Materialized view selection under the maintenance time constraint

A data warehouse is a data repository which collects and maintains a large amount of data from multiple distributed, autonomous and possibly heterogeneous data sources. Often the data is stored in the form of materialized views in order to provide fast access to the integrated data. One of the most important decisions in designing a data warehouse is the selection of views for materialization. The objective is to select an appropriate set of views that minimizes the total query response time with the constraint that the total maintenance time for these materialized views is within a given bound. This view selection problem is totally different from the view selection problem under the disk space constraint. In this paper the view selection problem under the maintenance time constraint is investigated. Two efficient, heuristic algorithms for the problem are proposed. The key to devising the proposed algorithms is to define good heuristic functions and to reduce the problem to some well-solved optimization problems. As a result, an approximate solution of the known optimization problem will give a feasible solution of the original problem. (C) 2001 Elsevier Science B.V. All rights reserved.

The SB-index and the HSB-index: efficient indices for spatial data warehouses

Spatial data warehouses (SDWs) allow for spatial analysis together with analytical multidimensional queries over huge volumes of data. The challenge is to retrieve data related to ad hoc spatial query windows according to spatial predicates, avoiding the high cost of joining large tables. Therefore, mechanisms to provide efficient query processing over SDWs are essential. In this paper, we propose two efficient indices for SDW: the SB-index and the HSB-index. The proposed indices share the following characteristics. They enable multidimensional queries with spatial predicate for SDW and also support predefined spatial hierarchies. Furthermore, they compute the spatial predicate and transform it into a conventional one, which can be evaluated together with other conventional predicates by accessing a star-join Bitmap index. While the SB-index has a sequential data structure, the HSB-index uses a hierarchical data structure to enable spatial objects clustering and a specialized buffer-pool to decrease the number of disk accesses. The advantages of the SB-index and the HSB-index over the DBMS resources for SDW indexing (i.e. star-join computation and materialized views) were investigated through performance tests, which issued roll-up operations extended with containment and intersection range queries. The performance results showed that improvements ranged from 68% up to 99% over both the star-join computation and the materialized view. Furthermore, the proposed indices proved to be very compact, adding only less than 1% to the storage requirements. Therefore, both the SB-index and the HSB-index are excellent choices for SDW indexing. Choosing between the SB-index and the HSB-index mainly depends on the query selectivity of spatial predicates. While low query selectivity benefits the HSB-index, the SB-index provides better performance for higher query selectivity.

Decision-making algorithms in geometric modelling

Many of the applications of geometric modelling are concerned with the computation of well-defined properties of the model. The applications which have received less attention are those which address questions to which there is no unique answer. This thesis describes such an application: the automatic production of a dimensioned engineering drawing. One distinctive feature of this operation is the requirement for sophisticated decision-making algorithms at each stage in the processing of the geometric model. Hence, the thesis is focussed upon the design, development and implementation of such algorithms. Various techniques for geometric modelling are briefly examined and then details are given of the modelling package that was developed for this project, The principles of orthographic projection and dimensioning are treated and some published work on the theory of dimensioning is examined. A new theoretical approach to dimensioning is presented and discussed. The existing body of knowledge on decision-making is sampled and the author then shows how methods which were originally developed for management decisions may be adapted to serve the purposes of this project. The remainder of the thesis is devoted to reports on the development of decision-making algorithms for orthographic view selection, sectioning and crosshatching, the preparation of orthographic views with essential hidden detail, and two approaches to the actual insertion of dimension lines and text. The thesis concludes that the theories of decision-making can be applied to work of this kind. It may be possible to generate computer solutions that are closer to the optimum than some man-made dimensioning schemes. Further work on important details is required before a commercially acceptable package could be produced.

Context tree selection: A unifying view

Context tree models have been introduced by Rissanen in [25] as a parsimonious generalization of Markov models. Since then, they have been widely used in applied probability and statistics. The present paper investigates non-asymptotic properties of two popular procedures of context tree estimation: Rissanen's algorithm Context and penalized maximum likelihood. First showing how they are related, we prove finite horizon bounds for the probability of over- and under-estimation. Concerning overestimation, no boundedness or loss-of-memory conditions are required: the proof relies on new deviation inequalities for empirical probabilities of independent interest. The under-estimation properties rely on classical hypotheses for processes of infinite memory. These results improve on and generalize the bounds obtained in Duarte et al. (2006) [12], Galves et al. (2008) [18], Galves and Leonardi (2008) [17], Leonardi (2010) [22], refining asymptotic results of Buhlmann and Wyner (1999) [4] and Csiszar and Talata (2006) [9]. (C) 2011 Elsevier B.V. All rights reserved.

A unified view on lifetime distributions arising from selection mechanisms

In this paper, we formulate a flexible density function from the selection mechanism viewpoint (see, for example, Bayarri and DeGroot (1992) and Arellano-Valle et al. (2006)) which possesses nice biological and physical interpretations. The new density function contains as special cases many models that have been proposed recently in the literature. In constructing this model, we assume that the number of competing causes of the event of interest has a general discrete distribution characterized by its probability generating function. This function has an important role in the selection procedure as well as in computing the conditional personal cure rate. Finally, we illustrate how various models can be deduced as special cases of the proposed model. (C) 2011 Elsevier B.V. All rights reserved.

SELECTION OF TRICHOGRAMMA PRETIOSUM LINEAGES FOR CONTROL OF GRAPHOLITA MOLESTA IN PEACH

Grapholita molesta (Lepidoptera: Tortricidae) is one of the main pests of peach trees in Brazil, causing fruit losses of 3-5%. Among possible biological control agents, Trichogramma pretiosum (Hymenoptera: Trichogrammatidae) has been found in peach orchards. Our objectives were to study the rearing of T pretiosum in eggs of G. molesta and Anagasta kuehniella (Lepidoptera: Pyralidae), and select lineages of this parasitoid that have the potential to control G. molesta. Selection of best lineages was made from 5 populations of T pretiosum collected from organically-cultivated peach orchards. The study was done under controlled temperature (25 +/- 2 degrees C), relative humidity (70 +/- 10%) and 14:10 h (light:dark) photoperiod conditions. Grapholita molesta eggs were found to be adequate hosts for the development of T pretiosum, and the parameters for number of parasitized eggs, percent parasitized eggs, and sex ratio were similar to those for A. kuehniella eggs. The highest rate of parasitism of G. molesta eggs occurred in eggs with up to 48 h of embryonic development. Among the lineages of T pretiosum that were collected, HO8, PO8, PEL, and L3M showed the best biological performance and are therefore indicated for semi-field and field studies for biological control of oriental fruit moth.

Does using stepwise variable selection to build sequential path analysis models make sense?

Causal inference methods - mainly path analysis and structural equation modeling - offer plant physiologists information about cause-and-effect relationships among plant traits. Recently, an unusual approach to causal inference through stepwise variable selection has been proposed and used in various works on plant physiology. The approach should not be considered correct from a biological point of view. Here, it is explained why stepwise variable selection should not be used for causal inference, and shown what strange conclusions can be drawn based upon the former analysis when one aims to interpret cause-and-effect relationships among plant traits.

Geographic variation and positive selection on M7 lysin, an acrosomal sperm protein in mussels (Mytilus spp.)

Successful fertilization in free-spawning marine organisms depends on the interactions between genes expressed on the surfaces of eggs and sperm. Positive selection frequently characterizes the molecular evolution of such genes, raising the possibility that some common deterministic process drives the evolution of gamete recognition genes and may even be important for understanding the evolution of prezygotic isolation and speciation in the marine realm. One hypothesis is that gamete recognition genes are subject to selection for prezygotic isolation, namely reinforcement. In a previous study, positive selection on the gene coding for the acrosomal sperm protein M7 lysin was demonstrated among allopatric populations of mussels in the Mytilus edulis species group (M. edulis, M. galloprovincialis, and M. trossulus). Here, we expand sampling to include M7 lysin haplotypes from populations where mussel species are sympatric and hybridize to determine whether there is a pattern of reproductive character displacement, which would be consistent with reinforcement driving selection on this gene. We do not detect a strong pattern of reproductive character displacement; there are no unique haplotypes in sympatry nor is there consistently greater population structure in comparisons involving sympatric populations. One distinct group of haplotypes, however, is strongly affected by natural selection and this group of haplotypes is found within M. galloprovincialis populations throughout the Northern Hemisphere concurrent with haplotypes common to M. galloprovincialis and M. edulis. We suggest that balancing selection, perhaps resulting from sexual conflicts between sperm and eggs, maintains old allelic diversity within M. galloprovincialis.

Weibull model selection for reliability modelling

A large number of models have been derived from the two-parameter Weibull distribution and are referred to as Weibull models. They exhibit a wide range of shapes for the density and hazard functions, which makes them suitable for modelling complex failure data sets. The WPP and IWPP plot allows one to determine in a systematic manner if one or more of these models are suitable for modelling a given data set. This paper deals with this topic.

Positive selection on an acrosomal sperm protein, M7 lysin, in three species of the mussel genus Mytilus

Marine invertebrate sperm proteins are particularly interesting because they are characterized by positive selection and are likely to be involved in prezyogotic isolation and, thus, speciation. Here, we present the first survey of inter and intraspecific variation of a bivalve sperm protein among a group of species that regularly hybridize in nature. M7 lysin is found in sperm acrosomes of mussels and dissolves the egg vitelline coat, permitting fertilization. We sequenced multiple alleles of the mature protein-coding region of M7 lysin from allopatric populations of mussels in the Mytilus edulis species group (M. edulis, M. galloprovincialis, and M. trossulus). A significant McDonald-Kreitman test showed an excess of fixed amino acid replacing substitutions between species, consistent with positive selection. In addition, Kolmogorov-Smirnov tests showed significant heterogeneity in polymorphism to divergence ratios for both synonymous variation and combined synonymous and non-synonymous variation within M. galloprovincialis. These results indicate that there has been adaptive evolution at M7 lysin and, furthermore, shows that positive selection on sperm proteins can occur even when post-zygotic reproductive isolation is incomplete.

Selection bias in gene extraction on the basis of microarray gene-expression data

In the context of cancer diagnosis and treatment, we consider the problem of constructing an accurate prediction rule on the basis of a relatively small number of tumor tissue samples of known type containing the expression data on very many (possibly thousands) genes. Recently, results have been presented in the literature suggesting that it is possible to construct a prediction rule from only a few genes such that it has a negligible prediction error rate. However, in these results the test error or the leave-one-out cross-validated error is calculated without allowance for the selection bias. There is no allowance because the rule is either tested on tissue samples that were used in the first instance to select the genes being used in the rule or because the cross-validation of the rule is not external to the selection process; that is, gene selection is not performed in training the rule at each stage of the cross-validation process. We describe how in practice the selection bias can be assessed and corrected for by either performing a cross-validation or applying the bootstrap external to the selection process. We recommend using 10-fold rather than leave-one-out cross-validation, and concerning the bootstrap, we suggest using the so-called. 632+ bootstrap error estimate designed to handle overfitted prediction rules. Using two published data sets, we demonstrate that when correction is made for the selection bias, the cross-validated error is no longer zero for a subset of only a few genes.