• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.36 no.6
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• pp.594-599
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• 2008

Image data produced from ADD water-tunnel test are currently analyzed manually. The accuracy and elapsed time of this process can be determined by observers. In this paper, the algorithm based on MATLAB for improved image data processing and analysis is proposed. This algorithm consists of camera calibration, gray-level transformation, noise filtering and binarization in image preprocessing, vortex trajectory measurement in image analysis. Experimental results show that the proposed algorithm has better accuracy and execution speed than those of the existing methods.

• Proceedings of the Korea Contents Association Conference
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• 2019.05a
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• pp.271-272
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• 2019

4차 산업시대로의 진입과 함께 인구 고령화 현상이 지속되면서 정보, 의료, 식품 분야 등의 역할이 중요해지고 있다. 특히 건강한 삶을 영위하기 위해 식품과 의료가 융합한 식치 정보에 대한 사람들의 관심과 필요성이 증가하고 있는 것에 비해 이에 대한 연구는 부족한 실정이다. 따라서 본 연구는 식품과 한의 정보를 수집하고 융합하여 식품 또는 식재료의 영양, 성질, 효능, 질병 등이 결합된 하나의 식치 데이터를 시스템 상으로 구축하고자 하였다. 이를 위해 고조리서, 한의서, 역사서 등의 고문헌과 논문, 특허 등의 현대 과학적 연구 자료를 수집하였으며, 수집된 자료들을 일정 기준에 따라 분류하고 코드화 하였다. 이후 정제된 각각의 데이터들 간의 연관성을 파악하고 연결 지어 식품과 한의 정보가 통합된 하나의 새로운 식치 데이터를 구축하였다.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.100-112
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• 2021

With the recent growth of the big data technology market, interest in visualization technology has steadily increased over the past few years. Data visualization is currently used in a wide range of disciplines such as information science, computer science, human-computer interaction, statistics, data mining, cartography, and journalism, each with a slightly different meaning. Big data visualization in smart cities that require multidisciplinary research enables an objective and scientific approach to developing user-centered smart city services and related policies. In particular, spatial-based data visualization enables efficient collaboration of various stakeholders through visualization data in the process of establishing city policy. In this paper, a user-centered spatial big data visualization expression request method was derived by examining the spatial-based big data visualization expression process and principle from the viewpoint of effective information delivery, not just a visualization tool.

• Journal of Information Management
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• v.33 no.4
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• pp.129-144
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• 2002

SICI(Serial Item and Contribution Identifier) is intended primarily for use by those involved in the use or management of serial titles and their contributions. And SICI is a standard that is developed for interoperability and electronic data exchange because of increasing need of the unique resource identifier. This paper introduces metadata standard ANSI/NISO Z39.56 that relates serials management. And it examines applications and implementations of Z39.56 toward serials management.

• Journal of radiological science and technology
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• v.39 no.2
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• pp.143-148
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• 2016

The purpose of this study was examined the measurement error factor on AMARES of jMRUI method for magnetic resonance spectroscopy (MRS) quantitative analysis by skilled and unskilled observer method and identified the reason of independent observers. The Point-resolved spectroscopy sequence was used to acquired magnetic resonance spectroscopy data of 10 weeks male Sprague-Dawley rat liver. The methylene protons ($(-CH_{2-})n$) of 1.3 ppm and water proton ($H_2O$) of 4.7 ppm ratio was calculated by LCModel software for using the reference data. The seven unskilled observers were calculated total lipid (methylene/water) using the jMRUI AMARES technique twice every 1 week, and we conducted interclass correlation coefficient (ICC) statistical analysis by SPSS software. The inter-observer reliability (ICC) of Cronbach's alpha value was less than 0.1. The average value of seven observer's total lipid ($0.096{\pm}0.038$) was 50% higher than LCModel reference value. The jMRUI AMARES analysis method is need to minimize the presence of the residual metabolite by identified metabolite MRS profile in order to obtain the same results as the LCModel.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.645-646
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• 2023

본 연구에서는 원격강좌(콘텐츠 기반)를 이용하여 학습하는 학습자들의 학습 형태를 분석하여 효율적인 원격강좌 운영을 위한 제도 마련에 대한 필요성을 제시하고자 하였다. 학습자들이 원격강좌를 학습한 정규교과 1년의 데이터를 가지고 분석한 결과 학습자들은 오후8시부터 자정까지 학습하는 빈도가 가장 높았다. 이는 교과 구분 형태인 전공/교양 모두에서 나타나는 분석결과였다. 또한 요일별로 분석해 보면 특정 요일에 학습의 빈도가 높았는데 이 요일은 한 주간의 강의가 종료되는 요일이었다. 이러한 분석 결과를 기반으로 효율적인 원격강좌가 운영되기 위한 제도적 보완 - 원격강좌별로 종료되는 요일을 달리한다든지 -을 생각해 볼 필요가 있다 하겠다.

• Journal of KIISE
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• v.42 no.5
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• pp.580-590
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• 2015

Recently, the issue of efficient power management in datacenters as a part of green computing has gained prominence. For realizing efficient power management, effective power monitoring and analysis must be conducted for servers in a datacenter. However, an administrator should know the exact structure of the datacenter and its associated databases, and is required to analyze relationships among the observed data. This is because according to previous monitoring approaches, servers are usually managed using only databases. In addition, it is not possible to monitor data that are not indicated in databases. To overcome these drawbacks, we proposed an ontology-based monitoring approach. We constructed domain ontology for management servers at a datacenter, and mapped observed data onto the constructed domain ontology by using semantic annotation. Moreover, we defined query creation rules and server state rules. To demonstrate the proposed approach, we designed an ontology based monitoring system architecture, and constructed a knowledge system. Subsequently, we implemented the pilot system to verify its effectiveness.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.1091-1094
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• 2012

산업 및 무역, 유통 기업들은 수많은 물류자원이 된다. 이러한 기업들은 물류 비용을 절감하기 위해 전문 물류 기업에 물품 운송 부분을 맡긴다. 전문 물류 관리 기업들은 컴퓨터와 인터넷의 발전으로 공급자, 구매자와 타사 기업들간에 인터넷으로 서로 연결된다. 하지만 서로 다른 회사에서 사용하고 관리하는 소프트웨어 때문에 이기종데이터는 타사 기업을 위한 물류 정보시스템에 큰 문제가 된다. 따라서, 본 연구에서는 전문 물류 회사를 위한 도메인 온톨로지 기반의 검색 프레임워크를 제안한다. 제안한 도메인 온톨로지 기반의 검색 프레임워크는 통합 환경에서 전문 물류 회사를 위한 다양한 시스템과 프로세스를 포함한 문서로 제공될 수 있고 여러 다양한 문서의 통합 검색을 지원하며 문서 안의 의미 정보를 고려할 수 있다.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.32 no.6
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• pp.1113-1120
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• 2022

Recently, the investigation has been difficult due to the emergence of messengers that encrypt and store data for the purpose of protecting personal information and provide services such as end-to-end encryption with a focus on security. Accordingly, the number of crime cases using security messengers is increasing, but research on data decoding for security messengers is needed. Element security messengers provide end-to-end encryption functions so that only conversation participants can check conversation history, but research on decoding them is insufficient. Therefore, in this paper, we analyze the instant messenger Element, which provides end-to-end encryption, and propose a plaintext verification of the history of encrypted secure chat rooms using decryption keys stored in the Windows Credential Manager service without user passwords. In addition, we summarize the results of analyzing significant general and secure chat-related artifacts from a digital forensics investigation perspective.

• Journal of The Korean Association For Science Education
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• v.43 no.3
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• pp.237-251
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• 2023

This study explores the possibility of automated scoring for scientific graph answers by designing an automated scoring model using convolutional neural networks and applying it to students' kinematics graph answers. The researchers prepared 2,200 answers, which were divided into 2,000 training data and 200 validation data. Additionally, 202 student answers were divided into 100 training data and 102 test data. First, in the process of designing an automated scoring model and validating its performance, the automated scoring model was optimized for graph image classification using the answer dataset prepared by the researchers. Next, the automated scoring model was trained using various types of training datasets, and it was used to score the student test dataset. The performance of the automated scoring model has been improved as the amount of training data increased in amount and diversity. Finally, compared to human scoring, the accuracy was 97.06%, the kappa coefficient was 0.957, and the weighted kappa coefficient was 0.968. On the other hand, in the case of answer types that were not included in the training data, the s coring was almos t identical among human s corers however, the automated scoring model performed inaccurately.