• Journal of Korean Critical Care Nursing
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• v.14 no.2
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• pp.1-11
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• 2021

Purpose : The aim of this study was to propose appropriate nurse staffing of adult intensive care units considering patients' nursing care needs according to the Workload Management System for Critical Care Nurses (WMSCN). Methods : In a cross-sectional survey conducted in September 2017, 1,786 patients' WMSCN scores, surveys from 2,145 nurses, and administrative data from 118 units in 41 hospitals were analyzed. The means (standard deviations) of the aforementioned scores and nursing hours per patient day were presented. Nurse-to-patient ratios and nurse-to bed ratios for staffing to meet patients' nursing care needs were calculated. Results : The mean WMSCN scores were 109.50±17.17 in tertiary hospitals and 96.38±19.26 in general hospitals. Nursing hours per patient day were 12.47±2.80 in tertiary hospitals and 11.01±2.45 in general hospitals. Nursing hours per patient day correlated with WMSCN scores. Nurse-to-bed ratios required for the provision of ICU nursing care ranged from 1: 0.36 to 1: 0.48. Conclusion : Our findings provide evidence that current ICU nurse staffing is insufficient for meeting patients' nursing care needs. We suggest adjusting the legal standards for adequate nurse staffing considering these needs.

• Applied Chemistry for Engineering
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• v.22 no.1
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• pp.98-103
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• 2011

We prepared a counter electrode by electroplating Ni as underlayer and Pt as plating layer on the FTO glass to increase the efficiency of dye-sensitized solar cell (DSSC). We found an excellent adhesion between Ni underlayer and FTO glass when Ni underlayer was electroplated at $10mA/cm^2$ for 2 min on FTO glass. We observed Ni and Pt metal diffraction peaks by XRD analysis when Ni underlayer was electroplated at $10mA/cm^2$ for 2 min, and Pt layer was electroplated at $5mA/cm^2$ for 1 min on the Ni underlayer. Photovoltaic performance and impedance analysis of DSSCs fabricated with this counter electrode shows the highest efficiency of 5.6% and the lowest resistance of 75 ohm.

• Journal of Digital Convergence
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• v.19 no.7
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• pp.271-282
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• 2021

This study was conducted to develop a model for predicting the length of stay for premature infants through machine learning. For the development of this model, 6,149 cases of premature infants discharged from the hospital from 2011 to 2016 of the discharge injury in-depth survey data collected by the Korea Centers for Disease Control and Prevention were used. The neural network model of the initial hospitalization was superior to other models with an explanatory power (R²) of 0.75. In the model added by converting the clinical diagnosis to CCS(Clinical class ification software), the explanatory power (R²) of the cubist model was 0.81, which was superior to the random forest, gradient boost, neural network, and penalty regression models. In this study, using national data, a model for predicting the length of stay for premature infants was presented through machine learning and its applicability was confirmed. However, due to the lack of clinical information and parental information, additional research is needed to improve future performance.

• The Korean Journal of Applied Statistics
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• v.34 no.3
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• pp.411-425
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• 2021

Accelerated failure time (AFT) model represents a linear relationship between the log-survival time and covariates. We are interested in the inference of covariate's effect affecting the variation of survival times in the AFT model. Thus, we need to model the variance as well as the mean of survival times. We call the resulting model mean and variance AFT (MV-AFT) model. In this paper, we propose a variable selection procedure of regression parameters of mean and variance in MV-AFT model using penalized likelihood function. For the variable selection, we study four penalty functions, i.e. least absolute shrinkage and selection operator (LASSO), adaptive lasso (ALASSO), smoothly clipped absolute deviation (SCAD) and hierarchical likelihood (HL). With this procedure we can select important covariates and estimate the regression parameters at the same time. The performance of the proposed method is evaluated using simulation studies. The proposed method is illustrated with a clinical example dataset.

• Journal of Drive and Control
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• v.17 no.4
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• pp.125-132
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• 2020

The objective of this study was to analyze the axle load of a rice transplanter when planting rice seedlings at different working load conditions to select a suitable gear stage and a constant planting depth for rice seedlings. In this study, there are four levels of planting distances (26, 35, 43, and 80 cm) and three planting depths (low, medium, and high) with two gear stages (1.3 and 1.7 m/s). Axle loads and required planting pressures were analyzed statistically. It was observed that axle torques were increased with increasing planting depths for both gear stages, meaning that axle torques were directly proportional to planting depths for both gear stages. It was also observed that required planting pressures had a significant difference between planting distances. Planting pressures also showed significant difference according to gear stage and planting depth. These results indicate that planting pressures were directly proportional to both gear stage and planting depth. Results revealed that the automatic depth control system of a rice transplanter could not guarantee a constant planting depth as supplied pressures were variable. This indicates that a control algorithm is needed to ensure a constant planting depth. In the future, a control algorithm will be developed for an automatic depth control system of a rice transplanter to improve its comprehensive performance and efficiency.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.261-270
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• 2020

In this study, we identify promising technologies for Piggyback transportation system by analyzing the relevant patent information. In order for this, we first develop the patent database by extracting relevant technology keywords from the pioneering research papers for the Piggyback flactcar system. We then employed textmining to identify the frequently referred words from the patent database, and using these words, we applied the LDA (Latent Dirichlet Allocation) algorithm in order to identify "topics" that are corresponding to "key" technologies for the Piggyback system. Finally, we employ the ARIMA model to forecast the trends of these "key" technologies for technology forecasting, and identify the promising technologies for the Piggyback system. with keyword search method the patent analysis. The results show that data-driven integrated management system, operation planning system and special cargo (especially fluid and gas) handling/storage technologies are identified to be the "key" promising technolgies for the future of the Piggyback system, and data reception/analysis techniques must be developed in order to improve the system performance. The proposed procedure and analysis method provides useful insights to develop the R&D strategy and the technology roadmap for the Piggyback system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.12
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• pp.1644-1649
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• 2019

With the rapid development of mobile communication systems, various mobile convergence services are appearing and data traffic is exploding accordingly. Because the number of base stations to support these surging devices is also increasing, from a network provider's point of view, reducing energy consumption through these mobile communication networks is one of the most important issues. Therefore, in this paper, we apply the DBSCAN (density-based spatial clustering of applications with noise) algorithm, one of the representative user-density based clustering algorithms, in order to extract the dense area with user density and apply the thinning process to each extracted sub-network to efficiently control the mode of the base stations. Extensive simulations show that the proposed algorithm has better performance results than the conventional algorithms with respect to area throughput and energy efficiency.

• Journal of Chest Surgery
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• v.54 no.1
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• pp.17-24
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• 2021

Background: Although extracorporeal membrane oxygenation (ECMO) is generally performed percutaneously, the technology is deployed under sedation and necessitates endotracheal intubation. However, in some patients, the use of venoarterial (VA) ECMO without intubation may be beneficial. Herein, we describe our experiences with VA ECMO performed without prior endotracheal intubation. Methods: A total of 783 patients treated with VA ECMO at a single center between January 2013 and July 2018 were reviewed retrospectively. We included patients who underwent successful VA ECMO implementation without prior endotracheal intubation, and excluded those who were younger than 18 years, had ongoing cardiopulmonary resuscitation status, and had poor quality of the vessels needed for percutaneous cannulation. The primary study outcome was in-hospital survival. Results: In total, 50 patients were included in this study, 94% of whom showed cardiogenic shock. The mean age of the study participants was 56.3±14.5 years. The median VA ECMO support time was 7 days (range, 2-13 days). Twenty-one patients (42%) did not receive ventilator care during the VA ECMO support period, while 29 patients (58%) progressed to intubation after VA ECMO implementation. The rates of survival at discharge and weaning success were 82% (n=41) and 92% (n=46), respectively, and 80% (n=40) of patients presented good Glasgow-Pittsburgh Cerebral Performance Categories scores at discharge. Conclusion: Even in patients with cardiogenic shock, percutaneous VA ECMO can be introduced safely without prior endotracheal intubation by an experienced care team. The application of nonintubated VA ECMO might be a feasible strategy in selected cases.

• Convergence Security Journal
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• v.20 no.5
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• pp.65-74
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• 2020

Recently, with the rapid development of eXtended Reality(XR) technology, the development and use of education and training systems using XR technology is increasing significantly. In particular, in areas that involve great risks and high costs such as military training and counter-terrorism training, the use of XR based simulators is preferred because they can improve training performance, reduce training costs, and minimize the risk of safety issues that may occur in actual training, by creating a training environment similar to actual training. In this paper, we propose a plan to build and evaluate an XR based hyper-realistic counter-terrorism education, training, and evaluation system to improve the ROK police's ability to respond to terrorist situations using the 5G and AR based Integrated Command and Control Platform previously developed by the Korea Military Academy. The proposed system is designed to improve counter-terrorism capabilities with virtual training for individual and team units based on hyper-realistic content and training scenarios. Futhermore, it can also be used as a on-site command and control post in connection with a simulation training site and an actual operation site.

• Journal of Trauma and Injury
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• v.33 no.4
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• pp.219-226
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• 2020

Purpose: Although the Advanced Trauma Life Support (ATLS) course is now taught internationally, it has not been implemented in Korea. In recent years, interest has increased in simulation as a teaching tool in the ATLS course. We therefore hypothesized that simulation training would be a useful adjunct to the ATLS course. Methods: We designed a 1-day curriculum that included skill development workstations, expert lectures, trauma patient simulations, and group discussion for general surgery residents. We conducted a survey to evaluate participants' level of understanding of the initial evaluation and treatment of trauma patients, their degree of knowledge and technical improvement, their satisfaction with the learning goals, and their overall satisfaction with the curriculum. We then analyzed the effects before and after the training. Results: Nine residents attended this course. None of the residents initially reported that they could perform a primary survey of trauma patients. The analysis revealed significant improvements after training in the questionnaire areas of "assembly of the team and preparation for resuscitation of a trauma patient" (p=0.008), "performance of a primary survey for trauma patients" (p=0.007), "resuscitative procedures for trauma patients" (p=0.008), "importance of re-evaluation" (p=0.007), "identifying the pitfalls associated with the initial assessment and management" (p=0.007), and "importance of teamwork" (p=0.007). Conclusions: After the ATLS simulation training, all participants showed significant improvements in their understanding of how to manage multiple trauma patients. Therefore, ATLS simulation training for residents will help in the management of trauma patients.