• 헤리티지:역사와 과학
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• 제57권1호
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• pp.82-108
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• 2024

고고 자료의 기록방식이 아날로그 기록에서 디지털로 전환되면서 3D 스캐닝 기술의 도입은 본격화되었다. 현재 3D스캔과 사진측량을 이용한 고고 자료의 디지털 기록에 대한 연구와 도입은 지속적으로 이루어지고 있다. 하지만 비용, 인력 문제 등으로 인해 대부분의 매장문화재 기관에서는 적극적인 디지털 기술의 도입을 주저하고 있다. 본고는 3D 스캔 방식 중 효율성이 가장 높다고 평가되는 사진측량 기술을 이용하여 오픈소스 소프트웨어를 활용한 유물의 디지털 실측 방법을 제시하고자 한다. 유물의 디지털 실측 절차는 크게 3D 모델 획득, 3D 모델 편집 및 입단면도 제작, 전자도면 작성의 세 단계로 이루어진다. 디지털 기술 적용의 접근성을 살펴보기 위해 전 과정은 오픈소스 소프트웨어만을 이용하였다. 연구 결과 정량적 평가에서 실제 유물과 3D 모델의 수치 데이터 간 계측의 편차가 크지 않았다. 또한, 오픈소스 소프트웨어와 상용 소프트웨어 간 정량적 품질 비교분석 결과 유사도가 높았다. 다만 데이터 처리시간은 상용 소프트웨어의 성능이 우위에 있었다. 이는 지속적인 알고리즘 개선으로 인한 연산속도 향상의 결과로 판단된다. 정성적 평가에서는 메시 및 텍스처 품질의 차이가 일부 발생하였다. 오픈소스 소프트웨어로 생성된 3D 모델은 메시표면에 노이즈가 다수 발생하거나 메시의 표면이 부드럽지 않고 유물의 제작흔, 문양의 표현을 확인하기 어려웠다. 하지만 일부 프로그램에서 정량적·정성적 평가에서 상용 소프트웨어에 견줄 만한 품질을 획득할 수 있었다. 3D 모델 편집을 위한 오픈소스 소프트웨어에서는 사진실측 결과물의 후처리, 정합, 병합뿐만 아니라 유물 실측에 필요한 스케일 조정, 입단면도 제작 및 이미지 렌더링까지 가능하였다. 이후 오픈소스 캐드 프로그램에서 트레이싱하여 최종 도면을 완성하였다. 고고학 연구에서 사진실측의 적용은 발굴과정부터 보고서 작성 그리고 3D 모델 데이터의 수치정보를 이용한 연구 등 활용 가능성이 매우 높다. 컴퓨터 비전의 획기적인 발전으로 오픈소스 소프트웨어의 종류도 다양해졌고 성능도 상당부분 개선된 것으로 확인되었다. 누구나 쉽게 디지털 기술의 적용이 가능한 현재 고고 자료의 3D 모델 데이터의 획득은 문화유산의 보존과 연구 활성화를 위한 기초자료로 활용될 수 있다.

• Asia pacific journal of information systems
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• 제23권3호
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• pp.25-53
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• 2013

This study analyzes the effect of Computer Aided Innovation (CAI) to improve R&D Capabilities empirically. Survey was distributed by e-mail and Google Docs, targeting CTO of 235 SMEs. 142 surveys were returned back (rate of return 60.4%) from companies. Survey results from 119 companies (83.8%) which are effective samples except no-response, insincere response, estimated value, etc. were used for statistics analysis. Companies with less than 50billion KRW sales of entire researched companies occupy 76.5% in terms of sample traits. Companies with less than 300 employees occupy 83.2%. In terms of the type of company business Partners (called 'partners with big companies' hereunder) who work with big companies for business occupy 68.1%. SMEs based on their own business (called 'independent small companies') appear to occupy 31.9%. The present status of holding IT system according to traits of company business was classified into partners with big companies versus independent SMEs. The present status of ERP is 18.5% to 34.5%. QMS is 11.8% to 9.2%. And PLM (Product Life-cycle Management) is 6.7% to 2.5%. The holding of 3D CAD is 47.1% to 21%. IT system-holding and its application of independent SMEs seemed very vulnerable, compared with partner companies of big companies. This study is comprised of IT infra and IT Utilization as CAI capacity factors which are independent variables. factors of R&D capabilities which are independent variables are organization capability, process capability, HR capability, technology-accumulating capability, and internal/external collaboration capability. The highest average value of variables was 4.24 in organization capability 2. The lowest average value was 3.01 in IT infra which makes users access to data and information in other areas and use them with ease when required during new product development. It seems that the inferior environment of IT infra of general SMEs is reflected in CAI itself. In order to review the validity used to measure variables, Factors have been analyzed. 7 factors which have over 1.0 pure value of their dependent and independent variables were extracted. These factors appear to explain 71.167% in total of total variances. From the result of factor analysis about measurable variables in this study, reliability of each item was checked by Cronbach's Alpha coefficient. All measurable factors at least over 0.611 seemed to acquire reliability. Next, correlation has been done to explain certain phenomenon by correlation analysis between variables. As R&D capabilities factors which are arranged as dependent variables, organization capability, process capability, HR capability, technology-accumulating capability, and internal/external collaboration capability turned out that they acquire significant correlation at 99% reliability level in all variables of IT infra and IT Utilization which are independent variables. In addition, correlation coefficient between each factor is less than 0.8, which proves that the validity of this study judgement has been acquired. The pair with the highest coefficient had 0.628 for IT utilization and technology-accumulating capability. Regression model which can estimate independent variables was used in this study under the hypothesis that there is linear relation between independent variables and dependent variables so as to identify CAI capability's impact factors on R&D. The total explanations of IT infra among CAI capability for independent variables such as organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability are 10.3%, 7%, 11.9%, 30.9%, and 10.5% respectively. IT Utilization exposes comprehensively low explanatory capability with 12.4%, 5.9%, 11.1%, 38.9%, and 13.4% for organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability respectively. However, both factors of independent variables expose very high explanatory capability relatively for technology-accumulating capability among independent variable. Regression formula which is comprised of independent variables and dependent variables are all significant (P<0.005). The suitability of regression model seems high. When the results of test for dependent variables and independent variables are estimated, the hypothesis of 10 different factors appeared all significant in regression analysis model coefficient (P<0.01) which is estimated to affect in the hypothesis. As a result of liner regression analysis between two independent variables drawn by influence factor analysis for R&D capability and R&D capability. IT infra and IT Utilization which are CAI capability factors has positive correlation to organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability with inside and outside which are dependent variables, R&D capability factors. It was identified as a significant factor which affects R&D capability. However, considering adjustable variables, a big gap is found, compared to entire company. First of all, in case of partner companies with big companies, in IT infra as CAI capability, organization capability, process capability, human resources capability, and technology capability out of R&D capacities seems to have positive correlation. However, collaboration capability appeared insignificance. IT utilization which is a CAI capability factor seemed to have positive relation to organization capability, process capability, human resources capability, and internal/external collaboration capability just as those of entire companies. Next, by analyzing independent types of SMEs as an adjustable variable, very different results were found from those of entire companies or partner companies with big companies. First of all, all factors in IT infra except technology-accumulating capability were rejected. IT utilization was rejected except technology-accumulating capability and collaboration capability. Comprehending the above adjustable variables, the following results were drawn in this study. First, in case of big companies or partner companies with big companies, IT infra and IT utilization affect improving R&D Capabilities positively. It was because most of big companies encourage innovation by using IT utilization and IT infra building over certain level to their partner companies. Second, in all companies, IT infra and IT utilization as CAI capability affect improving technology-accumulating capability positively at least as R&D capability factor. The most of factor explanation is low at around 10%. However, technology-accumulating capability is rather high around 25.6% to 38.4%. It was found that CAI capability contributes to technology-accumulating capability highly. Companies shouldn't consider IT infra and IT utilization as a simple product developing tool in R&D section. However, they have to consider to use them as a management innovating strategy tool which proceeds entire-company management innovation centered in new product development. Not only the improvement of technology-accumulating capability in department of R&D. Centered in new product development, it has to be used as original management innovative strategy which proceeds entire company management innovation. It suggests that it can be a method to improve technology-accumulating capability in R&D section and Dynamic capability to acquire sustainable competitive advantage.