记忆与延续——浅析苏州博物馆与宁波博物馆建筑设计

博物馆建筑,是一个城市文化的象征,如何使博物馆具有文化感,体现传统的审美文化,又具有新的设计元素,引导人类审美意识,苏州博物馆与宁波博物馆做了比较好的探索。     

基于词性的文本挖掘算法在IDS日志中的应用

提出一种以词性为参考值的文本挖掘算法,能有效挖掘与种子词有关的关联规则。基于Bootstrapping算法思想,既减少了预处理阶段对于词根还原的依赖,能处理日志中出现的中文词汇。增加了对于日志文本上下的理解,提高了关联规则的有效性,并应用与IDS日志挖掘之中,有效改善挖掘效率,为规则库提供关联规则。     

A belief-rule-based inventory control method under nonstationary and uncertain demand

This paper is devoted to investigating inventory control problems under nonstationary and uncertain demand. A belief-rule-based inventory control (BRB-IC) method is developed, which can be applied in situations where demand and demand-forecast-error (DFE) do not follow certain stochastic distribution and forecasting demand is given in single-point or interval styles. The method can assist decision-making through a belief-rule structure that can be constructed, initialized and adjusted using both manager’s knowledge and operational data. An extended optimal base stock (EOBS) policy is proved for initializing the belief-rule-base (BRB), and a BRB-IC inference approach with interval inputs is proposed. A numerical example and a case study are examined to demonstrate potential applications of the BRB-IC method. These studies show that the belief-rule-based expert system is flexible and valid for inventory control. The case study also shows that the BRB-IC method can compensate DFE by training BRB using historical demand data for generating reliable ordering policy.     

基于使用控制模型的防恶意下载系统

为了对恶意下载行为实施有效控制,研究通用访问控制框架和使用控制模型(UCON),提出基于流量的UCON。设计并实现基于UCON的防恶意下载系统,阐述其关键技术和实现方法。实验结果表明,该模型能有效控制用户下载行为,具有高安全性和较强的操作灵活性。     

一种基于不放回抽样的图像混沌加密算法

针对现有基于混沌序列的图像加密算法的缺陷,提出一种基于不放回抽样的图像混沌加密算法。该算法采用可变模运算和间接地址映射技术,将混沌序列一对一、高度随机地转换为图像像素地址,实现图像的位置置乱和灰度扰乱加密。对混沌序列的分布无严格要求,使混沌序列的参数和初值可以作为密钥被使用。实验结果表明,与现有同类算法相比,该算法性能优越、运算速度快且易于实现。     

Spatial interest pixels (SIPs): useful low-level features of visual media data

Visual media data such as an image is the raw data representation for many important applications. Reducing the dimensionality of raw visual media data is desirable since high dimensionality degrades not only the effectiveness but also the efficiency of visual recognition algorithms. We present a comparative study on spatial interest pixels (SIPs), including eight-way (a novel SIP detector), Harris, and Lucas‐Kanade, whose extraction is considered as an important step in reducing the dimensionality of visual media data. With extensive case studies, we have shown the usefulness of SIPs as low-level features of visual media data. A class-preserving dimension reduction algorithm (using GSVD) is applied to further reduce the dimension of feature vectors based on SIPs. The experiments showed its superiority over PCA.

世界城市发展的大生态观与制度制衡

一、生态足迹视野下的四大城市发展弊端加拿大不列颠哥伦比亚大学社区与区域规划学院教授WilliamRees(威廉姆?里斯)2012年3月7日在纽卡斯尔大学建筑规划景观学院发表演讲,提出了"可持续性的障碍是什么?为什么我们如梦游一般走入全球生态危机之中?"的设问。他从生态足迹分析角度,指出了现代城市     

Synthesis of neural tree models by improved breeder genetic programming

Neural tree model has been successfully applied to solving a variety of interesting problems. In most previous studies, optimization of the neural tree model was divided into two steps: first structure optimization, then parameter optimization. One major problem in the evolution of structure without parameter information was noisy fitness evaluation. In this paper, an improved breeder genetic programming algorithm is proposed to the synthesis of neural tree model. The effectiveness and performance of the method are evaluated on time series prediction problems and compared with those of related methods. Simulation results show that the proposed algorithm is a potential method with better performance and effectiveness.