• Journal of the Earthquake Engineering Society of Korea
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• v.6 no.4
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• pp.65-73
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• 2002

It has been recognized that the damage control must become a more explicit design consideration. In an effort to develop design methods based on performance it is clear that the evaluation of the nonlinear response is required. The methods available to the design engineer today are nonlinear time history analyses, monotonic static nonlinear analyses, or equivalent static analyses with simulated nonlinear influences. Some building codes propose the capacity spectrum method based on the nonlinear static analysis(pushover analysis) to determine the earthquake-induced demand given by the structure pushover curve. These procedures are conceptually simple but iterative and time consuming with some errors. This paper presents a nonlinear direct spectrum method(NDSM) to evaluate seismic performance of structures, without iterative computations, given by the structural initial elastic period and yield strength from the pushover analysis, especially for MDF(multi degree of freedom) systems. The purpose of this paper is to investigate the accuracy and confidence of this method from a point of view of various earthquakes and unloading stiffness degradation parameters. The conclusions of this study are as follows; 1) NDSM is considered as practical method because the peak deformations of nonlinear system of MDF by NDSM are almost equal to the results of nonlinear time history analysis(NTHA) for various ground motions. 2) When the results of NDSM are compared with those of NTHA. mean of errors is the smallest in case of post-yielding stiffness factor 0.1, static force by MAD(modal adaptive distribution) and unloading stiffness degradation factor 0.2~0.3.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.202-211
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• 2015

Companies build the factory automation system to improve management effectiveness and productivity as prime strategies for sustainable growth. But most companies undergo various trials and errors while carrying out the project without elaborate preparation stage for factory automation. In this study, we tried to verify what factors are critical to effectively building distribution automation system, which is a branch of factory automation system. A consulting model for setting up a Material Handling Automation System by utilizing the Stage-Gate Process, which is product development process was studied. 29 material handling automation projects carried out between the year 1990 to 2013 at K-Company were selected. Interviews with the project managers, operators and maintenance personnels, various records and current status of the projects were used as data for structural equations based on the Milan consulting model and existing researches of factory automation, CIM for material handling automation. Creating effective basis of production, material handling system and energy saving system with expert review, when preparing a material handling automation project, help promote the project planning thus contributing to the performance of the resulting system, which appears though rather weakly in our data. Also the effect of material handling automation can be enhanced through sufficient and effective links to the relevant environments such as production logistics management and automated warehouses. More detailed planning characteristics of project promotion or some time-series data of effective Material Handling Automation System could enhace furthur studies. We propose a consulting model for setting up an efficient material handling automation system.

• Journal of Venture Innovation
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• v.7 no.1
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• pp.17-39
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• 2024

The purpose of this study was to analyze the effect of the government's R&D support and the use of stock options by venture companies on the innovation of venture companies, that is, innovation capabilities and innovation performance. An empirical analysis was conducted using the partial least squares structural equation modeling (PLS-SEM) method using the data from the detailed survey of venture companies conducted on domestic venture confirmation companies. As a result of the analysis, it was found that the benefit of government R&D support had a positive (+) effect on strengthening the innovation capabilities of venture companies, and R&D support also had a positive (+) effect on the innovation performance of venture companies. Next, it was found that the use of stock options by venture companies had a positive (+) effect on the reinforcement of the innovation capabilities of companies and a positive (+) effect on the innovation performance of venture companies. In addition, it was found that the innovation capabilities of venture companies significantly mediate between the government's R&D support and the use of stock options by venture companies and the innovation performance of companies. These analysis results show that the government's R&D support and the use of stock option systems can play a meaningful role in the innovation of venture companies, and also show that the innovation capabilities of venture companies have an important meaning in the process of innovation. Therefore, it is necessary to continue the stance of R&D support for ventures and at the same time to introduce multi-faceted policy measures to support corporate capacity building, and legal and institutional maintenance and policy support to revitalize the stock option system need to be continuously provided.

• Journal of Intelligence and Information Systems
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• v.20 no.2
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• pp.59-71
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• 2014

System trading is becoming more popular among Korean traders recently. System traders use automatic order systems based on the system generated buy and sell signals. These signals are generated from the predetermined entry and exit rules that were coded by system traders. Most researches on system trading have focused on designing profitable entry and exit rules using technical indicators. However, market conditions, strategy characteristics, and money management also have influences on the profitability of the system trading. Unexpected price deviations from the predetermined trading rules can incur large losses to system traders. Therefore, most professional traders use strategy portfolios rather than only one strategy. Building a good strategy portfolio is important because trading performance depends on strategy portfolios. Despite of the importance of designing strategy portfolio, rule of thumb methods have been used to select trading strategies. In this study, we propose a SVM-based strategy portfolio management system. SVM were introduced by Vapnik and is known to be effective for data mining area. It can build good portfolios within a very short period of time. Since SVM minimizes structural risks, it is best suitable for the futures trading market in which prices do not move exactly the same as the past. Our system trading strategies include moving-average cross system, MACD cross system, trend-following system, buy dips and sell rallies system, DMI system, Keltner channel system, Bollinger Bands system, and Fibonacci system. These strategies are well known and frequently being used by many professional traders. We program these strategies for generating automated system signals for entry and exit. We propose SVM-based strategies selection system and portfolio construction and order routing system. Strategies selection system is a portfolio training system. It generates training data and makes SVM model using optimal portfolio. We make $m{\times}n$ data matrix by dividing KOSPI 200 index futures data with a same period. Optimal strategy portfolio is derived from analyzing each strategy performance. SVM model is generated based on this data and optimal strategy portfolio. We use 80% of the data for training and the remaining 20% is used for testing the strategy. For training, we select two strategies which show the highest profit in the next day. Selection method 1 selects two strategies and method 2 selects maximum two strategies which show profit more than 0.1 point. We use one-against-all method which has fast processing time. We analyse the daily data of KOSPI 200 index futures contracts from January 1990 to November 2011. Price change rates for 50 days are used as SVM input data. The training period is from January 1990 to March 2007 and the test period is from March 2007 to November 2011. We suggest three benchmark strategies portfolio. BM1 holds two contracts of KOSPI 200 index futures for testing period. BM2 is constructed as two strategies which show the largest cumulative profit during 30 days before testing starts. BM3 has two strategies which show best profits during testing period. Trading cost include brokerage commission cost and slippage cost. The proposed strategy portfolio management system shows profit more than double of the benchmark portfolios. BM1 shows 103.44 point profit, BM2 shows 488.61 point profit, and BM3 shows 502.41 point profit after deducting trading cost. The best benchmark is the portfolio of the two best profit strategies during the test period. The proposed system 1 shows 706.22 point profit and proposed system 2 shows 768.95 point profit after deducting trading cost. The equity curves for the entire period show stable pattern. With higher profit, this suggests a good trading direction for system traders. We can make more stable and more profitable portfolios if we add money management module to the system.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.34 no.6
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• pp.1731-1741
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• 2014

Recently, many overpasses, highway, and advanced transit systems have been constructed to distribute the traffic congestion, thus small size of curved bridges with small curvature such as ramp structures have been increasing. Many of early curved bridges had been constructed by using straight beams with curved slabs, but curved steel beams have replaced them due to the cost, aesthetic and the advantage in building the section form and manipulating the curvature of beams, thereby large portion of curved bridges were applied with steel box girders. However, steel box girder bridges needs comparatively high initial costs and continuous maintenance such as repainting, which is the one of the reason for increasing the cost. Moreover, I-type steel plate girder which is being studied by many researchers recently, seem to have problems in stability due to the low torsional stiffness, resulting from the section characteristics with thin plate used for web and open section forms. Therefore, in recent studies, researchers have proposed curved precast PSC girders with low cost and could secured safety which could replace the curved steel girder type bridges. Hence, this study developed a Smart Mold system to manufacture efficient curved precast PSC girders. And by using this mold system a 40 m 2-girder bridge was constructed for a static flexural test, to evaluate the safety and performance under ultimate load. At the manufacturing stage, each single girder showed problems in the stability due to the torsional moment, but after the girders were connected by cross beams and decks, the bridge successfully distributed the stress, thereby the stability was confirmed. The static loading test results show that the initial crack was observed at 1,400 kN when the design load was 450 kN, and the load at the allowable deflection by code was 1,800 kN, which shows that the safety and usability of the curved precast PSC bridge manufactured by Smart Mold system is secured.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.19-36
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• 2015

Social media is an emerging issue in content services and in current business environment. YouTube is the most representative social media service in the world. YouTube is different from other conventional content services in its open user participation and contents creation methods. To promote a content in YouTube, it is important to understand the diffusion phenomena of contents and the network structural characteristics. Most previous studies analyzed impact factors of contents diffusion from the view point of general behavioral factors. Currently some researchers use network structure factors. However, these two approaches have been used separately. However this study tries to analyze the general impact factors on the view count and content based network structures all together. In addition, when building a content based network, this study forms the network structure by analyzing user comments on 22,370 contents of YouTube not based on the individual user based network. From this study, we re-proved statistically the causal relations between view count and not only general factors but also network factors. Moreover by analyzing this integrated research model, we found that these factors affect the view count of YouTube according to the following order; Uploader Followers, Video Age, Betweenness Centrality, Comments, Closeness Centrality, Clustering Coefficient and Rating. However Degree Centrality and Eigenvector Centrality affect the view count negatively. From this research some strategic points for the utilizing of contents diffusion are as followings. First, it is needed to manage general factors such as the number of uploader followers or subscribers, the video age, the number of comments, average rating points, and etc. The impact of average rating points is not so much important as we thought before. However, it is needed to increase the number of uploader followers strategically and sustain the contents in the service as long as possible. Second, we need to pay attention to the impacts of betweenness centrality and closeness centrality among other network factors. Users seems to search the related subject or similar contents after watching a content. It is needed to shorten the distance between other popular contents in the service. Namely, this study showed that it is beneficial for increasing view counts by decreasing the number of search attempts and increasing similarity with many other contents. This is consistent with the result of the clustering coefficient impact analysis. Third, it is important to notice the negative impact of degree centrality and eigenvector centrality on the view count. If the number of connections with other contents is too much increased it means there are many similar contents and eventually it might distribute the view counts. Moreover, too high eigenvector centrality means that there are connections with popular contents around the content, and it might lose the view count because of the impact of the popular contents. It would be better to avoid connections with too powerful popular contents. From this study we analyzed the phenomenon and verified diffusion factors of Youtube contents by using an integrated model consisting of general factors and network structure factors. From the viewpoints of social contribution, this study might provide useful information to music or movie industry or other contents vendors for their effective contents services. This research provides basic schemes that can be applied strategically in online contents marketing. One of the limitations of this study is that this study formed a contents based network for the network structure analysis. It might be an indirect method to see the content network structure. We can use more various methods to establish direct content network. Further researches include more detailed researches like an analysis according to the types of contents or domains or characteristics of the contents or users, and etc.