• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.3
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• pp.11-28
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• 2021

Due to its size and complex characteristics, it is not often to newly create a large park within an existing urban area. Also, there has been a lack of research on the planting design methodologies for a large park. This study aims to elucidate how ecological ideas can be applied to planting practice from a designer's perspective, and eventually suggest a planting design framework in the actual case, the Central Park in the City of Gwangju. This framework consists of spatial structure of planting area in order to connect and unite the separated green patches, to adapt to the changes of existing vegetation patterns, to maintain the visual continuity of landscape, and to organize the whole open space system. The framework can be provided for the spatial planning and planting design phase in which the landscape designer flexibly uses it with the design intentions as well as with an understanding of the physical, social, and aesthetic characteristics of the site. The significance of this approach is, first that it can maintain ecological and visual consistency of the both existing and introduced landscapes as a whole in spite of its intrinsic complexity and largeness, and second that it can help efficiently respond to the unexpected changes in the landscape. In the case study, comprehensive site analysis is conducted before developing the framework. In particular, wetlands and grasslands have been identified as potential wildlife habitat which critically determines the vegetation patterns of the green area. Accordingly, the lists of plant communities are presented along with the planting scheme for their shape, layout, and relations. The model of the plant community is developed responding to the structure of surrounding natural landscape. However, it is not designed to evolve to a specific plant community, but is rather a conceptual model of ecological potentials. Therefore, the application of the model has great flexibility by using other plant communities as an alternative as long as the characteristics of the communities are appropriate to the physical conditions. Even though this research provides valuable implications for landscape planning and design in the similar circumstances, there are several limitations to be overcome in the further research. First, there needs to be more sufficient field surveys on the wildlife habitats, which would help generate a more concrete planting model. Second, a landscape management plan should be included considering the condition of existing forest, in particular the afforested landscapes. Last, there is a lack of quantitative data for the models of some plant communities.

• Journal of The Korean Association For Science Education
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• v.40 no.6
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• pp.657-670
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• 2020

The knowledge-information-processing competency is the most essential competency in a knowledge-information-based society and is the most fundamental competency in the new problem-solving ability. Data-driven science inquiry, which emphasizes how to find and solve problems using vast amounts of data and information, is a way to cultivate the problem-solving ability in a knowledge-information-based society. Therefore, this study aims to develop a teaching-learning model and strategy for data-driven science inquiry and to verify the validity of the model in terms of knowledge information processing competency. This study is developmental research. Based on literature, the initial model and strategy were developed, and the final model and teaching strategy were completed by securing external validity through on-site application and internal validity through expert advice. The development principle of the inquiry model is the literature study on science inquiry, data science, and a statistical problem-solving model based on resource-based learning theory, which is known to be effective for the knowledge-information-processing competency and critical thinking. This model is titled "Exploratory Scientific Data Analysis" The model consisted of selecting tools, collecting and analyzing data, finding problems and exploring problems. The teaching strategy is composed of seven principles necessary for each stage of the model, and is divided into instructional strategies and guidelines for environment composition. The development of the ESDA inquiry model and teaching strategy is not easy to generalize to the whole school level because the sample was not large, and research was qualitative. While this study has a limitation that a quantitative study over large number of students could not be carried out, it has significance that practical model and strategy was developed by approaching the knowledge-information-processing competency with respect of science inquiry.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.3
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• pp.247-262
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• 2022

In domestic tunnels, it is mandatory to install CCTVs in tunnels longer than 200 m which are also recommended by installation of a CCTV-based automatic accident detection system. In general, the CCTVs in the tunnel are installed at a low height as well as near by the moving vehicles due to the spatial limitation of tunnel structure, so a severe perspective effect takes place in the distance of installed CCTV and moving vehicles. Because of this effect, conventional CCTV-based accident detection systems in tunnel are known in general to be very hard to achieve the performance in detection of unexpected accidents such as stop or reversely moving vehicles, person on the road and fires, especially far from 100 m. Therefore, in this study, the region of interest is set up and a new concept of inverse perspective transformation technique is introduced. Since moving vehicles in the transformed image is enlarged proportionally to the distance from CCTV, it is possible to achieve consistency in object detection and identification of actual speed of moving vehicles in distance. To show this aspect, two datasets in the same conditions are composed with the original and the transformed images of CCTV in tunnel, respectively. A comparison of variation of appearance speed and size of moving vehicles in distance are made. Then, the performances of the object detection in distance are compared with respect to the both trained deep-learning models. As a result, the model case with the transformed images are able to achieve consistent performance in object and accident detections in distance even by 200 m.

• Journal of Korea Water Resources Association
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• v.55 no.11
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• pp.931-939
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• 2022

In Korea, about two-thirds of the precipitation is concentrated in the summer season, so the problem of turbidity in the summer flood season varies from year to year. Concentrated rainfall due to abnormal rainfall and extreme weather is on the rise. The inflow of turbidity caused a sudden increase in turbidity in the water, causing a problem of turbidity in the dam reservoir. In particular, in Korea, where rivers and dam reservoirs are used for most of the annual average water consumption, if turbidity problems are prolonged, social and environmental problems such as agriculture, industry, and aquatic ecosystems in downstream areas will occur. In order to cope with such turbidity prediction, research on turbidity modeling is being actively conducted. Flow rate, water temperature, and SS data are required to model turbid water. To this end, the national measurement network measures turbidity by measuring SS in rivers and dam reservoirs, but there is a limitation in that the data resolution is low due to insufficient facilities. However, there is an unmeasured period depending on each dam and weather conditions. As a sensor for measuring turbidity, there are Optical Backscatter Sensor (OBS) and YSI, and a sensor for measuring SS uses equipment such as Laser In-Situ Scattering and Transmissometry (LISST). However, in the case of such a high-tech sensor, there is a limit due to the stability of the equipment. Therefore, there is an unmeasured period through analysis based on the acquired flow rate, water temperature, SS, and turbidity data, so it is necessary to develop a relational expression to calculate the SS used for the input data. In this study, the AEM3D model used in the Water Resources Corporation SURIAN system was used to improve the accuracy of prediction of turbidity through the turbidity-SS relationship developed based on the measurement data near the dam outlet.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.40 no.1
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• pp.98-102
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• 1995

Popped popcorn generally have a regular popping direction and typical shape. But the reason and mechanism are not clear yet. This experiment was carried out to investigate the shape moulding factor of popped popcorn. Pericarp thickness of tip-cap section of kernels is slightly thicker than that of top section and this fact provides the important information to the reason. Popping starts when the moisture pressure of heated popcorn is increased and reaches at the critical pressure. Therefore, in the same moisture pressure conditions, top sections are bursted first because their pericarp section is thinner than that of tip-cap section. At the very moment tip-cap sections pull down the top sections of peri carp as bi-metal does. So kernels which removed tip-cap section showed the irregular popping shape because they lost the tip-cap pericarp function. How-ever, kernels which removed embryo showed the typical popping shape but their popping volume was small due to emition and shortage of critical moisture pressure. But kernels which removed the whole pericarp and top pericarp were not popped at all because moisture was entirely emitting out of kernels. These results suggest that the shape moulding factor of popped popcorn is the pericarp thickness differences between the top and tip-cap section of kernels.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.24 no.3
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• pp.21-25
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• 1979

To evaluate the possibility of hardening of rice seedlings to chilling injury by low temperature conditioning for improvement of nursery temperature management a chilling sensitive new variety Tongil from Indica \times Japonica cross and a chilling tolerant Japonica variety Jinheung were reared by the 3rd leaf-stage in a day $30^{\circ}C/night\; 20^{\circ}C$ growth chamber, and were subjected to temperature conditioning for hardening against chilling injury for 6 days. Then the seedlings conditioned and unconditioned were chilled in a day and night $8^{\circ}C$ chamber for 2, 4, 6, or 8 days long and returned to the day and night $30^{\circ}C/night\; 20^{\circ}C$ condition for development of chilling injuries. Survival rate after chilling injury development of the variety Tongil showed distinct effect of hardening, i. e. the unhardened-25 % survival, the hardened by a gradual drop of temperature regime $(30^{\circ}C/20^{\circ}C\rightarrow24^{\circ}C/14^{\circ}C\rightarrow18^{\circ}C/12^{\circ}C\rightarrow8^{\circ}C)4 -59% survival and the hardened. by repeated brief exposure (4hrs. to 6hrs.) to $8^{\circ}C$ shock-89% survival against chilling of $8^{\circ}C$ for 4 days long. The variety Jinheung survived even against 8 days chilling at $8^{\circ}C$ C, but the discoloration rate of leaves due to chilling showed noticeably the hardening effect as repeated shock was much better than the gradually lowering temperatures.

• The Journal of Korean Philosophical History
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• no.27
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• pp.223-254
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• 2009

This thesis is aimed at researching the formation of democracy in socialist China. Due to a sense of cultural superiority on the basis of their developed civilization, they already formed a strong cultural nationalism, which has come to firm up into "Sinocentrism" through long periods of time. However, there arose a sense of crisis due to the Western invasion after the Opium War and the intellectuals in China happened to seek the solution to rescuing their mother land from ruin; in the midst of this process, the theory of social evolution of the West was introduced and accepted. The acceptance of this theory of social evolution gradually transformed in confrontation with a logical limit that China defeated in international competition could not but be plundered by imperialism after all, but it contributed to Chinese intellectuals' forming the concept of the modern state nationalism of the West deviating from cultural Sinocentrism. After the Russian Revolution, a large number of Chinese progressive intellectuals developed their socialist movement with the recognition that Marxism was a practicable alternative to rescue China from its crisis. The Chinese Communist Party was under guidance of the Comintern from the early process of its formation, in which they emphasized the fact the national liberation struggle in colonialized countries was an indispensable element in the world communist movement under the condition of the control of the world by imperialist capital at that time and subsequently, Marxism characterized by resistant nationalism in China gained its cause. Afterwards, the People's Republic of China was established by the Chinese Communists which came to get widespread support from the Chinese through anti-imperialism &feudalism in the process of the Sino-Japanese War, and thus China equipped with a full-blown socialism system set sails. However, with the relations with the Soviet Union getting worse under the international conditions of a cold war, the development of the Chinese socialism couldn't but resort to the concentrated power of its people, which was linked to the boost of continuous patriotism of the Chinese Communists. Particularly, due to the newly-emerging contradictions after reform & opening [gig kifng], China underwent disruption; thus, as an ideology to integrate such disruptive elements, Sinocentrism based on China's cultural pride re-appeared. Recently, a very strong form of Sinocentrism has come to the fore as their superiority of traditional cultures is emphasized in China whose international position as an economic power has been raised.

• Journal of Korea Water Resources Association
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• v.56 no.3
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• pp.195-210
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• 2023

Additional deposition and erosion in large rivers in South Korea have continued to occur toward morphological stabilization after massive dredging through the four major river restoration project, subsequently requiring precise bathymetry monitoring. Hyperspectral bathymetry method has increasingly been highlighted as an alternative way to estimate bathymetry with high spatial resolution in shallow depth for replacing classical intrusive direct measurement techniques. This study introduced the conventional Optimal Band Ratio Analysis (OBRA) of hyperspectral bathymetry method, and evaluated the performance in a domestic large river in normal turbid and flow condition. Maximum measurable depth was estimated by applying correlation coefficient and root mean square error (RMSE) produced during OBRA with cascadedly applying cut-off depth, where the consequent hyperspectral bathymetry map excluded the region over the derived maximum measurable depth. Also non-linearity was considered in building relation between optimal band and depth. We applied the method to the Nakdong and Hwang River confluence as a large river case and obtained the following features. First, the hyperspectal method showed acceptable performance in morphological mapping for shallow regions, where the maximum measurable depth was 2.5 m and 1.25 m in the Nakdong and Hwang river, respectively. Second, RMSE was more feasible to derive the maximum measurable depth rather than the conventional correlation coefficient whereby considering various scenario of excluding range of in situ depths for OBRA. Third, highly turbid region in Hwang River did not allow hyperspectral bathymetry mapping compared with the case of adjacent Nakdong River, where maximum measurable depth was down to half in Hwang River.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.6-7
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• 2021

Vegetation development in rivers is one of the important issues not only in academic fields such as geomorphology, ecology, hydraulics, etc., but also in river management practices. The problem of river vegetation is directly connected to the harmony of conflicting values of flood management and ecosystem conservation. In Korea, since the 2000s, the issue of river vegetation and land formation has been continuously raised under various conditions, such as the regulating rivers downstream of the dams, the small eutrophicated tributary rivers, and the floodplain sites for the four major river projects. In this background, this study proposes a method for classifying the distribution of vegetation in rivers based on remote sensing data, and presents the results of applying this to the Naeseong Stream. The Naeseong Stream is a representative example of the river landscape that has changed due to vegetation development from 2014 to the latest. The remote sensing data used in the study are images of Sentinel 1 and 2 satellites, which is operated by the European Aerospace Administration (ESA), and provided by Google Earth Engine. For the ground truth, manually classified dataset on the surface of the Naeseong Stream in 2016 were used, where the area is divided into eight types including water, sand and herbaceous and woody vegetation. The classification method used a random forest classification technique, one of the machine learning algorithms. 1,000 samples were extracted from 10 pre-selected polygon regions, each half of them were used as training and verification data. The accuracy based on the verification data was found to be 82~85%. The model established through training was also applied to images from 2016 to 2020, and the process of changes in vegetation zones according to the year was presented. The technical limitations and improvement measures of this paper were considered. By providing quantitative information of the vegetation distribution, this technique is expected to be useful in practical management of vegetation such as thinning and rejuvenation of river vegetation as well as technical fields such as flood level calculation and flow-vegetation coupled modeling in rivers.

• Korean Journal of Remote Sensing
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• v.39 no.2
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• pp.207-221
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• 2023

This study suggests deep neural network models for estimating air temperature with Level 1B (L1B) datasets of GEO-KOMPSAT-2A (GK-2A). The temperature at 1.5 m above the ground impact not only daily life but also weather warnings such as cold and heat waves. There are many studies to assume the air temperature from the land surface temperature (LST) retrieved from satellites because the air temperature has a strong relationship with the LST. However, an algorithm of the LST, Level 2 output of GK-2A, works only clear sky pixels. To overcome the cloud effects, we apply a deep neural network (DNN) model to assume the air temperature with L1B calibrated for radiometric and geometrics from raw satellite data and compare the model with a linear regression model between LST and air temperature. The root mean square errors (RMSE) of the air temperature for model outputs are used to evaluate the model. The number of 95 in-situ air temperature data was 2,496,634 and the ratio of datasets paired with LST and L1B show 42.1% and 98.4%. The training years are 2020 and 2021 and 2022 is used to validate. The DNN model is designed with an input layer taking 16 channels and four hidden fully connected layers to assume an air temperature. As a result of the model using 16 bands of L1B, the DNN with RMSE 2.22℃ showed great performance than the baseline model with RMSE 3.55℃ on clear sky conditions and the total RMSE including overcast samples was 3.33℃. It is suggested that the DNN is able to overcome cloud effects. However, it showed different characteristics in seasonal and hourly analysis and needed to append solar information as inputs to make a general DNN model because the summer and winter seasons showed a low coefficient of determinations with high standard deviations.