Measurement of H'(0.07) with pulse height weighting integration method
Liye, LIU; Gang, JIN; Jizeng, MA
2002-01-01
H'(0.07) is an important quantity for radiation field measurement in health physics. One of the plastic scintillator measurement methods is employing the weak current produced by PMT. However, there are some weaknesses in the current method. For instance: sensitive to environment humidity and temperature, non-linearity energy response. In order to increase the precision of H'(0.07) measurement, a Pulse Height Weighting Integration Method is introduced for its advantages: low noise, high sensitivity, data processable, wide measurement range. Pulse Height Weighting Integration Method seems to be acceptable to measure directional dose equivalent. The representative theoretical energy response of the pre-described method accords with the preliminary experiment result
Improving Allergen Prediction in Main Crops Using a Weighted Integrative Method.
Li, Jing; Wang, Jing; Li, Jing
2017-12-01
As a public health problem, food allergy is frequently caused by food allergy proteins, which trigger a type-I hypersensitivity reaction in the immune system of atopic individuals. The food allergens in our daily lives are mainly from crops including rice, wheat, soybean and maize. However, allergens in these main crops are far from fully uncovered. Although some bioinformatics tools or methods predicting the potential allergenicity of proteins have been proposed, each method has their limitation. In this paper, we built a novel algorithm PREAL W , which integrated PREAL, FAO/WHO criteria and motif-based method by a weighted average score, to benefit the advantages of different methods. Our results illustrated PREAL W has better performance significantly in the crops' allergen prediction. This integrative allergen prediction algorithm could be useful for critical food safety matters. The PREAL W could be accessed at http://lilab.life.sjtu.edu.cn:8080/prealw .
Accelerated gradient methods for constrained image deblurring
Bonettini, S; Zanella, R; Zanni, L; Bertero, M
2008-01-01
In this paper we propose a special gradient projection method for the image deblurring problem, in the framework of the maximum likelihood approach. We present the method in a very general form and we give convergence results under standard assumptions. Then we consider the deblurring problem and the generality of the proposed algorithm allows us to add a energy conservation constraint to the maximum likelihood problem. In order to improve the convergence rate, we devise appropriate scaling strategies and steplength updating rules, especially designed for this application. The effectiveness of the method is evaluated by means of a computational study on astronomical images corrupted by Poisson noise. Comparisons with standard methods for image restoration, such as the expectation maximization algorithm, are also reported.
Constrained potential method for false vacuum decays
Park, Jae-hyeon
2010-11-01
A procedure is reported for numerical analysis of false vacuum transition in a model with multiple scalar fields. It is a refined version of the approach by Konstandin and Huber. The alteration makes it possible to tackle a class of problems that was difficult or unsolvable with the original method, i.e. those with a distant or nonexistent true vacuum. An example with an unbounded-from-below direction is presented. (orig.)
Constrained variable projection method for blind deconvolution
Cornelio, A; Piccolomini, E Loli; Nagy, J G
2012-01-01
This paper is focused on the solution of the blind deconvolution problem, here modeled as a separable nonlinear least squares problem. The well known ill-posedness, both on recovering the blurring operator and the true image, makes the problem really difficult to handle. We show that, by imposing appropriate constraints on the variables and with well chosen regularization parameters, it is possible to obtain an objective function that is fairly well behaved. Hence, the resulting nonlinear minimization problem can be effectively solved by classical methods, such as the Gauss-Newton algorithm.
Superalloy design - A Monte Carlo constrained optimization method
Stander, CM
1996-01-01
Full Text Available optimization method C. M. Stander Division of Materials Science and Technology, CSIR, PO Box 395, Pretoria, Republic of South Africa Received 74 March 1996; accepted 24 June 1996 A method, based on Monte Carlo constrained... successful hit, i.e. when Liow < LMP,,, < Lhiph, and for all the properties, Pj?, < P, < Pi@?. If successful this hit falls within the ROA. Repeat steps 4 and 5 to find at least ten (or more) successful hits with values...
Exact methods for time constrained routing and related scheduling problems
Kohl, Niklas
1995-01-01
of customers. In the VRPTW customers must be serviced within a given time period - a so called time window. The objective can be to minimize operating costs (e.g. distance travelled), fixed costs (e.g. the number of vehicles needed) or a combination of these component costs. During the last decade optimization......This dissertation presents a number of optimization methods for the Vehicle Routing Problem with Time Windows (VRPTW). The VRPTW is a generalization of the well known capacity constrained Vehicle Routing Problem (VRP), where a fleet of vehicles based at a central depot must service a set...... of J?rnsten, Madsen and S?rensen (1986), which has been tested computationally by Halse (1992). Both methods decompose the problem into a series of time and capacity constrained shotest path problems. This yields a tight lower bound on the optimal objective, and the dual gap can often be closed...
Antifungal susceptibility testing method for resource constrained laboratories
Khan S
2006-01-01
Full Text Available Purpose: In resource-constrained laboratories of developing countries determination of antifungal susceptibility testing by NCCLS/CLSI method is not always feasible. We describe herein a simple yet comparable method for antifungal susceptibility testing. Methods: Reference MICs of 72 fungal isolates including two quality control strains were determined by NCCLS/CLSI methods against fluconazole, itraconazole, voriconazole, amphotericin B and cancidas. Dermatophytes were also tested against terbinafine. Subsequently, on selection of optimum conditions, MIC was determined for all the fungal isolates by semisolid antifungal agar susceptibility method in Brain heart infusion broth supplemented with 0.5% agar (BHIA without oil overlay and results were compared with those obtained by reference NCCLS/CLSI methods. Results: Comparable results were obtained by NCCLS/CLSI and semisolid agar susceptibility (SAAS methods against quality control strains. MICs for 72 isolates did not differ by more than one dilution for all drugs by SAAS. Conclusions: SAAS using BHIA without oil overlay provides a simple and reproducible method for obtaining MICs against yeast, filamentous fungi and dermatophytes in resource-constrained laboratories.
An improved partial bundle method for linearly constrained minimax problems
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.
Basis set approach in the constrained interpolation profile method
Utsumi, T.; Koga, J.; Yabe, T.; Ogata, Y.; Matsunaga, E.; Aoki, T.; Sekine, M.
2003-07-01
We propose a simple polynomial basis-set that is easily extendable to any desired higher-order accuracy. This method is based on the Constrained Interpolation Profile (CIP) method and the profile is chosen so that the subgrid scale solution approaches the real solution by the constraints from the spatial derivative of the original equation. Thus the solution even on the subgrid scale becomes consistent with the master equation. By increasing the order of the polynomial, this solution quickly converges. 3rd and 5th order polynomials are tested on the one-dimensional Schroedinger equation and are proved to give solutions a few orders of magnitude higher in accuracy than conventional methods for lower-lying eigenstates. (author)
A Sequential Quadratically Constrained Quadratic Programming Method of Feasible Directions
Jian Jinbao; Hu Qingjie; Tang Chunming; Zheng Haiyan
2007-01-01
In this paper, a sequential quadratically constrained quadratic programming method of feasible directions is proposed for the optimization problems with nonlinear inequality constraints. At each iteration of the proposed algorithm, a feasible direction of descent is obtained by solving only one subproblem which consist of a convex quadratic objective function and simple quadratic inequality constraints without the second derivatives of the functions of the discussed problems, and such a subproblem can be formulated as a second-order cone programming which can be solved by interior point methods. To overcome the Maratos effect, an efficient higher-order correction direction is obtained by only one explicit computation formula. The algorithm is proved to be globally convergent and superlinearly convergent under some mild conditions without the strict complementarity. Finally, some preliminary numerical results are reported
A Globally Convergent Matrix-Free Method for Constrained Equations and Its Linear Convergence Rate
Min Sun
2014-01-01
Full Text Available A matrix-free method for constrained equations is proposed, which is a combination of the well-known PRP (Polak-Ribière-Polyak conjugate gradient method and the famous hyperplane projection method. The new method is not only derivative-free, but also completely matrix-free, and consequently, it can be applied to solve large-scale constrained equations. We obtain global convergence of the new method without any differentiability requirement on the constrained equations. Compared with the existing gradient methods for solving such problem, the new method possesses linear convergence rate under standard conditions, and a relax factor γ is attached in the update step to accelerate convergence. Preliminary numerical results show that it is promising in practice.
A Spatial Shape Constrained Clustering Method for Mammographic Mass Segmentation
Jian-Yong Lou
2015-01-01
error of 7.18% for well-defined masses (or 8.06% for ill-defined masses was obtained by using DACF on MiniMIAS database, with 5.86% (or 5.55% and 6.14% (or 5.27% improvements as compared to the standard DA and fuzzy c-means methods.
San-Yang Liu
2014-01-01
Full Text Available Two unified frameworks of some sufficient descent conjugate gradient methods are considered. Combined with the hyperplane projection method of Solodov and Svaiter, they are extended to solve convex constrained nonlinear monotone equations. Their global convergence is proven under some mild conditions. Numerical results illustrate that these methods are efficient and can be applied to solve large-scale nonsmooth equations.
Subspace Barzilai-Borwein Gradient Method for Large-Scale Bound Constrained Optimization
Xiao Yunhai; Hu Qingjie
2008-01-01
An active set subspace Barzilai-Borwein gradient algorithm for large-scale bound constrained optimization is proposed. The active sets are estimated by an identification technique. The search direction consists of two parts: some of the components are simply defined; the other components are determined by the Barzilai-Borwein gradient method. In this work, a nonmonotone line search strategy that guarantees global convergence is used. Preliminary numerical results show that the proposed method is promising, and competitive with the well-known method SPG on a subset of bound constrained problems from CUTEr collection
Axelsson, Owe; Farouq, S.; Neytcheva, M.
2017-01-01
Roč. 74, č. 1 (2017), s. 19-37 ISSN 1017-1398 Institutional support: RVO:68145535 Keywords : PDE-constrained optimization problems * finite elements * iterative solution method s * preconditioning Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 1.241, year: 2016 https://link.springer.com/article/10.1007%2Fs11075-016-0136-5
Analysis of neutron and x-ray reflectivity data by constrained least-squares methods
Pedersen, J.S.; Hamley, I.W.
1994-01-01
. The coefficients in the series are determined by constrained nonlinear least-squares methods, in which the smoothest solution that agrees with the data is chosen. In the second approach the profile is expressed as a series of sine and cosine terms. A smoothness constraint is used which reduces the coefficients...
Axelsson, Owe; Farouq, S.; Neytcheva, M.
2017-01-01
Roč. 74, č. 1 (2017), s. 19-37 ISSN 1017-1398 Institutional support: RVO:68145535 Keywords : PDE-constrained optimization problems * finite elements * iterative solution methods * preconditioning Subject RIV: BA - General Mathematics OBOR OECD: Applied mathematics Impact factor: 1.241, year: 2016 https://link.springer.com/article/10.1007%2Fs11075-016-0136-5
ODE constrained mixture modelling: a method for unraveling subpopulation structures and dynamics.
Jan Hasenauer
2014-07-01
Full Text Available Functional cell-to-cell variability is ubiquitous in multicellular organisms as well as bacterial populations. Even genetically identical cells of the same cell type can respond differently to identical stimuli. Methods have been developed to analyse heterogeneous populations, e.g., mixture models and stochastic population models. The available methods are, however, either incapable of simultaneously analysing different experimental conditions or are computationally demanding and difficult to apply. Furthermore, they do not account for biological information available in the literature. To overcome disadvantages of existing methods, we combine mixture models and ordinary differential equation (ODE models. The ODE models provide a mechanistic description of the underlying processes while mixture models provide an easy way to capture variability. In a simulation study, we show that the class of ODE constrained mixture models can unravel the subpopulation structure and determine the sources of cell-to-cell variability. In addition, the method provides reliable estimates for kinetic rates and subpopulation characteristics. We use ODE constrained mixture modelling to study NGF-induced Erk1/2 phosphorylation in primary sensory neurones, a process relevant in inflammatory and neuropathic pain. We propose a mechanistic pathway model for this process and reconstructed static and dynamical subpopulation characteristics across experimental conditions. We validate the model predictions experimentally, which verifies the capabilities of ODE constrained mixture models. These results illustrate that ODE constrained mixture models can reveal novel mechanistic insights and possess a high sensitivity.
ODE constrained mixture modelling: a method for unraveling subpopulation structures and dynamics.
Hasenauer, Jan; Hasenauer, Christine; Hucho, Tim; Theis, Fabian J
2014-07-01
Functional cell-to-cell variability is ubiquitous in multicellular organisms as well as bacterial populations. Even genetically identical cells of the same cell type can respond differently to identical stimuli. Methods have been developed to analyse heterogeneous populations, e.g., mixture models and stochastic population models. The available methods are, however, either incapable of simultaneously analysing different experimental conditions or are computationally demanding and difficult to apply. Furthermore, they do not account for biological information available in the literature. To overcome disadvantages of existing methods, we combine mixture models and ordinary differential equation (ODE) models. The ODE models provide a mechanistic description of the underlying processes while mixture models provide an easy way to capture variability. In a simulation study, we show that the class of ODE constrained mixture models can unravel the subpopulation structure and determine the sources of cell-to-cell variability. In addition, the method provides reliable estimates for kinetic rates and subpopulation characteristics. We use ODE constrained mixture modelling to study NGF-induced Erk1/2 phosphorylation in primary sensory neurones, a process relevant in inflammatory and neuropathic pain. We propose a mechanistic pathway model for this process and reconstructed static and dynamical subpopulation characteristics across experimental conditions. We validate the model predictions experimentally, which verifies the capabilities of ODE constrained mixture models. These results illustrate that ODE constrained mixture models can reveal novel mechanistic insights and possess a high sensitivity.
A constrained Hartree-Fock-Bogoliubov equation derived from the double variational method
Onishi, Naoki; Horibata, Takatoshi.
1980-01-01
The double variational method is applied to the intrinsic state of the generalized BCS wave function. A constrained Hartree-Fock-Bogoliubov equation is derived explicitly in the form of an eigenvalue equation. A method of obtaining approximate overlap and energy overlap integrals is proposed. This will help development of numerical calculations of the angular momentum projection method, especially for general intrinsic wave functions without any symmetry restrictions. (author)
A penalty method for PDE-constrained optimization in inverse problems
Leeuwen, T van; Herrmann, F J
2016-01-01
Many inverse and parameter estimation problems can be written as PDE-constrained optimization problems. The goal is to infer the parameters, typically coefficients of the PDE, from partial measurements of the solutions of the PDE for several right-hand sides. Such PDE-constrained problems can be solved by finding a stationary point of the Lagrangian, which entails simultaneously updating the parameters and the (adjoint) state variables. For large-scale problems, such an all-at-once approach is not feasible as it requires storing all the state variables. In this case one usually resorts to a reduced approach where the constraints are explicitly eliminated (at each iteration) by solving the PDEs. These two approaches, and variations thereof, are the main workhorses for solving PDE-constrained optimization problems arising from inverse problems. In this paper, we present an alternative method that aims to combine the advantages of both approaches. Our method is based on a quadratic penalty formulation of the constrained optimization problem. By eliminating the state variable, we develop an efficient algorithm that has roughly the same computational complexity as the conventional reduced approach while exploiting a larger search space. Numerical results show that this method indeed reduces some of the nonlinearity of the problem and is less sensitive to the initial iterate. (paper)
Minggang Dong
2014-01-01
Full Text Available Motivated by recent advancements in differential evolution and constraints handling methods, this paper presents a novel modified oracle penalty function-based composite differential evolution (MOCoDE for constrained optimization problems (COPs. More specifically, the original oracle penalty function approach is modified so as to satisfy the optimization criterion of COPs; then the modified oracle penalty function is incorporated in composite DE. Furthermore, in order to solve more complex COPs with discrete, integer, or binary variables, a discrete variable handling technique is introduced into MOCoDE to solve complex COPs with mix variables. This method is assessed on eleven constrained optimization benchmark functions and seven well-studied engineering problems in real life. Experimental results demonstrate that MOCoDE achieves competitive performance with respect to some other state-of-the-art approaches in constrained optimization evolutionary algorithms. Moreover, the strengths of the proposed method include few parameters and its ease of implementation, rendering it applicable to real life. Therefore, MOCoDE can be an efficient alternative to solving constrained optimization problems.
Null Space Integration Method for Constrained Multibody Systems with No Constraint Violation
Terze, Zdravko; Lefeber, Dirk; Muftic, Osman
2001-01-01
A method for integrating equations of motion of constrained multibody systems with no constraint violation is presented. A mathematical model, shaped as a differential-algebraic system of index 1, is transformed into a system of ordinary differential equations using the null-space projection method. Equations of motion are set in a non-minimal form. During integration, violations of constraints are corrected by solving constraint equations at the position and velocity level, utilizing the metric of the system's configuration space, and projective criterion to the coordinate partitioning method. The method is applied to dynamic simulation of 3D constrained biomechanical system. The simulation results are evaluated by comparing them to the values of characteristic parameters obtained by kinematics analysis of analyzed motion based unmeasured kinematics data
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.
Guo, Sangang
2017-09-01
There are two stages in solving security-constrained unit commitment problems (SCUC) within Lagrangian framework: one is to obtain feasible units’ states (UC), the other is power economic dispatch (ED) for each unit. The accurate solution of ED is more important for enhancing the efficiency of the solution to SCUC for the fixed feasible units’ statues. Two novel methods named after Convex Combinatorial Coefficient Method and Power Increment Method respectively based on linear programming problem for solving ED are proposed by the piecewise linear approximation to the nonlinear convex fuel cost functions. Numerical testing results show that the methods are effective and efficient.
Zheng Ling
2011-01-01
Full Text Available Damping treatments have been extensively used as a powerful means to damp out structural resonant vibrations. Usually, damping materials are fully covered on the surface of plates. The drawbacks of this conventional treatment are also obvious due to an added mass and excess material consumption. Therefore, it is not always economical and effective from an optimization design view. In this paper, a topology optimization approach is presented to maximize the modal damping ratio of the plate with constrained layer damping treatment. The governing equation of motion of the plate is derived on the basis of energy approach. A finite element model to describe dynamic performances of the plate is developed and used along with an optimization algorithm in order to determine the optimal topologies of constrained layer damping layout on the plate. The damping of visco-elastic layer is modeled by the complex modulus formula. Considering the vibration and energy dissipation mode of the plate with constrained layer damping treatment, damping material density and volume factor are considered as design variable and constraint respectively. Meantime, the modal damping ratio of the plate is assigned as the objective function in the topology optimization approach. The sensitivity of modal damping ratio to design variable is further derived and Method of Moving Asymptote (MMA is adopted to search the optimized topologies of constrained layer damping layout on the plate. Numerical examples are used to demonstrate the effectiveness of the proposed topology optimization approach. The results show that vibration energy dissipation of the plates can be enhanced by the optimal constrained layer damping layout. This optimal technology can be further extended to vibration attenuation of sandwich cylindrical shells which constitute the major building block of many critical structures such as cabins of aircrafts, hulls of submarines and bodies of rockets and missiles as an
A first-order multigrid method for bound-constrained convex optimization
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
Bertschinger, E.
1987-01-01
Path integrals may be used to describe the statistical properties of a random field such as the primordial density perturbation field. In this framework the probability distribution is given for a Gaussian random field subjected to constraints such as the presence of a protovoid or supercluster at a specific location in the initial conditions. An algorithm has been constructed for generating samples of a constrained Gaussian random field on a lattice using Monte Carlo techniques. The method makes possible a systematic study of the density field around peaks or other constrained regions in the biased galaxy formation scenario, and it is effective for generating initial conditions for N-body simulations with rare objects in the computational volume. 21 references
A Variant of the Topkis-Veinott Method for Solving Inequality Constrained Optimization Problems
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
Multi-example feature-constrained back-projection method for image super-resolution
Junlei Zhang; Dianguang Gai; Xin Zhang; Xuemei Li
2017-01-01
Example-based super-resolution algorithms,which predict unknown high-resolution image information using a relationship model learnt from known high- and low-resolution image pairs, have attracted considerable interest in the field of image processing. In this paper, we propose a multi-example feature-constrained back-projection method for image super-resolution. Firstly, we take advantage of a feature-constrained polynomial interpolation method to enlarge the low-resolution image. Next, we consider low-frequency images of different resolutions to provide an example pair. Then, we use adaptive k NN search to find similar patches in the low-resolution image for every image patch in the high-resolution low-frequency image, leading to a regression model between similar patches to be learnt. The learnt model is applied to the low-resolution high-frequency image to produce high-resolution high-frequency information. An iterative back-projection algorithm is used as the final step to determine the final high-resolution image.Experimental results demonstrate that our method improves the visual quality of the high-resolution image.
A New Self-Constrained Inversion Method of Potential Fields Based on Probability Tomography
Sun, S.; Chen, C.; WANG, H.; Wang, Q.
2014-12-01
The self-constrained inversion method of potential fields uses a priori information self-extracted from potential field data. Differing from external a priori information, the self-extracted information are generally parameters derived exclusively from the analysis of the gravity and magnetic data (Paoletti et al., 2013). Here we develop a new self-constrained inversion method based on probability tomography. Probability tomography doesn't need any priori information, as well as large inversion matrix operations. Moreover, its result can describe the sources, especially the distribution of which is complex and irregular, entirely and clearly. Therefore, we attempt to use the a priori information extracted from the probability tomography results to constrain the inversion for physical properties. The magnetic anomaly data was taken as an example in this work. The probability tomography result of magnetic total field anomaly(ΔΤ) shows a smoother distribution than the anomalous source and cannot display the source edges exactly. However, the gradients of ΔΤ are with higher resolution than ΔΤ in their own direction, and this characteristic is also presented in their probability tomography results. So we use some rules to combine the probability tomography results of ∂ΔΤ⁄∂x, ∂ΔΤ⁄∂y and ∂ΔΤ⁄∂z into a new result which is used for extracting a priori information, and then incorporate the information into the model objective function as spatial weighting functions to invert the final magnetic susceptibility. Some magnetic synthetic examples incorporated with and without a priori information extracted from the probability tomography results were made to do comparison, results of which show that the former are more concentrated and with higher resolution of the source body edges. This method is finally applied in an iron mine in China with field measured ΔΤ data and performs well. ReferencesPaoletti, V., Ialongo, S., Florio, G., Fedi, M
Lowest-order constrained variational method for simple many-fermion systems
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.)
A Hybrid Method for the Modelling and Optimisation of Constrained Search Problems
Sitek Pawel
2014-08-01
Full Text Available The paper presents a concept and the outline of the implementation of a hybrid approach to modelling and solving constrained problems. Two environments of mathematical programming (in particular, integer programming and declarative programming (in particular, constraint logic programming were integrated. The strengths of integer programming and constraint logic programming, in which constraints are treated in a different way and different methods are implemented, were combined to use the strengths of both. The hybrid method is not worse than either of its components used independently. The proposed approach is particularly important for the decision models with an objective function and many discrete decision variables added up in multiple constraints. To validate the proposed approach, two illustrative examples are presented and solved. The first example is the authors’ original model of cost optimisation in the supply chain with multimodal transportation. The second one is the two-echelon variant of the well-known capacitated vehicle routing problem.
A Decomposition Method for Security Constrained Economic Dispatch of a Three-Layer Power System
Yang, Junfeng; Luo, Zhiqiang; Dong, Cheng; Lai, Xiaowen; Wang, Yang
2018-01-01
This paper proposes a new decomposition method for the security-constrained economic dispatch in a three-layer large-scale power system. The decomposition is realized using two main techniques. The first is to use Ward equivalencing-based network reduction to reduce the number of variables and constraints in the high-layer model without sacrificing accuracy. The second is to develop a price response function to exchange signal information between neighboring layers, which significantly improves the information exchange efficiency of each iteration and results in less iterations and less computational time. The case studies based on the duplicated RTS-79 system demonstrate the effectiveness and robustness of the proposed method.
Input-constrained model predictive control via the alternating direction method of multipliers
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...
Method for exploiting bias in factor analysis using constrained alternating least squares algorithms
Keenan, Michael R.
2008-12-30
Bias plays an important role in factor analysis and is often implicitly made use of, for example, to constrain solutions to factors that conform to physical reality. However, when components are collinear, a large range of solutions may exist that satisfy the basic constraints and fit the data equally well. In such cases, the introduction of mathematical bias through the application of constraints may select solutions that are less than optimal. The biased alternating least squares algorithm of the present invention can offset mathematical bias introduced by constraints in the standard alternating least squares analysis to achieve factor solutions that are most consistent with physical reality. In addition, these methods can be used to explicitly exploit bias to provide alternative views and provide additional insights into spectral data sets.
Blind Channel Equalization with Colored Source Based on Constrained Optimization Methods
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 channelÃ¢Â€Â”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.
Constrained-DFT method for accurate energy-level alignment of metal/molecule interfaces
Souza, A. M.
2013-10-07
We present a computational scheme for extracting the energy-level alignment of a metal/molecule interface, based on constrained density functional theory and local exchange and correlation functionals. The method, applied here to benzene on Li(100), allows us to evaluate charge-transfer energies, as well as the spatial distribution of the image charge induced on the metal surface. We systematically study the energies for charge transfer from the molecule to the substrate as function of the molecule-substrate distance, and investigate the effects arising from image-charge confinement and local charge neutrality violation. For benzene on Li(100) we find that the image-charge plane is located at about 1.8 Å above the Li surface, and that our calculated charge-transfer energies compare perfectly with those obtained with a classical electrostatic model having the image plane located at the same position. The methodology outlined here can be applied to study any metal/organic interface in the weak coupling limit at the computational cost of a total energy calculation. Most importantly, as the scheme is based on total energies and not on correcting the Kohn-Sham quasiparticle spectrum, accurate results can be obtained with local/semilocal exchange and correlation functionals. This enables a systematic approach to convergence.
Constrained non-rigid registration for whole body image registration: method and validation
Li, Xia; Yankeelov, Thomas E.; Peterson, Todd E.; Gore, John C.; Dawant, Benoit M.
2007-03-01
3D intra- and inter-subject registration of image volumes is important for tasks that include measurements and quantification of temporal/longitudinal changes, atlas-based segmentation, deriving population averages, or voxel and tensor-based morphometry. A number of methods have been proposed to tackle this problem but few of them have focused on the problem of registering whole body image volumes acquired either from humans or small animals. These image volumes typically contain a large number of articulated structures, which makes registration more difficult than the registration of head images, to which the vast majority of registration algorithms have been applied. To solve this problem, we have previously proposed an approach, which initializes an intensity-based non-rigid registration algorithm with a point based registration technique [1, 2]. In this paper, we introduce new constraints into our non-rigid registration algorithm to prevent the bones from being deformed inaccurately. Results we have obtained show that the new constrained algorithm leads to better registration results than the previous one.
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.
Constrained-DFT method for accurate energy-level alignment of metal/molecule interfaces
Souza, A. M.; Rungger, I.; Pemmaraju, C. D.; Schwingenschlö gl, Udo; Sanvito, S.
2013-01-01
We present a computational scheme for extracting the energy-level alignment of a metal/molecule interface, based on constrained density functional theory and local exchange and correlation functionals. The method, applied here to benzene on Li(100), allows us to evaluate charge-transfer energies, as well as the spatial distribution of the image charge induced on the metal surface. We systematically study the energies for charge transfer from the molecule to the substrate as function of the molecule-substrate distance, and investigate the effects arising from image-charge confinement and local charge neutrality violation. For benzene on Li(100) we find that the image-charge plane is located at about 1.8 Å above the Li surface, and that our calculated charge-transfer energies compare perfectly with those obtained with a classical electrostatic model having the image plane located at the same position. The methodology outlined here can be applied to study any metal/organic interface in the weak coupling limit at the computational cost of a total energy calculation. Most importantly, as the scheme is based on total energies and not on correcting the Kohn-Sham quasiparticle spectrum, accurate results can be obtained with local/semilocal exchange and correlation functionals. This enables a systematic approach to convergence.
A decomposition method for network-constrained unit commitment with AC power flow constraints
Bai, Yang; Zhong, Haiwang; Xia, Qing; Kang, Chongqing; Xie, Le
2015-01-01
To meet the increasingly high requirement of smart grid operations, considering AC power flow constraints in the NCUC (network-constrained unit commitment) is of great significance in terms of both security and economy. This paper proposes a decomposition method to solve NCUC with AC power flow constraints. With conic approximations of the AC power flow equations, the master problem is formulated as a MISOCP (mixed integer second-order cone programming) model. The key advantage of this model is that the active power and reactive power are co-optimised, and the transmission losses are considered. With the AC optimal power flow model, the AC feasibility of the UC result of the master problem is checked in subproblems. If infeasibility is detected, feedback constraints are generated based on the sensitivity of bus voltages to a change in the unit reactive power generation. They are then introduced into the master problem in the next iteration until all AC violations are eliminated. A 6-bus system, a modified IEEE 30-bus system and the IEEE 118-bus system are used to validate the performance of the proposed method, which provides a satisfactory solution with approximately 44-fold greater computational efficiency. - Highlights: • A decomposition method is proposed to solve the NCUC with AC power flow constraints • The master problem considers active power, reactive power and transmission losses. • OPF-based subproblems check the AC feasibility using parallel computing techniques. • An effective feedback constraint interacts between the master problem and subproblem. • Computational efficiency is significantly improved with satisfactory accuracy
Farzamian, Mohammad; Monteiro Santos, Fernando A.; Khalil, Mohamed A.
2017-12-01
The coupled hydrogeophysical approach has proved to be a valuable tool for improving the use of geoelectrical data for hydrological model parameterization. In the coupled approach, hydrological parameters are directly inferred from geoelectrical measurements in a forward manner to eliminate the uncertainty connected to the independent inversion of electrical resistivity data. Several numerical studies have been conducted to demonstrate the advantages of a coupled approach; however, only a few attempts have been made to apply the coupled approach to actual field data. In this study, we developed a 1D coupled hydrogeophysical code to estimate the van Genuchten-Mualem model parameters, K s, n, θ r and α, from time-lapse vertical electrical sounding data collected during a constant inflow infiltration experiment. van Genuchten-Mualem parameters were sampled using the Latin hypercube sampling method to provide a full coverage of the range of each parameter from their distributions. By applying the coupled approach, vertical electrical sounding data were coupled to hydrological models inferred from van Genuchten-Mualem parameter samples to investigate the feasibility of constraining the hydrological model. The key approaches taken in the study are to (1) integrate electrical resistivity and hydrological data and avoiding data inversion, (2) estimate the total water mass recovery of electrical resistivity data and consider it in van Genuchten-Mualem parameters evaluation and (3) correct the influence of subsurface temperature fluctuations during the infiltration experiment on electrical resistivity data. The results of the study revealed that the coupled hydrogeophysical approach can improve the value of geophysical measurements in hydrological model parameterization. However, the approach cannot overcome the technical limitations of the geoelectrical method associated with resolution and of water mass recovery.
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)
Change Semantic Constrained Online Data Cleaning Method for Real-Time Observational Data Stream
Ding, Yulin; Lin, Hui; Li, Rongrong
2016-06-01
to large estimation error. In order to achieve the best generalization error, it is an important challenge for the data cleaning methodology to be able to characterize the behavior of data stream distributions and adaptively update a model to include new information and remove old information. However, the complicated data changing property invalidates traditional data cleaning methods, which rely on the assumption of a stationary data distribution, and drives the need for more dynamic and adaptive online data cleaning methods. To overcome these shortcomings, this paper presents a change semantics constrained online filtering method for real-time observational data. Based on the principle that the filter parameter should vary in accordance to the data change patterns, this paper embeds semantic description, which quantitatively depicts the change patterns in the data distribution to self-adapt the filter parameter automatically. Real-time observational water level data streams of different precipitation scenarios are selected for testing. Experimental results prove that by means of this method, more accurate and reliable water level information can be available, which is prior to scientific and prompt flood assessment and decision-making.
CHANGE SEMANTIC CONSTRAINED ONLINE DATA CLEANING METHOD FOR REAL-TIME OBSERVATIONAL DATA STREAM
Y. Ding
2016-06-01
data streams, which may led to large estimation error. In order to achieve the best generalization error, it is an important challenge for the data cleaning methodology to be able to characterize the behavior of data stream distributions and adaptively update a model to include new information and remove old information. However, the complicated data changing property invalidates traditional data cleaning methods, which rely on the assumption of a stationary data distribution, and drives the need for more dynamic and adaptive online data cleaning methods. To overcome these shortcomings, this paper presents a change semantics constrained online filtering method for real-time observational data. Based on the principle that the filter parameter should vary in accordance to the data change patterns, this paper embeds semantic description, which quantitatively depicts the change patterns in the data distribution to self-adapt the filter parameter automatically. Real-time observational water level data streams of different precipitation scenarios are selected for testing. Experimental results prove that by means of this method, more accurate and reliable water level information can be available, which is prior to scientific and prompt flood assessment and decision-making.
Configuration mixing calculations with basis states obtained from constrained variational methods
Miller, H.G.; Schroeder, H.P.
1982-01-01
Configuration mixing calculations have been performed in 20 Ne using basis states which are energetically the lowest-lying solutions of the constrained Hartree-Fock equations with an angular momentum constraint of the form 2 > = J(J + 1), For J = 6, very good agreement with the lower-lying 6 + states in an exact eigenvalue spectrum has been obtained with relatively few PAV-K mixed CHF basis states. (orig.)
Axelsson, Owe; Farouq, S.; Neytcheva, M.
2016-01-01
Roč. 73, č. 3 (2016), s. 631-633 ISSN 1017-1398 R&D Projects: GA MŠk ED1.1.00/02.0070 Institutional support: RVO:68145535 Keywords : PDE-constrained optimization problems * finite elements * iterative solution methods Subject RIV: BA - General Mathematics Impact factor: 1.241, year: 2016 http://link.springer.com/article/10.1007%2Fs11075-016-0111-1
Constraining Basin Depth and Fault Displacement in the Malombe Basin Using Potential Field Methods
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
Constraining the cross section of 82Se(n, γ)83Se to validate the β-Oslo method
Childers, K.; Liddick, S. N.; Crider, B. P.; Dombos, A. C.; Lewis, R.; Spyrou, A.; Couture, A.; Mosby, S.; Prokop, C. J.; Naqvi, F.; Larsen, A. C.; Guttormsen, M.; Campo, L. C.; Renstrom, T.; Siem, S.; Bleuel, D. L.; Perdikakis, G.; Quinn, S.
2017-09-01
Neutron capture cross sections of short-lived nuclei are important for a variety of basic and applied nuclear science problems. However, because of the short half-lives of the nuclei involved and the nonexistence of a neutron target, indirect measurement methods are required. One such method is the β-Oslo method. The nuclear level density and γ strength function of a nucleus are extracted after β-decay and used in a statistical reaction model to constrain the neutron capture cross section. This method has been used previously, but must be validated against a directly measured neutron capture cross section. The neutron capture cross section of 82Se has been measured previously, and 83Se can be accessed by the β-decay of 83As. The β-decay of 83As to 83Se was studied using the SuN detector at the NSCL and the β-Oslo method was utilized to constrain the neutron capture cross section of 82Se, which is compared to the directly measured value.
Hadi, Fatemeh; Janbozorgi, Mohammad; Sheikhi, M. Reza H.; Metghalchi, Hameed
2016-10-01
The rate-controlled constrained-equilibrium (RCCE) method is employed to study the interactions between mixing and chemical reaction. Considering that mixing can influence the RCCE state, the key objective is to assess the accuracy and numerical performance of the method in simulations involving both reaction and mixing. The RCCE formulation includes rate equations for constraint potentials, density and temperature, which allows taking account of mixing alongside chemical reaction without splitting. The RCCE is a dimension reduction method for chemical kinetics based on thermodynamics laws. It describes the time evolution of reacting systems using a series of constrained-equilibrium states determined by RCCE constraints. The full chemical composition at each state is obtained by maximizing the entropy subject to the instantaneous values of the constraints. The RCCE is applied to a spatially homogeneous constant pressure partially stirred reactor (PaSR) involving methane combustion in oxygen. Simulations are carried out over a wide range of initial temperatures and equivalence ratios. The chemical kinetics, comprised of 29 species and 133 reaction steps, is represented by 12 RCCE constraints. The RCCE predictions are compared with those obtained by direct integration of the same kinetics, termed detailed kinetics model (DKM). The RCCE shows accurate prediction of combustion in PaSR with different mixing intensities. The method also demonstrates reduced numerical stiffness and overall computational cost compared to DKM.
Peng, Guoyi; Cao, Shuliang; Ishizuka, Masaru; Hayama, Shinji
2002-06-01
This paper is concerned with the design optimization of axial flow hydraulic turbine runner blade geometry. In order to obtain a better design plan with good performance, a new comprehensive performance optimization procedure has been presented by combining a multi-variable multi-objective constrained optimization model with a Q3D inverse computation and a performance prediction procedure. With careful analysis of the inverse design of axial hydraulic turbine runner, the total hydraulic loss and the cavitation coefficient are taken as optimization objectives and a comprehensive objective function is defined using the weight factors. Parameters of a newly proposed blade bound circulation distribution function and parameters describing positions of blade leading and training edges in the meridional flow passage are taken as optimization variables.The optimization procedure has been applied to the design optimization of a Kaplan runner with specific speed of 440 kW. Numerical results show that the performance of designed runner is successfully improved through optimization computation. The optimization model is found to be validated and it has the feature of good convergence. With the multi-objective optimization model, it is possible to control the performance of designed runner by adjusting the value of weight factors defining the comprehensive objective function. Copyright
Constrained structural dynamic model verification using free vehicle suspension testing methods
Blair, Mark A.; Vadlamudi, Nagarjuna
1988-01-01
Verification of the validity of a spacecraft's structural dynamic math model used in computing ascent (or in the case of the STS, ascent and landing) loads is mandatory. This verification process requires that tests be carried out on both the payload and the math model such that the ensuing correlation may validate the flight loads calculations. To properly achieve this goal, the tests should be performed with the payload in the launch constraint (i.e., held fixed at only the payload-booster interface DOFs). The practical achievement of this set of boundary conditions is quite difficult, especially with larger payloads, such as the 12-ton Hubble Space Telescope. The development of equations in the paper will show that by exciting the payload at its booster interface while it is suspended in the 'free-free' state, a set of transfer functions can be produced that will have minima that are directly related to the fundamental modes of the payload when it is constrained in its launch configuration.
Weak gravitational lensing as a method to constrain unstable dark matter
Wang Meiyu; Zentner, Andrew R.
2010-01-01
The nature of the dark matter remains a mystery. The possibility of an unstable dark matter particle decaying to invisible daughter particles has been explored many times in the past few decades. Meanwhile, weak gravitational lensing shear has gained a lot of attention as a probe of dark energy, though it was previously considered a dark matter probe. Weak lensing is a useful tool for constraining the stability of the dark matter. In the coming decade a number of large galaxy imaging surveys will be undertaken and will measure the statistics of cosmological weak lensing with unprecedented precision. Weak lensing statistics are sensitive to unstable dark matter in at least two ways. Dark matter decays alter the matter power spectrum and change the angular diameter distance-redshift relation. We show how measurements of weak lensing shear correlations may provide the most restrictive, model-independent constraints on the lifetime of unstable dark matter. Our results rely on assumptions regarding nonlinear evolution of density fluctuations in scenarios of unstable dark matter and one of our aims is to stimulate interest in theoretical work on nonlinear structure growth in unstable dark matter models.
Constraining East Asian CO2 emissions with GOSAT retrievals: methods and policy implications
Shim, C.; Henze, D. K.; Deng, F.
2017-12-01
The world largest CO2 emissions are from East Asia. However, there are large uncertainties in CO2 emission inventories, mainly because of imperfections in bottom-up statistics and a lack of observations for validating emission fluxes, particularly over China. Here we tried to constrain East Asian CO2 emissions with GOSAT retrievals applying 4-Dvar GEOS-Chem and its adjoint model. We applied the inversion to only the cold season (November - February) in 2009 - 2010 since the summer monsoon and greater transboundary impacts in spring and fall greatly reduced the GOSAT retrievals. In the cold season, the a posteriori CO2 emissions over East Asia generally higher by 5 - 20%, particularly Northeastern China shows intensively higher in a posteriori emissions ( 20%), where the Chinese government is recently focusing on mitigating the air pollutants. In another hand, a posteriori emissions from Southern China are lower 10 - 25%. A posteriori emissions in Korea and Japan are mostly higher by 10 % except over Kyushu region. With our top-down estimates with 4-Dvar CO2 inversion, we will evaluate the current regional CO2 emissions inventories and potential uncertainties in the sectoral emissions. This study will help understand the quantitative information on anthropogenic CO2 emissions over East Asia and will give policy implications for the mitigation targets.
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.
Solution of Constrained Optimal Control Problems Using Multiple Shooting and ESDIRK Methods
Capolei, Andrea; Jørgensen, John Bagterp
2012-01-01
of this paper is the use of ESDIRK integration methods for solution of the initial value problems and the corresponding sensitivity equations arising in the multiple shooting algorithm. Compared to BDF-methods, ESDIRK-methods are advantageous in multiple shooting algorithms in which restarts and frequent...... algorithm. As we consider stiff systems, implicit solvers with sensitivity computation capabilities for initial value problems must be used in the multiple shooting algorithm. Traditionally, multi-step methods based on the BDF algorithm have been used for such problems. The main novel contribution...... discontinuities on each shooting interval are present. The ESDIRK methods are implemented using an inexact Newton method that reuses the factorization of the iteration matrix for the integration as well as the sensitivity computation. Numerical experiments are provided to demonstrate the algorithm....
Chan, C. H.; Brown, G.; Rikvold, P. A.
2017-05-01
A generalized approach to Wang-Landau simulations, macroscopically constrained Wang-Landau, is proposed to simulate the density of states of a system with multiple macroscopic order parameters. The method breaks a multidimensional random-walk process in phase space into many separate, one-dimensional random-walk processes in well-defined subspaces. Each of these random walks is constrained to a different set of values of the macroscopic order parameters. When the multivariable density of states is obtained for one set of values of fieldlike model parameters, the density of states for any other values of these parameters can be obtained by a simple transformation of the total system energy. All thermodynamic quantities of the system can then be rapidly calculated at any point in the phase diagram. We demonstrate how to use the multivariable density of states to draw the phase diagram, as well as order-parameter probability distributions at specific phase points, for a model spin-crossover material: an antiferromagnetic Ising model with ferromagnetic long-range interactions. The fieldlike parameters in this model are an effective magnetic field and the strength of the long-range interaction.
Lukšan, Ladislav; Vlček, Jan
1998-01-01
Roč. 5, č. 3 (1998), s. 219-247 ISSN 1070-5325 R&D Projects: GA ČR GA201/96/0918 Keywords : nonlinear programming * sparse problems * equality constraints * truncated Newton method * augmented Lagrangian function * indefinite systems * indefinite preconditioners * conjugate gradient method * residual smoothing Subject RIV: BA - General Mathematics Impact factor: 0.741, year: 1998
Effective Alternating Direction Optimization Methods for Sparsity-Constrained Blind Image Deblurring
Naixue Xiong
2017-01-01
Full Text Available Single-image blind deblurring for imaging sensors in the Internet of Things (IoT is a challenging ill-conditioned inverse problem, which requires regularization techniques to stabilize the image restoration process. The purpose is to recover the underlying blur kernel and latent sharp image from only one blurred image. Under many degraded imaging conditions, the blur kernel could be considered not only spatially sparse, but also piecewise smooth with the support of a continuous curve. By taking advantage of the hybrid sparse properties of the blur kernel, a hybrid regularization method is proposed in this paper to robustly and accurately estimate the blur kernel. The effectiveness of the proposed blur kernel estimation method is enhanced by incorporating both the L 1 -norm of kernel intensity and the squared L 2 -norm of the intensity derivative. Once the accurate estimation of the blur kernel is obtained, the original blind deblurring can be simplified to the direct deconvolution of blurred images. To guarantee robust non-blind deconvolution, a variational image restoration model is presented based on the L 1 -norm data-fidelity term and the total generalized variation (TGV regularizer of second-order. All non-smooth optimization problems related to blur kernel estimation and non-blind deconvolution are effectively handled by using the alternating direction method of multipliers (ADMM-based numerical methods. Comprehensive experiments on both synthetic and realistic datasets have been implemented to compare the proposed method with several state-of-the-art methods. The experimental comparisons have illustrated the satisfactory imaging performance of the proposed method in terms of quantitative and qualitative evaluations.
Charge-constrained auxiliary-density-matrix methods for the Hartree–Fock exchange contribution
Merlot, Patrick; Izsak, Robert; Borgoo, Alex
2014-01-01
Three new variants of the auxiliary-density-matrix method (ADMM) of Guidon, Hutter, and VandeVondele [J. Chem. Theory Comput. 6, 2348 (2010)] are presented with the common feature thatthey have a simplified constraint compared with the full orthonormality requirement of the earlier ADMM1 method. ....... All ADMM variants are tested for accuracy and performance in all-electron B3LYP calculations with several commonly used basis sets. The effect of the choice of the exchange functional for the ADMM exchange–correction term is also investigated....
Kieseler, Jan
2017-11-01
A method is discussed that allows combining sets of differential or inclusive measurements. It is assumed that at least one measurement was obtained with simultaneously fitting a set of nuisance parameters, representing sources of systematic uncertainties. As a result of beneficial constraints from the data all such fitted parameters are correlated among each other. The best approach for a combination of these measurements would be the maximization of a combined likelihood, for which the full fit model of each measurement and the original data are required. However, only in rare cases this information is publicly available. In absence of this information most commonly used combination methods are not able to account for these correlations between uncertainties, which can lead to severe biases as shown in this article. The method discussed here provides a solution for this problem. It relies on the public result and its covariance or Hessian, only, and is validated against the combined-likelihood approach. A dedicated software package implementing this method is also presented. It provides a text-based user interface alongside a C++ interface. The latter also interfaces to ROOT classes for simple combination of binned measurements such as differential cross sections.
Kieseler, Jan [CERN, Geneva (Switzerland)
2017-11-15
A method is discussed that allows combining sets of differential or inclusive measurements. It is assumed that at least one measurement was obtained with simultaneously fitting a set of nuisance parameters, representing sources of systematic uncertainties. As a result of beneficial constraints from the data all such fitted parameters are correlated among each other. The best approach for a combination of these measurements would be the maximization of a combined likelihood, for which the full fit model of each measurement and the original data are required. However, only in rare cases this information is publicly available. In absence of this information most commonly used combination methods are not able to account for these correlations between uncertainties, which can lead to severe biases as shown in this article. The method discussed here provides a solution for this problem. It relies on the public result and its covariance or Hessian, only, and is validated against the combined-likelihood approach. A dedicated software package implementing this method is also presented. It provides a text-based user interface alongside a C++ interface. The latter also interfaces to ROOT classes for simple combination of binned measurements such as differential cross sections. (orig.)
Sankaran, Sethuraman; Audet, Charles; Marsden, Alison L.
2010-01-01
Recent advances in coupling novel optimization methods to large-scale computing problems have opened the door to tackling a diverse set of physically realistic engineering design problems. A large computational overhead is associated with computing the cost function for most practical problems involving complex physical phenomena. Such problems are also plagued with uncertainties in a diverse set of parameters. We present a novel stochastic derivative-free optimization approach for tackling such problems. Our method extends the previously developed surrogate management framework (SMF) to allow for uncertainties in both simulation parameters and design variables. The stochastic collocation scheme is employed for stochastic variables whereas Kriging based surrogate functions are employed for the cost function. This approach is tested on four numerical optimization problems and is shown to have significant improvement in efficiency over traditional Monte-Carlo schemes. Problems with multiple probabilistic constraints are also discussed.
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
Numerical Methods for Constrained Optimization in 2D and 3D Biomechanics
Nedoma, Jiří; Bartoš, M.; Kestřánek sen., Z.; Kestřánek, Zdeněk; Stehlík, J.
1999-01-01
Roč. 6, č. 7 (1999), s. 557-586 ISSN 1070-5325. [IMBB'98, 27.09.1998-30.09.1998] Grant - others:MŠMT ČR(CZ) OK 158 Institutional research plan: AV0Z1030915 Keywords : variational inequalities * FEM * conjugate gradient method * preconditioning * quadratic programming * biomechanics Subject RIV: BA - General Mathematics Impact factor: 1.083, year: 1999
A multi-fidelity analysis selection method using a constrained discrete optimization formulation
Stults, Ian C.
The purpose of this research is to develop a method for selecting the fidelity of contributing analyses in computer simulations. Model uncertainty is a significant component of result validity, yet it is neglected in most conceptual design studies. When it is considered, it is done so in only a limited fashion, and therefore brings the validity of selections made based on these results into question. Neglecting model uncertainty can potentially cause costly redesigns of concepts later in the design process or can even cause program cancellation. Rather than neglecting it, if one were to instead not only realize the model uncertainty in tools being used but also use this information to select the tools for a contributing analysis, studies could be conducted more efficiently and trust in results could be quantified. Methods for performing this are generally not rigorous or traceable, and in many cases the improvement and additional time spent performing enhanced calculations are washed out by less accurate calculations performed downstream. The intent of this research is to resolve this issue by providing a method which will minimize the amount of time spent conducting computer simulations while meeting accuracy and concept resolution requirements for results. In many conceptual design programs, only limited data is available for quantifying model uncertainty. Because of this data sparsity, traditional probabilistic means for quantifying uncertainty should be reconsidered. This research proposes to instead quantify model uncertainty using an evidence theory formulation (also referred to as Dempster-Shafer theory) in lieu of the traditional probabilistic approach. Specific weaknesses in using evidence theory for quantifying model uncertainty are identified and addressed for the purposes of the Fidelity Selection Problem. A series of experiments was conducted to address these weaknesses using n-dimensional optimization test functions. These experiments found that model
Hummels, Cameron
Computational hydrodynamical simulations are a very useful tool for understanding how galaxies form and evolve over cosmological timescales not easily revealed through observations. However, they are only useful if they reproduce the sorts of galaxies that we see in the real universe. One of the ways in which simulations of this sort tend to fail is in the prescription of stellar feedback, the process by which nascent stars return material and energy to their immediate environments. Careful treatment of this interaction in subgrid models, so-called because they operate on scales below the resolution of the simulation, is crucial for the development of realistic galaxy models. Equally important is developing effective methods for comparing simulation data against observations to ensure galaxy models which mimic reality and inform us about natural phenomena. This thesis examines the formation and evolution of galaxies and the observable characteristics of the resulting systems. We employ extensive use of cosmological hydrodynamical simulations in order to simulate and interpret the evolution of massive spiral galaxies like our own Milky Way. First, we create a method for producing synthetic photometric images of grid-based hydrodynamical models for use in a direct comparison against observations in a variety of filter bands. We apply this method to a simulation of a cluster of galaxies to investigate the nature of the red-sequence/blue-cloud dichotomy in the galaxy color-magnitude diagram. Second, we implement several subgrid models governing the complex behavior of gas and stars on small scales in our galaxy models. Several numerical simulations are conducted with similar initial conditions, where we systematically vary the subgrid models, afterward assessing their efficacy through comparisons of their internal kinematics with observed systems. Third, we generate an additional method to compare observations with simulations, focusing on the tenuous circumgalactic
A New Method to Constrain Supernova Fractions Using X-ray Observations of Clusters of Galaxies
Bulbul, Esra; Smith, Randall K.; Loewenstein, Michael
2012-01-01
Supernova (SN) explosions enrich the intracluster medium (ICM) both by creating and dispersing metals. We introduce a method to measure the number of SNe and relative contribution of Type Ia supernovae (SNe Ia) and core-collapse supernovae (SNe cc) by directly fitting X-ray spectral observations. The method has been implemented as an XSPEC model called snapec. snapec utilizes a single-temperature thermal plasma code (apec) to model the spectral emission based on metal abundances calculated using the latest SN yields from SN Ia and SN cc explosion models. This approach provides a self-consistent single set of uncertainties on the total number of SN explosions and relative fraction of SN types in the ICM over the cluster lifetime by directly allowing these parameters to be determined by SN yields provided by simulations. We apply our approach to XMM-Newton European Photon Imaging Camera (EPIC), Reflection Grating Spectrometer (RGS), and 200 ks simulated Astro-H observations of a cooling flow cluster, A3112.We find that various sets of SN yields present in the literature produce an acceptable fit to the EPIC and RGS spectra of A3112. We infer that 30.3% plus or minus 5.4% to 37.1% plus or minus 7.1% of the total SN explosions are SNe Ia, and the total number of SN explosions required to create the observed metals is in the range of (1.06 plus or minus 0.34) x 10(exp 9), to (1.28 plus or minus 0.43) x 10(exp 9), fromsnapec fits to RGS spectra. These values may be compared to the enrichment expected based on well-established empirically measured SN rates per star formed. The proportions of SNe Ia and SNe cc inferred to have enriched the ICM in the inner 52 kiloparsecs of A3112 is consistent with these specific rates, if one applies a correction for the metals locked up in stars. At the same time, the inferred level of SN enrichment corresponds to a star-to-gas mass ratio that is several times greater than the 10% estimated globally for clusters in the A3112 mass range.
Recover Act. Verification of Geothermal Tracer Methods in Highly Constrained Field Experiments
Becker, Matthew W. [California State University, Long Beach, CA (United States)
2014-05-16
The prediction of the geothermal system efficiency is strong linked to the character of the flow system that connects injector and producer wells. If water flow develops channels or “short circuiting” between injection and extraction wells thermal sweep is poor and much of the reservoir is left untapped. The purpose of this project was to understand how channelized flow develops in fracture geothermal reservoirs and how it can be measured in the field. We explored two methods of assessing channelization: hydraulic connectivity tests and tracer tests. These methods were tested at a field site using two verification methods: ground penetrating radar (GPR) images of saline tracer and heat transfer measurements using distributed temperature sensing (DTS). The field site for these studies was the Altona Flat Fractured Rock Research Site located in northeastern New York State. Altona Flat Rock is an experimental site considered a geologic analog for some geothermal reservoirs given its low matrix porosity. Because soil overburden is thin, it provided unique access to saturated bedrock fractures and the ability image using GPR which does not effectively penetrate most soils. Five boreholes were drilled in a “five spot” pattern covering 100 m2 and hydraulically isolated in a single bedding plane fracture. This simple system allowed a complete characterization of the fracture. Nine small diameter boreholes were drilled from the surface to just above the fracture to allow the measurement of heat transfer between the fracture and the rock matrix. The focus of the hydraulic investigation was periodic hydraulic testing. In such tests, rather than pumping or injection in a well at a constant rate, flow is varied to produce an oscillating pressure signal. This pressure signal is sensed in other wells and the attenuation and phase lag between the source and receptor is an indication of hydraulic connection. We found that these tests were much more effective than constant
Leyendecker, Sigrid; Betsch, Peter; Steinmann, Paul
2008-01-01
In the present work, the unified framework for the computational treatment of rigid bodies and nonlinear beams developed by Betsch and Steinmann (Multibody Syst. Dyn. 8, 367-391, 2002) is extended to the realm of nonlinear shells. In particular, a specific constrained formulation of shells is proposed which leads to the semi-discrete equations of motion characterized by a set of differential-algebraic equations (DAEs). The DAEs provide a uniform description for rigid bodies, semi-discrete beams and shells and, consequently, flexible multibody systems. The constraints may be divided into two classes: (i) internal constraints which are intimately connected with the assumption of rigidity of the bodies, and (ii) external constraints related to the presence of joints in a multibody framework. The present approach thus circumvents the use of rotational variables throughout the whole time discretization, facilitating the design of energy-momentum methods for flexible multibody dynamics. After the discretization has been completed a size-reduction of the discrete system is performed by eliminating the constraint forces. Numerical examples dealing with a spatial slider-crank mechanism and with intersecting shells illustrate the performance of the proposed method
Yakai Xu
2017-01-01
Full Text Available Dynamic stiffness and damping of the headstock, which is a critical component of precision horizontal machining center, are two main factors that influence machining accuracy and surface finish quality. Constrained Layer Damping (CLD structure is proved to be effective in raising damping capacity for the thin plate and shell structures. In this paper, one kind of high damping material is utilized on the headstock to improve damping capacity. The dynamic characteristic of the hybrid headstock is investigated analytically and experimentally. The results demonstrate that the resonant response amplitudes of the headstock with damping material can decrease significantly compared to original cast structure. To obtain the optimal configuration of damping material, a topology optimization method based on the Evolutionary Structural Optimization (ESO is implemented. Modal Strain Energy (MSE method is employed to analyze the damping and to derive the sensitivity of the modal loss factor. The optimization results indicate that the added weight of damping material decreases by 50%; meanwhile the first two orders of modal loss factor decrease by less than 23.5% compared to the original structure.
Pettersen, G.; Oestgaard, E.
1988-01-01
The ground-state energy of solid hydrogen and deuterium is calculated by means of a modified variational lowest order constrained-variation (LOCV) method. Both fcc and hcp H 2 and D 2 are considered, and the calculations are done for five different two-body potentials. For solid H 2 we obtain theoretical results for the ground-state binding energy per particle from -74.9 K at an equilibrium particle density of 0.700 σ -3 or a molar volume of 22.3 cm 3 /mole to -91.3 K at a particle density of 0.725 σ -3 or a molar volume of 21.5 cm 3 /mole, where σ = 2.958 A. The corresponding experimental result is -92.3 K at a particle density of 0.688 σ -3 or a molar volume of 22.7 cm 3 /mole. For solid D 2 we obtain theoretical results for the ground-state binding energy per particle from -125.7 K at an equilibrium particle density of 0.830 σ -3 or a molar volume of 18.8 cm 3 /mole to -140.1 K at a particle density of 0.843 σ -3 or a molar volume of 18.5 cm 3 /mole. The corresponding experimental result is -137.9 K at a particle density of 0.797 σ -3 or a molar volume of 19.6 cm 3 /mole
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...
Pettersen, G.; Ostgaard, E.
1988-01-01
The pressure and the compressibility of solid H 2 and D 2 are obtained from ground-state energies calculated by means of a modified variational lowest order constrained-variation (LOCV) method. Both fcc and hcp structures are considered, but results are given for the fcc structure only. The pressure and the compressibility are calculated or estimated from the dependence of the ground-state energy on density or molar volume, generally in a density region of 0.65σ -3 to 1.3σ -3 , corresponding to a molar volume of 0.65σ -3 to 1.3σ -3 , corresponding to a molar volume of 12-24 cm 3 mole, where σ = 2.958 angstrom, and the calculations are done for five different two-body potentials. Theoretical results for the pressure are 340-460 atm for solid H 2 at a particle density of 0.82σ -3 or a molar volume of 19 cm 3 /mole, and 370-490 atm for solid 4 He at a particle density of 0.92σ -3 or a molar volume of 17 cm 3 /mole. The corresponding experimental results are 650 and 700 atm, respectively. Theoretical results for the compressibility are 210 times 10 -6 to 260 times 10 -6 atm -1 for solid H 2 at a particle density of 0.82σ -3 or a molar volume of 19 cm 3 /mole, and 150 times 10 -6 to 180 times 10 -6 atm -1 for solid D 2 at a particle density of 0.92σ -3 or a molar volume of 17 cm 3 mole. The corresponding experimental results are 180 times 10 -6 and 140 times 10 -6 atm -1 , respectively. The agreement with experimental results is better for higher densities
Crown, William; Buyukkaramikli, Nasuh; Thokala, Praveen; Morton, Alec; Sir, Mustafa Y; Marshall, Deborah A; Tosh, Jon; Padula, William V; Ijzerman, Maarten J; Wong, Peter K; Pasupathy, Kalyan S
2017-03-01
Providing health services with the greatest possible value to patients and society given the constraints imposed by patient characteristics, health care system characteristics, budgets, and so forth relies heavily on the design of structures and processes. Such problems are complex and require a rigorous and systematic approach to identify the best solution. Constrained optimization is a set of methods designed to identify efficiently and systematically the best solution (the optimal solution) to a problem characterized by a number of potential solutions in the presence of identified constraints. This report identifies 1) key concepts and the main steps in building an optimization model; 2) the types of problems for which optimal solutions can be determined in real-world health applications; and 3) the appropriate optimization methods for these problems. We first present a simple graphical model based on the treatment of "regular" and "severe" patients, which maximizes the overall health benefit subject to time and budget constraints. We then relate it back to how optimization is relevant in health services research for addressing present day challenges. We also explain how these mathematical optimization methods relate to simulation methods, to standard health economic analysis techniques, and to the emergent fields of analytics and machine learning. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Alabau-Boussouira, Fatiha
2005-01-01
This work is concerned with the stabilization of hyperbolic systems by a nonlinear feedback which can be localized on a part of the boundary or locally distributed. We show that general weighted integral inequalities together with convexity arguments allow us to produce a general semi-explicit formula which leads to decay rates of the energy in terms of the behavior of the nonlinear feedback close to the origin. This formula allows us to unify for instance the cases where the feedback has a polynomial growth at the origin, with the cases where it goes exponentially fast to zero at the origin. We also give three other significant examples of nonpolynomial growth at the origin. We also prove the optimality of our results for the one-dimensional wave equation with nonlinear boundary dissipation. The key property for obtaining our general energy decay formula is the understanding between convexity properties of an explicit function connected to the feedback and the dissipation of energy
Saini, Surendra Singh; Sarkar, Ushnish; Swaroop, Tumapala Teja; Panjikkal, Sreejith; Ray, Debasish Datta
2016-01-01
In master slave manipulator, slave arm is controlled by an operator to manipulate the objects in remote environment using an iso-kinematic master arm which is located in the control room. In such a scenario, where the actual work environment is separated from the operator, formulation of techniques for assisting the operator to execute constrained motion (preferential inclusion or preferential exclusion of workspace zones) in the slave environment are not only helpful, but also essential. We had earlier demonstrated the efficacy of constraint motion with predefined geometrical constraints of various types. However, in a hot-cell scenario the generation of the constraint equations is difficult since we shall not have access to the cell for taking measurements. In this paper, a user friendly method is proposed for image based acquisition of the various constraint geometries thus eliminating the need to take in-cell measurements. For this purpose various hot cell tasks and required geometrical primitives pertaining to these tasks have been surveyed and an algorithm has been developed for generating the constraint geometry for each primitive. This methodology shall increase the efficiency and ease of use of the hot cell Telemanipulator by providing real time constraint acquisition and subsequent assistive force based constrained motion. (author)
Kieseler, Jan
2017-11-22
A method is discussed that allows combining sets of differential or inclusive measurements. It is assumed that at least one measurement was obtained with simultaneously fitting a set of nuisance parameters, representing sources of systematic uncertainties. As a result of beneficial constraints from the data all such fitted parameters are correlated among each other. The best approach for a combination of these measurements would be the maximization of a combined likelihood, for which the full fit model of each measurement and the original data are required. However, only in rare cases this information is publicly available. In absence of this information most commonly used combination methods are not able to account for these correlations between uncertainties, which can lead to severe biases as shown in this article. The method discussed here provides a solution for this problem. It relies on the public result and its covariance or Hessian, only, and is validated against the combined-likelihood approach. A d...
Akaa Agbaeze Eteng
Full Text Available Q-factor constraints are usually imposed on conductor loops employed as proximity range High Frequency Radio Frequency Identification (HF-RFID reader antennas to ensure adequate data bandwidth. However, pairing such low Q-factor loops in inductive energy transmission links restricts the link transmission performance. The contribution of this paper is to assess the improvement that is reached with a two-stage design method, concerning the transmission performance of a planar square loop relative to an initial design, without compromise to a Q-factor constraint. The first stage of the synthesis flow is analytical in approach, and determines the number and spacing of turns by which coupling between similar paired square loops can be enhanced with low deviation from the Q-factor limit presented by an initial design. The second stage applies full-wave electromagnetic simulations to determine more appropriate turn spacing and widths to match the Q-factor constraint, and achieve improved coupling relative to the initial design. Evaluating the design method in a test scenario yielded a more than 5% increase in link transmission efficiency, as well as an improvement in the link fractional bandwidth by more than 3%, without violating the loop Q-factor limit. These transmission performance enhancements are indicative of a potential for modifying proximity HF-RFID reader antennas for efficient inductive energy transfer and data telemetry links.
Jyuo-Min Shyu
2010-11-01
Full Text Available A great deal of work has been done to develop techniques for odor analysis by electronic nose systems. These analyses mostly focus on identifying a particular odor by comparing with a known odor dataset. However, in many situations, it would be more practical if each individual odorant could be determined directly. This paper proposes two methods for such odor components analysis for electronic nose systems. First, a K-nearest neighbor (KNN-based local weighted nearest neighbor (LWNN algorithm is proposed to determine the components of an odor. According to the component analysis, the odor training data is firstly categorized into several groups, each of which is represented by its centroid. The examined odor is then classified as the class of the nearest centroid. The distance between the examined odor and the centroid is calculated based on a weighting scheme, which captures the local structure of each predefined group. To further determine the concentration of each component, odor models are built by regressions. Then, a weighted and constrained least-squares (WCLS method is proposed to estimate the component concentrations. Experiments were carried out to assess the effectiveness of the proposed methods. The LWNN algorithm is able to classify mixed odors with different mixing ratios, while the WCLS method can provide good estimates on component concentrations.
Slow-wave sleep estimation on a load-cell-installed bed: a non-constrained method
Choi, Byung Hun; Chung, Gih Sung; Lee, Jin-Seong; Jeong, Do-Un; Park, Kwang Suk
2009-01-01
Polysomnography (PSG) involves simultaneous and continuous monitoring of relevant normal and abnormal physiological activity during sleep. At present, an electroencephalography-based rule is generally used for classifying sleep stages. However, scoring the PSG record is quite laborious and time consuming. In this paper, movement and cardiac activity were measured unobtrusively by a load-cell-installed bed, and sleep was classified into two stages: slow-wave sleep and non-slow-wave sleep. From the measured cardiac activity, we extracted heartbeat data and calculated heart rate variability parameters: standard deviation of R–R intervals SDNN, low frequency-to-high frequency ratio, alpha of detrended fluctuation analysis and correlation coefficient of R–R interval. The developed system showed a substantial concordance with PSG results when compared using a contingency test. The mean epoch-by-epoch agreement between the proposed method and PSG was 92.5% and Cohen's kappa was 0.62
Mirzaei, Mahmood; Tibaldi, Carlo; Hansen, Morten Hartvig
2016-01-01
to automatically tune the wind turbine controller subject to robustness constraints. The properties of the system such as the maximum sensitivity and complementary sensitivity functions (Ms and Mt), along with some of the responses of the system, are used to investigate the controller performance and formulate...... the optimization problem. The cost function is the integral absolute error (IAE) of the rotational speed from a disturbance modeled as a step in wind speed. Linearized model of the DTU 10-MW reference wind turbine is obtained using HAWCStab2. Thereafter, the model is reduced with model order reduction. The trade......PI/PID controllers are the most common wind turbine controllers. Normally a first tuning is obtained using methods such as pole-placement or Ziegler-Nichols and then extensive aeroelastic simulations are used to obtain the best tuning in terms of regulation of the outputs and reduction of the loads...
Ouyang, Qi; Lu, Wenxi; Hou, Zeyu; Zhang, Yu; Li, Shuai; Luo, Jiannan
2017-05-01
In this paper, a multi-algorithm genetically adaptive multi-objective (AMALGAM) method is proposed as a multi-objective optimization solver. It was implemented in the multi-objective optimization of a groundwater remediation design at sites contaminated by dense non-aqueous phase liquids. In this study, there were two objectives: minimization of the total remediation cost, and minimization of the remediation time. A non-dominated sorting genetic algorithm II (NSGA-II) was adopted to compare with the proposed method. For efficiency, the time-consuming surfactant-enhanced aquifer remediation simulation model was replaced by a surrogate model constructed by a multi-gene genetic programming (MGGP) technique. Similarly, two other surrogate modeling methods-support vector regression (SVR) and Kriging (KRG)-were employed to make comparisons with MGGP. In addition, the surrogate-modeling uncertainty was incorporated in the optimization model by chance-constrained programming (CCP). The results showed that, for the problem considered in this study, (1) the solutions obtained by AMALGAM incurred less remediation cost and required less time than those of NSGA-II, indicating that AMALGAM outperformed NSGA-II. It was additionally shown that (2) the MGGP surrogate model was more accurate than SVR and KRG; and (3) the remediation cost and time increased with the confidence level, which can enable decision makers to make a suitable choice by considering the given budget, remediation time, and reliability. Copyright © 2017 Elsevier B.V. All rights reserved.
Saide, Pablo (CGRER, Center for Global and Regional Environmental Research, Univ. of Iowa, Iowa City, IA (United States)), e-mail: pablo-saide@uiowa.edu; Bocquet, Marc (Universite Paris-Est, CEREA Joint Laboratory Ecole des Ponts ParisTech and EDF RandD, Champs-sur-Marne (France); INRIA, Paris Rocquencourt Research Center (France)); Osses, Axel (Departamento de Ingeniera Matematica, Universidad de Chile, Santiago (Chile); Centro de Modelamiento Matematico, UMI 2807/Universidad de Chile-CNRS, Santiago (Chile)); Gallardo, Laura (Centro de Modelamiento Matematico, UMI 2807/Universidad de Chile-CNRS, Santiago (Chile); Departamento de Geofisica, Universidad de Chile, Santiago (Chile))
2011-07-15
When constraining surface emissions of air pollutants using inverse modelling one often encounters spurious corrections to the inventory at places where emissions and observations are colocated, referred to here as the colocalization problem. Several approaches have been used to deal with this problem: coarsening the spatial resolution of emissions; adding spatial correlations to the covariance matrices; adding constraints on the spatial derivatives into the functional being minimized; and multiplying the emission error covariance matrix by weighting factors. Intercomparison of methods for a carbon monoxide inversion over a city shows that even though all methods diminish the colocalization problem and produce similar general patterns, detailed information can greatly change according to the method used ranging from smooth, isotropic and short range modifications to not so smooth, non-isotropic and long range modifications. Poisson (non-Gaussian) and Gaussian assumptions both show these patterns, but for the Poisson case the emissions are naturally restricted to be positive and changes are given by means of multiplicative correction factors, producing results closer to the true nature of emission errors. Finally, we propose and test a new two-step, two-scale, fully Bayesian approach that deals with the colocalization problem and can be implemented for any prior density distribution
Ouyang, Qi; Lu, Wenxi; Hou, Zeyu; Zhang, Yu; Li, Shuai; Luo, Jiannan
2017-05-01
In this paper, a multi-algorithm genetically adaptive multi-objective (AMALGAM) method is proposed as a multi-objective optimization solver. It was implemented in the multi-objective optimization of a groundwater remediation design at sites contaminated by dense non-aqueous phase liquids. In this study, there were two objectives: minimization of the total remediation cost, and minimization of the remediation time. A non-dominated sorting genetic algorithm II (NSGA-II) was adopted to compare with the proposed method. For efficiency, the time-consuming surfactant-enhanced aquifer remediation simulation model was replaced by a surrogate model constructed by a multi-gene genetic programming (MGGP) technique. Similarly, two other surrogate modeling methods-support vector regression (SVR) and Kriging (KRG)-were employed to make comparisons with MGGP. In addition, the surrogate-modeling uncertainty was incorporated in the optimization model by chance-constrained programming (CCP). The results showed that, for the problem considered in this study, (1) the solutions obtained by AMALGAM incurred less remediation cost and required less time than those of NSGA-II, indicating that AMALGAM outperformed NSGA-II. It was additionally shown that (2) the MGGP surrogate model was more accurate than SVR and KRG; and (3) the remediation cost and time increased with the confidence level, which can enable decision makers to make a suitable choice by considering the given budget, remediation time, and reliability.
Almeida Bezerra, Marcos, E-mail: mbezerra47@yahoo.com.br [Universidade Estadual do Sudoeste da Bahia, Laboratorio de Quimica Analitica, 45200-190, Jequie, Bahia (Brazil); Teixeira Castro, Jacira [Universidade Federal do Reconcavo da Bahia, Centro de Ciencias Exatas e Tecnologicas, 44380-000, Cruz das Almas, Bahia (Brazil); Coelho Macedo, Reinaldo; Goncalves da Silva, Douglas [Universidade Estadual do Sudoeste da Bahia, Laboratorio de Quimica Analitica, 45200-190, Jequie, Bahia (Brazil)
2010-06-18
A slurry suspension sampling technique has been developed for manganese and zinc determination in tea leaves by using flame atomic absorption spectrometry. The proportions of liquid-phase of the slurries composed by HCl, HNO{sub 3} and Triton X-100 solutions have been optimized applying a constrained mixture design. The optimized conditions were 200 mg of sample ground in a tungsten carbide balls mill (particle size < 100 {mu}m), dilution in a liquid-phase composed by 2.0 mol L{sup -1} nitric, 2.0 mol L{sup -1} hydrochloric acid and 2.5% Triton X-100 solutions (in the proportions of 50%, 12% and 38% respectively), sonication time of 10 min and final slurry volume of 50.0 mL. This method allowed the determination of manganese and zinc by FAAS, with detection limits of 0.46 and 0.66 {mu}g g{sup -1}, respectively. The precisions, expressed as relative standard deviation (RSD), are 6.9 and 5.5% (n = 10), for concentrations of manganese and zinc of 20 and 40 {mu}g g{sup -1}, respectively. The accuracy of the method was confirmed by analysis of the certified apple leaves (NIST 1515) and spinach leaves (NIST 1570a). The proposed method was applied for the determination of manganese and zinc in tea leaves used for the preparation of infusions. The obtained concentrations varied between 42 and 118 {mu}g g{sup -1} and 18.6 and 90 {mu}g g{sup -1}, respectively, for manganese and zinc. The results were compared with those obtained by an acid digestion procedure and determination of the elements by FAAS. There was no significant difference between the results obtained by the two methods based on a paired t-test (at 95% confidence level).
Constrained bidirectional propagation and stroke segmentation
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.
Evolutionary constrained optimization
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...
Verde, Licia; Jimenez, Raul [Institute of Cosmos Sciences, University of Barcelona, IEEC-UB, Martí Franquès, 1, E08028 Barcelona (Spain); Bellini, Emilio [University of Oxford, Denys Wilkinson Building, Keble Road, Oxford, OX1 3RH (United Kingdom); Pigozzo, Cassio [Instituto de Física, Universidade Federal da Bahia, Salvador, BA (Brazil); Heavens, Alan F., E-mail: liciaverde@icc.ub.edu, E-mail: emilio.bellini@physics.ox.ac.uk, E-mail: cpigozzo@ufba.br, E-mail: a.heavens@imperial.ac.uk, E-mail: raul.jimenez@icc.ub.edu [Imperial Centre for Inference and Cosmology (ICIC), Imperial College, Blackett Laboratory, Prince Consort Road, London SW7 2AZ (United Kingdom)
2017-04-01
We investigate our knowledge of early universe cosmology by exploring how much additional energy density can be placed in different components beyond those in the ΛCDM model. To do this we use a method to separate early- and late-universe information enclosed in observational data, thus markedly reducing the model-dependency of the conclusions. We find that the 95% credibility regions for extra energy components of the early universe at recombination are: non-accelerating additional fluid density parameter Ω{sub MR} < 0.006 and extra radiation parameterised as extra effective neutrino species 2.3 < N {sub eff} < 3.2 when imposing flatness. Our constraints thus show that even when analyzing the data in this largely model-independent way, the possibility of hiding extra energy components beyond ΛCDM in the early universe is seriously constrained by current observations. We also find that the standard ruler, the sound horizon at radiation drag, can be well determined in a way that does not depend on late-time Universe assumptions, but depends strongly on early-time physics and in particular on additional components that behave like radiation. We find that the standard ruler length determined in this way is r {sub s} = 147.4 ± 0.7 Mpc if the radiation and neutrino components are standard, but the uncertainty increases by an order of magnitude when non-standard dark radiation components are allowed, to r {sub s} = 150 ± 5 Mpc.
Zhou Jinghao; Kim, Sung; Jabbour, Salma; Goyal, Sharad; Haffty, Bruce; Chen, Ting; Levinson, Lydia; Metaxas, Dimitris; Yue, Ning J.
2010-01-01
Purpose: In the external beam radiation treatment of prostate cancers, successful implementation of adaptive radiotherapy and conformal radiation dose delivery is highly dependent on precise and expeditious segmentation and registration of the prostate volume between the simulation and the treatment images. The purpose of this study is to develop a novel, fast, and accurate segmentation and registration method to increase the computational efficiency to meet the restricted clinical treatment time requirement in image guided radiotherapy. Methods: The method developed in this study used soft tissues to capture the transformation between the 3D planning CT (pCT) images and 3D cone-beam CT (CBCT) treatment images. The method incorporated a global-to-local deformable mesh model based registration framework as well as an automatic anatomy-constrained robust active shape model (ACRASM) based segmentation algorithm in the 3D CBCT images. The global registration was based on the mutual information method, and the local registration was to minimize the Euclidian distance of the corresponding nodal points from the global transformation of deformable mesh models, which implicitly used the information of the segmented target volume. The method was applied on six data sets of prostate cancer patients. Target volumes delineated by the same radiation oncologist on the pCT and CBCT were chosen as the benchmarks and were compared to the segmented and registered results. The distance-based and the volume-based estimators were used to quantitatively evaluate the results of segmentation and registration. Results: The ACRASM segmentation algorithm was compared to the original active shape model (ASM) algorithm by evaluating the values of the distance-based estimators. With respect to the corresponding benchmarks, the mean distance ranged from -0.85 to 0.84 mm for ACRASM and from -1.44 to 1.17 mm for ASM. The mean absolute distance ranged from 1.77 to 3.07 mm for ACRASM and from 2.45 to
Lambert, M.; Lesselier, D.; Kooij, B. J.
1998-10-01
The retrieval of an unknown, possibly inhomogeneous, penetrable cylindrical obstacle buried entirely in a known homogeneous half-space - the constitutive material parameters of the obstacle and of its embedding obey a Maxwell model - is considered from single- or multiple-frequency aspect-limited data collected by ideal sensors located in air above the embedding half-space, when a small number of time-harmonic transverse electric (TE)-polarized line sources - the magnetic field H is directed along the axis of the cylinder - is also placed in air. The wavefield is modelled from a rigorous H-field domain integral-differential formulation which involves the dot product of the gradients of the single component of H and of the Green function of the stratified environment times a scalar-valued contrast function which contains the obstacle parameters (the frequency-independent, position-dependent relative permittivity and conductivity). A modified gradient method is developed in order to reconstruct the maps of such parameters within a prescribed search domain from the iterative minimization of a cost functional which incorporates both the error in reproducing the data and the error on the field built inside this domain. Non-physical values are excluded and convergence reached by incorporating in the solution algorithm, from a proper choice of unknowns, the condition that the relative permittivity be larger than or equal to 1, and the conductivity be non-negative. The efficiency of the constrained method is illustrated from noiseless and noisy synthetic data acquired independently. The importance of the choice of the initial values of the sought quantities, the need for a periodic refreshment of the constitutive parameters to avoid the algorithm providing inconsistent results, and the interest of a frequency-hopping strategy to obtain finer and finer features of the obstacle when the frequency is raised, are underlined. It is also shown that though either the permittivity
Exploring Constrained Creative Communication
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...
Choosing health, constrained choices.
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.
Cascading Constrained 2-D Arrays using Periodic Merging Arrays
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...
Operator approach to solutions of the constrained BKP hierarchy
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.
Modeling the microstructural evolution during constrained sintering
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...
Constrained superfields in supergravity
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.
Minimal constrained supergravity
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
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.
Minimal constrained supergravity
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.
On the origin of constrained superfields
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.
Meschis, Marco; Roberts, Gerald P.; Robertson, Jennifer
2016-04-01
Long-term curstal extension rates, accommodated by active normal faults, can be constrained by investigating Late Quaternary vertical movements. Sequences of marine terraces tectonically deformed by active faults mark the interaction between tectonic activity, sea-level changes and active faulting throughout the Quaternary (e.g. Armijo et al., 1996, Giunta et al, 2011, Roberts et al., 2013). Crustal deformation can be calculated over multiple seismic cycles by mapping Quaternary tectonically-deformed palaeoshorelines, both in the hangingwall and footwall of active normal faults (Roberts et al., 2013). Here we use a synchronous correlation method between palaeoshorelines elevations and the ages of sea-level highstands (see Roberts et al., 2013 for further details) which takes advantage of the facts that (i) sea-level highstands are not evenly-spaced in time, yet must correlate with palaeoshorelines that are commonly not evenly-spaced in elevation, and (ii) that older terraces may be destroyed and/or overprinted by younger highstands, so that the next higher or lower paleoshoreline does not necessarily correlate with the next older or younger sea-level highstand. We investigated a flight of Late Quaternary marine terraces deformed by normal faulting as a result of the Capo D'Orlando Fault in NE Sicily (e.g. Giunta et al., 2011). This fault lies within the Calabrian Arc which has experienced damaging seismic events such as the 1908 Messina Straits earthquake ~ Mw 7. Our mapping and previous mapping (Giunta et al. (2011) demonstrate that the elevations of marine terraces inner edges change along the strike the NE - SW oriented normal fault. This confirms active deformation on the Capo D'Orlando Fault, strongly suggesting that it should be added into the Database of Individual Seismogenic Sources (DISS, Basili et al., 2008). Giunta et al. (2011) suggested that uplift rates and hence faults lip-rates vary through time for this examples. We update the ages assigned to
Coherent states in constrained systems
Nakamura, M.; Kojima, K.
2001-01-01
When quantizing the constrained systems, there often arise the quantum corrections due to the non-commutativity in the re-ordering of constraint operators in the products of operators. In the bosonic second-class constraints, furthermore, the quantum corrections caused by the uncertainty principle should be taken into account. In order to treat these corrections simultaneously, the alternative projection technique of operators is proposed by introducing the available minimal uncertainty states of the constraint operators. Using this projection technique together with the projection operator method (POM), these two kinds of quantum corrections were investigated
Constrained Vapor Bubble Experiment
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.
Constrained noninformative priors
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
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...
Sharp spatially constrained inversion
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....
Reflected stochastic differential equation models for constrained animal movement
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.
Tang, Shuaiqi
Atmospheric vertical velocities and advective tendencies are essential as large-scale forcing data to drive single-column models (SCM), cloud-resolving models (CRM) and large-eddy simulations (LES). They cannot be directly measured or easily calculated with great accuracy from field measurements. In the Atmospheric Radiation Measurement (ARM) program, a constrained variational algorithm (1DCVA) has been used to derive large-scale forcing data over a sounding network domain with the aid of flux measurements at the surface and top of the atmosphere (TOA). We extend the 1DCVA algorithm into three dimensions (3DCVA) along with other improvements to calculate gridded large-scale forcing data. We also introduce an ensemble framework using different background data, error covariance matrices and constraint variables to quantify the uncertainties of the large-scale forcing data. The results of sensitivity study show that the derived forcing data and SCM simulated clouds are more sensitive to the background data than to the error covariance matrices and constraint variables, while horizontal moisture advection has relatively large sensitivities to the precipitation, the dominate constraint variable. Using a mid-latitude cyclone case study in March 3rd, 2000 at the ARM Southern Great Plains (SGP) site, we investigate the spatial distribution of diabatic heating sources (Q1) and moisture sinks (Q2), and show that they are consistent with the satellite clouds and intuitive structure of the mid-latitude cyclone. We also evaluate the Q1 and Q2 in analysis/reanalysis, finding that the regional analysis/reanalysis all tend to underestimate the sub-grid scale upward transport of moist static energy in the lower troposphere. With the uncertainties from large-scale forcing data and observation specified, we compare SCM results and observations and find that models have large biases on cloud properties which could not be fully explained by the uncertainty from the large-scale forcing
Constrained optimization via simulation models for new product innovation
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.
Constraining neutrinoless double beta decay
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.
Hyperbolicity and constrained evolution in linearized gravity
Matzner, Richard A.
2005-01-01
Solving the 4-d Einstein equations as evolution in time requires solving equations of two types: the four elliptic initial data (constraint) equations, followed by the six second order evolution equations. Analytically the constraint equations remain solved under the action of the evolution, and one approach is to simply monitor them (unconstrained evolution). Since computational solution of differential equations introduces almost inevitable errors, it is clearly 'more correct' to introduce a scheme which actively maintains the constraints by solution (constrained evolution). This has shown promise in computational settings, but the analysis of the resulting mixed elliptic hyperbolic method has not been completely carried out. We present such an analysis for one method of constrained evolution, applied to a simple vacuum system, linearized gravitational waves. We begin with a study of the hyperbolicity of the unconstrained Einstein equations. (Because the study of hyperbolicity deals only with the highest derivative order in the equations, linearization loses no essential details.) We then give explicit analytical construction of the effect of initial data setting and constrained evolution for linearized gravitational waves. While this is clearly a toy model with regard to constrained evolution, certain interesting features are found which have relevance to the full nonlinear Einstein equations
Branda, Martin; Bucher, M.; Červinka, Michal; Schwartz, A.
2018-01-01
Roč. 70, č. 2 (2018), s. 503-530 ISSN 0926-6003 R&D Projects: GA ČR GA15-00735S Institutional support: RVO:67985556 Keywords : Cardinality constraints * Regularization method * Scholtes regularization * Strong stationarity * Sparse portfolio optimization * Robust portfolio optimization Subject RIV: BB - Applied Statistics, Operational Research OBOR OECD: Statistics and probability Impact factor: 1.520, year: 2016 http://library.utia.cas.cz/separaty/2018/MTR/branda-0489264.pdf
Constrained evolution in numerical relativity
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.
Enrico Sciubba
2011-06-01
Full Text Available In this paper, the entropy generation minimization (EGM method is applied to an industrial heat transfer problem: the forced convective cooling of a LED-based spotlight. The design specification calls for eighteen diodes arranged on a circular copper plate of 35 mm diameter. Every diode dissipates 3 W and the maximum allowedtemperature of the plate is 80 °C. The cooling relies on the forced convection driven by a jet of air impinging on the plate. An initial complex geometry of plate fins is presented and analyzed with a commercial CFD code that computes the entropy generation rate. A pseudo-optimization process is carried out via a successive series of design modifications based on a careful analysis of the entropy generation maps. One of the advantages of the EGM method is that the rationale behind each step of the design process can be justified on a physical basis. It is found that the best performance is attained when the fins are periodically spaced in the radial direction.
Lightweight cryptography for constrained devices
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....
Statistical mechanics of budget-constrained auctions
Altarelli, F.; Braunstein, A.; Realpe-Gomez, J.; Zecchina, R.
2009-01-01
Finding the optimal assignment in budget-constrained auctions is a combinatorial optimization problem with many important applications, a notable example being the sale of advertisement space by search engines (in this context the problem is often referred to as the off-line AdWords problem). Based on the cavity method of statistical mechanics, we introduce a message passing algorithm that is capable of solving efficiently random instances of the problem extracted from a natural distribution,...
Onomatopoeia characters extraction from comic images using constrained Delaunay triangulation
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.
Constrained blind deconvolution using Wirtinger flow methods
Walk, Philipp; Jung, Peter; Hassibi, Babak
2017-01-01
In this work we consider one-dimensional blind deconvolution with prior knowledge of signal autocorrelations in the classical framework of polynomial factorization. In particular this univariate case highly suffers from several non-trivial ambiguities and therefore blind deconvolution is known to be ill-posed in general. However, if additional autocorrelation information is available and the corresponding polynomials are co-prime, blind deconvolution is uniquely solvable up to global phase. Using lifting, the outer product of the unknown vectors is the solution to a (convex) semi-definite program (SDP) demonstrating that -theoretically- recovery is computationally tractable. However, for practical applications efficient algorithms are required which should operate in the original signal space. To this end we also discuss a gradient descent algorithm (Wirtinger flow) for the original non-convex problem. We demonstrate numerically that such an approach has performance comparable to the semidefinite program in the noisy case. Our work is motivated by applications in blind communication scenarios and we will discuss a specific signaling scheme where information is encoded into polynomial roots.
Constrained blind deconvolution using Wirtinger flow methods
Walk, Philipp
2017-09-04
In this work we consider one-dimensional blind deconvolution with prior knowledge of signal autocorrelations in the classical framework of polynomial factorization. In particular this univariate case highly suffers from several non-trivial ambiguities and therefore blind deconvolution is known to be ill-posed in general. However, if additional autocorrelation information is available and the corresponding polynomials are co-prime, blind deconvolution is uniquely solvable up to global phase. Using lifting, the outer product of the unknown vectors is the solution to a (convex) semi-definite program (SDP) demonstrating that -theoretically- recovery is computationally tractable. However, for practical applications efficient algorithms are required which should operate in the original signal space. To this end we also discuss a gradient descent algorithm (Wirtinger flow) for the original non-convex problem. We demonstrate numerically that such an approach has performance comparable to the semidefinite program in the noisy case. Our work is motivated by applications in blind communication scenarios and we will discuss a specific signaling scheme where information is encoded into polynomial roots.
Coding for Two Dimensional Constrained Fields
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....
Clustering Using Boosted Constrained k-Means Algorithm
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.
Order-constrained linear optimization.
Tidwell, Joe W; Dougherty, Michael R; Chrabaszcz, Jeffrey S; Thomas, Rick P
2017-11-01
Despite the fact that data and theories in the social, behavioural, and health sciences are often represented on an ordinal scale, there has been relatively little emphasis on modelling ordinal properties. The most common analytic framework used in psychological science is the general linear model, whose variants include ANOVA, MANOVA, and ordinary linear regression. While these methods are designed to provide the best fit to the metric properties of the data, they are not designed to maximally model ordinal properties. In this paper, we develop an order-constrained linear least-squares (OCLO) optimization algorithm that maximizes the linear least-squares fit to the data conditional on maximizing the ordinal fit based on Kendall's τ. The algorithm builds on the maximum rank correlation estimator (Han, 1987, Journal of Econometrics, 35, 303) and the general monotone model (Dougherty & Thomas, 2012, Psychological Review, 119, 321). Analyses of simulated data indicate that when modelling data that adhere to the assumptions of ordinary least squares, OCLO shows minimal bias, little increase in variance, and almost no loss in out-of-sample predictive accuracy. In contrast, under conditions in which data include a small number of extreme scores (fat-tailed distributions), OCLO shows less bias and variance, and substantially better out-of-sample predictive accuracy, even when the outliers are removed. We show that the advantages of OCLO over ordinary least squares in predicting new observations hold across a variety of scenarios in which researchers must decide to retain or eliminate extreme scores when fitting data. © 2017 The British Psychological Society.
Constraining walking and custodial technicolor
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...
Constrained multi-degree reduction with respect to Jacobi norms
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
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.
Free and constrained symplectic integrators for numerical general relativity
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
Quantization of soluble classical constrained systems
Belhadi, Z.; Menas, F.; Bérard, A.; Mohrbach, H.
2014-01-01
The derivation of the brackets among coordinates and momenta for classical constrained systems is a necessary step toward their quantization. Here we present a new approach for the determination of the classical brackets which does neither require Dirac’s formalism nor the symplectic method of Faddeev and Jackiw. This approach is based on the computation of the brackets between the constants of integration of the exact solutions of the equations of motion. From them all brackets of the dynamical variables of the system can be deduced in a straightforward way
Quantization of soluble classical constrained systems
Belhadi, Z. [Laboratoire de physique et chimie quantique, Faculté des sciences, Université Mouloud Mammeri, BP 17, 15000 Tizi Ouzou (Algeria); Laboratoire de physique théorique, Faculté des sciences exactes, Université de Bejaia, 06000 Bejaia (Algeria); Menas, F. [Laboratoire de physique et chimie quantique, Faculté des sciences, Université Mouloud Mammeri, BP 17, 15000 Tizi Ouzou (Algeria); Ecole Nationale Préparatoire aux Etudes d’ingéniorat, Laboratoire de physique, RN 5 Rouiba, Alger (Algeria); Bérard, A. [Equipe BioPhysStat, Laboratoire LCP-A2MC, ICPMB, IF CNRS No 2843, Université de Lorraine, 1 Bd Arago, 57078 Metz Cedex (France); Mohrbach, H., E-mail: herve.mohrbach@univ-lorraine.fr [Equipe BioPhysStat, Laboratoire LCP-A2MC, ICPMB, IF CNRS No 2843, Université de Lorraine, 1 Bd Arago, 57078 Metz Cedex (France)
2014-12-15
The derivation of the brackets among coordinates and momenta for classical constrained systems is a necessary step toward their quantization. Here we present a new approach for the determination of the classical brackets which does neither require Dirac’s formalism nor the symplectic method of Faddeev and Jackiw. This approach is based on the computation of the brackets between the constants of integration of the exact solutions of the equations of motion. From them all brackets of the dynamical variables of the system can be deduced in a straightforward way.
Trends in PDE constrained optimization
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”...
Pole shifting with constrained output feedback
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
Value, Cost, and Sharing: Open Issues in Constrained Clustering
Wagstaff, Kiri L.
2006-01-01
Clustering is an important tool for data mining, since it can identify major patterns or trends without any supervision (labeled data). Over the past five years, semi-supervised (constrained) clustering methods have become very popular. These methods began with incorporating pairwise constraints and have developed into more general methods that can learn appropriate distance metrics. However, several important open questions have arisen about which constraints are most useful, how they can be actively acquired, and when and how they should be propagated to neighboring points. This position paper describes these open questions and suggests future directions for constrained clustering research.
Constraining Lyman continuum escape using Machine Learning
Giri, Sambit K.; Zackrisson, Erik; Binggeli, Christian; Pelckmans, Kristiaan; Cubo, Rubén; Mellema, Garrelt
2018-05-01
The James Webb Space Telescope (JWST) will observe the rest-frame ultraviolet/optical spectra of galaxies from the epoch of reionization (EoR) in unprecedented detail. While escaping into the intergalactic medium, hydrogen-ionizing (Lyman continuum; LyC) photons from the galaxies will contribute to the bluer end of the UV slope and make nebular emission lines less prominent. We present a method to constrain leakage of the LyC photons using the spectra of high redshift (z >~ 6) galaxies. We simulate JWST/NIRSpec observations of galaxies at z =6-9 by matching the fluxes of galaxies observed in the Frontier Fields observations of galaxy cluster MACS-J0416. Our method predicts the escape fraction fesc with a mean absolute error Δfesc ~ 0.14. The method also predicts the redshifts of the galaxies with an error .
Constrained least squares regularization in PET
Choudhury, K.R.; O'Sullivan, F.O.
1996-01-01
Standard reconstruction methods used in tomography produce images with undesirable negative artifacts in background and in areas of high local contrast. While sophisticated statistical reconstruction methods can be devised to correct for these artifacts, their computational implementation is excessive for routine operational use. This work describes a technique for rapid computation of approximate constrained least squares regularization estimates. The unique feature of the approach is that it involves no iterative projection or backprojection steps. This contrasts with the familiar computationally intensive algorithms based on algebraic reconstruction (ART) or expectation-maximization (EM) methods. Experimentation with the new approach for deconvolution and mixture analysis shows that the root mean square error quality of estimators based on the proposed algorithm matches and usually dominates that of more elaborate maximum likelihood, at a fraction of the computational effort
Nested Sampling with Constrained Hamiltonian Monte Carlo
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.
Constrained minimization in C ++ environment
Dymov, S.N.; Kurbatov, V.S.; Silin, I.N.; Yashchenko, S.V.
1998-01-01
Based on the ideas, proposed by one of the authors (I.N.Silin), the suitable software was developed for constrained data fitting. Constraints may be of the arbitrary type: equalities and inequalities. The simplest of possible ways was used. Widely known program FUMILI was realized to the C ++ language. Constraints in the form of inequalities φ (θ i ) ≥ a were taken into account by change into equalities φ (θ i ) = t and simple inequalities of type t ≥ a. The equalities were taken into account by means of quadratic penalty functions. The suitable software was tested on the model data of the ANKE setup (COSY accelerator, Forschungszentrum Juelich, Germany)
Extended shadow test approach for constrained adaptive testing
Veldkamp, Bernard P.; Ariel, A.
2002-01-01
Several methods have been developed for use on constrained adaptive testing. Item pool partitioning, multistage testing, and testlet-based adaptive testing are methods that perform well for specific cases of adaptive testing. The weighted deviation model and the Shadow Test approach can be more
Formal language constrained path problems
Barrett, C.; Jacob, R.; Marathe, M.
1997-07-08
In many path finding problems arising in practice, certain patterns of edge/vertex labels in the labeled graph being traversed are allowed/preferred, while others are disallowed. Motivated by such applications as intermodal transportation planning, the authors investigate the complexity of finding feasible paths in a labeled network, where the mode choice for each traveler is specified by a formal language. The main contributions of this paper include the following: (1) the authors show that the problem of finding a shortest path between a source and destination for a traveler whose mode choice is specified as a context free language is solvable efficiently in polynomial time, when the mode choice is specified as a regular language they provide algorithms with improved space and time bounds; (2) in contrast, they show that the problem of finding simple paths between a source and a given destination is NP-hard, even when restricted to very simple regular expressions and/or very simple graphs; (3) for the class of treewidth bounded graphs, they show that (i) the problem of finding a regular language constrained simple path between source and a destination is solvable in polynomial time and (ii) the extension to finding context free language constrained simple paths is NP-complete. Several extensions of these results are presented in the context of finding shortest paths with additional constraints. These results significantly extend the results in [MW95]. As a corollary of the results, they obtain a polynomial time algorithm for the BEST k-SIMILAR PATH problem studied in [SJB97]. The previous best algorithm was given by [SJB97] and takes exponential time in the worst case.
Constrained KP models as integrable matrix hierarchies
Aratyn, H.; Ferreira, L.A.; Gomes, J.F.; Zimerman, A.H.
1997-01-01
We formulate the constrained KP hierarchy (denoted by cKP K+1,M ) as an affine [cflx sl](M+K+1) matrix integrable hierarchy generalizing the Drinfeld endash Sokolov hierarchy. Using an algebraic approach, including the graded structure of the generalized Drinfeld endash Sokolov hierarchy, we are able to find several new universal results valid for the cKP hierarchy. In particular, our method yields a closed expression for the second bracket obtained through Dirac reduction of any untwisted affine Kac endash Moody current algebra. An explicit example is given for the case [cflx sl](M+K+1), for which a closed expression for the general recursion operator is also obtained. We show how isospectral flows are characterized and grouped according to the semisimple non-regular element E of sl(M+K+1) and the content of the center of the kernel of E. copyright 1997 American Institute of Physics
Statistical mechanics of budget-constrained auctions
Altarelli, F; Braunstein, A; Realpe-Gomez, J; Zecchina, R
2009-01-01
Finding the optimal assignment in budget-constrained auctions is a combinatorial optimization problem with many important applications, a notable example being in the sale of advertisement space by search engines (in this context the problem is often referred to as the off-line AdWords problem). On the basis of the cavity method of statistical mechanics, we introduce a message-passing algorithm that is capable of solving efficiently random instances of the problem extracted from a natural distribution, and we derive from its properties the phase diagram of the problem. As the control parameter (average value of the budgets) is varied, we find two phase transitions delimiting a region in which long-range correlations arise
Statistical mechanics of budget-constrained auctions
Altarelli, F.; Braunstein, A.; Realpe-Gomez, J.; Zecchina, R.
2009-07-01
Finding the optimal assignment in budget-constrained auctions is a combinatorial optimization problem with many important applications, a notable example being in the sale of advertisement space by search engines (in this context the problem is often referred to as the off-line AdWords problem). On the basis of the cavity method of statistical mechanics, we introduce a message-passing algorithm that is capable of solving efficiently random instances of the problem extracted from a natural distribution, and we derive from its properties the phase diagram of the problem. As the control parameter (average value of the budgets) is varied, we find two phase transitions delimiting a region in which long-range correlations arise.
Time-constrained project scheduling with adjacent resources
Hurink, Johann L.; Kok, A.L.; Paulus, J.J.; Schutten, Johannes M.J.
We develop a decomposition method for the Time-Constrained Project Scheduling Problem (TCPSP) with adjacent resources. For adjacent resources the resource units are ordered and the units assigned to a job have to be adjacent. On top of that, adjacent resources are not required by single jobs, but by
In vitro transcription of a torsionally constrained template
Bentin, Thomas; Nielsen, Peter E
2002-01-01
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...
GPS-based ionospheric tomography with a constrained adaptive ...
Gauss weighted function is introduced to constrain the tomography system in the new method. It can resolve the ... the research focus in the fields of space geodesy and ... ment of GNSS such as GPS, Glonass, Galileo and. Compass, as these ...
Binary classification posed as a quadratically constrained quadratic ...
Binary classification is posed as a quadratically constrained quadratic problem and solved using the proposed method. Each class in the binary classification problem is modeled as a multidimensional ellipsoid to forma quadratic constraint in the problem. Particle swarms help in determining the optimal hyperplane or ...
GPS-based ionospheric tomography with a constrained adaptive ...
According to the continuous smoothness of the variations of ionospheric electron density (IED) among neighbouring voxels, Gauss weighted function is introduced to constrain the tomography system in the new method. It can resolve the dependence on the initial values for those voxels without any GPS rays traversing them ...
Time-constrained project scheduling with adjacent resources
Hurink, Johann L.; Kok, A.L.; Paulus, J.J.; Schutten, Johannes M.J.
2008-01-01
We develop a decomposition method for the Time-Constrained Project Scheduling Problem (TCPSP) with Adjacent Resources. For adjacent resources the resource units are ordered and the units assigned to a job have to be adjacent. On top of that, adjacent resources are not required by single jobs, but by
Solution of a Complex Least Squares Problem with Constrained Phase.
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.
In vitro transcription of a torsionally constrained template
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....
Constrained convex minimization via model-based excessive gap
Tran Dinh, Quoc; Cevher, Volkan
2014-01-01
We introduce a model-based excessive gap technique to analyze first-order primal- dual methods for constrained convex minimization. As a result, we construct new primal-dual methods with optimal convergence rates on the objective residual and the primal feasibility gap of their iterates separately. Through a dual smoothing and prox-function selection strategy, our framework subsumes the augmented Lagrangian, and alternating methods as special cases, where our rates apply.
Wavelet library for constrained devices
Ehlers, Johan Hendrik; Jassim, Sabah A.
2007-04-01
The wavelet transform is a powerful tool for image and video processing, useful in a range of applications. This paper is concerned with the efficiency of a certain fast-wavelet-transform (FWT) implementation and several wavelet filters, more suitable for constrained devices. Such constraints are typically found on mobile (cell) phones or personal digital assistants (PDA). These constraints can be a combination of; limited memory, slow floating point operations (compared to integer operations, most often as a result of no hardware support) and limited local storage. Yet these devices are burdened with demanding tasks such as processing a live video or audio signal through on-board capturing sensors. In this paper we present a new wavelet software library, HeatWave, that can be used efficiently for image/video processing/analysis tasks on mobile phones and PDA's. We will demonstrate that HeatWave is suitable for realtime applications with fine control and range to suit transform demands. We shall present experimental results to substantiate these claims. Finally this library is intended to be of real use and applied, hence we considered several well known and common embedded operating system platform differences; such as a lack of common routines or functions, stack limitations, etc. This makes HeatWave suitable for a range of applications and research projects.
Constraining the roughness degree of slip heterogeneity
Causse, Mathieu
2010-05-07
This article investigates different approaches for assessing the degree of roughness of the slip distribution of future earthquakes. First, we analyze a database of slip images extracted from a suite of 152 finite-source rupture models from 80 events (Mw = 4.1–8.9). This results in an empirical model defining the distribution of the slip spectrum corner wave numbers (kc) as a function of moment magnitude. To reduce the “epistemic” uncertainty, we select a single slip model per event and screen out poorly resolved models. The number of remaining models (30) is thus rather small. In addition, the robustness of the empirical model rests on a reliable estimation of kc by kinematic inversion methods. We address this issue by performing tests on synthetic data with a frequency domain inversion method. These tests reveal that due to smoothing constraints used to stabilize the inversion process, kc tends to be underestimated. We then develop an alternative approach: (1) we establish a proportionality relationship between kc and the peak ground acceleration (PGA), using a k−2 kinematic source model, and (2) we analyze the PGA distribution, which is believed to be better constrained than slip images. These two methods reveal that kc follows a lognormal distribution, with similar standard deviations for both methods.
Sequential unconstrained minimization algorithms for constrained optimization
Byrne, Charles
2008-01-01
The problem of minimizing a function f(x):R J → R, subject to constraints on the vector variable x, occurs frequently in inverse problems. Even without constraints, finding a minimizer of f(x) may require iterative methods. We consider here a general class of iterative algorithms that find a solution to the constrained minimization problem as the limit of a sequence of vectors, each solving an unconstrained minimization problem. Our sequential unconstrained minimization algorithm (SUMMA) is an iterative procedure for constrained minimization. At the kth step we minimize the function G k (x)=f(x)+g k (x), to obtain x k . The auxiliary functions g k (x):D subset of R J → R + are nonnegative on the set D, each x k is assumed to lie within D, and the objective is to minimize the continuous function f:R J → R over x in the set C = D-bar, the closure of D. We assume that such minimizers exist, and denote one such by x-circumflex. We assume that the functions g k (x) satisfy the inequalities 0≤g k (x)≤G k-1 (x)-G k-1 (x k-1 ), for k = 2, 3, .... Using this assumption, we show that the sequence {(x k )} is decreasing and converges to f(x-circumflex). If the restriction of f(x) to D has bounded level sets, which happens if x-circumflex is unique and f(x) is closed, proper and convex, then the sequence {x k } is bounded, and f(x*)=f(x-circumflex), for any cluster point x*. Therefore, if x-circumflex is unique, x* = x-circumflex and {x k } → x-circumflex. When x-circumflex is not unique, convergence can still be obtained, in particular cases. The SUMMA includes, as particular cases, the well-known barrier- and penalty-function methods, the simultaneous multiplicative algebraic reconstruction technique (SMART), the proximal minimization algorithm of Censor and Zenios, the entropic proximal methods of Teboulle, as well as certain cases of gradient descent and the Newton–Raphson method. The proof techniques used for SUMMA can be extended to obtain related results
The cost-constrained traveling salesman problem
Sokkappa, P.R.
1990-10-01
The Cost-Constrained Traveling Salesman Problem (CCTSP) is a variant of the well-known Traveling Salesman Problem (TSP). In the TSP, the goal is to find a tour of a given set of cities such that the total cost of the tour is minimized. In the CCTSP, each city is given a value, and a fixed cost-constraint is specified. The objective is to find a subtour of the cities that achieves maximum value without exceeding the cost-constraint. Thus, unlike the TSP, the CCTSP requires both selection and sequencing. As a consequence, most results for the TSP cannot be extended to the CCTSP. We show that the CCTSP is NP-hard and that no K-approximation algorithm or fully polynomial approximation scheme exists, unless P = NP. We also show that several special cases are polynomially solvable. Algorithms for the CCTSP, which outperform previous methods, are developed in three areas: upper bounding methods, exact algorithms, and heuristics. We found that a bounding strategy based on the knapsack problem performs better, both in speed and in the quality of the bounds, than methods based on the assignment problem. Likewise, we found that a branch-and-bound approach using the knapsack bound was superior to a method based on a common branch-and-bound method for the TSP. In our study of heuristic algorithms, we found that, when selecting modes for inclusion in the subtour, it is important to consider the neighborhood'' of the nodes. A node with low value that brings the subtour near many other nodes may be more desirable than an isolated node of high value. We found two types of repetition to be desirable: repetitions based on randomization in the subtour buildings process, and repetitions encouraging the inclusion of different subsets of the nodes. By varying the number and type of repetitions, we can adjust the computation time required by our method to obtain algorithms that outperform previous methods.
Resource Management in Constrained Dynamic Situations
Seok, Jinwoo
Resource management is considered in this dissertation for systems with limited resources, possibly combined with other system constraints, in unpredictably dynamic environments. Resources may represent fuel, power, capabilities, energy, and so on. Resource management is important for many practical systems; usually, resources are limited, and their use must be optimized. Furthermore, systems are often constrained, and constraints must be satisfied for safe operation. Simplistic resource management can result in poor use of resources and failure of the system. Furthermore, many real-world situations involve dynamic environments. Many traditional problems are formulated based on the assumptions of given probabilities or perfect knowledge of future events. However, in many cases, the future is completely unknown, and information on or probabilities about future events are not available. In other words, we operate in unpredictably dynamic situations. Thus, a method is needed to handle dynamic situations without knowledge of the future, but few formal methods have been developed to address them. Thus, the goal is to design resource management methods for constrained systems, with limited resources, in unpredictably dynamic environments. To this end, resource management is organized hierarchically into two levels: 1) planning, and 2) control. In the planning level, the set of tasks to be performed is scheduled based on limited resources to maximize resource usage in unpredictably dynamic environments. In the control level, the system controller is designed to follow the schedule by considering all the system constraints for safe and efficient operation. Consequently, this dissertation is mainly divided into two parts: 1) planning level design, based on finite state machines, and 2) control level methods, based on model predictive control. We define a recomposable restricted finite state machine to handle limited resource situations and unpredictably dynamic environments
Laterally constrained inversion for CSAMT data interpretation
Wang, Ruo; Yin, Changchun; Wang, Miaoyue; Di, Qingyun
2015-10-01
Laterally constrained inversion (LCI) has been successfully applied to the inversion of dc resistivity, TEM and airborne EM data. However, it hasn't been yet applied to the interpretation of controlled-source audio-frequency magnetotelluric (CSAMT) data. In this paper, we apply the LCI method for CSAMT data inversion by preconditioning the Jacobian matrix. We apply a weighting matrix to Jacobian to balance the sensitivity of model parameters, so that the resolution with respect to different model parameters becomes more uniform. Numerical experiments confirm that this can improve the convergence of the inversion. We first invert a synthetic dataset with and without noise to investigate the effect of LCI applications to CSAMT data, for the noise free data, the results show that the LCI method can recover the true model better compared to the traditional single-station inversion; and for the noisy data, the true model is recovered even with a noise level of 8%, indicating that LCI inversions are to some extent noise insensitive. Then, we re-invert two CSAMT datasets collected respectively in a watershed and a coal mine area in Northern China and compare our results with those from previous inversions. The comparison with the previous inversion in a coal mine shows that LCI method delivers smoother layer interfaces that well correlate to seismic data, while comparison with a global searching algorithm of simulated annealing (SA) in a watershed shows that though both methods deliver very similar good results, however, LCI algorithm presented in this paper runs much faster. The inversion results for the coal mine CSAMT survey show that a conductive water-bearing zone that was not revealed by the previous inversions has been identified by the LCI. This further demonstrates that the method presented in this paper works for CSAMT data inversion.
Optimal Power Constrained Distributed Detection over a Noisy Multiaccess Channel
Zhiwen Hu
2015-01-01
Full Text Available The problem of optimal power constrained distributed detection over a noisy multiaccess channel (MAC is addressed. Under local power constraints, we define the transformation function for sensor to realize the mapping from local decision to transmitted waveform. The deflection coefficient maximization (DCM is used to optimize the performance of power constrained fusion system. Using optimality conditions, we derive the closed-form solution to the considered problem. Monte Carlo simulations are carried out to evaluate the performance of the proposed new method. Simulation results show that the proposed method could significantly improve the detection performance of the fusion system with low signal-to-noise ratio (SNR. We also show that the proposed new method has a robust detection performance for broad SNR region.
Covariant gauges for constrained systems
Gogilidze, S.A.; Khvedelidze, A.M.; Pervushin, V.N.
1995-01-01
The method of constructing of extended phase space for singular theories which permits the consideration of covariant gauges without the introducing of a ghost fields, is proposed. The extension of the phase space is carried out by the identification of the initial theory with an equivalent theory with higher derivatives and applying to it the Ostrogradsky method of Hamiltonian description. 7 refs
Asymptotic Likelihood Distribution for Correlated & Constrained Systems
Agarwal, Ujjwal
2016-01-01
It describes my work as summer student at CERN. The report discusses the asymptotic distribution of the likelihood ratio for total no. of parameters being h and 2 out of these being are constrained and correlated.
Mathematical Modeling of Constrained Hamiltonian Systems
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
Client's Constraining Factors to Construction Project Management
factors as a significant system that constrains project management success of public and ... finance for the project and prompt payment for work executed; clients .... consideration of the loading patterns of these variables, the major factor is ...
Scheduling Aircraft Landings under Constrained Position Shifting
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.
The bounds of feasible space on constrained nonconvex quadratic programming
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.
THE DUBINS TRAVELING SALESMAN PROBLEM WITH CONSTRAINED COLLECTING MANEUVERS
Petr Váňa
2016-11-01
Full Text Available In this paper, we introduce a variant of the Dubins traveling salesman problem (DTSP that is called the Dubins traveling salesman problem with constrained collecting maneuvers (DTSP-CM. In contrast to the ordinary formulation of the DTSP, in the proposed DTSP-CM, the vehicle is requested to visit each target by specified collecting maneuver to accomplish the mission. The proposed problem formulation is motivated by scenarios with unmanned aerial vehicles where particular maneuvers are necessary for accomplishing the mission, such as object dropping or data collection with sensor sensitive to changes in vehicle heading. We consider existing methods for the DTSP and propose its modifications to use these methods to address a variant of the introduced DTSP-CM, where the collecting maneuvers are constrained to straight line segments.
How well do different tracers constrain the firn diffusivity profile?
C. M. Trudinger
2013-02-01
Full Text Available Firn air transport models are used to interpret measurements of the composition of air in firn and bubbles trapped in ice in order to reconstruct past atmospheric composition. The diffusivity profile in the firn is usually calibrated by comparing modelled and measured concentrations for tracers with known atmospheric history. However, in most cases this is an under-determined inverse problem, often with multiple solutions giving an adequate fit to the data (this is known as equifinality. Here we describe a method to estimate the firn diffusivity profile that allows multiple solutions to be identified, in order to quantify the uncertainty in diffusivity due to equifinality. We then look at how well different combinations of tracers constrain the firn diffusivity profile. Tracers with rapid atmospheric variations like CH_{3}CCl_{3}, HFCs and ^{14}CO_{2} are most useful for constraining molecular diffusivity, while &delta:^{15}N_{2} is useful for constraining parameters related to convective mixing near the surface. When errors in the observations are small and Gaussian, three carefully selected tracers are able to constrain the molecular diffusivity profile well with minimal equifinality. However, with realistic data errors or additional processes to constrain, there is benefit to including as many tracers as possible to reduce the uncertainties. We calculate CO_{2} age distributions and their spectral widths with uncertainties for five firn sites (NEEM, DE08-2, DSSW20K, South Pole 1995 and South Pole 2001 with quite different characteristics and tracers available for calibration. We recommend moving away from the use of a firn model with one calibrated parameter set to infer atmospheric histories, and instead suggest using multiple parameter sets, preferably with multiple representations of uncertain processes, to assist in quantification of the uncertainties.
A constrained variational calculation for beta-stable matter
Howes, C.; Bishop, R.F.; Irvine, J.M
1978-01-01
A method of lowest-order constrained variation previously applied by the authors to asymmetric nuclear matter is extended to include electrons and muons making the nucleon fluid electrically neutral and stable against beta decay. The equilibrium composition of a nucleon fluid is calculated as a function of baryon number density and an equation of state for beta-stable matter is deduced for the Reid soft-core interaction. (author)
Styron, Jedediah D.
The focus of this work is the characterization of a typical neutron time-of-flight (NTOF) detector that is fielded on inertial confinement fusion (ICF) experiments conducted at the Z-experimental facility with emphasis on the Magnetized Liner Fusion (MagLIF) concept. An NTOF detector consisting of EJ-228 scintillator and two independent photomultiplier tubes (PMTs), a Hamamatsu-mod 5 and Photek-PMT240, has been characterized in terms of the absolute time and energy response. The characterization was done by measuring single, neutron-induced events in the scintillator by measuring the alpha particle and neutron produced from the D-T reaction in kinematic coincidence. The results of these experiments provided the time dependent instrument response function and the detector sensitivity as a function of applied voltage covering the entire dynamic range of the detector. Historically, impulse response functions have been measured using various photon sources as surrogates for a neutron source. Thus, this measurement using a single hit neutron source results in the most accurate measured response function, which will improve the accuracy of impulse response corrections to the NTOF signals. While this detector has not yet been fielded on any MagLIF experiments, the development of a predictive capability was desired for transferring the measured detector response from the calibration geometry to the more complex Z geometry. As a proof-of-principle, a detailed model of the Z-machine was developed in MCNP6 to correct for geometry issues when transferring the calibration results from a light lab setting to the Z-environment. Representative values for the instrument response function and the sensitivity for the current detectors fielded on MagLIF experiments were convolved with the modeled results. These results were compared with data collected on three previous MagLIF experiments. The comparison shows the model results can be used to constrain three parameters that are
Positive Scattering Cross Sections using Constrained Least Squares
Dahl, J.A.; Ganapol, B.D.; Morel, J.E.
1999-01-01
A method which creates a positive Legendre expansion from truncated Legendre cross section libraries is presented. The cross section moments of order two and greater are modified by a constrained least squares algorithm, subject to the constraints that the zeroth and first moments remain constant, and that the standard discrete ordinate scattering matrix is positive. A method using the maximum entropy representation of the cross section which reduces the error of these modified moments is also presented. These methods are implemented in PARTISN, and numerical results from a transport calculation using highly anisotropic scattering cross sections with the exponential discontinuous spatial scheme is presented
Emission constrained secure economic dispatch
Arya, L.D.; Choube, S.C.; Kothari, D.P.
1997-01-01
This paper describes a methodology for secure economic operation of power system accounting emission constraint areawise as well as in totality. Davidon-Fletcher-Powell's method of optimization has been used. Inequality constraints are accounted for by a penalty function. Sensitivity coefficients have been used to evaluate the gradient vector as well as for the calculation of incremental transmission loss (ITL). AC load flow results are required in the beginning only. The algorithm has been tested on IEEE 14- and 25-bus test systems. (Author)
Quasicanonical structure of optimal control in constrained discrete systems
Sieniutycz, S.
2003-06-01
This paper considers discrete processes governed by difference rather than differential equations for the state transformation. The basic question asked is if and when Hamiltonian canonical structures are possible in optimal discrete systems. Considering constrained discrete control, general optimization algorithms are derived that constitute suitable theoretical and computational tools when evaluating extremum properties of constrained physical models. The mathematical basis of the general theory is the Bellman method of dynamic programming (DP) and its extension in the form of the so-called Carathéodory-Boltyanski (CB) stage criterion which allows a variation of the terminal state that is otherwise fixed in the Bellman's method. Two relatively unknown, powerful optimization algorithms are obtained: an unconventional discrete formalism of optimization based on a Hamiltonian for multistage systems with unconstrained intervals of holdup time, and the time interval constrained extension of the formalism. These results are general; namely, one arrives at: the discrete canonical Hamilton equations, maximum principles, and (at the continuous limit of processes with free intervals of time) the classical Hamilton-Jacobi theory along with all basic results of variational calculus. Vast spectrum of applications of the theory is briefly discussed.
Constraining new physics models with isotope shift spectroscopy
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.
Balancing computation and communication power in power constrained clusters
Piga, Leonardo; Paul, Indrani; Huang, Wei
2018-05-29
Systems, apparatuses, and methods for balancing computation and communication power in power constrained environments. A data processing cluster with a plurality of compute nodes may perform parallel processing of a workload in a power constrained environment. Nodes that finish tasks early may be power-gated based on one or more conditions. In some scenarios, a node may predict a wait duration and go into a reduced power consumption state if the wait duration is predicted to be greater than a threshold. The power saved by power-gating one or more nodes may be reassigned for use by other nodes. A cluster agent may be configured to reassign the unused power to the active nodes to expedite workload processing.
Towards weakly constrained double field theory
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.
Continuation of Sets of Constrained Orbit Segments
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....
Paul, Prasanta; Sänger-van de Griend, Cari; Adams, Erwin; Van Schepdael, Ann
2018-01-01
A simple and robust capillary zone electrophoresis Method was developed and validated for the determination of amoxicillin and clavulanate, ampicillin, phenoxymethyl penicillin (Pen V) as well as flucloxacillin. Capacitively coupled contactless conductivity detection was employed as detection Mode
Constrained principal component analysis and related techniques
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
Priority classes and weighted constrained equal awards rules for the claims problem
Szwagrzak, Karol
2015-01-01
. They are priority-augmented versions of the standard weighted constrained equal awards rules, also known as weighted gains methods (Moulin, 2000): individuals are sorted into priority classes; the resource is distributed among the individuals in the first priority class using a weighted constrained equal awards...... rule; if some of the resource is left over, then it is distributed among the individuals in the second priority class, again using a weighted constrained equal awards rule; the distribution carries on in this way until the resource is exhausted. Our characterization extends to a generalized version...
On gauge fixing and quantization of constrained Hamiltonian systems
Dayi, O.F.
1989-06-01
In constrained Hamiltonian systems which possess first class constraints some subsidiary conditions should be imposed for detecting physical observables. This issue and quantization of the system are clarified. It is argued that the reduced phase space and Dirac method of quantization, generally, differ only in the definition of the Hilbert space one should use. For the dynamical systems possessing second class constraints the definition of physical Hilbert space in the BFV-BRST operator quantization method is different from the usual definition. (author). 18 refs
Constraining Light-Quark Yukawa Couplings from Higgs Distributions
Bishara, Fady
2017-03-20
We propose a novel strategy to constrain the bottom and charm Yukawa couplings by exploiting LHC measurements of transverse momentum distributions in Higgs production. Our method does not rely on the reconstruction of exclusive final states or heavy-flavour tagging. Compared to other proposals it leads to an enhanced sensitivity to the Yukawa couplings due to distortions of the differential Higgs spectra from emissions which either probe quark loops or are associated to quark-initiated production. We derive constraints using data from LHC Run I, and we explore the prospects of our method at future LHC runs. Finally, we comment on the possibility of bounding the strange Yukawa coupling.
Adaptively Learning an Importance Function Using Transport Constrained Monte Carlo
Booth, T.E.
1998-01-01
It is well known that a Monte Carlo estimate can be obtained with zero-variance if an exact importance function for the estimate is known. There are many ways that one might iteratively seek to obtain an ever more exact importance function. This paper describes a method that has obtained ever more exact importance functions that empirically produce an error that is dropping exponentially with computer time. The method described herein constrains the importance function to satisfy the (adjoint) Boltzmann transport equation. This constraint is provided by using the known form of the solution, usually referred to as the Case eigenfunction solution
Finding intrinsic rewards by embodied evolution and constrained reinforcement learning.
Uchibe, Eiji; Doya, Kenji
2008-12-01
Understanding the design principle of reward functions is a substantial challenge both in artificial intelligence and neuroscience. Successful acquisition of a task usually requires not only rewards for goals, but also for intermediate states to promote effective exploration. This paper proposes a method for designing 'intrinsic' rewards of autonomous agents by combining constrained policy gradient reinforcement learning and embodied evolution. To validate the method, we use Cyber Rodent robots, in which collision avoidance, recharging from battery packs, and 'mating' by software reproduction are three major 'extrinsic' rewards. We show in hardware experiments that the robots can find appropriate 'intrinsic' rewards for the vision of battery packs and other robots to promote approach behaviors.
Applications of a constrained mechanics methodology in economics
Janová, Jitka
2011-11-01
This paper presents instructive interdisciplinary applications of constrained mechanics calculus in economics on a level appropriate for undergraduate physics education. The aim of the paper is (i) to meet the demand for illustrative examples suitable for presenting the background of the highly expanding research field of econophysics even at the undergraduate level and (ii) to enable the students to gain a deeper understanding of the principles and methods routinely used in mechanics by looking at the well-known methodology from the different perspective of economics. Two constrained dynamic economic problems are presented using the economic terminology in an intuitive way. First, the Phillips model of the business cycle is presented as a system of forced oscillations and the general problem of two interacting economies is solved by the nonholonomic dynamics approach. Second, the Cass-Koopmans-Ramsey model of economical growth is solved as a variational problem with a velocity-dependent constraint using the vakonomic approach. The specifics of the solution interpretation in economics compared to mechanics is discussed in detail, a discussion of the nonholonomic and vakonomic approaches to constrained problems in mechanics and economics is provided and an economic interpretation of the Lagrange multipliers (possibly surprising for the students of physics) is carefully explained. This paper can be used by the undergraduate students of physics interested in interdisciplinary physics applications to gain an understanding of the current scientific approach to economics based on a physical background, or by university teachers as an attractive supplement to classical mechanics lessons.
Applications of a constrained mechanics methodology in economics
Janova, Jitka
2011-01-01
This paper presents instructive interdisciplinary applications of constrained mechanics calculus in economics on a level appropriate for undergraduate physics education. The aim of the paper is (i) to meet the demand for illustrative examples suitable for presenting the background of the highly expanding research field of econophysics even at the undergraduate level and (ii) to enable the students to gain a deeper understanding of the principles and methods routinely used in mechanics by looking at the well-known methodology from the different perspective of economics. Two constrained dynamic economic problems are presented using the economic terminology in an intuitive way. First, the Phillips model of the business cycle is presented as a system of forced oscillations and the general problem of two interacting economies is solved by the nonholonomic dynamics approach. Second, the Cass-Koopmans-Ramsey model of economical growth is solved as a variational problem with a velocity-dependent constraint using the vakonomic approach. The specifics of the solution interpretation in economics compared to mechanics is discussed in detail, a discussion of the nonholonomic and vakonomic approaches to constrained problems in mechanics and economics is provided and an economic interpretation of the Lagrange multipliers (possibly surprising for the students of physics) is carefully explained. This paper can be used by the undergraduate students of physics interested in interdisciplinary physics applications to gain an understanding of the current scientific approach to economics based on a physical background, or by university teachers as an attractive supplement to classical mechanics lessons.
Applications of a constrained mechanics methodology in economics
Janova, Jitka, E-mail: janova@mendelu.cz [Department of Theoretical Physics and Astrophysics, Faculty of Science, Masaryk University, Kotlarska 2, 611 37 Brno (Czech Republic); Department of Statistics and Operation Analysis, Faculty of Business and Economics, Mendel University in Brno, Zemedelska 1, 613 00 Brno (Czech Republic)
2011-11-15
This paper presents instructive interdisciplinary applications of constrained mechanics calculus in economics on a level appropriate for undergraduate physics education. The aim of the paper is (i) to meet the demand for illustrative examples suitable for presenting the background of the highly expanding research field of econophysics even at the undergraduate level and (ii) to enable the students to gain a deeper understanding of the principles and methods routinely used in mechanics by looking at the well-known methodology from the different perspective of economics. Two constrained dynamic economic problems are presented using the economic terminology in an intuitive way. First, the Phillips model of the business cycle is presented as a system of forced oscillations and the general problem of two interacting economies is solved by the nonholonomic dynamics approach. Second, the Cass-Koopmans-Ramsey model of economical growth is solved as a variational problem with a velocity-dependent constraint using the vakonomic approach. The specifics of the solution interpretation in economics compared to mechanics is discussed in detail, a discussion of the nonholonomic and vakonomic approaches to constrained problems in mechanics and economics is provided and an economic interpretation of the Lagrange multipliers (possibly surprising for the students of physics) is carefully explained. This paper can be used by the undergraduate students of physics interested in interdisciplinary physics applications to gain an understanding of the current scientific approach to economics based on a physical background, or by university teachers as an attractive supplement to classical mechanics lessons.
Bidirectional Dynamic Diversity Evolutionary Algorithm for Constrained Optimization
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.
On Tree-Constrained Matchings and Generalizations
S. Canzar (Stefan); K. Elbassioni; G.W. Klau (Gunnar); J. Mestre
2011-01-01
htmlabstractWe consider the following \\textsc{Tree-Constrained Bipartite Matching} problem: Given two rooted trees $T_1=(V_1,E_1)$, $T_2=(V_2,E_2)$ and a weight function $w: V_1\\times V_2 \\mapsto \\mathbb{R}_+$, find a maximum weight matching $\\mathcal{M}$ between nodes of the two trees, such that
Constrained systems described by Nambu mechanics
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
Client's constraining factors to construction project management ...
This study analyzed client's related factors that constrain project management success of public and private sector construction in Nigeria. Issues that concern clients in any project can not be undermined as they are the owners and the initiators of project proposals. It is assumed that success, failure or abandonment of ...
A Dynamic Programming Approach to Constrained Portfolios
Kraft, Holger; Steffensen, Mogens
2013-01-01
This paper studies constrained portfolio problems that may involve constraints on the probability or the expected size of a shortfall of wealth or consumption. Our first contribution is that we solve the problems by dynamic programming, which is in contrast to the existing literature that applies...
A model for optimal constrained adaptive testing
van der Linden, Willem J.; Reese, Lynda M.
2001-01-01
A model for constrained computerized adaptive testing is proposed in which the information on the test at the ability estimate is maximized subject to a large variety of possible constraints on the contents of the test. At each item-selection step, a full test is first assembled to have maximum
A model for optimal constrained adaptive testing
van der Linden, Willem J.; Reese, Lynda M.
1997-01-01
A model for constrained computerized adaptive testing is proposed in which the information in the test at the ability estimate is maximized subject to a large variety of possible constraints on the contents of the test. At each item-selection step, a full test is first assembled to have maximum
Neutron Powder Diffraction and Constrained Refinement
Pawley, G. S.; Mackenzie, Gordon A.; Dietrich, O. W.
1977-01-01
The first use of a new program, EDINP, is reported. This program allows the constrained refinement of molecules in a crystal structure with neutron diffraction powder data. The structures of p-C6F4Br2 and p-C6F4I2 are determined by packing considerations and then refined with EDINP. Refinement is...
Terrestrial Sagnac delay constraining modified gravity models
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.
Chance constrained uncertain classification via robust optimization
Ben-Tal, A.; Bhadra, S.; Bhattacharayya, C.; Saketha Nat, J.
2011-01-01
This paper studies the problem of constructing robust classifiers when the training is plagued with uncertainty. The problem is posed as a Chance-Constrained Program (CCP) which ensures that the uncertain data points are classified correctly with high probability. Unfortunately such a CCP turns out
Integrating job scheduling and constrained network routing
Gamst, Mette
2010-01-01
This paper examines the NP-hard problem of scheduling jobs on resources such that the overall profit of executed jobs is maximized. Job demand must be sent through a constrained network to the resource before execution can begin. The problem has application in grid computing, where a number...
Neuroevolutionary Constrained Optimization for Content Creation
Liapis, Antonios; Yannakakis, Georgios N.; Togelius, Julian
2011-01-01
and thruster types and topologies) independently of game physics and steering strategies. According to the proposed framework, the designer picks a set of requirements for the spaceship that a constrained optimizer attempts to satisfy. The constraint satisfaction approach followed is based on neuroevolution...... and survival tasks and are also visually appealing....
Models of Flux Tubes from Constrained Relaxation
tribpo
J. Astrophys. Astr. (2000) 21, 299 302. Models of Flux Tubes from Constrained Relaxation. Α. Mangalam* & V. Krishan†, Indian Institute of Astrophysics, Koramangala,. Bangalore 560 034, India. *e mail: mangalam @ iiap. ernet. in. † e mail: vinod@iiap.ernet.in. Abstract. We study the relaxation of a compressible plasma to ...
Low-lying excited states by constrained DFT
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.
de Oliveira, Rodrigo Rocha; de Lima, Kássio Michell Gomes; Tauler, Romà; de Juan, Anna
2014-07-01
This study describes two applications of a variant of the multivariate curve resolution alternating least squares (MCR-ALS) method with a correlation constraint. The first application describes the use of MCR-ALS for the determination of biodiesel concentrations in biodiesel blends using near infrared (NIR) spectroscopic data. In the second application, the proposed method allowed the determination of the synthetic antioxidant N,N'-Di-sec-butyl-p-phenylenediamine (PDA) present in biodiesel mixtures from different vegetable sources using UV-visible spectroscopy. Well established multivariate regression algorithm, partial least squares (PLS), were calculated for comparison of the quantification performance in the models developed in both applications. The correlation constraint has been adapted to handle the presence of batch-to-batch matrix effects due to ageing effects, which might occur when different groups of samples were used to build a calibration model in the first application. Different data set configurations and diverse modes of application of the correlation constraint are explored and guidelines are given to cope with different type of analytical problems, such as the correction of matrix effects among biodiesel samples, where MCR-ALS outperformed PLS reducing the relative error of prediction RE (%) from 9.82% to 4.85% in the first application, or the determination of minor compound with overlapped weak spectroscopic signals, where MCR-ALS gave higher (RE (%)=3.16%) for prediction of PDA compared to PLS (RE (%)=1.99%), but with the advantage of recovering the related pure spectral profile of analytes and interferences. The obtained results show the potential of the MCR-ALS method with correlation constraint to be adapted to diverse data set configurations and analytical problems related to the determination of biodiesel mixtures and added compounds therein. Copyright © 2014 Elsevier B.V. All rights reserved.
INTAN S. AHMAD
2008-04-01
Full Text Available This work presents the application of a primal-dual interior point method to minimax optimisation problems. The algorithm differs significantly from previous approaches as it involves a novel non-monotone line search procedure, which is based on the use of standard penalty methods as the merit function used for line search. The crucial novel concept is the discretisation of the penalty parameter used over a finite range of orders of magnitude and the provision of a memory list for each such order. An implementation within a logarithmic barrier algorithm for bounds handling is presented with capabilities for large scale application. Case studies presented demonstrate the capabilities of the proposed methodology, which relies on the reformulation of minimax models into standard nonlinear optimisation models. Some previously reported case studies from the open literature have been solved, and with significantly better optimal solutions identified. We believe that the nature of the non-monotone line search scheme allows the search procedure to escape from local minima, hence the encouraging results obtained.
Generation and Analysis of Constrained Random Sampling Patterns
Pierzchlewski, Jacek; Arildsen, Thomas
2016-01-01
Random sampling is a technique for signal acquisition which is gaining popularity in practical signal processing systems. Nowadays, event-driven analog-to-digital converters make random sampling feasible in practical applications. A process of random sampling is defined by a sampling pattern, which...... indicates signal sampling points in time. Practical random sampling patterns are constrained by ADC characteristics and application requirements. In this paper, we introduce statistical methods which evaluate random sampling pattern generators with emphasis on practical applications. Furthermore, we propose...... algorithm generates random sampling patterns dedicated for event-driven-ADCs better than existed sampling pattern generators. Finally, implementation issues of random sampling patterns are discussed....
Stress-constrained topology optimization for compliant mechanism design
de Leon, Daniel M.; Alexandersen, Joe; Jun, Jun S.
2015-01-01
This article presents an application of stress-constrained topology optimization to compliant mechanism design. An output displacement maximization formulation is used, together with the SIMP approach and a projection method to ensure convergence to nearly discrete designs. The maximum stress...... is approximated using a normalized version of the commonly-used p-norm of the effective von Mises stresses. The usual problems associated with topology optimization for compliant mechanism design: one-node and/or intermediate density hinges are alleviated by the stress constraint. However, it is also shown...
Self-constrained inversion of potential fields
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.
Cosmogenic photons strongly constrain UHECR source models
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.
A constrained supersymmetric left-right model
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.
Communication Schemes with Constrained Reordering of Resources
Popovski, Petar; Utkovski, Zoran; Trillingsgaard, Kasper Fløe
2013-01-01
This paper introduces a communication model inspired by two practical scenarios. The first scenario is related to the concept of protocol coding, where information is encoded in the actions taken by an existing communication protocol. We investigate strategies for protocol coding via combinatorial...... reordering of the labelled user resources (packets, channels) in an existing, primary system. However, the degrees of freedom of the reordering are constrained by the operation of the primary system. The second scenario is related to communication systems with energy harvesting, where the transmitted signals...... are constrained by the energy that is available through the harvesting process. We have introduced a communication model that covers both scenarios and elicits their key feature, namely the constraints of the primary system or the harvesting process. We have shown how to compute the capacity of the channels...
Q-deformed systems and constrained dynamics
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.)
Quan, Lulin; Yang, Zhixin
2010-05-01
To address the issues in the area of design customization, this paper expressed the specification and application of the constrained surface deformation, and reported the experimental performance comparison of three prevail effective similarity assessment algorithms on constrained surface deformation domain. Constrained surface deformation becomes a promising method that supports for various downstream applications of customized design. Similarity assessment is regarded as the key technology for inspecting the success of new design via measuring the difference level between the deformed new design and the initial sample model, and indicating whether the difference level is within the limitation. According to our theoretical analysis and pre-experiments, three similarity assessment algorithms are suitable for this domain, including shape histogram based method, skeleton based method, and U system moment based method. We analyze their basic functions and implementation methodologies in detail, and do a series of experiments on various situations to test their accuracy and efficiency using precision-recall diagram. Shoe model is chosen as an industrial example for the experiments. It shows that shape histogram based method gained an optimal performance in comparison. Based on the result, we proposed a novel approach that integrating surface constrains and shape histogram description with adaptive weighting method, which emphasize the role of constrains during the assessment. The limited initial experimental result demonstrated that our algorithm outperforms other three algorithms. A clear direction for future development is also drawn at the end of the paper.
Online constrained model-based reinforcement learning
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...
Constraining supergravity models from gluino production
Barbieri, R.; Gamberini, G.; Giudice, G.F.; Ridolfi, G.
1988-01-01
The branching ratios for gluino decays g tilde → qanti qΧ, g tilde → gΧ into a stable undetected neutralino are computed as functions of the relevant parameters of the underlying supergravity theory. A simple way of constraining supergravity models from gluino production emerges. The effectiveness of hadronic versus e + e - colliders in the search for supersymmetry can be directly compared. (orig.)
Cosmicflows Constrained Local UniversE Simulations
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.
Dynamic Convex Duality in Constrained Utility Maximization
Li, Yusong; Zheng, Harry
2016-01-01
In this paper, we study a constrained utility maximization problem following the convex duality approach. After formulating the primal and dual problems, we construct the necessary and sufficient conditions for both the primal and dual problems in terms of FBSDEs plus additional conditions. Such formulation then allows us to explicitly characterize the primal optimal control as a function of the adjoint process coming from the dual FBSDEs in a dynamic fashion and vice versa. Moreover, we also...
Constraining neutron star matter with Quantum Chromodynamics
Kurkela, Aleksi; Schaffner-Bielich, Jurgen; Vuorinen, Aleksi
2014-01-01
In recent years, there have been several successful attempts to constrain the equation of state of neutron star matter using input from low-energy nuclear physics and observational data. We demonstrate that significant further restrictions can be placed by additionally requiring the pressure to approach that of deconfined quark matter at high densities. Remarkably, the new constraints turn out to be highly insensitive to the amount --- or even presence --- of quark matter inside the stars.
Constraining the mass of the Local Group
Carlesi, Edoardo; Hoffman, Yehuda; Sorce, Jenny G.; Gottlöber, Stefan
2017-03-01
The mass of the Local Group (LG) is a crucial parameter for galaxy formation theories. However, its observational determination is challenging - its mass budget is dominated by dark matter that cannot be directly observed. To meet this end, the posterior distributions of the LG and its massive constituents have been constructed by means of constrained and random cosmological simulations. Two priors are assumed - the Λ cold dark matter model that is used to set up the simulations, and an LG model that encodes the observational knowledge of the LG and is used to select LG-like objects from the simulations. The constrained simulations are designed to reproduce the local cosmography as it is imprinted on to the Cosmicflows-2 data base of velocities. Several prescriptions are used to define the LG model, focusing in particular on different recent estimates of the tangential velocity of M31. It is found that (a) different vtan choices affect the peak mass values up to a factor of 2, and change mass ratios of MM31 to MMW by up to 20 per cent; (b) constrained simulations yield more sharply peaked posterior distributions compared with the random ones; (c) LG mass estimates are found to be smaller than those found using the timing argument; (d) preferred Milky Way masses lie in the range of (0.6-0.8) × 1012 M⊙; whereas (e) MM31 is found to vary between (1.0-2.0) × 1012 M⊙, with a strong dependence on the vtan values used.
A method of generating moving objects on the constrained network
Zhang, Jie; Ma, Linbing
2008-10-01
Moving objects databases have become an important research issue in recent years. In case large real data sets acquired by GPS, PDA or other mobile devices are not available, benchmarking requires the generation of artificial data sets following the real-world behavior of spatial objects that change their locations over time. In the field of spatiotemporal databases, a number of publications about the generation of test data are restricted to few papers. However, most of the existing moving-object generators assume a fixed and often unrealistic mobility model and do not consider several important characteristics of the network. In this paper, a new generator is presented to solve these problems. First of all, the network is realistic transportation network of Guangzhou. Second, the observation records of vehicle flow are available. Third, in order to simplify the whole simulation process and to help us visualize the process, this framework is built under .Net development platform of Microsoft and ArcEngine9 environment.
Constraining spacetime nonmetricity with Lorentz-violation methods
Xiao, Zhi; Lehnert, Ralf; Snow, W. M.; Xu, Rui
2018-01-01
In this report, we will give the first constraints on in-matter nonmetricity. We will show how the effective-field-theory (EFT) toolbox developed for the study of Lorentz violation (LV) can be employed for investigations of the “effective LV” background caused by nonmetricity, a geometric object extending the notion of a Riemannian manifold. The idea is to probe for the effects of spacetime nonmetricity sourced by liquid 4He with polarized slow neutrons. We present the first constraints on isotropic and parity-odd nonmetricity components. Further constraints on anisotropic nonmetricity components within this EFT framework may be feasible with proper experimental techniques in the near future.
Resource Constrained Planning of Multiple Projects with Separable Activities
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.
Maximum Constrained Directivity of Oversteered End-Fire Sensor Arrays
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.
Constraining continuous rainfall simulations for derived design flood estimation
Woldemeskel, F. M.; Sharma, A.; Mehrotra, R.; Westra, S.
2016-11-01
Stochastic rainfall generation is important for a range of hydrologic and water resources applications. Stochastic rainfall can be generated using a number of models; however, preserving relevant attributes of the observed rainfall-including rainfall occurrence, variability and the magnitude of extremes-continues to be difficult. This paper develops an approach to constrain stochastically generated rainfall with an aim of preserving the intensity-durationfrequency (IFD) relationships of the observed data. Two main steps are involved. First, the generated annual maximum rainfall is corrected recursively by matching the generated intensity-frequency relationships to the target (observed) relationships. Second, the remaining (non-annual maximum) rainfall is rescaled such that the mass balance of the generated rain before and after scaling is maintained. The recursive correction is performed at selected storm durations to minimise the dependence between annual maximum values of higher and lower durations for the same year. This ensures that the resulting sequences remain true to the observed rainfall as well as represent the design extremes that may have been developed separately and are needed for compliance reasons. The method is tested on simulated 6 min rainfall series across five Australian stations with different climatic characteristics. The results suggest that the annual maximum and the IFD relationships are well reproduced after constraining the simulated rainfall. While our presentation focusses on the representation of design rainfall attributes (IFDs), the proposed approach can also be easily extended to constrain other attributes of the generated rainfall, providing an effective platform for post-processing of stochastic rainfall generators.
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.
Incomplete Dirac reduction of constrained Hamiltonian systems
Chandre, C., E-mail: chandre@cpt.univ-mrs.fr
2015-10-15
First-class constraints constitute a potential obstacle to the computation of a Poisson bracket in Dirac’s theory of constrained Hamiltonian systems. Using the pseudoinverse instead of the inverse of the matrix defined by the Poisson brackets between the constraints, we show that a Dirac–Poisson bracket can be constructed, even if it corresponds to an incomplete reduction of the original Hamiltonian system. The uniqueness of Dirac brackets is discussed. The relevance of this procedure for infinite dimensional Hamiltonian systems is exemplified.
Capturing Hotspots For Constrained Indoor Movement
Ahmed, Tanvir; Pedersen, Torben Bach; Lu, Hua
2013-01-01
Finding the hotspots in large indoor spaces is very important for getting overloaded locations, security, crowd management, indoor navigation and guidance. The tracking data coming from indoor tracking are huge in volume and not readily available for finding hotspots. This paper presents a graph......-based model for constrained indoor movement that can map the tracking records into mapping records which represent the entry and exit times of an object in a particular location. Then it discusses the hotspots extraction technique from the mapping records....
Toward Cognitively Constrained Models of Language Processing: A Review
Margreet Vogelzang
2017-09-01
Full Text Available Language processing is not an isolated capacity, but is embedded in other aspects of our cognition. However, it is still largely unexplored to what extent and how language processing interacts with general cognitive resources. This question can be investigated with cognitively constrained computational models, which simulate the cognitive processes involved in language processing. The theoretical claims implemented in cognitive models interact with general architectural constraints such as memory limitations. This way, it generates new predictions that can be tested in experiments, thus generating new data that can give rise to new theoretical insights. This theory-model-experiment cycle is a promising method for investigating aspects of language processing that are difficult to investigate with more traditional experimental techniques. This review specifically examines the language processing models of Lewis and Vasishth (2005, Reitter et al. (2011, and Van Rij et al. (2010, all implemented in the cognitive architecture Adaptive Control of Thought—Rational (Anderson et al., 2004. These models are all limited by the assumptions about cognitive capacities provided by the cognitive architecture, but use different linguistic approaches. Because of this, their comparison provides insight into the extent to which assumptions about general cognitive resources influence concretely implemented models of linguistic competence. For example, the sheer speed and accuracy of human language processing is a current challenge in the field of cognitive modeling, as it does not seem to adhere to the same memory and processing capacities that have been found in other cognitive processes. Architecture-based cognitive models of language processing may be able to make explicit which language-specific resources are needed to acquire and process natural language. The review sheds light on cognitively constrained models of language processing from two angles: we
Changes in epistemic frameworks: Random or constrained?
Ananka Loubser
2012-11-01
Full Text Available Since the emergence of a solid anti-positivist approach in the philosophy of science, an important question has been to understand how and why epistemic frameworks change in time, are modified or even substituted. In contemporary philosophy of science three main approaches to framework-change were detected in the humanist tradition:1. In both the pre-theoretical and theoretical domains changes occur according to a rather constrained, predictable or even pre-determined pattern (e.g. Holton.2. Changes occur in a way that is more random or unpredictable and free from constraints (e.g. Kuhn, Feyerabend, Rorty, Lyotard.3. Between these approaches, a middle position can be found, attempting some kind of synthesis (e.g. Popper, Lakatos.Because this situation calls for clarification and systematisation, this article in fact tried to achieve more clarity on how changes in pre-scientific frameworks occur, as well as provided transcendental criticism of the above positions. This article suggested that the above-mentioned positions are not fully satisfactory, as change and constancy are not sufficiently integrated. An alternative model was suggested in which changes in epistemic frameworks occur according to a pattern, neither completely random nor rigidly constrained, which results in change being dynamic but not arbitrary. This alternative model is integral, rather than dialectical and therefore does not correspond to position three.
Fringe instability in constrained soft elastic layers.
Lin, Shaoting; Cohen, Tal; Zhang, Teng; Yuk, Hyunwoo; Abeyaratne, Rohan; Zhao, Xuanhe
2016-11-04
Soft elastic layers with top and bottom surfaces adhered to rigid bodies are abundant in biological organisms and engineering applications. As the rigid bodies are pulled apart, the stressed layer can exhibit various modes of mechanical instabilities. In cases where the layer's thickness is much smaller than its length and width, the dominant modes that have been studied are the cavitation, interfacial and fingering instabilities. Here we report a new mode of instability which emerges if the thickness of the constrained elastic layer is comparable to or smaller than its width. In this case, the middle portion along the layer's thickness elongates nearly uniformly while the constrained fringe portions of the layer deform nonuniformly. When the applied stretch reaches a critical value, the exposed free surfaces of the fringe portions begin to undulate periodically without debonding from the rigid bodies, giving the fringe instability. We use experiments, theory and numerical simulations to quantitatively explain the fringe instability and derive scaling laws for its critical stress, critical strain and wavelength. We show that in a force controlled setting the elastic fingering instability is associated with a snap-through buckling that does not exist for the fringe instability. The discovery of the fringe instability will not only advance the understanding of mechanical instabilities in soft materials but also have implications for biological and engineered adhesives and joints.
Block-triangular preconditioners for PDE-constrained optimization
Rees, Tyrone; Stoll, Martin
2010-01-01
In this paper we investigate the possibility of using a block-triangular preconditioner for saddle point problems arising in PDE-constrained optimization. In particular, we focus on a conjugate gradient-type method introduced by Bramble and Pasciak that uses self-adjointness of the preconditioned system in a non-standard inner product. We show when the Chebyshev semi-iteration is used as a preconditioner for the relevant matrix blocks involving the finite element mass matrix that the main drawback of the Bramble-Pasciak method-the appropriate scaling of the preconditioners-is easily overcome. We present an eigenvalue analysis for the block-triangular preconditioners that gives convergence bounds in the non-standard inner product and illustrates their competitiveness on a number of computed examples. Copyright © 2010 John Wiley & Sons, Ltd.
A Constrained Algorithm Based NMFα for Image Representation
Chenxue Yang
2014-01-01
Full Text Available Nonnegative matrix factorization (NMF is a useful tool in learning a basic representation of image data. However, its performance and applicability in real scenarios are limited because of the lack of image information. In this paper, we propose a constrained matrix decomposition algorithm for image representation which contains parameters associated with the characteristics of image data sets. Particularly, we impose label information as additional hard constraints to the α-divergence-NMF unsupervised learning algorithm. The resulted algorithm is derived by using Karush-Kuhn-Tucker (KKT conditions as well as the projected gradient and its monotonic local convergence is proved by using auxiliary functions. In addition, we provide a method to select the parameters to our semisupervised matrix decomposition algorithm in the experiment. Compared with the state-of-the-art approaches, our method with the parameters has the best classification accuracy on three image data sets.
Constraining Light-Quark Yukawa Couplings from Higgs Distributions
Bishara, Fady; Haisch, Ulrich; Monni, Pier Francesco; Re, Emanuele
2017-03-01
We propose a novel strategy to constrain the bottom and charm Yukawa couplings by exploiting Large Hadron Collider (LHC) measurements of transverse momentum distributions in Higgs production. Our method does not rely on the reconstruction of exclusive final states or heavy-flavor tagging. Compared to other proposals, it leads to an enhanced sensitivity to the Yukawa couplings due to distortions of the differential Higgs spectra from emissions which either probe quark loops or are associated with quark-initiated production. We derive constraints using data from LHC run I, and we explore the prospects of our method at future LHC runs. Finally, we comment on the possibility of bounding the strange Yukawa coupling.
Block-triangular preconditioners for PDE-constrained optimization
Rees, Tyrone
2010-11-26
In this paper we investigate the possibility of using a block-triangular preconditioner for saddle point problems arising in PDE-constrained optimization. In particular, we focus on a conjugate gradient-type method introduced by Bramble and Pasciak that uses self-adjointness of the preconditioned system in a non-standard inner product. We show when the Chebyshev semi-iteration is used as a preconditioner for the relevant matrix blocks involving the finite element mass matrix that the main drawback of the Bramble-Pasciak method-the appropriate scaling of the preconditioners-is easily overcome. We present an eigenvalue analysis for the block-triangular preconditioners that gives convergence bounds in the non-standard inner product and illustrates their competitiveness on a number of computed examples. Copyright © 2010 John Wiley & Sons, Ltd.
Constrained non-linear waves for offshore wind turbine design
Rainey, P J; Camp, T R
2007-01-01
Advancements have been made in the modelling of extreme wave loading in the offshore environment. We give an overview of wave models used at present, and their relative merits. We describe a method for embedding existing non-linear solutions for large, regular wave kinematics into linear, irregular seas. Although similar methods have been used before, the new technique is shown to offer advances in computational practicality, repeatability, and accuracy. NewWave theory has been used to constrain the linear simulation, allowing best possible fit with the large non-linear wave. GH Bladed was used to compare the effect of these models on a generic 5 MW turbine mounted on a tripod support structure
Constraining Light-Quark Yukawa Couplings from Higgs Distributions.
Bishara, Fady; Haisch, Ulrich; Monni, Pier Francesco; Re, Emanuele
2017-03-24
We propose a novel strategy to constrain the bottom and charm Yukawa couplings by exploiting Large Hadron Collider (LHC) measurements of transverse momentum distributions in Higgs production. Our method does not rely on the reconstruction of exclusive final states or heavy-flavor tagging. Compared to other proposals, it leads to an enhanced sensitivity to the Yukawa couplings due to distortions of the differential Higgs spectra from emissions which either probe quark loops or are associated with quark-initiated production. We derive constraints using data from LHC run I, and we explore the prospects of our method at future LHC runs. Finally, we comment on the possibility of bounding the strange Yukawa coupling.
Pareto-optimal estimates that constrain mean California precipitation change
Langenbrunner, B.; Neelin, J. D.
2017-12-01
Global climate model (GCM) projections of greenhouse gas-induced precipitation change can exhibit notable uncertainty at the regional scale, particularly in regions where the mean change is small compared to internal variability. This is especially true for California, which is located in a transition zone between robust precipitation increases to the north and decreases to the south, and where GCMs from the Climate Model Intercomparison Project phase 5 (CMIP5) archive show no consensus on mean change (in either magnitude or sign) across the central and southern parts of the state. With the goal of constraining this uncertainty, we apply a multiobjective approach to a large set of subensembles (subsets of models from the full CMIP5 ensemble). These constraints are based on subensemble performance in three fields important to California precipitation: tropical Pacific sea surface temperatures, upper-level zonal winds in the midlatitude Pacific, and precipitation over the state. An evolutionary algorithm is used to sort through and identify the set of Pareto-optimal subensembles across these three measures in the historical climatology, and we use this information to constrain end-of-century California wet season precipitation change. This technique narrows the range of projections throughout the state and increases confidence in estimates of positive mean change. Furthermore, these methods complement and generalize emergent constraint approaches that aim to restrict uncertainty in end-of-century projections, and they have applications to even broader aspects of uncertainty quantification, including parameter sensitivity and model calibration.
Constrained Null Space Component Analysis for Semiblind Source Separation Problem.
Hwang, Wen-Liang; Lu, Keng-Shih; Ho, Jinn
2018-02-01
The blind source separation (BSS) problem extracts unknown sources from observations of their unknown mixtures. A current trend in BSS is the semiblind approach, which incorporates prior information on sources or how the sources are mixed. The constrained independent component analysis (ICA) approach has been studied to impose constraints on the famous ICA framework. We introduced an alternative approach based on the null space component (NCA) framework and referred to the approach as the c-NCA approach. We also presented the c-NCA algorithm that uses signal-dependent semidefinite operators, which is a bilinear mapping, as signatures for operator design in the c-NCA approach. Theoretically, we showed that the source estimation of the c-NCA algorithm converges with a convergence rate dependent on the decay of the sequence, obtained by applying the estimated operators on corresponding sources. The c-NCA can be formulated as a deterministic constrained optimization method, and thus, it can take advantage of solvers developed in optimization society for solving the BSS problem. As examples, we demonstrated electroencephalogram interference rejection problems can be solved by the c-NCA with proximal splitting algorithms by incorporating a sparsity-enforcing separation model and considering the case when reference signals are available.
A New Interpolation Approach for Linearly Constrained Convex Optimization
Espinoza, Francisco
2012-08-01
In this thesis we propose a new class of Linearly Constrained Convex Optimization methods based on the use of a generalization of Shepard\\'s interpolation formula. We prove the properties of the surface such as the interpolation property at the boundary of the feasible region and the convergence of the gradient to the null space of the constraints at the boundary. We explore several descent techniques such as steepest descent, two quasi-Newton methods and the Newton\\'s method. Moreover, we implement in the Matlab language several versions of the method, particularly for the case of Quadratic Programming with bounded variables. Finally, we carry out performance tests against Matab Optimization Toolbox methods for convex optimization and implementations of the standard log-barrier and active-set methods. We conclude that the steepest descent technique seems to be the best choice so far for our method and that it is competitive with other standard methods both in performance and empirical growth order.
Comparison of phase-constrained parallel MRI approaches: Analogies and differences.
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.
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.
Lidar Penetration Depth Observations for Constraining Cloud Longwave Feedbacks
Vaillant de Guelis, T.; Chepfer, H.; Noel, V.; Guzman, R.; Winker, D. M.; Kay, J. E.; Bonazzola, M.
2017-12-01
Satellite-borne active remote sensing Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations [CALIPSO; Winker et al., 2010] and CloudSat [Stephens et al., 2002] provide direct measurements of the cloud vertical distribution, with a very high vertical resolution. The penetration depth of the laser of the lidar Z_Opaque is directly linked to the LongWave (LW) Cloud Radiative Effect (CRE) at Top Of Atmosphere (TOA) [Vaillant de Guélis et al., in review]. In addition, this measurement is extremely stable in time making it an excellent observational candidate to verify and constrain the cloud LW feedback mechanism [Chepfer et al., 2014]. In this work, we present a method to decompose the variations of the LW CRE at TOA using cloud properties observed by lidar [GOCCP v3.0; Guzman et al., 2017]. We decompose these variations into contributions due to changes in five cloud properties: opaque cloud cover, opaque cloud altitude, thin cloud cover, thin cloud altitude, and thin cloud emissivity [Vaillant de Guélis et al., in review]. We apply this method, in the real world, to the CRE variations of CALIPSO 2008-2015 record, and, in climate model, to LMDZ6 and CESM simulations of the CRE variations of 2008-2015 period and of the CRE difference between a warm climate and the current climate. In climate model simulations, the same cloud properties as those observed by CALIOP are extracted from the CFMIP Observation Simulator Package (COSP) [Bodas-Salcedo et al., 2011] lidar simulator [Chepfer et al., 2008], which mimics the observations that would be performed by the lidar on board CALIPSO satellite. This method, when applied on multi-model simulations of current and future climate, could reveal the altitude of cloud opacity level observed by lidar as a strong constrain for cloud LW feedback, since the altitude feedback mechanism is physically explainable and the altitude of cloud opacity accurately observed by lidar.
Scheduling of resource-constrained projects
Klein, Robert
2000-01-01
Project management has become a widespread instrument enabling organizations to efficiently master the challenges of steadily shortening product life cycles, global markets and decreasing profit margins. With projects increasing in size and complexity, their planning and control represents one of the most crucial management tasks. This is especially true for scheduling, which is concerned with establishing execution dates for the sub-activities to be performed in order to complete the project. The ability to manage projects where resources must be allocated between concurrent projects or even sub-activities of a single project requires the use of commercial project management software packages. However, the results yielded by the solution procedures included are often rather unsatisfactory. Scheduling of Resource-Constrained Projects develops more efficient procedures, which can easily be integrated into software packages by incorporated programming languages, and thus should be of great interest for practiti...
Constrained mathematics evaluation in probabilistic logic analysis
Arlin Cooper, J
1998-06-01
A challenging problem in mathematically processing uncertain operands is that constraints inherent in the problem definition can require computations that are difficult to implement. Examples of possible constraints are that the sum of the probabilities of partitioned possible outcomes must be one, and repeated appearances of the same variable must all have the identical value. The latter, called the 'repeated variable problem', will be addressed in this paper in order to show how interval-based probabilistic evaluation of Boolean logic expressions, such as those describing the outcomes of fault trees and event trees, can be facilitated in a way that can be readily implemented in software. We will illustrate techniques that can be used to transform complex constrained problems into trivial problems in most tree logic expressions, and into tractable problems in most other cases.
Constraining dark sectors with monojets and dijets
Chala, Mikael; Kahlhoefer, Felix; Nardini, Germano; Schmidt-Hoberg, Kai; McCullough, Matthew
2015-03-01
We consider dark sector particles (DSPs) that obtain sizeable interactions with Standard Model fermions from a new mediator. While these particles can avoid observation in direct detection experiments, they are strongly constrained by LHC measurements. We demonstrate that there is an important complementarity between searches for DSP production and searches for the mediator itself, in particular bounds on (broad) dijet resonances. This observation is crucial not only in the case where the DSP is all of the dark matter but whenever - precisely due to its sizeable interactions with the visible sector - the DSP annihilates away so efficiently that it only forms a dark matter subcomponent. To highlight the different roles of DSP direct detection and LHC monojet and dijet searches, as well as perturbativity constraints, we first analyse the exemplary case of an axial-vector mediator and then generalise our results. We find important implications for the interpretation of LHC dark matter searches in terms of simplified models.
Quantum cosmology of classically constrained gravity
Gabadadze, Gregory; Shang Yanwen
2006-01-01
In [G. Gabadadze, Y. Shang, hep-th/0506040] we discussed a classically constrained model of gravity. This theory contains known solutions of General Relativity (GR), and admits solutions that are absent in GR. Here we study cosmological implications of some of these new solutions. We show that a spatially-flat de Sitter universe can be created from 'nothing'. This universe has boundaries, and its total energy equals to zero. Although the probability to create such a universe is exponentially suppressed, it favors initial conditions suitable for inflation. Then we discuss a finite-energy solution with a nonzero cosmological constant and zero space-time curvature. There is no tunneling suppression to fluctuate into this state. We show that for a positive cosmological constant this state is unstable-it can rapidly transition to a de Sitter universe providing a new unsuppressed channel for inflation. For a negative cosmological constant the space-time flat solutions is stable.
Multiple Clustering Views via Constrained Projections
Dang, Xuan-Hong; Assent, Ira; Bailey, James
2012-01-01
Clustering, the grouping of data based on mutual similarity, is often used as one of principal tools to analyze and understand data. Unfortunately, most conventional techniques aim at finding only a single clustering over the data. For many practical applications, especially those being described...... in high dimensional data, it is common to see that the data can be grouped into different yet meaningful ways. This gives rise to the recently emerging research area of discovering alternative clusterings. In this preliminary work, we propose a novel framework to generate multiple clustering views....... The framework relies on a constrained data projection approach by which we ensure that a novel alternative clustering being found is not only qualitatively strong but also distinctively different from a reference clustering solution. We demonstrate the potential of the proposed framework using both synthetic...
Shape space exploration of constrained meshes
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.
Shape space exploration of constrained meshes
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.
Constrained vertebrate evolution by pleiotropic genes.
Hu, Haiyang; Uesaka, Masahiro; Guo, Song; Shimai, Kotaro; Lu, Tsai-Ming; Li, Fang; Fujimoto, Satoko; Ishikawa, Masato; Liu, Shiping; Sasagawa, Yohei; Zhang, Guojie; Kuratani, Shigeru; Yu, Jr-Kai; Kusakabe, Takehiro G; Khaitovich, Philipp; Irie, Naoki
2017-11-01
Despite morphological diversification of chordates over 550 million years of evolution, their shared basic anatomical pattern (or 'bodyplan') remains conserved by unknown mechanisms. The developmental hourglass model attributes this to phylum-wide conserved, constrained organogenesis stages that pattern the bodyplan (the phylotype hypothesis); however, there has been no quantitative testing of this idea with a phylum-wide comparison of species. Here, based on data from early-to-late embryonic transcriptomes collected from eight chordates, we suggest that the phylotype hypothesis would be better applied to vertebrates than chordates. Furthermore, we found that vertebrates' conserved mid-embryonic developmental programmes are intensively recruited to other developmental processes, and the degree of the recruitment positively correlates with their evolutionary conservation and essentiality for normal development. Thus, we propose that the intensively recruited genetic system during vertebrates' organogenesis period imposed constraints on its diversification through pleiotropic constraints, which ultimately led to the common anatomical pattern observed in vertebrates.
Constraining Dark Sectors with Monojets and Dijets
Chala, Mikael; McCullough, Matthew; Nardini, Germano; Schmidt-Hoberg, Kai
2015-01-01
We consider dark sector particles (DSPs) that obtain sizeable interactions with Standard Model fermions from a new mediator. While these particles can avoid observation in direct detection experiments, they are strongly constrained by LHC measurements. We demonstrate that there is an important complementarity between searches for DSP production and searches for the mediator itself, in particular bounds on (broad) dijet resonances. This observation is crucial not only in the case where the DSP is all of the dark matter but whenever - precisely due to its sizeable interactions with the visible sector - the DSP annihilates away so efficiently that it only forms a dark matter subcomponent. To highlight the different roles of DSP direct detection and LHC monojet and dijet searches, as well as perturbativity constraints, we first analyse the exemplary case of an axial-vector mediator and then generalise our results. We find important implications for the interpretation of LHC dark matter searches in terms of simpli...
Constraining dark sectors with monojets and dijets
Chala, Mikael; Kahlhoefer, Felix; Nardini, Germano; Schmidt-Hoberg, Kai [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); McCullough, Matthew [European Organization for Nuclear Research (CERN), Geneva (Switzerland). Theory Div.
2015-03-15
We consider dark sector particles (DSPs) that obtain sizeable interactions with Standard Model fermions from a new mediator. While these particles can avoid observation in direct detection experiments, they are strongly constrained by LHC measurements. We demonstrate that there is an important complementarity between searches for DSP production and searches for the mediator itself, in particular bounds on (broad) dijet resonances. This observation is crucial not only in the case where the DSP is all of the dark matter but whenever - precisely due to its sizeable interactions with the visible sector - the DSP annihilates away so efficiently that it only forms a dark matter subcomponent. To highlight the different roles of DSP direct detection and LHC monojet and dijet searches, as well as perturbativity constraints, we first analyse the exemplary case of an axial-vector mediator and then generalise our results. We find important implications for the interpretation of LHC dark matter searches in terms of simplified models.
Constraining the dark side with observations
Diez-Tejedor, Alberto
2007-01-01
The main purpose of this talk is to use the observational evidences pointing out to the existence of a dark side in the universe in order to infer some of the properties of the unseen material. We will work within the Unified Dark Matter models, in which both, Dark Matter and Dark Energy appear as the result of one unknown component. By modeling effectively this component with a classical scalar field minimally coupled to gravity, we will use the observations to constrain the form of the dark action. Using the flat rotation curves of spiral galaxies we will see that we are restringed to the use of purely kinetic actions, previously studied in cosmology by Scherrer. Finally we arrive to a simple action which fits both cosmological and astrophysical observations
Constraining the dark side with observations
Diez-Tejedor, Alberto [Dpto. de Fisica Teorica, Universidad del PaIs Vasco, Apdo. 644, 48080, Bilbao (Spain)
2007-05-15
The main purpose of this talk is to use the observational evidences pointing out to the existence of a dark side in the universe in order to infer some of the properties of the unseen material. We will work within the Unified Dark Matter models, in which both, Dark Matter and Dark Energy appear as the result of one unknown component. By modeling effectively this component with a classical scalar field minimally coupled to gravity, we will use the observations to constrain the form of the dark action. Using the flat rotation curves of spiral galaxies we will see that we are restringed to the use of purely kinetic actions, previously studied in cosmology by Scherrer. Finally we arrive to a simple action which fits both cosmological and astrophysical observations.
Hard exclusive meson production to constrain GPDs
Wolbeek, Johannes ter; Fischer, Horst; Gorzellik, Matthias; Gross, Arne; Joerg, Philipp; Koenigsmann, Kay; Malm, Pasquale; Regali, Christopher; Schmidt, Katharina; Sirtl, Stefan; Szameitat, Tobias [Physikalisches Institut, Albert-Ludwigs-Universitaet Freiburg, Freiburg im Breisgau (Germany); Collaboration: COMPASS Collaboration
2014-07-01
The concept of Generalized Parton Distributions (GPDs) combines the two-dimensional spatial information, given by form factors, with the longitudinal momentum information from the PDFs. Thus, GPDs provide a three-dimensional 'tomography' of the nucleon. Furthermore, according to Ji's sum rule, the GPDs H and E enable access to the total angular momenta of quarks, antiquarks and gluons. While H can be approached using electroproduction cross section, hard exclusive meson production off a transversely polarized target can help to constrain the GPD E. At the COMPASS experiment at CERN, two periods of data taking were performed in 2007 and 2010, using a longitudinally polarized 160 GeV/c muon beam and a transversely polarized NH{sub 3} target. This talk introduces the data analysis of the process μ + p → μ' + p' + V, and recent results are presented.
Metal artifact reduction in x-ray computed tomography (CT) by constrained optimization
Zhang Xiaomeng; Wang Jing; Xing Lei
2011-01-01
Purpose: The streak artifacts caused by metal implants have long been recognized as a problem that limits various applications of CT imaging. In this work, the authors propose an iterative metal artifact reduction algorithm based on constrained optimization. Methods: After the shape and location of metal objects in the image domain is determined automatically by the binary metal identification algorithm and the segmentation of ''metal shadows'' in projection domain is done, constrained optimization is used for image reconstruction. It minimizes a predefined function that reflects a priori knowledge of the image, subject to the constraint that the estimated projection data are within a specified tolerance of the available metal-shadow-excluded projection data, with image non-negativity enforced. The minimization problem is solved through the alternation of projection-onto-convex-sets and the steepest gradient descent of the objective function. The constrained optimization algorithm is evaluated with a penalized smoothness objective. Results: The study shows that the proposed method is capable of significantly reducing metal artifacts, suppressing noise, and improving soft-tissue visibility. It outperforms the FBP-type methods and ART and EM methods and yields artifacts-free images. Conclusions: Constrained optimization is an effective way to deal with CT reconstruction with embedded metal objects. Although the method is presented in the context of metal artifacts, it is applicable to general ''missing data'' image reconstruction problems.
Constraining the volatile fraction of planets from transit observations
Alibert, Y.
2016-06-01
Context. The determination of the abundance of volatiles in extrasolar planets is very important as it can provide constraints on transport in protoplanetary disks and on the formation location of planets. However, constraining the internal structure of low-mass planets from transit measurements is known to be a degenerate problem. Aims: Using planetary structure and evolution models, we show how observations of transiting planets can be used to constrain their internal composition, in particular the amount of volatiles in the planetary interior, and consequently the amount of gas (defined in this paper to be only H and He) that the planet harbors. We first explore planets that are located close enough to their star to have lost their gas envelope. We then concentrate on planets at larger distances and show that the observation of transiting planets at different evolutionary ages can provide statistical information on their internal composition, in particular on their volatile fraction. Methods: We computed the evolution of low-mass planets (super-Earths to Neptune-like) for different fractions of volatiles and gas. We used a four-layer model (core, silicate mantle, icy mantle, and gas envelope) and computed the internal structure of planets for different luminosities. With this internal structure model, we computed the internal and gravitational energy of planets, which was then used to derive the time evolution of the planet. Since the total energy of a planet depends on its heat capacity and density distribution and therefore on its composition, planets with different ice fractions have different evolution tracks. Results: We show for low-mass gas-poor planets that are located close to their central star that assuming evaporation has efficiently removed the entire gas envelope, it is possible to constrain the volatile fraction of close-in transiting planets. We illustrate this method on the example of 55 Cnc e and show that under the assumption of the absence of
Weighted -Integral Representations of -Functions in
Arman H. Karapetyan
2012-01-01
Full Text Available For 1-functions , given in the complex space , integral representations of the form =(−( are obtained. Here, is the orthogonal projector of the space 2{;−||||(} onto its subspace of entire functions and the integral operator appears by means of explicitly constructed kernel Φ which is investigated in detail.
Assessment of oscillatory stability constrained available transfer capability
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)
Optimal dispatch in dynamic security constrained open power market
Singh, S.N.; David, A.K.
2002-01-01
Power system security is a new concern in the competitive power market operation, because the integration of the system controller and the generation owner has been broken. This paper presents an approach for dynamic security constrained optimal dispatch in restructured power market environment. The transient energy margin using transient energy function (TEF) approach has been used to calculate the stability margin of the system and a hybrid method is applied to calculate the approximate unstable equilibrium point (UEP) that is used to calculate the exact UEP and thus, the energy margin using TEF. The case study results illustrated on two systems shows that the operating mechanisms are compatible with the new business environment. (author)
Stall Recovery Guidance Algorithms Based on Constrained Control Approaches
Stepanyan, Vahram; Krishnakumar, Kalmanje; Kaneshige, John; Acosta, Diana
2016-01-01
Aircraft loss-of-control, in particular approach to stall or fully developed stall, is a major factor contributing to aircraft safety risks, which emphasizes the need to develop algorithms that are capable of assisting the pilots to identify the problem and providing guidance to recover the aircraft. In this paper we present several stall recovery guidance algorithms, which are implemented in the background without interfering with flight control system and altering the pilot's actions. They are using input and state constrained control methods to generate guidance signals, which are provided to the pilot in the form of visual cues. It is the pilot's decision to follow these signals. The algorithms are validated in the pilot-in-the loop medium fidelity simulation experiment.
Rejane Joas Silveira
2002-04-01
Full Text Available Neste artigo estudamos um caso particular dos problemas de corte, denominado problema bidimensional guilhotinado restrito (PGR. O PGR é um problema NP-difícil que aparece em diversos processos industriais de corte de chapas retangulares, em particular, na indústria de vidro e placas de circuito impresso. Para resolvê-lo, exploramos uma variação do método exato de CHRISTOFIDES & HADJICONSTANTINOU (1995, baseada numa relaxação do espaço de estados de uma formulação de programação dinâmica do PGR, num procedimento do tipo otimização do subgradiente, e numa heurística de factibilização. O resultado é um método sem garantia de otimalidade, porém bem mais rápido e capaz de resolver problemas maiores do que o método exato de Christofides e Hadjiconstantinou. O desempenho computacional do método é avaliado resolvendo-se diversos exemplos da literatura e exemplos aleatórios, e comparando-se as soluções obtidas com as de CHRISTOFIDES & HADJICONSTANTINOU (1995 e da conhecida heurística de WANG (1983.In this paper we study a particular case of two-dimensional cutting problems named constrained guillotine cutting (CGC. The CGC is an NP-hard problem that appears in different industrial processes of cutting rectangular plates, such as in the glass and circuit board industries. To solve the problem we present a variation of the exact method of CHRISTOFIDES & HADJICONSTANTINOU (1995, based on a state space relaxation of a dynamic programming formulation of the CGC, a procedure of subgradient optimization type, and a feasibility heuristic. The result is a method without guarantee of optimality, however, faster and able to solve larger problems than the exact method of Christofides and Hadjiconstantinou. The computational performance of the approach is evaluated solving several examples of the literature as well as randomly generated examples, and comparing the solutions obtained with the ones of Christofides and Hadjiconstantinou
Volume-constrained optimization of magnetorheological and electrorheological valves and dampers
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.
Cooke, Christopher C; Hozack, William; Lavernia, Carlos; Sharkey, Peter; Shastri, Shani; Rothman, Richard H
2003-10-01
Fifty-eight patients received an Osteonics constrained acetabular implant for recurrent instability (46), girdlestone reimplant (8), correction of leg lengthening (3), and periprosthetic fracture (1). The constrained liner was inserted into a cementless shell (49), cemented into a pre-existing cementless shell (6), cemented into a cage (2), and cemented directly into the acetabular bone (1). Eight patients (13.8%) required reoperation for failure of the constrained implant. Type I failure (bone-prosthesis interface) occurred in 3 cases. Two cementless shells became loose, and in 1 patient, the constrained liner was cemented into an acetabular cage, which then failed by pivoting laterally about the superior fixation screws. Type II failure (liner locking mechanism) occurred in 2 cases. Type III failure (femoral head locking mechanism) occurred in 3 patients. Seven of the 8 failures occurred in patients with recurrent instability. Constrained liners are an effective method for treatment during revision total hip arthroplasty but should be used in select cases only.
A One-Layer Recurrent Neural Network for Constrained Complex-Variable Convex Optimization.
Qin, Sitian; Feng, Jiqiang; Song, Jiahui; Wen, Xingnan; Xu, Chen
2018-03-01
In this paper, based on calculus and penalty method, a one-layer recurrent neural network is proposed for solving constrained complex-variable convex optimization. It is proved that for any initial point from a given domain, the state of the proposed neural network reaches the feasible region in finite time and converges to an optimal solution of the constrained complex-variable convex optimization finally. In contrast to existing neural networks for complex-variable convex optimization, the proposed neural network has a lower model complexity and better convergence. Some numerical examples and application are presented to substantiate the effectiveness of the proposed neural network.
Changes of gait parameters following constrained-weight shift training in patients with stroke
Nam, Seok Hyun; Son, Sung Min; Kim, Kyoung
2017-01-01
[Purpose] This study aimed to investigate the effects of training involving compelled weight shift on the paretic lower limb on gait parameters and plantar pressure distribution in patients with stroke. [Subjects and Methods] Forty-five stroke patients participated in the study and were randomly divided into: group with a 5-mm lift on the non-paretic side for constrained weight shift training (5: constrained weight shift training) (n=15); group with a 10-mm lift on the non-paretic side for co...
HotpathVM: An Effective JIT for Resource-constrained Devices
Gal, Andreas; Franz, Michael; Probst, Christian
2006-01-01
We present a just-in-time compiler for a Java VM that is small enough to fit on resource-constrained devices, yet surprisingly effective. Our system dynamically identifies traces of frequently executed bytecode instructions (which may span several basic blocks across several methods) and compiles...
Minimizers of a Class of Constrained Vectorial Variational Problems: Part I
Hajaiej, Hichem
2014-04-18
In this paper, we prove the existence of minimizers of a class of multiconstrained variational problems. We consider systems involving a nonlinearity that does not satisfy compactness, monotonicity, neither symmetry properties. Our approach hinges on the concentration-compactness approach. In the second part, we will treat orthogonal constrained problems for another class of integrands using density matrices method. © 2014 Springer Basel.
Mixed Integer PDE Constrained Optimization for the Control of a Wildfire Hazard
2017-01-01
Constrained Optimization for the Control of a Wildfire Hazard Herausgegeben von der Professor fur Angewandte Mathematik Professor Dr. rer. nat. Armin...and H.H. Tan . Finite difference methods for solving the two-dimensional advection-diffusion equation. Int. J. Numer. Meth. Fluids, 9:75-98, 1989. 6
Liu, Zhaoxi; Wu, Qiuwei; Oren, Shmuel S.
2017-01-01
This paper presents a distribution locational marginal pricing (DLMP) method through chance constrained mixed-integer programming designed to alleviate the possible congestion in the future distribution network with high penetration of electric vehicles (EVs). In order to represent the stochastic...
k-t PCA: temporally constrained k-t BLAST reconstruction using principal component analysis
Pedersen, Henrik; Kozerke, Sebastian; Ringgaard, Steffen
2009-01-01
in applications exhibiting a broad range of temporal frequencies such as free-breathing myocardial perfusion imaging. We show that temporal basis functions calculated by subjecting the training data to principal component analysis (PCA) can be used to constrain the reconstruction such that the temporal resolution...... is improved. The presented method is called k-t PCA....
Robust Layout Synthesis of a MEM Crab-Leg Resonator Using a Constrained Genetic Algorithm
Fan, Zhun; Achiche, Sofiane
2007-01-01
The research work carried out in this paper introduces a robust design method for layout synthesis of MEM resonator subject to inherent geometric uncertainties such as the fabrication error on the sidewall of the structure. The robust design problem is formulated as a multi-objective constrained...
Path-Constrained Motion Planning for Robotics Based on Kinematic Constraints
Dijk, van N.J.M.; Wouw, van de N.; Pancras, W.C.M.; Nijmeijer, H.
2007-01-01
Common robotic tracking tasks consist of motions along predefined paths. The design of time-optimal path-constrained trajectories for robotic applications is discussed in this paper. To increase industrial applicability, the proposed method accounts for robot kinematics together with actuator
Constraining the magnitude of the largest event in a foreshock-main shock-aftershock sequence
Shcherbakov, Robert; Zhuang, Jiancang; Ogata, Yosihiko
2018-01-01
Extreme value statistics and Bayesian methods are used to constrain the magnitudes of the largest expected earthquakes in a sequence governed by the parametric time-dependent occurrence rate and frequency-magnitude statistics. The Bayesian predictive distribution for the magnitude of the largest event in a sequence is derived. Two types of sequences are considered, that is, the classical aftershock sequences generated by large main shocks and the aftershocks generated by large foreshocks preceding a main shock. For the former sequences, the early aftershocks during a training time interval are used to constrain the magnitude of the future extreme event during the forecasting time interval. For the latter sequences, the earthquakes preceding the main shock are used to constrain the magnitudes of the subsequent extreme events including the main shock. The analysis is applied retrospectively to past prominent earthquake sequences.
Mesh dependence in PDE-constrained optimisation an application in tidal turbine array layouts
Schwedes, Tobias; Funke, Simon W; Piggott, Matthew D
2017-01-01
This book provides an introduction to PDE-constrained optimisation using finite elements and the adjoint approach. The practical impact of the mathematical insights presented here are demonstrated using the realistic scenario of the optimal placement of marine power turbines, thereby illustrating the real-world relevance of best-practice Hilbert space aware approaches to PDE-constrained optimisation problems. Many optimisation problems that arise in a real-world context are constrained by partial differential equations (PDEs). That is, the system whose configuration is to be optimised follows physical laws given by PDEs. This book describes general Hilbert space formulations of optimisation algorithms, thereby facilitating optimisations whose controls are functions of space. It demonstrates the importance of methods that respect the Hilbert space structure of the problem by analysing the mathematical drawbacks of failing to do so. The approaches considered are illustrated using the optimisation problem arisin...
Explaining evolution via constrained persistent perfect phylogeny
2014-01-01
Background The perfect phylogeny is an often used model in phylogenetics since it provides an efficient basic procedure for representing the evolution of genomic binary characters in several frameworks, such as for example in haplotype inference. The model, which is conceptually the simplest, is based on the infinite sites assumption, that is no character can mutate more than once in the whole tree. A main open problem regarding the model is finding generalizations that retain the computational tractability of the original model but are more flexible in modeling biological data when the infinite site assumption is violated because of e.g. back mutations. A special case of back mutations that has been considered in the study of the evolution of protein domains (where a domain is acquired and then lost) is persistency, that is the fact that a character is allowed to return back to the ancestral state. In this model characters can be gained and lost at most once. In this paper we consider the computational problem of explaining binary data by the Persistent Perfect Phylogeny model (referred as PPP) and for this purpose we investigate the problem of reconstructing an evolution where some constraints are imposed on the paths of the tree. Results We define a natural generalization of the PPP problem obtained by requiring that for some pairs (character, species), neither the species nor any of its ancestors can have the character. In other words, some characters cannot be persistent for some species. This new problem is called Constrained PPP (CPPP). Based on a graph formulation of the CPPP problem, we are able to provide a polynomial time solution for the CPPP problem for matrices whose conflict graph has no edges. Using this result, we develop a parameterized algorithm for solving the CPPP problem where the parameter is the number of characters. Conclusions A preliminary experimental analysis shows that the constrained persistent perfect phylogeny model allows to
Constrained Sypersymmetric Flipped SU (5) GUT Phenomenology
Ellis, John; /CERN /King' s Coll. London; Mustafayev, Azar; /Minnesota U., Theor. Phys. Inst.; Olive, Keith A.; /Minnesota U., Theor. Phys. Inst. /Minnesota U. /Stanford U., Phys. Dept. /SLAC
2011-08-12
We explore the phenomenology of the minimal supersymmetric flipped SU(5) GUT model (CFSU(5)), whose soft supersymmetry-breaking (SSB) mass parameters are constrained to be universal at some input scale, Min, above the GUT scale, M{sub GUT}. We analyze the parameter space of CFSU(5) assuming that the lightest supersymmetric particle (LSP) provides the cosmological cold dark matter, paying careful attention to the matching of parameters at the GUT scale. We first display some specific examples of the evolutions of the SSB parameters that exhibit some generic features. Specifically, we note that the relationship between the masses of the lightest neutralino {chi} and the lighter stau {tilde {tau}}{sub 1} is sensitive to M{sub in}, as is the relationship between m{sub {chi}} and the masses of the heavier Higgs bosons A,H. For these reasons, prominent features in generic (m{sub 1/2}, m{sub 0}) planes such as coannihilation strips and rapid-annihilation funnels are also sensitive to Min, as we illustrate for several cases with tan {beta} = 10 and 55. However, these features do not necessarily disappear at large Min, unlike the case in the minimal conventional SU(5) GUT. Our results are relatively insensitive to neutrino masses.
Constrained supersymmetric flipped SU(5) GUT phenomenology
Ellis, John [CERN, TH Division, PH Department, Geneva 23 (Switzerland); King' s College London, Theoretical Physics and Cosmology Group, Department of Physics, London (United Kingdom); Mustafayev, Azar [University of Minnesota, William I. Fine Theoretical Physics Institute, Minneapolis, MN (United States); Olive, Keith A. [University of Minnesota, William I. Fine Theoretical Physics Institute, Minneapolis, MN (United States); Stanford University, Department of Physics and SLAC, Palo Alto, CA (United States)
2011-07-15
We explore the phenomenology of the minimal supersymmetric flipped SU(5) GUT model (CFSU(5)), whose soft supersymmetry-breaking (SSB) mass parameters are constrained to be universal at some input scale, M{sub in}, above the GUT scale, M{sub GUT}. We analyze the parameter space of CFSU(5) assuming that the lightest supersymmetric particle (LSP) provides the cosmological cold dark matter, paying careful attention to the matching of parameters at the GUT scale. We first display some specific examples of the evolutions of the SSB parameters that exhibit some generic features. Specifically, we note that the relationship between the masses of the lightest neutralino {chi} and the lighter stau {tau}{sub 1} is sensitive to M{sub in}, as is the relationship between m{sub {chi}} and the masses of the heavier Higgs bosons A,H. For these reasons, prominent features in generic (m{sub 1/2},m{sub 0}) planes such as coannihilation strips and rapid-annihilation funnels are also sensitive to M{sub in}, as we illustrate for several cases with tan {beta}=10 and 55. However, these features do not necessarily disappear at large M{sub in}, unlike the case in the minimal conventional SU(5) GUT. Our results are relatively insensitive to neutrino masses. (orig.)
Joint Chance-Constrained Dynamic Programming
Ono, Masahiro; Kuwata, Yoshiaki; Balaram, J. Bob
2012-01-01
This paper presents a novel dynamic programming algorithm with a joint chance constraint, which explicitly bounds the risk of failure in order to maintain the state within a specified feasible region. A joint chance constraint cannot be handled by existing constrained dynamic programming approaches since their application is limited to constraints in the same form as the cost function, that is, an expectation over a sum of one-stage costs. We overcome this challenge by reformulating the joint chance constraint into a constraint on an expectation over a sum of indicator functions, which can be incorporated into the cost function by dualizing the optimization problem. As a result, the primal variables can be optimized by a standard dynamic programming, while the dual variable is optimized by a root-finding algorithm that converges exponentially. Error bounds on the primal and dual objective values are rigorously derived. We demonstrate the algorithm on a path planning problem, as well as an optimal control problem for Mars entry, descent and landing. The simulations are conducted using a real terrain data of Mars, with four million discrete states at each time step.
Technologies for a greenhouse-constrained society
Kuliasha, M.A.; Zucker, A.; Ballew, K.J.
1992-01-01
This conference explored how three technologies might help society adjust to life in a greenhouse-constrained environment. Technology experts and policy makers from around the world met June 11--13, 1991, in Oak Ridge, Tennessee, to address questions about how energy efficiency, biomass, and nuclear technologies can mitigate the greenhouse effect and to explore energy production and use in countries in various stages of development. The conference was organized by Oak Ridge National Laboratory and sponsored by the US Department of Energy. Energy efficiency biomass, and nuclear energy are potential substitutes for fossil fuels that might help slow or even reverse the global warming changes that may result from mankind's thirst for energy. Many other conferences have questioned whether the greenhouse effect is real and what reductions in greenhouse gas emissions might be necessary to avoid serious ecological consequences; this conference studied how these reductions might actually be achieved. For these conference proceedings, individuals papers are processed separately for the Energy Data Base
Constrained Supersymmetric Flipped SU(5) GUT Phenomenology
Ellis, John; Olive, Keith A
2011-01-01
We explore the phenomenology of the minimal supersymmetric flipped SU(5) GUT model (CFSU(5)), whose soft supersymmetry-breaking (SSB) mass parameters are constrained to be universal at some input scale, $M_{in}$, above the GUT scale, $M_{GUT}$. We analyze the parameter space of CFSU(5) assuming that the lightest supersymmetric particle (LSP) provides the cosmological cold dark matter, paying careful attention to the matching of parameters at the GUT scale. We first display some specific examples of the evolutions of the SSB parameters that exhibit some generic features. Specifically, we note that the relationship between the masses of the lightest neutralino and the lighter stau is sensitive to $M_{in}$, as is the relationship between the neutralino mass and the masses of the heavier Higgs bosons. For these reasons, prominent features in generic $(m_{1/2}, m_0)$ planes such as coannihilation strips and rapid-annihilation funnels are also sensitive to $M_{in}$, as we illustrate for several cases with tan(beta)...
Constrained supersymmetric flipped SU(5) GUT phenomenology
Ellis, John; Mustafayev, Azar; Olive, Keith A.
2011-01-01
We explore the phenomenology of the minimal supersymmetric flipped SU(5) GUT model (CFSU(5)), whose soft supersymmetry-breaking (SSB) mass parameters are constrained to be universal at some input scale, M in , above the GUT scale, M GUT . We analyze the parameter space of CFSU(5) assuming that the lightest supersymmetric particle (LSP) provides the cosmological cold dark matter, paying careful attention to the matching of parameters at the GUT scale. We first display some specific examples of the evolutions of the SSB parameters that exhibit some generic features. Specifically, we note that the relationship between the masses of the lightest neutralino χ and the lighter stau τ 1 is sensitive to M in , as is the relationship between m χ and the masses of the heavier Higgs bosons A,H. For these reasons, prominent features in generic (m 1/2 ,m 0 ) planes such as coannihilation strips and rapid-annihilation funnels are also sensitive to M in , as we illustrate for several cases with tan β=10 and 55. However, these features do not necessarily disappear at large M in , unlike the case in the minimal conventional SU(5) GUT. Our results are relatively insensitive to neutrino masses. (orig.)
Should we still believe in constrained supersymmetry?
Balazs, Csaba; Buckley, Andy; Carter, Daniel; Farmer, Benjamin; White, Martin
2013-01-01
We calculate partial Bayes factors to quantify how the feasibility of the constrained minimal supersymmetric standard model (CMSSM) has changed in the light of a series of observations. This is done in the Bayesian spirit where probability reflects a degree of belief in a proposition and Bayes' theorem tells us how to update it after acquiring new information. Our experimental baseline is the approximate knowledge that was available before LEP, and our comparison model is the Standard Model with a simple dark matter candidate. To quantify the amount by which experiments have altered our relative belief in the CMSSM since the baseline data we compute the partial Bayes factors that arise from learning in sequence the LEP Higgs constraints, the XENON100 dark matter constraints, the 2011 LHC supersymmetry search results, and the early 2012 LHC Higgs search results. We find that LEP and the LHC strongly shatter our trust in the CMSSM (with M 0 and M 1/2 below 2 TeV), reducing its posterior odds by approximately two orders of magnitude. This reduction is largely due to substantial Occam factors induced by the LEP and LHC Higgs searches. (orig.)
Electricity in a Climate-Constrained World
NONE
2012-07-01
After experiencing a historic drop in 2009, electricity generation reached a record high in 2010, confirming the close linkage between economic growth and electricity usage. Unfortunately, CO2 emissions from electricity have also resumed their growth: Electricity remains the single-largest source of CO2 emissions from energy, with 11.7 billion tonnes of CO2 released in 2010. The imperative to 'decarbonise' electricity and improve end-use efficiency remains essential to the global fight against climate change. The IEA’s Electricity in a Climate-Constrained World provides an authoritative resource on progress to date in this area, including statistics related to CO2 and the electricity sector across ten regions of the world (supply, end-use and capacity additions). It also presents topical analyses on the challenge of rapidly curbing CO2 emissions from electricity. Looking at policy instruments, it focuses on emissions trading in China, using energy efficiency to manage electricity supply crises and combining policy instruments for effective CO2 reductions. On regulatory issues, it asks whether deregulation can deliver decarbonisation and assesses the role of state-owned enterprises in emerging economies. And from technology perspectives, it explores the rise of new end-uses, the role of electricity storage, biomass use in Brazil, and the potential of carbon capture and storage for ‘negative emissions’ electricity supply.
A discretized algorithm for the solution of a constrained, continuous ...
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 ...
I/O-Efficient Construction of Constrained Delaunay Triangulations
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...
Fast optimization of statistical potentials for structurally constrained phylogenetic models
Rodrigue Nicolas
2009-09-01
Full Text Available Abstract Background Statistical approaches for protein design are relevant in the field of molecular evolutionary studies. In recent years, new, so-called structurally constrained (SC models of protein-coding sequence evolution have been proposed, which use statistical potentials to assess sequence-structure compatibility. In a previous work, we defined a statistical framework for optimizing knowledge-based potentials especially suited to SC models. Our method used the maximum likelihood principle and provided what we call the joint potentials. However, the method required numerical estimations by the use of computationally heavy Markov Chain Monte Carlo sampling algorithms. Results Here, we develop an alternative optimization procedure, based on a leave-one-out argument coupled to fast gradient descent algorithms. We assess that the leave-one-out potential yields very similar results to the joint approach developed previously, both in terms of the resulting potential parameters, and by Bayes factor evaluation in a phylogenetic context. On the other hand, the leave-one-out approach results in a considerable computational benefit (up to a 1,000 fold decrease in computational time for the optimization procedure. Conclusion Due to its computational speed, the optimization method we propose offers an attractive alternative for the design and empirical evaluation of alternative forms of potentials, using large data sets and high-dimensional parameterizations.
Quasi-Newton Exploration of Implicitly Constrained Manifolds
Tang, Chengcheng
2011-08-01
A family of methods for the efficient update of second order approximations of a constraint manifold is proposed in this thesis. The concept of such a constraint manifold corresponds to an abstract space prescribed by implicit nonlinear constraints, which can be a set of objects satisfying certain desired properties. This concept has a variety of applications, and it has been successfully introduced to fabrication-aware architectural design as a shape space consisting of all the implementable designs. The local approximation of such a manifold can be first order, in the tangent space, or second order, in the osculating surface, with higher precision. For a nonlinearly constrained manifold with rather high dimension and codimension, the computation of second order approximants (osculants) is time consuming. In this thesis, a type of so-called quasi-Newton manifold exploration methods which approximate the new osculants by updating the ones of a neighbor point by 1st-order information is introduced. The procedures are discussed in detail and the examples implemented to visually verify the methods are illustrated.
Tongue Images Classification Based on Constrained High Dispersal Network
Dan Meng
2017-01-01
Full Text Available Computer aided tongue diagnosis has a great potential to play important roles in traditional Chinese medicine (TCM. However, the majority of the existing tongue image analyses and classification methods are based on the low-level features, which may not provide a holistic view of the tongue. Inspired by deep convolutional neural network (CNN, we propose a novel feature extraction framework called constrained high dispersal neural networks (CHDNet to extract unbiased features and reduce human labor for tongue diagnosis in TCM. Previous CNN models have mostly focused on learning convolutional filters and adapting weights between them, but these models have two major issues: redundancy and insufficient capability in handling unbalanced sample distribution. We introduce high dispersal and local response normalization operation to address the issue of redundancy. We also add multiscale feature analysis to avoid the problem of sensitivity to deformation. Our proposed CHDNet learns high-level features and provides more classification information during training time, which may result in higher accuracy when predicting testing samples. We tested the proposed method on a set of 267 gastritis patients and a control group of 48 healthy volunteers. Test results show that CHDNet is a promising method in tongue image classification for the TCM study.
Sparse/Low Rank Constrained Reconstruction for Dynamic PET Imaging.
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.
Regional Responses to Constrained Water Availability
Cui, Y.; Calvin, K. V.; Hejazi, M. I.; Clarke, L.; Kim, S. H.; Patel, P.
2017-12-01
There have been many concerns about water as a constraint to agricultural production, electricity generation, and many other human activities in the coming decades. Nevertheless, how different countries/economies would respond to such constraints has not been explored. Here, we examine the responding mechanism of binding water availability constraints at the water basin level and across a wide range of socioeconomic, climate and energy technology scenarios. Specifically, we look at the change in water withdrawals between energy, land-use and other sectors within an integrated framework, by using the Global Change Assessment Model (GCAM) that also endogenizes water use and allocation decisions based on costs. We find that, when water is taken into account as part of the production decision-making, countries/basins in general fall into three different categories, depending on the change of water withdrawals and water re-allocation between sectors. First, water is not a constraining factor for most of the basins. Second, advancements in water-saving technologies of the electricity generation cooling systems are sufficient of reducing water withdrawals to meet binding water availability constraints, such as in China and the EU-15. Third, water-saving in the electricity sector alone is not sufficient and thus cannot make up the lowered water availability from the binding case; for example, many basins in Pakistan, Middle East and India have to largely reduce irrigated water withdrawals by either switching to rain-fed agriculture or reducing production. The dominant responding strategy for individual countries/basins is quite robust across the range of alternate scenarios that we test. The relative size of water withdrawals between energy and agriculture sectors is one of the most important factors that affect the dominant mechanism.
Constraining Cosmic Evolution of Type Ia Supernovae
Foley, Ryan J.; Filippenko, Alexei V.; Aguilera, C.; Becker, A.C.; Blondin, S.; Challis, P.; Clocchiatti, A.; Covarrubias, R.; Davis, T.M.; Garnavich, P.M.; Jha, S.; Kirshner, R.P.; Krisciunas, K.; Leibundgut, B.; Li, W.; Matheson, T.; Miceli, A.; Miknaitis, G.; Pignata, G.; Rest, A.; Riess, A.G.; /UC, Berkeley, Astron. Dept. /Cerro-Tololo InterAmerican Obs. /Washington U., Seattle, Astron. Dept. /Harvard-Smithsonian Ctr. Astrophys. /Chile U., Catolica /Bohr Inst. /Notre Dame U. /KIPAC, Menlo Park /Texas A-M /European Southern Observ. /NOAO, Tucson /Fermilab /Chile U., Santiago /Harvard U., Phys. Dept. /Baltimore, Space Telescope Sci. /Johns Hopkins U. /Res. Sch. Astron. Astrophys., Weston Creek /Stockholm U. /Hawaii U. /Illinois U., Urbana, Astron. Dept.
2008-02-13
We present the first large-scale effort of creating composite spectra of high-redshift type Ia supernovae (SNe Ia) and comparing them to low-redshift counterparts. Through the ESSENCE project, we have obtained 107 spectra of 88 high-redshift SNe Ia with excellent light-curve information. In addition, we have obtained 397 spectra of low-redshift SNe through a multiple-decade effort at Lick and Keck Observatories, and we have used 45 ultraviolet spectra obtained by HST/IUE. The low-redshift spectra act as a control sample when comparing to the ESSENCE spectra. In all instances, the ESSENCE and Lick composite spectra appear very similar. The addition of galaxy light to the Lick composite spectra allows a nearly perfect match of the overall spectral-energy distribution with the ESSENCE composite spectra, indicating that the high-redshift SNe are more contaminated with host-galaxy light than their low-redshift counterparts. This is caused by observing objects at all redshifts with similar slit widths, which corresponds to different projected distances. After correcting for the galaxy-light contamination, subtle differences in the spectra remain. We have estimated the systematic errors when using current spectral templates for K-corrections to be {approx}0.02 mag. The variance in the composite spectra give an estimate of the intrinsic variance in low-redshift maximum-light SN spectra of {approx}3% in the optical and growing toward the ultraviolet. The difference between the maximum-light low and high-redshift spectra constrain SN evolution between our samples to be < 10% in the rest-frame optical.
Dong, Yao-Jun; Belabbes, Abderrezak; Manchon, Aurelien
2017-01-01
Dzyaloshinskii-Moriya interaction (DMI) at Pt/Co interfaces is investigated theoretically using two different first principles methods. The first one uses the constrained moment method to build a spin spiral in real space, while the second method uses the generalized Bloch theorem approach to construct a spin spiral in reciprocal space. We show that although the two methods produce an overall similar total DMI energy, the dependence of DMI as a function of the spin spiral wavelength is dramatically different. We suggest that long-range magnetic interactions, that determine itinerant magnetism in transition metals, are responsible for this discrepancy. We conclude that the generalized Bloch theorem approach is more adapted to model DMI in transition metal systems, where magnetism is delocalized, while the constrained moment approach is mostly applicable to weak or insulating magnets, where magnetism is localized.
Dong, Yao-Jun
2017-10-29
Dzyaloshinskii-Moriya interaction (DMI) at Pt/Co interfaces is investigated theoretically using two different first principles methods. The first one uses the constrained moment method to build a spin spiral in real space, while the second method uses the generalized Bloch theorem approach to construct a spin spiral in reciprocal space. We show that although the two methods produce an overall similar total DMI energy, the dependence of DMI as a function of the spin spiral wavelength is dramatically different. We suggest that long-range magnetic interactions, that determine itinerant magnetism in transition metals, are responsible for this discrepancy. We conclude that the generalized Bloch theorem approach is more adapted to model DMI in transition metal systems, where magnetism is delocalized, while the constrained moment approach is mostly applicable to weak or insulating magnets, where magnetism is localized.
Qiuyu Wang
2014-01-01
descent method at first finite number of steps and then by conjugate gradient method subsequently. Under some appropriate conditions, we show that the algorithm converges globally. Numerical experiments and comparisons by using some box-constrained problems from CUTEr library are reported. Numerical comparisons illustrate that the proposed method is promising and competitive with the well-known method—L-BFGS-B.
Current-State Constrained Filter Bank for Wald Testing of Spacecraft Conjunctions
Carpenter, J. Russell; Markley, F. Landis
2012-01-01
We propose a filter bank consisting of an ordinary current-state extended Kalman filter, and two similar but constrained filters: one is constrained by a null hypothesis that the miss distance between two conjuncting spacecraft is inside their combined hard body radius at the predicted time of closest approach, and one is constrained by an alternative complementary hypothesis. The unconstrained filter is the basis of an initial screening for close approaches of interest. Once the initial screening detects a possibly risky conjunction, the unconstrained filter also governs measurement editing for all three filters, and predicts the time of closest approach. The constrained filters operate only when conjunctions of interest occur. The computed likelihoods of the innovations of the two constrained filters form a ratio for a Wald sequential probability ratio test. The Wald test guides risk mitigation maneuver decisions based on explicit false alarm and missed detection criteria. Since only current-state Kalman filtering is required to compute the innovations for the likelihood ratio, the present approach does not require the mapping of probability density forward to the time of closest approach. Instead, the hard-body constraint manifold is mapped to the filter update time by applying a sigma-point transformation to a projection function. Although many projectors are available, we choose one based on Lambert-style differential correction of the current-state velocity. We have tested our method using a scenario based on the Magnetospheric Multi-Scale mission, scheduled for launch in late 2014. This mission involves formation flight in highly elliptical orbits of four spinning spacecraft equipped with antennas extending 120 meters tip-to-tip. Eccentricities range from 0.82 to 0.91, and close approaches generally occur in the vicinity of perigee, where rapid changes in geometry may occur. Testing the method using two 12,000-case Monte Carlo simulations, we found the
KINETIC CONSEQUENCES OF CONSTRAINING RUNNING BEHAVIOR
John A. Mercer
2005-06-01
Full Text Available It is known that impact forces increase with running velocity as well as when stride length increases. Since stride length naturally changes with changes in submaximal running velocity, it was not clear which factor, running velocity or stride length, played a critical role in determining impact characteristics. The aim of the study was to investigate whether or not stride length influences the relationship between running velocity and impact characteristics. Eight volunteers (mass=72.4 ± 8.9 kg; height = 1.7 ± 0.1 m; age = 25 ± 3.4 years completed two running conditions: preferred stride length (PSL and stride length constrained at 2.5 m (SL2.5. During each condition, participants ran at a variety of speeds with the intent that the range of speeds would be similar between conditions. During PSL, participants were given no instructions regarding stride length. During SL2.5, participants were required to strike targets placed on the floor that resulted in a stride length of 2.5 m. Ground reaction forces were recorded (1080 Hz as well as leg and head accelerations (uni-axial accelerometers. Impact force and impact attenuation (calculated as the ratio of head and leg impact accelerations were recorded for each running trial. Scatter plots were generated plotting each parameter against running velocity. Lines of best fit were calculated with the slopes recorded for analysis. The slopes were compared between conditions using paired t-tests. Data from two subjects were dropped from analysis since the velocity ranges were not similar between conditions resulting in the analysis of six subjects. The slope of impact force vs. velocity relationship was different between conditions (PSL: 0.178 ± 0.16 BW/m·s-1; SL2.5: -0.003 ± 0.14 BW/m·s-1; p < 0.05. The slope of the impact attenuation vs. velocity relationship was different between conditions (PSL: 5.12 ± 2.88 %/m·s-1; SL2.5: 1.39 ± 1.51 %/m·s-1; p < 0.05. Stride length was an important factor
CONSTRAINED-TRANSPORT MAGNETOHYDRODYNAMICS WITH ADAPTIVE MESH REFINEMENT IN CHARM
Miniati, Francesco; Martin, Daniel F.
2011-01-01
We present the implementation of a three-dimensional, second-order accurate Godunov-type algorithm for magnetohydrodynamics (MHD) in the adaptive-mesh-refinement (AMR) cosmological code CHARM. The algorithm is based on the full 12-solve spatially unsplit corner-transport-upwind (CTU) scheme. The fluid quantities are cell-centered and are updated using the piecewise-parabolic method (PPM), while the magnetic field variables are face-centered and are evolved through application of the Stokes theorem on cell edges via a constrained-transport (CT) method. The so-called multidimensional MHD source terms required in the predictor step for high-order accuracy are applied in a simplified form which reduces their complexity in three dimensions without loss of accuracy or robustness. The algorithm is implemented on an AMR framework which requires specific synchronization steps across refinement levels. These include face-centered restriction and prolongation operations and a reflux-curl operation, which maintains a solenoidal magnetic field across refinement boundaries. The code is tested against a large suite of test problems, including convergence tests in smooth flows, shock-tube tests, classical two- and three-dimensional MHD tests, a three-dimensional shock-cloud interaction problem, and the formation of a cluster of galaxies in a fully cosmological context. The magnetic field divergence is shown to remain negligible throughout.
Elastic Model Transitions Using Quadratic Inequality Constrained Least Squares
Orr, Jeb S.
2012-01-01
A technique is presented for initializing multiple discrete finite element model (FEM) mode sets for certain types of flight dynamics formulations that rely on superposition of orthogonal modes for modeling the elastic response. Such approaches are commonly used for modeling launch vehicle dynamics, and challenges arise due to the rapidly time-varying nature of the rigid-body and elastic characteristics. By way of an energy argument, a quadratic inequality constrained least squares (LSQI) algorithm is employed to e ect a smooth transition from one set of FEM eigenvectors to another with no requirement that the models be of similar dimension or that the eigenvectors be correlated in any particular way. The physically unrealistic and controversial method of eigenvector interpolation is completely avoided, and the discrete solution approximates that of the continuously varying system. The real-time computational burden is shown to be negligible due to convenient features of the solution method. Simulation results are presented, and applications to staging and other discontinuous mass changes are discussed
Constrained motion estimation-based error resilient coding for HEVC
Guo, Weihan; Zhang, Yongfei; Li, Bo
2018-04-01
Unreliable communication channels might lead to packet losses and bit errors in the videos transmitted through it, which will cause severe video quality degradation. This is even worse for HEVC since more advanced and powerful motion estimation methods are introduced to further remove the inter-frame dependency and thus improve the coding efficiency. Once a Motion Vector (MV) is lost or corrupted, it will cause distortion in the decoded frame. More importantly, due to motion compensation, the error will propagate along the motion prediction path, accumulate over time, and significantly degrade the overall video presentation quality. To address this problem, we study the problem of encoder-sider error resilient coding for HEVC and propose a constrained motion estimation scheme to mitigate the problem of error propagation to subsequent frames. The approach is achieved by cutting off MV dependencies and limiting the block regions which are predicted by temporal motion vector. The experimental results show that the proposed method can effectively suppress the error propagation caused by bit errors of motion vector and can improve the robustness of the stream in the bit error channels. When the bit error probability is 10-5, an increase of the decoded video quality (PSNR) by up to1.310dB and on average 0.762 dB can be achieved, compared to the reference HEVC.
CCTOP: a Consensus Constrained TOPology prediction web server.
Dobson, László; Reményi, István; Tusnády, Gábor E
2015-07-01
The Consensus Constrained TOPology prediction (CCTOP; http://cctop.enzim.ttk.mta.hu) server is a web-based application providing transmembrane topology prediction. In addition to utilizing 10 different state-of-the-art topology prediction methods, the CCTOP server incorporates topology information from existing experimental and computational sources available in the PDBTM, TOPDB and TOPDOM databases using the probabilistic framework of hidden Markov model. The server provides the option to precede the topology prediction with signal peptide prediction and transmembrane-globular protein discrimination. The initial result can be recalculated by (de)selecting any of the prediction methods or mapped experiments or by adding user specified constraints. CCTOP showed superior performance to existing approaches. The reliability of each prediction is also calculated, which correlates with the accuracy of the per protein topology prediction. The prediction results and the collected experimental information are visualized on the CCTOP home page and can be downloaded in XML format. Programmable access of the CCTOP server is also available, and an example of client-side script is provided. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.
Chance-Constrained Guidance With Non-Convex Constraints
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
Splines and polynomial tools for flatness-based constrained motion planning
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.
The Smoothing Artifact of Spatially Constrained Canonical Correlation Analysis in Functional MRI
Dietmar Cordes
2012-01-01
Full Text Available A wide range of studies show the capacity of multivariate statistical methods for fMRI to improve mapping of brain activations in a noisy environment. An advanced method uses local canonical correlation analysis (CCA to encompass a group of neighboring voxels instead of looking at the single voxel time course. The value of a suitable test statistic is used as a measure of activation. It is customary to assign the value to the center voxel; however, this is a choice of convenience and without constraints introduces artifacts, especially in regions of strong localized activation. To compensate for these deficiencies, different spatial constraints in CCA have been introduced to enforce dominance of the center voxel. However, even if the dominance condition for the center voxel is satisfied, constrained CCA can still lead to a smoothing artifact, often called the “bleeding artifact of CCA”, in fMRI activation patterns. In this paper a new method is introduced to measure and correct for the smoothing artifact for constrained CCA methods. It is shown that constrained CCA methods corrected for the smoothing artifact lead to more plausible activation patterns in fMRI as shown using data from a motor task and a memory task.
Cotter, Simon L., E-mail: simon.cotter@manchester.ac.uk
2016-10-15
Efficient analysis and simulation of multiscale stochastic systems of chemical kinetics is an ongoing area for research, and is the source of many theoretical and computational challenges. In this paper, we present a significant improvement to the constrained approach, which is a method for computing effective dynamics of slowly changing quantities in these systems, but which does not rely on the quasi-steady-state assumption (QSSA). The QSSA can cause errors in the estimation of effective dynamics for systems where the difference in timescales between the “fast” and “slow” variables is not so pronounced. This new application of the constrained approach allows us to compute the effective generator of the slow variables, without the need for expensive stochastic simulations. This is achieved by finding the null space of the generator of the constrained system. For complex systems where this is not possible, or where the constrained subsystem is itself multiscale, the constrained approach can then be applied iteratively. This results in breaking the problem down into finding the solutions to many small eigenvalue problems, which can be efficiently solved using standard methods. Since this methodology does not rely on the quasi steady-state assumption, the effective dynamics that are approximated are highly accurate, and in the case of systems with only monomolecular reactions, are exact. We will demonstrate this with some numerics, and also use the effective generators to sample paths of the slow variables which are conditioned on their endpoints, a task which would be computationally intractable for the generator of the full system.
Carbon-constrained scenarios. Final report
2009-05-01
This report provides the results of the study entitled 'Carbon-Constrained Scenarios' that was funded by FONDDRI from 2004 to 2008. The study was achieved in four steps: (i) Investigating the stakes of a strong carbon constraint for the industries participating in the study, not only looking at the internal decarbonization potential of each industry but also exploring the potential shifts of the demand for industrial products. (ii) Developing an hybrid modelling platform based on a tight dialog between the sectoral energy model POLES and the macro-economic model IMACLIM-R, in order to achieve a consistent assessment of the consequences of an economy-wide carbon constraint on energy-intensive industrial sectors, while taking into account technical constraints, barriers to the deployment of new technologies and general economic equilibrium effects. (iii) Producing several scenarios up to 2050 with different sets of hypotheses concerning the driving factors for emissions - in particular the development styles. (iv) Establishing an iterative dialog between researchers and industry representatives on the results of the scenarios so as to improve them, but also to facilitate the understanding and the appropriate use of these results by the industrial partners. This report provides the results of the different scenarios computed in the course of the project. It is a partial synthesis of the work that has been accomplished and of the numerous exchanges that this study has induced between modellers and stakeholders. The first part was written in April 2007 and describes the first reference scenario and the first mitigation scenario designed to achieve stabilization at 450 ppm CO 2 at the end of the 21. century. This scenario has been called 'mimetic' because it has been build on the assumption that the ambitious climate policy would coexist with a progressive convergence of development paths toward the current paradigm of industrialized countries: urban sprawl, general
FXR agonist activity of conformationally constrained analogs of GW 4064.
Akwabi-Ameyaw, Adwoa; Bass, Jonathan Y; Caldwell, Richard D; Caravella, Justin A; Chen, Lihong; Creech, Katrina L; Deaton, David N; Madauss, Kevin P; Marr, Harry B; McFadyen, Robert B; Miller, Aaron B; Navas, Frank; Parks, Derek J; Spearing, Paul K; Todd, Dan; Williams, Shawn P; Bruce Wisely, G
2009-08-15
Two series of conformationally constrained analogs of the FXR agonist GW 4064 1 were prepared. Replacement of the metabolically labile stilbene with either benzothiophene or naphthalene rings led to the identification of potent full agonists 2a and 2g.
Automated Precision Maneuvering and Landing in Extreme and Constrained Environments
National Aeronautics and Space Administration — Autonomous, precise maneuvering and landing in extreme and constrained environments is a key enabler for future NASA missions. Missions to map the interior of a...
Security constrained optimal power flow by modern optimization tools
Security constrained optimal power flow by modern optimization tools. ... International Journal of Engineering, Science and Technology ... If you would like more information about how to print, save, and work with PDFs, Highwire Press ...
Affine Lie algebraic origin of constrained KP hierarchies
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
Slow logarithmic relaxation in models with hierarchically constrained dynamics
Brey, J. J.; Prados, A.
2000-01-01
A general kind of models with hierarchically constrained dynamics is shown to exhibit logarithmic anomalous relaxation, similarly to a variety of complex strongly interacting materials. The logarithmic behavior describes most of the decay of the response function.
Synthesis of conformationally constrained peptidomimetics using multicomponent reactions
Scheffelaar, R.; Klein Nijenhuis, R.A.; Paravidino, M.; Lutz, M.; Spek, A.L.; Ehlers, A.W.; de Kanter, F.J.J.; Groen, M.B.; Orru, R.V.A.; Ruijter, E.
2009-01-01
A novel modular synthetic approach toward constrained peptidomimetics is reported. The approach involves a highly efficient three-step sequence including two multicomponent reactions, thus allowing unprecedented diversification of both the peptide moieties and the turn-inducing scaffold. The
Filter Pattern Search Algorithms for Mixed Variable Constrained Optimization Problems
Abramson, Mark A; Audet, Charles; Dennis, Jr, J. E
2004-01-01
.... This class combines and extends the Audet-Dennis Generalized Pattern Search (GPS) algorithms for bound constrained mixed variable optimization, and their GPS-filter algorithms for general nonlinear constraints...
Capacity Constrained Routing Algorithms for Evacuation Route Planning
Lu, Qingsong; George, Betsy; Shekhar, Shashi
2006-01-01
.... In this paper, we propose a new approach, namely a capacity constrained routing planner which models capacity as a time series and generalizes shortest path algorithms to incorporate capacity constraints...
New Exact Penalty Functions for Nonlinear Constrained Optimization Problems
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.
Constraining the roughness degree of slip heterogeneity
Causse, Mathieu; Cotton, Fabrice; Mai, Paul Martin
2010-01-01
out poorly resolved models. The number of remaining models (30) is thus rather small. In addition, the robustness of the empirical model rests on a reliable estimation of kc by kinematic inversion methods. We address this issue by performing tests
Liu, X; Belcher, AH; Wiersma, R [The University of Chicago, Chicago, IL (United States)
2016-06-15
Purpose: In radiation therapy optimization the constraints can be either hard constraints which must be satisfied or soft constraints which are included but do not need to be satisfied exactly. Currently the voxel dose constraints are viewed as soft constraints and included as a part of the objective function and approximated as an unconstrained problem. However in some treatment planning cases the constraints should be specified as hard constraints and solved by constrained optimization. The goal of this work is to present a computation efficiency graph form alternating direction method of multipliers (ADMM) algorithm for constrained quadratic treatment planning optimization and compare it with several commonly used algorithms/toolbox. Method: ADMM can be viewed as an attempt to blend the benefits of dual decomposition and augmented Lagrangian methods for constrained optimization. Various proximal operators were first constructed as applicable to quadratic IMRT constrained optimization and the problem was formulated in a graph form of ADMM. A pre-iteration operation for the projection of a point to a graph was also proposed to further accelerate the computation. Result: The graph form ADMM algorithm was tested by the Common Optimization for Radiation Therapy (CORT) dataset including TG119, prostate, liver, and head & neck cases. Both unconstrained and constrained optimization problems were formulated for comparison purposes. All optimizations were solved by LBFGS, IPOPT, Matlab built-in toolbox, CVX (implementing SeDuMi) and Mosek solvers. For unconstrained optimization, it was found that LBFGS performs the best, and it was 3–5 times faster than graph form ADMM. However, for constrained optimization, graph form ADMM was 8 – 100 times faster than the other solvers. Conclusion: A graph form ADMM can be applied to constrained quadratic IMRT optimization. It is more computationally efficient than several other commercial and noncommercial optimizers and it also
Alternatively Constrained Dictionary Learning For Image Superresolution.
Lu, Xiaoqiang; Yuan, Yuan; Yan, Pingkun
2014-03-01
Dictionaries are crucial in sparse coding-based algorithm for image superresolution. Sparse coding is a typical unsupervised learning method to study the relationship between the patches of high-and low-resolution images. However, most of the sparse coding methods for image superresolution fail to simultaneously consider the geometrical structure of the dictionary and the corresponding coefficients, which may result in noticeable superresolution reconstruction artifacts. In other words, when a low-resolution image and its corresponding high-resolution image are represented in their feature spaces, the two sets of dictionaries and the obtained coefficients have intrinsic links, which has not yet been well studied. Motivated by the development on nonlocal self-similarity and manifold learning, a novel sparse coding method is reported to preserve the geometrical structure of the dictionary and the sparse coefficients of the data. Moreover, the proposed method can preserve the incoherence of dictionary entries and provide the sparse coefficients and learned dictionary from a new perspective, which have both reconstruction and discrimination properties to enhance the learning performance. Furthermore, to utilize the model of the proposed method more effectively for single-image superresolution, this paper also proposes a novel dictionary-pair learning method, which is named as two-stage dictionary training. Extensive experiments are carried out on a large set of images comparing with other popular algorithms for the same purpose, and the results clearly demonstrate the effectiveness of the proposed sparse representation model and the corresponding dictionary learning algorithm.
Investigating multiple solutions in the constrained minimal supersymmetric standard model
Allanach, B.C. [DAMTP, CMS, University of Cambridge,Wilberforce Road, Cambridge, CB3 0HA (United Kingdom); George, Damien P. [DAMTP, CMS, University of Cambridge,Wilberforce Road, Cambridge, CB3 0HA (United Kingdom); Cavendish Laboratory, University of Cambridge,JJ Thomson Avenue, Cambridge, CB3 0HE (United Kingdom); Nachman, Benjamin [SLAC, Stanford University,2575 Sand Hill Rd, Menlo Park, CA 94025 (United States)
2014-02-07
Recent work has shown that the Constrained Minimal Supersymmetric Standard Model (CMSSM) can possess several distinct solutions for certain values of its parameters. The extra solutions were not previously found by public supersymmetric spectrum generators because fixed point iteration (the algorithm used by the generators) is unstable in the neighbourhood of these solutions. The existence of the additional solutions calls into question the robustness of exclusion limits derived from collider experiments and cosmological observations upon the CMSSM, because limits were only placed on one of the solutions. Here, we map the CMSSM by exploring its multi-dimensional parameter space using the shooting method, which is not subject to the stability issues which can plague fixed point iteration. We are able to find multiple solutions where in all previous literature only one was found. The multiple solutions are of two distinct classes. One class, close to the border of bad electroweak symmetry breaking, is disfavoured by LEP2 searches for neutralinos and charginos. The other class has sparticles that are heavy enough to evade the LEP2 bounds. Chargino masses may differ by up to around 10% between the different solutions, whereas other sparticle masses differ at the sub-percent level. The prediction for the dark matter relic density can vary by a hundred percent or more between the different solutions, so analyses employing the dark matter constraint are incomplete without their inclusion.
A constrained conjugate gradient algorithm for computed tomography
Azevedo, S.G.; Goodman, D.M. [Lawrence Livermore National Lab., CA (United States)
1994-11-15
Image reconstruction from projections of x-ray, gamma-ray, protons and other penetrating radiation is a well-known problem in a variety of fields, and is commonly referred to as computed tomography (CT). Various analytical and series expansion methods of reconstruction and been used in the past to provide three-dimensional (3D) views of some interior quantity. The difficulties of these approaches lie in the cases where (a) the number of views attainable is limited, (b) the Poisson (or other) uncertainties are significant, (c) quantifiable knowledge of the object is available, but not implementable, or (d) other limitations of the data exist. We have adapted a novel nonlinear optimization procedure developed at LLNL to address limited-data image reconstruction problems. The technique, known as nonlinear least squares with general constraints or constrained conjugate gradients (CCG), has been successfully applied to a number of signal and image processing problems, and is now of great interest to the image reconstruction community. Previous applications of this algorithm to deconvolution problems and x-ray diffraction images for crystallography have shown the great promise.
Classification of Hyperspectral Images Using Kernel Fully Constrained Least Squares
Jianjun Liu
2017-11-01
Full Text Available As a widely used classifier, sparse representation classification (SRC has shown its good performance for hyperspectral image classification. Recent works have highlighted that it is the collaborative representation mechanism under SRC that makes SRC a highly effective technique for classification purposes. If the dimensionality and the discrimination capacity of a test pixel is high, other norms (e.g., ℓ 2 -norm can be used to regularize the coding coefficients, except for the sparsity ℓ 1 -norm. In this paper, we show that in the kernel space the nonnegative constraint can also play the same role, and thus suggest the investigation of kernel fully constrained least squares (KFCLS for hyperspectral image classification. Furthermore, in order to improve the classification performance of KFCLS by incorporating spatial-spectral information, we investigate two kinds of spatial-spectral methods using two regularization strategies: (1 the coefficient-level regularization strategy, and (2 the class-level regularization strategy. Experimental results conducted on four real hyperspectral images demonstrate the effectiveness of the proposed KFCLS, and show which way to incorporate spatial-spectral information efficiently in the regularization framework.
Constraining decaying dark matter with FERMI-LAT gamma rays
Maccione, L.
2011-01-01
High energy electron sand positrons from decaying dark matter can produce a significant flux of gamma rays by inverse Compton of low energy photons in the interstellar radiation field. This possibility is inevitably related with the dark matter interpretation of the observed PAMELA and FERMI excesses. We will describe a simple and universal method to constrain dark matter models which produce electrons and positrons in their decay by using the FERMI-LAT gamma-ray observations in the energy range between 0.5 GeV and 300 GeV, by exploiting universal response functions that, once convolved with a specific dark matter model, produce the desired constraint. The response functions contain all the astrophysical inputs. Here is discussed the uncertainties in the determination of the response functions and apply them to place constraints on some specific dark matter decay models that can well fit the positron and electron fluxes observed by PAMELA and FERMI LAT, also taking into account prompt radiation from the dark matter decay. With the available data decaying dark matter can not be excluded as source of the PAMELA positron excess.
Bulk diffusion in a kinetically constrained lattice gas
Arita, Chikashi; Krapivsky, P. L.; Mallick, Kirone
2018-03-01
In the hydrodynamic regime, the evolution of a stochastic lattice gas with symmetric hopping rules is described by a diffusion equation with density-dependent diffusion coefficient encapsulating all microscopic details of the dynamics. This diffusion coefficient is, in principle, determined by a Green-Kubo formula. In practice, even when the equilibrium properties of a lattice gas are analytically known, the diffusion coefficient cannot be computed except when a lattice gas additionally satisfies the gradient condition. We develop a procedure to systematically obtain analytical approximations for the diffusion coefficient for non-gradient lattice gases with known equilibrium. The method relies on a variational formula found by Varadhan and Spohn which is a version of the Green-Kubo formula particularly suitable for diffusive lattice gases. Restricting the variational formula to finite-dimensional sub-spaces allows one to perform the minimization and gives upper bounds for the diffusion coefficient. We apply this approach to a kinetically constrained non-gradient lattice gas in two dimensions, viz. to the Kob-Andersen model on the square lattice.
Constraining decaying dark matter with Fermi LAT gamma-rays
Zhang, Le; Sigl, Günter; Weniger, Christoph; Maccione, Luca; Redondo, Javier
2010-01-01
High energy electrons and positrons from decaying dark matter can produce a significant flux of gamma rays by inverse Compton off low energy photons in the interstellar radiation field. This possibility is inevitably related with the dark matter interpretation of the observed PAMELA and FERMI excesses. The aim of this paper is providing a simple and universal method to constrain dark matter models which produce electrons and positrons in their decay by using the Fermi LAT gamma-ray observations in the energy range between 0.5 GeV and 300 GeV. We provide a set of universal response functions that, once convolved with a specific dark matter model produce the desired constraints. Our response functions contain all the astrophysical inputs such as the electron propagation in the galaxy, the dark matter profile, the gamma-ray fluxes of known origin, and the Fermi LAT data. We study the uncertainties in the determination of the response functions and apply them to place constraints on some specific dark matter decay models that can well fit the positron and electron fluxes observed by PAMELA and Fermi LAT. To this end we also take into account prompt radiation from the dark matter decay. We find that with the available data decaying dark matter cannot be excluded as source of the PAMELA positron excess
Wang, Yong; Cai, Zixing; Zhou, Yuren
2009-01-01
A novel approach to deal with numerical and engineering constrained optimization problems, which incorporates a hybrid evolutionary algorithm and an adaptive constraint-handling technique, is presented in this paper. The hybrid evolutionary algorithm simultaneously uses simplex crossover and two...... mutation operators to generate the offspring population. Additionally, the adaptive constraint-handling technique consists of three main situations. In detail, at each situation, one constraint-handling mechanism is designed based on current population state. Experiments on 13 benchmark test functions...... and four well-known constrained design problems verify the effectiveness and efficiency of the proposed method. The experimental results show that integrating the hybrid evolutionary algorithm with the adaptive constraint-handling technique is beneficial, and the proposed method achieves competitive...
Wang, Mingming; Luo, Jianjun; Yuan, Jianping; Walter, Ulrich
2018-05-01
Application of the multi-arm space robot will be more effective than single arm especially when the target is tumbling. This paper investigates the application of particle swarm optimization (PSO) strategy to coordinated trajectory planning of the dual-arm space robot in free-floating mode. In order to overcome the dynamics singularities issue, the direct kinematics equations in conjunction with constrained PSO are employed for coordinated trajectory planning of dual-arm space robot. The joint trajectories are parametrized with Bézier curve to simplify the calculation. Constrained PSO scheme with adaptive inertia weight is implemented to find the optimal solution of joint trajectories while specific objectives and imposed constraints are satisfied. The proposed method is not sensitive to the singularity issue due to the application of forward kinematic equations. Simulation results are presented for coordinated trajectory planning of two kinematically redundant manipulators mounted on a free-floating spacecraft and demonstrate the effectiveness of the proposed method.
Dynamic Load Balancing Based on Constrained K-D Tree Decomposition for Parallel Particle Tracing
Zhang, Jiang; Guo, Hanqi; Yuan, Xiaoru; Hong, Fan; Peterka, Tom
2018-01-01
Particle tracing is a fundamental technique in flow field data visualization. In this work, we present a novel dynamic load balancing method for parallel particle tracing. Specifically, we employ a constrained k-d tree decomposition approach to dynamically redistribute tasks among processes. Each process is initially assigned a regularly partitioned block along with duplicated ghost layer under the memory limit. During particle tracing, the k-d tree decomposition is dynamically performed by constraining the cutting planes in the overlap range of duplicated data. This ensures that each process is reassigned particles as even as possible, and on the other hand the new assigned particles for a process always locate in its block. Result shows good load balance and high efficiency of our method.
A First-order Prediction-Correction Algorithm for Time-varying (Constrained) Optimization: Preprint
Dall-Anese, Emiliano [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Simonetto, Andrea [Universite catholique de Louvain
2017-07-25
This paper focuses on the design of online algorithms based on prediction-correction steps to track the optimal solution of a time-varying constrained problem. Existing prediction-correction methods have been shown to work well for unconstrained convex problems and for settings where obtaining the inverse of the Hessian of the cost function can be computationally affordable. The prediction-correction algorithm proposed in this paper addresses the limitations of existing methods by tackling constrained problems and by designing a first-order prediction step that relies on the Hessian of the cost function (and do not require the computation of its inverse). Analytical results are established to quantify the tracking error. Numerical simulations corroborate the analytical results and showcase performance and benefits of the algorithms.
The Combinatorial Multi-Mode Resource Constrained Multi-Project Scheduling Problem
Denis Pinha
2016-11-01
Full Text Available This paper presents the formulation and solution of the Combinatorial Multi-Mode Resource Constrained Multi-Project Scheduling Problem. The focus of the proposed method is not on finding a single optimal solution, instead on presenting multiple feasible solutions, with cost and duration information to the project manager. The motivation for developing such an approach is due in part to practical situations where the definition of optimal changes on a regular basis. The proposed approach empowers the project manager to determine what is optimal, on a given day, under the current constraints, such as, change of priorities, lack of skilled worker. The proposed method utilizes a simulation approach to determine feasible solutions, under the current constraints. Resources can be non-consumable, consumable, or doubly constrained. The paper also presents a real-life case study dealing with scheduling of ship repair activities.
USING COSMIC MICROWAVE BACKGROUND LENSING TO CONSTRAIN THE MULTIPLICATIVE BIAS OF COSMIC SHEAR
Vallinotto, Alberto
2012-01-01
Weak gravitational lensing is one of the key probes of cosmology. Cosmic shear surveys aimed at measuring the distribution of matter in the universe are currently being carried out (Pan-STARRS) or planned for the coming decade (DES, LSST, EUCLID, WFIRST). Crucial to the success of these surveys is the control of systematics. In this work, a new method to constrain one such family of systematics, known as multiplicative bias, is proposed. This method exploits the cross-correlation between weak-lensing measurements from galaxy surveys and the ones obtained from high-resolution cosmic microwave background experiments. This cross-correlation is shown to have the power to break the degeneracy between the normalization of the matter power spectrum and the multiplicative bias of cosmic shear and to be able to constrain the latter to a few percent.
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.
Dino Bindi; Stefano Parolai; M. Picozzi; A. Ansal
2010-01-01
We apply a deconvolution approach to the problem of determining the input motion at the base of an instrumented borehole using only a pair of recordings, one at the borehole surface and the other at its bottom. To stabilize the bottom-tosurface spectral ratio, we apply an iterative regularization algorithm that allows us to constrain the solution to be positively defined and to have a finite time duration. Through the analysis of synthetic data, we show that the method is capab...
Time constrained liner shipping network design
Karsten, Christian Vad; Brouer, Berit Dangaard; Desaulniers, Guy
2017-01-01
We present a mathematical model and a solution method for the liner shipping network design problem. The model takes into account coordination between vessels and transit time restrictions on the cargo flow. The solution method is an improvement heuristic, where an integer program is solved...... iteratively to perform moves in a large neighborhood search. Our improvement heuristic is applicable as a real-time decision support tool for a liner shipping company. It can be used to find improvements to the network when evaluating changes in operating conditions or testing different scenarios...
Moment constrained semi-supervised LDA
Loog, Marco
2012-01-01
This BNAIC compressed contribution provides a summary of the work originally presented at the First IAPR Workshop on Partially Supervised Learning and published in [5]. It outlines the idea behind supervised and semi-supervised learning and highlights the major shortcoming of many current methods...
Identification of Constrained Cancer Driver Genes Based on Mutation Timing
Sakoparnig, Thomas; Fried, Patrick; Beerenwinkel, Niko
2015-01-01
Cancer drivers are genomic alterations that provide cells containing them with a selective advantage over their local competitors, whereas neutral passengers do not change the somatic fitness of cells. Cancer-driving mutations are usually discriminated from passenger mutations by their higher degree of recurrence in tumor samples. However, there is increasing evidence that many additional driver mutations may exist that occur at very low frequencies among tumors. This observation has prompted alternative methods for driver detection, including finding groups of mutually exclusive mutations and incorporating prior biological knowledge about gene function or network structure. Dependencies among drivers due to epistatic interactions can also result in low mutation frequencies, but this effect has been ignored in driver detection so far. Here, we present a new computational approach for identifying genomic alterations that occur at low frequencies because they depend on other events. Unlike passengers, these constrained mutations display punctuated patterns of occurrence in time. We test this driver–passenger discrimination approach based on mutation timing in extensive simulation studies, and we apply it to cross-sectional copy number alteration (CNA) data from ovarian cancer, CNA and single-nucleotide variant (SNV) data from breast tumors and SNV data from colorectal cancer. Among the top ranked predicted drivers, we find low-frequency genes that have already been shown to be involved in carcinogenesis, as well as many new candidate drivers. The mutation timing approach is orthogonal and complementary to existing driver prediction methods. It will help identifying from cancer genome data the alterations that drive tumor progression. PMID:25569148
A HARDCORE model for constraining an exoplanet's core size
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.
Constrained Local UniversE Simulations: a Local Group factory
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.
Unintended Consequences: How Qualification Constrains Innovation
Brice, Craig A.
2011-01-01
The development and implementation of new materials and manufacturing processes for aerospace application is often hindered by the high cost and long time span associated with current qualification procedures. The data requirements necessary for material and process qualification are extensive and often require millions of dollars and multiple years to complete. Furthermore, these qualification data can become obsolete for even minor changes to the processing route. This burden is a serious impediment to the pursuit of revolutionary new materials and more affordable processing methods for air vehicle structures. The application of integrated computational materials engineering methods to this problem can help to reduce the barriers to rapid insertion of new materials and processes. By establishing predictive capability for the development of microstructural features in relation to processing and relating this to critical property characteristics, a streamlined approach to qualification is possible. This paper critically examines the advantages and challenges to a modeling-assisted qualification approach for aerospace structural materials. An example of how this approach might apply towards the emerging field of additive manufacturing is discussed in detail.
Constrained Optimization of MIMO Training Sequences
Coon Justin P
2007-01-01
Full Text Available Multiple-input multiple-output (MIMO systems have shown a huge potential for increased spectral efficiency and throughput. With an increasing number of transmitting antennas comes the burden of providing training for channel estimation for coherent detection. In some special cases optimal, in the sense of mean-squared error (MSE, training sequences have been designed. However, in many practical systems it is not feasible to analytically find optimal solutions and numerical techniques must be used. In this paper, two systems (unique word (UW single carrier and OFDM with nulled subcarriers are considered and a method of designing near-optimal training sequences using nonlinear optimization techniques is proposed. In particular, interior-point (IP algorithms such as the barrier method are discussed. Although the two systems seem unrelated, the cost function, which is the MSE of the channel estimate, is shown to be effectively the same for each scenario. Also, additional constraints, such as peak-to-average power ratio (PAPR, are considered and shown to be easily included in the optimization process. Numerical examples illustrate the effectiveness of the designed training sequences, both in terms of MSE and bit-error rate (BER.
Can strong gravitational lensing constrain dark energy?
Lee, Seokcheon; Ng, K.-W.
2007-01-01
We discuss the ratio of the angular diameter distances from the source to the lens, D ds , and to the observer at present, D s , for various dark energy models. It is well known that the difference of D s s between the models is apparent and this quantity is used for the analysis of Type Ia supernovae. However we investigate the difference between the ratio of the angular diameter distances for a cosmological constant, (D ds /D s ) Λ , and that for other dark energy models, (D ds /D s ) other , in this paper. It has been known that there is lens model degeneracy in using strong gravitational lensing. Thus, we investigate the model independent observable quantity, Einstein radius (θ E ), which is proportional to both D ds /D s and velocity dispersion squared, σ v 2 . D ds /D s values depend on the parameters of each dark energy model individually. However, (D ds /D s ) Λ -(D ds /D s ) other for the various dark energy models, is well within the error of σ v for most of the parameter spaces of the dark energy models. Thus, a single strong gravitational lensing by use of the Einstein radius may not be a proper method to investigate the property of dark energy. However, better understanding to the mass profile of clusters in the future or other methods related to arc statistics rather than the distances may be used for constraints on dark energy
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.
A simple way to constrain the stoichiometry of secondary smectites upon aqueous glass alteration
Thien, Bruno M.J.
2014-01-01
Highlights: • Si/Al of different glasses were compared to Si/Al of associated secondary smectites. • Si/Al of secondary smectite is nearly equal to Si/Al of parent glass. • This is a simple way which can help to constrain smectite composition. • Accurate smectite composition cannot be measured in many cases. - Abstract: The comparison of the stoichiometry of several nuclear waste glasses and basaltic glasses with their associated secondary smectites evidenced that Si/Al ratios of secondary smectites are nearly equal to the Si/Al ratios of parent glasses. This information may be very useful in constraining secondary smectites structure and stoichiometry in cases where other identification methods are difficult to apply
A one-layer recurrent neural network for constrained nonsmooth invex optimization.
Li, Guocheng; Yan, Zheng; Wang, Jun
2014-02-01
Invexity is an important notion in nonconvex optimization. In this paper, a one-layer recurrent neural network is proposed for solving constrained nonsmooth invex optimization problems, designed based on an exact penalty function method. It is proved herein that any state of the proposed neural network is globally convergent to the optimal solution set of constrained invex optimization problems, with a sufficiently large penalty parameter. In addition, any neural state is globally convergent to the unique optimal solution, provided that the objective function and constraint functions are pseudoconvex. Moreover, any neural state is globally convergent to the feasible region in finite time and stays there thereafter. The lower bounds of the penalty parameter and convergence time are also estimated. Two numerical examples are provided to illustrate the performances of the proposed neural network. Copyright © 2013 Elsevier Ltd. All rights reserved.
Gamst, M.
2014-01-01
problem. The methods are computationally evaluated on test instances arising from telecommunications with up to 500 jobs and 500 machines. Results show that solving the integrated job scheduling and constrained network routing problem to optimality is very difficult. The exact solution approach performs......This paper examines the problem of scheduling a number of jobs on a finite set of machines such that the overall profit of executed jobs is maximized. Each job has a certain demand, which must be sent to the executing machine via constrained paths. A job cannot start before all its demands have...... arrived at the machine. Furthermore, two resource demand transmissions cannot use the same edge in the same time period. The problem has application in grid computing, where a number of geographically distributed machines work together for solving large problems. The machines are connected through...
Hybrid real-code ant colony optimisation for constrained mechanical design
Pholdee, Nantiwat; Bureerat, Sujin
2016-01-01
This paper proposes a hybrid meta-heuristic based on integrating a local search simplex downhill (SDH) method into the search procedure of real-code ant colony optimisation (ACOR). This hybridisation leads to five hybrid algorithms where a Monte Carlo technique, a Latin hypercube sampling technique (LHS) and a translational propagation Latin hypercube design (TPLHD) algorithm are used to generate an initial population. Also, two numerical schemes for selecting an initial simplex are investigated. The original ACOR and its hybrid versions along with a variety of established meta-heuristics are implemented to solve 17 constrained test problems where a fuzzy set theory penalty function technique is used to handle design constraints. The comparative results show that the hybrid algorithms are the top performers. Using the TPLHD technique gives better results than the other sampling techniques. The hybrid optimisers are a powerful design tool for constrained mechanical design problems.
Constrained Hartree-Fock and beyond
Berger, J.F.; Girod, M.; Gogny, D.
1989-01-01
Completely microscopic descriptions of the fission phenomenon based on the nuclear mean field theory and its extensions are reviewed. The basic ideas underlying this kind of approach and the way one can set up a consistent microscopic dynamical model of the low energy fission process are presented. The main difficulties encountered in earlier calculations when trying to reproduce experimental fission barriers and to account for scission are recalled. We describe the method by which these difficulties have been overcome and discuss recent results. They concern a proposed interpretation for the scission mechanism and 'cold fission' events. Other issues like adiabaticity in the descent from the second saddle to scission and odd-even effects in cold fission are also discussed. (orig.)
Facies Constrained Elastic Full Waveform Inversion
Zhang, Z.
2017-05-26
Current efforts to utilize full waveform inversion (FWI) as a tool beyond acoustic imaging applications, for example for reservoir analysis, face inherent limitations on resolution and also on the potential trade-off between elastic model parameters. Adding rock physics constraints does help to mitigate these issues. However, current approaches to add such constraints are based on averaged type rock physics regularization terms. Since the true earth model consists of different facies, averaging over those facies naturally leads to smoothed models. To overcome this, we propose a novel way to utilize facies based constraints in elastic FWI. A so-called confidence map is calculated and updated at each iteration of the inversion using both the inverted models and the prior information. The numerical example shows that the proposed method can reduce the cross-talks and also can improve the resolution of inverted elastic properties.
Facies Constrained Elastic Full Waveform Inversion
Zhang, Z.; Zabihi Naeini, E.; Alkhalifah, Tariq Ali
2017-01-01
Current efforts to utilize full waveform inversion (FWI) as a tool beyond acoustic imaging applications, for example for reservoir analysis, face inherent limitations on resolution and also on the potential trade-off between elastic model parameters. Adding rock physics constraints does help to mitigate these issues. However, current approaches to add such constraints are based on averaged type rock physics regularization terms. Since the true earth model consists of different facies, averaging over those facies naturally leads to smoothed models. To overcome this, we propose a novel way to utilize facies based constraints in elastic FWI. A so-called confidence map is calculated and updated at each iteration of the inversion using both the inverted models and the prior information. The numerical example shows that the proposed method can reduce the cross-talks and also can improve the resolution of inverted elastic properties.
Constrained Dynamic Optimality and Binomial Terminal Wealth
Pedersen, J. L.; Peskir, G.
2018-01-01
with interest rate $r \\in {R}$). Letting $P_{t,x}$ denote a probability measure under which $X^u$ takes value $x$ at time $t,$ we study the dynamic version of the nonlinear optimal control problem $\\inf_u\\, Var{t,X_t^u}(X_T^u)$ where the infimum is taken over admissible controls $u$ subject to $X_t^u \\ge e...... a martingale method combined with Lagrange multipliers, we derive the dynamically optimal control $u_*^d$ in closed form and prove that the dynamically optimal terminal wealth $X_T^d$ can only take two values $g$ and $\\beta$. This binomial nature of the dynamically optimal strategy stands in sharp contrast...... with other known portfolio selection strategies encountered in the literature. A direct comparison shows that the dynamically optimal (time-consistent) strategy outperforms the statically optimal (time-inconsistent) strategy in the problem....
Auction dynamics: A volume constrained MBO scheme
Jacobs, Matt; Merkurjev, Ekaterina; Esedoǧlu, Selim
2018-02-01
We show how auction algorithms, originally developed for the assignment problem, can be utilized in Merriman, Bence, and Osher's threshold dynamics scheme to simulate multi-phase motion by mean curvature in the presence of equality and inequality volume constraints on the individual phases. The resulting algorithms are highly efficient and robust, and can be used in simulations ranging from minimal partition problems in Euclidean space to semi-supervised machine learning via clustering on graphs. In the case of the latter application, numerous experimental results on benchmark machine learning datasets show that our approach exceeds the performance of current state-of-the-art methods, while requiring a fraction of the computation time.
Ling Fiona W.M.
2017-01-01
Full Text Available Rapid prototyping of microchannel gain lots of attention from researchers along with the rapid development of microfluidic technology. The conventional methods carried few disadvantages such as high cost, time consuming, required high operating pressure and temperature and involve expertise in operating the equipment. In this work, new method adapting xurography method is introduced to replace the conventional method of fabrication of microchannels. The novelty in this study is replacing the adhesion film with clear plastic film which was used to cut the design of the microchannel as the material is more suitable for fabricating more complex microchannel design. The microchannel was then mold using polymethyldisiloxane (PDMS and bonded with a clean glass to produce a close microchannel. The microchannel produced had a clean edge indicating good master mold was produced using the cutting plotter and the bonding between the PDMS and glass was good where no leakage was observed. The materials used in this method is cheap and the total time consumed is less than 5 hours where this method is suitable for rapid prototyping of microchannel.
Wave speed in excitable random networks with spatially constrained connections.
Nikita Vladimirov
Full Text Available Very fast oscillations (VFO in neocortex are widely observed before epileptic seizures, and there is growing evidence that they are caused by networks of pyramidal neurons connected by gap junctions between their axons. We are motivated by the spatio-temporal waves of activity recorded using electrocorticography (ECoG, and study the speed of activity propagation through a network of neurons axonally coupled by gap junctions. We simulate wave propagation by excitable cellular automata (CA on random (Erdös-Rényi networks of special type, with spatially constrained connections. From the cellular automaton model, we derive a mean field theory to predict wave propagation. The governing equation resolved by the Fisher-Kolmogorov PDE fails to describe wave speed. A new (hyperbolic PDE is suggested, which provides adequate wave speed v( that saturates with network degree , in agreement with intuitive expectations and CA simulations. We further show that the maximum length of connection is a much better predictor of the wave speed than the mean length. When tested in networks with various degree distributions, wave speeds are found to strongly depend on the ratio of network moments / rather than on mean degree , which is explained by general network theory. The wave speeds are strikingly similar in a diverse set of networks, including regular, Poisson, exponential and power law distributions, supporting our theory for various network topologies. Our results suggest practical predictions for networks of electrically coupled neurons, and our mean field method can be readily applied for a wide class of similar problems, such as spread of epidemics through spatial networks.
Simulated Galactic methanol maser distribution to constrain Milky Way parameters
Quiroga-Nuñez, L. H.; van Langevelde, H. J.; Reid, M. J.; Green, J. A.
2017-08-01
Context. Using trigonometric parallaxes and proper motions of masers associated with massive young stars, the Bar and Spiral Structure Legacy (BeSSeL) survey has reported the most accurate values of the Galactic parameters so far. The determination of these parameters with high accuracy has a widespread impact on Galactic and extragalactic measurements. Aims: This research is aimed at establishing the confidence with which such parameters can be determined. This is relevant for the data published in the context of the BeSSeL survey collaboration, but also for future observations, in particular from the southern hemisphere. In addition, some astrophysical properties of the masers can be constrained, notably the luminosity function. Methods: We have simulated the population of maser-bearing young stars associated with Galactic spiral structure, generating several samples and comparing them with the observed samples used in the BeSSeL survey. Consequently, we checked the determination of Galactic parameters for observational biases introduced by the sample selection. Results: Galactic parameters obtained by the BeSSeL survey do not seem to be biased by the sample selection used. In fact, the published error estimates appear to be conservative for most of the parameters. We show that future BeSSeL data and future observations with southern arrays will improve the Galactic parameters estimates and smoothly reduce their mutual correlation. Moreover, by modeling future parallax data with larger distance values and, thus, greater relative uncertainties for a larger numbers of sources, we found that parallax-distance biasing is an important issue. Hence, using fractional parallax uncertainty in the weighting of the motion data is imperative. Finally, the luminosity function for 6.7 GHz methanol masers was determined, allowing us to estimate the number of Galactic methanol masers.
Constraining Depositional Slope From Sedimentary Structures in Sandy Braided Streams
Lynds, R. M.; Mohrig, D.; Heller, P. L.
2003-12-01
Determination of paleoslopes in ancient fluvial systems has potentially broad application to quantitatively constraining the history of tectonics and paleoclimate in continental sequences. Our method for calculating paleoslopes for sandy braided streams is based upon a simple physical model that establishes depositional skin-frictional shear stresses from assemblages of sedimentary structures and their associated grain size distributions. The addition of a skin-frictional shear stress, with a geometrically determined form-drag shear stress results in a total boundary shear stress which is directly related to water-surface slope averaged over an appropriate spatial scale. In order to apply this model to ancient fluvial systems, it is necessary to measure the following: coarsest suspended sediment size, finest grain size carried in bed load, flow depth, dune height, and dune length. In the rock record, suspended load and bed load can be accurately assessed by well-preserved suspended load deposits ("low-energy" ripples) and bed load deposits (dune foresets). This model predicts an average slope for the North Loup River near Taylor, Nebraska (modern case study) of 2.7 x 10-3. The measured reach-averaged water surface slope for the same reach of the river is 1.37 x 10-3. We suggest that it is possible to calculate the depositional slope of a sandy fluvial system by a factor of approximately two. Additionally, preliminary application of this model to the Lower Jurassic Kayenta Formation throughout the Colorado Plateau provides a promising and consistent evaluation of paleoslope in an ancient and well-preserved, sandy braided stream deposit.
Maxillofacial prostheses challenges in resource constrained regions.
Tetteh, Sophia; Bibb, Richard J; Martin, Simon J
2017-10-24
This study reviewed the current state of maxillofacial rehabilitation in resource-limited nations. A rigorous literature review was undertaken using several technical and clinical databases using a variety of key words pertinent to maxillofacial prosthetic rehabilitation and resource-limited areas. In addition, interviews were conducted with researchers, clinicians and prosthetists that had direct experience of volunteering or working in resource-limited countries. Results from the review and interviews suggest rehabilitating patients in resource-limited countries remains challenging and efforts to improve the situation requires a multifactorial approach. In conclusion, public health awareness programmes to reduce the causation of injuries and bespoke maxillofacial prosthetics training programmes to suit these countries, as opposed to attempting to replicate Western training programmes. It is also possible that usage of locally sourced and cheaper materials and the use of low-cost technologies could greatly improve maxillofacial rehabilitation efforts in these localities. Implications for Rehabilitation More information and support needs to be provided to maxillofacial defect/injuries patients and to their families or guardians in a culturally sensitive manner by governments. The health needs, economic and psychological needs of the patients need to be taken into account during the rehabilitation process by clinicians and healthcare organizations. The possibility of developing training programs to suit these resource limited countries and not necessarily follow conventional fabrication methods must be looked into further by educational entities.
Node Discovery and Interpretation in Unstructured Resource-Constrained Environments
Gechev, Miroslav; Kasabova, Slavyana; Mihovska, Albena D.
2014-01-01
for the discovery, linking and interpretation of nodes in unstructured and resource-constrained network environments and their interrelated and collective use for the delivery of smart services. The model is based on a basic mathematical approach, which describes and predicts the success of human interactions...... in the context of long-term relationships and identifies several key variables in the context of communications in resource-constrained environments. The general theoretical model is described and several algorithms are proposed as part of the node discovery, identification, and linking processes in relation...
L. M. Kimball
2002-01-01
Full Text Available This paper presents an interior point algorithm to solve the multiperiod hydrothermal economic dispatch (HTED. The multiperiod HTED is a large scale nonlinear programming problem. Various optimization methods have been applied to the multiperiod HTED, but most neglect important network characteristics or require decomposition into thermal and hydro subproblems. The algorithm described here exploits the special bordered block diagonal structure and sparsity of the Newton system for the first order necessary conditions to result in a fast efficient algorithm that can account for all network aspects. Applying this new algorithm challenges a conventional method for the use of available hydro resources known as the peak shaving heuristic.
Khan, Amir; Connolly, J.A.D.; Olsen, Nils
2006-01-01
We present a general method to constrain planetary composition and thermal state from an inversion of long-period electromagnetic sounding data. As an example of our approach, we reexamine the problem of inverting lunar day-side transfer functions to constrain the internal structure of the Moon. We...... to significantly influence the inversion results. In order to improve future inferences about lunar composition and thermal state, more electrical conductivity measurements are needed especially for minerals appropriate to the Moon, such as pyrope and almandine....
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.
Constraining the Surface Energy Balance of Snow in Complex Terrain
Lapo, Karl E.
Physically-based snow models form the basis of our understanding of current and future water and energy cycles, especially in mountainous terrain. These models are poorly constrained and widely diverge from each other, demonstrating a poor understanding of the surface energy balance. This research aims to improve our understanding of the surface energy balance in regions of complex terrain by improving our confidence in existing observations and improving our knowledge of remotely sensed irradiances (Chapter 1), critically analyzing the representation of boundary layer physics within land models (Chapter 2), and utilizing relatively novel observations to in the diagnoses of model performance (Chapter 3). This research has improved the understanding of the literal and metaphorical boundary between the atmosphere and land surface. Solar irradiances are difficult to observe in regions of complex terrain, as observations are subject to harsh conditions not found in other environments. Quality control methods were developed to handle these unique conditions. These quality control methods facilitated an analysis of estimated solar irradiances over mountainous environments. Errors in the estimated solar irradiance are caused by misrepresenting the effect of clouds over regions of topography and regularly exceed the range of observational uncertainty (up to 80Wm -2) in all regions examined. Uncertainty in the solar irradiance estimates were especially pronounced when averaging over high-elevation basins, with monthly differences between estimates up to 80Wm-2. These findings can inform the selection of a method for estimating the solar irradiance and suggest several avenues of future research for improving existing methods. Further research probed the relationship between the land surface and atmosphere as it pertains to the stable boundary layers that commonly form over snow-covered surfaces. Stable conditions are difficult to represent, especially for low wind speed
Quesada-Montano, Beatriz; Westerberg, Ida K.; Fuentes-Andino, Diana; Hidalgo-Leon, Hugo; Halldin, Sven
2017-04-01
Long-term hydrological data are key to understanding catchment behaviour and for decision making within water management and planning. Given the lack of observed data in many regions worldwide, hydrological models are an alternative for reproducing historical streamflow series. Additional types of information - to locally observed discharge - can be used to constrain model parameter uncertainty for ungauged catchments. Climate variability exerts a strong influence on streamflow variability on long and short time scales, in particular in the Central-American region. We therefore explored the use of climate variability knowledge to constrain the simulated discharge uncertainty of a conceptual hydrological model applied to a Costa Rican catchment, assumed to be ungauged. To reduce model uncertainty we first rejected parameter relationships that disagreed with our understanding of the system. We then assessed how well climate-based constraints applied at long-term, inter-annual and intra-annual time scales could constrain model uncertainty. Finally, we compared the climate-based constraints to a constraint on low-flow statistics based on information obtained from global maps. We evaluated our method in terms of the ability of the model to reproduce the observed hydrograph and the active catchment processes in terms of two efficiency measures, a statistical consistency measure, a spread measure and 17 hydrological signatures. We found that climate variability knowledge was useful for reducing model uncertainty, in particular, unrealistic representation of deep groundwater processes. The constraints based on global maps of low-flow statistics provided more constraining information than those based on climate variability, but the latter rejected slow rainfall-runoff representations that the low flow statistics did not reject. The use of such knowledge, together with information on low-flow statistics and constraints on parameter relationships showed to be useful to
An experimental comparison of some heuristics for cardinality constrained bin packing problem
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.
Automatic Bayes Factors for Testing Equality- and Inequality-Constrained Hypotheses on Variances.
Böing-Messing, Florian; Mulder, Joris
2018-05-03
In comparing characteristics of independent populations, researchers frequently expect a certain structure of the population variances. These expectations can be formulated as hypotheses with equality and/or inequality constraints on the variances. In this article, we consider the Bayes factor for testing such (in)equality-constrained hypotheses on variances. Application of Bayes factors requires specification of a prior under every hypothesis to be tested. However, specifying subjective priors for variances based on prior information is a difficult task. We therefore consider so-called automatic or default Bayes factors. These methods avoid the need for the user to specify priors by using information from the sample data. We present three automatic Bayes factors for testing variances. The first is a Bayes factor with equal priors on all variances, where the priors are specified automatically using a small share of the information in the sample data. The second is the fractional Bayes factor, where a fraction of the likelihood is used for automatic prior specification. The third is an adjustment of the fractional Bayes factor such that the parsimony of inequality-constrained hypotheses is properly taken into account. The Bayes factors are evaluated by investigating different properties such as information consistency and large sample consistency. Based on this evaluation, it is concluded that the adjusted fractional Bayes factor is generally recommendable for testing equality- and inequality-constrained hypotheses on variances.
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.
Coherent Structures and Entropy in Constrained, Modulationally Unstable, Nonintegrable Systems
Rumpf, Benno; Newell, Alan C.
2001-01-01
Many studies have shown that nonintegrable systems with modulational instabilities constrained by more than one conservation law exhibit universal long time behavior involving large coherent structures in a sea of small fluctuations. We show how this behavior can be explained in detail by simple thermodynamic arguments
Invariant set computation for constrained uncertain discrete-time systems
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
Applications of a Constrained Mechanics Methodology in Economics
Janova, Jitka
2011-01-01
This paper presents instructive interdisciplinary applications of constrained mechanics calculus in economics on a level appropriate for undergraduate physics education. The aim of the paper is (i) to meet the demand for illustrative examples suitable for presenting the background of the highly expanding research field of econophysics even at the…
Excision technique in constrained formulations of Einstein equations: collapse scenario
Cordero-Carrión, I; Vasset, N; Novak, J; Jaramillo, J L
2015-01-01
We present a new excision technique used in constrained formulations of Einstein equations to deal with black hole in numerical simulations. We show the applicability of this scheme in several scenarios. In particular, we present the dynamical evolution of the collapse of a neutron star to a black hole, using the CoCoNuT code and this excision technique. (paper)
Constraining the evolution of the Hubble Parameter using cosmic chronometers
Dickinson, Hugh
2017-08-01
Substantial investment is being made in space- and ground-based missions with the goal of revealing the nature of the observed cosmic acceleration. This is one of the most important unsolved problems in cosmology today.We propose here to constrain the evolution of the Hubble parameter [H(z)] between 1.3 fundamental nature of dark energy.
Nonmonotonic Skeptical Consequence Relation in Constrained Default Logic
Mihaiela Lupea
2010-12-01
Full Text Available This paper presents a study of the nonmonotonic consequence relation which models the skeptical reasoning formalised by constrained default logic. The nonmonotonic skeptical consequence relation is defined using the sequent calculus axiomatic system. We study the formal properties desirable for a good nonmonotonic relation: supraclassicality, cut, cautious monotony, cumulativity, absorption, distribution.
Evaluation of constrained mobility for programmability in network management
Bohoris, C.; Liotta, A.; Pavlou, G.; Ambler, A.P.; Calo, S.B.; Kar, G.
2000-01-01
In recent years, a significant amount of research work has addressed the use of code mobility in network management. In this paper, we introduce first three aspects of code mobility and argue that constrained mobility offers a natural and easy approach to network management programmability. While
Testing a Constrained MPC Controller in a Process Control Laboratory
Ricardez-Sandoval, Luis A.; Blankespoor, Wesley; Budman, Hector M.
2010-01-01
This paper describes an experiment performed by the fourth year chemical engineering students in the process control laboratory at the University of Waterloo. The objective of this experiment is to test the capabilities of a constrained Model Predictive Controller (MPC) to control the operation of a Double Pipe Heat Exchanger (DPHE) in real time.…
Constrained variational calculus for higher order classical field theories
Campos, Cedric M; De Leon, Manuel; De Diego, David MartIn, E-mail: cedricmc@icmat.e, E-mail: mdeleon@icmat.e, E-mail: david.martin@icmat.e [Instituto de Ciencias Matematicas, CSIC-UAM-UC3M-UCM, Serrano 123, 28006 Madrid (Spain)
2010-11-12
We develop an intrinsic geometrical setting for higher order constrained field theories. As a main tool we use an appropriate generalization of the classical Skinner-Rusk formalism. Some examples of applications are studied, in particular to the geometrical description of optimal control theory for partial differential equations.
Identification of different geologic units using fuzzy constrained resistivity tomography
Singh, Anand; Sharma, S. P.
2018-01-01
Different geophysical inversion strategies are utilized as a component of an interpretation process that tries to separate geologic units based on the resistivity distribution. In the present study, we present the results of separating different geologic units using fuzzy constrained resistivity tomography. This was accomplished using fuzzy c means, a clustering procedure to improve the 2D resistivity image and geologic separation within the iterative minimization through inversion. First, we developed a Matlab-based inversion technique to obtain a reliable resistivity image using different geophysical data sets (electrical resistivity and electromagnetic data). Following this, the recovered resistivity model was converted into a fuzzy constrained resistivity model by assigning the highest probability value of each model cell to the cluster utilizing fuzzy c means clustering procedure during the iterative process. The efficacy of the algorithm is demonstrated using three synthetic plane wave electromagnetic data sets and one electrical resistivity field dataset. The presented approach shows improvement on the conventional inversion approach to differentiate between different geologic units if the correct number of geologic units will be identified. Further, fuzzy constrained resistivity tomography was performed to examine the augmentation of uranium mineralization in the Beldih open cast mine as a case study. We also compared geologic units identified by fuzzy constrained resistivity tomography with geologic units interpreted from the borehole information.
Constrained variational calculus for higher order classical field theories
Campos, Cedric M; De Leon, Manuel; De Diego, David MartIn
2010-01-01
We develop an intrinsic geometrical setting for higher order constrained field theories. As a main tool we use an appropriate generalization of the classical Skinner-Rusk formalism. Some examples of applications are studied, in particular to the geometrical description of optimal control theory for partial differential equations.
Bounds on the capacity of constrained two-dimensional codes
Forchhammer, Søren; Justesen, Jørn
2000-01-01
Bounds on the capacity of constrained two-dimensional (2-D) codes are presented. The bounds of Calkin and Wilf apply to first-order symmetric constraints. The bounds are generalized in a weaker form to higher order and nonsymmetric constraints. Results are given for constraints specified by run-l...
The balance of payment-constrained economic growth in Ethiopia ...
The objective of this paper is to empirically test the validity of the simplified version of the balance of payment-constrained economic growth model for Ethiopia during the period 1971-20082. According to the model, economies only grow at a pace allowed by the constraints imposed by the requirement of balance of payment ...
Toward cognitively constrained models of language processing : A review
Vogelzang, Margreet; Mills, Anne C.; Reitter, David; van Rij, Jacolien; Hendriks, Petra; van Rijn, Hedderik
2017-01-01
Language processing is not an isolated capacity, but is embedded in other aspects of our cognition. However, it is still largely unexplored to what extent and how language processing interacts with general cognitive resources. This question can be investigated with cognitively constrained
The Balance of Payment-Constrained Economic Growth in Ethiopia ...
Administrator
Page 100 financial liberalization and export promotion strategy necessarily lead to better growth performance. Rather, one should consider not only exports of goods and services, but also the income elasticity of imports. The balance of payments-constrained growth model postulates that the rate of growth in any country is ...
Evaluating potentialities and constrains of Problem Based Learning curriculum
Guerra, Aida
2013-01-01
This paper presents a research design to evaluate Problem Based Learning (PBL) curriculum potentialities and constrains for future changes. PBL literature lacks examples of how to evaluate and analyse established PBL learning environments to address new challenges posed. The research design......) in the curriculum and a mean to choose cases for further case study (third phase)....
Constrained relationship agency as the risk factor for intimate ...
We used structural equation modelling to identify and measure constrained relationship agency (CRA) as a latent variable, and then tested the hypothesis that CRA plays a significant role in the pathway between IPV and transactional sex. After controlling for CRA, receiving more material goods from a sexual partner was ...
Chance-constrained optimization of demand response to price signals
Dorini, Gianluca Fabio; Pinson, Pierre; Madsen, Henrik
2013-01-01
within a recursive least squares (RLS) framework using data measurable at the grid level, in an adaptive fashion. Optimal price signals are generated by embedding the FIR models within a chance-constrained optimization framework. The objective is to keep the price signal as unchanged as possible from...
Dark matter, constrained minimal supersymmetric standard model, and lattice QCD.
Giedt, Joel; Thomas, Anthony W; Young, Ross D
2009-11-13
Recent lattice measurements have given accurate estimates of the quark condensates in the proton. We use these results to significantly improve the dark matter predictions in benchmark models within the constrained minimal supersymmetric standard model. The predicted spin-independent cross sections are at least an order of magnitude smaller than previously suggested and our results have significant consequences for dark matter searches.
Constrained Quantum Mechanics: Chaos in Non-Planar Billiards
Salazar, R.; Tellez, G.
2012-01-01
We illustrate some of the techniques to identify chaos signatures at the quantum level using as guiding examples some systems where a particle is constrained to move on a radial symmetric, but non-planar, surface. In particular, two systems are studied: the case of a cone with an arbitrary contour or "dunce hat billiard" and the rectangular…
Constrained control of a once-through boiler with recirculation
Trangbæk, K
2008-01-01
There is an increasing need to operate power plants at low load for longer periods of time. When a once-through boiler operates at a sufficiently low load, recirculation is introduced, significantly altering the control structure. This paper illustrates the possibilities for using constrained con...
On the Integrated Job Scheduling and Constrained Network Routing Problem
Gamst, Mette
This paper examines the NP-hard problem of scheduling a number of jobs on a finite set of machines such that the overall profit of executed jobs is maximized. Each job demands a number of resources, which must be sent to the executing machine via constrained paths. Furthermore, two resource demand...
Effective Teaching of Economics: A Constrained Optimization Problem?
Hultberg, Patrik T.; Calonge, David Santandreu
2017-01-01
One of the fundamental tenets of economics is that decisions are often the result of optimization problems subject to resource constraints. Consumers optimize utility, subject to constraints imposed by prices and income. As economics faculty, instructors attempt to maximize student learning while being constrained by their own and students'…
Vacuum expectation values in a scalar constrained theory
Alonso, F.; Julve, J.; Tiemblo, A.
1985-01-01
A class of finite Green functions in the context of a scalar constrained theory is studied. In a particular model the one-point GFs show that the vacuum expectation values for some fields vanish while one of them remains finite, a feature exhibited by the Goldstone and Higgs fields respectively. (orig.)
Lagrangian formalism for constrained systems. 2. Gauge symmetries
Pyatov, P.N.
1990-01-01
Using the Lagrangian formalism for constrained systems all gauge symmetries peculiar for a given Lagrangian system and in establishing the relation between them and the constraints are constructed. Besides, the question about the possible dependence of gauge transformations on accelerations and other higher order time derivatives of coordinates is clarified. 14 refs
Factors constraining accessibility and usage of information among ...
Various factors may negatively impact on information acquisition and utilisation. To improve understanding of the determinants of information acquisition and utilisation, this study investigated the factors constraining accessibility and usage of poultry management information in three rural districts of Tanzania. The findings ...
Constrained Geocast to Support Cooperative Adaptive Cruise Control (CACC) Merging
Klein Wolterink, W.; Heijenk, Geert; Karagiannis, Georgios
2010-01-01
In this paper we introduce a new geocasting concept to target vehicles based on where they will be in the direct future, in stead of their current position. We refer to this concept as constrained geocast. This may be useful in situations where vehicles have interdependencies based on (future)
Son, Junbo; Zhou, Shiyu; Sankavaram, Chaitanya; Du, Xinyu; Zhang, Yilu
2016-01-01
In this paper, a statistical prognostic method to predict the remaining useful life (RUL) of individual units based on noisy condition monitoring signals is proposed. The prediction accuracy of existing data-driven prognostic methods depends on the capability of accurately modeling the evolution of condition monitoring (CM) signals. Therefore, it is inevitable that the RUL prediction accuracy depends on the amount of random noise in CM signals. When signals are contaminated by a large amount of random noise, RUL prediction even becomes infeasible in some cases. To mitigate this issue, a robust RUL prediction method based on constrained Kalman filter is proposed. The proposed method models the CM signals subject to a set of inequality constraints so that satisfactory prediction accuracy can be achieved regardless of the noise level of signal evolution. The advantageous features of the proposed RUL prediction method is demonstrated by both numerical study and case study with real world data from automotive lead-acid batteries. - Highlights: • A computationally efficient constrained Kalman filter is proposed. • Proposed filter is integrated into an online failure prognosis framework. • A set of proper constraints significantly improves the failure prediction accuracy. • Promising results are reported in the application of battery failure prognosis.
W. Li
2017-11-01
Full Text Available The use of dynamic global vegetation models (DGVMs to estimate CO2 emissions from land-use and land-cover change (LULCC offers a new window to account for spatial and temporal details of emissions and for ecosystem processes affected by LULCC. One drawback of LULCC emissions from DGVMs, however, is lack of observation constraint. Here, we propose a new method of using satellite- and inventory-based biomass observations to constrain historical cumulative LULCC emissions (ELUCc from an ensemble of nine DGVMs based on emerging relationships between simulated vegetation biomass and ELUCc. This method is applicable on the global and regional scale. The original DGVM estimates of ELUCc range from 94 to 273 PgC during 1901–2012. After constraining by current biomass observations, we derive a best estimate of 155 ± 50 PgC (1σ Gaussian error. The constrained LULCC emissions are higher than prior DGVM values in tropical regions but significantly lower in North America. Our emergent constraint approach independently verifies the median model estimate by biomass observations, giving support to the use of this estimate in carbon budget assessments. The uncertainty in the constrained ELUCc is still relatively large because of the uncertainty in the biomass observations, and thus reduced uncertainty in addition to increased accuracy in biomass observations in the future will help improve the constraint. This constraint method can also be applied to evaluate the impact of land-based mitigation activities.
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.
Constraining the surface properties of effective Skyrme interactions
Jodon, R.; Bender, M.; Bennaceur, K.; Meyer, J.
2016-08-01
Background: Deformation energy surfaces map how the total binding energy of a nuclear system depends on the geometrical properties of intrinsic configurations, thereby providing a powerful tool to interpret nuclear spectroscopy and large-amplitude collective-motion phenomena such as fission. The global behavior of the deformation energy is known to be directly connected to the surface properties of the effective interaction used for its calculation. Purpose: The precise control of surface properties during the parameter adjustment of an effective interaction is key to obtain a reliable and predictive description of nuclear properties. The most relevant indicator is the surface-energy coefficient asurf. There are several possibilities for its definition and estimation, which are not fully equivalent and require a computational effort that can differ by orders of magnitude. The purpose of this study is threefold: first, to identify a scheme for the determination of asurf that offers the best compromise between robustness, precision, and numerical efficiency; second, to analyze the correlation between values for asurf and the characteristic energies of the fission barrier of 240Pu; and third, to lay out an efficient and robust procedure for how the deformation properties of the Skyrme energy density functional (EDF) can be constrained during the parameter fit. Methods: There are several frequently used possibilities to define and calculate the surface energy coefficient asurf of effective interactions built for the purpose of self-consistent mean-field calculations. The most direct access is provided by the model system of semi-infinite nuclear matter, but asurf can also be extracted from the systematics of binding energies of finite nuclei. Calculations can be carried out either self-consistently [Hartree-Fock (HF)], which incorporates quantal shell effects, or in one of the semiclassical extended Thomas-Fermi (ETF) or modified Thomas-Fermi (MTF) approximations. The
Phillips, Jordan J; Peralta, Juan E
2011-11-14
We introduce a method for evaluating magnetic exchange couplings based on the constrained density functional theory (C-DFT) approach of Rudra, Wu, and Van Voorhis [J. Chem. Phys. 124, 024103 (2006)]. Our method shares the same physical principles as C-DFT but makes use of the fact that the electronic energy changes quadratically and bilinearly with respect to the constraints in the range of interest. This allows us to use coupled perturbed Kohn-Sham spin density functional theory to determine approximately the corrections to the energy of the different spin configurations and construct a priori the relevant energy-landscapes obtained by constrained spin density functional theory. We assess this methodology in a set of binuclear transition-metal complexes and show that it reproduces very closely the results of C-DFT. This demonstrates a proof-of-concept for this method as a potential tool for studying a number of other molecular phenomena. Additionally, routes to improving upon the limitations of this method are discussed. © 2011 American Institute of Physics
CLFs-based optimization control for a class of constrained visual servoing systems.
Song, Xiulan; Miaomiao, Fu
2017-03-01
In this paper, we use the control Lyapunov function (CLF) technique to present an optimized visual servo control method for constrained eye-in-hand robot visual servoing systems. With the knowledge of camera intrinsic parameters and depth of target changes, visual servo control laws (i.e. translation speed) with adjustable parameters are derived by image point features and some known CLF of the visual servoing system. The Fibonacci method is employed to online compute the optimal value of those adjustable parameters, which yields an optimized control law to satisfy constraints of the visual servoing system. The Lyapunov's theorem and the properties of CLF are used to establish stability of the constrained visual servoing system in the closed-loop with the optimized control law. One merit of the presented method is that there is no requirement of online calculating the pseudo-inverse of the image Jacobian's matrix and the homography matrix. Simulation and experimental results illustrated the effectiveness of the method proposed here. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.
Satheesh Kumar, S.S.; Raghu, T.
2014-01-01
Highlights: • High purity aluminium sheets constrained groove pressed up to plastic strain of 5.8. • Microstructural evolution studied by TEM and X-ray diffraction profile analysis. • Ultrafine grained structure with grain size ∼900 nm achieved in sheets. • Yield strength increased by 5.3 times and tensile strength doubled after first pass. • Enhanced deformation homogeneity seen with increased accumulated plastic strain. - Abstract: High purity aluminium sheets (∼99.9%) are subjected to intense plastic straining by constrained groove pressing method successfully up to 5 passes thereby imparting an effective plastic strain of 5.8. Transmission electron microscopy studies of constrained groove pressed sheets divulged significant grain refinement and the average grain sizes obtained after five pass is estimated to be ∼0.9 μm. In addition to that, microstructural evolution of constrained groove pressed sheets is characterized by X-ray diffraction peak profile analysis employing Williamson–Hall method and the results obtained fairly concur with electron microscopy findings. The tensile behaviour evolution with increased straining indicates substantial improvement of yield strength by ∼5.3 times from 17 MPa to 90 MPa during first pass corroborated to grain refinement observed. Marginal increase in strengths is noticed during second pass followed by minor drop in strengths attributed to predominance of dislocation recovery is noticed in subsequent passes. Quantitative assessment of degree of deformation homogeneity using microhardness profiles reveal relatively better strain homogeneity at higher number of passes
Modeling of Passive Constrained Layer Damping as Applied to a Gun Tube
Margaret Z. Kiehl
2001-01-01
Full Text Available We study the damping effects of a cantilever beam system consisting of a gun tube wrapped with a constrained viscoelastic polymer on terrain induced vibrations. A time domain solution to the forced motion of this system is developed using the GHM (Golla-Hughes-McTavish method to incorporate the viscoelastic properties of the polymer. An impulse load is applied at the free end and the tip deflection of the cantilevered beam system is determined. The resulting GHM equations are then solved in MATLAB by transformation to the state-space domain.
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.
Neutrino-Electron Scattering in MINERvA for Constraining the NuMI Neutrino Flux
Park, Jaewon [Univ. of Rochester, NY (United States)
2013-01-01
Neutrino-electron elastic scattering is used as a reference process to constrain the neutrino flux at the Main Injector (NuMI) beam observed by the MINERvA experiment. Prediction of the neutrino flux at accelerator experiments from other methods has a large uncertainty, and this uncertainty degrades measurements of neutrino oscillations and neutrino cross-sections. Neutrino-electron elastic scattering is a rare process, but its cross-section is precisely known. With a sample corresponding to $3.5\\times10^{20}$ protons on target in the NuMI low-energy neutrino beam, a sample of $120$ $\
A Few Expanding Integrable Models, Hamiltonian Structures and Constrained Flows
Zhang Yufeng
2011-01-01
Two kinds of higher-dimensional Lie algebras and their loop algebras are introduced, for which a few expanding integrable models including the coupling integrable couplings of the Broer-Kaup (BK) hierarchy and the dispersive long wave (DLW) hierarchy as well as the TB hierarchy are obtained. From the reductions of the coupling integrable couplings, the corresponding coupled integrable couplings of the BK equation, the DLW equation, and the TB equation are obtained, respectively. Especially, the coupling integrable coupling of the TB equation reduces to a few integrable couplings of the well-known mKdV equation. The Hamiltonian structures of the coupling integrable couplings of the three kinds of soliton hierarchies are worked out, respectively, by employing the variational identity. Finally, we decompose the BK hierarchy of evolution equations into x-constrained flows and t n -constrained flows whose adjoint representations and the Lax pairs are given. (general)
Transient thermal stresses in a circular cylinder with constrained ends
Goshima, Takahito; Miyao, Kaju
1986-01-01
This paker deals with the transient thermal stresses in a finite circular cylinder constrained at both end surfaces and subjected to axisymmetric temperature distribution on the lateral surface. The thermoelastic problem is formulated in terms of a thermoelastic displacement potential and three harmonic stress functions. Numerical calculations are carried out for the case of the uniform temperature distribution on the lateral surface. The stress distributions on the constrained end and the free suface are shown graphically, and the singularity in stresses appearing at the circumferencial edge is considered. Moreover, the approximate solution based upon the plane strain theory is introduced in order to compare the rigorous one, and it is considered how the length of the cylinder and the time proceeds affect on the accuracy of the approximation. (author)
Dark matter scenarios in a constrained model with Dirac gauginos
Goodsell, Mark D.; Müller, Tobias; Porod, Werner; Staub, Florian
2015-01-01
We perform the first analysis of Dark Matter scenarios in a constrained model with Dirac Gauginos. The model under investigation is the Constrained Minimal Dirac Gaugino Supersymmetric Standard model (CMDGSSM) where the Majorana mass terms of gauginos vanish. However, $R$-symmetry is broken in the Higgs sector by an explicit and/or effective $B_\\mu$-term. This causes a mass splitting between Dirac states in the fermion sector and the neutralinos, which provide the dark matter candidate, become pseudo-Dirac states. We discuss two scenarios: the universal case with all scalar masses unified at the GUT scale, and the case with non-universal Higgs soft-terms. We identify different regions in the parameter space which fullfil all constraints from the dark matter abundance, the limits from SUSY and direct dark matter searches and the Higgs mass. Most of these points can be tested with the next generation of direct dark matter detection experiments.
Constraining the noncommutative spectral action via astrophysical observations.
Nelson, William; Ochoa, Joseph; Sakellariadou, Mairi
2010-09-03
The noncommutative spectral action extends our familiar notion of commutative spaces, using the data encoded in a spectral triple on an almost commutative space. Varying a rather simple action, one can derive all of the standard model of particle physics in this setting, in addition to a modified version of Einstein-Hilbert gravity. In this Letter we use observations of pulsar timings, assuming that no deviation from general relativity has been observed, to constrain the gravitational sector of this theory. While the bounds on the coupling constants remain rather weak, they are comparable to existing bounds on deviations from general relativity in other settings and are likely to be further constrained by future observations.
Constraint-Based Local Search for Constrained Optimum Paths Problems
Pham, Quang Dung; Deville, Yves; van Hentenryck, Pascal
Constrained Optimum Path (COP) problems arise in many real-life applications and are ubiquitous in communication networks. They have been traditionally approached by dedicated algorithms, which are often hard to extend with side constraints and to apply widely. This paper proposes a constraint-based local search (CBLS) framework for COP applications, bringing the compositionality, reuse, and extensibility at the core of CBLS and CP systems. The modeling contribution is the ability to express compositional models for various COP applications at a high level of abstraction, while cleanly separating the model and the search procedure. The main technical contribution is a connected neighborhood based on rooted spanning trees to find high-quality solutions to COP problems. The framework, implemented in COMET, is applied to Resource Constrained Shortest Path (RCSP) problems (with and without side constraints) and to the edge-disjoint paths problem (EDP). Computational results show the potential significance of the approach.
A constrained approximation for nuclear barrier penetration and fission
Tang, H.H.K.; Negele, J.W.; Massachusetts Inst. of Tech., Cambridge; Massachusetts Inst. of Tech., Cambridge
1983-01-01
An approximation to the time-dependent mean-field theory for barrier penetration by a nucleus is obtained in terms of constrained Hartree-Fock wave functions and a coherent velocity field. A discrete approximation to the continuum theory suitable for practical numerical calculations is presented and applied to three illustrative models. Potential application of the theory to the study of nuclear fission is discussed. (orig.)
A Globally Convergent Parallel SSLE Algorithm for Inequality Constrained Optimization
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.
Multivariable controller for discrete stochastic amplitude-constrained systems
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.
Modeling constrained sintering of bi-layered tubular structures
Tadesse Molla, Tesfaye; Kothanda Ramachandran, Dhavanesan; Ni, De Wei
2015-01-01
Constrained sintering of tubular bi-layered structures is being used in the development of various technologies. Densification mismatch between the layers making the tubular bi-layer can generate stresses, which may create processing defects. An analytical model is presented to describe the densi...... and thermo-mechanical analysis. Results from the analytical model are found to agree well with finite element simulations as well as measurements from sintering experiment....
Tree dimension in verification of constrained Horn clauses
Kafle, Bishoksan; Gallagher, John Patrick; Ganty, Pierre
2018-01-01
In this paper, we show how the notion of tree dimension can be used in the verification of constrained Horn clauses (CHCs). The dimension of a tree is a numerical measure of its branching complexity and the concept here applies to Horn clause derivation trees. Derivation trees of dimension zero c...... algorithms using these constructions to decompose a CHC verification problem. One variation of this decomposition considers derivations of successively increasing dimension. The paper includes descriptions of implementations and experimental results....
Distributionally Robust Joint Chance Constrained Problem under Moment Uncertainty
Ke-wei Ding
2014-01-01
Full Text Available We discuss and develop the convex approximation for robust joint chance constraints under uncertainty of first- and second-order moments. Robust chance constraints are approximated by Worst-Case CVaR constraints which can be reformulated by a semidefinite programming. Then the chance constrained problem can be presented as semidefinite programming. We also find that the approximation for robust joint chance constraints has an equivalent individual quadratic approximation form.
Hydrologic and hydraulic flood forecasting constrained by remote sensing data
Li, Y.; Grimaldi, S.; Pauwels, V. R. N.; Walker, J. P.; Wright, A. J.
2017-12-01
Flooding is one of the most destructive natural disasters, resulting in many deaths and billions of dollars of damages each year. An indispensable tool to mitigate the effect of floods is to provide accurate and timely forecasts. An operational flood forecasting system typically consists of a hydrologic model, converting rainfall data into flood volumes entering the river system, and a hydraulic model, converting these flood volumes into water levels and flood extents. Such a system is prone to various sources of uncertainties from the initial conditions, meteorological forcing, topographic data, model parameters and model structure. To reduce those uncertainties, current forecasting systems are typically calibrated and/or updated using ground-based streamflow measurements, and such applications are limited to well-gauged areas. The recent increasing availability of spatially distributed remote sensing (RS) data offers new opportunities to improve flood forecasting skill. Based on an Australian case study, this presentation will discuss the use of 1) RS soil moisture to constrain a hydrologic model, and 2) RS flood extent and level to constrain a hydraulic model.The GRKAL hydrological model is calibrated through a joint calibration scheme using both ground-based streamflow and RS soil moisture observations. A lag-aware data assimilation approach is tested through a set of synthetic experiments to integrate RS soil moisture to constrain the streamflow forecasting in real-time.The hydraulic model is LISFLOOD-FP which solves the 2-dimensional inertial approximation of the Shallow Water Equations. Gauged water level time series and RS-derived flood extent and levels are used to apply a multi-objective calibration protocol. The effectiveness with which each data source or combination of data sources constrained the parameter space will be discussed.
Nonlinear Chance Constrained Problems: Optimality Conditions, Regularization and Solvers
Adam, Lukáš; Branda, Martin
2016-01-01
Roč. 170, č. 2 (2016), s. 419-436 ISSN 0022-3239 R&D Projects: GA ČR GA15-00735S Institutional support: RVO:67985556 Keywords : Chance constrained programming * Optimality conditions * Regularization * Algorithms * Free MATLAB codes Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 1.289, year: 2016 http://library.utia.cas.cz/separaty/2016/MTR/adam-0460909.pdf
How market environment may constrain global franchising in emerging markets
Baena Graciá, Verónica
2011-01-01
Although emerging markets are some of the fastest growing economies in the world and represent countries that are experiencing a substantial economic transformation, little is known about the factors influencing country selection for expansion in those markets. In an attempt to enhance the knowledge that managers and scholars have on franchising expansion, the present study examines how market conditions may constrain international diffusion of franchising in emerging markets. They are: i) ge...
Anti-B-B Mixing Constrains Topcolor-Assisted Technicolor
Burdman, Gustavo; Lane, Kenneth; Rador, Tonguc
2000-01-01
We argue that extended technicolor augmented with topcolor requires that all mixing between the third and the first two quark generations resides in the mixing matrix of left-handed down quarks. Then, the anti-B d -B d mixing that occurs in topcolor models constrains the coloron and Z(prime) boson masses to be greater than about 5 TeV. This implies fine tuning of the topcolor couplings to better than 1 percent
Mature Basin Development Portfolio Management in a Resource Constrained Environment
Mandhane, J. M.; Udo, S. D.
2002-01-01
Nigerian Petroleum industry is constantly faced with management of resource constraints stemming from capital and operating budget, availability of skilled manpower, capacity of an existing surface facility, size of well assets, amount of soft and hard information, etceteras. Constrained capital forces the industry to rank subsurface resource and potential before proceeding with preparation of development scenarios. Availability of skilled manpower limits scope of integrated reservoir studies. Level of information forces technical and management to find low-risk development alternative in a limited time. Volume of either oil or natural gas or water or combination of them may be constrained due to design limits of the existing facility, or an external OPEC quota, requires high portfolio management skills.The first part of the paper statistically analyses development portfolio of a mature basin for (a) subsurface resources volume, (b) developed and undeveloped and undeveloped volumes, (c) sweating of wells, and (d) facility assets. The analysis presented conclusively demonstrates that the 80/20 is active in the statistical sample. The 80/20 refers to 80% of the effect coming from the 20% of the cause. The second part of the paper deals with how 80/20 could be applied to manage portfolio for a given set of constraints. Three application examples are discussed. Feedback on implementation of them resulting in focussed resource management with handsome rewards is documented.The statistical analysis and application examples from a mature basin form a way forward for a development portfolio management in an resource constrained environment
Groundwater availability as constrained by hydrogeology and environmental flows.
Watson, Katelyn A; Mayer, Alex S; Reeves, Howard W
2014-01-01
Groundwater pumping from aquifers in hydraulic connection with nearby streams has the potential to cause adverse impacts by decreasing flows to levels below those necessary to maintain aquatic ecosystems. The recent passage of the Great Lakes-St. Lawrence River Basin Water Resources Compact has brought attention to this issue in the Great Lakes region. In particular, the legislation requires the Great Lakes states to enact measures for limiting water withdrawals that can cause adverse ecosystem impacts. This study explores how both hydrogeologic and environmental flow limitations may constrain groundwater availability in the Great Lakes Basin. A methodology for calculating maximum allowable pumping rates is presented. Groundwater availability across the basin may be constrained by a combination of hydrogeologic yield and environmental flow limitations varying over both local and regional scales. The results are sensitive to factors such as pumping time, regional and local hydrogeology, streambed conductance, and streamflow depletion limits. Understanding how these restrictions constrain groundwater usage and which hydrogeologic characteristics and spatial variables have the most influence on potential streamflow depletions has important water resources policy and management implications. © 2013, National Ground Water Association.
Physics constrained nonlinear regression models for time series
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)
A simple two stage optimization algorithm for constrained power economic dispatch
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 New Continuous-Time Equality-Constrained Optimization to Avoid Singularity.
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.
Prior image constrained image reconstruction in emerging computed tomography applications
Brunner, Stephen T.
Advances have been made in computed tomography (CT), especially in the past five years, by incorporating prior images into the image reconstruction process. In this dissertation, we investigate prior image constrained image reconstruction in three emerging CT applications: dual-energy CT, multi-energy photon-counting CT, and cone-beam CT in image-guided radiation therapy. First, we investigate the application of Prior Image Constrained Compressed Sensing (PICCS) in dual-energy CT, which has been called "one of the hottest research areas in CT." Phantom and animal studies are conducted using a state-of-the-art 64-slice GE Discovery 750 HD CT scanner to investigate the extent to which PICCS can enable radiation dose reduction in material density and virtual monochromatic imaging. Second, we extend the application of PICCS from dual-energy CT to multi-energy photon-counting CT, which has been called "one of the 12 topics in CT to be critical in the next decade." Numerical simulations are conducted to generate multiple energy bin images for a photon-counting CT acquisition and to investigate the extent to which PICCS can enable radiation dose efficiency improvement. Third, we investigate the performance of a newly proposed prior image constrained scatter correction technique to correct scatter-induced shading artifacts in cone-beam CT, which, when used in image-guided radiation therapy procedures, can assist in patient localization, and potentially, dose verification and adaptive radiation therapy. Phantom studies are conducted using a Varian 2100 EX system with an on-board imager to investigate the extent to which the prior image constrained scatter correction technique can mitigate scatter-induced shading artifacts in cone-beam CT. Results show that these prior image constrained image reconstruction techniques can reduce radiation dose in dual-energy CT by 50% in phantom and animal studies in material density and virtual monochromatic imaging, can lead to radiation
The Two-stage Constrained Equal Awards and Losses Rules for Multi-Issue Allocation Situation
Lorenzo-Freire, S.; Casas-Mendez, B.; Hendrickx, R.L.P.
2005-01-01
This paper considers two-stage solutions for multi-issue allocation situations.Characterisations are provided for the two-stage constrained equal awards and constrained equal losses rules, based on the properties of composition and path independence.
Zhensheng Wang
2017-02-01
Full Text Available The spatial variation of geographical phenomena is a classical problem in spatial data analysis and can provide insight into underlying processes. Traditional exploratory methods mostly depend on the planar distance assumption, but many spatial phenomena are constrained to a subset of Euclidean space. In this study, we apply a method based on a hierarchical Bayesian model to analyse the spatial variation of network-constrained phenomena represented by a link attribute in conjunction with two experiments based on a simplified hypothetical network and a complex road network in Shenzhen that includes 4212 urban facility points of interest (POIs for leisure activities. Then, the methods named local indicators of network-constrained clusters (LINCS are applied to explore local spatial patterns in the given network space. The proposed method is designed for phenomena that are represented by attribute values of network links and is capable of removing part of random variability resulting from small-sample estimation. The effects of spatial dependence and the base distribution are also considered in the proposed method, which could be applied in the fields of urban planning and safety research.
Free versus constrained evolution of the 2+1 equivariant wave map
Peter, Ralf; Frauendiener, Jörg
2012-01-01
We compare the numerical solutions of the 2+1 equivariant wave map problem computed with the symplectic, constraint respecting Rattle algorithm and the well known fourth order Runge–Kutta method. We show the advantages of the Rattle algorithm for the constrained system compared to the free evolution with the Runge–Kutta method. We also present an expression, which represents the energy loss due to constraint violation. Taking this expression into account we can achieve energy conservation for the Runge–Kutta scheme, which is better than with the Rattle method. Using the symplectic scheme with constraint enforcement, we can reproduce previous calculations of the equivariant case without imposing the symmetry explicitly, thereby confirming that the critical behaviour is stable. (paper)
Uniform discretizations: a quantization procedure for totally constrained systems including gravity
Campiglia, Miguel [Instituto de Fisica, Facultad de Ciencias, Igua 4225, esq. Mataojo, Montevideo (Uruguay); Di Bartolo, Cayetano [Departamento de Fisica, Universidad Simon BolIvar, Aptdo. 89000, Caracas 1080-A (Venezuela); Gambini, Rodolfo [Instituto de Fisica, Facultad de Ciencias, Igua 4225, esq. Mataojo, Montevideo (Uruguay); Pullin, Jorge [Department of Physics and Astronomy, Louisiana State University, Baton Rouge, LA 70803-4001 (United States)
2007-05-15
We present a new method for the quantization of totally constrained systems including general relativity. The method consists in constructing discretized theories that have a well defined and controlled continuum limit. The discrete theories are constraint-free and can be readily quantized. This provides a framework where one can introduce a relational notion of time and that nevertheless approximates in a well defined fashion the theory of interest. The method is equivalent to the group averaging procedure for many systems where the latter makes sense and provides a generalization otherwise. In the continuum limit it can be shown to contain, under certain assumptions, the 'master constraint' of the 'Phoenix project'. It also provides a correspondence principle with the classical theory that does not require to consider the semiclassical limit.
Quan, Zhe; Wu, Lei
2017-09-01
This article investigates the use of parallel computing for solving the disjunctively constrained knapsack problem. The proposed parallel computing model can be viewed as a cooperative algorithm based on a multi-neighbourhood search. The cooperation system is composed of a team manager and a crowd of team members. The team members aim at applying their own search strategies to explore the solution space. The team manager collects the solutions from the members and shares the best one with them. The performance of the proposed method is evaluated on a group of benchmark data sets. The results obtained are compared to those reached by the best methods from the literature. The results show that the proposed method is able to provide the best solutions in most cases. In order to highlight the robustness of the proposed parallel computing model, a new set of large-scale instances is introduced. Encouraging results have been obtained.
YANG Wei
2017-02-01
Full Text Available Extraction of road boundary accurately from crowdsourcing trajectory lines is still a hard work.Therefore,this study presented a new approach to use vehicle trajectory lines to extract road boundary.Firstly, constructing constrained Delaunay triangulation within interpolated track lines to calculate road boundary descriptors using triangle edge length and Voronoi cell.Road boundary recognition model was established by integrating the two boundary descriptors.Then,based on seed polygons,a regional growing method was proposed to extract road boundary. Finally, taxi GPS traces in Beijing were used to verify the validity of the novel method, and the results also showed that our method was suitable for GPS traces with disparity density,complex road structure and different time interval.
Locality constrained joint dynamic sparse representation for local matching based face recognition.
Wang, Jianzhong; Yi, Yugen; Zhou, Wei; Shi, Yanjiao; Qi, Miao; Zhang, Ming; Zhang, Baoxue; Kong, Jun
2014-01-01
Recently, Sparse Representation-based Classification (SRC) has attracted a lot of attention for its applications to various tasks, especially in biometric techniques such as face recognition. However, factors such as lighting, expression, pose and disguise variations in face images will decrease the performances of SRC and most other face recognition techniques. In order to overcome these limitations, we propose a robust face recognition method named Locality Constrained Joint Dynamic Sparse Representation-based Classification (LCJDSRC) in this paper. In our method, a face image is first partitioned into several smaller sub-images. Then, these sub-images are sparsely represented using the proposed locality constrained joint dynamic sparse representation algorithm. Finally, the representation results for all sub-images are aggregated to obtain the final recognition result. Compared with other algorithms which process each sub-image of a face image independently, the proposed algorithm regards the local matching-based face recognition as a multi-task learning problem. Thus, the latent relationships among the sub-images from the same face image are taken into account. Meanwhile, the locality information of the data is also considered in our algorithm. We evaluate our algorithm by comparing it with other state-of-the-art approaches. Extensive experiments on four benchmark face databases (ORL, Extended YaleB, AR and LFW) demonstrate the effectiveness of LCJDSRC.
Dynamically constrained ensemble perturbations – application to tides on the West Florida Shelf
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.
Efficient non-negative constrained model-based inversion in optoacoustic tomography
Ding, Lu; Luís Deán-Ben, X; Lutzweiler, Christian; Razansky, Daniel; Ntziachristos, Vasilis
2015-01-01
The inversion accuracy in optoacoustic tomography depends on a number of parameters, including the number of detectors employed, discrete sampling issues or imperfectness of the forward model. These parameters result in ambiguities on the reconstructed image. A common ambiguity is the appearance of negative values, which have no physical meaning since optical absorption can only be higher or equal than zero. We investigate herein algorithms that impose non-negative constraints in model-based optoacoustic inversion. Several state-of-the-art non-negative constrained algorithms are analyzed. Furthermore, an algorithm based on the conjugate gradient method is introduced in this work. We are particularly interested in investigating whether positive restrictions lead to accurate solutions or drive the appearance of errors and artifacts. It is shown that the computational performance of non-negative constrained inversion is higher for the introduced algorithm than for the other algorithms, while yielding equivalent results. The experimental performance of this inversion procedure is then tested in phantoms and small animals, showing an improvement in image quality and quantitativeness with respect to the unconstrained approach. The study performed validates the use of non-negative constraints for improving image accuracy compared to unconstrained methods, while maintaining computational efficiency. (paper)
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.
Locality constrained joint dynamic sparse representation for local matching based face recognition.
Jianzhong Wang
Full Text Available Recently, Sparse Representation-based Classification (SRC has attracted a lot of attention for its applications to various tasks, especially in biometric techniques such as face recognition. However, factors such as lighting, expression, pose and disguise variations in face images will decrease the performances of SRC and most other face recognition techniques. In order to overcome these limitations, we propose a robust face recognition method named Locality Constrained Joint Dynamic Sparse Representation-based Classification (LCJDSRC in this paper. In our method, a face image is first partitioned into several smaller sub-images. Then, these sub-images are sparsely represented using the proposed locality constrained joint dynamic sparse representation algorithm. Finally, the representation results for all sub-images are aggregated to obtain the final recognition result. Compared with other algorithms which process each sub-image of a face image independently, the proposed algorithm regards the local matching-based face recognition as a multi-task learning problem. Thus, the latent relationships among the sub-images from the same face image are taken into account. Meanwhile, the locality information of the data is also considered in our algorithm. We evaluate our algorithm by comparing it with other state-of-the-art approaches. Extensive experiments on four benchmark face databases (ORL, Extended YaleB, AR and LFW demonstrate the effectiveness of LCJDSRC.
A RSSI-based parameter tracking strategy for constrained position localization
Du, Jinze; Diouris, Jean-François; Wang, Yide
2017-12-01
In this paper, a received signal strength indicator (RSSI)-based parameter tracking strategy for constrained position localization is proposed. To estimate channel model parameters, least mean squares method (LMS) is associated with the trilateration method. In the context of applications where the positions are constrained on a grid, a novel tracking strategy is proposed to determine the real position and obtain the actual parameters in the monitored region. Based on practical data acquired from a real localization system, an experimental channel model is constructed to provide RSSI values and verify the proposed tracking strategy. Quantitative criteria are given to guarantee the efficiency of the proposed tracking strategy by providing a trade-off between the grid resolution and parameter variation. The simulation results show a good behavior of the proposed tracking strategy in the presence of space-time variation of the propagation channel. Compared with the existing RSSI-based algorithms, the proposed tracking strategy exhibits better localization accuracy but consumes more calculation time. In addition, a tracking test is performed to validate the effectiveness of the proposed tracking strategy.
21 CFR 888.3300 - Hip joint metal constrained cemented or uncemented prosthesis.
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...
21 CFR 888.3110 - Ankle joint metal/polymer semi-constrained cemented prosthesis.
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...
Tews, I.; Carlson, J.; Gandolfi, S.; Reddy, S.
2018-06-01
The dense matter equation of state (EOS) determines neutron star (NS) structure but can be calculated reliably only up to one to two times the nuclear saturation density, using accurate many-body methods that employ nuclear interactions from chiral effective field theory constrained by scattering data. In this work, we use physically motivated ansatzes for the speed of sound c S at high density to extend microscopic calculations of neutron-rich matter to the highest densities encountered in stable NS cores. We show how existing and expected astrophysical constraints on NS masses and radii from X-ray observations can constrain the speed of sound in the NS core. We confirm earlier expectations that c S is likely to violate the conformal limit of {c}S2≤slant {c}2/3, possibly reaching values closer to the speed of light c at a few times the nuclear saturation density, independent of the nuclear Hamiltonian. If QCD obeys the conformal limit, we conclude that the rapid increase of c S required to accommodate a 2 M ⊙ NS suggests a form of strongly interacting matter where a description in terms of nucleons will be unwieldy, even between one and two times the nuclear saturation density. For typical NSs with masses in the range of 1.2–1.4 M ⊙, we find radii between 10 and 14 km, and the smallest possible radius of a 1.4 M ⊙ NS consistent with constraints from nuclear physics and observations is 8.4 km. We also discuss how future observations could constrain the EOS and guide theoretical developments in nuclear physics.
Multiple utility constrained multi-objective programs using Bayesian theory
Abbasian, Pooneh; Mahdavi-Amiri, Nezam; Fazlollahtabar, Hamed
2018-03-01
A utility function is an important tool for representing a DM's preference. We adjoin utility functions to multi-objective optimization problems. In current studies, usually one utility function is used for each objective function. Situations may arise for a goal to have multiple utility functions. Here, we consider a constrained multi-objective problem with each objective having multiple utility functions. We induce the probability of the utilities for each objective function using Bayesian theory. Illustrative examples considering dependence and independence of variables are worked through to demonstrate the usefulness of the proposed model.
Constrained Optimization and Optimal Control for Partial Differential Equations
Leugering, Günter; Griewank, Andreas
2012-01-01
This special volume focuses on optimization and control of processes governed by partial differential equations. The contributors are mostly participants of the DFG-priority program 1253: Optimization with PDE-constraints which is active since 2006. The book is organized in sections which cover almost the entire spectrum of modern research in this emerging field. Indeed, even though the field of optimal control and optimization for PDE-constrained problems has undergone a dramatic increase of interest during the last four decades, a full theory for nonlinear problems is still lacking. The cont
Frequency Constrained ShiftCP Modeling of Neuroimaging Data
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...
Dimensionally constrained energy confinement analysis of W7-AS data
Dose, V.; Preuss, R.; Linden, W. von der
1998-01-01
A recently assembled W7-AS stellarator database has been subject to dimensionally constrained confinement analysis. The analysis employs Bayesian inference. Dimensional information is taken from the Connor-Taylor (CT) similarity transformation theory, which provides six possible physical scenarios with associated dimensional conditions. Bayesian theory allows the calculations of the probability for each model and it is found that the present W7-AS data are most probably described by the collisionless high-β case. Probabilities for all models and the associated exponents of a power law scaling function are presented. (author)
Preparation and biological evaluation of conformationally constrained BACE1 inhibitors.
Winneroski, Leonard L; Schiffler, Matthew A; Erickson, Jon A; May, Patrick C; Monk, Scott A; Timm, David E; Audia, James E; Beck, James P; Boggs, Leonard N; Borders, Anthony R; Boyer, Robert D; Brier, Richard A; Hudziak, Kevin J; Klimkowski, Valentine J; Garcia Losada, Pablo; Mathes, Brian M; Stout, Stephanie L; Watson, Brian M; Mergott, Dustin J
2015-07-01
The BACE1 enzyme is a key target for Alzheimer's disease. During our BACE1 research efforts, fragment screening revealed that bicyclic thiazine 3 had low millimolar activity against BACE1. Analysis of the co-crystal structure of 3 suggested that potency could be increased through extension toward the S3 pocket and through conformational constraint of the thiazine core. Pursuit of S3-binding groups produced low micromolar inhibitor 6, which informed the S3-design for constrained analogs 7 and 8, themselves prepared via independent, multi-step synthetic routes. Biological characterization of BACE inhibitors 6-8 is described. Copyright © 2015 Elsevier Ltd. All rights reserved.
Coping strategies and attitudes to food in budget constrained households
Lund, Thomas Bøker; Nielsen, Annemette Ljungdalh; Holm, Lotte
2015-01-01
of food budget constraints (this includes: abstaining from luxury, prioritizing cheaper food, household efficiency) is associated with a reduced risk of obesity. Using a combined dataset with respondents that completed both the 2008 and 2012 questionnaire (approximately N=1080) we then examine whether...... people who (in 2012) report that they are budget restrained have changed food values from 2008 to 2012 (we look at health considerations and importance attached to food quality) Following that, it is analyzed to what extent changes in food attitudes explain the higher obesity levels in the group...... of respondents that are budget constrained....
Constrained generalized mechanics. The second-order case
Tapia, V.
1985-01-01
The Dirac formalism for constrained systems is developed for systems described by a Lagrangian depending on up to a second-order time derivatives of the generalized co-ordinates (accelerations). It turns out that for a Lagrangian of this kind differing by a total time derivative from a Lagrangian depending on only up to first-order time-derivatives of the generalized co-ordinates (velocities), both classical mechanics at the Lagrangian level are the same; at the Hamiltonian level the two classical mechanics differ conceptually even when the solutions to both sets of Hamiltonian equations of motion are the same
Robust stability in constrained predictive control through the Youla parameterisations
Thomsen, Sven Creutz; Niemann, Hans Henrik; Poulsen, Niels Kjølstad
2011-01-01
In this article we take advantage of the primary and dual Youla parameterisations to set up a soft constrained model predictive control (MPC) scheme. In this framework it is possible to guarantee stability in face of norm-bounded uncertainties. Under special conditions guarantees are also given...... for hard input constraints. In more detail, we parameterise the MPC predictions in terms of the primary Youla parameter and use this parameter as the on-line optimisation variable. The uncertainty is parameterised in terms of the dual Youla parameter. Stability can then be guaranteed through small gain...
Constraining dark matter in the MSSM at the LHC
Nojiri, Mihoko M.; Polesello, Giacomo; Tovey, Daniel R.
2006-01-01
In the event that R-Parity conserving supersymmetry (SUSY) is discovered at the LHC, a key issue which will need to be addressed will be the consistency of that signal with astrophysical and non-accelerator constraints on SUSY Dark Matter. This issue is studied for a benchmark model based on measurements of end-points and thresholds in the invariant mass spectra of various combinations of leptons and jets. These measurements are used to constrain the soft SUSY breaking parameters at the electroweak scale in a general MSSM model. Based on these constraints, we assess the accuracy with which the Dark Matter relic density can be measured
Constraining axion dark matter with Big Bang Nucleosynthesis
Blum, Kfir; D' Agnolo, Raffaele Tito [Institute for Advanced Study, Princeton, NJ 08540 (United States); Lisanti, Mariangela; Safdi, Benjamin R. [Department of Physics, Princeton University, Princeton, NJ 08544 (United States)
2014-10-07
We show that Big Bang Nucleosynthesis (BBN) significantly constrains axion-like dark matter. The axion acts like an oscillating QCD θ angle that redshifts in the early Universe, increasing the neutron–proton mass difference at neutron freeze-out. An axion-like particle that couples too strongly to QCD results in the underproduction of {sup 4}He during BBN and is thus excluded. The BBN bound overlaps with much of the parameter space that would be covered by proposed searches for a time-varying neutron EDM. The QCD axion does not couple strongly enough to affect BBN.
Constraining axion dark matter with Big Bang Nucleosynthesis
Kfir Blum
2014-10-01
Full Text Available We show that Big Bang Nucleosynthesis (BBN significantly constrains axion-like dark matter. The axion acts like an oscillating QCD θ angle that redshifts in the early Universe, increasing the neutron–proton mass difference at neutron freeze-out. An axion-like particle that couples too strongly to QCD results in the underproduction of He4 during BBN and is thus excluded. The BBN bound overlaps with much of the parameter space that would be covered by proposed searches for a time-varying neutron EDM. The QCD axion does not couple strongly enough to affect BBN.
Constraining axion dark matter with Big Bang Nucleosynthesis
Blum, Kfir; D'Agnolo, Raffaele Tito; Lisanti, Mariangela; Safdi, Benjamin R.
2014-01-01
We show that Big Bang Nucleosynthesis (BBN) significantly constrains axion-like dark matter. The axion acts like an oscillating QCD θ angle that redshifts in the early Universe, increasing the neutron–proton mass difference at neutron freeze-out. An axion-like particle that couples too strongly to QCD results in the underproduction of 4 He during BBN and is thus excluded. The BBN bound overlaps with much of the parameter space that would be covered by proposed searches for a time-varying neutron EDM. The QCD axion does not couple strongly enough to affect BBN
Constraining axion dark matter with Big Bang Nucleosynthesis
Blum, Kfir; D'Agnolo, Raffaele Tito; Lisanti, Mariangela; Safdi, Benjamin R.
2014-10-01
We show that Big Bang Nucleosynthesis (BBN) significantly constrains axion-like dark matter. The axion acts like an oscillating QCD θ angle that redshifts in the early Universe, increasing the neutron-proton mass difference at neutron freeze-out. An axion-like particle that couples too strongly to QCD results in the underproduction of 4He during BBN and is thus excluded. The BBN bound overlaps with much of the parameter space that would be covered by proposed searches for a time-varying neutron EDM. The QCD axion does not couple strongly enough to affect BBN.
Guyen, Olivier; Lewallen, David G; Cabanela, Miguel E
2008-07-01
The Osteonics constrained tripolar implant has been one of the most commonly used options to manage recurrent instability after total hip arthroplasty. Mechanical failures were expected and have been reported. The purpose of this retrospective review was to identify the observed modes of failure of this device. Forty-three failed Osteonics constrained tripolar implants were revised at our institution between September 1997 and April 2005. All revisions related to the constrained acetabular component only were considered as failures. All of the devices had been inserted for recurrent or intraoperative instability during revision procedures. Seven different methods of implantation were used. Operative reports and radiographs were reviewed to identify the modes of failure. The average time to failure of the forty-three implants was 28.4 months. A total of five modes of failure were observed: failure at the bone-implant interface (type I), which occurred in eleven hips; failure at the mechanisms holding the constrained liner to the metal shell (type II), in six hips; failure of the retaining mechanism of the bipolar component (type III), in ten hips; dislocation of the prosthetic head at the inner bearing of the bipolar component (type IV), in three hips; and infection (type V), in twelve hips. The mode of failure remained unknown in one hip that had been revised at another institution. The Osteonics constrained tripolar total hip arthroplasty implant is a complex device involving many parts. We showed that failure of this device can occur at most of its interfaces. It would therefore appear logical to limit its application to salvage situations.
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
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.
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.
Egg Production Constrains Chemical Defenses in a Neotropical Arachnid.
Taís M Nazareth
Full Text Available Female investment in large eggs increases the demand for fatty acids, which are allocated for yolk production. Since the biosynthetic pathway leading to fatty acids uses the same precursors used in the formation of polyketides, allocation trade-offs are expected to emerge. Therefore, egg production should constrain the investment in chemical defenses based on polyketides, such as benzoquinones. We tested this hypothesis using the harvestman Acutiosoma longipes, which produces large eggs and releases benzoquinones as chemical defense. We predicted that the amount of secretion released by ovigerous females (OFs would be smaller than that of non-ovigerous females (NOF. We also conducted a series of bioassays in the field and in the laboratory to test whether egg production renders OFs more vulnerable to predation. OFs produce less secretion than NOFs, which is congruent with the hypothesis that egg production constrains the investment in chemical defenses. Results of the bioassays show that the secretion released by OFs is less effective in deterring potential predators (ants and spiders than the secretion released by NOFs. In conclusion, females allocate resources to chemical defenses in a way that preserves a primary biological function related to reproduction. However, the trade-off between egg and secretion production makes OFs vulnerable to predators. We suggest that egg production is a critical moment in the life of harvestman females, representing perhaps the highest cost of reproduction in the group.
Butterfly Encryption Scheme for Resource-Constrained Wireless Networks
Raghav V. Sampangi
2015-09-01
Full Text Available Resource-constrained wireless networks are emerging networks such as Radio Frequency Identification (RFID and Wireless Body Area Networks (WBAN that might have restrictions on the available resources and the computations that can be performed. These emerging technologies are increasing in popularity, particularly in defence, anti-counterfeiting, logistics and medical applications, and in consumer applications with growing popularity of the Internet of Things. With communication over wireless channels, it is essential to focus attention on securing data. In this paper, we present an encryption scheme called Butterfly encryption scheme. We first discuss a seed update mechanism for pseudorandom number generators (PRNG, and employ this technique to generate keys and authentication parameters for resource-constrained wireless networks. Our scheme is lightweight, as in it requires less resource when implemented and offers high security through increased unpredictability, owing to continuously changing parameters. Our work focuses on accomplishing high security through simplicity and reuse. We evaluate our encryption scheme using simulation, key similarity assessment, key sequence randomness assessment, protocol analysis and security analysis.
Butterfly Encryption Scheme for Resource-Constrained Wireless Networks.
Sampangi, Raghav V; Sampalli, Srinivas
2015-09-15
Resource-constrained wireless networks are emerging networks such as Radio Frequency Identification (RFID) and Wireless Body Area Networks (WBAN) that might have restrictions on the available resources and the computations that can be performed. These emerging technologies are increasing in popularity, particularly in defence, anti-counterfeiting, logistics and medical applications, and in consumer applications with growing popularity of the Internet of Things. With communication over wireless channels, it is essential to focus attention on securing data. In this paper, we present an encryption scheme called Butterfly encryption scheme. We first discuss a seed update mechanism for pseudorandom number generators (PRNG), and employ this technique to generate keys and authentication parameters for resource-constrained wireless networks. Our scheme is lightweight, as in it requires less resource when implemented and offers high security through increased unpredictability, owing to continuously changing parameters. Our work focuses on accomplishing high security through simplicity and reuse. We evaluate our encryption scheme using simulation, key similarity assessment, key sequence randomness assessment, protocol analysis and security analysis.
Constraining dark sector perturbations I: cosmic shear and CMB lensing
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
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.
Autonomous Navigation with Constrained Consistency for C-Ranger
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.
Calcium constrains plant control over forest ecosystem nitrogen cycling.
Groffman, Peter M; Fisk, Melany C
2011-11-01
Forest ecosystem nitrogen (N) cycling is a critical controller of the ability of forests to prevent the movement of reactive N to receiving waters and the atmosphere and to sequester elevated levels of atmospheric carbon dioxide (CO2). Here we show that calcium (Ca) constrains the ability of northern hardwood forest trees to control the availability and loss of nitrogen. We evaluated soil N-cycling response to Ca additions in the presence and absence of plants and observed that when plants were present, Ca additions "tightened" the ecosystem N cycle, with decreases in inorganic N levels, potential net N mineralization rates, microbial biomass N content, and denitrification potential. In the absence of plants, Ca additions induced marked increases in nitrification (the key process controlling ecosystem N losses) and inorganic N levels. The observed "tightening" of the N cycle when Ca was added in the presence of plants suggests that the capacity of forests to absorb elevated levels of atmospheric N and CO2 is fundamentally constrained by base cations, which have been depleted in many areas of the globe by acid rain and forest harvesting.
An inexact fuzzy-chance-constrained air quality management model.
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.
Multiplicative algorithms for constrained non-negative matrix factorization
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.
Constrained Sintering in Fabrication of Solid Oxide Fuel Cells.
Lee, Hae-Weon; Park, Mansoo; Hong, Jongsup; Kim, Hyoungchul; Yoon, Kyung Joong; Son, Ji-Won; Lee, Jong-Ho; Kim, Byung-Kook
2016-08-09
Solid oxide fuel cells (SOFCs) are inevitably affected by the tensile stress field imposed by the rigid substrate during constrained sintering, which strongly affects microstructural evolution and flaw generation in the fabrication process and subsequent operation. In the case of sintering a composite cathode, one component acts as a continuous matrix phase while the other acts as a dispersed phase depending upon the initial composition and packing structure. The clustering of dispersed particles in the matrix has significant effects on the final microstructure, and strong rigidity of the clusters covering the entire cathode volume is desirable to obtain stable pore structure. The local constraints developed around the dispersed particles and their clusters effectively suppress generation of major process flaws, and microstructural features such as triple phase boundary and porosity could be readily controlled by adjusting the content and size of the dispersed particles. However, in the fabrication of the dense electrolyte layer via the chemical solution deposition route using slow-sintering nanoparticles dispersed in a sol matrix, the rigidity of the cluster should be minimized for the fine matrix to continuously densify, and special care should be taken in selecting the size of the dispersed particles to optimize the thermodynamic stability criteria of the grain size and film thickness. The principles of constrained sintering presented in this paper could be used as basic guidelines for realizing the ideal microstructure of SOFCs.
Data-constrained reionization and its effects on cosmological parameters
Pandolfi, S.; Ferrara, A.; Choudhury, T. Roy; Mitra, S.; Melchiorri, A.
2011-01-01
We perform an analysis of the recent WMAP7 data considering physically motivated and viable reionization scenarios with the aim of assessing their effects on cosmological parameter determinations. The main novelties are: (i) the combination of cosmic microwave background data with astrophysical results from quasar absorption line experiments; (ii) the joint variation of both the cosmological and astrophysical [governing the evolution of the free electron fraction x e (z)] parameters. Including a realistic, data-constrained reionization history in the analysis induces appreciable changes in the cosmological parameter values deduced through a standard WMAP7 analysis. Particularly noteworthy are the variations in Ω b h 2 =0.02258 -0.00056 +0.00057 [WMAP7 (Sudden)] vs Ω b h 2 =0.02183±0.00054[WMAP7+ASTRO (CF)] and the new constraints for the scalar spectral index, for which WMAP7+ASTRO (CF) excludes the Harrison-Zel'dovich value n s =1 at >3σ. Finally, the electron-scattering optical depth value is considerably decreased with respect to the standard WMAP7, i.e. τ e =0.080±0.012. We conclude that the inclusion of astrophysical data sets, allowing to robustly constrain the reionization history, in the extraction procedure of cosmological parameters leads to relatively important differences in the final determination of their values.
Constrained Sintering in Fabrication of Solid Oxide Fuel Cells
Lee, Hae-Weon; Park, Mansoo; Hong, Jongsup; Kim, Hyoungchul; Yoon, Kyung Joong; Son, Ji-Won; Lee, Jong-Ho; Kim, Byung-Kook
2016-01-01
Solid oxide fuel cells (SOFCs) are inevitably affected by the tensile stress field imposed by the rigid substrate during constrained sintering, which strongly affects microstructural evolution and flaw generation in the fabrication process and subsequent operation. In the case of sintering a composite cathode, one component acts as a continuous matrix phase while the other acts as a dispersed phase depending upon the initial composition and packing structure. The clustering of dispersed particles in the matrix has significant effects on the final microstructure, and strong rigidity of the clusters covering the entire cathode volume is desirable to obtain stable pore structure. The local constraints developed around the dispersed particles and their clusters effectively suppress generation of major process flaws, and microstructural features such as triple phase boundary and porosity could be readily controlled by adjusting the content and size of the dispersed particles. However, in the fabrication of the dense electrolyte layer via the chemical solution deposition route using slow-sintering nanoparticles dispersed in a sol matrix, the rigidity of the cluster should be minimized for the fine matrix to continuously densify, and special care should be taken in selecting the size of the dispersed particles to optimize the thermodynamic stability criteria of the grain size and film thickness. The principles of constrained sintering presented in this paper could be used as basic guidelines for realizing the ideal microstructure of SOFCs. PMID:28773795
Constraining Alternative Theories of Gravity Using Pulsar Timing Arrays
Cornish, Neil J.; O'Beirne, Logan; Taylor, Stephen R.; Yunes, Nicolás
2018-05-01
The opening of the gravitational wave window by ground-based laser interferometers has made possible many new tests of gravity, including the first constraints on polarization. It is hoped that, within the next decade, pulsar timing will extend the window by making the first detections in the nanohertz frequency regime. Pulsar timing offers several advantages over ground-based interferometers for constraining the polarization of gravitational waves due to the many projections of the polarization pattern provided by the different lines of sight to the pulsars, and the enhanced response to longitudinal polarizations. Here, we show that existing results from pulsar timing arrays can be used to place stringent limits on the energy density of longitudinal stochastic gravitational waves. However, unambiguously distinguishing these modes from noise will be very difficult due to the large variances in the pulsar-pulsar correlation patterns. Existing upper limits on the power spectrum of pulsar timing residuals imply that the amplitude of vector longitudinal (VL) and scalar longitudinal (SL) modes at frequencies of 1/year are constrained, AVL<4 ×10-16 and ASL<4 ×10-17, while the bounds on the energy density for a scale invariant cosmological background are ΩVLh2<4 ×10-11 and ΩSLh2<3 ×10-13.
Ding, A Adam; Wu, Hulin
2014-10-01
We propose a new method to use a constrained local polynomial regression to estimate the unknown parameters in ordinary differential equation models with a goal of improving the smoothing-based two-stage pseudo-least squares estimate. The equation constraints are derived from the differential equation model and are incorporated into the local polynomial regression in order to estimate the unknown parameters in the differential equation model. We also derive the asymptotic bias and variance of the proposed estimator. Our simulation studies show that our new estimator is clearly better than the pseudo-least squares estimator in estimation accuracy with a small price of computational cost. An application example on immune cell kinetics and trafficking for influenza infection further illustrates the benefits of the proposed new method.
Nicholas Scott Cardell
2013-05-01
Full Text Available Maximum entropy methods of parameter estimation are appealing because they impose no additional structure on the data, other than that explicitly assumed by the analyst. In this paper we prove that the data constrained GME estimator of the general linear model is consistent and asymptotically normal. The approach we take in establishing the asymptotic properties concomitantly identifies a new computationally efficient method for calculating GME estimates. Formulae are developed to compute asymptotic variances and to perform Wald, likelihood ratio, and Lagrangian multiplier statistical tests on model parameters. Monte Carlo simulations are provided to assess the performance of the GME estimator in both large and small sample situations. Furthermore, we extend our results to maximum cross-entropy estimators and indicate a variant of the GME estimator that is unbiased. Finally, we discuss the relationship of GME estimators to Bayesian estimators, pointing out the conditions under which an unbiased GME estimator would be efficient.
Detecting anomalies in crowded scenes via locality-constrained affine subspace coding
Fan, Yaxiang; Wen, Gongjian; Qiu, Shaohua; Li, Deren
2017-07-01
Video anomaly event detection is the process of finding an abnormal event deviation compared with the majority of normal or usual events. The main challenges are the high structure redundancy and the dynamic changes in the scenes that are in surveillance videos. To address these problems, we present a framework for anomaly detection and localization in videos that is based on locality-constrained affine subspace coding (LASC) and a model updating procedure. In our algorithm, LASC attempts to reconstruct the test sample by its top-k nearest subspaces, which are obtained by segmenting the normal samples space using a clustering method. A sample with a large reconstruction cost is detected as abnormal by setting a threshold. To adapt to the scene changes over time, a model updating strategy is proposed. We experiment on two public datasets: the UCSD dataset and the Avenue dataset. The results demonstrate that our method achieves competitive performance at a 700 fps on a single desktop PC.
L1 norm constrained migration of blended data with the FISTA algorithm
Lu, Xinting; Han, Liguo; Yu, Jianglong; Chen, Xue
2015-01-01
Blended acquisition significantly improves the seismic acquisition efficiency. However, the direct imaging of blended data is not satisfactory due to the crosstalk contamination. Assuming that the distribution of subsurface reflectivity is sparse, in this paper, we formulate the seismic imaging problem of blended data as a Basis Pursuit denoise (BPDN) problem. Based on compressed sensing, we propose a L1 norm constrained migration method applying to the direct imaging of blended data. The Fast Iterative Shrinkage-Thresholding Algorithm, which is stable and computationally efficient, is implemented in our method. Numerical tests on the theoretical models show that the crosstalk introduced by blended sources is effectively attenuated and the migration quality has been improved enormously. (paper)
Resolving combinatorial ambiguities in dilepton t t¯ event topologies with constrained M2 variables
Debnath, Dipsikha; Kim, Doojin; Kim, Jeong Han; Kong, Kyoungchul; Matchev, Konstantin T.
2017-10-01
We advocate the use of on-shell constrained M2 variables in order to mitigate the combinatorial problem in supersymmetry-like events with two invisible particles at the LHC. We show that in comparison to other approaches in the literature, the constrained M2 variables provide superior ansätze for the unmeasured invisible momenta and therefore can be usefully applied to discriminate combinatorial ambiguities. We illustrate our procedure with the example of dilepton t t ¯ events. We critically review the existing methods based on the Cambridge MT 2 variable and MAOS reconstruction of invisible momenta, and show that their algorithm can be simplified without loss of sensitivity, due to a perfect correlation between events with complex solutions for the invisible momenta and events exhibiting a kinematic endpoint violation. Then we demonstrate that the efficiency for selecting the correct partition is further improved by utilizing the M2 variables instead. Finally, we also consider the general case when the underlying mass spectrum is unknown, and no kinematic endpoint information is available.
Hemmati, Reza; Hooshmand, Rahmat-Allah; Khodabakhshian, Amin
2013-01-01
Highlights: • Generation expansion planning is presented in deregulated electricity market. • Wind farm uncertainty is modeled in the problem. • The profit of each GENCO is maximized and also the safe operation of system is satisfied. • Salve sector is managed as an optimization programming and solved by using PSO technique. • Master sector is considered in pool market and Cournot model is used to simulate it. - Abstract: This paper addresses reliability constrained generation expansion planning (GEP) in the presence of wind farm uncertainty in deregulated electricity market. The proposed GEP aims at maximizing the expected profit of all generation companies (GENCOs), while considering security and reliability constraints such as reserve margin and loss of load expectation (LOLE). Wind farm uncertainty is also considered in the planning and GENCOs denote their planning in the presence of wind farm uncertainty. The uncertainty is modeled by probability distribution function (PDF) and Monte-Carlo simulation (MCS) is used to insert uncertainty into the problem. The proposed GEP is a constrained, nonlinear, mixed-integer optimization programming and solved by using particle swarm optimization (PSO) method. In this paper, Electricity market structure is modeled as a pool market. Simulation results verify the effectiveness and validity of the proposed planning for maximizing GENCOs profit in the presence of wind farms uncertainties in electricity market
Fuzzy Constrained Predictive Optimal Control of High Speed Train with Actuator Dynamics
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.
Hailong Wang
2018-01-01
Full Text Available The backtracking search optimization algorithm (BSA is a population-based evolutionary algorithm for numerical optimization problems. BSA has a powerful global exploration capacity while its local exploitation capability is relatively poor. This affects the convergence speed of the algorithm. In this paper, we propose a modified BSA inspired by simulated annealing (BSAISA to overcome the deficiency of BSA. In the BSAISA, the amplitude control factor (F is modified based on the Metropolis criterion in simulated annealing. The redesigned F could be adaptively decreased as the number of iterations increases and it does not introduce extra parameters. A self-adaptive ε-constrained method is used to handle the strict constraints. We compared the performance of the proposed BSAISA with BSA and other well-known algorithms when solving thirteen constrained benchmarks and five engineering design problems. The simulation results demonstrated that BSAISA is more effective than BSA and more competitive with other well-known algorithms in terms of convergence speed.
Constraining the mSUGRA parameter space through entropy and abundance criteria
Cabral-Rosetti, Luis G.; Mondragon, Myriam; Nunez, Dario; Sussman, Roberto A.; Zavala, Jesus; Nellen, Lukas
2007-01-01
We explore the use of two criteria to constrain the allowed parameter space in mSUGRA models; both criteria are based in the calculation of the present density of neutralinos χ0 as Dark Matter in the Universe. The first one is the usual ''abundance'' criterion that requieres that present neutralino relic density complies with 0.0945 < ΩCDMh2 < 0.1287, which are the 2σ bounds according to WMAP. To calculate the relic density we use the public numerical code micrOMEGAS. The second criterion is the original idea presented in [3] that basically applies the microcanonical definition of entropy to a weakly interacting and self-gravitating gas, and then evaluate the change in entropy per particle of this gas between the freeze-out era and present day virialized structures. An 'entropy consistency' criterion emerges by comparing theoretical and empirical estimates of this entropy. One of the objetives of the work is to analyze the joint application of both criteria, already done in [3], to see if their results, using approximations for the calculations of the relic density, agree with the results coming from the exact numerical results of micrOMEGAS. The main objetive of the work is to use this method to constrain the parameter space in mSUGRA models that are inputs for the calculations of micrOMEGAS, and thus to get some bounds on the predictions for the SUSY spectra
A Chance-Constrained Economic Dispatch Model in Wind-Thermal-Energy Storage System
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.
Secure Fusion Estimation for Bandwidth Constrained Cyber-Physical Systems Under Replay Attacks.
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.
Wan, Xiaoqing; Zhao, Chunhui
2017-06-01
As a competitive machine learning algorithm, the stacked sparse autoencoder (SSA) has achieved outstanding popularity in exploiting high-level features for classification of hyperspectral images (HSIs). In general, in the SSA architecture, the nodes between adjacent layers are fully connected and need to be iteratively fine-tuned during the pretraining stage; however, the nodes of previous layers further away may be less likely to have a dense correlation to the given node of subsequent layers. Therefore, to reduce the classification error and increase the learning rate, this paper proposes the general framework of locally connected SSA; that is, the biologically inspired local receptive field (LRF) constrained SSA architecture is employed to simultaneously characterize the local correlations of spectral features and extract high-level feature representations of hyperspectral data. In addition, the appropriate receptive field constraint is concurrently updated by measuring the spatial distances from the neighbor nodes to the corresponding node. Finally, the efficient random forest classifier is cascaded to the last hidden layer of the SSA architecture as a benchmark classifier. Experimental results on two real HSI datasets demonstrate that the proposed hierarchical LRF constrained stacked sparse autoencoder and random forest (SSARF) provides encouraging results with respect to other contrastive methods, for instance, the improvements of overall accuracy in a range of 0.72%-10.87% for the Indian Pines dataset and 0.74%-7.90% for the Kennedy Space Center dataset; moreover, it generates lower running time compared with the result provided by similar SSARF based methodology.
Ren, Hai-Sheng; Ming, Mei-Jun; Ma, Jian-Yi; Li, Xiang-Yuan
2013-08-22
Within the framework of constrained density functional theory (CDFT), the diabatic or charge localized states of electron transfer (ET) have been constructed. Based on the diabatic states, inner reorganization energy λin has been directly calculated. For solvent reorganization energy λs, a novel and reasonable nonequilibrium solvation model is established by introducing a constrained equilibrium manipulation, and a new expression of λs has been formulated. It is found that λs is actually the cost of maintaining the residual polarization, which equilibrates with the extra electric field. On the basis of diabatic states constructed by CDFT, a numerical algorithm using the new formulations with the dielectric polarizable continuum model (D-PCM) has been implemented. As typical test cases, self-exchange ET reactions between tetracyanoethylene (TCNE) and tetrathiafulvalene (TTF) and their corresponding ionic radicals in acetonitrile are investigated. The calculated reorganization energies λ are 7293 cm(-1) for TCNE/TCNE(-) and 5939 cm(-1) for TTF/TTF(+) reactions, agreeing well with available experimental results of 7250 cm(-1) and 5810 cm(-1), respectively.
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)
Designing equitable antiretroviral allocation strategies in resource-constrained countries.
David P Wilson
2005-02-01
Full Text Available Recently, a global commitment has been made to expand access to antiretrovirals (ARVs in the developing world. However, in many resource-constrained countries the number of individuals infected with HIV in need of treatment will far exceed the supply of ARVs, and only a limited number of health-care facilities (HCFs will be available for ARV distribution. Deciding how to allocate the limited supply of ARVs among HCFs will be extremely difficult. Resource allocation decisions can be made on the basis of many epidemiological, ethical, or preferential treatment priority criteria.Here we use operations research techniques, and we show how to determine the optimal strategy for allocating ARVs among HCFs in order to satisfy the equitable criterion that each individual infected with HIV has an equal chance of receiving ARVs. We present a novel spatial mathematical model that includes heterogeneity in treatment accessibility. We show how to use our theoretical framework, in conjunction with an equity objective function, to determine an optimal equitable allocation strategy (OEAS for ARVs in resource-constrained regions. Our equity objective function enables us to apply the egalitarian principle of equity with respect to access to health care. We use data from the detailed ARV rollout plan designed by the government of South Africa to determine an OEAS for the province of KwaZulu-Natal. We determine the OEAS for KwaZulu-Natal, and we then compare this OEAS with two other ARV allocation strategies: (i allocating ARVs only to Durban (the largest urban city in KwaZulu-Natal province and (ii allocating ARVs equally to all available HCFs. In addition, we compare the OEAS to the current allocation plan of the South African government (which is based upon allocating ARVs to 17 HCFs. We show that our OEAS significantly improves equity in treatment accessibility in comparison with these three ARV allocation strategies. We also quantify how the size of the
Constraining cosmic curvature by using age of galaxies and gravitational lenses
Rana, Akshay; Mahajan, Shobhit; Mukherjee, Amitabha [Department of Physics and Astrophysics, University of Delhi, Delhi 110007 (India); Jain, Deepak, E-mail: arana@physics.du.ac.in, E-mail: djain@ddu.du.ac.in, E-mail: shobhit.mahajan@gmail.com, E-mail: amimukh@gmail.com [Deen Dayal Upadhyaya College, University of Delhi, Sector-3, Dwarka, Delhi 110078 (India)
2017-03-01
We use two model-independent methods to constrain the curvature of the universe. In the first method, we study the evolution of the curvature parameter (Ω {sub k} {sup 0}) with redshift by using the observations of the Hubble parameter and transverse comoving distances obtained from the age of galaxies. Secondly, we also use an indirect method based on the mean image separation statistics of gravitationally lensed quasars. The basis of this methodology is that the average image separation of lensed images will show a positive, negative or zero correlation with the source redshift in a closed, open or flat universe respectively. In order to smoothen the datasets used in both the methods, we use a non-parametric method namely, Gaussian Process (GP). Finally from first method we obtain Ω {sub k} {sup 0} = 0.025±0.57 for a presumed flat universe while the cosmic curvature remains constant throughout the redshift region 0 < z < 1.37 which indicates that the universe may be homogeneous. Moreover, the combined result from both the methods suggests that the universe is marginally closed. However, a flat universe can be incorporated at 3σ level.
Constraining cosmic curvature by using age of galaxies and gravitational lenses
Rana, Akshay; Mahajan, Shobhit; Mukherjee, Amitabha; Jain, Deepak
2017-01-01
We use two model-independent methods to constrain the curvature of the universe. In the first method, we study the evolution of the curvature parameter (Ω k 0 ) with redshift by using the observations of the Hubble parameter and transverse comoving distances obtained from the age of galaxies. Secondly, we also use an indirect method based on the mean image separation statistics of gravitationally lensed quasars. The basis of this methodology is that the average image separation of lensed images will show a positive, negative or zero correlation with the source redshift in a closed, open or flat universe respectively. In order to smoothen the datasets used in both the methods, we use a non-parametric method namely, Gaussian Process (GP). Finally from first method we obtain Ω k 0 = 0.025±0.57 for a presumed flat universe while the cosmic curvature remains constant throughout the redshift region 0 < z < 1.37 which indicates that the universe may be homogeneous. Moreover, the combined result from both the methods suggests that the universe is marginally closed. However, a flat universe can be incorporated at 3σ level.
The Rate-Controlled Constrained-Equilibrium Approach to Far-From-Local-Equilibrium Thermodynamics
Hameed Metghalchi
2012-01-01
Full Text Available The Rate-Controlled Constrained-Equilibrium (RCCE method for the description of the time-dependent behavior of dynamical systems in non-equilibrium states is a general, effective, physically based method for model order reduction that was originally developed in the framework of thermodynamics and chemical kinetics. A generalized mathematical formulation is presented here that allows including nonlinear constraints in non-local equilibrium systems characterized by the existence of a non-increasing Lyapunov functional under the system’s internal dynamics. The generalized formulation of RCCE enables to clarify the essentials of the method and the built-in general feature of thermodynamic consistency in the chemical kinetics context. In this paper, we work out the details of the method in a generalized mathematical-physics framework, but for definiteness we detail its well-known implementation in the traditional chemical kinetics framework. We detail proofs and spell out explicit functional dependences so as to bring out and clarify each underlying assumption of the method. In the standard context of chemical kinetics of ideal gas mixtures, we discuss the relations between the validity of the detailed balance condition off-equilibrium and the thermodynamic consistency of the method. We also discuss two examples of RCCE gas-phase combustion calculations to emphasize the constraint-dependent performance of the RCCE method.
The Compton-thick Growth of Supermassive Black Holes constrained
Buchner, J.; Georgakakis, A.; Nandra, K.
2017-10-01
A heavily obscured growth phase of supermassive black holes (SMBH) is thought to be important in the co-evolution with galaxies. X-rays provide a clean and efficient selection of unobscured and obscured AGN. Recent work with deeper observations and improved analysis methodology allowed us to extend constraints to Compton-thick number densities. We present the first luminosity function of Compton-thick AGN at z=0.5-4 and constrain the overall mass density locked into black holes over cosmic time, a fundamental constraint for cosmological simulations. Recent studies including ours find that the obscuration is redshift and luminosity-dependent in a complex way, which rules out entire sets of obscurer models. A new paradigm, the radiation-lifted torus model, is proposed, in which the obscurer is Eddington-rate dependent and accretion creates and displaces torus clouds. We place observational limits on the behaviour of this mechanism.
Lifetime of the solar nebula constrained by meteorite paleomagnetism.
Wang, Huapei; Weiss, Benjamin P; Bai, Xue-Ning; Downey, Brynna G; Wang, Jun; Wang, Jiajun; Suavet, Clément; Fu, Roger R; Zucolotto, Maria E
2017-02-10
A key stage in planet formation is the evolution of a gaseous and magnetized solar nebula. However, the lifetime of the nebular magnetic field and nebula are poorly constrained. We present paleomagnetic analyses of volcanic angrites demonstrating that they formed in a near-zero magnetic field (nebula field, and likely the nebular gas, had dispersed by this time. This sets the time scale for formation of the gas giants and planet migration. Furthermore, it supports formation of chondrules after 4563.5 million years ago by non-nebular processes like planetesimal collisions. The core dynamo on the angrite parent body did not initiate until about 4 to 11 million years after solar system formation. Copyright © 2017, American Association for the Advancement of Science.
Constrain the SED Type of Unidentified Fermi Objects
An-Li Tsai
2013-09-01
Full Text Available 2FGL J1823.8+4312 and 2FGL J1304.1-2415 are two unidentified Fermi objects which are associated with cluster of galaxies. In order to exam the possibility of cluster of galaxies as gamma-ray emitters, we search for counterpart of these two unidentified Fermi objects in other wavebands. However, we find other candidate to be more likely the counterpart of the unidentified Fermi object for both sources. We compare their light curves and SEDs in order to identify their source types. However, data at millimeter and sub-millimeter wavebands, which is important for us to constrain the SED at synchrotron peak, is lacking of measurement. Therefore, we proposed to SMA observation for these two sources. We have got data and are doing further analysis.
Late time CMB anisotropies constrain mini-charged particles
Burrage, C.; Redondo, J.; Ringwald, A. [Deutsches Elektronen-Synchrotron (DESY), Hamburg (Germany); Jaeckel, J. [Univ. of Durham, Inst. for Particle Physics Phenomenology (United Kingdom)
2009-09-15
Observations of the temperature anisotropies induced as light from the CMB passes through large scale structures in the late universe are a sensitive probe of the interactions of photons in such environments. In extensions of the Standard Model which give rise to mini-charged particles, photons propagating through transverse magnetic fields can be lost to pair production of such particles. Such a decrement in the photon flux would occur as photons from the CMB traverse the magnetic fields of galaxy clusters. Therefore late time CMB anisotropies can be used to constrain the properties of mini- charged particles. We outline how this test is constructed, and present new constraints on mini-charged particles from observations of the Sunyaev-Zel'dovich effect in the Coma cluster. (orig.)
A new approach to nonlinear constrained Tikhonov regularization
Ito, Kazufumi
2011-09-16
We present a novel approach to nonlinear constrained Tikhonov regularization from the viewpoint of optimization theory. A second-order sufficient optimality condition is suggested as a nonlinearity condition to handle the nonlinearity of the forward operator. The approach is exploited to derive convergence rate results for a priori as well as a posteriori choice rules, e.g., discrepancy principle and balancing principle, for selecting the regularization parameter. The idea is further illustrated on a general class of parameter identification problems, for which (new) source and nonlinearity conditions are derived and the structural property of the nonlinearity term is revealed. A number of examples including identifying distributed parameters in elliptic differential equations are presented. © 2011 IOP Publishing Ltd.
Constraining generalized non-local cosmology from Noether symmetries.
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.
Maximizing entropy of image models for 2-D constrained coding
Forchhammer, Søren; Danieli, Matteo; Burini, Nino
2010-01-01
This paper considers estimating and maximizing the entropy of two-dimensional (2-D) fields with application to 2-D constrained coding. We consider Markov random fields (MRF), which have a non-causal description, and the special case of Pickard random fields (PRF). The PRF are 2-D causal finite...... context models, which define stationary probability distributions on finite rectangles and thus allow for calculation of the entropy. We consider two binary constraints and revisit the hard square constraint given by forbidding neighboring 1s and provide novel results for the constraint that no uniform 2...... £ 2 squares contains all 0s or all 1s. The maximum values of the entropy for the constraints are estimated and binary PRF satisfying the constraint are characterized and optimized w.r.t. the entropy. The maximum binary PRF entropy is 0.839 bits/symbol for the no uniform squares constraint. The entropy...
Reinforcement Learning for Constrained Energy Trading Games With Incomplete Information.
Wang, Huiwei; Huang, Tingwen; Liao, Xiaofeng; Abu-Rub, Haitham; Chen, Guo
2017-10-01
This paper considers the problem of designing adaptive learning algorithms to seek the Nash equilibrium (NE) of the constrained energy trading game among individually strategic players with incomplete information. In this game, each player uses the learning automaton scheme to generate the action probability distribution based on his/her private information for maximizing his own averaged utility. It is shown that if one of admissible mixed-strategies converges to the NE with probability one, then the averaged utility and trading quantity almost surely converge to their expected ones, respectively. For the given discontinuous pricing function, the utility function has already been proved to be upper semicontinuous and payoff secure which guarantee the existence of the mixed-strategy NE. By the strict diagonal concavity of the regularized Lagrange function, the uniqueness of NE is also guaranteed. Finally, an adaptive learning algorithm is provided to generate the strategy probability distribution for seeking the mixed-strategy NE.
An ascending multi-item auction with financially constrained bidders
Gerard van der Laan
2016-12-01
Full Text Available Several heterogeneous items are to be sold to a group of potentially budget- constrained bidders. Every bidder has private knowledge of his own valuation of the items and his own budget. Due to budget constraints, bidders may not be able to pay up to their values and typically no Walrasian equilibrium exists. To deal with such markets, we propose the notion of 'equilibrium under allotment' and develop an ascending auction mechanism that always finds such an equilibrium assignment and a corresponding system of prices in finite time. The auction can be viewed as a novel generalization of the ascending auction of Demange et al. (1986 from settings without financial constraints to settings with financial constraints. We examine various strategic and efficiency properties of the auction and its outcome.
Solving of L0 norm constrained EEG inverse problem.
Xu, Peng; Lei, Xu; Hu, Xiao; Yao, Dezhong
2009-01-01
l(0) norm is an effective constraint used to solve EEG inverse problem for a sparse solution. However, due to the discontinuous and un-differentiable properties, it is an open issue to solve the l(0) norm constrained problem, which is usually instead solved by using some alternative functions like l(1) norm to approximate l(0) norm. In this paper, a continuous and differentiable function having the same form as the transfer function of Butterworth low-pass filter is introduced to approximate l(0) norm constraint involved in EEG inverse problem. The new approximation based approach was compared with l(1) norm and LORETA solutions on a realistic head model using simulated sources. The preliminary results show that this alternative approximation to l(0) norm is promising for the estimation of EEG sources with sparse distribution.
Gluon field strength correlation functions within a constrained instanton model
Dorokhov, A.E.; Esaibegyan, S.V.; Maximov, A.E.; Mikhailov, S.V.
2000-01-01
We suggest a constrained instanton (CI) solution in the physical QCD vacuum which is described by large-scale vacuum field fluctuations. This solution decays exponentially at large distances. It is stable only if the interaction of the instanton with the background vacuum field is small and additional constraints are introduced. The CI solution is explicitly constructed in the ansatz form, and the two-point vacuum correlator of the gluon field strengths is calculated in the framework of the effective instanton vacuum model. At small distances the results are qualitatively similar to the single instanton case; in particular, the D 1 invariant structure is small, which is in agreement with the lattice calculations. (orig.)
The evolutionary value of recombination is constrained by genome modularity.
Darren P Martin
2005-10-01
Full Text Available Genetic recombination is a fundamental evolutionary mechanism promoting biological adaptation. Using engineered recombinants of the small single-stranded DNA plant virus, Maize streak virus (MSV, we experimentally demonstrate that fragments of genetic material only function optimally if they reside within genomes similar to those in which they evolved. The degree of similarity necessary for optimal functionality is correlated with the complexity of intragenomic interaction networks within which genome fragments must function. There is a striking correlation between our experimental results and the types of MSV recombinants that are detectable in nature, indicating that obligatory maintenance of intragenome interaction networks strongly constrains the evolutionary value of recombination for this virus and probably for genomes in general.
Membrane-constrained acoustic metamaterials for low frequency sound insulation
Wang, Xiaole; Zhao, Hui; Luo, Xudong; Huang, Zhenyu
2016-01-01
We present a constrained membrane-type acoustic metamaterial (CMAM) that employs constraint sticks to add out-of-plane dimensions in the design space of MAM. A CMAM sample, which adopts constraint sticks to suppress vibrations at the membrane center, was fabricated to achieve a sound transmission loss (STL) peak of 26 dB at 140 Hz, with the static areal density of 6.0 kg/m2. The working mechanism of the CMAM as an acoustic metamaterial is elucidated by calculating the averaged normal displacement, the equivalent areal density, and the effective dynamic mass of a unit cell through finite element simulations. Furthermore, the vibration modes of the CMAM indicate that the eigenmodes related to STL dips are shifted into high frequencies, thus broadening its effective bandwidth significantly. Three samples possessing the same geometry and material but different constraint areas were fabricated to illustrate the tunability of STL peaks at low frequencies.
Thermally-Constrained Fuel-Optimal ISS Maneuvers
Bhatt, Sagar; Svecz, Andrew; Alaniz, Abran; Jang, Jiann-Woei; Nguyen, Louis; Spanos, Pol
2015-01-01
Optimal Propellant Maneuvers (OPMs) are now being used to rotate the International Space Station (ISS) and have saved hundreds of kilograms of propellant over the last two years. The savings are achieved by commanding the ISS to follow a pre-planned attitude trajectory optimized to take advantage of environmental torques. The trajectory is obtained by solving an optimal control problem. Prior to use on orbit, OPM trajectories are screened to ensure a static sun vector (SSV) does not occur during the maneuver. The SSV is an indicator that the ISS hardware temperatures may exceed thermal limits, causing damage to the components. In this paper, thermally-constrained fuel-optimal trajectories are presented that avoid an SSV and can be used throughout the year while still reducing propellant consumption significantly.
Conflict processing in the anterior cingulate cortex constrains response priming.
Pastötter, Bernhard; Hanslmayr, Simon; Bäuml, Karl-Heinz T
2010-05-01
A prominent function of the anterior cingulate cortex (ACC) is to process conflict between competing response options. In this study, we investigated the role of conflict processing in a response-priming task in which manual responses were either validly or invalidly cued. Examining electrophysiological measurements of oscillatory brain activity on the source level, we found response priming to be related to a beta power decrease in the premotor cortex and conflict processing to be linked to a theta power increase in the ACC. In particular, correlation of oscillatory brain activities in the ACC and the premotor cortex showed that conflict processing reduces response priming by slowing response time in valid trials and lowering response errors in invalid trials. This relationship emerged on a between subjects level as well as within subjects, on a single trial level. These findings suggest that conflict processing in the ACC constrains the automatic priming process. 2010 Elsevier Inc. All rights reserved.
Transmission-constrained oligopoly in the Japanese electricity market
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)
Constrained recycling: a framework to reduce landfilling in developing countries.
Diaz, Ricardo; Otoma, Suehiro
2013-01-01
This article presents a model that integrates three branches of research: (i) economics of solid waste that assesses consumer's willingness to recycle and to pay for disposal; (ii) economics of solid waste that compares private and social costs of final disposal and recycling; and (iii) theories on personal attitudes and social influence. The model identifies two arenas where decisions are made: upstream arena, where residents are decision-makers, and downstream arena, where municipal authorities are decision-makers, and graphically proposes interactions between disposal and recycling, as well as the concept of 'constrained recycling' (an alternative to optimal recycling) to guide policy design. It finally concludes that formative instruments, such as environmental education and benchmarks, should be combined with economic instruments, such as subsidies, to move constraints on source separation and recycling in the context of developing countries.
Constraining viscous dark energy models with the latest cosmological data
Wang, Deng; Yan, Yang-Jie; Meng, Xin-He
2017-10-01
Based on the assumption that the dark energy possessing bulk viscosity is homogeneously and isotropically permeated in the universe, we propose three new viscous dark energy (VDE) models to characterize the accelerating universe. By constraining these three models with the latest cosmological observations, we find that they just deviate very slightly from the standard cosmological model and can alleviate effectively the current H_0 tension between the local observation by the Hubble Space Telescope and the global measurement by the Planck Satellite. Interestingly, we conclude that a spatially flat universe in our VDE model with cosmic curvature is still supported by current data, and the scale invariant primordial power spectrum is strongly excluded at least at the 5.5σ confidence level in the three VDE models as the Planck result. We also give the 95% upper limits of the typical bulk viscosity parameter η in the three VDE scenarios.