• 자원환경지질
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• 제53권4호
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• pp.479-489
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• 2020

단층은 근원암에서 형성된 석유 가스 등의 탄화수소가 이동하는 통로이자 탄화수소를 가두는 덮개암의 역할을 할 수 있는 지질구조로, 탄화수소가 축적된 저류층을 찾기 위한 탄성파 탐사의 주요 대상 중 하나이다. 하지만 기존의 유사성, 응집성, 분산, 기울기, 단층가능성 등 탄성파 자료의 측면 방향 불연속성을 활용하는 단층 감지 방법들은 전문지식을 갖춘 해석자가 많은 계산 비용과 시간을 투자해야 한다는 문제가 있다. 따라서 많은 연구자들이 단층 해석에 필요한 계산 비용과 시간을 절약하기 위한 다양한 연구를 진행하고 있고, 최근에는 머신러닝 기술을 활용한 연구들이 활발히 수행되고 있다. 단층 해석에는 다양한 머신러닝 기술들 중 서포트백터머신, 다층퍼셉트론, 심층 신경망, 합성곱 신경망 등의 알고리즘이 사용되고 있다. 특히 합성곱 신경망을 활용한 연구는 독자적인 구조의 모델을 사용한 연구뿐만 아니라, 이미지 처리 분야에서 성능이 검증된 모델을 활용한 연구 및 단층의 위치와 주향, 경사 등의 정보를 함께 해석하는 연구도 활발히 진행되고 있다. 이 논문에서는 이러한 연구들을 조사하고 분석하여, 현재까지 단층 위치 및 단층 정보 해석에 가장 효과적인 기술은 영상 처리 분야에서 검증된 U-Net 구조를 바탕으로 한 합성곱 신경망인 것을 확인했다. 이러한 합성곱 신경망에 전이학습 및 데이터 증식 기법을 접목하면 앞으로 더욱 효과적인 단층 감지 및 정보 해석이 가능할 것으로 기대된다.

• Structural Engineering and Mechanics
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• 제46권3호
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• pp.433-445
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• 2013

Vibration-based structural identification has become an important tool for structural health monitoring and safety evaluation. However, various kinds of uncertainties (e.g., observation noise) involved in the field test data obstruct automation system identification for accurate and fast structural safety evaluation. A practical way including a data preprocessing procedure and a vector backward auto-regressive (VBAR) method has been investigated for practical bridge identification. The data preprocessing procedure serves to improve the data quality, which consists of multi-level uncertainty mitigation techniques. The VBAR method provides a determinative way to automatically distinguish structural modes from extraneous modes arising from uncertainty. Ambient test data of a cantilever beam is investigated to demonstrate how the proposed method automatically interprets vibration data for structural modal estimation. Especially, structural identification of a truss bridge using field test data is also performed to study the effectiveness of the proposed method for real bridge identification.

• Journal of Information Processing Systems
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• 제19권4호
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• pp.474-482
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• 2023

Data mining is a technique for extracting valuable information from vast amounts of data by analyzing statistical and mathematical operations, rules, and relationships. In this study, we employed data mining technology to analyze the data concerning the painting poetry of Maehwado (plum blossom paintings) from the early Joseon Dynasty. The data was extracted from the Hanguk Munjip Chonggan (Korean Literary Collections in Classical Chinese) in the Hanguk Gojeon Jonghap database (Korea Classics DB). Using computer information processing techniques, we carried out web scraping and classification of the painting poetry from the Hanguk Munjip Chonggan. Subsequently, we narrowed down our focus to the painting poetry specifically related to Maehwado in the early Joseon Dynasty. Based on this, refined dataset, we conducted an in-depth analysis and interpretation of the text data at the syllable corpus level. As a result, we found a direct correlation between the corpus statistics for each syllable in Maehwado painting poetry and the symbolic meaning of plum blossoms.

• 상하수도학회지
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• 제36권4호
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• pp.239-248
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• 2022

The prediction of algal bloom is an important field of study in algal bloom management, and chlorophyll-a concentration(Chl-a) is commonly used to represent the status of algal bloom. In, recent years advanced machine learning algorithms are increasingly used for the prediction of algal bloom. In this study, XGBoost(XGB), an ensemble machine learning algorithm, was used to develop a model to predict Chl-a in a reservoir. The daily observation of water quality data and climate data was used for the training and testing of the model. In the first step of the study, the input variables were clustered into two groups(low and high value groups) based on the observed value of water temperature(TEMP), total organic carbon concentration(TOC), total nitrogen concentration(TN) and total phosphorus concentration(TP). For each of the four water quality items, two XGB models were developed using only the data in each clustered group(Model 1). The results were compared to the prediction of an XGB model developed by using the entire data before clustering(Model 2). The model performance was evaluated using three indices including root mean squared error-observation standard deviation ratio(RSR). The model performance was improved using Model 1 for TEMP, TN, TP as the RSR of each model was 0.503, 0.477 and 0.493, respectively, while the RSR of Model 2 was 0.521. On the other hand, Model 2 shows better performance than Model 1 for TOC, where the RSR was 0.532. Explainable artificial intelligence(XAI) is an ongoing field of research in machine learning study. Shapley value analysis, a novel XAI algorithm, was also used for the quantitative interpretation of the XGB model performance developed in this study.

• 아태비즈니스연구
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• 제14권1호
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• pp.365-379
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• 2023

Purpose - Our previous study (Chang & Lee, 2023) presented observations on the recent changes in the year-on-year (YoY) Consumer Price Index (CPI) of the Republic of Korea (ROK) after the COVID-19 pandemic. The purpose of this article is to present an integrated analysis and interpretation of the recent changes in CPI and the Aggregate Import Price Index (IPI) by incorporating recent data, specifically data from September 2022 to December 2022. Design/methodology/approach - This study collected CPI (YoY) data in the ROK from January 2019 to December 2022 using e-National Indicator System provided by the ROK. Statistical analysis was employed to analyze the data. Findings - First, we confirm the extended results of the existing study by Chang and Lee (2023). Second, we demonstrate that the Aggregate IPI in ROK increased significantly in 2022 compared to 2021. We then provide an integrated interpretation on the significant increase in CPI and aggregate IPI in ROK, which complements Chang and Lee (2023) that limits their discussion to YoY CPI. Moreover, we show that the IPI of the semiconductor in ROK decreased significantly in 2022 compared to 2021. Research implications or Originality - Our results provide important insights into the recent changes in the CPI in the ROK. The results suggest that these changes can be partially attributed to various factors, such as the global supply chain disruptions resulting from the spread of the COVID-19 pandemic and the prolonged war between Russia and Ukraine, the side effect of quantitative easing by the US Federal Reserve, heat waves and droughts caused by climate change in ROK, a surge in demand following a gradual daily recovery, US-China trade conflict, etc. Our study shows statistically comprehensive results compared to the studies that limit their discussion to YoY average growth rate.

• 대한불안의학회지
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• 제3권2호
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• pp.116-122
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• 2007

Objective : The purpose of this study was to investigate the strategies used to cope with stress and the cognitive characteristics of somatic symptom perception in patients with panic disorder. Methods : A total of 101 patients who met the DSM-IV criteria for panic disorder and 60 normal controls were recruited for participation in this study. We evaluated the subjects using The Way of Stress Coping Questionnaire (SCQ), Somato-Sensory Amplification Scale (SSAS), Symptom Interpretation Questionnaire (SIQ), and the Panic Disorder Severity Scale (PDSS). We analyzed the data using an independent t-test and Pearson correlation analysis (p<0.05). Results : The patients who used emotionally focused coping strategies scored significantly lower on the SCQ. The patients with panic disorder showed greater amplification of body sensations in the SSAS, a significantly higher score on the physical interpretation subset of the SIQ, and a lower score on the environmental interpretation subset of the SIQ than the normal controls. The PDSS scores were positively correlated with the SSAS score and physical interpretation score on the SIQ. Conclusion : These results show that patients with panic disorder have poor emotionally focused strategies for coping with stress, greater amplification of body sensations, and a tendency towards a physical interpretation of somatic symptoms.

• 한국임상수의학회지
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• 제26권3호
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• pp.189-199
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• 2009

With the growing importance of evidence-based medicine, clinical or biomedical research relies critically on the validity and reliability of data, and the subsequent statistical inferences for medical decision-making may lead to valid conclusion. Despite widespread use of analytical techniques in papers published in the Journal of Veterinary Clinics statistical errors particularly in design of experiments, research methodology or data analysis methods are commonly encountered. These flaws often leading to misinterpretation of the data, thereby, subjected to inappropriate conclusions. This article is the first in a series of nontechnical introduction designed not to systemic review of medical statistics but intended to provide the journal readers with an understanding of common statistical concepts, including data scale, selection of appropriate statistical methods, descriptive statistics, data transformation, confidence interval, the principles of hypothesis testing, sampling distribution, and interpretation of results.

• 한국방사선학회논문지
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• 제16권5호
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• pp.649-660
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• 2022

1959년도 Satomura가 분광 도플러 초음파를 이용하여 시간변화에 따른 적혈구의 속도를 표현하였고 Kato가 혈류의 방향을 알 수 있는 제로베이스 선(Zerobase line)을 정의하면서 혈류의 방향을 알 수 있게 되었다. 이는 현재 폭넓게 사용하고 있는 삼상파 (Triphasic), 이상파(Biphasic), 단상파(Monophasic) 분류의 기초가 되었다. 하지만 위와 같은 분류는 임상 환경에서 사용 의미와 시점에 사용자들에게 혼란을 주는 한계가 있었고 이와 같은 결과로 미국의 혈관의학회(Society for Vascular Medicine, SVM)와 혈관초음파학회(Society for Vascular Ultrasound, SVU)가 구성한 공동 위원회에서 도플러 파형 해석 합의문(Consensus document)을 선언하였다. 본 연구에서는 이 합의문을 고찰하고 국내 혈관 초음파 임상 현장에서 사용될 수 있는 명명법과 수식어를 제언하고자 하였다. SVM과 SVU가 구성한 공동 위원회에서는 동맥 삼상파(Triphasic waveform)와 이상파(Biphasic waveform)의 해석의 모호함을 이유로 사용을 지양하고 다상파(Multiphasic waveform)로 사용하길 권고 하였다. 또한 임상 환경에서 항상 해석의 문제가 되었던 단상파이면서 고저항성 파형인 하이브리드 형태 파형을 중저항성 파형(Intermediate resistive)으로 명명하기로 합의하였다. 또한 판독의사와 초음파사간에 의사소통의 효율성을 높이기 위해 파형 해석을 주 설명어(Main descriptor)와 수식어(Modifier)로 분류하였고 다양하게 사용하던 동의어들을 통일하여 하나의 명명법으로 사용하도록 권고하였다. 본 문헌 고찰을 통해 임상에서 혈관 초음파 검사 직무를 수행하는 방사선사들에게 정확한 동맥 분광 도플러 파형 해석과 합의된 명명법을 제공하여 국민보건향상에 이바지할 수 있는 기초자료로 활용되기를 기대한다.

• 한국정보통신학회논문지
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• 제11권9호
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• pp.1771-1780
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• 2007

인터넷의 발달과 기업환경의 변화로 인해 정보통합의 필요성이 강조되고 있고, 기업에서는M&A를 통해 기존의 구축된 멀티-데이터 베이스를 통합해야 하는 경우가 많다. 이러한 정보의 통합을 위해서는 이질성의 문제를 해결하여 상호운용성을 보장해야 하며, 안정된 통합을 보장해야 한다. 본 논문에서는 이질성 환경에서 상호운용성 문제를 해결하기 위해 표준과 로컬간의 연관성을 명시한 XMDR(eXtended Meta-Data Registry)을 기반으로 상호운영을 위한 글로벌 XML 쿼리를 로컬 XML 쿼리로 변화할 수 있는 방법을 제안한다. 따라서 XMDR에 의한 글로벌 XML 쿼리를 생성하여 멀티-데이터 베이스를 하나의 질의로 검색과 수정이 가능하게 하고, 래퍼는 레거시에 적합하도록 변환할 수 있도록 레퍼를 구체적으로 설계된 모델을 제안하고, 이러한 처리를 위하여 기존의 분산 트랜잭션 처리기법인 2PC방식을 적용하였다.

• Journal of the Korean Data and Information Science Society
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• 제25권6호
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• pp.1531-1538
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• 2014

The causes of cancer are diverse, complex, and only partially understood. Many factors including health behaviors, socioeconomic environments and geographical locations can directly damage genes or combine with existing genetic faults within cells to cause cancerous mutations. Collecting the cancer data and reporting the statistics, therefore, are important to help identify health trends and establish normal health changes in geographical areas. In this article, we analyzed cancer data and demon-strated how spatial patterns of the age-standardized rate and health indicators can be examined visually and simultaneously using linked micromap plots. As a result of data analysis, the age-standardized rate has positive correlativity with thyroid and breast cancer, but the rate has negative correlativity with smoking and drinking. In addition, the regions with high age-standardized rate are located in southwest and the areas of high population density while the standardized mortality ratio is higher in southwest and northeast where there are lots of rural areas.