The Analysis of a Diet for the Human Being and the Companion Animal using Big Data in 2016

( Eun-jin Jung ),( Young-suk Kim ),( Jung-wa Choi ),( Hye Won Kang ),( Un-jae Chang ) 한국임상영양학회 2017 Clinical Nutrition Research Vol.6 No.4

The purpose of this study was to investigate the diet tendencies of human and companion animals using big data analysis. The keyword data of human diet and companion animals' diet were collected from the portal site Naver from January 1, 2016 until December 31, 2016 and collected data were analyzed by simple frequency analysis, N-gram analysis, keyword network analysis and seasonality analysis. In terms of human, the word exercise had the highest frequency through simple frequency analysis, whereas diet menu most frequently appeared in the N-gram analysis. companion animals, the term dog had the highest frequency in simple frequency analysis, whereas diet method was most frequent through N-gram analysis. Keyword network analysis for human indicated 4 groups: diet group, exercise group, commercial diet food group, and commercial diet program group. However, the keyword network analysis for companion animals indicated 3 groups: diet group, exercise group, and professional medical help group. The analysis of seasonality showed that the interest in diet for both human and companion animals increased steadily since February of 2016 and reached its peak in July. In conclusion, diets of human and companion animals showed similar tendencies, particularly having higher preference for dietary control over other methods. The diets of companion animals are determined by the choice of their owners as effective diet method for owners are usually applied to the companion animals. Therefore, it is necessary to have empirical demonstration of whether correlation of obesity between human being and the companion animals exist.

Analysis of Research Trends of NRF’s Humanities City Support Project

최에스더,정진경,이규태 한국비교정부학회 2023 한국비교정부학보 Vol.27 No.4

(Purpose) Through the analysis of unstructured big data, this study analyzes the research trends in the field of the Humanities Popularization Project of the Korea Research Foundation over the past 10 years to examine whether the purpose of the Humanities City Support Project is being effectively promoted and to explore the way forward. (Design/methodology/approach) After collecting data related to keywords, research goals, expected effects, and research summaries of the research project, we connected the data to the data held by Textom, a big data analysis solution program, to perform data purification and preprocessing. The frequency and matrix files generated by Textom were connected to the UciNet program to perform semantic linkage network and centrality analysis. CONCOR analysis, a technique that clusters keywords in structural positions by analyzing the relationship between co-occurring keywords, was performed. (Findings) The results of the TF-IDF analysis were presented in the order of 'healing', 'humanities', 'culture', 'happiness', 'city', 'community', 'region', 'citizen', 'art', and 'resident'. The results of the connection centrality analysis show that 'humanities' and 'humanities' 'culture', 'city', 'region', 'citizen', 'course', 'business', 'history', 'experience', 'society', and 'program' are highly active, which is similar to the results of the frequency and TF-IDF analysis. In addition, the results of the dominance centrality analysis are similar to the results of the connection centrality analysis. The CONCOR analysis shows that the first group is highly related to keywords related to the understanding of humanities such as 'humanities', 'humanities', 'culture', 'humanities-based', 'tradition', and 'human'. The second group shows high keyword relevance for humanities subjects such as "city," "region," "citizen," "community," "communication," "participation," "residents," and "youth. The third group includes humanities programs such as "history," "courses," "programs," "topics," "education," "composition," "literature," "art," and "content," and the fourth group includes humanities directions such as "life," "values," "healing," "spirit," "meaning," "proliferation," "stagnation," "future," "opportunity," and "contribution. (Research implications or Originality) Based on these findings, we believe that the way forward is to develop humanities programs that directly involve local community members in order to meet the goals of the HRF's Humanities Popularization Project. To this end, we summarize our policy suggestions as follows. First, budgetary support is needed to increase the value of the humanities through the Humanities City Support Project and to share and spread humanities programs with the public. Second, the Humanities City Support Project should be renamed the 'Humanities and Arts City Support Project' by including the arts in its scope, and should be made more public-friendly by adding experiences and performances to humanities-centered lectures. Third, as the times are changing rapidly and the channels for listening to theoretical humanities lectures through online media are diversifying and popularizing, it is necessary to specialize in programs that can generate experience and interest and activate community resources instead of focusing on lectures. If the project so far has been mainly a case of mobilizing audiences artificially, we should avoid this and ask for a way to actively engage basic local governments in lifelong education.

HUMAN ERRORS DURING THE SIMULATIONS OF AN SGTR SCENARIO: APPLICATION OF THE HERA SYSTEM

WONDEA JUNG,APRIL M. WHALEY,BRUCE P. HALLBERT 한국원자력학회 2009 Nuclear Engineering and Technology Vol.41 No.10

Due to the need of data for a Human Reliability Analysis (HRA), a number of data collection efforts have been undertaken in several different organizations. As a part of this effort, a human error analysis that focused on a set of simulator records on a Steam Generator Tube Rupture (SGTR) scenario was performed by using the Human Event Repository and Analysis (HERA) system. This paper summarizes the process and results of the HERA analysis, including discussions about the usability of the HERA system for a human error analysis of simulator data. Five simulated records of an SGTR scenario were analyzed with the HERA analysis process in order to scrutinize the causes and mechanisms of the human related events. From this study, the authors confirmed that the HERA was a serviceable system that can analyze human performance qualitatively from simulator data. It was possible to identify the human related events in the simulator data that affected the system safety not only negatively but also positively. It was also possible to scrutinize the Performance Shaping Factors (PSFs) and the relevant contributory factors with regard to each identified human event.

Data-driven Co-Design Process for New Product Development : A Case Study on Smart Heating Jacket

Sooyeon Leem,Sang Won Lee 한국융합학회 2021 한국융합학회논문지 Vol.12 No.1

본 연구는 객관적인 데이터 기반 방법을 통해 인간 중심 디자인 과정을 효과적으로 보완하는 디자인 프로세스를 제시한다. 즉, 주관적 방법에 의한 인간 중심 디자인 프로세스에서 결여되는 객관성이 데이터 기반 접근에 의해 보완되 어 숨겨진 사용자의 니즈를 효과적으로 발견하는 프로세스로 발전될 수 있다. 이에 본 연구에서는 설문조사 데이터 마이닝 분석 과정과 공동 디자인 프로세스가 접목된 인간 중심 디자인 프로세스를 제시하며, 스마트 난방복 사례연구를 통해 이를 검증한다. 설문조사 데이터 마이닝 분석 과정에서는 클러스터링과 의사결정 나무의 두 가지 분석 방법이 사용된다. 클러스터링은 타겟 그룹을 선정하는 기준이 되는 페르소나의 초안을 제시하며, 의사결정 나무는 제품 구매에 중요한 사용자 인식 속성 파악과 사용자 가치 체계를 일차적으로 제안한다. 이후 데이터 분석을 통해 얻어진 광범위한 관점에 대하여 타겟 그룹을 대표하는 사용자가 직접 참여하는 공동 디자인 프로세스가 수행되며 맞춤형 워크북을 이용 하여 신제품에 대한 사용자의 여정맵, 니즈, 아이디어, 가치 체계 등을 체계적으로 도출한다. 본 논문에서 수행한 스마 트 난방복 사례 연구는 제안된 방법론의 적용성을 보여주고 있다. This research suggests a design process that effectively complements the human-centered design through an objective data-driven approach. The subjective human-centered design process can often lack objectivity and can be supplemented by the data-driven approaches to effectively discover hidden user needs. This research combines the data mining analysis with co-design process and verifies its applicability through the case study on the smart heating jacket. In the data mining process, the clustering can group the users which is the basis for selecting the target groups and the decision tree analysis primarily identifies the important user perception attributes and values. The broad point of view based on the data analysis is modified through the co-design process which is the deeper human-centered design process by using the developed workbook. In the co-design process, the journey maps, needs and pain points, ideas, values for the target user groups are identified and finalized. They can become the basis for starting new product development.

HUMAN ERRORS DURING THE SIMULATIONS OF AN SGTR SCENARIO: APPLICATION OF THE HERA SYSTEM

Jung, Won-Dea,Whaley, April M.,Hallbert, Bruce P. Korean Nuclear Society 2009 Nuclear Engineering and Technology Vol.41 No.10

Due to the need of data for a Human Reliability Analysis (HRA), a number of data collection efforts have been undertaken in several different organizations. As a part of this effort, a human error analysis that focused on a set of simulator records on a Steam Generator Tube Rupture (SGTR) scenario was performed by using the Human Event Repository and Analysis (HERA) system. This paper summarizes the process and results of the HERA analysis, including discussions about the usability of the HERA system for a human error analysis of simulator data. Five simulated records of an SGTR scenario were analyzed with the HERA analysis process in order to scrutinize the causes and mechanisms of the human related events. From this study, the authors confirmed that the HERA was a serviceable system that can analyze human performance qualitatively from simulator data. It was possible to identify the human related events in the simulator data that affected the system safety not only negatively but also positively. It was also possible to scrutinize the Performance Shaping Factors (PSFs) and the relevant contributory factors with regard to each identified human event.

엔그램 뷰어를 이용한 인문학의 빅데이타 사례 연구

문상호 사단법인 인문사회과학기술융합학회 2015 예술인문사회융합멀티미디어논문지 Vol.5 No.6

최근에 학술 연구의 한 방법으로서 인문학과 정보기술이 융합된 형태의 시스템에 대한 사용자 요구 및 사례가 증가되고 있는 추세이다. 그리고 모바일 시대를 맞이하여 데이터 양이 기하급수적으로 증가하는 엄청난 양의 데이터를 처리할 수 있는 빅데이타 기술이 정보기술 분야의 차세대 패러다임으로 주목받고 있다. 이러한 추세에 맞추어 빅데이타가 인문학과 결합한 형태인 빅데이타 인문학이 디지털 인문학과 연계하여 새롭게 떠오르고 있다. 아직은 빅데이타 인문학 분야가 초기 단계에 머물러 있지만, 디지털 아카이빙을 통하여 축적된 인문학 관련 정보들을 기반으로 빅데이타 응용 기술을 활용한다면 인문학 관련 연구 수행이나 결과 활용 및 확산에 많은 파급 효과가 있을 것으로 판단된다. 본 논문에서는 이러한 빅데이타 인문학에 대하여 구글의 엔그램 뷰어를 중심으로 한 사례 연구를 수행한다. 세부적으로 이스라엘·팔레스타인 분쟁, 이란 혁명 등을 대상으로 주요 키워드를 추출한 후에, 특정 시기의 도서들에서 이 키워드들의 출현 빈도 추세를 통하여 분석하였다. As a methodology for academic studies, user requirements and use cases on systems which are fusion of Humanities and information technology are increasing. Because the amount of data increases exponentially with the advent of the mobile era, big data technologies are being hailed as the next-generation paradigm of information technology. Big data humanities is a field of study that combines big data and Humanities, and is emerging with digital humanities. Big data humanities has remained yet at an early stage. But, there are a lot of effects on humanities research if big data application technologies will be utilized on huge humanities information accumulated through digital archiving. In this paper, we carry out case studies of big data in Humanities using Ngram viewer of Google. In detail, first, we extract the main keywords on events such as Israeli-Palestinian conflict and Iranian revolution. Then, analysis was performed through occurrence frequency trend which these keywords appear in the books of particular times.

빅데이터 산업 인력양성 방안에 대한 연구 : 뉴스 네트워크 분석을 중심으로

이호,송주호 한국지식정보기술학회 2021 한국지식정보기술학회 논문지 Vol.16 No.6

The Fourth Industrial Revolution has made data and knowledge more important than the major factors of production of the past, such as labor and capital. However, although the demand for data job manpower in all domestic industries is rapidly increasing, it is expected that the manpower supply will be insufficient. Therefore, this study intends to explore the phenomena of industry and manpower in the field of big data, which became the most basic in the intelligent information society, by collecting and analyzing media big data, and to suggest the directions for solving the industry's human resource paradox. As a research method, we used quantitative text network analysis and qualitative analysis from industry experts to interpret the results. A total of 36,693 news data mentioning 'big data' were extracted, and data preprocessing for the synonyms and negative words were performed. The constructed text network is non-directional and consists of 310,028 words (nodes) and 3,055,375 word combinations (edges). Among the 11 clusters, additional content analysis was conducted for the top 4 clusters that accounted for more than 10% of the network proportion. As a result of analyzing, it was revealed whether the government's efforts to revitalize big data analysis are continuing, and there is still a lack in data utilization and human resource training in other fields except finical industry. It is expected that job training for big data analysis centered on middle-aged people with domain knowledge in appropriate field will lead directly to fostering convergent talents and solving job problems.

데이터 분석 기반의 이스라엘-팔레스타인 분쟁 연구

강지훈 국제차세대융합기술학회 2024 차세대융합기술학회논문지 Vol.8 No.1

데이터 기반의 정량 연구는 연구의 객관성을 담보할 수 있다는 점에서 다양한 분야의 학술연구에 적용된다. 특히 정보기술의 도움 없이 수행하기 힘든 빅데이터 처리를 통한 데이터 분석이 필요한 분야의 연구는 정보기술의 활용이 필수적이다. 본 연구는 빅데이터를 활용해 인문학, 지역학 연구를 수행하는 방안을 제시한다. 특히 데이터 분석 절차와 방법에 따라 분석 결과 및 해석이 크게 달라질 수 있음에 주목한다. 세부적으로 특정 지역을 연구하는 지역학 분야 연구 시 공간데이터의 활용 유무에 따라 다양한 분석 결과와 해석이 가능함을 사례연구를 통해 검증한다. 본 연구에서는 이스라엘-팔레스타인 분쟁에 대해 통계 분석 및 공간데이터 기반의 공간 분석을 병행하여 해당 분쟁지역에 대해 분석했다. 분석 결과 공간데이터 활용 유무에 따라 이스라엘-팔레스타인 분쟁에 대한분석과 해석에 대한 방향성이 확연한 차이가 있음을 확인했다. Data-based quantitative research is actively applied to academic research in various fields because it can guarantee the objectivity of research. This study focuses on the fact that when applying data analysis techniques to academic research such as humanities or area studies, analysis results and interpretations can vary greatly depending on the data analysis process. In detail, verify through case studies that various analysis results and interpretations are possible depending on the use or absence of spatial data when conducting research in the field of area studies that studies a specific area. In this study, the conflict area of the Israel-Palestine conflict was analyzed using statistical analysis and spatial analysis based on spatial data in parallel. As a result of the analysis, it was confirmed that there was a clear difference in the direction of analysis and interpretation of the Israel-Palestine conflict depending on whether spatial data was used or not.

빅데이터와 고전문학 연구방법론

김바로,강우규 중앙어문학회 2019 語文論集 Vol.78 No.-

This paper examines various digital methodologies that can be used in classical literature research, and presents the necessity and direction of big data and classical literature convergence research. Using digital analysis techniques, such as a language analysis method, network analysis method, and spatial analysis method, a new study direction of limited classical literary text can be suggested. However, existing digital analysis techniques cannot be applied to classical literary texts, and new digital analysis techniques optimized for classical literary texts need to be developed. In this situation, the direction of big data and classical literature convergence research is to build a sophisticated data model to produce meaningful knowledge. In addition, for classical literature to appreciate its own value, it is necessary to carry out continuous research and make public use plans. In this respect, we call for researchers' interest in classical literature, big data convergence research, and active sharing of classical literary data. 본 논문은 고전문학 연구에 활용될 수 있는 다양한 디지털 방법론을 검토하 여 빅데이터와 고전문학 융합연구의 현재를 진단하고 그 필요성 및 방향성을 제시하였다. 언어분석방법, 네트워크분석방법, 공간분석방법 등의 디지털 분석 기법을 활용하면 한정된 고전문학 텍스트에 대한 새로운 연구 방향성을 제시 해줄 수 있다. 하지만 고전문학 텍스트에 현존하는 디지털 분석 기법을 그대로 적용할 수 없고, 고전문학 텍스트에 최적화된 디지털 분석 기법을 새롭게 개발 해야 할 필요가 있다. 이러한 상황에서 빅데이터와 고전문학 융합연구가 나아갈 방향은 정교한 데이터 모델을 구축하여 의미 있는 지식을 생산해내는 것에 있다. 또한 고전문학 이 고전으로서의 가치를 평가받기 위해서는 끊임없는 연구와 함께 대중적 활 용방안의 마련도 필요하다. 이러한 측면에서 고전문학과 빅데이터 융합연구, 고전문학 데이터의 적극적인 공유에 대한 연구자들의 관심을 촉구한다.

A classification scheme of erroneous behaviors for human error probability estimations based on simulator data

Kim, Yochan,Park, Jinkyun,Jung, Wondea Elsevier 2017 Reliability engineering & system safety Vol.163 No.-

<P><B>Abstract</B></P> <P>Because it has been indicated that empirical data supporting the estimates used in human reliability analysis (HRA) is insufficient, several databases have been constructed recently. To generate quantitative estimates from human reliability data, it is important to appropriately sort the erroneous behaviors found in the reliability data. Therefore, this paper proposes a scheme to classify the erroneous behaviors identified by the HuREX (Human Reliability data Extraction) framework through a review of the relevant literature. A case study of the human error probability (HEP) calculations is conducted to verify that the proposed scheme can be successfully implemented for the categorization of the erroneous behaviors and to assess whether the scheme is useful for the HEP quantification purposes. Although continuously accumulating and analyzing simulator data is desirable to secure more reliable HEPs, the resulting HEPs were insightful in several important ways with regard to human reliability in off-normal conditions. From the findings of the literature review and the case study, the potential and limitations of the proposed method are discussed.</P> <P><B>Highlights</B></P> <P> <UL> <LI> A taxonomy of erroneous behaviors is proposed to estimate HEPs from a database. </LI> <LI> The cognitive models, procedures, HRA methods, and HRA databases were reviewed. </LI> <LI> HEPs for several types of erroneous behaviors are calculated as a case study. </LI> </UL> </P>