Exactness of penalization for exact minimax penalty function method in nonconvex programming

The exact minimax penalty function method is used to solve a noncon- vex differentiable optimization problem with both inequality and equality constraints. The conditions for exactness of the penalization for the exact minimax penalty function method are established by assuming that the functions constituting the considered con- strained optimization problem are invex with respect to the same function η （with the exception of those equality constraints for which the associated Lagrange multipliers are negative these functions should be assumed to be incave with respect to η）. Thus, a threshold of the penalty parameter is given such that, for all penalty parameters exceeding this threshold, equivalence holds between the set of optimal solutions in the considered constrained optimization problem and the set of minimizer in its associated penalized problem with an exact minimax penalty function. It is shown that coercivity is not suf- ficient to prove the results.

Comparison of the efficacies of patching and penalization therapies for the treatment of amblyopia patients

AIM:To compare the efficacies of patching and penalization therapies for the treatment of amblyopia patients.METHODS:The records of 64 eyes of 50 patients 7 to16y of age who had presented to our clinics with a diagnosis of amblyopia,were evaluated retrospectively.Forty eyes of 26 patients who had received patching therapy and 24 eyes of 24 patients who had received penalization therapy included in this study.The latencies and amplitudes of visual evoked potential(VEP)records and best corrected visual acuities(BCVA)of these two groups were compared before and six months after the treatment.RESULTS:In both patching and the penalization groups,the visual acuities increased significantly following the treatments(P【0.05).The latency measurements of the P100 wave obtained at 1.0°,15 arc min.Patterns of both groups significantly decreased following the 6-months-treatment.However,the amplitude measurements increased(P【0.05).CONCLUSION:The patching and the penalization methods,which are the main methods used in the treatment of amblyopia,were also effective over the age of 7y,which has been accepted as the critical age for the treatment of amblyopia.

Objectively-measured compliance to atropine penalization treatment in children with amblyopia: a pilot study

Background:To date,compliance to atropine penalization in amblyopic children has only been assessed through self-report.The goal of this pilot study is to measure compliance to atropine penalization objectively.Methods:Seven amblyopic children(3-8 years;20/40-20/125 in the amblyopic eye) were enrolled.None had been treated with atropine previously.Children were prescribed either a twice per week or daily atropine regimen by their physicians.Compliance was defined as the percentage of days in which the atropine eye drop was taken compared to the number of doses prescribed.We used medication event monitoring system(MEMS) caps to objectively measure compliance.The MEMS caps are designed to electronically record the time and date when the bottle is opened.The parents of the children were provided a calendar log to subjectively report compliance.Participants were scheduled for return visits at 4 and 12 weeks.Weekly compliance was analyzed.Results:At 4 weeks,objective compliance averaged 88%(range,57-100%),while subjective compliance was 98%(range,90-100%).The actual dose in grams and visual acuity(VA) response relationship(r=0.79,P=0.03) was significantly better than the relationship between regimen and response(r=0.41,P>0.05),or the relationship between actual dose in drops and response(r=0.52,P>0.05).Conclusions:Objective compliance to atropine penalization instructions can be monitored with MEMS,which may facilitate our understanding of the dose-response relationship.Objective compliance with atropine penalization decreases over time and varies with regimen.On average,subjective parental reporting of compliance is overestimated.

Isogeometric topology optimization based on energy penalization for symmetric structure

We present an energy penalization method for isogeometric topology optimization using moving morphable components(ITO–MMC),propose an ITO–MMC with an additional bilateral or periodic symmetric constraint for symmetric structures,and then extend the proposed energy penalization method to an ITO–MMC with a symmetric constraint.The energy penalization method can solve the problems of numerical instability and convergence for the ITO–MMC and the ITO–MMC subjected to the structural symmetric constraint with asymmetric loads.Topology optimization problems of asymmetric,bilateral symmetric,and periodic symmetric structures are discussed to validate the effectiveness of the proposed energy penalization approach.Compared with the conventional ITO–MMC,the energy penalization method for the ITO–MMC can improve the convergence rate from 18.6%to 44.5%for the optimization of the asymmetric structure.For the ITO–MMC under a bilateral symmetric constraint,the proposed method can reduce the objective value by 5.6%and obtain a final optimized topology that has a clear boundary with decreased iterations.For the ITO–MMC under a periodic symmetric constraint,the proposed energy penalization method can dramatically reduce the number of iterations and obtain a speedup of more than 2.

Augmented Lagrangian Methods for p-Harmonic Flows with the Generalized Penalization Terms and Application to Image Processing

In this paper,we propose a generalized penalization technique and a convex constraint minimization approach for the p-harmonic flow problem following the ideas in[Kang&March,IEEE T.Image Process.,16(2007),2251–2261].We use fast algorithms to solve the subproblems,such as the dual projection methods,primal-dual methods and augmented Lagrangian methods.With a special penalization term,some special algorithms are presented.Numerical experiments are given to demonstrate the performance of the proposed methods.We successfully show that our algorithms are effective and efficient due to two reasons:the solver for subproblem is fast in essence and there is no need to solve the subproblem accurately(even 2 inner iterations of the subproblem are enough).It is also observed that better PSNR values are produced using the new algorithms.

A New Approach for Error Reduction in the Volume Penalization Method

A new approach for reducing error of the volume penalization method is proposed.The mask function is modified by shifting the interface between solid and fluid by√νηtoward the fluid region,whereνandηare the viscosity and the permeability,respectively.The shift length√νηis derived from the analytical solution of the one-dimensional diffusion equation with a penalization term.The effect of the error reduction is verified numerically for the one-dimensional diffusion equation,Burgers’equation,and the two-dimensional Navier-Stokes equations.The results show that the numerical error is reduced except in the vicinity of the interface showing overall second-order accuracy,while it converges to a non-zero constant value as the number of grid points increases for the original mask function.However,the new approach is effective when the grid resolution is sufficiently high so that the boundary layer,whose width is proportional to√νη,is resolved.Hence,the approach should be used when an appropriate combination ofνandηis chosen with a given numerical grid.

Classifying Big Medical Data through Bootstrap Decision Forest Using Penalizing Attributes

Decision forest is a well-renowned machine learning technique to address the detection and prediction problems related to clinical data.But,the tra-ditional decision forest(DF)algorithms have lower classification accuracy and cannot handle high-dimensional feature space effectively.In this work,we pro-pose a bootstrap decision forest using penalizing attributes(BFPA)algorithm to predict heart disease with higher accuracy.This work integrates a significance-based attribute selection(SAS)algorithm with the BFPA classifier to improve the performance of the diagnostic system in identifying cardiac illness.The pro-posed SAS algorithm is used to determine the correlation among attributes and to select the optimum subset of feature space for learning and testing processes.BFPA selects the optimal number of learning and testing data points as well as the density of trees in the forest to realize higher prediction accuracy in classifying imbalanced datasets effectively.The effectiveness of the developed classifier is cautiously verified on the real-world database(i.e.,Heart disease dataset from UCI repository)by relating its enactment with many advanced approaches with respect to the accuracy,sensitivity,specificity,precision,and intersection over-union(IoU).The empirical results demonstrate that the intended classification approach outdoes other approaches with superior enactment regarding the accu-racy,precision,sensitivity,specificity,and IoU of 94.7%,99.2%,90.1%,91.1%,and 90.4%,correspondingly.Additionally,we carry out Wilcoxon’s rank-sum test to determine whether our proposed classifier with feature selection method enables a noteworthy enhancement related to other classifiers or not.From the experimental results,we can conclude that the integration of SAS and BFPA outperforms other classifiers recently reported in the literature.

基于SIMP及应变能理论的高速动车齿轮箱结构优化

为获得高速动车齿轮箱最优结构设计方案,针对目前国产高速动车牵引齿轮箱箱体特点及存在的问题,基于SIMP(solid isotropic material with penalization)材料插值模型及应变能理论,利用软件HyperMesh中的拓扑优化与形状优化模块对动车齿轮箱箱体结构进行拓扑优化和局部形状优化。优化结果表明:优化后的动车齿轮箱结构的最大变形和最大应力有大幅度降低,能有效提高齿轮箱箱体的刚度和强度。文中结果可为设计性能优异的国产化高速动车齿轮箱提供数据支持。

Characterization, passive and active treatment in strabismic amblyopia: a narrative review

Strabismic amblyopia is characterized by a distorted spatial perception.In this condition,the neurofunctional disorder occurring during first years of life provoke several monocular and binocular anomalies such as crowding,deficits in the accommodative response,contrast sensitivity,and ocular motility abilities.The inhibition of the binocular function of the brain by the misaligned amblyopic eye induces a binocular imbalance leading to interocular suppression and the reduction or lack of stereoacuity.Passive treatments such as occlusion,optical and/or pharmacological penalization,and Bangerter foils has been demonstrated to be potentially useful treatments for strabismic amblyopia.Recent researches have proved new pharmacological options to improve and maintain visual acuity af ter occlusion treatment in strabismic amblyopia.Likewise,the active vision therapy,in the last years,is becoming a very relevant therapeutic option in combination with passive treatments,especially during and after monocular therapy,in the attempt of recovering the imbalanced binocular vision.

MULTIPLICITY AND CONCENTRATION BEHAVIOUR OF POSITIVE SOLUTIONS FOR SCHRDINGER-KIRCHHOFF TYPE EQUATIONS INVOLVING THE p-LAPLACIAN IN R^N

In this article, we study the multiplicity and concentration behavior of positive solutions for the p-Laplacian equation of SchrSdinger-Kirchhoff type -εpM（εp-N∫RN｜△u｜p）△pu＋v（x｜u｜p-2u=f（u）in RN, where △p is the p-Laplacian operator, 1 〈 p 〈 N, M ： R＋ → R＋ and V ： RN →R＋ are continuous functions, ε is a positive parameter, and f is a continuous function with subcritical growth. We assume that V satisfies the local condition introduced by M. del Pino and P. Felmer. By the variational methods, penalization techniques, and Lyusternik- Schnirelmann theory, we prove the existence, multiplicity, and concentration of solutions for the above equation.

Entropy Unilateral Solution for Some Noncoercive Nonlinear Parabolic Problems Via a Sequence of Penalized Equations

We give an existence result of the obstacle parabolic equations3b（x,u） div（a（x,t,u, Vu））＋div（（x,t,u））=f in QT, 3twhere b（x,u） is bounded function ot u, the term atva,x,r,u, v u）） is a Letay type operator and the function is a nonlinear lower order and satisfy only the growth condition. The second term belongs to L1 （QT）. The proof of an existence solution is based on the penalization methods.

An adaptive method for high-resolution topology design

For the purpose of achieving high-resolution optimal solutions this paper proposes a nodal design variablebased adaptive method for topology optimization of continuum structures. The analysis mesh-independent density field, interpolated by the nodal design variables at a given set of density points, is adaptively refined/coarsened accord- ing to a criterion regarding the gray-scale measure of local regions. New density points are added into the gray regions and redundant ones are removed from the regions occupied by purely solid/void phases for decreasing the number of de- sign variables. A penalization factor adaptivity technique is employed-to prevent premature convergence of the optimiza- tion iterations. Such an adaptive scheme not only improves the structural boundary description quality, but also allows for sufficient further topological evolution of the structural layout in higher adaptivity levels and thus essentially enables high-resolution solutions. Moreover, compared with the case with uniformly and finely distributed density points, the proposed adaptive method can achieve a higher numerical efficiency of the optimization process.

Influence of wing flexibility on the aerodynamic performance of a tethered flapping bumblebee

The sophisticated structures of flapping insect wings make it challenging to study the role of wing flexibility in insect flight.In this study,a mass-spring system is used to model wing structural dynamics as a thin,flexible membrane supported by a network of veins.The vein mechanical properties can be estimated based on their diameters and the Young's modulus of cuticle.In order to analyze the effect of wing flexibility,the Young's modulus is varied to make a comparison between two different wing models that we refer to as flexible and highly flexible.The wing models are coupled with a pseudo-spectral code solving the incompressible Navier–Stokes equations,allowing us to investigate the influence of wing deformation on the aerodynamic efficiency of a tethered flapping bumblebee.Compared to the bumblebee model with rigid wings,the one with flexible wings flies more efficiently,characterized by a larger lift-to-power ratio.

THE MULTIPLICITY AND CONCENTRATION OF POSITIVE SOLUTIONS FOR THE KIRCHHOFF-CHOQUARD EQUATION WITH MAGNETIC FIELDS

In this paper,we study the multiplicity and concentration of positive solutions for the following fractional Kirchhoff-Choquard equation with magnetic fields:(aε^(2s)+bε^(4 s-3)[u]_(ε)^(2),A/ε)(-Δ)_(A/ε)^(s)u+V(x)u=ε^(-α)(Iα*F(|u|^(2)))f(|u|^(2))u in R^(3).Hereε>0 is a small parameter,a,b>0 are constants,s E(0,1),(-Δ)As is the fractional magnetic Laplacian,A:R^(3)→R^(3) is a smooth magnetic potential,Iα=Γ(3-α/2)/2απ3/2Γ(α/2)·1/|x|^(α) is the Riesz potential,the potential V is a positive continuous function having a local minimum,and f:R→R is a C^(1) subcritical nonlinearity.Under some proper assumptions regarding V and f,we show the multiplicity and concentration of positive solutions with the topology of the set M:={x∈R^(3):V(x)=inf V}by applying the penalization method and LjusternikSchnirelmann theory for the above equation.

Design of small-scale gradient coils in magnetic resonance imaging by using the topology optimization method

A topology optimization method based on the solid isotropic material with penalization interpolation scheme is utilized for designing gradient coils for use in magnetic resonance microscopy. Unlike the popular stream function method, the proposed method has design variables that are the distribution of conductive material. A voltage-driven transverse gradient coil is proposed to be used as micro-scale magnetic resonance imaging（MRI） gradient coils, thus avoiding introducing a coil-winding pattern and simplifying the coil configuration. The proposed method avoids post-processing errors that occur when the continuous current density is approximated by discrete wires in the stream function approach. The feasibility and accuracy of the method are verified through designing the z-gradient and y-gradient coils on a cylindrical surface.Numerical design results show that the proposed method can provide a new coil layout in a compact design space.

A Cell-Based Linear Smoothed Finite Element Method for Polygonal Topology Optimization

The aim of this work is to employ a modified cell-based smoothed finite element method(S-FEM)for topology optimization with the domain discretized with arbitrary polygons.In the present work,the linear polynomial basis function is used as the weight function instead of the constant weight function used in the standard S-FEM.This improves the accuracy and yields an optimal convergence rate.The gradients are smoothed over each smoothing domain,then used to compute the stiffness matrix.Within the proposed scheme,an optimum topology procedure is conducted over the smoothing domains.Structural materials are distributed over each smoothing domain and the filtering scheme relies on the smoothing domain.Numerical tests are carried out to pursue the performance of the proposed optimization by comparing convergence,efficiency and accuracy.

ASYMPTOTIC PROPERTIES OF ESTIMATORS IN PARTIALLY LINEAR SINGLE-INDEX MODEL FOR LONGITUDINAL DATA

In this article, a partially linear single-index model /or longitudinal data is investigated. The generalized penalized spline least squares estimates of the unknown parameters are suggested. All parameters can be estimated simultaneously by the proposed method while the feature of longitudinal data is considered. The existence, strong consistency and asymptotic normality of the estimators are proved under suitable conditions. A simulation study is conducted to investigate the finite sample performance of the proposed method. Our approach can also be used to study the pure single-index model for longitudinal data.

Penalized total least squares method for dealing with systematic errors in partial EIV model and its precision estimation

When the total least squares(TLS)solution is used to solve the parameters in the errors-in-variables(EIV)model,the obtained parameter estimations will be unreliable in the observations containing systematic errors.To solve this problem,we propose to add the nonparametric part(systematic errors)to the partial EIV model,and build the partial EIV model to weaken the influence of systematic errors.Then,having rewritten the model as a nonlinear model,we derive the formula of parameter estimations based on the penalized total least squares criterion.Furthermore,based on the second-order approximation method of precision estimation,we derive the second-order bias and covariance of parameter estimations and calculate the mean square error(MSE).Aiming at the selection of the smoothing factor,we propose to use the U curve method.The experiments show that the proposed method can mitigate the influence of systematic errors to a certain extent compared with the traditional method and get more reliable parameter estimations and its precision information,which validates the feasibility and effectiveness of the proposed method.

HAZARD REGRESSION WITH PENALIZED SPLINE:THE SMOOTHING PARAMETER CHOICE AND ASYMPTOTICS

In this article, we use penalized spline to estimate the hazard function from a set of censored failure time data. A new approach to estimate the amount of smoothing is provided. Under regularity conditions we establish the consistency and the asymptotic normality of the penalized likelihood estimators. Numerical studies and an example are conducted to evaluate the performances of the new procedure.

Additive mixed models to study the effect of tree age and climatic factors on stem radial growth of Eucalyptus trees

The effect of tree age and climatic variables on stem radial growth of two hybrid clones of Eucalyptus was determined using longitudinal data from eastern South Africa.The stem radius of was measured weekly as the response variable.In addition to tree age,average weekly temperature,solar radiation,relative humidity and wind speed were simultaneously recorded with total rainfall at the site.An additive mixed effects model that incorporates a non-parametric smooth function was used.The results of the analysis indicate that the relationship between stem radius and each of the covariates can be explained by nonlinear functions.Models that account for the effect of clone and season together with their interaction in the parametric part of the additive mixed model were also fitted.The interaction between clone and season was not significant in all cases.For analyzing the joint effect all the covariates,additive mixed models that included two or more covariates were fitted.A significant effect of tree age was found in all cases.Although tree age was the key determinant of stem radial growth,weather variables also had a significant effect that was dependent on season.