• Korean Journal of Computational Design and Engineering
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• v.8 no.1
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• pp.48-54
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• 2003

In a design-to-manufacturing environment, the product data is shared by various CAD/CAM/CAE systems with little integration or substantial data redundancy. The main purpose of this paper is to build a database containing all the features required for STEP-NC machining and to show how a STEP-NC repository can support the complete process for machining. A STEP-NC database schema has been constructed and several query functions have been built for the purpose of implementing the retrieving system of a STEP-NC database. The EXPRESS data model of ISO 14649 has been mapped to the database data definition language of the Oracle database. To apply the STEP-NC database to an industry example, the ISO 14649 part program has been stored into the STEP-NC database. To implement example scenarios, the sample query interface has been built.

• Korean Journal of Computational Design and Engineering
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• v.7 no.3
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• pp.202-209
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• 2002

It is difficult to support collaborative design with a conventional ship CAD system which manages design information using files. In this research, file storage has been replaced with a database. This paper describes the OpenDIS which is an interface between the geometric kernel and the database. Its main purpose is to implement the CAD system which has the STEP database as the native storage. A prototype CAD system has been implemented using that OpenDIS interface which is implemented by OpenCascade geometric kernel and the Objectstore object-oriented database. The STEP methodology is used as the database schema. This CAD system has been applied to the hull design of a ship in order to verify the usefulness of the interface.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.5
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• pp.523-532
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• 2019

Microservice architecture focuses on dividing it into small and lightweight services to build for the purpose of performing very close business functions. So it tends to concentrate only on agility, productivity, reliability, and ease of deployment of software development. Microservice architecture considers database as just a file or storage for storing and extracting data, emphasizing that data quality can be sacrificed for convenience and scalability of software development. Database reverse engineering for understanding database structure and data semantics is needed for data utilization for business decision making. However, it is difficult that reverse database engineering is applied in microservice architecture that neglects data quality. This study proposes database reverse engineering method that utilizes master data to restore the conceptual data model as a solution. The proposed method is applied to the return service database implemented by microservice architecture and verified its applicability.

• Journal of International Society for Simulation Surgery
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• v.2 no.2
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• pp.64-66
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• 2015

Purpose : In this paper we proposed cascade feature filter and projection method for rapid human face recognition for the large-scale high-dimensional face database. Materials and Methods : The relevant features are selected from the large feature set using Fast Correlation-Based Filter method. After feature selection, project them into discriminant using Principal Component Analysis or Linear Discriminant Analysis. Their cascade method reduces the time-complexity without significant degradation of the performance. Results : In our experiments, the ORL database and the extended Yale face database b were used for evaluation. On the ORL database, the processing time was approximately 30-times faster than typical approach with recognition rate 94.22% and on the extended Yale face database b, the processing time was approximately 300-times faster than typical approach with recognition rate 98.74 %. Conclusion : The recognition rate and time-complexity of the proposed method is suitable for real-time face recognition system on the large-scale high-dimensional face database.

• Journal of information and communication convergence engineering
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• v.21 no.3
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• pp.244-251
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• 2023

Engineering or humanities data are stored in databases and are often used for search services. While the latest deep-learning technologies, such like BART and BERT, are utilized for data analysis, humanities data still rely on traditional databases. Representative analysis methods include n-gram and lexical statistical extraction. However, when using a database, performance limitation is often imposed on the result calculations. This study presents an experimental process using MariaDB on a PC, which is easily accessible in a laboratory, to analyze the impact of the database on data analysis performance. The findings highlight the fact that the database becomes a bottleneck when analyzing large-scale text data, particularly over hundreds of thousands of records. To address this issue, a method was proposed to provide real-time humanities data analysis web services by leveraging the open source database, with a focus on the Seungjeongwon-Ilgy, one of the largest datasets in the humanities fields.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.1
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• pp.30-36
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• 2001

We present a new algorithm for mining association rules in the large database. Association rules are the relationships of items in the same transaction. These rules provide useful information for marketing. Since Apriori algorithm was introduced in 1994, many researchers have worked to improve Apriori algorithm. However, the drawback of Apriori-based algorithm is that it scans the transaction database repeatedly. The algorithm which we propose scans the database twice. The first scanning of the database collects frequent length l-itemsets. And then, the algorithm scans the database one more time to construct the data structure Common-Item Tree which stores the information about frequent itemsets. To find all frequent itemsets, the algorithm scans Common-Item Tree instead of the database. As scanning Common-Item Tree takes less time than scanning the database, the algorithm proposed is more efficient than Apriori-based algorithm.

• Journal of Biosystems Engineering
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• v.28 no.1
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• pp.59-64
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• 2003

This study was carried out to develop database system using internet fur greenhouse. The database system consisted of group monitor, client monitor. server monitor and DBMS. The results of the study are summarized as follows. 1. The monitoring module, as data collection system for database. could monitor the state of the control device and the greenhouse environment. 2 The group monitor was connected to the house monitors by RS-485 communication method. Data received by the group monitor were sent to the server monitor and then stored in database server by TCP/IP and MIDAS. 3. The data of database consisted of on growing environment. control devices, operation and cultivation data in greenhouse. It was developed using MS-SQL server. 4. Remote monitoring of greenhouse was realized in a client/server environment. The client module. which was named as the client monitor. made requests to access the measurement data of greenhouse through the remote data module of the server monitor in internet environment.

• Computers and Concrete
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• v.28 no.5
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• pp.441-450
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• 2021

This study presents the first analysis system and fast-access cloud database for shrinkage and creep of concrete in the world, named "shrinkage and creep database in Taiwan", SCDT. SCDT not only has the most comprehensive experimental data, including NU, JSCE, Europe, and TW databases, but provides a design tool for researchers and engineers. It can further facilitate the development of prediction models for localized concrete. Users can obtain the shrinkage and creep curves based on their selected prediction models in SCDT. Comparisons of the predicted results of selected models and test results in the chosen database can be generated in seconds. One example of the development of basic creep prediction model in Taiwan based on model B4 by using SCDT to reflect concrete characteristics in Taiwan is also presented in this study. Users anywhere in the world can easily access SCDT to browse and upload data, receive predictive results, or develop predictive models.

• Journal of Information Processing Systems
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• v.8 no.1
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• pp.85-100
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• 2012

The Hartley transform based feature extraction method is proposed for fingerprint matching. Hartley transform is applied on a smaller region that has been cropped around the core point. The performance of this proposed method is evaluated based on the standard database of Bologna University and the database of the FVC2002. We used the city block distance to compute the similarity between the test fingerprint and database fingerprint image. The results obtained are compared with the discrete wavelet transform (DWT) based method. The experimental results show that, the proposed method reduces the false acceptance rate (FAR) from 21.48% to 16.74 % based on the database of Bologna University and from 31.29% to 28.69% based on the FVC2002 database.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 1998.06a
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• pp.539-542
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• 1998

In this paper, we devised pulse rate diagnosis database system for provide basic index of Cold-Hot diagnosis. The system consist of database part and pulse rate detection part that for detection pulse wave, respiration and ECG. The database is constructed windows95 platform using DAO(Data Access Object). Search algorithm used ISAM algorithm. The database consist of patient information and medical report for a subject and detected biological signals.