• Geomechanics and Engineering
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• v.29 no.3
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• pp.207-218
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• 2022

In submerged floating tunnels (SFTs), a next-generation maritime transportation infrastructure, the tunnel module floats in water due to buoyancy. For the effective and economical use of SFTs, connection with the ground is inevitable, but the stability of the shore connection is weak due to stress concentration caused by the displacement difference between the subsea bored tunnel and the SFT. The use of an elastic joint has been proposed as a solution to solve the stability problem, but it changes the dynamic characteristics of the SFT, such as natural frequency and mode shape. In this study, the finite element method (FEM) was used to simulate the elastic joints in shore connections, assuming that the ground is a hard rock without displacement. In addition, a small-scale model test was performed for FEM model validation. A parametric study was conducted on the resonance behavior such as the natural frequency change and velocity, stress, and reaction force distribution change of the SFT system by varying the joint stiffness under loading conditions of various frequencies and directions. The results indicated that the natural frequency of the SFT system increased as the stiffness of the elastic joint increased, and the risk of resonance was the highest in the low-frequency environment. Moreover, stress concentration was observed in both the SFT and the shore connection when resonance occurred in the vertical mode. The results of this study are expected to be utilized in the process of quantitative research such as designing elastic joints to prevent resonance in the future.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.59 no.1
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• pp.55-64
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• 2023

Gas turbine engines are widely used as prime movers of generator and propulsion system in warships. This study addresses the problem of designing a DS-based PID controller for speed control of the LM-2500 gas turbine engine used for propulsion in warships. To this end, we first derive a dynamic model of the LM-2500 using actual sea trail data. Next, the PRC (process reaction curve) method is used to approximate the first-order plus time delay (FOPTD) model, and the DS-based PID controller design technique is proposed according to approximation of the time delay term. The proposed controller conducts set-point tracking simulation using MATLAB (2016b), and evaluates and compares the performance index with the existing control methods. As a result of simulation at each operating point, the proposed controller showed the smallest in %OS, which means that the rpm does not change rapidly. In addition, IAE and IAC were also the smallest, showing the best result in error performance and controller effort.

• International Journal of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.267-277
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• 2024

This paper explores the use of machine learning in game production to create goal-oriented, realistic animations for skeleton monsters. The purpose of this research is to enhance realism by implementing intelligent movements in monsters within game development. To achieve this, we designed and implemented a learning model for skeleton monsters using reinforcement learning algorithms. During the machine learning process, various reward conditions were established, including the monster's speed, direction, leg movements, and goal contact. The use of configurable joints introduced physical constraints. The experimental method validated performance through seven statistical graphs generated using machine learning methods. The results demonstrated that the developed model allows skeleton monsters to move to their target points efficiently and with natural animation. This paper has implemented a method for creating game monster animations using machine learning, which can be applied in various gaming environments in the future. The year 2024 is expected to bring expanded innovation in the gaming industry. Currently, advancements in technology such as virtual reality, AI, and cloud computing are redefining the sector, providing new experiences and various opportunities. Innovative content optimized for this period is needed to offer new gaming experiences. A high level of interaction and realism, along with the immersion and fun it induces, must be established as the foundation for the environment in which these can be implemented. Recent advancements in AI technology are significantly impacting the gaming industry. By applying many elements necessary for game development, AI can efficiently optimize the game production environment. Through this research, We demonstrate that the application of machine learning to Unity and game engines in game development can contribute to creating more dynamic and realistic game environments. To ensure that VR gaming does not end as a mere craze, we propose new methods in this study to enhance realism and immersion, thereby increasing enjoyment for continuous user engagement.

• Journal of Distribution Science
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• v.11 no.6
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• pp.59-65
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• 2013

Purpose - Studies of mechanism as a competitive strategy, a relatively new field in the study of strategic management research, has recently drawn the attention of the business management scholars. The literature has so far proposed the subjective-based view, environment-based view, and the resource-based view in its analyses of firm management. Hence, it is highly likely for the firm management to be reasonably thought of as a combination of and interaction among the three key elements of subject, environment, and resources this is the mechanism-based view (MBV). It is reasonable to consider firm management to be the combination of and interaction among the three key elements of subject, environment, and resources. The overall dynamic process that integrates these three elements and creates functional harmony is identified as the mechanism, the principle of firm management. Much of the extant literatures on MBV has mainly focused on case studies, a qualitative approach prone to subjectivity of the researcher, although the intuition from the study may lead to meaningful insights into a firm-specific mechanism. This study's focus is also on case analysis, but it still attempts a quantitative approach in order to reach a scientific and systematic understanding of the MBV. Research design, data, and methodology - I used both a qualitative and quantitative approach to a single model, given the complexity of the innovation processes. I conducted in-depth interviews with POSCO employees-20 from general management, two from human resources, eight from information technology, five from finance and accounting, and five from production and logistics management. Once the innovative events were selected, the interview results were double-checked by the interviewees themselves to ensure the accuracy of the answers recorded. Based on the interview, I then conducted statistical validation using the survey results as well. Results - This study analyzes the building process of innovation and the effect of the mechanism pattern on innovation by examining the case of POSCO, which has survived over the past 21 years. I apply a new analytical tool to study mechanism innovation types, perform a new classification, and describe the interrelationships among the mechanism factors. This process allows me to see how the "Subject"factor interacts with the other factors. I found that, in the innovation process of the adoption stage, Subject had a mediating effect but that the mediating effect of resource and performance was smaller than the effect of Subject on performance alone. During the implementation stage, the mediating effect of Subject increased. Conclusion - Therefore, I have confirmed that the subject utilizes resources reasonably and efficiently. I have also advanced mechanism studies: whereas the field's research methods have been largely confined to single case studies, I have used both qualitative and quantitative methods to examine the relationships among mechanisms.

• World Technopolis Review
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• v.4 no.1
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• pp.11-22
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• 2015

Globalization, increasing technological advancements and dynamic knowledge diffusion are moving our world closer together at a unique scale and pace. At the same time, our rapidly changing society is confronted with major challenges ranging from demographic to economic ones; challenges that necessitate highly innovative solutions, forcing us to reconsider the way that we actually innovate and create shared value. As such the linear, centralized innovation models of the past need to be replaced with new approaches; approaches that are based upon an open and collaborative, global network perspective where all innovation actors strategically network and collaborate, openly distribute their ideas and co-innovate/co-create in a global context utilizing our society's full innovation potential (Innovation 4.0 - Open Innovation 2.0). These emerging innovation paradigms create "an opportunity for a new entrepreneurial renaissance which can drive a Cambrian like explosion of sustainable wealth creation" (Curley 2013). Thus, in order to materialize this entrepreneurial renaissance, it is critical not only to value but also to actively employ this new innovation paradigms so as to derive community-driven shared value that stems from global innovation networks. This paper argues that there is a gap in existing business incubation model that needs to be filled, in that the innovation and entrepreneurship community cannot afford to ignore the emerging innovation paradigms and rely upon closed incubation models but has to adopt an "open incubation" (Ziouvelou 2013). The open incubation model is based on the principles of open innovation, crowdsourcing and co-creation of shared value and enables individual users and innovation stakeholders to strategically network, find collaborators and partners, co-create ideas and prototypes, share their ideas/prototypes and utilize the wisdom of the crowd to assess the value of these project ideas/prototypes, while at the same time find connections/partners, business and technical information, knowledge on start-up related topics, online tools, online content, open data and open educational material and most importantly access to capital and crowd-funding. By introducing a new incubation phase, namely the "interest phase", open incubation bridges the gap between entrepreneurial need and action and addresses the wantpreneurial needs during the innovation conception phase. In this context one such ecosystem that aligns fully with the open incubation model and theoretical approach, is the VOICE ecosystem. VOICE is an international, community-driven innovation and entrepreneurship ecosystem based on open innovation, crowdsourcing and co-creation principles that has no physical location as opposed to traditional business incubators. VOICE aims to tap into the collective intelligence of the crowd and turn their entrepreneurial interest or need into a collaborative project that will result into a prototype and to a successful "crowd-venture".

• Computers and Concrete
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• v.22 no.3
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• pp.337-353
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• 2018

The present study focuses on examining the structural behaviour of steel-fibre-reinforced concrete (SFRC) beams under high rates of loading largely associated with impact problems. Fibres are added to the concrete mix to enhance ductility and energy absorption, which is important for impact-resistant design. A simple, yet practical non-linear finite-element analysis (NLFEA) model was used in the present study. Experimental static and impact tests were also carried out on beams spanning 1.3 meter with weights dropped from heights of 1.5 m and 2.5 m, respectively. The numerical model realistically describes the fully-brittle tensile behaviour of plain concrete as well as the contribution of steel fibres to the post-cracking response (the latter was allowed for by conveniently adjusting the constitutive relations for plain concrete, mainly in uniaxial tension). Suitable material relations (describing compression, tension and shear) were selected for SFRC and incorporated into ABAQUS software Brittle Cracking concrete model. A more complex model (i.e., the Damaged Plasticity concrete model in ABAQUS) was also considered and it was found that the seemingly simple (but fundamental) Brittle Cracking model yielded reliable results. Published data obtained from drop-weight experimental tests on RC and SFRC beams indicates that there is an increase in the maximum load recorded (compared to the corresponding static one) and a reduction in the portion of the beam span reacting to the impact load. However, there is considerable scatter and the specimens were often tested to complete destruction and thus yielding post-failure characteristics of little design value and making it difficult to pinpoint the actual load-carrying capacity and identify the associated true ultimate limit state (ULS). To address this, dynamic NLFEA was employed and the impact load applied was reduced gradually and applied in pulses to pinpoint the actual failure point. Different case studies were considered covering impact loading responses at both the material and structural levels as well as comparisons between RC and SFRC specimens. Steel fibres were found to increase the load-carrying capacity and deformability by offering better control over the cracking process concrete undergoes and allowing the impact energy to be absorbed more effectively compared to conventional RC members. This is useful for impact-resistant design of SFRC beams.

• Journal of the Korean earth science society
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• v.39 no.3
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• pp.211-227
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• 2018

This study evaluates the prediction skills of stratospheric polar vortex intensification events (VIEs) in Global Seasonal Forecasting System (GloSea5) model, an operational subseasonal-to-seasonal (S2S) prediction model of Korea Meteorological Administration (KMA). The results show that the prediction limits of VIEs, diagnosed with anomaly correlation coefficient (ACC) and mean squared skill score (MSSS), are 13.6 days and 18.5 days, respectively. These prediction limits are mainly determined by the eddy error, especially the large-scale eddy phase error from the eddies with the zonal wavenumber 1. This might imply that better prediction skills for VIEs can be obtained by improving the model performance in simulating the phase of planetary scale eddy. The stratospheric prediction skills, on the other hand, tend to not affect the tropospheric prediction skills in the analyzed cases. This result may indicate that stratosphere-troposphere dynamic coupling associated with VIEs might not be well predicted by GloSea5 model. However, it is possible that the coupling process, even if well predicted by the model, cannot be recognized by monotonic analyses, because intrinsic modes in the troposphere often have larger variability compared to the stratospheric impact.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.3
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• pp.568-576
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• 2003

This paper proposes a moving object tracking algorithm by using hierarchical search method in dynamic scenes. Proposed algorithm is based on two main steps: generation step of initial model from different pictures, and tracking step of moving object under the time-yawing scenes. With a series of this procedure, tracking process is not only stable under far distance circumstance with respect to the previous frame but also reliable under shape variation from the 3-dimensional(3D) motion and camera sway, and consequently, by correcting position of moving object, tracking time is relatively reduced. Partial Hausdorff distance is also utilized as an estimation function to determine the similarity between model and moving object. In order to testify the performance of proposed method, the extraction and tracking performance have tested using some kinds of moving car in dynamic scenes. Experimental results showed that the proposed algorithm provides higher performance. Namely, matching order is 28.21 times on average, and considering the processing time per frame, it is 53.21ms/frame. Computation result between the tracking position and that of currently real with respect to the root-mean-square(rms) is 1.148. In the occasion of different vehicle in terms of size, color and shape, tracking performance is 98.66%. In such case as background-dependence due to the analogy to road is 95.33%, and total average is 97%.

• Korean Chemical Engineering Research
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• v.53 no.2
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• pp.150-155
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• 2015

Recently, LNG receiving terminals have been widely constructed and expanded for an increase in LNG demand. Selection of the storage tank for send-out and estimation of send-out flow rate have significant influence to process operation and economics. In this study, a send-out flow rate of each storage tank is optimized in order to minimize the total BOG generation rate. Considering a size and characteristic of each storage tanks, BOG flow rates are estimated using a dynamic simulation with varying liquid levels in the tanks. The regression model is developed fitting BOG flow rates and tank liquid levels, which are boil off rate model to predict BOG flow rates with particular level data. The objective function and constraints including required total send-out flow rate and level limit in the tanks are formulated to optimize a send-out flow rate of each tank. This method for optimization of send-out operation is applied to the Incheon LNG receiving terminal considering two scenarios for various liquid levels and maximum and minimum required send-out flow rates. For maximum required send-out flow rate, this method achieves BOG reduction of 9% comparing with assumed conventional operation.

• Journal of Korea Port Economic Association
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• v.27 no.3
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• pp.41-64
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• 2011

This article investigates the interrelationships in daily returns using fractionally integrated error correction term and volatilities using constant conditional correlation and dynamic conditional correlation GARCH with asymmetries between Capesize and Panamax markets. Our findings are as follows. First, for the fractionally cointegrated error correction model, there is a unidirectional relationship in returns from the Panamax market to the Capesize market, but a bidirectional causal relationship prevails for the traditional error correction models. Second, the coefficients for the error correction term are all statistically significant. Of particular interest are the signs of the estimates for the error correction term, which are all negative for the Capesize return equation and all positive for the Panamax return. Third, there are bidirectional volatility spillovers between both markets and the direction of the information flow seems to be stronger from Panamax to Capesize. Fourth, the coefficients for the asymmetric term are all significantly positive in the Capesize market, but the Panamax market does not have a significant effect. However, the coefficients for the asymmetric term are all significant, implying that the leverage effect does exist in the Capesize and Panamax markets.