“How do you know that I don’t understand?” A look at the future of intelligent tutoring systems

Many software systems would significantly improve performance if they could adapt to the emotional state of the user, for example if Intelligent Tutoring Systems (ITSs), ATM’s, ticketing machines could recognise when users were confused, frustrated or angry they could guide the user back to remedial help systems so improving the service. Many researchers now feel strongly that ITSs would be significantly enhanced if computers could adapt to the emotions of students. This idea has spawned the developing field of affective tutoring systems (ATSs): ATSs are ITSs that are able to adapt to the affective state of students. The term “affective tutoring system” can be traced back as far as Rosalind Picard’s book Affective Computing in 1997.This paper presents research leading to the development of Easy with Eve, an ATS for primary school mathematics. The system utilises a network of computer systems, mainly embedded devices to detect student emotion and other significant bio-signals. It will then adapt to students and displays emotion via a lifelike agent called Eve. Eve’s tutoring adaptations are guided by a case-based method for adapting to student states; this method uses data that was generated by an observational study of human tutors. This paper presents the observational study, the case-based method, the ATS itself and its implementation on a distributed computer systems for real-time performance, and finally the implications of the findings for Human Computer Interaction in general and e-learning in particular. Web-based applications of the technology developed in this research are discussed throughout the paper.     

An architecture framework for an adaptive extensible processor

To improve the performance of embedded processors, an effective technique is collapsing critical computation subgraphs as application-specific instruction set extensions and executing them on custom functional units. The problem with this approach is the immense cost and the long times required to design a new processor for each application. As a solution to this issue, we propose an adaptive extensible processor in which custom instructions (CIs) are generated and added after chip-fabrication. To support this feature, custom functional units are replaced by a reconfigurable matrix of functional units (FUs). A systematic quantitative approach is used for determining the appropriate structure of the reconfigurable functional unit (RFU). We also introduce an integrated framework for generating mappable CIs on the RFU. Using this architecture, performance is improved by up to 1.33, with an average improvement of 1.16, compared to a 4-issue in-order RISC processor. By partitioning the configuration memory, detecting similar/subset CIs and merging small CIs, the size of the configuration memory is reduced by 40%.     

Signal enhancement of surface plasmon resonance-based immunoassays for the allergen detection

A surface plasmon resonance (SPR) biosensor was used to determine the recombinant group 1 house dust mite allergen (rDer f1) in both HBS-EP buffer and fetal bovine serum (FBS). The monoclonal antibody was immobilized onto the CM5 sensor chip surface using an amine coupling method. The procedures of antibody immobilization and the subsequent primary and enhanced immunoassay were monitored in real time. The sensitivity for rDer f1 detection was remarkably improved by using intact polyclonal antibody as signal amplifying agent. Using this signal enhanced SPR immunosensor, rDer f1 in HBS-EP buffer and FBS was detected at a concentration of 15.4 and 32.1 ng/ml, respectively. The result demonstrates that SPR biosensor is a simple and reliable method for allergen detection.     

Automatic composition of broadcast sports video

This study examines an automatic broadcast soccer video composition system. The research is important as the ability to automatically compose broadcast sports video will not only improve broadcast video generation efficiency, but also provides the possibility to customize sports video broadcasting. We present a novel approach to the two major issues required in the system’s implementation, specifically the camera view selection/switching module and the automatic replay generation module. In our implementation, we use multi-modal framework to perform video content analysis, event and event boundary detection from the raw unedited main/sub-camera captures. This framework explores the possible cues using mid-level representations to bridge the gap between low-level features and high-level semantics. The video content analysis results are utilized for camera view selection/switching in the generated video composition, and the event detection results and mid-level representations are used to generate replays which are automatically inserted into the broadcast soccer video. Our experimental results are promising and found to be comparable to those generated by broadcast professionals.     

Multivariate statistical process control based on multiway locality preserving projections

An approach for multivariate statistical process control based on multiway locality preserving projections (LPP) is presented. The recently developed LPP is a linear dimensionality reduction technique for preserving the neighborhood structure of the data set. It is characterized by capturing the intrinsic structure of the observed data and finding more meaningful low-dimensional information hidden in the high-dimensional observations compared with PCA. In this study, LPP is used to extract the intrinsic geometrical structure of the process data. Hotelling’s T² (D) and the squared prediction error (SPE or Q) statistic charts for on-line monitoring are then presented, and the contribution plots of these two statistical indices are used for fault diagnosis. Moreover, a moving window technique is used for the implementation of on-line monitoring. Case study was carried out with the data of industrial penicillin fed-batch cultivations. As a comparison, the results obtained with the MPCA are also presented. It is concluded that the Multiway LPP (MLPP) outperforms the conventional MPCA. Finally, the robustness of the MLPP monitoring is analyzed by adding noises to the original data.     

称重式烟箱缺条检测与自动剔除控制系统

为了防止缺条烟箱流入市场给烟草企业造成不良影响,对烟厂条烟装箱时出现缺条的现象进行了研究.详细介绍了如何利用滑动平均值的方法来实现称重式烟箱缺条检测与自动剔除控制,并介绍了系统的数据采集方式和数据处理过程以及系统软件所能实现的功能.通过引入烟箱的条形码信息,增加了系统的缺码检测功能.在数据处理上使用滑动平均值,能够根据生产的实际情况动态调整烟箱的标准重量,保证了整个系统准确、快速、稳定的运行.     

使用非均匀量化的Hough空间进行直线段检测

分析图像中最近邻直线间距离和夹角的非均匀性,得到这两个参数与线段方向和长度的相关关系,并由此提出了非均匀量化Hough空间的直线检测算法NUHT (Nonuniform Hough Transform).实验结果表明,NUHT在不降低运算效率的情况下,有2倍于标准Hough变换SHT (Standard Hough Transform)的直线段检测能力,同时误报率低于SHT的1/2.     

多模态特征融合的新闻视频故事分割方法

新闻视频故事分割是新闻视频分析的重要底层支持技术,本文提出了一种融合音频、视频等多模态特征的新闻视频故事分割方法.首先分析音频特征的静音片段作为音频特征候选点,对视频进行镜头分割,并将镜头分割结果分类为播音员镜头和新闻报道镜头,将所有的镜头分割点和播音员镜头片段提取为视频片段候选点;然后通过对新闻视频编辑规则的研究,对视频、音频特征候选点融合分析来获取新闻视频的故事分割,实验表明该方法在不同新闻视频编辑规则下都具有较好的分割效率.     

基于IPv6的入侵检测与防火墙联动系统

网络安全中入侵检测与防火墙的联动是研究的热点,目前已经实现的联动系统多局限于IPv4网络,该文基于IPv6网络的防火墙和入侵检测系统,提出一种分布式的网络安全防护体系,通过设置入侵检测代理和集中控制服务器,分析检测到的入侵状况信息后主动调整防火墙的规则策略,实现支持IPv6/IPv4双协议的入侵检测与防火墙动态联动。测试结果表明,系统有效可靠。     

移动自组网中的MAC地址动态分配

减小动态源路由协议DSR的开销、提高无线信道的利用率的关键是在协议运行时,使用1 B的MAC地址对节点进行标识。该文研究了如何为特定IP地址标识的网络节点动态分配MAC地址,实现了一种基于预测的无冲突MAC地址动态分配方法,其中所引入的开销较低。实际应用表明,该分配方法具有较强的适用性、可靠性。