Wheat is one of the most grown crops in the world. The yield of the wheat can be reduced by fungal infections, like the powdery mildew. The prediction of infestations, that can endanger the yield, is of corresponding importance. This report presents an approach to predict such infestation events in a spatial and temporal dimension, considering hourly weather and longtime climate data. Furthermo...

We consider an M/G/1 retrial queue with general retrial times and single working vacation. During the working vacation period, customers can be served at a lower rate. Both service times in a vacation period and in a service period are generally distributed random variables. Using supplementary variable method we obtain the probability generating function for the number of customers and the ave...

Cephalometric analysis is commonly used as a standard tool for orthodontic diagnosis and treatment planning. The identification of cephalometric landmarks on images of the skull allows the quantification and classification of anatomical abnormalities. In clinical practice, the landmarks are placed manually which is time-consuming and subjective. This work investigates the application of Random ...

Since the pioneering works of C.C. Heyde, A.V. Nagaev, and S.V. Nagaev in 1960’s and 1970’s, the precise asymptotic behavior of large-deviation probabilities of sums of heavy-tailed random variables has been extensively investigated by many people, but mostly it is assumed that the random variables under discussion are independent. In this paper, we extend the study to the case of negatively de...

We describe the approach that we submitted to the 2015 PAN competition [7] for the author identification task. The task consists in determining if an unknown document was authored by the same author of a set of documents with the same author. We propose a machine learning approach based on a number of different features that characterize documents from widely different points of view. We constr...

We consider the problem of data-stream classification, introducing a stream-classification algorithm, Dynamic Streaming Random Forests, that is able to handle evolving data streams using an entropy-based drift-detection technique. The algorithm automatically adjusts its parameters based on the data seen so far. Experimental results show that the algorithm handles multi-class problems for which ...

Major severe weather events can cause a significant loss of life and property. We seek to revolutionize our understanding of and ability to predict such events through the mining of severe weather data. Because weather is inherently a spatiotemporal phenomenon, mining such data requires a model capable of representing and reasoning about complex spatiotemporal dynamics, including temporally and...

In this paper we present our approach to extract profile information from anonymized tweets for the author profiling task at PAN 2015 [10]. Particularly we explore the versatility of random forest classifiers for the genre and age groups information and random forest regressions to score important aspects of the personality of a user. Furthermore we propose a set of features tailored for this t...