• Structural Engineering and Mechanics
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• v.32 no.6
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• pp.787-809
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• 2009

Recent interest in the use of wireless sensor networks for structural health monitoring (SHM) is mainly due to their low implementation costs and potential to measure the responses of a structure at unprecedented spatial resolution. Approaches capable of detecting damage using distributed processing must be developed in parallel with this technology to significantly reduce the power consumption and communication bandwidth requirements of the sensor platforms. In this investigation, a damage detection system based on a distributed processing approach is proposed and experimentally validated using a wireless sensor network deployed on two laboratory structures. In this distributed approach, on-board processing capabilities of the wireless sensor are exploited to significantly reduce the communication load and power consumption. The Damage Location Assurance Criterion (DLAC) is used for localizing damage. Processing of the raw data is conducted at the sensor level, and a reduced data set is transmitted to the base station for decision-making. The results indicate that this distributed implementation can be used to successfully detect and localize regions of damage in a structure. To further support the experimental results obtained, the capabilities of the proposed system were tested through a series of numerical simulations with an expanded set of damage scenarios.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.3
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• pp.180-190
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• 2011

Efficient energy consumption is a critical factor for deployment and operation of wireless sensor networks (WSNs). To achieve energy efficiency there have been several hierarchical routing protocols that organize sensors into clusters where one sensor is a cluster-head to forward messages received from its cluster-member sensors to the base station of the WSN. In this paper, we propose a self-organized clustering method for cluster-head selection and cluster based routing for a WSN. To select cluster-heads and organize clustermembers for each cluster, every sensor uses only local information and simple decision mechanisms which are aimed at configuring a self-organized system. By these self-organized interactions among sensors and selforganized selection of cluster-heads, the suggested method can form clusters for a WSN and decide routing paths energy efficiently. We compare our clustering method with a clustering method that is a well known routing protocol for the WSNs. In our computational experiments, we show that the energy consumptions and the lifetimes of our method are better than those of the compared method. The experiments also shows that the suggested method demonstrate properly some self-organized properties such as robustness and adaptability against uncertainty for WSN's.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2805-2826
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• 2021

In most cases, the routing policy of networks shows a preference for a static one-to-one mapping of communication pairs to routing paths, which offers adversaries a great advantage to conduct thorough reconnaissance and organize an effective attack in a stress-free manner. With the evolution of network intelligence, some flexible and adaptive routing policies have already proposed to intensify the network defender to turn the situation. Routing mutation is an effective strategy that can invalidate the unvarying nature of routing information that attackers have collected from exploiting the static configuration of the network. However, three constraints execute press on routing mutation deployment in practical: insufficient route mutation space, expensive control costs, and incompatibility. To enhance the availability of route mutation, we propose an OpenFlow-based route mutation technique called Polymorphic Path Transferring (PPT), which adopts a physical and virtual path segment mixed construction technique to enlarge the routing path space for elevating the security of communication. Based on the Markov Decision Process, with considering flows distribution in the network, the PPT adopts an evolution routing path scheduling algorithm with a segment path update strategy, which relieves the press on the overhead of control and incompatibility. Our analysis demonstrates that PPT can secure data delivery in the worst network environment while countering sophisticated attacks in an evasion-free manner (e.g., advanced persistent threat). Case study and experiment results show its effectiveness in proactively defending against targeted attacks and its advantage compared with previous route mutation methods.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.59-66
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• 2020

In this study, we consider the problem of forecasting the number of inbound foreigners visiting Korea. Forecasting tourism demand is an essential decision to plan related facilities and staffs, thus many studies have been carried out, mainly focusing on the number of inbound or outbound tourists. In order to forecast tourism demand, we use a seasonal ARIMA (SARIMA) model, as well as a SARIMAX model which additionally comprises an exogenous variable affecting the dependent variable, i.e., tourism demand. For constructing the forecasting model, we use a search procedure that can be used to determine the values of the orders of the SARIMA and SARIMAX. For the exogenous variable, we introduce factors that could cause the tourism demand reduction, such as the 9/11 attack, the SARS and MERS epidemic, and the deployment of THAAD. In this study, we propose a procedure, called Measuring Impact on Demand (MID), where the impact of each factor on tourism demand is measured and the value of the exogenous variable corresponding to the factor is determined based on the measurement. To show the performance of the proposed forecasting method, an empirical analysis was conducted where the monthly number of foreign visitors in 2019 were forecasted. It was shown that the proposed method can find more accurate forecasts than other benchmarks in terms of the mean absolute percentage error (MAPE).

• Nuclear Engineering and Technology
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• v.54 no.2
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• pp.749-763
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• 2022

The fulcrum of economic development is a sustainable supply of electricity. Nigeria is plagued with blackouts, with one of the lowest per capita electricity consumption in the world (circa. 120 kWh per capita). Hence, policies have been instigated to integrate electricity generation from nuclear power plants (NPP) on or before 2027. However, a critical requirement for NPP generation is the implementation of robust human resource development (HRD) programs. This paper presents the perspective of Nigeria in assessing human resources needs over the entire NPP lifecycle following the milestone approach and employing the IAEA's Nuclear Power Human Resource (NPHR) modeling tool. Three workforce organizations are in focus including the owner/operator, regulators, and construction workers following three decades timeframe (2015-2045). The results indicate that for the study period, a maximum of approximately 9045 personnel (73% construction workers, 24% owner/operator, and 3% regulators) should be directly involved in the NPP program just before the commissioning of the third NPP in 2033. However, this number decreases by about 73% (2465 personnel including 94% operator and 6% regulator) at the end of the study timeframe. The results can potentially provide clarity and guidance in HRD decision-making programs.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.4
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• pp.288-295
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• 2023

This paper deals with the dynamic simulation method for analysis of driving characteristics of aircraft and towing vehicles (TUG) on carrier vessel in wave motions. For prompt deployment in a short period of time, optimization of the movement of carrier aircraft becomes a major issue. In this regards, strategy studies using real-time simulation technology and optimal decision-making technologies are being conducted. In the present work, the dynamic characteristics of carrier aircraft and TUG connected by towbar or towbarless mechanism were investigated by means of multi-body dynamics model. Meanwhile, for real-time simulation, Dugoff's model of tire loads calculation was adopted. Through comparative analysis it was confirmed that the similarity of results between the multi-body contact model and the tire load calculation model can be achieved by coefficients tuning.

• Korean Journal of Construction Engineering and Management
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• v.25 no.3
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• pp.68-82
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• 2024

The planning stage of laser scanning is crucial for acquiring high-quality 3D source data. It involves assessing the target space's environment and formulating an effective measurement strategy. However, existing practices often overlook on-site conditions, with decisions on scanner deployment and scanning locations relying heavily on the operators' experience. This approach has resulted in frequent modifications to scanning locations and diminished 3D data quality. Previous research has explored the selection of optimal scanner locations and conducted preliminary reviews through simulation, but these methods have significant drawbacks. They fail to consider scanner inaccuracies, do not support the use of multiple scanners, rely on less accurate 2D drawings, and require specialized knowledge in 3D modeling and programming. This study introduces an optimization technique for laser scanning planning using 3D simulation to address these issues. By evaluating the accuracy of scan data from various laser scanners and their positioning for scanning a retaining wall structure in a small-scale building, this method aids in refining the laser scanning plan. It enhances the decision-making process for end-users by ensuring data quality and reducing the need for plan adjustments during the planning phase.

• Journal of the Korean Society of Marine Environment & Safety
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• v.26 no.5
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• pp.466-473
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• 2020

A marine air drone is a new device that can be used to respond to and prevent marine casualties. Determining the districts where marine air drones can be deployed helps the government decision makers identify efficient policy. The aim of this study is to develop a model using the fuzzy-analytic hierarchy process (F-AHP) and additive ratio assessment (ARAS) method to evaluate appropriate districts for deploying marine air drones. To verify the applicability of the proposed model, a case study was performed with respect to the Korea coast guard (KCG) districts. Since the deployed marine air drones are characterized by a high degree of overlap between the evaluation attributes. the F-AHP is used to determine the weights of identified criteria. The results of this study, show that missing people from the shore was the most important criterion for deployment of the drone. For ranking the local districts of the KCG, the ARAS is applied in the case study with the single goal of 50% reduction in marine casualties. Consequently, the highest priority district was identified as Mokpo, followed by Incheon, Seogwipo, Taean, Wando, Yeosu, Pohang, Tongyeong, Gunsan, Bolyeong, Jeju, Buan, Donghae, Sokcho, Ulsan, Uljin, Busan, Changwon, and Pyeongtaeg.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.13 no.4
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• pp.35-48
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• 2018

This study aims to assess the training effect of QFD(Quality Functional Deployment) program for 3 years over startups, adopted from the conventional QFD widely used in the large companies to break up to a sluggish sales and growth, for employees working in startup whether the participants in startup and venture company taking this lessons into their real tasks or not. In particular, the focus of this study falls on figuring out whether individual characteristics of the participants play a role in moderating effect over transfer intension factors and its link path structure. The research results drive out two significant findings. First, in terms of relationship between the influence of transfer intension by self-efficacy and the validity of training content with the learner's readiness, the moderating effect of demographic features of the participants is effective partially by the sex and fully by their working position, but not statistically significant by age, education, and the prior startup career. This research deliver the following significant implication that the active participation of CEO level, decision-maker guarantee the higher performance of the training program like QFD program, more stresses falling on practical implementation in real business rather than just ending up with career training. This study gives significant policy implication to quasi-government organization running all public startup training projects.

• Environmental and Resource Economics Review
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• v.31 no.4
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• pp.645-668
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• 2022

Hydrogen energy is emerging as an important means of carbon neutrality in the various sectors including power, transportation, storage, and industrial processes. Fuel cell power plants are the fastest spreading in the hydrogen ecosystem and are one of the key power sources among means of implementing carbon neutrality in 2050. However, high volatility in system marginal price (SMP) and renewable energy certificate (REC) prices, which affect the profits of fuel cell power plants, delay the investment timing and deployment. This study applied the real option methodology to analyze how the dual uncertainties in both SMP and REC prices affect the investment trigger price level in the irreversible investment decision of fuel cell power plants. The analysis is summarized into the following three. First, under the current Renewable Portfolio Standard (RPS), dual price uncertainties passed on to plant owners has significantly increased the investment trigger price relative to one under the deterministic price case. Second, reducing the volatility of REC price by half of the current level caused a significant drop in investment trigger prices and its investment trigger price is similar to one caused by offering one additional REC multiplier. Third, investment trigger price based on gray hydrogen and green hydrogen were analyzed along with the existing byproduct hydrogen-based fuel cells, and in the case of gray hydrogen, economic feasibility were narrowed significantly with green hydrogen when carbon costs were applied. The results of this study suggest that the current RPS system works as an obstacle to the deployment of fuel cell power plants, and policy that provides more stable revenue to plants is needed to build a more cost-effective and stable hydrogen ecosystem.