• Bulletin of the Korean Space Science Society
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• 2003.10a
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• pp.62-62
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• 2003

과학위성 1호에는 위성의 임무를 수행하기 위하여 광학계, 구조부, 및 전자부 등 여러가지 부품들이 실장되는데, 그 중 전자부의 가장 중요한 부품 중의 하나인 인쇄회로기판(Printed Circuit Board, PCB)의 우주환경에서의 특성 대해서 논의하고자 한다. Solder Resistor(Solder Mask)의 화학성분이 위성체가 작동하는 우주환경에서 위성체 임무수행 시 발생할 수 있는 out-gassing으로 인해 위성체가 본연의 임무 실패라는 결과를 초래할 수 있다 NASA 및 ESA의 Out-gassing에 관한 규정과 TRW에 의한 KOMSAT에 사용된 재료의 진공상태의 Outgassing에 관한 내용에 의하면, 재료의 진공상태와 Out-gassing은 America Society for Testing and Materials에서 제시한 ASTM E959 기준에 따라 제작된다. 일반적으로 우주 환경에서 광학계나 전자부의 원활한 동작을 위해서는 인쇄 회로 기판의 총 질량손실(Total Mass Loss, TML)은 1.00%을 넘지 말아야 하며, 휘발성 응축 질량 (Collected Volatile Condensable Mass, CVCM)은 0.1% 미만이어야 한다. Total Mass Loss(TML) 방법은 대기중에서 측정한 질량과 진공 조건에서 변화되는 질량을 측정함으로써 진공조건에서의 탈기체 특성을 측정하는 방법이다. 본 연구에서는 Solder Resistor(Solder Mask)의 탈기체 측정을 위한 진공챔버의 측정방법 및 진공 형성 과정을 기술하고 실제 과학위성1호에 장착될 시료를 예로 들어 인쇄회로기판에 입힌 Solder Resistor(Solder Mask)가 우주환경인 진공상태에서 위성체 부품의 작동 시 발생할 수 있는 탈기체되는 정도를 질량의 변화분으로 측정하여 위성체가 우주 환경에서 본연의 임무를 안전하게 수행할 있는지를 검증하였다.부분이다.다.향을 해석하고 시뮬레이션 하였다.Device Controller)는 ECU로부터 명령어를 받아서 arm 및 safe 상태에 대한 텔리 메트리 데이터를 제공한다 그리고, SAR(Solar Array Regulator)는 ECU로부터 Bypass Relay 및 ARM Relay에 관한 명령어를 받아 수행되며 그에 따른 텔리 메트리 데이터를 제공한다. 마지막으로 EPS 소프트웨어를 검증하는 EPS Software Verification을 수행하였다 전력계 소프트웨어의 설계의 검증 부분은 현재 설계 제작된 전력계 .소프트웨어의 동작 특성 이 위성 의 전체 운용개념과 연계하여 전력계 소프트웨어가 전력계 및 위성체의 요구조건을 만족시키는지를 확인하는데 있다. 전력계 운용 소프트웨어는 배터리의 충ㆍ방전을 효율적으로 관리해 3년의 임무 기간동안 위성체에 전력을 공급할 수 있도록 설계되어 있다this hot-core has a mass of 10sR1 which i:s about an order of magnitude larger those obtained by previous studies.previous studies.업순서들의 상관관계를 고려하여 보다 개선된 해를 구하기 위한 연구가 요구된다. 또한, 준비작업비용을 발생시키는 작업장의 작업순서결정에 대해서도 연구를 행하여, 보완작업비용과 준비비용을 고려한 GMMAL 작업순서문제를 해결하기 위한 연구가 수행되어야 할 것이다.로 이루어 져야 할 것이다.태를 보다 효율적으로 증진시킬 수 있는 대안이 마련되어져야 한다고 사료된다.$\ulcorner$순응$\lrcorner$의 범위를 벗어나지 않는다. 그렇기 때문에도 $\ulcorner$순응$\lrcorner$과 $\ulcorner$표현$\lrcorner$의 성격과 형태를 외형상으로

• Journal of radiological science and technology
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• v.26 no.1
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• pp.71-82
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• 2003

In this paper, I proposed a classifier of liver cirrhotic step using T1-weighted MRI(magnetic resonance imaging) and hierarchical neural network. The data sets for classification of each stage, which were normal, 1type, 2type and 3type, were obtained in Pusan National University Hospital from June 2001 to december 2001. And the number of data was 46. We extracted liver region and nodule region from T1-weighted MR liver image. Then objective interpretation classifier of liver cirrhotic steps in T1-weighted MR liver images. Liver cirrhosis classifier implemented using hierarchical neural network which gray-level analysis and texture feature descriptors to distinguish normal liver and 3 types of liver cirrhosis. Then proposed Neural network classifier teamed through error back-propagation algorithm. A classifying result shows that recognition rate of normal is 100%, 1type is 82.3%, 2type is 86.7%, 3type is 83.7%. The recognition ratio very high, when compared between the result of obtained quantified data to that of doctors decision data and neural network classifier value. If enough data is offered and other parameter is considered, this paper according to we expected that neural network as well as human experts and could be useful as clinical decision support tool for liver cirrhosis patients.

• Horticultural Science & Technology
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• v.34 no.2
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• pp.324-330
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• 2016

To determine whether FT-IR spectral analysis based on multivariate analysis for whole cell extracts can be used to discriminate between artichoke (Cynara cardunculus var. scolymus L.) plants at the metabolic level, leaves of ten artichoke plants were subjected to Fourier transform infrared(FT-IR) spectroscopy. FT-IR spectral data from leaves were analyzed by principal component analysis (PCA), partial least square discriminant analysis (PLS-DA) and hierarchical clustering analysis (HCA). FT-IR spectra confirmed typical spectral differences between the frequency regions of 1,700-1,500, 1,500-1,300 and $1,100-950cm^{-1}$, respectively. These spectral regions reflect the quantitative and qualitative variations of amide I, II from amino acids and proteins ($1,700-1,500cm^{-1}$), phosphodiester groups from nucleic acid and phospholipid ($1,500-1,300cm^{-1}$) and carbohydrate compounds ($1,100-950cm^{-1}$). PCA revealed separate clusters that corresponded to their species relationship. Thus, PCA could be used to distinguish between artichoke species with different metabolite contents. PLS-DA showed similar species classification of artichoke. Furthermore these metabolic discrimination systems could be used for the rapid selection and classification of useful artichoke cultivars.

• Journal of KIISE
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• v.44 no.8
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• pp.803-812
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• 2017

T-commerce is technology-fusion service on which the user can purchase using data broadcasting technology based on bi-directional digital TVs. To achieve the best revenue under a limited environment in regard to the channel number and the variety of sales goods, organizing broadcast programs to maximize the expected sales considering the selling power of each product at each time slot. For this, this paper proposes a method to predict the sales of goods when it is assigned to each time slot. The proposed method predicts the sales of product at a time slot given the week-in-year and weather of the target day. Additionally, it combines a statistical predict model applying SVD (Singular Value Decomposition) to mitigate the sparsity problem caused by the bias in sales record. In experiments on the sales data of W-shopping, a T-commerce company, the proposed method showed NMAE (Normalized Mean Absolute Error) of 0.12 between the prediction and the actual sales, which confirms the effectiveness of the proposed method. The proposed method is practically applied to the T-commerce system of W-shopping and used for broadcasting organization.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.7
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• pp.843-856
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• 2023

The global surge in maritime traffic has resulted in an increased number of ship collisions, leading to significant economic, environmental, physical, and human damage. The causes of these maritime accidents are multifaceted, often arising from a combination of crew judgment errors, negligence, complexity of navigation routes, weather conditions, and technical deficiencies in the vessels. Given the intricate nuances and contextual information inherent in each incident, a methodology capable of deeply understanding the semantics and context of sentences is imperative. Accordingly, this study utilized the SentenceBERT model to analyze maritime safety tribunal decisions over the last 20 years in the Busan Sea area, which encapsulated data on ship collision incidents. The analysis revealed important keywords potentially responsible for these incidents. Cluster analysis based on the frequency of specific keyword appearances was conducted and visualized. This information can serve as foundational data for the preemptive identification of accident causes and the development of strategies for collision prevention and response.

• Journal of the Korean Society for Library and Information Science
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• v.56 no.4
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• pp.491-514
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• 2022

Public reforms based on New Public Management have made the public sector specialized, and accordingly the role of public administration has expanded as well as the demand on professional jobs has increased. On the other hand, with the rapid development of information and communication technology, the data produced by public sector organizations has also significantly increased. This environmental changes made data management and a data management job in the public sector critical. However, there have been very few studies of conceptualizations and systematic investigations on data management jobs. Moreover, specific definitions, types or qualifications of/for a data management job or a person who do this job are rarely reflected in relevant laws and regulations. Based on the systematic literature review, this study conceptualized professionalism, identified its multiple dimensions, and draw a conceptual research framework. Focusing on the professional control on personnel management which is one of the dimensions of professionalism, relevant laws, work guidelines and job descriptions included in job openings were analyzed with regard to a data management job in the public sector. The findings are as follows. First, an assigned role and responsibility associated with a data management job have vague boundaries. Second, work guidelines and manuals only focus on the post quality control stage rather than equally addressing all the eight stages of the data lifecycle. Third, neither a data management job in the public sector nor a person who take care of this job is not appropriately defined. Therefore, a role and responsibility of/for the job and a person in charge should be reflected in the relevant laws and guidelines in a tailored way. More importantly, job analyses and evaluations should be thoroughly conducted to enhance professionalism on data management jobs in the long term.

• Korean Journal of Heritage: History & Science
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• v.57 no.1
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• pp.82-108
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• 2024

With the transition of archaeological recording method's transition from analog to digital, the 3D scanning technology has been actively adopted within the field. Research on the digital archaeological digital data gathered from 3D scanning and photogrammetry is continuously being conducted. However, due to cost and manpower issues, most buried cultural heritage organizations are hesitating to adopt such digital technology. This paper aims to present a digital recording method of relics utilizing open-source software and photogrammetry technology, which is believed to be the most efficient method among 3D scanning methods. The digital recording process of relics consists of three stages: acquiring a 3D model, creating a joining map with the edited 3D model, and creating an digital drawing. In order to enhance the accessibility, this method only utilizes open-source software throughout the entire process. The results of this study confirms that in terms of quantitative evaluation, the deviation of numerical measurement between the actual artifact and the 3D model was minimal. In addition, the results of quantitative quality analysis from the open-source software and the commercial software showed high similarity. However, the data processing time was overwhelmingly fast for commercial software, which is believed to be a result of high computational speed from the improved algorithm. In qualitative evaluation, some differences in mesh and texture quality occurred. In the 3D model generated by opensource software, following problems occurred: noise on the mesh surface, harsh surface of the mesh, and difficulty in confirming the production marks of relics and the expression of patterns. However, some of the open source software did generate the quality comparable to that of commercial software in quantitative and qualitative evaluations. Open-source software for editing 3D models was able to not only post-process, match, and merge the 3D model, but also scale adjustment, join surface production, and render image necessary for the actual measurement of relics. The final completed drawing was tracked by the CAD program, which is also an open-source software. In archaeological research, photogrammetry is very applicable to various processes, including excavation, writing reports, and research on numerical data from 3D models. With the breakthrough development of computer vision, the types of open-source software have been diversified and the performance has significantly improved. With the high accessibility to such digital technology, the acquisition of 3D model data in archaeology will be used as basic data for preservation and active research of cultural heritage.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1491-1506
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• 2021

To estimate errors in GEMS retrievals for bromine monoxide (BrO) total vertical column densities(VCDs), we perform a sensitivity test using synthetic spectra generated by a radiative transfer model. Hourly synthetic data are produced for 00-07 UTC on the first day of every month in Jul 2013- Jun 2014. Solution errors estimated by the optimal estimation method tend to decrease with increasing air mass factors (AMFs) but increase when AMFs are larger than 5. Interference errors induced by formaldehyde (HCHO) absorption appear to be larger with smaller BrO AMFs. Total BrO retrieval errors estimated by combining solution and interference errors show an average of 26.74±30.18% for all data samples and 60.39±133.78% for those with solar zenith angles higher than 80°. Due to interfering spectral features and measurement errors not considered in thisstudy, errorsin BrO retrievals from actual GEMS measurements may have different magnitudes from our estimates. However, the variability of errors assessed in this study is still expected to appear in the actual BrO retrievals.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.212-220
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• 2021

National R&D investment has steadily increased, reaching number 5 in the world as of 2018. However, for public technology commercialization, the level of discovery of policy models through various cooperation initiatives between government ministries is insufficient, and the performance system that can spread technology commercialization is also limited. In this respect, in order to create results in public technology commercialization, it is necessary to prepare alternatives to strengthen multi-ministerial policy cooperation and increase policy execution power. In this paper, we analyzed the current state of national R&D projects by major ministries and suggested an optimized technology commercialization plan through analysis of the structure, budget, and form of each project. In particular, an alternative in terms of policy efficiency was suggested by analyzing the problems of policy discovery that have not been studied previously. This study is of great significance in that it diagnosed problems of public technology commercialization in terms of the lack of systematic research on public technology commercialization and suggested policy advancement for the spread of technology use and the strategic direction in terms of commercialization.

• Journal of The Korean Society of Grassland and Forage Science
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• v.41 no.4
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• pp.287-294
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• 2021

The objective of this study was conducted to calculate the damage of whole crop maize in accordance with abnormal climate using the forage yield prediction model through machine learning. The forage yield prediction model was developed through 8 machine learning by processing after collecting whole crop maize and climate data, and the experimental area was selected as Gyeonggi-do. The forage yield prediction model was developed using the DeepCrossing (R²=0.5442, RMSE=0.1769) technique of the highest accuracy among machine learning techniques. The damage was calculated as the difference between the predicted dry matter yield of normal and abnormal climate. In normal climate, the predicted dry matter yield varies depending on the region, it was found in the range of 15,003~17,517 kg/ha. In abnormal temperature, precipitation, and wind speed, the predicted dry matter yield differed according to region and abnormal climate level, and ranged from 14,947 to 17,571, 14,986 to 17,525, and 14,920 to 17,557 kg/ha, respectively. In abnormal temperature, precipitation, and wind speed, the damage was in the range of -68 to 89 kg/ha, -17 to 17 kg/ha, and -112 to 121 kg/ha, respectively, which could not be judged as damage. In order to accurately calculate the damage of whole crop maize need to increase the number of abnormal climate data used in the forage yield prediction model.