• 대한공업교육학회지
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• v.31 no.2
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• pp.364-380
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• 2006

This paper presents a procedure for designing command to maneuver flexible structure with very little residual vibration, even in the presence of modeling errors. For the open loop maneuver, the various shaped profiles using multiple step inputs delayed in time are considered for robustness and compared with the responses of rigid body and flexible body in virtue of simulations and experiments. Input shaping generates vibration-reducing shaped commands through convolution of an impulse sequence with the desired command. A flexible model with a cylindrical hub and four symmetric appendages is considered to examine the responses to real plant, and to illustrate the effectiveness of the proposed shapers. The appendages are long and flexible, leading to low frequency vibration under any control action. It is shown by a series of simulation that a properly designed feedback controller with input shaper performs well, as compared with open loop controller with input shaper. The control objective is to achieve a fast settling time of residual vibration to flexible structure and robustness (insensitivity)to plant uncertainty, to eliminate residual vibration.

• Journal of KIISE:Databases
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• v.32 no.1
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• pp.71-85
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• 2005

Various researches on moving object modeling, uncertainty processing, and moving object indexing have been tarried out in the field of moving object databases. However. previous location tracking systems cannot efficiently retrieve location data of vehicles, because they manage all location information of vehicles using the conventional database. In this paper, we design the vehicle location management systen that is able to manage and retrieve vehicle locations efficiently in mobile environment. The proposed system consists of a server for managing vehicle locations and mobile clients. The system is able to not only process spatiotemporal queries related to locations of moving vehicles but also Provide moving vehicles' locations which are not stored in the system. The system is also able to manage vehicle location data effectively using a moving object index.

• The Transactions of the Korea Information Processing Society
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• v.3 no.3
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• pp.543-563
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• 1996

In this paper, we propose a Timed Fuzzy Petri Net(TFPN) model as a new model of real-time fuzzy control. The TFPN model, which is useful for fuzzy inference and fuzzy control is an integrated model of Timed PetriNet and Fuzzy Petri Net. Additionally, a Timed Fuzzy Control Language is defined as a textual specification model of fuzzy control rues, and proposed a TFPN modeling method. The TFPN model is a Petri Net formalism of fuzzy control systems. Execution rule is consisted of marking(i.e,fuzzyfication) and firing(i.e,inference and defuzzyfication) procedures. A simple case work by using TFPN model shows us computing time of inference and defuzzyfication is low and uncertainty and visibility of fuzzy control rule are modeled effectively.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.3
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• pp.372-377
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• 2011

This paper propose the robust stability algorithm for controlling a hybrid magnetic bearing system. The control object in the magnetic bearing system enables the rotor to rotate without any physical contact by using magnetic force. Generally, the system dynamics of the magnetic bearing system has severe nonlinearity and uncertainty so that it is not easy to obtain the control objective. For solving these problems, we propose the fuzzy modelling and robust control algorithm for hybrind magnetic bearing system. The sufficient conditions for robust controller are obtained in terms of solutions to linear matrix inequalities (LMIs). Simulation results for HMB are demonstrated to visualize the feasibility of the proposed method.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.22 no.1
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• pp.33-45
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• 2019

Compound disaster is the type that increases the impact affected by two or more hazard events, and attention to compound disaster and multi-hazards risk is growing due to potential damages which are difficult to predict. The objective of this study is to analyze the possible impacts of post-fire landslide scenario quantitatively by using TRIGRS (Transient Rainfall Infiltration and Grid-Based Regional Slope-Stability Analysis), a physics-based landslide model. In the case of wildfire, soil organic material and density are altered, and saturated hydraulic conductivity decrease because of soil exposed to high temperature. We have included the change of soil saturated hydraulic conductivity into the TRIGRS model through literature review. For a case study, we selected the area of $8km^2$ in Pyeongchang County. The landslide modeling process was calibrated before simulate the post-wildfire impact based on landslide inventory data to reduce uncertainty. As a result, the mean of the total factor of safety values in the case of landslide was 2.641 when rainfall duration is 1 hour with rainfall intensity of 100mm per day, while the mean value for the case of post-wildfire landslide was lower to 2.579, showing potential landslide occurrence areas appear more quickly in the compound disaster scenario. This study can be used to prevent potential losses caused by the compound disaster such as post-wildfire debris flow or landslides.

• Journal of Ecology and Environment
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• v.45 no.3
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• pp.130-142
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• 2021

Background: Climate change is occurring rapidly around the world, and is predicted to have a large impact on biodiversity. Various studies have shown that climate change can alter the geographical distribution of wild bees. As climate change affects the species distribution and causes range shift, the degree of range shift and the quality of the habitats are becoming more important for securing the species diversity. In addition, those pollinator insects are contributing not only to shaping the natural ecosystem but also to increased crop production. The distributional and habitat quality changes of wild bees are of utmost importance in the climate change era. This study aims to investigate the impact of climate change on distributional and habitat quality changes of five wild bees in northwestern regions of Iran under two representative concentration pathway scenarios (RCP 4.5 and RCP 8.5). We used species distribution models to predict the potential range shift of these species in the year 2070. Result: The effects of climate change on different species are different, and the increase in temperature mainly expands the distribution ranges of wild bees, except for one species that is estimated to have a reduced potential range. Therefore, the increase in temperature would force wild bees to shift to higher latitudes. There was also significant uncertainty in the use of different models and the number of environmental layers employed in the modeling of habitat suitability. Conclusion: The increase in temperature caused the expansion of species distribution and wider areas would be available to the studied species in the future. However, not all of this possible range may include high-quality habitats, and wild bees may limit their niche to suitable habitats. On the other hand, the movement of species to higher latitudes will cause a mismatch between farms and suitable areas for wild bees, and as a result, farmers will face a shortage of pollination from wild bees. We suggest that farmers in these areas be aware of the effects of climate change on agricultural production and consider the use of managed bees in the future.

• Structural Engineering and Mechanics
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• v.77 no.2
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• pp.197-215
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• 2021

Under a severe environment of multiple hazards such as earthquakes and winds, the life-cycle performance of engineering structures may inevitably be deteriorated due to the fatigue effect caused by long-term exposure to wind loads, which would further increase the structural vulnerability to earthquakes. This paper presents a framework for evaluating the lifetime structural seismic performance under the effect of wind-induced fatigue considering different sources of uncertainties. The seismic behavior of a high-rise steel-concrete composite frame with buckling-restrained braces (FBRB) during its service life is systematically investigated using the proposed approach. Recorded field data for the wind hazard of Fuzhou, Fujian Province of China from Jan. 1, 1980 to Mar. 31, 2019 is collected, based on which the distribution of wind velocity is constructed by the Gumbel model after comparisons. The OpenSees platform is employed to establish the numerical model of the FBRB and conduct subsequent numerical computations. Allowed for the uncertainties caused by the wind generation and structural modeling, the final annual fatigue damage takes the average of 50 groups of simulations. The lifetime structural performance assessments, including static pushover analyses, nonlinear dynamic time history analyses and fragility analyses, are conducted on the time-dependent finite element (FE) models which are modified in lines with the material deterioration models. The results indicate that the structural performance tends to degrade over time under the effect of fatigue, while the influencing degree of fatigue varies with the duration time of fatigue process and seismic intensity. The impact of wind-induced fatigue on structural responses and fragilities are explicitly quantified and discussed in details.

• Journal of Korean Society on Water Environment
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• v.37 no.3
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• pp.204-216
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• 2021

It is important to understand the factors influencing the temporal and spatial variability of water quality in order to establish an effective customized management strategy for contaminated aquatic ecosystems. In this study, the spatial diversity of the 5-year (2015 - 2019) average total phosphorus (TP) concentration observed in 40 Total Maximum Daily Loads unit-basins in the Nakdong River watershed was analyzed using 50 predictive variables of watershed characteristics, climate characteristics, land use characteristics, and soil characteristics. Cross-correlation analysis, a two-stage exhaustive search approach, and Bayesian inference were applied to identify predictors that best matched the time-averaged TP. The predictors that were finally identified included watershed altitude, precipitation in fall, precipitation in winter, residential area, public facilities area, paddy field, soil available phosphate, soil magnesium, soil available silicic acid, and soil potassium. Among them, it was found that the most influential factors for the spatial difference of TP were watershed altitude in watershed characteristics, public facilities area in land use characteristics, and soil available silicic acid in soil characteristics. This means that artificial factors have a great influence on the spatial variability of TP. It is expected that the proposed statistical modeling approach can be applied to the identification of major factors affecting the spatial variability of the temporal average state of various water quality parameters.

• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.247-258
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• 2021

Recently, organizations are demanding strict information security behavior from their employees. Strict information security policies and techniques can cause information security related stress. The purpose of this study is to present the negative effects of information security related techno stress and role stress that reduce knowledge sharing behavior and person-organization fit. The survey was conducted to people working in organizations with information security policies and system, and the research hypothesis was verified by structural equation modeling using 309 samples. As a result of the study, person-organization fit had a positive effect on knowledge sharing behavior, but role stress had a negative effect. And, techno-stress negatively affected the person-organization fit. Additionally, role ambiguity had a moderating effect between person-organization fit and knowledge sharing behavior. The implications of the study were to confirm the negative effects of information security related techno stress and role stress, and to suggest directions for minimizing negative behavior of insiders.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.36-48
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• 2022

As a valid numerical method to obtain a high-resolution result of a flow field, computational fluid dynamics (CFD) have been widely used to study coolant flow and heat transfer characteristics in fuel rod bundles. However, the time-consuming, iterative calculation of Navier-Stokes equations makes CFD unsuitable for the scenarios that require efficient simulation such as sensitivity analysis and uncertainty quantification. To solve this problem, a reduced-order model (ROM) based on proper orthogonal decomposition (POD) and machine learning (ML) is proposed to simulate the flow field efficiently. Firstly, a validated CFD model to output the flow field data set of the rod bundle is established. Secondly, based on the POD method, the modes and corresponding coefficients of the flow field were extracted. Then, an deep feed-forward neural network, due to its efficiency in approximating arbitrary functions and its ability to handle high-dimensional and strong nonlinear problems, is selected to build a model that maps the non-linear relationship between the mode coefficients and the boundary conditions. A trained surrogate model for modes coefficients prediction is obtained after a certain number of training iterations. Finally, the flow field is reconstructed by combining the product of the POD basis and coefficients. Based on the test dataset, an evaluation of the ROM is carried out. The evaluation results show that the proposed POD-ROM accurately describe the flow status of the fluid field in rod bundles with high resolution in only a few milliseconds.