While it is usually not difficult to compute principal curvatures of a smooth surface of sufficient differentiability, it is a rather difficult task when only a polygonal approximation of the surface is available, because of the inherent ambiguity of such representation. A number of different approaches has been proposed in the past that tackle this problem using various techniques. Most papers tend to focus on a particular method, while an comprehensive comparison of the different approaches is usually missing. We present results of a large experiment, involving both common and recently proposed curvature estimation techniques, applied to triangle meshes of varying properties. It turns out that none of the approaches provides reliable results under all circumstances. Motivated by this observation, we investigate mesh statistics, which can be computed from vertex positions and mesh connectivity information only, and which can help in deciding which estimator will work best for a particular case. Finally, we propose a meta‐estimator, which makes a choice between existing algorithms based on the value of the mesh statistics, and we demonstrate that such meta‐estimator, despite its simplicity, provides considerably more robust results than any existing approach.

Purpose The purpose of this paper is to examine and verify the competitive intelligence tools Alexa and SimilarWeb, which are broadly used for website traffic data estimation. Tested tools belong to the state of the art in this area. Design/methodology/approach The authors use quantitative approach. Research was conducted on a sample of Czech websites for which there are accurate traffic data values, against which the other data sets (less accurate) provided by Alexa and SimilarWeb will be compared. Findings The results show that neither tool can accurately determine the ranking of websites on the internet. However, it is possible to approximately determine the significance of a particular website. These results are useful for another research studies which use data from Alexa or SimilarWeb. Moreover, the results show that it is still not possible to accurately estimate website traffic of any website in the world. Research limitations/implications The limitation of the research lies in the fact that it was conducted solely in the Czech market. Originality/value Significant amount of research studies use data sets provided by Alexa and SimilarWeb. However, none of these research studies focus on the quality of the website traffic data acquired by Alexa or SimilarWeb, nor do any of them refer to other studies that would deal with this issue. Furthermore, authors describe approaches to measuring website traffic and based on the analysis, the possible usability of these methods is discussed.

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Abstract. Automatic methods for identifying and tracking cyclones were firstly constructed in 1990's and since then there was a big increase in a precision and probability of detection. These methods have been traditionally focused on cyclones (and particularly on tropical cyclones), but the question of anticyclone centers detection remained unsolved since they are usually not a source of turbulent weather, precipitation etc. However, this issue can be important in the era of the climate change. In this paper, an algorithm for an automatic detection of both, cyclones and anticyclones based on mean sea level pressure field, is presented. The algorithm uses two-dimensional raster data as an input and returns a list of detected pressure systems. The main advantages of our solution are easy implementation since it is based on the standard image processing algorithm, sufficient performance of the algorithm, and especially the possibility of high-pressure systems detection. Moreover, the presented solution does not need a direct terrain filtering needed for some algorithms to be done. To validate the quality of detection algorithm results, a comparison against manually prepared data by Met Office was used. It follows from the comparison that the presented algorithm produces results similar to those by Met Office. The most significant differences can be found in the detection of cyclones at the beginning or the end of the lifespan stage. Met Office detects more cyclones in these stages than the presented solution.

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