A new method for expiration code detection and recognition using gabor features based collaborative representation

Text in images and video contains important information for visual content understanding, indexing, and recognizing. Extraction of this information involves preprocessing, localization and extraction of the text from a given image. In this paper, we propose a novel expiration code detection and recognition algorithm by using Gabor features and collaborative representation based classification. The proposed system consists of four steps: expiration code location, character isolation, Gabor features extraction and characters recognition. For expiration code detection, the Gabor energy (GE) and the maximum energy difference (MED) are extracted. The performance of the recognition algorithm is tested over three Gabor features: GE, magnitude response (MR) and imaginary response (IR). The Gabor features are classified based on collaborative representation based classifier (GCRC). To encompass all frequencies and orientations, downsampling and principal component analysis (PCA) are applied in order to reduce the features space dimensionality. The effectiveness of the proposed localization algorithm is highlighted and compared with other existing methods. Extensive testing shows that the suggested detection scheme outperforms existing methods in terms of detection rate for large image database. Also, GCRC show very competitive results compared with Gabor feature sparse representation based classification (GSRC). Also, the proposed system outperforms the nearest neighbor (NN) classifier and the collaborative representation based classification (CRC).     

Comparing interpolation techniques for monthly rainfall mapping using multiple evaluation criteria and auxiliary data sources: A case study of Sri Lanka

Interpolating climatic variables such as rainfall is challenging due to the highly variable nature of meteorological processes, the effects of terrain and geography, and the difficulty in establishing a representative network of stations. While interpolation models are being adapted to include these effects, often the rainfall data contain significant gaps in coverage. In this paper, we evaluated rainfall data from an agro-ecological monitoring network for producing maps of total monthly rainfall in Sri Lanka. We compared four spatial interpolation techniques: inverse distance weighting, thin-plate splines, ordinary kriging, and Bayesian kriging. Error metrics were used to validate interpolations against independent data. Satellite data were used to assess the spatial pattern of rainfall. Results indicated that Bayesian kriging and splines performed best in low and high rainfall, respectively. Rainfall maps generated from the agro-ecological network were found to have accuracies consistent with previous studies in Sri Lanka.     

显微红外热成像技术在故障定位中的应用

电子元器件是整机的基础,在装备的生产和使用过程中,元器件工作异常将影响整个装备的正常运行,元器件发生故障时,必须迅速、准确地进行故障分析和失效定位,避免军用装备在关键时刻发生故障。显微红外热成像技术是一种对电子元器件的微小面积进行高精度非接触的测量,能够显示元器件的反常热分布,暴露不合理的设计和工艺缺陷。论文介绍了显微红外热像仪的原理及特点,举例说明了显微红外热成像技术在失效分析故障定位中的应用,对元器件的故障失效分析和有效性检测提供了指导作用。     

主成分分析法在学生成绩分析中的应用

本文从大学四年成绩的真实数据入手,利用主成分分析法,建立了数学模型,然后给出各主成分的得分函数,并结合成绩进行分析,最后得出影响成绩的主要课程,并验证了学校实行的学分绩是合理的。该研究结果为今后的教学研究和管理提供了科学的依据。     

Microsoft Windows vs. Apple Mac OS X: Resilience against ARP cache poisoning attack in a local area network

ABSTRACT

Robust security measures are integrated into new release versions of operating systems (OSs) to ensure that users have a more secure and reliable environment in which to run their daily tasks. In this article, through extensive practical experiments, we evaluate and compare the resilience of popular versions of Microsoft Windows OSs and Apple Mac OS X against Address Resolution Protocol (ARP) cache poisoning attack in a local area network (LAN). The experimental results demonstrate clearly that all tested versions of Windows OSs and Apple Mac OS X are vulnerable to the ARP cache poisoning attack, and do not deploy built-in efficient security features to prevent success of this attack. In addition, the experimental results directly contradict the common belief that Windows OSs are always less secure than Apple OSs. On the other hand, the article analyzes the efforts that have been made and the different methods that have been applied to detect and prevent ARP cache poisoning attacks. The article shows that none of these efforts and methods has been able to give satisfactory results.     

Variance sensitive adaptive threshold-based PCA method for fault detection with experimental application

Principal Component Analysis (PCA) is a statistical process monitoring technique that has been widely used in industrial applications. PCA methods for Fault Detection (FD) use data collected from a steady-state process to monitor T² and Q statistics with a fixed threshold. For the systems where transient values of the processes must be taken into account, the usage of a fixed threshold in PCA method causes false alarms and missing data that significantly compromise the reliability of the monitoring systems. In the present article, a new PCA method based on variance sensitive adaptive threshold (T_vsa) is proposed to overcome false alarms which occur in the transient states according to changing process conditions and the missing data problem. The proposed method is implemented and validated experimentally on an electromechanical system. The method is compared with the conventional monitoring methods. Experimental tests and tabulated results confirm the fact that the proposed method is applicable and effective for both the steady-state and transient operations and gives early warning to operators.     

基于主成分迭代支集检测的多对比度 磁共振快速成像

很多磁共振成像应用(如 T1、T2 参数成像)需要连续采集一系列不同对比度的图像。丰富的对比度机制反映了 人体组织的内在特性,为临床提供了有效的定量诊断手段。然而,由于扫描时间过长,这种方法在临床上的应用受到一 定的限制。近几年兴起的压缩感知理论在磁共振快速成像方面显示了巨大的潜能。其中,学者们提出一种基于主成分分 析的快速磁共振成像方法。该方法从已知的解析物理模型和参数范围中训练主成分,并通过截断的方式利用图像序列的 时域稀疏性。但是,当这种截断先验信息不准确时,上述方法可能会产生模型误差。 本文通过采用迭代支集检测的方法 实现主成分系数支集的适应性估计。文章最后通过两组人体膝盖数据的重建实验,验证了该方法的有效性。     

辽河流域水环境时空差异性评价

采用聚类分析和主成分分析等多元统计方法对辽河流域的水环境时空差异性进行分析评价.依据流域内4条主要河流(辽河、浑河、太子河和大辽河)的25个监测点2000-2009年资料,监测点分为重度污染区、中度污染区和水质清洁区,反映不同采样点的水质水平和污染程度.通过重度污染区和中度污染区的各个站点主成分综合得分的计算,得到辽河...     

Developing a Higher-Cycled Product Design CAE Model： The Evolution of Automotive Product Design and CAE

To help corporations survive amidst worldwide quality competition, the authors have focused on the strategic development of a higher-cycled product design CAE model employing a highly reliable CAE analysis technology component model. Their efforts are part of principle-based research aimed at evolving product design and CAE development processes to ensure better quality assurance. To satisfy the requirements of developing and producing high quality products while also reducing costs and shortening development times, the effectiveness of this model was verified by successfully applying it to the technological problems of loosening bolts and other product design bottlenecks at auto manufacturers.     

基于广义积分器的谐波电流检测方法研究

针对四桥臂有源电力滤波器的谐波检测环节,提出了一种基于广义积分器的谐波电流检测方法,分析了该检测方法的检测原理及参数k的变化对谐波电流检测效果的影响。仿真结果表明,当电网频率稳定时,该检测方法可准确地提取谐波电流中的基波分量;参数k影响检测的快速性和精确性,应合理设置;该检测方法结构简单,易于实现,对于电网电压畸变、电网频率波动及三相负载不平衡的情况有一定的适应性。