Toward efficient multifeature query processing

In many advanced applications, data are described by multiple high-dimensional features. Moreover, different queries may weight these features differently; some may not even specify all the features. In this paper, we propose our solution to support efficient query processing in these applications. We devise a novel representation that compactly captures f features into two components: The first component is a 2D vector that reflects a distance range ( minimum and maximum values) of the f features with respect to a reference point ( the center of the space) in a metric space and the second component is a bit signature, with two bits per dimension, obtained by analyzing each feature's descending energy histogram. This representation enables two levels of filtering: The first component prunes away points that do not share similar distance ranges, while the bit signature filters away points based on the dimensions of the relevant features. Moreover, the representation facilitates the use of a single index structure to further speed up processing. We employ the classical B+-tree for this purpose. We also propose a KNN search algorithm that exploits the access orders of critical dimensions of highly selective features and partial distances to prune the search space more effectively. Our extensive experiments on both real-life and synthetic data sets show that the proposed solution offers significant performance advantages over sequential scan and retrieval methods using single and multiple VA-files.

Efficiently computing weighted proximity relationships in spatial databases

Spatial data mining recently emerges from a number of real applications, such as real-estate marketing, urban planning, weather forecasting, medical image analysis, road traffic accident analysis, etc. It demands for efficient solutions for many new, expensive, and complicated problems. In this paper, we investigate the problem of evaluating the top k distinguished “features” for a “cluster” based on weighted proximity relationships between the cluster and features. We measure proximity in an average fashion to address possible nonuniform data distribution in a cluster. Combining a standard multi-step paradigm with new lower and upper proximity bounds, we presented an efficient algorithm to solve the problem. The algorithm is implemented in several different modes. Our experiment results not only give a comparison among them but also illustrate the efficiency of the algorithm.

Feasibility And Reproducibility Of Diffusion-weighted Magnetic Resonance Imaging Of The Fetal Brain In Twin-twin Transfusion Syndrome.

The aim of this study is to test the feasibility and reproducibility of diffusion-weighted magnetic resonance imaging (DW-MRI) evaluations of the fetal brains in cases of twin-twin transfusion syndrome (TTTS). From May 2011 to June 2012, 24 patients with severe TTTS underwent MRI scans for evaluation of the fetal brains. Datasets were analyzed offline on axial DW images and apparent diffusion coefficient (ADC) maps by two radiologists. The subjective evaluation was described as the absence or presence of water diffusion restriction. The objective evaluation was performed by the placement of 20-mm(2) circular regions of interest on the DW image and ADC maps. Subjective interobserver agreement was assessed by the kappa correlation coefficient. Objective intraobserver and interobserver agreements were assessed by proportionate Bland-Altman tests. Seventy-four DW-MRI scans were performed. Sixty of them (81.1%) were considered to be of good quality. Agreement between the radiologists was 100% for the absence or presence of diffusion restriction of water. For both intraobserver and interobserver agreement of ADC measurements, proportionate Bland-Altman tests showed average percentage differences of less than 1.5% and 95% CI of less than 18% for all sites evaluated. Our data demonstrate that DW-MRI evaluation of the fetal brain in TTTS is feasible and reproducible.

The impact of spatial data redundancy on SOLAP query performance

Geographic Data Warehouses (GDW) are one of the main technologies used in decision-making processes and spatial analysis, and the literature proposes several conceptual and logical data models for GDW. However, little effort has been focused on studying how spatial data redundancy affects SOLAP (Spatial On-Line Analytical Processing) query performance over GDW. In this paper, we investigate this issue. Firstly, we compare redundant and non-redundant GDW schemas and conclude that redundancy is related to high performance losses. We also analyze the issue of indexing, aiming at improving SOLAP query performance on a redundant GDW. Comparisons of the SB-index approach, the star-join aided by R-tree and the star-join aided by GiST indicate that the SB-index significantly improves the elapsed time in query processing from 25% up to 99% with regard to SOLAP queries defined over the spatial predicates of intersection, enclosure and containment and applied to roll-up and drill-down operations. We also investigate the impact of the increase in data volume on the performance. The increase did not impair the performance of the SB-index, which highly improved the elapsed time in query processing. Performance tests also show that the SB-index is far more compact than the star-join, requiring only a small fraction of at most 0.20% of the volume. Moreover, we propose a specific enhancement of the SB-index to deal with spatial data redundancy. This enhancement improved performance from 80 to 91% for redundant GDW schemas.

Weighted S-Asymptotically omega-Periodic Solutions of a Class of Fractional Differential Equations

We study the existence of weighted S-asymptotically omega-periodic mild solutions for a class of abstract fractional differential equations of the form u' = partial derivative (alpha vertical bar 1)Au + f(t, u), 1 < alpha < 2, where A is a linear sectorial operator of negative type.

Definition of priority areas for forest conservation through the ordered weighted averaging method

The general objective of this study was to evaluate the ordered weighted averaging (OWA) method, integrated to a geographic information systems (GIS), in the definition of priority areas for forest conservation in a Brazilian river basin, aiming at to increase the regional biodiversity. We demonstrated how one could obtain a range of alternatives by applying OWA, including the one obtained by the weighted linear combination method and, also the use of the analytic hierarchy process (AHP) to structure the decision problem and to assign the importance to each criterion. The criteria considered important to this study were: proximity to forest patches; proximity among forest patches with larger core area; proximity to surface water; distance from roads: distance from urban areas; and vulnerability to erosion. OWA requires two sets of criteria weights: the weights of relative criterion importance and the order weights. Thus, Participatory Technique was used to define the criteria set and the criterion importance (based in AHP). In order to obtain the second set of weights we considered the influence of each criterion, as well as the importance of each one, on this decision-making process. The sensitivity analysis indicated coherence among the criterion importance weights, the order weights, and the solution. According to this analysis, only the proximity to surface water criterion is not important to identify priority areas for forest conservation. Finally, we can highlight that the OWA method is flexible, easy to be implemented and, mainly, it facilitates a better understanding of the alternative land-use suitability patterns. (C) 2008 Elsevier B.V. All rights reserved.

Diffusion- and perfusion-weighted MRI response to thrombolysis in stroke

Diffusion- and perfusion-weighted magnetic resonance imaging provides important pathophysiological information in acute bra-in ischemia. We performed a prospective study in 19 sub-6-hour stroke patients using serial diffusion- and perfusion-weighted imaging before intravenous thrombolysis, with repeat studies, both subacutely and at outcome. For comparison of ischemic lesion evolution and clinical outcome, we used a historical control group of 21 sub-6-hour ischemic stroke patients studied serially with diffusion- and perfusion-weighted imaging. The two groups were well matched for the baseline National Institutes of Health Stroke Scale and magnetic resonance parameters. Perfusion-weighted imaging-diffusion-weighted imaging mismatch was present in 16 of 19 patients treated with tissue plasminogen activator, and 16 of 21 controls. Perfusion-weighted imaging-diffusion-weighted imaging mismatch patients treated with tissue plaminogen activator had higher recanalization rates and enhanced reperfusion at day 3 (81% vs 47% in controls), and a greater proportion of severely hypoperfused acute mismatch tissue not progressing to infarction (82% vs -25% in controls). Despite similar baseline diffusion-weighted imaging lesions, infarct expansion was less in the recombinant tissue plaminogen activator group (14cm(3) vs 56cm(3) in controls). The positive effect of thrombolysis on lesion growth in mismatch patients translated into a greater improvement in baseline to outcome National Institutes of Health Stroke Scale in the group treated with recombinant tissue plaminogen activator, and a significantly larger proportion of patients treated with recombinant tissue plaminogen activator having a clinically meaningful improvement in National Institutes of Health Stroke Scale of;2:7 points. The natural evolution of acute perfusion-weighted imaging-diffusion-weighted imaging mismatch tissue may be altered by thrombolysis, with improved stroke outcome. This has implications for the use of diffusion- and perfusion-weighted imaging in selecting and monitoring patients for thrombolytic therapy.

Acute Toxic Leukoencephalopathy: Potential for Reversibility Clinically and on MRI With Diffusion-Weighted and FLAIR Imaging

OBJECTIVE. Toxic leukoencephalopathy may present acutely or subacutely with symmetrically reduced diffusion in the periventricular and supraventricular white matter, hereafter referred to as periventricular white matter. This entity may reverse both on imaging and clinically. However, a gathering together of the heterogeneous causes of this disorder as seen on MRI with diffusion-weighted imaging (DWI) and an analysis of their likelihood to reverse has not yet been performed. Our goals were to gather causes of acute or subacute toxic leukoencephalopathy that can present with reduced diffusion of periventricular white matter in order to promote recognition of this entity, to evaluate whether DWI with apparent diffusion coefficient (ADC) values can predict the extent of chronic FLAIR abnormality ( imaging reversibility), and to evaluate whether DWI can predict the clinical outcome ( clinical reversibility). MATERIALS AND METHODS. Two neuroradiologists retrospectively reviewed the MRI examinations of 39 patients with acute symptoms and reduced diffusion of periventricular white matter. The reviewers then scored the extent of abnormality on DWI and FLAIR. ADC ratios of affected white matter versus the unaffected periventricular white matter were obtained. Each patient`s clinical records were reviewed to determine the cause and clinical outcome. Histology findings were available in three patients. Correlations were calculated between the initial MRI markers and both the clinical course and the follow-up extent on FLAIR using Spearman`s correlation coefficient. RESULTS. Of the initial 39 patients, seven were excluded because of a nontoxic cause (hypoxic-ischemic encephalopathy [HIE] or congenital genetic disorders) or because of technical errors. In the remaining 32 patients, no correlation was noted between any of the initial MRI markers (percentage of ADC reduction, DWI extent, or FLAIR extent) with the clinical outcome. Three patients had histologic correlation. However, moderate correlation was seen between the extent of abnormality on initial FLAIR and the extent on follow-up FLAIR (r = 0.441, p = 0.047). Of the 13 patients who underwent repeat MRI at 21 days or longer, the reduced diffusion resolved in all but one. Significant differences were noted between ADC values in affected white matter versus unaffected periventricular white matter on initial (p < 0.0001) but not on follow-up MRI (p = 0.13), and in affected white matter on initial versus follow-up (p = 0.0014) in those individuals who underwent repeat imaging on the same magnet (n = 9), confirming resolution of the DWI abnormalities. CONCLUSION. Acute toxic leukoencephalopathy with reduced diffusion may be clinically reversible and radiologically reversible on DWI, and may also be reversible, but to a lesser degree, on FLAIR MRI. None of the imaging markers measured in this study appears to correlate with clinical outcome, which underscores the necessity for prompt recognition of this entity. Alerting the clinician to this potentially reversible syndrome can facilitate treatment and removal of the offending agent in the early stages.

Changes in Perfusion-Weighted Magnetic Resonance Imaging after Carotid Angioplasty with Stent

Carotid artery stenosis due to arteriosclerosis increases the risk of cerebral ischemia via embolic phenomena or reduced blood flow. The changes in cerebral perfusion that may occur after treatment are not clearly understood. This study evaluated the changes in cerebral microcirculation following carotid angioplasty with stenting (CAS) under cerebral protection with filters using ultrafast gradient echo (GRE) perfusion weighted imaging (PWI) with magnetic resonance imaging (MRI). Prospectively, 21 cervical carotid stenosis patients, mean age 69.95 years, underwent MRI 12 h before and 72 h after CAS. PWI parameters were collected for statistical analysis: cerebral blood volume (CB V), mean transit time (MTT) and time to peak (TTP). Statistical analysis was applied to absolute parameters and to values normalized against those from the contralateral parenchyma. The main finding of this study was improved hemodynamics for the normalized data after CAS, shown by reduced MTT (p<0.001) and TTP (p=0.019) in the territory fed by the middle cerebral artery ipsilateral to the CAS. Absolute data showed increased blood volume in the cerebral hemispheres after CAS, which was more accentuated on the stent side (p=0.016) than the contralateral side (p=0.029). Early improvements in cerebral perfusion, mainly seen in the normalized data, were clearly demonstrated in the timing parameters - TTP & MTT - after CAS.

The effects of information request ambiguity and construct incongruence on query development

This paper examines the effects of information request ambiguity and construct incongruence on end user's ability to develop SQL queries with an interactive relational database query language. In this experiment, ambiguity in information requests adversely affected accuracy and efficiency. Incongruities among the information request, the query syntax, and the data representation adversely affected accuracy, efficiency, and confidence. The results for ambiguity suggest that organizations might elicit better query development if end users were sensitized to the nature of ambiguities that could arise in their business contexts. End users could translate natural language queries into pseudo-SQL that could be examined for precision before the queries were developed. The results for incongruence suggest that better query development might ensue if semantic distances could be reduced by giving users data representations and database views that maximize construct congruence for the kinds of queries in typical domains. (C) 2001 Elsevier Science B.V. All rights reserved.

A segmentation-based and partial-volume-compensated method for an accurate measurement of lateral ventricular volumes on T-1-weighted magnetic resonance images

Lateral ventricular volumes based on segmented brain MR images can be significantly underestimated if partial volume effects are not considered. This is because a group of voxels in the neighborhood of lateral ventricles is often mis-classified as gray matter voxels due to partial volume effects. This group of voxels is actually a mixture of ventricular cerebro-spinal fluid and the white matter and therefore, a portion of it should be included as part of the lateral ventricular structure. In this note, we describe an automated method for the measurement of lateral ventricular volumes on segmented brain MR images. Image segmentation was carried in combination of intensity correction and thresholding. The method is featured with a procedure for addressing mis-classified voxels in the surrounding of lateral ventricles. A detailed analysis showed that lateral ventricular volumes could be underestimated by 10 to 30% depending upon the size of the lateral ventricular structure, if mis-classified voxels were not included. Validation of the method was done through comparison with the averaged manually traced volumes. Finally, the merit of the method is demonstrated in the evaluation of the rate of lateral ventricular enlargement. (C) 2001 Elsevier Science Inc. All rights reserved.