Edinburgh Napier University

About: Edinburgh Napier University is a education organization based out in Edinburgh, United Kingdom. It is known for research contribution in the topics: Population & Health care. The organization has 2665 authors who have published 6859 publications receiving 175272 citations.

Energy supply, its demand and security issues for developed and emerging economies

Abstract: Energy is inevitable for human life and a secure and accessible supply of energy is crucial for the sustainability of modern societies. Continuation of the use of fossil fuels is set to face multiple challenges: depletion of fossil fuel reserves, global warming and other environmental concerns, geopolitical and military conflicts and of late, continued and significant fuel price rise. These problems indicate an unsustainable situation. Renewable energy is the solution to the growing energy challenges. Renewable energy resources such as solar, wind, biomass, and wave and tidal energy, are abundant, inexhaustible and environmentally friendly. This article provides an overview of the current and projected energy scene. Five countries, that presently have a significant impact on global energy situation, have been studied in this work. These include China, India, Russia, UK and USA. Together the present energy budget of these countries is roughly half that of the globe. Four of the above five countries that are discussed in this work—China, India, UK and USA are all net importers of energy and are heavily dependent on imports of fuel to sustain their energy demands. Their respective local oil reserves will only last 9, 6, 7 and 4 years, respectively. China, the emerging economy in the world, is however making exemplary development in renewable energy—in 2004 renewable energy in China grew by 25% against 7–9% growth in electricity demand. While in the same year, wind energy in China saw a growth of 35%. China is also leading the global solar thermal market as it has already installed solar collectors over 65 million square meters, accounting for more than 40% of the world's total collector area. This article quantifies the period of exhaustion of the current major energy sources, i.e. coal, oil, gas and nuclear fissile material. Projected demand for energy is also presented and a feasibility of switch over to renewable energy is discussed. The article also presents the size of respective wind- and solar farms that would be required for each of the five countries under discussion to meet their year 2020 energy demands. It has been found that to meet 50% of the total energy demands the proposed area for collection of solar and wind energy by means of ultra-large scale farms in fact will occupy a mere fraction of the available land and near-offshore area for the respective countries, e.g. a solar PV electricity farm of 61 km 2 for China represents 0.005% of the Gobi desert. Likewise, the 26 and 36 km 2 PV farm area, respectively, required for India and the US represents 0.01% and 0.014% land area of Rajasthan and Baja deserts. The above areas required for the farms may be further split to form a cluster of smaller energy farms.

The Concept of Employability

Abstract: The concept of 'employability' plays a crucial role in informing labour market policy in the UK, the EU and beyond. This paper analyses current and previous applications of the term and discusses its value as an exploratory concept and a framework for policy analysis. It then traces the development of the concept, discusses its role in current labour market and training strategies (with particular reference to the UK) and seeks to identify an approach to defining employability that can better inform labour market policy, by transcending explanations of employment and unemployment that focus solely on either supply-side or demand-side factors. Although the literature offers a range of definitions of 'employability', many policy-makers have recently used the term as shorthand for 'the individual's employability skills and attributes'. It is argued that this 'narrow' usage can lead to a 'hollowing out' of the concept of employability. The paper concludes by presenting a broad framework for analysing employability built around individual factors, personal circumstances and external factors, which acknowledges the importance of both supply- and demand-side factors.

Unified Language Model Pre-training for Natural Language Understanding and Generation

Abstract: This paper presents a new Unified pre-trained Language Model (UniLM) that can be fine-tuned for both natural language understanding and generation tasks. The model is pre-trained using three types of language modeling tasks: unidirectional, bidirectional, and sequence-to-sequence prediction. The unified modeling is achieved by employing a shared Transformer network and utilizing specific self-attention masks to control what context the prediction conditions on. UniLM compares favorably with BERT on the GLUE benchmark, and the SQuAD 2.0 and CoQA question answering tasks. Moreover, UniLM achieves new state-of-the-art results on five natural language generation datasets, including improving the CNN/DailyMail abstractive summarization ROUGE-L to 40.51 (2.04 absolute improvement), the Gigaword abstractive summarization ROUGE-L to 35.75 (0.86 absolute improvement), the CoQA generative question answering F1 score to 82.5 (37.1 absolute improvement), the SQuAD question generation BLEU-4 to 22.12 (3.75 absolute improvement), and the DSTC7 document-grounded dialog response generation NIST-4 to 2.67 (human performance is 2.65). The code and pre-trained models are available at https://github.com/microsoft/unilm.

Cartesian Genetic Programming

Abstract: This paper presents a new form of Genetic Programming called Cartesian Genetic Programming in which a program is represented as an indexed graph. The graph is encoded in the form of a linear string of integers. The inputs or terminal set and node outputs are numbered sequentially. The node functions are also separately numbered. The genotype is just a list of node connections and functions. The genotype is then mapped to an indexed graph that can be executed as a program. Evolutionary algorithms are used to evolve the genotype in a symbolic regression problem (sixth order polynomial) and the Santa Fe Ant Trail. The computational effort is calculated for both cases. It is suggested that hit effort is a more reliable measure of computational efficiency. A neutral search strategy that allows the fittest genotype to be replaced by another equally fit genotype (a neutral genotype) is examined and compared with non-neutral search for the Santa Fe ant problem. The neutral search proves to be much more effective.