• Proceedings of the Korean Nuclear Society Conference
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• 1998.05a
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• pp.789-794
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• 1998

중대사고 해석 전산 코드 국산화의 필요성이 대두되고 있는 이때 우리가 개발해야 할 코드의 요건을 다음 여섯 가지로 정리하였다: 1) 종합적인 해석 코드. 2) 1차계통과 격납건물 모사 능력의 유연성, 3) 자세한 발전소 거동 모사, 4) 사용자 편의성, 5) 개선 및 새로운 모델 접목의 용이성. 그리소 6) 최신 모델 포함. 이런 관점에서 기존의 중대사고 해석코드를 분석한 결과 코드 개발의 기준 코드로 MELCOR를 선정하였다. MELCOR는 계통 모사의 유연성 때문에 상용 발전소 뿐만 아니라 앞으로 개발 계획 중인 차세대나 중소형 원자로까지도 확장이 가능하며, 상세한 열수력 기본 지배 방정식을 활용하고. 모델 분석 및 개선에 필요한 코드에의 자유로운 접근이 허용되며, 지속적인 코드 개선이 이루어져 최신 모델을 보유하고 있다. 이미 MELCOR는 상당한 수준의 결과를 예측하고 있기만. 노심 손상 모델을 개선하고 격납건물 안에서의 주요 현상 모사 모델을 추가하며. 또한 국내에서 이루어지고 있는 SONATA 실험이나 증기 폭발 실험 결과들을 MELCOR에 반영하는 것이 가급적 짧은 시간에 기술 자립을 이를 수 있는 방법으로 판단된다.

• Journal of Advanced Navigation Technology
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• v.14 no.5
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• pp.684-690
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• 2010

Recently, the NG(Next Generation) system is studied for supporting convergence of various services and multi mode of single terminal. And a demand of user for taking the various services is getting increased, for supporting these services, many systems being able to transmit a large message have been appeared. In the NG system, it has to be supporting the CDMA and WCDMA besides the tele communication systems using OFDM method with single terminal An intergrated system can be improved with adopting of SoC technique. For adopting SoC technique on the intergrated terminal, we have to solve the non linear problem of HPA(High Power Amplifier). Nonlinear characteristic of HPA distorts both amplitude and phase of transmit signal, this distortion cause deep adjacent channel interference. We adopt a polynomial pre-distortion technique for this problem. In this paper, a noble modem design for NG mobile communication service and a method using polynomial pre-distorter with PAPR technique for counterbalancing nonlinear characteristic of the HPA are proposed.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04a
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• pp.683-685
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• 2003

차세대 전자상거래 기술로 인정되고 있는 기업간 워크플로우(Cross-Organizational Workflow)기술의 핵심인 기업간 워크플로우 모델과 그의 효율적인 운영환경을 제공하는 것은 국내외적으로 주목을 받고 있는 연구개발 분야이며. 효과적인 워크플로우 모델링 기법에 대한 필요성은 날로 증가하고 있다. 이에 본 논문에서는 각 조직에서 실제로 액티비티를 수행하는 참여자 또는 관리자들이 협업을 통한 스윔레인(Swimlane) 모델로 워크플로우 프로세스를 정의하는 방법론을 제안한다. 협동 스윔레인 워크플로우 모델에서는 비즈니스 프로세스의 각 엑티비티를 먼저 정의하고, 각 엑티비티로 구성되는 전체 글로벌 프로세스를 정의하게 되는Fragment-driven 방식의 모델을 사용한다. 또한, 프로세스 정의 시에 각 엑티비티를 수행하게 되는 조직 또는 롤의 그룹이 직접적으로 참여함으로써 보다 거대하고 복잡한 프로세스를 정의하는데 있어서 협업을 통한 효율성과 각 조직들의 독립성을 꾀한다.

• Journal of The Korean Association of Information Education
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• v.14 no.2
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• pp.165-174
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• 2010

The digital textbook project which embarked by the Ministry of Education, Science and Technology has focused on experiments and practices from the school designated by the government. However the previous research about digital textbook provides static interaction models and teaching-learning models analogous to web-based learning based desktop PC even the framework of the digital textbook is based of Tablet PC. This paper provides learning and teaching models for next generation digital textbook which based digital inking techinques for sketcth interface and AR(augmented reality) interactions between teacher and learner. The proposed method of this paper is applied to educational contents and we found positive effect which is supported by statistical experiments. The results of this study in the future and the future development of digital textbooks in effect will be an effective development plan.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.4
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• pp.7-17
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• 2019

Machine learning is one of the most accurate techniques to predict and analyze various phenomena. K-means clustering is a kind of machine learning technique that classifies given data into clusters of similar data. Because it is desirable to perform an analysis based on a lot of data for better performance, K-means clustering can be performed in a model with a server that calculates the centroids of the clusters, and a number of clients that provide data to server. However, this model has the problem that if the clients' data are associated with private information, the server can infringe clients' privacy. In this paper, to solve this problem in a model with a number of clients, we propose a privacy-preserving K-means clustering method that can perform machine learning, concealing private information using homomorphic encryption.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.5
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• pp.53-63
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• 2019

To provide a hand gesture interface through deep learning in mobile environments, research on the light-weighting of networks is essential for high recognition rates while at the same time preventing degradation of execution speed. This paper proposes a method of real-time recognition of written characters in the air using a finger on mobile devices through the light-weighting of deep-learning model. Based on the SSD (Single Shot Detector), which is an object detection model that utilizes MobileNet as a feature extractor, it detects index finger and generates a result text image by following fingertip path. Then, the image is sent to the server to recognize the characters based on the learned OCR model. To verify our method, 12 users tested 1,000 words using a GALAXY S10+ and recognized their finger with an average accuracy of 88.6%, indicating that recognized text was printed within 124 ms and could be used in real-time. Results of this research can be used to send simple text messages, memos, and air signatures using a finger in mobile environments.

• The Journal of Korean Institute of Next Generation Computing
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• v.15 no.4
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• pp.80-88
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• 2019

Software Defined Networking (SDN) is the future network paradigm of decoupling control and data functions. In SDN structure, it is hard to address scalability in case of large-scale networks because single controller managed thousands of switches in a centralized fashion. Most of previous studies have focused on horizontal scalability, where distributed controllers are assigned to network devices. However, they have abstracted the control plane and the application plane into a single controller. The layer of the common SDN architecture is divided into data plane, control plane, and application plane, but the control plane and application plane have been modeled as a single controller although they are logically separated. In this paper, we propose a analytical traffic model considering the both application plane and control plane based on queuing theory. This model can be used to address scalability issues such as controller placement problem without complicated simulations.

• Atmosphere
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• v.32 no.4
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• pp.353-365
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• 2022

This paper evaluates precipitation forecast skill of Global/Regional Integrated Model system (GRIMs) over South Korea in a boreal winter from December 2013 to February 2014. Three types of precipitation are classified based on development mechanism: 1) convection type (C type), 2) low pressure type (L type), and 3) orographic type (O type), in which their frequencies are 44.4%, 25.0%, and 30.6%, respectively. It appears that the model significantly overestimates precipitation occurrence (0.1 mm d^-1) for all types of winter precipitation. Objective measured skill scores of GRIMs are comparably high for L type and O type. Except for precipitation occurrence, the model shows high predictability for L type precipitation with the most unbiased prediction. It is noted that Equitable Threat Score (ETS) is inappropriate for measuring rare events due to its high dependency on the sample size, as in the case of Critical Success Index as well. The Symmetric Extreme Dependency Score (SEDS) demonstrates less sensitivity on the number of samples. Thus, SEDS is used for the evaluation of prediction skill to supplement the limit of ETS. The evaluation via SEDS shows that the prediction skill score for L type is the highest in the range of 5.0, 10.0 mm d^-1 and the score for O type is the highest in the range of 1.0, 20.0 mm d^-1. C type has the lowest scores in overall range. The difference in precipitation forecast skill by precipitation type can be explained by the spatial distribution and intensity of precipitation in each representative case.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.2
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• pp.102-110
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• 2017

Current word sense disambiguation techniques employ various machine learning-based methods. Various approaches have been proposed to address this problem, including the knowledge base approach. This approach defines the sense of an ambiguous word in accordance with knowledge base information with no training corpus. In unsupervised learning techniques that use a knowledge base approach, graph-based and similarity-based methods have been the main research areas. The graph-based method has the advantage of constructing a semantic graph that delineates all paths between different senses that an ambiguous word may have. However, unnecessary semantic paths may be introduced, thereby increasing the risk of errors. To solve this problem and construct a fine-grained graph, in this paper, we propose a model that iteratively constructs the graph while eliminating unnecessary nodes and edges, i.e., senses and semantic paths. The hybrid similarity estimation model was applied to estimate a more accurate sense in the constructed semantic graph. Because the proposed model uses BabelNet, a multilingual lexical knowledge base, the model is not limited to a specific language.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.9B
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• pp.760-773
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• 2003

The Internet is evolving from best-effort service toward an integrated or differentiated service framework with quality-of-service (QoS) assurances that are required for new multimedia service applications. Given this increasing demand for high bandwidth Internet with QoS assurances in the coming years, an IP/MPLS-based control plane combined. with a wavelength-routed dense-wavelength division multiplexing (DWDM) optical network is seen as a very promising approach for the realization of future re-configurable transport networks. This paper proposes a differentiated lambda establishment process for QoS guarantees based on the differentiated MPLS service (DMS) model. According to the QoS characteristics of wavelength in optical links and the type of used Optical Cross-Connect (OXC) nodes in DWDM next generation optical Internet backbone network, a differentiated wavelength assignment strategy that considers QoS recovery capability is also suggested.