On the Prediction of Visibility for Deep-Sky Objects
نویسنده
چکیده
Knowing in advance the visibility of a given object is important when planning an observation. New amateurs usually search only bright objects since they present smaller difficulties for finding and observing them, except perhaps under severe conditions (e.g., city, full moon). Nevertheless, amateurs gradually extend their observations to more challenging targets, fainter and more elusive. These objects, being more difficult, can offer dramatically different images depending on the telescope aperture and sky quality. Therefore, to predict with certain accuracy the difficulty that an observation will involve may become a puzzling task. Most observers estimates the possibilities of observing a celestial object in a subjective way, depending on experience in handling their telescopes and knowledge on deep-sky objects. It would be however convenient to have a more objective tool to decide whether a given object will be visible or not.
منابع مشابه
DASTWAR: a tool for completeness estimation in magnitude-size plane
Today, great observatories around the world, devote a substantial amount of observing time to sky surveys. The resulted images are inputs of source finder modules. These modules search for the target objects and provide us with source catalogues. We sought to quantify the ability of detection tools in recovering faint galaxies regularly encountered in deep surveys. Our approach was based on com...
متن کاملInvestigation of the daily minimum visibility meteorological conditions using RVR data at IKA airport during 2013-2014
Investigation of the daily minimum visibility meteorological conditions using RVR data at IKA airport during 2013-2014 Hatami, J. 1, Sabetghadam, S. 2*, Ahmadi-Givi, F. 3 1M.Sc. Student, Institute of Geophysics, University of Tehran 2Assistant Professor, Institute of Geophysics, University of Tehran 3Associate Professor, Institute of Geophysics, University of Tehran Abstract Atmospher...
متن کاملShort term electric load prediction based on deep neural network and wavelet transform and input selection
Electricity demand forecasting is one of the most important factors in the planning, design, and operation of competitive electrical systems. However, most of the load forecasting methods are not accurate. Therefore, in order to increase the accuracy of the short-term electrical load forecast, this paper proposes a hybrid method for predicting electric load based on a deep neural network with a...
متن کاملPrediction of earing in deep drawing of anisotropic aluminum alloy sheet using BBC2003 yield criterion
This paper investigates the earing phenomenon in deep drawing of AA3105 aluminum alloy, experimentally and numerically. Earing defect is mainly attributed to the plastic anisotropy of sheet metal. In order to control such defect, predicting the evolution of ears in sheet metal forming analyses becomes indispensable. In this regard, the present study implements the advanced yield criterion BBC20...
متن کاملLink Prediction using Network Embedding based on Global Similarity
Background: The link prediction issue is one of the most widely used problems in complex network analysis. Link prediction requires knowing the background of previous link connections and combining them with available information. The link prediction local approaches with node structure objectives are fast in case of speed but are not accurate enough. On the other hand, the global link predicti...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2000