A manifesto for the creative economy

The UK\u27s creative economy is one of its great national strengths, historically deeply rooted and accounting for around one-tenth of the whole economy. It provides jobs for 2.5 million people – more than in financial services, advanced manufacturing or construction – and in recent years, this creative workforce has grown four times faster than the workforce as a whole. But behind this success lies much disruption and business uncertainty, associated with digital technologies. Previously profitable business models have been swept away, young companies from outside the UK have dominated new internet markets, and some UK creative businesses have struggled to compete. UK policymakers too have failed to keep pace with developments in North America and parts of Asia. But it is not too late to refresh tired policies. This manifesto sets out our 10-point plan to bolster one of the UK\u27s fastest growing sectors

Classification of information systems research revisited: A keyword analysis approach

A number of studies have previously been conducted on keyword analysis in order to provide a comprehensive scheme to classify information systems (IS) research. However, these studies appeared prior to 1994, and IS research has clearly developed substantially since then with the emergence of areas such as electronic commerce, electronic government, electronic health and numerous others. Furthermore, the majority of European IS outlets - such as the European Journal of Information Systems and Information Systems Journal - were founded in the early 1990s, and keywords from these journals were not included in any previous work. Given that a number of studies have raised the issue of differences in European and North American IS research topics and approaches, it is arguable that any such analysis must consider sources from both locations to provide a representative and balanced view of IS classification. Moreover, it has also been argued that there is a need for further work in order to create a comprehensive keyword classification scheme reflecting the current state of the art. Consequently, the aim of this paper is to present the results of a keyword analysis utilizing keywords appearing in major peer-reviewed IS publications after the year 1990 through to 2007. This aim is realized by means of the two following objectives: (1) collect all keywords appearing in 24 peer reviewed IS journals after 1990; and (2) identify keywords not included in the previous IS keyword classification scheme. This paper also describes further research required in order to place new keywords in appropriate IS research categories. The paper makes an incremental contribution toward a contemporary means of classifying IS research. This work is important and useful for researchers in understanding the area and evolution of the IS field and also has implications for improving information search and retrieval activities

International Mobility of Engineers and the Rise of Entrepreneurship in the Periphery

entrepreneurship, knowledge economy, start-ups, information technology, venture capital, China, India, USA

FORGE: An eLearning Framework for Remote Laboratory Experimentation on FIRE Testbed Infrastructure

The Forging Online Education through FIRE (FORGE) initiative provides educators and learners in higher education with access to world-class FIRE testbed infrastructure. FORGE supports experimentally driven research in an eLearning environment by complementing traditional classroom and online courses with interactive remote laboratory experiments. The project has achieved its objectives by defining and implementing a framework called FORGEBox. This framework offers the methodology, environment, tools and resources to support the creation of HTML-based online educational material capable accessing virtualized and physical FIRE testbed infrastruc- ture easily. FORGEBox also captures valuable quantitative and qualitative learning analytic information using questionnaires and Learning Analytics that can help optimise and support student learning. To date, FORGE has produced courses covering a wide range of networking and communication domains. These are freely available from FORGEBox.eu and have resulted in over 24,000 experiments undertaken by more than 1,800 students across 10 countries worldwide. This work has shown that the use of remote high- performance testbed facilities for hands-on remote experimentation can have a valuable impact on the learning experience for both educators and learners. Additionally, certain challenges in developing FIRE-based courseware have been identified, which has led to a set of recommendations in order to support the use of FIRE facilities for teaching and learning purposes

Software defined wireless network (sdwn) for industrial environment: case of underground mine

Avec le développement continu des industries minières canadiennes, l’établissement des réseaux de communications souterrains avancés et sans fil est devenu un élément essentiel du processus industriel minier et ceci pour améliorer la productivité et assurer la communication entre les mineurs. Cette étude vise à proposer un système de communication minier en procurant une architecture SDWN (Software Defined Wireless Network) basée sur la technologie de communication LTE. Dans cette étude, les plateformes les plus importantes de réseau mobile 4G ont été étudiées, configurées et testées dans deux zones différentes : un tunnel de mine souterrain et un couloir intérieur étroit. Également, une architecture mobile combinant SDWN et NFV (Network Functions Virtualization) a été réalisée

Assessing and augmenting SCADA cyber security: a survey of techniques

SCADA systems monitor and control critical infrastructures of national importance such as power generation and distribution, water supply, transportation networks, and manufacturing facilities. The pervasiveness, miniaturisations and declining costs of internet connectivity have transformed these systems from strictly isolated to highly interconnected networks. The connectivity provides immense benefits such as reliability, scalability and remote connectivity, but at the same time exposes an otherwise isolated and secure system, to global cyber security threats. This inevitable transformation to highly connected systems thus necessitates effective security safeguards to be in place as any compromise or downtime of SCADA systems can have severe economic, safety and security ramifications. One way to ensure vital asset protection is to adopt a viewpoint similar to an attacker to determine weaknesses and loopholes in defences. Such mind sets help to identify and fix potential breaches before their exploitation. This paper surveys tools and techniques to uncover SCADA system vulnerabilities. A comprehensive review of the selected approaches is provided along with their applicability

Case studies in applying data mining for churn analysis

The advent of price and product comparison sites now makes it even more important to retain customers and identify those that might be at risk of leaving. The use of data mining methods has been widely advocated for predicting customer churn. This paper presents two case studies that utilize decision tree learning methods to develop models for predicting churn for a software company. The first case study aims to predict churn for organizations which currently have an ongoing project, to determine if organizations are likely to continue with other projects. While the second case study presents a more traditional example, where the aim is to predict organizations likely to cease being a subscriber to a service. The case studies include presentation of the accuracy of the models using a standard methodology as well as comparing the results with what happened in practice. Both case studies show the significant savings that can be made, plus potential increase in revenue by using decision tree learning for churn analysis

A taxonomy of software engineering challenges for machine learning systems: An empirical investigation

Artificial intelligence enabled systems have been an inevitable part of everyday life. However, efficient software engineering principles and processes need to be considered and extended when developing AI- enabled systems. The objective of this study is to identify and classify software engineering challenges that are faced by different companies when developing software-intensive systems that incorporate machine learning components. Using case study approach, we explored the development of machine learning systems from six different companies across various domains and identified main software engineering challenges. The challenges are mapped into a proposed taxonomy that depicts the evolution of use of ML components in software-intensive system in industrial settings. Our study provides insights to software engineering community and research to guide discussions and future research into applied machine learning