乐滩灌区输水隧洞穿合山煤矿采空区处理设计

分析了乐滩灌区工程北干渠溯河隧洞段长约1.06 km穿合山煤矿采空区的地质情况.借鉴高速公路煤矿采空区的成功处理经验,通过科学分析,对采空区变形和区域内覆岩的稳定性做了评价,论述了输水线路穿采空区段采取全充填压力注浆法的工程处理方法.     

横泉水库供水发电洞工程地质分析与评价

通过大量野外工程地质勘察与测试工作，在此基础上给出了横泉水库供水发电洞的工程地质分析与评价，从而使该水库的施工有了充分的理论依据。     

沉管隧道水下最终接头施工技术初探

简述了沉管隧道水下最终接头施工技术的应用现状，结合具体隧道工程实例，从外模工程、混凝土结构两方面介绍了最终接头施工技术，表明了该技术具有运用价值。     

基于服务器端会话追踪的Web查询服务的研究

在探讨了Web查询服务的典型模型后,论文阐述了服务器端会话追踪机制的实现方式,设计了基于服务器端会话追踪的Web查询服务的典型解决方案。该设计方案可以较为安全地保存和维护客户的上下文信息,可靠地跟踪用户查询所处的状态,有效地实现有状态的Web查询服务。     

网络安全事件的关联分析方法的比较研究

随着当前攻击手段和技术的日益复杂化,一次入侵事件往往需要多个步骤才能完成,这些步骤都是彼此相关的。但是传统的入侵检测集中于检测底层的入侵或异常,所检测到的结果也仅仅是一次完整入侵的一部分,所以不能将不同的报警结合起来以发现入侵的逻辑步骤或者入侵背后的攻击策略。关联分析技术将不同分析器上产生的报警进行融合与关联分析,极大地减少了报警的数量,降低了入侵检测的误报率,并且适当的减少了入侵检测的漏报率。文中在对网络安全事件关联分析方法的系统结构进行分析后,着重介绍了当前比较流行的几种网络安全事件关联分析方法,最后对各种方法进行了比较研究。     

一种基于混沌渐近同步的数字保密通信方法

根据驱动－响应混沌同步原理，提出了一种基于混沌渐近同步的数字保密通信方法。通过设计对发射信号进行多级单值非线性变换，使得通过预测法的攻击完全失效，因而这种通信方法具有较高的抗破译能力。理论分析和数值模拟结果证实了本方法的正确性与有效性。     

定向断裂爆破技术在特软岩层巷道中的应用

介绍了大雁矿区特软岩层巷道成型新技术,包括定向断裂爆破技术的机理、爆破参数,以及大雁矿区特软岩层条件下实施定向断裂爆破的技术关键和注意事项。应用该技术不仅提高了巷道成型质量、节约了材料,而且保护了围岩稳定,对软岩巷道维护有重要作用。     

基于JSP技术的Web网站安全性研究

通过对基于JSP技术的Web网站的体系结构的介绍．从Web服务器安全、JSP脚本编程及数据库安全等几方面分析研究了web网站存在的安全问题，并探讨了web网站开发时应采取的安全措施。     

Implementing Qubits with Superconducting Integrated Circuits

Superconducting qubits are solid state electrical circuits fabricated using techniques borrowed from conventional integrated circuits. They are based on the Josephson tunnel junction, the only non-dissipative, strongly non-linear circuit element available at low temperature. In contrast to microscopic entities such as spins or atoms, they tend to be well coupled to other circuits, which make them appealling from the point of view of readout and gate implementation. Very recently, new designs of superconducting qubits based on multi-junction circuits have solved the problem of isolation from unwanted extrinsic electromagnetic perturbations. We discuss in this review how qubit decoherence is affected by the intrinsic noise of the junction and what can be done to improve it. PACS: 03.67.-a, 03.65.Yz, 85.25.-j, 85.35.Gv     

An intelligent web-page classifier with fair feature-subset selection

The explosion of on-line information has given rise to many manually constructed topic hierarchies (such as Yahoo!!). But with the current growth rate in the amount of information, manual classification in topic hierarchies results in an immense information bottleneck. Therefore, developing an automatic classifier is an urgent need. However, classifiers suffer from enormous dimensionality, since the dimensionality is determined by the number of distinct keywords in a document corpus. More seriously, most classifiers are either working slowly or they are constructed subjectively without any learning ability. In this paper, we address these problems with a fair feature-subset selection (FFSS) algorithm and an adaptive fuzzy learning network (AFLN) for classification. The FFSS algorithm is used to reduce the enormous dimensionality. It not only gives fair treatment to each category but also has ability to identify useful features, including both positive and negative features. On the other hand, the AFLN provides extremely fast learning ability to model the uncertain behavior for classification so as to correct the fuzzy matrix automatically. Experimental results show that both FFSS algorithm and the AFLN lead to a significant improvement in document classification, compared to alternative approaches.