Smart Asset Management for Electric Utilities: Big Data and Future

This paper discusses about future challenges in terms of big data and new technologies. Utilities have been collecting data in large amounts but they are hardly utilized because they are huge in amount and also there is uncertainty associated with it. Condition monitoring of assets collects large amounts of data during daily operations. The question arises "How to extract information from large chunk of data?" The concept of "rich data and poor information" is being challenged by big data analytics with advent of machine learning techniques. Along with technological advancements like Internet of Things (IoT), big data analytics will play an important role for electric utilities. In this paper, challenges are answered by pathways and guidelines to make the current asset management practices smarter for the future.Comment: 13 pages, 3 figures, Proceedings of 12th World Congress on Engineering Asset Management (WCEAM) 201

Privacy matters:issues within mechatronics

As mechatronic devices and components become increasingly integrated with and within wider systems concepts such as Cyber-Physical Systems and the Internet of Things, designer engineers are faced with new sets of challenges in areas such as privacy. The paper looks at the current, and potential future, of privacy legislation, regulations and standards and considers how these are likely to impact on the way in which mechatronics is perceived and viewed. The emphasis is not therefore on technical issues, though these are brought into consideration where relevant, but on the soft, or human centred, issues associated with achieving user privacy

Enterprise application reuse: Semantic discovery of business grid services

Web services have emerged as a prominent paradigm for the development of distributed software systems as they provide the potential for software to be modularized in a way that functionality can be described, discovered and deployed in a platform independent manner over a network (e.g., intranets, extranets and the Internet). This paper examines an extension of this paradigm to encompass ‘Grid Services’, which enables software capabilities to be recast with an operational focus and support a heterogeneous mix of business software and data, termed a Business Grid - "the grid of semantic services". The current industrial representation of services is predominantly syntactic however, lacking the fundamental semantic underpinnings required to fulfill the goals of any semantically-oriented Grid. Consequently, the use of semantic technology in support of business software heterogeneity is investigated as a likely tool to support a diverse and distributed software inventory and user. Service discovery architecture is therefore developed that is (a) distributed in form, (2) supports distributed service knowledge and (3) automatically extends service knowledge (as greater descriptive precision is inferred from the operating application system). This discovery engine is used to execute several real-word scenarios in order to develop and test a framework for engineering such grid service knowledge. The examples presented comprise software components taken from a group of Investment Banking systems. Resulting from the research is a framework for engineering servic

Open secrets

The law of trade secrets is often conceptualized in bilateral terms, as creating and enforcing rights between trade secret owners, on the one hand, and misappropriators on the other hand. This paper, a chapter in a forthcoming collection on the law of trade secrets, argues that trade secrets and the law that guards them can serve structural and institutional roles as well. Somewhat surprisingly, given the law’s focus on secrecy, among the institutional products of trade secrets law are commons, or managed openness: environments designed to facilitate the structured sharing of information. The paper illustrates with examples drawn from existing literature on cuisine, magic, and Internet search.

Initial public offerings and venture capital in Germany

We present a survey on the role of initial public offerings (Epos) and venture capital (VC) in Germany after the Second World War. Between 1945 and 1983 IPOs hardly played a role at all and only a minor role thereafter. In addition, companies that chose an IPO were much older and larger than the average companies going public for the first time in the US or the UK. The level of IPO underpricing in Germany, in contrast, has not been fundamentally different from that in other countries. The picture for venture capital financing is not much different from that provided by IPOs in Germany. For a long time venture capital financing was hardly significant, particularly as a source of early stage financing. The unprecedented boom on the Neuer Markt between 1997 and 2000, when many small venture capital financed firms entered the market, provides a striking contrast to the preceding era. However, by US standards, the levels of both IPO and venture capital activities remained rather low even in this boom phase. The extent to which recent developments will have a lasting impact on the financing of German firms, the level of IPO activity, and venture capital financing, remains to be seen. At the time of writing, activity has come to a near stand still and the Neuer Markt has just been dissolved. The low number of IPOs and the fairly low volume of VC financing in Germany before the introduction of the Neuer Markt are a striking and much debated phenomenon. Understanding the reasons for these apparent peculiarities is vital to understanding the German financial system. The potential explanations that have been put forward range from differentces in mentality to legal and institutional impediments and the availability of alternative sources of financing. Moreover the recent literature discusses how interest groups may have benefited and influenced the situation. These groups include politicians, unions/workers, managers/controlling-owners of established firms as well as banks. Revised version forthcoming in "The German Financial System", edited by Jan P. Krahnen and Reinhard H. Schmidt, Oxford University Press

Russian police and transition to democracy: lessons from one empirical study

The paper discusses public experiences of policing in today’s Russia, public attitudes towards police resulting from such experiences and wider social implications of those attitudes. At the basis of the discussion is an empirical study which has been carried out by the author. The study has found abundant evidence of distrust towards – and fear of – police by contemporary Russians. It is argued that the corrupt, brutal and unaccountable police who lack legitimacy in the eyes of citizens trigger public responses that may help to deepen social inequalities, subvert the process of establishing the rule of law and impede the Russian transition to democracy. Moreover, if citizens view the police as illegitimate – indeed, believe that the very state agency designed to protect them actually presents threats to their security – the legitimacy of the entire state structure is at risk

Big data analytics:Computational intelligence techniques and application areas

Big Data has significant impact in developing functional smart cities and supporting modern societies. In this paper, we investigate the importance of Big Data in modern life and economy, and discuss challenges arising from Big Data utilization. Different computational intelligence techniques have been considered as tools for Big Data analytics. We also explore the powerful combination of Big Data and Computational Intelligence (CI) and identify a number of areas, where novel applications in real world smart city problems can be developed by utilizing these powerful tools and techniques. We present a case study for intelligent transportation in the context of a smart city, and a novel data modelling methodology based on a biologically inspired universal generative modelling approach called Hierarchical Spatial-Temporal State Machine (HSTSM). We further discuss various implications of policy, protection, valuation and commercialization related to Big Data, its applications and deployment

MANAGING KNOWLEDGE AND DATA FOR A BETTER DECISION IN PUBLIC ADMINISTRATION

In the current context, the society is dominated by the rapid development of computer networks and the integration of services and facilities offered by the Internet environment at the organizational level. The success of an organization depends largely on the quality and quantity of information it has available to develop quickly decisions able to meet the current needs. The need for a collaborative environment within the central administration leads to the unification of resources and instruments around the Center of Government, to increase both the quality and efficiency of decision - making, especially reducing the time spent with decision - making, and upgrading the decision – making act.administration, strategy, decision, complex systems, management, infrastructure, e-government, information society, government platform.