949 resultados para Optimisation de formes


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The increase in renewable energy generators introduced into the electricity grid is putting pressure on its stability and management as predictions of renewable energy sources cannot be accurate or fully controlled. This, with the additional pressure of fluctuations in demand, presents a problem more complex than the current methods of controlling electricity distribution were designed for. A global approximate and distributed optimisation method for power allocation that accommodates uncertainties and volatility is suggested and analysed. It is based on a probabilistic method known as message passing [1], which has deep links to statistical physics methodology. This principled method of optimisation is based on local calculations and inherently accommodates uncertainties; it is of modest computational complexity and provides good approximate solutions.We consider uncertainty and fluctuations drawn from a Gaussian distribution and incorporate them into the message-passing algorithm. We see the effect that increasing uncertainty has on the transmission cost and how the placement of volatile nodes within a grid, such as renewable generators or consumers, effects it.

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Floods are one of the most dangerous and common disasters worldwide, and these disasters are closely linked to the geography of the affected area. As a result, several papers in the academic field of humanitarian logistics have incorporated the use of Geographical Information Systems (GIS) for disaster management. However, most of the contributions in the literature are using these systems for network analysis and display, with just a few papers exploiting the capabilities of GIS to improve planning and preparedness. To show the capabilities of GIS for disaster management, this paper uses raster GIS to analyse potential flooding scenarios and provide input to an optimisation model. The combination is applied to two real-world floods in Mexico to evaluate the value of incorporating GIS for disaster planning. The results provide evidence that including GIS analysis for a decision-making tool in disaster management can improve the outcome of disaster operations by reducing the number of facilities used at risk of flooding. Empirical results imply the importance of the integration of advanced remote sensing images and GIS for future systems in humanitarian logistics.

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To explore the views of pharmacy and rheumatology stakeholders about system-related barriers to medicines optimisation activities with young people with long-term conditions. A three-phase consensus-building study comprising (1) focus groups with community and hospital pharmacists; (2) semi-structured telephone interviews with lay and professional adolescent rheumatology stakeholders and pharmacy policymakers, and (3) multidisciplinary discussion groups with community and hospital pharmacists and rheumatology staff. Qualitative verbatim transcripts from phases 1 and 2 were subjected to framework analysis. Themes from phase 1 underpinned a briefing for phase 2 interviewees. Themes from phases 1 and 2 generated elements of good pharmacy practice and current/future pharmacy roles for ranking in phase 3. Results from phase 3 prioritisation and ranking exercises were captured on self-completion data collection forms, entered into an Excel spreadsheet and subjected to descriptive statistical analysis. Institutional ethical approval was given by Aston University Health and Life Sciences Research Ethics Committee. Four focus groups were conducted with 18 pharmacists across England, Scotland and Wales (7 hospital, 10 community and 1 community/public health). Fifteen stakeholders took part in telephone interviews (3 pharmacist commissioners; 2 pharmacist policymakers; 2 pharmacy staff members (1 community and 1 hospital); 4 rheumatologists; 1 specialist nurse, and 3 lay juvenile arthritis advocates). Twenty-five participants took part in three discussion groups in adolescent rheumatology centres across England and Scotland (9 community pharmacists; 4 hospital pharmacists; 6 rheumatologists; 5 specialist nurses, and 1 physiotherapist). In all phases of the study, system-level issues were acknowledged as barriers to more engagement with young people and families. Community pharmacists in the focus groups reported that opportunities for engaging with young people were low if parents collected prescriptions alone, which was agreed by other stakeholders. Moreover, institutional/company prescription collection policies – an activity largely disallowed for a young person under 16 without an accompanying parent - were identified by hospital and community pharmacists as barriers to open discussion and engagement. Few community pharmacists reported using Medicines Use Review (England/Wales) or Chronic Medication Service (Scotland) as a medicines optimisation activity with young people; many were unsure about consent procedures. Despite these limitations, rheumatology stakeholders ranked highly the potential of pharmacists empowering young people with general health care skills, such as repeat prescription ordering. The pharmacy profession lacks vision for its role in the care of young people with long-term conditions. Pharmacists and rheumatology stakeholders identified system-level barriers to more engagement with young people who take medicines regularly. We acknowledge that the modest number of participants may have had a specific interest and thus bias for the topic, but this underscores their frank admission of the challenges. Professional guidance and policy, practice frameworks and institutional/company policies must promote flexibility for pharmacy staff to recognise and empower young people who are able to give consent and take responsibility for medicines activities. This will increase mutual confidence and trust, and foster pharmacy’s role in teaching general health care skills. In this way, pharmacists will be able to build long-term relationships with young people and families.

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We numerically optimise in-span signal power asymmetry in advanced Raman amplification schemes, reaching 3% over 62 km SMF, and evaluate its impact on the performance of systems using mid-link OPC using 7 × 15 16QAM Nyquist-spaced WDM-PDM. © 2015 OSA.

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We numerically optimise in-span signal power asymmetry in different advanced Raman amplification schemes, achieving a 3% asymmetry over 62 km SMF using random DFB Raman laser amplifier. We then evaluate the impact of such asymmetry on the performance of systems using mid-link OPC by simulating transmission of 7 x 15 Gbaud 16QAM Nyquist-spaced WDM-PDM signals. (C) 2015 Optical Society of America

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The multiple-input multiple-output (MIMO) technique can be used to improve the performance of ad hoc networks. Various medium access control (MAC) protocols with multiple contention slots have been proposed to exploit spatial multiplexing for increasing the transport throughput of MIMO ad hoc networks. However, the existence of multiple request-to-send/clear-to-send (RTS/CTS) contention slots represents a severe overhead that limits the improvement on transport throughput achieved by spatial multiplexing. In addition, when the number of contention slots is fixed, the efficiency of RTS/CTS contention is affected by the transmitting power of network nodes. In this study, a joint optimisation scheme on both transmitting power and contention slots number for maximising the transport throughput is presented. This includes the establishment of an analytical model of a simplified MAC protocol with multiple contention slots, the derivation of transport throughput as a function of both transmitting power and the number of contention slots, and the optimisation process based on the transport throughput formula derived. The analytical results obtained, verified by simulation, show that much higher transport throughput can be achieved using the joint optimisation scheme proposed, compared with the non-optimised cases and the results previously reported.

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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.

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Phospholipid oxidation by adventitious damage generates a wide variety of products with potentially novel biological activities that can modulate inflammatory processes associated with various diseases. To understand the biological importance of oxidised phospholipids (OxPL) and their potential role as disease biomarkers requires precise information about the abundance of these compounds in cells and tissues. There are many chemiluminescence and spectrophotometric assays available for detecting oxidised phospholipids, but they all have some limitations. Mass spectrometry coupled with liquid chromatography is a powerful and sensitive approach that can provide detailed information about the oxidative lipidome, but challenges still remain. The aim of this work is to develop improved methods for detection of OxPLs by optimisation of chromatographic separation through testing several reverse phase columns and solvent systems, and using targeted mass spectrometry approaches. Initial experiments were carried out using oxidation products generated in vitro to optimise the chromatography separation parameters and mass spectrometry parameters. We have evaluated the chromatographic separation of oxidised phosphatidylcholines (OxPCs) and oxidised phosphatidylethanolamines (OXPEs) using C8, C18 and C30 reverse phase, polystyrene – divinylbenzene based monolithic and mixed – mode hydrophilic interaction (HILIC) columns, interfaced with mass spectrometry. Our results suggest that the monolithic column was best able to separate short chain OxPCs and OxPEs from long chain oxidised and native PCs and PEs. However, variation in charge of polar head groups and extreme diversity of oxidised species make analysis of several classes of OxPLs within one analytical run impractical. We evaluated and optimised the chromatographic separation of OxPLs by serially coupling two columns: HILIC and monolith column that provided us the larger coverage of OxPL species in a single analytical run.

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From 1992 to 2012 4.4 billion people were affected by disasters with almost 2 trillion USD in damages and 1.3 million people killed worldwide. The increasing threat of disasters stresses the need to provide solutions for the challenges faced by disaster managers, such as the logistical deployment of resources required to provide relief to victims. The location of emergency facilities, stock prepositioning, evacuation, inventory management, resource allocation, and relief distribution have been identified to directly impact the relief provided to victims during the disaster. Managing appropriately these factors is critical to reduce suffering. Disaster management commonly attracts several organisations working alongside each other and sharing resources to cope with the emergency. Coordinating these agencies is a complex task but there is little research considering multiple organisations, and none actually optimising the number of actors required to avoid shortages and convergence. The aim of the this research is to develop a system for disaster management based on a combination of optimisation techniques and geographical information systems (GIS) to aid multi-organisational decision-making. An integrated decision system was created comprising a cartographic model implemented in GIS to discard floodable facilities, combined with two models focused on optimising the decisions regarding location of emergency facilities, stock prepositioning, the allocation of resources and relief distribution, along with the number of actors required to perform these activities. Three in-depth case studies in Mexico were studied gathering information from different organisations. The cartographic model proved to reduce the risk to select unsuitable facilities. The preparedness and response models showed the capacity to optimise the decisions and the number of organisations required for logistical activities, pointing towards an excess of actors involved in all cases. The system as a whole demonstrated its capacity to provide integrated support for disaster preparedness and response, along with the existence of room for improvement for Mexican organisations in flood management.

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Water-alternating-gas (WAG) is an enhanced oil recovery method combining the improved macroscopic sweep of water flooding with the improved microscopic displacement of gas injection. The optimal design of the WAG parameters is usually based on numerical reservoir simulation via trial and error, limited by the reservoir engineer’s availability. Employing optimisation techniques can guide the simulation runs and reduce the number of function evaluations. In this study, robust evolutionary algorithms are utilized to optimise hydrocarbon WAG performance in the E-segment of the Norne field. The first objective function is selected to be the net present value (NPV) and two global semi-random search strategies, a genetic algorithm (GA) and particle swarm optimisation (PSO) are tested on different case studies with different numbers of controlling variables which are sampled from the set of water and gas injection rates, bottom-hole pressures of the oil production wells, cycle ratio, cycle time, the composition of the injected hydrocarbon gas (miscible/immiscible WAG) and the total WAG period. In progressive experiments, the number of decision-making variables is increased, increasing the problem complexity while potentially improving the efficacy of the WAG process. The second objective function is selected to be the incremental recovery factor (IRF) within a fixed total WAG simulation time and it is optimised using the same optimisation algorithms. The results from the two optimisation techniques are analyzed and their performance, convergence speed and the quality of the optimal solutions found by the algorithms in multiple trials are compared for each experiment. The distinctions between the optimal WAG parameters resulting from NPV and oil recovery optimisation are also examined. This is the first known work optimising over this complete set of WAG variables. The first use of PSO to optimise a WAG project at the field scale is also illustrated. Compared to the reference cases, the best overall values of the objective functions found by GA and PSO were 13.8% and 14.2% higher, respectively, if NPV is optimised over all the above variables, and 14.2% and 16.2% higher, respectively, if IRF is optimised.

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Peer reviewed

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Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

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Mémoire numérisé par la Direction des bibliothèques de l'Université de Montréal.