• 한국정보컨버전스학회:학술대회논문집
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• 한국정보컨버전스학회 2008년도 International conference on information convergence
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• pp.39-42
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• 2008

G protein-coupled receptor(GPCR) family is a cell membrane protein, and plays an important role in a signaling mechanism which transmits external signals through cell membranes into cells. Now, it is estimated that there may be about 800-1000 GPCRs in a human genome. But, GPCRs each are known to have various complex control mechanisms and very unique signaling mechanisms. GPCRs are involved in maintaining homeostasis of various human systems including an endocrine system or a neural system and thus, disorders in activity control of GPCRs are thought to be the major source of cardiovascular disorders, metabolic disorders, degenerative disorders, carcinogenesis and the like. As more than 60% of currently marketed therapeutic agents target GPCRs, the GPCR field has been actively explored in the pharmaceutical industry. Structural features, and class and subfamily of GPCRs are well known by function, and accordingly, the most fundamental work in studies identifying the previous GPCRs is to classify the GPCRs with given protein sequences. Studies for classifying previously identified GPCRs more easily with mathematical models have been mainly going on. Considering that secondary sequences of proteins, namely, secondary binding structures of amino acids constituting proteins are closely related to functions, the present paper does not place the focus on primary sequences of proteins as previously practiced, but instead, proposes a method to transform primary sequences into secondary structures and compare the secondary structures, and then detect an unknown GPCR assumed to have a same function in databases of previously identified GPCRs.

• The Journal of Korean Medicine Ophthalmology and Otolaryngology and Dermatology
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• 제30권3호
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• pp.155-165
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• 2017

Objectives : The purpose of this study is to analyze the trends of domestic experimental research of external treatment in Korean medicine and use it as a basic data to expand the therapeutic field of Korean medicine. Methods : In December 2016, two authors searched for experimental studies of external treatment in Korean medicine researches in 6 Korean databases. Results : Among the 379 researches that were initially searched, two authors reviewed 190 researches, excluding duplicate researches, and finally 11 researches were selected for the study. The target disease was confined to the skin and mucosa, and the most of selected Korean medicine was based on the literature. Conclusions : Considering the range of application of the external treatment described in the literature and the domestic market for external medicine, it is expected that the development of various external medicine using herbal medicine will be expected in the future.

• Journal of Service Research and Studies
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• 제1권1호
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• pp.61-69
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• 2011

Data mining that can not be extracted with a simple query in the form of "useful" means to find information in large databases from the existing and unknown knowledge. It is based on this insight about the data can be defined as a gain. In this paper, we use the Internet to find useful patterns on the Web or saved data to the target Web site, which is to analyze the characteristics of users. A general statistical information on Internet users to the data by applying a relevance analysis, Internet use affect the amount of time to analyze the characteristics of Internet users. Only through experiments extracting data from the association rules, producing optimal results apply for the data pre-processing and algorithm for mining the Web to Internet users. characteristics were analyzed.

• Journal of the Korea Society of Computer and Information
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• 제21권8호
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• pp.77-84
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• 2016

In general statistical analysis, we need to make a normal assumption. If this assumption is not satisfied, we cannot expect a good result of statistical data analysis. Most of statistical methods processing the outlier and noise also need to the assumption. But the assumption is not satisfied in big data because of its large volume and heterogeneity. So we propose a methodology based on box-plot and data smoothing for controling outlier and noise in big data analysis. The proposed methodology is not dependent upon the normal assumption. In addition, we select patent documents as target domain of big data because patent big data analysis is a important issue in management of technology. We analyze patent documents using big data learning methods for technology analysis. The collected patent data from patent databases on the world are preprocessed and analyzed by text mining and statistics. But the most researches about patent big data analysis did not consider the outlier and noise problem. This problem decreases the accuracy of prediction and increases the variance of parameter estimation. In this paper, we check the existence of the outlier and noise in patent big data. To know whether the outlier is or not in the patent big data, we use box-plot and smoothing visualization. We use the patent documents related to three dimensional printing technology to illustrate how the proposed methodology can be used for finding the existence of noise in the searched patent big data.

• Journal of Integrative Natural Science
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• 제3권1호
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• pp.49-53
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• 2010

Molecular docking is a critical event which mostly forms Van der waals complex in molecular recognition. Since the majority of developed drugs are small molecules, docking them into proteins has been a prime concern in drug discovery community. Since the binding pose space is too vast to cover completely, many search algorithms such as genetic algorithm, Monte Carlo, simulated annealing, distance geometry have been developed. Proper evaluation of the quality of binding is an essential problem. Scoring functions derived from force fields handle the ligand binding prediction with the use of potential energies and sometimes in combination with solvation and entropy contributions. Knowledge-based scoring functions are based on atom pair potentials derived from structural databases. Forces and potentials are collected from known protein-ligand complexes to get a score for their binding affinities (e.g. PME). Empirical scoring functions are derived from training sets of protein-ligand complexes with determined affinity data. Because non of any single scoring function performs generally better than others, some other approaches have been tried. Although numerous scoring functions have been developed to locate the correct binding poses, it still remains a major hurdle to derive an accurate scoring function for general targets. Recently, consensus scoring functions and target specific scoring functions have been studied to overcome the current limitations.

• Journal of Korean Medicine Rehabilitation
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• 제21권4호
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• pp.77-86
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• 2011

Objectives: This study aims to evaluate domestic clinical studies related to the exercise program targeting farmers. Methods: Five Korean databases were seamed for prospective clinical trials of exercise program targeting farmers from 2001 to August, 2011. Only studies conducted in Korean language were searched. Results: Thirteen clinical studies were included among 3374 studies searched. Six were observational studies, four were non-randomized controlled trials, and three were randomized controlled trials. All of included studies reported favorable effects of exercise group compared to baseline of controlled group. Conclusions: We found various mistake in the applications of statistical methodologies in the studies of exercise program targeting farmers. It is necessary for more randomized controlled trials to evaluate effect of exercise program target farmers.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 한국지능정보시스템학회 2000년도 추계정기학술대회:지능형기술과 CRM
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• pp.289-299
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• 2000

This study provides an application of datamining approach to CQI(Continuous Quality Improvement) using the discharge summary. First, we found a process variation in hospital infection rate by SPC (Statistical Process Control) technique. Second, importance of factors influencing hospital infection was inferred through the decision tree analysis which is a classification method in data-mining approach. The most important factor was surgery followed by comorbidity and length of operation. Comorbidity was further divided into age and principal diagnosis and the length of operation was further divided into age and chief complaint. 24 rules of hospital infection were generated by the decision tree analysis. Of these, 9 rules with predictive prover greater than 50% were suggested as guidelines for hospital infection control. The optimum range of target group in hospital infection control were Identified through the information gain summary. Association rule, which is another kind of datamining method, was performed to analyze the relationship between principal diagnosis and comorbidity. The confidence score, which measures the decree of association, between urinary tract infection and causal bacillus was the highest, followed by the score between postoperative wound disruption find postoperative wound infection. This study demonstrated how datamining approach could be used to provide information to support prospective surveillance of hospital infection. The datamining technique can also be applied to various areas fur CQI using other hospital databases.

• Journal of Preventive Medicine and Public Health
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• 제40권2호
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• pp.185-190
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• 2007

Objectives : Since the first human infection from avian influenza was reported in Hong Kong in 1997, many Asian countries have confirmed outbreaks of highly pathogenic H5N1 avian influenza viruses. In addition to Asian countries, the EU authorities also held an urgent meeting in February 2006 at which it was agreed that Europe could also become the next target for H5N1 avian influenza in the near future. In this paper, we provide the general and applicable information on the avian influenza in the bioinformatics field to assist future studies in preventive medicine. Methods : We introduced some up-to-date analytical tools in bioinformatics research, and discussed the current trends of avian influenza outbreaks. Among the bioinformatics methods, we focused our interests on two topics: pattern analysis using the secondary database of avian influenza, and structural analysis using the molecular dynamics simulations in vaccine design. Results : Use of the public genome databases available in the bioinformatics field enabled intensive analysis of the genetic patterns. Moreover, molecular dynamic simulations have also undergone remarkable development on the basis of the high performance supercomputing infrastructure these days. Conclusions : The bioinformatics techniques we introduced in this study may be useful in preventive medicine, especially in vaccine and drug discovery.

• Journal of KIISE:Software and Applications
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• 제32권9호
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• pp.920-926
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• 2005

Nearest neighbor algorithms classify an unseen input instance by selecting similar cases and use the discovered membership to make predictions about the unknown features of the input instance. The usefulness of the nearest neighbor algorithms have been demonstrated sufficiently in many real-world domains. In nearest neighbor algorithms, it is an important issue to assign proper weights to the attributes. Therefore, in this paper, we propose a new method which can automatically assigns to each attribute a weight of its importance with respect to the target attribute. The method has been implemented as a computer program and its effectiveness has been tested on a number of machine learning databases publicly available.

• Journal of Oriental Neuropsychiatry
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• 제32권3호
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• pp.219-234
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• 2021

Objectives: The objective of this study was to review and analyze domestic research trends of ear acupuncture and ear acupressure (EAs) in elderly population. Methods: We searched five domestic databases to collect relevant original clinical studies up to July 2, 2021. Conditions of elderly participants and results reported in included studies were analyzed. Methods of EAs used were analyzed referring to STandards for Reporting Interventions in Clinical Trials of Acupuncture. Results: A total of 17 studies including nine randomized controlled trials were analyzed. As for the target condition, sleep disorder was the most common (n=9), followed by pain condition (n=6). There were three studies on participants with specific Sasang constitution. Procedures of EAs used in nursing studies were generally similar to those of Korean medicine (KM). Conclusions: Domestic studies have reported that EAs might be helpful in improving the health of the elderly. In the future, more research studies using EAs for the elderly are needed in KM field. Collaborative research with KM nurses is recommended. EAs should be further investigated as a promising KM intervention in terms of health and welfare for the elderly.