• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.62.2-62.2
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• 2019

한국의 고천문 자료는 삼국시대 이후 근대 조선까지 다수가 존재하여 세계적으로 드문 기록 문화를 보유하고 있으나, 한문 번역이 많이 이루어지지 않아 학술적 활용이 활발하지 못한 상태이다. 고문헌의 한문 문장 번역은 전문인력의 수작업에 의존하는 만큼 소요 시간이 길기에 투자대비 효율성이 떨어지는 편이다. 이에 최근 여러 분야에서 응용되는 인공지능의 적용을 대안으로 삼을 수 있으며, 초벌 번역 수준일지라도 자동번역기의 개발은 유용한 학술도구가 될 수 있다. 한국천문연구원은 한국정보화진흥원이 주관하는 2019년도 Information and Communication Technology 기반 공공서비스 촉진사업에 한국고전번역원과 공동 참여하여 인공신경망 기계학습이 적용된 고문헌 자동번역모델을 개발하고자 한다. 이 연구는 고천문 도메인에 특화된 인공지능 기계학습 기법으로 자동번역모델을 개발하여 이를 서비스하는 것을 목적으로 한다. 연구 방법은 크게 4가지 개발을 진행하는 것으로 나누어 볼 수 있다. 첫째, 인공지능의 학습 데이터에 해당되는 '코퍼스'를 구축하는 것이다. 이는 고문헌의 한자 원문과 한글 번역문이 쌍을 이루도록 만들어 줌으로써 학습에 최적화한 데이터를 최소 6만 개 이상 추출하는 것이다. 둘째, 추출된 학습 데이터 코퍼스를 다양한 인공지능 기계학습 기법에 적용하여 천문 분야 특수고전 도메인에 특화된 자동번역 모델을 생성하는 것이다. 셋째, 클라우드 기반에서 참여 기관별로 소장한 고문헌을 자동 번역 모델에 기반하여 도메인 특화된 모델로 도출 및 활용할 수 있는 대기관 서비스 플랫폼 구축이다. 넷째, 개발된 자동 번역기의 대국민 개방을 위해 웹과 모바일 메신저를 통해 자동 번역 서비스를 클라우드 기반으로 구축하는 것이다. 이 연구는 시스템 요구사항 분석과 정의를 바탕으로 설계가 진행 또는 일부 완료되어 구현 중에 있다. 추후 이 연구의 성능 평가는 자동번역모델 평가와 응용시스템 시험으로 나누어 진행된다. 자동번역모델은 평가용 테스트셋에 의한 자동 평가와 전문가에 의한 휴먼 평가에 따라 모델의 품질을 수치로 측정할 수 있다. 또한 응용시스템 시험은 소프트웨어 방법론의 개발 단계별 테스트를 적용한다. 이 연구를 통해 고천문 분야가 인공지능 자동번역 확산 플랫폼 시범의 첫 케이스라는 점에서 의의가 있다. 즉, 클라우드 기반으로 시스템을 구축함으로써 상대적으로 적은 초기 비용을 투자하여 활용성이 높은 한문 문장 자동 번역기라는 연구 인프라를 확보하는 첫 적용 학문 분야이다. 향후 이를 활용한 고천문 분야 학술 활동이 더욱 활발해질 것을 기대해 볼 수 있다.

• Journal of Advanced Technology Convergence
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• v.3 no.3
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• pp.17-27
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• 2024

This study focuses on the development and evaluation of a chatbot system based on the International Classification of Functioning, Disability, and Health (ICF) framework to enhance community participation among elderly individuals with mild dementia in South Korea. The study involved 12 elderly participants who were living alone and had been diagnosed with mild dementia, along with 15 caregivers who were actively involved in their daily care. The development process included a comprehensive needs assessment, system design, content creation, natural language processing using Transformer Attention Algorithm, and usability testing. The chatbot is designed to offer personalized activity recommendations, reminders, and information that support physical, social, and cognitive engagement. Usability testing revealed high levels of user satisfaction and perceived usefulness, with significant improvements in community activities and social interactions. Quantitative analysis showed a 92% increase in weekly community activities and an 84% increase in social interactions. Qualitative feedback highlighted the chatbot's user-friendly interface, relevance of suggested activities, and its role in reducing caregiver burden. The study demonstrates that an ICF-based chatbot system can effectively promote community participation and improve the quality of life for elderly individuals with mild dementia. Future research should focus on refining the system and evaluating its long-term impact.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.5
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• pp.274-292
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• 2024

The purpose of this study is to develop test scenarios utilizing V2X (Vehicle-to-Everything) communication technology for the prevention of pedestrian accidents and to validate these scenarios through simulation. To this end, this researcher used existing traffic accident databases to categorize vehicle-to-pedestrian accident data, and drew key accident patterns through the analysis of accident types and the speeds of pedestrians and vehicles. Based on the analyzed data, scenarios were established where V2X technology can be applied under various conditions of pedestrians and vehicles. These scenarios were specifically classified into conditions where physical avoidance of an accident is impossible and conditions where accident avoidance is possible through V2X technology. In the developed test matrix, simulations were conducted in diverse scenarios to evaluate the performance of the V2X-based accident prevention system. The research results confirmed that the application of V2X technology is effective for preventing pedestrian accidents. It is expected that these scenarios can serve as standardized guidelines for future traffic safety improvements. This study provides useful data for policymakers for traffic safety, vehicle manufacturers, and technology developers, and proposes a new approach to enhance pedestrian safety.

• Journal of the Korean Society for information Management
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• v.26 no.2
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• pp.83-103
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• 2009

The Computer Interchange of Museum Information (CIMI), operating from 1990-2003, was charged with creating and introducing the international museum community to the concept of adopting metadata industry standards. The CIMI consortium exceeded its original mission by; creating a standards framework, profile, testbeds, important metadata publications, free downloadable metadata software and protocols, and providing instrumental guidance and support in development of new projects. However, CIMI's emphasis on the importance and utility of a standards-based approach and the necessity for implementing the CIMI Standards Framework is probably its most important achievement. During CIMI's tenure, museums reaped the benefits by learning how to apply the model and standards to meet their individual needs while not having to invent new ones or bear the cost of software development. Although CIMI operations ceased in 2003, its impacts on museum related metadata application and research were unprecedented in that it provided the standards prototype and foundations on which to build. This paper discusses what CIMI bequeathed to the next generation of museum metadata field developers and describes the anticipated realm of future projects and advancement.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.5 no.7
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• pp.1332-1339
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• 2001

SoC(System on Chip) technology is widely used in the field of embedded systems by providing high flexibility for a specific application domain. An important aspect of development any new embedded system is verification which usually requires lengthy software and hardware co-design. To reduce development cost of design effort, the instruction set of microprocessor must be suitable for a high level language compiler. And FPGA prototype system could be derived and tested for design verification. In this paper, we propose a 16 bit FPGA microprocessor, which is tentatively-named EISC16, based on an EISC(Extendable Instruction Set Computer) architecture for embedded applications. The proposed EISC16 has a 16 bit fixed length instruction set which has the short length offset and small immediate operand. A 16 bit offset and immediate operand could be extended using by an extension register and an extension flag. We developed a cross C/C++ compiler and development software of the EISC16 by porting GNU on an IBM-PC and SUN workstation and compared the object code size created after compiling a C/C. standard library, concluding that EISC16 exhibits a higher code density than existing 16 microprocessors. The proposed EISC16 requires approximately 6,000 gates when designed and synthesized with RTL level VHDL at Xilinix's Virtex XCV300 FPGA. And we design a test board which consists of EISC16 ROM, RAM, LED/LCD panel, periodic timer, input key pad and RS-232C controller. 11 works normally at 7MHz Clock.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.581-588
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• 2020

This study examined a brake pad wear compensation method for an Electro-Mechanical Brake (EMB) using the braking test device. A three-phase Interior Permanent Magnet Synchronous Motor (IPMSM) was applied to drive the actuator of an EMB. Current control, speed control, and position control were used to control the clamping force of the EMB. The wear compensation method was performed using a software algorithm that updates the motor model equation by comparing the motor output torque current with a reference current. In addition, a simple first-order motor model equation was applied to estimate the output clamping force. The operation time to the maximum clamping force increased within 0.1 seconds compared to the brake pad in its initial condition. The experiment verified that the reference operating time was within 0.5 seconds, and the maximum value of the clamping force was satisfied under the wear condition. The wear compensation method based on the software algorithm in this paper can be performed in the pre-departure test of rolling stock.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.1
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• pp.83-95
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• 2018

With recent technological advances in the shipbuilding industry, vessels have been improved in size and performance. As a result, an accident such as grounding, caused by a single ship-to-ship collision, could lead to a large-scale maritime disaster. Considering the seriousness of the situation, the international community has been consistently updating the standards for Electronic Navigational Chart(ENC) to improve the maritime safety. S-57, the existing ENC standard governed by the International Hydrographic Organization(IHO), includes standards for generating conventional binary-type ENC data sets. The S-57 standard, however, has not been updated since the release of Version 3.1 in December 2000. Since then, the standard has failed to reflect technological development regarding maritime spacial information, which has been consistently improving. In an effort to address this concern, the IHO designated S-100, i.e., the next-generation ENC production standard. S-100 differs from S-57 in data exchange type. Contrary to the conventional ENC standards, which use binary-type data, S-10X, based on the next-generation ENC standards, uses ENC data composed of Feature Catalogue, Portrayal Catalogue, and GML. Considering this fact, it is necessary to update S-58, the ENC validation check standard, or designate a new standard for ENC validation checks. This study is developed own software to implement validation checks for new types of data, and identified improvement points based on the test results.

• Smart Media Journal
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• v.4 no.4
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• pp.24-32
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• 2015

Recently, SDN is actively used as datacenter networks and gradually increase its applied areas. Along with this change of networking environment, research of deploying network security systems on SDN becomes highlighted. Especially, systems for detecting network flooding attacks by monitoring every packets through ports of OpenFlow switches have been proposed. However, because of the centralized management of a SDN controller which manage multiple switches, it may be substantial overhead that the attack detection system continuously monitors all the flows. In this paper, a sampling based network flooding attack detection and prevention system is proposed to reduce the overhead of monitoring packets and to achieve reasonable functionality of attack detection and prevention. The proposed system periodically takes sample packets of network flows with the given sampling conditions, analyzes the sampled packets to detect network flooding attacks, and block the attack flows actively by managing the flow entries in OpenFlow switches. As network traffic sampler, sFlow agent is used, and snort, an opensource IDS, is used to detect network flooding attack from the sampled packets. For active prevention of the detected attacks, an OpenDaylight application is developed and applied. The proposed system is evaluated on the local testbed composed with multiple OVSes (Open Virtual Switch), and the performance and overhead of the proposed system under various sampling condition is analyzed.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.6B
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• pp.954-961
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• 2010

Stream cipher was worse than block cipher in terms of security, but faster in execution speed as an advantage. However, since so far there have been many algorithm researches about the execution speed of block cipher, these days, there is almost no difference between them in the execution speed of AES. Therefore an secure and fast stream cipher development is urgently needed. In this paper, we propose a 32bit output fast stream cipher, AA32, which is composed of ASR(Arithmetic Shifter Register) and simple logical operation. Proposed algorithm is a cipher algorithm which has been designed to be implemented by software easily. AA32 supports 128bit key and executes operations by word and byte unit. As Linear Feedback Sequencer, ASR 151bit is applied to AA32 and the reduction function is a very simple structure stream cipher, which consists of two major parts, using simple logical operations, instead of S-Box for a non-linear operation. The proposed stream cipher AA32 shows the result that it is faster than SSC2 and Salsa20 and satisfied with the security required for these days. Proposed cipher algorithm is a fast stream cipher algorithm which can be used in the field which requires wireless internet environment such as mobile phone system and real-time processing such as DRM(Digital Right Management) and limited computational environments such as WSN(Wireless Sensor Network).

• KIPS Transactions on Software and Data Engineering
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• v.8 no.11
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• pp.441-448
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• 2019

Previous researches on automatic spacing of Korean sentences has been researched to correct spacing errors by using n-gram based statistical techniques or morpheme analyzer to insert blanks in the word boundary. In this paper, we propose an end-to-end automatic word spacing by using deep neural network. Automatic word spacing problem could be defined as a tag classification problem in unit of syllable other than word. For contextual representation between syllables, Bi-LSTM encodes the dependency relationship between syllables into a fixed-length vector of continuous vector space using forward and backward LSTM cell. In order to conduct automatic word spacing of Korean sentences, after a fixed-length contextual vector by Bi-LSTM is classified into auto-spacing tag(B or I), the blank is inserted in the front of B tag. For tag classification method, we compose three types of classification neural networks. One is feedforward neural network, another is neural network language model and the other is linear-chain CRF. To compare our models, we measure the performance of automatic word spacing depending on the three of classification networks. linear-chain CRF of them used as classification neural network shows better performance than other models. We used KCC150 corpus as a training and testing data.