Suchergebnisse

A long-term ambition of researchers is to develop readily available expert systems to support decision makers. There is great interest in combining web-based information and Machine Learning techniques, which are enjoying a renaissance attributed to the ready availability of computing resources, to answer real-world strategic questions. Given the contribution of industry to overall national economic health, one such question is what industry mix is necessary to support national strategy? The proposed conceptual graph model and accompanying framework, applied the strengths of machines and computational techniques to inform national industrial policy in a data-driven paradigm. This thesis makes three contributions: the development of a novel conceptual graph model and associated framework, both based on a multi-disciplinary literature review, and their subsequent demonstration using both simulated binary and real-world statistical data. The graph model, drawing from experience in the government defence sector, linked national intent to industry via intermediate nodes such as capability. The wider framework combined supervised Bayesian Belief Network Machine Learning with web-scraping via the graph model to infer national intent. Proof of concept was achieved through the use of both simulated and real-world data, confirming the ability of the chosen inference approach to learn the required relations. Ultimately the framework was able to identify industry variables which best explain observed capability for two real-world case studies although it failed to draw inferences across industries using real data. Further avenues of investigation were addressed, including the use of unstructured text as a data source and alternative Machine Learning methods to account for time-series data. The potential of the web as a data source is truly staggering. This thesis goes some way to bridging the gap between this vast store of information and its incorporation in an evidence-driven pipeline in support of strategic decision making. ; Open Access

Access to space technology has changed dramatically in the past 10 years. Traditionally, access to space capabilities required dedicated receivers and significant investment. With the advent of new information technologies that incorporate and disseminate the benefits of space directly to users, access to space technology is no longer so exclusive. As the seamless delivery of space capabilities, from navigation and position to data flows, makes it difficult to distinguish space capabilities from other information infrastructures, legal structures developed to govern space technologies are being forced into contact with a variety of other legal structures. Legal questions abound as new markets, innovative technologies, and increased data access emerge, and the lex specialis of space accommodates these trends. This book investigates how traditional space law is developing as space technology enters the daily lives of individuals everywhere