基于主题图的文献资源组织模型及应用研究

文章分析了主题图的相关理论和传统文献组织方法优劣,论证了主题图在文献资源组织中的可行性,提出了基于主题图的文献资源组织模型及构建方法,引申了基于该模型的文献检索、主题导学、个性化资源推荐等应用研究。     

研讨支持系统中基于主题聚类的热点提取

研讨支持系统是一种旨在通过计算机技术代替传统面对面的研讨方式,并利用信息处理、数据挖掘等方法自动形成决策的网络研讨平台。研讨过程中会产生海量发言,如何自动挖掘和提取发言中的热点是本文研究重点。文章采用文本聚类的方法从发言中得到主题簇,并结合提出的热度值计算公式找出热门主题和热门观点。最后引用一个实例分析和验证了热点提取过程。     

Fuzzy sets and similarity relations for semantic web service matching

Semantic Web Services (SWS) were introduced to facilitate the publication, discovery, and execution of web services. A semantic matchmaker enhances the capability of UDDI service registries in the SWS architecture and it is able to recognize various degrees of matching for web services. On the basis of SWS and fuzzy-set theory, a fuzzy matching approach for semantic web services is proposed, to support a more automated and veracious service discovery process.     

Synthesis of quantum size ZnO crystals and their gas sensing properties for NO2

Quantum size ZnO crystals have been synthesized successfully by a room temperature sol-gel process. Oleic acid (OA) has been used as capping agent to control the particle size of ZnO. The crystal structure and size of the ZnO are characterized by the X-ray diffraction (XRD) and transmission electron microscope (TEM). The XRD results show the as-synthesized ZnO has hexagonal wurtzite structure and the average crystallite size is 5.7 nm which is little less than TEM result. It is testified by photoluminescence (PL) and Raman spectra that the quantum size ZnO keeps the crystal structure of the bulk ZnO and possesses more surface defects. The quantum size ZnO has the highest response of 280 to NO₂ and the highest selectivity of 31 and 49 corresponding to CO and CH₄ at operating temperature of 290 °C. The effect of calcination temperatures on sensing property and transient response of the ZnO sensor are also investigated.     

DCS电源供电系统的可靠性定量分析

根据DCS电源系统的现状,对目前几种不同的电源设计方案进行可靠性定量分析.通过建立不同DCS电源系统可靠性框图并估算相关的可靠性指标,比较了不同方案下的平均无故障工作时间 (MTBF),给出了系统可靠性的分析结果和改进措施,定量分析了改进后的方案.结果表明电源系统的MTBF有了明显的改善.     

基于WinCE的电梯监控系统多串口通信实现

提出了一种基于WinCE的多串口电梯远程监控系统的实现方法.该方法以S3C2440微处理器为核心构建硬件平台,实现了与其他设备的串口通信;同时以WinCE5.0为软件平台,完成多串口分层流驱动的设计.通过文件映射,解决了访问多串口设备时产生的竞态问题.测试结果表明,该系统通信正常、数据稳定,能充分满足电梯监控对串行通信的要求.     

Robust optimization of supply chain network design in fuzzy decision system

This paper presents a new robust optimization method for supply chain network design problem by employing variable possibility distributions. Due to the variability of market conditions and demands, there exist some impreciseness and ambiguousness in developing procurement and distribution plans. The proposed optimization method incorporates the uncertainties encountered in the manufacturing industry. The main motivation for building this optimization model is to make tools available for producers to develop robust supply chain network design. The modeling approach selected is a fuzzy value-at-risk (VaR) optimization model, in which the uncertain demands and transportation costs are characterized by variable possibility distributions. The variable possibility distributions are obtained by using the method of possibility critical value reduction to the secondary possibility distributions of uncertain demands and costs. We also discuss the equivalent parametric representation of credibility constraints and VaR objective function. Furthermore, we take the advantage of structural characteristics of the equivalent optimization model to design a parameter-based domain decomposition method. Using the proposed method, the original optimization problem is decomposed to two equivalent mixed-integer parametric programming sub-models so that we can solve the original optimization problem indirectly by solving its sub-models. Finally, we present an application example about a food processing company with four suppliers, five plants, five distribution centers and five customer zones. We formulate our application example as parametric optimization models and conduct our numerical experiments in the cases when the input data (demands and costs) are deterministic, have fixed possibility distributions and have variable possibility distributions. Experimental results show that our parametric optimization method can provide an effective and flexible way for decision makers to design a supply chain network.     

An effective algorithm to detect both smoke and flame using color and wavelet analysis

Fire detection is an important task in many applications. Smoke and flame are two essential symbols of fire in images. In this paper, we propose an algorithm to detect smoke and flame simultaneously for color dynamic video sequences obtained from a stationary camera in open space. Motion is a common feature of smoke and flame and usually has been used at the beginning for extraction from a current frame of candidate areas. The adaptive background subtraction has been utilized at a stage of moving detection. In addition, the optical flow-based movement estimation has been applied to identify a chaotic motion. With the spatial and temporal wavelet analysis, Weber contrast analysis and color segmentation, we achieved moving blobs classification. Real video surveillance sequences from publicly available datasets have been used for smoke detection with the utilization of our algorithm. We also have conducted a set of experiments. Experiments results have shown that our algorithm can achieve higher detection rate of 87% for smoke and 92% for flame.     

PolSAR image compression based on online sparse K-SVD dictionary learning

we present a novel polarimetric synthetic aperture radar (PolSAR) image compression scheme. PolSAR data contains lots of similar redundancies in single-channel and massively correlation between polarimetric channels. So these features make it difficult to represent PolSAR data efficiently. In this paper, discrete cosine transform (DCT) is adopted to remove redundancies between polarimetric channels, simple but quite efficient in improving compressibility. Sparse K-singular value decomposition (K-SVD) dictionary learning algorithm is utilized to remove redundancies within each channel image. Double sparsity scheme will be able to achieve fast convergence and low representation error by using a small number of sparsity dictionary elements, which is beneficial for the task of PolSAR image compression. Experimental results demonstrate that both numerical evaluation indicators and visual effect of reconstructed images outperform other methods, such as SPIHT, JPEG2000, and offline method.     

The subspace global skyline query processing over dynamic databases

The global skyline, as an important variant of the skyline, has been widely applied in multi-criteria decision making, business planning and data mining. In this paper, we extend our early work and propose the maintenance methods to process the subspace global skyline (SGS) queries in dynamic databases. In the previous work, we proposed the index structure RB-tree, which can effectively manage the data to accelerate the subspace global skyline calculation. Also, the basic single SGS algorithm based on RB-tree (SSRB) and the optimized single SGS algorithm (OSSRB) were proposed to process a single SGS query. In addition, the multiple SGS algorithm (MSRB) was proposed to calculate multiple SGS queries by sharing the scan spaces of different queries. In this paper, we design some data structures and propose the maintenance approaches of SSRB, OSSRB and MSRB to cope with updates that happen to data sets. Thus our extended algorithms can be adopted for dynamic data sets. Finally, the experimental results show that the proposed algorithms OSSRB and MSRB have good performance to process SGS queries and they can be easily maintained with dynamic datasets.