• Title/Summary/Keyword: integrated data model

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Education of Collaborative Product Data Management by Using Social Media in a Product Data Management System (소셜미디어와 PDM 시스템을 활용한 협업적 제품자료관리 교육)

  • Do, Namchul
    • Korean Journal of Computational Design and Engineering
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    • v.20 no.3
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    • pp.254-262
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    • 2015
  • This study proposes an approach to Product Data Management (PDM) education for collaborative product data management, which can support collaborative product development process. This approach introduces social media and a PDM system into a framework for PDM education supported by consistent product development process and product data model. It has been applied to two PDM classes and the result shows that the social media in PDM education can support not only experiences of the collaborative product data management but also interactive and informal communications among instructors and participants using integrated social media with product data during courses.

Two-Stage forecasting Using Change-Point Detection and Artificial Neural Networks for Stock Price Index

  • Oh, Kyong-Joo;Kim, Kyoung-Jae;Ingoo Han
    • Proceedings of the Korea Inteligent Information System Society Conference
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    • 2000.11a
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    • pp.427-436
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    • 2000
  • The prediction of stock price index is a very difficult problem because of the complexity of the stock market data it data. It has been studied by a number of researchers since they strong1y affect other economic and financial parameters. The movement of stock price index has a series of change points due to the strategies of institutional investors. This study presents a two-stage forecasting model of stock price index using change-point detection and artificial neural networks. The basic concept of this proposed model is to obtain Intervals divided by change points, to identify them as change-point groups, and to use them in stock price index forecasting. First, the proposed model tries to detect successive change points in stock price index. Then, the model forecasts the change-point group with the backpropagation neural network (BPN). Fina1ly, the model forecasts the output with BPN. This study then examines the predictability of the integrated neural network model for stock price index forecasting using change-point detection.

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Validation of the correlation-based aerosol model in the ISFRA sodium-cooled fast reactor safety analysis code

  • Yoon, Churl;Kim, Sung Il;Lee, Sung Jin;Kang, Seok Hun;Paik, Chan Y.
    • Nuclear Engineering and Technology
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    • v.53 no.12
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    • pp.3966-3978
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    • 2021
  • ISFRA (Integrated SFR Analysis Program for PSA) computer program has been developed for simulating the response of the PGSFR pool design with metal fuel during a severe accident. This paper describes validation of the ISFRA aerosol model against the Aerosol Behavior Code Validation and Evaluation (ABCOVE) experiments undertaken in 1980s for radionuclide transport within a SFR containment. ABCOVE AB5, AB6, and AB7 tests are simulated using the ISFRA aerosol model and the results are compared against the measured data as well as with the simulation results of the MELCOR severe accident code. It is revealed that the ISFRA prediction of single-component aerosols inside a vessel (AB5) is in good agreement with the experimental data as well as with the results of the aerosol model in MELCOR. Moreover, the ISFRA aerosol model can predict the "washout" phenomenon due to the interaction between two aerosol species (AB6) and two-component aerosols without strong mutual interference (AB7). Based on the theory review of the aerosol correlation technique, it is concluded that the ISFRA aerosol model can provide fast, stable calculations with reasonable accuracy for most of the cases unless the aerosol size distribution is strongly deformed from log-normal distribution.

Conceptualizing 5G's of Green Marketing for Retail Consumers and Validating the Measurement Model Through a Pilot Study

  • ANSARI, Hafiz Waqas Ahmed;FAUZI, Waida Irani Mohd;SALIMON, Maruf Gbadebo
    • Journal of Distribution Science
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    • v.20 no.4
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    • pp.33-50
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    • 2022
  • Purpose: This pilot study aims to conceptualize a new green marketing mix for retail consumers based on Stimulus-Organism-Response (SOR) model. Moreover, it also aims to conceptualize a testable research model of new green marketing mix with consumers' green purchasing behavior, and to validate the measurement model with traditional as well as modern suggested validating techniques. Research design, data and methodology: A pilot test data from 75 respondents of retail buyers of energy-efficient electric appliances in Pakistan were tested for the confirmatory factor analysis (CFA) by examining a measurement model of the construct through different validation techniques (like Composite Reliability, McDonald's Omega (ω), rho (ρA), HTMT, etc.) as heretofore these scales were not validated through these modern methods. Results: The results revealed that the instrument has a certain degree of reliability and validity through different validating techniques. All the measurement items reach the suggested threshold values. Conclusions: Therefore, this study conceptualized an integrated framework of all the three stakeholders of the environment (government, companies, and public or consumers) to achieve environmental sustainability. Hence, future studies can extend these findings and conduct a full-scale study to establish an empirical relationship between the 5G's of green marketing for retailing businesses and consumers' green purchase behavior.

A Study on Development of 3D Data Model for Underground Facilities Using CityGML ADE (CityGML ADE를 이용한 3차원 지하시설물 데이터 모델 개발에 관한 연구)

  • Jeong, Da Woon;Shin, Dong Bin
    • Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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    • v.39 no.4
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    • pp.245-252
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    • 2021
  • Underground facilities were constructed as needed by various management organizations, the result of which was the disordered and scattered underground spaces. This phenomenon can be viewed as the main cause of safety accidents in the underground space. To solve this problem, research on systematic construction and management of underground facilities should be conducted. Therefore, to improve the accuracy and the quality of information and to facilitate the systematic construction and management of underground facility information, this study aims to establish a 3D data model that conforms to international spatial information standards for pipeline underground facilities and to implement the data model to enable visualization. The result of this study can be used to improve the consistency of information not only between underground facilities, but also the correspondence between above ground and underground facilities. As such, this study has academic significance in that it presents an integrated data model that includes various objects in the ground and underground spaces and enables interoperability between diverse domain data.

A study on market-production model building for small bar steels (소봉제품의 시장생산 모형 구축에 관한 연구)

  • 김수홍;유정빈
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 1996.10a
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    • pp.139-145
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    • 1996
  • A forecast on the past output data sets of small bar steels is very important information to make a decision on the future production quantities. In many cases, however, it has been mainly determined by experience (or rule of thumb). In this paper, past basic data sets of each small bar steels are statistically analyzed by some graphical and statistical forecasting methods. This work is mainly done by SAS. Among various quantitative forecasting methods in SAS, STEPAR forecasting method was best performed to the above data sets. By the method, the future production quantities of each small bar steels are forecasted. As a result of this statistical analysis, 95% confidence intervals for future forecast quantities are very wide. To improve this problem, a suitable systematic database system, integrated management system of demand-production-inventory and integrated computer system should be required.

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Attribute-Based Data Sharing with Flexible and Direct Revocation in Cloud Computing

  • Zhang, Yinghui;Chen, Xiaofeng;Li, Jin;Li, Hui;Li, Fenghua
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.11
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    • pp.4028-4049
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    • 2014
  • Attribute-based encryption (ABE) is a promising cryptographic primitive for implementing fine-grained data sharing in cloud computing. However, before ABE can be widely deployed in practical cloud storage systems, a challenging issue with regard to attributes and user revocation has to be addressed. To our knowledge, most of the existing ABE schemes fail to support flexible and direct revocation owing to the burdensome update of attribute secret keys and all the ciphertexts. Aiming at tackling the challenge above, we formalize the notion of ciphertext-policy ABE supporting flexible and direct revocation (FDR-CP-ABE), and present a concrete construction. The proposed scheme supports direct attribute and user revocation. To achieve this goal, we introduce an auxiliary function to determine the ciphertexts involved in revocation events, and then only update these involved ciphertexts by adopting the technique of broadcast encryption. Furthermore, our construction is proven secure in the standard model. Theoretical analysis and experimental results indicate that FDR-CP-ABE outperforms the previous revocation-related methods.

Big Data Governance Model for Effective Operation in Cyberspace (효과적인 사이버공간 작전수행을 위한 빅데이터 거버넌스 모델)

  • Jang, Won-gu;Lee, Kyung-ho
    • The Journal of Bigdata
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    • v.4 no.1
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    • pp.39-51
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    • 2019
  • With the advent of the fourth industrial revolution characterized by hyperconnectivity and superintelligence and the emerging cyber physical systems, enormous volumes of data are being generated in the cyberspace every day ranging from the records about human life and activities to the communication records of computers, information and communication devices, and the Internet of things. Big data represented by 3Vs (volume, velocity, and variety) are actively used in the defence field as well. This paper proposes a big data governance model to support effective military operations in the cyberspace. Cyberspace operation missions and big data types that can be collected in the cyberspace are classified and integrated with big data governance issues to build a big data governance framework model. Then the effectiveness of the constructed model is verified through examples. The result of this study will be able to assist big data utilization planning in the defence sector.

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Optimization of the Vertical Localization Scale for GPS-RO Data Assimilation within KIAPS-LETKF System (KIAPS 앙상블 자료동화 시스템을 이용한 GPS 차폐자료 연직 국지화 규모 최적화)

  • Jo, Youngsoon;Kang, Ji-Sun;Kwon, Hataek
    • Atmosphere
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    • v.25 no.3
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    • pp.529-541
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    • 2015
  • Korea Institute of Atmospheric Prediction System (KIAPS) has been developing a global numerial prediction model and data assimilation system. We has implemented LETKF (Local Ensemble Transform Kalman Filter, Hunt et al., 2007) data assimilation system to NCAR CAM-SE (National Center for Atmospheric Research Community Atmosphere Model with Spectral Element dynamical core, Dennis et al., 2012) that has cubed-sphere grid, known as the same grid system of KIAPS Integrated Model (KIM) now developing. In this study, we have assimilated Global Positioning System Radio Occultation (GPS-RO) bending angle measurements in addition to conventional data within ensemble-based data assimilation system. Before assimilating bending angle data, we performed a vertical unit conversion. The information of vertical localization for GPS-RO data is given by the unit of meter, but the vertical localization method in the LETKF system is based on pressure unit. Therefore, with a clever conversion of the vertical information, we have conducted experiments to search for the best vertical localization scale on GPS-RO data under the Observing System Simulation Experiments (OSSEs). As a result, we found the optimal setting of vertical localization for the GPS-RO bending angle data assimilation. We plan to apply the selected localization strategy to the LETKF system implemented to KIM which is expected to give better analysis of GPS-RO data assimilation due to much higher model top.

A Study on Development of Integrated OPAC Based on Hypermedia Techniques (하이퍼미디어 기술에 기반한 통합 OPAC구현에 관한 연구)

  • Ahn, Tae Kyoung;Kim, Hyun Hee
    • Journal of Information Management
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    • v.27 no.1
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    • pp.1-39
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    • 1996
  • The purpose of this paper is to design a model of integrated OPAC called as EconRef. This model not only provides users of libraries with systematic, rapid information service, but also supports librarians to do their tasks effectively. The designed model is constructed based on two operating systems such as REGIS system and The Book House and is developed by using KPWin++ is an expert system shell which combines hypertext and expert system functions. The designed system consists of six modules ; three reference expert systems for document sources, experts and statistical sources; OPAC ; external database ; user's guide. For the evaluation of the designed system, performance of EconRef system is compared with that of the naive and expert reference librarians. And also the features of the system are compared with those of REGIS systems. The tests comparing BconRef system searching with librarians searching have shown that EconRef system is at least as good as searching with expert librarians and much superior to searching with naive librarians.

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