Anderson v London Fire and Emergency Service 2012

Case law report - online

Optimizing search engines results using linear programming

When a query is passed to multiple search engines, each search engine returns a ranked list of documents. Researchers have demonstrated that combining results, in the form of a "metasearch engine", produces a significant improvement in coverage and search effectiveness. This paper proposes a linear programming mathematical model for optimizing the ranked list result of a given group of Web search engines for an issued query. An application with a numerical illustration shows the advantages of the proposed method. © 2011 Elsevier Ltd. All rights reserved.

The effectiveness of an organisations' equal opportunities policy for the role and training of women, particularly in the fire service

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Engines for combined heat and power

Spark-ignited (SI) gas engines are for the use of fuel gas only and are limited to the flammable range of the gas; this means the range of a concentration of a gas or vapor that will burn after ignition. Fuel gas like syngas from gasification or biogas must meet high quality and chemical purity standards for combustion in SI gas engines. Considerable effort has been devoted to fast pyrolysis over the years and some of the product oils have been tested in diesel or dual-fuel engines since 1993. For biogas conversion, usually dual-fuel engines are used, while for synthesis gas the use of gas engines is more common. The trials using wood derived pyrolysis oil from fast pyrolysis have not yet been a success story and these approaches have usually failed due to the high corrosivity of the pyrolysis oils.

The effect of a curing agent on the thermal degradation of fire retardant brominated epoxy resins

The diglycidyl ether of tetrabromobisphenol A, the diglycidyl ether of bisphenol A and their mixture was cured by 4,4'-diaminodiphenyl methane. The pyrolysis of the obtained epoxy resins was studied by TG, DSC, TG/FTIR as well as FTIR characterization of pyrolysis residues. The gaseous and high boiling pyrolysis products were collected, characterized by GC/MS and their formation is discussed. The brominated epoxy resins are thermally less stable than the non-brominated ones. This effect is caused by the amine-containing hardener. The degradation initiation reaction is associated with the formation of hydrogen bromide which further destabilizes the epoxy network. The effect of the curing agent can be used in recycling of epoxy resins to separate brominated pyrolysis products from non-brominated ones.

Review of low-temperature vapour power cycle engines with quasi-isothermal expansion

External combustion heat cycle engines convert thermal energy into useful work. Thermal energy resources include solar, geothermal, bioenergy, and waste heat. To harness these and maximize work output, there has been a renaissance of interest in the investigation of vapour power cycles for quasi-isothermal (near constant temperature) instead of adiabatic expansion. Quasi-isothermal expansion has the advantage of bringing the cycle efficiency closer to the ideal Carnot efficiency, but it requires heat to be transferred to the working fluid as it expands. This paper reviews various low-temperature vapour power cycle heat engines with quasi-isothermal expansion, including the methods employed to realize the heat transfer. The heat engines take the form of the Rankine cycle with continuous heat addition during the expansion process, or the Stirling cycle with a condensable vapour as working fluid. Compared to more standard Stirling engines using gas, the specific work output is higher. Cryogenic heat engines based on the Rankine cycle have also been enhanced with quasi-isothermal expansion. Liquid flooded expansion and expander surface heating are the two main heat transfer methods employed. Liquid flooded expansion has been applied mainly in rotary expanders, including scroll turbines; whereas surface heating has been applied mainly in reciprocating expanders. © 2014 Elsevier Ltd.

Benchmarking of distributed computing engines spark and GraphLab for big data analytics

In this paper we evaluate and compare two representativeand popular distributed processing engines for large scalebig data analytics, Spark and graph based engine GraphLab. Wedesign a benchmark suite including representative algorithmsand datasets to compare the performances of the computingengines, from performance aspects of running time, memory andCPU usage, network and I/O overhead. The benchmark suite istested on both local computer cluster and virtual machines oncloud. By varying the number of computers and memory weexamine the scalability of the computing engines with increasingcomputing resources (such as CPU and memory). We also runcross-evaluation of generic and graph based analytic algorithmsover graph processing and generic platforms to identify thepotential performance degradation if only one processing engineis available. It is observed that both computing engines showgood scalability with increase of computing resources. WhileGraphLab largely outperforms Spark for graph algorithms, ithas close running time performance as Spark for non-graphalgorithms. Additionally the running time with Spark for graphalgorithms over cloud virtual machines is observed to increaseby almost 100% compared to over local computer clusters.