941 resultados para Arterial segmentation
Resumo:
Transit passenger market segmentation enables transit operators to target different classes of transit users for targeted surveys and various operational and strategic planning improvements. However, the existing market segmentation studies in the literature have been generally done using passenger surveys, which have various limitations. The smart card (SC) data from an automated fare collection system facilitate the understanding of the multiday travel pattern of transit passengers and can be used to segment them into identifiable types of similar behaviors and needs. This paper proposes a comprehensive methodology for passenger segmentation solely using SC data. After reconstructing the travel itineraries from SC transactions, this paper adopts the density-based spatial clustering of application with noise (DBSCAN) algorithm to mine the travel pattern of each SC user. An a priori market segmentation approach then segments transit passengers into four identifiable types. The methodology proposed in this paper assists transit operators to understand their passengers and provides them oriented information and services.
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This paper describes our participation in the Chinese word segmentation task of CIPS-SIGHAN 2010. We implemented an n-gram mutual information (NGMI) based segmentation algorithm with the mixed-up features from unsupervised, supervised and dictionarybased segmentation methods. This algorithm is also combined with a simple strategy for out-of-vocabulary (OOV) word recognition. The evaluation for both open and closed training shows encouraging results of our system. The results for OOV word recognition in closed training evaluation were however found unsatisfactory.
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Market segmentation has received relatively limited attention in social marketing, particularly within the context of changing children’s physical activity behaviour. This is an important area of investigation given growing concern over childhood obesity globally. The present research aims to extend current understanding of the applicability of market segmentation within this context. The results of a two-step cluster analysis on data from 512 respondents of an online survey show three distinct segments of caregivers, each with unique beliefs about their primary school children walking to/from school. The results demonstrate the validity of employing the process of market segmentation within this social context and provide further insights for targeting the identified segments through tailored social marketing programs.
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Recent changes in the aviation industry and in the expectations of travellers have begun to alter the way we approach our understanding, and thus the segmentation, of airport passengers. The key to successful segmentation of any population lies in the selection of the criteria on which the partitions are based. Increasingly, the basic criteria used to segment passengers (purpose of trip and frequency of travel) no longer provide adequate insights into the passenger experience. In this paper, we propose a new model for passenger segmentation based on the passenger core value, time. The results are based on qualitative research conducted in-situ at Brisbane International Terminal during 2012-2013. Based on our research, a relationship between time sensitivity and degree of passenger engagement was identified. This relationship was used as the basis for a new passenger segmentation model, namely: Airport Enthusiast (engaged, non time sensitive); Time Filler (non engaged, non time sensitive); Efficiency Lover (non engaged, time sensitive) and Efficient Enthusiast (engaged, time sensitive). The outcomes of this research extend the theoretical knowledge about passenger experience in the terminal environment. These new insights can ultimately be used to optimise the allocation of space for future terminal planning and design.
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Objective This study seeks establish whether meaningful subgroups exist within a 14-16 year old adolescent population and if these segments respond differently to the Game On: Know Alcohol (GOKA) intervention, a school-based alcohol social marketing program. Methodology This study is part of a larger cluster randomized controlled evaluation of the Game On: Know Alcohol (GOKA) program implemented in 14 schools in 2013/2014. TwoStep cluster analysis was conducted to segment 2114 high school adolescents (14-16 years old) on the basis of 22 demographic, behavioral and psychographic variables. Program effects on knowledge, attitudes, behavioral intentions, social norms, expectancies and refusal self-efficacy of identified segments was subsequently examined. Results Three segments were identified: (1) Abstainers (2) Bingers (3) Moderate Drinkers. Program effects varied significantly across segments. The strongest positive change effects post participation were observed for the Bingers, while mixed effects were evident for Moderate Drinkers and Abstainers. Conclusions These findings provide preliminary empirical evidence supporting application of social marketing segmentation in alcohol education programs. Development of targeted programs that meet the unique needs of each of the three identified segments is indicated to extend the social marketing footprint in alcohol education.
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The objective of this study was to identify symptom clusters and their effect on quality of life (QOL) of adults with chronic leg ulcers of mixed venous and arterial aetiology. A secondary analysis of data from four existing prospective longitudinal studies conducted by a wound healing research group in Australia was undertaken. A total of 110 patients who met the inclusion criteria were selected for this study. Exploratory factor analysis (EFA) was used to identify symptom clusters and correlational analyses to examine relationships between the identified symptom clusters and QOL. The EFA identified two distinct symptom clusters: a 'systemic symptom cluster' consisting of pain, fatigue and depressive symptoms; and a 'localised-leg symptom cluster' including pain, fatigue, oedema, lower limb inflammation and exudate. Physical QOL correlated significantly with the systemic symptom cluster (r = -0·055, P < 0·0001) and the localised-leg symptom cluster (r = -0·054, P < 0·0001), whereas mental QOL was associated only with the systemic symptom cluster (r = -0·038, P = 0·01). The results suggest that appropriate intervention strategies targeting specific symptom clusters should be developed. Targeting patients with symptom clusters is particularly important because they are at high risk and the most vulnerable for reduced QOL.
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Robust and automatic non-rigid registration depends on many parameters that have not yet been systematically explored. Here we determined how tissue classification influences non-linear fluid registration of brain MRI. Twin data is ideal for studying this question, as volumetric correlations between corresponding brain regions that are under genetic control should be higher in monozygotic twins (MZ) who share 100% of their genes when compared to dizygotic twins (DZ) who share half their genes on average. When these substructure volumes are quantified using tensor-based morphometry, improved registration can be defined based on which method gives higher MZ twin correlations when compared to DZs, as registration errors tend to deplete these correlations. In a study of 92 subjects, higher effect sizes were found in cumulative distribution functions derived from statistical maps when performing tissue classification before fluid registration, versus fluidly registering the raw images. This gives empirical evidence in favor of pre-segmenting images for tensor-based morphometry.
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In this paper we present a robust method to detect handwritten text from unconstrained drawings on normal whiteboards. Unlike printed text on documents, free form handwritten text has no pattern in terms of size, orientation and font and it is often mixed with other drawings such as lines and shapes. Unlike handwritings on paper, handwritings on a normal whiteboard cannot be scanned so the detection has to be based on photos. Our work traces straight edges on photos of the whiteboard and builds graph representation of connected components. We use geometric properties such as edge density, graph density, aspect ratio and neighborhood similarity to differentiate handwritten text from other drawings. The experiment results show that our method achieves satisfactory precision and recall. Furthermore, the method is robust and efficient enough to be deployed in a mobile device. This is an important enabler of business applications that support whiteboard-centric visual meetings in enterprise scenarios. © 2012 IEEE.
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Background: Inflammation and biomechanical factors have been associated with the development of vulnerable atherosclerotic plaques. Lipid-lowering therapy has been shown to be effective in stabilizing them by reducing plaque inflammation. Its effect on arterial wall strain, however, remains unknown. The aim of the present study was to investigate the role of high- and low-dose lipid-lowering therapy using an HMG-CoA reductase inhibitor, atorvastatin, on arterial wall strain. Methods and Results: Forty patients with carotid stenosis >40% were successfully followed up during the Atorvastatin Therapy: Effects on Reduction Of Macrophage Activity (ATHEROMA; ISRCTN64894118) Trial. All patients had plaque inflammation as shown by intraplaque accumulation of ultrasmall super paramagnetic particles of iron oxide on magnetic resonance imaging at baseline. Structural analysis was performed and change of strain was compared between high- and low-dose statin at 0 and 12 weeks. There was no significant difference in strain between the 2 groups at baseline (P=0.6). At 12 weeks, the maximum strain was significantly lower in the 80-mg group than in the 10-mg group (0.085±0.033 vs. 0.169±0.084; P=0.001). A significant reduction (26%) of maximum strain was observed in the 80-mg group at 12 weeks (0.018±0.02; P=0.01). Conclusions: Aggressive lipid-lowering therapy is associated with a significant reduction in arterial wall strain. The reduction in biomechanical strain may be associated with reductions in plaque inflammatory burden.
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Stroke is one of the leading causes of death in the world, resulting mostly from the sudden ruptures of atherosclerosis carotid plaques. Until now, the exact plaque rupture mechanism has not been fully understood, and also the plaque rupture risk stratification. The advanced multi-spectral magnetic resonance imaging (MRI) has allowed the plaque components to be visualized in-vivo and reconstructed by computational modeling. In the study, plaque stress analysis using fully coupled fluid structure interaction was applied to 20 patients (12 symptomatic and 8 asymptomatic) reconstructed from in-vivo MRI, followed by a detailed biomechanics analysis, and morphological feature study. The locally extreme stress conditions can be found in the fibrous cap region, 85% at the plaque shoulder based on the present study cases. Local maximum stress values predicted in the plaque region were found to be significantly higher in symptomatic patients than that in asymptomatic patients (200±43. kPa vs. 127±37. kPa, p=0.001). Plaque stress level, defined by excluding 5% highest stress nodes in the fibrous cap region based on the accumulative histogram of stress experienced on the computational nodes in the fibrous cap, was also significantly higher in symptomatic patients than that in asymptomatic patients (154±32. kPa vs. 111±23. kPa, p<0.05). Although there was no significant difference in lipid core size between the two patient groups, symptomatic group normally had a larger lipid core and a significantly thinner fibrous cap based on the reconstructed plaques using 3D interpolation from stacks of 2D contours. Plaques with a higher stenosis were more likely to have extreme stress conditions upstream of plaque throat. The combined analyses of plaque MR image and plaque stress will advance our understanding of plaque rupture, and provide a useful tool on assessing plaque rupture risk.
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High mechanical stress in atherosclerotic plaques at vulnerable sites, called critical stress, contributes to plaque rupture. The site of minimum fibrous cap (FC) thickness (FCMIN) and plaque shoulder are well-documented vulnerable sites. The inherent weakness of the FC material at the thinnest point increases the stress, making it vulnerable, and it is the big curvature of the lumen contour over FC which may result in increased plaque stress. We aimed to assess critical stresses at FCMIN and the maximum lumen curvature over FC (LCMAX) and quantify the difference to see which vulnerable site had the highest critical stress and was, therefore, at highest risk of rupture. One hundred patients underwent high resolution carotid magnetic resonance (MR) imaging. We used 352 MR slices with delineated atherosclerotic components for the simulation study. Stresses at all the integral nodes along the lumen surface were calculated using the finite-element method. FCMIN and LCMAX were identified, and critical stresses at these sites were assessed and compared. Critical stress at FC MIN was significantly lower than that at LCMAX (median: 121.55 kPa; inter quartile range (IQR) = [60.70-180.32] kPa vs. 150.80 kPa; IQR = [91.39-235.75] kPa, p < 0.0001). If critical stress at FCMIN was only used, then the stress condition of 238 of 352 MR slices would be underestimated, while if the critical stress at LCMAX only was used, then 112 out of 352 would be underestimated. Stress analysis at FCMIN and LCMAX should be used for a refined mechanical risk assessment of atherosclerotic plaques, since material failure at either site may result in rupture.
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Atherosclerotic plaque rupture has been extensively considered as the leading cause of death in western countries. It is believed that high stresses within plaque can be an important factor on triggering the rupture of the plaque. Stress analysis in the coronary and carotid arteries with plaque have been developed by many researchers from 2D to 3-D models, from structure analysis only to the Fluid-Structure Interaction (FSI) models[1].
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Atherosclerotic plaque rupture has been extensively considered as the leading cause of death in the world. It is believed that high stress within plaque can be an important factor which can trigger the rupture of the plaque. High resolution multi-spectral magnetic resonance imaging (MRI) has allowed the plaque components (arterial wall, lipids, and fibrous cap) to be visualized in vivo [1]. The patient specific finite element model can be generated from the image data to perform stress analysis and provide critical information on understanding plaque rupture mechanisms [2]. The present work is to apply the procedure to a total of 14 patients (S1 ∼ S14), to study the stress distributions on carotid artery plaque reconstructed from multi-spectral magnetic resonance images, and the possible relationships between stress and plaque burdens.
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The mechanical properties of arterial walls have long been recognized to play an essential role in the development and progression of cardiovascular disease (CVD). Early detection of variations in the elastic modulus of arteries would help in monitoring patients at high cardiovascular risk stratifying them according to risk. An in vivo, non-invasive, high resolution MR-phase-contrast based method for the estimation of the time-dependent elastic modulus of healthy arteries was developed, validated in vitro by means of a thin walled silicon rubber tube integrated into an existing MR-compatible flow simulator and used on healthy volunteers. A comparison of the elastic modulus of the silicon tube measured from the MRI-based technique with direct measurements confirmed the method's capability. The repeatability of the method was assessed. Viscoelastic and inertial effects characterizing the dynamic response of arteries in vivo emerged from the comparison of the pressure waveform and the area variation curve over a period. For all the volunteers who took part in the study the elastic modulus was found to be in the range 50-250 kPa, to increase during the rising part of the cycle, and to decrease with decreasing pressure during the downstroke of systole and subsequent diastole.
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Arterial compliance has been shown to correlate well with overall cardiovascular outcome and it may also be a potential risk factor for the development of atheromatous disease. This study assesses the utility of 2-D phase contrast Magnetic Resonance (MR) imaging with intra-sequence blood pressure measurement to determine carotid compliance and distensibility. 20 patients underwent 2-D phase contrast MR imaging and also ultrasound-based wall tracking measurements. Values for carotid compliance and distensibility were derived from the two different modalities and compared. Linear regression analysis was utilised to determine the extent of correlation between MR and ultrasound derived parameters. In those variables that could be directly compared, an agreement analysis was undertaken. MR measures of compliance showed a good correlation with measures based on ultrasound wall-tracking (r=0.61, 95% CI 0.34 to 0.81 p=0.0003). Vessels that had undergone carotid endarterectomy previously were significantly less compliant than either diseased or normal contralateral vessels (p=0.04). Agreement studies showed a relatively poor intra-class correlation coefficient (ICC) between diameter-based measures of compliance through either MR or ultrasound (ICC=0.14). MRI based assessment of local carotid compliance appears to be both robust and technically feasible in most subjects. Measures of compliance correlate well with ultrasound-based values and correlate best when cross-sectional area change is used rather than derived diameter changes. If validated by further larger studies, 2-D phase contrast imaging with intra-sequence blood pressure monitoring and off-line radial artery tonometry may provide a useful tool in further assessment of patients with carotid atheroma.