• Korean Institute of Interior Design Journal
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• v.15 no.6 s.59
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• pp.205-212
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• 2006

The premise of this study is that an ultimate objective in planning an exhibition space is spectators' experiences shaped by a result of their first-hand experiences and responses within an exhibition space, and this result can be recognized in the spectators' movement. Thus, the sign system that can directly affects viewers' main line of flow and movement patterns was examined vis--vis a mutually complementary relation in a triangular composition with the structure of exhibition space and the exhibition contents. Based on the findings, predictive values before and after a complementary application of the sign system to the structure of exhibition space was analyzed and its validity was assessed. The results of this research analysis were drawn as follows. It was shown that an understanding of the locations of direction signs and the degree of recognition can function as an important factor to predict viewers' movement, along with an understanding of topological characteristics of an exhibition space. In terms of the connection and disconnection of space units that form the space structure, it suggests that the distribution of signs and the degree of recognition can adjust the degree of connection and disconnection. Even though exhibition spaces for research subjects were selected from a relatively large number of museums, but the research was limited with a focus on the structure of exhibition space and sign systems. Thus, it is proposed that future studies should be conducted by including varieties of exhibition and environmental factors.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.111-123
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• 2013

Semantic similarity/relatedness measure between two concepts plays an important role in research on system integration and database integration. Moreover, current research on keyword recommendation or tag clustering strongly depends on this kind of semantic measure. For this reason, many researchers in various fields including computer science and computational linguistics have tried to improve methods to calculating semantic similarity/relatedness measure. This study of similarity between concepts is meant to discover how a computational process can model the action of a human to determine the relationship between two concepts. Most research on calculating semantic similarity usually uses ready-made reference knowledge such as semantic network and dictionary to measure concept similarity. The topological method is used to calculated relatedness or similarity between concepts based on various forms of a semantic network including a hierarchical taxonomy. This approach assumes that the semantic network reflects the human knowledge well. The nodes in a network represent concepts, and way to measure the conceptual similarity between two nodes are also regarded as ways to determine the conceptual similarity of two words(i.e,. two nodes in a network). Topological method can be categorized as node-based or edge-based, which are also called the information content approach and the conceptual distance approach, respectively. The node-based approach is used to calculate similarity between concepts based on how much information the two concepts share in terms of a semantic network or taxonomy while edge-based approach estimates the distance between the nodes that correspond to the concepts being compared. Both of two approaches have assumed that the semantic network is static. That means topological approach has not considered the change of semantic relation between concepts in semantic network. However, as information communication technologies make advantage in sharing knowledge among people, semantic relation between concepts in semantic network may change. To explain the change in semantic relation, we adopt the cognitive semantics. The basic assumption of cognitive semantics is that humans judge the semantic relation based on their cognition and understanding of concepts. This cognition and understanding is called 'World Knowledge.' World knowledge can be categorized as personal knowledge and cultural knowledge. Personal knowledge means the knowledge from personal experience. Everyone can have different Personal Knowledge of same concept. Cultural Knowledge is the knowledge shared by people who are living in the same culture or using the same language. People in the same culture have common understanding of specific concepts. Cultural knowledge can be the starting point of discussion about the change of semantic relation. If the culture shared by people changes for some reasons, the human's cultural knowledge may also change. Today's society and culture are changing at a past face, and the change of cultural knowledge is not negligible issues in the research on semantic relationship between concepts. In this paper, we propose the future directions of research on semantic similarity. In other words, we discuss that how the research on semantic similarity can reflect the change of semantic relation caused by the change of cultural knowledge. We suggest three direction of future research on semantic similarity. First, the research should include the versioning and update methodology for semantic network. Second, semantic network which is dynamically generated can be used for the calculation of semantic similarity between concepts. If the researcher can develop the methodology to extract the semantic network from given knowledge base in real time, this approach can solve many problems related to the change of semantic relation. Third, the statistical approach based on corpus analysis can be an alternative for the method using semantic network. We believe that these proposed research direction can be the milestone of the research on semantic relation.

• Korean Journal of Environmental Agriculture
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• v.38 no.4
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• pp.219-224
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• 2019

BACKGROUND: Soil bacteria play important roles in organic matter decomposition and nutrient cycling during the non-growing season. The purpose of this study was to investigate the effects of soil management and chemical properties on the utilization of carbon sources by soil bacteria in paddy fields. METHODS AND RESULTS: The Biolog EcoPlate was used for analyzing community-level carbon substrate utilization profiles of soil bacteria. Soils were collected from the following three types of areas: plain, interface and mountain areas, which were tested to investigate the topology effect. The results of canonical correspondence analysis and Kendall rank correlation analysis showed that soil C/N ratio and NH₄⁺ influenced utilization of carbon sources by bacteria. The utilization of carbohydrates and complex carbon sources were positively correlated with NH₄⁺ concentration. Cultivated paddy fields were compared with adjacent abandoned fields to investigate the impact of cultivation cessation. The level of utilization of putrescine was lower in abandoned fields than in cultivated fields. Monoculture fields were compared with double cropping fields cultivated with barley to investigate the impact of winter crop cultivation. Cropping system altered bacterial use of carbon sources, as reflected by the enhanced utilization of 2-hydroxy benzoic acid under monoculture conditions. CONCLUSION: These results show that soil use intensity and topological characteristics have a minimal impact on soil bacterial functioning in relation to carbon substrate utilization. Moreover, soil chemical properties were found to be important factors determining the physiological profile of the soil bacterial community in paddy fields.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.3
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• pp.56-63
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• 1999

In power system, substation facilities have become too complex and large according to extended power system. Also, some facilities becorre old and often break down unexpectedly. In order to improve the sectrity of transformer out of substation facilities, the development of diagnosis technique to transformer is very needed. In this paper, we developed a method to be analysis the origin and degree of aging by KSOM based on the dissolved gases in power transfonrer. KSOM can do topological mapping for the multi-dimensional pattern based on the dissolved gases to two dimensional plane. And potential possibility and degree of aging for nonna1 transfonrer are presented using the proposed quantitative criterion. Furtherrrore, the aging process of transfonrer is analyzed based on the proposed criterion to special transfonrer. To demonstrate the validity of peoposed method, case study is performed and its results are presented.sented.

• Journal of Microbiology and Biotechnology
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• v.25 no.10
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• pp.1670-1679
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• 2015

Two hollow fiber membrane biofilm reactors (HF-MBfRs) were operated for autotrophic nitrification and hydrogenotrophic denitrification for over 300 days. Oxygen and hydrogen were supplied through the hollow fiber membrane for nitrification and denitrification, respectively. During the period, the nitrogen was removed with the efficiency of 82-97% for ammonium and 87-97% for nitrate and with the nitrogen removal load of 0.09-0.26 kg NH₄⁺-N/m³/d and 0.10-0.21 kg NO₃^--N/m³/d, depending on hydraulic retention time variation by the two HF-MBfRs for autotrophic nitrification and hydrogenotrophic denitrification, respectively. Biofilms were collected from diverse topological positions in the reactors, each at different nitrogen loading rates, and the microbial communities were analyzed with partial 16S rRNA gene sequences in denaturing gradient gel electrophoresis (DGGE). Detected DGGE band sequences in the reactors were correlated with nitrification or denitrification. The profile of the DGGE bands depended on the NH₄⁺ or NO₃^- loading rate, but it was hard to find a major strain affecting the nitrogen removal efficiency. Nitrospira-related phylum was detected in all biofilm samples from the nitrification reactors. Paracoccus sp. and Aquaspirillum sp., which are an autohydrogenotrophic bacterium and an oligotrophic denitrifier, respectively, were observed in the denitrification reactors. The distribution of microbial communities was relatively stable at different nitrogen loading rates, and DGGE analysis based on 16S rRNA (341f /534r) could successfully detect nitrate-oxidizing and hydrogen-oxidizing bacteria but not ammonium-oxidizing bacteria in the HF-MBfRs.

• Journal of Intelligence and Information Systems
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• v.4 no.1
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• pp.133-147
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• 1998

Recently, many researchers have been involved in finding deterministic equations which can accurately predict future event, based on chaotic theory, or fractal theory. The theory says that some events which seem very random but internally deterministic can be accurately predicted by fractal equations. In contrast to the conventional methods, such as AR model, MA, model, or ARIMA model, the fractal equation attempts to discover a deterministic order inherent in time series data set. In discovering deterministic order, researchers have found that neural networks are much more effective than the conventional statistical models. Even though prediction accuracy of the network can be different depending on the topological structure and modification of the algorithms, many researchers asserted that the neural network systems outperforms other systems, because of non-linear behaviour of the network models, mechanisms of massive parallel processing, generalization capability based on adaptive learning. However, recent survey shows that prediction accuracy of the forecasting models can be determined by the model structure and data structures. In the experiments based on actual economic data sets, it was found that the prediction accuracy of the neural network model is similar to the performance level of the conventional forecasting model. Especially, for the data set which is deterministically chaotic, the AR model, a conventional statistical model, was not significantly different from the MLP model, a neural network model. This result shows that the forecasting model. This result shows that the forecasting model a, pp.opriate to a prediction task should be selected based on characteristics of the time series data set. Analysis of the characteristics of the data set was performed by fractal analysis, measurement of Hurst index, and measurement of Lyapunov exponents. As a conclusion, a significant difference was not found in forecasting future events for the time series data which is deterministically chaotic, between a conventional forecasting model and a typical neural network model.

• International Journal of CAD/CAM
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• v.7 no.1
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• pp.71-80
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• 2007

Recently, feature-based solid modeling systems have been widely used in product design. However, for engineering analysis of a product model, an ed CAD model composed of mid-surfaces is desirable for conditions in which the ed model does not affect analysis result seriously. To meet this requirement, a variety of solid ion methods such as MAT (medial axis transformation) have been proposed to provide an ed CAE model from a solid design model. The algorithm of the MAT approach can be applied to any complicated solid model. However, additional work to trim and extend some parts of the result is required to obtain a practically useful CAE model because the inscribed sphere used in the MAT method generates insufficient surfaces with branches. On the other hand, the mid-surface ion approach supports a practical method for generating a two-dimensional ed model, even though it has difficulties in creating a mid-surface from some complicated parts. In this paper, we propose a dimension reduction approach on solid models based on the midsurface abstraction approach. This approach simplifies the solid model by abbreviating or removing trivial features first such as the fillet, mounting, or protrusion. The geometry of each face is replaced with mid-patches from the simplified model, and then unnecessary topological entities are deleted to generate a clean ed model. Also, additional work, such as extending and stitching mid-patches, completes the generation of a mid-surface model from the patches.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.5
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• pp.479-493
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• 2016

LiDAR(Light Detection and Ranging) data acquired from ALS(Airborne Laser Scanner) has been intensively utilized to reconstruct object models. Especially, researches for 3D modeling from LiDAR data have been performed to establish high quality spatial information such as precise 3D city models and true orthoimages efficiently. To reconstruct object models from irregularly distributed LiDAR point clouds, sensor calibration, noise removal, filtering to separate objects from ground surfaces are required as pre-processing. Classification and segmentation based on geometric homogeneity of the features, grouping and representation of the segmented surfaces, topological analysis of the surface patches for modeling, and accuracy assessment are accompanied by modeling procedure. While many modeling methods are based on the segmentation process, this paper proposed to extract key points directly for building modeling without segmentation. The method was applied to simulated and real data sets with various roof shapes. The results demonstrate feasibility of the proposed method through the accuracy analysis.

• Journal of Wetlands Research
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• v.15 no.3
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• pp.397-406
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• 2013

Wetland conservation plan has been established to protect ecologically important wetlands based on vegetation integrity, spatial distribution of endangered species, but recently more demands are concentrated on the landscape ecological approaches such as topological relationship, neighboring area, spatial arrangements between wetlands at the broad scale. Landscape ecological analysis and graph theory are conducted to identify spatial characteristics related to core nodes and weak links of wetland networks in Nakdong basin. Regular planar model, which is selected for wetland networks, is applied in the Nakdong basin. The analysis indicates that 5 regional groups and 4 core wetlands are extracted with 15km threshold distance. The IIC and PC values based on the binary and probability models suggest that the wetland group C composed of main stream of Nakdong river and Geumho river is the most important area for wetland network. Wetland conservation plan, restoration projected of damaged and weak links between wetlands should be proposed through evaluating the node, links, and networks from wetlands at the local to the regional scale in Nakdong basin.

• Journal of the Korean GEO-environmental Society
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• v.20 no.2
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• pp.5-18
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• 2019

In this study, it was conducted a broad-area landslide analysis for the entire area of Kyungsangbuk-do Province based on spatially-distributed wetness index and root reinforcement infinity slope stability theory. Specifically, digital map, soil map and forest map were used to extract topological and geological parameters, and to build spatially-distributed database at $10m{\times}10m$ resolution. Infinity flow direction method was used for rain catchment area to produce spatially-distributed wetness index. The safety level that indicates risk of a broad-area landslide was classified into four groups. The result showed that areas with a high estimated risk of a landslide coincided with areas that recently went through an actual landslide, including Bonghwa and Gimcheon, and unstable areas were clustered around mountainous areas. A comparison between the estimation result and the records of actual landslide showed that the analysis model is effective for estimating a risk of a broad-area landslide based on accumulation of reasonable parameters.