• Proceedings of the Zoological Society Korea Conference
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• 2001.10a
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• pp.233.2-233
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• 2001

No Abstract, See Full Text

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.12
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• pp.1690-1696
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• 2014

Network RTK generates spatial corrections by using differenced measurements from reference stations in the network, and the corrections are then provided to a rover. The rover, generally, uses linear interpolation, which assumes that the corrections at each reference station are spatially correlated, to obtain a precise correction of its location. However, an irregularity of the tropospheric delay is a real-world factor that violates this assumption. Tropospheric delay is a result of weather conditions, such as humidity, temperature and pressure, and it can cause spatial decorrelation when there are changes in the local climate. In this paper, we have defined the non-linear characteristics of the tropospheric delay between reference stations or user within a region as the "irregularity of tropospheric delay". Such an irregularity can negatively impact the network RTK performance. Therefore, we analyze the influence of the irregularity of tropospheric delay in network RTK based on meteorological data.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.251-254
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• 2006

A precise real-time method of using the IGS ultra rapid products (IGU) and the GPS broadcast ephemeris to calculate the VRS orbit corrections was presented here which was suited for GPS/VRS reference station network based positioning. Test data acquired from both the SGRSN (Sichuan GPS Reference Station Network) and SCIGN (Southern California integrated GPS network) were used to evaluate the performance of the modeling techniques. The new method was proven to be more precise and reliable compared with the existing conventional network-based orbit error interpolation method. It was shown that 0.004ppm relative accuracy was reached, namely the influence from the orbit bias for the RTK positioning within 100km area can be of sub-millimeter level.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4684-4692
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• 2022

Radionuclide identification is an important part of the nuclear material identification system. The development of artificial intelligence and machine learning has made nuclide identification rapid and automatic. However, many methods directly use existing deep learning models to analyze the gamma-ray spectrum, which lacks interpretability for researchers. This study proposes an explainable radionuclide identification algorithm based on the convolutional neural network and class activation mapping. This method shows the area of interest of the neural network on the gamma-ray spectrum by generating a class activation map. We analyzed the class activation map of the gamma-ray spectrum of different types, different gross counts, and different signal-to-noise ratios. The results show that the convolutional neural network attempted to learn the relationship between the input gamma-ray spectrum and the nuclide type, and could identify the nuclide based on the photoelectric peak and Compton edge. Furthermore, the results explain why the neural network could identify gamma-ray spectra with low counts and low signal-to-noise ratios. Thus, the findings improve researchers' confidence in the ability of neural networks to identify nuclides and promote the application of artificial intelligence methods in the field of nuclide identification.

• KNOM Review
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• v.22 no.2
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• pp.1-11
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• 2019

The paradigm of science and technology and R&D system changes from the existing form of independent research to community research which transmits and stores large-capacity data generated from observation and experiment to the research site through a high-speed network. Network-dependent advanced research is improves form of collaboration, sharing, globalization. For this purpose, not only the integration of science and IT technology, but also the optimized network infrastructure and technology for real-time sharing of the enormous data is necessary. This paper explains the direction of change through the case of KREONET's network-dependent advanced research and analyzes the technology and network resources supported in each research field. Through this, we propose a network optimization model for each advanced research field with the main data flow and satisfy the network required performance by advanced applications on KREONET.

• 한국정보통신설비학회:학술대회논문집
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• 2004.08a
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• pp.234-236
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• 2004

현재 전화국 통신 시설물에 대한 상면 배치 및 배선의 설계와 공사 업무의 관리는 2차원 도면 설계 툴과 별도의 물자 산출 툴에 의해 수행되고 있다. 사용자 편의를 고려한 3차원 도면 설계 툴이 있기는 하지만 통신 시설물 공사에 최적화된 툴은 없으며 주로 기계 설계나 금형 설계 작업에서 부분적으로 사용되고 있는 실정이다. 본 논문에서는 실제 환경에 가까운 3차원 그래픽 사용자 인터페이스에 의한 도면 설계 기능, 설계된 도면 DB와 물자 단가 DB의 연동을 통한 소요 물자의 자동 산출 기능 등을 수행하는 시스템 모델의 개념을 제시하고 개발 현황을 소개하고자 한다. 본 논문에서 소개된 시스템을 통해 전화국 통신 시설물에 대한 설계와 공사 업무의 편리화, 자동화, 일원화를 이룰 수 있을 것이다.

• Perspectives in Nursing Science
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• v.16 no.1
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• pp.12-24
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• 2019

Purpose: This study examined the suitability of using text network analysis (TNA) methodology for topic analysis of academic papers related to nursing. Methods: TNA background theories, software programs, and research processes have been described in this paper. Additionally, the research methodology that applied TNA to the topic analysis of the academic nursing papers was analyzed. Results: As background theories for the study, we explained information theory, word co-occurrence analysis, graph theory, network theory, and social network analysis. The TNA procedure was described as follows: 1) collection of academic articles, 2) text extraction, 3) preprocessing, 4) generation of word co-occurrence matrices, 5) social network analysis, and 6) interpretation and discussion. Conclusion: TNA using author-keywords has several advantages. It can utilize recognized terms such as MeSH headings or terms chosen by professionals, and it saves time and effort. Additionally, the study emphasizes the necessity of developing a sophisticated research design that explores nursing research trends in a multidimensional method by applying TNA methodology.

• Journal of the Korea Society of Computer and Information
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• v.24 no.7
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• pp.135-141
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• 2019

The purpose of this study is to extract the key words from the list of research subjects related to 'hotel workers' published in recent 10 years(2009~2018) by using the language network analysis method and to confirm the relation between the key words. In this paper, we propose a semantic network analysis that can overcome limitations of longitudinal study, analyze the recent research trends, and widely use as a research model. The results of this study are as follows ; First, in analyzing major key words in the title of 'Hotel Employer' in recent 10 years, the major keyword of job satisfaction(40), special grade(26), organizational commitment(20), emotional labor(19), service(12), restaurant(10), and turnover intention(9). Second, we analyzed the relation of language network among major key words extracted from the study title of 'hotel workers'. Such a research process is expected to grasp the trends of research related to 'hotel workers' and give implications for the future direction of related research.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.4
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• pp.269-284
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• 2022

Exploring research similarity of researchers offers insight on research communities and potential interactions among scholars. While co-authorship is a popular measure for studying research similarity of researchers, it cannot provide insight on authors who have not collaborated yet. In this work, we present novel approach to capture research similarity of authors using citation information. Extensive study is conducted on DATA & KNOWLEDGE ENGINEERING (DKE) publications to demonstrate and compare suggested approach with co-authorship based approach. Analysis result shows that proposed approach distinguishes author relationships that is not shown in co-authorship network.

• KNOM Review
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• v.22 no.2
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• pp.39-47
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• 2019

There are several big data-driven advanced research activities such as meteorological climate information, high energy physics, astronomy research, satellite information data, and genomic research data on KREONET. Since the performance degradation occurs in the environment with the existing network security equipment, methods for preventing the performance degradation on the high-performance research-only network and for high-speed research collaboration are being studied. In addition, the recent issue of quantum computers has been a threat to security using the existing encryption system. In this paper, we construct quantum cryptography-based communication network through environment construction and high-performance transmission test that build physical security through quantum cryptography-based communication network in end-to-end high-speed research network. The purpose of this study is to analyze the effect on network performance when performing physical encryption and to use it as basic data for constructing high-performance research collaboration network.