• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.5
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• pp.125-137
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• 2021

How can we explain the phenomenon of small, old alleyways in the city becoming rising commercial places attracting people from an aesthetic perspective? This research discusses distinctive aesthetic experiences of urban commercial alleyways, which are located on inner roads and consist of small-scale stores and explore the specific aspects of Sharosu-gil, located in Gwanak-gu, Seoul. The aesthetic experience of urban commercial alleyways is generated by the contrast with the refined urban fabric along main roads in terms of space, the gap between the old and the new, and the antagonism between the known and the less known. The approach to Sharosu-gil consists of the high-rise buildings along the main road built in the 2000s, then encountering low-rise buildings on inside roads built from the late 1970s to the present. Therefore, it is judged that the site has sufficient conditions to generate the aesthetic experience as an urban commercial alleyway. As a result of analyzing the street improvement projects, first, the official announcement of the name 'Sharosu-gil' was interpreted as an escape from the place specificity and garnered the acquisition of the characteristics of an alternative. Secondly, the improvement project for old-established signboards was interpreted as harmony between the new and the old and the loss of temporality. Thirdly, in the pedestrian priority road project, the pavement was interpreted as a reinforcement of the identity as an alleyway and the visualization of the area. Since the reality of urban commercial alleyways depends on the user's visiting, it is necessary to interpret alleyways from the perspective of the senses and aesthetics, not just from social phenomena or capital logic perspective. The study will cast implications for relevant schemes and data-driven research.

• Clean Technology
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• v.27 no.3
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• pp.232-239
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• 2021

In order to develop a novel system named "thermal medium and gas circulation type pyrolysis system," this study was conducted to obtain basic data for process simulation before performing the pyrolysis experiment. Polypropylene (PP) was chosen as model material in the basic pyrolysis experiment instead of waste plastic and fluidized sand (hereinafter referred to as "sand"), and it was used as a heat transfer material in the "thermal medium and gas circulation type pyrolysis system." Ni was impregnated as an active catalyst on the sand to promote catalytic pyrolysis. The basic physical properties of PP were analyzed using a thermogravimetric analyzer, and pyrolysis was performed at 600 ℃ in an N₂ atmosphere to produce liquid oil. The distribution of the carbon number of the liquid oil generated through the catalytic pyrolysis reaction was analyzed using GC/MS. We investigated the effects of varying the pyrolysis space velocity and catalyst amount on the yield of liquid oil and the carbon number distribution of the liquid oil. Using Ni/sand, the yield of liquid oil was increased except with the pyrolysis condition of 10 wt% Ni/sand at a space velocity of 30,000 h^-1, and the composition of C₆ ~ C₁₂ hydrocarbons increased. With increases in the space velocity, higher yields of liquid oil were obtained, but the composition of C₆ ~ C₁₂ hydrocarbons was reduced. With 1 wt% Ni/sand, the oil yield obtained was greater than that obtained with 10 wt% Ni/sand. In summary, when 1 wt% Ni/sand was used at a space velocity of 10,000 h^-1, the oil yield was 60.99 wt% and the composition of C₆ ~ C₁₂ hydrocarbons was highest at 42.06 area%.

• Journal of agricultural medicine and community health
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• v.46 no.2
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• pp.78-88
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• 2021

Objectives: This study aimed to investigate health risk awareness pertaining to fine dust exposure and the use of face masks in farmers, as well as their attitude toward education regarding fine dust-related respiratory disease prevention. Methods: In total, 295 farmers were interviewed in a survey using a structured questionnaire to obtain data on general characteristics, farming-related characteristics, health risk awareness pertaining to fine dust exposure, attitude toward education on fine dust-related respiratory disease prevention and the use of face masks. This study was analyzed the correlation between the perceived susceptibility to fine dust exposure and willingness to participate in education on fine dust-related respiratory disease prevention. Results: The mean score for perceived susceptibility to fine dust exposure was 3.8 (out of 5), and the participants were highly willing to receive education on fine dust-related respiratory disease prevention. In Multiple response analysis of reactions to exposure to fine dust generated during work, 221 participants responded that they practiced at least one preventive action; participants gave a positive response to "wearing masks" (56.1%), "personal hygiene, such as hand washing." (52.9%). In terms of education methods, 94 (33.6%) participants preferred to learn online or via text messages. Conclusions: The significant correlation between the perceived susceptibility to fine dust exposure and willingness to participate in education on fine dust-related respiratory disease prevention shows the importance of promoting education on prevention. The results of this study can help understand as reference for education on fine dust-related respiratory disease prevention.

• Economic and Environmental Geology
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• v.54 no.1
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• pp.77-89
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• 2021

In this study, a method has been proposed to improve the performance of hydraulic property estimation model developed by Jeong et al. (2020). In their study, low-dimensional features of the annual groundwater level (GWL) fluctuation patterns extracted based on a Denoising autoencoder (DAE) was used to develop a regression model for predicting hydraulic properties of an aquifer. However, low-dimensional features of the DAE are highly dependent on the precipitation pattern even if the GWL is monitored at the same location, causing uncertainty in hydraulic property estimation of the regression model. To solve the above problem, a process for generating the GWL fluctuation pattern for conditioning the precipitation is proposed based on a conditional variational autoencoder (CVAE). The CVAE trains a statistical relationship between GWL fluctuation and precipitation pattern. The actual GWL and precipitation data monitored on a total of 71 monitoring stations over 10 years in South Korea was applied to validate the effect of using CVAE. As a result, the trained CVAE model reasonably generated GWL fluctuation pattern with the conditioning of various precipitation patterns for all the monitoring locations. Based on the trained CVAE model, the low-dimensional features of the GWL fluctuation pattern without interference of different precipitation patterns were extracted for all monitoring stations, and they were compared to the features extracted based on the DAE. Consequently, it can be confirmed that the statistical consistency of the features extracted using CVAE is improved compared to DAE. Thus, we conclude that the proposed method may be useful in extracting a more accurate feature of GWL fluctuation pattern affected solely by hydraulic characteristics of the aquifer, which would be followed by the improved performance of the previously developed regression model.

• Korean Journal of Mineralogy and Petrology
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• v.33 no.4
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• pp.307-324
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• 2020

Major and trace elements, and Sr, Nd, isotopic composition analysis have been carried out on the Miocene basalt (Huangsongpu basalt, 20 Ma) 25 km to northeast from the Mt. Baekdu. The basalt has Na2O+K2O=3.5~4.7 wt.%, and MgO=9.9~11.1 wt.%, containing Mg-rich olivine (Mg#=75~86), clinopyroxene (Mg#=72~85) and Ca-rich plagioclase micro-phenocrysts. These data suggest that the basalt belongs to the alkaline magma series with a primitive nature, crystallized at a near-liquidus. The basalt is also characterized by high Cr (394~479 ppm) and Ni (389~519 ppm) contents, Nb-Ta enrichment anomalies and OIB-like trace elements patterns, displaying identical signatures to those of typical intraplate magmas. The rare earth element (REE) patterns of the basalt and high (Gd/Yb)sample/(Gd/Yb)PM ratio (=2.8~3.5) suggest the parental magma was derived from relatively low-degree (3~5%) partial melting of garnet peridotite. The 143Nd/144Nd and 87Sr/86Sr composition of the basalt are higher than those of BSE. The high 87Sr/86Sr (= ~0.7058) ratio of the basalt indicates a contribution of recycled ancient oceanic crust or continental crust on the Pacific slab suggesting that the Huangsongpu basalt was generated from metasomatized mantle.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.6
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• pp.131-144
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• 2021

The organizational ambidexterity is an organizational strategy designed to pursue exploration activities to seize new opportunities and exploitation activities to efficiently use resources. Most of these ambidextrous structures have been studied for large corporations with slack resources, and there are still not many studies on the necessity of an ambidextrous structure for startups with relatively low-level resources. However, recently, the startup ecosystem is being advanced globally, and the amount of VC investment is rapidly increasing. This is a time when a lot of venture fund is invested in startups and a startup-friendly environment for rapid growth is created. This is the time to discuss the necessity and applicability of an ambidextrous organizational structure for startups. Therefore, this study conducted a hypothesis test whether the importance and necessity of balance that startups solving market problems with new ideas and utilizing accumulated resources have. To conduct this study, we analyzed 140 startups data gathered from the survey and the moderation effect was also analyzed. As a result of the study, it was verified that the balance of startup exploration and exploitation had a significant effect on startup performance, and the moderating effect of environmental dynamics was found to have a significant effect on the relationship with non-financial performance. Therefore, for startups with insufficient resources, it was concluded that the surplus resources generated in the process of a firm's growth should be effectively utilized and the balance between exploration and exploitation should be balanced from the initial stage of searching for a new business. In other words, it was confirmed that it is important for continuous growth and survival to seek the structure of an ambidextrous organization in order to internalize a mechanism that enables startups to pursue both effectiveness and efficiency in the long term. This study suggests a strategic direction for the growth of startups from the perspective of organizational structure. We expect that this meaningful results on the relationship between the ambidextrous capabilities of startups and performance contribute to the growth of startups in the rapidly growing startup venture environment.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1505-1514
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• 2022

Image matching is a crucial preprocessing step for effective utilization of multi-temporal and multi-sensor very high resolution (VHR) satellite images. Deep learning (DL) method which is attracting widespread interest has proven to be an efficient approach to measure the similarity between image pairs in quick and accurate manner by extracting complex and detailed features from satellite images. However, Image matching of VHR satellite images remains challenging due to limitations of DL models in which the results are depending on the quantity and quality of training dataset, as well as the difficulty of creating training dataset with VHR satellite images. Therefore, this study examines the feasibility of DL-based method in matching pair extraction which is the most time-consuming process during image registration. This paper also aims to analyze factors that affect the accuracy based on the configuration of training dataset, when developing training dataset from existing multi-sensor VHR image database with bias for DL-based image matching. For this purpose, the generated training dataset were composed of correct matching pairs and incorrect matching pairs by assigning true and false labels to image pairs extracted using a grid-based Scale Invariant Feature Transform (SIFT) algorithm for a total of 12 multi-temporal and multi-sensor VHR images. The Siamese convolutional neural network (SCNN), proposed for matching pair extraction on constructed training dataset, proceeds with model learning and measures similarities by passing two images in parallel to the two identical convolutional neural network structures. The results from this study confirm that data acquired from VHR satellite image database can be used as DL training dataset and indicate the potential to improve efficiency of the matching process by appropriate configuration of multi-sensor images. DL-based image matching techniques using multi-sensor VHR satellite images are expected to replace existing manual-based feature extraction methods based on its stable performance, thus further develop into an integrated DL-based image registration framework.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1691-1707
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• 2022

Cheonji Lake, the caldera of Baekdu Mountain, located on the border of the Korean Peninsula and China, alternates between melting and freezing seasonally. There is a magma chamber beneath Cheonji, and variations in the magma chamber cause volcanic antecedents such as changes in the temperature and water pressure of hot spring water. Consequently, there is an abnormal region in Cheonji where ice melts quicker than in other areas, freezes late even during the freezing period, and has a high-temperature water surface. The abnormal area is a discharge region for hot spring water, and its ice gradient may be used to monitor volcanic activity. However, due to geographical, political and spatial issues, periodic observation of abnormal regions of Cheonji is limited. In this study, the degree of ice change in the optimal region was quantified using a Landsat -5/-7/-8 optical satellite image and a Modified U-Net regression model. From January 22, 1985 to December 8, 2020, the Visible and Near Infrared (VNIR) band of 83 Landsat images including anomalous regions was utilized. Using the relative spectral reflectance of water and ice in the VNIR band, unique data were generated for quantitative ice variability monitoring. To preserve as much information as possible from the visible and near-infrared bands, ice gradient was noticed by applying it to U-Net with two encoders, achieving good prediction accuracy with a Root Mean Square Error (RMSE) of 140 and a correlation value of 0.9968. Since the ice change value can be seen with high precision from Landsat images using Modified U-Net in the future may be utilized as one of the methods to monitor Baekdu Mountain's volcanic activity, and a more specific volcano monitoring system can be built.

• Resources Recycling
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• v.31 no.4
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• pp.56-65
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• 2022

Copper is one of the non-ferrous metals used in the electrical/electronic manufacturing industries due to its superior properties particularly the high conductivity and less resistivity. The effluent generated from the surface finishing process of these industries contains higher copper content which gets discharged in to water bodies directly or indirectly. This causes severe environmental pollution and also results in loss of an important valuable metal. To overcome this issue, continuous R & D activities are going on across the globe in adsorption area with the purpose of finding an efficient, low cost and ecofriendly adsorbent. In view of the above, present investigation was made to compare the performance of a plant root (Datura root powder) as a bio-adsorbent to that of the synthetic one (Tulsion T-42) for copper adsorption from such effluent. Experiments were carried out in batch studies to optimize parameters such as adsorbent dose, contact time, pH, feed concentration, etc. Results of the batch experiments indicate that 0.2 g of Datura root powder and 0.1 g of Tulsion T-42 showed 95% copper adsorption from an initial feed/solution of 100 ppm Cu at pH 4 in contact time of 15 and 30 min, respectively. Adsorption data for both the adsorbents were fitted well to the Freundlich isotherm. Experimental results were also validated with the kinetic model, which showed that the adsorption of copper followed pseudo-second order rate expression for the both adsorbents. Overall result demonstrates that the bio-adsorbent tested has a potential applicability for metal recovery from the waste solutions/effluents of metal finishing units. In view of the requirements of commercial viability and minimal environmental damage there from, Datura root powder being an effective material for metal uptake, may prove to be a feasible adsorbent for copper recovery after the necessary scale-up studies.

• Journal of the Korean Society of Radiology
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• v.17 no.1
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• pp.157-165
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• 2023

Ultrasound imaging uses sound waves of frequencies to cause physical actions such as reflection, absorption, refraction, and transmission at the edge between different tissues. Improvement is needed because there is a lot of noise due to the characteristics of the data generated from the ultrasound equipment, and it is difficult to grasp the shape of the tissue to be actually observed because the edge is vague. The edge enhancement method is used as a method to solve the case where the edge surface looks clumped due to a decrease in image quality. In this paper, as a method to strengthen the interface, the quality improvement was confirmed by strengthening the interface, which is the high-frequency part, in each image using an unsharpening mask and high boost. The mask filtering used for each image was evaluated by measuring PSNR and SNR. Abdominal, head, heart, liver, kidney, breast, and fetal images were obtained from Philips epiq5g and affiniti70g and Alpinion E-cube 15 ultrasound equipment. The program used to implement the algorithm was implemented with MATLAB R2022a of MathWorks. The unsharpening and high-boost mask array size was set to 3*3, and the laplacian filter, a spatial filter used to create outline-enhanced images, was applied equally to both masks. ImageJ program was used for quantitative evaluation of image quality. As a result of applying the mask filter to various ultrasound images, the subjective image quality showed that the overall contour lines of the image were clearly visible when unsharpening and high-boost mask were applied to the original image. When comparing the quantitative image quality, the image quality of the image to which the unsharpening mask and the high boost mask were applied was evaluated higher than that of the original image. In the portal vein, head, gallbladder, and kidney images, the SNR, PSNR, RMSE and MAE of the image to which the high-boost mask was applied were measured to be high. Conversely, for images of the heart, breast, and fetus, SNR, PSNR, RMSE and MAE values were measured as images with the unsharpening mask applied. It is thought that using the optimal mask according to the image will help to improve the image quality, and the contour information was provided to improve the image quality.