• Journal of Astronomy and Space Sciences
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• 제41권1호
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• pp.35-42
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• 2024

Sungrazing comets, known for their proximity to the Sun, are traditionally classified into broad groups like Kreutz, Marsden, Kracht, Meyer, and non-group comets. While existing methods successfully categorize these groups, finer distinctions within the Kreutz subgroup remain a challenge. In this study, we introduce an automated classification technique using the densitybased spatial clustering of applications with noise (DBSCAN) algorithm to categorize sungrazing comets. Our method extends traditional classifications by finely categorizing the Kreutz subgroup into four distinct subgroups based on a comprehensive range of orbital parameters, providing critical insights into the origins and dynamics of these comets. Corroborative analyses validate the accuracy and effectiveness of our method, offering a more efficient framework for understanding the categorization of sungrazing comets.

• 지능정보연구
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• 제21권4호
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• pp.1-16
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• 2015

교통사고의 원인을 규명하고 미래의 사고를 방지하기 위한 노력의 일환으로 데이터 마이닝 기법을 이용한 교통 데이터 분석의 연구가 이루어지고 있다. 하지만 기존의 교통 데이터를 이용한 마이닝 연구들은 학습된 결과를 사람이 이해하기 어려워 분석에 많은 노력이 필요하다는 문제가 있었다. 본 논문에서는 많은 속성들로 표현된 교통사고 데이터로부터 유용한 패턴을 발견하기 위해 규칙 학습 기반의 데이터 마이닝 기법인 연관규칙 학습기법과 서브그룹 발견기법을 적용하였다. 연관규칙 학습기법은 비지도 학습 기법의 하나로 데이터 내에서 동시에 많이 등장하는 아이템(item)들을 찾아 규칙의 형태로 가공해 주며, 서브그룹 발견기법은 사용자가 지정한 대상 속성이 결론부에 나타나는 규칙을 학습하는 지도학습 기반 기법으로 일반성과 흥미도가 높은 규칙을 학습한다. 규칙 학습 시 사용자의 의도를 반영하기 위해서는 하나 이상의 관심 속성들을 조합한 합성 속성을 만들어 규칙을 학습할 수 있다. 규칙이 도출되고 나면 후처리 과정을 통해 중복된 규칙을 제거하고 유사한 규칙을 일반화하여 규칙들을 더 단순하고 이해하기 쉬운 형태로 가공한다. 교통사고 데이터를 대상으로 두 기법을 적용한 결과 대상 속성을 지정하지 않고 연관규칙 학습기법을 적용하는 경우 사용자가 쉽게 알기 어려운 속성 사이의 숨겨진 관계를 발견할 수 있었으며, 대상 속성을 지정하여 연관규칙 학습기법과 서브그룹 발견기법을 적용하는 경우 파라미터 조정에 많은 노력을 기울여야 하는 연관규칙 학습기법에 비해 서브그룹 발견기법이 흥미로운 규칙들을 더 쉽게 찾을 수 있음을 확인하였다.

• 디지털산업정보학회논문지
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• 제17권1호
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• pp.75-84
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• 2021

For analyzing big data, the social network is increasingly being utilized through relational data, which means the connection characteristics between entities such as people and objects. When the relational data does not exist directly, a social network can be configured by calculating relational data such as attribute similarity from attribute data of entities and using it as links. In this paper, the composition method of the social network using the attribute similarity between entities as a connection relationship, and the clustering method using subgroups for the configured social network are suggested, and the clustering effectiveness of the clustering results is evaluated. The analysis results can vary depending on the type and characteristics of the data to be analyzed, the type of attribute similarity selected, and the criterion value. In addition, the clustering effectiveness may not be consistent depending on the its evaluation method. Therefore, selections and experiments are necessary for better analysis results. Since the analysis results may be different depending on the type and characteristics of the analysis target, options for clustering, etc., there is a limitation. In addition, for performance evaluation of clustering, a study is needed to compare the method of this paper with the conventional method such as k-means.

• The Plant Pathology Journal
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• 제30권2호
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• pp.183-187
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• 2014

Lettuce mosaic virus (LMV) causes disease of plants in the family Asteraceae, especially lettuce crops. LMV isolates have previously been clustered in three main groups, LMV-Yar, LMV-Greek and LMV-RoW. The first two groups, LMV-Yar and LMV-Greek, have similar characteristics such as no seed-borne transmission and non-resistance-breaking. The latter one, LMV-RoW, comprising a large percentage of the LMV isolates contains two large subgroups, LMV-Common and LMV-Most. To date, however, no Korean LMV isolate has been classified and characterized. In this study, LMV-Muju, the Korean LMV isolate, was isolated from lettuce showing pale green and mottle symptoms, and its complete genome sequence was determined. Classification method of LMV isolates based on nucleotide sequence divergence of the NIb-CP junction showed that LMV-Muju was categorized as LMV-Common. LMV-Muju was more similar to LMV-O (LMV-Common subgroup) than to LMV-E (LMV-RoW group but not LMV-Common subgroup) even in the amino acid domains of HC-Pro associated with pathogenicity, and in the CI and VPg regions related to ability to overcome resistance. Taken together, LMV-Muju belongs to the LMV-Common subgroup, and is expected to be a seed-borne, non-resistance-breaking isolate. According to our analysis, all other LMV isolates not previously assigned to a subgroup were also included in the LMV-RoW group.

• Journal of Cerebrovascular and Endovascular Neurosurgery
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• 제25권2호
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• pp.143-149
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• 2023

Objective: The purpose of this nationwide age- and sex- matched longitudinal study was to determine the pyogenic spondylitis (PS) increases the incidence of ischemic stroke (IS) in Korea. Methods: From the National Health Insurance Service (NHIS), we collected the patient data for the period from January 1, 2004 to December 31, 2015. PS was classified according to the International Classification of Disease codes M46.2-M46.8, M49.2, and M49.3. By using a 1:5 age- and sex- stratified matching, a total of 628 patients and 3140 control subjects were included in the study. The IS incidence rates in PS and control group was calculated by using the Kaplan-Meier method. The outcome of hazard ratio of IS was estimated by Cox proportional hazards regression analyses. This study did not exclude PS as a result of postoperative complications. Results: According to the study, 51 patients (8.12%) in the PS group and 201 patients (6.4%) in the control group experienced IS. The adjusted hazard ratio of IS in the PS group was 3.419 (95% CI: 2.473-4.729) after adjusting individual medical condition and demographics. Following the results of subgroup analysis, the risk ratio of IS was greater in most of the subgroup categories (male, female, age <65, age >65, non-diabetic, hypertensive, non-hypertensive, dyslipidemic and non-dyslipidemic subgroup). However, the risk of IS did not differ significantly in diabetic subgroup (95% CI: 0.953-4.360). Conclusions: The risk rate of IS increased in patient with pyogenic spondylitis.

• Nuclear Engineering and Technology
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• 제47권7호
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• pp.791-803
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• 2015

The effective cross sections (XSs) in the direct whole core calculation code nTRACER are evaluated by the equivalence theory-based resonance-integral-table method using the WIMS-based library as an alternative to the subgroup method. The background XSs, as well as the Dancoff correction factors, were evaluated by the enhanced neutron-current method. A method, with pointwise microscopic XSs on a union-lethargy grid, was used for the generation of resonance-interference factors (RIFs) for mixed resonant absorbers. This method was modified by the intermediate-resonance approximation by replacing the potential XSs for the non-absorbing moderator nuclides with the background XSs and neglecting the resonance-elastic scattering. The resonance-escape probability was implemented to incorporate the energy self-shielding effect in the spectrum. The XSs were improved using the proposed method as compared to the narrow resonance infinite massbased method. The RIFs were improved by 1% in $^{235}U$, 7% in $^{239}Pu$, and >2% in $^{240}Pu$. To account for thermal feedback, a new feature was incorporated with the interpolation of pre-generated RIFs at the multigroup level and the results compared with the conventional resonance-interference model. This method provided adequate results in terms of XSs and k-eff. The results were verified first by the comparison of RIFs with the exact RIFs, and then comparing the XSs with the McCARD calculations for the homogeneous configurations, with burned fuel containing a mixture of resonant nuclides at different burnups and temperatures. The RIFs and XSs for the mixture showed good agreement, which verified the accuracy of the RIF evaluation using the proposed method. The method was then verified by comparing the XSs for the virtual environment for reactor applicationbenchmark pin-cell problem, as well as the heterogeneous pin cell containing burned fuel with McCARD. The method works well for homogeneous, as well as heterogeneous configurations.

• 대한수학회보
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• 제46권5호
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• pp.823-833
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• 2009

It is well-known that if a convex hyperbolic polygon is constructed as a fundamental domain for a subgroup of the modular group, then its translates by the group elements form a locally finite tessellation and its side-pairing transformations form a system of generators for the group. Such hyperbolically convex polygons can be obtained by using Dirichlet's and Ford's polygon constructions. Another method of obtaining a fundamental domain for subgroups of the modular group is through the use of a right coset decomposition and we call such domains standard fundamental domains. In this paper we give subgroups of the modular group which do not have hyperbolically convex standard fundamental domain containing only inequivalent cusps.

• 품질경영학회지
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• 제19권2호
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• pp.172-180
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• 1991

The null hypothesis being tested by $the{\bar{X}}$ control chart is that the process is in control at a quality level ${\mu}o$. An ${\bar{X}}control$ chart is a tool for detecting process average changes due to assingnable causes. The major weakness of $the{\bar{X}}$ control chart is that it is relatively insensitive to small changes in the population mean. This paper presents one way to remedy this weakness is to allow each plotted value to depend not only on the most recent subgroup average but on some of the other subgroup averages as well. Two approaches for doing this are based on (1) moving averages and (2) exponentially weighted moving averages of forecasting method.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 2002년도 추계학술발표회요약집
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• pp.50-50
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• 2002

• 한국산림과학회지
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• 제105권1호
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• pp.48-62
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• 2016

본 연구는 덕유산국립공원 향적봉 및 중봉 아고산대를 대상으로 총 48개소의 고정방형구를 설치하여 Z-M 식물사회학적 방법으로 군락유형분류와 임분 구조를 분석하였던 바, 신갈나무군락군에서 군락단위로 가문비나무군락, 까치박달군락, 피나무군락으로 분류되었으며 가문비나무군락은 물참대군, 백당나무군으로 세분되었다. 군단위로 물참대군은 복장나무소군과 까치밥나무소군으로 세분되었으며, 백당나무군은 각시원추리소군과 귀룽나무소군으로 세분되었다. 중요치를 분석한 결과, 교목층을 구성하는 주요 종으로는 신갈나무(23.9%), 구상나무(14.7%), 주목(10.2%), 가문나무(8.2%), 사스래나무(7.4%)로 나타났으며, 아교목층은 시닥나무(18.6%), 당단풍나무(18.4%), 신갈나무(8.9%)로 나타났으며, 관목층은 철쭉(20.7%), 당단풍나무(17.4%), 노린재나무(8.5%)로 나타났다. 식생단위 1의 지표종은 산수국, 들메나무, 물참대와 같은 아고산의 적습한 계곡부 또는 전석지 환경을 선호하는 종들이 나타났다. 종다양도는 식생단위 1, 4, 5는 생육환경이 이질적이고 복잡하거나 국소적인 교란이 있었을 것으로 사료된다. 가문비나무군락의 하위단위인 복장나무아군, 까치밥나무아군, 각시원추리아군, 귀룽나무아군의 식생단위 1, 2, 3, 4는 유사도 지수가 0.5 이상으로 식생단위 간 유사도가 높은 경향으로 나타나, 식생단위 간 구성종의 차이가 크지 않은 것으로 판단된다.