Long Term Trends in Resource Exergy Consumption and Useful Work Supplies in the UK, 1900-2000

Our aim is to explain historical economic growth in the UK economy by introducing an empirical measure for useful work derived from natural resource energy inputs into an augmented production function. To do this, we estimate the long-term (1900-2000) trends in resource exergy supply and conversion to useful work in the United Kingdom. The exergy resources considered included domestic consumption of coal, crude oil and petroleum products, natural gas, nuclear and renewable resources (including biomass). All flows of exergy were allocated to an end use such as providing heat, light, transport, human and animal work and electrical power. For each end-use we estimated a time dependent efficiency of conversion from exergy to useful work. The 3-factor production function (of capital, labour and useful work) is able to reproduce the historic trajectory of economic growth without recourse to any exogenous assumptions of technological progress or total factor productivity. The results indicate that useful work derived from natural resource exergy is an important factor of production.exergy, energy, efficiency, economic growth, United Kingdom

Advertising and Word-of-Mouth Effects on Pre-launch Consumer Interest and Initial Sales of Experience Products

This study examines how consumers' interest in a new experience product develops as a result of advertising and word-of-mouth activities during the pre-launch period. The empirical settings are the U.S. motion picture and video game industries. The focal variables include weekly ad spend, blog volume, online search volume during pre-launch periods, opening-week sales, and product characteristics. We treat pre-launch search volume of keywords as a measure of pre-launch consumer interest in the related product. To identify probable persistent effects among the pre-launch time-series variables, we apply a vector autoregressive modeling approach. We find that blog postings have permanent, trend-setting effects on pre-launch consumer interest in a new product, while advertising has only temporary effects. In the U.S. motion picture industry, the four-week cumulative elasticity of pre-launch consumer interest is 0.187 to advertising and 0.635 to blog postings. In the U.S. video game industry, the elasticities are 0.093 and 1.306, respectively. We also find long-run co-evolution between blog and search volume, which suggests that consumers' interest in the upcoming product cannot grow without bounds for a given level of blog volume

A brief network analysis of Artificial Intelligence publication

In this paper, we present an illustration to the history of Artificial Intelligence(AI) with a statistical analysis of publish since 1940. We collected and mined through the IEEE publish data base to analysis the geological and chronological variance of the activeness of research in AI. The connections between different institutes are showed. The result shows that the leading community of AI research are mainly in the USA, China, the Europe and Japan. The key institutes, authors and the research hotspots are revealed. It is found that the research institutes in the fields like Data Mining, Computer Vision, Pattern Recognition and some other fields of Machine Learning are quite consistent, implying a strong interaction between the community of each field. It is also showed that the research of Electronic Engineering and Industrial or Commercial applications are very active in California. Japan is also publishing a lot of papers in robotics. Due to the limitation of data source, the result might be overly influenced by the number of published articles, which is to our best improved by applying network keynode analysis on the research community instead of merely count the number of publish.Comment: 18 pages, 7 figure

Information and intellectual property: The global challenges

The paper analyses the contribution of 'golden papers' - seminal works whose ideas remain as fresh and relevant today as when they were first published decades ago - and which continue to dominate academic discourse among successive generations of scholars. The authors analyse why two works written within an industrial development context: The simple economics of basic scientific research, by Richard Nelson (1959) and Kenneth Arrows Economic Welfare and the Allocation of Resources for Invention (1962), are so relevant in today’s knowledge-driven economic paradigm. Focusing on the papers’ application to current global policy debates on information/knowledge and intellectual property, they argue that while the context has changed the essential nature of innovation - driven by widespread access to the ability to replicate and improve - remains the same. Hence a focus on endogenous innovation policy is as relevant today as it was 50 years ago.knowledge economy, science and technology, innovation, intellectual property rights, institutional change

A 64mW DNN-based Visual Navigation Engine for Autonomous Nano-Drones

Fully-autonomous miniaturized robots (e.g., drones), with artificial intelligence (AI) based visual navigation capabilities are extremely challenging drivers of Internet-of-Things edge intelligence capabilities. Visual navigation based on AI approaches, such as deep neural networks (DNNs) are becoming pervasive for standard-size drones, but are considered out of reach for nanodrones with size of a few cm${}^\mathrm{2}$. In this work, we present the first (to the best of our knowledge) demonstration of a navigation engine for autonomous nano-drones capable of closed-loop end-to-end DNN-based visual navigation. To achieve this goal we developed a complete methodology for parallel execution of complex DNNs directly on-bard of resource-constrained milliwatt-scale nodes. Our system is based on GAP8, a novel parallel ultra-low-power computing platform, and a 27 g commercial, open-source CrazyFlie 2.0 nano-quadrotor. As part of our general methodology we discuss the software mapping techniques that enable the state-of-the-art deep convolutional neural network presented in [1] to be fully executed on-board within a strict 6 fps real-time constraint with no compromise in terms of flight results, while all processing is done with only 64 mW on average. Our navigation engine is flexible and can be used to span a wide performance range: at its peak performance corner it achieves 18 fps while still consuming on average just 3.5% of the power envelope of the deployed nano-aircraft.Comment: 15 pages, 13 figures, 5 tables, 2 listings, accepted for publication in the IEEE Internet of Things Journal (IEEE IOTJ

ReSCon '12, Research Student Conference: Book of Abstracts

The fifth SED Research Student Conference (ReSCon2012) was hosted over three days, 18-20 June 2012, in the Hamilton Centre at Brunel University. The conference consisted of 130 oral and 70 poster presentations, based on the high quality and diverse research being conducted within the School of Engineering and Design by postgraduate research students. The conference is held annually, and ReSCon plays a key role in contributing to research and innovations within the School