• Journal of information and communication convergence engineering
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• v.20 no.4
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• pp.265-272
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• 2022

The most effective method to improve information system capabilities is to enable instant access to several relational database sources and transform data with a logical structure into multiple target relational databases. There are numerous data transformation tools available; however, they typically contain fixed procedures that cannot be changed by the user, making it impossible to fulfill the near-real-time data transformation requirements. Furthermore, some tools cannot build object references or alter attribute constraints. There are various situations in which tool changes in data type cause conflicts and difficulties with data quality while transforming between the two systems. The R-programming language was extensively used throughout this study, and several different relational database structures were utilized to complete the proposed study. Experiments showed that the developed study can improve the performance of information systems by interacting with and exchanging data with various relational databases. The study addresses data quality issues, particularly the completeness and integrity dimensions of the data transformation processes.

• 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 Internet Computing and Services
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• v.3 no.5
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• pp.19-29
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• 2002

With the progress of information-oriented society, many device with advanced technologies invented by many companies. However, the current firmware technologies have many problems to meet such high level of new Technologies, Recently it become necessary new manufactures of information-oriented society to require such embedded operating system as their system-level platform. Embedded linux, which could be on alternative proposal of existing high-cost embedded operating system, become available commercially by many companies Linux has many programs, But, embedded databases require very high cost. In this paper, we suggest ERT DE which has a small size and is suitable for embedded real-time technologies.

• Proceedings of the Korea Information Processing Society Conference
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• 2017.11a
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• pp.395-398
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• 2017

We propose a web crawler system with keyword extraction function in this paper. Researches on the keyword extraction in existing text mining are mostly based on databases which have already been grabbed by documents or corpora, but the purpose of this paper is to establish a real-time keyword extraction system which can extract the keywords of the corresponding text and store them into the database together while grasping the text of the web page. In this paper, we design and implement a crawler combining RAKE keyword extraction algorithm. It can extract keywords from the corresponding content while grasping the content of web page. As a result, the performance of the RAKE algorithm is improved by increasing the weight of the important features (such as the noun appearing in the title). The experimental results show that this method is superior to the existing method and it can extract keywords satisfactorily.

• Genomics & Informatics
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• v.4 no.3
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• pp.118-124
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• 2006

For the direct understanding of flow, pathway data are usually represented as directed graphs in biological journals and texts. Databases of metabolic pathways or signal transduction pathways inevitably contain these kinds of graphs to show the flow. KEGG, one of the representative pathway databases, uses the manually drawn figure which can not be easily maintained. Graph layout algorithms are applied for visualizing metabolic pathways in some databases, such as EcoCyc. Although these can express any changes of data in the real time, it exponentially increases the edge crossings according to the increase of nodes. For the understanding of genome scale flow of metabolism, it is very important to reduce the unnecessary edge crossings which exist in the automatic graph layout. We propose a metabolic pathway drawing algorithm for reducing the number of edge crossings by considering the fact that metabolic pathway graph is scale-free network. The experimental results show that the number of edge crossings is reduced about $37{\sim}40%$ by the consideration of scale-free network in contrast with non-considering scale-free network. And also we found that the increase of nodes do not always mean that there is an increase of edge crossings.

• Convergence Security Journal
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• v.4 no.3
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• pp.57-82
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• 2004

The confluence of computers, communications, and databases is quickly creating a distributed database where many applications require real-time access to temporally consistent sensor data. We have developed an object-oriented real-time database system called BeeHive to provide a significant improvement in performance and functionality over conventional non-real-time database and object management systems. In this paper, the performance of two data-deadline cognizant scheduling policies EDDF and EDF-DC and the baseline EDF policy with/without admission control are evaluated through extensive experiments on BeeHive. The ranges where data-deadline cognizant scheduling policies are effective and where admission control plays a role are identified.

• The Journal of the Acoustical Society of Korea
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• v.25 no.1E
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• pp.20-24
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• 2006

In this paper, we focused on the real time implementation of a speech recognition system with medium size of vocabulary considering its application to a mobile phone. First, we developed the PC based variable vocabulary word recognizer having the size of program memory and total acoustic models as small as possible. To reduce the memory size of acoustic models, linear discriminant analysis and phonetic tied mixture were applied in the feature selection process and training HMMs, respectively. In addition, state based Gaussian selection method with the real time cepstral normalization was used for reduction of computational load and robust recognition. Then, we verified the real-time operation of the implemented recognition system on the TMS320C6201 EVM board. The implemented recognition system uses memory size of about 610 kbytes including both program memory and data memory. The recognition rate was 95.86% for ETRI 445DB, and 96.4%, 97.92%, 87.04% for three kinds of name databases collected through the mobile phones.

• Journal of Broadcast Engineering
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• v.25 no.1
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• pp.105-108
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• 2020

This paper presents a real-time low-resolution face recognition method that uses a super-resolution technique. Conventional face recognition methods are limited by low accuracy resulting from the distance between the camera and objects. Although super-resolution methods have been developed to resolve this issue, they are not suitable for integrated face recognition systems. The proposed method recognizes faces with low resolution using key frame selection, super resolution, face detection, and recognition on real-time processing. Experiments involving several databases indicated that the proposed algorithm is superior to conventional methods in terms of face recognition accuracy.

• Journal of Korea Multimedia Society
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• v.22 no.3
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• pp.366-373
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• 2019

The development of monitoring and analysis systems to increase productivity while saving energy is needed as a method to reduce huge amount of energy consumed in the process of producing large forged products. In this paper, we propose a system to monitor and analyze energy usage in real-time collected from gas-meter, wattmeter, and thermometer based on IoT installed in forging factories. The system consists of a data collection server for collecting and processing data from IoT- based platform and existing SCADA equipment and ERP/MES system in forging factories, and an application server for providing services to users. To develop the system, the overall system structure is logically diagrammed, and the databases configuration and implementation modules to efficiently store and manage data are presented. In the future, the system will be utilized to reduce energy consumption by analyzing energy usage pattern and optimizing process works with real-time energy usage and production process data for each facility.

• Journal of Korea Spatial Information System Society
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• v.5 no.2 s.10
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• pp.5-21
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• 2003

Sptaio-temporal databases are important to store the real-time location information of large spatio-temporal objects efficiently and retrieve them rapidly. Accordingly necessity for spatio-temporal database system that can manage spatial information, aspatial information and temporal information of spatio-temporal objects is increasing. Sptaio-temporal databases are important to store the real-time location information of large spatio-temporal objects efficiently and retrieve them rapidly. Accordingly necessity for spatio-temporal database system that can manage spatial information, aspatial information and temporal information of spatio-temporal objects is increasing. Therefore, in this paper, we propose a spatio-temporal data model that is able to efficiently manage historical spatio-temporal objects that change dynamically their states as time. Also, various spatio-temporal operations and constraint conditions are defined to keep integrity of spatio-temporal data and spatio-temporal operations.