• Economic and Environmental Geology
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• v.44 no.3
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• pp.229-238
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• 2011

S-wave, which provides lithology and pore fluid information, plays a key role in estimating gas-hydrate saturation. In general, P- and S-wave velocities increase in the presence of gas-hydrate and the P-wave velocity decreases in the presence of free gas under the gas-hydrate layer. Whereas there are very small changes, even slightly increases, in the S-wave velocity in the free gas layer because S-wave is not affected by the pore fluid when propagating in the free gas layer. To verify those velocity properties of the BSR (bottom-simulating reflector) depth in the gas-hydrate prospect area in the Ulleung Basin, P- and S-wave velocity profiles were derived from multi-component ocean-bottom seismic data which were acquired by Korea Institute of Geoscience and Mineral Resources (KIGAM) in May 2009. OBS (ocean-bottom seismometer) hydrophone component data were modeled and inverted first through the traveltime inversion method to derive P-wave velocity and depth model of survey area. 2-D multichannel stacked data were incorporated as an initial model. Two horizontal geophone component data, then, were polarization filtered and rotated to make radial component section. Traveltimes of main S-wave events were picked and used for forward modeling incorporating Poisson's ratio. This modeling provides S-wave profiles and Poisson's ratio profiles at every OBS site. The results shows that P-wave velocities in most OBS sites decrease beneath the BSR, whereas S-wave velocities slightly increase. Consequently, Poisson's ratio decreased strongly beneath the BSR indicating the presence of a free gas layer under the BSR.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.5
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• pp.79-96
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• 2021

Green infrastructure planning represents landscape planning measures to reduce particulate matter. This study aimed to derive factors that may be used in planning green infrastructure for particulate matter reduction using text mining techniques. A range of analyses were carried out by focusing on keywords such as 'particulate matter reduction plan' and 'green infrastructure planning elements'. The analyses included Term Frequency-Inverse Document Frequency (TF-IDF) analysis, centrality analysis, related word analysis, and topic modeling analysis. These analyses were carried out via text mining by collecting information on previous related research, policy reports, and laws. Initially, TF-IDF analysis results were used to classify major keywords relating to particulate matter and green infrastructure into three groups: (1) environmental issues (e.g., particulate matter, environment, carbon, and atmosphere), target spaces (e.g., urban, park, and local green space), and application methods (e.g., analysis, planning, evaluation, development, ecological aspect, policy management, technology, and resilience). Second, the centrality analysis results were found to be similar to those of TF-IDF; it was confirmed that the central connectors to the major keywords were 'Green New Deal' and 'Vacant land'. The results from the analysis of related words verified that planning green infrastructure for particulate matter reduction required planning forests and ventilation corridors. Additionally, moisture must be considered for microclimate control. It was also confirmed that utilizing vacant space, establishing mixed forests, introducing particulate matter reduction technology, and understanding the system may be important for the effective planning of green infrastructure. Topic analysis was used to classify the planning elements of green infrastructure based on ecological, technological, and social functions. The planning elements of ecological function were classified into morphological (e.g., urban forest, green space, wall greening) and functional aspects (e.g., climate control, carbon storage and absorption, provision of habitats, and biodiversity for wildlife). The planning elements of technical function were classified into various themes, including the disaster prevention functions of green infrastructure, buffer effects, stormwater management, water purification, and energy reduction. The planning elements of the social function were classified into themes such as community function, improving the health of users, and scenery improvement. These results suggest that green infrastructure planning for particulate matter reduction requires approaches related to key concepts, such as resilience and sustainability. In particular, there is a need to apply green infrastructure planning elements in order to reduce exposure to particulate matter.

• Korean Journal of Remote Sensing
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• v.37 no.6_1
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• pp.1757-1766
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• 2021

The green coverage ratio is the ratio of the land area to green coverage area, and it is used as a practical urban greening index. The green coverage ratio is calculated based on the land cover map, but low spatial resolution and inconsistent production cycle of land cover map make it difficult to calculate the correct green coverage area and analyze the precise green coverage. Therefore, this study proposes a new method to calculate green coverage area using aerial images and deep neural networks. Green coverage ratio can be quickly calculated using manned aerial images acquired by local governments, but precise analysis is difficult because components of image such as acquisition date, resolution, and sensors cannot be selected and modified. This limitation can be supplemented by using an unmanned aerial vehicle that can mount various sensors and acquire high-resolution images due to low-altitude flight. In this study, we proposed a method to calculate green coverage ratio from manned or unmanned aerial images, and experimentally verified the proposed method. Aerial images enable precise analysis by high resolution and relatively constant cycles, and deep learning can automatically detect green coverage area in aerial images. Local governments acquire manned aerial images for various purposes every year and we can utilize them to calculate green coverage ratio quickly. However, acquired manned aerial images may be difficult to accurately analyze because details such as acquisition date, resolution, and sensors cannot be selected. These limitations can be supplemented by using unmanned aerial vehicles that can mount various sensors and acquire high-resolution images due to low-altitude flight. Accordingly, the green coverage ratio was calculated from the two aerial images, and as a result, it could be calculated with high accuracy from all green types. However, the green coverage ratio calculated from manned aerial images had limitations in complex environments. The unmanned aerial images used to compensate for this were able to calculate a high accuracy of green coverage ratio even in complex environments, and more precise green area detection was possible through additional band images. In the future, it is expected that the rust rate can be calculated effectively by using the newly acquired unmanned aerial imagery supplementary to the existing manned aerial imagery.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.3
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• pp.1-10
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• 2021

This study aimed to evaluate preferences of Bukhansan dulegil using sentiment analysis, a natural language processing technique, to derive preferred and non-preferred factors. Therefore, we collected blog articles written in 2019 and produced sentimental scores by the derivation of positive and negative words in the texts for 21 dulegil courses. Then, content analysis was conducted to determine which factors led visitors to prefer or dislike each course. In blogs written about Bukhansan dulegil, positive words appeared in approximately 73% of the content, and the percentage of positive documents was significantly higher than that of negative documents for each course. Through this, it can be seen that visitors generally had positive sentiments toward Bukhansan dulegil. Nevertheless, according to the sentiment score analysis, all 21 dulegil courses belonged to both the preferred and non-preferred courses. Among courses, visitors preferred less difficult courses, in which they could walk without a burden, and in which various landscape elements (visual, auditory, olfactory, etc.) were harmonious yet distinct. Furthermore, they preferred courses with various landscapes and landscape sequences. Additionally, visitors appreciated the presence of viewpoints, such as observation decks, as a significant factor and preferred courses with excellent accessibility and information provisions, such as information boards. Conversely, the dissatisfaction with the dulegil courses was due to noise caused by adjacent roads, excessive urban areas, and the inequality or difficulty of the course which was primarily attributed to insufficient information on the landscape or section of the course. The results of this study can serve not only serve as a guide in national parks but also in the management of nearby forest green areas to formulate a plan to repair and improve dulegil. Further, the sentiment analysis used in this study is meaningful in that it can continuously monitor actual users' responses towards natural areas. However, since it was evaluated based on a predefined sentiment dictionary, continuous updates are needed. Additionally, since there is a tendency to share positive content rather than negative views due to the nature of social media, it is necessary to compare and review the results of analysis, such as with on-site surveys.

• Journal of the Society of Disaster Information
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• v.18 no.1
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• pp.182-193
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• 2022

Purpose: By measuring and evaluating the risk of biodiesel through non-volatile residue (NVR) and flash point and explosion limit measurement at a specific temperature according to ASTM test standards, the risk of chemical fire causative substances is identified and a universal evaluation method By derivation and securing the risk-related data of the material, it can be used for the identification and analysis of the cause of the fire, and it can be applied to the risk assessment of other chemical substances Method: In order to measure the risk of biodiesel, it was measured using the non-volatile residue(NVR) measurement method, which measures how much flammable liquid is generated at a specific temperature. Heating was tested by applying KS M 5000: 2009 Test Method 4111. In addition, the flash point was measured using the method specified in ASTM E659-782005, and the energy supply method was measured using the constant temperature method. In addition, the explosion limit measurement was conducted in accordance with ASTM E 681-04 「Standard test method for concentration limits of flammability of chemicals(Vapors and gases)」 test standard. Result: As a result of checking the amount of combustible liquid by the non-volatile residue (NVR)measurement method, the non-volatile residue(NVR) of general diesel when left at 105±2℃ for 3 hours was about 30% (70% of volatile matter) and about 4% of biodiesel. In addition, similar results were obtained for the non-volatile residue(NVR)heating temperature of 150±2℃, 3 hours and 200±2℃ for 1 hour, and white smoke was generated at 200℃ or higher. In addition, similar values were obtained as a result of experimentally checking the explosion (combustion) limits of general diesel, general diesel containing 20% biodiesel, and 100% biodiesel. Therefore, it was confirmed that the flammability risk did not significantly affect the explosion risk. Conclusion: The results of this study suggested the risk judgment criteria for mixtures through experimental research on flammable mixtures for the purpose of securing the effectiveness, reliability, and reproducibility of the details of the criteria for determining dangerous substances in the existing Dangerous Materials Safety Management Act. It will be possible to provide reference data for the judgment criteria for flammable liquids that are regulated in the field. In addition, if the know-how for each test method is accumulated through this study, it is expected that it will be used as basic data in the research on risk assessment of dangerous substances and as a basis for research on the determination of dangerous substances.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1107-1118
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• 2021

Climate change brought on by global warming increased the frequency of flood and drought on the Korean Peninsula, along with the casualties and physical damage resulting therefrom. Preparation and response to these water disasters requires national-level planning for water resource management. In addition, watershed-level management of water resources requires flow duration curves (FDC) derived from continuous data based on long-term observations. Traditionally, in water resource studies, physical rainfall-runoff models are widely used to generate duration curves. However, a number of recent studies explored the use of data-based deep learning techniques for runoff prediction. Physical models produce hydraulically and hydrologically reliable results. However, these models require a high level of understanding and may also take longer to operate. On the other hand, data-based deep-learning techniques offer the benefit if less input data requirement and shorter operation time. However, the relationship between input and output data is processed in a black box, making it impossible to consider hydraulic and hydrological characteristics. This study chose one from each category. For the physical model, this study calculated long-term data without missing data using parameter calibration of the Soil Water Assessment Tool (SWAT), a physical model tested for its applicability in Korea and other countries. The data was used as training data for the Long Short-Term Memory (LSTM) data-based deep learning technique. An anlysis of the time-series data fond that, during the calibration period (2017-18), the Nash-Sutcliffe Efficiency (NSE) and the determinanation coefficient for fit comparison were high at 0.04 and 0.03, respectively, indicating that the SWAT results are superior to the LSTM results. In addition, the annual time-series data from the models were sorted in the descending order, and the resulting flow duration curves were compared with the duration curves based on the observed flow, and the NSE for the SWAT and the LSTM models were 0.95 and 0.91, respectively, and the determination coefficients were 0.96 and 0.92, respectively. The findings indicate that both models yield good performance. Even though the LSTM requires improved simulation accuracy in the low flow sections, the LSTM appears to be widely applicable to calculating flow duration curves for large basins that require longer time for model development and operation due to vast data input, and non-measured basins with insufficient input data.

• Journal of Korean Society of Disaster and Security
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• v.14 no.4
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• pp.47-60
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• 2021

Recently, as the occurrence frequency of sudden floods due to climate variability increased, the damage of aging chuteway slabs of spillway are on the rise. Accordingly, a wide array of field survey, hydraulic experiment and numerical simulation have been conducted to find the cause of damage on chuteway slabs. However, these studies generally reviewed the flow characteristics and distribution of pressure on chuteway slabs. Therefore the derivation of damage on chuteway slabs was relatively insufficient in the literature. In this study, the cavitation erosion and hydraulic jacking were assumed to be the causes of damage on chuteway slabs, and the phenomena were reproduced using 3D numerical models, FLOW-3D and COMSOL Multiphysics. In addition, the cavitation index was calculated and the von Mises stress by uplift pressure distribution was compared with tensile and bending strength of concrete to evaluate the possibility of cavitation erosion and hydraulic jacking. As a result of numerical simulation on cavitation erosion and hydraulic jacking under various flow conditions with complete opening gate, the cavitation index in the downstream of spillway was less than 0.3, and the von Mises stress on concrete was 4.6 to 5.0 MPa. When von Mises stress was compared with tensile and bending strength of concrete, the fatigue failure caused by continuous pressure fluctuation occurred on chuteway slabs. Therefore, the cavitation erosion and hydraulic jacking caused by high speed flow were one of the main causes of damage to the chuteway slabs in spillway. However, this study has limitations in that the various shape conditions of damage(cavity and crack) and flow conditions were not considered and Fluid-Structure Interaction (FSI) was not simulated. If these limitations are supplemented and reviewed, it is expected to derive more efficient utilization of the maintenance plan on spillway in the future.

• Science of Emotion and Sensibility
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• v.25 no.1
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• pp.3-20
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• 2022

Recently, prior to the commercialization of urban air mobility (UAM), the importance of R&D for air transportation-related industries in urban areas has significantly increased. To create a UAM environment, research is being conducted on personal air vehicles (PAVs). They are key means of air transportation, but research on the physical factors influencing their passengers is relatively insufficient. In particular, because the PAV is expected to be used as a living space for the passengers, research on the effects of the physical elements generated in the PAV on the human body is essential to design an interior space that supports the in-vehicle activities of the passengers. Therefore, the purpose of this study is to derive the constraint factors that affect the human body due to the air navigation characteristics of the PAV and to understand the impact of these constraint factors on the bodies of the passengers performing in-vehicle activities. The results of this study indicate that when the PAV was operated at less than 4,000 ft, which is the operating standard, the constraint factors were noise, vibration, and motion sickness caused by low-frequency motion. These constraint factors affect in-vehicle activity; thus, the in-vehicle activities that can be performed in a PAV were derived using autonomous cars, airplanes, and PAV concept cases. Furthermore, considering the impact of the constraint factors and their levels on the human body, recommended constraint factor criteria to support in-vehicle activities were established. To reduce the level of impact of the constraint factors on the human body and to support in-vehicle activity, the seat's shape and built-in functions of the seat (vibration reduction function, temperature control, LED lighting, etc.) and external noise reduction using a directional speaker for each individual seat were recommended. Moreover, it was suggested that interior materials for noise and vibration reduction should be used in the design of the interior space. The contributions of this study are the determination of the constraint factors affecting the in-vehicle PAV activity and the confirmation of the level of impact of the factors on the human body; in the future, these findings can be used as basic data for suitable PAV interior design.

• Journal of Service Research and Studies
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• v.12 no.2
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• pp.65-79
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• 2022

Non-face-to-face classes continue due to Covid-19. There have been e-learning classes since the past, but the difference is that the current non-face-to-face classes are blended classes that combine real-time and recording classes or combine face-to-face and non-face classes. It is also characterized by being able to self-filmed or choose various lecture platforms in a place other than a dedicated studio. The advantages of non-face-to-face classes can be learned beyond time and space, and repetitive viewing and learning speed can be adjusted. Greening classes have no time and place constraints, and real-time classes have the advantage of high communication effects with learners. Evaluating whether non-face-to-face classes provide sufficient quality compared to face-to-face classes or e-learning will be necessary if branded classes are considered for post Covid. In this paper, for the evaluation of the service quality of non-face-to-face classes, the essential attributes desired by the instructors were derived from the viewpoint of Kano quality attributes and a quality improvement plan was proposed. After expressing the degree of functions that non-face-to-face classes should have on the X-axis and the satisfaction of learners on the Y-axis, 23 quality attributes were classified into 6 quality dimensions. In addition, satisfaction coefficient, dissatisfaction coefficient, and customer satisfaction improvement index were derived. As a result, 50% of learners were satisfied with non-face-to-face classes, but the preference was slightly higher than satisfaction, suggesting the sustainability of non-face-to-face classes. In terms of the customer satisfaction improvement index, the ranking of attributes with the largest increase in satisfaction when improving class quality was as follows. Professors' quick answers to learners' questions, content that can fully explain the subject, what the professor explains easily, develop high-quality content that can be learned on mobile phones, fairness of attendance checks, and real-time classes should start on time.

• Journal of the Korea Organic Resources Recycling Association
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• v.31 no.1
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• pp.69-84
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• 2023

Despite the continuous installation and regular inspection of waste treatment facilities, complaints about excessive incineration and illegal dumping stench continue to occur at on-site treatment facilities. In addition, field surveys were conducted on the waste treatment facilities currently in operation (6 type) to understand the waste treatment process for each field, to grasp the main operating factors applied to the inspection. In addition, we calculated the material·energy balance for each main process and confirmed the proper operation of the waste disposal facility. As a result of the site survey, in the case of heat treatment facilities such as incineration, cement kilns, and incineration heat recovery facilities, the main factors are maintenance of the temperature of the incinerator required for incineration and treatment of the generated air pollutants, and in the case of landfill facilities Retaining wall stability, closed landfill leachate and emission control emerged as major factors. In the case of sterilization and crushing facilities, the most important factor is whether or not sterilization is possible (apobacterium inspection).In the case of food distribution waste treatment facilities, retention time and odor control during fermentation (digestion, decomposed) are major factors. Calculation results of material balance and energy resin for each waste treatment facility In the case of incineration facilities, it was confirmed that the amount of flooring materials generated is about 14 % and the amount of scattering materials is about 3 % of the amount of waste input, and that the facility is being operated properly. In addition, among foodwaste facilities, in the case of an anaerobic digestion facility, the amount of biogas generated relative to the amount of inflow is about 17 %, and the biogas conversion efficiency is about 81 %, in the case of composting facility, about 11 % composting of the inflow waste was produced, and it was comfirmend that all were properly operated. As a result, in order to improve the inspection method for waste treatment facilities, it is necessary not only to accumulate quantitative standards for detailed inspection methods, but also to collect operational data for one year at the time of regular inspections of each facility, Grasping the flow and judging whether or not the treatment facility is properly operated. It is then determined that the operation and management efficiency of the treatment facility will increase.