• 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 Internet Computing and Services
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• v.6 no.4
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• pp.59-73
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• 2005

Caching query results and reusing them in processing of subsequent queries is an important query optimization technique. Materialized view and view indexing are the representative examples of such a technique. The two schemes had received much attention for relational databases, and have been investigated for XML data since XML emerged as the standard for data exchange on the Web. In XML view indexing, XML view xv which is the result of an XML query is represented as an XML view index(XVI), a structure containing the identifiers of xv's underlying XML elements as well as the information on xv. Since XVI for xv stores just the identifiers of the XML elements not the elements themselves, when xv is requested, its XVI should be materialized against xv's underlying XML documents. In this paper, we address the problem of integrating an XML view index management system with an RDBMS based XML storage system. The proposed system was implemented in Java on Windows 2000 Server with each of two different commercial RDBMSs, and used in evaluating performance improvement through XML view indexing as well as its overheads. The experimental results revealed that XML view indexing was very effective with an RDBMS based XML storage system while its overhead was negligible.

• Journal of Korean Tunnelling and Underground Space Association
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• v.17 no.3
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• pp.257-266
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• 2015

This study introduce that we studied optimization and possibility of smoke spread prevention with air-curtain system in undersea tunnel named from Ho-Nam to Jeju line in domestic if a fire break out in train. To verify performance, air-curtain system is installed between rescue station platform and each door of passenger car to provide safety route to evacuator and we studied simulation model of various cases about 15 MW fire severity considering domestic specifications. As a result we verified the fact that CASE1(air jet with 15degree toward passenger car) and CASE 5 (air jet with 15degree toward passenger car and pressure air blast from cross passage) is best Smoke Spread Prevention and less inflow carbon monoxide. Through above results, we expect that air-curtain system is one of the facilities for fire safety and provide us safety platform route in undersea tunnel.

• Journal of radiological science and technology
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• v.39 no.4
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• pp.571-575
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• 2016

Monte Carlo simulations are widely used as the most accurate technique for dose calculation in radiation therapy. In this paper, the GATE6(Geant4 Application for Tomographic Emission ver.6) code was employed to calculate the dosimetric performance of the photon beams from a linear accelerator(LINAC). The treatment head of a Varian 21EX Clinac was modeled including the major geometric structures within the beam path such as a target, a primary collimator, a flattening filter, a ion chamber, and jaws. The 6 MV photon spectra were characterized in a standard $10{\times}10cm^2$ field at 100 cm source-to-surface distance(SSD) and subsequent dose estimations were made in a water phantom. The measurements of percentage depth dose and dose profiles were performed with 3D water phantom and the simulated data was compared to measured reference data. The simulated results agreed very well with the measured data. It has been found that the GATE6 code is an effective tool for dose optimization in radiotherapy applications.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.176-183
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• 2008

Recently, several large-scale Mega-Projects are being conducted. For these urban revitalization projects which requires many complex functions, the existing project management system based on single project level is limited in application. Therefore, our main objectives of this research are two 1) Develop a brand-new program management system(Prototype Ver 1.0) for mega-projects where various facilities are combined both horizontally and vertically. 2) Develop management strategies(Prototype Ver 1.0) based on the program level that enable the comprehensive management of a multiple various projects. The subtitles of this Research are i-PMIS(Program Management Information System) Development, Standardization & Optimization of Construction Life-Cycle Process, Comprehensive Project Cost & Process Management Technology, Effective and Optimized Integrated Performance Management Technology, and, we suggest to optimize the whole life cycle process, predict and respond to various risks, predict and control the process, the cost and the schedule, achieve maximum return on investment to the participating parties, and provide a brand-new Program-MIS including the visual-based web-portal platform to respond the changing business environments and decision making.

• Analytical Science and Technology
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• v.35 no.6
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• pp.256-266
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• 2022

It is important to determine the concentration of long-lived radionuclides (e.g., ¹²⁹I) in nuclear waste to ensure safety when handling it. To analyze nuclides in a solid sample (e.g., concrete and soil), it is essential to effectively separate and purify the nuclides of interest in the sample. This study reports the comprehensive efforts made to validate the analytical procedure for ¹²⁹I detection in solid samples, using a high-temperature combustion furnace. ¹²⁹I volatilized from the sample collected in 0.01 M HNO₃ solution with a reducing agent (e.g., NaHSO₃) and was rapidly measured by ICP-MS. Analytical conditions, such as pyrolysis temperature and types of mobile phase gas, catalyst, and trapping solution, were optimized to obtain a high recovery rate of spiked ¹²⁹I. Finally, the optimized method was applied for the simultaneous analysis of other volatile radionuclides, such as ³H and ¹⁴C. The performance test results for the optimized method confirmed that the LSC (for ³H and ¹⁴C) and ICP-MS (for ¹²⁹I) measurements, with the separation of volatile nuclides using a high-temperature combustion furnace, were reliable.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.59-76
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• 2023

Since the COVID-19 era, the rise in apartment prices has been unconventional. In this uncertain real estate market, price prediction research is very important. In this paper, a model is created to predict the actual transaction price of future apartments after building a vast data set of 870,000 from 2015 to 2020 through data collection and crawling on various real estate sites and collecting as many variables as possible. This study first solved the multicollinearity problem by removing and combining variables. After that, a total of five variable selection algorithms were used to extract meaningful independent variables, such as Forward Selection, Backward Elimination, Stepwise Selection, L1 Regulation, and Principal Component Analysis(PCA). In addition, a total of four machine learning and deep learning algorithms were used for deep neural network(DNN), XGBoost, CatBoost, and Linear Regression to learn the model after hyperparameter optimization and compare predictive power between models. In the additional experiment, the experiment was conducted while changing the number of nodes and layers of the DNN to find the most appropriate number of nodes and layers. In conclusion, as a model with the best performance, the actual transaction price of apartments in 2021 was predicted and compared with the actual data in 2021. Through this, I am confident that machine learning and deep learning will help investors make the right decisions when purchasing homes in various economic situations.

• Journal of the Korea Computer Graphics Society
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• v.29 no.3
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• pp.85-92
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• 2023

Recently, interest in artificial intelligence has increased due to the development of artificial intelligence fields such as ChatGPT and self-driving cars. However, there are still many unknown elements in training process of artificial intelligence, so that optimizing the model requires more time and effort than it needs. Therefore, there is a need for a tool or methodology that can analyze the weight changes during the training process of artificial intelligence and help out understatnding those changes. In this research, I propose a visualization system which helps people to understand the accumulated weight changes. The system calculates the weights for each training period to accumulates weight changes and stores accumulated weight changes to plot them in 3D space. This research will allow us to explore different aspect of artificial intelligence learning process, such as understanding how the model get trained and providing us an indicator on which hyperparameters should be changed for better performance. These attempts are expected to explore better in artificial intelligence learning process that is still considered as unknown and contribute to the development and application of artificial intelligence models.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.8
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• pp.572-578
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• 2020

The stock market is affected by unexpected factors, such as politics, society, and natural disasters, as well as by corporate performance and economic conditions. In recent days, artificial intelligence has become popular, and many researchers have tried to conduct experiments with that. Our study proposes an experiment using not only stock-related data but also other various economic data. We acquired a year's worth of data on stock prices, the percentage of foreigners, interest rates, and exchange rates, and combined them in various ways. Thus, our input data became diversified, and we put the combined input data into a nonlinear autoregressive network with exogenous inputs (NARX) model. With the input data in the NARX model, we analyze and compare them to the original data. As a result, the model exhibits a root mean square error (RMSE) of 0.08 as being the most accurate when we set 10 neurons and two delays with a combination of stock prices and exchange rates from the U.S., China, Europe, and Japan. This study is meaningful in that the exchange rate has the greatest influence on stock prices, lowering the error from RMSE 0.589 when only closing data are used.

• KIPS Transactions on Computer and Communication Systems
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• v.2 no.8
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• pp.317-326
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• 2013

In this paper, we present an effective method for comparing control flow graphs which represent static structures of binary programs. To compare control flow graphs, we measure similarities by comparing instructions and syntactic information contained in basic blocks. In addition, we also consider similarities of edges, which represent control flows between basic blocks, by edge extension. Based on the comparison results of basic blocks and edges, we match most similar basic blocks in two control flow graphs, and then calculate the similarity between control flow graphs. We evaluate the proposed edge extension method in real world Java programs with respect to structural similarities of their control flow graphs. To compare the performance of the proposed method, we also performed experiments with a previous structural comparison for control flow graphs. From the experimental results, the proposed method is evaluated to have enough distinction ability between control flow graphs which have different structural characteristics. Although the method takes more time than previous method, it is evaluated to be more resilient than previous method in comparing control flow graphs which have similar structural characteristics. Control flow graph can be effectively used in program analysis and understanding, and the proposed method is expected to be applied to various areas, such as code optimization, detection of similar code, and detection of code plagiarism.