AMBER on the VLTI: data processing and calibration issues

We present here the current performances of the AMBER / VLTI instrument for standard use and compare these with the offered modes of the instrument. We show that the instrument is able to reach its specified precision only for medium and high spectral resolution modes, differential observables and bright objects. For absolute observables, the current achievable accuracy is strongly limited by the vibrations of the Unit Telescopes, and also by the observing procedure which does not take into account the night-long transfer function monitoring. For low-resolution mode, the current limitation is more in the data reduction side, since several effects negligible at medium spectral resolution are not taken into account in the current pipeline. Finally, for faint objects (SNR around 1 per spectral channel), electromagnetic interferences in the VLTI interferometric laboratory with the detector electronics prevents currently to get unbiased measurements. Ideas are under study to correct in the data processing side this effect, but a hardware fix should be investigated seriously since it limits seriously the effective limiting magnitude of the instrument.Comment: 10 page

How Smart Operations Help Better Planning and Replenishment?

This chapter discusses various roles of smart information in Supply Chains (SC) of digital age and tries to answer an important question - What types of collaborative arrangements facilitate smart operations to improve planning, production and timely replenishment? We have conducted longitudinal case studies with firms practicing SC collaborations and also using smart information for operations. Based on the case analysis, the companies are further classified as 'smart planning' and 'traditional planning'. Research findings show the importance of aligning SC partnerships based on smart information requirements. These findings are based on case studies of Indian firms with global SC collaboration. We also discuss the role of Big Data for the companies using smart planning

Partial feild data of Tarmin desert, Xinjiang China

       Because of desert geologic features, high-frequency signals and noise are absorbed by soft covering layer, low-frequency signals are mixed with the same frequency noise, and the seismic data characteristics are extremely complicatedBecause of desert geologic features, high-frequency signals and noise are absorbed by soft covering layer, low-frequency signals are mixed with the same frequency noise, and the seismic data characteristics are extremely complicated.</p