Optimal ensemble construction via meta-evolutionary ensembles

In this paper, we propose a meta-evolutionary approach to improve on the performance of individual classifiers. In the proposed system, individual classifiers evolve, competing to correctly classify test points, and are given extra rewards for getting difficult points right. Ensembles consisting of multiple classifiers also compete for member classifiers, and are rewarded based on their predictive performance. In this way we aim to build small-sized optimal ensembles rather than form large-sized ensembles of individually-optimized classifiers. Experimental results on 15 data sets suggest that our algorithms can generate ensembles that are more effective than single classifiers and traditional ensemble methods.     

孕妇服装的设计与选择

针对孕妇的生理和心理特征，从结构、色彩、材料等方面论述了孕妇服装设计要有利于孕妇和胎儿的安全及身心健康，介绍了几款不同类型的孕妇装，指出了孕妇内衣和鞋子的选择应遵循的原则。     

真空制盐蒸发结晶器的设计与实践

真空蒸发制盐外热式强制逆循环轴向出料蒸发结晶器，经多个厂家生产应用实践证明是成功的，具有生命力的。这种新型结构，作为一项新技术新设备应加强研究，总结提高，推广应用。不断完善。文章从流体力学、结晶机理角度要求，到具体工程设计参数和材质选用。论述了该罐的特点。     

珠钢滤波-无功补偿优化调整方案

本文主要论述了珠钢滤波-无功补偿优化调整方案在生产中的应用。     

Anti-Dissipative Schemes for Advection and Application to Hamilton–Jacobi–Bellmann Equations

We propose two new antidiffusive schemes for advection (or linear transport), one of them being a mixture of Roe’s Super-Bee scheme and of the “Ultra-Bee” scheme. We show how to apply these schemes to treat time-dependent first order Hamilton–Jacobi–Bellman equations with discontinuous initial data, possibly infinitely-valued. Numerical tests are proposed, in one and two space dimensions, in order to validate the methods AMS subject classifications. Primary 65M12, Secondary 58J47     

长距离温泉输水管道设计

福州市首次把城市外围的温泉水引入市区,本文简要介绍长距离温泉输水管道设计中一些做法。     

浅谈工程设计阶段的造价控制

文章主要介绍针对工程设计现状,分析工程造价失控原因,提出控制造价要点及方法,为有效控制工程造价提供探讨。     

Differential effects of cue changes and task changes on task-set selection costs.

A task-switching paradigm with a 2:1 mapping between cues and tasks was used to separate cue-switching processes (indexed through pure cue-switch costs) from actual task-switching processes (indexed through additional costs in case of cue and task changes). A large portion of total switch costs was due to cue changes (Experiments 1 and 2), and cue-switch costs but not task-switch costs were sensitive to effects of practice (Experiment 1) and preparation (Experiment 2). In contrast, task-switch costs were particularly sensitive to response-priming effects (Experiments 1 and 2) and task-set inhibition (Experiment 3). Results suggest two processing stages relevant during task-set selection: cue-driven retrieval of task rules from long-term memory and the automatic application of rules to a particular stimulus situation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Three-dimensional MHD high-resolution computations with CWENO employing adaptive mesh refinement

Until recently, numerical simulations of discontinuities in highly super-Alfvénic plasmas have been severely limited by comparatively crude resolution and accuracy. Significant progress in the numerical simulation of such plasmas was achieved with the recently implemented Central Weighted Essentially Non-Oscillatory (CWENO) scheme. Combining this technique with that of adaptive mesh refinement (AMR), we have developed a third-order numerical scheme, which is able to efficiently capture strong gradients on spatial scales being small compared to the overall scale of the plasma system considered. Here, we first describe important algorithmic aspects of the scheme as well as the physics included in it. Second, we present the results of various performance tests. And, third, we illustrate its application to ‘real world problems’ using the example of the dynamics of a Sedov-type explosion.     

Estimation for the number of components in a mixture model using stepwise split-and-merge EM algorithm

The main difficulty with EM algorithm for mixture model concerns the number of components, say g. This is the question of model selection, and the EM algorithm itself could not estimate g. On the contrary, the algorithm requires g to be specified before the remaining parameters can be estimated. To solve this problem, a new algorithm, which is called stepwise split-and-merge EM (SSMEM) algorithm, is proposed. The SSMEM algorithm alternately splits and merges components, estimating g and other parameters of components simultaneously. Also, two novel criteria are introduced to efficiently select the components for split or merge. Experimental results on simulated and real data demonstrate the effectivity of the proposed algorithm.