• Journal of Korea Society of Industrial Information Systems
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• v.2 no.2
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• pp.189-207
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• 1997

Recently, we have witnessed a host of emerging tools in the management support systems (MSS) area including the data warehouse/multidimensinal databases (MDDB), data mining, on-line analytical processing (OLAP), intelligent agents, World Wide Web(WWW) technologies, the Internet, and corporate intranets. These tools are reshaping MSS developments in organizations. This article reviews a set of emerging data management technologies in the knowledge discovery in databases(KDD) process and analyzes their implications for decision support. Furthermore, today's MSS are equipped with a plethora of AI techniques (artifical neural networks, and genetic algorithms, etc) fuzzy sets, modeling by example , geographical information system(GIS), logic modeling, and visual interactive modeling (VIM) , All these developments suggest that we are shifting the corporate decision making paradigm form information-driven decision making in the1980s to knowledge-driven decision making in the 1990s.

• Journal of Internet Computing and Services
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• v.19 no.1
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• pp.123-130
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• 2018

With the emergence of a new paradigm called Open Science and Big Data, the need for data sharing and collaboration is also emerging in the computational science field. This paper, we analyzed data-driven research cases for computational science by field; material design, bioinformatics, high energy physics. We also studied the characteristics of the computational science data and the data management issues. To manage computational science data effectively it is required to have data quality management, increased data reliability, flexibility to support a variety of data types, and tools for analysis and linkage to the computing infrastructure. In addition, we analyzed trends of platform technology for efficient sharing and management of computational science data. The main contribution of this paper is to review the various computational science data repositories and related platform technologies to analyze the characteristics of computational science data and the problems of data management, and to present design considerations for building a future computational science data platform.

• Asia Pacific Journal of Corpus Research
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• v.2 no.2
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• pp.43-48
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• 2021

The aim of this study is to analyze the trends of corpus driven research in Korean education. For this purpose, a total of 14 papers was searched online with the keywords including Korean corpus and Korean education. The data was categorized into three: vocabulary education, grammar education and corpus data construction methods. The analysis results suggest that the number of corpus studies in the field of Korean education is not large enough but continues to increase, especially in the research on data construction tools. This suggests there is a significant demand in corpus driven studies in Korean education field.

• Nuclear Engineering and Technology
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• v.52 no.12
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• pp.2687-2698
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• 2020

Most of the machine learning-based intrusion detection tools developed for Industrial Control Systems (ICS) are trained on network packet captures, and they rely on monitoring network layer traffic alone for intrusion detection. This approach produces weak intrusion detection systems, as ICS cyber-attacks have a real and significant impact on the process variables. A limited number of researchers consider integrating process measurements. However, in complex systems, process variable changes could result from different combinations of abnormal occurrences. This paper examines recent advances in intrusion detection algorithms, their limitations, challenges and the status of their application in critical infrastructures. We also introduce the discussion on the similarities and conflicts observed in the development of machine learning tools and techniques for fault diagnosis and cybersecurity in the protection of complex systems and the need to establish a clear difference between them. As a case study, we discuss special characteristics in nuclear power control systems and the factors that constraint the direct integration of security algorithms. Moreover, we discuss data reliability issues and present references and direct URL to recent open-source data repositories to aid researchers in developing data-driven ICS intrusion detection systems.

• Journal of Information Technology Services
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• v.8 no.1
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• pp.1-9
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• 2009

It is essential for companies to manage massive data for dealing with large volume of transactions and customers' needs. To this end, the companies have operated data warehouse with many complex tools for data gathering and reporting to the end-users. However, the data from the heterogeneous tools at the various sources cannot be exchanged because of the different interfaces. Therefore, the data cannot be controlled with integrated manner, and furthermore the companies do not focus the quality of data resulting in the data quality problem. Thus, this study suggests how to manage massive data with a metadata. In particular, we investigate current status of metadata management, its appliance, and perspectives. The contribution of this research is to apply the metadata management system to the real world and to suggest its management procedure.

• Molecules and Cells
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• v.44 no.11
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• pp.843-850
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• 2021

The rapid increase in collateral omics and phenotypic data has enabled data-driven studies for the fast discovery of cancer targets and biomarkers. Thus, it is necessary to develop convenient tools for general oncologists and cancer scientists to carry out customized data mining without computational expertise. For this purpose, we developed innovative software that enables user-driven analyses assisted by knowledge-based smart systems. Publicly available data on mutations, gene expression, patient survival, immune score, drug screening and RNAi screening were integrated from the TCGA, GDSC, CCLE, NCI, and DepMap databases. The optimal selection of samples and other filtering options were guided by the smart function of the software for data mining and visualization on Kaplan-Meier plots, box plots and scatter plots of publication quality. We implemented unique algorithms for both data mining and visualization, thus simplifying and accelerating user-driven discovery activities on large multiomics datasets. The present Q-omics software program (v0.95) is available at http://qomics.sookmyung.ac.kr.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.49 no.4
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• pp.15-25
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• 2012

The research on the FPGA CAD tools in academia has been lacking practicality due to the underlying FPGA fabric architecture which is too simple and inefficient to be applied for commercial FPGAs. Recently, the database of placement positions and routing graphs on commercial FPGA architectures has been built, and provided for enabling the academic development of placement and routing tools. To extend the limit of academic CAD tools even further, we have developed the evaluation toolkit for the K-FPGA architecture which is under development. By providing interface for exchanging data with a commercial FPGA toolkit at every step of mapping, packing, placement and routing in the tool chain, the toolkit enables individual tools to be developed without waiting for the results of the preceding step, and with no dependency on the quality of the results, and compared in detail with commercial tools at any step. Also, the fabric primitive library is developed by extracting the prototype from a reporting file of a commercial FPGA, restructuring it, and modeling the behavior of basic gates. This library can be used as the benchmarking target, and a reference design for new FPGA architectures. Since the architecture is described in a standard HDL which is familiar with hardware designers, and read in the tools rather than hard coded, the tools are "data-driven", and tolerable with the architectural changes due to the design space exploration. The experiments confirm that the developed library is correct, and the functional correctness of applications implemented on the FPGA fabric can be validated by simulation. The placement and routing tools are under development. The completion of the toolkit will enable the development of practical FPGA architectures which, in return, will synergically animate the research on optimization CAD tools.

• Journal of Wellbeing Management and Applied Psychology
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• v.7 no.1
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• pp.17-25
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• 2024

Purpose: This study aims to explore the citizens' perceptions of living labs in the context of enhancing the living environment. Specifically, it employs quantitative research to investigate the perspectives of Millennials and Generation Z. This study proposed research questions to examine how the impacts of citizen-driven management, social factors, locally-driven management, open innovation operation, economic value, and environmental value influence the overall attitude toward living labs. Additionally, this study investigated the effects of overall attitudes on intention to participate in living labs and expected satisfaction towards living labs. Research design, data and methodology: This study employed an online survey conducted by a well-known research organization. Factor and regression analysis were utilized for data analysis. Results: The results revealed significant effects of citizen-driven management, social factors, economic value, and environmental value on overall attitude, with social factors exhibiting the highest effect size on overall attitude. Additionally, significant effects of overall attitude on intention and expected satisfaction were observed. Conclusions: The findings suggest which aspects of living labs should be fostered for the development of residents, the local economy, and citizens' quality of life, particularly with consideration of the perspectives of Millennials and Generation Z, who play a crucial role in utilizing a diverse array of ICT tools.

• Proceedings of the Korea Technical Association of the Pulp and Paper Industry Conference
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• 2006.06b
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• pp.191-195
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• 2006

Multivariate data analysis tools were used to improve the understanding of the wet end chemistry and white water system of the Papermill at NorskeCanada Crofton Division. Specifically, the analysis was aimed at identifying what variables were contributing to increased retention aid use and wet end instability. Several models were developed using data sets with up to 88 process variables and over 3000 observations. It was found that increased retention aid use was driven primarily by PCC and TMP usage as well as the addition of Alaskan White Spruce to the TMP furnish.

• Journal of Korean Institute of Industrial Engineers
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• v.40 no.5
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• pp.492-500
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• 2014

Activity monitoring has been widely recognized as important and critical tools in system monitoring for detection of abnormal behavior. In this research, we propose a data-driven activity monitoring method to measure relative sales performance which is not sensitive to special event which frequently occur in marketing area. Moreover, the proposed method can automatically updates the monitoring threshold that accommodates a drastically changing business environment. The results from simulation and practical case study from sales of electronic devices demonstrate the usefulness and applicability of the proposed activity monitoring method.