• Journal of Korea Port Economic Association
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• v.38 no.4
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• pp.107-118
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• 2022

In this study, daily data from January 2002 to June 2022 were used to investigate the relationship between risk-return relationship and market fear, uncertainty, stock market, and maritime freight index for the crude oil market. For this study, the time varying EGARCH-M model was applied to the risk-return relationship, and the wavelet consistency model was used to analyze the relationship between market fear, uncertainty, stock market, and maritime freight index. The analysis results of this study are as follows. First, according to the results of the time-varying risk-return relationship, the crude oil market was found to be related to high returns and high risks. Second, the results of correlation and Granger causality test, it was found that there was a weak correlation between the risk-return relationship and VIX, EPU, S&P500, and BDI. In addition, it was found that there was no two-way causal relationship in the risk-return relationship with EPU and S&P500, but VIX and BDI were found to affect the risk-return relationship. Third, looking at the results of wavelet coherence, it was found that the degree of the risk-return relationship and the relationship between VIX, EPU, S&P500, and BDI was time-varying. In particular, it was found that the relationship between each other was high before and after the crisis period (financial crisis, COVID-19). And it was found to be highly associated with organs. In addition, the risk-return relationship was found to have a positive relationship with VIX and EPU, and a negative relationship with S&P500 and BDI. Therefore, market participants should be well aware of economic environmental changes when making decisions.

• The KIPS Transactions:PartD
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• v.17D no.1
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• pp.1-8
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• 2010

Association rule mining techniques enable us to acquire knowledge concerning sales patterns among individual items from voluminous transactional data. Certainly, one of the major purposes of association rule mining is utilizing the acquired knowledge to provide marketing strategies such as catalogue design, cross-selling and shop allocation. However, this requires too much time and high cost to only extract the actionable and profitable knowledge from tremendous numbers of discovered patterns. In currently available literature, a number of interest measures have been devised to accelerate and systematize the process of pattern evaluation. Unfortunately, most of such measures, including support and confidence, are prone to yielding impractical results because they are calculated only from the sales frequencies of items. For instance, traditional measures cannot differentiate between the purchases in a small basket and those in a large shopping cart. Therefore, some adjustment should be made to the size of market baskets because there is a strong possibility that mutually irrelevant items could appear together in a large shopping cart. Contrary to the previous approaches, we attempted to consider market basket's size in calculating interest measures. Because the devised measure assigns different weights to individual purchases according to their basket sizes, we expect that the measure can minimize distortion of results caused by accidental patterns. Additionally, we performed intensive computer simulations under various environments, and we performed real case analyses to analyze the correctness and consistency of the devised measure.

• Information Systems Review
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• v.8 no.2
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• pp.119-138
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• 2006

Association Rule Mining has been successfully used for mining knowledge in static environment but it provides limited features to discovery time-dependent knowledge from multi-point data set. The aim of this paper is to develop a methodology which detects changes of customer behavior automatically from customer profiles and sales data at different multi-point snapshots. This paper proposes a procedure named 'Recursive Change Mining' for detecting continuous change of customer purchase behavior. The Recursive Change Mining Procedure is basically extended association rule mining and it assures to discover continuous and repetitive changes from data sets which collected at multi-periods. A case study on L department store is also provided.

• Korean Journal of Clinical Laboratory Science
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• v.51 no.1
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• pp.86-92
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• 2019

Di-ethylhexyl phthalate (DEHP) is an environmental contaminant that is used as a plasticizer. Endometriosis is a complex disease with an unknown etiology that is believed to be associated with exposure to DEHP. The present study examined the potential toxicity of DEHP by exposing endometrial adenocarcinoma cells (Ishikawa cells) to DEHP. In the experiments, the cells were treated with stepwise DEHP concentrations (0, 0.01, 0.1, 1, and $5{\mu}M$) for different exposure times (24, 48, and 72 h). When the relationship between the resulting survival rate of the cells and initial inflammation was examined, the cell viability, expression of $TNF-{\alpha}$, an inflammatory mediator, and the expression of MMP-9, an ECM degradation protein, were increased remarkably when the cells were exposed to $5{\mu}M$ DEHP for 48 and 72 hours. These results suggest that the exposure of Ishikawa cells to certain concentrations of DEHP, estrogen mimics, may cause time-dependent toxicity that affects the cell viability and inflammation, implying a potential role in the etiology of endometriosis. Further research on the effects of endocrine disruptors on the pathogenesis of endometriosis may reveal strategies to prevent this disease.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.111-126
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• 2017

Recommender systems based on association rule mining significantly contribute to seller's sales by reducing consumers' time to search for products that they want. Recommendations based on the frequency of transactions such as orders can effectively screen out the products that are statistically marketable among multiple products. A product with a high possibility of sales, however, can be omitted from the recommendation if it records insufficient number of transactions at the beginning of the sale. Products missing from the associated recommendations may lose the chance of exposure to consumers, which leads to a decline in the number of transactions. In turn, diminished transactions may create a vicious circle of lost opportunity to be recommended. Thus, initial sales are likely to remain stagnant for a certain period of time. Products that are susceptible to fashion or seasonality, such as clothing, may be greatly affected. This study was aimed at expanding association rules to include into the list of recommendations those products whose initial trading frequency of transactions is low despite the possibility of high sales. The particular purpose is to predict the strength of the direct connection of two unconnected items through the properties of the paths located between them. An association between two items revealed in transactions can be interpreted as the interaction between them, which can be expressed as a link in a social network whose nodes are items. The first step calculates the centralities of the nodes in the middle of the paths that indirectly connect the two nodes without direct connection. The next step identifies the number of the paths and the shortest among them. These extracts are used as independent variables in the regression analysis to predict future connection strength between the nodes. The strength of the connection between the two nodes of the model, which is defined by the number of nodes between the two nodes, is measured after a certain period of time. The regression analysis results confirm that the number of paths between the two products, the distance of the shortest path, and the number of neighboring items connected to the products are significantly related to their potential strength. This study used actual order transaction data collected for three months from February to April in 2016 from an online commerce company. To reduce the complexity of analytics as the scale of the network grows, the analysis was performed only on miscellaneous goods. Two consecutively purchased items were chosen from each customer's transactions to obtain a pair of antecedent and consequent, which secures a link needed for constituting a social network. The direction of the link was determined in the order in which the goods were purchased. Except for the last ten days of the data collection period, the social network of associated items was built for the extraction of independent variables. The model predicts the number of links to be connected in the next ten days from the explanatory variables. Of the 5,711 previously unconnected links, 611 were newly connected for the last ten days. Through experiments, the proposed model demonstrated excellent predictions. Of the 571 links that the proposed model predicts, 269 were confirmed to have been connected. This is 4.4 times more than the average of 61, which can be found without any prediction model. This study is expected to be useful regarding industries whose new products launch quickly with short life cycles, since their exposure time is critical. Also, it can be used to detect diseases that are rarely found in the early stages of medical treatment because of the low incidence of outbreaks. Since the complexity of the social networking analysis is sensitive to the number of nodes and links that make up the network, this study was conducted in a particular category of miscellaneous goods. Future research should consider that this condition may limit the opportunity to detect unexpected associations between products belonging to different categories of classification.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.2B
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• pp.191-198
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• 2010

Assessing seasonality of precipitation is necessarily required to establish future plans and policies for water resources management. In this regard, a main objective of the study is to introduce an effective approach for assessing the seasonality of the precipitation and evaluate the seasonality through the proposed one. We have used circular statistics to characterize the seasonality on the precipitation in Korea. The circular statistics allow us to effectively assess changes in timing of the seasonality in detail. It was found that peak time on monthly rainfall occurred between end of June and early July in southern coastal area while the timing was delayed in northern part of Korea because of monsoon moving in from south to north. In case of annual daily peak precipitation, spatio-temporal variation of the peak time was increased. It is mainly because of geophysical effects, frequency and paths of typhoons. Finally, temporal variations on the timing of the peak seasons were evaluated through circular statistics by 30-year moving average data. The peak season in the Northen part of Korea (e.g. Seoul and Gangrung) has been moved back from early July to end of July while the peak season has been moved up from middle of July to early July in the Southern part of Korea (e.g. Busan and Mokpo). It seems that changes in seasonality are mostly modulated by variability in the east-asia monsoon system.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.113-122
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• 2021

This study begins on the basis of Jacques Lacan's article 『Logical Time and Assertions of Preemptive Certainty: A New Sophism』 published in the reissue of 『Art Note Les Cahiers d'Art』 in March 1945. In this paper, a guard presents an esoteric problem to three prisoners. If the problem is solved, the prisoner is released. A condition is given to solve a problem. Conversation between prisoners is prohibited, and the disc behind them cannot be seen. In this time and space, prisoners place themselves in logical time through the 'time of understanding' in order to become the chosen ones. We always live in logical time. We will argue the point at which Lacan destroys logical time in psychoanalysis. Time in Lacanian psychoanalysis transcends time divisions of the past, present, and future. Our time is always the past in the present. In Lacanian psychoanalysis, logical time is the time in the Other. The transcendence of the Lacanian psychoanalysis concept of time shows the deviation of logical time. In this text, We try to prove how Lacan contrasts psychoanalysis and the problem of time with time in the other. First, we will examine how logical time and impulse are related in psychoanalysis. Second, the postmortemity of the signifient (signifier) will be discussed. Third, Lacan psychoanalysis will present the transcendence of time. In conclusion, We will present the view that the time of Lacan psychoanalysis is flowing backwards. In Lacanian psychoanalysis, we try to prove that logical time is in the territory of the Other and is infinite time.

• Korea journal of population studies
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• v.32 no.3
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• pp.21-41
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• 2009

본 연구는 소비자의 의료서비스 만족도에 영향을 미치는 중요한 요인들을 규명해 보고 그 관계를 살펴보고자 하였다. 특히 의료소비자가 인지하는 의료서비스의 만족도에 영향을 미치는 구성요소 가운데 의사, 간호사 등 의료인력 요소와 시설, 대기시간, 행정절차 등 비의료적 구성요소를 중심으로 만족도에 영향을 미치는 관련요인을 규명해 보았다. 본 연구에서 사용된 실증적 자료는 서울에 거주하는 사람으로 조사시점인 2007년 10월을 기점으로 지난 3개월 내에 의료서비스를 이용한 경험이 있는 사람을 대상으로 설문조사에 의해 수집되었고, 최종 543사례가 분석에 활용되었다. 의료서비스에 대한 만족도와 요인들간의 관련성을 파악하기 위해 상관관계 분석과 다중회귀분석을 실시하였고 특히 의료서비스의 질과 만족도에 직접적인 영향을 미치는 의료 인력의 자질과 태도와의 연관성에 초점을 두어 분석하였다. 분석결과, 소비자의 의료서비스 만족도에 영향을 미치는 핵심적인 관련 요인으로는 의료인력 구성요소로서 통계적으로 유의미한 영향을 미치는 것으로 나타났다. 특히 "의사실력", "의사의 자상한 설명과 친절", "의사의 믿음직함", 그리고 "의사가 환자의 얘기를 귀담아 들어줌"이라는 의사의 자질과 태도가 가장 중요한 요인이라고 할 수 있다. 이와 같은 의료서비스의 질과 만족도연구는 소비자의 의료서비스 만족도 정보로 활용하므로 의료서비스 공급자와 의료기관 종사자들의 책임의식 고취와 고객중심적 의료서비스 문화 정착에 도움이 되고 소비자들에게 좀 더 나은 의료서비스를 제공할 수 있도록 의료공급자들에게 동기를 부여해 준다는 점에서도 의의가 있을 것이다.

• Journal of Marine Bioscience and Biotechnology
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• v.1 no.2
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• pp.126-135
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• 2006

Phlorotannins which is oligomeric polyphenol of phloroglucinol unit were isolated from solvent fractions of methanolic extract of the brown alga, Ecklonia cava (EC). The inhibitory effects of phlorotannins from EC solvent fractions on oxidative stress were examined in human dermal fibroblasts (HDFs) related to wrinkle formation. Among the solvent fractions, phlorotannins from ethyl acetate fraction exerted the highest scavenging effect on DPPH radical, hydroxyl radical and alkyl radical analyzed by electron spin resonance (ESR) spectroscopy. The levels of intracellular reactive oxygen species (ROS) and lipid peroxidation were measured using 2',7'-dichlorofluorescin diacetate (DCFH-DA) and diphenyl-1-pyrenylphosphine (DPPP), respectively. Their levels were significantly decreased in the presence of phlorotannins from ethyl acetate fraction, compared with other fractions obtained from EC extract (P < 0.01). Furthermore, intracellular glutathione (GSH) level was significantly increased in a time dependent manner by the phlorotannins. Therefore, these results suggest that phlorotannins from EC extract could have a therapeutic potential for prevention and treatment of several diseases such as wrinkle formation related to oxidative stress.

• 한국항공운항학회:학술대회논문집
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• 2016.05a
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• pp.136-141
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• 2016

본 논문에서는 항행안전시설을 구성하는 구성요소를 체계별로 구분하고 체계별 운영시간 에 따른 고장율 등을 분석한다. 아울러 설계수명에 점차 도달한 항행안전시설 운영단계에서 발생한 유지보수비용 데이터를 토대로 남은 설계수명 기간 동안 향후 발생 가능한 유지보수 비용을 추정한다. 이런 분석결과를 통해 장비의 신뢰성 관련 선행연구들에서 주로 인용되고 있는 욕조커브(Bathtub Curve) 이론과 본 연구의 비용예측 결과와의 연관성을 진단하고 안정적인 유지보수를 위한 기초자료로서 활용되고자 한다. ARIMA 예측모형을 토대로 향후 10개월 간 발생가능한 유지보수 비용을 예측한 결과 비용이 상승할 것이라는 통계적으로 신뢰할 만한 추정 결과를 얻었다. ARIMA를 활용한 추정결과는 앞선 MTBF 분석내용을 지지함과 동시에 시설의 정비 신뢰도를 보여주는 욕조커브 분포와 일치하는 신뢰할 수 있는 결론을 얻은 것이다.