Data quality and firm performance: empirical evidence from the Korean financial industry

Despite popular belief that timely and precise data are important and indispensable to good decisions and that good decisions are related to better firm performance, empirical research that examines the effect of data quality on firm performance is still scarce. How great an impact does data quality have on firm performance? This study empirically investigates the effect of firm-level data quality on firm performance in the Korean financial industry during 2008–2010. The results show that commercial banks have high-quality data, while credit unions have comparatively low-quality data. They also show that better data quality has a positive influence on sales, operating profit, and value added. Improving the level of data quality management maturity by one can increase firm performance by 33.7 % in sales, 64.4 % in operating profit, and 26.2 % in value added.     

Fractional-Order Complementary Filters for Small Unmanned Aerial System Navigation

Orientation estimation is very important for development of unmanned aerial systems (UASs), and is performed by combining data from several sources and sensors. Kalman filters are widely used for this task, however they typically assume linearity and Gaussian noise statistics. While these assumptions work well for high-quality, high-cost sensors, it does not work as well for low-cost, low-quality sensors. For low-cost sensors, complementary filters can be used since no assumptions are made with regards to linearity and noise statistics. In this article, the history and basics of complementary filters are included with examples, the concepts of filtering based on fractional-order calculus are applied to the complementary filter, and the efficacy of non-integer-order filtering on systems with non-Gaussian noise is explored with good success.     

基于光滑表示的半监督分类算法

近年来,基于图的半监督分类是机器学习与数据挖掘领域的研究热点之一.该类方法一般通过构造图来挖掘数据中隐含的信息,并利用图的结构信息来对无标签样本进行分类.因此,半监督分类的效果严重依赖于图的质量.文中提出了一种基于光滑表示的半监督分类算法.具体来说,此方法通过应用一个低通滤波器来实现数据的平滑,然后将光滑数据用于半监督...     

Semantic Provenance for eScience: Managing the Deluge of Scientific Data

Provenance information in eScience is metadata that's critical to effectively manage the exponentially increasing volumes of scientific data from industrial-scale experiment protocols. Semantic provenance, based on domain-specific provenance ontologies, lets software applications unambiguously interpret data in the correct context. The semantic provenance framework for eScience data comprises expressive provenance information and domain-specific provenance ontologies and applies this information to data management. The authors' "two degrees of separation" approach advocates the creation of high-quality provenance information using specialized services. In contrast to workflow engines generating provenance information as a core functionality, the specialized provenance services are integrated into a scientific workflow on demand. This article describes an implementation of the semantic provenance framework for glycoproteomics.     

Assessing information quality of e-learning systems: a web mining approach

E-learning systems provide a promising solution as an information exchanging channel. Improved technologies could mean faster and easier access to information but do not necessarily ensure the quality of this information; for this reason it is essential to develop valid and reliable methods of quality measurement and carry out careful information quality evaluations. This paper proposes an assessment model for information quality in e-learning systems based on the quality framework we proposed previously: the proposed framework consists of 14 quality dimensions grouped in three quality factors: intrinsic, contextual representation and accessibility. We use the relative importance as a parameter in a linear equation for the measurement scheme. Formerly, we implemented a goal-question-metrics approach to develop a set of quality metrics for the identified quality attributes within the proposed framework. In this paper, the proposed metrics were computed to produce a numerical rating indicating the overall information quality published in a particular e-learning system. The data collection and evaluation processes were automated using a web data extraction technique and results on a case study are discussed. This assessment model could be useful to e-learning systems designers, providers and users as it provides a comprehensive indication of the quality of information in such systems.     

IPSec安全策略形式化技术的研究

IPSec安全策略配置是一项复杂和易出错的工作。为解决这问题,提出了通过有序两元判定图表(OBDD)提供全面的IPSec安全策略冲突识别和分类的通用架构模型,并基于该架构模型,开发了一组在通用IPSec策略配置过程中发现策略内部的冲突问题的技术。实验测试证明了该架构模型和技术在发现和解决策略冲突问题的有效性。     

IPSec策略冲突发现形式化技术的研究

IPSec目前已成为Internet安全事实上的标准协议,尽管IPSec为网络安全提供了丰富的安全保护模式和操作,但其策略配置是非常复杂和易出错的一项工作.为解决这问题提出了通过有序两元判定图表（OBDD）来提供全面的IPSec安全策略冲突的识别和分类的通用架构模型,并且基于这种架构模型,开发了一组在通用IPSec策略配置过程中发现策略内部的冲突问题的技术。通过实验测试证明了该架构模型和技术在发现和解决策略冲突问题的有效性。     

A privacy preserving authorisation system for the cloud

In this paper we describe a policy based authorisation infrastructure that a cloud provider can run as an infrastructure service for its users. It will protect the privacy of users? data by allowing the users to set their own privacy policies, and then enforcing them so that no unauthorised access is allowed to their data. The infrastructure ensures that the users? privacy policies are stuck to their data, so that access will always be controlled by the policies even if the data is transferred between cloud providers or services. This infrastructure also ensures the enforcement of privacy policies which may be written in different policy languages by multiple authorities such as: legal, data subject, data issuer and data controller. A conflict resolution strategy is presented which resolves conflicts among the decisions returned by the different policy decision points (PDPs). The performance figures are presented which show that the system performs well and that each additional PDP only imposes a small overhead.     

Provenance in Agent-Mediated Healthcare Systems

This article is part of a special issue on Intelligent Agents in Healthcare. Healthcare information systems can use agent-oriented cooperation techniques and standardized, electronic healthcare-record-exchange protocols to combine information about the different facets of a patient's therapy provided by different healthcare providers at different locations. Provenance is an innovative approach to tracing events in complex distributed processes. It also traces dependencies between such events and associated decisions by human actors. This article focuses on three aspects of provenance in agent-mediated healthcare systems. First, it defines provenance and shows how to apply it in agent-mediated healthcare applications. Second, it introduces a method that lets independent, autonomous healthcare agents that don't directly interact document their processes. Third, it shows how this approach helps institutions contend with privacy issues.     

Signaling theory and information asymmetry in online commerce

An e-business environment results in information asymmetry because buyers cannot physically evaluate the quality of products and easily assess the trustworthiness of sellers. Product and seller quality are communicated through website signals. Using signaling theory, we developed a three-dimensional framework to classify website signals. We empirically tested the framework with a comparative content analysis of websites from a sample of online pharmacies. We found that low-quality sellers were likely to avoid costly and easy-to-verify signals and used fewer signals than did high-quality sellers, who used costly and difficult-to-verify signals and displayed more signals. These results provide information to online buyers and regulatory institutions in charge of online retailer evaluation.     

基于图像质量分区的指纹特征提取

低质量指纹图像的特征提取和变形指纹的匹配是当前指纹识别研究中的两个主要问题。很多算法在特征提取时不区分高、低质量区域,结果在高质量区域耗费了过多的运算时间和计算资源。本文提出了一种基于图像质量分区的指纹特征提取方法,先用一种简单的图像区域质量计算方法评价各区域的图像质量,然后对高质量区域直接从灰度图像跟踪纹线、提取节点,对低质量区域执行传统的方向计算、增强、二值化和细化后提取特征。实验结果表明,该方法不仅提高了特征提取的速度,在准确性上也有所提高。     

基于SAML的真单点登录框架

随着企业信息化进程的推进,企业业务系统不断地增加.陆续加入的业务系统往往采用不同实现技术和安全策略,并且各自维护独立的认证授权体系,这样很容易形成"信息孤岛".为消除这种系统访问控制孤立,基于统一认证的单点登录(SingleSignOn)系统应运而生.然而,现有的单点登录模型在安全性、扩展性、可维护性等方面都存在诸多不足.本文基于安全断言标记语言SAML,设计了一个安全性高、互操作性好、松耦合的的统一认证单点登录框架,主要包括身份提供者过滤器和服务提供者过滤器模块、单点登录交互协议和安全保障机制.     

Balancing behavioral privacy and information utility in sensory data flows

Miniaturized smart sensors are increasingly being used to collect personal data which embed minute details of our everyday life. When shared, the data streams can easily be mined to draw a rich set of inferences regarding private behaviors and lifestyle patterns. Disclosure of some of these unintended inferences gives rise to the notion of behavioral privacy different from traditional identity privacy typically addressed in the literature. From the provider’s perspective, we summarize these privacy concerns into three basic questions: (i) Whom to share data with? (ii) How much data to share? and (iii) What data to share?In this paper, we outline the architecture of SensorSafe as a software-based framework with support for three basic mechanisms to allow privacy-aware data sharing. First, it provides a library of routines accessible using a simple GUI for providers to define fine-grained, context-dependent access control. Second, it uses the trust network between consumers and providers to derive the optimal rate of information flow which would maintain both provider privacy and consumer utility. Finally, it introduces a compressive sensing based feature-sharing procedure to further control the amount of information release. We provide simulation results to illustrate the efficacy of each of these mechanisms.     

The effects of information overload on consumers’ subjective state towards buying decision in the internet shopping environment

One of the strengths of e-retailers is their ability to convey rich information to their customers. The theory of information overload, however, predicts that, beyond a threshold, more information leads to worse quality of, but a better subjective state towards the buying decisions. This study, via re-appraising the conception of decision quality, subjective state towards decision, and threshold of information load, proposes an extended model, considering the roles of information filtering mechanisms, on-line shopping experience, and perceived information overload, to examine the effects of information load on subjective state towards decision. An experiment was conducted to test the research model. The results indicate that rich information leads to a perception of high information overload; and the latter lead consumers to a worse subject state towards decision. Information filtering tools and on-line shopping experience may have influences on relieving but are not the panacea to the phenomenon of information overload. Novice consumers may face a more serious information overload problem.     

Supplying Web 2.0: An empirical investigation of the drivers of consumer transmutation of culture-oriented digital information goods

This paper describes an empirical study of behaviors associated with consumers’ creative modification of digital information goods found in Web 2.0 and elsewhere. They are products of culture such as digital images, music, video, news and computer games. We will refer to them as “digital culture products”. How do consumers who transmute such products differ from those who do not, and from each other? This study develops and tests a theory of consumer behavior in transmuting digital culture products, separating consumers into different groups based on how and why they transmute. With our theory, we posit these groups as having differences of motivation, as measured by product involvement and innovativeness, and of ability as measured by computer skills. A survey instrument to collect data from Internet-capable computer users on the relevant constructs, and on their transmutation activities, is developed and distributed using a web-based survey hosting service. The data are used to test hypotheses that consumers’ enduring involvement and innovativeness are positively related to transmutation behaviors, and that computer self-efficacy moderates those relationships. The empirical results support the hypotheses that enduring involvement and innovativeness do motivate transmutation behavior. The data analysis also supports the existence of a moderating relationship of computer self-efficacy with respect to enduring involvement, but not of computer self-efficacy with respect to innovativeness. The findings further indicate that transmutation activities should be expected to impact Web 2.0-oriented companies, both incumbents and start-ups, as they make decisions about how to incorporate consumers into their business models not only as recipients of content, but also as its producers.     

Inference management,trust and obfuscation principles for quality of information in emerging pervasive environments

The emergence of large scale, distributed, sensor-enabled, machine-to-machine pervasive applications necessitates engaging with providers of information on demand to collect the information, of varying quality levels, to be used to infer about the state of the world and decide actions in response. In these highly fluid operational environments, involving information providers and consumers of various degrees of trust and intentions, information transformation, such as obfuscation, is used to manage the inferences that could be made to protect providers from misuses of the information they share, while still providing benefits to their information consumers. In this paper, we develop the initial principles for relating to inference management and the role that trust and obfuscation plays in it within the context of this emerging breed of applications. We start by extending the definitions of trust and obfuscation into this emerging application space. We, then, highlight their role as we move from the tightly-coupled to loosely-coupled sensory-inference systems and describe how quality, value and risk of information relate in collaborative and adversarial systems. Next, we discuss quality distortion illustrated through a human activity recognition sensory system. We then present a system architecture to support an inference firewall capability in a publish/subscribe system for sensory information and conclude with a discussion and closing remarks.     

Lattice-Based High-Dimensional Gaussian Filtering and the Permutohedral Lattice

High-dimensional Gaussian filtering is a popular technique in image processing, geometry processing and computer graphics for smoothing data while preserving important features. For instance, the bilateral filter, cross bilateral filter and non-local means filter fall under the broad umbrella of high-dimensional Gaussian filters. Recent algorithmic advances therein have demonstrated that by relying on a sampled representation of the underlying space, one can obtain speed-ups of orders of magnitude over the naïve approach. The simplest such sampled representation is a lattice, and it has been used successfully in the bilateral grid and the permutohedral lattice algorithms. In this paper, we analyze these lattice-based algorithms, developing a general theory of lattice-based high-dimensional Gaussian filtering. We consider the set of criteria for an optimal lattice for filtering, as it offers a good tradeoff of quality for computational efficiency, and evaluate the existing lattices under the criteria. In particular, we give a rigorous exposition of the properties of the permutohedral lattice and argue that it is the optimal lattice for Gaussian filtering. Lastly, we explore further uses of the permutohedral-lattice-based Gaussian filtering framework, showing that it can be easily adapted to perform mean shift filtering and yield improvement over the traditional approach based on a Cartesian grid.     

基于容积卡尔曼滤波的异类多传感器一致性融合算法

针对单一光频传感器获取目标特征信息存在的不一致性,提出一种基于容积卡尔曼滤波的异类多传感器一致性融合方法。首先,从原理上分析了激光、红外与雷达三类传感器量测信息的特征及其存在的差异,进而在容积卡尔曼滤波框架下,针对雷达、红外和激光探测等组成的典型目标侦测系统,结合一致性融合策略,通过对目标距离和方位信息融合处理改善目标状态估计精度。仿真结果表明：相对于传统的单传感器滤波方法,所提出的融合方法和策略具有较好的滤波性能。     

基于形式化技术的IPSec安全策略冲突发现研究

基于安全策略形式化技术,提出了通过有序两元判定图表(OBDD)提供全面IPSec安全策略冲突的识别和分类的通用架构模型.基于这架构模型,研究了在通用IPSec策略配置过程中发现策略内部的冲突问题的技术.实验测试证明了该架构模型和技术在发现和解决策略冲突问题的有效性.