Outlier Detection in Large-Scale Traffic Data by Regression Analysis

Few studies have reported the relationship between knee pain and hypercholesterolemia in the elderly population with osteoarthritis (OA), independent of other variables. The aim of this study was to reveal the association between knee pain and metabolic diseases including hypercholesterolemia using a large-scale cohort. A cross-sectional study was conducted using data from the Korea National Health and the Nutrition Examination Survey (KNHANES-V, VI-1; 2010–2013). Among the subjects aged ≥60 years, 7438 subjects (weighted number estimate = 35,524,307) who replied knee pain item and performed the simple radiographs of knee were enrolled. Using multivariable ordinal logistic regression analysis, variables affecting knee pain were identified, and the odds ratio (OR) was calculated. Of the 35,524,307 subjects, 10,630,836 (29.9%) subjects experienced knee pain. Overall, 20,290,421 subjects (56.3%) had radiographic OA, and 8,119,372 (40.0%) of them complained of knee pain. Multivariable ordinal logistic regression analysis showed that among the metabolic diseases, only hypercholesterolemia was positively correlated with knee pain in the OA group (OR 1.24; 95% Confidence Interval 1.02–1.52, p = 0.033). There were no metabolic diseases correlated with knee pain in the non-OA group. This large-scale study revealed that in the elderly, hypercholesterolemia was positively associated with knee pain independent of body mass index and other metabolic diseases in the OA group, but not in the non-OA group. These results will help in understanding the nature of arthritic pain, and may support the need for exploring the longitudinal associations.

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Outlier detection in traffic data based on the Dirichlet process mixture model

IET Intelligent Transport Systems ◽

10.1049/iet-its.2014.0063 ◽

2015 ◽

Vol 9 (7) ◽

pp. 773-781 ◽

Cited By ~ 12

Author(s):

Henry Y.T. Ngan ◽

Anthony G.O. Yeh ◽

Nelson H.C. Yung

Keyword(s):

Outlier Detection ◽

Mixture Model ◽

Dirichlet Process ◽

Traffic Data ◽

Dirichlet Process Mixture ◽

Dirichlet Process Mixture Model

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When Taxi Meets Bus: Night Bus Stop Planning over Large-Scale Traffic Data

2016 7th International Conference on Cloud Computing and Big Data (CCBD) ◽

10.1109/ccbd.2016.015 ◽

2016 ◽

Cited By ~ 2

Author(s):

Luyan Xiao ◽

Xiaopeng Fan ◽

Haixia Mao ◽

Chengzhong Xu ◽

Ping Lu ◽

...

Keyword(s):

Large Scale ◽

Traffic Data ◽

Bus Stop

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Anatomical Predictors of Endoleaks or Migration After Endovascular Aneurysm Sealing

Journal of Endovascular Therapy ◽

10.1177/1526602818808296 ◽

2018 ◽

Vol 25 (6) ◽

pp. 719-725 ◽

Cited By ~ 7

Author(s):

Kim van Noort ◽

Johannes T. Boersen ◽

Aleksandra C. Zoethout ◽

Richte C. L. Schuurmann ◽

Jan M. M. Heyligers ◽

...

Keyword(s):

Regression Analysis ◽

Large Scale ◽

High Volume ◽

Control Group ◽

Neck Length ◽

Aortic Neck ◽

Distal Migration ◽

Aneurysm Growth ◽

Instructions For Use ◽

Neck Diameter

Purpose: To identify preoperative anatomical aortic characteristics that predict seal failures after endovascular aneurysm sealing (EVAS) and compare the incidence of events experienced by patients treated within vs outside the instructions for use (IFU). Methods: Of 355 patients treated with the Nellix EndoVascular Aneurysm Sealing System (generation 3SQ+) at 3 high-volume centers from March 2013 to December 2015, 94 patients were excluded, leaving 261 patients (mean age 76±8 years; 229 men) for regression analysis. Of these, 83 (31.8%) suffered one or more of the following events: distal migration ⩾5 mm of one or both stent frames, any endoleak, and/or aneurysm growth >5 mm. Anatomical characteristics were determined on preoperative computed tomography (CT) scans. Patients were divided into 3 groups: treated within the original IFU (n=166), outside the original IFU (n=95), and within the 2016 revised IFU (n=46). Categorical data are presented as the median (interquartile range Q1, Q3). Results: Neck diameter was significantly larger in the any-event cohort vs the control cohort [23.7 mm (21.7, 26.3) vs 23.0 mm (20.9, 25.2) mm, p=0.022]. Neck length was significantly shorter in the any-event cohort [15.0 mm (10.0, 22.5) vs 19.0 mm (10.0, 21.8), p=0.006]. Maximum abdominal aortic aneurysm (AAA) diameter and the ratio between the maximum AAA diameter and lumen diameter in the any-event group were significantly larger than the control group (p=0.041 and p=0.002, respectively). Regression analysis showed aortic neck diameter (p=0.006), neck length (p=0.001), and the diameter ratio (p=0.011) as significant predictors of any event. In the comparison of events to IFU status, 52 (31.3%) of 166 patients in the inside the original IFU group suffered an event compared to 13 (28.3%) of 46 patients inside the 2016 IFU group (p=0.690). Conclusion: Large neck diameter, short aortic neck length, and the ratio between the maximum AAA and lumen diameters are preoperative anatomical predictors of the occurrence of migration (⩾5 mm), any endoleak, and/or aneurysm growth (>5 mm) after EVAS. Even under the refined 2016 IFU, more than a quarter of patients suffered from an event. Improvements in the device seem to be necessary before this technique can be implemented on a large scale in endovascular AAA repair.

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Do Housing Vacancies Induce More Crime? A Spatiotemporal Regression Analysis

Crime & Delinquency ◽

10.1177/0011128719854347 ◽

2019 ◽

Vol 66 (11) ◽

pp. 1579-1605 ◽

Cited By ~ 1

Author(s):

Xiaojin Chen ◽

Patrick Rafail

Keyword(s):

Regression Analysis ◽

Collective Efficacy ◽

Large Scale ◽

Spillover Effect ◽

Property Crime ◽

Drug Offense ◽

Community Based Programs ◽

The City ◽

Housing Vacancy ◽

Neighborhood Level

This study aims to investigate the longitudinal associations between patterns of housing vacancies, neighborhood social disorder, and crime in the city of New Orleans. Using large-scale administrative and contextual data collected from the year 2012 to 2018, our spatiotemporal regression analysis provides empirical evidence for the salient effects of housing vacancy on neighborhood level of property crime and violence. In addition, the spillover effect of housing vacancy is observed on the neighborhood level of drug offense, property crime, and violence. These results potentially identify vacant properties as a modifiable target for intervention to reduce urban crime and suggest that community-based programs aiming to enhance informal social control and collective efficacy may be as important as broken window policing programs.

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The Impact of Extraversion and Sensation Seeking on Tourist Role

Social Behavior and Personality An International Journal ◽

10.2224/sbp.2015.43.1.75 ◽

2015 ◽

Vol 43 (1) ◽

pp. 75-84 ◽

Cited By ~ 6

Author(s):

Cheng-Yu Li ◽

Shiao-Yuan Lu ◽

Bi-Kun Tsai ◽

Keh-Yuan Yu

Keyword(s):

Logistic Regression ◽

Regression Analysis ◽

Logistic Regression Analysis ◽

Sensation Seeking ◽

Large Scale ◽

Personality Variables ◽

Tourism Marketing ◽

Large Scale Survey ◽

And Behaviors ◽

The Impact

In recent years, personality variables, such as extraversion and sensation seeking, have been used to investigate tourist preferences and behaviors. For this study, we classified tourist roles into three types: the familiarized mass tourist, the organized mass tourist, and the independent tourist. We investigated the impact of extraversion and sensation seeking on tourist roles in a large-scale survey of Taiwanese citizens (N = 1,249) aged 20 years and older. Using logistic regression analysis, the results indicated that sensation seeking was a significant predictor of tourist role, but extraversion was not. Compared to familiarized mass tourists, people who are sensation-seeking are more likely to become independent tourists rather than organized mass tourists. We provide suggestions for tourism marketing.

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