• 한국산학기술학회논문지
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• 제11권1호
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• pp.209-213
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• 2010

본 논문에서 엔트로피 코딩을 위한 효과적인 예측기를 제안한다. 제안하는 예측기는 MED(median edge detector)와 GAP(gradient adaptive prediction)의 예측 에러 중의 하나를 적응적으로 선택한다. 감소한 에러는 기존의 엔트로피 코딩 방법을 이용하여 부호화한다. 실험 결과, 제안하는 알고리즘이 기존 예측 방법보다 향상된 압축이 가능함을 보인다.

• 대한금속재료학회지
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• 제46권9호
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• pp.554-562
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• 2008

The distribution and prediction interval for the misorientation angle of grain boundary at which $Cr_2N$ was precipitated during heating at $900^{\circ}C$ for $10^4$ sec were newly estimated, and followed by the estimation of mathematical and median rank methods. The probability density function of the misorientation angle can be estimated by a statistical analysis. And then the ($1-{\alpha}$)100% prediction interval of misorientation angle obtained by the estimated probability density function. If the estimated probability density function was symmetric then a prediction interval for the misorientation angle could be derived by the estimated probability density function. In the case of non-symmetric probability density function, the prediction interval could be obtained from the cumulative distribution function of the estimated probability density function. In this paper, 95, 99 and 99.73% prediction interval obtained by probability density function method and cumulative distribution function method and compared with the former results by median rank regression or mathematical method.

• Korean Journal of Radiology
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• 제22권5호
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• pp.697-705
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• 2021

Objective: To investigate the feasibility and the accuracy of the coronary CT angiography (CCTA)-derived Registry of Crossboss and Hybrid procedures in France, the Netherlands, Belgium and United Kingdom (RECHARGE) score (RECHARGECCTA) for the prediction of procedural success and 30-minutes guidewire crossing in percutaneous coronary intervention (PCI) for chronic total occlusion (CTO). Materials and Methods: One hundred and twenty-four consecutive patients (mean age, 54 years; 79% male) with 131 CTO lesions who underwent CCTA before catheter angiography (CA) with CTO-PCI were retrospectively enrolled in this study. The RECHARGECCTA scores were calculated and compared with RECHARGECA and other CTA-based prediction scores, including Multicenter CTO Registry of Japan (J-CTO), CT Registry of CTO Revascularisation (CT-RECTOR), and Korean Multicenter CTO CT Registry (KCCT) scores. Results: The procedural success rate of the CTO-PCI procedures was 72%, and 61% of cases achieved the 30-minutes wire crossing. No significant difference was observed between the RECHARGECCTA score and the RECHARGECA score for procedural success (median 2 vs. median 2, p = 0.084). However, the RECHARGECCTA score was higher than the RECHARGECA score for the 30-minutes wire crossing (median 2 vs. median 1.5, p = 0.001). The areas under the curve (AUCs) of the RECHARGECCTA and RECHARGECA scores for predicting procedural success showed no statistical significance (0.718 vs. 0.757, p = 0.655). The sensitivity, specificity, positive predictive value, and the negative predictive value of the RECHARGECCTA scores of ≤ 2 for predictive procedural success were 78%, 60%, 43%, and 87%, respectively. The RECHARGECCTA score showed a discriminative performance that was comparable to those of the other CTA-based prediction scores (AUC = 0.718 vs. 0.665-0.717, all p > 0.05). Conclusion: The non-invasive RECHARGECCTA score performs better than the invasive determination for the prediction of the 30-minutes wire crossing of CTO-PCI. However, the RECHARGECCTA score may not replace other CTA-based prediction scores for predicting CTO-PCI success.

• 전자공학회논문지 IE
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• 제47권2호
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• pp.27-31
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• 2010

본 논문에서는 무손실 압축을 위하여 예측기를 스위칭하는 알고리즘을 제안한다. 제안하는 방법은 MED(median edge detector), GAP(gradient adaptive prediction) 예측기의 예측 에러들에 따라 적응적으로 하나의 예측기를 이용하여 화소값을 예측한다. 그리고, 에러는 기존의 엔트로피 방법을 이용하여 측정한다. 실험 결과, 제안하는 알고리즘이 기존 예측 방법보다 적은 에러값과 엔트로피를 가짐으로써 향상된 압축을 할 수 있음을 보인다.

• Journal of Electrical Engineering and Technology
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• 제13권4호
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• pp.1504-1514
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• 2018

The objective of this study is to compare the suitability of a non-parametric and 3 parametric distributions in the characterization of prediction intervals of photovoltaic power forecasts with high confidence levels. The prediction intervals of the forecasts are calculated using a method based on recent past data similar to the target forecast input data, and on a distribution assumption for the forecast error. To compare the suitability of the distributions, prediction intervals were calculated using the proposed method and each of the 4 distributions. The calculations were done for one year of day-ahead forecasts of hourly power generation of 432 PV systems. The systems have different sizes and specifications, and are installed in different locations in Japan. The results show that, in general, the non-parametric distribution assumption for the forecast error yielded the best prediction intervals. For example, with a confidence level of 85% the use of the non-parametric distribution assumption yielded a median annual forecast error coverage of 86.9%. This result was close to the one obtained with the Laplacian distribution assumption (87.8% of coverage for the same confidence level). Contrasting with that, using a Gaussian and Hyperbolic distributions yielded median annual forecast error coverage of 89.5% and 90.5%.

• ETRI Journal
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• 제34권4호
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• pp.564-571
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• 2012

This paper presents an algorithm for removing high-density impulsive noise that generates some serious distortions in edge regions of an image. Although many works have been presented to reduce edge distortions, these existing methods cannot sufficiently restore distorted edges in images with large amounts of impulsive noise. To solve this problem, this paper proposes a method using connected lines extracted from a binarized image, which segments an image into uniform and edge regions. For uniform regions, the existing simple adaptive median filter is applied to remove impulsive noise, and, for edge regions, a prediction filter and a line-weighted median filter using the connected lines are proposed. Simulation results show that the proposed method provides much better performance in restoring distorted edges than existing methods provide. When noise content is more than 20 percent, existing algorithms result in severe edge distortions, while the proposed algorithm can reconstruct edge regions similar to those of the original image.

• Communications for Statistical Applications and Methods
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• 제22권3호
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• pp.241-253
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• 2015

In this paper we predict the track of typhoons using a Bayesian principal component regression model based on wind field data. Data is obtained at each time point and we applied the Bayesian principal component regression model to conduct the track prediction based on the time point. Based on regression model, we applied to variable selection prior and two kinds of prior distribution; normal and Laplace distribution. We show prediction results based on Bayesian Model Averaging (BMA) estimator and Median Probability Model (MPM) estimator. We analysis 8 typhoons in 2006 using data obtained from previous 6 years (2000-2005). We compare our prediction results with a moving-nest typhoon model (MTM) proposed by the Korea Meteorological Administration. We posit that is possible to predict the track of a typhoon accurately using only a statistical model and without a dynamical model.

• 대한원격탐사학회지
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• 제38권6_1호
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• pp.1047-1056
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• 2022

지구 온난화의 중요한 지시자인 북극의 바다 얼음인 해빙은 기후 시스템, 선박의 항로 안내, 어업 활동 등에서의 중요성으로 인해 다양한 학문 분야에서 관심을 받고 있다. 최근 자동화와 효율적인 미래 예측에 대한 요구가 커지면서 인공지능을 이용한 새로운 해빙 예측 모델들이 전통적인 수치 및 통계 예측 모델을 대체하기 위해 개발되고 있다. 본 연구에서는 북극 해빙의 전역적, 지역적 특징을 학습할 수 있는 two-stream convolutional long- and short-term memory (TS-ConvLSTM) 인공지능 모델의 북극 해빙 면적이 최저를 보이는 9월에 대해 2001년부터 2021년까지 장기적인 성능 검증을 통해 향후 운용 가능한 시스템으로써의 가능성을 살펴보고자 한다. 장기 자료를 통한 검증 결과 TS-ConvLSTM 모델이 훈련자료의 양이 증가하면서 향상된 예측 성능을 보여주고 있지만, 최근 지구 온난화로 인한 단년생 해빙의 감소로 인해 해빙 농도 5-50% 구간에서는 예측력이 저하되고 있음을 보여주었다. 반면 TS-ConvLSTM에 의해 예측된 해빙 면적과 달리 Sea Ice Prediction Network에 제출된 Sea Ice Outlook (SIO)들의 해빙 면적 중간값의 경우 훈련자료가 늘어나더라도 눈에 띄는 향상을 보이지 않았다. 본 연구를 통해 TS-ConvLSTM 모델의 향후 북극 해빙 예측 시스템의 운용 가능 잠재성을 확인하였으나, 향후 연구에서는 예측이 어려운 자연 환경에서 더욱 안정성 있는 예측 시스템 개발을 위해 더 많은 시공간 변화 패턴을 학습할 수 있는 방안을 고려해야 할 것이다.

• 대한한의학회지
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• 제41권2호
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• pp.58-79
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• 2020

Objectives: The purpose of this study is to predict the weight loss by applying machine learning using real-world clinical data from overweight and obese adults on weight loss program in 4 Korean Medicine obesity clinics. Methods: From January, 2017 to May, 2019, we collected data from overweight and obese adults (BMI≥23 kg/m2) who registered for a 3-month Gamitaeeumjowi-tang prescription program. Predictive analysis was conducted at the time of three prescriptions, and the expected reduced rate and reduced weight at the next order of prescription were predicted as binary classification (classification benchmark: highest quartile, median, lowest quartile). For the median, further analysis was conducted after using the variable selection method. The data set for each analysis was 25,988 in the first, 6,304 in the second, and 833 in the third. 5-fold cross validation was used to prevent overfitting. Results: Prediction accuracy was increased from 1^st to 2^nd and 3^rd analysis. After selecting the variables based on the median, artificial neural network showed the highest accuracy in 1^st (54.69%), 2^nd (73.52%), and 3^rd (81.88%) prediction analysis based on reduced rate. The prediction performance was additionally confirmed through AUC, Random Forest showed the highest in 1^st (0.640), 2^nd (0.816), and 3^rd (0.939) prediction analysis based on reduced weight. Conclusions: The prediction of weight loss by applying machine learning showed that the accuracy was improved by using the initial weight loss information. There is a possibility that it can be used to screen patients who need intensive intervention when expected weight loss is low.

• Asian Pacific Journal of Cancer Prevention
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• 제14권8호
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• pp.4847-4851
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• 2013

Objectives: To evaluate accuracy of FDG-PET CT in prediction of persistent disease in head and neck cancer cases and to determine prognostic value of metabolic tumor response. Materials and Methods: Between 2009 and 2011, 46 patients with squamous cell carcinoma of head and neck receiving PET-CT were treated with definitive radiotherapy, with or without chemotherapy. There were 29 nasopharyngeal, 11 hypopharyngeal, 3 oropharyngeal and 3 laryngeal cancer patients, with a median age of 50.5 years (range 16-84), 32 males and 14 females. All patients were evaluated with PET-CT median 3-5 months (2.4-9.4) after completion of radiotherapy. Results: After a median 20 months of follow up, complete metabolic response was observed in 63% of patients. Suspicious residual uptake was present in 10.9% and residual metabolic uptake in 26.0% of patients. The overall sensitivity, specificity, positive predictive value and negative predictive value of FDG-PET-CT for detection of residual disease was 91% and 81%, 64% and 96% respectively. Two year LRC was 95% in complete responders while it was 34% in non-complete responders. Conclusions: FDG PET CT is a valuable tool for assessment of treatment response, especially in patients at high risk of local recurrence, and also as an indicator of prognosis. Definitely more precise criteria are required for assessment of response, there being no clear cut uptake value indicating residual disease. Futhermore, repair processes of normal tissue may consume glucose which appear as increased uptake in control FDG PET CT.