Probability of graphs with large spectral gap by multicanonical Monte Carlo

Graphs with large spectral gap are important in various fields such as biology, sociology and computer science. In designing such graphs, an important question is how the probability of graphs with large spectral gap behaves. A method based on multicanonical Monte Carlo is introduced to quantify the behavior of this probability, which enables us to calculate extreme tails of the distribution. The proposed method is successfully applied to random 3-regular graphs and large deviation probability is estimated.     

Efficient region-aware large graph construction towards scalable multi-label propagation

With fast growing number of images on photo-sharing websites such as Flickr and Picasa, it is in urgent need to develop scalable multi-label propagation algorithms for image indexing, management and retrieval. It has been well acknowledged that analysis in semantic region level may greatly improve image annotation performance compared to that in the holistic image level. However, region level approach increases the data scale to several orders of magnitude and proposes new challenges to most existing algorithms. In this work, we present a novel framework to effectively compute pairwise image similarity by accumulating the information of semantic image regions. Firstly, each image is encoded as Bag-of-Regions based on multiple image segmentations. Secondly, all image regions are separated into buckets with efficient locality-sensitive hashing (LSH) method, which guarantees high collision probabilities for similar regions. The k-nearest neighbors of each image and the corresponding similarities can be efficiently approximated with these indexed patches. Lastly, the sparse and region-aware image similarity matrix is fed into the multi-label extension of the entropic graph regularized semi-supervised learning algorithm [1]. In combination they naturally yield the capability of handling large-scale dataset. Extensive experiments on NUS-WIDE (260k images) and COREL-5k datasets validate the effectiveness and efficiency of our proposed framework for region-aware and scalable multi-label propagation.     

Normal shock boundary layer control with various vortex generator geometries

Various vortex generators which include ramp, split-ramp and a new hybrid concept “ramped-vane” are investigated under normal shock conditions with a diffuser at Mach number of 1.3. The dimensions of the computational domain were designed using Reynolds Average Navier–Stokes studies to be representative of the flow in an external-compression supersonic inlet. Using this flow geometry, various vortex generator concepts were studied with Implicit Large Eddy Simulation. In general, the ramped-vane provided increased vorticity compared to the other devices and reduced the separation length downstream of the device centerline. In addition, the size, edge gap and streamwise position respect to the shock were studied for the ramped-vane and it was found that a height of about half the boundary thickness and a large trailing edge gap yielded a fully attached flow downstream of the device. This ramped-vane also provided the largest reduction in the turbulent kinetic energy and pressure fluctuations. Additional benefits include negligible drag while the reductions in boundary layer displacement thickness and shape factor were seen compared to other devices.     

基于本体的语义分析过程与方法的研究应用*

为了提高信息化环境下语义分析能力,将本体引入语义分析。通过对典型本体构建方法的比较与综合,形成一种持续优化的本体构建方法,在此基础上进行概念分析、关系推理。进一步对比基于本体的语义分析和其它语义分析方法,指出基于本体的语义分析更具系统性、针对性,推理能力强。最后,将基于本体的语义分析应用到软件缺陷分析系统中。结果表明,它能够集成到原有系统中并有效进行关系推理和冲突识别。     

电磁流量计在分流支管中的应用

为解决目前国内电磁流量计无法同时满足高温、高压、耐腐蚀、大通径流量测量的难题,提出了利用小口径电磁流量计,通过测量分流支管中的流体流量,达到替代大口径电磁流量计测量大流量的目的。中还提出了延长电磁流量计使用寿命的措施。     

Computation and the Three Worlds

Discussions about the achievements and limitations of the various approaches to the development of intelligent systems can have an essential impact on empirically based research, and with that also on the future development of computer technologies. However, such discussions are often based on vague concepts and assumptions. In this context, we claim that the proposed `three-world ontology' offers the most appropriate conceptual framework in which the basic problems concerned with cognition and computation can be suitably expressed and discussed, although the solutions of some of these problems seem to lie beyond the horizon of our current understanding. We stress the necessity to differentiate between authentic and functional cognitive abilities; although computation is not a plausible way towards authentic intelligence, we claim that computational systems do offer virtually unlimited possibilities to replicate and surpass human cognitive abilities on the functional level.     

基于AJAX的智能检索在Web搜索的研究

为了实现Web智能检索,提出一种Web智能搜索引擎的模型,它是基于自然语言库和本体库对关键词进行解析,在AJAX模式中实现启发式检索,收集和使用用户反馈的重要叁数,并在此基础上设计和实现了一个Web搜索引擎。     

基于Lucene的语义搜索引擎设计

该文在开源全文搜索引擎Lucene的基础上设计了一个结合本体与自然语言处理技术的语义检索系统。系统分析了如何对文本进行语义分析,设计了语义索引项以存储语义信息,并提出了使用语义信息的网页排序算法。     

RRL:对语义Web上Ontology表示语言OWL的一种扩展方案

针对OWL在表示约束和规则方面的缺陷,提出了对OWL的一种扩充方案:在OWL上面再建立一层RRL,并在RRL中定义属性值的区间约束表示本体,使得OWL在用RRL层扩充以后可以方便地表示属性值的区间约束。     

大型水轮机综合特性曲线处理的研究

水轮机设计的基础理论是相似理论。选型设计决定水轮机性能参数尺寸,其中最关键的技术是水轮机特性曲线的处理,即模型综合特性曲线和真机运动特性曲线的处理。本文应用CAD技术,提出了特性曲线处理算法,极大地提高了水轮机方案设计的效率。该算法已经应用于国家863／CIMS重点应用示范工程中。