• Journal of Korea Water Resources Association
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• v.40 no.12
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• pp.985-994
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• 2007

Small hydropower is the one of the cleanest one among new and renewable energy with less green house gas emissions. Recently, the necessity of developing small hydropower is emerging since its remaining potential resources in this country are abundant. However, a survey or research on the small hydropower development has been hardly performed since the 1990#s. These circumstances encourages a systematic approach for the small hydropower development. The purpose of this study is to propose a methodology of the location analysis for developing small hydropower. To this end, constraint and location criteria with weights are established and quantification method of each factor is presented. Especially, the analysis procedure is established on the basis of GSIS. Also the study focus on raising the objectivity and precision of analysis by developing system model with automatic search. The proposed methodology is applied to Bochung stream in Keum Riverbasin. The result selects the four and two locations of dam type and run-of-river type respectively. This study will be beneficial to the future activation of small hydropower development as a fundamental work.

• Informatization Policy
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• v.23 no.2
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• pp.73-97
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• 2016

Social changes due to ICT like Big Data, IoT, Cloud and Mobile is progressing rapidly. Now, we get out of the old-fashioned frame was measured at the level of the information society through the introduction of PC, Internet speed and Internet subscribers etc and there is a need for a new type of diagnostic information society framework. This study is the study for the framework established to diagnose and measure post-information society. The framework and indicators were chosen in accordance with the technological society coevolution theory and information society-related indicators presented from authoritative international organizations. Empirical results utilizing the indicators and framework developed in this study were as follows: First, the three sectors, six clusters (items), 25 nodes (indicators) that make up the information society showed that all strongly connected. Second, it was diagnosed as information society development (50.34%), technology-based expansion (25.03%) and ICT effect (24.63%) through a network analysis (ANP) for the measurement of importance of the information society. Third, the result of calculating the relative importance of the cluster and nodes showed us (1)social development potential (26.04%), (2)competitiveness (15.9%), (3)ICT literacy (15.5%) (4) (social)capital (24.3 %), (5)ICT acceptance(9.54%), (6)quality of life(8.7%). Consequently, We should take into account the effect of the economy and quality of life beyond ICT infrastructure-centric when we measure the post-information society. By applying the weighting we should performs a comparison between countries and we should diagnose the level of Korea and provide policy implications for the preparation of post-information society.

• Journal of KIISE:Software and Applications
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• v.27 no.7
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• pp.769-783
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• 2000

In this paper, in order to disambiguate Korean noun word sense, we define a local context and explain how to extract it from a raw corpus. Following the intuition that two different nouns are likely to have similar meanings if they occur in the same local context, we use, as a clue, the word that occurs in the same local context where the target noun occurs. This method increases the usability of extracted knowledge and makes it possible to disambiguate the sense of infrequent words. And we can overcome the data sparseness problem by extending the verbs in a local context. The sense of a target noun is decided by the maximum similarity to the clues learned previously. The similarity between two words is computed by their concept distance in the sense hierarchy borrowed from WordNet. By reducing the multiplicity of clues gradually in the process of computing maximum similarity, we can speed up for next time calculation. When a target noun has more than two local contexts, we assign a weight according to the type of each local context to implement the differences according to the strength of semantic restriction of local contexts. As another knowledge source, we get a co-occurrence information from dictionary definitions and example sentences about the target noun. This is used to support local contexts and helps to select the most appropriate sense of the target noun. Through experiments using the proposed method, we discovered that the applicability of local contexts is very high and the co-occurrence information can supplement the local context for the precision. In spite of the high multiplicity of the target nouns used in our experiments, we can achieve higher performance (89.8%) than the supervised methods which use a sense-tagged corpus.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.3
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• pp.190-198
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• 2020

For domestic urban railways, which have a 19.7% aging rate, a performance evaluation is necessary to establish capital improvement investment plans. The performance evaluation, which was recently enacted in the relevant law, points out the excessive time and effort for acquiring data and evaluation. This study developed a performance evaluation simulation prototype using a virtual reality (VR) method to use as training contents for railway performance evaluations. The practical use of the VR technique to reduce the working time under poor environment conditions was confirmed through a literature review. A survey and consultation were conducted for urban railway experts to determine the weight of the performance evaluation items and the facility breakdown structure. This information was utilized to develop performance evaluation sheets for simulation. Based on the evaluation sheet, a training content prototype that evaluates the performance of platform safety doors was developed using VR techniques with HTC VIVE equipment. VR simulation tests were conducted for six players, and the prototype was sufficiently advantageous for a visual confirmation of the facility information. The result is expected to be useful for engineers to understand the performance evaluation process efficiently before an actual performance evaluation of urban railway facilities.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.1
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• pp.56-63
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• 2016

In this study, we introduce a design of Fuzzy RBFNNs-based digit recognition system using the incremental-PCA in order to recognize the handwritten digits. The Principal Component Analysis (PCA) is a widely-adopted dimensional reduction algorithm, but it needs high computing overhead for feature extraction in case of using high dimensional images or a large amount of training data. To alleviate such problem, the incremental-PCA is proposed for the computationally efficient processing as well as the incremental learning of high dimensional data in the feature extraction stage. The architecture of Fuzzy Radial Basis Function Neural Networks (RBFNN) consists of three functional modules such as condition, conclusion, and inference part. In the condition part, the input space is partitioned with the use of fuzzy clustering realized by means of the Fuzzy C-Means (FCM) algorithm. Also, it is used instead of gaussian function to consider the characteristic of input data. In the conclusion part, connection weights are used as the extended diverse types in polynomial expression such as constant, linear, quadratic and modified quadratic. Experimental results conducted on the benchmarking MNIST handwritten digit database demonstrate the effectiveness and efficiency of the proposed digit recognition system when compared with other studies.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.3
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• pp.989-998
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• 2014

Recently volcanic eruptions and activities occurring in many parts of world have become a common global concern to many countries. The severity of these Volcanic disasters, such as of Mt. Eyjafjallajokull in Iceland and Mt. Merapi in Indonesia, have caused damages and causalities reaching astronomical levels. The infrastructure is categorized into 18sections that appropriately reflecting the survey data collected from various government agents, current inhabitant and engineers to accumulate a database on the priorities and preferences of restoring and reconstructing many kinds of infrastructure and facilities. The survey data was collect by using the "Likert 5 Scale Method" which emphasized the importance and priority of reconstruction and restoration for the specific facilities and infrastructures. The data was corrugated, organized and used in plotting and planning a strategic recovery agenda. The survey results were analyzed and verified to ensure the validity and reliability of the data by using chi-square test. This paper presents that recovery period and recovery cost to the total damage of infrastructure and facilities were used to make a recovery network with implemented construction management method. The research is expected that a more efficient and prompt recovery protocol and recovery plan can be executed and can be use as a reference and database.

• Korean Journal of Remote Sensing
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• v.33 no.5_3
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• pp.879-888
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• 2017

This study is a preliminary research conducted in Buhansan mountain National Park to develop a management system to predict and control oak wilt disease by indicating spatial factors which affect diffusion of the disease. After analysing altitude factor during the estimation of spatial analysis of damaged area, it is indicated that damaged trees are mainly distributed at altitude of 200-500 m and number decreased drastically over the altitude of 500 m. The result showed that 92% of total damaged trees are on slope between 20~40 degrees and the number decreased drastically on slope steeper than 40 degrees. It is indicated that damaged area is mainly distributed on southern aspect. It is estimated by using CART that slope factor affected the diffusion of disease mostly but aspect factor did not. Surface temperature and altitude showed similar effect.By simulating possible diffusion scenario, it is estimated that the disease could spread to DO-BONG Mt., northeast of Bukhansan mountain.

• Journal of Korea Water Resources Association
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• v.37 no.3
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• pp.195-206
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• 2004

One of the main factors which reduces the efficiency of a sewage treatment plant is the Inflow/Infiltration(Ⅰ/Ⅰ) in the sewer First we must calculate the quantity of Ⅰ/Ⅰ via the investigation of each sewer to establish the reduction plan of Ⅰ/Ⅰ. However, in Korea, we apply the results of a surveyed sample to the entire study area to establish the reduction plan of Ⅰ/Ⅰ. This methodology just considers the total Ⅰ/Ⅰ for the entire study area but it does not consider the quantity of Ⅰ/Ⅰ for the individual sewer systems. Therefore, we may need the model to consider the Ⅰ/Ⅰ in the individual sewer systems and we develop the model to calculate the Ⅰ/Ⅰ that happen in urban sewer systems. We estimate the Ⅰ/Ⅰ of individual systems by the developed model and the estimated Ⅰ/Ⅰ are utilized as the basic data for the establishment of Ⅰ/Ⅰ reduction plan. The observed Ⅰ/Ⅰ for the entire study area is distributed into the individual sewer systems according to their defect states. Here, the weights of defect elements are calculated using AHP(Analytic Hierarchy Process) and we perform the uncertainty analysis for considering the errors using MCS(Monte Carlo Simulation).

• Journal of KIISE:Computing Practices and Letters
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• v.10 no.2
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• pp.174-188
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• 2004

In the life environment changed with not only the quality and the price of the products but also the material abundance, it is the most crucial factor for the strategy of product sales to investigate consumer's sensibility and preference degree. In this perspective, it is necessary to design and merchandise the products in cope with each consumer's sensibility and needs as well as its functional aspects. In this paper, we propose the Fashion Design Recommender Agent System (FDRAS-pro) for textile design applying collaborative filtering personalization technique as one of the methods of material development centered on consumer's sensibility and preference. For a collaborative filtering system based on textile, Representative-Attribute Neighborhood is adopted to determine the number or neighbors that will be used for preferences estimation. Pearson's Correlation Coefficient is used to calculate similarity weights among users. We build a database founded on the sensibility adjectives to develop textile designs by extracting the representative sensibility adjectives from users' sensibility and preferences about textile designs. FDRAS-pro recommends textile designs to a customer who has a similar propensity about textile. To investigate the sensibility and emotion according to the effect of design factors, fertile designs were analyzed in terms of 9 design factors, such as, motif source, motif-background ratio, motif variation, motif interpretation, motif arrangement, motif articulation, hue contrast, value contrast, chroma contrast. Finally, we plan to conduct empirical applications to verify the adequacy and the validity of our system.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.2
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• pp.29-33
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• 2010

The purpose of LiDAR ground classification is to archive both goals which are acquiring confident ground points with high precision and describing ground shape in detail. In spite of many studies about developing optimized algorithms to kick out this, it is very difficult to classify ground points and describing ground shape by airborne LiDAR data. Especially it is more difficult in a dense forested area like Korea. Principle misclassification was mainly caused by complex forest canopy hierarchy in Korea and relatively coarse LiDAR points density for ground classification. Unfortunately, a lot of LiDAR surveying performed in summer in South Korea. And by that reason, schematic LiDAR points distribution is very different from those of Europe. So, this study propose enhanced ground classification method considering Korean land cover characteristics. Firstly, this study designate highly confident candidated LiDAR points as a first ground points which is acquired by using big roller classification algorithm. Secondly, this study applied weighted gradient kernel(WGK) algorithm to find and include highly expected ground points from the remained candidate points. This study methods is very useful for reconstruct deformed terrain due to misclassification results by detecting and include important terrain model key points for describing ground shape at site. Especially in the case of deformed bank side of river area, this study showed highly enhanced classification and reconstruction results by using WGK algorithm.