混合模式的入侵检测技术研究

针对传统入侵检测所采用模式匹配技术存在的弊端,介绍了协议分析技术在入侵检测中的应用,提出了一种混合模式的入侵检测技术,即混合使用特征匹配模式和协议分析技术,充分发挥两者的长处。研究表明,该模型提高了检测效率,减少了误报和漏报。     

富田古村传统民居室外门楣匾额特征及文化研究 #

匾额是中华传统文化的瑰宝,是一个地区历史、文化、艺术及民风民俗的重要体现,也是居民生活的缩影。富田古村位于江西吉安青原区,是江西庐陵文化的典型代表,挖掘其传统民居室外门楣匾额的类别、特征及文化内涵,研究其蕴含的社会、教育和生态意义,有助于促进优秀传统建筑文化、工匠精神的传承和发扬。     

基于社会网络的语义Web服务发现模型

web服务发现模型是为了满足用户各种用途的web服务方式,以代码重入和松散耦合的方式以最优的组合实现可以提供用户需要的web服务模型。web服务发现模型是一种面向服务系统架构的一类基础性问题,但是又是解决用户不同需求十分有效的模型。通过对本体特性和发现模型的结构特点的研究,在本文中引入了本体解析的web服务标注算法和环境语义web发现模型。从而更好地实现web服务发现模型的选择用户所要求的服务的准确性,也为web服务的智能匹配做出了探索。     

景象匹配区选择方法研究

通过试验研究了景象匹配概率与实时图的独立像元数、方差、纹理能量比和互相关峰等图像特征的关系,并以此提出了基于这些图像特征的景象匹配区选择方法。图像测试结果表明,该方法可以成功地规划出满足要求的景象匹配区。     

Choice of a pertinent color space for color texture characterization using parametric spectral analysis

This article presents a comparison of different color spaces including RGB, IHLS and L?a*b* for color texture characterization. This comparison is based on the fusion of the independent spatial structure and color feature cues. In IHLS and L*a*b*, two channel complex color images are created from the luminance and the chrominance values. For such images, two dimensional complex multichannel linear prediction models are used to perform parametric power spectrum estimation and the structure feature cues are computed from this estimated power spectrum. Quantitative comparison of auto spectra of luminance and combined chrominance channels for different color spaces is done. This comparison is based on the degree of decorrelation between luminance and chrominance information provided by different color space transformations. Three dimensional histograms are used as color feature cues. Then, to classify color textures, Kullback-Leibler divergence based symmetric distance measures are calculated for pure color, luminance structure and chrominance structure feature cues. Individual as well as combined effect of information from all feature cues on classification results is then compared for different color spaces and different color texture data sets. The proposed color texture classification method performs better than the state of the art methods in certain cases. The L*a*b* color space gives us a better characterization of the chrominance spatial structure as well as the overall spatial structure for all of the chosen data sets. Experimental results on pixel classification of color textures are also presented and discussed.     

冰箱匹配变频压缩机箱体振动高分析、研究与优化

本文针对冰箱系统匹配变频压缩机过程中存在的2000～3000rpm转速段箱体振动高问题进行了系统的分析与研究。采用模态分析法与振动响应相结合的技术手段,定位了箱体匹配的6个主要模态频率,并结合系统随转速变化的振动曲线加以分析,得出发生振动高的根本原因。同时结合声学理论知识,通过更换胶脚的方式使问题彻底解决。该研究成果为冰箱与压缩机在匹配过程中解决并优化其系统振动、提高整机的声品质提供了重要的科学依据和实践经验。     

An optimal scheduling and routing under adaptive spectrum-matching framework for MIMO systems

Multi-users (MUs) along the communication links cause noise and traffic in the channel. The prediction of availability and the optimal usage of channels are the main objectives of the multi-input multi-output (MIMO) system. Several optimisation algorithms select the optimal channel for the users effectively. But the high-error rate and the probability values are the two major problems in traditionally optimised channel selection methods. The bandwidth allotted for information transmission is minimum. Moreover, the outage probability values are maximum in traditional scheduling algorithms. This paper proposes the new optimisation algorithm that predicts the channels for transmission and adaptive spectrum matching concept to predict the suitable channel from allocated bands. Also, the prioritisation on high-spectrum intensity basis assures an efficient data delivery to the receiver. The scheduling of available channels and data prioritisation minimises the error probability rates. This paper investigates the effectiveness of proposed optimal channel utilisation against the different modulation schemes such as three-dimensional complementary codes, linear network coding with the quadrature phase shift keying in terms of the average block error probability and bit error rate.     

Visible–infrared person re-identification based on key-point feature extraction and optimization

Feature extraction for visible–infrared person re-identification (VI-ReID) is challenging because of the cross-modality discrepancy in the images taken by different spectral cameras. Most of the existing VI-ReID methods often ignore the potential relationship between features. In this paper, we intend to transform low-order person features into high-order graph features, and make full use of the hidden information between person features. Therefore, we propose a multi-hop attention graph convolution network (MAGC) to extract robust person joint feature information using residual attention mechanism while reducing the impact of environmental noise. The transfer of higher order graph features within MAGC enables the network to learn the hidden relationship between features. We also introduce the self-attention semantic perception layer (SSPL) which can adaptively select more discriminant features to further promote the transmission of useful information. The experiments on VI-ReID datasets demonstrate its effectiveness.