The effectiveness of an orthogonal to backward mean transformation is investigated in the context a non-stationary panel data model. It shown that corresponding estimator as efficient Transformed Maximum Likelihood when autoregressive parameter equal unity. Furthermore, recently introduced bias-corrected version almost Pooled Least Squares estimator.

Discrete Wavelet Transform is a data transformation method that represents in the time domain and frequency domain. This appears to overcome weakness of Fourier transform which only able provide one information limited certain windowing . The type wavelet used Haar Wavelet. Identification periodicity using Periodogram analysis with Fisher's Test statistics. transformed decomposed into two compo...

The development of technological solutions satisfying nondiscriminatory requirements is one the main current challenges for data processing. Back-end operators preparing, i.e., extracting and transforming, play a relevant role w.r.t. nondiscrimination, since they can introduce bias with an impact on entire life-cycle. In this article, we focus back-end transformations , defined in terms Select-...

As economies become increasingly data-driven, big data technologies and software products are turning into key tools for managing technological processes in real time more efficient delivery of public services to citizens. The change the interaction between state society implies creation a unified digital ecosystem, centered around data. Such paradigm calls rethinking administration principles ...

Recent data protection laws in the EU institutionalise NGO engagement with regulators and enable new mechanisms for bottom-up policy implementation. The article studies thirteen European NGOs maps their contribution to implementation based on a novel typology understanding scope (national vs. transnational) goals (direct strategic) of actions. asks: (1) how do vary privacy Europe? (2) what are ...