• 한국통신학회논문지
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• 제36권12B호
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• pp.1509-1521
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• 2011

비즈니스 프로세스 및 워크플로우 기술의 국제표준화기구인 WfMCl)에서는 최근 비즈니스 프로세스 인텔리전스 마이닝 분야에 대한 산업체의 관심이 증가함에 따라 프로세스 실행이벤트로그 표준포맷인 비즈니스 프로세스 분석로그 포맷, BPAF2) 1.0을 공식적으로 발표한 바 있다. 즉, 비즈니스 프로세스 인텔리전스 마이닝 기술은 비즈니스 프로세스 모델의 실행이벤트로그로부터 제어흐름, 데이터흐름, 역할흐름, 수행자흐름 등의 흐름중심의 인텔리전스와 최근에 관심이 집중되는 프로세스기반 소셜네트워크, 소속성네트워크 등의 관계중심의 인텔리전스를 마이닝하는 일련의 알고리즘들과 분석기법들로 구성되는데 현재의 표준포맷인 BPAF 1.0은 비즈니스 프로세스의 제어흐름 인텔리전스 마이닝에 초점 맞추고 있어 최근에 관심이 집중되는 관계중심의 인텔리전스 마이닝을 지원할 수가 없다. 따라서, 본 표준화 논문에서는 제어흐름 인텔리전스 이외에 데이터흐름, 역할흐름, 수행자흐름의 흐름 중심 인텔리전스 뿐만 아니라 프로세스기반 소셜네트워크, 소속성 네트워크의 관계중심 인텔리전스의 마이닝을 지원할 수 있도록 기존의 BPAF 1.0 표준포맷을 확장한 BPAF 2.0 표준포맷을 제안한다. 특히, 본 논문에서 제안하는 BPAF 2.0은 한국정보통신기술협회 표준총회의 e 비즈니스 프로젝트 그룹을 통한 국내 표준안의 기반기술이 될 뿐 만 아니라 BPAF 1.0을 제정한 WfMC 국제표준화기구의 국제 표준안의 확장에 기여할 것이라고 판단한다.

• 경영정보학연구
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• 제21권2호
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• pp.117-137
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• 2019

빅데이터 시대를 맞아 다양한 도메인에서 수없이 많은 데이터들이 생산되면서 데이터 사이언스가 대중화 되었고, 데이터의 힘이 곧 경쟁력인 시대가 되었다. 특히 전 세계 데이터의 80% 이상을 차지하는 비정형 데이터에 대한 관심이 부각되고 있다. 소셜 미디어의 발전과 더불어 비정형 데이터의 대부분은 텍스트 데이터의 형태로 발생하고 있으며, 마케팅, 금융, 유통 등 다양한 분야에서 중요한 역할을 하고 있다. 하지만 이러한 소셜 미디어를 활용한 텍스트 마이닝은 수치형 데이터를 활용한 데이터 마이닝 분야에 비해 접근이 어렵고 복잡해 기대에 비해 그 활용도가 높지 못한 실정이다. 이에 본 연구는 프로그래밍 언어나 고사양 하드웨어나 솔루션에 의존하지 않고, 쉽고 간편한 소셜 미디어 텍스트 마이닝을 위한 통합 애플리케이션으로 Korean Natural Language Application(KoALA)을 개발하고자 한다. KoALA는 소셜 미디어 텍스트 마이닝에 특화된 애플리케이션으로, 한글, 영문을 가리지 않고 분석 가능한 통합 애플리케이션이다. 데이터 수집에서 전처리, 분석, 그리고 시각화에 이르는 전 과정을 처리해준다. 본 논문에서는 디자인 사이언스(design science) 방법론을 활용해 KoALA 애플리케이션을 디자인, 구현, 적용하는 과정에 대해서 다룬다. 마지막으로 블록체인 비즈니스 관련 사례를 들어 KoALA의 실제 활용방안에 대해서 다룬다. 본 논문을 통해 소셜 미디어 텍스트 마이닝의 대중화와 다양한 도메인에서 텍스트 마이닝의 실무적, 학술적 활용을 기대해 본다.

• Geomechanics and Engineering
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• 제20권1호
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• pp.1-7
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• 2020

In structures excavated in rock mass, load progressively increases to a level and remains constant during the construction. Rocks display different elastic properties such as E_i and ʋ under different loading conditions and this requires to use the true values of elastic properties for the design of safe structures in rock. Also, rocks will undergo horizontal and vertical deformations depending on the amount of load applied. However, under constant loads, values of E_i and ʋ will vary in time and induce variations in the behavior of the rock mass. In some empirical equations in which deformation modulus of the rock mass is taken into consideration, elastic parameters of intact rock become functions in the equation. Hence, the use of time dependent elastic properties determined under constant loading will yield more reliable results than when only constant elastic properties are used. As well known, rock material will play an important role in the deformation mechanism since the discontinuities will be closed due to the load. In this study, E_i and ʋ values of intact rocks were investigated under different constant loads for certain rocks with high deformation capabilities. The results indicated significant time dependent variations in elastic properties under constant loading conditions. E_i value obtained from deformability test was found to be higher than the E_i value obtained from the constant loading test. This implies that when static values of elastic properties are used, the material is defined as more elastic than the rock material itself. In fact, E_i and ʋ values embedded in empirical equations are not static. Hence, this workattempts to emerge a new understanding in designing of safer structures in rock mass by numerical methods. The use of time-dependent values of E_i and ʋ under different constant loads will yield more accurate results in numerical modeling analysis.

• Journal of Microbiology and Biotechnology
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• 제28권6호
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• pp.957-967
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• 2018

A novel $g-C_3N_4$/ZnO/stellerite (CNZOS) hybrid photocatalyst, which was synthesized by coupled hydro thermal-thermal polymerization processing, was applied as an efficient visible-light-driven photocatalyst against Staphylococcus aureus. The optimum synthesized hybrid photocatalyst showed a sandwich structure morphology with layered $g-C_3N_4$ (doping amount: 40 wt%) deposited onto micron-sized ZnO/stellerite particles (ZnO average diameter: ~18 nm). It had a narrowing band gap (2.48 eV) and enlarged specific surface area ($23.05m^2/g$). The semiconductor heterojunction effect from ZnO to $g-C_3N_4$ leads to intensive absorption of the visible region and rapid separation of the photogenerated electron-hole pairs. In this study, CNZOS showed better photocatalytic disinfection efficiency than $g-C_3N_4/ZnO$ powders. The disinfection mechanism was systematically investigated by scavenger-quenching methods, indicating the important role of $H_2O_2$ in both systems. Furthermore, $h^+$ was demonstrated as another important radical in oxidative inactivation of the CNZOS system. In respect of the great disinfection efficiency and practicability, the CNZOS heterojunction photocatalyst may offer many disinfection applications.

• 정보처리학회논문지D
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• 제18D권5호
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• pp.385-392
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• 2011

최근 농업 분야에 IT를 접목시킨 농업-IT 융합 기술에 대한 연구가 주목 받고 있다. 특히, 공간 데이터 마이닝(spatial data mining, SDM)을 이용한 농작물 관련 예측 서비스들을 통해 자연재해에 대한 피해를 줄이고 농작물의 생산성을 높이고자 하는 연구들이 있어 왔다. 그러나 예측 서비스를 위한 SDM에 필요한 학습 데이터는 분산되어 있는 데이터간의 이질성으로 인해 데이터 변환과 통합과정에 많은 비용과 시간이 발생한다. 또한 공간 데이터와 비공간 데이터 간의 공간적 이웃 관계를 연산하기 위해 대용량의 데이터에 대한 복잡한 연산과정이 필요하다. 본 논문에서는 각각의 데이터 소스를 하나의 서비스 단위로 취급함으로써 분산된 이질적인 데이터를 효과적으로 통합 관리할 수 있고 SDM을 위한 학습 데이터의 생산성을 향상시켜 최적의 예측 서비스의 발견을 지원해 주는 SOA 기반의 데이터 통합 프레임워크를 제안한다. 실험을 통해 경기도 이천시의 복숭아나무의 동해 피해지역에 대한 최적의 예측 서비스의 발견을 위해 제안 프레임워크를 효과적으로 적용할 수 있음을 확인하였다.

• Geomechanics and Engineering
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• 제18권5호
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• pp.515-525
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• 2019

A karst collapse, as a natural hazard, is totally different to a normal collapse. In recent years, karst collapses have caused substantial economic losses and even threatened human safety. A risk assessment model for karst collapse was developed based on the fuzzy analytic hierarchy process (FAHP) and grey relational analysis (GRA), which is a simple and effective mathematical algorithm. An evaluation index played an important role in the process of completing the risk assessment model. In this study, the proposed model was applied to Jiaobai village in southwest China. First, the main controlling factors were summarized as an evaluation index of the model based on an investigation and statistical analysis of the natural formation law of karst collapse. Second, the FAHP was used to determine the relative weights and GRA was used to calculate the grey relational coefficient among the indices. Finally, the relational sequence of evaluation objects was established by calculating the grey weighted relational degree. According to the maximum relational rule, the greater the relational degree the better the relational degree with the hierarchy set. The results showed that the model accurately simulated the field condition. It is also demonstrated the contribution of various control factors to the process of karst collapse and the degree of collapse in the study area.

• 한국정보시스템학회지:정보시스템연구
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• 제28권2호
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• pp.153-179
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• 2019

Purpose This study collects the issues about work-life balance in Korea and United States and suggests the specific plans for work-life balance by the comparison and analysis. The objective of this study is to contribute to the improvement of people's life quality by understanding the concept of work-life balance that has become the issue recently and offering the detailed plans to be considered in respect of individual, corporate and governmental level for society of work-life balance. Design/methodology/approach This study collects work-life balance related issues through recruit sites in Korea and United States, compares and analyzes the collected data from the results of three text mining techniques such as LDA topic modeling, term frequency analysis and keyword extraction analysis. Findings According to the text mining results, this study shows that it is important to build corporate culture that support work-life balance in free organizational atmosphere especially in Korea. It also appears that there are the differences against whether work-life balance can be achieved and recognition and satisfaction about work-life balance along type of company or sort of working. In case of United States, it shows that it is important for them to work more efficiently by raising teamwork level among team members who work together as well as the role of the leaders who lead the teams in the organization. It is also significant for the company to provide their employees with the opportunity of education and training that enables them to improve their individual capability or skill. Furthermore, it suggests the roles of individuals, company and government and specific plans based on the analysis of text mining results in both countries.

• Imaging Science in Dentistry
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• 제50권4호
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• pp.323-330
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• 2020

Purpose: The mastoid region is ideal for studying sexual dimorphism due to its anatomical position at the base of the skull. This study aimed to determine sex in the Iranian population based on measurements of the mastoid process using different data mining algorithms. Materials and Methods: This retrospective study was conducted on 190 3-dimensional cone-beam computed tomographic (CBCT) images of 105 women and 85 men between the ages of 18 and 70 years. On each CBCT scan, the following 9 landmarks were measured: the distance between the porion and the mastoidale; the mastoid length, height, and width; the distance between the mastoidale and the mastoid incision; the intermastoid distance (IMD); the distance between the lowest point of the mastoid triangle and the most prominent convex surface of the mastoid (MF); the distance between the most prominent convex mastoid point (IMSLD); and the intersecting angle drawn from the most prominent right and left mastoid point (MMCA). Several predictive models were constructed and their accuracy was compared using cross-validation. Results: The results of the t-test revealed a statistically significant difference between the sexes in all variables except MF and MMCA. The random forest model, with an accuracy of 97.0%, had the best performance in predicting sex. The IMSLD and IMD made the largest contributions to predicting sex, while the MMCA variable had the least significant role. Conclusion: These results show the possibility of developing an accurate tool using data mining algorithms for sex determination in the forensic framework.

• 치위생과학회지
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• 제21권1호
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• pp.70-78
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• 2021

Background: The aim of this study was to analyze the public demand for information about the job of dental hygienists by mining text data collected from the online Q & A section on an Internet portal site. Methods: Text data were collected from inquiries that were posted on the Naver Q & A section from January 2003 to July 2020 using "dental hygienist job recognition," "role recognition," "medical assistance," and "scaling" as search keywords. Text mining techniques were used to identify significant Korean words and their frequency of occurrence. In addition, the association between words was analyzed. Results: A total of 10,753 Korean words related to the job of dental hygienists were extracted from the text data. "Chi-lyo (treatment)," "chigwa (dental clinic)," "ske-illing (scaling)," "itmom (gum)," and "chia (tooth)" were the five most frequently used words. The words were classified into the following areas of job of the dental hygienist: periodontal disease treatment and prevention, medical assistance, patient care and consultation, and others. Among these areas, the number of words related to medical assistance was the largest, with sixty-six association rules found between the words, and "chi-lyo," "chigwa," and "ske-illing" as core words. Conclusion: The public demand for information about the job of dental hygienists was mainly related to "chi-lyo," "chigwa," and "ske-illing" as core words, demonstrating that scaling is recognized by the public as the job of a dental hygienist. However, the high demand for information related to treatment and medical assistance in the context of dental hygienists indicates that the job of dental hygienists is recognized by the public as being more focused on medical assistance than preventive dental care that are provided with job autonomy.

• 한국의류학회지
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• 제46권6호
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• pp.1142-1160
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• 2022

Text data plays a significant role in understanding and analyzing trends in consumer, business, and social sectors. For text analysis, there must be a corpus that reflects specific domain knowledge. However, in the field of fashion, the professional corpus is insufficient. This study aims to develop a taxonomy and thesaurus that considers the specialty of fashion products. To this end, about 100,000 fashion vocabulary terms were collected by crawling text data from WSGN, Pantone, and online platforms; text subsequently was extracted through preprocessing with Python. The taxonomy was composed of items, silhouettes, details, styles, colors, textiles, and patterns/prints, which are seven attributes of clothes. The corpus was completed through processing synonyms of terms from fashion books such as dictionaries. Finally, 10,294 vocabulary words, including 1,956 standard Korean words, were classified in the taxonomy. All data was then developed into a web dictionary system. Quantitative and qualitative performance tests of the results were conducted through expert reviews. The performance of the thesaurus also was verified by comparing the results of text mining analysis through the previously developed corpus. This study contributes to achieving a text data standard and enables meaningful results of text mining analysis in the fashion field.