• Journal of the Korea Safety Management & Science
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• v.12 no.2
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• pp.161-166
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• 2010

EPC Information Services (EPCIS) is an EPCglobal standard designed to enable EPC-related data sharing within and across supply chain. The EPCIS standard defines standard interfaces to enable EPC-related data to be captured and subsequently to be queried using a set of service operations and an associated data model. There are two kinds of EPCIS data: event data and master data. Event data is created in the process of carrying out business processes. Traceability of goods across supply chain is based on event data. Therefore, each company must have an event data. This study compared he difference between MS-SQL(DRDBMS) and ALTIBASE(MMDBMS) for data storage. We compared the difference between two database management in many respects such as insert time and select time. We come to a conclusion that ALTIBASE is more efficient than MS-SQL.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.559-563
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• 2015

Identification of energy use patterns in buildings has a great opportunity for energy saving. To find what energy use patterns exist, clustering analysis has been commonly used such as K-means and hierarchical clustering method. In case of high dimensional data such as energy use time-series, data reduction should be considered to avoid the curse of dimensionality. Principle Component Analysis, Autocorrelation Function, Discrete Fourier Transform and Discrete Wavelet Transform have been widely used to map the original data into the lower dimensional spaces. However, there still remains an ongoing issue since the performance of clustering analysis is dependent on data type, purpose and application. Therefore, we need to understand which data reduction techniques are suitable for energy use management. This research aims find the best clustering method using energy use data obtained from Seoul National University campus. The results of this research show that most experiments with data reduction techniques have a better performance. Also, the results obtained helps facility managers optimally control energy systems such as HVAC to reduce energy use in buildings.

• Journal of the Society of Naval Architects of Korea
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• v.43 no.6 s.150
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• pp.700-706
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• 2006

As development of information technology, companies stress the need of knowledge management. Companies construct ERP system including knowledge management. But, it is not easy to formalize knowledge in organization. They experience that constructing information system help knowledge management. Now, we focus on engineering knowledge. Because engineering data contains experts' experience and know-how in its own, engineering knowledge is a treasure house of knowledge. Korean shipyards are leader of world shipbuilding industry. They have accumulated a store of knowledge and data. But, they don't have data mining tool to utilize accumulated data. This paper treats development of data mining tools for the utilization of shipbuilding knowledge based on genetic programming(GP).

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1260-1263
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• 2005

Data storage related with writing and retrieving requires high storage capacity, fast transfer rate and less access time. Today any data storage system cannot satisfy these conditions, however holographic data storage system can perform faster data transfer rate because it is a page oriented memory system using volume hologram in writing and retrieving data. System can be constructed without mechanical actuating part therefore fast data transfer rate and high storage capacity about 1Tb/cm3 can be realized. In this research, to reduce errors of binary data stored in holographic data storage system, a new method for bit error reduction is suggested. First, find fuzzy rule using experimental system for Element of Holographic Digital Data System. Second, make fuzzy rule table using Genetic algorithm. Third, reduce prior error element and recording Digital Data. Recording ratio and reconstruction ratio will be very good performance

• 정보저장시스템학회:학술대회논문집
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• 2005.10a
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• pp.129-133
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• 2005

Data storage related with writing and retrieving requires high storage capacity, fast transfer rate and less access time. Today any data storage system cannot satisfy these conditions, however holographic data storage system can perform faster data transfer rate because it is a page oriented memory system using volume hologram in writing and retrieving data. System can be constructed without mechanical actuating part therefore fast data transfer rate and high storage capacity about $1Tb/cm^3$ can be realized. In this paper, to reduce errors of binary data stored in holographic data storage system, a new method for bit error reduction is suggested. First, find cluster centers using subtractive clustering algorithm then reduce intensities of pixels around cluster centers and fuzzy rules. Therefore, By using this error reduction method following results are obtained ; the effect of Inter Pixel Interference noise is decreased and the intensity profile of data page becomes uniform therefore the better data storage system can be constructed.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.6 no.3
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• pp.210-216
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• 2006

In the rule based modeling, data partitioning plays crucial role be cause partitioned sub data set implies particular information of the given data set or system. In this paper, we present an empirical study result of the data pattern estimation to find underlying data patterns of the given data. Presented method performs crisp type clustering with given n number of data samples by means of the sequential agglomerative hierarchical nested model (SAHN). In each sequence, the average value of the sum of all inter-distance between centroid and data point. In the sequel, compute the derivation of the weighted average distance to observe a pattern distribution. For the final step, after overall clustering process is completed, weighted average distance value is applied to estimate range of the number of clusters in given dataset. The proposed estimation method and its result are considered with the use of FCM demo data set in MATLAB fuzzy logic toolbox and Box and Jenkins's gas furnace data.

• 시스템엔지니어링워크숍
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• s.4
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• pp.135-140
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• 2004

Defense analysis & evaluation includes menace analysis, validation analysis, problem analysis, scientific technical analysis, technical trad-off analysis, alternative analysis, cost analysis, etc. Reliable related data is required to perform these analysis activities efficiently. but in case of these defense analysis & evaluation data acquisition system, the data is insufficient and scattered about each organization. the data of database system is also not utilized sufficiently. abroad technical data is also low level data such as catalog or military officer's collection. therefore, this paper propose defense analysis & evaluation data acquisition system by systems engineering process. we also propose construction method of data acquisition system.

• Proceedings of the KIEE Conference
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• 2006.07d
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• pp.2142-2143
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• 2006

Today any data storage system cannot satisfy all of these conditions, however holographic data storage system can perform faster data transfer rate because it is a page oriented memory system using volume hologram in writing and retrieving data. System can be constructed without mechanically actuating part therefore fast data transfer rate and high storage capacity about 1Tb/cm3 can be realized. In this research, to reduce errors of binary data stored in holographic data storage system, a new method for bit error reduction is suggested. Firstly, find fuzzy rule to use test bed system for Element of Holographic Digital Data System. Secondly, make fuzzy rule table using DNA coding method. Finally, reduce prior error element and recording digital data. Recording ratio and reconstruction ratio show good performance.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.124-125
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• 2023

Defect detection during liquid crystal display (LCD) manufacturing has always been a critical challenge. This study aims to address this issue by proposing a data augmentation method based on generative adversarial networks (GAN) to improve defect identification accuracy in LCD production. By leveraging synthetically generated image data from GAN, we effectively augment the original dataset to make it more representative and diverse. This data augmentation strategy enhances the model's generalization capability and robustness on real-world data. Compared to traditional data augmentation techniques, the synthetic data from GAN are more realistic, diverse and broadly distributed. Experimental results demonstrate that training models with GAN-generated data combined with the original dataset significantly improves the detection accuracy of critical defects in LCD manufacturing, compared to using the original dataset alone. This study provides an effective data augmentation approach for intelligent quality control in LCD production.

• Proceedings of the Korea Contents Association Conference
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• 2016.05a
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• pp.23-24
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• 2016

본 논문에서는 과학 데이터 특성을 고려한 아카이브 시스템 설계를 위한 Data Curation Profile을 분석한다. Data Curation Profile은 생명과학데이터, 천문우주 데이터, 지질 데이터화학데이터, 사회과학데이터 등과 같은 13개의 과학데이터로 이루어져 있다. 13개의 과학데이터의 분석된 내용을 바탕으로 아카이브 시스템 설계시 고려해야 할 과학데이터 특성을 도출하고 이를 아카이브 요소 기술과 연계한다.