Integrated assessment of bioelectricity technology options

Power generation from biomass is a sustainable energy technology which can contribute to substantial reductions in greenhouse gas emissions, but with greater potential for environmental, economic and social impacts than most other renewable energy technologies. It is important therefore in assessing bioenergy systems to take account of not only technical, but also environmental, economic and social parameters on a common basis. This work addresses the challenge of analysing, quantifying and comparing these factors for bioenergy power generation systems. A life-cycle approach is used to analyse the technical, environmental, economic and social impacts of entire bioelectricity systems, with a number of life-cycle indicators as outputs to facilitate cross-comparison. The results show that similar greenhouse gas savings are achieved with the wide variety of technologies and scales studied, but land-use efficiency of greenhouse gas savings and specific airborne emissions varied substantially. Also, while specific investment costs and electricity costs vary substantially from one system to another the number of jobs created per unit of electricity delivered remains roughly constant. Recorded views of stakeholders illustrate that diverging priorities exist for different stakeholder groups and this will influence appropriate choice of bioenergy systems for different applications.

Techno-economic assessment and uncertainty analysis of thermochemical processes for second generation biofuels

Biomass-To-Liquid (BTL) is one of the most promising low carbon processes available to support the expanding transportation sector. This multi-step process produces hydrocarbon fuels from biomass, the so-called “second generation biofuels” that, unlike first generation biofuels, have the ability to make use of a wider range of biomass feedstock than just plant oils and sugar/starch components. A BTL process based on gasification has yet to be commercialized. This work focuses on the techno-economic feasibility of nine BTL plants. The scope was limited to hydrocarbon products as these can be readily incorporated and integrated into conventional markets and supply chains. The evaluated BTL systems were based on pressurised oxygen gasification of wood biomass or bio-oil and they were characterised by different fuel synthesis processes including: Fischer-Tropsch synthesis, the Methanol to Gasoline (MTG) process and the Topsoe Integrated Gasoline (TIGAS) synthesis. This was the first time that these three fuel synthesis technologies were compared in a single, consistent evaluation. The selected process concepts were modelled using the process simulation software IPSEpro to determine mass balances, energy balances and product distributions. For each BTL concept, a cost model was developed in MS Excel to estimate capital, operating and production costs. An uncertainty analysis based on the Monte Carlo statistical method, was also carried out to examine how the uncertainty in the input parameters of the cost model could affect the output (i.e. production cost) of the model. This was the first time that an uncertainty analysis was included in a published techno-economic assessment study of BTL systems. It was found that bio-oil gasification cannot currently compete with solid biomass gasification due to the lower efficiencies and higher costs associated with the additional thermal conversion step of fast pyrolysis. Fischer-Tropsch synthesis was the most promising fuel synthesis technology for commercial production of liquid hydrocarbon fuels since it achieved higher efficiencies and lower costs than TIGAS and MTG. None of the BTL systems were competitive with conventional fossil fuel plants. However, if government tax take was reduced by approximately 33% or a subsidy of £55/t dry biomass was available, transport biofuels could be competitive with conventional fuels. Large scale biofuel production may be possible in the long term through subsidies, fuels price rises and legislation.

Fuzzy assessment of performance of a decision making units using DEA:a non-radical approach

Data Envelopment Analysis (DEA) is recognized as a modern approach to the assessment of performance of a set of homogeneous Decision Making Units (DMUs) that use similar sources to produce similar outputs. While DEA commonly is used with precise data, recently several approaches are introduced for evaluating DMUs with uncertain data. In the existing approaches many information on uncertainties are lost. For example in the defuzzification, the a-level and fuzzy ranking approaches are not considered. In the tolerance approach the inequality or equality signs are fuzzified but the fuzzy coefficients (inputs and outputs) are not treated directly. The purpose of this paper is to develop a new model to evaluate DMUs under uncertainty using Fuzzy DEA and to include a-level to the model under fuzzy environment. An example is given to illustrate this method in details.

Can computer-based testing achieve quality and efficiency in assessment?

This paper reports findings of a two year study concerning the development and implementation of a general-purpose computer-based assessment (CBA) system at a UK University. Data gathering took place over a period of nineteen months, involving a number of formative and summative assessments. Approximately 1,000 students, drawn from undergraduate courses, were involved in the exercise. The techniques used in gathering data included questionnaires, observation, interviews and an analysis of student scores in both conventional examinations and computer-based assessments. Comparisons with conventional assessment methods suggest that the use of CBA techniques may improve the overall performance of students. However it is clear that the technique must not be seen as a "quick fix" for problems such as rising student numbers. If one accepts that current systems test only a relatively narrow range of skills, then the hasty implementation of CBA systems will result in a distorted and inaccurate view of student performance. In turn, this may serve to reduce the overall quality of courses and - ultimately - detract from the student learning experience. On the other hand, if one adopts a considered and methodical approach to computer-based assessment, positive benefits might include increased efficiency and quality, leading to improved student learning.

Designing multiple user perspectives and functionality for clinical decision support systems

Clinical Decision Support Systems (CDSSs) need to disseminate expertise in formats that suit different end users and with functionality tuned to the context of assessment. This paper reports research into a method for designing and implementing knowledge structures that facilitate the required flexibility. A psychological model of expertise is represented using a series of formally specified and linked XML trees that capture increasing elements of the model, starting with hierarchical structuring, incorporating reasoning with uncertainty, and ending with delivering the final CDSS. The method was applied to the Galatean Risk and Safety Tool, GRiST, which is a web-based clinical decision support system (www.egrist.org) for assessing mental-health risks. Results of its clinical implementation demonstrate that the method can produce a system that is able to deliver expertise targetted and formatted for specific patient groups, different clinical disciplines, and alternative assessment settings. The approach may be useful for developing other real-world systems using human expertise and is currently being applied to a logistics domain. © 2013 Polish Information Processing Society.

Linking comprehensive performance assessment to the balanced scorecard:evidence from Hertfordshire County Council

Over the course of the last twenty years there has been a growing academic interest in performance management, particularly in respect of the evolution of new techniques and their resulting impact. One important theoretical development has been the emergence of multidimensional performance measurement models that are potentially applicable within the public sector. Empirically, academic researchers are increasingly supporting the use of such models as a way of improving public sector management and the effectiveness of service provision (Mayston, 1985; Pollitt, 1986; Bates and Brignall, 1993; and Massey, 1999). This paper seeks to add to the literature by using both theoretical and empirical evidence to argue that CPA, the external inspection tool used by the Audit Commission to evaluate local authority performance management, is a version of the Balanced Scorecard which, when adapted for internal use, may have beneficial effects. After demonstrating the parallels between the CPA framework and Kaplan and Norton's public sector Balanced Scorecard (BSC), we use a case study of the BSC based performance management system in Hertfordshire County Council to demonstrate the empirical linkages between a local scorecard and CPA. We conclude that CPA is based upon the BSC and has the potential to serve as a springboard for the evolution of local authority performance management systems.

Model and performance of a no-reference quality assessment metric for video streaming

Video streaming via Transmission Control Protocol (TCP) networks has become a popular and highly demanded service, but its quality assessment in both objective and subjective terms has not been properly addressed. In this paper, based on statistical analysis a full analytic model of a no-reference objective metric, namely pause intensity (PI), for video quality assessment is presented. The model characterizes the video playout buffer behavior in connection with the network performance (throughput) and the video playout rate. This allows for instant quality measurement and control without requiring a reference video. PI specifically addresses the need for assessing the quality issue in terms of the continuity in the playout of TCP streaming videos, which cannot be properly measured by other objective metrics such as peak signal-to-noise-ratio, structural similarity, and buffer underrun or pause frequency. The performance of the analytical model is rigidly verified by simulation results and subjective tests using a range of video clips. It is demonstrated that PI is closely correlated with viewers' opinion scores regardless of the vastly different composition of individual elements, such as pause duration and pause frequency which jointly constitute this new quality metric. It is also shown that the correlation performance of PI is consistent and content independent. © 2013 IEEE.

A new scheduling method for enhanced quality of experience in LTE systems

In this paper a new approach to the resource allocation and scheduling mechanism that reflects the effect of user's Quality of Experience is presented. The proposed scheduling algorithm is examined in the context of 3GPP Long Term Evolution (LTE) system. Pause Intensity (PI) as an objective and no-reference quality assessment metric is employed to represent user's satisfaction in the scheduler of eNodeB. PI is in fact a measurement of discontinuity in the service. The performance of the scheduling method proposed is compared with two extreme cases: maxCI and Round Robin scheduling schemes which correspond to the efficiency and fairness oriented mechanisms, respectively. Our work reveals that the proposed method is able to perform between fairness and efficiency requirements, in favor of higher satisfaction for the users to the desired level. © VDE VERLAG GMBH.

Perceptions and experiences of the implementation, management, use and optimisation of electronic prescribing systems in hospital settings:protocol for a systematic review of qualitative studies

Introduction: There is increasing evidence that electronic prescribing (ePrescribing) or computerised provider/physician order entry (CPOE) systems can improve the quality and safety of healthcare services. However, it has also become clear that their implementation is not straightforward and may create unintended or undesired consequences once in use. In this context, qualitative approaches have been particularly useful and their interpretative synthesis could make an important and timely contribution to the field. This review will aim to identify, appraise and synthesise qualitative studies on ePrescribing/CPOE in hospital settings, with or without clinical decision support. Methods and analysis: Data sources will include the following bibliographic databases: MEDLINE, MEDLINE In Process, EMBASE, PsycINFO, Social Policy and Practice via Ovid, CINAHL via EBSCO, The Cochrane Library (CDSR, DARE and CENTRAL databases), Nursing and Allied Health Sources, Applied Social Sciences Index and Abstracts via ProQuest and SCOPUS. In addition, other sources will be searched for ongoing studies (ClinicalTrials.gov) and grey literature: Healthcare Management Information Consortium, Conference Proceedings Citation Index (Web of Science) and Sociological abstracts. Studies will be independently screened for eligibility by 2 reviewers. Qualitative studies, either standalone or in the context of mixed-methods designs, reporting the perspectives of any actors involved in the implementation, management and use of ePrescribing/CPOE systems in hospital-based care settings will be included. Data extraction will be conducted by 2 reviewers using a piloted form. Quality appraisal will be based on criteria from the Critical Appraisal Skills Programme checklist and Standards for Reporting Qualitative Research. Studies will not be excluded based on quality assessment. A postsynthesis sensitivity analysis will be undertaken. Data analysis will follow the thematic synthesis method. Ethics and dissemination: The study does not require ethical approval as primary data will not be collected. The results of the study will be published in a peer-reviewed journal and presented at relevant conferences.