• 폴리머
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• 제37권2호
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• pp.135-140
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• 2013

Poly(methyl acrylate)-poly(acrylonitrile) 공중합체의 응력완화 실험은 용매기를 부착한 인장 시험기를 사용하여 여러 온도의 공기 중, 증류수, pH 3, 7, 11 용액에서 실행하였다. Ree-Eyring and Maxwell 모델로부터 얻은 완화스펙트럼 식에 실험적인 응력완화 곡선을 대입하여 poly(methyl acrylate)-poly(acrylonitrile) 공중합체의 완화스펙트럼을 얻었다. 완화스펙트럼의 계산은 Laplace 변환법을 사용한 컴퓨터 프로그램을 이용하였다. 이들 시료의 완화스펙트럼은 유동단위의 분자량과 자체확산 분포와 밀접한 관계가 있음을 알 수 있었다.

• 한국대기환경학회지
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• 제24권1호
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• pp.100-107
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• 2008

The objective of this study was to quantitatively estimate PM-10 source contribution in Gumi City, Korea. Ambient PM-10 samples were collected by a high volume air sampler, which operated for 84 different days with a 24-h sampling basis, from June 14,2001 though May 19, 2003. The filter samples were analyzed for determining 13 inorganic elements, 3 anions, and a total carbon. The study has intensively applied a receptor model, the PMF (Positive Matrix Factorization) model. The results from PMF modeling indicated that a total of seven sources were independently identified and each source was contributed to the ambient Gumi City from secondary sulfate (34%), motor vehicle (26%), soil relation (5%), field burning (3%), industrial relation (3%), secondary nitrate (22%), and incinration (7%) in terms of PM-10 mass, respectively.

• Journal of the Korean Wood Science and Technology
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• 제47권1호
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• pp.101-109
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• 2019

This paper examines the classification of five coniferous species, including larch (Larix kaempferi), red pine (Pinus densiflora), Korean pine (Pinus koraiensis), cedar (Cryptomeria japonica), and cypress (Chamaecyparis obtusa), using near-infrared (NIR) spectra. Fifty lumber samples were collected for each species. After air-drying the lumber, the NIR spectra (wavelength = 780-2500 nm) were acquired on the wide face of the lumber samples. Soft independent modeling of class analogy (SIMCA) was performed to classify the five species using their NIR spectra. Three types of spectra (raw, standard normal variated, and Savitzky-Golay $2^{nd}$ derivative) were used to compare the classification reliability of the SIMCA models. The SIMCA model based on Savitzky-Golay $2^{nd}$ derivatives preprocessing was determined as the best classification model in this study. The accuracy, minimum precision, and minimum recall of the best model (PCA models using Savitzky-Golay $2^{nd}$ derivative preprocessed spectra) were evaluated as 73.00%, 98.54% (Korean pine), and 67.50% (Korean pine), respectively.

• 한국멀티미디어학회논문지
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• 제25권1호
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• pp.82-91
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• 2022

In this paper, time series prediction method of photovoltaic power is introduced using seasonal autoregressive integrated moving average (SARIMA). In order to obtain the best fitting model by a time series method in the absence of an environmental sensor, this research was used data below 50% of cloud cover. Three samples were extracted by time intervals from the raw data. After that, the best fitting models were derived from mean absolute percentage error (MAPE) with the minimum akaike information criterion (AIC) or beysian information criterion (BIC). They are SARIMA (1,0,0)(0,2,2)14, SARIMA (1,0,0)(0,2,2)28, SARIMA (2,0,3)(1,2,2)55. Generally parameter of model derived from BIC was lower than AIC. SARIMA (2,0,3)(1,2,2)55, unlike other models, was drawn by AIC. And the performance of models obtained by SARIMA was compared. MAPE value was affected by the seasonal period of the sample. It is estimated that long seasonal period samples include atmosphere irregularity. Consequently using 1 hour or 30 minutes interval sample is able to be helpful for prediction accuracy improvement.

• Communications for Statistical Applications and Methods
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• 제30권6호
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• pp.589-603
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• 2023

Deep generative models target to infer the underlying true data distribution, and it leads to a huge success in generating fake-but-realistic data. Regarding such a perspective, the data attributes can be a crucial factor in the data generation process since non-existent counterfactual samples can be generated by altering certain factors. For example, we can generate new portrait images by flipping the gender attribute or altering the hair color attributes. This paper proposes counterfactual disentangled variational autoencoder generative adversarial networks (CDVAE-GAN), specialized for data attribute level counterfactual data generation. The structure of the proposed CDVAE-GAN consists of variational autoencoders and generative adversarial networks. Specifically, we adopt a Gaussian variational autoencoder to extract low-dimensional disentangled data features and auxiliary Bernoulli latent variables to model the data attributes separately. Also, we utilize a generative adversarial network to generate data with high fidelity. By enjoying the benefits of the variational autoencoder with the additional Bernoulli latent variables and the generative adversarial network, the proposed CDVAE-GAN can control the data attributes, and it enables producing counterfactual data. Our experimental result on the CelebA dataset qualitatively shows that the generated samples from CDVAE-GAN are realistic. Also, the quantitative results support that the proposed model can produce data that can deceive other machine learning classifiers with the altered data attributes.

• International Journal of Advanced Culture Technology
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• 제11권3호
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• pp.297-301
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• 2023

The study identified the various causes of odor problems, the discomfort they cause, and the importance of the public health and environmental issues associated with them. To solve the odor problem, you must identify the cause and perform an accurate analysis. Therefore, we proposed a CNN-Transformer hybrid model (CTHM) that combines CNN and Transformer and evaluated its performance. It was evaluated using a dataset consisting of 120,000 odor samples, and experimental results showed that CTHM achieved an accuracy of 93.000%, a precision of 92.553%, a recall of 94.167%, an F1 score of 92.880%, and an RMSE of 0.276. Our results showed that CTHM was suitable for odor analysis and had excellent prediction performance. Utilization of this model is expected to help address odor problems and alleviate public health and environmental concerns.

• Structural Engineering and Mechanics
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• 제87권6호
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• pp.601-614
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• 2023

In this study, the uniaxial ratcheting effect of Z2CND18.12N austenitic stainless steel at room and elevated temperatures is firstly simulated based on the Ahmadzadeh-Varvani hardening rule (A-V model), which is embedded into the finite element software ABAQUS by writing the user material subroutine UMAT. The results show that the predicted results of A-V model are lower than the experimental data, and the A-V model is difficult to control ratcheting strain rate. In order to improve the predictive ability of the A-V model, the parameter γ2 of the A-V model is modified using the isotropic hardening criterion, and the extended A-V model is proposed. Comparing the predicted results of the above two models with the experimental data, it is shown that the prediction results of the extended A-V model are in good agreement with the experimental data.

• Earthquakes and Structures
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• 제25권6호
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• pp.429-442
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• 2023

To study the seismic vulnerability of the composite material structure of adobe and timber, we collected and statistically analysed empirical observation samples of 542,214,937 m² and 467,177 buildings that were significantly impacted during the 179 earthquakes that occurred in mainland China from 1976 to 2010. In multi-intensity regions, combined with numerical analysis and a probability model, a non-linear continuous regression model of the vulnerability, considering the empirical seismic damage area (number of buildings) and the ratio of seismic damage, was established. Moreover, a probability matrix model of the empirical seismic damage mean value was provided. Considering the coupling effect of the annual and seismic fortification factors, an empirical seismic vulnerability curve model was constructed in the multiple-intensity regions. A probability matrix model of the mean vulnerability index (MVI) was proposed, and was validated through the above-mentioned reconnaissance sample data. A matrix model of the MVI of the regions (19 provinces in mainland China) based on the parameter (MVI) was established.

• 한국지반공학회논문집
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• 제24권8호
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• pp.99-109
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• 2008

본 연구는 군산 새만금지역의 점성토를 소성지수 15%, 30%, 45%, 60%가 되도록 벤초나이트를 첨가한 인공의 시료를 이용하여 하중재하기간을 1일, 2일, 4일, 8일 등으로 달리한 표준압밀시험을 실시하였다. 그리고 인천, 광양, 울산지역의 불교란 시료에 대한 압밀시험도 같이 수행하여 소성지수와 압밀하중재하기간이 2차 압밀에 어떤 영향이 있는지를 밝혔다. 그리고 각 소성지수에 따른 하중과 침하특성, 압밀계수특성, 압축지수 및 2차 압축지수특성, 간극수압특성을 밝히고 압축지수, 압밀계수, 2차 압축지수 등을 소성지수, 하중에 관하여 정식화하였다. 또한 정식화한 식을 이용한 1차 및 2차 압밀침하량 예측결과와 탄소성 구성모델인 수정 Cam-Clay모델과 탄 점소성 모델인 Sekiguchi모델을 이용한 예측결과를 모형시험 결과와 같이 비교하였다. 그 결과, 2차 압밀특성을 고려한 Sekiguchi모델이 매우 정도 높게 결과를 예측할 수 있음을 알 수 있었다.

• 한국노년학
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• 제31권2호
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• pp.381-400
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• 2011

본 연구의 목적은 한국노인을 위한 성공적 노화 전략으로서의 선택, 최적화, 보상(SOC) 척도를 개발하는 것이다. 24명의 노인을 대상으로 심층면접을 통해 개발된 16문항과 SOC 원척도 48문항을 합하여 총 64개의 예비 문항이 개발되었다. 일대일 면접설문지를 통해 수집된 표본 592부를 무선 분할하여 개발 표본 300부와 타당화 표본 292부에 대한 탐색적 요인분석과 확인적 요인분석을 실시하여 최종적으로 20문항으로 구성된 한국 노인의 성공적 노화 전략으로서의 SOC 척도를 개발하였다. 이 척도는 SOC 원척도와 마찬가지로 '임의적 선택'(ES), '상실에 기초한 선택'(LBS), '최적화'(O), '보상'(C)의 4개 요인으로 구성되어있으며, 각 요인별로 5개 문항이 선택되었다. Cronbach's α 값이 .903으로 높은 내적 일치도를 보였으며, 모형 적합도지수 TLI가 .939, CFI가 .947, 그리고 RMSEA가 .058로 만족할 만한 수준의 타당도를 나타내었다. 또한 문항반응이론을 통해 20문항에 대한 난이도와 문항적합도를 검토한 결과 양호한 것으로 나타났으며, 국내에서 개발된 2개의 성공적 노화 척도 및 삶의 만족도(SLWS) 척도와 상관분석을 한 결과 유의한 정적(+) 상관관계를 보여 타당도가 확인되었다.