Human error identification in human reliability assessment. Part 2: Detailed comparison of techniques

This is the second part of a two-part review of human error identification (HEI) approaches in human reliability assessment (HRA). Part 1 reviewed the probabilistic risk assessment (PRA) context in which HRA occurs, and then detailed 12 HEI techniques which have evolved in the field of HRA. Part 2 attempts to compare the way these techniques perform against a range of criteria relevant to HEI theoretical and empirical validity, and practical usefulness in applied HRA. It is hoped that these comparisons will help assessors in the selection of techniques for practical applications. The comparisons also point to research and development needs in the area of applied HEI.     

Robust spatial flood vulnerability assessment for Han River using fuzzy TOPSIS with α-cut level set

This study aims to improve the general flood vulnerability approach using fuzzy TOPSIS based on α-cut level sets which can reduce the uncertainty inherent in even fuzzy multi-criteria decision making process. Since fuzzy TOPSIS leads to a crisp closeness for each alternative, it is frequently argued that fuzzy weights and fuzzy ratings should be in fuzzy relative closeness. Therefore, this study used a modified α-cut level set based fuzzy TOPSIS to develop a spatial flood vulnerability approach for Han River in Korea, considering various uncertainties in weights derivation and crisp data aggregation. Two results from fuzzy TOPSIS and modified fuzzy TOPSIS were compared. Some regions which showed no or small ranking changes have their centro-symmetric distributions, while other regions whose rankings varied dynamically, have biased (anti-symmetric) distributions. It can be concluded that α-cut level set based fuzzy TOPSIS produce more robust prioritization since more uncertainties can be considered. This method can be applied to robust spatial vulnerability or decision making in water resources management.     

PRIVACY LEAKAGE IN HEALTH SOCIAL NETWORKS

Members of health social networks may be susceptible to privacy leaks by the amount of information they leave behind. The threat to privacy increases when members of these networks reuse their pseudonyms in other social networks. The risk of re‐identifying users from such networks requires quantitative estimates to evaluate its magnitude. The estimates will enable managers and members of health social communities to take corrective measures. We introduce a new re‐identification attack, the social network attack, that takes advantage of the fact that users reuse their pseudonyms. To demonstrate the attack, we establish links between MedHelp and Twitter (two popular social networks) based on matching pseudonyms. We used Bayesian networks to model the re‐identification risk and used stylometric techniques to identify the strength of the links. On the basis of our model 7‐11. 8% of the MedHelp members in the sample population who reused their pseudonyms in Twitter were re‐identifiable compared with 1% who did not. The risk estimates were measured at the 5% risk threshold. Our model was able to re‐identify users with a sensitivity of 41% and specificity of 96%. The potential for re‐identification increases as more data is accumulated from these profiles, which makes the threat of re‐identification more serious.     

基于多决策树的RFID入侵检测模型

为了能够有效对RFID系统的已知攻击和未知攻击进行检测和预警,在分析大量RFID安全协议的基础上,提出了利用构建多决策树的方法对RFID系统的入侵行为进行检测。通过分析,得到所构造出的多决策树能够发现针对RFID系统的攻击之间的关系,并且具有可扩展性和高效性,使之能够适用于各种实际的RFID系统的应用。     

基于ARM的仪器管理系统设计与实现

针对学校等大型科研平台拥有的精密器材种类繁多、安置位置分散、操作流程特异、操作人员流动性大的现象,基于监测的思想设计了此仪器管理系统,旨在督促实验人员按稳妥的使用流程操作仪器,并为器材的更迭维修提供参考。系统分为终端、服务端两部分,终端通过检测电流来判断仪器状态,使用者使用需用有效IC卡辨别身份,终端相应给予声光提示,并且拍照留据。相应的状态情况可以通过网络传输到服务器,例如使用者有效卡号、报警照片等且客户端可以从服务端获取人员信息更新等资料。通过对本工程中心内部分仪器的监管测试表明,较好的提高了操作人员使用素质,提高了仪器管理水平。     

3D fingerprint reconstruction system using feature correspondences and prior estimated finger model

The paper studies a 3D fingerprint reconstruction technique based on multi-view touchless fingerprint images. This technique offers a solution for 3D fingerprint image generation and application when only multi-view 2D images are available. However, the difficulties and stresses of 3D fingerprint reconstruction are the establishment of feature correspondences based on 2D touchless fingerprint images and the estimation of the finger shape model. In this paper, several popular used features, such as scale invariant feature transformation (SIFT) feature, ridge feature and minutiae, are employed for correspondences establishment. To extract these fingerprint features accurately, an improved fingerprint enhancement method has been proposed by polishing orientation and ridge frequency maps according to the characteristics of 2D touchless fingerprint images. Therefore, correspondences can be established by adopting hierarchical fingerprint matching approaches. Through an analysis of 440 3D point cloud finger data (220 fingers, 2 pictures each) collected by a 3D scanning technique, i.e., the structured light illumination (SLI) method, the finger shape model is estimated. It is found that the binary quadratic function is more suitable for the finger shape model than the other mixed model tested in this paper. In our experiments, the reconstruction accuracy is illustrated by constructing a cylinder. Furthermore, results obtained from different fingerprint feature correspondences are analyzed and compared to show which features are more suitable for 3D fingerprint images generation.     

Fast and robust face recognition via coding residual map learning based adaptive masking

Robust face recognition (FR) is an active topic in computer vision and biometrics, while face occlusion is one of the most challenging problems for robust FR. Recently, the representation (or coding) based FR schemes with sparse coding coefficients and coding residual have demonstrated good robustness to face occlusion; however, the high complexity of l₁-minimization makes them less useful in practical applications. In this paper we propose a novel coding residual map learning scheme for fast and robust FR based on the fact that occluded pixels usually have higher coding residuals when representing an occluded face image over the non-occluded training samples. A dictionary is learned to code the training samples, and the distribution of coding residuals is computed. Consequently, a residual map is learned to detect the occlusions by adaptive thresholding. Finally the face image is identified by masking the detected occlusion pixels from face representation. Experiments on benchmark databases show that the proposed scheme has much lower time complexity but comparable FR accuracy with other popular approaches.     

Gender,culture and determinants of behavioural intents to adopt mobile commerce among the Y Generation in transition economies: evidence from Kazakhstan

This study investigates perceived risk and trust in relationship to the Diffusion of Innovation Theory [Rogers, E.M., 1962. Diffusion of innovations. Glencoe, IL: The Free Press; 1983. Diffusion of innovations. 3rd ed. New York: The Free Press] from a cultural perspective to understand the determinants of behavioural intent to adopt mobile commerce among the Y Generation in Kazakhstan. Surveys from 345 university-level students and subsequent structural equation modelling revealed perceived risk, trustworthiness and Rogers’ five innovation characteristics are important determinants. Perceived risk and trustworthiness are important determinants because of the high uncertainty avoidance characteristics of the Kazakh society. This study advances theory regarding culture- and generation-based characteristics to transition economies by verifying theoretical proposition regarding the behavioural intent towards mobile commerce adoption, resulting in a greater understanding of mobile commerce adoption among the Y Generation in transition economies. Marketing implications are discussed.     

General triangular midpoint subdivision

In this paper, we introduce triangular subdivision operators which are composed of a refinement operator and several averaging operators, where the refinement operator splits each triangle uniformly into four congruent triangles and in each averaging operation, every vertex will be replaced by a convex combination of itself and its neighboring vertices. These operators form an infinite class of triangular subdivision schemes including Loop's algorithm with a restricted parameter range and the midpoint schemes for triangular meshes. We analyze the smoothness of the resulting subdivision surfaces at their regular and extraordinary points by generalizing an established technique for analyzing midpoint subdivision on quadrilateral meshes. General triangular midpoint subdivision surfaces are smooth at all regular points and they are also smooth at extraordinary points under certain conditions. We show some general triangular subdivision surfaces and compare them with Loop subdivision surfaces.