• Journal of the Korean Society for Railway
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• v.20 no.4
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• pp.521-528
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• 2017

In this study, vertical loading tests were conducted to investigate the nonlinear behaviors of the fastening systems that have generally been used in the concrete track of domestic railway lines. Nonlinear load-displacement curve models were derived based on the test results. The uplift forces generated in the fastening systems were evaluated by applying the derived nonlinear models as well as the existing linear models. The influence of the factors on the maximum uplift force of the fastening system was analyzed through a parameter study on the distance between neighboring sleepers, the horizontal distance between the center of the bearing and the nearest fastening system from the deck end, and the height of the bridge girder. From the evaluation results it is known that, for economical track and bridge design, due to deck end deformation, it is necessary to consider the nonlinear behavior of the fastening system in the calculation of the uplift force of the fastening systems.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.4
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• pp.1786-1795
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• 2011

The trajectory control for omni-directional mobile robot is not easy. Especially, the tracking control which system uncertainty problem is included is much more difficult. This paper develops trajectory controller of 3-wheels omni-directional mobile robot using fuzzy multi-layered algorithm. The fuzzy control method is able to solve the problems of classical adaptive controller and conventional fuzzy adaptive controllers. It explains the architecture of a fuzzy adaptive controller using the robust property of a fuzzy controller. The basic idea of new adaptive control scheme is that an adaptive controller can be constructed with parallel combination of robust controllers. This new adaptive controller uses a fuzzy multi-layered architecture which has several independent fuzzy controllers in parallel, each with different robust stability area. Out of several independent fuzzy controllers, the most suited one is selected by a system identifier which observes variations in the controlled system parameter. This paper proposes a design procedure which can be carried out mathematically and systematically from the model of a controlled system; related mathematical theorems and their proofs are also given. Finally, the good performance of the developed mobile robot is confirmed through live tests of path control task.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.476-482
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• 2019

Regulatory protocols such as the Convention on Climate Change and the regulation of greenhouse gas emissions act as catalysts for the development of high-efficiency energy equipment and the efficient use of energy. Among the fields where energy consumption is high, the electric heating equipment is not efficient. The electric boiler mainly uses a method of circulating water by contacting the heater. When the existing electric boiler is used, the water minerals are contacted with the high-temperature heater to be carbonized and adsorbed, thereby promoting the corrosion of the heater and lowering the efficiency of the heater. For this reason, an electric induction boiler, which has high energy efficiency and is applied to an induction heating system that can uniformly heat the object to be heated rather than conduction or convection heating, is in the limelight. This method induces a boiler pipe And it is recognized as an alternative that can solve the problem that occurs when heating is performed by direct heating. Despite the fact that research on induction heating has been conducted for a relatively long period of time, there have been few studies on the electrothermal technology using induction heating. Therefore, in this paper, to improve the heat efficiency of electric induction boiler, the influence of the cross sectional area, number of windings and winding layers is analyzed by finite element method through parametric study method. The method of finding the design point which maximizes the total loss is proposed by the alternating winding design method which can maximize the heat generation by analyzing copper and iron losses.

• Ecology and Resilient Infrastructure
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• v.8 no.4
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• pp.223-232
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• 2021

In general, stormwater flows to the road surface, especially in urban areas, and it is discharged through the drainage grate inlets on roads. The appropriate evaluation of the road drainage capacity is essential not only in the design of roads and inlets but also in the design of sewer systems. However, the method of road surface flow analysis that reflects the topographical and hydraulic conditions might not be fully developed. Therefore, the enhanced method of road surface flow analysis should be presented by investigating the existing analysis method such as the flow analysis module (uniform; varied) and the flow travel time (critical; fixed). In this study, the algorithm based on varied and uniform flow analysis was developed to analyze the flow pattern of road surface. The numerical analysis applied the uniform and varied flow analysis module and travel time as parameters were conducted to estimate the characteristics of rainfall-runoff in various road conditions using the developed algorithm. The width of the road (two-lane (6 m)) and the slope of the road (longitudinal slope of road 1 - 10%, transverse slope of road 2%, and transverse slope of gutter 2 - 10%) was considered. In addition, the flow of the road surface is collected from the gutter along the road slope and drained through the gutter in the downstream part, and the width of the gutter was selected to be 0.5 m. The simulation results were revealed that the runoff characteristics were affected by the road slope conditions, and it was found that the varied flow analysis module adequately reflected the gutter flow which is changed along the downstream caused by collecting of road surface flow at the gutter. The varied flow analysis module simulated 11.80% longer flow travel time on average (max. 23.66%) and 4.73% larger total road surface discharge on average (max. 9.50%) than the uniform flow analysis module. In order to accurately estimate the amount of runoff from the road, it was appropriate to perform flow analysis by applying the critical duration and the varied flow analysis module. The developed algorithm was expected to be able to be used in the design of road drainage because it was accurately simulated the runoff characteristics on the road surface.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.25 no.3
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• pp.147-153
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• 2013

There exist various types of the WEC (Wave Energy Converter), and among them, the point absorber is the most popularly investigated type. However, it is difficult to find examples of systematically measured data analysis for the design of the point absorber type of power buoy in the world. The study investigates the wave load acting on the point absorber type resonance power buoy wave energy extraction system proposed by Kweon et al. (2010). This study analyzes the time series spectra with respect to the three-year wave data (2002.05.01~2005.03.29) measured using the pressure type wave gage at the seaside of north breakwater of Hupo harbor located in the east coast of the Korean peninsula. From the analysis results, it could be deduced that monthly wave period and wave height variations were apparent and that monthly wave powers were unevenly distributed annually. The average wave steepness of the usual wave was 0.01, lower than that of the wind wave range of 0.02-0.04. The mode of the average wave period has the value of 5.31 sec, while mode of the wave height of the applicable period has the value of 0.29 m. The occurrence probability of the peak period is a bi-modal type, with a mode value between 4.47 sec and 6.78 sec. The design wave period can be selected from the above four values of 0.01, 5.31, 4.47, 6.78. About 95% of measured wave heights are below 1 m. Through this study, it was found that a resonance power buoy system is necessary in coastal areas with low wave energy and that the optimal design for overcoming the uneven monthly distribution of wave power is a major task in the development of a WEF (Wave Energy Farm). Finding it impossible to express the average spectrum of the usual wave in terms of the standard spectrum equation, this study proposes a new spectrum equation with three parameters, with which basic data for the prediction of the power production using wave power buoy and the fatigue analysis of the system can be given.

• Korean Security Journal
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• no.42
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• pp.7-36
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• 2015

This study aims at analyzing difference of social Security network, Community unity and local government trust according to socio-demographical features, exploring the relation of social Security network, Community unity and local government trust according to socio-demographical features, presenting results between each variable as a model and verifying the property of mutual ones. This study sampled general citizens in Gwangju for about 15 days Aug. 15 through Aug. 30, 2014, distributed total 450 copies using cluster random sampling, gathered 438 persons, 412 persons of whom were used for analysis. This study verified the validity and credibility of the questionnaire through an experts' meeting, preliminary test, factor analysis and credibility analysis. The credibility of questionnaire was ${\alpha}=.809{\sim}{\alpha}=.890$. The inout data were analyzed by study purpose using SPSSWIN 18.0, as statistical techniques, factor analysis, credibility analysis, correlation analysis, independent sample t verification, ANOVA, multi-regression analysis, path analysis etc. were used. the findings obtained through the above study methods are as follows. First, building a social Security network has an effect on Community institution. That is, the more activated a, the higher awareness on institution. the more activated street CCTV facilities, anti-crime design, local government Security education, the higher the stability. Second, building a social Security network has an effect on trust of local government. That is, the activated local autonomous anti-crime activity, anti-crime design. local government's Security education, police public oder service, the more increased trust of policy, service management, busines performance. Third, Community unity has an effect on trust of local government. That is, the better Community institution is achieved, the higher trust of policy. Also the stabler Community institution, the higher trust of business performance. Fourth, building a social Security network has a direct or indirect effect on Community unity and local government trust. That is, social Security network has a direct effect on trust of local government, but it has a higher effect through Community unity of parameter. Such results showed that Community unity in Gwangju Region is an important factor, which means it is an important variable mediating building a social Security network and trust of local government. To win trust of local residents, we need to prepare for various cultural events and active communication space and build a social Security network for uniting them.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.2
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• pp.19-24
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• 2020

The interest in renewable energy is increasing due to the depletion of fossil fuels. In particular, active research on wave power, which is highly predictable and abundant, is being conducted. The coaxial accelerator-type wave power generator used in this study was designed to improve the power generation efficiency by converting bidirectional linear motion into a rotational force. In an offshore engineering basin, waves were generated, and case tests were performed according to the wave period and wave height. The experimental results were verified by the theoretical method related to the frequency response, and the overall trend was confirmed to be consistent. These results are expected to be useful in estimating the power of wave generators and designing parameters to improve the efficiency of wave energy in the design stage before manufacturing. In addition, the manufacturer can predict the wave energy efficiency of wave generators, which can reduce the development time and cost by preventing trial and error processes.

• Journal of Korean Tunnelling and Underground Space Association
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• v.20 no.2
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• pp.513-525
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• 2018

A 3 dimensional numerical analysis for shield TBM tunnel should take into account various characteristics of the shield TBM excavation, such as gap, tail void, segment installation, and backfill injection. However, analysis method considering excavation characteristics are generally mixed with various method, resulting in concern of consistency and reliability degradation of the analytical results. In this paper, a parametric study is carried out by using actually measured ground settlement data on various methods that can be used for 3 dimensional numerical analysis of shield TBM tunneling. As a result, we have analyzed and arranged an analytical method to predict similarly the behavior of ground settlement and tunnel face pressure at the design stage. Skin plate pressure, backfill pressure and soil model have been identified as the most significant influences on the ground settlement. The grout pressure model is considered to be applicable when there is no volume loss information on the excavated ground, such as seabed tunnels, or when it is important to identify the behavior around a tunnel, such as surface settlement as well as face pressure. And it is considered that designers can use these guidelines as a base material to perform a reasonable 3 dimensional numerical analysis that reflects the ground conditions and the features of the shield TBM tunneling.

• Korean Chemical Engineering Research
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• v.57 no.5
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• pp.628-636
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• 2019

In various industrial processes, piping serves as a link between unit processes and is an essential installation for internal flow. Therefore, the optimum design of the piping system is very important in terms of safety and cost, which requires the estimation of the pressure drop, flow rate, pipe size, etc. in the piping system. In this study, we developed a software that determines pressure drop, flow rate, and pipe size when any two of these design variables are known. We categorized the flows into single phase, homogeneous two phase, and separated two phase flows, and applied suitable calculation models accordingly. We also constructed a system library for the calculation of the pipe material, relative roughness, fluid property, and friction coefficients to minimize user input. We further created a costing library according to the piping material for the calculation of the investment cost of the pipe per unit length. We implemented all these functions in an integrated environment using a graphical user interface for user convenience, and C # programming language. Finally, we verified the accuracy of the software using literature data and examples from an industrial process with obtained deviations of 1% and 8.8% for the single phase and two-phase models.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.147-168
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• 2017

There have been many studies on accurate stock market forecasting in academia for a long time, and now there are also various forecasting models using various techniques. Recently, many attempts have been made to predict the stock index using various machine learning methods including Deep Learning. Although the fundamental analysis and the technical analysis method are used for the analysis of the traditional stock investment transaction, the technical analysis method is more useful for the application of the short-term transaction prediction or statistical and mathematical techniques. Most of the studies that have been conducted using these technical indicators have studied the model of predicting stock prices by binary classification - rising or falling - of stock market fluctuations in the future market (usually next trading day). However, it is also true that this binary classification has many unfavorable aspects in predicting trends, identifying trading signals, or signaling portfolio rebalancing. In this study, we try to predict the stock index by expanding the stock index trend (upward trend, boxed, downward trend) to the multiple classification system in the existing binary index method. In order to solve this multi-classification problem, a technique such as Multinomial Logistic Regression Analysis (MLOGIT), Multiple Discriminant Analysis (MDA) or Artificial Neural Networks (ANN) we propose an optimization model using Genetic Algorithm as a wrapper for improving the performance of this model using Multi-classification Support Vector Machines (MSVM), which has proved to be superior in prediction performance. In particular, the proposed model named GA-MSVM is designed to maximize model performance by optimizing not only the kernel function parameters of MSVM, but also the optimal selection of input variables (feature selection) as well as instance selection. In order to verify the performance of the proposed model, we applied the proposed method to the real data. The results show that the proposed method is more effective than the conventional multivariate SVM, which has been known to show the best prediction performance up to now, as well as existing artificial intelligence / data mining techniques such as MDA, MLOGIT, CBR, and it is confirmed that the prediction performance is better than this. Especially, it has been confirmed that the 'instance selection' plays a very important role in predicting the stock index trend, and it is confirmed that the improvement effect of the model is more important than other factors. To verify the usefulness of GA-MSVM, we applied it to Korea's real KOSPI200 stock index trend forecast. Our research is primarily aimed at predicting trend segments to capture signal acquisition or short-term trend transition points. The experimental data set includes technical indicators such as the price and volatility index (2004 ~ 2017) and macroeconomic data (interest rate, exchange rate, S&P 500, etc.) of KOSPI200 stock index in Korea. Using a variety of statistical methods including one-way ANOVA and stepwise MDA, 15 indicators were selected as candidate independent variables. The dependent variable, trend classification, was classified into three states: 1 (upward trend), 0 (boxed), and -1 (downward trend). 70% of the total data for each class was used for training and the remaining 30% was used for verifying. To verify the performance of the proposed model, several comparative model experiments such as MDA, MLOGIT, CBR, ANN and MSVM were conducted. MSVM has adopted the One-Against-One (OAO) approach, which is known as the most accurate approach among the various MSVM approaches. Although there are some limitations, the final experimental results demonstrate that the proposed model, GA-MSVM, performs at a significantly higher level than all comparative models.