• Korean Journal of Mineralogy and Petrology
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• v.35 no.3
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• pp.345-353
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• 2022

This study aimed to fundamentally understand changes of cell parameters of cation-exchanged mordenites using high resolution X-ray powder diffraction for studies that immobilization of various heavy metal cation using synthesis mordenite (Na_6.6Al_6.6Si_41.4O₉₆·20.4H₂O, Na-MOR). As a results of measurement by Thermogravimetric analysis (TGA), it was confirmed that 19.4, 20.4 water molecules per unit cell were present in monovalent-cation substituted MOR (Cs-MOR, Na-MOR), and 21, 23.1, 23.2 water molecules per unit cell were present in divalent-cation substituted MOR (Pb-MOR, Sr-MOR, Cd-MOR). The space group of all the samples were identified as Cmcm belonging to the orthorhombic crystal system. Compared to Na-MOR, starting material, relative peak intensity of (110) and (200) is significantly changed after cation substitution whereas peak position is almost similar. Also, (220) peak that was not found in Na-MOR was clearly observed in Pb-, Cd- and Sr-exchanged MOR. Thus, it was estimated that changes of atomic distribution usually occurred on ab-plane while changes of cell parameters were little. Detailed changes in the cell parameters of cation-exchanged mordenites were derived from whole profile fitting method using the GSAS suite program. Changes in the axial lengths and unit cell volume of cation substitution showed different relationship depending on ionic radius and charge number. In case of monovalent-cation substituted MOR, the length of a-axis increases whereas the length of b- and c-axis decrease by absorbed cation radius. In the case of divalent-cation exchanged MOR, the length of a-axis usually decreases while the length of b- and c-axis increases by cation radius. It was confirmed that unit cell volume of monovalent and divalent cation substituted MORs had an independent tendency by cation radius.

• Korean Journal of Social Welfare Studies
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• v.41 no.4
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• pp.225-246
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• 2010

The family environment children are exposed to growing up greatly influences their future potential and achievements. Previous findings show that changes in family structure during childhood, particularly those resulting from divorce or death, cause lasting negative consequence that affect the child physically, psychologically, economically, and socially. Unfortunately, single-parent households are becoming increasingly common in Korea, nearly doubling to more than a million cases in the last two decades. Existing domestic and international studies of this area tend to focus on the short-term effects of growing up in a single-parent household. In addition, these studies group their samples in ways that result in findings that may be too broad or are not necessarily an accurate representation of the subjects. This study attempts to address some of these shortcomings by focusing on the long-term effects of how changes in family structure early in children's lives affect achievement during their transition to adulthood. In addition, it takes into account the development cycle the child is in at the time of family restructuring, and what kind of long-term effects result from that. In this analysis, we find that there are several cases of statistically significantly differences in domain achievement depending on the developmental stage the child was in when the parental divorce or death occurred. The findings indicate that changes in family structure during the infant/toddler period influence health condition and depression, while changes in family structure during middle-childhood and adolescence do not. Meanwhile, changes in family structure during any point in the developmental stages have negative effects on educational attainment, with the severity of these negative effects depending on when the family changes occur. The negative effect on educational attainment is most prominent when a change in family structure occurs during the infant/toddler period, followed by adolescence, then middle-childhood.

• Journal of the Korean Institute of Landscape Architecture
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• v.51 no.2
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• pp.1-11
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• 2023

This study intended to develop a technique for quantitatively and 3-dimensionally predicting the potential failure zone and impulse that may occur when trees are fall down. The main outcomes of this study are as follows. First, this study established the potential failure zone and impulse calculation formula in order to quantitatively calculate the risks generated when trees are fallen down. When estimating the potential failure zone, the calculation was performed by magnifying the height of trees by 1.5 times, reflecting the likelihood of trees falling down and slipping. With regard to the slope of a tree, the range of 360° centered on the root collar was set in the case of trees that grow upright and the range of 180° from the inclined direction was set in the case of trees that grow inclined. The angular momentum was calculated by reflecting the rotational motion from the root collar when the trees fell down, and the impulse was calculated by converting it into the linear momentum. Second, the program to calculate a potential failure zone and impulse was developed using Rhino3D and Grasshopper. This study created the 3-dimensional models of the shapes for topography, buildings, and trees using the Rhino3D, thereby connecting them to Grasshopper to construct the spatial information. The algorithm was programmed using the calculation formula in the stage of risk calculation. This calculation considered the information on the trees' growth such as the height, inclination, and weight of trees and the surrounding environment including adjacent trees, damage targets, and analysis ranges. In the stage of risk inquiry, the calculation results were visualized into a three-dimensional model by summarizing them. For instance, the risk degrees were classified into various colors to efficiently determine the dangerous trees and dangerous areas.

• Clean Technology
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• v.29 no.1
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• pp.10-21
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• 2023

Hydrogels that are made of natural polymer-based double networks have excellent biocompatibility, low cytotoxicity, and high water content, assuring that the material has the properties required for a variety of biomedical applications. However, hydrogels also have limitations due to their relatively weak mechanical properties. In this study, hydrogels based on an alginate di-aldehyde (ADA) and gelatin (Gel) double network that is reinforced with additional hydrogen bonds formed between the hydroxyl (-OH) groups of the hyperbranched polymer (HPG) and the functional groups present inside of the hydrogels were successfully synthesized. The enhanced mechanical properties of these synthesized hydrogels were evaluated by varying the amount of HPG added during the hydrogel synthesis from 0 to 25%. In addition, magnetite nanoparticles (Fe₃O₄ NPs) were synthesized within the hydrogels and the structures and the magnetic properties of the hydrogels were also characterized. The hydrogels that contained 15% HPG and Fe₃O₄ NPs exhibited superparamagnetic behaviors with a saturation magnetization value of 3.8 emu g^-1. These particular hydrogels also had strengthened mechanical properties with a maximum compressive stress of 1.1 MPa at a strain of 67.4%. Magnetic hydrogels made with natural polymer-based double networks provide improved mechanical properties and have a significant potential for drug delivery and biomaterial application.

• Korean Journal of Environmental Biology
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• v.40 no.4
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• pp.413-422
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• 2022

Barnea manilensis is a bivalve which bores soft rocks, such as, limestone or mudstone in the low intertidal zone. They make burrows which have narrow entrances and wide interiors and live in these burrows for a lifetime. In this study, the morphology and the microstructure of the valve of rock-boring clam B. manilensis were observed using a stereoscopic microscope and FE-SEM, respectively. The chemical composition of specific part of the valve was assessed by energy dispersive X-ray spectroscopy (EDS) analysis. 3D modeling and structural dynamic analysis were used to simulate the boring behavior of B. manilensis. Microscopy results showed that the valve was asymmetric with plow-like spikes which were located on the anterior surface of the valve and were distributed in a specific direction. The anterior parts of the valve were thicker than the posterior parts. EDS results indicated that the valve mainly consisted of calcium carbonate, while metal elements, such as, Al, Si, Mn, Fe, and Mg were detected on the outer surface of the anterior spikes. It was assumed that the metal elements increased the strength of the valve, thus helping the B. manilensis to bore sediment. The simulation showed that spikes located on the anterior part of the valve received a load at all angles. It was suggested that the anterior part of the shell received the load while drilling rocks. The boring mechanism using the amorphous valve of B. manilensis is expected to be used as basic data to devise an efficient drilling mechanism.

• Journal of the Korean Society of Marine Environment & Safety
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• v.29 no.4
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• pp.363-371
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• 2023

To construct a ship, blocks of various sizes must be moved and erected . In this process, lugs are used such that they match the block fastening method and various functions suitable for the characteristics of each shipyard facility. The sizes and shapes of the lugs vary depending on the weight and shape of the block structures. The structure is reinforced by welding the doubling pads to compensate for insufficient rigidity around the holes where the shackle is fastened. As for the method of designing lugs according to lifting loading conditions, a simple calculation based on the beam theory and structural analysis using numerical modeling are performed. In the case of the analytical method, a standardized evaluation method must be established because results may differ depending on the type of element and modeling method. The application of this ambiguous methodology may cause serious safety problems during the process of moving and turning-over blocks. In this study , the effects of various parameters are compared and analyzed through numerical structural analysis to determine the modeling conditions and evaluation method that can evaluate the actual structural response of the lug. The modeling technique that represents the plate part and weld bead around the lug hole provides the most realistic behavior results. The modeling results with the same conditions as those of the actual lug where only the weld bead is connected to the main body of the lug, showed a lower ulimated strength compared with the results obtained by applying the MPC load. The two-dimensional shell element is applied to reduce the modeling and analysis time, and a safety working load was verified to be predicted by reducing the thickness of the doubling pad by 85%. The results of the effects of various parameters reviewed in the study are expected to be used as good reference data for the lug design and safe working load prediction.

• 한국노년학
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• v.31 no.3
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• pp.505-526
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• 2011

The purposes of this paper were to examine the level of knowledge of and attitudes toward the elderly and investigate the differences in the level of knowledge of and attitudes about the elderly by selected socio-demographic factors and aging related factors in Korea and the United States. The research subjects were 1129 college students attending 10 schools in Korea and the United States(840 Korean students in 5 schools, located in Seoul City, Gyeonggi-Do, Chungcheong-Do in Korea and 289 American students in 5 schools located in the State of New York of the United States). They were interviewed, using the structured questionnaire, and the data were analyzed by SPSS 15.0 for Windows. The research questionnaire was composed of Fact on Aging Quiz Part 1(FAQ 1) developed by Palmore(1998), Semantic Differential Scale development by Sanders et al., and several socio-demographic and aging related variables. The results indicated that, first, the level of knowledge of the elderly for Korean students was 12.51/25 and for American students was 11.57/25, resulting that the knowledge level of the elderly in Korea was higher than that of the United States. In addition, the results of students' knowledge differences between korea and the United States showed that Korean students showed high ratio of correct answer in 9 questions while American students showed high ratio of correct answer in only 4 questions, resulting that Korean students have higher knowledge than American students. Second, the level of attitudes toward the elderly for Korean students was 77.54 and for American students was 70.07 in 20-140 points, resulting that the attitude level of the elderly among American students were more positive than that of Korean students. The results of students' attitudes differences between Korea and the United States showed that Korean students responded positive tendency in only one question while American students responded positive tendencies in 14 questions, resulting that American students were more positive attitudes toward the elderly than that of Korean students. Third, there is a significant correlation between the knowledge of and attitudes toward the elderly in both Korean and American students. Based on these results, implications for policy, practice, and research were further discussed.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1353-1369
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• 2023

In the event of a disaster accident at sea, the scale of damage will vary due to weather effects such as wind, currents, and tidal waves, and it is obligatory to minimize the scale of damage by establishing appropriate control plans through quick on-site identification. In particular, it is difficult to identify pollutants that exist in a thin film at sea surface due to their relatively low viscosity and surface tension among pollutants discharged into the sea. Therefore, this study aims to develop an algorithm to detect suspended pollutants on the sea surface in RGB images using imaging equipment that can be easily used in the field, and to evaluate the performance of the algorithm using input data obtained from actual waters. The developed algorithm uses image enhancement techniques to improve the contrast between the intensity values of pollutants and general sea surfaces, and through histogram analysis, the background threshold is found,suspended solids other than pollutants are removed, and finally pollutants are classified. In this study, a real sea test using substitute materials was performed to evaluate the performance of the developed algorithm, and most of the suspended marine pollutants were detected, but the false detection area occurred in places with strong waves. However, the detection results are about three times better than the detection method using a single threshold in the existing algorithm. Through the results of this R&D, it is expected to be useful for on-site control response activities by detecting suspended marine pollutants that were difficult to identify with the naked eye at existing sites.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1413-1425
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• 2023

The increasing frequency of wildfires due to climate change is causing extreme loss of life and property. They cause loss of vegetation and affect ecosystem changes depending on their intensity and occurrence. Ecosystem changes, in turn, affect wildfire occurrence, causing secondary damage. Thus, accurate estimation of the areas affected by wildfires is fundamental. Satellite remote sensing is used for forest fire detection because it can rapidly acquire topographic and meteorological information about the affected area after forest fires. In addition, deep learning algorithms such as convolutional neural networks (CNN) and transformer models show high performance for more accurate monitoring of fire-burnt regions. To date, the application of deep learning models has been limited, and there is a scarcity of reports providing quantitative performance evaluations for practical field utilization. Hence, this study emphasizes a comparative analysis, exploring performance enhancements achieved through both model selection and data design. This study examined deep learning models for detecting wildfire-damaged areas using Landsat 8 satellite images in California. Also, we conducted a comprehensive comparison and analysis of the detection performance of multiple models, such as U-Net and High-Resolution Network-Object Contextual Representation (HRNet-OCR). Wildfire-related spectral indices such as normalized difference vegetation index (NDVI) and normalized burn ratio (NBR) were used as input channels for the deep learning models to reflect the degree of vegetation cover and surface moisture content. As a result, the mean intersection over union (mIoU) was 0.831 for U-Net and 0.848 for HRNet-OCR, showing high segmentation performance. The inclusion of spectral indices alongside the base wavelength bands resulted in increased metric values for all combinations, affirming that the augmentation of input data with spectral indices contributes to the refinement of pixels. This study can be applied to other satellite images to build a recovery strategy for fire-burnt areas.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.979-995
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• 2023

As wildfires are difficult to predict, real-time monitoring is crucial for a timely response. Geostationary satellite images are very useful for active fire detection because they can monitor a vast area with high temporal resolution (e.g., 2 min). Existing satellite-based active fire detection algorithms detect thermal outliers using threshold values based on the statistical analysis of brightness temperature. However, the difficulty in establishing suitable thresholds for such threshold-based methods hinders their ability to detect fires with low intensity and achieve generalized performance. In light of these challenges, machine learning has emerged as a potential-solution. Until now, relatively simple techniques such as random forest, Vanilla convolutional neural network (CNN), and U-net have been applied for active fire detection. Therefore, this study proposed an active fire detection algorithm using state-of-the-art (SOTA) deep learning techniques using data from the Advanced Himawari Imager and evaluated it over East Asia and Australia. The SOTA model was developed by applying EfficientNet and lion optimizer, and the results were compared with the model using the Vanilla CNN structure. EfficientNet outperformed CNN with F1-scores of 0.88 and 0.83 in East Asia and Australia, respectively. The performance was better after using weighted loss, equal sampling, and image augmentation techniques to fix data imbalance issues compared to before the techniques were used, resulting in F1-scores of 0.92 in East Asia and 0.84 in Australia. It is anticipated that timely responses facilitated by the SOTA deep learning-based approach for active fire detection will effectively mitigate the damage caused by wildfires.