• Journal of the Society of Naval Architects of Korea
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• v.55 no.6
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• pp.482-489
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• 2018

Most of the numerical and experimental studies on supercavitating flows are focused on the cavitator only. However, the partial cavity growing into the supercavity is affected by the shape of the body placed behind the cavitator. In this paper, we develope a numerical method which is based on the boundary element method to predict supercavitating flow around three-dimensional axisymmetric bodies. We estimate the influence of the body shape on the supercavity growth. Here, we consider various parameters of the body such as cavitator shape, shoulder length and body diameter, and compare the results with the case of the cavitator only. In summary, it is found that the body may impede the cavity growth, the shoulder mainly affects the cavity length, and the supercavity occurring in the cone type cavitator is strongly influenced rather than that of the disk type cavitator.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.1111-1124
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• 2021

This research aims to investigate The Role of Calling and Membership as Mediation on the Influence of Spiritual Leadership against Organizational Commitment and its Effect on the Performance of Lembaga Perkreditan Desa (LPD). This study has outlined organizational commitment as a construct thought to be theoretically strategic to empower organizations through calling and membership. The research was conducted upon LPDs in Bali. Inferential analysis techniques have been used to test the empirical model and the hypotheses proposed in this study. The analysis technique used is the structural equation model (SEM) based on variance or component, called Partial Least Square (PLS). The significant findings of this research are, first, spiritual leadership has a positive and significant effect on calling; second, calling has a positive and significant impact on organizational commitment; and third, calling has a positive and significant effect on organizational performance. Several studies have been conducted to estimate the mediating role of calling in explaining the relationship of spiritual leadership with organizational commitment. The results of the study by Bodla and Ali (2012) and Bodla et al. (2013) state that spiritual leadership, which consists of vision and altruistic love, has a positive and significant influence on organizational commitment. Likewise, spiritual leadership has a positive and significant effect on calling.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.171-176
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• 2022

A dramatic rise in the number of people dying from heart disease has prompted efforts to find a way to identify it sooner using efficient approaches. A variety of variables contribute to the condition and even hereditary factors. The current estimate approaches use an automated diagnostic system that fails to attain a high level of accuracy because it includes irrelevant dataset information. This paper presents an effective neural network with convolutional layers for classifying clinical data that is highly class-imbalanced. Traditional approaches rely on massive amounts of data rather than precise predictions. Data must be picked carefully in order to achieve an earlier prediction process. It's a setback for analysis if the data obtained is just partially complete. However, feature extraction is a major challenge in classification and prediction since increased data increases the training time of traditional machine learning classifiers. The work integrates the CNN-MDRP classifier (convolutional neural network (CNN)-based efficient multimodal disease risk prediction with TANFIS (tuned adaptive neuro-fuzzy inference system) for earlier accurate prediction. Perform data cleaning by transforming partial data to informative data from the dataset in this project. The recommended TANFIS tuning parameters are then improved using a Laplace Gaussian mutation-based grasshopper and moth flame optimization approach (LGM²G). The proposed approach yields a prediction accuracy of 98.40 percent when compared to current algorithms.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.20 no.4
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• pp.455-468
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• 2022

Colloid Formation and Migration (CFM) project is being carried out within the Grimsel Test Site (GTS) Phase Ⅵ. Since 2008, the Korea Atomic Energy Research Institute (KAERI) has joined CFM to investigate the behavior of colloid-facilitated radionuclide transport in a generic Underground Research Laboratory (URL). The CFM project includes a long-term in-situ test (LIT) and an in-rock bentonite erosion test (i-BET) to assess the in-situ colloid-facilitated radionuclide transport through the bentonite erosion in the natural flow field. In the LIT experiment, radionuclide-containing compacted bentonite was equipped with a triple-packer system and then positioned at the borehole in the shear zone. It was observed that colloid transport was limited owing to the low swelling pressure and low hydraulic conductivity. Therefore, a postmortem analysis is being conducted to estimate the partial migration and diffusion of radionuclides. The i-BET experiment, that focuses more on bentonite erosion, was newly designed to assess colloid formation in another flow field. The i-BET experiment started with the placement of compacted bentonite rings in the double-packer system, and the hydraulic parameters and bentonite erosion have been monitored since December 2018.

• Korea Trade Review
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• v.45 no.6
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• pp.77-97
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• 2020

This study investigates the effects of O2O-based mobile shopping application (O2O MSA)'s information and service quality on the user's perceived privacy protection, satisfaction and loyalty. In this study, 969 questionnaire reponses were collected, out of which 555 were used to estimate the structural paths using PLS-SEM (partial least square structural equation model) for the hypothesis test. Our empirical findings are drawn from Chinese respondents that live in a 1-line city in China and use O2O MSAs serviced by China's leading companies. This study examines and confirms that qualified information and service of O2O MSA positively affect both perceived privacy protection and customer satisfaction, which finally leads to customer behavioral loyalty through the perceived privacy protection. Further, this study presents effective practical implications for application development strategy suitable for users in the O2O-based mobile shopping industry.

• Journal of the Korean Institute of Landscape Architecture
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• v.38 no.2
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• pp.25-36
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• 2010

The generally known important functions of forests include air purification and the health benefits that humans can receive when relaxing and enjoying recreation in the forests. In recent years, people have appreciated the value of the natural environment but it is not easy to answer the question how much monetary value a natural environment has. Because environmental property is public property, which is not traded on the market, market prices cannot be established, so it is not easy to assess the currency value. Methods for estimating environmental property value have been studied by economists. The representative method for measuring environmental property value is a contingent valuation method, or CVM. Various methods have been researched and attempted along with the development and fusion of mathematics, statistics, and economics. Representative methods of CVM are single-bound and double-bound logit and probit methods. This study has been carried out to compare four estimates. Estimates are as follows: the lowest estimate is derived from a single-bound logit WTPmedian while the highest estimate is from double-bound probit WTPmean. While there are some preceding studies on price estimation and methods of measurement through CVM, they offer only partial comparisons. This study suggests four analytic methods and prices through 1,123 questionnaires. The results can be used for the subsequent comparison of estimate prices and the methods of measurement

• Korean Chemical Engineering Research
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• v.54 no.5
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• pp.621-629
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• 2016

Recently, the researches on quantitative structure activity relationship (QSAR) for describing toxicities or activities of chemicals based on chemical structural characteristics have been widely carried out in order to estimate the toxicity of chemicals in multiuse facilities. Because the toxicity of chemicals are explained by various kinds of molecular descriptors, an important step for QSAR model development is how to select significant molecular descriptors. This research proposes a statistical selection of significant molecular descriptors and a new QSAR model based on partial least square (PLS). The proposed QSAR model is applied to estimate the logarithm of partition coefficients (log P) of 130 polychlorinated biphenyls (PCBs) and lethal concentration ($LC_{50}$) of 14 PCBs, where the prediction accuracies of the proposed QSAR model are compared to a conventional QSAR model provided by OECD QSAR toolbox. For the selection of significant molecular descriptors that have high correlation with molecular descriptors and activity information of the chemicals of interest, correlation coefficient (r) and variable importance of projection (VIP) are applied and then PLS model of the selected molecular descriptors and activity information is used to predict toxicities and activity information of chemicals. In the prediction results of coefficient of regression ($R^2$) and prediction residual error sum of square (PRESS), the proposed QSAR model showed improved prediction performances of log P and $LC_{50}$ by 26% and 91% than the conventional QSAR model, respectively. The proposed QSAR method based on computational toxicology can improve the prediction performance of the toxicities and the activity information of chemicals, which can contribute to the health and environmental risk assessment of toxic chemicals.

• The Korean Journal of Nuclear Medicine Technology
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• v.14 no.1
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• pp.13-17
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• 2010

Purpose: Partial volume effect (PVE) is the phenomenon to lower the accuracy of image due to low estimate, which is to occur from PET/CT 3D image acquisition. The more resolution is declined and the lesion is small, the more it causes a big error. So that it can influence the test result. Studied the optimum image reconstruction method by using variation of parameter, which can influence the PVE. Materials and Methods: It acquires the image in each size spheres which is injected $^{18}F$-FDG to hot site and background in the ratio 4:1 for 10 minutes by using NEMA 2001 IEC phantom in GE Discovey STE 16. The iterative reconstruction is used and gives variety to iteration 2-50 times, subset number 1-56. The analysis's fixed region of interest in detail part of image and compute % difference and signal to noise ratio (SNR) using $SUV_{max}$. Results: It's measured that $SUV_{max}$ of 10 mm spheres, which is changed subset number to 2, 5, 8, 20, 56 in fixed iteration to times, SNR is indicated 0.19, 0.30, 0.40, 0.48, 0.45. As well as each sphere's of total SNR is measured 2.73, 3.38, 3.64, 3.63, 3.38. Conclusion: In iteration 6th to 20th, it indicates similar value in % difference and SNR ($3.47{\pm}0.09$). Over 20th, it increases the phenomenon, which is placed low value on $SUV_{max}$ through the influence of noise. In addition, the identical iteration, it indicates that SNR is high value in 8th to 20th in variation of subset number. Therefore, to reduce partial volume effect of small lesion, it can be declined the partial volume effect in iteration 6 times, subset number 8~20 times, considering reconstruction time.

• Journal of the Korean Geotechnical Society
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• v.35 no.11
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• pp.51-62
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• 2019

In this study, a simple method to estimate the soil water content variation in a wide area was proposed using hyperspectral near-infrared images. The reflectance data of a sand, granite soils, and a kaolinite were measured by reflecting the soil samples with different wavelengths in the visible and near-infrared (VNIR) regions using hyperspectral cameras. The measured reflectances and parameters were used to build a water content prediction model using the Partial Least Square Regression (PLSR) analysis. In the water content prediction model, the Area of Reflectance (Near-infrared, NIR) parameter was the most suitable parameter to determine the water content. The parameter was applicable regardless of the soil type, as the coefficient of determination (R²) exceeded 0.9 for each soil sample. Additionally, the mean absolute percentage error (MAPE) was less than 15% when compared with the actual water content of the soil. Therefore, the predictability of water content variation for soils with water content lower than 50% was confirmed. Accordingly through this study, the predictability of water content variation in several soil types using the hyperspectral near-infrared images was confirmed. For further development, a model that incorporates soil classification would be required to improve the accuracy of the model and to predict higher range of water contents.

• Journal of the Society of Disaster Information
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• v.16 no.3
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• pp.542-549
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• 2020

Purpose: As nitrate nitrogen produced during fermentation of liquid fertilizer is a pollution indicator of water, in this study, four research areas where liquid fertilizer was sprayed were selected, and a model was designed to estimate the concentration of nitrate nitrogen pollution. Method: Prior to shooting on site, a spectrum library was constructed by dividing the ratio of liquid fertilizer into 5 groups: 0%, 25%, 50%, 75%, and 100%. PLSR (Partial least squares regression) method was applied to hyperspectral images acquired in the study area based on the aspect of spectrum. Result: The behavior of nitrate nitrogen was confirmed by 1st and 2nd differentiation of the spectrum of the constructed liquid fertilizer. PLSR concentration estimation modeling was implemented using images from field experiments and compared with actual concentration of nitrate nitrogen. Conclusion: When comparing the PLSR concentration estimation model with the actual concentration of nitrate nitrogen, it was measured that the detection is possible in high concentration areas where the concentration of nitrate nitrogen is 70mg/kg or more.