Ranking Related Research Papers Based on Citation Graph

Research papers are of great importance for researchers to record and share their ideas, studies and results. Meanwhile, they are the bases for further research work. Finding related research papers is the preliminary of good research. A new method for ranking related research papers is introduced in this paper. Given a set of interested papers, the method proposed in this paper may rank related papers just based on a citation graph by constructing the minimal Steiner trees. The method can work with the existing keyword based methods. Intensive experiments on a specific research topic show that the proposed method provides a different ranking criterion to existing ones, and can effectively retrieve those highly related papers.     

基于膜盘菌属的两种系统发育研究方法的比较研究

以rDNA ITS1-5.8S-ITS2序列作为分子标记,采用直接优化和常规分析两种方法,探讨膜盘菌属内种间及其与相关属间的亲缘关系,并比较了两种建树方法在解决该属内种间关系的效果。以Lachnum spartinae为外群,选取31条序列构建了最小进化树、最大简约树和直接优化树。结果表明,Hymenoscyphus ericae复合种与其他膜盘菌属的成员关系较远,除了H.ericae外,其他膜盘菌形成一个单系群。模式种Hymenoscyphus fructigenus与H.caudatus,H.fucatus,H.scutulus等构成一个高支持率的分支,与另一分支(H.epiphyllus,H.lasiopodium)形成姐妹群。相对于常规的两步分析法,直接优化所产生的系统树与当前形态学特征基本相符合,因而更合理地反映膜盘菌属的分类地位和种间关系,表明该分析方法在真菌系统发育分析中具有较大的应用价值。     

基于B+树的BPEL流程异常处理机制研究

Web服务组合具有松耦合、自治性的特点,BPEL规范中的异常处理机制也不完善,于是BPEL流程中的异常处理方法是研究的一个主要问题。针对该问题,在流程运行阶段处理异常的一些通用的策略的基础上,提出了基于B+树的等价服务替换算法,分别阐述了BPEL中同步和异步调用Web服务产生异常的情况,最后构架了一个异常处理的系统框架原型。     

基于回归树与衰减函数的在线负面口碑影响力预测

影响力预测是企业在线负面口碑处理的关键环节.论文通过综合考虑信息发布者特征和信息内容特征两个维度形成特征空间,采用影响力衰减函数描述负面口碑影响力的多变趋势,提出了一种基于回归树与衰减函数的IMM-RTDF模型来预测在线负面口碑的影响力.实验结果表明,考虑信息内容特征有助于提高预测精度,同时发现用不同的衰减函数能更好地描述异质负面口碑影响力的变化趋势,进而能提高模型性能.基于此方法的在线负面口碑处理策略为企业进行客户关系管理和资源配置提供了决策支持.     

热带地区几个珍贵树种干形曲线研究

准确描述热带珍贵树种的林木干形变化,可为预估各材种数量、蓄积量及合理造材提供支撑。以热带格木、红锥和柚木3个珍贵树种,共120株解析木为研究对象,利用简单削度方程、分段削度方程和可变指数削度方程分别构建格木、红锥和柚木3个热带树种的干形曲线方程,通过相关指数、剩余残差平方和、平均残差、残差方差和均方误差统计量比较分析,找出最佳削度模型作为3个树种最终的干形曲线方程,并对各曲线变化趋势进行了初步的定量分析。结果表明,所选的3类典型基础模型对每个树种的预估效果都很好,其中基于双因素自动优选法拟合且以分段削度方程构建的干形曲线预估效果最好。3个树种的干形曲线变化趋势表明:相对高在(0~0.8)时,柚木干形变化最大,红锥干形变化最小,格木干形介于二者之间;当相对高0.8时,红锥干形变化最大,格木和柚木干形变化几乎相同。因此,基于双因素自动优选法拟合的分段削度方程可作为3种热带树种的干形曲线方程,用于3种珍贵树种活立木蓄积量和材种数量的估计,以及指导合理造材。     

关于λ-修改的Wiener指数

令（n，△）是具有n个顶点，最大度为△的树的全体．1．△（n）是具有n个顶点且每个顶点的度是1或△的树的全体．对于任意λ≠0，本文分别在（n，△）和。1.△（n）中确定了具有最大的五一修改的Wjener指数的极值图．     

Cooperative Sensor Anomaly Detection Using Global Information

Sensor networks are deployed in many application areas nowadays ranging from environment monitoring, industrial monitoring, and agriculture monitoring to military battlefield sensing. The accuracy of sensor readings is without a doubt one of the most important measures to evaluate the quality of a sensor and its network. Therefore, this work is motivated to propose approaches that can detect and repair erroneous (i.e., dirty) data caused by inevitable system problems involving various hardware and software components of sensor networks. As information about a single event of interest in a sensor network is usually reflected in multiple measurement points, the inconsistency among multiple sensor measurements serves as an indicator for data quality problem. The focus of this paper is thus to study methods that can effectively detect and identify erroneous data among inconsistent observations based on the inherent structure of various sensor measurement series from a group of sensors. Particularly, we present three models to characterize the inherent data structures among sensor measurement traces and then apply these models individually to guide the error detection of a sensor network. First, we propose a multivariate Gaussian model which explores the correlated data changes of a group of sensors. Second, we present a Principal Component Analysis (PCA) model which captures the sparse geometric relationship among sensors in a network. The PCA model is motivated by the fact that not all sensor networks have clustered sensor deployment and clear data correlation structure. Further, if the sensor data show non-linear characteristic, a traditional PCA model can not capture the data attributes properly. Therefore, we propose a third model which utilizes kernel functions to map the original data into a high dimensional feature space and then apply PCA model on the mapped linearized data. All these three models serve the purpose of capturing the underlying phenomenon of a sensor network from its global view, and then guide the error detection to discover any anomaly observations. We conducted simulations for each of the proposed models, and evaluated the performance by deriving the Receiver Operating Characteristic (ROC) curves.     

闽粤赣客属地区族谱数据库建设构想

介绍了客家族谱的价值,分析了客家族谱数据库建设的必要性及现状,以闽粤赣客属地区族谱数据库建设为例,提出了客家族谱数据库建设构想。     

HIV模型的统计诊断

描述HIV的数学模型是一组非线性常微分方程,其中包括CD4+T细胞再感染率和死亡率,HIV病毒死亡率等多个重要未知参数,准确估计这些参数有助于正确了解患者病情发展,以采用个人化治疗方案.针对此模型已提出多个参数估计方法,包括基于数值解的非线性最小二乘,截面似然及两步估计.另一方面,由于客观因素影响,各观测数据对于参数估计的影响大小不同,找出对参数估计影响大的观测值,进一步分析其原因具有重要意义.基于HIV模型的两步估计,构造了用于影响分析的非参数Cook型统计量,并给出其大样本分布.通过模拟数据和临床数据分析发现:(1)所构造统计量可以检测中度以上偏移.(2)相对于内点,边界点对HIV模型的参数估计影响更大.基于以上结论,建议对HIV模型进行参数估计时,对边界点应加以格外关注.提出的方法也可以推广到其他线性常微分方程模型的统计诊断问题中.     

两种带多约束的组播路由算法

组播对其成员节点能够提供服务质量,且组播在未来通信网络当中起到越来越重要的角色.对多约束斯坦利最小树问题,提出了基于Boruvka方法的多约束组播算法(BMCMRA)与基于Kruskal方法的多约束组播算法(KMCMRA).仿真试验表明算法具有良好代价性能,且能够很好地满足多约束条件.