Optimal adaptive generalized Pólya urn design for multi-arm clinical trials

A class of optimal adaptive multi-arm clinical trial designs is proposed based on an extended generalized Pólya urn (GPU) model. The design is applicable to both the qualitative and quantitative responses and achieves, asymptotically, some pre-specified optimality criterion. Such criterion is specified by a functional of the response distributions and is implemented through the relationship between the design matrix and its first eigenvector. The asymptotic properties of the design are studied using the existing methods on GPU. Some examples for commonly used clinical designs are given as illustration.     

基于似无关回归的多元稳健损失函数方法

针对多响应参数优化问题,考虑响应间相关性和可控因子波动的影响,提出了一种基于似无关回归的多元稳健损失函数方法。首先采用似无关回归对模型拟合和过程优化中的相关参数进行估计,更有效地利用响应间相关性信息;然后利用给定点处梯度信息来估计可控因子波动对过程稳健性的影响。算例表明,当响应间存在相关性时,与最小二乘方法相比,采用似无关回归拟合的响应曲面模型精度更高;与传统质量损失函数相比,在采用相同质量成本矩阵时,采用稳健损失函数方法得到的最优解处期望质量损失更小。     

Modeling and simulation of injection molding process of polymer melt by a robust SPH method

In the present study, the injection molding process of polymer melt based on the generalized Newtonian fluid model is investigated by a robust smoothed particle hydrodynamics (SPH) method. The numerical method is proposed by introducing a Rusanov flux into the continuity equation to improve the prediction of the pressure distribution and employing a corrected kernel gradient to improve the computational accuracy. In addition, a robust treatment of solid boundary is presented and verified by the spin-down problem. The merits of the robust SPH method are firstly illustrated by 2D dam breaking flow. Then the numerical method is extended to deal with the flow phenomena related to injection molding process of polymer melt. A number of numerical examples including 2D injection moldings of a thin plate mold, a circular disc with core, a ring-shaped channel, and a S-shaped cavity, and 3D injection moldings of a Z-shaped cavity and a four-legged fork are conducted. The numerical results are in agreement with the experiments, which demonstrate that the SPH method proposed here is capable of handling with injection molding process of polymer melt in a robust manner. Moreover, the robust SPH method allows to recover the fluctuations-free pressure and velocity fields which in most cases cannot be easily obtained by the traditional SPH method.     

Applying neural network and scatter search to optimize parameter design with dynamic characteristics

Parameter design is critical to enhancing a system's robustness by identifying specific control factor set points (levels) that make the system least sensitive to noise. Engineers have conventionally applied Taguchi methods to optimize parameter design. However, Taguchi methods can only obtain the optimal solution among the specified control factor levels. They cannot identify the real optimum when the parameter values are continuous. This study proposes a hybrid procedure combining neural networks and scatter search to optimize the continuous parameter design problem. First, neural networks are used to simulate the relationship between the control factor values and corresponding responses. Second, scatter search is employed to obtain the optimal parameter settings. The desirability function is utilized to transform the multiple responses into a single response. A case with dynamic characteristics is carried out in blood glucose strip manufacturing in Taiwan to demonstrate the practicability of the proposed procedure.     

Extension of SPH to simulate non-isothermal free surface flows during the injection molding process

This article presents an extension of smoothed particle hydrodynamics (SPH) to non-isothermal free surface flows during the injection molding process. Specifically, we use the method presented by Xu and Yu, Appl. Math. Model. 48 (2017) pp. 384–409, in which the corrected kernel gradient is implemented to increase the computational accuracy and the Rusanov flux is introduced into the continuity equation to alleviate large and random pressure oscillations. To model non-isothermal free surface flows, a working SPH discretization of the temperature equation is derived. An enhanced treatment of the wall boundary is further developed, which can model arbitrary-shaped mold walls. The proposed SPH method is first validated by solving non-isothermal Couette flow and non-isothermal injection molding of a circular disc with a core and comparing the SPH results with those obtained by other numerical methods or experiments. We then extend the numerical method to non-isothermal injection molding of F-shaped and N-shaped cavities. The convergence of the method is examined with several different particle sizes. The effects of the operating conditions (e.g., injection temperature, temperature of the mold wall, and injection velocity) on the flow behavior are analyzed. All the results illustrate that the present SPH method is a powerful computational tool for simulations of non-isothermal free surface flows during the injection molding process.     

Single objective layout design of user interface components with multiple qualitative factors

The purpose of this paper is to present a model to design the layout of the user interface components that handles many numbers of qualitative factors. An alternate rating system is also proposed for the closeness relationship ratings between the various pairs of components evaluated by using GOMS (goals, operators, methods and selection rules) technique. The proposed model is applied to the design of the part of the user interface in order to obtain the best layout of the components. The results of the proposed model are compared with that of an existing model, which handles single qualitative factor applied to obtain the layouts of user interface components.     

Exploring the Relationship Between Teaching Efficacy and Cultural Efficacy of Novice Science Teachers in High‐Needs Schools

This qualitative case study sought to investigate what relationship exists between teaching efficacy and cultural efficacy of novice science teachers in high‐needs, high‐minority urban schools. One major theme—the importance of establishing positive teacher–student relationships—surrounding teaching efficacy in the context of cultural efficacy emerged. The data sources included: (a) teachers' responses to a focus group interview conducted at the end of their first year, (b) written reports and documentation from university‐based field supervisors' observations during the teachers' first year, and (c) teachers' self‐reported responses on the Science Teaching Efficacy Belief Instrument designed to measure science teaching efficacy. Final analysis of the data reflects a strong relationship between teaching efficacy and practice within the context of culture. The results of this study also indicated an existing relationship between teaching efficacy and cultural efficacy through cultural connections with students. Encouraging the development of teacher efficacy in the context of cultural efficacy becomes important at all levels of teacher preparation, especially to ensure the retention of high‐quality science teachers in high‐needs schools.     

An interactive desirability function method to multiresponse optimization

Multiresponse optimization problems often involve incommensurate and conflicting responses. To obtain a satisfactory compromise in such a case, a decision maker (DM)’s preference information on the tradeoffs among the responses should be incorporated into the problem. This paper proposes an interactive method based on the desirability function approach to facilitate the preference articulation process. The proposed method allows the DM to adjust any of the preference parameters, namely, the shape, bound, and target of a desirability function in a single, integrated framework. The proposed method would be highly effective in generating a compromise solution that is faithful to the DM’s preference structure.     

Optimal Control for an SEIR Epidemic Model with Nonlinear Incidence Rate

The objective of this paper is to explore possible impacts of nonlinearity of functional responses and a number of compartments of an infection disease model on principal qualitative properties of the optimal controls. To address this issue, we consider optimal controls for an Susceptible‐Exposed‐Infectious‐Removed (SEIR) model of an endemically persisting infectious disease. We assume that the incidence rate is given by an unspecified nonlinear function constrained by a few biologically motivated conditions. For this model, we consider five controls (which comprise all controls that are possible for this model) with a possibility of acting simultaneously, and establish principal qualitative properties of the controls. A comparison with a similar SIR model is provided.     

Bayesian inference on partially linear mixed-effects joint models for longitudinal data with multiple features

The relationship between viral load and CD4 cell count is one of the interesting questions in AIDS research. Statistical models are powerful tools for clarifying this important problem. Partially linear mixed-effects (PLME) model which accounts for the unknown function of time effect is one of the important models for this purpose. Meanwhile, the mixed-effects modeling approach is suitable for the longitudinal data analysis. However, the complex process of data collection in clinical trials has made it impossible to rely on one particular model to address the issues. Asymmetric distribution, measurement error and left censoring are features commonly arisen in longitudinal studies. It is crucial to take into account these features in the modeling process to achieve reliable estimation and valid conclusion. In this article, we establish a joint model that accounts for all these features in the framework of PLME models. A Bayesian inferential procedure is proposed to estimate parameters in the joint model. A real data example is analyzed to demonstrate the proposed modeling approach for inference and the results are reported by comparing various scenarios-based models.     

Fuzzy measures of supplier evaluation under lean concepts

Supplier evaluation is a multiple attribute decision-making (MADM) problem involving a mixture of qualitative and quantitative attributes. Some mathematical programming techniques have difficulty in dealing with the qualitative attributes that are not easy to measure but very important in supplier evaluation. Fuzzy set theory is useful whenever variables defining a complex and vague system can neither be quantitatively defined nor assigned very precise measures, but are described by linguistic values. This paper presents a procedure for supplier evaluation by incorporating fuzzy set theory into the evaluation process to handle the qualitative attributes in the problem. A mathematical ranking method is used to convert the qualitative attributes into crisp scores. All the quantitative and qualitative performance measures are normalized and then using the proposed model, data are integrated into a single score to rank suppliers. The model application is demonstrated through two previously reported data sets under lean philosophy.     

Ⅰ型拉伸试样金属注射成形多相流动的三维数值模拟

将粉末注射成形充模过程视为粘结剂、粉末和空气的三相流动过程,基于多相流理论给出金属注射成形的多相流动控制方程。根据金属注射成形的工艺特点确定多相流动控制方程的初边界条件,用多相流数值分析软件CFX对Ⅰ型拉伸试样的铁粉注射成形充模流动过程实现了三维数值模拟,分析了模腔中不同位置处粘结剂一粉末流动的速度曲线。数值模拟结果表明在Ⅰ型拉伸试样金属注射成形充模流动过程中发生过两相分离的现象,数值模拟的瞬态信息可用于金属注射成形产品缺陷的分析与控制。     

具有类反斜线回滞执行器的非线性系统的自适应控制

针对类反斜线回滞非线性系统,设计了自适应控制器,保持系统稳定并实现对参考信号的任意精度跟踪.在控制器设计中,通过构造足够光滑的非线性函数作为符号函数的逼近,从而解决了传统自适应控制器设计中由于符号函数的引入而导致控制器不连续的问题,避免了因此而产生的抖震现象.在系统模型中充分考虑未建模动态,使模型更具一般性.最后应用MATLAB软件进行仿真实验,结果进一步验证了该控制器的有效性.     

Ⅱ型区间删失数据下广义部分线性模型的筛极大似然估计(英文)

This article concerded with a semiparametric generalized partial linear model （GPLM） with the type Ⅱ censored data. A sieve maximum likelihood estimator （MLE） is proposed to estimate the parameter component, allowing exploration of the nonlinear relationship between a certain covariate and the response function. Asymptotic properties of the proposed sieve MLEs are discussed. Under some mild conditions, the estimators are shown to be strongly consistent. Moreover, the estimators of the unknown parameters are asymptotically normal and efficient, and the estimator of the nonparametric function has an optimal convergence rate.     

A Bayesian approach for multiple criteria decision making with applications in Design for Six Sigma

Linking end-customer preferences with variables controlled at a manufacturing plant is a main idea behind popular Design for Six Sigma management techniques. Multiple criteria decision making (MCDM) approaches can be used for such purposes, but in these techniques the decision-maker's (DM) utility function, if modelled explicitly, is considered known with certainty once assessed. Here, a new algorithm is proposed to solve a MCDM problem with applications to Design for Six Sigma based on a Bayesian methodology. At a first stage, it is assumed that there are process responses that are functions of certain controllable factors or regressors. This relation is modelled based on experimental data. At a second stage, the utility function of one or more DMs or customers is described in a statistical model as a function of the process responses, based on surveys. This step considers the uncertainty in the utility function(s) explicitly. The methodology presented then maximizes the probability that the DM's or customer's utility is greater than some given lower bound with respect to the controllable factors of the first stage. Both stages are modelled with Bayesian regression techniques. The advantages of using the Bayesian approach as opposed to traditional methods are highlighted.     

The convergence of a dual algorithm for nonlinear programming

A dual algorithm based on the smooth function proposed by Polyak (1988) is constructed for solving nonlinear programming problems with inequality constraints. It generates a sequence of points converging locally to a Kuhn-Tucker point by solving an unconstrained minimizer of a smooth potential function with a parameter. We study the relationship between eigenvalues of the Hessian of this smooth potential function and the parameter, which is useful for analyzing the effectiveness of the dual algorithm.     

粘附弹性体切变的定解问题及其差分解法

两刚性平行平面之间粘附长条弹性体(其横截面为矩形),在上下两面相反方向切向力的作用下,弹性体将发生变形.在导出这种变形的数学模型的基础上,给出了一种新的差分解法.对于具有奇性的边界条件,进行了详细的分析和推导,给出了一种合理而有效的新的离散边界条件.模拟计算表明,其结果与定性分析相吻合.因此对该类问题的研究提供了新的实用的数值解法和数值分析方法.     

Rheology of Organodispersions of Alumina Nanopowders Used in Producing Articles from Engineering Ceramics

The rheological properties of molding suspensions of alumina nanopowder in paraffin have been studied. Powders with specific surface areas of 32 and 55 m²/g and the surface-active substances oleic acid and Hypermer LP1 were used. The Hamaker constant for alumina particles in paraffin wax was estimated. A rough calculation showed that a gel should arise in the suspensions studied. The linearly viscoelastic characteristics determined by the method of small-amplitude periodic shear (on the frequency range from 0.063 to 157 s⁻¹) confirmed this conclusion. The flow curves of the molding feedstock, determined over a broad range of shear rates (from 0.018 to 1070 s⁻¹), point to a pseudoplastic character of the flow. From the rheological studies it follows that, in manufacturing engineering ceramics by injection molding from the suspensions investigated and in designing or selecting the forming equipment, the realization of maximum high shear strains must be ensured, which will promote a qualitative filling of intricately shaped and small-size molds.__________Translated from Mekhanika Kompozitnykh Materialov, Vol. 41, No. 3, pp. 373–390, May–June, 2005.     

Inference for Shot Noise

This paper studies estimation issues for Poisson shot noise models from a data history observed on a discrete-time lattice. Optimal estimating function methods in the sense of Godambe (1985) are developed for the case when the impulse response function of the shot process is interval similar; moment methods are explored for compactly supported impulse responses. Asymptotic normality of the proposed estimates is established and the limiting covariance of the estimates is derived. Applications of the methods to several parametric shot function types are presented.     

Control-oriented modeling of servo-pump driven injection molding machines in the filling and packing phase

Servo-valves or variable displacement pumps are typically used to control conventional hydraulic injection molding machines (IMMs). Recent developments in electrical drive technology allow to utilize servo-motor driven pumps instead, which is beneficial due to their higher energy efficiency. Their dynamic behavior, however, is significantly different compared to the conventional setup. Thus, currently used mathematical models and control concepts cannot be directly applied. This paper presents a computationally efficient and scalable mathematical model of the injection process for these servo-pump driven IMMs. A first-principles model of the injection machine is combined with a phenomenological model describing the injection process, i.e. the compression of the melt and the polymer flow into the mold. The proposed model is tailored to real-time applications and serves as an ideal basis for the design of model-based control strategies. The feasibility of the proposed model is demonstrated by a number of different experiments. They confirm a high model accuracy over the whole operating range for different mold geometries.