• 기록학연구
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• 제1호
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• pp.23-76
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• 2000

In this paper, I examined what have been researched and determined about preservation strategy and selection of preservation media in the western archival community. Archivists have primarily been concerned with 'preservation' and 'use' of archival materials worth of being preserved permanently. In the new information era, preservation and use of archival materials were faced with new challenge. Life expectancy of paper records was shortened due to acidification and brittleness of the modem papers. Also emergence of information technology affects the traditional way of preservation and use of archival materials. User expectations are becoming so high technology-oriented and so complicated as to make archivists act like information managers using computer technology rather than traditional archival handicraft. Preservation strategy plays an important role in archival management as well as information management. For a cost-effective management of archives and archival institutions, preservation strategy is a must. The preservation strategy encompasses all aspects of archival preservation process and practices, from selection of archives, appraisal, inventorying, arrangement, description, conservation, microfilming or digitization, archival buildings, and access service. Those archival functions should be considered in their relations to each other to ensure proper preservation of archival materials. In the integrated preservation strategy, 'preservation' and 'use' should be combined and fulfilled without sacrificing the other. Preservation strategy planning is essential to determine the policies of archives to preserve their holdings safe and provide people with a maximum access in most effective ways. Preservation microfilming is to ensure permanent preservation of information held in important archival materials. To do this, a detailed standardization has been developed to guarantee the permanence of microfilm as well as its product quality. Silver gelatin film can last up to 500 years in the optimum storage environment and the most viable option for permanent preservation media. ISO and ANIS developed such standards for the quality of microfilms and microfilming technology. Preservation microfilming guidelines was also developed to ensure effective archival management and picture quality of microfilms. It is essential to assess the need of preservation microfilming. Limit in resources always put a restraint on preservation management. Appraisal (and selection) of what to be preserved was the most important part of preservation microfilming. In addition, microfilms with standard quality can be scanned to produce quality digital images for instant use through internet. As information technology develops, archivists began to utilize information technology to make preservation easier and more economical, and to promote use of archival materials through computer communication network. Digitization was introduced to provide easy and universal access to unique archives, and its large capacity of preserving archival data seems very promising. However, digitization, i.e., transferring images of records to electronic codes, still, needs to be standardized. Digitized data are electronic records, and st present electronic records are very unstable and not to be preserved permanently. Digital media including optical disks materials have not been proved as reliable media for permanent preservation. Due to their chemical coating and physical character using light, they are not stable and can be preserved at best 100 years in the optimum storage environment. Most CD-R can last only 20 years. Furthermore, obsolescence of hardware and software makes hard to reproduce digital images made from earlier versions. Even if when reformatting is possible, the cost of refreshing or upgrading of digital images is very expensive and the very process has to be done at least every five to ten years. No standard for this obsolescence of hardware and software has come into being yet. In short, digital permanence is not a fact, but remains to be uncertain possibility. Archivists must consider in their preservation planning both risk of introducing new technology and promising possibility of new technology at the same time. In planning digitization of historical materials, archivists should incorporate planning for maintaining digitized images and reformatting them in the coming generations of new applications. Without the comprehensive planning, future use of the expensive digital images will become unavailable. And that is a loss of information, and a final failure of both 'preservation' and 'use' of archival materials. As peter Adelstein said, it is wise to be conservative when considerations of conservations are involved.

• Korean Chemical Engineering Research
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• 제57권5호
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• pp.637-651
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• 2019

정유 또는 석유화학플랜트에서 폭발 등과 중대사고가 발생할 때 심각한 인명 및 재산피해를 야기시켜 보험시장에 큰 영향을 끼쳐왔다. 일반적으로 정유, 석유화학공장 등 장치산업에서 이러한 사고 발생시 국립과학수사연구원, 사고원인 조사자, 손해보험사 손해사정사 등이 조사하여 손해 및 사고와 가장 인접한 근인 위주로 사고원인을 도출하고 있다. 반면 실제 중대사고로 이어지기까지 문제 및 결함으로 작용한 여러 중대사고 전조신호에 대한 근본원인분석을 실시하여 예방대책을 수립하는 것이 중요하나 그 동안이에 대한 것이 미흡하였다. 이에 본 연구에서는 전 세계에서 발생된 중대사고 사례에 대하여 근본원인분석 방법과 스위스치즈모델 원리를 활용한 기여요소분석법 등을 통하여 도출하였던 미국 화학공정안전센터의 중대사고 전조신호 자체평가 도구의 전조신호 판단기준 항목을 우선적으로 고찰하였다. 여기에 실제 정유 및 석유화학플랜트 내 중대사고 전조신호가 해외재보험사 Loss control engineer 등 Auditor 들에게 어떠한 식으로 권고되어 왔는지 확인하고자 지난 17년간 Loss Control Engineer가 Risk Survey 이후 도출하였던 안전권고사항 약 614개를 분석하였다. 최종적으로 이를 중대사고 전조신호 평가지표로 개발이 용이하도록 정유 및 석유화학플랜트에서의 중대사고 전조신호 판단기준을 유형별로 그룹화한 후 상위 및 하위 항목으로 구분하였다. 또한, 정유 및 석유화학공장 관련 전문가(40명)에게 설문 실시 및 AHP기법을 적용하여 각 항목별 가중치(중요도)를 도출하여 최종 전조신호 판단기준과 항목별 가중치가 적용된 '정유 및 석유화학플랜트에서의 중대사고 전조신호 평가지표'를 개발하였다. 그리고 개발한 지표를 8개의 정유 및 석유화학플랜트에 적용하여 분석하였다. 본 연구에서 개발된 평가지표는 정유 및 석유화학공장 등 장치산업에서의 중대사고 예방을 위하여 추적관리 되어야 할 전조신호 항목 및 요소가 무엇인지 인식하고 취약수준을 평가하는데 도움이 될 수 있고, 관련 사업장 자체 관계자뿐만 아니라 외부 auditor들에게 유용하게 활용되리라 판단된다.

• 지능정보연구
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• 제28권1호
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• pp.89-106
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• 2022

최근 영상 데이터의 급증으로 이를 효과적으로 처리하기 위해 객체 탐지 및 추적, 행동 인식, 표정 인식, 재식별(Re-ID)과 같은 다양한 컴퓨터비전 기술에 대한 수요도 급증했다. 그러나 객체 탐지 및 추적 기술은 객체의 영상 촬영 장소 이탈과 재등장, 오클루전(Occlusion) 등과 같이 성능을 저하시키는 많은 어려움을 안고 있다. 이에 따라 객체 탐지 및 추적 모델을 근간으로 하는 행동 및 표정 인식 모델 또한 객체별 데이터 추출에 난항을 겪는다. 또한 다양한 모델을 활용한 딥러닝 아키텍처는 병목과 최적화 부족으로 성능 저하를 겪는다. 본 연구에서는 YOLOv5기반 DeepSORT 객체추적 모델, SlowFast 기반 행동 인식 모델, Torchreid 기반 재식별 모델, 그리고 AWS Rekognition의 표정 인식 모델을 활용한 영상 분석 시스템에 단일 연결 계층적 군집화(Single-linkage Hierarchical Clustering)를 활용한 재식별(Re-ID) 기법과 GPU의 메모리 스루풋(Throughput)을 극대화하는 처리 기법을 적용한 행동 및 표정 검출용 영상 분석 시스템을 제안한다. 본 연구에서 제안한 시스템은 간단한 메트릭을 사용하는 재식별 모델의 성능보다 높은 정확도와 실시간에 가까운 처리 성능을 가지며, 객체의 영상 촬영 장소 이탈과 재등장, 오클루전 등에 의한 추적 실패를 방지하고 영상 내 객체별 행동 및 표정 인식 결과를 동일 객체에 지속적으로 연동하여 영상을 효율적으로 분석할 수 있다.

• 중소기업연구
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• 제31권1호
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• pp.73-88
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• 2009

본 연구는 우리나라 대표적인 강소기업들을 대상으로 심층적 사례조사를 실시하여 새로운 비즈니스 영역의 창출에 필요한 정책적 과제를 도출하고자 했다. 이를 통해 경제 구조적전환기에 금융위기가 가중된 경영환경 속에서 과연 중소기업들이 어떻게 신시장을 개척하고 신성장동력을 지속적으로 유지할 수 있는지에 관해 답변해보고자 했다. 24개 강소기업들에 관한 심층적 전략분석을 토대로 이들의 성공유형과 잠재된 실패요인(성공함정)들을 조사했으며, 그 결과 한국 강소기업의 8가지 유형을 제시했다. 또한 이들의 생존비결과 그에 따른 문제점을 살펴봄으로써 향후 지속적인 경쟁력 유지를 위해 고려해야 할 당면과제들을 도출했다. 이러한 조사결과들을 토대로 우리나라 강소기업들이 신성장동력을 지속적으로 확보하기 위한 전략대안과 정책적 지원방안에 관해서 논의하였다. 이와 함께 '저탄소 녹색성장'의 국가비전에 대해서도 중소기업을 위한 기회창출이라는 차원에서 논의하였다.

• 벤처창업연구
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• 제18권5호
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• pp.91-107
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• 2023

린 스타트업은 효율적인 기업 운영 방식을 의미하는 '린(lean)'과 창업 초기기업을 의미하는 '스타트업(startup)'을 결합해 만들어진 개념으로 창업 초기기업, 특히 소프트웨어 기반 스타트업의 실패 최소화 전략으로 자주 인용되고 있다. 본 연구는 초기스타트업 L사의 사례를 통하여 하드웨어·제조업 기업도 린 스타트업 방법론(LSM)을 유용하게 활용할 수 있음을 제시하고, 초기 스타트업이 LSM을 성공적으로 실천하기 위한 방안을 도출하였다. 이를 위해 LSM의 핵심 개념인 가설중심의 접근법, BML 피드백 순환, 최소요건제품(MVP) 및 피봇을 설명하고, 이를 바탕으로 LSM의 성공적인 실천 여부를 평가할 수 있는 기준을 도출한 후 동 기준을 중심으로 L사의 사례를 분석하였다. L사는 거동불편환자용 배변알리미 제품에서 출발하여, 영유아용 배변알리미를 거쳐, 최종적으로는 영유아용 스마트바틀을 주력 제품으로 사업을 확장하고 있는 스타트업이다. LSM의 관점에서 분석한 결과, L사는 창업 초기에는 창업 아이디어를 구체적인 고객 가치가설로 수립하지 못했고, 신속한 MVP실험을 통해 검증하는 데에도 실패하였으므로 만들기-측정-학습의 순환을 만들어내는데 실패하였다. 그러나 두 차례에 걸친 피봇을 통해 새로운 타겟 고객군과 고객 니즈를 개발하였고, 이를 최소의 노력과 시간을 들인 MVP로 반복적으로 실험함으로써 성공적인 비즈니스모델을 도출할 수 있었다. L사의 사례를 통해 사업초기에 반드시 고객-시장 검증 단계를 거쳐야 하며, 이는 스타트업의 시간과 자원이 낭비되지 않는 MVP 방식으로 진행되어야 함을 확인할 수 있었다. 또한 고객이 원하지 않는 제품이나 서비스는 기술적으로 우수하고 기능적으로 완성도가 높다 하더라도 과감히 포기하고 피봇할 필요성이 있음도 확인하였다. 마지막으로 린 스타트업 방법론이 소프트웨어 산업에 국한되지 않고, 기술기반 제조업에도 적용 가능함을 증명하였다. 본 연구의 결과는 향후 창업 초기기업이 실패를 최소화하고, 비즈니스모델 확립과 스케일업, 글로벌 진출에 이르는 과정을 가속화하기 위한 지침과 방법론으로 활용될 수 있을 것이다.

• 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.

• 마케팅과학연구
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• 제20권2호
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• pp.208-218
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• 2010

互联网快速增长, 已经成为一个重要的零售渠道, 并出现了各种互联网零售商, 又称电子零售商. 一种网上代购店蓬勃发展起来, 吸引了国内市场的消费者. 这是一种独特的电子零售商, 他们从全球购买国内市场尚未进口的名牌产品, 寄给个人购买者, 并收取服务费. 有些消费者喜欢高端独特但无进口资格的品牌, 却因付款问题或国内的寄送问题很难直接从海外零售商处购买. 在韩国, 网上代购店的数量和销售量快速增长-2008年韩国有超过430个活跃商店和5000亿销售额, 需要这种代购服务的消费者数量也在急剧增加. 这种电子零售的概念源于 "代理中介采购" -种存在已久的形式和内容多样化的代购. 通常市场经营者面对的是购买者的代表人而非本人, 由消费者决定的代理购买者影响越来越大. 很多市场营销和心理学领域的学者都研究过代理对消费者购买决定的影响范围. 然而, 在互联网商务方面却没有深入的研究. 此外, 网上代购店作为代理购买者, 将海外品牌或零售商同国内消费者连接起来. 它有一个特点, 代理购买国, 即代购商品所在国的形象对消费者的态度和购买倾向有重要影响, 还会影响消费者在进行信息处理时所感知的风险维度. 然而, 尽管对原产国不同维度的影响已有很多研究, 对网络内容的相关研究却很少. 已有研究证明, 原产国信息作为产品制造情况的线索对消费者的评价有正面影响, 但对这种形式下网络代理购买国的形象和产品评价之间的关系进行的研究却很少. 因此, 作者们发这种具体的零售渠道很值得研究, 重点结构间的系统关系以及各自不同的路径很值得探索. 已有研究证明代购原产国, 也就是代购店购买商品所在地的形象, 不仅对消费者的产品评价(包括态度和购买意向)有正面影响, 还对感知风险的三个维度有负面影响: 产品相关, 行员相关, 以及购买后的风险. 在所有的感知风险中, 由于对产品性能的高度不确定性, 产品相关的风险受负面形象的影响最大(${\beta}$= -.30), 其次是航运相关风险(${\beta}$= -.18)和购买后的风险(${\beta}$= -.15). 对产品态度(${\beta}$= .10)和购买倾向(${\beta}$= .14)也有一定影响. 此外, 经证明, 感知风险的三个维度通过对产品的态度作为中介, 对购买倾向有负面的的影响(${\beta}$= -.57: 产品相关风险${\rightarrow}$ 对产品的态度; ${\beta}$= -.24: 航运相关风险${\rightarrow}$ 对产品的态度; ${\beta}$= -.44: 购买后风险${\rightarrow}$ 对产品的态度). 从更多的分析可以看出, 消费者处理信息的路径会因其对产品知识的等级不同而改变. 新手购买者知识等级较低, 只会考虑感知风险, 而知识等级较高的专家购买者则会考虑到代理购买国的形象和感知风险两个方面, 对产品形成更准确更系统的态度和决定. 这同之前的研究相一致. 本研究提出一些理论和实际的建议. 代理购买国的形象会影响消费者的风险感知和行为结果, 因此应谨慎选择代购国家, 如果这种新型的零售业务快速发展起来, 应控制好消费者的风险, 无论是新手或专家. 另外, 由于消费者各自知识等级不同, 处理信息的路径也不尽相同, 针对不同消费者应形成成熟的市场营销手段. 新手购买者需要风险消减方面的建议, 以帮助他们形成更好的态度, 而专家购买者应选择更好更发达的国家进行代购. 消费者可以使用担保策略来促使在线购物的顺利进行. 本研究没有拘于概括性等限制. 在今后的研究中, 应进一步测试比较有相关结构的不同电子零售商.