Classes of Split‐plot Response Surface Designs for Equivalent Estimation

When planning an experimental investigation, we are frequently faced with factors that are difficult or time consuming to manipulate, thereby making complete randomization impractical. A split‐plot structure differentiates between the experimental units associated with these hard‐to‐change factors and those that are relatively easy‐to‐change. Furthermore, it provides an efficient strategy that integrates the restrictions imposed by the experimental apparatus into the design structure. In this paper, several industrial and scientific examples are presented to highlight design considerations when a restriction on randomization is encountered. We propose classes of split‐plot response designs that provide an intuitive and natural extension from the completely randomized context. For these designs, the ordinary least‐squares estimates of the model are equivalent to the generalized least‐squares estimates. This property provides best linear unbiased estimators and simplifies model estimation. The design conditions that provide equivalent estimation are presented and lead to design construction strategies to transform completely randomized Box–Behnken, equiradial and small composite designs into a split‐plot structure. Published in 2006 by John Wiley & Sons, Ltd.     

Mixed Methods Research Designs in Counseling Psychology.

With the increased popularity of qualitative research, researchers in counseling psychology are expanding their methodologies to include mixed methods designs. These designs involve the collection, analysis, and integration of quantitative and qualitative data in a single or multiphase study. This article presents an overview of mixed methods research designs. It defines mixed methods research, discusses its origins and philosophical basis, advances steps and procedures used in these designs, and identifies 6 different types of designs. Important design features are illustrated using studies published in the counseling literature. Finally, the article ends with recommendations for designing, implementing, and reporting mixed methods studies in the literature and for discussing their viability and continued usefulness in the field of counseling psychology. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Intuitionistic fuzzy rough sets: at the crossroads of imperfect knowledge

Abstract: Just like rough set theory, fuzzy set theory addresses the topic of dealing with imperfect knowledge. Recent investigations have shown how both theories can be combined into a more flexible, more expressive framework for modelling and processing incomplete information in information systems. At the same time, intuitionistic fuzzy sets have been proposed as an attractive extension of fuzzy sets, enriching the latter with extra features to represent uncertainty (on top of vagueness). Unfortunately, the various tentative definitions of the concept of an ‘intuitionistic fuzzy rough set’ that were raised in their wake are a far cry from the original objectives of rough set theory. We intend to fill an obvious gap by introducing a new definition of intuitionistic fuzzy rough sets, as the most natural generalization of Pawlak's original concept of rough sets.     

基于决策树的不完全决策表的数据补充及规则提取

不完全信息系统中遗失数据的补充和规则的提取，一直是数据挖掘技术面临的重要问题。文中给出了一种基于决策树来求解此问题的算法。对于给定的不完全决策表，该算法应用改进的ID3算法来构造决策树，在构造决策树的过程中对遗失值进行补充。对于不能在决策树上补充的遗失值，定义了一种相关对象之间的相似度来填充。该算法简单，易于操作。     

Voltage-Clock Scaling for Low Energy Consumption in Fixed-Priority Real-Time Systems

Power and energy constraints are becoming increasingly prevalent in real-time embedded systems. Voltage-scaling is a promising technique to reduce energy and power consumption: clock speed tends to decrease linearly with supply voltage while power consumption goes down quadratically. We therefore have a tradeoff between the energy consumption of a task and the speed with which it can be completed. The timing constraints associated with real-time tasks can be used to resolve this tradeoff. In this paper, we present two algorithms for voltage-scaling. Assuming that a processor can operate in one of two modes: high voltage and low voltage, we show how to schedule the voltage settings so that deadlines are met while reducing the total energy consumed. We show that significant reductions can be made in energy consumption.     

A Neuro-fuzzy Coding for Processing Incomplete Data: Application to the Classification of Seismic Events

This letter presents a method for modelling and processing incomplete data in connectionist systems. The approach consists in applying a neuro-fuzzy coding to the input data of a neural network. After an introduction to the different kinds of imperfections, we propose a neuro-fuzzy coding in order to take incomplete data into account. We show the efficiency of this coding on the problem of the classification of seismic events. The results show that a neuro-fuzzy coding of the inputs of a neural network increases the performance and classifies incomplete data with little affect on the results.     

丙烷不完全燃烧法制备优质炭黑的研究

炭黑的物理、化学性质与其所使用的原料、燃烧裂解方法等工艺条件密切相关,文中以工业丙烷为燃料,通过不完全的方法制备了尺寸很小、纯度很高的优质炭黑,并通过TEM、XRD等手段对其粒径、形貌、吸油值、pH值等主要的性能进行了表征,并对其反应过程进行了分析。研究表明,改变丙烷与空气/氧气的比例可以得到具有不同结构的产品,该比例对炭黑pH值的影响不大,以氧气为原料的炭黑pH值明显低于以空气为原料的炭黑pH值。     

不完备信息系统中一个变精度粗糙集模型

针对不完备信息系统的知识获取,提出了一种基于相容度的变精度粗糙集模型,该模型是变精度粗糙集模型在不完备信息系统中的拓展.定义了这种模型上的知识约简,并给出了求约简的一个启发式算法.最后通过实例分析说明了算法的有效性.     

基于AP聚类的不完整大数据填充

不完整数据的分析与填充一直是大数据处理的热点研究课题,传统的分析方法无法对不完整数据直接聚类,大部分方法先填充缺失值,然后对数据聚类。这些方法一般利用整个数据集对缺失数据进行填充,使得填充值容易受到噪声的干扰,导致填充结果不精确,进而造成聚类精度很低。提出一种不完整数据聚类算法,对不完全信息系统的相似度公式进行重新定义,给出不完整数据对象间的相似度度量方式,进而直接对不完整数据聚类。根据聚类结果将同一类对象划分到相同的簇中,通过同一类对象的属性值对缺失值进行填充,避免噪声对填充值的干扰,提高填充结果的精确性。实验结果表明,提出的方法能够对不完整数据进行聚类,并有效提高缺失数据的填充精度。