Assessment of chemical equivalence in herbal materials using chromatographic fingerprints by combination of three similarity indices and three-dimensional kernel density estimation

Lee, Gwang Jin,Lee, Jeong Hee,Park, Jeong Hill,Kwon, Sung Won,Lim, Johan,Lee, Sungim,Lee, Jeongmi Elsevier 2018 Analytica chimica acta Vol.1037 No.-

<P><B>Abstract</B></P> <P>An intuitive and practical way to control chemical equivalence of secondary metabolites in herbal materials based on chromatographic fingerprints deserves a thorough discussion, yet it is relatively unexplored. For the first time, we propose a mixture of three similarity indices, the congruence coefficient, the average of the peak area ratios, and the larger value between the maximum peak area ratio and the reciprocal of the minimum peak area ratio, to make up for the weak points of some widely used similarity indices and to evaluate the chemical equivalence of two fingerprints from various perspectives. The three similarity values are fed into a three-dimensional kernel density estimation to determine the quality of herbal materials. This estimation enables precise detection of anomalies in the absence of prior quality determination experience. Forty <I>Atractylodes</I> samples similar in appearance and indiscriminately used for medical purposes were used to demonstrate the effectiveness of the developed approach. After a reference sample was postulated, a quality assessment of the 40 samples was performed using the three similarity values and the estimated kernel density. The samples that were judged by the developed approach to be of good quality were compared with those chosen by the most popular approach using decision criterion of a single similarity index. The benefits of the proposed approach were evident in that the qualified samples had the composition ratio and individual concentrations of multi-components closer to those of the reference in general, and their inter-sample deviation was significantly smaller.</P> <P><B>Highlights</B></P> <P> <UL> <LI> A novel method was developed to assess chemical equivalence of herbal materials. </LI> <LI> A mixture of three similarity indices from chromatographic fingerprints was used. </LI> <LI> Three-dimensional kernel density estimation was applied in herbal fingerprints. </LI> <LI> The new method was successfully applied to quality assessment of 40 real samples. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>

Design of combined Shewhart-EWMA schemes

( Sungim Lee ),( Johan Lim ) 한국품질경영학회 2020 한국품질경영학회 학술대회 Vol.2020 No.-

A control chart is a popular tool to detect changes in process in various applications, including the manufacturing industry. We often meet two types of changes in process; one is a large and abrupt change, and the other is small and gradual changes over time. The two most popular charts in the literature are the X chart and the EWMA chart about two types of changes. The X chart is known to effectively detect a large and abrupt change, whereas the EWMA chart is known to work well for small and gradual changes. However, in practice, the types of changes are unknown, and also they can come together. For this reason, many researchers propose to use a combination of both, named X-EWMA, which displays two sets of control statistics and their control limits in one chart. Liu and Tien (2011) improve the X-EWMA chart to a single-featured X-EWMA chart by using a scaled EWMA instead of the original EWMA. This single- featured X-EWMA chart, have the same center line and control limits, and, in consequence, the chart becomes much readable and interpretable compared to the X-EWMA chart. However, as noted by the authors, two source charts (their statistics) are dependent on each other, and it is not easy to set the control limits at the aimed level of false alarm rate. In this paper, we suggest a simple modification of a single-featured X-EWMA to make the control limits be at the exact level with a cost of one-time delay in detecting the small and gradual change. Finally, we apply it to real examples for the detection of network intrusions.

[P2-44] Mercury Contents in Kimchi and Pickle Products

Sungim Im,Jinwook Jang,Kwangsoo Lee,Seongcheol Kim,Kyunga An,Ryunkyung Lee,Hyuna Kim,Miok Kim,Jeongmin Kim,Miwha Parka,Yong seok Ko,Sohee Kim,Daebyeong Kim 한국식품영양과학회 2007 한국식품영양과학회 학술대회발표집 Vol.2007 No.10

First Job Waiting Times after College Graduation Based on the Graduates Occupational Mobility Survey in Korea

Lee, Sungim,Moon, Jeounghoon 한국통계학회 2012 응용통계연구 Vol.25 No.6

Each year research institutions such as the Korea Employment Information Service(KEIS), a government institution established for the advancement of employment support services, and Job Korea, a popular Korean job website, announce first job waiting times after college graduation. This provides useful information understand and resolve youth unemployment problems. However, previous reports deal with the time as a completely observed one and are not appropriate. This paper proposes a new study on first job waiting times after college graduation set to 4 months prior to graduation. In Korea, most college students hunt for jobs before college graduation in addition, the full-fledged job markets also open before graduation. In this case the exact waiting time of college graduates can be right-censored. We apply a Cox proportional hazards model to evaluate the associations between first job waiting times and risk factors. A real example is based on the 2008 Graduates Occupational Mobility Survey(GOMS).

프로그래밍 학습을 위한 AJAX의 활용

이성임 ( Sungim Lee ),우종정 ( Jongjung Woo ) 한국정보처리학회 2008 한국정보처리학회 학술대회논문집 Vol.15 No.1

학교 현장에서 이루어지는 교육의 대부분은 교수자 중심의 내용 전달식이다. 프로그래밍 언어와 같은 실습을 필요로 하는 학습에 교수자 중심의 교육을 적용할 경우 문제점이 많다. 실습을 통한 활용보다 언어 자체의 기능 설명에 비중을 두기 때문에 학생들의 흥미와 관심을 유발하지 못하고 있다. 따라서 최근 주목받고 있는 Web 2.0 패러다임인 참여, 공유 및 개방을 교육 분야에 적용하는 것은 당연할 것이다. 본 연구는 C 프로그래밍 언어 학습에 있어서 Web 2.0 클라이언트 기술 중 Ajax를 활용하여 학습자의 참여를 북돋우며, 또한 학습 시스템의 효율적인 자원 사용을 도모하고자 한다.

Diagnostic usefulness of the QuantiFERON-TB gold in-tube test (QFT-GIT) for tuberculous vertebral osteomyelitis

Choi, Sungim,Jung, Kyung Hwa,Son, Hyo-Ju,Lee, Seung Hyun,Hong, Jung Min,Kim, Min Chul,Kim, Min Jae,Chong, Yong Pil,Sung, Heungsup,Lee, Sang-Oh,Choi, Sang-Ho,Kim, Yang Soo,Woo, Jun Hee,Kim, Sung-Han Informa UK (TaylorFrancis) 2018 Infectious diseases Vol.50 No.5

<P>Conclusion: The QFT-GIT appears to be a useful adjunct test for diagnosing TB vertebral osteomyelitis because the negative test results may be useful for excluding a diagnosis of active TB vertebral osteomyelitis.</P>

Bootstrap method to evaluate tightness of clusters with application to the Korean standard occlusion study

Lim, Johan,Lee, Sungim,Park, Heon-Jin,Eun Lee, Kyeong,Lee, Shin-Jae Taylor Francis 2014 JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION Vol.84 No.2

CUSUM 통계량과 FLSA의 변화점 식별 성능에 대한 실증적 비교

이가령(Garyeong Lee),손원(Won Son),이성임(Sungim Lee),유동현(Donghyeon Yu) 한국데이터정보과학회 2021 한국데이터정보과학회지 Vol.32 No.6

CUSUM 통계량은 오차의 누적합을 기반으로 정의된 통계량으로 binary segmentation (BS), circular BS, wild BS 등의 알고리즘에 적용되어 변화점 식별을 위해 널리 사용되고 있다. Fused lasso signal approximator (FLSA)는 총변동 벌점이 부여된 최소제곱법을 사용하여 구간별 상수 구조를 구현하는 방법으로 다중변화점 식별을 위해 자주 활용되고 있다. 한편, FLSA는 변화점 식별에서의 점근적 일치성이 보장되지 않으므로 Son과 Lim (2019)은 FLSA을 변형한 modified FLSA (mFLSA)을 제안하고 점근적 일치성을 보인 바 있다. 이 연구에서는 서로 다른 관점에서 개발된 이 변화점 식별방법들이 실제로는 간단한 정리 과정을 통해 매우 비슷한 형태의 통계량으로 변환될 수 있음을 보였다. 또, 다중변화점 식별 문제에 있어서 CUSUM 통계량, FLSA, mFLSA의 특징을 살펴보고 모의실험을 통해 각 방법들의 성능을 실증적으로 비교보았다. 모의실험 결과, 세 변화점 식별 방법 중 어느 하나가 다른 방법보다 절대적으로 우월하다고 볼 수 없으며 오차항의 분산, 평균모형의 구조 등에 따라 변화점 식별 성능에 차이가 발생을 확인하였다. In this paper, we study the performance of the Cumulative Sum (CUSUM) and the Fused Lasso Signal Approximator (FLSA) for detecting change points in a mean model. The two methods are widely used for identifying change points. The CUSUM statistic is based on the cumulative sums over the two intervals separated by a candidate change point. On the other hand, the FLSA is a form of regularized method, a combination of the residual sum of squares and a total variation penalty term. Although the two methods are developed from quite a different motivation, these statistics can be expressed in very similar form. The FLSA statistics derived from the pathwise algorithm (Hoefling, 2010) and the modified FLSA statistics (Son and Lim, 2019) can be used for false change points elimination and eventually for change points detection. The modified FLSA statistics are equivalent to the CUSUM statistics divided by the standard error of the difference between the means of the neighboring two blocks. We compare the performance of these statistics in various situations and find that each method has its own advantage and disadvantage for change point detection.

Gate bias-dependent junction characteristics of silicon nanowires suspended between polysilicon electrodes

Lee, Yun-Hi,Park, Sungim Elsevier 2011 Science and technology of advanced materials Vol.12 No.6

<P>Realistic integration of 1D materials into future nanodevices is limited by the lack of a manipulation process that allows a large number of nanowires to be arranged into an integrated circuit. In this work, we have grown Si nanowire bridges using a thin-film catalyst in a batch process at 200 °C and characterized the produced devices consisting of a p<SUP>+</SUP>-Si contact electrode, a suspended Si nanochannel, and a polysilicon contact electrode. Both the electrodes and connecting lines are made of Si-based materials by conventional low-pressure chemical vapor deposition. The results indicate that these devices can act as gate-controllable Schottky diodes in integrated nanocircuits.</P>

호텔링 T²의 이상신호 원인 식별

이성임,Lee, Sungim 한국통계학회 2018 응용통계연구 Vol.31 No.6

호텔링 $T^2$ 통계량에 근거한 다변량 관리도는 공정의 이상상태를 식별하는 통계적 공정관리의 강력한 도구 중 하나이다. 다수의 품질 특성치를 동시에 모니터링하는데 사용된다. $T^2$ 관리도를 통해 이상신호가 탐지된다는 것은 평균 벡터의 변화가 있다는 것을 의미하게 된다. 그러나, 이러한 다변량 통계량의 신호는 이상신호에 대한 원인을 식별하기 어렵게 한다. 이 논문에서는 $T^2$ 통계량을 서로 독립인 항으로 분해한 Mason, Young, Tracy (MYT) 분해에 기반한 원인 식별 방법들을 살펴본다. 또한, R 소프트웨어를 사용하여 사례분석을 하고, 모의실험을 통해 각 절차의 성능을 비교 평가해보고자 한다. Multivariate control chart based on Hotelling's $T^2$ statistic is a powerful tool in statistical process control for identifying an out-of-control process. It is used to monitor multiple process characteristics simultaneously. Detection of the out-of-control signal with the $T^2$ chart indicates mean vector shifts. However, these multivariate signals make it difficult to interpret the cause of the out-of-control signal. In this paper, we review methods of signal interpretation based on the Mason, Young, and Tracy (MYT) decomposition of the $T^2$ statistic. We also provide an example on how to implement it using R software and demonstrate simulation studies for comparing the performance of these methods.