• Title/Summary/Keyword: predictive distribution

검색결과 294건 처리시간 0.029초

다변수 LSTM 순환신경망 딥러닝 모형을 이용한 미술품 가격 예측에 관한 실증연구 (An Empirical Study on Prediction of the Art Price using Multivariate Long Short Term Memory Recurrent Neural Network Deep Learning Model)

  • 이지인;송정석
    • 한국콘텐츠학회논문지
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    • 제21권6호
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    • pp.552-560
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    • 2021
  • 새로운 미술품 유통방식의 발달로 미술품의 미적 효용을 넘어 투자재로서 바라보는 시각이 활성화되고 있다. 미술품의 가격은 주식이나 채권 등과 달리 객관적 요소와 주관적 요소들이 모두 반영되어 결정되는 이질적 특성이 있기 때문에 가격 예측에 있어서 그 불확실성이 높다. 본 연구에서는 LSTM(장단기 기억) 순환신경망 딥러닝 모형을 활용하여 낙찰총액 순위 1위부터 10위까지의 한국 작가의 회화 작품을 대상으로 작가의 특성, 작품의 물리적 특성, 판매적 특성 등을 입력으로 하여 경매 낙찰가의 예측을 시도하였다. 연구 결과, 모델에 의한 예측 가격과 실제 낙찰 가격의 차이를 설명하는 RMSE 값이 0.064 수준이었으며 작가별로는 이대원 작가의 예측력이 가장 높았고, 이중섭 작가의 예측력이 가장 낮았다. 투자재로서 미술품 시장이 더욱 활성화되고 경매 낙찰 가격의 예측 수요가 높아지면서 본 연구의 결과가 활용될 수 있을 것이다.

Licochalcone H Induces Cell Cycle Arrest and Apoptosis in Human Skin Cancer Cells by Modulating JAK2/STAT3 Signaling

  • Park, Kyung-Ho;Joo, Sang Hoon;Seo, Ji-Hye;Kim, Jumi;Yoon, Goo;Jeon, Young-Joo;Lee, Mee-Hyun;Chae, Jung-Il;Kim, Woo-Keun;Shim, Jung-Hyun
    • Biomolecules & Therapeutics
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    • 제30권1호
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    • pp.72-79
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    • 2022
  • Licochalcone H (LCH) is a phenolic compound synthetically derived from licochalcone C (LCC) that exerts anticancer activity. In this study, we investigated the anticancer activity of LCH in human skin cancer A375 and A431 cells. The 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium (MTS) cell viability assay was used to evaluate the antiproliferative activity of LCH. Cell cycle distribution and the induction of apoptosis were analyzed by flow cytometry. Western blotting assays were performed to detect the levels of proteins involved in cell cycle progression, apoptosis, and the JAK2/STAT3 signaling pathway. LCH inhibited the growth of cells in dose- and time-dependent manners. The annexin V/propidium iodide double staining assay revealed that LCH induced apoptosis, and the LCH-induced apoptosis was accompanied by cell cycle arrest in the G1 phase. Western blot analysis showed that the phosphorylation of JAK2 and STAT3 was decreased by treatment with LCH. The inhibition of the JAK2/STAT3 signaling pathway by pharmacological inhibitors against JAK2/STAT3 (cryptotanshinone (CTS) and S3I-201) simulated the antiproliferative effect of LCH suggesting that LCH induced apoptosis by modulating JAK2/STAT3 signaling.

SMOTE와 Light GBM 기반의 불균형 데이터 개선 기법 (Imbalanced Data Improvement Techniques Based on SMOTE and Light GBM)

  • 한영진;조인휘
    • 정보처리학회논문지:컴퓨터 및 통신 시스템
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    • 제11권12호
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    • pp.445-452
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    • 2022
  • 디지털 세상에서 불균형 데이터에 대한 클래스 분포는 중요한 부분이며 사이버 보안에 큰 의미를 차지한다. 불균형 데이터의 비정상적인 활동을 찾고 문제를 해결해야 한다. 모든 트랜잭션의 패턴을 추적할 수 있는 시스템이 필요하지만, 일반적으로 패턴이 비정상인 불균형 데이터로 기계학습을 하면 소수 계층에 대한 성능은 무시되고 저하되며 예측 모델은 부정확하게 편향될 수 있다. 본 논문에서는 불균형 데이터 세트를 해결하기 위한 접근 방식으로 Synthetic Minority Oversampling Technique(SMOTE)와 Light GBM 알고리즘을 이용하여 추정치를 결합하여 대상 변수를 예측하고 정확도를 향상시켰다. 실험 결과는 Logistic Regression, Decision Tree, KNN, Random Forest, XGBoost 알고리즘과 비교하였다. 정확도, 재현율에서는 성능이 모두 비슷했으나 정밀도에서는 2개의 알고리즘 Random Forest 80.76%, Light GBM 97.16% 성능이 나왔고, F1-score에서는 Random Forest 84.67%, Light GBM 91.96% 성능이 나왔다. 이 실험 결과로 Light GBM은 성능이 5개의 알고리즘과 비교하여 편차없이 비슷하거나 최대 16% 향상됨을 접근 방식으로 확인할 수 있었다.

딥러닝 기반 함수비 예측을 이용한 사질토 지반 침투 및 수분 재분포 분석 (Infiltration and Water Redistribution in Sandy Soil: Analysis Using Deep Learning-Based Soil Moisture Prediction)

  • 정은수;봉태호;서정일
    • 한국산림과학회지
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    • 제112권4호
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    • pp.490-501
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    • 2023
  • 본 연구에서는 강우의 침투과정 및 수분 재분포 현상을 분석하기 위하여 실내 컬럼실험을 수행하였으며, 토층 내 함수비를 효율적으로 측정하기 위하여 딥러닝 기법 중 하나인 합성곱신경망(Convolutional Neural Network, CNN)을 사용하여 함수비 예측 모델을 구축하였다. 컬럼실험으로부터 획득된 디지털 이미지를 구축된 CNN 모델에 적용한 결과 시간에 따른 토층별 함수비를 효과적으로 측정할 수 있었으며, 토층별로 설치된 함수비 센서에 따른 함수비와도 비교적 잘 일치하는 것으로 나타났다. 결과적으로 CNN을 활용하여 토층 내 연속적인 함수비 분포를 파악하는 것이 가능하였으며, 토성 및 지반 함수비 조건에 따른 침투 과정을 효과적으로 분석할 수 있었다.

Hepatocellular Carcinoma: Texture Analysis of Preoperative Computed Tomography Images Can Provide Markers of Tumor Grade and Disease-Free Survival

  • Jiseon Oh;Jeong Min Lee;Junghoan Park;Ijin Joo;Jeong Hee Yoon;Dong Ho Lee;Balaji Ganeshan;Joon Koo Han
    • Korean Journal of Radiology
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    • 제20권4호
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    • pp.569-579
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    • 2019
  • Objective: To investigate the usefulness of computed tomography (CT) texture analysis (CTTA) in estimating histologic tumor grade and in predicting disease-free survival (DFS) after surgical resection in patients with hepatocellular carcinoma (HCC). Materials and Methods: Eighty-one patients with a single HCC who had undergone quadriphasic liver CT followed by surgical resection were enrolled. Texture analysis of tumors on preoperative CT images was performed using commercially available software. The mean, mean of positive pixels (MPP), entropy, kurtosis, skewness, and standard deviation (SD) of the pixel distribution histogram were derived with and without filtration. The texture features were then compared between groups classified according to histologic grade. Kaplan-Meier and Cox proportional hazards analyses were performed to determine the relationship between texture features and DFS. Results: SD and MPP quantified from fine to coarse textures on arterial-phase CT images showed significant positive associations with the histologic grade of HCC (p < 0.05). Kaplan-Meier analysis identified most CT texture features across the different filters from fine to coarse texture scales as significant univariate markers of DFS. Cox proportional hazards analysis identified skewness on arterial-phase images (fine texture scale, spatial scaling factor [SSF] 2.0, p < 0.001; medium texture scale, SSF 3.0, p < 0.001), tumor size (p = 0.001), microscopic vascular invasion (p = 0.034), rim arterial enhancement (p = 0.024), and peritumoral parenchymal enhancement (p = 0.010) as independent predictors of DFS. Conclusion: CTTA was demonstrated to provide texture features significantly correlated with higher tumor grade as well as predictive markers of DFS after surgical resection of HCCs in addition to other valuable imaging and clinico-pathologic parameters.

아스팔트 혼합물의 골재 간극률 예측을 위한 기계학습 프레임워크 (Machine Learning Framework for Predicting Voids in the Mineral Aggregation in Asphalt Mixtures)

  • 박혜민;나일호;김현환;지봉준
    • 한국지반신소재학회논문집
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    • 제23권1호
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    • pp.17-25
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    • 2024
  • 골재 간극률은 구조적 강도, 내구성, 배수 및 투수성 등 다양한 아스팔트의 특성에 직접적인 영향을 미친다. 따라서 아스팔트 포장이 사용되는 위치, 기후, 환경 등에 적절하도록 골재 간극률이 설계되어야한다. 하지만 골재 간극률은 다양한 요인들에 의해 영향을 받으므로 그 설계가 쉽지 않다. 예를 들어 골재 입자의 크기 분포, 구성이나 아스팔트 바인더의 양, 다짐 수준 등 다양한 영향인자가 존재한다. 본 연구에서는 골재 간극률에 영향을 미치는 요인들로부터 골재 간극률을 예측하고자 하였다. 이를 위해 다양한 기계학습 모델 방법을 적용하였고 단일 기계학습 모델을 적용했을 때보다 높은 정확도로 골재 간극률을 예측할 수 있음을 보였다. 본 연구의 결과는 경험과 노동집약적인 실험에 의존하는 골재 간극률 예측에 데이터 기반의 접근방법을 적용할 수 있음을 보였으며 향후 최적 골재 간극률 설계 등에 활용 가능할 것으로 기대된다.

가계 재무건전성이 주택투자수요에 미치는 영향에 관한 연구 (A Study on the Financial Strength of Households on House Investment Demand)

  • 노상윤;윤보현;최영민
    • 유통과학연구
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    • 제12권4호
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    • pp.31-39
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    • 2014
  • Purpose - This study investigates the following two issues. First, we attempt to find the important determinants of housing investment and to identify their significance rank using survey panel data. Recently, the expansion of global uncertainty in the real estate market has directly and indirectly influenced the Korean housing market; households demonstrate a sensitive reaction to changes in that market. Therefore, this study aims to draw conclusions from understanding how the impact of financial strength of the household is related to house investment. Second, we attempt to verify the effectiveness of diverse indices of financial strength such as DTI, LTV, and PIR as measures to monitor the housing market. In the continuous housing market recession after the global crisis, the government places top priority on residence stability. However, the government still imposes forceful restraints on indices of financial strength. We believe this study verifies the utility of these regulations when used in the housing market. Research design, data, and methodology - The data source for this study is the "National Survey of Tax and Benefit" from 2007 (1st) to 2011 (5th) by the Korea Institute of Public Finance. Based on this survey data, we use panel data of 3,838 households that have been surveyed continuously for 5 years. We sort the base variables according to relevance of house investment criteria using the decision tree model (DTM), which is the standard decision-making model for data-mining techniques. The DTM method is known as a powerful methodology to identify contributory variables for predictive power. In addition, we analyze how important explanatory variables and the financial strength index of households affect housing investment with the binary logistic multi-regressive model. Based on the analyses, we conclude that the financial strength index has a significant role in house investment demand. Results - The results of this research are as follows: 1) The determinants of housing investment are age, consumption expenditures, income, total assets, rent deposit, housing price, habits satisfaction, housing scale, number of household members, and debt related to housing. 2) The impact power of these determinants has changed more or less annually due to economic situations and housing market conditions. The level of consumption expenditure and income are the main determinants before 2009; however, the determinants of housing investment changed to indices of the financial strength of households, i.e., DTI, LTV, and PIR, after 2009. 3) Most of all, since 2009, housing loans has been a more important variable than the level of consumption in making housing market decisions. Conclusions - The results of this research show that sound financing of households has a stronger effect on housing investment than reduced consumption expenditures. At the same time, the key indices that must be monitored by the government under economic emergency conditions differ from those requiring monitoring under normal market conditions; therefore, political indices to encourage and promote the housing market must be divided based on market conditions.

소아 무균성 뇌막염의 역학적 연구를 위한 건강보험자료원의 유용성 평가 (Assessment of the Availability of Health Insurance Data for Epidemiologic Study of Childhood Aseptic Meningitis)

  • 박수경;기모란;손영모;김호;정해관
    • Journal of Preventive Medicine and Public Health
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    • 제36권4호
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    • pp.349-358
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    • 2003
  • Objectives : Aseptic meningitis is a major cause of Korean childhood morbidity late spring and early summer. However, the nationwide incidences of the disease have not been reported. This study was conducted to evaluate the availability of National Health Insurance data (NHID) for the study of an epidemiological trend in the surveillance of aseptic meningitis in children. Methods : All the claims, under A87, A87.8, and A87.9 by ICD-10, among children below 15 years of age, to the National Health Insurance Corporation, between January and December 1998, were extracted. A survey of the medical record of 3,874 cases from 136 general hospitals was peformed. The availability of the NHID was evaluated by the three following methods: 1) The diagnostic accuracy (the positive Predictive value : proportion of the confirmed aseptic meningitis among the subjects registered as above disease-codes in NHID) was evaluated through a chart review, and according to age, gender, month and region of disease-occurrence. 2) The distribution of confirmed cases was compared with the distribution of total subjects from the NHID, for subjects in General hospitals, or the subjects surveyed. 3) The proportion of confirmed CSF test was confirmed, and the relating factor, which was the difference in CSF-test rate, analyzed. Results : Among 3,874 cases, CSF examinations were peformed on 1,845 (47.6%), and the CSF-test rates were different according to the medical utility (admission vs. OPD visit) and the severity of the symptoms and signs. The diagnostic accuracy for aseptic meningitis, and during the epidemic (May-Aug) and sporadic (Sept-Apr) periods, were 85.0 (1,568/1,845), 86.0 (1,239/l,440) and 81.2% (329/405), respectively. The distributions by age, sex, month or period (epidemic/sporadic) and region, in the confirmed cases, were similar to those in the NHID, in both the subjects at General hospitals and in those surveyed, to within ${\pm}7%$. Conclusions : In this paper, the NHID for the subjects registered with an aseptic meningitis disease-code might be available for an epidemiological study on the incidence-estimation of childhood aseptic meningitis, as the NHID could include both the probable and definite cases. On the basis of this result, further studies of time-series and secular trend analyses, using the NHID, will be peformed.

유통업체의 부실예측모형 개선에 관한 연구 (Performance Evaluation and Forecasting Model for Retail Institutions)

  • 김정욱
    • 유통과학연구
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    • 제12권11호
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    • pp.77-83
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    • 2014
  • Purpose - The National Agricultural Cooperative Federation of Korea and National Fisheries Cooperative Federation of Korea have prosecuted both financial and retail businesses. As cooperatives are public institutions and receive government support, their sound management is required by the Financial Supervisory Service in Korea. This is mainly managed by CAEL, which is changed by CAMEL. However, NFFC's business section, managing the finance and retail businesses, is unified and evaluated; the CAEL model has an insufficient classification to evaluate the retail industry. First, there is discrimination power as regards CAEL. Although the retail business sector union can receive a higher rating on a CAEL model, defaults have often been reported. Therefore, a default prediction model is needed to support a CAEL model. As we have the default prediction model using a subdivision of indexes and statistical methods, it can be useful to have a prevention function through the estimation of the retail sector's default probability. Second, separating the difference between the finance and retail business sectors is necessary. Their businesses have different characteristics. Based on various management indexes that have been systematically managed by the National Fisheries Cooperative Federation of Korea, our model predicts retail default, and is better than the CAEL model in its failure prediction because it has various discriminative financial ratios reflecting the retail industry situation. Research design, data, and methodology - The model to predict retail default was presented using logistic analysis. To develop the predictive model, we use the retail financial statements of the NFCF. We consider 93 unions each year from 2006 to 2012 to select confident management indexes. We also adapted the statistical power analysis that is a t-test, logit analysis, AR (accuracy ratio), and AUROC (Area Under Receiver Operating Characteristic) analysis. Finally, through the multivariate logistic model, we show that it is excellent in its discrimination power and higher in its hit ratio for default prediction. We also evaluate its usefulness. Results - The statistical power analysis using the AR (AUROC) method on the short term model shows that the logistic model has excellent discrimination power, with 84.6%. Further, it is higher in its hit ratio for failure (prediction) of total model, at 94%, indicating that it is temporally stable and useful for evaluating the management status of retail institutions. Conclusions - This model is useful for evaluating the management status of retail union institutions. First, subdividing CAEL evaluation is required. The existing CAEL evaluation is underdeveloped, and discrimination power falls. Second, efforts to develop a varied and rational management index are continuously required. An index reflecting retail industry characteristics needs to be developed. However, extending this study will need the following. First, it will require a complementary default model reflecting size differences. Second, in the case of small and medium retail, it will need non-financial information. Therefore, it will be a hybrid default model reflecting financial and non-financial information.

중선형 모형을 이용한 비선형 시계열 패널자료의 동질성검정에 대한 연구 (A Study on the Test of Homogeneity for Nonlinear Time Series Panel Data Using Bilinear Models)

  • 김인규
    • 디지털융복합연구
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    • 제12권7호
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    • pp.261-266
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    • 2014
  • 시계열 모형에서 모수의 수가 많으면 모수추정에 따르는 오차가 커지게 되므로 예측을 하는데 많은 어려움이 있다. 만약 여러개의 시계열 자료들이 동일한 모형에서부터 얻어졌다고 하는 동질성 가설이 채택되면 모수축약을 이룰 수 있고, 더 좋은 예측값을 얻을 수 있다. 비선형 시계열 패널 자료는 각각의 시계열마다 모수들이 있기 때문에 매우 많은 모수가 존재하게되고, 모수의 수가 많으면 모수추정에 따르는 오차가 커지게 되어 예측의 정확도가 떨어지게 된다. 패널내에 존재하는 독립적인 여러 시계열들의 동질성이 만족되면 시계열을 종합하여 모수를 추정하고 검정할 수 있다. m개의 독립적인 비선형 시계열 패널 자료의 동질성 검정을 알아보기 위하여 모형을 설정하고 이 모형에 대한 정상성 조건을 구하였고, 동질성 검정통계량을 유도했으며, 구한 검정 통계량의 극한분포가 ${\chi}^2$ 분포를 따르는 것을 보였다. 실증분석에 있어서는 비선형 시계열 자료중 중선형 시계열 모형의 동질성 검정을 하고, 실제 우리나라 주식자료를 2개의 집단으로 나누어 비선형 시계열 패널 자료의 동질성 검정에 대한 분석을 하였다.