• Geophysics and Geophysical Exploration
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• v.10 no.4
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• pp.252-258
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• 2007

We have studied the feasibility of geostatistics approach to enhancing analysis of sparsely obtained seismic data by combining with satellite gravity data. The shallow depth and numerous fishing nets in The Yellow Sea, west of Korea, makes it difficult to do seismic surveys in this area. Therefore, we have attempted to use geostatistics to integrate the seismic data along with gravity data. To evaluate the feasibility of this approach, we have extracted only a few seismic profile data from previous surveys in the Yellow Sea and performed integrated analysis combining with the results from gravity data under the assumption that seismic velocity and density have a high physical correlation. First, we analyzed the correlation between extracted seismic profiles and depths obtained from gravity inversion. Next, we transferred the gravity depth to travel time using non-linear indicator transform and analyze residual values by kriging with varying local means. Finally, the reconstructed time structure map was compared with the original seismic section given in the previous study. Our geostatistical approach demonstrates relatively satisfactory results and especially, in the boundary area where seismic lines are sparse, gives us more in-depth information than previously available.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.3
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• pp.639-647
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• 2011

In this paper, we introduce a design methodology of data-centroid Radial Basis Function neural networks with extended polynomial function. The two underlying design mechanisms of such networks involve K-means clustering method and Particle Swarm Optimization(PSO). The proposed algorithm is based on K-means clustering method for efficient processing of data and the optimization of model was carried out using PSO. In this paper, as the connection weight of RBF neural networks, we are able to use four types of polynomials such as simplified, linear, quadratic, and modified quadratic. Using K-means clustering, the center values of Gaussian function as activation function are selected. And the PSO-based RBF neural networks results in a structurally optimized structure and comes with a higher level of flexibility than the one encountered in the conventional RBF neural networks. The PSO-based design procedure being applied at each node of RBF neural networks leads to the selection of preferred parameters with specific local characteristics (such as the number of input variables, a specific set of input variables, and the distribution constant value in activation function) available within the RBF neural networks. To evaluate the performance of the proposed data-centroid RBF neural network with extended polynomial function, the model is experimented with using the nonlinear process data(2-Dimensional synthetic data and Mackey-Glass time series process data) and the Machine Learning dataset(NOx emission process data in gas turbine plant, Automobile Miles per Gallon(MPG) data, and Boston housing data). For the characteristic analysis of the given entire dataset with non-linearity as well as the efficient construction and evaluation of the dynamic network model, the partition of the given entire dataset distinguishes between two cases of Division I(training dataset and testing dataset) and Division II(training dataset, validation dataset, and testing dataset). A comparative analysis shows that the proposed RBF neural networks produces model with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• Journal of the Korean Institute of Landscape Architecture
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• v.48 no.4
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• pp.19-28
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• 2020

The Urban Heat Island (UHI) Effect has intensified due to urbanization and heat management at the urban level is treated as an important issue. Green space improvement projects and environmental policies are being implemented as a way to alleviate Urban Heat Islands. Several studies have been conducted to analyze the correlation between urban green areas and heat with linear regression models. However, linear regression models have limitations explaining the correlation between heat and the multitude of variables as heat is a result of a combination of non-linear factors. This study evaluated the Heat Island alleviating effects in Seoul during the summer by using a deep neural network model methodology, which has strengths in areas where it is difficult to analyze data with existing statistical analysis methods due to variable factors and a large amount of data. Wide-area data was acquired using Landsat 8. Seoul was divided into a grid (30m × 30m) and the heat island reduction variables were enter in each grid space to create a data structure that is needed for the construction of a deep neural network using ArcGIS 10.7 and Python3.7 with Keras. This deep neural network was used to analyze the correlation between land surface temperature and the variables. We confirmed that the deep neural network model has high explanatory accuracy. It was found that the cooling effect by NDVI was the greatest, and cooling effects due to the park size and green space proximity were also shown. Previous studies showed that the cooling effects related to park size was 2℃-3℃, and the proximity effect was found to lower the temperature 0.3℃-2.3℃. There is a possibility of overestimation of the results of previous studies. The results of this study can provide objective information for the justification and more effective formation of new urban green areas to alleviate the Urban Heat Island phenomenon in the future.

• Tuberculosis and Respiratory Diseases
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• v.56 no.4
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• pp.393-404
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• 2004

Background : Nucleic acid hybridization has become an essential technique in the development of our understanding of gene structure and function. The quantitative analysis of hybridization has been used in the measurement of genome complexity and gene copy number. The filter hybridization assay is rapid, sensitive and can be used to measure RNAs complementary to any cloned DNA sequence. Methods : The authors assessed the accuracy, linearity, correlation coefficient and specificity of the hybridization depending on the added dose(0, 1, 5, and $10{\mu}g$) of non-specific rat spleen RNA to hybridization of surfactant protein A mRNA. Filter hybridization assays were used to obtain the equation of standard curve and thereby to quantitate the mRNA quantitation. Results : 1. Standard curve equation of filter hybridization assay between counts per minute (X) and spleen RNA input (Y) was Y=0.13X-19.35. Correlation coefficient was 0.98. 2. Standard curve equation of filter hybridization assay between counts per minute (X) and surfactant protein A mRNA transcript input (Y) was Y=0.00066X-0.046. Correlation coefficient was 0.99. 3. Standard curve equation of filter hybridization assay between counts per minute (X) and surfactant protein A mRNA transcript input (Y) after the addition of $1{\mu}g$ spleen RNA was Y=0.00056X-0.051. Correlation coefficient was 0.99. 4. Standard curve equation of filter hybridization assay between counts per minute (X) and surfactant protein A mRNA transcript input (Y) after the addition of $5{\mu}g$ spleen RNA was Y=0.00065X-0.088. Correlation coefficient was 0.99. 5. Standard curve equation of filter hybridization assay between counts per minute (X) and surfactant protein A mRNA transcript input (Y) after the addition of $10{\mu}g$ spleen RNA was Y=0.00051X-0.10. Correlation coefficient was 0.99. Conclusions : Comparison of cpm/filter in a linear range allowed accurate and reproducible estimation of surfactant protein A mRNA copy number irrespective of the addition dosage of non-specific rat spleen RNA over the range $0-10{\mu}g$.

• Journal of the Korean Geosynthetics Society
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• v.14 no.1
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• pp.1-10
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• 2015

Recently, several researches on the development of new economical anchor systems have been performed to support floating structures. This study focused on the group suction piles, which connect mid-sized suction piles instead of a single suction pile with large-diameter. The group suction pile shows the complex bearing behavior with translation and rotation, so it is difficult to apply conventional design methods. Therefore, the numerical modeling technique was developed to evaluate the horizontal bearing capacity of the group suction piles in clay. The technique models suction piles as beam elements and soil reaction as non-linear springs. To analyze the applicability of the modeling, the horizontal load-movement curves of the proposed modeling were compared with those of three-dimensional finite element analyses. The comparison showed that the modeling underestimates the capacity and overestimate the displacement corresponding to the maximum capacity. Therefore, the correction factors for the horizontal soil resistance was proposed to match the bearing capacity from the three-dimensional finite element analyses.

• Journal of Korean Society of Forest Science
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• v.96 no.6
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• pp.625-632
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• 2007

The purpose of this study was to analyze the conceptional structure of residents' perception among tourism development impacts (economic benefits, social and environmental impact), community attachment and attitudes towards the effects of Baekdudaegan tourism development. This paper was adopted LISREL (linear structural relationships) approach, covariance structural equation model, to provided some insights on tourism development. Data of 356 were collected from Youngu and Mungyeong cities surrounding Baekdudaegan in Gyeongsangbuk-do. The results indicate that perceived economic benefits are rather greater impacts on attitudes than perceived social and environmental ones directly and indirectly. Also, perceived social impacts influence community attachment, however, perceived economic benefits and environmental impacts do not influence community attachment directly. Finally results reveal that the attitudes for supporting tourism development were found positively influenced by the identity of community attachment. Differently social exchange theory, the results suggested that residents' attitudes towards Baekdudaegan tourism development perceived positive strongly even a non related tourism resident.

• Archives of design research
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• v.17 no.1
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• pp.211-220
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• 2004

The Chaos theory of complexity and Fractal theory which became a prominent figure as a new paradigm of natural science should be understood not as whole, and not into separate elements of nature. Fractal Dimensions are used to measure the complexity of objects. We now have ways of measuring things that were traditionally meaningless or impossible to measure. They are capable of describing many irregularly shaped objects including man and nature. It is compatible method of application to express complexity of nature in the dimension of non-fixed number by placing our point of view to lean toward non-linear, diverse, endless time, and complexity when we look at our world. Fractal Dimension allows us to measure the complexity of an object. Having a wide application of fractal geometry and Chaos theory to the art field is the territory of imagination where art and science encounter each other and yet there has not been much research in this area. The formative word has been extracted in this study by analyzing objective data to grasp formative principle and geometric characteristic of (this)distinct figures of Fractals. With this form of research, it is not so much about fractal in mathematics, but the concept of self-similarity and recursiveness, randomness, devices expressed from unspeakable space, and the formative similarity to graphic design are focused in this study. The fractal figures have characteristics in which the structure doesn't change the nature of things of the figure even in the process if repeated infinitely many times, the limit of the process produces is fractal. Almost all fractals are at least partially self-similar. This means that a part of the fractal is identical to the entire fractal itself even if there is an enlargement to infinitesimal. This means any part has all the information to recompose as whole. Based on this scene, the research is intended to examine possibility of analysis of fractals in geometric characteristics in plasticity toward forms in graphic design. As a result, a beautiful proportion appears in graphic design with calculation of mathematic. It should be an appropriate equation to express nature since the fractal dimension allows us to measure the complexity of an object and the Fractla geometry should pick out high addition in value of peculiarity and characteristics in the complex of art and science. At the stage where the necessity of accepting this demand and adapting ourselves to the change is gathering strength is very significant in this research.

• Journal of Environmental Impact Assessment
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• v.32 no.6
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• pp.437-449
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• 2023

This study measured PM₁₀ concentrations and wind speeds in buffer green spaces and neighborhood parks located along the road, and compared them with roadside measurementresults to understand the effect of mitigating PM₁₀ concentrations by type of green space and the influence of wind speeds on it. As a result of the analysis, the effect of mitigating PM₁₀ concentration was different depending on the type of roadside green space, and an increase in wind speed had a significant effect on reducing PM₁₀ concentration. In buffer green areas with high planting density, wind speed was low and PM₁₀ stagnated inside, resulting in the highest concentration. On the other hand, green areas in neighborhood parks with relatively low planting density had high wind speeds and the lowest PM₁₀ concentration. The non-green area within the neighborhood park recorded the highest wind speed, which was advantageous for the spread of PM₁₀, but the concentration was higherthan that of the green area. Therefore, in orderto reduce PM₁₀ concentration in roadside green space, it is necessary to create green space with good ventilation, and the combined effect of green space and wind speed seems to be more advantageous in reducing PM₁₀ concentration. Green spaces capture and remove PM inside, contributing to reducing the concentration of PM outside. In order to manage PM in the entire city and on roads, it is necessary to increase planting density and leaf area in roadside green spaces, such as buffer green spaces, so that PM can be removed within the green spaces. However, in green spaces such as neighborhood parks that are actively used by city residents, in orderto minimize damage to users due to PM, it is desirable to create green spaces with a structure that allows PM to spread to the outside rather than stagnate inside.