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Book
Nonparametric functional estimation under random censoring and a new semiparametric model of random censorship: proefschrift
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Year: 1992 Publisher: Leuven KUL

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Book
Statistiek in de praktijk toegepast met excel
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Year: 2001 Publisher: Kortrijk KUL. Campus Kortrijk. Postuniversitair centrum West-Vlaanderen

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Book
Eindige kansmodellen en toetsen van hypothesen
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ISBN: 9033430622 Year: 1994 Volume: *1 Publisher: Leuven Amersfoort Acco


Dissertation
Het schatten van prevalence van slachtofferschap, gebaseerd op gegevens van dd National Crime Survey
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Year: 1986 Publisher: s. n. Leuven s.n.

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Dissertation
Nonparametric functional estimation under random censoring and a new semiparametric model of random censorship

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Book
Comparing the efficiency of three matresses, Back Position
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Year: 2016 Publisher: Leuven KU Leuven.Faculteit wetenschappen

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Comparing the efficiency of two mattresses, back position
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Year: 2005 Publisher: Leuven KU Leuven.Faculteit wetenschappen

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Comparing the efficiency of two mattresses, side position
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Year: 2016 Publisher: Leuven KU Leuven.Faculteit wetenschappen

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Dissertation
Measuring visitor satisfaction in the context of a big cultural event: Mons 2015
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Year: 2015 Publisher: Leuven : KU Leuven. Faculteit Wetenschappen

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The global increase of income and leisure time, the improved educational levels, the progressive decrease of travel costs and the consequent 'democratization' of travels have encouraged more and more cities to enter the tourism market. However, while opportunities to attract tourists seem to be increasing, time remains a limited resource and competition to attract tourists stays fierce. Understanding what determines tourism satisfaction can be particularly useful for both policy makers and destination marketers. Satisfaction is indeed a necessary condition to ensure repeat visitation or, at least, positive word-of-mouth. Getting a better insight on these topics can therefore be extremely useful to understand whether cities are positioning themselves competitively in the tourism market. In the last 20 years, tourism has become an integral part of the so called 'experience economy': for the holidaymaker, the tourism experience is of high personal value and is accompanied with satisfying and pleasurable emotions. The destination's 'basic' offerings (e.g. accommodation, information services) are not sufficient anymore at fully satisfying tourists. Emotional reactions to the tourism experience are fundamental determinants of satisfaction and post-consumption behaviors such as willingness to come back and intention to recommend. Apart from some exceptions, however, research on the experiential dimensions of the tourism offerings remains largely underexplored. Academic authors have mainly focused on satisfaction with 'physical' destination attributes, with little evidence being available about 'immaterial' factors affecting tourists' satisfaction. This thesis wants address the following research questions: what does determine visitor satisfaction in a tourism destination? Is the emotional dimension of a tourism destination a signification determinant of visitor satisfaction? The city of Mons was chosen to empirically answer these questions. Mons - a medium size city, counting around 95,000 inhabitants and located in a former industrial region in Belgium ('Le Centre' - is the European Capital of Culture (ECoC) 2015. As part of Mons 2015, a new tourism strategy was devised aiming at boosting both cultural and business tourism. This strategy wants to build on the potential echo of this mega-event to attract at least 500,000 visitors by 2015, compared to 250,000 in 2011. The modelling strategy used in this thesis draws on Structural Equation Modelling (SEM) with the objective to explore the relationships between four constructs, namely: perceived emotional quality, perceived quality of the destination's offerings, overall satisfaction and post-consumption behavior. The model was tested on a sample of 297 visitors selected randomly at major tourist locations in Mons from January until June 2015. The results confirm that both the perceived quality of the destination's offerings and perceived quality of the emotional experience are significant predictors of visitor satisfaction, with a stronger effect of 'emotional quality'. The parameter estimate for the relationship between visitor satisfaction and post consumption behavior is also strong and positive. However, we have to reject the hypothesis according to which the perceived emotional and functional quality would impact on destination loyalty.

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Dissertation
Classification of Flight Safety Data
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Year: 2015 Publisher: Leuven : KU Leuven. Faculteit Wetenschappen

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Safety has always been of great importance in air travel. In recent years, a large amount of data are accumulated in the aviation industry, from everyday routine operations. These are analyzed in order to provide useful knowledge that could assist the improvement of aviation safety. During a flight a large amount of parameters are recorded, based on which, events are identified. An event is triggered when certain parameters exceed pre-determined limits, indicating that the aircraft does not operate within the airlines standard operation procedures. The analysis of flight event data provide useful information that can be used to assist the evaluation of daily operations and the performance of the flight's crew. Currently, Flight Safety Investigators analyze the events triggered during each single flight in order to identify specific flights exhibiting characteristics meriting further investigation. The purpose of this study was to create a classification model that mimics the behavior of the Flight Safety Investigator and classifies the flights in two categories, the first containing flights that require further investigation and the second flights that do not. The amount of flights that actually require further investigation is significantly lower than those that do not, therefore one of the two classification categories in the dataset appears rarely. In this study we explored different data mining methods that could be applied in imbalanced datasets in order to create an accurate classification model, focusing on the flights that do require an investigation. The methodology followed was divided in three steps, initially, the most informative variables were identified and then three different classification models were investigated and compared according to their performance, emphasizing on the correct classification of the flights that require investigation. During this process certain events were identified that have a great influence on the decision whether a flight requires further investigation or not. In general, models containing more variables provided better predictive results, in terms of both classification categories. Concluding this study, the use of class-weighted support vector machines was identified as the most effective model for the classification of flight safety data.

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