• International Journal of Computer Science & Network Security
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• v.22 no.2
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• pp.406-412
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• 2022

Storing large amounts of data has always been a big problem from the beginning of computing history. Big Data has made huge advancements in improving business processes by finding the customers' needs using prediction models based on web and social media search. The main purpose of big data stream processing frameworks is to allow programmers to directly query the continuous stream without dealing with the lower-level mechanisms. In other words, programmers write the code to process streams using these runtime libraries (also called Stream Processing Engines). This is achieved by taking large volumes of data and analyzing them using Big Data frameworks. Streaming platforms are an emerging technology that deals with continuous streams of data. There are several streaming platforms of Big Data freely available on the Internet. However, selecting the most appropriate one is not easy for programmers. In this paper, we present a detailed description of two of the state-of-the-art and most popular streaming frameworks: Apache Ignite and Hazelcast. In addition, the performance of these frameworks is compared using selected attributes. Different types of databases are used in common to store the data. To process the data in real-time continuously, data streaming technologies are developed. With the development of today's large-scale distributed applications handling tons of data, these databases are not viable. Consequently, Big Data is introduced to store, process, and analyze data at a fast speed and also to deal with big users and data growth day by day.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.162-176
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• 2021

Recently, Autonomous Vehicle(AV) has been expected to solve various transportation problems. s the problem of environmental pollution become serious, research to reduce pollution is needed. However, empirical research on AV related pollution is insufficient. Based on this background, this study analyzed network performance changes and CO₂ emissions introduc AVs and Electric Vehicles(EV) in eight intersections. The results show that when AVs with internal combustion engines were, the effect of carbon reduction over the network was insignificant. On the other hand, it was that the total amount of CO₂ generated in the network decreased significantly when EVs and autonomous electric vehicles were emissions in the transportation sector.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.1
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• pp.24-29
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• 2022

Semantic role labeling task used in various natural language processing fields, such as information extraction and question answering systems, is the task of identifying the arugments for a given sentence and predicate. Predicate used as semantic role labeling input are extracted using lexical analysis results such as POS-tagging, but the problem is that predicate can't extract all linguistic patterns because predicate in korean language has various patterns, depending on the meaning of sentence. In this paper, we propose a korean predicate recognition method using neural network model with pre-trained embedding models and lexical features. The experiments compare the performance on the hyper parameters of models and with or without the use of embedding models and lexical features. As a result, we confirm that the performance of the proposed neural network model was 92.63%.

• Journal of Korean Critical Care Nursing
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• v.15 no.1
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• pp.1-12
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• 2022

Purpose : This study aimed to identify the status of intrahospital transport (IHT) of critically ill patients and provide baseline data to form recommendations for safer transport. Methods : Data were collected from 141 intensive care unit (ICU) nurses who attended national conferences between February and August, 2018. The collected data were analyzed using descriptive statistics and ANOVA, and post-hoc analysis was conducted with the Scheffé and Games-Howell tests. Results : Of the nurses surveyed, 61.7% answered that their workplace had a transport guideline. In terms of the experience of ICU nurses, 31.2% of respondents answered that they had received training on IHT. This result indicated that the degree of implementation of the guidelines for IHT was generally high, but some, including guidelines on personnel, equipment, and monitoring, were not. Guidelines of IHT were well observed when the institutes had specific guidelines for IHT of critically ill patients with specified transport grades, a scoring system to assess stability of a patient, a checklist and a protocol for action in case of problems, and when healthcare providers were provided with training. Conclusion : These results suggest that organized infrastructure, such as a transport guideline with transport grades, a checklist to improve the implementation of guidelines, and a protocol for coping with a problem, should be provided for safe transport. Additionally, effective education and evaluation to improve the competency of staff participating in the transport of patients will help reduce the occurrence of adverse events in intensive care transport in hospitals and promote patient safety.

• 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.