Cost modelling for cloud computing utilisation in long term digital preservation

The rapid increase in volume of digital information can cause concern among organisations regarding manageability, costs and security of their information in the long-term. As cloud computing technology is often used for digital preservation purposes and is still evolving, there is difficulty in determining its long-term costs. This paper presents the development of a generic cost model for public and private clouds utilisation in long term digital preservation (LTDP), considering the impact of uncertainties and obsolescence issues. The cost model consists of rules and assumptions and was built using a combination of activity based and parametric cost estimation techniques. After generation of cost breakdown structures for both clouds, uncertainties and obsolescence were categorised. To quantify impacts of uncertainties on cost, three-point estimate technique was employed and Monte Carlo simulation was applied to generate the probability distribution on each cost driver. A decision support cost estimation tool with dashboard representation of results was developed

A formal verification framework and associated tools for enterprise modeling : application to UEML

The aim of this paper is to propose and apply a verification and validation approach to Enterprise Modeling that enables the user to improve the relevance and correctness, the suitability and coherence of a model by using properties specification and formal proof of properties

Enterprise model verification and validation : an approach

This article presents a verification and validation approach which is used here in order to complete the classical tool box the industrial user may utilize in enterprise modeling and integration domain. This approach, which has been defined independently from any application domain is based on several formal concepts and tools presented in this paper. These concepts are property concepts, property reference matrix, properties graphs, enterprise modeling domain ontology, conceptual graphs and formal reasoning mechanisms

The role of learning on industrial simulation design and analysis

The capability of modeling real-world system operations has turned simulation into an indispensable problemsolving methodology for business system design and analysis. Today, simulation supports decisions ranging from sourcing to operations to finance, starting at the strategic level and proceeding towards tactical and operational levels of decision-making. In such a dynamic setting, the practice of simulation goes beyond being a static problem-solving exercise and requires integration with learning. This article discusses the role of learning in simulation design and analysis motivated by the needs of industrial problems and describes how selected tools of statistical learning can be utilized for this purpose

Aerated blast furnace slag filters for enhanced nitrogen and phosphorus removal from small wastewater treatment plants

Rock filters (RF) are a promising alternative technology for natural wastewater treatment for upgrading WSP effluent. However, the application of RF in the removal of eutrophic nutrients, nitrogen and phosphorus, is very limited. Accordingly, the overall objective of this study was to develop a lowcost RF system for the purpose of enhanced nutrient removal from WSP effluents, which would be able to produce effluents which comply with the requirements of the EU Urban Waste Water Treatment Directive (UWWTD) (911271lEEC) and suitable for small communities. Therefore, a combination system comprising a primary facultative pond and an aerated rock filter (ARF) system-either vertically or horizontally loaded-was investigated at the University of Leeds' experimental station at Esholt Wastewater Treatment Works, Bradford, UK. Blast furnace slag (BFS) and limestone were selected for use in the ARF system owing to their high potential for P removal and their low cost. This study involved three major qperiments: (1) a comparison of aerated vertical-flow and horizontal-flow limestone filters for nitrogen removal; (2) a comparison of aerated limestone + blast furnace slag (BFS) filter and aerated BFS filters for nitrogen and phosphorus removal; and (3) a comparison of vertical-flow and horizontal-flow BFS filters for nitrogen and phosphorus removal. The vertical upward-flow ARF system was found to be superior to the horizontal-flow ARF system in terms of nitrogen removal, mostly thiough bacterial nitrification processes in both the aerated limestone and BFS filter studies. The BFS filter medium (whieh is low-cost) showed a much higher potential in removing phosphortls from pond effluent than the limestone medium. As a result, the combination of a vertical upward-flow ARF system and an economical and effective P-removal filter medium, such as BFS, was found to be an ideal optionfor the total nutrient removal of both nitrogen and phosphorus from wastewater. In parallel with these experiments, studies on the aerated BFS filter effective life and major in-filter phosphorus removal pathways were carried out. From the standard batch experiments of Pmax adsorption capacity of BFS, as well as six-month data collection of daily average P-removal, it was found that the effective life of the aerated BFS filter was 6.5 years. Scanning electron microscopy and X-ray diffraction spectrometric analyses on the surface of BFS, particulates and sediment samples revealed that the apparent mechanisms of P-removal in the filter are adsorption on the amorphous oxide phase of the BFS surface and precipitation within the filter