• Journal of the Korean Society for Precision Engineering
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• v.22 no.12 s.177
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• pp.184-189
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• 2005

An experimental study of the femtosecond laser machining of Si materials was carried out. Direct laser machining of the materials for the feature size of a few micron scale has the advantage of low cost and simple process comparing to the semiconductor process, E-beam lithography, ECM and other machining process. Further, the femtosecond laser is the better tool to machine the micro parts due to its characteristics of minimizing the heat affected zone(HAZ). As a result of line cutting of Si, the optimal condition had the region of the effective energy of 2mJ/mm-2.5mJ/mm with the power of 0.5mW-1.5mW. The polarization effects of the incident beam existed in the machining qualities, therefore the sample motion should be perpendicular to the projection of the electric vector. We also observed the periodic ripple patterns which come out in condition of the pulse overlap with the threshold energy. Finally, we could machined the groove with the linewidth of below $2{\mu}m$ for the application of MEMS device repairing, scribing and arbitrary patterning.

• Journal of the Korean association of regional geographers
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• v.18 no.4
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• pp.473-493
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• 2012

Malaria infection is sensitively influenced by regional meteorological conditions along with global climate change. Remote sensing techniques have become an important tool for extraction of climatic and environmental factors, including rainfall, temperature, surface water, soil moisture, and land use, which are directly linked to the habitat qualities of malaria mosquitoes. Improvement of sensor fidelity with higher spatial and spectral resolution, new multinational sensor development, and decreased data cost have nurtured diverse remote sensing applications in malaria research. In 1984, eradication of endemic malaria was declared in Korea, but reemergence of malaria was reported in mid-1990s. Considering constant changes in malaria cases since 2000, the epidemiological management of the disease needs careful monitoring. Geographically, northmost counties neighboring North Korea have been ranked high in the number of malaria cases. High infection rates in these areas drew special attention and led to a hypothesis that malaria dispersion in these border counties might be caused by north-origin, malaria-bearing adult mosquitoes. Habitat conditions of malaria mosquitoes are important parameters for prediction of the vector abundance. However, it should be realized that malaria infection and transmission is a complex mechanism, where non-environmental factors, including human behavior, demographic structure, landscape structure, and spatial relationships between human residence and the vector habitats, are also significant considerations in the framework of medical geography.

• Tunnel and Underground Space
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• v.15 no.1 s.54
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• pp.28-38
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• 2005

According to the recent development of measurement system utilizing one or a set of boreholes, visualization of the explored underground became to be a major issue. It induced even the introduction of monitoring apparatuses on the borehole wall with multi-function tool, but the usage of these was often limited by where is unfavorable rock condition and a few of engineers can approach. And so, a portable type of borehole camera with only the essential function has been investigated and a few of commercial models about this is recently being applied into the field condition. This paper was based on the monitoring results obtained using a commercial model by Dr. Nakagawa. Discontinuities in rock mass were the topic for the visualization, and it was studied how can visualize their three dimensional distribution and what a numerical formulation is needed and how to understand the visualization result. The numerical formulation was based on the geometric correlation between the dip direction / dip of discontinuous plane and the trend / plunge of borehole, a set of the equation of a plane was induced. As field application of this into two places, it is found that the above visualization methodology will be especially an useful geotechlical tool for analyzing the local distribution of discontinuities.

• Journal of Intelligence and Information Systems
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• v.27 no.4
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• pp.73-95
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• 2021

This study uses Node2vec graph embedding method and Light GBM link prediction to explore undeveloped export candidate countries in Korea's food and beverage industry. Node2vec is the method that improves the limit of the structural equivalence representation of the network, which is known to be relatively weak compared to the existing link prediction method based on the number of common neighbors of the network. Therefore, the method is known to show excellent performance in both community detection and structural equivalence of the network. The vector value obtained by embedding the network in this way operates under the condition of a constant length from an arbitrarily designated starting point node. Therefore, it has the advantage that it is easy to apply the sequence of nodes as an input value to the model for downstream tasks such as Logistic Regression, Support Vector Machine, and Random Forest. Based on these features of the Node2vec graph embedding method, this study applied the above method to the international trade information of the Korean food and beverage industry. Through this, we intend to contribute to creating the effect of extensive margin diversification in Korea in the global value chain relationship of the industry. The optimal predictive model derived from the results of this study recorded a precision of 0.95 and a recall of 0.79, and an F1 score of 0.86, showing excellent performance. This performance was shown to be superior to that of the binary classifier based on Logistic Regression set as the baseline model. In the baseline model, a precision of 0.95 and a recall of 0.73 were recorded, and an F1 score of 0.83 was recorded. In addition, the light GBM-based optimal prediction model derived from this study showed superior performance than the link prediction model of previous studies, which is set as a benchmarking model in this study. The predictive model of the previous study recorded only a recall rate of 0.75, but the proposed model of this study showed better performance which recall rate is 0.79. The difference in the performance of the prediction results between benchmarking model and this study model is due to the model learning strategy. In this study, groups were classified by the trade value scale, and prediction models were trained differently for these groups. Specific methods are (1) a method of randomly masking and learning a model for all trades without setting specific conditions for trade value, (2) arbitrarily masking a part of the trades with an average trade value or higher and using the model method, and (3) a method of arbitrarily masking some of the trades with the top 25% or higher trade value and learning the model. As a result of the experiment, it was confirmed that the performance of the model trained by randomly masking some of the trades with the above-average trade value in this method was the best and appeared stably. It was found that most of the results of potential export candidates for Korea derived through the above model appeared appropriate through additional investigation. Combining the above, this study could suggest the practical utility of the link prediction method applying Node2vec and Light GBM. In addition, useful implications could be derived for weight update strategies that can perform better link prediction while training the model. On the other hand, this study also has policy utility because it is applied to trade transactions that have not been performed much in the research related to link prediction based on graph embedding. The results of this study support a rapid response to changes in the global value chain such as the recent US-China trade conflict or Japan's export regulations, and I think that it has sufficient usefulness as a tool for policy decision-making.