基于查询的新闻多文档自动摘要技术研究

针对新闻文本领域,该文提出一种基于查询的自动文本摘要技术,更加有针对性地满足用户信息需求。根据句子的TF-IDF、与查询句的相似度等要素,计算句子权重,并根据句子指示的时间给定不同的时序权重系数,使得最近发生的新闻内容具有更高的权重,最后使用最大边界相关的方法选择摘要句。通过与基于TF-IDF、Text-Rank、LDA等六种方法的对比,该摘要方法ROUGE评测指标上优于其他方法。从结合评测结果及摘要示例可以看出,该文提出的方法可以有效地从新闻文档集中摘取核心信息,满足用户查询内容的信息需求。     

Pricing Exotic Option Under Jump-Diffusion Models by the Quadrature Method

This paper extends the quadrature method to price exotic options under jump-diffusion models. We compute the transition density of jump-extended models using convolution integrals. Furthermore, a simpler and more efficient lattice grid is introduced to implement the recursion more directly in matrix form. It can be shown that a lot of running time can be saved. At last, we apply the developed approach to the different jump-extended models to demonstrate its universality and provide a detailed comparison for the discrete path-dependent options to demonstrate its advantages in terms of speed and accuracy.

     

Comparative study on economic contribution rate of education of China and foreign countries based on soft computing method

Economic contribution rate of education (ECRE) is the key factor of education economics. This article selected China, South Korea, United States and other countries for a total of 15 samples, and put the data of the same period under the framework of soft computing, to simulate the production chain of “education–potential human capital–actual human capital–economic growth”. The basic idea is: Firstly, 15 countries are softly categorized according to the level of science and technology (S&T) progress. Secondly, potential human capital and actual human capital establish the internal correlation (fuzzy mapping) in the same classification, and we conceptualize actual human capital as one production factor, joined with the other two production factors, fixed asset and land, to set up the fuzzy mapping to economic growth., and then calculate economic contribution rate of education of China and foreign by two fuzzy mapping of them. Thirdly, this paper analyzes the present state and differences in the development of education between China and foreign according to different ECRE, and offers proposals for promoting the education in China.     

Software rejuvenation in cluster computing systems with dependency between nodes

Software rejuvenation is a preventive and proactive fault management technique that is particularly useful for counteracting the phenomenon of software aging, aimed at cleaning up the system internal state to prevent the occurrence of future failure. The increasing interest in combing software rejuvenation with cluster systems has given rise to a prolific research activity in recent years. However, so far there have been few reports on the dependency between nodes in cluster systems when software rejuvenation is applied. This paper investigates the software rejuvenation policy for cluster computing systems with dependency between nodes, and reconstructs an stochastic reward net model of the software rejuvenation in such cluster systems. Simulation experiments and results reveal that the software rejuvenation strategy can decrease the failure rate and increase the availability of the cluster system. It also shows that the dependency between nodes affects software rejuvenation policy. Based on the theoretic analysis of the software rejuvenation model, a prototype is implemented on the Smart Platform cluster computing system. Performance measurement is carried out on this prototype, and experimental results reveal that software rejuvenation can effectively prevent systems from entering into disabled states, and thereby improving the ability of software fault-tolerance and the availability of cluster computing systems.     

视线交互中两类扫视运动的人机工效评估研究

Fitts法则是人机交互领域预测人机工效的一个有效模型,在许多交互方式中都得到了验证,是传统人机工效研究的理论基础。然而在视线交互中,由于眼动肌肉神经控制机制与肢体运动不同,Fitts法则并不适用。近两年的相关研究提出了一个新的专门针对视线点击任务的难度指数IDeye,它比经典的Fitts指数更能准确预测视线交互的工效。然而,在新模型的有效性验证实验中并没有考虑两种典型的扫视运动(向心和离心运动)的差异。为此,在前期研究的基础上设计组织实验,验证了视线交互中离心和向心这两种眼球运动所带来的人机工效和稳定性的差异,并证实新的IDeye模型仍然能有效预测单纯的离心或向心扫视条件下的人机工效,是对视线交互工效研究的重要补充。     

新媒体时代新闻众筹在中国的发展与对策

新闻众筹作为一种在全球范围内方兴未艾的众筹类型,在中国刚刚崭露头角.本文介绍了新闻众筹的概念及影响,提出了新闻众筹的发展瓶颈,最后针对新闻众筹的持续性发展提出了建议.     

全局性模态词与基本模态语言的扩充

模态语言是讨论关系结构的一种简洁的语言。基本模态语言是仅有一个模态算子◇的模态语言,用ML（◇）表示此语言,但基本模态语言对框架关系的表达力并不是完全的,加入新的模态算子是增强模态语言表达力的方法之一。在基本模态语言ML（◇）基础上增加全局性模态词“E”得到ML（◇,E）语言,这种更丰富的语言对关系模型和关系框架的表达力明显强于基本模态语言。     

敏感性问题的一种调查方法

基于调查数量特征的敏感性问题的随机变量乘法模型提出了一种改进模型,该模型比随机变量乘法模型有着更高的精度．由此,将此改进模型推广到最优分配下的分层抽样情形,在总体适合分层时,能提高总体估计量的估计精度;另外,由于在不同层中可以使用不同的随机化装置,这在实际的调查操作中有着更强的可行性．     

基于视频和人体姿态估计的老年人摔倒监测研究

人口老龄化所带来的养老服务问题是现代社会面临的严重问题。例如在很多国家跌倒是造成老年人因伤致死的最大原因,因此如何对老年人进行自动摔倒监测就成为养老服务亟待解决的问题。目前,在室内摔倒监测领域中,基于可穿戴设备和基于环境传感器等主流摔倒监测方法面临着设备复杂、成本较高等问题。鉴于此,将人体姿态估计引入摔倒监测领域,提出了一种基于2D视频的摔倒监测算法。首先利用OpenPose数据集提取原始数据中人体关节的位置;其次利用这些具有增强特征的数据构建静态分类模型和动态分类模型;最后,在3个公共摔倒数据集上进行模型训练和摔倒监测的测试,取得了较好的效果,可以为摔倒监测相关研究提供一定的参考。