• Geomechanics and Engineering
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• v.32 no.4
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• pp.375-385
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• 2023

There are many joint fissures distributed in the engineering rock mass. In the process of geological history, the underground rock mass undergoes strong geological processes, and undergoes complex geological processes such as fracture breeding, expansion, recementation, and re-expansion. In this paper, the damage-stick-slip process (DSSP), an analysis model used for rock mass failure slip, was established to examine the master control and time-dependent mechanical properties of the new and primary fractures of a multi-fractured rock mass under the action of stress loading. The experimental system for the recemented multi-fractured rock mass was developed to validate the above theory. First, a rock mass failure test was conducted. Then, the failure stress state was kept constant, and the fractured rock mass was grouted and cemented. A secondary loading was applied until the grouted mass reached the intended strength to investigate the bearing capacity of the recemented multi-fractured rock mass, and an acoustic emission (AE) system was used to monitor AE events and the update of damage energy. The results show that the initial fracture angle and direction had a significant effect on the re-failure process of the cement rock mass; Compared with the monitoring results of the acoustic emission (AE) measurements, the master control surface, key blocks and other control factors in the multi-fractured rock mass were obtained; The triangular shaped block in rock mass plays an important role in the stress and displacement change of multi-fracture rock mass and the long fissure and the fractures with close fracture tip are easier to activate, and the position where the longer fractures intersect with the smaller fractures is easier to generate new fractures. The results are of great significance to a multi-block structure, which affects the safety of underground coal mining.

• Korean Journal of Heritage: History & Science
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• v.57 no.1
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• pp.6-19
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• 2024

The Korean Archaeological Dictionary, which represents Korean archaeological knowledge information, contains refined and high-quality information written by expert collective intelligence. This is a characteristic that clearly distinguishes it from overseas archaeological data archives, and can be called differentiated infrastructure data. However, it has not played a role as an information service or knowledge information platform reflecting the latest digital technology. As a way to maximize these strengths and compensate for weaknesses, it was proposed to develop and operate a GIS-based knowledge and information platform for Korean archaeology. To realize this, it is necessary to develop a title management system centered on repositories and metadata that can collect and store various information, link open linked data design and related systems, develop a search function that can analyze and visualize data in response to the big data era, and establish a WebGIS-based information service system. This will be a platform to continuously manage, supplement, and update Korean archaeological knowledge information, build a ubiquitous environment where anyone can use information anytime, anywhere, and create various types of business models.

• Economic and Environmental Geology
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• v.48 no.1
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• pp.51-63
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• 2015

I produced a secular variation model of geomagnetic field by using the magnetic component data from four geomagnetic observatories located in Northeast Asia during the years between 1997 and 2011. The Earth's magnetic field varies with time and location due to the dynamics of fluid outer core and the magnetic observatories on the surface measure in time series. To adequately represent the magnetic field or secular variations of the Earth, a spatio-temporal model is required. In making a global model, satellite observations as well as limited observatory data are necessary to cover the regions and time intervals. However, you need a considerable work and time to process a huge amount of the dataset with complicated signal separation procedures. When you update the model, the same amount of chores is demanded. Besides, the global model might be affected by the measurement errors of each observatory that are biased and the processing errors in satellite data so that the accuracy of the model would be degraded. In this study, as considered these problems, I introduced a localized method in modeling secular variation of the Earth's magnetic field over Northeast Asia region. Secular variation data from three Japanese observatories and one Chinese observatory that are all in the INTERMAGNET are implemented in the model valid between 1997 to 2011 with the interval of 6 months. With the resulting model, I compared with the global model called CHAOS-4, which includes the main, secular variation and secular acceleration models between 1997 to 2013 by using the three satellites' databases and INTERMAGNET observatory data. Also, the geomagnetic 'jerk' which is known as a sudden change in the time derivatives of the main field of the Earth, was discussed from the localized secular acceleration coefficients derived from spline models.

• 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.

• Journal of the Korean GEO-environmental Society
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• v.18 no.2
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• pp.47-51
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• 2017

In this study, the optimization algorithm by inverse analysis that is the core of the adaptive management technique was adopted to update the soil engineering properties based on the ground response during the construction. Adaptive management technique is the framework wherein construction and design procedures are adjusted based on observations and measurements made as construction proceeds. To evaluate the performance of the adaptive management technique, the numerical simulation for the triaxial tests and the synthetic deep excavation were conducted with the Hardening Soil model. To effectively conduct the analysis, the effective parameters among the parameters employed in the model were selected based on the composite scaled sensitivity analysis. The results from the undrained triaxial tests performed with soft Chicago clays were used for the parameter calibration. The simulation for the synthetic deep excavation were conducted assuming that the soil engineering parameters obtained from the triaxial simulation represent the actual field condition. These values were used as the reference values. The observation for the synthetic deep excavation simulations was the horizontal displacement of the support wall that has the highest composite scaled sensitivity among the other possible observations. It was found that the horizontal displacement of the support wall with the various initial soil properties were converged to the reference displacement by using the adaptive management technique.

• Journal of the Korean Association of Geographic Information Studies
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• v.17 no.2
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• pp.32-43
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• 2014

To identify major causes of the global environment changes arising from extreme and unusual weather patterns occurring these days, and to foresee future environmental changes, it is highly important to shed light on the correlation between climate changes and global environment system. To investigate the correlation between climate changes and global environment system, it calls for establishing an integrated climate-environment DB for analyzing comparatively the data on climatic changes and global environment system. In the preceding studies, we researched an XML-based integrated climate-environment DB and developed a management system for the DB. However, the existing integrated climate-environment DB, designed and installed only for individual PCs, does not allow multiple users 'simultaneous access. Accordingly, it fails to systematically update and sharing data which is being generated continuingly. Hence, this study aims to develop an easy-to-use GIS-based integrated DB management system by improving the existing integrated climate-environment DB through the adoption of the client/server model. For this, this study collected and analyzed climate and environment data prior to designing and building a DBMS-based integrated DB. In addition, in order for multidisciplinary researchers to easily get access and apply the integrated DB, this study designed and developed a GIS-based integrated DB management system using a client/server model which facilitates connections with multiple PCs. The GIS-based integrated climate-environment DB management system makes it easier to efficiently manage and locate scattered climate-environment data. It is also expected that the DB system will bring the effects in saving time and cost by avoiding the overlapping generation of data in the areas of integrated climate-environment research.

• Korean Journal of Agricultural and Forest Meteorology
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• v.15 no.1
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• pp.40-49
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• 2013

Current service system of the Korea Meteorological Administration (KMA) for blooming date forecasting in spring depends on regression equations derived from long term observations in both temperature and phenology at a given station. This regression based system does not allow a timely correction or update of forecasts that are highly sensitive to fluctuating weather conditions. Furthermore, the system cannot afford plant responses to climate extremes which were not observed before. Most of all, this method may not be applicable to locations other than that which the regression equations were derived from. This note suggests a way to replace the location restricted regression equations with a thermal time based phenology model to complement the KMA blooming forecast system. Necessary parameters such as reference temperature, chilling requirement and heating requirement were derived from phenology data for forsythia, azaleas and Japanese cherry at 29 KMA stations for the 1951-1980 period to optimize spring phenology prediction model for each species. Best fit models for each species were used to predict blooming dates and the results were compared with the observed dates to produce a correction grid across the whole nation. The models were driven by the KMA's daily temperature data at a 5km grid spacing and subsequently adjusted by the correction grid to produce the blooming date maps. Validation with the 1971-2012 period data showed the RMSE of 2-3 days for Japanese cherry, showing a feasibility of operational service; whereas higher RMSE values were observed with forsythia and azaleas.

• Journal of Korean Society of Transportation
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• v.18 no.5
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• pp.83-97
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• 2000

The traffic management schemes through traffic signal control and information provision could be effective when the link-level data and trip-level data were used simultaneously in analysis Procedures. But, because the trip-level data. such as origin, destination and departure time, can not be obtained through the existing surveillance systems directly. It is needed to estimate it using the link-level data which can be obtained easily. Therefore the objective of this study is to develop the model to estimate O-D demand using only the link flows in highway network as a real time. The methodological approaches in this study are kalman filer, least-square method and normalized least-square method. The kalman filter is developed in the basis of the bayesian update. The normalized least-square method is developed in the basis of the least-square method and the natural constraint equation. These three models were experimented using two kinds of simulated data. The one has two abrupt changing Patterns in traffic flow rates The other is a 24 hours data that has three Peak times in a day Among these models, kalman filer has Produced more accurate and adaptive results than others. Therefore it is seemed that this model could be used in traffic demand management. control, travel time forecasting and dynamic assignment, and so forth.

• Journal of Internet Computing and Services
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• v.12 no.5
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• pp.171-179
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• 2011

In this paper it is hypothesized that word stimuli that are presented by Google’s search word, would improve the quality of the design solution, so this research examines the effect of related search word stimuli in concept generation and analyzes the results through the processes of creative cognition. In the process of concept generation, words are given as stimuli which are generated through Google's related search and these search words are given by 5 levels. Google search is based on the collaboration philosophy. People's participation and contribution recreate knowledge and information, so these renewed and related search words update in real time by people are used as stimuli. Two problems are provided with related search words. After the design concept generation the results are analyzed by 3 bases: the usage of related search words and those of frequency, creativity, and Finke's 12 Geneplore model. These are the results of the research. Many levels of related search words are used in design concept generation but especially higher levels which are more related to search words are more used than lower levels. The usage of multi words and conjunction with higher levels and lower levels words are observed in creative results. On the creative cognitive processes, it is more creative when using association and mental transformation with the related search words than using the related search words simply. Creative outputs also use conceptual interpretation, functional inference, and contextual shifting of creative cognitive processes of Finke's 12 Geneplore model.

• Journal of Service Research and Studies
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• v.1 no.1
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• pp.29-48
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• 2011

Recently not only industry but also academy have shown an intense interest in social networking service. However, reckless imitation will not guarantee the successful eco-system of social networking service without rich understanding of growth driver and business model. Hence, this study aims at analyzing open platform strategy and business model conducted by a representative social networking service provider in order to provide platform operator, network operator, and portal provider with meaningful implications. Advertisers may pay great attention to social networking service because it has strong ability to provide users with spontaneous motivation to manage and update their profile, and these valuable information can be utilized for providing personalized advertisement on social networking service. As a result, one side of consumers in two side market, advertisers, tend to pay more expenditure to place advertisements. In addition, the open platform adopted by social networking service providers causes pro-sumers to participate in the eco-system, and thereby the explosive quantitative growth is realized. The fact of that this open social networking service can invade other web service area via an unified platform indicates that it may expand its service scope into a wide variety of web service areas. Hence, domestic portal services providers and network providers should consider social networking service not as one of new web services but as an disruptive service platform. Corresponding to the emergence of social networking service, especially if their business area is related to display advertising market, they should seek a way to provide social networking service access users's newly updated information and develop innovative media technologies to enter context awareness ads market.