• Title/Summary/Keyword: PD classification

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Charlson comorbidity index as a predictor of periodontal disease in elderly participants

  • Lee, Jae-Hong;Choi, Jung-Kyu;Jeong, Seong-Nyum;Choi, Seong-Ho
    • Journal of Periodontal and Implant Science
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    • v.48 no.2
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    • pp.92-102
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    • 2018
  • Purpose: This study investigated the validity of the Charlson comorbidity index (CCI) as a predictor of periodontal disease (PD) over a 12-year period. Methods: Nationwide representative samples of 149,785 adults aged ${\geq}60$ years with PD (International Classification of Disease, 10th revision [ICD-10], K052-K056) were derived from the National Health Insurance Service-Elderly Cohort during 2002-2013. The degree of comorbidity was measured using the CCI (grade 0-6), including 17 diseases weighted on the basis of their association with mortality, and data were analyzed using multivariate Cox proportional-hazards regression in order to investigate the associations of comorbid diseases (CDs) with PD. Results: The multivariate Cox regression analysis with adjustment for sociodemographic factors (sex, age, household income, insurance status, residence area, and health status) and CDs (acute myocardial infarction, congestive heart failure, peripheral vascular disease, cerebral vascular accident, dementia, pulmonary disease, connective tissue disorders, peptic ulcer, liver disease, diabetes, diabetes complications, paraplegia, renal disease, cancer, metastatic cancer, severe liver disease, and human immunodeficiency virus [HIV]) showed that the CCI in elderly comorbid participants was significantly and positively correlated with the presence of PD (grade 1: hazard ratio [HR], 1.11; P<0.001; grade ${\geq}2$: HR, 1.12, P<0.001). Conclusions: We demonstrated that a higher CCI was a significant predictor of greater risk for PD in the South Korean elderly population.

Fractal Analysis of GIS PD Patterns (GIS 부분방전 패턴의 프랙탈 해석)

  • Choi, Ho-Woong;Kim, Eun-Young;Min, Byoung-Woon;Lee, Dong-Chul;Kim, Hee-Soo
    • Proceedings of the KIEE Conference
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    • 2006.07e
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    • pp.55-56
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    • 2006
  • In prevention and diagnostic system of GIS, pattern classification is focused on the detection of unnatural patterns in PD(Partial discharge) image data. Fractals have been used extensively to provide a description and to model mathematically many of the naturally occurring complex shapes, such as coastlines, mountain ranges, clouds, etc., and have also received increased attention in the field of image processing, for purposes of segmentation and recognition of regions and objects present in natural scenes. Among the numerous fractal features that could be defined and used for image data, fractal dimension and lacunarity have been found to be useful for recognition purposes Partial discharge(PD) occuring in GIS system is a very complex phenomenon, and more so are the shapes of the various 2-d patterns obtained during routine tests and measurements. It has been fairly well established that these pattern shapes and underlying defects causing PD have a 1:1 correspondence, and therefore methods to describe and qunatify these pattern shapes must be explored, before recognition systems based on them could be developed. The computed fractal features(fractal dimension and lacunarity) for standard library of PD data were analyzed and found to possess fairly reasonable pattern discriminating abilities. This new approach appears promising, and further research is essential before any long-term predictions can be made.

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Smoking Rate of Workers according to Employment Status and Industry: 1992-2006 (산업군별 고용형태에 따른 근로자 흡연율 변화 추이: 1992-2006)

  • Kim, Il-Ho;Park, Ki-Soo;Chun, Hee-Ran;Noh, Samuel
    • Korean Journal of Health Education and Promotion
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    • v.28 no.4
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    • pp.15-25
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    • 2011
  • Objectives: The present study examined whether smoking rate has declined in 1992-2006 and who the high risk groups were on industry classification and employment type. Methods: Data from 91,263 persons aged 25-64 years were analyzed from three rounds of the Social Statistical Surveys of Korea between 1992 and 2006. Industry indicators were divided by the 9th Korean Standard Industrial Classification. Age-adjusted prevalence of smoking was calculated. Prevalence ratios(PR) and differences(PD) were estimated using log-binomial regression analysis. Results: Age-adjusted prevalence of smoking decreased between 1992 and 2006, specially the smoking prevalence of regular employees decreased most. PD in age-adjusted prevalence of smoking were the biggest between regular and daily employees. PR of the temporary employees', daily employees', self-employed persons' in order was wider than that of regular employees. PR increased significantly increased between 1999 and 2006 for those in manufacturing, construction, wholesale & retail trade, service industries. Increases in PR(regular/irregular) for women in service industry were statistically significant. Conclusions: Despite reducing overall cigarette smoking rates in males, the smoking rate was not reduced equally by industry classification and employment type in both genders. More adjustable antismoking policies and consideration of employment type are requested to reduce inequalities in smoking.

Evaluation on Degradation of Solid Insulator by PCA-LDA algorithm (PCA-LDA 알고리즘을 이용한 고체절연물의 열화도 판별)

  • Park, Seong-Hee;Kang, Seong-Hwa;Lim, Kee-Joe
    • Proceedings of the KIEE Conference
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    • 2005.07c
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    • pp.2079-2081
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    • 2005
  • Electrical treeing occurrence is caused by some defect in solid insulator. Those are accompany the PD(partial discharge) occurrence. And lifetime of the insulator is affected by PD. So, detection of electrical treeing is important thing as this view. Especially, detection of the end treeing is more important and have meaning for industrial engineering because concerned with maintenance and replacement of equipment. In this paper, evaluation of treeing process were studied and PCA(principle component analysis)-LDA(linear discriminant analysis) as classification method were used. The result is present the good recognition.

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Quantitatively Investigating the Effects of Multiple Strategies on Pre-Services Teachers' Mindset and Persistence

  • Meiners, Amanda;Choi, Kyong Mi;Hong, Dae
    • Research in Mathematical Education
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    • v.23 no.2
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    • pp.113-133
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    • 2020
  • Pre-service teachers (PST) are students who are developing their mindset, persistence, instructional practices, and perception of tasks from two perspectives: as current students and as future teachers. As part of a larger study with PSTs engaged in a mindset intervention, this study quantitatively investigated PSTs mindset and persistence. During professional development (PD), PSTs engaged in multiple strategies (MS) tasks that promoted changes to PSTs mindset and persistence. PSTs' mindset pre- and post- PD were categorized after attending at least 4 interventions as fixed, mixed, or growth using the theory of intelligence, and their persistence as high or low using the Grit-S. Changes in categorization were noticed and explored for reasons of what could be done to make mindset interventions more effective such as consistently using challenging mathematics tasks with more open ended answers and focusing on discussion based mathematical lessons.

A COMPARATIVE STUDY ON THE THEMATIC DISTRIBUTION OF THE ARTICLES PUBLISHED IN THE JOURNAL OF THE AMERICAN ACADEMY OF PEDIATRIC DENTISTRY AND THE JAPANESE SOCIETY OF PEDIATRIC DENTISTRY (90년대 이후 미국과 일본 소아치과학회지 게재논문의 분야별 분포에 관한 비교 연구)

  • Yeom, Junng-Hyun;Kim, Shin;Jeong, Tae-Sung
    • Journal of the korean academy of Pediatric Dentistry
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    • v.29 no.4
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    • pp.539-554
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    • 2002
  • To identify the trend of pediatric dentistry in USA and Japan, closely related to Korean pediatric dentistry. The Japanese Journal of Pediatric Dentistry(JJPD) and The Journal of the American Academy of Pediatric Dentistry(PD) were reviewed. We collected the bibliographical data of the articles published in the two journals from 1991 to 2000. We analyzed thematic distributions and chronological changes, and then compare those of two groups. The following results were obtained: 1. The 869 articles were published in JJPD and 672 in PD. This was about 30% more in JJPD. 2. In both JJPD and PD, the case reports were a quarter of scientific articles in quantity. 3. The studies on the systemic diseases had the highest proportion in both JJPD and PD. The studies on the dental caries and restorative materials also had high proportion in both journals. 4. The studies on the sedation and biochemical survey had high proportion in PD when had low proportion in JJPD. To the contrary, The studies on the behavior science in JJPD were about double of those in PD. 5. There was no statistically significant difference in quantity between JJPD and PD in the studies on the dental caries, prevention of dental caries, community dental survey, conservative treatment, restorative materials, pulp treatment, diagnosis and treatment of malocclusion, oral pathology and minor surgery, local anesthesia and nerve tissue, traumatic injuries. 6. There was statistically significant increase in the studies on the dental equipment in JJPD and in those on restorative materials in PD. 7. There was statistically significant decrease in the studies on the prevention of dental caries and local anesthesia and nerve tissue in JJPD, and those on conservative treatment in PD.

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Bio-marker Detector and Parkinson's disease diagnosis Approach based on Samples Balanced Genetic Algorithm and Extreme Learning Machine (균형 표본 유전 알고리즘과 극한 기계학습에 기반한 바이오표지자 검출기와 파킨슨 병 진단 접근법)

  • Sachnev, Vasily;Suresh, Sundaram;Choi, YongSoo
    • Journal of Digital Contents Society
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    • v.17 no.6
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    • pp.509-521
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    • 2016
  • A novel Samples Balanced Genetic Algorithm combined with Extreme Learning Machine (SBGA-ELM) for Parkinson's Disease diagnosis and detecting bio-markers is presented in this paper. Proposed approach uses genes' expression data of 22,283 genes from open source ParkDB data base for accurate PD diagnosis and detecting bio-markers. Proposed SBGA-ELM includes two major steps: feature (genes) selection and classification. Feature selection procedure is based on proposed Samples Balanced Genetic Algorithm designed specifically for genes expression data from ParkDB. Proposed SBGA searches a robust subset of genes among 22,283 genes available in ParkDB for further analysis. In the "classification" step chosen set of genes is used to train an Extreme Learning Machine (ELM) classifier for an accurate PD diagnosis. Discovered robust subset of genes creates ELM classifier with stable generalization performance for PD diagnosis. In this research the robust subset of genes is also used to discover 24 bio-markers probably responsible for Parkinson's Disease. Discovered robust subset of genes was verified by using existing PD diagnosis approaches such as SVM and PBL-McRBFN. Both tested methods caused maximum generalization performance.

Partial Discharge Data Analysis with Unsupervised Classification (무감독분류 기법에 의한 부분방전 데이터 분석)

  • Cho, Kyungsoon;Hong, Seonhack
    • Journal of Korea Society of Digital Industry and Information Management
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    • v.14 no.4
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    • pp.9-16
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    • 2018
  • This study described partial discharge(PD) distribution analysis between the XLPE(Cross-Linked PolyEthylene)and EPDM(Ethylene Propylene Diene Monomer) interface with unsupervised classification. The ${\phi}-q-n$ patterns were analyzed using phase resolved partial discharge(PRPD). K-means cluster analysis forms a cluster based on similarities and distances among scattered individuals, and analyzes the characteristics of the formed clusters, dividing the multivariate data into several groups according to the similarity of each characteristic, Is a statistical analysis that makes it easier to navigate. It was confirmed that the phase angle of the cluster with the maximum discharge charge was concentrated around $0^{\circ}$ and $180^{\circ}$ at 30 kV after the initial phase distribution localized around $90^{\circ}$ and $300^{\circ}$ expanded to the whole phase angle according to the voltage rise. The Euclidean distance between the center of gravity and the discharge charge in the ${\Phi}-q$ cluster increased with increasing applied voltage.

Effect of TLR4 and B7-H1 on Immune Escape of Urothelial Bladder Cancer and its Clinical Significance

  • Wang, Yong-Hua;Cao, Yan-Wei;Yang, Xue-Cheng;Niu, Hai-Tao;Sun, Li-Jiang;Wang, Xin-Sheng;Liu, Jing
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.3
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    • pp.1321-1326
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    • 2014
  • Background/Aim: Toll-like receptor 4 (TLR4) and B7-H1, both normally expressed restricted to immune cells, are found to be aberrantly expressed in a majority of human tumors and may play important roles in regulation of tumor immunity. It has been shown that urothelial bladder cancer (UBC) patients can manifest tumoral immune escape which may be a potential critical factor in tumor pathogenesis and progression. However, so far, the mechanisms of UBC-related immune escape have not been clarified. The aim of this study was to investigate the effect of TLR4 and B7-H1 on immune escape of UBC. Methods: Bladder cancer T24 cells were pre-incubated with LPS and co-cultured with tumor specific CTLs. CTL cytotoxicity and apoptosis rates were measured by MTT assay and flow cytometry, respectively. The effects of an ERK inhibitor on B7-H1 expression and CTL cytotoxicity against T24 cells were also evaluated. In addition, TLR4, B7-H1 and PD-1 protein expression was analyzed by immunohistochemistry in 60 UBC specimens and 10 normal urothelia. Results: TLR4 activation protected T24 cells from CTL killing via B7-H1 overexpression. However PD98059, an inhibitor of ERK, enhanced CTL killing of T24 cells by reducing B7-H1 expression. TLR4 expression was generally decreased in UBC specimens, while B7-H1 and PD-1 were greatly overexpressed. Moreover, expression of both B7-H1 and PD-1 was significantly associated with UICC stage and WHO grade classification. Conclusions: TLR4 and B7-H1 may contribute to immune escape of UBC. Targeting B7-H1 or the ERK pathway may offer new immunotherapy strategies for bladder cancer.

Classification of metals inducing filed aided lateral crystallization (FALC) of amorphous silicon

  • Jae-Bok Lee;Se-Youl Kwon;Duck-Kyun Choi
    • Journal of the Korean Crystal Growth and Crystal Technology
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    • v.11 no.4
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    • pp.160-165
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    • 2001
  • The effects of various metals on Field Aided Lateral Crystallization (FALC) behaviors of amorphous silicon (a-Si) were investigated. Under an influence of electric field, metals such s Cu, Ni and Co were found to fasten the lateral crystallization toward a metal-free region, exhibiting a typical FALC behavior while the lateral crystallization of a-Si was not obvious for Pd. However, Au, Al and Cr did not induce the lateral crystallization of a-Si in metal-free region. Such phenomenological differences in various metals were studied in terms of dominant diffusing species (DDS) in the reaction between metal and Si. It was judged that the applied electric field enhanced the crystallization velocity by accelerating the diffusion of metal atoms since the occurrence of lateral crystallization would be strongly dependent on the diffusion of metal atoms than that of Si atoms. Therefore, it was concluded that he only metal-dominant diffusing species in the reaction between metal and Si results in the crystallization of a-Si in metal-free region.

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