• Journal of the Microelectronics and Packaging Society
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• v.28 no.1
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• pp.39-46
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• 2021

The quantitative measurement of interfacial adhesion energy (Gc) of multilayer thin films for Cu interconnects was investigated using a double cantilever beam (DCB) and 4-point bending (4-PB) test. In the case of a sample with Ta diffusion barrier applied, all Gc values measured by the DCB and 4-PB tests were higher than 5 J/㎡, which is the minimum criterion for Cu/low-k integration without delamination. However, in the case of the Ta/Cu sample, measured Gc value of the DCB test was lower than 5 J/㎡. All Gc values measured by the 4-PB test were higher than those of the DCB test. Measured Gc values increase with increasing phase angle, that is, 4-PB test higher than DCB test due to increasing plastic energy dissipation and roughness-related shielding effects, which matches well interfacial fracture mechanics theory. As a result of the 4-PB test, Ta/Cu and Cu/Ta interfaces measured Gc values were higher than 5 J/㎡, suggesting that Ta is considered to be applicable as a diffusion barrier and a capping layer for Cu interconnects. The 4-PB test method is recommended for quantitative adhesion energy measurement of the Cu interconnect interface because the thermal stress due to the difference in coefficient of thermal expansion and the delamination due to chemical mechanical polishing have a large effect of the mixing mode including shear stress.

• Korean Journal of Remote Sensing
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• v.38 no.3
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• pp.265-282
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• 2022

Sea surface temperature (SST) is a factor that greatly influences ocean circulation and ecosystems in the Earth system. As global warming causes changes in the SST near the Korean Peninsula, abnormal water temperature phenomena (high water temperature, low water temperature) occurs, causing continuous damage to the marine ecosystem and the fishery industry. Therefore, this study proposes a methodology to predict the SST near the Korean Peninsula and prevent damage by predicting abnormal water temperature phenomena. The study area was set near the Korean Peninsula, and ERA5 data from the European Center for Medium-Range Weather Forecasts (ECMWF) was used to utilize SST data at the same time period. As a research method, Long Short-Term Memory (LSTM) algorithm specialized for time series data prediction among deep learning models was used in consideration of the time series characteristics of SST data. The prediction model predicts the SST near the Korean Peninsula after 1- to 7-days and predicts the high water temperature or low water temperature phenomenon. To evaluate the accuracy of SST prediction, Coefficient of determination (R²), Root Mean Squared Error (RMSE), and Mean Absolute Percentage Error (MAPE) indicators were used. The summer (JAS) 1-day prediction result of the prediction model, R²=0.996, RMSE=0.119℃, MAPE=0.352% and the winter (JFM) 1-day prediction result is R²=0.999, RMSE=0.063℃, MAPE=0.646%. Using the predicted SST, the accuracy of abnormal sea surface temperature prediction was evaluated with an F1 Score (F1 Score=0.98 for high water temperature prediction in summer (2021/08/05), F1 Score=1.0 for low water temperature prediction in winter (2021/02/19)). As the prediction period increased, the prediction model showed a tendency to underestimate the SST, which also reduced the accuracy of the abnormal water temperature prediction. Therefore, it is judged that it is necessary to analyze the cause of underestimation of the predictive model in the future and study to improve the prediction accuracy.

• Journal of Bio-Environment Control
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• v.31 no.4
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• pp.409-415
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• 2022

Plant growth and development are also affected by root-zone environment. Therefore, it is important to consider the variables of the root-zone environment when establishing an irrigation strategy. The purpose of this study is to analyze the relationship between the volumetric moisture content (VWC), Bulk EC (ECb), and Pore EC (ECp) used by plant roots using FDR sensors in two types of rockwool media with different water transmission characteristics, using the method above this was used to establish a method for collecting and correcting available root-zone environmental data. For the experiment, two types of rockwool medium (RW1, RW2) with different physical characteristics were used. The moisture content (MC) and ECb were measured using an FDR sensor, ECp was measured after extracting the residual nutrient solution from the medium using a disposable syringe in the center of the medium at a volumetric moisture content (VWC) of 10-100%. Then, ECb and ECp are measured by supplying nutrient solution having different concentration (distilled water, 0.5-5.0) to two types of media (RW1, RW2) in each volume water content range (0 to 100%). The relationship between ECb and ECp in RW1 and RW2 media is best suited for cubic polynomial. The relationship between ECb and ECp according to volume moisture content (VWC) range showed a large error rate in the low volume moisture content (VWC) range of 10-60%. The correlation between the sensor measured value (ECb) and the ECp used by plant roots according to the volumetric water content (VWC) range was the most suitable for the Paraboloid equation in both media (RW1, RW2). The coefficient of determination the calibration equation for RW1 and RW2 media were 0.936, 0.947, respectively.

• Journal of Korea Port Economic Association
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• v.37 no.4
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• pp.127-144
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• 2021

The purpose of this study is to derive service factors based on the "Rail Statistical Yearbook" data of railroad service providers from 1990 to 2019, and to analyze the effect of the service factors on the operating profit ratio(OPR), a representative management performance variable of railroad transport service providers. In particular, it has academic significance in terms of empirical research to evaluate whether the management innovation of the KoRail has changed in line with the purpose of establishing the corporation by dividing the research period into the first period (1990-2003) and the latter (2004-2019). The contents of this study investigated previous studies on the quality of railway passenger transportation service and analyzed the contents of government presentation data related to the management performance evaluation of the KoRail. As an empirical analysis model, a research model was constructed using OPR as a dependent variable and service factor variables of infrastructure, economy, safety, connectivity, and business diversity as explanatory variables based on the operation and management activity information during the analysis period 30 years. On the results of research analysis, OPR is that the infrastructure factor is improved by structural reform or efficiency improvement. And economic factors are the fact that operating profit ratio improves by reducing costs. The safety factor did not reveal the significant explanatory power of the regression coefficient, but the sign of influence was the same as the prediction. Connectivity factor reveals a influence on differences between first period and latter, but OPR impact direction is changed from negative in before to positive in late. This is an evironment in which connectivity is actually realized in later period. On diversity factor, there is no effect of investment share in subsidiaries and government subsidies on OPR.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.609-625
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• 2022

Validation of satellite data products is critical for subsequent analysis that is based on the data. Particularly, performance of ocean color products in turbid and shallow near-land ocean areas has been questioned for long time for its difficulty that stems from the complex optical environment with varying distribution of water constituents. Furthermore, validation with ship-based or station-based measurements has also exhibited clear limitation in its spatial scale that is not compatible with that of satellite data. This study firstly performed validation of major GOCI-II products such as remote sensing reflectance, chlorophyll-a concentration, suspended particulate matter, and colored dissolved organic matter, using the in-situ measurements collected from ship-based field campaign. Secondly, this study also presents preliminary analysis on the use of drone images for product validation. Multispectral images were acquired from a MicaSense RedEdge camera onboard a UAV to compensate for the significant scale difference between the ship-based measurements and the satellite data. Variation of water radiance in terms of camera altitude was analyzed for future application of drone images for validation. Validation conducted with a limited number of samples showed that GOCI-II remote sensing reflectance at 555 nm is overestimated more than 30%, and chlorophyll-a and colored dissolved organic matter products exhibited little correlation with in-situ measurements. Suspended particulate matter showed moderate correlation with in-situ measurements (R²~0.6), with approximately 20% uncertainty.

• Journal of the Microelectronics and Packaging Society
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• v.28 no.4
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• pp.11-18
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• 2021

A novel microwave dielectric composite material for ultra-low temperature co-fired ceramics (ULTCC) with (1-x)BaWO₄-xBaV₂O₆ (x=0.54~0.85) composition was prepared by firing a mixture of BaWO₄ and BaV₂O₆. Shrinkage tests showed that the ceramic composite begins to densify at a temperature as low as 550℃ and can be sintered at 650℃ with 98% of relative density under the influence of BaV₂O₆. X-ray diffraction analysis showed that BaWO₄ and BaV₂O₆ coexisted and no secondary phase was detected in the sintered bodies, implying good chemical compatibility between the two phases. Near-zero temperature coefficients of the resonant frequency (𝛕_f) could be achieved by controlling the relative content of the two phases, due to their positive and negative 𝛕_f values, respectively. With increasing BaV₂O₆ (x from 0.53 to 0.85), the 𝛕_f value of the composites increased from -7.54 to 14.49 ppm/℃, ε_r increased from 10.08 to 11.17 and the quality factor (Q×f value) decreased from 47,661 to 37,131 GHz. The best microwave dielectric properties were obtained for x=0.6 samples with ε_r=10.4, Q×f=44,090 GHz, and 𝛕_f=-2.38 ppm/℃. Chemical compatibility experiments showed the developed composites are compatible with aluminum electrode during co-firing process.

• Economic and Environmental Geology
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• v.56 no.4
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• pp.435-445
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• 2023

A delta is a depositional landform that is formed when sediment transported by a river is deposited in a relatively low-energy environment, such as a lake, sea, or a main channel. Among these, a delta formed at the confluence of rivers has a great importance in river management and research because it has a significant impact on the hydraulic and sedimentological characteristics of the river. Recently, the equilibrium state of the confluence area has been disrupted by large-scale dredging and construction of levees in the Nakdong River. However, due to the natural recovery of the river, the confluence area is returning to its pre-dredging natural state through ongoing sedimentation. The time-series data show that the confluence delta has been steadily growing since the dredging, but once it reaches a certain size, it repeats growth and retreat, and the overall size does not change significantly. In this study, we developed a model to explain the sedimentation-erosion processes in the confluence area based on the assumption that the confluence delta reaches a dynamic equilibrium. The model is based on two fundamental principles: sedimentation due to supply from the tributary and erosion due to the main channel. The erosion coefficient that represents the Nakdong River confluence areas, was obtained using data from the tributaries of the Nakdong River. Sensitivity analyses were conducted using the developed model to understand how the confluence delta responds to changes in the sediment and water discharges of the tributary and the main channel, respectively. We then used annual average discharge of the Nakdong River's tributaries to predict the dynamic equilibrium positions of the confluence deltas. Finally, we conducted a simulation experiment on the development of the Gamcheon-Nakdong River delta using recorded daily discharge. The results showed that even though it is a simple model, it accurately predicted the dynamic equilibrium positions of the confluence deltas in the Nakdong River, including the areas where the delta had not formed, and those where the delta had already formed and predicted the trend of the response of the Gamcheon-Nakdong River delta. However, the actual retreat in the Gamcheon-Nakdong River delta was not captured fully due to errors and limitations in the simplification process. The insights through this study provide basic information on the sediment supply of the Nakdong River through the confluence areas, which can be implemented as a basic model for river maintenance and management.

• Journal of Food Hygiene and Safety
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• v.38 no.2
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• pp.46-54
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• 2023

In this study, we examined the residual amounts of formaldehyde in hygiene products to determine the safety of these products in Gyeonggi-do. Formaldehyde is among the harmful substances that may remain within certain hygiene products. On the basis of an analysis of formaldehyde in a total of 222 items (6 disposable paper straws, 9 disposable paper napkins, 21 toilet papers, 13 disposable dishcloths, 16 disposable paper towels, 32 wet wipes for food service restaurants, 25 disposable cotton swabs, and 100 disposable diapers), we detected traces in three wet wipes for food service restaurants (1.87 to 4.45 mg/kg), which is approximately 9% to 22% of the standard level (20 mg/kg). We established that all the hygiene products assessed in the study met the individual standards for formaldehyde, thereby confirming that safe products are being distributed. In the standards and specifications for hygiene products, the formaldehyde test method is regulated for application with respect to three categories based on the type of product. The samples used in this study were of types for which method 1 or method 2 is applied, and the limits of detection, limits of quantification, linearity, and recovery rates were reviewed to verify the validity of each test method. When method 2 was applied, we experienced interference when performing analysis at a wavelength of 412 nm, which was associated with the influence of impurities in some samples of disposable cotton swabs and disposable diapers. Consequently, in these cases, the results were compared after analysis using method 1. By comparing the results obtained using method 2 with those obtained using method 1, the latter of which were unaffected by the interference of impurities, we were able to detect formaldehyde at low concentrations. These findings accordingly highlight the necessity to standardize the formaldehyde test method for future analyses.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.2
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• pp.80-98
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• 2023

This study explores the effectiveness of various data preprocessing algorithms for improving subseasonal to seasonal (S2S) climate predictions from six climate forecast models and their Multi-Model Ensemble (MME) using a deep learning-based postprocessing model. A pipeline of data transformation algorithms was constructed to convert raw S2S prediction data into the training data processed with several statistical distribution. A dimensionality reduction algorithm for selecting features through rankings of correlation coefficients between the observed and the input data. The training model in the study was designed with TimeDistributed wrapper applied to all convolutional layers of U-Net: The TimeDistributed wrapper allows a U-Net convolutional layer to be directly applied to 5-dimensional time series data while maintaining the time axis of data, but every input should be at least 3D in U-Net. We found that Robust and Standard transformation algorithms are most suitable for improving S2S predictions. The dimensionality reduction based on feature selections did not significantly improve predictions of daily precipitation for six climate models and even worsened predictions of daily maximum and minimum temperatures. While deep learning-based postprocessing was also improved MME S2S precipitation predictions, it did not have a significant effect on temperature predictions, particularly for the lead time of weeks 1 and 2. Further research is needed to develop an optimal deep learning model for improving S2S temperature predictions by testing various models and parameters.

• Journal of Korea Entertainment Industry Association
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• v.13 no.3
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• pp.213-220
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• 2019

Desire for a happy life becomes the will that man instinctively desires. In that the conditions of happiness are subjective and varied, the will of subjective desires has been studied with the attention of objective tendencies. The positive and meaningful will of life in the desire for happiness leads us to be the functionaries who act. These wills can be the driving force of a happy life, which allows one to have a hopeful reflective will in one's inner life, connecting oneself with others, and working in relationships with others. In addition, those who become lazy or lose their orientation in life can instill a will to be the main character of life, and furthermore, to give the ultimate meaning and goals of life. To understand and analyze these wills for happy lives more specifically, structural model compatibility and confirmatory factors were conducted. relatively reliable α=.855 value, the coefficient of correlation between recognition and will **p<.01, *p<.05 statistically significant measuring tool of not less than 05 was used. The study results of the structural model suitability of the factors of will and the confirmatory factor analysis showed that the model set by the researcher could reflect the characteristics of the data collected, and that the χ²(Chi-square) value was .126, which was consistent with the model by satisfying the acceptance criteria, and that the comparison of the reference values of the study model showed a relatively high level of suitability. To identify the relationship between cognitive and defined and behavioral factors of subjective will and existent will variables, the results of a verification factor analysis show that the χ²(Chi-square) value is 2.36 and the model and data are consistent with the acceptance criteria, and that the test data is consistent with the model and data set by the researcher are consistent with the model5.0 Through structural model analysis of human will, it was confirmed that the variables of subjective and existential, sensible and reflective will directly and indirectly influence and form a complex relationship. Our will is recognized as the subjective will, and the structure of the subjective will consists of the sensible and reflective will, and the relationship between the cognitive and just action elements and the subjective will of the human life and the will to exist is shown to be very meaningful, so we should conduct the education of the happy will of the emotional and just areas of life as well as the reestablishment of the cognitive educational direction that can lead to action.