• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.227-229
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• 2014

Recent share large amounts of data in a mobile network environment for the efficient service environment by using Cloud services are being made information sharing. At that time, the data communication transmission technology is a wide area, narrow-area communication, proximity communication with a second type, and the second near field communication in the mobile NFC capable mobile devices mainly used in In this paper, an extension of local area network technology, Zing NFC technology using techniques to share large amounts of data efficiently, a system is proposed. Cloud proposed system is the proximity of sharing information between terminals which may occur when the problem was solved interoperability.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.9
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• pp.197-206
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• 2020

Collaborative research in science applications based on HPC service needs rapid transfers of massive data between research colleagues over wide area network. With regard to this requirement, researches on enhancing data transfer performance between major superfacilities in the U.S. have been conducted recently. In this paper, we deploy multiple data transfer nodes(DTNs) over high-speed science networks in order to move rapidly large amounts of data in the parallel filesystem of KISTI's Nurion supercomputer, and perform transfer experiments between endpoints with approximately 130ms round trip time. We have shown the results of transfer throughput in different size file sets and compared them. In addition, it has been confirmed that the DTN cluster with three nodes can provide about 1.8 and 2.7 times higher transfer throughput than a single node in two types of concurrency and parallelism settings.

• Journal of Korean Library and Information Science Society
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• v.53 no.2
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• pp.95-115
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• 2022

The purpose of this study is to transform the sub-categorization terms of the National Science and Technology Standards Classification System into technical keywords by applying a machine learning algorithm. For this purpose, AttentionMeSH was used as a learning algorithm suitable for topic word recommendation. For source data, four-year research status files from 2017 to 2020, refined by the Korea Institute of Science and Technology Planning and Evaluation, were used. For learning, four attributes that well express the research content were used: task name, research goal, research abstract, and expected effect. As a result, it was confirmed that the result of MiF 0.6377 was derived when the threshold was 0.5. In order to utilize machine learning in actual work in the future and to secure technical keywords, it is expected that it will be necessary to establish a term management system and secure data of various attributes.

• Journal of Information Management
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• v.43 no.4
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• pp.69-96
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• 2012

Based on analysis of trend and development of industrial and technical information such as patents and scientific data, using industrial and technical information in the process of planning can be a important factor to reduce budget and opportunity cost. This study aims to investigate needs to collect and analyze industrial and technical information in planning of R&D project. To do it, this study examines definitions, needs and types of industrial and technical information for planning of R&D project. And then this study investigates the importance of use of industrial and technical information in the process of planning of R&D and performs case study in domestic and foreign countries. Lastly, this study investigates a method to analyze industrial and technical information for R&D planning and proposes the role of a library for R&D planning.

• Journal of the Korea Institute of Military Science and Technology
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• v.21 no.6
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• pp.826-841
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• 2018

The military satellite communication of ROK military, ANASIS is designed for analog data such as voice and streaming data. ANASIS cannot fully support ALL-IP communications due to its long propagation delay. The next generation satellite communication system is being designed to overcome the limitation. Next generation satellite communications system considers both high-speed and low-speed networks to support various operating environment. The low-speed satellite supports both broadband and narrow-band communication. This network works as the infrastructure for of wide-area internetworking over multiple AS's in the terrestrial network. It requires minimum satellite frequency and minimum power and works without PEP and router. In this paper, we propose a network operation structure to enable the inter-operation between high and low-speed satellite networks. In addition, we propose a data link protocol for low speed satellite networks.

• Korean Journal of Remote Sensing
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• v.34 no.6_1
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• pp.847-855
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• 2018

GMTI (Ground Moving Target Indicator) is a kind of airborne radar function that is used widely in military applications to detect the moving targets on the ground. In this paper, GMTI signal processing technique was presented and its performance was verified using sum and difference channels raw data obtained by the captive flight test.

• Annual Conference of KIPS
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• 2022.11a
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• pp.905-907
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• 2022

악성코드를 분석하는 기존 기법인 정적분석은 빠르고 효율적으로 악성코드를 탐지할 수 있지만 난독화된 파일에 취약한 반면,, 동적분석은 난독화된 파일에 적합하지만 느리고 비용이 많이 든다는 단점을 가진다. 본 연구에서는 두 분석 기법의 단점을 해결하기 위해 딥러닝 모델을 활용한 난독화에 강한 정적분석 모델을 제안하였다. 본 연구에서 제안한 방법은 원본 코드 및 난독화된 파일을 grayscale 이미지로 변환하여 데이터셋을 구축하고 AutoEncoder 를 사전학습시켜 encoder 가 원본 파일과 난독화된 파일로부터 원본 파일의 특징을 추출할 수 있도록 한 이후, encoder 의 output 을 fully connected layer 의 입력으로 넣고 전이학습시켜 악성코드를 탐지하도록 하였다. 본 연구에서는 제안한 방법론은 난독화된 파일에서 악성코드를 탐지하는 성능을 F1 score 기준 14.17% 포인트 향상시켰고, 난독화된 파일과 원본 파일을 전체를 합친 데이터셋에서도 악성코드 탐지 성능을 F1 score 기준 7.22% 포인트 향상시켰다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.73-75
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• 2022

본 논문에서는 자율운항선박의 예측 가능한 운항 경로 상에 잠재된 비상상황을 인식하기 위하여 운항 해역의 항적 정보를 활용한 방안과 이를 기반으로 충돌 위험과 같은 비상위험을 식별하는 프레임워크를 설계하였다. 설계한 프레임워크는 크게 항적 특성 분석 모듈, 항로예측 모듈, 위험 식별 모듈로 구성된다. 항적 특성 분석 모듈에서는 자율운항선박의 운항 해역에 관한 선박들의 항적 정보를 활용하기 위하여, 대상 VTS 관제 영역 내에서 취합된 누적 선박자동식별장치(AIS) 데이터를 이용하여 선박의 항적 특성을 분석하여 데이터베이스(DB)를 생성하였다. 그리고 운항 경로 예측 모듈에서는 누적된 항적 정보와 자율운항선박의 현재 운항 정보를 기반으로 특정 시간 동안의 운항 경로를 예측하기 위한 학습 네트워크 모델을 구성하였다. 마지막으로, 위험 식별 모듈에서는 예측한 운항 경로 상에 최근접점과 최근접점 거리 정보를 이용하여 충돌 위험 가능성이 있는 충돌위험영역을 식별하였다. 설계한 프레임워크는 자율운항선박의 육상 관제소에서 원격 제어를 통해 위험상황을 인지하고 회피할 수 있는 정보를 제공할 수 있음을 실제 항적 데이터를 활용하여 그 결과를 검증하였다.

• Annual Conference of KIPS
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• 2023.11a
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• pp.23-26
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• 2023

본 논문에서는 서술형 수학 문제 풀이 모델의 숫자 대소관계 파악을 위한 명시적 자질추출방식 Explicit Feature Extraction(EFE) Reasoner 모델을 제안한다. 서술형 수학 문제는 자연현상이나 일상에서 벌어지는 사건을 수학적으로 기술한 문제이다. 서술형 수학 문제 풀이를 위해서는 인공지능 모델이 문장에 함축된 논리를 파악하여 수식 또는 답을 도출해야 한다. 때문에 서술형 수학 문제 데이터셋은 인공지능 모델의 언어 이해 및 추론 능력을 평가하는 지표로 활용되고 있다. 기존 연구에서는 문제를 이해할 때 숫자의 대소관계를 파악하지 않고 문제에 등장하는 변수의 논리적인 관계만을 사용하여 수식을 도출한다는 한계점이 존재했다. 본 논문에서는 자연어 이해계열 모델 중 SVAMP 데이터셋에서 가장 높은 성능을 내고 있는 Deductive-Reasoner 모델에 숫자의 대소관계를 파악할 수 있는 방법론인 EFE 를 적용했을 때 RoBERTa-base 에서 1.1%, RoBERTa-large 에서 2.8%의 성능 향상을 얻었다. 이 결과를 통해 자연어 이해 모델이 숫자의 대소관계를 이해하는 것이 정답률 향상에 기여할 수 있음을 확인한다.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.475-480
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• 2021

With the rapid development of mobile, cloud computing technology and social network services, we are in the flood of huge data and realize that these large-scale data contain very precious value and important information. Big data, however, have both latent useful value and critical risks, so, nowadays, a lot of researches and applications for big data has been executed actively in order to extract useful information from big data efficiently and make the most of the potential information effectively. At this moment, the data analysis technique that can extract precious information from big data efficiently is the most important step in big data computing process. In this study, we investigate various data analysis techniques that can extract the most useful information in big data computing process efficiently, compare pros and cons of those techniques, and propose proper data analysis method that can help us to find out the best solution of the big data analysis in the peculiar situation.