980 resultados para Tables(data)
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Errata pages inserted in vol. 2.
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Mode of access: Internet.
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Mode of access: Internet.
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At head of title: Department of commerce. Bureau of foreign and domestic commerce. A.H. Baldwin, chief.
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Mode of access: Internet.
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"Memorandum of certain 1946-1947 references not incorporated in regular text": p. xvii-xxv.
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Our ability to project the impact of global change on marine ecosystem is limited by our poor understanding on how to predict species sensitivity. For example, the impact of ocean acidification is highly species-specific, even in closely related taxa. The aim of this study was to test the hypothesis that the tolerance range of a given species to decreased pH corresponds to their natural range of exposure. Larvae of the green sea urchin Strongylocentrotus droebachiensis were cultured from fertilization to metamorphic competence (29 days) under a wide range of pH (from pHT = 8.0/pCO2 ~ 480 ?atm to pHT = 6.5/pCO2 ~ 20 000 ?atm) covering present (from pHT 8.7 to 7.6), projected near-future variability (from pHT 8.3 to 7.2) and beyond. Decreasing pH impacted all tested parameters (mortality, symmetry, growth, morphometry and respiration). Development of normal, although showing morphological plasticity, swimming larvae was possible as low as pHT >= 7.0. Within that range, decreasing pH increased mortality and asymmetry and decreased body length (BL) growth rate. Larvae raised at lowered pH and with similar BL had shorter arms and a wider body. Relative to a given BL, respiration rates and stomach volume both increased with decreasing pH suggesting changes in energy budget. At the lowest pHs (pHT <= 6.5), all the tested parameters were strongly negatively affected and no larva survived past 13 days post fertilization. In conclusion, sea urchin larvae appeared to be highly plastic when exposed to decreased pH until a physiological tipping point at pHT = 7.0. However, this plasticity was associated with direct (increased mortality) and indirect (decreased growth) consequences for fitness.
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A survey of a number of schools in a number of different climates was carried out to determine the condition of building components of interest in the project. Schools in Melbourne, the Victorian Surf Coast, Brisbane, Townsville and the Sunshine Coast were inspected. A rating system was devised to categorise the components and the results collated in tables. Analysis of the data (where sufficient examples permitted) resulted in formulae to predict the service of the components and a database was derived.
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BACKGROUND Collaborative and active learning have been clearly identified as ways students can engage in learning with each other and the academic staff. Traditional tier based lecture theatres and the didactic style they engender are not popular with students today as evidenced by the low attendance rates for lectures. Many universities are installing spaces designed with tables for group interaction with evolutions on spaces such as the TEAL (Technology Enabled Active Learning) (Massachusetts Institute of Technology, n.d.) and SCALE-UP (Student-Centred Activities for Large-Enrolment Undergraduate Programs) (North Carolina State University, n.d.) models. Technology advances in large screen computers and applications have also aided the move to these collaborative spaces. How well have universities structured learning using these spaces and how have students engaged with the content, technology, space and each other? This paper investigates the application of collaborative learning in such spaces for a cohort of 800+ first year engineers in the context of learning about and developing professional skills representative of engineering practice. PURPOSE To determine whether moving from tiers to tables enhances the student experience. Does utilising technology rich, activity based, collaborative learning spaces lead to positive experiences and active engagement of first year undergraduate engineering students? In developing learning methodology and approach in new learning spaces, what needs to change from a more traditional lecture and tutorial configuration? DESIGN/METHOD A post delivery review and analysis of outcomes was undertaken to determine how well students and tutors engaged with learning in new collaborative learning spaces. Data was gathered via focus group and survey of tutors, students survey and attendance observations. The authors considered the unit delivery approach along with observed and surveyed outcomes then conducted further review to produce the reported results. RESULTS Results indicate high participation in the collaborative sessions while the accompanying lectures were poorly attended. Students reported a high degree of satisfaction with the learning experience; however more investigation is required to determine the degree of improvement in retained learning outcomes. Survey feedback from tutors found that students engaged well in the activities during tutorials and there was an observed improvement in the quality of professional practice modelled by students during sessions. Student feedback confirmed the positive experiences in these collaborative learning spaces with 30% improvement in satisfaction ratings from previous years. CONCLUSIONS It is concluded that the right mix of space, technology and appropriate activities does engage students, improve participation and create a rich experience to facilitate potential for improved learning outcomes. The new Collaborative Teaching Spaces, together with integrated technology and tailored activities, has transformed the delivery of this unit and improved student satisfaction in tutorials significantly.
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Background Accumulated biological research outcomes show that biological functions do not depend on individual genes, but on complex gene networks. Microarray data are widely used to cluster genes according to their expression levels across experimental conditions. However, functionally related genes generally do not show coherent expression across all conditions since any given cellular process is active only under a subset of conditions. Biclustering finds gene clusters that have similar expression levels across a subset of conditions. This paper proposes a seed-based algorithm that identifies coherent genes in an exhaustive, but efficient manner. Methods In order to find the biclusters in a gene expression dataset, we exhaustively select combinations of genes and conditions as seeds to create candidate bicluster tables. The tables have two columns: (a) a gene set, and (b) the conditions on which the gene set have dissimilar expression levels to the seed. First, the genes with less than the maximum number of dissimilar conditions are identified and a table of these genes is created. Second, the rows that have the same dissimilar conditions are grouped together. Third, the table is sorted in ascending order based on the number of dissimilar conditions. Finally, beginning with the first row of the table, a test is run repeatedly to determine whether the cardinality of the gene set in the row is greater than the minimum threshold number of genes in a bicluster. If so, a bicluster is outputted and the corresponding row is removed from the table. Repeating this process, all biclusters in the table are systematically identified until the table becomes empty. Conclusions This paper presents a novel biclustering algorithm for the identification of additive biclusters. Since it involves exhaustively testing combinations of genes and conditions, the additive biclusters can be found more readily.
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Open the sports or business section of your daily newspaper, and you are immediately bombarded with an array of graphs, tables, diagrams, and statistical reports that require interpretation. Across all walks of life, the need to understand statistics is fundamental. Given that our youngsters’ future world will be increasingly data laden, scaffolding their statistical understanding and reasoning is imperative, from the early grades on. The National Council of Teachers of Mathematics (NCTM) continues to emphasize the importance of early statistical learning; data analysis and probability was the Council’s professional development “Focus of the Year” for 2007–2008. We need such a focus, especially given the results of the statistics items from the 2003 NAEP. As Shaughnessy (2007) noted, students’ performance was weak on more complex items involving interpretation or application of items of information in graphs and tables. Furthermore, little or no gains were made between the 2000 NAEP and the 2003 NAEP studies. One approach I have taken to promote young children’s statistical reasoning is through data modeling. Having implemented in grades 3 –9 a number of model-eliciting activities involving working with data (e.g., English 2010), I observed how competently children could create their own mathematical ideas and representations—before being instructed how to do so. I thus wished to introduce data-modeling activities to younger children, confi dent that they would likewise generate their own mathematics. I recently implemented data-modeling activities in a cohort of three first-grade classrooms of six year- olds. I report on some of the children’s responses and discuss the components of data modeling the children engaged in.
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The Bluetooth technology is being increasingly used, among the Automated Vehicle Identification Systems, to retrieve important information about urban networks. Because the movement of Bluetooth-equipped vehicles can be monitored, throughout the network of Bluetooth sensors, this technology represents an effective means to acquire accurate time dependant Origin Destination information. In order to obtain reliable estimations, however, a number of issues need to be addressed, through data filtering and correction techniques. Some of the main challenges inherent to Bluetooth data are, first, that Bluetooth sensors may fail to detect all of the nearby Bluetooth-enabled vehicles. As a consequence, the exact journey for some vehicles may become a latent pattern that will need to be estimated. Second, sensors that are in close proximity to each other may have overlapping detection areas, thus making the task of retrieving the correct travelled path even more challenging. The aim of this paper is twofold: to give an overview of the issues inherent to the Bluetooth technology, through the analysis of the data available from the Bluetooth sensors in Brisbane; and to propose a method for retrieving the itineraries of the individual Bluetooth vehicles. We argue that estimating these latent itineraries, accurately, is a crucial step toward the retrieval of accurate dynamic Origin Destination Matrices.
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Abstract-To detect errors in decision tables one needs to decide whether a given set of constraints is feasible or not. This paper describes an algorithm to do so when the constraints are linear in variables that take only integer values. Decision tables with such constraints occur frequently in business data processing and in nonnumeric applications. The aim of the algorithm is to exploit. the abundance of very simple constraints that occur in typical decision table contexts. Essentially, the algorithm is a backtrack procedure where the the solution space is pruned by using the set of simple constrains. After some simplications, the simple constraints are captured in an acyclic directed graph with weighted edges. Further, only those partial vectors are considered from extension which can be extended to assignments that will at least satisfy the simple constraints. This is how pruning of the solution space is achieved. For every partial assignment considered, the graph representation of the simple constraints provides a lower bound for each variable which is not yet assigned a value. These lower bounds play a vital role in the algorithm and they are obtained in an efficient manner by updating older lower bounds. Our present algorithm also incorporates an idea by which it can be checked whether or not an (m - 2)-ary vector can be extended to a solution vector of m components, thereby backtracking is reduced by one component.
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This paper presents a fast algorithm for data exchange in a network of processors organized as a reconfigurable tree structure. For a given data exchange table, the algorithm generates a sequence of tree configurations in which the data exchanges are to be executed. A significant feature of the algorithm is that each exchange is executed in a tree configuration in which the source and destination nodes are adjacent to each other. It has been proved in a theorem that for every pair of nodes in the reconfigurable tree structure, there always exists two and only two configurations in which these two nodes are adjacent to each other. The algorithm utilizes this fact and determines the solution so as to optimize both the number of configurations required and the time to perform the data exchanges. Analysis of the algorithm shows that it has linear time complexity, and provides a large reduction in run-time as compared to a previously proposed algorithm. This is well-confirmed from the experimental results obtained by executing a large number of randomly-generated data exchange tables. Another significant feature of the algorithm is that the bit-size of the routing information code is always two bits, irrespective of the number of nodes in the tree. This not only increases the speed of the algorithm but also results in simpler hardware inside each node.
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Table of Contents [pdf, 0.13 Mb] Section I - Practical Workshop Description [pdf, 21.22 Mb] Section II - Site Description and Oceanography [pdf, 0.40 Mb] Section III - Extended Abstracts Contaminant Concentrations in Sediment and Biota [pdf, 1.36 Mb] Biochemical and Physiological Studies [pdf, 0.77 Mb] Community Studies [pdf, 1.01 Mb] Harmful Algae Studies [pdf, 0.67 Mb] Section IV - Comprehensive Data Tables Site Locations [pdf, 0.10 Mb] Sediment Chemistry [pdf, 0.54 Mb] Tissue Chemistry – Fish [pdf, 1.20 Mb] Tissue Chemistry – Bivalves [pdf, 0.49 Mb] Lipid and Fatty Acids in Mytilus trossulus [pdf, 0.15 Mb] Biochemical, Physiological and Histopathological Parameters [pdf, 1.20 Mb] Biological Community Data – Fish and Mussels [pdf, 0.87 Mb] Biological Community Data – Macrobenthos [pdf, 0.85 Mb] Harmful Algae [pdf, 0.07 Mb] (Document contains 205 pages)