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There is considerable variation in the extent to which environmental measures are adopted in housing construction in various European countries. Whereas sustainable housing is dearly part of day-to-day building practice in some countries, in others the topic seldom receives serious attention. None of the environmental measures which are considered as such in the Netherlands are adopted frequently in all countries. On the other hand, various measures are adopted regularly everywhere. An overall comparison of 24 countries shows that Denmark is currently the country where the greatest number of sustainable housing measures are actually adopted, followed (some way behind) by countries such as Austria and Sweden.

More than half of the world population lives in urban areas concentrating and increasing the magnitude of social and environmental impacts. The potential role of cities in a transition to a sustainable society started to be widely recognized after the 1992 Rio conference where the Agenda 21 program was signed. Since then, a number of urban developments that aim to be sustainable have been and are being implemented worldwide. Numerous research efforts have been done in order to assess how sustainable these developments are, but too little is understood regarding the process of how they actually came (or come) about. In fact, sustainable urban developments require innovative governance arrangements in their planning and implementation. However, there is not one best way to go about and different arrangements may emerge in different contexts. In this paper we are going to analyze two innovative governance arrangements: Hammarby Sjöstad, a district in Stockholm and EVALanxmeer in Culemborg (the Netherlands). By doing this analysis, we seek to understand why certain governance arrangements are chosen for and what the implications of these choices are. Conclusions and recommendations will be formulated as to the approach and process of constructing and transforming to eco-cities.

The paper considers the role of the private rented sector in supplying housing that can be defined as social housing. It will do this by considering policy initiatives in Germany, France, the USA and England that use privately owned housing to meet social needs. The operation of these initiatives will be compared. The allocation and rent conditions attached to dwellings supplied under selected schemes will be exam-ined as will the incentives for landlords to offer housing under these conditions. The functions of the conditions and the time limits attached to them will be compared. It will be shown that such schemes raise questions about the definition and the role of the sector in varying institutional contexts. The paper draws on some of the evidence in the authors’ research report for the English Department of Communities and Local Government: Promoting Investment in Private Rented Housing Supply: International Policy Comparisons (November 2010). See: http://www.communities.gov.uk/publications/housing/investprivaterentedhousing

The space that can be improved to get a better prediction bridging the gap between simulation and reality, and its reactions on design revision to increase the fire-resistance of a façade product before a formal test is the issue of this thesis. Regulations and design principles concerning a fire-resistant façade have been studies. With the technical support from Scheldebouw company, a running project was able to be taken as a case study, which is the main tool to look for the answers in this research. Calculation models with VOLTRA had been designed for this project and been compared with pre-test results to find out the link with reality and the limitation of simulation. An experiment on a simple model was made and analyzed with the help of TU Delft to get more information about a good prediction by simulation. Then via illustrating the revision steps based on the estimation of each phase, an economically and efficiently meliorated fire-resistant design procedure generated. Finally the thesis ended with evoking a space for the architects to rethink about the decisions made at an early stage.

A comparison between the pleintje, priority intersection and roundabout based on the criteria cyclist traffic safety, traffic flow and environment.

The building industry is a fragmented and project-driven industry with specific characteristics, which can sometimes result in negative effects. Reference has often been made to other industries, particularly manufacturing, that would function more effectively and efficiently. Major differences between both include the organisation and coordination of the supply chain. Supply chain integration has been suggested as a solution for the building supply chain. This thesis has aimed to contribute to the conceptual development of supply chain integration for building by means of hypothesis-generating research. The concept of supply chain integration has first been explored on the basis of related thoughts and concepts in building practice and literature. The concept has been framed further based on four theoretical perspectives: economic, production, organisational and social theory. In the empirical part, supply chain integration practices have first been studied in six different industries: automotive, aerospace, computers, electronics, clothing and grocery. The findings have indicated advanced forms and high levels of supply chain integration. The building cases have included five firm types in the building supply chain: clients, developers, designers, builders and suppliers. The findings have demonstrated relatively less advanced and less comprehensive approaches to supply chain integration, as compared to theory and manufacturing. Based on the confrontation of the empirical findings with the theory, four hypotheses have been shaped representing partial descriptions of what constitutes a concept of supply chain integration in building. As a consequence, this would imply a shift of the building supply chain towards higher levels of repetitiveness and integration of products, processes and organisational arrangements.

The potential for volunteer groups to contribute geographic data to National Mapping Agencies has been widely recognised. Several investigations have been done to determine the geometric accuracy of this data for the purposes of national mapping. Beyond accuracy, from a production perspective National Mapping Agencies will also be interested in the sufficiency and uniformity of the data. This paper presents an investigation of whether presently geographic data generated by volunteers is uniform across a country and whether the rate of production of data is consistent. For the purpose of the test, changes in data of South Africa from OpenStreetMap are analysed for the period 2006 to 2011. Here only point and line data are considered. The results generally show that the rate at which data is generated varies in space and time. The results also confirm that volunteers emphasise on the capture of certain information and that the capture doesn’t average out as might be expected. The results also showed that social events, such as a World Cup, also have the effect of spurring the generation of volunteer geographic data. The implication of these results for National Mapping Agencies is that they cannot treat volunteer geographic information as being of a uniform standard. How National Mapping Agencies respond to this will have to be the subject of other investigations.

Audio fingerprints can be seen as hashes of the perceptual content of an audio excerpt. Applications include linking metadata to unlabeled audio, watermark support, and broadcast monitoring. Existing systems identify a song by comparing its fingerprint to pre-computed fingerprints in a database. Small changes of the audio induce small differences in the fingerprint. The song is identified if these fingerprint differences are small enough. In addition, we found that distances between fingerprints of the original and a compressed version can be used to estimate the quality (bitrate) of the compressed version. In this paper, we study the relationship between compression bit-rate and fingerprint differences. We present a comparative study of the response to compression using three fingerprint algorithms (each representative for a larger set of algorithms), developed at Philips, Polytechnic University of Milan, and Microsoft, respectively. We have conducted experiments both using the original algorithms and using versions modified to achieve similar operation conditions, i.e., the fingerprints use the same number of bits per second. Our study shows similar behavior for these three algorithms.

School travel is highly neglected in transport science. It contributes little to today’s most envisaged transport problems but it generates its own problems. The paper presents results of a study on travel behaviour of pupils travelling to primary and secondary schools. The study focuses on two aspects: the distances between home and school and the modal choice. The study regions are the Netherlands and Flanders. Though educational policies are similar in both regions, there are significant differences in travel behaviour. In Flanders, distances to primary schools are on average considerably larger than in the Netherlands. Distances to secondary schools are more similar. The bicycle is the dominant mode for Dutch pupils. Flemish pupils use the bicycle predominantly for shorter distances (<5 km). They are travelling larger distances more frequently by car, even to secondary schools, and they are more inclined to use public transport. Both travelled distances and modal choice are mainly explained by ‘hard’ factors, like locations of home and school for distances and quality of the transport modes for modal choice. However, other factors play a role, too. Their role seems to be larger for the Flemish than for the Dutch. In particular, gender is a significant variable for explaining modal choice of the Flemish. Boys are more inclined to use the bicycle than girls, while the latter more frequently use public transport. Additionally, household income has a substantial influence on modal choice of the Flemish pupils. Increasing income enlarges the probability of car use.

Nested or intersecting surfaces are proven techniques for visualizing shape differences between static 3D objects (Weigle and Taylor II, IEEE Visualization, Proceedings, pp. 503–510, 2005). In this paper we present an image-based formulation for these techniques that extends their use to dynamic scenarios, in which surfaces can be manipulated or even deformed interactively. The formulation is based on our new layered rendering pipeline, a generic image-based approach for rendering nested surfaces based on depth peeling and deferred shading. We use layered rendering to enhance the intersecting surfaces visualization. In addition to enabling interactive performance, our enhancements address several limitations of the original technique. Contours remove ambiguity regarding the shape of intersections. Local distances between the surfaces can be visualized at any point using either depth fogging or distance fields: Depth fogging is used as a cue for the distance between two surfaces in the viewing direction, whereas closest-point distance measures are visualized interactively by evaluating one surface’s distance field on the other surface. Furthermore, we use these measures to define a three-way surface segmentation, which visualizes regions of growth, shrinkage, and no change of a test surface compared with a reference surface. Finally, we demonstrate an application of our technique in the visualization of statistical shape models. We evaluate our technique based on feedback provided by medical image analysis researchers, who are experts in working with such models.

Shelter programs are being implemented within Haiti by hundreds of Non-Governmental Organizations, but there is a lack of experience in shelter strategies confronting the urban living environment. A comparison on the implementation process of shelter programs, between the rural and urban context, would have to point out which difficulties a more dense context brings along, in facilitating the transition from the phase of relief to the phase of development, for the process of post-disaster reconstruction.

This thesis deals with the optimal use of existing models that predict certain phenomena of the road traffic system. Such models are extensively used in Advanced Traffic Information Systems (ATIS), Dynamic Traffic Management (DTM) or Model Predictive Control (MPC) approaches in order to improve the traffic system. As road traffic is the result of human behavior which is ever changing and which varies internationally, for each of these phenomena a multitude of models exist. The scientific literature generally is not conclusive about which of these models should be preferred. One common problem in road traffic science is therefore that for each application a choice has to be made from a set of available models. A second task that always needs to be performed is the calibration of the parameters of the models. A third and last task is the application of the chosen and calibrated model(s) to predict a part of the traffic system. For each of these three steps, generally data (measurements of the traffic system) is required. In this thesis, all three uses of data are summarized into data assimilation, which is defined as “the use of techniques aimed at the treatment of data in coherence with models in order to construct an as accurate and consistent picture of reality as possible. It comprises the use of data for model validation and identification (choosing between models), model calibration and estimation and prediction and specifically deals with the interactions between all these tasks”. In this thesis, a Bayesian framework is used in which these interactions can be treated consistently: solving one of these steps automatically leads to the solution of the other steps. Throughout the thesis, the calibration task is always performed first using standard optimization techniques such as regression or gradient-based algorithms. Once all available models are calibrated, a choice can be made between them. The selected model(s) can then be used to make an as accurate prediction as possible. One very important feature of the Bayesian framework is that it takes the complexity of models into account in the model comparison step. More complex models generally show a lower calibration error than more simple models, but they do not necessarily make better predictions. This is known as the problem of overfitting. The Bayesian framework deals with overfitting by penalizing models which contain more parameters and are thus more complex. The Bayesian assessment of models produces a measure called the evidence, which balances between a goodness of fit to the calibration data set and the complexity of the model. Besides this, the framework has more benefits. First, prior information can easily be included in each step of data assimilation. Second, error bars can be constructed on the predictions. This may be beneficial to the performance or public acceptance of ATIS, DTM or MPC systems. Third, a committee can be constructed, in which predictions of multiple models are combined. Committees generally produce more accurate predictions than individual models. The Bayesian framework for data assimilation is applied to three different phenomena: (1) car-following modeling, (2) travel time prediction and (3) traffic state estimation using a first order traffic flowmodel (the LWR model) and an Extended Kalman Filter. Finally, a part of the research is devoted to speeding up the EKF such that it can be applied together with the LWR model in real time to large networks. Car-following behavior Recent research has revealed that there exists large heterogeneity in car-following behavior such that different car-following models best describe different drivers behavior. The choice of a car-following model thus has to be made for each individual driver. Current approaches to calibrate and compare different models for one driver do not take the complexity of the model into account or are only able to compare a specific set of models. Using the Bayesian framework for data assimilation the suitability of any set of models can be quantitatively assessed for each single driver. In this research the Bayesian framework for data assimilation is applied to two simple car-following models, the CHM model and the Helly model. The workings of the Bayesian framework are demonstrated in a real-world experiment using 229 trajectories of drivers who were in car-following mode. Aggregated over all drivers, the probabilities of each model relative to the probability of all used models can be computed. This can serve as input to a heterogeneous microscopic simulation of traffic. The outcomes of this experiment show that averaged over all drivers the CHM model has a probability of 31% and the Helly model of 69%. Travel time prediction In this research different types of models are applied to the problem of travel time prediction: linear regression models and neural networks. Three experiments are performed on an 8.5 km long stretch of the A12 motorway in the Netherlands. Travel time data was collected during a period of three months in early 2007. In every experiment the Bayesian framework is applied to calibrate a set of available models, to make choices between models and to make predictions of the travel times. In all experiments a committee is used. In the first experiment two linear regression models are used. In this experiment the framework is applied dynamically: each time step, the available measured travel times and a set of historic loop detector data are used to recalibrate the models using standard regression tools. After this regression (calibration) is finished, the evidence measure assigns a preference for one of the two models over the other. Two strategies are tested: (1) the prediction of the model with the highest evide nce is used and (2) the weighted average of the predictions of both models is used, where the evidence is used as a weight factor. The results show that both models perform similarly well, and that the committees show a slight improvement of accuracy. A clear difference between the two strategies was not found. In the second experiment feed forward neural networks are used, with one hidden layer with different numbers of hidden nodes. The Bayesian framework is used to train (calibrate) 84 different neural networks, and the evidence measure is used to select highpotential networks. Using a separate validation data set, the evidence is tested as a predictor of the true prediction error. It is found that there is a correlation between the two, but that the evidence is not a perfect predictor of a well-performing neural network due to several reasons: (1) the size of the data sets may be too small so that the validation error does not equal the true error, (2) the models that are used may require improvement, such as weight pruning and (3) several assumptions were made in order to solve the necessary equations, such as the assumption that all distributions are Gaussian. In the same experiment a committee was tested using a simple average of the outcomes of a selection of models, ranked on the evidence. It was found that the average prediction error decreased from 8.1% of the best individual neural network to 7.8% for the committee. Finally, in the experiment the construction of error bars was tested, and it was shown that 97.4% of the true travel time fell within the 95% prediction intervals. The discrepancy between the two can be attributed to the relative simplicity of the used neural networks. In the third and final experiment feed forward neural networks (FFNN) as well as state-space neural networks (SSNN, a specific type of a recurrent or Elman neural network) were applied. The SSNN generally contains more parameters than the FFNN, but potentially are more accurate because they can take time dependencies into account: a typical problem of the necessity of balancing complexity against the ability to fit to a data set. For the Bayesian framework to be applied, the Jacobian and Hessian of the SSNN were derived (see Appendix A). Then, the Bayesian framework could again be used to compute the evidence for each model. In the experiments 70 FFNN and 70 SSNN were trained. The evidence was then used to form a committee of neural networks to predict the travel time on the selected motorway. The results show that the FFNN perform better on a short prediction horizon (5 minutes ahead), while the SSNN perform better on a longer horizon (15 minutes). The results also show that the use of a committee improves the accuracy of the predictions. In this experiment the calibration error was found to be a better predictor of the true error than the evidence. Nevertheless, the experiments show nearly no difference in performance of committees ranked on the evidence or ranked on the calibration error. The first order model with an Extended Kalman Filter In this research, two studies are performed on the application of a first order model (the LWR model) in combination with an Extended Kalman Filter (EKF) to create a networkwide estimate of the traffic state. The first study deals with the fact that the EKF itself contains parameters that require calibration. Using the Bayesian framework that has also been applied to calibrate car-following models and travel time prediction models, a method to calibrate the parameters of the EKF is derived. Using this result, the EKF parameters can be dynamically adapted during simulation. In an experiment on a small network it is then shown that the dynamic Bayesian choice for parameters leads to nearly the same accuracy compared to the optimal choice of fixed parameter values. This result is especially useful in large-scale applications, where it is impossible to test all possible fixed parameter values of the EKF. Finally, the last study overcomes a large disadvantage of the EKF: it is too slow to perform in real-time on large networks. To overcome this problem the novel Localized EKF (L-EKF) is proposed. The logic of the traffic network is used to correct only the state in the vicinity of a detector. The L-EKF does not use all information available to correct the state of the network; the resulting accuracy is however equal in case the radius of the local filters is taken sufficiently large. In two experiments, one on synthetic data and one on real-world data, it is shown that the L-EKF is much faster than the traditional Global EKF (G-EKF), that it scales much better with the network size and that it leads to estimates with the same accuracy as the G-EKF, even if the spacing between detectors is up to 5 kilometers. Opposed to the G-EKF, the L-EKF is hence a highly scalable solution to the state estimation problem.

We have built an all-solid-state camera that is directly modulated at the pixel level for frequency-domain fluorescence lifetime imaging microscopy (FLIM) measurements. This novel camera eliminates the need for an image intensifier through the use of an application-specific charge coupled device design in a frequency-domain FLIM system. The first stage of evaluation for the camera has been carried out. Camera characteristics such as noise distribution, dark current influence, camera gain, sampling density, sensitivity, linearity of photometric response, and optical transfer function have been studied through experiments. We are able to do lifetime measurement using our modulated, electron-multiplied fluorescence lifetime imaging microscope (MEM-FLIM) camera for various objects, e.g., fluorescein solution, fixed green fluorescent protein (GFP) cells, and GFP-actin stained live cells. A detailed comparison of a conventional microchannel plate (MCP)-based FLIM system and the MEM-FLIM system is presented. The MEM-FLIM camera shows higher resolution and a better image quality. The MEM-FLIM camera provides a new opportunity for performing frequency-domain FLIM.

Considering the recent increase in the use of fiber reinforced polymers in the civil engineering industry in general and in the bridge engineering industry in particular, as well as the recently more and more applied cylindrical truss bridge type, this research focuses on the question whether it is possible to combine fiber reinforced polymers as stand-alone structural material and this bridge type to construct a bridge suitable for heavy traffic as well as bicycle and pedestrian traffic. This research combines an extensive literature study on the use of fiber reinforced polymers for bridge engineering with a theoretical feasibility- and design-study on fiber reinforced polymer cylindrical truss bridges for heavy traffic. During the design study the spatial needs of all bridge users were defined to obtain an initial shape of the bridge. This shape was then optimized in several steps using finite-element-modeling and -analysis, yielding a final shape of the bridge. The behavior of this structure under design loads was then extensively investigated, again using finite element analysis, showing that the bridge could very well meet the self-derived deflection limit for fiber reinforced polymers at relatively low stress levels. Since fiber reinforced materials are a very diverse field of material, with hundreds of different compositions being available, the first result of this study was the choice of a suitable composite for further analysis. For this bridge design very high fiber content (>60%) carbon/epoxy composite was used. The main reason for this choice was the high modulus and -strength of the carbon fibers and the high durability and strength of the epoxy resin. A major reason of the slow implementation of fiber reinforced polymers in the bridge engineering industry are the worries concerning the lack of fire safety of the material. The literature study of this research showed however that it is possible to construct a heavy traffic full-FRP truss bridge, while complying with the known fire safety standards. The virgin FRP material can be adapted by several fire-protection measures; it turned out that a combination of intumescent gel-coating and low volume phosphorous filler systems works best in increasing the fire resistance and thereby providing a fire resistance class of R30 for hydrocarbon fire curve loading. The initial shape of the bridge was optimized in three stages: first several different truss topologies, which were derived with a parametric geometric model, were analyzed and compared using finite element analysis software, yielding the square truss with one diagonal as most efficient topology. In the next steps several grid sizes of this truss as well as several cross section dimensions were compared, again using finite element analysis software. An optimum was found between minimum material usage and minimum deflection, which reduced the material usage of the main load bearing elliptical truss by about 40% compared to the initial variant. The optimized structure was then fitted with the inner bridge deck supporting trusses as well as the cantilever trusses. The elliptical truss bridge performed very well considering the maximum deflections and stresses under Eurocode design loads and load combinations that were derived in finite element modeling software. When comparing the full-FRP bridge design with similar, existing steel structures, the maximum deformations and –stresses were considerably lower for the full-FRP bridge while only weighing about 60% of the steel structure. This research showed that the ‘new’ cylindrical truss bridge type is not only an aesthetically appealing structure but also performs structurally very well when combined with fiber reinforced polymer as structural material. It turned out that fiber reinforced polymers can be used as stand-alone structural material for medium span heavy traffic bridges. Next to that, this research clarified that there is no legitimate structural reason for the fact that fiber reinforced polymers are used relatively scarcely in the civil engineering- and bridge engineering industry compared to traditional building materials such as steel and concrete. Since this research is one of the first researches of its kind, using FRP as stand-alone structural material for a relatively new and complex bridge type, more research is needed in the field of high order connections for fiber reinforced polymer circular hollow sections. Next to that the possibility of the use of differently sized and shaped cross sections for the truss members should be investigated.

In this thesis modeling, analysis, design and measurement of exterior rotor permanent magnet (PM) machines with concentrated windings are dealt with. Special attention is paid to slotting effect. The PM machine is integrated in flywheel and used for small-scale ship application. Analytical model and automated nonlinear transient finite-element-model (FEM) including rotor motion are developed. A new hybrid model combining analytical model and static FEM model with single rotor position for the design of PM machines is developed. The hybrid model is an improvement of the analytical model on calculation accuracy and of the transient FEM on calculation time. The electromagnetic FEM model and circuit thermal model are coupled to form a multiphysics model for the design of PM machines taking temperature constraints into account. New insights into the influence of slotting effect on the performance of PM machines in the range of small slot opening are provided. Optimizing design parameters of the PM machine is investigated. Iron loss modeling and analysis are also addressed. The most suitable configuration of the PM machine for the application is found and described. The developed models are experimentally validated.