• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.9-16
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• 2022

In this paper, we propose a plan to design and utilize the RDBS(Record Block Data file management System) so that data can be recovered when data files in the Combat Management System are mismatched. The CMS(Combat Management System) manages the same files in multiple IPN(Infomation Processing Node) repositories to support multiplexing. However, mismatches in data files can occur due to equipment maintenance or user immaturity. The existing CMS does not manage the history of changes in data files, and when a mismatch occurs, data file were synchronized based on the latest date. But, It is difficult to say that files with the latest date have the highest reliability, and once the file synchronization has progressed, it cannot be recovered with pre-synchronization data. To solve this problem, data was stored and synchronized in units of record blocks using RDBS proposed in this paper, and the Rsync algorithm was used to reduce the overhead of file synchronization due to units of record blocks. SW applied with RDBS was tested for performance in a simulated environment, and it was confirmed that it could be applied to CMS through normal operation confirmation.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.49-59
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• 2022

In this paper, we designed a new enzyme function prediction model PSCREM based on a study that compared and evaluated CNN and LSTM/GRU models, which are the most widely used deep learning models in the field of predicting functions and structures using protein sequences in 2020, under the same conditions. Sequence evolution information was used to preserve detailed patterns which would miss in CNN convolution, and the relationship information between amino acids with functional significance was extracted through overlapping RNNs. It was referenced to feature map production. The RNN family of algorithms used in small CNN-RNN models are LSTM algorithms and GRU algorithms, which are usually stacked two to three times over 100 units, but in this paper, small RNNs consisting of 10 and 20 units are overlapped. The model used the PSSM profile, which is transformed from protein sequence data. The experiment proved 86.4% the performance for the problem of predicting the main classes of enzyme number, and it was confirmed that the performance was 84.4% accurate up to the sub-sub classes of enzyme number. Thus, PSCREM better identifies unique patterns related to protein function through overlapped RNN, and Overlapped RNN is proposed as a novel methodology for protein function and structure prediction extraction.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.32 no.2
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• pp.77-82
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• 2022

Recently, research on the development of low-cost/high-efficiency water electrolysis catalysts to replace noble metal catalysts is being actively conducted. Since overvoltage reduces the overall efficiency of the water splitting device, lowering the overvoltage of the oxygen evolution reaction (OER) is the most important task in order to generate hydrogen more efficiently. Currently, noble metal catalysts show excellent characteristics in OER performance, but they are experiencing great difficulties in commercialization due to their high price and efficiency limitations due to low reactivity. In this study, a water electrolysis catalyst Ni-MWCNT was prepared by successfully doping Ni into the MWCNTs structure through the pulsed laser ablation in liquid (PLAL) process. High resolution-transmission electron microscopy (HR-TEM) and X-ray photoelectron spectroscopy (XPS) were performed for the structure and chemical composition of the synthesized Ni-MWCNT. Catalytic oxygen evolution reaction evaluation was performed by linear sweep voltammetry (LSV) overvoltage characteristics, Tafel slope, electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV) and Chronoamperometry (CA) was used for measurement.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.28 no.1
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• pp.31-38
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• 2022

Due to the increasing consumer demands for the safety, shelf life, and quality of food, the application and development of active packaging in the food and packaging industry have been improved. According to the standards and specifications of the Republic of Korea for utensils, containers, and packages, the function of active packaging is to remove or alleviate factors that degrade food quality. Although extensive reviews regarding the development and commercialization of active packaging have been conducted, the legal regulations and safety assessments concerning active packaging have rarely been examined. This review provides information regarding the definition, structure, components, operational mechanisms, and applications for active packaging that actively removes oxygen, moisture, carbon dioxide, and ethylene. Furthermore, the legal regulations and research results related to the development of test methods for safety assessments of active packaging are investigated.

• Journal of the Korean Society of Propulsion Engineers
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• v.26 no.3
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• pp.32-42
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• 2022

The strategy to develop a launch vehicle family by bundling multiple rocket engines of a single type has been proven by SpaceX and their reusable fleet comprised of Falcon 9 and Falcon Heavy. In this study, we revisit a potential launch vehicle family out of a 35 tonf-class methalox staged combustion cycle engine and evaluate their utility and performance in various space missions. For example, a Korean version of Falcon 9 can deliver 4.7 tons of payload into 500 km SSO in an expendable mode while the payload is reduced to 2.16 tons in a sea-landing reusable mode. A Korean version of Falcon Heavy can deliver 4.4 tons into GTO when launched from the Naro Space Center, indicating that this common booster core configuration can handle Cheollian 2 albeit the high inclination. Once developed, the same methaloax engine can power the first-stage of smallsat launch vehicles and air launch vehicles.

• Journal of the Korea Computer Graphics Society
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• v.28 no.3
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• pp.79-89
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• 2022

With the popularity and the advanced graphics hardware technology of mobile devices, various mobile applications that help children with physical activities have been studied. This paper presents SandUp, a mobile application that guides the play of building sand castles using artificial intelligence and augmented reality(AR) technology. In the process of building the sandcastle, children can interactively explore the target virtual sandcastle through the smartphone display using AR technology. In addition, to help children complete the sandcastle, SandUp informs the sand shape and task required step by step and provides visual and auditory feedback while recognizing progress in real-time using the phone's camera and deep learning classification. We prototyped our SandUp app using Flutter and TensorFlow Lite. To evaluate the usability and effectiveness of the proposed SandUp, we conducted a questionnaire survey on 50 adults and a user study on 20 children aged 4~7 years. The survey results showed that SandUp effectively helps build the sandcastle with proper interactive guidance. Based on the results from the user study on children and feedback from their parents, we also derived usability issues that can be further improved and suggested future research directions.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.57-62
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• 2022

Recently, the tracking radar continues research to develop a new operation algorithm that can acquire and track a target in various environments. In general, modeling similar to the real target and environment is used to develop a new operation algorithm, but there is a limit to modeling the real environment. In this paper, a RAW data storage device was developed to efficiently develop a new operation algorithm required for the tracking radar using millimeter wave to acquire and track the target. The RAW data storage equipment is designed so that the signal processing device of the tracking radar using millimeter wave can save the RAW data output from 8 channels to OOOMSPS. RAW data storage equipment consists of data acquisition equipment and data storage equipment. The data acquisition equipment was implemented using a commercial Xilinx KCU 105 Evaluation KIT capable of high-speed data communication interface, and the data storage equipment was implemented by applying a computer compatible with the commercial Xilinx KCU 105 Evaluation KIT. In this paper, the performance of the implemented RAW data storage equipment was verified through repeated interlocking tests with the signal processing device of the millimeter wave tracking radar.

• Journal of Aerospace System Engineering
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• v.16 no.5
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• pp.62-69
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• 2022

EHA (Electro-Hydrostatic Actuator) is more energy efficiency than a centralized hydraulic system. In particular, the EHA used for aircraft has a redundant design in preparation for failure scenario. Also, due to the aircraft's internal space limitation, the actuator's length must be optimized. Therefore, a series configuration of double rod and single rod cylinder is advantageous. However, due to the asymmetry of the cross-sectional area of the piston, the force fighting phenomenon between the two cylinder areas occurs during redundant operation with a general control system. In this paper, the force fighting phenomenon of redundant EHA was simulated. A controller with load compensation and a force control-based position controller as a method to suppress its stimulation

• KOREAN JOURNAL OF CROP SCIENCE
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• v.67 no.4
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• pp.274-284
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• 2022

To use kenaf (Hibiscus cannabinus L.) as a fiber and livestock feed, a high-yielding variety needs to be identified. For this, accurate phenotyping of plant height is required for this breeding purpose due to the strong relationship between plant height and yield. Plant height can be estimated using RGB images from unmanned aerial vehicles (UAV-RGB) and photogrammetry based on Structure from Motion (SfM) algorithms. In kenaf, accurate measurement of height is limited because kenaf stems have high flexibility and its height is easily affected by wind, growing up to 3 ~ 4 m. Therefore, we aimed to identify a method suitable for the accurate estimation of plant height of kenaf and investigate the feasibility of using the UAV-RGB-derived plant height map. Height estimation derived from UAV-RGB was improved using multi-point calibration against the five different wooden structures with known heights (30, 60, 90, 120, and 150 cm). Using the proposed method, we analyzed the variation in temporal height of 23 kenaf cultivars. Our results demontrated that the actual and estimated heights were reliably comparable with the coefficient of determination (R²) of 0.80 and a slope of 0.94. This method enabled the effective identification of cultivars with significantly different heights at each growth stages.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.36 no.4
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• pp.221-232
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• 2023

This paper presents a novel convolutional neural network (CNN)-based approach for predicting bolt clamping force in the early bolt loosening state of bolted structures. The approach entails tightening eight bolts with different clamping forces and generating frequency responses, which are then used to create a similarity map. This map quantifies the magnitude and shape similarity between the frequency responses and the initial model in a fully fastened state. Krylov subspace-based model order reduction is employed to efficiently handle the large amount of frequency response data. The CNN model incorporates a regression output layer to predict the clamping forces of the bolts. Its performance is evaluated by training the network by using various amounts of training data and convolutional layers. The input data for the model are derived from the magnitude and shape similarity map obtained from the frequency responses. The results demonstrate the diagnostic potential and effectiveness of the proposed approach in detecting early bolt loosening. Accurate bolt clamping force predictions in the early loosening state can thus be achieved by utilizing the frequency response data and CNN model. The findings afford valuable insights into the application of CNNs for assessing the integrity of bolted structures.