• 산업기술연구
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• 제21권A호
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• pp.141-146
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• 2001

XML is fast emerging as the dominant standard to represent and exchange data in the Web. As the amount of data available in the Web has increased dramatically in recent years, the data resides in different forms ranging from semi-structured data to highly structured data in relational database. As semi-structured data will be represented by XML, XML will increase the ability of semi-structured data. In this paper, we propose an idea for extracting schema in XML document using DTD.

• 응용통계연구
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• 제19권2호
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• pp.271-282
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• 2006

본 논문에서는 범주형과 연속형 변수들이 혼합된 데이터에 적용할 수 있는 나무형 군집화 알고리즘을 제안하였다. 특히 혼합된 변수들이 공통의 의미를 갖도록 하기 위해 범주형 변수들을 전처리하는 방법을 고안하였다. 수치 예로서 SPSS의 신용(credit) 데이터와 독일신용자료(German credit data)에 알고리즘을 적용하고 그 결과를 검토하였다.

• Journal of the Korean Data and Information Science Society
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• 제16권2호
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• pp.301-311
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• 2005

This study has conducted to measure the internet banking customer satisfaction using structured equation model. Data was collected by e-mail system. Among survey panel who had experience of using Hanwha-Bank internet banking service, final samples were 2,848 respondents. The results showed that usage convenience and economy factor was most correlated with customer satisfaction. And we found that word-of-mouth behavior was affected customer satisfaction.

• 대한산업공학회지
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• 제14권2호
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• pp.71-80
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• 1988

The primary purpose of this study is to develop an automation tool capable of converting the specification of structured analysis into that of structured design. Structured Analysis and Structured Design Language (SASDL) is a computer-aided description language based on ERA model and particulariged by ISLDM/SEM. The automation tool utilizes the specifications of data flow diagram described in SASDL to produce their corresponding SASDL specification of structure chart. The main idea behind the automatic conversion process is to categorize the bubbles in data flow diagram and to determine the positions of the bubbles in structure chart according to their categories and the relative locations in data flow diagram. To make the problem into manageable size, the whole system is broken down into separate parts called activity units. A great deal of manual jobs, such as checking processes leveling, checking data derivation of processes, deriving structure chart from data flow diagram, checking any inconsistency between data flow diagram and structure chart and so forth, can be automated by using SASDL and conversion tool. The specification of structure chart derived by conversion tool may be used in an initial step of design to be refined by SASDL users.

• ETRI Journal
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• 제42권6호
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• pp.899-911
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• 2020

The data in tables are accurate and rich in information, which facilitates the performance of information extraction and question answering (QA) tasks. TableQA, which is based on tables, solves problems by understanding the table structure and searching for answers to questions. In this paper, we introduce both novice and intermediate Korean TableQA tasks that involve deducing the answer to a question from structured tabular data and using it to build a question answering pair. To solve Korean TableQA tasks, we use S3-NET, which has shown a good performance in machine reading comprehension (MRC), and propose a method of converting structured tabular data into a record format suitable for MRC. Our experimental results show that the proposed method outperforms a baseline in both the novice task (exact match (EM) 96.48% and F1 97.06%) and intermediate task (EM 99.30% and F1 99.55%).

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.93-96
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• 1996

Structured laser light is a widely used method for obtaining 3D range information in Machine Vision. However, The structured laser light method is based on assumption that the surface of objects is Lambertian. When the observed surfaces are highly specularly reflective, the laser light can be detected in various parts on the image due to a specular reflection and secondary reflection. This makes wrong range data and the image sensor unusable for the specular objects. To discriminate wrong range data from obtained image data, we have proposed a new algorithm by using the cross section of image block. To show the performance of the proposed method, a series of experiments was, carried out on: the simple geometric shaped objects. The proposed method shows a dramatic improvement of 3D range data better than the typical structured laser light method.

• 국제학술발표논문집
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• The 6th International Conference on Construction Engineering and Project Management
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• pp.276-279
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• 2015

Along with the increase of the quantity of data in various industries, the construction industry has also developed various systems focusing on collecting data related to the construction performance such as productivity and costs achieved in construction job sites. Numerous researchers worldwide have been focusing on developing efficient methodologies to analyze such data. However, applications of such methodologies have shown serious limitations on practical applications due to lack of data and difficulty in finding appropriate analytic methodologies which were capable of implementing significant insights. With development of information technology, the new trend in analytic methodologies has been introduced and steeply developed with the new name of "big data analysis" in various fields in academia and industry. The new concept of big data can be applied for significant analysis on various formats of construction data such as structured, semi-structured, or non-structured formats. This study investigates preliminary application methods based on data collected from actual construction site. This preliminary investigation in this study expects to assess fundamental feasibility of big data analytic applications in construction.

• 한국빅데이터학회지
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• 제6권2호
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• pp.169-179
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• 2021

소비자의 식품소비행동은 소비자 패널 데이터와 같은 정형 데이터 뿐 아니라 매스미디어와 소셜미디어(SNS) 등 비정형 데이터로부터 영향을 받을 가능성이 높아지고 있다. 본 연구에서는 식품소비 관련된 정형 데이터와 비정형 데이터를 연계한 융합데이터 셋에 대하여 딥러닝 기반의 소비예측 모델을 생성하고 이를 검증한다. 연구의 결과는 정형 데이터와 비정형 데이터를 결합할 때 모델 정확도가 향상되었음을 보여주었다. 또한 비정형 데이터가 모델 예측 가능성을 향상시키는 것으로 나타났다. 변수들의 중요도를 식별하기 위해 SHAP 기법을 사용한 결과 블로그 및 비디오 데이터 관련 변수가 상위 목록에 있었고, 파프리카 구매 금액과 양의 상관관계가 있음을 알 수 있었다. 또한 실험 결과에 따르면 머신러닝 모델이 딥러닝 모델보다 높은 정확도를 보였고, 기존의 시계열 분석 모델링에 대한 효율적인 대안이 될 수 있음을 확인하였다.

• Current Optics and Photonics
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• 제2권6호
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• pp.554-562
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• 2018

This study presents a color 3D scanner based on the laser structured-light imaging method that can simultaneously acquire 3D shape data and color of a target object using a single camera. The 3D data acquisition of the scanner is based on the structured-light imaging method, and the color data is obtained from a natural color image. Because both the laser image and the color image are acquired by the same camera, it is efficient to obtain the 3D data and the color data of a pixel by avoiding the complicated correspondence algorithm. In addition to the 3D data, the color data is helpful for enhancing the realism of an object model. The proposed scanner consists of two line lasers, a color camera, and a rotation table. The line lasers are deployed at either side of the camera to eliminate shadow areas of a target object. This study addresses the calibration methods for the parameters of the camera, the plane equations covered by the line lasers, and the center of the rotation table. Experimental results demonstrate the performance in terms of accurate color and 3D data acquisition in this study.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2006년도 추계학술대회 논문집
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• pp.153-154
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• 2006