• Title/Summary/Keyword: Classification of potential source

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토양.지하수오염원 분류체계 구축방안: 1. 국내외 현황 및 시사점 (Building a Classification Scheme of Soil and Groundwater Contamination Sources in Korea: 1. State-of-the-Art and Suggestions)

  • 안정이;신경희;황상일
    • 한국지하수토양환경학회지:지하수토양환경
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    • 제15권6호
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    • pp.64-71
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    • 2010
  • National inventory of soil and groundwater contamination is an efficient decision-making tool to identify and manage existing or potential contaminated sources and contaminants. It has been used as basic data for establishing the scheme of regulations and remediation plans of soil and groundwater contamination in developed countries. This study examined classification of existing or potential sources of soil and groundwater contamination from various countries to suggest implications that required for development of classification of soil and groundwater contamination sources in Korea. Each country has provided a list of currently or potentially contaminating activities or landuses and identified some of the potential contaminants related to those contamination sources. Consideration of sources which had not been mentioned or regarded as contamination sources before was suggested for Korea situation. In addition, it is necessary to compile a list of existing data and information as much as possible to develop a detailed and practical list of various contamination sources.

토양.지하수오염원 분류체계 구축방안: 2. 분류체계 구축 및 속성자료 활용방안 (Building a Classification Scheme of Soil and Groundwater Contamination Sources in Korea: 2. Construction of Classification System and Applications of Attribute Data)

  • 안정이;신경희;황상일
    • 한국지하수토양환경학회지:지하수토양환경
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    • 제15권6호
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    • pp.122-127
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    • 2010
  • Constructing the national inventory that can be used as a tool to identify and assess existing or potential contamination is necessary for efficiently managing the soil and groundwater contamination. In order to start this construction, the first step is how we define and classify potential contamination sources of soil and groundwater. After selecting the basic classification model of contamination sources from developed countries, we suggested the classification and list of the potential contamination sources of soil and groundwater which are appropriate for specific conditions of South Korea. In addition, we investigated several databases to confirm the existence of available data sources and then examined established attribute data through chemical accident response information system (CARIS) and water information system (WIS) in National Institute of Environmental Research and mine geographic information system (MGIS) in Mine Reclamation Corporation. All sorts of attribute data in the existing databases can be utilized as significant assessment factors for determining the management priority of potential contamination sources in the future. Therefore, it is required the expanded investigation of additional database sources and the continual modification so that the classification system of potential contamination sources can be improved.

A Statistical Analysis of JERS L-band SAR Backscatter and Coherence Data for Forest Type Discrimination

  • Zhu Cheng;Myeong Soo-Jeong
    • 대한원격탐사학회지
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    • 제22권1호
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    • pp.25-40
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    • 2006
  • Synthetic aperture radar (SAR) from satellites provides the opportunity to regularly incorporate microwave information into forest classification. Radar backscatter can improve classification accuracy, and SAR interferometry could provide improved thematic information through the use of coherence. This research examined the potential of using multi-temporal JERS-l SAR (L band) backscatter information and interferometry in distinguishing forest classes of mountainous areas in the Northeastern U.S. for future forest mapping and monitoring. Raw image data from a pair of images were processed to produce coherence and backscatter data. To improve the geometric characteristics of both the coherence and the backscatter images, this study used the interferometric techniques. It was necessary to radiometrically correct radar backscatter to account for the effect of topography. This study developed a simplified method of radiometric correction for SAR imagery over the hilly terrain, and compared the forest-type discriminatory powers of the radar backscatter, the multi-temporal backscatter, the coherence, and the backscatter combined with the coherence. Statistical analysis showed that the method of radiometric correction has a substantial potential in separating forest types, and the coherence produced from an interferometric pair of images also showed a potential for distinguishing forest classes even though heavily forested conditions and long time separation of the images had limitations in the ability to get a high quality coherence. The method of combining the backscatter images from two different dates and the coherence in a multivariate approach in identifying forest types showed some potential. However, multi-temporal analysis of the backscatter was inconclusive because leaves were not the primary scatterers of a forest canopy at the L-band wavelengths. Further research in forest classification is suggested using diverse band width SAR imagery and fusing with other imagery source.

소스코드 주제를 이용한 인공신경망 기반 경고 분류 방법 (Warning Classification Method Based On Artificial Neural Network Using Topics of Source Code)

  • 이정빈
    • 정보처리학회논문지:컴퓨터 및 통신 시스템
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    • 제9권11호
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    • pp.273-280
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    • 2020
  • 자동화된 정적분석 도구는 소스 코드상에 잠재된 결함을 개발자들이 적은 노력으로 빠르게 찾을 수 있도록 도와준다. 하지만 이러한 정적분석 도구는 수정할 필요가 없는 오탐지 경고들을 무수하게 발생시킨다. 본 연구에서는 소스코드 블록의 토픽 모델을 이용한 인공신경망 기반의 경고 분류 기법을 제안한다. 소프트웨어 변경 관리 시스템으로부터 버그를 수정한 리비전들을 수집하고, 개발자들로부터 수정된 코드 블록들을 추출한다. 토픽 모델링을 이용하여 수집된 코드 블록의 토픽 분포 값을 구하고, 코드 블록의 리비전 간 경고들의 삭제 여부를 표현하는 이진데이터를 인공신경망의 입력 값과 출력 값으로 사용하여 심층 학습을 수행한다. 그 결과, 인공신경망 기반의 분류 모델이 높은 예측 성능으로 진성 또는 오탐지 경고를 분류하였다.

Classification, Structure, and Bioactive Functions of Oligosaccharides in Milk

  • Mijan, Mohammad Al;Lee, Yun-Kyung;Kwak, Hae-Soo
    • 한국축산식품학회지
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    • 제31권5호
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    • pp.631-640
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    • 2011
  • Milk oligosaccharides are the complex mixture of six monosaccharides namely, D-glucose, D-galactose, N-acetyl-glucosamine, N-acetyl-galactosamine, L-fucose, and N-acetyl-neuraminic acid. The mixture is categorized as neutral and acidic classes. Previously, 25 oligosaccharides in bovine milk and 115 oligosaccharides in human milk have been characterized. Because human intestine lacks the enzyme to hydrolyze the oligosaccharide structures, these substances can reach the colon without degradation and are known to have many health beneficial functions. It has been shown that this fraction of carbohydrate can increase the bifidobacterial population in the intestine and colon, resulting in a significant reduction of pathogenic bacteria. The role of milk oligosaccharides as a barrier against pathogens binding to the cell surface has recently been demonstrated. Milk oligosaccharides have the potential to produce immuno-modulation effects. It is also well known that oligosaccharides in milk have a significant influence on intestinal mineral absorption and in the formation of the brain and central nervous system. Due to its structural resemblance, bovine milk is considered to be the most potential source of oligosaccharides to produce the same effect of oligosaccharides present in human milk. This review describes the characteristics and potential health benefits of milk oligosaccharides as well as the prospects of oligosaccharides in bovine milk for use in functional foods.

Fault Diagnostics Algorithm of Rotating Machinery Using ART-Kohonen Neural Network

  • 안경룡;한천;양보석;전재진;김원철
    • 한국소음진동공학회논문집
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    • 제12권10호
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    • pp.799-807
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    • 2002
  • The vibration signal can give an indication of the condition of rotating machinery, highlighting potential faults such as unbalance, misalignment and bearing defects. The features in the vibration signal provide an important source of information for the faults diagnosis of rotating machinery. When additional training data become available after the initial training is completed, the conventional neural networks (NNs) must be retrained by applying total data including additional training data. This paper proposes the fault diagnostics algorithm using the ART-Kohonen network which does not destroy the initial training and can adapt additional training data that is suitable for the classification of machine condition. The results of the experiments confirm that the proposed algorithm performs better than other NNs as the self-organizing feature maps (SOFM) , learning vector quantization (LYQ) and radial basis function (RBF) NNs with respect to classification quality. The classification success rate for the ART-Kohonen network was 94 o/o and for the SOFM, LYQ and RBF network were 93 %, 93 % and 89 % respectively.

Use of In-Situ Optical Emission Spectroscopy for Leak Fault Detection and Classification in Plasma Etching

  • Lee, Ho Jae;Seo, Dong-Sun;May, Gary S.;Hong, Sang Jeen
    • JSTS:Journal of Semiconductor Technology and Science
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    • 제13권4호
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    • pp.395-401
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    • 2013
  • In-situ optical emission spectroscopy (OES) is employed for leak detection in plasma etching system. A misprocessing is reported for significantly reduced silicon etch rate with chlorine gas, and OES is used as a supplementary sensor to analyze the gas phase species that reside in the process chamber. Potential cause of misprocessing reaches to chamber O-ring wear out, MFC leaks, and/or leak at gas delivery line, and experiments are performed to funnel down the potential of the cause. While monitoring the plasma chemistry of the process chamber using OES, the emission trace for nitrogen species is observed at the chlorine gas supply. No trace of nitrogen species is found in other than chlorine gas supply, and we found that the amount of chlorine gas is slightly fluctuating. We successfully found the root cause of the reported misprocessing which may jeopardize the quality of thin film processing. Based on a quantitative analysis of the amount of nitrogen observed in the chamber, we conclude that the source of the leak is the fitting of the chlorine mass flow controller with the amount of around 2-5 sccm.

입원환자의 낙상발생 연구 자료원으로서의 국제간호실무분류체계 기반 전자간호기록의 유용성 (Exploring the Utility of the ICNP based Electronic Nursing Records as a Research Source for Inpatients' Falls)

  • 조인숙;박인숙;김은만
    • Perspectives in Nursing Science
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    • 제5권1호
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    • pp.33-43
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    • 2008
  • Objective: This study explored the reuse of data captured into an electronic nursing record system using the International Classification for Nursing Practice to support nursing research of inpatient's falls. Methods: Risk factors relevant to inpatients falls ;n an acute setting were identified from the literature review. Four risk assessment tools and two risk identification studies were selected. To examine the availability of coded data in an electronic nursing record system for the identified fall fisk factors, we reviewed 11.319 hospital-day records of 118 patients who were reported by the self-report system. Results: We identified 24 fall risk factors of five categories from the literature review, which were used to identify the standard nursing statements addressing fall risks. One hundred thirty five nursing statements were searched from the hospital's nursing data dictionary of statements and were matched with 14 fall fisk factors. Using the 135 statements. we found that mental status, catheter of drip in situ, abnormal gait, insomnia, surgical procedure. and dizziness/vertigo appeared frequently in the nursing records of inpatients with fall s. Also we found 6 risk factors more through the record review. Conclusion: The electronic records would be a good research source for inpatients' falls. Specifically international classification for nursing practice based nursing record system has the potential for promoting clinical researches.

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POTENTIAL OF MULTI-BAND SAR DATA FOR CLASSIFYING FOREST COVER TYPE

  • Shin, Jung-Il;Yoon, Jong-Suk;Kang, Sung-Jin;Lee, Kyu-Sung
    • 대한원격탐사학회:학술대회논문집
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    • 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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    • pp.258-261
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    • 2007
  • Although there have been lack of studies using X-band SAR data particularly for forestry application as compared to C-, and L-band SAR data, it has a potential to distinguish tree species because most signals are backscattered on the top of canopy. This study aimed to compare signal characteristics of multi-band SAR data including X-band for classifying tree species. The data used for the study are SIR-C/X-SAR data (X-, C-, L-band) obtained on Oct. 3, 1994 over the forest area near Seoul, S. Korea. Thirty ground sample plots were collected per each tree species. Initial comparison of backscattering coefficients among three SAR bands shows that X-band data showed better separation of tree species than C- and L-band SAR data irrespective of polarization. The weak penetrating in canopy layer might be possible source of information for X-band data to be useful for the classification of forest species and cover type mapping.

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음향 홀로-그래피에서 빔 형성을 이용한 부분 음장 분리 (Beamforming-based Partial Field Decomposition in Acoustical Holography)

  • 황의석;조영만;강연준
    • 한국소음진동공학회논문집
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    • 제11권6호
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    • pp.200-207
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    • 2001
  • In this paper, a new method for Partial field decomposition is developed that is based on the beamforming algorithm for the application of acoustical holography to a composite sound field generated by multiple incoherent sound sources. In the proposed method, source Positions are first predicted by MUSIC(multiple signal classification) algorithm. The composite sound fields can then be decomposed into each partial field by the beamforming. Results of both numerical simulations and experiments show that the method can find each partial field very accurately and effectively, and that it also has Potential to be used for application to distributed sources.

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