• Journal of the Mineralogical Society of Korea
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• v.23 no.1
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• pp.85-91
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• 2010

The various forms of heavy metals in soil environments have been studied by sequential extraction method. We tested conventional Tessier sequential extraction and new ultrasound-sonication extraction methods, and compared their extraction efficiency. Total As, Cd, Cu, Pb, and Zn contents of the target soil (NIST SRM 2710 Montana Soil), by three methods (USEPA Method 3050B, KBSI Method, and ultrasound-sonication method) were all consistent with the certified values. Sequential extraction efficiency along with step-wise extraction values was similar in both Tessier method and ultrasound-sonication method. The ultrasound-sonication method took about 3 hours to complete whole procedure while the Tessier sequential extraction method took around 12 hours. Ultrasound-sonication method was estimated as one of the best methods with a relatively short application time and no requirement of high temperature treatment.

• The Journal of Korean Association of Computer Education
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• v.17 no.2
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• pp.31-38
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• 2014

This paper reveals continuity of related events which are occurred and changing from moment to moment accident/events collected from various social media channels. Among them, we especially define the events which have big social influence as "issue event" and investigate the type and characteristics of continuous issue event for each domain. We also introduce a automatic issue detection system in social media text. Based on the extracted issue event results in a particular domain, we analyse the continuity of those events by illustrating in time and place-axis. Furthermore, we identify the relationship between social media in terms of issue events propagation.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.170-171
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• 2008

연속적인 음성 인식 결과는 띄어쓰기를 하지 않은 연속 음절 문장들로 이루어져 있다. 본 논문은 음성 인식 후처리 단계에서 연속 음절 문장을 조사/어미 사전을 이용한 어절 생성 과정과 형태소 분석기를 이용하여 어절을 생성한 후 키워드를 추출한다. 실험 결과, 어절 생성기만 적용한 방식보다 제안된 알고리즘의 인식률이 향상되는 것을 확인하였다.

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.1
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• pp.94-100
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• 2010

Data Mining is mainly used for pattern extracting and information discovery from collected data. However previous methods is difficult to reflect changing patterns with time. In this paper, we introduce Streaming Decision Tree(SDT) analyzing data with continuity, large scale, and changed patterns. SDT defines continuity data as blocks and extracts rules using a Decision Tree's learning method. The extracted rules are combined considering time of occurrence, frequency, and contradiction. In experiment, we applied time series data and confirmed resonable result.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.124-126
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• 2001

시차를 두고 발생한 사건속에서 잠재해있는 패턴을 발견하는 연속패턴(sequential pattern) 생성기술은 데이터 마이닝 분야에서 최근 관심을 모으고 있는 분야이다. 본 연구는 정보이론을 이용하여 데이터베이스로부터 연속패턴을 자동으로 발견하는 방법에 관한 내용이다. 본 연구에서 제시하는 방법은 기존의 방법과는 달리 테이블내의 모든 속성간의 연속패턴 관계를 탐지할 수 있으며 헬링거(Hellinger) 변량을 이용하여 발견된 연속패턴들의 중요도를 측정할 수 있다. 또한 헬링거 변량의 함수적인 특성을 분석하여 연속패턴 추출의 복잡도를 줄이기 위한 두 가지의 법칙이 제안되었다.

• KIPS Transactions on Computer and Communication Systems
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• v.3 no.10
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• pp.377-382
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• 2014

Analysis techniques of the data over time from the mobile environment and IoT, is mainly used for extracting patterns from the collected data, to find meaningful information. However, analytical methods existing, is based to be analyzed in a state where the data collection is complete, to reflect changes in time series data associated with the passage of time is difficult. In this paper, we introduce a method for analyzing multi-block streaming data(AM-MBSD: Analysis Method for Multi-Block Stream Data) for the analysis of the data stream with multiple properties, such as variability of pattern and large capacitive and continuity of data. The multi-block streaming data, define a plurality of blocks of data to be continuously generated, each block, by using the analysis method of the proposed method of analysis to extract meaningful patterns. The patterns that are extracted, generation time, frequency, were collected and consideration of such errors. Through analysis experiments using time series data.

• 대한방사선방어학회:학술대회논문집
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• 2010.04a
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• pp.84-85
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• 2010

• Korean Journal of Cognitive Science
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• v.1 no.2
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• pp.255-257
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• 1989

This paper proposes a method for extracting the imformation of aspect and modality from the predicative part which is consisted of main verbal and auxiiary verbals.Data which are expressed by the compound predicate with many consecutive verbals are collected and analyzed to thirty-six structual forms of the predicative part.Inthe final analysis, an extracting function of conceptual information is derived to find the connoted aspect and modality in each structure.The informations which are obtained by this function decrease the individual ambiguity of an auxiliary verbal and offer a detailed meaning inthe syntactic and semantic analysis of machine translation system or inference machine.

• Journal of Cadastre & Land InformatiX
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• v.49 no.1
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• pp.103-112
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• 2019

Extraction of region of interest for satellite image classification is one of the important techniques for efficient management of the national land space. However, recent studies on satellite image classification often depend on the information of the selected image in selecting the region of interest. This study propose an effective method of selecting the area of interest using the continuous digital topographic map constructed from high resolution images. The spatial information used in this research is based on the digital topographic map from 2013 to 2017 provided by the National Geographical Information Institute and the 2015 Sejong City land cover map provided by the Ministry of Environment. To verify the accuracy of the extracted area of interest, KOMPSAT-3A satellite images were used which taken on October 28, 2018 and July 7, 2018. The baseline samples for 2015 were extracted using the unchanged area of the continuous digital topographic map for 2013-2015 and the land cover map for 2015, and also extracted the baseline samples in 2018 using the unchanged area of the continuous digital topographic map for 2015-2017 and the land cover map for 2015. The redundant areas that occurred when merging continuous digital topographic maps and land cover maps were removed to prevent confusion of data. Finally, the checkpoints are generated within the region of interest, and the accuracy of the region of interest extracted from the K3A satellite images and the error matrix in 2015 and 2018 is shown, and the accuracy is approximately 93% and 72%, respectively. The accuracy of the region of interest can be used as a region of interest, and the misclassified region can be used as a reference for change detection.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.6
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• pp.144-152
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• 2018

This study focuses on collecting traffic data using drones to compensate for limitation of the data collected by the existing traffic data collection devices. Feasibility analysis was performed to verify the traffic data extracted from drone videos and optimal methodology for extracting data was established through analysis of various data reduction scenarios. It was found from this study that drones are very economical traffic data collection devices and have strength of determining the level-of-service(LOS) for uninterrupted flow condition in a very simple and intuitive way.