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하수처리장 유입수의 특성평가를 위한 실시간 수질예측 (Real-time Water Quality Prediction for Evaluation of Influent Characteristics in a Full-scale Sewerage Treatment Plant)

  • 김연권;채수권;한인선;김주환
    • 환경영향평가
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    • 제19권6호
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    • pp.617-623
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    • 2010
  • It is the most important subject to figure out characteristics of the wastewater inflows of sewerage treatment plant(STP) when situation models are applied to operation of the biological processes and in the automatic control based on ICA(Instrument, Control and Automation). For the purposes, real-time influent monitoring method has been applied by using on-line monitoring equipments for the process optimization in conventional STP. Since, the influent of STP is consist of complex components such as, COD, BOD, TN, $NH_4$-N, $NO_3$-N, TP and $PO_4$-P. MRA2(Microbial Respiration Analyzer 2), which is capable of real-time analyzing of wastewater characteristics is used to overcome the limitations and defects of conventional online monitoring equipments in this study. Rapidity, accuracy and stability of developed MRA2 are evaluated and compared with the results from on-line monitoring equipments for seven months after installation in Full-scale STP.

순환신경망을 이용한 실시간 시추매개변수 예측 연구 (A Study on Real-time Drilling Parameters Prediction Using Recurrent Neural Network)

  • 한동권;서형준;김민수;권순일
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2021년도 춘계학술대회
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    • pp.204-206
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    • 2021
  • 실시간 시추매개변수 예측은 시추효율의 극대화 관점에서 상당히 중요한 연구이다. 시추 극대화 방법 중 시추속도를 향상시키는 방법이 일반적인데 이는 굴진율, 시추스트링 회전속도, 비트 하중, 시추이수 유량과 연관관계를 지니고 있다. 본 연구는 실시간 시추매개변수 중 하나인 굴진율을 순환신경망기반 딥러닝 모델을 이용하여 예측하는 방법을 제안하였으며 기존의 물리적 기반의 굴진율 모델과 딥러닝 모델을 이용한 예측 모델을 비교해 보고자 한다.

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도시 빅데이터를 활용한 스마트시티의 교통 예측 모델 - 환경 데이터와의 상관관계 기계 학습을 통한 예측 모델의 구축 및 검증 - (Big Data Based Urban Transportation Analysis for Smart Cities - Machine Learning Based Traffic Prediction by Using Urban Environment Data -)

  • 장선영;신동윤
    • 한국BIM학회 논문집
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    • 제8권3호
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    • pp.12-19
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    • 2018
  • The research aims to find implications of machine learning and urban big data as a way to construct the flexible transportation network system of smart city by responding the urban context changes. This research deals with a problem that existing a bus headway model is difficult to respond urban situations in real-time. Therefore, utilizing the urban big data and machine learning prototyping tool in weathers, traffics, and bus statues, this research presents a flexible headway model to predict bus delay and analyze the result. The prototyping model is composed by real-time data of buses. The data is gathered through public data portals and real time Application Program Interface (API) by the government. These data are fundamental resources to organize interval pattern models of bus operations as traffic environment factors (road speeds, station conditions, weathers, and bus information of operating in real-time). The prototyping model is implemented by the machine learning tool (RapidMiner Studio) and conducted several tests for bus delays prediction according to specific circumstances. As a result, possibilities of transportation system are discussed for promoting the urban efficiency and the citizens' convenience by responding to urban conditions.

결핵균과 비결핵성항산균 검출에 Real-time PCR의 유용성 (Usefulness of Real-time PCR to Detect Mycobacterium tuberculosis and Nontuberculous Mycobacteria)

  • 윤은영;조수희;고세일;백종하;김유은;마정은;이기동;조유지;정이영;김호철;이종덕;김선주;황영실
    • Tuberculosis and Respiratory Diseases
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    • 제69권4호
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    • pp.250-255
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    • 2010
  • Background: The purpose of this study was to evaluate recently developed real-time polymerase chain reaction (PCR) assay kit to detect Mycobacterium tuberculosis (MTB) and nontuberculous mycobacteria (NTM) in respiratory specimens. Methods: We assessed the positive rate of the real-time PCR assay to detect MTB and NTM in 87 culture-positive specimens (37 sputum, 50 bronchial washing), which were performed real-time PCR by using $Real-Q_{TM}$ MTB&NTM Kit from January 2009 to June 2009, at Gyeongsang University Hospital. To compare the efficacy with the TB-PCR assay, we evaluated 63 culture-positive specimens (19 sputum, 44 bronchial washing) for MTB or NTM, which were performed TB-PCR by using ABSOLUTETM MTB II PCR Kit from March 2008 to August 2008. Results: Among 87 specimens tested using real-time PCR, MTB and NTM were cultured in 58 and 29, respectively. The positive rate of real-time PCR assay to detect MTB was 71% (22/31) and 92.6% (25/27) in AFB stain-negative and stain-positive specimens. For NTM, the positive rate of real-time PCR was 11.1% (2/18) and 72.7% (8/11) in AFB stain-negative and stain-positive specimens. Among 63 specimens performed using TB-PCR, MTB and NTM were cultured in 46 and 17, respectively. The positive rate of TB-PCR was 61.7% (21/34) and 100% (12/12) in AFB stain-negative and stain-positive specimens. TB-PCR was negative in all NTM-cultured 17 specimens. Conclusion: TB/NTM real-time PCR assay is useful to differentiate MTB and NTM in AFB stain-positive respiratory specimens and it is as effective in detecting MTB with TB-PCR.

차세대 웨이퍼 생산시스템에서의 실시간 스케줄링 시스템 아키텍처 (A Real-Time Scheduling System Architecture in Next Generation Wafer Production System)

  • 이현;허선;박유진;이건우;조용주
    • 산업경영시스템학회지
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    • 제33권3호
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    • pp.184-191
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    • 2010
  • In the environment of 450mm wafers production known as the next-generation semiconductor production process, one of the most significant features is the full automation over the whole manufacturing processes involved. The full automation system for 450mm wafer production will minimize the human workers' involvement in the manufacturing process as much as possible. In addition, since the importance of an individual wafer processing increases noticeably, it is necessary to develop more robust scheduling systems in the whole manufacturing process than so ever. The scheduling systems for the next-generation semiconductor production processes also should be capable of monitoring individual wafers and collecting useful data on them in real time. Based on the information gathered from these processes, the system should finally have a real-time scheduling functions controlling whole the semiconductor manufacturing processes. In this study, preliminary investigations on the requirements and needed functions for constructing the real time scheduling system and transforming manufacturing environments for 300mm wafers to those of 400mm are conducted and through which the next generation semiconductor processes for efficient scheduling in a clustered production system architecture of the scheduler is proposed. Our scheduling architecture is composed of the modules for real-time scheduling, the clustered production type supporting, the optimal scheduling and so on. The specifications of modules to define the major required functions, capabilities, and the relationship between them are presented.

개선한 아다부스트 알고리즘을 이용한 기울어진 얼굴 실시간 검출 (Real-time Slant Face detection using improvement AdaBoost algorithm)

  • 나종원
    • 한국항행학회논문지
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    • 제12권3호
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    • pp.280-285
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    • 2008
  • 기존의 얼굴 검출 방법은 프레임 간의 차를 이용하여 움직임을 검출하는 방법이 사용되어 왔다. 그러나, 대부분이 실시간을 고려하지 않은 수학적 접근법을 사용하거나 알고리즘이 지나치게 복잡하여 실시간 구현에 용이하지 않았다. 본 논문에서는 실시간 얼굴검출을 위하여 감시카메라에서 입력된 RGB영상을 YCbCr 영상으로 변환한 후 연속된 두 영상의 차를 구하고 Glassfire 라벨링을 실시했다. 라벨링 결과 가장 넓은 구역의 면적과 Area 임계치 값을 비교하여 임계값 이상의 면적이면 동작변환으로 인식하고 영상을 추출하였다. 이렇게 추출된 동작변환 영상을 대상으로 얼굴 검출을 실시하였다. 얼굴 검출에 필요한 특징을 추출하기 위해 아다부스트 알고리즘을 사용하였다.

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실시간 IoT Big Data 분석 플랫폼 요건 (Real-time IoT Big Data Analysis Platform Requirements)

  • 강선경;이현창;신성윤
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2017년도 춘계학술대회
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    • pp.165-166
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    • 2017
  • 어느 곳에서나 실시간으로 데이터의 정보를 전달 받고 그를 의미 있는 데이터로 분석해 내는 것을 요구하고 있다. 이러한 분석을 위한 플랫폼에 대한 연구도 활발히 진행 중에 있다. 본 논문에서는 실시간으로 IoT 데이터를 수집하고 분석하는데 겪는 문제들을 해결해 내기 위해 중요한 요소가 무엇인지를 알아보려 한다. 기존의 데이터 수집 방법과 분석 방법보다 얼마나 더 나은지가 그 데이터의 가치를 판단하는 기준이 될 수 있다. 실시간으로 많은 곳에 있는 센서로부터 보다 빠르고 신속하게 데이터를 정확히 수집하고 저장하는 기술과 그 저장되어진 데이터로부터 값을 도출해 낼 수 있는 분석 방법이 중요하다. 따라서 IoT 환경에서의 분석 플랫폼의 중요한 요건은 대량의 데이터를 실시간 처리하고 그를 집중화 시켜 관리하는 것이라 할 수 있다.

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홍수시 실시간 저수지 운영을 위한 의사결정 지원시스템 (Decision Suport System for Real-Time Reservoir Operation during Flood Period)

  • 심순보;김선구
    • 한국수자원학회논문집
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    • 제30권5호
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    • pp.431-439
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    • 1997
  • 본 연구의 목적은 다목적 조수지의 홍수조절능력을 극대화하기 위한 홍수시 실시간 저수지운영 의사결정 지원 시스템을 개발하는 것이다. 본 연구를 통해 개발된 의사결정 지원시스템은 모델베이스와 실시간 자료처리 부시스템, 사용자 인터페이스로 구성되어 있으며, 사용자 인터페이스는 모형에 의해 예측된 홍수조절지점의 수문곡선과 저수지의 저수위 그래프르 그래픽 형태로 보여줄 수 있도록 개발되었다. 개발된 시스템의 적용성을 검증하기 위하여 금강유역의 1987년 7월 및 1995년 8월의 과거 홍수 사상을 가상 실시간으로 대청댐 저수지 운영에 적용하여 의사결정과정을 수행하고, 당시의 운영 실적과 비교·검토하였다. 개발된 시스템의 의한 저수지 운영은 홍수유출모형에 의해 모의되었으며, 그 결과 본 시스템에 의한 저수지운영은 금강하류의 홍수조절에 기여할 수 있는 것으로 나타났다.

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시간지연을 갖는 불확정성 선형 시스템의 강인 안정성에 관한 연구 (A Study on Robust Stability of Uncertain Linear Systems with Time-delay)

  • 이희송;마삼선;유정웅;김진훈
    • 대한전기학회논문지:전력기술부문A
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    • 제48권5호
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    • pp.615-621
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    • 1999
  • In this paper, we consider the robust stability of uncertain linear systems with time-delay in the time domain. The considered uncertainties are both the unstructured uncertainty which is only Known its norm bound and the structured uncertainty which is known its structured. Based on Lyapunov stability theorem and{{{{ { H}_{$\infty$ } }}}} theory known as Strictly Bounded Real Lemma (SBRL), we present new conditions that guarantee the robust stability of system. Also, we extend this to multiple time-varying delays systems and large-scale systems, respectively. Finally, we show the usefulness of our results by numerical examples.

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Evaluation of Galactomannan Enzyme Immunoassay and Quantitative Real-Time PCR for the Diagnosis of Invasive Pulmonary Aspergillosis in a Rat Model

  • Lin, Jian-Cong;Xing, Yan-Li;Xu, Wen-Ming;Li, Ming;Bo, Pang;Niu, Yuan-Yuan;Zhang, Chang-Ran
    • Journal of Microbiology and Biotechnology
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    • 제24권8호
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    • pp.1044-1050
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    • 2014
  • Since there is no consensus about the most reliable assays to detect invasive aspergillosis from samples obtained by minimally invasive or noninvasive methods, we compared the efficacy of an enzyme-linked immunosorbent assay (ELISA) for galactomannan (GM) detection and quantitative real-time PCR assay (qRT-PCR) for the diagnosis of invasive pulmonary aspergillosis. Neutropenic, male Sprague-Dawley rats (specific pathogen free; 8 weeks old; weight, $200{\pm}20g$) were immunosuppressed with cyclophosphamide and infected with Aspergillus fumigatus intratracheally. Tissue and whole blood samples were harvested on days 1, 3, 5, and 7 post-infection and examined with GM ELISA and qRT-PCR. The A. fumigatus DNA detection sequence was detected in the following number of samples from 12 immunosuppressed, infected rats examined on the scheduled days: day 1 (0/12), day 3 (0/12), day 5 (6/12), and day 7 (8/12) post-infection. The sensitivity and specificity of the qRT-PCR assay was 29.2% and 100%, respectively. Receiver operating characteristic curve (ROC) analysis indicated a Ct (cycle threshold) cut-off value of 15.35, and the area under the curve (AUC) was 0.627. The GM assay detected antigen in sera obtained on day 1 (5/12), day 3 (9/12), day 5 (12/12), and day 7 (12/12) post-infection, and thus had a sensitivity of 79.2% and a specificity of 100%. The ROC of the GM assay indicated that the optimal Ct cut-off value was 1.40 (AUC, 0.919). The GM assay was more sensitive than the qRT-PCR assay in diagnosing invasive pulmonary aspergillosis in rats.