• KEPCO Journal on Electric Power and Energy
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• v.7 no.2
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• pp.269-275
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• 2021

The turbine rotor, one of the main facilities in a power plant, it generates electricity while rotating at 3600 RPM. Because it rotates at high speed, it requires careful management because high vibration occurs even if it is deformed by only 0.1mm. However, bending occurs due to various causes during turbine operating. If turbine rotor bending occurs, the power plant must be stopped and repaired. In the past, straightening was carried out using a heating torch and furnace in the field. In case of straightening in this way, it is impossible to proceed systematically, so damage to the turbine rotor may occur and take long period for maintenance. Long maintenance period causes excessive cost, so it is necessary to straighten the rotor by minimizing damage to the rotor in a short period of time. To solve this problem, we developed a turbine rotor straightening equipment using high-frequency induction heating equipment. A straightening was validated for 500MW HIP rotor, and the optimal parameters for straightening were selected. In addition, based on the experimental results, finite element analysis was performed to build a database. Using the database, a straightening amount prediction model available for rotor straightening was developed. Using the developed straightening equipment and straightening prediction model, it is possible to straightening the rotor with minimized damage to the rotor in a short period of time.

• Journal of Astronomy and Space Sciences
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• v.38 no.4
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• pp.217-227
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• 2021

In this study, we describe an analytical process for designing a low Earth orbit constellation for discontinuous regional coverage, to be used for a surveillance and reconnaissance space mission. The objective of this study was to configure a satellite constellation that targeted multiple areas near the Korean Peninsula. The constellation design forms part of a discontinuous regional coverage problem with a minimum revisit time. We first introduced an optimal inclination search algorithm to calculate the orbital inclination that maximizes the geometrical coverage of single or multiple ground targets. The common ground track (CGT) constellation pattern with a repeating period of one nodal day was then used to construct the rest of the orbital elements of the constellation. Combining these results, we present an analytical design process that users can directly apply to their own situation. For Seoul, for example, 39.0° was determined as the optimal orbital inclination, and the maximum and average revisit times were 58.1 min and 27.9 min for a 20-satellite constellation, and 42.5 min and 19.7 min for a 30-satellite CGT constellation, respectively. This study also compares the revisit times of the proposed method with those of a traditional Walker-Delta constellation under three inclination conditions: optimal inclination, restricted inclination by launch trajectories from the Korean Peninsula, and inclination for the sun-synchronous orbit. A comparison showed that the CGT constellation had the shortest revisit times with a non-optimal inclination condition. The results of this analysis can serve as a reference for determining the appropriate constellation pattern for a given inclination condition.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.727-734
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• 2021

The purpose of this study is to analyze the perception of the residents of the new city by examining the consciousness of the occupants to understand the characteristics of the residents of the city of Bundang. As a result of evaluating and analyzing the durability by visual inspection and some equipment tests at the site of the on-site investigation, it was found that there is a problem with the quality, and continuous maintenance is required to improve the durability and usability of the apartment house. In particular, many cracks appearing in the rapidly deteriorated part should be repaired promptly, and a systematic plan should be formulated and carried out. In the apartment housing perception survey of Bundang new city residents, about 93.4% showed above-average satisfaction, and 43.4% showed a favorable preference toward the residential area.

• Journal of radiological science and technology
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• v.45 no.2
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• pp.151-158
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• 2022

The Cardiac Gated Blood Pool (GBP) scintigram, a nuclear medicine imaging, calculates the left ventricular Ejection Fraction (EF) by segmenting the left ventricle from the heart. However, in order to accurately segment the substructure of the heart, specialized knowledge of cardiac anatomy is required, and depending on the expert's processing, there may be a problem in which the left ventricular EF is calculated differently. In this study, using the DeepLabV3 architecture, GBP images were trained on 93 training data with a ResNet-50 backbone. Afterwards, the trained model was applied to 23 separate test sets of GBP to evaluate the reproducibility of the region of interest and left ventricular EF. Pixel accuracy, dice coefficient, and IoU for the region of interest were 99.32±0.20, 94.65±1.45, 89.89±2.62(%) at the diastolic phase, and 99.26±0.34, 90.16±4.19, and 82.33±6.69(%) at the systolic phase, respectively. Left ventricular EF was calculated to be an average of 60.37±7.32% in the ROI set by humans and 58.68±7.22% in the ROI set by the deep learning segmentation model. (p<0.05) The automated segmentation method using deep learning presented in this study similarly predicts the average human-set ROI and left ventricular EF when a random GBP image is an input. If the automatic segmentation method is developed and applied to the functional examination method that needs to set ROI in the field of cardiac scintigram in nuclear medicine in the future, it is expected to greatly contribute to improving the efficiency and accuracy of processing and analysis by nuclear medicine specialists.

• The Journal of Information Systems
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• v.31 no.1
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• pp.239-269
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• 2022

Purpose This paper attempts to identify items for improving the usage of PLM(Product Lifecycle Management) systems and suggests ways to prioritize improvement items on the basis of importance. It also tries to find out differences in the importance of improvement items due to the company size, the industry, the job, or the PLM solution. Design/methodology/approach Through a survey from participants to a PLM System Conference, data were collected from a sample of 181 users who had the previous experience in using a PLM system. In order to figure out the differences in the importance among user groups, the F-test with the Scheffe test as a post-hoc analysis was used in case of equal variances and the Welch test with the Dunnett T3 test was used in case of unequal variances. Findings This study sorted out 25 improvement ideas according to their importance assessed by the PLM system users. The top five ideas are improving data consistency, error minimization, fast system response time, enhancing user recognition, and business process improvement. The support group puts higher importance than the general user group in data consistency, fast system response time, enhancing user recognition, business process improvement, dedicated team for data consistency, continuous support from management, hardware performance upgrade, output linkage to other systems, and shortening problem solving duration. The largest company group attaches significantly higher weights than the smallest company group to data consistency, error minimization, fast system response time, business process improvement, dedicated team for data consistency, security with proper access management, output linkage to other systems, and better user interface.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.173-182
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• 2022

In this paper, we propose a machine learning model that can prevent fraudulent transactions in advance and interpret them using the XAI approach. For the experiment, we collected a real data set of 12,258 mobile phone sales posts from Joonggonara, a major domestic online C2C resale trading platform. Characteristics of the text corresponding to the post body were extracted using Doc2vec, dimensionality was reduced through PCA, and various derived variables were created based on previous research. To mitigate the data imbalance problem in the preprocessing stage, a complex sampling method that combines oversampling and undersampling was applied. Then, various machine learning models were built to detect fraudulent postings. As a result of the analysis, LightGBM showed the best performance compared to other machine learning models. And as a result of SHAP, if the price is unreasonably low compared to the market price and if there is no indication of the transaction area, there was a high probability that it was a fraudulent post. Also, high price, no safe transaction, the more the courier transaction, and the higher the ratio of 0 in the price also led to fraud.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.12
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• pp.1027-1035
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• 2021

We presents a design of 3U cubesat MIMAN (Monochrome imaging for monitoring aerosol by nano-satellite) for aerosol monitoring mission with high spatial resolution. The main objective of MIMAN mission is to take images of aerosols around Korea and to provide auxiliary data for GK 2B cloud masking. For this mission, we derived mission requirements and constraints for the MIMAN mission. We designed the mission architecture and concept of operations. To reduce risk factors in space operation, we considered the safety of the communication. In every operation modes, UHF communication is available so that the cubesat can operate based on the ground commands. So, we can handle every problem at the ground station during mission operations. Based on the mission and concept of operations, we confirmed that the system design satisfied the system requirements. We designed the system interface considering data flow of each hardware, and evaluated the safety of the system with system budget analysis.

• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.36-48
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• 2022

As a valid numerical method to obtain a high-resolution result of a flow field, computational fluid dynamics (CFD) have been widely used to study coolant flow and heat transfer characteristics in fuel rod bundles. However, the time-consuming, iterative calculation of Navier-Stokes equations makes CFD unsuitable for the scenarios that require efficient simulation such as sensitivity analysis and uncertainty quantification. To solve this problem, a reduced-order model (ROM) based on proper orthogonal decomposition (POD) and machine learning (ML) is proposed to simulate the flow field efficiently. Firstly, a validated CFD model to output the flow field data set of the rod bundle is established. Secondly, based on the POD method, the modes and corresponding coefficients of the flow field were extracted. Then, an deep feed-forward neural network, due to its efficiency in approximating arbitrary functions and its ability to handle high-dimensional and strong nonlinear problems, is selected to build a model that maps the non-linear relationship between the mode coefficients and the boundary conditions. A trained surrogate model for modes coefficients prediction is obtained after a certain number of training iterations. Finally, the flow field is reconstructed by combining the product of the POD basis and coefficients. Based on the test dataset, an evaluation of the ROM is carried out. The evaluation results show that the proposed POD-ROM accurately describe the flow status of the fluid field in rod bundles with high resolution in only a few milliseconds.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.37-44
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• 2022

The purpose of this study is to investigate how the local community case management council perceives the expected outcome of the council and case management service by participating actors in order to establish the identity and direction of the activities of the council through concept mapping. A total of 12 practitioners from participating organizations freely expressed and shared their opinions about the case management service performance with the local community case management council in a brainstorming manner, producing a total of 42 statements. Through concept mapping, participants were empowered in the decision-making process, and their opinions were not alienated, but were accepted and rationally handled. It can be said that it is important to provide an opportunity for the participants to discuss on an equal footing in the decision-making process. Through this, it can be seen that the agreement between the case management council and the case management service was quickly reached, and the direction for subsequent activities was clearly set.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1800-1817
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• 2022

With the development of the economy and the improvement of living standards, the hot issues in the subject area have become the main research direction, and the mining of the hot issues in the subject currently has problems such as a large amount of data and a complex algorithm structure. Therefore, in response to this problem, this study proposes a method for extracting hot keywords in scientific journals based on the improved BERT model.It can also provide reference for researchers,and the research method improves the overall similarity measure of the ensemble,introducing compound keyword word density, combining word segmentation, word sense set distance, and density clustering to construct an improved BERT framework, establish a composite keyword heat analysis model based on I-BERT framework.Taking the 14420 articles published in 21 kinds of social science management periodicals collected by CNKI(China National Knowledge Infrastructure) in 2017-2019 as the experimental data, the superiority of the proposed method is verified by the data of word spacing, class spacing, extraction accuracy and recall of hot keywords. In the experimental process of this research, it can be found that the method proposed in this paper has a higher accuracy than other methods in extracting hot keywords, which can ensure the timeliness and accuracy of scientific journals in capturing hot topics in the discipline, and finally pass Use information technology to master popular key words.