Case Study Of London Research Articles

A validated methodology for the prediction of heating and cooling energy demand for buildings within the Urban Heat Island: Case-study of London

This paper describes a method for predicting air temperatures within the Urban Heat Island at discreet locations based on input data from one meteorological station for the time the prediction is required and historic measured air temperatures within the city. It uses London as a case-study to describe the method and its applications. The prediction model is based on Artificial Neural Network (ANN) modelling and it is termed the London Site Specific Air Temperature (LSSAT) predictor. The temporal and spatial validity of the model was tested using data measured 8 years later from the original dataset; it was found that site specific hourly air temperature prediction provides acceptable accuracy and improves considerably for average monthly values. It thus is a very reliable tool for use as part of the process of predicting heating and cooling loads for urban buildings. This is illustrated by the computation of Heating Degree Days (HDD) and Cooling Degree Hours (CDH) for a West–East Transect within London. The described method could be used for any city for which historic hourly air temperatures are available for a number of locations; for example air pollution measuring sites, common in many cities, typically measure air temperature on an hourly basis.

Wireless sensor networks for underground railway applications: case studies in Prague and London

There is increasing interest in using structural monitoring as a cost effective way of managing risks once an area of concern has been identified. However, it is challenging to deploy an effective, reliable, large-scale, long-term and real-time monitoring system in an underground railway environment (subway / metro). The use of wireless sensor technology allows for rapid deployment of a monitoring scheme and thus has significant potential benefits as the time available for access is often severely limited. This paper identifies the critical factors that should be considered in the design of a wireless sensor network, including the availability of electrical power and communications networks. Various issues facing underground deployment of wireless sensor networks will also be discussed, in particular for two field case studies involving networks deployed for structural monitoring in the Prague Metro and the London Underground. The paper describes the network design, the radio propagation, the network topology as well as the practical issues involved in deploying a wireless sensor network in these two tunnels.

Nineteenth-Century Bookcloth Grain Classification and the Special Collections Cataloguer

Previous articleNext article No AccessBibliographical NoteNineteenth-Century Bookcloth Grain Classification and the Special Collections CataloguerCarlo DumontetCarlo Dumontet Search for more articles by this author PDFPDF PLUSFull Text Add to favoritesDownload CitationTrack CitationsPermissionsReprints Share onFacebookTwitterLinkedInRedditEmail SectionsMoreDetailsFiguresReferencesCited by The Papers of the Bibliographical Society of America Volume 104, Number 1March 2010 Published for the Bibliographical Society of America Article DOIhttps://doi.org/10.1086/680916 Views: 71Total views on this site Citations: 2Citations are reported from Crossref © 2010 by the Bibliographical Society of America. All rights reserved.PDF download Crossref reports the following articles citing this article:Chris Fripp How I Learned to Stop Worrying and Love the Cloth: The Collection Management and Descriptive Cataloging of Publishers’ Bindings in Research Libraries, Art Documentation: Journal of the Art Libraries Society of North America 40, no.22 (Nov 2021): 221–248.https://doi.org/10.1086/716923KE Attar Modern special collections cataloguing: A University of London case study, Journal of Librarianship and Information Science 45, no.22 (Feb 2012): 168–176.https://doi.org/10.1177/0961000611435255

An integrated tool to assess the role of new planting in PM 10 capture and the human health benefits: A case study in London

The role of vegetation in mitigating the effects of PM 10 pollution has been highlighted as one potential benefit of urban greenspace. An integrated modelling approach is presented which utilises air dispersion (ADMS-Urban) and particulate interception (UFORE) to predict the PM 10 concentrations both before and after greenspace establishment, using a 10 × 10 km area of East London Green Grid (ELGG) as a case study. The corresponding health benefits, in terms of premature mortality and respiratory hospital admissions, as a result of the reduced exposure of the local population are also modelled. PM 10 capture from the scenario comprising 75% grassland, 20% sycamore maple ( Acer pseudoplatanus L.) and 5% Douglas fir ( Pseudotsuga menziesii (Mirb.) Franco) was estimated to be 90.41 t yr −1, equating to 0.009 t ha −1 yr −1 over the whole study area. The human health modelling estimated that 2 deaths and 2 hospital admissions would be averted per year.

A study of travel time prediction using universal kriging

This study describes an approach for predicting travel time by kriging. The kriging method, which is a means of spatial prediction, is used as prediction measure for car travel time in an imaginary four-dimensional space. Each point in the space represents a single journey: the coordinates of a point are the coordinates of the origin and destination on a plane. The travel time can then be viewed as a function over this four-dimensional space. The prediction relies on the feature that nearby points (in the four-dimensional space) will have almost the same travel time. In this approach, it is not necessary to break down travel times from origin to destination into link travel times. The approach will also allow us to use information from “probe vehicles” for travel time prediction in the near future. The feasibility of this approach is demonstrated through a case study in London and its environs. The case study uses 200 observations for verification. The multiple correlation coefficient of estimated travel time and the verification data is 0.9045. The results indicate that 95% prediction limits are between ±10 minutes and ±30 minutes for travel between two arbitrary points. This prediction method is effective for urban districts with links having changeable travel time owing to congestion.

Awareness, acceptability and attitudes towards hydrogen vehicles and filling stations: A Greater Stavanger case study and comparisons with London

This article investigates the determinants of knowledge and acceptability of hydrogen vehicles and filling stations among residents in the Greater Stavanger area on the west coast of Norway and compares the results with the findings from a London case study. The data were collected from 1000 residents and based on the survey developed and used by O'Garra, et al. Int J Hydrogen Energy 2005; 30: 649–659. The results indicate that hydrogen as a fuel for transport is better known in Greater Stavanger and also that the population is clearly more favourable towards the introduction of hydrogen vehicles. Although only just over one third are clearly in favour of the introduction of hydrogen vehicles in London, the number in Greater Stavanger is close to 60%. The key determinants of acceptability discussed are prior knowledge and awareness of hydrogen, sociodemographic background variables and environmental knowledge. In addition, the study also explores the effects of proximity to the filling station. The site for the location of the London filling station was a matter of public controversy and met with resistance from people living close to the filling station. Based on these experiences, the Greater Stavanger sample was divided into two. One sample was drawn from residents living within a 1-km circle of the location of the filling station, and one control sample was drawn from the Greater Stavanger area. Somewhat surprisingly, the support for the introduction of hydrogen vehicles is greater among people living closer to the filling station than in the region as such.

Evaluating critical lines and stations considering the impact of the consequence using transit assignment model ‐case study of London's underground network

AbstractAs the problem of full transit vehicles is encountered daily by passengers in most of the big cities, previous research evaluated the consequence of overcrowding in terms of on‐board crowding and passengers not being able to board with full vehicles. The impact of overcrowding in the real world is, however, not necessarily proportional to these numbers. This paper attempts to specify the critical lines and stations of a network by considering the number of passengers failing to board and attempting to evaluate its impact on service quality and safety risks. The hypothesis is that larger stations with wider platforms can often cope better with overcrowding than smaller stations. Therefore a station size dependent satisfaction function is proposed, which takes values from 0 to 1. The method is applied to London's underground network with a number of scenarios which show critical stations in the network if delays occur.

P2-290: Modernising a mental health service for older people: A case study in London, UK

P2-290: Modernising a mental health service for older people: A case study in London, UK

Learning how to deal with uncertainty of flood risk in long‐term planning

Long‐term planning in the context of Flood Risk Management (FRM) necessarily involves dealing with considerable uncertainties. In the past, there have been general doubts about the usefulness of long‐term plans as guiding frameworks for decision makers. Since the mid‐1990s, there has been a revival of long‐term planning to shape the future of European societies and cities. This revival will last in flood risk management only if the implications of dealing with uncertainty for practitioners can be specified. The paper explores learning as one reason to consider developments in the long run. It draws a distinction between exploiting what is already known and exploring what might come to be known in the future. Based upon theoretical reasoning and findings from case studies in London and Dresden, three recommendations to long‐term planners are derived to handle uncertainty in planning: (1) Balance learning to exploit a certain past and learning to explore uncertain futures, (2) Use forums for learning about uncertainties in long‐term strategies of FRM, and (3) Think of dealing with uncertainty in long‐term FRM as a social process prone to interruption, irrelevance for ongoing decision making, and post‐disaster politics.

Sewer storage tank performance under climate change

This paper describes a study of the potential effects of climate change on the design and performance of sewer storage tanks. A long-term synthetic rainfall time-series has been derived based on the IPPC medium-high emission scenario for a case study in London. Results indicate a 35% increase in the number of storm events that cause filling of the tank and a 57% increase in the average volume of storage required. A method to estimate the required future storage volume for any given return period has been developed and described. Indications are that significantly larger storage volumes will be required to maintain the same level of flood protection.

Multi-objective signal control of urban junctions – Framework and a London case study

This paper presents an approach to multi-objective signal control using fuzzy logic. The signal control uses fuzzy logic where the membership functions are optimised according to the Bellman–Zadeh principle of fuzzy decision-making. This approach is both practical for the decision-maker and efficient, as it leads directly to a Pareto-optimal solution. Signal control priorities are ultimately a political decision. Therefore the tool developed in this research allows the traffic engineer to balance the objectives easily by setting acceptability and unacceptability thresholds for each objective. Particular attention is given in the example to pedestrian delays. The membership functions of the fuzzy logic are optimised by a genetic algorithm coupled to the VISSIM microscopic traffic simulator. The concept is illustrated with a case study of the Marylebone Road–Baker Street intersection in London at which pedestrians as well as vehicle flows are high. The results prove the feasibility of the framework and show the vehicle delays for a more pedestrian friendly signal control strategy.

E-Government information systems: Evaluation-led design for public value and client trust

e-Government systems differ from commercial information systems (IS) in that they frequently encompass strategic goals that go beyond efficiency, effectiveness and economy, and include political and social objectives such as trust in government, social inclusion, community regeneration, community well-being and sustainability. Designing e-Government systems that help to meet these objectives is a significant challenge for the future. This paper develops an evaluative design framework for e-Government projects that complements traditional approaches to IS evaluation. The framework is based upon Moor's concept of public value. It focuses upon citizens' and clients' experiences of service provision and service outcomes as contributors to the formation of public trust. Trust is shown to be related to the extent to which people feel that an e-Government service enhances their sense of being well-informed, gives them greater personal control, and provides them with a sense of influence or contingency. The framework's development and validation are founded upon analyses of a two live case studies in south-east England and London, U.K.

Modelling the impact on Hepatitis C transmission of reducing syringe sharing: London case study

Hepatitis C virus (HCV) prevalence and incidence among injecting drug users (IDUs) has increased in London and rest of UK. To inform public health action, mathematical modelling is used to explore the possible impact of strategies to decrease syringe sharing. A mathematical model was developed to simulate HCV transmission amongst IDUs in London. Because of parameter uncertainty, numerical search algorithms were used to obtain different model fits to HCV seroprevalence data from London for 2002-03. These simulations were used to explore the likely impact of HCV prevention activities that reduce syringe sharing amongst all IDUs, IDUs that have injected for greater than one year, or IDUs with lower or higher frequencies of syringe sharing. Key differences between model fits centred on how they simulated the high HCV incidence amongst new injectors, either through assuming increased HCV infectivity during acute infection, a large sub-group of high frequency syringe sharers, or increased sharing among new IDUs. Despite parameter uncertainty, the model projections suggest that modest reductions in syringe sharing frequency (<25%) will reduce the HCV seroprevalence in newly initiated IDUs (injecting less than four years) but much larger and sustained reductions (>50%) are required to reduce the HCV seroprevalence in long-term IDUs (injecting more than 8 years). Critically the model also suggested that large reductions in HCV seroprevalence will be achieved only if interventions target all IDUs and reach IDUs within 12 months of injecting. Public health interventions must reduce syringe sharing amongst all IDUs, including newly initiated IDUs, and be sustained for many years to reduce HCV infection. More accurate data on key behavioural (sharing frequency) and biological (percentage of infected IDUs that clear infection) parameters is required to improve model projections.

Comparison of spatial methods for measuring road accident 'hotspots': a case study of London

Comparison of spatial methods for measuring road accident 'hotspots': a case study of London

Comparison of spatial methods for measuring road accident ‘hotspots’: a case study of London

There is a continuing determination by academics and road professionals alike to investigate the most appropriate methods for identifying road accident hotspots particularly in urban areas. Increasingly this research has involved the use of GIS and spatial analysis in order to define both visually and statistically what can be defined as a road accident hotspot. Traditional methods of hotspot detection by road professionals have included comparing count data at different locations and rating the areas by severity. However the increase use of GIS has lead to academics using sophisticated methods to quantify hotspots. There is, however, no universal definition of a road accident hotspot which means that the definition of a hotspot is open to much speculation. This paper seeks to investigate the merits of three different spatial techniques for quantifying road accident hotspots. Kernel density estimation, network analysis and area wide analysis are used to demonstrate three methods. The methods are then reviewed. There is however an exhaustive list of hotspot detection techniques, not all of which can be outlined in this paper.

Racism, criminalization and the development of night-time economies: Two case studies in London and Manchester

Nightlife has historically been identified as a social problem. In the contemporary context, however, this perspective competes with the promotion of the ‘night-time economy’ as a source of economic regeneration and extended licensing as a means to establish a more genteel ‘café society’. However, these changes have concealed a reconfiguration of differentiating strategies. This article explores this neglected issue through two cases studies, one based in London and one in Manchester, and examines the fate of black cultural forms, venues and licensees in contemporary nightlife. It will argue that, due to the historical criminalization of black youth, music and residential areas, black cultural spaces have been subject to a process of exclusion in the new playgrounds of the night-time economy. The implications of this for social cohesion will be examined.

Geoadditive Survival Models

Survival data often contain small-area geographical or spatial information, such as the residence of individuals. In many cases, the impact of such spatial effects on hazard rates is of considerable substantive interest. Therefore, extensions of known survival or hazard rate models to spatial models have been suggested. Mostly, a spatial component is added to the usual linear predictor of the Cox model. In this article flexible continuous-time geoadditive models are proposed, extending the Cox model with respect to several aspects often needed in applications. The common linear predictor is generalized to an additive predictor, including nonparametric components for the log-baseline hazard, time-varying effects, and possibly nonlinear effects of continuous covariates or further time scales, and a spatial component for geographical effects. In addition, uncorrelated frailty effects or nonlinear two-way interactions can be incorporated. Inference is developed within a unified fully Bayesian framework. Penalized regression splines and Markov random fields are suggested as basic building blocks, and geostatistical (kriging) models are also considered. Posterior analysis uses computationally efficient Markov chain Monte Carlo sampling schemes. Smoothing parameters are an integral part of the model and are estimated automatically. Propriety of posteriors is shown under fairly general conditions, and practical performance is investigated through simulation studies. Our approach is applied to data from a case study in London and Essex that aims to estimate the effect of area of residence and further covariates on waiting times to coronary artery bypass grafting. Results provide clear evidence of nonlinear time-varying effects, and considerable spatial variability of waiting times to bypass grafting.

Social housing and green space: a case study in Inner London

Urban woodlands and green spaces provide a range of benefits to people in densely populated areas: as places to use, view and enjoy. There is increasing interest in green spaces and their impacts on people's quality of life. The work described in this paper involved a partnership between Peabody Trust, a social housing association; the Forestry Commission and Trees for Cities, an environmental charity. The aim of the project was to involve residents in the use and enjoyment of their local woodland. The research gained an understanding of how the residents of two housing estates in South London view and experience their local woodland, called Peabody Hill Wood. Three focus groups and a questionnaire were undertaken with residents. Observations were also made at a community activity day and walk through the wood with local residents. From the analysis of the data, there was a complex mix of attitudes towards Peabody Hill Wood that related to not only the management of the wood but also the management of the buildings by Peabody Trust. This research highlights, as a number of other studies have, that woodlands near to where people live are valuable spaces and play a significant role by providing opportunity for contact with nature. Key implications of the research suggest that housing associations can have an important role to play in green space management. Partnership working with the environmental sector can help bring about much needed improvements to the environment. Working with communities and sustaining long-term commitment are also advocated.

Making Embeddedness Work: Social Practice Institutions in Foreign Consulting Markets

This paper develops conceptual and empirical evidence for the importance of social practice institutions in the internationalisation process of management-consulting firms. Personal trust and reputation rather than price are examined as key mechanisms of foreign market entry and penetration. Empirical case studies in London, Frankfurt, and Madrid produce three findings. First, enduring client relations and client referrals facilitated most foreign firm entries and the majority of local client acquisition. Second, interview findings imply a critical assessment and reconceptualisation of trust and reputation. Empirically, goodwill trust and networked reputation are substantiated as particularly important transaction mechanisms. Third, a triangulation of interview and survey data reveals a causal relation between trust and reputation that enhanced a cumulative growth of social networks within the new host markets. This research points to the importance of social practice institutions for economic organisation and exchange across geographic distance.

Analysing awareness and acceptability of hydrogen vehicles: A London case study

This paper investigates the determinants of knowledge and acceptability of hydrogen vehicles among London residents. Data was collected via a socio-economic survey of over four hundred residents. Results indicate that, at present, less than half of respondents have heard of hydrogen as a fuel for transport, and just over one-third are clearly in favour of the introduction of hydrogen vehicles. The key determinant of acceptability was having prior awareness of hydrogen technologies, as identified via logit regression analysis. Hydrogen awareness in turn was found to be related to gender, age, education and environmental knowledge. These results suggest that there is an opportunity to raise awareness of hydrogen technologies among the remaining three-fifths of the London population, although this is likely to require a differential approach to information provision.