• 생명과학회지
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• 제31권12호
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• pp.1079-1087
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• 2021

본 연구는 국내 가축의 장내 미생물 군집 분포와 시료간 미생물학적 차이에 대하여 차세대 염기서열 분석법(NGS)을 이용하여 분석하였다. 전국의 축사에서 닭, 돼지, 소의 분변시료를 무작위로 채집하여 α-diversity를 분석한 결과, 종 추정치와 종 풍부도가 세 종류의 가축 모두에서 통계학적 유의성을 가지면서 소, 돼지, 닭 순으로 높게 분석되었다. 그러나 조류에 속하는 닭과 포유류에 속하는 돼지, 소에 대한 각 사이의 종 다양성은 통계학적 유의성이 있는 것으로 분석되었으나, 돼지와 소의 사이의 종 다양성은 통계학적 유의성이 없는 것으로 분석되었다. 각 가축 내 장내 미생물 군집의 분포를 분석한 결과, 문 수준에서 세 종류의 가축 모두 Firmicutes가 우점한 것으로 나타났으며, 속 수준에서는 닭의 분변시료는 Weissella, 돼지의 분변시료는 Prevotella, 소의 분변시료는 Acinetobacter가 우점 속으로 나타났다. 각 가축 분변시료의 미생물 군집 분포에 차이가 있는지 분석하기 위해 PERMANOVA 분석을 수행한 결과, 닭, 돼지, 소의 분변시료 내 미생물 군집의 중심과 산포는 통계학적으로 유의성을 가진 것으로 나타났다. 또한 각 가축 분변시료의 미생물 군집을 대표하는 biomarker를 분석하기 위해 LEfSe 분석을 수행한 결과, Weissella와 Lactobacillus는 닭의 분변을 다른 두 가축과 구분할 수 있는 미생물로, Preveotella는 돼지의 분변을 다른 두 가축과 구분할 수 있는 미생물로, Acinetobacter는 소의 분변을 다른 두 가축과 구분할 수 있는 미생물로 분석되었다. 본 연구를 기반으로 축사 여건에 적합한 체증 관련 미생물의 탐색, 생애주기별 장내 미생물 군집과 유전체 분석 및 각 가축에 특화된 생균제 개발 등 추가적인 연구 진행에 필요한 미생물학적 기초자료로 활용할 수 있을 것으로 기대된다.

• 한국재난정보학회 논문집
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• 제16권4호
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• pp.813-823
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• 2020

연구목적: 원자로 내부 시설물 해체 등의 고위험 시설이나 고비용 작업에 앞서 시뮬레이션을 통한 작업의 안정성과 생산성을 최대화하기 위해 실제 제어 장비의 제원을 시뮬레이션 상에 모사하고 이를 통해 정밀 제어될 수 있는 디지털 트윈 기술을 이용하고자 한다. 디지털 트윈 기술을 적용함에 정밀 제어 장비와 시뮬레이션의 시간적 격차로 인해 발생할 수 있는 동작 제어 오차는 위험 시설물과 제어 장비 간의 충돌 등과 같은 위험 요소들을 발생시킬 수 있다. 이러한 상황을 제거하고 통제하기 위해서는 사전 연구가 필요하다. 연구방법: 현재 시뮬레이션을 개발함에 가장 대중적으로 사용되는 엔진으로는 Unity 3D가 있다. 하지만 Unity 3D 엔진 내부의 시간 보정으로 인해 발생할 수 있는 제어 오차가 존재한다. 그 오차는 여러 환경에 예상되고 그 오차는 시스템 사양 등의 개발 환경에 따라 다를 수 있다. 이를 입증하기 위해 Unity 3D 엔진을 이용하여 충돌 시뮬레이션 개발하고 이를 통해 다양한 조건의 충돌실험을 진행하고 그에 따른 결과를 정리하고 분석하여 이를 토대로 정밀 제어 장비의 허용 오차를 도출한다. 연구결과: 충돌실험 시뮬레이션을 통한 실험에서 엔진 내부 함수호출에 1/1000초 단위의 시간 보정으로 인해 충돌체의 이동제어에 단위 시간당 거리오차가 발생하고 거리오차는 충돌체의 이동속도와 비례한다. 결론: 디지털 트윈을 이용한 원격해체 시뮬레이터는 하드웨어와 소프트웨어 환경과 수동 제어 시 정밀 제어 장치의 요구 정밀도에 따른 이동속도의 제한이 필요할 것으로 판단된다. 그리고 운용 제어 장비의 가용 및 허용 오차와 작업의 요구 속도를 시스템 개발 환경, 하드웨어 사양과 시뮬레이션에 모사된 제어 장비 및 시설물 등의 모델링 데이터의 크기도 반드시 고려한다.

• Asia pacific journal of information systems
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• 제24권4호
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• pp.443-472
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• 2014

To survive in the global competitive environment, enterprise should be able to solve various problems and find the optimal solution effectively. The big-data is being perceived as a tool for solving enterprise problems effectively and improve competitiveness with its' various problem solving and advanced predictive capabilities. Due to its remarkable performance, the implementation of big data systems has been increased through many enterprises around the world. Currently the big-data is called the 'crude oil' of the 21st century and is expected to provide competitive superiority. The reason why the big data is in the limelight is because while the conventional IT technology has been falling behind much in its possibility level, the big data has gone beyond the technological possibility and has the advantage of being utilized to create new values such as business optimization and new business creation through analysis of big data. Since the big data has been introduced too hastily without considering the strategic value deduction and achievement obtained through the big data, however, there are difficulties in the strategic value deduction and data utilization that can be gained through big data. According to the survey result of 1,800 IT professionals from 18 countries world wide, the percentage of the corporation where the big data is being utilized well was only 28%, and many of them responded that they are having difficulties in strategic value deduction and operation through big data. The strategic value should be deducted and environment phases like corporate internal and external related regulations and systems should be considered in order to introduce big data, but these factors were not well being reflected. The cause of the failure turned out to be that the big data was introduced by way of the IT trend and surrounding environment, but it was introduced hastily in the situation where the introduction condition was not well arranged. The strategic value which can be obtained through big data should be clearly comprehended and systematic environment analysis is very important about applicability in order to introduce successful big data, but since the corporations are considering only partial achievements and technological phases that can be obtained through big data, the successful introduction is not being made. Previous study shows that most of big data researches are focused on big data concept, cases, and practical suggestions without empirical study. The purpose of this study is provide the theoretically and practically useful implementation framework and strategies of big data systems with conducting comprehensive literature review, finding influencing factors for successful big data systems implementation, and analysing empirical models. To do this, the elements which can affect the introduction intention of big data were deducted by reviewing the information system's successful factors, strategic value perception factors, considering factors for the information system introduction environment and big data related literature in order to comprehend the effect factors when the corporations introduce big data and structured questionnaire was developed. After that, the questionnaire and the statistical analysis were performed with the people in charge of the big data inside the corporations as objects. According to the statistical analysis, it was shown that the strategic value perception factor and the inside-industry environmental factors affected positively the introduction intention of big data. The theoretical, practical and political implications deducted from the study result is as follows. The frist theoretical implication is that this study has proposed theoretically effect factors which affect the introduction intention of big data by reviewing the strategic value perception and environmental factors and big data related precedent studies and proposed the variables and measurement items which were analyzed empirically and verified. This study has meaning in that it has measured the influence of each variable on the introduction intention by verifying the relationship between the independent variables and the dependent variables through structural equation model. Second, this study has defined the independent variable(strategic value perception, environment), dependent variable(introduction intention) and regulatory variable(type of business and corporate size) about big data introduction intention and has arranged theoretical base in studying big data related field empirically afterwards by developing measurement items which has obtained credibility and validity. Third, by verifying the strategic value perception factors and the significance about environmental factors proposed in the conventional precedent studies, this study will be able to give aid to the afterwards empirical study about effect factors on big data introduction. The operational implications are as follows. First, this study has arranged the empirical study base about big data field by investigating the cause and effect relationship about the influence of the strategic value perception factor and environmental factor on the introduction intention and proposing the measurement items which has obtained the justice, credibility and validity etc. Second, this study has proposed the study result that the strategic value perception factor affects positively the big data introduction intention and it has meaning in that the importance of the strategic value perception has been presented. Third, the study has proposed that the corporation which introduces big data should consider the big data introduction through precise analysis about industry's internal environment. Fourth, this study has proposed the point that the size and type of business of the corresponding corporation should be considered in introducing the big data by presenting the difference of the effect factors of big data introduction depending on the size and type of business of the corporation. The political implications are as follows. First, variety of utilization of big data is needed. The strategic value that big data has can be accessed in various ways in the product, service field, productivity field, decision making field etc and can be utilized in all the business fields based on that, but the parts that main domestic corporations are considering are limited to some parts of the products and service fields. Accordingly, in introducing big data, reviewing the phase about utilization in detail and design the big data system in a form which can maximize the utilization rate will be necessary. Second, the study is proposing the burden of the cost of the system introduction, difficulty in utilization in the system and lack of credibility in the supply corporations etc in the big data introduction phase by corporations. Since the world IT corporations are predominating the big data market, the big data introduction of domestic corporations can not but to be dependent on the foreign corporations. When considering that fact, that our country does not have global IT corporations even though it is world powerful IT country, the big data can be thought to be the chance to rear world level corporations. Accordingly, the government shall need to rear star corporations through active political support. Third, the corporations' internal and external professional manpower for the big data introduction and operation lacks. Big data is a system where how valuable data can be deducted utilizing data is more important than the system construction itself. For this, talent who are equipped with academic knowledge and experience in various fields like IT, statistics, strategy and management etc and manpower training should be implemented through systematic education for these talents. This study has arranged theoretical base for empirical studies about big data related fields by comprehending the main variables which affect the big data introduction intention and verifying them and is expected to be able to propose useful guidelines for the corporations and policy developers who are considering big data implementationby analyzing empirically that theoretical base.