Construction of a century solar chromosphere data set for solar activity related research
Линь ГанхуаLin Gang-huaВан Сяо-ФаньWang Xiao FanЯн СяоXiao YangЛю СоSuo LiuЧжан МэйMei ZhangВан ХайминьHaimin WangSumei LiChang LiuСюй ЯньYan XuA. TlatovA. TlatovM. L. DemidovM. L. DemidovАлександр БоровикАлександр БоровикАлексей ГоловкоA. A. Golovko
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This article introduces our ongoing project “Construction of a Century Solar Chromosphere Data Set for Solar Activity Related Research”. Solar activities are the major sources of space weather that affects human lives. Some of the serious space weather consequences, for instance, include interruption of space communication and navigation, compromising the safety of astronauts and satellites, and damaging power grids. Therefore, the solar activity research has both scientific and social impacts. The major database is built up from digitized and standardized film data obtained by several observatories around the world and covers a timespan more than 100 years. After careful calibration, we will develop feature extraction and data mining tools and provide them together with the comprehensive database for the astronomical community. Our final goal is to address several physical issues: filament behavior in solar cycles, abnormal behavior of solar cycle 24, large-scale solar eruptions, and sympathetic remote brightenings. Significant progresses are expected in data mining algorithms and software development, which will benefit the scientific analysis and eventually advance our understanding of solar cycles.Keywords:
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Collected data must be organized to be utilized efficiently, and hierarchical classification of data is efficient approach to organize data. When data is classified to multiple categories or annotated with a set of labels, users request multi-labeled data by giving a set of labels. There are several interpretations of the data expressed by a set of labels. This paper discusses which data is expressed by a set of labels by introducing orders for sets of labels and shows that there are four types of orders, which are characterized by whether the labels of expressed data includes every label of the given set of labels within the range of the set. Desirable properties of the orders, data is also expressed by the higher set of labels and different sets of labels express different data, are discussed for the orders. Keywords—Classification Hierarchies, Multi-labeled Data, Multiple Classificaiton, Orders of Sets of Labels
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The objective of this paper is to use data from the highest level in men's tennis to assess whether there is any evidence to reject the hypothesis that the two players in a match have a constant probability of winning each set in the match. The data consists of all 4883 matches of grand slam men's singles over a 10 year period from 1995 to 2004. Each match is categorised by its sequence of win (W) or loss (L) (in set 1, set 2, set 3,...) to the eventual winner. Thus, there are several categories of matches from WWW to LLWWW. The methodology involves fitting several probabilistic models to the frequencies of the above ten categories. One four-set category is observed to occur significantly more often than the other two. Correspondingly, a couple of the five-set categories occur more frequently than the others. This pattern is consistent when the data is split into two five-year subsets. The data provides significant statistical evidence that the probability of winning a set within a match varies from set to set. The data supports the conclusion that, at the highest level of men's singles tennis, the better player (not necessarily the winner) lifts his play in certain situations at least some of the time. Key PointsUsing grand slam men's singles data, the probability of winning a set has been shown to vary from set to set.The data provides statistical evidence that the better player (not necessarily the winner) in some matches is able to lift his play in certain situations. This result gives encouragement to the better player when in difficulties in a match.The authors found no evidence that the weaker player was able to lift his play. The weaker player, when ahead in a match, should be on his guard for his opponent to have a real capacity to lift his game.
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xcollapse is an extended version of collapse, which creates a data set with one observation per combination of values of a list of variables in the existing data set and new variables containing summary statistics of other variables (eg means) in each combination. xcollapse allows the user to choose the destination of the output data set, which may either be listed to the Stata log, or saved to a disk file, or written to the memory (overwriting any existing data set).
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Abstract We open a source program written in C to generate an input data set for the set covering problem. We explain how it generates a benchmark input data set with service programs to convert it into MPS/X formatted data set, LINGO formatted data set and List formatted data set. We also present source programs to convert List formatted data set into our data set on our web site. We think that researchers who want to make up good algorithms to approximately solve the set covering problem will find our work helpful for them because our work will let them concentrate their powers on developing good algorithms to approximately solve the set covering problem.
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This article introduces the High School and Beyond (HS&B) data set to bilingual education researchers. The special inclusion of the Hispanic population, the largest language minority in the U. S., will enable researchers to carry out detailed analyses on that population. In addition, the HS&B data set contains information from the students, parents, teachers, and school administrators, thus providing needed variables to test the validity of many of the heated arguments surrounding bilingual education. After describing the variables and the complicated file structures of the HS&B data set, this article concludes that despite its sample constraints, it will be an invaluable set of resources for researchers in bilingual education.
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Is the solar chromosphere always hot, with relatively small temperature variations (δT/T ~ 0.1), or is it cold most of the time, with temperature fluctuations that reach δT/T ~ 10 at the top of the chromosphere? Or, equivalently, is the chromosphere heated continually or only for a few seconds once every 3 minutes? Two types of empirical model, one essentially time independent and always hot, the other highly time dependent and mostly cold, come to fundamentally different conclusions. This paper analyzes the time-dependent model of the quiet, nonmagnetic chromosphere by Carlsson & Stein and shows that it predicts deep absorption lines, none of which are observed; intensity fluctuations in the Lyman continuum that are much larger than observed; and time-averaged emission that falls far short of the observed emission. The paper concludes that the solar chromosphere, while time-dependent, is never cold and dark. The same conclusion applies for stellar chromospheres. A complete, time-dependent model of the nonmagnetic chromosphere must describe two phenomena: (1) dynamics, like that modeled by Carlsson & Stein for chromospheric bright points but corrected for the geometrical properties of shocks propagating in an upward-expanding channel, and (2) the energetically more important general, sustained heating of the chromosphere, as described by current time-independent empirical models but modified in the upper photosphere for the formation of molecular absorption lines of CO in a dynamical medium. This model is always hot and, except for absorption features caused by departures from local thermodynamic equilibrium, shows chromospheric lines only in emission.
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Collected data must be organized to be utilized efficiently, and hierarchical classification of data is efficient approach to organize data. When data is classified to multiple categories or annotated with a set of labels, users request multi-labeled data by giving a set of labels. There are several interpretations of the data expressed by a set of labels. This paper discusses which data is expressed by a set of labels by introducing orders for sets of labels and shows that there are four types of orders, which are characterized by whether the labels of expressed data includes every label of the given set of labels within the range of the set. Desirable properties of the orders, data is also expressed by the higher set of labels and different sets of labels express different data, are discussed for the orders. Keywords—Classification Hierarchies, Multi-labeled Data, Multiple Classificaiton, Orders of Sets of Labels
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This article introduces the High School and Beyond (HS&B) data set to bilingual education researchers. The special inclusion of the Hispanic population, the largest language minority in the U. S., will enable researchers to carry out detailed analyses on that population. In addition, the HS&B data set contains information from the students, parents, teachers, and school administrators, thus providing needed variables to test the validity of many of the heated arguments surrounding bilingual education. After describing the variables and the complicated file structures of the HS&B data set, this article concludes that despite its sample constraints, it will be an invaluable set of resources for researchers in bilingual education.
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