• Journal of Korean Tunnelling and Underground Space Association
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• v.10 no.3
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• pp.303-312
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• 2008

Multi-axial compression tests have been frequently adopted for the evaluation of material properties of rock cores and rock fracture model tests. Special care has to be applied on the boundary condition between the specimen and loading platen to draw the precise test results of the multi-axial compression tests. With the use of dry steel platen, the stress rotation will occur, due to the frictional restraint from the boundary between the specimen and loading platen. The restraint will deviate the expected test results under the conditions of the given external pressures. Various methods have been applied to reduce the side restraint along the specimen/loading platen interface. The steel brush type loading platen is one example of the attempts. In this paper, a new type of loading platen is introduced to overcome the limitation caused by the use of the brush type loading platen, which requires some internal space for the installation of the brushes. The new type of loading platen, roller supported steel piston type loading platen. is constituted of shot steel pistons which have sufficient stiffness to deliver the external pressure and the shaft type roller installed at the rear of the pistons. The pistons are designed to follow the local deformation of the specimens. In this paper, structural details of the loading platen are presented and frictional and biaxial compression tests results are shown to verify the required functions of the loading platen. Furthermore, calibration process is followed by a comparison between the test results and numerical analyses.

• Journal of the Korea Society of Computer and Information
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• v.15 no.11
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• pp.143-156
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• 2010

Faced with an increase of malicious threats from the Internet as well as local area networks, many companies are considering deploying a security system. To help a decision maker select a suitable security tool, this paper proposed a three-step integrated framework using linear fuzzy regression (LFR) and physical programming (PP). First, based on the experts' estimations on security criteria, analytic hierarchy process (AHP) and quality function deployment (QFD) are employed to specify an intermediate score for each criterion and the relationship among these criteria. Next, evaluation value of each criterion is computed by using LFR. Finally, a goal programming (GP) method is customized to obtain the most appropriate security tool for an organization, considering a tradeoff among the multi-objectives associated with quality, credibility and costs, utilizing the relative weights calculated by the physical programming weights (PPW) algorithm. A numerical example provided illustrates the advantages and contributions of this approach. Proposed approach is anticipated to help a decision maker select a suitable security tool by taking advantage of experts' experience, with noises eliminated, as well as the accuracy of mathematical optimization methods.

• Journal of the Earthquake Engineering Society of Korea
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• v.11 no.2 s.54
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• pp.57-68
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• 2007

The mega frame system is becoming popular for the design and construction of skyscrapers because this system exhibits structural efficiency by allowing high rigidity of the structure while minimizing the amount of structural materials to be used. Since the mega frame system is usually adopted for super high-rise buildings, the comfort of occupants may be main concerns in the practical application of this system. For the enhancement of the serviceability of mega frame structures, a semi-active tuned mass damper (STMD) is developed in this study. To this end, a Magnetorheological (MR) damper is employed replacing passive damper as a semi-active damper to improve the control effect of a conventional TMD. Since a conventional finite element model of mega frame structures has significant numbers of DOFs, numerical simulation for investigation of control performances of a STMD is impossible by using the full-order model. Therefore, a reduced-order system using minimal DOFs, which can accurately represent the dynamic behavior of a mega frame structure, is proposed in this study through the matrix condensation technique To improve the efficiency of the matrix condensation technique, multi-level matrix condensation technique is proposed using the structural characteristics of mega frame structures. The efficiency and accuracy of the reduced-order control proposed in this study and the control performance of a STMD were verified using example structures.

• 한국지구물리탐사학회:학술대회논문집
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• 2006.06a
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• pp.201-206
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• 2006

Earth sciences is undergoing a gradual but massive shift from description of the earth and earth systems, toward process modeling, simulation, and process visualization. This shift is very challenging because the underlying physical and chemical processes are often nonlinear and coupled. In addition, we are especially challenged when the processes take place in strongly heterogeneous systems. An example is two-phase fluid flow in rocks, which is a nonlinear, coupled and time-dependent problem and occurs in complex porous media. To understand and simulate these complex processes, the knowledge of underlying pore-scale processes is essential. This paper presents a new attempt to use pore-scale simulations for understanding physical properties of rocks. A rigorous pore-scale simulator requires three important traits: reliability, efficiency, and ability to handle complex microstructures. We use the Lattice-Boltzmann (LB) method for singleand two-phase flow properties, finite-element methods (FEM) for elastic and electrical properties of rocks. These rigorous pore-scale simulators can significantly complement the physical laboratory, with several distinct advantages: (1) rigorous prediction of the physical properties, (2) interrelations among the different rock properties in a given pore geometry, and (3) simulation of dynamic problems, which describe coupled, nonlinear, transient and complex behavior of Earth systems.

• Geophysics and Geophysical Exploration
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• v.21 no.1
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• pp.54-60
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• 2018

The data acquired from seismic exploration can be used to detect the existence of oil and gas resources through appropriate processing and interpretation. The seismic attributes indicating the existence of resources are extracted from amplitude information, where the Q-factor representing intrinsic attenuation plays an useful role of hydrocarbon indicator. So, the accuracy of Q-factor estimation is very important to investigate the existence of resources. In this study, we calculated the Q-factor and analyzed the error rate through a numerical example. To mimic real data, random noise was added to the synthetic data. With the noise-added data, the Q-factor was estimated and the error rate was analyzed by using the spectral ratio method (SRM) and peak frequency shift method (PFSM). Both methods provided a relatively accurate Q-factor when the signal-to-noise ratio was 90 dB. However, the peak frequency shift method (PFSM) produced better results than the spectral ratio method (SRM) as the level of random noise increased.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.2
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• pp.57-63
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• 2012

Software release planning model of software product lines was formulated as a precedence-constrained multiple 0-1 knapsack problem. The purpose of the model was to maximize the total profit of an entire set of selected features in a software product line over a multi-release planning horizon. The solution approach is a dynamic programming procedure. Feasible solutions at each stage in dynamic programming are determined by using backward dynamic programming approach while dynamic programming for multi-release planning is forward approach. The pre-processing procedure with a heuristic and reduction algorithm was applied to the single-release problems corresponding to each stage in multi-release dynamic programming in order to reduce the problem size. The heuristic algorithm is used to find a lower bound to the problem. The reduction method makes use of the lower bound to fix a number of variables at either 0 or 1. Then the reduced problem can be solved easily by the dynamic programming approaches. These procedures keep on going until release t = T. A numerical example was developed to show how well the solution procedures in this research works on it. Future work in this area could include the development of a heuristic to obtain lower bounds closer to the optimal solution to the model in this article, as well as computational test of the heuristic algorithm and the exact solution approach developed in this paper. Also, more constraints reflecting the characteristics of software product lines may be added to the model. For instance, other resources such as multiple teams, each developing one product or a platform in a software product line could be added to the model.

• Proceedings of the Korean Society of Crop Science Conference
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• 2017.06a
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• pp.303-303
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• 2017

Japanese agriculture has faced to several threats: aging and decrease of farmer population, global competition, and the risk of climate change as well as harsh and variable weather. On the other hands, the number of large scale farms is increasing, because farm lands have been being aggregated to fewer numbers of farms. Cost cutting, development of efficient ways to manage complicatedly scattered farm lands, maintaining yield and quality under variable weather conditions, are required to adapt to changing environments. Information and communications technology (ICT) would contribute to solve such problems and to create innovative technologies. Thus we have been developing an early warning and decision support system to reduce weather and climate risks for rice, wheat and soybean production in Japan. The concept and prototype of the system will be shown. The system consists of a weather data system (Agro-Meteorological Grid Square Data System, AMGSDS), decision support contents where information is automatically created by crop models and delivers information to users via internet. AMGSDS combines JMA's Automated Meteorological Data Acquisition System (AMeDAS) data, numerical weather forecast data and normal values, for all of Japan with about 1km Grid Square throughout years. Our climate-smart system provides information on the prediction of crop phenology, created with weather forecast data and crop phenology models, as an important function. The system also makes recommendations for crop management, such as nitrogen-topdressing, suitable harvest time, water control, pesticide spray. We are also developing methods to perform risk analysis on weather-related damage to crop production. For example, we have developed an algorism to determine the best transplanting date in rice under a given environment, using the results of multi-year simulation, in order to answer the question "when is the best transplanting date to minimize yield loss, to avoid low temperature damage and to avoid high temperature damage?".

• Parasites, Hosts and Diseases
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• v.29 no.2
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• pp.101-112
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• 1991

While various examples of rationale or benefits of ascariasis control could justify a necessity of control activity in a community, few practical index other than the e99 Prevalence or intensity of infection has been used to evaluate the efficacy obtained by the control activity. A literature-based retrospective study was undertaken to provide some numerical data on the decreasing morbidity of surgical ascariasis as a consequence of ascariasis control in Korea. A thorough review of literatures (1959∼1990) on biliary and other surgical complications of ascariasis reported from general hospitals revealed that their incidence has been decreasing very proportionally to the national figures of its e99 Prevalence and worm burden. For example, according to the remarkable decreases of the prevalence of ascariasis, there is an evident decreasing tendency of the proportion(%) of ciliary ascariasis cases among all biliary surgical patients and the proportion of biliary ascariasis cases among all biliary stone patients in general hospitals. It is highly suggested that the Korean people have been much benefited by the control activity of ascariasis executed at a national scale since 1960s, especially in terms of incidence of biliary and other surgical complications of ascariasis.

• Journal of Korean Society of Transportation
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• v.18 no.6
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• pp.89-99
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• 2000

To cope with the limits of conventional O-D trip matrix collecting methods, several approaches have been developed. One of them is bilevel Programming method Proposed by Yang(1995), which uses Sensitivity Analysis Based(SAB) algorithm to solve Generalized Least Square(GLS) problem. However, the SAB a1gorithm has revealed two critical short-comings. The first is that when there exists a significant difference between target O-D matrix and true O-D matrix, SAB algorithm may not produce correct solution. This stems from the heavy dependance on the historical O-D information, in special when gravel Patterns are dramatically changed. The second is the assumption of iterative linear approximation to original Problem. Because of the approximation, SAB algorithm has difficulty in converging to Perfect Stackelberg game condition. So as to avoid the Problems. we need a more robust and stable solution method. The main purpose of this Paper is to show the problem of the dependency of Previous models and to Propose an alternative solution method to handle it. The Problem of O-D matrix estimation is intrinsically nonlinear and nonconvex. thus it has multiple solutions. Therefore it is necessary to require a method for searching globa1 solution. In this paper, we develop a solution algorithm combined with genetic algorithm(GA) , which is widely used as probabilistic global searching method To compare the efficiency of the algorithm, SAB algorithm suggested by Yang et al. (1992,1995) is used. From the results of numerical example, the Proposed algorithm is superior to SAB algorithm irrespective of travel patterns.

• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.523-532
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• 2013

Generally, data mining is the process of analyzing big data from different perspectives and summarizing it into useful information. The most widely used data mining technique is to generate association rules, and it finds the relevance between two items in a huge database. This technique has been used to find the relationship between each set of items based on the interestingness measures such as support, confidence, lift, etc. Among many interestingness measures, confidence is the most frequently used, but it has the drawback that it can not determine the direction of the association. The attributably pure confidence and compared confidence are able to determine the direction of the association, but their ranges are not [-1, +1]. So we can not interpret the degree of association operationally by their values. This paper propose a compared and attributably pure confidence to compensate for this drawback, and then describe some properties for a proposed measure. The comparative studies with confidence, compared confidence, attributably pure confidence, and a proposed measure are shown by numerical example. The results show that the a compared and attributably pure confidence is better than any other confidences.