• KSCE Journal of Civil and Environmental Engineering Research
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• v.6 no.4
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• pp.53-60
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• 1986

This study is directed to propose a probability based LRFD design code, which could possibly replace the traditional USD provisions of the current code, based on the AFOSM reliability theory. The uncertainties of resistances and load effects for each R.C. structural elements are evaluated and adopted considering our practice, and a set of rational target reliability indices are selected based on the calibration with the reliability of the current R.C. design code and by considering the desired hierarchy of safety level. Then, a set of common load factors are chosen from the results of load and resistance factors which are computed by AFOSM method using the Rackwitz-Fiessler's efficient practical algorithm which is to transform the non-normal variables into the equivalent normal variables. It may be asserted that the proposed LRFD code for the R.C. building structures may have to be incorporated into the current RC. design codes as a design provision corresponding to the USD provisions of the current R.C. design code.

• Journal of Soil and Groundwater Environment
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• v.10 no.4
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• pp.54-61
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• 2005

An aquifer thermal energy storage (ATES) system can be very cost-effective and renewable energy sources, depending on site-specific parameters and load characteristics. In order to develop the ATES system which has certain hydrogeological characteristics, understanding the thermohydraulic process of an aquifer is necessary for a proper design of an aquifer heat storage system under given conditions. The thermohydraulic transfer for heat storage was simulated according to two sets of simple pumping and waste water reinjection scenarios of groundwater heat pump system operation in a two-layered aquifer model. In the first set of the scenarios, the movement of the thermal front and groundwater level was simulated by changing the locations of injection and pumping wells in a seasonal cycle. However, in the second set the simulation was performed in the state of fixing the locations of pumping and injection wells. After 365 days simulation period, the shape of temperature distribution was highly dependent on the injected water temperature and the distance from the injection well. A small temperature change appeared on the surface compared to other simulated temperature distributions of 30 and 50 m depths. The porosity and groundwater flow characteristics of each layer sensitively affected the heat transfer. The groundwater levels and temperature changes in injection and pumping wells were monitored and the thermal interference between the wells was analyzed to test the effectiveness of the heat pump operation method applied.

• Korean Journal of Remote Sensing
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• v.35 no.2
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• pp.299-316
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• 2019

The purpose of this study was to analyze landslide susceptibility in the Pyeongchang area using Weight of Evidence (WOE) and Evidential Belief Function (EBF) as probability models and Artificial Neural Networks (ANN) as a machine learning model in a geographic information system (GIS). This study examined the widespread shallow landslides triggered by heavy rainfall during Typhoon Ewiniar in 2006, which caused serious property damage and significant loss of life. For the landslide susceptibility mapping, 3,955 landslide occurrences were detected using aerial photographs, and environmental spatial data such as terrain, geology, soil, forest, and land use were collected and constructed in a spatial database. Seventeen factors that could affect landsliding were extracted from the spatial database. All landslides were randomly separated into two datasets, a training set (50%) and validation set (50%), to establish and validate the EBF, WOE, and ANN models. According to the validation results of the area under the curve (AUC) method, the accuracy was 74.73%, 75.03%, and 70.87% for WOE, EBF, and ANN, respectively. The EBF model had the highest accuracy. However, all models had predictive accuracy exceeding 70%, the level that is effective for landslide susceptibility mapping. These models can be applied to predict landslide susceptibility in an area where landslides have not occurred previously based on the relationships between landslide and environmental factors. This susceptibility map can help reduce landslide risk, provide guidance for policy and land use development, and save time and expense for landslide hazard prevention. In the future, more generalized models should be developed by applying landslide susceptibility mapping in various areas.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.99-112
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• 2010

Ensemble learning is a method for improving the performance of classification and prediction algorithms. It is a method for finding a highly accurateclassifier on the training set by constructing and combining an ensemble of weak classifiers, each of which needs only to be moderately accurate on the training set. Ensemble learning has received considerable attention from machine learning and artificial intelligence fields because of its remarkable performance improvement and flexible integration with the traditional learning algorithms such as decision tree (DT), neural networks (NN), and SVM, etc. In those researches, all of DT ensemble studies have demonstrated impressive improvements in the generalization behavior of DT, while NN and SVM ensemble studies have not shown remarkable performance as shown in DT ensembles. Recently, several works have reported that the performance of ensemble can be degraded where multiple classifiers of an ensemble are highly correlated with, and thereby result in multicollinearity problem, which leads to performance degradation of the ensemble. They have also proposed the differentiated learning strategies to cope with performance degradation problem. Hansen and Salamon (1990) insisted that it is necessary and sufficient for the performance enhancement of an ensemble that the ensemble should contain diverse classifiers. Breiman (1996) explored that ensemble learning can increase the performance of unstable learning algorithms, but does not show remarkable performance improvement on stable learning algorithms. Unstable learning algorithms such as decision tree learners are sensitive to the change of the training data, and thus small changes in the training data can yield large changes in the generated classifiers. Therefore, ensemble with unstable learning algorithms can guarantee some diversity among the classifiers. To the contrary, stable learning algorithms such as NN and SVM generate similar classifiers in spite of small changes of the training data, and thus the correlation among the resulting classifiers is very high. This high correlation results in multicollinearity problem, which leads to performance degradation of the ensemble. Kim,s work (2009) showedthe performance comparison in bankruptcy prediction on Korea firms using tradition prediction algorithms such as NN, DT, and SVM. It reports that stable learning algorithms such as NN and SVM have higher predictability than the unstable DT. Meanwhile, with respect to their ensemble learning, DT ensemble shows the more improved performance than NN and SVM ensemble. Further analysis with variance inflation factor (VIF) analysis empirically proves that performance degradation of ensemble is due to multicollinearity problem. It also proposes that optimization of ensemble is needed to cope with such a problem. This paper proposes a hybrid system for coverage optimization of NN ensemble (CO-NN) in order to improve the performance of NN ensemble. Coverage optimization is a technique of choosing a sub-ensemble from an original ensemble to guarantee the diversity of classifiers in coverage optimization process. CO-NN uses GA which has been widely used for various optimization problems to deal with the coverage optimization problem. The GA chromosomes for the coverage optimization are encoded into binary strings, each bit of which indicates individual classifier. The fitness function is defined as maximization of error reduction and a constraint of variance inflation factor (VIF), which is one of the generally used methods to measure multicollinearity, is added to insure the diversity of classifiers by removing high correlation among the classifiers. We use Microsoft Excel and the GAs software package called Evolver. Experiments on company failure prediction have shown that CO-NN is effectively applied in the stable performance enhancement of NNensembles through the choice of classifiers by considering the correlations of the ensemble. The classifiers which have the potential multicollinearity problem are removed by the coverage optimization process of CO-NN and thereby CO-NN has shown higher performance than a single NN classifier and NN ensemble at 1% significance level, and DT ensemble at 5% significance level. However, there remain further research issues. First, decision optimization process to find optimal combination function should be considered in further research. Secondly, various learning strategies to deal with data noise should be introduced in more advanced further researches in the future.

• Journal of radiological science and technology
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• v.32 no.4
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• pp.361-370
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• 2009

The image quality management of bone mineral density is the responsibility and duty of radiologists who carry out examinations. However, inaccurate conclusions due to lack of understanding and ignorance regarding the methodology of image quality management can be a fatal error to the patient. Therefore, objective of this paper is to understand proper image quality management and enumerate methods for examiners and patients, thereby ensuring the reliability of bone mineral density exams. The accuracy and precision of bone mineral density measurements must be at the highest level so that actual biological changes can be detected with even slight changes in bone mineral density. Accuracy and precision should be continuously preserved for image quality of machines. Those factors will contribute to ensure the reliability in bone mineral density exams. Proper equipment management or control methods are set with correcting equipment each morning and after image quality management, a phantom, recommended from the manufacturer, is used for ten to twenty-five measurements in search of a mean value with a permissible range of ${\pm}1.5%$ set as standard. There needs to be daily measurement inspections on the phantom or at least inspections three times a week in order to confirm the existence or nonexistence of changes in values in actual bone mineral density. in addition, bone mineral density measurements were evaluated and recorded following the rules of Shewhart control chart. This type of management has to be conducted for the installation and movement of equipment. For the management methods of inspectors, evaluation of the measurement precision was conducted by testing the reproducibility of the exact same figures without any real biological changes occurring during reinspection. Bone mineral density inspection was applied as the measurement method for patients either taking two measurements thirty times or three measurements fifteen times. An important point when taking measurements was after a measurement whether it was the second or third examination, it was required to descend from the table and then reascend. With a 95% confidence level, the precision error produced from the measurement bone mineral figures came to 2.77 times the minimum of the biological bone mineral density change. The value produced can be stated as the least significant change (LSC) and in the case the value is greater, it can be stated as a section of genuine biological change. From the initial inspection to equipment moving and shifter, management must be carried out and continued in order to achieve the effects. The enforcement of proper quality control of radiologists performing bone mineral density inspections which brings about the durability extensions of equipment and accurate results of calculations will help the assurance of reliable inspections.

• Korean Journal of Applied Biomechanics
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• v.26 no.2
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• pp.143-151
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• 2016

Objective: The purpose of this study was to investigate the effect of fatigue induction on ground reaction force (GRF) components, postural stability, and vertical jump performance in Taekwondo athletes. Method: Ten Taekwondo athletes (5 men, 5 women; mean age, $22.30{\pm}2.62years$; mean height, $174.21{\pm}9.20cm$; mean body weight, $67.28{\pm}12.56kg$) participated in this study. Fatigue was induced by a short period of strenuous exercise performed on a motorized treadmill. The analyzed variables included vertical jump performance, static stability (mediolateral [ML], center of pressure [COP], anteroposterior [AP] COP, ${\Delta}COPx$, ${\Delta}COPy$, and COP area), postural stability index values (ML stability index [MLSI], AP stability index [APSI], vertical stability index [VSI], dynamic postural stability index [DPSI]), and GRF components (ML force, AP force, peak vertical force [PVF], and loading rate). To analyze the variables measured in this study, PASW version 22.0 was used to calculate the mean and standard deviation, while a paired t-test was used to evaluate the pre- versus post-fatigue results. Pearson's correlation coefficients among variables were also analyzed. The statistical significance level was set at ${\alpha}$ = .05. Results: Vertical jump performance decreased significantly after the induction of fatigue, while AP COP, ${\Delta}COPx$, COP area, APSI, VSI, and DPSI increased significantly. PVF and loading rate increased significantly after the induction of fatigue, while the postural stability variables (AP COP, ${\Delta}COPy$, COP area, APSI, VSI, DPSI) were similarly correlated with GRF components (PVF, loading rate) after fatigue was achieved (r = .600, $R^2$ = 37%). Conclusion: These results suggest that the induction of fatigue can decrease postural stability and exercise performance of Taekwondo athletes during training and competition sessions.

• Korean Journal of Applied Biomechanics
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• v.26 no.2
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• pp.153-159
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• 2016

Objective: The purpose of this study was to investigate the effects of joint mobilization on foot pressure, ankle moment, and vertical ground reaction force in subjects with ankle instability. Method: Twenty male subjects (age, $25.38{\pm}3.62yr$; height, $170.92{\pm}5.41cm$; weight, $60.74{\pm}9.63kg$; body mass index (BMI), $19.20{\pm}1.67kg/m^2$) participated and underwent ankle joint mobilization. Weight-bearing distribution, ankle dorsi/plantar flexion moment, and vertical ground reaction force were measured using a GPS 400 and a VICON Motion System (Oxford, UK), and subsequently analyzed. SPSS 20.0 for Windows was used for data processing and paired t-tests were used to compare pre- and post-mobilization measurements. The significance level was set at ${\alpha}$ = .05. Results: The results indicated changes in weight-bearing, ankle dorsi/plantar flexion moment, and vertical ground reaction force. The findings showed changes in weight-bearing distribution on the left (pre $29.51{\pm}6.31kg$, post $29.57{\pm}5.02kg$) and right foot (pre $32.40{\pm}6.30kg$, post $31.18{\pm}5.47kg$). There were significant differences in dorsi/plantar flexion moment (p < .01), and there were significant increases in vertical ground reaction forces at initial stance (Fz1) and terminal stance (Fz2, p < .05). Additionally, there was a significant reduction in vertical ground reaction force at midstance (Fz2, p < .001). Conclusion: Joint mobilization appears to alter weight-bearing distribution in subjects with ankle instability, with resultant improvements in stability.

• Journal of Korea Society of Industrial Information Systems
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• v.21 no.6
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• pp.109-123
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• 2016

This study investigates the importance of government's support for logistics security assurance through certification programs. First, the study analyzed priorities among the requirements of logistics firms through Analytic Hierarchy Process(AHP) and Quality Function Deployment(QFD) approaches. For this process we invited 21 logistics experts to assess the relationships between logistic firms' requirements and government policies regarding logistics security using the house of quality, a set of matrices of QFD. The results of this phase of the study revealed the priorities of logistics firms' goals regarding the diffusion of the government security certification program as follows: integrated logistics security systems(40.3%), strengthening government support systems(32.4%), and operational effectiveness of logistics security certification(27.2%). Second, a relative weights applied QFD method based on AHP was applied to determined the expected outcome of the logistics security certification program. The results indicated as follows: productivity improvement(28.4%), improved level of service(26.7%), logistics cost reduction(21.6%), advanced information systems(19.7%), and improved environmental protection(3.6%). The results of this study provide new insights concerning logistics firms' requirements for supply chain security and the importance of government's support policies through logistics security certification programs.

• International Commerce and Information Review
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• v.14 no.3
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• pp.31-47
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• 2012

The Eurozone was launched to set a goal on using the single currency perfectly in 1999. Using the Euro could get rid of exchange cost and cost of Foreign exchange risk management which was approximately 1% of each member's GDP. It was possible that members has maintained a stable level of inflation and stimulate investment and employment with low interest rate. In addition, they could lead to economic growth and investment as well as increase the Euro demand in financial market. Especially, members has used the Euro as the method of payment on trade each other so that the volume of trade among the Eurozone members has increased continuously which was called "the effect of single market." This paper analyzes the correlation between using the Euro and members' export/import by using random effect estimation and fixed effect estimation. As a result, Eurozone members can get export decreasing effect of 4.68% and import increasing effect of 10.5% respectively on average by using the Euro.

• Journal of Biomedical Engineering Research
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• v.36 no.3
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• pp.61-68
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• 2015

In this paper, we studied the effects of intersection angles of the flow-foucusing type droplet generation device inlet channel on droplet diameter using numerical simulation modeling. We modeled different intersection angles with a fixed continuous channel width, dispersed channels width, orifices width, and expansion channels width. Numerical simulations were performed using COMSOL Multiphysics$^{(R)}$ to solve the incompressible Navier-Stokes equations for a two-phase flow in various flow-focusing geometries. Modeling results showed that an increase of the intersection angle causes an increase in the modification of the dispersed flow rate ($v^{\prime}{_d}$), and the increase of the modification of the continuous flow rate ($v^{\prime}{_c}$) obstructs the dispersed phase fluid flow, thereby reducing the droplet diameter. However, the droplet diameter did not decrease, even when the intersection angle increased. The droplet diameter decreased when the intersection angle was less than $90^{\circ}$, increased at an intersection angle of $90^{\circ}$, and decreased when the intersection angle was more than $90^{\circ}$. Furthermore, when the intermediate energy deceased, there was a decrease in the droplet diameter when the intersection angle increased. Therefore, variations in the droplet diameter can be used to change the intersection angle and fluid flow rate.