• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.4
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• pp.145-152
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• 2009

Domestic Kori-1 MCR was partially modified in 2007 and will be renovated entirely in 2013. Digital devices partially replacing original analog devices have been introduced and standard alone computer systems such as SPDS have been integrated into the plant computer. Upgrading KSNP's MCR based on the ditalization is planned for 2015. However, the site engineers and operators are reluctant to the advanced systems. Therefore, a prototype for the KSNP's advanced MCR has been developed to increase the acceptance level of the operators and field engineers and also, to evaluate user interfaces and I&C architecture. For enhancing support of the operators' work, a P&ID based display system composed of multi-layers, which are linked through a context sensitive menu each other, has been adopted. The $1^{st}$ layer displays a simplified P&ID, the $2^{nd}$ layer control related diagrams such as controllers and logic diagrams, the $3^{rd}$ layer trends, etc. The end point view of MCR for KSNP is also suggested considering reliability and operability of the digital systems. Additionally, modernization strategies over the overhaul periods, that do not have much impact on operation and configuration efforts are suggested.

• Journal of the Korean Institute of Gas
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• v.1 no.1
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• pp.56-63
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• 1997

This paper presents a hybrid network model(HY-PIPENET) implementing a minimum cost spanning tree(MCST) network algorithm to be able to determine optimum path and constrained derivative(CD) method to select optimum Pipe diameter. The HY-PIPENET has been validated with the published data of 6-node/7-pipe network. Networking system and also this system has been optimized with MCST-CD method. As a result, it was found that the gas can be sufficiently supplied at the lower pressure with the smaller diameters of pipe compared to the original system in 6-node/7-pipe network. Hence, the construction cost was reduced about $40\%$ in the optimized system. The hybrid networking model has been also applied to a complicated domestic gas pipeline network in metropolitan area, Korea. In this simulation, parametric study was peformed to understand the role of each individual parameter such as source pressure, flow rate, and pipe diameter on the optimized network. From the results of these simulations, we have proposed the optimized network as tree-type structure with optimum pipe diameter and source pressure in metropolitan area, Korea, however, this proposed system does not consider the environmental problems or safety concerns.

• Journal of Korean Society of Forest Science
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• v.107 no.1
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• pp.59-70
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• 2018

The objective of this study was to develop erosion control dam for preventing disaster in consideration of characteristics of forested catchment near urban area, and to assess its stability and functionality to see its practicability in the field. Two types of hybrid erosion control dams were developed including debris flow prevention dam by using pillar and float board screen type and debris flow control dam by using groyne. Also, review about their static (sliding, overturning, bearing capacity) and dynamic (member force) stability was carried out. According to the result, most of the assessed items met standard safety level although there were some cases where assessed items were short of stability criteria against impact. Also, after miniature flume experiments based on the developed erosion control dam to prove structure function (material catch, deposit), it turned out the dam decreased flow sediment amount and velocity while increasing sediment-capturing capacity by 3.5 times on average compared to the one controlled without erosion control dam. When function of erosion control dam for forested catchment near urban area is quantified based on future flume experiments in a variety of conditions, the dams can be practically used in the urban area, contribution to effectively reducing debris flow damage.

• Journal of Korean Society of Transportation
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• v.23 no.2
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• pp.107-116
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• 2005

The information on travel time in providing the information of traffic to drivers is one of the most important data to control a traffic congestion efficiently. Especially, this information is the major element of route choice of drivers, and based on the premise that it has the high degree of confidence in real situation. This study developed a vehicle arrival time prediction algorithm called as "VAT-DV" for 6 corridors in total 6.1Km of "Nam-san area trffic information system" in order to give an information of congestion to drivers using VMS, ARS, and WEB. The spatial scope of this study is 2.5km~3km sections of each corridor, but there are various situations of traffic flow in a short period because they have signalized intersections in a departure point and an arrival point of each corridor, so they have almost characteristics of interrupted and uninterrupted traffic flow. The algorithm uses the information on a demand volume and a queue length. The demand volume is estimated from density of each points based on the Greenburg model, and the queue length is from the density and speed of each point. In order to settle the variation of the unit time, the result of this algorithm is strategically regulated by importing the AVI(Automatic Vehicle Identification), one of the number plate matching methods. In this study, the AVI travel time information is composed by Hybrid Model in order to use it as the basic parameter to make one travel time in a day using ILD to classify the characteristics of the traffic flow along the queue length. According to the result of this study, in congestion situation, this algorithm has about more than 84% degree of accuracy. Specially, the result of providing the information of "Nam-san area traffic information system" shows that 72.6% of drivers are available.

• 한국노년학
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• v.29 no.1
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• pp.195-213
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• 2009

The purpose of this study is to analyse how consumption value affects the loyalty of green product through satisfaction and trust among elderly consumers. Data were collected from a cross-sectional survey of 314 older adults (age≥60) in the U. S., who bought and possessed a hybrid car, a representative green product. The statistical methodology is employed a structural equation model. The results demonstrated several important findings. First, perceived social value among elderly population had significant effects on green product satisfaction, while hedonic value did not. Second, both perceived functional value and environment friendly value had a significant positive effect on trust in green products. Third, satisfaction with green products also led to trust in green products. Finally, trust in green products showed their significant effects on loyalty in green product. These results provide practical implications to improve the trust and loyalty in green products among the elderly consumers. Furthermore, by deriving major components of consumption values in green products among the elderly, and analyzing the mechanism of satisfaction, trust, and loyalty, the study emphasizes relationship marketing in implementing "green" marketing strategies.

• Journal of Intelligence and Information Systems
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• v.17 no.4
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• pp.241-254
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• 2011

Financial time-series forecasting is one of the most important issues because it is essential for the risk management of financial institutions. Therefore, researchers have tried to forecast financial time-series using various data mining techniques such as regression, artificial neural networks, decision trees, k-nearest neighbor etc. Recently, support vector machines (SVMs) are popularly applied to this research area because they have advantages that they don't require huge training data and have low possibility of overfitting. However, a user must determine several design factors by heuristics in order to use SVM. For example, the selection of appropriate kernel function and its parameters and proper feature subset selection are major design factors of SVM. Other than these factors, the proper selection of instance subset may also improve the forecasting performance of SVM by eliminating irrelevant and distorting training instances. Nonetheless, there have been few studies that have applied instance selection to SVM, especially in the domain of stock market prediction. Instance selection tries to choose proper instance subsets from original training data. It may be considered as a method of knowledge refinement and it maintains the instance-base. This study proposes the novel instance selection algorithm for SVMs. The proposed technique in this study uses genetic algorithm (GA) to optimize instance selection process with parameter optimization simultaneously. We call the model as ISVM (SVM with Instance selection) in this study. Experiments on stock market data are implemented using ISVM. In this study, the GA searches for optimal or near-optimal values of kernel parameters and relevant instances for SVMs. This study needs two sets of parameters in chromosomes in GA setting : The codes for kernel parameters and for instance selection. For the controlling parameters of the GA search, the population size is set at 50 organisms and the value of the crossover rate is set at 0.7 while the mutation rate is 0.1. As the stopping condition, 50 generations are permitted. The application data used in this study consists of technical indicators and the direction of change in the daily Korea stock price index (KOSPI). The total number of samples is 2218 trading days. We separate the whole data into three subsets as training, test, hold-out data set. The number of data in each subset is 1056, 581, 581 respectively. This study compares ISVM to several comparative models including logistic regression (logit), backpropagation neural networks (ANN), nearest neighbor (1-NN), conventional SVM (SVM) and SVM with the optimized parameters (PSVM). In especial, PSVM uses optimized kernel parameters by the genetic algorithm. The experimental results show that ISVM outperforms 1-NN by 15.32%, ANN by 6.89%, Logit and SVM by 5.34%, and PSVM by 4.82% for the holdout data. For ISVM, only 556 data from 1056 original training data are used to produce the result. In addition, the two-sample test for proportions is used to examine whether ISVM significantly outperforms other comparative models. The results indicate that ISVM outperforms ANN and 1-NN at the 1% statistical significance level. In addition, ISVM performs better than Logit, SVM and PSVM at the 5% statistical significance level.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.4
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• pp.579-586
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• 2018

Short-term prediction of travel speed has been widely studied using data-driven non-parametric techniques. There is, however, a lack of research on the prediction aimed at urban areas due to their complex dynamics stemming from traffic signals and intersections. The purpose of this study is to develop a hybrid approach combining ensemble empirical mode decomposition (EEMD) and artificial neural network (ANN) for predicting urban travel speed. The EEMD decomposes the time-series data of travel speed into intrinsic mode functions (IMFs) and residue. The decomposed IMFs represent local characteristics of time-scale components and they are predicted using an ANN, respectively. The IMFs can be predicted more accurately than their original travel speed since they mitigate the complexity of the original data such as non-linearity, non-stationarity, and oscillation. The predicted IMFs are summed up to represent the predicted travel speed. To evaluate the proposed method, the travel speed data from the dedicated short range communication (DSRC) in Daegu City are used. Performance evaluations are conducted targeting on the links that are particularly hard to predict. The results show the developed model has the mean absolute error rate of 10.41% in the normal condition and 25.35% in the break down for the 15-min-ahead prediction, respectively, and it outperforms the simple ANN model. The developed model contributes to the provision of the reliable traffic information in urban transportation management systems.

• Restorative Dentistry and Endodontics
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• v.33 no.1
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• pp.28-38
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• 2008

This study was to investigate the influence of composite resins with different elastic modulus, cavity modification and occlusal loading condition on the stress distribution of restored notch-shaped noncarious cervical lesion using 3-dimensional (3D) finite element (FE) analysis. The extracted maxillary second premolar was scanned serially with Micro-CT. The 3D images were processed by 3D-DOCTOR. ANSYS was used to mesh and analyze 3D FE model. A notch-shaped cavity and a modified cavity with a rounded apex were modeled. Unmodified and modified cavities were filled with hybrid or flowable resin. After restoration, a static load of 500N was applied in a point-load condition at buccal cusp and palatal cusp. The stress data were analyzed using analysis of principal stress. The results were as follows: 1. In the unrestored cavity, the stresses were highly concentrated at mesial CEJ and lesion apex and the peak stress was observed at the mesial point angle under both loading conditions. 2. After restoration of the cavity, stresses were significantly reduced at the lesion apex, however cervical cavosurface margin, stresses were more increased than before restoration under both loading conditions. 3. When restoring the notch-shaped lesion, material with high elastic modulus worked well at the lesion apex and material with low elastic modulus worked well at the cervical cavosurface margin. 4. Cavity modification the rounding apex did not reduce compressive stress, but tensile stress was reduced.

• Journal of Korean Academy of Nursing
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• v.27 no.4
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• pp.933-942
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• 1997

There has recently been an increased interest in women's health from, various disciplines, with different perspectives presented according to each profession's academic background. This has led to many instances of incorrectly defining, or misinterpretation, of the issues even among professionals. Nurse scholars as well as practitioners who work in women's health care need to have a clear conceptual understanding of women's health in order to build a body of knowledge, delineate curricular activities, and set directions for professional nursing interventions. In addition, a conceptual model that may be directly utilized in practice is needed to maintain and promote women's health issues. The purpose of this study was to apply a Hybrid model, analyzing conceptual definitions and discussions related to women's health gathered from review of the literature. Further to compare analyticals the concepts and properties observed from field work, so as to present a final definition of women's health and, build a conceptual framework for a united comprehensive perspective on the concept as well as on nursing practice. Data collection and analysis consisted of a theoretical stage, field work stage, and final analysis. A heterogeneous group of professionals and lay persons, 39 in all, participated in the field work. Study findings Include several subconcepts under the concept of women's health : a woman's whole life, holistic health, quality of life, awareness of being a woman, individual nursing, self care ability, reproductive health, and family health. Thus, a comprehensive definition was built, 1. e., "Women's health care be defined as improvement in the quality of life of women through attainment of holistic health throughout the life span. With reproductive health at the core, the concept is directly related to family and national health, and includes taking care of one's own health based on awareness of being a woman and utilizing self care activities. Women's health care issues are unique and allow various responses, therefore women's health professionals need to apply individual approaches to reach solutions in attaining holistic health and improving quality of life." The constructual factors of women's health were found to be reproductive functions, diseases more common in woman, self actualization, mental health, women's health policies, sexuality, midlife changes, and marital relations, with each factor having more than three properties. Positive factors affecting women's health were found to be a normal childbearing process, a healthy lifestyle, active health management, health information, support, and resources, and interpersonal relationships. Negative factors were found to be overwhelming role stress, cultural oppression, gender inequality, distorted sexual identity, economic difficulties, misuse and/or abuse of substances, and stress. The model of women's health may be visualized as a balance scale set upon a woman's life, supporting 4 concentric circles. The innermost circle and second circle incorporate conceptual definitions of women's health, and the outer two circles represent the constructional factors and properties of women's health. Each circle has its own color that symbolizes the conceptual meaning. Positive and negative factors are represented as weights at either end of the scale, and are affected by nursing intervention, i. e., health and wellness increase when positive factors are stronger, whereas disease and illness increase when negative factors are stronger. This model is only a preliminary effort and requires much discussion and testing to be further developed. Continuous research is also required.

• Journal of Korean Society of Transportation
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• v.32 no.2
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• pp.93-105
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• 2014

This study evaluated the relative efficiency of mobile emission reduction countermeasures through a Data Envelopment Analysis (DEA) approach and determined the priority of countermeasures based on the efficiency. Ten countermeasures currently applied for reducing greenhouse gases and air pollution materials were selected to make a scenario for evaluation. The reduction volumes of four air pollution materials(CO, HC, NOX, PM) and three greenhouse gases($CO_2$, $CH_4$, $N_2O$) for the year 2027, which is the last target year, were calculated by utilizing both a travel demand forecasting model and variable composite emission factors with respect to future travel patterns. To estimate the relative effectiveness of reduction countermeasures, this study performed a super-efficiency analysis among the Data Envelopment Analysis models. It was found that expanding the participation in self car-free day program was the most superior reduction measurement with 1.879 efficiency points, followed by expansion of exclusive bus lanes and promotion of CNG hybrid bus diffusion. The results of this study do not represent the absolute data for prioritizing reduction countermeasures for mobile greenhouse gases and air pollution materials. However, in terms of presenting the direction for establishing reduction countermeasures, this study may contribute to policy selection for mobile emission reduction measures and the establishment of systematic mid- and long-term reduction measures.