43,554 research outputs found

    Fundamentals and applications of order dependencies

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    Business-intelligence queries often involve SQL functions and algebraic expressions. There can be clear semantic relationships between a column's values and the values of a function over that column. A common property is monotonicity: as the column's values ascend, so do the function's values (or the other column's values). This we call an order dependency (OD). Queries can be evaluated more efficiently when the query optimizer uses order dependencies. They can be run even faster when the optimizer can also reason over known ODs to infer new ones. Order dependencies can be declared as integrity constraints, and they can be detected automatically for many types of SQL functions and algebraic expressions. We present optimization techniques using ODs for queries that involve join, order by, group by, partition by, and distinct. Essentially, ODs can further exploit interesting orders to eliminate or simplify potentially expensive sorts in the query plan. We evaluate these techniques over our prototype implementation in IBM® DB2® using the TPC-DS® benchmark schema and some customer inspired queries. Our experimental results demonstrate a significant performance gain. Dependencies have played an important role in database theory. We study the theoretical aspects of order dependencies-and unidirectional order dependencies (UODs), a proper sub-class of ODs-which describe the relationships among lexicographical orderings of sets of tuples. We investigate the inference problem for order dependencies. We establish the following: (i) a sound and complete axiomatization for UODs which is sound for ODs; (ii) a hierarchy of order dependency classes; (iii) a proof of co-NP-completeness of the inference problem for ODs and for the subclass of UODs; (iv) a proof of co-NP-completeness of the inference problem of functional dependencies (FDs) from ODs in general, but demonstrate linear time complexity for the inference of FDs from UODs; (v) a sound and complete elimination procedure for testing logical implication over ODs; and (vi) a sound and complete polynomial inference algorithm for sets of UODs over natural domains

    Key courses of academic curriculum uncovered by data mining of students' grades

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    Learning is a complex cognitive process that depends not only on an individual capability of knowledge absorption but it can be also influenced by various group interactions and by the structure of an academic curriculum. We have applied methods of statistical analyses and data mining (Principal Component Analysis and Maximal Spanning Tree) for anonymized students' scores at Faculty of Physics, Warsaw University of Technology. A slight negative linear correlation exists between mean and variance of course grades, i.e. courses with higher mean scores tend to possess a lower scores variance. There are courses playing a central role, e.g. their scores are highly correlated to other scores and they are in the centre of corresponding Maximal Spanning Trees. Other courses contribute significantly to students' score variance as well to the first principal component and they are responsible for differentiation of students' scores. Correlations of the first principal component to courses' mean scores and scores variance suggest that this component can be used for assigning ECTS points to a given course. The analyse is independent from declared curricula of considered courses. The proposed methodology is universal and can be applied for analysis of student's scores and academic curriculum at any faculty

    Financing asset growth : [version 11 august 2013]

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    In this paper we provide new evidence that corporate financing decisions are associated with managerial incentives to report high equity earnings. Managers rely most heavily on debt to finance their asset growth when their future earnings prospects are poor, when they are under pressure due to past declines in earnings, negative past stock returns, and excessively optimistic analyst earnings forecasts, and when the earnings yield is high relative to bond yields so that from an accounting perspective equity is ‘expensive’. Managers of high debt issuing firms are more likely to be newly appointed and also more likely to be replaced in subsequent years. Abnormal returns on portfolios formed on the basis of asset growth and debt issuance are strongly positively associated with the contemporaneous changes in returns on assets and on equity as well as with earnings surprises. This may account for the finding that debt issuance forecasts negative abnormal returns, since debt issuance also forecasts negative changes in returns on assets and on equity and negative earnings surprises. Different mechanisms appear to be at work for firms that retire debt

    Observation and Assignment of Silent and Higher Order Vibrations in the Infrared Transmission of C60 Crystals

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    We report the measurement of infrared transmission of large C60 single crystals. The spectra exhibit a very rich structure with over 180 vibrational absorptions visible in the 100 - 4000 cm-1 range. Many silent modes are observed to have become weakly IR-active. We also observe a large number of higher order combination modes. The temperature (77K - 300K) and pressure (0 - 25KBar) dependencies of these modes were measured and are presented. Careful analysis of the IR spectra in conjunction with Raman scattering data showing second order modes and neutron scattering data, allow the selection of the 46 vibrational modes C60. We are able to fit *all* of the first and second order data seen in the present IR spectra and the previously published Raman data (~300 lines total), using these 46 modes and their group theory allowed second order combinations.Comment: REVTEX v3.0 in LaTeX. 12 pages. 8 Figures by request. c60lon

    A Call to Arms: Revisiting Database Design

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    Good database design is crucial to obtain a sound, consistent database, and - in turn - good database design methodologies are the best way to achieve the right design. These methodologies are taught to most Computer Science undergraduates, as part of any Introduction to Database class. They can be considered part of the "canon", and indeed, the overall approach to database design has been unchanged for years. Moreover, none of the major database research assessments identify database design as a strategic research direction. Should we conclude that database design is a solved problem? Our thesis is that database design remains a critical unsolved problem. Hence, it should be the subject of more research. Our starting point is the observation that traditional database design is not used in practice - and if it were used it would result in designs that are not well adapted to current environments. In short, database design has failed to keep up with the times. In this paper, we put forth arguments to support our viewpoint, analyze the root causes of this situation and suggest some avenues of research.Comment: Removed spurious column break. Nothing else was change

    Studies of the dose-effect relation

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    Dose-effect relations and, specifically, cell survival curves are surveyed with emphasis on the interplay of the random factors — biological variability, stochastic reaction of the cell, and the statistics of energy deposition —that co-determine their shape. The global parameters mean inactivation dose, , and coefficient of variance, V, represent this interplay better than conventional parameters. Mechanisms such as lesion interaction, misrepair, repair overload, or repair depletion have been invoked to explain sigmoid dose dependencies, but these notions are partly synonymous and are largely undistinguishable on the basis of observed dose dependencies. All dose dependencies reflect, to varying degree, the microdosimetric fluctuations of energy deposition, and these have certain implications, e.g. the linearity of the dose dependence at small doses, that apply regardless of unresolved molecular mechanisms of cellular radiation action

    Using concept lattices to mine functional dependencies

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    Concept Lattices have been proved to be a valuable tool to represent the knowlegde in a database. In this paper we show how functional dependencies in databases can be extracted using Concept Lattices, not preprocessing the original database, but providing a new closure operator. We also prove that this method generalizes the previous methods and closure operators that are being used to find association rules in binary databases.Postprint (published version
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