• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.2
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• pp.125-132
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• 2015

This paper is about analysis of UDRE monitoring method for Korean Satellite navigation system, which is the correction parameter of satellite measurements. New receiver clock bias and tropospheric delay error estimation method to make pseudo-range residual for UDRE monitoring is proposed. Saastamoinen model and Neill mapping function are used for estimate the tropospheric delay and EKF is used for estimgate the receiver clock bias. Through the satellite measurements and regional weather data received directly from the domestic is using for UDRE monitoring analysis, more suitable UDRE monitoring threshold can be deducted and it is expected to be utilized for fault detection technique of Korean Satellite Navigation System.

• Journal of KIISE:Computing Practices and Letters
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• v.8 no.5
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• pp.501-509
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• 2002

SGML(ISO 8879) has been proliferated to support various document styles and to transfer documents into different platforms. SGML documents have logical structure information in addition to contents. As SGML documents are widely used, there is an increasing need for database storage and retrieval system using the logical structure of documents. However. traditional search engines using document indexes cannot exploit the logical structure. In this Paper, we have developed an SGML document storage system, which is DTD-independent and store the document type and the document instance separately by using Grove which is the document model for DSSSL and HyTime. We have used the Object Store, an object-oriented DBMS, to store the structure information appropriately without any loss of structural information. Also, we have supported a index structure for search efficiency like the relational DBMS, and constructed an effective user interface which combines content-based search with structure-based search.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.163-171
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• 2021

In this paper, the energy transaction system was optimized by applying a resource allocation algorithm and deep reinforcement learning in the distributed power system. The power demand and supply environment were predicted by deep reinforcement learning. We propose a system that pursues common interests in power trading and increases the efficiency of long-term power transactions in the paradigm shift from conventional centralized to distributed power systems in the power trading system. For a realistic energy simulation model and environment, we construct the energy market by learning weather and monthly patterns adding Gaussian noise. In simulation results, we confirm that the proposed power trading systems are cooperative with each other, seek common interests, and increase profits in the prolonged energy transaction.

• Journal of the Korean Electrochemical Society
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• v.11 no.4
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• pp.273-283
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• 2008

GDL(Gas Diffusion Layer) is one of the main components of PEM fuel cell. It transports reactants from the channel to the catalyst and removes reaction products from the catalyst to the channels in the flow filed plate. It is known that higher permeability of GDL can make it possible to enhance the gas transport through GDL, leading to better performance. And MEA's temperature is determined by gas and heat transport. In this paper, three dimensional numerical simulation of PEM fuel cell of parallel channel and serpentine channel by the permeability of GDL is presented to analysis heat and mass transfer characteristics using a FLUENT modified to include the electrochemical behavior. Results show that in the case of parallel channel, performance variation with change of permeability of GDL was not so much. This is thought because mass transfer is carried out by diffusion mechanism in parallel channel. Also, in the case of serpentine channel, higher GDL permeability resulted in better performance of PEM fuel cell because of convection flow though GDL. And mass transfer process is changed from convection to diffusion when the permeability becomes low.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05b
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• pp.141-147
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• 1996

1979년 3월 Three Mile Island 2 (TMI-2) 발전소에서 사고가 발생했을 때 원자로용기내에 생성된 수소기체로 인하여 운전원은 원자로용기의 수위를 정확히 측정할 수 없었으며, 이로 인하여 사고상태를 신속히 파악하지 못하였다. TMI 사고이후 미국 원자력규제위원회 NRC는 이 같은 문제점을 해결하고자 미국내 모든 원전에서 사고 또는 비정상 조건이 발생할 경우에 원자로 용기 수위에 대하여 운전원이 신뢰성을 갖을 수 있는 후속조치를 수행토록 요구하였다. 또한 미국의 대표적인 전력연구소인 EFRI에서는 개량형 경수로 (Advanced Light Water Reactor : ALWR) 설계 요건으로 이러한 설계가 반영되도록 요건화 하였다.［1］. 본 논문에서는 2,825 MWt급 한국형 표준원전을 대상으로 EPRI에서 요구한 설계요건에 따라 TMI 2 발전소에서와 같은 사고로 인하여 수소기체가 발생했을 경우와 발전소가 비정상 상태로 인하여 증기가 발생했을 경우에, 이를 신속히 제거하여 운전원이 원자로용기의 수위를 정확히 감지할 수 있도록 하는 설계 방안을 검토하였다. 따라서, 설계방안으로 원자로용기에 모인 증기 또는 수소기체를 계통중 가장 높은 위치에 있으며, 계통구성 기기중 유일하게 2상을 유지하고 있는 가압기로 배출시키고자 두 기기간에 연결관을 설치하는 방안에 대해서 분석하였다. 원자로용기 상부해드와 가압기를 연결하는 방안은 여러가지가 있으나, 검토한 결과 한국형 표준원전에서는 연결관을 가압기 상부해드보다 4m 높게하여 원자로용기 상부해드와 연결하는 방안이 EPRI의 설계요건을 만족하면서 기존설계에 영향을 가장 적게 미치는 적합한 설계방안으로 분석되었다.크다는 단점이 있다.TEX>$_2$O$_3$ 흡착제 제조시 TiO$_2$ 함량에 따른 Co$^{2＋}$ 흡착량과 25$0^{\circ}C$의 고온에서 ZrO$_2$와 $Al_2$O$_3$의 표면에 생성된 코발트 화합물을 XPS와 EPMA로 부터 확인하였다.인을 명시적으로 설명할 수 있다. 둘째, 오류의 시발점을 정확히 포착하여 동기가 분명한 수정대책을 강구할 수 있다. 셋째, 음운 과 정의 분석 모델은 새로운 언어 학습시에 관련된 언어 상호간의 구조적 마찰을 설명해 줄 수 있다. 넷째, 불규칙적이며 종잡기 힘들고 단편적인 것으로만 보이던 중간언어도 일정한 체계 속에서 변화한다는 사실을 알 수 있다. 다섯째, 종전의 오류 분석에서는 지나치게 모국어의 영향만 강조하고 다른 요인들에 대해서는 다분히 추상적인 언급으로 끝났지만 이 분석을 통 해서 배경어, 목표어, 특히 중간규칙의 역할이 괄목할 만한 것임을 가시적으로 관찰할 수 있 다. 이와 같은 오류분석 방법은 학습자의 모국어 및 관련 외국어의 음운규칙만 알면 어느 학습대상 외국어에라도 적용할 수 있는 보편성을 지니는 것으로 사료된다.없다. 그렇다면 겹의문사를 [-wh]의리를 지 닌 의문사의 병렬로 분석할 수 없다. 예를 들어 누구누구를 [주구-이-ν가] [누구누구-이- ν가]로부터 생성되었다고 볼 수 없다. 그러므로 [-wh] 겹의문사는 복수 의미를 지닐 수 없 다. 그러면 단수 의미는 어떻게 생성되는가\ulcorner 본 논문에서는 표면적 형태에도 불구하고

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.195-204
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• 2023

In this study, prompt engineering that improves prompts was explored to improve the performance of teaching and learning materials recommendations using generative artificial intelligence such as GPT and Stable Diffusion. Picture materials were used as the types of teaching and learning materials. To explore the impact of the prompt composition, a Zero-Shot prompt, a prompt containing learning target grade information, a prompt containing learning goals, and a prompt containing both learning target grades and learning goals were designed to collect responses. The collected responses were embedded using Sentence Transformers, dimensionalized to t-SNE, and visualized, and then the relationship between prompts and responses was explored. In addition, each response was clustered using the k-means clustering algorithm, then the adjacent value of the widest cluster was selected as a representative value, imaged using Stable Diffusion, and evaluated by 30 elementary school teachers according to the criteria for evaluating teaching and learning materials. Thirty teachers judged that three of the four picture materials recommended were of educational value, and two of them could be used for actual classes. The prompt that recommended the most valuable picture material appeared as a prompt containing both the target grade and the learning goal.

• Journal of KIISE:Software and Applications
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• v.36 no.7
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• pp.523-530
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• 2009

Despite the growing need for customized operating system kernels for embedded devices, kernel development continues to suffer from insufficient reliability and high testing cost for several reasons such as the high complexity of the kernel code. To alleviate these difficulties, this study proposes the MOdel-based KERnel Testing (MOKERT) framework for detection of concurrency bugs in the kernel. MOKERT translates a given C program into a corresponding Promela model, and then tries to find a counter example with regard to a given requirement property, If found, MOKERT executes that counter example on the real kernel code to check whether the counter example is a false alarm or not, The MOKERT framework was applied to the Linux proc file system and confirmed that the bug reported in a ChangeLog actually caused a data race problem, In addition, a new data race bug in the Linux proc file system was found, which causes kernel panic.

• Journal of the Korea Computer Graphics Society
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• v.20 no.2
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• pp.1-11
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• 2014

The quality of 2D-to-3D conversion depends on the accuracy of the assigned depth to scene objects. Manual depth painting for given objects is labor intensive as each frame is painted. Specifically, a human is one of the most challenging objects for a high-quality conversion, as a human body is an articulated figure and has many degrees of freedom (DOF). In addition, various styles of clothes, accessories, and hair create a very complex silhouette around the 2D human object. We propose an efficient method to estimate visually pleasing depths of a human at every frame in a monocular video. First, a 3D template model is matched to a person in a monocular video with a small number of specified user correspondences. Our pose estimation with sequential joint angular constraints reproduces a various range of human motions (i.e., spine bending) by allowing the utilization of a fully skinned 3D model with a large number of joints and DOFs. The initial depth of the 2D object in the video is assigned from the matched results, and then propagated toward areas where the depth is missing to produce a complete depth map. For the effective handling of the complex silhouettes and appearances, we introduce a partial depth propagation method based on color segmentation to ensure the detail of the results. We compared the result and depth maps painted by experienced artists. The comparison shows that our method produces viable depth maps of humans in monocular videos efficiently.

• Journal of Christian Education in Korea
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• v.78
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• pp.57-85
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• 2024

Purpose of the study: In order to utilize artificial intelligence-generated AI in educational ministry, this study analyzes the concept of artificial intelligence and generative AI and the educational theological aspects of educational ministry to find ways to efficiently utilize artificial intelligence ChatGPT in educational ministry. Contents and methods of the study: The contents of this study are. First, the contents of this study were analyzed by dividing the concepts of artificial intelligence and generative AI into the concept of artificial intelligence, types of artificial intelligence, and generative language model AI ChatGPT. Second, the educational theological analysis of educational ministry was divided into the concept of educational ministry, the goals of educational ministry, the content of educational ministry, and the direction of educational ministry in the era of artificial intelligence. Third, the plan to use artificial intelligence ChatGPT in educational ministry is to provide tools for writing sermon manuscripts, preparation tools for worship and prayer, and church education, focusing on the five functions of the early church community. It was analyzed by dividing it into tools for teaching, tools for teaching materials for believers, and tools for serving and volunteering. Conclusion and Recommendation: The conclusion of this study is that, first, when writing sermon manuscripts through artificial intelligence ChatGPT, high-quality sermon manuscripts can be written through the preacher's spirituality, faith, and insight. Second, through artificial intelligence ChatGPT, you can efficiently design and plan worship services and prepare services that serve the congregation objectively through various scenarios. Third, by using artificial intelligence ChatGPT in church education, it can be used while maintaining a complementary relationship with teachers through collaboration with human and artificial intelligence teachers. Fourth, through artificial intelligence ChatGPT, we provide a program that allows members of the church community to share spiritual fellowship, a plan to meet the needs of church members and strengthen interdependence, and an attitude of actively welcoming new people and respecting diversity. It provides useful materials that can play an important role in giving, loving, serving, and growing together in the love of Christ. Lastly, through artificial intelligence ChatGPT, we are seeking ways to provide various information about volunteer activities, learning support for children and youth in the community, mentoring-related programs, and playing a leading role in forming a village community in the local community.

• Journal of Digital Convergence
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• v.11 no.4
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• pp.251-258
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• 2013

Recently companies are confronted with a much more sophisticated business environment than before and at the same time have to be able to adapt to rapid changes. Accordingly, the need for selecting among alternatives and managing systematic decision-making has been steadily increasing to respond to a more diverse customer needs and keep up with the fierce competition. In this study, we propose a framework that consist of problem solving procedures and techniques and knowledge structure built on processes to support strategic decision making. and discuss how to utilize simulation tools as the knowledge-based problem solving tools. In addition we discuss how to build and advance the knowledge structure to implement the proposed architecture. Management decision support systems architecture consist of three key factors. The first is Problem Solving Approach which is used as reference. The second is knowledge structure on business processes that includes standard and reference business processes. The third is simulators that are able to generate and analyze alternatives using problem solving techniques and knowledge base. In sum, the proposed framework of decision-making support systems facilitates knowledge-intensive consulting processes to promote the development and application of consulting knowledge and techniques and increase the efficiency of consulting firms and industry.