• The Journal of the Korea Contents Association
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• v.13 no.5
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• pp.253-261
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• 2013

This study analyzed the preparation characteristics for old age of the baby boomers by the framework of the multi-pillar pension system. Analysis results are as follows. First, multi-pillar pension system's subscription rates of baby boomers was public pension 59%, private pension 11.5% and retirement pension 1.5%. The baby boomers isn't ready for old age life. Second, women and people with the low level of education are less prepared for old age. Third, people in a bad health state are less prepared for old age. Forth, low-income people are less prepared for old age. We must support baby boomers' preparations for old age by establishing income security system for old age. We must establish public pension support policy for the people of the low level of education and economic hierarchy, women, bad health status people, and must introduce universal old-age allowance policy for guaranteeing the minimum income of baby boomers.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.6
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• pp.488-496
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• 2015

This paper proposes a framework to determine the routes of multiple unmanned aerial vehicles (UAVs) to conduct multiple tasks in different locations considering the survivability of the vehicles. The routing problem can be formulated as the vehicle routing problem (VRP) with different cost matrices representing the trade-off between the safety of the UAVs and the mission completion time. The threat level for a UAV at a certain location was modeled considering the detection probability and the shoot-down probability. The minimal-cost path connecting two locations considering the threat level and the flight distance was obtained using the Dijkstra algorithm in hexagonal cells. A case study for determining the optimal routes for a persistent multi-UAVs surveillance and reconnaissance missions given multiple enemy bases was conducted and its results were discussed.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.42 no.2
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• pp.108-118
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• 2014

On the optimization design problem using surrogate model, it requires considerable number of sampling points to construct a surrogate model which retains the accuracy. As an alternative to reduce construction cost of the surrogate model, Variable-Fidelity Modeling(VFM) technique, where correct high fidelity model based on the low fidelity surrogate model is introduced. In this study, hierarchical kriging model for variable-fidelity surrogate modeling is used and an optimization framework with multi-objective genetic algorithm(MOGA) is presented. To prove the feasibility of this framework, airfoil design optimization process is performed for the transonic region. The parameters of PARSEC are used to design variables and the optimization process is performed in case of varying number of grid and varying fidelity. The results showed that pareto front of all variable-fidelity models are similar with its single-level of fidelity model and calculation time is considerably reduced. Based on computational results, it is shown that VFM is a more efficient way and has an accuracy as high as that single-level of fidelity model optimization.

• Journal of Korea Water Resources Association
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• v.39 no.10 s.171
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• pp.867-880
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• 2006

Hydrological models with many parameters and complex model structures require a powerful and detailed model calibration/validation scheme. In this study, we proposed a multi-variable and multi-site calibration and validation framework for the Soil Water Assessment Tool (SWAT) model applied in the Gap-cheon catchment located downstream of the Geum river basin. The sensitivity analysis conducted before main calibration helped understand various hydrological processes and the characteristics of subcatchments by identifying sensitive parameters in the model. In addition, the model's parameters were estimated based on existing data prior to calibration in order to increase the validity of model. The Nash-Sutcliffe coefficients and correlation coefficient were used to estimate compare model output with the observed streamflow data: $R_{eff}\;and\;R^2$ ranged 0.41-0.84 and 0.5-0.86, respectively, at the Heuduck station. Model reproduced baseflow estimated using recursive digital filter except for 2-5% overestimation at the Sindae and Boksu stations. Model also reproduced the temporal variability and fluctuation magnitude of observed groundwater levels with $R^2$ of 0.71 except for certain periods. Therefore, it was concluded that the use of multi-variable and multi-site method provided high confidence for the structure and estimated parameter values of the model.

• Journal of the Institute of Electronics and Information Engineers
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• v.52 no.12
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• pp.142-149
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• 2015

Most of the mono-camera based lane detection systems are fragile on poor illumination conditions. In order to compensate limitations of single sensor utilization, lane information fusion system using multiple lane sensors is an alternative to stabilize performance and guarantee high precision. However, conventional fusion schemes, which only concerns object detection, are inappropriate to apply to the lane information fusion. Even few studies considering lane information fusion have dealt with limited aids on back-up sensor or omitted cases of asynchronous multi-rate and coverage. In this paper, we propose a lane information fusion scheme utilizing multiple lane sensors with different coverage and cycle. The precise lane information fusion is achieved by the proposed fusion framework which considers individual ranging capability and processing time of diverse types of lane sensors. In addition, a novel lane estimation model is proposed to synchronize multi-rate sensors precisely by up-sampling spare lane information signals. Through quantitative vehicle-level experiments with around view monitoring system and frontal camera system, we demonstrate the robustness of the proposed lane fusion scheme.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5301-5323
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• 2017

Small cell deployment offers a low-cost solution for the boosted traffic demand in heterogeneous cellular networks (HCNs). Besides improved spatial spectrum efficiency and energy efficiency, future HCNs are also featured with the trend of network architecture convergence and feasibility for flexible mobile applications. To achieve these goals, dual connectivity (DC) is playing a more and more important role to support control/user-plane splitting, which enables maintaining fixed control channel connections for reliability. In this paper, we develop a tractable framework for the downlink SINR analysis of DC assisted HCN. Based on stochastic geometry model, the data-control joint coverage probabilities under multi-frequency and single-frequency tiering are derived, which involve quick integrals and admit simple closed-forms in special cases. Monte Carlo simulations confirm the accuracy of the expressions. It is observed that the increase in mobility robustness of DC is at the price of control channel SINR degradation. This degradation severely worsens the joint coverage performance under single-frequency tiering, proving multi-frequency tiering a more feasible networking scheme to utilize the advantage of DC effectively. Moreover, the joint coverage probability can be maximized by adjusting the density ratio of small cell and macro cell eNBs under multi-frequency tiering, though changing cell association bias has little impact on the level of the maximal coverage performance.

• Structural Engineering and Mechanics
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• v.32 no.2
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• pp.193-212
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• 2009

The resilience of a city confronted with a terrorist bomb attack is the background of the paper. The resilience strongly depends on vital infrastructure and the physical protection of people. The protection buildings provide in case of an external explosion is one of the important elements in safety assessment. Besides the aspect of protection, buildings facilitate and enable many functions, e.g., offices, data storage, -handling and -transfer, energy supply, banks, shopping malls etc. When a building is damaged, the loss of functions is directly related to the location, amount of damage and the damage level. At TNO Defence, Security and Safety methods are developed to quantify the resilience of city infrastructure systems (Weerheijm et al. 2007b). In this framework, the dynamic response, damage levels and residual bearing capacity of multi-storey RC buildings is studied. The current paper addresses the aspects of dynamic response and progressive collapse, as well as the proposed method to relate the structural damage to a volume-damage parameter, which can be linked to the loss of functionality. After a general introduction to the research programme and progressive collapse, the study of the dynamic response and damage due to blast loading for a single RC element is described. Shock tube experiments on plates are used as a reference to study the possibilities of engineering methods and an explicit finite element code to quantify the response and residual bearing capacity. Next the dynamic response and progressive collapse of a multi storey RC building is studied numerically, using a number of models. Conclusions are drawn on the ability to predict initial blast damage and progressive collapse. Finally the link between the structural damage of a building and its loss of functionality is described, which is essential input for the envisaged method to quantify the resilience of city infrastructure.

• Asia pacific journal of information systems
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• v.20 no.1
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• pp.57-79
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• 2010

In a virtual community, one can possess multiple identities and pretend to be different by creating self-identity in contrast with his or her actual self. Does false identity undermine the qualitative growth of a virtual community by reducing members' accountability? Or does it stimulate their contributive behaviors by ensuring freedom of speech? It is imperative to understand the effects of multi-identity considering the distinct properties of a virtual community in which people easily change their identities at little or no cost. To answer these questions, we adopted the concept of self-discrepancy from the social psychology theory rooted in the concept of the self and developed a theoretical model to predict quality of contribution of the individual member in virtual communities. Based on the self-discrepancy theory, we first identified two different domains of the self: (1) an "actual self" that consists of attributes that the person believes he or she currently possesses in real life and (2) a "cyber self" that consists of attributes the person believes he or she possesses in a virtual community. Next, we derived an index for two different types of self-discrepancy by using the differences between the actual and the cyber identities: Personal Self-discrepancy and Social Self-discrepancy. Personal Self-discrepancy reflects the degree of discrepancy between actual and cyber identity regarding a person's intelligence, education, and expertise. Social Self-discrepancy reflects the degree of discrepancy between actual and cyber identity regarding a person's morality, sociability, and accordance with social norms. Finally, we linked them with sense of virtual community, perceived privacy rights, and quality of contribution to examine how having a multi-identity influences an individual's psychological state and contributive behaviors in a virtual community. The results of the analysis based on 266 respondents showed that Social Self-discrepancy negatively influenced both the Sense of Virtual Community and Perceived Privacy Rights, while Personal Self-discrepancy negatively influenced only Perceived Privacy Rights, thereby resulting in reduced quality of contribution in virtual communities. Based on the results of this analysis, we can explain the dysfunctions of multi-identity in virtual communities. First, people who pretend to be different by engaging in socially undesirable behaviors under their alternative identities are more likely to suffer lower levels of psychological wellbeing and thus experience lower levels of sense of virtual community than others. Second, people do not perceive a high level of privacy rights reflecting catharsis, recovery, or autonomy, even though they create different selves and engage in socially undesirable behaviors in a virtual community. Third, people who pretend to be different persons in terms of their intelligence, education, or expertise also indirectly debase the quality of contribution by decreasing perceived privacy rights. The results suggest that virtual community managers should pay more attention to the negative influences exercised by multi-identity on the quality of contribution, thereby controlling the need to create alternative identities in virtual communities. We hope that more research will be conducted on this underexplored area of multi-identity and that our theoretical framework will serve as a useful conceptual tool for all endeavors.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.390-399
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• 2022

Cyber security and resilience are phrases that describe safeguards of ICTs (information and communication technologies) from cyber-attacks or mitigations of cyber event impacts. The sole purpose of Risk models are detections, analyses, and handling by considering all relevant perceptions of risks. The current research effort has resulted in the development of a new paradigm for safeguarding services offered online which can be utilized by both service providers and users. customers. However, rather of relying on detailed studies, this approach emphasizes task selection and execution that leads to successful risk treatment outcomes. Modelling intelligent CSGs (Cyber Security Games) using MLTs (machine learning techniques) was the focus of this research. By limiting mission risk, CSGs maximize ability of systems to operate unhindered in cyber environments. The suggested framework's main components are the Threat and Risk models. These models are tailored to meet the special characteristics of online services as well as the cyberspace environment. A risk management procedure is included in the framework. Risk scores are computed by combining probabilities of successful attacks with findings of impact models that predict cyber catastrophe consequences. To assess successful attacks, models emulating defense against threats can be used in topologies. CSGs consider widespread interconnectivity of cyber systems which forces defending all multi-step attack paths. In contrast, attackers just need one of the paths to succeed. CSGs are game-theoretic methods for identifying defense measures and reducing risks for systems and probe for maximum cyber risks using game formulations (MiniMax). To detect the impacts, the attacker player creates an attack tree for each state of the game using a modified Extreme Gradient Boosting Decision Tree (that sees numerous compromises ahead). Based on the findings, the proposed model has a high level of security for the web sources used in the experiment.

• Journal of KIISE
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• v.44 no.6
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• pp.613-620
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• 2017

Skyline queries are used extensively to solve various problems, such as in decision-making, because they find data that meet a variety of user criteria. Recent research has focused on skyline queries by using the MapReduce framework for large database processing, mainly in terms of applying existing index structures to MapReduce. In a skyline, data closer to the origin dominate more area. However, the existing index structure does not reflect such characteristics of the skyline. In this paper, we propose a grid-block structure that groups grid cells to match the characteristics of a skyline, and a two-level grid-block structure that can be used even when there are no data close to the origin. We also propose an efficient skyline-query algorithm that uses the two-level grid-block structure.