Experiences and issues for environmental engineering sensor network deployments

Sensor network research is a large and growing area of academic effort, examining technological and deployment issues in the area of environmental monitoring. These technologies are used by environmental engineers and scientists to monitor a multiplicity of environments and services, and, specific to this paper, energy and water supplied to the built environment. Although the technology is developed by Computer Science specialists, the use and deployment is traditionally performed by environmental engineers. This paper examines deployment from the perspectives of environmental engineers and scientists and asks what computer scientists can do to improve the process. The paper uses a case study to demonstrate the agile operation of WSNs within the Cloud Computing infrastructure, and thus the demand-driven, collaboration-intense paradigm of Digital Ecosystems in Complex Environments

Experiences and issues for environmental science sensor network deployments

Sensor network research is a large and growing area of academic effort, examining technological and deployment issues in the area of environmental monitoring. These technologies are used by environmental engineers and scientists to monitor a multiplicity of environments and services, and, specific to this paper, energy and water supplied to the built environment. Although the technology is developed by Computer Science specialists, the use and deployment is traditionally performed by environmental engineers. This paper examines deployment from the perspectives of environmental engineers and scientists and asks what computer scientists can do to improve the process. The paper uses a case study to demonstrate the agile operation of WSNs within the Cloud Computing infrastructure, and thus the demand-driven, collaboration-intense paradigm of Digital Ecosystems in Complex Environments

Applications of lean thinking: a briefing document

This report has been put together by the Health and Care Infrastructure Research and Innovation Centre (HaCIRIC) at the University of Salford for the Department of Health. The need for the report grew out of two main simple questions, o Is Lean applicable in sectors other than manufacturing? o Can the service delivery sector learn from the success of lean in manufacturing and realise the benefits of its implementation?The aim of the report is to list together examples of lean thinking as it is evidenced in the public and private service sector. Following a review of various sources a catalogue of evidence is put together in an organised manner which demonstrates that Lean principles and techniques, when applied rigorously and throughout an entire organization/unit, they can have a positive impact on productivity, cost, quality, and timely delivery of services

Moving Cooler: An Analysis of Transportation Strategies for Reducing Greenhouse Gas Emissions

Summarizes estimates of the costs and impact on greenhouse gas emissions of transportation strategies that raise fuel efficiency, lower fuel carbon content, reduce vehicle travel, and improve the transportation network and of combinations of strategies

Newton Rigg College: report from the Inspectorate (FEFC inspection report; 22/94 and 97/98)

The Further Education Funding Council has a legal duty to make sure further education in England is properly assessed. The FEFC’s inspectorate inspects and reports on each college of further education according to a four-year cycle. This record comprises the reports for periods 1993-94 and 1997-98

Learning Curves For Energy Technology: A Critical Assessment

In this paper, which forms a chapter in the forthcoming Book “Delivering a Low Carbon Electricity System: Technologies, Economics and Policy”, Jamasb and Kohler revisit the literature on learning curves and their application to energy technology and climate change policy analysis and modeling. The academic literature and policy documents have in recent years embraced the learning curves and applied the concept to technology analysis and forecasting cost reductions. We argue that learning curves have often been used or assumed uncritically in technology analysis and draw parallels between the use of learning rates in energy technological progress and climate change modeling to that of discount rates in social cost benefit analysis. The paper discusses that care needs to be taken in applying learning curves, originally developed as an empirical tool to assess the effect of learning by doing in manufacturing, to analysis innovation and technical change. Finally, we suggest some potential extensions of learning curves, e.g. by incorporating R&D and diffusion effects into learning models, and other areas where learning curves may potentially be a useful tool in energy technology policy and analysis

Scaling-up Early Learning in Ethiopia: Exploring the Potential of O-Class

SDG Target 4.2 identifies ‘pre-primary education’ as a strategy to strengthen school readiness and contribute to the quality and outcomes of education, which is supported by the powerful evidence from evaluation research. The challenge faced by many countries is to deliver the proven potential of well-planned, quality programmes to scale. This working paper summarises Ethiopia’s growing commitment to pre-primary education and reports recent Young Lives engagement with the Ministry of Education in Ethiopia and other partners to support scale-up. Ethiopia’s most recent ambitious targets for early learning have been set out in the Fifth Education Sector Development Programme (ESDP V 2015), with pre-primary classes (known as O-Class) within primary schools being seen as the most rapid route to scale-up. The paper reports on the progress and the challenges in delivering ambitious targets. We report key findings from exploratory fieldwork on two key themes, namely the response of Regional Education Bureaus in planning, financing, management and ensuring human capacity for scale-up; and the potential of Ethiopia’s Colleges of Teacher Education to supply sufficient trained teachers to work with young children, especially in the rapidly expanding O- Classes. The final section draws on parallel experiences of other countries, notably Grade R in South Africa, and reports on six key challenges for scale-up; equity; age-appropriateness; cross- sectoral coordination; capacity building; and research and evidence. Other key challenges go beyond the scope of this working paper, notably the models for governance and financing that can deliver quality early education for all. While Ethiopia’s initiative to scale-up O-Class is a welcome indicator of policy commitment to SDG Target 4.2, we conclude that there is a risk that low quality pre-primary programmes will not deliver on the potential of early childhood education and that children (especially poor children) will be the losers