at some unknown time in the video, and the goal is to detect and segment the object as soon it moves in an online manner. Due to unreliability of motion between frames, more than two frames are needed to reliably detect the object. Our method is designed to detect the object(s) with minimum delay, i.e., frames after the object moves, constraining the false alarms. Experiments on a new extensive dataset for moving object detection show that our method achieves less delay for all false alarm constraints than existing state-of-the-art.

Constrained dansyl derivatives reveal bacterial specificity of highly conserved thymidylate synthases.

Science.gov (United States)

Calò, Sanuele; Tondi, Donatella; Ferrari, Stefania; Venturelli, Alberto; Ghelli, Stefano; Costi, Maria Paola

2008-03-25

The elucidation of the structural/functional specificities of highly conserved enzymes remains a challenging area of investigation, and enzymes involved in cellular replication are important targets for functional studies and drug discovery. Thymidylate synthase (TS, ThyA) governs the synthesis of thymidylate for use in DNA synthesis. The present study focused on Lactobacillus casei TS (LcTS) and Escherichia coli TS (EcTS), which exhibit 50 % sequence identity and strong folding similarity. We have successfully designed and validated a chemical model in which linear, but not constrained, dansyl derivatives specifically complement the LcTS active site. Conversely, chemically constrained dansyl derivatives showed up to 1000-fold improved affinity for EcTS relative to the inhibitory activity of linear derivatives. This study demonstrates that the accurate design of small ligands can uncover functional features of highly conserved enzymes.

Online constrained model-based reinforcement learning

CSIR Research Space (South Africa)

Van Niekerk, B

2017-08-01

Full Text Available Constrained Model-based Reinforcement Learning Benjamin van Niekerk School of Computer Science University of the Witwatersrand South Africa Andreas Damianou∗ Amazon.com Cambridge, UK Benjamin Rosman Council for Scientific and Industrial Research, and School... MULTIPLE SHOOTING Using direct multiple shooting (Bock and Plitt, 1984), problem (1) can be transformed into a structured non- linear program (NLP). First, the time horizon [t0, t0 + T ] is partitioned into N equal subintervals [tk, tk+1] for k = 0...

Flexure Based Linear and Rotary Bearings

Science.gov (United States)

Voellmer, George M. (Inventor)

2016-01-01

A flexure based linear bearing includes top and bottom parallel rigid plates; first and second flexures connecting the top and bottom plates and constraining exactly four degrees of freedom of relative motion of the plates, the four degrees of freedom being X and Y axis translation and rotation about the X and Y axes; and a strut connecting the top and bottom plates and further constraining exactly one degree of freedom of the plates, the one degree of freedom being one of Z axis translation and rotation about the Z axis.

Parameters Tuning of Model Free Adaptive Control Based on Minimum Entropy

Institute of Scientific and Technical Information of China (English)

Chao Ji; Jing Wang; Liulin Cao; Qibing Jin

2014-01-01

Dynamic linearization based model free adaptive control(MFAC) algorithm has been widely used in practical systems, in which some parameters should be tuned before it is successfully applied to process industries. Considering the random noise existing in real processes, a parameter tuning method based on minimum entropy optimization is proposed,and the feature of entropy is used to accurately describe the system uncertainty. For cases of Gaussian stochastic noise and non-Gaussian stochastic noise, an entropy recursive optimization algorithm is derived based on approximate model or identified model. The extensive simulation results show the effectiveness of the minimum entropy optimization for the partial form dynamic linearization based MFAC. The parameters tuned by the minimum entropy optimization index shows stronger stability and more robustness than these tuned by other traditional index,such as integral of the squared error(ISE) or integral of timeweighted absolute error(ITAE), when the system stochastic noise exists.

Risk-constrained self-scheduling of a fuel and emission constrained power producer using rolling window procedure

International Nuclear Information System (INIS)

Kazempour, S. Jalal; Moghaddam, Mohsen Parsa

2011-01-01

This work addresses a relevant methodology for self-scheduling of a price-taker fuel and emission constrained power producer in day-ahead correlated energy, spinning reserve and fuel markets to achieve a trade-off between the expected profit and the risk versus different risk levels based on Markowitz's seminal work in the area of portfolio selection. Here, a set of uncertainties including price forecasting errors and available fuel uncertainty are considered. The latter uncertainty arises because of uncertainties in being called for reserve deployment in the spinning reserve market and availability of power plant. To tackle the price forecasting errors, variances of energy, spinning reserve and fuel prices along with their covariances which are due to markets correlation are taken into account using relevant historical data. In order to tackle available fuel uncertainty, a framework for self-scheduling referred to as rolling window is proposed. This risk-constrained self-scheduling framework is therefore formulated and solved as a mixed-integer non-linear programming problem. Furthermore, numerical results for a case study are discussed. (author)

Minimum relative entropy, Bayes and Kapur

Science.gov (United States)

Woodbury, Allan D.

2011-04-01

The focus of this paper is to illustrate important philosophies on inversion and the similarly and differences between Bayesian and minimum relative entropy (MRE) methods. The development of each approach is illustrated through the general-discrete linear inverse. MRE differs from both Bayes and classical statistical methods in that knowledge of moments are used as ‘data’ rather than sample values. MRE like Bayes, presumes knowledge of a prior probability distribution and produces the posterior pdf itself. MRE attempts to produce this pdf based on the information provided by new moments. It will use moments of the prior distribution only if new data on these moments is not available. It is important to note that MRE makes a strong statement that the imposed constraints are exact and complete. In this way, MRE is maximally uncommitted with respect to unknown information. In general, since input data are known only to within a certain accuracy, it is important that any inversion method should allow for errors in the measured data. The MRE approach can accommodate such uncertainty and in new work described here, previous results are modified to include a Gaussian prior. A variety of MRE solutions are reproduced under a number of assumed moments and these include second-order central moments. Various solutions of Jacobs & van der Geest were repeated and clarified. Menke's weighted minimum length solution was shown to have a basis in information theory, and the classic least-squares estimate is shown as a solution to MRE under the conditions of more data than unknowns and where we utilize the observed data and their associated noise. An example inverse problem involving a gravity survey over a layered and faulted zone is shown. In all cases the inverse results match quite closely the actual density profile, at least in the upper portions of the profile. The similar results to Bayes presented in are a reflection of the fact that the MRE posterior pdf, and its mean

Linear-Array Photoacoustic Imaging Using Minimum Variance-Based Delay Multiply and Sum Adaptive Beamforming Algorithm

OpenAIRE

Mozaffarzadeh, Moein; Mahloojifar, Ali; Orooji, Mahdi; Kratkiewicz, Karl; Adabi, Saba; Nasiriavanaki, Mohammadreza

2017-01-01

In Photoacoustic imaging (PA), Delay-and-Sum (DAS) beamformer is a common beamforming algorithm having a simple implementation. However, it results in a poor resolution and high sidelobes. To address these challenges, a new algorithm namely Delay-Multiply-and-Sum (DMAS) was introduced having lower sidelobes compared to DAS. To improve the resolution of DMAS, a novel beamformer is introduced using Minimum Variance (MV) adaptive beamforming combined with DMAS, so-called Minimum Variance-Based D...

Solution of a Complex Least Squares Problem with Constrained Phase.

Science.gov (United States)

Bydder, Mark

2010-12-30

The least squares solution of a complex linear equation is in general a complex vector with independent real and imaginary parts. In certain applications in magnetic resonance imaging, a solution is desired such that each element has the same phase. A direct method for obtaining the least squares solution to the phase constrained problem is described.

Pole shifting with constrained output feedback

International Nuclear Information System (INIS)

Hamel, D.; Mensah, S.; Boisvert, J.

1984-03-01

The concept of pole placement plays an important role in linear, multi-variable, control theory. It has received much attention since its introduction, and several pole shifting algorithms are now available. This work presents a new method which allows practical and engineering constraints such as gain limitation and controller structure to be introduced right into the pole shifting design strategy. This is achieved by formulating the pole placement problem as a constrained optimization problem. Explicit constraints (controller structure and gain limits) are defined to identify an admissible region for the feedback gain matrix. The desired pole configuration is translated into an appropriate cost function which must be closed-loop minimized. The resulting constrained optimization problem can thus be solved with optimization algorithms. The method has been implemented as an algorithmic interactive module in a computer-aided control system design package, MVPACK. The application of the method is illustrated to design controllers for an aircraft and an evaporator. The results illustrate the importance of controller structure on overall performance of a control system

Multivariable controller for discrete stochastic amplitude-constrained systems

Directory of Open Access Journals (Sweden)

Hannu T. Toivonen

1983-04-01

Full Text Available A sub-optimal multivariable controller for discrete stochastic amplitude-constrained systems is presented. In the approach the regulator structure is restricted to the class of linear saturated feedback laws. The stationary covariances of the controlled system are evaluated by approximating the stationary probability distribution of the state by a gaussian distribution. An algorithm for minimizing a quadratic loss function is given, and examples are presented to illustrate the performance of the sub-optimal controller.

Design for minimum energy in interstellar communication

Science.gov (United States)

Messerschmitt, David G.

2015-02-01

Microwave digital communication at interstellar distances is the foundation of extraterrestrial civilization (SETI and METI) communication of information-bearing signals. Large distances demand large transmitted power and/or large antennas, while the propagation is transparent over a wide bandwidth. Recognizing a fundamental tradeoff, reduced energy delivered to the receiver at the expense of wide bandwidth (the opposite of terrestrial objectives) is advantageous. Wide bandwidth also results in simpler design and implementation, allowing circumvention of dispersion and scattering arising in the interstellar medium and motion effects and obviating any related processing. The minimum energy delivered to the receiver per bit of information is determined by cosmic microwave background alone. By mapping a single bit onto a carrier burst, the Morse code invented for the telegraph in 1836 comes closer to this minimum energy than approaches used in modern terrestrial radio. Rather than the terrestrial approach of adding phases and amplitudes increases information capacity while minimizing bandwidth, adding multiple time-frequency locations for carrier bursts increases capacity while minimizing energy per information bit. The resulting location code is simple and yet can approach the minimum energy as bandwidth is expanded. It is consistent with easy discovery, since carrier bursts are energetic and straightforward modifications to post-detection pattern recognition can identify burst patterns. Time and frequency coherence constraints leading to simple signal discovery are addressed, and observations of the interstellar medium by transmitter and receiver constrain the burst parameters and limit the search scope.

Linear regressive model structures for estimation and prediction of compartmental diffusive systems

NARCIS (Netherlands)

Vries, D; Keesman, K.J.; Zwart, Heiko J.

In input-output relations of (compartmental) diffusive systems, physical parameters appear non-linearly, resulting in the use of (constrained) non-linear parameter estimation techniques with its short-comings regarding global optimality and computational effort. Given a LTI system in state space

Linear regressive model structures for estimation and prediction of compartmental diffusive systems

NARCIS (Netherlands)

Vries, D.; Keesman, K.J.; Zwart, H.

2006-01-01

Abstract In input-output relations of (compartmental) diffusive systems, physical parameters appear non-linearly, resulting in the use of (constrained) non-linear parameter estimation techniques with its short-comings regarding global optimality and computational effort. Given a LTI system in state

Small-kernel constrained-least-squares restoration of sampled image data

Science.gov (United States)

Hazra, Rajeeb; Park, Stephen K.

1992-10-01

Constrained least-squares image restoration, first proposed by Hunt twenty years ago, is a linear image restoration technique in which the restoration filter is derived by maximizing the smoothness of the restored image while satisfying a fidelity constraint related to how well the restored image matches the actual data. The traditional derivation and implementation of the constrained least-squares restoration filter is based on an incomplete discrete/discrete system model which does not account for the effects of spatial sampling and image reconstruction. For many imaging systems, these effects are significant and should not be ignored. In a recent paper Park demonstrated that a derivation of the Wiener filter based on the incomplete discrete/discrete model can be extended to a more comprehensive end-to-end, continuous/discrete/continuous model. In a similar way, in this paper, we show that a derivation of the constrained least-squares filter based on the discrete/discrete model can also be extended to this more comprehensive continuous/discrete/continuous model and, by so doing, an improved restoration filter is derived. Building on previous work by Reichenbach and Park for the Wiener filter, we also show that this improved constrained least-squares restoration filter can be efficiently implemented as a small-kernel convolution in the spatial domain.

Anti-D3 branes and moduli in non-linear supergravity

Science.gov (United States)

Garcia del Moral, Maria P.; Parameswaran, Susha; Quiroz, Norma; Zavala, Ivonne

2017-10-01

Anti-D3 branes and non-perturbative effects in flux compactifications spontaneously break supersymmetry and stabilise moduli in a metastable de Sitter vacua. The low energy 4D effective field theory description for such models would be a supergravity theory with non-linearly realised supersymmetry. Guided by string theory modular symmetry, we compute this non-linear supergravity theory, including dependence on all bulk moduli. Using either a constrained chiral superfield or a constrained vector field, the uplifting contribution to the scalar potential from the anti-D3 brane can be parameterised either as an F-term or Fayet-Iliopoulos D-term. Using again the modular symmetry, we show that 4D non-linear supergravities that descend from string theory have an enhanced protection from quantum corrections by non-renormalisation theorems. The superpotential giving rise to metastable de Sitter vacua is robust against perturbative string-loop and α' corrections.

On a Minimum Problem in Smectic Elastomers

International Nuclear Information System (INIS)

Buonsanti, Michele; Giovine, Pasquale

2008-01-01

Smectic elastomers are layered materials exhibiting a solid-like elastic response along the layer normal and a rubbery one in the plane. Balance equations for smectic elastomers are derived from the general theory of continua with constrained microstructure. In this work we investigate a very simple minimum problem based on multi-well potentials where the microstructure is taken into account. The set of polymeric strains minimizing the elastic energy contains a one-parameter family of simple strain associated with a micro-variation of the degree of freedom. We develop the energy functional through two terms, the first one nematic and the second one considering the tilting phenomenon; after, by developing in the rubber elasticity framework, we minimize over the tilt rotation angle and extract the engineering stress

A method for fitting regression splines with varying polynomial order in the linear mixed model.

Science.gov (United States)

Edwards, Lloyd J; Stewart, Paul W; MacDougall, James E; Helms, Ronald W

2006-02-15

The linear mixed model has become a widely used tool for longitudinal analysis of continuous variables. The use of regression splines in these models offers the analyst additional flexibility in the formulation of descriptive analyses, exploratory analyses and hypothesis-driven confirmatory analyses. We propose a method for fitting piecewise polynomial regression splines with varying polynomial order in the fixed effects and/or random effects of the linear mixed model. The polynomial segments are explicitly constrained by side conditions for continuity and some smoothness at the points where they join. By using a reparameterization of this explicitly constrained linear mixed model, an implicitly constrained linear mixed model is constructed that simplifies implementation of fixed-knot regression splines. The proposed approach is relatively simple, handles splines in one variable or multiple variables, and can be easily programmed using existing commercial software such as SAS or S-plus. The method is illustrated using two examples: an analysis of longitudinal viral load data from a study of subjects with acute HIV-1 infection and an analysis of 24-hour ambulatory blood pressure profiles.

Dynamically constrained ensemble perturbations – application to tides on the West Florida Shelf

Directory of Open Access Journals (Sweden)

F. Lenartz

2009-07-01

Full Text Available A method is presented to create an ensemble of perturbations that satisfies linear dynamical constraints. A cost function is formulated defining the probability of each perturbation. It is shown that the perturbations created with this approach take the land-sea mask into account in a similar way as variational analysis techniques. The impact of the land-sea mask is illustrated with an idealized configuration of a barrier island. Perturbations with a spatially variable correlation length can be also created by this approach. The method is applied to a realistic configuration of the West Florida Shelf to create perturbations of the M2 tidal parameters for elevation and depth-averaged currents. The perturbations are weakly constrained to satisfy the linear shallow-water equations. Despite that the constraint is derived from an idealized assumption, it is shown that this approach is applicable to a non-linear and baroclinic model. The amplitude of spurious transient motions created by constrained perturbations of initial and boundary conditions is significantly lower compared to perturbing the variables independently or to using only the momentum equation to compute the velocity perturbations from the elevation.

A first-order multigrid method for bound-constrained convex optimization

Czech Academy of Sciences Publication Activity Database

Kočvara, Michal; Mohammed, S.

2016-01-01

Roč. 31, č. 3 (2016), s. 622-644 ISSN 1055-6788 R&D Projects: GA ČR(CZ) GAP201/12/0671 Grant - others:European Commission - EC(XE) 313781 Institutional support: RVO:67985556 Keywords : bound-constrained optimization * multigrid methods * linear complementarity problems Subject RIV: BA - General Mathematics Impact factor: 1.023, year: 2016 http://library.utia.cas.cz/separaty/2016/MTR/kocvara-0460326.pdf

Risk adjusted receding horizon control of constrained linear parameter varying systems

NARCIS (Netherlands)

Sznaier, M.; Lagoa, C.; Stoorvogel, Antonie Arij; Li, X.

2005-01-01

In the past few years, control of Linear Parameter Varying Systems (LPV) has been the object of considerable attention, as a way of formalizing the intuitively appealing idea of gain scheduling control for nonlinear systems. However, currently available LPV techniques are both computationally

Constraining Basin Depth and Fault Displacement in the Malombe Basin Using Potential Field Methods

Science.gov (United States)

Beresh, S. C. M.; Elifritz, E. A.; Méndez, K.; Johnson, S.; Mynatt, W. G.; Mayle, M.; Atekwana, E. A.; Laó-Dávila, D. A.; Chindandali, P. R. N.; Chisenga, C.; Gondwe, S.; Mkumbwa, M.; Kalaguluka, D.; Kalindekafe, L.; Salima, J.

2017-12-01

The Malombe Basin is part of the Malawi Rift which forms the southern part of the Western Branch of the East African Rift System. At its southern end, the Malawi Rift bifurcates into the Bilila-Mtakataka and Chirobwe-Ntcheu fault systems and the Lake Malombe Rift Basin around the Shire Horst, a competent block under the Nankumba Peninsula. The Malombe Basin is approximately 70km from north to south and 35km at its widest point from east to west, bounded by reversing-polarity border faults. We aim to constrain the depth of the basin to better understand displacement of each border fault. Our work utilizes two east-west gravity profiles across the basin coupled with Source Parameter Imaging (SPI) derived from a high-resolution aeromagnetic survey. The first gravity profile was done across the northern portion of the basin and the second across the southern portion. Gravity and magnetic data will be used to constrain basement depths and the thickness of the sedimentary cover. Additionally, Shuttle Radar Topography Mission (SRTM) data is used to understand the topographic expression of the fault scarps. Estimates for minimum displacement of the border faults on either side of the basin were made by adding the elevation of the scarps to the deepest SPI basement estimates at the basin borders. Our preliminary results using SPI and SRTM data show a minimum displacement of approximately 1.3km for the western border fault; the minimum displacement for the eastern border fault is 740m. However, SPI merely shows the depth to the first significantly magnetic layer in the subsurface, which may or may not be the actual basement layer. Gravimetric readings are based on subsurface density and thus circumvent issues arising from magnetic layers located above the basement; therefore expected results for our work will be to constrain more accurate basin depth by integrating the gravity profiles. Through more accurate basement depth estimates we also gain more accurate displacement

Experimental Approaches at Linear Colliders

International Nuclear Information System (INIS)

Jaros, John A

2002-01-01

Precision measurements have played a vital role in our understanding of elementary particle physics. Experiments performed using e + e - collisions have contributed an essential part. Recently, the precision measurements at LEP and SLC have probed the standard model at the quantum level and severely constrained the mass of the Higgs boson [1]. Coupled with the limits on the Higgs mass from direct searches [2], this enables the mass to be constrained to be in the range 115-205 GeV. Developments in accelerator R and D have matured to the point where one could contemplate construction of a linear collider with initial energy in the 500 GeV range and a credible upgrade path to ∼ 1 TeV. Now is therefore the correct time to critically evaluate the case for such a facility

Linearly Refined Session Types

Directory of Open Access Journals (Sweden)

Pedro Baltazar

2012-11-01

Full Text Available Session types capture precise protocol structure in concurrent programming, but do not specify properties of the exchanged values beyond their basic type. Refinement types are a form of dependent types that can address this limitation, combining types with logical formulae that may refer to program values and can constrain types using arbitrary predicates. We present a pi calculus with assume and assert operations, typed using a session discipline that incorporates refinement formulae written in a fragment of Multiplicative Linear Logic. Our original combination of session and refinement types, together with the well established benefits of linearity, allows very fine-grained specifications of communication protocols in which refinement formulae are treated as logical resources rather than persistent truths.

An experimental comparison of some heuristics for cardinality constrained bin packing problem

Directory of Open Access Journals (Sweden)

Maja Remic

2012-01-01

Full Text Available Background: Bin packing is an NPhard optimization problem of packing items of given sizes into minimum number of capacitylimited bins. Besides the basic problem, numerous other variants of bin packing exist. The cardinality constrained bin packing adds an additional constraint that the number of items in a bin must not exceed a given limit Nmax. Objectives: Goal of the paper is to present a preliminary experimental study which demostrates adaptations of the new algorithms to the general cardinality constrained bin packing problem. Methods/Approach: Straightforward modifications of First Fit Decreasing (FFD, Refined First Fit (RFF and the algorithm by Zhang et al. for the bin packing problem are compared to four cardinality constrained bin packing problem specific algorithms on random lists of items with 0%, 10%, 30% and 50% of large items. The behaviour of all algorithms when cardinality constraint Nmax increases is also studied. Results: Results show that all specific algorithms outperform the general algorithms on lists with low percentage of big items. Conclusions: One of the specific algorithms performs better or equally well even on lists with high percentage of big items and is therefore of significant interest. The behaviour when Nmax increases shows that specific algorithms can be used for solving the general bin packing problem as well.

Determining the Optimal Solution for Quadratically Constrained Quadratic Programming (QCQP) on Energy-Saving Generation Dispatch Problem

Science.gov (United States)

Lesmana, E.; Chaerani, D.; Khansa, H. N.

2018-03-01

Energy-Saving Generation Dispatch (ESGD) is a scheme made by Chinese Government in attempt to minimize CO2 emission produced by power plant. This scheme is made related to global warming which is primarily caused by too much CO2 in earth’s atmosphere, and while the need of electricity is something absolute, the power plants producing it are mostly thermal-power plant which produced many CO2. Many approach to fulfill this scheme has been made, one of them came through Minimum Cost Flow in which resulted in a Quadratically Constrained Quadratic Programming (QCQP) form. In this paper, ESGD problem with Minimum Cost Flow in QCQP form will be solved using Lagrange’s Multiplier Method

Constraining ALPs with linear and circular polarisation measurements of quasar light

International Nuclear Information System (INIS)

Payez, Alexandre

2013-09-01

We discuss the constraints derived on the mixing of photons with light pseudoscalars using the distributions of good-quality linear and circular polarisation measurements of light from the least polarised classes of quasars. We also provide the dependence of our limit on the average electron density in the local supercluster for nearly massless particles.

Constraining ALPs with linear and circular polarisation measurements of quasar light

Energy Technology Data Exchange (ETDEWEB)

Payez, Alexandre [Liege Univ. (Belgium). IFPA Group; Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany)

2013-09-15

We discuss the constraints derived on the mixing of photons with light pseudoscalars using the distributions of good-quality linear and circular polarisation measurements of light from the least polarised classes of quasars. We also provide the dependence of our limit on the average electron density in the local supercluster for nearly massless particles.

Stability analysis of switched linear systems defined by graphs

NARCIS (Netherlands)

Athanasopoulos, N.; Lazar, M.

2014-01-01

We present necessary and sufficient conditions for global exponential stability for switched discrete-time linear systems, under arbitrary switching, which is constrained within a set of admissible transitions. The class of systems studied includes the family of systems under arbitrary switching,

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

Linear programming foundations and extensions

CERN Document Server

Vanderbei, Robert J

2001-01-01

Linear Programming: Foundations and Extensions is an introduction to the field of optimization. The book emphasizes constrained optimization, beginning with a substantial treatment of linear programming, and proceeding to convex analysis, network flows, integer programming, quadratic programming, and convex optimization. The book is carefully written. Specific examples and concrete algorithms precede more abstract topics. Topics are clearly developed with a large number of numerical examples worked out in detail. Moreover, Linear Programming: Foundations and Extensions underscores the purpose of optimization: to solve practical problems on a computer. Accordingly, the book is coordinated with free efficient C programs that implement the major algorithms studied: -The two-phase simplex method; -The primal-dual simplex method; -The path-following interior-point method; -The homogeneous self-dual methods. In addition, there are online JAVA applets that illustrate various pivot rules and variants of the simplex m...

A linear time algorithm for minimum fill-in and treewidth for distance heredity graphs

NARCIS (Netherlands)

Broersma, Haitze J.; Dahlhaus, E.; Kloks, A.J.J.; Kloks, T.

2000-01-01

A graph is distance hereditary if it preserves distances in all its connected induced subgraphs. The MINIMUM FILL-IN problem is the problem of finding a chordal supergraph with the smallest possible number of edges. The TREEWIDTH problem is the problem of finding a chordal embedding of the graph

Evolutionary constrained optimization

CERN Document Server

Deb, Kalyanmoy

2015-01-01

This book makes available a self-contained collection of modern research addressing the general constrained optimization problems using evolutionary algorithms. Broadly the topics covered include constraint handling for single and multi-objective optimizations; penalty function based methodology; multi-objective based methodology; new constraint handling mechanism; hybrid methodology; scaling issues in constrained optimization; design of scalable test problems; parameter adaptation in constrained optimization; handling of integer, discrete and mix variables in addition to continuous variables; application of constraint handling techniques to real-world problems; and constrained optimization in dynamic environment. There is also a separate chapter on hybrid optimization, which is gaining lots of popularity nowadays due to its capability of bridging the gap between evolutionary and classical optimization. The material in the book is useful to researchers, novice, and experts alike. The book will also be useful...

Improved initial guess for minimum energy path calculations

International Nuclear Information System (INIS)

Smidstrup, Søren; Pedersen, Andreas; Stokbro, Kurt; Jónsson, Hannes

2014-01-01

A method is presented for generating a good initial guess of a transition path between given initial and final states of a system without evaluation of the energy. An objective function surface is constructed using an interpolation of pairwise distances at each discretization point along the path and the nudged elastic band method then used to find an optimal path on this image dependent pair potential (IDPP) surface. This provides an initial path for the more computationally intensive calculations of a minimum energy path on an energy surface obtained, for example, by ab initio or density functional theory. The optimal path on the IDPP surface is significantly closer to a minimum energy path than a linear interpolation of the Cartesian coordinates and, therefore, reduces the number of iterations needed to reach convergence and averts divergence in the electronic structure calculations when atoms are brought too close to each other in the initial path. The method is illustrated with three examples: (1) rotation of a methyl group in an ethane molecule, (2) an exchange of atoms in an island on a crystal surface, and (3) an exchange of two Si-atoms in amorphous silicon. In all three cases, the computational effort in finding the minimum energy path with DFT was reduced by a factor ranging from 50% to an order of magnitude by using an IDPP path as the initial path. The time required for parallel computations was reduced even more because of load imbalance when linear interpolation of Cartesian coordinates was used

Heuristic algorithm for single resource constrained project scheduling problem based on the dynamic programming

Directory of Open Access Journals (Sweden)

Stanimirović Ivan

2009-01-01

Full Text Available We introduce a heuristic method for the single resource constrained project scheduling problem, based on the dynamic programming solution of the knapsack problem. This method schedules projects with one type of resources, in the non-preemptive case: once started an activity is not interrupted and runs to completion. We compare the implementation of this method with well-known heuristic scheduling method, called Minimum Slack First (known also as Gray-Kidd algorithm, as well as with Microsoft Project.

Time and Memory Efficient Online Piecewise Linear Approximation of Sensor Signals.

Science.gov (United States)

Grützmacher, Florian; Beichler, Benjamin; Hein, Albert; Kirste, Thomas; Haubelt, Christian

2018-05-23

Piecewise linear approximation of sensor signals is a well-known technique in the fields of Data Mining and Activity Recognition. In this context, several algorithms have been developed, some of them with the purpose to be performed on resource constrained microcontroller architectures of wireless sensor nodes. While microcontrollers are usually constrained in computational power and memory resources, all state-of-the-art piecewise linear approximation techniques either need to buffer sensor data or have an execution time depending on the segment’s length. In the paper at hand, we propose a novel piecewise linear approximation algorithm, with a constant computational complexity as well as a constant memory complexity. Our proposed algorithm’s worst-case execution time is one to three orders of magnitude smaller and its average execution time is three to seventy times smaller compared to the state-of-the-art Piecewise Linear Approximation (PLA) algorithms in our experiments. In our evaluations, we show that our algorithm is time and memory efficient without sacrificing the approximation quality compared to other state-of-the-art piecewise linear approximation techniques, while providing a maximum error guarantee per segment, a small parameter space of only one parameter, and a maximum latency of one sample period plus its worst-case execution time.

Resource Constrained Planning of Multiple Projects with Separable Activities

Science.gov (United States)

Fujii, Susumu; Morita, Hiroshi; Kanawa, Takuya

In this study we consider a resource constrained planning problem of multiple projects with separable activities. This problem provides a plan to process the activities considering a resource availability with time window. We propose a solution algorithm based on the branch and bound method to obtain the optimal solution minimizing the completion time of all projects. We develop three methods for improvement of computational efficiency, that is, to obtain initial solution with minimum slack time rule, to estimate lower bound considering both time and resource constraints and to introduce an equivalence relation for bounding operation. The effectiveness of the proposed methods is demonstrated by numerical examples. Especially as the number of planning projects increases, the average computational time and the number of searched nodes are reduced.

An optimally weighted estimator of the linear power spectrum disentangling the growth of density perturbations across galaxy surveys

International Nuclear Information System (INIS)

Sorini, D.

2017-01-01

Measuring the clustering of galaxies from surveys allows us to estimate the power spectrum of matter density fluctuations, thus constraining cosmological models. This requires careful modelling of observational effects to avoid misinterpretation of data. In particular, signals coming from different distances encode information from different epochs. This is known as ''light-cone effect'' and is going to have a higher impact as upcoming galaxy surveys probe larger redshift ranges. Generalising the method by Feldman, Kaiser and Peacock (1994) [1], I define a minimum-variance estimator of the linear power spectrum at a fixed time, properly taking into account the light-cone effect. An analytic expression for the estimator is provided, and that is consistent with the findings of previous works in the literature. I test the method within the context of the Halofit model, assuming Planck 2014 cosmological parameters [2]. I show that the estimator presented recovers the fiducial linear power spectrum at present time within 5% accuracy up to k ∼ 0.80 h Mpc −1 and within 10% up to k ∼ 0.94 h Mpc −1 , well into the non-linear regime of the growth of density perturbations. As such, the method could be useful in the analysis of the data from future large-scale surveys, like Euclid.

Robustification and Optimization in Repetitive Control For Minimum Phase and Non-Minimum Phase Systems

Science.gov (United States)

Prasitmeeboon, Pitcha

repetitive control FIR compensator. The aim is to reduce the final error level by using real time frequency response model updates to successively increase the cutoff frequency, each time creating the improved model needed to produce convergence zero error up to the higher cutoff. Non-minimum phase systems present a difficult design challenge to the sister field of Iterative Learning Control. The third topic investigates to what extent the same challenges appear in RC. One challenge is that the intrinsic non-minimum phase zero mapped from continuous time is close to the pole of repetitive controller at +1 creating behavior similar to pole-zero cancellation. The near pole-zero cancellation causes slow learning at DC and low frequencies. The Min-Max cost function over the learning rate is presented. The Min-Max can be reformulated as a Quadratically Constrained Linear Programming problem. This approach is shown to be an RC design approach that addresses the main challenge of non-minimum phase systems to have a reasonable learning rate at DC. Although it was illustrated that using the Min-Max objective improves learning at DC and low frequencies compared to other designs, the method requires model accuracy at high frequencies. In the real world, models usually have error at high frequencies. The fourth topic addresses how one can merge the quadratic penalty to the Min-Max cost function to increase robustness at high frequencies. The topic also considers limiting the Min-Max optimization to some frequencies interval and applying an FIR zero-phase low-pass filter to cutoff the learning for frequencies above that interval.

Linear zonal atmospheric prediction for adaptive optics

Science.gov (United States)

McGuire, Patrick C.; Rhoadarmer, Troy A.; Coy, Hanna A.; Angel, J. Roger P.; Lloyd-Hart, Michael

2000-07-01

We compare linear zonal predictors of atmospheric turbulence for adaptive optics. Zonal prediction has the possible advantage of being able to interpret and utilize wind-velocity information from the wavefront sensor better than modal prediction. For simulated open-loop atmospheric data for a 2- meter 16-subaperture AO telescope with 5 millisecond prediction and a lookback of 4 slope-vectors, we find that Widrow-Hoff Delta-Rule training of linear nets and Back- Propagation training of non-linear multilayer neural networks is quite slow, getting stuck on plateaus or in local minima. Recursive Least Squares training of linear predictors is two orders of magnitude faster and it also converges to the solution with global minimum error. We have successfully implemented Amari's Adaptive Natural Gradient Learning (ANGL) technique for a linear zonal predictor, which premultiplies the Delta-Rule gradients with a matrix that orthogonalizes the parameter space and speeds up the training by two orders of magnitude, like the Recursive Least Squares predictor. This shows that the simple Widrow-Hoff Delta-Rule's slow convergence is not a fluke. In the case of bright guidestars, the ANGL, RLS, and standard matrix-inversion least-squares (MILS) algorithms all converge to the same global minimum linear total phase error (approximately 0.18 rad2), which is only approximately 5% higher than the spatial phase error (approximately 0.17 rad2), and is approximately 33% lower than the total 'naive' phase error without prediction (approximately 0.27 rad2). ANGL can, in principle, also be extended to make non-linear neural network training feasible for these large networks, with the potential to lower the predictor error below the linear predictor error. We will soon scale our linear work to the approximately 108-subaperture MMT AO system, both with simulations and real wavefront sensor data from prime focus.

Linearized Alternating Direction Method of Multipliers for Constrained Nonconvex Regularized Optimization

Science.gov (United States)

2016-11-22

structure of the graph, we replace the ℓ1- norm by the nonconvex Capped -ℓ1 norm , and obtain the Generalized Capped -ℓ1 regularized logistic regression...X. M. Yuan. Linearized augmented lagrangian and alternating direction methods for nuclear norm minimization. Mathematics of Computation, 82(281):301...better approximations of ℓ0- norm theoretically and computationally beyond ℓ1- norm , for example, the compressive sensing (Xiao et al., 2011). The

An Equilibrium Chance-Constrained Multiobjective Programming Model with Birandom Parameters and Its Application to Inventory Problem

Directory of Open Access Journals (Sweden)

Zhimiao Tao

2013-01-01

Full Text Available An equilibrium chance-constrained multiobjective programming model with birandom parameters is proposed. A type of linear model is converted into its crisp equivalent model. Then a birandom simulation technique is developed to tackle the general birandom objective functions and birandom constraints. By embedding the birandom simulation technique, a modified genetic algorithm is designed to solve the equilibrium chance-constrained multiobjective programming model. We apply the proposed model and algorithm to a real-world inventory problem and show the effectiveness of the model and the solution method.

Frequency Constrained ShiftCP Modeling of Neuroimaging Data

DEFF Research Database (Denmark)

Mørup, Morten; Hansen, Lars Kai; Madsen, Kristoffer H.

2011-01-01

The shift invariant multi-linear model based on the CandeComp/PARAFAC (CP) model denoted ShiftCP has proven useful for the modeling of latency changes in trial based neuroimaging data[17]. In order to facilitate component interpretation we presently extend the shiftCP model such that the extracted...... components can be constrained to pertain to predefined frequency ranges such as alpha, beta and gamma activity. To infer the number of components in the model we propose to apply automatic relevance determination by imposing priors that define the range of variation of each component of the shiftCP model...

Minimum Delay Moving Object Detection

KAUST Repository

Lao, Dong

2017-05-14

This thesis presents a general framework and method for detection of an object in a video based on apparent motion. The object moves, at some unknown time, differently than the “background” motion, which can be induced from camera motion. The goal of proposed method is to detect and segment the object as soon it moves in an online manner. Since motion estimation can be unreliable between frames, more than two frames are needed to reliably detect the object. Observing more frames before declaring a detection may lead to a more accurate detection and segmentation, since more motion may be observed leading to a stronger motion cue. However, this leads to greater delay. The proposed method is designed to detect the object(s) with minimum delay, i.e., frames after the object moves, constraining the false alarms, defined as declarations of detection before the object moves or incorrect or inaccurate segmentation at the detection time. Experiments on a new extensive dataset for moving object detection show that our method achieves less delay for all false alarm constraints than existing state-of-the-art.

Solving discretely-constrained MPEC problems with applications in electric power markets

International Nuclear Information System (INIS)

Gabriel, Steven A.; Leuthold, Florian U.

2010-01-01

Many of the European energy markets are characterized by dominant players that own a large share of their respective countries' generation capacities. In addition to that, there is a significant lack of cross-border transmission capacity. Combining both facts justifies the assumption that these dominant players are able to influence the market outcome of an internal European energy market due to strategic behavior. In this paper, we present a mathematical formulation in order to solve a Stackelberg game for a network-constrained energy market using integer programming. The strategic player is the Stackelberg leader and the independent system operator (including the decisions of the competitive fringe firms) acts as follower. We assume that there is one strategic player which results in a mathematical program with equilibrium constraints (MPEC). This MPEC is reformulated as mixed-integer linear program (MILP) by using disjunctive constraints and linearization. The MILP formulation gives the opportunity to solve the problems reliably and paves the way to add discrete constraints to the original MPEC formulation which can be used in order to solve discretely-constrained mathematical programs with equilibrium constraints (DC-MPECs). We report computational results for a small illustrative network as well as a stylized Western European grid with realistic data. (author)

Solving discretely-constrained MPEC problems with applications in electric power markets

Energy Technology Data Exchange (ETDEWEB)

Gabriel, Steven A. [1143 Glenn L. Martin Hall, Department of Civil and Environmental Engineering, University of Maryland, College Park, MD 20742-3021 (United States); Leuthold, Florian U. [Chair of Energy Economics and Public Sector Management, Dresden University of Technology, 01069 Dresden (Germany)

2010-01-15

Many of the European energy markets are characterized by dominant players that own a large share of their respective countries' generation capacities. In addition to that, there is a significant lack of cross-border transmission capacity. Combining both facts justifies the assumption that these dominant players are able to influence the market outcome of an internal European energy market due to strategic behavior. In this paper, we present a mathematical formulation in order to solve a Stackelberg game for a network-constrained energy market using integer programming. The strategic player is the Stackelberg leader and the independent system operator (including the decisions of the competitive fringe firms) acts as follower. We assume that there is one strategic player which results in a mathematical program with equilibrium constraints (MPEC). This MPEC is reformulated as mixed-integer linear program (MILP) by using disjunctive constraints and linearization. The MILP formulation gives the opportunity to solve the problems reliably and paves the way to add discrete constraints to the original MPEC formulation which can be used in order to solve discretely-constrained mathematical programs with equilibrium constraints (DC-MPECs). We report computational results for a small illustrative network as well as a stylized Western European grid with realistic data. (author)

Application of a Double-Sided Chance-Constrained Integer Linear Program for Optimization of the Incremental Value of Ecosystem Services in Jilin Province, China

Directory of Open Access Journals (Sweden)

Baofeng Cai

2017-08-01

Full Text Available The Interconnected River System Network Project (IRSNP is a significant water supply engineering project, which is capable of effectively utilizing flood resources to generate ecological value, by connecting 198 lakes and ponds in western Jilin, northeast China. In this article, an optimization research approach has been proposed to maximize the incremental value of IRSNP ecosystem services. A double-sided chance-constrained integer linear program (DCCILP method has been proposed to support the optimization, which can deal with uncertainties presented as integers or random parameters that appear on both sides of the decision variable at the same time. The optimal scheme indicates that after rational optimization, the total incremental value of ecosystem services from the interconnected river system network project increased 22.25%, providing an increase in benefits of 3.26 × 109 ¥ compared to the original scheme. Most of the functional area is swamp wetland, which provides the greatest ecological benefits. Adjustment services increased obviously, implying that the optimization scheme prioritizes ecological benefits rather than supply and production services.

Chance-constrained programming approach to natural-gas curtailment decisions

Energy Technology Data Exchange (ETDEWEB)

Guldmann, J M

1981-10-01

This paper presents a modeling methodology for the determination of optimal-curtailment decisions by a gas-distribution utility during a chronic gas-shortage situation. Based on the end-use priority approach, a linear-programming model is formulated, that reallocates the available gas supply among the utility's customers while minimizing fuel switching, unemployment, and utility operating costs. This model is then transformed into a chance-constrained program in order to account for the weather-related variability of the gas requirements. The methodology is applied to the East Ohio Gas Company. 16 references, 2 figures, 3 tables.

A Design of Mechanical Frequency Converter Linear and Non-linear Spring Combination for Energy Harvesting

International Nuclear Information System (INIS)

Yamamoto, K; Fujita, T; Kanda, K; Maenaka, K; Badel, A; Formosa, F

2014-01-01

In this study, the improvement of energy harvesting from wideband vibration with random change by using a combination of linear and nonlinear spring system is investigated. The system consists of curved beam spring for non-linear buckling, which supports the linear mass-spring resonator. Applying shock acceleration generates a snap through action to the buckling spring. From the FEM analysis, we showed that the snap through acceleration from the buckling action has no relationship with the applied shock amplitude and duration. We use this uniform acceleration as an impulse shock source for the linear resonator. It is easy to obtain the maximum shock response from the uniform snap through acceleration by using a shock response spectrum (SRS) analysis method. At first we investigated the relationship between the snap-through behaviour and an initial curved deflection. Then a time response result for non-linear springs with snap through and minimum force that makes a buckling behaviour were obtained by FEM analysis. By obtaining the optimum SRS frequency for linear resonator, we decided its resonant frequency with the MATLAB simulator

Model Predictive Control Based on Kalman Filter for Constrained Hammerstein-Wiener Systems

Directory of Open Access Journals (Sweden)

Man Hong

2013-01-01

Full Text Available To precisely track the reactor temperature in the entire working condition, the constrained Hammerstein-Wiener model describing nonlinear chemical processes such as in the continuous stirred tank reactor (CSTR is proposed. A predictive control algorithm based on the Kalman filter for constrained Hammerstein-Wiener systems is designed. An output feedback control law regarding the linear subsystem is derived by state observation. The size of reaction heat produced and its influence on the output are evaluated by the Kalman filter. The observation and evaluation results are calculated by the multistep predictive approach. Actual control variables are computed while considering the constraints of the optimal control problem in a finite horizon through the receding horizon. The simulation example of the CSTR tester shows the effectiveness and feasibility of the proposed algorithm.

Solving Fully Fuzzy Linear System of Equations in General Form

Directory of Open Access Journals (Sweden)

A. Yousefzadeh

2012-06-01

Full Text Available In this work, we propose an approach for computing the positive solution of a fully fuzzy linear system where the coefficient matrix is a fuzzy $nimes n$ matrix. To do this, we use arithmetic operations on fuzzy numbers that introduced by Kaffman in and convert the fully fuzzy linear system into two $nimes n$ and $2nimes 2n$ crisp linear systems. If the solutions of these linear systems don't satisfy in positive fuzzy solution condition, we introduce the constrained least squares problem to obtain optimal fuzzy vector solution by applying the ranking function in given fully fuzzy linear system. Using our proposed method, the fully fuzzy linear system of equations always has a solution. Finally, we illustrate the efficiency of proposed method by solving some numerical examples.

A Projected Non-linear Conjugate Gradient Method for Interactive Inverse Kinematics

DEFF Research Database (Denmark)

Engell-Nørregård, Morten; Erleben, Kenny

2009-01-01

Inverse kinematics is the problem of posing an articulated figure to obtain a wanted goal, without regarding inertia and forces. Joint limits are modeled as bounds on individual degrees of freedom, leading to a box-constrained optimization problem. We present A projected Non-linear Conjugate...... Gradient optimization method suitable for box-constrained optimization problems for inverse kinematics. We show application on inverse kinematics positioning of a human figure. Performance is measured and compared to a traditional Jacobian Transpose method. Visual quality of the developed method...

Maximum And Minimum Temperature Trends In Mexico For The Last 31 Years

Science.gov (United States)

Romero-Centeno, R.; Zavala-Hidalgo, J.; Allende Arandia, M. E.; Carrasco-Mijarez, N.; Calderon-Bustamante, O.

2013-05-01

Based on high-resolution (1') daily maps of the maximum and minimum temperatures in Mexico, an analysis of the last 31-year trends is performed. The maps were generated using all the available information from more than 5,000 stations of the Mexican Weather Service (Servicio Meteorológico Nacional, SMN) for the period 1979-2009, along with data from the North American Regional Reanalysis (NARR). The data processing procedure includes a quality control step, in order to eliminate erroneous daily data, and make use of a high-resolution digital elevation model (from GEBCO), the relationship between air temperature and elevation by means of the average environmental lapse rate, and interpolation algorithms (linear and inverse-distance weighting). Based on the monthly gridded maps for the mentioned period, the maximum and minimum temperature trends calculated by least-squares linear regression and their statistical significance are obtained and discussed.

Constraining dark sector perturbations I: cosmic shear and CMB lensing

International Nuclear Information System (INIS)

Battye, Richard A.; Moss, Adam; Pearson, Jonathan A.

2015-01-01

We present current and future constraints on equations of state for dark sector perturbations. The equations of state considered are those corresponding to a generalized scalar field model and time-diffeomorphism invariant L(g) theories that are equivalent to models of a relativistic elastic medium and also Lorentz violating massive gravity. We develop a theoretical understanding of the observable impact of these models. In order to constrain these models we use CMB temperature data from Planck, BAO measurements, CMB lensing data from Planck and the South Pole Telescope, and weak galaxy lensing data from CFHTLenS. We find non-trivial exclusions on the range of parameters, although the data remains compatible with w=−1. We gauge how future experiments will help to constrain the parameters. This is done via a likelihood analysis for CMB experiments such as CoRE and PRISM, and tomographic galaxy weak lensing surveys, focussing in on the potential discriminatory power of Euclid on mildly non-linear scales

Constraining dark sector perturbations I: cosmic shear and CMB lensing

Science.gov (United States)

Battye, Richard A.; Moss, Adam; Pearson, Jonathan A.

2015-04-01

We present current and future constraints on equations of state for dark sector perturbations. The equations of state considered are those corresponding to a generalized scalar field model and time-diffeomorphism invariant Script L(g) theories that are equivalent to models of a relativistic elastic medium and also Lorentz violating massive gravity. We develop a theoretical understanding of the observable impact of these models. In order to constrain these models we use CMB temperature data from Planck, BAO measurements, CMB lensing data from Planck and the South Pole Telescope, and weak galaxy lensing data from CFHTLenS. We find non-trivial exclusions on the range of parameters, although the data remains compatible with w=-1. We gauge how future experiments will help to constrain the parameters. This is done via a likelihood analysis for CMB experiments such as CoRE and PRISM, and tomographic galaxy weak lensing surveys, focussing in on the potential discriminatory power of Euclid on mildly non-linear scales.

A New Continuous-Time Equality-Constrained Optimization to Avoid Singularity.

Science.gov (United States)

Quan, Quan; Cai, Kai-Yuan

2016-02-01

In equality-constrained optimization, a standard regularity assumption is often associated with feasible point methods, namely, that the gradients of constraints are linearly independent. In practice, the regularity assumption may be violated. In order to avoid such a singularity, a new projection matrix is proposed based on which a feasible point method to continuous-time, equality-constrained optimization is developed. First, the equality constraint is transformed into a continuous-time dynamical system with solutions that always satisfy the equality constraint. Second, a new projection matrix without singularity is proposed to realize the transformation. An update (or say a controller) is subsequently designed to decrease the objective function along the solutions of the transformed continuous-time dynamical system. The invariance principle is then applied to analyze the behavior of the solution. Furthermore, the proposed method is modified to address cases in which solutions do not satisfy the equality constraint. Finally, the proposed optimization approach is applied to three examples to demonstrate its effectiveness.

Solving portfolio selection problems with minimum transaction lots based on conditional-value-at-risk

Science.gov (United States)

Setiawan, E. P.; Rosadi, D.

2017-01-01

Portfolio selection problems conventionally means ‘minimizing the risk, given the certain level of returns’ from some financial assets. This problem is frequently solved with quadratic or linear programming methods, depending on the risk measure that used in the objective function. However, the solutions obtained by these method are in real numbers, which may give some problem in real application because each asset usually has its minimum transaction lots. In the classical approach considering minimum transaction lots were developed based on linear Mean Absolute Deviation (MAD), variance (like Markowitz’s model), and semi-variance as risk measure. In this paper we investigated the portfolio selection methods with minimum transaction lots with conditional value at risk (CVaR) as risk measure. The mean-CVaR methodology only involves the part of the tail of the distribution that contributed to high losses. This approach looks better when we work with non-symmetric return probability distribution. Solution of this method can be found with Genetic Algorithm (GA) methods. We provide real examples using stocks from Indonesia stocks market.

Chance Constrained Input Relaxation to Congestion in Stochastic DEA. An Application to Iranian Hospitals.

Science.gov (United States)

Kheirollahi, Hooshang; Matin, Behzad Karami; Mahboubi, Mohammad; Alavijeh, Mehdi Mirzaei

2015-01-01

This article developed an approached model of congestion, based on relaxed combination of inputs, in stochastic data envelopment analysis (SDEA) with chance constrained programming approaches. Classic data envelopment analysis models with deterministic data have been used by many authors to identify congestion and estimate its levels; however, data envelopment analysis with stochastic data were rarely used to identify congestion. This article used chance constrained programming approaches to replace stochastic models with "deterministic equivalents". This substitution leads us to non-linear problems that should be solved. Finally, the proposed method based on relaxed combination of inputs was used to identify congestion input in six Iranian hospital with one input and two outputs in the period of 2009 to 2012.

Constraining omega and bias from the Stromlo-APM survey

International Nuclear Information System (INIS)

Loveday, J.

1995-05-01

Galaxy redshift surveys provide a distorted picture of the universe due to the non-Hubble component of galaxy motions. By measuring such distortions in the linear regime one can constrain the quantity β = Ω 0.6 where Ω is the cosmological density parameter and b is the (linear) bias factor for optically-selected galaxies. In this paper we estimate β from the Stromlo-APM redshift survey by comparing the amplitude of the direction-averaged redshift space correlation function to the real space correlation function. We find a 95% confidence upper limit of β = 0.75, with a 'best estimate' of β ∼ 0.48. A bias parameter b ∼ 2 is thus required if Ω ≡ 1. However, higher-order correlations measured from the APM galaxy survey indicate a low value for the bias parameter b ∼ 1, requiring that Q approx-lt 0.6

The influence of gender and bruxism on human minimum interdental threshold ability

Directory of Open Access Journals (Sweden)

Patrícia dos Santos Calderon

2009-06-01

Full Text Available OBJECTIVE: To evaluate the influence of gender and bruxism on the ability to discriminate minimum interdental threshold. MATERIAL AND METHODS: One hundred and fifteen individuals, representing both genders, bruxers and non-bruxers, with a mean age of 23.64 years, were selected for this study. For group allocation, every individual was subjected to a specific physical examination to detect bruxism (performed by three different examiners. Evaluation of the ability to discriminate minimum interdental threshold was performed using industrialized 0.010 mm-, 0.024 mm-, 0.030 mm-, 0.050 mm-, 0.080 mm- and 0.094 mm-thick aluminum foils that were placed between upper and lower premolars. Data were analyzed statistically by multiple linear regression analysis at 5% significance level. RESULTS: Neither gender nor bruxism influenced the ability to discriminate minimum interdental threshold (p>0.05. CONCLUSIONS: Gender and the presence of bruxism do not play a role in the minimum interdental threshold.

Stability of the minimum of a SO(N)-invariant Higgs potential with reducible Higgs fields

International Nuclear Information System (INIS)

Thornburg, R.J.

1986-01-01

The present work takes up the problem of finding the absolute minimum of a SO(N)-invariant Higgs potential for the reducible representation of Higgs fields consisting of the antisymmetric (A) and symmetric (S) traceless second-rank tensors. The stability of the minimum under changes on the potential's parameters is also investigated. Potentials containing S alone, both A and S coupled by a positive semi-definite term are minimized. Eigenstates of the Higgs mass matrix are calculated and related to the behavior of the SO(N)-action. Previous results relying on the absence of pseudo-Goldstone models and a new application of the geometry of the action show that the minimum is stable under small changes of the parameters. It is thus stable in an open region of the full eleven-dimensional parameter space of the most general potential of its kind. The isotropy group of the minimum is found to be either SO(N-p) x SO(p-2) x SO(2) or U({N-p}/2) x U(p/2), and the relative magnitudes of the vacuum expectation values of A and S are not constrained. For SO(10), U(3) x U(2) contains the standard model. One-loop Renormalization Group β-functions are calculated for all parameters of the model

Decentralized Pricing in Minimum Cost Spanning Trees

DEFF Research Database (Denmark)

Hougaard, Jens Leth; Moulin, Hervé; Østerdal, Lars Peter

In the minimum cost spanning tree model we consider decentralized pricing rules, i.e. rules that cover at least the ecient cost while the price charged to each user only depends upon his own connection costs. We de ne a canonical pricing rule and provide two axiomatic characterizations. First......, the canonical pricing rule is the smallest among those that improve upon the Stand Alone bound, and are either superadditive or piece-wise linear in connection costs. Our second, direct characterization relies on two simple properties highlighting the special role of the source cost....

EEG source reconstruction reveals frontal-parietal dynamics of spatial conflict processing

NARCIS (Netherlands)

Cohen, M.X.; Ridderinkhof, K.R.

2013-01-01

Cognitive control requires the suppression of distracting information in order to focus on task-relevant information. We applied EEG source reconstruction via time-frequency linear constrained minimum variance beamforming to help elucidate the neural mechanisms involved in spatial conflict

A constrained Delaunay discretization method for adaptively meshing highly discontinuous geological media

Science.gov (United States)

Wang, Yang; Ma, Guowei; Ren, Feng; Li, Tuo

2017-12-01

A constrained Delaunay discretization method is developed to generate high-quality doubly adaptive meshes of highly discontinuous geological media. Complex features such as three-dimensional discrete fracture networks (DFNs), tunnels, shafts, slopes, boreholes, water curtains, and drainage systems are taken into account in the mesh generation. The constrained Delaunay triangulation method is used to create adaptive triangular elements on planar fractures. Persson's algorithm (Persson, 2005), based on an analogy between triangular elements and spring networks, is enriched to automatically discretize a planar fracture into mesh points with varying density and smooth-quality gradient. The triangulated planar fractures are treated as planar straight-line graphs (PSLGs) to construct piecewise-linear complex (PLC) for constrained Delaunay tetrahedralization. This guarantees the doubly adaptive characteristic of the resulted mesh: the mesh is adaptive not only along fractures but also in space. The quality of elements is compared with the results from an existing method. It is verified that the present method can generate smoother elements and a better distribution of element aspect ratios. Two numerical simulations are implemented to demonstrate that the present method can be applied to various simulations of complex geological media that contain a large number of discontinuities.

Optimization of a constrained linear monochromator design for neutral atom beams.

Science.gov (United States)

Kaltenbacher, Thomas

2016-04-01

A focused ground state, neutral atom beam, exploiting its de Broglie wavelength by means of atom optics, is used for neutral atom microscopy imaging. Employing Fresnel zone plates as a lens for these beams is a well established microscopy technique. To date, even for favorable beam source conditions a minimal focus spot size of slightly below 1μm was reached. This limitation is essentially given by the intrinsic spectral purity of the beam in combination with the chromatic aberration of the diffraction based zone plate. Therefore, it is important to enhance the monochromaticity of the beam, enabling a higher spatial resolution, preferably below 100nm. We propose to increase the monochromaticity of a neutral atom beam by means of a so-called linear monochromator set-up - a Fresnel zone plate in combination with a pinhole aperture - in order to gain more than one order of magnitude in spatial resolution. This configuration is known in X-ray microscopy and has proven to be useful, but has not been applied to neutral atom beams. The main result of this work is optimal design parameters based on models for this linear monochromator set-up followed by a second zone plate for focusing. The optimization was performed for minimizing the focal spot size and maximizing the centre line intensity at the detector position for an atom beam simultaneously. The results presented in this work are for, but not limited to, a neutral helium atom beam. Copyright © 2016 Elsevier B.V. All rights reserved.

Structure-constrained sparse canonical correlation analysis with an application to microbiome data analysis.

Science.gov (United States)

Chen, Jun; Bushman, Frederic D; Lewis, James D; Wu, Gary D; Li, Hongzhe

2013-04-01

Motivated by studying the association between nutrient intake and human gut microbiome composition, we developed a method for structure-constrained sparse canonical correlation analysis (ssCCA) in a high-dimensional setting. ssCCA takes into account the phylogenetic relationships among bacteria, which provides important prior knowledge on evolutionary relationships among bacterial taxa. Our ssCCA formulation utilizes a phylogenetic structure-constrained penalty function to impose certain smoothness on the linear coefficients according to the phylogenetic relationships among the taxa. An efficient coordinate descent algorithm is developed for optimization. A human gut microbiome data set is used to illustrate this method. Both simulations and real data applications show that ssCCA performs better than the standard sparse CCA in identifying meaningful variables when there are structures in the data.

Constrained evolution in numerical relativity

Science.gov (United States)

Anderson, Matthew William

The strongest potential source of gravitational radiation for current and future detectors is the merger of binary black holes. Full numerical simulation of such mergers can provide realistic signal predictions and enhance the probability of detection. Numerical simulation of the Einstein equations, however, is fraught with difficulty. Stability even in static test cases of single black holes has proven elusive. Common to unstable simulations is the growth of constraint violations. This work examines the effect of controlling the growth of constraint violations by solving the constraints periodically during a simulation, an approach called constrained evolution. The effects of constrained evolution are contrasted with the results of unconstrained evolution, evolution where the constraints are not solved during the course of a simulation. Two different formulations of the Einstein equations are examined: the standard ADM formulation and the generalized Frittelli-Reula formulation. In most cases constrained evolution vastly improves the stability of a simulation at minimal computational cost when compared with unconstrained evolution. However, in the more demanding test cases examined, constrained evolution fails to produce simulations with long-term stability in spite of producing improvements in simulation lifetime when compared with unconstrained evolution. Constrained evolution is also examined in conjunction with a wide variety of promising numerical techniques, including mesh refinement and overlapping Cartesian and spherical computational grids. Constrained evolution in boosted black hole spacetimes is investigated using overlapping grids. Constrained evolution proves to be central to the host of innovations required in carrying out such intensive simulations.

Fitting and forecasting coupled dark energy in the non-linear regime

Energy Technology Data Exchange (ETDEWEB)

Casas, Santiago; Amendola, Luca; Pettorino, Valeria; Vollmer, Adrian [Institut für Theoretische Physik, Ruprecht-Karls-Universität Heidelberg, Philosophenweg 16, Heidelberg, 69120 Germany (Germany); Baldi, Marco, E-mail: casas@thphys.uni-heidelberg.de, E-mail: l.amendola@thphys.uni-heidelberg.de, E-mail: mail@marcobaldi.it, E-mail: v.pettorino@thphys.uni-heidelberg.de, E-mail: vollmer@thphys.uni-heidelberg.de [Dipartimento di Fisica e Astronomia, Alma Mater Studiorum Università di Bologna, viale Berti Pichat, 6/2, Bologna, I-40127 Italy (Italy)

2016-01-01

We consider cosmological models in which dark matter feels a fifth force mediated by the dark energy scalar field, also known as coupled dark energy. Our interest resides in estimating forecasts for future surveys like Euclid when we take into account non-linear effects, relying on new fitting functions that reproduce the non-linear matter power spectrum obtained from N-body simulations. We obtain fitting functions for models in which the dark matter-dark energy coupling is constant. Their validity is demonstrated for all available simulations in the redshift range 0z=–1.6 and wave modes below 0k=1 h/Mpc. These fitting formulas can be used to test the predictions of the model in the non-linear regime without the need for additional computing-intensive N-body simulations. We then use these fitting functions to perform forecasts on the constraining power that future galaxy-redshift surveys like Euclid will have on the coupling parameter, using the Fisher matrix method for galaxy clustering (GC) and weak lensing (WL). We find that by using information in the non-linear power spectrum, and combining the GC and WL probes, we can constrain the dark matter-dark energy coupling constant squared, β{sup 2}, with precision smaller than 4% and all other cosmological parameters better than 1%, which is a considerable improvement of more than an order of magnitude compared to corresponding linear power spectrum forecasts with the same survey specifications.

Fitting and forecasting coupled dark energy in the non-linear regime

International Nuclear Information System (INIS)

Casas, Santiago; Amendola, Luca; Pettorino, Valeria; Vollmer, Adrian; Baldi, Marco

2016-01-01

We consider cosmological models in which dark matter feels a fifth force mediated by the dark energy scalar field, also known as coupled dark energy. Our interest resides in estimating forecasts for future surveys like Euclid when we take into account non-linear effects, relying on new fitting functions that reproduce the non-linear matter power spectrum obtained from N-body simulations. We obtain fitting functions for models in which the dark matter-dark energy coupling is constant. Their validity is demonstrated for all available simulations in the redshift range 0z=–1.6 and wave modes below 0k=1 h/Mpc. These fitting formulas can be used to test the predictions of the model in the non-linear regime without the need for additional computing-intensive N-body simulations. We then use these fitting functions to perform forecasts on the constraining power that future galaxy-redshift surveys like Euclid will have on the coupling parameter, using the Fisher matrix method for galaxy clustering (GC) and weak lensing (WL). We find that by using information in the non-linear power spectrum, and combining the GC and WL probes, we can constrain the dark matter-dark energy coupling constant squared, β 2 , with precision smaller than 4% and all other cosmological parameters better than 1%, which is a considerable improvement of more than an order of magnitude compared to corresponding linear power spectrum forecasts with the same survey specifications

Lowest-order constrained variational method for simple many-fermion systems

International Nuclear Information System (INIS)

Alexandrov, I.; Moszkowski, S.A.; Wong, C.W.

1975-01-01

The authors study the potential energy of many-fermion systems calculated by the lowest-order constrained variational (LOCV) method of Pandharipande. Two simple two-body interactions are used. For a simple hard-core potential in a dilute Fermi gas, they find that the Huang-Yang exclusion correction can be used to determine a healing distance. The result is close to the older Pandharipande prescription for the healing distance. For a hard core plus attractive exponential potential, the LOCV result agrees closely with the lowest-order separation method of Moszkowski and Scott. They find that the LOCV result has a shallow minimum as a function of the healing distance at the Moszkowski-Scott separation distance. The significance of the absence of a Brueckner dispersion correction in the LOCV result is discussed. (Auth.)

Numerical Methods for Solution of the Extended Linear Quadratic Control Problem

DEFF Research Database (Denmark)

Jørgensen, John Bagterp; Frison, Gianluca; Gade-Nielsen, Nicolai Fog

2012-01-01

In this paper we present the extended linear quadratic control problem, its efficient solution, and a discussion of how it arises in the numerical solution of nonlinear model predictive control problems. The extended linear quadratic control problem is the optimal control problem corresponding...... to the Karush-Kuhn-Tucker system that constitute the majority of computational work in constrained nonlinear and linear model predictive control problems solved by efficient MPC-tailored interior-point and active-set algorithms. We state various methods of solving the extended linear quadratic control problem...... and discuss instances in which it arises. The methods discussed in the paper have been implemented in efficient C code for both CPUs and GPUs for a number of test examples....

Low-lying excited states by constrained DFT

Science.gov (United States)

Ramos, Pablo; Pavanello, Michele

2018-04-01

Exploiting the machinery of Constrained Density Functional Theory (CDFT), we propose a variational method for calculating low-lying excited states of molecular systems. We dub this method eXcited CDFT (XCDFT). Excited states are obtained by self-consistently constraining a user-defined population of electrons, Nc, in the virtual space of a reference set of occupied orbitals. By imposing this population to be Nc = 1.0, we computed the first excited state of 15 molecules from a test set. Our results show that XCDFT achieves an accuracy in the predicted excitation energy only slightly worse than linear-response time-dependent DFT (TDDFT), but without incurring into problems of variational collapse typical of the more commonly adopted ΔSCF method. In addition, we selected a few challenging processes to test the limits of applicability of XCDFT. We find that in contrast to TDDFT, XCDFT is capable of reproducing energy surfaces featuring conical intersections (azobenzene and H3) with correct topology and correct overall energetics also away from the intersection. Venturing to condensed-phase systems, XCDFT reproduces the TDDFT solvatochromic shift of benzaldehyde when it is embedded by a cluster of water molecules. Thus, we find XCDFT to be a competitive method among single-reference methods for computations of excited states in terms of time to solution, rate of convergence, and accuracy of the result.

Quantization of the Linearized Kepler Problem

OpenAIRE

Guerrero, Julio; Perez, Jose Miguel

2003-01-01

The linearized Kepler problem is considered, as obtained from the Kustaanheimo-Stiefel (K-S)transformation, both for negative and positive energies. The symmetry group for the Kepler problem turns out to be SU(2,2). For negative energies, the Hamiltonian of Kepler problem can be realized as the sum of the energies of four harmonic oscillator with the same frequency, with a certain constrain. For positive energies, it can be realized as the sum of the energies of four repulsive oscillator with...

An Improved Minimum Error Interpolator of CNC for General Curves Based on FPGA

Directory of Open Access Journals (Sweden)

Jiye HUANG

2014-05-01

Full Text Available This paper presents an improved minimum error interpolation algorithm for general curves generation in computer numerical control (CNC. Compared with the conventional interpolation algorithms such as the By-Point Comparison method, the Minimum- Error method and the Digital Differential Analyzer (DDA method, the proposed improved Minimum-Error interpolation algorithm can find a balance between accuracy and efficiency. The new algorithm is applicable for the curves of linear, circular, elliptical and parabolic. The proposed algorithm is realized on a field programmable gate array (FPGA with Verilog HDL language, and simulated by the ModelSim software, and finally verified on a two-axis CNC lathe. The algorithm has the following advantages: firstly, the maximum interpolation error is only half of the minimum step-size; and secondly the computing time is only two clock cycles of the FPGA. Simulations and actual tests have proved that the high accuracy and efficiency of the algorithm, which shows that it is highly suited for real-time applications.

Autonomous Navigation with Constrained Consistency for C-Ranger

Directory of Open Access Journals (Sweden)

Shujing Zhang

2014-06-01

Full Text Available Autonomous underwater vehicles (AUVs have become the most widely used tools for undertaking complex exploration tasks in marine environments. Their synthetic ability to carry out localization autonomously and build an environmental map concurrently, in other words, simultaneous localization and mapping (SLAM, are considered to be pivotal requirements for AUVs to have truly autonomous navigation. However, the consistency problem of the SLAM system has been greatly ignored during the past decades. In this paper, a consistency constrained extended Kalman filter (EKF SLAM algorithm, applying the idea of local consistency, is proposed and applied to the autonomous navigation of the C-Ranger AUV, which is developed as our experimental platform. The concept of local consistency (LC is introduced after an explicit theoretical derivation of the EKF-SLAM system. Then, we present a locally consistency-constrained EKF-SLAM design, LC-EKF, in which the landmark estimates used for linearization are fixed at the beginning of each local time period, rather than evaluated at the latest landmark estimates. Finally, our proposed LC-EKF algorithm is experimentally verified, both in simulations and sea trials. The experimental results show that the LC-EKF performs well with regard to consistency, accuracy and computational efficiency.

An inexact fuzzy-chance-constrained air quality management model.

Science.gov (United States)

Xu, Ye; Huang, Guohe; Qin, Xiaosheng

2010-07-01

Regional air pollution is a major concern for almost every country because it not only directly relates to economic development, but also poses significant threats to environment and public health. In this study, an inexact fuzzy-chance-constrained air quality management model (IFAMM) was developed for regional air quality management under uncertainty. IFAMM was formulated through integrating interval linear programming (ILP) within a fuzzy-chance-constrained programming (FCCP) framework and could deal with uncertainties expressed as not only possibilistic distributions but also discrete intervals in air quality management systems. Moreover, the constraints with fuzzy variables could be satisfied at different confidence levels such that various solutions with different risk and cost considerations could be obtained. The developed model was applied to a hypothetical case of regional air quality management. Six abatement technologies and sulfur dioxide (SO2) emission trading under uncertainty were taken into consideration. The results demonstrated that IFAMM could help decision-makers generate cost-effective air quality management patterns, gain in-depth insights into effects of the uncertainties, and analyze tradeoffs between system economy and reliability. The results also implied that the trading scheme could achieve lower total abatement cost than a nontrading one.

What is the minimum value of the safety factor on the magnetic axis

International Nuclear Information System (INIS)

Bussac, M.N.; Pellat, R.; Edery, D.; Soule, J.L.

This paper is presented in the following way: in chapter 2 the main stability properties in the vicinity of the magnetic axis with respect to the localized modes is recalled. The possibility of decreasing the minimum value of the safety factor q below unity, without violating Mercier's criterion is emphasized. In chapter 3 the ideal internal kink in cylindrical geometry for non-circular cross-sections is studied. The main findings are the small destabilizing effect of an elliptical deformation and the larger stabilizing effect of a triangular deformation. In chapter 4 the previous analysis is completed by toroidal corrections and the complete result for the ideal internal kink for circular magnetic surfaces is given. This mode may be stable in toroidal geometry provided the minimum value of q remains larger than 1/2. In chapter 5 the resistive internal kink and its collisionless high temperature limit is discussed. Toroidal effects and non-linear effects in the non-linear development of the tearing modes are compared

Anesthesiologists' perceptions of minimum acceptable work habits of nurse anesthetists.

Science.gov (United States)

Logvinov, Ilana I; Dexter, Franklin; Hindman, Bradley J; Brull, Sorin J

2017-05-01

Work habits are non-technical skills that are an important part of job performance. Although non-technical skills are usually evaluated on a relative basis (i.e., "grading on a curve"), validity of evaluation on an absolute basis (i.e., "minimum passing score") needs to be determined. Survey and observational study. None. None. The theme of "work habits" was assessed using a modification of Dannefer et al.'s 6-item scale, with scores ranging from 1 (lowest performance) to 5 (highest performance). E-mail invitations were sent to all consultant and fellow anesthesiologists at Mayo Clinic in Florida, Arizona, and Minnesota. Because work habits expectations can be generational, the survey was designed for adjustment based on all invited (responding or non-responding) anesthesiologists' year of graduation from residency. The overall mean±standard deviation of the score for anesthesiologists' minimum expectations of nurse anesthetists' work habits was 3.64±0.66 (N=48). Minimum acceptable scores were correlated with the year of graduation from anesthesia residency (linear regression P=0.004). Adjusting for survey non-response using all N=207 anesthesiologists, the mean of the minimum acceptable work habits adjusted for year of graduation was 3.69 (standard error 0.02). The minimum expectations for nurse anesthetists' work habits were compared with observational data obtained from the University of Iowa. Among 8940 individual nurse anesthetist work habits scores, only 2.6% were habits scores were significantly greater than the Mayo estimate (3.69) for the minimum expectations; all Phabits of nurse anesthetists within departments should not be compared with an appropriate minimum score (i.e., of 3.69). Instead, work habits scores should be analyzed based on relative reporting among anesthetists. Copyright © 2017 Elsevier Inc. All rights reserved.

Relaxation Methods for Strictly Convex Regularizations of Piecewise Linear Programs

International Nuclear Information System (INIS)

Kiwiel, K. C.

1998-01-01

We give an algorithm for minimizing the sum of a strictly convex function and a convex piecewise linear function. It extends several dual coordinate ascent methods for large-scale linearly constrained problems that occur in entropy maximization, quadratic programming, and network flows. In particular, it may solve exact penalty versions of such (possibly inconsistent) problems, and subproblems of bundle methods for nondifferentiable optimization. It is simple, can exploit sparsity, and in certain cases is highly parallelizable. Its global convergence is established in the recent framework of B -functions (generalized Bregman functions)

Splines and polynomial tools for flatness-based constrained motion planning

Science.gov (United States)

Suryawan, Fajar; De Doná, José; Seron, María

2012-08-01

This article addresses the problem of trajectory planning for flat systems with constraints. Flat systems have the useful property that the input and the state can be completely characterised by the so-called flat output. We propose a spline parametrisation for the flat output, the performance output, the states and the inputs. Using this parametrisation the problem of constrained trajectory planning can be cast into a simple quadratic programming problem. An important result is that the B-spline parametrisation used gives exact results for constrained linear continuous-time system. The result is exact in the sense that the constrained signal can be made arbitrarily close to the boundary without having intersampling issues (as one would have in sampled-data systems). Simulation examples are presented, involving the generation of rest-to-rest trajectories. In addition, an experimental result of the method is also presented, where two methods to generate trajectories for a magnetic-levitation (maglev) system in the presence of constraints are compared and each method's performance is discussed. The first method uses the nonlinear model of the plant, which turns out to belong to the class of flat systems. The second method uses a linearised version of the plant model around an operating point. In every case, a continuous-time description is used. The experimental results on a real maglev system reported here show that, in most scenarios, the nonlinear and linearised models produce almost similar, indistinguishable trajectories.

Implementation of neural network based non-linear predictive

DEFF Research Database (Denmark)

Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole

1998-01-01

The paper describes a control method for non-linear systems based on generalized predictive control. Generalized predictive control (GPC) was developed to control linear systems including open loop unstable and non-minimum phase systems, but has also been proposed extended for the control of non......-linear systems. GPC is model-based and in this paper we propose the use of a neural network for the modeling of the system. Based on the neural network model a controller with extended control horizon is developed and the implementation issues are discussed, with particular emphasis on an efficient Quasi......-Newton optimization algorithm. The performance is demonstrated on a pneumatic servo system....

Shape space exploration of constrained meshes

KAUST Repository

Yang, Yongliang; Yang, Yijun; Pottmann, Helmut; Mitra, Niloy J.

2011-01-01

We present a general computational framework to locally characterize any shape space of meshes implicitly prescribed by a collection of non-linear constraints. We computationally access such manifolds, typically of high dimension and co-dimension, through first and second order approximants, namely tangent spaces and quadratically parameterized osculant surfaces. Exploration and navigation of desirable subspaces of the shape space with regard to application specific quality measures are enabled using approximants that are intrinsic to the underlying manifold and directly computable in the parameter space of the osculant surface. We demonstrate our framework on shape spaces of planar quad (PQ) meshes, where each mesh face is constrained to be (nearly) planar, and circular meshes, where each face has a circumcircle. We evaluate our framework for navigation and design exploration on a variety of inputs, while keeping context specific properties such as fairness, proximity to a reference surface, etc. © 2011 ACM.

Shape space exploration of constrained meshes

KAUST Repository

Yang, Yongliang

2011-12-12

We present a general computational framework to locally characterize any shape space of meshes implicitly prescribed by a collection of non-linear constraints. We computationally access such manifolds, typically of high dimension and co-dimension, through first and second order approximants, namely tangent spaces and quadratically parameterized osculant surfaces. Exploration and navigation of desirable subspaces of the shape space with regard to application specific quality measures are enabled using approximants that are intrinsic to the underlying manifold and directly computable in the parameter space of the osculant surface. We demonstrate our framework on shape spaces of planar quad (PQ) meshes, where each mesh face is constrained to be (nearly) planar, and circular meshes, where each face has a circumcircle. We evaluate our framework for navigation and design exploration on a variety of inputs, while keeping context specific properties such as fairness, proximity to a reference surface, etc. © 2011 ACM.

Linear-array photoacoustic imaging using minimum variance-based delay multiply and sum adaptive beamforming algorithm

Science.gov (United States)

Mozaffarzadeh, Moein; Mahloojifar, Ali; Orooji, Mahdi; Kratkiewicz, Karl; Adabi, Saba; Nasiriavanaki, Mohammadreza

2018-02-01

In photoacoustic imaging, delay-and-sum (DAS) beamformer is a common beamforming algorithm having a simple implementation. However, it results in a poor resolution and high sidelobes. To address these challenges, a new algorithm namely delay-multiply-and-sum (DMAS) was introduced having lower sidelobes compared to DAS. To improve the resolution of DMAS, a beamformer is introduced using minimum variance (MV) adaptive beamforming combined with DMAS, so-called minimum variance-based DMAS (MVB-DMAS). It is shown that expanding the DMAS equation results in multiple terms representing a DAS algebra. It is proposed to use the MV adaptive beamformer instead of the existing DAS. MVB-DMAS is evaluated numerically and experimentally. In particular, at the depth of 45 mm MVB-DMAS results in about 31, 18, and 8 dB sidelobes reduction compared to DAS, MV, and DMAS, respectively. The quantitative results of the simulations show that MVB-DMAS leads to improvement in full-width-half-maximum about 96%, 94%, and 45% and signal-to-noise ratio about 89%, 15%, and 35% compared to DAS, DMAS, MV, respectively. In particular, at the depth of 33 mm of the experimental images, MVB-DMAS results in about 20 dB sidelobes reduction in comparison with other beamformers.

Convergence Guaranteed Nonlinear Constraint Model Predictive Control via I/O Linearization

Directory of Open Access Journals (Sweden)

Xiaobing Kong

2013-01-01

Full Text Available Constituting reliable optimal solution is a key issue for the nonlinear constrained model predictive control. Input-output feedback linearization is a popular method in nonlinear control. By using an input-output feedback linearizing controller, the original linear input constraints will change to nonlinear constraints and sometimes the constraints are state dependent. This paper presents an iterative quadratic program (IQP routine on the continuous-time system. To guarantee its convergence, another iterative approach is incorporated. The proposed algorithm can reach a feasible solution over the entire prediction horizon. Simulation results on both a numerical example and the continuous stirred tank reactors (CSTR demonstrate the effectiveness of the proposed method.

Integer Linear Programming for Constrained Multi-Aspect Committee Review Assignment

Science.gov (United States)

Karimzadehgan, Maryam; Zhai, ChengXiang

2011-01-01

Automatic review assignment can significantly improve the productivity of many people such as conference organizers, journal editors and grant administrators. A general setup of the review assignment problem involves assigning a set of reviewers on a committee to a set of documents to be reviewed under the constraint of review quota so that the reviewers assigned to a document can collectively cover multiple topic aspects of the document. No previous work has addressed such a setup of committee review assignments while also considering matching multiple aspects of topics and expertise. In this paper, we tackle the problem of committee review assignment with multi-aspect expertise matching by casting it as an integer linear programming problem. The proposed algorithm can naturally accommodate any probabilistic or deterministic method for modeling multiple aspects to automate committee review assignments. Evaluation using a multi-aspect review assignment test set constructed using ACM SIGIR publications shows that the proposed algorithm is effective and efficient for committee review assignments based on multi-aspect expertise matching. PMID:22711970

A Homogeneous and Self-Dual Interior-Point Linear Programming Algorithm for Economic Model Predictive Control

DEFF Research Database (Denmark)

Sokoler, Leo Emil; Frison, Gianluca; Skajaa, Anders

2015-01-01

We develop an efficient homogeneous and self-dual interior-point method (IPM) for the linear programs arising in economic model predictive control of constrained linear systems with linear objective functions. The algorithm is based on a Riccati iteration procedure, which is adapted to the linear...... system of equations solved in homogeneous and self-dual IPMs. Fast convergence is further achieved using a warm-start strategy. We implement the algorithm in MATLAB and C. Its performance is tested using a conceptual power management case study. Closed loop simulations show that 1) the proposed algorithm...

Improved multi-microphone noise reduction preserving binaural cues

NARCIS (Netherlands)

Koutrouvelis, A.; Hendriks, R.C.; Jensen, J; Heusdens, R.; Dong, Min; Zheng, Thomas Fang

2016-01-01

We propose a new multi-microphone noise reduction technique for binaural cue preservation of the desired source and the interferers. This method is based on the linearly constrained minimum variance (LCMV) framework, where the constraints are used for the binaural cue preservation of the desired

Relaxed Binaural LCMV Beamforming

NARCIS (Netherlands)

Koutrouvelis, A.; Hendriks, R.C.; Heusdens, R.; Jensen, Jesper Rindom

2017-01-01

In this paper, we propose a new binaural beamforming technique, which can be seen as a relaxation of the linearly constrained minimum variance (LCMV) framework. The proposed method can achieve simultaneous noise reduction and exact binaural cue preservation of the target source, similar to the

Input-constrained model predictive control via the alternating direction method of multipliers

DEFF Research Database (Denmark)

Sokoler, Leo Emil; Frison, Gianluca; Andersen, Martin S.

2014-01-01

This paper presents an algorithm, based on the alternating direction method of multipliers, for the convex optimal control problem arising in input-constrained model predictive control. We develop an efficient implementation of the algorithm for the extended linear quadratic control problem (LQCP......) with input and input-rate limits. The algorithm alternates between solving an extended LQCP and a highly structured quadratic program. These quadratic programs are solved using a Riccati iteration procedure, and a structure-exploiting interior-point method, respectively. The computational cost per iteration...... is quadratic in the dimensions of the controlled system, and linear in the length of the prediction horizon. Simulations show that the approach proposed in this paper is more than an order of magnitude faster than several state-of-the-art quadratic programming algorithms, and that the difference in computation...

Hybrid vehicle optimal control : Linear interpolation and singular control

NARCIS (Netherlands)

Delprat, S.; Hofman, T.

2015-01-01

Hybrid vehicle energy management can be formulated as an optimal control problem. Considering that the fuel consumption is often computed using linear interpolation over lookup table data, a rigorous analysis of the necessary conditions provided by the Pontryagin Minimum Principle is conducted. For

A MATLAB Script for Solving 2D/3D Minimum Compliance Problems using Anisotropic Mesh Adaptation

DEFF Research Database (Denmark)

Jensen, Kristian Ejlebjerg

2017-01-01

We present a pure MATLAB implementation for solving 2D/3D compliance minimization problems using the density method. A filtered design variable with a minimum length is computed using a Helmholtz-type differential equation. The optimality criteria is used as optimizer and to avoid local minima we...... apply continuation of an exponent that controls the stiffness associated with intermediate design variables. We constrain the volume from above and use the implementation to show that optimizations with dynamic meshes can save significant amounts of computational time compared to fixed meshes without...

Optimization of a constrained linear monochromator design for neutral atom beams

International Nuclear Information System (INIS)

Kaltenbacher, Thomas

2016-01-01

A focused ground state, neutral atom beam, exploiting its de Broglie wavelength by means of atom optics, is used for neutral atom microscopy imaging. Employing Fresnel zone plates as a lens for these beams is a well established microscopy technique. To date, even for favorable beam source conditions a minimal focus spot size of slightly below 1 μm was reached. This limitation is essentially given by the intrinsic spectral purity of the beam in combination with the chromatic aberration of the diffraction based zone plate. Therefore, it is important to enhance the monochromaticity of the beam, enabling a higher spatial resolution, preferably below 100 nm. We propose to increase the monochromaticity of a neutral atom beam by means of a so-called linear monochromator set-up – a Fresnel zone plate in combination with a pinhole aperture – in order to gain more than one order of magnitude in spatial resolution. This configuration is known in X-ray microscopy and has proven to be useful, but has not been applied to neutral atom beams. The main result of this work is optimal design parameters based on models for this linear monochromator set-up followed by a second zone plate for focusing. The optimization was performed for minimizing the focal spot size and maximizing the centre line intensity at the detector position for an atom beam simultaneously. The results presented in this work are for, but not limited to, a neutral helium atom beam. - Highlights: • The presented results are essential for optimal operation conditions of a neutral atom microscope set-up. • The key parameters for the experimental arrangement of a neutral microscopy set-up are identified and their interplay is quantified. • Insights in the multidimensional problem provide deep and crucial understanding for pushing beyond the apparent focus limitations. • This work points out the trade-offs for high intensity and high spatial resolution indicating several use cases.

Optimization of a constrained linear monochromator design for neutral atom beams

Energy Technology Data Exchange (ETDEWEB)

Kaltenbacher, Thomas

2016-04-15

A focused ground state, neutral atom beam, exploiting its de Broglie wavelength by means of atom optics, is used for neutral atom microscopy imaging. Employing Fresnel zone plates as a lens for these beams is a well established microscopy technique. To date, even for favorable beam source conditions a minimal focus spot size of slightly below 1 μm was reached. This limitation is essentially given by the intrinsic spectral purity of the beam in combination with the chromatic aberration of the diffraction based zone plate. Therefore, it is important to enhance the monochromaticity of the beam, enabling a higher spatial resolution, preferably below 100 nm. We propose to increase the monochromaticity of a neutral atom beam by means of a so-called linear monochromator set-up – a Fresnel zone plate in combination with a pinhole aperture – in order to gain more than one order of magnitude in spatial resolution. This configuration is known in X-ray microscopy and has proven to be useful, but has not been applied to neutral atom beams. The main result of this work is optimal design parameters based on models for this linear monochromator set-up followed by a second zone plate for focusing. The optimization was performed for minimizing the focal spot size and maximizing the centre line intensity at the detector position for an atom beam simultaneously. The results presented in this work are for, but not limited to, a neutral helium atom beam. - Highlights: • The presented results are essential for optimal operation conditions of a neutral atom microscope set-up. • The key parameters for the experimental arrangement of a neutral microscopy set-up are identified and their interplay is quantified. • Insights in the multidimensional problem provide deep and crucial understanding for pushing beyond the apparent focus limitations. • This work points out the trade-offs for high intensity and high spatial resolution indicating several use cases.

Finite-Time H∞ Filtering for Linear Continuous Time-Varying Systems with Uncertain Observations

Directory of Open Access Journals (Sweden)

Huihong Zhao

2012-01-01

Full Text Available This paper is concerned with the finite-time H∞ filtering problem for linear continuous time-varying systems with uncertain observations and ℒ2-norm bounded noise. The design of finite-time H∞ filter is equivalent to the problem that a certain indefinite quadratic form has a minimum and the filter is such that the minimum is positive. The quadratic form is related to a Krein state-space model according to the Krein space linear estimation theory. By using the projection theory in Krein space, the finite-time H∞ filtering problem is solved. A numerical example is given to illustrate the performance of the H∞ filter.

Exploring Constrained Creative Communication

DEFF Research Database (Denmark)

Sørensen, Jannick Kirk

2017-01-01

Creative collaboration via online tools offers a less ‘media rich’ exchange of information between participants than face-to-face collaboration. The participants’ freedom to communicate is restricted in means of communication, and rectified in terms of possibilities offered in the interface. How do...... these constrains influence the creative process and the outcome? In order to isolate the communication problem from the interface- and technology problem, we examine via a design game the creative communication on an open-ended task in a highly constrained setting, a design game. Via an experiment the relation...... between communicative constrains and participants’ perception of dialogue and creativity is examined. Four batches of students preparing for forming semester project groups were conducted and documented. Students were asked to create an unspecified object without any exchange of communication except...

Distribution of the minimum path on percolation clusters: A renormalization group calculation

International Nuclear Information System (INIS)

Hipsh, Lior.

1993-06-01

This thesis uses the renormalization group for the research of the chemical distance or the minimal path on percolation clusters on a 2 dimensional square lattice. Our aims are to calculate analytically (iterative calculation) the fractal dimension of the minimal path. d min. , and the distributions of the minimum paths, l min for different lattice sizes and for different starting densities (including the threshold value p c ). For the distributions. We seek for an analytic form which describes them. The probability to get a minimum path for each linear size L is calculated by iterating the distribution of l min for the basic cell of size 2*2 to the next scale sizes, using the H cell renormalization group. For the threshold value of p and for values near to p c . We confirm a scaling in the form: P(l,L) =f1/l(l/(L d min ). L - the linear size, l - the minimum path. The distribution can be also represented in the Fourier space, so we will try to solve the renormalization group equations in this space. A numerical fitting is produced and compared to existing numerical results. In order to improve the agreement between the renormalization group and the numerical simulations, we also present attempts to generalize the renormalization group by adding more parameters, e.g. correlations between bonds in different directions or finite densities for occupation of bonds and sites. (author) 17 refs

Constraining the Stellar Mass Function in the Galactic Center via Mass Loss from Stellar Collisions

Directory of Open Access Journals (Sweden)

Douglas Rubin

2011-01-01

Full Text Available The dense concentration of stars and high-velocity dispersions in the Galactic center imply that stellar collisions frequently occur. Stellar collisions could therefore result in significant mass loss rates. We calculate the amount of stellar mass lost due to indirect and direct stellar collisions and find its dependence on the present-day mass function of stars. We find that the total mass loss rate in the Galactic center due to stellar collisions is sensitive to the present-day mass function adopted. We use the observed diffuse X-ray luminosity in the Galactic center to preclude any present-day mass functions that result in mass loss rates >10-5M⨀yr−1 in the vicinity of ~1″. For present-day mass functions of the form, dN/dM∝M-α, we constrain the present-day mass function to have a minimum stellar mass ≲7M⨀ and a power-law slope ≳1.25. We also use this result to constrain the initial mass function in the Galactic center by considering different star formation scenarios.

Linear-array photoacoustic imaging using minimum variance-based delay multiply and sum adaptive beamforming algorithm.

Science.gov (United States)

Mozaffarzadeh, Moein; Mahloojifar, Ali; Orooji, Mahdi; Kratkiewicz, Karl; Adabi, Saba; Nasiriavanaki, Mohammadreza

2018-02-01

In photoacoustic imaging, delay-and-sum (DAS) beamformer is a common beamforming algorithm having a simple implementation. However, it results in a poor resolution and high sidelobes. To address these challenges, a new algorithm namely delay-multiply-and-sum (DMAS) was introduced having lower sidelobes compared to DAS. To improve the resolution of DMAS, a beamformer is introduced using minimum variance (MV) adaptive beamforming combined with DMAS, so-called minimum variance-based DMAS (MVB-DMAS). It is shown that expanding the DMAS equation results in multiple terms representing a DAS algebra. It is proposed to use the MV adaptive beamformer instead of the existing DAS. MVB-DMAS is evaluated numerically and experimentally. In particular, at the depth of 45 mm MVB-DMAS results in about 31, 18, and 8 dB sidelobes reduction compared to DAS, MV, and DMAS, respectively. The quantitative results of the simulations show that MVB-DMAS leads to improvement in full-width-half-maximum about 96%, 94%, and 45% and signal-to-noise ratio about 89%, 15%, and 35% compared to DAS, DMAS, MV, respectively. In particular, at the depth of 33 mm of the experimental images, MVB-DMAS results in about 20 dB sidelobes reduction in comparison with other beamformers. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Split diversity in constrained conservation prioritization using integer linear programming.

Science.gov (United States)

Chernomor, Olga; Minh, Bui Quang; Forest, Félix; Klaere, Steffen; Ingram, Travis; Henzinger, Monika; von Haeseler, Arndt

2015-01-01

Phylogenetic diversity (PD) is a measure of biodiversity based on the evolutionary history of species. Here, we discuss several optimization problems related to the use of PD, and the more general measure split diversity (SD), in conservation prioritization.Depending on the conservation goal and the information available about species, one can construct optimization routines that incorporate various conservation constraints. We demonstrate how this information can be used to select sets of species for conservation action. Specifically, we discuss the use of species' geographic distributions, the choice of candidates under economic pressure, and the use of predator-prey interactions between the species in a community to define viability constraints.Despite such optimization problems falling into the area of NP hard problems, it is possible to solve them in a reasonable amount of time using integer programming. We apply integer linear programming to a variety of models for conservation prioritization that incorporate the SD measure.We exemplarily show the results for two data sets: the Cape region of South Africa and a Caribbean coral reef community. Finally, we provide user-friendly software at http://www.cibiv.at/software/pda.

Noise Reduction with Optimal Variable Span Linear Filters

DEFF Research Database (Denmark)

Jensen, Jesper Rindom; Benesty, Jacob; Christensen, Mads Græsbøll

2016-01-01

In this paper, the problem of noise reduction is addressed as a linear filtering problem in a novel way by using concepts from subspace-based enhancement methods, resulting in variable span linear filters. This is done by forming the filter coefficients as linear combinations of a number...... included in forming the filter. Using these concepts, a number of different filter designs are considered, like minimum distortion, Wiener, maximum SNR, and tradeoff filters. Interestingly, all these can be expressed as special cases of variable span filters. We also derive expressions for the speech...... demonstrate the advantages and properties of the variable span filter designs, and their potential performance gain compared to widely used speech enhancement methods....

f (T) Non-linear Massive Gravity and the Cosmic Acceleration

International Nuclear Information System (INIS)

Wu You; Chen Zu-Cheng; Wei Hao; Wang Jia-Xin

2015-01-01

Inspired by the f (R) non-linear massive gravity, we propose a new kind of modified gravity model, namely f (T) non-linear massive gravity, by adding the dRGT mass term reformulated in the vierbein formalism, to the f (T) theory. We then investigate the cosmological evolution of f (T) massive gravity, and constrain it by using the latest observational data. We find that it slightly favors a crossing of the phantom divide line from the quintessence-like phase (w_d_e > −1) to the phantom-like one (w_d_e < −1) as redshift decreases. (paper)

Synchronization of linearly coupled unified chaotic systems based on linear balanced feedback scheme with constraints

International Nuclear Information System (INIS)

Chen, H.-H.; Chen, C.-S.; Lee, C.-I

2009-01-01

This paper investigates the synchronization of unidirectional and bidirectional coupled unified chaotic systems. A balanced coupling coefficient control method is presented for global asymptotic synchronization using the Lyapunov stability theorem and a minimum scheme with no constraints/constraints. By using the result of the above analysis, the balanced coupling coefficients are then designed to achieve the chaos synchronization of linearly coupled unified chaotic systems. The feasibility and effectiveness of the proposed chaos synchronization scheme are verified via numerical simulations.

Maximum Constrained Directivity of Oversteered End-Fire Sensor Arrays

Directory of Open Access Journals (Sweden)

Andrea Trucco

2015-06-01

Full Text Available For linear arrays with fixed steering and an inter-element spacing smaller than one half of the wavelength, end-fire steering of a data-independent beamformer offers better directivity than broadside steering. The introduction of a lower bound on the white noise gain ensures the necessary robustness against random array errors and sensor mismatches. However, the optimum broadside performance can be obtained using a simple processing architecture, whereas the optimum end-fire performance requires a more complicated system (because complex weight coefficients are needed. In this paper, we reconsider the oversteering technique as a possible way to simplify the processing architecture of equally spaced end-fire arrays. We propose a method for computing the amount of oversteering and the related real-valued weight vector that allows the constrained directivity to be maximized for a given inter-element spacing. Moreover, we verify that the maximized oversteering performance is very close to the optimum end-fire performance. We conclude that optimized oversteering is a viable method for designing end-fire arrays that have better constrained directivity than broadside arrays but with a similar implementation complexity. A numerical simulation is used to perform a statistical analysis, which confirms that the maximized oversteering performance is robust against sensor mismatches.

A linear programming approach to characterizing norm bounded uncertainty from experimental data

Science.gov (United States)

Scheid, R. E.; Bayard, D. S.; Yam, Y.

1991-01-01

The linear programming spectral overbounding and factorization (LPSOF) algorithm, an algorithm for finding a minimum phase transfer function of specified order whose magnitude tightly overbounds a specified nonparametric function of frequency, is introduced. This method has direct application to transforming nonparametric uncertainty bounds (available from system identification experiments) into parametric representations required for modern robust control design software (i.e., a minimum-phase transfer function multiplied by a norm-bounded perturbation).

A symmetric Roos bound for linear codes

NARCIS (Netherlands)

Duursma, I.M.; Pellikaan, G.R.

2006-01-01

The van Lint–Wilson AB-method yields a short proof of the Roos bound for the minimum distance of a cyclic code. We use the AB-method to obtain a different bound for the weights of a linear code. In contrast to the Roos bound, the role of the codes A and B in our bound is symmetric. We use the bound

Implementation of neural network based non-linear predictive control

DEFF Research Database (Denmark)

Sørensen, Paul Haase; Nørgård, Peter Magnus; Ravn, Ole

1999-01-01

This paper describes a control method for non-linear systems based on generalized predictive control. Generalized predictive control (GPC) was developed to control linear systems, including open-loop unstable and non-minimum phase systems, but has also been proposed to be extended for the control...... of non-linear systems. GPC is model based and in this paper we propose the use of a neural network for the modeling of the system. Based on the neural network model, a controller with extended control horizon is developed and the implementation issues are discussed, with particular emphasis...... on an efficient quasi-Newton algorithm. The performance is demonstrated on a pneumatic servo system....

Constraining the electric dipole photon strength function in {sup 130}Te

Energy Technology Data Exchange (ETDEWEB)

Isaak, J.; Loeher, B.; Savran, D.; Silva, J. [ExtreMe Matter Institute EMMI and Research Division, Darmstadt (Germany); FIAS, Frankfurt (Germany); Ahmed, M.W.; Kelley, J.H.; Tornow, W.; Weller, H.R. [Department of Physics, Duke University, TUNL (United States); Beller, J.; Pietralla, N.; Romig, C.; Zweidinger, M. [Institut fuer Kernphysik, TU Darmstadt (Germany); Glorius, J.; Sonnabend, K. [Institut fuer Angewandte Physik, Goethe-Universitaet Frankfurt (Germany); Krticka, M. [Faculty of Mathematics and Physics, Charles University, Prague (Czech Republic); Rusev, G. [Chemistry Division, LANL (United States); Scheck, M. [School of Engineering, University of the West of Scotland (United Kingdom); Tonchev, A.P. [Physics Division, LLNL (United States)

2014-07-01

The decay properties of photo-excited states in {sup 130}Te have been investigated by means of Nuclear Resonance Fluorescence experiments at the Darmstadt High Intensity Photon Setup (DHIPS) and the High Intensity γ-ray Source (HIγS). The combination of continuous-energy bremsstrahlung on the one hand and the quasi-monoenergetic and linearly polarized photon beam on the other enables a detailed insight into the photoabsorption cross section and the decay behavior of spin-1 states. Comparing these results to simulations within the statistical model allow for constraining the electric dipole photon strength function (E1-PSF). Results are presented and discussed.

Feature and Pose Constrained Visual Aided Inertial Navigation for Computationally Constrained Aerial Vehicles

Science.gov (United States)

Williams, Brian; Hudson, Nicolas; Tweddle, Brent; Brockers, Roland; Matthies, Larry

2011-01-01

A Feature and Pose Constrained Extended Kalman Filter (FPC-EKF) is developed for highly dynamic computationally constrained micro aerial vehicles. Vehicle localization is achieved using only a low performance inertial measurement unit and a single camera. The FPC-EKF framework augments the vehicle's state with both previous vehicle poses and critical environmental features, including vertical edges. This filter framework efficiently incorporates measurements from hundreds of opportunistic visual features to constrain the motion estimate, while allowing navigating and sustained tracking with respect to a few persistent features. In addition, vertical features in the environment are opportunistically used to provide global attitude references. Accurate pose estimation is demonstrated on a sequence including fast traversing, where visual features enter and exit the field-of-view quickly, as well as hover and ingress maneuvers where drift free navigation is achieved with respect to the environment.

Stress-constrained truss topology optimization problems that can be solved by linear programming

DEFF Research Database (Denmark)

Stolpe, Mathias; Svanberg, Krister

2004-01-01

We consider the problem of simultaneously selecting the material and determining the area of each bar in a truss structure in such a way that the cost of the structure is minimized subject to stress constraints under a single load condition. We show that such problems can be solved by linear...... programming to give the global optimum, and that two different materials are always sufficient in an optimal structure....

Minimum triplet covers of binary phylogenetic X-trees.

Science.gov (United States)

Huber, K T; Moulton, V; Steel, M

2017-12-01

Trees with labelled leaves and with all other vertices of degree three play an important role in systematic biology and other areas of classification. A classical combinatorial result ensures that such trees can be uniquely reconstructed from the distances between the leaves (when the edges are given any strictly positive lengths). Moreover, a linear number of these pairwise distance values suffices to determine both the tree and its edge lengths. A natural set of pairs of leaves is provided by any 'triplet cover' of the tree (based on the fact that each non-leaf vertex is the median vertex of three leaves). In this paper we describe a number of new results concerning triplet covers of minimum size. In particular, we characterize such covers in terms of an associated graph being a 2-tree. Also, we show that minimum triplet covers are 'shellable' and thereby provide a set of pairs for which the inter-leaf distance values will uniquely determine the underlying tree and its associated branch lengths.

Choosing health, constrained choices.

Science.gov (United States)

Chee Khoon Chan

2009-12-01

In parallel with the neo-liberal retrenchment of the welfarist state, an increasing emphasis on the responsibility of individuals in managing their own affairs and their well-being has been evident. In the health arena for instance, this was a major theme permeating the UK government's White Paper Choosing Health: Making Healthy Choices Easier (2004), which appealed to an ethos of autonomy and self-actualization through activity and consumption which merited esteem. As a counterpoint to this growing trend of informed responsibilization, constrained choices (constrained agency) provides a useful framework for a judicious balance and sense of proportion between an individual behavioural focus and a focus on societal, systemic, and structural determinants of health and well-being. Constrained choices is also a conceptual bridge between responsibilization and population health which could be further developed within an integrative biosocial perspective one might refer to as the social ecology of health and disease.

A Mixed Integer Linear Programming Approach to Electrical Stimulation Optimization Problems.

Science.gov (United States)

Abouelseoud, Gehan; Abouelseoud, Yasmine; Shoukry, Amin; Ismail, Nour; Mekky, Jaidaa

2018-02-01

Electrical stimulation optimization is a challenging problem. Even when a single region is targeted for excitation, the problem remains a constrained multi-objective optimization problem. The constrained nature of the problem results from safety concerns while its multi-objectives originate from the requirement that non-targeted regions should remain unaffected. In this paper, we propose a mixed integer linear programming formulation that can successfully address the challenges facing this problem. Moreover, the proposed framework can conclusively check the feasibility of the stimulation goals. This helps researchers to avoid wasting time trying to achieve goals that are impossible under a chosen stimulation setup. The superiority of the proposed framework over alternative methods is demonstrated through simulation examples.

Iterated non-linear model predictive control based on tubes and contractive constraints.

Science.gov (United States)

Murillo, M; Sánchez, G; Giovanini, L

2016-05-01

This paper presents a predictive control algorithm for non-linear systems based on successive linearizations of the non-linear dynamic around a given trajectory. A linear time varying model is obtained and the non-convex constrained optimization problem is transformed into a sequence of locally convex ones. The robustness of the proposed algorithm is addressed adding a convex contractive constraint. To account for linearization errors and to obtain more accurate results an inner iteration loop is added to the algorithm. A simple methodology to obtain an outer bounding-tube for state trajectories is also presented. The convergence of the iterative process and the stability of the closed-loop system are analyzed. The simulation results show the effectiveness of the proposed algorithm in controlling a quadcopter type unmanned aerial vehicle. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

Constraining neutrinoless double beta decay

International Nuclear Information System (INIS)

Dorame, L.; Meloni, D.; Morisi, S.; Peinado, E.; Valle, J.W.F.

2012-01-01

A class of discrete flavor-symmetry-based models predicts constrained neutrino mass matrix schemes that lead to specific neutrino mass sum-rules (MSR). We show how these theories may constrain the absolute scale of neutrino mass, leading in most of the cases to a lower bound on the neutrinoless double beta decay effective amplitude.

Decoding and finding the minimum distance with Gröbner bases : history and new insights

NARCIS (Netherlands)

Bulygin, S.; Pellikaan, G.R.; Woungang, I.; Misra, S.; Misra, S.C.

2010-01-01

In this chapter, we discuss decoding techniques and finding the minimum distance of linear codes with the use of Grobner bases. First, we give a historical overview of decoding cyclic codes via solving systems polynominal equations over finite fields. In particular, we mention papers of Cooper,.

Do Minimum Wages Fight Poverty?

OpenAIRE

David Neumark; William Wascher

1997-01-01

The primary goal of a national minimum wage floor is to raise the incomes of poor or near-poor families with members in the work force. However, estimates of employment effects of minimum wages tell us little about whether minimum wages are can achieve this goal; even if the disemployment effects of minimum wages are modest, minimum wage increases could result in net income losses for poor families. We present evidence on the effects of minimum wages on family incomes from matched March CPS s...

Particle swarm optimization - Genetic algorithm (PSOGA) on linear transportation problem

Science.gov (United States)

Rahmalia, Dinita

2017-08-01

Linear Transportation Problem (LTP) is the case of constrained optimization where we want to minimize cost subject to the balance of the number of supply and the number of demand. The exact method such as northwest corner, vogel, russel, minimal cost have been applied at approaching optimal solution. In this paper, we use heurisitic like Particle Swarm Optimization (PSO) for solving linear transportation problem at any size of decision variable. In addition, we combine mutation operator of Genetic Algorithm (GA) at PSO to improve optimal solution. This method is called Particle Swarm Optimization - Genetic Algorithm (PSOGA). The simulations show that PSOGA can improve optimal solution resulted by PSO.

Nested Sampling with Constrained Hamiltonian Monte Carlo

OpenAIRE

Betancourt, M. J.

2010-01-01

Nested sampling is a powerful approach to Bayesian inference ultimately limited by the computationally demanding task of sampling from a heavily constrained probability distribution. An effective algorithm in its own right, Hamiltonian Monte Carlo is readily adapted to efficiently sample from any smooth, constrained distribution. Utilizing this constrained Hamiltonian Monte Carlo, I introduce a general implementation of the nested sampling algorithm.

SU-F-T-78: Minimum Data Set of Measurements for TG 71 Based Electron Monitor-Unit Calculations

International Nuclear Information System (INIS)

Xu, H; Guerrero, M; Prado, K; Yi, B

2016-01-01

Purpose: Building up a TG-71 based electron monitor-unit (MU) calculation protocol usually involves massive measurements. This work investigates a minimum data set of measurements and its calculation accuracy and measurement time. Methods: For 6, 9, 12, 16, and 20 MeV of our Varian Clinac-Series linear accelerators, the complete measurements were performed at different depth using 5 square applicators (6, 10, 15, 20 and 25 cm) with different cutouts (2, 3, 4, 6, 10, 15 and 20 cm up to applicator size) for 5 different SSD’s. For each energy, there were 8 PDD scans and 150 point measurements for applicator factors, cutout factors and effective SSDs that were then converted to air-gap factors for SSD 99–110cm. The dependence of each dosimetric quantity on field size and SSD was examined to determine the minimum data set of measurements as a subset of the complete measurements. The “missing” data excluded in the minimum data set were approximated by linear or polynomial fitting functions based on the included data. The total measurement time and the calculated electron MU using the minimum and the complete data sets were compared. Results: The minimum data set includes 4 or 5 PDD’s and 51 to 66 point measurements for each electron energy, and more PDD’s and fewer point measurements are generally needed as energy increases. Using only <50% of complete measurement time, the minimum data set generates acceptable MU calculation results compared to those with the complete data set. The PDD difference is within 1 mm and the calculated MU difference is less than 1.5%. Conclusion: Data set measurement for TG-71 electron MU calculations can be minimized based on the knowledge of how each dosimetric quantity depends on various setup parameters. The suggested minimum data set allows acceptable MU calculation accuracy and shortens measurement time by a few hours.

SU-F-T-78: Minimum Data Set of Measurements for TG 71 Based Electron Monitor-Unit Calculations

Energy Technology Data Exchange (ETDEWEB)

Xu, H; Guerrero, M; Prado, K; Yi, B [University of Maryland School of Medicine, Baltimore, MD (United States)

2016-06-15

Purpose: Building up a TG-71 based electron monitor-unit (MU) calculation protocol usually involves massive measurements. This work investigates a minimum data set of measurements and its calculation accuracy and measurement time. Methods: For 6, 9, 12, 16, and 20 MeV of our Varian Clinac-Series linear accelerators, the complete measurements were performed at different depth using 5 square applicators (6, 10, 15, 20 and 25 cm) with different cutouts (2, 3, 4, 6, 10, 15 and 20 cm up to applicator size) for 5 different SSD’s. For each energy, there were 8 PDD scans and 150 point measurements for applicator factors, cutout factors and effective SSDs that were then converted to air-gap factors for SSD 99–110cm. The dependence of each dosimetric quantity on field size and SSD was examined to determine the minimum data set of measurements as a subset of the complete measurements. The “missing” data excluded in the minimum data set were approximated by linear or polynomial fitting functions based on the included data. The total measurement time and the calculated electron MU using the minimum and the complete data sets were compared. Results: The minimum data set includes 4 or 5 PDD’s and 51 to 66 point measurements for each electron energy, and more PDD’s and fewer point measurements are generally needed as energy increases. Using only <50% of complete measurement time, the minimum data set generates acceptable MU calculation results compared to those with the complete data set. The PDD difference is within 1 mm and the calculated MU difference is less than 1.5%. Conclusion: Data set measurement for TG-71 electron MU calculations can be minimized based on the knowledge of how each dosimetric quantity depends on various setup parameters. The suggested minimum data set allows acceptable MU calculation accuracy and shortens measurement time by a few hours.

Clustering Using Boosted Constrained k-Means Algorithm

Directory of Open Access Journals (Sweden)

Masayuki Okabe

2018-03-01

Full Text Available This article proposes a constrained clustering algorithm with competitive performance and less computation time to the state-of-the-art methods, which consists of a constrained k-means algorithm enhanced by the boosting principle. Constrained k-means clustering using constraints as background knowledge, although easy to implement and quick, has insufficient performance compared with metric learning-based methods. Since it simply adds a function into the data assignment process of the k-means algorithm to check for constraint violations, it often exploits only a small number of constraints. Metric learning-based methods, which exploit constraints to create a new metric for data similarity, have shown promising results although the methods proposed so far are often slow depending on the amount of data or number of feature dimensions. We present a method that exploits the advantages of the constrained k-means and metric learning approaches. It incorporates a mechanism for accepting constraint priorities and a metric learning framework based on the boosting principle into a constrained k-means algorithm. In the framework, a metric is learned in the form of a kernel matrix that integrates weak cluster hypotheses produced by the constrained k-means algorithm, which works as a weak learner under the boosting principle. Experimental results for 12 data sets from 3 data sources demonstrated that our method has performance competitive to those of state-of-the-art constrained clustering methods for most data sets and that it takes much less computation time. Experimental evaluation demonstrated the effectiveness of controlling the constraint priorities by using the boosting principle and that our constrained k-means algorithm functions correctly as a weak learner of boosting.

Transmission-constrained oligopoly in the Japanese electricity market

International Nuclear Information System (INIS)

Tanaka, Makoto

2009-01-01

We simulate the Japanese wholesale electricity market as a transmission-constrained Cournot market using a linear complementarity approach. First, we investigate the effects of upgrading the bottleneck transmission line between the eastern and western regions, focusing on the mitigation of transmission congestion. Although increasing the bottleneck capacity would lead to welfare gains, they might not be substantial particularly when transmission capacity costs are taken into account. Second, we examine the effects of splitting the largest electric power company, which is located in the eastern region, focusing on the mitigation of market power. Splitting the largest company into two companies would lead to a 25% reduction in the eastern price, and a 50% reduction in deadweight loss. The divestiture of the largest company would have a significant effect of mitigating market power in the Japanese electricity market. (author)

Assessment of oscillatory stability constrained available transfer capability

International Nuclear Information System (INIS)

Jain, T.; Singh, S.N.; Srivastava, S.C.

2009-01-01

This paper utilizes a bifurcation approach to compute oscillatory stability constrained available transfer capability (ATC) in an electricity market having bilateral as well as multilateral transactions. Oscillatory instability in non-linear systems can be related to Hopf bifurcation. At the Hopf bifurcation, one pair of the critical eigenvalues of the system Jacobian reaches imaginary axis. A new optimization formulation, including Hopf bifurcation conditions, has been developed in this paper to obtain the dynamic ATC. An oscillatory stability based contingency screening index, which takes into account the impact of transactions on severity of contingency, has been utilized to identify critical contingencies to be considered in determining ATC. The proposed method has been applied for dynamic ATC determination on a 39-bus New England system and a practical 75-bus Indian system considering composite static load as well as dynamic load models. (author)

Constrained dynamics of universally coupled massive spin 2-spin 0 gravities

International Nuclear Information System (INIS)

Pitts, J Brian

2006-01-01

The 2-parameter family of massive variants of Einsteins gravity (on a Minkowski background) found by Ogievetsky and Polubarinov by excluding lower spins can also be derived using universal coupling. A Dirac-Bergmann constrained dynamics analysis seems not to have been presented for these theories, the Freund-Maheshwari-Schonberg special case, or any other massive gravity beyond the linear level treated by Marzban, Whiting and van Dam. Here the Dirac-Bergmann apparatus is applied to these theories. A few remarks are made on the question of positive energy. Being bimetric, massive gravities have a causality puzzle, but it appears soluble by the introduction and judicious use of gauge freedom

How CMB and large-scale structure constrain chameleon interacting dark energy

International Nuclear Information System (INIS)

Boriero, Daniel; Das, Subinoy; Wong, Yvonne Y.Y.

2015-01-01

We explore a chameleon type of interacting dark matter-dark energy scenario in which a scalar field adiabatically traces the minimum of an effective potential sourced by the dark matter density. We discuss extensively the effect of this coupling on cosmological observables, especially the parameter degeneracies expected to arise between the model parameters and other cosmological parameters, and then test the model against observations of the cosmic microwave background (CMB) anisotropies and other cosmological probes. We find that the chameleon parameters α and β, which determine respectively the slope of the scalar field potential and the dark matter-dark energy coupling strength, can be constrained to α < 0.17 and β < 0.19 using CMB data and measurements of baryon acoustic oscillations. The latter parameter in particular is constrained only by the late Integrated Sachs-Wolfe effect. Adding measurements of the local Hubble expansion rate H 0 tightens the bound on α by a factor of two, although this apparent improvement is arguably an artefact of the tension between the local measurement and the H 0 value inferred from Planck data in the minimal ΛCDM model. The same argument also precludes chameleon models from mimicking a dark radiation component, despite a passing similarity between the two scenarios in that they both delay the epoch of matter-radiation equality. Based on the derived parameter constraints, we discuss possible signatures of the model for ongoing and future large-scale structure surveys

How CMB and large-scale structure constrain chameleon interacting dark energy

Energy Technology Data Exchange (ETDEWEB)

Boriero, Daniel [Fakultät für Physik, Universität Bielefeld, Universitätstr. 25, Bielefeld (Germany); Das, Subinoy [Indian Institute of Astrophisics, Bangalore, 560034 (India); Wong, Yvonne Y.Y., E-mail: boriero@physik.uni-bielefeld.de, E-mail: subinoy@iiap.res.in, E-mail: yvonne.y.wong@unsw.edu.au [School of Physics, The University of New South Wales, Sydney NSW 2052 (Australia)

2015-07-01

We explore a chameleon type of interacting dark matter-dark energy scenario in which a scalar field adiabatically traces the minimum of an effective potential sourced by the dark matter density. We discuss extensively the effect of this coupling on cosmological observables, especially the parameter degeneracies expected to arise between the model parameters and other cosmological parameters, and then test the model against observations of the cosmic microwave background (CMB) anisotropies and other cosmological probes. We find that the chameleon parameters α and β, which determine respectively the slope of the scalar field potential and the dark matter-dark energy coupling strength, can be constrained to α < 0.17 and β < 0.19 using CMB data and measurements of baryon acoustic oscillations. The latter parameter in particular is constrained only by the late Integrated Sachs-Wolfe effect. Adding measurements of the local Hubble expansion rate H{sub 0} tightens the bound on α by a factor of two, although this apparent improvement is arguably an artefact of the tension between the local measurement and the H{sub 0} value inferred from Planck data in the minimal ΛCDM model. The same argument also precludes chameleon models from mimicking a dark radiation component, despite a passing similarity between the two scenarios in that they both delay the epoch of matter-radiation equality. Based on the derived parameter constraints, we discuss possible signatures of the model for ongoing and future large-scale structure surveys.

The effects of linear accelerations on the maximum heat transfer capacity of micro pipes with triangular grooves

International Nuclear Information System (INIS)

Shokouhmand, H.; Kahrobaian, A.; Tabandeh, N.; Jalilvand, A.

2002-01-01

Micro heat pipes are widely used for the thermal control of spacecraft and their electronic components. In this paper the influence of linear accelerations in micro grooves has been studied. A mathematical model for predicating the minimum meniscus radius and the maximum heat transport in triangular groove under the influence of linear acceleration is presented and method for determining the theoretical minimum meniscus radius is developed. It is shown that both, the direction and the magnitude of the acceleration have a great effect upon heat transfer capability of micro heat pipes. The analysis presented here provides a mechanism where by the groove geometry can be optimized with respect to the length of the heat pipe and direction and magnitude of linear acceleration

Peak thrust operation of linear induction machines from parameter identification

Energy Technology Data Exchange (ETDEWEB)

Zhang, Z.; Eastham, T.R.; Dawson, G.E. [Queen`s Univ., Kingston, Ontario (Canada). Dept. of Electrical and Computer Engineering

1995-12-31

Various control strategies are being used to achieve high performance operation of linear drives. To maintain minimum volume and weight of the power supply unit on board the transportation vehicle, peak thrust per unit current operation is a desirable objective. True peak thrust per unit current through slip control is difficult to achieve because the parameters of linear induction machines vary during normal operation. This paper first develops a peak thrust per unit current control law based on the per-phase equivalent circuit for linear induction machines. The algorithm for identification of the variable parameters in induction machines is then presented. Application to an operational linear induction machine (LIM) demonstrates the utility of this algorithm. The control strategy is then simulated, based on an operational transit LIM, to show the capability of achieving true peak thrust operation for linear induction machines.

Optimal linear detectors for nonorthogonal amplify-and-forward protocol

KAUST Repository

Ahmed, Qasim Zeeshan; Park, Kihong; Alouini, Mohamed-Slim; Aissa, Sonia

2013-01-01

In this paper, we propose optimal linear detectors for non-orthogonal amplify-and-forward cooperative protocol when considering a single-relay scenario. Two types of detectors are proposed based on the principles of minimum mean square error (MMSE) and minimum bit error rate (MBER). The MMSE detector minimizes the mean square error, while the MBER minimizes the system bit error rate (BER). Both detectors exhibit excellent BER performance with relatively low complexity as compared to the maximal likelihood (ML) detector. The BER performance of both detectors is superior to the channel inversion, the maximal ratio combining, and the biased ML detectors. © 2013 IEEE.

Optimal linear detectors for nonorthogonal amplify-and-forward protocol

KAUST Repository

Ahmed, Qasim Zeeshan

2013-06-01

In this paper, we propose optimal linear detectors for non-orthogonal amplify-and-forward cooperative protocol when considering a single-relay scenario. Two types of detectors are proposed based on the principles of minimum mean square error (MMSE) and minimum bit error rate (MBER). The MMSE detector minimizes the mean square error, while the MBER minimizes the system bit error rate (BER). Both detectors exhibit excellent BER performance with relatively low complexity as compared to the maximal likelihood (ML) detector. The BER performance of both detectors is superior to the channel inversion, the maximal ratio combining, and the biased ML detectors. © 2013 IEEE.

Development of novel segmented-plate linearly tunable MEMS capacitors

International Nuclear Information System (INIS)

Shavezipur, M; Khajepour, A; Hashemi, S M

2008-01-01

In this paper, novel MEMS capacitors with flexible moving electrodes and high linearity and tunability are presented. The moving plate is divided into small and rigid segments connected to one another by connecting beams at their end nodes. Under each node there is a rigid step which selectively limits the vertical displacement of the node. A lumped model is developed to analytically solve the governing equations of coupled structural-electrostatic physics with mechanical contact. Using the analytical solver, an optimization program finds the best set of step heights that provides the highest linearity. Analytical and finite element analyses of two capacitors with three-segmented- and six-segmented-plate confirm that the segmentation technique considerably improves the linearity while the tunability remains as high as that of a conventional parallel-plate capacitor. Moreover, since the new designs require customized fabrication processes, to demonstrate the applicability of the proposed technique for standard processes, a modified capacitor with flexible steps designed for PolyMUMPs is introduced. Dimensional optimization of the modified design results in a combination of high linearity and tunability. Constraining the displacement of the moving plate can be extended to more complex geometries to obtain smooth and highly linear responses

Nonlinear vs. linear biasing in Trp-cage folding simulations

Energy Technology Data Exchange (ETDEWEB)

Spiwok, Vojtěch, E-mail: spiwokv@vscht.cz; Oborský, Pavel; Králová, Blanka [Department of Biochemistry and Microbiology, University of Chemistry and Technology, Prague, Technická 3, Prague 6 166 28 (Czech Republic); Pazúriková, Jana [Institute of Computer Science, Masaryk University, Botanická 554/68a, 602 00 Brno (Czech Republic); Křenek, Aleš [Institute of Computer Science, Masaryk University, Botanická 554/68a, 602 00 Brno (Czech Republic); Center CERIT-SC, Masaryk Univerzity, Šumavská 416/15, 602 00 Brno (Czech Republic)

2015-03-21

Biased simulations have great potential for the study of slow processes, including protein folding. Atomic motions in molecules are nonlinear, which suggests that simulations with enhanced sampling of collective motions traced by nonlinear dimensionality reduction methods may perform better than linear ones. In this study, we compare an unbiased folding simulation of the Trp-cage miniprotein with metadynamics simulations using both linear (principle component analysis) and nonlinear (Isomap) low dimensional embeddings as collective variables. Folding of the mini-protein was successfully simulated in 200 ns simulation with linear biasing and non-linear motion biasing. The folded state was correctly predicted as the free energy minimum in both simulations. We found that the advantage of linear motion biasing is that it can sample a larger conformational space, whereas the advantage of nonlinear motion biasing lies in slightly better resolution of the resulting free energy surface. In terms of sampling efficiency, both methods are comparable.

Observations of non-linear plasmon damping in dense plasmas

Science.gov (United States)

Witte, B. B. L.; Sperling, P.; French, M.; Recoules, V.; Glenzer, S. H.; Redmer, R.

2018-05-01

We present simulations using finite-temperature density-functional-theory molecular-dynamics to calculate dynamic dielectric properties in warm dense aluminum. The comparison between exchange-correlation functionals in the Perdew, Burke, Ernzerhof approximation, Strongly Constrained and Appropriately Normed Semilocal Density Functional, and Heyd, Scuseria, Ernzerhof (HSE) approximation indicates evident differences in the electron transition energies, dc conductivity, and Lorenz number. The HSE calculations show excellent agreement with x-ray scattering data [Witte et al., Phys. Rev. Lett. 118, 225001 (2017)] as well as dc conductivity and absorption measurements. These findings demonstrate non-Drude behavior of the dynamic conductivity above the Cooper minimum that needs to be taken into account to determine optical properties in the warm dense matter regime.

Rising above the Minimum Wage.

Science.gov (United States)

Even, William; Macpherson, David

An in-depth analysis was made of how quickly most people move up the wage scale from minimum wage, what factors influence their progress, and how minimum wage increases affect wage growth above the minimum. Very few workers remain at the minimum wage over the long run, according to this study of data drawn from the 1977-78 May Current Population…

Assessing the impacts of Saskatchewan's minimum alcohol pricing regulations on alcohol-related crime.

Science.gov (United States)

Stockwell, Tim; Zhao, Jinhui; Sherk, Adam; Callaghan, Russell C; Macdonald, Scott; Gatley, Jodi

2017-07-01

Saskatchewan's introduction in April 2010 of minimum prices graded by alcohol strength led to an average minimum price increase of 9.1% per Canadian standard drink (=13.45 g ethanol). This increase was shown to be associated with reduced consumption and switching to lower alcohol content beverages. Police also informally reported marked reductions in night-time alcohol-related crime. This study aims to assess the impacts of changes to Saskatchewan's minimum alcohol-pricing regulations between 2008 and 2012 on selected crime events often related to alcohol use. Data were obtained from Canada's Uniform Crime Reporting Survey. Auto-regressive integrated moving average time series models were used to test immediate and lagged associations between minimum price increases and rates of night-time and police identified alcohol-related crimes. Controls were included for simultaneous crime rates in the neighbouring province of Alberta, economic variables, linear trend, seasonality and autoregressive and/or moving-average effects. The introduction of increased minimum-alcohol prices was associated with an abrupt decrease in night-time alcohol-related traffic offences for men (-8.0%, P prices may contribute to reductions in alcohol-related traffic-related and violent crimes perpetrated by men. Observed lagged effects for violent incidents may be due to a delay in bars passing on increased prices to their customers, perhaps because of inventory stockpiling. [Stockwell T, Zhao J, Sherk A, Callaghan RC, Macdonald S, Gatley J. Assessing the impacts of Saskatchewan's minimum alcohol pricing regulations on alcohol-related crime. Drug Alcohol Rev 2017;36:492-501]. © 2016 Australasian Professional Society on Alcohol and other Drugs.

Layered and Laterally Constrained 2D Inversion of Time Domain Induced Polarization Data

DEFF Research Database (Denmark)

Fiandaca, Gianluca; Ramm, James; Auken, Esben

description of the transmitter waveform and of the receiver transfer function allowing for a quantitative interpretation of the parameters. The code has been optimized for parallel computation and the inversion time is comparable to codes inverting just for direct current resistivity. The new inversion......In a sedimentary environment, quasi-layered models often represent the actual geology more accurately than smooth minimum-structure models. We have developed a new layered and laterally constrained inversion algorithm for time domain induced polarization data. The algorithm is based on the time...... transform of a complex resistivity forward response and the inversion extracts the spectral information of the time domain measures in terms of the Cole-Cole parameters. The developed forward code and inversion algorithm use the full time decay of the induced polarization response, together with an accurate...

Stable 1-Norm Error Minimization Based Linear Predictors for Speech Modeling

DEFF Research Database (Denmark)

Giacobello, Daniele; Christensen, Mads Græsbøll; Jensen, Tobias Lindstrøm

2014-01-01

In linear prediction of speech, the 1-norm error minimization criterion has been shown to provide a valid alternative to the 2-norm minimization criterion. However, unlike 2-norm minimization, 1-norm minimization does not guarantee the stability of the corresponding all-pole filter and can generate...... saturations when this is used to synthesize speech. In this paper, we introduce two new methods to obtain intrinsically stable predictors with the 1-norm minimization. The first method is based on constraining the roots of the predictor to lie within the unit circle by reducing the numerical range...... based linear prediction for modeling and coding of speech....

Maximum error-bounded Piecewise Linear Representation for online stream approximation

KAUST Repository

Xie, Qing; Pang, Chaoyi; Zhou, Xiaofang; Zhang, Xiangliang; Deng, Ke

2014-01-01

Given a time series data stream, the generation of error-bounded Piecewise Linear Representation (error-bounded PLR) is to construct a number of consecutive line segments to approximate the stream, such that the approximation error does not exceed a prescribed error bound. In this work, we consider the error bound in L∞ norm as approximation criterion, which constrains the approximation error on each corresponding data point, and aim on designing algorithms to generate the minimal number of segments. In the literature, the optimal approximation algorithms are effectively designed based on transformed space other than time-value space, while desirable optimal solutions based on original time domain (i.e., time-value space) are still lacked. In this article, we proposed two linear-time algorithms to construct error-bounded PLR for data stream based on time domain, which are named OptimalPLR and GreedyPLR, respectively. The OptimalPLR is an optimal algorithm that generates minimal number of line segments for the stream approximation, and the GreedyPLR is an alternative solution for the requirements of high efficiency and resource-constrained environment. In order to evaluate the superiority of OptimalPLR, we theoretically analyzed and compared OptimalPLR with the state-of-art optimal solution in transformed space, which also achieves linear complexity. We successfully proved the theoretical equivalence between time-value space and such transformed space, and also discovered the superiority of OptimalPLR on processing efficiency in practice. The extensive results of empirical evaluation support and demonstrate the effectiveness and efficiency of our proposed algorithms.

Maximum error-bounded Piecewise Linear Representation for online stream approximation

KAUST Repository

Xie, Qing

2014-04-04

Given a time series data stream, the generation of error-bounded Piecewise Linear Representation (error-bounded PLR) is to construct a number of consecutive line segments to approximate the stream, such that the approximation error does not exceed a prescribed error bound. In this work, we consider the error bound in L∞ norm as approximation criterion, which constrains the approximation error on each corresponding data point, and aim on designing algorithms to generate the minimal number of segments. In the literature, the optimal approximation algorithms are effectively designed based on transformed space other than time-value space, while desirable optimal solutions based on original time domain (i.e., time-value space) are still lacked. In this article, we proposed two linear-time algorithms to construct error-bounded PLR for data stream based on time domain, which are named OptimalPLR and GreedyPLR, respectively. The OptimalPLR is an optimal algorithm that generates minimal number of line segments for the stream approximation, and the GreedyPLR is an alternative solution for the requirements of high efficiency and resource-constrained environment. In order to evaluate the superiority of OptimalPLR, we theoretically analyzed and compared OptimalPLR with the state-of-art optimal solution in transformed space, which also achieves linear complexity. We successfully proved the theoretical equivalence between time-value space and such transformed space, and also discovered the superiority of OptimalPLR on processing efficiency in practice. The extensive results of empirical evaluation support and demonstrate the effectiveness and efficiency of our proposed algorithms.

Lightweight cryptography for constrained devices

DEFF Research Database (Denmark)

Alippi, Cesare; Bogdanov, Andrey; Regazzoni, Francesco

2014-01-01

Lightweight cryptography is a rapidly evolving research field that responds to the request for security in resource constrained devices. This need arises from crucial pervasive IT applications, such as those based on RFID tags where cost and energy constraints drastically limit the solution...... complexity, with the consequence that traditional cryptography solutions become too costly to be implemented. In this paper, we survey design strategies and techniques suitable for implementing security primitives in constrained devices....

Universal Linear Precoding for NBI-Proof Widely Linear Equalization in MC Systems

Directory of Open Access Journals (Sweden)

Donatella Darsena

2007-09-01

Full Text Available In multicarrier (MC systems, transmitter redundancy, which is introduced by means of finite-impulse response (FIR linear precoders, allows for perfect or zero-forcing (ZF equalization of FIR channels (in the absence of noise. Recently, it has been shown that the noncircular or improper nature of some symbol constellations offers an intrinsic source of redundancy, which can be exploited to design efficient FIR widely-linear (WL receiving structures for MC systems operating in the presence of narrowband interference (NBI. With regard to both cyclic-prefixed and zero-padded transmission techniques, it is shown in this paper that, with appropriately designed precoders, it is possible to synthesize in both cases WL-ZF universal equalizers, which guarantee perfect symbol recovery for any FIR channel. Furthermore, it is theoretically shown that the intrinsic redundancy of the improper symbol sequence also enables WL-ZF equalization, based on the minimum mean output-energy criterion, with improved NBI suppression capabilities. Finally, results of numerical simulations are presented, which assess the merits of the proposed precoding designs and validate the theoretical analysis carried out.

Linearly convergent stochastic heavy ball method for minimizing generalization error

KAUST Repository

Loizou, Nicolas

2017-10-30

In this work we establish the first linear convergence result for the stochastic heavy ball method. The method performs SGD steps with a fixed stepsize, amended by a heavy ball momentum term. In the analysis, we focus on minimizing the expected loss and not on finite-sum minimization, which is typically a much harder problem. While in the analysis we constrain ourselves to quadratic loss, the overall objective is not necessarily strongly convex.

Analysis of interactive fixed effects dynamic linear panel regression with measurement error

OpenAIRE

Nayoung Lee; Hyungsik Roger Moon; Martin Weidner

2011-01-01

This paper studies a simple dynamic panel linear regression model with interactive fixed effects in which the variable of interest is measured with error. To estimate the dynamic coefficient, we consider the least-squares minimum distance (LS-MD) estimation method.

Constraining generalized non-local cosmology from Noether symmetries.

Science.gov (United States)

Bahamonde, Sebastian; Capozziello, Salvatore; Dialektopoulos, Konstantinos F

2017-01-01

We study a generalized non-local theory of gravity which, in specific limits, can become either the curvature non-local or teleparallel non-local theory. Using the Noether symmetry approach, we find that the coupling functions coming from the non-local terms are constrained to be either exponential or linear in form. It is well known that in some non-local theories, a certain kind of exponential non-local couplings is needed in order to achieve a renormalizable theory. In this paper, we explicitly show that this kind of coupling does not need to be introduced by hand, instead, it appears naturally from the symmetries of the Lagrangian in flat Friedmann-Robertson-Walker cosmology. Finally, we find de Sitter and power-law cosmological solutions for different non-local theories. The symmetries for the generalized non-local theory are also found and some cosmological solutions are also achieved using the full theory.

Comparing Multiple-Group Multinomial Log-Linear Models for Multidimensional Skill Distributions in the General Diagnostic Model. Research Report. ETS RR-08-35

Science.gov (United States)

Xu, Xueli; von Davier, Matthias

2008-01-01

The general diagnostic model (GDM) utilizes located latent classes for modeling a multidimensional proficiency variable. In this paper, the GDM is extended by employing a log-linear model for multiple populations that assumes constraints on parameters across multiple groups. This constrained model is compared to log-linear models that assume…

Adaptive Constrained Optimal Control Design for Data-Based Nonlinear Discrete-Time Systems With Critic-Only Structure.

Science.gov (United States)

Luo, Biao; Liu, Derong; Wu, Huai-Ning

2018-06-01

Reinforcement learning has proved to be a powerful tool to solve optimal control problems over the past few years. However, the data-based constrained optimal control problem of nonaffine nonlinear discrete-time systems has rarely been studied yet. To solve this problem, an adaptive optimal control approach is developed by using the value iteration-based Q-learning (VIQL) with the critic-only structure. Most of the existing constrained control methods require the use of a certain performance index and only suit for linear or affine nonlinear systems, which is unreasonable in practice. To overcome this problem, the system transformation is first introduced with the general performance index. Then, the constrained optimal control problem is converted to an unconstrained optimal control problem. By introducing the action-state value function, i.e., Q-function, the VIQL algorithm is proposed to learn the optimal Q-function of the data-based unconstrained optimal control problem. The convergence results of the VIQL algorithm are established with an easy-to-realize initial condition . To implement the VIQL algorithm, the critic-only structure is developed, where only one neural network is required to approximate the Q-function. The converged Q-function obtained from the critic-only VIQL method is employed to design the adaptive constrained optimal controller based on the gradient descent scheme. Finally, the effectiveness of the developed adaptive control method is tested on three examples with computer simulation.

Employment effects of minimum wages

OpenAIRE

Neumark, David

2014-01-01

The potential benefits of higher minimum wages come from the higher wages for affected workers, some of whom are in low-income families. The potential downside is that a higher minimum wage may discourage employers from using the low-wage, low-skill workers that minimum wages are intended to help. Research findings are not unanimous, but evidence from many countries suggests that minimum wages reduce the jobs available to low-skill workers.

Improved linear least squares estimation using bounded data uncertainty

KAUST Repository

Ballal, Tarig

2015-04-01

This paper addresses the problemof linear least squares (LS) estimation of a vector x from linearly related observations. In spite of being unbiased, the original LS estimator suffers from high mean squared error, especially at low signal-to-noise ratios. The mean squared error (MSE) of the LS estimator can be improved by introducing some form of regularization based on certain constraints. We propose an improved LS (ILS) estimator that approximately minimizes the MSE, without imposing any constraints. To achieve this, we allow for perturbation in the measurement matrix. Then we utilize a bounded data uncertainty (BDU) framework to derive a simple iterative procedure to estimate the regularization parameter. Numerical results demonstrate that the proposed BDU-ILS estimator is superior to the original LS estimator, and it converges to the best linear estimator, the linear-minimum-mean-squared error estimator (LMMSE), when the elements of x are statistically white.

Improved linear least squares estimation using bounded data uncertainty

KAUST Repository

Ballal, Tarig; Al-Naffouri, Tareq Y.

2015-01-01

This paper addresses the problemof linear least squares (LS) estimation of a vector x from linearly related observations. In spite of being unbiased, the original LS estimator suffers from high mean squared error, especially at low signal-to-noise ratios. The mean squared error (MSE) of the LS estimator can be improved by introducing some form of regularization based on certain constraints. We propose an improved LS (ILS) estimator that approximately minimizes the MSE, without imposing any constraints. To achieve this, we allow for perturbation in the measurement matrix. Then we utilize a bounded data uncertainty (BDU) framework to derive a simple iterative procedure to estimate the regularization parameter. Numerical results demonstrate that the proposed BDU-ILS estimator is superior to the original LS estimator, and it converges to the best linear estimator, the linear-minimum-mean-squared error estimator (LMMSE), when the elements of x are statistically white.

Knot Undulator to Generate Linearly Polarized Photons with Low on-Axis Power Density

International Nuclear Information System (INIS)

Qiao, S.

2009-01-01

Heat load on beamline optics is a serious problem to generate pure linearly polarized photons in the third generation synchrotron radiation facilities. For permanent magnet undulators, this problem can be overcome by a figure-8 operating mode. But there is still no good method to tackle this problem for electromagnetic elliptical undulators. Here, a novel operating mode is suggested, which can generate pure linearly polarized photons with very low on-axis heat load. Also the available minimum photon energy of linearly polarized photons can be extended much by this method.

Minimum and Maximum Entropy Distributions for Binary Systems with Known Means and Pairwise Correlations

Science.gov (United States)

2017-08-21

number of neurons. Time is discretized and we assume any neuron can spike no more than once in a time bin. We have ν ≤ µ because ν is the probability of a...Comput. Appl. Math . 2000, 121, 331–354. 27. Shalizi, C.; Crutchfield, J. Computational mechanics: Pattern and prediction, structure and simplicity. J...Minimization of a Linearly Constrained Function by Partition of Feasible Domain. Math . Oper. Res. 1983, 8, 215–230. Entropy 2017, 19, 427 33 of 33 54. Candes, E

Event-triggered decentralized robust model predictive control for constrained large-scale interconnected systems

Directory of Open Access Journals (Sweden)

Ling Lu

2016-12-01

Full Text Available This paper considers the problem of event-triggered decentralized model predictive control (MPC for constrained large-scale linear systems subject to additive bounded disturbances. The constraint tightening method is utilized to formulate the MPC optimization problem. The local predictive control law for each subsystem is determined aperiodically by relevant triggering rule which allows a considerable reduction of the computational load. And then, the robust feasibility and closed-loop stability are proved and it is shown that every subsystem state will be driven into a robust invariant set. Finally, the effectiveness of the proposed approach is illustrated via numerical simulations.

Output Feedback Adaptive Control of Non-Minimum Phase Systems Using Optimal Control Modification

Science.gov (United States)

Nguyen, Nhan; Hashemi, Kelley E.; Yucelen, Tansel; Arabi, Ehsan

2018-01-01

This paper describes output feedback adaptive control approaches for non-minimum phase SISO systems with relative degree 1 and non-strictly positive real (SPR) MIMO systems with uniform relative degree 1 using the optimal control modification method. It is well-known that the standard model-reference adaptive control (MRAC) cannot be used to control non-SPR plants to track an ideal SPR reference model. Due to the ideal property of asymptotic tracking, MRAC attempts an unstable pole-zero cancellation which results in unbounded signals for non-minimum phase SISO systems. The optimal control modification can be used to prevent the unstable pole-zero cancellation which results in a stable adaptation of non-minimum phase SISO systems. However, the tracking performance using this approach could suffer if the unstable zero is located far away from the imaginary axis. The tracking performance can be recovered by using an observer-based output feedback adaptive control approach which uses a Luenberger observer design to estimate the state information of the plant. Instead of explicitly specifying an ideal SPR reference model, the reference model is established from the linear quadratic optimal control to account for the non-minimum phase behavior of the plant. With this non-minimum phase reference model, the observer-based output feedback adaptive control can maintain stability as well as tracking performance. However, in the presence of the mismatch between the SPR reference model and the non-minimum phase plant, the standard MRAC results in unbounded signals, whereas a stable adaptation can be achieved with the optimal control modification. An application of output feedback adaptive control for a flexible wing aircraft illustrates the approaches.

Minimum Wages and Poverty

OpenAIRE

Fields, Gary S.; Kanbur, Ravi

2005-01-01

Textbook analysis tells us that in a competitive labor market, the introduction of a minimum wage above the competitive equilibrium wage will cause unemployment. This paper makes two contributions to the basic theory of the minimum wage. First, we analyze the effects of a higher minimum wage in terms of poverty rather than in terms of unemployment. Second, we extend the standard textbook model to allow for incomesharing between the employed and the unemployed. We find that there are situation...

LDPC Codes with Minimum Distance Proportional to Block Size

Science.gov (United States)

Divsalar, Dariush; Jones, Christopher; Dolinar, Samuel; Thorpe, Jeremy

2009-01-01

Low-density parity-check (LDPC) codes characterized by minimum Hamming distances proportional to block sizes have been demonstrated. Like the codes mentioned in the immediately preceding article, the present codes are error-correcting codes suitable for use in a variety of wireless data-communication systems that include noisy channels. The previously mentioned codes have low decoding thresholds and reasonably low error floors. However, the minimum Hamming distances of those codes do not grow linearly with code-block sizes. Codes that have this minimum-distance property exhibit very low error floors. Examples of such codes include regular LDPC codes with variable degrees of at least 3. Unfortunately, the decoding thresholds of regular LDPC codes are high. Hence, there is a need for LDPC codes characterized by both low decoding thresholds and, in order to obtain acceptably low error floors, minimum Hamming distances that are proportional to code-block sizes. The present codes were developed to satisfy this need. The minimum Hamming distances of the present codes have been shown, through consideration of ensemble-average weight enumerators, to be proportional to code block sizes. As in the cases of irregular ensembles, the properties of these codes are sensitive to the proportion of degree-2 variable nodes. A code having too few such nodes tends to have an iterative decoding threshold that is far from the capacity threshold. A code having too many such nodes tends not to exhibit a minimum distance that is proportional to block size. Results of computational simulations have shown that the decoding thresholds of codes of the present type are lower than those of regular LDPC codes. Included in the simulations were a few examples from a family of codes characterized by rates ranging from low to high and by thresholds that adhere closely to their respective channel capacity thresholds; the simulation results from these examples showed that the codes in question have low

Efficient Preconditioning of Sequences of Nonsymmetric Linear Systems

Czech Academy of Sciences Publication Activity Database

Duintjer Tebbens, Jurjen; Tůma, Miroslav

2007-01-01

Roč. 29, č. 5 (2007), s. 1918-1941 ISSN 1064-8275 R&D Projects: GA AV ČR 1ET400300415; GA AV ČR KJB100300703 Institutional research plan: CEZ:AV0Z10300504 Keywords : preconditioned iterative methods * sparse matrices * sequences of linear algebraic systems * incomplete factorizations * factorization updates * Gauss–Jordan transformations * minimum spanning tree Subject RIV: BA - General Mathematics Impact factor: 1.784, year: 2007

Achievable Performance of Zero-Delay Variable-Rate Coding in Rate-Constrained Networked Control Systems with Channel Delay

DEFF Research Database (Denmark)

Barforooshan, Mohsen; Østergaard, Jan; Stavrou, Fotios

2017-01-01

This paper presents an upper bound on the minimum data rate required to achieve a prescribed closed-loop performance level in networked control systems (NCSs). The considered feedback loop includes a linear time-invariant (LTI) plant with single measurement output and single control input. Moreover......, in this NCS, a causal but otherwise unconstrained feedback system carries out zero-delay variable-rate coding, and control. Between the encoder and decoder, data is exchanged over a rate-limited noiseless digital channel with a known constant time delay. Here we propose a linear source-coding scheme...

A non-linear model of economic production processes

Science.gov (United States)

Ponzi, A.; Yasutomi, A.; Kaneko, K.

2003-06-01

We present a new two phase model of economic production processes which is a non-linear dynamical version of von Neumann's neoclassical model of production, including a market price-setting phase as well as a production phase. The rate of an economic production process is observed, for the first time, to depend on the minimum of its input supplies. This creates highly non-linear supply and demand dynamics. By numerical simulation, production networks are shown to become unstable when the ratio of different products to total processes increases. This provides some insight into observed stability of competitive capitalist economies in comparison to monopolistic economies. Capitalist economies are also shown to have low unemployment.

Constrained optimization via simulation models for new product innovation

Science.gov (United States)

Pujowidianto, Nugroho A.

2017-11-01

We consider the problem of constrained optimization where the decision makers aim to optimize the primary performance measure while constraining the secondary performance measures. This paper provides a brief overview of stochastically constrained optimization via discrete event simulation. Most review papers tend to be methodology-based. This review attempts to be problem-based as decision makers may have already decided on the problem formulation. We consider constrained optimization models as there are usually constraints on secondary performance measures as trade-off in new product development. It starts by laying out different possible methods and the reasons using constrained optimization via simulation models. It is then followed by the review of different simulation optimization approach to address constrained optimization depending on the number of decision variables, the type of constraints, and the risk preferences of the decision makers in handling uncertainties.

Formation of Linear Gradient of Antibiotics on Microfluidic Chips for High-throughput Antibiotic Susceptibility Testing

Science.gov (United States)

Kim, Seunggyu; Lee, Seokhun; Jeon, Jessie S.

2017-11-01

To determine the most effective antimicrobial treatments of infectious pathogen, high-throughput antibiotic susceptibility test (AST) is critically required. However, the conventional AST requires at least 16 hours to reach the minimum observable population. Therefore, we developed a microfluidic system that allows maintenance of linear antibiotic concentration and measurement of local bacterial density. Based on the Stokes-Einstein equation, the flow rate in the microchannel was optimized so that linearization was achieved within 10 minutes, taking into account the diffusion coefficient of each antibiotic in the agar gel. As a result, the minimum inhibitory concentration (MIC) of each antibiotic against P. aeruginosa could be immediately determined 6 hours after treatment of the linear antibiotic concentration. In conclusion, our system proved the efficacy of a high-throughput AST platform through MIC comparison with Clinical and Laboratory Standards Institute (CLSI) range of antibiotics. This work was supported by the Climate Change Research Hub (Grant No. N11170060) of the KAIST and by the Brain Korea 21 Plus project.

75 FR 6151 - Minimum Capital

Science.gov (United States)

2010-02-08

... capital and reserve requirements to be issued by order or regulation with respect to a product or activity... minimum capital requirements. Section 1362(a) establishes a minimum capital level for the Enterprises... entities required under this section.\\6\\ \\3\\ The Bank Act's current minimum capital requirements apply to...

Sensitivity theory for general non-linear algebraic equations with constraints

International Nuclear Information System (INIS)

Oblow, E.M.

1977-04-01

Sensitivity theory has been developed to a high state of sophistication for applications involving solutions of the linear Boltzmann equation or approximations to it. The success of this theory in the field of radiation transport has prompted study of possible extensions of the method to more general systems of non-linear equations. Initial work in the U.S. and in Europe on the reactor fuel cycle shows that the sensitivity methodology works equally well for those non-linear problems studied to date. The general non-linear theory for algebraic equations is summarized and applied to a class of problems whose solutions are characterized by constrained extrema. Such equations form the basis of much work on energy systems modelling and the econometrics of power production and distribution. It is valuable to have a sensitivity theory available for these problem areas since it is difficult to repeatedly solve complex non-linear equations to find out the effects of alternative input assumptions or the uncertainties associated with predictions of system behavior. The sensitivity theory for a linear system of algebraic equations with constraints which can be solved using linear programming techniques is discussed. The role of the constraints in simplifying the problem so that sensitivity methodology can be applied is highlighted. The general non-linear method is summarized and applied to a non-linear programming problem in particular. Conclusions are drawn in about the applicability of the method for practical problems

A Pareto-Improving Minimum Wage

OpenAIRE

Eliav Danziger; Leif Danziger

2014-01-01

This paper shows that a graduated minimum wage, in contrast to a constant minimum wage, can provide a strict Pareto improvement over what can be achieved with an optimal income tax. The reason is that a graduated minimum wage requires high-productivity workers to work more to earn the same income as low-productivity workers, which makes it more difficult for the former to mimic the latter. In effect, a graduated minimum wage allows the low-productivity workers to benefit from second-degree pr...

Application of pattern search method to power system security constrained economic dispatch with non-smooth cost function

International Nuclear Information System (INIS)

Al-Othman, A.K.; El-Naggar, K.M.

2008-01-01

Direct search methods are evolutionary algorithms used to solve optimization problems. (DS) methods do not require any information about the gradient of the objective function at hand while searching for an optimum solution. One of such methods is Pattern Search (PS) algorithm. This paper presents a new approach based on a constrained pattern search algorithm to solve a security constrained power system economic dispatch problem (SCED) with non-smooth cost function. Operation of power systems demands a high degree of security to keep the system satisfactorily operating when subjected to disturbances, while and at the same time it is required to pay attention to the economic aspects. Pattern recognition technique is used first to assess dynamic security. Linear classifiers that determine the stability of electric power system are presented and added to other system stability and operational constraints. The problem is formulated as a constrained optimization problem in a way that insures a secure-economic system operation. Pattern search method is then applied to solve the constrained optimization formulation. In particular, the method is tested using three different test systems. Simulation results of the proposed approach are compared with those reported in literature. The outcome is very encouraging and proves that pattern search (PS) is very applicable for solving security constrained power system economic dispatch problem (SCED). In addition, valve-point effect loading and total system losses are considered to further investigate the potential of the PS technique. Based on the results, it can be concluded that the PS has demonstrated ability in handling highly nonlinear discontinuous non-smooth cost function of the SCED. (author)

State Estimation for Linear Systems Driven Simultaneously by Wiener and Poisson Processes.

Science.gov (United States)

1978-12-01

The state estimation problem of linear stochastic systems driven simultaneously by Wiener and Poisson processes is considered, especially the case...where the incident intensities of the Poisson processes are low and the system is observed in an additive white Gaussian noise. The minimum mean squared

Parameter optimization in the regularized kernel minimum noise fraction transformation

DEFF Research Database (Denmark)

Nielsen, Allan Aasbjerg; Vestergaard, Jacob Schack

2012-01-01

Based on the original, linear minimum noise fraction (MNF) transformation and kernel principal component analysis, a kernel version of the MNF transformation was recently introduced. Inspired by we here give a simple method for finding optimal parameters in a regularized version of kernel MNF...... analysis. We consider the model signal-to-noise ratio (SNR) as a function of the kernel parameters and the regularization parameter. In 2-4 steps of increasingly refined grid searches we find the parameters that maximize the model SNR. An example based on data from the DLR 3K camera system is given....

An algorithm for the solution of dynamic linear programs

Science.gov (United States)

Psiaki, Mark L.

1989-01-01

The algorithm's objective is to efficiently solve Dynamic Linear Programs (DLP) by taking advantage of their special staircase structure. This algorithm constitutes a stepping stone to an improved algorithm for solving Dynamic Quadratic Programs, which, in turn, would make the nonlinear programming method of Successive Quadratic Programs more practical for solving trajectory optimization problems. The ultimate goal is to being trajectory optimization solution speeds into the realm of real-time control. The algorithm exploits the staircase nature of the large constraint matrix of the equality-constrained DLPs encountered when solving inequality-constrained DLPs by an active set approach. A numerically-stable, staircase QL factorization of the staircase constraint matrix is carried out starting from its last rows and columns. The resulting recursion is like the time-varying Riccati equation from multi-stage LQR theory. The resulting factorization increases the efficiency of all of the typical LP solution operations over that of a dense matrix LP code. At the same time numerical stability is ensured. The algorithm also takes advantage of dynamic programming ideas about the cost-to-go by relaxing active pseudo constraints in a backwards sweeping process. This further decreases the cost per update of the LP rank-1 updating procedure, although it may result in more changes of the active set that if pseudo constraints were relaxed in a non-stagewise fashion. The usual stability of closed-loop Linear/Quadratic optimally-controlled systems, if it carries over to strictly linear cost functions, implies that the saving due to reduced factor update effort may outweigh the cost of an increased number of updates. An aerospace example is presented in which a ground-to-ground rocket's distance is maximized. This example demonstrates the applicability of this class of algorithms to aerospace guidance. It also sheds light on the efficacy of the proposed pseudo constraint relaxation

Minimum critical mass systems

International Nuclear Information System (INIS)

Dam, H. van; Leege, P.F.A. de

1987-01-01

An analysis is presented of thermal systems with minimum critical mass, based on the use of materials with optimum neutron moderating and reflecting properties. The optimum fissile material distributions in the systems are obtained by calculations with standard computer codes, extended with a routine for flat fuel importance search. It is shown that in the minimum critical mass configuration a considerable part of the fuel is positioned in the reflector region. For 239 Pu a minimum critical mass of 87 g is found, which is the lowest value reported hitherto. (author)

Constraining generalized non-local cosmology from Noether symmetries

Energy Technology Data Exchange (ETDEWEB)

Bahamonde, Sebastian [University College London, Department of Mathematics, London (United Kingdom); Capozziello, Salvatore [Universita di Napoli ' ' Federico II' ' , Dipartimento di Fisica ' ' E. Pancini' ' , Naples (Italy); Gran Sasso Science Institute, L' Aquila (Italy); Complesso di Monte Sant' Angelo, Naples (Italy); INFN Sezione di Napoli, Naples (Italy); Dialektopoulos, Konstantinos F. [Universita di Napoli ' ' Federico II' ' , Dipartimento di Fisica ' ' E. Pancini' ' , Naples (Italy); Complesso di Monte Sant' Angelo, Naples (Italy); INFN Sezione di Napoli, Naples (Italy)

2017-11-15

We study a generalized non-local theory of gravity which, in specific limits, can become either the curvature non-local or teleparallel non-local theory. Using the Noether symmetry approach, we find that the coupling functions coming from the non-local terms are constrained to be either exponential or linear in form. It is well known that in some non-local theories, a certain kind of exponential non-local couplings is needed in order to achieve a renormalizable theory. In this paper, we explicitly show that this kind of coupling does not need to be introduced by hand, instead, it appears naturally from the symmetries of the Lagrangian in flat Friedmann-Robertson-Walker cosmology. Finally, we find de Sitter and power-law cosmological solutions for different non-local theories. The symmetries for the generalized non-local theory are also found and some cosmological solutions are also achieved using the full theory. (orig.)

Constrained multi-objective optimization of storage ring lattices

Science.gov (United States)

Husain, Riyasat; Ghodke, A. D.

2018-03-01

The storage ring lattice optimization is a class of constrained multi-objective optimization problem, where in addition to low beam emittance, a large dynamic aperture for good injection efficiency and improved beam lifetime are also desirable. The convergence and computation times are of great concern for the optimization algorithms, as various objectives are to be optimized and a number of accelerator parameters to be varied over a large span with several constraints. In this paper, a study of storage ring lattice optimization using differential evolution is presented. The optimization results are compared with two most widely used optimization techniques in accelerators-genetic algorithm and particle swarm optimization. It is found that the differential evolution produces a better Pareto optimal front in reasonable computation time between two conflicting objectives-beam emittance and dispersion function in the straight section. The differential evolution was used, extensively, for the optimization of linear and nonlinear lattices of Indus-2 for exploring various operational modes within the magnet power supply capabilities.

Cascading Constrained 2-D Arrays using Periodic Merging Arrays

DEFF Research Database (Denmark)

Forchhammer, Søren; Laursen, Torben Vaarby

2003-01-01

We consider a method for designing 2-D constrained codes by cascading finite width arrays using predefined finite width periodic merging arrays. This provides a constructive lower bound on the capacity of the 2-D constrained code. Examples include symmetric RLL and density constrained codes...

Robust model predictive control for constrained continuous-time nonlinear systems

Science.gov (United States)

Sun, Tairen; Pan, Yongping; Zhang, Jun; Yu, Haoyong

2018-02-01

In this paper, a robust model predictive control (MPC) is designed for a class of constrained continuous-time nonlinear systems with bounded additive disturbances. The robust MPC consists of a nonlinear feedback control and a continuous-time model-based dual-mode MPC. The nonlinear feedback control guarantees the actual trajectory being contained in a tube centred at the nominal trajectory. The dual-mode MPC is designed to ensure asymptotic convergence of the nominal trajectory to zero. This paper extends current results on discrete-time model-based tube MPC and linear system model-based tube MPC to continuous-time nonlinear model-based tube MPC. The feasibility and robustness of the proposed robust MPC have been demonstrated by theoretical analysis and applications to a cart-damper springer system and a one-link robot manipulator.

Trends in Mean Annual Minimum and Maximum Near Surface Temperature in Nairobi City, Kenya

Directory of Open Access Journals (Sweden)

George Lukoye Makokha

2010-01-01

Full Text Available This paper examines the long-term urban modification of mean annual conditions of near surface temperature in Nairobi City. Data from four weather stations situated in Nairobi were collected from the Kenya Meteorological Department for the period from 1966 to 1999 inclusive. The data included mean annual maximum and minimum temperatures, and was first subjected to homogeneity test before analysis. Both linear regression and Mann-Kendall rank test were used to discern the mean annual trends. Results show that the change of temperature over the thirty-four years study period is higher for minimum temperature than maximum temperature. The warming trends began earlier and are more significant at the urban stations than is the case at the sub-urban stations, an indication of the spread of urbanisation from the built-up Central Business District (CBD to the suburbs. The established significant warming trends in minimum temperature, which are likely to reach higher proportions in future, pose serious challenges on climate and urban planning of the city. In particular the effect of increased minimum temperature on human physiological comfort, building and urban design, wind circulation and air pollution needs to be incorporated in future urban planning programmes of the city.

Modeling the microstructural evolution during constrained sintering

DEFF Research Database (Denmark)

Bjørk, Rasmus; Frandsen, Henrik Lund; Tikare, V.

A numerical model able to simulate solid state constrained sintering of a powder compact is presented. The model couples an existing kinetic Monte Carlo (kMC) model for free sintering with a finite element (FE) method for calculating stresses on a microstructural level. The microstructural response...... to the stress field as well as the FE calculation of the stress field from the microstructural evolution is discussed. The sintering behavior of two powder compacts constrained by a rigid substrate is simulated and compared to free sintering of the same samples. Constrained sintering result in a larger number...

5 CFR 551.301 - Minimum wage.

Science.gov (United States)

2010-01-01

... 5 Administrative Personnel 1 2010-01-01 2010-01-01 false Minimum wage. 551.301 Section 551.301... FAIR LABOR STANDARDS ACT Minimum Wage Provisions Basic Provision § 551.301 Minimum wage. (a)(1) Except... employees wages at rates not less than the minimum wage specified in section 6(a)(1) of the Act for all...

A simple two stage optimization algorithm for constrained power economic dispatch

International Nuclear Information System (INIS)

Huang, G.; Song, K.

1994-01-01

A simple two stage optimization algorithm is proposed and investigated for fast computation of constrained power economic dispatch control problems. The method is a simple demonstration of the hierarchical aggregation-disaggregation (HAD) concept. The algorithm first solves an aggregated problem to obtain an initial solution. This aggregated problem turns out to be classical economic dispatch formulation, and it can be solved in 1% of overall computation time. In the second stage, linear programming method finds optimal solution which satisfies power balance constraints, generation and transmission inequality constraints and security constraints. Implementation of the algorithm for IEEE systems and EPRI Scenario systems shows that the two stage method obtains average speedup ratio 10.64 as compared to classical LP-based method

A nonlinear plate control without linearization

Directory of Open Access Journals (Sweden)

Yildirim Kenan

2017-03-01

Full Text Available In this paper, an optimal vibration control problem for a nonlinear plate is considered. In order to obtain the optimal control function, wellposedness and controllability of the nonlinear system is investigated. The performance index functional of the system, to be minimized by minimum level of control, is chosen as the sum of the quadratic 10 functional of the displacement. The velocity of the plate and quadratic functional of the control function is added to the performance index functional as a penalty term. By using a maximum principle, the nonlinear control problem is transformed to solving a system of partial differential equations including state and adjoint variables linked by initial-boundary-terminal conditions. Hence, it is shown that optimal control of the nonlinear systems can be obtained without linearization of the nonlinear term and optimal control function can be obtained analytically for nonlinear systems without linearization.

On the origin of constrained superfields

Energy Technology Data Exchange (ETDEWEB)

Dall’Agata, G. [Dipartimento di Fisica “Galileo Galilei”, Università di Padova,Via Marzolo 8, 35131 Padova (Italy); INFN, Sezione di Padova,Via Marzolo 8, 35131 Padova (Italy); Dudas, E. [Centre de Physique Théorique, École Polytechnique, CNRS, Université Paris-Saclay,F-91128 Palaiseau (France); Farakos, F. [Dipartimento di Fisica “Galileo Galilei”, Università di Padova,Via Marzolo 8, 35131 Padova (Italy); INFN, Sezione di Padova,Via Marzolo 8, 35131 Padova (Italy)

2016-05-06

In this work we analyze constrained superfields in supersymmetry and supergravity. We propose a constraint that, in combination with the constrained goldstino multiplet, consistently removes any selected component from a generic superfield. We also describe its origin, providing the operators whose equations of motion lead to the decoupling of such components. We illustrate our proposal by means of various examples and show how known constraints can be reproduced by our method.

Inexact nonlinear improved fuzzy chance-constrained programming model for irrigation water management under uncertainty

Science.gov (United States)

Zhang, Chenglong; Zhang, Fan; Guo, Shanshan; Liu, Xiao; Guo, Ping

2018-01-01

An inexact nonlinear mλ-measure fuzzy chance-constrained programming (INMFCCP) model is developed for irrigation water allocation under uncertainty. Techniques of inexact quadratic programming (IQP), mλ-measure, and fuzzy chance-constrained programming (FCCP) are integrated into a general optimization framework. The INMFCCP model can deal with not only nonlinearities in the objective function, but also uncertainties presented as discrete intervals in the objective function, variables and left-hand side constraints and fuzziness in the right-hand side constraints. Moreover, this model improves upon the conventional fuzzy chance-constrained programming by introducing a linear combination of possibility measure and necessity measure with varying preference parameters. To demonstrate its applicability, the model is then applied to a case study in the middle reaches of Heihe River Basin, northwest China. An interval regression analysis method is used to obtain interval crop water production functions in the whole growth period under uncertainty. Therefore, more flexible solutions can be generated for optimal irrigation water allocation. The variation of results can be examined by giving different confidence levels and preference parameters. Besides, it can reflect interrelationships among system benefits, preference parameters, confidence levels and the corresponding risk levels. Comparison between interval crop water production functions and deterministic ones based on the developed INMFCCP model indicates that the former is capable of reflecting more complexities and uncertainties in practical application. These results can provide more reliable scientific basis for supporting irrigation water management in arid areas.

Effects of Linear Falling Ramp Reset Pulse on Addressing Operation in AC PDP

International Nuclear Information System (INIS)

Liu Zujun; Liang Zhihu; Liu Chunliang; Meng Lingguo

2006-01-01

The effects of linear falling ramp reset pulse related to addressing operation in an alternating current plasma display panel (AC PDP) were studied. The wall charge waveforms were measured by the electrode balance method in a 12-inch coplanar AC PDP. The wall charge waveforms show the relationship between the slope ratio of the falling ramp reset pulse and the wall charges at the end of the falling ramp reset pulse which influences the addressing stability. Then the effects of the slope ratio of the linear falling ramp reset pulse on the addressing voltage and addressing time were investigated. The experimental results show that the minimum addressing voltage increases with the increase of the slope ratio of the falling ramp reset pulse, and so does the minimum addressing time. Based on the experimental results, the optimization of the addressing time and the slope ratio of the falling ramp pulse is discussed

Reflected stochastic differential equation models for constrained animal movement

Science.gov (United States)

Hanks, Ephraim M.; Johnson, Devin S.; Hooten, Mevin B.

2017-01-01

Movement for many animal species is constrained in space by barriers such as rivers, shorelines, or impassable cliffs. We develop an approach for modeling animal movement constrained in space by considering a class of constrained stochastic processes, reflected stochastic differential equations. Our approach generalizes existing methods for modeling unconstrained animal movement. We present methods for simulation and inference based on augmenting the constrained movement path with a latent unconstrained path and illustrate this augmentation with a simulation example and an analysis of telemetry data from a Steller sea lion (Eumatopias jubatus) in southeast Alaska.

Advanced Computational Methods for Security Constrained Financial Transmission Rights: Structure and Parallelism

Energy Technology Data Exchange (ETDEWEB)

Elbert, Stephen T.; Kalsi, Karanjit; Vlachopoulou, Maria; Rice, Mark J.; Glaesemann, Kurt R.; Zhou, Ning

2012-07-26

Financial Transmission Rights (FTRs) help power market participants reduce price risks associated with transmission congestion. FTRs are issued based on a process of solving a constrained optimization problem with the objective to maximize the FTR social welfare under power flow security constraints. Security constraints for different FTR categories (monthly, seasonal or annual) are usually coupled and the number of constraints increases exponentially with the number of categories. Commercial software for FTR calculation can only provide limited categories of FTRs due to the inherent computational challenges mentioned above. In this paper, a novel non-linear dynamical system (NDS) approach is proposed to solve the optimization problem. The new formulation and performance of the NDS solver is benchmarked against widely used linear programming (LP) solvers like CPLEX™ and tested on large-scale systems using data from the Western Electricity Coordinating Council (WECC). The NDS is demonstrated to outperform the widely used CPLEX algorithms while exhibiting superior scalability. Furthermore, the NDS based solver can be easily parallelized which results in significant computational improvement.

Free Magnetic Energy in Solar Active Regions above the Minimum-Energy Relaxed State

OpenAIRE

Regnier, S.; Priest, E. R.

2008-01-01

To understand the physics of solar flares, including the local reorganization of the magnetic field and the acceleration of energetic particles, we have first to estimate the free magnetic energy available for such phenomena, which can be converted into kinetic and thermal energy. The free magnetic energy is the excess energy of a magnetic configuration compared to the minimum-energy state, which is a linear force-free field if the magnetic helicity of the configuration is conserved. We inves...

Updating QR factorization procedure for solution of linear least squares problem with equality constraints.

Science.gov (United States)

Zeb, Salman; Yousaf, Muhammad

2017-01-01

In this article, we present a QR updating procedure as a solution approach for linear least squares problem with equality constraints. We reduce the constrained problem to unconstrained linear least squares and partition it into a small subproblem. The QR factorization of the subproblem is calculated and then we apply updating techniques to its upper triangular factor R to obtain its solution. We carry out the error analysis of the proposed algorithm to show that it is backward stable. We also illustrate the implementation and accuracy of the proposed algorithm by providing some numerical experiments with particular emphasis on dense problems.

Towards weakly constrained double field theory

Directory of Open Access Journals (Sweden)

Kanghoon Lee

2016-08-01

Full Text Available We show that it is possible to construct a well-defined effective field theory incorporating string winding modes without using strong constraint in double field theory. We show that X-ray (Radon transform on a torus is well-suited for describing weakly constrained double fields, and any weakly constrained fields are represented as a sum of strongly constrained fields. Using inverse X-ray transform we define a novel binary operation which is compatible with the level matching constraint. Based on this formalism, we construct a consistent gauge transform and gauge invariant action without using strong constraint. We then discuss the relation of our result to the closed string field theory. Our construction suggests that there exists an effective field theory description for massless sector of closed string field theory on a torus in an associative truncation.

Operator approach to solutions of the constrained BKP hierarchy

International Nuclear Information System (INIS)

Shen, Hsin-Fu; Lee, Niann-Chern; Tu, Ming-Hsien

2011-01-01

The operator formalism to the vector k-constrained BKP hierarchy is presented. We solve the Hirota bilinear equations of the vector k-constrained BKP hierarchy via the method of neutral free fermion. In particular, by choosing suitable group element of O(∞), we construct rational and soliton solutions of the vector k-constrained BKP hierarchy.

Kalman filtering for time-delayed linear systems

Institute of Scientific and Technical Information of China (English)

LU Xiao; WANG Wei

2006-01-01

This paper is to study the linear minimum variance estimation for discrete- time systems. A simple approach to the problem is presented by developing re-organized innovation analysis for the systems with instantaneous and double time-delayed measurements. It is shown that the derived estimator involves solving three different standard Kalman filtering with the same dimension as the original system. The obtained results form the basis for solving some complicated problems such as H∞ fixed-lag smoothing, preview control, H∞ filtering and control with time delays.

Sensitive Constrained Optimal PMU Allocation with Complete Observability for State Estimation Solution

Directory of Open Access Journals (Sweden)

R. Manam

2017-12-01

Full Text Available In this paper, a sensitive constrained integer linear programming approach is formulated for the optimal allocation of Phasor Measurement Units (PMUs in a power system network to obtain state estimation. In this approach, sensitive buses along with zero injection buses (ZIB are considered for optimal allocation of PMUs in the network to generate state estimation solutions. Sensitive buses are evolved from the mean of bus voltages subjected to increase of load consistently up to 50%. Sensitive buses are ranked in order to place PMUs. Sensitive constrained optimal PMU allocation in case of single line and no line contingency are considered in observability analysis to ensure protection and control of power system from abnormal conditions. Modeling of ZIB constraints is included to minimize the number of PMU network allocations. This paper presents optimal allocation of PMU at sensitive buses with zero injection modeling, considering cost criteria and redundancy to increase the accuracy of state estimation solution without losing observability of the whole system. Simulations are carried out on IEEE 14, 30 and 57 bus systems and results obtained are compared with traditional and other state estimation methods available in the literature, to demonstrate the effectiveness of the proposed method.

Métodos do tipo dual simplex para problemas de otimização linear canalizados

Directory of Open Access Journals (Sweden)

Ricardo Silveira Sousa

2005-12-01

Full Text Available Neste artigo estudamos o problema de otimização linear canalizado (restrições e variáveis canalizadas, chamado formato geral e desenvolvemos métodos do tipo dual simplex explorando o problema dual, o qual é linear por partes, num certo sentido não-linear. Várias alternativas de busca unidimensional foram examinadas. Experimentos computacionais revelam que a busca unidimensional exata na direção dual simplex apresenta melhor desempenho.In this paper we study the linear optimization problem lower and upper constrained (i.e., there are lower and upper bounds on constraints and variables and develop dual simplex methods that explore the dual problem, which is piecewise linear, in some sense nonlinear. Different one-dimensional searches were examined. Computational experiments showed that the exact one-dimensional search in the dual simplex direction has the best performance.

An historical survey of computational methods in optimal control.

Science.gov (United States)

Polak, E.

1973-01-01

Review of some of the salient theoretical developments in the specific area of optimal control algorithms. The first algorithms for optimal control were aimed at unconstrained problems and were derived by using first- and second-variation methods of the calculus of variations. These methods have subsequently been recognized as gradient, Newton-Raphson, or Gauss-Newton methods in function space. A much more recent addition to the arsenal of unconstrained optimal control algorithms are several variations of conjugate-gradient methods. At first, constrained optimal control problems could only be solved by exterior penalty function methods. Later algorithms specifically designed for constrained problems have appeared. Among these are methods for solving the unconstrained linear quadratic regulator problem, as well as certain constrained minimum-time and minimum-energy problems. Differential-dynamic programming was developed from dynamic programming considerations. The conditional-gradient method, the gradient-projection method, and a couple of feasible directions methods were obtained as extensions or adaptations of related algorithms for finite-dimensional problems. Finally, the so-called epsilon-methods combine the Ritz method with penalty function techniques.

Application of linear programming and perturbation theory in optimization of fuel utilization in a nuclear reactor

International Nuclear Information System (INIS)

Zavaljevski, N.

1985-01-01

Proposed optimization procedure is fast due to application of linear programming. Non-linear constraints which demand iterative application of linear programming are slowing down the calculation. Linearization can be done by different procedures starting from simple empirical rules for fuel in-core management to complicated general perturbation theory with higher order of corrections. A mathematical model was formulated for optimization of improved fuel cycle. A detailed algorithm for determining minimum of fresh fuel at the beginning of each fuel cycle is shown and the problem is linearized by first order perturbation theory and it is optimized by linear programming. Numerical illustration of the proposed method was done for the experimental reactor mostly for saving computer time

Reachable Distance Space: Efficient Sampling-Based Planning for Spatially Constrained Systems

KAUST Repository

Xinyu Tang,

2010-01-25

Motion planning for spatially constrained robots is difficult due to additional constraints placed on the robot, such as closure constraints for closed chains or requirements on end-effector placement for articulated linkages. It is usually computationally too expensive to apply sampling-based planners to these problems since it is difficult to generate valid configurations. We overcome this challenge by redefining the robot\\'s degrees of freedom and constraints into a new set of parameters, called reachable distance space (RD-space), in which all configurations lie in the set of constraint-satisfying subspaces. This enables us to directly sample the constrained subspaces with complexity linear in the number of the robot\\'s degrees of freedom. In addition to supporting efficient sampling of configurations, we show that the RD-space formulation naturally supports planning and, in particular, we design a local planner suitable for use by sampling-based planners. We demonstrate the effectiveness and efficiency of our approach for several systems including closed chain planning with multiple loops, restricted end-effector sampling, and on-line planning for drawing/sculpting. We can sample single-loop closed chain systems with 1,000 links in time comparable to open chain sampling, and we can generate samples for 1,000-link multi-loop systems of varying topologies in less than a second. © 2010 The Author(s).

A Linear Programming Approach to Routing Control in Networks of Constrained Nonlinear Positive Systems with Concave Flow Rates

Science.gov (United States)

Arneson, Heather M.; Dousse, Nicholas; Langbort, Cedric

2014-01-01

We consider control design for positive compartmental systems in which each compartment's outflow rate is described by a concave function of the amount of material in the compartment.We address the problem of determining the routing of material between compartments to satisfy time-varying state constraints while ensuring that material reaches its intended destination over a finite time horizon. We give sufficient conditions for the existence of a time-varying state-dependent routing strategy which ensures that the closed-loop system satisfies basic network properties of positivity, conservation and interconnection while ensuring that capacity constraints are satisfied, when possible, or adjusted if a solution cannot be found. These conditions are formulated as a linear programming problem. Instances of this linear programming problem can be solved iteratively to generate a solution to the finite horizon routing problem. Results are given for the application of this control design method to an example problem. Key words: linear programming; control of networks; positive systems; controller constraints and structure.

Prospects of measuring general Higgs couplings at e{sup +}e{sup -} linear colliders

Energy Technology Data Exchange (ETDEWEB)

Hagiwara, K. [KEK, Ibaraki (Japan). Theory Group; Ishihara, S. [KEK, Ibaraki (Japan). Theory Group; Department of Physics, Hyogo University of Education, 941-1 Shimokume, Yashiro, Kato, Hyogo 673-1494 (Japan); Kamoshita, J. [Department of Physics, Ochanomizu University, 2-1-1 Otsuka, Bunkyo, Tokyo 112-8610 (Japan); Kniehl, B.A. [II. Institut fuer Theoretische Physik, Universitaet Hamburg, Luruper Chaussee 149, 22761 Hamburg (Germany)

2000-06-01

We examine how accurately the general HZV couplings, with V=Z{gamma}, may be determined by studying e{sup +}e{sup -}{yields}Hf anti f processes at future e{sup +}e{sup -} linear colliders. By using the optimal-observable method, which makes use of all available experimental information, we find out which combinations of the various HZV coupling terms may be constrained most efficiently with high luminosity. We also assess the benefits of measuring the tau-lepton helicities, identifying the bottom-hadron charges, polarizing the electron beam and running at two different collider energies. The HZZ couplings are generally found to be well constrained, even without these options, while the HZ{gamma} couplings are not. The constraints on the latter may be significantly improved by beam polarization. (orig.)

An Integer Programming Formulation of the Minimum Common String Partition Problem.

Directory of Open Access Journals (Sweden)

S M Ferdous

Full Text Available We consider the problem of finding a minimum common string partition (MCSP of two strings, which is an NP-hard problem. The MCSP problem is closely related to genome comparison and rearrangement, an important field in Computational Biology. In this paper, we map the MCSP problem into a graph applying a prior technique and using this graph, we develop an Integer Linear Programming (ILP formulation for the problem. We implement the ILP formulation and compare the results with the state-of-the-art algorithms from the literature. The experimental results are found to be promising.

Minimum income protection in the Netherlands

NARCIS (Netherlands)

van Peijpe, T.

2009-01-01

This article offers an overview of the Dutch legal system of minimum income protection through collective bargaining, social security, and statutory minimum wages. In addition to collective agreements, the Dutch statutory minimum wage offers income protection to a small number of workers. Its

Constrained dictionary learning and probabilistic hypergraph ranking for person re-identification

Science.gov (United States)

He, You; Wu, Song; Pu, Nan; Qian, Li; Xiao, Guoqiang

2018-04-01

Person re-identification is a fundamental and inevitable task in public security. In this paper, we propose a novel framework to improve the performance of this task. First, two different types of descriptors are extracted to represent a pedestrian: (1) appearance-based superpixel features, which are constituted mainly by conventional color features and extracted from the supepixel rather than a whole picture and (2) due to the limitation of discrimination of appearance features, the deep features extracted by feature fusion Network are also used. Second, a view invariant subspace is learned by dictionary learning constrained by the minimum negative sample (termed as DL-cMN) to reduce the noise in appearance-based superpixel feature domain. Then, we use deep features and sparse codes transformed by appearancebased features to establish the hyperedges respectively by k-nearest neighbor, rather than jointing different features simply. Finally, a final ranking is performed by probabilistic hypergraph ranking algorithm. Extensive experiments on three challenging datasets (VIPeR, PRID450S and CUHK01) demonstrate the advantages and effectiveness of our proposed algorithm.

A proposal of comparative Maunder minimum cosmogenic isotope measurements

International Nuclear Information System (INIS)

Attolini, M.R.; Nanni, T.; Galli, M.; Povinec, P.

1989-01-01

There are at present contraddictory conclusions about solar activity and cosmogenic isotope production variation during Maunder Minimum. The interaction of solar wind with galactic cosmic rays, the dynamic behaviour of the Sun either as a system having an internal clock, and/or as a forced non linear system, are important aspects that can shed new light on solar physics, the Earth-Sun relationship and the climatic variation. An essential progress in the matter might be made by clarifying the cosmogenic isotope production during the mentioned interval. As it seems that during Maunder Minimum the Be10 production oscillates of about a factor of two, the authors have also to expect short scale enhanced variations in tree rings radiocarbon concentrations for the same interval. It is therefore highly desirable that for the same interval, that the authors would identify with 1640-1720 AD, detailed concentration measurements both of Be10 (in dated polar ice in addition to those of Beer et al.) and of tree ring radiocarbon, be made with cross-checking, in samples of different latitudes, longitudes and within short and large distance of the sea. The samples could be taken, as for example in samples from the central Mediterranean region, in the Baltic region and in other sites from central Europe and Asia

Non-linear realizations and higher curvature supergravity

Energy Technology Data Exchange (ETDEWEB)

Farakos, F. [Dipartimento di Fisica e Astronomia ' ' Galileo Galilei' ' , Universita di Padova (Italy); INFN, Sezione di Padova (Italy); Ferrara, S. [Department of Theoretical Physics, Geneva (Switzerland); INFN - Laboratori Nazionali di Frascati, Frascati (Italy); Department of Physics and Astronomy, Mani L. Bhaumik Institute for Theoretical Physics, U.C.L.A., Los Angeles, CA (United States); Kehagias, A. [Physics Division, National Technical University of Athens (Greece); Luest, D. [Arnold Sommerfeld Center for Theoretical Physics, Muenchen (Germany); Max-Planck-Institut fuer Physik, Muenchen (Germany)

2017-12-15

We focus on non-linear realizations of local supersymmetry as obtained by using constrained superfields in supergravity. New constraints, beyond those of rigid supersymmetry, are obtained whenever curvature multiplets are affected as well as higher derivative interactions are introduced. In particular, a new constraint, which removes a very massive gravitino is introduced, and in the rigid limit it merely reduces to an explicit supersymmetry breaking. Higher curvature supergravities free of ghosts and instabilities are also obtained in this way. Finally, we consider direct coupling of the goldstino multiplet to the super Gauss-Bonnet multiplet and discuss the emergence of a new scalar degree of freedom. (copyright 2017 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

Aspects of general linear modelling of migration.

Science.gov (United States)

Congdon, P

1992-01-01

"This paper investigates the application of general linear modelling principles to analysing migration flows between areas. Particular attention is paid to specifying the form of the regression and error components, and the nature of departures from Poisson randomness. Extensions to take account of spatial and temporal correlation are discussed as well as constrained estimation. The issue of specification bears on the testing of migration theories, and assessing the role migration plays in job and housing markets: the direction and significance of the effects of economic variates on migration depends on the specification of the statistical model. The application is in the context of migration in London and South East England in the 1970s and 1980s." excerpt

Signal Enhancement with Variable Span Linear Filters

DEFF Research Database (Denmark)

Benesty, Jacob; Christensen, Mads Græsbøll; Jensen, Jesper Rindom

. Variable span filters combine the ideas of optimal linear filters with those of subspace methods, as they involve the joint diagonalization of the correlation matrices of the desired signal and the noise. The book shows how some well-known filter designs, e.g. the minimum distortion, maximum signal...... the time and STFT domains, and, lastly, in time-domain binaural enhancement. In these contexts, the properties of these filters are analyzed in terms of their noise reduction capabilities and desired signal distortion, and the analyses are validated and further explored in simulations....

Constrained Perturbation Regularization Approach for Signal Estimation Using Random Matrix Theory

KAUST Repository

Suliman, Mohamed Abdalla Elhag

2016-10-06

In this work, we propose a new regularization approach for linear least-squares problems with random matrices. In the proposed constrained perturbation regularization approach, an artificial perturbation matrix with a bounded norm is forced into the system model matrix. This perturbation is introduced to improve the singular-value structure of the model matrix and, hence, the solution of the estimation problem. Relying on the randomness of the model matrix, a number of deterministic equivalents from random matrix theory are applied to derive the near-optimum regularizer that minimizes the mean-squared error of the estimator. Simulation results demonstrate that the proposed approach outperforms a set of benchmark regularization methods for various estimated signal characteristics. In addition, simulations show that our approach is robust in the presence of model uncertainty.

All-Pass Filter Based Linear Voltage Controlled Quadrature Oscillator

Directory of Open Access Journals (Sweden)

Koushick Mathur

2017-01-01

Full Text Available A linear voltage controlled quadrature oscillator implemented from a first-order electronically tunable all-pass filter (ETAF is presented. The active element is commercially available current feedback amplifier (AD844 in conjunction with the relatively new Multiplication Mode Current Conveyor (MMCC device. Electronic tunability is obtained by the control node voltage (V of the MMCC. Effects of the device nonidealities, namely, the parasitic capacitors and the roll-off poles of the port-transfer ratios of the device, are shown to be negligible, even though the usable high-frequency ranges are constrained by these imperfections. Subsequently the filter is looped with an electronically tunable integrator (ETI to implement the quadrature oscillator (QO. Experimental responses on the voltage tunable phase of the filter and the linear-tuning law of the quadrature oscillator up to 9.9 MHz at low THD are verified by simulation and hardware tests.

Robust non-gradient C subroutines for non-linear optimization

DEFF Research Database (Denmark)

Brock, Pernille; Madsen, Kaj; Nielsen, Hans Bruun

2004-01-01

This report presents a package of robust and easy-to-use C subroutines for solving unconstrained and constrained non-linear optimization problems, where gradient information is not required. The intention is that the routines should use the currently best algorithms available. All routines have...... subroutines are obtained by changing 0 to 1. The present report is a new and updated version of a previous report NI-91-04 with the title Non-gradient c Subroutines for Non- Linear Optimization, [16]. Both the previous and the present report describe a collection of subroutines, which have been translated...... from Fortran to C. The reason for writing the present report is that some of the C subroutines have been replaced by more e ective and robust versions translated from the original Fortran subroutines to C by the Bandler Group, see [1]. Also the test examples have been modified to some extent...

Geodynamic inversion to constrain the non-linear rheology of the lithosphere

Science.gov (United States)

Baumann, T. S.; Kaus, Boris J. P.

2015-08-01

One of the main methods to determine the strength of the lithosphere is by estimating it's effective elastic thickness. This method assumes that the lithosphere is a thin elastic plate that floats on the mantle and uses both topography and gravity anomalies to estimate the plate thickness. Whereas this seems to work well for oceanic plates, it has given controversial results in continental collision zones. For most of these locations, additional geophysical data sets such as receiver functions and seismic tomography exist that constrain the geometry of the lithosphere and often show that it is rather complex. Yet, lithospheric geometry by itself is insufficient to understand the dynamics of the lithosphere as this also requires knowledge of the rheology of the lithosphere. Laboratory experiments suggest that rocks deform in a viscous manner if temperatures are high and stresses low, or in a plastic/brittle manner if the yield stress is exceeded. Yet, the experimental results show significant variability between various rock types and there are large uncertainties in extrapolating laboratory values to nature, which leaves room for speculation. An independent method is thus required to better understand the rheology and dynamics of the lithosphere in collision zones. The goal of this paper is to discuss such an approach. Our method relies on performing numerical thermomechanical forward models of the present-day lithosphere with an initial geometry that is constructed from geophysical data sets. We employ experimentally determined creep-laws for the various parts of the lithosphere, but assume that the parameters of these creep-laws as well as the temperature structure of the lithosphere are uncertain. This is used as a priori information to formulate a Bayesian inverse problem that employs topography, gravity, horizontal and vertical surface velocities to invert for the unknown material parameters and temperature structure. In order to test the general methodology

The fastclime Package for Linear Programming and Large-Scale Precision Matrix Estimation in R.

Science.gov (United States)

Pang, Haotian; Liu, Han; Vanderbei, Robert

2014-02-01

We develop an R package fastclime for solving a family of regularized linear programming (LP) problems. Our package efficiently implements the parametric simplex algorithm, which provides a scalable and sophisticated tool for solving large-scale linear programs. As an illustrative example, one use of our LP solver is to implement an important sparse precision matrix estimation method called CLIME (Constrained L 1 Minimization Estimator). Compared with existing packages for this problem such as clime and flare, our package has three advantages: (1) it efficiently calculates the full piecewise-linear regularization path; (2) it provides an accurate dual certificate as stopping criterion; (3) it is completely coded in C and is highly portable. This package is designed to be useful to statisticians and machine learning researchers for solving a wide range of problems.

Pleistocene Thermocline Reconstruction and Oxygen Minimum Zone Evolution in the Maldives

Science.gov (United States)

Yu, S. M.; Wright, J.

2017-12-01

Drift deposits of the southern flank the Kardiva Channel in the eastern Inner Sea of the Maldives provide a complete record of Pleistocene water column changes in conjunction with monsoon cyclicity and fluctuations in the current system. We sampled IODP Site 359-U1467 to reconstruct water column using foraminiferal stable isotope records. This unlithified lithostratigraphic unit is rich in well-preserved microfossils and has an average sedimentation rate of 3.4 cm/yr. Marine Isotope Stages 1-6 were identified and show higher sedimentation rates during the interglacial sections approaching 6 cm/kyr. We present the δ13C and δ18O record of planktonic and benthic foraminiferal species taken at intervals of 3 cm. Globigerinoides ruber was used to constrain surface conditions. The thermocline dwelling species, Globorotalia menardii, was chosen to monitor fluctuations in the thermocline compared to the mixed layer. Lastly, the δ13C of the benthic species, Cibicidoides subhaidingerii and Planulina renzi, reveal changes to the bottom water ventilation and expansion of oxygen minimum zones over time. All three taxa recorded similar changes in δ18O over the glacial/interglacial cycles which is remarkable given the large sea level change ( 120 m) and the relatively shallow water depth ( 450 m). There is a small increase in the δ13C gradient during the glacial intervals which might reflect less ventilated bottom waters in the Inner Sea. This multispecies approach allows us to better constrain the thermocline hydrography and suggests that changes in the OMZ thickness are driven by the intensification of the monsoon cycles while painting a more cohesive picture to the changes in the water column structure.

Interpretation of Flow Logs from Nevada Test Site Boreholes to Estimate Hydraulic Conductivity Using Numerical Simulations Constrained by Single-Well Aquifer Tests

Science.gov (United States)

Garcia, C. Amanda; Halford, Keith J.; Laczniak, Randell J.

2010-01-01

Hydraulic conductivities of volcanic and carbonate lithologic units at the Nevada Test Site were estimated from flow logs and aquifer-test data. Borehole flow and drawdown were integrated and interpreted using a radial, axisymmetric flow model, AnalyzeHOLE. This integrated approach is used because complex well completions and heterogeneous aquifers and confining units produce vertical flow in the annular space and aquifers adjacent to the wellbore. AnalyzeHOLE simulates vertical flow, in addition to horizontal flow, which accounts for converging flow toward screen ends and diverging flow toward transmissive intervals. Simulated aquifers and confining units uniformly are subdivided by depth into intervals in which the hydraulic conductivity is estimated with the Parameter ESTimation (PEST) software. Between 50 and 150 hydraulic-conductivity parameters were estimated by minimizing weighted differences between simulated and measured flow and drawdown. Transmissivity estimates from single-well or multiple-well aquifer tests were used to constrain estimates of hydraulic conductivity. The distribution of hydraulic conductivity within each lithology had a minimum variance because estimates were constrained with Tikhonov regularization. AnalyzeHOLE simulated hydraulic-conductivity estimates for lithologic units across screened and cased intervals are as much as 100 times less than those estimated using proportional flow-log analyses applied across screened intervals only. Smaller estimates of hydraulic conductivity for individual lithologic units are simulated because sections of the unit behind cased intervals of the wellbore are not assumed to be impermeable, and therefore, can contribute flow to the wellbore. Simulated hydraulic-conductivity estimates vary by more than three orders of magnitude across a lithologic unit, indicating a high degree of heterogeneity in volcanic and carbonate-rock units. The higher water transmitting potential of carbonate-rock units relative

Interpretation of Flow Logs from Nevada Test Site Boreholes to Estimate Hydraulic conductivity Using Numerical Simulations Constrained by Single-Well Aquifer Tests

Energy Technology Data Exchange (ETDEWEB)

Garcia, C. Amanda; Halford, Keith J.; Laczniak, Randell J.

2010-02-12

Hydraulic conductivities of volcanic and carbonate lithologic units at the Nevada Test Site were estimated from flow logs and aquifer-test data. Borehole flow and drawdown were integrated and interpreted using a radial, axisymmetric flow model, AnalyzeHOLE. This integrated approach is used because complex well completions and heterogeneous aquifers and confining units produce vertical flow in the annular space and aquifers adjacent to the wellbore. AnalyzeHOLE simulates vertical flow, in addition to horizontal flow, which accounts for converging flow toward screen ends and diverging flow toward transmissive intervals. Simulated aquifers and confining units uniformly are subdivided by depth into intervals in which the hydraulic conductivity is estimated with the Parameter ESTimation (PEST) software. Between 50 and 150 hydraulic-conductivity parameters were estimated by minimizing weighted differences between simulated and measured flow and drawdown. Transmissivity estimates from single-well or multiple-well aquifer tests were used to constrain estimates of hydraulic conductivity. The distribution of hydraulic conductivity within each lithology had a minimum variance because estimates were constrained with Tikhonov regularization. AnalyzeHOLE simulated hydraulic-conductivity estimates for lithologic units across screened and cased intervals are as much as 100 times less than those estimated using proportional flow-log analyses applied across screened intervals only. Smaller estimates of hydraulic conductivity for individual lithologic units are simulated because sections of the unit behind cased intervals of the wellbore are not assumed to be impermeable, and therefore, can contribute flow to the wellbore. Simulated hydraulic-conductivity estimates vary by more than three orders of magnitude across a lithologic unit, indicating a high degree of heterogeneity in volcanic and carbonate-rock units. The higher water transmitting potential of carbonate-rock units relative

Eigenspace-Based Minimum Variance Adaptive Beamformer Combined with Delay Multiply and Sum: Experimental Study

OpenAIRE

Mozaffarzadeh, Moein; Mahloojifar, Ali; Nasiriavanaki, Mohammadreza; Orooji, Mahdi

2017-01-01

Delay and sum (DAS) is the most common beamforming algorithm in linear-array photoacoustic imaging (PAI) as a result of its simple implementation. However, it leads to a low resolution and high sidelobes. Delay multiply and sum (DMAS) was used to address the incapabilities of DAS, providing a higher image quality. However, the resolution improvement is not well enough compared to eigenspace-based minimum variance (EIBMV). In this paper, the EIBMV beamformer has been combined with DMAS algebra...

Robust Management of Combined Heat and Power Systems via Linear Decision Rules

DEFF Research Database (Denmark)

Zugno, Marco; Morales González, Juan Miguel; Madsen, Henrik

2014-01-01

The heat and power outputs of Combined Heat and Power (CHP) units are jointly constrained. Hence, the optimal management of systems including CHP units is a multicommodity optimization problem. Problems of this type are stochastic, owing to the uncertainty inherent both in the demand for heat and...... linear decision rules to guarantee both tractability and a correct representation of the dynamic aspects of the problem. Numerical results from an illustrative example confirm the value of the proposed approach....

DATA-CONSTRAINED CORONAL MASS EJECTIONS IN A GLOBAL MAGNETOHYDRODYNAMICS MODEL

Energy Technology Data Exchange (ETDEWEB)

Jin, M. [Lockheed Martin Solar and Astrophysics Lab, Palo Alto, CA 94304 (United States); Manchester, W. B.; Van der Holst, B.; Sokolov, I.; Tóth, G.; Gombosi, T. I. [Climate and Space Sciences and Engineering, University of Michigan, Ann Arbor, MI 48109 (United States); Mullinix, R. E.; Taktakishvili, A.; Chulaki, A., E-mail: jinmeng@lmsal.com, E-mail: chipm@umich.edu, E-mail: richard.e.mullinix@nasa.gov, E-mail: Aleksandre.Taktakishvili-1@nasa.gov [Community Coordinated Modeling Center, NASA Goddard Space Flight Center, Greenbelt, MD 20771 (United States)

2017-01-10

We present a first-principles-based coronal mass ejection (CME) model suitable for both scientific and operational purposes by combining a global magnetohydrodynamics (MHD) solar wind model with a flux-rope-driven CME model. Realistic CME events are simulated self-consistently with high fidelity and forecasting capability by constraining initial flux rope parameters with observational data from GONG, SOHO /LASCO, and STEREO /COR. We automate this process so that minimum manual intervention is required in specifying the CME initial state. With the newly developed data-driven Eruptive Event Generator using Gibson–Low configuration, we present a method to derive Gibson–Low flux rope parameters through a handful of observational quantities so that the modeled CMEs can propagate with the desired CME speeds near the Sun. A test result with CMEs launched with different Carrington rotation magnetograms is shown. Our study shows a promising result for using the first-principles-based MHD global model as a forecasting tool, which is capable of predicting the CME direction of propagation, arrival time, and ICME magnetic field at 1 au (see the companion paper by Jin et al. 2016a).

Understanding the Minimum Wage: Issues and Answers.

Science.gov (United States)

Employment Policies Inst. Foundation, Washington, DC.

This booklet, which is designed to clarify facts regarding the minimum wage's impact on marketplace economics, contains a total of 31 questions and answers pertaining to the following topics: relationship between minimum wages and poverty; impacts of changes in the minimum wage on welfare reform; and possible effects of changes in the minimum wage…

Youth minimum wages and youth employment

NARCIS (Netherlands)

Marimpi, Maria; Koning, Pierre

2018-01-01

This paper performs a cross-country level analysis on the impact of the level of specific youth minimum wages on the labor market performance of young individuals. We use information on the use and level of youth minimum wages, as compared to the level of adult minimum wages as well as to the median

Discretization of space and time: determining the values of minimum length and minimum time

OpenAIRE

Roatta , Luca

2017-01-01

Assuming that space and time can only have discrete values, we obtain the expression of the minimum length and the minimum time interval. These values are found to be exactly coincident with the Planck's length and the Planck's time but for the presence of h instead of ħ .

Minimum wage development in the Russian Federation

OpenAIRE

Bolsheva, Anna

2012-01-01

The aim of this paper is to analyze the effectiveness of the minimum wage policy at the national level in Russia and its impact on living standards in the country. The analysis showed that the national minimum wage in Russia does not serve its original purpose of protecting the lowest wage earners and has no substantial effect on poverty reduction. The national subsistence minimum is too low and cannot be considered an adequate criterion for the setting of the minimum wage. The minimum wage d...

Continuation of Sets of Constrained Orbit Segments

DEFF Research Database (Denmark)

Schilder, Frank; Brøns, Morten; Chamoun, George Chaouki

Sets of constrained orbit segments of time continuous flows are collections of trajectories that represent a whole or parts of an invariant set. A non-trivial but simple example is a homoclinic orbit. A typical representation of this set consists of an equilibrium point of the flow and a trajectory...... that starts close and returns close to this fixed point within finite time. More complicated examples are hybrid periodic orbits of piecewise smooth systems or quasi-periodic invariant tori. Even though it is possible to define generalised two-point boundary value problems for computing sets of constrained...... orbit segments, this is very disadvantageous in practice. In this talk we will present an algorithm that allows the efficient continuation of sets of constrained orbit segments together with the solution of the full variational problem....

Minimum emittance of three-bend achromats

International Nuclear Information System (INIS)

Li Xiaoyu; Xu Gang

2012-01-01

The calculation of the minimum emittance of three-bend achromats (TBAs) made by Mathematical software can ignore the actual magnets lattice in the matching condition of dispersion function in phase space. The minimum scaling factors of two kinds of widely used TBA lattices are obtained. Then the relationship between the lengths and the radii of the three dipoles in TBA is obtained and so is the minimum scaling factor, when the TBA lattice achieves its minimum emittance. The procedure of analysis and the results can be widely used in achromats lattices, because the calculation is not restricted by the actual lattice. (authors)

Constrained consequence

CSIR Research Space (South Africa)

Britz, K

2011-09-01

Full Text Available their basic properties and relationship. In Section 3 we present a modal instance of these constructions which also illustrates with an example how to reason abductively with constrained entailment in a causal or action oriented context. In Section 4 we... of models with the former approach, whereas in Section 3.3 we give an example illustrating ways in which C can be de ned with both. Here we employ the following versions of local consequence: De nition 3.4. Given a model M = hW;R;Vi and formulas...

Constrained statistical inference: sample-size tables for ANOVA and regression

Directory of Open Access Journals (Sweden)

Leonard eVanbrabant

2015-01-01

Full Text Available Researchers in the social and behavioral sciences often have clear expectations about the order/direction of the parameters in their statistical model. For example, a researcher might expect that regression coefficient beta1 is larger than beta2 and beta3. The corresponding hypothesis is H: beta1 > {beta2, beta3} and this is known as an (order constrained hypothesis. A major advantage of testing such a hypothesis is that power can be gained and inherently a smaller sample size is needed. This article discusses this gain in sample size reduction, when an increasing number of constraints is included into the hypothesis. The main goal is to present sample-size tables for constrained hypotheses. A sample-size table contains the necessary sample-size at a prespecified power (say, 0.80 for an increasing number of constraints. To obtain sample-size tables, two Monte Carlo simulations were performed, one for ANOVA and one for multiple regression. Three results are salient. First, in an ANOVA the needed sample-size decreases with 30% to 50% when complete ordering of the parameters is taken into account. Second, small deviations from the imposed order have only a minor impact on the power. Third, at the maximum number of constraints, the linear regression results are comparable with the ANOVA results. However, in the case of fewer constraints, ordering the parameters (e.g., beta1 > beta2 results in a higher power than assigning a positive or a negative sign to the parameters (e.g., beta1 > 0.

Robust linear discriminant analysis with distance based estimators

Science.gov (United States)

Lim, Yai-Fung; Yahaya, Sharipah Soaad Syed; Ali, Hazlina

2017-11-01

Linear discriminant analysis (LDA) is one of the supervised classification techniques concerning relationship between a categorical variable and a set of continuous variables. The main objective of LDA is to create a function to distinguish between populations and allocating future observations to previously defined populations. Under the assumptions of normality and homoscedasticity, the LDA yields optimal linear discriminant rule (LDR) between two or more groups. However, the optimality of LDA highly relies on the sample mean and pooled sample covariance matrix which are known to be sensitive to outliers. To alleviate these conflicts, a new robust LDA using distance based estimators known as minimum variance vector (MVV) has been proposed in this study. The MVV estimators were used to substitute the classical sample mean and classical sample covariance to form a robust linear discriminant rule (RLDR). Simulation and real data study were conducted to examine on the performance of the proposed RLDR measured in terms of misclassification error rates. The computational result showed that the proposed RLDR is better than the classical LDR and was comparable with the existing robust LDR.

The number of subjects per variable required in linear regression analyses.

Science.gov (United States)

Austin, Peter C; Steyerberg, Ewout W

2015-06-01

To determine the number of independent variables that can be included in a linear regression model. We used a series of Monte Carlo simulations to examine the impact of the number of subjects per variable (SPV) on the accuracy of estimated regression coefficients and standard errors, on the empirical coverage of estimated confidence intervals, and on the accuracy of the estimated R(2) of the fitted model. A minimum of approximately two SPV tended to result in estimation of regression coefficients with relative bias of less than 10%. Furthermore, with this minimum number of SPV, the standard errors of the regression coefficients were accurately estimated and estimated confidence intervals had approximately the advertised coverage rates. A much higher number of SPV were necessary to minimize bias in estimating the model R(2), although adjusted R(2) estimates behaved well. The bias in estimating the model R(2) statistic was inversely proportional to the magnitude of the proportion of variation explained by the population regression model. Linear regression models require only two SPV for adequate estimation of regression coefficients, standard errors, and confidence intervals. Copyright © 2015 The Authors. Published by Elsevier Inc. All rights reserved.

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

Directory of Open Access Journals (Sweden)

Xi Wang

2016-01-01

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

Constrained Versions of DEDICOM for Use in Unsupervised Part-Of-Speech Tagging

Energy Technology Data Exchange (ETDEWEB)

Dunlavy, Daniel; Peter A. Chew

2016-05-01

This reports describes extensions of DEDICOM (DEcomposition into DIrectional COMponents) data models [3] that incorporate bound and linear constraints. The main purpose of these extensions is to investigate the use of improved data models for unsupervised part-of-speech tagging, as described by Chew et al. [2]. In that work, a single domain, two-way DEDICOM model was computed on a matrix of bigram fre- quencies of tokens in a corpus and used to identify parts-of-speech as an unsupervised approach to that problem. An open problem identi ed in that work was the com- putation of a DEDICOM model that more closely resembled the matrices used in a Hidden Markov Model (HMM), speci cally through post-processing of the DEDICOM factor matrices. The work reported here consists of the description of several models that aim to provide a direct solution to that problem and a way to t those models. The approach taken here is to incorporate the model requirements as bound and lin- ear constrains into the DEDICOM model directly and solve the data tting problem as a constrained optimization problem. This is in contrast to the typical approaches in the literature, where the DEDICOM model is t using unconstrained optimization approaches, and model requirements are satis ed as a post-processing step.

Constraining dark energy and modified gravity with galaxy clusters, Oskar Klein Center for Cosmoparticle Physics, Stockholm, Sweden

DEFF Research Database (Denmark)

Rapetti Serra, David Angelo

2011-01-01

Using measurements of the abundance of galaxy clusters we obtain constraints on dark energy and gravity at cosmological scales. Our data set consists of 238 cluster detections drawn from the ROSAT All-Sky Survey and X-ray follow-up observations of 94 of those clusters. Using a new statistical...... framework we self-consistently and simultaneously constrain cosmology and observable-mass scaling relations accounting for survey biases, parameter covariances and systematic uncertainties. Allowing the linear growth index and the dark energy equation of state to take any constant values, we find...

Free and constrained symplectic integrators for numerical general relativity

International Nuclear Information System (INIS)

Richter, Ronny; Lubich, Christian

2008-01-01

We consider symplectic time integrators in numerical general relativity and discuss both free and constrained evolution schemes. For free evolution of ADM-like equations we propose the use of the Stoermer-Verlet method, a standard symplectic integrator which here is explicit in the computationally expensive curvature terms. For the constrained evolution we give a formulation of the evolution equations that enforces the momentum constraints in a holonomically constrained Hamiltonian system and turns the Hamilton constraint function from a weak to a strong invariant of the system. This formulation permits the use of the constraint-preserving symplectic RATTLE integrator, a constrained version of the Stoermer-Verlet method. The behavior of the methods is illustrated on two effectively (1+1)-dimensional versions of Einstein's equations, which allow us to investigate a perturbed Minkowski problem and the Schwarzschild spacetime. We compare symplectic and non-symplectic integrators for free evolution, showing very different numerical behavior for nearly-conserved quantities in the perturbed Minkowski problem. Further we compare free and constrained evolution, demonstrating in our examples that enforcing the momentum constraints can turn an unstable free evolution into a stable constrained evolution. This is demonstrated in the stabilization of a perturbed Minkowski problem with Dirac gauge, and in the suppression of the propagation of boundary instabilities into the interior of the domain in Schwarzschild spacetime

Complexation of Polyelectrolyte Micelles with Oppositely Charged Linear Chains.

Science.gov (United States)

Kalogirou, Andreas; Gergidis, Leonidas N; Miliou, Kalliopi; Vlahos, Costas

2017-03-02

The formation of interpolyelectrolyte complexes (IPECs) from linear AB diblock copolymer precursor micelles and oppositely charged linear homopolymers is studied by means of molecular dynamics simulations. All beads of the linear polyelectrolyte (C) are charged with elementary quenched charge +1e, whereas in the diblock copolymer only the solvophilic (A) type beads have quenched charge -1e. For the same Bjerrum length, the ratio of positive to negative charges, Z +/- , of the mixture and the relative length of charged moieties r determine the size of IPECs. We found a nonmonotonic variation of the size of the IPECs with Z +/- . For small Z +/- values, the IPECs retain the size of the precursor micelle, whereas at larger Z +/- values the IPECs decrease in size due to the contraction of the corona and then increase as the aggregation number of the micelle increases. The minimum size of the IPECs is obtained at lower Z +/- values when the length of the hydrophilic block of the linear diblock copolymer decreases. The aforementioned findings are in agreement with experimental results. At a smaller Bjerrum length, we obtain the same trends but at even smaller Z +/- values. The linear homopolymer charged units are distributed throughout the corona.

I/O-Efficient Construction of Constrained Delaunay Triangulations

DEFF Research Database (Denmark)

Agarwal, Pankaj Kumar; Arge, Lars; Yi, Ke

2005-01-01

In this paper, we designed and implemented an I/O-efficient algorithm for constructing constrained Delaunay triangulations. If the number of constraining segments is smaller than the memory size, our algorithm runs in expected O( N B logM/B NB ) I/Os for triangulating N points in the plane, where...

Analytical and Algorithmic Approaches to Determine the Number of Sensor Nodes for Minimum Power Consumption in LWSNs

Directory of Open Access Journals (Sweden)

Ali Soner Kilinc

2017-08-01

Full Text Available A Linear Wireless Sensor Network (LWSN is a kind of wireless sensor network where the nodes are deployed in a line. Since the sensor nodes are energy restricted, energy efficiency becomes one of the most significant design issues for LWSNs as well as wireless sensor networks. With the proper deployment, the power consumption could be minimized by adjusting the distance between the sensor nodes which is known as hop length. In this paper, analytical and algorithmic approaches are presented to determine the number of hops and sensor nodes for minimum power consumption in a linear wireless sensor network including equidistantly placed sensor nodes.

Constrained Vapor Bubble Experiment

Science.gov (United States)

Gokhale, Shripad; Plawsky, Joel; Wayner, Peter C., Jr.; Zheng, Ling; Wang, Ying-Xi

2002-11-01

Microgravity experiments on the Constrained Vapor Bubble Heat Exchanger, CVB, are being developed for the International Space Station. In particular, we present results of a precursory experimental and theoretical study of the vertical Constrained Vapor Bubble in the Earth's environment. A novel non-isothermal experimental setup was designed and built to study the transport processes in an ethanol/quartz vertical CVB system. Temperature profiles were measured using an in situ PC (personal computer)-based LabView data acquisition system via thermocouples. Film thickness profiles were measured using interferometry. A theoretical model was developed to predict the curvature profile of the stable film in the evaporator. The concept of the total amount of evaporation, which can be obtained directly by integrating the experimental temperature profile, was introduced. Experimentally measured curvature profiles are in good agreement with modeling results. For microgravity conditions, an analytical expression, which reveals an inherent relation between temperature and curvature profiles, was derived.

30 CFR 57.19021 - Minimum rope strength.

Science.gov (United States)

2010-07-01

... feet: Minimum Value=Static Load×(7.0−0.001L) For rope lengths 3,000 feet or greater: Minimum Value=Static Load×4.0. (b) Friction drum ropes. For rope lengths less than 4,000 feet: Minimum Value=Static Load×(7.0−0.0005L) For rope lengths 4,000 feet or greater: Minimum Value=Static Load×5.0. (c) Tail...

30 CFR 56.19021 - Minimum rope strength.

Science.gov (United States)

2010-07-01

... feet: Minimum Value=Static Load×(7.0-0.001L) For rope lengths 3,000 feet or greater: Minimum Value=Static Load×4.0 (b) Friction drum ropes. For rope lengths less than 4,000 feet: Minimum Value=Static Load×(7.0-0.0005L) For rope lengths 4,000 feet or greater: Minimum Value=Static Load×5.0 (c) Tail ropes...

Linear Model for Optimal Distributed Generation Size Predication

Directory of Open Access Journals (Sweden)

Ahmed Al Ameri

2017-01-01

Full Text Available This article presents a linear model predicting optimal size of Distributed Generation (DG that addresses the minimum power loss. This method is based fundamentally on strong coupling between active power and voltage angle as well as between reactive power and voltage magnitudes. This paper proposes simplified method to calculate the total power losses in electrical grid for different distributed generation sizes and locations. The method has been implemented and tested on several IEEE bus test systems. The results show that the proposed method is capable of predicting approximate optimal size of DG when compared with precision calculations. The method that linearizes a complex model showed a good result, which can actually reduce processing time required. The acceptable accuracy with less time and memory required can help the grid operator to assess power system integrated within large-scale distribution generation.

Experimental performance assessment of the sub-band minimum variance beamformer for ultrasound imaging

DEFF Research Database (Denmark)

Diamantis, Konstantinos; Greenaway, Alan H.; Anderson, Tom

2017-01-01

Recent progress in adaptive beamforming techniques for medical ultrasound has shown that current resolution limits can be surpassed. One method of obtaining improved lateral resolution is the Minimum Variance (MV) beamformer. The frequency domain implementation of this method effectively divides...... the broadband ultrasound signals into sub-bands (MVS) to conform with the narrow-band assumption of the original MV theory. This approach is investigated here using experimental Synthetic Aperture (SA) data from wire and cyst phantoms. A 7 MHz linear array transducer is used with the SARUS experimental...

Reconciling the Log-Linear and Non-Log-Linear Nature of the TSH-Free T4 Relationship: Intra-Individual Analysis of a Large Population.

Science.gov (United States)

Rothacker, Karen M; Brown, Suzanne J; Hadlow, Narelle C; Wardrop, Robert; Walsh, John P

2016-03-01

The TSH-T4 relationship was thought to be inverse log-linear, but recent cross-sectional studies report a complex, nonlinear relationship; large, intra-individual studies are lacking. Our objective was to analyze the TSH-free T4 relationship within individuals. We analyzed data from 13 379 patients, each with six or more TSH/free T4 measurements and at least a 5-fold difference between individual median TSH and minimum or maximum TSH. Linear and nonlinear regression models of log TSH on free T4 were fitted to data from individuals and goodness of fit compared by likelihood ratio testing. Comparing all models, the linear model achieved best fit in 31% of individuals, followed by quartic (27%), cubic (15%), null (12%), and quadratic (11%) models. After eliminating least favored models (with individuals reassigned to best fitting, available models), the linear model fit best in 42% of participants, quartic in 43%, and null model in 15%. As the number of observations per individual increased, so did the proportion of individuals in whom the linear model achieved best fit, to 66% in those with more than 20 observations. When linear models were applied to all individuals and averaged according to individual median free T4 values, variations in slope and intercept indicated a nonlinear log TSH-free T4 relationship across the population. The log TSH-free T4 relationship appears linear in some individuals and nonlinear in others, but is predominantly linear in those with the largest number of observations. A log-linear relationship within individuals can be reconciled with a non-log-linear relationship in a population.

A Dantzig-Wolfe decomposition algorithm for linear economic model predictive control of dynamically decoupled subsystems

DEFF Research Database (Denmark)

Sokoler, Leo Emil; Standardi, Laura; Edlund, Kristian

2014-01-01

This paper presents a warm-started Dantzig–Wolfe decomposition algorithm tailored to economic model predictive control of dynamically decoupled subsystems. We formulate the constrained optimal control problem solved at each sampling instant as a linear program with state space constraints, input...... limits, input rate limits, and soft output limits. The objective function of the linear program is related directly to the cost of operating the subsystems, and the cost of violating the soft output constraints. Simulations for large-scale economic power dispatch problems show that the proposed algorithm...... is significantly faster than both state-of-the-art linear programming solvers, and a structure exploiting implementation of the alternating direction method of multipliers. It is also demonstrated that the control strategy presented in this paper can be tuned using a weighted ℓ1-regularization term...

A Theoretically Consistent Method for Minimum Mean-Square Error Estimation of Mel-Frequency Cepstral Features

DEFF Research Database (Denmark)

Jensen, Jesper; Tan, Zheng-Hua

2014-01-01

We propose a method for minimum mean-square error (MMSE) estimation of mel-frequency cepstral features for noise robust automatic speech recognition (ASR). The method is based on a minimum number of well-established statistical assumptions; no assumptions are made which are inconsistent with others....... The strength of the proposed method is that it allows MMSE estimation of mel-frequency cepstral coefficients (MFCC's), cepstral mean-subtracted MFCC's (CMS-MFCC's), velocity, and acceleration coefficients. Furthermore, the method is easily modified to take into account other compressive non-linearities than...... the logarithmic which is usually used for MFCC computation. The proposed method shows estimation performance which is identical to or better than state-of-the-art methods. It further shows comparable ASR performance, where the advantage of being able to use mel-frequency speech features based on a power non...

Active constrained layer damping of geometrically nonlinear vibrations of functionally graded plates using piezoelectric fiber-reinforced composites

International Nuclear Information System (INIS)

Panda, Satyajit; Ray, M C

2008-01-01

In this paper, a geometrically nonlinear dynamic analysis has been presented for functionally graded (FG) plates integrated with a patch of active constrained layer damping (ACLD) treatment and subjected to a temperature field. The constraining layer of the ACLD treatment is considered to be made of the piezoelectric fiber-reinforced composite (PFRC) material. The temperature field is assumed to be spatially uniform over the substrate plate surfaces and varied through the thickness of the host FG plates. The temperature-dependent material properties of the FG substrate plates are assumed to be graded in the thickness direction of the plates according to a power-law distribution while the Poisson's ratio is assumed to be a constant over the domain of the plate. The constrained viscoelastic layer of the ACLD treatment is modeled using the Golla–Hughes–McTavish (GHM) method. Based on the first-order shear deformation theory, a three-dimensional finite element model has been developed to model the open-loop and closed-loop nonlinear dynamics of the overall FG substrate plates under the thermal environment. The analysis suggests the potential use of the ACLD treatment with its constraining layer made of the PFRC material for active control of geometrically nonlinear vibrations of FG plates in the absence or the presence of the temperature gradient across the thickness of the plates. It is found that the ACLD treatment is more effective in controlling the geometrically nonlinear vibrations of FG plates than in controlling their linear vibrations. The analysis also reveals that the ACLD patch is more effective for controlling the nonlinear vibrations of FG plates when it is attached to the softest surface of the FG plates than when it is bonded to the stiffest surface of the plates. The effect of piezoelectric fiber orientation in the active constraining PFRC layer on the damping characteristics of the overall FG plates is also discussed

Active constrained layer damping of geometrically nonlinear vibrations of functionally graded plates using piezoelectric fiber-reinforced composites

Science.gov (United States)

Panda, Satyajit; Ray, M. C.

2008-04-01

In this paper, a geometrically nonlinear dynamic analysis has been presented for functionally graded (FG) plates integrated with a patch of active constrained layer damping (ACLD) treatment and subjected to a temperature field. The constraining layer of the ACLD treatment is considered to be made of the piezoelectric fiber-reinforced composite (PFRC) material. The temperature field is assumed to be spatially uniform over the substrate plate surfaces and varied through the thickness of the host FG plates. The temperature-dependent material properties of the FG substrate plates are assumed to be graded in the thickness direction of the plates according to a power-law distribution while the Poisson's ratio is assumed to be a constant over the domain of the plate. The constrained viscoelastic layer of the ACLD treatment is modeled using the Golla-Hughes-McTavish (GHM) method. Based on the first-order shear deformation theory, a three-dimensional finite element model has been developed to model the open-loop and closed-loop nonlinear dynamics of the overall FG substrate plates under the thermal environment. The analysis suggests the potential use of the ACLD treatment with its constraining layer made of the PFRC material for active control of geometrically nonlinear vibrations of FG plates in the absence or the presence of the temperature gradient across the thickness of the plates. It is found that the ACLD treatment is more effective in controlling the geometrically nonlinear vibrations of FG plates than in controlling their linear vibrations. The analysis also reveals that the ACLD patch is more effective for controlling the nonlinear vibrations of FG plates when it is attached to the softest surface of the FG plates than when it is bonded to the stiffest surface of the plates. The effect of piezoelectric fiber orientation in the active constraining PFRC layer on the damping characteristics of the overall FG plates is also discussed.

Constrained noninformative priors

International Nuclear Information System (INIS)

Atwood, C.L.

1994-10-01

The Jeffreys noninformative prior distribution for a single unknown parameter is the distribution corresponding to a uniform distribution in the transformed model where the unknown parameter is approximately a location parameter. To obtain a prior distribution with a specified mean but with diffusion reflecting great uncertainty, a natural generalization of the noninformative prior is the distribution corresponding to the constrained maximum entropy distribution in the transformed model. Examples are given

30 CFR 77.1431 - Minimum rope strength.

Science.gov (United States)

2010-07-01

... feet: Minimum Value=Static Load×(7.0−0.001L) For rope lengths 3,000 feet or greater: Minimum Value=Static Load×4.0 (b) Friction drum ropes. For rope lengths less than 4,000 feet: Minimum Value=Static Load×(7.0−0.0005L) For rope lengths 4,000 feet or greater: Minimum Value=Static Load×5.0 (c) Tail ropes...

Solving project scheduling problems by minimum cut computations

NARCIS (Netherlands)

Möhring, R.H.; Schulz, A.S.; Stork, F.; Uetz, Marc Jochen

In project scheduling, a set of precedence-constrained jobs has to be scheduled so as to minimize a given objective. In resource-constrained project scheduling, the jobs additionally compete for scarce resources. Due to its universality, the latter problem has a variety of applications in

A Phosphate Minimum in the Oxygen Minimum Zone (OMZ) off Peru

Science.gov (United States)

Paulmier, A.; Giraud, M.; Sudre, J.; Jonca, J.; Leon, V.; Moron, O.; Dewitte, B.; Lavik, G.; Grasse, P.; Frank, M.; Stramma, L.; Garcon, V.

2016-02-01

The Oxygen Minimum Zone (OMZ) off Peru is known to be associated with the advection of Equatorial SubSurface Waters (ESSW), rich in nutrients and poor in oxygen, through the Peru-Chile UnderCurrent (PCUC), but this circulation remains to be refined within the OMZ. During the Pelágico cruise in November-December 2010, measurements of phosphate revealed the presence of a phosphate minimum (Pmin) in various hydrographic stations, which could not be explained so far and could be associated with a specific water mass. This Pmin, localized at a relatively constant layer ( 20minimum with a mean vertical phosphate decrease of 0.6 µM but highly variable between 0.1 and 2.2 µM. In average, these Pmin are associated with a predominant mixing of SubTropical Under- and Surface Waters (STUW and STSW: 20 and 40%, respectively) within ESSW ( 25%), complemented evenly by overlying (ESW, TSW: 8%) and underlying waters (AAIW, SPDW: 7%). The hypotheses and mechanisms leading to the Pmin formation in the OMZ are further explored and discussed, considering the physical regional contribution associated with various circulation pathways ventilating the OMZ and the local biogeochemical contribution including the potential diazotrophic activity.

The impact of initialization procedures on unsupervised unmixing of hyperspectral imagery using the constrained positive matrix factorization

Science.gov (United States)

Masalmah, Yahya M.; Vélez-Reyes, Miguel

2007-04-01

The authors proposed in previous papers the use of the constrained Positive Matrix Factorization (cPMF) to perform unsupervised unmixing of hyperspectral imagery. Two iterative algorithms were proposed to compute the cPMF based on the Gauss-Seidel and penalty approaches to solve optimization problems. Results presented in previous papers have shown the potential of the proposed method to perform unsupervised unmixing in HYPERION and AVIRIS imagery. The performance of iterative methods is highly dependent on the initialization scheme. Good initialization schemes can improve convergence speed, whether or not a global minimum is found, and whether or not spectra with physical relevance are retrieved as endmembers. In this paper, different initializations using random selection, longest norm pixels, and standard endmembers selection routines are studied and compared using simulated and real data.

Implementing nonprojective measurements via linear optics: An approach based on optimal quantum-state discrimination

International Nuclear Information System (INIS)

Loock, Peter van; Nemoto, Kae; Munro, William J.; Raynal, Philippe; Luetkenhaus, Norbert

2006-01-01

We discuss the problem of implementing generalized measurements [positive operator-valued measures (POVMs)] with linear optics, either based upon a static linear array or including conditional dynamics. In our approach, a given POVM shall be identified as a solution to an optimization problem for a chosen cost function. We formulate a general principle: the implementation is only possible if a linear-optics circuit exists for which the quantum mechanical optimum (minimum) is still attainable after dephasing the corresponding quantum states. The general principle enables us, for instance, to derive a set of necessary conditions for the linear-optics implementation of the POVM that realizes the quantum mechanically optimal unambiguous discrimination of two pure nonorthogonal states. This extends our previous results on projection measurements and the exact discrimination of orthogonal states

Double vector meson production in the International Linear Collider

Energy Technology Data Exchange (ETDEWEB)

Carvalho, F. [Universidade Federal de Sao Paulo, Departamento de Ciencias Exatas e da Terra, Diadema, SP (Brazil); Goncalves, V.P. [Universidade Federal de Pelotas, High and Medium Energy Group, Instituto de Fisica e Matematica, Caixa Postal 354, Pelotas, RS (Brazil); Moreira, B.D.; Navarra, F.S. [Universidade de Sao Paulo, Instituto de Fisica, C.P. 66318, Sao Paulo, SP (Brazil)

2015-08-15

In this paper we study double vector meson production in γγ interactions at high energies and estimate, using the color dipole picture, the main observables which can be probed at the International Linear Collider (ILC). The total γ(Q{sub 1}{sup 2}) + γ(Q{sub 2}{sup 2}) → V{sub 1} + V{sub 2} cross sections for V{sub i} = ρ, J/ψ, and Υ are computed and the energy and virtuality dependencies are studied in detail. Our results demonstrate that the experimental analysis of this process is feasible at the ILC and it can be useful to constrain the QCD dynamics at high energies. (orig.)

Ad Hoc Microphone Array Beamforming Using the Primal-Dual Method of Multipliers

DEFF Research Database (Denmark)

Tavakoli, Vincent Mohammad; Jensen, Jesper Rindom; Heusdens, Richard

2016-01-01

In the recent years, there have been increasing amount of researches aiming at optimal beamforming with ad hoc microphone arrays, mostly with fusion-based schemes. However, huge amount of computational complexity and communication overhead impede many of these algorithms from being useful in prac...... the distributed linearly-constrained minimum variance beamformer using the the state of the art primal-dual method of multipliers. We study the proposed algorithm with an experiment....

EEG source reconstruction reveals frontal-parietal dynamics of spatial conflict processing

OpenAIRE

Cohen, M.X.; Ridderinkhof, K.R.

2013-01-01

Cognitive control requires the suppression of distracting information in order to focus on task-relevant information. We applied EEG source reconstruction via time-frequency linear constrained minimum variance beamforming to help elucidate the neural mechanisms involved in spatial conflict processing. Human subjects performed a Simon task, in which conflict was induced by incongruence between spatial location and response hand. We found an early (?200 ms post-stimulus) conflict modulation in ...

Age of Barrier Canyon-style rock art constrained by cross-cutting relations and luminescence dating techniques

DEFF Research Database (Denmark)

Pederson, Joel L.; Chapot, Melissa S.; Simms, Steven R.

2014-01-01

Rock art compels interest from both researchers and a broader public, inspiring many hypotheses about its cultural origin and meaning, but it is notoriously difficult to date numerically. Barrier Canyon-style (BCS) pictographs of the Colorado Plateau are among the most debated examples; hypotheses......, the type section of BCS art in Canyon-lands National Park, southeastern Utah. Alluvial chronostratigraphy constrains the burial and exhumation of the alcove containing the panel, and limits are also set by our related research dating both a rockfall that removed some figures and the rock's exposure...... duration before that time. Results provide a maximum possible age, a minimum age, and an exposure time window for the creation of the Great Gallery panel, respectively. The only prior hypothesis not disproven is a late Archaic origin for BCS rock art, although our age result of A. D. similar to 1...

Improving boiler unit performance using an optimum robust minimum-order observer

International Nuclear Information System (INIS)

Moradi, Hamed; Bakhtiari-Nejad, Firooz

2011-01-01

Research highlights: → Multivariable model of a boiler unit with uncertainty. → Design of a robust minimum-order observer. → Developing an optimal functional code in MATLAB environment. → Finding optimum region of observer-based controller poles. → Guarantee of robust performance in the presence of parametric uncertainties. - Abstract: To achieve a good performance of the utility boiler, dynamic variables such as drum pressure, steam temperature and water level of drum must be controlled. In this paper, a linear time invariant (LTI) model of a boiler system is considered in which the input variables are feed-water and fuel mass rates. Due to the inaccessibility of some state variables of boiler system, a minimum-order observer is designed based on Luenberger's model to gain an estimate state x-tilde of the true state x. Low cost of design and high accuracy of states estimation are the main advantages of the minimum-order observer; in comparison with previous designed full-order observers. By applying the observer on the closed-loop system, a regulator system is designed. Using an optimal functional code developed in MATLAB environment, desired observer poles are found such that suitable time response specifications of the boiler system are achieved and the gain and phase margin values are adjusted in an acceptable range. However, the real dynamic model may associate with parametric uncertainties. In that case, optimum region of poles of observer-based controller are found such that the robust performance of the boiler system against model uncertainties is guaranteed.

A novel approach based on preference-based index for interval bilevel linear programming problem

OpenAIRE

Aihong Ren; Yuping Wang; Xingsi Xue

2017-01-01

This paper proposes a new methodology for solving the interval bilevel linear programming problem in which all coefficients of both objective functions and constraints are considered as interval numbers. In order to keep as much uncertainty of the original constraint region as possible, the original problem is first converted into an interval bilevel programming problem with interval coefficients in both objective functions only through normal variation of interval number and chance-constrain...

Adaptive Finite Element Method for Optimal Control Problem Governed by Linear Quasiparabolic Integrodifferential Equations

Directory of Open Access Journals (Sweden)

Wanfang Shen

2012-01-01

Full Text Available The mathematical formulation for a quadratic optimal control problem governed by a linear quasiparabolic integrodifferential equation is studied. The control constrains are given in an integral sense: Uad={u∈X;∫ΩUu⩾0, t∈[0,T]}. Then the a posteriori error estimates in L∞(0,T;H1(Ω-norm and L2(0,T;L2(Ω-norm for both the state and the control approximation are given.

A separation theorem for the stochastic sampled-data LQG problem. [control of continuous linear plant disturbed by white noise

Science.gov (United States)

Halyo, N.; Caglayan, A. K.

1976-01-01

This paper considers the control of a continuous linear plant disturbed by white plant noise when the control is constrained to be a piecewise constant function of time; i.e. a stochastic sampled-data system. The cost function is the integral of quadratic error terms in the state and control, thus penalizing errors at every instant of time while the plant noise disturbs the system continuously. The problem is solved by reducing the constrained continuous problem to an unconstrained discrete one. It is shown that the separation principle for estimation and control still holds for this problem when the plant disturbance and measurement noise are Gaussian.

A less-constrained (2,0) super-Yang-Mills model: the coupling to non-linear σ-models

International Nuclear Information System (INIS)

Almeida, C.A.S.; Doria, R.M.

1990-01-01

Considering a class of (2,0) super-Yang-Mills multiplets characterised by the appearance of a pair of independent gauge potentials, we present here their coupling to non-linear σ-models in (2,0)-superspace. Contrary to the case of the coupling to (2,0) matter superfields, the extra gauge potential present in the Yang-Mills sector does not decouple from the theory in the case one gauges isometry groups of σ-models. (author)

Statistical mechanical analysis of linear programming relaxation for combinatorial optimization problems

Science.gov (United States)

Takabe, Satoshi; Hukushima, Koji

2016-05-01

Typical behavior of the linear programming (LP) problem is studied as a relaxation of the minimum vertex cover (min-VC), a type of integer programming (IP) problem. A lattice-gas model on the Erdös-Rényi random graphs of α -uniform hyperedges is proposed to express both the LP and IP problems of the min-VC in the common statistical mechanical model with a one-parameter family. Statistical mechanical analyses reveal for α =2 that the LP optimal solution is typically equal to that given by the IP below the critical average degree c =e in the thermodynamic limit. The critical threshold for good accuracy of the relaxation extends the mathematical result c =1 and coincides with the replica symmetry-breaking threshold of the IP. The LP relaxation for the minimum hitting sets with α ≥3 , minimum vertex covers on α -uniform random graphs, is also studied. Analytic and numerical results strongly suggest that the LP relaxation fails to estimate optimal values above the critical average degree c =e /(α -1 ) where the replica symmetry is broken.

Statistical mechanical analysis of linear programming relaxation for combinatorial optimization problems.

Science.gov (United States)

Takabe, Satoshi; Hukushima, Koji

2016-05-01

Typical behavior of the linear programming (LP) problem is studied as a relaxation of the minimum vertex cover (min-VC), a type of integer programming (IP) problem. A lattice-gas model on the Erdös-Rényi random graphs of α-uniform hyperedges is proposed to express both the LP and IP problems of the min-VC in the common statistical mechanical model with a one-parameter family. Statistical mechanical analyses reveal for α=2 that the LP optimal solution is typically equal to that given by the IP below the critical average degree c=e in the thermodynamic limit. The critical threshold for good accuracy of the relaxation extends the mathematical result c=1 and coincides with the replica symmetry-breaking threshold of the IP. The LP relaxation for the minimum hitting sets with α≥3, minimum vertex covers on α-uniform random graphs, is also studied. Analytic and numerical results strongly suggest that the LP relaxation fails to estimate optimal values above the critical average degree c=e/(α-1) where the replica symmetry is broken.

A Unique Technique to get Kaprekar Iteration in Linear Programming Problem

Science.gov (United States)

Sumathi, P.; Preethy, V.

2018-04-01

This paper explores about a frivolous number popularly known as Kaprekar constant and Kaprekar numbers. A large number of courses and the different classroom capacities with difference in study periods make the assignment between classrooms and courses complicated. An approach of getting the minimum value of number of iterations to reach the Kaprekar constant for four digit numbers and maximum value is also obtained through linear programming techniques.

Evaluation of Forest Dynamics Focusing on Various Minimum Harvesting Ages in Multi-Purpose Forest Management Planning

Directory of Open Access Journals (Sweden)

Derya Mumcu Kucuker

2015-04-01

Full Text Available Aim of study: Exploring the potential effects of various forest management strategies on the ability of forest ecosystems to sequester carbon and produce water has become of great concern among forest researchers. The main purpose of this study is to evaluate the effects of management strategies with different minimum harvesting ages on the amount and monetary worth of carbon, water and timber values. Area of study: The study was performed in the Yalnızçam planning unit located on the northeastern part of Turkey. Material and Methods: A forest management model with linear programming (LP was developed to determine the effects of various minimum harvesting ages. Twenty-four different management strategies were developed to maximize the economic Net Present Value (NPV of timber, water and carbon values in addition to their absolute quantities over time. Amount and NPV of forest values and ending inventory with different minimum harvesting ages were used as performance indicators to assess and thus understand forest dynamics. Main results: Amount and NPV of timber and carbon generally decreased with extended minimum harvesting ages. However, similar trends were not observed for water production values. The results pointed out that the performance of a management strategy depends highly on the development of a management strategy and the initial forest structure aside from the growth rate Research highlights: Minimum harvesting ages affect forest outputs under the same objectives and constraints. Performance of a management strategy highly depends on initial age class structure in addition to the contents of a management strategy.

12 CFR 564.4 - Minimum appraisal standards.

Science.gov (United States)

2010-01-01

... 12 Banks and Banking 5 2010-01-01 2010-01-01 false Minimum appraisal standards. 564.4 Section 564.4 Banks and Banking OFFICE OF THRIFT SUPERVISION, DEPARTMENT OF THE TREASURY APPRAISALS § 564.4 Minimum appraisal standards. For federally related transactions, all appraisals shall, at a minimum: (a...

The minimum wage in the Czech enterprises

OpenAIRE

Eva Lajtkepová

2010-01-01

Although the statutory minimum wage is not a new category, in the Czech Republic we encounter the definition and regulation of a minimum wage for the first time in the 1990 amendment to Act No. 65/1965 Coll., the Labour Code. The specific amount of the minimum wage and the conditions of its operation were then subsequently determined by government regulation in February 1991. Since that time, the value of minimum wage has been adjusted fifteenth times (the last increase was in January 2007). ...

Factorization of Constrained Energy K-Network Reliability with Perfect Nodes

OpenAIRE

Burgos, Juan Manuel

2013-01-01

This paper proves a new general K-network constrained energy reliability global factorization theorem. As in the unconstrained case, beside its theoretical mathematical importance the theorem shows how to do parallel processing in exact network constrained energy reliability calculations in order to reduce the processing time of this NP-hard problem. Followed by a new simple factorization formula for its calculation, we propose a new definition of constrained energy network reliability motiva...

Minimum Wages and Regional Disparity: An analysis on the evolution of price-adjusted minimum wages and their effects on firm profitability (Japanese)

OpenAIRE

MORIKAWA Masayuki

2013-01-01

This paper, using prefecture level panel data, empirically analyzes 1) the recent evolution of price-adjusted regional minimum wages and 2) the effects of minimum wages on firm profitability. As a result of rapid increases in minimum wages in the metropolitan areas since 2007, the regional disparity of nominal minimum wages has been widening. However, the disparity of price-adjusted minimum wages has been shrinking. According to the analysis of the effects of minimum wages on profitability us...

CONSTRAINED EVOLUTION OF A RADIALLY MAGNETIZED PROTOPLANETARY DISK: IMPLICATIONS FOR PLANETARY MIGRATION

Energy Technology Data Exchange (ETDEWEB)

Russo, Matthew [Department of Physics, University of Toronto, 60 St. George St., Toronto, ON M5S 1A7 (Canada); Thompson, Christopher [Canadian Institute for Theoretical Astrophysics, 60 St. George St., Toronto, ON M5S 3H8 (Canada)

2015-12-10

We consider the inner ∼1 AU of a protoplanetary disk (PPD) at a stage where angular momentum transport is driven by the mixing of a radial magnetic field into the disk from a T Tauri wind. Because the radial profile of the imposed magnetic field is well constrained, a constrained calculation of the disk mass flow becomes possible. The vertical disk profiles obtained in Paper I imply a stronger magnetization in the inner disk, faster accretion, and a secular depletion of the disk material. Inward transport of solids allows the disk to maintain a broad optical absorption layer even when the grain abundance becomes too small to suppress its ionization. Thus, a PPD may show a strong mid- to near-infrared spectral excess even while its mass profile departs radically from the minimum-mass solar nebula. The disk surface density is buffered at ∼30 g cm{sup −2}; below this, X-rays trigger magnetorotational turbulence at the midplane strong enough to loft millimeter- to centimeter-sized particles high in the disk, followed by catastrophic fragmentation. A sharp density gradient bounds the inner depleted disk and propagates outward to ∼1–2 AU over a few megayears. Earth-mass planets migrate through the inner disk over a similar timescale, whereas the migration of Jupiters is limited by the supply of gas. Gas-mediated migration must stall outside 0.04 AU, where silicates are sublimated and the disk shifts to a much lower column. A transition disk emerges when the dust/gas ratio in the MRI-active layer falls below X{sub d} ∼ 10{sup −6} (a{sub d}/μm), where a{sub d} is the grain size.

Minimum Lens Size Supporting the Leaky-Wave Nature of Slit Dipole Antenna at Terahertz Frequency

Directory of Open Access Journals (Sweden)

Niamat Hussain

2016-01-01

Full Text Available We designed a slit dipole antenna backed by an extended hemispherical silicon lens and investigated the minimum lens size in which the slit dipole antenna works as a leaky-wave antenna. The slit dipole antenna consists of a planar feeding structure, which is a center-fed and open-ended slot line. A slit dipole antenna backed by an extended hemispherical silicon lens is investigated over a frequency range from 0.2 to 0.4 THz with the center frequency at 0.3 THz. The numerical results show that the antenna gain responses exhibited an increased level of sensitivity to the lens size and increased linearly with increasing lens radius. The lens with the radius of 1.2λo is found to be the best possible minimum lens size for a slit dipole antenna on an extended hemispherical silicon lens.

An ILP based memetic algorithm for finding minimum positive influence dominating sets in social networks

Science.gov (United States)

Lin, Geng; Guan, Jian; Feng, Huibin

2018-06-01

The positive influence dominating set problem is a variant of the minimum dominating set problem, and has lots of applications in social networks. It is NP-hard, and receives more and more attention. Various methods have been proposed to solve the positive influence dominating set problem. However, most of the existing work focused on greedy algorithms, and the solution quality needs to be improved. In this paper, we formulate the minimum positive influence dominating set problem as an integer linear programming (ILP), and propose an ILP based memetic algorithm (ILPMA) for solving the problem. The ILPMA integrates a greedy randomized adaptive construction procedure, a crossover operator, a repair operator, and a tabu search procedure. The performance of ILPMA is validated on nine real-world social networks with nodes up to 36,692. The results show that ILPMA significantly improves the solution quality, and is robust.

Linear CMOS RF power amplifiers a complete design workflow

CERN Document Server

Ruiz, Hector Solar

2013-01-01

The work establishes the design flow for the optimization of linear CMOS power amplifiers from the first steps of the design to the final IC implementation and tests. The authors also focuses on design guidelines of the inductor's geometrical characteristics for power applications and covers their measurement and characterization. Additionally, a model is proposed which would facilitate designs in terms of transistor sizing, required inductor quality factors or minimum supply voltage. The model considers limitations that CMOS processes can impose on implementation. The book also provides diffe

41 CFR 50-201.1101 - Minimum wages.

Science.gov (United States)

2010-07-01

... 41 Public Contracts and Property Management 1 2010-07-01 2010-07-01 true Minimum wages. 50-201... Contracts PUBLIC CONTRACTS, DEPARTMENT OF LABOR 201-GENERAL REGULATIONS § 50-201.1101 Minimum wages. Determinations of prevailing minimum wages or changes therein will be published in the Federal Register by the...

Trends in PDE constrained optimization

CERN Document Server

Benner, Peter; Engell, Sebastian; Griewank, Andreas; Harbrecht, Helmut; Hinze, Michael; Rannacher, Rolf; Ulbrich, Stefan

2014-01-01

Optimization problems subject to constraints governed by partial differential equations (PDEs) are among the most challenging problems in the context of industrial, economical and medical applications. Almost the entire range of problems in this field of research was studied and further explored as part of the Deutsche Forschungsgemeinschaft (DFG) priority program 1253 on “Optimization with Partial Differential Equations” from 2006 to 2013. The investigations were motivated by the fascinating potential applications and challenging mathematical problems that arise in the field of PDE constrained optimization. New analytic and algorithmic paradigms have been developed, implemented and validated in the context of real-world applications. In this special volume, contributions from more than fifteen German universities combine the results of this interdisciplinary program with a focus on applied mathematics.   The book is divided into five sections on “Constrained Optimization, Identification and Control”...

Constrained superfields in supergravity

Energy Technology Data Exchange (ETDEWEB)

Dall’Agata, Gianguido; Farakos, Fotis [Dipartimento di Fisica ed Astronomia “Galileo Galilei”, Università di Padova,Via Marzolo 8, 35131 Padova (Italy); INFN, Sezione di Padova,Via Marzolo 8, 35131 Padova (Italy)

2016-02-16

We analyze constrained superfields in supergravity. We investigate the consistency and solve all known constraints, presenting a new class that may have interesting applications in the construction of inflationary models. We provide the superspace Lagrangians for minimal supergravity models based on them and write the corresponding theories in component form using a simplifying gauge for the goldstino couplings.

Bounds and maximum principles for the solution of the linear transport equation

International Nuclear Information System (INIS)

Larsen, E.W.

1981-01-01

Pointwise bounds are derived for the solution of time-independent linear transport problems with surface sources in convex spatial domains. Under specified conditions, upper bounds are derived which, as a function of position, decrease with distance from the boundary. Also, sufficient conditions are obtained for the existence of maximum and minimum principles, and a counterexample is given which shows that such principles do not always exist

A Chance-Constrained Economic Dispatch Model in Wind-Thermal-Energy Storage System

Directory of Open Access Journals (Sweden)

Yanzhe Hu

2017-03-01

Full Text Available As a type of renewable energy, wind energy is integrated into the power system with more and more penetration levels. It is challenging for the power system operators (PSOs to cope with the uncertainty and variation of the wind power and its forecasts. A chance-constrained economic dispatch (ED model for the wind-thermal-energy storage system (WTESS is developed in this paper. An optimization model with the wind power and the energy storage system (ESS is first established with the consideration of both the economic benefits of the system and less wind curtailments. The original wind power generation is processed by the ESS to obtain the final wind power output generation (FWPG. A Gaussian mixture model (GMM distribution is adopted to characterize the probabilistic and cumulative distribution functions with an analytical expression. Then, a chance-constrained ED model integrated by the wind-energy storage system (W-ESS is developed by considering both the overestimation costs and the underestimation costs of the system and solved by the sequential linear programming method. Numerical simulation results using the wind power data in four wind farms are performed on the developed ED model with the IEEE 30-bus system. It is verified that the developed ED model is effective to integrate the uncertain and variable wind power. The GMM distribution could accurately fit the actual distribution of the final wind power output, and the ESS could help effectively decrease the operation costs.

Minimum Wage Laws and the Distribution of Employment.

Science.gov (United States)

Lang, Kevin

The desirability of raising the minimum wage long revolved around just one question: the effect of higher minimum wages on the overall level of employment. An even more critical effect of the minimum wage rests on the composition of employment--who gets the minimum wage job. An examination of employment in eating and drinking establishments…

Cross-constrained problems for nonlinear Schrodinger equation with harmonic potential

Directory of Open Access Journals (Sweden)

Runzhang Xu

2012-11-01

Full Text Available This article studies a nonlinear Schodinger equation with harmonic potential by constructing different cross-constrained problems. By comparing the different cross-constrained problems, we derive different sharp criterion and different invariant manifolds that separate the global solutions and blowup solutions. Moreover, we conclude that some manifolds are empty due to the essence of the cross-constrained problems. Besides, we compare the three cross-constrained problems and the three depths of the potential wells. In this way, we explain the gaps in [J. Shu and J. Zhang, Nonlinear Shrodinger equation with harmonic potential, Journal of Mathematical Physics, 47, 063503 (2006], which was pointed out in [R. Xu and Y. Liu, Remarks on nonlinear Schrodinger equation with harmonic potential, Journal of Mathematical Physics, 49, 043512 (2008].

29 CFR 505.3 - Prevailing minimum compensation.

Science.gov (United States)

2010-07-01

... 29 Labor 3 2010-07-01 2010-07-01 false Prevailing minimum compensation. 505.3 Section 505.3 Labor... HUMANITIES § 505.3 Prevailing minimum compensation. (a)(1) In the absence of an alternative determination...)(2) of this section, the prevailing minimum compensation required to be paid under the Act to the...

Positioning of the rf potential minimum line of a linear Paul trap with micrometer precision

DEFF Research Database (Denmark)

Herskind, Peter Fønss; Dantan, Aurélien; Albert, Magnus

2009-01-01

We demonstrate a general technique to achieve a precise radial displacement of the nodal line of the radiofrequency (rf) field in a linear Paul trap. The technique relies on the selective adjustment of the load capacitance of the trap electrodes, achieved through the addition of capacitors...... to the basic resonant rf circuit used to drive the trap. Displacements of up to ~100 µm with micrometer precision are measured using a combination of fluorescence images of ion Coulomb crystals and coherent coupling of such crystals to a mode of an optical cavity. The displacements are made without measurable...

Characterization of the International Linear Collider damping ring optics

Science.gov (United States)

Shanks, J.; Rubin, D. L.; Sagan, D.

2014-10-01

A method is presented for characterizing the emittance dilution and dynamic aperture for an arbitrary closed lattice that includes guide field magnet errors, multipole errors and misalignments. This method, developed and tested at the Cornell Electron Storage Ring Test Accelerator (CesrTA), has been applied to the damping ring lattice for the International Linear Collider (ILC). The effectiveness of beam based emittance tuning is limited by beam position monitor (BPM) measurement errors, number of corrector magnets and their placement, and correction algorithm. The specifications for damping ring magnet alignment, multipole errors, number of BPMs, and precision in BPM measurements are shown to be consistent with the required emittances and dynamic aperture. The methodology is then used to determine the minimum number of position monitors that is required to achieve the emittance targets, and how that minimum depends on the location of the BPMs. Similarly, the maximum tolerable multipole errors are evaluated. Finally, the robustness of each BPM configuration with respect to random failures is explored.

In vitro transcription of a torsionally constrained template

DEFF Research Database (Denmark)

Bentin, Thomas; Nielsen, Peter E

2002-01-01

RNA polymerase (RNAP) and the DNA template must rotate relative to each other during transcription elongation. In the cell, however, the components of the transcription apparatus may be subject to rotary constraints. For instance, the DNA is divided into topological domains that are delineated...... of torsionally constrained DNA by free RNAP. We asked whether or not a newly synthesized RNA chain would limit transcription elongation. For this purpose we developed a method to immobilize covalently closed circular DNA to streptavidin-coated beads via a peptide nucleic acid (PNA)-biotin conjugate in principle...... constrained. We conclude that transcription of a natural bacterial gene may proceed with high efficiency despite the fact that newly synthesized RNA is entangled around the template in the narrow confines of torsionally constrained supercoiled DNA....

Terrestrial Sagnac delay constraining modified gravity models

Science.gov (United States)

Karimov, R. Kh.; Izmailov, R. N.; Potapov, A. A.; Nandi, K. K.

2018-04-01

Modified gravity theories include f(R)-gravity models that are usually constrained by the cosmological evolutionary scenario. However, it has been recently shown that they can also be constrained by the signatures of accretion disk around constant Ricci curvature Kerr-f(R0) stellar sized black holes. Our aim here is to use another experimental fact, viz., the terrestrial Sagnac delay to constrain the parameters of specific f(R)-gravity prescriptions. We shall assume that a Kerr-f(R0) solution asymptotically describes Earth's weak gravity near its surface. In this spacetime, we shall study oppositely directed light beams from source/observer moving on non-geodesic and geodesic circular trajectories and calculate the time gap, when the beams re-unite. We obtain the exact time gap called Sagnac delay in both cases and expand it to show how the flat space value is corrected by the Ricci curvature, the mass and the spin of the gravitating source. Under the assumption that the magnitude of corrections are of the order of residual uncertainties in the delay measurement, we derive the allowed intervals for Ricci curvature. We conclude that the terrestrial Sagnac delay can be used to constrain the parameters of specific f(R) prescriptions. Despite using the weak field gravity near Earth's surface, it turns out that the model parameter ranges still remain the same as those obtained from the strong field accretion disk phenomenon.

SLFP: a stochastic linear fractional programming approach for sustainable waste management.

Science.gov (United States)

Zhu, H; Huang, G H

2011-12-01

A stochastic linear fractional programming (SLFP) approach is developed for supporting sustainable municipal solid waste management under uncertainty. The SLFP method can solve ratio optimization problems associated with random information, where chance-constrained programming is integrated into a linear fractional programming framework. It has advantages in: (1) comparing objectives of two aspects, (2) reflecting system efficiency, (3) dealing with uncertainty expressed as probability distributions, and (4) providing optimal-ratio solutions under different system-reliability conditions. The method is applied to a case study of waste flow allocation within a municipal solid waste (MSW) management system. The obtained solutions are useful for identifying sustainable MSW management schemes with maximized system efficiency under various constraint-violation risks. The results indicate that SLFP can support in-depth analysis of the interrelationships among system efficiency, system cost and system-failure risk. Copyright © 2011 Elsevier Ltd. All rights reserved.

A constrained robust least squares approach for contaminant release history identification

Science.gov (United States)

Sun, Alexander Y.; Painter, Scott L.; Wittmeyer, Gordon W.

2006-04-01

Contaminant source identification is an important type of inverse problem in groundwater modeling and is subject to both data and model uncertainty. Model uncertainty was rarely considered in the previous studies. In this work, a robust framework for solving contaminant source recovery problems is introduced. The contaminant source identification problem is first cast into one of solving uncertain linear equations, where the response matrix is constructed using a superposition technique. The formulation presented here is general and is applicable to any porous media flow and transport solvers. The robust least squares (RLS) estimator, which originated in the field of robust identification, directly accounts for errors arising from model uncertainty and has been shown to significantly reduce the sensitivity of the optimal solution to perturbations in model and data. In this work, a new variant of RLS, the constrained robust least squares (CRLS), is formulated for solving uncertain linear equations. CRLS allows for additional constraints, such as nonnegativity, to be imposed. The performance of CRLS is demonstrated through one- and two-dimensional test problems. When the system is ill-conditioned and uncertain, it is found that CRLS gave much better performance than its classical counterpart, the nonnegative least squares. The source identification framework developed in this work thus constitutes a reliable tool for recovering source release histories in real applications.

Do Some Workers Have Minimum Wage Careers?

Science.gov (United States)

Carrington, William J.; Fallick, Bruce C.

2001-01-01

Most workers who begin their careers in minimum-wage jobs eventually gain more experience and move on to higher paying jobs. However, more than 8% of workers spend at least half of their first 10 working years in minimum wage jobs. Those more likely to have minimum wage careers are less educated, minorities, women with young children, and those…

Does the Minimum Wage Affect Welfare Caseloads?

Science.gov (United States)

Page, Marianne E.; Spetz, Joanne; Millar, Jane

2005-01-01

Although minimum wages are advocated as a policy that will help the poor, few studies have examined their effect on poor families. This paper uses variation in minimum wages across states and over time to estimate the impact of minimum wage legislation on welfare caseloads. We find that the elasticity of the welfare caseload with respect to the…

29 CFR 4.159 - General minimum wage.

Science.gov (United States)

2010-07-01

... 29 Labor 1 2010-07-01 2010-07-01 true General minimum wage. 4.159 Section 4.159 Labor Office of... General minimum wage. The Act, in section 2(b)(1), provides generally that no contractor or subcontractor... a contract less than the minimum wage specified under section 6(a)(1) of the Fair Labor Standards...

Constrained principal component analysis and related techniques

CERN Document Server

Takane, Yoshio

2013-01-01

In multivariate data analysis, regression techniques predict one set of variables from another while principal component analysis (PCA) finds a subspace of minimal dimensionality that captures the largest variability in the data. How can regression analysis and PCA be combined in a beneficial way? Why and when is it a good idea to combine them? What kind of benefits are we getting from them? Addressing these questions, Constrained Principal Component Analysis and Related Techniques shows how constrained PCA (CPCA) offers a unified framework for these approaches.The book begins with four concre

PERIOD–COLOR AND AMPLITUDE–COLOR RELATIONS AT MAXIMUM AND MINIMUM LIGHT FOR RR LYRAE STARS IN THE SDSS STRIPE 82 REGION

Energy Technology Data Exchange (ETDEWEB)

Ngeow, Chow-Choong [Graduate Institute of Astronomy, National Central University, Jhongli 32001, Taiwan (China); Kanbur, Shashi M.; Schrecengost, Zachariah [Department of Physics, SUNY Oswego, Oswego, NY 13126 (United States); Bhardwaj, Anupam; Singh, Harinder P. [Department of Physics and Astrophysics, University of Delhi, Delhi 110007 (India)

2017-01-10

Investigation of period–color (PC) and amplitude–color (AC) relations at the maximum and minimum light can be used to probe the interaction of the hydrogen ionization front (HIF) with the photosphere and the radiation hydrodynamics of the outer envelopes of Cepheids and RR Lyraes. For example, theoretical calculations indicated that such interactions would occur at minimum light for RR Lyrae and result in a flatter PC relation. In the past, the PC and AC relations have been investigated by using either the ( V − R ){sub MACHO} or ( V − I ) colors. In this work, we extend previous work to other bands by analyzing the RR Lyraes in the Sloan Digital Sky Survey Stripe 82 Region. Multi-epoch data are available for RR Lyraes located within the footprint of the Stripe 82 Region in five ( ugriz ) bands. We present the PC and AC relations at maximum and minimum light in four colors: ( u − g ){sub 0}, ( g − r ){sub 0}, ( r − i ){sub 0}, and ( i − z ){sub 0}, after they are corrected for extinction. We found that the PC and AC relations for this sample of RR Lyraes show a complex nature in the form of flat, linear or quadratic relations. Furthermore, the PC relations at minimum light for fundamental mode RR Lyrae stars are separated according to the Oosterhoff type, especially in the ( g − r ){sub 0} and ( r − i ){sub 0} colors. If only considering the results from linear regressions, our results are quantitatively consistent with the theory of HIF-photosphere interaction for both fundamental and first overtone RR Lyraes.

Chance-Constrained Guidance With Non-Convex Constraints

Science.gov (United States)

Ono, Masahiro

2011-01-01

Missions to small bodies, such as comets or asteroids, require autonomous guidance for descent to these small bodies. Such guidance is made challenging by uncertainty in the position and velocity of the spacecraft, as well as the uncertainty in the gravitational field around the small body. In addition, the requirement to avoid collision with the asteroid represents a non-convex constraint that means finding the optimal guidance trajectory, in general, is intractable. In this innovation, a new approach is proposed for chance-constrained optimal guidance with non-convex constraints. Chance-constrained guidance takes into account uncertainty so that the probability of collision is below a specified threshold. In this approach, a new bounding method has been developed to obtain a set of decomposed chance constraints that is a sufficient condition of the original chance constraint. The decomposition of the chance constraint enables its efficient evaluation, as well as the application of the branch and bound method. Branch and bound enables non-convex problems to be solved efficiently to global optimality. Considering the problem of finite-horizon robust optimal control of dynamic systems under Gaussian-distributed stochastic uncertainty, with state and control constraints, a discrete-time, continuous-state linear dynamics model is assumed. Gaussian-distributed stochastic uncertainty is a more natural model for exogenous disturbances such as wind gusts and turbulence than the previously studied set-bounded models. However, with stochastic uncertainty, it is often impossible to guarantee that state constraints are satisfied, because there is typically a non-zero probability of having a disturbance that is large enough to push the state out of the feasible region. An effective framework to address robustness with stochastic uncertainty is optimization with chance constraints. These require that the probability of violating the state constraints (i.e., the probability of

LINEAR2007, Linear-Linear Interpolation of ENDF Format Cross-Sections

International Nuclear Information System (INIS)

2007-01-01

1 - Description of program or function: LINEAR converts evaluated cross sections in the ENDF/B format into a tabular form that is subject to linear-linear interpolation in energy and cross section. The code also thins tables of cross sections already in that form. Codes used subsequently need thus to consider only linear-linear data. IAEA1311/15: This version include the updates up to January 30, 2007. Changes in ENDF/B-VII Format and procedures, as well as the evaluations themselves, make it impossible for versions of the ENDF/B pre-processing codes earlier than PREPRO 2007 (2007 Version) to accurately process current ENDF/B-VII evaluations. The present code can handle all existing ENDF/B-VI evaluations through release 8, which will be the last release of ENDF/B-VI. Modifications from previous versions: - Linear VERS. 2007-1 (JAN. 2007): checked against all ENDF/B-VII; increased page size from 60,000 to 600,000 points 2 - Method of solution: Each section of data is considered separately. Each section of File 3, 23, and 27 data consists of a table of cross section versus energy with any of five interpolation laws. LINEAR will replace each section with a new table of energy versus cross section data in which the interpolation law is always linear in energy and cross section. The histogram (constant cross section between two energies) interpolation law is converted to linear-linear by substituting two points for each initial point. The linear-linear is not altered. For the log-linear, linear-log and log- log laws, the cross section data are converted to linear by an interval halving algorithm. Each interval is divided in half until the value at the middle of the interval can be approximated by linear-linear interpolation to within a given accuracy. The LINEAR program uses a multipoint fractional error thinning algorithm to minimize the size of each cross section table

Solution of Large Systems of Linear Equations with Quadratic or Non-Quadratic Matrices and Deconvoiution of Spectra

Energy Technology Data Exchange (ETDEWEB)

Nygaard, K

1967-12-15

The numerical deconvolution of spectra is equivalent to the solution of a (large) system of linear equations with a matrix which is not necessarily a square matrix. The demand that the square sum of the residual errors shall be minimum is not in general sufficient to ensure a unique or 'sound' solution. Therefore other demands which may include the demand for minimum square errors are introduced which lead to 'sound' and 'non-oscillatory' solutions irrespective of the shape of the original matrix and of the determinant of the matrix of the normal equations.

Experimental investigations of the minimum ignition energy and the minimum ignition temperature of inert and combustible dust cloud mixtures

Energy Technology Data Exchange (ETDEWEB)

Addai, Emmanuel Kwasi, E-mail: emmanueladdai41@yahoo.com; Gabel, Dieter; Krause, Ulrich

2016-04-15

Highlights: • Ignition sensitivity of a highly flammable dust decreases upon addition of inert dust. • Minimum ignition temperature of a highly flammable dust increases when inert concentration increase. • Minimum ignition energy of a highly flammable dust increases when inert concentration increase. • The permissible range for the inert mixture to minimize the ignition risk lies between 60 to 80%. - Abstract: The risks associated with dust explosions still exist in industries that either process or handle combustible dust. This explosion risk could be prevented or mitigated by applying the principle of inherent safety (moderation). This is achieved by adding an inert material to a highly combustible material in order to decrease the ignition sensitivity of the combustible dust. The presented paper deals with the experimental investigation of the influence of adding an inert dust on the minimum ignition energy and the minimum ignition temperature of the combustible/inert dust mixtures. The experimental investigation was done in two laboratory scale equipment: the Hartmann apparatus and the Godbert-Greenwald furnace for the minimum ignition energy and the minimum ignition temperature test respectively. This was achieved by mixing various amounts of three inert materials (magnesium oxide, ammonium sulphate and sand) and six combustible dusts (brown coal, lycopodium, toner, niacin, corn starch and high density polyethylene). Generally, increasing the inert materials concentration increases the minimum ignition energy as well as the minimum ignition temperatures until a threshold is reached where no ignition was obtained. The permissible range for the inert mixture to minimize the ignition risk lies between 60 to 80%.

Experimental investigations of the minimum ignition energy and the minimum ignition temperature of inert and combustible dust cloud mixtures

International Nuclear Information System (INIS)

Addai, Emmanuel Kwasi; Gabel, Dieter; Krause, Ulrich

2016-01-01

Highlights: • Ignition sensitivity of a highly flammable dust decreases upon addition of inert dust. • Minimum ignition temperature of a highly flammable dust increases when inert concentration increase. • Minimum ignition energy of a highly flammable dust increases when inert concentration increase. • The permissible range for the inert mixture to minimize the ignition risk lies between 60 to 80%. - Abstract: The risks associated with dust explosions still exist in industries that either process or handle combustible dust. This explosion risk could be prevented or mitigated by applying the principle of inherent safety (moderation). This is achieved by adding an inert material to a highly combustible material in order to decrease the ignition sensitivity of the combustible dust. The presented paper deals with the experimental investigation of the influence of adding an inert dust on the minimum ignition energy and the minimum ignition temperature of the combustible/inert dust mixtures. The experimental investigation was done in two laboratory scale equipment: the Hartmann apparatus and the Godbert-Greenwald furnace for the minimum ignition energy and the minimum ignition temperature test respectively. This was achieved by mixing various amounts of three inert materials (magnesium oxide, ammonium sulphate and sand) and six combustible dusts (brown coal, lycopodium, toner, niacin, corn starch and high density polyethylene). Generally, increasing the inert materials concentration increases the minimum ignition energy as well as the minimum ignition temperatures until a threshold is reached where no ignition was obtained. The permissible range for the inert mixture to minimize the ignition risk lies between 60 to 80%.

A Trivial Linear Discriminant Function

Directory of Open Access Journals (Sweden)

Shuichi Shinmura

2015-11-01

Full Text Available In this paper, we focus on the new model selection procedure of the discriminant analysis. Combining re-sampling technique with k-fold cross validation, we develop a k-fold cross validation for small sample method. By this breakthrough, we obtain the mean error rate in the validation samples (M2 and the 95\\% confidence interval (CI of discriminant coefficient. Moreover, we propose the model  selection  procedure  in  which  the model having a minimum M2 was  chosen  to  the  best  model.  We  apply  this  new  method and procedure to the pass/ fail determination of  exam  scores.  In  this  case,  we  fix  the constant =1 for seven linear discriminant  functions  (LDFs  and  several  good  results  were obtained as follows: 1 M2 of Fisher's LDF are over 4.6\\% worse than Revised IP-OLDF. 2 A soft-margin  SVM  for  penalty c=1  (SVM1  is  worse  than  another  mathematical  programming (MP based LDFs and logistic regression . 3 The 95\\% CI of the best discriminant coefficients was obtained. Seven LDFs except for Fisher's LDF are almost the same as a trivial LDF for the linear separable model. Furthermore, if we choose the median of the coefficient of seven LDFs except for Fisher's LDF,  those are almost the same as the trivial LDF for the linear separable model.

Self-Tuning Control of Linear Systems Followed by Deadzones

Directory of Open Access Journals (Sweden)

K. Kazlauskas

2014-02-01

Full Text Available The aim of the present paper is to increase the efficiency of self-tuning generalized minimum variance (GMV control of linear time-invariant (LTI systems followed by deadzone nonlinearities. An approach, based on reordering of observations to be processed for the reconstruction of an unknown internal signal that acts between LTI system and a static nonlinear block of the closed-loop Wiener system, has been developed. The results of GMV self-tuning control of the second order LTI system with an ordinary deadzone are given.

Eigenspace-based minimum variance adaptive beamformer combined with delay multiply and sum: experimental study

Science.gov (United States)

Mozaffarzadeh, Moein; Mahloojifar, Ali; Nasiriavanaki, Mohammadreza; Orooji, Mahdi

2018-02-01

Delay and sum (DAS) is the most common beamforming algorithm in linear-array photoacoustic imaging (PAI) as a result of its simple implementation. However, it leads to a low resolution and high sidelobes. Delay multiply and sum (DMAS) was used to address the incapabilities of DAS, providing a higher image quality. However, the resolution improvement is not well enough compared to eigenspace-based minimum variance (EIBMV). In this paper, the EIBMV beamformer has been combined with DMAS algebra, called EIBMV-DMAS, using the expansion of DMAS algorithm. The proposed method is used as the reconstruction algorithm in linear-array PAI. EIBMV-DMAS is experimentally evaluated where the quantitative and qualitative results show that it outperforms DAS, DMAS and EIBMV. The proposed method degrades the sidelobes for about 365 %, 221 % and 40 %, compared to DAS, DMAS and EIBMV, respectively. Moreover, EIBMV-DMAS improves the SNR about 158 %, 63 % and 20 %, respectively.

Adaptive Control for Linear Uncertain Systems with Unmodeled Dynamics Revisited via Optimal Control Modification

Science.gov (United States)

Nguyen, Nhan

2013-01-01

This paper presents the optimal control modification for linear uncertain plants. The Lyapunov analysis shows that the modification parameter has a limiting value depending on the nature of the uncertainty. The optimal control modification exhibits a linear asymptotic property that enables it to be analyzed in a linear time invariant framework for linear uncertain plants. The linear asymptotic property shows that the closed-loop plants in the limit possess a scaled input-output mapping. Using this property, we can derive an analytical closed-loop transfer function in the limit as the adaptive gain tends to infinity. The paper revisits the Rohrs counterexample problem that illustrates the nature of non-robustness of model-reference adaptive control in the presence of unmodeled dynamics. An analytical approach is developed to compute exactly the modification parameter for the optimal control modification that stabilizes the plant in the Rohrs counterexample. The linear asymptotic property is also used to address output feedback adaptive control for non-minimum phase plants with a relative degree 1.

Onomatopoeia characters extraction from comic images using constrained Delaunay triangulation

Science.gov (United States)

Liu, Xiangping; Shoji, Kenji; Mori, Hiroshi; Toyama, Fubito

2014-02-01

A method for extracting onomatopoeia characters from comic images was developed based on stroke width feature of characters, since they nearly have a constant stroke width in a number of cases. An image was segmented with a constrained Delaunay triangulation. Connected component grouping was performed based on the triangles generated by the constrained Delaunay triangulation. Stroke width calculation of the connected components was conducted based on the altitude of the triangles generated with the constrained Delaunay triangulation. The experimental results proved the effectiveness of the proposed method.

Improving boiler unit performance using an optimum robust minimum-order observer

Energy Technology Data Exchange (ETDEWEB)

Moradi, Hamed; Bakhtiari-Nejad, Firooz [Energy and Control Centre of Excellence, Department of Mechanical Engineering, Amirkabir University of Technology, Tehran (Iran, Islamic Republic of)

2011-03-15

To achieve a good performance of the utility boiler, dynamic variables such as drum pressure, steam temperature and water level of drum must be controlled. In this paper, a linear time invariant (LTI) model of a boiler system is considered in which the input variables are feed-water and fuel mass rates. Due to the inaccessibility of some state variables of boiler system, a minimum-order observer is designed based on Luenberger's model to gain an estimate state x of the true state x. Low cost of design and high accuracy of states estimation are the main advantages of the minimum-order observer; in comparison with previous designed full-order observers. By applying the observer on the closed-loop system, a regulator system is designed. Using an optimal functional code developed in MATLAB environment, desired observer poles are found such that suitable time response specifications of the boiler system are achieved and the gain and phase margin values are adjusted in an acceptable range. However, the real dynamic model may associate with parametric uncertainties. In that case, optimum region of poles of observer-based controller are found such that the robust performance of the boiler system against model uncertainties is guaranteed. (author)

New Minimum Wage Research: A Symposium.

Science.gov (United States)

Ehrenberg, Ronald G.; And Others

1992-01-01

Includes "Introduction" (Ehrenberg); "Effect of the Minimum Wage [MW] on the Fast-Food Industry" (Katz, Krueger); "Using Regional Variation in Wages to Measure Effects of the Federal MW" (Card); "Do MWs Reduce Employment?" (Card); "Employment Effects of Minimum and Subminimum Wages" (Neumark,…

Constraining walking and custodial technicolor

DEFF Research Database (Denmark)

Foadi, Roshan; Frandsen, Mads Toudal; Sannino, Francesco

2008-01-01

We show how to constrain the physical spectrum of walking technicolor models via precision measurements and modified Weinberg sum rules. We also study models possessing a custodial symmetry for the S parameter at the effective Lagrangian level-custodial technicolor-and argue that these models...

Teaching the Minimum Wage in Econ 101 in Light of the New Economics of the Minimum Wage.

Science.gov (United States)

Krueger, Alan B.

2001-01-01

Argues that the recent controversy over the effect of the minimum wage on employment offers an opportunity for teaching introductory economics. Examines eight textbooks to determine topic coverage but finds little consensus. Describes how minimum wage effects should be taught. (RLH)

21 CFR 888.3300 - Hip joint metal constrained cemented or uncemented prosthesis.

Science.gov (United States)

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Hip joint metal constrained cemented or uncemented... HUMAN SERVICES (CONTINUED) MEDICAL DEVICES ORTHOPEDIC DEVICES Prosthetic Devices § 888.3300 Hip joint metal constrained cemented or uncemented prosthesis. (a) Identification. A hip joint metal constrained...

30 CFR 75.1431 - Minimum rope strength.

Science.gov (United States)

2010-07-01

..., including rotation resistant). For rope lengths less than 3,000 feet: Minimum Value=Static Load×(7.0−0.001L) For rope lengths 3,000 feet or greater: Minimum Value=Static Load×4.0 (b) Friction drum ropes. For rope lengths less than 4,000 feet: Minimum Value=Static Load×(7.0−0.0005L) For rope lengths 4,000 feet...

Robust linear registration of CT images using random regression forests

Science.gov (United States)

Konukoglu, Ender; Criminisi, Antonio; Pathak, Sayan; Robertson, Duncan; White, Steve; Haynor, David; Siddiqui, Khan

2011-03-01

Global linear registration is a necessary first step for many different tasks in medical image analysis. Comparing longitudinal studies1, cross-modality fusion2, and many other applications depend heavily on the success of the automatic registration. The robustness and efficiency of this step is crucial as it affects all subsequent operations. Most common techniques cast the linear registration problem as the minimization of a global energy function based on the image intensities. Although these algorithms have proved useful, their robustness in fully automated scenarios is still an open question. In fact, the optimization step often gets caught in local minima yielding unsatisfactory results. Recent algorithms constrain the space of registration parameters by exploiting implicit or explicit organ segmentations, thus increasing robustness4,5. In this work we propose a novel robust algorithm for automatic global linear image registration. Our method uses random regression forests to estimate posterior probability distributions for the locations of anatomical structures - represented as axis aligned bounding boxes6. These posterior distributions are later integrated in a global linear registration algorithm. The biggest advantage of our algorithm is that it does not require pre-defined segmentations or regions. Yet it yields robust registration results. We compare the robustness of our algorithm with that of the state of the art Elastix toolbox7. Validation is performed via 1464 pair-wise registrations in a database of very diverse 3D CT images. We show that our method decreases the "failure" rate of the global linear registration from 12.5% (Elastix) to only 1.9%.

Robust and Reliable Portfolio Optimization Formulation of a Chance Constrained Problem

Directory of Open Access Journals (Sweden)

Sengupta Raghu Nandan

2017-02-01

Full Text Available We solve a linear chance constrained portfolio optimization problem using Robust Optimization (RO method wherein financial script/asset loss return distributions are considered as extreme valued. The objective function is a convex combination of portfolio’s CVaR and expected value of loss return, subject to a set of randomly perturbed chance constraints with specified probability values. The robust deterministic counterpart of the model takes the form of Second Order Cone Programming (SOCP problem. Results from extensive simulation runs show the efficacy of our proposed models, as it helps the investor to (i utilize extensive simulation studies to draw insights into the effect of randomness in portfolio decision making process, (ii incorporate different risk appetite scenarios to find the optimal solutions for the financial portfolio allocation problem and (iii compare the risk and return profiles of the investments made in both deterministic as well as in uncertain and highly volatile financial markets.

Coding for Two Dimensional Constrained Fields

DEFF Research Database (Denmark)

Laursen, Torben Vaarbye

2006-01-01

a first order model to model higher order constraints by the use of an alphabet extension. We present an iterative method that based on a set of conditional probabilities can help in choosing the large numbers of parameters of the model in order to obtain a stationary model. Explicit results are given...... for the No Isolated Bits constraint. Finally we present a variation of the encoding scheme of bit-stuffing that is applicable to the class of checkerboard constrained fields. It is possible to calculate the entropy of the coding scheme thus obtaining lower bounds on the entropy of the fields considered. These lower...... bounds are very tight for the Run-Length limited fields. Explicit bounds are given for the diamond constrained field as well....

Q-deformed systems and constrained dynamics

International Nuclear Information System (INIS)

Shabanov, S.V.

1993-01-01

It is shown that quantum theories of the q-deformed harmonic oscillator and one-dimensional free q-particle (a free particle on the 'quantum' line) can be obtained by the canonical quantization of classical Hamiltonian systems with commutative phase-space variables and a non-trivial symplectic structure. In the framework of this approach, classical dynamics of a particle on the q-line coincides with the one of a free particle with friction. It is argued that q-deformed systems can be treated as ordinary mechanical systems with the second-class constraints. In particular, second-class constrained systems corresponding to the q-oscillator and q-particle are given. A possibility of formulating q-deformed systems via gauge theories (first-class constrained systems) is briefly discussed. (orig.)

21 CFR 888.3110 - Ankle joint metal/polymer semi-constrained cemented prosthesis.

Science.gov (United States)

2010-04-01

... 21 Food and Drugs 8 2010-04-01 2010-04-01 false Ankle joint metal/polymer semi-constrained... Ankle joint metal/polymer semi-constrained cemented prosthesis. (a) Identification. An ankle joint metal/polymer semi-constrained cemented prosthesis is a device intended to be implanted to replace an ankle...

Minimum curvilinearity to enhance topological prediction of protein interactions by network embedding

KAUST Repository

Cannistraci, Carlo

2013-06-21

Motivation: Most functions within the cell emerge thanks to protein-protein interactions (PPIs), yet experimental determination of PPIs is both expensive and time-consuming. PPI networks present significant levels of noise and incompleteness. Predicting interactions using only PPI-network topology (topological prediction) is difficult but essential when prior biological knowledge is absent or unreliable.Methods: Network embedding emphasizes the relations between network proteins embedded in a low-dimensional space, in which protein pairs that are closer to each other represent good candidate interactions. To achieve network denoising, which boosts prediction performance, we first applied minimum curvilinear embedding (MCE), and then adopted shortest path (SP) in the reduced space to assign likelihood scores to candidate interactions. Furthermore, we introduce (i) a new valid variation of MCE, named non-centred MCE (ncMCE); (ii) two automatic strategies for selecting the appropriate embedding dimension; and (iii) two new randomized procedures for evaluating predictions.Results: We compared our method against several unsupervised and supervisedly tuned embedding approaches and node neighbourhood techniques. Despite its computational simplicity, ncMCE-SP was the overall leader, outperforming the current methods in topological link prediction.Conclusion: Minimum curvilinearity is a valuable non-linear framework that we successfully applied to the embedding of protein networks for the unsupervised prediction of novel PPIs. The rationale for our approach is that biological and evolutionary information is imprinted in the non-linear patterns hidden behind the protein network topology, and can be exploited for predicting new protein links. The predicted PPIs represent good candidates for testing in high-throughput experiments or for exploitation in systems biology tools such as those used for network-based inference and prediction of disease-related functional modules. The

Linearization Method and Linear Complexity

Science.gov (United States)

Tanaka, Hidema

We focus on the relationship between the linearization method and linear complexity and show that the linearization method is another effective technique for calculating linear complexity. We analyze its effectiveness by comparing with the logic circuit method. We compare the relevant conditions and necessary computational cost with those of the Berlekamp-Massey algorithm and the Games-Chan algorithm. The significant property of a linearization method is that it needs no output sequence from a pseudo-random number generator (PRNG) because it calculates linear complexity using the algebraic expression of its algorithm. When a PRNG has n [bit] stages (registers or internal states), the necessary computational cost is smaller than O(2n). On the other hand, the Berlekamp-Massey algorithm needs O(N2) where N(≅2n) denotes period. Since existing methods calculate using the output sequence, an initial value of PRNG influences a resultant value of linear complexity. Therefore, a linear complexity is generally given as an estimate value. On the other hand, a linearization method calculates from an algorithm of PRNG, it can determine the lower bound of linear complexity.

A novel method to design sparse linear arrays for ultrasonic phased array.

Science.gov (United States)

Yang, Ping; Chen, Bin; Shi, Ke-Ren

2006-12-22

In ultrasonic phased array testing, a sparse array can increase the resolution by enlarging the aperture without adding system complexity. Designing a sparse array involves choosing the best or a better configuration from a large number of candidate arrays. We firstly designed sparse arrays by using a genetic algorithm, but found that the arrays have poor performance and poor consistency. So, a method based on the Minimum Redundancy Linear Array was then adopted. Some elements are determined by the minimum-redundancy array firstly in order to ensure spatial resolution and then a genetic algorithm is used to optimize the remaining elements. Sparse arrays designed by this method have much better performance and consistency compared to the arrays designed only by a genetic algorithm. Both simulation and experiment confirm the effectiveness.

Constrained Local UniversE Simulations: a Local Group factory

Science.gov (United States)

Carlesi, Edoardo; Sorce, Jenny G.; Hoffman, Yehuda; Gottlöber, Stefan; Yepes, Gustavo; Libeskind, Noam I.; Pilipenko, Sergey V.; Knebe, Alexander; Courtois, Hélène; Tully, R. Brent; Steinmetz, Matthias

2016-05-01

Near-field cosmology is practised by studying the Local Group (LG) and its neighbourhood. This paper describes a framework for simulating the `near field' on the computer. Assuming the Λ cold dark matter (ΛCDM) model as a prior and applying the Bayesian tools of the Wiener filter and constrained realizations of Gaussian fields to the Cosmicflows-2 (CF2) survey of peculiar velocities, constrained simulations of our cosmic environment are performed. The aim of these simulations is to reproduce the LG and its local environment. Our main result is that the LG is likely a robust outcome of the ΛCDMscenario when subjected to the constraint derived from CF2 data, emerging in an environment akin to the observed one. Three levels of criteria are used to define the simulated LGs. At the base level, pairs of haloes must obey specific isolation, mass and separation criteria. At the second level, the orbital angular momentum and energy are constrained, and on the third one the phase of the orbit is constrained. Out of the 300 constrained simulations, 146 LGs obey the first set of criteria, 51 the second and 6 the third. The robustness of our LG `factory' enables the construction of a large ensemble of simulated LGs. Suitable candidates for high-resolution hydrodynamical simulations of the LG can be drawn from this ensemble, which can be used to perform comprehensive studies of the formation of the LG.

30 CFR 281.30 - Minimum royalty.

Science.gov (United States)

2010-07-01

... 30 Mineral Resources 2 2010-07-01 2010-07-01 false Minimum royalty. 281.30 Section 281.30 Mineral Resources MINERALS MANAGEMENT SERVICE, DEPARTMENT OF THE INTERIOR OFFSHORE LEASING OF MINERALS OTHER THAN OIL, GAS, AND SULPHUR IN THE OUTER CONTINENTAL SHELF Financial Considerations § 281.30 Minimum royalty...

Metric preheating and limitations of linearized gravity

International Nuclear Information System (INIS)

Bassett, Bruce A.; Tamburini, Fabrizio; Kaiser, David I.; Maartens, Roy

1999-01-01

During the preheating era after inflation, resonant amplification of quantum field fluctuations takes place. Recently it has become clear that this must be accompanied by resonant amplification of scalar metric fluctuations, since the two are united by Einstein's equations. Furthermore, this 'metric preheating' enhances particle production, and leads to gravitational rescattering effects even at linear order. In multi-field models with strong preheating (q>>1), metric perturbations are driven non-linear, with the strongest amplification typically on super-Hubble scales (k→0). This amplification is causal, being due to the super-Hubble coherence of the inflaton condensate, and is accompanied by resonant growth of entropy perturbations. The amplification invalidates the use of the linearized Einstein field equations, irrespective of the amount of fine-tuning of the initial conditions. This has serious implications on all scales - from large-angle cosmic microwave background (CMB) anisotropies to primordial black holes. We investigate the (q,k) parameter space in a two-field model, and introduce the time to non-linearity, t nl , as the timescale for the breakdown of the linearized Einstein equations. t nl is a robust indicator of resonance behavior, showing the fine structure in q and k that one expects from a quasi-Floquet system, and we argue that t nl is a suitable generalization of the static Floquet index in an expanding universe. Backreaction effects are expected to shut down the linear resonances, but cannot remove the existing amplification, which threatens the viability of strong preheating when confronted with the CMB. Mode-mode coupling and turbulence tend to re-establish scale invariance, but this process is limited by causality and for small k the primordial scale invariance of the spectrum may be destroyed. We discuss ways to escape the above conclusions, including secondary phases of inflation and preheating solely to fermions. The exclusion principle

Reinforcement learning solution for HJB equation arising in constrained optimal control problem.

Science.gov (United States)

Luo, Biao; Wu, Huai-Ning; Huang, Tingwen; Liu, Derong

2015-11-01

The constrained optimal control problem depends on the solution of the complicated Hamilton-Jacobi-Bellman equation (HJBE). In this paper, a data-based off-policy reinforcement learning (RL) method is proposed, which learns the solution of the HJBE and the optimal control policy from real system data. One important feature of the off-policy RL is that its policy evaluation can be realized with data generated by other behavior policies, not necessarily the target policy, which solves the insufficient exploration problem. The convergence of the off-policy RL is proved by demonstrating its equivalence to the successive approximation approach. Its implementation procedure is based on the actor-critic neural networks structure, where the function approximation is conducted with linearly independent basis functions. Subsequently, the convergence of the implementation procedure with function approximation is also proved. Finally, its effectiveness is verified through computer simulations. Copyright © 2015 Elsevier Ltd. All rights reserved.

State cigarette minimum price laws - United States, 2009.

Science.gov (United States)

2010-04-09

Cigarette price increases reduce the demand for cigarettes and thereby reduce smoking prevalence, cigarette consumption, and youth initiation of smoking. Excise tax increases are the most effective government intervention to increase the price of cigarettes, but cigarette manufacturers use trade discounts, coupons, and other promotions to counteract the effects of these tax increases and appeal to price-sensitive smokers. State cigarette minimum price laws, initiated by states in the 1940s and 1950s to protect tobacco retailers from predatory business practices, typically require a minimum percentage markup to be added to the wholesale and/or retail price. If a statute prohibits trade discounts from the minimum price calculation, these laws have the potential to counteract discounting by cigarette manufacturers. To assess the status of cigarette minimum price laws in the United States, CDC surveyed state statutes and identified those states with minimum price laws in effect as of December 31, 2009. This report summarizes the results of that survey, which determined that 25 states had minimum price laws for cigarettes (median wholesale markup: 4.00%; median retail markup: 8.00%), and seven of those states also expressly prohibited the use of trade discounts in the minimum retail price calculation. Minimum price laws can help prevent trade discounting from eroding the positive effects of state excise tax increases and higher cigarette prices on public health.

A Stationary North-Finding Scheme for an Azimuth Rotational IMU Utilizing a Linear State Equality Constraint

Directory of Open Access Journals (Sweden)

Huapeng Yu

2015-02-01

Full Text Available The Kalman filter (KF has always been used to improve north-finding performance under practical conditions. By analyzing the characteristics of the azimuth rotational inertial measurement unit (ARIMU on a stationary base, a linear state equality constraint for the conventional KF used in the fine north-finding filtering phase is derived. Then, a constrained KF using the state equality constraint is proposed and studied in depth. Estimation behaviors of the concerned navigation errors when implementing the conventional KF scheme and the constrained KF scheme during stationary north-finding are investigated analytically by the stochastic observability approach, which can provide explicit formulations of the navigation errors with influencing variables. Finally, multiple practical experimental tests at a fixed position are done on a postulate system to compare the stationary north-finding performance of the two filtering schemes. In conclusion, this study has successfully extended the utilization of the stochastic observability approach for analytic descriptions of estimation behaviors of the concerned navigation errors, and the constrained KF scheme has demonstrated its superiority over the conventional KF scheme for ARIMU stationary north-finding both theoretically and practically.

Constrained non-linear multi-objective optimisation of preventive maintenance scheduling for offshore wind farms

Science.gov (United States)

Zhong, Shuya; Pantelous, Athanasios A.; Beer, Michael; Zhou, Jian

2018-05-01

Offshore wind farm is an emerging source of renewable energy, which has been shown to have tremendous potential in recent years. In this blooming area, a key challenge is that the preventive maintenance of offshore turbines should be scheduled reasonably to satisfy the power supply without failure. In this direction, two significant goals should be considered simultaneously as a trade-off. One is to maximise the system reliability and the other is to minimise the maintenance related cost. Thus, a non-linear multi-objective programming model is proposed including two newly defined objectives with thirteen families of constraints suitable for the preventive maintenance of offshore wind farms. In order to solve our model effectively, the nondominated sorting genetic algorithm II, especially for the multi-objective optimisation is utilised and Pareto-optimal solutions of schedules can be obtained to offer adequate support to decision-makers. Finally, an example is given to illustrate the performances of the devised model and algorithm, and explore the relationships of the two targets with the help of a contrast model.

Constrained Bayesian Active Learning of Interference Channels in Cognitive Radio Networks

Science.gov (United States)

Tsakmalis, Anestis; Chatzinotas, Symeon; Ottersten, Bjorn

2018-02-01

In this paper, a sequential probing method for interference constraint learning is proposed to allow a centralized Cognitive Radio Network (CRN) accessing the frequency band of a Primary User (PU) in an underlay cognitive scenario with a designed PU protection specification. The main idea is that the CRN probes the PU and subsequently eavesdrops the reverse PU link to acquire the binary ACK/NACK packet. This feedback indicates whether the probing-induced interference is harmful or not and can be used to learn the PU interference constraint. The cognitive part of this sequential probing process is the selection of the power levels of the Secondary Users (SUs) which aims to learn the PU interference constraint with a minimum number of probing attempts while setting a limit on the number of harmful probing-induced interference events or equivalently of NACK packet observations over a time window. This constrained design problem is studied within the Active Learning (AL) framework and an optimal solution is derived and implemented with a sophisticated, accurate and fast Bayesian Learning method, the Expectation Propagation (EP). The performance of this solution is also demonstrated through numerical simulations and compared with modified versions of AL techniques we developed in earlier work.

9 CFR 147.51 - Authorized laboratory minimum requirements.

Science.gov (United States)

2010-01-01

... 9 Animals and Animal Products 1 2010-01-01 2010-01-01 false Authorized laboratory minimum requirements. 147.51 Section 147.51 Animals and Animal Products ANIMAL AND PLANT HEALTH INSPECTION SERVICE... Authorized Laboratories and Approved Tests § 147.51 Authorized laboratory minimum requirements. These minimum...

Volume-constrained optimization of magnetorheological and electrorheological valves and dampers

Science.gov (United States)

Rosenfeld, Nicholas C.; Wereley, Norman M.

2004-12-01

This paper presents a case study of magnetorheological (MR) and electrorheological (ER) valve design within a constrained cylindrical volume. The primary purpose of this study is to establish general design guidelines for volume-constrained MR valves. Additionally, this study compares the performance of volume-constrained MR valves against similarly constrained ER valves. Starting from basic design guidelines for an MR valve, a method for constructing candidate volume-constrained valve geometries is presented. A magnetic FEM program is then used to evaluate the magnetic properties of the candidate valves. An optimized MR valve is chosen by evaluating non-dimensional parameters describing the candidate valves' damping performance. A derivation of the non-dimensional damping coefficient for valves with both active and passive volumes is presented to allow comparison of valves with differing proportions of active and passive volumes. The performance of the optimized MR valve is then compared to that of a geometrically similar ER valve using both analytical and numerical techniques. An analytical equation relating the damping performances of geometrically similar MR and ER valves in as a function of fluid yield stresses and relative active fluid volume, and numerical calculations are provided to calculate each valve's damping performance and to validate the analytical calculations.

Comparison of phase-constrained parallel MRI approaches: Analogies and differences.

Science.gov (United States)

Blaimer, Martin; Heim, Marius; Neumann, Daniel; Jakob, Peter M; Kannengiesser, Stephan; Breuer, Felix A

2016-03-01

Phase-constrained parallel MRI approaches have the potential for significantly improving the image quality of accelerated MRI scans. The purpose of this study was to investigate the properties of two different phase-constrained parallel MRI formulations, namely the standard phase-constrained approach and the virtual conjugate coil (VCC) concept utilizing conjugate k-space symmetry. Both formulations were combined with image-domain algorithms (SENSE) and a mathematical analysis was performed. Furthermore, the VCC concept was combined with k-space algorithms (GRAPPA and ESPIRiT) for image reconstruction. In vivo experiments were conducted to illustrate analogies and differences between the individual methods. Furthermore, a simple method of improving the signal-to-noise ratio by modifying the sampling scheme was implemented. For SENSE, the VCC concept was mathematically equivalent to the standard phase-constrained formulation and therefore yielded identical results. In conjunction with k-space algorithms, the VCC concept provided more robust results when only a limited amount of calibration data were available. Additionally, VCC-GRAPPA reconstructed images provided spatial phase information with full resolution. Although both phase-constrained parallel MRI formulations are very similar conceptually, there exist important differences between image-domain and k-space domain reconstructions regarding the calibration robustness and the availability of high-resolution phase information. © 2015 Wiley Periodicals, Inc.

Experimental investigations of the minimum ignition energy and the minimum ignition temperature of inert and combustible dust cloud mixtures.

Science.gov (United States)

Addai, Emmanuel Kwasi; Gabel, Dieter; Krause, Ulrich

2016-04-15

The risks associated with dust explosions still exist in industries that either process or handle combustible dust. This explosion risk could be prevented or mitigated by applying the principle of inherent safety (moderation). This is achieved by adding an inert material to a highly combustible material in order to decrease the ignition sensitivity of the combustible dust. The presented paper deals with the experimental investigation of the influence of adding an inert dust on the minimum ignition energy and the minimum ignition temperature of the combustible/inert dust mixtures. The experimental investigation was done in two laboratory scale equipment: the Hartmann apparatus and the Godbert-Greenwald furnace for the minimum ignition energy and the minimum ignition temperature test respectively. This was achieved by mixing various amounts of three inert materials (magnesium oxide, ammonium sulphate and sand) and six combustible dusts (brown coal, lycopodium, toner, niacin, corn starch and high density polyethylene). Generally, increasing the inert materials concentration increases the minimum ignition energy as well as the minimum ignition temperatures until a threshold is reached where no ignition was obtained. The permissible range for the inert mixture to minimize the ignition risk lies between 60 to 80%. Copyright © 2016 Elsevier B.V. All rights reserved.

A supply function model for representing the strategic bidding of the producers in constrained electricity markets

International Nuclear Information System (INIS)

Bompard, Ettore; Napoli, Roberto; Lu, Wene; Jiang, Xiuchen

2010-01-01

The modeling of the bidding behaviour of the producer is a key-point in the modeling and simulation of the competitive electricity markets. In our paper, the linear supply function model is applied so as to find the Supply Function Equilibrium analytically. It also proposed a new and efficient approach to find SFEs for the network constrained electricity markets by finding the best slope of the supply function with the help of changing the intercept, and the method can be applied on the large systems. The approach proposed is applied to study IEEE-118 bus test systems and the comparison between bidding slope and bidding intercept is presented, as well, with reference to the test system. (author)

Sparse/Low Rank Constrained Reconstruction for Dynamic PET Imaging.

Directory of Open Access Journals (Sweden)

Xingjian Yu

Full Text Available In dynamic Positron Emission Tomography (PET, an estimate of the radio activity concentration is obtained from a series of frames of sinogram data taken at ranging in duration from 10 seconds to minutes under some criteria. So far, all the well-known reconstruction algorithms require known data statistical properties. It limits the speed of data acquisition, besides, it is unable to afford the separated information about the structure and the variation of shape and rate of metabolism which play a major role in improving the visualization of contrast for some requirement of the diagnosing in application. This paper presents a novel low rank-based activity map reconstruction scheme from emission sinograms of dynamic PET, termed as SLCR representing Sparse/Low Rank Constrained Reconstruction for Dynamic PET Imaging. In this method, the stationary background is formulated as a low rank component while variations between successive frames are abstracted to the sparse. The resulting nuclear norm and l1 norm related minimization problem can also be efficiently solved by many recently developed numerical methods. In this paper, the linearized alternating direction method is applied. The effectiveness of the proposed scheme is illustrated on three data sets.

A Benders approach for the constrained minimum break problem

DEFF Research Database (Denmark)

Rasmussen, Rasmus Vinther; Trick, Michael

2007-01-01

This paper presents a hybrid IP/CP algorithm for designing a double round robin schedule with a minimal number of breaks. Both mirrored and non-mirrored schedules with and without place constraints are considered. The algorithm uses Benders cuts to obtain feasible home-away pattern sets in few it...

Positive solution of non-square fully Fuzzy linear system of equation in general form using least square method

Directory of Open Access Journals (Sweden)

Reza Ezzati

2014-08-01

Full Text Available In this paper, we propose the least square method for computing the positive solution of a non-square fully fuzzy linear system. To this end, we use Kaffman' arithmetic operations on fuzzy numbers \\cite{17}. Here, considered existence of exact solution using pseudoinverse, if they are not satisfy in positive solution condition, we will compute fuzzy vector core and then we will obtain right and left spreads of positive fuzzy vector by introducing constrained least squares problem. Using our proposed method, non-square fully fuzzy linear system of equations always has a solution. Finally, we illustrate the efficiency of proposed method by solving some numerical examples.

A discretized algorithm for the solution of a constrained, continuous ...

African Journals Online (AJOL)

A discretized algorithm for the solution of a constrained, continuous quadratic control problem. ... The results obtained show that the Discretized constrained algorithm (DCA) is much more accurate and more efficient than some of these techniques, particularly the FSA. Journal of the Nigerian Association of Mathematical ...

Rate of bedrock channel incision by waterfall retreat and landscape response constrained by cosmogenic 3He, Kauai, Hawaii

Science.gov (United States)

Mackey, B. H.; Lamb, M. P.; Scheingross, J. S.; Farley, K. A.

2011-12-01

Channel incision and knickpoint retreat are the drivers of landscape evolution, yet we are still challenged to quantify the rate and processes by which rivers cut into rock. The Napali Coast on the northwestern side of Kauai, Hawaii, has multiple linear channels incising >200 m into the shield volcano surface. The channels have well-constrained initial conditions, including original topography, and relatively uniform layered basalt of known age (~4.5 Ma), which have attracted previous studies of channel evolution (e.g., Seidl et al., 1994, 1997). Many channels feature prominent waterfalls, although the mechanism of knickpoint initiation (submarine landslide vs cliff erosion) and subsequent retreat remain ambiguous. Motivated by these knowledge gaps and recent advances in cosmogenic helium geochronology, we revisited the Kaulaula Valley, a 9 km long narrow valley, beheaded on its upslope extent by the Waimea Canyon, and ending near the coast at the northern Mana Plain. Four kilometers up the canyon is a prominent 40 m high vertical knickpoint, dividing the valley into strongly contrasting geomorphic domains. The boulder-lined channel below the knickpoint is linear, steep (15%), and confined to a narrow valley with steep rocky cliffs (average slope 31°). Large, >2 m diameter angular boulders in the lower section of channel show evidence of mobility from debris flows. Above the knickpoint, average channel gradient is reduced (9%), bed load is much finer, and convex, soil-mantled hillslopes have a consistently lower mean slope of 18°. We constrained the exposure age of 18 features (in-channel boulders, stable boulders on terraces, and in-channel bedrock) along the length of the channel, by analysis of cosmogenic 3He in olivine phenocrysts. Cosmogenic exposure ages are oldest near the coast (80 ka) and systematically decrease with upstream distance towards the waterfall (model of knickpoint retreat and downstream terrace abandonment advocated by Seidl (1997), and we

Response Surface Method and Linear Programming in the development of mixed nectar of acceptability high and minimum cost

Directory of Open Access Journals (Sweden)

Enrique López Calderón

2012-06-01

Full Text Available The aim of this study was to develop a high acceptability mixed nectar and low cost. To obtain the nectar mixed considered different amounts of passion fruit, sweet pepino, sucrose, and completing 100% with water, following a two-stage design: screening (using a design of type 2 3 + 4 center points and optimization (using a design of type 2 2 + 2*2 + 4 center points; stages that allow explore a high acceptability formulation. Then we used the technique of Linear Programming to minimize the cost of high acceptability nectar. Result of this process was obtained a mixed nectar optimal acceptability (score of 7, when the formulation is between 9 and 14% of passion fruit, 4 and 5% of sucrose, 73.5% of sweet pepino juice and filling with water to the 100%. Linear Programming possible reduced the cost of nectar mixed with optimal acceptability at S/.174 for a production of 1000 L/day.

Minimum Price Guarantees In a Consumer Search Model

NARCIS (Netherlands)

M.C.W. Janssen (Maarten); A. Parakhonyak (Alexei)

2009-01-01

textabstractThis paper is the first to examine the effect of minimum price guarantees in a sequential search model. Minimum price guarantees are not advertised and only known to consumers when they come to the shop. We show that in such an environment, minimum price guarantees increase the value of

LPmerge: an R package for merging genetic maps by linear programming.

Science.gov (United States)

Endelman, Jeffrey B; Plomion, Christophe

2014-06-01

Consensus genetic maps constructed from multiple populations are an important resource for both basic and applied research, including genome-wide association analysis, genome sequence assembly and studies of evolution. The LPmerge software uses linear programming to efficiently minimize the mean absolute error between the consensus map and the linkage maps from each population. This minimization is performed subject to linear inequality constraints that ensure the ordering of the markers in the linkage maps is preserved. When marker order is inconsistent between linkage maps, a minimum set of ordinal constraints is deleted to resolve the conflicts. LPmerge is on CRAN at http://cran.r-project.org/web/packages/LPmerge. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

The Karush–Kuhn–Tucker optimality conditions in minimum weight design of elastic rotating disks with variable thickness and density

Directory of Open Access Journals (Sweden)

Sanaz Jafari

2011-10-01

Full Text Available Rotating discs work mostly at high angular velocity. High speed results in large centrifugal forces in discs and induces large stresses and deformations. Minimizing weight of such disks yields various benefits such as low dead weights and lower costs. In order to attain a certain and reliable analysis, disk with variable thickness and density is considered. Semi-analytical solutions for the elastic stress distribution in rotating annular disks with uniform and variable thicknesses and densities are obtained under plane stress assumption by authors in previous works. The optimum disk profile for minimum weight design is achieved by the Karush–Kuhn–Tucker (KKT optimality conditions. Inequality constrain equation is used in optimization to make sure that maximum von Mises stress is always less than yielding strength of the material of the disk.

Wage inequality, minimum wage effects and spillovers

OpenAIRE

Stewart, Mark B.

2011-01-01

This paper investigates possible spillover effects of the UK minimum wage. The halt in the growth in inequality in the lower half of the wage distribution (as measured by the 50:10 percentile ratio) since the mid-1990s, in contrast to the continued inequality growth in the upper half of the distribution, suggests the possibility of a minimum wage effect and spillover effects on wages above the minimum. This paper analyses individual wage changes, using both a difference-in-differences estimat...

Minimum Variance Portfolios in the Brazilian Equity Market

Directory of Open Access Journals (Sweden)

Alexandre Rubesam

2013-03-01

Full Text Available We investigate minimum variance portfolios in the Brazilian equity market using different methods to estimate the covariance matrix, from the simple model of using the sample covariance to multivariate GARCH models. We compare the performance of the minimum variance portfolios to those of the following benchmarks: (i the IBOVESPA equity index, (ii an equally-weighted portfolio, (iii the maximum Sharpe ratio portfolio and (iv the maximum growth portfolio. Our results show that the minimum variance portfolio has higher returns with lower risk compared to the benchmarks. We also consider long-short 130/30 minimum variance portfolios and obtain similar results. The minimum variance portfolio invests in relatively few stocks with low βs measured with respect to the IBOVESPA index, being easily replicable by individual and institutional investors alike.

Minimum Covers of Fixed Cardinality in Weighted Graphs.

Science.gov (United States)

White, Lee J.

Reported is the result of research on combinatorial and algorithmic techniques for information processing. A method is discussed for obtaining minimum covers of specified cardinality from a given weighted graph. By the indicated method, it is shown that the family of minimum covers of varying cardinality is related to the minimum spanning tree of…

Ring-constrained Join

DEFF Research Database (Denmark)

Yiu, Man Lung; Karras, Panagiotis; Mamoulis, Nikos

2008-01-01

. This new operation has important applications in decision support, e.g., placing recycling stations at fair locations between restaurants and residential complexes. Clearly, RCJ is defined based on a geometric constraint but not on distances between points. Thus, our operation is fundamentally different......We introduce a novel spatial join operator, the ring-constrained join (RCJ). Given two sets P and Q of spatial points, the result of RCJ consists of pairs (p, q) (where p ε P, q ε Q) satisfying an intuitive geometric constraint: the smallest circle enclosing p and q contains no other points in P, Q...

Multi-UAV Routing for Area Coverage and Remote Sensing with Minimum Time.

Science.gov (United States)

Avellar, Gustavo S C; Pereira, Guilherme A S; Pimenta, Luciano C A; Iscold, Paulo

2015-11-02

This paper presents a solution for the problem of minimum time coverage of ground areas using a group of unmanned air vehicles (UAVs) equipped with image sensors. The solution is divided into two parts: (i) the task modeling as a graph whose vertices are geographic coordinates determined in such a way that a single UAV would cover the area in minimum time; and (ii) the solution of a mixed integer linear programming problem, formulated according to the graph variables defined in the first part, to route the team of UAVs over the area. The main contribution of the proposed methodology, when compared with the traditional vehicle routing problem's (VRP) solutions, is the fact that our method solves some practical problems only encountered during the execution of the task with actual UAVs. In this line, one of the main contributions of the paper is that the number of UAVs used to cover the area is automatically selected by solving the optimization problem. The number of UAVs is influenced by the vehicles' maximum flight time and by the setup time, which is the time needed to prepare and launch a UAV. To illustrate the methodology, the paper presents experimental results obtained with two hand-launched, fixed-wing UAVs.

Non-linear dynamo waves in an incompressible medium when the turbulence dissipative coefficients depend on temperature

Directory of Open Access Journals (Sweden)

A. D. Pataraya

1997-01-01

Full Text Available Non-linear α-ω; dynamo waves existing in an incompressible medium with the turbulence dissipative coefficients depending on temperature are studied in this paper. We investigate of α-ω solar non-linear dynamo waves when only the first harmonics of magnetic induction components are included. If we ignore the second harmonics in the non-linear equation, the turbulent magnetic diffusion coefficient increases together with the temperature, the coefficient of turbulent viscosity decreases, and for an interval of time the value of dynamo number is greater than 1. In these conditions a stationary solution of the non-linear equation for the dynamo wave's amplitude exists; meaning that the magnetic field is sufficiently excited. The amplitude of the dynamo waves oscillates and becomes stationary. Using these results we can explain the existence of Maunder's minimum.

Seattle's minimum wage ordinance did not affect supermarket food prices by food processing category.

Science.gov (United States)

Spoden, Amanda L; Buszkiewicz, James H; Drewnowski, Adam; Long, Mark C; Otten, Jennifer J

2018-06-01

To examine the impacts of Seattle's minimum wage ordinance on food prices by food processing category. Supermarket food prices were collected for 106 items using a University of Washington Center for Public Health Nutrition market basket at affected and unaffected supermarket chain stores at three times: March 2015 (1-month pre-policy enactment), May 2015 (1-month post-policy enactment) and May 2016 (1-year post-policy enactment). Food items were categorized into four food processing groups, from minimally to ultra-processed. Data were analysed across time using a multilevel, linear difference-in-differences model at the store and price level stratified by level of food processing. Six large supermarket chain stores located in Seattle ('intervention') affected by the policy and six same-chain but unaffected stores in King County ('control'), Washington, USA. One hundred and six food and beverage items. The largest change in average price by food item was +$US 0·53 for 'processed foods' in King County between 1-month post-policy and 1-year post-policy enactment (P food processing level strata in Seattle v. King County stores at 1-month or 1-year post-policy enactment. Supermarket food prices do not appear to be differentially impacted by Seattle's minimum wage ordinance by level of the food's processing. These results suggest that the early implementation of a city-level minimum wage policy does not alter supermarket food prices by level of food processing.

Who Benefits from a Minimum Wage Increase?

OpenAIRE

John W. Lopresti; Kevin J. Mumford

2015-01-01

This paper addresses the question of how a minimum wage increase affects the wages of low-wage workers. Most studies assume that there is a simple mechanical increase in the wage for workers earning a wage between the old and the new minimum wage, with some studies allowing for spillovers to workers with wages just above this range. Rather than assume that the wages of these workers would have remained constant, this paper estimates how a minimum wage increase impacts a low-wage worker's wage...

CP properties of symmetry-constrained two-Higgs-doublet models

CERN Document Server

Ferreira, P M; Nachtmann, O; Silva, Joao P

2010-01-01

The two-Higgs-doublet model can be constrained by imposing Higgs-family symmetries and/or generalized CP symmetries. It is known that there are only six independent classes of such symmetry-constrained models. We study the CP properties of all cases in the bilinear formalism. An exact symmetry implies CP conservation. We show that soft breaking of the symmetry can lead to spontaneous CP violation (CPV) in three of the classes.

Constrained multi-degree reduction with respect to Jacobi norms

KAUST Repository

Ait-Haddou, Rachid; Barton, Michael

2015-01-01

We show that a weighted least squares approximation of Bézier coefficients with factored Hahn weights provides the best constrained polynomial degree reduction with respect to the Jacobi L2L2-norm. This result affords generalizations to many previous findings in the field of polynomial degree reduction. A solution method to the constrained multi-degree reduction with respect to the Jacobi L2L2-norm is presented.

Constrained multi-degree reduction with respect to Jacobi norms

KAUST Repository

Ait-Haddou, Rachid

2015-12-31

We show that a weighted least squares approximation of Bézier coefficients with factored Hahn weights provides the best constrained polynomial degree reduction with respect to the Jacobi L2L2-norm. This result affords generalizations to many previous findings in the field of polynomial degree reduction. A solution method to the constrained multi-degree reduction with respect to the Jacobi L2L2-norm is presented.

Continuous-Time Mean-Variance Portfolio Selection with Random Horizon

International Nuclear Information System (INIS)

Yu, Zhiyong

2013-01-01

This paper examines the continuous-time mean-variance optimal portfolio selection problem with random market parameters and random time horizon. Treating this problem as a linearly constrained stochastic linear-quadratic optimal control problem, I explicitly derive the efficient portfolios and efficient frontier in closed forms based on the solutions of two backward stochastic differential equations. Some related issues such as a minimum variance portfolio and a mutual fund theorem are also addressed. All the results are markedly different from those in the problem with deterministic exit time. A key part of my analysis involves proving the global solvability of a stochastic Riccati equation, which is interesting in its own right

Continuous-Time Mean-Variance Portfolio Selection with Random Horizon

Energy Technology Data Exchange (ETDEWEB)

Yu, Zhiyong, E-mail: yuzhiyong@sdu.edu.cn [Shandong University, School of Mathematics (China)

2013-12-15

This paper examines the continuous-time mean-variance optimal portfolio selection problem with random market parameters and random time horizon. Treating this problem as a linearly constrained stochastic linear-quadratic optimal control problem, I explicitly derive the efficient portfolios and efficient frontier in closed forms based on the solutions of two backward stochastic differential equations. Some related issues such as a minimum variance portfolio and a mutual fund theorem are also addressed. All the results are markedly different from those in the problem with deterministic exit time. A key part of my analysis involves proving the global solvability of a stochastic Riccati equation, which is interesting in its own right.

Mathematical Modeling of Constrained Hamiltonian Systems

NARCIS (Netherlands)

Schaft, A.J. van der; Maschke, B.M.

1995-01-01

Network modelling of unconstrained energy conserving physical systems leads to an intrinsic generalized Hamiltonian formulation of the dynamics. Constrained energy conserving physical systems are directly modelled as implicit Hamiltonian systems with regard to a generalized Dirac structure on the

Cosmogenic photons strongly constrain UHECR source models

Directory of Open Access Journals (Sweden)

van Vliet Arjen

2017-01-01

Full Text Available With the newest version of our Monte Carlo code for ultra-high-energy cosmic ray (UHECR propagation, CRPropa 3, the flux of neutrinos and photons due to interactions of UHECRs with extragalactic background light can be predicted. Together with the recently updated data for the isotropic diffuse gamma-ray background (IGRB by Fermi LAT, it is now possible to severely constrain UHECR source models. The evolution of the UHECR sources especially plays an important role in the determination of the expected secondary photon spectrum. Pure proton UHECR models are already strongly constrained, primarily by the highest energy bins of Fermi LAT’s IGRB, as long as their number density is not strongly peaked at recent times.

The minimum wage in the Czech enterprises

Directory of Open Access Journals (Sweden)

Eva Lajtkepová

2010-01-01

Full Text Available Although the statutory minimum wage is not a new category, in the Czech Republic we encounter the definition and regulation of a minimum wage for the first time in the 1990 amendment to Act No. 65/1965 Coll., the Labour Code. The specific amount of the minimum wage and the conditions of its operation were then subsequently determined by government regulation in February 1991. Since that time, the value of minimum wage has been adjusted fifteenth times (the last increase was in January 2007. The aim of this article is to present selected results of two researches of acceptance of the statutory minimum wage by Czech enterprises. The first research makes use of the data collected by questionnaire research in 83 small and medium-sized enterprises in the South Moravia Region in 2005, the second one the data of 116 enterprises in the entire Czech Republic (in 2007. The data have been processed by means of the standard methods of descriptive statistics and of the appropriate methods of the statistical analyses (Spearman correlation coefficient of sequential correlation, Kendall coefficient, χ2 - independence test, Kruskal-Wallis test, and others.

How unprecedented a solar minimum was it?

Science.gov (United States)

Russell, C T; Jian, L K; Luhmann, J G

2013-05-01

The end of the last solar cycle was at least 3 years late, and to date, the new solar cycle has seen mainly weaker activity since the onset of the rising phase toward the new solar maximum. The newspapers now even report when auroras are seen in Norway. This paper is an update of our review paper written during the deepest part of the last solar minimum [1]. We update the records of solar activity and its consequent effects on the interplanetary fields and solar wind density. The arrival of solar minimum allows us to use two techniques that predict sunspot maximum from readings obtained at solar minimum. It is clear that the Sun is still behaving strangely compared to the last few solar minima even though we are well beyond the minimum phase of the cycle 23-24 transition.

Constrained bidirectional propagation and stroke segmentation

Energy Technology Data Exchange (ETDEWEB)

Mori, S; Gillespie, W; Suen, C Y

1983-03-01

A new method for decomposing a complex figure into its constituent strokes is described. This method, based on constrained bidirectional propagation, is suitable for parallel processing. Examples of its application to the segmentation of Chinese characters are presented. 9 references.

Minimum Q Electrically Small Antennas

DEFF Research Database (Denmark)

Kim, O. S.

2012-01-01

Theoretically, the minimum radiation quality factor Q of an isolated resonance can be achieved in a spherical electrically small antenna by combining TM1m and TE1m spherical modes, provided that the stored energy in the antenna spherical volume is totally suppressed. Using closed-form expressions...... for a multiarm spherical helix antenna confirm the theoretical predictions. For example, a 4-arm spherical helix antenna with a magnetic-coated perfectly electrically conducting core (ka=0.254) exhibits the Q of 0.66 times the Chu lower bound, or 1.25 times the minimum Q....

PERFORMANCE OPTIMIZATION OF LINEAR INDUCTION MOTOR BY EDDY CURRENT AND FLUX DENSITY DISTRIBUTION ANALYSIS

Directory of Open Access Journals (Sweden)

M. S. MANNA

2011-12-01

Full Text Available The development of electromagnetic devices as machines, transformers, heating devices confronts the engineers with several problems. For the design of an optimized geometry and the prediction of the operational behaviour an accurate knowledge of the dependencies of the field quantities inside the magnetic circuits is necessary. This paper provides the eddy current and core flux density distribution analysis in linear induction motor. Magnetic flux in the air gap of the Linear Induction Motor (LIM is reduced to various losses such as end effects, fringes, effect, skin effects etc. The finite element based software package COMSOL Multiphysics Inc. USA is used to get the reliable and accurate computational results for optimization the performance of Linear Induction Motor (LIM. The geometrical characteristics of LIM are varied to find the optimal point of thrust and minimum flux leakage during static and dynamic conditions.

Non Linear Modelling and Control of Hydraulic Actuators

Directory of Open Access Journals (Sweden)

B. Šulc

2002-01-01

Full Text Available This paper deals with non-linear modelling and control of a differential hydraulic actuator. The nonlinear state space equations are derived from basic physical laws. They are more powerful than the transfer function in the case of linear models, and they allow the application of an object oriented approach in simulation programs. The effects of all friction forces (static, Coulomb and viscous have been modelled, and many phenomena that are usually neglected are taken into account, e.g., the static term of friction, the leakage between the two chambers and external space. Proportional Differential (PD and Fuzzy Logic Controllers (FLC have been applied in order to make a comparison by means of simulation. Simulation is performed using Matlab/Simulink, and some of the results are compared graphically. FLC is tuned in a such way that it produces a constant control signal close to its maximum (or minimum, where possible. In the case of PD control the occurrence of peaks cannot be avoided. These peaks produce a very high velocity that oversteps the allowed values.

Updating Linear Schedules with Lowest Cost: a Linear Programming Model

Science.gov (United States)

Biruk, Sławomir; Jaśkowski, Piotr; Czarnigowska, Agata

2017-10-01

Many civil engineering projects involve sets of tasks repeated in a predefined sequence in a number of work areas along a particular route. A useful graphical representation of schedules of such projects is time-distance diagrams that clearly show what process is conducted at a particular point of time and in particular location. With repetitive tasks, the quality of project performance is conditioned by the ability of the planner to optimize workflow by synchronizing the works and resources, which usually means that resources are planned to be continuously utilized. However, construction processes are prone to risks, and a fully synchronized schedule may expire if a disturbance (bad weather, machine failure etc.) affects even one task. In such cases, works need to be rescheduled, and another optimal schedule should be built for the changed circumstances. This typically means that, to meet the fixed completion date, durations of operations have to be reduced. A number of measures are possible to achieve such reduction: working overtime, employing more resources or relocating resources from less to more critical tasks, but they all come at a considerable cost and affect the whole project. The paper investigates the problem of selecting the measures that reduce durations of tasks of a linear project so that the cost of these measures is kept to the minimum and proposes an algorithm that could be applied to find optimal solutions as the need to reschedule arises. Considering that civil engineering projects, such as road building, usually involve less process types than construction projects, the complexity of scheduling problems is lower, and precise optimization algorithms can be applied. Therefore, the authors put forward a linear programming model of the problem and illustrate its principle of operation with an example.

Application of fast orthogonal search to linear and nonlinear stochastic systems

DEFF Research Database (Denmark)

Chon, K H; Korenberg, M J; Holstein-Rathlou, N H

1997-01-01

Standard deterministic autoregressive moving average (ARMA) models consider prediction errors to be unexplainable noise sources. The accuracy of the estimated ARMA model parameters depends on producing minimum prediction errors. In this study, an accurate algorithm is developed for estimating...... linear and nonlinear stochastic ARMA model parameters by using a method known as fast orthogonal search, with an extended model containing prediction errors as part of the model estimation process. The extended algorithm uses fast orthogonal search in a two-step procedure in which deterministic terms...

Linear Optics From Closed Orbits (LOCO): An Introduction

International Nuclear Information System (INIS)

Safranek, James

2009-01-01

The LOCO code is used to find and correct errors in the linear optics of storage rings. The original FORTRAN code was written to correct the optics of the NSLS X-Ray ring, and was applied soon thereafter to debug problems with the ALS optics. The ideas used in the code were developed from previous work at SLAC. Several years ago, LOCO was rewritten in MATLAB. As described in this newsletter, the MATLAB version includes a user-friendly interface, with many useful fitting and analysis options. LOCO has been used at many accelerators. Presently, a search for LOCO in the text of papers on the Joint Accelerator Conferences Website yields 107 papers. A comprehensive survey of applications will not be included here. Details of recent results at a few light sources are included in this newsletter. In the past, the quality of LOCO fitting results varied significantly, depending on the storage ring. In particular, the results were mixed for colliding beam facilities, where there tend to be fewer BPMs that in light sources. Fitting rings with less BPM data to constrain the fit optics parameters often led to unreasonably large fit quadrupole gradient variations. Recently, modifications have been made to the LOCO fitting algorithm which leads to much better results when the BPM data does not tightly constrain the fit parameters. The modifications are described in this newsletter, and an example of results with this new algorithm is included.

Unsupervised Bayesian linear unmixing of gene expression microarrays.

Science.gov (United States)

Bazot, Cécile; Dobigeon, Nicolas; Tourneret, Jean-Yves; Zaas, Aimee K; Ginsburg, Geoffrey S; Hero, Alfred O

2013-03-19

This paper introduces a new constrained model and the corresponding algorithm, called unsupervised Bayesian linear unmixing (uBLU), to identify biological signatures from high dimensional assays like gene expression microarrays. The basis for uBLU is a Bayesian model for the data samples which are represented as an additive mixture of random positive gene signatures, called factors, with random positive mixing coefficients, called factor scores, that specify the relative contribution of each signature to a specific sample. The particularity of the proposed method is that uBLU constrains the factor loadings to be non-negative and the factor scores to be probability distributions over the factors. Furthermore, it also provides estimates of the number of factors. A Gibbs sampling strategy is adopted here to generate random samples according to the posterior distribution of the factors, factor scores, and number of factors. These samples are then used to estimate all the unknown parameters. Firstly, the proposed uBLU method is applied to several simulated datasets with known ground truth and compared with previous factor decomposition methods, such as principal component analysis (PCA), non negative matrix factorization (NMF), Bayesian factor regression modeling (BFRM), and the gradient-based algorithm for general matrix factorization (GB-GMF). Secondly, we illustrate the application of uBLU on a real time-evolving gene expression dataset from a recent viral challenge study in which individuals have been inoculated with influenza A/H3N2/Wisconsin. We show that the uBLU method significantly outperforms the other methods on the simulated and real data sets considered here. The results obtained on synthetic and real data illustrate the accuracy of the proposed uBLU method when compared to other factor decomposition methods from the literature (PCA, NMF, BFRM, and GB-GMF). The uBLU method identifies an inflammatory component closely associated with clinical symptom scores

Minimum entropy production principle

Czech Academy of Sciences Publication Activity Database

Maes, C.; Netočný, Karel

2013-01-01

Roč. 8, č. 7 (2013), s. 9664-9677 ISSN 1941-6016 Institutional support: RVO:68378271 Keywords : MINEP Subject RIV: BE - Theoretical Physics http://www.scholarpedia.org/article/Minimum_entropy_production_principle

Dynamical insurance models with investment: Constrained singular problems for integrodifferential equations

Science.gov (United States)

Belkina, T. A.; Konyukhova, N. B.; Kurochkin, S. V.

2016-01-01

Previous and new results are used to compare two mathematical insurance models with identical insurance company strategies in a financial market, namely, when the entire current surplus or its constant fraction is invested in risky assets (stocks), while the rest of the surplus is invested in a risk-free asset (bank account). Model I is the classical Cramér-Lundberg risk model with an exponential claim size distribution. Model II is a modification of the classical risk model (risk process with stochastic premiums) with exponential distributions of claim and premium sizes. For the survival probability of an insurance company over infinite time (as a function of its initial surplus), there arise singular problems for second-order linear integrodifferential equations (IDEs) defined on a semiinfinite interval and having nonintegrable singularities at zero: model I leads to a singular constrained initial value problem for an IDE with a Volterra integral operator, while II model leads to a more complicated nonlocal constrained problem for an IDE with a non-Volterra integral operator. A brief overview of previous results for these two problems depending on several positive parameters is given, and new results are presented. Additional results are concerned with the formulation, analysis, and numerical study of "degenerate" problems for both models, i.e., problems in which some of the IDE parameters vanish; moreover, passages to the limit with respect to the parameters through which we proceed from the original problems to the degenerate ones are singular for small and/or large argument values. Such problems are of mathematical and practical interest in themselves. Along with insurance models without investment, they describe the case of surplus completely invested in risk-free assets, as well as some noninsurance models of surplus dynamics, for example, charity-type models.

A Spatially Constrained Multi-autoencoder Approach for Multivariate Geochemical Anomaly Recognition

Science.gov (United States)

Lirong, C.; Qingfeng, G.; Renguang, Z.; Yihui, X.

2017-12-01

Separating and recognizing geochemical anomalies from the geochemical background is one of the key tasks in geochemical exploration. Many methods have been developed, such as calculating the mean ±2 standard deviation, and fractal/multifractal models. In recent years, deep autoencoder, a deep learning approach, have been used for multivariate geochemical anomaly recognition. While being able to deal with the non-normal distributions of geochemical concentrations and the non-linear relationships among them, this self-supervised learning method does not take into account the spatial heterogeneity of geochemical background and the uncertainty induced by the randomly initialized weights of neurons, leading to ineffective recognition of weak anomalies. In this paper, we introduce a spatially constrained multi-autoencoder (SCMA) approach for multivariate geochemical anomaly recognition, which includes two steps: spatial partitioning and anomaly score computation. The first step divides the study area into multiple sub-regions to segregate the geochemical background, by grouping the geochemical samples through K-means clustering, spatial filtering, and spatial constraining rules. In the second step, for each sub-region, a group of autoencoder neural networks are constructed with an identical structure but different initial weights on neurons. Each autoencoder is trained using the geochemical samples within the corresponding sub-region to learn the sub-regional geochemical background. The best autoencoder of a group is chosen as the final model for the corresponding sub-region. The anomaly score at each location can then be calculated as the euclidean distance between the observed concentrations and reconstructed concentrations of geochemical elements.The experiments using the geochemical data and Fe deposits in the southwestern Fujian province of China showed that our SCMA approach greatly improved the recognition of weak anomalies, achieving the AUC of 0.89, compared

Wronskian type solutions for the vector k-constrained KP hierarchy

International Nuclear Information System (INIS)

Zhang Youjin.

1995-07-01

Motivated by a relation of the 1-constrained Kadomtsev-Petviashvili (KP) hierarchy with the 2 component KP hierarchy, the tau-conditions of the vector k-constrained KP hierarchy are constructed by using an analogue of the Baker-Akhiezer (m + 1)-point function. These tau functions are expressed in terms of Wronskian type determinants. (author). 20 refs

A constrained supersymmetric left-right model

Energy Technology Data Exchange (ETDEWEB)

Hirsch, Martin [AHEP Group, Instituto de Física Corpuscular - C.S.I.C./Universitat de València, Edificio de Institutos de Paterna, Apartado 22085, E-46071 València (Spain); Krauss, Manuel E. [Bethe Center for Theoretical Physics & Physikalisches Institut der Universität Bonn, Nussallee 12, 53115 Bonn (Germany); Institut für Theoretische Physik und Astronomie, Universität Würzburg,Emil-Hilb-Weg 22, 97074 Wuerzburg (Germany); Opferkuch, Toby [Bethe Center for Theoretical Physics & Physikalisches Institut der Universität Bonn, Nussallee 12, 53115 Bonn (Germany); Porod, Werner [Institut für Theoretische Physik und Astronomie, Universität Würzburg,Emil-Hilb-Weg 22, 97074 Wuerzburg (Germany); Staub, Florian [Theory Division, CERN,1211 Geneva 23 (Switzerland)

2016-03-02

We present a supersymmetric left-right model which predicts gauge coupling unification close to the string scale and extra vector bosons at the TeV scale. The subtleties in constructing a model which is in agreement with the measured quark masses and mixing for such a low left-right breaking scale are discussed. It is shown that in the constrained version of this model radiative breaking of the gauge symmetries is possible and a SM-like Higgs is obtained. Additional CP-even scalars of a similar mass or even much lighter are possible. The expected mass hierarchies for the supersymmetric states differ clearly from those of the constrained MSSM. In particular, the lightest down-type squark, which is a mixture of the sbottom and extra vector-like states, is always lighter than the stop. We also comment on the model’s capability to explain current anomalies observed at the LHC.

Time-varying linear control for tiltrotor aircraft

Directory of Open Access Journals (Sweden)

Jing ZHANG

2018-04-01

Full Text Available Tiltrotor aircraft have three flight modes: helicopter mode, airplane mode, and transition mode. A tiltrotor has characteristics of highly nonlinear, time-varying flight dynamics and inertial/control couplings in its transition mode. It can transit from the helicopter mode to the airplane mode by tilting its nacelles, and an effective controller is crucial to accomplish tilting transition missions. Longitudinal dynamic characteristics of the tiltrotor are described by a nonlinear Lagrange-form model, which takes into account inertial/control couplings and aerodynamic interferences. Reference commands for airspeed velocity and attitude in the transition mode are calculated dynamically by visiting a command library which is founded in advance by analyzing the flight envelope of the tiltrotor. A Time-Varying Linear (TVL model is obtained using a Taylor-expansion based online linearization technique from the nonlinear model. Subsequently, based on an optimal control concept, an online optimization based control method with input constraints considered is proposed. To validate the proposed control method, three typical tilting transition missions are simulated using the nonlinear model of XV-15 tiltrotor aircraft. Simulation results show that the controller can be used to control the tiltrotor throughout its operating envelop which includes a transition flight, and can also deal with vertical gust disturbances. Keywords: Constrained optimal control, Inertia/control couplings, Tiltrotor aircraft, Time-varying control, Transition mode

Constraining primordial non-Gaussianity with cosmological weak lensing: shear and flexion

International Nuclear Information System (INIS)

Fedeli, C.; Bartelmann, M.; Moscardini, L.

2012-01-01

, improves the shear constraints by ∼ 10% when added. However on such small scales the highly non-linear clustering of matter, the impact of baryonic physics, and the non-Gaussian part of the covariance matrix make any error estimation uncertain. By considering lower, and possibly more realistic, values of the flexion intrinsic shape noise results in flexion constraining power being a factor of ∼ 2 better than that of shear, and the bounds on σ 8 and f NL being improved by a factor of ∼ 3 upon their combination

Ion trapping in one-minimum potentials via charge-exchange collisions

International Nuclear Information System (INIS)

Maier, H.; Kuhn, S.

1994-01-01

A (1 d, 2 v), electrostatic, kinetics model for time-independent single-ended Q-machine states with a positively biased cold plate and a single internal minimum near the hot plate is presented. While the electrons are treated as collisionless, charge-exchange collisions between the ions and the neutral background gas atoms are taken into account by means of a linearized Boltzmann collision operator. The self-consistent plasma states are found by using an iterative analytic-numerical trajectory-simulation method in which the charge-density and potential distributions are alternately determined numerical results clearly demonstrate the sensitive role that trapped ions play in shaping the microscopic and macroscopic properties of the dc states under study. The trapped-ion distributions themselves are shown to be controlled critically by the detailed scattering conditions, which in turn are determined by the choice of the background properties. (author). 10 refs, 3 figs

A Methodology for Rapid Prototyping Peak-Constrained Least-Squares Bit-Serial Finite Impulse Response Filters in FPGAs

Directory of Open Access Journals (Sweden)

Alex Carreira

2003-05-01

Full Text Available Area-efficient peak-constrained least-squares (PCLS bit-serial finite impulse response (FIR filter implementations can be rapidly prototyped in field programmable gate arrays (FPGA with the methodology presented in this paper. Faster generation of the FPGA configuration bitstream is possible with a new application-specific mapping and placement method that uses JBits to avoid conventional general-purpose mapping and placement tools. JBits is a set of Java classes that provide an interface into the Xilinx Virtex FPGA configuration bitstream, allowing the user to generate new configuration bitstreams. PCLS coefficient generation allows passband-to-stopband energy ratio (PSR performance to be traded for a reduction in the filter's hardware cost without altering the minimum stopband attenuation. Fixed-point coefficients that meet the frequency response and hardware cost specifications can be generated with the PCLS method. It is not possible to meet these specifications solely by the quantization of floating-point coefficients generated in other methods.

Robust linear discriminant models to solve financial crisis in banking sectors

Science.gov (United States)

Lim, Yai-Fung; Yahaya, Sharipah Soaad Syed; Idris, Faoziah; Ali, Hazlina; Omar, Zurni

2014-12-01

Linear discriminant analysis (LDA) is a widely-used technique in patterns classification via an equation which will minimize the probability of misclassifying cases into their respective categories. However, the performance of classical estimators in LDA highly depends on the assumptions of normality and homoscedasticity. Several robust estimators in LDA such as Minimum Covariance Determinant (MCD), S-estimators and Minimum Volume Ellipsoid (MVE) are addressed by many authors to alleviate the problem of non-robustness of the classical estimates. In this paper, we investigate on the financial crisis of the Malaysian banking institutions using robust LDA and classical LDA methods. Our objective is to distinguish the "distress" and "non-distress" banks in Malaysia by using the LDA models. Hit ratio is used to validate the accuracy predictive of LDA models. The performance of LDA is evaluated by estimating the misclassification rate via apparent error rate. The results and comparisons show that the robust estimators provide a better performance than the classical estimators for LDA.

Convex optimisation approach to constrained fuel optimal control of spacecraft in close relative motion

Science.gov (United States)

Massioni, Paolo; Massari, Mauro

2018-05-01

This paper describes an interesting and powerful approach to the constrained fuel-optimal control of spacecraft in close relative motion. The proposed approach is well suited for problems under linear dynamic equations, therefore perfectly fitting to the case of spacecraft flying in close relative motion. If the solution of the optimisation is approximated as a polynomial with respect to the time variable, then the problem can be approached with a technique developed in the control engineering community, known as "Sum Of Squares" (SOS), and the constraints can be reduced to bounds on the polynomials. Such a technique allows rewriting polynomial bounding problems in the form of convex optimisation problems, at the cost of a certain amount of conservatism. The principles of the techniques are explained and some application related to spacecraft flying in close relative motion are shown.

Slope constrained Topology Optimization

DEFF Research Database (Denmark)

Petersson, J.; Sigmund, Ole

1998-01-01

The problem of minimum compliance topology optimization of an elastic continuum is considered. A general continuous density-energy relation is assumed, including variable thickness sheet models and artificial power laws. To ensure existence of solutions, the design set is restricted by enforcing...

Linear transceiver design for nonorthogonal amplify-and-forward protocol using a bit error rate criterion

KAUST Repository

Ahmed, Qasim Zeeshan

2014-04-01

The ever growing demand of higher data rates can now be addressed by exploiting cooperative diversity. This form of diversity has become a fundamental technique for achieving spatial diversity by exploiting the presence of idle users in the network. This has led to new challenges in terms of designing new protocols and detectors for cooperative communications. Among various amplify-and-forward (AF) protocols, the half duplex non-orthogonal amplify-and-forward (NAF) protocol is superior to other AF schemes in terms of error performance and capacity. However, this superiority is achieved at the cost of higher receiver complexity. Furthermore, in order to exploit the full diversity of the system an optimal precoder is required. In this paper, an optimal joint linear transceiver is proposed for the NAF protocol. This transceiver operates on the principles of minimum bit error rate (BER), and is referred as joint bit error rate (JBER) detector. The BER performance of JBER detector is superior to all the proposed linear detectors such as channel inversion, the maximal ratio combining, the biased maximum likelihood detectors, and the minimum mean square error. The proposed transceiver also outperforms previous precoders designed for the NAF protocol. © 2002-2012 IEEE.

Minimum emittance in TBA and MBA lattices

Science.gov (United States)

Xu, Gang; Peng, Yue-Mei

2015-03-01

For reaching a small emittance in a modern light source, triple bend achromats (TBA), theoretical minimum emittance (TME) and even multiple bend achromats (MBA) have been considered. This paper derived the necessary condition for achieving minimum emittance in TBA and MBA theoretically, where the bending angle of inner dipoles has a factor of 31/3 bigger than that of the outer dipoles. Here, we also calculated the conditions attaining the minimum emittance of TBA related to phase advance in some special cases with a pure mathematics method. These results may give some directions on lattice design.

Minimum emittance in TBA and MBA lattices

International Nuclear Information System (INIS)

Xu Gang; Peng Yuemei

2015-01-01

For reaching a small emittance in a modern light source, triple bend achromats (TBA), theoretical minimum emittance (TME) and even multiple bend achromats (MBA) have been considered. This paper derived the necessary condition for achieving minimum emittance in TBA and MBA theoretically, where the bending angle of inner dipoles has a factor of 3 1/3 bigger than that of the outer dipoles. Here, we also calculated the conditions attaining the minimum emittance of TBA related to phase advance in some special cases with a pure mathematics method. These results may give some directions on lattice design. (authors)

Linear Algebra and Smarandache Linear Algebra

OpenAIRE

Vasantha, Kandasamy

2003-01-01

The present book, on Smarandache linear algebra, not only studies the Smarandache analogues of linear algebra and its applications, it also aims to bridge the need for new research topics pertaining to linear algebra, purely in the algebraic sense. We have introduced Smarandache semilinear algebra, Smarandache bilinear algebra and Smarandache anti-linear algebra and their fuzzy equivalents. Moreover, in this book, we have brought out the study of linear algebra and vector spaces over finite p...

An algorithm for mass matrix calculation of internally constrained molecular geometries

International Nuclear Information System (INIS)

Aryanpour, Masoud; Dhanda, Abhishek; Pitsch, Heinz

2008-01-01

Dynamic models for molecular systems require the determination of corresponding mass matrix. For constrained geometries, these computations are often not trivial but need special considerations. Here, assembling the mass matrix of internally constrained molecular structures is formulated as an optimization problem. Analytical expressions are derived for the solution of the different possible cases depending on the rank of the constraint matrix. Geometrical interpretations are further used to enhance the solution concept. As an application, we evaluate the mass matrix for a constrained molecule undergoing an electron-transfer reaction. The preexponential factor for this reaction is computed based on the harmonic model

An algorithm for mass matrix calculation of internally constrained molecular geometries.

Science.gov (United States)

Aryanpour, Masoud; Dhanda, Abhishek; Pitsch, Heinz

2008-01-28

Dynamic models for molecular systems require the determination of corresponding mass matrix. For constrained geometries, these computations are often not trivial but need special considerations. Here, assembling the mass matrix of internally constrained molecular structures is formulated as an optimization problem. Analytical expressions are derived for the solution of the different possible cases depending on the rank of the constraint matrix. Geometrical interpretations are further used to enhance the solution concept. As an application, we evaluate the mass matrix for a constrained molecule undergoing an electron-transfer reaction. The preexponential factor for this reaction is computed based on the harmonic model.

41 CFR 50-202.2 - Minimum wage in all industries.

Science.gov (United States)

2010-07-01

... 41 Public Contracts and Property Management 1 2010-07-01 2010-07-01 true Minimum wage in all... Public Contracts PUBLIC CONTRACTS, DEPARTMENT OF LABOR 202-MINIMUM WAGE DETERMINATIONS Groups of Industries § 50-202.2 Minimum wage in all industries. In all industries, the minimum wage applicable to...

29 CFR 525.13 - Renewal of special minimum wage certificates.

Science.gov (United States)

2010-07-01

... 29 Labor 3 2010-07-01 2010-07-01 false Renewal of special minimum wage certificates. 525.13... minimum wage certificates. (a) Applications may be filed for renewal of special minimum wage certificates.... (c) Workers with disabilities may not continue to be paid special minimum wages after notice that an...

An Empirical Analysis of the Relationship between Minimum Wage ...

African Journals Online (AJOL)

An Empirical Analysis of the Relationship between Minimum Wage, Investment and Economic Growth in Ghana. ... In addition, the ratio of public investment to tax revenue must increase as minimum wage increases since such complementary changes are more likely to lead to economic growth. Keywords: minimum wage ...

12 CFR 3.6 - Minimum capital ratios.

Science.gov (United States)

2010-01-01

... should have well-diversified risks, including no undue interest rate risk exposure; excellent control... 12 Banks and Banking 1 2010-01-01 2010-01-01 false Minimum capital ratios. 3.6 Section 3.6 Banks and Banking COMPTROLLER OF THE CURRENCY, DEPARTMENT OF THE TREASURY MINIMUM CAPITAL RATIOS; ISSUANCE...

12 CFR 615.5330 - Minimum surplus ratios.

Science.gov (United States)

2010-01-01

... 12 Banks and Banking 6 2010-01-01 2010-01-01 false Minimum surplus ratios. 615.5330 Section 615.5330 Banks and Banking FARM CREDIT ADMINISTRATION FARM CREDIT SYSTEM FUNDING AND FISCAL AFFAIRS, LOAN POLICIES AND OPERATIONS, AND FUNDING OPERATIONS Surplus and Collateral Requirements § 615.5330 Minimum...

Self-constrained inversion of potential fields

Science.gov (United States)

Paoletti, V.; Ialongo, S.; Florio, G.; Fedi, M.; Cella, F.

2013-11-01

We present a potential-field-constrained inversion procedure based on a priori information derived exclusively from the analysis of the gravity and magnetic data (self-constrained inversion). The procedure is designed to be applied to underdetermined problems and involves scenarios where the source distribution can be assumed to be of simple character. To set up effective constraints, we first estimate through the analysis of the gravity or magnetic field some or all of the following source parameters: the source depth-to-the-top, the structural index, the horizontal position of the source body edges and their dip. The second step is incorporating the information related to these constraints in the objective function as depth and spatial weighting functions. We show, through 2-D and 3-D synthetic and real data examples, that potential field-based constraints, for example, structural index, source boundaries and others, are usually enough to obtain substantial improvement in the density and magnetization models.

New Exact Penalty Functions for Nonlinear Constrained Optimization Problems

Directory of Open Access Journals (Sweden)

Bingzhuang Liu

2014-01-01

Full Text Available For two kinds of nonlinear constrained optimization problems, we propose two simple penalty functions, respectively, by augmenting the dimension of the primal problem with a variable that controls the weight of the penalty terms. Both of the penalty functions enjoy improved smoothness. Under mild conditions, it can be proved that our penalty functions are both exact in the sense that local minimizers of the associated penalty problem are precisely the local minimizers of the original constrained problem.

A HARDCORE model for constraining an exoplanet's core size

Science.gov (United States)

Suissa, Gabrielle; Chen, Jingjing; Kipping, David

2018-05-01

The interior structure of an exoplanet is hidden from direct view yet likely plays a crucial role in influencing the habitability of the Earth analogues. Inferences of the interior structure are impeded by a fundamental degeneracy that exists between any model comprising more than two layers and observations constraining just two bulk parameters: mass and radius. In this work, we show that although the inverse problem is indeed degenerate, there exists two boundary conditions that enables one to infer the minimum and maximum core radius fraction, CRFmin and CRFmax. These hold true even for planets with light volatile envelopes, but require the planet to be fully differentiated and that layers denser than iron are forbidden. With both bounds in hand, a marginal CRF can also be inferred by sampling in-between. After validating on the Earth, we apply our method to Kepler-36b and measure CRFmin = (0.50 ± 0.07), CRFmax = (0.78 ± 0.02), and CRFmarg = (0.64 ± 0.11), broadly consistent with the Earth's true CRF value of 0.55. We apply our method to a suite of hypothetical measurements of synthetic planets to serve as a sensitivity analysis. We find that CRFmin and CRFmax have recovered uncertainties proportional to the relative error on the planetary density, but CRFmarg saturates to between 0.03 and 0.16 once (Δρ/ρ) drops below 1-2 per cent. This implies that mass and radius alone cannot provide any better constraints on internal composition once bulk density constraints hit around a per cent, providing a clear target for observers.

Robust C subroutines for non-linear optimization

DEFF Research Database (Denmark)

Brock, Pernille; Madsen, Kaj; Nielsen, Hans Bruun

2004-01-01

This report presents a package of robust and easy-to-use C subroutines for solving unconstrained and constrained non-linear optimization problems. The intention is that the routines should use the currently best algorithms available. All routines have standardized calls, and the user does not have...... by changing 1 to 0. The present report is a new and updated version of a previous report NI-91-03 with the same title, [16]. Both the previous and the present report describe a collection of subroutines, which have been translated from Fortran to C. The reason for writing the present report is that some...... of the C subroutines have been replaced by more effective and robust versions translated from the original Fortran subroutines to C by the Bandler Group, see [1]. Also the test examples have been modi ed to some extent. For a description of the original Fortran subroutines see the report [17]. The software...

Hamiltonian analysis for linearly acceleration-dependent Lagrangians

Energy Technology Data Exchange (ETDEWEB)

Cruz, Miguel, E-mail: miguelcruz02@uv.mx, E-mail: roussjgc@gmail.com, E-mail: molgado@fc.uaslp.mx, E-mail: efrojas@uv.mx; Gómez-Cortés, Rosario, E-mail: miguelcruz02@uv.mx, E-mail: roussjgc@gmail.com, E-mail: molgado@fc.uaslp.mx, E-mail: efrojas@uv.mx; Rojas, Efraín, E-mail: miguelcruz02@uv.mx, E-mail: roussjgc@gmail.com, E-mail: molgado@fc.uaslp.mx, E-mail: efrojas@uv.mx [Facultad de Física, Universidad Veracruzana, 91000 Xalapa, Veracruz, México (Mexico); Molgado, Alberto, E-mail: miguelcruz02@uv.mx, E-mail: roussjgc@gmail.com, E-mail: molgado@fc.uaslp.mx, E-mail: efrojas@uv.mx [Facultad de Ciencias, Universidad Autónoma de San Luis Potosí, Avenida Salvador Nava S/N Zona Universitaria, CP 78290 San Luis Potosí, SLP, México (Mexico)

2016-06-15

We study the constrained Ostrogradski-Hamilton framework for the equations of motion provided by mechanical systems described by second-order derivative actions with a linear dependence in the accelerations. We stress out the peculiar features provided by the surface terms arising for this type of theories and we discuss some important properties for this kind of actions in order to pave the way for the construction of a well defined quantum counterpart by means of canonical methods. In particular, we analyse in detail the constraint structure for these theories and its relation to the inherent conserved quantities where the associated energies together with a Noether charge may be identified. The constraint structure is fully analyzed without the introduction of auxiliary variables, as proposed in recent works involving higher order Lagrangians. Finally, we also provide some examples where our approach is explicitly applied and emphasize the way in which our original arrangement results in propitious for the Hamiltonian formulation of covariant field theories.

5 CFR 551.601 - Minimum age standards.

Science.gov (United States)

2010-01-01

... ADMINISTRATION UNDER THE FAIR LABOR STANDARDS ACT Child Labor § 551.601 Minimum age standards. (a) 16-year... subject to its child labor provisions, with certain exceptions not applicable here. (b) 18-year minimum... occupation found and declared by the Secretary of Labor to be particularly hazardous for the employment of...

12 CFR 932.8 - Minimum liquidity requirements.

Science.gov (United States)

2010-01-01

... 12 Banks and Banking 7 2010-01-01 2010-01-01 false Minimum liquidity requirements. 932.8 Section... CAPITAL STANDARDS FEDERAL HOME LOAN BANK CAPITAL REQUIREMENTS § 932.8 Minimum liquidity requirements. In addition to meeting the deposit liquidity requirements contained in § 965.3 of this chapter, each Bank...

Bounds on the Capacity of Weakly constrained two-dimensional Codes

DEFF Research Database (Denmark)

Forchhammer, Søren

2002-01-01

Upper and lower bounds are presented for the capacity of weakly constrained two-dimensional codes. The maximum entropy is calculated for two simple models of 2-D codes constraining the probability of neighboring 1s as an example. For given models of the coded data, upper and lower bounds...... on the capacity for 2-D channel models based on occurrences of neighboring 1s are considered....

[Hospitals failing minimum volumes in 2004: reasons and consequences].

Science.gov (United States)

Geraedts, M; Kühnen, C; Cruppé, W de; Blum, K; Ohmann, C

2008-02-01

In 2004 Germany introduced annual minimum volumes nationwide on five surgical procedures: kidney, liver, stem cell transplantation, complex oesophageal, and pancreatic interventions. Hospitals that fail to reach the minimum volumes are no longer allowed to perform the respective procedures unless they raise one of eight legally accepted exceptions. The goal of our study was to investigate how many hospitals fell short of the minimum volumes in 2004, whether and how this was justified, and whether hospitals that failed the requirements experienced any consequences. We analysed data on meeting the minimum volume requirements in 2004 that all German hospitals were obliged to publish as part of their biannual structured quality reports. We performed telephone interviews: a) with all hospitals not achieving the minimum volumes for complex oesophageal, and pancreatic interventions, and b) with the national umbrella organisations of all German sickness funds. In 2004, one quarter of all German acute care hospitals (N=485) performed 23,128 procedures where minimum volumes applied. 197 hospitals (41%) did not meet at least one of the minimum volumes. These hospitals performed N=715 procedures (3.1%) where the minimum volumes were not met. In 43% of these cases the hospitals raised legally accepted exceptions. In 33% of the cases the hospitals argued using reasons that were not legally acknowledged. 69% of those hospitals that failed to achieve the minimum volumes for complex oesophageal and pancreatic interventions did not experience any consequences from the sickness funds. However, one third of those hospitals reported that the sickness funds addressed the issue and partially announced consequences for the future. The sickness funds' umbrella organisations stated that there were only sparse activities related to the minimum volumes and that neither uniform registrations nor uniform proceedings in case of infringements of the standards had been agreed upon. In spite of the

Physics constrained nonlinear regression models for time series

International Nuclear Information System (INIS)

Majda, Andrew J; Harlim, John

2013-01-01

A central issue in contemporary science is the development of data driven statistical nonlinear dynamical models for time series of partial observations of nature or a complex physical model. It has been established recently that ad hoc quadratic multi-level regression (MLR) models can have finite-time blow up of statistical solutions and/or pathological behaviour of their invariant measure. Here a new class of physics constrained multi-level quadratic regression models are introduced, analysed and applied to build reduced stochastic models from data of nonlinear systems. These models have the advantages of incorporating memory effects in time as well as the nonlinear noise from energy conserving nonlinear interactions. The mathematical guidelines for the performance and behaviour of these physics constrained MLR models as well as filtering algorithms for their implementation are developed here. Data driven applications of these new multi-level nonlinear regression models are developed for test models involving a nonlinear oscillator with memory effects and the difficult test case of the truncated Burgers–Hopf model. These new physics constrained quadratic MLR models are proposed here as process models for Bayesian estimation through Markov chain Monte Carlo algorithms of low frequency behaviour in complex physical data. (paper)

Bidirectional Dynamic Diversity Evolutionary Algorithm for Constrained Optimization

Directory of Open Access Journals (Sweden)

Weishang Gao

2013-01-01

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

Systems analysis on the condition of market penetration for hydrogen technologies using linear programming model

International Nuclear Information System (INIS)

Kato, K.; Ihara, S.

1993-01-01

Hydrogen is expected to be an important energy carrier, especially in the frame of global warming problem solution. The purpose of this study is to examine the condition of market penetration of hydrogen technologies in reducing CO 2 emissions. A multi-time-period linear programming model (MARKAL, Market Allocation)) is used to explore technology options and cost for meeting the energy demands while reducing CO 2 emissions from energy systems. The results show that hydrogen technologies become economical when CO 2 emissions are stringently constrained. 9 figs., 2 refs

The Distribution of the Sample Minimum-Variance Frontier

OpenAIRE

Raymond Kan; Daniel R. Smith

2008-01-01

In this paper, we present a finite sample analysis of the sample minimum-variance frontier under the assumption that the returns are independent and multivariate normally distributed. We show that the sample minimum-variance frontier is a highly biased estimator of the population frontier, and we propose an improved estimator of the population frontier. In addition, we provide the exact distribution of the out-of-sample mean and variance of sample minimum-variance portfolios. This allows us t...

A new methodological development for solving linear bilevel integer programming problems in hybrid fuzzy environment

Directory of Open Access Journals (Sweden)

Animesh Biswas

2016-04-01

Full Text Available This paper deals with fuzzy goal programming approach to solve fuzzy linear bilevel integer programming problems with fuzzy probabilistic constraints following Pareto distribution and Frechet distribution. In the proposed approach a new chance constrained programming methodology is developed from the view point of managing those probabilistic constraints in a hybrid fuzzy environment. A method of defuzzification of fuzzy numbers using ?-cut has been adopted to reduce the problem into a linear bilevel integer programming problem. The individual optimal value of the objective of each DM is found in isolation to construct the fuzzy membership goals. Finally, fuzzy goal programming approach is used to achieve maximum degree of each of the membership goals by minimizing under deviational variables in the decision making environment. To demonstrate the efficiency of the proposed approach, a numerical example is provided.

24 CFR 891.145 - Owner deposit (Minimum Capital Investment).

Science.gov (United States)

2010-04-01

... General Program Requirements § 891.145 Owner deposit (Minimum Capital Investment). As a Minimum Capital... Investment shall be one-half of one percent (0.5%) of the HUD-approved capital advance, not to exceed $25,000. ... 24 Housing and Urban Development 4 2010-04-01 2010-04-01 false Owner deposit (Minimum Capital...

Linearity improvement on wide-range log signal of neutron measurement system for HANARO

International Nuclear Information System (INIS)

Kim, Young-Ki; Tuetken, Jeffrey S.

1998-01-01

This paper discusses engineering activities for improving the linearity characteristics of the Log Power signal from the neutron measurement system for HANARO. This neutron measurement system uses a fission chamber based detector which covers 10.3 decade-wide range from 10 -8 % full power(FP) up to 200%FP, The Log Power signal is designed to control the reactor at low power levels where most of the reactor physics tests are carried out. Therefore, the linearity characteristics of the Log Power signal is the major factor for accurate reactor power control. During the commissioning of the neutron measurement system, it was found that the linearity characteristics of the Log Power signal, especially near 10 -2 %FP, were not accurate enough for controlling the reactor during physics testing. Analysis of the system linearity data directly measured with reactor operating determined that the system was not operating per the design characteristics established from previous installations. The linearity data, which were taken as the reactor was increased in power, were sent to manufacturer's engineering group and a follow-up measures based on the analysis were then fed back to the field. Through step by step trouble-shooting activities, which included minor circuit modifications and alignment procedure changes, the linearity characteristics have been successfully improved and now exceed minimum performance requirements. This paper discusses the trouble-shooting techniques applied, the changes in the linearity characteristics, special circumstances in the HANARO application and the final resolution. (author)

Sensorless State-Space Control of Elastic Two-Inertia Drive System Using a Minimum State Order Observer

Directory of Open Access Journals (Sweden)

V. Comnac

2009-12-01

Full Text Available The paper presents sensorless state-space control of two-inertia drive system with resilient coupling. The control structure contains an I+PI controller for load speed regulation and a state feedback controller for effective vibration suppression of the elastic coupling. Mechanical state variable of two-inertia drive are obtained by using a linear minimum-order (Gopinath state observer. The design of the combined (I+PI and state feedback controller is achieved with the extended version of the modulus criterion [5]. The dynamic behavior of presented control structure has been examined, for different conditions, using MATLAB/SIMULINK simulation.

Robustness of quantum correlations against linear noise

International Nuclear Information System (INIS)

Guo, Zhihua; Cao, Huaixin; Qu, Shixian

2016-01-01

Relative robustness of quantum correlations (RRoQC) of a bipartite state is firstly introduced relative to a classically correlated state. Robustness of quantum correlations (RoQC) of a bipartite state is then defined as the minimum of RRoQC of the state relative to all classically correlated ones. It is proved that as a function on quantum states, RoQC is nonnegative, lower semi-continuous and neither convex nor concave; especially, it is zero if and only if the state is classically correlated. Thus, RoQC not only quantifies the endurance of quantum correlations of a state against linear noise, but also can be used to distinguish between quantum and classically correlated states. Furthermore, the effects of local quantum channels on the robustness are explored and characterized. (paper)

Reduction of Linear Programming to Linear Approximation

OpenAIRE

Vaserstein, Leonid N.

2006-01-01

It is well known that every Chebyshev linear approximation problem can be reduced to a linear program. In this paper we show that conversely every linear program can be reduced to a Chebyshev linear approximation problem.

Construction of Healthy and Palatable Diet for Low Socioeconomic Female Adults using Linear Programming

OpenAIRE

Roslee Rajikan; Nurul Izza Ahmad Zaidi; Siti Masitah Elias; Suzana Shahar; Zahara Abd Manaf; Noor Aini Md Yusoff

2017-01-01

Differences in socioeconomic profile may influences healthy food choices, particularly among individuals with low socioeconomic status. Thus, high-energy dense foods become the preferences compared to high nutritional content foods due to their cheaper price. The present study aims to develop healthy and palatable diet at the minimum cost based on Malaysian Dietary Guidelines 2010 and Recommended Nutrient Intake 2005 via linear programming. A total of 96 female adults from low socioeconomic f...

Minimum Wages and the Distribution of Family Incomes

OpenAIRE

Dube, Arindrajit

2017-01-01

Using the March Current Population Survey data from 1984 to 2013, I provide a comprehensive evaluation of how minimum wage policies influence the distribution of family incomes. I find robust evidence that higher minimum wages shift down the cumulative distribution of family incomes at the bottom, reducing the share of non-elderly individuals with incomes below 50, 75, 100, and 125 percent of the federal poverty threshold. The long run (3 or more years) minimum wage elasticity of the non-elde...

Constrained systems described by Nambu mechanics

International Nuclear Information System (INIS)

Lassig, C.C.; Joshi, G.C.

1996-01-01

Using the framework of Nambu's generalised mechanics, we obtain a new description of constrained Hamiltonian dynamics, involving the introduction of another degree of freedom in phase space, and the necessity of defining the action integral on a world sheet. We also discuss the problem of quantizing Nambu mechanics. (authors). 5 refs