• 지식경영연구
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• 제1권1호
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• pp.91-107
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• 2000

This paper proposes the Organizational Knowledge Discovery Process Model (OK-DPM) as an initiative for developing a knowledge management methodology. OK-DPM is a model designed to effectively discover knowledge useful to the organization. It explains the knowledge discovery process from the conceptual level to the application level. It decomposes the organizational knowledge discovery process into 3 sub-processes; Creation, Suggestion and Validation. For each sub-process, design components are identified and possible methods for supporting each one are suggested. Also, the relationship patterns between the knowledge discovery process and knowledge type are explored. By applying OK-DPM to two real cases where the knowledge management projects are ongoing, the model was validated and revised. Even though we need to investigate with more cases to refine the OK-DPM, we found that it could provide some insights in developing the effective knowledge discovery process.

• 디지털융복합연구
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• 제10권8호
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• pp.287-297
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• 2012

본 논문에서는 미국의 전자증거개시(E-Discovery) 제도의 확산에 따라 국내 도입에 대비하여 표준화 된 업무 수행 절차 확립을 위해 선행 연구가 이루어지고 있는 EDRM(Electronic Discovery Reference Model) 및 The Sedona Conference 프로젝트에 대한 분석을 바탕으로 일반화 된 E-Discovery 프로세스와 세부 절차 별 필수 업무 사항들을 제시한다. 또한 이런 절차들이 실제 소송에 활용됨에 있어서 근본적으로 내포하고 있는 시간과 비용 문제를 해결하기 위한 대체 기술로써 기계 학습, 오픈 소스 형태의 정보 검색 라이브러리, Hadoop 기반의 대용량 데이터 분산 처리 기법 등을 소개하고, E-Discovery 프로세스 상에서의 활용 방안을 제시하여, 관련 서비스 및 솔루션을 개발하고자 하는 벤더들에게 유용한 정보를 제공한다. 이는 또한 제도적 변화에 발맞추어 업무 시스템을 재정비하고자 하는 기업들로 하여금 소송에 보다 효과적으로 대처할 수 있도록 한다.

• Journal of Multimedia Information System
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• 제4권2호
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• pp.57-64
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• 2017

Numerous software vulnerabilities have been found in the popular operating systems. And recently, robust linear behaviors in software vulnerability discovery process have been noticeably observed among the many popular systems having multi-versions released. Software users need to estimate how much their software systems are risk enough so that they need to take an action before it is too late. Security vulnerabilities are discovered throughout the life of a software system by both the developers, and normal end-users. So far there have been several vulnerability discovery models are proposed to describe the vulnerability discovery pattern for determining readiness for patch release, optimal resource allocations or evaluating the risk of vulnerability exploitation. Here, we apply a linear vulnerability discovery model into Windows operating systems to see the linear discovery trends currently observed often. The applicability of the observation form the paper show that linear discovery model fits very well with aggregate version rather than each version.

• 지식경영연구
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• 제1권1호
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• pp.81-90
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• 2000

This study proposes the knowledge discovery process for the effective mining of knowledge on the web. The proposed knowledge discovery process uses the Prior knowledge base and the Prior knowledge management system to reflect tacit knowledge in addition to explicit knowledge. The prior knowledge management system constructs the prior knowledge base using a fuzzy cognitive map, and defines information to be extracted from the web. In addition, it transforms the extracted information into the form being handled in mining process. Experiments using case-based reasoning and neural network" are performed to verify the usefulness of the proposed model. The experimental results are encouraging and prove the usefulness of the proposed model.

• 정보교육학회논문지
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• 제12권1호
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• pp.89-97
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• 2008

제 7차 초등학교 과학과 교육과정에서는 특히 탐구학습을 강조하고 있다. 그러나 단위 시간과 학습자료의 부족이라는 현실적인 이유 때문에 학교 교육 현장에서는 실제적인 적용이 어렵다. 본 연구에서는 이러한 문제점을 해결하기 위하여 웹기반 발견학습 시스템을 설계 구현하고 그 효과성을 검증하는데 목적이 있다. 검증 과정으로 초등학교 4학년 과학과의 용수철 늘이기 단원을 대상으로 일반적인 발견학습 모형을 적용한 비교집단과 웹기반 발견학습 시스템으로 수업을 받은 실험집단의 학업성취도에 있어 유의미한 차이가 있는지 조사하였다. 적용 결과, 웹기반 발견학습 시스템으로 수업을 한 경우, 전통적인 발견학습 모형 그대로 적용한 경우보다 학업 성취도가 높았다.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2001년도 The Pacific Aisan Confrence On Intelligent Systems 2001
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• pp.431-434
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• 2001

Knowledge discovery in databases(KDD) is the process for extracting valid, novel, potentially useful and understandable knowledge form real data. There are many academic and industrial activities with new technologies and application areas. Particularly, data mining is the core step in the KDD process, consisting of many algorithms to perform clustering, pattern recognition and rule induction functions. The main goal of these algorithms is prediction and description. Prediction means the assessment of unknown variables. Description is concerned with providing understandable results in a compatible format to human users. We introduce an efficient data mining algorithm considering predictive and descriptive capability. Reasonable pattern is derived from real world data by a revised neural network model and a proposed fuzzy rule extraction technique is applied to obtain understandable knowledge. The proposed neural network model is a hierarchical self-organizing system. The rule base is compatible to decision makers perception because the generated fuzzy rule set reflects the human information process. Results from real world application are analyzed to evaluate the system\`s performance.

• Journal of Multimedia Information System
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• 제9권3호
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• pp.191-200
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• 2022

These days, businesses, in both online and offline, have started accepting cryptocurrencies as payment methods. Even in countries like El Salvador, cryptocurrencies are recognized as fiat currencies. Meanwhile, publicly known, but not patched software vulnerabilities are security threats to not only software users but also to our society in general. As the status of cryptocurrencies has gradually increased, the impact of security vulnerabilities related to cryptocurrencies on our society has increased as well. In this paper, we first analyze vulnerabilities from the two major cryptocurrency vendors of Bitcoin and Ethereum in a quantitative manner with the respect to the CVSS, to see how the vulnerabilities are roughly structured in those systems. Then we introduce a modified AML vulnerability discovery model for the vulnerability datasets from the two vendors, after showing the original AML dose not accurately represent the vulnerability discovery trends on the datasets. The analysis shows that the modified model performs better than the original AML model for the vulnerability datasets from the major cryptocurrencies.

• Journal of Multimedia Information System
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• 제8권4호
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• pp.259-266
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• 2021

Security vulnerabilities have been reported in major design software systems such as Adobe Photoshop and Illustrator, which are recognized as de facto standard design tools in most of the design industries. Companies need to evaluate and manage their risk levels posed by those vulnerabilities, so that they could mitigate the potential security bridges in advance. In general, security vulnerabilities are discovered throughout their life cycles repeatedly if software systems are continually used. Hence, in this study, we empirically analyze risk levels for the three major graphical design software systems, namely Photoshop, Illustrator and GIMP with respect to a software vulnerability discovery model. The analysis reveals that the Alhazmi-Malaiya Logistic model tends to describe the vulnerability discovery patterns significantly. This indicates that the vulnerability discovery model makes it possible to predict vulnerability discovery in advance for the software systems. Also, we found that none of the examined vulnerabilities requires even a single authentication step for successful attacks, which suggests that adding an authentication process in software systems dramatically reduce the probability of exploitations. The analysis also discloses that, for all the three software systems, the predictions with evenly distributed and daily based datasets perform better than the estimations with the datasets of vulnerability reporting dates only. The observed outcome from the analysis allows software development managers to prepare proactively for a hostile environment by deploying necessary resources before the expected time of vulnerability discovery. In addition, it can periodically remind designers who use the software systems to be aware of security risk, related to their digital work environments.

• 공학교육연구
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• 제21권6호
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• pp.54-62
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• 2018

This study is an analysis of the process of the discovery of the DNA double helix structure from an engineering literacy education perspective. The explanation of the DNA double helix structure by James Watson and Francis Crick in 1952 is a well-known scientific episode. The process is also a combination of various incidents that can frequently happen in competitive engineering research and development situations. Therefore, the process of the discovery of the DNA structure is a remarkable event that can cover all subjects, such as engineering and ethics, research ethics, communication between researchers, engineering and leadership, engineering and teamwork, and engineering and women. This paper focuses on analyzing the research ethics issues associated with Rosalind Franklin and comparing and analyzing the three teams that were very close to the discovery of the DNA structure. By looking at why the Watson and Crick team got the final answer instead of the Linus Pauling's team or the Maurice Wilkins and Rosalind Franklin's team, the virtues of the technology development process that should be taught in engineering literacy education will be naturally presented.

• 지식경영연구
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• 제2권1호
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• pp.109-132
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• 2001

The purpose of this article is to develop a dynamic model of organizational capabilities and knowledge creation, and at the same time identify the organizational capability factors for effective knowledge creation, by empirically analyzing the history of new Quinolone antibacterial drug compound (LB20304a) discovery process at LG, as a case in point. Major findings of this study are as follows. First, in a science-based area such as drug development, the core of successful knowledge creation lies in creative combination of different bodies of scientific explicit knowledge. Second, the greater the difficulty of learning external knowledge, the more tacit knowledge is needed for the recipient firm to effectively exploit that knowledge. Third, in science-based sector such as pharmaceutical industry, the key for successful knowledge creation lies in the capability of recruiting and retaining star scientists. Finally, for effective knowledge creation, a firm must keep its balance among three dimensions of organizational capabilities: local, process, architectural capabilities.