AbstractOne of the most important changes in observational astronomy of the 21st Century is a rapid shift from classical object-by-object observations to extensive automatic surveys. As CCD detectors are getting better and their prices are getting lower, more and more small and medium-size observatories are refocusing their attention to detection of stellar variability through systematic sky-scanning missions. This trend is aditionally powered by the success of pioneering surveys such as ASAS, DENIS, OGLE, TASS, their space counterpart Hipparcos and others. Such surveys produce massive amounts of data and it is not at all clear how these data are to be reduced and analysed. This is especially striking in the eclipsing binary (EB) field, where most frequently used tools are optimized for object-by-object analysis. A clear need for thorough, reliable and fully automated approaches to modeling and analysis of EB data is thus obvious. This task is very difficult because of limited data quality, non-uniform phase coverage and solution degeneracy. This paper reviews recent advancements in putting together semi-automatic and fully automatic pipelines for EB data processing. Automatic procedures have already been used to process Hipparcos data, LMC/SMC observations, OGLE and ASAS catalogs etc. We discuss the advantages and shortcomings of these procedures.
Modeling and Analysis of Uplink Non-Orthogonal Multiple Access (NOMA) in Large-Scale Cellular Networks Using Poisson Cluster Processes