University of Derby

Derby, United Kingdom

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Department of Psychology
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Department of Biological Sciences
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    ABSTRACT: Two studies, which took social categorization and right-wing authoritarianism into account two factors unexamined jointly in previous research, explored reporting of potential terrorist threats in cyberspace in a generally Muslim-intolerant ‘Eastern European’ setting. In Study 1, 92 white men observed a simulated online encounter between an anti-Muslim extremist and two of his apparent followers ‘planning to do something big and violent.’ The results show that participants took less time to respond to the terrorist threat if Muslims were referred to in terms of a broad European identity rather than a narrow national identity, but only when participants were primed with the broad identity. In Study 2, where a separate group of 100 white men observed the same encounter, the focus was put on the mono-cultural and multicultural primes of their national identity. The response time was shorter when participants were primed with the multicultural contents, but only when the Muslim outgroup was described in terms of national rather than European inclusion. Providing theoretical guidelines for facilitating the reporting of potential terrorist threats in cyberspace, this work complements the classical social identity model of helping by revealing new layers of complex interactive categorization and their potential application to mobilizing counter-terrorist community responses.
    Computers in Human Behavior 07/2014; 36:76–81.
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    ABSTRACT: In self-hosted environments it was feared that Business Intelligence (BI) will eventually face a resource crunch situation due to the never ending expansion of data warehouses and the online analytical processing (OLAP) demands on the underlying networking. Cloud computing has instigated a new hope for future prospects of BI. However, how will BI be implemented on Cloud and how will the traffic and demand profile look like? This research attempts to answer these key questions in regards to taking BI to the Cloud. The Cloud hosting of BI has been demonstrated with the help of a simulation on OPNET comprising a Cloud model with multiple OLAP application servers applying parallel query loads on an array of servers hosting relational databases. The simulation results reflected that extensible parallel processing of database servers on the Cloud can efficiently process OLAP application demands on Cloud computing.
    Journal of Computer and System Sciences 01/2014;
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    ABSTRACT: Am I the only one getting fed up with all this talk of safe staffing levels in NHS hospitals (News, Analysis and Letters December 4)?
    Nursing standard: official newspaper of the Royal College of Nursing 12/2013; 28(15):33.


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12/2007: pages 35-50;
Journal of Investigative Psychology and Offender Profiling 01/2011; 8:149-162.

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