• 한국산업정보학회논문지
• /
• 제2권2호
• /
• pp.189-207
• /
• 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.

• 인터넷정보학회논문지
• /
• 제19권1호
• /
• pp.123-130
• /
• 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.

• 아시아태평양코퍼스연구
• /
• 제2권2호
• /
• pp.43-48
• /
• 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
• /
• 제52권12호
• /
• pp.2687-2698
• /
• 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.

• 한국IT서비스학회지
• /
• 제8권1호
• /
• pp.1-9
• /
• 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
• /
• 제44권11호
• /
• pp.843-850
• /
• 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.

• 대한전자공학회논문지SD
• /
• 제49권4호
• /
• pp.15-25
• /
• 2012

FPGA용 CAD툴에 대한 학계의 연구는 상용 FPGA에 적용하기에는 단순하고 비효율적인 아키텍처를 가정하고 있기 때문에 실용성 측면에서 뒤처져 왔다. 최근 상용 FPGA 아키텍처의 배치 위치 및 배선 그래프 데이터베이스를 구축하고 인터페이스를 제공함으로써 상용 FPGA에 적용할 수 있는 배치 배선 툴의 개발을 가능하게 하려는 시도가 있었다. 본 논문은 신규 FPGA 아키텍처로 개발되고 있는 K-FPGA의 경쟁력을 벤치마킹 할 수 있는 툴킷 개발에 대해 기술한다. 이는 학계 CAD 툴의 실용성 한계를 한층 더 확장하고 있다. 기존 상용 툴과 매핑, 패킹, 배치, 배선 각 단계 별로 데이터를 교환할 수 있어 세부 툴별 비교 평가가 가능하며 이전 단계의 결과물을 기다리거나 결과의 질에 영향을 받지 않으면서 각 단계를 독립적으로 개발할 수 있는 체계를 구축하였다. 또한, 상용 FPGA의 아키텍처를 추출하여 단위 셀 라이브러리를 구축함으로써 FPGA 아키텍처의 신규 개발 시 참조 설계 역할을 할 뿐만 아니라 상시 벤치마킹 환경을 제공하도록 하였다. 특히, 아키텍처 정보를 툴 내에 하드 코딩하지 않고 하드웨어 설계자에게 익숙한 표준 HDL 형식으로 기술하여 읽어 들일 수 있도록 함으로써 아키텍처에 수시로 다양한 변경을 시도하면서 최적화해도 툴이 유연하게 수용할 수 있는 데이터 구동 방식의 툴 개발을 추구하였다. 실험을 통해 단위 셀 라이브러리 및 툴 기능을 검증하였으며 개발 중에 변경되고 있는 FPGA 아키텍처 상에서 임의의 설계를 매핑해 보고 정상 동작할 지 시뮬레이션으로 검증할 수 있음을 확인하였다. 배치 및 배선 툴이 개발 중이며 이들이 완성되면 실용적이고 다양한 신규 FPGA 아키텍처들을 개발하고 그 경쟁력을 평가할 수 있게 될 뿐만 아니라 신규 아키텍처를 위한 최적화 CAD 툴 개발 연구가 활발해지는 시너지 효과도 기대할 수 있다.

• 웰빙융합연구
• /
• 제7권1호
• /
• pp.17-25
• /
• 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.

• 한국펄프종이공학회:학술대회논문집
• /
• 한국펄프종이공학회 2006년도 PAN PACIFIC CONFERENCE vol.2
• /
• pp.191-195
• /
• 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.

• 대한산업공학회지
• /
• 제40권5호
• /
• pp.492-500
• /
• 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.