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Upcoming Features of SPLAT-VO in Astroinformatics
Šaloun, P. ; Andrešič, D. ; Škoda, Petr ; Zelinka, I.
During last decade was developed fully automatized (robotic) class of telescopes, that produce huge amount of data per each night. Amount of recorded data is usually in the scale of petabytes. To process properly all data and select an important events it is needed to use sophisticated software methods and algorithms. It caused an appearance of a new field of science - astroinformatics. In this paper we introduce a small part of our contribution to the astroinformatics field - a specialized software SPLAT-VO. It is used for processing and visualization of astrophysical data generated by nonlinear, complex or even chaotic processes in the space. Overview of new features so far prepared for new version of SPLAT-VO. The overview is focused on enhancements of user experience, work with SAMP protocol and other interoperability that improves work with global list of spectra, plot window and analysis menu.
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Wavelet Based Feature Extraction for Clustering of Be Stars
Bromová, P. ; Škoda, Petr ; Zendulka, J.
The goal of our work is to create a feature extraction method for classification of Be stars. Be stars are characterized by prominent emission lines in their spectrum. We focus on the automated classification of Be stars based on typical shapes of their emission lines. We aim to design a reduced, specific set of features characterizing and discriminating the shapes of Be lines. In this paper, we present a feature extraction method based on the wavelet transform and its power spectrum. Both the discrete and continuous wavelet transform are used. Different feature vectors are created and compared on clustering of Be stars spectra from the archive of the Astronomical Institute of the Academy of Sciences of the Czech Republic. The clustering is performed using the kmeans algorithm. The results of our method are promising and encouraging to more detailed analysis.
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Characteristics of the Chen Attractor
Augustová, Petra ; Beran, Zdeněk
Within the paper a mathematical representation of the so-called Chen model is described as a particular parametric three-dimensional chaotic dynamical system, i.e. a system of three nonlinear differential equations evolving in time. The main aim of this paper is to find for the Chen system the properties that are known for the Lorenz system and its famous Lorenz attractor. First, the integrals of motion are derived for some parameters of the Chen system. The integrals of motions play an important role in physics, e.g. for conservation laws. Next, the shape of the global attractor of this system is approximated by volumes that contain the attractor. The shape predicts the future behavior of the system. To obtain these results, the already proved fact that the Chen system is a continued transition of the Lorenz system is used. According to our knowledge, the same approach of shifting the known facts about the Lorenz system to a newdynamical system, the Chen system in this context, has not been presented yet.
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Message Embedded Synchronization for the Generalized Lorenz System and Its Use for Chaotic Masking
Čelikovský, Sergej ; Lynnyk, Volodymyr
This paper implements and analyzes the well-known message embedded synchronization scheme for the case of the generalized Lorenz system. Such a synchronization may be used for chaotic masking scheme using a single channel only. This method was already discussed in the earlier literature for the particular classes of systems. In this paper, a more general class wheremessage embedded synchronization is possible is described. Then, it is shown that the generalized Lorenz system falls within that class. Furthermore, using the resulting synchronization, the novel secure encryption scheme is proposed. It requires very reasonable amount of data to encrypt and time to decrypt one bit. Basically, to encrypt one bit, only one iteration (i.e. only one real number of 6 valid digits) is needed. At the same time, 100 percent of the carrying chaotic signal can be used. The method is also demonstrated by numerical simulations of a digital data encryption and decryption.
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