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De publicatielijst bevat alle publicaties waar Harmen Bijwaard aan bijgedragen heeft in de periode 1998 - 2013
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Based on the soil data established previously by a team of researchers at the Technical University of Istanbul, a wave amplification study is conducted for the town of Avcılar, Istanbul, located at about 120 km west of the epicentre of the Kocaeli earthquake of August 17, 1999. It is determined, through the use of well known computer program SHAKE, that the three major predominant periods of the ground are, 1.60, 1.00 and 0.70 s. Thus, the reasons of extensive damage occurred to 5–8 storey high residential buildings in the region, may be attributed to both the long distance effects of the high period waves of the earthquake and soil amplification.
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DBELA is a Displacement-Based Earthquake Loss Assessment methodology for urban areas which relates the displacement capacity of the building stock to the displacement demand from earthquake scenarios. The building stock is modeled as a random population of building classes with varying geometrical and material properties. The period of vibration of each building in the random population is calculated using a simplified equation based on the height of the building and building type, whilst the displacement capacity at different limit states is predicted using simple equations which are a function of the randomly simulated geometrical and material properties. The displacement capacity of each building is then compared to the displacement demand obtained, from an over-damped displacement spectrum, using its period of vibration; the proportion of buildings which exceed each damage state can thus be estimated. DBELA has been calibrated to the Turkish building stock following the collection of a large database of structural characteristics of buildings from the northern Marmara region. The probabilistic distributions for each of the structural characteristics (e.g. story height, steel properties etc.) have been defined using the aforementioned database. The methodology has then been applied to predict preliminary damage distributions and social losses for the Istanbul Metropolitan Municipality for a Mw 7.5 scenario earthquake.
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Cooperatives are special because the members not only own the cooperative, but also patronize it. CEO’s decision has an impact on the overall members’ interests. Understanding how CEOs differ from members regarding their evaluations on cooperative performance and what causes the differences, is valuable for CEOs to best serve the members. This paper evaluates the difference between CEO and member evaluation regarding their cooperatives, and further examines the role of governance in predicting the evaluations and differences in evaluations, based on a set of first-hand data containing Chinese agricultural cooperatives (240 CEOs and 543 members). Cooperative performance is measured by three indicators: member profitability, social influence in the local community, and overall performance. The results show that members have higher scores than CEOs regarding member profitability and overall performance, while CEOs have a higher evaluation regarding social influence. “This is an Accepted Manuscript of an article published by Taylor & Francis in 'The Social Science Journal' on 27 Jan. 2020 available online: https://www.tandfonline.com/doi/abs/10.1016/j.soscij.2019.01.006. LinkedIn: https://www.linkedin.com/in/xiao-peng-20466772/
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Author supplied: "This paper gives a linearised adjustment model for the affine, similarity and congruence transformations in 3D that is easily extendable with other parameters to describe deformations. The model considers all coordinates stochastic. Full positive semi-definite covariance matrices and correlation between epochs can be handled. The determination of transformation parameters between two or more coordinate sets, determined by geodetic monitoring measurements, can be handled as a least squares adjustment problem. It can be solved without linearisation of the functional model, if it concerns an affine, similarity or congruence transformation in one-, two- or three-dimensional space. If the functional model describes more than such a transformation, it is hardly ever possible to find a direct solution for the transformation parameters. Linearisation of the functional model and applying least squares formulas is then an appropriate mode of working. The adjustment model is given as a model of observation equations with constraints on the parameters. The starting point is the affine transformation, whose parameters are constrained to get the parameters of the similarity or congruence transformation. In this way the use of Euler angles is avoided. Because the model is linearised, iteration is necessary to get the final solution. In each iteration step approximate coordinates are necessary that fulfil the constraints. For the affine transformation it is easy to get approximate coordinates. For the similarity and congruence transformation the approximate coordinates have to comply to constraints. To achieve this, use is made of the singular value decomposition of the rotation matrix. To show the effectiveness of the proposed adjustment model total station measurements in two epochs of monitored buildings are analysed. Coordinate sets with full, rank deficient covariance matrices are determined from the measurements and adjusted with the proposed model. Testing the adjustment for deformations results in detection of the simulated deformations."
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Preprint submitted to Information Processing & Management Tags are a convenient way to label resources on the web. An interesting question is whether one can determine the semantic meaning of tags in the absence of some predefined formal structure like a thesaurus. Many authors have used the usage data for tags to find their emergent semantics. Here, we argue that the semantics of tags can be captured by comparing the contexts in which tags appear. We give an approach to operationalizing this idea by defining what we call paradigmatic similarity: computing co-occurrence distributions of tags with tags in the same context, and comparing tags using information theoretic similarity measures of these distributions, mostly the Jensen-Shannon divergence. In experiments with three different tagged data collections we study its behavior and compare it to other distance measures. For some tasks, like terminology mapping or clustering, the paradigmatic similarity seems to give better results than similarity measures based on the co-occurrence of the documents or other resources that the tags are associated to. We argue that paradigmatic similarity, is superior to other distance measures, if agreement on topics (as opposed to style, register or language etc.), is the most important criterion, and the main differences between the tagged elements in the data set correspond to different topics
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The decomposition of a body is influenced by burial conditions, making it crucial to understand the impact of different conditions for accurate grave detection. Geophysical techniques using drones have gained popularity in locating clandestine graves, offering non-invasive methods for detecting surface and subsurface irregularities. Ground-penetrating radar (GPR) is an effective technology for identifying potential grave locations without disturbance. This research aimed to prototype a drone system integrating GPR to assist in grave localization and to develop software for data management. Initial experiments compared GPR with other technologies, demonstrating its valuable applicability. It is suitable for various decomposition stages and soil types, although certain soil compositions have limitations. The research used the DJI M600 Pro drone and a drone-based GPR system enhanced by the real-time kinematic (RTK) global positioning system (GPS) for precision and autonomy. Tests with simulated graves and cadavers validated the system’s performance, evaluating optimal altitude, speed, and obstacle avoidance techniques. Furthermore, global and local planning algorithms ensured efficient and obstacle-free flight paths. The results highlighted the potential of the drone-based GPR system in locating clandestine graves while minimizing disturbance, contributing to the development of effective tools for forensic investigations and crime scene analysis.
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The decomposition of a body is influenced by burial conditions, making it crucial to understand the impact of different conditions for accurate grave detection. Geophysical techniques using drones have gained popularity in locating clandestine graves, offering non-invasive methods for detecting surface and subsurface irregularities. Ground-penetrating radar (GPR) is an effective technology for identifying potential grave locations without disturbance. This research aimed to prototype a drone system integrating GPR to assist in grave localization and to develop software for data management. Initial experiments compared GPR with other technologies, demonstrating its valuable applicability. It is suitable for various decomposition stages and soil types, although certain soil compositions have limitations. The research used the DJI M600 Pro drone and a drone-based GPR system enhanced by the real-time kinematic (RTK) global positioning system (GPS) for precision and autonomy. Tests with simulated graves and cadavers validated the system’s performance, evaluating optimal altitude, speed, and obstacle avoidance techniques. Furthermore, global and local planning algorithms ensured efficient and obstacle-free flight paths. The results highlighted the potential of the drone-based GPR system in locating clandestine graves while minimizing disturbance, contributing to the development of effective tools for forensic investigations and crime scene analysis.
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With summaries in Dutch, Esperanto and English. DOI: 10.4233/uuid:d7132920-346e-47c6-b754-00dc5672b437 "The subject of this study is deformation analysis of the earth's surface (or part of it) and spatial objects on, above or below it. Such analyses are needed in many domains of society. Geodetic deformation analysis uses various types of geodetic measurements to substantiate statements about changes in geometric positions.Professional practice, e.g. in the Netherlands, regularly applies methods for geodetic deformation analysis that have shortcomings, e.g. because the methods apply substandard analysis models or defective testing methods. These shortcomings hamper communication about the results of deformation analyses with the various parties involved. To improve communication solid analysis models and a common language have to be used, which requires standardisation.Operational demands for geodetic deformation analysis are the reason to formulate in this study seven characteristic elements that a solid analysis model needs to possess. Such a model can handle time series of several epochs. It analyses only size and form, not position and orientation of the reference system; and datum points may be under influence of deformation. The geodetic and physical models are combined in one adjustment model. Full use is made of available stochastic information. Statistical testing and computation of minimal detectable deformations is incorporated. Solution methods can handle rank deficient matrices (both model matrix and cofactor matrix). And, finally, a search for the best hypothesis/model is implemented. Because a geodetic deformation analysis model with all seven elements does not exist, this study develops such a model.For effective standardisation geodetic deformation analysis models need: practical key performance indicators; a clear procedure for using the model; and the possibility to graphically visualise the estimated deformations."
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