Cluster analysis in industrial market segmentation through artificial neural network

Market segmentation has commonly applied cluster analysis. This study intends to make the comparison of conventional two-stage method with proposed two-stage method through the simulated data. The proposed two-stage method is the combination of self-organizing feature maps and K-means method. The simulation results show that the proposed scheme is better than the conventional two-stage method based on the rate of misclassification.     

盖层封闭能力的灰聚类评价方法

提出灰聚类评价方法，用于盖层封闭能力定量评价。所有被评价对象构成聚类对象集，所有评价指标构成评价指标集，所划分的盖层封闭能力等级构成聚类的灰类集，按照最大聚类权确定对象所属的灰类，即盖层的封闭能力级别。评价流程是：确定指标灰类模式→数据预处理→利用聚类公式计算→利用最大聚类权准则抉择。这种方法避免了加法评分法要依靠人的主观经验划定总评分值的问题，而且由于把评价对象视为“灰”的，具有处理边缘信息的能力。以琼东南盆地３个主要探区的盖层封闭性评价为例，介绍了灰聚类评价的具体应用方法。灰聚类评价方法同样可用于储集层评价、圈闭评价等地质问题的定量研究。表２参３（王孝陵摘     

A novel optical burst switching scheme—logical cascaded private subnet with start wavelength assignment policy

Many recent studies have convincingly demonstrated that network traffic exhibits a noticeable self-similar nature, which has a considerable impact on network performance, and most studies of optical burst switching (OBS) networks are under a fundamental assumption that full wavelength conversion is available throughout the network. In practice, however, economic and technical considerations are likely to dictate a more limited and sparse deployment of wavelength converters in the optical network. Therefore, we present a novel scheme for OBS networks, called logical cascaded private subnet (LCPN) with start wavelength assignment policy. We define the concept of canoe relative to cluster in self-similar traffic, and introduce a new device named payload segregator at the edge node as a gateway to the core node in OBS Networks. According to the changes in the edge node framework, we put forward the concept of cluster private subnet and canoe private subnet in the core node correspondingly. A new start wavelength assignment policy is proposed for the absence of (full) wavelength conversion capabilities in the core node of OBS Networks. The performance study indicates that, our new scheme is robust under self-similar traffic and wavelength continuity constraint.     

基于Java RMI技术的大型机群监控系统的设计与实现

机群监控系统可有效的提高大型机群的可管理性和可用性。本文提出了一种基于JAVA RMI技术的机群监控系统模型，并给出其实现方法。该系统具有开发快速、可跨平台、易于扩展等特性。     

Local wind patterns for modeling renewable energy systems by means of cluster analysis techniques

A method based on cluster analysis techniques is proposed in order to obtain representative local wind patterns. Modeling renewable energy systems, in an accurate way which strongly depends on wind loads, requires reliable data to analyze their response and evaluate their performance. Otherwise poor agreement with the models may be obtained. In a case study for La Paz, Baja California Sur, Mexico, four different wind patterns were obtained from a one-year data set recorded at 10-min intervals.     

Review of Le choc de l'informatique: Les répercussions psychosociales et le r?le des attitudes.

Reviews the book, ILe choc de l'informatique: Les répercussions psychosociales et le r?le des attitudes by Serge Guimond and Guy Bégin (1987). This monograph is concise and easy to read. The reader knows immediately that technological questions will be explored, as well as the psychological and human questions being attached to the new use of information technology. Three fields are covered, each one the subject of a chapter: 1) computers in the educational circle; 2) computers and work; and 3) computers in the house. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Evaluating reactivity to ecological momentary assessment during smoking cessation.

Ecological momentary assessment (EMA) consists of assessing phenomena in real time in the natural environment. EMA allows for more fine-grained analyses of addictive behavior and minimizes threats to internal validity, such as recall biases and errors. However, because of the intensive monitoring involved in EMA, measurement reactivity is a concern. To test whether EMA with palmtop personal computers induces reactivity, the authors compared smoking-related outcomes between smokers using EMA and those not using EMA during a quit attempt. The use of no-EMA control groups has been rare in reactivity investigations to date. The EMA protocol included event-contingent assessments (smoking episodes, urge episodes) and random assessments. Outcomes included biologically confirmed abstinence and self-report measures of withdrawal, self-efficacy, motivation, affect, and temptations. Participants were smokers motivated to quit (N = 96). They were randomized to 1 of 3 groups: EMA for the week preceding a planned quit date, EMA for the week following the quit date, and no EMA. Abstinence rates did not differ between the groups at Day 7 or at Day 28 postcessation. For the 20 subscales assessed at each of 3 assessment times, there were significant differences between participants with and without EMA experience for 3 subscales at the 1st of 3 assessment times, and significant differences for 3 different subscales at the 3rd assessment time. These differences suggest some reactivity to EMA, although the inconsistent pattern across time indicates that further research is needed to definitively conclude that EMA induces reactivity. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

沉积环境与多元统计综合分析法

本文首先根据地震资料提取了十二种地震参数，然后通过对ＬＨ油田ＴＺ地区沙三上段下部地层进行沉积环境分析，确定了可能存在的沉积相类型，并用有序样品聚类的方法对过井和井旁地震测线按沉积相个数进行分割，由此而建立了该区各类沉积相的判别函数。通过这些判别函数，用逐步判别分析的方法，对该区其它地震测线的参数进行判别分类，最后搞清了研究区目的层的沉积相展布。通过分析和计算证明，这一方法对有地震资料的盆地或地区进行沉积相的划分，是行之有效的     

基于聚类优化主动模型人脸识别算法研究

研究人脸识别和跟踪准确度问题。针对在使用大数据样本进行训练前提下,以往AAM算法人脸识别与定位不准确的缺陷,提出了一种新的利用聚类算法对样本空间进行划分,并在此基础上训练多个AAM的分层人脸识别和跟踪算法。首先利用所有训练样本训练得到初始AAM,然后利用一个全新的相似度计算公式,将所有训练样本划分成若干个子类别,在此基础上,针对每个子类别,训练一个相对稳定的AAM。在识别与跟踪过程中,先使用初始AAM进行定位,然后根据子类AAM进行精细化定位,从而得到比以往算法更为精确的定位效果。仿真结果显示改进的算法能准确定位出人脸所在位置,并且具有很高的运算效率,可以方便的实现实时监控系统的人脸跟踪定位及识别等目标。