• Journal of the Korean Society for Library and Information Science
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• v.55 no.4
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• pp.219-243
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• 2021

This study analyzes the effects of community-level socioeconomic deprivations (SED) on public libraries' book circulation in the Seoul metropolitan area. The study design draws upon the theory of local information landscapes, which explains the relationship between community characteristics and information behavior. Using four-year (2015-2018) open government and public library circulation data, we constructed a socioeconomic deprivation index by adjusting a multi-dimensional deprivation index and generated other variables. Multi-level robust linear regression models were used to examine the relationship between SED and public library circulation. In addition, we tested the moderating effects of the library collection size and the number of libraries per unit area, respectively, on library circulation. The results show that there is a significant negative relationship between socioeconomic deprivation and library circulation rate. Also, we found that the size of the library collection negatively moderates the effects of SED in areas with a large number of books, and the number of libraries per unit area was positvely related to the library book circulation, not moderating the effects of SED. These findings suggest that public libraries and policymakers should consider community characteristics in designing strategic plans for public libraries.

• Journal of the Korean Society for information Management
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• v.38 no.4
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• pp.1-23
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• 2021

The purpose of this study is to analyze the effects of the bestseller ranks on the book circulations in public libraries. To achieve this goal, the weekly data sets of 179 books' library circulation and bestseller list from January 1, 2018 to December 29, 2019 were constructed based on the data collected from BigData MarketC and YES24. Three methods for analyzing panel data including linear regression, fixed-effect, and random effect models were compared, and it turned out that fixed-effect model was better than other methods. The results show that the average ranks of bestsellers were associated with their public library circulations visually. Also, the analysis of fixed-effect model showed that the single rank decline of a book on the bestseller list decreases its average circulation of 0.108 while the size of effect varied depending on subject of books. The study empirically demonstrated the impact of a bestseller list on people's book circulation behavior, suggesting that public libraries need to reference sociocultural context as well as bestseller book lists to predict library user needs and to formulate collection development policy.

• The Journal of the Korea Contents Association
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• v.22 no.7
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• pp.55-62
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• 2022

The perovskite solar cell is an active part of research in renewable energy fields such as solar energy, wind, hydroelectric power, marine energy, bioenergy, and hydrogen energy to replace fossil fuels such as oil, coal, and natural gas, which will gradually disappear as power demand increases due to the increase in use of the Internet of Things and Virtual environments due to the 4th industrial revolution. The perovskite solar cell is a solar cell device using an organic-inorganic hybrid material having a perovskite structure, and has advantages of replacing existing silicon solar cells with high efficiency, low cost solutions, and low temperature processes. In order to optimize the light absorption layer thin film predicted by the existing empirical method, reliability must be verified through device characteristics evaluation. However, since it costs a lot to evaluate the characteristics of the light-absorbing layer thin film device, the number of tests is limited. In order to solve this problem, the development and applicability of a clear and valid model using machine learning or artificial intelligence model as an auxiliary means for optimizing the light absorption layer thin film are considered infinite. In this study, to estimate the light absorption layer thin-film optimization of perovskite solar cells, the regression models of the support vector machine's linear kernel, R.B.F kernel, polynomial kernel, and sigmoid kernel were compared to verify the accuracy difference for each kernel function.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1141-1180
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• 2022

The application of satellite imageries has increased in the field of hydrology and water resources in recent years. However, challenges have been encountered on obtaining accurate evapotranspiration and soil moisture. Therefore, present researches have emphasized the necessity to obtain estimations of satellite-based evapotranspiration and soil moisture with related development researches. In this study, we presented the research status in Korea by investigating the current trends and methodologies for evapotranspiration and soil moisture. As a result of examining the detailed methodologies, we have ascertained that, in general, evapotranspiration is estimated using Energy balance models, such as Surface Energy Balance Algorithm for Land (SEBAL) and Mapping Evapotranspiration with Internalized Calibration (METRIC). In addition, Penman-Monteith and Priestley-Taylor equations are also used to estimate evapotranspiration. In the case of soil moisture, in general, active (AMSR-E, AMSR2, MIRAS, and SMAP) and passive (ASCAT and SAR)sensors are used for estimation. In terms of statistics, deep learning, as well as linear regression equations and artificial neural networks, are used for estimating these parameters. There were a number of research cases in which various indices were calculated using satellite-based data and applied to the characterization of drought. In some cases, hydrological cycle factors of evapotranspiration and soil moisture were calculated based on the Land Surface Model (LSM). Through this process, by comparing, reviewing, and presenting major detailed methodologies, we intend to use these references in related research, and lay the foundation for the advancement of researches on the calculation of satellite-based hydrological cycle data in the future.

• Journal of Nutrition and Health
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• v.55 no.1
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• pp.188-199
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• 2022

Purpose: This study investigated the relationship between 3 major constructs of the theory of planned behavior (TPB), i.e., attitude, subjective norms and perceived behavioral control (PBC) and past experience of healthy eating and intentions of healthy eating in the short-term and long-term in adults living in Shanghai and parts of Anhui Province, China. Methods: The online study questionnaire for this cross-sectional study was based on previously validated items. A total of 408 Chinese adults (aged 18-64 years) residing in Shanghai and parts of Anhui Province, China were included to examine relationships between 3 major constructs of TPB and past experience of healthy eating, and short-term and long-term intentions of healthy eating. Multiple linear regression model adjusted for age and body mass index (BMI) was employed to test relationships. Results: Only PBC among 3 major constructs of TPB was significantly related to short-term (p < 0.001) and long-term (p = 0.002) intention of healthy eating after adjustment for age and BMI. Past experience of healthy eating was more significantly related to long-term intention (p < 0.001) compared to short-term (p = 0.020) intention of healthy eating. The short-term and long-term intention models explained 70.5% and 48.8% of the variance, respectively. Conclusion: PBC is a potential determinant of both short-term and long-term behavioral intention of healthy eating regardless of past experience of healthy eating in adults residing in Shanghai and parts of Anhui Province, China. Our results indicate that programs promoting healthy eating to Chinese adults incorporate PCB to perform healthy eating under his or her control.

• Journal of the Korean Geotechnical Society
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• v.24 no.9
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• pp.41-48
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• 2008

The aim of this study is to present a graphical method in order to evaluate stages in shrinkage cracking. Firstly, the distribution of crack openings is established by sorting the openings of individual cracks in the soil cracking system. Secondly, it is normalized in a range of 0 to 1 to obtain the normalized crack opening distribution. Thirdly, three S-shape curve models introduced by Brooks and Corey(1964), Fredlund and Xing(1994) and van Genuchten(1980) are chosen to fit the normalized crack opening distribution using a curve fitting method. The accuracy of fitting which is described through fitting parameters by the van Genuchten equation is much higher than that by the Brooks and Corey equation and slightly higher than that by the Fredlund and Xing equation; thus the van Genuchten model is used. Finally, the stages of shrinkage cracking are graphically evaluated by drawing three separate straight lines corresponding to three linear parts of the fitted normalized crack opening distribution. The proposed method is tested with different sample thicknesses. The measured data are fitted by the selected model with the fairly high regression coefficient and small root mean square error. The results show graphically that shrinkage cracking comprises three stages; namely, primary, secondary and residual stages. Subsequently, the ranges of evaluated crack opening for each of these stages are presented.

• Geomechanics and Engineering
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• v.35 no.2
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• pp.121-133
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• 2023

The demand for cement and limestone crushed materials has increased many folds due to the tremendous increase in construction activities in Pakistan during the past few decades. The number of cement production industries has increased correspondingly, and so the rock-blasting operations at the limestone quarry sites. However, the safety procedures warranted at these sites for the blast-induced ground vibrations (BIGV) have not been adequately developed and/or implemented. Proper prediction and monitoring of BIGV are necessary to ensure the safety of structures in the vicinity of these quarry sites. In this paper, an attempt has been made to predict BIGV using artificial neural network (ANN) at three selected limestone quarries of Pakistan. The ANN has been developed in Python using Keras with sequential model and dense layers. The hyper parameters and neurons in each of the activation layers has been optimized using randomized and grid search method. The input parameters for the model include distance, a maximum charge per delay (MCPD), depth of hole, burden, spacing, and number of blast holes, whereas, peak particle velocity (PPV) is taken as the only output parameter. A total of 110 blast vibrations datasets were recorded from three different limestone quarries. The dataset has been divided into 85% for neural network training, and 15% for testing of the network. A five-layer ANN is trained with Rectified Linear Unit (ReLU) activation function, Adam optimization algorithm with a learning rate of 0.001, and batch size of 32 with the topology of 6-32-32-256-1. The blast datasets were utilized to compare the performance of ANN, multivariate regression analysis (MVRA), and empirical predictors. The performance was evaluated using the coefficient of determination (R²), mean absolute error (MAE), mean squared error (MSE), mean absolute percentage error (MAPE), and root mean squared error (RMSE)for predicted and measured PPV. To determine the relative influence of each parameter on the PPV, sensitivity analyses were performed for all input parameters. The analyses reveal that ANN performs superior than MVRA and other empirical predictors, andthat83% PPV is affected by distance and MCPD while hole depth, number of blast holes, burden and spacing contribute for the remaining 17%. This research provides valuable insights into improving safety measures and ensuring the structural integrity of buildings near limestone quarry sites.

• The Journal of the Acoustical Society of Korea
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• v.28 no.7
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• pp.661-667
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• 2009

Trabecular-bone-mimicking phantoms consisting of parallel-nylon-wire arrays were used to investigate correlations of phase velocity and attenuation coefficient with structural properties in trabecular bone. Trabecular separation (Tb.Sp) of the 7 trabecular-bone-mimicking phantoms ranged from 300 to $900\;{\mu}m$ and volume fraction (VF) from 1.6% to 8.7%. Phase velocity and attenuation coefficient of the phantoms were measured by using a through-transmission method in water, with a matched pair of broadband unfocused transducers with a diameter of 12.7 mm and a center frequency of 1 MHz. Phase velocity and attenuation coefficient at 1 MHz decreased almost linearly with increasing Tb. Sp and increased almost linearly with increasing VF. The simple and multiple linear regression models with phase velocity and attenuation coefficient as independent vanables and Tb.Sp and VF as dependent variables demonstrated that the coefficients of determination for the prediction of VF were higher than those for the prediction of Tb.Sp. The results obtained in the trabecular-bone-mimicking phantoms consisting of parallel-nylon-wire arrays were consistent with those in human trabecular bone suggesting that the structural properties can be estimated from the measurements of phase velocity and attenuation coefficient in trabecular bone.

• Clinical and Experimental Pediatrics
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• v.51 no.9
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• pp.998-1006
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• 2008

Purpose : Hypertension is defined as average systolic blood pressure and/or diastolic blood pressure that is ${\geq}95^{th}$ percentile for gender, age, and height on ${\geq}three$ occasions. Knowing that blood pressure values increase in children as they grow older, the purposes of this study were to measure blood pressure by an oscillometric device and to determine normal values and percentile curves for children. Methods : Systolic and diastolic blood pressures were measured twice with an oscillometric device in 3,545 boys and 3,145 girls under six years of age, in Seoul. Using this data, we determined average blood pressure values and percentile curves based on gender and age; we subdivided these values into blood pressures of $50^{th}$, $90^{th}$, $95^{th}$, and $99^{th}$ percentiles, by percentile of height. The regression coefficients and standard deviations of the systolic and diastolic blood pressure values were obtained from linear regression models. Results : Older boys and girls had higher systolic and diastolic blood pressure values. Older boys and girls in the same percentile of height for age had higher systolic and diastolic blood pressure values. Taller boys and girls within the same age group had higher systolic and diastolic blood pressure values. Conclusion : Blood pressure standards based on gender, age, and height were obtained via an oscillometric method. Llimitation of this study is that the study population was not from the whole country, but exclusively from Seoul. Nonetheless, the data from this study will be helpful in diagnosing and managing hypertension in Korean children.

• Journal of Korean Society of Transportation
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• v.18 no.1
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• pp.75-85
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• 2000

In existing models in optimization, the crisp data improve has been used in the objective or constraints to derive the optimal solution, Besides, the subjective environments are eliminated because the complex and uncertain circumstances were regarded as Probable ambiguity, In other words those optimal solutions in the existing models could be the complete satisfactory solutions to the objective functions in the Process of application for industrial engineering methods to minimize risks of decision-making. As a result of those, decision-makers in location Problems couldn't face appropriately with the variation of demand as well as other variables and couldn't Provide the chance of wide selection because of the insufficient information. So under the circumstance. it has been to develop the model for the location and size decision problems of logistics facility in the use of the fuzzy theory in the intention of making the most reasonable decision in the Point of subjective view under ambiguous circumstances, in the foundation of the existing decision-making problems which must satisfy the constraints to optimize the objective function in strictly given conditions in this study. Introducing the Process used in this study after the establishment of a general mixed integer Programming(MIP) model based upon the result of existing studies to decide the location and size simultaneously, a fuzzy mixed integer Programming(FMIP) model has been developed in the use of fuzzy theory. And the general linear Programming software, LINDO 6.01 has been used to simulate, to evaluate the developed model with the examples and to judge of the appropriateness and adaptability of the model(FMIP) in the real world.