• Proceeding of EDISON Challenge
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• 2015.03a
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• pp.117-123
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• 2015

본 연구에서는 DFT를 이용하여 Nucleophilicity와 Basicity의 연관성에 대한 계산화학적 분석을 수행하였다. Basicity는 선정된 모델 분자의 protonation 반응에서 생성물과 반응물의 enthalpy 변화량인 양성자 친화도(Proton affinity, PA) 값을 구하여 분석하였다. 계산한 결과는 실험을 통해 얻은 PA 결과와 경향성이 거의 일치함을 확인하였다. Nucleophilicity는 모델 분자들과 $CH_3Br$ (electrophile)의 $SN_2$반응에서 gibbs free energy of activation(${\Delta}G^{\ddag}$) 값으로 그 경향성을 분석하였다. 또한 용매의 종류를 다르게 하여 용매에 따른 ${\Delta}G^{\ddag}$ 값의 경향성도 확인하였다. 각 용매에 따라 구한 ${\Delta}G^{\ddag}$와 PA의 상관관계를 비교하였으나, 큰 연관성은 보이지 않았다. 이에 ${\Delta}G^{\ddag}$와 PA의 상관관계를 보여줄 수 있는 parameter를 찾기 위하여 각 모델 분자의 Electronegativity와 Polarizability를 계산하여 연관성을 비교해보았다. Polarizability를 적용했을 때 Nucleophilicity와 Basicity사이의 연관성을 나타낼 수 없었던 반면, Electronegativity를 적용하여 Basicity와 Nucleophilicity의 연관성 보일 수 있음을 이론적으로 규명하였다.

• The Journal of the Korea Contents Association
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• v.13 no.3
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• pp.299-306
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• 2013

The purpose of this research is to analyze the questionnaire of oriental medicine and bio-signal data and to identify the correlation between symptoms of oriental medicine and bio-signal in order to develop the customization model for individual patients. First, this research analyzes the questionnaire data using the developed questionnaire for oriental medicine symptoms and selects the optimized questionnaires for identifying the symptoms. Using data mining technologies with the selected questionnaires, this research divides the normal group and the group with symptoms. Finally, this research identifies the correlation between the questionnaire for oriental medicine symptoms and electrogastrogram signal.

• Journal of the Korea Convergence Society
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• v.13 no.3
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• pp.203-216
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• 2022

In the recent business environment, purchase patterns are changing around the influence of COVID-19 and the online market. This study analyzed cluster and correlation analysis based on purchase and product information. The cluster analysis of new methods was attempted by creating customer, product, and cross-bonding clusters. The cross-bonding cluster analysis was performed based on the results of each cluster analysis. As a result of the correlation analysis, it was analyzed that more association rules were derived from a cross-bonding cluster, and the overlap rate was less. The cross-bonding cluster was found to be highly efficient. The cross-bonding cluster is the most suitable model for recommending products according to customer needs. The cross-bonding cluster model can save time and provide useful information to consumers. It is expected to bring positive effects such as increasing sales for the company.

• Journal of Preventive Medicine and Public Health
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• v.30 no.4 s.59
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• pp.729-740
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• 1997

To determine the relationship between hypertension and nutrient intake cross-sectional study were performed in a rural area. Adult resident over 30-year-old age were measured blood pressure and body mass index(BMI), and interviewed about food in-take for the previous 24 hours. 250 men and 297 women participated the survey. Significant correlation was showen in men between mean systolic blood pressure and protein density. Significant correlation with mean diastolic blood pressure was showen on protein density, protein energy(%), calcium density and energy-adjusted protein in men. We analysed risk factor for hypertension adjust the effect of age, BMI, sex and family history by multiple logistic regression. Protein density(odds ratio=3.18), fat density(odds ratio=1.94) and energy-adjusted protein(odds ratio=1.01) intake were positively associated with hypertension but sodium density(odds ratio=0.73) was showen to have inverse relationship.

• Journal of KIISE:Databases
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• v.29 no.1
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• pp.1-14
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• 2002

Association rule discovery is a method of mining for the associated item set on large databases based on support and confidence threshold. The discovered association rules can be applied to the marketing pattern analysis in E-commerce, large shopping mall and so on. The association rule discovery makes multiple scan over the database storing large transaction data, thus, the algorithm requiring very high overhead might not be useful in real-time association rule discovery in dynamic environment. Therefore this paper proposes an active candidate set management model based on trigger and incremental update mechanism to overcome non-realtime limitation of association rule discovery. In order to implement the proposed model, we not only describe an implementation model for incremental updating operation, but also evaluate the performance characteristics of this model through the experiment.

• The KIPS Transactions:PartD
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• v.18D no.4
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• pp.237-244
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• 2011

Opinion Mining summarizes with classifying sensitive opinions of customers in huge online customer reviews for the attributes of products or services by positive and negative opinions. Because the customers represent their interests through subjective opinions as well as objective facts, the existing opinion mining techniques, which can analyze just the sensitive opinions, need to be expanded.. In this paper, We propose the novel entity association network model which expands the existing opinion mining techniques. The entity association model can not only represent positive and negative degree of the sensitive opinions, but also can represent the degree of the associations and relative importances between entities. We designed and implemented the customer reviews analysis system based on the entity association network model. We recognized that the system can represent more abundant information than the existing opinion mining techniques.

• The Journal of the Korea Contents Association
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• v.11 no.1
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• pp.371-378
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• 2011

This paper examines the estimate the economic impact of 2008 Andong Maskdance Festival, using an Input-Output(I-O) model. For the research, the Regional Input-Output analysis was used, which makes it easy to grasp the economic impact of the tourism industry and other industries in Andong. Based on the regional I-O transactions tables which were developed by Bank of Korea(2009), the industry multipliers were derived with respect to output, income, and value-added. The results show that in 2008 Andong Maskdance Festival receipts generated output impact of 30,961 million won and 15,800 million won of income impact, 14,310 million won of value-added impact, respectively. I think the result of this study can be used as an objective indicator to help to establish and implement regional festival policies for the local government.

• Proceedings of the Korean Society of Computer Information Conference
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• 2020.07a
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• pp.307-310
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• 2020

본 논문에서 이슈 키워드 추출을 위해 텍스트 마이닝(Text Mining) 기술을 요구한다. 사회적 이슈 키워드를 추출하기 위해 키워드 수집 모델이 되는 사이트에서 크롤링(crawling)을 수행한 뒤, 형태소 단위 의미있는 단어를 수집하기 위해 형태소 분석(morphological analysis)을 수행한다. 한국어 형태소 분석을 위해 파이썬의 코엔엘파이(KoNLPy) 패키지를 활용한다. 형태소 분석을 통해 나뉘어진 단어에서 통계를 내어 이슈 키워드 추출한다. 이슈 키워드를 뒷받침할 연관 단어를 분석하기 위해 단어 임베딩(Word Embedding)을 수행한다. 단어 임베딩 수행을 위해 Word2Vec 모델 중 Skip-Gram 방법론을 적용하여 연관 단어를 분석하도록 개발하였다. 웹 소켓(Web Socket) 통신을 통한 채팅 프로그램의 상단에 분석한 이슈 키워드와 연관 단어를 출력하도록 개발하였다.

• The KIPS Transactions:PartD
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• v.9D no.2
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• pp.215-226
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• 2002

Considering the rapid process of media's breakthrough and diverse patterns of consumptions's analysis, a uniform analysis might be much rooms to be desired for interpretation of new phenomena. In special, the products happening intensive sails on around an anniversary or fresh food have the restricted marketing hours. Moreover, traditional association rule discovery algorithms might not be appropriate for analysis of sales pattern given in a specific time because existing approaches require iterative scan operation to find association rule in large scale transaction databases. in this paper, we propose an incremental candidate set management model based on twin-hashing technique to find association rule in special sales pattern using database trigger and stored procedure. We also prove performance of the proposed model through implementation and experiment.

• Journal of the Korean Data and Information Science Society
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• v.27 no.1
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• pp.1-8
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• 2016

In the recently, violent crime and accidental crime has been generated continuously. Consequently, people anxiety has been heightened. The Closed Circuit Television (CCTV) has been used to ensure the security and evidence for the crimes. However, the video captured from CCTV has being used in the post-processing to apply to the evidence. In this paper, we propose a flexible multi-level models for estimating whether dangerous behavior and the environment and context for pedestrians. The situation analysis builds the knowledge for the pedestrians tracking. Finally, the decision step decides and notifies the threat situation when the behavior observed object is determined to abnormal behavior. Thereby, tracking the behavior of objects in a multi-region, it can be seen that the risk of the object behavior. It can be predicted by the behavior prediction of crime.