An Approach to Security for Unstructured Big Data

Security of Big Data is a huge concern. In a broad sense, Big Data contains two types of data: structured and unstructured. Providing security to unstructured data is more difficult than providing security to structured data. In this paper, we have developed an approach to provide adequate security to unstructured data by considering types of data and their sensitivity levels. We have reviewed the different analytics methods of Big Data to build nodes of different types of data. Each type of data has been classified to provide adequate security and enhance the overhead of the security system. To provide security to a data node, and a security suite has been designed by incorporating different security algorithms. Those security algorithms collectively form a security suite which has been interfaced with the data node. Information on data sensitivity has been collected through a survey. We have shown through several experiments on multiple computer systems with varied configurations that data classification with respect to sensitivity levels enhances the performance of the system. The experimental results show how and in what amount the designed security suite reduces overhead and increases security simultaneously.     

The effect of the dynamics of knowledge base complexity on Schumpeterian patterns of innovation: the upstream petroleum industry

This article analyzes important changes in technological innovation in the upstream petroleum industry. It provides evidence that shifts in sectoral patterns of innovation over the petroleum industry's lifecycle from the 1970s up to 2005 were dependent on the dynamics of knowledge base complexity (KBC), a key dimension of an industry's technological regime. Accordingly, observed shifts in innovation patterns are understood to be the aggregated strategic response of industry innovators to changes in the technological regime. The article proposes a quantitative method for exploring KBC and Schumpeterian patterns of innovation, and interactions between the two at the industry level. As the industry evolved, its knowledge base moved to higher orders of complexity creating a shift in the Schumpeterian pattern of innovation. Increased KBC was found to alter Schumpeterian patterns from Mark I toward a ‘modified’ Mark II. Instead of coming predominantly from ‘traditional’ established oil operators, technological innovation was increasingly triggered by a new class of emergent integrated service companies – ‘second tier’ systems integrators of the upstream sector able to cope with increased KBC.     

Hydrochloric acid tank explosion

Explosions in hydrogen chloride storage tanks are very rare. However, we have experienced one. The explosion was so powerful that the tank with a capacity 250 kL, 60% filled with 33% HCL, took off from the ground went up to 8–9 m high in air and landed around 50 m away. The contents of the tank sprayed all over the nearby area. Though the tank was surrounded by other plants and equipment, fortunately, it landed in a barren area. This averted loss of life and property that would have otherwise resulted. © 2009 American Institute of Chemical Engineers Process Saf Prog, 2009     

Internal green integration and environmental performance: The predictive power of proactive environmental strategy,greening the supplier,and environmental collaboration with the supplier

The effect of proactive environmental strategies (PES) on corporate performance has been debated extensively among academics; however, the significance of the pathway of those strategies—internal green integration (IGI) through greening the supplier (GTS) and environmental collaboration with suppliers (ECS)—remains undecided. This study examines environmental performance (EP) through GTS, IGI, and ECS. It also examines the direct link between PES and IGI. A conceptual framework was designed following a rigorous review of the literature. A survey questionnaire was used to collect cross-sectional data from a random sample of manufacturing firms, obtaining 196 usable samples. Using AMOS, the structural equal modeling found a positive and significant impact of PES on IGI. Significant predictors of EP were GTS, IGI, and ECS. The findings of the study can provide managers with guidelines for dealing with business and environmental concerns. They can also contribute to creating strategies for environmental protection and management and reducing adverse effects on the environment. Finally, by examining the direct links between GTS, ECS, and EP, particularly in a developing context, the study may contribute to the literature of environmental policy.     

Information flows within and across sectors in Chinese stock markets

We examine the patterns of information flows within and across sectors of the two Chinese stock exchanges in Shanghai and Shenzhen during 1994–2001. Using the generalized forecast error variance decomposition, we find a high degree of interdependence, indicating that the sectors are highly integrated and sector prices reflect information from other sectors. Industry is the most influential sector in both exchanges, while Finance in Shenzhen is the least integrated with other sectors. Implications of the findings for investors and policymakers are also discussed.     

Herding with collective preferences

This paper studies a simple model of observational learning where agents care not only about the information of others but also about their actions. We show that despite complex strategic considerations that arise from forward-looking incentives, herd behavior can arise in equilibrium. The model encompasses applications such as sequential elections, public good contributions, and leadership charitable giving.     

Estimation of the scale matrix of a multivariate t-model under entropy loss

This paper deals with the estimation of the scale matrix of a multivariatet-model with unknown location vector and scale matrix to improve upon the usual estimators based on the sample sum of product matrix. The well-known results of the estimation of the scale matrix of the multivariate normal model under the assumption of entropy loss function have been generalized to that of a multivariatet-model. The paper is based on the first author’s unpublished Ph.D. dissertation ‘Estimation of the Scale Matrix of a Multivariate T-model’, University of Western Ontario, Canada. Present address: School of Mathematics and Statistics, The University of Sydney, NSW 2006, Australia.     

Product choice for a firm selling related products: A parimutuel application

This paper provides a framework for analysis of product choice by a multiproduct firm selling several products whose demands are interrelated. The decision making process of a racetrack-racebook regarding the parimutuel wagering products (both number and which ones) it should supply is illustrated. A racetrack-racebook is a business entity, which offers its patrons the opportunity to wager, not only on live horse racing conducted at the racetrack but also on races simulcast to that racetrack from a variety of racetracks, from both in-state and out-of-state locations. The demands for these wagering products are interrelated and these interrelationships play a key role in determining the number (and which ones) of these wagering opportunities that will be supplied. Based on the experience of a specific racetrack-racebook, these demand functions are estimated econometrically and the role of these interrelated demands in the supply decision is explored. An algorithm is developed to search over all possible product portfolios to determine that combination of products yielding the highest sales, revenue, or profit.     

Is all turnover intent the same? Exploring future job preference and environmental considerations

This study approaches turnover intent in a novel way by incorporating both environmental and internal organizational factors together to create a more nuanced view of what drives turnover. The analytical focus is on senior-level employees in four agencies within the US Department of Health and Human Services. The findings show that internal organizational factors partially explain decisions to change jobs, but agency and time differences remain even after controlling for those factors. It also finds that the decision to leave government is driven by different factors than the decision to move to other jobs within government.