• 제목/요약/키워드: data quality

검색결과 21,001건 처리시간 0.045초

Onco. Flash Processing 적용에 따른 핵의학 영상의 유용성 평가 (Usefulness in Evaluation of NM Image which It Follows in Onco. Flash Processing Application)

  • 김정수;김병진;김진의;우재룡;김현주;신희원
    • 핵의학기술
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    • 제12권1호
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    • pp.13-18
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    • 2008
  • 목적: 다양한 algorism에 의한 영상처리기법은 핵의학 영상을 결정짓는 중요한 부분을 차지하고 있다. 이에 새로운 영상처리기법인 SIEMENS (made by pixon)사의 Onco. flash processing reconstruction을 적용하여 기존의 영상처리기법을 이용한 영상과 비교 분석함으로써 그 임상적 유용성을 평가한다. 대상 및 방법: 1) Scan speed의 차이에 의한 whole body bone scan을 시행하고, raw data와 processing data의 imaeg quality를 비교 분석하여 상대 평가한다. 2) Bone static scan을 acquisition count를 달리하여 시행하고, raw data와 processing data의 image quality를 비교 분석하여 상대 평가한다. 3) 4 quadrant - bar phantom을 이용하여 raw data와 processing data와의 육안적 평가를 통한 image quality를 확인한다. 4) LSF을 통한 raw data와 processing data의 FWHM을 구하여 해상력 평가를 확인한다. 결과: 1) Whole body bone scan을 시행하여 본원 핵의학 판독의의 blinding test한 결과 scan speed 20 cm/min의 raw data와 30 cm/min의 processing data에는 임상 판독에 영향을 미칠 수준의 image quality 저하가 없었으나, 40 cm/min processing data는 영상 판독과 진단에 오류의 가능성을 배제 할 수 없는 image quality의 향상을 볼 수 없었다. 2) Bone static scan의 경우 200 kcts processing data는 200 kcts raw data보다 확실한 image quality의 향상을 가져왔으며 400 kcts raw data와 비교한 본원 핵의학 판독의 blinding test 결과 판독과 진단에 무리가 없을 수준의 유사한 image quality를 보였다. 3) 4 quadrant - bar phantom을 이용하여 raw data와 processing data와의 육안적 평가는 processing을 통한 image quality의 향상을 확인할 수 있었다. 4) LSF을 통한 raw data와 processing data의 FWHM 평가 결과, resolution의 뚜렷한 증가나 감소의 확인은 할 수 없었다. 이는 noise level의 감소와 high S/N ratio 때문이라 판단된다. 결론: 기존의 영상과 비교 분석하여 평가한 결과 Onco. flash processing reconstruction을 적용한 경우 일정 수준까지 뚜렷한 image quality의 향상을 보였으며, 이는 장비 가동률의 상승과 환자 대기일수의 단축 그리고 저선량 검사에 따른 방사선 피폭에 대한 적극적 방어의 관점에서 현재 임상 핵의학에 충분한 유용성과 타당성이 있을 것으로 사료된다.

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CTQ 데이터 선정 모델에 관한 연구 (Study on the Selection Model CTQ data)

  • 김승희;김우제
    • 한국컴퓨터정보학회논문지
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    • 제18권4호
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    • pp.97-112
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    • 2013
  • 데이터의 품질은 효율적인 데이터 활용을 위한 가장 기본적인 전제이다. 수많은 연구와 사례를 통해 오류 데이터로 인한 손실과 그로 인한 문제점들이 대두되고 있고, 국가적으로는 데이터 품질 인증제도가 시행되고 있으나 데이터를 생성하고 관리해야 하는 조직 관점의 CTQ 데이터 선정 방법에 대한 연구는 극히 미흡한 상황이다. 본 모델은 조직에서 품질관리 대상이 되는 주요 CTQ 데이터를 선정하여 체계적으로 관리할 수 있도록 업무 및 IT측면의 CTQ 데이터의 기준을 수립하고 그에 따라 데이터를 선별하여 계량화 할 수 있게 있는 전사적 규모의 CTQ 데이터 관리 방법을 구체적으로 제시하였다. 이를 위해 SPSS를 활용하여 요인분석을 수행하고, 계량화를 위해 AHP 방법론을 사용하였다. 특히, DB 품질인증제도의 본격 시행에 따라 실무 적용에 용이하도록 CTQ-DSMM 모델을 활용한 조직 내 데이터 성숙도 관리 방안의 틀도 함께 제시하였다.

철도 산업의 공기 질 데이터베이스 연합형 통합을 위한 지능형 데이터 거버넌스 (Intelligent Data Governance for the Federated Integration of Air Quality Databases in the Railway Industry)

  • 김민정;원종운;박상찬;박가영
    • 품질경영학회지
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    • 제50권4호
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    • pp.811-830
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    • 2022
  • Purpose: In this paper, we will discuss 1) prioritizing databases to be integrated; 2) which data elements should be emphasized in federated database integration; and 3) the degree of efficiency in the integration. This paper aims to lay the groundwork for building data governance by presenting guidelines for database integration using metrics to identify and evaluate the capabilities of the UK's air quality databases. Methods: This paper intends to perform relative efficiency analysis using Data Envelope Analysis among the multi-criteria decision-making methods. In federated database integration, it is important to identify databases with high integration efficiency when prioritizing databases to be integrated. Results: The outcome of this paper aims not to present performance indicators for the implementation and evaluation of data governance, but rather to discuss what criteria should be used when performing 'federated integration'. Using Data Envelope Analysis in the process of implementing intelligent data governance, authors will establish and present practical strategies to discover databases with high integration efficiency. Conclusion: Through this study, it was possible to establish internal guidelines from an integrated point of view of data governance. The flexiblity of the federated database integration under the practice of the data governance, makes it possible to integrate databases quickly, easily, and effectively. By utilizing the guidelines presented in this study, authors anticipate that the process of integrating multiple databases, including the air quality databases, will evolve into the intelligent data governance based on the federated database integration when establishing the data governance practice in the railway industry.

A Pilot Study of the Scanning Beam Quality Assurance Using Machine Log Files in Proton Beam Therapy

  • Chung, Kwangzoo
    • 한국의학물리학회지:의학물리
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    • 제28권3호
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    • pp.129-133
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    • 2017
  • The machine log files recorded by a scanning control unit in proton beam therapy system have been studied to be used as a quality assurance method of scanning beam deliveries. The accuracy of the data in the log files have been evaluated with a standard calibration beam scan pattern. The proton beam scan pattern has been delivered on a gafchromic film located at the isocenter plane of the proton beam treatment nozzle and found to agree within ${\pm}1.0mm$. The machine data accumulated for the scanning beam proton therapy of five different cases have been analyzed using a statistical method to estimate any systematic error in the data. The high-precision scanning beam log files in line scanning proton therapy system have been validated to be used for off-line scanning beam monitoring and thus as a patient-specific quality assurance method. The use of the machine log files for patient-specific quality assurance would simplify the quality assurance procedure with accurate scanning beam data.

ARIMA 모형에 의한 하천수질 예측

  • 류병로;한양수
    • 한국환경과학회지
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    • 제7권4호
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    • pp.433-440
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    • 1998
  • This study was carried out to develop the stream water quality model for the intaking station of Kongju waterworks in the Keum River system. The monthly water quality(total nitrogen and total phosphorus) with periodicity and trend were forecasted by multiplicative ARIU models and then the applicability of the models was tested based on 7 years of the historical monthly water quality data at Kongju intaking strate. The parameter estimation was made with the monthly observed data. The last one year data was used to compare the forecasted water Quality by ARU model with the observed one. The models are ARIMA(2,0,0)$\times$(0,1,1)l2 for total nitrogen, ARIMA(0,1,1)x(0,1,1)l2 for total phosphorus. The forecasting results showed a good agreement with the observed data. It is implying the applicability of multiplicative ARIMA model for forecasting monthly water quality at the Kongju site.

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수면생리신호와 수면 만족감과의 관계 (The relationship between sleep physiological signals data and subjective feeling of sleep quality.)

  • 이현자;박세진
    • 한국감성과학회:학술대회논문집
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    • 한국감성과학회 2002년도 춘계학술대회 논문집
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    • pp.181-185
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    • 2002
  • The purpose of this study was to find out the relationship between sleep physiological signals data and subjective feeling of sleep quality. Sixteen subjective were investigated and they slept on both comfortable mattress and uncomfortable mattress. Information of sleep stage is one of the most important clues for sleep quality. Polysomnography is basically the recording of sleep. The several channels of brain waves (EEG), eyes (EOG), chin movements (EMG) and heart (ECG) were monitored. Sixteen subjects spent 6 days and nights in the laboratory and the data of sleeping 7h for each of 3 nights was analyzed. Percentage of deep sleep (III and IV, sleep efficiency, WASO, stage 1 and subjective feeling of sleep quality were significantly affected with mattress types (comfortable and uncomfortable mattress). When subjects slept on comfortable beds, percentage of deep sleep and sleep efficiency were higher than those of uncomfortable bed. The percentages of wake after sleep onset and stage 1 were lower when subject slept in a comfortable bed. The subjective feeling of sleep quality agreed with the recorded sleep data also.

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소프트웨어 오류 데이터를 기반으로 한 소프트웨어 신뢰성 성장 모델 제안 (The Software Reliability Growth Model base on Software Error Data)

  • 정혜정;한군희
    • 한국융합학회논문지
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    • 제10권3호
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    • pp.59-65
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    • 2019
  • 본 연구에서는 기존에 소프트웨어 품질 평가를 위해서 사용되었던 ISO/IEC 9126-2와의 차이점을 비교하기 위해서 소프트웨어 품질 평가를 위해서 새롭게 제시된 ISO/IEC 25023의 소프트웨어 품질 측정 메트릭을 제시하고 제시된 메트릭에 대해서 품질을 측정하는 방안을 제시한다. ISO/IEC 25023에 제시된 8가지 품질 특성 중에서 신뢰성에 대한 품질 측정 방안을 소프트웨어 신뢰성 성장 모델을 기반으로 평가하는 방안을 제시한다. ISO/IEC 25023을 기반으로 소프트웨어 품질을 평가하게 되어지면 신뢰성에 대한 평가에 있어 다소 리스크가 있을 수 있음을 데이터를 기반으로 하여 입증한다.

성별에 따른 중년 성인의 신체건강 및 정신건강이 삶의 질에 미치는 영향 (Effects of Physical and Mental Health on Quality of Life in Middle-aged Adults by Gender)

  • 방소연
    • Journal of Information Technology Applications and Management
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    • 제29권2호
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    • pp.27-37
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    • 2022
  • This study was attempted to identify the effects of physical and mental health on quality of life in middle-aged adults by gender. The Data were analyzed for 4,511 adults (2,260 men, 2,251 women) aged 45 to 65 who had no missing values in major variables based on the data of the 2016 Korea Health Panel. According to the data, the quality of life in middle-aged adults was .92 (±.08) for men and .91 (±.10) for women, which was significantly higher than that of women (t=3.54, p<.001). Factors affecting the quality of life in middle-aged men were subjective health status (β=.40, p<.001), stress (β=-.17, p<.001) and education level (β=.10, p<.001), and these variables explained 23% of the quality of life (F=227.28, p<.001). Factors affecting the quality of life in middle-aged women were subjective health status (β=.40, p<.001), stress (β=-.11, p<.001), education level (β=.05, p=.011) and anxiety (β=-.05, p=.022), and these variables explained 21% of the quality of life (F=145.42, p<.001). Based on the results of this study, the group with low level of education in middle-aged adults needs health management, education on how to relieve stress, and intensive management to improve the quality of life. In addition, the differentiated approach should be required to reduce anxiety in middle-aged women.

방류수질 예측을 위한 AI 모델 적용 및 평가 (Application and evaluation for effluent water quality prediction using artificial intelligence model)

  • 김민철;박영호;유광태;김종락
    • 상하수도학회지
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    • 제38권1호
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    • pp.1-15
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    • 2024
  • Occurrence of process environment changes, such as influent load variances and process condition changes, can reduce treatment efficiency, increasing effluent water quality. In order to prevent exceeding effluent standards, it is necessary to manage effluent water quality based on process operation data including influent and process condition before exceeding occur. Accordingly, the development of the effluent water quality prediction system and the application of technology to wastewater treatment processes are getting attention. Therefore, in this study, through the multi-channel measuring instruments in the bio-reactor and smart multi-item water quality sensors (location in bio-reactor influent/effluent) were installed in The Seonam water recycling center #2 treatment plant series 3, it was collected water quality data centering around COD, T-N. Using the collected data, the artificial intelligence-based effluent quality prediction model was developed, and relative errors were compared with effluent TMS measurement data. Through relative error comparison, the applicability of the artificial intelligence-based effluent water quality prediction model in wastewater treatment process was reviewed.

Data Segmentation for a Better Prediction of Quality in a Multi-stage Process

  • Kim, Eung-Gu;Lee, Hye-Seon;Jun, Chi-Hyuek
    • Journal of the Korean Data and Information Science Society
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    • 제19권2호
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    • pp.609-620
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    • 2008
  • There may be several parallel equipments having the same function in a multi-stage manufacturing process, which affect the product quality differently and have significant differences in defect rate. The product quality may depend on what equipments it has been processed as well as what process variable values it has. Applying one model ignoring the presence of different equipments may distort the prediction of defect rate and the identification of important quality variables affecting the defect rate. We propose a procedure for data segmentation when constructing models for predicting the defect rate or for identifying major process variables influencing product quality. The proposed procedure is based on the principal component analysis and the analysis of variance, which demonstrates a better performance in predicting defect rate through a case study with a PDP manufacturing process.

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