• Journal of Astronomy and Space Sciences
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• v.37 no.4
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• pp.219-228
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• 2020

A CubeSat platform has become a popular choice due to inexpensive commercial off-the-shelf (COTS) components and low launch cost. However, it requires more power-efficient and higher-data rate downlink capability for space applications related to remote sensing. In addition, the platform is limited by the size, weight and power (SWaP) constraints as well as the regulatory issue of licensing the radio frequency (RF) spectrum. The requirements and limitations have put optical communications on promising alternatives to RF communications for a CubeSat platform, owing to the power efficiency and high data rate as well as the license free spectrum. In this study, we analyzed the performance of optical downlink communications compatible with CubeSat platforms in terms of data rate, bit error rate (BER) and outage probability. Mathematical models of BER and outage probability were derived based on not only the log-normal model of atmospheric turbulence but also a transmitter with a finite extinction ratio. Given the fixed slot width, the optimal guard time and modulation orders were chosen to achieve the target data rate. And the two performance metrics, BER and outage data rate, were analyzed and discussed with respect to beam divergence angle, scintillation index and zenith angle.

• The Korean Journal of Pain
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• v.34 no.1
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• pp.114-123
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• 2021

Background: Evaluation of the effectiveness of caudal epidural injection on pain, spine mobility, disease activity, and activity of daily living in axial spondyloarthritis (SpA) patients. Methods: A total sample of 47 patients were registered in this study. They were randomly assigned into 2 groups; Group I received caudal epidural injections, ultrasound-guided, with 1% lidocaine hydrochloride mixed with triamcinolone, whereas Group II did not receive any injections. All participants fulfilled the ASAS criteria for axial SpA. Outcome measures were as follows: visual analogue scale, Oswestry disability index (ODI), modified Schober test, lateral lumbar flexion, and Ankylosing Spondylitis Disease Activity Score (ASDAS) with assessment at baseline, 2 weeks, and 8 weeks post-treatment. This clinical trial was registered on clinicaltrials.gov under the number NCT04143165. Results: There was a significant difference between both groups regarding pain, ODI, spine mobility and ASDAS scores in favor of group I. This effect was at its maximum after 2 weeks. Despite the decline of this effect after 2 months, the difference between the groups remained significant. Higher disease activity, younger age, and shorter disease duration were associated with better outcomes. Conclusions: Epidural injection of lidocaine and triamcinolone is a cost effective and a practical technique for controlling pain, as well as improving the function of the spine and disease activity scores in axial SpA patients with acceptable complications and relatively sustained effect.

• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.940-947
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• 2022

Meta-heuristic algorithms have found their place in optimization problems. Henry gas solubility optimization (HGSO) is one of the newest population-based algorithms. This algorithm is inspired by Henry's law of physics. To evaluate the performance of a new algorithm, it must be used in various problems. On the other hand, the optimization of the proportional-integral-derivative (PID) gains for load-following of a nuclear power plant (NPP) is a good challenge to assess the performance of HGSO. Accordingly, the power control of a pressurized water reactor (PWR) is targeted, based on the point kinetics model with six groups of delayed-neutron precursors. In any optimization problem based on meta-heuristic algorithms, an efficient objective function is required. Therefore, the integral of the time-weighted square error (ITSE) performance index is utilized as the objective (cost) function of HGSO, which is constrained by a stability criterion in steady-state operations. A Lyapunov approach guarantees this stability. The results show that this method provides superior results compared to an empirically tuned PID controller with the least error. It also achieves good accuracy compared to an established GA-tuned PID controller.

• Journal of Korea Trade
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• v.26 no.1
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• pp.99-112
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• 2022

Purpose - This paper empirically investigates via a spatial lag model from the perspective of space economy to find the influencing factors of South Korea's OFDI along with 60 countries. Design/methodology - In the study of regional economic phenomena, we must first test the corresponding spatial correlation, and on this basis, complete the construction of the spatial model. For the target research object, after testing the spatial correlation, if there is spatial correlation, a spatial measurement model is needed. This paper uses the global Moran's I index for calculation. Based on the characteristics and research needs of the research object, this paper selects the spatial lag model to verify the existence of the spatial effect and factors affecting OFDI. Findings - Our results show that export scale, infrastructure, technology level, political stability, resource endowment, market size, distance and labor cost have a certain impact on Korea's OFDI, but at present the distance and market size factors are the most important influencing factors for South Korea's OFDI, The technical level and political stability have little effect on South Korea's OFDI, and are not main factors determining South Korea's OFDI. Originality/value - Through spatial measurement verification, it was found that the spatial effect has a significant impact on OFDI, along with more than 60 countries. On this basis, relevant suggestions are put forward, which have strong practical significance for South Korea's OFDI to achieve healthy and sustainable development.

• Journal of Information Science Theory and Practice
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• v.10 no.3
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• pp.68-82
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• 2022

This study aims to determine the awareness and perceptions of Korean researchers regarding mandatory open access (OA) and OA publishing of publicly-funded research papers. In July 2019, Korean researchers who had published in Science Citation Index Expanded journals as first authors and corresponding authors participated in an online survey distributed via e-mail. A total of 1,172 valid responses were collected and analyzed using SPSS 18. The results indicated that the level of awareness of OA differed significantly based on occupation and research experience (p<0.001). Although 52.56% of the respondents had experienced OA publishing, only 22.35% had self-archiving experience. Regardless of the amount of publishing cost support, researchers showed a high level of willingness to publish OA articles. Yet, since the importance of impact factor was evaluated to be very high, at present OA publication might have a limited role as a publication platform.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2556-2563
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• 2021

Metaheuristic algorithms can work well in solving or optimizing problems, especially those that require approximation or do not have a good analytical solution. Particle swarm optimization (PSO) is one of these algorithms. The response quality of these algorithms depends on the objective function and its regulated parameters. The nonlinear nature of the pressurized light-water nuclear reactor (PWR) dynamics is a significant target for PSO. The two-point kinetics model of this type of reactor is used because of fission products properties. The proportional-integral-derivative (PID) controller is intended to control the power level of the PWR at a short-time transient. The absolute error (IAE), integral of square error (ISE), integral of time-absolute error (ITAE), and integral of time-square error (ITSE) objective functions have been used as performance indexes to tune the PID gains with PSO. The optimization results with each of them are evaluated with the number of function evaluations (NFE). All performance indexes achieve good results with differences in the rate of over/under-shoot or convergence rate of the cost function, in the desired time domain.

• Smart Structures and Systems
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• v.29 no.2
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• pp.361-374
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• 2022

As civil infrastructure has continued to age worldwide, its structural integrity has been threatened owing to material deteriorations and continual loadings from the external environment. Structural Health Monitoring (SHM) has emerged as a cost-efficient method for ensuring structural safety and durability. As SHM research has gradually addressed an increasing number of structure-related problems, it has become difficult to understand the changing research topic trends. Although previous review papers have analyzed research trends on specific SHM topics, these studies have faced challenges in providing (1) consistent insights regarding macroscopic SHM research trends, (2) empirical evidence for research topic changes in overall SHM fields, and (3) methodological validations for the insights. To overcome these challenges, this study proposes a framework tailored to capturing the trends of research topics in SHM through a bibliometric and network analysis. The framework is applied to track SHM research topics over 15 years by identifying both quantitative and relational changes in the author keywords provided from representative SHM journals. The results of this study confirm that overall SHM research has become diversified and multi-disciplinary. Especially, the rapidly growing research topics are tightly related to applying machine learning and computer vision techniques to solve SHM-related issues. In addition, the research topic network indicates that damage detection and vibration control have been both steadily and actively studied in SHM research.

• Transactions of the Korean hydrogen and new energy society
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• v.33 no.4
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• pp.437-445
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• 2022

This paper presents an experimental study on the main management factors of the condenser contamination such as fouling and corrosion for the R-134a turbo-chiller to save energy, reduce corrosion rates, and reduce maintenance costs through the application of condenser non-cleaning water treatment chemical. The series of experiment is conducted using combining oxidative microbial sterilizers, non-oxidizing microbial sterilizers, and anti-corrosion agents. The leaving temperature difference and corrosion rates for three different combination of chemicals are collected and analyzed. The experimental results show that the cost reduction (4,066,000 Won/year) of the disinfectant (FT-830) can be achieved by adding the oxidative disinfectant (NaOCl) and the non-oxidizing disinfectant (NX-1116). The LTD value is maintained at 1.9℃, and the corrosion rates of copper and carbon steel specimens are 0.07 mpy and 1.61 mpy, respectively.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.569-572
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• 1998

The semiconductor technology for the deep submicron $regime(0.18\mu\textrm{m})$ and larger wafer $diameters(300\mu\textrm{m})$ has been increased its cost with each wafer. Hence, in order to reduce the number of characterization experiments of a new process, lithographic modeling is more important than it was. In this paper, we introduced a new method to extract Dill ABC parameters from the refractive index changes. In order to evaluate our exact method, results of experiments and calculations for several resists were compared with other methods〔1〕through the lithographic simulation.

• Computers and Concrete
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• v.32 no.3
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• pp.313-326
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• 2023

The seismic safety of the shear wall structure can be assessed through seismic fragility analysis, which requires high computational costs in estimating seismic demands. Accordingly, machine learning methods have been applied to such fragility analyses in recent years to reduce the numerical analysis cost, but it still remains a challenging task. Therefore, this study uses the ensemble machine learning method to present an improved framework for developing a more accurate seismic demand model than the existing ones. To this end, a rank-based selection method that enables determining an excellent model among several single machine learning models is presented. In addition, an index that can evaluate the degree of overfitting/underfitting of each model for the selection of an excellent single model is suggested. Furthermore, based on the selected single machine learning model, we propose a method to derive a more accurate ensemble model based on the bagging method. As a result, the seismic demand model for which the proposed framework is applied shows about 3-17% better prediction performance than the existing single machine learning models. Finally, the seismic fragility obtained from the proposed framework shows better accuracy than the existing fragility methods.