• Journal of Korea Water Resources Association
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• v.40 no.7
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• pp.545-554
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• 2007

This study characterized the storm events recorded in the Annals of Chosun Dynasty and evaluated them using a simple rectangular pulses Poisson process model. Storm events without in detail explanation like Keun-Bi (big rain) were found to have rather short return periods compared to the storm events with lengthy explanation about damages like Keun-Mul (high water), Hong-Soo (flood), and Pok-Woo (torrential rain). Not all storm events recorded were the size of annual maxima, so their return periods were found not to be higher than a certain level. Another noticeable fact is that these storm events recorded seem more sensitive to the storm duration rather than the storm intensity. That is, most storms recorded seem to be focused on long durations rather than high intensities. Those storm events with long durations must have caused serious flood damages, which maybe the critical reason why they were recorded.

• Journal of the Korea Convergence Society
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• v.12 no.4
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• pp.23-30
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• 2021

An Automated Industry and Occupation Coding System assigns statistical classification code to the enormous amount of natural language data collected from people who write about their industry and occupation. Unlike previous studies that applied information retrieval, we propose a system that does not need an index database and gives proper code regardless of the level of classification. Also, we show our model, which utilized KoBERT that achieves high performance in natural language downstream tasks with deep learning, outperforms baseline. Our method achieves 95.65%, 91.51%, and 97.66% in Occupation/Industry Code Classification of Population and Housing Census, and Industry Code Classification of Census on Basic Characteristics of Establishments. Moreover, we also demonstrate future improvements through error analysis in the respect of data and modeling.

• Korean Journal of Remote Sensing
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• v.38 no.1
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• pp.83-101
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• 2022

Accurate atmospheric correction is essential for the analysis of land surface and environmental monitoring. Aerosol optical depth (AOD) information is particularly important in atmospheric correction because the radiation attenuation by Mie scattering makes the differences between the radiation calculated at the satellite sensor and the radiation measured at the land surface. Thus, it is necessary to use high-quality AOD data for an appropriate atmospheric correction of high-resolution satellite images. In this study, we examined the Second Simulation of a Satellite Signal in the Solar Spectrum (6S)-based atmospheric correction results for the Sentinel-2 images in South Korea using raster AOD (MODIS) and single-point AOD (AERONET). The 6S result was overall agreed with the Sentinel-2 level 2 data. Moreover, using raster AOD showed better performance than using single-point AOD. The atmospheric correction using the single-point AOD yielded some inappropriate values for forest and water pixels, where as the atmospheric correction using raster AOD produced stable and natural patterns in accordance with the land cover map. Also, the Sentinel-2 normalized difference vegetation index (NDVI) after the 6S correction had similar patterns to the up scaled drone NDVI, although Sentinel-2 NDVI had relatively low values. Also, the spatial distribution of both images seemed very similar for growing and harvest seasons. Future work will be necessary to make efforts for the gap-filling of AOD data and an accurate bi-directional reflectance distribution function (BRDF) model for high-resolution atmospheric correction. These methods can help improve the land surface monitoring using the future Compact Advanced Satellite 500 in South Korea.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.111-136
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• 2018

In this paper, we propose a methodology to extract answer information about queries from various types of unstructured documents collected from multi-sources existing on web in order to expand knowledge base. The proposed methodology is divided into the following steps. 1) Collect relevant documents from Wikipedia, Naver encyclopedia, and Naver news sources for "subject-predicate" separated queries and classify the proper documents. 2) Determine whether the sentence is suitable for extracting information and derive the confidence. 3) Based on the predicate feature, extract the information in the proper sentence and derive the overall confidence of the information extraction result. In order to evaluate the performance of the information extraction system, we selected 400 queries from the artificial intelligence speaker of SK-Telecom. Compared with the baseline model, it is confirmed that it shows higher performance index than the existing model. The contribution of this study is that we develop a sequence tagging model based on bi-directional LSTM-CRF using the predicate feature of the query, with this we developed a robust model that can maintain high recall performance even in various types of unstructured documents collected from multiple sources. The problem of information extraction for knowledge base extension should take into account heterogeneous characteristics of source-specific document types. The proposed methodology proved to extract information effectively from various types of unstructured documents compared to the baseline model. There is a limitation in previous research that the performance is poor when extracting information about the document type that is different from the training data. In addition, this study can prevent unnecessary information extraction attempts from the documents that do not include the answer information through the process for predicting the suitability of information extraction of documents and sentences before the information extraction step. It is meaningful that we provided a method that precision performance can be maintained even in actual web environment. The information extraction problem for the knowledge base expansion has the characteristic that it can not guarantee whether the document includes the correct answer because it is aimed at the unstructured document existing in the real web. When the question answering is performed on a real web, previous machine reading comprehension studies has a limitation that it shows a low level of precision because it frequently attempts to extract an answer even in a document in which there is no correct answer. The policy that predicts the suitability of document and sentence information extraction is meaningful in that it contributes to maintaining the performance of information extraction even in real web environment. The limitations of this study and future research directions are as follows. First, it is a problem related to data preprocessing. In this study, the unit of knowledge extraction is classified through the morphological analysis based on the open source Konlpy python package, and the information extraction result can be improperly performed because morphological analysis is not performed properly. To enhance the performance of information extraction results, it is necessary to develop an advanced morpheme analyzer. Second, it is a problem of entity ambiguity. The information extraction system of this study can not distinguish the same name that has different intention. If several people with the same name appear in the news, the system may not extract information about the intended query. In future research, it is necessary to take measures to identify the person with the same name. Third, it is a problem of evaluation query data. In this study, we selected 400 of user queries collected from SK Telecom 's interactive artificial intelligent speaker to evaluate the performance of the information extraction system. n this study, we developed evaluation data set using 800 documents (400 questions * 7 articles per question (1 Wikipedia, 3 Naver encyclopedia, 3 Naver news) by judging whether a correct answer is included or not. To ensure the external validity of the study, it is desirable to use more queries to determine the performance of the system. This is a costly activity that must be done manually. Future research needs to evaluate the system for more queries. It is also necessary to develop a Korean benchmark data set of information extraction system for queries from multi-source web documents to build an environment that can evaluate the results more objectively.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.22 no.4
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• pp.355-362
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• 2009

Many of residential buildings, which have pilotis in lower stories to meet the architectural needs, are recently constructed in Korea. Usually, infill walls located in the upper stories of these buildings may cause a soft first story, which is very weak from the earthquake resistance. In the design of the buildings, the infill walls of upper stories are usually considered as non-structural elements and thus they are not included in the analytical model. However, the infill walls may affect the seismic behavior of the residential buildings. Therefore, the differences in seismic behaviors of RC buildings with and without masonry infill walls are required to be investigated. In this study, seismic fragility analyses were performed for masonry infilled low-rise RC moment-resisting frames. And seismic behaviors of RC moment-resisting frame with/without masonry infill walls were evaluated. Two types of structural system with the same frame and different allocation of infill walls are used to evaluate the influence of masonry infill walls on seismic behavior of RC moment-resisting frames. The infill walls were modeled as bi-equivalent diagonal struts. The fragility analyses show that the seismic performance of RC moment-resisting frames with soft story is below the desirable building seismic performance level recommended by current seismic codes, indicating high vulnerability of RC moment-resisting frames with soft story.

• Journal of Energy Engineering
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• v.25 no.4
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• pp.93-102
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• 2016

Vehicle-to-Grid (V2G) system, bi-direction power trading technology, enables drivers possessing electric vehicle to sell the spare electricity charged in the vehicle to power distribution company. The drivers gain profit by charging electricity in the day time of high electricity rate. In this regard, the government is preparing the policies of building and supporting V2G infrastructure and demanding the potential consumers' preference for the V2G system. This paper attempts to analyze the consumers' preference using the data from obtained a survey of randomly selected 1,000 individuals. To this end, choice experiment, an economic technique, is employed here. The attributes considered in the study are residual amount of electricity, electricity trading hours, required plug-in time, and price measured as an amount additional to current gasoline vehicle price. The multinomial logit model, which requires the assumption of 'independence of irrelevant alternatives', is applied but the assumption could not be satisfied in our data. Thus, we finally utilized nested logit model which does not require the assumption. All the parameter estimates in the utility function are statistically significant at the 10% level. The estimation results show that the marginal willingness to pay (MWTP) for one hour increase in electricity trading hours is estimated to be KRW 1,601,057. On the other hand, a one percent reduction in residual amount of electricity and one hour reduction in required plug-in time in V2G system are computed to be KRW -91,911 and -470,619, respectively. The findings can provide policy makers with useful information for decision-making about introducing and managing V2G system.

• Journal of Acupuncture Research
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• v.21 no.4
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• pp.177-196
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• 2004

Objective : Rheumatoid arthritis is an autoimmune disease that pathogenesis is not fully understood and one of the most intractable musculoskeletal diseases. The concern in the immunopathogenesis of rheumatoid arthritis has been increased since 1980's and many immunotherapeutic agents including disease-modifying antirheumatic drugs (DMARDs) were developed and became the mainstay of treatment of rheumatoid arthritis. However, the cure of the disease has hardly been achieved. In oriental medicine, rheumatoid arthritis is related to Bi-Zheng(痺證), that presents pain, swelling, andlor loss of joint function as major clinical manifestations, and also known to be deeply involved in suppression of immune function related to weakness of Jung-Ki(正氣). The herbal medicine, empirically used, could be a potential resource of development of new immunotherapeutic agents for rheumatoid arthritis. Methods : We developed a search strategy using terms to include "rheumatoid arthritis and herbal medicine" combined with "Chinese medicine" and/or "Oriental medicine". The search was focused on experimental studies of herbal medicine (January 1999 to May 2004), which is known to have effects on immune function of patients with rheumatoid arthritis. Computerized search used Internet databases including KISS and RISS4U (Korea), CNKI (China), MOMJ (Main Oriental Medicine Journal, Japan), and PubMed. The articles were selected from journals of universities or major research institutes. Results : The literature search for experimental studies on effects of herbal medicine on immunity of rheumatoid arthritis retrieved a total of 21 articles (Korea; 8, China ; 12, Japan ; 1). Of 21 articles, 10 were related to single-drug formula, 2 to drug interaction, and 9 to multi-drug formula. Single-drug formula was mainly used for aqua-acupuncture and researches on active components. Studies of drug interaction emphasized harmony of Ki-Hyul(氣血) and balance of Han-Yeul(寒熱). Multi-drug regimen was mainly found among formulas for Bo-Ki-Hyul(補氣血) and Bo-Sin(補腎). Conclusion : Studies on rheumatoid arthritis were performed both in vitro and in vivo in vitro study, LPS-stimulated splenocytes and synoviocytes were treated with herbal medicine, resulting in proliferation and activation of immune cells and suppression of cytokine activities in vivo study CIA animal model demonstrated that herbal medicine decreased antibody production and improved function of immune cells. In cellular and molecular study herbal medicine showed profound effects on the level of mRNA expression of certain cytokines related to immune function. This study revealed that herbal medicine has significant immune modulatory action and could be used for recovery of immune dysfunction of rheumatoid arthritis patients.