Titlebook: Data Science: New Issues, Challenges and Applications; Gintautas Dzemyda,Jolita Bernatavi?ien?,Janusz Kac Book 2020 Springer Nature Switze

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Data Analysis in Setting Action Plans of Telecom Operators,ull development and it opens opportunities for operators, institutions or for the public, potentially consuming such services. Telecom operators are particularly well positioned to begin to capitalize on this opportunity and build a distinct position in the market for defining suitable value proposa

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Extending Model-Driven Development Process with Causal Modeling Approach,), and some other types of complex systems. Causality is an important concept in modeling; it helps to reveal the properties of the domain hidden from the outside observer. Great results of CPS engineering based on the perceived causality of specific domain—physical system. The subject domain of the

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Investigating Feature Spaces for Isolated Word Recognition,on deep learning techniques. The approach combines Convolutional Neural Networks (CNNs) and time-frequency signal representation converted to the investigated feature spaces. In particular, waveforms and fractal dimension features of the signal were chosen for the time domain, and three feature spac

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Developing Algorithmic Thinking Through Computational Making,s necessary for digital learners. However, it is still a challenge for educators to teach CT in an attractive way for learners, also to find support to CT teaching content design and assessment. To address this problem, the literature review on CT in education was conducted and the main ideas of CT

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Zerocross Density Decomposition: A Novel Signal Decomposition Method,hod is based on the histogram of zero-crosses of a signal across different scales. We discuss the main properties of ZCD and parameters of ZCD modes (statistical characteristics, principal frequencies and energy distribution) and compare it with well-known Empirical Mode Decomposition (EMD). To anal