针对视频会议的一种传输控制方案

为满足视频会议中网络流量的平滑稳定性以及公平竞争性,设计了一种新的传输拥塞控制方案——CTP( Conference Transmission Protocol).CTP在逻辑上分为DCC(Dynamic Congestion Control Layer)和RAC( Rate Amended Control Layer...     

Hydrogen sensor based on Pd-functionalized film bulk acoustic resonator

We present an application of the Pd-functionalized film bulk acoustic resonator for hydrogen detection. The resonator consisted of an AlN piezoelectric stack and a Bragg reflector has a working resonance near 2.23 GHz and a high performance. A 50 nm thick Pd film was coated on the top electrode as a specific layer to capture hydrogen. The absorption of hydrogen can trigger changes of elastic properties of the Pd layer, which affects the resonance frequency of the resonator. The experimental results show that the Pd-functionalized film bulk acoustic resonator can yield a rapid, sensitive, reversible and reproducible response to hydrogen in the concentrations from 0.3% to 2%. The advantages of this sensor, including the simple fabrication process, ease of detection method, rapid response and high sensitivity and working at room temperature, make this promising in the early alarm of hydrogen leaking.     

Exploiting effective features for chinese sentiment classification

Features play a fundamental role in sentiment classification. How to effectively select different types of features to improve sentiment classification performance is the primary topic of this paper. Ngram features are commonly employed in text classification tasks; in this paper, sentiment-words, substrings, substring-groups, and key-substring-groups, which have never been considered in sentiment classification area before, are also extracted as features. The extracted features are then compared and analyzed. To demonstrate generality, we use two authoritative Chinese data sets in different domains to conduct our experiments. Our statistical analysis of the experimental results indicate the following: (1) different types of features possess different discriminative capabilities in Chinese sentiment classification; (2) character bigram features perform the best among the Ngram features; (3) substring-group features have greater potential to improve the performance of sentiment classification by combining substrings of different lengths; (4) sentiment words or phrases extracted from existing sentiment lexicons are not effective for sentiment classification; (5) effective features are usually at varying lengths rather than fixed lengths.     

A multi-strategy knowledge interoperability framework for heterogeneous learning objects

This paper presents a knowledge exchange framework that can leverage the interoperability among semantically heterogeneous learning objects. With the release of various e-Learning standards, learning contents and digital courses are easy to achieve cross-platform sharing, exchanging, and even reorganizing. However, knowledge sharing in semantic level is still a challenge due to that the learning materials can be presented in any form, such as audios, videos, web pages, and even flash files. The proposed knowledge exchange framework allows users to share their learning materials (also called “learning objects”) in semantic level automatically. This framework contains two methodologies: the first is a semantic mapping between knowledge bases (i.e. ontologies) which have essentially similar concepts, and the second is an ontology-based classification algorithm for sharable learning objects. The proposed algorithm adopts the IMS DRI standard and classifies the sharable learning objects from heterogeneous repositories into a local knowledge base by their inner meaning instead of keyword matching. Significance of this research lies in the semantic inferring rules for ontology mapping and learning objects classification as well as the full automatic processing and self-optimizing capability. Focused on digital learning materials and contrasted to other traditional technologies, the proposed approach has experimentally demonstrated significantly improvement in performance.     

基于有损连接的个性化隐私保护

数据表的k-匿名化(k-anonymization)是数据发布环境下保护数据隐私的一种重要方法,在此基础上提出的(,)-匿名模型则是有效的个性化隐私保护方法,泛化/隐匿是实现匿名化的传统技术,然而该技术存在效率低,信息损失量大等缺陷。针对上述问题,引入有损连接的思想,提出了基于贪心策略的(,)-匿名聚类算法,该方法通过准标识符属性和敏感属性间的有损连接来保护隐私数据。实验结果表明,与泛化/隐匿方法相比,该方法在信息损失量和时间效率上具有明显的优势,可以获得更好的隐私信息保护。     

多域光网络控制平面互通技术的解决方案

为了提供跨越多域的动态的端到端的业务,对多域光网络控制平面的互通技术进行了研究。根据国际标准化组织的研究,分析了多域光网络控制平面互通技术的研究现状,并介绍了多域光网络的控制平面的分类方法及控制平面互通的需求分析。最后结合控制平面互通的需求分析,给出了几种互通技术的解决方案。分析结果表明,这些方案可以实现不同网络域的控制平面的互通操作。     

改进遗传算法在移动机器人全局路径规划中的应用

针对应用遗传算法进行移动机器人全局路径规划时遇到的早熟收敛和收敛速度慢等问题,提出一种基于定长二进制路径编码方式的改进遗传算法。研究此编码方式下的改进遗传操作,采用比例阈值自适应((N+K,N)+N)双种群进化策略,有效提高了算法收敛速度和全局寻优能力。仿真实验表明了该算法的有效性。     

一种基于半监督学习的多模态Web查询精化方法

Web搜索系统往往通过与用户的交互来精化查询以提高搜索性能.除文字之外,网页中还存在着大量其它模态的信息,如图像、音频和视频等.以往对于查询精化的研究很少涉及对多模态信息的利用.文中提出了一种基于半监督学习的多模态Web查询精化方法M2S2QR,将Web查询精化转化为一个机器学习问题加以解决.首先,基于用户判断后的网页信息,分别为不同模态训练相应的学习器,然后利用未经用户判断的网页信息来提高学习器性能,最后将不同模态学习器结合起来使用.实验验证了文中方法的有效性.     

一种无线传感器监测系统的设计和研究

给出了一种无线传感器监测系统的设计与开发,结合MEMS微传感器和无线通信技术,研究了MEMS微加速度计检测信号的测量与无线传输技术,设计了系统电路,并完成了原型装置的制作与调试。通过无线、有线传感器的时频响应特性比较表明,无线传感器监测系统能够满足桥梁健康监测的要求。     

基于信道色噪声抑制的信号搜索方法

针对信号搜索过程中存在的色噪声干扰及门限电平难设置的问题,通过全景频谱色噪声边缘提取及差值预处理,提出了一种抑制信道色噪声的信号搜索方法。实际测试表明,该方法能较好地抑制信号搜索谱中存在的信道色噪声,提高信号搜索方法的适用性及搜索性能。