• Title/Summary/Keyword: 이차 데이터 분석

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Impact of Anthropometric Indices of Obesity on the Risk of Incident Hypertension in Adults with Prehypertension: A Secondary Analysis of a Cohort Study (고혈압 전단계 성인의 비만 인체측정지수가 고혈압 발생 위험에 미치는 영향: 코호트 연구를 활용한 이차분석)

  • Jang, Se Young;Kim, Jihun;Kim, Seonhwa;Lee, Eun Sun;Choi, Eun Jeong
    • Journal of Korean Academy of Nursing
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    • v.54 no.1
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    • pp.18-31
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    • 2024
  • Purpose: This study aimed to investigate the impact of anthropometric indices of obesity (body mass index [BMI], waist circumference, waist hip ratio, and body fat percentage) on the incidence of hypertension in adults with prehypertension. Methods: A longitudinal study design using secondary data form the Korean Genome and Epidemiology Study was employed. The study included 1,838 adults with prehypertension tracked every two years from 2001 to 2018. Statistical analyses, including frequency assessments, number of cases per 1,000 person-years, log-rank tests, Kaplan-Meier curves, and Cox's proportional hazards regression, were conducted using SPSS version 25. Results: Over the observation period (15,783.6 person-years), 1,136 individuals developed hypertension. The incidence of hypertension was significantly higher in the obesity groups defined by BMI (hazard ratio [HR] = 1.33), waist circumference (HR = 1.34), waist hip ratio (HR = 1.29), and body fat percentage (HR = 1.31) compared to the non-obese group. These findings indicate an increased risk of hypertension associated with obesity as measured by these indices. Conclusion: The study underscores the importance of avoiding obesity to prevent hypertension in individuals with prehypertension. Specifically, BMI, waist circumference, waist hip circumference, and body fat percentage were identified as significant risk factors for hypertension. The results suggest the need for individualized weight control interventions, emphasizing the role of health professionals in addressing the heightened hypertension risk in this population.

A Physical Design Method of Storage Structures for MOLAP Systems of Data Warehouse (데이터 웨어하우스의 다차원 온라인 분석처리 시스템을 위한 저장구조의 물리적 설계기법)

  • Lee Jong-Hak
    • Journal of Korea Multimedia Society
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    • v.8 no.3
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    • pp.297-312
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    • 2005
  • Aggregation is an operation that plays a key role in multidimensional OLAP (MOLAP) systems of data warehouse. Existing aggregation operations in MOLAP have been proposed for file structures such as multidimensional arrays. These tile structures do not work well with skewed distributions. This paper presents a physical design methodology for storage structures ni MOLAP that use the multidimensional tile organizations adapting to a skewed distribution. In uniform data distribution, we first show that the performance of multidimensional analytical processing is highly affected by the similarity of the shapes between query regions and page regions in the domain space of the multidimensional file organizations. And than, in skewed distributions, we reflect the effect of data distributions on the design by using the shapes of the normalized query regions that are weighted with data density of those query regions. Finally, we demonstrate that the physical design methodology theoretically derived is indeed correct in real environments. In the two-dimensional file organizations, the results of experiments indicate that the performance of the proposed method is enhanced by more than seven times over the conventional method. We expect that the performance will be more enhanced when the dimensionality is more than two. The result confirms that the proposed physical design methodology is useful in a practical way.

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Design of Real-time Face Recognition Systems Based on Data-Preprocessing and Neuro-Fuzzy Networks for the Improvement of Recognition Rate (인식률 향상을 위한 데이터 전처리와 Neuro-Fuzzy 네트워크 기반의 실시간 얼굴 인식 시스템 설계)

  • Yoo, Sung-Hoon;Oh, Sung-Kwun;Kim, Hyun-Ki
    • Proceedings of the KIEE Conference
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    • 2011.07a
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    • pp.1952-1953
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    • 2011
  • 본 논문에서는 다항식 기반 Radial Basis Function(RBF)신경회로망(Polynomial based Radial Basis function Neural Network)을 설계하고 이를 n-클래스 패턴 분류 문제에 적용한다. 제안된 다항식기반 RBF 신경회로망은 입력층, 은닉층, 출력층으로 이루어진다. 입력층은 입력 벡터의 값들을 은닉층으로 전달하는 기능을 수행하고 은닉층과 출력층사이의 연결가중치는 상수, 선형식 또는 이차식으로 이루어지며 경사 하강법에 의해 학습된다. Networks의 최종 출력은 연결가중치와 은닉층 출력의 곱에 의해 퍼지추론의 결과로서 얻어진다. 패턴분류기의 최적화는 PSO(Particle Swarm Optimization)알고리즘을 통해 이루어진다. 그리고 제안된 패턴분류기는 실제 얼굴인식 시스템으로 응용하여 직접 CCD 카메라로부터 입력받은 데이터를 영상 보정, 얼굴 검출, 특징 추출 등과 같은 처리 과정을 포함하여 서로 다른 등록인물의 n-클래스 분류 문제에 적용 및 평가되어 분류기로써의 성능을 분석해본다.

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Improving Image Quality of MRI using Frequency Filter (Frequency Filter를 사용한 MRI 영상 화질의 향상)

  • Kim, Dong-Hyun
    • The Journal of the Korea Contents Association
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    • v.9 no.11
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    • pp.309-315
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    • 2009
  • Image reconstruction of Inverse Fourier Transform after Frequency Domain Data is filtered applies to Image signal acquired from MR. There are various kinds of image processing techniques; image preprocessing, image reconstruction, image compression, image restoration image mixture, noise and artifact elimination, and image quality improvement. In this paper, optimum filter applicable to diagnosis in clinic by comparing and analyzing the characteristics of the filter will be explained. Fermi-Dirac filter will improve the image quality better than the previous MR image.

Performance Evaluation of Skewed Read-Head for Shingled Magnetic Recording (트랙을 겹쳐서 쓰는 자기기록 방식에서 리드헤드가 틀어진 경우의 성능 분석)

  • Kim, Byungsun;Lee, Jaejin
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.39A no.9
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    • pp.514-518
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    • 2014
  • The shingled magnetic recording method has interference between adjacent tracks. Furthermore, when read-head reads the data along the track, the head can be skewed by some physical effects. In this paper, in order to solve this problem, we propose a two-dimensional equalizer that uses two heads. If the head is skewed, it is possible to complement the performance by positioning the two heads at the center of the current track.

A Study on Pattern Recognition Using Polynomial-based Radial Basis Function Neural Networks (다항식기반 RBF 신경회로망을 이용한 패턴인식에 대한 연구)

  • Ji, Kwang-Hee;Kim, Woong-Ki;Oh, Sung-Kwun
    • Proceedings of the IEEK Conference
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    • 2009.05a
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    • pp.387-389
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    • 2009
  • 본 논문에서는 다항식 기반 Radial Basis Function(RBF)신경 회로망을 설계하고 이를 패턴분류 문제에 적용하여 그 성능을 분석한다. 제안된 RBF 신경회로망은 입력층, 은닉층, 출력층으로 이루어진다. 입력층의 연결가중치는 1로서 입력층의 입력벡터는 그대로 은닉층으로 전달되고 은닉층은 FCM(Fuzzy C-means Clustering)방법을 통하여 뉴런의 출력 값으로 내보낸다. 은닉층과 출력층사이의 연결가중치는 상수, 선형식 또는 이차식으로 이루어지며 경사 하강법에 의해 학습되어진다. 네트워크의 최종 출력은 연결가중치와 은닉층 출력의 곱에 의한 퍼지추론의 결과로 얻어진다. 제안된 RBF 신경회로망은 여러 종류의 machine learning 데이터에 적용하여 패턴분류기로서의 성능을 평가받는다.

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Comparison of Discriminant Analyses for Consumers' Taste Grade on Hanwoo (한우 맛 등급 판별방법 비교 연구)

  • Kim, Jae-Hee;Seo, Gu-Re-Oun-Den-Nim
    • The Korean Journal of Applied Statistics
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    • v.21 no.6
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    • pp.969-980
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    • 2008
  • This paper presents the comparison of four methods, linear, quadratic, canonical and non-parametric discriminant analyses to discriminate the consumers' taste grade with sensory variables, such as tenderness, juiciness, flavor, and overall acceptability based on Consumer Sensory Survey. The classification ability of each method is measured and compared by the resubstitution error rate.

Field Data Analyses of Two-Dimensional Warranty Data (이차원 보증 사용현장데이터의 분석)

  • Jung Min;Bai Do Sun
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2002.05a
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    • pp.762-766
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    • 2002
  • This paper proposes a method or estimating lifetime distribution for products under two-dimensional warranty in which age and usage are used simultaneously to determine the eligibility of a warranty claim. For such a case, existing methods reduce the two-dimensional time stale to a single stale assuming that the two variables have a functional relationship. This assumption is, however, not appropriate since the functional relationship is unknown in practice. In this paper, the field age and usage data are modeled with a bivariate lifetime distribution. Method of obtaining maximum likelihood estimators is outlined, their asymptotic properties are studied and specific formulas for a bivariate Weibull distribution are obtained. The proposed model is compared with the existing one which assumes a lineal relationship between the two variables Simulation studios are performed to investigate the effect of the degree of dependency between the two variables.

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A Design Method of Storage Structures for MOLAP Systems (MOLAP 시스템을 위한 다차원 저장구조의 설계기법)

  • Lee Jong-Hak;Lee Seong-Won
    • Proceedings of the Korean Information Science Society Conference
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    • 2005.07b
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    • pp.130-132
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    • 2005
  • 다차원 온라인 분석처리 시스템(MOLAP)에서 집계 연산은 중요한 기본 연산이다. 기존의 MOLAP 집계 연산은 다차원 배열구조를 기반으로 한 파일구조에 대해서 연구되어 왔다. 다차원 배열구조는 편중된 분포를 갖는 데이터에서는 잘 동작하지 못한다는 단점이 있다. 본 논문에서는 편중된 분포에도 잘 동작하는 다차원 파일구조를 사용한 MOLAP 저장구조의 물리적 설계기법을 제안한다. 실험결과에 의하면 이차원 파일구조의 경우 집계 연산처리를 위한 저장구조의 성능이 일곱 배 이상까지 향상됨을 확인하였다. 삼차원 이상의 파일구조에 대해서는 더욱더 큰 성능향상이 예상된다. 이러한 성능의 향상은 제안된 MOLAP 저장구조의 물리적 설계기법이 매우 유용함을 나타내는 것이다.

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Analysis of Secondary Battery Based on Image Processing of Computed Tomography (CT 기반 영상처리를 이용한 이차전지의 분석)

  • Jea-Seok Oh;Sang-Yeol Lee;Yoon-Gi Yang;Keun-Ho Rew
    • Journal of Information Technology Applications and Management
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    • v.29 no.6
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    • pp.13-21
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    • 2022
  • In this study, we presented a method to inspect the mechanical defects of 4680 type lithium-ion batteries through image processing method. The raw X-ray images are filtered with CLAHE, then Radon inverse transformations are calculated to reconstruct 3D computed tomography of the battery. Using Haar-cascade, the ROI is targeted automatically, and the template matchings are applied twice. The variations of contrast between template and background show the appropriate values for detecting tabs. It was shown that the proposed algorithm can detect all the tab inside the battery and the distances between tabs. Finally, we successfully found the geometrical defects of battery.