4,782 research outputs found
Picturing protein disaggregation
No full textGreen Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.BN/Sander Tans La
Over het optimaal routeren van schepen: IV Het berekenen van golfvelden uit windvelden op de Atlantische Oceaan.
No full textIn minimal-time ship routing there are two main problems: 1. The computation of wavecharts from windcharts. 2. The determination of the least time track for a ship given these wavecharts and a polar velocity diagram. The second problem has been treated in the foregoing report (Bijlsma en Van Rietschote, 1972 I, II en III). In this report the first problem is dealt with. Hereby we assume that the problem of (forecasting and) converting pressure charts into wind charts has been solved. In practice this is a delicate problem depending mainly on the accuracy with which the pressure charts are given. The computation of waves from windfields goes back to the second part of the nineteenth century when some empirical formulas were derived in order to descrive the wave-wing relation (for a review of some of these relationships one is referred to Sverdrup, Johnson and Fleming (1942) and Defant (1961)). The first theoretical attempt however was made by Sverdrup and Munk (1947), when the outbreak of world war II made it necessary to have sea and swell forecasts at one's disposal. Although in later years applications of the developments in statistical analysis made the foundations on which their theory (revised by Brettschneider (1952)) was based, very disputable, it is nevertheless still in rather wide use. In this report (section 1) a brief outline is given of a wave forecasting method due to Pierson (1952). In his theory the forecast of ocean waves is considered as an application of the theory the stochastic processes. In this section, moreover, some elementary aspects of nonlinear wave interaction are given. Based on results of the last mentioned theory a computerprogram has been constructed for the computation of wave fields on the North Atlantic. Applications are given and compared with results of manual treatment (section 3). The computerprogram and a flow diagram of it are added
On the edge of an inverse cascade
No full textWe demonstrate that systems with a parameter-controlled inverse cascade can exhibit critical behavior for which at the critical value of the control parameter the inverse cascade stops. In many dynamical systems in nature energy is transferred to small or to large length scales by a forward or inverse cascade, respectively. In three-dimensional hydrodynamic (HD) turbulence energy cascades forward from large to small scales while in two-dimensional HD turbulence energy cascades inversely from small scales to large scales. There are some examples, however, that have a mixed behavior such as fast rotating fluids, conducting fluids in the presence of strong magnetic fields, flows in constrained geometry, and others. In these examples the injected energy cascades both forward and inversely in fractions that depend on the value of a control parameter (rotation rate/magnetic field/aspect ratio ect). In the presented work we demonstrate using the 2D-MHD model that the transition from a forward to an inverse cascade can occur by a critical transition, . In the absence of any external magnetic forcing the system reduces to hydrodynamic fluid turbulence with an inverse energy cascade. In the presence of strong magnetic forcing the system behaves as 2D-MHD turbulence with forward energy cascade. As the amplitude of the magnetic forcing is varied a critical value is met for which the energy flux towards the large scales becomes zero. Close to this point the energy flux scales as a power law with the departure from the critical point and the normalized amplitude of the fluctuations diverges. The generality of this behavior to other systems with variable inverse cascades will be discussed
Over het optimaal routeren van schepen: V. Een geautomatiseerd systeem.
No full textThis report concludes a series of previous reports on minimal-time ship routing, dealing both with the problem of determining the least-time track (Bijlsma en Van Rietschote, 1972, I, II, III) and with that of the computation of wavecharts from windcharts (Bijlsma en Folkers, 1973). It contains an (experimental) method for the solution of the remaining problem: to bring into agreement, by taking into account observations of ships, windcharts of the Atlantic Ocean derived from pressurecharts, with those used by the Routing Office (see chapter 1). With the solution of this problem we are in a position to compare optimal routes, obtained both in a manual way (by Routing Office) and in a computational way (way the automated system) starting from the same pressurecharts (chapter 2)
Property A and affine buildings
No full textYu's Property A is a non-equivariant generalisation of amenability introduced in his study of the coarse Baum Connes conjecture. In this paper we show that all affine buildings of type A2, B2 and G2 have Property A. Together with results of Guentner, Higson and Weinberger, this completes a programme to show that all affine building have Property A. In passing we use our technique to obtain a new proof for groups acting on buildings.The author was supported by EPSRC postdoctoral fellowship EP/C53171X/1.<br/
Identifying movement patterns from large scale Wifi-based location data: A case study of the TU Delft Campus
No full textLocation is a key element of many processes and activities, and the understanding of human movement behaviour is becoming increasingly important. Knowledge of people’s locations and related mobility patterns are important for numerous activities, such as urban planning, transport planning and facility management. How to efficiently use the available space, is a common problem in many fields. In the educational sector, universities are struggling to meet the higher expectations of facilities for education and research by students and academic staff. Managing the campus of a university has become a complex and challenging task, including the involvement ofmany stakeholders. Campus managers are in need for evidence-based information to support their decision making (Heijer den 2012). This includes better location data to detect activities, occupancy and usage of the infrastructure. To understand the human motion behaviour many studies are conducted based on data collection of GPS receivers. The Global Navigation Satellite System (GNSS) is commonly used to track people in large scale environments. Spek 2008 studied the movement of pedestrians in city centres, where potential participants were asked to carry a GPS receiver. However, the distribution of GPS devices to participants limits the possibilities to collect location data at a large scale. Furthermore, due to poor quality of received signals from satellites in indoor environments, GPS receivers are not suitable in these conditions. Technological developments in the acquisition of location data by smart phones and the use of Wi-Fi networks, enables new opportunities to track users. Wireless Local Area Networks (WLAN) are widely used for indoor positioning of mobile devices within this network. The use of theWi-Fi network to estimate the location of people is an attractive approach, sinceWi- Fi access points (AP) are often available in indoor environments. Furthermore, smart phones are becoming essential in daily life, making it convincing to track mobile devices. This provides a platform to track people by using WLAN as a sensor network, and study the mobility of users inside buildings or groups of buildings. At Delft University of Technology (TU Delft) a large scale Wi-Fi network is deployed across all facilities covering the indoor space of the campus. The network is known as an international roaming service for users in educational environments and is called the eduroam network. It allows students and staff members from the university to use the infrastructure throughout the campus for free. This enables the possibility to collectWi- Fi logs, including individual scans of mobile devices, at a large scale. A continuous collection of re-locations of devices to access points for a long duration will return detailed records of people’s movement. This ubiquitous and individual georeferenced data derived from smart phones will present valuable knowledge about the movement on the campus. Several work has been made for studying human mobility patterns in a University’s campus. Meneses and Moreira 2012 used the eduroam network to study connectivity between two places, by computing the number ofmovements between two places within a given observation time period. Previous work has also been made at TU Delft (Kalogianni et al. 2015), where several Wi-Fi monitors were placed to detect occupation and movement between different faculties. In this paper, we attempt to identify people’s movement patterns from the eduroam network of TU Delft. Other than previous studies, this research-driven project analysed data from more than 30.000 users, and tries to detect movement patterns between buildings, and between large indoor regions. The project is carried out in request of the university’s department of Facility Management and Real Estate (FMRE). With this project, we try to illustrate to what extend movement patterns in and between buildings can be identified from anonymised Wi-Fi logs. Firstly, individual states are extracted from the Wi-Fi logs, where users stay for a longer time period. Secondly, movements are detected between a sequence of states. Thirdly, movement patterns can be identified by counting the amount of movement from, to or between certain locations at different time intervals. The aim of this paper is not to improve a Wi-Fi based positioning technique, but to use the location data to conduct a mobility analysis producing knowledge about the University’s campus. Based on the three steps mentioned above, the aim of this project is to provide a method to detect movement patterns from anonymised Wi-Fi logs. This includes the separation of mobile devices (i.e. smart phones) and static devices (e.g. laptops) from the Wi-Fi logs, and detecting movement to and from beyond the spatial extent of the eduroam network by introducing the concept of a ‘world’ state. Hereby, this paper attempts to contribute with a method to automatically mine people’s movement patterns at two spatial levels. First, movement at building level is analysed. Subsequently, indoor movement at building-part level is studied, by constructing a network graph of the underlying building floorplan. The structure of this paper is as follows. Section 2.1.1, describes the case study of TU Delft, the tracking technique and the acquired data that is used in the study. In section 2.2 we present our methodology. Section 2.3 discusses the obtained results. Finally, in section 2.4, we present our concluding remarks and recommendations.Architecture and The Built EnvironmentGeo-information TechnologyGeomatics for the Built Environmen
Walter E. Oberer Retirement Luncheon
No full textDean Oberer was emeritus of law and former dean of the S.J. Quinney College of Law. He received the Burlington Resources Foundation Faculty Achievement Award in 1991 and was particularly noted for his scholarship in labor law and was co-author of a book, "Cases and Materials on Labor Law: Collective Bargaining in a Free Society.
How to regenerate Yeouido as an international business center of Seoul
No full textSeoul has developed very fast from 1970 and achieved a dramatic economic development in a short period. Korea's development was depending on labor-intensive industries for many years such as a textile. And in these days the manufacturing industry is concentrating on the technology intensive manufacturing like semiconductors and parts of cars. However, these manufacturing industries have been relocated from Seoul to other cities, especially satellite cities of Seoul. By this phenomenon, there is an obvious trend towards the specialization of command and control activities in City of Seoul and the relocation of manufacturing industries to the Seoul capital region. In the flow of globalization, most of Asian cities are trying to become a global city or major centers both in finance and in the international business services. The competition to become an attractive major center between the cities is very keen. City of Seoul also performs as one of the major centers in advanced producer services. However Seoul faced the challenge how to enhance the economic performance in the competition with other Asian cities. In order to boost Seoul's economic performance, it was relevant to research the main business centers of Seoul because the advanced producer services are all concentrated on the main business centers of Seoul. In addition Dunford and Kafkalas insist that the business center is the economic engine of the city, networked in the global economy. Seoul has three main business centers; CBD, Teheran street and Yeouido. Seoul has been developed focusing on them. The business centers have shaped spatial structure of Seoul and caused unbalanced development. By the empirical analysis of Seoul following three business centers it is found that the competitiveness of Yeouido as a business center of Seoul is decreasing and it is not performing well even as a local center. Therefore this graduate project was focused on the Yeouido business center to solve the current problems and to regenerate the business center into an attractive international business center.Architectur
Influence of weather parameters on a fireball’s dark flight
No full textThe computation of the dark flight of a bright fireball requires knowledge of the atmospheric parameters. In particular wind and wind direction as a function of height are crucial for an accurate trajectory. In this paper we compare different sources of sounding balloon and model data, and study the effect on the dark flight.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Planetary Exploratio
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