B2C电子商务站点中知识发现的研究

基于国内外最新的研究成果对电子商务中的知识发现进行了综述;首先介绍了在B2C电子商务站点中发现隐含的、未知的但有价值的商业知识的基本流程、主要方法和技术;然后概括了数据挖掘技术目前在B2C电子商务中的应用情况;最后对电子商务中知识发现的发展趋势进行了展望。     

灵活性住宅类型

欧洲受到当今全球性生态和经济的挑战,可持续性和适应性的建筑结构设计概念再次变得愈发重要。此外,个性化的要求、人口结构的变化、民族的多样化以及向灵活工作方式的过渡也激发了对适应性住房需求的日益增长。自20世纪80年代末以来,灵活住宅的范围在欧洲显著扩大,并产生了多种类型：从功能开放的楼层平面、活动墙体的楼层平面以及各种组合类型,到前卫的空间场景、实验性高科技适应结构以及开放功能计划的建筑类型。建立起一种实现灵活性之方法的框架,并介绍了几个具有创新性的案例。     

色彩设计和品牌核心竞争力

论述了随着社会的快速发展和市场竞争程度的不断深化,对色彩合理、有效、创造性的设计,不仅关系到满足不同消费者的不同需求和创造设计的附加值,而且关系到品牌的长远发展战略目标和可续性发展,并最终构成品牌的核心竞争力.     

城市青年公寓设计研究——重庆“跨越·新天地”设计

通过重庆市"跨越·新天地"公寓的设计实践与研究,提出小型公寓设计需要着力解决的问题,以及现代城市青年公寓的设计心得.     

从"需要层次论"分析历史上服装的个性化与中性化现象

从“需要层次论”的观点来分析人类服装所表现出的个性与中性化现象，并阐述了随着社会文明的进步，服装的个性化与中性化已发生了质的变化。     

基于Web挖掘的个性化学习系统

随着Internet的深入发展和不断的普及,Web已经成为人们获取信息,进行学习的最重要的手段之一.但是,目前Web系统只为所有用户提供相同的服务,而Web用户的需求却千差万别,用户希望Web系统能够根据他们的不同特性提供个性化的服务.普通的学习系统已经不能适应他们的学习,不能体现他们的个性化.因此,根据他们的不同特性开发个性化的学习系统已变得相当重要.     

生态住宅设计理论和住宅功能"模糊概念"

为适应当今住宅需求的特征,住宅建设创新要求新的理念,以不断提高静态住宅对居住动态需求的适应性。论述了生态住宅及功能“模糊概念”的内涵,使当今建设的住宅满足今后发展不同时期的需要,今天的住宅能顺利走向明天。     

浅谈移动通信的发展趋势

从六个不同的阶段．介绍了我国移动通信的发展状况，阐述了第三代移动通信系统的先进性，论述了移动通信的微型化、宽带化、综合化和智能化，指出通信个人化是通信的理想目标。     

A Stochastic Optimization approach for the design of Individualized Dosage Regimens

Quantitative methods for individualizing and optimizing the dosage regimen and clinically monitoring each patient are desirable to insure that each patient can obtain effective therapeutic benefit while minimizing undesirable side effects. This is of special concern for medicines that are expensive or whose toxic side effects are severe (e.g., oncological agents). The optimal dosage regimen for an individual is a combination of dose amount and/or dosing interval (i.e., time between doses) which minimizes the risk that the drug exposure deviates from the desired therapeutic window. The therapeutic window is defined as the range of drug exposure (e.g., blood concentration, area under the curve concentration‐time) which is below a threshold defining an acceptable toxic side effect and above a threshold defining a minimum acceptable level of therapeutic efficacy. In this work, the dosage regimen optimization problem defined in terms of general pharmacometric models (i.e., described by differential‐algebraic equations) is presented and a solution approach outlined which uses a scenario‐based stochastic optimization formulation that minimizes a risk metric. The scenarios are derived from the posterior joint probability distribution of the individual's pharmacometric parameters which is obtained following an approximate Bayesian inference approach. A Smolyak rule is used for the selection of the scenarios (i.e., combination of pharmacometric parameters) to be considered and for computing the approximation to the risk metric. Two case studies, gabapentin and cyclophosphamide, are presented to elucidate the advantages and limitations of the proposed approach. The numerical results demonstrate that low risk optimal solutions can be generated via the proposed stochastic optimization; while significantly reducing the computational burden in comparison with the conventional Markov chain Monte Carlo—grid search approach. This partially alleviates implementation issues preventing the deployment of dosage regimen individualization in clinical practice. Since stochastic optimization has been extensively used in other domains, the approach for uncertainty characterization proposed in this work may have general relevance beyond the pharmacometrics domain. © 2013 American Institute of Chemical Engineers AIChE J, 59: 3296–3307, 2013