• 한국컴퓨터산업학회논문지
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• 제8권3호
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• pp.147-154
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• 2007

각 급 학교에서는 학습이 끝난 후에 실시하는 총괄평가의 결과만으로 학습평가를 하고 있는데 이러한 평가 방식은 학습자의 학습능력의 형성과정을 고려하지 않는 결과위주의 학습평가로 볼 수 있다. 또 기존의 학습평가는 학습 수행능력을 판정하기 위한 진단평가와 학습능력의 향상 정도를 측정하기 위한 형성평가를 각기 개별적으로 수행하여 평가하기 때문에 학습 수행능력을 보다 명확하게 처리하기 곤란한 점이 있다. 따라서 본 논문에서는 학습자의 능력을 보다 객관적으로 평가하기 위한 방안으로 퍼지 추론을 이용하여 진단평가와 형성평가를 통합 평가할 수 있는 학습평가 방법을 제안한다.

• Asian Pacific Journal of Cancer Prevention
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• 제15권13호
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• pp.5123-5126
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• 2014

Background: To evaluate the diagnostic performance of IOTA simple rules in differentiating between benign and malignant ovarian tumors. Materials and Methods: A study of diagnostic performance was conducted on women scheduled for elective surgery due to ovarian masses between March 2007 and March 2012. All patients underwent ultrasound examination for IOTA simple rules within 24 hours of surgery. All examinations were performed by the authors, who had no any clinical information of the patients, to differentiate between benign and malignant adnexal masses using IOTA simple rules. Gold standard diagnosis was based on pathological or operative findings. Results: A total of 398 adnexal masses, in 376 women, were available for analysis. Of them, the IOTA simple rules could be applied in 319 (80.1%) including 212 (66.5%) benign tumors and 107 (33.6%) malignant tumors. The simple rules yielded inconclusive results in 79 (19.9%) masses. In the 319 masses for which the IOTA simple rules could be applied, sensitivity was 82.9% and specificity 95.3%. Conclusions: The IOTA simple rules have high diagnostic performance in differentiating between benign and malignant adnexal masses. Nevertheless, inconclusive results are relatively common.

• 정보처리학회논문지A
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• 제16A권6호
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• pp.481-488
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• 2009

가스절연개폐장치(Gas Insulated Switchgear:GIS)는 SF6가스를 절연 매체로 하는 대용량 전력 차단기기이다. GIS는 단순한 구조로 고장이 적고 신뢰성이 높은 편이지만 내부를 볼 수 없어 고장 확인이 어렵고 고장이 발생하면 파급 효과가 크고 복구가 어렵다. 따라서 GIS 내부의 이상 징후를 초기에 찾아낼 수 있도록 GIS 예방진단시스템이 도입되었다. GIS 예방진단시스템은 센서에서 수집, 분석한 정보로 이상 징후를 판 단하기 때문에 데이터의 신뢰성과 적시성이 중요하다. 하지만 기존 시스템은 중앙 집중 데이터 수집 방식으로 효율이 낮고 신뢰성과 적시성의 보장이 어렵다. 이러한 신뢰성과 적시성을 보장하기 위하여 GIS 예방진단시스템은 실시간성을 보장하는 미들웨어를 탑재해야 한다. 따라서 본 논문에서는 GIS 예방진단시스템의 신뢰성 향상을 위하여 실시간 분산 컴퓨팅의 적시성 보장을 위해 제안된 TMO를 적용한 미들웨어를 사용한 다. 그리고 TMO를 적용한 데이터 수집 및 감시, 제어 방법을 적용한 새로운 GIS 예방진단 시스템을 제안한다. 논문에서 제안하는 시스템은 TMO의 실시간 기능을 활용하여 데이터의 분산 처리가 가능한 통신제어장치를 개발하여 사용한다. 통신제어장치는 TMO를 통해 실시간 데이 터 수집 및 처리 과정의 적시성을 보장하고 데이터의 신뢰성을 높여 시스템의 성능 향상에 기여한다. 또한, 기존의 서버의 데이터 수집 및 처 리 과정을 통신제어장치가 부담하여 서버의 부하를 줄이고 향후 분산 환경을 지원할 수 있도록 설계하였다. 따라서 제안하는 시스템은 통신제 어장치의 적시성 보장을 통해 GIS 예방진단시스템의 신뢰성과 성능을 향상시키고 GIS의 안정적인 운영을 보장할 수 있다.

• Korean Journal of Radiology
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• 제22권7호
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• pp.1213-1224
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• 2021

Objective: To develop a machine learning (ML) pipeline based on radiomics to predict Coronavirus Disease 2019 (COVID-19) severity and the future deterioration to critical illness using CT and clinical variables. Materials and Methods: Clinical data were collected from 981 patients from a multi-institutional international cohort with real-time polymerase chain reaction-confirmed COVID-19. Radiomics features were extracted from chest CT of the patients. The data of the cohort were randomly divided into training, validation, and test sets using a 7:1:2 ratio. A ML pipeline consisting of a model to predict severity and time-to-event model to predict progression to critical illness were trained on radiomics features and clinical variables. The receiver operating characteristic area under the curve (ROC-AUC), concordance index (C-index), and time-dependent ROC-AUC were calculated to determine model performance, which was compared with consensus CT severity scores obtained by visual interpretation by radiologists. Results: Among 981 patients with confirmed COVID-19, 274 patients developed critical illness. Radiomics features and clinical variables resulted in the best performance for the prediction of disease severity with a highest test ROC-AUC of 0.76 compared with 0.70 (0.76 vs. 0.70, p = 0.023) for visual CT severity score and clinical variables. The progression prediction model achieved a test C-index of 0.868 when it was based on the combination of CT radiomics and clinical variables compared with 0.767 when based on CT radiomics features alone (p < 0.001), 0.847 when based on clinical variables alone (p = 0.110), and 0.860 when based on the combination of visual CT severity scores and clinical variables (p = 0.549). Furthermore, the model based on the combination of CT radiomics and clinical variables achieved time-dependent ROC-AUCs of 0.897, 0.933, and 0.927 for the prediction of progression risks at 3, 5 and 7 days, respectively. Conclusion: CT radiomics features combined with clinical variables were predictive of COVID-19 severity and progression to critical illness with fairly high accuracy.

• 대한디지털의료영상학회논문지
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• 제11권2호
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• pp.69-77
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• 2009

This study gives an account of the collateral standards in IEC 60601-1-3: 2008 specifying the general requirements for basic safety and essential performance of diagnostic X-ray equipment regarding radiation protection as it pertains to the production of X-rays. The collateral standards establish general requirements for safety regarding ionization radiation in diagnostic radiation systems and describe a verifiable evaluation method of suitable requirements regarding control over the lowest possible dose equivalent for patients, radiologic technologists, and others. The particular standards for each equipment can be determined by the general requirements in the collateral standard and the particular standard is followed in the risk management file. The guidelines for radiation safety of diagnostic radiation systems is written up in ISO 13485, ISO 14971, IEC 60601-1-3(2002)1st edition, medical electric equipment part 1-3, and the general requirements for safety-collateral standards: programmable electrical medical systems. Therefore the diagnostic radiation system protects citizens' health rights with the establishment and revisions of laws and standards for diagnostic radiation systems as a background for the general requirements of radiation safe guards applies, as an international trend, standards regarding the medical radiation safety management. The diagnostic radiation system will also assure competitive power through a conforming evaluation unifying the differing standards, technical specifications, and recognized processes.

• Imaging Science in Dentistry
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• 제41권4호
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• pp.143-150
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• 2011

Purpose : The aim of this study was to compare the diagnostic accuracy of cone-beam computed tomography (CBCT) images and bitewing images in detection of secondary caries. Materials and Methods : One hundred and twenty proximal slots of Class II cavities were randomly prepared on human premolar and molar teeth, and restored with amalgam (n=60) and composite resin (n=60). Then, artificial secondary caries lesions were randomly created using round steel No. 4 bur. The teeth were radiographed with a conventional bitewing technique and two CBCT systems; Pax-500ECT and Promax 3D. All images were evaluated by five observers. The area under the receiver operating characteristic (ROC) curve ($A_z$) was used to evaluate the diagnostic accuracy. Significant difference was tested using the Friedman test (p value<0.05). Results : The mean $A_z$ values for bitewing, Pax-500ECT, and Promax 3D imaging systems were 0.882, 0.995, and 0.978, respectively. Significant differences were found between the two CBCT systems and film (p=0.007). For CBCT systems, the axial plane showed the greatest $A_z$ value. Conclusion : Based on the design of this study, CBCT images were better than bitewing radiographs in detection of secondary caries.

• Journal of Advanced Marine Engineering and Technology
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• 제29권5호
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• pp.502-508
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• 2005

Fouling causes serious maintenance problems on heat exchanger tubes and process facilities. To avoid such fouling problems, numerous efforts have been tried. e.g., diagnosis of fouling, reducing and eliminating the fouling. etc.. The objective of the present study is to develop an innovative diagnostic system of fouling, which can detect the scaling attached to the wall non-homogeneously. The performance of the diagnostic system has been evaluated with a scaling simulator that generates scaling on tested tube wall. The measured values with the diagnostic system were compared with the amounts of the scaling generated by the simulator. In addition to, we showed the data that have been executed in field test for reliability verification.

• 품질경영학회지
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• 제28권1호
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• pp.119-131
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• 2000

This paper suggests a new diagnostic measure for detecting influential observations in linear discriminant analysis (LDA). It is developed from a Bayesian point of view using a default Bayes factor obtained from the imaginary training sample methodology. The Bayes factor is taken as a criterion for testing homogeneity of covariance matrices in LDA model. It is noted that the effect of an observation over the criterion is fully explained by the diagnostic measure. We suggest a graphical method that can be taken as a tool for interpreting the diagnostic measure and detecting influential observations. Performance of the measure is examined through an illustrative example.

• 한국정밀공학회지
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• 제21권12호
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• pp.75-83
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• 2004

With the rotating machinery getting more accurate and diversified, the necessity fur an appropriate diagnosis technique and maintenance system has been greatly recognized. However, until now, the operator has executed a monitoring of the machine by the senses or simple the change of RMS (root mean Square) value. So, the diagnostic expert system using the fuzzy inference which the operator can judge easily and expertly a condition of the machine is developed through this study. In this paper, the hardware and software of the diagnostic expert system was composed and the identification of the diagnostic performance of the developed system for 5 fault phenomena was carried out.

• Journal of Electrical Engineering and Technology
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• 제11권2호
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• pp.499-507
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• 2016

Medical imaging techniques such as Magnetic Resonance Imaging (MRI), Computed Tomography (CT) and Ultrasound (US) produce a large amount of digital medical images. Hence, compression of digital images becomes essential and is very much desired in medical applications to solve both storage and transmission problems. But at the same time, an efficient image compression scheme that reduces the size of medical images without sacrificing diagnostic information is required. This paper proposes a novel threshold-based medical image compression algorithm to reduce the size of the medical image without degradation in the diagnostic information. This algorithm discusses a novel type of thresholding to maximize Compression Ratio (CR) without sacrificing diagnostic information. The compression algorithm is designed to get image with high optimum compression efficiency and also with high fidelity, especially for Peak Signal to Noise Ratio (PSNR) greater than or equal to 36 dB. This value of PSNR is chosen because it has been suggested by previous researchers that medical images, if have PSNR from 30 dB to 50 dB, will retain diagnostic information. The compression algorithm utilizes one-level wavelet decomposition with threshold-based coefficient selection.