• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권2호
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• pp.907-923
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• 2020

For the severe haze situation in the Beijing-Tianjin-Hebei region, conventional fine particulate matter (PM2.5) concentration prediction methods based on pollutant data face problems such as incomplete data, which may lead to poor prediction performance. Therefore, this paper proposes a method of predicting the PM2.5 concentration based on image analysis technology that combines image data, which can reflect the original weather conditions, with currently popular machine learning methods. First, based on local parameter estimation, autoregressive (AR) model analysis and local estimation of the increase in image blur, we extract features from the weather images using an approach inspired by free energy and a no-reference robust metric model. Next, we compare the coefficient energy and contrast difference of each pixel in the AR model and then use the percentages to calculate the image sharpness to derive the overall mass fraction. Furthermore, the results are compared. The relationship between residual value and PM2.5 concentration is fitted by generalized Gauss distribution (GGD) model. Finally, nonlinear mapping is performed via the wavelet neural network (WNN) method to obtain the PM2.5 concentration. Experimental results obtained on real data show that the proposed method offers an improved prediction accuracy and lower root mean square error (RMSE).

• 한국환경복원기술학회지
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• 제11권3호
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• pp.28-38
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• 2008

The purpose of this study are to compare existing presence-absence predictive models and to predict suitable habitat for Goral (Nemorhaedus caudatus raddeanus) that is an endangered and protected species in Seoraksan national park using the best model among existing predictive models. The methods of this study are as follows. First, 375 location data and 9 environmental data layers were implemented to build a model. Secondly, 4 existing presence-absence models : Generalized Linear Model (GLM), Generalized Addictive Model (GAM), Classification and Regression Tree (CART), and Artificial Neural Network (ANN) were tested to predict the Goal habitat. Thirdly, ROC (Receiver Operating Characteristic) and Kappa statistics were used to calculate a model performance. Lastly, we verified models and created habitat suitability maps. The ROC AUC (Area Under the Curve) and Kappa values were 0.697/0.266 (GLM), 0.729/0.313 (GAM), 0.776/0.453 (CART), and 0.858/0.559 (ANN). Therefore, ANN was selected as the best model among 4 models. The models showed that elevation, slope, and distance to stream were the significant factors for Goal habitat. The ratio of predicted area of ANN using a threshold was 31.29%, but the area decreased when human effect was considered. We need to investigate the difference of various models to build a suitable wildlife habitat model under a given condition.

• Korean Journal of Radiology
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• 제19권6호
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• pp.1021-1030
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• 2018

Objective: We evaluated the effect of various patient characteristics and time-density curve (TDC)-factors on the test bolus-affected vessel enhancement on coronary computed tomography angiography (CCTA). We also assessed the value of generalized linear regression models (GLMs) for predicting enhancement on CCTA. Materials and Methods: We performed univariate and multivariate regression analysis to evaluate the effect of patient characteristics and to compare contrast enhancement per gram of iodine on test bolus (${\Delta}HUTEST$) and CCTA (${\Delta}HUCCTA$). We developed GLMs to predict ${\Delta}HUCCTA$. GLMs including independent variables were validated with 6-fold cross-validation using the correlation coefficient and Bland-Altman analysis. Results: In multivariate analysis, only total body weight (TBW) and ${\Delta}HUTEST$ maintained their independent predictive value (p < 0.001). In validation analysis, the highest correlation coefficient between ${\Delta}HUCCTA$ and the prediction values was seen in the GLM (r = 0.75), followed by TDC (r = 0.69) and TBW (r = 0.62). The lowest Bland-Altman limit of agreement was observed with GLM-3 (mean difference, $-0.0{\pm}5.1$ Hounsfield units/grams of iodine [HU/gI]; 95% confidence interval [CI], -10.1, 10.1), followed by ${\Delta}HUCCTA$ ($-0.0{\pm}5.9HU/gI$; 95% CI, -11.9, 11.9) and TBW ($1.1{\pm}6.2HU/gI$; 95% CI, -11.2, 13.4). Conclusion: We demonstrated that the patient's TBW and ${\Delta}HUTEST$ significantly affected contrast enhancement on CCTA images and that the combined use of clinical information and test bolus results is useful for predicting aortic enhancement.

• Investigative Magnetic Resonance Imaging
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• 제20권2호
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• pp.88-94
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• 2016

Purpose: Fluid-attenuated inversion recovery (FLAIR) imaging can be obtained faster with shorter repletion time (TR), but it gets noisier. We hypothesized that shorter-TR FLAIR obtained at 3 tesla (3T) with a 32-channel coil may be comparable to conventional FLAIR. The aim of this study was to compare the diagnostic value between conventional FLAIR (TR = 9000 ms, FLAIR9000) and shorter-TR FLAIR (TR = 6000 ms, FLAIR6000) at 3T in terms of diffusion-weighted imaging-FLAIR mismatch. Materials and Methods: We recruited 184 patients with acute ischemic stroke (28 patients < 4.5 hours) who had undergone 5-mm diffusion-weighted imaging (DWI) and two successive 5-mm FLAIR images (no gap; in-plane resolution, $0.9{\times}0.9mm$) at 3T with a 32-channel coil. The acquisition times for FLAIR9000 and FLAIR6000 were 108 seconds (generalized autocalibrating partially parallel acquisitions [GRAPPA] = 2) and 60 seconds (GRAPPA = 3), respectively. Two radiologists independently assessed the paired imaging sets (DWI-FLAIR9000 and DWI-FLAIR6000) for the presence of matched hyperintense lesions on each FLAIR imaging. The signal intensity ratios (area of DWI lesion to contralateral normal-appearing region) on both FLAIR imaging sets were compared. Results: DWI-FLAIR9000 mismatch was present in 39 of 184 (21.2%) patients, which was perfectly the same on FLAIR6000. Three of 145 patients (2%) with DWI-matched lesions on FLAIR9000 had discrepancy on FLAIR6000, showing no significant difference (P > 0.05). Interobserver agreement was excellent for both DWI-FLAIR9000 and DWI-FLAIR6000 (k = 0.904 and 0.883, respectively). Between the two FLAIR imaging sets, there was no significant difference of signal intensity ratio (mean, standard deviation; $1.25{\pm}0.20$; $1.24{\pm}0.20$, respectively) (P > 0.05). Conclusion: For the determination of mismatch or match between DWI and FLAIR imaging, there is no significant difference between FLAIR9000 and FLAIR6000 at 3T with a 32-channel coil.

• Journal of Korean Biological Nursing Science
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• 제23권3호
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• pp.180-187
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• 2021

Purpose: This study aimed to compare breast milk minerals between mothers with gestational diabetes mellitus (GDM) and healthy mothers. Methods: This study was a short-term prospective study to determine the difference in milk minerals of 30 GDM mothers and 30 healthy mothers. Mineral concentrations in breast milk were measured for Na, K, Ca, Mg, and P. The first breast milk was collected on the 5th day after childbirth, while the second one was collected on the 14th day. For the variation of mineral content of breast milk over time between groups, generalized estimation equations were used. Results: The mean age of the GDM group and healthy mother group was 32.56 and 31.17 years old, respectively. Na was significantly higher in GDM mother group (Wild 𝛘²=4.35, p=.037) over time (Wild 𝛘²=21.59, p<.001), and Ca was significantly higher in healthy mother group (Wild 𝛘²=1.77, p=.018) over time (Wild 𝛘²=19.09, p<.001). Mg, P, and K showed a significant difference in time (Wild 𝛘²=18.12, p<.001; Wild 𝛘²=7.73, p=.005; Wild 𝛘²=7.10, p=.008). P was significantly higher in GDM mother group on 5th day of delivery (t=2.08, p=.042). Conclusion: There was a difference in the mineral composition of breast milk between GDM mothers and healthy mothers. Therefore, it is necessary to develop and apply intervention programs such as effective prenatal blood sugar management and postpartum breast massage considering the characteristics of GDM mothers.

• The Journal of Korean Physical Therapy
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• 제24권2호
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• pp.98-106
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• 2012

Purpose: The goal of this study was to analyze the degree of stress and methods of coping with stress in mothers of cerebral palsied children and to provide a basic resource for the development of policies to improve the mental health of mothers with cerebral palsied children. Methods: 85 mothers with cerebral palsied children and 77 mothers of normal children completed a self-administered questionnaire that evaluated the degree of stress and methods of coping with stress. Cronbach's ${\alpha}$ score was used to determine the internal consistency of the acquired data and the discriminated validity was estimated by Pearson's correlation coefficient. Independent t-tests were conducted to compare the degree of stress and method of coping with stress between mothers of cerebral palsied children and mothers of normal children and one-way ANOVA was performed to analyze the effect of generalized characteristics on stress in mothers of cerebral palsied children. Results: The degree of stress in terms of anxiety response and roles as mother for mothers with cerebral palsied children was higher than mothers with normal children. However, there was no significant difference between two group in regards to the methods of coping with stress during a stressful episode. The degree of stress for mothers with cerebral palsied children was greater when the child was younger. Conclusion: Mothers of cerebral palsied children had higher stress than that of mothers with normal children and felt more stress when their child was younger. Therefore, these results suggest that health-based policies should be developed to improve the mental health of mothers with cerebral palsied children.

• The Journal of Asian Finance, Economics and Business
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• 제7권6호
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• pp.173-183
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• 2020

The paper investigates the determinants of foreign direct investment (FDI) in Vietnam in 2000-2019 period. This study uses difference Generalized Methods of Moments (GMM) and Pooled Mean Group (PMG) to analyse panel data officially provided by General Statistical Office of Vietnam. The results show that market size impacts positively significant on FDI attraction: 1% -1.45% (PMG) and 1% -1.25% (GMM). Besides, some other factors have positive influences as labor force, macroeconomic policy, macroeconomic stability and skilled labor. Meantime, the trade openness negatively affects FDI inflows in the short-term, while not being statistically significant in the long-term. Moreover, economic shocks often have a negative impact on FDI inflows. The findings of this study lead to the following recommendations. First, authorities should pay special attention to encourage economic growth rate in Vietnam to expand market size because this is the first priority of foreign investors. Second, authorities need to continue increasing the rate of skilled labor, especially highly qualified management force, engineers and well-skilled workers. Third, the authorities should adjust trade openness to boost the role of its determinant in attracting FDI inflows. Fourth, macroeconomic stability needs to be governed by international standards in order to secure the belief of foreign investors in the long-term.

• 한국지반공학회논문집
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• 제21권3호
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• pp.141-148
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• 2005

연약지반의 불균질성, 시료의 교란, 토질상수의 입력오차, 압밀이촌의 단점 등으로 예측된 압밀침하량 및 시간은 대부분 실측치와 잘 일치하지 않고 있다. 따라서 압밀기간동안 계측자료를 활용한 침하량 예측기법은 실무에서 매우 유용한 수단이라 할 수 있다. 본 논문에서는 예측기법으로 많이 활용되는 방곡선법, 아사오카범, 호시노법을 비롯한 최근에 제안된 4법의 이론적 공통점을 바탕으로 아사오카법을 제외한 나머지 분석기법들에 대하여 일반화된 쌍곡선 형태의 수식화 작업으로 새로운 분석 기법을 제안하였으며, 사례를 통하여 유용한 계측분석기법으로 적용성을 확인하였다.

• 비파괴검사학회지
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• 제19권5호
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• pp.340-346
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• 1999

액체/고체 경계면에 표면파가 발생할 때 나타나는 최소반사 및 후방복사 현상을 이용하여 brass와 aluminum 시편 그리고 copper/stainless steel, nickel/brass, nickel/aluminum 도금시편에 대한 표면 탄성파 속도의 주파수 의존성이 측정되었다. 측정된 속도의 분산관계는 일반화 램 표면파의 분산 특성과 잘 일치하였다. 시편들의 분산 특징에 따라 최소반사와 후방복사에 의해 결정된 속도 차이의 경향이 다르게 나타났다. 이러한 대응 관계는 두 현상의 생성 메커니즘과 군속도의 도입으로 설명되었다.

• The Journal of Asian Finance, Economics and Business
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• 제7권7호
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• pp.251-260
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• 2020

The purpose of this paper is to investigate the impact of total factor productivity (TFP), institutional quality, and interactive variable between them on economic growth in 13 low-middle income countries in Asia for the period 2000-2018. The paper uses the difference Generalized Method of Moments (GMM) to explore the dataset provided by the World Bank. The empirical results show that TFP and the interactive variable positively impact on the economic growth, while the institutional determinants have a negative influence. The negative effect is explained by the weak institutions in these low-middle income countries. The findings of the study suggest two points. First, the government should continue to improve TFP, which is associated with the application of technical advances, technological innovations, improvement of management methods, and skilled workers. Second, far more important, is that the authorities should pay special attention to implement institutional reform and strengthen the governance in the future. The successful experiences from Japan, Korea and Singapore will help other governments in Asian low-middle income countries to build developmental state. Probably, the developmental state actively interfere in the market to promote and realize the development goals. By doing so, these economies might overcome the so-called "middle-income trap".