• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.8 no.2
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• pp.55-60
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• 2012

In many cases, geothemal wells will not be opened up a geothermal reservoir under such conditions that an extraction of geothermal energy is economically viable without any further measures. Geothermal wells often have to be stimulated, in order to increase productivity. For the non-volcanic area, such as Korea, the hydraulic stimulation is necessary to complete geothermal power plant. The analysis of induced seismic event showed that the thermal resource might have a much wider extent and a much higher generation potential than previously assumed. In order to record compressional and shear waves emitted during fracture stimulation, three-component geophones are placed in a seismometer. The recorded data from one seismometer is the convolution of the source magnitude, the transmission media, and the sensitivity of the instrument.

• The Journal of the Acoustical Society of Korea
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• v.39 no.5
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• pp.414-423
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• 2020

In this paper, we propose a Dilated Convolution Gate Linear Unit (DCGLU) to mitigate the lack of sparsity and small receptive field problems caused by the segmentation map extraction process in sound event detection with weak labels. In the advent of deep learning framework, segmentation map extraction approaches have shown improved performance in noisy environments. However, these methods are forced to maintain the size of the feature map to extract the segmentation map as the model would be constructed without a pooling operation. As a result, the performance of these methods is deteriorated with a lack of sparsity and a small receptive field. To mitigate these problems, we utilize GLU to control the flow of information and Dilated Convolutional Neural Networks (DCNNs) to increase the receptive field without additional learning parameters. For the performance evaluation, we employ a URBAN-SED and self-organized bird sound dataset. The relevant experiments show that our proposed DCGLU model outperforms over other baselines. In particular, our method is shown to exhibit robustness against nature sound noises with three Signal to Noise Ratio (SNR) levels (20 dB, 10 dB and 0 dB).

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.6
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• pp.1277-1284
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• 2023

In this paper, a web page that is easy for consumers to access event products in progress at convenience stores was created. In the production process, static crawling and dynamic crawling, two crawling methods for extracting data from event products, were compared and used. Static crawling is an extraction method of collecting static data from a homepage, and dynamic crawling is a method of collecting data from pages dynamically generated from a web page. Through the comparison of the two crawlings, we studied which crawl method is more effective in extracting event product data. Among them, a web page was created using effective static crawling, and 1+1 and 2+1 products were categorized and a search function was added to create a web page.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2003.10a
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• pp.3-3
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• 2003

With biomedical literature expanding so rapidly, there is an urgent need to discover and organize knowledge extracted from texts. Although factual databases contain crucial information the overwhelming amount of new knowledge remains in textual form (e.g. MEDLINE). In addition, new terms are constantly coined as the relationships linking new genes, drugs, proteins etc. As the size of biomedical literature is expanding, more systems are applying a variety of methods to automate the process of knowledge acquisition and management. In my talk, I focus on the project, GENIA, of our group at the University of Tokyo, the objective of which is to construct an information extraction system of protein - protein interaction from abstracts of MEDLINE. The talk includes (1) Techniques we use fDr named entity recognition (1-a) SOHMM (Self-organized HMM) (1-b) Maximum Entropy Model (1-c) Lexicon-based Recognizer (2) Treatment of term variants and acronym finders (3) Event extraction using a full parser (4) Linguistic resources for text mining (GENIA corpus) (4-a) Semantic Tags (4-b) Structural Annotations (4-c) Co-reference tags (4-d) GENIA ontology I will also talk about possible extension of our work that links the findings of molecular biology with clinical findings, and claim that textual based or conceptual based biology would be a viable alternative to system biology that tends to emphasize the role of simulation models in bioinformatics.

• Journal of information and communication convergence engineering
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• v.7 no.4
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• pp.419-430
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• 2009

Reading comprehension (RC) systems are to understand a given text and return answers in response to questions about the text. Many previous studies extract sentences that are the most similar to questions as answers. However, texts for RC tests are generally short and facts about an event or entity are often expressed in multiple sentences. The answers for some questions might be indirectly presented in the sentences having few overlapping words with the questions. This paper proposes a conceptual graph matching method towards RC tests to extract answer strings. The method first represents the text and questions as conceptual graphs, and then extracts subgraphs for every candidate answer concept from the text graph. All candidate answer concepts will be scored and ranked according to the matching similarity between their sub-graphs and question graph. The top one will be returned as answer seed to form a concise answer string. Since the sub-graphs for candidate answer concepts are not restricted to only covering a single sentence, our approach improved the performance of answer extraction on the Remedia test data.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2004.09a
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• pp.147-150
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• 2004

Firstly, the precipitation data have to be interpolated for the estimation of water resources. For this purpose, the correlative analysis is made between the topographic variables, which, influence the precipitation phenomena, are classified by elevation(ELEV), slope(SLOPE), distance to the sea(SEA), obstacle (OBST), barrier(BAR), and roughness index(SHIELD), using TOVA(Topographic Variables Extraction Program) and events precipitation during the periods from january the 1st 2000 to December 31 2002. The coefficients of determination show that each event has different topographic influence and ELEV, SLOPE and OBST to the South-West, and SHIELD of every direction have close relationship with the precipitation. The multiple regression model explains 96% of the spatial variation of precipitation.

• Annual Conference on Human and Language Technology
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• 2002.10e
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• pp.325-331
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• 2002

정보추출 시스템의 목적은 관심의 대상이 되는 특정 정보를 선택적으로 찾아내 제시하는데 있다. 따라서 도메인 정보에 의존적인 방법으로 정보추출이 이루어질 수밖에 없고, 이에 따른 도메인 정보 구축의 부담이 컸다. 이러한 부담을 줄이기 위해 본 연구에서는 특정 주제영역과 관련한 문서로부터 자동으로 이벤트 문장을 추출하는 시스템을 제안한다. 이벤트 문장이란, 특정도메인에서 다루어지는 이벤트의 구체적인 내용을 포함하고 있는 문장이다. 이러한 문장을 추출함으로써 기본적인 수준의 정보추출 요구를 만족시킬 수 있을 뿐만 아니라, 주출된 이벤트 문장을 도메인 정보 구축에 활용할 수 있을 것이다. 본 연구에서는 동사, 명사, 명사구, 및 3W 자질을 이용하여 문장추출의 성능을 최대화하기 위한 방안을 제안하고, 세 개의 평가 도메인을 대상으로 실험을 수행하였다. 실험 결과, when 및 where 자질과 동사, 명사. 명사구의 가중치를 이용하여 문장 가중치를 계산함으로써 최적의 이벤트 문장추출 성능을 얻을 수 있음을 알 수 있었다.

• Journal of Radiation Protection and Research
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• v.41 no.2
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• pp.117-121
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• 2016

Background: Definition and grouping of initiating events (IEs) are important basics for probabilistic safety assessment (PSA). An IE in a spent fuel reprocessing plant (SFRP) is an event that probably leads to the release of dangerous material to jeopardize workers, public and environment. The main difference between SFRPs and nuclear power plants (NPPs) is that hazard materials spread diffusely in a SFRP and radioactive material is just one kind of hazard material. Materials and Methods: Since the research on IEs for NPPs is in-depth around the world, there are several general methods to identify IEs: reference of lists in existence, review of experience feedback, qualitative analysis method, and deductive analysis method. While failure mode and effect analysis (FMEA) is an important qualitative analysis method, master logic diagram (MLD) method is the deductive analysis method. IE identification in SFRPs should be consulted with the experience of NPPs, however the differences between SFRPs and NPPs should be considered seriously. Results and Discussion: The plutonium uranium reduction extraction (Purex) process is adopted by the technics in a model reprocessing plant. The first extraction cycle (FEC) is the pivotal process in the Purex process. Whether the FEC can function safely and steadily would directly influence the production process of the whole plant-production quality. Important facilities of the FEC are installed in the equipment cells (ECs). In this work, IEs in the FEC process were identified and categorized by FMEA and MLD two methods, based on the fact that ECs are containments in the plant. Conclusion: The results show that only two ECs in the FEC do not need to be concerned particularly with safety problems, and criticality, fire and red oil explosion are IEs which should be emphatically analyzed. The results are accordant with the references.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.15 no.2
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• pp.167-173
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• 2015

Extraction of Finger-end points is one of the most process for user multi-commands in the Hand-Gesture interface technology. However, most of previous works use the geometric and morphological method for extracting a finger-end points. Therefore, this paper proposes the method of user finger-end points extraction that is motivated a ultrared diffused illumination, which is used for the user commands in the multi-touch display device. Proposed air-mouse is worked by the quantity state and moving direction of extracted finger-end points. Also, our system includes a basic mouse event, as well as the continuous command function for expending a user multi-gesture. In order to evaluate the performance of the our proposed method, after applying to the web browser application as a command device. As a result, the proposed method showed the average 90% success-rate for the various user-commands.

• Journal of the Korea Convergence Society
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• v.12 no.1
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• pp.99-104
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• 2021

In this paper, we propose health risk management using feature extraction and cluster analysis considering time flow. The proposed method proceeds in three steps. The first is the pre-processing and feature extraction step. It collects user's lifelog using a wearable device, removes incomplete data, errors, noise, and contradictory data, and processes missing values. Then, for feature extraction, important variables are selected through principal component analysis, and data similar to the relationship between the data are classified through correlation coefficient and covariance. In order to analyze the features extracted from the lifelog, dynamic clustering is performed through the K-means algorithm in consideration of the passage of time. The new data is clustered through the similarity distance measurement method based on the increment of the sum of squared errors. Next is to extract information about the cluster by considering the passage of time. Therefore, using the health decision-making system through feature clusters, risks able to managed through factors such as physical characteristics, lifestyle habits, disease status, health care event occurrence risk, and predictability. The performance evaluation compares the proposed method using Precision, Recall, and F-measure with the fuzzy and kernel-based clustering. As a result of the evaluation, the proposed method is excellently evaluated. Therefore, through the proposed method, it is possible to accurately predict and appropriately manage the user's potential health risk by using the similarity with the patient.