Parallel-vector computation for structural analysis and nonlinear unconstrained optimization problems

NASA Technical Reports Server (NTRS)

Nguyen, Duc T.

1990-01-01

Practical engineering application can often be formulated in the form of a constrained optimization problem. There are several solution algorithms for solving a constrained optimization problem. One approach is to convert a constrained problem into a series of unconstrained problems. Furthermore, unconstrained solution algorithms can be used as part of the constrained solution algorithms. Structural optimization is an iterative process where one starts with an initial design, a finite element structure analysis is then performed to calculate the response of the system (such as displacements, stresses, eigenvalues, etc.). Based upon the sensitivity information on the objective and constraint functions, an optimizer such as ADS or IDESIGN, can be used to find the new, improved design. For the structural analysis phase, the equation solver for the system of simultaneous, linear equations plays a key role since it is needed for either static, or eigenvalue, or dynamic analysis. For practical, large-scale structural analysis-synthesis applications, computational time can be excessively large. Thus, it is necessary to have a new structural analysis-synthesis code which employs new solution algorithms to exploit both parallel and vector capabilities offered by modern, high performance computers such as the Convex, Cray-2 and Cray-YMP computers. The objective of this research project is, therefore, to incorporate the latest development in the parallel-vector equation solver, PVSOLVE into the widely popular finite-element production code, such as the SAP-4. Furthermore, several nonlinear unconstrained optimization subroutines have also been developed and tested under a parallel computer environment. The unconstrained optimization subroutines are not only useful in their own right, but they can also be incorporated into a more popular constrained optimization code, such as ADS.

Optimization of flexible wing structures subject to strength and induced drag constraints

NASA Technical Reports Server (NTRS)

Haftka, R. T.

1977-01-01

An optimization procedure for designing wing structures subject to stress, strain, and drag constraints is presented. The optimization method utilizes an extended penalty function formulation for converting the constrained problem into a series of unconstrained ones. Newton's method is used to solve the unconstrained problems. An iterative analysis procedure is used to obtain the displacements of the wing structure including the effects of load redistribution due to the flexibility of the structure. The induced drag is calculated from the lift distribution. Approximate expressions for the constraints used during major portions of the optimization process enhance the efficiency of the procedure. A typical fighter wing is used to demonstrate the procedure. Aluminum and composite material designs are obtained. The tradeoff between weight savings and drag reduction is investigated.

Graph cuts via l1 norm minimization.

PubMed

Bhusnurmath, Arvind; Taylor, Camillo J

2008-10-01

Graph cuts have become an increasingly important tool for solving a number of energy minimization problems in computer vision and other fields. In this paper, the graph cut problem is reformulated as an unconstrained l1 norm minimization that can be solved effectively using interior point methods. This reformulation exposes connections between the graph cuts and other related continuous optimization problems. Eventually the problem is reduced to solving a sequence of sparse linear systems involving the Laplacian of the underlying graph. The proposed procedure exploits the structure of these linear systems in a manner that is easily amenable to parallel implementations. Experimental results obtained by applying the procedure to graphs derived from image processing problems are provided.

New displacement-based methods for optimal truss topology design

NASA Technical Reports Server (NTRS)

Bendsoe, Martin P.; Ben-Tal, Aharon; Haftka, Raphael T.

1991-01-01

Two alternate methods for maximum stiffness truss topology design are presented. The ground structure approach is used, and the problem is formulated in terms of displacements and bar areas. This large, nonconvex optimization problem can be solved by a simultaneous analysis and design approach. Alternatively, an equivalent, unconstrained, and convex problem in the displacements only can be formulated, and this problem can be solved by a nonsmooth, steepest descent algorithm. In both methods, the explicit solving of the equilibrium equations and the assembly of the global stiffness matrix are circumvented. A large number of examples have been studied, showing the attractive features of topology design as well as exposing interesting features of optimal topologies.

Numerical analysis of fluid flow and heat transfer during melting inside a cylindrical container for thermal energy storage system

NASA Astrophysics Data System (ADS)

Bellan, Selvan; Cheok, Cho Hyun; Gokon, Nobuyuki; Matsubara, Koji; Kodama, Tatsuya

2017-06-01

This paper presents a numerical analysis of unconstrained melting of high temperature(>1000K) phase change material (PCM) inside a cylindrical container. Sodium chloride and Silicon carbide have been used as phase change material and shell of the capsule respectively. The control volume discretization approach has been used to solve the conservation equations of mass, momentum and energy. The enthalpy-porosity method has been used to track the solid-liquid interface of the PCM during melting process. Transient numerical simulations have been performed in order to study the influence of radius of the capsule and the Stefan number on the heat transfer rate. The simulation results show that the counter-clockwise Buoyancy driven convection over the top part of the solid PCM enhances the melting rate quite faster than the bottom part.

Multibody dynamical modeling for spacecraft docking process with spring-damper buffering device: A new validation approach

NASA Astrophysics Data System (ADS)

Daneshjou, Kamran; Alibakhshi, Reza

2018-01-01

In the current manuscript, the process of spacecraft docking, as one of the main risky operations in an on-orbit servicing mission, is modeled based on unconstrained multibody dynamics. The spring-damper buffering device is utilized here in the docking probe-cone system for micro-satellites. Owing to the impact occurs inevitably during docking process and the motion characteristics of multibody systems are remarkably affected by this phenomenon, a continuous contact force model needs to be considered. Spring-damper buffering device, keeping the spacecraft stable in an orbit when impact occurs, connects a base (cylinder) inserted in the chaser satellite and the end of docking probe. Furthermore, by considering a revolute joint equipped with torsional shock absorber, between base and chaser satellite, the docking probe can experience both translational and rotational motions simultaneously. Although spacecraft docking process accompanied by the buffering mechanisms may be modeled by constrained multibody dynamics, this paper deals with a simple and efficient formulation to eliminate the surplus generalized coordinates and solve the impact docking problem based on unconstrained Lagrangian mechanics. By an example problem, first, model verification is accomplished by comparing the computed results with those recently reported in the literature. Second, according to a new alternative validation approach, which is based on constrained multibody problem, the accuracy of presented model can be also evaluated. This proposed verification approach can be applied to indirectly solve the constrained multibody problems by minimum required effort. The time history of impact force, the influence of system flexibility and physical interaction between shock absorber and penetration depth caused by impact are the issues followed in this paper. Third, the MATLAB/SIMULINK multibody dynamic analysis software will be applied to build impact docking model to validate computed results and then, investigate the trajectories of both satellites to take place the successful capture process.

Dai-Kou type conjugate gradient methods with a line search only using gradient.

PubMed

Huang, Yuanyuan; Liu, Changhe

2017-01-01

In this paper, the Dai-Kou type conjugate gradient methods are developed to solve the optimality condition of an unconstrained optimization, they only utilize gradient information and have broader application scope. Under suitable conditions, the developed methods are globally convergent. Numerical tests and comparisons with the PRP+ conjugate gradient method only using gradient show that the methods are efficient.

An Algorithm for the Weighted Earliness-Tardiness Unconstrained Project Scheduling Problem

NASA Astrophysics Data System (ADS)

Afshar Nadjafi, Behrouz; Shadrokh, Shahram

This research considers a project scheduling problem with the object of minimizing weighted earliness-tardiness penalty costs, taking into account a deadline for the project and precedence relations among the activities. An exact recursive method has been proposed for solving the basic form of this problem. We present a new depth-first branch and bound algorithm for extended form of the problem, which time value of money is taken into account by discounting the cash flows. The algorithm is extended with two bounding rules in order to reduce the size of the branch and bound tree. Finally, some test problems are solved and computational results are reported.

Limited-memory trust-region methods for sparse relaxation

NASA Astrophysics Data System (ADS)

Adhikari, Lasith; DeGuchy, Omar; Erway, Jennifer B.; Lockhart, Shelby; Marcia, Roummel F.

2017-08-01

In this paper, we solve the l2-l1 sparse recovery problem by transforming the objective function of this problem into an unconstrained differentiable function and applying a limited-memory trust-region method. Unlike gradient projection-type methods, which uses only the current gradient, our approach uses gradients from previous iterations to obtain a more accurate Hessian approximation. Numerical experiments show that our proposed approach eliminates spurious solutions more effectively while improving computational time.

MO-FG-CAMPUS-TeP2-01: A Graph Form ADMM Algorithm for Constrained Quadratic Radiation Treatment Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Liu, X; Belcher, AH; Wiersma, R

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 optimizationmore » 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 used significantly less computer memory.« less

Robust penalty method for structural synthesis

NASA Technical Reports Server (NTRS)

Kamat, M. P.

1983-01-01

The Sequential Unconstrained Minimization Technique (SUMT) offers an easy way of solving nonlinearly constrained problems. However, this algorithm frequently suffers from the need to minimize an ill-conditioned penalty function. An ill-conditioned minimization problem can be solved very effectively by posing the problem as one of integrating a system of stiff differential equations utilizing concepts from singular perturbation theory. This paper evaluates the robustness and the reliability of such a singular perturbation based SUMT algorithm on two different problems of structural optimization of widely separated scales. The report concludes that whereas conventional SUMT can be bogged down by frequent ill-conditioning, especially in large scale problems, the singular perturbation SUMT has no such difficulty in converging to very accurate solutions.

Extremal Optimization for Quadratic Unconstrained Binary Problems

NASA Astrophysics Data System (ADS)

Boettcher, S.

We present an implementation of τ-EO for quadratic unconstrained binary optimization (QUBO) problems. To this end, we transform modify QUBO from its conventional Boolean presentation into a spin glass with a random external field on each site. These fields tend to be rather large compared to the typical coupling, presenting EO with a challenging two-scale problem, exploring smaller differences in couplings effectively while sufficiently aligning with those strong external fields. However, we also find a simple solution to that problem that indicates that those external fields apparently tilt the energy landscape to a such a degree such that global minima become more easy to find than those of spin glasses without (or very small) fields. We explore the impact of the weight distribution of the QUBO formulation in the operations research literature and analyze their meaning in a spin-glass language. This is significant because QUBO problems are considered among the main contenders for NP-hard problems that could be solved efficiently on a quantum computer such as D-Wave.

First-order convex feasibility algorithms for x-ray CT

PubMed Central

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

2013-01-01

Purpose: Iterative image reconstruction (IIR) algorithms in computed tomography (CT) are based on algorithms for solving a particular optimization problem. Design of the IIR algorithm, therefore, is aided by knowledge of the solution to the optimization problem on which it is based. Often times, however, it is impractical to achieve accurate solution to the optimization of interest, which complicates design of IIR algorithms. This issue is particularly acute for CT with a limited angular-range scan, which leads to poorly conditioned system matrices and difficult to solve optimization problems. In this paper, we develop IIR algorithms which solve a certain type of optimization called convex feasibility. The convex feasibility approach can provide alternatives to unconstrained optimization approaches and at the same time allow for rapidly convergent algorithms for their solution—thereby facilitating the IIR algorithm design process. Methods: An accelerated version of the Chambolle−Pock (CP) algorithm is adapted to various convex feasibility problems of potential interest to IIR in CT. One of the proposed problems is seen to be equivalent to least-squares minimization, and two other problems provide alternatives to penalized, least-squares minimization. Results: The accelerated CP algorithms are demonstrated on a simulation of circular fan-beam CT with a limited scanning arc of 144°. The CP algorithms are seen in the empirical results to converge to the solution of their respective convex feasibility problems. Conclusions: Formulation of convex feasibility problems can provide a useful alternative to unconstrained optimization when designing IIR algorithms for CT. The approach is amenable to recent methods for accelerating first-order algorithms which may be particularly useful for CT with limited angular-range scanning. The present paper demonstrates the methodology, and future work will illustrate its utility in actual CT application. PMID:23464295

Performance enhancement of fin attached ice-on-coil type thermal storage tank for different fin orientations using constrained and unconstrained simulations

NASA Astrophysics Data System (ADS)

Kim, M. H.; Duong, X. Q.; Chung, J. D.

2017-03-01

One of the drawbacks in latent thermal energy storage system is the slow charging and discharging time due to the low thermal conductivity of the phase change materials (PCM). This study numerically investigated the PCM melting process inside a finned tube to determine enhanced heat transfer performance. The influences of fin length and fin numbers were investigated. Also, two different fin orientations, a vertical and horizontal type, were examined, using two different simulation methods, constrained and unconstrained. The unconstrained simulation, which considers the density difference between the solid and liquid PCM showed approximately 40 % faster melting rate than that of constrained simulation. For a precise estimation of discharging performance, unconstrained simulation is essential. Thermal instability was found in the liquid layer below the solid PCM, which is contrary to the linear stability theory, due to the strong convection driven by heat flux from the coil wall. As the fin length increases, the area affected by the fin becomes larger, thus the discharging time becomes shorter. The discharging performance also increased as the fin number increased, but the enhancement of discharging performance by more than two fins was not discernible. The horizontal type shortened the complete melting time by approximately 10 % compared to the vertical type.

A new modified conjugate gradient coefficient for solving system of linear equations

NASA Astrophysics Data System (ADS)

Hajar, N.; ‘Aini, N.; Shapiee, N.; Abidin, Z. Z.; Khadijah, W.; Rivaie, M.; Mamat, M.

2017-09-01

Conjugate gradient (CG) method is an evolution of computational method in solving unconstrained optimization problems. This approach is easy to implement due to its simplicity and has been proven to be effective in solving real-life application. Although this field has received copious amount of attentions in recent years, some of the new approaches of CG algorithm cannot surpass the efficiency of the previous versions. Therefore, in this paper, a new CG coefficient which retains the sufficient descent and global convergence properties of the original CG methods is proposed. This new CG is tested on a set of test functions under exact line search. Its performance is then compared to that of some of the well-known previous CG methods based on number of iterations and CPU time. The results show that the new CG algorithm has the best efficiency amongst all the methods tested. This paper also includes an application of the new CG algorithm for solving large system of linear equations

Partial differential equations constrained combinatorial optimization on an adiabatic quantum computer

NASA Astrophysics Data System (ADS)

Chandra, Rishabh

Partial differential equation-constrained combinatorial optimization (PDECCO) problems are a mixture of continuous and discrete optimization problems. PDECCO problems have discrete controls, but since the partial differential equations (PDE) are continuous, the optimization space is continuous as well. Such problems have several applications, such as gas/water network optimization, traffic optimization, micro-chip cooling optimization, etc. Currently, no efficient classical algorithm which guarantees a global minimum for PDECCO problems exists. A new mapping has been developed that transforms PDECCO problem, which only have linear PDEs as constraints, into quadratic unconstrained binary optimization (QUBO) problems that can be solved using an adiabatic quantum optimizer (AQO). The mapping is efficient, it scales polynomially with the size of the PDECCO problem, requires only one PDE solve to form the QUBO problem, and if the QUBO problem is solved correctly and efficiently on an AQO, guarantees a global optimal solution for the original PDECCO problem.

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

PubMed

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.

Computational alternatives to obtain time optimal jet engine control. M.S. Thesis

NASA Technical Reports Server (NTRS)

Basso, R. J.; Leake, R. J.

1976-01-01

Two computational methods to determine an open loop time optimal control sequence for a simple single spool turbojet engine are described by a set of nonlinear differential equations. Both methods are modifications of widely accepted algorithms which can solve fixed time unconstrained optimal control problems with a free right end. Constrained problems to be considered have fixed right ends and free time. Dynamic programming is defined on a standard problem and it yields a successive approximation solution to the time optimal problem of interest. A feedback control law is obtained and it is then used to determine the corresponding open loop control sequence. The Fletcher-Reeves conjugate gradient method has been selected for adaptation to solve a nonlinear optimal control problem with state variable and control constraints.

Optimal mistuning for enhanced aeroelastic stability of transonic fans

NASA Technical Reports Server (NTRS)

Hall, K. C.; Crawley, E. F.

1983-01-01

An inverse design procedure was developed for the design of a mistuned rotor. The design requirements are that the stability margin of the eigenvalues of the aeroelastic system be greater than or equal to some minimum stability margin, and that the mass added to each blade be positive. The objective was to achieve these requirements with a minimal amount of mistuning. Hence, the problem was posed as a constrained optimization problem. The constrained minimization problem was solved by the technique of mathematical programming via augmented Lagrangians. The unconstrained minimization phase of this technique was solved by the variable metric method. The bladed disk was modelled as being composed of a rigid disk mounted on a rigid shaft. Each of the blades were modelled with a single tosional degree of freedom.

A computational algorithm for spacecraft control and momentum management

NASA Technical Reports Server (NTRS)

Dzielski, John; Bergmann, Edward; Paradiso, Joseph

1990-01-01

Developments in the area of nonlinear control theory have shown how coordinate changes in the state and input spaces of a dynamical system can be used to transform certain nonlinear differential equations into equivalent linear equations. These techniques are applied to the control of a spacecraft equipped with momentum exchange devices. An optimal control problem is formulated that incorporates a nonlinear spacecraft model. An algorithm is developed for solving the optimization problem using feedback linearization to transform to an equivalent problem involving a linear dynamical constraint and a functional approximation technique to solve for the linear dynamics in terms of the control. The original problem is transformed into an unconstrained nonlinear quadratic program that yields an approximate solution to the original problem. Two examples are presented to illustrate the results.

Poster — Thur Eve — 69: Computational Study of DVH-guided Cancer Treatment Planning Optimization Methods

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ghomi, Pooyan Shirvani; Zinchenko, Yuriy

2014-08-15

Purpose: To compare methods to incorporate the Dose Volume Histogram (DVH) curves into the treatment planning optimization. Method: The performance of three methods, namely, the conventional Mixed Integer Programming (MIP) model, a convex moment-based constrained optimization approach, and an unconstrained convex moment-based penalty approach, is compared using anonymized data of a prostate cancer patient. Three plans we generated using the corresponding optimization models. Four Organs at Risk (OARs) and one Tumor were involved in the treatment planning. The OARs and Tumor were discretized into total of 50,221 voxels. The number of beamlets was 943. We used commercially available optimization softwaremore » Gurobi and Matlab to solve the models. Plan comparison was done by recording the model runtime followed by visual inspection of the resulting dose volume histograms. Conclusion: We demonstrate the effectiveness of the moment-based approaches to replicate the set of prescribed DVH curves. The unconstrained convex moment-based penalty approach is concluded to have the greatest potential to reduce the computational effort and holds a promise of substantial computational speed up.« less

Application of augmented-Lagrangian methods in meteorology: Comparison of different conjugate-gradient codes for large-scale minimization

NASA Technical Reports Server (NTRS)

Navon, I. M.

1984-01-01

A Lagrange multiplier method using techniques developed by Bertsekas (1982) was applied to solving the problem of enforcing simultaneous conservation of the nonlinear integral invariants of the shallow water equations on a limited area domain. This application of nonlinear constrained optimization is of the large dimensional type and the conjugate gradient method was found to be the only computationally viable method for the unconstrained minimization. Several conjugate-gradient codes were tested and compared for increasing accuracy requirements. Robustness and computational efficiency were the principal criteria.

Very Large Scale Optimization

NASA Technical Reports Server (NTRS)

Vanderplaats, Garrett; Townsend, James C. (Technical Monitor)

2002-01-01

The purpose of this research under the NASA Small Business Innovative Research program was to develop algorithms and associated software to solve very large nonlinear, constrained optimization tasks. Key issues included efficiency, reliability, memory, and gradient calculation requirements. This report describes the general optimization problem, ten candidate methods, and detailed evaluations of four candidates. The algorithm chosen for final development is a modern recreation of a 1960s external penalty function method that uses very limited computer memory and computational time. Although of lower efficiency, the new method can solve problems orders of magnitude larger than current methods. The resulting BIGDOT software has been demonstrated on problems with 50,000 variables and about 50,000 active constraints. For unconstrained optimization, it has solved a problem in excess of 135,000 variables. The method includes a technique for solving discrete variable problems that finds a "good" design, although a theoretical optimum cannot be guaranteed. It is very scalable in that the number of function and gradient evaluations does not change significantly with increased problem size. Test cases are provided to demonstrate the efficiency and reliability of the methods and software.

A GA based penalty function technique for solving constrained redundancy allocation problem of series system with interval valued reliability of components

NASA Astrophysics Data System (ADS)

Gupta, R. K.; Bhunia, A. K.; Roy, D.

2009-10-01

In this paper, we have considered the problem of constrained redundancy allocation of series system with interval valued reliability of components. For maximizing the overall system reliability under limited resource constraints, the problem is formulated as an unconstrained integer programming problem with interval coefficients by penalty function technique and solved by an advanced GA for integer variables with interval fitness function, tournament selection, uniform crossover, uniform mutation and elitism. As a special case, considering the lower and upper bounds of the interval valued reliabilities of the components to be the same, the corresponding problem has been solved. The model has been illustrated with some numerical examples and the results of the series redundancy allocation problem with fixed value of reliability of the components have been compared with the existing results available in the literature. Finally, sensitivity analyses have been shown graphically to study the stability of our developed GA with respect to the different GA parameters.

Genetic Algorithm for Optimization: Preprocessor and Algorithm

NASA Technical Reports Server (NTRS)

Sen, S. K.; Shaykhian, Gholam A.

2006-01-01

Genetic algorithm (GA) inspired by Darwin's theory of evolution and employed to solve optimization problems - unconstrained or constrained - uses an evolutionary process. A GA has several parameters such the population size, search space, crossover and mutation probabilities, and fitness criterion. These parameters are not universally known/determined a priori for all problems. Depending on the problem at hand, these parameters need to be decided such that the resulting GA performs the best. We present here a preprocessor that achieves just that, i.e., it determines, for a specified problem, the foregoing parameters so that the consequent GA is a best for the problem. We stress also the need for such a preprocessor both for quality (error) and for cost (complexity) to produce the solution. The preprocessor includes, as its first step, making use of all the information such as that of nature/character of the function/system, search space, physical/laboratory experimentation (if already done/available), and the physical environment. It also includes the information that can be generated through any means - deterministic/nondeterministic/graphics. Instead of attempting a solution of the problem straightway through a GA without having/using the information/knowledge of the character of the system, we would do consciously a much better job of producing a solution by using the information generated/created in the very first step of the preprocessor. We, therefore, unstintingly advocate the use of a preprocessor to solve a real-world optimization problem including NP-complete ones before using the statistically most appropriate GA. We also include such a GA for unconstrained function optimization problems.

Path Following in the Exact Penalty Method of Convex Programming.

PubMed

Zhou, Hua; Lange, Kenneth

2015-07-01

Classical penalty methods solve a sequence of unconstrained problems that put greater and greater stress on meeting the constraints. In the limit as the penalty constant tends to ∞, one recovers the constrained solution. In the exact penalty method, squared penalties are replaced by absolute value penalties, and the solution is recovered for a finite value of the penalty constant. In practice, the kinks in the penalty and the unknown magnitude of the penalty constant prevent wide application of the exact penalty method in nonlinear programming. In this article, we examine a strategy of path following consistent with the exact penalty method. Instead of performing optimization at a single penalty constant, we trace the solution as a continuous function of the penalty constant. Thus, path following starts at the unconstrained solution and follows the solution path as the penalty constant increases. In the process, the solution path hits, slides along, and exits from the various constraints. For quadratic programming, the solution path is piecewise linear and takes large jumps from constraint to constraint. For a general convex program, the solution path is piecewise smooth, and path following operates by numerically solving an ordinary differential equation segment by segment. Our diverse applications to a) projection onto a convex set, b) nonnegative least squares, c) quadratically constrained quadratic programming, d) geometric programming, and e) semidefinite programming illustrate the mechanics and potential of path following. The final detour to image denoising demonstrates the relevance of path following to regularized estimation in inverse problems. In regularized estimation, one follows the solution path as the penalty constant decreases from a large value.

Path Following in the Exact Penalty Method of Convex Programming

PubMed Central

Zhou, Hua; Lange, Kenneth

2015-01-01

Classical penalty methods solve a sequence of unconstrained problems that put greater and greater stress on meeting the constraints. In the limit as the penalty constant tends to ∞, one recovers the constrained solution. In the exact penalty method, squared penalties are replaced by absolute value penalties, and the solution is recovered for a finite value of the penalty constant. In practice, the kinks in the penalty and the unknown magnitude of the penalty constant prevent wide application of the exact penalty method in nonlinear programming. In this article, we examine a strategy of path following consistent with the exact penalty method. Instead of performing optimization at a single penalty constant, we trace the solution as a continuous function of the penalty constant. Thus, path following starts at the unconstrained solution and follows the solution path as the penalty constant increases. In the process, the solution path hits, slides along, and exits from the various constraints. For quadratic programming, the solution path is piecewise linear and takes large jumps from constraint to constraint. For a general convex program, the solution path is piecewise smooth, and path following operates by numerically solving an ordinary differential equation segment by segment. Our diverse applications to a) projection onto a convex set, b) nonnegative least squares, c) quadratically constrained quadratic programming, d) geometric programming, and e) semidefinite programming illustrate the mechanics and potential of path following. The final detour to image denoising demonstrates the relevance of path following to regularized estimation in inverse problems. In regularized estimation, one follows the solution path as the penalty constant decreases from a large value. PMID:26366044

Mobile EEG on the bike: disentangling attentional and physical contributions to auditory attention tasks

NASA Astrophysics Data System (ADS)

Zink, Rob; Hunyadi, Borbála; Van Huffel, Sabine; De Vos, Maarten

2016-08-01

Objective. In the past few years there has been a growing interest in studying brain functioning in natural, real-life situations. Mobile EEG allows to study the brain in real unconstrained environments but it faces the intrinsic challenge that it is impossible to disentangle observed changes in brain activity due to increase in cognitive demands by the complex natural environment or due to the physical involvement. In this work we aim to disentangle the influence of cognitive demands and distractions that arise from such outdoor unconstrained recordings. Approach. We evaluate the ERP and single trial characteristics of a three-class auditory oddball paradigm recorded in outdoor scenario’s while peddling on a fixed bike or biking freely around. In addition we also carefully evaluate the trial specific motion artifacts through independent gyro measurements and control for muscle artifacts. Main results. A decrease in P300 amplitude was observed in the free biking condition as compared to the fixed bike conditions. Above chance P300 single-trial classification in highly dynamic real life environments while biking outdoors was achieved. Certain significant artifact patterns were identified in the free biking condition, but neither these nor the increase in movement (as derived from continuous gyrometer measurements) can explain the differences in classification accuracy and P300 waveform differences with full clarity. The increased cognitive load in real-life scenarios is shown to play a major role in the observed differences. Significance. Our findings suggest that auditory oddball results measured in natural real-life scenarios are influenced mainly by increased cognitive load due to being in an unconstrained environment.

Mobile EEG on the bike: disentangling attentional and physical contributions to auditory attention tasks.

PubMed

Zink, Rob; Hunyadi, Borbála; Huffel, Sabine Van; Vos, Maarten De

2016-08-01

In the past few years there has been a growing interest in studying brain functioning in natural, real-life situations. Mobile EEG allows to study the brain in real unconstrained environments but it faces the intrinsic challenge that it is impossible to disentangle observed changes in brain activity due to increase in cognitive demands by the complex natural environment or due to the physical involvement. In this work we aim to disentangle the influence of cognitive demands and distractions that arise from such outdoor unconstrained recordings. We evaluate the ERP and single trial characteristics of a three-class auditory oddball paradigm recorded in outdoor scenario's while peddling on a fixed bike or biking freely around. In addition we also carefully evaluate the trial specific motion artifacts through independent gyro measurements and control for muscle artifacts. A decrease in P300 amplitude was observed in the free biking condition as compared to the fixed bike conditions. Above chance P300 single-trial classification in highly dynamic real life environments while biking outdoors was achieved. Certain significant artifact patterns were identified in the free biking condition, but neither these nor the increase in movement (as derived from continuous gyrometer measurements) can explain the differences in classification accuracy and P300 waveform differences with full clarity. The increased cognitive load in real-life scenarios is shown to play a major role in the observed differences. Our findings suggest that auditory oddball results measured in natural real-life scenarios are influenced mainly by increased cognitive load due to being in an unconstrained environment.

Guided particle swarm optimization method to solve general nonlinear optimization problems

NASA Astrophysics Data System (ADS)

Abdelhalim, Alyaa; Nakata, Kazuhide; El-Alem, Mahmoud; Eltawil, Amr

2018-04-01

The development of hybrid algorithms is becoming an important topic in the global optimization research area. This article proposes a new technique in hybridizing the particle swarm optimization (PSO) algorithm and the Nelder-Mead (NM) simplex search algorithm to solve general nonlinear unconstrained optimization problems. Unlike traditional hybrid methods, the proposed method hybridizes the NM algorithm inside the PSO to improve the velocities and positions of the particles iteratively. The new hybridization considers the PSO algorithm and NM algorithm as one heuristic, not in a sequential or hierarchical manner. The NM algorithm is applied to improve the initial random solution of the PSO algorithm and iteratively in every step to improve the overall performance of the method. The performance of the proposed method was tested over 20 optimization test functions with varying dimensions. Comprehensive comparisons with other methods in the literature indicate that the proposed solution method is promising and competitive.

A sequential solution for anisotropic total variation image denoising with interval constraints

NASA Astrophysics Data System (ADS)

Xu, Jingyan; Noo, Frédéric

2017-09-01

We show that two problems involving the anisotropic total variation (TV) and interval constraints on the unknown variables admit, under some conditions, a simple sequential solution. Problem 1 is a constrained TV penalized image denoising problem; problem 2 is a constrained fused lasso signal approximator. The sequential solution entails finding first the solution to the unconstrained problem, and then applying a thresholding to satisfy the constraints. If the interval constraints are uniform, this sequential solution solves problem 1. If the interval constraints furthermore contain zero, the sequential solution solves problem 2. Here uniform interval constraints refer to all unknowns being constrained to the same interval. A typical example of application is image denoising in x-ray CT, where the image intensities are non-negative as they physically represent linear attenuation coefficient in the patient body. Our results are simple yet seem unknown; we establish them using the Karush-Kuhn-Tucker conditions for constrained convex optimization.

A Path Algorithm for Constrained Estimation

PubMed Central

Zhou, Hua; Lange, Kenneth

2013-01-01

Many least-square problems involve affine equality and inequality constraints. Although there are a variety of methods for solving such problems, most statisticians find constrained estimation challenging. The current article proposes a new path-following algorithm for quadratic programming that replaces hard constraints by what are called exact penalties. Similar penalties arise in l1 regularization in model selection. In the regularization setting, penalties encapsulate prior knowledge, and penalized parameter estimates represent a trade-off between the observed data and the prior knowledge. Classical penalty methods of optimization, such as the quadratic penalty method, solve a sequence of unconstrained problems that put greater and greater stress on meeting the constraints. In the limit as the penalty constant tends to ∞, one recovers the constrained solution. In the exact penalty method, squared penalties!are replaced by absolute value penalties, and the solution is recovered for a finite value of the penalty constant. The exact path-following method starts at the unconstrained solution and follows the solution path as the penalty constant increases. In the process, the solution path hits, slides along, and exits from the various constraints. Path following in Lasso penalized regression, in contrast, starts with a large value of the penalty constant and works its way downward. In both settings, inspection of the entire solution path is revealing. Just as with the Lasso and generalized Lasso, it is possible to plot the effective degrees of freedom along the solution path. For a strictly convex quadratic program, the exact penalty algorithm can be framed entirely in terms of the sweep operator of regression analysis. A few well-chosen examples illustrate the mechanics and potential of path following. This article has supplementary materials available online. PMID:24039382

Influence of Valley Floor Landforms on Stream Ecosystems

Treesearch

Stanley V. Gregory; Gary A. Lamberti; Kelly M. S. Moore

1989-01-01

A hierarchical perspective of relationships between valley floor landforms, riparian plant communities, and aquatic ecosystems has been developed, based on studies of two fifth-order basins in the Cascade Mountains of Oregon. Retention of dissolved nitrogen and leaves were approximately 2-3 times greater in unconstrained reaches than in constrained reaches. Both valley...

Impact of DNA twist accumulation on progressive helical wrapping of torsionally constrained DNA.

PubMed

Li, Wei; Wang, Peng-Ye; Yan, Jie; Li, Ming

2012-11-21

DNA wrapping is an important mechanism for chromosomal DNA packaging in cells and viruses. Previous studies of DNA wrapping have been performed mostly on torsionally unconstrained DNA, while in vivo DNA is often under torsional constraint. In this study, we extend a previously proposed theoretical model for wrapping of torsionally unconstrained DNA to a new model including the contribution of DNA twist energy, which influences DNA wrapping drastically. In particular, due to accumulation of twist energy during DNA wrapping, it predicts a finite amount of DNA that can be wrapped on a helical spool. The predictions of the new model are tested by single-molecule study of DNA wrapping under torsional constraint using magnetic tweezers. The theoretical predictions and the experimental results are consistent with each other and their implications are discussed.

Thermo-mechanical behavior and structure of melt blown shape-memory polyurethane nonwovens.

PubMed

Safranski, David L; Boothby, Jennifer M; Kelly, Cambre N; Beatty, Kyle; Lakhera, Nishant; Frick, Carl P; Lin, Angela; Guldberg, Robert E; Griffis, Jack C

2016-09-01

New processing methods for shape-memory polymers allow for tailoring material properties for numerous applications. Shape-memory nonwovens have been previously electrospun, but melt blow processing has yet to be evaluated. In order to determine the process parameters affecting shape-memory behavior, this study examined the effect of air pressure and collector speed on the mechanical behavior and shape-recovery of shape-memory polyurethane nonwovens. Mechanical behavior was measured by dynamic mechanical analysis and tensile testing, and shape-recovery was measured by unconstrained and constrained recovery. Microstructure changes throughout the shape-memory cycle were also investigated by micro-computed tomography. It was found that increasing collector speed increases elastic modulus, ultimate strength and recovery stress of the nonwoven, but collector speed does not affect the failure strain or unconstrained recovery. Increasing air pressure decreases the failure strain and increases rubbery modulus and unconstrained recovery, but air pressure does not influence recovery stress. It was also found that during the shape-memory cycle, the connectivity density of the fibers upon recovery does not fully return to the initial values, accounting for the incomplete shape-recovery seen in shape-memory nonwovens. With these parameter to property relationships identified, shape-memory nonwovens can be more easily manufactured and tailored for specific applications. Copyright © 2016 Elsevier Ltd. All rights reserved.

A transformation method for constrained-function minimization

NASA Technical Reports Server (NTRS)

Park, S. K.

1975-01-01

A direct method for constrained-function minimization is discussed. The method involves the construction of an appropriate function mapping all of one finite dimensional space onto the region defined by the constraints. Functions which produce such a transformation are constructed for a variety of constraint regions including, for example, those arising from linear and quadratic inequalities and equalities. In addition, the computational performance of this method is studied in the situation where the Davidon-Fletcher-Powell algorithm is used to solve the resulting unconstrained problem. Good performance is demonstrated for 19 test problems by achieving rapid convergence to a solution from several widely separated starting points.

Global Optimization of Interplanetary Trajectories in the Presence of Realistic Mission Contraints

NASA Technical Reports Server (NTRS)

Hinckley, David, Jr.; Englander, Jacob; Hitt, Darren

2015-01-01

Interplanetary missions are often subject to difficult constraints, like solar phase angle upon arrival at the destination, velocity at arrival, and altitudes for flybys. Preliminary design of such missions is often conducted by solving the unconstrained problem and then filtering away solutions which do not naturally satisfy the constraints. However this can bias the search into non-advantageous regions of the solution space, so it can be better to conduct preliminary design with the full set of constraints imposed. In this work two stochastic global search methods are developed which are well suited to the constrained global interplanetary trajectory optimization problem.

Generalized Pattern Search methods for a class of nonsmooth optimization problems with structure

NASA Astrophysics Data System (ADS)

Bogani, C.; Gasparo, M. G.; Papini, A.

2009-07-01

We propose a Generalized Pattern Search (GPS) method to solve a class of nonsmooth minimization problems, where the set of nondifferentiability is included in the union of known hyperplanes and, therefore, is highly structured. Both unconstrained and linearly constrained problems are considered. At each iteration the set of poll directions is enforced to conform to the geometry of both the nondifferentiability set and the boundary of the feasible region, near the current iterate. This is the key issue to guarantee the convergence of certain subsequences of iterates to points which satisfy first-order optimality conditions. Numerical experiments on some classical problems validate the method.

Spacecraft inertia estimation via constrained least squares

NASA Technical Reports Server (NTRS)

Keim, Jason A.; Acikmese, Behcet A.; Shields, Joel F.

2006-01-01

This paper presents a new formulation for spacecraft inertia estimation from test data. Specifically, the inertia estimation problem is formulated as a constrained least squares minimization problem with explicit bounds on the inertia matrix incorporated as LMIs [linear matrix inequalities). The resulting minimization problem is a semidefinite optimization that can be solved efficiently with guaranteed convergence to the global optimum by readily available algorithms. This method is applied to data collected from a robotic testbed consisting of a freely rotating body. The results show that the constrained least squares approach produces more accurate estimates of the inertia matrix than standard unconstrained least squares estimation methods.

Task Context Influences Brain Activation during Music Listening

PubMed Central

Markovic, Andjela; Kühnis, Jürg; Jäncke, Lutz

2017-01-01

In this paper, we examined brain activation in subjects during two music listening conditions: listening while simultaneously rating the musical piece being played [Listening and Rating (LR)] and listening to the musical pieces unconstrained [Listening (L)]. Using these two conditions, we tested whether the sequence in which the two conditions were fulfilled influenced the brain activation observable during the L condition (LR → L or L → LR). We recorded high-density EEG during the playing of four well-known positively experienced soundtracks in two subject groups. One group started with the L condition and continued with the LR condition (L → LR); the second group performed this experiment in reversed order (LR → L). We computed from the recorded EEG the power for different frequency bands (theta, lower alpha, upper alpha, lower beta, and upper beta). Statistical analysis revealed that the power in all examined frequency bands increased during the L condition but only when the subjects had not had previous experience with the LR condition (i.e., L → LR). For the subjects who began with the LR condition, there were no power increases during the L condition. Thus, the previous experience with the LR condition prevented subjects from developing the particular mental state associated with the typical power increase in all frequency bands. The subjects without previous experience of the LR condition listened to the musical pieces in an unconstrained and undisturbed manner and showed a general power increase in all frequency bands. We interpret the fact that unconstrained music listening was associated with increased power in all examined frequency bands as a neural indicator of a mental state that can best be described as a mind-wandering state during which the subjects are “drawn into” the music. PMID:28706480

NEWSUMT: A FORTRAN program for inequality constrained function minimization, users guide

NASA Technical Reports Server (NTRS)

Miura, H.; Schmit, L. A., Jr.

1979-01-01

A computer program written in FORTRAN subroutine form for the solution of linear and nonlinear constrained and unconstrained function minimization problems is presented. The algorithm is the sequence of unconstrained minimizations using the Newton's method for unconstrained function minimizations. The use of NEWSUMT and the definition of all parameters are described.

Modeling Latent Interactions at Level 2 in Multilevel Structural Equation Models: An Evaluation of Mean-Centered and Residual-Centered Unconstrained Approaches

ERIC Educational Resources Information Center

Leite, Walter L.; Zuo, Youzhen

2011-01-01

Among the many methods currently available for estimating latent variable interactions, the unconstrained approach is attractive to applied researchers because of its relatively easy implementation with any structural equation modeling (SEM) software. Using a Monte Carlo simulation study, we extended and evaluated the unconstrained approach to…

Geomorphic and Riparian Influences on the Distribution and Abundance of Salmonids in a Cascade Mountain Stream

Treesearch

Kelly M.S. Moore; Stan V. Gregory

1989-01-01

Abundance of resident cutthroat (Salmo clarki) and rainbow (Salmo gairdneri) trout was generally 1.5 to 3.5 times greater in unconstrained reaches than in con-strained reaches of Lookout Creek, a fourth-order tributary to the McKenzie River, Oregon. The presence of adult rainbow trout depressed juvenile abundance in pools with...

Minimal norm constrained interpolation. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Irvine, L. D.

1985-01-01

In computational fluid dynamics and in CAD/CAM, a physical boundary is usually known only discreetly and most often must be approximated. An acceptable approximation preserves the salient features of the data such as convexity and concavity. In this dissertation, a smooth interpolant which is locally concave where the data are concave and is locally convex where the data are convex is described. The interpolant is found by posing and solving a minimization problem whose solution is a piecewise cubic polynomial. The problem is solved indirectly by using the Peano Kernal theorem to recast it into an equivalent minimization problem having the second derivative of the interpolant as the solution. This approach leads to the solution of a nonlinear system of equations. It is shown that Newton's method is an exceptionally attractive and efficient method for solving the nonlinear system of equations. Examples of shape-preserving interpolants, as well as convergence results obtained by using Newton's method are also shown. A FORTRAN program to compute these interpolants is listed. The problem of computing the interpolant of minimal norm from a convex cone in a normal dual space is also discussed. An extension of de Boor's work on minimal norm unconstrained interpolation is presented.

Infrared and visible image fusion based on total variation and augmented Lagrangian.

PubMed

Guo, Hanqi; Ma, Yong; Mei, Xiaoguang; Ma, Jiayi

2017-11-01

This paper proposes a new algorithm for infrared and visible image fusion based on gradient transfer that achieves fusion by preserving the intensity of the infrared image and then transferring gradients in the corresponding visible one to the result. The gradient transfer suffers from the problems of low dynamic range and detail loss because it ignores the intensity from the visible image. The new algorithm solves these problems by providing additive intensity from the visible image to balance the intensity between the infrared image and the visible one. It formulates the fusion task as an l 1 -l 1 -TV minimization problem and then employs variable splitting and augmented Lagrangian to convert the unconstrained problem to a constrained one that can be solved in the framework of alternating the multiplier direction method. Experiments demonstrate that the new algorithm achieves better fusion results with a high computation efficiency in both qualitative and quantitative tests than gradient transfer and most state-of-the-art methods.

Boosting quantum annealer performance via sample persistence

NASA Astrophysics Data System (ADS)

Karimi, Hamed; Rosenberg, Gili

2017-07-01

We propose a novel method for reducing the number of variables in quadratic unconstrained binary optimization problems, using a quantum annealer (or any sampler) to fix the value of a large portion of the variables to values that have a high probability of being optimal. The resulting problems are usually much easier for the quantum annealer to solve, due to their being smaller and consisting of disconnected components. This approach significantly increases the success rate and number of observations of the best known energy value in samples obtained from the quantum annealer, when compared with calling the quantum annealer without using it, even when using fewer annealing cycles. Use of the method results in a considerable improvement in success metrics even for problems with high-precision couplers and biases, which are more challenging for the quantum annealer to solve. The results are further enhanced by applying the method iteratively and combining it with classical pre-processing. We present results for both Chimera graph-structured problems and embedded problems from a real-world application.

Performance evaluation of firefly algorithm with variation in sorting for non-linear benchmark problems

NASA Astrophysics Data System (ADS)

Umbarkar, A. J.; Balande, U. T.; Seth, P. D.

2017-06-01

The field of nature inspired computing and optimization techniques have evolved to solve difficult optimization problems in diverse fields of engineering, science and technology. The firefly attraction process is mimicked in the algorithm for solving optimization problems. In Firefly Algorithm (FA) sorting of fireflies is done by using sorting algorithm. The original FA is proposed with bubble sort for ranking the fireflies. In this paper, the quick sort replaces bubble sort to decrease the time complexity of FA. The dataset used is unconstrained benchmark functions from CEC 2005 [22]. The comparison of FA using bubble sort and FA using quick sort is performed with respect to best, worst, mean, standard deviation, number of comparisons and execution time. The experimental result shows that FA using quick sort requires less number of comparisons but requires more execution time. The increased number of fireflies helps to converge into optimal solution whereas by varying dimension for algorithm performed better at a lower dimension than higher dimension.

Digital Image Restoration Under a Regression Model - The Unconstrained, Linear Equality and Inequality Constrained Approaches

DTIC Science & Technology

1974-01-01

REGRESSION MODEL - THE UNCONSTRAINED, LINEAR EQUALITY AND INEQUALITY CONSTRAINED APPROACHES January 1974 Nelson Delfino d’Avila Mascarenha;? Image...Report 520 DIGITAL IMAGE RESTORATION UNDER A REGRESSION MODEL THE UNCONSTRAINED, LINEAR EQUALITY AND INEQUALITY CONSTRAINED APPROACHES January...a two- dimensional form adequately describes the linear model . A dis- cretization is performed by using quadrature methods. By trans

New hybrid conjugate gradient methods with the generalized Wolfe line search.

PubMed

Xu, Xiao; Kong, Fan-Yu

2016-01-01

The conjugate gradient method was an efficient technique for solving the unconstrained optimization problem. In this paper, we made a linear combination with parameters β k of the DY method and the HS method, and putted forward the hybrid method of DY and HS. We also proposed the hybrid of FR and PRP by the same mean. Additionally, to present the two hybrid methods, we promoted the Wolfe line search respectively to compute the step size α k of the two hybrid methods. With the new Wolfe line search, the two hybrid methods had descent property and global convergence property of the two hybrid methods that can also be proved.

Kinetic and dynamic Delaunay tetrahedralizations in three dimensions

NASA Astrophysics Data System (ADS)

Schaller, Gernot; Meyer-Hermann, Michael

2004-09-01

We describe algorithms to implement fully dynamic and kinetic three-dimensional unconstrained Delaunay triangulations, where the time evolution of the triangulation is not only governed by moving vertices but also by a changing number of vertices. We use three-dimensional simplex flip algorithms, a stochastic visibility walk algorithm for point location and in addition, we propose a new simple method of deleting vertices from an existing three-dimensional Delaunay triangulation while maintaining the Delaunay property. As an example, we analyse the performance in various cases of practical relevance. The dual Dirichlet tessellation can be used to solve differential equations on an irregular grid, to define partitions in cell tissue simulations, for collision detection etc.

Robust Adaptive Modified Newton Algorithm for Generalized Eigendecomposition and Its Application

NASA Astrophysics Data System (ADS)

Yang, Jian; Yang, Feng; Xi, Hong-Sheng; Guo, Wei; Sheng, Yanmin

2007-12-01

We propose a robust adaptive algorithm for generalized eigendecomposition problems that arise in modern signal processing applications. To that extent, the generalized eigendecomposition problem is reinterpreted as an unconstrained nonlinear optimization problem. Starting from the proposed cost function and making use of an approximation of the Hessian matrix, a robust modified Newton algorithm is derived. A rigorous analysis of its convergence properties is presented by using stochastic approximation theory. We also apply this theory to solve the signal reception problem of multicarrier DS-CDMA to illustrate its practical application. The simulation results show that the proposed algorithm has fast convergence and excellent tracking capability, which are important in a practical time-varying communication environment.

A new nonlinear conjugate gradient coefficient under strong Wolfe-Powell line search

NASA Astrophysics Data System (ADS)

Mohamed, Nur Syarafina; Mamat, Mustafa; Rivaie, Mohd

2017-08-01

A nonlinear conjugate gradient method (CG) plays an important role in solving a large-scale unconstrained optimization problem. This method is widely used due to its simplicity. The method is known to possess sufficient descend condition and global convergence properties. In this paper, a new nonlinear of CG coefficient βk is presented by employing the Strong Wolfe-Powell inexact line search. The new βk performance is tested based on number of iterations and central processing unit (CPU) time by using MATLAB software with Intel Core i7-3470 CPU processor. Numerical experimental results show that the new βk converge rapidly compared to other classical CG method.

Numerical optimization methods for controlled systems with parameters

NASA Astrophysics Data System (ADS)

Tyatyushkin, A. I.

2017-10-01

First- and second-order numerical methods for optimizing controlled dynamical systems with parameters are discussed. In unconstrained-parameter problems, the control parameters are optimized by applying the conjugate gradient method. A more accurate numerical solution in these problems is produced by Newton's method based on a second-order functional increment formula. Next, a general optimal control problem with state constraints and parameters involved on the righthand sides of the controlled system and in the initial conditions is considered. This complicated problem is reduced to a mathematical programming one, followed by the search for optimal parameter values and control functions by applying a multimethod algorithm. The performance of the proposed technique is demonstrated by solving application problems.

Distributed Optimization

NASA Technical Reports Server (NTRS)

Macready, William; Wolpert, David

2005-01-01

We demonstrate a new framework for analyzing and controlling distributed systems, by solving constrained optimization problems with an algorithm based on that framework. The framework is ar. information-theoretic extension of conventional full-rationality game theory to allow bounded rational agents. The associated optimization algorithm is a game in which agents control the variables of the optimization problem. They do this by jointly minimizing a Lagrangian of (the probability distribution of) their joint state. The updating of the Lagrange parameters in that Lagrangian is a form of automated annealing, one that focuses the multi-agent system on the optimal pure strategy. We present computer experiments for the k-sat constraint satisfaction problem and for unconstrained minimization of NK functions.

Multidigit force control during unconstrained grasping in response to object perturbations

PubMed Central

Haschke, Robert; Ritter, Helge; Santello, Marco; Ernst, Marc O.

2017-01-01

Because of the complex anatomy of the human hand, in the absence of external constraints, a large number of postures and force combinations can be used to attain a stable grasp. Motor synergies provide a viable strategy to solve this problem of motor redundancy. In this study, we exploited the technical advantages of an innovative sensorized object to study unconstrained hand grasping within the theoretical framework of motor synergies. Participants were required to grasp, lift, and hold the sensorized object. During the holding phase, we repetitively applied external disturbance forces and torques and recorded the spatiotemporal distribution of grip forces produced by each digit. We found that the time to reach the maximum grip force during each perturbation was roughly equal across fingers, consistent with a synchronous, synergistic stiffening across digits. We further evaluated this hypothesis by comparing the force distribution of human grasping vs. robotic grasping, where the control strategy was set by the experimenter. We controlled the global hand stiffness of the robotic hand and found that this control algorithm produced a force pattern qualitatively similar to human grasping performance. Our results suggest that the nervous system uses a default whole hand synergistic control to maintain a stable grasp regardless of the number of digits involved in the task, their position on the objects, and the type and frequency of external perturbations. NEW & NOTEWORTHY We studied hand grasping using a sensorized object allowing unconstrained finger placement. During object perturbation, the time to reach the peak force was roughly equal across fingers, consistently with a synergistic stiffening across fingers. Force distribution of a robotic grasping hand, where the control algorithm is based on global hand stiffness, was qualitatively similar to human grasping. This suggests that the central nervous system uses a default whole hand synergistic control to maintain a stable grasp. PMID:28228582

Constrained Laboratory vs. Unconstrained Steering-Induced Rollover Crash Tests.

PubMed

Kerrigan, Jason R; Toczyski, Jacek; Roberts, Carolyn; Zhang, Qi; Clauser, Mark

2015-01-01

The goal of this study was to evaluate how well an in-laboratory rollover crash test methodology that constrains vehicle motion can reproduce the dynamics of unconstrained full-scale steering-induced rollover crash tests in sand. Data from previously-published unconstrained steering-induced rollover crash tests using a full-size pickup and mid-sized sedan were analyzed to determine vehicle-to-ground impact conditions and kinematic response of the vehicles throughout the tests. Then, a pair of replicate vehicles were prepared to match the inertial properties of the steering-induced test vehicles and configured to record dynamic roof structure deformations and kinematic response. Both vehicles experienced greater increases in roll-axis angular velocities in the unconstrained tests than in the constrained tests; however, the increases that occurred during the trailing side roof interaction were nearly identical between tests for both vehicles. Both vehicles experienced linear accelerations in the constrained tests that were similar to those in the unconstrained tests, but the pickup, in particular, had accelerations that were matched in magnitude, timing, and duration very closely between the two test types. Deformations in the truck test were higher in the constrained than the unconstrained, and deformations in the sedan were greater in the unconstrained than the constrained as a result of constraints of the test fixture, and differences in impact velocity for the trailing side. The results of the current study suggest that in-laboratory rollover tests can be used to simulate the injury-causing portions of unconstrained rollover crashes. To date, such a demonstration has not yet been published in the open literature. This study did, however, show that road surface can affect vehicle response in a way that may not be able to be mimicked in the laboratory. Lastly, this study showed that configuring the in-laboratory tests to match the leading-side touchdown conditions could result in differences in the trailing side impact conditions.

Improvements on ν-Twin Support Vector Machine.

PubMed

Khemchandani, Reshma; Saigal, Pooja; Chandra, Suresh

2016-07-01

In this paper, we propose two novel binary classifiers termed as "Improvements on ν-Twin Support Vector Machine: Iν-TWSVM and Iν-TWSVM (Fast)" that are motivated by ν-Twin Support Vector Machine (ν-TWSVM). Similar to ν-TWSVM, Iν-TWSVM determines two nonparallel hyperplanes such that they are closer to their respective classes and are at least ρ distance away from the other class. The significant advantage of Iν-TWSVM over ν-TWSVM is that Iν-TWSVM solves one smaller-sized Quadratic Programming Problem (QPP) and one Unconstrained Minimization Problem (UMP); as compared to solving two related QPPs in ν-TWSVM. Further, Iν-TWSVM (Fast) avoids solving a smaller sized QPP and transforms it as a unimodal function, which can be solved using line search methods and similar to Iν-TWSVM, the other problem is solved as a UMP. Due to their novel formulation, the proposed classifiers are faster than ν-TWSVM and have comparable generalization ability. Iν-TWSVM also implements structural risk minimization (SRM) principle by introducing a regularization term, along with minimizing the empirical risk. The other properties of Iν-TWSVM, related to support vectors (SVs), are similar to that of ν-TWSVM. To test the efficacy of the proposed method, experiments have been conducted on a wide range of UCI and a skewed variation of NDC datasets. We have also given the application of Iν-TWSVM as a binary classifier for pixel classification of color images. Copyright © 2016 Elsevier Ltd. All rights reserved.

Split Bregman's optimization method for image construction in compressive sensing

NASA Astrophysics Data System (ADS)

Skinner, D.; Foo, S.; Meyer-Bäse, A.

2014-05-01

The theory of compressive sampling (CS) was reintroduced by Candes, Romberg and Tao, and D. Donoho in 2006. Using a priori knowledge that a signal is sparse, it has been mathematically proven that CS can defY Nyquist sampling theorem. Theoretically, reconstruction of a CS image relies on the minimization and optimization techniques to solve this complex almost NP-complete problem. There are many paths to consider when compressing and reconstructing an image but these methods have remained untested and unclear on natural images, such as underwater sonar images. The goal of this research is to perfectly reconstruct the original sonar image from a sparse signal while maintaining pertinent information, such as mine-like object, in Side-scan sonar (SSS) images. Goldstein and Osher have shown how to use an iterative method to reconstruct the original image through a method called Split Bregman's iteration. This method "decouples" the energies using portions of the energy from both the !1 and !2 norm. Once the energies are split, Bregman iteration is used to solve the unconstrained optimization problem by recursively solving the problems simultaneously. The faster these two steps or energies can be solved then the faster the overall method becomes. While the majority of CS research is still focused on the medical field, this paper will demonstrate the effectiveness of the Split Bregman's methods on sonar images.

Using Grey Wolf Algorithm to Solve the Capacitated Vehicle Routing Problem

NASA Astrophysics Data System (ADS)

Korayem, L.; Khorsid, M.; Kassem, S. S.

2015-05-01

The capacitated vehicle routing problem (CVRP) is a class of the vehicle routing problems (VRPs). In CVRP a set of identical vehicles having fixed capacities are required to fulfill customers' demands for a single commodity. The main objective is to minimize the total cost or distance traveled by the vehicles while satisfying a number of constraints, such as: the capacity constraint of each vehicle, logical flow constraints, etc. One of the methods employed in solving the CVRP is the cluster-first route-second method. It is a technique based on grouping of customers into a number of clusters, where each cluster is served by one vehicle. Once clusters are formed, a route determining the best sequence to visit customers is established within each cluster. The recently bio-inspired grey wolf optimizer (GWO), introduced in 2014, has proven to be efficient in solving unconstrained, as well as, constrained optimization problems. In the current research, our main contributions are: combining GWO with the traditional K-means clustering algorithm to generate the ‘K-GWO’ algorithm, deriving a capacitated version of the K-GWO algorithm by incorporating a capacity constraint into the aforementioned algorithm, and finally, developing 2 new clustering heuristics. The resulting algorithm is used in the clustering phase of the cluster-first route-second method to solve the CVR problem. The algorithm is tested on a number of benchmark problems with encouraging results.

Long-range interacting systems in the unconstrained ensemble.

PubMed

Latella, Ivan; Pérez-Madrid, Agustín; Campa, Alessandro; Casetti, Lapo; Ruffo, Stefano

2017-01-01

Completely open systems can exchange heat, work, and matter with the environment. While energy, volume, and number of particles fluctuate under completely open conditions, the equilibrium states of the system, if they exist, can be specified using the temperature, pressure, and chemical potential as control parameters. The unconstrained ensemble is the statistical ensemble describing completely open systems and the replica energy is the appropriate free energy for these control parameters from which the thermodynamics must be derived. It turns out that macroscopic systems with short-range interactions cannot attain equilibrium configurations in the unconstrained ensemble, since temperature, pressure, and chemical potential cannot be taken as a set of independent variables in this case. In contrast, we show that systems with long-range interactions can reach states of thermodynamic equilibrium in the unconstrained ensemble. To illustrate this fact, we consider a modification of the Thirring model and compare the unconstrained ensemble with the canonical and grand-canonical ones: The more the ensemble is constrained by fixing the volume or number of particles, the larger the space of parameters defining the equilibrium configurations.

The tangential velocity of M31: CLUES from constrained simulations

NASA Astrophysics Data System (ADS)

Carlesi, Edoardo; Hoffman, Yehuda; Sorce, Jenny G.; Gottlöber, Stefan; Yepes, Gustavo; Courtois, Hélène; Tully, R. Brent

2016-07-01

Determining the precise value of the tangential component of the velocity of M31 is a non-trivial astrophysical issue that relies on complicated modelling. This has recently lead to conflicting estimates, obtained by several groups that used different methodologies and assumptions. This Letter addresses the issue by computing a Bayesian posterior distribution function of this quantity, in order to measure the compatibility of those estimates with Λ cold dark matter (ΛCDM). This is achieved using an ensemble of Local Group (LG) look-alikes collected from a set of constrained simulations (CSs) of the local Universe, and a standard unconstrained ΛCDM. The latter allows us to build a control sample of LG-like pairs and to single out the influence of the environment in our results. We find that neither estimate is at odds with ΛCDM; however, whereas CSs favour higher values of vtan, the reverse is true for estimates based on LG samples gathered from unconstrained simulations, overlooking the environmental element.

Intraoperative pulmonary embolism of Harrington rod during spinal surgery: the potential dangers of rod cutting.

PubMed

Aylott, Caspar E W; Hassan, Kamran; McNally, Donal; Webb, John K

2006-12-01

This is a case report and laboratory-based biomechanics study. The objective is to report the first case of Titanium rod embolisation during scoliosis surgery into the Pulmonary artery. To investigate the potential of an unconstrained cut Titanium rod fragment to cause wounding with reference to recognised weapons. Embolisation of a foreign body to the heart is rare. Bullet embolisation to the heart and lungs is infrequently reported in the last 80 years. Iatrogenic cases of foreign body embolisation are very rare. Fifty 1-2 cm segments of Titanium rod were cut in an unconstrained manner and a novel method was used to calculate velocity. A high-speed camera (6,000 frames/s) was used to further measure velocity and study projectile motion. The wounding potential was investigated using lambs liver, high-speed photography and local dissection. Rod velocities were measured in excess of 23 m s(-1). Rods were seen to tumble end-over-end with a maximum speed of 560 revolutions/s. The maximum kinetic energy was 0.61 J which is approximately 2% that of a crossbow. This is sufficient to cause significant liver damage. The degree of surface damage and internal disruption was influenced by the orientation of the rod fragment at impact. An unconstrained cut segment of a Titanium rod has a significant potential to wound. Precautions should be taken to avoid this potentially disastrous but preventable complication.

Differential geometric treewidth estimation in adiabatic quantum computation

NASA Astrophysics Data System (ADS)

Wang, Chi; Jonckheere, Edmond; Brun, Todd

2016-10-01

The D-Wave adiabatic quantum computing platform is designed to solve a particular class of problems—the Quadratic Unconstrained Binary Optimization (QUBO) problems. Due to the particular "Chimera" physical architecture of the D-Wave chip, the logical problem graph at hand needs an extra process called minor embedding in order to be solvable on the D-Wave architecture. The latter problem is itself NP-hard. In this paper, we propose a novel polynomial-time approximation to the closely related treewidth based on the differential geometric concept of Ollivier-Ricci curvature. The latter runs in polynomial time and thus could significantly reduce the overall complexity of determining whether a QUBO problem is minor embeddable, and thus solvable on the D-Wave architecture.

Metabolic flux estimation using particle swarm optimization with penalty function.

PubMed

Long, Hai-Xia; Xu, Wen-Bo; Sun, Jun

2009-01-01

Metabolic flux estimation through 13C trace experiment is crucial for quantifying the intracellular metabolic fluxes. In fact, it corresponds to a constrained optimization problem that minimizes a weighted distance between measured and simulated results. In this paper, we propose particle swarm optimization (PSO) with penalty function to solve 13C-based metabolic flux estimation problem. The stoichiometric constraints are transformed to an unconstrained one, by penalizing the constraints and building a single objective function, which in turn is minimized using PSO algorithm for flux quantification. The proposed algorithm is applied to estimate the central metabolic fluxes of Corynebacterium glutamicum. From simulation results, it is shown that the proposed algorithm has superior performance and fast convergence ability when compared to other existing algorithms.

Some new results on the central overlap problem in astrometry

NASA Astrophysics Data System (ADS)

Rapaport, M.

1998-07-01

The central overlap problem in astrometry has been revisited in the recent last years by Eichhorn (1988) who explicitly inverted the matrix of a constrained least squares problem. In this paper, the general explicit solution of the unconstrained central overlap problem is given. We also give the explicit solution for an other set of constraints; this result is a confirmation of a conjecture expressed by Eichhorn (1988). We also consider the use of iterative methods to solve the central overlap problem. A surprising result is obtained when the classical Gauss Seidel method is used; the iterations converge immediately to the general solution of the equations; we explain this property writing the central overlap problem in a new set of variables.

Single-Camera-Based Method for Step Length Symmetry Measurement in Unconstrained Elderly Home Monitoring.

PubMed

Cai, Xi; Han, Guang; Song, Xin; Wang, Jinkuan

2017-11-01

single-camera-based gait monitoring is unobtrusive, inexpensive, and easy-to-use to monitor daily gait of seniors in their homes. However, most studies require subjects to walk perpendicularly to camera's optical axis or along some specified routes, which limits its application in elderly home monitoring. To build unconstrained monitoring environments, we propose a method to measure step length symmetry ratio (a useful gait parameter representing gait symmetry without significant relationship with age) from unconstrained straight walking using a single camera, without strict restrictions on walking directions or routes. according to projective geometry theory, we first develop a calculation formula of step length ratio for the case of unconstrained straight-line walking. Then, to adapt to general cases, we propose to modify noncollinear footprints, and accordingly provide general procedure for step length ratio extraction from unconstrained straight walking. Our method achieves a mean absolute percentage error (MAPE) of 1.9547% for 15 subjects' normal and abnormal side-view gaits, and also obtains satisfactory MAPEs for non-side-view gaits (2.4026% for 45°-view gaits and 3.9721% for 30°-view gaits). The performance is much better than a well-established monocular gait measurement system suitable only for side-view gaits with a MAPE of 3.5538%. Independently of walking directions, our method can accurately estimate step length ratios from unconstrained straight walking. This demonstrates our method is applicable for elders' daily gait monitoring to provide valuable information for elderly health care, such as abnormal gait recognition, fall risk assessment, etc. single-camera-based gait monitoring is unobtrusive, inexpensive, and easy-to-use to monitor daily gait of seniors in their homes. However, most studies require subjects to walk perpendicularly to camera's optical axis or along some specified routes, which limits its application in elderly home monitoring. To build unconstrained monitoring environments, we propose a method to measure step length symmetry ratio (a useful gait parameter representing gait symmetry without significant relationship with age) from unconstrained straight walking using a single camera, without strict restrictions on walking directions or routes. according to projective geometry theory, we first develop a calculation formula of step length ratio for the case of unconstrained straight-line walking. Then, to adapt to general cases, we propose to modify noncollinear footprints, and accordingly provide general procedure for step length ratio extraction from unconstrained straight walking. Our method achieves a mean absolute percentage error (MAPE) of 1.9547% for 15 subjects' normal and abnormal side-view gaits, and also obtains satisfactory MAPEs for non-side-view gaits (2.4026% for 45°-view gaits and 3.9721% for 30°-view gaits). The performance is much better than a well-established monocular gait measurement system suitable only for side-view gaits with a MAPE of 3.5538%. Independently of walking directions, our method can accurately estimate step length ratios from unconstrained straight walking. This demonstrates our method is applicable for elders' daily gait monitoring to provide valuable information for elderly health care, such as abnormal gait recognition, fall risk assessment, etc.

Exploring quantum computing application to satellite data assimilation

NASA Astrophysics Data System (ADS)

Cheung, S.; Zhang, S. Q.

2015-12-01

This is an exploring work on potential application of quantum computing to a scientific data optimization problem. On classical computational platforms, the physical domain of a satellite data assimilation problem is represented by a discrete variable transform, and classical minimization algorithms are employed to find optimal solution of the analysis cost function. The computation becomes intensive and time-consuming when the problem involves large number of variables and data. The new quantum computer opens a very different approach both in conceptual programming and in hardware architecture for solving optimization problem. In order to explore if we can utilize the quantum computing machine architecture, we formulate a satellite data assimilation experimental case in the form of quadratic programming optimization problem. We find a transformation of the problem to map it into Quadratic Unconstrained Binary Optimization (QUBO) framework. Binary Wavelet Transform (BWT) will be applied to the data assimilation variables for its invertible decomposition and all calculations in BWT are performed by Boolean operations. The transformed problem will be experimented as to solve for a solution of QUBO instances defined on Chimera graphs of the quantum computer.

UAV path planning using artificial potential field method updated by optimal control theory

NASA Astrophysics Data System (ADS)

Chen, Yong-bo; Luo, Guan-chen; Mei, Yue-song; Yu, Jian-qiao; Su, Xiao-long

2016-04-01

The unmanned aerial vehicle (UAV) path planning problem is an important assignment in the UAV mission planning. Based on the artificial potential field (APF) UAV path planning method, it is reconstructed into the constrained optimisation problem by introducing an additional control force. The constrained optimisation problem is translated into the unconstrained optimisation problem with the help of slack variables in this paper. The functional optimisation method is applied to reform this problem into an optimal control problem. The whole transformation process is deduced in detail, based on a discrete UAV dynamic model. Then, the path planning problem is solved with the help of the optimal control method. The path following process based on the six degrees of freedom simulation model of the quadrotor helicopters is introduced to verify the practicability of this method. Finally, the simulation results show that the improved method is more effective in planning path. In the planning space, the length of the calculated path is shorter and smoother than that using traditional APF method. In addition, the improved method can solve the dead point problem effectively.

Mind your step: metabolic energy cost while walking an enforced gait pattern.

PubMed

Wezenberg, D; de Haan, A; van Bennekom, C A M; Houdijk, H

2011-04-01

The energy cost of walking could be attributed to energy related to the walking movement and energy related to balance control. In order to differentiate between both components we investigated the energy cost of walking an enforced step pattern, thereby perturbing balance while the walking movement is preserved. Nine healthy subjects walked three times at comfortable walking speed on an instrumented treadmill. The first trial consisted of unconstrained walking. In the next two trials, subject walked while following a step pattern projected on the treadmill. The steps projected were either composed of the averaged step characteristics (periodic trial), or were an exact copy including the variability of the steps taken while walking unconstrained (variable trial). Metabolic energy cost was assessed and center of pressure profiles were analyzed to determine task performance, and to gain insight into the balance control strategies applied. Results showed that the metabolic energy cost was significantly higher in both the periodic and variable trial (8% and 13%, respectively) compared to unconstrained walking. The variation in center of pressure trajectories during single limb support was higher when a gait pattern was enforced, indicating a more active ankle strategy. The increased metabolic energy cost could originate from increased preparatory muscle activation to ensure proper foot placement and a more active ankle strategy to control for lateral balance. These results entail that metabolic energy cost of walking can be influenced significantly by control strategies that do not necessary alter global gait characteristics. Copyright © 2011 Elsevier B.V. All rights reserved.

3D-2D registration in mobile radiographs: algorithm development and preliminary clinical evaluation

NASA Astrophysics Data System (ADS)

Otake, Yoshito; Wang, Adam S.; Uneri, Ali; Kleinszig, Gerhard; Vogt, Sebastian; Aygun, Nafi; Lo, Sheng-fu L.; Wolinsky, Jean-Paul; Gokaslan, Ziya L.; Siewerdsen, Jeffrey H.

2015-03-01

An image-based 3D-2D registration method is presented using radiographs acquired in the uncalibrated, unconstrained geometry of mobile radiography. The approach extends a previous method for six degree-of-freedom (DOF) registration in C-arm fluoroscopy (namely ‘LevelCheck’) to solve the 9-DOF estimate of geometry in which the position of the source and detector are unconstrained. The method was implemented using a gradient correlation similarity metric and stochastic derivative-free optimization on a GPU. Development and evaluation were conducted in three steps. First, simulation studies were performed that involved a CT scan of an anthropomorphic body phantom and 1000 randomly generated digitally reconstructed radiographs in posterior-anterior and lateral views. A median projection distance error (PDE) of 0.007 mm was achieved with 9-DOF registration compared to 0.767 mm for 6-DOF. Second, cadaver studies were conducted using mobile radiographs acquired in three anatomical regions (thorax, abdomen and pelvis) and three levels of source-detector distance (~800, ~1000 and ~1200 mm). The 9-DOF method achieved a median PDE of 0.49 mm (compared to 2.53 mm for the 6-DOF method) and demonstrated robustness in the unconstrained imaging geometry. Finally, a retrospective clinical study was conducted with intraoperative radiographs of the spine exhibiting real anatomical deformation and image content mismatch (e.g. interventional devices in the radiograph that were not in the CT), demonstrating a PDE = 1.1 mm for the 9-DOF approach. Average computation time was 48.5 s, involving 687 701 function evaluations on average, compared to 18.2 s for the 6-DOF method. Despite the greater computational load, the 9-DOF method may offer a valuable tool for target localization (e.g. decision support in level counting) as well as safety and quality assurance checks at the conclusion of a procedure (e.g. overlay of planning data on the radiograph for verification of the surgical product) in a manner consistent with natural surgical workflow.

A new smoothing modified three-term conjugate gradient method for [Formula: see text]-norm minimization problem.

PubMed

Du, Shouqiang; Chen, Miao

2018-01-01

We consider a kind of nonsmooth optimization problems with [Formula: see text]-norm minimization, which has many applications in compressed sensing, signal reconstruction, and the related engineering problems. Using smoothing approximate techniques, this kind of nonsmooth optimization problem can be transformed into a general unconstrained optimization problem, which can be solved by the proposed smoothing modified three-term conjugate gradient method. The smoothing modified three-term conjugate gradient method is based on Polak-Ribière-Polyak conjugate gradient method. For the Polak-Ribière-Polyak conjugate gradient method has good numerical properties, the proposed method possesses the sufficient descent property without any line searches, and it is also proved to be globally convergent. Finally, the numerical experiments show the efficiency of the proposed method.

Structural optimization with approximate sensitivities

NASA Technical Reports Server (NTRS)

Patnaik, S. N.; Hopkins, D. A.; Coroneos, R.

1994-01-01

Computational efficiency in structural optimization can be enhanced if the intensive computations associated with the calculation of the sensitivities, that is, gradients of the behavior constraints, are reduced. Approximation to gradients of the behavior constraints that can be generated with small amount of numerical calculations is proposed. Structural optimization with these approximate sensitivities produced correct optimum solution. Approximate gradients performed well for different nonlinear programming methods, such as the sequence of unconstrained minimization technique, method of feasible directions, sequence of quadratic programming, and sequence of linear programming. Structural optimization with approximate gradients can reduce by one third the CPU time that would otherwise be required to solve the problem with explicit closed-form gradients. The proposed gradient approximation shows potential to reduce intensive computation that has been associated with traditional structural optimization.

Influence of sex on performance fatigability of the plantar flexors following repeated maximal dynamic shortening contractions.

PubMed

Lanning, Amelia C; Power, Geoffrey A; Christie, Anita D; Dalton, Brian H

2017-10-01

The purpose was to determine sex differences in fatigability during maximal, unconstrained velocity, shortening plantar flexions. The role of time-dependent measures (i.e., rate of torque development, rate of velocity development, and rate of neuromuscular activation) in such sex-related differences was also examined. By task termination, females exhibited smaller reductions in power and similar changes in rate of neuromuscular activation than males, indicating females were less fatigable than males.

[Retrieval of crown closure of moso bamboo forest using unmanned aerial vehicle (UAV) remotely sensed imagery based on geometric-optical model].

PubMed

Wang, Cong; Du, Hua-qiang; Zhou, Guo-mo; Xu, Xiao-jun; Sun, Shao-bo; Gao, Guo-long

2015-05-01

This research focused on the application of remotely sensed imagery from unmanned aerial vehicle (UAV) with high spatial resolution for the estimation of crown closure of moso bamboo forest based on the geometric-optical model, and analyzed the influence of unconstrained and fully constrained linear spectral mixture analysis (SMA) on the accuracy of the estimated results. The results demonstrated that the combination of UAV remotely sensed imagery and geometric-optical model could, to some degrees, achieve the estimation of crown closure. However, the different SMA methods led to significant differentiation in the estimation accuracy. Compared with unconstrained SMA, the fully constrained linear SMA method resulted in higher accuracy of the estimated values, with the coefficient of determination (R2) of 0.63 at 0.01 level, against the measured values acquired during the field survey. Root mean square error (RMSE) of approximate 0.04 was low, indicating that the usage of fully constrained linear SMA could bring about better results in crown closure estimation, which was closer to the actual condition in moso bamboo forest.

Parallel-vector computation for linear structural analysis and non-linear unconstrained optimization problems

NASA Technical Reports Server (NTRS)

Nguyen, D. T.; Al-Nasra, M.; Zhang, Y.; Baddourah, M. A.; Agarwal, T. K.; Storaasli, O. O.; Carmona, E. A.

1991-01-01

Several parallel-vector computational improvements to the unconstrained optimization procedure are described which speed up the structural analysis-synthesis process. A fast parallel-vector Choleski-based equation solver, pvsolve, is incorporated into the well-known SAP-4 general-purpose finite-element code. The new code, denoted PV-SAP, is tested for static structural analysis. Initial results on a four processor CRAY 2 show that using pvsolve reduces the equation solution time by a factor of 14-16 over the original SAP-4 code. In addition, parallel-vector procedures for the Golden Block Search technique and the BFGS method are developed and tested for nonlinear unconstrained optimization. A parallel version of an iterative solver and the pvsolve direct solver are incorporated into the BFGS method. Preliminary results on nonlinear unconstrained optimization test problems, using pvsolve in the analysis, show excellent parallel-vector performance indicating that these parallel-vector algorithms can be used in a new generation of finite-element based structural design/analysis-synthesis codes.

Development and comparison of advanced reduced-basis methods for the transient structural analysis of unconstrained structures

NASA Technical Reports Server (NTRS)

Mcgowan, David M.; Bostic, Susan W.; Camarda, Charles J.

1993-01-01

The development of two advanced reduced-basis methods, the force derivative method and the Lanczos method, and two widely used modal methods, the mode displacement method and the mode acceleration method, for transient structural analysis of unconstrained structures is presented. Two example structural problems are studied: an undamped, unconstrained beam subject to a uniformly distributed load which varies as a sinusoidal function of time and an undamped high-speed civil transport aircraft subject to a normal wing tip load which varies as a sinusoidal function of time. These example problems are used to verify the methods and to compare the relative effectiveness of each of the four reduced-basis methods for performing transient structural analyses on unconstrained structures. The methods are verified with a solution obtained by integrating directly the full system of equations of motion, and they are compared using the number of basis vectors required to obtain a desired level of accuracy and the associated computational times as comparison criteria.

Learning Incoherent Sparse and Low-Rank Patterns from Multiple Tasks

PubMed Central

Chen, Jianhui; Liu, Ji; Ye, Jieping

2013-01-01

We consider the problem of learning incoherent sparse and low-rank patterns from multiple tasks. Our approach is based on a linear multi-task learning formulation, in which the sparse and low-rank patterns are induced by a cardinality regularization term and a low-rank constraint, respectively. This formulation is non-convex; we convert it into its convex surrogate, which can be routinely solved via semidefinite programming for small-size problems. We propose to employ the general projected gradient scheme to efficiently solve such a convex surrogate; however, in the optimization formulation, the objective function is non-differentiable and the feasible domain is non-trivial. We present the procedures for computing the projected gradient and ensuring the global convergence of the projected gradient scheme. The computation of projected gradient involves a constrained optimization problem; we show that the optimal solution to such a problem can be obtained via solving an unconstrained optimization subproblem and an Euclidean projection subproblem. We also present two projected gradient algorithms and analyze their rates of convergence in details. In addition, we illustrate the use of the presented projected gradient algorithms for the proposed multi-task learning formulation using the least squares loss. Experimental results on a collection of real-world data sets demonstrate the effectiveness of the proposed multi-task learning formulation and the efficiency of the proposed projected gradient algorithms. PMID:24077658

Learning Incoherent Sparse and Low-Rank Patterns from Multiple Tasks.

PubMed

Chen, Jianhui; Liu, Ji; Ye, Jieping

2012-02-01

We consider the problem of learning incoherent sparse and low-rank patterns from multiple tasks. Our approach is based on a linear multi-task learning formulation, in which the sparse and low-rank patterns are induced by a cardinality regularization term and a low-rank constraint, respectively. This formulation is non-convex; we convert it into its convex surrogate, which can be routinely solved via semidefinite programming for small-size problems. We propose to employ the general projected gradient scheme to efficiently solve such a convex surrogate; however, in the optimization formulation, the objective function is non-differentiable and the feasible domain is non-trivial. We present the procedures for computing the projected gradient and ensuring the global convergence of the projected gradient scheme. The computation of projected gradient involves a constrained optimization problem; we show that the optimal solution to such a problem can be obtained via solving an unconstrained optimization subproblem and an Euclidean projection subproblem. We also present two projected gradient algorithms and analyze their rates of convergence in details. In addition, we illustrate the use of the presented projected gradient algorithms for the proposed multi-task learning formulation using the least squares loss. Experimental results on a collection of real-world data sets demonstrate the effectiveness of the proposed multi-task learning formulation and the efficiency of the proposed projected gradient algorithms.

Constraint Embedding Technique for Multibody System Dynamics

NASA Technical Reports Server (NTRS)

Woo, Simon S.; Cheng, Michael K.

2011-01-01

Multibody dynamics play a critical role in simulation testbeds for space missions. There has been a considerable interest in the development of efficient computational algorithms for solving the dynamics of multibody systems. Mass matrix factorization and inversion techniques and the O(N) class of forward dynamics algorithms developed using a spatial operator algebra stand out as important breakthrough on this front. Techniques such as these provide the efficient algorithms and methods for the application and implementation of such multibody dynamics models. However, these methods are limited only to tree-topology multibody systems. Closed-chain topology systems require different techniques that are not as efficient or as broad as those for tree-topology systems. The closed-chain forward dynamics approach consists of treating the closed-chain topology as a tree-topology system subject to additional closure constraints. The resulting forward dynamics solution consists of: (a) ignoring the closure constraints and using the O(N) algorithm to solve for the free unconstrained accelerations for the system; (b) using the tree-topology solution to compute a correction force to enforce the closure constraints; and (c) correcting the unconstrained accelerations with correction accelerations resulting from the correction forces. This constraint-embedding technique shows how to use direct embedding to eliminate local closure-loops in the system and effectively convert the system back to a tree-topology system. At this point, standard tree-topology techniques can be brought to bear on the problem. The approach uses a spatial operator algebra approach to formulating the equations of motion. The operators are block-partitioned around the local body subgroups to convert them into aggregate bodies. Mass matrix operator factorization and inversion techniques are applied to the reformulated tree-topology system. Thus in essence, the new technique allows conversion of a system with closure-constraints into an equivalent tree-topology system, and thus allows one to take advantage of the host of techniques available to the latter class of systems. This technology is highly suitable for the class of multibody systems where the closure-constraints are local, i.e., where they are confined to small groupings of bodies within the system. Important examples of such local closure-constraints are constraints associated with four-bar linkages, geared motors, differential suspensions, etc. One can eliminate these closure-constraints and convert the system into a tree-topology system by embedding the constraints directly into the system dynamics and effectively replacing the body groupings with virtual aggregate bodies. Once eliminated, one can apply the well-known results and algorithms for tree-topology systems to solve the dynamics of such closed-chain system.

Adaptive nearly optimal control for a class of continuous-time nonaffine nonlinear systems with inequality constraints.

PubMed

Fan, Quan-Yong; Yang, Guang-Hong

2017-01-01

The state inequality constraints have been hardly considered in the literature on solving the nonlinear optimal control problem based the adaptive dynamic programming (ADP) method. In this paper, an actor-critic (AC) algorithm is developed to solve the optimal control problem with a discounted cost function for a class of state-constrained nonaffine nonlinear systems. To overcome the difficulties resulting from the inequality constraints and the nonaffine nonlinearities of the controlled systems, a novel transformation technique with redesigned slack functions and a pre-compensator method are introduced to convert the constrained optimal control problem into an unconstrained one for affine nonlinear systems. Then, based on the policy iteration (PI) algorithm, an online AC scheme is proposed to learn the nearly optimal control policy for the obtained affine nonlinear dynamics. Using the information of the nonlinear model, novel adaptive update laws are designed to guarantee the convergence of the neural network (NN) weights and the stability of the affine nonlinear dynamics without the requirement for the probing signal. Finally, the effectiveness of the proposed method is validated by simulation studies. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

The Evolution of the Intergalactic Medium

NASA Astrophysics Data System (ADS)

McQuinn, Matthew

2016-09-01

The bulk of cosmic matter resides in a dilute reservoir that fills the space between galaxies, the intergalactic medium (IGM). The history of this reservoir is intimately tied to the cosmic histories of structure formation, star formation, and supermassive black hole accretion. Our models for the IGM at intermediate redshifts (2≲z≲5) are a tremendous success, quantitatively explaining the statistics of Lyα absorption of intergalactic hydrogen. However, at both lower and higher redshifts (and around galaxies) much is still unknown about the IGM. We review the theoretical models and measurements that form the basis for the modern understanding of the IGM, and we discuss unsolved puzzles (ranging from the largely unconstrained process of reionization at high z to the missing baryon problem at low z), highlighting the efforts that have the potential to solve them.

Bayesian Optimization Under Mixed Constraints with A Slack-Variable Augmented Lagrangian

DOE Office of Scientific and Technical Information (OSTI.GOV)

Picheny, Victor; Gramacy, Robert B.; Wild, Stefan M.

An augmented Lagrangian (AL) can convert a constrained optimization problem into a sequence of simpler (e.g., unconstrained) problems, which are then usually solved with local solvers. Recently, surrogate-based Bayesian optimization (BO) sub-solvers have been successfully deployed in the AL framework for a more global search in the presence of inequality constraints; however, a drawback was that expected improvement (EI) evaluations relied on Monte Carlo. Here we introduce an alternative slack variable AL, and show that in this formulation the EI may be evaluated with library routines. The slack variables furthermore facilitate equality as well as inequality constraints, and mixtures thereof.more » We show our new slack “ALBO” compares favorably to the original. Its superiority over conventional alternatives is reinforced on several mixed constraint examples.« less

Global Convergence of the EM Algorithm for Unconstrained Latent Variable Models with Categorical Indicators

ERIC Educational Resources Information Center

Weissman, Alexander

2013-01-01

Convergence of the expectation-maximization (EM) algorithm to a global optimum of the marginal log likelihood function for unconstrained latent variable models with categorical indicators is presented. The sufficient conditions under which global convergence of the EM algorithm is attainable are provided in an information-theoretic context by…

Constrained and Unconstrained Partial Adjacent Category Logit Models for Ordinal Response Variables

ERIC Educational Resources Information Center

Fullerton, Andrew S.; Xu, Jun

2018-01-01

Adjacent category logit models are ordered regression models that focus on comparisons of adjacent categories. These models are particularly useful for ordinal response variables with categories that are of substantive interest. In this article, we consider unconstrained and constrained versions of the partial adjacent category logit model, which…

Butane dihedral angle dynamics in water is dominated by internal friction

PubMed Central

Daldrop, Jan O.; Kappler, Julian; Brünig, Florian N.; Netz, Roland R.

2018-01-01

The dihedral dynamics of butane in water is known to be rather insensitive to the water viscosity; possible explanations for this involve inertial effects or Kramers’ turnover, the finite memory time of friction, and the presence of so-called internal friction. To disentangle these factors, we introduce a method to directly extract the friction memory function from unconstrained simulations in the presence of an arbitrary free-energy landscape. By analysis of the dihedral friction in butane for varying water viscosity, we demonstrate the existence of an internal friction contribution that does not scale linearly with water viscosity. At normal water viscosity, the internal friction turns out to be eight times larger than the solvent friction and thus completely dominates the effective friction. By comparison with simulations of a constrained butane molecule that has the dihedral as the only degree of freedom, we show that internal friction comes from the six additional degrees of freedom in unconstrained butane that are orthogonal to the dihedral angle reaction coordinate. While the insensitivity of butane’s dihedral dynamics to water viscosity is solely due to the presence of internal friction, inertial effects nevertheless crucially influence the resultant transition rates. In contrast, non-Markovian effects due to the finite memory time are present but do not significantly influence the dihedral barrier-crossing rate of butane. These results not only settle the character of dihedral dynamics in small solvated molecular systems such as butane, they also have important implications for the folding of polymers and proteins. PMID:29712838

Weighted SGD for ℓ p Regression with Randomized Preconditioning.

PubMed

Yang, Jiyan; Chow, Yin-Lam; Ré, Christopher; Mahoney, Michael W

2016-01-01

In recent years, stochastic gradient descent (SGD) methods and randomized linear algebra (RLA) algorithms have been applied to many large-scale problems in machine learning and data analysis. SGD methods are easy to implement and applicable to a wide range of convex optimization problems. In contrast, RLA algorithms provide much stronger performance guarantees but are applicable to a narrower class of problems. We aim to bridge the gap between these two methods in solving constrained overdetermined linear regression problems-e.g., ℓ 2 and ℓ 1 regression problems. We propose a hybrid algorithm named pwSGD that uses RLA techniques for preconditioning and constructing an importance sampling distribution, and then performs an SGD-like iterative process with weighted sampling on the preconditioned system.By rewriting a deterministic ℓ p regression problem as a stochastic optimization problem, we connect pwSGD to several existing ℓ p solvers including RLA methods with algorithmic leveraging (RLA for short).We prove that pwSGD inherits faster convergence rates that only depend on the lower dimension of the linear system, while maintaining low computation complexity. Such SGD convergence rates are superior to other related SGD algorithm such as the weighted randomized Kaczmarz algorithm.Particularly, when solving ℓ 1 regression with size n by d , pwSGD returns an approximate solution with ε relative error in the objective value in (log n ·nnz( A )+poly( d )/ ε 2 ) time. This complexity is uniformly better than that of RLA methods in terms of both ε and d when the problem is unconstrained. In the presence of constraints, pwSGD only has to solve a sequence of much simpler and smaller optimization problem over the same constraints. In general this is more efficient than solving the constrained subproblem required in RLA.For ℓ 2 regression, pwSGD returns an approximate solution with ε relative error in the objective value and the solution vector measured in prediction norm in (log n ·nnz( A )+poly( d ) log(1/ ε )/ ε ) time. We show that for unconstrained ℓ 2 regression, this complexity is comparable to that of RLA and is asymptotically better over several state-of-the-art solvers in the regime where the desired accuracy ε , high dimension n and low dimension d satisfy d ≥ 1/ ε and n ≥ d 2 / ε . We also provide lower bounds on the coreset complexity for more general regression problems, indicating that still new ideas will be needed to extend similar RLA preconditioning ideas to weighted SGD algorithms for more general regression problems. Finally, the effectiveness of such algorithms is illustrated numerically on both synthetic and real datasets, and the results are consistent with our theoretical findings and demonstrate that pwSGD converges to a medium-precision solution, e.g., ε = 10 -3 , more quickly.

Weighted SGD for ℓp Regression with Randomized Preconditioning*

PubMed Central

Yang, Jiyan; Chow, Yin-Lam; Ré, Christopher; Mahoney, Michael W.

2018-01-01

In recent years, stochastic gradient descent (SGD) methods and randomized linear algebra (RLA) algorithms have been applied to many large-scale problems in machine learning and data analysis. SGD methods are easy to implement and applicable to a wide range of convex optimization problems. In contrast, RLA algorithms provide much stronger performance guarantees but are applicable to a narrower class of problems. We aim to bridge the gap between these two methods in solving constrained overdetermined linear regression problems—e.g., ℓ2 and ℓ1 regression problems. We propose a hybrid algorithm named pwSGD that uses RLA techniques for preconditioning and constructing an importance sampling distribution, and then performs an SGD-like iterative process with weighted sampling on the preconditioned system.By rewriting a deterministic ℓp regression problem as a stochastic optimization problem, we connect pwSGD to several existing ℓp solvers including RLA methods with algorithmic leveraging (RLA for short).We prove that pwSGD inherits faster convergence rates that only depend on the lower dimension of the linear system, while maintaining low computation complexity. Such SGD convergence rates are superior to other related SGD algorithm such as the weighted randomized Kaczmarz algorithm.Particularly, when solving ℓ1 regression with size n by d, pwSGD returns an approximate solution with ε relative error in the objective value in 𝒪(log n·nnz(A)+poly(d)/ε2) time. This complexity is uniformly better than that of RLA methods in terms of both ε and d when the problem is unconstrained. In the presence of constraints, pwSGD only has to solve a sequence of much simpler and smaller optimization problem over the same constraints. In general this is more efficient than solving the constrained subproblem required in RLA.For ℓ2 regression, pwSGD returns an approximate solution with ε relative error in the objective value and the solution vector measured in prediction norm in 𝒪(log n·nnz(A)+poly(d) log(1/ε)/ε) time. We show that for unconstrained ℓ2 regression, this complexity is comparable to that of RLA and is asymptotically better over several state-of-the-art solvers in the regime where the desired accuracy ε, high dimension n and low dimension d satisfy d ≥ 1/ε and n ≥ d2/ε. We also provide lower bounds on the coreset complexity for more general regression problems, indicating that still new ideas will be needed to extend similar RLA preconditioning ideas to weighted SGD algorithms for more general regression problems. Finally, the effectiveness of such algorithms is illustrated numerically on both synthetic and real datasets, and the results are consistent with our theoretical findings and demonstrate that pwSGD converges to a medium-precision solution, e.g., ε = 10−3, more quickly. PMID:29782626

Vector Graph Assisted Pedestrian Dead Reckoning Using an Unconstrained Smartphone

PubMed Central

Qian, Jiuchao; Pei, Ling; Ma, Jiabin; Ying, Rendong; Liu, Peilin

2015-01-01

The paper presents a hybrid indoor positioning solution based on a pedestrian dead reckoning (PDR) approach using built-in sensors on a smartphone. To address the challenges of flexible and complex contexts of carrying a phone while walking, a robust step detection algorithm based on motion-awareness has been proposed. Given the fact that step length is influenced by different motion states, an adaptive step length estimation algorithm based on motion recognition is developed. Heading estimation is carried out by an attitude acquisition algorithm, which contains a two-phase filter to mitigate the distortion of magnetic anomalies. In order to estimate the heading for an unconstrained smartphone, principal component analysis (PCA) of acceleration is applied to determine the offset between the orientation of smartphone and the actual heading of a pedestrian. Moreover, a particle filter with vector graph assisted particle weighting is introduced to correct the deviation in step length and heading estimation. Extensive field tests, including four contexts of carrying a phone, have been conducted in an office building to verify the performance of the proposed algorithm. Test results show that the proposed algorithm can achieve sub-meter mean error in all contexts. PMID:25738763

SEMIPARAMETRIC ZERO-INFLATED MODELING IN MULTI-ETHNIC STUDY OF ATHEROSCLEROSIS (MESA)

PubMed Central

Liu, Hai; Ma, Shuangge; Kronmal, Richard; Chan, Kung-Sik

2013-01-01

We analyze the Agatston score of coronary artery calcium (CAC) from the Multi-Ethnic Study of Atherosclerosis (MESA) using semi-parametric zero-inflated modeling approach, where the observed CAC scores from this cohort consist of high frequency of zeroes and continuously distributed positive values. Both partially constrained and unconstrained models are considered to investigate the underlying biological processes of CAC development from zero to positive, and from small amount to large amount. Different from existing studies, a model selection procedure based on likelihood cross-validation is adopted to identify the optimal model, which is justified by comparative Monte Carlo studies. A shrinkaged version of cubic regression spline is used for model estimation and variable selection simultaneously. When applying the proposed methods to the MESA data analysis, we show that the two biological mechanisms influencing the initiation of CAC and the magnitude of CAC when it is positive are better characterized by an unconstrained zero-inflated normal model. Our results are significantly different from those in published studies, and may provide further insights into the biological mechanisms underlying CAC development in human. This highly flexible statistical framework can be applied to zero-inflated data analyses in other areas. PMID:23805172

Neck muscle fatigue differentially alters scapular and humeral kinematics during humeral elevation in subclinical neck pain participants versus healthy controls.

PubMed

Zabihhosseinian, Mahboobeh; Holmes, Michael W R; Howarth, Samuel; Ferguson, Brad; Murphy, Bernadette

2017-04-01

Scapular orientation is highly dependent on axioscapular muscle function. This study examined the impact of neck muscle fatigue on scapular and humeral kinematics in participants with and without subclinical neck pain (SCNP) during humeral elevation. Ten SCNP and 10 control participants performed three unconstrained trials of dominant arm humeral elevation in the scapular plane to approximately 120 degrees before and after neck extensor muscle fatigue. Three-dimensional scapular and humeral kinematics were measured during the humeral elevation trials. Humeral elevation plane angle showed a significant interaction between groups (SCNP vs controls) and trial (pre- vs post-fatigue) (p=0.001). Controls began the unconstrained humeral elevation task after fatigue in a more abducted position, (p=0.002). Significant baseline differences in scapular rotation existed between the two groups (Posterior/Anterior tilt, p=0.04; Internal/External Rotation, p=0.001). SCNP contributed to altered scapular kinematics. Neck muscle fatigue influenced humeral kinematics in controls but not the SCNP group; suggesting that altered scapular motor control in the SCNP group resulted in an impaired adaption further to the neck muscle fatigue. Copyright © 2017 Elsevier Ltd. All rights reserved.

Unconstrained Structural Equation Models of Latent Interactions: Contrasting Residual- and Mean-Centered Approaches

ERIC Educational Resources Information Center

Marsh, Herbert W.; Wen, Zhonglin; Hau, Kit-Tai; Little, Todd D.; Bovaird, James A.; Widaman, Keith F.

2007-01-01

Little, Bovaird and Widaman (2006) proposed an unconstrained approach with residual centering for estimating latent interaction effects as an alternative to the mean-centered approach proposed by Marsh, Wen, and Hau (2004, 2006). Little et al. also differed from Marsh et al. in the number of indicators used to infer the latent interaction factor…

Still-to-video face recognition in unconstrained environments

NASA Astrophysics Data System (ADS)

Wang, Haoyu; Liu, Changsong; Ding, Xiaoqing

2015-02-01

Face images from video sequences captured in unconstrained environments usually contain several kinds of variations, e.g. pose, facial expression, illumination, image resolution and occlusion. Motion blur and compression artifacts also deteriorate recognition performance. Besides, in various practical systems such as law enforcement, video surveillance and e-passport identification, only a single still image per person is enrolled as the gallery set. Many existing methods may fail to work due to variations in face appearances and the limit of available gallery samples. In this paper, we propose a novel approach for still-to-video face recognition in unconstrained environments. By assuming that faces from still images and video frames share the same identity space, a regularized least squares regression method is utilized to tackle the multi-modality problem. Regularization terms based on heuristic assumptions are enrolled to avoid overfitting. In order to deal with the single image per person problem, we exploit face variations learned from training sets to synthesize virtual samples for gallery samples. We adopt a learning algorithm combining both affine/convex hull-based approach and regularizations to match image sets. Experimental results on a real-world dataset consisting of unconstrained video sequences demonstrate that our method outperforms the state-of-the-art methods impressively.

Locating Critical Circular and Unconstrained Failure Surface in Slope Stability Analysis with Tailored Genetic Algorithm

NASA Astrophysics Data System (ADS)

Pasik, Tomasz; van der Meij, Raymond

2017-12-01

This article presents an efficient search method for representative circular and unconstrained slip surfaces with the use of the tailored genetic algorithm. Searches for unconstrained slip planes with rigid equilibrium methods are yet uncommon in engineering practice, and little publications regarding truly free slip planes exist. The proposed method presents an effective procedure being the result of the right combination of initial population type, selection, crossover and mutation method. The procedure needs little computational effort to find the optimum, unconstrained slip plane. The methodology described in this paper is implemented using Mathematica. The implementation, along with further explanations, is fully presented so the results can be reproduced. Sample slope stability calculations are performed for four cases, along with a detailed result interpretation. Two cases are compared with analyses described in earlier publications. The remaining two are practical cases of slope stability analyses of dikes in Netherlands. These four cases show the benefits of analyzing slope stability with a rigid equilibrium method combined with a genetic algorithm. The paper concludes by describing possibilities and limitations of using the genetic algorithm in the context of the slope stability problem.

Image Registration and Data Assimilation as a QUBO on the D-Wave Quantum Annealer

NASA Astrophysics Data System (ADS)

Pelissier, C.; LeMoigne, J.; Halem, M.; Simpson, D. G.; Clune, T.

2016-12-01

The advent of the commercially available D-Wave quantum annealer has for the first time allowed investigations of the potential of quantum effects to efficiently carry out certain numerical tasks. The D-Wave computer was initially promoted as a tool to solve Quadratic Unconstrained Binary Optimization problems (QUBOs), but currently, it is also being used to generate the Boltzmann statistics required to train Restricted Boltzmann machines (RBMs). We consider the potential of this new architecture in performing numerical computations required to estimate terrestrial carbon fluxes from OCO-2 observations using the LIS model. The use of RBMs is being investigated in this work, but here we focus on the D-Wave as a QUBO solver, and it's potential to carry out image registration and data assimilation. QUBOs are formulated for both problems and results generated using the D-Wave 2Xtm at the NAS supercomputing facility are presented.

QSPIN: A High Level Java API for Quantum Computing Experimentation

NASA Technical Reports Server (NTRS)

Barth, Tim

2017-01-01

QSPIN is a high level Java language API for experimentation in QC models used in the calculation of Ising spin glass ground states and related quadratic unconstrained binary optimization (QUBO) problems. The Java API is intended to facilitate research in advanced QC algorithms such as hybrid quantum-classical solvers, automatic selection of constraint and optimization parameters, and techniques for the correction and mitigation of model and solution errors. QSPIN includes high level solver objects tailored to the D-Wave quantum annealing architecture that implement hybrid quantum-classical algorithms [Booth et al.] for solving large problems on small quantum devices, elimination of variables via roof duality, and classical computing optimization methods such as GPU accelerated simulated annealing and tabu search for comparison. A test suite of documented NP-complete applications ranging from graph coloring, covering, and partitioning to integer programming and scheduling are provided to demonstrate current capabilities.

Gender recognition from unconstrained and articulated human body.

PubMed

Wu, Qin; Guo, Guodong

2014-01-01

Gender recognition has many useful applications, ranging from business intelligence to image search and social activity analysis. Traditional research on gender recognition focuses on face images in a constrained environment. This paper proposes a method for gender recognition in articulated human body images acquired from an unconstrained environment in the real world. A systematic study of some critical issues in body-based gender recognition, such as which body parts are informative, how many body parts are needed to combine together, and what representations are good for articulated body-based gender recognition, is also presented. This paper also pursues data fusion schemes and efficient feature dimensionality reduction based on the partial least squares estimation. Extensive experiments are performed on two unconstrained databases which have not been explored before for gender recognition.

Gender Recognition from Unconstrained and Articulated Human Body

PubMed Central

Wu, Qin; Guo, Guodong

2014-01-01

Gender recognition has many useful applications, ranging from business intelligence to image search and social activity analysis. Traditional research on gender recognition focuses on face images in a constrained environment. This paper proposes a method for gender recognition in articulated human body images acquired from an unconstrained environment in the real world. A systematic study of some critical issues in body-based gender recognition, such as which body parts are informative, how many body parts are needed to combine together, and what representations are good for articulated body-based gender recognition, is also presented. This paper also pursues data fusion schemes and efficient feature dimensionality reduction based on the partial least squares estimation. Extensive experiments are performed on two unconstrained databases which have not been explored before for gender recognition. PMID:24977203

Gaussian Accelerated Molecular Dynamics in NAMD.

PubMed

Pang, Yui Tik; Miao, Yinglong; Wang, Yi; McCammon, J Andrew

2017-01-10

Gaussian accelerated molecular dynamics (GaMD) is a recently developed enhanced sampling technique that provides efficient free energy calculations of biomolecules. Like the previous accelerated molecular dynamics (aMD), GaMD allows for "unconstrained" enhanced sampling without the need to set predefined collective variables and so is useful for studying complex biomolecular conformational changes such as protein folding and ligand binding. Furthermore, because the boost potential is constructed using a harmonic function that follows Gaussian distribution in GaMD, cumulant expansion to the second order can be applied to recover the original free energy profiles of proteins and other large biomolecules, which solves a long-standing energetic reweighting problem of the previous aMD method. Taken together, GaMD offers major advantages for both unconstrained enhanced sampling and free energy calculations of large biomolecules. Here, we have implemented GaMD in the NAMD package on top of the existing aMD feature and validated it on three model systems: alanine dipeptide, the chignolin fast-folding protein, and the M 3 muscarinic G protein-coupled receptor (GPCR). For alanine dipeptide, while conventional molecular dynamics (cMD) simulations performed for 30 ns are poorly converged, GaMD simulations of the same length yield free energy profiles that agree quantitatively with those of 1000 ns cMD simulation. Further GaMD simulations have captured folding of the chignolin and binding of the acetylcholine (ACh) endogenous agonist to the M 3 muscarinic receptor. The reweighted free energy profiles are used to characterize the protein folding and ligand binding pathways quantitatively. GaMD implemented in the scalable NAMD is widely applicable to enhanced sampling and free energy calculations of large biomolecules.

Butane dihedral angle dynamics in water is dominated by internal friction.

PubMed

Daldrop, Jan O; Kappler, Julian; Brünig, Florian N; Netz, Roland R

2018-05-15

The dihedral dynamics of butane in water is known to be rather insensitive to the water viscosity; possible explanations for this involve inertial effects or Kramers' turnover, the finite memory time of friction, and the presence of so-called internal friction. To disentangle these factors, we introduce a method to directly extract the friction memory function from unconstrained simulations in the presence of an arbitrary free-energy landscape. By analysis of the dihedral friction in butane for varying water viscosity, we demonstrate the existence of an internal friction contribution that does not scale linearly with water viscosity. At normal water viscosity, the internal friction turns out to be eight times larger than the solvent friction and thus completely dominates the effective friction. By comparison with simulations of a constrained butane molecule that has the dihedral as the only degree of freedom, we show that internal friction comes from the six additional degrees of freedom in unconstrained butane that are orthogonal to the dihedral angle reaction coordinate. While the insensitivity of butane's dihedral dynamics to water viscosity is solely due to the presence of internal friction, inertial effects nevertheless crucially influence the resultant transition rates. In contrast, non-Markovian effects due to the finite memory time are present but do not significantly influence the dihedral barrier-crossing rate of butane. These results not only settle the character of dihedral dynamics in small solvated molecular systems such as butane, they also have important implications for the folding of polymers and proteins. Copyright © 2018 the Author(s). Published by PNAS.

Monolithic, multi-bandgap, tandem, ultra-thin, strain-counterbalanced, photovoltaic energy converters with optimal subcell bandgaps

DOEpatents

Wanlass, Mark W [Golden, CO; Mascarenhas, Angelo [Lakewood, CO

2012-05-08

Modeling a monolithic, multi-bandgap, tandem, solar photovoltaic converter or thermophotovoltaic converter by constraining the bandgap value for the bottom subcell to no less than a particular value produces an optimum combination of subcell bandgaps that provide theoretical energy conversion efficiencies nearly as good as unconstrained maximum theoretical conversion efficiency models, but which are more conducive to actual fabrication to achieve such conversion efficiencies than unconstrained model optimum bandgap combinations. Achieving such constrained or unconstrained optimum bandgap combinations includes growth of a graded layer transition from larger lattice constant on the parent substrate to a smaller lattice constant to accommodate higher bandgap upper subcells and at least one graded layer that transitions back to a larger lattice constant to accommodate lower bandgap lower subcells and to counter-strain the epistructure to mitigate epistructure bowing.

Quantum-enhanced reinforcement learning for finite-episode games with discrete state spaces

NASA Astrophysics Data System (ADS)

Neukart, Florian; Von Dollen, David; Seidel, Christian; Compostella, Gabriele

2017-12-01

Quantum annealing algorithms belong to the class of metaheuristic tools, applicable for solving binary optimization problems. Hardware implementations of quantum annealing, such as the quantum annealing machines produced by D-Wave Systems, have been subject to multiple analyses in research, with the aim of characterizing the technology's usefulness for optimization and sampling tasks. Here, we present a way to partially embed both Monte Carlo policy iteration for finding an optimal policy on random observations, as well as how to embed n sub-optimal state-value functions for approximating an improved state-value function given a policy for finite horizon games with discrete state spaces on a D-Wave 2000Q quantum processing unit (QPU). We explain how both problems can be expressed as a quadratic unconstrained binary optimization (QUBO) problem, and show that quantum-enhanced Monte Carlo policy evaluation allows for finding equivalent or better state-value functions for a given policy with the same number episodes compared to a purely classical Monte Carlo algorithm. Additionally, we describe a quantum-classical policy learning algorithm. Our first and foremost aim is to explain how to represent and solve parts of these problems with the help of the QPU, and not to prove supremacy over every existing classical policy evaluation algorithm.

Genetically engineered peptides for inorganics: study of an unconstrained bacterial display technology and bulk aluminum alloy.

PubMed

Adams, Bryn L; Finch, Amethist S; Hurley, Margaret M; Sarkes, Deborah A; Stratis-Cullum, Dimitra N

2013-09-06

The first-ever peptide biomaterial discovery using an unconstrained engineered bacterial display technology is reported. Using this approach, we have developed genetically engineered peptide binders for a bulk aluminum alloy and use molecular dynamics simulation of peptide conformational fluctuations to demonstrate sequence-dependent, structure-function relationships for metal and metal oxide interactions. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

An indirect method for numerical optimization using the Kreisselmeir-Steinhauser function

NASA Technical Reports Server (NTRS)

Wrenn, Gregory A.

1989-01-01

A technique is described for converting a constrained optimization problem into an unconstrained problem. The technique transforms one of more objective functions into reduced objective functions, which are analogous to goal constraints used in the goal programming method. These reduced objective functions are appended to the set of constraints and an envelope of the entire function set is computed using the Kreisselmeir-Steinhauser function. This envelope function is then searched for an unconstrained minimum. The technique may be categorized as a SUMT algorithm. Advantages of this approach are the use of unconstrained optimization methods to find a constrained minimum without the draw down factor typical of penalty function methods, and that the technique may be started from the feasible or infeasible design space. In multiobjective applications, the approach has the advantage of locating a compromise minimum design without the need to optimize for each individual objective function separately.

Small convolution kernels for high-fidelity image restoration

NASA Technical Reports Server (NTRS)

Reichenbach, Stephen E.; Park, Stephen K.

1991-01-01

An algorithm is developed for computing the mean-square-optimal values for small, image-restoration kernels. The algorithm is based on a comprehensive, end-to-end imaging system model that accounts for the important components of the imaging process: the statistics of the scene, the point-spread function of the image-gathering device, sampling effects, noise, and display reconstruction. Subject to constraints on the spatial support of the kernel, the algorithm generates the kernel values that restore the image with maximum fidelity, that is, the kernel minimizes the expected mean-square restoration error. The algorithm is consistent with the derivation of the spatially unconstrained Wiener filter, but leads to a small, spatially constrained kernel that, unlike the unconstrained filter, can be efficiently implemented by convolution. Simulation experiments demonstrate that for a wide range of imaging systems these small kernels can restore images with fidelity comparable to images restored with the unconstrained Wiener filter.

Content-based unconstrained color logo and trademark retrieval with color edge gradient co-occurrence histograms

NASA Astrophysics Data System (ADS)

Phan, Raymond; Androutsos, Dimitrios

2008-01-01

In this paper, we present a logo and trademark retrieval system for unconstrained color image databases that extends the Color Edge Co-occurrence Histogram (CECH) object detection scheme. We introduce more accurate information to the CECH, by virtue of incorporating color edge detection using vector order statistics. This produces a more accurate representation of edges in color images, in comparison to the simple color pixel difference classification of edges as seen in the CECH. Our proposed method is thus reliant on edge gradient information, and as such, we call this the Color Edge Gradient Co-occurrence Histogram (CEGCH). We use this as the main mechanism for our unconstrained color logo and trademark retrieval scheme. Results illustrate that the proposed retrieval system retrieves logos and trademarks with good accuracy, and outperforms the CECH object detection scheme with higher precision and recall.

Burst Testing of Triaxial Braided Composite Tubes

NASA Technical Reports Server (NTRS)

Salem, J. A.; Bail, J. L.; Wilmoth, N. G.; Ghosn, L. J.; Kohlman, L. W.; Roberts, G. D.; Martin, R. E.

2014-01-01

Applications using triaxial braided composites are limited by the materials transverse strength which is determined by the delamination capacity of unconstrained, free-edge tows. However, structural applications such as cylindrical tubes can be designed to minimize free edge effects and thus the strength with and without edge stresses is relevant to the design process. The transverse strength of triaxial braided composites without edge effects was determined by internally pressurizing tubes. In the absence of edge effects, the axial and transverse strength were comparable. In addition, notched specimens, which minimize the effect of unconstrained tow ends, were tested in a variety of geometries. Although the commonly tested notch geometries exhibited similar axial and transverse net section failure strength, significant dependence on notch configuration was observed. In the absence of unconstrained tows, failure ensues as a result of bias tow rotation, splitting, and fracture at cross-over regions.

On the equivalence of the dual-wavelength and polarimetric equations for estimation of the raindrop size distribution

NASA Technical Reports Server (NTRS)

Meneghini, Robert; Liao, Liang

2006-01-01

In writing the integral equations for the median mass diameter and particle concentration, or comparable parameters of the raindrop size distribution, it is apparent that when attenuation effects are included, the forms of the equations for polarimetric and dual wavelength radars are identical. In both sets of equations, differences in the backscattering and extinction cross sections appear: in the polarimetric equations, the differences are taken with respect polarization at a fixed frequency while for the dual wavelength equations, the differences are taken with respect to wavelength at a fixed polarization. Because the forms of the equations are the same, the ways in which they can be solved are similar as well. To avoid instabilities in the forward recursion procedure, the equations can be expressed in the form of a final-value. Solving the equations in this way traditionally has required estimates of the path attenuations to the final gate: either the attenuations at horizontal and vertical polarizations at the same frequency or attenuations at two frequencies with the same polarization. This has been done for dual-frequency (air/spaceborne case) and polarimetric radars by the respective use of the surface reference technique and the differential phase shift. An alternative to solving the constrained version of the equations is an iterative procedure recently proposed in which independent estimates of path attenuation are not required. Although the procedure has limitations, it appears to be quite useful. Simulations of the retrievals help clarify the relationship between the constrained and unconstrained approaches and their application to the polarimetric and dual-wavelength equations.

An overview of unconstrained free boundary problems

PubMed Central

Figalli, Alessio; Shahgholian, Henrik

2015-01-01

In this paper, we present a survey concerning unconstrained free boundary problems of type where B1 is the unit ball, Ω is an unknown open set, F1 and F2 are elliptic operators (admitting regular solutions), and is a functions space to be specified in each case. Our main objective is to discuss a unifying approach to the optimal regularity of solutions to the above matching problems, and list several open problems in this direction. PMID:26261367

An improved marriage in honey bees optimization algorithm for single objective unconstrained optimization.

PubMed

Celik, Yuksel; Ulker, Erkan

2013-01-01

Marriage in honey bees optimization (MBO) is a metaheuristic optimization algorithm developed by inspiration of the mating and fertilization process of honey bees and is a kind of swarm intelligence optimizations. In this study we propose improved marriage in honey bees optimization (IMBO) by adding Levy flight algorithm for queen mating flight and neighboring for worker drone improving. The IMBO algorithm's performance and its success are tested on the well-known six unconstrained test functions and compared with other metaheuristic optimization algorithms.

A general-purpose optimization program for engineering design

NASA Technical Reports Server (NTRS)

Vanderplaats, G. N.; Sugimoto, H.

1986-01-01

A new general-purpose optimization program for engineering design is described. ADS (Automated Design Synthesis) is a FORTRAN program for nonlinear constrained (or unconstrained) function minimization. The optimization process is segmented into three levels: Strategy, Optimizer, and One-dimensional search. At each level, several options are available so that a total of nearly 100 possible combinations can be created. An example of available combinations is the Augmented Lagrange Multiplier method, using the BFGS variable metric unconstrained minimization together with polynomial interpolation for the one-dimensional search.

Control pole placement relationships

NASA Technical Reports Server (NTRS)

Ainsworth, O. R.

1982-01-01

Using a simplified Large Space Structure (LSS) model, a technique was developed which gives algebraic relationships for the unconstrained poles. The relationships, which were obtained by this technique, are functions of the structural characteristics and the control gains. Extremely interesting relationships evolve for the case when the structural damping is zero. If the damping is zero, the constrained poles are uncoupled from the structural mode shapes. These relationships, which are derived for structural damping and without structural damping, provide new insight into the migration of the unconstrained poles for the CFPPS.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luo, Yousong, E-mail: yousong.luo@rmit.edu.au

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

Constraining movement alters the recruitment of motor processes in mental rotation.

PubMed

Moreau, David

2013-02-01

Does mental rotation depend on the readiness to act? Recent evidence indicates that the involvement of motor processes in mental rotation is experience-dependent, suggesting that different levels of expertise in sensorimotor interactions lead to different strategies to solve mental rotation problems. Specifically, experts in motor activities perceive spatial material as objects that can be acted upon, triggering covert simulation of rotations. Because action simulation depends on the readiness to act, movement restriction should therefore disrupt mental rotation performance in individuals favoring motor processes. In this experiment, wrestlers and non-athletes judged whether pairs of three-dimensional stimuli were identical or different, with their hands either constrained or unconstrained. Wrestlers showed higher performance than controls in the rotation of geometric stimuli, but this difference disappeared when their hands were constrained. However, movement restriction had similar consequences for both groups in the rotation of hands. These findings suggest that expert's advantage in mental rotation of abstract objects is based on the readiness to act, even when physical manipulation is impossible.

Efficient and stable exponential time differencing Runge-Kutta methods for phase field elastic bending energy models

NASA Astrophysics Data System (ADS)

Wang, Xiaoqiang; Ju, Lili; Du, Qiang

2016-07-01

The Willmore flow formulated by phase field dynamics based on the elastic bending energy model has been widely used to describe the shape transformation of biological lipid vesicles. In this paper, we develop and investigate some efficient and stable numerical methods for simulating the unconstrained phase field Willmore dynamics and the phase field Willmore dynamics with fixed volume and surface area constraints. The proposed methods can be high-order accurate and are completely explicit in nature, by combining exponential time differencing Runge-Kutta approximations for time integration with spectral discretizations for spatial operators on regular meshes. We also incorporate novel linear operator splitting techniques into the numerical schemes to improve the discrete energy stability. In order to avoid extra numerical instability brought by use of large penalty parameters in solving the constrained phase field Willmore dynamics problem, a modified augmented Lagrange multiplier approach is proposed and adopted. Various numerical experiments are performed to demonstrate accuracy and stability of the proposed methods.

[Medical image elastic registration smoothed by unconstrained optimized thin-plate spline].

PubMed

Zhang, Yu; Li, Shuxiang; Chen, Wufan; Liu, Zhexing

2003-12-01

Elastic registration of medical image is an important subject in medical image processing. Previous work has concentrated on selecting the corresponding landmarks manually and then using thin-plate spline interpolating to gain the elastic transformation. However, the landmarks extraction is always prone to error, which will influence the registration results. Localizing the landmarks manually is also difficult and time-consuming. We the optimization theory to improve the thin-plate spline interpolation, and based on it, used an automatic method to extract the landmarks. Combining these two steps, we have proposed an automatic, exact and robust registration method and have gained satisfactory registration results.

Enhanced Multiobjective Optimization Technique for Comprehensive Aerospace Design. Part A

NASA Technical Reports Server (NTRS)

Chattopadhyay, Aditi; Rajadas, John N.

1997-01-01

A multidisciplinary design optimization procedure which couples formal multiobjectives based techniques and complex analysis procedures (such as computational fluid dynamics (CFD) codes) developed. The procedure has been demonstrated on a specific high speed flow application involving aerodynamics and acoustics (sonic boom minimization). In order to account for multiple design objectives arising from complex performance requirements, multiobjective formulation techniques are used to formulate the optimization problem. Techniques to enhance the existing Kreisselmeier-Steinhauser (K-S) function multiobjective formulation approach have been developed. The K-S function procedure used in the proposed work transforms a constrained multiple objective functions problem into an unconstrained problem which then is solved using the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm. Weight factors are introduced during the transformation process to each objective function. This enhanced procedure will provide the designer the capability to emphasize specific design objectives during the optimization process. The demonstration of the procedure utilizes a computational Fluid dynamics (CFD) code which solves the three-dimensional parabolized Navier-Stokes (PNS) equations for the flow field along with an appropriate sonic boom evaluation procedure thus introducing both aerodynamic performance as well as sonic boom as the design objectives to be optimized simultaneously. Sensitivity analysis is performed using a discrete differentiation approach. An approximation technique has been used within the optimizer to improve the overall computational efficiency of the procedure in order to make it suitable for design applications in an industrial setting.

Overcoming free energy barriers using unconstrained molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Hénin, Jérôme; Chipot, Christophe

2004-08-01

Association of unconstrained molecular dynamics (MD) and the formalisms of thermodynamic integration and average force [Darve and Pohorille, J. Chem. Phys. 115, 9169 (2001)] have been employed to determine potentials of mean force. When implemented in a general MD code, the additional computational effort, compared to other standard, unconstrained simulations, is marginal. The force acting along a chosen reaction coordinate ξ is estimated from the individual forces exerted on the chemical system and accumulated as the simulation progresses. The estimated free energy derivative computed for small intervals of ξ is canceled by an adaptive bias to overcome the barriers of the free energy landscape. Evolution of the system along the reaction coordinate is, thus, limited by its sole self-diffusion properties. The illustrative examples of the reversible unfolding of deca-L-alanine, the association of acetate and guanidinium ions in water, the dimerization of methane in water, and its transfer across the water liquid-vapor interface are examined to probe the efficiency of the method.

Overcoming free energy barriers using unconstrained molecular dynamics simulations.

PubMed

Hénin, Jérôme; Chipot, Christophe

2004-08-15

Association of unconstrained molecular dynamics (MD) and the formalisms of thermodynamic integration and average force [Darve and Pohorille, J. Chem. Phys. 115, 9169 (2001)] have been employed to determine potentials of mean force. When implemented in a general MD code, the additional computational effort, compared to other standard, unconstrained simulations, is marginal. The force acting along a chosen reaction coordinate xi is estimated from the individual forces exerted on the chemical system and accumulated as the simulation progresses. The estimated free energy derivative computed for small intervals of xi is canceled by an adaptive bias to overcome the barriers of the free energy landscape. Evolution of the system along the reaction coordinate is, thus, limited by its sole self-diffusion properties. The illustrative examples of the reversible unfolding of deca-L-alanine, the association of acetate and guanidinium ions in water, the dimerization of methane in water, and its transfer across the water liquid-vapor interface are examined to probe the efficiency of the method. (c) 2004 American Institute of Physics.

An Improved Marriage in Honey Bees Optimization Algorithm for Single Objective Unconstrained Optimization

PubMed Central

Celik, Yuksel; Ulker, Erkan

2013-01-01

Marriage in honey bees optimization (MBO) is a metaheuristic optimization algorithm developed by inspiration of the mating and fertilization process of honey bees and is a kind of swarm intelligence optimizations. In this study we propose improved marriage in honey bees optimization (IMBO) by adding Levy flight algorithm for queen mating flight and neighboring for worker drone improving. The IMBO algorithm's performance and its success are tested on the well-known six unconstrained test functions and compared with other metaheuristic optimization algorithms. PMID:23935416

Reflected stochastic differential equation models for constrained animal movement

USGS Publications Warehouse

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.

The Influence of Cognitive Abilities on Mathematical Problem Solving Performance

ERIC Educational Resources Information Center

Bahar, Abdulkadir

2013-01-01

Problem solving has been a core theme in education for several decades. Educators and policy makers agree on the importance of the role of problem solving skills for school and real life success. A primary purpose of this study was to investigate the influence of cognitive abilities on mathematical problem solving performance of students. The…

Influence of Efficacy and Resilience on Problem Solving in the United States, Taiwan, and China

ERIC Educational Resources Information Center

Li, Ming-hui; Eschenauer, Robert; Yang, Yan

2013-01-01

This study explores factors that influence problem-solving coping style across cultures. There was no significant difference in applying problem solving across U.S., Taiwanese, and Chinese samples. The effective predictors of problem solving in the U.S. and Chinese samples were self-efficacy and trait resilience, respectively. In the Taiwanese…

A Study of Penalty Function Methods for Constraint Handling with Genetic Algorithm

NASA Technical Reports Server (NTRS)

Ortiz, Francisco

2004-01-01

COMETBOARDS (Comparative Evaluation Testbed of Optimization and Analysis Routines for Design of Structures) is a design optimization test bed that can evaluate the performance of several different optimization algorithms. A few of these optimization algorithms are the sequence of unconstrained minimization techniques (SUMT), sequential linear programming (SLP) and the sequential quadratic programming techniques (SQP). A genetic algorithm (GA) is a search technique that is based on the principles of natural selection or "survival of the fittest". Instead of using gradient information, the GA uses the objective function directly in the search. The GA searches the solution space by maintaining a population of potential solutions. Then, using evolving operations such as recombination, mutation and selection, the GA creates successive generations of solutions that will evolve and take on the positive characteristics of their parents and thus gradually approach optimal or near-optimal solutions. By using the objective function directly in the search, genetic algorithms can be effectively applied in non-convex, highly nonlinear, complex problems. The genetic algorithm is not guaranteed to find the global optimum, but it is less likely to get trapped at a local optimum than traditional gradient-based search methods when the objective function is not smooth and generally well behaved. The purpose of this research is to assist in the integration of genetic algorithm (GA) into COMETBOARDS. COMETBOARDS cast the design of structures as a constrained nonlinear optimization problem. One method used to solve constrained optimization problem with a GA to convert the constrained optimization problem into an unconstrained optimization problem by developing a penalty function that penalizes infeasible solutions. There have been several suggested penalty function in the literature each with there own strengths and weaknesses. A statistical analysis of some suggested penalty functions is performed in this study. Also, a response surface approach to robust design is used to develop a new penalty function approach. This new penalty function approach is then compared with the other existing penalty functions.

Local adaptation within a hybrid species

PubMed Central

Eroukhmanoff, F; Hermansen, J S; Bailey, R I; Sæther, S A; Sætre, G-P

2013-01-01

Ecological divergence among populations may be strongly influenced by their genetic background. For instance, genetic admixture through introgressive hybridization or hybrid speciation is likely to affect the genetic variation and evolvability of phenotypic traits. We studied geographic variation in two beak dimensions and three other phenotypic traits of the Italian sparrow (Passer italiae), a young hybrid species formed through interbreeding between house sparrows (P. domesticus) and Spanish sparrows (P. hispaniolensis). We found that beak morphology was strongly influenced by precipitation regimes and that it appeared to be the target of divergent selection within Italian sparrows. Interestingly, however, the degree of parental genetic contribution in the hybrid species had no effect on phenotypic beak variation. Moreover, beak height divergence may mediate genetic differentiation between populations, consistent with isolation-by-adaptation within this hybrid species. The study illustrates how hybrid species may be relatively unconstrained by their admixed genetic background, allowing them to adapt rapidly to environmental variation. PMID:23695379

Should policy ethics come in two colours: green or white?

PubMed

Oswald, Malcolm

2013-05-01

When writing about policy, do you think in green or white? If not, I recommend that you do. I suggest that writers and journal editors should explicitly label every policy ethics paper either 'green' or 'white'. A green paper is an unconstrained exploration of a policy question. The controversial 'After-birth abortion' paper is an example. Had it been labelled as 'green', readers could have understood what Giubilini and Minerva explained later: that it was a discussion of philosophical ideas, and not a policy proposal advocating infanticide. A serious policy proposal should be labelled by writer(s) and editor(s) as 'white'. Its purpose should be to influence policy. In order to influence policy, I suggest three essential, and two desirable, characteristics of any white paper. Most importantly, a white paper should be set in the context in which the policy is to be made and applied.

The influence of meridional ice transport on Europa's ocean stratification and heat content

NASA Astrophysics Data System (ADS)

Zhu, Peiyun; Manucharyan, Georgy E.; Thompson, Andrew F.; Goodman, Jason C.; Vance, Steven D.

2017-06-01

Jupiter's moon Europa likely hosts a saltwater ocean beneath its icy surface. Geothermal heating and rotating convection in the ocean may drive a global overturning circulation that redistributes heat vertically and meridionally, preferentially warming the ice shell at the equator. Here we assess the previously unconstrained influence of ocean-ice coupling on Europa's ocean stratification and heat transport. We demonstrate that a relatively fresh layer can form at the ice-ocean interface due to a meridional ice transport forced by the differential ice shell heating between the equator and the poles. We provide analytical and numerical solutions for the layer's characteristics, highlighting their sensitivity to critical ocean parameters. For a weakly turbulent and highly saline ocean, a strong buoyancy gradient at the base of the freshwater layer can suppress vertical tracer exchange with the deeper ocean. As a result, the freshwater layer permits relatively warm deep ocean temperatures.

The influence of meridional ice transport on Europa's ocean stratification and heat content

NASA Astrophysics Data System (ADS)

Zhu, P.; Manucharyan, G.; Thompson, A. F.; Goodman, J. C.; Vance, S.

2017-12-01

Jupiter's moon Europa likely hosts a saltwater ocean beneath its icy surface. Geothermal heating and rotating convection in the ocean may drive a global overturning circulation that redistributes heat vertically and meridionally, preferentially warming the ice shell at the equator. Here we assess thepreviously unconstrained influence of ocean-ice coupling on Europa's ocean stratification and heat transport. We demonstrate that a relatively fresh layer can form at the ice-ocean interface due to a meridional ice transport forced by the differential ice shell heating between the equator and the poles. We provide analytical and numerical solutions for the layer's characteristics, highlighting their sensitivity to critical ocean parameters. For a weakly turbulent and highly saline ocean, a strong buoyancy gradient at the base of the freshwater layer can suppress vertical tracer exchange with the deeper ocean. As a result, the freshwater layer permits relatively warm deep ocean temperatures.

Body stability and muscle and motor cortex activity during walking with wide stance

PubMed Central

Farrell, Brad J.; Bulgakova, Margarita A.; Beloozerova, Irina N.; Sirota, Mikhail G.

2014-01-01

Biomechanical and neural mechanisms of balance control during walking are still poorly understood. In this study, we examined the body dynamic stability, activity of limb muscles, and activity of motor cortex neurons [primarily pyramidal tract neurons (PTNs)] in the cat during unconstrained walking and walking with a wide base of support (wide-stance walking). By recording three-dimensional full-body kinematics we found for the first time that during unconstrained walking the cat is dynamically unstable in the forward direction during stride phases when only two diagonal limbs support the body. In contrast to standing, an increased lateral between-paw distance during walking dramatically decreased the cat's body dynamic stability in double-support phases and prompted the cat to spend more time in three-legged support phases. Muscles contributing to abduction-adduction actions had higher activity during stance, while flexor muscles had higher activity during swing of wide-stance walking. The overwhelming majority of neurons in layer V of the motor cortex, 82% and 83% in the forelimb and hindlimb representation areas, respectively, were active differently during wide-stance walking compared with unconstrained condition, most often by having a different depth of stride-related frequency modulation along with a different mean discharge rate and/or preferred activity phase. Upon transition from unconstrained to wide-stance walking, proximal limb-related neuronal groups subtly but statistically significantly shifted their activity toward the swing phase, the stride phase where most of body instability occurs during this task. The data suggest that the motor cortex participates in maintenance of body dynamic stability during locomotion. PMID:24790167

Comparing kinematic changes between a finger-tapping task and unconstrained finger flexion-extension task in patients with Parkinson's disease.

PubMed

Teo, W P; Rodrigues, J P; Mastaglia, F L; Thickbroom, G W

2013-06-01

Repetitive finger tapping is a well-established clinical test for the evaluation of parkinsonian bradykinesia, but few studies have investigated other finger movement modalities. We compared the kinematic changes (movement rate and amplitude) and response to levodopa during a conventional index finger-thumb-tapping task and an unconstrained index finger flexion-extension task performed at maximal voluntary rate (MVR) for 20 s in 11 individuals with levodopa-responsive Parkinson's disease (OFF and ON) and 10 healthy age-matched controls. Between-task comparisons showed that for all conditions, the initial movement rate was greater for the unconstrained flexion-extension task than the tapping task. Movement rate in the OFF state was slower than in controls for both tasks and normalized in the ON state. The movement amplitude was also reduced for both tasks in OFF and increased in the ON state but did not reach control levels. The rate and amplitude of movement declined significantly for both tasks under all conditions (OFF/ON and controls). The time course of rate decline was comparable for both tasks and was similar in OFF/ON and controls, whereas the tapping task was associated with a greater decline in MA, both in controls and ON, but not OFF. The findings indicate that both finger movement tasks show similar kinematic changes during a 20-s sustained MVR, but that movement amplitude is less well sustained during the tapping task than the unconstrained finger movement task. Both movement rate and amplitude improved with levodopa; however, movement rate was more levodopa responsive than amplitude.

Kalman Filter Constraint Tuning for Turbofan Engine Health Estimation

NASA Technical Reports Server (NTRS)

Simon, Dan; Simon, Donald L.

2005-01-01

Kalman filters are often used to estimate the state variables of a dynamic system. However, in the application of Kalman filters some known signal information is often either ignored or dealt with heuristically. For instance, state variable constraints are often neglected because they do not fit easily into the structure of the Kalman filter. Recently published work has shown a new method for incorporating state variable inequality constraints in the Kalman filter, which has been shown to generally improve the filter s estimation accuracy. However, the incorporation of inequality constraints poses some risk to the estimation accuracy as the Kalman filter is theoretically optimal. This paper proposes a way to tune the filter constraints so that the state estimates follow the unconstrained (theoretically optimal) filter when the confidence in the unconstrained filter is high. When confidence in the unconstrained filter is not so high, then we use our heuristic knowledge to constrain the state estimates. The confidence measure is based on the agreement of measurement residuals with their theoretical values. The algorithm is demonstrated on a linearized simulation of a turbofan engine to estimate engine health.

Bending stiffness and interlayer shear modulus of few-layer graphene

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Xiaoming; Yi, Chenglin; Ke, Changhong, E-mail: cke@binghamton.edu

2015-03-09

Interlayer shear deformation occurs in the bending of multilayer graphene with unconstrained ends, thus influencing its bending rigidity. Here, we investigate the bending stiffness and interlayer shear modulus of few-layer graphene through examining its self-folding conformation on a flat substrate using atomic force microscopy in conjunction with nonlinear mechanics modeling. The results reveal that the bending stiffness of 2–6 layers graphene follows a square-power relationship with its thickness. The interlayer shear modulus is found to be in the range of 0.36–0.49 GPa. The research findings show that the weak interlayer shear interaction has a substantial stiffening effect for multilayer graphene.

Adaptive velocity-based six degree of freedom load control for real-time unconstrained biomechanical testing.

PubMed

Lawless, I M; Ding, B; Cazzolato, B S; Costi, J J

2014-09-22

Robotic biomechanics is a powerful tool for further developing our understanding of biological joints, tissues and their repair. Both velocity-based and hybrid force control methods have been applied to biomechanics but the complex and non-linear properties of joints have limited these to slow or stepwise loading, which may not capture the real-time behaviour of joints. This paper presents a novel force control scheme combining stiffness and velocity based methods aimed at achieving six degree of freedom unconstrained force control at physiological loading rates. Copyright © 2014 Elsevier Ltd. All rights reserved.

Trajectory optimization and guidance law development for national aerospace plane applications

NASA Technical Reports Server (NTRS)

Calise, A. J.; Flandro, G. A.; Corban, J. E.

1988-01-01

The work completed to date is comprised of the following: a simple vehicle model representative of the aerospace plane concept in the hypersonic flight regime, fuel-optimal climb profiles for the unconstrained and dynamic pressure constrained cases generated using a reduced order dynamic model, an analytic switching condition for transition to rocket powered flight as orbital velocity is approached, simple feedback guidance laws for both the unconstrained and dynamic pressure constrained cases derived via singular perturbation theory and a nonlinear transformation technique, and numerical simulation results for ascent to orbit in the dynamic pressure constrained case.

Resolving ice cloud optical thickness biases between CALIOP and MODIS using infrared retrievals

NASA Astrophysics Data System (ADS)

Holz, R. E.; Platnick, S.; Meyer, K.; Vaughan, M.; Heidinger, A.; Yang, P.; Wind, G.; Dutcher, S.; Ackerman, S.; Amarasinghe, N.; Nagle, F.; Wang, C.

2015-10-01

Despite its importance as one of the key radiative properties that determines the impact of upper tropospheric clouds on the radiation balance, ice cloud optical thickness (IOT) has proven to be one of the more challenging properties to retrieve from space-based remote sensing measurements. In particular, optically thin upper tropospheric ice clouds (cirrus) have been especially challenging due to their tenuous nature, extensive spatial scales, and complex particle shapes and light scattering characteristics. The lack of independent validation motivates the investigation presented in this paper, wherein systematic biases between MODIS Collection 5 (C5) and CALIOP Version 3 (V3) unconstrained retrievals of tenuous IOT (< 3) are examined using a month of collocated A-Train observations. An initial comparison revealed a factor of two bias between the MODIS and CALIOP IOT retrievals. This bias is investigated using an infrared (IR) radiative closure approach that compares both products with MODIS IR cirrus retrievals developed for this assessment. The analysis finds that both the MODIS C5 and the unconstrained CALIOP V3 retrievals are biased (high and low, respectively) relative to the IR IOT retrievals. Based on this finding, the MODIS and CALIOP algorithms are investigated with the goal of explaining and minimizing the biases relative to the IR. For MODIS we find that the assumed ice single scattering properties used for the C5 retrievals are not consistent with the mean IR COT distribution. The C5 ice scattering database results in the asymmetry parameter (g) varying as a function of effective radius with mean values that are too large. The MODIS retrievals have been brought into agreement with the IR by adopting a new ice scattering model for Collection 6 (C6) consisting of a modified gamma distribution comprised of a single habit (severely roughened aggregated columns); the C6 ice cloud optical property models have a constant g ~ 0.75 in the mid-visible spectrum, 5-15 % smaller than C5. For CALIOP, the assumed lidar ratio for unconstrained retrievals is fixed at 25 sr for the V3 data products. This value is found to be inconsistent with the constrained (predominantly nighttime) CALIOP retrievals. An experimental data set was produced using a modified lidar ratio of 32 sr for the unconstrained retrievals (an increase of 28 %), selected to provide consistency with the constrained V3 results. These modifications greatly improve the agreement with the IR and provide consistency between the MODIS and CALIOP products. Based on these results the recently released MODIS C6 optical products use the single habit distribution given above, while the upcoming CALIOP V4 unconstrained algorithm will use higher lidar ratios for unconstrained retrievals.

Resolving Ice Cloud Optical Thickness Biases Between CALIOP and MODIS Using Infrared Retrievals

NASA Technical Reports Server (NTRS)

Holz, R. E.; Platnick, S.; Meyer, K.; Vaughan, M.; Heidinger, A.; Yang, P.; Wind, G.; Dutcher, S.; Ackerman, S.; Amarasinghe, N.;

Resolving ice cloud optical thickness biases between CALIOP and MODIS using infrared retrievals

NASA Astrophysics Data System (ADS)

Holz, Robert E.; Platnick, Steven; Meyer, Kerry; Vaughan, Mark; Heidinger, Andrew; Yang, Ping; Wind, Gala; Dutcher, Steven; Ackerman, Steven; Amarasinghe, Nandana; Nagle, Fredrick; Wang, Chenxi

2016-04-01

Despite its importance as one of the key radiative properties that determines the impact of upper tropospheric clouds on the radiation balance, ice cloud optical thickness (IOT) has proven to be one of the more challenging properties to retrieve from space-based remote sensing measurements. In particular, optically thin upper tropospheric ice clouds (cirrus) have been especially challenging due to their tenuous nature, extensive spatial scales, and complex particle shapes and light-scattering characteristics. The lack of independent validation motivates the investigation presented in this paper, wherein systematic biases between MODIS Collection 5 (C5) and CALIOP Version 3 (V3) unconstrained retrievals of tenuous IOT (< 3) are examined using a month of collocated A-Train observations. An initial comparison revealed a factor of 2 bias between the MODIS and CALIOP IOT retrievals. This bias is investigated using an infrared (IR) radiative closure approach that compares both products with MODIS IR cirrus retrievals developed for this assessment. The analysis finds that both the MODIS C5 and the unconstrained CALIOP V3 retrievals are biased (high and low, respectively) relative to the IR IOT retrievals. Based on this finding, the MODIS and CALIOP algorithms are investigated with the goal of explaining and minimizing the biases relative to the IR. For MODIS we find that the assumed ice single-scattering properties used for the C5 retrievals are not consistent with the mean IR COT distribution. The C5 ice scattering database results in the asymmetry parameter (g) varying as a function of effective radius with mean values that are too large. The MODIS retrievals have been brought into agreement with the IR by adopting a new ice scattering model for Collection 6 (C6) consisting of a modified gamma distribution comprised of a single habit (severely roughened aggregated columns); the C6 ice cloud optical property models have a constant g ≈ 0.75 in the mid-visible spectrum, 5-15 % smaller than C5. For CALIOP, the assumed lidar ratio for unconstrained retrievals is fixed at 25 sr for the V3 data products. This value is found to be inconsistent with the constrained (predominantly nighttime) CALIOP retrievals. An experimental data set was produced using a modified lidar ratio of 32 sr for the unconstrained retrievals (an increase of 28 %), selected to provide consistency with the constrained V3 results. These modifications greatly improve the agreement with the IR and provide consistency between the MODIS and CALIOP products. Based on these results the recently released MODIS C6 optical products use the single-habit distribution given above, while the upcoming CALIOP V4 unconstrained algorithm will use higher lidar ratios for unconstrained retrievals.

Beyond the functional matrix hypothesis: a network null model of human skull growth for the formation of bone articulations

PubMed Central

Esteve-Altava, Borja; Rasskin-Gutman, Diego

2014-01-01

Craniofacial sutures and synchondroses form the boundaries among bones in the human skull, providing functional, developmental and evolutionary information. Bone articulations in the skull arise due to interactions between genetic regulatory mechanisms and epigenetic factors such as functional matrices (soft tissues and cranial cavities), which mediate bone growth. These matrices are largely acknowledged for their influence on shaping the bones of the skull; however, it is not fully understood to what extent functional matrices mediate the formation of bone articulations. Aiming to identify whether or not functional matrices are key developmental factors guiding the formation of bone articulations, we have built a network null model of the skull that simulates unconstrained bone growth. This null model predicts bone articulations that arise due to a process of bone growth that is uniform in rate, direction and timing. By comparing predicted articulations with the actual bone articulations of the human skull, we have identified which boundaries specifically need the presence of functional matrices for their formation. We show that functional matrices are necessary to connect facial bones, whereas an unconstrained bone growth is sufficient to connect non-facial bones. This finding challenges the role of the brain in the formation of boundaries between bones in the braincase without neglecting its effect on skull shape. Ultimately, our null model suggests where to look for modified developmental mechanisms promoting changes in bone growth patterns that could affect the development and evolution of the head skeleton. PMID:24975579

Students' Use of Technological Features while Solving a Mathematics Problem

ERIC Educational Resources Information Center

Lee, Hollylynne Stohl; Hollebrands, Karen F.

2006-01-01

The design of technology tools has the potential to dramatically influence how students interact with tools, and these interactions, in turn, may influence students' mathematical problem solving. To better understand these interactions, we analyzed eighth grade students' problem solving as they used a java applet designed to specifically accompany…

Innovation and problem solving: a review of common mechanisms.

PubMed

Griffin, Andrea S; Guez, David

2014-11-01

Behavioural innovations have become central to our thinking about how animals adjust to changing environments. It is now well established that animals vary in their ability to innovate, but understanding why remains a challenge. This is because innovations are rare, so studying innovation requires alternative experimental assays that create opportunities for animals to express their ability to invent new behaviours, or use pre-existing ones in new contexts. Problem solving of extractive foraging tasks has been put forward as a suitable experimental assay. We review the rapidly expanding literature on problem solving of extractive foraging tasks in order to better understand to what extent the processes underpinning problem solving, and the factors influencing problem solving, are in line with those predicted, and found, to underpin and influence innovation in the wild. Our aim is to determine whether problem solving can be used as an experimental proxy of innovation. We find that in most respects, problem solving is determined by the same underpinning mechanisms, and is influenced by the same factors, as those predicted to underpin, and to influence, innovation. We conclude that problem solving is a valid experimental assay for studying innovation, propose a conceptual model of problem solving in which motor diversity plays a more central role than has been considered to date, and provide recommendations for future research using problem solving to investigate innovation. This article is part of a Special Issue entitled: Cognition in the wild. Copyright © 2014 Elsevier B.V. All rights reserved.

Spontaneous gestures influence strategy choices in problem solving.

PubMed

Alibali, Martha W; Spencer, Robert C; Knox, Lucy; Kita, Sotaro

2011-09-01

Do gestures merely reflect problem-solving processes, or do they play a functional role in problem solving? We hypothesized that gestures highlight and structure perceptual-motor information, and thereby make such information more likely to be used in problem solving. Participants in two experiments solved problems requiring the prediction of gear movement, either with gesture allowed or with gesture prohibited. Such problems can be correctly solved using either a perceptual-motor strategy (simulation of gear movements) or an abstract strategy (the parity strategy). Participants in the gesture-allowed condition were more likely to use perceptual-motor strategies than were participants in the gesture-prohibited condition. Gesture promoted use of perceptual-motor strategies both for participants who talked aloud while solving the problems (Experiment 1) and for participants who solved the problems silently (Experiment 2). Thus, spontaneous gestures influence strategy choices in problem solving.

Comparative Evaluation of Different Optimization Algorithms for Structural Design Applications

NASA Technical Reports Server (NTRS)

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

1996-01-01

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

A Modified Penalty Parameter Approach for Optimal Estimation of UH with Simultaneous Estimation of Infiltration Parameters

NASA Astrophysics Data System (ADS)

Bhattacharjya, Rajib Kumar

2018-05-01

The unit hydrograph and the infiltration parameters of a watershed can be obtained from observed rainfall-runoff data by using inverse optimization technique. This is a two-stage optimization problem. In the first stage, the infiltration parameters are obtained and the unit hydrograph ordinates are estimated in the second stage. In order to combine this two-stage method into a single stage one, a modified penalty parameter approach is proposed for converting the constrained optimization problem to an unconstrained one. The proposed approach is designed in such a way that the model initially obtains the infiltration parameters and then searches the optimal unit hydrograph ordinates. The optimization model is solved using Genetic Algorithms. A reduction factor is used in the penalty parameter approach so that the obtained optimal infiltration parameters are not destroyed during subsequent generation of genetic algorithms, required for searching optimal unit hydrograph ordinates. The performance of the proposed methodology is evaluated by using two example problems. The evaluation shows that the model is superior, simple in concept and also has the potential for field application.

An adaptive evolutionary multi-objective approach based on simulated annealing.

PubMed

Li, H; Landa-Silva, D

2011-01-01

A multi-objective optimization problem can be solved by decomposing it into one or more single objective subproblems in some multi-objective metaheuristic algorithms. Each subproblem corresponds to one weighted aggregation function. For example, MOEA/D is an evolutionary multi-objective optimization (EMO) algorithm that attempts to optimize multiple subproblems simultaneously by evolving a population of solutions. However, the performance of MOEA/D highly depends on the initial setting and diversity of the weight vectors. In this paper, we present an improved version of MOEA/D, called EMOSA, which incorporates an advanced local search technique (simulated annealing) and adapts the search directions (weight vectors) corresponding to various subproblems. In EMOSA, the weight vector of each subproblem is adaptively modified at the lowest temperature in order to diversify the search toward the unexplored parts of the Pareto-optimal front. Our computational results show that EMOSA outperforms six other well established multi-objective metaheuristic algorithms on both the (constrained) multi-objective knapsack problem and the (unconstrained) multi-objective traveling salesman problem. Moreover, the effects of the main algorithmic components and parameter sensitivities on the search performance of EMOSA are experimentally investigated.

Performance Trend of Different Algorithms for Structural Design Optimization

NASA Technical Reports Server (NTRS)

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

1996-01-01

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

Structural brain correlates of unconstrained motor activity in people with schizophrenia.

PubMed

Farrow, Tom F D; Hunter, Michael D; Wilkinson, Iain D; Green, Russell D J; Spence, Sean A

2005-11-01

Avolition affects quality of life in chronic schizophrenia. We investigated the relationship between unconstrained motor activity and the volume of key executive brain regions in 16 male patients with schizophrenia. Wristworn actigraphy monitors were used to record motor activity over a 20 h period. Structural magnetic resonance imaging brain scans were parcellated and individual volumes for anterior cingulate cortex and dorsolateral prefrontal cortex extracted. Patients'total activity was positively correlated with volume of left anterior cingulate cortex. These data suggest that the volume of specific executive structures may affect (quantifiable) motor behaviours, having further implications for models of the 'will' and avolition.

Unconstrained paving and plastering method for generating finite element meshes

DOEpatents

Staten, Matthew L.; Owen, Steven J.; Blacker, Teddy D.; Kerr, Robert

2010-03-02

Computer software for and a method of generating a conformal all quadrilateral or hexahedral mesh comprising selecting an object with unmeshed boundaries and performing the following while unmeshed voids are larger than twice a desired element size and unrecognizable as either a midpoint subdividable or pave-and-sweepable polyhedra: selecting a front to advance; based on sizes of fronts and angles with adjacent fronts, determining which adjacent fronts should be advanced with the selected front; advancing the fronts; detecting proximities with other nearby fronts; resolving any found proximities; forming quadrilaterals or unconstrained columns of hexahedra where two layers cross; and establishing hexahedral elements where three layers cross.

Identification of terms to define unconstrained air transportation demands

NASA Technical Reports Server (NTRS)

Jacobson, I. D.; Kuhilhau, A. R.

1982-01-01

The factors involved in the evaluation of unconstrained air transportation systems were carefully analyzed. By definition an unconstrained system is taken to be one in which the design can employ innovative and advanced concepts no longer limited by present environmental, social, political or regulatory settings. Four principal evaluation criteria are involved: (1) service utilization, based on the operating performance characteristics as viewed by potential patrons; (2) community impacts, reflecting decisions based on the perceived impacts of the system; (3) technological feasibility, estimating what is required to reduce the system to practice; and (4) financial feasibility, predicting the ability of the concepts to attract financial support. For each of these criteria, a set of terms or descriptors was identified, which should be used in the evaluation to render it complete. It is also demonstrated that these descriptors have the following properties: (a) their interpretation may be made by different groups of evaluators; (b) their interpretations and the way they are used may depend on the stage of development of the system in which they are used; (c) in formulating the problem, all descriptors should be addressed independent of the evaluation technique selected.

The effects of expected reward on creative problem solving.

PubMed

Cristofori, Irene; Salvi, Carola; Beeman, Mark; Grafman, Jordan

2018-06-12

Creative problem solving involves search processes, and it is known to be hard to motivate. Reward cues have been found to enhance performance across a range of tasks, even when cues are presented subliminally, without being consciously detected. It is uncertain whether motivational processes, such as reward, can influence problem solving. We tested the effect of supraliminal and subliminal reward on participant performance on problem solving that can be solved by deliberate analysis or by insight. Forty-one participants attempted to solve 100 compound remote associate problems. At the beginning of each problem, a potential reward cue (1 or 25 cents) was displayed, either subliminally (17 ms) or supraliminally (100 ms). Participants earned the displayed reward if they solved the problem correctly. Results showed that the higher subliminal reward increased the percentage of problems solved correctly overall. Second, we explored if subliminal rewards preferentially influenced solutions that were achieved via a sudden insight (mostly processed below awareness) or via a deliberate analysis. Participants solved more problems via insight following high subliminal reward when compared with low subliminal reward, and compared with high supraliminal reward, with no corresponding effect on analytic solving. Striatal dopamine (DA) is thought to influence motivation, reinforce behavior, and facilitate cognition. We speculate that subliminal rewards activate the striatal DA system, enhancing the kinds of automatic integrative processes that lead to more creative strategies for problem solving, without increasing the selectivity of attention, which could impede insight.

Molecular driving forces defining lipid positions around aquaporin-0

PubMed Central

Aponte-Santamaría, Camilo; Briones, Rodolfo; Schenk, Andreas D.; Walz, Thomas; de Groot, Bert L.

2012-01-01

Lipid–protein interactions play pivotal roles in biological membranes. Electron crystallographic studies of the lens-specific water channel aquaporin-0 (AQP0) revealed atomistic views of such interactions, by providing high-resolution structures of annular lipids surrounding AQP0. It remained unclear, however, whether these lipid structures are representative of the positions of unconstrained lipids surrounding an individual protein, and what molecular determinants define the lipid positions around AQP0. We addressed these questions by using molecular dynamics simulations and crystallographic refinement, and calculated time-averaged densities of dimyristoyl-phosphatidylcholine lipids around AQP0. Our simulations demonstrate that, although the experimentally determined crystallographic lipid positions are constrained by the crystal packing, they appropriately describe the behavior of unconstrained lipids around an individual AQP0 tetramer, and thus likely represent physiologically relevant lipid positions.While the acyl chains were well localized, the lipid head groups were not. Furthermore, in silico mutations showed that electrostatic interactions do not play a major role attracting these phospholipids towards AQP0. Instead, the mobility of the protein crucially modulates the lipid localization and explains the difference in lipid density between extracellular and cytoplasmic leaflets. Moreover, our simulations support a general mechanism in which membrane proteins laterally diffuse accompanied by several layers of localized lipids, with the positions of the annular lipids being influenced the most by the protein surface. We conclude that the acyl chains rather than the head groups define the positions of dimyristoyl-phosphatidylcholine lipids around AQP0. Lipid localization is largely determined by the mobility of the protein surface, whereas hydrogen bonds play an important but secondary role. PMID:22679286

Beyond the functional matrix hypothesis: a network null model of human skull growth for the formation of bone articulations.

PubMed

Esteve-Altava, Borja; Rasskin-Gutman, Diego

2014-09-01

Craniofacial sutures and synchondroses form the boundaries among bones in the human skull, providing functional, developmental and evolutionary information. Bone articulations in the skull arise due to interactions between genetic regulatory mechanisms and epigenetic factors such as functional matrices (soft tissues and cranial cavities), which mediate bone growth. These matrices are largely acknowledged for their influence on shaping the bones of the skull; however, it is not fully understood to what extent functional matrices mediate the formation of bone articulations. Aiming to identify whether or not functional matrices are key developmental factors guiding the formation of bone articulations, we have built a network null model of the skull that simulates unconstrained bone growth. This null model predicts bone articulations that arise due to a process of bone growth that is uniform in rate, direction and timing. By comparing predicted articulations with the actual bone articulations of the human skull, we have identified which boundaries specifically need the presence of functional matrices for their formation. We show that functional matrices are necessary to connect facial bones, whereas an unconstrained bone growth is sufficient to connect non-facial bones. This finding challenges the role of the brain in the formation of boundaries between bones in the braincase without neglecting its effect on skull shape. Ultimately, our null model suggests where to look for modified developmental mechanisms promoting changes in bone growth patterns that could affect the development and evolution of the head skeleton. © 2014 Anatomical Society.

CometBoards Users Manual Release 1.0

NASA Technical Reports Server (NTRS)

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

1996-01-01

Several nonlinear mathematical programming algorithms for structural design applications are available at present. These include the sequence of unconstrained minimizations technique, the method of feasible directions, and the sequential quadratic programming technique. The optimality criteria technique and the fully utilized design concept are two other structural design methods. A project was undertaken to bring all these design methods under a common computer environment so that a designer can select any one of these tools that may be suitable for his/her application. To facilitate selection of a design algorithm, to validate and check out the computer code, and to ascertain the relative merits of the design tools, modest finite element structural analysis programs based on the concept of stiffness and integrated force methods have been coupled to each design method. The code that contains both these design and analysis tools, by reading input information from analysis and design data files, can cast the design of a structure as a minimum-weight optimization problem. The code can then solve it with a user-specified optimization technique and a user-specified analysis method. This design code is called CometBoards, which is an acronym for Comparative Evaluation Test Bed of Optimization and Analysis Routines for the Design of Structures. This manual describes for the user a step-by-step procedure for setting up the input data files and executing CometBoards to solve a structural design problem. The manual includes the organization of CometBoards; instructions for preparing input data files; the procedure for submitting a problem; illustrative examples; and several demonstration problems. A set of 29 structural design problems have been solved by using all the optimization methods available in CometBoards. A summary of the optimum results obtained for these problems is appended to this users manual. CometBoards, at present, is available for Posix-based Cray and Convex computers, Iris and Sun workstations, and the VM/CMS system.

A "Reverse-Schur" Approach to Optimization With Linear PDE Constraints: Application to Biomolecule Analysis and Design.

PubMed

Bardhan, Jaydeep P; Altman, Michael D; Tidor, B; White, Jacob K

2009-01-01

We present a partial-differential-equation (PDE)-constrained approach for optimizing a molecule's electrostatic interactions with a target molecule. The approach, which we call reverse-Schur co-optimization, can be more than two orders of magnitude faster than the traditional approach to electrostatic optimization. The efficiency of the co-optimization approach may enhance the value of electrostatic optimization for ligand-design efforts-in such projects, it is often desirable to screen many candidate ligands for their viability, and the optimization of electrostatic interactions can improve ligand binding affinity and specificity. The theoretical basis for electrostatic optimization derives from linear-response theory, most commonly continuum models, and simple assumptions about molecular binding processes. Although the theory has been used successfully to study a wide variety of molecular binding events, its implications have not yet been fully explored, in part due to the computational expense associated with the optimization. The co-optimization algorithm achieves improved performance by solving the optimization and electrostatic simulation problems simultaneously, and is applicable to both unconstrained and constrained optimization problems. Reverse-Schur co-optimization resembles other well-known techniques for solving optimization problems with PDE constraints. Model problems as well as realistic examples validate the reverse-Schur method, and demonstrate that our technique and alternative PDE-constrained methods scale very favorably compared to the standard approach. Regularization, which ordinarily requires an explicit representation of the objective function, can be included using an approximate Hessian calculated using the new BIBEE/P (boundary-integral-based electrostatics estimation by preconditioning) method.

A “Reverse-Schur” Approach to Optimization With Linear PDE Constraints: Application to Biomolecule Analysis and Design

PubMed Central

Bardhan, Jaydeep P.; Altman, Michael D.

2009-01-01

We present a partial-differential-equation (PDE)-constrained approach for optimizing a molecule’s electrostatic interactions with a target molecule. The approach, which we call reverse-Schur co-optimization, can be more than two orders of magnitude faster than the traditional approach to electrostatic optimization. The efficiency of the co-optimization approach may enhance the value of electrostatic optimization for ligand-design efforts–in such projects, it is often desirable to screen many candidate ligands for their viability, and the optimization of electrostatic interactions can improve ligand binding affinity and specificity. The theoretical basis for electrostatic optimization derives from linear-response theory, most commonly continuum models, and simple assumptions about molecular binding processes. Although the theory has been used successfully to study a wide variety of molecular binding events, its implications have not yet been fully explored, in part due to the computational expense associated with the optimization. The co-optimization algorithm achieves improved performance by solving the optimization and electrostatic simulation problems simultaneously, and is applicable to both unconstrained and constrained optimization problems. Reverse-Schur co-optimization resembles other well-known techniques for solving optimization problems with PDE constraints. Model problems as well as realistic examples validate the reverse-Schur method, and demonstrate that our technique and alternative PDE-constrained methods scale very favorably compared to the standard approach. Regularization, which ordinarily requires an explicit representation of the objective function, can be included using an approximate Hessian calculated using the new BIBEE/P (boundary-integral-based electrostatics estimation by preconditioning) method. PMID:23055839

Neural Networks for Computer Vision: A Framework for Specifications of a General Purpose Vision System

NASA Astrophysics Data System (ADS)

Skrzypek, Josef; Mesrobian, Edmond; Gungner, David J.

1989-03-01

The development of autonomous land vehicles (ALV) capable of operating in an unconstrained environment has proven to be a formidable research effort. The unpredictability of events in such an environment calls for the design of a robust perceptual system, an impossible task requiring the programming of a system bases on the expectation of future, unconstrained events. Hence, the need for a "general purpose" machine vision system that is capable of perceiving and understanding images in an unconstrained environment in real-time. The research undertaken at the UCLA Machine Perception Laboratory addresses this need by focusing on two specific issues: 1) the long term goals for machine vision research as a joint effort between the neurosciences and computer science; and 2) a framework for evaluating progress in machine vision. In the past, vision research has been carried out independently within different fields including neurosciences, psychology, computer science, and electrical engineering. Our interdisciplinary approach to vision research is based on the rigorous combination of computational neuroscience, as derived from neurophysiology and neuropsychology, with computer science and electrical engineering. The primary motivation behind our approach is that the human visual system is the only existing example of a "general purpose" vision system and using a neurally based computing substrate, it can complete all necessary visual tasks in real-time.

Robust 3D Position Estimation in Wide and Unconstrained Indoor Environments

PubMed Central

Mossel, Annette

2015-01-01

In this paper, a system for 3D position estimation in wide, unconstrained indoor environments is presented that employs infrared optical outside-in tracking of rigid-body targets with a stereo camera rig. To overcome limitations of state-of-the-art optical tracking systems, a pipeline for robust target identification and 3D point reconstruction has been investigated that enables camera calibration and tracking in environments with poor illumination, static and moving ambient light sources, occlusions and harsh conditions, such as fog. For evaluation, the system has been successfully applied in three different wide and unconstrained indoor environments, (1) user tracking for virtual and augmented reality applications, (2) handheld target tracking for tunneling and (3) machine guidance for mining. The results of each use case are discussed to embed the presented approach into a larger technological and application context. The experimental results demonstrate the system’s capabilities to track targets up to 100 m. Comparing the proposed approach to prior art in optical tracking in terms of range coverage and accuracy, it significantly extends the available tracking range, while only requiring two cameras and providing a relative 3D point accuracy with sub-centimeter deviation up to 30 m and low-centimeter deviation up to 100 m. PMID:26694388

A smart health monitoring chair for nonintrusive measurement of biological signals.

PubMed

Baek, Hyun Jae; Chung, Gih Sung; Kim, Ko Keun; Park, Kwang Suk

2012-01-01

We developed nonintrusive methods for simultaneous electrocardiogram, photoplethysmogram, and ballistocardiogram measurements that do not require direct contact between instruments and bare skin. These methods were applied to the design of a diagnostic chair for unconstrained heart rate and blood pressure monitoring purposes. Our methods were operationalized through capacitively coupled electrodes installed in the chair back that include high-input impedance amplifiers, and conductive textiles installed in the seat for capacitive driven-right-leg circuit configuration that is capable of recording electrocardiogram information through clothing. Photoplethysmograms were measured through clothing using seat mounted sensors with specially designed amplifier circuits that vary in light intensity according to clothing type. Ballistocardiograms were recorded using a film type transducer material, polyvinylidenefluoride (PVDF), which was installed beneath the seat cover. By simultaneously measuring signals, beat-to-beat heart rates could be monitored even when electrocardiograms were not recorded due to movement artifacts. Beat-to-beat blood pressure was also monitored using unconstrained measurements of pulse arrival time and other physiological parameters, and our experimental results indicated that the estimated blood pressure tended to coincide with actual blood pressure measurements. This study demonstrates the feasibility of our method and device for biological signal monitoring through clothing for unconstrained long-term daily health monitoring that does not require user awareness and is not limited by physical activity.

Rumination, Social Problem Solving and Suicide Intent Among Egyptians With a Recent Suicide Attempt.

PubMed

Sharaf, Amira Y; Lachine, Ola A; Thompson, Elaine A

2018-02-01

The more complex influences of social problem-solving abilities and rumination-specifically brooding and reflection-on suicide intent is not well understood. We hypothesized that social problem solving would moderate the association between reflection and suicide intent, and mediate the influence of brooding on suicide intent. A convenience sample (N=186) of individuals hospitalized for recent suicide attempt was interviewed, assessing suicide intent, social problem solving, brooding, reflection and depression. Brooding and reflection were positively associated with suicide intent. The mediating, but not the moderating, hypothesis was supported. Brooding was not significant (β=0.15, t=1.92, p=0.06) with social problem solving controlled. Interventions to disengage rumination and improve social problem-solving skills are underscored. Copyright © 2017 Elsevier Inc. All rights reserved.

Genetic influences on insight problem solving: the role of catechol-O-methyltransferase (COMT) gene polymorphisms

PubMed Central

Jiang, Weili; Shang, Siyuan; Su, Yanjie

2015-01-01

People may experience an “aha” moment, when suddenly realizing a solution of a puzzling problem. This experience is called insight problem solving. Several findings suggest that catecholamine-related genes may contribute to insight problem solving, among which the catechol-O-methyltransferase (COMT) gene is the most promising candidate. The current study examined 753 healthy individuals to determine the associations between 7 candidate single nucleotide polymorphisms on the COMT gene and insight problem-solving performance, while considering gender differences. The results showed that individuals carrying A allele of rs4680 or T allele of rs4633 scored significantly higher on insight problem-solving tasks, and the COMT gene rs5993883 combined with gender interacted with correct solutions of insight problems, specifically showing that this gene only influenced insight problem-solving performance in males. This study presents the first investigation of the genetic impact on insight problem solving and provides evidence that highlights the role that the COMT gene plays in insight problem solving. PMID:26528222

Genetic influences on insight problem solving: the role of catechol-O-methyltransferase (COMT) gene polymorphisms.

PubMed

Jiang, Weili; Shang, Siyuan; Su, Yanjie

2015-01-01

People may experience an "aha" moment, when suddenly realizing a solution of a puzzling problem. This experience is called insight problem solving. Several findings suggest that catecholamine-related genes may contribute to insight problem solving, among which the catechol-O-methyltransferase (COMT) gene is the most promising candidate. The current study examined 753 healthy individuals to determine the associations between 7 candidate single nucleotide polymorphisms on the COMT gene and insight problem-solving performance, while considering gender differences. The results showed that individuals carrying A allele of rs4680 or T allele of rs4633 scored significantly higher on insight problem-solving tasks, and the COMT gene rs5993883 combined with gender interacted with correct solutions of insight problems, specifically showing that this gene only influenced insight problem-solving performance in males. This study presents the first investigation of the genetic impact on insight problem solving and provides evidence that highlights the role that the COMT gene plays in insight problem solving.

How Culture Influences Teacher Self-Reflective Problem Solving Behavior and Self-Efficacy: Experiences of White Female Teachers Working through Relationship with Black Students in a Mid-Western American City

ERIC Educational Resources Information Center

Tolson, Bonnie Lynn

2013-01-01

Teachers make a difference. White female middle-class teachers represent 84 percent of Americas' teachers. How does culture influence the self-reflective problem-solving behaviors of urban teachers? Urban schools fail youth by opening the doors for a mass exodus. The problem solving behavior of urban teachers may contribute to the student exodus…

Unconstrained Capacities of Quantum Key Distribution and Entanglement Distillation for Pure-Loss Bosonic Broadcast Channels.

PubMed

Takeoka, Masahiro; Seshadreesan, Kaushik P; Wilde, Mark M

2017-10-13

We consider quantum key distribution (QKD) and entanglement distribution using a single-sender multiple-receiver pure-loss bosonic broadcast channel. We determine the unconstrained capacity region for the distillation of bipartite entanglement and secret key between the sender and each receiver, whenever they are allowed arbitrary public classical communication. A practical implication of our result is that the capacity region demonstrated drastically improves upon rates achievable using a naive time-sharing strategy, which has been employed in previously demonstrated network QKD systems. We show a simple example of a broadcast QKD protocol overcoming the limit of the point-to-point strategy. Our result is thus an important step toward opening a new framework of network channel-based quantum communication technology.

Gaussian Accelerated Molecular Dynamics: Unconstrained Enhanced Sampling and Free Energy Calculation.

PubMed

Miao, Yinglong; Feher, Victoria A; McCammon, J Andrew

2015-08-11

A Gaussian accelerated molecular dynamics (GaMD) approach for simultaneous enhanced sampling and free energy calculation of biomolecules is presented. By constructing a boost potential that follows Gaussian distribution, accurate reweighting of the GaMD simulations is achieved using cumulant expansion to the second order. Here, GaMD is demonstrated on three biomolecular model systems: alanine dipeptide, chignolin folding, and ligand binding to the T4-lysozyme. Without the need to set predefined reaction coordinates, GaMD enables unconstrained enhanced sampling of these biomolecules. Furthermore, the free energy profiles obtained from reweighting of the GaMD simulations allow us to identify distinct low-energy states of the biomolecules and characterize the protein-folding and ligand-binding pathways quantitatively.

Gaussian Accelerated Molecular Dynamics: Unconstrained Enhanced Sampling and Free Energy Calculation

PubMed Central

2016-01-01

A Gaussian accelerated molecular dynamics (GaMD) approach for simultaneous enhanced sampling and free energy calculation of biomolecules is presented. By constructing a boost potential that follows Gaussian distribution, accurate reweighting of the GaMD simulations is achieved using cumulant expansion to the second order. Here, GaMD is demonstrated on three biomolecular model systems: alanine dipeptide, chignolin folding, and ligand binding to the T4-lysozyme. Without the need to set predefined reaction coordinates, GaMD enables unconstrained enhanced sampling of these biomolecules. Furthermore, the free energy profiles obtained from reweighting of the GaMD simulations allow us to identify distinct low-energy states of the biomolecules and characterize the protein-folding and ligand-binding pathways quantitatively. PMID:26300708

Wavefront Control Toolbox for James Webb Space Telescope Testbed

NASA Technical Reports Server (NTRS)

Shiri, Ron; Aronstein, David L.; Smith, Jeffery Scott; Dean, Bruce H.; Sabatke, Erin

2007-01-01

We have developed a Matlab toolbox for wavefront control of optical systems. We have applied this toolbox to the optical models of James Webb Space Telescope (JWST) in general and to the JWST Testbed Telescope (TBT) in particular, implementing both unconstrained and constrained wavefront optimization to correct for possible misalignments present on the segmented primary mirror or the monolithic secondary mirror. The optical models implemented in Zemax optical design program and information is exchanged between Matlab and Zemax via the Dynamic Data Exchange (DDE) interface. The model configuration is managed using the XML protocol. The optimization algorithm uses influence functions for each adjustable degree of freedom of the optical mode. The iterative and non-iterative algorithms have been developed to converge to a local minimum of the root-mean-square (rms) of wavefront error using singular value decomposition technique of the control matrix of influence functions. The toolkit is highly modular and allows the user to choose control strategies for the degrees of freedom to be adjusted on a given iteration and wavefront convergence criterion. As the influence functions are nonlinear over the control parameter space, the toolkit also allows for trade-offs between frequency of updating the local influence functions and execution speed. The functionality of the toolbox and the validity of the underlying algorithms have been verified through extensive simulations.

Emotion and persuasion: cognitive and meta-cognitive processes impact attitudes.

PubMed

Petty, Richard E; Briñol, Pablo

2015-01-01

This article addresses the multiple ways in which emotions can influence attitudes and persuasion via primary and secondary (meta-) cognition. Using the elaboration likelihood model of persuasion as a guide, we review evidence for five fundamental processes that occur at different points along the elaboration continuum. When the extent of thinking is constrained to be low, emotions influence attitudes by relatively simple processes that lead them to change in a manner consistent with the valence of the emotion. When thinking is constrained to be high, emotions can serve as arguments in favour of a proposal if they are relevant to the merits of the advocacy or they can bias thinking if the emotion precedes the message. If thinking is high and emotions become salient after thinking, they can lead people to rely or not rely on the thoughts generated either because the emotion leads people to like or dislike their thoughts (affective validation) or feel more confident or doubtful in their thoughts (cognitive validation). When thinking is unconstrained, emotions influence the extent of thinking about the persuasive communication. Although prior theories have addressed one or more of these fundamental processes, no other approach has integrated them into one framework.

Surveying Graduate Students' Attitudes and Approaches to Problem Solving

ERIC Educational Resources Information Center

Mason, Andrew; Singh, Chandralekha

2010-01-01

Students' attitudes and approaches to problem solving in physics can profoundly influence their motivation to learn and development of expertise. We developed and validated an Attitudes and Approaches to Problem Solving survey by expanding the Attitudes toward Problem Solving survey of Marx and Cummings and administered it to physics graduate…

Factors Contributing to Problem-Solving Performance in First-Semester Organic Chemistry

ERIC Educational Resources Information Center

Lopez, Enrique J.; Shavelson, Richard J.; Nandagopal, Kiruthiga; Szu, Evan; Penn, John

2014-01-01

Problem solving is a highly valued skill in chemistry. Courses within this discipline place a substantial emphasis on problem-solving performance and tend to weigh such performance heavily in assessments of learning. Researchers have dedicated considerable effort investigating individual factors that influence problem-solving performance. The…

Distributed Constrained Optimization with Semicoordinate Transformations

NASA Technical Reports Server (NTRS)

Macready, William; Wolpert, David

2006-01-01

Recent work has shown how information theory extends conventional full-rationality game theory to allow bounded rational agents. The associated mathematical framework can be used to solve constrained optimization problems. This is done by translating the problem into an iterated game, where each agent controls a different variable of the problem, so that the joint probability distribution across the agents moves gives an expected value of the objective function. The dynamics of the agents is designed to minimize a Lagrangian function of that joint distribution. Here we illustrate how the updating of the Lagrange parameters in the Lagrangian is a form of automated annealing, which focuses the joint distribution more and more tightly about the joint moves that optimize the objective function. We then investigate the use of "semicoordinate" variable transformations. These separate the joint state of the agents from the variables of the optimization problem, with the two connected by an onto mapping. We present experiments illustrating the ability of such transformations to facilitate optimization. We focus on the special kind of transformation in which the statistically independent states of the agents induces a mixture distribution over the optimization variables. Computer experiment illustrate this for &sat constraint satisfaction problems and for unconstrained minimization of NK functions.

Finding Maximum Cliques on the D-Wave Quantum Annealer

DOE PAGES

Chapuis, Guillaume; Djidjev, Hristo; Hahn, Georg; ...

2018-05-03

This work assesses the performance of the D-Wave 2X (DW) quantum annealer for finding a maximum clique in a graph, one of the most fundamental and important NP-hard problems. Because the size of the largest graphs DW can directly solve is quite small (usually around 45 vertices), we also consider decomposition algorithms intended for larger graphs and analyze their performance. For smaller graphs that fit DW, we provide formulations of the maximum clique problem as a quadratic unconstrained binary optimization (QUBO) problem, which is one of the two input types (together with the Ising model) acceptable by the machine, andmore » compare several quantum implementations to current classical algorithms such as simulated annealing, Gurobi, and third-party clique finding heuristics. We further estimate the contributions of the quantum phase of the quantum annealer and the classical post-processing phase typically used to enhance each solution returned by DW. We demonstrate that on random graphs that fit DW, no quantum speedup can be observed compared with the classical algorithms. On the other hand, for instances specifically designed to fit well the DW qubit interconnection network, we observe substantial speed-ups in computing time over classical approaches.« less

A case study in programming a quantum annealer for hard operational planning problems

NASA Astrophysics Data System (ADS)

Rieffel, Eleanor G.; Venturelli, Davide; O'Gorman, Bryan; Do, Minh B.; Prystay, Elicia M.; Smelyanskiy, Vadim N.

2015-01-01

We report on a case study in programming an early quantum annealer to attack optimization problems related to operational planning. While a number of studies have looked at the performance of quantum annealers on problems native to their architecture, and others have examined performance of select problems stemming from an application area, ours is one of the first studies of a quantum annealer's performance on parametrized families of hard problems from a practical domain. We explore two different general mappings of planning problems to quadratic unconstrained binary optimization (QUBO) problems, and apply them to two parametrized families of planning problems, navigation-type and scheduling-type. We also examine two more compact, but problem-type specific, mappings to QUBO, one for the navigation-type planning problems and one for the scheduling-type planning problems. We study embedding properties and parameter setting and examine their effect on the efficiency with which the quantum annealer solves these problems. From these results, we derive insights useful for the programming and design of future quantum annealers: problem choice, the mapping used, the properties of the embedding, and the annealing profile all matter, each significantly affecting the performance.

Hidden Markov random field model and Broyden-Fletcher-Goldfarb-Shanno algorithm for brain image segmentation

NASA Astrophysics Data System (ADS)

Guerrout, EL-Hachemi; Ait-Aoudia, Samy; Michelucci, Dominique; Mahiou, Ramdane

2018-05-01

Many routine medical examinations produce images of patients suffering from various pathologies. With the huge number of medical images, the manual analysis and interpretation became a tedious task. Thus, automatic image segmentation became essential for diagnosis assistance. Segmentation consists in dividing the image into homogeneous and significant regions. We focus on hidden Markov random fields referred to as HMRF to model the problem of segmentation. This modelisation leads to a classical function minimisation problem. Broyden-Fletcher-Goldfarb-Shanno algorithm referred to as BFGS is one of the most powerful methods to solve unconstrained optimisation problem. In this paper, we investigate the combination of HMRF and BFGS algorithm to perform the segmentation operation. The proposed method shows very good segmentation results comparing with well-known approaches. The tests are conducted on brain magnetic resonance image databases (BrainWeb and IBSR) largely used to objectively confront the results obtained. The well-known Dice coefficient (DC) was used as similarity metric. The experimental results show that, in many cases, our proposed method approaches the perfect segmentation with a Dice Coefficient above .9. Moreover, it generally outperforms other methods in the tests conducted.

A Minimax Network Flow Model for Characterizing the Impact of Slot Restrictions

NASA Technical Reports Server (NTRS)

Lee, Douglas W.; Patek, Stephen D.; Alexandrov, Natalia; Bass, Ellen J.; Kincaid, Rex K.

2010-01-01

This paper proposes a model for evaluating long-term measures to reduce congestion at airports in the National Airspace System (NAS). This model is constructed with the goal of assessing the global impacts of congestion management strategies, specifically slot restrictions. We develop the Minimax Node Throughput Problem (MINNTHRU), a multicommodity network flow model that provides insight into air traffic patterns when one minimizes the worst-case operation across all airports in a given network. MINNTHRU is thus formulated as a model where congestion arises from network topology. It reflects not market-driven airline objectives, but those of a regulatory authority seeking a distribution of air traffic beneficial to all airports, in response to congestion management measures. After discussing an algorithm for solving MINNTHRU for moderate-sized (30 nodes) and larger networks, we use this model to study the impacts of slot restrictions on the operation of an entire hub-spoke airport network. For both a small example network and a medium-sized network based on 30 airports in the NAS, we use MINNTHRU to demonstrate that increasing the severity of slot restrictions increases the traffic around unconstrained hub airports as well as the worst-case level of operation over all airports.

Finding Maximum Cliques on the D-Wave Quantum Annealer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chapuis, Guillaume; Djidjev, Hristo; Hahn, Georg

This work assesses the performance of the D-Wave 2X (DW) quantum annealer for finding a maximum clique in a graph, one of the most fundamental and important NP-hard problems. Because the size of the largest graphs DW can directly solve is quite small (usually around 45 vertices), we also consider decomposition algorithms intended for larger graphs and analyze their performance. For smaller graphs that fit DW, we provide formulations of the maximum clique problem as a quadratic unconstrained binary optimization (QUBO) problem, which is one of the two input types (together with the Ising model) acceptable by the machine, andmore » compare several quantum implementations to current classical algorithms such as simulated annealing, Gurobi, and third-party clique finding heuristics. We further estimate the contributions of the quantum phase of the quantum annealer and the classical post-processing phase typically used to enhance each solution returned by DW. We demonstrate that on random graphs that fit DW, no quantum speedup can be observed compared with the classical algorithms. On the other hand, for instances specifically designed to fit well the DW qubit interconnection network, we observe substantial speed-ups in computing time over classical approaches.« less

Swarm satellite mission scheduling & planning using Hybrid Dynamic Mutation Genetic Algorithm

NASA Astrophysics Data System (ADS)

Zheng, Zixuan; Guo, Jian; Gill, Eberhard

2017-08-01

Space missions have traditionally been controlled by operators from a mission control center. Given the increasing number of satellites for some space missions, generating a command list for multiple satellites can be time-consuming and inefficient. Developing multi-satellite, onboard mission scheduling & planning techniques is, therefore, a key research field for future space mission operations. In this paper, an improved Genetic Algorithm (GA) using a new mutation strategy is proposed as a mission scheduling algorithm. This new mutation strategy, called Hybrid Dynamic Mutation (HDM), combines the advantages of both dynamic mutation strategy and adaptive mutation strategy, overcoming weaknesses such as early convergence and long computing time, which helps standard GA to be more efficient and accurate in dealing with complex missions. HDM-GA shows excellent performance in solving both unconstrained and constrained test functions. The experiments of using HDM-GA to simulate a multi-satellite, mission scheduling problem demonstrates that both the computation time and success rate mission requirements can be met. The results of a comparative test between HDM-GA and three other mutation strategies also show that HDM has outstanding performance in terms of speed and reliability.

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

NASA Technical Reports Server (NTRS)

Ono, Masahiro; Kuwata, Yoshiaki

2013-01-01

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

Maximum-entropy probability distributions under Lp-norm constraints

NASA Technical Reports Server (NTRS)

Dolinar, S.

1991-01-01

Continuous probability density functions and discrete probability mass functions are tabulated which maximize the differential entropy or absolute entropy, respectively, among all probability distributions with a given L sub p norm (i.e., a given pth absolute moment when p is a finite integer) and unconstrained or constrained value set. Expressions for the maximum entropy are evaluated as functions of the L sub p norm. The most interesting results are obtained and plotted for unconstrained (real valued) continuous random variables and for integer valued discrete random variables. The maximum entropy expressions are obtained in closed form for unconstrained continuous random variables, and in this case there is a simple straight line relationship between the maximum differential entropy and the logarithm of the L sub p norm. Corresponding expressions for arbitrary discrete and constrained continuous random variables are given parametrically; closed form expressions are available only for special cases. However, simpler alternative bounds on the maximum entropy of integer valued discrete random variables are obtained by applying the differential entropy results to continuous random variables which approximate the integer valued random variables in a natural manner. All the results are presented in an integrated framework that includes continuous and discrete random variables, constraints on the permissible value set, and all possible values of p. Understanding such as this is useful in evaluating the performance of data compression schemes.

Infrared and visible fusion face recognition based on NSCT domain

NASA Astrophysics Data System (ADS)

Xie, Zhihua; Zhang, Shuai; Liu, Guodong; Xiong, Jinquan

2018-01-01

Visible face recognition systems, being vulnerable to illumination, expression, and pose, can not achieve robust performance in unconstrained situations. Meanwhile, near infrared face images, being light- independent, can avoid or limit the drawbacks of face recognition in visible light, but its main challenges are low resolution and signal noise ratio (SNR). Therefore, near infrared and visible fusion face recognition has become an important direction in the field of unconstrained face recognition research. In this paper, a novel fusion algorithm in non-subsampled contourlet transform (NSCT) domain is proposed for Infrared and visible face fusion recognition. Firstly, NSCT is used respectively to process the infrared and visible face images, which exploits the image information at multiple scales, orientations, and frequency bands. Then, to exploit the effective discriminant feature and balance the power of high-low frequency band of NSCT coefficients, the local Gabor binary pattern (LGBP) and Local Binary Pattern (LBP) are applied respectively in different frequency parts to obtain the robust representation of infrared and visible face images. Finally, the score-level fusion is used to fuse the all the features for final classification. The visible and near infrared face recognition is tested on HITSZ Lab2 visible and near infrared face database. Experiments results show that the proposed method extracts the complementary features of near-infrared and visible-light images and improves the robustness of unconstrained face recognition.

Real-time in vivo uric acid biosensor system for biophysical monitoring of birds.

PubMed

Gumus, A; Lee, S; Karlsson, K; Gabrielson, R; Winkler, D W; Erickson, D

2014-02-21

Research on birds has long played an important role in ecological investigations, as birds are relatively easily observed, and their high metabolic rates and diurnal habits make them quite evidently responsive to changes in their environments. A mechanistic understanding of such avian responses requires a better understanding of how variation in physiological state conditions avian behavior and integrates the effects of recent environmental changes. There is a great need for sensor systems that will allow free-flying birds to interact with their environment and make unconstrained decisions about their spatial location at the same time that their physiological state is being monitored in real time. We have developed a miniature needle-based enzymatic sensor system suitable for continuous real-time amperometric monitoring of uric acid levels in unconstrained live birds. The sensor system was constructed with Pt/Ir wire and Ag/AgCl paste. Uricase enzyme was immobilized on a 0.7 mm sensing cavity of Nafion/cellulose inner membrane to minimize the influences of background interferents. The sensor response was linear from 0.05 to 0.6 mM uric acid, which spans the normal physiological range for most avian species. We developed a two-electrode potentiostat system that drives the biosensor, reads the output current, and wirelessly transmits the data. In addition to extensive characterization of the sensor and system, we also demonstrate autonomous operation of the system by collecting in vivo extracellular uric acid measurements on a domestic chicken. The results confirm our needle-type sensor system's potential for real-time monitoring of birds' physiological state. Successful application of the sensor in migratory birds could open up a new era of studying both the physiological preparation for migration and the consequences of sustained avian flight.

Detachable glass microelectrodes for recording action potentials in active moving organs.

PubMed

Barbic, Mladen; Moreno, Angel; Harris, Tim D; Kay, Matthew W

2017-06-01

Here, we describe new detachable floating glass micropipette electrode devices that provide targeted action potential recordings in active moving organs without requiring constant mechanical constraint or pharmacological inhibition of tissue motion. The technology is based on the concept of a glass micropipette electrode that is held firmly during cell targeting and intracellular insertion, after which a 100-µg glass microelectrode, a "microdevice," is gently released to remain within the moving organ. The microdevices provide long-term recordings of action potentials, even during millimeter-scale movement of tissue in which the device is embedded. We demonstrate two different glass micropipette electrode holding and detachment designs appropriate for the heart (sharp glass microdevices for cardiac myocytes in rats, guinea pigs, and humans) and the brain (patch glass microdevices for neurons in rats). We explain how microdevices enable measurements of multiple cells within a moving organ that are typically difficult with other technologies. Using sharp microdevices, action potential duration was monitored continuously for 15 min in unconstrained perfused hearts during global ischemia-reperfusion, providing beat-to-beat measurements of changes in action potential duration. Action potentials from neurons in the hippocampus of anesthetized rats were measured with patch microdevices, which provided stable base potentials during long-term recordings. Our results demonstrate that detachable microdevices are an elegant and robust tool to record electrical activity with high temporal resolution and cellular level localization without disturbing the physiological working conditions of the organ. NEW & NOTEWORTHY Cellular action potential measurements within tissue using glass micropipette electrodes usually require tissue immobilization, potentially influencing the physiological relevance of the measurement. Here, we addressed this limitation with novel 100-µg detachable glass microelectrodes that can be precisely positioned to provide long-term measurements of action potential duration during unconstrained tissue movement. Copyright © 2017 the American Physiological Society.

Prompting in Web-Based Environments: Supporting Self-Monitoring and Problem Solving Skills in College Students

ERIC Educational Resources Information Center

Kauffman, Douglas F.; Ge, Xun; Xie, Kui; Chen, Ching-Huei

2008-01-01

This study explored Metacognition and how automated instructional support in the form of problem-solving and self-reflection prompts influenced students' capacity to solve complex problems in a Web-based learning environment. Specifically, we examined the independent and interactive effects of problem-solving prompts and reflection prompts on…

Noticing relevant problem features: activating prior knowledge affects problem solving by guiding encoding

PubMed Central

Crooks, Noelle M.; Alibali, Martha W.

2013-01-01

This study investigated whether activating elements of prior knowledge can influence how problem solvers encode and solve simple mathematical equivalence problems (e.g., 3 + 4 + 5 = 3 + __). Past work has shown that such problems are difficult for elementary school students (McNeil and Alibali, 2000). One possible reason is that children's experiences in math classes may encourage them to think about equations in ways that are ultimately detrimental. Specifically, children learn a set of patterns that are potentially problematic (McNeil and Alibali, 2005a): the perceptual pattern that all equations follow an “operations = answer” format, the conceptual pattern that the equal sign means “calculate the total”, and the procedural pattern that the correct way to solve an equation is to perform all of the given operations on all of the given numbers. Upon viewing an equivalence problem, knowledge of these patterns may be reactivated, leading to incorrect problem solving. We hypothesized that these patterns may negatively affect problem solving by influencing what people encode about a problem. To test this hypothesis in children would require strengthening their misconceptions, and this could be detrimental to their mathematical development. Therefore, we tested this hypothesis in undergraduate participants. Participants completed either control tasks or tasks that activated their knowledge of the three patterns, and were then asked to reconstruct and solve a set of equivalence problems. Participants in the knowledge activation condition encoded the problems less well than control participants. They also made more errors in solving the problems, and their errors resembled the errors children make when solving equivalence problems. Moreover, encoding performance mediated the effect of knowledge activation on equivalence problem solving. Thus, one way in which experience may affect equivalence problem solving is by influencing what students encode about the equations. PMID:24324454

Constraints on geomagnetic secular variation modeling from electromagnetism and fluid dynamics of the Earth's core

NASA Technical Reports Server (NTRS)

Benton, E. R.

1986-01-01

A spherical harmonic representation of the geomagnetic field and its secular variation for epoch 1980, designated GSFC(9/84), is derived and evaluated. At three epochs (1977.5, 1980.0, 1982.5) this model incorporates conservation of magnetic flux through five selected patches of area on the core/mantle boundary bounded by the zero contours of vertical magnetic field. These fifteen nonlinear constraints are included like data in an iterative least squares parameter estimation procedure that starts with the recently derived unconstrained field model GSFC (12/83). Convergence is approached within three iterations. The constrained model is evaluated by comparing its predictive capability outside the time span of its data, in terms of residuals at magnetic observatories, with that for the unconstrained model.

Automated acquisition system for routine, noninvasive monitoring of physiological data.

PubMed

Ogawa, M; Tamura, T; Togawa, T

1998-01-01

A fully automated, noninvasive data-acquisition system was developed to permit long-term measurement of physiological functions at home, without disturbing subjects' normal routines. The system consists of unconstrained monitors built into furnishings and structures in a home environment. An electrocardiographic (ECG) monitor in the bathtub measures heart function during bathing, a temperature monitor in the bed measures body temperature, and a weight monitor built into the toilet serves as a scale to record weight. All three monitors are connected to one computer and function with data-acquisition programs and a data format rule. The unconstrained physiological parameter monitors and fully automated measurement procedures collect data noninvasively without the subject's awareness. The system was tested for 1 week by a healthy male subject, aged 28, in laboratory-based facilities.

Steepest descent method implementation on unconstrained optimization problem using C++ program

NASA Astrophysics Data System (ADS)

Napitupulu, H.; Sukono; Mohd, I. Bin; Hidayat, Y.; Supian, S.

2018-03-01

Steepest Descent is known as the simplest gradient method. Recently, many researches are done to obtain the appropriate step size in order to reduce the objective function value progressively. In this paper, the properties of steepest descent method from literatures are reviewed together with advantages and disadvantages of each step size procedure. The development of steepest descent method due to its step size procedure is discussed. In order to test the performance of each step size, we run a steepest descent procedure in C++ program. We implemented it to unconstrained optimization test problem with two variables, then we compare the numerical results of each step size procedure. Based on the numerical experiment, we conclude the general computational features and weaknesses of each procedure in each case of problem.

3D modeling of unconstrained HPT process: role of strain gradient on high deformed microstructure formation

NASA Astrophysics Data System (ADS)

Ben Kaabar, A.; Aoufi, A.; Descartes, S.; Desrayaud, C.

2017-05-01

During tribological contact’s life, different deformation paths lead to the formation of high deformed microstructure, in the near-surface layers of the bodies. The mechanical conditions (high pressure, shear) occurring under contact, are reproduced through unconstrained High Pressure Torsion configuration. A 3D finite element model of this HPT test is developed to study the local deformation history leading to high deformed microstructure with nominal pressure and friction coefficient. For the present numerical study the friction coefficient at the interface sample/anvils is kept constant at 0.3; the material used is high purity iron. The strain distribution in the sample bulk, as well as the main components of the strain gradients according to the spatial coordinates are investigated, with rotation angle of the anvil.

Conceptual/preliminary design study of subsonic v/stol and stovl aircraft derivatives of the S-3A

NASA Technical Reports Server (NTRS)

Kidwell, G. H., Jr.

1981-01-01

A computerized aircraft synthesis program was used to examine the feasibility and capability of a V/STOL aircraft based on the Navy S-3A aircraft. Two major airframe modifications are considered: replacement of the wing, and substitution of deflected thrust turbofan engines similar to the Pegasus engine. Three planform configurations for the all composite wing were investigated: an unconstrained span design, a design with the span constrained to 64 feet, and an unconstrained span oblique wing design. Each design was optimized using the same design variables, and performance and control analyses were performed. The oblique wing configuration was found to have the greatest potential in this application. The mission performance of these V/STOL aircraft compares favorably with that of the CTOL S-3A.

The effectiveness of problem-based learning on students’ problem solving ability in vector analysis course

NASA Astrophysics Data System (ADS)

Mushlihuddin, R.; Nurafifah; Irvan

2018-01-01

The student’s low ability in mathematics problem solving proved to the less effective of a learning process in the classroom. Effective learning was a learning that affects student’s math skills, one of which is problem-solving abilities. Problem-solving capability consisted of several stages: understanding the problem, planning the settlement, solving the problem as planned, re-examining the procedure and the outcome. The purpose of this research was to know: (1) was there any influence of PBL model in improving ability Problem solving of student math in a subject of vector analysis?; (2) was the PBL model effective in improving students’ mathematical problem-solving skills in vector analysis courses? This research was a quasi-experiment research. The data analysis techniques performed from the test stages of data description, a prerequisite test is the normality test, and hypothesis test using the ANCOVA test and Gain test. The results showed that: (1) there was an influence of PBL model in improving students’ math problem-solving abilities in vector analysis courses; (2) the PBL model was effective in improving students’ problem-solving skills in vector analysis courses with a medium category.

The coordination of problem solving strategies: when low competence sources exert more influence on task processing than high competence sources.

PubMed

Quiamzade, Alain; Mugny, Gabriel; Darnon, Céline

2009-03-01

Previous research has shown that low competence sources, compared to highly competent sources, can exert influence in aptitudes tasks in as much as they induce people to focus on the task and to solve it more deeply. Two experiments aimed at testing the coordination between self and source's problem solving strategies as a main explanation of such a difference in influence. The influence of a low versus high competence source has been examined in an anagram task that allows for distinguishing between three response strategies, including one that corresponds to the coordination between the source's strategy and participants' own strategy. In Study 1 the strategy suggested by the source was either relevant and useful or irrelevant and useless for solving the task. Results indicated that participants used the coordination strategy in a larger extend when they had been confronted to a low competence rather than a highly competent source but only when the source displayed a strategy that was useful to solve the task. In Study 2 the source's strategy was always relevant and useful, but a decentring procedure was introduced for half of the participants. This procedure induced participants to consider other points of view than their own. Results replicated the difference observed in Study 1 when no decentring was introduced. The difference however disappeared when decentring was induced, because of an increase of the high competence source's influence. These results highlight coordination of strategies as one mechanism underlying influence from low competence sources.

Progression paths in children's problem solving: The influence of dynamic testing, initial variability, and working memory.

PubMed

Resing, Wilma C M; Bakker, Merel; Pronk, Christine M E; Elliott, Julian G

2017-01-01

The current study investigated developmental trajectories of analogical reasoning performance of 104 7- and 8-year-old children. We employed a microgenetic research method and multilevel analysis to examine the influence of several background variables and experimental treatment on the children's developmental trajectories. Our participants were divided into two treatment groups: repeated practice alone and repeated practice with training. Each child received an initial working memory assessment and was subsequently asked to solve figural analogies on each of several sessions. We examined children's analogical problem-solving behavior and their subsequent verbal accounts of their employed solving processes. We also investigated the influence of verbal and visual-spatial working memory capacity and initial variability in strategy use on analogical reasoning development. Results indicated that children in both treatment groups improved but that gains were greater for those who had received training. Training also reduced the influence of children's initial variability in the use of analogical strategies with the degree of improvement in reasoning largely unrelated to working memory capacity. Findings from this study demonstrate the value of a microgenetic research method and the use of multilevel analysis to examine inter- and intra-individual change in problem-solving processes. Copyright © 2016 Elsevier Inc. All rights reserved.

JWST Wavefront Control Toolbox

NASA Technical Reports Server (NTRS)

Shin, Shahram Ron; Aronstein, David L.

2011-01-01

A Matlab-based toolbox has been developed for the wavefront control and optimization of segmented optical surfaces to correct for possible misalignments of James Webb Space Telescope (JWST) using influence functions. The toolbox employs both iterative and non-iterative methods to converge to an optimal solution by minimizing the cost function. The toolbox could be used in either of constrained and unconstrained optimizations. The control process involves 1 to 7 degrees-of-freedom perturbations per segment of primary mirror in addition to the 5 degrees of freedom of secondary mirror. The toolbox consists of a series of Matlab/Simulink functions and modules, developed based on a "wrapper" approach, that handles the interface and data flow between existing commercial optical modeling software packages such as Zemax and Code V. The limitations of the algorithm are dictated by the constraints of the moving parts in the mirrors.

Data Assimilation on a Quantum Annealing Computer: Feasibility and Scalability

NASA Astrophysics Data System (ADS)

Nearing, G. S.; Halem, M.; Chapman, D. R.; Pelissier, C. S.

2014-12-01

Data assimilation is one of the ubiquitous and computationally hard problems in the Earth Sciences. In particular, ensemble-based methods require a large number of model evaluations to estimate the prior probability density over system states, and variational methods require adjoint calculations and iteration to locate the maximum a posteriori solution in the presence of nonlinear models and observation operators. Quantum annealing computers (QAC) like the new D-Wave housed at the NASA Ames Research Center can be used for optimization and sampling, and therefore offers a new possibility for efficiently solving hard data assimilation problems. Coding on the QAC is not straightforward: a problem must be posed as a Quadratic Unconstrained Binary Optimization (QUBO) and mapped to a spherical Chimera graph. We have developed a method for compiling nonlinear 4D-Var problems on the D-Wave that consists of five steps: Emulating the nonlinear model and/or observation function using radial basis functions (RBF) or Chebyshev polynomials. Truncating a Taylor series around each RBF kernel. Reducing the Taylor polynomial to a quadratic using ancilla gadgets. Mapping the real-valued quadratic to a fixed-precision binary quadratic. Mapping the fully coupled binary quadratic to a partially coupled spherical Chimera graph using ancilla gadgets. At present the D-Wave contains 512 qbits (with 1024 and 2048 qbit machines due in the next two years); this machine size allows us to estimate only 3 state variables at each satellite overpass. However, QAC's solve optimization problems using a physical (quantum) system, and therefore do not require iterations or calculation of model adjoints. This has the potential to revolutionize our ability to efficiently perform variational data assimilation, as the size of these computers grows in the coming years.

Factors Influencing Mathematic Problem-Solving Ability of Sixth Grade Students

ERIC Educational Resources Information Center

Pimta, Sakorn; Tayraukham, Sombat; Nuangchalerm, Prasart

2009-01-01

Problem statement: This study aims to investigate factors influencing mathematic problem-solving ability of sixth grade students. One thousand and twenty eight of sixth grade students, studying in the second semester of academic year 2007 were sampled by stratified random sampling technique. Approach: The research instruments used in the study…

Cognitive Backgrounds of Problem Solving: A Comparison of Open-Ended vs. Closed Mathematics Problems

ERIC Educational Resources Information Center

Bahar, Abdulkadir; Maker, C. June

2015-01-01

Problem solving has been a core theme in education for several decades. Educators and policy makers agree on the importance of the role of problem solving skills for school and real life success. A primary purpose of this study was to investigate the influence of cognitive abilities on mathematical problem solving performance of elementary…

Temperament and Social Problem Solving Competence in Preschool: Influences on Academic Skills in Early Elementary School

ERIC Educational Resources Information Center

Walker, Olga L.; Henderson, Heather A.

2012-01-01

The goals of the current study were to examine whether children's social problem solving (SPS) skills are a mechanism through which temperament influences later academic achievement and whether sex moderates these associations. The participants included 1117 children enrolled in the National Institute of Child Health and Human Development Study of…

Creativity in Unique Problem-Solving in Mathematics and Its Influence on Motivation for Learning

ERIC Educational Resources Information Center

Bishara, Saied

2016-01-01

This research study investigates the ability of students to tackle the solving of unique mathematical problems in the domain of numerical series, verbal and formal, and its influence on the motivation of junior high students with learning disabilities in the Arab sector. Two instruments were used to collect the data: mathematical series were…

Number-unconstrained quantum sensing

NASA Astrophysics Data System (ADS)

Mitchell, Morgan W.

2017-12-01

Quantum sensing is commonly described as a constrained optimization problem: maximize the information gained about an unknown quantity using a limited number of particles. Important sensors including gravitational wave interferometers and some atomic sensors do not appear to fit this description, because there is no external constraint on particle number. Here, we develop the theory of particle-number-unconstrained quantum sensing, and describe how optimal particle numbers emerge from the competition of particle-environment and particle-particle interactions. We apply the theory to optical probing of an atomic medium modeled as a resonant, saturable absorber, and observe the emergence of well-defined finite optima without external constraints. The results contradict some expectations from number-constrained quantum sensing and show that probing with squeezed beams can give a large sensitivity advantage over classical strategies when each is optimized for particle number.

Gaussian Accelerated Molecular Dynamics: Theory, Implementation, and Applications

PubMed Central

Miao, Yinglong; McCammon, J. Andrew

2018-01-01

A novel Gaussian Accelerated Molecular Dynamics (GaMD) method has been developed for simultaneous unconstrained enhanced sampling and free energy calculation of biomolecules. Without the need to set predefined reaction coordinates, GaMD enables unconstrained enhanced sampling of the biomolecules. Furthermore, by constructing a boost potential that follows a Gaussian distribution, accurate reweighting of GaMD simulations is achieved via cumulant expansion to the second order. The free energy profiles obtained from GaMD simulations allow us to identify distinct low energy states of the biomolecules and characterize biomolecular structural dynamics quantitatively. In this chapter, we present the theory of GaMD, its implementation in the widely used molecular dynamics software packages (AMBER and NAMD), and applications to the alanine dipeptide biomolecular model system, protein folding, biomolecular large-scale conformational transitions and biomolecular recognition. PMID:29720925

An expert system for choosing the best combination of options in a general purpose program for automated design synthesis

NASA Technical Reports Server (NTRS)

Rogers, J. L.; Barthelemy, J.-F. M.

1986-01-01

An expert system called EXADS has been developed to aid users of the Automated Design Synthesis (ADS) general purpose optimization program. ADS has approximately 100 combinations of strategy, optimizer, and one-dimensional search options from which to choose. It is difficult for a nonexpert to make this choice. This expert system aids the user in choosing the best combination of options based on the users knowledge of the problem and the expert knowledge stored in the knowledge base. The knowledge base is divided into three categories; constrained problems, unconstrained problems, and constrained problems being treated as unconstrained problems. The inference engine and rules are written in LISP, contains about 200 rules, and executes on DEC-VAX (with Franz-LISP) and IBM PC (with IQ-LISP) computers.

Optimal projection method determination by Logdet Divergence and perturbed von-Neumann Divergence.

PubMed

Jiang, Hao; Ching, Wai-Ki; Qiu, Yushan; Cheng, Xiao-Qing

2017-12-14

Positive semi-definiteness is a critical property in kernel methods for Support Vector Machine (SVM) by which efficient solutions can be guaranteed through convex quadratic programming. However, a lot of similarity functions in applications do not produce positive semi-definite kernels. We propose projection method by constructing projection matrix on indefinite kernels. As a generalization of the spectrum method (denoising method and flipping method), the projection method shows better or comparable performance comparing to the corresponding indefinite kernel methods on a number of real world data sets. Under the Bregman matrix divergence theory, we can find suggested optimal λ in projection method using unconstrained optimization in kernel learning. In this paper we focus on optimal λ determination, in the pursuit of precise optimal λ determination method in unconstrained optimization framework. We developed a perturbed von-Neumann divergence to measure kernel relationships. We compared optimal λ determination with Logdet Divergence and perturbed von-Neumann Divergence, aiming at finding better λ in projection method. Results on a number of real world data sets show that projection method with optimal λ by Logdet divergence demonstrate near optimal performance. And the perturbed von-Neumann Divergence can help determine a relatively better optimal projection method. Projection method ia easy to use for dealing with indefinite kernels. And the parameter embedded in the method can be determined through unconstrained optimization under Bregman matrix divergence theory. This may provide a new way in kernel SVMs for varied objectives.

Long-term Outcome of Unconstrained Primary Total Hip Arthroplasty in Ipsilateral Residual Poliomyelitis.

PubMed

Buttaro, Martín A; Slullitel, Pablo A; García Mansilla, Agustín M; Carlucci, Sofía; Comba, Fernando M; Zanotti, Gerardo; Piccaluga, Francisco

2017-03-01

Incapacitating articular sequelae in the hip joint have been described for patients with late effects of poliomyelitis. In these patients, total hip arthroplasty (THA) has been associated with a substantial rate of dislocation. This study was conducted to evaluate the long-term clinical and radiologic outcomes of unconstrained THA in this specific group of patients. The study included 6 patients with ipsilateral polio who underwent primary THA between 1985 and 2006. Patients with polio who underwent THA on the nonparalytic limb were excluded. Mean follow-up was 119.5 months (minimum, 84 months). Clinical outcomes were evaluated with the modified Harris Hip Score (mHHS) and the visual analog scale (VAS) pain score. Radiographs were examined to identify the cause of complications and determine the need for revision surgery. All patients showed significantly better functional results when preoperative and postoperative mHHS (67.58 vs 87.33, respectively; P=.002) and VAS pain score (7.66 vs 2, respectively; P=.0003) were compared. Although 2 cases of instability were diagnosed, only 1 patient needed acetabular revision as a result of component malpositioning. None of the patients had component loosening, osteolysis, or infection. Unconstrained THA in the affected limb of patients with poliomyelitis showed favorable long-term clinical results, with improved function and pain relief. Nevertheless, instability may be a more frequent complication in this group of patients compared with the general population. [Orthopedics. 2017; 40(2):e255-e261.]. Copyright 2016, SLACK Incorporated.

Ethanol self-administration in serotonin transporter knockout mice: unconstrained demand and elasticity.

PubMed

Lamb, R J; Daws, L C

2013-10-01

Low serotonin function is associated with alcoholism, leading to speculation that increasing serotonin function could decrease ethanol consumption. Mice with one or two deletions of the serotonin transporter (SERT) gene have increased extracellular serotonin. To examine the relationship between SERT genotype and motivation for alcohol, we compared ethanol self-administration in mice with zero (knockout, KO), one (HET) or two copies (WT) of the SERT gene. All three genotypes learned to self-administer ethanol. The SSRI, fluvoxamine, decreased responding for ethanol in the HET and WT, but not the KO mice. When tested under a progressive ratio schedule, KO mice had lower breakpoints than HET or WT. As work requirements were increased across sessions, behavioral economic analysis of ethanol self-administration indicated that the decreased breakpoint in KO as compared to HET or WT mice was a result of lower levels of unconstrained demand, rather than differences in elasticity, i.e. the proportional decreases in ethanol earned with increasing work requirements were similar across genotypes. The difference in unconstrained demand was unlikely to result from motor or general motivational factors, as both WT and KO mice responded at high levels for a 50% condensed milk solution. As elasticity is hypothesized to measure essential value, these results indicate that KO value ethanol similarly to WT or HET mice despite having lower break points for ethanol. © 2013 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

Assessment of patient functional performance in different knee arthroplasty designs during unconstrained squat

PubMed Central

Verdini, Federica; Zara, Claudio; Leo, Tommaso; Mengarelli, Alessandro; Cardarelli, Stefano; Innocenti, Bernardo

2017-01-01

Summary Background In this paper, squat named by Authors unconstrained because performed without constrains related to feet position, speed, knee maximum angle to be reached, was tested as motor task revealing differences in functional performance after knee arthroplasty. It involves large joints ranges of motion, does not compromise joint safety and requires accurate control strategies to maintain balance. Methods Motion capture techniques were used to study squat on a healthy control group (CTR) and on three groups, each characterised by a specific knee arthroplasty design: a Total Knee Arthroplasty (TKA), a Mobile Bearing and a Fixed Bearing Unicompartmental Knee Arthroplasty (respectively MBUA and FBUA). Squat was analysed during descent, maintenance and ascent phase and described by speed, angular kinematics of lower and upper body, the Center of Pressure (CoP) trajectory and muscle activation timing of quadriceps and biceps femoris. Results Compared to CTR, for TKA and MBUA knee maximum flexion was lower, vertical speed during descent and ascent reduced and the duration of whole movement was longer. CoP mean distance was higher for all arthroplasty groups during descent as higher was, CoP mean velocity for MBUA and TKA during ascent and descent. Conclusions Unconstrained squat is able to reveal differences in the functional performance among control and arthroplasty groups and between different arthroplasty designs. Considering the similarity index calculated for the variables showing statistically significance, FBUA performance appears to be closest to that of the CTR group. Level of evidence III a. PMID:29387646

The Influence of Game Design on the Collaborative Problem Solving Process: A Cross-Case Study of Multi-Player Collaborative Gameplay Analysis

ERIC Educational Resources Information Center

Yildirim, Nilay

2013-01-01

This cross-case study examines the relationships between game design attributes and collaborative problem solving process in the context of multi-player video games. The following game design attributes: sensory stimuli elements, level of challenge, and presentation of game goals and rules were examined to determine their influence on game…

The Influence of Self-Efficacy Beliefs and Metacognitive Prompting on Genetics Problem Solving Ability among High School Students in Kenya

ERIC Educational Resources Information Center

Aurah, Catherine Muhonja

2013-01-01

Within the framework of social cognitive theory, the influence of self-efficacy beliefs and metacognitive prompting on genetics problem solving ability among high school students in Kenya was examined through a mixed methods research design. A quasi-experimental study, supplemented by focus group interviews, was conducted to investigate both the…

Schema Knowledge for Solving Arithmetic Story Problems: Some Affective Components.

ERIC Educational Resources Information Center

Marshall, Sandra P.

This report discusses the role of affect in cognitive processing. The importance of affect in processing mathematical information is described in the context of solving arithmetic story problems. Some ideas are offered about the way affective responses to mathematical problem solving situations influence the development, maintenance, and retrieval…

The Influence of English-Korean Bilingualism in Solving Mathematics Word Problems.

ERIC Educational Resources Information Center

Whang, Woo-Hyung

1996-01-01

Purposeful sampling was used to select six English-Korean bilingual students to investigate language difficulties and cognitive processes in solving mathematics word problems. These six case studies revealed distinct patterns of difficulties in solving problems written in English and Korean, especially for students in transition stage. (Author/KMC)

Sea level driven marsh expansion in a coupled model of marsh erosion and migration

USGS Publications Warehouse

Kirwan, Matthew L.; Walters, David C.; Reay, William G.; Carr, Joel

2016-01-01

Coastal wetlands are among the most valuable ecosystems on Earth, where ecosystem services such as flood protection depend nonlinearly on wetland size and are threatened by sea level rise and coastal development. Here we propose a simple model of marsh migration into adjacent uplands and couple it with existing models of seaward edge erosion and vertical soil accretion to explore how ecosystem connectivity influences marsh size and response to sea level rise. We find that marsh loss is nearly inevitable where topographic and anthropogenic barriers limit migration. Where unconstrained by barriers, however, rates of marsh migration are much more sensitive to accelerated sea level rise than rates of edge erosion. This behavior suggests a counterintuitive, natural tendency for marsh expansion with sea level rise and emphasizes the disparity between coastal response to climate change with and without human intervention.

Optimal estimation for discrete time jump processes

NASA Technical Reports Server (NTRS)

Vaca, M. V.; Tretter, S. A.

1977-01-01

Optimum estimates of nonobservable random variables or random processes which influence the rate functions of a discrete time jump process (DTJP) are obtained. The approach is based on the a posteriori probability of a nonobservable event expressed in terms of the a priori probability of that event and of the sample function probability of the DTJP. A general representation for optimum estimates and recursive equations for minimum mean squared error (MMSE) estimates are obtained. MMSE estimates are nonlinear functions of the observations. The problem of estimating the rate of a DTJP when the rate is a random variable with a probability density function of the form cx super K (l-x) super m and show that the MMSE estimates are linear in this case. This class of density functions explains why there are insignificant differences between optimum unconstrained and linear MMSE estimates in a variety of problems.

Optimal estimation for discrete time jump processes

NASA Technical Reports Server (NTRS)

Vaca, M. V.; Tretter, S. A.

1978-01-01

Optimum estimates of nonobservable random variables or random processes which influence the rate functions of a discrete time jump process (DTJP) are derived. The approach used is based on the a posteriori probability of a nonobservable event expressed in terms of the a priori probability of that event and of the sample function probability of the DTJP. Thus a general representation is obtained for optimum estimates, and recursive equations are derived for minimum mean-squared error (MMSE) estimates. In general, MMSE estimates are nonlinear functions of the observations. The problem is considered of estimating the rate of a DTJP when the rate is a random variable with a beta probability density function and the jump amplitudes are binomially distributed. It is shown that the MMSE estimates are linear. The class of beta density functions is rather rich and explains why there are insignificant differences between optimum unconstrained and linear MMSE estimates in a variety of problems.

The eigenstate thermalization hypothesis in constrained Hilbert spaces: A case study in non-Abelian anyon chains

NASA Astrophysics Data System (ADS)

Chandran, A.; Schulz, Marc D.; Burnell, F. J.

2016-12-01

Many phases of matter, including superconductors, fractional quantum Hall fluids, and spin liquids, are described by gauge theories with constrained Hilbert spaces. However, thermalization and the applicability of quantum statistical mechanics has primarily been studied in unconstrained Hilbert spaces. In this paper, we investigate whether constrained Hilbert spaces permit local thermalization. Specifically, we explore whether the eigenstate thermalization hypothesis (ETH) holds in a pinned Fibonacci anyon chain, which serves as a representative case study. We first establish that the constrained Hilbert space admits a notion of locality by showing that the influence of a measurement decays exponentially in space. This suggests that the constraints are no impediment to thermalization. We then provide numerical evidence that ETH holds for the diagonal and off-diagonal matrix elements of various local observables in a generic disorder-free nonintegrable model. We also find that certain nonlocal observables obey ETH.

Functional-anatomic correlates of individual differences in memory.

PubMed

Kirchhoff, Brenda A; Buckner, Randy L

2006-07-20

Memory abilities differ greatly across individuals. To explore a source of these differences, we characterized the varied strategies people adopt during unconstrained encoding. Participants intentionally encoded object pairs during functional MRI. Principal components analysis applied to a strategy questionnaire revealed that participants variably used four main strategies to aid learning. Individuals' use of verbal elaboration and visual inspection strategies independently correlated with their memory performance. Verbal elaboration correlated with activity in a network of regions that included prefrontal regions associated with controlled verbal processing, while visual inspection correlated with activity in a network of regions that included an extrastriate region associated with object processing. Activity in regions associated with use of these strategies was also correlated with memory performance. This study reveals functional-anatomic correlates of verbal and perceptual strategies that are variably used by individuals during encoding. These strategies engage distinct brain regions and may separately influence memory performance.

Diagrams benefit symbolic problem-solving.

PubMed

Chu, Junyi; Rittle-Johnson, Bethany; Fyfe, Emily R

2017-06-01

The format of a mathematics problem often influences students' problem-solving performance. For example, providing diagrams in conjunction with story problems can benefit students' understanding, choice of strategy, and accuracy on story problems. However, it remains unclear whether providing diagrams in conjunction with symbolic equations can benefit problem-solving performance as well. We tested the impact of diagram presence on students' performance on algebra equation problems to determine whether diagrams increase problem-solving success. We also examined the influence of item- and student-level factors to test the robustness of the diagram effect. We worked with 61 seventh-grade students who had received 2 months of pre-algebra instruction. Students participated in an experimenter-led classroom session. Using a within-subjects design, students solved algebra problems in two matched formats (equation and equation-with-diagram). The presence of diagrams increased equation-solving accuracy and the use of informal strategies. This diagram benefit was independent of student ability and item complexity. The benefits of diagrams found previously for story problems generalized to symbolic problems. The findings are consistent with cognitive models of problem-solving and suggest that diagrams may be a useful additional representation of symbolic problems. © 2017 The British Psychological Society.

Meta-Analysis inside and outside Particle Physics: Convergence Using the Path of Least Resistance?

ERIC Educational Resources Information Center

Jackson, Dan; Baker, Rose

2013-01-01

In this note, we explain how the method proposed by Hartung and Knapp provides a compromise between conventional meta-analysis methodology and "unconstrained averaging", as used by the Particle Data Group.

The cost of noise reduction in commercial tilt rotor aircraft

NASA Technical Reports Server (NTRS)

Faulkner, H. B.

1974-01-01

The relationship between direct operating cost (DOC) and departure noise annoyance was developed for commercial tilt rotor aircraft. This was accomplished by generating a series of tilt rotor aircraft designs to meet various noise goals at minimum DOC. These vehicles were spaced across the spectrum of possible noise levels from completely unconstrained to the quietest vehicle that could be designed within the study ground rules. A group of optimization parameters were varied to find the minimum DOC while other inputs were held constant and some external constraints were met. This basic variation was then extended to different aircraft sizes and technology time frames. It was concluded that reducing noise annoyance by designing for lower rotor tip speeds is a very promising avenue for future research and development. It appears that the cost of halving the annoyance compared to an unconstrained design is insignificant and the cost of halving the annoyance again is small.

A wearable computing platform for developing cloud-based machine learning models for health monitoring applications.

PubMed

Patel, Shyamal; McGinnis, Ryan S; Silva, Ikaro; DiCristofaro, Steve; Mahadevan, Nikhil; Jortberg, Elise; Franco, Jaime; Martin, Albert; Lust, Joseph; Raj, Milan; McGrane, Bryan; DePetrillo, Paolo; Aranyosi, A J; Ceruolo, Melissa; Pindado, Jesus; Ghaffari, Roozbeh

2016-08-01

Wearable sensors have the potential to enable clinical-grade ambulatory health monitoring outside the clinic. Technological advances have enabled development of devices that can measure vital signs with great precision and significant progress has been made towards extracting clinically meaningful information from these devices in research studies. However, translating measurement accuracies achieved in the controlled settings such as the lab and clinic to unconstrained environments such as the home remains a challenge. In this paper, we present a novel wearable computing platform for unobtrusive collection of labeled datasets and a new paradigm for continuous development, deployment and evaluation of machine learning models to ensure robust model performance as we transition from the lab to home. Using this system, we train activity classification models across two studies and track changes in model performance as we go from constrained to unconstrained settings.

Unconstrained tripolar implants for primary total hip arthroplasty in patients at risk for dislocation.

PubMed

Guyen, Olivier; Pibarot, Vincent; Vaz, Gualter; Chevillotte, Christophe; Carret, Jean-Paul; Bejui-Hugues, Jacques

2007-09-01

We performed a retrospective study on 167 primary total hip arthroplasty (THA) procedures in 163 patients at high risk for instability to assess the reliability of unconstrained tripolar implants (press-fit outer metal shell articulating a bipolar polyethylene component) in preventing dislocations. Eighty-four percent of the patients had at least 2 risk factors for dislocation. The mean follow-up length was 40.2 months. No dislocation was observed. Harris hip scores improved significantly. Six hips were revised, and no aseptic loosening of the cup was observed. The tripolar implant was extremely successful in achieving stability. However, because of the current lack of data documenting polyethylene wear at additional bearing, the routine use of tripolar implants in primary THA is discouraged and should be considered at the present time only for selected patients at high risk for dislocation and with limited activities.

Direct brain recordings reveal hippocampal rhythm underpinnings of language processing.

PubMed

Piai, Vitória; Anderson, Kristopher L; Lin, Jack J; Dewar, Callum; Parvizi, Josef; Dronkers, Nina F; Knight, Robert T

2016-10-04

Language is classically thought to be supported by perisylvian cortical regions. Here we provide intracranial evidence linking the hippocampal complex to linguistic processing. We used direct recordings from the hippocampal structures to investigate whether theta oscillations, pivotal in memory function, track the amount of contextual linguistic information provided in sentences. Twelve participants heard sentences that were either constrained ("She locked the door with the") or unconstrained ("She walked in here with the") before presentation of the final word ("key"), shown as a picture that participants had to name. Hippocampal theta power increased for constrained relative to unconstrained contexts during sentence processing, preceding picture presentation. Our study implicates hippocampal theta oscillations in a language task using natural language associations that do not require memorization. These findings reveal that the hippocampal complex contributes to language in an active fashion, relating incoming words to stored semantic knowledge, a necessary process in the generation of sentence meaning.

Beyond the group mind: a quantitative review of the interindividual-intergroup discontinuity effect.

PubMed

Wildschut, Tim; Pinter, Brad; Vevea, Jack L; Insko, Chester A; Schopler, John

2003-09-01

This quantitative review of 130 comparisons of interindividual and intergroup interactions in the context of mixed-motive situations reveals that intergroup interactions are generally more competitive than interindividual interactions. The authors identify 4 moderators of this interindividual-intergroup discontinuity effect, each based on the theoretical perspective that the discontinuity effect flows from greater fear and greed in intergroup relative to interindividual interactions. Results reveal that each moderator shares a unique association with the magnitude of the discontinuity effect. The discontinuity effect is larger when (a) participants interact with an opponent whose behavior is unconstrained by the experimenter or constrained by the experimenter to be cooperative rather than constrained by the experimenter to be reciprocal, (b) group members make a group decision rather than individual decisions, (c) unconstrained communication between participants is present rather than absent, and (d) conflict of interest is severe rather than mild.

Single Crystals Grown Under Unconstrained Conditions

NASA Astrophysics Data System (ADS)

Sunagawa, Ichiro

Based on detailed investigations on morphology (evolution and variation in external forms), surface microtopography of crystal faces (spirals and etch figures), internal morphology (growth sectors, growth banding and associated impurity partitioning) and perfection (dislocations and other lattice defects) in single crystals, we can deduce how and by what mechanism the crystal grew and experienced fluctuation in growth parameters through its growth and post-growth history under unconstrained condition. The information is useful not only in finding appropriate way to growing highly perfect and homogeneous single crystals, but also in deciphering letters sent from the depth of the Earth and the Space. It is also useful in discriminating synthetic from natural gemstones. In this chapter, available methods to obtain molecular information are briefly summarized, and actual examples to demonstrate the importance of this type of investigations are selected from both natural minerals (diamond, quartz, hematite, corundum, beryl, phlogopite) and synthetic crystals (SiC, diamond, corundum, beryl).

Practical global oceanic state estimation

NASA Astrophysics Data System (ADS)

Wunsch, Carl; Heimbach, Patrick

2007-06-01

The problem of oceanographic state estimation, by means of an ocean general circulation model (GCM) and a multitude of observations, is described and contrasted with the meteorological process of data assimilation. In practice, all such methods reduce, on the computer, to forms of least-squares. The global oceanographic problem is at the present time focussed primarily on smoothing, rather than forecasting, and the data types are unlike meteorological ones. As formulated in the consortium Estimating the Circulation and Climate of the Ocean (ECCO), an automatic differentiation tool is used to calculate the so-called adjoint code of the GCM, and the method of Lagrange multipliers used to render the problem one of unconstrained least-squares minimization. Major problems today lie less with the numerical algorithms (least-squares problems can be solved by many means) than with the issues of data and model error. Results of ongoing calculations covering the period of the World Ocean Circulation Experiment, and including among other data, satellite altimetry from TOPEX/POSEIDON, Jason-1, ERS- 1/2, ENVISAT, and GFO, a global array of profiling floats from the Argo program, and satellite gravity data from the GRACE mission, suggest that the solutions are now useful for scientific purposes. Both methodology and applications are developing in a number of different directions.

Quadratic constrained mixed discrete optimization with an adiabatic quantum optimizer

NASA Astrophysics Data System (ADS)

Chandra, Rishabh; Jacobson, N. Tobias; Moussa, Jonathan E.; Frankel, Steven H.; Kais, Sabre

2014-07-01

We extend the family of problems that may be implemented on an adiabatic quantum optimizer (AQO). When a quadratic optimization problem has at least one set of discrete controls and the constraints are linear, we call this a quadratic constrained mixed discrete optimization (QCMDO) problem. QCMDO problems are NP-hard, and no efficient classical algorithm for their solution is known. Included in the class of QCMDO problems are combinatorial optimization problems constrained by a linear partial differential equation (PDE) or system of linear PDEs. An essential complication commonly encountered in solving this type of problem is that the linear constraint may introduce many intermediate continuous variables into the optimization while the computational cost grows exponentially with problem size. We resolve this difficulty by developing a constructive mapping from QCMDO to quadratic unconstrained binary optimization (QUBO) such that the size of the QUBO problem depends only on the number of discrete control variables. With a suitable embedding, taking into account the physical constraints of the realizable coupling graph, the resulting QUBO problem can be implemented on an existing AQO. The mapping itself is efficient, scaling cubically with the number of continuous variables in the general case and linearly in the PDE case if an efficient preconditioner is available.

Algorithms for accelerated convergence of adaptive PCA.

PubMed

Chatterjee, C; Kang, Z; Roychowdhury, V P

2000-01-01

We derive and discuss new adaptive algorithms for principal component analysis (PCA) that are shown to converge faster than the traditional PCA algorithms due to Oja, Sanger, and Xu. It is well known that traditional PCA algorithms that are derived by using gradient descent on an objective function are slow to converge. Furthermore, the convergence of these algorithms depends on appropriate choices of the gain sequences. Since online applications demand faster convergence and an automatic selection of gains, we present new adaptive algorithms to solve these problems. We first present an unconstrained objective function, which can be minimized to obtain the principal components. We derive adaptive algorithms from this objective function by using: 1) gradient descent; 2) steepest descent; 3) conjugate direction; and 4) Newton-Raphson methods. Although gradient descent produces Xu's LMSER algorithm, the steepest descent, conjugate direction, and Newton-Raphson methods produce new adaptive algorithms for PCA. We also provide a discussion on the landscape of the objective function, and present a global convergence proof of the adaptive gradient descent PCA algorithm using stochastic approximation theory. Extensive experiments with stationary and nonstationary multidimensional Gaussian sequences show faster convergence of the new algorithms over the traditional gradient descent methods.We also compare the steepest descent adaptive algorithm with state-of-the-art methods on stationary and nonstationary sequences.

Teachers Beliefs in Problem Solving in Rural Malaysian Secondary Schools

ERIC Educational Resources Information Center

Palraj, Shalini; DeWitt, Dorothy; Alias, Norlidah

2017-01-01

Problem solving is the highest level of cognitive skill. However, this skill seems to be lacking among secondary school students. Teachers' beliefs influence the instructional strategies used for students' learning. Hence, it is important to understand teachers' beliefs so as to improve the processes for teaching problem solving. The purpose of…

Assessing Leadership and Problem-Solving Skills and Their Impacts in the Community.

ERIC Educational Resources Information Center

Rohs, F. Richard; Langone, Christine A.

1993-01-01

A pretest-posttest control group design was used to assess the leadership and problem-solving skills of 281 participants and 110 controls in a statewide community leadership development program. Quantitative and qualitative data demonstrate that the program has been a catalyst to influence leadership and problem-solving skills for community…

Students Problem-Solving Difficulties and Implications in Physics: An Empirical Study on Influencing Factors

ERIC Educational Resources Information Center

Reddy, M. Vijaya Bhaskara; Panacharoensawad, Buncha

2017-01-01

In twenty first century, abundant innovative tools have been identified by the researchers to evaluate the conceptual understandings, problem solving, beliefs and attitudes about physics. Nevertheless, lacking of wide variety of evaluation instruments with respect to problem solving in physics. It indicates that the complexity of the domain fields…

Effect of the mandible on mouthguard measurements of head kinematics.

PubMed

Kuo, Calvin; Wu, Lyndia C; Hammoor, Brad T; Luck, Jason F; Cutcliffe, Hattie C; Lynall, Robert C; Kait, Jason R; Campbell, Kody R; Mihalik, Jason P; Bass, Cameron R; Camarillo, David B

2016-06-14

Wearable sensors are becoming increasingly popular for measuring head motions and detecting head impacts. Many sensors are worn on the skin or in headgear and can suffer from motion artifacts introduced by the compliance of soft tissue or decoupling of headgear from the skull. The instrumented mouthguard is designed to couple directly to the upper dentition, which is made of hard enamel and anchored in a bony socket by stiff ligaments. This gives the mouthguard superior coupling to the skull compared with other systems. However, multiple validation studies have yielded conflicting results with respect to the mouthguard׳s head kinematics measurement accuracy. Here, we demonstrate that imposing different constraints on the mandible (lower jaw) can alter mouthguard kinematic accuracy in dummy headform testing. In addition, post mortem human surrogate tests utilizing the worst-case unconstrained mandible condition yield 40% and 80% normalized root mean square error in angular velocity and angular acceleration respectively. These errors can be modeled using a simple spring-mass system in which the soft mouthguard material near the sensors acts as a spring and the mandible as a mass. However, the mouthguard can be designed to mitigate these disturbances by isolating sensors from mandible loads, improving accuracy to below 15% normalized root mean square error in all kinematic measures. Thus, while current mouthguards would suffer from measurement errors in the worst-case unconstrained mandible condition, future mouthguards should be designed to account for these disturbances and future validation testing should include unconstrained mandibles to ensure proper accuracy. Copyright © 2016 Elsevier Ltd. All rights reserved.

Oxygen Desaturation Index Estimation through Unconstrained Cardiac Sympathetic Activity Assessment Using Three Ballistocardiographic Systems.

PubMed

Jung, Da Woon; Hwang, Su Hwan; Lee, Yu Jin; Jeong, Do-Un; Park, Kwang Suk

2016-01-01

Nocturnal hypoxemia, characterized by abnormally low oxygen saturation levels in arterial blood during sleep, is a significant feature of various pathological conditions. The oxygen desaturation index, commonly used to evaluate the nocturnal hypoxemia severity, is acquired using nocturnal pulse oximetry that requires the overnight wear of a pulse oximeter probe. This study aimed to suggest a method for the unconstrained estimation of the oxygen desaturation index. We hypothesized that the severity of nocturnal hypoxemia would be positively associated with cardiac sympathetic activation during sleep. Unconstrained heart rate variability monitoring was conducted using three different ballistocardiographic systems to assess cardiac sympathetic activity. Overnight polysomnographic and ballistocardiographic recording pairs were collected from the 20 non-nocturnal hypoxemia (oxygen desaturation index <5 events/h) subjects and the 76 nocturnal hypoxemia patients. Among the 96 recording pairs, 48 were used as training data and the remaining 48 as test data. The regression analysis, performed using the low-frequency component of heart rate variability, exhibited a root mean square error of 3.33 events/h between the estimates and the reference values of the oxygen desaturation index. The nocturnal hypoxemia diagnostic performance produced by our method was presented with an average accuracy of 96.5% at oxygen desaturation index cutoffs of ≥5, 15, and 30 events/h. Our method has the potential to serve as a complementary measure against the accidental slip-out of a pulse oximeter probe during nocturnal pulse oximetry. The independent application of our method could facilitate home-based long-term oxygen desaturation index monitoring. © 2016 S. Karger AG, Basel.

An apparent contradiction: increasing variability to achieve greater precision?

PubMed

Rosenblatt, Noah J; Hurt, Christopher P; Latash, Mark L; Grabiner, Mark D

2014-02-01

To understand the relationship between variability of foot placement in the frontal plane and stability of gait patterns, we explored how constraining mediolateral foot placement during walking affects the structure of kinematic variance in the lower-limb configuration space during the swing phase of gait. Ten young subjects walked under three conditions: (1) unconstrained (normal walking), (2) constrained (walking overground with visual guides for foot placement to achieve the measured unconstrained step width) and, (3) beam (walking on elevated beams spaced to achieve the measured unconstrained step width). The uncontrolled manifold analysis of the joint configuration variance was used to quantify two variance components, one that did not affect the mediolateral trajectory of the foot in the frontal plane ("good variance") and one that affected this trajectory ("bad variance"). Based on recent studies, we hypothesized that across conditions (1) the index of the synergy stabilizing the mediolateral trajectory of the foot (the normalized difference between the "good variance" and "bad variance") would systematically increase and (2) the changes in the synergy index would be associated with a disproportionate increase in the "good variance." Both hypotheses were confirmed. We conclude that an increase in the "good variance" component of the joint configuration variance may be an effective method of ensuring high stability of gait patterns during conditions requiring increased control of foot placement, particularly if a postural threat is present. Ultimately, designing interventions that encourage a larger amount of "good variance" may be a promising method of improving stability of gait patterns in populations such as older adults and neurological patients.

Gender influences on preschool children's social problem-solving strategies.

PubMed

Walker, Sue; Irving, Kym; Berthelsen, Donna

2002-06-01

The authors investigated gender influences on the nature and competency of preschool children's social problem-solving strategies. Preschool-age children (N = 179; 91 boys, 88 girls) responded to hypothetical social situations designed to assess their social problem-solving skills in the areas of provocation, peer group entry, and sharing or taking turns. Results indicated that, overall, girls' responses were more competent (i.e., reflective of successful functioning with peers) than those of boys, and girls' strategies were less likely to involve retaliation or verbal or physical aggression. The competency of the children's responses also varied with the gender of the target child. Findings are discussed in terms of the influence of gender-related social experiences on the types of strategies and behaviors that may be viewed as competent for boys and girls of preschool age.

In Praise of Ignorance

ERIC Educational Resources Information Center

Formica, Piero

2014-01-01

In this article Piero Formica examines the difference between incremental and revolutionary innovation, distinguishing between the constrained "path finders" and the unconstrained "path creators". He argues that an acceptance of "ignorance" and a willingness to venture into the unknown are critical elements in…

A proportional control scheme for high density force myography.

PubMed

Belyea, Alexander T; Englehart, Kevin B; Scheme, Erik J

2018-08-01

Force myography (FMG) has been shown to be a potentially higher accuracy alternative to electromyography for pattern recognition based prosthetic control. Classification accuracy, however, is just one factor that affects the usability of a control system. Others, like the ability to start and stop, to coordinate dynamic movements, and to control the velocity of the device through some proportional control scheme can be of equal importance. To impart effective fine control using FMG-based pattern recognition, it is important that a method of controlling the velocity of each motion be developed. In this work force myography data were collected from 14 able bodied participants and one amputee participant as they performed a set of wrist and hand motions. The offline proportional control performance of a standard mean signal amplitude approach and a proposed regression-based alternative was compared. The impact of providing feedback during training, as well as the use of constrained or unconstrained hand and wrist contractions, were also evaluated. It is shown that the commonly used mean of rectified channel amplitudes approach commonly employed with electromyography does not translate to force myography. The proposed class-based regression proportional control approach is shown significantly outperform this standard approach (ρ  <  0.001), yielding a R 2 correlation coefficients of 0.837 and 0.830 for constrained and unconstrained forearm contractions, respectively for able bodied participants. No significant difference (ρ  =  0.693) was found in R 2 performance when feedback was provided during training or not. The amputee subject achieved a classification accuracy of 83.4%  ±  3.47% demonstrating the ability to distinguish contractions well with FMG. In proportional control the amputee participant achieved an R 2 of of 0.375 for regression based proportional control during unconstrained contractions. This is lower than the unconstrained case for able-bodied subjects for this particular amputee, possibly due to difficultly in visualizing contraction level modulation without feedback. This may be remedied in the use of a prosthetic limb that would provide real-time feedback in the form of device speed. A novel class-specific regression-based approach is proposed for multi-class control is described and shown to provide an effective means of providing FMG-based proportional control.

Metaphor and analogy in everyday problem solving.

PubMed

Keefer, Lucas A; Landau, Mark J

2016-11-01

Early accounts of problem solving focused on the ways people represent information directly related to target problems and possible solutions. Subsequent theory and research point to the role of peripheral influences such as heuristics and bodily states. We discuss how metaphor and analogy similarly influence stages of everyday problem solving: Both processes mentally map features of a target problem onto the structure of a relatively more familiar concept. When individuals apply this structure, they use a well-known concept as a framework for reasoning about real world problems and candidate solutions. Early studies found that analogy use helped people gain insight into novel problems. More recent research on metaphor goes further to show that activating mappings has subtle, sometimes surprising effects on judgment and reasoning in everyday problem solving. These findings highlight situations in which mappings can help or hinder efforts to solve problems. WIREs Cogn Sci 2016, 7:394-405. doi: 10.1002/wcs.1407 For further resources related to this article, please visit the WIREs website. © 2016 Wiley Periodicals, Inc.

Understanding the determinants of problem-solving behavior in a complex environment

NASA Technical Reports Server (NTRS)

Casner, Stephen A.

1994-01-01

It is often argued that problem-solving behavior in a complex environment is determined as much by the features of the environment as by the goals of the problem solver. This article explores a technique to determine the extent to which measured features of a complex environment influence problem-solving behavior observed within that environment. In this study, the technique is used to determine how complex flight deck and air traffic control environment influences the strategies used by airline pilots when controlling the flight path of a modern jetliner. Data collected aboard 16 commercial flights are used to measure selected features of the task environment. A record of the pilots' problem-solving behavior is analyzed to determine to what extent behavior is adapted to the environmental features that were measured. The results suggest that the measured features of the environment account for as much as half of the variability in the pilots' problem-solving behavior and provide estimates on the probable effects of each environmental feature.

The Influence of Different Representations on Solving Concentration Problems at Elementary School

NASA Astrophysics Data System (ADS)

Liu, Chia-Ju; Shen, Ming-Hsun

2011-10-01

This study investigated the students' learning process of the concept of concentration at the elementary school level in Taiwan. The influence of different representational types on the process of proportional reasoning was also explored. The participants included nineteen third-grade and eighteen fifth-grade students. Eye-tracking technology was used in conducting the experiment. The materials were adapted from Noelting's (1980a) "orange juice test" experiment. All problems on concentration included three stages (the intuitive, the concrete operational, and the formal operational), and each problem was displayed in iconic and symbolic representations. The data were collected through eye-tracking technology and post-test interviews. The results showed that the representational types influenced students' solving of concentration problems. Furthermore, the data on eye movement indicated that students used different strategies or rules to solve concentration problems at the different stages of the problems with different representational types. This study is intended to contribute to the understanding of elementary school students' problem-solving strategies and the usability of eye-tracking technology in related studies.

Performance in Mathematical Problem Solving as a Function of Comprehension and Arithmetic Skills

ERIC Educational Resources Information Center

Voyer, Dominic

2011-01-01

Many factors influence a student's performance in word (or textbook) problem solving in class. Among them is the comprehension process the pupils construct during their attempt to solve the problem. The comprehension process may include some less formal representations, based on pupils' real-world knowledge, which support the construction of a…

Perception and Selection of Information Sources by Undergraduate Students: Effects of Avoidant Style, Confidence, and Personal Control in Problem-Solving

ERIC Educational Resources Information Center

Kim, Kyung-Sun; Sin, Sei-Ching Joanna

2007-01-01

A survey of undergraduate students examined how students' beliefs about their problem-solving styles and abilities (including avoidant style, confidence, and personal control in problem-solving) influenced their perception and selection of sources, as reflected in (1) perceived characteristics of sources, (2) source characteristics considered…

Three-and-a-half-factor model? The genetic and environmental structure of the CBCL/6-18 internalizing grouping.

PubMed

Franić, Sanja; Dolan, Conor V; Borsboom, Denny; van Beijsterveldt, Catherina E M; Boomsma, Dorret I

2014-05-01

In the present article, multivariate genetic item analyses were employed to address questions regarding the ontology and the genetic and environmental etiology of the Anxious/Depressed, Withdrawn, and Somatic Complaints syndrome dimensions of the Internalizing grouping of the Child Behavior Checklist/6-18 (CBCL/6-18). Using common and independent pathway genetic factor modeling, it was examined whether these syndrome dimensions can be ascribed a realist ontology. Subsequently, the structures of the genetic and environmental influences giving rise to the observed symptom covariation were examined. Maternal ratings of a population-based sample of 17,511 Dutch twins of mean age 7.4 (SD = 0.4) on the items of the Internalizing grouping of the Dutch CBCL/6-18 were analyzed. Applications of common and independent pathway modeling demonstrated that the Internalizing syndrome dimensions may be better understood as a composite of unconstrained genetic and environmental influences than as causally relevant entities generating the observed symptom covariation. Furthermore, the results indicate a common genetic basis for anxiety, depression, and withdrawn behavior, with the distinction between these syndromes being driven by the individual-specific environment. Implications for the substantive interpretation of these syndrome dimensions are discussed.

THE INFLUENCE OF LEXICAL FACTORS ON VOWEL DISTINCTIVENESS: EFFECTS OF JAW POSITIONING.

PubMed

Munson, Benjamin; Solomon, Nancy Pearl

2016-11-01

The phonetic characteristics of words are influenced by lexical characteristics, including word frequency and phonological neighborhood density (Baese-Berke & Goldrick, 2009; Wright, 2004). In our previous research, we replicated this effect with neurologically healthy young adults (Munson & Solomon, 2004). In research with the same set of participants, we showed that speech sounded less natural when produced with bite blocks than with an unconstrained jaw (Solomon, Makashay, & Munson, 2016). The current study combined these concepts to examine whether a bite-block perturbation exaggerated or reduced the effects of lexical factors on normal speech. Ten young adults produced more challenging lexical stimuli (i.e. infrequent words with many phonological neighbors) with shorter vowels and more disperse F1/F2 spaces than less challenging words (i.e. frequent words with few phonological neighbors). This difference was exaggerated when speaking with a 10-mm bite block, though the interaction between jaw positioning and lexical competition did not achieve statistical significance. Results indicate that talkers alter vowel characteristics in response both to biomechanical and linguistic demands, and that the effect of lexical characteristics is robust to the articulatory reorganization required for successful bite-block compensation.

Problem-solving skills and perceived stress among undergraduate students: The moderating role of hardiness.

PubMed

Abdollahi, Abbas; Abu Talib, Mansor; Carlbring, Per; Harvey, Richard; Yaacob, Siti Nor; Ismail, Zanariah

2016-06-01

This study was designed to examine the relationships between problem-solving skills, hardiness, and perceived stress and to test the moderating role of hardiness in the relationship between problem-solving skills and perceived stress among 500 undergraduates from Malaysian public universities. The analyses showed that undergraduates with poor problem-solving confidence, external personal control of emotion, and approach-avoidance style were more likely to report perceived stress. Hardiness moderated the relationships between problem-solving skills and perceived stress. These findings reinforce the importance of moderating role of hardiness as an influencing factor that explains how problem-solving skills affect perceived stress among undergraduates.

Factors Influencing Problem-Solving in Middle-Aged and Elderly Adults

ERIC Educational Resources Information Center

Kesler, Mary S.; And Others

1976-01-01

Groups of middle-aged and elderly men and women were compared on three problem solving tasks, including written problems, the 20-questions procedure, and problems administered on a Heuristic Evaluation Problem Programmer. (MS)

Characteristics of Handwriting of People With Cerebellar Ataxia: Three-Dimensional Movement Analysis of the Pen Tip, Finger, and Wrist.

PubMed

Fujisawa, Yuhki; Okajima, Yasutomo

2015-11-01

There are several functional tests for evaluating manual performance; however, quantitative manual tests for ataxia, especially those for evaluating handwriting, are limited. This study aimed to investigate the characteristics of cerebellar ataxia by analyzing handwriting, with a special emphasis on correlation between the movement of the pen tip and the movement of the finger or wrist. This was an observational study. Eleven people who were right-handed and had cerebellar ataxia and 17 people to serve as controls were recruited. The Scale for the Assessment and Rating of Ataxia was used to grade the severity of ataxia. Handwriting movements of both hands were analyzed. The time required for writing a character, the variability of individual handwriting, and the correlation between the movement of the pen tip and the movement of the finger or wrist were evaluated for participants with ataxia and control participants. The writing time was longer and the velocity profile and shape of the track of movement of the pen tip were more variable in participants with ataxia than in control participants. For participants with ataxia, the direction of movement of the pen tip deviated more from that of the finger or wrist, and the shape of the track of movement of the pen tip differed more from that of the finger or wrist. The severity of upper extremity ataxia measured with the Scale for the Assessment and Rating of Ataxia was mostly correlated with the variability parameters. Furthermore, it was correlated with the directional deviation of the trajectory of movement of the pen tip from that of the finger and with increased dissimilarity of the shapes of the tracks. The results may have been influenced by the scale and parameters used to measure movement. Ataxic handwriting with increased movement noise is characterized by irregular pen tip movements unconstrained by the finger or wrist. The severity of ataxia is correlated with these unconstrained movements. © 2015 American Physical Therapy Association.

Influence of Wiring Cost on the Large-Scale Architecture of Human Cortical Connectivity

PubMed Central

Samu, David; Seth, Anil K.; Nowotny, Thomas

2014-01-01

In the past two decades some fundamental properties of cortical connectivity have been discovered: small-world structure, pronounced hierarchical and modular organisation, and strong core and rich-club structures. A common assumption when interpreting results of this kind is that the observed structural properties are present to enable the brain's function. However, the brain is also embedded into the limited space of the skull and its wiring has associated developmental and metabolic costs. These basic physical and economic aspects place separate, often conflicting, constraints on the brain's connectivity, which must be characterized in order to understand the true relationship between brain structure and function. To address this challenge, here we ask which, and to what extent, aspects of the structural organisation of the brain are conserved if we preserve specific spatial and topological properties of the brain but otherwise randomise its connectivity. We perform a comparative analysis of a connectivity map of the cortical connectome both on high- and low-resolutions utilising three different types of surrogate networks: spatially unconstrained (‘random’), connection length preserving (‘spatial’), and connection length optimised (‘reduced’) surrogates. We find that unconstrained randomisation markedly diminishes all investigated architectural properties of cortical connectivity. By contrast, spatial and reduced surrogates largely preserve most properties and, interestingly, often more so in the reduced surrogates. Specifically, our results suggest that the cortical network is less tightly integrated than its spatial constraints would allow, but more strongly segregated than its spatial constraints would necessitate. We additionally find that hierarchical organisation and rich-club structure of the cortical connectivity are largely preserved in spatial and reduced surrogates and hence may be partially attributable to cortical wiring constraints. In contrast, the high modularity and strong s-core of the high-resolution cortical network are significantly stronger than in the surrogates, underlining their potential functional relevance in the brain. PMID:24699277

The influence of open goals on the acquisition of problem-relevant information.

PubMed

Moss, Jarrod; Kotovsky, Kenneth; Cagan, Jonathan

2007-09-01

There have been a number of recent findings indicating that unsolved problems, or open goals more generally, influence cognition even when the current task has no relation to the task in which the goal was originally set. It was hypothesized that open goals would influence what information entered the problem-solving process. Three studies were conducted to establish the effect of open goals on the acquisition of problem-relevant information. It was found that problem-relevant information, or hints, presented implicitly in a 2nd task in between attempts at solving problems aided problem solving. This effect cannot be attributed to strategic behavior after participants caught on to the manipulation, as most participants were not aware of the relationship. The implications of this research are discussed, including potential contributions to our understanding of insight, incubation, transfer, and creativity. 2007 APA

Technology Confidence, Competence and Problem Solving Strategies: Differences within Online and Face-to-Face Formats

ERIC Educational Resources Information Center

Peterson, Sharon L.; Palmer, Louann Bierlein

2011-01-01

This study identified the problem solving strategies used by students within a university course designed to teach pre-service teachers educational technology, and whether those strategies were influenced by the format of the course (i.e., face-to-face computer lab vs. online). It also examined to what extent the type of problem solving strategies…

Pupils' Visual Representations in Standard and Problematic Problem Solving in Mathematics: Their Role in the Breach of the Didactical Contract

ERIC Educational Resources Information Center

Deliyianni, Eleni; Monoyiou, Annita; Elia, Iliada; Georgiou, Chryso; Zannettou, Eleni

2009-01-01

This study investigated the modes of representations generated by kindergarteners and first graders while solving standard and problematic problems in mathematics. Furthermore, it examined the influence of pupils' visual representations on the breach of the didactical contract rules in problem solving. The sample of the study consisted of 38…

Others' Anger Makes People Work Harder Not Smarter: The Effect of Observing Anger and Sarcasm on Creative and Analytic Thinking

ERIC Educational Resources Information Center

Miron-Spektor, Ella; Efrat-Treister, Dorit; Rafaeli, Anat; Schwarz-Cohen, Orit

2011-01-01

The authors examine whether and how observing anger influences thinking processes and problem-solving ability. In 3 studies, the authors show that participants who listened to an angry customer were more successful in solving analytic problems, but less successful in solving creative problems compared with participants who listened to an…

Will farmers save water? A theoretical analysis of groundwater conservation policies

USDA-ARS?s Scientific Manuscript database

The development of agricultural irrigation systems has generated significant increases in food production and farm income. However, unplanned and unconstrained groundwater use could also cause serious consequences. To extend the economic life of groundwater, water conservation issues have become the...

Defending Collegiality

ERIC Educational Resources Information Center

Fischer, Michael

2009-01-01

In his provocatively titled recent book, "The No Asshole Rule: Building a Civilized Workplace and Surviving One That Isn't", Robert I. Sutton argues for zero tolerance of "bullies, creeps, jerks, weasels, tormentors, tyrants, serial slammers, despots, [and] unconstrained egomaniacs" in the workplace. These individuals systematically prey on their…

Pre-trained D-CNN models for detecting complex events in unconstrained videos

NASA Astrophysics Data System (ADS)

Robinson, Joseph P.; Fu, Yun

2016-05-01

Rapid event detection faces an emergent need to process large videos collections; whether surveillance videos or unconstrained web videos, the ability to automatically recognize high-level, complex events is a challenging task. Motivated by pre-existing methods being complex, computationally demanding, and often non-replicable, we designed a simple system that is quick, effective and carries minimal overhead in terms of memory and storage. Our system is clearly described, modular in nature, replicable on any Desktop, and demonstrated with extensive experiments, backed by insightful analysis on different Convolutional Neural Networks (CNNs), as stand-alone and fused with others. With a large corpus of unconstrained, real-world video data, we examine the usefulness of different CNN models as features extractors for modeling high-level events, i.e., pre-trained CNNs that differ in architectures, training data, and number of outputs. For each CNN, we use 1-fps from all training exemplar to train one-vs-rest SVMs for each event. To represent videos, frame-level features were fused using a variety of techniques. The best being to max-pool between predetermined shot boundaries, then average-pool to form the final video-level descriptor. Through extensive analysis, several insights were found on using pre-trained CNNs as off-the-shelf feature extractors for the task of event detection. Fusing SVMs of different CNNs revealed some interesting facts, finding some combinations to be complimentary. It was concluded that no single CNN works best for all events, as some events are more object-driven while others are more scene-based. Our top performance resulted from learning event-dependent weights for different CNNs.

Reliability of the Achilles tendon tap reflex evoked during stance using a pendulum hammer.

PubMed

Mildren, Robyn L; Zaback, Martin; Adkin, Allan L; Frank, James S; Bent, Leah R

2016-01-01

The tendon tap reflex (T-reflex) is often evoked in relaxed muscles to assess spinal reflex circuitry. Factors contributing to reflex excitability are modulated to accommodate specific postural demands. Thus, there is a need to be able to assess this reflex in a state where spinal reflex circuitry is engaged in maintaining posture. The aim of this study was to determine whether a pendulum hammer could provide controlled stimuli to the Achilles tendon and evoke reliable muscle responses during normal stance. A second aim was to establish appropriate stimulus parameters for experimental use. Fifteen healthy young adults stood on a forceplate while taps were applied to the Achilles tendon under conditions in which postural sway was constrained (by providing centre of pressure feedback) or unconstrained (no feedback) from an invariant release angle (50°). Twelve participants repeated this testing approximately six months later. Within one experimental session, tap force and T-reflex amplitude were found to be reliable regardless of whether postural sway was constrained (tap force ICC=0.982; T-reflex ICC=0.979) or unconstrained (tap force ICC=0.968; T-reflex ICC=0.964). T-reflex amplitude was also reliable between experimental sessions (constrained ICC=0.894; unconstrained ICC=0.890). When a T-reflex recruitment curve was constructed, optimal mid-range responses were observed using a 50° release angle. These results demonstrate that reliable Achilles T-reflexes can be evoked in standing participants without the need to constrain posture. The pendulum hammer provides a simple method to allow researchers and clinicians to gather information about reflex circuitry in a state where it is involved in postural control. Copyright © 2015 Elsevier B.V. All rights reserved.

Patterns of thought: Population variation in the associations between large-scale network organisation and self-reported experiences at rest.

PubMed

Wang, Hao-Ting; Bzdok, Danilo; Margulies, Daniel; Craddock, Cameron; Milham, Michael; Jefferies, Elizabeth; Smallwood, Jonathan

2018-08-01

Contemporary cognitive neuroscience recognises unconstrained processing varies across individuals, describing variation in meaningful attributes, such as intelligence. It may also have links to patterns of on-going experience. This study examined whether dimensions of population variation in different modes of unconstrained processing can be described by the associations between patterns of neural activity and self-reports of experience during the same period. We selected 258 individuals from a publicly available data set who had measures of resting-state functional magnetic resonance imaging, and self-reports of experience during the scan. We used machine learning to determine patterns of association between the neural and self-reported data, finding variation along four dimensions. 'Purposeful' experiences were associated with lower connectivity - in particular default mode and limbic networks were less correlated with attention and sensorimotor networks. 'Emotional' experiences were associated with higher connectivity, especially between limbic and ventral attention networks. Experiences focused on themes of 'personal importance' were associated with reduced functional connectivity within attention and control systems. Finally, visual experiences were associated with stronger connectivity between visual and other networks, in particular the limbic system. Some of these patterns had contrasting links with cognitive function as assessed in a separate laboratory session - purposeful thinking was linked to greater intelligence and better abstract reasoning, while a focus on personal importance had the opposite relationship. Together these findings are consistent with an emerging literature on unconstrained states and also underlines that these states are heterogeneous, with distinct modes of population variation reflecting the interplay of different large-scale networks. Copyright © 2018 Elsevier Inc. All rights reserved.

Accuracy in breast shape alignment with 3D surface fitting algorithms.

PubMed

Riboldi, Marco; Gierga, David P; Chen, George T Y; Baroni, Guido

2009-04-01

Surface imaging is in use in radiotherapy clinical practice for patient setup optimization and monitoring. Breast alignment is accomplished by searching for a tentative spatial correspondence between the reference and daily surface shape models. In this study, the authors quantify whole breast shape alignment by relying on texture features digitized on 3D surface models. Texture feature localization was validated through repeated measurements in a silicone breast phantom, mounted on a high precision mechanical stage. Clinical investigations on breast shape alignment included 133 fractions in 18 patients treated with accelerated partial breast irradiation. The breast shape was detected with a 3D video based surface imaging system so that breathing was compensated. An in-house algorithm for breast alignment, based on surface fitting constrained by nipple matching (constrained surface fitting), was applied. Results were compared with a commercial software where no constraints are utilized (unconstrained surface fitting). Texture feature localization was validated within 2 mm in each anatomical direction. Clinical data show that unconstrained surface fitting achieves adequate accuracy in most cases, though nipple mismatch is considerably higher than residual surface distances (3.9 mm vs 0.6 mm on average). Outliers beyond 1 cm can be experienced as the result of a degenerate surface fit, where unconstrained surface fitting is not sufficient to establish spatial correspondence. In the constrained surface fitting algorithm, average surface mismatch within 1 mm was obtained when nipple position was forced to match in the [1.5; 5] mm range. In conclusion, optimal results can be obtained by trading off the desired overall surface congruence vs matching of selected landmarks (constraint). Constrained surface fitting is put forward to represent an improvement in setup accuracy for those applications where whole breast positional reproducibility is an issue.

Near infrared and visible face recognition based on decision fusion of LBP and DCT features

NASA Astrophysics Data System (ADS)

Xie, Zhihua; Zhang, Shuai; Liu, Guodong; Xiong, Jinquan

2018-03-01

Visible face recognition systems, being vulnerable to illumination, expression, and pose, can not achieve robust performance in unconstrained situations. Meanwhile, near infrared face images, being light- independent, can avoid or limit the drawbacks of face recognition in visible light, but its main challenges are low resolution and signal noise ratio (SNR). Therefore, near infrared and visible fusion face recognition has become an important direction in the field of unconstrained face recognition research. In order to extract the discriminative complementary features between near infrared and visible images, in this paper, we proposed a novel near infrared and visible face fusion recognition algorithm based on DCT and LBP features. Firstly, the effective features in near-infrared face image are extracted by the low frequency part of DCT coefficients and the partition histograms of LBP operator. Secondly, the LBP features of visible-light face image are extracted to compensate for the lacking detail features of the near-infrared face image. Then, the LBP features of visible-light face image, the DCT and LBP features of near-infrared face image are sent to each classifier for labeling. Finally, decision level fusion strategy is used to obtain the final recognition result. The visible and near infrared face recognition is tested on HITSZ Lab2 visible and near infrared face database. The experiment results show that the proposed method extracts the complementary features of near-infrared and visible face images and improves the robustness of unconstrained face recognition. Especially for the circumstance of small training samples, the recognition rate of proposed method can reach 96.13%, which has improved significantly than 92.75 % of the method based on statistical feature fusion.

Advantages and Disadvantages of Transtibial, Anteromedial Portal, and Outside-In Femoral Tunnel Drilling in Single-Bundle Anterior Cruciate Ligament Reconstruction: A Systematic Review.

PubMed

Robin, Brett N; Jani, Sunil S; Marvil, Sean C; Reid, John B; Schillhammer, Carl K; Lubowitz, James H

2015-07-01

Controversy exists regarding the best method for creating the knee anterior cruciate ligament (ACL) femoral tunnel or socket. The purpose of this study was to systematically review the risks, benefits, advantages, and disadvantages of the endoscopic transtibial (TT) technique, anteromedial portal technique, outside-in technique, and outside-in retrograde drilling technique for creating the ACL femoral tunnel. A PubMed search of English-language studies published between January 1, 2000, and February 17, 2014, was performed using the following keywords: "anterior cruciate ligament" AND "femoral tunnel." Included were studies reporting risks, benefits, advantages, and/or disadvantages of any ACL femoral technique. In addition, references of included articles were reviewed to identify potential studies missed in the original search. A total of 27 articles were identified through the search. TT technique advantages include familiarity and proven long-term outcomes; disadvantages include the risk of nonanatomic placement because of constrained (TT) drilling. Anteromedial portal technique advantages include unconstrained anatomic placement; disadvantages include technical challenges, short tunnels or sockets, and posterior-wall blowout. Outside-in technique advantages include unconstrained anatomic placement; disadvantages include the need for 2 incisions. Retrograde drilling technique advantages include unconstrained anatomic placement, as well as all-epiphyseal drilling in skeletally immature patients; disadvantages include the need for fluoroscopy for all-epiphyseal drilling. There is no one, single, established "gold-standard" technique for creation of the ACL femoral socket. Four accepted techniques show diverse and subjective advantages, disadvantages, risks, and benefits. Level V, systematic review of Level II through V evidence. Copyright © 2015 Arthroscopy Association of North America. Published by Elsevier Inc. All rights reserved.

The ABCs of Math: A Genetic Analysis of Mathematics and Its Links With Reading Ability and General Cognitive Ability

PubMed Central

Hart, Sara A.; Petrill, Stephen A.; Thompson, Lee A.; Plomin, Robert

2009-01-01

The goal of this first major report from the Western Reserve Reading Project Math component is to explore the etiology of the relationship among tester-administered measures of mathematics ability, reading ability, and general cognitive ability. Data are available on 314 pairs of monozygotic and same-sex dizygotic twins analyzed across 5 waves of assessment. Univariate analyses provide a range of estimates of genetic (h2 = .00 –.63) and shared (c2 = .15–.52) environmental influences across math calculation, fluency, and problem solving measures. Multivariate analyses indicate genetic overlap between math problem solving with general cognitive ability and reading decoding, whereas math fluency shares significant genetic overlap with reading fluency and general cognitive ability. Further, math fluency has unique genetic influences. In general, math ability has shared environmental overlap with general cognitive ability and decoding. These results indicate that aspects of math that include problem solving have different genetic and environmental influences than math calculation. Moreover, math fluency, a timed measure of calculation, is the only measured math ability with unique genetic influences. PMID:20157630

The effectiveness of learning with concept mapping on the science problem-solving of sixth-grade children

NASA Astrophysics Data System (ADS)

Jolly, Anju B.

The purpose of this study was to analyze the relationship of concept mapping to science problem solving in sixth grade elementary school children. The study proposes to determine whether the students' ability to perform higher cognitive processes was a predictor of students' performance in solving problems in science and whether gender and socioeconomic status are related to performance in solving problems. Two groups participated in the study. Both groups were given a pre-test of higher cognitive ability--the Ross Test of Higher Cognitive Ability. One group received instruction on a science unit of study in concept mapping format and the other group received instruction in traditional format. The instruction lasted approximately 4 weeks. Both groups were given a problem-solving post-test. A comparison of post-test means was done using Analysis of Covariance (ANCOVA) as the statistical procedure with scores on the test of higher cognitive ability as the covariate. Also, Multiple Regression was performed to analyze the influence of participants' gender and socioeconomic status on their performance in solving problems. Results from the analysis of covariance showed that the group receiving instruction in the concept mapping format performed significantly better than the group receiving instruction in traditional format. Also the Ross Test of Higher Cognitive Processes emerged to be a predictor of performance on problem solving. There was no significant difference in the analysis of the performance of males and females. No pattern emerged regarding the influence of socioeconomic status on problem solving performance. In conclusion, the study showed that concept mapping improved problem solving in the classroom, and that gender and socioeconomic status are not predictors of student success in problem solving.

Is Perceptual Narrowing Too Narrow?

ERIC Educational Resources Information Center

Cashon, Cara H.; Denicola, Christopher A.

2011-01-01

There is a growing list of examples illustrating that infants are transitioning from having earlier abilities that appear more "universal," "broadly tuned," or "unconstrained" to having later abilities that appear more "specialized," "narrowly tuned," or "constrained." Perceptual narrowing, a well-known phenomenon related to face, speech, and…

Towards Mapping the Provision of Ecosystem Services from Headwater Wetlands in the Susquehanna River Basin

EPA Science Inventory

Headwater wetlands provide a range of ecosystem services including habitat provisioning and flood retention. Following the River Ecosystem Synthesis framework we identified and assessed not only headwater wetlands, but unconstrained reaches with the potential to support diverse s...

The Shock and Vibration Digest. Volume 13, Number 11

DTIC Science & Technology

1981-11-01

Beams with Unconstrained Damping Treatment G.R. Bhashyam and G. Prathap S. Narayanan, J.P. Verma, and A.K. Mallik Dept. of Aerospace and Mech. Engrg...2337 Sasaki, R ............... 2297 Mallik , A.K ............. 2384 Ookuma, M ............. 2463 Sasakura, Y ............. 2503 85 WaeskA

Compensation for Unconstrained Catheter Shaft Motion in Cardiac Catheters

PubMed Central

Degirmenci, Alperen; Loschak, Paul M.; Tschabrunn, Cory M.; Anter, Elad; Howe, Robert D.

2016-01-01

Cardiac catheterization with ultrasound (US) imaging catheters provides real time US imaging from within the heart, but manually navigating a four degree of freedom (DOF) imaging catheter is difficult and requires extensive training. Existing work has demonstrated robotic catheter steering in constrained bench top environments. Closed-loop control in an unconstrained setting, such as patient vasculature, remains a significant challenge due to friction, backlash, and physiological disturbances. In this paper we present a new method for closed-loop control of the catheter tip that can accurately and robustly steer 4-DOF cardiac catheters and other flexible manipulators despite these effects. The performance of the system is demonstrated in a vasculature phantom and an in vivo porcine animal model. During bench top studies the robotic system converged to the desired US imager pose with sub-millimeter and sub-degree-level accuracy. During animal trials the system achieved 2.0 mm and 0.65° accuracy. Accurate and robust robotic navigation of flexible manipulators will enable enhanced visualization and treatment during procedures. PMID:27525170

Unconstrained Respiration Measurement and Respiratory Arrest Detection Method by Dynamic Threshold in Transferring Patients by Stretchers

NASA Astrophysics Data System (ADS)

Kurihara, Yosuke; Watanabe, Kajiro; Kobayashi, Kazuyuki; Tanaka, Hiroshi

General anesthesia used for surgical operations may cause unstable conditions of the patients after the operations, which could lead to respiratory arrests. Under such circumstances, nurses could fail in finding the change of the conditions, and other malpractices could also occur. It is highly possible that such malpractices may occur while transferring a patient from ICU to the room using a stretcher. Monitoring the change in the blood oxygen saturation concentration and other vital signs to detect a respiratory arrest is not easy when transferring a patient on a stretcher. Here we present several noise reduction system and algorithm to detect respiratory arrests in transferring a patient, based on the unconstrained air pressure method that the authors presented previously. As the result, when the acceleration level of the stretcher noise was 0.5G, the respiratory arrest detection ratio using this novel method was 65%, while that with the conventional method was 0%.

Prediction-Correction Algorithms for Time-Varying Constrained Optimization

DOE PAGES

Simonetto, Andrea; Dall'Anese, Emiliano

2017-07-26

This article develops online algorithms to track solutions of time-varying constrained optimization problems. Particularly, resembling workhorse Kalman filtering-based approaches for dynamical systems, the proposed methods involve prediction-correction steps to provably track the trajectory of the optimal solutions of time-varying convex problems. The merits of existing prediction-correction methods have been shown for unconstrained problems and for setups where computing the inverse of the Hessian of the cost function is computationally affordable. This paper addresses the limitations of existing methods by tackling constrained problems and by designing first-order prediction steps that rely on the Hessian of the cost function (and do notmore » require the computation of its inverse). In addition, the proposed methods are shown to improve the convergence speed of existing prediction-correction methods when applied to unconstrained problems. Numerical simulations corroborate the analytical results and showcase performance and benefits of the proposed algorithms. A realistic application of the proposed method to real-time control of energy resources is presented.« less

Development of unconstrained heartbeat and respiration measurement system with pneumatic flow.

PubMed

Kurihara, Yosuke; Watanabe, Kajiro

2012-12-01

The management of health through daily monitoring of heartbeat and respiration signals is of major importance for early diagnosis to prevent diseases of the respiratory and circulatory system. However, such daily health monitoring is possible only if the monitoring system is physically and psychologically noninvasive. In this paper, an unconstrained method of measuring heartbeat and respiration signals, by using a thermistor to measure the air flows from the air mattress to an air tube accompanying the subject's heartbeat and respiration, is proposed. The SN ratio with interference by opening and closing of a door as environmental noise was compared with that obtained by the conventional condenser microphone method. As a result, the SN ratios with the condenser microphone method were 26.6 ± 4.2 dB for heartbeat and 27.8 ± 3.0 dB for respiration, whereas with the proposed method they were 34.9 ± 3.1 dB and 42.1 ± 2.5 dB, respectively.

An Improved Quantum-Behaved Particle Swarm Optimization Algorithm with Elitist Breeding for Unconstrained Optimization.

PubMed

Yang, Zhen-Lun; Wu, Angus; Min, Hua-Qing

2015-01-01

An improved quantum-behaved particle swarm optimization with elitist breeding (EB-QPSO) for unconstrained optimization is presented and empirically studied in this paper. In EB-QPSO, the novel elitist breeding strategy acts on the elitists of the swarm to escape from the likely local optima and guide the swarm to perform more efficient search. During the iterative optimization process of EB-QPSO, when criteria met, the personal best of each particle and the global best of the swarm are used to generate new diverse individuals through the transposon operators. The new generated individuals with better fitness are selected to be the new personal best particles and global best particle to guide the swarm for further solution exploration. A comprehensive simulation study is conducted on a set of twelve benchmark functions. Compared with five state-of-the-art quantum-behaved particle swarm optimization algorithms, the proposed EB-QPSO performs more competitively in all of the benchmark functions in terms of better global search capability and faster convergence rate.

Introspective Minds: Using ALE Meta-Analyses to Study Commonalities in the Neural Correlates of Emotional Processing, Social & Unconstrained Cognition

PubMed Central

Schilbach, Leonhard; Bzdok, Danilo; Timmermans, Bert; Fox, Peter T.; Laird, Angela R.; Vogeley, Kai; Eickhoff, Simon B.

2012-01-01

Previous research suggests overlap between brain regions that show task-induced deactivations and those activated during the performance of social-cognitive tasks. Here, we present results of quantitative meta-analyses of neuroimaging studies, which confirm a statistical convergence in the neural correlates of social and resting state cognition. Based on the idea that both social and unconstrained cognition might be characterized by introspective processes, which are also thought to be highly relevant for emotional experiences, a third meta-analysis was performed investigating studies on emotional processing. By using conjunction analyses across all three sets of studies, we can demonstrate significant overlap of task-related signal change in dorso-medial prefrontal and medial parietal cortex, brain regions that have, indeed, recently been linked to introspective abilities. Our findings, therefore, provide evidence for the existence of a core neural network, which shows task-related signal change during socio-emotional tasks and during resting states. PMID:22319593

Variable Autosomal and X Divergence Near and Far from Genes Affects Estimates of Male Mutation Bias in Great Apes

PubMed Central

Narang, Pooja; Wilson Sayres, Melissa A.

2016-01-01

Male mutation bias, when more mutations are passed on via the male germline than via the female germline, is observed across mammals. One common way to infer the magnitude of male mutation bias, α, is to compare levels of neutral sequence divergence between genomic regions that spend different amounts of time in the male and female germline. For great apes, including human, we show that estimates of divergence are reduced in putatively unconstrained regions near genes relative to unconstrained regions far from genes. Divergence increases with increasing distance from genes on both the X chromosome and autosomes, but increases faster on the X chromosome than autosomes. As a result, ratios of X/A divergence increase with increasing distance from genes and corresponding estimates of male mutation bias are significantly higher in intergenic regions near genes versus far from genes. Future studies in other species will need to carefully consider the effect that genomic location will have on estimates of male mutation bias. PMID:27702816

Facial First Impressions Across Culture: Data-Driven Modeling of Chinese and British Perceivers' Unconstrained Facial Impressions.

PubMed

Sutherland, Clare A M; Liu, Xizi; Zhang, Lingshan; Chu, Yingtung; Oldmeadow, Julian A; Young, Andrew W

2018-04-01

People form first impressions from facial appearance rapidly, and these impressions can have considerable social and economic consequences. Three dimensions can explain Western perceivers' impressions of Caucasian faces: approachability, youthful-attractiveness, and dominance. Impressions along these dimensions are theorized to be based on adaptive cues to threat detection or sexual selection, making it likely that they are universal. We tested whether the same dimensions of facial impressions emerge across culture by building data-driven models of first impressions of Asian and Caucasian faces derived from Chinese and British perceivers' unconstrained judgments. We then cross-validated the dimensions with computer-generated average images. We found strong evidence for common approachability and youthful-attractiveness dimensions across perceiver and face race, with some evidence of a third dimension akin to capability. The models explained ~75% of the variance in facial impressions. In general, the findings demonstrate substantial cross-cultural agreement in facial impressions, especially on the most salient dimensions.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nash, C.; Williams, M.; Restivo, M.

All prior testing with SuperLig® 639 has been done with the aqueous concentration of LAW at ~5 M [Na+], where the resin sinks, and can be used in a conventional down-flow column orientation. However, the aqueous LAW stream from the Waste Treatment Plant is expected to be ~8 M [Na+]. The resin would float in this higher density liquid, potentially disrupting the ability to achieve a good decontamination due to poor packing of the resin that leads to channeling. Testing was completed with a higher salt concentration in the feed simulant (7.8 M [Na+]) in an engineering-scale apparatus with twomore » columns, each containing ~0.9 L of resin. Testing of this system used a simulant of the LAW solution, and substituted ReO4 - as a surrogate for TcO4 -. Results were then compared using computer modeling. Bench-scale testing was also performed, and examined an unconstrained resin bed, while engineering-scale tests used both constrained and unconstrained beds in a two-column, lead and lag sequential arrangement.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Simonetto, Andrea; Dall'Anese, Emiliano

This article develops online algorithms to track solutions of time-varying constrained optimization problems. Particularly, resembling workhorse Kalman filtering-based approaches for dynamical systems, the proposed methods involve prediction-correction steps to provably track the trajectory of the optimal solutions of time-varying convex problems. The merits of existing prediction-correction methods have been shown for unconstrained problems and for setups where computing the inverse of the Hessian of the cost function is computationally affordable. This paper addresses the limitations of existing methods by tackling constrained problems and by designing first-order prediction steps that rely on the Hessian of the cost function (and do notmore » require the computation of its inverse). In addition, the proposed methods are shown to improve the convergence speed of existing prediction-correction methods when applied to unconstrained problems. Numerical simulations corroborate the analytical results and showcase performance and benefits of the proposed algorithms. A realistic application of the proposed method to real-time control of energy resources is presented.« less

The Fisher-Markov selector: fast selecting maximally separable feature subset for multiclass classification with applications to high-dimensional data.

PubMed

Cheng, Qiang; Zhou, Hongbo; Cheng, Jie

2011-06-01

Selecting features for multiclass classification is a critically important task for pattern recognition and machine learning applications. Especially challenging is selecting an optimal subset of features from high-dimensional data, which typically have many more variables than observations and contain significant noise, missing components, or outliers. Existing methods either cannot handle high-dimensional data efficiently or scalably, or can only obtain local optimum instead of global optimum. Toward the selection of the globally optimal subset of features efficiently, we introduce a new selector--which we call the Fisher-Markov selector--to identify those features that are the most useful in describing essential differences among the possible groups. In particular, in this paper we present a way to represent essential discriminating characteristics together with the sparsity as an optimization objective. With properly identified measures for the sparseness and discriminativeness in possibly high-dimensional settings, we take a systematic approach for optimizing the measures to choose the best feature subset. We use Markov random field optimization techniques to solve the formulated objective functions for simultaneous feature selection. Our results are noncombinatorial, and they can achieve the exact global optimum of the objective function for some special kernels. The method is fast; in particular, it can be linear in the number of features and quadratic in the number of observations. We apply our procedure to a variety of real-world data, including mid--dimensional optical handwritten digit data set and high-dimensional microarray gene expression data sets. The effectiveness of our method is confirmed by experimental results. In pattern recognition and from a model selection viewpoint, our procedure says that it is possible to select the most discriminating subset of variables by solving a very simple unconstrained objective function which in fact can be obtained with an explicit expression.

Method of interplanetary trajectory optimization for the spacecraft with low thrust and swing-bys

NASA Astrophysics Data System (ADS)

Konstantinov, M. S.; Thein, M.

2017-07-01

The method developed to avoid the complexity of solving the multipoint boundary value problem while optimizing interplanetary trajectories of the spacecraft with electric propulsion and a sequence of swing-bys is presented in the paper. This method is based on the use of the preliminary problem solutions for the impulsive trajectories. The preliminary problem analyzed at the first stage of the study is formulated so that the analysis and optimization of a particular flight path is considered as the unconstrained minimum in the space of the selectable parameters. The existing methods can effectively solve this problem and make it possible to identify rational flight paths (the sequence of swing-bys) to receive the initial approximation for the main characteristics of the flight path (dates, values of the hyperbolic excess velocity, etc.). These characteristics can be used to optimize the trajectory of the spacecraft with electric propulsion. The special feature of the work is the introduction of the second (intermediate) stage of the research. At this stage some characteristics of the analyzed flight path (e.g. dates of swing-bys) are fixed and the problem is formulated so that the trajectory of the spacecraft with electric propulsion is optimized on selected sites of the flight path. The end-to-end optimization is carried out at the third (final) stage of the research. The distinctive feature of this stage is the analysis of the full set of optimal conditions for the considered flight path. The analysis of the characteristics of the optimal flight trajectories to Jupiter with Earth, Venus and Mars swing-bys for the spacecraft with electric propulsion are presented. The paper shows that the spacecraft weighing more than 7150 kg can be delivered into the vicinity of Jupiter along the trajectory with two Earth swing-bys by use of the space transportation system based on the "Angara A5" rocket launcher, the chemical upper stage "KVTK" and the electric propulsion system with input electrical power of 100 kW.

Hybridisations of Variable Neighbourhood Search and Modified Simplex Elements to Harmony Search and Shuffled Frog Leaping Algorithms for Process Optimisations

NASA Astrophysics Data System (ADS)

Aungkulanon, P.; Luangpaiboon, P.

2010-10-01

Nowadays, the engineering problem systems are large and complicated. An effective finite sequence of instructions for solving these problems can be categorised into optimisation and meta-heuristic algorithms. Though the best decision variable levels from some sets of available alternatives cannot be done, meta-heuristics is an alternative for experience-based techniques that rapidly help in problem solving, learning and discovery in the hope of obtaining a more efficient or more robust procedure. All meta-heuristics provide auxiliary procedures in terms of their own tooled box functions. It has been shown that the effectiveness of all meta-heuristics depends almost exclusively on these auxiliary functions. In fact, the auxiliary procedure from one can be implemented into other meta-heuristics. Well-known meta-heuristics of harmony search (HSA) and shuffled frog-leaping algorithms (SFLA) are compared with their hybridisations. HSA is used to produce a near optimal solution under a consideration of the perfect state of harmony of the improvisation process of musicians. A meta-heuristic of the SFLA, based on a population, is a cooperative search metaphor inspired by natural memetics. It includes elements of local search and global information exchange. This study presents solution procedures via constrained and unconstrained problems with different natures of single and multi peak surfaces including a curved ridge surface. Both meta-heuristics are modified via variable neighbourhood search method (VNSM) philosophy including a modified simplex method (MSM). The basic idea is the change of neighbourhoods during searching for a better solution. The hybridisations proceed by a descent method to a local minimum exploring then, systematically or at random, increasingly distant neighbourhoods of this local solution. The results show that the variant of HSA with VNSM and MSM seems to be better in terms of the mean and variance of design points and yields.

Robust approximate optimal guidance strategies for aeroassisted orbital transfer missions

NASA Astrophysics Data System (ADS)

Ilgen, Marc R.

This thesis presents the application of game theoretic and regular perturbation methods to the problem of determining robust approximate optimal guidance laws for aeroassisted orbital transfer missions with atmospheric density and navigated state uncertainties. The optimal guidance problem is reformulated as a differential game problem with the guidance law designer and Nature as opposing players. The resulting equations comprise the necessary conditions for the optimal closed loop guidance strategy in the presence of worst case parameter variations. While these equations are nonlinear and cannot be solved analytically, the presence of a small parameter in the equations of motion allows the method of regular perturbations to be used to solve the equations approximately. This thesis is divided into five parts. The first part introduces the class of problems to be considered and presents results of previous research. The second part then presents explicit semianalytical guidance law techniques for the aerodynamically dominated region of flight. These guidance techniques are applied to unconstrained and control constrained aeroassisted plane change missions and Mars aerocapture missions, all subject to significant atmospheric density variations. The third part presents a guidance technique for aeroassisted orbital transfer problems in the gravitationally dominated region of flight. Regular perturbations are used to design an implicit guidance technique similar to the second variation technique but that removes the need for numerically computing an optimal trajectory prior to flight. This methodology is then applied to a set of aeroassisted inclination change missions. In the fourth part, the explicit regular perturbation solution technique is extended to include the class of guidance laws with partial state information. This methodology is then applied to an aeroassisted plane change mission using inertial measurements and subject to uncertainties in the initial value of the flight path angle. A summary of performance results for all these guidance laws is presented in the fifth part of this thesis along with recommendations for further research.

Measuring Category Intuitiveness in Unconstrained Categorization Tasks

ERIC Educational Resources Information Center

Pothos, Emmanuel M.; Perlman, Amotz; Bailey, Todd M.; Kurtz, Ken; Edwards, Darren J.; Hines, Peter; McDonnell, John V.

2011-01-01

What makes a category seem natural or intuitive? In this paper, an unsupervised categorization task was employed to examine observer agreement concerning the categorization of nine different stimulus sets. The stimulus sets were designed to capture different intuitions about classification structure. The main empirical index of category…

Vocabulary, Grammar, Sex, and Aging

ERIC Educational Resources Information Center

Moscoso del Prado Martín, Fermín

2017-01-01

Understanding the changes in our language abilities along the lifespan is a crucial step for understanding the aging process both in normal and in abnormal circumstances. Besides controlled experimental tasks, it is equally crucial to investigate language in unconstrained conversation. I present an information-theoretical analysis of a corpus of…

Patterns of Ground Water Movement in a Portion of the Willamette River Floodplain, Oregon

EPA Science Inventory

In reaches unconstrained by revetments, the Willamette River and its floodplain along its lowland mainstem is a continually evolving system. Several channel reconstruction and restoration projects have been implemented or planned in order to obtain beneficial services along the r...

A New Hydrogeological Research Site in the Willamette River Floodplain

EPA Science Inventory

The Willamette River is a ninth-order tributary of the Columbia which passes through a productive and populous region in northwest Oregon. Where unconstrained by shoreline revetments, the floodplain of this river is a high-energy, dynamic system which supports a variety of ripari...

High-Level Event Recognition in Unconstrained Videos

DTIC Science & Technology

2013-01-01

frames per- forms well for urban soundscapes but not for polyphonic music. In place of GMM, Lu et al. [78] adopted spectral clustering to generate...Aucouturier JJ, Defreville B, Pachet F (2007) The bag-of-frames approach to audio pattern recognition: a sufficientmodel for urban soundscapes but not

Personality and Situation in the Prediction of Women's Life Patterns.

ERIC Educational Resources Information Center

Stewart, Abigail J.

1980-01-01

Marriage, achievement need, children and self-definition predicted negative career persistence and career activity patterns in some family situations. Self-definition was associated with professional career activity among unconstrained women, but with freelance activity among married mothers. Personality variables may predict behavior within broad…

Characteristics of Students at Risk for Mathematics Difficulties Predicting Arithmetic Word Problem Solving Performance: The Role of Attention, Behavior, and Reading

ERIC Educational Resources Information Center

Jitendra, Asha K.; Corroy, Kelly Cozine; Dupuis, Danielle N.

2013-01-01

The purposes of this study were (a) to evaluate differences in arithmetic word problem solving between high and low at-risk students for mathematics difficulties (MD) and (b) to assess the influence of attention, behavior, reading, and socio-economic status (SES) in predicting the word problem solving performance of third-grade students with MD.…

Evaluation of three force-position hybrid control methods for a robot-based biological joint-testing system.

PubMed

Hsieh, Hong-Jung; Hu, Chih-Chung; Lu, Tung-Wu; Lu, Hsuan-Lun; Kuo, Mei-Ying; Kuo, Chien-Chung; Hsu, Horng-Chaung

2016-06-07

Robot-based joint-testing systems (RJTS) can be used to perform unconstrained laxity tests, measuring the stiffness of a degree of freedom (DOF) of the joint at a fixed flexion angle while allowing the other DOFs unconstrained movement. Previous studies using the force-position hybrid (FPH) control method proposed by Fujie et al. (J Biomech Eng 115(3):211-7, 1993) focused on anterior/posterior tests. Its convergence and applicability on other clinically relevant DOFs such as valgus/varus have not been demonstrated. The current s1tudy aimed to develop a 6-DOF RJTS using an industrial robot, to propose two new force-position hybrid control methods, and to evaluate the performance of the methods and FPH in controlling the RJTS for anterior/posterior and valgus/varus laxity tests of the knee joint. An RJTS was developed using an industrial 6-DOF robot with a 6-component load-cell attached at the effector. The performances of FPH and two new control methods, namely force-position alternate control (FPA) and force-position hybrid control with force-moment control (FPHFM), for unconstrained anterior/posterior and valgus/varus laxity tests were evaluated and compared with traditional constrained tests (CT) in terms of the number of control iterations, total time and the constraining forces and moments. As opposed to CT, the other three control methods successfully reduced the constraining forces and moments for both anterior/posterior and valgus/varus tests, FPHFM being the best followed in order by FPA and FPH. FPHFM had root-mean-squared constraining forces and moments of less than 2.2 N and 0.09 Nm, respectively at 0° flexion, and 2.3 N and 0.14 Nm at 30° flexion. The corresponding values for FPH were 8.5 N and 0.33 Nm, and 11.5 N and 0.45 Nm, respectively. Given the same control parameters including the compliance matrix, FPHFM and FPA reduced the constraining loads of FPH at the expense of additional control iterations, and thus increased total time, FPA taking about 10 % longer than FPHFM. The FPHFM would be the best choice among the methods considered when longer total time is acceptable in the intended clinical applications. The current results will be useful for selecting a force-position hybrid control method for unconstrained laxity tests using an RJTS.

Problem Solving in Genetics: Conceptual and Procedural Difficulties

ERIC Educational Resources Information Center

Karagoz, Meryem; Cakir, Mustafa

2011-01-01

The purpose of this study was to explore prospective biology teachers' understandings of fundamental genetics concepts and the association between misconceptions and genetics problem solving abilities. Specifically, the study describes conceptual and procedural difficulties which influence prospective biology teachers' genetics problem solving…

Diagrams Benefit Symbolic Problem-Solving

ERIC Educational Resources Information Center

Chu, Junyi; Rittle-Johnson, Bethany; Fyfe, Emily R.

2017-01-01

Background: The format of a mathematics problem often influences students' problem-solving performance. For example, providing diagrams in conjunction with story problems can benefit students' understanding, choice of strategy, and accuracy on story problems. However, it remains unclear whether providing diagrams in conjunction with symbolic…

Paradigms and Problem-Solving: A Literature Review.

ERIC Educational Resources Information Center

Berner, Eta S.

1984-01-01

Thomas Kuhn's conceptions of the influence of paradigms on the progress of science form the framework for analyzing how medical educators have approached research on medical problem solving. A new paradigm emphasizing multiple types of problems with varied solution strategies is proposed. (Author/MLW)

A point cloud modeling method based on geometric constraints mixing the robust least squares method

NASA Astrophysics Data System (ADS)

Yue, JIanping; Pan, Yi; Yue, Shun; Liu, Dapeng; Liu, Bin; Huang, Nan

2016-10-01

The appearance of 3D laser scanning technology has provided a new method for the acquisition of spatial 3D information. It has been widely used in the field of Surveying and Mapping Engineering with the characteristics of automatic and high precision. 3D laser scanning data processing process mainly includes the external laser data acquisition, the internal industry laser data splicing, the late 3D modeling and data integration system. For the point cloud modeling, domestic and foreign researchers have done a lot of research. Surface reconstruction technology mainly include the point shape, the triangle model, the triangle Bezier surface model, the rectangular surface model and so on, and the neural network and the Alfa shape are also used in the curved surface reconstruction. But in these methods, it is often focused on single surface fitting, automatic or manual block fitting, which ignores the model's integrity. It leads to a serious problems in the model after stitching, that is, the surfaces fitting separately is often not satisfied with the well-known geometric constraints, such as parallel, vertical, a fixed angle, or a fixed distance. However, the research on the special modeling theory such as the dimension constraint and the position constraint is not used widely. One of the traditional modeling methods adding geometric constraints is a method combing the penalty function method and the Levenberg-Marquardt algorithm (L-M algorithm), whose stability is pretty good. But in the research process, it is found that the method is greatly influenced by the initial value. In this paper, we propose an improved method of point cloud model taking into account the geometric constraint. We first apply robust least-squares to enhance the initial value's accuracy, and then use penalty function method to transform constrained optimization problems into unconstrained optimization problems, and finally solve the problems using the L-M algorithm. The experimental results show that the internal accuracy is improved, and it is shown that the improved method for point clouds modeling proposed by this paper outperforms the traditional point clouds modeling methods.

Interconnection-wide hour-ahead scheduling in the presence of intermittent renewables and demand response: A surplus maximizing approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Behboodi, Sahand; Chassin, David P.; Djilali, Ned

This study describes a new approach for solving the multi-area electricity resource allocation problem when considering both intermittent renewables and demand response. The method determines the hourly inter-area export/import set that maximizes the interconnection (global) surplus satisfying transmission, generation and load constraints. The optimal inter-area transfer set effectively makes the electricity price uniform over the interconnection apart from constrained areas, which overall increases the consumer surplus more than it decreases the producer surplus. The method is computationally efficient and suitable for use in simulations that depend on optimal scheduling models. The method is demonstrated on a system that represents Northmore » America Western Interconnection for the planning year of 2024. Simulation results indicate that effective use of interties reduces the system operation cost substantially. Excluding demand response, both the unconstrained and the constrained scheduling solutions decrease the global production cost (and equivalently increase the global economic surplus) by 12.30B and 10.67B per year, respectively, when compared to the standalone case in which each control area relies only on its local supply resources. This cost saving is equal to 25% and 22% of the annual production cost. Including 5% demand response, the constrained solution decreases the annual production cost by 10.70B, while increases the annual surplus by 9.32B in comparison to the standalone case.« less

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dunlavy, Daniel; Chew, Peter A.

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

Multi-Objectivising Combinatorial Optimisation Problems by Means of Elementary Landscape Decompositions.

PubMed

Ceberio, Josu; Calvo, Borja; Mendiburu, Alexander; Lozano, Jose A

2018-02-15

In the last decade, many works in combinatorial optimisation have shown that, due to the advances in multi-objective optimisation, the algorithms from this field could be used for solving single-objective problems as well. In this sense, a number of papers have proposed multi-objectivising single-objective problems in order to use multi-objective algorithms in their optimisation. In this article, we follow up this idea by presenting a methodology for multi-objectivising combinatorial optimisation problems based on elementary landscape decompositions of their objective function. Under this framework, each of the elementary landscapes obtained from the decomposition is considered as an independent objective function to optimise. In order to illustrate this general methodology, we consider four problems from different domains: the quadratic assignment problem and the linear ordering problem (permutation domain), the 0-1 unconstrained quadratic optimisation problem (binary domain), and the frequency assignment problem (integer domain). We implemented two widely known multi-objective algorithms, NSGA-II and SPEA2, and compared their performance with that of a single-objective GA. The experiments conducted on a large benchmark of instances of the four problems show that the multi-objective algorithms clearly outperform the single-objective approaches. Furthermore, a discussion on the results suggests that the multi-objective space generated by this decomposition enhances the exploration ability, thus permitting NSGA-II and SPEA2 to obtain better results in the majority of the tested instances.

Interconnection-wide hour-ahead scheduling in the presence of intermittent renewables and demand response: A surplus maximizing approach

DOE PAGES

Behboodi, Sahand; Chassin, David P.; Djilali, Ned; ...

2016-12-23

This study describes a new approach for solving the multi-area electricity resource allocation problem when considering both intermittent renewables and demand response. The method determines the hourly inter-area export/import set that maximizes the interconnection (global) surplus satisfying transmission, generation and load constraints. The optimal inter-area transfer set effectively makes the electricity price uniform over the interconnection apart from constrained areas, which overall increases the consumer surplus more than it decreases the producer surplus. The method is computationally efficient and suitable for use in simulations that depend on optimal scheduling models. The method is demonstrated on a system that represents Northmore » America Western Interconnection for the planning year of 2024. Simulation results indicate that effective use of interties reduces the system operation cost substantially. Excluding demand response, both the unconstrained and the constrained scheduling solutions decrease the global production cost (and equivalently increase the global economic surplus) by 12.30B and 10.67B per year, respectively, when compared to the standalone case in which each control area relies only on its local supply resources. This cost saving is equal to 25% and 22% of the annual production cost. Including 5% demand response, the constrained solution decreases the annual production cost by 10.70B, while increases the annual surplus by 9.32B in comparison to the standalone case.« less

An effective parameter optimization with radiation balance constraints in the CAM5

NASA Astrophysics Data System (ADS)

Wu, L.; Zhang, T.; Qin, Y.; Lin, Y.; Xue, W.; Zhang, M.

2017-12-01

Uncertain parameters in physical parameterizations of General Circulation Models (GCMs) greatly impact model performance. Traditional parameter tuning methods are mostly unconstrained optimization, leading to the simulation results with optimal parameters may not meet the conditions that models have to keep. In this study, the radiation balance constraint is taken as an example, which is involved in the automatic parameter optimization procedure. The Lagrangian multiplier method is used to solve this optimization problem with constrains. In our experiment, we use CAM5 atmosphere model under 5-yr AMIP simulation with prescribed seasonal climatology of SST and sea ice. We consider the synthesized metrics using global means of radiation, precipitation, relative humidity, and temperature as the goal of optimization, and simultaneously consider the conditions that FLUT and FSNTOA should satisfy as constraints. The global average of the output variables FLUT and FSNTOA are set to be approximately equal to 240 Wm-2 in CAM5. Experiment results show that the synthesized metrics is 13.6% better than the control run. At the same time, both FLUT and FSNTOA are close to the constrained conditions. The FLUT condition is well satisfied, which is obviously better than the average annual FLUT obtained with the default parameters. The FSNTOA has a slight deviation from the observed value, but the relative error is less than 7.7‰.

First- and third-party ground truth for key frame extraction from consumer video clips

NASA Astrophysics Data System (ADS)

Costello, Kathleen; Luo, Jiebo

2007-02-01

Extracting key frames (KF) from video is of great interest in many applications, such as video summary, video organization, video compression, and prints from video. KF extraction is not a new problem. However, current literature has been focused mainly on sports or news video. In the consumer video space, the biggest challenges for key frame selection from consumer videos are the unconstrained content and lack of any preimposed structure. In this study, we conduct ground truth collection of key frames from video clips taken by digital cameras (as opposed to camcorders) using both first- and third-party judges. The goals of this study are: (1) to create a reference database of video clips reasonably representative of the consumer video space; (2) to identify associated key frames by which automated algorithms can be compared and judged for effectiveness; and (3) to uncover the criteria used by both first- and thirdparty human judges so these criteria can influence algorithm design. The findings from these ground truths will be discussed.

Facilitation of voluntary goal-directed action by reward cues.

PubMed

Lovibond, Peter F; Colagiuri, Ben

2013-10-01

Reward-associated cues are known to influence motivation to approach both natural and man-made rewards, such as food and drugs. However, the mechanisms underlying these effects are not well understood. To model these processes in the laboratory with humans, we developed an appetitive Pavlovian-instrumental transfer procedure with a chocolate reward. We used a single unconstrained response that led to an actual rather than symbolic reward to assess the strength of reward motivation. Presentation of a chocolate-paired cue, but not an unpaired cue, markedly enhanced instrumental responding over a 30-s period. The same pattern was observed with 10-s and 30-s cues, showing that close cue-reward contiguity is not necessary for facilitation of reward-directed action. The results confirm that reward-related cues can instigate voluntary action to obtain that reward. The effectiveness of long-duration cues suggests that in clinical settings, attention should be directed to both proximal and distal cues for reward.

Microenvironmental independence associated with tumor progression.

PubMed

Anderson, Alexander R A; Hassanein, Mohamed; Branch, Kevin M; Lu, Jenny; Lobdell, Nichole A; Maier, Julie; Basanta, David; Weidow, Brandy; Narasanna, Archana; Arteaga, Carlos L; Reynolds, Albert B; Quaranta, Vito; Estrada, Lourdes; Weaver, Alissa M

2009-11-15

Tumor-microenvironment interactions are increasingly recognized to influence tumor progression. To understand the competitive dynamics of tumor cells in diverse microenvironments, we experimentally parameterized a hybrid discrete-continuum mathematical model with phenotypic trait data from a set of related mammary cell lines with normal, transformed, or tumorigenic properties. Surprisingly, in a resource-rich microenvironment, with few limitations on proliferation or migration, transformed (but not tumorigenic) cells were most successful and outcompeted other cell types in heterogeneous tumor simulations. Conversely, constrained microenvironments with limitations on space and/or growth factors gave a selective advantage to phenotypes derived from tumorigenic cell lines. Analysis of the relative performance of each phenotype in constrained versus unconstrained microenvironments revealed that, although all cell types grew more slowly in resource-constrained microenvironments, the most aggressive cells were least affected by microenvironmental constraints. A game theory model testing the relationship between microenvironment resource availability and competitive cellular dynamics supports the concept that microenvironmental independence is an advantageous cellular trait in resource-limited microenvironments.

Radar altimetry systems cost analysis

NASA Technical Reports Server (NTRS)

Escoe, D.; Heuring, F. T.; Denman, W. F.

1976-01-01

This report discusses the application and cost of two types of altimeter systems (spaceborne (satellite and shuttle) and airborne) to twelve user requirements. The overall design of the systems defined to meet these requirements is predicated on an unconstrained altimetry technology; that is, any level of altimeter or supporting equipment performance is possible.

Moving Beyond a Deficit Perspective with Qualitative Research Methods.

ERIC Educational Resources Information Center

Anzul, Margaret; Evans, Judith F.; King, Rita; Tellier-Robinson, Dora

2001-01-01

Four researchers argue the merits of qualitative methodology and its particular relevance to those in special education who seek to move beyond a deficit perspective. Unconstrained by defined variables and decontextualized settings, qualitative methods allowed the researchers to extend the scope of their studies beyond originally stated research…

Estimating Latent Variable Interactions with Nonnormal Observed Data: A Comparison of Four Approaches

ERIC Educational Resources Information Center

Cham, Heining; West, Stephen G.; Ma, Yue; Aiken, Leona S.

2012-01-01

A Monte Carlo simulation was conducted to investigate the robustness of 4 latent variable interaction modeling approaches (Constrained Product Indicator [CPI], Generalized Appended Product Indicator [GAPI], Unconstrained Product Indicator [UPI], and Latent Moderated Structural Equations [LMS]) under high degrees of nonnormality of the observed…

A Latent Class Unfolding Model for Analyzing Single Stimulus Preference Ratings.

ERIC Educational Resources Information Center

De Soete, Geert; Heiser, Willem J.

1993-01-01

A latent class unfolding model is developed for single stimulus preference ratings. One advantage is the possibility of testing the spatial unfolding model against the unconstrained latent class model for rating data. The model is applied to data about party preferences of members of the Dutch parliament. (SLD)

Women in the World. A Ford Foundation Position Paper.

ERIC Educational Resources Information Center

Ford Foundation, New York, NY.

This report presents the rationale for the expanded women's programs sponsored by the Ford Foundation and describes their current and projected activities. Both men and women should have opportunities to choose roles and lifestyles unconstrained by sex discrimination. The gross under-representation of women cited in figures throughout this report…

Admonitory Behavioral Norms of Campus Housing and Residence Life Professionals

ERIC Educational Resources Information Center

Wilson, Maureen E.; Hirschy, Amy S.; Braxton, John M.

2016-01-01

To protect the welfare of students, staff, and other clients in housing and residence life (HRL), administrators must understand what behaviors are unacceptable. Professionals might make idiosyncratic and unconstrained decisions when there is no conduct code or set of informal rules. Informal rules may become norms comprising normative structures…

Developing Unconstrained Methods for Enzyme Evolution

DTIC Science & Technology

2014-09-19

Equivalent: Total Number: Sunil Kumar 1.00 1.00 1 PERCENT_SUPPORTEDNAME FTE Equivalent: Total Number: National Academy Member John C. Chaput 0.10 No 0.10...synthetic ATP-binding protein leads to novel phenotypic changes in Escherichia coli. ACS Chemical Biology 8, 451-456. c. Student Support Dr. Sunil

A study of the two-control operation of an airplane

NASA Technical Reports Server (NTRS)

Jones, Robert T

1938-01-01

The two-control operation of a conventional airplane is treated by means of the theory of disturbed motions. The consequences of this method of control are studied with regard to the stability of the airplane in its unconstrained components of motion and the movements set up during turn maneuvers.

Robustness of Hierarchical Modeling of Skill Association in Cognitive Diagnosis Models

ERIC Educational Resources Information Center

Templin, Jonathan L.; Henson, Robert A.; Templin, Sara E.; Roussos, Louis

2008-01-01

Several types of parameterizations of attribute correlations in cognitive diagnosis models use the reduced reparameterized unified model. The general approach presumes an unconstrained correlation matrix with K(K - 1)/2 parameters, whereas the higher order approach postulates K parameters, imposing a unidimensional structure on the correlation…

Bite Block Vowel Production in Apraxia of Speech

ERIC Educational Resources Information Center

Jacks, Adam

2008-01-01

Purpose: This study explored vowel production and adaptation to articulatory constraints in adults with acquired apraxia of speech (AOS) plus aphasia. Method: Five adults with acquired AOS plus aphasia and 5 healthy control participants produced the vowels [iota], [epsilon], and [ash] in four word-length conditions in unconstrained and bite block…

Expecting innovation: psychoactive drug primes and the generation of creative solutions.

PubMed

Hicks, Joshua A; Pedersen, Sarah L; Pederson, Sarah L; Friedman, Ronald S; McCarthy, Denis M

2011-08-01

Many individuals expect that alcohol and drug consumption will enhance creativity. The present studies tested whether substance related primes would influence creative performance for individuals who possessed creativity-related substance expectancies. Participants (n = 566) were briefly exposed to stimuli related to psychoactive substances (alcohol, for Study 1, Sample 1, and Study 2; and marijuana, for Study 1, Sample 2) or neutral stimuli. Participants in Study 1 then completed a creative problem-solving task, while participants in Study 2 completed a divergent thinking task or a task unrelated to creative problem solving. The results of Study 1 revealed that exposure to the experimental stimuli enhanced performance on the creative problem-solving task for those who expected the corresponding substance would trigger creative functioning. In a conceptual replication, Study 2 showed that participants exposed to alcohol cues performed better on a divergent thinking task if they expected alcohol to enhance creativity. It is important to note that this same interaction did not influence performance on measures unrelated to creative problem solving, suggesting that the activation of creativity-related expectancies influenced creative performance, specifically. These findings highlight the importance of assessing expectancies when examining pharmacological effects of alcohol and marijuana. Future directions and implications for substance-related interventions are discussed. (c) 2011 APA, all rights reserved.

The Influence of Self-Efficacy Beliefs and Metacognitive Prompting on Genetics Problem Solving Ability among High School Students in Kenya

NASA Astrophysics Data System (ADS)

Aurah, Catherine Muhonja

Within the framework of social cognitive theory, the influence of self-efficacy beliefs and metacognitive prompting on genetics problem solving ability among high school students in Kenya was examined through a mixed methods research design. A quasi-experimental study, supplemented by focus group interviews, was conducted to investigate both the outcomes and the processes of students' genetics problem-solving ability. Focus group interviews substantiated and supported findings from the quantitative instruments. The study was conducted in 17 high schools in Western Province, Kenya. A total of 2,138 high school students were purposively sampled. A sub-sample of 48 students participated in focus group interviews to understand their perspectives and experiences during the study so as to corroborate the quantitative data. Quantitative data were analyzed through descriptive statistics, zero-order correlations, 2 x 2 factorial ANOVA,, and sequential hierarchical multiple regressions. Qualitative data were transcribed, coded, and reported thematically. Results revealed metacognitive prompts had significant positive effects on student problem-solving ability independent of gender. Self-efficacy and metacognitive prompting significantly predicted genetics problem-solving ability. Gender differences were revealed, with girls outperforming boys on the genetics problem-solving test. Furthermore, self-efficacy moderated the relationship between metacognitive prompting and genetics problem-solving ability. This study established a foundation for instructional methods for biology teachers and recommendations are made for implementing metacognitive prompting in a problem-based learning environment in high schools and science teacher education programs in Kenya.

Metaphors we think with: the role of metaphor in reasoning.

PubMed

Thibodeau, Paul H; Boroditsky, Lera

2011-02-23

The way we talk about complex and abstract ideas is suffused with metaphor. In five experiments, we explore how these metaphors influence the way that we reason about complex issues and forage for further information about them. We find that even the subtlest instantiation of a metaphor (via a single word) can have a powerful influence over how people attempt to solve social problems like crime and how they gather information to make "well-informed" decisions. Interestingly, we find that the influence of the metaphorical framing effect is covert: people do not recognize metaphors as influential in their decisions; instead they point to more "substantive" (often numerical) information as the motivation for their problem-solving decision. Metaphors in language appear to instantiate frame-consistent knowledge structures and invite structurally consistent inferences. Far from being mere rhetorical flourishes, metaphors have profound influences on how we conceptualize and act with respect to important societal issues. We find that exposure to even a single metaphor can induce substantial differences in opinion about how to solve social problems: differences that are larger, for example, than pre-existing differences in opinion between Democrats and Republicans.

The Mathematical Preparation of Prospective Elementary Teachers: Reflections from Solving an "Interesting Problem"

ERIC Educational Resources Information Center

Ellis, Mark W.; Contreras, Jose; Martinez-Cruz, Armando M.

2009-01-01

Problem solving tasks offer valuable opportunities to strengthen prospective elementary teachers' knowledge of and disposition toward mathematics, providing them with new experiences doing mathematics. Mathematics educators can influence future instruction by modeling effective pedagogical strategies that engage students in making sense of…

Effect of Dimensional Salience and Salience of Variability on Problem Solving: A Developmental Study

ERIC Educational Resources Information Center

Zelniker, Tamar; And Others

1975-01-01

A matching task was presented to 120 subjects from 6 to 20 years of age to investigate the relative influence of dimensional salience and salience of variability on problem solving. The task included four dimensions: form, color, number, and position. (LLK)

Gender Influences on Parent-Child Science Problem-Solving Behaviors

ERIC Educational Resources Information Center

Short-Meyerson, Katherine; Sandrin, Susannah; Edwards, Chris

2016-01-01

Gender is a critical social factor influencing how children view the world from very early childhood. Additionally, during the early elementary years, parents can have a significant influence on their child's behaviors and dispositions in fields such as science. This study examined the influence of parent gender and child gender on 2nd- and…

Minimalism as a Guiding Principle: Linking Mathematical Learning to Everyday Knowledge

ERIC Educational Resources Information Center

Inoue, Noriyuki

2008-01-01

Studies report that students often fail to consider familiar aspects of reality in solving mathematical word problems. This study explored how different features of mathematical problems influence the way that undergraduate students employ realistic considerations in mathematical problem solving. Incorporating familiar contents in the word…

Pre-University Tuition in Science and Technology Can Influence Executive Functions

ERIC Educational Resources Information Center

Méndez, Marta; Arias, Natalia; Menéndez, José R.; Villar, José R.; Neira, Ángel; Romano, Pedro V.; Núñez, José Carlos; Arias, Jorge L.

2014-01-01

Introduction: Scientific and technological areas include tuition based on highly visuo-spatial specialization and problem solving. Spatial skills and problem solving are embedded in a curriculum that promotes understanding of Science and technical subjects. These abilities are related to the development of executive functions (EFs). We aim to…

Finding the Optimal Scaffoldings for Learners' Epistemological Beliefs during Ill-Structured Problem Solving

ERIC Educational Resources Information Center

Shin, Suhkyung; Song, Hae-Deok

2016-01-01

This study investigates how scaffolding type and learners' epistemological beliefs influence ill-structured problem solving. The independent variables in this study include the type of scaffolding (task-supported, self-monitoring) and the student's epistemological belief level (more advanced, less advanced). The dependent variables include three…

Influence of forest and rangeland management on anadromous fish habitat in Western North America: effects of livestock grazing.

Treesearch

William S. Platts

1981-01-01

This paper documents current knowledge on interactions of livestock and fish habitat. Included are discussions of incompatibility and compatibility between livestock grazing and fisheries, present management guidelines, information needed for problem solving, information available for problem solving, and future research needs.

Influence of personality, age, sex, and estrous state on chimpanzee problem-solving success

PubMed Central

Hopper, Lydia M.; Price, Sara A.; Freeman, Hani D.; Lambeth, Susan P.; Schapiro, Steven J.

2015-01-01

Despite the importance of individual problem solvers for group- and individual-level fitness, the correlates of individual problem-solving success are still an open topic of investigation. In addition to demographic factors, such as age or sex, certain personality dimensions have also been revealed as reliable correlates of problem-solving by animals. Such correlates, however, have been little-studied in chimpanzees. To empirically test the influence of age, sex, estrous state, and different personality factors on chimpanzee problem-solving, we individually tested 36 captive chimpanzees with two novel foraging puzzles. We included both female (N = 24) and male (N = 12) adult chimpanzees (aged 14–47 years) in our sample. We also controlled for the females’ estrous state—a potential influence on cognitive reasoning—by testing cycling females both when their sexual swelling was maximally tumescent (associated with the luteinizing hormone surge of a female’s estrous cycle) and again when it was detumescent. Although we found no correlation between the chimpanzees’ success with either puzzle and their age or sex, the chimpanzees’ personality ratings did correlate with responses to the novel foraging puzzles. Specifically, male chimpanzees that were rated highly on the factors Methodical, Openness (to experience), and Dominance spent longer interacting with the puzzles. There was also a positive relationship between the latency of females to begin interacting with the two tasks and their rating on the factor Reactivity/Undependability. No other significant correlations were found, but we report tentative evidence for increased problem-solving success by the females when they had detumescent estrous swellings. PMID:24322874

Influence of personality, age, sex, and estrous state on chimpanzee problem-solving success.

PubMed

Hopper, Lydia M; Price, Sara A; Freeman, Hani D; Lambeth, Susan P; Schapiro, Steven J; Kendal, Rachel L

2014-07-01

Despite the importance of individual problem solvers for group- and individual-level fitness, the correlates of individual problem-solving success are still an open topic of investigation. In addition to demographic factors, such as age or sex, certain personality dimensions have also been revealed as reliable correlates of problem-solving by animals. Such correlates, however, have been little-studied in chimpanzees. To empirically test the influence of age, sex, estrous state, and different personality factors on chimpanzee problem-solving, we individually tested 36 captive chimpanzees with two novel foraging puzzles. We included both female (N=24) and male (N=12) adult chimpanzees (aged 14-47 years) in our sample. We also controlled for the females' estrous state-a potential influence on cognitive reasoning-by testing cycling females both when their sexual swelling was maximally tumescent (associated with the luteinizing hormone surge of a female's estrous cycle) and again when it was detumescent. Although we found no correlation between the chimpanzees' success with either puzzle and their age or sex, the chimpanzees' personality ratings did correlate with responses to the novel foraging puzzles. Specifically, male chimpanzees that were rated highly on the factors Methodical, Openness (to experience), and Dominance spent longer interacting with the puzzles. There was also a positive relationship between the latency of females to begin interacting with the two tasks and their rating on the factor Reactivity/Undependability. No other significant correlations were found, but we report tentative evidence for increased problem-solving success by the females when they had detumescent estrous swellings.

Flexibility in Mathematics Problem Solving Based on Adversity Quotient

NASA Astrophysics Data System (ADS)

Dina, N. A.; Amin, S. M.; Masriyah

2018-01-01

Flexibility is an ability which is needed in problem solving. One of the ways in problem solving is influenced by Adversity Quotient (AQ). AQ is the power of facing difficulties. There are three categories of AQ namely climber, camper, and quitter. This research is a descriptive research using qualitative approach. The aim of this research is to describe flexibility in mathematics problem solving based on Adversity Quotient. The subjects of this research are climber student, camper student, and quitter student. This research was started by giving Adversity Response Profile (ARP) questioner continued by giving problem solving task and interviews. The validity of data measurement was using time triangulation. The results of this research shows that climber student uses two strategies in solving problem and doesn’t have difficulty. The camper student uses two strategies in solving problem but has difficulty to finish the second strategies. The quitter student uses one strategy in solving problem and has difficulty to finish it.

Thinking aloud influences perceived time.

PubMed

Hertzum, Morten; Holmegaard, Kristin Due

2015-02-01

We investigate whether thinking aloud influences perceived time. Thinking aloud is widely used in usability evaluation, yet it is debated whether thinking aloud influences thought and behavior. If thinking aloud is restricted to the verbalization of information to which a person is already attending, there is evidence that thinking aloud does not influence thought and behavior. In an experiment, 16 thinking-aloud participants and 16 control participants solved a code-breaking task 24 times each. Participants estimated task duration. The 24 trials involved two levels of time constraint (timed, untimed) and resulted in two levels of success (solved, unsolved). The ratio of perceived time to clock time was lower for thinking-aloud than control participants. Participants overestimated time by an average of 47% (thinking aloud) and 94% (control). The effect of thinking aloud on time perception also held separately for timed, untimed, solved, and unsolved trials. Thinking aloud (verbalization at Levels 1 and 2) influences perceived time. Possible explanations of this effect include that thinking aloud may require attention, cause a processing shift that overshadows the perception of time, or increase mental workload. For usability evaluation, this study implies that time estimates made while thinking aloud cannot be compared with time estimates made while not thinking aloud, that ratings of systems experienced while thinking aloud may be inaccurate (because the experience of time influences other experiences), and that it may therefore be considered to replace concurrent thinking aloud with retrospective thinking aloud when evaluations involve time estimation.

Analysis of Foreign Area Officer (FAO) Requirements

DTIC Science & Technology

2007-02-01

East jArabic (MS) Attache Atache NORTHCOM C~anada, Ottawa Ontario ALUSNA 10-6 jAn jFrech Afttche A.ttache N0RTHCOM IMaesc ALUSNA 0-8 S Amyerica...GOG jArabic [Pal-miI/sales Total billets: 15 58 UNCLASSIFIED The Naval Component Commands identified these unconstrained FAQ billets. 58 UNCLASSIFIED

Promoting Effective E-Learning Practices through the Constructivist Pedagogy

ERIC Educational Resources Information Center

Keengwe, Jared; Onchwari, Grace; Agamba, Joachim

2014-01-01

Although rapid advances in technology has allowed for the growth of collaborative e-learning experiences unconstrained by time and space, technology has not been heavily infused in the activities of teaching and learning. This article examines the theory of constructivism as well as the design of e-learning activities using constructivist…

Qualitative Methods Can Enrich Quantitative Research on Occupational Stress: An Example from One Occupational Group

ERIC Educational Resources Information Center

Schonfeld, Irvin Sam; Farrell, Edwin

2010-01-01

The chapter examines the ways in which qualitative and quantitative methods support each other in research on occupational stress. Qualitative methods include eliciting from workers unconstrained descriptions of work experiences, careful first-hand observations of the workplace, and participant-observers describing "from the inside" a…

The Roles of Suprasegmental Features in Predicting English Oral Proficiency with an Automated System

ERIC Educational Resources Information Center

Kang, Okim; Johnson, David

2018-01-01

Suprasegmental features have received growing attention in the field of oral assessment. In this article we describe a set of computer algorithms that automatically scores the oral proficiency of non-native speakers using unconstrained English speech. The algorithms employ machine learning and 11 suprasegmental measures divided into four groups…

Speaker-dependent Multipitch Tracking Using Deep Neural Networks

DTIC Science & Technology

2015-01-01

connections through time. Studies have shown that RNNs are good at modeling sequential data like handwriting [12] and speech [26]. We plan to explore RNNs in...Schmidhuber, and S. Fernández, “Unconstrained on-line handwriting recognition with recurrent neural networks,” in Proceedings of NIPS, 2008, pp. 577–584. [13

Content-Based Indexing and Teaching Focus Mining for Lecture Videos

ERIC Educational Resources Information Center

Lin, Yu-Tzu; Yen, Bai-Jang; Chang, Chia-Hu; Lee, Greg C.; Lin, Yu-Chih

2010-01-01

Purpose: The purpose of this paper is to propose an indexing and teaching focus mining system for lecture videos recorded in an unconstrained environment. Design/methodology/approach: By applying the proposed algorithms in this paper, the slide structure can be reconstructed by extracting slide images from the video. Instead of applying…

Plant succession after hydrologic disturbance: Inferences from contemporary vegetation on a chronosequence of bars, Willamette River, Oregon, USA

EPA Science Inventory

Historic unconstrained, unregulated streamflow along the upper mainstem of the Willamette River, Oregon, produced a floodplain of coalescent bars supporting a mosaic of vegetation patches. We sampled the contemporary vegetation of 42 bars formed 3 to 64 + years ago in four, 1 km...

Network and Information Sciences (NIS) International Technology Alliance (ITA)

DTIC Science & Technology

2016-05-01

unpredictable, insights often unexpected, and innovation paths are diverse. On the one hand a laissez - faire and unconstrained management approach would...138 References . ..... ...... . . ... . . .. .. . . ..... . ....... . ... .. . 139 A NIS ITA Leadership ........... . . .. .. . . . . ..... . .. 141...ten-year programme, covering a range of perspectives of the work and the results achieved by the integrated technical leadership and wide research

The Allocation of Visual Attention in Multimedia Search Interfaces

ERIC Educational Resources Information Center

Hughes, Edith Allen

2017-01-01

Multimedia analysts are challenged by the massive numbers of unconstrained video clips generated daily. Such clips can include any possible scene and events, and generally have limited quality control. Analysts who must work with such data are overwhelmed by its volume and lack of computational tools to probe it effectively. Even with advances…

Testing the Factorial Invariance of the Black Racial Identity Scale across Gender

ERIC Educational Resources Information Center

Lott, Joe L., II

2011-01-01

Given that over 50 studies have been published using the Black Racial Identity Scale (BRIAS), the study of its dimensions and structural components are important to understanding Black people and the evolution of Black racial identity theory. Unconstrained and constrained confirmatory factor analysis models were estimated across males and females…

Radical Dewey: Deweyan Pedagogy in Mexico, 1915-1923

ERIC Educational Resources Information Center

Rodriguez, Victor J.

2013-01-01

From 1915 to 1923, the pedagogy of John Dewey became an important pillar of anarchist and socialist projects of education in Mexico. These radical experiments were based on the belief in an open-ended world amenable to the intervention of a new subject of modernity whose unconstrained operations created rather than disrupted social order.…

Matching Analysis of Socially Appropriate and Destructive Behavior in Developmental Disabilities

ERIC Educational Resources Information Center

Hoch, John; Symons, Frank J.

2007-01-01

This study examined socially appropriate and destructive behavior in unconstrained natural environments using a matching law analysis (MLA) of real time observational data. The participants were two school-age children and one adult with mild to moderate cognitive disabilities. Event lagged sequential analysis (SQA) provided the obtained rates of…

A Comparison of Methods for Estimating Quadratic Effects in Nonlinear Structural Equation Models

ERIC Educational Resources Information Center

Harring, Jeffrey R.; Weiss, Brandi A.; Hsu, Jui-Chen

2012-01-01

Two Monte Carlo simulations were performed to compare methods for estimating and testing hypotheses of quadratic effects in latent variable regression models. The methods considered in the current study were (a) a 2-stage moderated regression approach using latent variable scores, (b) an unconstrained product indicator approach, (c) a latent…

A National Primer on K-12 Online Learning

ERIC Educational Resources Information Center

Watson, John F.

2007-01-01

Online learning is growing rapidly across the United States within all levels of education, as more and more students and educators become familiar with the benefits of learning unconstrained by time and place. Across most states and all grade levels, students are finding increased opportunity, flexibility, and convenience through online learning.…

Application of real-time cooperative editing in urban planning management system

NASA Astrophysics Data System (ADS)

Jing, Changfeng; Liu, Renyi; Liu, Nan; Bao, Weizheng

2007-06-01

With the increasing of business requirement of urban planning bureau, co-edit function is needed urgently, however conventional GIS are not support this. In order to overcome this limitation, a new kind urban 1planning management system with co-edit function is needed. Such a system called PM2006 has been used in Suzhou Urban Planning Bureau. PM2006 is introduced in this paper. In this paper, four main issues of Co-edit system--consistency, responsiveness time, data recoverability and unconstrained operation--were discussed. And for these four questions, resolutions were put forward in paper. To resolve these problems of co-edit GIS system, a data model called FGDB (File and ESRI GeoDatabase) that is mixture architecture of File and ESRI Geodatabase was introduced here. The main components of FGDB data model are ESRI versioned Geodatabase and replicated architecture. With FGDB, client responsiveness, spatial data recoverability and unconstrained operation were overcome. In last of paper, MapServer, the co-edit map server module, is presented. Main functions of MapServer are operation serialization and spatial data replication between file and versioned data.

Fitting Nonlinear Curves by use of Optimization Techniques

NASA Technical Reports Server (NTRS)

Hill, Scott A.

2005-01-01

MULTIVAR is a FORTRAN 77 computer program that fits one of the members of a set of six multivariable mathematical models (five of which are nonlinear) to a multivariable set of data. The inputs to MULTIVAR include the data for the independent and dependent variables plus the user s choice of one of the models, one of the three optimization engines, and convergence criteria. By use of the chosen optimization engine, MULTIVAR finds values for the parameters of the chosen model so as to minimize the sum of squares of the residuals. One of the optimization engines implements a routine, developed in 1982, that utilizes the Broydon-Fletcher-Goldfarb-Shanno (BFGS) variable-metric method for unconstrained minimization in conjunction with a one-dimensional search technique that finds the minimum of an unconstrained function by polynomial interpolation and extrapolation without first finding bounds on the solution. The second optimization engine is a faster and more robust commercially available code, denoted Design Optimization Tool, that also uses the BFGS method. The third optimization engine is a robust and relatively fast routine that implements the Levenberg-Marquardt algorithm.

On Applicability of Tunable Filter Bank Based Feature for Ear Biometrics: A Study from Constrained to Unconstrained.

PubMed

Chowdhury, Debbrota Paul; Bakshi, Sambit; Guo, Guodong; Sa, Pankaj Kumar

2017-11-27

In this paper, an overall framework has been presented for person verification using ear biometric which uses tunable filter bank as local feature extractor. The tunable filter bank, based on a half-band polynomial of 14th order, extracts distinct features from ear images maintaining its frequency selectivity property. To advocate the applicability of tunable filter bank on ear biometrics, recognition test has been performed on available constrained databases like AMI, WPUT, IITD and unconstrained database like UERC. Experiments have been conducted applying tunable filter based feature extractor on subparts of the ear. Empirical experiments have been conducted with four and six subdivisions of the ear image. Analyzing the experimental results, it has been found that tunable filter moderately succeeds to distinguish ear features at par with the state-of-the-art features used for ear recognition. Accuracies of 70.58%, 67.01%, 81.98%, and 57.75% have been achieved on AMI, WPUT, IITD, and UERC databases through considering Canberra Distance as underlying measure of separation. The performances indicate that tunable filter is a candidate for recognizing human from ear images.

Outcomes of Medial Collateral Ligament Injuries during Total Knee Arthroplasty.

PubMed

Siqueira, Marcelo B P; Haller, Kathryn; Mulder, Andrew; Goldblum, Andrew S; Klika, Alison K; Barsoum, Wael K

2016-01-01

Intraoperative medial collateral ligament (MCL) disruption during total knee arthroplasty (TKA) is often managed with either primary repair or use of a constrained implant. A total of 23 patients with an MCL injury during TKA between 2003 and 2009 were compared with 92 matched controls. Of the 23 patients, 10 were treated with an unconstrained implant and primary MCL repair, 8 with constrained implants, 3 with constrained implants and MCL repair, and 2 with unconstrained implants and no MCL repair. After an average 5-year follow-up, patients had lower Knee Society Scores (KSS), 79 versus 87 (p = 0.03), but similar Knee Function Scores (KFS), 68 versus 72 (p = 0.35). The improvement between preoperative and postoperative KSS and KFS did not vary among the two groups (p = 0.88 and p = 0.77, respectively). Postoperative scores did not vary significantly among the four treatment modalities. Conservative treatment can provide satisfactory outcomes and avoid potential complications of increased constraint. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Imaging Brain Function with Functional Near-Infrared Spectroscopy in Unconstrained Environments.

PubMed

Balardin, Joana B; Zimeo Morais, Guilherme A; Furucho, Rogério A; Trambaiolli, Lucas; Vanzella, Patricia; Biazoli, Claudinei; Sato, João R

2017-01-01

Assessing the neural correlates of motor and cognitive processes under naturalistic experimentation is challenging due to the movement constraints of traditional brain imaging technologies. The recent advent of portable technologies that are less sensitive to motion artifacts such as Functional Near Infrared Spectroscopy (fNIRS) have been made possible the study of brain function in freely-moving participants. In this paper, we describe a series of proof-of-concept experiments examining the potential of fNIRS in assessing the neural correlates of cognitive and motor processes in unconstrained environments. We show illustrative applications for practicing a sport (i.e., table tennis), playing a musical instrument (i.e., piano and violin) alone or in duo and performing daily activities for many hours (i.e., continuous monitoring). Our results expand upon previous research on the feasibility and robustness of fNIRS to monitor brain hemodynamic changes in different real life settings. We believe that these preliminary results showing the flexibility and robustness of fNIRS measurements may contribute by inspiring future work in the field of applied neuroscience.

Imaging Brain Function with Functional Near-Infrared Spectroscopy in Unconstrained Environments

PubMed Central

Balardin, Joana B.; Zimeo Morais, Guilherme A.; Furucho, Rogério A.; Trambaiolli, Lucas; Vanzella, Patricia; Biazoli, Claudinei; Sato, João R.

2017-01-01

Assessing the neural correlates of motor and cognitive processes under naturalistic experimentation is challenging due to the movement constraints of traditional brain imaging technologies. The recent advent of portable technologies that are less sensitive to motion artifacts such as Functional Near Infrared Spectroscopy (fNIRS) have been made possible the study of brain function in freely-moving participants. In this paper, we describe a series of proof-of-concept experiments examining the potential of fNIRS in assessing the neural correlates of cognitive and motor processes in unconstrained environments. We show illustrative applications for practicing a sport (i.e., table tennis), playing a musical instrument (i.e., piano and violin) alone or in duo and performing daily activities for many hours (i.e., continuous monitoring). Our results expand upon previous research on the feasibility and robustness of fNIRS to monitor brain hemodynamic changes in different real life settings. We believe that these preliminary results showing the flexibility and robustness of fNIRS measurements may contribute by inspiring future work in the field of applied neuroscience. PMID:28567011

Positron annihilation lifetime study of polyvinylpyrrolidone for nanoparticle-stabilizing pharmaceuticals.

PubMed

Shpotyuk, O; Bujňáková, Z; Baláž, P; Ingram, A; Shpotyuk, Y

2016-01-05

Positron annihilation lifetime spectroscopy was applied to characterize free-volume structure of polyvinylpyrrolidone used as nonionic stabilizer in the production of many nanocomposite pharmaceuticals. The polymer samples with an average molecular weight of 40,000 g mol(-1) were pelletized in a single-punch tableting machine under an applied pressure of 0.7 GPa. Strong mixing in channels of positron and positronium trapping were revealed in the polyvinylpyrrolidone pellets. The positron lifetime spectra accumulated under normal measuring statistics were analysed in terms of unconstrained three- and four-term decomposition, the latter being also realized under fixed 0.125 ns lifetime proper to para-positronium self-annihilation in a vacuum. It was shown that average positron lifetime extracted from each decomposition was primary defined by long-lived ortho-positronium component. The positron lifetime spectra treated within unconstrained three-term fitting were in obvious preference, giving third positron lifetime dominated by ortho-positronium pick-off annihilation in a polymer matrix. This fitting procedure was most meaningful, when analysing expected positron trapping sites in polyvinylpyrrolidone-stabilized nanocomposite pharmaceuticals. Copyright © 2015 Elsevier B.V. All rights reserved.

On the evolution of cured voxel in bulk photopolymerization upon focused Gaussian laser exposure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bhole, Kiran, E-mail: kirandipali@gmail.com; Gandhi, Prasanna; Kundu, T.

Unconstrained depth photopolymerization is emerging as a promising technique for fabrication of several polymer microstructures such as self propagating waveguides, 3D freeform structures by bulk lithography, and polymer nanoparticles by flash exposure. Experimental observations reveal governing physics beyond Beer Lambert's law and scattering effects. This paper seeks to model unconstrained depth photopolymerization using classical nonlinear Schrödinger equation coupled with transient diffusion phenomenon. The beam propagation part of the proposed model considers scattering effects induced due to spatial variation of the refractive index as a function of the beam intensity. The critical curing energy model is used to further predict profilemore » of polymerized voxel. Profiles of photopolymerized voxel simulated using proposed model are compared with the corresponding experimental results for several cases of exposure dose and duration. The comparison shows close match leading to conclusion that the experimentally observed deviation from Beer Lambert's law is indeed due to combined effect of diffusion of photoinitiator and scattering of light because of change in the refractive index.« less

Automatic attention-based prioritization of unconstrained video for compression

NASA Astrophysics Data System (ADS)

Itti, Laurent

2004-06-01

We apply a biologically-motivated algorithm that selects visually-salient regions of interest in video streams to multiply-foveated video compression. Regions of high encoding priority are selected based on nonlinear integration of low-level visual cues, mimicking processing in primate occipital and posterior parietal cortex. A dynamic foveation filter then blurs (foveates) every frame, increasingly with distance from high-priority regions. Two variants of the model (one with continuously-variable blur proportional to saliency at every pixel, and the other with blur proportional to distance from three independent foveation centers) are validated against eye fixations from 4-6 human observers on 50 video clips (synthetic stimuli, video games, outdoors day and night home video, television newscast, sports, talk-shows, etc). Significant overlap is found between human and algorithmic foveations on every clip with one variant, and on 48 out of 50 clips with the other. Substantial compressed file size reductions by a factor 0.5 on average are obtained for foveated compared to unfoveated clips. These results suggest a general-purpose usefulness of the algorithm in improving compression ratios of unconstrained video.

Adaptive 3D Face Reconstruction from Unconstrained Photo Collections.

PubMed

Roth, Joseph; Tong, Yiying; Liu, Xiaoming

2016-12-07

Given a photo collection of "unconstrained" face images of one individual captured under a variety of unknown pose, expression, and illumination conditions, this paper presents a method for reconstructing a 3D face surface model of the individual along with albedo information. Unlike prior work on face reconstruction that requires large photo collections, we formulate an approach to adapt to photo collections with a high diversity in both the number of images and the image quality. To achieve this, we incorporate prior knowledge about face shape by fitting a 3D morphable model to form a personalized template, following by using a novel photometric stereo formulation to complete the fine details, under a coarse-to-fine scheme. Our scheme incorporates a structural similarity-based local selection step to help identify a common expression for reconstruction while discarding occluded portions of faces. The evaluation of reconstruction performance is through a novel quality measure, in the absence of ground truth 3D scans. Superior large-scale experimental results are reported on synthetic, Internet, and personal photo collections.

Unconstrained Enhanced Sampling for Free Energy Calculations of Biomolecules: A Review

PubMed Central

Miao, Yinglong; McCammon, J. Andrew

2016-01-01

Free energy calculations are central to understanding the structure, dynamics and function of biomolecules. Yet insufficient sampling of biomolecular configurations is often regarded as one of the main sources of error. Many enhanced sampling techniques have been developed to address this issue. Notably, enhanced sampling methods based on biasing collective variables (CVs), including the widely used umbrella sampling, adaptive biasing force and metadynamics, have been discussed in a recent excellent review (Abrams and Bussi, Entropy, 2014). Here, we aim to review enhanced sampling methods that do not require predefined system-dependent CVs for biomolecular simulations and as such do not suffer from the hidden energy barrier problem as encountered in the CV-biasing methods. These methods include, but are not limited to, replica exchange/parallel tempering, self-guided molecular/Langevin dynamics, essential energy space random walk and accelerated molecular dynamics. While it is overwhelming to describe all details of each method, we provide a summary of the methods along with the applications and offer our perspectives. We conclude with challenges and prospects of the unconstrained enhanced sampling methods for accurate biomolecular free energy calculations. PMID:27453631

Unconstrained Enhanced Sampling for Free Energy Calculations of Biomolecules: A Review.

PubMed

Miao, Yinglong; McCammon, J Andrew

Free energy calculations are central to understanding the structure, dynamics and function of biomolecules. Yet insufficient sampling of biomolecular configurations is often regarded as one of the main sources of error. Many enhanced sampling techniques have been developed to address this issue. Notably, enhanced sampling methods based on biasing collective variables (CVs), including the widely used umbrella sampling, adaptive biasing force and metadynamics, have been discussed in a recent excellent review (Abrams and Bussi, Entropy, 2014). Here, we aim to review enhanced sampling methods that do not require predefined system-dependent CVs for biomolecular simulations and as such do not suffer from the hidden energy barrier problem as encountered in the CV-biasing methods. These methods include, but are not limited to, replica exchange/parallel tempering, self-guided molecular/Langevin dynamics, essential energy space random walk and accelerated molecular dynamics. While it is overwhelming to describe all details of each method, we provide a summary of the methods along with the applications and offer our perspectives. We conclude with challenges and prospects of the unconstrained enhanced sampling methods for accurate biomolecular free energy calculations.

Wear characteristics of an unconstrained lumbar total disc replacement under a range of in vitro test conditions

PubMed Central

Fisher, John; Hall, Richard M.

2015-01-01

Abstract The effect of kinematics, loading and centre of rotation on the wear of an unconstrained total disc replacement have been investigated using the ISO 18192‐1 standard test as a baseline. Mean volumetric wear rate and surface morphological effects were reported. Changing the phasing of the flexions to create a low (but finite) amount of crossing path motion at the bearing surfaces resulted in a significant fall in wear volume. However, the rate of wear was still much larger than previously reported values under zero cross shear conditions. Reducing the load did not result in a significant change in wear rate. Moving the centre of rotation of the disc inferiorly did significantly increase wear rate. A phenomenon of debris re‐attachment on the UHMWPE surface was observed and hypothesised to be due to a relatively harsh tribological operating regime in which lubricant replenishment and particle migration out of the bearing contact zone were limited. © 2015 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 105B: 46–52, 2017. PMID:26411540

An experience sampling study of learning, affect, and the demands control support model.

PubMed

Daniels, Kevin; Boocock, Grahame; Glover, Jane; Holland, Julie; Hartley, Ruth

2009-07-01

The demands control support model (R. A. Karasek & T. Theorell, 1990) indicates that job control and social support enable workers to engage in problem solving. In turn, problem solving is thought to influence learning and well-being (e.g., anxious affect, activated pleasant affect). Two samples (N = 78, N = 106) provided data up to 4 times per day for up to 5 working days. The extent to which job control was used for problem solving was assessed by measuring the extent to which participants changed aspects of their work activities to solve problems. The extent to which social support was used to solve problems was assessed by measuring the extent to which participants discussed problems to solve problems. Learning mediated the relationship between changing aspects of work activities to solve problems and activated pleasant affect. Learning also mediated the relationship between discussing problems to solve problems and activated pleasant affect. The findings indicated that how individuals use control and support to respond to problem-solving demands is associated with organizational and individual phenomena, such as learning and affective well-being.

Informal schooling and problem-solving skills in second-grade science: A naturalistic investigation

NASA Astrophysics Data System (ADS)

Griffin, Georgia Inez Hunt

The influence of informal schooling on the problem solving skills of urban elementary school children is unclear. The relationship between culture and problem solving can be studied using subjective methodologies, particularly when investigating problem solving strategies that are culturally situated. Yet, little research has been conducted to investigate how informal learning of African American children are integrated as part of the problem solving used in school. This study has been designed to expand the existing literature in this area. The purpose of this study is therefore to explore how 15 African American children attending school in Southwest Philadelphia solve problems presented to them in second grade science. This was accomplished by assessing their ability to observe, classify, recall, and perceive space/time relationships. Think-aloud protocols were used for this examination. A naturalistic approach to the investigation was implemented. Individual children were selected because he or she exhibited unique and subjective characteristics associated with individual approaches to problem solving. Children responded to three tasks: interviews of their parents, an essay on community gardens, and a group diorama collaboratively designed. Content analysis was used to infer themes that were evident in the children's work and that revealed the extent to which informal schooling influenced solutions to a community garden problem. The investigations did increase the researcher's ability to understand and build upon the understanding of African American children in their indigenous community. The study also demonstrated how these same strategies can be used to involve parents in the science curriculum. Additionally, the researcher gained insight on how to bridge the gap between home, community, and school.

Comparison between Different Methods for Biomechanical Assessment of Ex Vivo Fracture Callus Stiffness in Small Animal Bone Healing Studies

PubMed Central

Steiner, Malte; Volkheimer, David; Meyers, Nicholaus; Wehner, Tim; Wilke, Hans-Joachim; Claes, Lutz; Ignatius, Anita

2015-01-01

For ex vivo measurements of fracture callus stiffness in small animals, different test methods, such as torsion or bending tests, are established. Each method provides advantages and disadvantages, and it is still debated which of those is most sensitive to experimental conditions (i.e. specimen alignment, directional dependency, asymmetric behavior). The aim of this study was to experimentally compare six different testing methods regarding their robustness against experimental errors. Therefore, standardized specimens were created by selective laser sintering (SLS), mimicking size, directional behavior, and embedding variations of respective rat long bone specimens. For the latter, five different geometries were created which show shifted or tilted specimen alignments. The mechanical tests included three-point bending, four-point bending, cantilever bending, axial compression, constrained torsion, and unconstrained torsion. All three different bending tests showed the same principal behavior. They were highly dependent on the rotational direction of the maximum fracture callus expansion relative to the loading direction (creating experimental errors of more than 60%), however small angular deviations (<15°) were negligible. Differences in the experimental results between the bending tests originate in their respective location of maximal bending moment induction. Compared to four-point bending, three-point bending is easier to apply on small rat and mouse bones under realistic testing conditions and yields robust measurements, provided low variation of the callus shape among the tested specimens. Axial compressive testing was highly sensitive to embedding variations, and therefore cannot be recommended. Although it is experimentally difficult to realize, unconstrained torsion testing was found to be the most robust method, since it was independent of both rotational alignment and embedding uncertainties. Constrained torsional testing showed small errors (up to 16.8%, compared to corresponding alignment under unconstrained torsion) due to a parallel offset between the specimens’ axis of gravity and the torsional axis of rotation. PMID:25781027

Effectiveness of a passive-active vibration isolation system with actuator constraints

NASA Astrophysics Data System (ADS)

Sun, Lingling; Sun, Wei; Song, Kongjie; Hansen, Colin H.

2014-05-01

In the prediction of active vibration isolation performance, control force requirements were ignored in previous work. This may limit the realization of theoretically predicted isolation performance if control force of large magnitude cannot be supplied by actuators. The behavior of a feed-forward active isolation system subjected to actuator output constraints is investigated. Distributed parameter models are developed to analyze the system response, and to produce a transfer matrix for the design of an integrated passive-active isolation system. Cost functions comprising a combination of the vibration transmission energy and the sum of the squared control forces are proposed. The example system considered is a rigid body connected to a simply supported plate via two passive-active isolation mounts. Vertical and transverse forces as well as a rotational moment are applied at the rigid body, and resonances excited in elastic mounts and the supporting plate are analyzed. The overall isolation performance is evaluated by numerical simulation. The simulation results are then compared with those obtained using unconstrained control strategies. In addition, the effects of waves in elastic mounts are analyzed. It is shown that the control strategies which rely on unconstrained actuator outputs may give substantial power transmission reductions over a wide frequency range, but also require large control force amplitudes to control excited vibration modes of the system. Expected power transmission reductions for modified control strategies that incorporate constrained actuator outputs are considerably less than typical reductions with unconstrained actuator outputs. In the frequency range in which rigid body modes are present, the control strategies can only achieve 5-10 dB power transmission reduction, when control forces are constrained to be the same order of the magnitude as the primary vertical force. The resonances of the elastic mounts result in a notable increase of power transmission in high frequency range and cannot be attenuated by active control. The investigation provides a guideline for design and evaluation of active vibration isolation systems.

Too Long, Too Short, or Too Variable? Sleep Intraindividual Variability and Its Associations With Perceived Sleep Quality and Mood in Adolescents During Naturalistically Unconstrained Sleep.

PubMed

Bei, Bei; Manber, Rachel; Allen, Nicholas B; Trinder, John; Wiley, Joshua F

2017-02-01

Research has extensively examined the relationship between adolescents' mental health and average sleep duration/quality. Using rigorous methodology, this study characterized adolescents' objective sleep intraindividual variability (IIV) and examined its role on mood beyond the effects of their respective individual mean (IIM) values. One hundred forty-six community-dwelling adolescents (47.3% male) aged 16.2 ± 1.0 (M ± SD) years wore an actigraph that assessed bedtime, risetime, time-in-bed (TIB), and sleep onset latency (SOL) throughout a 15-day vacation with relatively unconstrained sleep opportunity. Self-report sleep quality (SSQ), negative mood (MOOD), and other covariates were assessed using questionnaires. For each sleep variable, individuals' mean values (IIM) and IIV were used to simultaneously predict MOOD with SSQ as a mediator. Models were estimated in a Bayesian IIV framework; both linear and quadratic effects of the IIM and IIV were examined. Longer and more variable TIB, as well as more variable SOL (but not mean SOL), were associated with poorer SSQ (ps < .01), which in turn, was associated with more negative MOOD (ps < .05). The indirect effect of SOL IIV was curvilinear, such that as SOL became more variable, the deteriorating effect of high SOL IIV accelerated. Neither bedtime nor risetime IIV was significantly associated with SSQ or MOOD. During relatively unconstrained sleep opportunity, more variable TIB and SOL were associated with more negative mood, mediated by poorer perceived sleep quality. Significant effects of IIV were over and above that of mean values, suggesting that unique aspects of sleep IIV are relevant to how adolescents perceive sleep quality and their mood. © Sleep Research Society 2016. Published by Oxford University Press on behalf of the Sleep Research Society. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.

Muscle activity and head kinematics in unconstrained movements in subjects with chronic neck pain; cervical motor dysfunction or low exertion motor output?

PubMed

Vikne, Harald; Bakke, Eva Sigrid; Liestøl, Knut; Engen, Stian R; Vøllestad, Nina

2013-11-04

Chronic neck pain after whiplash associated disorders (WAD) may lead to reduced displacement and peak velocity of neck movements. Dynamic neck movements in people with chronic WAD are also reported to display altered movement patterns such as increased irregularity, which is suggested to signify impaired motor control. As movement irregularity is strongly related to the velocity and displacement of movement, we wanted to examine whether the increased irregularity in chronic WAD could be accounted for by these factors. Head movements were completed in four directions in the sagittal plane at three speeds; slow (S), preferred (P) and maximum (M) in 15 men and women with chronic WAD and 15 healthy, sex and age-matched control participants. Head kinematics and measures of movement smoothness and symmetry were calculated from position data. Surface electromyography (EMG) was recorded bilaterally from the sternocleidomastoid and splenius muscles and the root mean square (rms) EMG amplitude for the accelerative and decelerative phases of movement were analyzed. The groups differed significantly with regard to movement velocity, acceleration, displacement, smoothness and rmsEMG amplitude in agonist and antagonist muscles for a series of comparisons across the test conditions (range 17-121%, all p-values < 0.05). The group differences in peak movement velocity and acceleration persisted after controlling for movement displacement. Controlling for differences between the groups in displacement and velocity abolished the difference in measures of movement smoothness and rmsEMG amplitude. Simple, unconstrained head movements in participants with chronic WAD are accomplished with reduced velocity and displacement, but with normal muscle activation levels and movement patterns for a given velocity and displacement. We suggest that while reductions in movement velocity and displacement are robust changes and may be of clinical importance in chronic WAD, movement smoothness of unconstrained head movements is not.

Effects of "Handep" Cooperative Learning Based on Indigenous Knowledge on Mathematical Problem Solving Skill

ERIC Educational Resources Information Center

Demitra; Sarjoko

2018-01-01

Indigenous people of Dayak tribe in Kalimantan, Indonesia have traditionally relied on a system of mutual cooperation called "handep." The cultural context has an influence on students mathematics learning. The "handep" system might be suitable for modern learning situations to develop mathematical problem-solving skill. The…

Influence of Family Processes, Motivation, and Beliefs about Intelligence on Creative Problem Solving of Scientifically Talented Individuals

ERIC Educational Resources Information Center

Cho, Seokhee; Lin, Chia-Yi

2011-01-01

Predictive relationships among perceived family processes, intrinsic and extrinsic motivation, incremental beliefs about intelligence, confidence in intelligence, and creative problem-solving practices in mathematics and science were examined. Participants were 733 scientifically talented Korean students in fourth through twelfth grades as well as…

Learning on the Job: Cooperative Education, Internships and Engineering Problem-Solving Skills

ERIC Educational Resources Information Center

Yin, Alexander C.

2009-01-01

Cooperative education (co-op) and internships are forms of experiential education that allow students to complement their classroom experiences with work experience. This study examines the influence of co-op and internships on engineering problem-solving skills by answering the following research questions: (1) Does experience in cooperative…

Problem Solving and Emotional Education in Initial Primary Teacher Education

ERIC Educational Resources Information Center

Caballero, Ana; Blanco, Lorenzo J.; Guerrero, Eloisa

2011-01-01

Our work is based on two premises. The first is that affective factors (beliefs, attitudes, and emotions) influence teaching and learning mathematics, and problem solving in particular. The second is that initial teacher education is an important element in the process of improving overall educational practice. On this basis, our research group…

The Effect of Contextual and Conceptual Rewording on Mathematical Problem-Solving Performance

ERIC Educational Resources Information Center

Haghverdi, Majid; Wiest, Lynda R.

2016-01-01

This study shows how separate and combined contextual and conceptual problem rewording can positively influence student performance in solving mathematical word problems. Participants included 80 seventh-grade Iranian students randomly assigned in groups of 20 to three experimental groups involving three types of rewording and a control group. All…

Computer-Based Assessment of Complex Problem Solving: Concept, Implementation, and Application

ERIC Educational Resources Information Center

Greiff, Samuel; Wustenberg, Sascha; Holt, Daniel V.; Goldhammer, Frank; Funke, Joachim

2013-01-01

Complex Problem Solving (CPS) skills are essential to successfully deal with environments that change dynamically and involve a large number of interconnected and partially unknown causal influences. The increasing importance of such skills in the 21st century requires appropriate assessment and intervention methods, which in turn rely on adequate…

An Alternative Time for Telling: When Conceptual Instruction Prior to Problem Solving Improves Mathematical Knowledge

ERIC Educational Resources Information Center

Fyfe, Emily R.; DeCaro, Marci S.; Rittle-Johnson, Bethany

2014-01-01

Background: The sequencing of learning materials greatly influences the knowledge that learners construct. Recently, learning theorists have focused on the sequencing of instruction in relation to solving related problems. The general consensus suggests explicit instruction should be provided; however, when to provide instruction remains unclear.…

Testing problem-solving capacities: differences between individual testing and social group setting.

PubMed

Krasheninnikova, Anastasia; Schneider, Jutta M

2014-09-01

Testing animals individually in problem-solving tasks limits distractions of the subjects during the test, so that they can fully concentrate on the problem. However, such individual performance may not indicate the problem-solving capacity that is commonly employed in the wild when individuals are faced with a novel problem in their social groups, where the presence of a conspecific influences an individual's behaviour. To assess the validity of data gathered from parrots when tested individually, we compared the performance on patterned-string tasks among parrots tested singly and parrots tested in social context. We tested two captive groups of orange-winged amazons (Amazona amazonica) with several patterned-string tasks. Despite the differences in the testing environment (singly vs. social context), parrots from both groups performed similarly. However, we found that the willingness to participate in the tasks was significantly higher for the individuals tested in social context. The study provides further evidence for the crucial influence of social context on individual's response to a challenging situation such as a problem-solving test.

Influence of central set on anticipatory and triggered grip-force adjustments

NASA Technical Reports Server (NTRS)

Winstein, C. J.; Horak, F. B.; Fisher, B. E.; Peterson, B. W. (Principal Investigator)

2000-01-01

The effects of predictability of load magnitude on anticipatory and triggered grip-force adjustments were studied as nine normal subjects used a precision grip to lift, hold, and replace an instrumented test object. Experience with a predictable stimulus has been shown to enhance magnitude scaling of triggered postural responses to different amplitudes of perturbations. However, this phenomenon, known as a central-set effect, has not been tested systematically for grip-force responses in the hand. In our study, predictability was manipulated by applying load perturbations of different magnitudes to the test object under conditions in which the upcoming load magnitude was presented repeatedly or under conditions in which the load magnitudes were presented randomly, each with two different pre-load grip conditions (unconstrained and constrained). In constrained conditions, initial grip forces were maintained near the minimum level necessary to prevent pre-loaded object slippage, while in unconstrained conditions, no initial grip force restrictions were imposed. The effect of predictable (blocked) and unpredictable (random) load presentations on scaling of anticipatory and triggered grip responses was tested by comparing the slopes of linear regressions between the imposed load and grip response magnitude. Anticipatory and triggered grip force responses were scaled to load magnitude in all conditions. However, regardless of pre-load grip force constraint, the gains (slopes) of grip responses relative to load magnitudes were greater when the magnitude of the upcoming load was predictable than when the load increase was unpredictable. In addition, a central-set effect was evidenced by the fewer number of drop trials in the predictable relative to unpredictable load conditions. Pre-load grip forces showed the greatest set effects. However, grip responses showed larger set effects, based on prediction, when pre-load grip force was constrained to lower levels. These results suggest that anticipatory processes pertaining to load magnitude permit the response gain of both voluntary and triggered rapid grip force adjustments to be set, at least partially, prior to perturbation onset. Comparison of anticipatory set effects for reactive torque and lower extremity EMG postural responses triggered by surface translation perturbations suggests a more general rule governing anticipatory processes.

Impact of isoprene and HONO chemistry on ozone and OVOC formation in a semirural South Korean forest

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, Saewung; Kim, So-Young; Lee, Meehye

Rapid urbanization and economic development in East Asia in past decades has led to photochemical air pollution problems such as excess photochemical ozone and aerosol formation. Asian megacities such as Seoul, Tokyo, Shanghai, Gangzhou, and Beijing are surrounded by densely forested areas and recent research has consistently demonstrated the importance of biogenic volatile organic compounds from vegetation in determining oxidation capacity in the suburban Asian megacity regions. Uncertainties in constraining tropospheric oxidation capacity, dominated by hydroxyl radical concentrations, undermine our ability to assess regional photochemical air pollution problems. We present an observational dataset of CO, NOX, SO2, ozone, HONO, andmore » VOCs (anthropogenic and biogenic) from Taehwa Research Forest (TRF) near the Seoul Metropolitan Area (SMA) in early June 2012. The data show that TRF is influenced both by aged pollution and fresh BVOC emissions. With the dataset, we diagnose HOx (OH, HO2, and RO2) distributions calculated with the University of Washington Chemical Box Model (UWCM v 2.1). Uncertainty from unconstrained HONO sources and radical recycling processes highlighted in recent studies is examined using multiple model simulations with different model constraints. The results suggest that 1) different model simulation scenarios cause systematic differences in HOX distributions especially OH levels (up to 2.5 times) and 2) radical destruction (HO2+HO2 or HO2+RO2) could be more efficient than radical recycling (HO2+NO) especially in the afternoon. Implications of the uncertainties in radical chemistry are discussed with respect to ozone-VOC-NOX sensitivity and oxidation product formation rates. Overall, the VOC limited regime in ozone photochemistry is predicted but the degree of sensitivity can significantly vary depending on the model scenarios. The model results also suggest that RO2 levels are positively correlated with OVOCs production that is not routinely constrained by observations. These unconstrained OVOCs can cause higher than expected OH loss rates (missing OH reactivity) and secondary organic aerosol formation. The series of modeling experiments constrained by observations strongly urge observational constraint of the radical pool to enable precise understanding of regional photochemical pollution problems in the East Asian megacity region.« less

Enhancement of problem solving ability of high school students through learning with real engagement in active problem solving (REAPS) model on the concept of heat transfer

NASA Astrophysics Data System (ADS)

Yulindar, A.; Setiawan, A.; Liliawati, W.

2018-05-01

This study aims to influence the enhancement of problem solving ability before and after learning using Real Engagement in Active Problem Solving (REAPS) model on the concept of heat transfer. The research method used is quantitative method with 35 high school students in Pontianak as sample. The result of problem solving ability of students is obtained through the test in the form of 3 description questions. The instrument has tested the validity by the expert judgment and field testing that obtained the validity value of 0.84. Based on data analysis, the value of N-Gain is 0.43 and the enhancement of students’ problem solving ability is in medium category. This was caused of students who are less accurate in calculating the results of answers and they also have limited time in doing the questions given.

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

NASA Astrophysics Data System (ADS)

Lin, Geng; Guan, Jian; Feng, Huibin

2018-06-01

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

Refractive Thinking Profile In Solving Mathematical Problem Reviewed from Students Math Capability

NASA Astrophysics Data System (ADS)

Maslukha, M.; Lukito, A.; Ekawati, R.

2018-01-01

Refraction is a mental activity experienced by a person to make a decision through reflective thinking and critical thinking. Differences in mathematical capability have an influence on the difference of student’s refractive thinking processes in solving math problems. This descriptive research aims to generate a picture of refractive thinking of students in solving mathematical problems in terms of students’ math skill. Subjects in this study consisted of three students, namely students with high, medium, and low math skills based on mathematics capability test. Data collection methods used are test-based methods and interviews. After collected data is analyzed through three stages that are, condensing and displaying data, data display, and drawing and verifying conclusion. Results showed refractive thinking profiles of three subjects is different. This difference occurs at the planning and execution stage of the problem. This difference is influenced by mathematical capability and experience of each subject.

The effect of Missouri mathematics project learning model on students’ mathematical problem solving ability

NASA Astrophysics Data System (ADS)

Handayani, I.; Januar, R. L.; Purwanto, S. E.

2018-01-01

This research aims to know the influence of Missouri Mathematics Project Learning Model to Mathematical Problem-solving Ability of Students at Junior High School. This research is a quantitative research and uses experimental research method of Quasi Experimental Design. The research population includes all student of grade VII of Junior High School who are enrolled in the even semester of the academic year 2016/2017. The Sample studied are 76 students from experimental and control groups. The sampling technique being used is cluster sampling method. The instrument is consisted of 7 essay questions whose validity, reliability, difficulty level and discriminating power have been tested. Before analyzing the data by using t-test, the data has fulfilled the requirement for normality and homogeneity. The result of data shows that there is the influence of Missouri mathematics project learning model to mathematical problem-solving ability of students at junior high school with medium effect.

Real-time unconstrained object recognition: a processing pipeline based on the mammalian visual system.

PubMed

Aguilar, Mario; Peot, Mark A; Zhou, Jiangying; Simons, Stephen; Liao, Yuwei; Metwalli, Nader; Anderson, Mark B

2012-03-01

The mammalian visual system is still the gold standard for recognition accuracy, flexibility, efficiency, and speed. Ongoing advances in our understanding of function and mechanisms in the visual system can now be leveraged to pursue the design of computer vision architectures that will revolutionize the state of the art in computer vision.

Fixed-Choice Word-Association Tasks as Second-Language Lexical Tests: What Native-Speaker Performance Reveals about Their Potential Weaknesses

ERIC Educational Resources Information Center

Dronjic, Vedran; Helms-Park, Rena

2014-01-01

Qian and Schedl's Depth of Vocabulary Knowledge Test was administered to 31 native-speaker undergraduates under an "unconstrained" condition, in which the number of responses to headwords was unfixed, whereas a corresponding group ("n" = 36) completed the test under the original "constrained" condition. Results…

Towards Commanding Unmanned Ground Vehicle Movement in Unfamiliar Environments Using Unconstrained English: Initial Research Results

DTIC Science & Technology

2007-06-01

constrained list of command words could be valuable in many systems, as would the ability of driverless vehicles to navigate through a route...Sensemaking in UGVs • Future Combat Systems UGV roles – Driverless trucks – Robotic mules (soldier, squad aid) – Intelligent munitions – And more! • Some

[Tripolar cups].

PubMed

Fink, B

2015-04-01

Tripolar cups can be separated into constrained and unconstrained dual-mobility cups. The latter show better survival and revision rates. The main problem is the polyethylene wear. Therefore modern types of polyethylene are used in these cups. The indications for dual-mobility cups are recurrent dislocation and situations where the risk of dislocation is increased. Georg Thieme Verlag KG Stuttgart · New York.

Animal-Assisted Literacy: A Supportive Environment for Constrained and Unconstrained Learning

ERIC Educational Resources Information Center

Friesen, Lori; Delisle, Esther

2012-01-01

Over the last 20 years or so, the popularity of animal-assisted literacy learning programs has gained momentum in schools and libraries around the world (Intermountain Therapy Animals, 2011). To date, such programs are currently running in four Canadian provinces and 43 U.S. states, as well as in Australia, the United Kingdom, Italy, and India…

Stages in the Development of Children's Drawing.

ERIC Educational Resources Information Center

Dennis, Sonja I.

Case's cognitive developmental theory was used in an investigation of unconstrained drawings by children 4, 6, 8, and 10 years of age. The objectives were: (1) to look for qualitative changes in drawing at these ages, (2) to relate whatever changes were found to qualitative changes in other tasks during the same period, and (3) to test whether a…

Personality-dependent differences in problem-solving performance in a social context reflect foraging strategies.

PubMed

Zandberg, Lies; Quinn, John L; Naguib, Marc; van Oers, Kees

2017-01-01

Individuals develop innovative behaviours to solve foraging challenges in the face of changing environmental conditions. Little is known about how individuals differ in their tendency to solve problems and in their subsequent use of this solving behaviour in social contexts. Here we investigated whether individual variation in problem-solving performance could be explained by differences in the likelihood of solving the task, or if they reflect differences in foraging strategy. We tested this by studying the use of a novel foraging skill in groups of great tits (Parus major), consisting of three naive individuals with different personality, and one knowledgeable tutor. We presented them with multiple, identical foraging devices over eight trials. Though birds of different personality type did not differ in solving latency; fast and slow explorers showed a steeper increase over time in their solving rate, compared to intermediate explorers. Despite equal solving potential, personality influenced the subsequent use of the skill, as well as the pay-off received from solving. Thus, variation in the tendency to solve the task reflected differences in foraging strategy among individuals linked to their personality. These results emphasize the importance of considering the social context to fully understand the implications of learning novel skills. Copyright © 2016 Elsevier B.V. All rights reserved.

The Influence of Science Knowledge Structures on Children's Success in Solving Academic Problems.

ERIC Educational Resources Information Center

Champagne, Audrey B.; And Others

Presented is a study of eighth-grade students' academic problem-solving ability based on their knowledge structures, or their information stored in semantic or long-term memory. The authors describe a technique that they developed to probe knowledge structures with an extension of the card-sort method. The method, known as the Concept Structure…

Leisure Activities for the Development of Creative Intelligence in Mathematical Problem Solving

ERIC Educational Resources Information Center

Castro, Angélica Mercedes Tumbaco; Guerra, Galo Ernestro Cabanilla; Brito, Christian Antonio Pavón; Chávez, Tannia Gabriela Acosta

2018-01-01

The present work studies the influence of leisure activities on the creative intelligence of the students. An experimental pre- and post-test design was carried out with individuals selected in a sampling process. The design identifies the ease of students to place themselves in possible contexts and solve them mathematically through Polya's…

Studies of Visual Attention in Physics Problem Solving

ERIC Educational Resources Information Center

Madsen, Adrian M.

2013-01-01

The work described here represents an effort to understand and influence visual attention while solving physics problems containing a diagram. Our visual system is guided by two types of processes--top-down and bottom-up. The top-down processes are internal and determined by ones prior knowledge and goals. The bottom-up processes are external and…

Solving the Inverse-Square Problem with Complex Variables

ERIC Educational Resources Information Center

Gauthier, N.

2005-01-01

The equation of motion for a mass that moves under the influence of a central, inverse-square force is formulated and solved as a problem in complex variables. To find the solution, the constancy of angular momentum is first established using complex variables. Next, the complex position coordinate and complex velocity of the particle are assumed…

An Examination of Connections in Mathematical Processes in Students' Problem Solving: Connections between Representing and Justifying

ERIC Educational Resources Information Center

Stylianou, Despina A.

2013-01-01

Representation and justification are two central "mathematical practices". In the past, each has been examined to gain insights in the functions that they have in students' mathematical problem solving. Here, we examine the ways that representation and justification interact and influence the development of one another. We focus on the…

Prior Knowledge Influence on Self-Explanation Effectiveness when Solving Problems: An Exploratory Study in Science Learning

ERIC Educational Resources Information Center

Ionas, Ioan Gelu; Cernusca, Dan; Collier, Harvest L.

2012-01-01

This exploratory study presents the outcomes of using self-explanation to improve learners' performance in solving basic chemistry problems. The results of the randomized experiment show the existence of a moderation effect between prior knowledge and the level of support self-explanation provides to learners, suggestive of a synergistic effect…

Factors Influencing Filipino Children's Solutions to Addition and Subtraction Word Problems

ERIC Educational Resources Information Center

Bautista, Debbie; Mitchelmore, Michael; Mulligan, Joanne

2009-01-01

Young Filipino children are expected to solve mathematical word problems in English, which is not their mother tongue. Because of this, it is often assumed that Filipino children have difficulties in solving problems because they cannot read or comprehend what they have read. This study tested this assumption by determining whether presenting word…

Investigating the Influences of a LEAPS Model on Preservice Teachers' Problem Solving, Metacognition, and Motivation in an Educational Technology Course

ERIC Educational Resources Information Center

Lubin, Ian A.; Ge, Xun

2012-01-01

This paper discusses a qualitative study which examined students' problem-solving, metacognition, and motivation in a learning environment designed for teaching educational technology to pre-service teachers. The researchers converted a linear and didactic learning environment into a new open learning environment by contextualizing domain-related…

The Importance of Prior Knowledge when Comparing Examples: Influences on Conceptual and Procedural Knowledge of Equation Solving

ERIC Educational Resources Information Center

Rittle-Johnson, Bethany; Star, Jon R.; Durkin, Kelley

2009-01-01

Comparing multiple examples typically supports learning and transfer in laboratory studies and is considered a key feature of high-quality mathematics instruction. This experimental study investigated the importance of prior knowledge in learning from comparison. Seventh- and 8th-grade students (N = 236) learned to solve equations by comparing…

Hybrid genetic algorithm with an adaptive penalty function for fitting multimodal experimental data: application to exchange-coupled non-Kramers binuclear iron active sites.

PubMed

Beaser, Eric; Schwartz, Jennifer K; Bell, Caleb B; Solomon, Edward I

2011-09-26

A Genetic Algorithm (GA) is a stochastic optimization technique based on the mechanisms of biological evolution. These algorithms have been successfully applied in many fields to solve a variety of complex nonlinear problems. While they have been used with some success in chemical problems such as fitting spectroscopic and kinetic data, many have avoided their use due to the unconstrained nature of the fitting process. In engineering, this problem is now being addressed through incorporation of adaptive penalty functions, but their transfer to other fields has been slow. This study updates the Nanakorrn Adaptive Penalty function theory, expanding its validity beyond maximization problems to minimization as well. The expanded theory, using a hybrid genetic algorithm with an adaptive penalty function, was applied to analyze variable temperature variable field magnetic circular dichroism (VTVH MCD) spectroscopic data collected on exchange coupled Fe(II)Fe(II) enzyme active sites. The data obtained are described by a complex nonlinear multimodal solution space with at least 6 to 13 interdependent variables and are costly to search efficiently. The use of the hybrid GA is shown to improve the probability of detecting the global optimum. It also provides large gains in computational and user efficiency. This method allows a full search of a multimodal solution space, greatly improving the quality and confidence in the final solution obtained, and can be applied to other complex systems such as fitting of other spectroscopic or kinetics data.

Scope of Gradient and Genetic Algorithms in Multivariable Function Optimization

NASA Technical Reports Server (NTRS)

Shaykhian, Gholam Ali; Sen, S. K.

2007-01-01

Global optimization of a multivariable function - constrained by bounds specified on each variable and also unconstrained - is an important problem with several real world applications. Deterministic methods such as the gradient algorithms as well as the randomized methods such as the genetic algorithms may be employed to solve these problems. In fact, there are optimization problems where a genetic algorithm/an evolutionary approach is preferable at least from the quality (accuracy) of the results point of view. From cost (complexity) point of view, both gradient and genetic approaches are usually polynomial-time; there are no serious differences in this regard, i.e., the computational complexity point of view. However, for certain types of problems, such as those with unacceptably erroneous numerical partial derivatives and those with physically amplified analytical partial derivatives whose numerical evaluation involves undesirable errors and/or is messy, a genetic (stochastic) approach should be a better choice. We have presented here the pros and cons of both the approaches so that the concerned reader/user can decide which approach is most suited for the problem at hand. Also for the function which is known in a tabular form, instead of an analytical form, as is often the case in an experimental environment, we attempt to provide an insight into the approaches focusing our attention toward accuracy. Such an insight will help one to decide which method, out of several available methods, should be employed to obtain the best (least error) output. *

IN-SYNC. II. Virial Stars from Subvirial Cores—the Velocity Dispersion of Embedded Pre-main-sequence Stars in NGC 1333

NASA Astrophysics Data System (ADS)

Foster, Jonathan B.; Cottaar, Michiel; Covey, Kevin R.; Arce, Héctor G.; Meyer, Michael R.; Nidever, David L.; Stassun, Keivan G.; Tan, Jonathan C.; Chojnowski, S. Drew; da Rio, Nicola; Flaherty, Kevin M.; Rebull, Luisa; Frinchaboy, Peter M.; Majewski, Steven R.; Skrutskie, Michael; Wilson, John C.; Zasowski, Gail

2015-02-01

The initial velocity dispersion of newborn stars is a major unconstrained aspect of star formation theory. Using near-infrared spectra obtained with the APOGEE spectrograph, we show that the velocity dispersion of young (1-2 Myr) stars in NGC 1333 is 0.92 ± 0.12 km s-1 after correcting for measurement uncertainties and the effect of binaries. This velocity dispersion is consistent with the virial velocity of the region and the diffuse gas velocity dispersion, but significantly larger than the velocity dispersion of the dense, star-forming cores, which have a subvirial velocity dispersion of 0.5 km s-1. Since the NGC 1333 cluster is dynamically young and deeply embedded, this measurement provides a strong constraint on the initial velocity dispersion of newly formed stars. We propose that the difference in velocity dispersion between stars and dense cores may be due to the influence of a 70 μG magnetic field acting on the dense cores or be the signature of a cluster with initial substructure undergoing global collapse.

Isospin mixing reveals 30P(p, γ) 31S resonance influencing nova nucleosynthesis

DOE PAGES

Bennett, M. B.; Wrede, C.; Brown, B. A.; ...

2016-03-08

Here, the thermonuclear 30P(p, γ) 31S reaction rate is critical for modeling the final elemental and isotopic abundances of ONe nova nucleosynthesis, which affect the calibration of proposed nova thermometers and the identification of presolar nova grains, respectively. Unfortunately, the rate of this reaction is essentially unconstrained experimentally, because the strengths of key 31S proton capture resonance states are not known, largely due to uncertainties in their spins and parities. Using the β decay of 31Cl, we have observed the β-delayed γ decay of a 31S state at E x = 6390.2(7) keV, with a 30P(p, γ) 31S resonance energymore » of E r = 259.3(8) keV, in the middle of the 30P(p, γ) 31S Gamow window for peak nova temperatures. This state exhibits isospin mixing with the nearby isobaric analog state at E x = 6279.0(6) keV, giving it an unambiguous spin and parity of 3/2 + and making it an important l = 0 resonance for proton capture on 30P.« less

The ultraviolet radiation environment in the habitable zones around low-mass exoplanet host stars

NASA Astrophysics Data System (ADS)

France, Kevin; Linsky, Jeffrey L.; Loyd, R. O. Parke

2014-11-01

The EUV (200-911 Å), FUV (912-1750 Å), and NUV (1750-3200 Å) spectral energy distribution of exoplanet host stars has a profound influence on the atmospheres of Earth-like planets in the habitable zone. The stellar EUV radiation drives atmospheric heating, while the FUV (in particular, Ly α) and NUV radiation fields regulate the atmospheric chemistry: the dissociation of H2O and CO2, the production of O2 and O3, and may determine the ultimate habitability of these worlds. Despite the importance of this information for atmospheric modeling of exoplanetary systems, the EUV/FUV/NUV radiation fields of cool (K and M dwarf) exoplanet host stars are almost completely unconstrained by observation or theory. We present observational results from a Hubble Space Telescope survey of M dwarf exoplanet host stars, highlighting the importance of realistic UV radiation fields for the formation of potential biomarker molecules, O2 and O3. We conclude by describing preliminary results on the characterization of the UV time variability of these sources.

Self-Consistent Field Theory of Gaussian Ring Polymers

NASA Astrophysics Data System (ADS)

Kim, Jaeup; Yang, Yong-Biao; Lee, Won Bo

2012-02-01

Ring polymers, being free from chain ends, have fundamental importance in understanding the polymer statics and dynamics which are strongly influenced by the chain end effects. At a glance, their theoretical treatment may not seem particularly difficult, but the absence of chain ends and the topological constraints make the problem non-trivial, which results in limited success in the analytical or semi-analytical formulation of ring polymer theory. Here, I present a self-consistent field theory (SCFT) formalism of Gaussian (topologically unconstrained) ring polymers for the first time. The resulting static property of homogeneous and inhomogeneous ring polymers are compared with the random phase approximation (RPA) results. The critical point for ring homopolymer system is exactly the same as the linear polymer case, χN = 2, since a critical point does not depend on local structures of polymers. The critical point for ring diblock copolymer melts is χN 17.795, which is approximately 1.7 times of that of linear diblock copolymer melts, χN 10.495. The difference is due to the ring structure constraint.

Uncaring Nurses: Mobilizing Power, Knowledge, Difference, and Resistance to Explain Workplace Violence in Academia.

PubMed

Berquist, Renee; St-Pierre, Isabelle; Holmes, Dave

2018-05-01

Violence among nurses and in nursing academia is a significant issue, with attention increasingly focused on damage resulting from psychological violence, such as bullying, harassment, aggression, and incivility. Each workplace's interpretation of violence will impact individual behavior within the organization. Organizational and environmental factors can contribute to violent behaviors becoming normalized in the workplace. When violent behaviors go unconstrained, they become imbedded within the workplace culture. An increased understanding of workplace culture is required to address workplace violence. The purpose of this article is to demonstrate how the use of this theoretical framework can provide greater understanding of the role of workplace culture in sustaining violent behaviors in nursing academia. The theoretical perspectives of Gail Mason on interpersonal violence and Michel Foucault on power were utilized to inform the research process and guide data analysis. The framework makes possible the exposure of a dominant discourse perpetuating violence in nursing academia. Power and violence were found to work together to shape knowledge and influence group norms and behaviors. The framework is useful in providing greater understanding of how the concepts of power, knowledge, difference, and resistance support the enactment of workplace violence. Investigating the influence of these concepts in the development of accepted practices and discourses may allow greater insight into ways violence and power are used to negotiate and enforce organizational rules and norms.

Principles for Framing a Healthy Food System.

PubMed

Hamm, Michael W

2009-07-01

Wicked problems are most simply defined as ones that are impossible to solve. In other words, the range of complex interacting influences and effects; the influence of human values in all their range; and the constantly changing conditions in which the problem exists guarantee that what we strive to do is improve the situation rather than solve the wicked problem. This does not mean that we cannot move a long way toward resolving the problem but simply that there is no clean endpoint. This commentary outlines principles that could be used in moving us toward a healthy food system within the framework of it presenting as a wicked problem.

What Students Choose to Do and Have to Say about Use of Multiple Representations in College Algebra

ERIC Educational Resources Information Center

Herman, Marlena

2007-01-01

This report summarizes findings on strategies chosen by students (n=38) when solving algebra problems related to various functions with the freedom to use a TI-83 graphing calculator, influences on student problem-solving strategy choices, student ability to approach algebra problems with use of multiple representations, and student beliefs on how…

Exploring Factors of a Web-Based Seminar that Influence Hispanic Preservice Teachers' Critical Thinking and Problem-Solving Skills

ERIC Educational Resources Information Center

Garcia, Criselda G.; Hooper, H. H., Jr.

2011-01-01

The purpose of the qualitative study using a phenomenological approach was to gain insight of preservice teachers' experiences with a WebCT seminar designed to develop critical thinking and problem-solving skills in a Hispanic-Serving Institution's teacher education program. By applying a "holistic approach" to analyze data, NVivo software was…

The Computer-Based Assessment of Complex Problem Solving and How It Is Influenced by Students' Information and Communication Technology Literacy

ERIC Educational Resources Information Center

Greiff, Samuel; Kretzschmar, André; Müller, Jonas C.; Spinath, Birgit; Martin, Romain

2014-01-01

The 21st-century work environment places strong emphasis on nonroutine transversal skills. In an educational context, complex problem solving (CPS) is generally considered an important transversal skill that includes knowledge acquisition and its application in new and interactive situations. The dynamic and interactive nature of CPS requires a…

An Experience Sampling Study of Learning, Affect, and the Demands Control Support Model

ERIC Educational Resources Information Center

Daniels, Kevin; Boocock, Grahame; Glover, Jane; Hartley, Ruth; Holland, Julie

2009-01-01

The demands control support model (R. A. Karasek & T. Theorell, 1990) indicates that job control and social support enable workers to engage in problem solving. In turn, problem solving is thought to influence learning and well-being (e.g., anxious affect, activated pleasant affect). Two samples (N = 78, N = 106) provided data up to 4 times per…

How Partner Gender Influences Female Students' Problem Solving in Physics Education

NASA Astrophysics Data System (ADS)

Ding, N.; Harskamp, E.

2006-12-01

Research has shown that female students cannot profit as much as male students can from cooperative learning in physics, especially in mixed-gender dyads. This study has explored the influence of partner gender on female students' learning achievement, interaction and the problem-solving process during cooperative learning. In Shanghai, a total of 50 students (26 females and 24 males), drawn from two classes of a high school, took part in the study. Students were randomly paired, and there were three research groups: mixed-gender dyads (MG), female-female dyads (FF) and male-male dyads (MM). Analysis of students' pre- and post-test performances revealed that female students in the single-gender condition solved physics problems more effectively than did those in the mixed-gender condition, while the same was not the case for male students. We further explored the differences between female and male communication styles, and content among the three research groups. It showed that the females' interaction content and problem-solving processes were more sensitive to partner gender than were those for males. This might explain why mixed-gender cooperation in physics disadvantages females in high schools.

N =2 super Yang-Mills theory in projective superspace

NASA Astrophysics Data System (ADS)

Davgadorj, Ariunzul; von Unge, Rikard

2018-05-01

We find a formulation of N =2 supersymmetric Yang-Mills theory in projective superspace. In particular we find an expression for the field strength in terms of an unconstrained prepotential which is desirable when quantizing the theory. We use this to write the action in terms of the prepotential and show that it reduces to the known result in the Abelian limit.

Constrained and Unconstrained Localization for Automated Inspection of Marine Propellers

DTIC Science & Technology

1991-05-01

associated control polyhedron and hq, (0 < i < m - 1, 0 < j n - 1) are positive weights. B1 v(u) and Bj,’v) are the B-spline basis functions over open...Inspection by Database Matching. Technical Report CMU-RI-TR-85-4, The Robotics Institute, Carnegie Mellon University, March, 1985. Tuohy, S. T., Patrikalakis

Advanced Restricted Area Entry Control System (Araecs)

DTIC Science & Technology

2014-06-01

113  f.  Vascular Recognition ............................................................115  g.  Handwriting Recognition...independent (unconstrained mode). In a system using “text dependent” speech the individual will speak either a fixed password or prompted to say a...specific phrase (e.g. “Please say the following numbers 33, 45, 88”) (National Science and Technology Council 2006). A text independent system is more

Optimal lifting ascent trajectories for the space shuttle

NASA Technical Reports Server (NTRS)

Rau, T. R.; Elliott, J. R.

1972-01-01

The performance gains which are possible through the use of optimal trajectories for a particular space shuttle configuration are discussed. The spacecraft configurations and aerodynamic characteristics are described. Shuttle mission payload capability is examined with respect to the optimal orbit inclination for unconstrained, constrained, and nonlifting conditions. The effects of velocity loss and heating rate on the optimal ascent trajectory are investigated.

Petermann I and II spot size: Accurate semi analytical description involving Nelder-Mead method of nonlinear unconstrained optimization and three parameter fundamental modal field

NASA Astrophysics Data System (ADS)

Roy Choudhury, Raja; Roy Choudhury, Arundhati; Kanti Ghose, Mrinal

2013-01-01

A semi-analytical model with three optimizing parameters and a novel non-Gaussian function as the fundamental modal field solution has been proposed to arrive at an accurate solution to predict various propagation parameters of graded-index fibers with less computational burden than numerical methods. In our semi analytical formulation the optimization of core parameter U which is usually uncertain, noisy or even discontinuous, is being calculated by Nelder-Mead method of nonlinear unconstrained minimizations as it is an efficient and compact direct search method and does not need any derivative information. Three optimizing parameters are included in the formulation of fundamental modal field of an optical fiber to make it more flexible and accurate than other available approximations. Employing variational technique, Petermann I and II spot sizes have been evaluated for triangular and trapezoidal-index fibers with the proposed fundamental modal field. It has been demonstrated that, the results of the proposed solution identically match with the numerical results over a wide range of normalized frequencies. This approximation can also be used in the study of doped and nonlinear fiber amplifier.

Color object detection using spatial-color joint probability functions.

PubMed

Luo, Jiebo; Crandall, David

2006-06-01

Object detection in unconstrained images is an important image understanding problem with many potential applications. There has been little success in creating a single algorithm that can detect arbitrary objects in unconstrained images; instead, algorithms typically must be customized for each specific object. Consequently, it typically requires a large number of exemplars (for rigid objects) or a large amount of human intuition (for nonrigid objects) to develop a robust algorithm. We present a robust algorithm designed to detect a class of compound color objects given a single model image. A compound color object is defined as having a set of multiple, particular colors arranged spatially in a particular way, including flags, logos, cartoon characters, people in uniforms, etc. Our approach is based on a particular type of spatial-color joint probability function called the color edge co-occurrence histogram. In addition, our algorithm employs perceptual color naming to handle color variation, and prescreening to limit the search scope (i.e., size and location) for the object. Experimental results demonstrated that the proposed algorithm is insensitive to object rotation, scaling, partial occlusion, and folding, outperforming a closely related algorithm based on color co-occurrence histograms by a decisive margin.

Novel Mahalanobis-based feature selection improves one-class classification of early hepatocellular carcinoma.

PubMed

Thomaz, Ricardo de Lima; Carneiro, Pedro Cunha; Bonin, João Eliton; Macedo, Túlio Augusto Alves; Patrocinio, Ana Claudia; Soares, Alcimar Barbosa

2018-05-01

Detection of early hepatocellular carcinoma (HCC) is responsible for increasing survival rates in up to 40%. One-class classifiers can be used for modeling early HCC in multidetector computed tomography (MDCT), but demand the specific knowledge pertaining to the set of features that best describes the target class. Although the literature outlines several features for characterizing liver lesions, it is unclear which is most relevant for describing early HCC. In this paper, we introduce an unconstrained GA feature selection algorithm based on a multi-objective Mahalanobis fitness function to improve the classification performance for early HCC. We compared our approach to a constrained Mahalanobis function and two other unconstrained functions using Welch's t-test and Gaussian Data Descriptors. The performance of each fitness function was evaluated by cross-validating a one-class SVM. The results show that the proposed multi-objective Mahalanobis fitness function is capable of significantly reducing data dimensionality (96.4%) and improving one-class classification of early HCC (0.84 AUC). Furthermore, the results provide strong evidence that intensity features extracted at the arterial to portal and arterial to equilibrium phases are important for classifying early HCC.

A Method for Forecasting the Commercial Air Traffic Schedule in the Future

NASA Technical Reports Server (NTRS)

Long, Dou; Lee, David; Gaier, Eric; Johnson, Jesse; Kostiuk, Peter

1999-01-01

This report presents an integrated set of models that forecasts air carriers' future operations when delays due to limited terminal-area capacity are considered. This report models the industry as a whole, avoiding unnecessary details of competition among the carriers. To develop the schedule outputs, we first present a model to forecast the unconstrained flight schedules in the future, based on the assumption of rational behavior of the carriers. Then we develop a method to modify the unconstrained schedules, accounting for effects of congestion due to limited NAS capacities. Our underlying assumption is that carriers will modify their operations to keep mean delays within certain limits. We estimate values for those limits from changes in planned block times reflected in the OAG. Our method for modifying schedules takes many means of reducing the delays into considerations, albeit some of them indirectly. The direct actions include depeaking, operating in off-hours, and reducing hub airports'operations. Indirect actions include using secondary airports, using larger aircraft, and selecting new hub airports, which, we assume, have already been modeled in the FAA's TAF. Users of our suite of models can substitute an alternative forecast for the TAF.

Hydrological and biogeochemical constraints on terrestrial carbon cycle feedbacks

NASA Astrophysics Data System (ADS)

Mystakidis, Stefanos; Seneviratne, Sonia I.; Gruber, Nicolas; Davin, Edouard L.

2017-01-01

The feedbacks between climate, atmospheric CO2 concentration and the terrestrial carbon cycle are a major source of uncertainty in future climate projections with Earth systems models. Here, we use observation-based estimates of the interannual variations in evapotranspiration (ET), net biome productivity (NBP), as well as the present-day sensitivity of NBP to climate variations, to constrain globally the terrestrial carbon cycle feedbacks as simulated by models that participated in the fifth phase of the coupled model intercomparison project (CMIP5). The constraints result in a ca. 40% lower response of NBP to climate change and a ca. 30% reduction in the strength of the CO2 fertilization effect relative to the unconstrained multi-model mean. While the unconstrained CMIP5 models suggest an increase in the cumulative terrestrial carbon storage (477 PgC) in response to an idealized scenario of 1%/year atmospheric CO2 increase, the constraints imply a ca. 19% smaller change. Overall, the applied emerging constraint approach offers a possibility to reduce uncertainties in the projections of the terrestrial carbon cycle, which is a key determinant of the future trajectory of atmospheric CO2 concentration and resulting climate change.

The Advantages of Normalizing Electromyography to Ballistic Rather than Isometric or Isokinetic Tasks.

PubMed

Suydam, Stephen M; Manal, Kurt; Buchanan, Thomas S

2017-07-01

Isometric tasks have been a standard for electromyography (EMG) normalization stemming from anatomic and physiologic stability observed during contraction. Ballistic dynamic tasks have the benefit of eliciting maximum EMG signals for normalization, despite having the potential for greater signal variability. It is the purpose of this study to compare maximum voluntary isometric contraction (MVIC) to nonisometric tasks with increasing degrees of extrinsic variability, ie, joint range of motion, velocity, rate of contraction, etc., to determine if the ballistic tasks, which elicit larger peak EMG signals, are more reliable than the constrained MVIC. Fifteen subjects performed MVIC, isokinetic, maximum countermovement jump, and sprint tasks while EMG was collected from 9 muscles in the quadriceps, hamstrings, and lower leg. The results revealed the unconstrained ballistic tasks were more reliable compared to the constrained MVIC and isokinetic tasks for all triceps surae muscles. The EMG from sprinting was more reliable than the constrained cases for both the hamstrings and vasti. The most reliable EMG signals occurred when the body was permitted its natural, unconstrained motion. These results suggest that EMG is best normalized using ballistic tasks to provide the greatest within-subject reliability, which beneficially yield maximum EMG values.

The effect of imposing 'fractional abundance constraints' onto the multilayer perceptron for sub-pixel land cover classification

NASA Astrophysics Data System (ADS)

Heremans, Stien; Suykens, Johan A. K.; Van Orshoven, Jos

2016-02-01

To be physically interpretable, sub-pixel land cover fractions or abundances should fulfill two constraints, the Abundance Non-negativity Constraint (ANC) and the Abundance Sum-to-one Constraint (ASC). This paper focuses on the effect of imposing these constraints onto the MultiLayer Perceptron (MLP) for a multi-class sub-pixel land cover classification of a time series of low resolution MODIS-images covering the northern part of Belgium. Two constraining modes were compared, (i) an in-training approach that uses 'softmax' as the transfer function in the MLP's output layer and (ii) a post-training approach that linearly rescales the outputs of the unconstrained MLP. Our results demonstrate that the pixel-level prediction accuracy is markedly increased by the explicit enforcement, both in-training and post-training, of the ANC and the ASC. For aggregations of pixels (municipalities), the constrained perceptrons perform at least as well as their unconstrained counterparts. Although the difference in performance between the in-training and post-training approach is small, we recommend the former for integrating the fractional abundance constraints into MLPs meant for sub-pixel land cover estimation, regardless of the targeted level of spatial aggregation.

3D shape recovery of smooth surfaces: dropping the fixed-viewpoint assumption.

PubMed

Moses, Yael; Shimshoni, Ilan

2009-07-01

We present a new method for recovering the 3D shape of a featureless smooth surface from three or more calibrated images illuminated by different light sources (three of them are independent). This method is unique in its ability to handle images taken from unconstrained perspective viewpoints and unconstrained illumination directions. The correspondence between such images is hard to compute and no other known method can handle this problem locally from a small number of images. Our method combines geometric and photometric information in order to recover dense correspondence between the images and accurately computes the 3D shape. Only a single pass starting at one point and local computation are used. This is in contrast to methods that use the occluding contours recovered from many images to initialize and constrain an optimization process. The output of our method can be used to initialize such processes. In the special case of fixed viewpoint, the proposed method becomes a new perspective photometric stereo algorithm. Nevertheless, the introduction of the multiview setup, self-occlusions, and regions close to the occluding boundaries are better handled, and the method is more robust to noise than photometric stereo. Experimental results are presented for simulated and real images.

Polyvinylidene fluoride sensor-based method for unconstrained snoring detection.

PubMed

Hwang, Su Hwan; Han, Chung Min; Yoon, Hee Nam; Jung, Da Woon; Lee, Yu Jin; Jeong, Do-Un; Park, Kwang Suk

2015-07-01

We established and tested a snoring detection method using a polyvinylidene fluoride (PVDF) sensor for accurate, fast, and motion-artifact-robust monitoring of snoring events during sleep. Twenty patients with obstructive sleep apnea participated in this study. The PVDF sensor was located between a mattress cover and mattress, and the patients' snoring signals were unconstrainedly measured with the sensor during polysomnography. The power ratio and peak frequency from the short-time Fourier transform were used to extract spectral features from the PVDF data. A support vector machine was applied to the spectral features to classify the data into either the snore or non-snore class. The performance of the method was assessed using manual labelling by three human observers as a reference. For event-by-event snoring detection, PVDF data that contained 'snoring' (SN), 'snoring with movement' (SM), and 'normal breathing' epochs were selected for each subject. As a result, the overall sensitivity and the positive predictive values were 94.6% and 97.5%, respectively, and there was no significant difference between the SN and SM results. The proposed method can be applied in both residential and ambulatory snoring monitoring systems.

Unconstrained cranial evolution in Neandertals and modern humans compared to common chimpanzees

PubMed Central

Weaver, Timothy D.; Stringer, Chris B.

2015-01-01

A variety of lines of evidence support the idea that neutral evolutionary processes (genetic drift, mutation) have been important in generating cranial differences between Neandertals and modern humans. But how do Neandertals and modern humans compare with other species? And how do these comparisons illuminate the evolutionary processes underlying cranial diversification? To address these questions, we used 27 standard cranial measurements collected on 2524 recent modern humans, 20 Neandertals and 237 common chimpanzees to estimate split times between Neandertals and modern humans, and between Pan troglodytes verus and two other subspecies of common chimpanzee. Consistent with a neutral divergence, the Neandertal versus modern human split-time estimates based on cranial measurements are similar to those based on DNA sequences. By contrast, the common chimpanzee cranial estimates are much lower than DNA-sequence estimates. Apparently, cranial evolution has been unconstrained in Neandertals and modern humans compared with common chimpanzees. Based on these and additional analyses, it appears that cranial differentiation in common chimpanzees has been restricted by stabilizing natural selection. Alternatively, this restriction could be due to genetic and/or developmental constraints on the amount of within-group variance (relative to effective population size) available for genetic drift to act on. PMID:26468243

Variable Autosomal and X Divergence Near and Far from Genes Affects Estimates of Male Mutation Bias in Great Apes.

PubMed

Narang, Pooja; Wilson Sayres, Melissa A

2016-12-31

Male mutation bias, when more mutations are passed on via the male germline than via the female germline, is observed across mammals. One common way to infer the magnitude of male mutation bias, α, is to compare levels of neutral sequence divergence between genomic regions that spend different amounts of time in the male and female germline. For great apes, including human, we show that estimates of divergence are reduced in putatively unconstrained regions near genes relative to unconstrained regions far from genes. Divergence increases with increasing distance from genes on both the X chromosome and autosomes, but increases faster on the X chromosome than autosomes. As a result, ratios of X/A divergence increase with increasing distance from genes and corresponding estimates of male mutation bias are significantly higher in intergenic regions near genes versus far from genes. Future studies in other species will need to carefully consider the effect that genomic location will have on estimates of male mutation bias. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Automatic multiple zebrafish larvae tracking in unconstrained microscopic video conditions.

PubMed

Wang, Xiaoying; Cheng, Eva; Burnett, Ian S; Huang, Yushi; Wlodkowic, Donald

2017-12-14

The accurate tracking of zebrafish larvae movement is fundamental to research in many biomedical, pharmaceutical, and behavioral science applications. However, the locomotive characteristics of zebrafish larvae are significantly different from adult zebrafish, where existing adult zebrafish tracking systems cannot reliably track zebrafish larvae. Further, the far smaller size differentiation between larvae and the container render the detection of water impurities inevitable, which further affects the tracking of zebrafish larvae or require very strict video imaging conditions that typically result in unreliable tracking results for realistic experimental conditions. This paper investigates the adaptation of advanced computer vision segmentation techniques and multiple object tracking algorithms to develop an accurate, efficient and reliable multiple zebrafish larvae tracking system. The proposed system has been tested on a set of single and multiple adult and larvae zebrafish videos in a wide variety of (complex) video conditions, including shadowing, labels, water bubbles and background artifacts. Compared with existing state-of-the-art and commercial multiple organism tracking systems, the proposed system improves the tracking accuracy by up to 31.57% in unconstrained video imaging conditions. To facilitate the evaluation on zebrafish segmentation and tracking research, a dataset with annotated ground truth is also presented. The software is also publicly accessible.

A fast global fitting algorithm for fluorescence lifetime imaging microscopy based on image segmentation.

PubMed

Pelet, S; Previte, M J R; Laiho, L H; So, P T C

2004-10-01

Global fitting algorithms have been shown to improve effectively the accuracy and precision of the analysis of fluorescence lifetime imaging microscopy data. Global analysis performs better than unconstrained data fitting when prior information exists, such as the spatial invariance of the lifetimes of individual fluorescent species. The highly coupled nature of global analysis often results in a significantly slower convergence of the data fitting algorithm as compared with unconstrained analysis. Convergence speed can be greatly accelerated by providing appropriate initial guesses. Realizing that the image morphology often correlates with fluorophore distribution, a global fitting algorithm has been developed to assign initial guesses throughout an image based on a segmentation analysis. This algorithm was tested on both simulated data sets and time-domain lifetime measurements. We have successfully measured fluorophore distribution in fibroblasts stained with Hoechst and calcein. This method further allows second harmonic generation from collagen and elastin autofluorescence to be differentiated in fluorescence lifetime imaging microscopy images of ex vivo human skin. On our experimental measurement, this algorithm increased convergence speed by over two orders of magnitude and achieved significantly better fits. Copyright 2004 Biophysical Society

Vocal release time: a quantification of vocal offset.

PubMed

Watson, Ben C; Roark, Rick M; Baken, R J

2012-11-01

To determine the vocal release time (VRT) for linguistically unconstrained voice offsets in a healthy young adult population. Sound pressure (SP) and electroglottographic (EGG) recordings were obtained for 57 female and 55 male subjects while producing multiple tokens of three tasks (sustained /ɑ:/, "always," and "hallways") at comfortable pitch and loudness. SP and EGG signals were digitally time reversed and generalized sinusoidal models of the SP and EGG signals were obtained to compare rates of amplitude change. VRT was computed from the time lag of the cross-correlation function. Adjusted mean VRT values were significantly greater for females than for males. There was no systematic effect of age on VRT. However, 25-29-year old and >40 year old females showed shorter VRT values than the youngest female age group. Normative data are presented for a new measure of the duration of vocal offset, VRT. Acquisition of this measure requires little user intervention, thereby minimizing effects of subjective decision making. Comparison with previously reported vocal attack time (VAT) values for the same population suggests phenomenological differences between linguistically and physiologically constrained voice onsets and unconstrained voice offsets. Copyright © 2012 The Voice Foundation. Published by Mosby, Inc. All rights reserved.

Inhibitory Control, but Not Prolonged Object-Related Experience Appears to Affect Physical Problem-Solving Performance of Pet Dogs.

PubMed

Müller, Corsin A; Riemer, Stefanie; Virányi, Zsófia; Huber, Ludwig; Range, Friederike

2016-01-01

Human infants develop an understanding of their physical environment through playful interactions with objects. Similar processes may influence also the performance of non-human animals in physical problem-solving tasks, but to date there is little empirical data to evaluate this hypothesis. In addition or alternatively to prior experiences, inhibitory control has been suggested as a factor underlying the considerable individual differences in performance reported for many species. Here we report a study in which we manipulated the extent of object-related experience for a cohort of dogs (Canis familiaris) of the breed Border Collie over a period of 18 months, and assessed their level of inhibitory control, prior to testing them in a series of four physical problem-solving tasks. We found no evidence that differences in object-related experience explain variability in performance in these tasks. It thus appears that dogs do not transfer knowledge about physical rules from one physical problem-solving task to another, but rather approach each task as a novel problem. Our results, however, suggest that individual performance in these tasks is influenced in a complex way by the subject's level of inhibitory control. Depending on the task, inhibitory control had a positive or a negative effect on performance and different aspects of inhibitory control turned out to be the best predictors of individual performance in the different tasks. Therefore, studying the interplay between inhibitory control and problem-solving performance will make an important contribution to our understanding of individual and species differences in physical problem-solving performance.

Inhibitory Control, but Not Prolonged Object-Related Experience Appears to Affect Physical Problem-Solving Performance of Pet Dogs

PubMed Central

Müller, Corsin A.; Riemer, Stefanie; Virányi, Zsófia; Huber, Ludwig; Range, Friederike

2016-01-01

Human infants develop an understanding of their physical environment through playful interactions with objects. Similar processes may influence also the performance of non-human animals in physical problem-solving tasks, but to date there is little empirical data to evaluate this hypothesis. In addition or alternatively to prior experiences, inhibitory control has been suggested as a factor underlying the considerable individual differences in performance reported for many species. Here we report a study in which we manipulated the extent of object-related experience for a cohort of dogs (Canis familiaris) of the breed Border Collie over a period of 18 months, and assessed their level of inhibitory control, prior to testing them in a series of four physical problem-solving tasks. We found no evidence that differences in object-related experience explain variability in performance in these tasks. It thus appears that dogs do not transfer knowledge about physical rules from one physical problem-solving task to another, but rather approach each task as a novel problem. Our results, however, suggest that individual performance in these tasks is influenced in a complex way by the subject’s level of inhibitory control. Depending on the task, inhibitory control had a positive or a negative effect on performance and different aspects of inhibitory control turned out to be the best predictors of individual performance in the different tasks. Therefore, studying the interplay between inhibitory control and problem-solving performance will make an important contribution to our understanding of individual and species differences in physical problem-solving performance. PMID:26863141

The Influence of Open Goals on the Acquisition of Problem-Relevant Information

ERIC Educational Resources Information Center

Moss, Jarrod; Kotovsky, Kenneth; Cagan, Jonathan

2007-01-01

There have been a number of recent findings indicating that unsolved problems, or open goals more generally, influence cognition even when the current task has no relation to the task in which the goal was originally set. It was hypothesized that open goals would influence what information entered the problem-solving process. Three studies were…

The phase transition of matrix recovery from Gaussian measurements matches the minimax MSE of matrix denoising.

PubMed

Donoho, David L; Gavish, Matan; Montanari, Andrea

2013-05-21

Let X(0) be an unknown M by N matrix. In matrix recovery, one takes n < MN linear measurements y(1),…,y(n) of X(0), where y(i) = Tr(A(T)iX(0)) and each A(i) is an M by N matrix. A popular approach for matrix recovery is nuclear norm minimization (NNM): solving the convex optimization problem min ||X||*subject to y(i) =Tr(A(T)(i)X) for all 1 ≤ i ≤ n, where || · ||* denotes the nuclear norm, namely, the sum of singular values. Empirical work reveals a phase transition curve, stated in terms of the undersampling fraction δ(n,M,N) = n/(MN), rank fraction ρ=rank(X0)/min {M,N}, and aspect ratio β=M/N. Specifically when the measurement matrices Ai have independent standard Gaussian random entries, a curve δ*(ρ) = δ*(ρ;β) exists such that, if δ > δ*(ρ), NNM typically succeeds for large M,N, whereas if δ < δ*(ρ), it typically fails. An apparently quite different problem is matrix denoising in Gaussian noise, in which an unknown M by N matrix X(0) is to be estimated based on direct noisy measurements Y =X(0) + Z, where the matrix Z has independent and identically distributed Gaussian entries. A popular matrix denoising scheme solves the unconstrained optimization problem min|| Y-X||(2)(F)/2+λ||X||*. When optimally tuned, this scheme achieves the asymptotic minimax mean-squared error M(ρ;β) = lim(M,N → ∞)inf(λ)sup(rank(X) ≤ ρ · M)MSE(X,X(λ)), where M/N → . We report extensive experiments showing that the phase transition δ*(ρ) in the first problem, matrix recovery from Gaussian measurements, coincides with the minimax risk curve M(ρ)=M(ρ;β) in the second problem, matrix denoising in Gaussian noise: δ*(ρ)=M(ρ), for any rank fraction 0 < ρ < 1 (at each common aspect ratio β). Our experiments considered matrices belonging to two constraint classes: real M by N matrices, of various ranks and aspect ratios, and real symmetric positive-semidefinite N by N matrices, of various ranks.

A Confidant Support and Problem Solving Model of Divorced Fathers’ Parenting

PubMed Central

DeGarmo, David S.; Forgatch, Marion S.

2011-01-01

This study tested a hypothesized social interaction learning (SIL) model of confidant support and paternal parenting. The latent growth curve analysis employed 230 recently divorced fathers, of which 177 enrolled support confidants, to test confidant support as a predictor of problem solving outcomes and problem solving outcomes as predictors of change in fathers’ parenting. Fathers’ parenting was hypothesized to predict growth in child behavior. Observational measures of support behaviors and problem solving outcomes were obtained from structured discussions of personal and parenting issues faced by the fathers. Findings replicated and extended prior cross-sectional studies with divorced mothers and their confidants. Confidant support predicted better problem solving outcomes, problem solving predicted more effective parenting, and parenting in turn predicted growth in children’s reduced total problem behavior T scores over 18 months. Supporting a homophily perspective, fathers’ antisociality was associated with confidant antisociality but only fathers’ antisociality influenced the support process model. Intervention implications are discussed regarding SIL parent training and social support. PMID:21541814

A confidant support and problem solving model of divorced fathers' parenting.

PubMed

Degarmo, David S; Forgatch, Marion S

2012-03-01

This study tested a hypothesized social interaction learning (SIL) model of confidant support and paternal parenting. The latent growth curve analysis employed 230 recently divorced fathers, of which 177 enrolled support confidants, to test confidant support as a predictor of problem solving outcomes and problem solving outcomes as predictors of change in fathers' parenting. Fathers' parenting was hypothesized to predict growth in child behavior. Observational measures of support behaviors and problem solving outcomes were obtained from structured discussions of personal and parenting issues faced by the fathers. Findings replicated and extended prior cross-sectional studies with divorced mothers and their confidants. Confidant support predicted better problem solving outcomes, problem solving predicted more effective parenting, and parenting in turn predicted growth in children's reduced total problem behavior T scores over 18 months. Supporting a homophily perspective, fathers' antisociality was associated with confidant antisociality but only fathers' antisociality influenced the support process model. Intervention implications are discussed regarding SIL parent training and social support.

The impact of childhood emotional abuse and experiential avoidance on maladaptive problem solving and intimate partner violence.

PubMed

Bell, Kathryn M; Higgins, Lorrin

2015-04-16

The purpose of the current study was to examine the joint influences of experiential avoidance and social problem solving on the link between childhood emotional abuse (CEA) and intimate partner violence (IPV). Experiential avoidance following CEA may interfere with a person's ability to effectively problem solve in social situations, increasing risk for conflict and interpersonal violence. As part of a larger study, 232 women recruited from the community completed measures assessing childhood emotional, physical, and sexual abuse, experiential avoidance, maladaptive social problem solving, and IPV perpetration and victimization. Final trimmed models indicated that CEA was indirectly associated with IPV victimization and perpetration via experiential avoidance and Negative Problem Orientation (NPO) and Impulsivity/Carelessness Style (ICS) social problem solving strategies. Though CEA was related to an Avoidance Style (AS) social problem solving strategy, this strategy was not significantly associated with IPV victimization or perpetration. Experiential avoidance had both a direct and indirect effect, via NPO and ICS social problem solving, on IPV victimization and perpetration. Findings suggest that CEA may lead some women to avoid unwanted internal experiences, which may adversely impact their ability to effectively problem solve in social situations and increase IPV risk.

The Impact of Childhood Emotional Abuse and Experiential Avoidance on Maladaptive Problem Solving and Intimate Partner Violence

PubMed Central

Bell, Kathryn M.; Higgins, Lorrin

2015-01-01

The purpose of the current study was to examine the joint influences of experiential avoidance and social problem solving on the link between childhood emotional abuse (CEA) and intimate partner violence (IPV). Experiential avoidance following CEA may interfere with a person’s ability to effectively problem solve in social situations, increasing risk for conflict and interpersonal violence. As part of a larger study, 232 women recruited from the community completed measures assessing childhood emotional, physical, and sexual abuse, experiential avoidance, maladaptive social problem solving, and IPV perpetration and victimization. Final trimmed models indicated that CEA was indirectly associated with IPV victimization and perpetration via experiential avoidance and Negative Problem Orientation (NPO) and Impulsivity/Carelessness Style (ICS) social problem solving strategies. Though CEA was related to an Avoidance Style (AS) social problem solving strategy, this strategy was not significantly associated with IPV victimization or perpetration. Experiential avoidance had both a direct and indirect effect, via NPO and ICS social problem solving, on IPV victimization and perpetration. Findings suggest that CEA may lead some women to avoid unwanted internal experiences, which may adversely impact their ability to effectively problem solve in social situations and increase IPV risk. PMID:25893570

Moving your eyes to solution: effects of movements on the perception of a problem-solving task.

PubMed

Werner, K; Raab, M

2014-01-01

There is ample evidence suggesting a bidirectional connection between bodily movements and cognitive processes, such as problem solving. Current research suggests that previous movements can influence the problem-solving process, but it is unclear what phase of this process is affected. Therefore, we investigated participants' gaze behaviour in the first phase of arithmetic problem solving with two groups (plus group, minus group) to explore a spatial bias toward the left or the right while perceiving a problem-solving task (the water-jar problem) after two different movements-that is, for the plus group, sorting marbles from two outer bowls into one in the middle, and for the minus group, sorting marbles from the middle bowl to the outer ones. We showed a right shift of spatial bias for the plus and to the left for the minus group in the perception and problem tasks. Although movements affected gaze, the groups did not differ in their overall problem-solving strategies; however, the first correct solutions did differ. This study provides further evidence of sensorimotor effects on problem solving and spatial bias and offers insight into how a two-phase problem-solving process is guided by sensorimotor information.

Environmental problem-solving: Psychosocial factors

NASA Astrophysics Data System (ADS)

Miller, Alan

1982-11-01

This is a study of individual differences in environmental problem-solving, the probable roots of these differences, and their implications for the education of resource professionals. A group of student Resource Managers were required to elaborate their conception of a complex resource issue (Spruce Budworm management) and to generate some ideas on management policy. Of particular interest was the way in which subjects dealt with the psychosocial aspects of the problem. A structural and content analysis of responses indicated a predominance of relatively compartmentalized styles, a technological orientation, and a tendency to ignore psychosocial issues. A relationship between problem-solving behavior and personal (psychosocial) style was established which, in the context of other evidence, suggests that problem-solving behavior is influenced by more deep seated personality factors. The educational implication drawn was that problem-solving cannot be viewed simply as an intellectual-technical activity but one that involves, and requires the education of, the whole person.

Development of Mastery during Adolescence: The Role of Family Problem Solving*

PubMed Central

Conger, Katherine Jewsbury; Williams, Shannon Tierney; Little, Wendy M.; Masyn, Katherine E.; Shebloski, Barbara

2009-01-01

A sense of mastery is an important component of psychological health and well-being across the life-span; however, relatively little is known about the development of mastery during childhood and adolescence. Utilizing prospective, longitudinal data from 444 adolescent sibling pairs and their parents, our conceptual model proposes that family SES in the form of parental education promotes effective family problem solving which, in turn, fosters adolescent mastery. Results show: (1) a significant increase in mastery for younger and older siblings, (2) parental education promoted effective problem solving between parents and adolescents and between siblings but not between the parents themselves, and (3) all forms of effective family problem solving predicted greater adolescent mastery. Parental education had a direct effect on adolescent mastery as well as the hypothesized indirect effect through problem solving effectiveness, suggesting both a social structural and social process influence on the development of mastery during adolescence. PMID:19413137

Development of mastery during adolescence: the role of family problem-solving.

PubMed

Conger, Katherine Jewsbury; Williams, Shannon Tierney; Little, Wendy M; Masyn, Katherine E; Shebloski, Barbara

2009-03-01

A sense of mastery is an important component of psychological health and wellbeing across the life-span; however relatively little is known about the development of mastery during childhood and adolescence. Utilizing prospective, longitudinal data from 444 adolescent sibling pairs and their parents, our conceptual model proposes that family socioeconomic status (SES) in the form of parental education promotes effective family problem-solving, which, in turn, fosters adolescent mastery. Results show: (1) a significant increase in mastery for younger and older siblings, (2) parental education promoted effective problem-solving between parents and adolescents and between siblings but not between the parents themselves, and (3) all forms of effective family problem-solving predicted greater adolescent mastery. Parental education had a direct effect on adolescent mastery as well as the hypothesized indirect effect through problem-solving effectiveness, suggesting both a social structural and social process influence on the development of mastery during adolescence.

Implementing a Case-Based E-Learning Environment in a Lecture-Oriented Anaesthesiology Class: Do Learning Styles Matter in Complex Problem Solving over Time?

ERIC Educational Resources Information Center

Choi, Ikseon; Lee, Sang Joon; Kang, Jeongwan

2009-01-01

This study explores how students' learning styles influence their learning while solving complex problems when a case-based e-learning environment is implemented in a conventional lecture-oriented classroom. Seventy students from an anaesthesiology class at a dental school participated in this study over a 3-week period. Five learning-outcome…

Engineering-Based Problem Solving Strategies in AP Calculus: An Investigation into High School Student Performance on Related Rate Free-Response Problems

ERIC Educational Resources Information Center

Thieken, John

2012-01-01

A sample of 127 high school Advanced Placement (AP) Calculus students from two schools was utilized to study the effects of an engineering design-based problem solving strategy on student performance with AP style Related Rate questions and changes in conceptions, beliefs, and influences. The research design followed a treatment-control multiple…

Information transfer and shared mental models for decision making

NASA Technical Reports Server (NTRS)

Orasanu, Judith; Fischer, Ute

1991-01-01

A study to determine how communication influences flight crew performance is presented. This analysis focuses on the content of communication, principally asking what an utterance does from a cognitive, problem solving viewpoint. Two questions are addressed in this study: how is language utilized to manage problems in the cockpit, and are there differences between two- and three-member crews in their communication and problem solving strategies?

Relationship among Students' Problem-Solving Attitude, Perceived Value, Behavioral Attitude, and Intention to Participate in a Science and Technology Contest

ERIC Educational Resources Information Center

Huang, Neng-Tang Norman; Chiu, Li-Jia; Hong, Jon-Chao

2016-01-01

The strong humanistic and ethics-oriented philosophy of Confucianism tends to lead people influenced by these principles to undervalue the importance of hands-on practice and creativity in education. GreenMech, a science and technology contest, was implemented to encourage real-world, hands-on problem solving in an attempt to mitigate this effect.…

Development of multidisciplinary design optimization procedures for smart composite wings and turbomachinery blades

NASA Astrophysics Data System (ADS)

Jha, Ratneshwar

Multidisciplinary design optimization (MDO) procedures have been developed for smart composite wings and turbomachinery blades. The analysis and optimization methods used are computationally efficient and sufficiently rigorous. Therefore, the developed MDO procedures are well suited for actual design applications. The optimization procedure for the conceptual design of composite aircraft wings with surface bonded piezoelectric actuators involves the coupling of structural mechanics, aeroelasticity, aerodynamics and controls. The load carrying member of the wing is represented as a single-celled composite box beam. Each wall of the box beam is analyzed as a composite laminate using a refined higher-order displacement field to account for the variations in transverse shear stresses through the thickness. Therefore, the model is applicable for the analysis of composite wings of arbitrary thickness. Detailed structural modeling issues associated with piezoelectric actuation of composite structures are considered. The governing equations of motion are solved using the finite element method to analyze practical wing geometries. Three-dimensional aerodynamic computations are performed using a panel code based on the constant-pressure lifting surface method to obtain steady and unsteady forces. The Laplace domain method of aeroelastic analysis produces root-loci of the system which gives an insight into the physical phenomena leading to flutter/divergence and can be efficiently integrated within an optimization procedure. The significance of the refined higher-order displacement field on the aeroelastic stability of composite wings has been established. The effect of composite ply orientations on flutter and divergence speeds has been studied. The Kreisselmeier-Steinhauser (K-S) function approach is used to efficiently integrate the objective functions and constraints into a single envelope function. The resulting unconstrained optimization problem is solved using the Broyden-Fletcher-Goldberg-Shanno algorithm. The optimization problem is formulated with the objective of simultaneously minimizing wing weight and maximizing its aerodynamic efficiency. Design variables include composite ply orientations, ply thicknesses, wing sweep, piezoelectric actuator thickness and actuator voltage. Constraints are placed on the flutter/divergence dynamic pressure, wing root stresses and the maximum electric field applied to the actuators. Numerical results are presented showing significant improvements, after optimization, compared to reference designs. The multidisciplinary optimization procedure for the design of turbomachinery blades integrates aerodynamic and heat transfer design objective criteria along with various mechanical and geometric constraints on the blade geometry. The airfoil shape is represented by Bezier-Bernstein polynomials, which results in a relatively small number of design variables for the optimization. Thin shear layer approximation of the Navier-Stokes equation is used for the viscous flow calculations. Grid generation is accomplished by solving Poisson equations. The maximum and average blade temperatures are obtained through a finite element analysis. Total pressure and exit kinetic energy losses are minimized, with constraints on blade temperatures and geometry. The constrained multiobjective optimization problem is solved using the K-S function approach. The results for the numerical example show significant improvements after optimization.

2007 Joint Chemical Biological, Radiological and Nuclear (CBRN) Conference and Exhibition - Combating Weapons of Mass Destruction

DTIC Science & Technology

2007-06-27

Selected CB Defense Systems SHAPESENSE Joint Warning and Reporting Network JSLIST CB Protected Shelter Joint Vaccine Acquisition Program Joint Effects...military can operate in any environment, unconstrained by chemical or biological weapons. 21 SHIELD SUSTAIN Selected CB Defense Systems SHAPESENSE Joint...28070625_JCBRN_Conference_Reeves UNCLASSIFIED Decontamination Vision Strippable Barriers Self-Decontaminating Fabrics/Coatings Reduce Logistics Burden

Constrained versus Unconstrained Intensive Language Therapy in Two Individuals with Chronic, Moderate-to-Severe Aphasia and Apraxia of Speech: Behavioral and fMRI Outcomes

ERIC Educational Resources Information Center

Kurland, Jacquie; Pulvermuller, Friedemann; Silva, Nicole; Burke, Katherine; Andrianopoulos, Mary

2012-01-01

Purpose: This Phase I study investigated behavioral and functional MRI (fMRI) outcomes of 2 intensive treatment programs to improve naming in 2 participants with chronic moderate-to-severe aphasia with comorbid apraxia of speech (AOS). Constraint-induced aphasia therapy (CIAT; Pulvermuller et al., 2001) has demonstrated positive outcomes in some…

Sorting white blood cells in microfabricated arrays

NASA Astrophysics Data System (ADS)

Castelino, Judith Andrea Rose

Fractionating white cells in microfabricated arrays presents the potential for detecting cells with abnormal adhesive or deformation properties. A possible application is separating nucleated fetal red blood cells from maternal blood. Since fetal cells are nucleated, it is possible to extract genetic information about the fetus from them. Separating fetal cells from maternal blood would provide a low cost noninvasive prenatal diagnosis for genetic defects, which is not currently available. We present results showing that fetal cells penetrate further into our microfabricated arrays than adult cells, and that it is possible to enrich the fetal cell fraction using the arrays. We discuss modifications to the array which would result in further enrichment. Fetal cells are less adhesive and more deformable than adult white cells. To determine which properties limit penetration, we compared the penetration of granulocytes and lymphocytes in arrays with different etch depths, constriction size, constriction frequency, and with different amounts of metabolic activity. The penetration of lymphocytes and granulocytes into constrained and unconstrained arrays differed qualitatively. In constrained arrays, the cells were activated by repeated shearing, and the number of cells stuck as a function of distance fell superexponentially. In unconstrained arrays the number of cells stuck fell slower than an exponential. We attribute this result to different subpopulations of cells with different sticking parameters. We determined that penetration in unconstrained arrays was limited by metabolic processes, and that when metabolic activity was reduced penetration was limited by deformability. Fetal cells also contain a different form of hemoglobin with a higher oxygen affinity than adult hemoglobin. Deoxygenated cells are paramagnetic and are attracted to high magnetic field gradients. We describe a device which can separate cells using 10 μm magnetic wires to deflect the paramagnetic cells. We present preliminary results from a test system that separates paramagnetic beads from latex beads. The separation is limited by our ability to produce the high field gradients which are necessary to separate cells according to their hemoglobin content, and we present estimates of the magnetic gradients we achieved.

Mathematical Reasoning Requirements in Swedish National Physics Tests

ERIC Educational Resources Information Center

Johansson, Helena

2016-01-01

This paper focuses on one aspect of mathematical competence, namely mathematical reasoning, and how this competency influences students' knowing of physics. This influence was studied by analysing the mathematical reasoning requirements upper secondary students meet when solving tasks in national physics tests. National tests are constructed to…

From Research to Policy and Back

ERIC Educational Resources Information Center

Huston, Aletha C.

2008-01-01

Although science policy and social policy have distinct cultures, there are overlapping influences on both. Science policy decisions across the spectrum of basic and applied research are influenced by perceived social utility and the potential for solving current social problems. With the advent of evidence-based policy requirements, social…

Polarity related influence maximization in signed social networks.

PubMed

Li, Dong; Xu, Zhi-Ming; Chakraborty, Nilanjan; Gupta, Anika; Sycara, Katia; Li, Sheng

2014-01-01

Influence maximization in social networks has been widely studied motivated by applications like spread of ideas or innovations in a network and viral marketing of products. Current studies focus almost exclusively on unsigned social networks containing only positive relationships (e.g. friend or trust) between users. Influence maximization in signed social networks containing both positive relationships and negative relationships (e.g. foe or distrust) between users is still a challenging problem that has not been studied. Thus, in this paper, we propose the polarity-related influence maximization (PRIM) problem which aims to find the seed node set with maximum positive influence or maximum negative influence in signed social networks. To address the PRIM problem, we first extend the standard Independent Cascade (IC) model to the signed social networks and propose a Polarity-related Independent Cascade (named IC-P) diffusion model. We prove that the influence function of the PRIM problem under the IC-P model is monotonic and submodular Thus, a greedy algorithm can be used to achieve an approximation ratio of 1-1/e for solving the PRIM problem in signed social networks. Experimental results on two signed social network datasets, Epinions and Slashdot, validate that our approximation algorithm for solving the PRIM problem outperforms state-of-the-art methods.

Polarity Related Influence Maximization in Signed Social Networks

PubMed Central

Li, Dong; Xu, Zhi-Ming; Chakraborty, Nilanjan; Gupta, Anika; Sycara, Katia; Li, Sheng

2014-01-01

Influence maximization in social networks has been widely studied motivated by applications like spread of ideas or innovations in a network and viral marketing of products. Current studies focus almost exclusively on unsigned social networks containing only positive relationships (e.g. friend or trust) between users. Influence maximization in signed social networks containing both positive relationships and negative relationships (e.g. foe or distrust) between users is still a challenging problem that has not been studied. Thus, in this paper, we propose the polarity-related influence maximization (PRIM) problem which aims to find the seed node set with maximum positive influence or maximum negative influence in signed social networks. To address the PRIM problem, we first extend the standard Independent Cascade (IC) model to the signed social networks and propose a Polarity-related Independent Cascade (named IC-P) diffusion model. We prove that the influence function of the PRIM problem under the IC-P model is monotonic and submodular Thus, a greedy algorithm can be used to achieve an approximation ratio of 1-1/e for solving the PRIM problem in signed social networks. Experimental results on two signed social network datasets, Epinions and Slashdot, validate that our approximation algorithm for solving the PRIM problem outperforms state-of-the-art methods. PMID:25061986

Job Characteristics and Mentoring in Pre-Schools: Mentoring Relationships among the Educational Staff When Challenged by Problem-Solving Tasks

ERIC Educational Resources Information Center

Waaland, Torbjorn

2013-01-01

Purpose: The purpose of this paper is to study the influence of problem-solving tasks on mentoring received, peer mentoring and mentoring provided. Design/methodology/approach: This cross-sectional survey was based on a questionnaire that was sent to a total of 435 employees from 29 pre-schools in Norway. A total of 284 responses were returned, a…

Design of a cooperative problem-solving system for en-route flight planning: An empirical evaluation

NASA Technical Reports Server (NTRS)

Layton, Charles; Smith, Philip J.; Mc Coy, C. Elaine

1994-01-01

Both optimization techniques and expert systems technologies are popular approaches for developing tools to assist in complex problem-solving tasks. Because of the underlying complexity of many such tasks, however, the models of the world implicitly or explicitly embedded in such tools are often incomplete and the problem-solving methods fallible. The result can be 'brittleness' in situations that were not anticipated by the system designers. To deal with this weakness, it has been suggested that 'cooperative' rather than 'automated' problem-solving systems be designed. Such cooperative systems are proposed to explicitly enhance the collaboration of the person (or a group of people) and the computer system. This study evaluates the impact of alternative design concepts on the performance of 30 airline pilots interacting with such a cooperative system designed to support en-route flight planning. The results clearly demonstrate that different system design concepts can strongly influence the cognitive processes and resultant performances of users. Based on think-aloud protocols, cognitive models are proposed to account for how features of the computer system interacted with specific types of scenarios to influence exploration and decision making by the pilots. The results are then used to develop recommendations for guiding the design of cooperative systems.

Design of a cooperative problem-solving system for en-route flight planning: An empirical evaluation

NASA Technical Reports Server (NTRS)

Layton, Charles; Smith, Philip J.; McCoy, C. Elaine

1994-01-01

Both optimization techniques and expert systems technologies are popular approaches for developing tools to assist in complex problem-solving tasks. Because of the underlying complexity of many such tasks, however, the models of the world implicitly or explicitly embedded in such tools are often incomplete and the problem-solving methods fallible. The result can be 'brittleness' in situations that were not anticipated by the system designers. To deal with this weakness, it has been suggested that 'cooperative' rather than 'automated' problem-solving systems be designed. Such cooperative systems are proposed to explicitly enhance the collaboration of the person (or a group of people) and the computer system. This study evaluates the impact of alternative design concepts on the performance of 30 airline pilots interacting with such a cooperative system designed to support enroute flight planning. The results clearly demonstrate that different system design concepts can strongly influence the cognitive processes and resultant performances of users. Based on think-aloud protocols, cognitive models are proposed to account for how features of the computer system interacted with specific types of scenarios to influence exploration and decision making by the pilots. The results are then used to develop recommendations for guiding the design of cooperative systems.

The influence of eating psychopathology on autobiographical memory specificity and social problem-solving.

PubMed

Ridout, Nathan; Matharu, Munveen; Sanders, Elizabeth; Wallis, Deborah J

2015-08-30

The primary aim was to examine the influence of subclinical disordered eating on autobiographical memory specificity (AMS) and social problem solving (SPS). A further aim was to establish if AMS mediated the relationship between eating psychopathology and SPS. A non-clinical sample of 52 females completed the autobiographical memory test (AMT), where they were asked to retrieve specific memories of events from their past in response to cue words, and the means-end problem-solving task (MEPS), where they were asked to generate means of solving a series of social problems. Participants also completed the Eating Disorders Inventory (EDI) and Hospital Anxiety and Depression Scale. After controlling for mood, high scores on the EDI subscales, particularly Drive-for-Thinness, were associated with the retrieval of fewer specific and a greater proportion of categorical memories on the AMT and with the generation of fewer and less effective means on the MEPS. Memory specificity fully mediated the relationship between eating psychopathology and SPS. These findings have implications for individuals exhibiting high levels of disordered eating, as poor AMS and SPS are likely to impact negatively on their psychological wellbeing and everyday social functioning and could represent a risk factor for the development of clinically significant eating disorders. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Role of Context in Risk-Based Reasoning

ERIC Educational Resources Information Center

Pratt, Dave; Ainley, Janet; Kent, Phillip; Levinson, Ralph; Yogui, Cristina; Kapadia, Ramesh

2011-01-01

In this article we report the influence of contextual factors on mathematics and science teachers' reasoning in risk-based decision-making. We examine previous research that presents judgments of risk as being subjectively influenced by contextual factors and other research that explores the role of context in mathematical problem-solving. Our own…

Sex Differences in Spatial Ability: A Critique.

ERIC Educational Resources Information Center

Clear, Sarah-Jane

1978-01-01

Explores (1) problems of the validity of tests of spatial ability, and (2) problems of the recessive gene influence theory of the origin of sex differences in spatial ability. Studies of cognitive strategies in spatial problem solving are suggested as a way to further investigate recessive gene influence. (Author/RH)

Working memory components that predict word problem solving: Is it merely a function of reading, calculation, and fluid intelligence?

PubMed

Fung, Wenson; Swanson, H Lee

2017-07-01

The purpose of this study was to assess whether the differential effects of working memory (WM) components (the central executive, phonological loop, and visual-spatial sketchpad) on math word problem-solving accuracy in children (N = 413, ages 6-10) are completely mediated by reading, calculation, and fluid intelligence. The results indicated that all three WM components predicted word problem solving in the nonmediated model, but only the storage component of WM yielded a significant direct path to word problem-solving accuracy in the fully mediated model. Fluid intelligence was found to moderate the relationship between WM and word problem solving, whereas reading, calculation, and related skills (naming speed, domain-specific knowledge) completely mediated the influence of the executive system on problem-solving accuracy. Our results are consistent with findings suggesting that storage eliminates the predictive contribution of executive WM to various measures Colom, Rebollo, Abad, & Shih (Memory & Cognition, 34: 158-171, 2006). The findings suggest that the storage component of WM, rather than the executive component, has a direct path to higher-order processing in children.

Incremental planning to control a blackboard-based problem solver

NASA Technical Reports Server (NTRS)

Durfee, E. H.; Lesser, V. R.

1987-01-01

To control problem solving activity, a planner must resolve uncertainty about which specific long-term goals (solutions) to pursue and about which sequences of actions will best achieve those goals. A planner is described that abstracts the problem solving state to recognize possible competing and compatible solutions and to roughly predict the importance and expense of developing these solutions. With this information, the planner plans sequences of problem solving activities that most efficiently resolve its uncertainty about which of the possible solutions to work toward. The planner only details actions for the near future because the results of these actions will influence how (and whether) a plan should be pursued. As problem solving proceeds, the planner adds new details to the plan incrementally, and monitors and repairs the plan to insure it achieves its goals whenever possible. Through experiments, researchers illustrate how these new mechanisms significantly improve problem solving decisions and reduce overall computation. They briefly discuss current research directions, including how these mechanisms can improve a problem solver's real-time response and can enhance cooperation in a distributed problem solving network.

Bridging the gap: from biometrics to forensics.

PubMed

Jain, Anil K; Ross, Arun

2015-08-05

Biometric recognition, or simply biometrics, refers to automated recognition of individuals based on their behavioural and biological characteristics. The success of fingerprints in forensic science and law enforcement applications, coupled with growing concerns related to border control, financial fraud and cyber security, has generated a huge interest in using fingerprints, as well as other biological traits, for automated person recognition. It is, therefore, not surprising to see biometrics permeating various segments of our society. Applications include smartphone security, mobile payment, border crossing, national civil registry and access to restricted facilities. Despite these successful deployments in various fields, there are several existing challenges and new opportunities for person recognition using biometrics. In particular, when biometric data is acquired in an unconstrained environment or if the subject is uncooperative, the quality of the ensuing biometric data may not be amenable for automated person recognition. This is particularly true in crime-scene investigations, where the biological evidence gleaned from a scene may be of poor quality. In this article, we first discuss how biometrics evolved from forensic science and how its focus is shifting back to its origin in order to address some challenging problems. Next, we enumerate the similarities and differences between biometrics and forensics. We then present some applications where the principles of biometrics are being successfully leveraged into forensics in order to solve critical problems in the law enforcement domain. Finally, we discuss new collaborative opportunities for researchers in biometrics and forensics, in order to address hitherto unsolved problems that can benefit society at large. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

A LAGRANGIAN GAUSS-NEWTON-KRYLOV SOLVER FOR MASS- AND INTENSITY-PRESERVING DIFFEOMORPHIC IMAGE REGISTRATION.

PubMed

Mang, Andreas; Ruthotto, Lars

2017-01-01

We present an efficient solver for diffeomorphic image registration problems in the framework of Large Deformations Diffeomorphic Metric Mappings (LDDMM). We use an optimal control formulation, in which the velocity field of a hyperbolic PDE needs to be found such that the distance between the final state of the system (the transformed/transported template image) and the observation (the reference image) is minimized. Our solver supports both stationary and non-stationary (i.e., transient or time-dependent) velocity fields. As transformation models, we consider both the transport equation (assuming intensities are preserved during the deformation) and the continuity equation (assuming mass-preservation). We consider the reduced form of the optimal control problem and solve the resulting unconstrained optimization problem using a discretize-then-optimize approach. A key contribution is the elimination of the PDE constraint using a Lagrangian hyperbolic PDE solver. Lagrangian methods rely on the concept of characteristic curves. We approximate these curves using a fourth-order Runge-Kutta method. We also present an efficient algorithm for computing the derivatives of the final state of the system with respect to the velocity field. This allows us to use fast Gauss-Newton based methods. We present quickly converging iterative linear solvers using spectral preconditioners that render the overall optimization efficient and scalable. Our method is embedded into the image registration framework FAIR and, thus, supports the most commonly used similarity measures and regularization functionals. We demonstrate the potential of our new approach using several synthetic and real world test problems with up to 14.7 million degrees of freedom.

Can re-regulation reservoirs and batteries cost-effectively mitigate sub-daily hydropeaking?

NASA Astrophysics Data System (ADS)

Haas, J.; Nowak, W.; Anindito, Y.; Olivares, M. A.

2017-12-01

To compensate for mismatches between generation and load, hydropower plants frequently operate in strong hydropeaking schemes, which is harmful to the downstream ecosystem. Furthermore, new power market structures and variable renewable systems may exacerbate this behavior. Ecological constraints (minimum flows, maximum ramps) are frequently used to mitigate hydropeaking, but these stand in direct tradeoff with the operational flexibility required for integrating renewable technologies. Fortunately, there are also physical methods (i.e. re-regulation reservoirs and batteries) but to date, there are no studies about their cost-effectiveness for hydropeaking mitigation. This study aims to fill that gap. For this, we formulate an hourly mixed-integer linear optimization model to plan the weekly operation of a hydro-thermal-renewable power system from southern Chile. The opportunity cost of water (needed for this weekly scheduling) is obtained from a mid-term programming solved with dynamic programming. We compare the current (unconstrained) hydropower operation with an ecologically constrained operation. The resulting cost increase is then contrasted with the annual payments necessary for the physical hydropeaking mitigation options. For highly constrained operations, both re-regulation reservoirs and batteries show to be economically attractive for hydropeaking mitigation. For intermediate constrained scenarios, re-regulation reservoirs are still economic, whereas batteries can be a viable solution only if they become cheaper in future. Given current cost projections, their break-even point (for hydropeaking mitigation) is expected within the next ten years. Finally, less stringent hydropeaking constraints do not justify physical mitigation measures, as the necessary flexibility can be provided by other power plants of the system.

Structural Damage Detection Using Changes in Natural Frequencies: Theory and Applications

NASA Astrophysics Data System (ADS)

He, K.; Zhu, W. D.

2011-07-01

A vibration-based method that uses changes in natural frequencies of a structure to detect damage has advantages over conventional nondestructive tests in detecting various types of damage, including loosening of bolted joints, using minimum measurement data. Two major challenges associated with applications of the vibration-based damage detection method to engineering structures are addressed: accurate modeling of structures and the development of a robust inverse algorithm to detect damage, which are defined as the forward and inverse problems, respectively. To resolve the forward problem, new physics-based finite element modeling techniques are developed for fillets in thin-walled beams and for bolted joints, so that complex structures can be accurately modeled with a reasonable model size. To resolve the inverse problem, a logistical function transformation is introduced to convert the constrained optimization problem to an unconstrained one, and a robust iterative algorithm using a trust-region method, called the Levenberg-Marquardt method, is developed to accurately detect the locations and extent of damage. The new methodology can ensure global convergence of the iterative algorithm in solving under-determined system equations and deal with damage detection problems with relatively large modeling error and measurement noise. The vibration-based damage detection method is applied to various structures including lightning masts, a space frame structure and one of its components, and a pipeline. The exact locations and extent of damage can be detected in the numerical simulation where there is no modeling error and measurement noise. The locations and extent of damage can be successfully detected in experimental damage detection.

Bridging the gap: from biometrics to forensics

PubMed Central

Jain, Anil K.; Ross, Arun

2015-01-01

Biometric recognition, or simply biometrics, refers to automated recognition of individuals based on their behavioural and biological characteristics. The success of fingerprints in forensic science and law enforcement applications, coupled with growing concerns related to border control, financial fraud and cyber security, has generated a huge interest in using fingerprints, as well as other biological traits, for automated person recognition. It is, therefore, not surprising to see biometrics permeating various segments of our society. Applications include smartphone security, mobile payment, border crossing, national civil registry and access to restricted facilities. Despite these successful deployments in various fields, there are several existing challenges and new opportunities for person recognition using biometrics. In particular, when biometric data is acquired in an unconstrained environment or if the subject is uncooperative, the quality of the ensuing biometric data may not be amenable for automated person recognition. This is particularly true in crime-scene investigations, where the biological evidence gleaned from a scene may be of poor quality. In this article, we first discuss how biometrics evolved from forensic science and how its focus is shifting back to its origin in order to address some challenging problems. Next, we enumerate the similarities and differences between biometrics and forensics. We then present some applications where the principles of biometrics are being successfully leveraged into forensics in order to solve critical problems in the law enforcement domain. Finally, we discuss new collaborative opportunities for researchers in biometrics and forensics, in order to address hitherto unsolved problems that can benefit society at large. PMID:26101280

Assessment of soil hydrology variability of a new weighing lysimeter facility

NASA Astrophysics Data System (ADS)

Brown, S. E.; Wagner-Riddle, C.; Berg, A. A.

2017-12-01

Diversifying annual crop rotations is a strategy that mimics natural ecosystems and is postulated to increase agricultural resilience to climate change, soil quality and provision of soil ecosystem services. However, diverse cropping systems could increase soil mineral N levels and lead to greater leaching and/or N2O emissions; which raises the questions: (i) are diverse cropping systems actually beneficial for air and water quality? (ii) what are the trade-offs between soil, water, and air quality upon implementing a diverse cropping rotation? It can be difficult to fully evaluate the interactions between the two N-pollution pathways simultaneously in traditional field studies as drainage is largely unconstrained. Weighing lysimeters solve this issue by providing a closed system to measure N outputs via drainage and soil gas fluxes. A set of 18 weighting lysimeters were installed in Elora, Ontario, Canada in May 2016, to establish a long-term study of N-leaching and greenhouse gas emission from traditional and diverse cropping rotations for two different soil types. Each lysimeter is equipped with an automated chamber for continuous measurement of soil N2O and CO2 fluxes. A full characterization of variations of physical properties that may affect GHG emissions and N-leaching (e.g., soil temperature, moisture, drainage and evapotranspiration rates) amongst the lysimeters is required prior to application and assessment of the management treatments. Novel techniques such as wavelet analysis is required as standard statistical analyses are not applicable to the time series data. A full description of the lysimeters will be presented along with results of the characterization.

Criminals, Militias, and Insurgents: Organized Crime in Iraq

DTIC Science & Technology

2009-06-01

toppling of the regime, Iraq was also characterized by anomie. The concept of anomie, developed in the work of Emile 39 Durkheim and subsequently...behavior unconstrained by standard notions of what is acceptable. For Durkheim , this typically resulted from a crisis or transition in society in...concept of anomie, see The Durkheim and Merton Page at Middlesex University, London, United Kingdom, available at www.mdx. ac.uk/WWW/STUDY

Application of Biomedical Sensor and Transducer in the Elderly

NASA Astrophysics Data System (ADS)

Tamura, Toshiyo

In the elderly society, the sensor and transducers are applied to improve quality of life. Sensors are attached to the furniture or inside a room instead of attached to the human.The non-invasive and unconstrained monitoring are performed in the home and less constrained monitoring using portable-small sensor are used. In this paper, recent development of sensor and transducer in the Gerontechnology field is reviewed.

Adiabatic Quantum Computing with Neutral Atoms

NASA Astrophysics Data System (ADS)

Hankin, Aaron; Biedermann, Grant; Burns, George; Jau, Yuan-Yu; Johnson, Cort; Kemme, Shanalyn; Landahl, Andrew; Mangan, Michael; Parazzoli, L. Paul; Schwindt, Peter; Armstrong, Darrell

2012-06-01

We are developing, both theoretically and experimentally, a neutral atom qubit approach to adiabatic quantum computation. Using our microfabricated diffractive optical elements, we plan to implement an array of optical traps for cesium atoms and use Rydberg-dressed ground states to provide a controlled atom-atom interaction. We will develop this experimental capability to generate a two-qubit adiabatic evolution aimed specifically toward demonstrating the two-qubit quadratic unconstrained binary optimization (QUBO) routine.

Heterogenous fluorescence decay of (4→6)-and (4→8)-linked dimers of (+)-catechin and (-) epicatechin as a result of rotational isomerism.

Treesearch

Wolfgang R. Bergmann; Mary D. Barkley; Richard W. Hemingway; Wayne Mattice

1987-01-01

The time-resolved fluorescence of (+)-catechin and ( -)-epicatechin decays as a single exponential. In contrast dimers formed from (+)-catechin and (-)-epicatechin have more complex decays unless rotation about the interflavan bond is constrained by the introduction of a new ring. The fluorescence decay in unconstrained dimers is adequately described by the sum of two...

A New Method for Unconstrained Heart Rate Monitoring

DTIC Science & Technology

2001-10-25

members. However, care of bedridden elderly persons are not easy task, and this caused severe psychological and financial problems for other family...physical and mental conditions of bedridden elderly people at home and patients at hospitals and to contribute to the labor saving of the care and the...not suitable for home care of bedridden elderly people. Our method provides very small, simple and mechanically rugged device suitable for home

Distributed Learning, Extremum Seeking, and Model-Free Optimization for the Resilient Coordination of Multi-Agent Adversarial Groups

DTIC Science & Technology

2016-09-07

been demonstrated on maximum power point tracking for photovoltaic arrays and for wind turbines . 3. ES has recently been implemented on the Mars...high-dimensional optimization problems . Extensions and applications of these techniques were developed during the realization of the project. 15...studied problems of dynamic average consensus and a class of unconstrained continuous-time optimization algorithms for the coordination of multiple

Lateral dampers for thrust bearings

NASA Technical Reports Server (NTRS)

Hibner, D. H.; Szafir, D. R.

1985-01-01

The development of lateral damping schemes for thrust bearings was examined, ranking their applicability to various engine classes, selecting the best concept for each engine class and performing an in-depth evaluation. Five major engine classes were considered: large transport, military, small general aviation, turboshaft, and non-manrated. Damper concepts developed for evaluation were: curved beam, constrained and unconstrained elastomer, hybrid boost bearing, hydraulic thrust piston, conical squeeze film, and rolling element thrust face.

Constrained minimization of smooth functions using a genetic algorithm

NASA Technical Reports Server (NTRS)

Moerder, Daniel D.; Pamadi, Bandu N.

1994-01-01

The use of genetic algorithms for minimization of differentiable functions that are subject to differentiable constraints is considered. A technique is demonstrated for converting the solution of the necessary conditions for a constrained minimum into an unconstrained function minimization. This technique is extended as a global constrained optimization algorithm. The theory is applied to calculating minimum-fuel ascent control settings for an energy state model of an aerospace plane.

Department of Defense Mobile Device Strategy. Version 2.0

DTIC Science & Technology

2012-05-01

pilots and initiatives across DoD under common objectives, ensuring that the war:fighter benefits from such activities and aligns with efforts...regularly travel from place to place; and a growing number of teleworkers are beginning to operate from locations other than their primary offices...workforce with the benefits of mobile technology. Although achieving pockets of success, this unconstrained piloting has also resulted in the lack of

Sensor positioning and experimental constraints influence estimates of local dynamic stability during repetitive spine movements.

PubMed

Howarth, Samuel J; Graham, Ryan B

2015-04-13

Application of non-linear dynamics analyses to study human movement has increased recently, which necessitates an understanding of how dependent measures may be influenced by experimental design and setup. Quantifying local dynamic stability for a multi-articulated structure such as the spine presents the possibility for estimates to be influenced by positioning of kinematic sensors used to measure spine angular kinematics. Oftentimes researchers will also choose to constrain the spine's movement by physically restraining the pelvis and/or using targets to control movement endpoints. Ten healthy participants were recruited, and asked to perform separate trials of 35 consecutive cycles of spine flexion under both constrained and unconstrained conditions. Electromagnetic sensors that measure three-dimensional angular orientations were positioned over the pelvis and the spinous processes of L3, L1, and T11. Using the pelvic sensor as a reference, each sensor location on the spine was used to obtain a different representation of the three-dimensional spine angular kinematics. Local dynamic stability of each kinematic time-series was determined by calculating the maximum finite-time Lyapunov exponent (λmax). Estimates for λmax were significantly lower (i.e. dynamically more stable) for spine kinematic data obtained from the L3 sensor than those obtained from kinematic data using either the L1 or T11 sensors. Likewise, λmax was lower when the movement was constrained. These results emphasize the importance of proper placement of instrumentation for quantifying local dynamic stability of spine kinematics and are especially relevant for repeated measures designs where data are obtained from the same individual on multiple days. Copyright © 2015 Elsevier Ltd. All rights reserved.

Experimental and simulation studies of multivariable adaptive optimization of continuous bioreactors using bilevel forgetting factors.

PubMed

Chang, Y K; Lim, H C

1989-08-20

A multivariable on-line adaptive optimization algorithm using a bilevel forgetting factor method was developed and applied to a continuous baker's yeast culture in simulation and experimental studies to maximize the cellular productivity by manipulating the dilution rate and the temperature. The algorithm showed a good optimization speed and a good adaptability and reoptimization capability. The algorithm was able to stably maintain the process around the optimum point for an extended period of time. Two cases were investigated: an unconstrained and a constrained optimization. In the constrained optimization the ethanol concentration was used as an index for the baking quality of yeast cells. An equality constraint with a quadratic penalty was imposed on the ethanol concentration to keep its level close to a hypothetical "optimum" value. The developed algorithm was experimentally applied to a baker's yeast culture to demonstrate its validity. Only unconstrained optimization was carried out experimentally. A set of tuning parameter values was suggested after evaluating the results from several experimental runs. With those tuning parameter values the optimization took 50-90 h. At the attained steady state the dilution rate was 0.310 h(-1) the temperature 32.8 degrees C, and the cellular productivity 1.50 g/L/h.

Automatic extraction of numeric strings in unconstrained handwritten document images

NASA Astrophysics Data System (ADS)

Haji, M. Mehdi; Bui, Tien D.; Suen, Ching Y.

2011-01-01

Numeric strings such as identification numbers carry vital pieces of information in documents. In this paper, we present a novel algorithm for automatic extraction of numeric strings in unconstrained handwritten document images. The algorithm has two main phases: pruning and verification. In the pruning phase, the algorithm first performs a new segment-merge procedure on each text line, and then using a new regularity measure, it prunes all sequences of characters that are unlikely to be numeric strings. The segment-merge procedure is composed of two modules: a new explicit character segmentation algorithm which is based on analysis of skeletal graphs and a merging algorithm which is based on graph partitioning. All the candidate sequences that pass the pruning phase are sent to a recognition-based verification phase for the final decision. The recognition is based on a coarse-to-fine approach using probabilistic RBF networks. We developed our algorithm for the processing of real-world documents where letters and digits may be connected or broken in a document. The effectiveness of the proposed approach is shown by extensive experiments done on a real-world database of 607 documents which contains handwritten, machine-printed and mixed documents with different types of layouts and levels of noise.

Ambulatory estimation of mean step length during unconstrained walking by means of COG accelerometry.

PubMed

González, R C; Alvarez, D; López, A M; Alvarez, J C

2009-12-01

It has been reported that spatio-temporal gait parameters can be estimated using an accelerometer to calculate the vertical displacement of the body's centre of gravity. This method has the potential to produce realistic ambulatory estimations of those parameters during unconstrained walking. In this work, we want to evaluate the crude estimations of mean step length so obtained, for their possible application in the construction of an ambulatory walking distance measurement device. Two methods have been tested with a set of volunteers in 20 m excursions. Experimental results show that estimations of walking distance can be obtained with sufficient accuracy and precision for most practical applications (errors of 3.66 +/- 6.24 and 0.96 +/- 5.55%), the main difficulty being inter-individual variability (biggest deviations of 19.70 and 15.09% for each estimator). Also, the results indicate that an inverted pendulum model for the displacement during the single stance phase, and a constant displacement per step during double stance, constitute a valid model for the travelled distance with no need of further adjustments. It allows us to explain the main part of the erroneous distance estimations in different subjects as caused by fundamental limitations of the simple inverted pendulum approach.

Improving face image extraction by using deep learning technique

NASA Astrophysics Data System (ADS)

Xue, Zhiyun; Antani, Sameer; Long, L. R.; Demner-Fushman, Dina; Thoma, George R.

2016-03-01

The National Library of Medicine (NLM) has made a collection of over a 1.2 million research articles containing 3.2 million figure images searchable using the Open-iSM multimodal (text+image) search engine. Many images are visible light photographs, some of which are images containing faces ("face images"). Some of these face images are acquired in unconstrained settings, while others are studio photos. To extract the face regions in the images, we first applied one of the most widely-used face detectors, a pre-trained Viola-Jones detector implemented in Matlab and OpenCV. The Viola-Jones detector was trained for unconstrained face image detection, but the results for the NLM database included many false positives, which resulted in a very low precision. To improve this performance, we applied a deep learning technique, which reduced the number of false positives and as a result, the detection precision was improved significantly. (For example, the classification accuracy for identifying whether the face regions output by this Viola- Jones detector are true positives or not in a test set is about 96%.) By combining these two techniques (Viola-Jones and deep learning) we were able to increase the system precision considerably, while avoiding the need to manually construct a large training set by manual delineation of the face regions.

Use of a Dual Mobility Socket to Manage Total Hip Arthroplasty Instability

PubMed Central

Pibarot, Vincent; Vaz, Gualter; Chevillotte, Christophe; Béjui-Hugues, Jacques

2008-01-01

Unconstrained tripolar hip implants provide an additional bearing using a mobile polyethylene component between the prosthetic head and the outer metal shell. Such a design increases the effective head diameter and therefore is an attractive option in challenging situations of unstable total hip arthroplasties. We report our experience with 54 patients treated using this dual mobility implant in such situations. We ascertained its ability to restore and maintain stability, and examined component loosening and component failure. At a minimum followup of 2.2 years (mean, 4 years; range, 2.2–6.8 years), one hip had redislocated 2 months postoperatively and was managed successfully without reoperation by closed reduction with no additional dislocation. Two patients required revision of the implant because of dislocation at the inner bearing. Technical errors were responsible for these failures. Three patients had reoperations for deep infections. The postoperative radiographs at latest followup showed very satisfactory osseointegration of the acetabular component because no radiolucent line or osteolysis was reported. Use of this unconstrained tripolar design was successful in restoring and maintaining hip stability. We observed encouraging results at short-term followup regarding potential for loosening or mechanical failures. Level of Evidence: Level IV, therapeutic study. See the Guidelines for Authors for a complete description of levels of evidence. PMID:18780135

A Novel Walking Detection and Step Counting Algorithm Using Unconstrained Smartphones.

PubMed

Kang, Xiaomin; Huang, Baoqi; Qi, Guodong

2018-01-19

Recently, with the development of artificial intelligence technologies and the popularity of mobile devices, walking detection and step counting have gained much attention since they play an important role in the fields of equipment positioning, saving energy, behavior recognition, etc. In this paper, a novel algorithm is proposed to simultaneously detect walking motion and count steps through unconstrained smartphones in the sense that the smartphone placement is not only arbitrary but also alterable. On account of the periodicity of the walking motion and sensitivity of gyroscopes, the proposed algorithm extracts the frequency domain features from three-dimensional (3D) angular velocities of a smartphone through FFT (fast Fourier transform) and identifies whether its holder is walking or not irrespective of its placement. Furthermore, the corresponding step frequency is recursively updated to evaluate the step count in real time. Extensive experiments are conducted by involving eight subjects and different walking scenarios in a realistic environment. It is shown that the proposed method achieves the precision of 93.76 % and recall of 93.65 % for walking detection, and its overall performance is significantly better than other well-known methods. Moreover, the accuracy of step counting by the proposed method is 95.74 % , and is better than both of the several well-known counterparts and commercial products.

Subspecialization in the human posterior medial cortex

PubMed Central

Bzdok, Danilo; Heeger, Adrian; Langner, Robert; Laird, Angela R.; Fox, Peter T.; Palomero-Gallagher, Nicola; Vogt, Brent A.; Zilles, Karl; Eickhoff, Simon B.

2014-01-01

The posterior medial cortex (PMC) is particularly poorly understood. Its neural activity changes have been related to highly disparate mental processes. We therefore investigated PMC properties with a data-driven exploratory approach. First, we subdivided the PMC by whole-brain coactivation profiles. Second, functional connectivity of the ensuing PMC regions was compared by task-constrained meta-analytic coactivation mapping (MACM) and task-unconstrained resting-state correlations (RSFC). Third, PMC regions were functionally described by forward/reverse functional inference. A precuneal cluster was mostly connected to the intraparietal sulcus, frontal eye fields, and right temporo-parietal junction; associated with attention and motor tasks. A ventral posterior cingulate cortex (PCC) cluster was mostly connected to the ventromedial prefrontal cortex and middle left inferior parietal cortex (IPC); associated with facial appraisal and language tasks. A dorsal PCC cluster was mostly connected to the dorsomedial prefrontal cortex, anterior/posterior IPC, posterior midcingulate cortex, and left dorsolateral prefrontal cortex; associated with delay discounting. A cluster in the retrosplenial cortex was mostly connected to the anterior thalamus and hippocampus. Furthermore, all PMC clusters were congruently coupled with the default mode network according to task-constrained but not task-unconstrained connectivity. We thus identified distinct regions in the PMC and characterized their neural networks and functional implications. PMID:25462801

Online Pairwise Learning Algorithms.

PubMed

Ying, Yiming; Zhou, Ding-Xuan

2016-04-01

Pairwise learning usually refers to a learning task that involves a loss function depending on pairs of examples, among which the most notable ones are bipartite ranking, metric learning, and AUC maximization. In this letter we study an online algorithm for pairwise learning with a least-square loss function in an unconstrained setting of a reproducing kernel Hilbert space (RKHS) that we refer to as the Online Pairwise lEaRning Algorithm (OPERA). In contrast to existing works (Kar, Sriperumbudur, Jain, & Karnick, 2013 ; Wang, Khardon, Pechyony, & Jones, 2012 ), which require that the iterates are restricted to a bounded domain or the loss function is strongly convex, OPERA is associated with a non-strongly convex objective function and learns the target function in an unconstrained RKHS. Specifically, we establish a general theorem that guarantees the almost sure convergence for the last iterate of OPERA without any assumptions on the underlying distribution. Explicit convergence rates are derived under the condition of polynomially decaying step sizes. We also establish an interesting property for a family of widely used kernels in the setting of pairwise learning and illustrate the convergence results using such kernels. Our methodology mainly depends on the characterization of RKHSs using its associated integral operators and probability inequalities for random variables with values in a Hilbert space.

Constrained growth flips the direction of optimal phenological responses among annual plants.

PubMed

Lindh, Magnus; Johansson, Jacob; Bolmgren, Kjell; Lundström, Niklas L P; Brännström, Åke; Jonzén, Niclas

2016-03-01

Phenological changes among plants due to climate change are well documented, but often hard to interpret. In order to assess the adaptive value of observed changes, we study how annual plants with and without growth constraints should optimize their flowering time when productivity and season length changes. We consider growth constraints that depend on the plant's vegetative mass: self-shading, costs for nonphotosynthetic structural tissue and sibling competition. We derive the optimal flowering time from a dynamic energy allocation model using optimal control theory. We prove that an immediate switch (bang-bang control) from vegetative to reproductive growth is optimal with constrained growth and constant mortality. Increasing mean productivity, while keeping season length constant and growth unconstrained, delayed the optimal flowering time. When growth was constrained and productivity was relatively high, the optimal flowering time advanced instead. When the growth season was extended equally at both ends, the optimal flowering time was advanced under constrained growth and delayed under unconstrained growth. Our results suggests that growth constraints are key factors to consider when interpreting phenological flowering responses. It can help to explain phenological patterns along productivity gradients, and links empirical observations made on calendar scales with life-history theory. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Global Mass Flux Solutions from GRACE: A Comparison of Parameter Estimation Strategies - Mass Concentrations Versus Stokes Coefficients

NASA Technical Reports Server (NTRS)

Rowlands, D. D.; Luthcke, S. B.; McCarthy J. J.; Klosko, S. M.; Chinn, D. S.; Lemoine, F. G.; Boy, J.-P.; Sabaka, T. J.

2010-01-01

The differences between mass concentration (mas con) parameters and standard Stokes coefficient parameters in the recovery of gravity infonnation from gravity recovery and climate experiment (GRACE) intersatellite K-band range rate data are investigated. First, mascons are decomposed into their Stokes coefficient representations to gauge the range of solutions available using each of the two types of parameters. Next, a direct comparison is made between two time series of unconstrained gravity solutions, one based on a set of global equal area mascon parameters (equivalent to 4deg x 4deg at the equator), and the other based on standard Stokes coefficients with each time series using the same fundamental processing of the GRACE tracking data. It is shown that in unconstrained solutions, the type of gravity parameter being estimated does not qualitatively affect the estimated gravity field. It is also shown that many of the differences in mass flux derivations from GRACE gravity solutions arise from the type of smoothing being used and that the type of smoothing that can be embedded in mas con solutions has distinct advantages over postsolution smoothing. Finally, a 1 year time series based on global 2deg equal area mascons estimated every 10 days is presented.

Quantifying and Qualifying USGS ShakeMap Uncertainty

USGS Publications Warehouse

Wald, David J.; Lin, Kuo-Wan; Quitoriano, Vincent

2008-01-01

We describe algorithms for quantifying and qualifying uncertainties associated with USGS ShakeMap ground motions. The uncertainty values computed consist of latitude/longitude grid-based multiplicative factors that scale the standard deviation associated with the ground motion prediction equation (GMPE) used within the ShakeMap algorithm for estimating ground motions. The resulting grid-based 'uncertainty map' is essential for evaluation of losses derived using ShakeMaps as the hazard input. For ShakeMap, ground motion uncertainty at any point is dominated by two main factors: (i) the influence of any proximal ground motion observations, and (ii) the uncertainty of estimating ground motions from the GMPE, most notably, elevated uncertainty due to initial, unconstrained source rupture geometry. The uncertainty is highest for larger magnitude earthquakes when source finiteness is not yet constrained and, hence, the distance to rupture is also uncertain. In addition to a spatially-dependant, quantitative assessment, many users may prefer a simple, qualitative grading for the entire ShakeMap. We developed a grading scale that allows one to quickly gauge the appropriate level of confidence when using rapidly produced ShakeMaps as part of the post-earthquake decision-making process or for qualitative assessments of archived or historical earthquake ShakeMaps. We describe an uncertainty letter grading ('A' through 'F', for high to poor quality, respectively) based on the uncertainty map. A middle-range ('C') grade corresponds to a ShakeMap for a moderate-magnitude earthquake suitably represented with a point-source location. Lower grades 'D' and 'F' are assigned for larger events (M>6) where finite-source dimensions are not yet constrained. The addition of ground motion observations (or observed macroseismic intensities) reduces uncertainties over data-constrained portions of the map. Higher grades ('A' and 'B') correspond to ShakeMaps with constrained fault dimensions and numerous stations, depending on the density of station/data coverage. Due to these dependencies, the letter grade can change with subsequent ShakeMap revisions if more data are added or when finite-faulting dimensions are added. We emphasize that the greatest uncertainties are associated with unconstrained source dimensions for large earthquakes where the distance term in the GMPE is most uncertain; this uncertainty thus scales with magnitude (and consequently rupture dimension). Since this distance uncertainty produces potentially large uncertainties in ShakeMap ground-motion estimates, this factor dominates over compensating constraints for all but the most dense station distributions.

On Creativity: A Case Study of Military Innovation

DTIC Science & Technology

2015-09-01

HSI theses, it does not aim to define or refine the HSI process, nor does it seek to demonstrate how aspects of a problem pertain to or influence...Neuroscientists have found that the brain operates in both an externally focused, goal-directed mode, solving problems by the use of known patterns, and an...The entire brain is active when engaged in creative problem solving. During the creative process, an increase of new neurological connections between

Redd Site Selection and Spawning Habitat Use by Fall Chinook Salmon: The Importance of Geomorphic Features in Large Rivers

PubMed

Geist; Dauble

1998-09-01

/ Knowledge of the three-dimensional connectivity between rivers and groundwater within the hyporheic zone can be used to improve the definition of fall chinook salmon (Oncorhynchus tshawytscha) spawning habitat. Information exists on the microhabitat characteristics that define suitable salmon spawning habitat. However, traditional spawning habitat models that use these characteristics to predict available spawning habitat are restricted because they can not account for the heterogeneous nature of rivers. We present a conceptual spawning habitat model for fall chinook salmon that describes how geomorphic features of river channels create hydraulic processes, including hyporheic flows, that influence where salmon spawn in unconstrained reaches of large mainstem alluvial rivers. Two case studies based on empirical data from fall chinook salmon spawning areas in the Hanford Reach of the Columbia River are presented to illustrate important aspects of our conceptual model. We suggest that traditional habitat models and our conceptual model be combined to predict the limits of suitable fall chinook salmon spawning habitat. This approach can incorporate quantitative measures of river channel morphology, including general descriptors of geomorphic features at different spatial scales, in order to understand the processes influencing redd site selection and spawning habitat use. This information is needed in order to protect existing salmon spawning habitat in large rivers, as well as to recover habitat already lost.KEY WORDS: Hyporheic zone; Geomorphology; Spawning habitat; Large rivers; Fall chinook salmon; Habitat management

Cross-national comparisons of complex problem-solving strategies in two microworlds.

PubMed

Güss, C Dominik; Tuason, Ma Teresa; Gerhard, Christiane

2010-04-01

Research in the fields of complex problem solving (CPS) and dynamic decision making using microworlds has been mainly conducted in Western industrialized countries. This study analyzes the CPS process by investigating thinking-aloud protocols in five countries. Participants were 511 students from Brazil, Germany, India, the Philippines, and the United States who worked on two microworlds. On the basis of cultural-psychological theories, specific cross-national differences in CPS strategies were hypothesized. Following theories of situatedness of cognition, hypotheses about the specific frequency of problem-solving strategies in the two microworlds were developed. Results of the verbal protocols showed (a) modification of the theoretical CPS model, (b) task dependence of CPS strategies, and (c) cross-national differences in CPS strategies. Participants' CPS processes were particularly influenced by country-specific problem-solving strategies. Copyright © 2009 Cognitive Science Society, Inc.

Age-related changes in strategic variations during arithmetic problem solving: The role of executive control.

PubMed

Hinault, T; Lemaire, P

2016-01-01

In this review, we provide an overview of how age-related changes in executive control influence aging effects in arithmetic processing. More specifically, we consider the role of executive control in strategic variations with age during arithmetic problem solving. Previous studies found that age-related differences in arithmetic performance are associated with strategic variations. That is, when they accomplish arithmetic problem-solving tasks, older adults use fewer strategies than young adults, use strategies in different proportions, and select and execute strategies less efficiently. Here, we review recent evidence, suggesting that age-related changes in inhibition, cognitive flexibility, and working memory processes underlie age-related changes in strategic variations during arithmetic problem solving. We discuss both behavioral and neural mechanisms underlying age-related changes in these executive control processes. © 2016 Elsevier B.V. All rights reserved.

Numerical Investigation of Two-Phase Flows With Charged Droplets in Electrostatic Field

NASA Technical Reports Server (NTRS)

Kim, Sang-Wook

1996-01-01

A numerical method to solve two-phase turbulent flows with charged droplets in an electrostatic field is presented. The ensemble-averaged Navier-Stokes equations and the electrostatic potential equation are solved using a finite volume method. The transitional turbulence field is described using multiple-time-scale turbulence equations. The equations of motion of droplets are solved using a Lagrangian particle tracking scheme, and the inter-phase momentum exchange is described by the Particle-In-Cell scheme. The electrostatic force caused by an applied electrical potential is calculated using the electrostatic field obtained by solving a Laplacian equation and the force exerted by charged droplets is calculated using the Coulombic force equation. The method is applied to solve electro-hydrodynamic sprays. The calculated droplet velocity distributions for droplet dispersions occurring in a stagnant surrounding are in good agreement with the measured data. For droplet dispersions occurring in a two-phase flow, the droplet trajectories are influenced by aerodynamic forces, the Coulombic force, and the applied electrostatic potential field.

The impact of perceived self-efficacy on mental time travel and social problem solving.

PubMed

Brown, Adam D; Dorfman, Michelle L; Marmar, Charles R; Bryant, Richard A

2012-03-01

Current models of autobiographical memory suggest that self-identity guides autobiographical memory retrieval. Further, the capacity to recall the past and imagine one's self in the future (mental time travel) can influence social problem solving. We examined whether manipulating self-identity, through an induction task in which students were led to believe they possessed high or low self-efficacy, impacted episodic specificity and content of retrieved and imagined events, as well as social problem solving. Compared to individuals in the low self efficacy group, individuals in the high self efficacy group generated past and future events with greater (a) specificity, (b) positive words, and (c) self-efficacious statements, and also performed better on social problem solving indices. A lack of episodic detail for future events predicted poorer performance on social problem solving tasks. Strategies that increase perceived self-efficacy may help individuals to selectively construct a past and future that aids in negotiating social problems. Copyright © 2011 Elsevier Inc. All rights reserved.

Image Making and Meaning: Educational Benefits to Studying Design in the 21st Century

ERIC Educational Resources Information Center

Wynn, Nancy

2007-01-01

Over the past 27 years, the influence of technology has revolutionized the professional practice of Design and its products produced. At the same time, technology has also created more advanced and complex pedagogy for design education. However regardless of technology's influence, critical thinking, problem solving, and presentation are still…

The Influence of Different Representations on Solving Concentration Problems at Elementary School

ERIC Educational Resources Information Center

Liu, Chia-Ju; Shen, Ming-Hsun

2011-01-01

This study investigated the students' learning process of the concept of concentration at the elementary school level in Taiwan. The influence of different representational types on the process of proportional reasoning was also explored. The participants included nineteen third-grade and eighteen fifth-grade students. Eye-tracking technology was…

Generalized Linear Covariance Analysis

NASA Technical Reports Server (NTRS)

Carpenter, James R.; Markley, F. Landis

2014-01-01

This talk presents a comprehensive approach to filter modeling for generalized covariance analysis of both batch least-squares and sequential estimators. We review and extend in two directions the results of prior work that allowed for partitioning of the state space into solve-for'' and consider'' parameters, accounted for differences between the formal values and the true values of the measurement noise, process noise, and textita priori solve-for and consider covariances, and explicitly partitioned the errors into subspaces containing only the influence of the measurement noise, process noise, and solve-for and consider covariances. In this work, we explicitly add sensitivity analysis to this prior work, and relax an implicit assumption that the batch estimator's epoch time occurs prior to the definitive span. We also apply the method to an integrated orbit and attitude problem, in which gyro and accelerometer errors, though not estimated, influence the orbit determination performance. We illustrate our results using two graphical presentations, which we call the variance sandpile'' and the sensitivity mosaic,'' and we compare the linear covariance results to confidence intervals associated with ensemble statistics from a Monte Carlo analysis.

Multi-parameter geometrical scaledown study for energy optimization of MTJ and related spintronics nanodevices

NASA Astrophysics Data System (ADS)

Farhat, I. A. H.; Alpha, C.; Gale, E.; Atia, D. Y.; Stein, A.; Isakovic, A. F.

The scaledown of magnetic tunnel junctions (MTJ) and related nanoscale spintronics devices poses unique challenges for energy optimization of their performance. We demonstrate the dependence of the switching current on the scaledown variable, while considering the influence of geometric parameters of MTJ, such as the free layer thickness, tfree, lateral size of the MTJ, w, and the anisotropy parameter of the MTJ. At the same time, we point out which values of the saturation magnetization, Ms, and anisotropy field, Hk, can lead to lowering the switching current and overall decrease of the energy needed to operate an MTJ. It is demonstrated that scaledown via decreasing the lateral size of the MTJ, while allowing some other parameters to be unconstrained, can improve energy performance by a measurable factor, shown to be the function of both geometric and physical parameters above. Given the complex interdependencies among both families of parameters, we developed a particle swarm optimization (PSO) algorithm that can simultaneously lower energy of operation and the switching current density. Results we obtained in scaledown study and via PSO optimization are compared to experimental results. Support by Mubadala-SRC 2012-VJ-2335 is acknowledged, as are staff at Cornell-CNF and BNL-CFN.