We are living in the era of "Big Data" and the computing power required to deal with "Big Data" both in terms of its energy consumption and technical complexity is one of the key areas of research and development. The U.S. Environmental Protection Agency estimates that centralized computing infrastructures (data centres) currently use 7 giga watts of electricity during peak loads. This translates into about 61 billion kilowatt hours of electricity used. By the EPA's estimates, power-hungry data centres consume the annual output of 15 average-sized power plants. One of the top constraints to increasing computing power, besides the ability to cool, is simply delivering enough power to a given physical space. Green Information Technology: A Sustainable Approach offers in a single volume a broad collection of practical techniques and methodologies for designing, building and implementing a green technology strategy in any large enterprise environment, which up until now has been scattered in difficult-to-find scholarly resources. Included here is the latest information on emerging technologies and their environmental impact, how to effectively measure sustainability, discussions on sustainable hardware and software design, as well as how to use big data and cloud computing to drive efficiencies and establish a framework for sustainability in the information technology infrastructure. Written by recognized experts in both academia and industry, Green Information Technology: A Sustainable Approach is a must-have guide for researchers, computer architects, computer engineers and IT professionals with an interest in greater efficiency with less environmental impact. - Introduces the concept of using green procurement and supply chain programs in the IT infrastructure. - Discusses how to use big data to drive efficiencies and establish a framework for sustainability in the information technology infrastructure. - Explains how cloud computing can be used to consolidate corporate IT environments using large-scale shared infrastructure reducing the overall environmental impact and unlocking new efficiencies. - Provides specific use cases for Green IT such as data center energy efficiency and cloud computing sustainability and risk.
Application of Big Data for National Security provides users with state-of-the-art concepts, methods, and technologies for Big Data analytics in the fight against terrorism and crime, including a wide range of case studies and application scenarios. This book combines expertise from an international team of experts in law enforcement, national security, and law, as well as computer sciences, criminology, linguistics, and psychology, creating a unique cross-disciplinary collection of knowledge and insights into this increasingly global issue. The strategic frameworks and critical factors presented in Application of Big Data for National Security consider technical, legal, ethical, and societal impacts, but also practical considerations of Big Data system design and deployment, illustrating how data and security concerns intersect. In identifying current and future technical and operational challenges it supports law enforcement and government agencies in their operational, tactical and strategic decisions when employing Big Data for national security - Contextualizes the Big Data concept and how it relates to national security and crime detection and prevention - Presents strategic approaches for the design, adoption, and deployment of Big Data technologies in preventing terrorism and reducing crime - Includes a series of case studies and scenarios to demonstrate the application of Big Data in a national security context - Indicates future directions for Big Data as an enabler of advanced crime prevention and detection
In this chapter we present an empirically-based theory-independent framework of online radicalization. The framework provides a systematic basis for (a) the representation of causal mechanisms of online radicalization and (b) the identification of radicalized individuals. Its application lies in informing models of online radicalization, guiding the formulation of policies, and identifying gaps in our current knowledge of online radicalization.
The use of cyberspace to disseminate radical materials and messages has become the predominant method used by extremists to recruit and radicalize individuals to their cause. The phenomenon of online radicalization is increasing, presenting pressing security concerns. In direct response to the emerging threats and risks arising from online radicalization, global efforts are being made to monitor and disrupt contemporary cyber avenues of terrorist recruitment. Individuals, particularly young computer-literate males, are becoming self-radicalized through access to sophisticated online materials promoting and justifying extreme views and actions. The detection of these self-radicalized individuals is challenging. This chapter outlines a computational approach based on Fuzzy Cognitive Maps (FCMs) for the identification of radicalized individuals online. The model aims to inform and support the classification of individual profiles to tackle terrorist activities in the future.
Application of Big Data for National Security provides users with state-of-the-art concepts, methods, and technologies for Big Data analytics in the fight against terrorism and crime, including a wide range of case studies and application scenarios. This book combines expertise from an international team of experts in law enforcement, national security, and law, as well as computer sciences, criminology, linguistics, and psychology, creating a unique cross-disciplinary collection of knowledge and insights into this increasingly global issue. The strategic frameworks and critical factors presented in Application of Big Data for National Security consider technical, legal, ethical, and societal impacts, but also practical considerations of Big Data system design and deployment, illustrating how data and security concerns intersect. In identifying current and future technical and operational challenges it supports law enforcement and government agencies in their operational, tactical and strategic decisions when employing Big Data for national security - Contextualizes the Big Data concept and how it relates to national security and crime detection and prevention - Presents strategic approaches for the design, adoption, and deployment of Big Data technologies in preventing terrorism and reducing crime - Includes a series of case studies and scenarios to demonstrate the application of Big Data in a national security context - Indicates future directions for Big Data as an enabler of advanced crime prevention and detection
The current rapid development in both computing power and the ability to present and mine complex data sets in useful ways provides the backdrop to Intelligence Management: Knowledge Driven Frameworks for Combating Terrorism and Organized Crime. The chapters address the linkage between: law enforcement; developments in information and communication technologies and key ideas about the management of data, information, knowledge and intelligence. The work is conducted by a number of international academic and industrial research groups, law enforcement agencies, and end users. Section 1 presents four chapters that address the details, outcomes, user needs and background theoretical ideas behind a large-scale research aand development project in this domain (The Odyssey Project). This project explored the challenges of establishing a Pan-European ballistics and crime information intelligence network. It represents an example of the type of system that is likely to become commonly used by Law Enforcement Agencies in the near future. Many of the challenges are not technical but organisational, legal, economic, social and political. Sections 2 and 3 therefore present wider commentaries. Section 2 explores other research and development projects that attempt to exploit the power of contemporary ICT systems to support Law Enforcement Agencies in many aspects of their work including investigations, data analysis and presentation, identification, training and crime prevention. Section 3 takes a look at the social and organisational issues around aspects of crime prevention, crime detection and policing – with a view to the role of information and communication technologies in these contexts.
The 15th International Workshop on Conceptual Structures ICCS 2007 brings together numerous discussions between international groups of researchers from the field of Information and Communications Technology (ICT). At ICCS 2007 some of the world’s best minds in information technology, arts, humanities and social science met to explore novel ways that ICT can augment human intelligence. The workshops include, Rough sets and data mining, and ubiquitous and collaborative computing.
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