• Journal of Information Management
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• v.38 no.4
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• pp.145-166
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• 2007

This article analyzes the direction of 'business-Friendly' record management in electronic records environment which means paradigm shift in record management. In the first place, this article investigates the interrelationship of business, records and record management through natures of electronic records, and analyzes direction of purposes and roles of record management in electronic records environment. After all, this article rebuilds a significance and roles of record management in active stage, and provides theoretical bases for close relation between record management and information management in electronic records environment.

• Proceedings of the Korea Information Processing Society Conference
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• 2013.11a
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• pp.835-838
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• 2013

클라우드 컴퓨팅을 사용하면 컴퓨팅 자원을 구축하는 비용을 절감할 수 있다는 장점이 있다. 문제는 클라이언트가 데이터 센터와 서비스제공자를 완전히 신뢰할 수 없다는 것이다. 예를 들어, 클라우드에 저장된 파일이 손실되었을 때 서비스 제공자는 서비스의 신뢰도가 떨어지는 것을 막기 위해 이를 숨길 수 있다. 이때, 데이터가 저장 후에 손실되었다는 것을 증명하지 못하면, 그 피해는 클라이언트에게 돌아오게 된다. 따라서, 클라이언트의 데이터를 보호하기 위하여 무결성을 검증할 수 있는 적절한 기법을 적용하여야 한다. 기존 연구로는 homomorphic tags 기반의 기법들이 많이 제안되었으나 이 기법은 많은 지수연산을 필요로 하므로 상용화할 수 있을 만큼의 효율성을 가지지 못한다. 특히, 클라이언트가 증거 생성을 위해 많은 연산을 부담해야 한다. 본 논문에서는 효율성에 중점을 둔, 특히 클라이언트의 효율성에 중점을 둔 무결성 검증 기법을 제안한다. 제안하는 기법은 Modular arithmetic을 기반으로 설계되었으며, 무결성 검증뿐만 아니라 데이터가 자주 업데이트 되는 환경을 지원한다. Simulation result는 제안하는 기법이 기존 기법에 매우 효율적임을 보여준다.

• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.525-530
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• 2023

최근 소셜 네트워크 서비스(SNS) 및 모바일 서비스가 증가함에 따라 사용자들은 다양한 종류의 위험에 직면하고 있다. 특히 온라인 그루밍과 온라인 루머 같은 위험은 한 개인의 삶을 완전히 망가뜨릴 수 있을 정도로 심각한 문제로 자리 잡았다. 그러나 많은 경우 이러한 위험들을 판단하는 시점은 사건이 일어난 이후이고, 주로 법적인 증거채택을 위한 위험성 판별이 대다수이다. 따라서 본 논문은 이러한 문제를 사전에 예방하는 것에 초점을 맞추었고, 계속적으로 발생하는 대화와 같은 event를 실시간으로 감지하고, 위험을 사전에 탐지할 수 있는 Real-Time Early Risk Detection(RERD) 문제를 정의하고자 한다. 온라인 그루밍과 루머를 실시간 조기 위험 감지(RERD) 문제로 정의하고 해당 데이터셋과 평가지표를 소개한다. 또한 RERD 문제를 정확하고 신속하게 해결할 수 있는 강화학습 기반 새로운 방법론인 RT-ERD 모델을 소개한다. 해당 방법론은 RERD 문제를 이루고 있는 온라인 그루밍, 루머 도메인에 대한 실험에서 각각 기존의 모델들을 뛰어넘는 state-of-the-art의 성능을 달성하였다.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.4
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• pp.77-99
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• 2023

This study aims to quantitatively assess collection and circulation data of one small library in an area where multicultural users are concentrated and draw policy implications on improving multicultural services for public libraries. The Ansan Multicultural Small Library was selected for examining the library's collection and circulation usages from 2016 to 2022. The numbers of collection and circulation, collection turnover rates and use factors were calculated by year, language, and KDC subject. The result of this study presents the empirical evidence drawn from users' circulation usage, which can be a basis for leading to valid collection development and multicultural service policies.

• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.331-341
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• 2017

As increasing the importance of the R&D strategy planning based on S&T evidence, the S&T DB was conducted to develop appropriate basic research support strategies by collecting 49 multiple-nations' statistics and information, extracting 6446 raw data, categorizing 877 indicators including 208 core indicators. An statistical and knowledge map analysis using the highly cited publication-related indicators was conducted to examine the expansion of DB utilization by demonstrating effectiveness of Korea's basic research. As a result, basic research investment have a strong influence on creating outstanding R&D outcomes and on producing a foundation of various S&T based-growth engines.

• Journal of the Korean Chemical Society
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• v.68 no.4
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• pp.221-234
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• 2024

The purpose of this study was to examine the impact of Argument-based Inquiry approach on elementary school students' critical thinking in elementary school science class. For this purpose, 23 students from two 5th grade elementary school classes in a metropolitan city were selected. One class (11 students) was assigned as the experimental group which Argument-based inquiry approach on 10 topics were applied. To determine the impact of Argument-based Inquiry approach on critical thinking, we analyzed the results of critical thinking tests before and after class and recordings of the discussion process of students in the experimental group. As a result of the critical thinking analysis, the average score of the experimental group in the deduction section was statistically and significantly higher than that of the comparative group. And as a result of analysis of recordings of the discussion process, students used deductive reasoning more often than inductive reasoning, and their use of this reasoning increased significantly at the claim·evidence stage.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.10
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• pp.231-238
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• 2020

With a large number of documents appearing on the web, document-level novelty detection has become important since it can reduce the efforts of finding novel documents by discarding documents sharing redundant information already seen. A recent work proposed a convolutional neural network (CNN)-based novelty detection model with significant performance improvements. We observed that it has a restriction of using document-level information in determining novelty but assumed that the document-level information is more important. As a solution, this paper proposed two methods of effectively incorporating document-level information using a CNN-based novelty detection model. Our methods focus on constructing a feature vector of a target document to be classified by extracting relative information between the target document and source documents given as evidence. A series of experiments showed the superiority of our methods on a standard benchmark collection, TAP-DLND 1.0.

• Composites Research
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• v.26 no.1
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• pp.29-35
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• 2013

Composite sandwich structure can improve the specific bending stiffness significantly and save the weight nearly 30 percent compared with the composite laminates. However, it has more inherent uncertainties of the material property caused by manufacturing process than metals. Therefore, the reliability-based probabilistic design approach is required. In this paper, the PMS(Probabilistic Margin of Safety) is calculated for the simplified fuselage structure made of composite sandwich to provide the probabilistic reasonable evidence that the classical design method based on the safety factor cannot ensure the structural safety. In this phase, the probability density function estimated by CMCS(Crude Monte-Carlo Simulation) is used. Furthermore, the RBDO(Reliability-Based Design Optimization) under the probabilistic constraint are performed, and the RBDO-MPDF(RBDO by Moving Probability Density Function) is proposed for an efficient computation. The examined results in this paper can be helpful for advanced design techniques to ensure the reliability of structures under the uncertainty and computationally inexpensive RBDO methods.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.99-105
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• 2023

In the 4th industrial revolution, the field of criminal justice is paying attention to Legaltech using artificial intelligence to provide efficient legal services. This paper attempted to create a crime prediction model that can apply Recurrent Neural Network(RNN) to increase the potential for using legal technology in the domestic criminal justice field. To this end, the crime process was divided into pre, during, and post stages based on the criminal facts described in the judgment, utilizing crime script analysis techniques. In addition, at each time point, the method and evidence of crime were classified into objects, actions, and environments based on the sentence composition elements and the 8 principles of investigation. The case summary analysis framework derived from this study can contribute to establishing situational crime prevention strategies because it is easy to identify typical patterns of specific crime methods. Furthermore, the results of this study can be used as a useful reference for research on generating crime situation prediction data based on RNN models in future follow-up studies.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.6
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• pp.279-290
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• 2013

In digital forensics log files have been stored as a form of large data for the purpose of tracing users' past behaviors. It is difficult for investigators to manually analysis the large log data without clues. In this paper, we propose a text mining technique for extracting intrusion logs from a large log set to recommend reliable evidences to investigators. In the training stage, the proposed method extracts intrusion association words from a training log set by using Apriori algorithm after preprocessing and the probability of intrusion for association words are computed by combining support and confidence. Robinson's method of computing confidences for filtering spam mails is applied to extracting intrusion logs in the proposed method. As the results, the association word knowledge base is constructed by including the weights of the probability of intrusion for association words to improve the accuracy. In the test stage, the probability of intrusion logs and the probability of normal logs in a test log set are computed by Fisher's inverse chi-square classification algorithm based on the association word knowledge base respectively and intrusion logs are extracted from combining the results. Then, the intrusion logs are recommended to investigators. The proposed method uses a training method of clearly analyzing the meaning of data from an unstructured large log data. As the results, it complements the problem of reduction in accuracy caused by data ambiguity. In addition, the proposed method recommends intrusion logs by using Fisher's inverse chi-square classification algorithm. So, it reduces the rate of false positive(FP) and decreases in laborious effort to extract evidences manually.