Approximate processing of massive continuous quantile queries over high-speed data streams

Quantile computation has many applications including data mining and financial data analysis. It has been shown that an is an element of-approximate summary can be maintained so that, given a quantile query d (phi, is an element of), the data item at rank [phi N] may be approximately obtained within the rank error precision is an element of N over all N data items in a data stream or in a sliding window. However, scalable online processing of massive continuous quantile queries with different phi and is an element of poses a new challenge because the summary is continuously updated with new arrivals of data items. In this paper, first we aim to dramatically reduce the number of distinct query results by grouping a set of different queries into a cluster so that they can be processed virtually as a single query while the precision requirements from users can be retained. Second, we aim to minimize the total query processing costs. Efficient algorithms are developed to minimize the total number of times for reprocessing clusters and to produce the minimum number of clusters, respectively. The techniques are extended to maintain near-optimal clustering when queries are registered and removed in an arbitrary fashion against whole data streams or sliding windows. In addition to theoretical analysis, our performance study indicates that the proposed techniques are indeed scalable with respect to the number of input queries as well as the number of items and the item arrival rate in a data stream.

A combined spectrophotometric and morphometric study of the lunar mare dome fields near Cauchy, Arago, Hortensius, and Milichius

In this Study we examine the spectral and morphometric properties of the four important lunar mare dome fields near Cauchy, Arago, Hortensius. and Milichius. We utilize Clementine UV vis mulfispectral data to examine the soil composition of the mare domes while employing telescopic CCD imagery to compute digital elevation maps in order to determine their morphometric properties, especially flank slope, height, and edifice Volume. After reviewing previous attempts to determine topographic data for lunar domes, we propose an image-based 3D reconstruction approach which is based on a combination of photoclinometry and shape from shading. Accordingly, we devise a classification scheme for lunar Marc domes which is based on a principal component analysis of the determined spectral and morphometric features. For the effusive mare domes of the examined fields we establish four Classes, two of which are further divided into two subclasses, respectively, where each class represents distinct combinations of spectral and morphometric dome properties. As a general trend, shallow and steep domes formed out of low-TiO2 basalts are observed in the Hortensius and Milichius dome fields, while the domes near Cauchy and Arago that consist of high-TiO2 basalts are all very shallow. The intrusive domes of our data set cover a wide continuous range of spectral and morphometric quantities, generally characterized by larger diameters and shallower flank slopes than effusive domes. A comparison to effusive and intrusive mare domes in other lunar regions, highland domes, and lunar cones has shown that the examined four mare dome fields display Such a richness in spectral properties and 3D dome shape that the established representation remains valid in a more global context. Furthermore, we estimate the physical parameters of dome formation for the examined domes based on a rheologic model. Each class of effusive domes defined in terms of spectral and morphometric properties is characterized by its specific range of values for lava viscosity, effusion rate, and duration of the effusion process. For our data set we report lava viscosities between about 10(2) and 10(8) Pas, effusion rates between 25 and 600 m(3) s(-1), and durations of the effusion process between three weeks and 18 years. Lava viscosity decreases with increasing R-415/R-750 spectral ratio and thus TiO2 content; however, the correlation is not strong, implying an important influence of further parameters like effusion temperature on lava viscosity.

Using a clinical pathway and education to reduce inappropriate prescribing of enoxaparin in patients with acute coronary syndromes: a controlled study

Aims: To evaluate efficacy of a pathway-based quality improvement intervention on appropriate prescribing of the low molecular weight heparin, enoxaparin, in patients with varying risk categories of acute coronary syndrome (ACS). Methods: Rates of enoxaparin use retrospectively evaluated before and after pathway implementation at an intervention hospital were compared to concurrent control patients at a control hospital; both were community hospitals in south-east Queensland. The study population was a group of randomly selected patients (n = 439) admitted to study hospitals with a discharge diagnosis of chest pain, angina, or myocardial infarction, and stratified into high, intermediate, low-risk ACS or non-cardiac chest pain: 146 intervention patients (September-November 2003), 147 historical controls (August-December 2001) at the intervention hospital; 146 concurrent controls (September-November 2003) at the control hospital. Interventions were active implementation of a user-modified clinical pathway coupled with an iterative education programme to medical staff versus passive distribution of a similar pathway without user modification or targeted education. Outcome measures were rates of appropriate enoxaparin use in high-risk ACS patients and rates of inappropriate use in intermediate and low-risk patients. Results: Appropriate use of enoxaparin in high-risk ACS patients was above 90% in all patient groups. Inappropriate use of enoxaparin was significantly reduced as a result of pathway use in intermediate risk (9% intervention patients vs 75% historical controls vs 45% concurrent controls) and low-risk patients (9% vs 62% vs 41%; P < 0.001 for all comparisons). Pathway use was associated with a 3.5-fold (95% CI: 1.3-9.1; P = 0.012) increase in appropriate use of enoxaparin across all patient groups. Conclusion: Active implementation of an acute chest pain pathway combined with continuous education reduced inappropriate use of enoxaparin in patients presenting with intermediate or low-risk ACS.

Using continuous plankton recorder data

The continuous plankton recorder (CPR) survey is the largest multi-decadal plankton monitoring programme in the world. It was initiated in 1931 and by the end of 2004 had counted 207,619 samples and identified 437 phyto- and zoo-plankton taxa throughout the North Atlantic. CPR data are used extensively by the research community and in recent years have been used increasingly to underpin marine management. Here, we take a critical look at how best to use CPR data. We first describe the CPR itself, CPR sampling, and plankton counting procedures. We discuss the spatial and temporal biases in the Survey, summarise environmental data that have not previously been available, and describe the new data access policy. We supply information essential to using CPR data, including descriptions of each CPR taxonomic entity., the idiosyncrasies associated with counting many of the taxa, the logic behind taxonomic changes in the Survey, the semi-quantitative nature of CPR sampling, and recommendations on choosing the spatial and temporal scale of study. This forms the basis for a broader discussion on how to use CPR data for deriving ecologically meaningful indices based on size, functional groups and biomass that can be used to support research and management. This contribution should be useful for plankton ecologists, modellers and policy makers that actively use CPR data. (c) 2005 Elsevier Ltd. All rights reserved.

Application of Monte Carlo simulations to identify an appropriate dosage strategy for patients receiving a continuous intravenous infusion of enoxaparin

Aim: To identify an appropriate dosage strategy for patients receiving enoxaparin by continuous intravenous infusion (CII). Methods: Monte Carlo simulations were performed in NONMEM, (200 replicates of 1000 patients) to predict steady state anti-Xa concentrations (Css) for patients receiving a CII of enoxaparin. The covariate distribution model was simulated based on covariate demographics in the CII study population. The impact of patient weight, renal function (creatinine clearance (CrCL)) and patient location (intensive care unit (ICU)) were evaluated. A population pharmacokinetic model was used as the input-output model (1-compartment first order output model with mixed residual error structure). Success of a dosing regimen was based on the percent of Css that is between the therapeutic range of 0.5 IU/ml to 1.2 IU/ml. Results: The best dose for patients in the ICU was 4.2IU/kg/h (success mean 64.8% and 90% prediction interval (PI): 60.1–69.8%) if CrCL60ml/min, the best dose was 8.3IU/kg/h (success mean 65.4%, 90% PI: 58.5–73.2%). Simulations suggest that there was a 50% improvement in the success of the CII if the dose rate for ICU patients with CrCL

Data quality initiatives - striving for continuous improvements

Although managers consider accurate, timely, and relevant information as critical to the quality of their decisions, evidence of large variations in data quality abounds. Over a period of twelve months, the action research project reported herein attempted to investigate and track data quality initiatives undertaken by the participating organisation. The investigation focused on two types of errors: transaction input errors and processing errors. Whenever the action research initiative identified non-trivial errors, the participating organisation introduced actions to correct the errors and prevent similar errors in the future. Data quality metrics were taken quarterly to measure improvements resulting from the activities undertaken during the action research project. The action research project results indicated that for a mission-critical database to ensure and maintain data quality, commitment to continuous data quality improvement is necessary. Also, communication among all stakeholders is required to ensure common understanding of data quality improvement goals. The action research project found that to further substantially improve data quality, structural changes within the organisation and to the information systems are sometimes necessary. The major goal of the action research study is to increase the level of data quality awareness within all organisations and to motivate them to examine the importance of achieving and maintaining high-quality data.