• Journal of Aerospace System Engineering
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• v.15 no.5
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• pp.81-88
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• 2021

In general, a non-explosive nylon wire cutting-based holding and release mechanism has been used to store and deploy deployable solar panels of CubeSat. However, with this method, accessing the solar panel's access port for charging the cube satellite's battery and electrical inspection and testing of the PCB and payloads while the solar panel is in storage is difficult. Additionally, the mechanism must have a reliable release function in an in-orbit environment, and reusability for stow and deploy of the solar panel, which is a hassle for the operator and difficult to maintain a consistent nylon wire fastening process. In this study, we proposed a pin-puller-based solar panel holding and release mechanism that can easily deploy a solar panel without cutting nylon wires by separating constraining pins. The proposed mechanism's release function and performance were verified through a solar panel deployment test and a maximum separation load measurement test. Through this, we also verified the design feasibility and effectiveness of the pin-puller-based separation device.

• Journal of Broadcast Engineering
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• v.26 no.4
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• pp.409-418
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• 2021

Conformal coating is a technology that protects PCB(Printed Circuit Board) and minimizes PCB failures. Since the defects in the coating are linked to failure of the PCB, the coating surface is examined for air bubbles to satisfy the successful conditions of the conformal coating. In this paper, we propose an algorithm for detecting problematic bubbles in high-risk groups by applying image signal processing. The algorithm consists of finding candidates for problematic bubbles and verifying candidates. Bubbles do not appear in visible light images, but can be visually distinguished from UV(Ultra Violet) light sources. In particular the center of the problematic bubble is dark in brightness and the border is high in brightness. In the paper, these brightness characteristics are called valley and mountain features, and the areas where both characteristics appear at the same time are candidates for problematic bubbles. However, it is necessary to verify candidates because there may be candidates who are not bubbles. In the candidate verification phase, we used convolutional neural network models, and ResNet performed best compared to other models. The algorithms presented in this paper showed the performance of precision 0.805, recall 0.763, and f1-score 0.767, and these results show sufficient potential for bubble test automation.

• The Journal of the Korea Contents Association
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• v.21 no.12
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• pp.140-154
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• 2021

This study examines the structural relationship between parents' positive and negative parenting attitudes, life satisfaction, and academic helplessness. To this end, 2,595 middle school students (1,405 boys and 1,185 girls) were used among the KCYPS 2018 panel materials. The model was validated using a structural equation model, and the verification of the mediated effects of life satisfaction was significant with bootstraps. The results of the study are as follows. First, the positive and negative parenting attitudes of parents have a significant impact on life satisfaction. These results can be interpreted as having an impact on the lives of adolescent children, depending on their parenting attitudes. Second, the positive and negative parenting attitudes of parents have a significant impact on academic helplessness. These results can be interpreted as having an effect on the academic performance of adolescent children depending on their parenting attitudes. Third, satisfaction in life has a significant adverse effect on academic helplessness. These results can be interpreted as having a positive impact on studies according to the satisfaction level of youth's life, and having a negative impact on studies if life satisfaction is high and life satisfaction is low. Fourth, the satisfaction of life is mediated between parents' positive and negative parenting attitudes and academic helplessness. Through this study, it is meaningful in that it allows parents to understand the process of life satisfaction affecting their academic helplessness according to their parenting attitudes.

• Fire Science and Engineering
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• v.32 no.6
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• pp.1-6
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• 2018

This study is to analyze the characteristics of the yellow insulation ring type of the CSST used for tubing when it is artificially deteriorated and damaged by burning. The CSST for tubing consists of a tube, protective coating, nut, yellow insulation ring, packing, and socket. In addition, it is thought that a yellow insulation ring and rubber packing were used to connect the tube and socket in order to improve the airtightness and insulation performance. The result of the verification of the data acquired from the tests in the 95% confidence interval shows that the Anderson-Darling (AD) and P value were analyzed to be 0.945 and 0.015, respectively. This confirms that the test data of the CSST for tubing is reliable. The analysis of the arithmetic mean of the insulation resistance of a CSST showed that the CSST damaged by burning by a torch, and the one damaged by electrical burning, was $16.7k{\Omega}$ (the greatest relatively) and $208{\Omega}$ (the lowest), respectively, while it was $1.72k{\Omega}$ in the case of a normal product. Therefore, the analysis result of the insulation resistance of the CSST collected from the scene of a fire can be utilized to examine the cause of damage by burning. In addition, it was found that when the maximum current of 97 A was applied to the CSST for about 5 s using a Primary Current Injection Test System (PCITS) the protective film and insulation ring of the CSST has no difference from that of a normal product. However, a part of the metal tube was melted.

• Atmosphere
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• v.28 no.4
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• pp.369-382
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• 2018

Planetary boundary layer height (PBLH), produced by the Local Data Assimilation and Prediction System (LDAPS), was verified using RawinSonde (RS) data obtained from observation at Daegwallyeong (DGW) and Sokcho (SCW) during the International Collaborative Experiments for Pyeongchang 2018 Olympic and Paralympic winter games (ICE-POP 2018). The PBLH was calculated using RS data by applying the bulk Richardson number and the parcel method. This calculated PBLH was then compared to the values produced by LDAPS. The PBLH simulations for DGW and SCW were generally underestimation. However, the PBLH was an overestimation from surface to 200 m and 450 m at DGW and SCW, respectively; this result of model's failure to correctly simulate the Surface Boundary Layer (SBL) and the Mixing Layer (ML) as the PBLH. When the accuracy of the PBLH simulation is low, large errors are seen in the mid- and low-level humidity. The highest frequencies of Planetary boundary layer (PBL) types, calculated by the LDAPS at DGW and SCW, were presented as types Ι and II, respectively. Analysis of meteorological factors according to the PBL types indicate that the PBLH of the existing stratocumulus were overestimated when the mid- and low-level humidity errors were large. If the instabilities of the surface and vertical mixing into clouds are considered important factors affecting the estimation of PBLH into model, then mid- and low-level humidity should also be considered important factors influencing PBLH simulation performance.

• Journal of Korea Technology Innovation Society
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• v.22 no.2
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• pp.207-219
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• 2019

The international trends in activities of government R&D performance measurement is evolving into evidence-based approach to support the verification of objective policy implementation. The European Commission has been implementing KETs (Key Enabling Technologies) policy that incubates nanotech based emerging technologies to support the fourth industrial revolution/revitalization of high-tech manufacturing, and resulting innovations are quantified by KETs Observatory project. The European Commission also built Innovation Radar system that monitors potentially innovative projects within FP7 and Horizon2020 by data analysis. The United States is also upgrading its Federal RePORTER system to quantitatively monitor federal R&D investments with outcomes (including nanotechnology). In the field of Korean nanotechnology, basic statistical data by analyzing NTIS (National Science & Technology Information Service) information is applied in policy field. Developing innovation measurement methodology beyond basic statistical analysis is an international policy issue, and a long-term R&D investment area of a government. The objective of this model study is to quantify the innovation potential of nano R&D investments conducted by Korea government, using input-output based efficiency measurement model and NTIS (National Science & Technology Information Service) that is comprehensive data portal for national R&D investments/outcomes including nanotechnology.

• Convergence Security Journal
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• v.18 no.1
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• pp.19-31
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• 2018

As the ICT technologies advance, the unprecedently large amount of digital data is created, transferred, stored, and utilized in every industry. With the data scale extension and the applying technologies advancement, the new services emerging from the use of large scale data make our living more convenient and useful. But the cybercrimes such as data forgery and/or change of data generation time are also increasing. For the data security against the cybercrimes, the technology for data integrity and the time verification are necessary. Today, public key based signature technology is the most commonly used. But a lot of costly system resources and the additional infra to manage the certificates and keys for using it make it impractical to use in the large-scale data environment. In this research, a new and far less system resources consuming signature technology for large scale data, based on the Hash Function and Merkle tree, is introduced. An improved method for processing the distributed hash trees is also suggested to mitigate the disruptions by server failures. The prototype system was implemented, and its performance was evaluated. The results show that the technology can be effectively used in a variety of areas like cloud computing, IoT, big data, fin-tech, etc., which produce a large-scale data.

• Journal of Navigation and Port Research
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• v.43 no.1
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• pp.72-78
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• 2019

The second-hand ship market provides immediate access to the freight market for shipping investors. When introducing second-hand vessels, the precise estimate of the price is crucial to the decision-making process because it directly affects the burden of capital cost to investors in the future. Previous studies on the second-hand market have mainly focused on the market efficiency. The number of papers on the estimation of second-hand vessel values is very limited. This study proposes an artificial neural network model that has not been attempted in previous studies. Six factors, freight, new-building price, orderbook, scrap price, age and vessel size, that affect the second-hand ship price were identified through literature review. The employed data is 366 real trading records of Panamax second-hand vessels reported to Clarkson between January 2016 and December 2018. Statistical filtering was carried out through correlation analysis and stepwise regression analysis, and three parameters, which are freight, age and size, were selected. Ten-fold cross validation was used to estimate the hyper-parameters of the artificial neural network model. The result of this study confirmed that the performance of the artificial neural network model is better than that of simple stepwise regression analysis. The application of the statistical verification process and artificial neural network model differentiates this paper from others. In addition, it is expected that a scientific model that satisfies both statistical rationality and accuracy of the results will make a contribution to real-life practices.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.2
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• pp.127-134
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• 2019

With the advancement of IT technology, the amount of data generated has been growing exponentially every year. As an alternative to this, research on distributed systems and in-memory based big data processing schemes has been actively underway. The processing power of traditional big data processing schemes enables big data to be processed as fast as the number of nodes and memory capacity increases. However, the increase in the number of nodes inevitably raises the frequency of failures in a big data infrastructure environment, and infrastructure management points and infrastructure operating costs also increase accordingly. In addition, the increase in memory capacity raises infrastructure costs for a node configuration. Therefore, this paper proposes an in-memory-based hybrid big data processing scheme for improve the big data processing rate. The proposed scheme reduces the number of nodes compared to traditional big data processing schemes based on distributed systems by adding a combiner step to a distributed system processing scheme and applying an in-memory based processing technology at that step. It decreases the big data processing time by approximately 22%. In the future, realistic performance evaluation in a big data infrastructure environment consisting of more nodes will be required for practical verification of the proposed scheme.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.187-192
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• 2019

Hybrid power storage system with emergency power function for demand management and power outage minimizes the investment cost in the building of buildings and factories requiring emergency power generation facilities, We propose a new business model by developing technology that can secure economical efficiency by reducing power cost at all times. Normally, system power is supplied to load through STS (Static Transfer Switch), and PCS is connected to system in parallel to perform demand management. In order to efficiently operate the electric power through demand forecasting, the EMS issues a charge / discharge command to the ESS as a PMS (Power Management System), and the PMS transmits the command to the PCS controller to operate the system. During the power outage, the STS is rapidly disengaged from the system, and the PCS becomes an independent power supply and can supply constant voltage / constant frequency power to the load side. Therefore, it is possible to secure reliability through verification of actual system linkage and independent operation performance of hybrid ESS, By enabling low-carbon green growth technology to operate in conjunction with an efficient grid, it is possible to improve irregular power quality and contribute to peak load by generating renewable energy through ESS linkage. In addition, the ESS is replacing the frequency follow-up reserve, which is currently under the charge of coal-fired power generation, and thus it is anticipated that the operation cost of the LNG generator with high fuel cost can be reduced.